General, Applied and Systems Toxicology最新文献_第3页

Application of Ecotoxicogenomics for Understanding Mode of Action of Chemicals and Species Extrapolation 生态毒理基因组学在了解化学物质作用方式和物种外推中的应用

General, Applied and Systems Toxicology Pub Date : 2011-09-15 DOI: 10.1002/9780470744307.GAT204

Watanabe Hajime, Kato Yasuhiko, Iguchi Taisen

{"title":"Application of Ecotoxicogenomics for Understanding Mode of Action of Chemicals and Species Extrapolation","authors":"Watanabe Hajime, Kato Yasuhiko, Iguchi Taisen","doi":"10.1002/9780470744307.GAT204","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT204","url":null,"abstract":"Chemicals released into the environment have a potential to affect various species; therefore, evaluation of the impacts of the chemicals on ecosystems is an urgent issue. However, strategies to evaluate impacts of chemicals on ecosystems have been very limited, because species in the environment are too diverse to establish common strategy for the evaluation. This difficulty can be overcome by applying genomic approaches because genomic information is conserved among various species. Recent advances in toxicogenomics, the integration of genomics into toxicology, can be applied to ecotoxicology, named ecotoxicogenomics. Application of ecotoxicogenomics to Daphnia magna, a small crustacean, proved that it can be used for classification of chemicals. Similar approaches can also be applied to other organisms such as algae. By taking into account gene annotations and other genomic information, these analyses can be helpful to extrapolate the effects of chemicals to other species. \u0000 \u0000 \u0000Keywords: \u0000 \u0000algae; \u0000comparative genomics; \u0000Daphnia; \u0000DNA; \u0000microarray; \u0000ecotoxicogenomics","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125455183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Application of Proteomics to Study Mechanisms of Toxicity and Dose-Response Relationships of Chemical Exposure 应用蛋白质组学研究化学物质暴露的毒性机制和剂量-反应关系

General, Applied and Systems Toxicology Pub Date : 2011-09-15 DOI: 10.1002/9780470744307.GAT216

Zheying Zhu, R. Edwards

引用次数: 3

Toxicoinformatics for Systems Toxicology 系统毒理学毒理学信息学

General, Applied and Systems Toxicology Pub Date : 2011-09-15 DOI: 10.1002/9780470744307.GAT221

L. Burgoon

{"title":"Toxicoinformatics for Systems Toxicology","authors":"L. Burgoon","doi":"10.1002/9780470744307.GAT221","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT221","url":null,"abstract":"Systems biology and systems toxicology mean different things to different people. To some, both disciplines focus on the creation of biological networks, and may be called network biology. To others, these disciplines conjure images of mathematical models to explain biological phenomena. Others will take a stance that it is really the combination of these philosophies, while there are others who believe that they are no more than the integration of omics technologies with other biological disciplines. Regardless of where you fall in this spectrum there is one universal truth: investigators require a significant amount of data to perform systems biology and systems toxicology. This chapter discusses some ideas with respect to data management, including data security, as well as databases and data warehouses. The chapter closes with some discussion of modeling and gene regulatory element identification. After reading this chapter the reader should have a better idea of some of the issues with respect to data management and analysis in systems biology and systems toxicology. \u0000 \u0000 \u0000Keywords: \u0000 \u0000bioinformatics; \u0000database; \u0000data management; \u0000machine learning; \u0000toxicoinformatics","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133627272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Species‐Metabolite Relation Database KNApSAcK and Its Multifaceted Retrieval System, KNApSAcK Family 物种-代谢物关系数据库KNApSAcK及其多面检索系统，KNApSAcK家族

General, Applied and Systems Toxicology Pub Date : 2011-09-15 DOI: 10.1002/9780470744307.GAT218

Hiroki Takahashi, Aki Hirai, M. Shojo, K. Matsuda, A. Parvin, H. Asahi, Kensuke Nakamura, Altaf-Ul-Amin, S. Kanaya

{"title":"Species‐Metabolite Relation Database KNApSAcK and Its Multifaceted Retrieval System, KNApSAcK Family","authors":"Hiroki Takahashi, Aki Hirai, M. Shojo, K. Matsuda, A. Parvin, H. Asahi, Kensuke Nakamura, Altaf-Ul-Amin, S. Kanaya","doi":"10.1002/9780470744307.GAT218","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT218","url":null,"abstract":"In a metabolomics research, assignment of measured spectra to a specific metabolite is one of the most fundamental processes. The assignment is usually made by taking a match with known compounds, and therefore it is necessary to scan the spectra against whole previously studied compounds. This means the survey of whole natural products reported in the literature, which is an extremely tedious and daunting process. In order to make this process feasible, we have developed a metabolite database called KNApSAcK, which currently contains 76,357 species–metabolite relations involving 37,693 metabolites. In the present study, we review the current status of KNApSAcK database and its application to metabolomics and introduce the multifaceted retrieval system KNApSAcK family, which consists of seven parts for the purpose of retrieving metabolites from several different aspects. “Pocket” includes search system for species related to human living such as edible plants in Japan (“Lunch Box”), herb teas (“Tea Pot”, in progress), traditional Japanese medicine (“KAMPO”), poisonous plant (“Poison”, in progress), and bio-fuel resources (“Fuel”, in progress). “KNApSAcK from around the world” includes medicinal and edible plants utilized in each country. Seven thousand three hundred and fifty-six pairwise relations between medicinal/edible plants and 119 nations worldwide have been accumulated from scientific literatures. \u0000 \u0000 \u0000Keywords: \u0000 \u0000KNApSAcK; \u0000spece-metabolite relation database; \u0000metabolomics","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115039191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Toxicogenomics: An Overview with Special Reference to Genetic and Genomic Approaches to the Identification of Toxic Effects 毒物基因组学:概述与特别参考遗传和基因组方法鉴定毒性作用

General, Applied and Systems Toxicology Pub Date : 2011-09-15 DOI: 10.1002/9780470744307.GAT200

M. Banerjee, A. Giri

{"title":"Toxicogenomics: An Overview with Special Reference to Genetic and Genomic Approaches to the Identification of Toxic Effects","authors":"M. Banerjee, A. Giri","doi":"10.1002/9780470744307.GAT200","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT200","url":null,"abstract":"Toxicology, the study of poisons, has been explored widely since ages immemorial. However, only recently, workers have begun to apply the state-of-the-art “omics” technologies to study toxicological problems. This has led to exciting possibilities in the field of toxicology and holds promise to revolutionize the study of poisons and their effects in ways more than one. However, with all these advantages, this new technique also has the disadvantage of being exorbitantly costly as well as low in reproducibility. Hence, the results obtained from toxicogenomic techniques need to be vindicated by classical cytogenetic and molecular biology methods before reaching any tangible conclusion. This article gives a glimpse of the genomic and genetic components used extensively in contemporary toxicological studies and elucidates how an appropriate interaction between the two approaches can help workers to generate high-quality data and reach proper conclusions by avoiding possible pitfalls. \u0000 \u0000 \u0000Keywords: \u0000 \u0000chromosomal aberrations; \u0000microarray; \u0000micronucleus; \u0000miRNA; \u0000toxicogenomics; \u0000toxicology; \u0000single nucleotide polymorphism","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116266463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Systems Toxicology Modeling for Prediction in Humans 人类系统毒理学模型预测

General, Applied and Systems Toxicology Pub Date : 2011-09-15 DOI: 10.1002/9780470744307.GAT233

C. Migliorini, T. Lavé, N. Parrott, M. Reddy, H. Grimm, R. Penland, A. Soubret, G. Helmlinger, A. Georgieva, K. Zuideveld

引用次数: 0

Integrative Analysis of Microarray Data: A Path for Systems Toxicology 微阵列数据的综合分析:系统毒理学的路径

General, Applied and Systems Toxicology Pub Date : 2011-09-15 DOI: 10.1002/9780470744307.GAT207

A. Rasche, R. Yildirimman, R. Herwig

{"title":"Integrative Analysis of Microarray Data: A Path for Systems Toxicology","authors":"A. Rasche, R. Yildirimman, R. Herwig","doi":"10.1002/9780470744307.GAT207","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT207","url":null,"abstract":"Microarrays are the standard tool for a genome-wide analysis of gene expression. Multiple studies exist that, for example, track changes of systems with respect to compound treatment or compare the treated versus the untreated states. Besides these single studies, integrative approaches that analyze many such studies in parallel have gained increasing attention because they constitute a crucial step for the identification of general biological processes to relevant the system under analysis and would, thus, lead to the identification of more stable and robust marker genes. For gene expression analysis, the Affymetrix arrays are a well-established and widely used experimental system. In this chapter, we provide a basic understanding of this microarray technology and describe the design, pre-processing, and analysis of the data. Standardized and automatic pre-processing procedures are essential for the subsequent parallel analysis of many data sets. These procedures are greatly supported by storage and information systems collecting the essential information. As an example for an integrated analysis of a large number of toxicology data sets, we describe recent results on a meta-analysis combining different chip platforms, different species, and treatments with different genotoxic and non-genotoxic compounds. We show how general mechanisms, biological pathways, and endpoints of toxicity can be reconstructed by this approach. \u0000 \u0000 \u0000Keywords: \u0000 \u0000Affymetrix GeneChip; \u0000high-throughput data storage; \u0000meta-analysis; \u0000microarray","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125051774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Commonality and Stochasticity in Systems Toxicology 系统毒理学的共性与随机性

General, Applied and Systems Toxicology Pub Date : 2011-09-15 DOI: 10.1002/9780470744307.GAT227

Y. Hirabayashi, Tohru Inoue

{"title":"Commonality and Stochasticity in Systems Toxicology","authors":"Y. Hirabayashi, Tohru Inoue","doi":"10.1002/9780470744307.GAT227","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT227","url":null,"abstract":"“Systems toxicology” is “systems biology” applied to general toxicology, which is to elucidate a universal concept of biological interactions between living organisms and xenobiotics by global assays of transcriptomics, proteomics and other various applied omics studies, during various biological steps in in vivo responses, in developmental, pubertal and senescent stages, and at the ontological or phylogenical level, in addition to in vitro cellular responses. The aim of the chapter is to focus on systems toxicology to incorporate a new biological concept that distinguishes commonality and stochasticity from those xenobiotic responses when one incorporates computational toxicological data from the gene chip microarray into systems toxicology. The multiplicity of biological reactions can be better understood when common gene expression profiles and stochastic gene expression profiles would be unsupervisedly analyzed computationally. Previous toxicological data have been analysed frequently with their average endpoints focused on the commonality. However, probabilistic stochasticity may be analysed as specific stochastic clusters that elucidate other aspects of biological diversity in future “systems toxicology”. \u0000 \u0000 \u0000Keywords: \u0000 \u0000ageing; \u0000aryl hydrocarbon receptor-mediated toxicity; \u0000benzene-induced haematotoxicity; \u0000epigenetic stochasticity; \u0000haematotoxicology; \u0000predictable toxicology; \u0000radiation-induced myeloid leukaemia; \u0000stochastic gene expression; \u0000toxicogenomics; \u0000toxicoinformatics","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129771188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Systems Toxicological Approach to the Risk Assessment of Nanomaterials 纳米材料风险评估的系统毒理学方法

General, Applied and Systems Toxicology Pub Date : 2011-09-15 DOI: 10.1002/9780470744307.GAT247

Sang-Hee Jeong, W. Cho, Ji-Eun Kim, M. Cho

{"title":"Systems Toxicological Approach to the Risk Assessment of Nanomaterials","authors":"Sang-Hee Jeong, W. Cho, Ji-Eun Kim, M. Cho","doi":"10.1002/9780470744307.GAT247","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT247","url":null,"abstract":"Nowadays, nanomaterials have come into the spotlight as new materials that have lots of prominent benefits in various fields of human life. Risk assessment of the nanomaterials requires a multidisciplinary understanding of the differences from their large particles in surface physicochemistry and dosimetry. The size, biological effective dose, surface chemistry, interactions with biological membrane and dispersion media are important factors that make unique characteristics of nanomaterials in their toxicity potency. Conventional methods for the toxicological assessment may have limitations in proper understanding of the dose-response relationships of the diversity of structures and compositions of nanomaterials. Challenges to toxicological testing of nanomaterials will be covered with the strategy of systems toxicology including toxico-genomics, toxico-proteomics and toxico-metabolomics. The data driven from systems toxicology are valuable in the identification and characterization of the mode of action of nanomaterials. Many of toxicogenomic and toxicoproteomic studies have released that the production of reactive oxygen species and inflammation caused by oxidative stress are the key mechanism of toxicity of nanomaterials. However, there is still limited information for the assessment of toxicity thresholds based on dose-response relationships and for the estimation of exposure in risk assessment of nanomaterials. More integrated and systemic studies are required for the risk assessment of human health impact considering various but unique properties of nanomaterials. \u0000 \u0000 \u0000Keywords: \u0000 \u0000nanomaterials; \u0000systems toxicology; \u0000toxico-genomics; \u0000toxico-proteomics; \u0000toxico-metabolomics; \u0000risk assessment","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133439062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Mass Spectrometry‐Based Proteomics in Systems Toxicology 系统毒理学中基于质谱的蛋白质组学

General, Applied and Systems Toxicology Pub Date : 2011-09-15 DOI: 10.1002/9780470744307.GAT212

Li-Rong Yu, Yuan Gao, D. Mendrick

{"title":"Mass Spectrometry‐Based Proteomics in Systems Toxicology","authors":"Li-Rong Yu, Yuan Gao, D. Mendrick","doi":"10.1002/9780470744307.GAT212","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT212","url":null,"abstract":"Advances of proteomics and its application to toxicological studies have led to the development of a new discipline, toxicoproteomics. Toxicoproteomics and its associated technologies are vital for the understanding of toxicity in systems toxicology. Many quantitative proteomic technologies including gel-based and solution-based approaches have been developed. Mass spectrometry is the core technology in proteomics for its capabilities of protein identification and quantification. While global quantitative proteome analysis using either stable isotope labeling or label-free approaches enables the discovery of toxicity biomarkers and toxicity mechanisms, targeted proteomic approaches such as MRM could play important roles in biomarker validation and quantitative analysis of targeted proteins and pathways. To qualify biomarkers for clinical application, biomarker candidates have to be clinically verified and the assay has to be analytically validated. It is essential that quantitative proteomic analysis is eventually conducted in an absolute fashion. Such absolute quantification should be relied on robust stable isotope labeled peptide/protein standards. \u0000 \u0000 \u0000Keywords: \u0000 \u0000proteomics; \u00002D-PAGE; \u0000mass spectrometry; \u0000tandem MS; \u0000protein quantitation; \u0000stable isotope labeling; \u0000biomarker; \u0000toxicity mechanism; \u0000toxicoproteomics; \u0000systems biology","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131790071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0