Original Article

本研究の目的は,健康な小児ががんや白血病といった病名からどのようなイメージを抱くのか,自分が大きな病気になったとしたら,病名や治療などについて教えて欲しいと思っているのかを明らかにすることである。千葉県内の小中高校に通っている小学校5年生から高校3年生までの児童生徒1964名から得られたアンケートの回答を,統計ソフトSPSSにて分析を行い以下の結果を得た。1.健康な小児が抱くがんのイメージは,「死ぬ・治らない」「重い・危険・苦しい」といった悲観的なのものが多く,全体の約65%を占めていた。「聞いたことがない・わからない」と答えたものもおり全体の約15%であり,どの学年でも同様の傾向であった。2.健康な小児が抱く白血病のイメージは「病態や特徴について」「原因や治療について」といったものが,全体の約38%を占めていた。「聞いたことがない・わからない」と答えたものは全体の約33%を占め,小学生では半数以上が「聞いたことがない・わからない」と答えていた。3.自分が病気になったときにされる説明については小学生の80%,中学生の85%,高校生の91%が真実を伝えられることを求めていた。その理由として自分の知る権利,治療に前向きに取り組めるといった姿勢の向上,知らないことが不安になる,残された命を有意義に悔いのないように過ごしたいといったものがあげられていた。The purposes of this study were to identify the images of healthy children on cancer and leukemia, and the way of thinking of truth telling with disease. The number of subjects were 1964. They belonged to between the fifth grade of primary school and the third year in high school. They answered someitem-questionnaire, and the answers were analyzed using SPSS. The results were as follows: 1. Sixty-five percent of the images of cancer were pessimistic, like death or incurable and serious or painful . About fifteen percent were having no images. 2. Thirty-eight percent of the images of leukemia were the feature and the cause or the treatment . About thirty-three percent were having no images. 3. Truth telling was desired by eighty percent of students of primary schools, eighty-five percent of junior high schools and ninety-one percent of a high school. The reasons were the rights to know , to be patient with treatments , to become more anxious without truth telling , and to live the remaining days without regrets

Enhancing synchronizability of weighted dynamical networks using betweenness centrality

By considering the eigenratio of the Laplacian of the connection graph as synchronizability measure, we propose a procedure for weighting dynamical networks to enhance theirsynchronizability. The method is based on node and edge betweenness centrality measures and is tested on artificially const ructed scale-free, Watts-Strogatz and random networks as well as on some real-world graphs. It is also numerically shown that the same procedure could be used to enhance the phase synchronizability of networks of nonidentical oscillators

Optimisation of Signal Timings in a Road Network

This is the author accepted manuscript. The final version is available from Springer via the DOI in this recordRoad network simulation models and tools are increasingly being used for strategic and operational traffic management with the use of widely available online traffic data. The widespread use of such models raises the prospect of transport system optimisation, improving energy consumption, delays and carbon emissions. Although strategic interventions such as the building of new roads or infrastructure is costly and time-consuming, significant savings can be made through the modelling and optimisation of the operation of the network through signal timings.Innovate U

Application of Metaheuristics in Signal Optimisation of Transportation Networks: A Comprehensive Survey

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.With rapid population growth, there is an urgent need for intelligent traffic control techniques in urban transportation networks to improve the network performance. In an urban transportation network, traffic signals have a significant effect on reducing congestion, improving safety, and improving environmental pollution. In recent years, researchers have been applied metaheuristic techniques for signal timing optimisation as one of the practical solution to enhance the performance of the transportation networks. Current study presents a comprehensive survey of such techniques and tools used in signal optimisation of transportation networks, providing a categorisation of approaches, discussion, and suggestions for future research

Acetolactate synthase regulatory subunits play divergent and overlapping roles in branched-chain amino acid synthesis and Arabidopsis development

Branched-chain amino acids (BCAAs) are synthesized by plants, fungi, bacteria, and archaea with plants being the major source of these amino acids in animal diets. Acetolactate synthase (ALS) is the first enzyme in the BCAA synthesis pathway. Although the functional contribution of ALS to BCAA biosynthesis has been extensively characterized, a comprehensive understanding of the regulation of this pathway at the molecular level is still lacking

Bacterial flora-typing with targeted, chip-based Pyrosequencing

<p>Abstract</p> <p>Background</p> <p>The metagenomic analysis of microbial communities holds the potential to improve our understanding of the role of microbes in clinical conditions. Recent, dramatic improvements in DNA sequencing throughput and cost will enable such analyses on individuals. However, such advances in throughput generally come at the cost of shorter read-lengths, limiting the discriminatory power of each read. In particular, classifying the microbial content of samples by sequencing the < 1,600 bp 16S rRNA gene will be affected by such limitations.</p> <p>Results</p> <p>We describe a method for identifying the phylogenetic content of bacterial samples using high-throughput Pyrosequencing targeted at the 16S rRNA gene. Our analysis is adapted to the shorter read-lengths of such technology and uses a database of 16S rDNA to determine the most specific phylogenetic classification for reads, resulting in a weighted phylogenetic tree characterizing the content of the sample. We present results for six samples obtained from the human vagina during pregnancy that corroborates previous studies using conventional techniques.</p> <p>Next, we analyze the power of our method to classify reads at each level of the phylogeny using simulation experiments. We assess the impacts of read-length and database completeness on our method, and predict how we do as technology improves and more bacteria are sequenced. Finally, we study the utility of targeting specific 16S variable regions and show that such an approach considerably improves results for certain types of microbial samples. Using simulation, our method can be used to determine the most informative variable region.</p> <p>Conclusion</p> <p>This study provides positive validation of the effectiveness of targeting 16S metagenomes using short-read sequencing technology. Our methodology allows us to infer the most specific assignment of the sequence reads within the phylogeny, and to identify the most discriminative variable region to target. The analysis of high-throughput Pyrosequencing on human flora samples will accelerate the study of the relationship between the microbial world and ourselves.</p

EEG-Based Functional Brain Networks: Does the Network Size Matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks – whose nodes can vary from tens to hundreds – are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies

The correlation of RNase A enzymatic activity with the changes in the distance between Nepsilon2-His12 and N delta1-His119 upon addition of stabilizing and destabilizing salts.

The effect of stabilizing and destabilizing salts on the catalytic behavior of ribonuclease A (RNase A) was investigated at pH 7.5 and 25 degrees C, using spectrophotometric, viscometric and molecular dynamic methods. The changes in the distance between N(epsilon2) of His(12) and N(delta1) of His(119) at the catalytic center of RNase A upon the addition of sodium sulfate, sodium hydrogen sulfate and sodium thiocyanate were evaluated by molecular dynamic methods. The compactness and expansion in terms of Stokes radius of RNase A upon the addition of sulfate ions as kosmotropic salts, and thiocyanate ion as a chaotropic salt, were estimated by viscometric measurements. Enzyme activity was measured using cytidine 2', 3'-cyclic monophosphate as a substrate. The results from the measurements of distances between N(epsilon2) of His(12) and N(delta1) of His(119) and Stokes radius suggest (i) that the presence of sulfate ions decreases the distance between the catalytic His residues and increases the globular compactness, and (ii) that there is an expansion of the enzyme surface as well as elongation of the catalytic center in the presence of thiocyanate ion. These findings are in agreement with activity measurements