Characteristic Temperatures of Folding of a Small Peptide

We perform a generalized-ensemble simulation of a small peptide taking the interactions among all atoms into account. From this simulation we obtain thermodynamic quantities over a wide range of temperatures. In particular, we show that the folding of a small peptide is a multi-stage process associated with two characteristic temperatures, the collapse temperature T_{\theta} and the folding temperature T_f. Our results give supporting evidence for the energy landscape picture and funnel concept. These ideas were previously developed in the context of studies of simplified protein models, and here for the first time checked in an all-atom Monte Carlo simulation.Comment: Latex, 6 Figure

Basic rockfall simulation with consideration of vegetation and application to protection measure

The estimation of risk due to rockfall is often done empirically. As a rational and effective method towards performance-based design of protection measures, a three-dimensional simulation method helps to describe the motion of rockfall on a slope and to consider the effect of vegetation probabilistically. This document details a typical simulation method and analyses the manner of rockfalls paired with interference of vegetation and other factors. As application, an actual slope is analyzed where rockfall occurred during the Noto Peninsula Earthquake. Finally, the validity and the benefits of the shown method are the basis for a hazard mapping for rockfall and the planning of measures

PosMed (Positional Medline): prioritizing genes with an artificial neural network comprising medical documents to accelerate positional cloning

PosMed (http://omicspace.riken.jp/) prioritizes candidate genes for positional cloning by employing our original database search engine GRASE, which uses an inferential process similar to an artificial neural network comprising documental neurons (or ‘documentrons’) that represent each document contained in databases such as MEDLINE and OMIM. Given a user-specified query, PosMed initially performs a full-text search of each documentron in the first-layer artificial neurons and then calculates the statistical significance of the connections between the hit documentrons and the second-layer artificial neurons representing each gene. When a chromosomal interval(s) is specified, PosMed explores the second-layer and third-layer artificial neurons representing genes within the chromosomal interval by evaluating the combined significance of the connections from the hit documentrons to the genes. PosMed is, therefore, a powerful tool that immediately ranks the candidate genes by connecting phenotypic keywords to the genes through connections representing not only gene–gene interactions but also other biological interactions (e.g. metabolite–gene, mutant mouse–gene, drug–gene, disease–gene and protein–protein interactions) and ortholog data. By utilizing orthologous connections, PosMed facilitates the ranking of human genes based on evidence found in other model species such as mouse. Currently, PosMed, an artificial superbrain that has learned a vast amount of biological knowledge ranging from genomes to phenomes (or ‘omic space’), supports the prioritization of positional candidate genes in humans, mouse, rat and Arabidopsis thaliana

Metropolis simulations of Met-Enkephalin with solvent-accessible area parameterizations

We investigate the solvent-accessible area method by means of Metropolis simulations of the brain peptide Met-Enkephalin at 300$K$. For the energy function ECEPP/2 nine atomic solvation parameter (ASP) sets are studied. The simulations are compared with one another, with simulations with a distance dependent electrostatic permittivity $\epsilon (r)$, and with vacuum simulations ($\epsilon =2$). Parallel tempering and the biased Metropolis techniques RM$_1$ are employed and their performance is evaluated. The measured observables include energy and dihedral probability densities (pds), integrated autocorrelation times, and acceptance rates. Two of the ASP sets turn out to be unsuitable for these simulations. For all other systems selected configurations are minimized in search of the global energy minima, which are found for the vacuum and the $\epsilon(r)$ system, but for none of the ASP models. Other observables show a remarkable dependence on the ASPs. In particular, we find three ASP sets for which the autocorrelations at 300$$K are considerably smaller than for vacuum simulations.Comment: 10 pages and 8 figure

The RIKEN integrated database of mammals

The RIKEN integrated database of mammals (http://scinets.org/db/mammal) is the official undertaking to integrate its mammalian databases produced from multiple large-scale programs that have been promoted by the institute. The database integrates not only RIKEN’s original databases, such as FANTOM, the ENU mutagenesis program, the RIKEN Cerebellar Development Transcriptome Database and the Bioresource Database, but also imported data from public databases, such as Ensembl, MGI and biomedical ontologies. Our integrated database has been implemented on the infrastructure of publication medium for databases, termed SciNetS/SciNeS, or the Scientists’ Networking System, where the data and metadata are structured as a semantic web and are downloadable in various standardized formats. The top-level ontology-based implementation of mammal-related data directly integrates the representative knowledge and individual data records in existing databases to ensure advanced cross-database searches and reduced unevenness of the data management operations. Through the development of this database, we propose a novel methodology for the development of standardized comprehensive management of heterogeneous data sets in multiple databases to improve the sustainability, accessibility, utility and publicity of the data of biomedical information

MPHASYS: a mouse phenotype analysis system

<p>Abstract</p> <p>Background</p> <p>Systematic, high-throughput studies of mouse phenotypes have been hampered by the inability to analyze individual animal data from a multitude of sources in an integrated manner. Studies generally make comparisons at the level of genotype or treatment thereby excluding associations that may be subtle or involve compound phenotypes. Additionally, the lack of integrated, standardized ontologies and methodologies for data exchange has inhibited scientific collaboration and discovery.</p> <p>Results</p> <p>Here we introduce a Mouse Phenotype Analysis System (MPHASYS), a platform for integrating data generated by studies of mouse models of human biology and disease such as aging and cancer. This computational platform is designed to provide a standardized methodology for working with animal data; a framework for data entry, analysis and sharing; and ontologies and methodologies for ensuring accurate data capture. We describe the tools that currently comprise MPHASYS, primarily ones related to mouse pathology, and outline its use in a study of individual animal-specific patterns of multiple pathology in mice harboring a specific germline mutation in the DNA repair and transcription-specific gene Xpd.</p> <p>Conclusion</p> <p>MPHASYS is a system for analyzing multiple data types from individual animals. It provides a framework for developing data analysis applications, and tools for collecting and distributing high-quality data. The software is platform independent and freely available under an open-source license <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>.</p

Primary myoepithelial carcinoma of the lung: a rare entity treated with parenchymal sparing resection

Primary lung myoepithelial carcinomas are rare neoplasms arising from the salivary glands of the respiratory epithelium. Given the rare occurrences and reports of these tumors, appropriate recommendations for resection are difficult to formulate. Although classified as low-grade neoplasms, these tumors have a significant rate of recurrence and distant metastasis

The clinical significance of splice variants and subcellular localisation of survivin in non-small cell lung cancers

Survivin is a member of the inhibitor of apoptosis protein family. Survivin has splice variants with different biological functions associated with tumorigenesis. We investigated 134 non-small cell lung cancers (NSCLCs) to study the clinical significance of wild-type survivin, survivin-2B, and survivin-deltaEx3. Real-time PCR analyses were performed for their gene expressions. The subcellular localisation of survivin proteins was evaluated by immunohistochemistry. The Ki-67 proliferation index and the apoptotic index were also evaluated. The survivin-deltaEx3 gene expression was significantly higher in stage II–III than in stage I (P=0.0174), and significantly correlated with the nuclear pan-survivin expression (P<0.0001). The Ki-67 index was significantly higher in wild-type survivin-positive tumours (P<0.0001), survivin-deltaEx3-positive tumours (P<0.0001), and tumours with positive expression of the nuclear pan-survivin (P=0.0047). In contrast, the apoptotic index was significantly lower only in wild-type survivin-positive tumours (P<0.0001). Thus, the wild-type survivin gene expression was associated with apoptotic inhibition and tumour proliferation. Furthermore, the survivin-deltaEx3 gene expression was strongly associated with tumour proliferation, especially in advanced stage NSCLCs. In contrast, the survivin-2B gene expression did not correlate with tumour proliferation or tumour apoptosis

Prevalence of sexual dimorphism in mammalian phenotypic traits

The role of sex in biomedical studies has often been overlooked, despite evidence of sexually dimorphic effects in some biological studies. Here, we used high-throughput phenotype data from 14,250 wildtype and 40,192 mutant mice (representing 2,186 knockout lines), analysed for up to 234 traits, and found a large proportion of mammalian traits both in wildtype and mutants are influenced by sex. This result has implications for interpreting disease phenotypes in animal models and humans