Study support by cognitive counseling for a junior-high-school student who has difficulty with solving ratio-word-problems

This study is a case report of the cognitive counseling for a child who has difficulty with solving ratio-word-problems. The child in this study was a first-year junior-high-school female student. It was difficult for her to explain her idea in words. It seemed that the student has poor verbal working memory. To support her learning of ratio word problems, we used diagrams as an external resource for her thinking about meaning of the problems. In addition, we helped her use metacognition with cards that showed points to be paid attention to in the process of solving the problems. Our supports improved her performances of ratio word problems, and she came to draw diagrams spontaneously. In addition to that, she became able to control and monitor the process of calculation by herself

Effect of discussions about picture books among a group of young children on their narrations

In this study, we investigated how discussions about picture books among a group of young children would affect their narrations about the picture books. Thirty 5-year-old children participated in this study. The children received a verbal working memory task that required them to compare two non-words given sequentially over a headset. They also engaged in an activity involving picture books under one of two conditions. First, a female adult read one of two picture books to groups of children. Second, they answered questions about the picture book individually (the non-group activity condition) or in a group (the group activity condition). Finally, they were required to narrate a story about the picture book they were shown. We divided participants’ narrations into idea units (IUs): there are six types of IUs (basic IUs, point IUs, sophisticated IUs, picture IUs, erroneous IUs, and other IUs). Two university students independently classified the IUs. The results show that the partial correlations between the scores of the verbal working memory task and point IUs (r = .40) and between verbal working memory and other IUs (r = −.40) were significant when controlling for age in terms of months. This finding suggested that children with better verbal working memory would understand the main points of the stories. Although children were significantly more likely to report three types of IUs in the group activity condition than in the non-group activity condition, the differences were mediated by the content of the picture books: one picture book was more likely to stimulate the group activities, which facilitated the children’s narrations.本論文は，第2著者の卒業研究に基づいている

An endogenous factor enhances ferulic acid decarboxylation catalyzed by phenolic acid decarboxylase from Candida guilliermondii

Resource subsidies in the form of allochthonous primary production drive secondary production in many ecosystems, often sustaining diversity and overall productivity. Despite their importance in structuring marine communities, there is little understanding of how subsidies move through juxtaposed habitats and into recipient communities. We investigated the transport of detritus from kelp forests to a deep Arctic fjord (northern Norway). We quantified the seasonal abundance and size structure of kelp detritus in shallow subtidal (0‒12 m), deep subtidal (12‒85 m), and deep fjord (400‒450 m) habitats using a combination of camera surveys, dive observations, and detritus collections over 1 year. Detritus formed dense accumulations in habitats adjacent to kelp forests, and the timing of depositions coincided with the discrete loss of whole kelp blades during spring. We tracked these blades through the deep subtidal and into the deep fjord, and showed they act as a short-term resource pulse transported over several weeks. In deep subtidal regions, detritus consisted mostly of fragments and its depth distribution was similar across seasons (50% of total observations). Tagged pieces of detritus moved slowly out of kelp forests (displaced 4‒50 m (mean 11.8 m ± 8.5 SD) in 11‒17 days, based on minimum estimates from recovered pieces), and most (75%) variability in the rate of export was related to wave exposure and substrate. Tight resource coupling between kelp forests and deep fjords indicate that changes in kelp abundance would propagate through to deep fjord ecosystems, with likely consequences for the ecosystem functioning and services they provide

Protein complex prediction via verifying and reconstructing the topology of domain-domain interactions

<p>Abstract</p> <p>Background</p> <p>High-throughput methods for detecting protein-protein interactions enable us to obtain large interaction networks, and also allow us to computationally identify the associations of proteins as protein complexes. Although there are methods to extract protein complexes as sets of proteins from interaction networks, the extracted complexes may include false positives because they do not account for the structural limitations of the proteins and thus do not check that the proteins in the extracted complex can simultaneously bind to each other. In addition, there have been few searches for deeper insights into the protein complexes, such as of the topology of the protein-protein interactions or into the domain-domain interactions that mediate the protein interactions.</p> <p>Results</p> <p>Here, we introduce a combinatorial approach for prediction of protein complexes focusing not only on determining member proteins in complexes but also on the DDI/PPI organization of the complexes. Our method analyzes complex candidates predicted by the existing methods. It searches for optimal combinations of domain-domain interactions in the candidates based on an assumption that the proteins in a candidate can form a true protein complex if each of the domains is used by a single protein interaction. This optimization problem was mathematically formulated and solved using binary integer linear programming. By using publicly available sets of yeast protein-protein interactions and domain-domain interactions, we succeeded in extracting protein complex candidates with an accuracy that is twice the average accuracy of the existing methods, MCL, MCODE, or clustering coefficient. Although the configuring parameters for each algorithm resulted in slightly improved precisions, our method always showed better precision for most values of the parameters.</p> <p>Conclusions</p> <p>Our combinatorial approach can provide better accuracy for prediction of protein complexes and also enables to identify both direct PPIs and DDIs that mediate them in complexes.</p

A Comprehensive Resource of Interacting Protein Regions for Refining Human Transcription Factor Networks

Large-scale data sets of protein-protein interactions (PPIs) are a valuable resource for mapping and analysis of the topological and dynamic features of interactome networks. The currently available large-scale PPI data sets only contain information on interaction partners. The data presented in this study also include the sequences involved in the interactions (i.e., the interacting regions, IRs) suggested to correspond to functional and structural domains. Here we present the first large-scale IR data set obtained using mRNA display for 50 human transcription factors (TFs), including 12 transcription-related proteins. The core data set (966 IRs; 943 PPIs) displays a verification rate of 70%. Analysis of the IR data set revealed the existence of IRs that interact with multiple partners. Furthermore, these IRs were preferentially associated with intrinsic disorder. This finding supports the hypothesis that intrinsically disordered regions play a major role in the dynamics and diversity of TF networks through their ability to structurally adapt to and bind with multiple partners. Accordingly, this domain-based interaction resource represents an important step in refining protein interactions and networks at the domain level and in associating network analysis with biological structure and function