<Reports on the Sixteenth annual Meeting of the Tsukuba English Linguisic Society> Downstep in Japanese : Syntatic vs. Semantic Approach

It has been argued that the effect of downstep differently appears depending on the syntactic structure (Kubozono 1989, 1992 and Azuma 1992a, 1992b) or on the semantic information (Koori 1992a, 1992b) ..

Systems Biology Graphical Notation: Process Diagram Level 1

Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialised notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Diagrams, the Entity Relationship Diagrams and the Activity Flow Diagrams. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage in textbooks and its teaching directly in high schools. The first level of the SBGN Process Diagram has been publicly released. Software support for SBGN Process Diagram was developed concurrently with its specification in order to speed-up public adoption. Shared by the communities of biochemists, genomicians, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signalling pathways, metabolic networks and gene regulatory maps

Multi-dimensional computational pipeline for large-scale deep screening of compound effect assessment: an in silico case study on ageing-related compounds

Designing alternative approaches to efficiently screen chemicals on the efficacy landscape is a challenging yet indispensable task in the current compound profiling methods. Particularly, increasing regulatory restrictions underscore the need to develop advanced computational pipelines for efficacy assessment of chemical compounds as alternative means to reduce and/or replace in vivo experiments. Here, we present an innovative computational pipeline for large-scale assessment of chemical compounds by analysing and clustering chemical compounds on the basis of multiple dimensions—structural similarity, binding profiles and their network effects across pathways and molecular interaction maps—to generate testable hypotheses on the pharmacological landscapes as well as identify potential mechanisms of efficacy on phenomenological processes. Further, we elucidate the application of the pipeline on a screen of anti-ageing-related compounds to cluster the candidates based on their structure, docking profile and network effects on fundamental metabolic/molecular pathways associated with the cell vitality, highlighting emergent insights on compounds activities based on the multi-dimensional deep screen pipeline

AlzPathway: a comprehensive map of signaling pathways of Alzheimer’s disease

BACKGROUND: Alzheimer’s disease (AD) is the most common cause of dementia among the elderly. To clarify pathogenesis of AD, thousands of reports have been accumulating. However, knowledge of signaling pathways in the field of AD has not been compiled as a database before. DESCRIPTION: Here, we have constructed a publicly available pathway map called “AlzPathway” that comprehensively catalogs signaling pathways in the field of AD. We have collected and manually curated over 100 review articles related to AD, and have built an AD pathway map using CellDesigner. AlzPathway is currently composed of 1347 molecules and 1070 reactions in neuron, brain blood barrier, presynaptic, postsynaptic, astrocyte, and microglial cells and their cellular localizations. AlzPathway is available as both the SBML (Systems Biology Markup Language) map for CellDesigner and the high resolution image map. AlzPathway is also available as a web service (online map) based on Payao system, a community-based, collaborative web service platform for pathway model curation, enabling continuous updates by AD researchers. CONCLUSIONS: AlzPathway is the first comprehensive map of intra, inter and extra cellular AD signaling pathways which can enable mechanistic deciphering of AD pathogenesis. The AlzPathway map is accessible at http://alzpathway.org/

A comprehensive molecular interaction map of the budding yeast cell cycle

With the accumulation of data on complex molecular machineries coordinating cell-cycle dynamics, coupled with its central function in disease patho-physiologies, it is becoming increasingly important to collate the disparate knowledge sources into a comprehensive molecular network amenable to systems-level analyses. In this work, we present a comprehensive map of the budding yeast cell-cycle, curating reactions from ∼600 original papers. Toward leveraging the map as a framework to explore the underlying network architecture, we abstract the molecular components into three planes—signaling, cell-cycle core and structural planes. The planar view together with topological analyses facilitates network-centric identification of functions and control mechanisms. Further, we perform a comparative motif analysis to identify around 194 motifs including feed-forward, mutual inhibitory and feedback mechanisms contributing to cell-cycle robustness. We envisage the open access, comprehensive cell-cycle map to open roads toward community-based deeper understanding of cell-cycle dynamics

Evaluation of Therapeutic Target Gene Expression Based on Residual Cancer Burden Classification After Neoadjuvant Chemotherapy for HER2-Negative Breast Cancer

Introduction Patients with residual disease usually have a poor prognosis after neoadjuvant chemotherapy for breast cancer. The aim of this study was to explore therapeutic targets and potential additional adjuvant treatments for patients with residual disease after standard neoadjuvant chemotherapy. Patients and Methods We retrieved publicly available complementary DNA microarray data from 399 human epidermal growth factor receptor 2 (HER2)-negative primary breast cancer samples from patients who underwent standard neoadjuvant chemotherapy. We analyzed the messenger RNA (mRNA) expression levels of key breast cancer markers and therapeutic target genes according to residual cancer burden (RCB) classification: RCB-0/I, RCB-II, and RCB-III. Results Among hormone receptor–positive samples, there were more luminal A tumors by PAM50 (Prediction Analysis of Microarray 50 [Prosigna], aka Prosigna Breast Cancer Prognostic Gene Signature Assay) in RCB-III than in RCB-0/I and RCB-II (P Conclusion In hormone receptor–positive breast cancer, biological features such as luminal A were associated with RCB; this trend was not observed in TN breast cancer. Further, some targeted therapies should be tested as new strategies after standard neoadjuvant chemotherapy in future clinical trials

A comprehensive map of the mTOR signaling network

The mammalian target of rapamycin (mTOR) is a central regulator of cell growth and proliferation. mTOR signaling is frequently dysregulated in oncogenic cells, and thus an attractive target for anticancer therapy. Using CellDesigner, a modeling support software for graphical notation, we present herein a comprehensive map of the mTOR signaling network, which includes 964 species connected by 777 reactions. The map complies with both the systems biology markup language (SBML) and graphical notation (SBGN) for computational analysis and graphical representation, respectively. As captured in the mTOR map, we review and discuss our current understanding of the mTOR signaling network and highlight the impact of mTOR feedback and crosstalk regulations on drug-based cancer therapy. This map is available on the Payao platform, a Web 2.0 based community-wide interactive process for creating more accurate and information-rich databases. Thus, this comprehensive map of the mTOR network will serve as a tool to facilitate systems-level study of up-to-date mTOR network components and signaling events toward the discovery of novel regulatory processes and therapeutic strategies for cancer

Optimizing the timing of 3.6 mg Pegfilgrastim Administration for Dose-Dense Chemotherapy in Japanese Patients with Breast Cancer

Perioperative dose-dense chemotherapy (DDCT) with pegfilgrastim (Peg) prophylaxis is a standard treatment for high-risk breast cancer. We explored the optimal timing of administration of 3.6 mg Peg, the dose approved in Japan. In the phase II feasibility study of DDCT (adriamycin+cyclophosphamide or epirubicin+cyclophosphamide followed by paclitaxel) for breast cancer, we investigated the feasibility, safety, neutrophil transition, and optimal timing of Peg treatment by administering Peg at days 2, 3, and 4 post-chemotherapy (P2, P3, and P4 groups, respectively). Among the 52 women enrolled, 13 were aged > 60 years. The anthracycline sequence was administered to P2 (n=33), P3 (n=5), and P4 (n=14) patients, and the taxane sequence to P2 (n=38) and P3 (n=6) patients. Both sequences showed no interaction between Peg administration timing and treatment discontinuation, treatment delay, or dose reduction. However, the relative dose intensity (RDI) was significantly different among the groups. The neutrophil count transition differed significantly among the groups receiving the anthracycline sequence. However, the neutrophil count remained in the appropriate range for both sequences in the P2 group. The timing of Peg administration did not substantially affect the feasibility or safety of DDCT. Postoperative day 2 might be the optimal timing for DDCT