国文学研究資料館概要（和文）2015

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μTG及び大腸菌自動培養分注システムの応用研究

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Observation of B̅0→DsJ*(2317)+K- Decay

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Solar neutrino measurements in Super-Kamiokande-II

The results of the second phase of the Super-Kamiokande solar neutrino measurement are presented and compared to the first phase. The solar neutrino flux spectrum and time variation as well as oscillation results are statistically consistent with the first phase and do not show spectral distortion. The timedependent flux measurement of the combined first and second phases coincides with the full period of solar cycle 23 and shows no correlation with solar activity. The measured 8B total flux is (2:38± 0.05(stat.)/begin+0.16 // -0.15/end (sys.)) × 10^6 cm^{-2} s^{-1} and the day-night difference is found to be (-6.3 ±4.2(stat.)±3.7(sys.))%.There is no evidence of systematic tendencies between the first and second phases.journal articl

Connectivity Distribution of Simulated and Natural Networks

<div><p>(A) Connectivity distribution of 40 different simulated networks. As in the sample simulation, most metabolites are only involved in two or three reactions. On the other hand, the distribution shows that there are a number of hubs that are involved in up to 16 reactions.</p> <p>(B) The double-logarithmic plot of the distribution reveals a considerable deviation from a power-law distribution.</p> <p>(C) Connectivity distribution in natural metabolic networks of similar size. The networks are generated from the KEGG database for <i>E. coli</i> (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030228#s4" target="_blank">Materials and Methods</a>). The connectivity distribution of the simulated networks is consistent with that of the natural networks (chi square test: <i>p</i> ≈ 0.085; see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030228#s4" target="_blank">Materials and Methods</a>).</p> <p>(D) Simulations for monomolecular reaction networks. The initial network is equivalent to the group transfer networks (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030228#pbio-0030228-g001" target="_blank">Figure 1</a>C). In contrast to the group transfer network, we assume that groups are not transferred, but are added or removed by the enzymes. Therefore a reaction can transform a donor into its corresponding acceptor without being coupled to another half-reaction. The connectivity distribution of the emerging networks clearly differs from the connectivity distribution in the bimolecular group transfer networks. In particular, hubs are comparatively rare. This indicates that group transfer plays a key role in the emergence of hubs.</p></div

Structure of the Initial Network

<div><p>(A) Metabolites are assumed to consist of <i>N</i> different biochemical groups. Metabolites can be denoted as binary strings, because each group can be either present or absent. In the example given, the metabolite carries groups 1, 3, 4, and 5 whereas all other groups are absent.</p> <p>(B) Enzymes catalyze the transfer of specific biochemical groups between metabolites. For the group transfer we assume a ping-pong–like mechanism that consists of two half-reactions. In the first half-reaction, the group is transferred from a donor to the enzyme. Thereby the donor is transformed into its corresponding acceptor. In the second half-reaction, the enzyme transfers the group to another acceptor, thereby transforming it into its corresponding donor. We assume that a half-reaction follows linear reversible kinetics. This results in Michaelis-Menten–like kinetics for the transfer of a group from one metabolite to another. For the initial network we assume that enzymes are specific with regard to the group but unspecific with regard to donors and acceptors, i.e., they transfer a specific biochemical group from any donor to any acceptor.</p> <p>(C) The initial network consists of 2<i>^N</i> metabolites. A single half-reaction transforms the metabolites into one of the <i>N</i> neighbours, such that the initial network resembles an <i>N</i>-dimensional hypercube. Note, however, that for the transfer of a group, two edges (i.e., half-reactions) in the cube have to be coupled.</p> <p>(D) To study the impact of group transfer on the connectivity distribution of the simulated networks, we performed simulations with monomolecular reaction networks, in which groups are added and removed, but not transferred, by the enzymes. The initial network has a similar structure. However, in contrast to the group transfer network, each reaction can be performed without coupling to another reaction.</p></div

Sample Simulation for the Evolution of Metabolic Networks

<div><p>(A) The initial network consists of 128 metabolites, seven unspecific enzymes (each of which transfers one of the seven biochemical groups that metabolites carry), and a single unspecific transporter. Within the course of evolution, the enzymes and transporter duplicate and increase in specificity (i.e., the number of half-reactions per enzyme and of metabolites per transporter decreases). The emerging network consists of 23 enzymatic reactions and seven transport processes. In the sample simulation, all enzymes and transporters in the emerging network are highly specific, i.e., the enzymes catalyze only two half-reactions, and the transporters transport single metabolites. The emerging network contains only 33 metabolites. The remaining metabolites are not involved in the emerging network.</p> <p>(B) Connectivity distribution of the emerging group transfer network. Most metabolites are involved in only two reactions. However, a few metabolites are highly connected.</p> <p>(C) Pathway scheme of the emerging group transfer network. The metabolites X0 and X127 are taken up from the environment, whereas metabolites X4, X22, X94, X95, and X111 are excreted into the environment (white boxes). The network eventually transforms metabolites X0 and X127 into those metabolites that are involved in biomass formation (grey boxes). Interestingly, metabolite X4 is excreted although it is involved in biomass formation. Note that some half-reactions evolve, such as the one from X127 to X126, and monopolize the transfer of a specific group (in this case the first group in the binary string). These metabolites are involved in many reactions and therefore have high connectivity. The group transfer reactions of these hubs are summarized in the first line of the pathway scheme. The emerging group transfer network is much more complex than the corresponding monomolecular reaction network (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030228#pbio-0030228-g002" target="_blank">Figure 2</a>D) and even includes a cycle (X32 → X119 → X117 → X32), with the net reaction of X0 + X16 + X127 → X18 + X40 + X85).</p> <p>(D) Pathway scheme of an emerging monomolecular reaction network. Although the network produces the same set of metabolites involved in biomass formation as the group transfer network shown in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030228#pbio-0030228-g002" target="_blank">Figure 2</a>C, it has a much simpler, tree-like structure. Additionally, the network has no obvious hubs.</p></div

内子町の植生 : 郷土の永続的な発展をめざして

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