Sample records for air pathway analysis

  1. The Cardiopulmonary Effects of Ambient Air Pollution and Mechanistic Pathways: A Comparative Hierarchical Pathway Analysis

    PubMed Central

    Thomas, Duncan C.; Zhang, Junfeng; Kipen, Howard M.; Rich, David Q.; Zhu, Tong; Huang, Wei; Hu, Min; Wang, Guangfa; Wang, Yuedan; Zhu, Ping; Lu, Shou-En; Ohman-Strickland, Pamela; Diehl, Scott R.; Eckel, Sandrah P.

    2014-01-01

    Previous studies have investigated the associations between exposure to ambient air pollution and biomarkers of physiological pathways, yet little has been done on the comparison across biomarkers of different pathways to establish the temporal pattern of biological response. In the current study, we aim to compare the relative temporal patterns in responses of candidate pathways to different pollutants. Four biomarkers of pulmonary inflammation and oxidative stress, five biomarkers of systemic inflammation and oxidative stress, ten parameters of autonomic function, and three biomarkers of hemostasis were repeatedly measured in 125 young adults, along with daily concentrations of ambient CO, PM2.5, NO2, SO2, EC, OC, and sulfate, before, during, and after the Beijing Olympics. We used a two-stage modeling approach, including Stage I models to estimate the association between each biomarker and pollutant over each of 7 lags, and Stage II mixed-effect models to describe temporal patterns in the associations when grouping the biomarkers into the four physiological pathways. Our results show that candidate pathway groupings of biomarkers explained a significant amount of variation in the associations for each pollutant, and the temporal patterns of the biomarker-pollutant-lag associations varied across candidate pathways (p<0.0001) and were not linear (from lag 0 to lag 3: p = 0.0629, from lag 3 to lag 6: p = 0.0005). These findings suggest that, among this healthy young adult population, the pulmonary inflammation and oxidative stress pathway is the first to respond to ambient air pollution exposure (within 24 hours) and the hemostasis pathway responds gradually over a 2–3 day period. The initial pulmonary response may contribute to the more gradual systemic changes that likely ultimately involve the cardiovascular system. PMID:25502951

  2. ENGINEERING BULLETIN: AIR PATHWAY ANALYSIS

    EPA Science Inventory

    This bulletin presents information on estimating toxic air emissions from Superfund sites. The focus is on the collection of air emmissions data during the site inspection and remedial investigation/feasibility study and the use of these data for the selection or implementation o...

  3. Section 17: Air Pathway- Waste Characteristics and Targets

    EPA Pesticide Factsheets

    HRS Training. the air migration pathway evaluates the likelihood of release of hazardous substances into the atmosphere and how many people and sensitive environments could be exposed to hazardous substances carried in the air, including gases

  4. Future air pollution in the Shared Socio-economic Pathways

    DOE PAGES

    Rao, Shilpa; Klimont, Zbigniew; Smith, Steven J.; ...

    2016-07-15

    Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high,more » central, and low pollution control ambitions over the 21 st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. We provide an overview of pollutant emission trajectories under the SSP scenarios. Pollutant emissions in these scenarios cover a wider range than the scenarios used in previous international climate model comparisons. Furthermore, the SSP scenarios provide the opportunity to access a more comprehensive range of future global and regional air quality outcomes.« less

  5. Future air pollution in the Shared Socio-economic Pathways

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rao, Shilpa; Klimont, Zbigniew; Smith, Steven J.

    Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high,more » central, and low pollution control ambitions over the 21 st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. We provide an overview of pollutant emission trajectories under the SSP scenarios. Pollutant emissions in these scenarios cover a wider range than the scenarios used in previous international climate model comparisons. Furthermore, the SSP scenarios provide the opportunity to access a more comprehensive range of future global and regional air quality outcomes.« less

  6. Modeling the plant uptake of organic chemicals, including the soil-air-plant pathway.

    PubMed

    Collins, Chris D; Finnegan, Eilis

    2010-02-01

    The soil-air-plant pathway is potentially important in the vegetative accumulation of organic pollutants from contaminated soils. While a number of qualitative frameworks exist for the prediction of plant accumulation of organic chemicals by this pathway, there are few quantitative models that incorporate this pathway. The aim of the present study was to produce a model that included this pathway and could quantify its contribution to the total plant contamination for a range of organic pollutants. A new model was developed from three submodels for the processes controlling plant contamination via this pathway: aerial deposition, soil volatilization, and systemic translocation. Using the combined model, the soil-air-plant pathway was predicted to account for a significant proportion of the total shoot contamination for those compounds with log K(OA) > 9 and log K(AW) < -3. For those pollutants with log K(OA) < 9 and log K(AW) > -3 there was a higher deposition of pollutant via the soil-air-plant pathway than for those chemicals with log K(OA) > 9 and log K(AW) < -3, but this was an insignificant proportion of the total shoot contamination because of the higher mobility of these compounds via the soil-root-shoot pathway. The incorporation of the soil-air-plant pathway into the plant uptake model did not significantly improve the prediction of the contamination of vegetation from polluted soils when compared across a range of studies. This was a result of the high variability between the experimental studies where the bioconcentration factors varied by 2 orders of magnitude at an equivalent log K(OA). One potential reason for this is the background air concentration of the pollutants under study. It was found background air concentrations would dominate those from soil volatilization in many situations unless there was a soil hot spot of contamination, i.e., >100 mg kg(-1).

  7. SPECIAL ANALYSIS AIR PATHWAY MODELING OF E-AREA LOW-LEVEL WASTE FACILITY

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hiergesell, R.; Taylor, G.

    This Special Analysis (SA) was initiated to address a concern expressed by the Department of Energy's Low Level Waste Disposal Facility Federal Review Group (LFRG) Review Team during their review of the 2008 E-Area Performance Assessment (PA) (WSRC, 2008). Their concern was the potential for overlapping of atmospheric plumes, emanating from the soil surface above SRS LLW disposal facilities within the E-Area, to contribute to the dose received by a member of the public during the Institutional Control (IC) period. The implication of this concern was that the dose to the maximally-exposed individual (MEI) located at the SRS boundary mightmore » be underestimated during this time interval. To address this concern a re-analysis of the atmospheric pathway releases from E-Area was required. In the process of developing a new atmospheric release model (ARM) capable of addressing the LFRG plume overlap concern, it became obvious that new and better atmospheric pathway disposal limits should be developed for each of the E-Area disposal facilities using the new ARM. The scope of the SA was therefore expanded to include the generation of these new limits. The initial work conducted in this SA was to develop a new ARM using the GoldSim{reg_sign} program (GTG, 2009). The model simulates the subsurface vapor diffusion of volatile radionuclides as they release from E-Area disposal facility waste zones and migrate to the land surface. In the process of this work, many new features, including several new physical and chemical transport mechanisms, were incorporated into the model. One of the most important improvements was to incorporate a mechanism to partition volatile contaminants across the water-air interface within the partially saturated pore space of the engineered and natural materials through which vapor phase transport occurs. A second mechanism that was equally important was to incorporate a maximum concentration of 1.9E-07 Ci/m{sup 3} of {sup 14}CO{sub 2} in the air

  8. Linked Analysis of East Asia Emission Reduction Pathways

    NASA Astrophysics Data System (ADS)

    Kim, Y.; Woo, J. H.; Bu, C.; Lee, Y.; Kim, J.; Jang, Y.; Park, M.

    2017-12-01

    Air pollution and its impacts over the Northeast Asia are very severe because of the massive pollutant emissions and high population. Korea has been trying to improve air quality with the enhanced environmental legislation. The air quality over Korea, however, does not entirely dependent on its local emissions. Transboundary air pollution from China highly affects Korean atmosphere. The purpose of this research is to understand role of local and transbounday efforts to improve air quality changes over Korea. In this research, we have tried to set up the multiple emission scenario pathways for Korea and China using IIASA's GAINS (Greenhouse gas - Air pollution Interactions aNd Synergies) modeling framework. More up-to-date growth factors and control policy packets were made using regional socio-economic data and control policy information from local governments and international statistics. Four major scenario pathways, 1) Base (Baseline: current legislation), 2) OTB/OTB(On the book/On the way : existing control measure/planed control measure), 3) BOTW_GHG(Beyond on the way : OTW with GHG reduction plan), 4) BOTW_NH3 (OTW with additional NH3 reduction measure) were developed to represent air quality improvement pathways in consideration of both Korean and Chinese efforts. Strict ambient PM2.5 standards from Seoul metropolitan Air quality Improvement Plan(SAIP) seems too enthusiastic without linking air quality control efforts of China. Step-by-step emission controls and following air quality, control cost, health impact from each scenario will be presented at the conference. This subject is supported by Korea Ministry of Environment as "Climate Change Correspondence Program". And This work was supported under the framework of national strategy project on fine particulate matters by Ministry of Science, ICT and Future Planning.

  9. Pathway cross-talk network analysis identifies critical pathways in neonatal sepsis.

    PubMed

    Meng, Yu-Xiu; Liu, Quan-Hong; Chen, Deng-Hong; Meng, Ying

    2017-06-01

    Despite advances in neonatal care, sepsis remains a major cause of morbidity and mortality in neonates worldwide. Pathway cross-talk analysis might contribute to the inference of the driving forces in bacterial sepsis and facilitate a better understanding of underlying pathogenesis of neonatal sepsis. This study aimed to explore the critical pathways associated with the progression of neonatal sepsis by the pathway cross-talk analysis. By integrating neonatal transcriptome data with known pathway data and protein-protein interaction data, we systematically uncovered the disease pathway cross-talks and constructed a disease pathway cross-talk network for neonatal sepsis. Then, attract method was employed to explore the dysregulated pathways associated with neonatal sepsis. To determine the critical pathways in neonatal sepsis, rank product (RP) algorithm, centrality analysis and impact factor (IF) were introduced sequentially, which synthetically considered the differential expression of genes and pathways, pathways cross-talks and pathway parameters in the network. The dysregulated pathways with the highest IF values as well as RP<0.01 were defined as critical pathways in neonatal sepsis. By integrating three kinds of data, only 6919 common genes were included to perform the pathway cross-talk analysis. By statistic analysis, a total of 1249 significant pathway cross-talks were selected to construct the pathway cross-talk network. Moreover, 47 dys-regulated pathways were identified via attract method, 20 pathways were identified under RP<0.01, and the top 10 pathways with the highest IF were also screened from the pathway cross-talk network. Among them, we selected 8 common pathways, i.e. critical pathways. In this study, we systematically tracked 8 critical pathways involved in neonatal sepsis by integrating attract method and pathway cross-talk network. These pathways might be responsible for the host response in infection, and of great value for advancing

  10. Pathway enrichment analysis approach based on topological structure and updated annotation of pathway.

    PubMed

    Yang, Qian; Wang, Shuyuan; Dai, Enyu; Zhou, Shunheng; Liu, Dianming; Liu, Haizhou; Meng, Qianqian; Jiang, Bin; Jiang, Wei

    2017-08-16

    Pathway enrichment analysis has been widely used to identify cancer risk pathways, and contributes to elucidating the mechanism of tumorigenesis. However, most of the existing approaches use the outdated pathway information and neglect the complex gene interactions in pathway. Here, we first reviewed the existing widely used pathway enrichment analysis approaches briefly, and then, we proposed a novel topology-based pathway enrichment analysis (TPEA) method, which integrated topological properties and global upstream/downstream positions of genes in pathways. We compared TPEA with four widely used pathway enrichment analysis tools, including database for annotation, visualization and integrated discovery (DAVID), gene set enrichment analysis (GSEA), centrality-based pathway enrichment (CePa) and signaling pathway impact analysis (SPIA), through analyzing six gene expression profiles of three tumor types (colorectal cancer, thyroid cancer and endometrial cancer). As a result, we identified several well-known cancer risk pathways that could not be obtained by the existing tools, and the results of TPEA were more stable than that of the other tools in analyzing different data sets of the same cancer. Ultimately, we developed an R package to implement TPEA, which could online update KEGG pathway information and is available at the Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/TPEA/. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  11. The Pathway for Oxygen: Tutorial Modelling on Oxygen Transport from Air to Mitochondrion: The Pathway for Oxygen.

    PubMed

    Bassingthwaighte, James B; Raymond, Gary M; Dash, Ranjan K; Beard, Daniel A; Nolan, Margaret

    2016-01-01

    The 'Pathway for Oxygen' is captured in a set of models describing quantitative relationships between fluxes and driving forces for the flux of oxygen from the external air source to the mitochondrial sink at cytochrome oxidase. The intervening processes involve convection, membrane permeation, diffusion of free and heme-bound O2 and enzymatic reactions. While this system's basic elements are simple: ventilation, alveolar gas exchange with blood, circulation of the blood, perfusion of an organ, uptake by tissue, and consumption by chemical reaction, integration of these pieces quickly becomes complex. This complexity led us to construct a tutorial on the ideas and principles; these first PathwayO2 models are simple but quantitative and cover: (1) a 'one-alveolus lung' with airway resistance, lung volume compliance, (2) bidirectional transport of solute gasses like O2 and CO2, (3) gas exchange between alveolar air and lung capillary blood, (4) gas solubility in blood, and circulation of blood through the capillary syncytium and back to the lung, and (5) blood-tissue gas exchange in capillaries. These open-source models are at Physiome.org and provide background for the many respiratory models there.

  12. First report of Legionella pneumophila in car cabin air filters. Are these a potential exposure pathway for professional drivers?

    PubMed

    Alexandropoulou, Ioanna G; Konstantinidis, Theocharis G; Parasidis, Theodoros A; Nikolaidis, Christos; Panopoulou, Maria; Constantinidis, Theodoros C

    2013-12-01

    Recent findings have identified professional drivers as being at an increased risk of Legionnaires' disease. Our hypothesis was that used car cabin air filters represent a reservoir of Legionella bacteria, and thus a potential pathway for contamination. We analysed used cabin air filters from various types of car. The filters were analysed by culture and by molecular methods. Our findings indicated that almost a third of air filters were colonized with Legionella pneumophila. Here, we present the first finding of Legionella spp. in used car cabin air filters. Further investigations are needed in order to confirm this exposure pathway. The presence of Legionella bacteria in used cabin air filters may have been an unknown source of infection until now.

  13. Genome-wide pathway-based association analysis identifies risk pathways associated with Parkinson's disease.

    PubMed

    Zhang, Mingming; Mu, Hongbo; Shang, Zhenwei; Kang, Kai; Lv, Hongchao; Duan, Lian; Li, Jin; Chen, Xinren; Teng, Yanbo; Jiang, Yongshuai; Zhang, Ruijie

    2017-01-06

    Parkinson's disease (PD) is the second most common neurodegenerative disease. It is generally believed that it is influenced by both genetic and environmental factors, but the precise pathogenesis of PD is unknown to date. In this study, we performed a pathway analysis based on genome-wide association study (GWAS) to detect risk pathways of PD in three GWAS datasets. We first mapped all SNP markers to autosomal genes in each GWAS dataset. Then, we evaluated gene risk values using the minimum P-value of the tagSNPs. We took a pathway as a unit to identify the risk pathways based on the cumulative risks of the genes in the pathway. Finally, we combine the analysis results of the three datasets to detect the high risk pathways associated with PD. We found there were five same pathways in the three datasets. Besides, we also found there were five pathways which were shared in two datasets. Most of these pathways are associated with nervoussystem. Five pathways had been reported to be PD-related pathways in the previous literature. Our findings also implied that there was a close association between immune response and PD. Continued investigation of these pathways will further help us explain the pathogenesis of PD. Copyright © 2016. Published by Elsevier Ltd.

  14. A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways

    PubMed Central

    Han, Junwei; Li, Chunquan; Yang, Haixiu; Xu, Yanjun; Zhang, Chunlong; Ma, Jiquan; Shi, Xinrui; Liu, Wei; Shang, Desi; Yao, Qianlan; Zhang, Yunpeng; Su, Fei; Feng, Li; Li, Xia

    2015-01-01

    Identifying dysregulated pathways from high-throughput experimental data in order to infer underlying biological insights is an important task. Current pathway-identification methods focus on single pathways in isolation; however, consideration of crosstalk between pathways could improve our understanding of alterations in biological states. We propose a novel method of pathway analysis based on global influence (PAGI) to identify dysregulated pathways, by considering both within-pathway effects and crosstalk between pathways. We constructed a global gene–gene network based on the relationships among genes extracted from a pathway database. We then evaluated the extent of differential expression for each gene, and mapped them to the global network. The random walk with restart algorithm was used to calculate the extent of genes affected by global influence. Finally, we used cumulative distribution functions to determine the significance values of the dysregulated pathways. We applied the PAGI method to five cancer microarray datasets, and compared our results with gene set enrichment analysis and five other methods. Based on these analyses, we demonstrated that PAGI can effectively identify dysregulated pathways associated with cancer, with strong reproducibility and robustness. We implemented PAGI using the freely available R-based and Web-based tools (http://bioinfo.hrbmu.edu.cn/PAGI). PMID:25551156

  15. Pathway analysis with next-generation sequencing data.

    PubMed

    Zhao, Jinying; Zhu, Yun; Boerwinkle, Eric; Xiong, Momiao

    2015-04-01

    Although pathway analysis methods have been developed and successfully applied to association studies of common variants, the statistical methods for pathway-based association analysis of rare variants have not been well developed. Many investigators observed highly inflated false-positive rates and low power in pathway-based tests of association of rare variants. The inflated false-positive rates and low true-positive rates of the current methods are mainly due to their lack of ability to account for gametic phase disequilibrium. To overcome these serious limitations, we develop a novel statistic that is based on the smoothed functional principal component analysis (SFPCA) for pathway association tests with next-generation sequencing data. The developed statistic has the ability to capture position-level variant information and account for gametic phase disequilibrium. By intensive simulations, we demonstrate that the SFPCA-based statistic for testing pathway association with either rare or common or both rare and common variants has the correct type 1 error rates. Also the power of the SFPCA-based statistic and 22 additional existing statistics are evaluated. We found that the SFPCA-based statistic has a much higher power than other existing statistics in all the scenarios considered. To further evaluate its performance, the SFPCA-based statistic is applied to pathway analysis of exome sequencing data in the early-onset myocardial infarction (EOMI) project. We identify three pathways significantly associated with EOMI after the Bonferroni correction. In addition, our preliminary results show that the SFPCA-based statistic has much smaller P-values to identify pathway association than other existing methods.

  16. The Pathway for Oxygen: Tutorial Modelling on Oxygen Transport from Air to Mitochondrion

    PubMed Central

    Bassingthwaighte, James B.; Raymond, Gary M.; Dash, Ranjan K.; Beard, Daniel A.; Nolan, Margaret

    2016-01-01

    The ‘Pathway for Oxygen’ is captured in a set of models describing quantitative relationships between fluxes and driving forces for the flux of oxygen from the external air source to the mitochondrial sink at cytochrome oxidase. The intervening processes involve convection, membrane permeation, diffusion of free and heme-bound O2 and enzymatic reactions. While this system’s basic elements are simple: ventilation, alveolar gas exchange with blood, circulation of the blood, perfusion of an organ, uptake by tissue, and consumption by chemical reaction, integration of these pieces quickly becomes complex. This complexity led us to construct a tutorial on the ideas and principles; these first PathwayO2 models are simple but quantitative and cover: 1) a ‘one-alveolus lung’ with airway resistance, lung volume compliance, 2) bidirectional transport of solute gasses like O2 and CO2, 3) gas exchange between alveolar air and lung capillary blood, 4) gas solubility in blood, and circulation of blood through the capillary syncytium and back to the lung, and 5) blood-tissue gas exchange in capillaries. These open-source models are at Physiome.org and provide background for the many respiratory models there. PMID:26782201

  17. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data

    PubMed Central

    Yi, Ming; Horton, Jay D; Cohen, Jonathan C; Hobbs, Helen H; Stephens, Robert M

    2006-01-01

    Background Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data. Result WPS extracts gene lists with shared biological themes through color cue templates. WPS statistically evaluates global functional category enrichment of gene lists and pathway-level pattern enrichment of data. WPS incorporates well-known biological pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes) and Biocarta, GO (Gene Ontology) terms as well as user-defined pathways or relevant gene clusters or groups, and explores gene-term relationships within the derived gene-term association networks (GTANs). WPS simultaneously compares multiple datasets within biological contexts either as pathways or as association networks. WPS also integrates Genetic Association Database and Partial MedGene Database for disease-association information. We have used this program to analyze and compare microarray and proteomics datasets derived from a variety of biological systems. Application examples demonstrated the capacity of WPS to significantly facilitate the analysis of HTP data for integrative discovery. Conclusion This tool represents a pathway-based platform for discovery integration to maximize analysis power. The tool is freely available at . PMID:16423281

  18. Air pathway effects of nuclear materials production at the Hanford Site, 1983 to 1992

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Patton, G.W.; Cooper, A.T.

    1993-10-01

    This report describes the air pathway effects of Hanford Site operations from 1983 to 1992 on the local environment by summarizing the air concentrations of selected radionuclides at both onsite and offsite locations, comparing trends in environment concentrations to changing facility emissions, and briefly describing trends in the radiological dose to the hypothetical maximally exposed member of the public. The years 1983 to 1992 represent the last Hanford Site plutonium production campaign, and this report deals mainly with the air pathway effects from the 200 Areas, in which the major contributors to radiological emissions were located. An additional purpose formore » report was to review the environmental data for a long period of time to provide insight not available in an annual report format. The sampling and analytical systems used by the Surface Environmental Surveillance Project (SESP) to collect air samples during the period of this report were sufficiently sensitive to observe locally elevated concentrations of selected radionuclides near onsite source of emission as well as observing elevated levels, compared to distant locations, of some radionuclides at the down wind perimeter. The US DOE Derived Concentration Guides (DCGs) for airborne radionuclides were not exceeded for any air sample collected during 1983 to 1992, with annual average concentrations of all radionuclides at the downwind perimeter being considerably below the DCG values. Air emissions at the Hanford Site during the period of this report were dominated by releases from the PUREX Plant, with {sup 85}Kr being the major release on a curie basis and {sup 129}I being the major release on a radiological dose basis. The estimated potential radiological dose from Hanford Site point source emissions to the hypothetical maximally exposed individual (MEI) ranged from 0. 02 to 0.22 mrem/yr (effective dose equivalent), which is well below the DOE radiation limit to the public of 100 mrem/yr.« less

  19. Elementary Mode Analysis: A Useful Metabolic Pathway Analysis Tool for Characterizing Cellular Metabolism

    PubMed Central

    Trinh, Cong T.; Wlaschin, Aaron; Srienc, Friedrich

    2010-01-01

    Elementary Mode Analysis is a useful Metabolic Pathway Analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering. PMID:19015845

  20. Pathway Inspector: a pathway based web application for RNAseq analysis of model and non-model organisms.

    PubMed

    Bianco, Luca; Riccadonna, Samantha; Lavezzo, Enrico; Falda, Marco; Formentin, Elide; Cavalieri, Duccio; Toppo, Stefano; Fontana, Paolo

    2017-02-01

    Pathway Inspector is an easy-to-use web application helping researchers to find patterns of expression in complex RNAseq experiments. The tool combines two standard approaches for RNAseq analysis: the identification of differentially expressed genes and a topology-based analysis of enriched pathways. Pathway Inspector is equipped with ad hoc interactive graphical interfaces simplifying the discovery of modulated pathways and the integration of the differentially expressed genes in the corresponding pathway topology. Pathway Inspector is available at the website http://admiral.fmach.it/PI and has been developed in Python, making use of the Django Web Framework. Contact:paolo.fontana@fmach.it

  1. Pathway Inspector: a pathway based web application for RNAseq analysis of model and non-model organisms

    PubMed Central

    Bianco, Luca; Riccadonna, Samantha; Lavezzo, Enrico; Falda, Marco; Formentin, Elide; Cavalieri, Duccio; Toppo, Stefano

    2017-01-01

    Abstract Summary: Pathway Inspector is an easy-to-use web application helping researchers to find patterns of expression in complex RNAseq experiments. The tool combines two standard approaches for RNAseq analysis: the identification of differentially expressed genes and a topology-based analysis of enriched pathways. Pathway Inspector is equipped with ad hoc interactive graphical interfaces simplifying the discovery of modulated pathways and the integration of the differentially expressed genes in the corresponding pathway topology. Availability and Implementation: Pathway Inspector is available at the website http://admiral.fmach.it/PI and has been developed in Python, making use of the Django Web Framework. Contact: paolo.fontana@fmach.it PMID:28158604

  2. Validation of a novel air toxic risk model with air monitoring.

    PubMed

    Pratt, Gregory C; Dymond, Mary; Ellickson, Kristie; Thé, Jesse

    2012-01-01

    Three modeling systems were used to estimate human health risks from air pollution: two versions of MNRiskS (for Minnesota Risk Screening), and the USEPA National Air Toxics Assessment (NATA). MNRiskS is a unique cumulative risk modeling system used to assess risks from multiple air toxics, sources, and pathways on a local to a state-wide scale. In addition, ambient outdoor air monitoring data were available for estimation of risks and comparison with the modeled estimates of air concentrations. Highest air concentrations and estimated risks were generally found in the Minneapolis-St. Paul metropolitan area and lowest risks in undeveloped rural areas. Emissions from mobile and area (nonpoint) sources created greater estimated risks than emissions from point sources. Highest cancer risks were via ingestion pathway exposures to dioxins and related compounds. Diesel particles, acrolein, and formaldehyde created the highest estimated inhalation health impacts. Model-estimated air concentrations were generally highest for NATA and lowest for the AERMOD version of MNRiskS. This validation study showed reasonable agreement between available measurements and model predictions, although results varied among pollutants, and predictions were often lower than measurements. The results increased confidence in identifying pollutants, pathways, geographic areas, sources, and receptors of potential concern, and thus provide a basis for informing pollution reduction strategies and focusing efforts on specific pollutants (diesel particles, acrolein, and formaldehyde), geographic areas (urban centers), and source categories (nonpoint sources). The results heighten concerns about risks from food chain exposures to dioxins and PAHs. Risk estimates were sensitive to variations in methodologies for treating emissions, dispersion, deposition, exposure, and toxicity. © 2011 Society for Risk Analysis.

  3. Service-based analysis of biological pathways

    PubMed Central

    Zheng, George; Bouguettaya, Athman

    2009-01-01

    Background Computer-based pathway discovery is concerned with two important objectives: pathway identification and analysis. Conventional mining and modeling approaches aimed at pathway discovery are often effective at achieving either objective, but not both. Such limitations can be effectively tackled leveraging a Web service-based modeling and mining approach. Results Inspired by molecular recognitions and drug discovery processes, we developed a Web service mining tool, named PathExplorer, to discover potentially interesting biological pathways linking service models of biological processes. The tool uses an innovative approach to identify useful pathways based on graph-based hints and service-based simulation verifying user's hypotheses. Conclusion Web service modeling of biological processes allows the easy access and invocation of these processes on the Web. Web service mining techniques described in this paper enable the discovery of biological pathways linking these process service models. Algorithms presented in this paper for automatically highlighting interesting subgraph within an identified pathway network enable the user to formulate hypothesis, which can be tested out using our simulation algorithm that are also described in this paper. PMID:19796403

  4. Pathway Interaction Network Analysis Identifies Dysregulated Pathways in Human Monocytes Infected by Listeria monocytogenes.

    PubMed

    Fan, Wufeng; Zhou, Yuhan; Li, Hao

    2017-01-01

    In our study, we aimed to extract dysregulated pathways in human monocytes infected by Listeria monocytogenes (LM) based on pathway interaction network (PIN) which presented the functional dependency between pathways. After genes were aligned to the pathways, principal component analysis (PCA) was used to calculate the pathway activity for each pathway, followed by detecting seed pathway. A PIN was constructed based on gene expression profile, protein-protein interactions (PPIs), and cellular pathways. Identifying dysregulated pathways from the PIN was performed relying on seed pathway and classification accuracy. To evaluate whether the PIN method was feasible or not, we compared the introduced method with standard network centrality measures. The pathway of RNA polymerase II pretranscription events was selected as the seed pathway. Taking this seed pathway as start, one pathway set (9 dysregulated pathways) with AUC score of 1.00 was identified. Among the 5 hub pathways obtained using standard network centrality measures, 4 pathways were the common ones between the two methods. RNA polymerase II transcription and DNA replication owned a higher number of pathway genes and DEGs. These dysregulated pathways work together to influence the progression of LM infection, and they will be available as biomarkers to diagnose LM infection.

  5. The effect of long-range air mass transport pathways on PM10 and NO2 concentrations at urban and rural background sites in Ireland: Quantification using clustering techniques.

    PubMed

    Donnelly, Aoife A; Broderick, Brian M; Misstear, Bruce D

    2015-01-01

    The specific aims of this paper are to: (i) quantify the effects of various long range transport pathways nitrogen dioxide (NO2) and particulate matter with diameter less than 10μm (PM10) concentrations in Ireland and identify air mass movement corridors which may lead to incidences poor air quality for application in forecasting; (ii) compare the effects of such pathways at various sites; (iii) assess pathways associated with a period of decreased air quality in Ireland. The origin of and the regions traversed by an air mass 96h prior to reaching a receptor is modelled and k-means clustering is applied to create air-mass groups. Significant differences in air pollution levels were found between air mass cluster types at urban and rural sites. It was found that easterly or recirculated air masses lead to higher NO2 and PM10 levels with average NO2 levels varying between 124% and 239% of the seasonal mean and average PM10 levels varying between 103% and 199% of the seasonal mean at urban and rural sites. Easterly air masses are more frequent during winter months leading to higher overall concentrations. The span in relative concentrations between air mass clusters is highest at the rural site indicating that regional factors are controlling concentration levels. The methods used in this paper could be applied to assist in modelling and forecasting air quality based on long range transport pathways and forecast meteorology without the requirement for detailed emissions data over a large regional domain or the use of computationally demanding modelling techniques.

  6. Separate enrichment analysis of pathways for up- and downregulated genes.

    PubMed

    Hong, Guini; Zhang, Wenjing; Li, Hongdong; Shen, Xiaopei; Guo, Zheng

    2014-03-06

    Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.

  7. A strategy for evaluating pathway analysis methods.

    PubMed

    Yu, Chenggang; Woo, Hyung Jun; Yu, Xueping; Oyama, Tatsuya; Wallqvist, Anders; Reifman, Jaques

    2017-10-13

    Researchers have previously developed a multitude of methods designed to identify biological pathways associated with specific clinical or experimental conditions of interest, with the aim of facilitating biological interpretation of high-throughput data. Before practically applying such pathway analysis (PA) methods, we must first evaluate their performance and reliability, using datasets where the pathways perturbed by the conditions of interest have been well characterized in advance. However, such 'ground truths' (or gold standards) are often unavailable. Furthermore, previous evaluation strategies that have focused on defining 'true answers' are unable to systematically and objectively assess PA methods under a wide range of conditions. In this work, we propose a novel strategy for evaluating PA methods independently of any gold standard, either established or assumed. The strategy involves the use of two mutually complementary metrics, recall and discrimination. Recall measures the consistency of the perturbed pathways identified by applying a particular analysis method to an original large dataset and those identified by the same method to a sub-dataset of the original dataset. In contrast, discrimination measures specificity-the degree to which the perturbed pathways identified by a particular method to a dataset from one experiment differ from those identifying by the same method to a dataset from a different experiment. We used these metrics and 24 datasets to evaluate six widely used PA methods. The results highlighted the common challenge in reliably identifying significant pathways from small datasets. Importantly, we confirmed the effectiveness of our proposed dual-metric strategy by showing that previous comparative studies corroborate the performance evaluations of the six methods obtained by our strategy. Unlike any previously proposed strategy for evaluating the performance of PA methods, our dual-metric strategy does not rely on any ground truth

  8. Multi-membership gene regulation in pathway based microarray analysis

    PubMed Central

    2011-01-01

    Background Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. Results We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. Conclusions We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes. PMID:21939531

  9. Multi-membership gene regulation in pathway based microarray analysis.

    PubMed

    Pavlidis, Stelios P; Payne, Annette M; Swift, Stephen M

    2011-09-22

    Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes.

  10. minepath.org: a free interactive pathway analysis web server.

    PubMed

    Koumakis, Lefteris; Roussos, Panos; Potamias, George

    2017-07-03

    ( www.minepath.org ) is a web-based platform that elaborates on, and radically extends the identification of differentially expressed sub-paths in molecular pathways. Besides the network topology, the underlying MinePath algorithmic processes exploit exact gene-gene molecular relationships (e.g. activation, inhibition) and are able to identify differentially expressed pathway parts. Each pathway is decomposed into all its constituent sub-paths, which in turn are matched with corresponding gene expression profiles. The highly ranked, and phenotype inclined sub-paths are kept. Apart from the pathway analysis algorithm, the fundamental innovation of the MinePath web-server concerns its advanced visualization and interactive capabilities. To our knowledge, this is the first pathway analysis server that introduces and offers visualization of the underlying and active pathway regulatory mechanisms instead of genes. Other features include live interaction, immediate visualization of functional sub-paths per phenotype and dynamic linked annotations for the engaged genes and molecular relations. The user can download not only the results but also the corresponding web viewer framework of the performed analysis. This feature provides the flexibility to immediately publish results without publishing source/expression data, and get all the functionality of a web based pathway analysis viewer. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Pathway analysis of genome-wide association datasets of personality traits.

    PubMed

    Kim, H-N; Kim, B-H; Cho, J; Ryu, S; Shin, H; Sung, J; Shin, C; Cho, N H; Sung, Y A; Choi, B-O; Kim, H-L

    2015-04-01

    Although several genome-wide association (GWA) studies of human personality have been recently published, genetic variants that are highly associated with certain personality traits remain unknown, due to difficulty reproducing results. To further investigate these genetic variants, we assessed biological pathways using GWA datasets. Pathway analysis using GWA data was performed on 1089 Korean women whose personality traits were measured with the Revised NEO Personality Inventory for the 5-factor model of personality. A total of 1042 pathways containing 8297 genes were included in our study. Of these, 14 pathways were highly enriched with association signals that were validated in 1490 independent samples. These pathways include association of: Neuroticism with axon guidance [L1 cell adhesion molecule (L1CAM) interactions]; Extraversion with neuronal system and voltage-gated potassium channels; Agreeableness with L1CAM interaction, neurotransmitter receptor binding and downstream transmission in postsynaptic cells; and Conscientiousness with the interferon-gamma and platelet-derived growth factor receptor beta polypeptide pathways. Several genes that contribute to top-ranked pathways in this study were previously identified in GWA studies or by pathway analysis in schizophrenia or other neuropsychiatric disorders. Here we report the first pathway analysis of all five personality traits. Importantly, our analysis identified novel pathways that contribute to understanding the etiology of personality traits. © 2015 The Authors. Genes, Brain and Behavior published by International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd.

  12. ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis

    PubMed Central

    Han, Junwei; Shi, Xinrui; Zhang, Yunpeng; Xu, Yanjun; Jiang, Ying; Zhang, Chunlong; Feng, Li; Yang, Haixiu; Shang, Desi; Sun, Zeguo; Su, Fei; Li, Chunquan; Li, Xia

    2015-01-01

    Pathway analyses are playing an increasingly important role in understanding biological mechanism, cellular function and disease states. Current pathway-identification methods generally focus on only the changes of gene expression levels; however, the biological relationships among genes are also the fundamental components of pathways, and the dysregulated relationships may also alter the pathway activities. We propose a powerful computational method, Edge Set Enrichment Analysis (ESEA), for the identification of dysregulated pathways. This provides a novel way of pathway analysis by investigating the changes of biological relationships of pathways in the context of gene expression data. Simulation studies illustrate the power and performance of ESEA under various simulated conditions. Using real datasets from p53 mutation, Type 2 diabetes and lung cancer, we validate effectiveness of ESEA in identifying dysregulated pathways. We further compare our results with five other pathway enrichment analysis methods. With these analyses, we show that ESEA is able to help uncover dysregulated biological pathways underlying complex traits and human diseases via specific use of the dysregulated biological relationships. We develop a freely available R-based tool of ESEA. Currently, ESEA can support pathway analysis of the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther). PMID:26267116

  13. PathwaySplice: An R package for unbiased pathway analysis of alternative splicing in RNA-Seq data.

    PubMed

    Yan, Aimin; Ban, Yuguang; Gao, Zhen; Chen, Xi; Wang, Lily

    2018-04-24

    Pathway analysis of alternative splicing would be biased without accounting for the different number of exons or junctions associated with each gene, because genes with higher number of exons or junctions are more likely to be included in the "significant" gene list in alternative splicing. We present PathwaySplice, an R package that (1) Performs pathway analysis that explicitly adjusts for the number of exons or junctions associated with each gene; (2) Visualizes selection bias due to different number of exons or junctions for each gene and formally tests for presence of bias using logistic regression; (3) Supports gene sets based on the Gene Ontology terms, as well as more broadly defined gene sets (e.g. MSigDB) or user defined gene sets; (4) Identifies the significant genes driving pathway significance and (5) Organizes significant pathways with an enrichment map, where pathways with large number of overlapping genes are grouped together in a network graph. https://bioconductor.org/packages/release/bioc/html/PathwaySplice.html. lily.wangg@gmail.com, xi.steven.chen@gmail.com.

  14. Pathway Analysis and Omics Data Visualization Using Pathway Genome Databases: FragariaCyc, a Case Study.

    PubMed

    Naithani, Sushma; Jaiswal, Pankaj

    2017-01-01

    The species-specific plant Pathway Genome Databases (PGDBs) based on the BioCyc platform provide a conceptual model of the cellular metabolic network of an organism. Such frameworks allow analysis of the genome-scale expression data to understand changes in the overall metabolisms of an organism (or organs, tissues, and cells) in response to various extrinsic (e.g. developmental and differentiation) and/or extrinsic signals (e.g. pathogens and abiotic stresses) from the surrounding environment. Using FragariaCyc, a pathway database for the diploid strawberry Fragaria vesca, we show (1) the basic navigation across a PGDB; (2) a case study of pathway comparison across plant species; and (3) an example of RNA-Seq data analysis using Omics Viewer tool. The protocols described here generally apply to other Pathway Tools-based PGDBs.

  15. Systematic analysis of signaling pathways using an integrative environment.

    PubMed

    Visvanathan, Mahesh; Breit, Marc; Pfeifer, Bernhard; Baumgartner, Christian; Modre-Osprian, Robert; Tilg, Bernhard

    2007-01-01

    Understanding the biological processes of signaling pathways as a whole system requires an integrative software environment that has comprehensive capabilities. The environment should include tools for pathway design, visualization, simulation and a knowledge base concerning signaling pathways as one. In this paper we introduce a new integrative environment for the systematic analysis of signaling pathways. This system includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning signaling pathways that provides the basic understanding of the biological system, its structure and functioning. The system is designed with a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer. The TNFa-mediated NF-kB signal trans-duction pathway model was designed and tested using our integrative framework. It was also useful to define the structure of the knowledge base. Sensitivity analysis of this specific pathway was performed providing simulation data. Then the model was extended showing promising initial results. The proposed system offers a holistic view of pathways containing biological and modeling data. It will help us to perform biological interpretation of the simulation results and thus contribute to a better understanding of the biological system for drug identification.

  16. RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites

    PubMed Central

    Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K.

    2018-01-01

    The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be

  17. RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites.

    PubMed

    Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A

    2018-02-22

    The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be

  18. TabPath: interactive tables for metabolic pathway analysis.

    PubMed

    Moraes, Lauro Ângelo Gonçalves de; Felestrino, Érica Barbosa; Assis, Renata de Almeida Barbosa; Matos, Diogo; Lima, Joubert de Castro; Lima, Leandro de Araújo; Almeida, Nalvo Franco; Setubal, João Carlos; Garcia, Camila Carrião Machado; Moreira, Leandro Marcio

    2018-03-15

    Information about metabolic pathways in a comparative context is one of the most powerful tool to help the understanding of genome-based differences in phenotypes among organisms. Although several platforms exist that provide a wealth of information on metabolic pathways of diverse organisms, the comparison among organisms using metabolic pathways is still a difficult task. We present TabPath (Tables for Metabolic Pathway), a web-based tool to facilitate comparison of metabolic pathways in genomes based on KEGG. From a selection of pathways and genomes of interest on the menu, TabPath generates user-friendly tables that facilitate analysis of variations in metabolism among the selected organisms. TabPath is available at http://200.239.132.160:8686. lmmorei@gmail.com.

  19. Thinking outside of the lungs: systemic stress response as a pathway and modifier of air pollution health effects

    EPA Science Inventory

    This poster will describe the effects of non-chemical stressors (e.g. noise) on the physiological response to air pollution, as well as the role of systemic stress pathways in the mediating the adverse health effects. The findings presented here are important because they elucida...

  20. Mediation pathways and effects of green structures on respiratory mortality via reducing air pollution

    NASA Astrophysics Data System (ADS)

    Shen, Yu-Sheng; Lung, Shih-Chun Candice

    2017-02-01

    Previous studies have shown both health and environmental benefits of green spaces, especially in moderating temperature and reducing air pollution. However, the characteristics of green structures have been overlooked in previous investigations. In addition, the mediation effects of green structures on respiratory mortality have not been assessed. This study explores the potential mediation pathways and effects of green structure characteristics on respiratory mortality through temperature, primary and secondary air pollutants separately using partial least squares model with data from Taiwan. The measurable characteristics of green structure include the largest patch percentage, landscape proportion, aggregation, patch distance, and fragmentation. The results showed that mortality of pneumonia and chronic lower respiratory diseases could be reduced by minimizing fragmentation and increasing the largest patch percentage of green structure, and the mediation effects are mostly through reducing air pollutants rather than temperature. Moreover, a high proportion of but fragmented green spaces would increase secondary air pollutants and enhance health risks; demonstrating the deficiency of traditional greening policy with primary focus on coverage ratio. This is the first research focusing on mediation effects of green structure characteristics on respiratory mortality, revealing that appropriate green structure planning can be a useful complementary strategy in environmental health management.

  1. Mediation pathways and effects of green structures on respiratory mortality via reducing air pollution.

    PubMed

    Shen, Yu-Sheng; Lung, Shih-Chun Candice

    2017-02-23

    Previous studies have shown both health and environmental benefits of green spaces, especially in moderating temperature and reducing air pollution. However, the characteristics of green structures have been overlooked in previous investigations. In addition, the mediation effects of green structures on respiratory mortality have not been assessed. This study explores the potential mediation pathways and effects of green structure characteristics on respiratory mortality through temperature, primary and secondary air pollutants separately using partial least squares model with data from Taiwan. The measurable characteristics of green structure include the largest patch percentage, landscape proportion, aggregation, patch distance, and fragmentation. The results showed that mortality of pneumonia and chronic lower respiratory diseases could be reduced by minimizing fragmentation and increasing the largest patch percentage of green structure, and the mediation effects are mostly through reducing air pollutants rather than temperature. Moreover, a high proportion of but fragmented green spaces would increase secondary air pollutants and enhance health risks; demonstrating the deficiency of traditional greening policy with primary focus on coverage ratio. This is the first research focusing on mediation effects of green structure characteristics on respiratory mortality, revealing that appropriate green structure planning can be a useful complementary strategy in environmental health management.

  2. Systemic Analysis Approaches for Air Transportation

    NASA Technical Reports Server (NTRS)

    Conway, Sheila

    2005-01-01

    Air transportation system designers have had only limited success using traditional operations research and parametric modeling approaches in their analyses of innovations. They need a systemic methodology for modeling of safety-critical infrastructure that is comprehensive, objective, and sufficiently concrete, yet simple enough to be used with reasonable investment. The methodology must also be amenable to quantitative analysis so issues of system safety and stability can be rigorously addressed. However, air transportation has proven itself an extensive, complex system whose behavior is difficult to describe, no less predict. There is a wide range of system analysis techniques available, but some are more appropriate for certain applications than others. Specifically in the area of complex system analysis, the literature suggests that both agent-based models and network analysis techniques may be useful. This paper discusses the theoretical basis for each approach in these applications, and explores their historic and potential further use for air transportation analysis.

  3. Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways

    PubMed Central

    Kaushik, Abhinav; Ali, Shakir; Gupta, Dinesh

    2017-01-01

    Gene connection rewiring is an essential feature of gene network dynamics. Apart from its normal functional role, it may also lead to dysregulated functional states by disturbing pathway homeostasis. Very few computational tools measure rewiring within gene co-expression and its corresponding regulatory networks in order to identify and prioritize altered pathways which may or may not be differentially regulated. We have developed Altered Pathway Analyzer (APA), a microarray dataset analysis tool for identification and prioritization of altered pathways, including those which are differentially regulated by TFs, by quantifying rewired sub-network topology. Moreover, APA also helps in re-prioritization of APA shortlisted altered pathways enriched with context-specific genes. We performed APA analysis of simulated datasets and p53 status NCI-60 cell line microarray data to demonstrate potential of APA for identification of several case-specific altered pathways. APA analysis reveals several altered pathways not detected by other tools evaluated by us. APA analysis of unrelated prostate cancer datasets identifies sample-specific as well as conserved altered biological processes, mainly associated with lipid metabolism, cellular differentiation and proliferation. APA is designed as a cross platform tool which may be transparently customized to perform pathway analysis in different gene expression datasets. APA is freely available at http://bioinfo.icgeb.res.in/APA. PMID:28084397

  4. PyPathway: Python Package for Biological Network Analysis and Visualization.

    PubMed

    Xu, Yang; Luo, Xiao-Chun

    2018-05-01

    Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.

  5. Investigating ego modules and pathways in osteosarcoma by integrating the EgoNet algorithm and pathway analysis.

    PubMed

    Chen, X Y; Chen, Y H; Zhang, L J; Wang, Y; Tong, Z C

    2017-02-16

    Osteosarcoma (OS) is the most common primary bone malignancy, but current therapies are far from effective for all patients. A better understanding of the pathological mechanism of OS may help to achieve new treatments for this tumor. Hence, the objective of this study was to investigate ego modules and pathways in OS utilizing EgoNet algorithm and pathway-related analysis, and reveal pathological mechanisms underlying OS. The EgoNet algorithm comprises four steps: constructing background protein-protein interaction (PPI) network (PPIN) based on gene expression data and PPI data; extracting differential expression network (DEN) from the background PPIN; identifying ego genes according to topological features of genes in reweighted DEN; and collecting ego modules using module search by ego gene expansion. Consequently, we obtained 5 ego modules (Modules 2, 3, 4, 5, and 6) in total. After applying the permutation test, all presented statistical significance between OS and normal controls. Finally, pathway enrichment analysis combined with Reactome pathway database was performed to investigate pathways, and Fisher's exact test was conducted to capture ego pathways for OS. The ego pathway for Module 2 was CLEC7A/inflammasome pathway, while for Module 3 a tetrasaccharide linker sequence was required for glycosaminoglycan (GAG) synthesis, and for Module 6 was the Rho GTPase cycle. Interestingly, genes in Modules 4 and 5 were enriched in the same pathway, the 2-LTR circle formation. In conclusion, the ego modules and pathways might be potential biomarkers for OS therapeutic index, and give great insight of the molecular mechanism underlying this tumor.

  6. Investigating ego modules and pathways in osteosarcoma by integrating the EgoNet algorithm and pathway analysis

    PubMed Central

    Chen, X.Y.; Chen, Y.H.; Zhang, L.J.; Wang, Y.; Tong, Z.C.

    2017-01-01

    Osteosarcoma (OS) is the most common primary bone malignancy, but current therapies are far from effective for all patients. A better understanding of the pathological mechanism of OS may help to achieve new treatments for this tumor. Hence, the objective of this study was to investigate ego modules and pathways in OS utilizing EgoNet algorithm and pathway-related analysis, and reveal pathological mechanisms underlying OS. The EgoNet algorithm comprises four steps: constructing background protein-protein interaction (PPI) network (PPIN) based on gene expression data and PPI data; extracting differential expression network (DEN) from the background PPIN; identifying ego genes according to topological features of genes in reweighted DEN; and collecting ego modules using module search by ego gene expansion. Consequently, we obtained 5 ego modules (Modules 2, 3, 4, 5, and 6) in total. After applying the permutation test, all presented statistical significance between OS and normal controls. Finally, pathway enrichment analysis combined with Reactome pathway database was performed to investigate pathways, and Fisher's exact test was conducted to capture ego pathways for OS. The ego pathway for Module 2 was CLEC7A/inflammasome pathway, while for Module 3 a tetrasaccharide linker sequence was required for glycosaminoglycan (GAG) synthesis, and for Module 6 was the Rho GTPase cycle. Interestingly, genes in Modules 4 and 5 were enriched in the same pathway, the 2-LTR circle formation. In conclusion, the ego modules and pathways might be potential biomarkers for OS therapeutic index, and give great insight of the molecular mechanism underlying this tumor. PMID:28225867

  7. A System-Level Pathway-Phenotype Association Analysis Using Synthetic Feature Random Forest

    PubMed Central

    Pan, Qinxin; Hu, Ting; Malley, James D.; Andrew, Angeline S.; Karagas, Margaret R.; Moore, Jason H.

    2015-01-01

    As the cost of genome-wide genotyping decreases, the number of genome-wide association studies (GWAS) has increased considerably. However, the transition from GWAS findings to the underlying biology of various phenotypes remains challenging. As a result, due to its system-level interpretability, pathway analysis has become a popular tool for gaining insights on the underlying biology from high-throughput genetic association data. In pathway analyses, gene sets representing particular biological processes are tested for significant associations with a given phenotype. Most existing pathway analysis approaches rely on single-marker statistics and assume that pathways are independent of each other. As biological systems are driven by complex biomolecular interactions, embracing the complex relationships between single-nucleotide polymorphisms (SNPs) and pathways needs to be addressed. To incorporate the complexity of gene-gene interactions and pathway-pathway relationships, we propose a system-level pathway analysis approach, synthetic feature random forest (SF-RF), which is designed to detect pathway-phenotype associations without making assumptions about the relationships among SNPs or pathways. In our approach, the genotypes of SNPs in a particular pathway are aggregated into a synthetic feature representing that pathway via Random Forest (RF). Multiple synthetic features are analyzed using RF simultaneously and the significance of a synthetic feature indicates the significance of the corresponding pathway. We further complement SF-RF with pathway-based Statistical Epistasis Network (SEN) analysis that evaluates interactions among pathways. By investigating the pathway SEN, we hope to gain additional insights into the genetic mechanisms contributing to the pathway-phenotype association. We apply SF-RF to a population-based genetic study of bladder cancer and further investigate the mechanisms that help explain the pathway-phenotype associations using SEN. The

  8. Catalytic wet air oxidation of phenol with functionalized carbon materials as catalysts: reaction mechanism and pathway.

    PubMed

    Wang, Jianbing; Fu, Wantao; He, Xuwen; Yang, Shaoxia; Zhu, Wanpeng

    2014-08-01

    The development of highly active carbon material catalysts in catalytic wet air oxidation (CWAO) has attracted a great deal of attention. In this study different carbon material catalysts (multi-walled carbon nanotubes, carbon fibers and graphite) were developed to enhance the CWAO of phenol in aqueous solution. The functionalized carbon materials exhibited excellent catalytic activity in the CWAO of phenol. After 60 min reaction, the removal of phenol was nearly 100% over the functionalized multi-walled carbon, while it was only 14% over the purified multi-walled carbon under the same reaction conditions. Carboxylic acid groups introduced on the surface of the functionalized carbon materials play an important role in the catalytic activity in CWAO. They can promote the production of free radicals, which act as strong oxidants in CWAO. Based on the analysis of the intermediates produced in the CWAO reactions, a new reaction pathway for the CWAO of phenol was proposed in this study. There are some differences between the proposed reaction pathway and that reported in the literature. First, maleic acid is transformed directly into malonic acid. Second, acetic acid is oxidized into an unknown intermediate, which is then oxidized into CO2 and H2O. Finally, formic acid and oxalic acid can mutually interconvert when conditions are favorable. Copyright © 2014. Published by Elsevier B.V.

  9. Conceptual model for assessing criteria air pollutants in a multipollutant context: A modified adverse outcome pathway approach.

    PubMed

    Buckley, Barbara; Farraj, Aimen

    2015-09-01

    Air pollution consists of a complex mixture of particulate and gaseous components. Individual criteria and other hazardous air pollutants have been linked to adverse respiratory and cardiovascular health outcomes. However, assessing risk of air pollutant mixtures is difficult since components are present in different combinations and concentrations in ambient air. Recent mechanistic studies have limited utility because of the inability to link measured changes to adverse outcomes that are relevant to risk assessment. New approaches are needed to address this challenge. The purpose of this manuscript is to describe a conceptual model, based on the adverse outcome pathway approach, which connects initiating events at the cellular and molecular level to population-wide impacts. This may facilitate hazard assessment of air pollution mixtures. In the case reports presented here, airway hyperresponsiveness and endothelial dysfunction are measurable endpoints that serve to integrate the effects of individual criteria air pollutants found in inhaled mixtures. This approach incorporates information from experimental and observational studies into a sequential series of higher order effects. The proposed model has the potential to facilitate multipollutant risk assessment by providing a framework that can be used to converge the effects of air pollutants in light of common underlying mechanisms. This approach may provide a ready-to-use tool to facilitate evaluation of health effects resulting from exposure to air pollution mixtures. Published by Elsevier Ireland Ltd.

  10. Pathway Analysis in Attention Deficit Hyperactivity Disorder: An Ensemble Approach

    PubMed Central

    Mooney, Michael A.; McWeeney, Shannon K.; Faraone, Stephen V.; Hinney, Anke; Hebebrand, Johannes; Nigg, Joel T.; Wilmot, Beth

    2016-01-01

    Despite a wealth of evidence for the role of genetics in attention deficit hyperactivity disorder (ADHD), specific and definitive genetic mechanisms have not been identified. Pathway analyses, a subset of gene-set analyses, extend the knowledge gained from genome-wide association studies (GWAS) by providing functional context for genetic associations. However, there are numerous methods for association testing of gene sets and no real consensus regarding the best approach. The present study applied six pathway analysis methods to identify pathways associated with ADHD in two GWAS datasets from the Psychiatric Genomics Consortium. Methods that utilize genotypes to model pathway-level effects identified more replicable pathway associations than methods using summary statistics. In addition, pathways implicated by more than one method were significantly more likely to replicate. A number of brain-relevant pathways, such as RhoA signaling, glycosaminoglycan biosynthesis, fibroblast growth factor receptor activity, and pathways containing potassium channel genes, were nominally significant by multiple methods in both datasets. These results support previous hypotheses about the role of regulation of neurotransmitter release, neurite outgrowth and axon guidance in contributing to the ADHD phenotype and suggest the value of cross-method convergence in evaluating pathway analysis results. PMID:27004716

  11. Air-to-air combat analysis - Review of differential-gaming approaches

    NASA Technical Reports Server (NTRS)

    Ardema, M. D.

    1981-01-01

    The problem of evaluating the combat performance of fighter/attack aircraft is discussed, and the mathematical nature of the problem is examined. The following approaches to air combat analysis are reviewed: (1) differential-turning differential game and (2) coplanar differential game. Selected numerical examples of these approaches are presented. The relative advantages and disadvantages of each are analyzed, and it is concluded that air combat analysis is an extremely difficult mathematical problem and that no one method of approach is best for all purposes. The paper concludes with a discussion of how the two approaches might be used in a complementary manner.

  12. A Combined Pathway and Regional Heritability Analysis Indicates NETRIN1 Pathway Is Associated With Major Depressive Disorder.

    PubMed

    Zeng, Yanni; Navarro, Pau; Fernandez-Pujals, Ana M; Hall, Lynsey S; Clarke, Toni-Kim; Thomson, Pippa A; Smith, Blair H; Hocking, Lynne J; Padmanabhan, Sandosh; Hayward, Caroline; MacIntyre, Donald J; Wray, Naomi R; Deary, Ian J; Porteous, David J; Haley, Chris S; McIntosh, Andrew M

    2017-02-15

    Genome-wide association studies (GWASs) of major depressive disorder (MDD) have identified few significant associations. Testing the aggregation of genetic variants, in particular biological pathways, may be more powerful. Regional heritability analysis can be used to detect genomic regions that contribute to disease risk. We integrated pathway analysis and multilevel regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS samples [Generation Scotland: The Scottish Family Health Study (GS:SFHS, N = 6455) and Psychiatric Genomics Consortium (PGC:MDD) (N = 18,759)]. A polygenic risk score (PRS) composed of single nucleotide polymorphisms from the pathway most consistently associated with MDD was created, and its accuracy to predict MDD, using area under the curve, logistic regression, and linear mixed model analyses, was tested. In GS:SFHS, four pathways were significantly associated with MDD, and two of these explained a significant amount of pathway-level regional heritability. In PGC:MDD, one pathway was significantly associated with MDD. Pathway-level regional heritability was significant in this pathway in one subset of PGC:MDD. For both samples the regional heritabilities were further localized to the gene and subregion levels. The NETRIN1 signaling pathway showed the most consistent association with MDD across the two samples. PRSs from this pathway showed competitive predictive accuracy compared with the whole-genome PRSs when using area under the curve statistics, logistic regression, and linear mixed model. These post-GWAS analyses highlight the value of combining multiple methods on multiple GWAS data for the identification of risk pathways for MDD. The NETRIN1 signaling pathway is identified as a candidate pathway for MDD and should be explored in further large population studies. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights

  13. Dysregulated Pathway Identification of Alzheimer's Disease Based on Internal Correlation Analysis of Genes and Pathways.

    PubMed

    Kong, Wei; Mou, Xiaoyang; Di, Benteng; Deng, Jin; Zhong, Ruxing; Wang, Shuaiqun

    2017-11-20

    Dysregulated pathway identification is an important task which can gain insight into the underlying biological processes of disease. Current pathway-identification methods focus on a set of co-expression genes and single pathways and ignore the correlation between genes and pathways. The method proposed in this study, takes into account the internal correlations not only between genes but also pathways to identifying dysregulated pathways related to Alzheimer's disease (AD), the most common form of dementia. In order to find the significantly differential genes for AD, mutual information (MI) is used to measure interdependencies between genes other than expression valves. Then, by integrating the topology information from KEGG, the significant pathways involved in the feature genes are identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks since DC has the advantage of detecting nonlinear correlations when compared to Pearson correlation. Finally, the pathway pairs with significantly different correlations between normal and AD samples are known as dysregulated pathways. The molecular biology analysis demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered successfully by the internal correlation detection. Furthermore, the insights of the dysregulated pathways in the development and deterioration of AD will help to find new effective target genes and provide important theoretical guidance for drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  14. Seeking unique and common biological themes in multiple gene lists or datasets: pathway pattern extraction pipeline for pathway-level comparative analysis.

    PubMed

    Yi, Ming; Mudunuri, Uma; Che, Anney; Stephens, Robert M

    2009-06-29

    One of the challenges in the analysis of microarray data is to integrate and compare the selected (e.g., differential) gene lists from multiple experiments for common or unique underlying biological themes. A common way to approach this problem is to extract common genes from these gene lists and then subject these genes to enrichment analysis to reveal the underlying biology. However, the capacity of this approach is largely restricted by the limited number of common genes shared by datasets from multiple experiments, which could be caused by the complexity of the biological system itself. We now introduce a new Pathway Pattern Extraction Pipeline (PPEP), which extends the existing WPS application by providing a new pathway-level comparative analysis scheme. To facilitate comparing and correlating results from different studies and sources, PPEP contains new interfaces that allow evaluation of the pathway-level enrichment patterns across multiple gene lists. As an exploratory tool, this analysis pipeline may help reveal the underlying biological themes at both the pathway and gene levels. The analysis scheme provided by PPEP begins with multiple gene lists, which may be derived from different studies in terms of the biological contexts, applied technologies, or methodologies. These lists are then subjected to pathway-level comparative analysis for extraction of pathway-level patterns. This analysis pipeline helps to explore the commonality or uniqueness of these lists at the level of pathways or biological processes from different but relevant biological systems using a combination of statistical enrichment measurements, pathway-level pattern extraction, and graphical display of the relationships of genes and their associated pathways as Gene-Term Association Networks (GTANs) within the WPS platform. As a proof of concept, we have used the new method to analyze many datasets from our collaborators as well as some public microarray datasets. This tool provides a

  15. A rapid response air quality analysis system for use in projects having stringent quality assurance requirements

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bowman, A.W.

    1990-04-01

    This paper describes an approach to solve air quality problems which frequently occur during iterations of the baseline change process. From a schedule standpoint, it is desirable to perform this evaluation in as short a time as possible while budgetary pressures limit the size of the staff available to do the work. Without a method in place to deal with baseline change proposal requests the environment analysts may not be able to produce the analysis results in the time frame expected. Using a concept called the Rapid Response Air Quality Analysis System (RAAS), the problems of timing and cost becomemore » tractable. The system could be adapted to assess other atmospheric pathway impacts, e.g., acoustics or visibility. The air quality analysis system used to perform the EA analysis (EA) for the Salt Repository Project (part of the Civilian Radioactive Waste Management Program), and later to evaluate the consequences of proposed baseline changes, consists of three components: Emission source data files; Emission rates contained in spreadsheets; Impact assessment model codes. The spreadsheets contain user-written codes (macros) that calculate emission rates from (1) emission source data (e.g., numbers and locations of sources, detailed operating schedules, and source specifications including horsepower, load factor, and duty cycle); (2) emission factors such as those published by the U.S. Environmental Protection Agency, and (3) control efficiencies.« less

  16. Distribution pathways of hexachlorocyclohexane isomers in a soil-plant-air system. A case study with Cynara scolymus L. and Erica sp. plants grown in a contaminated site.

    PubMed

    Pereira, R Calvelo; Monterroso, C; Macías, F; Camps-Arbestain, M

    2008-09-01

    This study focuses on the main routes of distribution and accumulation of different hexachlorocyclohexane (HCH) isomers (mainly alpha-, beta-, gamma- and delta-HCH) in a soil-plant-air system. A field assay was carried out with two plant species, Cynara scolymus L. and Erica sp., which were planted either: (i) directly in the HCH-contaminated soil; or (ii) in pots filled with uncontaminated soil, which were placed in the HCH-contaminated soil. Both plant species accumulated HCH in their tissues, with relatively higher accumulation in above-ground biomass than in roots. The beta-HCH isomer was the main isomer in all plant tissues. Adsorption of HCH by the roots from contaminated soil (soil-->root pathway) and adsorption through the aerial biomass from either the surrounding air, following volatilization of the contaminant (soil-->air-->shoot pathway), and/or contact with air-suspended particles contaminated with HCH (soil particles-->shoot pathway) were the main mechanisms of accumulation. These results may have important implications for the use of plants for reducing the transfer of contaminants via the atmosphere.

  17. Plant Reactome: a resource for plant pathways and comparative analysis

    PubMed Central

    Naithani, Sushma; Preece, Justin; D'Eustachio, Peter; Gupta, Parul; Amarasinghe, Vindhya; Dharmawardhana, Palitha D.; Wu, Guanming; Fabregat, Antonio; Elser, Justin L.; Weiser, Joel; Keays, Maria; Fuentes, Alfonso Munoz-Pomer; Petryszak, Robert; Stein, Lincoln D.; Ware, Doreen; Jaiswal, Pankaj

    2017-01-01

    Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX. PMID:27799469

  18. Pathway analysis of high-throughput biological data within a Bayesian network framework.

    PubMed

    Isci, Senol; Ozturk, Cengizhan; Jones, Jon; Otu, Hasan H

    2011-06-15

    Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Proposed method takes into account the connectivity and relatedness between nodes of the pathway through factoring pathway topology in its model. Our simulations using synthetic data demonstrated robustness of our approach. We tested proposed method, Bayesian Pathway Analysis (BPA), on human microarray data regarding renal cell carcinoma (RCC) and compared our results with gene set enrichment analysis. BPA was able to find broader and more specific pathways related to RCC. Accompanying BPA software (BPAS) package is freely available for academic use at http://bumil.boun.edu.tr/bpa.

  19. Visual Analysis of Air Traffic Data

    NASA Technical Reports Server (NTRS)

    Albrecht, George Hans; Pang, Alex

    2012-01-01

    In this paper, we present visual analysis tools to help study the impact of policy changes on air traffic congestion. The tools support visualization of time-varying air traffic density over an area of interest using different time granularity. We use this visual analysis platform to investigate how changing the aircraft separation volume can reduce congestion while maintaining key safety requirements. The same platform can also be used as a decision aid for processing requests for unmanned aerial vehicle operations.

  20. A systematic analysis of a mi-RNA inter-pathway regulatory motif

    PubMed Central

    2013-01-01

    Background The continuing discovery of new types and functions of small non-coding RNAs is suggesting the presence of regulatory mechanisms far more complex than the ones currently used to study and design Gene Regulatory Networks. Just focusing on the roles of micro RNAs (miRNAs), they have been found to be part of several intra-pathway regulatory motifs. However, inter-pathway regulatory mechanisms have been often neglected and require further investigation. Results In this paper we present the result of a systems biology study aimed at analyzing a high-level inter-pathway regulatory motif called Pathway Protection Loop, not previously described, in which miRNAs seem to play a crucial role in the successful behavior and activation of a pathway. Through the automatic analysis of a large set of public available databases, we found statistical evidence that this inter-pathway regulatory motif is very common in several classes of KEGG Homo Sapiens pathways and concurs in creating a complex regulatory network involving several pathways connected by this specific motif. The role of this motif seems also confirmed by a deeper review of other research activities on selected representative pathways. Conclusions Although previous studies suggested transcriptional regulation mechanism at the pathway level such as the Pathway Protection Loop, a high-level analysis like the one proposed in this paper is still missing. The understanding of higher-level regulatory motifs could, as instance, lead to new approaches in the identification of therapeutic targets because it could unveil new and “indirect” paths to activate or silence a target pathway. However, a lot of work still needs to be done to better uncover this high-level inter-pathway regulation including enlarging the analysis to other small non-coding RNA molecules. PMID:24152805

  1. Automated retinofugal visual pathway reconstruction with multi-shell HARDI and FOD-based analysis.

    PubMed

    Kammen, Alexandra; Law, Meng; Tjan, Bosco S; Toga, Arthur W; Shi, Yonggang

    2016-01-15

    Diffusion MRI tractography provides a non-invasive modality to examine the human retinofugal projection, which consists of the optic nerves, optic chiasm, optic tracts, the lateral geniculate nuclei (LGN) and the optic radiations. However, the pathway has several anatomic features that make it particularly challenging to study with tractography, including its location near blood vessels and bone-air interface at the base of the cerebrum, crossing fibers at the chiasm, somewhat-tortuous course around the temporal horn via Meyer's Loop, and multiple closely neighboring fiber bundles. To date, these unique complexities of the visual pathway have impeded the development of a robust and automated reconstruction method using tractography. To overcome these challenges, we develop a novel, fully automated system to reconstruct the retinofugal visual pathway from high-resolution diffusion imaging data. Using multi-shell, high angular resolution diffusion imaging (HARDI) data, we reconstruct precise fiber orientation distributions (FODs) with high order spherical harmonics (SPHARM) to resolve fiber crossings, which allows the tractography algorithm to successfully navigate the complicated anatomy surrounding the retinofugal pathway. We also develop automated algorithms for the identification of ROIs used for fiber bundle reconstruction. In particular, we develop a novel approach to extract the LGN region of interest (ROI) based on intrinsic shape analysis of a fiber bundle computed from a seed region at the optic chiasm to a target at the primary visual cortex. By combining automatically identified ROIs and FOD-based tractography, we obtain a fully automated system to compute the main components of the retinofugal pathway, including the optic tract and the optic radiation. We apply our method to the multi-shell HARDI data of 215 subjects from the Human Connectome Project (HCP). Through comparisons with post-mortem dissection measurements, we demonstrate the retinotopic

  2. Identifying novel glioma associated pathways based on systems biology level meta-analysis.

    PubMed

    Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

    2013-01-01

    With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

  3. Plant Reactome: a resource for plant pathways and comparative analysis.

    PubMed

    Naithani, Sushma; Preece, Justin; D'Eustachio, Peter; Gupta, Parul; Amarasinghe, Vindhya; Dharmawardhana, Palitha D; Wu, Guanming; Fabregat, Antonio; Elser, Justin L; Weiser, Joel; Keays, Maria; Fuentes, Alfonso Munoz-Pomer; Petryszak, Robert; Stein, Lincoln D; Ware, Doreen; Jaiswal, Pankaj

    2017-01-04

    Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  4. Methods and approaches in the topology-based analysis of biological pathways

    PubMed Central

    Mitrea, Cristina; Taghavi, Zeinab; Bokanizad, Behzad; Hanoudi, Samer; Tagett, Rebecca; Donato, Michele; Voichiţa, Călin; Drăghici, Sorin

    2013-01-01

    The goal of pathway analysis is to identify the pathways significantly impacted in a given phenotype. Many current methods are based on algorithms that consider pathways as simple gene lists, dramatically under-utilizing the knowledge that such pathways are meant to capture. During the past few years, a plethora of methods claiming to incorporate various aspects of the pathway topology have been proposed. These topology-based methods, sometimes referred to as “third generation,” have the potential to better model the phenomena described by pathways. Although there is now a large variety of approaches used for this purpose, no review is currently available to offer guidance for potential users and developers. This review covers 22 such topology-based pathway analysis methods published in the last decade. We compare these methods based on: type of pathways analyzed (e.g., signaling or metabolic), input (subset of genes, all genes, fold changes, gene p-values, etc.), mathematical models, pathway scoring approaches, output (one or more pathway scores, p-values, etc.) and implementation (web-based, standalone, etc.). We identify and discuss challenges, arising both in methodology and in pathway representation, including inconsistent terminology, different data formats, lack of meaningful benchmarks, and the lack of tissue and condition specificity. PMID:24133454

  5. Analysis of Air Force Secondary Power Logistics Solution Contract

    DTIC Science & Technology

    2010-05-21

    IL 62225 SUBJECT: Audit. Analysis of Air Force Secondary Power Logistics Solution Contract, 748th Supply Chain Management Group, Hill Air Fon:r... Power Logis.tics Solution Contnict. 748111 Supply Ch.,in Management Group. !-lill Air FOfC! BII.SI!, UT (Project 02009· DOOOCH·0213.000) I. AUlIctlcd...00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Analysis of Air Force Secondary Power Logistics Solution Contract 5a. CONTRACT NUMBER 5b. GRANT

  6. AIR Model Preflight Analysis

    NASA Technical Reports Server (NTRS)

    Tai, H.; Wilson, J. W.; Maiden, D. L.

    2003-01-01

    The atmospheric ionizing radiation (AIR) ER-2 preflight analysis, one of the first attempts to obtain a relatively complete measurement set of the high-altitude radiation level environment, is described in this paper. The primary thrust is to characterize the atmospheric radiation and to define dose levels at high-altitude flight. A secondary thrust is to develop and validate dosimetric techniques and monitoring devices for protecting aircrews. With a few chosen routes, we can measure the experimental results and validate the AIR model predictions. Eventually, as more measurements are made, we gain more understanding about the hazardous radiation environment and acquire more confidence in the prediction models.

  7. Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

    PubMed

    Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

    2014-01-01

    A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

  8. Implications of alternative assumptions regarding future air pollution control in scenarios similar to the Representative Concentration Pathways

    NASA Astrophysics Data System (ADS)

    Chuwah, Clifford; van Noije, Twan; van Vuuren, Detlef P.; Hazeleger, Wilco; Strunk, Achim; Deetman, Sebastiaan; Beltran, Angelica Mendoza; van Vliet, Jasper

    2013-11-01

    The uncertain, future development of emissions of short-lived trace gases and aerosols forms a key factor for future air quality and climate forcing. The Representative Concentration Pathways (RCPs) only explore part of this range as they all assume that worldwide ambitious air pollution control policies will be implemented. In this study, we explore how different assumptions on future air pollution policy and climate policy lead to different concentrations of air pollutants for a set of RCP-like scenarios developed using the IMAGE model. These scenarios combine low and high air pollution variants of the scenarios with radiative forcing targets in 2100 of 2.6 W m-2 and 6.0 W m-2. Simulations using the global atmospheric chemistry and transport model TM5 for the present-day climate show that both climate mitigation and air pollution control policies have large-scale effects on pollutant concentrations, often of similar magnitude. If no further air pollution policies would be implemented, pollution levels could be considerably higher than in the RCPs, especially in Asia. Air pollution control measures could significantly reduce the warming by tropospheric ozone and black carbon and the cooling by sulphate by 2020, and in the longer term contribute to enhanced warming by methane. These effects tend to cancel each other on a global scale. According to our estimates the effect of the worldwide implementation of air pollution control measures on the total global mean direct radiative forcing in 2050 is +0.09 W m-2 in the 6.0 W m-2 scenario and -0.16 W m-2 in the 2.6 W m-2 scenario.

  9. Survival Analysis of US Air Force Officer Retention Rate

    DTIC Science & Technology

    2017-03-23

    Air Force Institute of Technology AFIT Scholar Theses and Dissertations 3-23-2017 Survival Analysis of US Air Force Officer Retention Rate Courtney N...AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio DISTRIBUTION STATEMENT A. APPROVED FOR PUBLIC RELEASE...to the Faculty Department of Operational Sciences Graduate School of Engineering and Management Air Force Institute of Technology Air University

  10. Air Pollution. Part A: Analysis.

    ERIC Educational Resources Information Center

    Ledbetter, Joe O.

    Two facets of the engineering control of air pollution (the analysis of possible problems and the application of effective controls) are covered in this two-volume text. Part A covers Analysis, and Part B, Prevention and Control. (This review is concerned with Part A only.) This volume deals with the terminology, methodology, and symptomatology…

  11. Assessment of health benefits related to air quality improvement strategies in urban areas: An Impact Pathway Approach.

    PubMed

    Silveira, Carlos; Roebeling, Peter; Lopes, Myriam; Ferreira, Joana; Costa, Solange; Teixeira, João P; Borrego, Carlos; Miranda, Ana I

    2016-12-01

    Air pollution is, increasingly, a concern to our society given the threats to human health and the environment. Concerted actions to improve air quality have been taken at different levels, such as through the development of Air Quality Plans (AQPs). However, air quality impacts associated with the implementation of abatement measures included in AQPs are often neglected. In order to identify the major gaps and strengths in current knowledge, a literature review has been performed on existing methodologies to estimate air pollution-related health impacts and subsequent external costs. Based on this review, the Impact Pathway Approach was adopted and applied within the context of the MAPLIA research project to assess the health impacts and benefits (or avoided external costs) derived from improvements in air quality. Seven emission abatement scenarios, based on individual and combined abatement measures, were tested for the major activity sectors (traffic, residential and industrial combustion and production processes) of a Portuguese urban area (Grande Porto) with severe particular matter (PM10) air pollution problems. Results revealed a strong positive correlation between population density and health benefits obtained from the assessed reduction scenarios. As a consequence, potential health benefits from reduction scenarios are largest in densely populated areas with high anthropic activity and, thus, where air pollution problems are most alarming. Implementation of all measures resulted in a reduction in PM10 emissions by almost 8%, improving air quality by about 1% and contributing to a benefit of 8.8 million €/year for the entire study domain. The introduction of PM10 reduction technologies in industrial units was the most beneficial abatement measure. This study intends to contribute to policy support for decision-making on air quality management. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Summary of the BIOMOVS A4 scenario: Testing models of the air-pasture-cow milk pathway using Chernobyl fallout data

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Peterson, S.R.; Hoffman, F.O.; Koehler, H.

    1996-08-01

    A unique opportunity to test dose assessment models arose after the Chernobyl reactor accident. During the passage of the contaminated plume, concentrations of {sup 131}I and {sup 137}Cs in air, pasture, and cow`s milk were collected at various sites in the northern hemisphere. Afterwards, contaminated pasture and milk samples were analyzed over time. Under the auspices of the Biospheric Model Validation Study (BIOMOVS), data from 13 sites for {sup 131}I and 10 sites for {sup 137}Cs were used to test model predictions for the air-pasture-cow milk pathway. Calculations were submitted for 23 models, 10 of which were quasi-steady state. Themore » others were time-dependent. Daily predictions and predictions of time-integrated concentration of {sup 131}I and {sup 137}Cs in pasture grass and milk for six months post-accident were calculated and compared with observed data. Testing against data from several locations over time for several steps in the air-to-milk pathway resulted in a better understanding of important processes and how they should be modeled. This model testing exercise showed both the strengths and weaknesses of the models and revealed the importance of testing all parts of dose assessment models whenever possible. 19 refs., 14 figs., 4 tabs.« less

  13. Analysis of Organizational Architectures for the Air Force Tuition Assistance Program

    DTIC Science & Technology

    2003-03-01

    FORCE TUITION ASSISTANCE PROGRAM THESIS Krista Zimmerman LaPietra AFIT/GOR/ENS/03-15 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR...ANALYSIS OF ORGANIZATIONAL ARCHITECTURES FOR THE AIR FORCE TUITION ASSISTANCE PROGRAM THESIS Presented to the Faculty Department...ANALYSIS OF ORGANIZATIONAL ARCHITECTURES FOR THE AIR FORCE TUITION ASSISTANCE PROGRAM Krista Zimmerman LaPietra, BS

  14. Air and radon pathways screenings methodologies for the next revision of the E-area PA

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dyer, J. A.

    The strategic plan for the next E-Area Low-Level Waste Facility Performance Assessment includes recommended changes to the screening criteria used to reduce the number of radioisotopes that are to be considered in the air and radon pathways incorporated into the GoldSim® atmospheric release model (ARM). For the air pathway, a revised screening methodology was developed based on refinement of previous E-Area PA screening approaches and consideration of the strategic plan recommendations. The revised methodology has three sequential screening steps for each radioisotope: (1) volatility test using the Periodic Table of the Elements, (2) stability test based on half-life, and (3)more » stability test based on volatility as measured by the Henry’s Law constant for the assumed dominant gaseous species or vapor pressure in the case of tritiated water. Of the 1252 radioisotopes listed in the International Commission on Radiological Protection Publication 107, only the 10 that satisfied all three steps of the revised screening methodology will be included in the ARM. They are: Ar-37, Ar-39, Ar-42, C-14, H-3, Hg-194, Hg-203, Kr-81, Kr-85, and Xe-127. For the radon pathway, a revised screening methodology was developed that also has three sequential steps: (1) identify all decay chains that terminate at Rn-222, (2) screen out parents that decay through U-238 because of its 4.5-billion-year primordial half-life, and (3) eliminate remaining parents whose half-life is shorter than one day. Of the 86 possible decay chains leading to Rn-222, six decay chains consist of 15 unique radioisotopes that will be incorporated into the ARM. The 15 radioisotopes are: U-238, Th-234, Pa-234m, Pu-238, U-234, Th-230, Ra-226, Cf-246, Cm-242, Am-242m, Am-242, Np-238, Np-234, Pa-230, and Rn-222.« less

  15. Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data.

    PubMed

    Lee, Hyeonjeong; Shin, Miyoung

    2017-01-01

    The problem of discovering genetic markers as disease signatures is of great significance for the successful diagnosis, treatment, and prognosis of complex diseases. Even if many earlier studies worked on identifying disease markers from a variety of biological resources, they mostly focused on the markers of genes or gene-sets (i.e., pathways). However, these markers may not be enough to explain biological interactions between genetic variables that are related to diseases. Thus, in this study, our aim is to investigate distinctive associations among active pathways (i.e., pathway-sets) shown each in case and control samples which can be observed from gene expression and/or methylation data. The pathway-sets are obtained by identifying a set of associated pathways that are often active together over a significant number of class samples. For this purpose, gene expression or methylation profiles are first analyzed to identify significant (active) pathways via gene-set enrichment analysis. Then, regarding these active pathways, an association rule mining approach is applied to examine interesting pathway-sets in each class of samples (case or control). By doing so, the sets of associated pathways often working together in activity profiles are finally chosen as our distinctive signature of each class. The identified pathway-sets are aggregated into a pathway activity network (PAN), which facilitates the visualization of differential pathway associations between case and control samples. From our experiments with two publicly available datasets, we could find interesting PAN structures as the distinctive signatures of breast cancer and uterine leiomyoma cancer, respectively. Our pathway-set markers were shown to be superior or very comparable to other genetic markers (such as genes or gene-sets) in disease classification. Furthermore, the PAN structure, which can be constructed from the identified markers of pathway-sets, could provide deeper insights into

  16. A novel bi-level meta-analysis approach: applied to biological pathway analysis.

    PubMed

    Nguyen, Tin; Tagett, Rebecca; Donato, Michele; Mitrea, Cristina; Draghici, Sorin

    2016-02-01

    The accumulation of high-throughput data in public repositories creates a pressing need for integrative analysis of multiple datasets from independent experiments. However, study heterogeneity, study bias, outliers and the lack of power of available methods present real challenge in integrating genomic data. One practical drawback of many P-value-based meta-analysis methods, including Fisher's, Stouffer's, minP and maxP, is that they are sensitive to outliers. Another drawback is that, because they perform just one statistical test for each individual experiment, they may not fully exploit the potentially large number of samples within each study. We propose a novel bi-level meta-analysis approach that employs the additive method and the Central Limit Theorem within each individual experiment and also across multiple experiments. We prove that the bi-level framework is robust against bias, less sensitive to outliers than other methods, and more sensitive to small changes in signal. For comparative analysis, we demonstrate that the intra-experiment analysis has more power than the equivalent statistical test performed on a single large experiment. For pathway analysis, we compare the proposed framework versus classical meta-analysis approaches (Fisher's, Stouffer's and the additive method) as well as against a dedicated pathway meta-analysis package (MetaPath), using 1252 samples from 21 datasets related to three human diseases, acute myeloid leukemia (9 datasets), type II diabetes (5 datasets) and Alzheimer's disease (7 datasets). Our framework outperforms its competitors to correctly identify pathways relevant to the phenotypes. The framework is sufficiently general to be applied to any type of statistical meta-analysis. The R scripts are available on demand from the authors. sorin@wayne.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e

  17. Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis.

    PubMed

    Mei, Hao; Li, Lianna; Liu, Shijian; Jiang, Fan; Griswold, Michael; Mosley, Thomas

    2017-01-21

    We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.

  18. Genetic variants in two pathways influence serum urate levels and gout risk: a systematic pathway analysis.

    PubMed

    Dong, Zheng; Zhou, Jingru; Xu, Xia; Jiang, Shuai; Li, Yuan; Zhao, Dongbao; Yang, Chengde; Ma, Yanyun; Wang, Yi; He, Hongjun; Ji, Hengdong; Zhang, Juan; Yuan, Ziyu; Yang, Yajun; Wang, Xiaofeng; Pang, Yafei; Jin, Li; Zou, Hejian; Wang, Jiucun

    2018-03-01

    The aims of this study were to identify candidate pathways associated with serum urate and to explore the genetic effect of those pathways on the risk of gout. Pathway analysis of the loci identified in genome-wide association studies (GWASs) showed that the ion transmembrane transporter activity pathway (GO: 0015075) and the secondary active transmembrane transporter activity pathway (GO: 0015291) were both associated with serum urate concentrations, with P FDR values of 0.004 and 0.007, respectively. In a Chinese population of 4,332 individuals, the two pathways were also found to be associated with serum urate (P FDR  = 1.88E-05 and 3.44E-04, separately). In addition, these two pathways were further associated with the pathogenesis of gout (P FDR  = 1.08E-08 and 2.66E-03, respectively) in the Chinese population and a novel gout-associated gene, SLC17A2, was identified (OR = 0.83, P FDR  = 0.017). The mRNA expression of candidate genes also showed significant differences among different groups at pathway level. The present study identified two transmembrane transporter activity pathways (GO: 0015075 and GO: 0015291) were associations with serum urate concentrations and the risk of gout. SLC17A2 was identified as a novel gene that influenced the risk of gout.

  19. Spatial assessment of air quality patterns in Malaysia using multivariate analysis

    NASA Astrophysics Data System (ADS)

    Dominick, Doreena; Juahir, Hafizan; Latif, Mohd Talib; Zain, Sharifuddin M.; Aris, Ahmad Zaharin

    2012-12-01

    This study aims to investigate possible sources of air pollutants and the spatial patterns within the eight selected Malaysian air monitoring stations based on a two-year database (2008-2009). The multivariate analysis was applied on the dataset. It incorporated Hierarchical Agglomerative Cluster Analysis (HACA) to access the spatial patterns, Principal Component Analysis (PCA) to determine the major sources of the air pollution and Multiple Linear Regression (MLR) to assess the percentage contribution of each air pollutant. The HACA results grouped the eight monitoring stations into three different clusters, based on the characteristics of the air pollutants and meteorological parameters. The PCA analysis showed that the major sources of air pollution were emissions from motor vehicles, aircraft, industries and areas of high population density. The MLR analysis demonstrated that the main pollutant contributing to variability in the Air Pollutant Index (API) at all stations was particulate matter with a diameter of less than 10 μm (PM10). Further MLR analysis showed that the main air pollutant influencing the high concentration of PM10 was carbon monoxide (CO). This was due to combustion processes, particularly originating from motor vehicles. Meteorological factors such as ambient temperature, wind speed and humidity were also noted to influence the concentration of PM10.

  20. Combinatorial complexity of pathway analysis in metabolic networks.

    PubMed

    Klamt, Steffen; Stelling, Jörg

    2002-01-01

    Elementary flux mode analysis is a promising approach for a pathway-oriented perspective of metabolic networks. However, in larger networks it is hampered by the combinatorial explosion of possible routes. In this work we give some estimations on the combinatorial complexity including theoretical upper bounds for the number of elementary flux modes in a network of a given size. In a case study, we computed the elementary modes in the central metabolism of Escherichia coli while utilizing four different substrates. Interestingly, although the number of modes occurring in this complex network can exceed half a million, it is still far below the upper bound. Hence, to a certain extent, pathway analysis of central catabolism is feasible to assess network properties such as flexibility and functionality.

  1. Whole-Genome Analysis of the SHORT-ROOT Developmental Pathway in Arabidopsis

    PubMed Central

    Busch, Wolfgang; Cui, Hongchang; Wang, Jean Y; Blilou, Ikram; Hassan, Hala; Nakajima, Keiji; Matsumoto, Noritaka; Lohmann, Jan U; Scheres, Ben

    2006-01-01

    Stem cell function during organogenesis is a key issue in developmental biology. The transcription factor SHORT-ROOT (SHR) is a critical component in a developmental pathway regulating both the specification of the root stem cell niche and the differentiation potential of a subset of stem cells in the Arabidopsis root. To obtain a comprehensive view of the SHR pathway, we used a statistical method called meta-analysis to combine the results of several microarray experiments measuring the changes in global expression profiles after modulating SHR activity. Meta-analysis was first used to identify the direct targets of SHR by combining results from an inducible form of SHR driven by its endogenous promoter, ectopic expression, followed by cell sorting and comparisons of mutant to wild-type roots. Eight putative direct targets of SHR were identified, all with expression patterns encompassing subsets of the native SHR expression domain. Further evidence for direct regulation by SHR came from binding of SHR in vivo to the promoter regions of four of the eight putative targets. A new role for SHR in the vascular cylinder was predicted from the expression pattern of several direct targets and confirmed with independent markers. The meta-analysis approach was then used to perform a global survey of the SHR indirect targets. Our analysis suggests that the SHR pathway regulates root development not only through a large transcription regulatory network but also through hormonal pathways and signaling pathways using receptor-like kinases. Taken together, our results not only identify the first nodes in the SHR pathway and a new function for SHR in the development of the vascular tissue but also reveal the global architecture of this developmental pathway. PMID:16640459

  2. Impacts of Lowered Urban Air Temperatures on Precursor Emission and Ozone Air Quality.

    PubMed

    Taha, Haider; Konopacki, Steven; Akbari, Hashem

    1998-09-01

    Meteorological, photochemical, building-energy, and power plant simulations were performed to assess the possible precursor emission and ozone air quality impacts of decreased air temperatures that could result from implementing the "cool communities" concept in California's South Coast Air Basin (SoCAB). Two pathways are considered. In the direct pathway, a reduction in cooling energy use translates into reduced demand for generation capacity and, thus, reduced precursor emissions from electric utility power plants. In the indirect pathway, reduced air temperatures can slow the atmospheric production of ozone as well as precursor emission from anthropogenic and biogenic sources. The simulations suggest small impacts on emissions following implementation of cool communities in the SoCAB. In summer, for example, there can be reductions of up to 3% in NO x emissions from in-basin power plants. The photochemical simulations suggest that the air quality impacts of these direct emission reductions are small. However, the indirect atmospheric effects of cool communities can be significant. For example, ozone peak concentrations can decrease by up to 11% in summer and population-weighted exceedance exposure to ozone above the California and National Ambient Air Quality Standards can decrease by up to 11 and 17%, respectively. The modeling suggests that if these strategies are combined with others, such as mobile-source emission control, the improvements in ozone air quality can be substantial.

  3. Implied Maximum Dose Analysis of Standard Values of 25 Pesticides Based on Major Human Exposure Pathways

    PubMed Central

    Li, Zijian; Jennings, Aaron A.

    2017-01-01

    Worldwide jurisdictions are making efforts to regulate pesticide standard values in residential soil, drinking water, air, and agricultural commodity to lower the risk of pesticide impacts on human health. Because human may exposure to pesticides from many ways, such as ingestion, inhalation, and dermal contact, it is important to examine pesticide standards by considering all major exposure pathways. Analysis of implied maximum dose limits for commonly historical and current used pesticides was adopted in this study to examine whether worldwide pesticide standard values are enough to prevent human health impact or not. Studies show that only U.S. has regulated pesticides standard in the air. Only 4% of the total number of implied maximum dose limits is based on three major exposures. For Chlorpyrifos, at least 77.5% of the total implied maximum dose limits are above the acceptable daily intake. It also shows that most jurisdictions haven't provided pesticide standards in all major exposures yet, and some of the standards are not good enough to protect human health. PMID:29546224

  4. A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations

    PubMed Central

    Zhang, Han; Wheeler, William; Hyland, Paula L.; Yang, Yifan; Shi, Jianxin; Chatterjee, Nilanjan; Yu, Kai

    2016-01-01

    Meta-analysis of multiple genome-wide association studies (GWAS) has become an effective approach for detecting single nucleotide polymorphism (SNP) associations with complex traits. However, it is difficult to integrate the readily accessible SNP-level summary statistics from a meta-analysis into more powerful multi-marker testing procedures, which generally require individual-level genetic data. We developed a general procedure called Summary based Adaptive Rank Truncated Product (sARTP) for conducting gene and pathway meta-analysis that uses only SNP-level summary statistics in combination with genotype correlation estimated from a panel of individual-level genetic data. We demonstrated the validity and power advantage of sARTP through empirical and simulated data. We conducted a comprehensive pathway-based meta-analysis with sARTP on type 2 diabetes (T2D) by integrating SNP-level summary statistics from two large studies consisting of 19,809 T2D cases and 111,181 controls with European ancestry. Among 4,713 candidate pathways from which genes in neighborhoods of 170 GWAS established T2D loci were excluded, we detected 43 T2D globally significant pathways (with Bonferroni corrected p-values < 0.05), which included the insulin signaling pathway and T2D pathway defined by KEGG, as well as the pathways defined according to specific gene expression patterns on pancreatic adenocarcinoma, hepatocellular carcinoma, and bladder carcinoma. Using summary data from 8 eastern Asian T2D GWAS with 6,952 cases and 11,865 controls, we showed 7 out of the 43 pathways identified in European populations remained to be significant in eastern Asians at the false discovery rate of 0.1. We created an R package and a web-based tool for sARTP with the capability to analyze pathways with thousands of genes and tens of thousands of SNPs. PMID:27362418

  5. A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations.

    PubMed

    Zhang, Han; Wheeler, William; Hyland, Paula L; Yang, Yifan; Shi, Jianxin; Chatterjee, Nilanjan; Yu, Kai

    2016-06-01

    Meta-analysis of multiple genome-wide association studies (GWAS) has become an effective approach for detecting single nucleotide polymorphism (SNP) associations with complex traits. However, it is difficult to integrate the readily accessible SNP-level summary statistics from a meta-analysis into more powerful multi-marker testing procedures, which generally require individual-level genetic data. We developed a general procedure called Summary based Adaptive Rank Truncated Product (sARTP) for conducting gene and pathway meta-analysis that uses only SNP-level summary statistics in combination with genotype correlation estimated from a panel of individual-level genetic data. We demonstrated the validity and power advantage of sARTP through empirical and simulated data. We conducted a comprehensive pathway-based meta-analysis with sARTP on type 2 diabetes (T2D) by integrating SNP-level summary statistics from two large studies consisting of 19,809 T2D cases and 111,181 controls with European ancestry. Among 4,713 candidate pathways from which genes in neighborhoods of 170 GWAS established T2D loci were excluded, we detected 43 T2D globally significant pathways (with Bonferroni corrected p-values < 0.05), which included the insulin signaling pathway and T2D pathway defined by KEGG, as well as the pathways defined according to specific gene expression patterns on pancreatic adenocarcinoma, hepatocellular carcinoma, and bladder carcinoma. Using summary data from 8 eastern Asian T2D GWAS with 6,952 cases and 11,865 controls, we showed 7 out of the 43 pathways identified in European populations remained to be significant in eastern Asians at the false discovery rate of 0.1. We created an R package and a web-based tool for sARTP with the capability to analyze pathways with thousands of genes and tens of thousands of SNPs.

  6. Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

    PubMed Central

    Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

    2017-01-01

    The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

  7. Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

    PubMed

    Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

    2017-01-01

    The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

  8. Pathway-based variant enrichment analysis on the example of dilated cardiomyopathy.

    PubMed

    Backes, Christina; Meder, Benjamin; Lai, Alan; Stoll, Monika; Rühle, Frank; Katus, Hugo A; Keller, Andreas

    2016-01-01

    Genome-wide association (GWA) studies have significantly contributed to the understanding of human genetic variation and its impact on clinical traits. Frequently only a limited number of highly significant associations were considered as biologically relevant. Increasingly, network analysis of affected genes is used to explore the potential role of the genetic background on disease mechanisms. Instead of first determining affected genes or calculating scores for genes and performing pathway analysis on the gene level, we integrated both steps and directly calculated enrichment on the genetic variant level. The respective approach has been tested on dilated cardiomyopathy (DCM) GWA data as showcase. To compute significance values, 5000 permutation tests were carried out and p values were adjusted for multiple testing. For 282 KEGG pathways, we computed variant enrichment scores and significance values. Of these, 65 were significant. Surprisingly, we discovered the "nucleotide excision repair" and "tuberculosis" pathways to be most significantly associated with DCM (p = 10(-9)). The latter pathway is driven by genes of the HLA-D antigen group, a finding that closely resembles previous discoveries made by expression quantitative trait locus analysis in the context of DCM-GWA. Next, we implemented a sub-network-based analysis, which searches for affected parts of KEGG, however, independent on the pre-defined pathways. Here, proteins of the contractile apparatus of cardiac cells as well as the FAS sub-network were found to be affected by common polymorphisms in DCM. In this work, we performed enrichment analysis directly on variants, leveraging the potential to discover biological information in thousands of published GWA studies. The applied approach is cutoff free and considers a ranked list of genetic variants as input.

  9. Monitoring and analysis of air quality in Riga

    NASA Astrophysics Data System (ADS)

    Ubelis, Arnolds; Leitass, Andris; Vitols, Maris

    1995-09-01

    Riga, the capital of Latvia is a city with nearly 900,000 inhabitants and various highly concentrated industries. Air pollution in Riga is a serious problem affecting health and damaging valuable buildings of historical importance, as acid rain and smog take their toll. Therefore the Air Quality Management System with significant assistance from Swedish Government and persistent efforts from Riga City Council was arranged in Riga. It contains INDIC AIRVIRO system which simulates and evaluates air pollution levels at various locations. It then processes the data in order to predict air quality based on a number of criteria and parameters, measured by OPSIS differential absorption instruments, as well as data from the Meteorological Service and results of episodic measurements. The analysis of the results provided by Riga Air Quality Management System for the first time allows us to start comprehensive supervision of troposphere physical, chemical, and photochemical processes in the air of Riga as well as to appreciate the influence of lcoal pollution and transboundary transfer. The report contains the actual results of this work and first attempts of analysis as well as overview about activities towards research and teaching in the fields of spectroscopy and photochemistry of polluted atmospheres.

  10. Pathway and network analysis of cancer genomes.

    PubMed

    Creixell, Pau; Reimand, Jüri; Haider, Syed; Wu, Guanming; Shibata, Tatsuhiro; Vazquez, Miguel; Mustonen, Ville; Gonzalez-Perez, Abel; Pearson, John; Sander, Chris; Raphael, Benjamin J; Marks, Debora S; Ouellette, B F Francis; Valencia, Alfonso; Bader, Gary D; Boutros, Paul C; Stuart, Joshua M; Linding, Rune; Lopez-Bigas, Nuria; Stein, Lincoln D

    2015-07-01

    Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations.

  11. Pathways of inhalation exposure to manganese in children ...

    EPA Pesticide Factsheets

    Manganese (Mn) is both essential element and neurotoxicant. Exposure to Mn can occur from various sources and routes. Structural equation modeling was used to examine routes of exposure to Mn among children residing near a ferromanganese refinery in Marietta, Ohio. An inhalation pathway model to ambient air Mn was hypothesized. Data for model evaluation were obtained from participants in the Communities Actively Researching Exposure Study (CARES). These data were collected in 2009 and included levels of Mn in residential soil and dust, levels of Mn in children's hair, information on the amount of time the child spent outside, heat and air conditioning in the home and level of parent education. Hair Mn concentration was the primary endogenous variable used to assess the theoretical inhalation exposure pathways. The model indicated that household dust Mn was a significant contributor to child hair Mn (0.37). Annual ambient air Mn concentration (0.26), time children spent outside (0.24) and soil Mn (0.24) significantly contributed to the amount of Mn in household dust. These results provide a potential framework for understanding the inhalation exposure pathway for children exposed to ambient air Mn who live in proximity to an industrial emission source. The purpose of this study was to use a structural equations modeling approach combined with exposure estimates derived from air-dispersion modeling to assess potential inhalation exposure pathways for children to a

  12. On-line metabolic pathway analysis based on metabolic signal flow diagram.

    PubMed

    Shi, H; Shimizu, K

    In this work, an integrated modeling approach based on a metabolic signal flow diagram and cellular energetics was used to model the metabolic pathway analysis for the cultivation of yeast on glucose. This approach enables us to make a clear analysis of the flow direction of the carbon fluxes in the metabolic pathways as well as of the degree of activation of a particular pathway for the synthesis of biomaterials for cell growth. The analyses demonstrate that the main metabolic pathways of Saccharomyces cerevisiae change significantly during batch culture. Carbon flow direction is toward glycolysis to satisfy the increase of requirement for precursors and energy. The enzymatic activation of TCA cycle seems to always be at normal level, which may result in the overflow of ethanol due to its limited capacity. The advantage of this approach is that it adopts both virtues of the metabolic signal flow diagram and the simple network analysis method, focusing on the investigation of the flow directions of carbon fluxes and the degree of activation of a particular pathway or reaction loop. All of the variables used in the model equations were determined on-line; the information obtained from the calculated metabolic coefficients may result in a better understanding of cell physiology and help to evaluate the state of the cell culture process. Copyright 1998 John Wiley & Sons, Inc.

  13. Research on Air Quality Evaluation based on Principal Component Analysis

    NASA Astrophysics Data System (ADS)

    Wang, Xing; Wang, Zilin; Guo, Min; Chen, Wei; Zhang, Huan

    2018-01-01

    Economic growth has led to environmental capacity decline and the deterioration of air quality. Air quality evaluation as a fundamental of environmental monitoring and air pollution control has become increasingly important. Based on the principal component analysis (PCA), this paper evaluates the air quality of a large city in Beijing-Tianjin-Hebei Area in recent 10 years and identifies influencing factors, in order to provide reference to air quality management and air pollution control.

  14. Air quality and passenger comfort in an air-conditioned bus micro-environment.

    PubMed

    Zhu, Xiaoxuan; Lei, Li; Wang, Xingshen; Zhang, Yinghui

    2018-04-12

    In this study, passenger comfort and the air pollution status of the micro-environmental conditions in an air-conditioned bus were investigated through questionnaires, field measurements, and a numerical simulation. As a subjective analysis, passengers' perceptions of indoor environmental quality and comfort levels were determined from questionnaires. As an objective analysis, a numerical simulation was conducted using a discrete phase model to determine the diffusion and distribution of pollutants, including particulate matter with a diameter < 10 μm (PM 10 ), which were verified by experimental results. The results revealed poor air quality and dissatisfactory thermal comfort conditions in Jinan's air-conditioned bus system. To solve these problems, three scenarios (schemes A, B, C) were designed to alter the ventilation parameters. According to the results of an improved simulation of these scenarios, reducing or adding air outputs would shorten the time taken to reach steady-state conditions and weaken the airflow or lower the temperature in the cabin. The airflow pathway was closely related to the layout of the air conditioning. Scheme B lowered the temperature by 0.4 K and reduced the airflow by 0.01 m/s, while scheme C reduced the volume concentration of PM 10 to 150 μg/m 3 . Changing the air supply angle could further improve the airflow and reduce the concentration of PM 10 . With regard to the perception of airflow and thermal comfort, the scheme with an airflow provided by a 60° nozzle was considered better, and the concentration of PM 10 was reduced to 130 μg/m 3 .

  15. Effect of curcumin on aged Drosophila melanogaster: a pathway prediction analysis.

    PubMed

    Zhang, Zhi-guo; Niu, Xu-yan; Lu, Ai-ping; Xiao, Gary Guishan

    2015-02-01

    To re-analyze the data published in order to explore plausible biological pathways that can be used to explain the anti-aging effect of curcumin. Microarray data generated from other study aiming to investigate effect of curcumin on extending lifespan of Drosophila melanogaster were further used for pathway prediction analysis. The differentially expressed genes were identified by using GeneSpring GX with a criterion of 3.0-fold change. Two Cytoscape plugins including BisoGenet and molecular complex detection (MCODE) were used to establish the protein-protein interaction (PPI) network based upon differential genes in order to detect highly connected regions. The function annotation clustering tool of Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for pathway analysis. A total of 87 genes expressed differentially in D. melanogaster melanogaster treated with curcumin were identified, among which 50 were up-regulated significantly and 37 were remarkably down-regulated in D. melanogaster melanogaster treated with curcumin. Based upon these differential genes, PPI network was constructed with 1,082 nodes and 2,412 edges. Five highly connected regions in PPI networks were detected by MCODE algorithm, suggesting anti-aging effect of curcumin may be underlined through five different pathways including Notch signaling pathway, basal transcription factors, cell cycle regulation, ribosome, Wnt signaling pathway, and p53 pathway. Genes and their associated pathways in D. melanogaster melanogaster treated with anti-aging agent curcumin were identified using PPI network and MCODE algorithm, suggesting that curcumin may be developed as an alternative therapeutic medicine for treating aging-associated diseases.

  16. Genome-wide pathway analysis of memory impairment in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks.

    PubMed

    Ramanan, Vijay K; Kim, Sungeun; Holohan, Kelly; Shen, Li; Nho, Kwangsik; Risacher, Shannon L; Foroud, Tatiana M; Mukherjee, Shubhabrata; Crane, Paul K; Aisen, Paul S; Petersen, Ronald C; Weiner, Michael W; Saykin, Andrew J

    2012-12-01

    Memory deficits are prominent features of mild cognitive impairment (MCI) and Alzheimer's disease (AD). The genetic architecture underlying these memory deficits likely involves the combined effects of multiple genetic variants operative within numerous biological pathways. In order to identify functional pathways associated with memory impairment, we performed a pathway enrichment analysis on genome-wide association data from 742 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. A composite measure of memory was generated as the phenotype for this analysis by applying modern psychometric theory to item-level data from the ADNI neuropsychological test battery. Using the GSA-SNP software tool, we identified 27 canonical, expertly-curated pathways with enrichment (FDR-corrected p-value < 0.05) against this composite memory score. Processes classically understood to be involved in memory consolidation, such as neurotransmitter receptor-mediated calcium signaling and long-term potentiation, were highly represented among the enriched pathways. In addition, pathways related to cell adhesion, neuronal differentiation and guided outgrowth, and glucose- and inflammation-related signaling were also enriched. Among genes that were highly-represented in these enriched pathways, we found indications of coordinated relationships, including one large gene set that is subject to regulation by the SP1 transcription factor, and another set that displays co-localized expression in normal brain tissue along with known AD risk genes. These results 1) demonstrate that psychometrically-derived composite memory scores are an effective phenotype for genetic investigations of memory impairment and 2) highlight the promise of pathway analysis in elucidating key mechanistic targets for future studies and for therapeutic interventions.

  17. PathVisio 3: an extendable pathway analysis toolbox.

    PubMed

    Kutmon, Martina; van Iersel, Martijn P; Bohler, Anwesha; Kelder, Thomas; Nunes, Nuno; Pico, Alexander R; Evelo, Chris T

    2015-02-01

    PathVisio is a commonly used pathway editor, visualization and analysis software. Biological pathways have been used by biologists for many years to describe the detailed steps in biological processes. Those powerful, visual representations help researchers to better understand, share and discuss knowledge. Since the first publication of PathVisio in 2008, the original paper was cited more than 170 times and PathVisio was used in many different biological studies. As an online editor PathVisio is also integrated in the community curated pathway database WikiPathways. Here we present the third version of PathVisio with the newest additions and improvements of the application. The core features of PathVisio are pathway drawing, advanced data visualization and pathway statistics. Additionally, PathVisio 3 introduces a new powerful extension systems that allows other developers to contribute additional functionality in form of plugins without changing the core application. PathVisio can be downloaded from http://www.pathvisio.org and in 2014 PathVisio 3 has been downloaded over 5,500 times. There are already more than 15 plugins available in the central plugin repository. PathVisio is a freely available, open-source tool published under the Apache 2.0 license (http://www.apache.org/licenses/LICENSE-2.0). It is implemented in Java and thus runs on all major operating systems. The code repository is available at http://svn.bigcat.unimaas.nl/pathvisio. The support mailing list for users is available on https://groups.google.com/forum/#!forum/wikipathways-discuss and for developers on https://groups.google.com/forum/#!forum/wikipathways-devel.

  18. Fuzzy cluster analysis of air quality in Beijing district

    NASA Astrophysics Data System (ADS)

    Liu, Hongkai

    2018-02-01

    The principle of fuzzy clustering analysis is applied in this article, by using the method of transitive closure, the main air pollutants in 17 districts of Beijing from 2014 to 2016 were classified. The results of the analysis reflects the nearly three year’s changes of the main air pollutants in Beijing. This can provide the scientific for atmospheric governance in the Beijing area and digital support.

  19. Speed estimation for air quality analysis.

    DOT National Transportation Integrated Search

    2005-05-01

    Average speed is an essential input to the air quality analysis model MOBILE6 for emission factor calculation. Traditionally, speed is obtained from travel demand models. However, such models are not usually calibrated to speeds. Furthermore, for rur...

  20. Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma.

    PubMed

    Li, Chaoxing; Liu, Li; Dinu, Valentin

    2018-01-01

    Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes

  1. In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

    PubMed

    Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

    2016-11-16

    Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

  2. In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development

    PubMed Central

    Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

    2016-01-01

    Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968

  3. Air pollution and quality of sperm: a meta-analysis.

    PubMed

    Fathi Najafi, Tahereh; Latifnejad Roudsari, Robab; Namvar, Farideh; Ghavami Ghanbarabadi, Vahid; Hadizadeh Talasaz, Zahra; Esmaeli, Mahin

    2015-04-01

    Air pollution is common in all countries and affects reproductive functions in men and women. It particularly impacts sperm parameters in men. This meta-analysis aimed to examine the impact of air pollution on the quality of sperm. The scientific databases of Medline, PubMed, Scopus, Google scholar, Cochrane Library, and Elsevier were searched to identify relevant articles published between 1978 to 2013. In the first step, 76 articles were selected. These studies were ecological correlation, cohort, retrospective, cross-sectional, and case control ones that were found through electronic and hand search of references about air pollution and male infertility. The outcome measurement was the change in sperm parameters. A total of 11 articles were ultimately included in a meta-analysis to examine the impact of air pollution on sperm parameters. The authors applied meta-analysis sheets from Cochrane library, then data extraction, including mean and standard deviation of sperm parameters were calculated and finally their confidence interval (CI) were compared to CI of standard parameters. The CI for pooled means were as follows: 2.68 ± 0.32 for ejaculation volume (mL), 62.1 ± 15.88 for sperm concentration (million per milliliter), 39.4 ± 5.52 for sperm motility (%), 23.91 ± 13.43 for sperm morphology (%) and 49.53 ± 11.08 for sperm count. The results of this meta-analysis showed that air pollution reduces sperm motility, but has no impact on the other sperm parameters of spermogram.

  4. Analysis of Geothermal Pathway in the Metamorphic Area, Northeastern Taiwan

    NASA Astrophysics Data System (ADS)

    Wang, C.; Wu, M. Y.; Song, S. R.; Lo, W.

    2016-12-01

    A quantitative measure by play fairway analysis in geothermal energy development is an important tool that can present the probability map of potential resources through the uncertainty studies in geology for early phase decision making purpose in the related industries. While source, pathway, and fluid are the three main geologic factors in traditional geothermal systems, identifying the heat paths is critical to reduce drilling cost. Taiwan is in East Asia and the western edge of Pacific Ocean, locating on the convergent boundary of Eurasian Plate and Philippine Sea Plate with many earthquake activities. This study chooses a metamorphic area in the western corner of Yi-Lan plain in northeastern Taiwan with high geothermal potential and several existing exploration sites. Having high subsurface temperature gradient from the mountain belts, and plenty hydrologic systems through thousands of millimeters annual precipitation that would bring up heats closer to the surface, current geothermal conceptual model indicates the importance of pathway distribution which affects the possible concentration of extractable heat location. The study conducts surface lineation analysis using analytic hierarchy process to determine weights among various fracture types for their roles in geothermal pathways, based on the information of remote sensing data, published geologic maps and field work measurements, to produce regional fracture distribution probability map. The results display how the spatial distribution of pathways through various fractures could affect geothermal systems, identify the geothermal plays using statistical data analysis, and compare against the existing drilling data.

  5. Low-temperature, mineral-catalyzed air oxidation: a possible new pathway for PAH stabilization in sediments and soils.

    PubMed

    Ghislain, Thierry; Faure, Pierre; Biache, Coralie; Michels, Raymond

    2010-11-15

    Reactivity of polycyclic aromatic hydrocarbons (PAHs) in the subsurface is of importance to environmental assessment, as they constitute a highly toxic hazard. Understanding their reactivity in the long term in natural recovering systems is thus a key issue. This article describes an experimental investigation on the air oxidation of fluoranthene (a PAH abundant in natural systems polluted by industrial coal use) at 100°C on different mineral substrates commonly found in soils and sediments (quartz sand, limestone, and clay). Results demonstrate that fluoranthene is readily oxidized in the presence of limestone and clay, leading to the formation of high molecular weight compounds and a carbonaceous residue as end product especially for clay experiments. As demonstrated elsewhere, the experimental conditions used permitted the reproduction of the geochemical pathway of organic matter observed under natural conditions. It is therefore suggested that low-temperature, mineral-catalyzed air oxidation is a mechanism relevant to the stabilization of PAHs in sediments and soils.

  6. Screening key candidate genes and pathways involved in insulinoma by microarray analysis.

    PubMed

    Zhou, Wuhua; Gong, Li; Li, Xuefeng; Wan, Yunyan; Wang, Xiangfei; Li, Huili; Jiang, Bin

    2018-06-01

    Insulinoma is a rare type tumor and its genetic features remain largely unknown. This study aimed to search for potential key genes and relevant enriched pathways of insulinoma.The gene expression data from GSE73338 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified between insulinoma tissues and normal pancreas tissues, followed by pathway enrichment analysis, protein-protein interaction (PPI) network construction, and module analysis. The expressions of candidate key genes were validated by quantitative real-time polymerase chain reaction (RT-PCR) in insulinoma tissues.A total of 1632 DEGs were obtained, including 1117 upregulated genes and 514 downregulated genes. Pathway enrichment results showed that upregulated DEGs were significantly implicated in insulin secretion, and downregulated DEGs were mainly enriched in pancreatic secretion. PPI network analysis revealed 7 hub genes with degrees more than 10, including GCG (glucagon), GCGR (glucagon receptor), PLCB1 (phospholipase C, beta 1), CASR (calcium sensing receptor), F2R (coagulation factor II thrombin receptor), GRM1 (glutamate metabotropic receptor 1), and GRM5 (glutamate metabotropic receptor 5). DEGs involved in the significant modules were enriched in calcium signaling pathway, protein ubiquitination, and platelet degranulation. Quantitative RT-PCR data confirmed that the expression trends of these hub genes were similar to the results of bioinformatic analysis.The present study demonstrated that candidate DEGs and enriched pathways were the potential critical molecule events involved in the development of insulinoma, and these findings were useful for better understanding of insulinoma genesis.

  7. Application of Petri net based analysis techniques to signal transduction pathways.

    PubMed

    Sackmann, Andrea; Heiner, Monika; Koch, Ina

    2006-11-02

    Signal transduction pathways are usually modelled using classical quantitative methods, which are based on ordinary differential equations (ODEs). However, some difficulties are inherent in this approach. On the one hand, the kinetic parameters involved are often unknown and have to be estimated. With increasing size and complexity of signal transduction pathways, the estimation of missing kinetic data is not possible. On the other hand, ODEs based models do not support any explicit insights into possible (signal-) flows within the network. Moreover, a huge amount of qualitative data is available due to high-throughput techniques. In order to get information on the systems behaviour, qualitative analysis techniques have been developed. Applications of the known qualitative analysis methods concern mainly metabolic networks. Petri net theory provides a variety of established analysis techniques, which are also applicable to signal transduction models. In this context special properties have to be considered and new dedicated techniques have to be designed. We apply Petri net theory to model and analyse signal transduction pathways first qualitatively before continuing with quantitative analyses. This paper demonstrates how to build systematically a discrete model, which reflects provably the qualitative biological behaviour without any knowledge of kinetic parameters. The mating pheromone response pathway in Saccharomyces cerevisiae serves as case study. We propose an approach for model validation of signal transduction pathways based on the network structure only. For this purpose, we introduce the new notion of feasible t-invariants, which represent minimal self-contained subnets being active under a given input situation. Each of these subnets stands for a signal flow in the system. We define maximal common transition sets (MCT-sets), which can be used for t-invariant examination and net decomposition into smallest biologically meaningful functional units. The

  8. Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma

    PubMed Central

    Liu, Li; Dinu, Valentin

    2018-01-01

    Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway’s topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher’s exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov–Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in

  9. Pathway Distiller - multisource biological pathway consolidation.

    PubMed

    Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong

    2012-01-01

    One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow

  10. Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

    PubMed

    Feng, Yinling; Wang, Xuefeng

    2017-03-01

    In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

  11. AOP: An R Package For Sufficient Causal Analysis in Pathway ...

    EPA Pesticide Factsheets

    Summary: How can I quickly find the key events in a pathway that I need to monitor to predict that a/an beneficial/adverse event/outcome will occur? This is a key question when using signaling pathways for drug/chemical screening in pharma-cology, toxicology and risk assessment. By identifying these sufficient causal key events, we have fewer events to monitor for a pathway, thereby decreasing assay costs and time, while maximizing the value of the information. I have developed the “aop” package which uses backdoor analysis of causal net-works to identify these minimal sets of key events that are suf-ficient for making causal predictions. Availability and Implementation: The source and binary are available online through the Bioconductor project (http://www.bioconductor.org/) as an R package titled “aop”. The R/Bioconductor package runs within the R statistical envi-ronment. The package has functions that can take pathways (as directed graphs) formatted as a Cytoscape JSON file as input, or pathways can be represented as directed graphs us-ing the R/Bioconductor “graph” package. The “aop” package has functions that can perform backdoor analysis to identify the minimal set of key events for making causal predictions.Contact: burgoon.lyle@epa.gov This paper describes an R/Bioconductor package that was developed to facilitate the identification of key events within an AOP that are the minimal set of sufficient key events that need to be tested/monit

  12. Computer Analysis of Air Pollution from Highways, Streets, and Complex Interchanges

    DOT National Transportation Integrated Search

    1974-03-01

    A detailed computer analysis of air quality for a complex highway interchange was prepared, using an in-house version of the Environmental Protection Agency's Gaussian Highway Line Source Model. This analysis showed that the levels of air pollution n...

  13. Aircraft/Air Traffic Management Functional Analysis Model: Technical Description. 2.0

    NASA Technical Reports Server (NTRS)

    Etheridge, Melvin; Plugge, Joana; Retina, Nusrat

    1998-01-01

    The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) under a National Aeronautics and Space Administration (NASA) contract. This document provides a technical description of FAM 2.0 and its computer files to enable the modeler and programmer to make enhancements or modifications to the model. Those interested in a guide for using the model in analysis should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Users Manual.

  14. Screening for Key Pathways Associated with the Development of Osteoporosis by Bioinformatics Analysis

    PubMed Central

    Liu, Yanqing; Wang, Yueqiu; Zhang, Yanxia; Liu, Zhiyong; Xiang, Hongfei; Peng, Xianbo

    2017-01-01

    Objectives. We aimed to find the key pathways associated with the development of osteoporosis. Methods. We downloaded expression profile data of GSE35959 and analyzed the differentially expressed genes (DEGs) in 3 comparison groups (old_op versus middle, old_op versus old, and old_op versus senescent). KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses were carried out. Besides, Venn diagram analysis and gene functional interaction (FI) network analysis were performed. Results. Totally 520 DEGs, 966 DEGs, and 709 DEGs were obtained in old_op versus middle, old_op versus old, and old_op versus senescent groups, respectively. Lysosome pathway was the significantly enriched pathways enriched by intersection genes. The pathways enriched by subnetwork modules suggested that mitotic metaphase and anaphase and signaling by Rho GTPases in module 1 had more proteins from module. Conclusions. Lysosome pathway, mitotic metaphase and anaphase, and signaling by Rho GTPases may be involved in the development of osteoporosis. Furthermore, Rho GTPases may regulate the balance of bone resorption and bone formation via controlling osteoclast and osteoblast. These 3 pathways may be regarded as the treatment targets for osteoporosis. PMID:28466021

  15. A Pathway-Centered Analysis of Pig Domestication and Breeding in Eurasia

    PubMed Central

    Leno-Colorado, Jordi; Hudson, Nick J.; Reverter, Antonio; Pérez-Enciso, Miguel

    2017-01-01

    Ascertaining the molecular and physiological basis of domestication and breeding is an active area of research. Due to the current wide distribution of its wild ancestor, the wild boar, the pig (Sus scrofa) is an excellent model to study these processes, which occurred independently in East Asia and Europe ca. 9000 yr ago. Analyzing genome variability patterns in terms of metabolic pathways is attractive since it considers the impact of interrelated functions of genes, in contrast to genome-wide scans that treat genes or genome windows in isolation. To that end, we studied 40 wild boars and 123 domestic pig genomes from Asia and Europe when metabolic pathway was the unit of analysis. We computed statistical significance for differentiation (Fst) and linkage disequilibrium (nSL) statistics at the pathway level. In terms of Fst, we found 21 and 12 pathways significantly differentiated at a q-value < 0.05 in Asia and Europe, respectively; five were shared across continents. In Asia, we found six significant pathways related to behavior, which involved essential neurotransmitters like dopamine and serotonin. Several significant pathways were interrelated and shared a variable percentage of genes. There were 12 genes present in >10 significant pathways (in terms of Fst), comprising genes involved in the transduction of a large number of signals, like phospholipase PCLB1, which is expressed in the brain, or ITPR3, which has an important role in taste transduction. In terms of nSL, significant pathways were mainly related to reproductive performance (ovarian steroidogenesis), a similarly important target trait during domestication and modern animal breeding. Different levels of recombination cannot explain these results, since we found no correlation between Fst and recombination rate. However, we did find an increased ratio of deleterious mutations in domestic vs. wild populations, suggesting a relaxed functional constraint associated with the domestication and breeding

  16. A Pathway-Centered Analysis of Pig Domestication and Breeding in Eurasia.

    PubMed

    Leno-Colorado, Jordi; Hudson, Nick J; Reverter, Antonio; Pérez-Enciso, Miguel

    2017-07-05

    Ascertaining the molecular and physiological basis of domestication and breeding is an active area of research. Due to the current wide distribution of its wild ancestor, the wild boar, the pig ( Sus scrofa ) is an excellent model to study these processes, which occurred independently in East Asia and Europe ca. 9000 yr ago. Analyzing genome variability patterns in terms of metabolic pathways is attractive since it considers the impact of interrelated functions of genes, in contrast to genome-wide scans that treat genes or genome windows in isolation. To that end, we studied 40 wild boars and 123 domestic pig genomes from Asia and Europe when metabolic pathway was the unit of analysis. We computed statistical significance for differentiation (Fst) and linkage disequilibrium (nSL) statistics at the pathway level. In terms of Fst, we found 21 and 12 pathways significantly differentiated at a q -value < 0.05 in Asia and Europe, respectively; five were shared across continents. In Asia, we found six significant pathways related to behavior, which involved essential neurotransmitters like dopamine and serotonin. Several significant pathways were interrelated and shared a variable percentage of genes. There were 12 genes present in >10 significant pathways (in terms of Fst), comprising genes involved in the transduction of a large number of signals, like phospholipase PCLB1, which is expressed in the brain, or ITPR3, which has an important role in taste transduction. In terms of nSL, significant pathways were mainly related to reproductive performance (ovarian steroidogenesis), a similarly important target trait during domestication and modern animal breeding. Different levels of recombination cannot explain these results, since we found no correlation between Fst and recombination rate. However, we did find an increased ratio of deleterious mutations in domestic vs. wild populations, suggesting a relaxed functional constraint associated with the domestication and

  17. Air Pollution and Quality of Sperm: A Meta-Analysis

    PubMed Central

    Fathi Najafi, Tahereh; Latifnejad Roudsari, Robab; Namvar, Farideh; Ghavami Ghanbarabadi, Vahid; Hadizadeh Talasaz, Zahra; Esmaeli, Mahin

    2015-01-01

    Context: Air pollution is common in all countries and affects reproductive functions in men and women. It particularly impacts sperm parameters in men. This meta-analysis aimed to examine the impact of air pollution on the quality of sperm. Evidence Acquisition: The scientific databases of Medline, PubMed, Scopus, Google scholar, Cochrane Library, and Elsevier were searched to identify relevant articles published between 1978 to 2013. In the first step, 76 articles were selected. These studies were ecological correlation, cohort, retrospective, cross-sectional, and case control ones that were found through electronic and hand search of references about air pollution and male infertility. The outcome measurement was the change in sperm parameters. A total of 11 articles were ultimately included in a meta-analysis to examine the impact of air pollution on sperm parameters. The authors applied meta-analysis sheets from Cochrane library, then data extraction, including mean and standard deviation of sperm parameters were calculated and finally their confidence interval (CI) were compared to CI of standard parameters. Results: The CI for pooled means were as follows: 2.68 ± 0.32 for ejaculation volume (mL), 62.1 ± 15.88 for sperm concentration (million per milliliter), 39.4 ± 5.52 for sperm motility (%), 23.91 ± 13.43 for sperm morphology (%) and 49.53 ± 11.08 for sperm count. Conclusions: The results of this meta-analysis showed that air pollution reduces sperm motility, but has no impact on the other sperm parameters of spermogram. PMID:26023349

  18. Identification of differential pathways in papillary thyroid carcinoma utilizing pathway co-expression analysis.

    PubMed

    Qiu, Wei-Hai; Chen, Gui-Yan; Cui, Lu; Zhang, Ting-Ming; Wei, Feng; Yang, Yong

    2016-01-01

    To identify differential pathways between papillary thyroid carcinoma (PTC) patients and normal controls utilizing a novel method which combined pathway with co-expression network. The proposed method included three steps. In the first step, we conducted pretreatments for background pathways and gained representative pathways in PTC. Subsequently, a co-expression network for representative pathways was constructed using empirical Bayes (EB) approach to assign a weight value for each pathway. Finally, random model was extracted to set the thresholds of identifying differential pathways. We obtained 1267 representative pathways and their weight values based on the co-expressed pathway network, and then by meeting the criterion (Weight > 0.0296), 87 differential pathways in total across PTC patients and normal controls were identified. The top three ranked differential pathways were CREB phosphorylation, attachment of GPI anchor to urokinase plasminogen activator receptor (uPAR) and loss of function of SMAD2/3 in cancer. In conclusion, we successfully identified differential pathways (such as CREB phosphorylation, attachment of GPI anchor to uPAR and post-translational modification: synthesis of GPI-anchored proteins) for PTC using the proposed pathway co-expression method, and these pathways might be potential biomarkers for target therapy and detection of PTC.

  19. Global thermal analysis of air-air cooled motor based on thermal network

    NASA Astrophysics Data System (ADS)

    Hu, Tian; Leng, Xue; Shen, Li; Liu, Haidong

    2018-02-01

    The air-air cooled motors with high efficiency, large starting torque, strong overload capacity, low noise, small vibration and other characteristics, are widely used in different department of national industry, but its cooling structure is complex, it requires the motor thermal management technology should be high. The thermal network method is a common method to calculate the temperature field of the motor, it has the advantages of small computation time and short time consuming, it can save a lot of time in the initial design phase of the motor. The domain analysis of air-air cooled motor and its cooler was based on thermal network method, the combined thermal network model was based, the main components of motor internal and external cooler temperature were calculated and analyzed, and the temperature rise test results were compared to verify the correctness of the combined thermal network model, the calculation method can satisfy the need of engineering design, and provide a reference for the initial and optimum design of the motor.

  20. Differential Expression and Pathway Analysis in Drug-Resistant Triple-Negative Breast Cancer Cell Lines Using RNASeq Analysis.

    PubMed

    Shaheen, Safa; Fawaz, Febin; Shah, Shaheen; Büsselberg, Dietrich

    2018-06-19

    Triple-negative breast cancer (TNBC) is among the most notorious types of breast cancer, the treatment of which does not give consistent results due to the absence of the three receptors (estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) as well as high amount of molecular variability. Drug resistance also contributes to treatment unresponsiveness. We studied differentially expressed genes, their biological roles, as well as pathways from RNA-Seq datasets of two different TNBC drug-resistant cell lines of Basal B subtype SUM159 and MDA-MB-231 treated with drugs JQ1 and Dexamethasone, respectively, to elucidate the mechanism of drug resistance. RNA sequencing(RNA-Seq) data analysis was done using edgeR which is an efficient program for determining the most significant Differentially Expressed Genes (DEGs), Gene Ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. iPathway analysis was further used to obtain validated results using analysis that takes into consideration type, function, and interactions of genes in the pathway. The significant similarities and differences throw light into the molecular heterogeneity of TNBC, giving clues into the aspects that can be focused to overcome drug resistance. From this study, cytokine-cytokine receptor interaction pathway appeared to be a key factor in TNBC drug resistance.

  1. Outdoor Ambient Air Pollution and Neurodegenerative Diseases: the Neuroinflammation Hypothesis.

    PubMed

    Jayaraj, Richard L; Rodriguez, Eric A; Wang, Yi; Block, Michelle L

    2017-06-01

    Accumulating research indicates that ambient outdoor air pollution impacts the brain and may affect neurodegenerative diseases, yet the potential underlying mechanisms are poorly understood. The neuroinflammation hypothesis holds that elevation of cytokines and reactive oxygen species in the brain mediates the deleterious effects of urban air pollution on the central nervous system (CNS). Studies in human and animal research document that neuroinflammation occurs in response to several inhaled pollutants. Microglia are a prominent source of cytokines and reactive oxygen species in the brain, implicated in the progressive neuron damage in diverse neurodegenerative diseases, and activated by inhaled components of urban air pollution through both direct and indirect pathways. The MAC1-NOX2 pathway has been identified as a mechanism through which microglia respond to different forms of air pollution, suggesting a potential common deleterious pathway. Multiple direct and indirect pathways in response to air pollution exposure likely interact in concert to exert CNS effects.

  2. General aviation air traffic pattern safety analysis

    NASA Technical Reports Server (NTRS)

    Parker, L. C.

    1973-01-01

    A concept is described for evaluating the general aviation mid-air collision hazard in uncontrolled terminal airspace. Three-dimensional traffic pattern measurements were conducted at uncontrolled and controlled airports. Computer programs for data reduction, storage retrieval and statistical analysis have been developed. Initial general aviation air traffic pattern characteristics are presented. These preliminary results indicate that patterns are highly divergent from the expected standard pattern, and that pattern procedures observed can affect the ability of pilots to see and avoid each other.

  3. Pathway Distiller - multisource biological pathway consolidation

    PubMed Central

    2012-01-01

    Background One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. Methods After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. Results We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/Pathway

  4. Aircraft/Air Traffic Management Functional Analysis Model. Version 2.0; User's Guide

    NASA Technical Reports Server (NTRS)

    Etheridge, Melvin; Plugge, Joana; Retina, Nusrat

    1998-01-01

    The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) a National Aeronautics and Space Administration (NASA) contract. This document provides a guide for using the model in analysis. Those interested in making enhancements or modification to the model should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Technical Description.

  5. Application of Petri net based analysis techniques to signal transduction pathways

    PubMed Central

    Sackmann, Andrea; Heiner, Monika; Koch, Ina

    2006-01-01

    Background Signal transduction pathways are usually modelled using classical quantitative methods, which are based on ordinary differential equations (ODEs). However, some difficulties are inherent in this approach. On the one hand, the kinetic parameters involved are often unknown and have to be estimated. With increasing size and complexity of signal transduction pathways, the estimation of missing kinetic data is not possible. On the other hand, ODEs based models do not support any explicit insights into possible (signal-) flows within the network. Moreover, a huge amount of qualitative data is available due to high-throughput techniques. In order to get information on the systems behaviour, qualitative analysis techniques have been developed. Applications of the known qualitative analysis methods concern mainly metabolic networks. Petri net theory provides a variety of established analysis techniques, which are also applicable to signal transduction models. In this context special properties have to be considered and new dedicated techniques have to be designed. Methods We apply Petri net theory to model and analyse signal transduction pathways first qualitatively before continuing with quantitative analyses. This paper demonstrates how to build systematically a discrete model, which reflects provably the qualitative biological behaviour without any knowledge of kinetic parameters. The mating pheromone response pathway in Saccharomyces cerevisiae serves as case study. Results We propose an approach for model validation of signal transduction pathways based on the network structure only. For this purpose, we introduce the new notion of feasible t-invariants, which represent minimal self-contained subnets being active under a given input situation. Each of these subnets stands for a signal flow in the system. We define maximal common transition sets (MCT-sets), which can be used for t-invariant examination and net decomposition into smallest biologically

  6. Air Quality Analysis

    EPA Pesticide Factsheets

    This site provides information for air quality data analysts inside and outside EPA. Much of the information is in the form of documented analyses that support the review of the national air qualiyt standards.

  7. A novel approach to select differential pathways associated with hypertrophic cardiomyopathy based on gene co‑expression analysis.

    PubMed

    Chen, Xiao-Min; Feng, Ming-Jun; Shen, Cai-Jie; He, Bin; Du, Xian-Feng; Yu, Yi-Bo; Liu, Jing; Chu, Hui-Min

    2017-07-01

    The present study was designed to develop a novel method for identifying significant pathways associated with human hypertrophic cardiomyopathy (HCM), based on gene co‑expression analysis. The microarray dataset associated with HCM (E‑GEOD‑36961) was obtained from the European Molecular Biology Laboratory‑European Bioinformatics Institute database. Informative pathways were selected based on the Reactome pathway database and screening treatments. An empirical Bayes method was utilized to construct co‑expression networks for informative pathways, and a weight value was assigned to each pathway. Differential pathways were extracted based on weight threshold, which was calculated using a random model. In order to assess whether the co‑expression method was feasible, it was compared with traditional pathway enrichment analysis of differentially expressed genes, which were identified using the significance analysis of microarrays package. A total of 1,074 informative pathways were screened out for subsequent investigations and their weight values were also obtained. According to the threshold of weight value of 0.01057, 447 differential pathways, including folding of actin by chaperonin containing T‑complex protein 1 (CCT)/T‑complex protein 1 ring complex (TRiC), purine ribonucleoside monophosphate biosynthesis and ubiquinol biosynthesis, were obtained. Compared with traditional pathway enrichment analysis, the number of pathways obtained from the co‑expression approach was increased. The results of the present study demonstrated that this method may be useful to predict marker pathways for HCM. The pathways of folding of actin by CCT/TRiC and purine ribonucleoside monophosphate biosynthesis may provide evidence of the underlying molecular mechanisms of HCM, and offer novel therapeutic directions for HCM.

  8. Mice exposed in situ to urban air pollution exhibit pulmonary alterations in gene expression in the lipid droplet synthesis pathways.

    PubMed

    Rowan-Carroll, Andrea; Halappanavar, Sabina; Williams, Andrew; Somers, Christophers M; Yauk, Carole L

    2013-05-01

    It is clear that particulate air pollution poses a serious risk to human health; however, the underlying mechanisms are not completely understood. We investigated pulmonary transcriptional responses in mice following in-situ exposure to ambient air in a heavily industrialized urban environment. Mature C57BL/CBA male mice were caged in sheds near two working steel mills and a major highway in Hamilton, Ontario, Canada in the spring/summer of 2004. Control mice were housed in the same environment, but received only high-efficiency particle filtered air (HEPA). Whole lung tissues were collected from mice exposed for 3, 10, or for 10 weeks followed by 6 weeks recovery in the laboratory (16 weeks). DNA microarrays were used to profile changes in pulmonary gene expression. Transcriptional profiling revealed changes in the expression of genes implicated in the lipid droplet synthesis (Plin I, Dgat2, Lpl, S3-12, and Agpat2), and antioxidant defense (Ucp1) pathways in mice breathing unfiltered air. We postulate that exposure to urban air, containing an abundance of particulate matter adsorbed with polycyclic aromatic hydrocarbons, triggers lipid droplet (holding depots for lipids and malformed/excess proteins tagged for degradation) synthesis in the lungs, which may act to sequester particulates. Increased lipid droplet synthesis could lead to endogenous/stressor-induced production of reactive oxygen species and activation of antioxidant mechanisms. Further investigation into the stimulation of lipid droplet synthesis in the lung in response to air pollution and the resulting health implications is warranted. Copyright © 2013 Wiley Periodicals, Inc.

  9. Metabolomic analysis reveals altered metabolic pathways in a rat model of gastric carcinogenesis.

    PubMed

    Gu, Jinping; Hu, Xiaomin; Shao, Wei; Ji, Tianhai; Yang, Wensheng; Zhuo, Huiqin; Jin, Zeyu; Huang, Huiying; Chen, Jiacheng; Huang, Caihua; Lin, Donghai

    2016-09-13

    Gastric cancer (GC) is one of the most malignant tumors with a poor prognosis. Alterations in metabolic pathways are inextricably linked to GC progression. However, the underlying molecular mechanisms remain elusive. We performed NMR-based metabolomic analysis of sera derived from a rat model of gastric carcinogenesis, revealed significantly altered metabolic pathways correlated with the progression of gastric carcinogenesis. Rats were histologically classified into four pathological groups (gastritis, GS; low-grade gastric dysplasia, LGD; high-grade gastric dysplasia, HGD; GC) and the normal control group (CON). The metabolic profiles of the five groups were clearly distinguished from each other. Furthermore, significant inter-metabolite correlations were extracted and used to reconstruct perturbed metabolic networks associated with the four pathological stages compared with the normal stage. Then, significantly altered metabolic pathways were identified by pathway analysis. Our results showed that oxidative stress-related metabolic pathways, choline phosphorylation and fatty acid degradation were continually disturbed during gastric carcinogenesis. Moreover, amino acid metabolism was perturbed dramatically in gastric dysplasia and GC. The GC stage showed more changed metabolite levels and more altered metabolic pathways. Two activated pathways (glycolysis; glycine, serine and threonine metabolism) substantially contributed to the metabolic alterations in GC. These results lay the basis for addressing the molecular mechanisms underlying gastric carcinogenesis and extend our understanding of GC progression.

  10. Modeling the optimal central carbon metabolic pathways under feedback inhibition using flux balance analysis.

    PubMed

    De, Rajat K; Tomar, Namrata

    2012-12-01

    Metabolism is a complex process for energy production for cellular activity. It consists of a cascade of reactions that form a highly branched network in which the product of one reaction is the reactant of the next reaction. Metabolic pathways efficiently produce maximal amount of biomass while maintaining a steady-state behavior. The steady-state activity of such biochemical pathways necessarily incorporates feedback inhibition of the enzymes. This observation motivates us to incorporate feedback inhibition for modeling the optimal activity of metabolic pathways using flux balance analysis (FBA). We demonstrate the effectiveness of the methodology on a synthetic pathway with and without feedback inhibition. Similarly, for the first time, the Central Carbon Metabolic (CCM) pathways of Saccharomyces cerevisiae and Homo sapiens have been modeled and compared based on the above understanding. The optimal pathway, which maximizes the amount of the target product(s), is selected from all those obtained by the proposed method. For this, we have observed the concentration of the product inhibited enzymes of CCM pathway and its influence on its corresponding metabolite/substrate. We have also studied the concentration of the enzymes which are responsible for the synthesis of target products. We further hypothesize that an optimal pathway would opt for higher flux rate reactions. In light of these observations, we can say that an optimal pathway should have lower enzyme concentration and higher flux rates. Finally, we demonstrate the superiority of the proposed method by comparing it with the extreme pathway analysis.

  11. Graphite Web: web tool for gene set analysis exploiting pathway topology

    PubMed Central

    Sales, Gabriele; Calura, Enrica; Martini, Paolo; Romualdi, Chiara

    2013-01-01

    Graphite web is a novel web tool for pathway analyses and network visualization for gene expression data of both microarray and RNA-seq experiments. Several pathway analyses have been proposed either in the univariate or in the global and multivariate context to tackle the complexity and the interpretation of expression results. These methods can be further divided into ‘topological’ and ‘non-topological’ methods according to their ability to gain power from pathway topology. Biological pathways are, in fact, not only gene lists but can be represented through a network where genes and connections are, respectively, nodes and edges. To this day, the most used approaches are non-topological and univariate although they miss the relationship among genes. On the contrary, topological and multivariate approaches are more powerful, but difficult to be used by researchers without bioinformatic skills. Here we present Graphite web, the first public web server for pathway analysis on gene expression data that combines topological and multivariate pathway analyses with an efficient system of interactive network visualizations for easy results interpretation. Specifically, Graphite web implements five different gene set analyses on three model organisms and two pathway databases. Graphite Web is freely available at http://graphiteweb.bio.unipd.it/. PMID:23666626

  12. Transcriptome Analysis in Tardigrade Species Reveals Specific Molecular Pathways for Stress Adaptations

    PubMed Central

    Förster, Frank; Beisser, Daniela; Grohme, Markus A.; Liang, Chunguang; Mali, Brahim; Siegl, Alexander Matthias; Engelmann, Julia C.; Shkumatov, Alexander V.; Schokraie, Elham; Müller, Tobias; Schnölzer, Martina; Schill, Ralph O.; Frohme, Marcus; Dandekar, Thomas

    2012-01-01

    Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade Milnesium tardigradum were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from Hypsibius dujardini, revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for M. tardigradum are different from typical motifs known from higher animals. M. tardigradum and H. dujardini protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of M. tardigradum. These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and M. tardigradum in particular so highly stress resistant. PMID:22563243

  13. Transcriptome analysis in tardigrade species reveals specific molecular pathways for stress adaptations.

    PubMed

    Förster, Frank; Beisser, Daniela; Grohme, Markus A; Liang, Chunguang; Mali, Brahim; Siegl, Alexander Matthias; Engelmann, Julia C; Shkumatov, Alexander V; Schokraie, Elham; Müller, Tobias; Schnölzer, Martina; Schill, Ralph O; Frohme, Marcus; Dandekar, Thomas

    2012-01-01

    Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade Milnesium tardigradum were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from Hypsibius dujardini, revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for M. tardigradum are different from typical motifs known from higher animals. M. tardigradum and H. dujardini protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of M. tardigradum. These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and M. tardigradum in particular so highly stress resistant.

  14. Analysis of the NAEG model of transuranic radionuclide transport and dose

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kercher, J.R.; Anspaugh, L.R.

    We analyze the model for estimating the dose from /sup 239/Pu developed for the Nevada Applied Ecology Group (NAEG) by using sensitivity analysis and uncertainty analysis. Sensitivity analysis results suggest that the air pathway is the critical pathway for the organs receiving the highest dose. Soil concentration and the factors controlling air concentration are the most important parameters. The only organ whose dose is sensitive to parameters in the ingestion pathway is the GI tract. The air pathway accounts for 100% of the dose to lung, upper respiratory tract, and thoracic lymph nodes; and 95% of its dose via ingestion.more » Leafy vegetable ingestion accounts for 70% of the dose from the ingestion pathway regardless of organ, peeled vegetables 20%; accidental soil ingestion 5%; ingestion of beef liver 4%; beef muscle 1%. Only a handful of model parameters control the dose for any one organ. The number of important parameters is usually less than 10. Uncertainty analysis indicates that choosing a uniform distribution for the input parameters produces a lognormal distribution of the dose. The ratio of the square root of the variance to the mean is three times greater for the doses than it is for the individual parameters. As found by the sensitivity analysis, the uncertainty analysis suggests that only a few parameters control the dose for each organ. All organs have similar distributions and variance to mean ratios except for the lymph modes. 16 references, 9 figures, 13 tables.« less

  15. Traffic-related air pollution and lung cancer: A meta-analysis

    PubMed Central

    Chen, Gongbo; Wan, Xia; Yang, Gonghuan; Zou, Xiaonong

    2015-01-01

    Background We conducted a meta-analysis to evaluate the association between traffic-related air pollution and lung cancer in order to provide evidence for control of traffic-related air pollution. Methods Several databases were searched for relevant studies up to December 2013. The quality of articles obtained was evaluated by the Strengthening the Reporting of Observational Studies in Epidemiology checklist. Statistical analysis, including pooling effective sizes and confidential intervals, was performed. Results A total of 1106 records were obtained through the database and 36 studies were included in our analysis. Among the studies included, 14 evaluated the association between ambient exposure to traffic-related air pollution and lung cancer and 22 studies involved occupational exposure to air pollution among professional drivers. Twenty-two studies were marked A level regarding quality, 13 were B level, and one was C level. Exposure to nitrogen dioxide (meta-odds ratio [OR]: 1.06, 95% confidence interval [CI]: 0.99–1.13), nitrogen oxide (meta-OR: 1.04, 95% CI: 1.01–1.07), sulfur dioxide (meta-OR: 1.03, 95% CI: 1.02–1.05), and fine particulate matter (meta-OR: 1.11, 95% CI: 1.00–1.22) were positively associated with a risk of lung cancer. Occupational exposure to air pollution among professional drivers significantly increased the incidence (meta-OR: 1.27, 95% CI: 1.19–1.36) and mortality of lung cancer (meta-OR: 1.14, 95% CI: 1.04–1.26). Conclusion Exposure to traffic-related air pollution significantly increased the risk of lung cancer. PMID:26273377

  16. Pathways Involved in Sasang Constitution from Genome-Wide Analysis in a Korean Population

    PubMed Central

    Yu, Sung-Gon; Kim, Jong-Yeol; Song, Kwang Hoon

    2012-01-01

    Abstract Objective Sasang constitution (SC) medicine, a branch of Korean traditional medicine, classifies the individual into one of four constitutional types (Taeum, TE; Soeum, SE; Soyang, SY; and Taeyang, TY) based on physiologic characteristics. The authors of the current article recently reported individual genetic elements associated with SC types via genome-wide association (GWA) analysis. However, to understand the biologic mechanisms underlying constitution, a comprehensive approach that combines individual genetic effects was applied. Design Genotypes of 1222 subjects of defined constitution types were measured for 341,998 genetic loci across the entire genome. The biologic pathways associated with SC types were identified via GWA analysis using three different algorithms—namely, the Z-static method, a restandardized gene set assay, and a gene set enrichment assay. Results Distinct pathways were associated (p<0.05) with each constitution type. The TE type was significantly associated with cytoskeleton-related pathways. The SE type was significantly associated with cardio- and amino-acid metabolism–related pathways. The SY type was associated with enriched melanoma-related pathways. TY subjects were excluded because of the small size of that sample. Among these functionally related pathways, core-node genes regulating multiple pathways were identified. TJP1, PTK2, and SRC were selected as core-nodes for TE; RHOA, and MAOA/MAOB for SE; and GNAO1 for SY (p<0.05), respectively. Conclusions The current authors systematically identified the biologic pathways and core-node genes associated with SC types from the GWA study; this information should provide insights regarding the molecular mechanisms inherent in constitutional pathophysiology. PMID:22889377

  17. On-line analysis of ambient air aerosols using laser-induced breakdown spectroscopy

    NASA Astrophysics Data System (ADS)

    Carranza, J. E.; Fisher, B. T.; Yoder, G. D.; Hahn, D. W.

    2001-06-01

    Laser-induced breakdown spectroscopy is developed for the detection of aerosols in ambient air, including quantitative mass concentration measurements and size/composition measurements of individual aerosol particles. Data are reported for ambient air aerosols containing aluminum, calcium, magnesium and sodium for a 6-week sampling period spanning the Fourth of July holiday period. Measured mass concentrations for these four elements ranged from 1.7 parts per trillion (by mass) to 1.7 parts per billion. Ambient air concentrations of magnesium and aluminum revealed significant increases during the holiday period, which are concluded to arise from the discharge of fireworks in the lower atmosphere. Real-time conditional data analysis yielded increases in analyte spectral intensity approaching 3 orders of magnitude. Analysis of single particles yielded composition-based aerosol size distributions, with measured aerosol diameters ranging from 100 nm to 2 μm. The absolute mass detection limits for single particle analysis exceeded sub-femtogram values for calcium-containing particles, and was on the order of 2-3 femtograms for magnesium and sodium-based particles. Overall, LIBS-based analysis of ambient air aerosols is a promising technique for the challenging issues associated with the real-time collection and analysis of ambient air particulate matter data.

  18. Proteomic analysis reveals diverse proline hydroxylation-mediated oxygen-sensing cellular pathways in cancer cells

    PubMed Central

    Liu, Bing; Gao, Yankun; Ruan, Hai-Bin; Chen, Yue

    2016-01-01

    Proline hydroxylation is a critical cellular mechanism regulating oxygen-response pathways in tumor initiation and progression. Yet, its substrate diversity and functions remain largely unknown. Here, we report a system-wide analysis to characterize proline hydroxylation substrates in cancer cells using an immunoaffinity-purification assisted proteomics strategy. We identified 562 sites from 272 proteins in HeLa cells. Bioinformatic analysis revealed that proline hydroxylation substrates are significantly enriched with mRNA processing and stress-response cellular pathways with canonical and diverse flanking sequence motifs. Structural analysis indicates a significant enrichment of proline hydroxylation participating in the secondary structure of substrate proteins. Our study identified and validated Brd4, a key transcription factor, as a novel proline hydroxylation substrate. Functional analysis showed that the inhibition of proline hydroxylation pathway significantly reduced the proline hydroxylation abundance on Brd4 and affected Brd4-mediated transcriptional activity as well as cell proliferation in AML leukemia cells. Taken together, our study identified a broad regulatory role of proline hydroxylation in cellular oxygen-sensing pathways and revealed potentially new targets that dynamically respond to hypoxia microenvironment in tumor cells. PMID:27764789

  19. Transcriptome Pathway Analysis of Pathological and Physiological Aldosterone-Producing Human Tissues.

    PubMed

    Zhou, Junhua; Lam, Brian; Neogi, Sudeshna G; Yeo, Giles S H; Azizan, Elena A B; Brown, Morris J

    2016-12-01

    Primary aldosteronism is present in ≈10% of hypertensives. We previously performed a microarray assay on aldosterone-producing adenomas and their paired zona glomerulosa and fasciculata. Confirmation of top genes validated the study design and functional experiments of zona glomerulosa selective genes established the role of the encoded proteins in aldosterone regulation. In this study, we further analyzed our microarray data using AmiGO 2 for gene ontology enrichment and Ingenuity Pathway Analysis to identify potential biological processes and canonical pathways involved in pathological and physiological aldosterone regulation. Genes differentially regulated in aldosterone-producing adenoma and zona glomerulosa were associated with steroid metabolic processes gene ontology terms. Terms related to the Wnt signaling pathway were enriched in zona glomerulosa only. Ingenuity Pathway Analysis showed "NRF2-mediated oxidative stress response pathway" and "LPS (lipopolysaccharide)/IL-1 (interleukin-1)-mediated inhibition of RXR (retinoid X receptor) function" were affected in both aldosterone-producing adenoma and zona glomerulosa with associated genes having up to 21- and 8-fold differences, respectively. Comparing KCNJ5-mutant aldosterone-producing adenoma, zona glomerulosa, and zona fasciculata samples with wild-type samples, 138, 56, and 59 genes were differentially expressed, respectively (fold-change >2; P<0.05). ACSS3, encoding the enzyme that synthesizes acetyl-CoA, was the top gene upregulated in KCNJ5-mutant aldosterone-producing adenoma compared with wild-type. NEFM, a gene highly upregulated in zona glomerulosa, was upregulated in KCNJ5 wild-type aldosterone-producing adenomas. NR4A2, the transcription factor for aldosterone synthase, was highly expressed in zona fasciculata adjacent to a KCNJ5-mutant aldosterone-producing adenoma. Further interrogation of these genes and pathways could potentially provide further insights into the pathology of primary

  20. Large-scale integrative network-based analysis identifies common pathways disrupted by copy number alterations across cancers

    PubMed Central

    2013-01-01

    Background Many large-scale studies analyzed high-throughput genomic data to identify altered pathways essential to the development and progression of specific types of cancer. However, no previous study has been extended to provide a comprehensive analysis of pathways disrupted by copy number alterations across different human cancers. Towards this goal, we propose a network-based method to integrate copy number alteration data with human protein-protein interaction networks and pathway databases to identify pathways that are commonly disrupted in many different types of cancer. Results We applied our approach to a data set of 2,172 cancer patients across 16 different types of cancers, and discovered a set of commonly disrupted pathways, which are likely essential for tumor formation in majority of the cancers. We also identified pathways that are only disrupted in specific cancer types, providing molecular markers for different human cancers. Analysis with independent microarray gene expression datasets confirms that the commonly disrupted pathways can be used to identify patient subgroups with significantly different survival outcomes. We also provide a network view of disrupted pathways to explain how copy number alterations affect pathways that regulate cell growth, cycle, and differentiation for tumorigenesis. Conclusions In this work, we demonstrated that the network-based integrative analysis can help to identify pathways disrupted by copy number alterations across 16 types of human cancers, which are not readily identifiable by conventional overrepresentation-based and other pathway-based methods. All the results and source code are available at http://compbio.cs.umn.edu/NetPathID/. PMID:23822816

  1. Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

    PubMed

    van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

    2015-01-01

    Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

  2. Design and analysis of aluminum/air battery system for electric vehicles

    NASA Astrophysics Data System (ADS)

    Yang, Shaohua; Knickle, Harold

    Aluminum (Al)/air batteries have the potential to be used to produce power to operate cars and other vehicles. These batteries might be important on a long-term interim basis as the world passes through the transition from gasoline cars to hydrogen fuel cell cars. The Al/air battery system can generate enough energy and power for driving ranges and acceleration similar to gasoline powered cars. From our design analysis, it can be seen that the cost of aluminum as an anode can be as low as US 1.1/kg as long as the reaction product is recycled. The total fuel efficiency during the cycle process in Al/air electric vehicles (EVs) can be 15% (present stage) or 20% (projected) comparable to that of internal combustion engine vehicles (ICEs) (13%). The design battery energy density is 1300 Wh/kg (present) or 2000 Wh/kg (projected). The cost of battery system chosen to evaluate is US 30/kW (present) or US$ 29/kW (projected). Al/air EVs life-cycle analysis was conducted and compared to lead/acid and nickel metal hydride (NiMH) EVs. Only the Al/air EVs can be projected to have a travel range comparable to ICEs. From this analysis, Al/air EVs are the most promising candidates compared to ICEs in terms of travel range, purchase price, fuel cost, and life-cycle cost.

  3. Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

    PubMed Central

    Moretti, Stefano; van Leeuwen, Danitsja; Gmuender, Hans; Bonassi, Stefano; van Delft, Joost; Kleinjans, Jos; Patrone, Fioravante; Merlo, Domenico Franco

    2008-01-01

    Background In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. Results In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. Conclusion CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between

  4. Pathway Analysis of Metabolic Syndrome Using a Genome-Wide Association Study of Korea Associated Resource (KARE) Cohorts.

    PubMed

    Shim, Unjin; Kim, Han-Na; Sung, Yeon-Ah; Kim, Hyung-Lae

    2014-12-01

    Metabolic syndrome (MetS) is a complex disorder related to insulin resistance, obesity, and inflammation. Genetic and environmental factors also contribute to the development of MetS, and through genome-wide association studies (GWASs), important susceptibility loci have been identified. However, GWASs focus more on individual single-nucleotide polymorphisms (SNPs), explaining only a small portion of genetic heritability. To overcome this limitation, pathway analyses are being applied to GWAS datasets. The aim of this study is to elucidate the biological pathways involved in the pathogenesis of MetS through pathway analysis. Cohort data from the Korea Associated Resource (KARE) was used for analysis, which include 8,842 individuals (age, 52.2 ± 8.9 years; body mass index, 24.6 ± 3.2 kg/m(2)). A total of 312,121 autosomal SNPs were obtained after quality control. Pathway analysis was conducted using Meta-analysis Gene-Set Enrichment of Variant Associations (MAGENTA) to discover the biological pathways associated with MetS. In the discovery phase, SNPs from chromosome 12, including rs11066280, rs2074356, and rs12229654, were associated with MetS (p < 5 × 10(-6)), and rs11066280 satisfied the Bonferroni-corrected cutoff (unadjusted p < 1.38 × 10(-7), Bonferroni-adjusted p < 0.05). Through pathway analysis, biological pathways, including electron carrier activity, signaling by platelet-derived growth factor (PDGF), the mitogen-activated protein kinase kinase kinase cascade, PDGF binding, peroxisome proliferator-activated receptor (PPAR) signaling, and DNA repair, were associated with MetS. Through pathway analysis of MetS, pathways related with PDGF, mitogen-activated protein kinase, and PPAR signaling, as well as nucleic acid binding, protein secretion, and DNA repair, were identified. Further studies will be needed to clarify the genetic pathogenesis leading to MetS.

  5. HIGH SPEED GC/MS FOR AIR ANALYSIS

    EPA Science Inventory

    A high speed GC/MS system consisting of a gas chromatograph equipped with a narrow bandwidth injection accessory and using a time-of-flight mass spectrometer detector has been adapted for analysis of ambient whole air samples which have been collected in passivated canisters. ...

  6. Analysis of Membrane Protein Topology in the Plant Secretory Pathway.

    PubMed

    Guo, Jinya; Miao, Yansong; Cai, Yi

    2017-01-01

    Topology of membrane proteins provides important information for the understanding of protein function and intermolecular associations. Integrate membrane proteins are generally transported from endoplasmic reticulum (ER) to Golgi and downstream compartments in the plant secretory pathway. Here, we describe a simple method to study membrane protein topology along the plant secretory pathway by transiently coexpressing a fluorescent protein (XFP)-tagged membrane protein and an ER export inhibitor protein, ARF1 (T31N), in tobacco BY-2 protoplast. By fractionation, microsome isolation, and trypsin digestion, membrane protein topology could be easily detected by either direct confocal microscopy imaging or western-blot analysis using specific XFP antibodies. A similar strategy in determining membrane protein topology could be widely adopted and applied to protein analysis in a broad range of eukaryotic systems, including yeast cells and mammalian cells.

  7. A Wavelet Analysis Approach for Categorizing Air Traffic Behavior

    NASA Technical Reports Server (NTRS)

    Drew, Michael; Sheth, Kapil

    2015-01-01

    In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.

  8. Pathways to Medical Home Recognition: A Qualitative Comparative Analysis of the PCMH Transformation Process.

    PubMed

    Mendel, Peter; Chen, Emily K; Green, Harold D; Armstrong, Courtney; Timbie, Justin W; Kress, Amii M; Friedberg, Mark W; Kahn, Katherine L

    2017-12-15

    To understand the process of practice transformation by identifying pathways for attaining patient-centered medical home (PCMH) recognition. The CMS Federally Qualified Health Center (FQHC) Advanced Primary Care Practice Demonstration was designed to help FQHCs achieve NCQA Level 3 PCMH recognition and improve patient outcomes. We used a stratified random sample of 20 (out of 503) participating sites for this analysis. We developed a conceptual model of structural, cultural, and implementation factors affecting PCMH transformation based on literature and initial qualitative interview themes. We then used conventional cross-case analysis, followed by qualitative comparative analysis (QCA), a cross-case method based on Boolean logic algorithms, to systematically identify pathways (i.e., combinations of factors) associated with attaining-or not attaining-Level 3 recognition. Site-level indicators were derived from semistructured interviews with site leaders at two points in time (mid- and late-implementation) and administrative data collected prior to and during the demonstration period. The QCA results identified five distinct pathways to attaining PCMH recognition and four distinct pathways to not attaining recognition by the end of the demonstration. Across these pathways, one condition (change leader capacity) was common to all pathways for attaining recognition, and another (previous improvement or recognition experience) was absent in all pathways for not attaining recognition. In general, sites could compensate for deficiencies in one factor with capacity in others, but they needed a threshold of strengths in cultural and implementation factors to attain PCMH recognition. Future efforts at primary care transformation should take into account multiple pathways sites may pursue. Sites should be assessed on key cultural and implementation factors, in addition to structural components, in order to differentiate interventions and technical assistance. © Health

  9. Fractal Analysis of Air Pollutant Concentrations

    NASA Astrophysics Data System (ADS)

    Cortina-Januchs, M. G.; Barrón-Adame, J. M.; Vega-Corona, A.; Andina, D.

    2010-05-01

    Air pollution poses significant threats to human health and the environment throughout the developed and developing countries. This work focuses on fractal analysis of pollutant concentration in Salamanca, Mexico. The city of Salamanca has been catalogued as one of the most polluted cities in Mexico. The main causes of pollution in this city are fixed emission sources, such as chemical industry and electricity generation. Sulphur Dioxide (SO2) and Particulate Matter less than 10 micrometer in diameter (PM10) are the most important pollutants in this region. Air pollutant concentrations were investigated by applying the box counting method in time series obtained of the Automatic Environmental Monitoring Network (AEMN). One year of time series of hourly average concentrations were analyzed in order to characterize the temporal structures of SO2 and PM10.

  10. Analysis of cancer-related lncRNAs using gene ontology and KEGG pathways.

    PubMed

    Chen, Lei; Zhang, Yu-Hang; Lu, Guohui; Huang, Tao; Cai, Yu-Dong

    2017-02-01

    Cancer is a disease that involves abnormal cell growth and can invade or metastasize to other tissues. It is known that several factors are related to its initiation, proliferation, and invasiveness. Recently, it has been reported that long non-coding RNAs (lncRNAs) can participate in specific functional pathways and further regulate the biological function of cancer cells. Studies on lncRNAs are therefore helpful for uncovering the underlying mechanisms of cancer biological processes. We investigated cancer-related lncRNAs using gene ontology (GO) terms and KEGG pathway enrichment scores of neighboring genes that are co-expressed with the lncRNAs by extracting important GO terms and KEGG pathways that can help us identify cancer-related lncRNAs. The enrichment theory of GO terms and KEGG pathways was adopted to encode each lncRNA. Then, feature selection methods were employed to analyze these features and obtain the key GO terms and KEGG pathways. The analysis indicated that the extracted GO terms and KEGG pathways are closely related to several cancer associated processes, such as hormone associated pathways, energy associated pathways, and ribosome associated pathways. And they can accurately predict cancer-related lncRNAs. This study provided novel insight of how lncRNAs may affect tumorigenesis and which pathways may play important roles during it. These results could help understanding the biological mechanisms of lncRNAs and treating cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.

    PubMed

    Zhang, Chaoyang; Peng, Li; Zhang, Yaqin; Liu, Zhaoyang; Li, Wenling; Chen, Shilian; Li, Guancheng

    2017-06-01

    Liver cancer is a serious threat to public health and has fairly complicated pathogenesis. Therefore, the identification of key genes and pathways is of much importance for clarifying molecular mechanism of hepatocellular carcinoma (HCC) initiation and progression. HCC-associated gene expression dataset was downloaded from Gene Expression Omnibus database. Statistical software R was used for significance analysis of differentially expressed genes (DEGs) between liver cancer samples and normal samples. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, based on R software, were applied for the identification of pathways in which DEGs significantly enriched. Cytoscape software was for the construction of protein-protein interaction (PPI) network and module analysis to find the hub genes and key pathways. Finally, weighted correlation network analysis (WGCNA) was conducted to further screen critical gene modules with similar expression pattern and explore their biological significance. Significance analysis identified 1230 DEGs with fold change >2, including 632 significantly down-regulated DEGs and 598 significantly up-regulated DEGs. GO term enrichment analysis suggested that up-regulated DEG significantly enriched in immune response, cell adhesion, cell migration, type I interferon signaling pathway, and cell proliferation, and the down-regulated DEG mainly enriched in response to endoplasmic reticulum stress and endoplasmic reticulum unfolded protein response. KEGG pathway analysis found DEGs significantly enriched in five pathways including complement and coagulation cascades, focal adhesion, ECM-receptor interaction, antigen processing and presentation, and protein processing in endoplasmic reticulum. The top 10 hub genes in HCC were separately GMPS, ACACA, ALB, TGFB1, KRAS, ERBB2, BCL2, EGFR, STAT3, and CD8A, which resulted from PPI network. The top 3 gene interaction modules in PPI network enriched

  12. An IR Sounding-Based Analysis of the Saharan Air Layer in North Africa

    NASA Technical Reports Server (NTRS)

    Nicholls, Stephen D.; Mohr, Karen I.

    2018-01-01

    Intense daytime surface heating over barren-to-sparsely vegetated surfaces results in dry convective mixing. In the absence of external forcing such as mountain waves, the dry convection can produce a deep, well-mixed, nearly isentropic boundary layer that becomes a well-mixed residual layer in the evening. These well-mixed layers (WML) retain their unique mid-tropospheric thermal and humidity structure for several days. To detect the SAL and characterize its properties, AIRS Level 2 Ver. 6 temperature and humidity products (2003-Present) are evaluated against rawinsondes and compared to model analysis at each of the 55 rawinsonde stations in northern Africa. To distinguish WML from Saharan air layers (WMLs of Saharan origin), the detection involved a two-step process: 1) algorithm-based detection of WMLs in dry environments (less than 7 g per kilogram mixing ratio) 2) identification of Sahara air layers (SAL) by applying Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) back trajectories to determine the history of each WML. WML occurrence rates from AIRS closely resemble that from rawinsondes, yet rates from model analysis were up to 30% higher than observations in the Sahara due to model errors. Despite the overly frequent occurrence of WMLs from model analysis, HYSPLIT trajectory analysis showed that SAL occurrence rates (given a WML exists) from rawinsondes, AIRS, and model analysis were nearly identical. Although the number of WMLs varied among the data sources, the proportion of WMLs which were classified as SAL was nearly the same. The analysis of SAL bulk properties showed that AIRS and model analysis exhibited a slight warm and moist bias relative to rawinsondes in non-Saharan locations, but model analysis was notably warmer than rawinsondes and AIRS within the Sahara. The latter result is likely associated with the dearth of available data assimilated by model analysis in the Sahara. The variability of SAL thicknesses was reasonably

  13. Pathway and network-based analysis of genome-wide association studies and RT-PCR validation in polycystic ovary syndrome

    PubMed Central

    Shen, Haoran; Liang, Zhou; Zheng, Saihua; Li, Xuelian

    2017-01-01

    The purpose of this study was to identify promising candidate genes and pathways in polycystic ovary syndrome (PCOS). Microarray dataset GSE345269 obtained from the Gene Expression Omnibus database includes 7 granulosa cell samples from PCOS patients, and 3 normal granulosa cell samples. Differentially expressed genes (DEGs) were screened between PCOS and normal samples. Pathway enrichment analysis was conducted for DEGs using ClueGO and CluePedia plugin of Cytoscape. A Reactome functional interaction (FI) network of the DEGs was built using ReactomeFIViz, and then network modules were extracted, followed by pathway enrichment analysis for the modules. Expression of DEGs in granulosa cell samples was measured using quantitative RT-PCR. A total of 674 DEGs were retained, which were significantly enriched with inflammation and immune-related pathways. Eight modules were extracted from the Reactome FI network. Pathway enrichment analysis revealed significant pathways of each module: module 0, Regulation of RhoA activity and Signaling by Rho GTPases pathways shared ARHGAP4 and ARHGAP9; module 2, GlycoProtein VI-mediated activation cascade pathway was enriched with RHOG; module 3, Thromboxane A2 receptor signaling, Chemokine signaling pathway, CXCR4-mediated signaling events pathways were enriched with LYN, the hub gene of module 3. Results of RT-PCR confirmed the finding of the bioinformatic analysis that ARHGAP4, ARHGAP9, RHOG and LYN were significantly upregulated in PCOS. RhoA-related pathways, GlycoProtein VI-mediated activation cascade pathway, ARHGAP4, ARHGAP9, RHOG and LYN may be involved in the pathogenesis of PCOS. PMID:28949383

  14. Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

    PubMed

    Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

    2015-03-09

    Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

  15. Pathway-Based Factor Analysis of Gene Expression Data Produces Highly Heritable Phenotypes That Associate with Age

    PubMed Central

    Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

    2015-01-01

    Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 “pathway phenotypes” that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold (P<5.38×10−5). These phenotypes are more heritable (h2=0.32) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. PMID:25758824

  16. Critical radionuclide/critical pathway analysis for the U.S. Department of Energy's Savannah River Site.

    PubMed

    Jannik, G T

    1999-06-01

    Many different radionuclides have been released to the environment from the Savannah River Site (SRS) during the facility's operational history. However, as shown by this analysis, only a small number of the released radionuclides have been significant contributors to potential doses and risks to off-site people. This article documents the radiological critical contaminant/critical pathway analysis performed for SRS. If site missions and operations remain constant over the next 30 years, only tritium oxide releases are projected to exceed a maximally exposed individual (MEI) risk of 1.0E-06 for either the airborne or liquid pathways. The critical exposure pathways associated with site airborne releases are inhalation and vegetation consumption, whereas the critical exposure pathways associated with liquid releases are drinking water and fish consumption. For the SRS-specific, nontypical exposure pathways (i.e., recreational fishing and deer and hog hunting), cesium-137 is the critical radionuclide.

  17. Air cleaning technologies: an evidence-based analysis.

    PubMed

    2005-01-01

    cluster ion surrounds the airborne particle, and the positive and negative ions react to form hydroxyls. These hydroxyls steal the airborne particle's hydrogen atom, which creates a hole in the particle's outer protein membrane, thereby rendering it inactive. Because influenza is primarily acquired by large droplets and direct and indirect contact with an infectious person, any in-room air cleaner will have little benefit in controlling and preventing its spread. Therefore, there is no role for the Plasmacluster ion air purifier or any other in-room air cleaner in the control of the spread of influenza. Accordingly, for purposes of this review, the Medical Advisory Secretariat presents no further analysis of the Plasmacluster. The objective of the systematic review was to determine the effectiveness of in-room air cleaners with built in UVGI lights and HEPA filtration compared with those using HEPA filtration only. The Medical Advisory Secretariat searched the databases of MEDLINE, EMBASE, Cochrane Database of Systematic Reviews, INAHATA (International Network of Agencies for Health Technology Assessment), Biosis Previews, Bacteriology Abstracts, Web of Science, Dissertation Abstracts, and NIOSHTIC 2. A meta-analysis was conducted if adequate data was available from 2 or more studies and where statistical and clinical heterogeneity among studies was not an issue. Otherwise, a qualitative review was completed. The GRADE system was used to summarize the quality of the body of evidence comprised of 1 or more studies. There were no existing health technology assessments on air cleaning technology located during the literature review. The literature search yielded 59 citations of which none were retained. (ABSTRACT TRUNCATED)

  18. Genome-wide analysis of a Wnt1-regulated transcriptional network implicates neurodegenerative pathways.

    PubMed

    Wexler, Eric M; Rosen, Ezra; Lu, Daning; Osborn, Gregory E; Martin, Elizabeth; Raybould, Helen; Geschwind, Daniel H

    2011-10-04

    Wnt proteins are critical to mammalian brain development and function. The canonical Wnt signaling pathway involves the stabilization and nuclear translocation of β-catenin; however, Wnt also signals through alternative, noncanonical pathways. To gain a systems-level, genome-wide view of Wnt signaling, we analyzed Wnt1-stimulated changes in gene expression by transcriptional microarray analysis in cultured human neural progenitor (hNP) cells at multiple time points over a 72-hour time course. We observed a widespread oscillatory-like pattern of changes in gene expression, involving components of both the canonical and the noncanonical Wnt signaling pathways. A higher-order, systems-level analysis that combined independent component analysis, waveform analysis, and mutual information-based network construction revealed effects on pathways related to cell death and neurodegenerative disease. Wnt effectors were tightly clustered with presenilin1 (PSEN1) and granulin (GRN), which cause dominantly inherited forms of Alzheimer's disease and frontotemporal dementia (FTD), respectively. We further explored a potential link between Wnt1 and GRN and found that Wnt1 decreased GRN expression by hNPs. Conversely, GRN knockdown increased WNT1 expression, demonstrating that Wnt and GRN reciprocally regulate each other. Finally, we provided in vivo validation of the in vitro findings by analyzing gene expression data from individuals with FTD. These unbiased and genome-wide analyses provide evidence for a connection between Wnt signaling and the transcriptional regulation of neurodegenerative disease genes.

  19. Comprehensive gene- and pathway-based analysis of depressive symptoms in older adults.

    PubMed

    Nho, Kwangsik; Ramanan, Vijay K; Horgusluoglu, Emrin; Kim, Sungeun; Inlow, Mark H; Risacher, Shannon L; McDonald, Brenna C; Farlow, Martin R; Foroud, Tatiana M; Gao, Sujuan; Callahan, Christopher M; Hendrie, Hugh C; Niculescu, Alexander B; Saykin, Andrew J

    2015-01-01

    Depressive symptoms are common in older adults and are particularly prevalent in those with or at elevated risk for dementia. Although the heritability of depression is estimated to be substantial, single nucleotide polymorphism-based genome-wide association studies of depressive symptoms have had limited success. In this study, we performed genome-wide gene- and pathway-based analyses of depressive symptom burden. Study participants included non-Hispanic Caucasian subjects (n = 6,884) from three independent cohorts, the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Health and Retirement Study (HRS), and the Indiana Memory and Aging Study (IMAS). Gene-based meta-analysis identified genome-wide significant associations (ANGPT4 and FAM110A, q-value = 0.026; GRM7-AS3 and LRFN5, q-value = 0.042). Pathway analysis revealed enrichment of association in 105 pathways, including multiple pathways related to ERK/MAPK signaling, GSK3 signaling in bipolar disorder, cell development, and immune activation and inflammation. GRM7, ANGPT4, and LRFN5 have been previously implicated in psychiatric disorders, including the GRM7 region displaying association with major depressive disorder. The ERK/MAPK signaling pathway is a known target of antidepressant drugs and has important roles in neuronal plasticity, and GSK3 signaling has been previously implicated in Alzheimer's disease and as a promising therapeutic target for depression. Our results warrant further investigation in independent and larger cohorts and add to the growing understanding of the genetics and pathobiology of depressive symptoms in aging and neurodegenerative disorders. In particular, the genes and pathways demonstrating association with depressive symptoms may be potential therapeutic targets for these symptoms in older adults.

  20. Comprehensive detection of genes causing a phenotype using phenotype sequencing and pathway analysis.

    PubMed

    Harper, Marc; Gronenberg, Luisa; Liao, James; Lee, Christopher

    2014-01-01

    Discovering all the genetic causes of a phenotype is an important goal in functional genomics. We combine an experimental design for detecting independent genetic causes of a phenotype with a high-throughput sequencing analysis that maximizes sensitivity for comprehensively identifying them. Testing this approach on a set of 24 mutant strains generated for a metabolic phenotype with many known genetic causes, we show that this pathway-based phenotype sequencing analysis greatly improves sensitivity of detection compared with previous methods, and reveals a wide range of pathways that can cause this phenotype. We demonstrate our approach on a metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli, which is crucial to a substantial number of metabolic pathways and under renewed interest for biofuel research. Out of 2157 mutations in these strains, pathway-phenoseq discriminated just five gene groups (12 genes) as statistically significant causes of the phenotype. Experimentally, these five gene groups, and the next two high-scoring pathway-phenoseq groups, either have a clear connection to the PEP metabolite level or offer an alternative path of producing oxaloacetate (OAA), and thus clearly explain the phenotype. These high-scoring gene groups also show strong evidence of positive selection pressure, compared with strictly neutral selection in the rest of the genome.

  1. Pathway and network-based analysis of genome-wide association studies and RT-PCR validation in polycystic ovary syndrome.

    PubMed

    Shen, Haoran; Liang, Zhou; Zheng, Saihua; Li, Xuelian

    2017-11-01

    The purpose of this study was to identify promising candidate genes and pathways in polycystic ovary syndrome (PCOS). Microarray dataset GSE345269 obtained from the Gene Expression Omnibus database includes 7 granulosa cell samples from PCOS patients, and 3 normal granulosa cell samples. Differentially expressed genes (DEGs) were screened between PCOS and normal samples. Pathway enrichment analysis was conducted for DEGs using ClueGO and CluePedia plugin of Cytoscape. A Reactome functional interaction (FI) network of the DEGs was built using ReactomeFIViz, and then network modules were extracted, followed by pathway enrichment analysis for the modules. Expression of DEGs in granulosa cell samples was measured using quantitative RT-PCR. A total of 674 DEGs were retained, which were significantly enriched with inflammation and immune-related pathways. Eight modules were extracted from the Reactome FI network. Pathway enrichment analysis revealed significant pathways of each module: module 0, Regulation of RhoA activity and Signaling by Rho GTPases pathways shared ARHGAP4 and ARHGAP9; module 2, GlycoProtein VI-mediated activation cascade pathway was enriched with RHOG; module 3, Thromboxane A2 receptor signaling, Chemokine signaling pathway, CXCR4-mediated signaling events pathways were enriched with LYN, the hub gene of module 3. Results of RT-PCR confirmed the finding of the bioinformatic analysis that ARHGAP4, ARHGAP9, RHOG and LYN were significantly upregulated in PCOS. RhoA-related pathways, GlycoProtein VI-mediated activation cascade pathway, ARHGAP4, ARHGAP9, RHOG and LYN may be involved in the pathogenesis of PCOS.

  2. Enhanced recovery pathways in abdominal gynecologic surgery: a systematic review and meta-analysis.

    PubMed

    de Groot, Jeanny J A; Ament, Stephanie M C; Maessen, José M C; Dejong, Cornelis H C; Kleijnen, Jos M P; Slangen, Brigitte F M

    2016-04-01

    Enhanced recovery pathways have been widely accepted and implemented for different types of surgery. Their overall effect in abdominal gynecologic surgery is still underdetermined. A systematic review and meta-analysis were performed to provide an overview of current evidence and to examine their effect on postoperative outcomes in women undergoing open gynecologic surgery. Searches were conducted using Embase, Medline, CINAHL, and the Cochrane Library up to 27 June 2014. Reference lists were screened to identify additional studies. Studies were included if at least four individual items of an enhanced recovery pathway were described. Outcomes included length of hospital stay, complication rates, readmissions, and mortality. Quantitative analysis was limited to comparative studies. Effect sizes were presented as relative risks or as mean differences (MD) with 95% confidence intervals (CI). Thirty-one records, involving 16 observational studies, were included. Diversity in reported elements within studies was observed. Preoperative education, early oral intake, and early mobilization were included in all pathways. Five studies, with a high risk of bias, were eligible for quantitative analysis. Enhanced recovery pathways reduced primary (MD -1.57 days, 95% CI CI -2.94 to -0.20) and total (MD -3.05 days, 95% CI -4.87 to -1.23) length of hospital stay compared with traditional perioperative care, without an increase in complications, mortality or readmission rates. The available evidence based on a broad range of non-randomized studies at high risk of bias suggests that enhanced recovery pathways may reduce length of postoperative hospital stay in abdominal gynecologic surgery. © 2015 Nordic Federation of Societies of Obstetrics and Gynecology.

  3. Penalized differential pathway analysis of integrative oncogenomics studies.

    PubMed

    van Wieringen, Wessel N; van de Wiel, Mark A

    2014-04-01

    Through integration of genomic data from multiple sources, we may obtain a more accurate and complete picture of the molecular mechanisms underlying tumorigenesis. We discuss the integration of DNA copy number and mRNA gene expression data from an observational integrative genomics study involving cancer patients. The two molecular levels involved are linked through the central dogma of molecular biology. DNA copy number aberrations abound in the cancer cell. Here we investigate how these aberrations affect gene expression levels within a pathway using observational integrative genomics data of cancer patients. In particular, we aim to identify differential edges between regulatory networks of two groups involving these molecular levels. Motivated by the rate equations, the regulatory mechanism between DNA copy number aberrations and gene expression levels within a pathway is modeled by a simultaneous-equations model, for the one- and two-group case. The latter facilitates the identification of differential interactions between the two groups. Model parameters are estimated by penalized least squares using the lasso (L1) penalty to obtain a sparse pathway topology. Simulations show that the inclusion of DNA copy number data benefits the discovery of gene-gene interactions. In addition, the simulations reveal that cis-effects tend to be over-estimated in a univariate (single gene) analysis. In the application to real data from integrative oncogenomic studies we show that inclusion of prior information on the regulatory network architecture benefits the reproducibility of all edges. Furthermore, analyses of the TP53 and TGFb signaling pathways between ER+ and ER- samples from an integrative genomics breast cancer study identify reproducible differential regulatory patterns that corroborate with existing literature.

  4. Large-scale transcriptome analysis reveals arabidopsis metabolic pathways are frequently influenced by different pathogens.

    PubMed

    Jiang, Zhenhong; He, Fei; Zhang, Ziding

    2017-07-01

    Through large-scale transcriptional data analyses, we highlighted the importance of plant metabolism in plant immunity and identified 26 metabolic pathways that were frequently influenced by the infection of 14 different pathogens. Reprogramming of plant metabolism is a common phenomenon in plant defense responses. Currently, a large number of transcriptional profiles of infected tissues in Arabidopsis (Arabidopsis thaliana) have been deposited in public databases, which provides a great opportunity to understand the expression patterns of metabolic pathways during plant defense responses at the systems level. Here, we performed a large-scale transcriptome analysis based on 135 previously published expression samples, including 14 different pathogens, to explore the expression pattern of Arabidopsis metabolic pathways. Overall, metabolic genes are significantly changed in expression during plant defense responses. Upregulated metabolic genes are enriched on defense responses, and downregulated genes are enriched on photosynthesis, fatty acid and lipid metabolic processes. Gene set enrichment analysis (GSEA) identifies 26 frequently differentially expressed metabolic pathways (FreDE_Paths) that are differentially expressed in more than 60% of infected samples. These pathways are involved in the generation of energy, fatty acid and lipid metabolism as well as secondary metabolite biosynthesis. Clustering analysis based on the expression levels of these 26 metabolic pathways clearly distinguishes infected and control samples, further suggesting the importance of these metabolic pathways in plant defense responses. By comparing with FreDE_Paths from abiotic stresses, we find that the expression patterns of 26 FreDE_Paths from biotic stresses are more consistent across different infected samples. By investigating the expression correlation between transcriptional factors (TFs) and FreDE_Paths, we identify several notable relationships. Collectively, the current study

  5. Transcriptome Analysis of Manganese-deficient Chlamydomonas reinhardtii Provides Insight on the Chlorophyll Biosynthesis Pathway

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lockhart, Ainsley; Zvenigorodsky, Natasha; Pedraza, Mary Ann

    2011-08-11

    The biosynthesis of chlorophyll and other tetrapyrroles is a vital but poorly understood process. Recent genomic advances with the unicellular green algae Chlamydomonas reinhardtii have created opportunity to more closely examine the mechanisms of the chlorophyll biosynthesis pathway via transcriptome analysis. Manganese is a nutrient of interest for complex reactions because of its multiple stable oxidation states and role in molecular oxygen coordination. C. reinhardtii was cultured in Manganese-deplete Tris-acetate-phosphate (TAP) media for 24 hours and used to create cDNA libraries for sequencing using Illumina TruSeq technology. Transcriptome analysis provided intriguing insight on possible regulatory mechanisms in the pathway. Evidencemore » supports similarities of GTR (Glutamyl-tRNA synthase) to its Chlorella vulgaris homolog in terms of Mn requirements. Data was also suggestive of Mn-related compensatory up-regulation for pathway proteins CHLH1 (Manganese Chelatase), GUN4 (Magnesium chelatase activating protein), and POR1 (Light-dependent protochlorophyllide reductase). Intriguingly, data suggests possible reciprocal expression of oxygen dependent CPX1 (coproporphyrinogen III oxidase) and oxygen independent CPX2. Further analysis using RT-PCR could provide compelling evidence for several novel regulatory mechanisms in the chlorophyll biosynthesis pathway.« less

  6. Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

    PubMed Central

    Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary

    2018-01-01

    Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574

  7. Axonal guidance signaling pathway interacting with smoking in modifying the risk of pancreatic cancer: a gene- and pathway-based interaction analysis of GWAS data.

    PubMed

    Tang, Hongwei; Wei, Peng; Duell, Eric J; Risch, Harvey A; Olson, Sara H; Bueno-de-Mesquita, H Bas; Gallinger, Steven; Holly, Elizabeth A; Petersen, Gloria; Bracci, Paige M; McWilliams, Robert R; Jenab, Mazda; Riboli, Elio; Tjønneland, Anne; Boutron-Ruault, Marie Christine; Kaaks, Rudolph; Trichopoulos, Dimitrios; Panico, Salvatore; Sund, Malin; Peeters, Petra H M; Khaw, Kay-Tee; Amos, Christopher I; Li, Donghui

    2014-05-01

    Cigarette smoking is the best established modifiable risk factor for pancreatic cancer. Genetic factors that underlie smoking-related pancreatic cancer have previously not been examined at the genome-wide level. Taking advantage of the existing Genome-wide association study (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study in 2028 cases and 2109 controls to examine gene-smoking interactions at pathway/gene/single nucleotide polymorphism (SNP) level. Using the likelihood ratio test nested in logistic regression models and ingenuity pathway analysis (IPA), we examined 172 KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, 3 manually curated gene sets, 3 nicotine dependency gene ontology pathways, 17 912 genes and 468 114 SNPs. None of the individual pathway/gene/SNP showed significant interaction with smoking after adjusting for multiple comparisons. Six KEGG pathways showed nominal interactions (P < 0.05) with smoking, and the top two are the pancreatic secretion and salivary secretion pathways (major contributing genes: RAB8A, PLCB and CTRB1). Nine genes, i.e. ZBED2, EXO1, PSG2, SLC36A1, CLSTN1, MTHFSD, FAT2, IL10RB and ATXN2 had P interaction < 0.0005. Five intergenic region SNPs and two SNPs of the EVC and KCNIP4 genes had P interaction < 0.00003. In IPA analysis of genes with nominal interactions with smoking, axonal guidance signaling $$\\left(P=2.12\\times 1{0}^{-7}\\right)$$ and α-adrenergic signaling $$\\left(P=2.52\\times 1{0}^{-5}\\right)$$ genes were significantly overrepresented canonical pathways. Genes contributing to the axon guidance signaling pathway included the SLIT/ROBO signaling genes that were frequently altered in pancreatic cancer. These observations need to be confirmed in additional data set. Once confirmed, it will open a new avenue to unveiling the etiology of smoking-associated pancreatic cancer.

  8. Performance analysis of underwater pump for water-air dual-use engine

    NASA Astrophysics Data System (ADS)

    Xia, Jun; Wang, Yun; Chen, Yu

    2017-10-01

    To make water-air dual-use engine work both in air and under water, the compressor of the engine should not only meet the requirements of air flight, but also must have the ability to work underwater. To verify the performance of the compressor when the water-air dual-use engine underwater propulsion mode, the underwater pumping water model of the air compressor is simulated by commercial CFD software, and the flow field analysis is carried out. The results show that conventional air compressors have a certain ability to work in the water environment, however, the blade has a great influence on the flow, and the compressor structure also affects the pump performance. Compressor can initially take into account the two modes of water and air. In order to obtain better performance, the structure of the compressor needs further improvement and optimization.

  9. Sources of Virginia meteorological and air quality data for use in highway air quality analysis with comments on their usefulness.

    DOT National Transportation Integrated Search

    1975-01-01

    The preparation of accurate air quality analysis portions of highway environmental impact statements requires valid meteorological and air quality data. These data are needed, in part, to determine the regional and local wind patterns on which pollut...

  10. Monitoring an air pollution episode in Shenzhen by combining MODIS satellite images and the HYSPLIT model

    NASA Astrophysics Data System (ADS)

    Li, Lili; Liu, Yihong; Wang, Yunpeng

    2017-07-01

    Urban air pollution is influenced not only by local emission sources including industry and vehicles, but also greatly by regional atmospheric pollutant transportation from the surrounding areas, especially in developed city clusters, like the Pearl River Delta (PRD). Taking an air pollution episode in Shenzhen as an example, this paper investigates the occurrence and evolution of the pollution episode and identifies the transport pathways of air pollutants in Shenzhen by combining MODIS satellite images and HYSPLIT back trajectory analysis. Results show that this pollution episode is mainly caused by the local emission of pollutants in PRD and oceanic air masses under specific weather conditions.

  11. Thermal imaging for cold air flow visualisation and analysis

    NASA Astrophysics Data System (ADS)

    Grudzielanek, M.; Pflitsch, A.; Cermak, J.

    2012-04-01

    In this work we present first applications of a thermal imaging system for animated visualization and analysis of cold air flow in field studies. The development of mobile thermal imaging systems advanced very fast in the last decades. The surface temperature of objects, which is detected with long-wave infrared radiation, affords conclusions in different problems of research. Modern thermal imaging systems allow infrared picture-sequences and a following data analysis; the systems are not exclusive imaging methods like in the past. Thus, the monitoring and analysing of dynamic processes became possible. We measured the cold air flow on a sloping grassland area with standard methods (sonic anemometers and temperature loggers) plus a thermal imaging system measuring in the range from 7.5 to 14µm. To analyse the cold air with the thermal measurements, we collected the surface infrared temperatures at a projection screen, which was located in cold air flow direction, opposite the infrared (IR) camera. The intention of using a thermal imaging system for our work was: 1. to get a general idea of practicability in our problem, 2. to assess the value of the extensive and more detailed data sets and 3. to optimise visualisation. The results were very promising. Through the possibility of generating time-lapse movies of the image sequences in time scaling, processes of cold air flow, like flow waves, turbulence and general flow speed, can be directly identified. Vertical temperature gradients and near-ground inversions can be visualised very well. Time-lapse movies will be presented. The extensive data collection permits a higher spatial resolution of the data than standard methods, so that cold air flow attributes can be explored in much more detail. Time series are extracted from the IR data series, analysed statistically, and compared to data obtained using traditional systems. Finally, we assess the usefulness of the additional measurement of cold air flow with thermal

  12. Modelling and performance analysis of clinical pathways using the stochastic process algebra PEPA.

    PubMed

    Yang, Xian; Han, Rui; Guo, Yike; Bradley, Jeremy; Cox, Benita; Dickinson, Robert; Kitney, Richard

    2012-01-01

    Hospitals nowadays have to serve numerous patients with limited medical staff and equipment while maintaining healthcare quality. Clinical pathway informatics is regarded as an efficient way to solve a series of hospital challenges. To date, conventional research lacks a mathematical model to describe clinical pathways. Existing vague descriptions cannot fully capture the complexities accurately in clinical pathways and hinders the effective management and further optimization of clinical pathways. Given this motivation, this paper presents a clinical pathway management platform, the Imperial Clinical Pathway Analyzer (ICPA). By extending the stochastic model performance evaluation process algebra (PEPA), ICPA introduces a clinical-pathway-specific model: clinical pathway PEPA (CPP). ICPA can simulate stochastic behaviours of a clinical pathway by extracting information from public clinical databases and other related documents using CPP. Thus, the performance of this clinical pathway, including its throughput, resource utilisation and passage time can be quantitatively analysed. A typical clinical pathway on stroke extracted from a UK hospital is used to illustrate the effectiveness of ICPA. Three application scenarios are tested using ICPA: 1) redundant resources are identified and removed, thus the number of patients being served is maintained with less cost; 2) the patient passage time is estimated, providing the likelihood that patients can leave hospital within a specific period; 3) the maximum number of input patients are found, helping hospitals to decide whether they can serve more patients with the existing resource allocation. ICPA is an effective platform for clinical pathway management: 1) ICPA can describe a variety of components (state, activity, resource and constraints) in a clinical pathway, thus facilitating the proper understanding of complexities involved in it; 2) ICPA supports the performance analysis of clinical pathway, thereby assisting

  13. Deriving pathway maps from automated text analysis using a grammar-based approach.

    PubMed

    Olsson, Björn; Gawronska, Barbara; Erlendsson, Björn

    2006-04-01

    We demonstrate how automated text analysis can be used to support the large-scale analysis of metabolic and regulatory pathways by deriving pathway maps from textual descriptions found in the scientific literature. The main assumption is that correct syntactic analysis combined with domain-specific heuristics provides a good basis for relation extraction. Our method uses an algorithm that searches through the syntactic trees produced by a parser based on a Referent Grammar formalism, identifies relations mentioned in the sentence, and classifies them with respect to their semantic class and epistemic status (facts, counterfactuals, hypotheses). The semantic categories used in the classification are based on the relation set used in KEGG (Kyoto Encyclopedia of Genes and Genomes), so that pathway maps using KEGG notation can be automatically generated. We present the current version of the relation extraction algorithm and an evaluation based on a corpus of abstracts obtained from PubMed. The results indicate that the method is able to combine a reasonable coverage with high accuracy. We found that 61% of all sentences were parsed, and 97% of the parse trees were judged to be correct. The extraction algorithm was tested on a sample of 300 parse trees and was found to produce correct extractions in 90.5% of the cases.

  14. Environmental Assessment: General Plan-Based Environmental Impact Analysis Process, Laughlin Air Force Base

    DTIC Science & Technology

    2007-05-01

    BASED ENVIROMENTAL IMPACT ANALYSIS PROCESS LAUGHLIN AIR FORCE BASE, TEXAS AGENCY: 47th Flying Training Wing (FTW), Laughlin Air Force Base (AFB), Texas...8217\\ \\ \\ \\ \\\\ \\ ~ >(- \\ , ~ AOC01 \\ PS018 / WP002 \\ DP008 // WP006 \\ ~ ,/ ’----- -----·-------------~--/·/ LAUGHLIN AIR FORCE BASE ENVIROMENTAL RESTORATION

  15. Geostationary Coastal and Air Pollution Events (GEO-CAPE) Sensitivity Analysis Experiment

    NASA Technical Reports Server (NTRS)

    Lee, Meemong; Bowman, Kevin

    2014-01-01

    Geostationary Coastal and Air pollution Events (GEO-CAPE) is a NASA decadal survey mission to be designed to provide surface reflectance at high spectral, spatial, and temporal resolutions from a geostationary orbit necessary for studying regional-scale air quality issues and their impact on global atmospheric composition processes. GEO-CAPE's Atmospheric Science Questions explore the influence of both gases and particles on air quality, atmospheric composition, and climate. The objective of the GEO-CAPE Observing System Simulation Experiment (OSSE) is to analyze the sensitivity of ozone to the global and regional NOx emissions and improve the science impact of GEO-CAPE with respect to the global air quality. The GEO-CAPE OSSE team at Jet propulsion Laboratory has developed a comprehensive OSSE framework that can perform adjoint-sensitivity analysis for a wide range of observation scenarios and measurement qualities. This report discusses the OSSE framework and presents the sensitivity analysis results obtained from the GEO-CAPE OSSE framework for seven observation scenarios and three instrument systems.

  16. Literature mining, gene-set enrichment and pathway analysis for target identification in Behçet's disease.

    PubMed

    Wilson, Paul; Larminie, Christopher; Smith, Rona

    2016-01-01

    To use literature mining to catalogue Behçet's associated genes, and advanced computational methods to improve the understanding of the pathways and signalling mechanisms that lead to the typical clinical characteristics of Behçet's patients. To extend this technique to identify potential treatment targets for further experimental validation. Text mining methods combined with gene enrichment tools, pathway analysis and causal analysis algorithms. This approach identified 247 human genes associated with Behçet's disease and the resulting disease map, comprising 644 nodes and 19220 edges, captured important details of the relationships between these genes and their associated pathways, as described in diverse data repositories. Pathway analysis has identified how Behçet's associated genes are likely to participate in innate and adaptive immune responses. Causal analysis algorithms have identified a number of potential therapeutic strategies for further investigation. Computational methods have captured pertinent features of the prominent disease characteristics presented in Behçet's disease and have highlighted NOD2, ICOS and IL18 signalling as potential therapeutic strategies.

  17. Flux analysis of cholesterol biosynthesis in vivo reveals multiple tissue and cell-type specific pathways

    PubMed Central

    Mitsche, Matthew A; McDonald, Jeffrey G; Hobbs, Helen H; Cohen, Jonathan C

    2015-01-01

    Two parallel pathways produce cholesterol: the Bloch and Kandutsch-Russell pathways. Here we used stable isotope labeling and isotopomer analysis to trace sterol flux through the two pathways in mice. Surprisingly, no tissue used the canonical K–R pathway. Rather, a hybrid pathway was identified that we call the modified K–R (MK–R) pathway. Proportional flux through the Bloch pathway varied from 8% in preputial gland to 97% in testes, and the tissue-specificity observed in vivo was retained in cultured cells. The distribution of sterol isotopomers in plasma mirrored that of liver. Sterol depletion in cultured cells increased flux through the Bloch pathway, whereas overexpression of 24-dehydrocholesterol reductase (DHCR24) enhanced usage of the MK–R pathway. Thus, relative use of the Bloch and MK–R pathways is highly variable, tissue-specific, flux dependent, and epigenetically fixed. Maintenance of two interdigitated pathways permits production of diverse bioactive sterols that can be regulated independently of cholesterol. DOI: http://dx.doi.org/10.7554/eLife.07999.001 PMID:26114596

  18. Genome-wide association and pathway analysis of feed efficiency in pigs reveal candidate genes and pathways for residual feed intake

    PubMed Central

    Do, Duy N.; Strathe, Anders B.; Ostersen, Tage; Pant, Sameer D.; Kadarmideen, Haja N.

    2014-01-01

    Residual feed intake (RFI) is a complex trait that is economically important for livestock production; however, the genetic and biological mechanisms regulating RFI are largely unknown in pigs. Therefore, the study aimed to identify single nucleotide polymorphisms (SNPs), candidate genes and biological pathways involved in regulating RFI using Genome-wide association (GWA) and pathway analyses. A total of 596 Yorkshire boars with phenotypes for two different measures of RFI (RFI1 and 2) and 60k genotypic data was used. GWA analysis was performed using a univariate mixed model and 12 and 7 SNPs were found to be significantly associated with RFI1 and RFI2, respectively. Several genes such as xin actin-binding repeat-containing protein 2 (XIRP2),tetratricopeptide repeat domain 29 (TTC29),suppressor of glucose, autophagy associated 1 (SOGA1),MAS1,G-protein-coupled receptor (GPCR) kinase 5 (GRK5),prospero-homeobox protein 1 (PROX1),GPCR 155 (GPR155), and FYVE domain containing the 26 (ZFYVE26) were identified as putative candidates for RFI based on their genomic location in the vicinity of these SNPs. Genes located within 50 kbp of SNPs significantly associated with RFI and RFI2 (q-value ≤ 0.2) were subsequently used for pathway analyses. These analyses were performed by assigning genes to biological pathways and then testing the association of individual pathways with RFI using a Fisher’s exact test. Metabolic pathway was significantly associated with both RFIs. Other biological pathways regulating phagosome, tight junctions, olfactory transduction, and insulin secretion were significantly associated with both RFI traits when relaxed threshold for cut-off p-value was used (p ≤ 0.05). These results implied porcine RFI is regulated by multiple biological mechanisms, although the metabolic processes might be the most important. Olfactory transduction pathway controlling the perception of feed via smell, insulin pathway controlling food intake might be important

  19. Incorporating principal component analysis into air quality ...

    EPA Pesticide Factsheets

    The efficacy of standard air quality model evaluation techniques is becoming compromised as the simulation periods continue to lengthen in response to ever increasing computing capacity. Accordingly, the purpose of this paper is to demonstrate a statistical approach called Principal Component Analysis (PCA) with the intent of motivating its use by the evaluation community. One of the main objectives of PCA is to identify, through data reduction, the recurring and independent modes of variations (or signals) within a very large dataset, thereby summarizing the essential information of that dataset so that meaningful and descriptive conclusions can be made. In this demonstration, PCA is applied to a simple evaluation metric – the model bias associated with EPA's Community Multi-scale Air Quality (CMAQ) model when compared to weekly observations of sulfate (SO42−) and ammonium (NH4+) ambient air concentrations measured by the Clean Air Status and Trends Network (CASTNet). The advantages of using this technique are demonstrated as it identifies strong and systematic patterns of CMAQ model bias across a myriad of spatial and temporal scales that are neither constrained to geopolitical boundaries nor monthly/seasonal time periods (a limitation of many current studies). The technique also identifies locations (station–grid cell pairs) that are used as indicators for a more thorough diagnostic evaluation thereby hastening and facilitating understanding of the prob

  20. Kinetic Analysis of Competitive Electrocatalytic Pathways: New Insights into Hydrogen Production with Nickel Electrocatalysts

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wiedner, Eric S.; Brown, Houston J.; Helm, Monte L.

    2016-01-20

    The hydrogen production electrocatalyst Ni(PPh2NPh2)22+ (1) is capable of traversing multiple electrocatalytic pathways. When using dimethylformamidium, DMF(H)+, the mechanism of formation of H2 catalyzed by 1 changes from an ECEC to an EECC mechanism as the potential approaches the Ni(I/0) couple. Two recent electrochemical methods, current-potential analysis and foot-of-the-wave analysis (FOWA), were performed on 1 to measure the detailed chemical kinetics of the competing ECEC and EECC pathways. A sensitivity analysis was performed on the electrochemical methods using digital simulations to gain a better understanding of their strengths and limitations. Notably, chemical rate constants were significantly underestimated when not accountingmore » for electron transfer kinetics, even when electron transfer was fast enough to afford a reversible non-catalytic wave. The EECC pathway of 1 was found to be faster than the ECEC pathway under all conditions studied. Using buffered DMF: DMF(H)+ mixtures led to an increase in the catalytic rate constant (kobs) of the EECC pathway, but kobs for the ECEC pathway did not change when using buffered acid. Further kinetic analysis of the ECEC path revealed that added base increases the rate of isomerization of the exo-protonated Ni(0) isomers to the catalytically active endo-isomers, but decreases the net rate of protonation of Ni(I). FOWA on 1 did not provide accurate rate constants due to incomplete reduction of the exo-protonated Ni(I) intermediate at the foot of the wave, but FOWA could be used to estimate the reduction potential of this previously undetected intermediate. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences. Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy.« less

  1. Identification of Major Signaling Pathways in Prion Disease Progression Using Network Analysis

    PubMed Central

    Newaz, Khalique; Sriram, K.; Bera, Debajyoti

    2015-01-01

    Prion diseases are transmissible neurodegenerative diseases that arise due to conformational change of normal, cellular prion protein (PrPC) to protease-resistant isofrom (rPrPSc). Deposition of misfolded PrpSc proteins leads to an alteration of many signaling pathways that includes immunological and apoptotic pathways. As a result, this culminates in the dysfunction and death of neuronal cells. Earlier works on transcriptomic studies have revealed some affected pathways, but it is not clear which is (are) the prime network pathway(s) that change during the disease progression and how these pathways are involved in crosstalks with each other from the time of incubation to clinical death. We perform network analysis on large-scale transcriptomic data of differentially expressed genes obtained from whole brain in six different mouse strain-prion strain combination models to determine the pathways involved in prion diseases, and to understand the role of crosstalks in disease propagation. We employ a notion of differential network centrality measures on protein interaction networks to identify the potential biological pathways involved. We also propose a crosstalk ranking method based on dynamic protein interaction networks to identify the core network elements involved in crosstalk with different pathways. We identify 148 DEGs (differentially expressed genes) potentially related to the prion disease progression. Functional association of the identified genes implicates a strong involvement of immunological pathways. We extract a bow-tie structure that is potentially dysregulated in prion disease. We also propose an ODE model for the bow-tie network. Predictions related to diseased condition suggests the downregulation of the core signaling elements (PI3Ks and AKTs) of the bow-tie network. In this work, we show using transcriptomic data that the neuronal dysfunction in prion disease is strongly related to the immunological pathways. We conclude that these

  2. Cognitive Pathways: Analysis of Students' Written Texts for Science Understanding

    ERIC Educational Resources Information Center

    Grimberg, Bruna Irene; Hand, Brian

    2009-01-01

    The purpose of this study was to reconstruct writers' reasoning process as reflected in their written texts. The codes resulting from the text analysis were related to cognitive operations, ranging from simple to more sophisticated ones. The sequence of the cognitive operations as the text unfolded represents the writer's cognitive pathway at the…

  3. HIV-1 Vpr modulates macrophage metabolic pathways: a SILAC-based quantitative analysis.

    PubMed

    Barrero, Carlos A; Datta, Prasun K; Sen, Satarupa; Deshmane, Satish; Amini, Shohreh; Khalili, Kamel; Merali, Salim

    2013-01-01

    Human immunodeficiency virus type 1 encoded viral protein Vpr is essential for infection of macrophages by HIV-1. Furthermore, these macrophages are resistant to cell death and are viral reservoir. However, the impact of Vpr on the macrophage proteome is yet to be comprehended. The goal of the present study was to use a stable-isotope labeling by amino acids in cell culture (SILAC) coupled with mass spectrometry-based proteomics approach to characterize the Vpr response in macrophages. Cultured human monocytic cells, U937, were differentiated into macrophages and transduced with adenovirus construct harboring the Vpr gene. More than 600 proteins were quantified in SILAC coupled with LC-MS/MS approach, among which 136 were significantly altered upon Vpr overexpression in macrophages. Quantified proteins were selected and clustered by biological functions, pathway and network analysis using Ingenuity computational pathway analysis. The proteomic data illustrating increase in abundance of enzymes in the glycolytic pathway (pentose phosphate and pyruvate metabolism) was further validated by western blot analysis. In addition, the proteomic data demonstrate down regulation of some key mitochondrial enzymes such as glutamate dehydrogenase 2 (GLUD2), adenylate kinase 2 (AK2) and transketolase (TKT). Based on these observations we postulate that HIV-1 hijacks the macrophage glucose metabolism pathway via the Vpr-hypoxia inducible factor 1 alpha (HIF-1 alpha) axis to induce expression of hexokinase (HK), glucose-6-phosphate dehyrogenase (G6PD) and pyruvate kinase muscle type 2 (PKM2) that facilitates viral replication and biogenesis, and long-term survival of macrophages. Furthermore, dysregulation of mitochondrial glutamate metabolism in macrophages can contribute to neurodegeneration via neuroexcitotoxic mechanisms in the context of NeuroAIDS.

  4. A novel method to identify hub pathways of rheumatoid arthritis based on differential pathway networks.

    PubMed

    Wei, Shi-Tong; Sun, Yong-Hua; Zong, Shi-Hua

    2017-09-01

    The aim of the current study was to identify hub pathways of rheumatoid arthritis (RA) using a novel method based on differential pathway network (DPN) analysis. The present study proposed a DPN where protein‑protein interaction (PPI) network was integrated with pathway‑pathway interactions. Pathway data was obtained from background PPI network and the Reactome pathway database. Subsequently, pathway interactions were extracted from the pathway data by building randomized gene‑gene interactions and a weight value was assigned to each pathway interaction using Spearman correlation coefficient (SCC) to identify differential pathway interactions. Differential pathway interactions were visualized using Cytoscape to construct a DPN. Topological analysis was conducted to identify hub pathways that possessed the top 5% degree distribution of DPN. Modules of DPN were mined according to ClusterONE. A total of 855 pathways were selected to build pathway interactions. By filtrating pathway interactions of weight values >0.7, a DPN with 312 nodes and 791 edges was obtained. Topological degree analysis revealed 15 hub pathways, such as heparan sulfate/heparin‑glycosaminoglycan (HS‑GAG) degradation, HS‑GAG metabolism and keratan sulfate degradation for RA based on DPN. Furthermore, hub pathways were also important in modules, which validated the significance of hub pathways. In conclusion, the proposed method is a computationally efficient way to identify hub pathways of RA, which identified 15 hub pathways that may be potential biomarkers and provide insight to future investigation and treatment of RA.

  5. Metabolic pathway analysis and kinetic studies for production of nattokinase in Bacillus subtilis.

    PubMed

    Unrean, Pornkamol; Nguyen, Nhung H A

    2013-01-01

    We have constructed a reaction network model of Bacillus subtilis. The model was analyzed using a pathway analysis tool called elementary mode analysis (EMA). The analysis tool was used to study the network capabilities and the possible effects of altered culturing conditions on the production of a fibrinolytic enzyme, nattokinase (NK) by B. subtilis. Based on all existing metabolic pathways, the maximum theoretical yield for NK synthesis in B. subtilis under different substrates and oxygen availability was predicted and the optimal culturing condition for NK production was identified. To confirm model predictions, experiments were conducted by testing these culture conditions for their influence on NK activity. The optimal culturing conditions were then applied to batch fermentation, resulting in high NK activity. The EMA approach was also applied for engineering B. subtilis metabolism towards the most efficient pathway for NK synthesis by identifying target genes for deletion and overexpression that enable the cell to produce NK at the maximum theoretical yield. The consistency between experiments and model predictions proves the feasibility of EMA being used to rationally design culture conditions and genetic manipulations for the efficient production of desired products.

  6. Association genetics and transcriptome analysis reveal a gibberellin-responsive pathway involved in regulating photosynthesis.

    PubMed

    Xie, Jianbo; Tian, Jiaxing; Du, Qingzhang; Chen, Jinhui; Li, Ying; Yang, Xiaohui; Li, Bailian; Zhang, Deqiang

    2016-05-01

    Gibberellins (GAs) regulate a wide range of important processes in plant growth and development, including photosynthesis. However, the mechanism by which GAs regulate photosynthesis remains to be understood. Here, we used multi-gene association to investigate the effect of genes in the GA-responsive pathway, as constructed by RNA sequencing, on photosynthesis, growth, and wood property traits, in a population of 435 Populus tomentosa By analyzing changes in the transcriptome following GA treatment, we identified many key photosynthetic genes, in agreement with the observed increase in measurements of photosynthesis. Regulatory motif enrichment analysis revealed that 37 differentially expressed genes related to photosynthesis shared two essential GA-related cis-regulatory elements, the GA response element and the pyrimidine box. Thus, we constructed a GA-responsive pathway consisting of 47 genes involved in regulating photosynthesis, including GID1, RGA, GID2, MYBGa, and 37 photosynthetic differentially expressed genes. Single nucleotide polymorphism (SNP)-based association analysis showed that 142 SNPs, representing 40 candidate genes in this pathway, were significantly associated with photosynthesis, growth, and wood property traits. Epistasis analysis uncovered interactions between 310 SNP-SNP pairs from 37 genes in this pathway, revealing possible genetic interactions. Moreover, a structural gene-gene matrix based on a time-course of transcript abundances provided a better understanding of the multi-gene pathway affecting photosynthesis. The results imply a functional role for these genes in mediating photosynthesis, growth, and wood properties, demonstrating the potential of combining transcriptome-based regulatory pathway construction and genetic association approaches to detect the complex genetic networks underlying quantitative traits. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights

  7. Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis

    PubMed Central

    Zhu, Zonghao; Shen, Qiang; Zhu, Liang; Wei, Xiaokang

    2017-01-01

    The present study aimed to identify key genes and pathways associated with spinal cord injury (SCI) and subsequently investigate possible therapeutic targets for the condition. The array data of GSE20907 was downloaded from the Gene Expression Omnibus database and 24 gene chips, including 3-day, 4-day, 1-week, 2-week and 1-month post-SCI together with control propriospinal neurons, were used for the analysis. The raw data was normalized and then the differentially expressed genes (DEGs) in the (A) 2-week post-SCI group vs. control group, (B) 1-month post-SCI group vs. control group, (C) 1-month and 2-week post-SCI group vs. control group, and (D) all post-SCI groups vs. all control groups, were analyzed with a limma package. Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for DEGs were performed. Cluster analysis was performed using ClusterOne plugins. All the DEGs identified were associated with immune and inflammatory responses. Signal transducer and activator of transcription 3 (STAT3), erb-B2 receptor tyrosine kinase 4 (ERBB4) and cytochrome B-245, α polypeptide (CYBA) were in the network diagrams of (A), (C) and (D), respectively. The enrichment analysis of DEGs identified in all samples demonstrated that the DEGs were also enriched in the chemokine signaling pathway (enriched in STAT3) and the high-affinity immunoglobulin E receptor (FcεRI) signaling pathway [enriched in proto-oncogene, src family tyrosine kinase (LYN)]. Immune and inflammatory responses serve significant roles in SCI. STAT3, ERBB4 and CYBA may be key genes associated with SCI at certain stages. Furthermore, STAT3 and LYN may be involved in the development of SCI via the chemokine and FcεRI signaling pathways, respectively. PMID:28731189

  8. Air ions and mood outcomes: a review and meta-analysis

    PubMed Central

    2013-01-01

    Background Psychological effects of air ions have been reported for more than 80 years in the media and scientific literature. This study summarizes a qualitative literature review and quantitative meta-analysis, where applicable, that examines the potential effects of exposure to negative and positive air ions on psychological measures of mood and emotional state. Methods A structured literature review was conducted to identify human experimental studies published through August, 2012. Thirty-three studies (1957–2012) evaluating the effects of air ionization on depression, anxiety, mood states, and subjective feelings of mental well-being in humans were included. Five studies on negative ionization and depression (measured using a structured interview guide) were evaluated by level of exposure intensity (high vs. low) using meta-analysis. Results Consistent ionization effects were not observed for anxiety, mood, relaxation/sleep, and personal comfort. In contrast, meta-analysis results showed that negative ionization, overall, was significantly associated with lower depression ratings, with a stronger association observed at high levels of negative ion exposure (mean summary effect and 95% confidence interval (CI) following high- and low-density exposure: 14.28 (95% CI: 12.93-15.62) and 7.23 (95% CI: 2.62-11.83), respectively). The response to high-density ionization was observed in patients with seasonal or chronic depression, but an effect of low-density ionization was observed only in patients with seasonal depression. However, no relationship between the duration or frequency of ionization treatment on depression ratings was evident. Conclusions No consistent influence of positive or negative air ionization on anxiety, mood, relaxation, sleep, and personal comfort measures was observed. Negative air ionization was associated with lower depression scores particularly at the highest exposure level. Future research is needed to evaluate the biological

  9. Proteomic analysis of pancreatic cancer stem cells: Functional role of fatty acid synthesis and mevalonate pathways.

    PubMed

    Brandi, Jessica; Dando, Ilaria; Pozza, Elisa Dalla; Biondani, Giulia; Jenkins, Rosalind; Elliott, Victoria; Park, Kevin; Fanelli, Giuseppina; Zolla, Lello; Costello, Eithne; Scarpa, Aldo; Cecconi, Daniela; Palmieri, Marta

    2017-01-06

    Recently, we have shown that the secretome of pancreatic cancer stem cells (CSCs) is characterized by proteins that participate in cancer differentiation, invasion, and metastasis. However, the differentially expressed intracellular proteins that lead to the specific characteristics of pancreatic CSCs have not yet been identified, and as a consequence the deranged metabolic pathways are yet to be elucidated. To identify the modulated proteins of pancreatic CSCs, iTRAQ-based proteomic analysis was performed to compare the proteome of Panc1 CSCs and Panc1 parental cells, identifying 230 modulated proteins. Pathway analysis revealed activation of glycolysis, the pentose phosphate pathway, the pyruvate-malate cycle, and lipid metabolism as well as downregulation of the Krebs cycle, the splicesome and non-homologous end joining. These findings were supported by metabolomics and immunoblotting analysis. It was also found that inhibition of fatty acid synthase by cerulenin and of mevalonate pathways by atorvastatin have a greater anti-proliferative effect on cancer stem cells than parental cells. Taken together, these results clarify some important aspects of the metabolic network signature of pancreatic cancer stem cells, shedding light on key and novel therapeutic targets and suggesting that fatty acid synthesis and mevalonate pathways play a key role in ensuring their viability. To better understand the altered metabolic pathways of pancreatic cancer stem cells (CSCs), a comprehensive proteomic analysis and metabolite profiling investigation of Panc1 and Panc1 CSCs were carried out. The findings obtained indicate that Panc1 CSCs are characterized by upregulation of glycolysis, pentose phosphate pathway, pyruvate-malate cycle, and lipid metabolism and by downregulation of Krebs cycle, spliceosome and non-homologous end joining. Moreover, fatty acid synthesis and mevalonate pathways are shown to play a critical contribution to the survival of pancreatic cancer stem cells

  10. Air concentrations of PBDEs on in-flight airplanes and assessment of flight crew inhalation exposure.

    PubMed

    Allen, Joseph G; Sumner, Ann Louise; Nishioka, Marcia G; Vallarino, Jose; Turner, Douglas J; Saltman, Hannah K; Spengler, John D

    2013-07-01

    To address the knowledge gaps regarding inhalation exposure of flight crew to polybrominated diphenyl ethers (PBDEs) on airplanes, we measured PBDE concentrations in air samples collected in the cabin air at cruising altitudes and used Bayesian Decision Analysis (BDA) to evaluate the likelihood of inhalation exposure to result in the average daily dose (ADD) of a member of the flight crew to exceed EPA Reference Doses (RfDs), accounting for all other aircraft and non-aircraft exposures. A total of 59 air samples were collected from different aircraft and analyzed for four PBDE congeners-BDE 47, 99, 100 and 209 (a subset were also analyzed for BDE 183). For congeners with a published RfD, high estimates of ADD were calculated for all non-aircraft exposure pathways and non-inhalation exposure onboard aircraft; inhalation exposure limits were then derived based on the difference between the RfD and ADDs for all other exposure pathways. The 95th percentile measured concentrations of PBDEs in aircraft air were <1% of the derived inhalation exposure limits. Likelihood probabilities of 95th percentile exposure concentrations >1% of the defined exposure limit were zero for all congeners with published RfDs.

  11. FMM: a web server for metabolic pathway reconstruction and comparative analysis.

    PubMed

    Chou, Chih-Hung; Chang, Wen-Chi; Chiu, Chih-Min; Huang, Chih-Chang; Huang, Hsien-Da

    2009-07-01

    Synthetic Biology, a multidisciplinary field, is growing rapidly. Improving the understanding of biological systems through mimicry and producing bio-orthogonal systems with new functions are two complementary pursuits in this field. A web server called FMM (From Metabolite to Metabolite) was developed for this purpose. FMM can reconstruct metabolic pathways form one metabolite to another metabolite among different species, based mainly on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and other integrated biological databases. Novel presentation for connecting different KEGG maps is newly provided. Both local and global graphical views of the metabolic pathways are designed. FMM has many applications in Synthetic Biology and Metabolic Engineering. For example, the reconstruction of metabolic pathways to produce valuable metabolites or secondary metabolites in bacteria or yeast is a promising strategy for drug production. FMM provides a highly effective way to elucidate the genes from which species should be cloned into those microorganisms based on FMM pathway comparative analysis. Consequently, FMM is an effective tool for applications in synthetic biology to produce both drugs and biofuels. This novel and innovative resource is now freely available at http://FMM.mbc.nctu.edu.tw/.

  12. Spatial Analysis of Air Quality Monitor Data in China, Japan, and South Korea

    NASA Astrophysics Data System (ADS)

    Rohde, Robert

    2016-04-01

    In 2015, Berkeley Earth published a widely-reported study concluding that air pollution contributes to 1.6 million deaths per year in China. This presentation will provide an update on that work with additional data for China and new analysis for South Korea and Japan. In China, two years of data from more than 1500 monitoring stations allows local trends to be estimated. Preliminary review indicates a trend towards improving air quality across most of China with decreasing emissions at most major population centers. Such improvements are consistent with tightening emissions standards and the decreasing usage of coal. In addition, new spatial analysis has been applied to ~900 monitoring sites in Japan and ~120 sites in South Korea. This new analysis provides information on air quality, pollutant source distributions, and implied mortality in these countries. Finally, boundary crossing fluxes in South Korea and Japan have been used to estimate the fraction of air pollution in Japan and South Korea that has being imported from sources in China.

  13. Genetic analysis of conidiation regulatory pathways in koji-mold Aspergillus oryzae.

    PubMed

    Ogawa, Masahiro; Tokuoka, Masafumi; Jin, Feng Jie; Takahashi, Tadashi; Koyama, Yasuji

    2010-01-01

    Conidia of koji-mold Aspergillus oryzae are often used as starters in the fermented food industry. However, little is known about conidiation regulation in A. oryzae. To improve the productivity of conidia in A. oryzae, it is necessary to understand conidiation regulation in the strain. Therefore, we analyzed the conidiation regulatory system in A. oryzae using 10 kinds of conidiation regulatory gene disruptants. The phenotypes of AorfluG, AorflbA, AorflbB, AorflbC, AorflbD, AorflbE, AorbrlA, AorabaA, AorwetA, and AorfadA mutants are almost identical to those of the corresponding mutants in Aspergillus nidulans. The results indicated that the functions of conidiation regulatory genes are almost conserved between A. oryzae and A. nidulans. However, the severely reduced conidiation phenotype of the AorfluG disruptant in A. oryzae differs from the phenotype of the corresponding mutant in Aspergillus fumigatus in air-exposed culture conditions. These results suggest that A. oryzae, A. nidulans, and A. fumigatus have a G-protein signaling pathway and brlA orthologs in common, and only A. fumigatus has particular brlA activation pathways that are independent of the fluG ortholog. Furthermore, the analyses of AorflbA disruptant and AorfadA dominant-active mutants implicated that AorFadA-mediated G-protein signaling suppresses vegetative growth of A. oryzae.

  14. Analysis of MINIE2013 Explosion Air-Blast Data

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Schnurr, Julie M.; Rodgers, Arthur J.; Kim, Keehoon

    We report analysis of air-blast overpressure measurements from the MINIE2013 explosive experiments. The MINIE2013 experiment involved a series of nearly 70 near-surface (height-ofburst, HOB, ranging from -1 to +4 m) low-yield (W=2-20 kg TNT equivalent) chemical highexplosives tests that were recorded at local distances (230 m – 28.5 km). Many of the W and HOB combinations were repeated, allowing for quantification of the variability in air-blast features and corresponding yield estimates. We measured canonical signal features (peak overpressure, impulse per unit area, and positive pulse duration) from the air-blast data and compared these to existing air-blast models. Peak overpressure measurementsmore » showed good agreement with the models at close ranges but tended to attenuate more rapidly at longer range (~ 1 km), which is likely caused by upward refraction of acoustic waves due to a negative vertical gradient of sound speed. We estimated yields of the MINIE2013 explosions using the Integrated Yield Determination Tool (IYDT). Errors of the estimated yields were on average within 30% of the reported yields, and there were no significant differences in the accuracy of the IYDT predictions grouped by yield. IYDT estimates tend to be lower than ground truth yields, possibly because of reduced overpressure amplitudes by upward refraction. Finally, we report preliminary results on a development of a new parameterized air-blast waveform.« less

  15. Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures

    PubMed Central

    Foroushani, Amir B.K.; Brinkman, Fiona S.L.

    2013-01-01

    Motivation. Predominant pathway analysis approaches treat pathways as collections of individual genes and consider all pathway members as equally informative. As a result, at times spurious and misleading pathways are inappropriately identified as statistically significant, solely due to components that they share with the more relevant pathways. Results. We introduce the concept of Pathway Gene-Pair Signatures (Pathway-GPS) as pairs of genes that, as a combination, are specific to a single pathway. We devised and implemented a novel approach to pathway analysis, Signature Over-representation Analysis (SIGORA), which focuses on the statistically significant enrichment of Pathway-GPS in a user-specified gene list of interest. In a comparative evaluation of several published datasets, SIGORA outperformed traditional methods by delivering biologically more plausible and relevant results. Availability. An efficient implementation of SIGORA, as an R package with precompiled GPS data for several human and mouse pathway repositories is available for download from http://sigora.googlecode.com/svn/. PMID:24432194

  16. Migration of Beryllium via Multiple Exposure Pathways among Work Processes in Four Different Facilities

    PubMed Central

    Armstrong, Jenna L.; Day, Gregory A.; Park, Ji Young; Stefaniak, Aleksandr B.; Stanton, Marcia L.; Deubner, David C.; Kent, Michael S.; Schuler, Christine R.; Virji, M. Abbas

    2016-01-01

    Inhalation of beryllium is associated with the development of sensitization; however, dermal exposure may also be important. The primary aim of this study was to elucidate relationships among exposure pathways in four different manufacturing and finishing facilities. Secondary aims were to identify jobs with increased levels of beryllium in air, on skin, and on surfaces; identify potential discrepancies in exposure pathways, and determine if these are related to jobs with previously identified risk. Beryllium was measured in air, on cotton gloves, and on work surfaces. Summary statistics were calculated and correlations among all three measurement types were examined at the facility and job level. Exposure ranking strategies were used to identify jobs with higher exposures. The highest air, glove, and surface measurements were observed in beryllium metal production and beryllium oxide ceramics manufacturing jobs that involved hot processes and handling powders. Two finishing and distribution facilities that handle solid alloy products had lower exposures than the primary production facilities, and there were differences observed among jobs. For all facilities combined, strong correlations were found between air-surface (rp ≥ 0.77), glove-surface (rp ≥ 0.76), and air-glove measurements (rp ≥ 0.69). In jobs where higher risk of beryllium sensitization or disease has been reported, exposure levels for all three measurement types were higher than in jobs with lower risk, though they were not the highest. Some jobs with low air concentrations had higher levels of beryllium on glove and surface wipe samples, suggesting a need to further evaluate the causes of the discrepant levels. Although such correlations provide insight on where beryllium is located throughout the workplace, they cannot identify the direction of the pathways between air, surface, or skin. Ranking strategies helped to identify jobs with the highest combined air, glove, and/or surface exposures

  17. Automatic variance analysis of multistage care pathways.

    PubMed

    Li, Xiang; Liu, Haifeng; Zhang, Shilei; Mei, Jing; Xie, Guotong; Yu, Yiqin; Li, Jing; Lakshmanan, Geetika T

    2014-01-01

    A care pathway (CP) is a standardized process that consists of multiple care stages, clinical activities and their relations, aimed at ensuring and enhancing the quality of care. However, actual care may deviate from the planned CP, and analysis of these deviations can help clinicians refine the CP and reduce medical errors. In this paper, we propose a CP variance analysis method to automatically identify the deviations between actual patient traces in electronic medical records (EMR) and a multistage CP. As the care stage information is usually unavailable in EMR, we first align every trace with the CP using a hidden Markov model. From the aligned traces, we report three types of deviations for every care stage: additional activities, absent activities and violated constraints, which are identified by using the techniques of temporal logic and binomial tests. The method has been applied to a CP for the management of congestive heart failure and real world EMR, providing meaningful evidence for the further improvement of care quality.

  18. Advanced Productivity Analysis Methods for Air Traffic Control Operations.

    DOT National Transportation Integrated Search

    1976-12-01

    This report gives a description of the Air Traffic Control (ATC) productivity analysis methods developed, implemented, and refined by the Stanford Research Institute (SRI) under the sponsorship of FAA and TSC. Two models are included in the productiv...

  19. An analysis of candidates for addition to the Clean Air Act list of hazardous air pollutants.

    PubMed

    Lunder, Sonya; Woodruff, Tracey J; Axelrad, Daniel A

    2004-02-01

    There are 188 air toxics listed as hazardous air pollutants (HAPs) in the Clean Air Act (CAA), based on their potential to adversely impact public health. This paper presents several analyses performed to screen potential candidates for addition to the HAPs list. We analyzed 1086 HAPs and potential HAPs, including chemicals regulated by the state of California or with emissions reported to the Toxics Release Inventory (TRI). HAPs and potential HAPs were ranked by their emissions to air, and by toxicity-weighted (tox-wtd) emissions for cancer and noncancer, using emissions information from the TRI and toxicity information from state and federal agencies. Separate consideration was given for persistent, bioaccumulative toxins (PBTs), reproductive or developmental toxins, and chemicals under evaluation for regulation as toxic air contaminants in California. Forty-four pollutants were identified as candidate HAPs based on three ranking analyses and whether they were a PBT or a reproductive or developmental toxin. Of these, nine qualified in two or three different rankings (ammonia [NH3], copper [Cu], Cu compounds, nitric acid [HNO3], N-methyl-2-pyrrolidone, sulfuric acid [H2SO4], vanadium [V] compounds, zinc [Zn], and Zn compounds). This analysis suggests further evaluation of several pollutants for possible addition to the CAA list of HAPs.

  20. Identifying key genes, pathways and screening therapeutic agents for manganese-induced Alzheimer disease using bioinformatics analysis.

    PubMed

    Ling, JunJun; Yang, Shengyou; Huang, Yi; Wei, Dongfeng; Cheng, Weidong

    2018-06-01

    Alzheimer disease (AD) is a progressive neurodegenerative disease, the etiology of which remains largely unknown. Accumulating evidence indicates that elevated manganese (Mn) in brain exerts toxic effects on neurons and contributes to AD development. Thus, we aimed to explore the gene and pathway variations through analysis of high through-put data in this process.To screen the differentially expressed genes (DEGs) that may play critical roles in Mn-induced AD, public microarray data regarding Mn-treated neurocytes versus controls (GSE70845), and AD versus controls (GSE48350), were downloaded and the DEGs were screened out, respectively. The intersection of the DEGs of each datasets was obtained by using Venn analysis. Then, gene ontology (GO) function analysis and KEGG pathway analysis were carried out. For screening hub genes, protein-protein interaction network was constructed. At last, DEGs were analyzed in Connectivity Map (CMAP) for identification of small molecules that overcome Mn-induced neurotoxicity or AD development.The intersection of the DEGs obtained 140 upregulated and 267 downregulated genes. The top 5 items of biological processes of GO analysis were taxis, chemotaxis, cell-cell signaling, regulation of cellular physiological process, and response to wounding. The top 5 items of KEGG pathway analysis were cytokine-cytokine receptor interaction, apoptosis, oxidative phosphorylation, Toll-like receptor signaling pathway, and insulin signaling pathway. Afterwards, several hub genes such as INSR, VEGFA, PRKACB, DLG4, and BCL2 that might play key roles in Mn-induced AD were further screened out. Interestingly, tyrphostin AG-825, an inhibitor of tyrosine phosphorylation, was predicted to be a potential agent for overcoming Mn-induced neurotoxicity or AD development.The present study provided a novel insight into the molecular mechanisms of Mn-induced neurotoxicity or AD development and screened out several small molecular candidates that might be

  1. Distributional benefit analysis of a national air quality rule.

    PubMed

    Post, Ellen S; Belova, Anna; Huang, Jin

    2011-06-01

    Under Executive Order 12898, the U.S. Environmental Protection Agency (EPA) must perform environmental justice (EJ) reviews of its rules and regulations. EJ analyses address the hypothesis that environmental disamenities are experienced disproportionately by poor and/or minority subgroups. Such analyses typically use communities as the unit of analysis. While community-based approaches make sense when considering where polluting sources locate, they are less appropriate for national air quality rules affecting many sources and pollutants that can travel thousands of miles. We compare exposures and health risks of EJ-identified individuals rather than communities to analyze EPA's Heavy Duty Diesel (HDD) rule as an example national air quality rule. Air pollutant exposures are estimated within grid cells by air quality models; all individuals in the same grid cell are assigned the same exposure. Using an inequality index, we find that inequality within racial/ethnic subgroups far outweighs inequality between them. We find, moreover, that the HDD rule leaves between-subgroup inequality essentially unchanged. Changes in health risks depend also on subgroups' baseline incidence rates, which differ across subgroups. Thus, health risk reductions may not follow the same pattern as reductions in exposure. These results are likely representative of other national air quality rules as well.

  2. Parallel labeling experiments for pathway elucidation and (13)C metabolic flux analysis.

    PubMed

    Antoniewicz, Maciek R

    2015-12-01

    Metabolic pathway models provide the foundation for quantitative studies of cellular physiology through the measurement of intracellular metabolic fluxes. For model organisms metabolic models are well established, with many manually curated genome-scale model reconstructions, gene knockout studies and stable-isotope tracing studies. However, for non-model organisms a similar level of knowledge is often lacking. Compartmentation of cellular metabolism in eukaryotic systems also presents significant challenges for quantitative (13)C-metabolic flux analysis ((13)C-MFA). Recently, innovative (13)C-MFA approaches have been developed based on parallel labeling experiments, the use of multiple isotopic tracers and integrated data analysis, that allow more rigorous validation of pathway models and improved quantification of metabolic fluxes. Applications of these approaches open new research directions in metabolic engineering, biotechnology and medicine. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

    PubMed Central

    He, Yue-E; Qiu, Hui-Xian; Jiang, Jian-Bing; Wu, Rong-Zhou; Xiang, Ru-Lian; Zhang, Yuan-Hai

    2017-01-01

    The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log2 fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF

  4. Prediction of enzymatic pathways by integrative pathway mapping

    PubMed Central

    Wichelecki, Daniel J; San Francisco, Brian; Zhao, Suwen; Rodionov, Dmitry A; Vetting, Matthew W; Al-Obaidi, Nawar F; Lin, Henry; O'Meara, Matthew J; Scott, David A; Morris, John H; Russel, Daniel; Almo, Steven C; Osterman, Andrei L

    2018-01-01

    The functions of most proteins are yet to be determined. The function of an enzyme is often defined by its interacting partners, including its substrate and product, and its role in larger metabolic networks. Here, we describe a computational method that predicts the functions of orphan enzymes by organizing them into a linear metabolic pathway. Given candidate enzyme and metabolite pathway members, this aim is achieved by finding those pathways that satisfy structural and network restraints implied by varied input information, including that from virtual screening, chemoinformatics, genomic context analysis, and ligand -binding experiments. We demonstrate this integrative pathway mapping method by predicting the L-gulonate catabolic pathway in Haemophilus influenzae Rd KW20. The prediction was subsequently validated experimentally by enzymology, crystallography, and metabolomics. Integrative pathway mapping by satisfaction of structural and network restraints is extensible to molecular networks in general and thus formally bridges the gap between structural biology and systems biology. PMID:29377793

  5. N-of-1-pathways MixEnrich: advancing precision medicine via single-subject analysis in discovering dynamic changes of transcriptomes.

    PubMed

    Li, Qike; Schissler, A Grant; Gardeux, Vincent; Achour, Ikbel; Kenost, Colleen; Berghout, Joanne; Li, Haiquan; Zhang, Hao Helen; Lussier, Yves A

    2017-05-24

    Transcriptome analytic tools are commonly used across patient cohorts to develop drugs and predict clinical outcomes. However, as precision medicine pursues more accurate and individualized treatment decisions, these methods are not designed to address single-patient transcriptome analyses. We previously developed and validated the N-of-1-pathways framework using two methods, Wilcoxon and Mahalanobis Distance (MD), for personal transcriptome analysis derived from a pair of samples of a single patient. Although, both methods uncover concordantly dysregulated pathways, they are not designed to detect dysregulated pathways with up- and down-regulated genes (bidirectional dysregulation) that are ubiquitous in biological systems. We developed N-of-1-pathways MixEnrich, a mixture model followed by a gene set enrichment test, to uncover bidirectional and concordantly dysregulated pathways one patient at a time. We assess its accuracy in a comprehensive simulation study and in a RNA-Seq data analysis of head and neck squamous cell carcinomas (HNSCCs). In presence of bidirectionally dysregulated genes in the pathway or in presence of high background noise, MixEnrich substantially outperforms previous single-subject transcriptome analysis methods, both in the simulation study and the HNSCCs data analysis (ROC Curves; higher true positive rates; lower false positive rates). Bidirectional and concordant dysregulated pathways uncovered by MixEnrich in each patient largely overlapped with the quasi-gold standard compared to other single-subject and cohort-based transcriptome analyses. The greater performance of MixEnrich presents an advantage over previous methods to meet the promise of providing accurate personal transcriptome analysis to support precision medicine at point of care.

  6. Comparative Proteomics Analysis Reveals L-Arginine Activates Ethanol Degradation Pathways in HepG2 Cells.

    PubMed

    Yan, Guokai; Lestari, Retno; Long, Baisheng; Fan, Qiwen; Wang, Zhichang; Guo, Xiaozhen; Yu, Jie; Hu, Jun; Yang, Xingya; Chen, Changqing; Liu, Lu; Li, Xiuzhi; Purnomoadi, Agung; Achmadi, Joelal; Yan, Xianghua

    2016-03-17

    L-Arginine (Arg) is a versatile amino acid that plays crucial roles in a wide range of physiological and pathological processes. In this study, to investigate the alteration induced by Arg supplementation in proteome scale, isobaric tags for relative and absolute quantification (iTRAQ) based proteomic approach was employed to comparatively characterize the differentially expressed proteins between Arg deprivation (Ctrl) and Arg supplementation (+Arg) treated human liver hepatocellular carcinoma (HepG2) cells. A total of 21 proteins were identified as differentially expressed proteins and these 21 proteins were all up-regulated by Arg supplementation. Six amino acid metabolism-related proteins, mostly metabolic enzymes, showed differential expressions. Intriguingly, Ingenuity Pathway Analysis (IPA) based pathway analysis suggested that the three ethanol degradation pathways were significantly altered between Ctrl and +Arg. Western blotting and enzymatic activity assays validated that the key enzymes ADH1C, ALDH1A1, and ALDH2, which are mainly involved in ethanol degradation pathways, were highly differentially expressed, and activated between Ctrl and +Arg in HepG2 cells. Furthermore, 10 mM Arg significantly attenuated the cytotoxicity induced by 100 mM ethanol treatment (P < 0.0001). This study is the first time to reveal that Arg activates ethanol degradation pathways in HepG2 cells.

  7. An approach to market analysis for lighter than air transportation of freight

    NASA Technical Reports Server (NTRS)

    Roberts, P. O.; Marcus, H. S.; Pollock, J. H.

    1975-01-01

    An approach is presented to marketing analysis for lighter than air vehicles in a commercial freight market. After a discussion of key characteristics of supply and demand factors, a three-phase approach to marketing analysis is described. The existing transportation systems are quantitatively defined and possible roles for lighter than air vehicles within this framework are postulated. The marketing analysis views the situation from the perspective of both the shipper and the carrier. A demand for freight service is assumed and the resulting supply characteristics are determined. Then, these supply characteristics are used to establish the demand for competing modes. The process is then iterated to arrive at the market solution.

  8. Incorporating Information of microRNAs into Pathway Analysis in a Genome-Wide Association Study of Bipolar Disorder

    PubMed Central

    Shih, Wei-Liang; Kao, Chung-Feng; Chuang, Li-Chung; Kuo, Po-Hsiu

    2012-01-01

    MicroRNAs (miRNAs) are known to be important post-transcriptional regulators that are involved in the etiology of complex psychiatric traits. The present study aimed to incorporate miRNAs information into pathway analysis using a genome-wide association dataset to identify relevant biological pathways for bipolar disorder (BPD). We selected psychiatric- and neurological-associated miRNAs (N = 157) from PhenomiR database. The miRNA target genes (miTG) predictions were obtained from microRNA.org. Canonical pathways (N = 4,051) were downloaded from the Molecule Signature Database. We employed a novel weighting scheme for miTGs in pathway analysis using methods of gene set enrichment analysis and sum-statistic. Under four statistical scenarios, 38 significantly enriched pathways (P-value < 0.01 after multiple testing correction) were identified for the risk of developing BPD, including pathways of ion channels associated (e.g., gated channel activity, ion transmembrane transporter activity, and ion channel activity) and nervous related biological processes (e.g., nervous system development, cytoskeleton, and neuroactive ligand receptor interaction). Among them, 19 were identified only when the weighting scheme was applied. Many miRNA-targeted genes were functionally related to ion channels, collagen, and axonal growth and guidance that have been suggested to be associated with BPD previously. Some of these genes are linked to the regulation of miRNA machinery in the literature. Our findings provide support for the potential involvement of miRNAs in the psychopathology of BPD. Further investigations to elucidate the functions and mechanisms of identified candidate pathways are needed. PMID:23264780

  9. CAVER 3.0: A Tool for the Analysis of Transport Pathways in Dynamic Protein Structures

    PubMed Central

    Strnad, Ondrej; Brezovsky, Jan; Kozlikova, Barbora; Gora, Artur; Sustr, Vilem; Klvana, Martin; Medek, Petr; Biedermannova, Lada; Sochor, Jiri; Damborsky, Jiri

    2012-01-01

    Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz. PMID:23093919

  10. CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structures.

    PubMed

    Chovancova, Eva; Pavelka, Antonin; Benes, Petr; Strnad, Ondrej; Brezovsky, Jan; Kozlikova, Barbora; Gora, Artur; Sustr, Vilem; Klvana, Martin; Medek, Petr; Biedermannova, Lada; Sochor, Jiri; Damborsky, Jiri

    2012-01-01

    Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz.

  11. Support Air and Space Expeditionary Forces. Analysis of Combat Support Basing Options

    DTIC Science & Technology

    2004-01-01

    Mahyar A . Amouzegar, Robert S. Tripp, Ronald G. McGarve Edward W Chan C. Robert Roll, Jr. _77 Ap L_ L; Reý PROJECT AIR FORCE - Supporting Air and Space...Expeditionary Forces Analysis of Combat Support Basing Options Mahyar A . Amouzegar Robert S. Tripp Ronald G. McGarvey Edward W. Chan C. Robert Roll...support basing options / Mahyar A . Amouzegar ... [et al. p. cm. "’MG-261." Indudes bibliographical references. ISBN 0-8330-3675-0 (pbk.) 1. Air bases

  12. Drug target inference through pathway analysis of genomics data

    PubMed Central

    Ma, Haisu; Zhao, Hongyu

    2013-01-01

    Statistical modeling coupled with bioinformatics is commonly used for drug discovery. Although there exist many approaches for single target based drug design and target inference, recent years have seen a paradigm shift to system-level pharmacological research. Pathway analysis of genomics data represents one promising direction for computational inference of drug targets. This article aims at providing a comprehensive review on the evolving issues is this field, covering methodological developments, their pros and cons, as well as future research directions. PMID:23369829

  13. The Aviation System Analysis Capability Air Carrier Cost-Benefit Model

    NASA Technical Reports Server (NTRS)

    Gaier, Eric M.; Edlich, Alexander; Santmire, Tara S.; Wingrove, Earl R.., III

    1999-01-01

    To meet its objective of assisting the U.S. aviation industry with the technological challenges of the future, NASA must identify research areas that have the greatest potential for improving the operation of the air transportation system. Therefore, NASA is developing the ability to evaluate the potential impact of various advanced technologies. By thoroughly understanding the economic impact of advanced aviation technologies and by evaluating how the new technologies will be used in the integrated aviation system, NASA aims to balance its aeronautical research program and help speed the introduction of high-leverage technologies. To meet these objectives, NASA is building the Aviation System Analysis Capability (ASAC). NASA envisions ASAC primarily as a process for understanding and evaluating the impact of advanced aviation technologies on the U.S. economy. ASAC consists of a diverse collection of models and databases used by analysts and other individuals from the public and private sectors brought together to work on issues of common interest to organizations in the aviation community. ASAC also will be a resource available to the aviation community to analyze; inform; and assist scientists, engineers, analysts, and program managers in their daily work. The ASAC differs from previous NASA modeling efforts in that the economic behavior of buyers and sellers in the air transportation and aviation industries is central to its conception. Commercial air carriers, in particular, are an important stakeholder in this community. Therefore, to fully evaluate the implications of advanced aviation technologies, ASAC requires a flexible financial analysis tool that credibly links the technology of flight with the financial performance of commercial air carriers. By linking technical and financial information, NASA ensures that its technology programs will continue to benefit the user community. In addition, the analysis tool must be capable of being incorporated into the

  14. Impacts of Four SO2 Oxidation Pathways on Wintertime Sulfate Concentrations

    NASA Astrophysics Data System (ADS)

    Sarwar, G.; Fahey, K.; Zhang, Y.; Kang, D.; Mathur, R.; Xing, J.; Wei, C.; Cheng, Y.

    2017-12-01

    Air quality models tend to under-estimate winter-time sulfate concentrations compared to observed data. Such under-estimations are particularly acute in China where very high concentrations of sulfate have been measured. Sulfate is produced by oxidation of sulfur dioxide (SO2) in gas-phase by hydroxyl radical and in aqueous-phase by hydrogen peroxide, ozone, etc. and most air quality models employ such typical reactions. Several additional SO2 oxidation pathways have recently been proposed. Heterogeneous reaction on dust has been suggested to be an important sink for SO2. Oxidation of SO2 on fine particles in presence of nitrogen dioxide (NO2) and ammonia (NH3) at high relative humidity has been implicated for sulfate formation in Chinese haze and London fog. Reactive nitrogen chemistry in aerosol water has also been suggested to produce winter-time sulfate in China. Specifically, high aerosol water can trap SO2 which can be subsequently oxidized by NO2 to form sulfate. Aqueous-phase (in-cloud) oxidation of SO2 by NO2 can also produce sulfate. Here, we use the hemispheric Community Multiscale Air Quality (CMAQ) modeling system to examine the potential impacts of these SO2 oxidation pathways on sulfate formation. We use anthropogenic emissions from the Emissions Database for Global Atmospheric Research and biogenic emissions from Global Emissions InitiAtive. We performed simulations without and with these SO2 oxidation pathways for October-December of 2014 using meteorological fields obtained from the Weather Research and Forecasting model. The standard CMAQ model contains one gas-phase chemical reaction and five aqueous-phase chemical reactions for SO2 oxidation. We implement four additional SO2 oxidation pathways into the CMAQ model. Our preliminary results suggest that the dust chemistry enhances mean sulfate over parts of China and Middle-East, the in-cloud SO2 oxidation by NO2 enhances sulfate over parts of western Europe, oxidation of SO2 by NO2 and NH3 on

  15. Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis.

    PubMed

    Georgii, Elisabeth; Jin, Ming; Zhao, Jin; Kanawati, Basem; Schmitt-Kopplin, Philippe; Albert, Andreas; Winkler, J Barbro; Schäffner, Anton R

    2017-07-10

    Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response. In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways. Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome

  16. Statistical analysis of the count and profitability of air conditioners.

    PubMed

    Rady, El Houssainy A; Mohamed, Salah M; Abd Elmegaly, Alaa A

    2018-08-01

    This article presents the statistical analysis of the number and profitability of air conditioners in an Egyptian company. Checking the same distribution for each categorical variable has been made using Kruskal-Wallis test.

  17. Aviation System Analysis Capability Air Carrier Investment Model-Cargo

    NASA Technical Reports Server (NTRS)

    Johnson, Jesse; Santmire, Tara

    1999-01-01

    The purpose of the Aviation System Analysis Capability (ASAC) Air Cargo Investment Model-Cargo (ACIMC), is to examine the economic effects of technology investment on the air cargo market, particularly the market for new cargo aircraft. To do so, we have built an econometrically based model designed to operate like the ACIM. Two main drivers account for virtually all of the demand: the growth rate of the Gross Domestic Product (GDP) and changes in the fare yield (which is a proxy of the price charged or fare). These differences arise from a combination of the nature of air cargo demand and the peculiarities of the air cargo market. The net effect of these two factors are that sales of new cargo aircraft are much less sensitive to either increases in GDP or changes in the costs of labor, capital, fuel, materials, and energy associated with the production of new cargo aircraft than the sales of new passenger aircraft. This in conjunction with the relatively small size of the cargo aircraft market means technology improvements to the cargo aircraft will do relatively very little to spur increased sales of new cargo aircraft.

  18. Dry Air Cooler Modeling for Supercritical Carbon Dioxide Brayton Cycle Analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Moisseytsev, A.; Sienicki, J. J.; Lv, Q.

    Modeling for commercially available and cost effective dry air coolers such as those manufactured by Harsco Industries has been implemented in the Argonne National Laboratory Plant Dynamics Code for system level dynamic analysis of supercritical carbon dioxide (sCO 2) Brayton cycles. The modeling can now be utilized to optimize and simulate sCO 2 Brayton cycles with dry air cooling whereby heat is rejected directly to the atmospheric heat sink without the need for cooling towers that require makeup water for evaporative losses. It has sometimes been stated that a benefit of the sCO 2 Brayton cycle is that it enablesmore » dry air cooling implying that the Rankine steam cycle does not. A preliminary and simple examination of a Rankine superheated steam cycle and an air-cooled condenser indicates that dry air cooling can be utilized with both cycles provided that the cycle conditions are selected appropriately« less

  19. Climate and human intervention effects on future fire activity and consequences for air pollution across the 21st century

    NASA Astrophysics Data System (ADS)

    Val Martin, M.; Pierce, J. R.; Heald, C. L.; Li, F.; Lawrence, D. M.; Wiedinmyer, C.; Tilmes, S.; Vitt, F.

    2016-12-01

    Emissions of aerosols and gases from fires have been shown to adversely affect air quality across the world. Fire activity is strongly related to climate and anthropogenic activities. Current fire projections for the 21st century seem very uncertain, ranging from increasing to declining depending on the climate, land cover change and population growth scenarios used. Here we present an analysis of the changes in future wildfire activity and consequences on air quality, with focus on PM2.5 and surface O3 over regions vulnerable to fire. We use the global Community Earth System Model (CESM) with a process-based fire model to simulate emissions from agriculture, peatland, deforestation and landscape fires for present-day and throughout the current century. We consider two future Representative Concentration Pathways climate scenarios combined with population density changes predicted from Shared Socio-economic Pathways to project climate and demographic effects on fire activity and further consequences for future air quality.

  20. Pathway-based personalized analysis of cancer

    PubMed Central

    Drier, Yotam; Sheffer, Michal; Domany, Eytan

    2013-01-01

    We introduce Pathifier, an algorithm that infers pathway deregulation scores for each tumor sample on the basis of expression data. This score is determined, in a context-specific manner, for every particular dataset and type of cancer that is being investigated. The algorithm transforms gene-level information into pathway-level information, generating a compact and biologically relevant representation of each sample. We demonstrate the algorithm’s performance on three colorectal cancer datasets and two glioblastoma multiforme datasets and show that our multipathway-based representation is reproducible, preserves much of the original information, and allows inference of complex biologically significant information. We discovered several pathways that were significantly associated with survival of glioblastoma patients and two whose scores are predictive of survival in colorectal cancer: CXCR3-mediated signaling and oxidative phosphorylation. We also identified a subclass of proneural and neural glioblastoma with significantly better survival, and an EGF receptor-deregulated subclass of colon cancers. PMID:23547110

  1. Comparative analysis of gene expression profiles of OPN signaling pathway in four kinds of liver diseases.

    PubMed

    Wang, Gaiping; Chen, Shasha; Zhao, Congcong; Li, Xiaofang; Zhao, Weiming; Yang, Jing; Chang, Cuifang; Xu, Cunshuan

    2016-09-01

    To explore the relevance of OPN signalling pathway to the occurrence and development of nonalcoholic fatty liver disease (NAFLD), liver cirrhosis (LC), hepatic cancer (HC) and acute hepatic failure (AHF) at transcriptional level, Rat Genome 230 2.0 Array was used to detect expression profiles of OPN signalling pathway-related genes in four kinds of liver diseases. The results showed that 23, 33, 59 and 74 genes were significantly changed in the above four kinds of liver diseases, respectively. H-clustering analysis showed that the expression profiles of OPN signalling-related genes were notably different in four kinds of liver diseases. Subsequently, a total of above-mentioned 147 genes were categorized into four clusters by k-means according to the similarity of gene expression, and expression analysis systematic explorer (EASE) functional enrichment analysis revealed that OPN signalling pathway-related genes were involved in cell adhesion and migration, cell proliferation, apoptosis, stress and inflammatory reaction, etc. Finally, ingenuity pathway analysis (IPA) software was used to predict the functions of OPN signalling-related genes, and the results indicated that the activities of ROS production, cell adhesion and migration, cell proliferation were remarkably increased, while that of apoptosis, stress and inflammatory reaction were reduced in four kinds of liver diseases. In summary, the above physiological activities changed more obviously in LC, HC and AHF than in NAFLD.

  2. PaintOmics 3: a web resource for the pathway analysis and visualization of multi-omics data.

    PubMed

    Hernández-de-Diego, Rafael; Tarazona, Sonia; Martínez-Mira, Carlos; Balzano-Nogueira, Leandro; Furió-Tarí, Pedro; Pappas, Georgios J; Conesa, Ana

    2018-05-25

    The increasing availability of multi-omic platforms poses new challenges to data analysis. Joint visualization of multi-omics data is instrumental in better understanding interconnections across molecular layers and in fully utilizing the multi-omic resources available to make biological discoveries. We present here PaintOmics 3, a web-based resource for the integrated visualization of multiple omic data types onto KEGG pathway diagrams. PaintOmics 3 combines server-end capabilities for data analysis with the potential of modern web resources for data visualization, providing researchers with a powerful framework for interactive exploration of their multi-omics information. Unlike other visualization tools, PaintOmics 3 covers a comprehensive pathway analysis workflow, including automatic feature name/identifier conversion, multi-layered feature matching, pathway enrichment, network analysis, interactive heatmaps, trend charts, and more. It accepts a wide variety of omic types, including transcriptomics, proteomics and metabolomics, as well as region-based approaches such as ATAC-seq or ChIP-seq data. The tool is freely available at www.paintomics.org.

  3. An analysis of spatial representativeness of air temperature monitoring stations

    NASA Astrophysics Data System (ADS)

    Liu, Suhua; Su, Hongbo; Tian, Jing; Wang, Weizhen

    2018-05-01

    Surface air temperature is an essential variable for monitoring the atmosphere, and it is generally acquired at meteorological stations that can provide information about only a small area within an r m radius ( r-neighborhood) of the station, which is called the representable radius. In studies on a local scale, ground-based observations of surface air temperatures obtained from scattered stations are usually interpolated using a variety of methods without ascertaining their effectiveness. Thus, it is necessary to evaluate the spatial representativeness of ground-based observations of surface air temperature before conducting studies on a local scale. The present study used remote sensing data to estimate the spatial distribution of surface air temperature using the advection-energy balance for air temperature (ADEBAT) model. Two target stations in the study area were selected to conduct an analysis of spatial representativeness. The results showed that one station (AWS 7) had a representable radius of about 400 m with a possible error of less than 1 K, while the other station (AWS 16) had the radius of about 250 m. The representable radius was large when the heterogeneity of land cover around the station was small.

  4. A Simple Geotracer Compositional Correlation Analysis Reveals Oil Charge and Migration Pathways

    NASA Astrophysics Data System (ADS)

    Yang, Yunlai; Arouri, Khaled

    2016-03-01

    A novel approach, based on geotracer compositional correlation analysis is reported, which reveals the oil charge sequence and migration pathways for five oil fields in Saudi Arabia. The geotracers utilised are carbazoles, a family of neutral pyrrolic nitrogen compounds known to occur naturally in crude oils. The approach is based on the concept that closely related fields, with respect to filling sequence, will show a higher carbazole compositional correlation, than those fields that are less related. That is, carbazole compositional correlation coefficients can quantify the charge and filling relationships among different fields. Consequently, oil migration pathways can be defined based on the established filling relationships. The compositional correlation coefficients of isomers of C1 and C2 carbazoles, and benzo[a]carbazole for all different combination pairs of the five fields were found to vary extremely widely (0.28 to 0.94). A wide range of compositional correlation coefficients allows adequate differentiation of separate filling relationships. Based on the established filling relationships, three distinct migration pathways were inferred, with each apparently being charged from a different part of a common source kitchen. The recognition of these charge and migration pathways will greatly aid the search for new accumulations.

  5. A Simple Geotracer Compositional Correlation Analysis Reveals Oil Charge and Migration Pathways.

    PubMed

    Yang, Yunlai; Arouri, Khaled

    2016-03-11

    A novel approach, based on geotracer compositional correlation analysis is reported, which reveals the oil charge sequence and migration pathways for five oil fields in Saudi Arabia. The geotracers utilised are carbazoles, a family of neutral pyrrolic nitrogen compounds known to occur naturally in crude oils. The approach is based on the concept that closely related fields, with respect to filling sequence, will show a higher carbazole compositional correlation, than those fields that are less related. That is, carbazole compositional correlation coefficients can quantify the charge and filling relationships among different fields. Consequently, oil migration pathways can be defined based on the established filling relationships. The compositional correlation coefficients of isomers of C1 and C2 carbazoles, and benzo[a]carbazole for all different combination pairs of the five fields were found to vary extremely widely (0.28 to 0.94). A wide range of compositional correlation coefficients allows adequate differentiation of separate filling relationships. Based on the established filling relationships, three distinct migration pathways were inferred, with each apparently being charged from a different part of a common source kitchen. The recognition of these charge and migration pathways will greatly aid the search for new accumulations.

  6. Understanding alternative fluxes/effluxes through comparative metabolic pathway analysis of phylum actinobacteria using a simplified approach.

    PubMed

    Verma, Mansi; Lal, Devi; Saxena, Anjali; Anand, Shailly; Kaur, Jasvinder; Kaur, Jaspreet; Lal, Rup

    2013-12-01

    Actinobacteria are known for their diverse metabolism and physiology. Some are dreadful human pathogens whereas some constitute the natural flora for human gut. Therefore, the understanding of metabolic pathways is a key feature for targeting the pathogenic bacteria without disturbing the symbiotic ones. A big challenge faced today is multiple drug resistance by Mycobacterium and other pathogens that utilize alternative fluxes/effluxes. With the availability of genome sequence, it is now feasible to conduct the comparative in silico analysis. Here we present a simplified approach to compare metabolic pathways so that the species specific enzyme may be traced and engineered for future therapeutics. The analyses of four key carbohydrate metabolic pathways, i.e., glycolysis, pyruvate metabolism, tri carboxylic acid cycle and pentose phosphate pathway suggest the presence of alternative fluxes. It was found that the upper pathway of glycolysis was highly variable in the actinobacterial genomes whereas lower glycolytic pathway was highly conserved. Likewise, pentose phosphate pathway was well conserved in contradiction to TCA cycle, which was found to be incomplete in majority of actinobacteria. The clustering based on presence and absence of genes of these metabolic pathways clearly revealed that members of different genera shared identical pathways and, therefore, provided an easy method to identify the metabolic similarities/differences between pathogenic and symbiotic organisms. The analyses could identify isoenzymes and some key enzymes that were found to be missing in some pathogenic actinobacteria. The present work defines a simple approach to explore the effluxes in four metabolic pathways within the phylum actinobacteria. The analysis clearly reflects that actinobacteria exhibit diverse routes for metabolizing substrates. The pathway comparison can help in finding the enzymes that can be used as drug targets for pathogens without effecting symbiotic organisms

  7. 7. Survivable low frequency communication system pathway, looking east ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    7. Survivable low frequency communication system pathway, looking east - Ellsworth Air Force Base, Delta Flight, Launch Control Facility, County Road CS23A, North of Exit 127, Interior, Jackson County, SD

  8. Migration of Beryllium via Multiple Exposure Pathways among Work Processes in Four Different Facilities.

    PubMed

    Armstrong, Jenna L; Day, Gregory A; Park, Ji Young; Stefaniak, Aleksandr B; Stanton, Marcia L; Deubner, David C; Kent, Michael S; Schuler, Christine R; Virji, M Abbas

    2014-01-01

    Inhalation of beryllium is associated with the development of sensitization; however, dermal exposure may also be important. The primary aim of this study was to elucidate relationships among exposure pathways in four different manufacturing and finishing facilities. Secondary aims were to identify jobs with increased levels of beryllium in air, on skin, and on surfaces; identify potential discrepancies in exposure pathways, and determine if these are related to jobs with previously identified risk. Beryllium was measured in air, on cotton gloves, and on work surfaces. Summary statistics were calculated and correlations among all three measurement types were examined at the facility and job level. Exposure ranking strategies were used to identify jobs with higher exposures. The highest air, glove, and surface measurements were observed in beryllium metal production and beryllium oxide ceramics manufacturing jobs that involved hot processes and handling powders. Two finishing and distribution facilities that handle solid alloy products had lower exposures than the primary production facilities, and there were differences observed among jobs. For all facilities combined, strong correlations were found between air-surface (rp ≥ 0.77), glove-surface (rp ≥ 0.76), and air-glove measurements (rp ≥ 0.69). In jobs where higher risk of beryllium sensitization or disease has been reported, exposure levels for all three measurement types were higher than in jobs with lower risk, though they were not the highest. Some jobs with low air concentrations had higher levels of beryllium on glove and surface wipe samples, suggesting a need to further evaluate the causes of the discrepant levels. Although such correlations provide insight on where beryllium is located throughout the workplace, they cannot identify the direction of the pathways between air, surface, or skin. Ranking strategies helped to identify jobs with the highest combined air, glove, and/or surface exposures

  9. Application of uncertainty and sensitivity analysis to the air quality SHERPA modelling tool

    NASA Astrophysics Data System (ADS)

    Pisoni, E.; Albrecht, D.; Mara, T. A.; Rosati, R.; Tarantola, S.; Thunis, P.

    2018-06-01

    Air quality has significantly improved in Europe over the past few decades. Nonetheless we still find high concentrations in measurements mainly in specific regions or cities. This dimensional shift, from EU-wide to hot-spot exceedances, calls for a novel approach to regional air quality management (to complement EU-wide existing policies). The SHERPA (Screening for High Emission Reduction Potentials on Air quality) modelling tool was developed in this context. It provides an additional tool to be used in support to regional/local decision makers responsible for the design of air quality plans. It is therefore important to evaluate the quality of the SHERPA model, and its behavior in the face of various kinds of uncertainty. Uncertainty and sensitivity analysis techniques can be used for this purpose. They both reveal the links between assumptions and forecasts, help in-model simplification and may highlight unexpected relationships between inputs and outputs. Thus, a policy steered SHERPA module - predicting air quality improvement linked to emission reduction scenarios - was evaluated by means of (1) uncertainty analysis (UA) to quantify uncertainty in the model output, and (2) by sensitivity analysis (SA) to identify the most influential input sources of this uncertainty. The results of this study provide relevant information about the key variables driving the SHERPA output uncertainty, and advise policy-makers and modellers where to place their efforts for an improved decision-making process.

  10. Pitching stability analysis of half-rotating wing air vehicle

    NASA Astrophysics Data System (ADS)

    Wang, Xiaoyi; Wu, Yang; Li, Qian; Li, Congmin; Qiu, Zhizhen

    2017-06-01

    Half-Rotating Wing (HRW) is a new power wing which had been developed by our work team using rotating-type flapping instead of oscillating-type flapping. Half-Rotating Wing Air Vehicle (HRWAV) is similar as Bionic Flapping Wing Air Vehicle (BFWAV). It is necessary to guarantee pitching stability of HRWAV to maintain flight stability. The working principle of HRW was firstly introduced in this paper. The rule of motion indicated that the fuselage of HRWAV without empennage would overturn forward as it generated increased pitching movement. Therefore, the empennage was added on the tail of HRWAV to balance the additional moment generated by aerodynamic force during flight. The stability analysis further shows that empennage could weaken rapidly the pitching disturbance on HRWAV and a new balance of fuselage could be achieved in a short time. Case study using numerical analysis verified correctness and validity of research results mentioned above, which could provide theoretical guidance to design and control HRWAV.

  11. Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes.

    PubMed

    King, Paula; Pham, Long K; Waltz, Shannon; Sphar, Dan; Yamamoto, Robert T; Conrad, Douglas; Taplitz, Randy; Torriani, Francesca; Forsyth, R Allyn

    2016-01-01

    We describe the sampling of sixty-three uncultured hospital air samples collected over a six-month period and analysis using shotgun metagenomic sequencing. Our primary goals were to determine the longitudinal metagenomic variability of this environment, identify and characterize genomes of potential pathogens and determine whether they are atypical to the hospital airborne metagenome. Air samples were collected from eight locations which included patient wards, the main lobby and outside. The resulting DNA libraries produced 972 million sequences representing 51 gigabases. Hierarchical clustering of samples by the most abundant 50 microbial orders generated three major nodes which primarily clustered by type of location. Because the indoor locations were longitudinally consistent, episodic relative increases in microbial genomic signatures related to the opportunistic pathogens Aspergillus, Penicillium and Stenotrophomonas were identified as outliers at specific locations. Further analysis of microbial reads specific for Stenotrophomonas maltophilia indicated homology to a sequenced multi-drug resistant clinical strain and we observed broad sequence coverage of resistance genes. We demonstrate that a shotgun metagenomic sequencing approach can be used to characterize the resistance determinants of pathogen genomes that are uncharacteristic for an otherwise consistent hospital air microbial metagenomic profile.

  12. Benchmarking pathway interaction network for colorectal cancer to identify dysregulated pathways.

    PubMed

    Wang, Q; Shi, C-J; Lv, S-H

    2017-03-30

    Different pathways act synergistically to participate in many biological processes. Thus, the purpose of our study was to extract dysregulated pathways to investigate the pathogenesis of colorectal cancer (CRC) based on the functional dependency among pathways. Protein-protein interaction (PPI) information and pathway data were retrieved from STRING and Reactome databases, respectively. After genes were aligned to the pathways, each pathway activity was calculated using the principal component analysis (PCA) method, and the seed pathway was discovered. Subsequently, we constructed the pathway interaction network (PIN), where each node represented a biological pathway based on gene expression profile, PPI data, as well as pathways. Dysregulated pathways were then selected from the PIN according to classification performance and seed pathway. A PIN including 11,960 interactions was constructed to identify dysregulated pathways. Interestingly, the interaction of mRNA splicing and mRNA splicing-major pathway had the highest score of 719.8167. Maximum change of the activity score between CRC and normal samples appeared in the pathway of DNA replication, which was selected as the seed pathway. Starting with this seed pathway, a pathway set containing 30 dysregulated pathways was obtained with an area under the curve score of 0.8598. The pathway of mRNA splicing, mRNA splicing-major pathway, and RNA polymerase I had the maximum genes of 107. Moreover, we found that these 30 pathways had crosstalks with each other. The results suggest that these dysregulated pathways might be used as biomarkers to diagnose CRC.

  13. Space-Time Analysis of the Air Quality Model Evaluation International Initiative (AQMEII) Phase 1 Air Quality Simulations

    EPA Science Inventory

    This study presents an evaluation of summertime daily maximum ozone concentrations over North America (NA) and Europe (EU) using the database generated during Phase 1 of the Air Quality Model Evaluation International Initiative (AQMEII). The analysis focuses on identifying tempor...

  14. Hanford Site Composite Analysis Technical Approach Description: Groundwater Pathway Dose Calculation.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Morgans, D. L.; Lindberg, S. L.

    The purpose of this technical approach document (TAD) is to document the assumptions, equations, and methods used to perform the groundwater pathway radiological dose calculations for the revised Hanford Site Composite Analysis (CA). DOE M 435.1-1, states, “The composite analysis results shall be used for planning, radiation protection activities, and future use commitments to minimize the likelihood that current low-level waste disposal activities will result in the need for future corrective or remedial actions to adequately protect the public and the environment.”

  15. Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma

    PubMed Central

    Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

    2014-01-01

    Background Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. Principal Findings In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Conclusions Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers. PMID:24988079

  16. Integrated analysis of mutation data from various sources identifies key genes and signaling pathways in hepatocellular carcinoma.

    PubMed

    Zhang, Yuannv; Qiu, Zhaoping; Wei, Lin; Tang, Ruqi; Lian, Baofeng; Zhao, Yingjun; He, Xianghuo; Xie, Lu

    2014-01-01

    Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers.

  17. Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer

    PubMed Central

    Duell, Eric J.; Yu, Kai; Risch, Harvey A.; Olson, Sara H.; Kooperberg, Charles; Wolpin, Brian M.; Jiao, Li; Dong, Xiaoqun; Wheeler, Bill; Arslan, Alan A.; Bueno-de-Mesquita, H. Bas; Fuchs, Charles S.; Gallinger, Steven; Gross, Myron; Hartge, Patricia; Hoover, Robert N.; Holly, Elizabeth A.; Jacobs, Eric J.; Klein, Alison P.; LaCroix, Andrea; Mandelson, Margaret T.; Petersen, Gloria; Zheng, Wei; Agalliu, Ilir; Albanes, Demetrius; Boutron-Ruault, Marie-Christine; Bracci, Paige M.; Buring, Julie E.; Canzian, Federico; Chang, Kenneth; Chanock, Stephen J.; Cotterchio, Michelle; Gaziano, J.Michael; Giovannucci, Edward L.; Goggins, Michael; Hallmans, Göran; Hankinson, Susan E.; Hoffman Bolton, Judith A.; Hunter, David J.; Hutchinson, Amy; Jacobs, Kevin B.; Jenab, Mazda; Khaw, Kay-Tee; Kraft, Peter; Krogh, Vittorio; Kurtz, Robert C.; McWilliams, Robert R.; Mendelsohn, Julie B.; Patel, Alpa V.; Rabe, Kari G.; Riboli, Elio; Shu, Xiao-Ou; Tjønneland, Anne; Tobias, Geoffrey S.; Trichopoulos, Dimitrios; Virtamo, Jarmo; Visvanathan, Kala; Watters, Joanne; Yu, Herbert; Zeleniuch-Jacquotte, Anne; Stolzenberg-Solomon, Rachael Z.

    2012-01-01

    Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case–control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10−6, 1.6 × 10−5, 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10−5), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H. pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer. PMID:22523087

  18. Data characteristic analysis of air conditioning load based on fast Fourier transform

    NASA Astrophysics Data System (ADS)

    Li, Min; Zhang, Yanchi; Xie, Da

    2018-04-01

    With the development of economy and the improvement of people's living standards, air conditioning equipment is more and more popular. The influence of air conditioning load for power grid is becoming more and more serious. In this context it is necessary to study the characteristics of air conditioning load. This paper analyzes the data of air conditioning power consumption in an office building. The data is used for Fast Fourier Transform by data analysis software. Then a series of maps are drawn for the transformed data. The characteristics of each map were analyzed separately. The hidden rules of these data are mined from the angle of frequency domain. And these rules are hard to find in the time domain.

  19. A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data

    PubMed Central

    Chen, Yi-Hau

    2017-01-01

    Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https

  20. A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data.

    PubMed

    Lai, En-Yu; Chen, Yi-Hau; Wu, Kun-Pin

    2017-06-01

    Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https

  1. Analysis of PIK3CA Mutations and Activation Pathways in Triple Negative Breast Cancer.

    PubMed

    Cossu-Rocca, Paolo; Orrù, Sandra; Muroni, Maria Rosaria; Sanges, Francesca; Sotgiu, Giovanni; Ena, Sara; Pira, Giovanna; Murgia, Luciano; Manca, Alessandra; Uras, Maria Gabriela; Sarobba, Maria Giuseppina; Urru, Silvana; De Miglio, Maria Rosaria

    2015-01-01

    Triple Negative Breast Cancer (TNBC) accounts for 12-24% of all breast carcinomas, and shows worse prognosis compared to other breast cancer subtypes. Molecular studies demonstrated that TNBCs are a heterogeneous group of tumors with different clinical and pathologic features, prognosis, genetic-molecular alterations and treatment responsivity. The PI3K/AKT is a major pathway involved in the regulation of cell survival and proliferation, and is the most frequently altered pathway in breast cancer, apparently with different biologic impact on specific cancer subtypes. The most common genetic abnormality is represented by PIK3CA gene activating mutations, with an overall frequency of 20-40%. The aims of our study were to investigate PIK3CA gene mutations on a large series of TNBC, to perform a wider analysis on genetic alterations involving PI3K/AKT and BRAF/RAS/MAPK pathways and to correlate the results with clinical-pathologic data. PIK3CA mutation analysis was performed by using cobas® PIK3CA Mutation Test. EGFR, AKT1, BRAF, and KRAS genes were analyzed by sequencing. Immunohistochemistry was carried out to identify PTEN loss and to investigate for PI3K/AKT pathways components. PIK3CA mutations were detected in 23.7% of TNBC, whereas no mutations were identified in EGFR, AKT1, BRAF, and KRAS genes. Moreover, we observed PTEN loss in 11.3% of tumors. Deregulation of PI3K/AKT pathways was revealed by consistent activation of pAKT and p-p44/42 MAPK in all PIK3CA mutated TNBC. Our data shows that PIK3CA mutations and PI3K/AKT pathway activation are common events in TNBC. A deeper investigation on specific TNBC genomic abnormalities might be helpful in order to select patients who would benefit from current targeted therapy strategies.

  2. Cargo Logistics Airlift Systems Study (CLASS). Volume 1: Analysis of current air cargo system

    NASA Technical Reports Server (NTRS)

    Burby, R. J.; Kuhlman, W. H.

    1978-01-01

    The material presented in this volume is classified into the following sections; (1) analysis of current routes; (2) air eligibility criteria; (3) current direct support infrastructure; (4) comparative mode analysis; (5) political and economic factors; and (6) future potential market areas. An effort was made to keep the observations and findings relating to the current systems as objective as possible in order not to bias the analysis of future air cargo operations reported in Volume 3 of the CLASS final report.

  3. Calibration and Data Analysis of the MC-130 Air Balance

    NASA Technical Reports Server (NTRS)

    Booth, Dennis; Ulbrich, N.

    2012-01-01

    Design, calibration, calibration analysis, and intended use of the MC-130 air balance are discussed. The MC-130 balance is an 8.0 inch diameter force balance that has two separate internal air flow systems and one external bellows system. The manual calibration of the balance consisted of a total of 1854 data points with both unpressurized and pressurized air flowing through the balance. A subset of 1160 data points was chosen for the calibration data analysis. The regression analysis of the subset was performed using two fundamentally different analysis approaches. First, the data analysis was performed using a recently developed extension of the Iterative Method. This approach fits gage outputs as a function of both applied balance loads and bellows pressures while still allowing the application of the iteration scheme that is used with the Iterative Method. Then, for comparison, the axial force was also analyzed using the Non-Iterative Method. This alternate approach directly fits loads as a function of measured gage outputs and bellows pressures and does not require a load iteration. The regression models used by both the extended Iterative and Non-Iterative Method were constructed such that they met a set of widely accepted statistical quality requirements. These requirements lead to reliable regression models and prevent overfitting of data because they ensure that no hidden near-linear dependencies between regression model terms exist and that only statistically significant terms are included. Finally, a comparison of the axial force residuals was performed. Overall, axial force estimates obtained from both methods show excellent agreement as the differences of the standard deviation of the axial force residuals are on the order of 0.001 % of the axial force capacity.

  4. Inhalation toxicity of indoor air pollutants in Drosophila melanogaster using integrated transcriptomics and computational behavior analyses

    NASA Astrophysics Data System (ADS)

    Eom, Hyun-Jeong; Liu, Yuedan; Kwak, Gyu-Suk; Heo, Muyoung; Song, Kyung Seuk; Chung, Yun Doo; Chon, Tae-Soo; Choi, Jinhee

    2017-06-01

    We conducted an inhalation toxicity test on the alternative animal model, Drosophila melanogaster, to investigate potential hazards of indoor air pollution. The inhalation toxicity of toluene and formaldehyde was investigated using comprehensive transcriptomics and computational behavior analyses. The ingenuity pathway analysis (IPA) based on microarray data suggests the involvement of pathways related to immune response, stress response, and metabolism in formaldehyde and toluene exposure based on hub molecules. We conducted a toxicity test using mutants of the representative genes in these pathways to explore the toxicological consequences of alterations of these pathways. Furthermore, extensive computational behavior analysis showed that exposure to either toluene or formaldehyde reduced most of the behavioral parameters of both wild-type and mutants. Interestingly, behavioral alteration caused by toluene or formaldehyde exposure was most severe in the p38b mutant, suggesting that the defects in the p38 pathway underlie behavioral alteration. Overall, the results indicate that exposure to toluene and formaldehyde via inhalation causes severe toxicity in Drosophila, by inducing significant alterations in gene expression and behavior, suggesting that Drosophila can be used as a potential alternative model in inhalation toxicity screening.

  5. Inhalation toxicity of indoor air pollutants in Drosophila melanogaster using integrated transcriptomics and computational behavior analyses

    PubMed Central

    Eom, Hyun-Jeong; Liu, Yuedan; Kwak, Gyu-Suk; Heo, Muyoung; Song, Kyung Seuk; Chung, Yun Doo; Chon, Tae-Soo; Choi, Jinhee

    2017-01-01

    We conducted an inhalation toxicity test on the alternative animal model, Drosophila melanogaster, to investigate potential hazards of indoor air pollution. The inhalation toxicity of toluene and formaldehyde was investigated using comprehensive transcriptomics and computational behavior analyses. The ingenuity pathway analysis (IPA) based on microarray data suggests the involvement of pathways related to immune response, stress response, and metabolism in formaldehyde and toluene exposure based on hub molecules. We conducted a toxicity test using mutants of the representative genes in these pathways to explore the toxicological consequences of alterations of these pathways. Furthermore, extensive computational behavior analysis showed that exposure to either toluene or formaldehyde reduced most of the behavioral parameters of both wild-type and mutants. Interestingly, behavioral alteration caused by toluene or formaldehyde exposure was most severe in the p38b mutant, suggesting that the defects in the p38 pathway underlie behavioral alteration. Overall, the results indicate that exposure to toluene and formaldehyde via inhalation causes severe toxicity in Drosophila, by inducing significant alterations in gene expression and behavior, suggesting that Drosophila can be used as a potential alternative model in inhalation toxicity screening. PMID:28621308

  6. Functional analysis of the MAPK pathways in fungi.

    PubMed

    Martínez-Soto, Domingo; Ruiz-Herrera, José

    The Mitogen-Activated Protein Kinase (MAPK) signaling pathways constitute one of the most important and evolutionarily conserved mechanisms for the perception of extracellular information in all the eukaryotic organisms. The MAPK pathways are involved in the transfer to the cell of the information perceived from extracellular stimuli, with the final outcome of activation of different transcription factors that regulate gene expression in response to them. In all species of fungi, the MAPK pathways have important roles in their physiology and development; e.g. cell cycle control, mating, morphogenesis, response to different stresses, resistance to UV radiation and to temperature changes, cell wall assembly and integrity, degradation of cellular organelles, virulence, cell-cell signaling, fungus-plant interaction, and response to damage-associated molecular patterns (DAMPs). Considering the importance of the phylogenetically conserved MAPK pathways in fungi, an updated review of the knowledge on them is discussed in this article. This information reveals their importance, their distribution in fungal species evolutionarily distant and with different lifestyles, their organization and function, and the interactions occurring between different MAPK pathways, and with other signaling pathways, for the regulation of the most complex cellular processes. Copyright © 2017 Asociación Española de Micología. Publicado por Elsevier España, S.L.U. All rights reserved.

  7. 75 FR 60493 - Advisory Circular 120-79A, Developing and Implementing an Air Carrier Continuing Analysis and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-30

    ... and Implementing an Air Carrier Continuing Analysis and Surveillance System AGENCY: Federal Aviation... Analysis and Surveillance System''. This new advisory circular (AC) updates AC 120-79 originally issued on... Analysis and Surveillance System (CASS) required for commercial operators and air carriers certificated...

  8. Potential Air Pollutant Emissions and Permitting Classifications for Two Biorefinery Process Designs in the United States

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Eberle, Annika; Bhatt, Arpit; Zhang, Yimin

    Advanced biofuel production facilities (biorefineries), such as those envisioned by the United States (U.S.) Renewable Fuel Standard and U.S. Department of Energy's research and development programs, often lack historical air pollutant emissions data, which can pose challenges for obtaining air emission permits that are required for construction and operation. To help fill this knowledge gap, we perform a thorough regulatory analysis and use engineering process designs to assess the applicability of federal air regulations and quantify air pollutant emissions for two feasibility-level biorefinery designs. We find that without additional emission-control technologies both biorefineries would likely be required to obtain majormore » source permits under the Clean Air Act's New Source Review program. The permitting classification (so-called 'major' or 'minor') has implications for the time and effort required for permitting and therefore affects the cost of capital and the fuel selling price. Consequently, we explore additional technically feasible emission-control technologies and process modifications that have the potential to reduce emissions to achieve a minor source permitting classification. Finally, our analysis of air pollutant emissions and controls can assist biorefinery developers with the air permitting process and inform regulatory agencies about potential permitting pathways for novel biorefinery designs.« less

  9. Potential Air Pollutant Emissions and Permitting Classifications for Two Biorefinery Process Designs in the United States

    DOE PAGES

    Eberle, Annika; Bhatt, Arpit; Zhang, Yimin; ...

    2017-04-26

    Advanced biofuel production facilities (biorefineries), such as those envisioned by the United States (U.S.) Renewable Fuel Standard and U.S. Department of Energy's research and development programs, often lack historical air pollutant emissions data, which can pose challenges for obtaining air emission permits that are required for construction and operation. To help fill this knowledge gap, we perform a thorough regulatory analysis and use engineering process designs to assess the applicability of federal air regulations and quantify air pollutant emissions for two feasibility-level biorefinery designs. We find that without additional emission-control technologies both biorefineries would likely be required to obtain majormore » source permits under the Clean Air Act's New Source Review program. The permitting classification (so-called 'major' or 'minor') has implications for the time and effort required for permitting and therefore affects the cost of capital and the fuel selling price. Consequently, we explore additional technically feasible emission-control technologies and process modifications that have the potential to reduce emissions to achieve a minor source permitting classification. Finally, our analysis of air pollutant emissions and controls can assist biorefinery developers with the air permitting process and inform regulatory agencies about potential permitting pathways for novel biorefinery designs.« less

  10. Potential Air Pollutant Emissions and Permitting Classifications for Two Biorefinery Process Designs in the United States.

    PubMed

    Eberle, Annika; Bhatt, Arpit; Zhang, Yimin; Heath, Garvin

    2017-06-06

    Advanced biofuel production facilities (biorefineries), such as those envisioned by the United States (U.S.) Renewable Fuel Standard and U.S. Department of Energy's research and development programs, often lack historical air pollutant emissions data, which can pose challenges for obtaining air emission permits that are required for construction and operation. To help fill this knowledge gap, we perform a thorough regulatory analysis and use engineering process designs to assess the applicability of federal air regulations and quantify air pollutant emissions for two feasibility-level biorefinery designs. We find that without additional emission-control technologies both biorefineries would likely be required to obtain major source permits under the Clean Air Act's New Source Review program. The permitting classification (so-called "major" or "minor") has implications for the time and effort required for permitting and therefore affects the cost of capital and the fuel selling price. Consequently, we explore additional technically feasible emission-control technologies and process modifications that have the potential to reduce emissions to achieve a minor source permitting classification. Our analysis of air pollutant emissions and controls can assist biorefinery developers with the air permitting process and inform regulatory agencies about potential permitting pathways for novel biorefinery designs.

  11. ARL Support and Analysis to the Army Public Health Command Kabul Air Quality Data Collection (Spring 2014)

    DTIC Science & Technology

    2016-05-01

    ARL-TR-7692•MAY 2016 US Army Research Laboratory ARL Support and Analysis to the Army Public Health Command Kabul Air Quality Data Collection (Spring...return it to the originator. ARL-TR-7692•MAY 2016 US Army Research Laboratory ARL Support and Analysis to the Army Public Health Command Kabul Air Quality ...and Analysis to the Army Public Health Command Kabul Air Quality Data Collection (Spring 2014) Alan Wetmore and Thomas DeFelice ARL-TR-7692 Approved

  12. Cost analysis of impacts of climate change on regional air quality.

    PubMed

    Liao, Kuo-Jen; Tagaris, Efthimios; Russell, Armistead G; Amar, Praveen; He, Shan; Manomaiphiboon, Kasemsan; Woo, Jung-Hun

    2010-02-01

    Climate change has been predicted to adversely impact regional air quality with resulting health effects. Here a regional air quality model and a technology analysis tool are used to assess the additional emission reductions required and associated costs to offset impacts of climate change on air quality. Analysis is done for six regions and five major cities in the continental United States. Future climate is taken from a global climate model simulation for 2049-2051 using the Intergovernmental Panel on Climate Change (IPCC) A1B emission scenario, and emission inventories are the same as current ones to assess impacts of climate change alone on air quality and control expenses. On the basis of the IPCC A1B emission scenario and current control technologies, least-cost sets of emission reductions for simultaneously offsetting impacts of climate change on regionally averaged 4th highest daily maximum 8-hr average ozone and yearly averaged PM2.5 (particulate matter [PM] with an aerodynamic diameter less than 2.5 microm) for the six regions examined are predicted to range from $36 million (1999$) yr(-1) in the Southeast to $5.5 billion yr(-1) in the Northeast. However, control costs to offset climate-related pollutant increases in urban areas can be greater than the regional costs because of the locally exacerbated ozone levels. An annual cost of $4.1 billion is required for offsetting climate-induced air quality impairment in 2049-2051 in the five cities alone. Overall, an annual cost of $9.3 billion is estimated for offsetting climate change impacts on air quality for the six regions and five cities examined. Much of the additional expense is to reduce increased levels of ozone. Additional control costs for offsetting the impacts everywhere in the United States could be larger than the estimates in this study. This study shows that additional emission controls and associated costs for offsetting climate impacts could significantly increase currently estimated

  13. An analysis of contact stiffness between a finger and an object when wearing an air-cushioned glove: the effects of the air pressure.

    PubMed

    Wu, John Z; Wimer, Bryan M; Welcome, Daniel E; Dong, Ren G

    2012-04-01

    Air-cushioned gloves have the advantages of lighter weight, lower cost, and unique mechanical performance, compared to gloves made of conventional engineering materials. The goal of this study is to analyze the contact interaction between fingers and object when wearing an air-cushioned glove. The contact interactions between the the fingertip and air bubbles, which is considered as a cell of a typical air-cushioned glove, has been analyzed theoretically. Two-dimensional finite element models were developed for the analysis. The fingertip model was assumed to be composed of skin layers, subcutaneous tissue, bone, and nail. The air bubbles were modeled as air sealed in the container of nonelastic membrane. We simulated two common scenarios: a fingertip in contact with one single air bubble and with two air cushion bubbles simultaneously. Our simulation results indicated that the internal air pressure can modulate the fingertip-object contact characteristics. The contact stiffness reaches a minimum when the initial air pressure is equal to 1.3 and 1.05 times of the atmosphere pressure for the single air bubble and the double air bubble contact, respectively. Furthermore, the simulation results indicate that the double air bubble contact will result in smaller volumetric tissue strain than the single air bubble contact for the same force. Published by Elsevier Ltd.

  14. Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis.

    PubMed

    Shchetynsky, Klementy; Diaz-Gallo, Lina-Marcella; Folkersen, Lasse; Hensvold, Aase Haj; Catrina, Anca Irinel; Berg, Louise; Klareskog, Lars; Padyukov, Leonid

    2017-02-02

    Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of "connector" genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA.

  15. In Silico Analysis of Putrefaction Pathways in Bacteria and Its Implication in Colorectal Cancer

    PubMed Central

    Kaur, Harrisham; Das, Chandrani; Mande, Sharmila S.

    2017-01-01

    Fermentation of undigested proteins in human gastrointestinal tract (gut) by the resident microbiota, a process called bacterial putrefaction, can sometimes disrupt the gut homeostasis. In this process, essential amino acids (e.g., histidine, tryptophan, etc.) that are required by the host may be utilized by the gut microbes. In addition, some of the products of putrefaction, like ammonia, putrescine, cresol, indole, phenol, etc., have been implicated in the disease pathogenesis of colorectal cancer (CRC). We have investigated bacterial putrefaction pathways that are known to be associated with such metabolites. Results of the comprehensive in silico analysis of the selected putrefaction pathways across bacterial genomes revealed presence of these pathways in limited bacterial groups. Majority of these bacteria are commonly found in human gut. These include Bacillus, Clostridium, Enterobacter, Escherichia, Fusobacterium, Salmonella, etc. Interestingly, while pathogens utilize almost all the analyzed pathways, commensals prefer putrescine and H2S production pathways for metabolizing the undigested proteins. Further, comparison of the putrefaction pathways in the gut microbiomes of healthy, carcinoma and adenoma datasets indicate higher abundances of putrefying bacteria in the carcinoma stage of CRC. The insights obtained from the present study indicate utilization of possible microbiome-based therapies to minimize the adverse effects of gut microbiome in enteric diseases. PMID:29163445

  16. Using Social Media to Detect Outdoor Air Pollution and Monitor Air Quality Index (AQI): A Geo-Targeted Spatiotemporal Analysis Framework with Sina Weibo (Chinese Twitter).

    PubMed

    Jiang, Wei; Wang, Yandong; Tsou, Ming-Hsiang; Fu, Xiaokang

    2015-01-01

    Outdoor air pollution is a serious problem in many developing countries today. This study focuses on monitoring the dynamic changes of air quality effectively in large cities by analyzing the spatiotemporal trends in geo-targeted social media messages with comprehensive big data filtering procedures. We introduce a new social media analytic framework to (1) investigate the relationship between air pollution topics posted in Sina Weibo (Chinese Twitter) and the daily Air Quality Index (AQI) published by China's Ministry of Environmental Protection; and (2) monitor the dynamics of air quality index by using social media messages. Correlation analysis was used to compare the connections between discussion trends in social media messages and the temporal changes in the AQI during 2012. We categorized relevant messages into three types, retweets, mobile app messages, and original individual messages finding that original individual messages had the highest correlation to the Air Quality Index. Based on this correlation analysis, individual messages were used to monitor the AQI in 2013. Our study indicates that the filtered social media messages are strongly correlated to the AQI and can be used to monitor the air quality dynamics to some extent.

  17. Using Social Media to Detect Outdoor Air Pollution and Monitor Air Quality Index (AQI): A Geo-Targeted Spatiotemporal Analysis Framework with Sina Weibo (Chinese Twitter)

    PubMed Central

    Tsou, Ming-Hsiang; Fu, Xiaokang

    2015-01-01

    Outdoor air pollution is a serious problem in many developing countries today. This study focuses on monitoring the dynamic changes of air quality effectively in large cities by analyzing the spatiotemporal trends in geo-targeted social media messages with comprehensive big data filtering procedures. We introduce a new social media analytic framework to (1) investigate the relationship between air pollution topics posted in Sina Weibo (Chinese Twitter) and the daily Air Quality Index (AQI) published by China’s Ministry of Environmental Protection; and (2) monitor the dynamics of air quality index by using social media messages. Correlation analysis was used to compare the connections between discussion trends in social media messages and the temporal changes in the AQI during 2012. We categorized relevant messages into three types, retweets, mobile app messages, and original individual messages finding that original individual messages had the highest correlation to the Air Quality Index. Based on this correlation analysis, individual messages were used to monitor the AQI in 2013. Our study indicates that the filtered social media messages are strongly correlated to the AQI and can be used to monitor the air quality dynamics to some extent. PMID:26505756

  18. Ecologic regression analysis and the study of the influence of air quality on mortality.

    PubMed Central

    Selvin, S; Merrill, D; Wong, L; Sacks, S T

    1984-01-01

    This presentation focuses entirely on the use and evaluation of regression analysis applied to ecologic data as a method to study the effects of ambient air pollution on mortality rates. Using extensive national data on mortality, air quality and socio-economic status regression analyses are used to study the influence of air quality on mortality. The analytic methods and data are selected in such a way that direct comparisons can be made with other ecologic regression studies of mortality and air quality. Analyses are performed by use of two types of geographic areas, age-specific mortality of both males and females and three pollutants (total suspended particulates, sulfur dioxide and nitrogen dioxide). The overall results indicate no persuasive evidence exists of a link between air quality and general mortality levels. Additionally, a lack of consistency between the present results and previous published work is noted. Overall, it is concluded that linear regression analysis applied to nationally collected ecologic data cannot be used to usefully infer a causal relationship between air quality and mortality which is in direct contradiction to other major published studies. PMID:6734568

  19. Cognitive Task Analysis of Prioritization in Air Traffic Control.

    ERIC Educational Resources Information Center

    Redding, Richard E.; And Others

    A cognitive task analysis was performed to analyze the key cognitive components of the en route air traffic controllers' jobs. The goals were to ascertain expert mental models and decision-making strategies and to identify important differences in controller knowledge, skills, and mental models as a function of expertise. Four groups of…

  20. A Simple Geotracer Compositional Correlation Analysis Reveals Oil Charge and Migration Pathways

    PubMed Central

    Yang, Yunlai; Arouri, Khaled

    2016-01-01

    A novel approach, based on geotracer compositional correlation analysis is reported, which reveals the oil charge sequence and migration pathways for five oil fields in Saudi Arabia. The geotracers utilised are carbazoles, a family of neutral pyrrolic nitrogen compounds known to occur naturally in crude oils. The approach is based on the concept that closely related fields, with respect to filling sequence, will show a higher carbazole compositional correlation, than those fields that are less related. That is, carbazole compositional correlation coefficients can quantify the charge and filling relationships among different fields. Consequently, oil migration pathways can be defined based on the established filling relationships. The compositional correlation coefficients of isomers of C1 and C2 carbazoles, and benzo[a]carbazole for all different combination pairs of the five fields were found to vary extremely widely (0.28 to 0.94). A wide range of compositional correlation coefficients allows adequate differentiation of separate filling relationships. Based on the established filling relationships, three distinct migration pathways were inferred, with each apparently being charged from a different part of a common source kitchen. The recognition of these charge and migration pathways will greatly aid the search for new accumulations. PMID:26965479

  1. Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

    PubMed

    Gao, Haiyan; Yang, Mei; Zhang, Xiaolan

    2018-04-01

    The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

  2. Analysis of organophosphate hydraulic fluids in U.S. Air force base soils

    PubMed

    David; Seiber

    1999-04-01

    Tri-aryl and tri-alkyl organophosphates (TAPs) have been used extensively as flame-retardant hydraulic fluids and fluid additives in commercial and military aircraft. Up to 80% of the consumption of these fluids has been estimated to be lost to unrecovered leakage. Tri-aryl phosphate components of these fluids are resistant to volatilization and solubilization in water, thus, their primary environmental fate pathway is sorption to soils. Environmental audits of military air bases generally do not include quantification of these compounds in soils. We have determined the presence and extent of TAP contamination in soil samples from several U.S. Air Force bases. Soils were collected, extracted, and analyzed using GC/FPD and GC/MS. Tricresyl phosphate was the most frequently found TAP in soil, ranging from 0.02 to 130 ppm. Other TAPs in soils included triphenyl phosphate and isopropylated triphenyl phosphate. Observations are made regarding the distribution, typical concentrations, persistence, and need for further testing of TAPs in soils at military installations. Additionally, GC and mass spectral data for these TAPs are presented, along with methods for their extraction, sample clean-up, and quantification.

  3. Analysis of dynamical response of air blast loaded safety device

    NASA Astrophysics Data System (ADS)

    Tropkin, S. N.; Tlyasheva, R. R.; Bayazitov, M. I.; Kuzeev, I. R.

    2018-03-01

    Equipment of many oil and gas processing plants in the Russian Federation is considerably worn-out. This causes the decrease of reliability and durability of equipment and rises the accident rate. An air explosion is the one of the most dangerous cases for plants in oil and gas industry, usually caused by uncontrolled emission and inflammation of oil products. Air explosion can lead to significant danger for life and health of plant staff, so it necessitates safety device usage. A new type of a safety device is designed. Numerical simulation is necessary to analyse design parameters and performance of the safety device, subjected to air blast loading. Coupled fluid-structure interaction analysis is performed to determine strength of the protective device and its performance. The coupled Euler-Lagrange method, allowable in Abaqus by SIMULIA, is selected as the most appropriate analysis tool to study blast wave interaction with the safety device. Absorption factors of blast wave are evaluated for the safety device. This factors allow one to assess efficiency of the safety device, and its main structural component – dampener. Usage of CEL allowed one to model fast and accurately the dampener behaviour, and to develop the parametric model to determine safety device sizes.

  4. Integrative pathway analysis of a genome-wide association study of V̇o2max response to exercise training

    PubMed Central

    Vivar, Juan C.; Sarzynski, Mark A.; Sung, Yun Ju; Timmons, James A.; Bouchard, Claude; Rankinen, Tuomo

    2013-01-01

    We previously reported the findings from a genome-wide association study of the response of maximal oxygen uptake (V̇o2max) to an exercise program. Here we follow up on these results to generate hypotheses on genes, pathways, and systems involved in the ability to respond to exercise training. A systems biology approach can help us better establish a comprehensive physiological description of what underlies V̇o2maxtrainability. The primary material for this exploration was the individual single-nucleotide polymorphism (SNP), SNP-gene mapping, and statistical significance levels. We aimed to generate novel hypotheses through analyses that go beyond statistical association of single-locus markers. This was accomplished through three complementary approaches: 1) building de novo evidence of gene candidacy through informatics-driven literature mining; 2) aggregating evidence from statistical associations to link variant enrichment in biological pathways to V̇o2max trainability; and 3) predicting possible consequences of variants residing in the pathways of interest. We started with candidate gene prioritization followed by pathway analysis focused on overrepresentation analysis and gene set enrichment analysis. Subsequently, leads were followed using in silico analysis of predicted SNP functions. Pathways related to cellular energetics (pantothenate and CoA biosynthesis; PPAR signaling) and immune functions (complement and coagulation cascades) had the highest levels of SNP burden. In particular, long-chain fatty acid transport and fatty acid oxidation genes and sequence variants were found to influence differences in V̇o2max trainability. Together, these methods allow for the hypothesis-driven ranking and prioritization of genes and pathways for future experimental testing and validation. PMID:23990238

  5. Microarray RNA expression analysis of cerebral white matter lesions reveals changes in multiple functional pathways.

    PubMed

    Simpson, Julie E; Hosny, Ola; Wharton, Stephen B; Heath, Paul R; Holden, Hazel; Fernando, Malee S; Matthews, Fiona; Forster, Gill; O'Brien, John T; Barber, Robert; Kalaria, Raj N; Brayne, Carol; Shaw, Pamela J; Lewis, Claire E; Ince, Paul G

    2009-02-01

    White matter lesions (WML) in brain aging are linked to dementia and depression. Ischemia contributes to their pathogenesis but other mechanisms may contribute. We used RNA microarray analysis with functional pathway grouping as an unbiased approach to investigate evidence for additional pathogenetic mechanisms. WML were identified by MRI and pathology in brains donated to the Medical Research Council Cognitive Function and Ageing Study Cognitive Function and Aging Study. RNA was extracted to compare WML with nonlesional white matter samples from cases with lesions (WM[L]), and from cases with no lesions (WM[C]) using RNA microarray and pathway analysis. Functional pathways were validated for selected genes by quantitative real-time polymerase chain reaction and immunocytochemistry. We identified 8 major pathways in which multiple genes showed altered RNA transcription (immune regulation, cell cycle, apoptosis, proteolysis, ion transport, cell structure, electron transport, metabolism) among 502 genes that were differentially expressed in WML compared to WM[C]. In WM[L], 409 genes were altered involving the same pathways. Genes selected to validate this microarray data all showed the expected changes in RNA levels and immunohistochemical expression of protein. WML represent areas with a complex molecular phenotype. From this and previous evidence, WML may arise through tissue ischemia but may also reflect the contribution of additional factors like blood-brain barrier dysfunction. Differential expression of genes in WM[L] compared to WM[C] indicate a "field effect" in the seemingly normal surrounding white matter.

  6. The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways.

    PubMed

    Beltrame, Luca; Calura, Enrica; Popovici, Razvan R; Rizzetto, Lisa; Guedez, Damariz Rivero; Donato, Michele; Romualdi, Chiara; Draghici, Sorin; Cavalieri, Duccio

    2011-08-01

    Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions. The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and 'wet lab' scientists. The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X.

  7. Analysis of flight equipment purchasing practices of representative air carriers

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The process through which representative air carriers decide whether or not to purchase flight equipment was investigated as well as their practices and policies in retiring surplus aircraft. An analysis of the flight equipment investment decision process in ten airlines shows that for the airline industry as a whole, the flight equipment investment decision is in a state of transition from a wholly informal process in earliest years to a much more organized and structured process in the future. Individual air carriers are in different stages with respect to the formality and sophistication associated with the flight equipment investment decision.

  8. Exploring pathway interactions in insulin resistant mouse liver

    PubMed Central

    2011-01-01

    Background Complex phenotypes such as insulin resistance involve different biological pathways that may interact and influence each other. Interpretation of related experimental data would be facilitated by identifying relevant pathway interactions in the context of the dataset. Results We developed an analysis approach to study interactions between pathways by integrating gene and protein interaction networks, biological pathway information and high-throughput data. This approach was applied to a transcriptomics dataset to investigate pathway interactions in insulin resistant mouse liver in response to a glucose challenge. We identified regulated pathway interactions at different time points following the glucose challenge and also studied the underlying protein interactions to find possible mechanisms and key proteins involved in pathway cross-talk. A large number of pathway interactions were found for the comparison between the two diet groups at t = 0. The initial response to the glucose challenge (t = 0.6) was typed by an acute stress response and pathway interactions showed large overlap between the two diet groups, while the pathway interaction networks for the late response were more dissimilar. Conclusions Studying pathway interactions provides a new perspective on the data that complements established pathway analysis methods such as enrichment analysis. This study provided new insights in how interactions between pathways may be affected by insulin resistance. In addition, the analysis approach described here can be generally applied to different types of high-throughput data and will therefore be useful for analysis of other complex datasets as well. PMID:21843341

  9. Automation Applications in an Advanced Air Traffic Management System : Volume 2A. Functional Analysis of Air Traffic Management.

    DOT National Transportation Integrated Search

    1974-08-01

    Volume 2 contains the analysis and description of air traffic management activities at three levels of detail - functions, subfunctions, and tasks. A total of 265 tasks are identified and described, and the flow of information inputs and outputs amon...

  10. Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing.

    PubMed

    Chen, Long; Zhang, Chunhua; Wang, Yanling; Li, Yuqian; Han, Qiaoqiao; Yang, Huixin; Zhu, Yuechun

    2017-08-01

    Human glucose-6-phosphate dehydrogenase (G6PD) is a crucial enzyme in the pentose phosphate pathway, and serves an important role in biosynthesis and the redox balance. G6PD deficiency is a major cause of neonatal jaundice and acute hemolyticanemia, and recently, G6PD has been associated with diseases including inflammation and cancer. The aim of the present study was to conduct a search of the National Center for Biotechnology Information PubMed library for articles discussing G6PD. Genes that were identified to be associated with G6PD were recorded, and the frequency at which each gene appeared was calculated. Gene ontology (GO), pathway and network analyses were then performed. A total of 98 G6PD‑associated genes and 33 microRNAs (miRNAs) that potentially regulate G6PD were identified. The 98 G6PD‑associated genes were then sub‑classified into three functional groups by GO analysis, followed by analysis of function, pathway, network, and disease association. Out of the 47 signaling pathways identified, seven were significantly correlated with G6PD‑associated genes. At least two out of four independent programs identified the 33 miRNAs that were predicted to target G6PD. miR‑1207‑5P, miR‑1 and miR‑125a‑5p were predicted by all four software programs to target G6PD. The results of the present study revealed that dysregulation of G6PD was associated with cancer, autoimmune diseases, and oxidative stress‑induced disorders. These results revealed the potential roles of G6PD‑regulated signaling and metabolic pathways in the etiology of these diseases.

  11. Data mining and pathway analysis of glucose-6-phosphate dehydrogenase with natural language processing

    PubMed Central

    Chen, Long; Zhang, Chunhua; Wang, Yanling; Li, Yuqian; Han, Qiaoqiao; Yang, Huixin; Zhu, Yuechun

    2017-01-01

    Human glucose-6-phosphate dehydrogenase (G6PD) is a crucial enzyme in the pentose phosphate pathway, and serves an important role in biosynthesis and the redox balance. G6PD deficiency is a major cause of neonatal jaundice and acute hemolyticanemia, and recently, G6PD has been associated with diseases including inflammation and cancer. The aim of the present study was to conduct a search of the National Center for Biotechnology Information PubMed library for articles discussing G6PD. Genes that were identified to be associated with G6PD were recorded, and the frequency at which each gene appeared was calculated. Gene ontology (GO), pathway and network analyses were then performed. A total of 98 G6PD-associated genes and 33 microRNAs (miRNAs) that potentially regulate G6PD were identified. The 98 G6PD-associated genes were then sub-classified into three functional groups by GO analysis, followed by analysis of function, pathway, network, and disease association. Out of the 47 signaling pathways identified, seven were significantly correlated with G6PD-associated genes. At least two out of four independent programs identified the 33 miRNAs that were predicted to target G6PD. miR-1207-5P, miR-1 and miR-125a-5p were predicted by all four software programs to target G6PD. The results of the present study revealed that dysregulation of G6PD was associated with cancer, autoimmune diseases, and oxidative stress-induced disorders. These results revealed the potential roles of G6PD-regulated signaling and metabolic pathways in the etiology of these diseases. PMID:28627690

  12. Regulatory Impact Analysis for the Final Cross-State Air Pollution Rule

    EPA Pesticide Factsheets

    This Regulatory Impact Analysis (RIA) presents the health and welfare benefits, costs, and other impacts of the Transport Rule, also called the Cross-State Air Pollution Rule, focusing primarily on 2014.

  13. Redundancy control in pathway databases (ReCiPa): an application for improving gene-set enrichment analysis in Omics studies and "Big data" biology.

    PubMed

    Vivar, Juan C; Pemu, Priscilla; McPherson, Ruth; Ghosh, Sujoy

    2013-08-01

    Abstract Unparalleled technological advances have fueled an explosive growth in the scope and scale of biological data and have propelled life sciences into the realm of "Big Data" that cannot be managed or analyzed by conventional approaches. Big Data in the life sciences are driven primarily via a diverse collection of 'omics'-based technologies, including genomics, proteomics, metabolomics, transcriptomics, metagenomics, and lipidomics. Gene-set enrichment analysis is a powerful approach for interrogating large 'omics' datasets, leading to the identification of biological mechanisms associated with observed outcomes. While several factors influence the results from such analysis, the impact from the contents of pathway databases is often under-appreciated. Pathway databases often contain variously named pathways that overlap with one another to varying degrees. Ignoring such redundancies during pathway analysis can lead to the designation of several pathways as being significant due to high content-similarity, rather than truly independent biological mechanisms. Statistically, such dependencies also result in correlated p values and overdispersion, leading to biased results. We investigated the level of redundancies in multiple pathway databases and observed large discrepancies in the nature and extent of pathway overlap. This prompted us to develop the application, ReCiPa (Redundancy Control in Pathway Databases), to control redundancies in pathway databases based on user-defined thresholds. Analysis of genomic and genetic datasets, using ReCiPa-generated overlap-controlled versions of KEGG and Reactome pathways, led to a reduction in redundancy among the top-scoring gene-sets and allowed for the inclusion of additional gene-sets representing possibly novel biological mechanisms. Using obesity as an example, bioinformatic analysis further demonstrated that gene-sets identified from overlap-controlled pathway databases show stronger evidence of prior association

  14. Tissue-Specific Analysis of Pharmacological Pathways.

    PubMed

    Hao, Yun; Quinnies, Kayla; Realubit, Ronald; Karan, Charles; Tatonetti, Nicholas P

    2018-06-19

    Understanding the downstream consequences of pharmacologically targeted proteins is essential to drug design. Current approaches investigate molecular effects under tissue-naïve assumptions. Many target proteins, however, have tissue-specific expression. A systematic study connecting drugs to target pathways in in vivo human tissues is needed. We introduced a data-driven method that integrates drug-target relationships with gene expression, protein-protein interaction, and pathway annotation data. We applied our method to four independent genomewide expression datasets and built 467,396 connections between 1,034 drugs and 954 pathways in 259 human tissues or cell lines. We validated our results using data from L1000 and Pharmacogenomics Knowledgebase (PharmGKB), and observed high precision and recall. We predicted and tested anticoagulant effects of 22 compounds experimentally that were previously unknown, and used clinical data to validate these effects retrospectively. Our systematic study provides a better understanding of the cellular response to drugs and can be applied to many research topics in systems pharmacology. © 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

  15. Ambient air pollution and thrombosis.

    PubMed

    Robertson, Sarah; Miller, Mark R

    2018-01-03

    Air pollution is a growing public health concern of global significance. Acute and chronic exposure is known to impair cardiovascular function, exacerbate disease and increase cardiovascular mortality. Several plausible biological mechanisms have been proposed for these associations, however, at present, the pathways are incomplete. A seminal review by the American Heart Association (2010) concluded that the thrombotic effects of particulate air pollution likely contributed to their effects on cardiovascular mortality and morbidity. The aim of the current review is to appraise the newly accumulated scientific evidence (2009-2016) on contribution of haemostasis and thrombosis towards cardiovascular disease induced by exposure to both particulate and gaseous pollutants.Seventy four publications were reviewed in-depth. The weight of evidence suggests that acute exposure to fine particulate matter (PM 2.5 ) induces a shift in the haemostatic balance towards a pro-thrombotic/pro-coagulative state. Insufficient data was available to ascertain if a similar relationship exists for gaseous pollutants, and very few studies have addressed long-term exposure to ambient air pollution. Platelet activation, oxidative stress, interplay between interleukin-6 and tissue factor, all appear to be potentially important mechanisms in pollution-mediated thrombosis, together with an emerging role for circulating microvesicles and epigenetic changes.Overall, the recent literature supports, and arguably strengthens, the contention that air pollution contributes to cardiovascular morbidity by promoting haemostasis. The volume and diversity of the evidence highlights the complexity of the pathophysiologic mechanisms by which air pollution promotes thrombosis; multiple pathways are plausible and it is most likely they act in concert. Future research should address the role gaseous pollutants play in the cardiovascular effects of air pollution mixture and direct comparison of potentially

  16. Determination of 14C/ 12C of acetaldehyde in indoor air by compound specific radiocarbon analysis

    NASA Astrophysics Data System (ADS)

    Kato, Yoshimi; Shinohara, Naohide; Yoshinaga, Jun; Uchida, Masao; Matsuda, Ayuri; Yoneda, Minoru; Shibata, Yasuyuki

    A method of compound-specific radiocarbon analysis (CSRA) for acetaldehyde in indoor air was established for the source apportionment purpose and the methodology was applied to indoor air samples. Acetaldehyde in indoor air samples was collected using the conventional 2,4-dinitrophenylhydrazine (DNPH) derivatization method. Typically 24-h air sampling at 5-10 L min -1 allowed collection of adequate amount of acetaldehyde for radiocarbon analysis by accelerator mass spectrometry (AMS). The 14C abundance of acetaldehyde in indoor air was measured by AMS after solvent extraction of derivatized acetaldehyde and sequential purification by a preparative liquid chromatography system and a preparative capillary gas chromatography system. The recovery and purity of the derivatized acetaldehyde was satisfactory for 14C analysis by AMS. 14C abundance of acetaldehyde was calculated by considering that of derivatizing agent DNPH. Our preliminary survey showed that percent modern carbon (pMC) values of acetaldehyde isolated from indoor air sampled in newly built, unoccupied housings ( n=5) in the suburb of Tokyo ranged from 49.4 to 67.0. This result indicated that contribution of anthropogenic source was greater than previously expected.

  17. Analysis of Air Traffic Track Data with the AutoBayes Synthesis System

    NASA Technical Reports Server (NTRS)

    Schumann, Johann Martin Philip; Cate, Karen; Lee, Alan G.

    2010-01-01

    The Next Generation Air Traffic System (NGATS) is aiming to provide substantial computer support for the air traffic controllers. Algorithms for the accurate prediction of aircraft movements are of central importance for such software systems but trajectory prediction has to work reliably in the presence of unknown parameters and uncertainties. We are using the AutoBayes program synthesis system to generate customized data analysis algorithms that process large sets of aircraft radar track data in order to estimate parameters and uncertainties. In this paper, we present, how the tasks of finding structure in track data, estimation of important parameters in climb trajectories, and the detection of continuous descent approaches can be accomplished with compact task-specific AutoBayes specifications. We present an overview of the AutoBayes architecture and describe, how its schema-based approach generates customized analysis algorithms, documented C/C++ code, and detailed mathematical derivations. Results of experiments with actual air traffic control data are discussed.

  18. Textile Inspired Lithium-Oxygen Battery Cathode with Decoupled Oxygen and Electrolyte Pathways.

    PubMed

    Xu, Shaomao; Yao, Yonggang; Guo, Yuanyuan; Zeng, Xiaoqiao; Lacey, Steven D; Song, Huiyu; Chen, Chaoji; Li, Yiju; Dai, Jiaqi; Wang, Yanbin; Chen, Yanan; Liu, Boyang; Fu, Kun; Amine, Khalil; Lu, Jun; Hu, Liangbing

    2018-01-01

    The lithium-air (Li-O 2 ) battery has been deemed one of the most promising next-generation energy-storage devices due to its ultrahigh energy density. However, in conventional porous carbon-air cathodes, the oxygen gas and electrolyte often compete for transport pathways, which limit battery performance. Here, a novel textile-based air cathode is developed with a triple-phase structure to improve overall battery performance. The hierarchical structure of the conductive textile network leads to decoupled pathways for oxygen gas and electrolyte: oxygen flows through the woven mesh while the electrolyte diffuses along the textile fibers. Due to noncompetitive transport, the textile-based Li-O 2 cathode exhibits a high discharge capacity of 8.6 mAh cm -2 , a low overpotential of 1.15 V, and stable operation exceeding 50 cycles. The textile-based structure can be applied to a range of applications (fuel cells, water splitting, and redox flow batteries) that involve multiple phase reactions. The reported decoupled transport pathway design also spurs potential toward flexible/wearable Li-O 2 batteries. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Analysis of molecular pathways in pancreatic ductal adenocarcinomas with a bioinformatics approach.

    PubMed

    Wang, Yan; Li, Yan

    2015-01-01

    Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death worldwide. Our study aimed to reveal molecular mechanisms. Microarray data of GSE15471 (including 39 matching pairs of pancreatic tumor tissues and patient-matched normal tissues) was downloaded from Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in PDAC tissues compared with normal tissues by limma package in R language. Then GO and KEGG pathway enrichment analyses were conducted with online DAVID. In addition, principal component analysis was performed and a protein-protein interaction network was constructed to study relationships between the DEGs through database STRING. A total of 532 DEGs were identified in the 38 PDAC tissues compared with 33 normal tissues. The results of principal component analysis of the top 20 DEGs could differentiate the PDAC tissues from normal tissues directly. In the PPI network, 8 of the 20 DEGs were all key genes of the collagen family. Additionally, FN1 (fibronectin 1) was also a hub node in the network. The genes of the collagen family as well as FN1 were significantly enriched in complement and coagulation cascades, ECM-receptor interaction and focal adhesion pathways. Our results suggest that genes of collagen family and FN1 may play an important role in PDAC progression. Meanwhile, these DEGs and enriched pathways, such as complement and coagulation cascades, ECM-receptor interaction and focal adhesion may be important molecular mechanisms involved in the development and progression of PDAC.

  20. TEGS-CN: A Statistical Method for Pathway Analysis of Genome-wide Copy Number Profile.

    PubMed

    Huang, Yen-Tsung; Hsu, Thomas; Christiani, David C

    2014-01-01

    The effects of copy number alterations make up a significant part of the tumor genome profile, but pathway analyses of these alterations are still not well established. We proposed a novel method to analyze multiple copy numbers of genes within a pathway, termed Test for the Effect of a Gene Set with Copy Number data (TEGS-CN). TEGS-CN was adapted from TEGS, a method that we previously developed for gene expression data using a variance component score test. With additional development, we extend the method to analyze DNA copy number data, accounting for different sizes and thus various numbers of copy number probes in genes. The test statistic follows a mixture of X (2) distributions that can be obtained using permutation with scaled X (2) approximation. We conducted simulation studies to evaluate the size and the power of TEGS-CN and to compare its performance with TEGS. We analyzed a genome-wide copy number data from 264 patients of non-small-cell lung cancer. With the Molecular Signatures Database (MSigDB) pathway database, the genome-wide copy number data can be classified into 1814 biological pathways or gene sets. We investigated associations of the copy number profile of the 1814 gene sets with pack-years of cigarette smoking. Our analysis revealed five pathways with significant P values after Bonferroni adjustment (<2.8 × 10(-5)), including the PTEN pathway (7.8 × 10(-7)), the gene set up-regulated under heat shock (3.6 × 10(-6)), the gene sets involved in the immune profile for rejection of kidney transplantation (9.2 × 10(-6)) and for transcriptional control of leukocytes (2.2 × 10(-5)), and the ganglioside biosynthesis pathway (2.7 × 10(-5)). In conclusion, we present a new method for pathway analyses of copy number data, and causal mechanisms of the five pathways require further study.

  1. Age and Pathway Diagnostics for a Stratospheric General Circulation Model

    NASA Technical Reports Server (NTRS)

    Schoeberl, Mark R.; Douglass, Anne R.; Polansky, Brian

    2004-01-01

    Using a variety of age diagnostic experiments we examine the stratospheric age spectrum of the Goddard Finite Volume Generd Circulation Model. Pulse tracer release age-of-air computations are compared to forward and backward trajectory computations. These comparisons show good agreement, and the age-of-air also compares well with observed long lived tracers. Pathway diagnostics show how air arrives in the lowermost stratosphere and the age structure of that region. Using tracers with different lifetimes we can estimate the age spectrum - this technique should be useful in diagnosing transport from various trace gas observations.

  2. Techno-Economic Analysis of Indian Draft Standard Levels for RoomAir Conditioners

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    McNeil, Michael A.; Iyer, Maithili

    The Indian Bureau of Energy Efficiency (BEE) finalized its first set of efficiency standards and labels for room air conditioners in July of 2006. These regulations followed soon after the publication of levels for frost-free refrigerators in the same year. As in the case of refrigerators, the air conditioner program introduces Minimum Efficiency Performance Standards (MEPS) and comparative labels simultaneously, with levels for one to five stars. Also like the refrigerator program, BEE defined several successive program phases of increasing stringency. In support of BEE's refrigerator program, Lawrence Berkeley National Laboratory (LBNL) produced an analysis of national impacts of standardsmore » in collaboration with the Collaborative Labeling and Standards Program (CLASP). That analysis drew on LBNL's experience with standards programs in the United States, as well as many other countries. Subsequently, as part of the process for setting optimal levels for air conditioner regulations, CLASP commissioned LBNL to provide support to BEE in the form of a techno-economic evaluation of air conditioner efficiency technologies. This report describes the methodology and results of this techno-economic evaluation. The analysis consists of three components: (1) Cost effectiveness to consumers of efficiency technologies relative to current baseline. (2) Impacts on the current market from efficiency regulations. (3) National energy and financial impacts. The analysis relied on detailed and up-to-date technical data made available by BEE and industry representatives. Technical parameters were used in conjunction with knowledge about air conditioner use patterns in the residential and commercial sectors, and prevailing marginal electricity prices, in order to give an estimate of per-unit financial impacts. In addition, the overall impact of the program was evaluated by combining unit savings with market forecasts in order to yield national impacts. LBNL presented preliminary

  3. A Method for Gene-Based Pathway Analysis Using Genomewide Association Study Summary Statistics Reveals Nine New Type 1 Diabetes Associations

    PubMed Central

    Evangelou, Marina; Smyth, Deborah J; Fortune, Mary D; Burren, Oliver S; Walker, Neil M; Guo, Hui; Onengut-Gumuscu, Suna; Chen, Wei-Min; Concannon, Patrick; Rich, Stephen S; Todd, John A; Wallace, Chris

    2014-01-01

    Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed () with 12 of the 22 SNPs showing . Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, ), NRP1 (rs722988, ), BAD (rs694739, ), CTSB (rs1296023, ), FYN (rs11964650, ), UBE2G1 (rs9906760, ), MAP3K14 (rs17759555, ), ITGB1 (rs1557150, ), and IL7R (rs1445898, ). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available. PMID:25371288

  4. Investigating multiple dysregulated pathways in rheumatoid arthritis based on pathway interaction network.

    PubMed

    Song, Xian-Dong; Song, Xian-Xu; Liu, Gui-Bo; Ren, Chun-Hui; Sun, Yuan-Bo; Liu, Ke-Xin; Liu, Bo; Liang, Shuang; Zhu, Zhu

    2018-03-01

    The traditional methods of identifying biomarkers in rheumatoid arthritis (RA) have focussed on the differentially expressed pathways or individual pathways, which however, neglect the interactions between pathways. To better understand the pathogenesis of RA, we aimed to identify dysregulated pathway sets using a pathway interaction network (PIN), which considered interactions among pathways. Firstly, RA-related gene expression profile data, protein-protein interactions (PPI) data and pathway data were taken up from the corresponding databases. Secondly, principal component analysis method was used to calculate the pathway activity of each of the pathway, and then a seed pathway was identified using data gleaned from the pathway activity. A PIN was then constructed based on the gene expression profile, pathway data, and PPI information. Finally, the dysregulated pathways were extracted from the PIN based on the seed pathway using the method of support vector machines and an area under the curve (AUC) index. The PIN comprised of a total of 854 pathways and 1064 pathway interactions. The greatest change in the activity score between RA and control samples was observed in the pathway of epigenetic regulation of gene expression, which was extracted and regarded as the seed pathway. Starting with this seed pathway, one maximum pathway set containing 10 dysregulated pathways was extracted from the PIN, having an AUC of 0.8249, and the result indicated that this pathway set could distinguish RA from the controls. These 10 dysregulated pathways might be potential biomarkers for RA diagnosis and treatment in the future.

  5. The air quality and health co-benefits of alternative post-2020 pathways for achieving peak carbon targets in Jiangsu, China

    NASA Astrophysics Data System (ADS)

    Liu, M.; Bi, J.; Huang, Y.; Kinney, P. L.

    2016-12-01

    Jiangsu, which has three national low-carbon pilot cities, is set to be a model province in China for achieving peak carbon targets before 2030. However, according to local planning of responding to climate change, carbon emissions are projected to keep going up before 2020 even the strictest measures are implemented. In other words, innovative measures must be in action after 2020. This work aimed at assessing the air quality and health co-benefits of alternative post-2020 measures to help remove barriers of policy implementation through tying it to local incentives for air quality improvement. To achieve the aim, we select 2010 as baseline year and develop Bussiness As Usual (BAU) and Traditional Carbon Reduction (TCR) scenarios before 2020. Under BAU, only existing climate and air pollution control policies are considered; under TCR, potential climate policies in local planning and existing air pollution control policies are considered. After 2020, integrated gasification combined cycle (IGCC) plant with carbon capture and storage (CCS) technology and large-scale substitution of renewable energy seem to be two promising pathways for achieving peak carbon targets. Therefore, two additional scenarios (TCR-IGCC and TCR-SRE) are set after 2020. Based on the projections of future energy balances and industrial productions, we estimate the pollutant emissions and simulate PM2.5 and ozone concentrations by 2017, 2020, 2030 and 2050 using CMAQ. Then using health impact assessment approach, the premature deaths are estimated and monetized. Results show that the carbon peak in Jiangsu will be achieved before 2030 only under TCR-IGCC and TCR-SRE scenarios. Under three policy scenarios, Jiangsu's carbon emission control targets would have substantial effects on primary air pollutant emissions far beyond those we estimate would be needed to meet the PM2.5 concentration targets in 2017. Compared with IGCC with CCS, large-scale substitutions of renewable energy bring

  6. Cost analysis of the History, ECG, Age, Risk factors, and initial Troponin (HEART) Pathway randomized control trial.

    PubMed

    Riley, Robert F; Miller, Chadwick D; Russell, Gregory B; Harper, Erin N; Hiestand, Brian C; Hoekstra, James W; Lefebvre, Cedric W; Nicks, Bret A; Cline, David M; Askew, Kim L; Mahler, Simon A

    2017-01-01

    The HEART Pathway is a diagnostic protocol designed to identify low-risk patients presenting to the emergency department with chest pain that are safe for early discharge. This protocol has been shown to significantly decrease health care resource utilization compared with usual care. However, the impact of the HEART Pathway on the cost of care has yet to be reported. We performed a cost analysis of patients enrolled in the HEART Pathway trial, which randomized participants to either usual care or the HEART Pathway protocol. For low-risk patients, the HEART Pathway recommended early discharge from the emergency department without further testing. We compared index visit cost, cost at 30 days, and cardiac-related health care cost at 30 days between the 2 treatment arms. Costs for each patient included facility and professional costs. Cost at 30 days included total inpatient and outpatient costs, including the index encounter, regardless of etiology. Cardiac-related health care cost at 30 days included the index encounter and costs adjudicated to be cardiac-related within that period. Two hundred seventy of the 282 patients enrolled in the trial had cost data available for analysis. There was a significant reduction in cost for the HEART Pathway group at 30 days (median cost savings of $216 per individual), which was most evident in low-risk (Thrombolysis In Myocardial Infarction score of 0-1) patients (median savings of $253 per patient) and driven primarily by lower cardiac diagnostic costs in the HEART Pathway group. Using the HEART Pathway as a decision aid for patients with undifferentiated chest pain resulted in significant cost savings. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Gene profile in the spleen under massive partial hepatectomy using complementary DNA microarray and pathway analysis.

    PubMed

    Arakawa, Yusuke; Shimada, Mitsuo; Utsunomiya, Tohru; Imura, Satoru; Morine, Yuji; Ikemoto, Tetsuya; Mori, Hiroki; Kanamoto, Mami; Iwahashi, Shuichi; Saito, Yu; Takasu, Chie

    2014-08-01

    In general, the spleen is one of the abdominal organs connected by the portal system, and a splenectomy improves hepatic functions in the settings of partial hepatectomy (Hx) for portal hypertensive cases or living donor liver transplantation with excessive portal vein flow. Those precise mechanisms remain still unclear; therefore, we investigated the DNA expression profile in the spleen after 90% Hx in rats using complementary DNA microarray and pathway analysis. Messenger RNAs (mRNAs) were prepared from three rat spleens at each time point (0, 3, and 6 h after 90% Hx). Using the gene chip, mRNA was hybridized to Affymetrix GeneChip Rat Genome 230 2.0 Array (Affymetrix®) and pathway analysis was done with Ingenuity Pathway Analysis (IPA®). We determined the 3-h or 6-h/0-h ratio to assess the influence of Hx, and cut-off values were set at more than 2.0-fold or less than 1/2 (0.5)-fold. Chemokine activity-related genes including Cxcl1 (GRO1) and Cxcl2 (MIP-2) related pathway were upregulated in the spleen. Also, immediate early response genes including early growth response-1 (EGR1), FBJ murine osteosarcoma (FOS) and activating transcription factor 3 (ATF3) related pathway were upregulated in the spleen. We concluded that in the spleen the expression of numerous inflammatory-related genes would occur after 90% Hx. The spleen could take a harmful role and provide a negative impact during post Hx phase due to the induction of chemokine and transcription factors including GRO1 and EGR1. © 2014 Journal of Gastroenterology and Hepatology Foundation and Wiley Publishing Asia Pty Ltd.

  8. Analysis of PIK3CA Mutations and Activation Pathways in Triple Negative Breast Cancer

    PubMed Central

    Muroni, Maria Rosaria; Sanges, Francesca; Sotgiu, Giovanni; Ena, Sara; Pira, Giovanna; Murgia, Luciano; Manca, Alessandra; Uras, Maria Gabriela; Sarobba, Maria Giuseppina; Urru, Silvana; De Miglio, Maria Rosaria

    2015-01-01

    Background Triple Negative Breast Cancer (TNBC) accounts for 12–24% of all breast carcinomas, and shows worse prognosis compared to other breast cancer subtypes. Molecular studies demonstrated that TNBCs are a heterogeneous group of tumors with different clinical and pathologic features, prognosis, genetic-molecular alterations and treatment responsivity. The PI3K/AKT is a major pathway involved in the regulation of cell survival and proliferation, and is the most frequently altered pathway in breast cancer, apparently with different biologic impact on specific cancer subtypes. The most common genetic abnormality is represented by PIK3CA gene activating mutations, with an overall frequency of 20–40%. The aims of our study were to investigate PIK3CA gene mutations on a large series of TNBC, to perform a wider analysis on genetic alterations involving PI3K/AKT and BRAF/RAS/MAPK pathways and to correlate the results with clinical-pathologic data. Materials and Methods PIK3CA mutation analysis was performed by using cobas® PIK3CA Mutation Test. EGFR, AKT1, BRAF, and KRAS genes were analyzed by sequencing. Immunohistochemistry was carried out to identify PTEN loss and to investigate for PI3K/AKT pathways components. Results PIK3CA mutations were detected in 23.7% of TNBC, whereas no mutations were identified in EGFR, AKT1, BRAF, and KRAS genes. Moreover, we observed PTEN loss in 11.3% of tumors. Deregulation of PI3K/AKT pathways was revealed by consistent activation of pAKT and p-p44/42 MAPK in all PIK3CA mutated TNBC. Conclusions Our data shows that PIK3CA mutations and PI3K/AKT pathway activation are common events in TNBC. A deeper investigation on specific TNBC genomic abnormalities might be helpful in order to select patients who would benefit from current targeted therapy strategies. PMID:26540293

  9. Analysis of aromatic catabolic pathways in Pseudomonas putida KT 2440 using a combined proteomic approach: 2-DE/MS and cleavable isotope-coded affinity tag analysis.

    PubMed

    Kim, Young Hwan; Cho, Kun; Yun, Sung-Ho; Kim, Jin Young; Kwon, Kyung-Hoon; Yoo, Jong Shin; Kim, Seung Il

    2006-02-01

    Proteomic analysis of Pseudomonas putida KT2440 cultured in monocyclic aromatic compounds was performed using 2-DE/MS and cleavable isotope-coded affinity tag (ICAT) to determine whether proteins involved in aromatic compound degradation pathways were altered as predicted by genomic analysis (Jiménez et al., Environ Microbiol. 2002, 4, 824-841). Eighty unique proteins were identified by 2-DE/MS or MS/MS analysis from P. putida KT2440 cultured in the presence of six different organic compounds. Benzoate dioxygenase (BenA, BenD) and catechol 1,2-dioxygenase (CatA) were induced by benzoate. Protocatechuate 3,4-dixoygenase (PcaGH) was induced by p-hydroxybenzoate and vanilline. beta-Ketoadipyl CoA thiolase (PcaF) and 3-oxoadipate enol-lactone hydrolase (PcaD) were induced by benzoate, p-hydroxybenzoate and vanilline, suggesting that benzoate, p-hydroxybenzoate and vanilline were degraded by different dioxygenases and then converged in the same beta-ketoadipate degradation pathway. An additional 110 proteins, including 19 proteins from 2-DE analysis, were identified by cleavable ICAT analysis for benzoate-induced proteomes, which complemented the 2-DE results. Phenylethylamine exposure induced beta-ketoacyl CoA thiolase (PhaD) and ring-opening enzyme (PhaL), both enzymes of the phenylacetate (pha) biodegradation pathway. Phenylalanine induced 4-hydroxyphenyl-pyruvate dioxygenase (Hpd) and homogentisate 1,2-dioxygenase (HmgA), key enzymes in the homogentisate degradation pathway. Alkyl hydroperoxide reductase (AphC) was induced under all aromatic compounds conditions. These results suggest that proteome analysis complements and supports predictive information obtained by genomic sequence analysis.

  10. Estimating pathway-specific contributions to biodegradation in aquifers based on dual isotope analysis: theoretical analysis and reactive transport simulations.

    PubMed

    Centler, Florian; Heße, Falk; Thullner, Martin

    2013-09-01

    At field sites with varying redox conditions, different redox-specific microbial degradation pathways contribute to total contaminant degradation. The identification of pathway-specific contributions to total contaminant removal is of high practical relevance, yet difficult to achieve with current methods. Current stable-isotope-fractionation-based techniques focus on the identification of dominant biodegradation pathways under constant environmental conditions. We present an approach based on dual stable isotope data to estimate the individual contributions of two redox-specific pathways. We apply this approach to carbon and hydrogen isotope data obtained from reactive transport simulations of an organic contaminant plume in a two-dimensional aquifer cross section to test the applicability of the method. To take aspects typically encountered at field sites into account, additional simulations addressed the effects of transverse mixing, diffusion-induced stable-isotope fractionation, heterogeneities in the flow field, and mixing in sampling wells on isotope-based estimates for aerobic and anaerobic pathway contributions to total contaminant biodegradation. Results confirm the general applicability of the presented estimation method which is most accurate along the plume core and less accurate towards the fringe where flow paths receive contaminant mass and associated isotope signatures from the core by transverse dispersion. The presented method complements the stable-isotope-fractionation-based analysis toolbox. At field sites with varying redox conditions, it provides a means to identify the relative importance of individual, redox-specific degradation pathways. © 2013.

  11. Numerical analysis of air-flow and temperature field in a passenger car compartment

    NASA Astrophysics Data System (ADS)

    Kamar, Haslinda Mohamed; Kamsah, Nazri; Mohammad Nor, Ahmad Miski

    2012-06-01

    This paper presents a numerical study on the temperature field inside a passenger's compartment of a Proton Wira saloon car using computational fluid dynamics (CFD) method. The main goal is to investigate the effects of different glazing types applied onto the front and rear windscreens of the car on the distribution of air-temperature inside the passenger compartment in the steady-state conditions. The air-flow condition in the passenger's compartment is also investigated. Fluent CFD software was used to develop a three-dimensional symmetrical model of the passenger's compartment. Simplified representations of the driver and one rear passenger were incorporated into the CFD model of the passenger's compartment. Two types of glazing were considered namely clear insulated laminated tint (CIL) with a shading coefficient of 0.78 and green insulated laminate tint (GIL) with a shading coefficient of 0.5. Results of the CFD analysis were compared with those obtained when the windscreens are made up of clear glass having a shading coefficient of 0.86. Results of the CFD analysis show that for a given glazing material, the temperature of the air around the driver is slightly lower than the air around the rear passenger. Also, the use of GIL glazing material on both the front and rear windscreens significantly reduces the air temperature inside the passenger's compartment of the car. This contributes to a better thermal comfort condition to the occupants. Swirling air flow condition occurs in the passenger compartment. The air-flow intensity and velocity are higher along the side wall of the passenger's compartment compared to that along the middle section of the compartment. It was also found that the use of glazing materials on both the front and rear windscreen has no significant effects on the air-flow condition inside the passenger's compartment of the car.

  12. Global Air Quality and Climate

    NASA Technical Reports Server (NTRS)

    Fiore, Arlene M.; Naik, Vaishali; Steiner, Allison; Unger, Nadine; Bergmann, Dan; Prather, Michael; Righi, Mattia; Rumbold, Steven T.; Shindell, Drew T.; Skeie, Ragnhild B.; hide

    2012-01-01

    Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O3 and SOA.

  13. Global air quality and climate.

    PubMed

    Fiore, Arlene M; Naik, Vaishali; Spracklen, Dominick V; Steiner, Allison; Unger, Nadine; Prather, Michael; Bergmann, Dan; Cameron-Smith, Philip J; Cionni, Irene; Collins, William J; Dalsøren, Stig; Eyring, Veronika; Folberth, Gerd A; Ginoux, Paul; Horowitz, Larry W; Josse, Béatrice; Lamarque, Jean-François; MacKenzie, Ian A; Nagashima, Tatsuya; O'Connor, Fiona M; Righi, Mattia; Rumbold, Steven T; Shindell, Drew T; Skeie, Ragnhild B; Sudo, Kengo; Szopa, Sophie; Takemura, Toshihiko; Zeng, Guang

    2012-10-07

    the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O(3) and SOA.

  14. An Optimal Bahadur-Efficient Method in Detection of Sparse Signals with Applications to Pathway Analysis in Sequencing Association Studies.

    PubMed

    Dai, Hongying; Wu, Guodong; Wu, Michael; Zhi, Degui

    2016-01-01

    Next-generation sequencing data pose a severe curse of dimensionality, complicating traditional "single marker-single trait" analysis. We propose a two-stage combined p-value method for pathway analysis. The first stage is at the gene level, where we integrate effects within a gene using the Sequence Kernel Association Test (SKAT). The second stage is at the pathway level, where we perform a correlated Lancaster procedure to detect joint effects from multiple genes within a pathway. We show that the Lancaster procedure is optimal in Bahadur efficiency among all combined p-value methods. The Bahadur efficiency,[Formula: see text], compares sample sizes among different statistical tests when signals become sparse in sequencing data, i.e. ε →0. The optimal Bahadur efficiency ensures that the Lancaster procedure asymptotically requires a minimal sample size to detect sparse signals ([Formula: see text]). The Lancaster procedure can also be applied to meta-analysis. Extensive empirical assessments of exome sequencing data show that the proposed method outperforms Gene Set Enrichment Analysis (GSEA). We applied the competitive Lancaster procedure to meta-analysis data generated by the Global Lipids Genetics Consortium to identify pathways significantly associated with high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, and total cholesterol.

  15. Heading in the right direction: thermodynamics-based network analysis and pathway engineering.

    PubMed

    Ataman, Meric; Hatzimanikatis, Vassily

    2015-12-01

    Thermodynamics-based network analysis through the introduction of thermodynamic constraints in metabolic models allows a deeper analysis of metabolism and guides pathway engineering. The number and the areas of applications of thermodynamics-based network analysis methods have been increasing in the last ten years. We review recent applications of these methods and we identify the areas that such analysis can contribute significantly, and the needs for future developments. We find that organisms with multiple compartments and extremophiles present challenges for modeling and thermodynamics-based flux analysis. The evolution of current and new methods must also address the issues of the multiple alternatives in flux directionalities and the uncertainties and partial information from analytical methods. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  16. Cancer Transcriptome Dataset Analysis: Comparing Methods of Pathway and Gene Regulatory Network-Based Cluster Identification.

    PubMed

    Nam, Seungyoon

    2017-04-01

    Cancer transcriptome analysis is one of the leading areas of Big Data science, biomarker, and pharmaceutical discovery, not to forget personalized medicine. Yet, cancer transcriptomics and postgenomic medicine require innovation in bioinformatics as well as comparison of the performance of available algorithms. In this data analytics context, the value of network generation and algorithms has been widely underscored for addressing the salient questions in cancer pathogenesis. Analysis of cancer trancriptome often results in complicated networks where identification of network modularity remains critical, for example, in delineating the "druggable" molecular targets. Network clustering is useful, but depends on the network topology in and of itself. Notably, the performance of different network-generating tools for network cluster (NC) identification has been little investigated to date. Hence, using gastric cancer (GC) transcriptomic datasets, we compared two algorithms for generating pathway versus gene regulatory network-based NCs, showing that the pathway-based approach better agrees with a reference set of cancer-functional contexts. Finally, by applying pathway-based NC identification to GC transcriptome datasets, we describe cancer NCs that associate with candidate therapeutic targets and biomarkers in GC. These observations collectively inform future research on cancer transcriptomics, drug discovery, and rational development of new analysis tools for optimal harnessing of omics data.

  17. Transport pathway and source area for Artemisia pollen in Beijing, China

    NASA Astrophysics Data System (ADS)

    Qin, Xiaoxin; Li, Yiyin; Sun, Xu; Meng, Ling; Wang, Xiaoke

    2017-12-01

    Artemisia pollen is an important allergen responsible for allergic rhinitis in Beijing, China. To explore the transport pathways and source areas of Artemisia pollen, we used Burkard 7-day traps to monitor daily pollen concentrations in 2016 in an urban and suburban locality. Backward trajectories of 24- and 96-h and their cluster analysis were performed to identify transport pathways of Artemisia pollen using the HYSPLIT model on 0.5° × 0.5° GADS meteorological data. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) were calculated to further identify the major potential source areas at local, regional, and long-range scales. Our results showed significant differences in Artemisia pollen concentration between urban and suburban areas, attributed to differences in plant distribution and altitude of the sampling locality. Such differences arisen from both pollen emission and air mass movements, hence pollen dispersal. At local or regional scales, source area of northwestern parts of Beijing City, Hebei Province and northern and northwestern parts of Inner Mongolia influenced the major transport pathways of Artemisia pollen. Transport pathway at a long-range scale and its corresponding source area extended to northwestern parts of Mongolia. The regional-scale transport affected by wind and altitude is more profound for Artemisia pollen at the suburban than at the urban station.

  18. Economic and energetic analysis of capturing CO2 from ambient air

    PubMed Central

    House, Kurt Zenz; Baclig, Antonio C.; Ranjan, Manya; van Nierop, Ernst A.; Wilcox, Jennifer; Herzog, Howard J.

    2011-01-01

    Capturing carbon dioxide from the atmosphere (“air capture”) in an industrial process has been proposed as an option for stabilizing global CO2 concentrations. Published analyses suggest these air capture systems may cost a few hundred dollars per tonne of CO2, making it cost competitive with mainstream CO2 mitigation options like renewable energy, nuclear power, and carbon dioxide capture and storage from large CO2 emitting point sources. We investigate the thermodynamic efficiencies of commercial separation systems as well as trace gas removal systems to better understand and constrain the energy requirements and costs of these air capture systems. Our empirical analyses of operating commercial processes suggest that the energetic and financial costs of capturing CO2 from the air are likely to have been underestimated. Specifically, our analysis of existing gas separation systems suggests that, unless air capture significantly outperforms these systems, it is likely to require more than 400 kJ of work per mole of CO2, requiring it to be powered by CO2-neutral power sources in order to be CO2 negative. We estimate that total system costs of an air capture system will be on the order of $1,000 per tonne of CO2, based on experience with as-built large-scale trace gas removal systems. PMID:22143760

  19. Note of the methodological flaws in the paper entitled "Polymorphisms in IL-4/IL-13 pathway genes and glioma risk: an updated meta-analysis".

    PubMed

    Wang, Ting-Ting; Li, Jin-Mei; Zhou, Dong

    2016-01-01

    With great interest, we read the paper "Polymorphisms in IL-4/IL-13 pathway genes and glioma risk: an updated meta-analysis" (by Chen PQ et al.) [1], which has reached important conclusions about the relationship between polymorphisms in interleukin (IL)-4/IL-13 pathway genes and glioma risk. Through quantitative analysis, the meta-analysis found no association between IL-4/IL-13 pathway genetic polymorphisms and glioma risk (Chen et al. in Tumor Biol 36:121-127, 2015). The meta-analysis is the most comprehensive study of polymorphisms in the IL-4/IL-13 pathway and glioma risk. Nevertheless, some deficiencies still exist in this meta-analysis that we would like to raise.

  20. Comparative In silico Analysis of Butyrate Production Pathways in Gut Commensals and Pathogens.

    PubMed

    Anand, Swadha; Kaur, Harrisham; Mande, Sharmila S

    2016-01-01

    Biosynthesis of butyrate by commensal bacteria plays a crucial role in maintenance of human gut health while dysbiosis in gut microbiome has been linked to several enteric disorders. Contrastingly, butyrate shows cytotoxic effects in patients with oral diseases like periodontal infections and oral cancer. In addition to these host associations, few syntrophic bacteria couple butyrate degradation with sulfate reduction and methane production. Thus, it becomes imperative to understand the distribution of butyrate metabolism pathways and delineate differences in substrate utilization between pathogens and commensals. The bacteria utilize four pathways for butyrate production with different initial substrates (Pyruvate, 4-aminobutyrate, Glutarate and Lysine) which follow a polyphyletic distribution. A comprehensive mining of complete/draft bacterial genomes indicated conserved juxtaposed genomic arrangement in all these pathways. This gene context information was utilized for an accurate annotation of butyrate production pathways in bacterial genomes. Interestingly, our analysis showed that inspite of a beneficial impact of butyrate in gut, not only commensals, but a few gut pathogens also possess butyrogenic pathways. The results further illustrated that all the gut commensal bacteria ( Faecalibacterium, Roseburia, Butyrivibrio , and commensal species of Clostridia etc) ferment pyruvate for butyrate production. On the contrary, the butyrogenic gut pathogen Fusobacterium utilizes different amino acid metabolism pathways like those for Glutamate (4-aminobutyrate and Glutarate) and Lysine for butyrogenesis which leads to a concomitant release of harmful by-products like ammonia in the process. The findings in this study indicate that commensals and pathogens in gut have divergently evolved to produce butyrate using distinct pathways. No such evolutionary selection was observed in oral pathogens ( Porphyromonas and Filifactor ) which showed presence of pyruvate as well as

  1. Genomic analysis of wig-1 pathways.

    PubMed

    Sedaghat, Yalda; Mazur, Curt; Sabripour, Mahyar; Hung, Gene; Monia, Brett P

    2012-01-01

    Wig-1 is a transcription factor regulated by p53 that can interact with hnRNP A2/B1, RNA Helicase A, and dsRNAs, which plays an important role in RNA and protein stabilization. in vitro studies have shown that wig-1 binds p53 mRNA and stabilizes it by protecting it from deadenylation. Furthermore, p53 has been implicated as a causal factor in neurodegenerative diseases based in part on its selective regulatory function on gene expression, including genes which, in turn, also possess regulatory functions on gene expression. In this study we focused on the wig-1 transcription factor as a downstream p53 regulated gene and characterized the effects of wig-1 down regulation on gene expression in mouse liver and brain. Antisense oligonucleotides (ASOs) were identified that specifically target mouse wig-1 mRNA and produce a dose-dependent reduction in wig-1 mRNA levels in cell culture. These wig-1 ASOs produced marked reductions in wig-1 levels in liver following intraperitoneal administration and in brain tissue following ASO administration through a single striatal bolus injection in FVB and BACHD mice. Wig-1 suppression was well tolerated and resulted in the reduction of mutant Htt protein levels in BACHD mouse brain but had no effect on normal Htt protein levels nor p53 mRNA or protein levels. Expression microarray analysis was employed to determine the effects of wig-1 suppression on genome-wide expression in mouse liver and brain. Reduction of wig-1 caused both down regulation and up regulation of several genes, and a number of wig-1 regulated genes were identified that potentially links wig-1 various signaling pathways and diseases. Antisense oligonucleotides can effectively reduce wig-1 levels in mouse liver and brain, which results in specific changes in gene expression for pathways relevant to both the nervous system and cancer.

  2. Genomic Analysis of wig-1 Pathways

    PubMed Central

    Sedaghat, Yalda; Mazur, Curt; Sabripour, Mahyar; Hung, Gene; Monia, Brett P.

    2012-01-01

    Background Wig-1 is a transcription factor regulated by p53 that can interact with hnRNP A2/B1, RNA Helicase A, and dsRNAs, which plays an important role in RNA and protein stabilization. in vitro studies have shown that wig-1 binds p53 mRNA and stabilizes it by protecting it from deadenylation. Furthermore, p53 has been implicated as a causal factor in neurodegenerative diseases based in part on its selective regulatory function on gene expression, including genes which, in turn, also possess regulatory functions on gene expression. In this study we focused on the wig-1 transcription factor as a downstream p53 regulated gene and characterized the effects of wig-1 down regulation on gene expression in mouse liver and brain. Methods and Results Antisense oligonucleotides (ASOs) were identified that specifically target mouse wig-1 mRNA and produce a dose-dependent reduction in wig-1 mRNA levels in cell culture. These wig-1 ASOs produced marked reductions in wig-1 levels in liver following intraperitoneal administration and in brain tissue following ASO administration through a single striatal bolus injection in FVB and BACHD mice. Wig-1 suppression was well tolerated and resulted in the reduction of mutant Htt protein levels in BACHD mouse brain but had no effect on normal Htt protein levels nor p53 mRNA or protein levels. Expression microarray analysis was employed to determine the effects of wig-1 suppression on genome-wide expression in mouse liver and brain. Reduction of wig-1 caused both down regulation and up regulation of several genes, and a number of wig-1 regulated genes were identified that potentially links wig-1 various signaling pathways and diseases. Conclusion Antisense oligonucleotides can effectively reduce wig-1 levels in mouse liver and brain, which results in specific changes in gene expression for pathways relevant to both the nervous system and cancer. PMID:22347364

  3. Internal air flow analysis of a bladeless micro aerial vehicle hemisphere body using computational fluid dynamic

    NASA Astrophysics Data System (ADS)

    Othman, M. N. K.; Zuradzman, M. Razlan; Hazry, D.; Khairunizam, Wan; Shahriman, A. B.; Yaacob, S.; Ahmed, S. Faiz; Hussain, Abadalsalam T.

    2014-12-01

    This paper explain the analysis of internal air flow velocity of a bladeless vertical takeoff and landing (VTOL) Micro Aerial Vehicle (MAV) hemisphere body. In mechanical design, before produce a prototype model, several analyses should be done to ensure the product's effectiveness and efficiency. There are two types of analysis method can be done in mechanical design; mathematical modeling and computational fluid dynamic. In this analysis, I used computational fluid dynamic (CFD) by using SolidWorks Flow Simulation software. The idea came through to overcome the problem of ordinary quadrotor UAV which has larger size due to using four rotors and the propellers are exposed to environment. The bladeless MAV body is designed to protect all electronic parts, which means it can be used in rainy condition. It also has been made to increase the thrust produced by the ducted propeller compare to exposed propeller. From the analysis result, the air flow velocity at the ducted area increased to twice the inlet air. This means that the duct contribute to the increasing of air velocity.

  4. Internal air flow analysis of a bladeless micro aerial vehicle hemisphere body using computational fluid dynamic

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Othman, M. N. K., E-mail: najibkhir86@gmail.com, E-mail: zuradzman@unimap.edu.my, E-mail: hazry@unimap.edu.my, E-mail: khairunizam@unimap.edu.my, E-mail: shahriman@unimap.edu.my, E-mail: s.yaacob@unimap.edu.my, E-mail: syedfaiz@unimap.edu.my, E-mail: abadal@unimap.edu.my; Zuradzman, M. Razlan, E-mail: najibkhir86@gmail.com, E-mail: zuradzman@unimap.edu.my, E-mail: hazry@unimap.edu.my, E-mail: khairunizam@unimap.edu.my, E-mail: shahriman@unimap.edu.my, E-mail: s.yaacob@unimap.edu.my, E-mail: syedfaiz@unimap.edu.my, E-mail: abadal@unimap.edu.my; Hazry, D., E-mail: najibkhir86@gmail.com, E-mail: zuradzman@unimap.edu.my, E-mail: hazry@unimap.edu.my, E-mail: khairunizam@unimap.edu.my, E-mail: shahriman@unimap.edu.my, E-mail: s.yaacob@unimap.edu.my, E-mail: syedfaiz@unimap.edu.my, E-mail: abadal@unimap.edu.my

    2014-12-04

    This paper explain the analysis of internal air flow velocity of a bladeless vertical takeoff and landing (VTOL) Micro Aerial Vehicle (MAV) hemisphere body. In mechanical design, before produce a prototype model, several analyses should be done to ensure the product's effectiveness and efficiency. There are two types of analysis method can be done in mechanical design; mathematical modeling and computational fluid dynamic. In this analysis, I used computational fluid dynamic (CFD) by using SolidWorks Flow Simulation software. The idea came through to overcome the problem of ordinary quadrotor UAV which has larger size due to using four rotors andmore » the propellers are exposed to environment. The bladeless MAV body is designed to protect all electronic parts, which means it can be used in rainy condition. It also has been made to increase the thrust produced by the ducted propeller compare to exposed propeller. From the analysis result, the air flow velocity at the ducted area increased to twice the inlet air. This means that the duct contribute to the increasing of air velocity.« less

  5. Metabolomics Coupled with Multivariate Data and Pathway Analysis on Potential Biomarkers in Gastric Ulcer and Intervention Effects of Corydalis yanhusuo Alkaloid

    PubMed Central

    Shuai, Wang; Yongrui, Bao; Shanshan, Guan; Bo, Liu; Lu, Chen; Lei, Wang; Xiaorong, Ran

    2014-01-01

    Metabolomics, the systematic analysis of potential metabolites in a biological specimen, has been increasingly applied to discovering biomarkers, identifying perturbed pathways, measuring therapeutic targets, and discovering new drugs. By analyzing and verifying the significant difference in metabolic profiles and changes of metabolite biomarkers, metabolomics enables us to better understand substance metabolic pathways which can clarify the mechanism of Traditional Chinese Medicines (TCM). Corydalis yanhusuo alkaloid (CA) is a major component of Qizhiweitong (QZWT) prescription which has been used for treating gastric ulcer for centuries and its mechanism remains unclear completely. Metabolite profiling was performed by high-performance liquid chromatography combined with time-of-flight mass spectrometry (HPLC/ESI-TOF-MS) and in conjunction with multivariate data analysis and pathway analysis. The statistic software Mass Profiller Prossional (MPP) and statistic method including ANOVA and principal component analysis (PCA) were used for discovering novel potential biomarkers to clarify mechanism of CA in treating acid injected rats with gastric ulcer. The changes in metabolic profiling were restored to their base-line values after CA treatment according to the PCA score plots. Ten different potential biomarkers and seven key metabolic pathways contributing to the treatment of gastric ulcer were discovered and identified. Among the pathways, sphingophospholipid metabolism and fatty acid metabolism related network were acutely perturbed. Quantitative real time polymerase chain reaction (RT-PCR) analysis were performed to evaluate the expression of genes related to the two pathways for verifying the above results. The results show that changed biomarkers and pathways may provide evidence to insight into drug action mechanisms and enable us to increase research productivity toward metabolomics drug discovery. PMID:24454691

  6. An Analysis of the Cost Accounting System for the Depot Maintenance Service, Air Force Industrial Fund.

    DTIC Science & Technology

    1987-09-01

    AN A NALYSIS OF THE COST ACCOUNTING SYSTEM FOR THE DEPOT 1/1 MRINTENANCE SERVI..(U) MIR FORCE INST OF TECH IIGHT-PTTERSON RFB OH SCHOOL OF SYST.. 0 L...I "VV h S~ ~~i FiLE COV, THSI CIO ~OF AN ANALYSIS OF THE COST ACCOUNTING SYSTEM FOR THE DEPOT MAINTENANCE SERVICE, AIR FORCE INDUSTRIAL FUND...Patterson Air Force Base, Ohio ~ p~UOW~~ ’ I ~ 1 12 02 0 AFIT/GLM/LSY/87S-83 AN ANALYSIS OF THE COST ACCOUNTING SYSTEM FOR THE DEPOT MAINTENANCE SERVICE, AIR

  7. [Design and implementation of online statistical analysis function in information system of air pollution and health impact monitoring].

    PubMed

    Lü, Yiran; Hao, Shuxin; Zhang, Guoqing; Liu, Jie; Liu, Yue; Xu, Dongqun

    2018-01-01

    To implement the online statistical analysis function in information system of air pollution and health impact monitoring, and obtain the data analysis information real-time. Using the descriptive statistical method as well as time-series analysis and multivariate regression analysis, SQL language and visual tools to implement online statistical analysis based on database software. Generate basic statistical tables and summary tables of air pollution exposure and health impact data online; Generate tendency charts of each data part online and proceed interaction connecting to database; Generate butting sheets which can lead to R, SAS and SPSS directly online. The information system air pollution and health impact monitoring implements the statistical analysis function online, which can provide real-time analysis result to its users.

  8. RNA-Seq Expression Analysis of Enteric Neuron Cells with Rotenone Treatment and Prediction of Regulated Pathways.

    PubMed

    Guan, Qiang; Wang, Xijin; Jiang, Yanyan; Zhao, Lijuan; Nie, Zhiyu; Jin, Lingjing

    2017-02-01

    The enteric nervous system (ENS) is involved in the initiation and development of the pathological process of Parkinson's disease (PD). The effect of rotenone on the ENS may trigger the progression of PD through the central nervous system (CNS). In this study, we used RNA-sequencing (RNA-seq) analysis to examine differential expression genes (DEGs) and pathways induced by in vitro treatment of rotenone in the enteric nervous cells isolated from rats. We identified 45 up-regulated and 30 down-regulated genes. The functional categorization revealed that the DEGs were involved in the regulation of cell differentiation and development, response to various stimuli, and regulation of neurogenesis. In addition, the pathway and network analysis showed that the Mitogen Activated Protein Kinase (MAPK), Toll-like receptor, Wnt, and Ras signaling pathways were intensively involved in the effect of rotenone on the ENS. Additionally, the quantitative real-time polymerase chain reaction result for the selected seven DEGs matched those of the RNA-seq analysis. Our results present a significant step in the identification of DEGs and provide new insight into the progression of PD in the rotenone-induced model.

  9. Automation Applications in an Advance Air Traffic Management System : Volume IIB : Functional Analysis of Air Traffic Management (Cont'd)

    DOT National Transportation Integrated Search

    1974-08-01

    Volume 2 contains the analysis and description of air traffic management activities at three levels of detail - functions, subfunctions, and tasks. A total of 265 tasks are identified and described, and the flow of information inputs and outputs amon...

  10. Control of asthma triggers in indoor air with air cleaners: a modeling analysis.

    PubMed

    Myatt, Theodore A; Minegishi, Taeko; Allen, Joseph G; Macintosh, David L

    2008-08-06

    Reducing exposure to environmental agents indoors shown to increase asthma symptoms or lead to asthma exacerbations is an important component of a strategy to manage asthma for individuals. Numerous investigations have demonstrated that portable air cleaning devices can reduce concentrations of asthma triggers in indoor air; however, their benefits for breathing problems have not always been reproducible. The potential exposure benefits of whole house high efficiency in-duct air cleaners for sensitive subpopulations have yet to be evaluated. We used an indoor air quality modeling system (CONTAM) developed by NIST to examine peak and time-integrated concentrations of common asthma triggers present in indoor air over a year as a function of natural ventilation, portable air cleaners, and forced air ventilation equipped with conventional and high efficiency filtration systems. Emission rates for asthma triggers were based on experimental studies published in the scientific literature. Forced air systems with high efficiency filtration were found to provide the best control of asthma triggers: 30-55% lower cat allergen levels, 90-99% lower risk of respiratory infection through the inhalation route of exposure, 90-98% lower environmental tobacco smoke (ETS) levels, and 50-75% lower fungal spore levels than the other ventilation/filtration systems considered. These results indicate that the use of high efficiency in-duct air cleaners provide an effective means of controlling allergen levels not only in a single room, like a portable air cleaner, but the whole house. These findings are useful for evaluating potential benefits of high efficiency in-duct filtration systems for controlling exposure to asthma triggers indoors and for the design of trials of environmental interventions intended to evaluate their utility in practice.

  11. Relative air temperature analysis external building on Gowa Campus

    NASA Astrophysics Data System (ADS)

    Mustamin, Tayeb; Rahim, Ramli; Baharuddin; Jamala, Nurul; Kusno, Asniawaty

    2018-03-01

    This study aims to data analyze the relative temperature and humidity of the air outside the building. Data retrieval taken from weather monitoring device (monitoring) Vaisala, RTU (Remote Terminal Unit), Which is part of the AWS (Automatic Weather Stations) Then Processing data processed and analyzed by using Microsoft Excel program in the form of graph / picture fluctuation Which shows the average value, standard deviation, maximum value, and minimum value. Results of data processing then grouped in the form: Daily, and monthly, based on time intervals every 30 minutes. The results showed Outside air temperatures in March, April, May and September 2016 Which entered in the thermal comfort zone according to SNI standard (Indonesian National Standard) only at 06.00-10.00. In late March to early April Thermal comfort zone also occurs at 15.30-18.00. The highest maximum air temperature occurred in September 2016 at 11.01-11.30 And the lowest minimum value in September 2016, time 6:00 to 6:30. The result of the next analysis shows the level of data conformity with thermal comfort zone based on SNI (Indonesian National Standard) every month.

  12. The Use of Sensory Analysis Techniques to Assess the Quality of Indoor Air.

    PubMed

    Lewkowska, Paulina; Dymerski, Tomasz; Gębicki, Jacek; Namieśnik, Jacek

    2017-01-02

    The quality of indoor air is one of the significant elements that influences people's well-being and health inside buildings. Emissions of pollutants, which may cause odor nuisance, are the main reason for people's complaints regarding the quality of indoor air. As a result, it is necessary to perform tests aimed at identifying the sources of odors inside buildings. The article contains basic information on the characteristics of the sources of indoor air pollution and the influence of the odor detection threshold on people's health and comfort. An attempt was also made to classify and use sensory analysis techniques to perform tests of the quality of indoor air, which would enable identification of sensory experience and would allow for indication of the degree of their intensity.

  13. [Sources analysis and contribution identification of polycyclic aromatic hydrocarbons in indoor and outdoor air of Hangzhou].

    PubMed

    Liu, Y; Zhu, L; Wang, J; Shen, X; Chen, X

    2001-11-01

    Twelve polycyclic aromatic hydrocarbons (PAHs) were measured in eight homes in Hangzhou during the summer and autumn in 1999. The sources of PAHs and the contributions of the sources to the total concentration of PAHs in the indoor air were identified by the combination of correlation analysis, factor analysis and multiple regression, and the equations between the concentrations of PAHs in indoor and outdoor air and factors were got. It was indicated that the factors of PAHs in the indoor air were domestic cuisine, the volatility of the mothball, cigarette smoke and heating, the waste gas from vehicles. In the smokers' home, cigarette smoke was the most important factor, and it contributed 25.8% of BaP to the indoor air of smokers' home.

  14. Signaling Pathways Involved in Lunar Dust Induced Cytotoxicity

    NASA Technical Reports Server (NTRS)

    Zhang, Ye; Lam, Chiu-Wing; Scully, Robert R.; Williams, Kyle; Zalesak, Selina; Wu, Honglu; James, John T.

    2014-01-01

    The Moon's surface is covered by a layer of fine, reactive dust. Lunar dust contain about 1-2% of very fine dust (< 3 micron), that is respirable. The habitable area of any lunar landing vehicle and outpost would inevitably be contaminated with lunar dust that could pose a health risk. The purpose of the study is to evaluate the toxicity of Apollo moon dust in rodents to assess the health risk of dust exposures to humans. One of the particular interests in the study is to evaluate dust-induced changes of the expression of fibrosis-related genes, and to identify specific signaling pathways involved in lunar dust-induced toxicity. F344 rats were exposed for 4 weeks (6h/d; 5d/wk) in nose-only inhalation chambers to concentrations of 0 (control air), 2.1, 6.1, 21, and 61 mg/m(exp 3) of lunar dust. Five rats per group were euthanized 1 day, 1 week, 1 month, and 3 months after the last inhalation exposure. The total RNAs were isolated from the blood or lung tissue after being lavaged, using the Qigen RNeasy kit. The Rat Fibrosis RT2 Profile PCR Array was used to profile the expression of 84 genes relevant to fibrosis. The genes with significant expression changes are identified and the gene expression data were further analyzed using IPA pathway analysis tool to determine the signaling pathways with significant changes.

  15. Pathway modeling of microarray data: A case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP)

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ovacik, Meric A.; Sen, Banalata; Euling, Susan Y.

    Pathway activity level analysis, the approach pursued in this study, focuses on all genes that are known to be members of metabolic and signaling pathways as defined by the KEGG database. The pathway activity level analysis entails singular value decomposition (SVD) of the expression data of the genes constituting a given pathway. We explore an extension of the pathway activity methodology for application to time-course microarray data. We show that pathway analysis enhances our ability to detect biologically relevant changes in pathway activity using synthetic data. As a case study, we apply the pathway activity level formulation coupled with significancemore » analysis to microarray data from two different rat testes exposed in utero to Dibutyl Phthalate (DBP). In utero DBP exposure in the rat results in developmental toxicity of a number of male reproductive organs, including the testes. One well-characterized mode of action for DBP and the male reproductive developmental effects is the repression of expression of genes involved in cholesterol transport, steroid biosynthesis and testosterone synthesis that lead to a decreased fetal testicular testosterone. Previous analyses of DBP testes microarray data focused on either individual gene expression changes or changes in the expression of specific genes that are hypothesized, or known, to be important in testicular development and testosterone synthesis. However, a pathway analysis may inform whether there are additional affected pathways that could inform additional modes of action linked to DBP developmental toxicity. We show that Pathway activity analysis may be considered for a more comprehensive analysis of microarray data.« less

  16. Functional Mission Analysis (FMA) for the Air Force Cyber Squadron Initiative (CS I)

    DTIC Science & Technology

    2017-03-17

    Analysis for the Air Force Cyber Squadron Initiative DESIGN PROJECT CONDUCTED 13 FEB – 17 FEB 17 Produced with input from numerous units...Success The Air Force’s base-level Communications Squadrons are engaged in a cultural and technological transformation through the Cyber Squadron...sharpening their focus to include active cyber defense and mission assurance as core competencies to enable operational advantages and out-maneuver our

  17. Control of asthma triggers in indoor air with air cleaners: a modeling analysis

    PubMed Central

    Myatt, Theodore A; Minegishi, Taeko; Allen, Joseph G; MacIntosh, David L

    2008-01-01

    Background Reducing exposure to environmental agents indoors shown to increase asthma symptoms or lead to asthma exacerbations is an important component of a strategy to manage asthma for individuals. Numerous investigations have demonstrated that portable air cleaning devices can reduce concentrations of asthma triggers in indoor air; however, their benefits for breathing problems have not always been reproducible. The potential exposure benefits of whole house high efficiency in-duct air cleaners for sensitive subpopulations have yet to be evaluated. Methods We used an indoor air quality modeling system (CONTAM) developed by NIST to examine peak and time-integrated concentrations of common asthma triggers present in indoor air over a year as a function of natural ventilation, portable air cleaners, and forced air ventilation equipped with conventional and high efficiency filtration systems. Emission rates for asthma triggers were based on experimental studies published in the scientific literature. Results Forced air systems with high efficiency filtration were found to provide the best control of asthma triggers: 30–55% lower cat allergen levels, 90–99% lower risk of respiratory infection through the inhalation route of exposure, 90–98% lower environmental tobacco smoke (ETS) levels, and 50–75% lower fungal spore levels than the other ventilation/filtration systems considered. These results indicate that the use of high efficiency in-duct air cleaners provide an effective means of controlling allergen levels not only in a single room, like a portable air cleaner, but the whole house. Conclusion These findings are useful for evaluating potential benefits of high efficiency in-duct filtration systems for controlling exposure to asthma triggers indoors and for the design of trials of environmental interventions intended to evaluate their utility in practice. PMID:18684328

  18. Air-coupled laser vibrometry: analysis and applications.

    PubMed

    Solodov, Igor; Döring, Daniel; Busse, Gerd

    2009-03-01

    Acousto-optic interaction between a narrow laser beam and acoustic waves in air is analyzed theoretically. The photoelastic relation in air is used to derive the phase modulation of laser light in air-coupled reflection vibrometry induced by angular spatial spectral components comprising the acoustic beam. Maximum interaction was found for the zero spatial acoustic component propagating normal to the laser beam. The angular dependence of the imaging efficiency is determined for the axial and nonaxial acoustic components with the regard for the laser beam steering in the scanning mode. The sensitivity of air-coupled vibrometry is compared with conventional "Doppler" reflection vibrometry. Applications of the methodology for visualization of linear and nonlinear air-coupled fields are demonstrated.

  19. Engineering Cost Analysis of the Urban-Tracked Air Cushion Vehicle System

    DOT National Transportation Integrated Search

    1972-01-01

    The Urban Tracked Air Cushion Vehicle (UTACV) is presently being developed as a means of improving urban transportation. This report covers the development of a cost analysis conducted for the UTACV. The report covers the development of a computer pr...

  20. Field validation of speed estimation techniques for air quality conformity analysis.

    DOT National Transportation Integrated Search

    2004-01-01

    The air quality conformity analysis process requires the estimation of speeds for a horizon year on a link-by-link basis where only a few future roadway characteristics, such as forecast volume and capacity, are known. Accordingly, the Virginia Depar...

  1. Novel degradation pathway and kinetic analysis for buprofezin removal by newly isolated Bacillus sp.

    PubMed

    Wang, Guangli; Xu, Dayong; Xiong, Minghua; Zhang, Hui; Li, Feng; Liu, Yuan

    2016-09-15

    Given the intensive and widespread application of the pesticide, buprofezin, its environmental residues potentially pose a problem; yet little is known about buprofezin's kinetic and metabolic behaviors. In this study, a novel gram-positive strain, designated BF-5, isolated from aerobic activated sludge, was found to be capable of metabolizing buprofezin as its sole energy, carbon, and nitrogen source. Based on its physiological and biochemical characteristics, other aspects of its phenotype, and a phylogenetic analysis, strain BF-5 was identified as Bacillus sp. This study investigated the effect of culture conditions on bacterial growth and substrate degradation, such as pH, temperature, initial concentration, different nitrogen source, and additional nitrogen sources as co-substrates. The degradation rate parameters, qmax, Ks, Ki and Sm were determined to be 0.6918 h(-1), 105.4 mg L(-1), 210.5 mg L(-1), and 148.95 mg L(-1) respectively. The capture of unpublished potential metabolites by gas chromatography-mass spectrometry (GC-MS) analysis has led to the proposal of a novel degradation pathway. Taken together, our results clarify buprofezin's biodegradation pathway(s) and highlight the promising potential of strain BF-5 in bioremediation of buprofezin-contaminated environments. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome.

    PubMed

    Morine, Melissa J; McMonagle, Jolene; Toomey, Sinead; Reynolds, Clare M; Moloney, Aidan P; Gormley, Isobel C; Gaora, Peadar O; Roche, Helen M

    2010-10-07

    Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways--selenoamino acid metabolism and steroid biosynthesis--illustrated clear diet-sensitive changes in

  3. Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

    PubMed Central

    2010-01-01

    Background Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Results Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p < 0.05), followed by muscle (601 genes) and adipose (16 genes). Results from modified GSEA showed that the high-CLA beef diet affected diverse biological processes across the three tissues, and that the majority of pathway changes reached significance only with the bi-directional test. Combining the liver tissue microarray results with plasma marker data revealed 110 CLA-sensitive genes showing strong canonical correlation with one or more plasma markers of metabolic health, and 9 significantly overrepresented pathways among this set; each of these pathways was also significantly changed by the high-CLA diet. Closer inspection of two of these pathways - selenoamino acid metabolism and steroid biosynthesis - illustrated clear diet

  4. Donor-Specific Indirect Pathway Analysis Reveals a B-Cell-Independent Signature Which Reflects Outcomes in Kidney Transplant Recipients

    PubMed Central

    Haynes, L. D.; Jankowska-Gan, E.; Sheka, A.; Keller, M. R.; Hernandez-Fuentes, M. P.; Lechler, R. I.; Seyfert-Margolis, V.; Turka, L. A.; Newell, K. A.; Burlingham, W. J.

    2012-01-01

    To investigate the role of donor-specific indirect pathway T cells in renal transplant tolerance, we analyzed responses in peripheral blood of 45 patients using the trans-vivo delayed-type hypersensitivity assay. Subjects were enrolled into five groups—identical twin, clinically tolerant (TOL), steroid monotherapy (MONO), standard immunosuppression (SI) and chronic rejection (CR)—based on transplant type, posttransplant immunosuppression and graft function. The indirect pathway was active in all groups except twins but distinct intergroup differences were evident, corresponding to clinical status. The antidonor indirect pathway T effector response increased across patient groups (TOL < MONO < SI < CR; p < 0.0001) whereas antidonor indirect pathway T regulatory response decreased (TOL > MONO = SI > CR; p < 0.005). This pattern differed from that seen in circulating naïve B-cell numbers and in a cross-platform biomarker analysis, where patients on monotherapy were not ranked closest to TOL patients, but rather were indistinguishable from chronically rejecting patients. Cross-sectional analysis of the indirect pathway revealed a spectrum in T-regulatory:T-effector balance, ranging from TOL patients having predominantly regulatory responses to CR patients having predominantly effector responses. Therefore, the indirect pathway measurements reflect a distinct aspect of tolerance from the recently reported elevation of circulating naïve B cells, which was apparent only in recipients off immunosuppression. PMID:22151236

  5. Forward Air Controller: Task Analysis and Development of Team Training Measures for Close Air Support

    DTIC Science & Technology

    2007-12-01

    responsable scientifique aux fins d’examen et d’incorporation dans la planification de l’exercice Northern Goshawk, une simulation répartie d’une opération...L. K. (Eds.) (1992). A guide to task analysis. London, UK: Taylor & Francis. Matthews, M. L. and Lamoureux, T . M. (2003). Development of Generic...for Close Air Support Operations (ATP-3.3.2.1(A)). Brussels, Belgium. Silverman, D. R., Spiker, V. A., Tourville, S. J., and Nullmeyer, R. T . (1997

  6. Applications of principal component analysis to breath air absorption spectra profiles classification

    NASA Astrophysics Data System (ADS)

    Kistenev, Yu. V.; Shapovalov, A. V.; Borisov, A. V.; Vrazhnov, D. A.; Nikolaev, V. V.; Nikiforova, O. Y.

    2015-12-01

    The results of numerical simulation of application principal component analysis to absorption spectra of breath air of patients with pulmonary diseases are presented. Various methods of experimental data preprocessing are analyzed.

  7. Global expression analysis of gene regulatory pathways during endocrine pancreatic development.

    PubMed

    Gu, Guoqiang; Wells, James M; Dombkowski, David; Preffer, Fred; Aronow, Bruce; Melton, Douglas A

    2004-01-01

    To define genetic pathways that regulate development of the endocrine pancreas, we generated transcriptional profiles of enriched cells isolated from four biologically significant stages of endocrine pancreas development: endoderm before pancreas specification, early pancreatic progenitor cells, endocrine progenitor cells and adult islets of Langerhans. These analyses implicate new signaling pathways in endocrine pancreas development, and identified sets of known and novel genes that are temporally regulated, as well as genes that spatially define developing endocrine cells from their neighbors. The differential expression of several genes from each time point was verified by RT-PCR and in situ hybridization. Moreover, we present preliminary functional evidence suggesting that one transcription factor encoding gene (Myt1), which was identified in our screen, is expressed in endocrine progenitors and may regulate alpha, beta and delta cell development. In addition to identifying new genes that regulate endocrine cell fate, this global gene expression analysis has uncovered informative biological trends that occur during endocrine differentiation.

  8. PathFinder: reconstruction and dynamic visualization of metabolic pathways.

    PubMed

    Goesmann, Alexander; Haubrock, Martin; Meyer, Folker; Kalinowski, Jörn; Giegerich, Robert

    2002-01-01

    Beyond methods for a gene-wise annotation and analysis of sequenced genomes new automated methods for functional analysis on a higher level are needed. The identification of realized metabolic pathways provides valuable information on gene expression and regulation. Detection of incomplete pathways helps to improve a constantly evolving genome annotation or discover alternative biochemical pathways. To utilize automated genome analysis on the level of metabolic pathways new methods for the dynamic representation and visualization of pathways are needed. PathFinder is a tool for the dynamic visualization of metabolic pathways based on annotation data. Pathways are represented as directed acyclic graphs, graph layout algorithms accomplish the dynamic drawing and visualization of the metabolic maps. A more detailed analysis of the input data on the level of biochemical pathways helps to identify genes and detect improper parts of annotations. As an Relational Database Management System (RDBMS) based internet application PathFinder reads a list of EC-numbers or a given annotation in EMBL- or Genbank-format and dynamically generates pathway graphs.

  9. A systems biology approach to detect key pathways and interaction networks in gastric cancer on the basis of microarray analysis.

    PubMed

    Guo, Leilei; Song, Chunhua; Wang, Peng; Dai, Liping; Zhang, Jianying; Wang, Kaijuan

    2015-11-01

    The aim of the present study was to explore key molecular pathways contributing to gastric cancer (GC) and to construct an interaction network between significant pathways and potential biomarkers. Publicly available gene expression profiles of GSE29272 for GC, and data for the corresponding normal tissue, were downloaded from Gene Expression Omnibus. Pre‑processing and differential analysis were performed with R statistical software packages, and a number of differentially expressed genes (DEGs) were obtained. A functional enrichment analysis was performed for all the DEGs with a BiNGO plug‑in in Cytoscape. Their correlation was analyzed in order to construct a network. The modularity analysis and pathway identification operations were used to identify graph clusters and associated pathways. The underlying molecular mechanisms involving these DEGs were also assessed by data mining. A total of 249 DEGs, which were markedly upregulated and downregulated, were identified. The extracellular region contained the most significantly over‑represented functional terms, with respect to upregulated and downregulated genes, and the closest topological matches were identified for taste transduction and regulation of autophagy. In addition, extracellular matrix‑receptor interactions were identified as the most relevant pathway associated with the progression of GC. The genes for fibronectin 1, secreted phosphoprotein 1, collagen type 4 variant α‑1/2 and thrombospondin 1, which are involved in the pathways, may be considered as potential therapeutic targets for GC. A series of associations between candidate genes and key pathways were also identified for GC, and their correlation may provide novel insights into the pathogenesis of GC.

  10. An Analysis of the Air Conditioning, Refrigerating and Heating Occupation.

    ERIC Educational Resources Information Center

    Frass, Melvin R.; Krause, Marvin

    The general purpose of the occupational analysis is to provide workable, basic information dealing with the many and varied duties performed in the air conditioning, refrigerating, and heating occupation. The document opens with a brief introduction followed by a job description. The bulk of the document is presented in table form. Six duties are…

  11. Air Leakage of US Homes: Regression Analysis and Improvements from Retrofit

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chan, Wanyu R.; Joh, Jeffrey; Sherman, Max H.

    2012-08-01

    LBNL Residential Diagnostics Database (ResDB) contains blower door measurements and other diagnostic test results of homes in United States. Of these, approximately 134,000 single-family detached homes have sufficient information for the analysis of air leakage in relation to a number of housing characteristics. We performed regression analysis to consider the correlation between normalized leakage and a number of explanatory variables: IECC climate zone, floor area, height, year built, foundation type, duct location, and other characteristics. The regression model explains 68% of the observed variability in normalized leakage. ResDB also contains the before and after retrofit air leakage measurements of approximatelymore » 23,000 homes that participated in weatherization assistant programs (WAPs) or residential energy efficiency programs. The two types of programs achieve rather similar reductions in normalized leakage: 30% for WAPs and 20% for other energy programs.« less

  12. An integrative somatic mutation analysis to identify pathways linked with survival outcomes across 19 cancer types

    PubMed Central

    Park, Sunho; Kim, Seung-Jun; Yu, Donghyeon; Peña-Llopis, Samuel; Gao, Jianjiong; Park, Jin Suk; Chen, Beibei; Norris, Jessie; Wang, Xinlei; Chen, Min; Kim, Minsoo; Yong, Jeongsik; Wardak, Zabi; Choe, Kevin; Story, Michael; Starr, Timothy; Cheong, Jae-Ho; Hwang, Tae Hyun

    2016-01-01

    Motivation: Identification of altered pathways that are clinically relevant across human cancers is a key challenge in cancer genomics. Precise identification and understanding of these altered pathways may provide novel insights into patient stratification, therapeutic strategies and the development of new drugs. However, a challenge remains in accurately identifying pathways altered by somatic mutations across human cancers, due to the diverse mutation spectrum. We developed an innovative approach to integrate somatic mutation data with gene networks and pathways, in order to identify pathways altered by somatic mutations across cancers. Results: We applied our approach to The Cancer Genome Atlas (TCGA) dataset of somatic mutations in 4790 cancer patients with 19 different types of tumors. Our analysis identified cancer-type-specific altered pathways enriched with known cancer-relevant genes and targets of currently available drugs. To investigate the clinical significance of these altered pathways, we performed consensus clustering for patient stratification using member genes in the altered pathways coupled with gene expression datasets from 4870 patients from TCGA, and multiple independent cohorts confirmed that the altered pathways could be used to stratify patients into subgroups with significantly different clinical outcomes. Of particular significance, certain patient subpopulations with poor prognosis were identified because they had specific altered pathways for which there are available targeted therapies. These findings could be used to tailor and intensify therapy in these patients, for whom current therapy is suboptimal. Availability and implementation: The code is available at: http://www.taehyunlab.org. Contact: jhcheong@yuhs.ac or taehyun.hwang@utsouthwestern.edu or taehyun.cs@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26635139

  13. AIR QUALITY FORECAST DATABASE AND ANALYSIS

    EPA Science Inventory

    In 2003, NOAA and EPA signed a Memorandum of Agreement to collaborate on the design and implementation of a capability to produce daily air quality modeling forecast information for the U.S. NOAA's ETA meteorological model and EPA's Community Multiscale Air Quality (CMAQ) model ...

  14. The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways

    PubMed Central

    Rizzetto, Lisa; Guedez, Damariz Rivero; Donato, Michele; Romualdi, Chiara; Draghici, Sorin; Cavalieri, Duccio

    2011-01-01

    Motivation: Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions. Results: The Biological Connection Markup Language (BCML) is a format to describe, annotate and visualize pathways. BCML is able to store multiple information, permitting a selective view of the pathway as it exists and/or behave in specific organisms, tissues and cells. Furthermore, BCML can be automatically converted into data formats suitable for analysis and into a fully SBGN-compliant graphical representation, making it an important tool that can be used by both computational biologists and ‘wet lab’ scientists. Availability and implementation: The XML schema and the BCML software suite are freely available under the LGPL for download at http://bcml.dc-atlas.net. They are implemented in Java and supported on MS Windows, Linux and OS X. Contact: duccio.cavalieri@unifi.it; sorin@wayne.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21653523

  15. A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

    PubMed

    Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

    2016-09-01

    Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

  16. Refining the quantitative pathway of the Pathways to Mathematics model.

    PubMed

    Sowinski, Carla; LeFevre, Jo-Anne; Skwarchuk, Sheri-Lynn; Kamawar, Deepthi; Bisanz, Jeffrey; Smith-Chant, Brenda

    2015-03-01

    In the current study, we adopted the Pathways to Mathematics model of LeFevre et al. (2010). In this model, there are three cognitive domains--labeled as the quantitative, linguistic, and working memory pathways--that make unique contributions to children's mathematical development. We attempted to refine the quantitative pathway by combining children's (N=141 in Grades 2 and 3) subitizing, counting, and symbolic magnitude comparison skills using principal components analysis. The quantitative pathway was examined in relation to dependent numerical measures (backward counting, arithmetic fluency, calculation, and number system knowledge) and a dependent reading measure, while simultaneously accounting for linguistic and working memory skills. Analyses controlled for processing speed, parental education, and gender. We hypothesized that the quantitative, linguistic, and working memory pathways would account for unique variance in the numerical outcomes; this was the case for backward counting and arithmetic fluency. However, only the quantitative and linguistic pathways (not working memory) accounted for unique variance in calculation and number system knowledge. Not surprisingly, only the linguistic pathway accounted for unique variance in the reading measure. These findings suggest that the relative contributions of quantitative, linguistic, and working memory skills vary depending on the specific cognitive task. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. A detailed pathway analysis of the chemical reaction system generating the Martian vertical ozone profile

    NASA Astrophysics Data System (ADS)

    Stock, Joachim W.; Blaszczak-Boxe, Christopher S.; Lehmann, Ralph; Grenfell, J. Lee; Patzer, A. Beate C.; Rauer, Heike; Yung, Yuk L.

    2017-07-01

    Atmospheric chemical composition is crucial in determining a planet's atmospheric structure, stability, and evolution. Attaining a quantitative understanding of the essential chemical mechanisms governing atmospheric composition is nontrivial due to complex interactions between chemical species. Trace species, for example, can participate in catalytic cycles - affecting the abundance of major and other trace gas species. Specifically, for Mars, such cycles dictate the abundance of its primary atmospheric constituent, carbon dioxide (CO2), but also for one of its trace gases, ozone (O3). The identification of chemical pathways/cycles by hand is extremely demanding; hence, the application of numerical methods, such as the Pathway Analysis Program (PAP), is crucial to analyze and quantitatively exemplify chemical reaction networks. Here, we carry out the first automated quantitative chemical pathway analysis of Mars' atmosphere with respect to O3. PAP was applied to JPL/Caltech's 1-D updated photochemical Mars model's output data. We determine all significant chemical pathways and their contribution to O3 production and consumption (up to 80 km) in order to investigate the mechanisms causing the characteristic shape of the O3 volume mixing ratio profile, i.e. a ground layer maximum and an ozone layer at ∼50 km. These pathways explain why an O3 layer is present, why it is located at that particular altitude and what the different processes forming the near-surface and middle atmosphere O3 maxima are. Furthermore, we show that the Martian atmosphere can be divided into two chemically distinct regions according to the O(3P):O3 ratio. In the lower region (below approximately 24 km altitude) O3 is the most abundant Ox (= O3 + O(3P)) species. In the upper region (above approximately 24 km altitude), where the O3 layer is located, O(3P) is the most abundant Ox species. Earlier results concerning the formation of O3 on Mars can now be explained with the help of chemical

  18. Systematic identification and analysis of frequent gene fusion events in metabolic pathways

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.

    Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

  19. Systematic identification and analysis of frequent gene fusion events in metabolic pathways

    DOE PAGES

    Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.; ...

    2016-06-24

    Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

  20. Pathway Activity Profiling (PAPi): from the metabolite profile to the metabolic pathway activity.

    PubMed

    Aggio, Raphael B M; Ruggiero, Katya; Villas-Bôas, Silas Granato

    2010-12-01

    Metabolomics is one of the most recent omics-technologies and uses robust analytical techniques to screen low molecular mass metabolites in biological samples. It has evolved very quickly during the last decade. However, metabolomics datasets are considered highly complex when used to relate metabolite levels to metabolic pathway activity. Despite recent developments in bioinformatics, which have improved the quality of metabolomics data, there is still no straightforward method capable of correlating metabolite level to the activity of different metabolic pathways operating within the cells. Thus, this kind of analysis still depends on extremely laborious and time-consuming processes. Here, we present a new algorithm Pathway Activity Profiling (PAPi) with which we are able to compare metabolic pathway activities from metabolite profiles. The applicability and potential of PAPi was demonstrated using a previously published data from the yeast Saccharomyces cerevisiae. PAPi was able to support the biological interpretations of the previously published observations and, in addition, generated new hypotheses in a straightforward manner. However, PAPi is time consuming to perform manually. Thus, we also present here a new R-software package (PAPi) which implements the PAPi algorithm and facilitates its usage to quickly compare metabolic pathways activities between different experimental conditions. Using the identified metabolites and their respective abundances as input, the PAPi package calculates pathways' Activity Scores, which represents the potential metabolic pathways activities and allows their comparison between conditions. PAPi also performs principal components analysis and analysis of variance or t-test to investigate differences in activity level between experimental conditions. In addition, PAPi generates comparative graphs highlighting up- and down-regulated pathway activity. These datasets are available in http://www.4shared

  1. Development of a solar-powered residential air conditioner: Screening analysis

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Screening analysis aimed at the definition of an optimum configuration of a Rankine cycle solar-powered air conditioner designed for residential application were conducted. Initial studies revealed that system performance and cost were extremely sensitive to condensing temperature and to the type of condenser used in the system. Consequently, the screening analyses were concerned with the generation of parametric design data for different condenser approaches; i. e., (1) an ambient air condenser, (2) a humidified ambient air condenser (3) an evaporative condenser, and (4) a water condenser (with a cooling tower). All systems feature a high performance turbocompressor and a single refrigerant (R-11) for the power and refrigeration loops. Data were obtained by computerized methods developed to permit system characterization over a broad range of operating and design conditions. The criteria used for comparison of the candidate system approaches were (1) overall system COP (refrigeration effect/solar heat input), (2) auxiliary electric power for fans and pumps, and (3) system installed cost or cost to the user.

  2. Multifractal detrended cross-correlation analysis on air pollutants of University of Hyderabad Campus, India

    NASA Astrophysics Data System (ADS)

    Manimaran, P.; Narayana, A. C.

    2018-07-01

    In this paper, we study the multifractal characteristics and cross-correlation behaviour of Air Pollution Index (API) time series data through multifractal detrended cross-correlation analysis method. We analyse the daily API records of nine air pollutants of the university of Hyderabad campus for a period of three years (2013-2016). The cross-correlation behaviour has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, it is found that the cross-correlation analysis shows anti-correlation behaviour for all possible 36 bivariate time series. We also observe the existence of multifractal nature in all the bivariate time series in which many of them show strong multifractal behaviour. In particular, the hazardous particulate matter PM2.5 and inhalable particulate matter PM10 shows anti-correlated behaviour with all air pollutants.

  3. An operational air quality objective analysis of surface pollutants

    NASA Astrophysics Data System (ADS)

    Menard, R.; Robichaud, A.

    2013-05-01

    As of December 2012 a surface analysis of O3, PM2.5 at a resolution of 10 km over Canada and USA has become an operational product of Environment Canada. Analyses based an optimum interpolation scheme adapted to the variability of surface pollutant is run each hour. We will briefly discuss the specifics of the scheme, the technical implementation that lead to an operational implementation, a description and validation of the product as it stands today. An analysis of NO2 and a map of an air quality health index is also under way. We are now developing a high resolution analysis, 2.5 km over major cities over the Montreal-Toronto area and over the Oil sands region. The effect of state-dependent error covariance modeling will be present with some early results of the high resolutions analysis/assimilation.

  4. Patterns and determinants of pathways to reach comprehensive emergency obstetric and neonatal care (CEmONC) in South Sudan: qualitative diagrammatic pathway analysis.

    PubMed

    Elmusharaf, Khalifa; Byrne, Elaine; AbuAgla, Ayat; AbdelRahim, Amal; Manandhar, Mary; Sondorp, Egbert; O'Donovan, Diarmuid

    2017-08-29

    Maternity referral systems have been under-documented, under-researched, and under-theorised. Responsive emergency referral systems and appropriate transportation are cornerstones in the continuum of care and central to the complex health system. The pathways that women follow to reach Emergency Obstetric and Neonatal Care (EmONC) once a decision has been made to seek care have received relatively little attention. The aim of this research was to identify patterns and determinants of the pathways pregnant women follow from the onset of labour or complications until they reach an appropriate health facility. This study was conducted in Renk County in South Sudan between 2010 and 2012. Data was collected using Critical Incident Technique (CIT) and stakeholder interviews. CIT systematically identified pathways to healthcare during labour, and factors associated with an event of maternal mortality or near miss through a series of in-depth interviews with witnesses or those involved. Face-to-face stakeholder interviews were conducted with 28 purposively identified key informants. Diagrammatic pathway and thematic analysis were conducted using NVIVO 10 software. Once the decision is made to seek emergency obstetric care, the pregnant woman may face a series of complex steps before she reaches an appropriate health facility. Four pathway patterns to CEmONC were identified of which three were associated with high rates of maternal death: late referral, zigzagging referral, and multiple referrals. Women who bypassed nonfunctional Basic EmONC facilities and went directly to CEmONC facilities (the fourth pathway pattern) were most likely to survive. Overall, the competencies of the providers and the functionality of the first point of service determine the pathway to further care. Our findings indicate that outcomes are better where there is no facility available than when the woman accesses a non-functioning facility, and the absence of a healthcare provider is better than

  5. WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research.

    PubMed

    Slenter, Denise N; Kutmon, Martina; Hanspers, Kristina; Riutta, Anders; Windsor, Jacob; Nunes, Nuno; Mélius, Jonathan; Cirillo, Elisa; Coort, Susan L; Digles, Daniela; Ehrhart, Friederike; Giesbertz, Pieter; Kalafati, Marianthi; Martens, Marvin; Miller, Ryan; Nishida, Kozo; Rieswijk, Linda; Waagmeester, Andra; Eijssen, Lars M T; Evelo, Chris T; Pico, Alexander R; Willighagen, Egon L

    2018-01-04

    WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. A method for gene-based pathway analysis using genomewide association study summary statistics reveals nine new type 1 diabetes associations.

    PubMed

    Evangelou, Marina; Smyth, Deborah J; Fortune, Mary D; Burren, Oliver S; Walker, Neil M; Guo, Hui; Onengut-Gumuscu, Suna; Chen, Wei-Min; Concannon, Patrick; Rich, Stephen S; Todd, John A; Wallace, Chris

    2014-12-01

    Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed (P=9.85×10-11) with 12 of the 22 SNPs showing P<0.05. Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, P=7.86×10-9), NRP1 (rs722988, 4.88×10-8), BAD (rs694739, 2.37×10-7), CTSB (rs1296023, 2.79×10-7), FYN (rs11964650, P=5.60×10-7), UBE2G1 (rs9906760, 5.08×10-7), MAP3K14 (rs17759555, 9.67×10-7), ITGB1 (rs1557150, 1.93×10-6), and IL7R (rs1445898, 2.76×10-6). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available. © 2014 The Authors. ** Genetic Epidemiology published by Wiley Periodicals, Inc.

  7. Cluster Analysis of Atmospheric Dynamics and Pollution Transport in a Coastal Area

    NASA Astrophysics Data System (ADS)

    Sokolov, Anton; Dmitriev, Egor; Maksimovich, Elena; Delbarre, Hervé; Augustin, Patrick; Gengembre, Cyril; Fourmentin, Marc; Locoge, Nadine

    2016-11-01

    Summertime atmospheric dynamics in the coastal zone of the industrialized Dunkerque agglomeration in northern France was characterized by a cluster analysis of back trajectories in the context of pollution transport. The MESO-NH atmospheric model was used to simulate the local dynamics at multiple scales with horizontal resolution down to 500 m, and for the online calculation of the Lagrangian backward trajectories with 30-min temporal resolution. Airmass transport was performed along six principal pathways obtained by the weighted k-means clustering technique. Four of these centroids corresponded to a range of wind speeds over the English Channel: two for wind directions from the north-east and two from the south-west. Another pathway corresponded to a south-westerly continental transport. The backward trajectories of the largest and most dispersed sixth cluster contained low wind speeds, including sea-breeze circulations. Based on analyses of meteorological data and pollution measurements, the principal atmospheric pathways were related to local air-contamination events. Continuous air quality and meteorological data were collected during the Benzene-Toluene-Ethylbenzene-Xylene 2006 campaign. The sites of the pollution measurements served as the endpoints for the backward trajectories. Pollutant transport pathways corresponding to the highest air contamination were defined.

  8. Automated Applications in an Advanced Air Traffic Management System : Volume 2B. Functional Analysis of Air Traffic Management (Cont'd.)

    DOT National Transportation Integrated Search

    1974-08-01

    Volume 2 contains the analysis and description of air traffic management activities at three levels of detail - functions, subfunctions, and tasks. A total of 265 tasks are identified and described, and the flow of information inputs and outputs amon...

  9. Automation Applications in an Advanced Air Traffic Management System : Volume 2C. Functional Analysis of Air Traffic Management (Cont.'d)

    DOT National Transportation Integrated Search

    1974-08-01

    Volume 2 contains the analysis and description of air traffic management activities at three levels of detail - functions, subfunctions, and tasks. A total of 265 tasks are identified and described, and the flow of information inputs and outputs amon...

  10. Major carcinogenic pathways identified by gene expression analysis of peritoneal mesotheliomas following chemical treatment in F344 rats

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kim, Yongbaek; Thai-Vu Ton; De Angelo, Anthony B.

    2006-07-15

    This study was performed to characterize the gene expression profile and to identify the major carcinogenic pathways involved in rat peritoneal mesothelioma (RPM) formation following treatment of Fischer 344 rats with o-nitrotoluene (o-NT) or bromochloracetic acid (BCA). Oligo arrays, with over 20,000 target genes, were used to evaluate o-NT- and BCA-induced RPMs, when compared to a non-transformed mesothelial cell line (Fred-PE). Analysis using Ingenuity Pathway Analysis software revealed 169 cancer-related genes that were categorized into binding activity, growth and proliferation, cell cycle progression, apoptosis, and invasion and metastasis. The microarray data were validated by positive correlation with quantitative real-time RT-PCRmore » on 16 selected genes including igf1, tgfb3 and nov. Important carcinogenic pathways involved in RPM formation included insulin-like growth factor 1 (IGF-1), p38 MAPkinase, Wnt/{beta}-catenin and integrin signaling pathways. This study demonstrated that mesotheliomas in rats exposed to o-NT- and BCA were similar to mesotheliomas in humans, at least at the cellular and molecular level.« less

  11. Analysis of Differentially Expressed Genes and Signaling Pathways Related to Intramuscular Fat Deposition in Skeletal Muscle of Sex-Linked Dwarf Chickens

    PubMed Central

    Ye, Yaqiong; Lin, Shumao; Mu, Heping; Tang, Xiaohong; Ou, Yangdan; Chen, Jian; Ma, Yongjiang; Li, Yugu

    2014-01-01

    Intramuscular fat (IMF) plays an important role in meat quality. However, the molecular mechanisms underlying IMF deposition in skeletal muscle have not been addressed for the sex-linked dwarf (SLD) chicken. In this study, potential candidate genes and signaling pathways related to IMF deposition in chicken leg muscle tissue were characterized using gene expression profiling of both 7-week-old SLD and normal chickens. A total of 173 differentially expressed genes (DEGs) were identified between the two breeds. Subsequently, 6 DEGs related to lipid metabolism or muscle development were verified in each breed based on gene ontology (GO) analysis. In addition, KEGG pathway analysis of DEGs indicated that some of them (GHR, SOCS3, and IGF2BP3) participate in adipocytokine and insulin signaling pathways. To investigate the role of the above signaling pathways in IMF deposition, the gene expression of pathway factors and other downstream genes were measured by using qRT-PCR and Western blot analyses. Collectively, the results identified potential candidate genes related to IMF deposition and suggested that IMF deposition in skeletal muscle of SLD chicken is regulated partially by pathways of adipocytokine and insulin and other downstream signaling pathways (TGF-β/SMAD3 and Wnt/catenin-β pathway). PMID:24757673

  12. Modeling biochemical pathways in the gene ontology

    DOE PAGES

    Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.; ...

    2016-09-01

    The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less

  13. Pathway-based analyses.

    PubMed

    Kent, Jack W

    2016-02-03

    New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

  14. Epigenome-Wide Meta-Analysis of Methylation in Children Related to Prenatal NO2 Air Pollution Exposure.

    PubMed

    Gruzieva, Olena; Xu, Cheng-Jian; Breton, Carrie V; Annesi-Maesano, Isabella; Antó, Josep M; Auffray, Charles; Ballereau, Stéphane; Bellander, Tom; Bousquet, Jean; Bustamante, Mariona; Charles, Marie-Aline; de Kluizenaar, Yvonne; den Dekker, Herman T; Duijts, Liesbeth; Felix, Janine F; Gehring, Ulrike; Guxens, Mònica; Jaddoe, Vincent V W; Jankipersadsing, Soesma A; Merid, Simon Kebede; Kere, Juha; Kumar, Ashish; Lemonnier, Nathanael; Lepeule, Johanna; Nystad, Wenche; Page, Christian Magnus; Panasevich, Sviatlana; Postma, Dirkje; Slama, Rémy; Sunyer, Jordi; Söderhäll, Cilla; Yao, Jin; London, Stephanie J; Pershagen, Göran; Koppelman, Gerard H; Melén, Erik

    2017-01-01

    Prenatal exposure to air pollution is considered to be associated with adverse effects on child health. This may partly be mediated by mechanisms related to DNA methylation. We investigated associations between exposure to air pollution, using nitrogen dioxide (NO2) as marker, and epigenome-wide cord blood DNA methylation. We meta-analyzed the associations between NO2 exposure at residential addresses during pregnancy and cord blood DNA methylation (Illumina 450K) in four European and North American studies (n = 1,508) with subsequent look-up analyses in children ages 4 (n = 733) and 8 (n = 786) years. Additionally, we applied a literature-based candidate approach for antioxidant and anti-inflammatory genes. To assess influence of exposure at the transcriptomics level, we related mRNA expression in blood cells to NO2 exposure in 4- (n = 111) and 16-year-olds (n = 239). We found epigenome-wide significant associations [false discovery rate (FDR) p < 0.05] between maternal NO2 exposure during pregnancy and DNA methylation in newborns for 3 CpG sites in mitochondria-related genes: cg12283362 (LONP1), cg24172570 (3.8 kbp upstream of HIBADH), and cg08973675 (SLC25A28). The associations with cg08973675 methylation were also significant in the older children. Further analysis of antioxidant and anti-inflammatory genes revealed differentially methylated CpGs in CAT and TPO in newborns (FDR p < 0.05). NO2 exposure at the time of biosampling in childhood had a significant impact on CAT and TPO expression. NO2 exposure during pregnancy was associated with differential offspring DNA methylation in mitochondria-related genes. Exposure to NO2 was also linked to differential methylation as well as expression of genes involved in antioxidant defense pathways. Citation: Gruzieva O, Xu CJ, Breton CV, Annesi-Maesano I, Antó JM, Auffray C, Ballereau S, Bellander T, Bousquet J, Bustamante M, Charles MA, de Kluizenaar Y, den Dekker HT, Duijts L, Felix JF, Gehring U, Guxens M, Jaddoe VV

  15. Air Pollution.

    ERIC Educational Resources Information Center

    Gilpin, Alan

    A summary of one of our most pressing environmental problems, air pollution, is offered in this book by the Director of Air Pollution Control for the Queensland (Australia) State Government. Discussion of the subject is not restricted to Queensland or Australian problems and policies, however, but includes analysis of air pollution the world over.…

  16. DEVELOPMENT AND ANALYSIS OF AIR QUALITY MODELING SIMULATIONS FOR HAZARDOUS AIR POLLUTANTS

    EPA Science Inventory

    The concentrations of five hazardous air pollutants were simulated using the Community Multi Scale Air Quality (CMAQ) modeling system. Annual simulations were performed over the continental United States for the entire year of 2001 to support human exposure estimates. Results a...

  17. A novel analysis strategy for integrating methylation and expression data reveals core pathways for thyroid cancer aetiology

    PubMed Central

    2015-01-01

    Background Recently, a wide range of diseases have been associated with changes in DNA methylation levels, which play a vital role in gene expression regulation. With ongoing developments in technology, attempts to understand disease mechanism have benefited greatly from epigenetics and transcriptomics studies. In this work, we have used expression and methylation data of thyroid carcinoma as a case study and explored how to optimally incorporate expression and methylation information into the disease study when both data are available. Moreover, we have also investigated whether there are important post-translational modifiers which could drive critical insights on thyroid cancer genetics. Results In this study, we have conducted a threshold analysis for varying methylation levels to identify whether setting a methylation level threshold increases the performance of functional enrichment. Moreover, in order to decide on best-performing analysis strategy, we have performed data integration analysis including comparison of 10 different analysis strategies. As a result, combining methylation with expression and using genes with more than 15% methylation change led to optimal detection rate of thyroid-cancer associated pathways in top 20 functional enrichment results. Furthermore, pooling the data from different experiments increased analysis confidence by improving the data range. Consequently, we have identified 207 transcription factors and 245 post-translational modifiers with more than 15% methylation change which may be important in understanding underlying mechanisms of thyroid cancer. Conclusion While only expression or only methylation information would not reveal both primary and secondary mechanisms involved in disease state, combining expression and methylation led to a better detection of thyroid cancer-related genes and pathways that are found in the recent literature. Moreover, focusing on genes that have certain level of methylation change improved the

  18. Optimizing Air Transportation Service to Metroplex Airports. Part 1; Analysis of Historical Data

    NASA Technical Reports Server (NTRS)

    Donohue, George; Hoffman, Karla; Sherry, Lance; Ferguson, John; Kara, Abdul Qadar

    2010-01-01

    The air transportation system is a significant driver of the U.S. economy, providing safe, affordable, and rapid transportation. During the past three decades airspace and airport capacity has not grown in step with demand for air transportation (+4% annual growth), resulting in unreliable service and systemic delays. Estimates of the impact of delays and unreliable air transportation service on the economy range from $32B to $41B per year. This report describes the results of an analysis of airline strategic decision-making with regards to: (1) geographic access, (2) economic access, and (3) airline finances. This analysis evaluated markets-served, scheduled flights, aircraft size, airfares, and profit from 2005-2009. During this period, airlines experienced changes in costs of operation (due to fluctuations in hedged fuel prices), changes in travel demand (due to changes in the economy), and changes in infrastructure capacity (due to the capacity limits at EWR, JFK, and LGA). This analysis captures the impact of the implementation of capacity limits at airports, as well as the effect of increased costs of operation (i.e. hedged fuel prices). The increases in costs of operation serve as a proxy for increased costs per flight that might occur if auctions or congestion pricing are imposed.

  19. The air quality analysis of Dalian based on the data of AQI

    NASA Astrophysics Data System (ADS)

    Gu, Ji-lin; Liu, Miao

    2018-02-01

    The data of AQI from 10 countries accused of automatic air quality monitoring station of Dalian from June 2015 to December 2016 were analyzed to investigate the daily mean change of air quality index, the change of the hour and the correlation analysis between AQI and PM2.5, PM10, SO2, NO2, CO, O3 six parameters. The 856,800 index samples showed that the air quality index of autumn and winter was obviously higher than that of summer. The maximum AQI value in autumn and winter reached 389, with an average of 82. The maximum value of AQI in summer was 130, and the average was 50. From 2015 to 2016, the excellent air quality in the summer in Dalian was 60.3%; the standard rate was 98.4%. The autumn and winter air quality accounted for 39.1% and the compliance rate was 68.5%. The mean of the AQI average daily was a wavy trend, and the changes of summer and autumn and winter were roughly the same. The regularity of AQI 24-hour showed multi-peak changes, bimodal changes and single peak changes. The air quality in Dalian is affected by the weather conditions such as wind direction, rainfall and fog, the air quality in surrounding cities, urban pollution, vehicle exhaust and excessive consumption of coal energy. Through correlation calculation, AQI, PM2.5, and PM10 were significantly correlated irrespective of season. AQI and O3 were positively correlated in summer, but negatively correlated in autumn and winter, which is the basis for the treatment of air pollution in Dalian.

  20. GWAS-based pathway analysis differentiates between fluid and crystallized intelligence.

    PubMed

    Christoforou, A; Espeseth, T; Davies, G; Fernandes, C P D; Giddaluru, S; Mattheisen, M; Tenesa, A; Harris, S E; Liewald, D C; Payton, A; Ollier, W; Horan, M; Pendleton, N; Haggarty, P; Djurovic, S; Herms, S; Hoffman, P; Cichon, S; Starr, J M; Lundervold, A; Reinvang, I; Steen, V M; Deary, I J; Le Hellard, S

    2014-09-01

    Cognitive abilities vary among people. About 40-50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) - the ability to reason in novel situations - and general crystallized intelligence (gC) - the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long-term depression (LTD) seemed to underlie gC. Thus, this study supports the gF-gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation. © 2014 The Authors. Genes, Brain and Behavior published by International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd.

  1. Aerosols in Northern Morocco: Input pathways and their chemical fingerprint

    NASA Astrophysics Data System (ADS)

    Benchrif, A.; Guinot, B.; Bounakhla, M.; Cachier, H.; Damnati, B.; Baghdad, B.

    2018-02-01

    The Mediterranean basin is one of the most sensitive regions in the world regarding climate change and air quality. Deserts and marine aerosols combine with combustion aerosols from maritime traffic, large urban centers, and at a larger scale from populated industrialized regions in Europe. From Tetouan city located in the North of Morocco, we attempted to better figure out the main aerosol transport pathways and their respective aerosol load and chemical profile by examining air mass back trajectory patterns and aerosol chemical compositions from May 2011 to April 2012. The back trajectory analysis throughout the sampling period led to four clusters, for which meteorological conditions and aerosol chemical characteristics have been investigated. The most frequent cluster (CL3: 39%) corresponds to polluted air masses coming from the Mediterranean Basin, characterized by urban and marine vessels emissions out of Spain and of Northern Africa. Two other polluted clusters were characterized. One is of local origin (CL1: 22%), with a marked contribution from urban aerosols (Rabat, Casablanca) and from biomass burning aerosols. The second (CL2: 32%) defines air masses from the near Atlantic Ocean, affected by pollutants emitted from the Iberian coast. A fourth cluster (CL4: 7%) is characterized by rather clean, fast and rainy oceanic air masses, influenced during their last 24 h before reaching Tetouan by similar sources with those affecting CL2, but to a lesser extent. The chemical data show that carbonaceous species are found in the fine aerosols fraction and are generally from local primary sources (low OC/EC) rather than long-range transported. In addition to fresh traffic and maritime vessel aerosols, our results suggest the contribution of local biomass burning.

  2. The Impacts of Policies To Meet The UK Climate Change Act Target on Air Quality - An Explicit Modelling Study

    NASA Astrophysics Data System (ADS)

    Williams, M.; Beevers, S.; Lott, M. C.; Kitwiroon, N.

    2016-12-01

    This paper presents a preliminary analysis of different pathways to meet the UK Climate Change Act target for 2050, of an 80% reduction in carbon dioxide equivalent emissions on a base year of 1990. The pathways can result in low levels of air pollution emissions through the use of renewables and nuclear power. But large increases in biomass burning and the continued use of diesel cars they can result in larger air quality impacts. The work evaluated the air quality impacts in several pathways using an energy system optimisation model (UK TIMES) and a chemical transport model (CMAQ). The work described in this paper goes beyond the `damage cost' approach where only emissions in each are assessed. In this work we used scenarios produced by the UK TIMES model which we converted into air pollution emissions. Emissions of ammonia from agriculture are not attributed to the energy system and are thus not captured by energy system models, yet are crucial in forming PM2.5, acknowledged to be currently the most important pollutant associated with premature deaths. Our model includes these emissions and other non-energy sources of hydrocarbons which lead to the formation of ozone, another significant cause of air pollution health impacts. A key policy issue is how much biogenic hydrocarbons contribute to ozone formation compared with man-made emissions. We modelled pollution concentrations at a resolution of 7 km across the UK and at 2km in urban areas. These results allow us to estimate changes in premature mortality and morbidity associated with the changes in air pollution and subsequently the economic cost of the impacts on public health. The work shows that in the `clean' scenario, urban exposures to particles (PM2.5) and NO2 could decrease by very large amounts, but ozone exposures are likely to increase without further significant reductions world-wide. Large increases in biomass use however could lead to increases in urban levels of carcinogens and primary PM.

  3. A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions

    NASA Astrophysics Data System (ADS)

    Roy, Raktim; Phani Shilpa, P.; Bagh, Sangram

    2016-09-01

    Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level.

  4. Mobile Air Monitoring: Measuring Change in Air Quality in the City of Hamilton, 2005-2010

    ERIC Educational Resources Information Center

    Adams, Matthew D.; DeLuca, Patrick F.; Corr, Denis; Kanaroglou, Pavlos S.

    2012-01-01

    This paper examines the change in air pollutant concentrations between 2005 and 2010 occurring in the City of Hamilton, Ontario, Canada. After analysis of stationary air pollutant concentration data, we analyze mobile air pollutant concentration data. Air pollutants included in the analysis are CO, PM[subscript 2.5], SO[subscript 2], NO,…

  5. Air pollution, inflammation and preterm birth: a potential mechanistic link.

    PubMed

    Vadillo-Ortega, Felipe; Osornio-Vargas, Alvaro; Buxton, Miatta A; Sánchez, Brisa N; Rojas-Bracho, Leonora; Viveros-Alcaráz, Martin; Castillo-Castrejón, Marisol; Beltrán-Montoya, Jorge; Brown, Daniel G; O'Neill, Marie S

    2014-02-01

    Preterm birth is a public health issue of global significance, which may result in mortality during the perinatal period or may lead to major health and financial consequences due to lifelong impacts. Even though several risk factors for preterm birth have been identified, prevention efforts have failed to halt the increasing rates of preterm birth. Epidemiological studies have identified air pollution as an emerging potential risk factor for preterm birth. However, many studies were limited by study design and inadequate exposure assessment. Due to the ubiquitous nature of ambient air pollution and the potential public health significance of any role in causing preterm birth, a novel focus investigating possible causal mechanisms influenced by air pollution is therefore a global health priority. We hypothesize that air pollution may act together with other biological factors to induce systemic inflammation and influence the duration of pregnancy. Evaluation and testing of this hypothesis is currently being conducted in a prospective cohort study in Mexico City and will provide an understanding of the pathways that mediate the effects of air pollution on preterm birth. The important public health implication is that crucial steps in this mechanistic pathway can potentially be acted on early in pregnancy to reduce the risk of preterm birth. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. AIR POLLUTION, INFLAMMATION AND PRETERM BIRTH: A POTENTIAL MECHANISTIC LINK

    PubMed Central

    Vadillo-Ortega, Felipe; Osornio-Vargas, Alvaro; Buxton, Miatta A.; Sánchez, Brisa N.; Rojas-Bracho, Leonora; Viveros-Alcaráz, Martin; Castillo-Castrejón, Marisol; Beltrán-Montoya, Jorge; Brown, Daniel G.; O´Neill, Marie S.

    2014-01-01

    Preterm birth is a public health issue of global significance, which may result in mortality during the perinatal period or may lead to major health and financial consequences due to lifelong impacts. Even though several risk factors for preterm birth have been identified, prevention efforts have failed to halt the increasing rates of preterm birth. Epidemiological studies have identified air pollution as an emerging potential risk factor for preterm birth. However, many studies were limited by study design and inadequate exposure assessment. Due to the ubiquitous nature of ambient air pollution and the potential public health significance of any role in causing preterm birth, a novel focus investigating possible causal mechanisms influenced by air pollution is therefore a global health priority. We hypothesize that air pollution may act together with other biological factors to induce systemic inflammation and influence the duration of pregnancy. Evaluation and testing of this hypothesis is currently being conducted in a prospective cohort study in Mexico City and will provide an understanding of the pathways that mediate the effects of air pollution on preterm birth. The important public health implication is that crucial steps in this mechanistic pathway can potentially be acted on early in pregnancy to reduce the risk of preterm birth. PMID:24382337

  7. The Measurement of Fuel-Air Ratio by Analysis for the Oxidized Exhaust Gas

    NASA Technical Reports Server (NTRS)

    Gerrish, Harold C.; Meem, J. Lawrence, Jr.

    1943-01-01

    An investigation was made to determine a method of measuring fuel-air ratio that could be used for test purposes in flight and for checking conventional equipment in the laboratory. Two single-cylinder test engines equipped with typical commercial engine cylinders were used. The fuel-air ratio of the mixture delivered to the engines was determined by direct measurement of the quantity of air and of fuel supplied and also by analysis of the oxidized exhaust gas and of the normal exhaust gas. Five fuels were used: gasoline that complied with Army-Navy fuel Specification No. AN-VV-F-781 and four mixtures of this gasoline with toluene, benzene, and xylene. The method of determining the fuel-air ratio described in this report involves the measurement of the carbon-dioxide content of the oxidized exhaust gas and the use of graphs for the presented equation. This method is considered useful in aircraft, in the field, or in the laboratory for a range of fuel-air ratios from 0.047 to 0.124.

  8. The Measurement of Fuel-air Ratio by Analysis of the Oxidized Exhaust Gas

    NASA Technical Reports Server (NTRS)

    Memm, J. Lawrence, Jr.

    1943-01-01

    An investigation was made to determine a method of measuring fuel-air ratio that could be used for test purposes in flight and for checking conventional equipment in the laboratory. Two single-cylinder test engines equipped with typical commercial engine cylinders were used. The fuel-air ratio of the mixture delivered to the engines was determined by direct measurement of the quantity of air and of fuel supplied and also by analysis of the oxidized exhaust gas and of the normal exhaust gas. Five fuels were used: gasoline that complied with Army-Navy Fuel Specification, No. AN-VV-F-781 and four mixtures of this gasoline with toluene, benzene, and xylene. The method of determining the fuel-air ratio described in this report involves the measurement of the carbon-dioxide content of the oxidized exhaust gas and the use of graphs or the presented equation. This method is considered useful in aircraft, in the field, or in the laboratory for a range of fuel-air ratios from 0.047 to 0.124

  9. An analysis of labor and multifactor productivity in air transportation : 1990 - 2001

    DOT National Transportation Integrated Search

    2002-01-01

    The analysis has two main objectives: 1) to examine : labor productivity and multifactor productivity : (MFP) in U.S. air transportation during the 1990 : to 2001 period and to compare these measures to : those of two other transportation subsectors ...

  10. Benefit Analysis Report, United States Air Force Technical Order Management Systems (AFTOMS)

    DOT National Transportation Integrated Search

    1989-08-01

    This report prepared by the Transportation Systems Center (TSC) concludes an analysis of the Technical Order (TO) costs and benefits, which was originally undertaken as part of the US Air Force Computer-aided Acquisition and Logistics Support (CALS) ...

  11. Estimating environmental co-benefits of U.S. low-carbon pathways using an integrated assessment model with state-level resolution.

    PubMed

    Ou, Yang; Shi, Wenjing; Smith, Steven J; Ledna, Catherine M; West, J Jason; Nolte, Christopher G; Loughlin, Daniel H

    2018-04-15

    There are many technological pathways that can lead to reduced carbon dioxide emissions. However, these pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. This study uses an integrated assessment model with state-level resolution of the energy system to compare environmental impacts of alternative low-carbon pathways for the United States. One set of pathways emphasizes nuclear energy and carbon capture and storage, while another set emphasizes renewable energy, including wind, solar, geothermal power, and bioenergy. These are compared with pathways in which all technologies are available. Air pollutant emissions, mortality costs attributable to particulate matter smaller than 2.5 μm in diameter, and energy-related water demands are evaluated for 50% and 80% carbon dioxide reduction targets in 2050. The renewable low-carbon pathways require less water withdrawal and consumption than the nuclear and carbon capture pathways. However, the renewable low-carbon pathways modeled in this study produce higher particulate matter-related mortality costs due to greater use of biomass in residential heating. Environmental co-benefits differ among states because of factors such as existing technology stock, resource availability, and environmental and energy policies.

  12. Developmental transcriptome analysis and identification of genes involved in formation of intestinal air-breathing function of Dojo loach, Misgurnus anguillicaudatus

    PubMed Central

    Luo, Weiwei; Cao, Xiaojuan; Xu, Xiuwen; Huang, Songqian; Liu, Chuanshu; Tomljanovic, Tea

    2016-01-01

    Dojo loach, Misgurnus anguillicaudatus is a freshwater fish species of the loach family Cobitidae, using its posterior intestine as an accessory air-breathing organ. Little is known about the molecular regulatory mechanisms in the formation of intestinal air-breathing function of M. anguillicaudatus. Here high-throughput sequencing of mRNAs was performed from six developmental stages of posterior intestine of M. anguillicaudatus: 4-Dph (days post hatch) group, 8-Dph group, 12-Dph group, 20-Dph group, 40-Dph group and Oyd (one-year-old) group. These six libraries were assembled into 81300 unigenes. Totally 40757 unigenes were annotated. Subsequently, 35291 differentially expressed genes (DEGs) were scanned among different developmental stages and clustered into 20 gene expression profiles. Finally, 15 key pathways and 25 key genes were mined, providing potential targets for candidate gene selection involved in formation of intestinal air-breathing function in M. anguillicaudatus. This is the first report of developmental transcriptome of posterior intestine in M. anguillicaudatus, offering a substantial contribution to the sequence resources for this species and providing a deep insight into the formation mechanism of its intestinal air-breathing function. This report demonstrates that M. anguillicaudatus is a good model for studies to identify and characterize the molecular basis of accessory air-breathing organ development in fish. PMID:27545457

  13. Urban Form, Air Pollution, and Health.

    PubMed

    Hankey, Steve; Marshall, Julian D

    2017-12-01

    Urban form can impact air pollution and public health. We reviewed health-related articles that assessed (1) the relationships among urban form, air pollution, and health as well as (2) aspects of the urban environment (i.e., green space, noise, physical activity) that may modify those relationships. Simulation and empirical studies demonstrate an association between compact growth, improved regional air quality, and health. Most studies are cross-sectional and focus on connections between transportation emissions and land use. The physical and mental health impacts of green space, public spaces that promote physical activity, and noise are well-studied aspects of the urban environment and there is evidence that these factors may modify the relationship between air pollution and health. Urban form can support efforts to design clean, health-promoting cities. More work is needed to operationalize specific strategies and to elucidate the causal pathways connecting various aspects of health.

  14. Cost Analysis of Outsourcing An Air Force Supply Squadron

    DTIC Science & Technology

    2006-12-01

    for her support and tolerance during the long hours it took to write this paper. -Scott Schofield I would like to thank my wife Isobelle...from the Air Force base which we studied. All of the materials provided, along with their expertise and patience in dealing with us, were critical to...fiscal year. With the entire life of the contract available for analysis, along with all of the material of the preceding A-76 process, an objective

  15. Thermo-economic comparative analysis of gas turbine GT10 integrated with air and steam bottoming cycle

    NASA Astrophysics Data System (ADS)

    Czaja, Daniel; Chmielnak, Tadeusz; Lepszy, Sebastian

    2014-12-01

    A thermodynamic and economic analysis of a GT10 gas turbine integrated with the air bottoming cycle is presented. The results are compared to commercially available combined cycle power plants based on the same gas turbine. The systems under analysis have a better chance of competing with steam bottoming cycle configurations in a small range of the power output capacity. The aim of the calculations is to determine the final cost of electricity generated by the gas turbine air bottoming cycle based on a 25 MW GT10 gas turbine with the exhaust gas mass flow rate of about 80 kg/s. The article shows the results of thermodynamic optimization of the selection of the technological structure of gas turbine air bottoming cycle and of a comparative economic analysis. Quantities are determined that have a decisive impact on the considered units profitability and competitiveness compared to the popular technology based on the steam bottoming cycle. The ultimate quantity that can be compared in the calculations is the cost of 1 MWh of electricity. It should be noted that the systems analyzed herein are power plants where electricity is the only generated product. The performed calculations do not take account of any other (potential) revenues from the sale of energy origin certificates. Keywords: Gas turbine air bottoming cycle, Air bottoming cycle, Gas turbine, GT10

  16. Microarray analysis of peripheral blood lymphocytes from ALS patients and the SAFE detection of the KEGG ALS pathway

    PubMed Central

    2011-01-01

    Background Sporadic amyotrophic lateral sclerosis (sALS) is a motor neuron disease with poorly understood etiology. Results of gene expression profiling studies of whole blood from ALS patients have not been validated and are difficult to relate to ALS pathogenesis because gene expression profiles depend on the relative abundance of the different cell types present in whole blood. We conducted microarray analyses using Agilent Human Whole Genome 4 × 44k Arrays on a more homogeneous cell population, namely purified peripheral blood lymphocytes (PBLs), from ALS patients and healthy controls to identify molecular signatures possibly relevant to ALS pathogenesis. Methods Differentially expressed genes were determined by LIMMA (Linear Models for MicroArray) and SAM (Significance Analysis of Microarrays) analyses. The SAFE (Significance Analysis of Function and Expression) procedure was used to identify molecular pathway perturbations. Proteasome inhibition assays were conducted on cultured peripheral blood mononuclear cells (PBMCs) from ALS patients to confirm alteration of the Ubiquitin/Proteasome System (UPS). Results For the first time, using SAFE in a global gene ontology analysis (gene set size 5-100), we show significant perturbation of the KEGG (Kyoto Encyclopedia of Genes and Genomes) ALS pathway of motor neuron degeneration in PBLs from ALS patients. This was the only KEGG disease pathway significantly upregulated among 25, and contributing genes, including SOD1, represented 54% of the encoded proteins or protein complexes of the KEGG ALS pathway. Further SAFE analysis, including gene set sizes >100, showed that only neurodegenerative diseases (4 out of 34 disease pathways) including ALS were significantly upregulated. Changes in UBR2 expression correlated inversely with time since onset of disease and directly with ALSFRS-R, implying that UBR2 was increased early in the course of ALS. Cultured PBMCs from ALS patients accumulated more ubiquitinated proteins

  17. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

    PubMed Central

    Caspi, Ron; Altman, Tomer; Dale, Joseph M.; Dreher, Kate; Fulcher, Carol A.; Gilham, Fred; Kaipa, Pallavi; Karthikeyan, Athikkattuvalasu S.; Kothari, Anamika; Krummenacker, Markus; Latendresse, Mario; Mueller, Lukas A.; Paley, Suzanne; Popescu, Liviu; Pujar, Anuradha; Shearer, Alexander G.; Zhang, Peifen; Karp, Peter D.

    2010-01-01

    The MetaCyc database (MetaCyc.org) is a comprehensive and freely accessible resource for metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are experimentally determined, small-molecule metabolic pathways and are curated from the primary scientific literature. With more than 1400 pathways, MetaCyc is the largest collection of metabolic pathways currently available. Pathways reactions are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes, and literature citations. BioCyc (BioCyc.org) is a collection of more than 500 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the full genome and predicted metabolic network of one organism. The network, which is predicted by the Pathway Tools software using MetaCyc as a reference, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs also contain additional features, such as predicted operons, transport systems, and pathway hole-fillers. The BioCyc Web site offers several tools for the analysis of the PGDBs, including Omics Viewers that enable visualization of omics datasets on two different genome-scale diagrams and tools for comparative analysis. The BioCyc PGDBs generated by SRI are offered for adoption by any party interested in curation of metabolic, regulatory, and genome-related information about an organism. PMID:19850718

  18. Mining disease fingerprints from within genetic pathways.

    PubMed

    Nabhan, Ahmed Ragab; Sarkar, Indra Neil

    2012-01-01

    Mining biological networks can be an effective means to uncover system level knowledge out of micro level associations, such as encapsulated in genetic pathways. Analysis of human disease genetic pathways can lead to the identification of major mechanisms that may underlie disorders at an abstract functional level. The focus of this study was to develop an approach for structural pattern analysis and classification of genetic pathways of diseases. A probabilistic model was developed to capture characteristic components ('fingerprints') of functionally annotated pathways. A probability estimation procedure of this model searched for fingerprints in each disease pathway while improving probability estimates of model parameters. The approach was evaluated on data from the Kyoto Encyclopedia of Genes and Genomes (consisting of 56 pathways across seven disease categories). Based on the achieved average classification accuracy of up to ~77%, the findings suggest that these fingerprints may be used for classification and discovery of genetic pathways.

  19. Mining Disease Fingerprints From Within Genetic Pathways

    PubMed Central

    Nabhan, Ahmed Ragab; Sarkar, Indra Neil

    2012-01-01

    Mining biological networks can be an effective means to uncover system level knowledge out of micro level associations, such as encapsulated in genetic pathways. Analysis of human disease genetic pathways can lead to the identification of major mechanisms that may underlie disorders at an abstract functional level. The focus of this study was to develop an approach for structural pattern analysis and classification of genetic pathways of diseases. A probabilistic model was developed to capture characteristic components (‘fingerprints’) of functionally annotated pathways. A probability estimation procedure of this model searched for fingerprints in each disease pathway while improving probability estimates of model parameters. The approach was evaluated on data from the Kyoto Encyclopedia of Genes and Genomes (consisting of 56 pathways across seven disease categories). Based on the achieved average classification accuracy of up to ∼77%, the findings suggest that these fingerprints may be used for classification and discovery of genetic pathways. PMID:23304411

  20. Spectroscopic analysis of femtosecond laser plasma filament in air

    NASA Astrophysics Data System (ADS)

    Bernhardt, J.; Liu, W.; Théberge, F.; Xu, H. L.; Daigle, J. F.; Châteauneuf, M.; Dubois, J.; Chin, S. L.

    2008-03-01

    We report a spectroscopic analysis of a filament generated by a femtosecond laser pulse in air. In the filament spectra, the characteristic Stark broadened atomic oxygen triplet centered at 777.4 nm has been observed. The measured electron impact Stark broadening parameter of the triplet is larger than the theoretical value by Griem [H.R. Griem, Plasma Spectroscopy, McGraw Hill, New York, 1964] by a factor 6.7 . Using the experimental value 0.0166nm , the plasma densities derived from Stark broadening agree well with those most recently obtained from Théberge et al.'s measurement of the nitrogen fluorescence calibrated by longitudinal diffraction [F. Théberge, W. Liu, P.T. Simard, A. Becker, S. L. Chin, Phys. Rev. E 74 (2006) 036406]. However, the Stark broadening approach is much simpler and can be used to non-invasively measure the filament plasma density distribution in air under different propagation conditions.

  1. Expression analysis in response to drought stress in soybean: Shedding light on the regulation of metabolic pathway genes.

    PubMed

    Guimarães-Dias, Fábia; Neves-Borges, Anna Cristina; Viana, Antonio Americo Barbosa; Mesquita, Rosilene Oliveira; Romano, Eduardo; de Fátima Grossi-de-Sá, Maria; Nepomuceno, Alexandre Lima; Loureiro, Marcelo Ehlers; Alves-Ferreira, Márcio

    2012-06-01

    Metabolomics analysis of wild type Arabidopsis thaliana plants, under control and drought stress conditions revealed several metabolic pathways that are induced under water deficit. The metabolic response to drought stress is also associated with ABA dependent and independent pathways, allowing a better understanding of the molecular mechanisms in this model plant. Through combining an in silico approach and gene expression analysis by quantitative real-time PCR, the present work aims at identifying genes of soybean metabolic pathways potentially associated with water deficit. Digital expression patterns of Arabidopsis genes, which were selected based on the basis of literature reports, were evaluated under drought stress condition by Genevestigator. Genes that showed strong induction under drought stress were selected and used as bait to identify orthologs in the soybean genome. This allowed us to select 354 genes of putative soybean orthologs of 79 Arabidopsis genes belonging to 38 distinct metabolic pathways. The expression pattern of the selected genes was verified in the subtractive libraries available in the GENOSOJA project. Subsequently, 13 genes from different metabolic pathways were selected for validation by qPCR experiments. The expression of six genes was validated in plants undergoing drought stress in both pot-based and hydroponic cultivation systems. The results suggest that the metabolic response to drought stress is conserved in Arabidopsis and soybean plants.

  2. Learning Principal Component Analysis by Using Data from Air Quality Networks

    ERIC Educational Resources Information Center

    Perez-Arribas, Luis Vicente; Leon-González, María Eugenia; Rosales-Conrado, Noelia

    2017-01-01

    With the final objective of using computational and chemometrics tools in the chemistry studies, this paper shows the methodology and interpretation of the Principal Component Analysis (PCA) using pollution data from different cities. This paper describes how students can obtain data on air quality and process such data for additional information…

  3. FORMAL UNCERTAINTY ANALYSIS OF A LAGRANGIAN PHOTOCHEMICAL AIR POLLUTION MODEL. (R824792)

    EPA Science Inventory

    This study applied Monte Carlo analysis with Latin
    hypercube sampling to evaluate the effects of uncertainty
    in air parcel trajectory paths, emissions, rate constants,
    deposition affinities, mixing heights, and atmospheric stability
    on predictions from a vertically...

  4. Investigating dysregulated pathways in Staphylococcus aureus (SA) exposed macrophages based on pathway interaction network.

    PubMed

    Zhou, Wei; Zhang, Yan; Li, Yue-Hua; Wang, Shuang; Zhang, Jing-Jing; Zhang, Cui-Xia; Zhang, Zhi-Sheng

    2017-02-01

    This work aimed to identify dysregulated pathways for Staphylococcus aureus (SA) exposed macrophages based on pathway interaction network (PIN). The inference of dysregulated pathways was comprised of four steps: preparing gene expression data, protein-protein interaction (PPI) data and pathway data; constructing a PIN dependent on the data and Pearson correlation coefficient (PCC); selecting seed pathway from PIN by computing activity score for each pathway according to principal component analysis (PCA) method; and investigating dysregulated pathways in a minimum set of pathways (MSP) utilizing seed pathway and the area under the receiver operating characteristics curve (AUC) index implemented in support vector machines (SVM) model. A total of 20,545 genes, 449,833 interactions and 1189 pathways were obtained in the gene expression data, PPI data and pathway data, respectively. The PIN was consisted of 8388 interactions and 1189 nodes, and Respiratory electron transport, ATP synthesis by chemiosmotic coupling, and heat production by uncoupling proteins was identified as the seed pathway. Finally, 15 dysregulated pathways in MSP (AUC=0.999) were obtained for SA infected samples, such as Respiratory electron transport and DNA Replication. We have identified 15 dysregulated pathways for SA infected macrophages based on PIN. The findings might provide potential biomarkers for early detection and therapy of SA infection, and give insights to reveal the molecular mechanism underlying SA infections. However, how these dysregulated pathways worked together still needs to be studied. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Estimating Environmental Co-benefits of U.S. CO2 Reduction Pathways Using the GCAM-USA Integrated Assessment Model

    EPA Science Inventory

    Various technological pathways can lead to reduced CO2 emissions. However, different pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. The Global Change Assessment Model (GCAM) is a high resolu...

  6. Proteomic Analysis Reveals the Contribution of TGFβ/Smad4 Signaling Pathway to Cell Differentiation During Planarian Tail Regeneration.

    PubMed

    Chen, Xiaoguang; Xu, Cunshuan

    2017-06-01

    After planarian tail is cut off, posterior end of the remaining fragment will regenerate a new tail within about 1 week. However, many details of this process remain unclear up to date. For this reason, we performed the dynamic proteomic analysis of the regenerating tail fragments at 6, 12, 24, 72, 120, and 168 h post-amputation (hpa). Using two-dimensional electrophoresis (2-DE) in combination with MALDI-TOF-TOF/MS analysis, a total of 1088 peptides were identified as significantly changed between tail-cutting groups and 0-h group, 482 of which have identifiable protein names. Of these 482 proteins, there were 111 originating from the Turbellaria. Protein functional categorization showed that these 111 proteins are mainly related to differentiation and development, transcription and translation, cell signal transduction, and cell proliferation. The screening of key protein considered the transcription factor Smad4 as important protein for planarian tail regeneration. Cell signaling pathway analysis, combined with proteomic profiling of regenerating tail fragment, showed that TGFβ/Smad4 pathway was activated during planarian tail regeneration. Based on a comprehensive analysis of 2-DE MALDI-TOF-TOF/MS and bioinformatics analyses, it could be concluded that TGFβ/Smad4 pathway perhaps plays an important role in tail regeneration via promoting cell differentiation.

  7. Impact of ambient air pollution on obesity: a systematic review.

    PubMed

    An, Ruopeng; Ji, Mengmeng; Yan, Hai; Guan, Chenghua

    2018-05-24

    Over 80% of the global populations living in urban areas are exposed to air quality levels that exceed the World Health Organization limits. Air pollution may lead to unhealthy body weight through metabolic dysfunction, chronic disease onset, and disruption of regular physical activity. A literature search was conducted in the PubMed and Web of Science for peer-reviewed articles published until September 2017 that assessed the relationship between air pollution and body weight status. A standardized data extraction form was used to collect methodological and outcome variables from each eligible study. Sixteen studies met the selection criteria and were included in the review. They were conducted in seven countries, including the US (n = 9), China (n = 2), Canada (n = 1), Italy (n = 1), The Netherlands (n = 1), Serbia (n = 1), and South Korea (n = 1). Half of them adopted a longitudinal study design, and the rest adopted a cross-sectional study design. Commonly examined air pollutants included PM, NO 2 , SO 2 , O 3 , and overall air quality index. Among a total of 66 reported associations between air pollution and body weight status, 29 (44%) found air pollution to be positively associated with body weight, 29 (44%) reported a null finding, and the remaining eight (12%) found air pollution to be negatively associated with body weight. The reported associations between air pollution and body weight status varied by sex, age group, and type of air pollutant. Three pathways hypothesized in the selected studies were through increased oxidative stress and adipose tissue inflammation, elevated risk for chronic comorbidities, and insufficient physical activity. Concurrent evidence regarding the impact of air pollution on body weight status remains mixed. Future studies should assess the impact of severe air pollution on obesity in developing countries, focus on a homogenous population subgroup, and elucidate the biomedical and psychosocial

  8. Functional pathway analysis of genes associated with response to treatment for chronic hepatitis C.

    PubMed

    Birerdinc, A; Afendy, A; Stepanova, M; Younossi, I; Manyam, G; Baranova, A; Younossi, Z M

    2010-10-01

    Chronic hepatitis C (CH-C) is among the most common causes of chronic liver disease. Approximately 50% of patients with CH-C treated with pegylated interferon-α and ribavirin (PEG-IFN-α + RBV) achieve a sustained virological response (SVR). Several factors such as genotype 1, African American (AA) race, obesity and the absence of an early virological response (EVR) are associated with low SVR. This study elucidates molecular pathways deregulated in patients with CH-C with negative predictors of response to antiviral therapy. Sixty-eight patients with CH-C who underwent a full course of treatment with PEG-IFN-α + RBV were included in the study. Pretreatment blood samples were collected in PAXgene™ RNA tubes. EVR, complete EVR (cEVR), and SVR rates were 76%, 57% and 41%, respectively. Total RNA was extracted from pretreatment peripheral blood mononuclear cells, quantified and used for one-step RT-PCR to profile 154 mRNAs. The expression of mRNAs was normalized with six 'housekeeping' genes. Differentially expressed genes were separated into up and downregulated gene lists according to the presence or absence of a risk factor and subjected to KEGG Pathway Painter which allows high-throughput visualization of the pathway-specific changes in expression profiles. The genes were consolidated into the networks associated with known predictors of response. Before treatment, various genes associated with core components of the JAK/STAT pathway were activated in the cohorts least likely to achieve SVR. Genes related to focal adhesion and TGF-β pathways were activated in some patients with negative predictors of response. Pathway-centred analysis of gene expression profiles from treated patients with CH-C points to the Janus kinase-signal transducers and activators of transcription signalling cascade as the major pathogenetic component responsible for not achieving SVR. In addition, focal adhesion and TGF-β pathways are associated with some predictors of response.

  9. Comparative Analysis of Argonaute-dependent Small RNA Pathways in Drosophila

    PubMed Central

    Zhou, Rui; Hotta, Ikuko; Denli, Ahmet M.; Hong, Pengyu; Perrimon, Norbert; Hannon, Gregory J.

    2008-01-01

    Summary The specificity of RNAi pathways is determined by several classes of small RNAs, which include siRNAs, piRNAs, endo-siRNAs, and microRNAs (miRNAs). These small RNAs are invariably incorporated into large Argonaute (Ago)-containing effector complexes known as RNA-induced silencing complexes (RISCs), which they guide to silencing targets. Both genetic and biochemical strategies have yielded conserved molecular components of small RNA biogenesis and effector machineries. However, given the complexity of these pathways, there are likely to be additional components and regulators that remain to be uncovered. We have undertaken a comparative and comprehensive RNAi screen to identify genes that impact three major Ago-dependent small RNA pathways that operate in Drosophila S2 cells. We identify subsets of candidates that act positively or negatively in siRNA, endo-siRNA and miRNA pathways. Our studies indicate that many components are shared among all three Argonaute-dependent silencing pathways, though each is also impacted by discrete sets of genes. PMID:19026789

  10. The impact of ambient air pollution on the human blood metabolome.

    PubMed

    Vlaanderen, J J; Janssen, N A; Hoek, G; Keski-Rahkonen, P; Barupal, D K; Cassee, F R; Gosens, I; Strak, M; Steenhof, M; Lan, Q; Brunekreef, B; Scalbert, A; Vermeulen, R C H

    2017-07-01

    Biological perturbations caused by air pollution might be reflected in the compounds present in blood originating from air pollutants and endogenous metabolites influenced by air pollution (defined here as part of the blood metabolome). We aimed to assess the perturbation of the blood metabolome in response to short term exposure to air pollution. We exposed 31 healthy volunteers to ambient air pollution for 5h. We measured exposure to particulate matter, particle number concentrations, absorbance, elemental/organic carbon, trace metals, secondary inorganic components, endotoxin content, gaseous pollutants, and particulate matter oxidative potential. We collected blood from the participants 2h before and 2 and 18h after exposure. We employed untargeted metabolite profiling to monitor 3873 metabolic features in 493 blood samples from these volunteers. We assessed lung function using spirometry and six acute phase proteins in peripheral blood. We assessed the association of the metabolic features with the measured air pollutants and with health markers that we previously observed to be associated with air pollution in this study. We observed 89 robust associations between air pollutants and metabolic features two hours after exposure and 118 robust associations 18h after exposure. Some of the metabolic features that were associated with air pollutants were also associated with acute health effects, especially changes in forced expiratory volume in 1s. We successfully identified tyrosine, guanosine, and hypoxanthine among the associated features. Bioinformatics approach Mummichog predicted enriched pathway activity in eight pathways, among which tyrosine metabolism. This study demonstrates for the first time the application of untargeted metabolite profiling to assess the impact of air pollution on the blood metabolome. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.

    PubMed

    Chen, Yunshun; Lun, Aaron T L; Smyth, Gordon K

    2016-01-01

    In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims of RNA-seq profiling is to identify genes or molecular pathways that are differentially expressed (DE) between two or more biological conditions. This article demonstrates a computational workflow for the detection of DE genes and pathways from RNA-seq data by providing a complete analysis of an RNA-seq experiment profiling epithelial cell subsets in the mouse mammary gland. The workflow uses R software packages from the open-source Bioconductor project and covers all steps of the analysis pipeline, including alignment of read sequences, data exploration, differential expression analysis, visualization and pathway analysis. Read alignment and count quantification is conducted using the Rsubread package and the statistical analyses are performed using the edgeR package. The differential expression analysis uses the quasi-likelihood functionality of edgeR.

  12. Diet and Colorectal Cancer: Analysis of a Candidate Pathway Using SNPS, Haplotypes, and Multi-Gene Assessment

    PubMed Central

    Slattery, Martha L.; Lundgreen, Abbie; Herrick, Jennifer S.; Caan, Bette J.; Potter, John D.; Wolff, Roger K.

    2012-01-01

    There is considerable biologic plausibility to the hypothesis that genetic variability in pathways involved in insulin signaling and energy homeostasis may modulate dietary risk associated with colorectal cancer. We utilized data from 2 population-based case-control studies of colon (n = 1,574 cases, 1,970 controls) and rectal (n = 791 cases, 999 controls) cancer to evaluate genetic variation in candidate SNPs identified from 9 genes in a candidate pathway: PDK1, RP6KA1, RPS6KA2, RPS6KB1, RPS6KB2, PTEN, FRAP1 (mTOR), TSC1, TSC2, Akt1, PIK3CA, and PRKAG2 with dietary intake of total energy, carbohydrates, fat, and fiber. We employed SNP, haplotype, and multiple-gene analysis to evaluate associations. PDK1 interacted with dietary fat for both colon and rectal cancer and with dietary carbohydrates for colon cancer. Statistically significant interaction with dietary carbohydrates and rectal cancer was detected by haplotype analysis of PDK1. Evaluation of dietary interactions with multiple genes in this candidate pathway showed several interactions with pairs of genes: Akt1 and PDK1, PDK1 and PTEN, PDK1 and TSC1, and PRKAG2 and PTEN. Analyses show that genetic variation influences risk of colorectal cancer associated with diet and illustrate the importance of evaluating dietary interactions beyond the level of single SNPs or haplotypes when a biologically relevant candidate pathway is examined. PMID:21999454

  13. Pathway collages: personalized multi-pathway diagrams.

    PubMed

    Paley, Suzanne; O'Maille, Paul E; Weaver, Daniel; Karp, Peter D

    2016-12-13

    Metabolic pathway diagrams are a classical way of visualizing a linked cascade of biochemical reactions. However, to understand some biochemical situations, viewing a single pathway is insufficient, whereas viewing the entire metabolic network results in information overload. How do we enable scientists to rapidly construct personalized multi-pathway diagrams that depict a desired collection of interacting pathways that emphasize particular pathway interactions? We define software for constructing personalized multi-pathway diagrams called pathway-collages using a combination of manual and automatic layouts. The user specifies a set of pathways of interest for the collage from a Pathway/Genome Database. Layouts for the individual pathways are generated by the Pathway Tools software, and are sent to a Javascript Pathway Collage application implemented using Cytoscape.js. That application allows the user to re-position pathways; define connections between pathways; change visual style parameters; and paint metabolomics, gene expression, and reaction flux data onto the collage to obtain a desired multi-pathway diagram. We demonstrate the use of pathway collages in two application areas: a metabolomics study of pathogen drug response, and an Escherichia coli metabolic model. Pathway collages enable facile construction of personalized multi-pathway diagrams.

  14. Identification and pathway analysis of microRNAs with no previous involvement in breast cancer.

    PubMed

    Romero-Cordoba, Sandra; Rodriguez-Cuevas, Sergio; Rebollar-Vega, Rosa; Quintanar-Jurado, Valeria; Maffuz-Aziz, Antonio; Jimenez-Sanchez, Gerardo; Bautista-Piña, Veronica; Arellano-Llamas, Rocio; Hidalgo-Miranda, Alfredo

    2012-01-01

    microRNA expression signatures can differentiate normal and breast cancer tissues and can define specific clinico-pathological phenotypes in breast tumors. In order to further evaluate the microRNA expression profile in breast cancer, we analyzed the expression of 667 microRNAs in 29 tumors and 21 adjacent normal tissues using TaqMan Low-density arrays. 130 miRNAs showed significant differential expression (adjusted P value = 0.05, Fold Change = 2) in breast tumors compared to the normal adjacent tissue. Importantly, the role of 43 of these microRNAs has not been previously reported in breast cancer, including several evolutionary conserved microRNA*, showing similar expression rates to that of their corresponding leading strand. The expression of 14 microRNAs was replicated in an independent set of 55 tumors. Bioinformatic analysis of mRNA targets of the altered miRNAs, identified oncogenes like ERBB2, YY1, several MAP kinases, and known tumor-suppressors like FOXA1 and SMAD4. Pathway analysis identified that some biological process which are important in breast carcinogenesis are affected by the altered microRNA expression, including signaling through MAP kinases and TP53 pathways, as well as biological processes like cell death and communication, focal adhesion and ERBB2-ERBB3 signaling. Our data identified the altered expression of several microRNAs whose aberrant expression might have an important impact on cancer-related cellular pathways and whose role in breast cancer has not been previously described.

  15. Pathway analysis from lists of microRNAs: common pitfalls and alternative strategy

    PubMed Central

    Godard, Patrice; van Eyll, Jonathan

    2015-01-01

    MicroRNAs (miRNAs) are involved in the regulation of gene expression at a post-transcriptional level. As such, monitoring miRNA expression has been increasingly used to assess their role in regulatory mechanisms of biological processes. In large scale studies, once miRNAs of interest have been identified, the target genes they regulate are often inferred using algorithms or databases. A pathway analysis is then often performed in order to generate hypotheses about the relevant biological functions controlled by the miRNA signature. Here we show that the method widely used in scientific literature to identify these pathways is biased and leads to inaccurate results. In addition to describing the bias and its origin we present an alternative strategy to identify potential biological functions specifically impacted by a miRNA signature. More generally, our study exemplifies the crucial need of relevant negative controls when developing, and using, bioinformatics methods. PMID:25800743

  16. Information-dependent enrichment analysis reveals time-dependent transcriptional regulation of the estrogen pathway of toxicity.

    PubMed

    Pendse, Salil N; Maertens, Alexandra; Rosenberg, Michael; Roy, Dipanwita; Fasani, Rick A; Vantangoli, Marguerite M; Madnick, Samantha J; Boekelheide, Kim; Fornace, Albert J; Odwin, Shelly-Ann; Yager, James D; Hartung, Thomas; Andersen, Melvin E; McMullen, Patrick D

    2017-04-01

    The twenty-first century vision for toxicology involves a transition away from high-dose animal studies to in vitro and computational models (NRC in Toxicity testing in the 21st century: a vision and a strategy, The National Academies Press, Washington, DC, 2007). This transition requires mapping pathways of toxicity by understanding how in vitro systems respond to chemical perturbation. Uncovering transcription factors/signaling networks responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining the chemical modes of action through which a toxicant acts. Traditionally, transcription factor identification is achieved via chromatin immunoprecipitation studies and summarized by calculating which transcription factors are statistically associated with up- and downregulated genes. These lists are commonly determined via statistical or fold-change cutoffs, a procedure that is sensitive to statistical power and may not be as useful for determining transcription factor associations. To move away from an arbitrary statistical or fold-change-based cutoff, we developed, in the context of the Mapping the Human Toxome project, an enrichment paradigm called information-dependent enrichment analysis (IDEA) to guide identification of the transcription factor network. We used a test case of activation in MCF-7 cells by 17β estradiol (E2). Using this new approach, we established a time course for transcriptional and functional responses to E2. ERα and ERβ were associated with short-term transcriptional changes in response to E2. Sustained exposure led to recruitment of additional transcription factors and alteration of cell cycle machinery. TFAP2C and SOX2 were the transcription factors most highly correlated with dose. E2F7, E2F1, and Foxm1, which are involved in cell proliferation, were enriched only at 24 h. IDEA should be useful for identifying candidate pathways of toxicity. IDEA outperforms gene set enrichment

  17. APPLICATION OF BAYESIAN MONTE CARLO ANALYSIS TO A LAGRANGIAN PHOTOCHEMICAL AIR QUALITY MODEL. (R824792)

    EPA Science Inventory

    Uncertainties in ozone concentrations predicted with a Lagrangian photochemical air quality model have been estimated using Bayesian Monte Carlo (BMC) analysis. Bayesian Monte Carlo analysis provides a means of combining subjective "prior" uncertainty estimates developed ...

  18. The Third Air Force/NASA Symposium on Recent Advances in Multidisciplinary Analysis and Optimization

    NASA Technical Reports Server (NTRS)

    1990-01-01

    The third Air Force/NASA Symposium on Recent Advances in Multidisciplinary Analysis and Optimization was held on 24-26 Sept. 1990. Sessions were on the following topics: dynamics and controls; multilevel optimization; sensitivity analysis; aerodynamic design software systems; optimization theory; analysis and design; shape optimization; vehicle components; structural optimization; aeroelasticity; artificial intelligence; multidisciplinary optimization; and composites.

  19. Prioritizing biological pathways by recognizing context in time-series gene expression data.

    PubMed

    Lee, Jusang; Jo, Kyuri; Lee, Sunwon; Kang, Jaewoo; Kim, Sun

    2016-12-23

    The primary goal of pathway analysis using transcriptome data is to find significantly perturbed pathways. However, pathway analysis is not always successful in identifying pathways that are truly relevant to the context under study. A major reason for this difficulty is that a single gene is involved in multiple pathways. In the KEGG pathway database, there are 146 genes, each of which is involved in more than 20 pathways. Thus activation of even a single gene will result in activation of many pathways. This complex relationship often makes the pathway analysis very difficult. While we need much more powerful pathway analysis methods, a readily available alternative way is to incorporate the literature information. In this study, we propose a novel approach for prioritizing pathways by combining results from both pathway analysis tools and literature information. The basic idea is as follows. Whenever there are enough articles that provide evidence on which pathways are relevant to the context, we can be assured that the pathways are indeed related to the context, which is termed as relevance in this paper. However, if there are few or no articles reported, then we should rely on the results from the pathway analysis tools, which is termed as significance in this paper. We realized this concept as an algorithm by introducing Context Score and Impact Score and then combining the two into a single score. Our method ranked truly relevant pathways significantly higher than existing pathway analysis tools in experiments with two data sets. Our novel framework was implemented as ContextTRAP by utilizing two existing tools, TRAP and BEST. ContextTRAP will be a useful tool for the pathway based analysis of gene expression data since the user can specify the context of the biological experiment in a set of keywords. The web version of ContextTRAP is available at http://biohealth.snu.ac.kr/software/contextTRAP .

  20. Canine Supply for Physical Security: An Analysis of the Royal Australian Air Force Military Working Dog Program

    DTIC Science & Technology

    2016-03-01

    PHYSICAL SECURITY: AN ANALYSIS OF THE ROYAL AUSTRALIAN AIR FORCE MILITARY WORKING DOG PROGRAM by Mark W. Powell March 2016 Thesis...AN ANALYSIS OF THE ROYAL AUSTRALIAN AIR FORCE MILITARY WORKING DOG PROGRAM 5. FUNDING NUMBERS 6. AUTHOR(S) Mark W. Powell 7. PERFORMING...increased demand on its physical security elements. Its military working dog (MWD) workforce is required to meet an inventory of 204 by end of year 2023 as

  1. MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

    PubMed Central

    Koumakis, Lefteris; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Vassou, Despoina; Marias, Kostas; Moustakis, Vassilis; Potamias, George

    2016-01-01

    Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the

  2. MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways.

    PubMed

    Koumakis, Lefteris; Kanterakis, Alexandros; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Tsiknakis, Manolis; Vassou, Despoina; Kafetzopoulos, Dimitris; Marias, Kostas; Moustakis, Vassilis; Potamias, George

    2016-11-01

    Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the

  3. Cell cycle pathway dysregulation in human keratinocytes during chronic exposure to low arsenite.

    PubMed

    Al-Eryani, Laila; Waigel, Sabine; Jala, Venkatakrishna; Jenkins, Samantha F; States, J Christopher

    2017-09-15

    Arsenic is naturally prevalent in the earth's crust and widely distributed in air and water. Chronic low arsenic exposure is associated with several cancers in vivo, including skin cancer, and with transformation in vitro of cell lines including immortalized human keratinocytes (HaCaT). Arsenic also is associated with cell cycle dysregulation at different exposure levels in multiple cell lines. In this work, we analyzed gene expression in HaCaT cells to gain an understanding of gene expression changes contributing to transformation at an early time point. HaCaT cells were exposed to 0 or 100nM NaAsO 2 for 7weeks. Total RNA was purified and analyzed by microarray hybridization. Differential expression with fold change≥|1.5| and p-value≤0.05 was determined using Partek Genomic Suite™ and pathway and network analyses using MetaCore™ software (FDR≤0.05). Cell cycle analysis was performed using flow cytometry. 644 mRNAs were differentially expressed. Cell cycle/cell cycle regulation pathways predominated in the list of dysregulated pathways. Genes involved in replication origin licensing were enriched in the network. Cell cycle assay analysis showed an increase in G2/M compartment in arsenite-exposed cells. Arsenite exposure induced differential gene expression indicating dysregulation of cell cycle control, which was confirmed by cell cycle analysis. The results suggest that cell cycle dysregulation is an early event in transformation manifested in cells unable to transit G2/M efficiently. Further study at later time points will reveal additional changes in gene expression related to transformation processes. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Analysis of data on Air Force personnel collected at Lackland Air Force Base

    DOT National Transportation Integrated Search

    1969-10-01

    In July, 1967, a report was published by the Personnel Research Laboratory, Lackland Air Force Base, entitled "An Attempt to Predict Automobile Accidents Among Air Force Personnnel". Approximately twelve thousand basic airmen and eleven hundred offic...

  5. Genomic pathway analysis reveals that EZH2 and HDAC4 represent mutually exclusive epigenetic pathways across human cancers

    PubMed Central

    2013-01-01

    Background Alterations in epigenetic marks, including methylation or acetylation, are common in human cancers. For many epigenetic pathways, however, direct measures of activity are unknown, making their role in various cancers difficult to assess. Gene expression signatures facilitate the examination of patterns of epigenetic pathway activation across and within human cancer types allowing better understanding of the relationships between these pathways. Methods We used Bayesian regression to generate gene expression signatures from normal epithelial cells before and after epigenetic pathway activation. Signatures were applied to datasets from TCGA, GEO, CaArray, ArrayExpress, and the cancer cell line encyclopedia. For TCGA data, signature results were correlated with copy number variation and DNA methylation changes. GSEA was used to identify biologic pathways related to the signatures. Results We developed and validated signatures reflecting downstream effects of enhancer of zeste homolog 2(EZH2), histone deacetylase(HDAC) 1, HDAC4, sirtuin 1(SIRT1), and DNA methyltransferase 2(DNMT2). By applying these signatures to data from cancer cell lines and tumors in large public repositories, we identify those cancers that have the highest and lowest activation of each of these pathways. Highest EZH2 activation is seen in neuroblastoma, hepatocellular carcinoma, small cell lung cancer, and melanoma, while highest HDAC activity is seen in pharyngeal cancer, kidney cancer, and pancreatic cancer. Across all datasets studied, activation of both EZH2 and HDAC4 is significantly underrepresented. Using breast cancer and glioblastoma as examples to examine intrinsic subtypes of particular cancers, EZH2 activation was highest in luminal breast cancers and proneural glioblastomas, while HDAC4 activation was highest in basal breast cancer and mesenchymal glioblastoma. EZH2 and HDAC4 activation are associated with particular chromosome abnormalities: EZH2 activation with

  6. Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future

    PubMed Central

    Barnes, Stephen; Benton, H. Paul; Casazza, Krista; Cooper, Sara; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H.; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K.; Renfrow, Matthew B.; Tiwari, Hemant K.

    2017-01-01

    Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites, and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. PMID:28239968

  7. Buffalo Air Traffic Control Tower Operations Analysis.

    DOT National Transportation Integrated Search

    1981-09-01

    This report provides a description of the non-surveillance aspects of the FAA air traffic control facility operation at Greater Buffalo International Airport from the air traffic controller's point of view. It includes photographs of all controller c...

  8. Molecular population genetics of the insulin/TOR signal transduction pathway: a network-level analysis in Drosophila melanogaster.

    PubMed

    Alvarez-Ponce, David; Guirao-Rico, Sara; Orengo, Dorcas J; Segarra, Carmen; Rozas, Julio; Aguadé, Montserrat

    2012-01-01

    The IT-insulin/target of rapamycin (TOR)-signal transduction pathway is a relatively well-characterized pathway that plays a central role in fundamental biological processes. Network-level analyses of DNA divergence in Drosophila and vertebrates have revealed a clear gradient in the levels of purifying selection along this pathway, with the downstream genes being the most constrained. Remarkably, this feature does not result from factors known to affect selective constraint such as gene expression, codon bias, protein length, and connectivity. The present work aims to establish whether the selective constraint gradient detected along the IT pathway at the between-species level can also be observed at a shorter time scale. With this purpose, we have surveyed DNA polymorphism in Drosophila melanogaster and divergence from D. simulans along the IT pathway. Our network-level analysis shows that DNA polymorphism exhibits the same polarity in the strength of purifying selection as previously detected at the divergence level. This equivalent feature detected both within species and between closely and distantly related species points to the action of a general mechanism, whose action is neither organism specific nor evolutionary time dependent. The detected polarity would be, therefore, intrinsic to the IT pathway architecture and function.

  9. The Akt signaling pathway

    PubMed Central

    Madhunapantula, SubbaRao V; Mosca, Paul J

    2011-01-01

    Studies using cultured melanoma cells and patient tumor biopsies have demonstrated deregulated PI3 kinase-Akt3 pathway activity in ∼70% of melanomas. Furthermore, targeting Akt3 and downstream PRAS40 has been shown to inhibit melanoma tumor development in mice. Although these preclinical studies and several other reports using small interfering RNAs and pharmacological agents targeting key members of this pathway have been shown to retard melanoma development, analysis of early Phase I and Phase II clinical trials using pharmacological agents to target this pathway demonstrate the need for (1) selection of patients whose tumors have PI3 kinase-Akt pathway deregulation, (2) further optimization of therapeutic agents for increased potency and reduced toxicity, (3) the identification of additional targets in the same pathway or in other signaling cascades that synergistically inhibit the growth and progression of melanoma, and (4) better methods for targeted delivery of pharmaceutical agents inhibiting this pathway. In this review we discuss key potential targets in PI3K-Akt3 signaling, the status of pharmacological agents targeting these proteins, drugs under clinical development, and strategies to improve the efficacy of therapeutic agents targeting this pathway. PMID:22157148

  10. Analysis of alternative pathways for reducing nitrogen oxide emissions.

    PubMed

    Loughlin, Daniel H; Kaufman, Katherine R; Lenox, Carol S; Hubbell, Bryan J

    2015-09-01

    Strategies for reducing tropospheric ozone (O3) typically include modifying combustion processes to reduce the formation of nitrogen oxides (NOx) and applying control devices that remove NOx from the exhaust gases of power plants, industrial sources and vehicles. For portions of the U.S., these traditional controls may not be sufficient to achieve the National Ambient Air Quality Standard for ozone. We apply the MARKet ALlocation (MARKAL) energy system model in a sensitivity analysis to explore whether additional NOx reductions can be achieved through extensive electrification of passenger vehicles, adoption of energy efficiency and conservation measures within buildings, and deployment of wind and solar power in the electric sector. Nationally and for each region of the country, we estimate the NOx implications of these measures. Energy efficiency and renewable electricity are shown to reduce NOx beyond traditional controls. Wide-spread light duty vehicle electrification produces varied results, with NOx increasing in some regions and decreasing in others. However, combining vehicle electrification with renewable electricity reduces NOx in all regions. State governments are charged with developing plans that demonstrate how air quality standards will be met and maintained. The results presented here provide an indication of the national and regional NOx reductions available beyond traditional controls via extensive adoption of energy efficiency, renewable electricity, and vehicle electrification.

  11. The Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-Life

    PubMed Central

    Chen, Lei; Lu, Jing; Kong, XiangYin; Huang, Tao; Li, HaiPeng

    2016-01-01

    A drug’s biological half-life is defined as the time required for the human body to metabolize or eliminate 50% of the initial drug dosage. Correctly measuring the half-life of a given drug is helpful for the safe and accurate usage of the drug. In this study, we investigated which gene ontology (GO) terms and biological pathways were highly related to the determination of drug half-life. The investigated drugs, with known half-lives, were analyzed based on their enrichment scores for associated GO terms and KEGG pathways. These scores indicate which GO terms or KEGG pathways the drug targets. The feature selection method, minimum redundancy maximum relevance, was used to analyze these GO terms and KEGG pathways and to identify important GO terms and pathways, such as sodium-independent organic anion transmembrane transporter activity (GO:0015347), monoamine transmembrane transporter activity (GO:0008504), negative regulation of synaptic transmission (GO:0050805), neuroactive ligand-receptor interaction (hsa04080), serotonergic synapse (hsa04726), and linoleic acid metabolism (hsa00591), among others. This analysis confirmed our results and may show evidence for a new method in studying drug half-lives and building effective computational methods for the prediction of drug half-lives. PMID:27780226

  12. Global Analysis of Perovskite Photophysics Reveals Importance of Geminate Pathways

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Manger, Lydia H.; Rowley, Matthew B.; Fu, Yongping

    Hybrid organic-inorganic perovskites demonstrate desirable photophysical behaviors and promising applications from efficient photovoltaics to lasing, but the fundamental nature of excited state species is still under debate. We also collected time-resolved photoluminescence of single-crystal nanoplates of methylammonium lead iodide perovskite (MAPbI3), with excitation over a range of fluences and repetition rates, to provide a more complete photophysical picture. A fundamentally different way of simulating the photophysics is developed that relies on unnormalized decays, global analysis over a large array of conditions, and inclusion of steady-state behavior; these details are critical to capturing observed behaviors. These additional constraints require inclusion ofmore » spatially-correlated pairs, along with free carriers and traps, demonstrating the importance of our comprehensive analysis. Modeling geminate and non-geminate pathways shows geminate processes are dominant at high carrier densities and early times. This combination of data and simulation provides a detailed picture of perovskite photophysics across multiple excitation regimes that was not previously available.« less

  13. Global Analysis of Perovskite Photophysics Reveals Importance of Geminate Pathways

    DOE PAGES

    Manger, Lydia H.; Rowley, Matthew B.; Fu, Yongping; ...

    2016-12-20

    Hybrid organic-inorganic perovskites demonstrate desirable photophysical behaviors and promising applications from efficient photovoltaics to lasing, but the fundamental nature of excited state species is still under debate. We also collected time-resolved photoluminescence of single-crystal nanoplates of methylammonium lead iodide perovskite (MAPbI3), with excitation over a range of fluences and repetition rates, to provide a more complete photophysical picture. A fundamentally different way of simulating the photophysics is developed that relies on unnormalized decays, global analysis over a large array of conditions, and inclusion of steady-state behavior; these details are critical to capturing observed behaviors. These additional constraints require inclusion ofmore » spatially-correlated pairs, along with free carriers and traps, demonstrating the importance of our comprehensive analysis. Modeling geminate and non-geminate pathways shows geminate processes are dominant at high carrier densities and early times. This combination of data and simulation provides a detailed picture of perovskite photophysics across multiple excitation regimes that was not previously available.« less

  14. Analysis of shielded CPW discontinuities with air-bridges

    NASA Technical Reports Server (NTRS)

    Dib, N. I.; Katehi, P. B.; Ponchak, George E.

    1992-01-01

    The effect of air-bridges on the performance of various coplanar waveguides (CPW) discontinuities is studied. Specifically, the coupled open-end CPW's and the short-end shunt CPW stub discontinuities are considered. The high frequency effect of the air-bridge is evaluated using a hybrid technique. At first, the frequency dependent equivalent circuit of the planar discontinuity without the air-bridge is derived using the Space Domain Integral Equation (SDIE) method. Then, the circuit is modified by incorporating the air-bridge's parasitic inductance and capacitance which are evaluated using a simple quasi-static model. The frequency response of each discontinuity with and without the air-bridge is studied and the scattering parameters are plotted in the frequency range 30-50 GHz for typical CPW dimensions.

  15. Targetome Analysis Revealed Involvement of MiR-126 in Neurotrophin Signaling Pathway: A Possible Role in Prevention of Glioma Development.

    PubMed

    Rouigari, Maedeh; Dehbashi, Moein; Ghaedi, Kamran; Pourhossein, Meraj

    2018-07-01

    For the first time, we used molecular signaling pathway enrichment analysis to determine possible involvement of miR-126 and IRS-1 in neurotrophin pathway. In this prospective study, Validated and predicted targets (targetome) of miR-126 were collected following searching miRtarbase (http://mirtarbase.mbc.nctu.edu.tw/) and miRWalk 2.0 databases, respectively. Then, approximate expression of miR-126 targeting in Glioma tissue was examined using UniGene database (http://www.ncbi. nlm.nih.gov/unigene). In silico molecular pathway enrichment analysis was carried out by DAVID 6.7 database (http://david. abcc.ncifcrf.gov/) to explore which signaling pathway is related to miR-126 targeting and how miR-126 attributes to glioma development. MiR-126 exerts a variety of functions in cancer pathogenesis via suppression of expression of target gene including PI3K, KRAS, EGFL7, IRS-1 and VEGF. Our bioinformatic studies implementing DAVID database, showed the involvement of miR-126 target genes in several signaling pathways including cancer pathogenesis, neurotrophin functions, Glioma formation, insulin function, focal adhesion production, chemokine synthesis and secretion and regulation of the actin cytoskeleton. Taken together, we concluded that miR-126 enhances the formation of glioma cancer stem cell probably via down regulation of IRS-1 in neurotrophin signaling pathway. Copyright© by Royan Institute. All rights reserved.

  16. Nonradiological chemical pathway analysis and identification of chemicals of concern for environmental monitoring at the Hanford Site

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Blanton, M.L.; Cooper, A.T.; Castleton, K.J.

    1995-11-01

    Pacific Northwest`s Surface Environmental Surveillance Project (SESP) is an ongoing effort tot design, review, and conducted monitoring on and off the Hanford site. Chemicals of concern that were selected are listed. Using modeled exposure pathways, the offsite cancer incidence and hazard quotient were calculated and a retrospective pathway analysis performed to estimate what onsite concentrations would be required in the soil for each chemical of concern and other detected chemicals that would be required to obtain an estimated offsite human-health risk of 1.0E-06 cancer incidence or 1.0 hazard quotient. This analysis indicates that current nonradiological chemical contamination occurring on themore » site does not pose a significant offsite human-health risk; the highest cancer incidence to the offsite maximally exposed individual was from arsenic (1.76E-10); the highest hazard quotient was chromium(VI) (1.48E-04). The most sensitive pathways of exposure were surfacewater and aquatic food consumption. Combined total offsite excess cancer incidence was 2.09E-10 and estimated hazard quotient was 2.40E-04. Of the 17 identified chemicals of concern, the SESP does not currently (routinely) monitor arsenic, benzo(a)pyrene, bis(2- ethylhexyl)phthalate (BEHP), and chrysene. Only 3 of the chemicals of concern (arsenic, BEHP, chloroform) could actually occur in onsite soil at concern high enough to cause a 1.0E-06 excess cancer incidence or a 1.0 hazard index for a given offsite exposure pathway. During the retrospective analysis, 20 other chemicals were also evaluated; only vinyl chloride and thallium could reach targeted offsite risk values.« less

  17. Biosynthetic Pathway for the Epipolythiodioxopiperazine Acetylaranotin in Aspergillus terreus Revealed by Genome-based Deletion Analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Guo, Chun-Jun; Yeh, Hsu-Hua; Chiang, Yi Ming

    2013-04-15

    Abstract Epipolythiodioxopiperazines (ETPs) are a class of fungal secondary metabolites derived from cyclic peptides. Acetylaranotin belongs to one structural subgroup of ETPs characterized by the presence of a seven-membered dihydrooxepine ring. Defining the genes involved in acetylaranotin biosynthesis should provide a means to increase production of these compounds and facilitate the engineering of second-generation molecules. The filamentous fungus Aspergillus terreus produces acetylaranotin and related natural products. Using targeted gene deletions, we have identified a cluster of 9 genes including one nonribosomal peptide synthase gene, ataP, that is required for acetylaranotin biosynthesis. Chemical analysis of the wild type and mutant strainsmore » enabled us to isolate seventeen natural products that are either intermediates in the normal biosynthetic pathway or shunt products that are produced when the pathway is interrupted through mutation. Nine of the compounds identified in this study are novel natural products. Our data allow us to propose a complete biosynthetic pathway for acetylaranotin and related natural products.« less

  18. Estimating environmental co-benefits of U.S. low-carbon pathways using an integrated assessment model with state-level resolution

    EPA Science Inventory

    There are many technological pathways that can lead to reduced carbon dioxide emissions. However, these pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. This study uses an integrated assessmen...

  19. Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis [Combined Proteomics and Metabolomics Analysis Reveals Grade-Dependent Metabolism Pathways in Kidney Cancer

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter

    Kidney cancer [or renal cell carcinoma (RCC)] is known as “the internist's tumor” because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel–Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburgmore » effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Altogether, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC« less

  20. Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis [Combined Proteomics and Metabolomics Analysis Reveals Grade-Dependent Metabolism Pathways in Kidney Cancer

    DOE PAGES

    Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter; ...

    2015-05-07

    Kidney cancer [or renal cell carcinoma (RCC)] is known as “the internist's tumor” because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel–Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburgmore » effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Altogether, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC« less

  1. Cyclic stress analysis of an air-cooled turbine vane

    NASA Technical Reports Server (NTRS)

    Kaufman, A.; Gauntner, D. J.; Gauntner, J. W.

    1975-01-01

    The effects of gas pressure level, coolant temperature, and coolant flow rate on the stress-strain history and life of an air-cooled vane were analyzed using measured and calculated transient metal temperatures and a turbine blade stress analysis program. Predicted failure locations were compared to results from cyclic tests in a static cascade and engine. The results indicate that a high gas pressure was detrimental, a high coolant flow rate somewhat beneficial, and a low coolant temperature the most beneficial to vane life.

  2. Genome-Wide Gene Set Analysis for Identification of Pathways Associated with Alcohol Dependence

    PubMed Central

    Biernacka, Joanna M.; Geske, Jennifer; Jenkins, Gregory D.; Colby, Colin; Rider, David N.; Karpyak, Victor M.; Choi, Doo-Sup; Fridley, Brooke L.

    2013-01-01

    It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the “Synthesis and Degradation of Ketone Bodies” pathway. Our results also support the potential involvement of the “Neuroactive Ligand Receptor Interaction” pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence. PMID:22717047

  3. The Analysis of PPM Levels of Gases in Air by Photoionization Mass Spectrometry

    ERIC Educational Resources Information Center

    Driscoll, John N.; Warneck, Peter

    1973-01-01

    Discusses analysis of trace gases in air by photoionization mass spectrometer. It is shown that the necessary sensitivity can be obtained by eliminating the UV monochromator and using direct ionization with a hydrogen light source. (JP)

  4. Reconstruction of metabolic pathways for the cattle genome

    PubMed Central

    Seo, Seongwon; Lewin, Harris A

    2009-01-01

    Background Metabolic reconstruction of microbial, plant and animal genomes is a necessary step toward understanding the evolutionary origins of metabolism and species-specific adaptive traits. The aims of this study were to reconstruct conserved metabolic pathways in the cattle genome and to identify metabolic pathways with missing genes and proteins. The MetaCyc database and PathwayTools software suite were chosen for this work because they are widely used and easy to implement. Results An amalgamated cattle genome database was created using the NCBI and Ensembl cattle genome databases (based on build 3.1) as data sources. PathwayTools was used to create a cattle-specific pathway genome database, which was followed by comprehensive manual curation for the reconstruction of metabolic pathways. The curated database, CattleCyc 1.0, consists of 217 metabolic pathways. A total of 64 mammalian-specific metabolic pathways were modified from the reference pathways in MetaCyc, and two pathways previously identified but missing from MetaCyc were added. Comparative analysis of metabolic pathways revealed the absence of mammalian genes for 22 metabolic enzymes whose activity was reported in the literature. We also identified six human metabolic protein-coding genes for which the cattle ortholog is missing from the sequence assembly. Conclusion CattleCyc is a powerful tool for understanding the biology of ruminants and other cetartiodactyl species. In addition, the approach used to develop CattleCyc provides a framework for the metabolic reconstruction of other newly sequenced mammalian genomes. It is clear that metabolic pathway analysis strongly reflects the quality of the underlying genome annotations. Thus, having well-annotated genomes from many mammalian species hosted in BioCyc will facilitate the comparative analysis of metabolic pathways among different species and a systems approach to comparative physiology. PMID:19284618

  5. An analysis of relational complexity in an air traffic control conflict detection task.

    PubMed

    Boag, Christine; Neal, Andrew; Loft, Shayne; Halford, Graeme S

    2006-11-15

    Theoretical analyses of air traffic complexity were carried out using the Method for the Analysis of Relational Complexity. Twenty-two air traffic controllers examined static air traffic displays and were required to detect and resolve conflicts. Objective measures of performance included conflict detection time and accuracy. Subjective perceptions of mental workload were assessed by a complexity-sorting task and subjective ratings of the difficulty of different aspects of the task. A metric quantifying the complexity of pair-wise relations among aircraft was able to account for a substantial portion of the variance in the perceived complexity and difficulty of conflict detection problems, as well as reaction time. Other variables that influenced performance included the mean minimum separation between aircraft pairs and the amount of time that aircraft spent in conflict.

  6. Analysis of air quality in Dire Dawa, Ethiopia.

    PubMed

    Kasim, Oluwasinaayomi Faith; Woldetisadik Abshare, Muluneh; Agbola, Samuel Babatunde

    2017-12-07

    Ambient air quality was monitored and analyzed to develop air quality index and its implications for livability and climate change in Dire Dawa, Ethiopia. Using survey research design, 16 georeferenced locations, representing different land uses, were randomly selected and assessed for sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), carbon dioxide (CO 2 ), carbon monoxide (CO),volatile organic compounds (VOCs), and meteorological parameters (temperature and relative humidity). The study found mean concentrations across all land uses for SO 2 of 0.37 ± 0.08 ppm, NO 2 of 0.13 ± 0.17 ppm, CO 2 of 465.65 ± 28.63 ppm, CO of 3.35 ± 2.04 ppm, and VOCs of 1850.67 ± 402 ppm. An air quality index indicated that ambient air quality for SO 2 was very poor, NO 2 ranged from moderate to very poor, whereas CO rating was moderate. Significant positive correlations existed between temperature and NO 2 , CO 2 , and CO and between humidity and VOCs. Significant relationships were also recorded between CO 2 and NO 2 and between CO and CO 2 . Poor urban planning, inadequate pollution control measure, and weak capacity to monitor air quality have implications for energy usage, air quality, and local meteorological parameters, with subsequent feedback into global climate change. Implementation of programs to monitor and control emissions in order to reduce air pollution will provide health, economic, and environmental benefits to the city. The need to develop and implement emission control programs to reduce air pollution in Dire Dawa City is urgent. This will provide enormous economic, health, and environmental benefits. It is expected that economic effects of air quality improvement will offset the expenditures for pollution control. Also, strategies that focus on air quality and climate change present a unique opportunity to engage different stakeholders in providing inclusive and sustainable development agenda for Dire Dawa.

  7. Identification of metabolic pathways using pathfinding approaches: a systematic review.

    PubMed

    Abd Algfoor, Zeyad; Shahrizal Sunar, Mohd; Abdullah, Afnizanfaizal; Kolivand, Hoshang

    2017-03-01

    Metabolic pathways have become increasingly available for various microorganisms. Such pathways have spurred the development of a wide array of computational tools, in particular, mathematical pathfinding approaches. This article can facilitate the understanding of computational analysis of metabolic pathways in genomics. Moreover, stoichiometric and pathfinding approaches in metabolic pathway analysis are discussed. Three major types of studies are elaborated: stoichiometric identification models, pathway-based graph analysis and pathfinding approaches in cellular metabolism. Furthermore, evaluation of the outcomes of the pathways with mathematical benchmarking metrics is provided. This review would lead to better comprehension of metabolism behaviors in living cells, in terms of computed pathfinding approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  8. Point Analysis in Java applied to histological images of the perforant pathway: a user's account.

    PubMed

    Scorcioni, Ruggero; Wright, Susan N; Patrick Card, J; Ascoli, Giorgio A; Barrionuevo, Germán

    2008-01-01

    The freeware Java tool Point Analysis in Java (PAJ), created to perform 3D point analysis, was tested in an independent laboratory setting. The input data consisted of images of the hippocampal perforant pathway from serial immunocytochemical localizations of the rat brain in multiple views at different resolutions. The low magnification set (x2 objective) comprised the entire perforant pathway, while the high magnification set (x100 objective) allowed the identification of individual fibers. A preliminary stereological study revealed a striking linear relationship between the fiber count at high magnification and the optical density at low magnification. PAJ enabled fast analysis for down-sampled data sets and a friendly interface with automated plot drawings. Noted strengths included the multi-platform support as well as the free availability of the source code, conducive to a broad user base and maximum flexibility for ad hoc requirements. PAJ has great potential to extend its usability by (a) improving its graphical user interface, (b) increasing its input size limit, (c) improving response time for large data sets, and (d) potentially being integrated with other Java graphical tools such as ImageJ.

  9. Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

    PubMed Central

    Silver, Matt; Chen, Peng; Li, Ruoying; Cheng, Ching-Yu; Wong, Tien-Yin; Tai, E-Shyong; Teo, Yik-Ying; Montana, Giovanni

    2013-01-01

    Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune

  10. Pathways-driven sparse regression identifies pathways and genes associated with high-density lipoprotein cholesterol in two Asian cohorts.

    PubMed

    Silver, Matt; Chen, Peng; Li, Ruoying; Cheng, Ching-Yu; Wong, Tien-Yin; Tai, E-Shyong; Teo, Yik-Ying; Montana, Giovanni

    2013-11-01

    Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait's genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune

  11. Atmospheric Ionizing Radiation (AIR) ER-2 Preflight Analysis

    NASA Technical Reports Server (NTRS)

    Tai, Hsiang; Wilson, John W.; Maiden, D. L.

    1998-01-01

    Atmospheric ionizing radiation (AIR) produces chemically active radicals in biological tissues that alter the cell function or result in cell death. The AIR ER-2 flight measurements will enable scientists to study the radiation risk associated with the high-altitude operation of a commercial supersonic transport. The ER-2 radiation measurement flights will follow predetermined, carefully chosen courses to provide an appropriate database matrix which will enable the evaluation of predictive modeling techniques. Explicit scientific results such as dose rate, dose equivalent rate, magnetic cutoff, neutron flux, and air ionization rate associated with those flights are predicted by using the AIR model. Through these flight experiments, we will further increase our knowledge and understanding of the AIR environment and our ability to assess the risk from the associated hazard.

  12. COMPADRE: an R and web resource for pathway activity analysis by component decompositions.

    PubMed

    Ramos-Rodriguez, Roberto-Rafael; Cuevas-Diaz-Duran, Raquel; Falciani, Francesco; Tamez-Peña, Jose-Gerardo; Trevino, Victor

    2012-10-15

    The analysis of biological networks has become essential to study functional genomic data. Compadre is a tool to estimate pathway/gene sets activity indexes using sub-matrix decompositions for biological networks analyses. The Compadre pipeline also includes one of the direct uses of activity indexes to detect altered gene sets. For this, the gene expression sub-matrix of a gene set is decomposed into components, which are used to test differences between groups of samples. This procedure is performed with and without differentially expressed genes to decrease false calls. During this process, Compadre also performs an over-representation test. Compadre already implements four decomposition methods [principal component analysis (PCA), Isomaps, independent component analysis (ICA) and non-negative matrix factorization (NMF)], six statistical tests (t- and f-test, SAM, Kruskal-Wallis, Welch and Brown-Forsythe), several gene sets (KEGG, BioCarta, Reactome, GO and MsigDB) and can be easily expanded. Our simulation results shown in Supplementary Information suggest that Compadre detects more pathways than over-representation tools like David, Babelomics and Webgestalt and less false positives than PLAGE. The output is composed of results from decomposition and over-representation analyses providing a more complete biological picture. Examples provided in Supplementary Information show the utility, versatility and simplicity of Compadre for analyses of biological networks. Compadre is freely available at http://bioinformatica.mty.itesm.mx:8080/compadre. The R package is also available at https://sourceforge.net/p/compadre.

  13. PATIKA: an integrated visual environment for collaborative construction and analysis of cellular pathways.

    PubMed

    Demir, E; Babur, O; Dogrusoz, U; Gursoy, A; Nisanci, G; Cetin-Atalay, R; Ozturk, M

    2002-07-01

    Availability of the sequences of entire genomes shifts the scientific curiosity towards the identification of function of the genomes in large scale as in genome studies. In the near future, data produced about cellular processes at molecular level will accumulate with an accelerating rate as a result of proteomics studies. In this regard, it is essential to develop tools for storing, integrating, accessing, and analyzing this data effectively. We define an ontology for a comprehensive representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information and supports manipulation and incorporation of the stored data, as well as multiple levels of abstraction. Based on this ontology, we present the architecture of an integrated environment named Patika (Pathway Analysis Tool for Integration and Knowledge Acquisition). Patika is composed of a server-side, scalable, object-oriented database and client-side editors to provide an integrated, multi-user environment for visualizing and manipulating network of cellular events. This tool features automated pathway layout, functional computation support, advanced querying and a user-friendly graphical interface. We expect that Patika will be a valuable tool for rapid knowledge acquisition, microarray generated large-scale data interpretation, disease gene identification, and drug development. A prototype of Patika is available upon request from the authors.

  14. Comparative study on gene set and pathway topology-based enrichment methods.

    PubMed

    Bayerlová, Michaela; Jung, Klaus; Kramer, Frank; Klemm, Florian; Bleckmann, Annalen; Beißbarth, Tim

    2015-10-22

    Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis. We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods. In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower. We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both

  15. Exploratory factor analysis of pathway copy number data with an application towards the integration with gene expression data.

    PubMed

    van Wieringen, Wessel N; van de Wiel, Mark A

    2011-05-01

    Realizing that genes often operate together, studies into the molecular biology of cancer shift focus from individual genes to pathways. In order to understand the regulatory mechanisms of a pathway, one must study its genes at all molecular levels. To facilitate such study at the genomic level, we developed exploratory factor analysis for the characterization of the variability of a pathway's copy number data. A latent variable model that describes the call probability data of a pathway is introduced and fitted with an EM algorithm. In two breast cancer data sets, it is shown that the first two latent variables of GO nodes, which inherit a clear interpretation from the call probabilities, are often related to the proportion of aberrations and a contrast of the probabilities of a loss and of a gain. Linking the latent variables to the node's gene expression data suggests that they capture the "global" effect of genomic aberrations on these transcript levels. In all, the proposed method provides an possibly insightful characterization of pathway copy number data, which may be fruitfully exploited to study the interaction between the pathway's DNA copy number aberrations and data from other molecular levels like gene expression.

  16. Design and analysis of synthetic carbon fixation pathways

    PubMed Central

    Bar-Even, Arren; Noor, Elad; Lewis, Nathan E.; Milo, Ron

    2010-01-01

    Carbon fixation is the process by which CO2 is incorporated into organic compounds. In modern agriculture in which water, light, and nutrients can be abundant, carbon fixation could become a significant growth-limiting factor. Hence, increasing the fixation rate is of major importance in the road toward sustainability in food and energy production. There have been recent attempts to improve the rate and specificity of Rubisco, the carboxylating enzyme operating in the Calvin–Benson cycle; however, they have achieved only limited success. Nature employs several alternative carbon fixation pathways, which prompted us to ask whether more efficient novel synthetic cycles could be devised. Using the entire repertoire of approximately 5,000 metabolic enzymes known to occur in nature, we computationally identified alternative carbon fixation pathways that combine existing metabolic building blocks from various organisms. We compared the natural and synthetic pathways based on physicochemical criteria that include kinetics, energetics, and topology. Our study suggests that some of the proposed synthetic pathways could have significant quantitative advantages over their natural counterparts, such as the overall kinetic rate. One such cycle, which is predicted to be two to three times faster than the Calvin–Benson cycle, employs the most effective carboxylating enzyme, phosphoenolpyruvate carboxylase, using the core of the naturally evolved C4 cycle. Although implementing such alternative cycles presents daunting challenges related to expression levels, activity, stability, localization, and regulation, we believe our findings suggest exciting avenues of exploration in the grand challenge of enhancing food and renewable fuel production via metabolic engineering and synthetic biology. PMID:20410460

  17. Recommended Henry’s Law Constants for Non-Groundwater Pathways Models in GoldSim

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dyer, J.

    This memorandum documents the source and numerical value of Henry’s law constants for volatile radionuclides of interest used in the non-groundwater (air and radon) pathways models for the 2018 E-Area Performance Assessment.

  18. Sulfur Hexafluoride 20% Versus Air 100% for Anterior Chamber Tamponade in DMEK: A Meta-Analysis.

    PubMed

    Marques, Raquel Esteves; Guerra, Paulo Silva; Sousa, David Cordeiro; Ferreira, Nuno Pinto; Gonçalves, Ana Inês; Quintas, Ana Miguel; Rodrigues, Walter

    2018-06-01

    To compare intracameral 20% sulfur hexafluoride (SF6) versus 100% air as tamponade for graft attachment in Descemet membrane endothelial keratoplasty (DMEK). Using an electronic database search on MEDLINE and CENTRAL from inception to December 2017, we performed a literature review and meta-analysis including all comparative studies of SF6 at a 20% concentration (20% SF6) versus pure air (100% air) for anterior chamber tamponade in DMEK. The primary outcome was the rebubbling rate at the final observation. The secondary outcomes were 1) the graft detachment rate, 2) mean difference (MD) in best-corrected visual acuity (BCVA), 3) manifest refraction spherical equivalent, 4) central corneal thickness (CCT), 5) percentage of endothelial cell loss (ECL), and 6) rate of pupillary block by the final observation. Statistical analysis was performed using RevMan5.3 software. Five retrospective studies were included, assessing 1195 eyes (SF6 277; air 918). The main indication for surgery was Fuchs endothelial dystrophy (SF6 85.2%; air 86.2%) and bullous keratopathy (SF6 10.8%; air 10.0%). Overall, studies were of moderate to good methodological quality. Patients in the SF6 group required 58% less rebubbling procedures (risk ratio 0.42, 95% confidence interval (CI), 0.31-0.56, P < 0.0001). No differences were found regarding BCVA improvement (MD 0.03, 95% CI, -0.05 to 0.11, P = 0.49). SF6 was associated with a minor hyperopic shift (MD 0.37 D, 95% CI, -0.95 to -0.21, P = 0.21). No differences were found regarding CCT, ECL, and rate of pupillary block (P > 0.05). In DMEK, 20% SF6 tamponade and longer postoperative time supine were associated with 58% fewer rebubbling procedures, and an ECL not statistically different from using 100% air.

  19. KEGGParser: parsing and editing KEGG pathway maps in Matlab.

    PubMed

    Arakelyan, Arsen; Nersisyan, Lilit

    2013-02-15

    KEGG pathway database is a collection of manually drawn pathway maps accompanied with KGML format files intended for use in automatic analysis. KGML files, however, do not contain the required information for complete reproduction of all the events indicated in the static image of a pathway map. Several parsers and editors of KEGG pathways exist for processing KGML files. We introduce KEGGParser-a MATLAB based tool for KEGG pathway parsing, semiautomatic fixing, editing, visualization and analysis in MATLAB environment. It also works with Scilab. The source code is available at http://www.mathworks.com/matlabcentral/fileexchange/37561.

  20. International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

    PubMed

    Cordell, Heather J; Han, Younghun; Mells, George F; Li, Yafang; Hirschfield, Gideon M; Greene, Casey S; Xie, Gang; Juran, Brian D; Zhu, Dakai; Qian, David C; Floyd, James A B; Morley, Katherine I; Prati, Daniele; Lleo, Ana; Cusi, Daniele; Gershwin, M Eric; Anderson, Carl A; Lazaridis, Konstantinos N; Invernizzi, Pietro; Seldin, Michael F; Sandford, Richard N; Amos, Christopher I; Siminovitch, Katherine A

    2015-09-22

    Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist.

  1. Impact of ambient air pollution on physical activity among adults: a systematic review and meta-analysis.

    PubMed

    An, Ruopeng; Zhang, Sheng; Ji, Mengmeng; Guan, Chenghua

    2018-03-01

    This study systematically reviewed literature regarding the impact of ambient air pollution on physical activity among children and adults. Keyword and reference search was conducted in PubMed and Web of Science to systematically identify articles meeting all of the following criteria - study designs: interventions or experiments, retrospective or prospective cohort studies, cross-sectional studies, and case-control studies; subjects: adults; exposures: specific air pollutants and overall air quality; outcomes: physical activity and sedentary behaviour; article types: peer-reviewed publications; and language: articles written in English. Meta-analysis was performed to estimate the pooled effect size of ambient PM 2.5 air pollution on physical inactivity. Seven studies met the inclusion criteria. Among them, six were conducted in the United States, and one was conducted in the United Kingdom. Six adopted a cross-sectional study design, and one used a prospective cohort design. Six had a sample size larger than 10,000. Specific air pollutants assessed included PM 2.5 , PM 10 , O 3 , and NO x , whereas two studies focused on overall air quality. All studies found air pollution level to be negatively associated with physical activity and positively associated with leisure-time physical inactivity. Study participants, and particularly those with respiratory disease, self-reported a reduction in outdoor activities to mitigate the detrimental impact of air pollution. Meta-analysis revealed a one unit (μg/m 3 ) increase in ambient PM 2.5 concentration to be associated with an increase in the odds of physical inactivity by 1.1% (odds ratio = 1.011; 95% confidence interval = 1.001, 1.021; p-value < .001) among US adults. Existing literature in general suggested that air pollution discouraged physical activity. Current literature predominantly adopted a cross-sectional design and focused on the United States. Future studies are warranted to implement a longitudinal

  2. Transcriptome profiling and pathway analysis of hepatotoxicity induced by tris (2-ethylhexyl) trimellitate (TOTM) in mice.

    PubMed

    Chen, Xian-Hua; Ma, Li; Hu, Yi-Xiang; Wang, Dan-Xian; Fang, Li; Li, Xue-Lai; Zhao, Jin-Chuan; Yu, Hai-Rong; Ying, Hua-Zhong; Yu, Chen-Huan

    2016-01-01

    Tris (2-ethylhexyl) trimellitate (TOTM) is commonly used as an alternative plasticizer for medical devices. But very little information was available on its biological effects. In this study, we investigated toxicity effects of TOTM on hepatic differential gene expression analyzed by using high-throughput sequencing analysis for over-represented functions and phenotypically anchored to complementary histopathologic, and biochemical data in the liver of mice. Among 1668 candidate genes, 694 genes were up-regulated and 974 genes were down-regulated after TOTM exposure. Using Gene Ontology analysis, TOTM affected three processes: the cell cycle, metabolic process and oxidative activity. Furthermore, 11 key genes involved in the above processes were validated by real time PCR. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that these genes were involved in the cell cycle pathway, lipid metabolism and oxidative process. It revealed the transcriptome gene expression response to TOTM exposure in mouse, and these data could contribute to provide a clearer understanding of the molecular mechanisms of TOTM-induced hepatotoxicity in human. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Microscopic analysis of filament in air

    DTIC Science & Technology

    2016-09-13

    scroll pump . The laser beam is shown with a red arrow. It is focused with a parabolic mirror inside at the center of the chamber which is the center...supersonic flow of air acts as a wall between our vacuum chamber and atmospheric air. This design enables us to measure the filaments directly as they...are launched in a vacuum chamber. 3 Technical discussion 3.1 Status of filament research Tinny “pits” were observed in mirrors placed in the path of

  4. Epigenome-Wide Meta-Analysis of Methylation in Children Related to Prenatal NO2 Air Pollution Exposure

    PubMed Central

    Gruzieva, Olena; Xu, Cheng-Jian; Breton, Carrie V.; Annesi-Maesano, Isabella; Antó, Josep M.; Auffray, Charles; Ballereau, Stéphane; Bellander, Tom; Bousquet, Jean; Bustamante, Mariona; Charles, Marie-Aline; de Kluizenaar, Yvonne; den Dekker, Herman T.; Duijts, Liesbeth; Felix, Janine F.; Gehring, Ulrike; Guxens, Mònica; Jaddoe, Vincent V.W.; Jankipersadsing, Soesma A.; Merid, Simon Kebede; Kere, Juha; Kumar, Ashish; Lemonnier, Nathanael; Lepeule, Johanna; Nystad, Wenche; Page, Christian Magnus; Panasevich, Sviatlana; Postma, Dirkje; Slama, Rémy; Sunyer, Jordi; Söderhäll, Cilla; Yao, Jin; London, Stephanie J.; Pershagen, Göran; Koppelman, Gerard H.; Melén, Erik

    2016-01-01

    Background: Prenatal exposure to air pollution is considered to be associated with adverse effects on child health. This may partly be mediated by mechanisms related to DNA methylation. Objectives: We investigated associations between exposure to air pollution, using nitrogen dioxide (NO2) as marker, and epigenome-wide cord blood DNA methylation. Methods: We meta-analyzed the associations between NO2 exposure at residential addresses during pregnancy and cord blood DNA methylation (Illumina 450K) in four European and North American studies (n = 1,508) with subsequent look-up analyses in children ages 4 (n = 733) and 8 (n = 786) years. Additionally, we applied a literature-based candidate approach for antioxidant and anti-inflammatory genes. To assess influence of exposure at the transcriptomics level, we related mRNA expression in blood cells to NO2 exposure in 4- (n = 111) and 16-year-olds (n = 239). Results: We found epigenome-wide significant associations [false discovery rate (FDR) p < 0.05] between maternal NO2 exposure during pregnancy and DNA methylation in newborns for 3 CpG sites in mitochondria-related genes: cg12283362 (LONP1), cg24172570 (3.8 kbp upstream of HIBADH), and cg08973675 (SLC25A28). The associations with cg08973675 methylation were also significant in the older children. Further analysis of antioxidant and anti-inflammatory genes revealed differentially methylated CpGs in CAT and TPO in newborns (FDR p < 0.05). NO2 exposure at the time of biosampling in childhood had a significant impact on CAT and TPO expression. Conclusions: NO2 exposure during pregnancy was associated with differential offspring DNA methylation in mitochondria-related genes. Exposure to NO2 was also linked to differential methylation as well as expression of genes involved in antioxidant defense pathways. Citation: Gruzieva O, Xu CJ, Breton CV, Annesi-Maesano I, Antó JM, Auffray C, Ballereau S, Bellander T, Bousquet J, Bustamante M, Charles MA, de Kluizenaar Y, den Dekker

  5. Microbiological Analysis of the Food Preparation and Dining Facilities at Fort Myer and Bolling Air Force Base

    DTIC Science & Technology

    1975-02-01

    the viewpoint of microbiological safety one would be tempted to conclude that Ft. Myer had a much lower risk hazard than Bolting Air Force Base. The...I TECHNICAL REPORT I I 76·63-FSL MICROBIOLOGICAL ANAL.YSIS OF THE FOOD PREPARATION AND DINING FACILITIES AT FORT MYER AND BOLLING AIR FORCE...RECIPIENT’ S CATALOG NUMBER 75-53-ESL 4. TITLE (and Subtltlo) 5. TYPE OF REPOR T & PERIOD COVERED Microbiological Analysis of the Food Preparation and

  6. Genetic susceptibility for air pollution-induced airway inflammation in the SALIA study.

    PubMed

    Hüls, Anke; Krämer, Ursula; Herder, Christian; Fehsel, Karin; Luckhaus, Christian; Stolz, Sabine; Vierkötter, Andrea; Schikowski, Tamara

    2017-01-01

    Long-term air pollution exposure has been associated with chronic inflammation providing a link to the development of chronic health effects. Furthermore, there is evidence that pathways activated by endoplasmatic reticulum (ER) stress induce airway inflammation and thereby play an important role in the pathogenesis of inflammatory diseases. We investigated the role of genetic variation of the ER stress pathway on air pollution-induced inflammation. We used the follow-up examination of the German SALIA study (N=402, age 68-79 years). Biomarkers of inflammation were determined in induced sputum. We calculated biomarker-specific weighted genetic risk scores (GRS) out of eight ER stress related single nucleotide polymorphisms and tested their interaction with PM 2.5 , PM 2.5 absorbance, PM 10 and NO 2 exposure on inflammation by adjusted linear regression. Genetic variation of the ER stress pathway was associated with higher concentration of inflammation-related biomarkers (levels of leukotriene (LT)B 4 , tumor necrosis factor-α (TNF-α), the total number of cells and nitric oxide (NO) derivatives). Furthermore, we observed a significant interaction between air pollution exposure and the ER stress risk score on the concentration of inflammation-related biomarkers. The strongest gene-environment interaction was found for LTB 4 (PM 2.5 : p-value=0.002, PM 2.5 absorbance: p-value=0.002, PM 10 : p-value=0.001 and NO 2 : p-value=0.004). Women with a high GRS had a 38% (95%-CI: 16-64%) higher LTB 4 level for an increase of 2.06μg/m³(IQR) in PM 2.5 (no associations in women with a low GRS). These results indicate that genetic variation in the ER stress pathway might play a role in air pollution induced inflammation in the lung. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. SPIKE – a database, visualization and analysis tool of cellular signaling pathways

    PubMed Central

    Elkon, Ran; Vesterman, Rita; Amit, Nira; Ulitsky, Igor; Zohar, Idan; Weisz, Mali; Mass, Gilad; Orlev, Nir; Sternberg, Giora; Blekhman, Ran; Assa, Jackie; Shiloh, Yosef; Shamir, Ron

    2008-01-01

    Background Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level. Results To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1) A database (DB) of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2) A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3) An algorithmic inference engine that analyzes the networks for novel functional interplays between network components. SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise. Conclusion The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data. PMID:18289391

  8. Nanosystem self-assembly pathways discovered via all-atom multiscale analysis.

    PubMed

    Pankavich, Stephen D; Ortoleva, Peter J

    2012-07-26

    We consider the self-assembly of composite structures from a group of nanocomponents, each consisting of particles within an N-atom system. Self-assembly pathways and rates for nanocomposites are derived via a multiscale analysis of the classical Liouville equation. From a reduced statistical framework, rigorous stochastic equations for population levels of beginning, intermediate, and final aggregates are also derived. It is shown that the definition of an assembly type is a self-consistency criterion that must strike a balance between precision and the need for population levels to be slowly varying relative to the time scale of atomic motion. The deductive multiscale approach is complemented by a qualitative notion of multicomponent association and the ensemble of exact atomic-level configurations consistent with them. In processes such as viral self-assembly from proteins and RNA or DNA, there are many possible intermediates, so that it is usually difficult to predict the most efficient assembly pathway. However, in the current study, rates of assembly of each possible intermediate can be predicted. This avoids the need, as in a phenomenological approach, for recalibration with each new application. The method accounts for the feedback across scales in space and time that is fundamental to nanosystem self-assembly. The theory has applications to bionanostructures, geomaterials, engineered composites, and nanocapsule therapeutic delivery systems.

  9. Air pollution and stroke - an overview of the evidence base.

    PubMed

    Maheswaran, Ravi

    2016-08-01

    Air pollution is being increasingly recognized as a significant risk factor for stroke. There are numerous sources of air pollution including industry, road transport and domestic use of biomass and solid fuels. Early reports of the association between air pollution and stroke come from studies investigating health effects of severe pollution episodes. Several daily time series and case-crossover studies have reported associations with stroke. There is also evidence linking chronic air pollution exposure with stroke and with reduced survival after stroke. A conceptual framework linking air pollution exposure and stroke is proposed. It links acute and chronic exposure to air pollution with pathways to acute and chronic effects on stroke risk. Current evidence regarding potential mechanisms mainly relate to particulate air pollution. Whilst further evidence would be useful, there is already sufficient evidence to support consideration of reduction in air pollution as a preventative measure to reduce the stroke burden globally. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Metabolic pathways for the whole community.

    PubMed

    Hanson, Niels W; Konwar, Kishori M; Hawley, Alyse K; Altman, Tomer; Karp, Peter D; Hallam, Steven J

    2014-07-22

    A convergence of high-throughput sequencing and computational power is transforming biology into information science. Despite these technological advances, converting bits and bytes of sequence information into meaningful insights remains a challenging enterprise. Biological systems operate on multiple hierarchical levels from genomes to biomes. Holistic understanding of biological systems requires agile software tools that permit comparative analyses across multiple information levels (DNA, RNA, protein, and metabolites) to identify emergent properties, diagnose system states, or predict responses to environmental change. Here we adopt the MetaPathways annotation and analysis pipeline and Pathway Tools to construct environmental pathway/genome databases (ePGDBs) that describe microbial community metabolism using MetaCyc, a highly curated database of metabolic pathways and components covering all domains of life. We evaluate Pathway Tools' performance on three datasets with different complexity and coding potential, including simulated metagenomes, a symbiotic system, and the Hawaii Ocean Time-series. We define accuracy and sensitivity relationships between read length, coverage and pathway recovery and evaluate the impact of taxonomic pruning on ePGDB construction and interpretation. Resulting ePGDBs provide interactive metabolic maps, predict emergent metabolic pathways associated with biosynthesis and energy production and differentiate between genomic potential and phenotypic expression across defined environmental gradients. This multi-tiered analysis provides the user community with specific operating guidelines, performance metrics and prediction hazards for more reliable ePGDB construction and interpretation. Moreover, it demonstrates the power of Pathway Tools in predicting metabolic interactions in natural and engineered ecosystems.

  11. A Canonical Correlation Analysis of AIDS Restriction Genes and Metabolic Pathways Identifies Purine Metabolism as a Key Cooperator.

    PubMed

    Ye, Hanhui; Yuan, Jinjin; Wang, Zhengwu; Huang, Aiqiong; Liu, Xiaolong; Han, Xiao; Chen, Yahong

    2016-01-01

    Human immunodeficiency virus causes a severe disease in humans, referred to as immune deficiency syndrome. Studies on the interaction between host genetic factors and the virus have revealed dozens of genes that impact diverse processes in the AIDS disease. To resolve more genetic factors related to AIDS, a canonical correlation analysis was used to determine the correlation between AIDS restriction and metabolic pathway gene expression. The results show that HIV-1 postentry cellular viral cofactors from AIDS restriction genes are coexpressed in human transcriptome microarray datasets. Further, the purine metabolism pathway comprises novel host factors that are coexpressed with AIDS restriction genes. Using a canonical correlation analysis for expression is a reliable approach to exploring the mechanism underlying AIDS.

  12. Core Proteomic Analysis of Unique Metabolic Pathways of Salmonella enterica for the Identification of Potential Drug Targets.

    PubMed

    Uddin, Reaz; Sufian, Muhammad

    2016-01-01

    Infections caused by Salmonella enterica, a Gram-negative facultative anaerobic bacteria belonging to the family of Enterobacteriaceae, are major threats to the health of humans and animals. The recent availability of complete genome data of pathogenic strains of the S. enterica gives new avenues for the identification of drug targets and drug candidates. We have used the genomic and metabolic pathway data to identify pathways and proteins essential to the pathogen and absent from the host. We took the whole proteome sequence data of 42 strains of S. enterica and Homo sapiens along with KEGG-annotated metabolic pathway data, clustered proteins sequences using CD-HIT, identified essential genes using DEG database and discarded S. enterica homologs of human proteins in unique metabolic pathways (UMPs) and characterized hypothetical proteins with SVM-prot and InterProScan. Through this core proteomic analysis we have identified enzymes essential to the pathogen. The identification of 73 enzymes common in 42 strains of S. enterica is the real strength of the current study. We proposed all 73 unexplored enzymes as potential drug targets against the infections caused by the S. enterica. The study is comprehensive around S. enterica and simultaneously considered every possible pathogenic strain of S. enterica. This comprehensiveness turned the current study significant since, to the best of our knowledge it is the first subtractive core proteomic analysis of the unique metabolic pathways applied to any pathogen for the identification of drug targets. We applied extensive computational methods to shortlist few potential drug targets considering the druggability criteria e.g. Non-homologous to the human host, essential to the pathogen and playing significant role in essential metabolic pathways of the pathogen (i.e. S. enterica). In the current study, the subtractive proteomics through a novel approach was applied i.e. by considering only proteins of the unique metabolic

  13. Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma.

    PubMed

    McGuire, Mary F; Sriram Iyengar, M; Mercer, David W

    2012-04-01

    Although trauma is the leading cause of death for those below 45years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. In the node/molecular analysis of the first 24h from trauma, PSA uncovered seven molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which three molecules had not been previously associated with any shock/trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships--activation, expression, inhibition, and transcription--and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction

  14. Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma

    PubMed Central

    McGuire, Mary F.; Iyengar, M. Sriram; Mercer, David W.

    2012-01-01

    Motivation Although trauma is the leading cause of death for those below 45 years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference. Results In the node/molecular analysis of the first 24 hours from trauma, PSA uncovered 7 molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which 3 molecules had not been previously associated with any shock / trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships – activation, expression, inhibition, and transcription – and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on

  15. The Peroxide Pathway

    NASA Technical Reports Server (NTRS)

    McNeal, Curtis I., Jr.; Anderson, William

    1999-01-01

    NASA's current focus on technology roadmaps as a tool for guiding investment decisions leads naturally to a discussion of NASA's roadmap for peroxide propulsion system development. NASA's new Second Generation Space Transportation System roadmap calls for an integrated Reusable Upper-Stage (RUS) engine technology demonstration in the FY03/FY04 time period. Preceding this integrated demonstration are several years of component developments and subsystem technology demonstrations. NASA and the Air Force took the first steps at developing focused upper stage technologies with the initiation of the Upper Stage Flight Experiment with Orbital Sciences in December 1997. A review of this program's peroxide propulsion development is a useful first step in establishing the peroxide propulsion pathway that could lead to a RUS demonstration in 2004.

  16. Analysis of the electromechanical characteristics of a piezoelectric multilayered structure for in-air ultrasound radiation

    NASA Astrophysics Data System (ADS)

    Shim, Hayeong; Roh, Yongrae

    2018-07-01

    Ultrasonic sensors in air are used to measure distances from obstacles in household appliances, automobiles, and other areas. Among these ultrasonic sensors in air, sensors using disk-shaped piezoelectric ceramics are composed of a multilayered structure having a vibrational plate, a piezoelectric ceramic disk, and a backing layer. In this study, we derived theoretical equations that can accurately analyze the acoustic characteristics of the piezoelectric multilayered structure, and then analyzed the performance of the ultrasonic sensor according to the geometrical change of the multilayered structure. The characteristics analyzed were the resonant frequency and the radiated sound pressure at a far field of the sensor. The validity of the theoretical analysis was verified by comparing the results with those obtained from the finite element analysis of the same structure. The exact functional forms of the resonant frequency of and the radiated sound pressure from the piezoelectric multilayered structure derived in this study can be directly utilized to maximize the performance of various ultrasonic sensors in air.

  17. Ambient air pollution and pregnancy-induced hypertensive disorders: a systematic review and meta-analysis.

    PubMed

    Pedersen, Marie; Stayner, Leslie; Slama, Rémy; Sørensen, Mette; Figueras, Francesc; Nieuwenhuijsen, Mark J; Raaschou-Nielsen, Ole; Dadvand, Payam

    2014-09-01

    Pregnancy-induced hypertensive disorders can lead to maternal and perinatal morbidity and mortality, but the cause of these conditions is not well understood. We have systematically reviewed and performed a meta-analysis of epidemiological studies investigating the association between exposure to ambient air pollution and pregnancy-induced hypertensive disorders including gestational hypertension and preeclampsia. We searched electronic databases for English language studies reporting associations between ambient air pollution and pregnancy-induced hypertensive disorders published between December 2009 and December 2013. Combined risk estimates were calculated using random-effect models for each exposure that had been examined in ≥4 studies. Heterogeneity and publication bias were evaluated. A total of 17 articles evaluating the impact of nitrogen oxides (NO2, NOX), particulate matter (PM10, PM2.5), carbon monoxide (CO), ozone (O3), proximity to major roads, and traffic density met our inclusion criteria. Most studies reported that air pollution increased risk for pregnancy-induced hypertensive disorders. There was significant heterogeneity in meta-analysis, which included 16 studies reporting on gestational hypertension and preeclampsia as separate or combined outcomes; there was less heterogeneity in findings of the 10 studies reporting solely on preeclampsia. Meta-analyses showed increased risks of hypertensive disorders in pregnancy for all pollutants except CO. Random-effect meta-analysis combined odds ratio associated with a 5-μg/m3 increase in PM2.5 was 1.57 (95% confidence interval, 1.26-1.96) for combined pregnancy-induced hypertensive disorders and 1.31 (95%confidence interval, 1.14-1.50) for preeclampsia [corrected]. Our results suggest that exposure to air pollution increases the risk of pregnancy-induced hypertensive disorders. © 2014 American Heart Association, Inc.

  18. [Time-series analysis on effect of air pollution on stroke mortality in Tianjin, China].

    PubMed

    Wang, De-zheng; Gu, Qing; Jiang, Guo-hong; Yang, De-yi; Zhang, Hui; Song, Gui-de; Zhang, Ying

    2012-12-01

    To investigate the effect of air pollution on stroke mortality in Tianjin, China, and to provide basis for stroke control and prevention. Total data of mortality surveillance were collected by Tianjin Centers for Disease Control and Prevention. Meteorological data and atmospheric pollution data were from Tianjin Meteorological Bureau and Tianjin Environmental Monitoring Center, respectively. Generalized additive Poisson regression model was used in time-series analysis on the relationship between air pollution and stroke mortality in Tianjin. Single-pollutant analysis and multi-pollutant analysis were performed after adjustment for confounding factors such as meteorological factors, long-term trend of death, "days of the week" effect and population. The crude death rates of stroke in Tianjin were from 136.67 in 2001 to 160.01/100000 in 2009, with an escalating trend (P = 0.000), while the standardized mortality ratios of stroke in Tianjin were from 138.36 to 99.14/100000, with a declining trend (P = 0.000). An increase of 10 µg/m³ in daily average concentrations of atmospheric SO₂, NO₂ and PM₁₀ led to 1.0105 (95%CI: 1.0060 ∼ 1.0153), 1.0197 (95%CI: 1.0149 ∼ 1.0246) and 1.0064 (95%CI: 1.0052 ∼ 1.0077), respectively, in relative risks of stroke mortality. SO₂ effect peaked after 1-day exposure, while NO₂ and PM₁₀ effects did within 1 day. Air pollution in Tianjin may increase the risk of stroke mortality in the population and induce acute onset of stroke. It is necessary to carry out air pollution control and allocate health resources rationally to reduce the hazard of stroke mortality.

  19. Genome Expression Pathway Analysis Tool – Analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

    PubMed Central

    Weniger, Markus; Engelmann, Julia C; Schultz, Jörg

    2007-01-01

    Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional

  20. Characterization of Changes in Gene Expression and Biochemical Pathways at Low Levels of Benzene Exposure

    PubMed Central

    Thomas, Reuben; Hubbard, Alan E.; McHale, Cliona M.; Zhang, Luoping; Rappaport, Stephen M.; Lan, Qing; Rothman, Nathaniel; Vermeulen, Roel; Guyton, Kathryn Z.; Jinot, Jennifer; Sonawane, Babasaheb R.; Smith, Martyn T.

    2014-01-01

    Benzene, a ubiquitous environmental pollutant, causes acute myeloid leukemia (AML). Recently, through transcriptome profiling of peripheral blood mononuclear cells (PBMC), we reported dose-dependent effects of benzene exposure on gene expression and biochemical pathways in 83 workers exposed across four airborne concentration ranges (from <1 ppm to >10 ppm) compared with 42 subjects with non-workplace ambient exposure levels. Here, we further characterize these dose-dependent effects with continuous benzene exposure in all 125 study subjects. We estimated air benzene exposure levels in the 42 environmentally-exposed subjects from their unmetabolized urinary benzene levels. We used a novel non-parametric, data-adaptive model selection method to estimate the change with dose in the expression of each gene. We describe non-parametric approaches to model pathway responses and used these to estimate the dose responses of the AML pathway and 4 other pathways of interest. The response patterns of majority of genes as captured by mean estimates of the first and second principal components of the dose-response for the five pathways and the profiles of 6 AML pathway response-representative genes (identified by clustering) exhibited similar apparent supra-linear responses. Responses at or below 0.1 ppm benzene were observed for altered expression of AML pathway genes and CYP2E1. Together, these data show that benzene alters disease-relevant pathways and genes in a dose-dependent manner, with effects apparent at doses as low as 100 ppb in air. Studies with extensive exposure assessment of subjects exposed in the low-dose range between 10 ppb and 1 ppm are needed to confirm these findings. PMID:24786086

  1. In response to 'Can sugars be produced from fatty acids? A test case for pathway analysis tools'.

    PubMed

    Faust, Karoline; Croes, Didier; van Helden, Jacques

    2009-12-01

    In their article entitled 'Can sugars be produced from fatty acids? A test case for pathway analysis tools' de Figueiredo and co-authors assess the performance of three pathway prediction tools (METATOOL, PathFinding and Pathway Hunter Tool) using the synthesis of glucose-6-phosphate (G6P) from acetyl-CoA in humans as a test case. We think that this article is biased for three reasons: (i) the metabolic networks used as input for the respective tools were of very different sizes; (ii) the 'assessment' is restricted to two study cases; (iii) developers are inherently more skilled to use their own tools than those developed by other people. We extended the analyses led by de Figueiredo and clearly show that the apparent superior performance of their tool (METATOOL) is partly due to the differences in input network sizes. We also see a conceptual problem in the comparison of tools that serve different purposes. In our opinion, metabolic path finding and elementary mode analysis are answering different biological questions, and should be considered as complementary rather than competitive approaches. Supplementary data are available at Bioinformatics online.

  2. Understanding Potential Air Emissions from a Cellulosic Biorefinery Producing Renewable Diesel Blendstock.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhang, Yimin; Heath, Garvin A.; Renzaglia, Jason

    2015-06-22

    The Energy Independence and Security Act of 2007, through the Renewable Fuel Standard (RFS), mandates increased use of biofuels, including cellulosic biofuels. The RFS is expected to spur the development of advanced biofuel technologies (e.g., new and innovative biofuel conversion pathways) as well as the construction of biorefineries (refineries that produce biofuels) using these technologies. To develop sustainable cellulosic biofuels, one of the goals of the Bioenergy Technologies Office (BETO) at the Department of Energy is to minimize air pollutants from the entire biofuel supply chain, as stated in their 2014 Multi-Year Program Plan (2014). Although biofuels in general havemore » been found to have lower life cycle greenhouse gas (GHG) emissions compared to petroleum fuels on an energy basis, biomass feedstock production, harvesting, transportation, processing and conversion are expected to emit a wide range of other air pollutants (e.g., criteria air pollutants, hazardous air pollutants), which could affect the environmental benefits of biofuels when displacing petroleum fuels. While it is important for policy makers, air quality planners and regulators, biofuel developers, and investors to understand the potential implications on air quality from a growing biofuel industry, there is a general lack of information and knowledge about the type, fate and magnitude of potential air pollutant emissions from the production of cellulosic biofuels due to the nascent stage of this emerging industry. This analysis assesses potential air pollutant emissions from a hypothetical biorefinery, selected by BETO for further research and development, which uses a biological conversion process of sugars to hydrocarbons to produce infrastructural-compatible renewable diesel blendstock from cellulosic biomass.« less

  3. iTRAQ proteomics analysis reveals that PI3K is highly associated with bupivacaine-induced neurotoxicity pathways.

    PubMed

    Zhao, Wei; Liu, Zhongjie; Yu, Xujiao; Lai, Luying; Li, Haobo; Liu, Zipeng; Li, Le; Jiang, Shan; Xia, Zhengyuan; Xu, Shi-yuan

    2016-02-01

    Bupivacaine, a commonly used local anesthetic, has potential neurotoxicity through diverse signaling pathways. However, the key mechanism of bupivacaine-induced neurotoxicity remains unclear. Cultured human SH-SY5Y neuroblastoma cells were treated (bupivacaine) or untreated (control) with bupivacaine for 24 h. Compared to the control group, bupivacaine significantly increased cyto-inhibition, cellular reactive oxygen species, DNA damage, mitochondrial injury, apoptosis (increased TUNEL-positive cells, cleaved caspase 3, and Bcl-2/Bax), and activated autophagy (enhanced LC3II/LC3I ratio). To explore changes in protein expression and intercommunication among the pathways involved in bupivacaine-induced neurotoxicity, an 8-plex iTRAQ proteomic technique and bioinformatics analysis were performed. Compared to the control group, 241 differentially expressed proteins were identified, of which, 145 were up-regulated and 96 were down-regulated. Bioinformatics analysis of the cross-talk between the significant proteins with altered expression in bupivacaine-induced neurotoxicity indicated that phosphatidyl-3-kinase (PI3K) was the most frequently targeted protein in each of the interactions. We further confirmed these results by determining the downstream targets of the identified signaling pathways (PI3K, Akt, FoxO1, Erk, and JNK). In conclusion, our study demonstrated that PI3K may play a central role in contacting and regulating the signaling pathways that contribute to bupivacaine-induced neurotoxicity. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Estimating environmental co-benefits of U.S. GHG reduction pathways using the GCAM-USA Integrated Assessment Model (A&WMA Presentation)

    EPA Science Inventory

    A variety of technological pathways lead to reduced greenhouse gas (GHG) emissions. However, different pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. In this study we use the Global Change ...

  5. Integrated lipidomics and transcriptomic analysis of peripheral blood reveals significantly enriched pathways in type 2 diabetes mellitus.

    PubMed

    Zhao, Chen; Mao, Jinghe; Ai, Junmei; Shenwu, Ming; Shi, Tieliu; Zhang, Daqing; Wang, Xiaonan; Wang, Yunliang; Deng, Youping

    2013-01-01

    Insulin resistance is a key element in the pathogenesis of type 2 diabetes mellitus. Plasma free fatty acids were assumed to mediate the insulin resistance, while the relationship between lipid and glucose disposal remains to be demonstrated across liver, skeletal muscle and blood. We profiled both lipidomics and gene expression of 144 total peripheral blood samples, 84 from patients with T2D and 60 from healthy controls. Then, factor and partial least squares models were used to perform a combined analysis of lipidomics and gene expression profiles to uncover the bioprocesses that are associated with lipidomic profiles in type 2 diabetes. According to factor analysis of the lipidomic profile, several species of lipids were found to be correlated with different phenotypes, including diabetes-related C23:2CE, C23:3CE, C23:4CE, ePE36:4, ePE36:5, ePE36:6; race-related (African-American) PI36:1; and sex-related PE34:1 and LPC18:2. The major variance of gene expression profile was not caused by known factors and no significant difference can be directly derived from differential gene expression profile. However, the combination of lipidomic and gene expression analyses allows us to reveal the correlation between the altered lipid profile with significantly enriched pathways, such as one carbon pool by folate, arachidonic acid metabolism, insulin signaling pathway, amino sugar and nucleotide sugar metabolism, propanoate metabolism, and starch and sucrose metabolism. The genes in these pathways showed a good capability to classify diabetes samples. Combined analysis of gene expression and lipidomic profiling reveals type 2 diabetes-associated lipid species and enriched biological pathways in peripheral blood, while gene expression profile does not show direct correlation. Our findings provide a new clue to better understand the mechanism of disordered lipid metabolism in association with type 2 diabetes.

  6. Potential Uses of Occupational Analysis Data By Air Force Management Engineering Teams.

    ERIC Educational Resources Information Center

    McFarland, Barry P.

    Both the occupational analysis program and the management engineering program are primarily concerned with task level descriptions of time spent to perform tasks required in the Air Force, the first being personnel specialty code oriented and the second being work center oriented. However two separate and independent techniques have been developed…

  7. Creep-rupture and fractographic analysis of candidate Stirling engine superalloys tested in air

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bhattachryya, S.

    The creep-rupture behavior of six candidate Stirling engine iron-base superalloys was determined in air. The alloys tested included four wrought alloys (A-286, INCOLOY Alloy 800H, N-155, and 19-9DL) and two cast alloys (CRM-6D and XF-818). The wrought alloys were evaluated in the form of sheet; the cast alloy specimens were investment cast to shape. The creep-rupture specimens were tested in air for up to 3000 hours over the temperature range 650/sup 0/ to 925/sup 0/C. Microstructural and fractographic aspects of the ruptured specimens are discussed with a few correlational graphical analyses included for XF-818 and 19-9DL. Tests are continuing inmore » 15 MPa hydrogen, and later these data will be correlated with air data and microstructural analysis of the specimens conducted.« less

  8. Gene-Based Mapping and Pathway Analysis of Metabolic Traits in Dairy Cows

    PubMed Central

    Ha, Ngoc-Thuy; Gross, Josef Johann; van Dorland, Annette; Tetens, Jens; Thaller, Georg; Schlather, Martin; Bruckmaier, Rupert; Simianer, Henner

    2015-01-01

    The metabolic adaptation of dairy cows during the transition period has been studied intensively in the last decades. However, until now, only few studies have paid attention to the genetic aspects of this process. Here, we present the results of a gene-based mapping and pathway analysis with the measurements of three key metabolites, (1) non-esterified fatty acids (NEFA), (2) beta-hydroxybutyrate (BHBA) and (3) glucose, characterizing the metabolic adaptability of dairy cows before and after calving. In contrast to the conventional single-marker approach, we identify 99 significant and biologically sensible genes associated with at least one of the considered phenotypes and thus giving evidence for a genetic basis of the metabolic adaptability. Moreover, our results strongly suggest three pathways involved in the metabolism of steroids and lipids are potential candidates for the adaptive regulation of dairy cows in their early lactation. From our perspective, a closer investigation of our findings will lead to a step forward in understanding the variability in the metabolic adaptability of dairy cows in their early lactation. PMID:25789767

  9. Variant allele frequency enrichment analysis in vitro reveals sonic hedgehog pathway to impede sustained temozolomide response in GBM.

    PubMed

    Biswas, Nidhan K; Chandra, Vikas; Sarkar-Roy, Neeta; Das, Tapojyoti; Bhattacharya, Rabindra N; Tripathy, Laxmi N; Basu, Sunandan K; Kumar, Shantanu; Das, Subrata; Chatterjee, Ankita; Mukherjee, Ankur; Basu, Pryiadarshi; Maitra, Arindam; Chattopadhyay, Ansuman; Basu, Analabha; Dhara, Surajit

    2015-01-21

    Neoplastic cells of Glioblastoma multiforme (GBM) may or may not show sustained response to temozolomide (TMZ) chemotherapy. We hypothesize that TMZ chemotherapy response in GBM is predetermined in its neoplastic clones via a specific set of mutations that alter relevant pathways. We describe exome-wide enrichment of variant allele frequencies (VAFs) in neurospheres displaying contrasting phenotypes of sustained versus reversible TMZ-responses in vitro. Enrichment of VAFs was found on genes ST5, RP6KA1 and PRKDC in cells showing sustained TMZ-effect whereas on genes FREM2, AASDH and STK36, in cells showing reversible TMZ-effect. Ingenuity pathway analysis (IPA) revealed that these genes alter cell-cycle, G2/M-checkpoint-regulation and NHEJ pathways in sustained TMZ-effect cells whereas the lysine-II&V/phenylalanine degradation and sonic hedgehog (Hh) pathways in reversible TMZ-effect cells. Next, we validated the likely involvement of the Hh-pathway in TMZ-response on additional GBM neurospheres as well as on GBM patients, by extracting RNA-sequencing-based gene expression data from the TCGA-GBM database. Finally, we demonstrated TMZ-sensitization of a TMZ non-responder neurosphere in vitro by treating them with the FDA-approved pharmacological Hh-pathway inhibitor vismodegib. Altogether, our results indicate that the Hh-pathway impedes sustained TMZ-response in GBM and could be a potential therapeutic target to enhance TMZ-response in this malignancy.

  10. A multi-model assessment of the co-benefits of climate mitigation for global air quality

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rao, Shilpa; Klimont, Zbigniew; Leitao, Joana

    The recent International Panel on Climate change (IPCC) report identifies significant co-benefits from climate policies on near-term ambient air pollution and related human health outcomes [1]. This is increasingly relevant for policy making as the health impacts of air pollution are a major global concern- the Global Burden of Disease (GBD) study identifies outdoor air pollution as the sixth major cause of death globally [2]. Integrated assessment models (IAMs) are an effective tool to evaluate future air pollution outcomes across a wide range of assumptions on socio-economic development and policy regimes. The Representative Concentration Pathways (RCPs) [3] were the firstmore » set of long-term global scenarios developed across multiple integrated assessment models that provided detailed estimates of a number of air pollutants until 2100. However these scenarios were primarily designed to cover a defined range of radiative forcing outcomes and thus did not specifically focus on the interactions of long-term climate goals on near-term air pollution impacts. More recently, [4] used the RCP4.5 scenario to evaluate the co-benefits of global GHG reductions on air quality and human health in 2030. [5-7] have further examined the interactions of more diverse pollution control regimes with climate policies. This paper extends the listed studies in a number of ways. Firstly it uses multiple IAMs to look into the co-benefits of a global climate policy for ambient air pollution under harmonized assumptions on near-term air pollution control. Multi-model frameworks have been extensively used in the analysis of climate change mitigation pathways, and the structural uncertainties regarding the underlying mechanisms (see for example [8-10]. This is to our knowledge the first time that a multi-model evaluation has been specifically designed and applied to analyze the co-benefits of climate change policy on ambient air quality, thus enabling a better understanding of at a

  11. Analysis of Ozone Transportation in Tlaxcala-Puebla Mexico Air Basin

    NASA Astrophysics Data System (ADS)

    Barrera-Huertas, H.; Torres, R.; Ruiz-Suárez, L. G.; Garcia, J.; Gutierrez, W.; Torres, A.

    2014-12-01

    Preliminary results of an investigation conducted between March and April 2012 on the influence of air pollutants transport in the Puebla-Tlaxcala Valley airshed are presented. The campaign included ozone (O3), nitrogen dioxide (NO2) and meteorological variables monitoring at surface in Huaquechula, Chipilo and Amozoc rural sites, and measurements of O3 vertical profile O3 and meteorology in Chipilo. The synoptic conditions during the campaign showed dominance of "Norte" conditions favoring air masses circulation from Pacific Ocean crossing southern Mexican Plateau to the Gulf of Mexico that influences the establishment of evening southeasterly winds in the Puebla-Tlaxcala Valley. Wind roses and contaminants analysis in surface for O3 during entire campaign indicates that before noon the movement of air masses was dominated by runoff of Malinche toward the southeast and south of the valley; and in the afternoon a regional pattern of winds from southwest Valley prevails coming from Cuautla Valley and south of Morelos State. The analysis of three representative days of atmospheric circulation in the valley as well as anthropogenic diurnal activity, a rate of morning increase in O3 concentrations similar at all three sites was observed, even in the absence of precursors such as NO2 during some weekends. By analyzing and engage data from O3 vertical profile and surface meteorology data, we could infer that there are minimal ozone contributions from local sources, but important from regional origin, and even O3 entrainment in height brought to the surface when mixing layer is growing. The back trajectory analysis from Chipilo at noon indicates that could be additional contributions of O3 from both Cuautla Valley and other areas of pollutants emission such as Tula, (in the north of Mexico City), and that weekend effect with the occurrence of high O3 levels observed there extends to this region. Although interbasin exchange of pollutants between the Puebla-Tlaxcala Valley

  12. Principles for circadian orchestration of metabolic pathways.

    PubMed

    Thurley, Kevin; Herbst, Christopher; Wesener, Felix; Koller, Barbara; Wallach, Thomas; Maier, Bert; Kramer, Achim; Westermark, Pål O

    2017-02-14

    Circadian rhythms govern multiple aspects of animal metabolism. Transcriptome-, proteome- and metabolome-wide measurements have revealed widespread circadian rhythms in metabolism governed by a cellular genetic oscillator, the circadian core clock. However, it remains unclear if and under which conditions transcriptional rhythms cause rhythms in particular metabolites and metabolic fluxes. Here, we analyzed the circadian orchestration of metabolic pathways by direct measurement of enzyme activities, analysis of transcriptome data, and developing a theoretical method called circadian response analysis. Contrary to a common assumption, we found that pronounced rhythms in metabolic pathways are often favored by separation rather than alignment in the times of peak activity of key enzymes. This property holds true for a set of metabolic pathway motifs (e.g., linear chains and branching points) and also under the conditions of fast kinetics typical for metabolic reactions. By circadian response analysis of pathway motifs, we determined exact timing separation constraints on rhythmic enzyme activities that allow for substantial rhythms in pathway flux and metabolite concentrations. Direct measurements of circadian enzyme activities in mouse skeletal muscle confirmed that such timing separation occurs in vivo.

  13. Principles for circadian orchestration of metabolic pathways

    PubMed Central

    Thurley, Kevin; Herbst, Christopher; Wesener, Felix; Koller, Barbara; Wallach, Thomas; Maier, Bert; Kramer, Achim

    2017-01-01

    Circadian rhythms govern multiple aspects of animal metabolism. Transcriptome-, proteome- and metabolome-wide measurements have revealed widespread circadian rhythms in metabolism governed by a cellular genetic oscillator, the circadian core clock. However, it remains unclear if and under which conditions transcriptional rhythms cause rhythms in particular metabolites and metabolic fluxes. Here, we analyzed the circadian orchestration of metabolic pathways by direct measurement of enzyme activities, analysis of transcriptome data, and developing a theoretical method called circadian response analysis. Contrary to a common assumption, we found that pronounced rhythms in metabolic pathways are often favored by separation rather than alignment in the times of peak activity of key enzymes. This property holds true for a set of metabolic pathway motifs (e.g., linear chains and branching points) and also under the conditions of fast kinetics typical for metabolic reactions. By circadian response analysis of pathway motifs, we determined exact timing separation constraints on rhythmic enzyme activities that allow for substantial rhythms in pathway flux and metabolite concentrations. Direct measurements of circadian enzyme activities in mouse skeletal muscle confirmed that such timing separation occurs in vivo. PMID:28159888

  14. Transcriptomic analysis in the developing zebrafish embryo after compound exposure: Individual gene expression and pathway regulation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hermsen, Sanne A.B., E-mail: Sanne.Hermsen@rivm.nl; Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht; Institute for Risk Assessment Sciences

    2013-10-01

    The zebrafish embryotoxicity test is a promising alternative assay for developmental toxicity. Classically, morphological assessment of the embryos is applied to evaluate the effects of compound exposure. However, by applying differential gene expression analysis the sensitivity and predictability of the test may be increased. For defining gene expression signatures of developmental toxicity, we explored the possibility of using gene expression signatures of compound exposures based on commonly expressed individual genes as well as based on regulated gene pathways. Four developmental toxic compounds were tested in concentration-response design, caffeine, carbamazepine, retinoic acid and valproic acid, and two non-embryotoxic compounds, D-mannitol andmore » saccharin, were included. With transcriptomic analyses we were able to identify commonly expressed genes, which were mostly development related, after exposure to the embryotoxicants. We also identified gene pathways regulated by the embryotoxicants, suggestive of their modes of action. Furthermore, whereas pathways may be regulated by all compounds, individual gene expression within these pathways can differ for each compound. Overall, the present study suggests that the use of individual gene expression signatures as well as pathway regulation may be useful starting points for defining gene biomarkers for predicting embryotoxicity. - Highlights: • The zebrafish embryotoxicity test in combination with transcriptomics was used. • We explored two approaches of defining gene biomarkers for developmental toxicity. • Four compounds in concentration-response design were tested. • We identified commonly expressed individual genes as well as regulated gene pathways. • Both approaches seem suitable starting points for defining gene biomarkers.« less

  15. Expression profiling and pathway analysis of Krüppel-like factor 4 in mouse embryonic fibroblasts

    PubMed Central

    Hagos, Engda G; Ghaleb, Amr M; Kumar, Amrita; Neish, Andrew S; Yang, Vincent W

    2011-01-01

    Background: Krüppel-like factor 4 (KLF4) is a zinc-finger transcription factor with diverse regulatory functions in proliferation, differentiation, and development. KLF4 also plays a role in inflammation, tumorigenesis, and reprogramming of somatic cells to induced pluripotent stem (iPS) cells. To gain insight into the mechanisms by which KLF4 regulates these processes, we conducted DNA microarray analyses to identify differentially expressed genes in mouse embryonic fibroblasts (MEFs) wild type and null for Klf4. Methods: Expression profiles of fibroblasts isolated from mouse embryos wild type or null for the Klf4 alleles were examined by DNA microarrays. Differentially expressed genes were subjected to the Database for Annotation, Visualization and Integrated Discovery (DAVID). The microarray data were also interrogated with the Ingenuity Pathway Analysis (IPA) and Gene Set Enrichment Analysis (GSEA) for pathway identification. Results obtained from the microarray analysis were confirmed by Western blotting for select genes with biological relevance to determine the correlation between mRNA and protein levels. Results: One hundred and sixty three up-regulated and 88 down-regulated genes were identified that demonstrated a fold-change of at least 1.5 and a P-value < 0.05 in Klf4-null MEFs compared to wild type MEFs. Many of the up-regulated genes in Klf4-null MEFs encode proto-oncogenes, growth factors, extracellular matrix, and cell cycle activators. In contrast, genes encoding tumor suppressors and those involved in JAK-STAT signaling pathways are down-regulated in Klf4-null MEFs. IPA and GSEA also identified various pathways that are regulated by KLF4. Lastly, Western blotting of select target genes confirmed the changes revealed by microarray data. Conclusions: These data are not only consistent with previous functional studies of KLF4's role in tumor suppression and somatic cell reprogramming, but also revealed novel target genes that mediate KLF4's

  16. Statistical Analysis of the Impacts of Regional Transportation on the Air Quality in Beijing

    NASA Astrophysics Data System (ADS)

    Huang, Zhongwen; Zhang, Huiling; Tong, Lei; Xiao, Hang

    2016-04-01

    From October to December 2015, Beijing-Tianjin-Hebei (BTH) region had experienced several severe haze events. In order to assess the effects of the regional transportation on the air quality in Beijing, the air monitoring data (PM2.5, SO2, NO2 and CO) from that period published by Chinese National Environmental Monitoring Center (CNEMC) was collected and analyzed with various statistical models. The cities within BTH area were clustered into three groups according to the geographical conditions, while the air pollutant concentrations of cities within a group sharing similar variation trends. The Granger causality test results indicate that significant causal relationships exist between the air pollutant data of Beijing and its surrounding cities (Baoding, Chengde, Tianjin and Zhangjiakou) for the reference period. Then, linear regression models were constructed to capture the interdependency among the multiple time series. It shows that the observed air pollutant concentrations in Beijing were well consistent with the model-fitted results. More importantly, further analysis suggests that the air pollutants in Beijing were strongly affected by regional transportation, as the local sources only contributed 17.88%, 27.12%, 14.63% and 31.36% of PM2.5, SO2, NO2 and CO concentrations, respectively. And the major foreign source for Beijing was from Southwest (Baoding) direction, account for more than 42% of all these air pollutants. Thus, by combining various statistical models, it may not only be able to quickly predict the air qualities of any cities on a regional scale, but also to evaluate the local and regional source contributions for a particular city. Key words: regional transportation, air pollution, Granger causality test, statistical models

  17. A Growing Role for Gender Analysis in Air Pollution Epidemiology

    PubMed Central

    Clougherty, Jane E.

    2010-01-01

    Objective Epidemiologic studies of air pollution effects on respiratory health report significant modification by sex, although results are not uniform. Importantly, it remains unclear whether modifications are attributable to socially derived gendered exposures, to sex-linked physiological differences, or to some interplay thereof. Gender analysis, which aims to disaggregate social from biological differences between males and females, may help to elucidate these possible sources of effect modification. Data sources and data extraction A PubMed literature search was performed in July 2009, using the terms “respiratory” and any of “sex” or “gender” or “men and women” or “boys and girls” and either “PM2.5” (particulate matter ≥ 2.5 μm in aerodynamic diameter) or “NO2” (nitrogen dioxide). I reviewed the identified studies, and others cited therein, to summarize current evidence of effect modification, with attention to authors’ interpretation of observed differences. Owing to broad differences in exposure mixes, outcomes, and analytic techniques, with few studies examining any given combination thereof, meta-analysis was not deemed appropriate at this time. Data synthesis More studies of adults report stronger effects among women, particularly for older persons or where using residential exposure assessment. Studies of children suggest stronger effects among boys in early life and among girls in later childhood. Conclusions The qualitative review describes possible sources of difference in air pollution response between women and men, which may vary by life stage, coexposures, hormonal status, or other factors. The sources of observed effect modifications remain unclear, although gender analytic approaches may help to disentangle gender and sex differences in pollution response. A framework for incorporating gender analysis into environmental epidemiology is offered, along with several potentially useful methods from gender analysis

  18. Final Report: Hydrogen Production Pathways Cost Analysis (2013 – 2016)

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    James, Brian David; DeSantis, Daniel Allan; Saur, Genevieve

    This report summarizes work conducted under a three year Department of Energy (DOE) funded project to Strategic Analysis, Inc. (SA) to analyze multiple hydrogen (H 2) production technologies and project their corresponding levelized production cost of H 2. The analysis was conducted using the H2A Hydrogen Analysis Tool developed by the DOE and National Renewable Energy Laboratory (NREL). The project was led by SA but conducted in close collaboration with the NREL and Argonne National Laboratory (ANL). In-depth techno-economic analysis (TEA) of five different H 2 production methods was conducted. These TEAs developed projections for capital costs, fuel/feedstock usage, energymore » usage, indirect capital costs, land usage, labor requirements, and other parameters, for each H 2 production pathway, and use the resulting cost and system parameters as inputs into the H2A discounted cash flow model to project the production cost of H 2 ($/kgH 2). Five technologies were analyzed as part of the project and are summarized in this report: Proton Exchange Membrane technology (PEM), High temperature solid oxide electrolysis cell technology (SOEC), Dark fermentation of biomass for H 2 production, H 2 production via Monolithic Piston-Type Reactors with rapid swing reforming and regeneration reactions, and Reformer-Electrolyzer-Purifier (REP) technology developed by Fuel Cell Energy, Inc. (FCE).« less

  19. An experimental and theoretical analysis of a foil-air bearing rotor system

    NASA Astrophysics Data System (ADS)

    Bonello, P.; Hassan, M. F. Bin

    2018-01-01

    Although there is considerable research on the experimental testing of foil-air bearing (FAB) rotor systems, only a small fraction has been correlated with simulations from a full nonlinear model that links the rotor, air film and foil domains, due to modelling complexity and computational burden. An approach for the simultaneous solution of the three domains as a coupled dynamical system, introduced by the first author and adopted by independent researchers, has recently demonstrated its capability to address this problem. This paper uses this approach, with further developments, in an experimental and theoretical study of a FAB-rotor test rig. The test rig is described in detail, including issues with its commissioning. The theoretical analysis uses a recently introduced modal-based bump foil model that accounts for interaction between the bumps and their inertia. The imposition of pressure constraints on the air film is found to delay the predicted onset of instability speed. The results lend experimental validation to a recent theoretically-based claim that the Gümbel condition may not be appropriate for a practical single-pad FAB. The satisfactory prediction of the salient features of the measured nonlinear behavior shows that the air film is indeed highly influential on the response, in contrast to an earlier finding.

  20. NO2 inhalation causes tauopathy by disturbing the insulin signaling pathway.

    PubMed

    Yan, Wei; Ku, Tingting; Yue, Huifeng; Li, Guangke; Sang, Nan

    2016-12-01

    Air pollution has been evidenced as a risk factor for neurodegenerative tauopathies. NO 2 , a primary component of air pollution, is negatively linked to neurodegenerative disorders, but its independent and direct association with tau lesion remains to be elucidated. Considering the fact that the insulin signaling pathway can be targeted by air pollutants and regulate tau function, this study focused on the role of insulin signaling in this NO 2 -induced tauopathy. Using a dynamic inhalation treatment, we demonstrated that exposure to NO 2 induced a disruption of insulin signaling in skeletal muscle, liver, and brain, with associated p38 MAPK and/or JNK activation. We also found that in parallel with these kinase signaling cascades, the compensatory hyperinsulinemia triggered by whole-body insulin resistance (IR) further attenuated the IRS-1/AKT/GSK-3β signaling pathway in the central nervous system, which consequently increased the phosphorylation of tau and reduced the expression of synaptic proteins that contributed to the development of the tau pathology. These findings provide new insight into the possible mechanisms involved in the etiopathogenesis of NO 2 -induced tauopathy, suggesting that the targeting of insulin signaling may be a promising therapeutic strategy to prevent this disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Design and Analysis of a Two-Stage Adsorption Air Chiller

    NASA Astrophysics Data System (ADS)

    Benrajesh, P.; Rajan, A. John

    2017-05-01

    The objective of this article is to design and build a bio-friendly air-conditioner, by using adsorption method in the presence of 15% of calcium carbide in water. Aluminum sheet metals are used to form three identical tunnels, to pass the air for processing. Exhaust heat generated from the dairy sterilizing unit process is reutilized, for cooling the environment through this equipment. This equipment is designed, and the analysis is carried out to quantify the COP, SCP, and cooling power. Heat exchangers are designed; its Performance Parameters are quantified and correlated with the conventional designs. It is observed that the new adsorption chiller can produce the coefficient of performance of chiller as 1.068; the Specific cooling power of 10.66 (W/Kg); and the Cooling power of 4.2 KW. This equipment needs 0 to 15 minutes to reach the desired cool breeze (24°c) from the existing room temperature (29°c).

  2. Adherence to an Accelerated Diagnostic Protocol for Chest Pain: Secondary Analysis of the HEART Pathway Randomized Trial

    PubMed Central

    Mahler, Simon A.; Riley, Robert F.; Russell, Gregory B.; Hiestand, Brian C.; Hoekstra, James W.; Lefebvre, Cedric W.; Nicks, Bret A.; Cline, David M.; Askew, Kim L.; Bringolf, John; Elliott, Stephanie B.; Herrington, David M.; Burke, Gregory L.; Miller, Chadwick D.

    2015-01-01

    Objectives Accelerated diagnostic protocols (ADP), such as the HEART Pathway, are gaining popularity in emergency departments (EDs) as tools used to risk-stratify patients with acute chest pain. However, provider non-adherence may threaten the safety and effectiveness of ADPs. The objective of this study was to determine the frequency and impact of ADP non-adherence. Methods A secondary analysis of participants enrolled in the HEART Pathway RCT was conducted. This trial enrolled 282 adult ED patients with symptoms concerning for acute coronary syndrome without ST-elevation on electrocardiogram. Patients randomized to the HEART Pathway (N = 141) were included in this analysis. Outcomes included index visit disposition, non-adherence, and major adverse cardiac events (MACE) at 30 days. MACE was defined as death, myocardial infarction, or revascularization. Non-adherence was defined as: 1) under-testing: discharging a high-risk patient from the ED without objective testing (stress testing or coronary angiography); or 2) over-testing: admitting or obtaining objective testing on a low-risk patient. Results Non-adherence to the HEART Pathway occurred in 28 out of 141 patients (20%, 95% CI = 14% to 27%). Over-testing occurred in 19 of 141 patients (13.5%, 95% CI = 8% to 19%) and under-testing in 9 of 141 patients (6%, 95% CI = 3% to 12%). None of these 28 patients suffered MACE. The net effect of non-adherence was ten additional admissions among patients identified as low-risk and appropriate for early discharge (absolute decrease in discharge rate of 7%, 95% CI = 3% to 13%). Conclusions Real-time use of the HEART Pathway resulted in a non-adherence rate of 20%, mostly due to over-testing. None of these patients had MACE within 30 days. Non-adherence decreased the discharge rate, attenuating the HEART Pathway’s impact on health care use. PMID:26720295

  3. Integrated pathway analysis of nasopharyngeal carcinoma implicates the axonemal dynein complex in the Malaysian cohort.

    PubMed

    Chin, Yoon-Ming; Tan, Lu Ping; Abdul Aziz, Norazlin; Mushiroda, Taisei; Kubo, Michiaki; Mohd Kornain, Noor Kaslina; Tan, Geok Wee; Khoo, Alan Soo-Beng; Krishnan, Gopala; Pua, Kin-Choo; Yap, Yoke-Yeow; Teo, Soo-Hwang; Lim, Paul Vey-Hong; Nakamura, Yusuke; Lum, Chee Lun; Ng, Ching-Ching

    2016-10-15

    Nasopharyngeal carcinoma (NPC) is an epithelial squamous cell carcinoma on the mucosal lining of the nasopharynx. The etiology of NPC remains elusive despite many reported studies. Most studies employ a single platform approach, neglecting the cumulative influence of both the genome and transcriptome toward NPC development. We aim to employ an integrated pathway approach to identify dysregulated pathways linked to NPC. Our approach combines imputation NPC GWAS data from a Malaysian cohort as well as published expression data GSE12452 from both NPC and non-NPC nasopharynx tissues. Pathway association for GWAS data was performed using MAGENTA while for expression data, GSA-SNP was used with gene p values derived from differential expression values from GEO2R. Our study identified NPC association in the gene ontology (GO) axonemal dynein complex pathway (pGWAS-GSEA  = 1.98 × 10(-2) ; pExpr-GSEA  = 1.27 × 10(-24) ; pBonf-Combined  = 4.15 × 10(-21) ). This association was replicated in a separate cohort using gene expression data from NPC and non-NPC nasopharynx tissues (pAmpliSeq-GSEA  = 6.56 × 10(-4) ). Loss of function in the axonemal dynein complex causes impaired cilia function, leading to poor mucociliary clearance and subsequently upper or lower respiratory tract infection, the former of which includes the nasopharynx. Our approach illustrates the potential use of integrated pathway analysis in detecting gene sets involved in the development of NPC in the Malaysian cohort. © 2016 UICC.

  4. Analysis of EPA and DOE WIPP Air Sampling Data

    EPA Pesticide Factsheets

    During the April 2014 EPA visit to WIPP, EPA co-located four ambient air samplers with existing Department of Energy (DOE) ambient air samplers to independently corroborate DOE's reported air sampling results.

  5. Integrative analysis of RUNX1 downstream pathways and target genes

    PubMed Central

    Michaud, Joëlle; Simpson, Ken M; Escher, Robert; Buchet-Poyau, Karine; Beissbarth, Tim; Carmichael, Catherine; Ritchie, Matthew E; Schütz, Frédéric; Cannon, Ping; Liu, Marjorie; Shen, Xiaofeng; Ito, Yoshiaki; Raskind, Wendy H; Horwitz, Marshall S; Osato, Motomi; Turner, David R; Speed, Terence P; Kavallaris, Maria; Smyth, Gordon K; Scott, Hamish S

    2008-01-01

    Background The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. Results Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBFβ, and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBFβ. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. Conclusion This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both

  6. Technology Candidates for Air-to-Air and Air-to-Ground Data Exchange

    NASA Technical Reports Server (NTRS)

    Haynes, Brian D.

    2015-01-01

    Technology Candidates for Air-to-Air and Air-to-Ground Data Exchange is a two-year research effort to visualize the U. S. aviation industry at a point 50 years in the future, and to define potential communication solutions to meet those future data exchange needs. The research team, led by XCELAR, was tasked with identifying future National Airspace System (NAS) scenarios, determining requirements and functions (including gaps), investigating technical and business issues for air, ground, & air-to-ground interactions, and reporting on the results. The project was conducted under technical direction from NASA and in collaboration with XCELAR's partner, National Institute of Aerospace, and NASA technical representatives. Parallel efforts were initiated to define the information exchange functional needs of the future NAS, and specific communication link technologies to potentially serve those needs. Those efforts converged with the mapping of each identified future NAS function to potential enabling communication solutions; those solutions were then compared with, and ranked relative to, each other on a technical basis in a structured analysis process. The technical solutions emerging from that process were then assessed from a business case perspective to determine their viability from a real-world adoption and deployment standpoint. The results of that analysis produced a proposed set of future solutions and most promising candidate technologies. Gap analyses were conducted at two points in the process, the first examining technical factors, and the second as part of the business case analysis. In each case, no gaps or unmet needs were identified in applying the solutions evaluated to the requirements identified. The future communication solutions identified in the research comprise both specific link technologies and two enabling technologies that apply to most or all specific links. As a result, the research resulted in a new analysis approach, viewing the

  7. The Role of AIRE in the Immunity Against Candida Albicans in a Model of Human Macrophages.

    PubMed

    de Albuquerque, Jose Antonio Tavares; Banerjee, Pinaki Prosad; Castoldi, Angela; Ma, Royce; Zurro, Nuria Bengala; Ynoue, Leandro Hideki; Arslanian, Christina; Barbosa-Carvalho, Marina Uchoa Wall; Correia-Deur, Joya Emilie de Menezes; Weiler, Fernanda Guimarães; Dias-da-Silva, Magnus Regios; Lazaretti-Castro, Marise; Pedroza, Luis Alberto; Câmara, Niels Olsen Saraiva; Mace, Emily; Orange, Jordan Scott; Condino-Neto, Antonio

    2018-01-01

    Autoimmune-polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) is a primary immunodeficiency caused by mutations in the autoimmune regulator gene ( AIRE ). Patients with AIRE mutations are susceptible to Candida albicans infection and present with autoimmune disorders. We previously demonstrated that cytoplasmic AIRE regulates the Syk-dependent Dectin-1 pathway. In this study, we further evaluated direct contact with fungal elements, synapse formation, and the response of macrophage-like THP-1 cells to C. albicans hyphae to determine the role of AIRE upon Dectin receptors function and signaling. We examined the fungal synapse (FS) formation in wild-type and AIRE-knockdown THP-1 cells differentiated to macrophages, as well as monocyte-derived macrophages from APECED patients. We evaluated Dectin-2 receptor signaling, phagocytosis, and cytokine secretion upon hyphal stimulation. AIRE co-localized with Dectin-2 and Syk at the FS upon hyphal stimulation of macrophage-like THP-1 cells. AIRE-knockdown macrophage-like THP-1 cells exhibited less Dectin-1 and Dectin-2 receptors accumulation, decreased signaling pathway activity at the FS, lower C. albicans phagocytosis, and less lysosome formation. Furthermore, IL-1β, IL-6, or TNF-α secretion by AIRE-knockdown macrophage-like THP-1 cells and AIRE-deficient patient macrophages was decreased compared to control cells. Our results suggest that AIRE modulates the FS formation and hyphal recognition and help to orchestrate an effective immune response against C. albicans .

  8. Pathway-Based Analysis of Genome-Wide siRNA Screens Reveals the Regulatory Landscape of App Processing

    PubMed Central

    Camargo, Luiz Miguel; Zhang, Xiaohua Douglas; Loerch, Patrick; Caceres, Ramon Miguel; Marine, Shane D.; Uva, Paolo; Ferrer, Marc; de Rinaldis, Emanuele; Stone, David J.; Majercak, John; Ray, William J.; Yi-An, Chen; Shearman, Mark S.; Mizuguchi, Kenji

    2015-01-01

    The progressive aggregation of Amyloid-β (Aβ) in the brain is a major trait of Alzheimer's Disease (AD). Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP). Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPPα. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A) recently implicated with AD through genome wide association studies (GWAS) and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the “regulatory landscape” of APP. PMID:25723573

  9. Respiratory effects of air pollution on children.

    PubMed

    Goldizen, Fiona C; Sly, Peter D; Knibbs, Luke D

    2016-01-01

    A substantial proportion of the global burden of disease is directly or indirectly attributable to exposure to air pollution. Exposures occurring during the periods of organogenesis and rapid lung growth during fetal development and early post-natal life are especially damaging. In this State of the Art review, we discuss air toxicants impacting on children's respiratory health, routes of exposure with an emphasis on unique pathways relevant to young children, methods of exposure assessment and their limitations and the adverse health consequences of exposures. Finally, we point out gaps in knowledge and research needs in this area. A greater understanding of the adverse health consequences of exposure to air pollution in early life is required to encourage policy makers to reduce such exposures and improve human health. © 2015 Wiley Periodicals, Inc.

  10. Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future.

    PubMed

    Barnes, Stephen; Benton, H Paul; Casazza, Krista; Cooper, Sara J; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K; Renfrow, Matthew B; Tiwari, Hemant K

    2016-08-01

    Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  11. Genome-Wide Analysis of DNA Methylation and Fine Particulate Matter Air Pollution in Three Study Populations: KORA F3, KORA F4, and the Normative Aging Study.

    PubMed

    Panni, Tommaso; Mehta, Amar J; Schwartz, Joel D; Baccarelli, Andrea A; Just, Allan C; Wolf, Kathrin; Wahl, Simone; Cyrys, Josef; Kunze, Sonja; Strauch, Konstantin; Waldenberger, Melanie; Peters, Annette

    2016-07-01

    Epidemiological studies have reported associations between particulate matter (PM) concentrations and cancer and respiratory and cardiovascular diseases. DNA methylation has been identified as a possible link but so far it has only been analyzed in candidate sites. We studied the association between DNA methylation and short- and mid-term air pollution exposure using genome-wide data and identified potential biological pathways for additional investigation. We collected whole blood samples from three independent studies-KORA F3 (2004-2005) and F4 (2006-2008) in Germany, and the Normative Aging Study (1999-2007) in the United States-and measured genome-wide DNA methylation proportions with the Illumina 450k BeadChip. PM concentration was measured daily at fixed monitoring stations and three different trailing averages were considered and regressed against DNA methylation: 2-day, 7-day and 28-day. Meta-analysis was performed to pool the study-specific results. Random-effect meta-analysis revealed 12 CpG (cytosine-guanine dinucleotide) sites as associated with PM concentration (1 for 2-day average, 1 for 7-day, and 10 for 28-day) at a genome-wide Bonferroni significance level (p ≤ 7.5E-8); 9 out of these 12 sites expressed increased methylation. Through estimation of I2 for homogeneity assessment across the studies, 4 of these sites (annotated in NSMAF, C1orf212, MSGN1, NXN) showed p > 0.05 and I2 < 0.5: the site from the 7-day average results and 3 for the 28-day average. Applying false discovery rate, p-value < 0.05 was observed in 8 and 1,819 additional CpGs at 7- and 28-day average PM2.5 exposure respectively. The PM-related CpG sites found in our study suggest novel plausible systemic pathways linking ambient PM exposure to adverse health effect through variations in DNA methylation. Panni T, Mehta AJ, Schwartz JD, Baccarelli AA, Just AC, Wolf K, Wahl S, Cyrys J, Kunze S, Strauch K, Waldenberger M, Peters A. 2016. A genome-wide analysis of DNA methylation and

  12. The evaluation of stack metal emissions from hazardous waste incinerators: assessing human exposure through noninhalation pathways.

    PubMed Central

    Sedman, R M; Polisini, J M; Esparza, J R

    1994-01-01

    Potential public health effects associated with exposure to metal emissions from hazardous waste incinerators through noninhalation pathways were evaluated. Instead of relying on modeling the movement of toxicants through various environmental media, an approach based on estimating changes from baseline levels of exposure was employed. Changes in soil and water As, Cd, Hg, Pb, Cr, and Be concentrations that result from incinerator emissions were first determined. Estimates of changes in human exposure due to direct contact with shallow soil or the ingestion of surface water were then ascertained. Projected changes in dietary intakes of metals due to incinerator emissions were estimated based on changes from baseline dietary intakes that are monitored in U.S. Food and Drug Administration total diet studies. Changes from baseline intake were deemed to be proportional to the projected changes in soil or surface water metal concentrations. Human exposure to metals emitted from nine hazardous waste incinerators were then evaluated. Metal emissions from certain facilities resulted in tangible human exposure through noninhalation pathways. However, the analysis indicated that the deposition of metals from ambient air would result in substantially greater human exposure through noninhalation pathways than the emissions from most of the facilities. PMID:7925180

  13. Co-expression analysis reveals key gene modules and pathway of human coronary heart disease.

    PubMed

    Tang, Yu; Ke, Zun-Ping; Peng, Yi-Gen; Cai, Ping-Tai

    2018-02-01

    Coronary heart disease is a kind of disease which causes great injury to people world-widely. Although gene expression analyses had been performed previously, to our best knowledge, systemic co-expression analysis for this disease is still lacking to date. Microarray data of coronary heart disease was downloaded from NCBI with the accession number of GSE20681. Co-expression modules were constructed by WGCNA. Besides, the connectivity degree of eigengenes was analyzed. Furthermore, GO and KEGG enrichment analysis was performed on these eigengenes in these constructed modules. A total of 11 co-expression modules were constructed by the 3000 up-regulated genes from the 99 samples with coronary heart disease. The average number of genes in these modules was 270. The interaction analysis indicated the relative independence of gene expression in these modules. The functional enrichment analysis showed that there was a significant difference in the enriched terms and degree among these 11 modules. The results showed that modules 9 and 10 played critical roles in the occurrence of coronary disease. Pathways of hsa00190 (oxidative phosphorylation) and (hsa01130: biosynthesis of antibiotics) were thought to be closely related to the occurrence and development of coronary heart disease. Our result demonstrated that modules 9 and 10 were the most critical modules in the occurrence of coronary heart disease. Pathways as hsa00190 (oxidative phosphorylation) and (hsa01130: biosynthesis of antibiotics) had the potential to serve as the prognostic and predictive marker of coronary heart disease. © 2017 Wiley Periodicals, Inc.

  14. Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology

    PubMed Central

    Paley, Suzanne M.; Krummenacker, Markus; Latendresse, Mario; Dale, Joseph M.; Lee, Thomas J.; Kaipa, Pallavi; Gilham, Fred; Spaulding, Aaron; Popescu, Liviu; Altman, Tomer; Paulsen, Ian; Keseler, Ingrid M.; Caspi, Ron

    2010-01-01

    Pathway Tools is a production-quality software environment for creating a type of model-organism database called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc integrates the evolving understanding of the genes, proteins, metabolic network and regulatory network of an organism. This article provides an overview of Pathway Tools capabilities. The software performs multiple computational inferences including prediction of metabolic pathways, prediction of metabolic pathway hole fillers and prediction of operons. It enables interactive editing of PGDBs by DB curators. It supports web publishing of PGDBs, and provides a large number of query and visualization tools. The software also supports comparative analyses of PGDBs, and provides several systems biology analyses of PGDBs including reachability analysis of metabolic networks, and interactive tracing of metabolites through a metabolic network. More than 800 PGDBs have been created using Pathway Tools by scientists around the world, many of which are curated DBs for important model organisms. Those PGDBs can be exchanged using a peer-to-peer DB sharing system called the PGDB Registry. PMID:19955237

  15. Constructing an AIRS Climatology for Data Visualization and Analysis to Serve the Climate Science and Application Communities

    NASA Technical Reports Server (NTRS)

    Ding, Feng; Keim, Elaine; Hearty, Thomas J.; Wei, Jennifer; Savtchenko, Andrey; Theobald, Michael; Vollmer, Bruce

    2016-01-01

    The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding SNPP CrIS mission. The AIRS mission is entering its 15th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases. The GES DISC, in collaboration with the AIRS Project, released product from the version 6 algorithm in early 2013. Giovanni, a Web-based application developed by the GES DISC, provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. Most important variables from version 6 AIRS product are available in Giovanni. We are developing a climatology product using 14-year AIRS retrievals. The study can be a good start for the long term climatology from NASA sounders: the AIRS and the succeeding CrIS. This presentation will show the impacts to the climatology product from different aggregation methods. The climatology can serve climate science and application communities in data visualization and analysis, which will be demonstrated using a variety of functions in version 4 Giovanni. The highlights of these functions include user-defined monthly and seasonal climatology, inter annual seasonal time series, anomaly analysis.

  16. Constructing an AIRS Climatology for Data Visualization and Analysis to Serve the Climate Science and Application Communities

    NASA Astrophysics Data System (ADS)

    Ding, F.; Keim, E.; Hearty, T. J., III; Wei, J. C.; Savtchenko, A.; Theobald, M.; Vollmer, B.

    2016-12-01

    The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding SNPP CrIS mission. The AIRS mission is entering its 15th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases. The GES DISC, in collaboration with the AIRS Project, released product from the version 6 algorithm in early 2013. Giovanni, a Web-based application developed by the GES DISC, provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. Most important variables from version 6 AIRS product are available in Giovanni. We are developing a climatology product using 14-year AIRS retrievals. The study can be a good start for the long term climatology from NASA sounders: the AIRS and the succeeding CrIS. This presentation will show the impacts to the climatology product from different aggregation methods. The climatology can serve climate science and application communities in data visualization and analysis, which will be demonstrated using a variety of functions in version 4 Giovanni. The highlights of these functions include user-defined monthly and seasonal climatology, inter annual seasonal time series, anomaly analysis.

  17. Lagrangian analysis of premixed turbulent combustion in hydrogen-air flames

    NASA Astrophysics Data System (ADS)

    Darragh, Ryan; Poludnenko, Alexei; Hamlington, Peter

    2016-11-01

    Lagrangian analysis has long been a tool used to analyze non-reacting turbulent flows, and has recently gained attention in the reacting flow and combustion communities. The approach itself allows one to separate local molecular effects, such as those due to reactions or diffusion, from turbulent advective effects along fluid pathlines, or trajectories. Accurate calculation of these trajectories can, however, be rather difficult due to the chaotic nature of turbulent flows and the added complexity of reactions. In order to determine resolution requirements and verify the numerical algorithm, extensive tests are described in this talk for prescribed steady, unsteady, and chaotic flows, as well as for direct numerical simulations (DNS) of non-reacting homogeneous isotropic turbulence. The Lagrangian analysis is then applied to DNS of premixed hydrogen-air flames at two different turbulence intensities for both single- and multi-step chemical mechanisms. Non-monotonic temperature and fuel-mass fraction evolutions are found to exist along trajectories passing through the flame brush. Such non-monotonicity is shown to be due to molecular diffusion resulting from large spatial gradients created by turbulent advection. This work was supported by the Air Force Office of Scientific Research (AFOSR) under Award No. FA9550-14-1-0273, and the Department of Defense (DoD) High Performance Computing Modernization Program (HPCMP) under a Frontier project award.

  18. Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

    PubMed

    Jiang, Yue; Xiong, Xuejian; Danska, Jayne; Parkinson, John

    2016-01-12

    Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function. Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76% of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions. The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of

  19. High Altitude Long Endurance Air Vehicle Analysis of Alternatives and Technology Requirements Development

    NASA Technical Reports Server (NTRS)

    Nickol, Craig L.; Guynn, Mark D.; Kohout, Lisa L.; Ozoroski, Thomas A.

    2007-01-01

    The objective of this study was to develop a variety of High Altitude Long Endurance (HALE) Unmanned Aerial Vehicle (UAV) conceptual designs for two operationally useful missions (hurricane science and communications relay) and compare their performance and cost characteristics. Sixteen potential HALE UAV configurations were initially developed, including heavier-than-air (HTA) and lighter-than-air (LTA) concepts with both consumable fuel and solar regenerative (SR) propulsion systems. Through an Analysis of Alternatives (AoA) down select process, the two leading consumable fuel configurations (one each from the HTA and LTA alternatives) and an HTA SR configuration were selected for further analysis. Cost effectiveness analysis of the consumable fuel configurations revealed that simply maximizing vehicle endurance can lead to a sub-optimum system solution. An LTA concept with a hybrid propulsion system (solar arrays and a hydrogen-air proton exchange membrane fuel cell) was found to have the best mission performance; however, an HTA diesel-fueled wing-body-tail configuration emerged as the preferred consumable fuel concept because of the large size and technical risk of the LTA concept. The baseline missions could not be performed by even the best HTA SR concept. Mission and SR technology trade studies were conducted to enhance understanding of the potential capabilities of such a vehicle. With near-term technology SR-powered HTA vehicles are limited to operation in favorable solar conditions, such as the long days and short nights of summer at higher latitudes. Energy storage system specific energy and solar cell efficiency were found to be the key technology areas for enhancing HTA SR performance.

  20. Fault tree analysis for exposure to refrigerants used for automotive air conditioning in the United States.

    PubMed

    Jetter, J J; Forte, R; Rubenstein, R

    2001-02-01

    A fault tree analysis was used to estimate the number of refrigerant exposures of automotive service technicians and vehicle occupants in the United States. Exposures of service technicians can occur when service equipment or automotive air-conditioning systems leak during servicing. The number of refrigerant exposures of service technicians was estimated to be 135,000 per year. Exposures of vehicle occupants can occur when refrigerant enters passenger compartments due to sudden leaks in air-conditioning systems, leaks following servicing, or leaks caused by collisions. The total number of exposures of vehicle occupants was estimated to be 3,600 per year. The largest number of exposures of vehicle occupants was estimated for leaks caused by collisions, and the second largest number of exposures was estimated for leaks following servicing. Estimates used in the fault tree analysis were based on a survey of automotive air-conditioning service shops, the best available data from the literature, and the engineering judgement of the authors and expert reviewers from the Society of Automotive Engineers Interior Climate Control Standards Committee. Exposure concentrations and durations were estimated and compared with toxicity data for refrigerants currently used in automotive air conditioners. Uncertainty was high for the estimated numbers of exposures, exposure concentrations, and exposure durations. Uncertainty could be reduced in the future by conducting more extensive surveys, measurements of refrigerant concentrations, and exposure monitoring. Nevertheless, the analysis indicated that the risk of exposure of service technicians and vehicle occupants is significant, and it is recommended that no refrigerant that is substantially more toxic than currently available substitutes be accepted for use in vehicle air-conditioning systems, absent a means of mitigating exposure.