Pathway analysis of IMC

DEFF Research Database (Denmark)

Skrypnyuk, Nataliya; Nielson, Flemming; Pilegaard, Henrik

2009-01-01

We present the ongoing work on the pathway analysis of a stochastic calculus. Firstly we present a particular stochastic calculus that we have chosen for our modeling - the Interactive Markov Chains calculus, IMC for short. After that we specify a few restrictions that we have introduced into the...... into the syntax of IMC in order to make our analysis feasible. Finally we describe the analysis itself together with several theoretical results that we have proved for it.......We present the ongoing work on the pathway analysis of a stochastic calculus. Firstly we present a particular stochastic calculus that we have chosen for our modeling - the Interactive Markov Chains calculus, IMC for short. After that we specify a few restrictions that we have introduced...

Life Cycle Greenhouse Gas Analysis of Multiple Vehicle Fuel Pathways in China

Directory of Open Access Journals (Sweden)

Tianduo Peng

2017-11-01

Full Text Available The Tsinghua University Life Cycle Analysis Model (TLCAM is applied to calculate the life cycle fossil energy consumption and greenhouse gas (GHG emissions for more than 20 vehicle fuel pathways in China. In addition to conventional gasoline and diesel, these include coal- and gas-based vehicle fuels, and electric vehicle (EV pathways. The results indicate the following. (1 China’s current dependence on coal and relative low-efficiency processes limits the potential for most alternative fuel pathways to decrease energy consumption and emissions; (2 Future low-carbon electricity pathways offer more obvious advantages, with coal-based pathways needing to adopt carbon dioxide capture and storage technology to compete; (3 A well-to-wheels analysis of the fossil energy consumption of vehicles fueled by compressed natural gas and liquefied natural gas (LNG showed that they are comparable to conventional gasoline vehicles. However, importing rather than domestically producing LNG for vehicle use can decrease domestic GHG emissions by 35% and 31% compared with those of conventional gasoline and diesel vehicles, respectively; (4 The manufacturing and recovery of battery and vehicle in the EV analysis has significant impact on the overall ability of EVs to decrease fossil energy consumption and GHG emissions from ICEVs.

Analysis of Membrane Protein Topology in the Plant Secretory Pathway.

Science.gov (United States)

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.

Extending in silico mechanism-of-action analysis by annotating targets with pathways: application to cellular cytotoxicity readouts.

Science.gov (United States)

Liggi, Sonia; Drakakis, Georgios; Koutsoukas, Alexios; Cortes-Ciriano, Isidro; Martínez-Alonso, Patricia; Malliavin, Thérèse E; Velazquez-Campoy, Adrian; Brewerton, Suzanne C; Bodkin, Michael J; Evans, David A; Glen, Robert C; Carrodeguas, José Alberto; Bender, Andreas

2014-01-01

An in silico mechanism-of-action analysis protocol was developed, comprising molecule bioactivity profiling, annotation of predicted targets with pathways and calculation of enrichment factors to highlight targets and pathways more likely to be implicated in the studied phenotype. The method was applied to a cytotoxicity phenotypic endpoint, with enriched targets/pathways found to be statistically significant when compared with 100 random datasets. Application on a smaller apoptotic set (10 molecules) did not allowed to obtain statistically relevant results, suggesting that the protocol requires modification such as analysis of the most frequently predicted targets/annotated pathways. Pathway annotations improved the mechanism-of-action information gained by target prediction alone, allowing a better interpretation of the predictions and providing better mapping of targets onto pathways.

A cross-study gene set enrichment analysis identifies critical pathways in endometriosis

Directory of Open Access Journals (Sweden)

Bai Chunyan

2009-09-01

Full Text Available Abstract Background Endometriosis is an enigmatic disease. Gene expression profiling of endometriosis has been used in several studies, but few studies went further to classify subtypes of endometriosis based on expression patterns and to identify possible pathways involved in endometriosis. Some of the observed pathways are more inconsistent between the studies, and these candidate pathways presumably only represent a fraction of the pathways involved in endometriosis. Methods We applied a standardised microarray preprocessing and gene set enrichment analysis to six independent studies, and demonstrated increased concordance between these gene datasets. Results We find 16 up-regulated and 19 down-regulated pathways common in ovarian endometriosis data sets, 22 up-regulated and one down-regulated pathway common in peritoneal endometriosis data sets. Among them, 12 up-regulated and 1 down-regulated were found consistent between ovarian and peritoneal endometriosis. The main canonical pathways identified are related to immunological and inflammatory disease. Early secretory phase has the most over-represented pathways in the three uterine cycle phases. There are no overlapping significant pathways between the dataset from human endometrial endothelial cells and the datasets from ovarian endometriosis which used whole tissues. Conclusion The study of complex diseases through pathway analysis is able to highlight genes weakly connected to the phenotype which may be difficult to detect by using classical univariate statistics. By standardised microarray preprocessing and GSEA, we have increased the concordance in identifying many biological mechanisms involved in endometriosis. The identified gene pathways will shed light on the understanding of endometriosis and promote the development of novel therapies.

Analysis of the Nevada-Applied-Ecology-Group model of transuranic radionuclide transport and dose

International Nuclear Information System (INIS)

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

1991-01-01

The authors analyze the model for estimating the dose from 239 Pu developed for the Nevada Applied Ecology Group (NAEG) by using sensitivity analysis and uncertainty analysis. Sensitivity analysis results suggest that the inhalation 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 inhalation pathway accounts for 100% of the dose to lung, upper respiratory tract and thoracic lymph nodes; and 95% of the dose to liver, bone, kidney and total body. The GI tract receives 99% of its dose via ingestion. 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%. 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 nodes. (author)

Pathway analysis of kidney cancer using proteomics and metabolic profiling

Directory of Open Access Journals (Sweden)

Fiehn Oliver

2006-11-01

Full Text Available Abstract Background Renal cell carcinoma (RCC is the sixth leading cause of cancer death and is responsible for 11,000 deaths per year in the US. Approximately one-third of patients present with disease which is already metastatic and for which there is currently no adequate treatment, and no biofluid screening tests exist for RCC. In this study, we have undertaken a comprehensive proteomic analysis and subsequently a pathway and network approach to identify biological processes involved in clear cell RCC (ccRCC. We have used these data to investigate urinary markers of RCC which could be applied to high-risk patients, or to those being followed for recurrence, for early diagnosis and treatment, thereby substantially reducing mortality of this disease. Results Using 2-dimensional electrophoresis and mass spectrometric analysis, we identified 31 proteins which were differentially expressed with a high degree of significance in ccRCC as compared to adjacent non-malignant tissue, and we confirmed some of these by immunoblotting, immunohistochemistry, and comparison to published transcriptomic data. When evaluated by several pathway and biological process analysis programs, these proteins are demonstrated to be involved with a high degree of confidence (p values Conclusion Extensive pathway and network analysis allowed for the discovery of highly significant pathways from a set of clear cell RCC samples. Knowledge of activation of these processes will lead to novel assays identifying their proteomic and/or metabolomic signatures in biofluids of patient at high risk for this disease; we provide pilot data for such a urinary bioassay. Furthermore, we demonstrate how the knowledge of networks, processes, and pathways altered in kidney cancer may be used to influence the choice of optimal therapy.

Phytohormone signaling pathway analysis method for comparing hormone responses in plant-pest interactions

Directory of Open Access Journals (Sweden)

Studham Matthew E

2012-07-01

Full Text Available Abstract Background Phytohormones mediate plant defense responses to pests and pathogens. In particular, the hormones jasmonic acid, ethylene, salicylic acid, and abscisic acid have been shown to dictate and fine-tune defense responses, and identification of the phytohormone components of a particular defense response is commonly used to characterize it. Identification of phytohormone regulation is particularly important in transcriptome analyses. Currently there is no computational tool to determine the relative activity of these hormones that can be applied to transcriptome analyses in soybean. Findings We developed a pathway analysis method that provides a broad measure of the activation or suppression of individual phytohormone pathways based on changes in transcript expression of pathway-related genes. The magnitude and significance of these changes are used to determine a pathway score for a phytohormone for a given comparison in a microarray experiment. Scores for individual hormones can then be compared to determine the dominant phytohormone in a given defense response. To validate this method, it was applied to publicly available data from previous microarray experiments that studied the response of soybean plants to Asian soybean rust and soybean cyst nematode. The results of the analyses for these experiments agreed with our current understanding of the role of phytohormones in these defense responses. Conclusions This method is useful in providing a broad measure of the relative induction and suppression of soybean phytohormones during a defense response. This method could be used as part of microarray studies that include individual transcript analysis, gene set analysis, and other methods for a comprehensive defense response characterization.

Pathway-based Analysis of the Hidden Genetic Heterogeneities in Cancers

Directory of Open Access Journals (Sweden)

Xiaolei Zhao

2014-02-01

Full Text Available Many cancers apparently showing similar phenotypes are actually distinct at the molecular level, leading to very different responses to the same treatment. It has been recently demonstrated that pathway-based approaches are robust and reliable for genetic analysis of cancers. Nevertheless, it remains unclear whether such function-based approaches are useful in deciphering molecular heterogeneities in cancers. Therefore, we aimed to test this possibility in the present study. First, we used a NCI60 dataset to validate the ability of pathways to correctly partition samples. Next, we applied the proposed method to identify the hidden subtypes in diffuse large B-cell lymphoma (DLBCL. Finally, the clinical significance of the identified subtypes was verified using survival analysis. For the NCI60 dataset, we achieved highly accurate partitions that best fit the clinical cancer phenotypes. Subsequently, for a DLBCL dataset, we identified three hidden subtypes that showed very different 10-year overall survival rates (90%, 46% and 20% and were highly significantly (P = 0.008 correlated with the clinical survival rate. This study demonstrated that the pathway-based approach is promising for unveiling genetic heterogeneities in complex human diseases.

[Analysis of Applying Chinese Medical Clinical Pathway for Treating Attention-deficit Hyperactivity Disorder].

Science.gov (United States)

Guo, Yu-qing; Han, Xin-min; Zhu, Xian-kang; Zhou, Zheng; Ma, Bing-xiang; Zhang, Bao-qing; Li, Yan-ning; Feng, Yu-lin; Xue, Zheng; Wang, Yong-hong; Li, Yi-min; Jiang, Zhi-mei; Xu, Jin-xing; Yue, Wei-zhen; Xiang, Xi-xiong

2015-12-01

To evaluate the application effect of Chinese medical clinical pathway for treating attention-deficit hyperactivity disorder (ADHD), and to provide evidence for further improving clinical pathways. Totally 270 ADHD children patients were recruited and treated at pediatrics clinics of 9 cooperative hospitals from December 2011 to December 2012. The treatment course for all was 3 months. Scores of attention deficit and hyperactivity rating scale, scores of behavior, Conners index of hyperactivity (CIH), and Chinese medical syndrome scores were compared between before and after treatment. The efficacy difference in various sexes, ages, and disease courses were evaluated by judging standards for Chinese medical syndrome and ADHD. Fifteen children patients who entered clinical pathway dropped out, and the rest 255 completed this trial. Compared with before treatment, total scores of attention deficit and hyperactivity rating scale, scores of attention deficit and hyperactivity rating scale, CIH, and Chinese medical syndrome scores obviously decreased (all P < 0.01). The total effective rate in disease efficacy was 87.8% (224/255 cases), and the total effective rate in Chinese medical syndrome curative effect was 87.5% (223/255 cases). The clinical curative effect was not influenced by age, gender, or course of disease when statistically analyzed from judging standards for Chinese medical syndrome or for disease efficacy. Intervention by Chinese medical clinical pathway could improve ADHD patients' symptoms, and its efficacy was not influenced by sex, age, or course of disease.

Constraint-based modeling and kinetic analysis of the Smad dependent TGF-beta signaling pathway.

Directory of Open Access Journals (Sweden)

Zhike Zi

Full Text Available BACKGROUND: Investigation of dynamics and regulation of the TGF-beta signaling pathway is central to the understanding of complex cellular processes such as growth, apoptosis, and differentiation. In this study, we aim at using systems biology approach to provide dynamic analysis on this pathway. METHODOLOGY/PRINCIPAL FINDINGS: We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-beta signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis. The performance of the model generated by constraint-based modeling method is significantly improved compared to the model obtained by only fitting the quantitative data. The model agrees well with the experimental analysis of TGF-beta pathway, such as the time course of nuclear phosphorylated Smad, the subcellular location of Smad and signal response of Smad phosphorylation to different doses of TGF-beta. CONCLUSIONS/SIGNIFICANCE: The simulation results indicate that the signal response to TGF-beta is regulated by the balance between clathrin dependent endocytosis and non-clathrin mediated endocytosis. This model is useful to be built upon as new precise experimental data are emerging. The constraint-based modeling method can also be applied to quantitative modeling of other signaling pathways.

Safety assessment for deep underground disposal vault-pathways analysis

International Nuclear Information System (INIS)

Lyon, R.B.; Rosinger, E.L.J.

1980-01-01

The concept verification phase of the Canadian programme for the disposal of nuclear fuel waste encompasses a period of about three years before the start of site selection. During this time, the methodology for Environmental and Safety Assessment studies is being developed by focusing on a model site. Pathways analysis is an important component of these studies. It involves the prediction of the rate at which radionuclides might be released from a disposal vault and travel through the geosphere and biosphere to reach man. The pathways analysis studies cover three major topics: geosphere pathways analysis, biosphere pathways analysis and potentially-disruptive-phenomena analysis. Geosphere pathways analysis includes a total systems analysis, using the computer program GARD2, vault analysis, which considers container failure and waste leaching, hydrogeological modelling and geochemical modelling. Biosphere pathways analysis incorporates a compartmental modelling approach using the computer program RAMM, and a food chain analysis using the computer program FOOD II. Potentially-disruptive-phenomena analysis involves the estimation of the probability and consequences of events such as earthquakes which might reduce the effectiveness of the barriers preventing the release of radionuclides. The current stage of development of the required methodology and data is discussed in each of the three areas and preliminary results are presented. (author)

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

Science.gov (United States)

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

Primary Metabolic Pathways and Metabolic Flux Analysis

DEFF Research Database (Denmark)

Villadsen, John

2015-01-01

his chapter introduces the metabolic flux analysis (MFA) or stoichiometry-based MFA, and describes the quantitative basis for MFA. It discusses the catabolic pathways in which free energy is produced to drive the cell-building anabolic pathways. An overview of these primary pathways provides...... the reader who is primarily trained in the engineering sciences with atleast a preliminary introduction to biochemistry and also shows how carbon is drained off the catabolic pathways to provide precursors for cell mass building and sometimes for important industrial products. The primary pathways...... to be examined in the following are: glycolysis, primarily by the EMP pathway, but other glycolytic pathways is also mentioned; fermentative pathways in which the redox generated in the glycolytic reactions are consumed; reactions in the tricarboxylic acid (TCA) cycle, which produce biomass precursors and redox...

A systems biology approach for pathway level analysis

OpenAIRE

Draghici, Sorin; Khatri, Purvesh; Tarca, Adi Laurentiu; Amin, Kashyap; Done, Arina; Voichita, Calin; Georgescu, Constantin; Romero, Roberto

2007-01-01

A common challenge in the analysis of genomics data is trying to understand the underlying phenomenon in the context of all complex interactions taking place on various signaling pathways. A statistical approach using various models is universally used to identify the most relevant pathways in a given experiment. Here, we show that the existing pathway analysis methods fail to take into consideration important biological aspects and may provide incorrect results in certain situations. By usin...

Final report on the Pathway Analysis Task

International Nuclear Information System (INIS)

Whicker, F.W.; Kirchner, T.B.

1993-04-01

The Pathway Analysis Task constituted one of several multi-laboratory efforts to estimate radiation doses to people, considering all important pathways of exposure, from the testing of nuclear devices at the Nevada Test Site (NTS). The primary goal of the Pathway Analysis Task was to predict radionuclide ingestion by residents of Utah, Nevada, and portions of seven other adjoining western states following radioactive fallout deposition from individual events at the NTS. This report provides comprehensive documentation of the activities and accomplishments of Colorado State University's Pathway Analysis Task during the entire period of support (1979--91). The history of the project will be summarized, indicating the principal dates and milestones, personnel involved, subcontractors, and budget information. Accomplishments, both primary and auxiliary, will be summarized with general results rather than technical details being emphasized. This will also serve as a guide to the reports and open literature publications produced, where the methodological details and specific results are documented. Selected examples of results on internal dose estimates are provided in this report because the data have not been published elsewhere

Final report on the Pathway Analysis Task

Energy Technology Data Exchange (ETDEWEB)

Whicker, F.W.; Kirchner, T.B. [Colorado State Univ., Fort Collins, CO (United States)

1993-04-01

The Pathway Analysis Task constituted one of several multi-laboratory efforts to estimate radiation doses to people, considering all important pathways of exposure, from the testing of nuclear devices at the Nevada Test Site (NTS). The primary goal of the Pathway Analysis Task was to predict radionuclide ingestion by residents of Utah, Nevada, and portions of seven other adjoining western states following radioactive fallout deposition from individual events at the NTS. This report provides comprehensive documentation of the activities and accomplishments of Colorado State University`s Pathway Analysis Task during the entire period of support (1979--91). The history of the project will be summarized, indicating the principal dates and milestones, personnel involved, subcontractors, and budget information. Accomplishments, both primary and auxiliary, will be summarized with general results rather than technical details being emphasized. This will also serve as a guide to the reports and open literature publications produced, where the methodological details and specific results are documented. Selected examples of results on internal dose estimates are provided in this report because the data have not been published elsewhere.

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

Directory of Open Access Journals (Sweden)

Chaoxing Li

2018-04-01

Full Text Available 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

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

Directory of Open Access Journals (Sweden)

Unjin Shim

2014-12-01

Full Text Available 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/m2. 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.

The future use of pathway analysis in IAEA safeguards

International Nuclear Information System (INIS)

Budlong Sylvester, Kory; Pilat, J.; Murphy, Chantell

2013-01-01

Pathway analysis has the potential to play an important role in the development of a safeguards system that is more information driven, leveraging all the information available to the International Atomic Energy Agency (IAEA). Pathway analysis should be seen as an extension of traditional hypothesis testing used by the Agency in the past. The most attractive pathways based on the assessed capabilities of a given state can be identified and used in the development of state-level safeguards approaches. This ranking of pathways can be revised based on evidence of pathway use, or preparations for use, allowing limited safeguards resources to flow to the areas of highest concern. The possible uses of pathway analysis in the implementation of the IAEA's state-level concept are described along with implementation issues that will likely arise. The paper is followed by the slides of the presentation. (authors)

Cleanup standards and pathways analysis methods

International Nuclear Information System (INIS)

Devgun, J.S.

1993-01-01

Remediation of a radioactively contaminated site requires that certain regulatory criteria be met before the site can be released for unrestricted future use. Since the ultimate objective of remediation is to protect the public health and safety, residual radioactivity levels remaining at a site after cleanup must be below certain preset limits or meet acceptable dose or risk criteria. Release of a decontaminated site requires proof that the radiological data obtained from the site meet the regulatory criteria for such a release. Typically release criteria consist of a composite of acceptance limits that depend on the radionuclides, the media in which they are present, and federal and local regulations. In recent years, the US Department of Energy (DOE) has developed a pathways analysis model to determine site-specific soil activity concentration guidelines for radionuclides that do not have established generic acceptance limits. The DOE pathways analysis computer code (developed by Argonne National Laboratory for the DOE) is called RESRAD (Gilbert et al. 1989). Similar efforts have been initiated by the US Nuclear Regulatory Commission (NRC) to develop and use dose-related criteria based on genetic pathways analyses rather than simplistic numerical limits on residual radioactivity. The focus of this paper is radionuclide contaminated soil. Cleanup standards are reviewed, pathways analysis methods are described, and an example is presented in which RESRAD was used to derive cleanup guidelines

Sensitivity and uncertainty analysis of the PATHWAY radionuclide transport model

International Nuclear Information System (INIS)

Otis, M.D.

1983-01-01

Procedures were developed for the uncertainty and sensitivity analysis of a dynamic model of radionuclide transport through human food chains. Uncertainty in model predictions was estimated by propagation of parameter uncertainties using a Monte Carlo simulation technique. Sensitivity of model predictions to individual parameters was investigated using the partial correlation coefficient of each parameter with model output. Random values produced for the uncertainty analysis were used in the correlation analysis for sensitivity. These procedures were applied to the PATHWAY model which predicts concentrations of radionuclides in foods grown in Nevada and Utah and exposed to fallout during the period of atmospheric nuclear weapons testing in Nevada. Concentrations and time-integrated concentrations of iodine-131, cesium-136, and cesium-137 in milk and other foods were investigated. 9 figs., 13 tabs

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

Directory of Open Access Journals (Sweden)

Wufeng Fan

2017-01-01

Full Text Available 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.

Integrating eQTL data with GWAS summary statistics in pathway-based analysis with application to schizophrenia.

Science.gov (United States)

Wu, Chong; Pan, Wei

2018-04-01

Many genetic variants affect complex traits through gene expression, which can be exploited to boost statistical power and enhance interpretation in genome-wide association studies (GWASs) as demonstrated by the transcriptome-wide association study (TWAS) approach. Furthermore, due to polygenic inheritance, a complex trait is often affected by multiple genes with similar functions as annotated in gene pathways. Here, we extend TWAS from gene-based analysis to pathway-based analysis: we integrate public pathway collections, expression quantitative trait locus (eQTL) data and GWAS summary association statistics (or GWAS individual-level data) to identify gene pathways associated with complex traits. The basic idea is to weight the SNPs of the genes in a pathway based on their estimated cis-effects on gene expression, then adaptively test for association of the pathway with a GWAS trait by effectively aggregating possibly weak association signals across the genes in the pathway. The P values can be calculated analytically and thus fast. We applied our proposed test with the KEGG and GO pathways to two schizophrenia (SCZ) GWAS summary association data sets, denoted by SCZ1 and SCZ2 with about 20,000 and 150,000 subjects, respectively. Most of the significant pathways identified by analyzing the SCZ1 data were reproduced by the SCZ2 data. Importantly, we identified 15 novel pathways associated with SCZ, such as GABA receptor complex (GO:1902710), which could not be uncovered by the standard single SNP-based analysis or gene-based TWAS. The newly identified pathways may help us gain insights into the biological mechanism underlying SCZ. Our results showcase the power of incorporating gene expression information and gene functional annotations into pathway-based association testing for GWAS. © 2018 WILEY PERIODICALS, INC.

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

Science.gov (United States)

Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-06

Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

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

Science.gov (United States)

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.

Pathway Processor 2.0: a web resource for pathway-based analysis of high-throughput data.

Science.gov (United States)

Beltrame, Luca; Bianco, Luca; Fontana, Paolo; Cavalieri, Duccio

2013-07-15

Pathway Processor 2.0 is a web application designed to analyze high-throughput datasets, including but not limited to microarray and next-generation sequencing, using a pathway centric logic. In addition to well-established methods such as the Fisher's test and impact analysis, Pathway Processor 2.0 offers innovative methods that convert gene expression into pathway expression, leading to the identification of differentially regulated pathways in a dataset of choice. Pathway Processor 2.0 is available as a web service at http://compbiotoolbox.fmach.it/pathwayProcessor/. Sample datasets to test the functionality can be used directly from the application. duccio.cavalieri@fmach.it Supplementary data are available at Bioinformatics online.

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

Science.gov (United States)

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.

Simplified analysis for liquid pathway studies

International Nuclear Information System (INIS)

Codell, R.B.

1984-08-01

The analysis of the potential contamination of surface water via groundwater contamination from severe nuclear accidents is routinely calculated during licensing reviews. This analysis is facilitated by the methods described in this report, which is codified into a BASIC language computer program, SCREENLP. This program performs simplified calculations for groundwater and surface water transport and calculates population doses to potential users for the contaminated water irrespective of possible mitigation methods. The results are then compared to similar analyses performed using data for the generic sites in NUREG-0440, Liquid Pathway Generic Study, to determine if the site being investigated would pose any unusual liquid pathway hazards

ComPath: comparative enzyme analysis and annotation in pathway/subsystem contexts

Directory of Open Access Journals (Sweden)

Kim Sun

2008-03-01

Full Text Available Abstract Background Once a new genome is sequenced, one of the important questions is to determine the presence and absence of biological pathways. Analysis of biological pathways in a genome is a complicated task since a number of biological entities are involved in pathways and biological pathways in different organisms are not identical. Computational pathway identification and analysis thus involves a number of computational tools and databases and typically done in comparison with pathways in other organisms. This computational requirement is much beyond the capability of biologists, so information systems for reconstructing, annotating, and analyzing biological pathways are much needed. We introduce a new comparative pathway analysis workbench, ComPath, which integrates various resources and computational tools using an interactive spreadsheet-style web interface for reliable pathway analyses. Results ComPath allows users to compare biological pathways in multiple genomes using a spreadsheet style web interface where various sequence-based analysis can be performed either to compare enzymes (e.g. sequence clustering and pathways (e.g. pathway hole identification, to search a genome for de novo prediction of enzymes, or to annotate a genome in comparison with reference genomes of choice. To fill in pathway holes or make de novo enzyme predictions, multiple computational methods such as FASTA, Whole-HMM, CSR-HMM (a method of our own introduced in this paper, and PDB-domain search are integrated in ComPath. Our experiments show that FASTA and CSR-HMM search methods generally outperform Whole-HMM and PDB-domain search methods in terms of sensitivity, but FASTA search performs poorly in terms of specificity, detecting more false positive as E-value cutoff increases. Overall, CSR-HMM search method performs best in terms of both sensitivity and specificity. Gene neighborhood and pathway neighborhood (global network visualization tools can be used

Handbook of Applied Analysis

CERN Document Server

Papageorgiou, Nikolaos S

2009-01-01

Offers an examination of important theoretical methods and procedures in applied analysis. This book details the important theoretical trends in nonlinear analysis and applications to different fields. It is suitable for those working on nonlinear analysis.

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

Science.gov (United States)

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.

Applied longitudinal analysis

CERN Document Server

Fitzmaurice, Garrett M; Ware, James H

2012-01-01

Praise for the First Edition "". . . [this book] should be on the shelf of everyone interested in . . . longitudinal data analysis.""-Journal of the American Statistical Association   Features newly developed topics and applications of the analysis of longitudinal data Applied Longitudinal Analysis, Second Edition presents modern methods for analyzing data from longitudinal studies and now features the latest state-of-the-art techniques. The book emphasizes practical, rather than theoretical, aspects of methods for the analysis of diverse types of lo

Pan-cancer analysis of TCGA data reveals notable signaling pathways

International Nuclear Information System (INIS)

Neapolitan, Richard; Horvath, Curt M.; Jiang, Xia

2015-01-01

A signal transduction pathway (STP) is a network of intercellular information flow initiated when extracellular signaling molecules bind to cell-surface receptors. Many aberrant STPs have been associated with various cancers. To develop optimal treatments for cancer patients, it is important to discover which STPs are implicated in a cancer or cancer-subtype. The Cancer Genome Atlas (TCGA) makes available gene expression level data on cases and controls in ten different types of cancer including breast cancer, colon adenocarcinoma, glioblastoma, kidney renal papillary cell carcinoma, low grade glioma, lung adenocarcinoma, lung squamous cell carcinoma, ovarian carcinoma, rectum adenocarcinoma, and uterine corpus endometriod carcinoma. Signaling Pathway Impact Analysis (SPIA) is a software package that analyzes gene expression data to identify whether a pathway is relevant in a given condition. We present the results of a study that uses SPIA to investigate all 157 signaling pathways in the KEGG PATHWAY database. We analyzed each of the ten cancer types mentioned above separately, and we perform a pan-cancer analysis by grouping the data for all the cancer types. In each analysis several pathways were found to be markedly more significant than all the other pathways. We call them notable. Research has already established a connection between many of these pathways and the corresponding cancer type. However, some of our discovered pathways appear to be new findings. Altogether there were 37 notable findings in the separate analyses, 26 of them occurred in 7 pathways. These 7 pathways included the 4 notable pathways discovered in the pan-cancer analysis. So, our results suggest that these 7 pathways account for much of the mechanisms of cancer. Furthermore, by looking at the overlap among pathways, we identified possible regions on the pathways where the aberrant activity is occurring. We obtained 37 notable findings concerning 18 pathways. Some of them appear to be

Computational Chemical Synthesis Analysis and Pathway Design

Directory of Open Access Journals (Sweden)

Fan Feng

2018-06-01

Full Text Available With the idea of retrosynthetic analysis, which was raised in the 1960s, chemical synthesis analysis and pathway design have been transformed from a complex problem to a regular process of structural simplification. This review aims to summarize the developments of computer-assisted synthetic analysis and design in recent years, and how machine-learning algorithms contributed to them. LHASA system started the pioneering work of designing semi-empirical reaction modes in computers, with its following rule-based and network-searching work not only expanding the databases, but also building new approaches to indicating reaction rules. Programs like ARChem Route Designer replaced hand-coded reaction modes with automatically-extracted rules, and programs like Chematica changed traditional designing into network searching. Afterward, with the help of machine learning, two-step models which combine reaction rules and statistical methods became the main stream. Recently, fully data-driven learning methods using deep neural networks which even do not require any prior knowledge, were applied into this field. Up to now, however, these methods still cannot replace experienced human organic chemists due to their relatively low accuracies. Future new algorithms with the aid of powerful computational hardware will make this topic promising and with good prospects.

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

Science.gov (United States)

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

Applied mediation analyses

DEFF Research Database (Denmark)

Lange, Theis; Hansen, Kim Wadt; Sørensen, Rikke

2017-01-01

In recent years, mediation analysis has emerged as a powerful tool to disentangle causal pathways from an exposure/treatment to clinically relevant outcomes. Mediation analysis has been applied in scientific fields as diverse as labour market relations and randomized clinical trials of heart...... disease treatments. In parallel to these applications, the underlying mathematical theory and computer tools have been refined. This combined review and tutorial will introduce the reader to modern mediation analysis including: the mathematical framework; required assumptions; and software implementation...

PyPathway: Python Package for Biological Network Analysis and Visualization.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Eva Chovancova

Full Text Available 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.

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

Science.gov (United States)

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

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

Directory of Open Access Journals (Sweden)

Gaora Peadar Ó

2010-10-01

Full Text Available Abstract 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 Conclusion Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of

Network Expansion and Pathway Enrichment Analysis towards Biologically Significant Findings from Microarrays

Directory of Open Access Journals (Sweden)

Wu Xiaogang

2012-06-01

Full Text Available In many cases, crucial genes show relatively slight changes between groups of samples (e.g. normal vs. disease, and many genes selected from microarray differential analysis by measuring the expression level statistically are also poorly annotated and lack of biological significance. In this paper, we present an innovative approach - network expansion and pathway enrichment analysis (NEPEA for integrative microarray analysis. We assume that organized knowledge will help microarray data analysis in significant ways, and the organized knowledge could be represented as molecular interaction networks or biological pathways. Based on this hypothesis, we develop the NEPEA framework based on network expansion from the human annotated and predicted protein interaction (HAPPI database, and pathway enrichment from the human pathway database (HPD. We use a recently-published microarray dataset (GSE24215 related to insulin resistance and type 2 diabetes (T2D as case study, since this study provided a thorough experimental validation for both genes and pathways identified computationally from classical microarray analysis and pathway analysis. We perform our NEPEA analysis for this dataset based on the results from the classical microarray analysis to identify biologically significant genes and pathways. Our findings are not only consistent with the original findings mostly, but also obtained more supports from other literatures.

Transcriptomic analysis in the developing zebrafish embryo after compound exposure: Individual gene expression and pathway regulation

Energy Technology Data Exchange (ETDEWEB)

Hermsen, Sanne A.B., E-mail: Sanne.Hermsen@rivm.nl [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands); Pronk, Tessa E. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Brandhof, Evert-Jan van den [Centre for Environmental Quality, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Ven, Leo T.M. van der [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Piersma, Aldert H. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands)

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 and 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.

Pathway-based analyses.

Science.gov (United States)

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.

Phase analysis in gated blood pool tomography. Detection of accessory conduction pathway

Energy Technology Data Exchange (ETDEWEB)

Nakajima, Kenichi; Bunko, Hisashi; Tada, Akira; Taki, Junichi; Nanbu, Ichiro (Kanazawa Univ. (Japan). School of Medicine)

1984-02-01

Phase analysis of gated blood pool study has been applied to detect the site of accessory conduction pathway (ACP) in the Wolff-Parkinson-White (WPW) syndrome; however, there was a limitation to detect the precise location of ACP by phase analysis alone. In this study, we applied phase analysis to gated blood pool tomography using seven pin hole tomography (7PT) and gated emission computed tomography (GECT) in 21 patients with WPW syndrome and 3 normal subjects. In 17 patients, the sites of ACPs were confirmed by epicardial mapping and the result of the surgical division of ACP. In 7PT, the site of ACP grossly agreed to the abnormal initial phase in phase image in 5 out of 6 patients with left cardiac type. In GECT, phase images were generated in short axial, vertical and horizontal long axial sections. In 8 out of 9 patients, the site of ACP was correctly identified by phase images, and in a patient who had two ACPs, initial phase corresponded to one of the two locations. Phase analysis of gated blood pool tomography has advantages for avoiding overlap of blood pools and for estimating three-dimensional propagation of the contraction, and can be a good adjunctive method in patients with WPW syndrome.

Pathway analysis for alternate low-level waste disposal methods

International Nuclear Information System (INIS)

Rao, R.R.; Kozak, M.W.; McCord, J.T.; Olague, N.E.

1992-01-01

The purpose of this paper is to evaluate a complete set of environmental pathways for disposal options and conditions that the Nuclear Regulatory Commission (NRC) may analyze for a low-level radioactive waste (LLW) license application. The regulations pertaining In the past, shallow-land burial has been used for the disposal of low-level radioactive waste. However, with the advent of the State Compact system of LLW disposal, many alternative technologies may be used. The alternative LLW disposal facilities include below- ground vault, tumulus, above-ground vault, shaft, and mine disposal This paper will form the foundation of an update of the previously developed Sandia National Laboratories (SNL)/NRC LLW performance assessment methodology. Based on the pathway assessment for alternative disposal methods, a determination will be made about whether the current methodology can satisfactorily analyze the pathways and phenomena likely to be important for the full range of potential disposal options. We have attempted to be conservative in keeping pathways in the lists that may usually be of marginal importance. In this way we can build confidence that we have spanned the range of cases likely to be encountered at a real site. Results of the pathway assessment indicate that disposal methods can be categorized in groupings based on their depth of disposal. For the deep disposal options of shaft and mine disposal, the key pathways are identical. The shallow disposal options, such as tumulus, shallow-land, and below-ground vault disposal also may be grouped together from a pathway analysis perspective. Above-ground vault disposal cannot be grouped with any of the other disposal options. The pathway analysis shows a definite trend concerning depth of disposal. The above-ground option has the largest number of significant pathways. As the waste becomes more isolated, the number of significant pathways is reduced. Similar to shallow-land burial, it was found that for all

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

Science.gov (United States)

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.

Applied Behavior Analysis

Science.gov (United States)

Szapacs, Cindy

2006-01-01

Teaching strategies that work for typically developing children often do not work for those diagnosed with an autism spectrum disorder. However, teaching strategies that work for children with autism do work for typically developing children. In this article, the author explains how the principles and concepts of Applied Behavior Analysis can be…

An Automated Pipeline for Engineering Many-Enzyme Pathways: Computational Sequence Design, Pathway Expression-Flux Mapping, and Scalable Pathway Optimization.

Science.gov (United States)

Halper, Sean M; Cetnar, Daniel P; Salis, Howard M

2018-01-01

Engineering many-enzyme metabolic pathways suffers from the design curse of dimensionality. There are an astronomical number of synonymous DNA sequence choices, though relatively few will express an evolutionary robust, maximally productive pathway without metabolic bottlenecks. To solve this challenge, we have developed an integrated, automated computational-experimental pipeline that identifies a pathway's optimal DNA sequence without high-throughput screening or many cycles of design-build-test. The first step applies our Operon Calculator algorithm to design a host-specific evolutionary robust bacterial operon sequence with maximally tunable enzyme expression levels. The second step applies our RBS Library Calculator algorithm to systematically vary enzyme expression levels with the smallest-sized library. After characterizing a small number of constructed pathway variants, measurements are supplied to our Pathway Map Calculator algorithm, which then parameterizes a kinetic metabolic model that ultimately predicts the pathway's optimal enzyme expression levels and DNA sequences. Altogether, our algorithms provide the ability to efficiently map the pathway's sequence-expression-activity space and predict DNA sequences with desired metabolic fluxes. Here, we provide a step-by-step guide to applying the Pathway Optimization Pipeline on a desired multi-enzyme pathway in a bacterial host.

The pain, depression, disability pathway in those with low back pain: a moderation analysis of health locus of control.

Science.gov (United States)

Campbell, Paul; Hope, Kate; Dunn, Kate M

2017-01-01

Low back pain (LBP) is common, impacts on the individual and society, and is a major health concern. Psychological consequences of LBP, such as depression, are significant barriers to recovery, but mechanisms for the development of depression are less well understood. One potential mechanism is the individual's health locus of control (HLoC), that is, perception of the level of control an individual has over their health. The objective of this study is to investigate the moderation effect of HLoC on the pain-depression-disability pathway in those with LBP. The design is a nested cross-sectional analysis of two existing cohorts of patients (n=637) who had previously consulted their primary care physician about LBP. Measures were taken of HLoC, pain intensity and interference, depression, disability, and bothersomeness. Structural Equation Modeling analysis was applied to two path models that examined the pain to depression to disability pathway moderated by the HLoC constructs of Internality and Externality, respectively. Critical ratio (CR) difference tests were applied to the coefficients using pairwise comparisons. The results show that both models had an acceptable model fit and pathways were significant. CR tests indicated a significant moderation effect, with stronger pathway coefficients for depression for those who report low Internality (β 0.48), compared to those with high Internality (β 0.28). No moderation effects were found within the Externality model. HLoC Internality significantly moderates the pain-depression pathway in those with LBP, meaning that those who have a low perception of control report greater levels of depression. HLoC may signify depression among people with LBP, and could potentially be a target for intervention.

GenMAPP 2: new features and resources for pathway analysis

Directory of Open Access Journals (Sweden)

Dahlquist Kam D

2007-06-01

Full Text Available Abstract Background Microarray technologies have evolved rapidly, enabling biologists to quantify genome-wide levels of gene expression, alternative splicing, and sequence variations for a variety of species. Analyzing and displaying these data present a significant challenge. Pathway-based approaches for analyzing microarray data have proven useful for presenting data and for generating testable hypotheses. Results To address the growing needs of the microarray community we have released version 2 of Gene Map Annotator and Pathway Profiler (GenMAPP, a new GenMAPP database schema, and integrated resources for pathway analysis. We have redesigned the GenMAPP database to support multiple gene annotations and species as well as custom species database creation for a potentially unlimited number of species. We have expanded our pathway resources by utilizing homology information to translate pathway content between species and extending existing pathways with data derived from conserved protein interactions and coexpression. We have implemented a new mode of data visualization to support analysis of complex data, including time-course, single nucleotide polymorphism (SNP, and splicing. GenMAPP version 2 also offers innovative ways to display and share data by incorporating HTML export of analyses for entire sets of pathways as organized web pages. Conclusion GenMAPP version 2 provides a means to rapidly interrogate complex experimental data for pathway-level changes in a diverse range of organisms.

Applied analysis and differential equations

CERN Document Server

Cârj, Ovidiu

2007-01-01

This volume contains refereed research articles written by experts in the field of applied analysis, differential equations and related topics. Well-known leading mathematicians worldwide and prominent young scientists cover a diverse range of topics, including the most exciting recent developments. A broad range of topics of recent interest are treated: existence, uniqueness, viability, asymptotic stability, viscosity solutions, controllability and numerical analysis for ODE, PDE and stochastic equations. The scope of the book is wide, ranging from pure mathematics to various applied fields such as classical mechanics, biomedicine, and population dynamics.

Social network analysis applied to team sports analysis

CERN Document Server

Clemente, Filipe Manuel; Mendes, Rui Sousa

2016-01-01

Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.

Pathway modeling of microarray data: A case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP)

International Nuclear Information System (INIS)

Ovacik, Meric A.; Sen, Banalata; Euling, Susan Y.; Gaido, Kevin W.; Ierapetritou, Marianthi G.; Androulakis, Ioannis P.

2013-01-01

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 significance 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

Pathway modeling of microarray data: A case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP)

Energy Technology Data Exchange (ETDEWEB)

Ovacik, Meric A. [Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ 08854 (United States); Sen, Banalata [National Center for Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC 27709 (United States); Euling, Susan Y. [National Center for Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Washington, DC 20460 (United States); Gaido, Kevin W. [U.S. Food and Drug Administration, Center for Veterinary Medicine, Office of New Animal Drug Evaluation, Division of Human Food Safety, Rockville, MD 20855 (United States); Ierapetritou, Marianthi G. [Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ 08854 (United States); Androulakis, Ioannis P., E-mail: yannis@rci.rutgers.edu [Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ 08854 (United States); Biomedical Engineering Department, Rutgers University, NJ 08854 (United States)

2013-09-15

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 significance 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.

Integrated In Silico Analysis of Pathway Designs for Synthetic Photo-Electro-Autotrophy.

Directory of Open Access Journals (Sweden)

Michael Volpers

Full Text Available The strong advances in synthetic biology enable the engineering of novel functions and complex biological features in unprecedented ways, such as implementing synthetic autotrophic metabolism into heterotrophic hosts. A key challenge for the sustainable production of fuels and chemicals entails the engineering of synthetic autotrophic organisms that can effectively and efficiently fix carbon dioxide by using sustainable energy sources. This challenge involves the integration of carbon fixation and energy uptake systems. A variety of carbon fixation pathways and several types of photosystems and other energy uptake systems can be chosen and, potentially, modularly combined to design synthetic autotrophic metabolism. Prior to implementation, these designs can be evaluated by the combination of several computational pathway analysis techniques. Here we present a systematic, integrated in silico analysis of photo-electro-autotrophic pathway designs, consisting of natural and synthetic carbon fixation pathways, a proton-pumping rhodopsin photosystem for ATP regeneration and an electron uptake pathway. We integrated Flux Balance Analysis of the heterotrophic chassis Escherichia coli with kinetic pathway analysis and thermodynamic pathway analysis (Max-min Driving Force. The photo-electro-autotrophic designs are predicted to have a limited potential for anaerobic, autotrophic growth of E. coli, given the relatively low ATP regenerating capacity of the proton pumping rhodopsin photosystems and the high ATP maintenance of E. coli. If these factors can be tackled, our analysis indicates the highest growth potential for the natural reductive tricarboxylic acid cycle and the synthetic pyruvate synthase-pyruvate carboxylate -glyoxylate bicycle. Both carbon fixation cycles are very ATP efficient, while maintaining fast kinetics, which also results in relatively low estimated protein costs for these pathways. Furthermore, the synthetic bicycles are highly

Independent component and pathway-based analysis of miRNA-regulated gene expression in a model of type 1 diabetes

Directory of Open Access Journals (Sweden)

Hagedorn Peter H

2011-02-01

Full Text Available Abstract Background Several approaches have been developed for miRNA target prediction, including methods that incorporate expression profiling. However the methods are still in need of improvements due to a high false discovery rate. So far, none of the methods have used independent component analysis (ICA. Here, we developed a novel target prediction method based on ICA that incorporates both seed matching and expression profiling of miRNA and mRNA expressions. The method was applied on a cellular model of type 1 diabetes. Results Microrray profiling identified eight miRNAs (miR-124/128/192/194/204/375/672/708 with differential expression. Applying ICA on the mRNA profiling data revealed five significant independent components (ICs correlating to the experimental conditions. The five ICs also captured the miRNA expressions by explaining >97% of their variance. By using ICA, seven of the eight miRNAs showed significant enrichment of sequence predicted targets, compared to only four miRNAs when using simple negative correlation. The ICs were enriched for miRNA targets that function in diabetes-relevant pathways e.g. type 1 and type 2 diabetes and maturity onset diabetes of the young (MODY. Conclusions In this study, ICA was applied as an attempt to separate the various factors that influence the mRNA expression in order to identify miRNA targets. The results suggest that ICA is better at identifying miRNA targets than negative correlation. Additionally, combining ICA and pathway analysis constitutes a means for prioritizing between the predicted miRNA targets. Applying the method on a model of type 1 diabetes resulted in identification of eight miRNAs that appear to affect pathways of relevance to disease mechanisms in diabetes.

Modelling and Analysis of Biochemical Signalling Pathway Cross-talk

Directory of Open Access Journals (Sweden)

Robin Donaldson

2010-02-01

Full Text Available Signalling pathways are abstractions that help life scientists structure the coordination of cellular activity. Cross-talk between pathways accounts for many of the complex behaviours exhibited by signalling pathways and is often critical in producing the correct signal-response relationship. Formal models of signalling pathways and cross-talk in particular can aid understanding and drive experimentation. We define an approach to modelling based on the concept that a pathway is the (synchronising parallel composition of instances of generic modules (with internal and external labels. Pathways are then composed by (synchronising parallel composition and renaming; different types of cross-talk result from different combinations of synchronisation and renaming. We define a number of generic modules in PRISM and five types of cross-talk: signal flow, substrate availability, receptor function, gene expression and intracellular communication. We show that Continuous Stochastic Logic properties can both detect and distinguish the types of cross-talk. The approach is illustrated with small examples and an analysis of the cross-talk between the TGF-b/BMP, WNT and MAPK pathways.

A framework for the exergy analysis of future transport pathways: Application for the United Kingdom transport system 2010–2050

International Nuclear Information System (INIS)

Byers, Edward A.; Gasparatos, Alexandros; Serrenho, André C.

2015-01-01

Exergy analysis has been used to quantify the historical resource use efficiency and environmental impact of transport systems. However, few exergy studies have explored future transport pathways. This study aims to, (a) develop a conceptual framework for the exergy analysis of multiple future transport and electricity pathways, (b) apply this framework to quantify future resource consumption and service delivery patterns, (c) discuss the policy-relevant results that exergy studies of future transport systems can offer. Multiple transport and electricity pathways developed by the UK Government are used to explore changes in energy use, useful work delivery and greenhouse gas emissions. In passenger transport, ambitious electrification results in a 20% increase of useful work delivery, whilst reducing GHG emissions and energy consumption by 65%. For freight, international shipping and aviation, smaller exergy efficiency improvements make useful work delivery and greenhouse gas emissions highly dependent on transport demand. Passenger transport electrification brings a step-change in useful work delivery, which if accompanied by low-carbon electricity, significantly reduces greenhouse gas emissions. The efficiency of low-carbon electricity systems is significant for useful work delivery, but not dominant across the scenarios explored. High penetration of renewables and electrified transport is the most resource-efficient combination in this context. - Highlights: • Develop an exergy analysis framework of future transport pathways and apply it to UK. • Electrification of personal transport brings step change in useful work delivery. • Efficiency of electricity supply becomes significant once transport is electrified. • High electrification increases useful work (+20%) and reduces emissions (−65%). • High penetration of renewables and electrified transport is most resource efficient

Predicting metabolic pathways by sub-network extraction.

Science.gov (United States)

Faust, Karoline; van Helden, Jacques

2012-01-01

Various methods result in groups of functionally related genes obtained from genomes (operons, regulons, syntheny groups, and phylogenetic profiles), transcriptomes (co-expression groups) and proteomes (modules of interacting proteins). When such groups contain two or more enzyme-coding genes, graph analysis methods can be applied to extract a metabolic pathway that interconnects them. We describe here the way to use the Pathway extraction tool available on the NeAT Web server ( http://rsat.ulb.ac.be/neat/ ) to piece together the metabolic pathway from a group of associated, enzyme-coding genes. The tool identifies the reactions that can be catalyzed by the products of the query genes (seed reactions), and applies sub-graph extraction algorithms to extract from a metabolic network a sub-network that connects the seed reactions. This sub-network represents the predicted metabolic pathway. We describe here the pathway prediction process in a step-by-step way, give hints about the main parametric choices, and illustrate how this tool can be used to extract metabolic pathways from bacterial genomes, on the basis of two study cases: the isoleucine-valine operon in Escherichia coli and a predicted operon in Cupriavidus (Ralstonia) metallidurans.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

Science.gov (United States)

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.

Effects of clinical pathways in the joint replacement: a meta-analysis

Directory of Open Access Journals (Sweden)

Faggiano F

2009-07-01

Full Text Available Abstract Background A meta-analysis was performed to evaluate the use of clinical pathways for hip and knee joint replacements when compared with standard medical care. The impact of clinical pathways was evaluated assessing the major outcomes of in-hospital hip and knee joint replacement processes: postoperative complications, number of patients discharged at home, length of in-hospital stay and direct costs. Methods Medline, Cinahl, Embase and the Cochrane Central Register of Controlled Trials were searched. The search was performed from 1975 to 2007. Each study was assessed independently by two reviewers. The assessment of methodological quality of the included studies was based on the Jadad methodological approach and on the New Castle Ottawa Scale. Data analysis abided by the guidelines set out by The Cochrane Collaboration regarding statistical methods. Meta-analyses were performed using RevMan software, version 4.2. Results Twenty-two studies met the study inclusion criteria and were included in the meta-analysis for a total sample of 6,316 patients. The aggregate overall results showed significantly fewer patients suffering postoperative complications in the clinical pathways group when compared with the standard care group. A shorter length of stay in the clinical pathway group was also observed and lower costs during hospital stay were associated with the use of the clinical pathways. No significant differences were found in the rates of discharge to home. Conclusion The results of this meta-analysis show that clinical pathways can significantly improve the quality of care even if it is not possible to conclude that the implementation of clinical pathways is a cost-effective process, because none of the included studies analysed the cost of the development and implementation of the pathways. Based on the results we assume that pathways have impact on the organisation of care if the care process is structured in a standardised way

Applied survival analysis using R

CERN Document Server

Moore, Dirk F

2016-01-01

Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics...

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

Science.gov (United States)

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.

Applied regression analysis a research tool

CERN Document Server

Pantula, Sastry; Dickey, David

1998-01-01

Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...

Biomarker Identification and Pathway Analysis by Serum Metabolomics of Lung Cancer

Directory of Open Access Journals (Sweden)

Yingrong Chen

2015-01-01

Full Text Available Lung cancer is one of the most common causes of cancer death, for which no validated tumor biomarker is sufficiently accurate to be useful for diagnosis. Additionally, the metabolic alterations associated with the disease are unclear. In this study, we investigated the construction, interaction, and pathways of potential lung cancer biomarkers using metabolomics pathway analysis based on the Kyoto Encyclopedia of Genes and Genomes database and the Human Metabolome Database to identify the top altered pathways for analysis and visualization. We constructed a diagnostic model using potential serum biomarkers from patients with lung cancer. We assessed their specificity and sensitivity according to the area under the curve of the receiver operator characteristic (ROC curves, which could be used to distinguish patients with lung cancer from normal subjects. The pathway analysis indicated that sphingolipid metabolism was the top altered pathway in lung cancer. ROC curve analysis indicated that glycerophospho-N-arachidonoyl ethanolamine (GpAEA and sphingosine were potential sensitive and specific biomarkers for lung cancer diagnosis and prognosis. Compared with the traditional lung cancer diagnostic biomarkers carcinoembryonic antigen and cytokeratin 19 fragment, GpAEA and sphingosine were as good or more appropriate for detecting lung cancer. We report our identification of potential metabolic diagnostic and prognostic biomarkers of lung cancer and clarify the metabolic alterations in lung cancer.

Conversation Analysis in Applied Linguistics

DEFF Research Database (Denmark)

Kasper, Gabriele; Wagner, Johannes

2014-01-01

on applied CA, the application of basic CA's principles, methods, and findings to the study of social domains and practices that are interactionally constituted. We consider three strands—foundational, social problem oriented, and institutional applied CA—before turning to recent developments in CA research...... on learning and development. In conclusion, we address some emerging themes in the relationship of CA and applied linguistics, including the role of multilingualism, standard social science methods as research objects, CA's potential for direct social intervention, and increasing efforts to complement CA......For the last decade, conversation analysis (CA) has increasingly contributed to several established fields in applied linguistics. In this article, we will discuss its methodological contributions. The article distinguishes between basic and applied CA. Basic CA is a sociological endeavor concerned...

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Directory of Open Access Journals (Sweden)

Zhongqi Ge

2018-04-01

Full Text Available Summary: Protein ubiquitination is a dynamic and reversible process of adding single ubiquitin molecules or various ubiquitin chains to target proteins. Here, using multidimensional omic data of 9,125 tumor samples across 33 cancer types from The Cancer Genome Atlas, we perform comprehensive molecular characterization of 929 ubiquitin-related genes and 95 deubiquitinase genes. Among them, we systematically identify top somatic driver candidates, including mutated FBXW7 with cancer-type-specific patterns and amplified MDM2 showing a mutually exclusive pattern with BRAF mutations. Ubiquitin pathway genes tend to be upregulated in cancer mediated by diverse mechanisms. By integrating pan-cancer multiomic data, we identify a group of tumor samples that exhibit worse prognosis. These samples are consistently associated with the upregulation of cell-cycle and DNA repair pathways, characterized by mutated TP53, MYC/TERT amplification, and APC/PTEN deletion. Our analysis highlights the importance of the ubiquitin pathway in cancer development and lays a foundation for developing relevant therapeutic strategies. : Ge et al. analyze a cohort of 9,125 TCGA samples across 33 cancer types to provide a comprehensive characterization of the ubiquitin pathway. They detect somatic driver candidates in the ubiquitin pathway and identify a cluster of patients with poor survival, highlighting the importance of this pathway in cancer development. Keywords: ubiquitin pathway, pan-cancer analysis, The Cancer Genome Atlas, tumor subtype, cancer prognosis, therapeutic targets, biomarker, FBXW7

Pathway analysis of GWAS provides new insights into genetic susceptibility to 3 inflammatory diseases.

Directory of Open Access Journals (Sweden)

Hariklia Eleftherohorinou

2009-11-01

Full Text Available Although the introduction of genome-wide association studies (GWAS have greatly increased the number of genes associated with common diseases, only a small proportion of the predicted genetic contribution has so far been elucidated. Studying the cumulative variation of polymorphisms in multiple genes acting in functional pathways may provide a complementary approach to the more common single SNP association approach in understanding genetic determinants of common disease. We developed a novel pathway-based method to assess the combined contribution of multiple genetic variants acting within canonical biological pathways and applied it to data from 14,000 UK individuals with 7 common diseases. We tested inflammatory pathways for association with Crohn's disease (CD, rheumatoid arthritis (RA and type 1 diabetes (T1D with 4 non-inflammatory diseases as controls. Using a variable selection algorithm, we identified variants responsible for the pathway association and evaluated their use for disease prediction using a 10 fold cross-validation framework in order to calculate out-of-sample area under the Receiver Operating Curve (AUC. The generalisability of these predictive models was tested on an independent birth cohort from Northern Finland. Multiple canonical inflammatory pathways showed highly significant associations (p 10(-3-10(-20 with CD, T1D and RA. Variable selection identified on average a set of 205 SNPs (149 genes for T1D, 350 SNPs (189 genes for RA and 493 SNPs (277 genes for CD. The pattern of polymorphisms at these SNPS were found to be highly predictive of T1D (91% AUC and RA (85% AUC, and weakly predictive of CD (60% AUC. The predictive ability of the T1D model (without any parameter refitting had good predictive ability (79% AUC in the Finnish cohort. Our analysis suggests that genetic contribution to common inflammatory diseases operates through multiple genes interacting in functional pathways.

GWAS-based pathway analysis differentiates between fluid and crystallized intelligence.

Science.gov (United States)

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.

Pathway Analysis of miR-181a in Hypopharyngeal Squamous Cell ...

African Journals Online (AJOL)

syakima

2012-03-15

Mar 15, 2012 ... Key words: MicroRNA, head and neck cancer, miR-181a, pathway analysis, luciferase assay, FaDu cell line, transfection ..... prostate carcinoma and glioblastoma cells. Nucleic Acids .... WNT pathway in oral cancer: epigenetic.

CRITICAL RADIONUCLIDE AND PATHWAY ANALYSIS FOR THE SAVANNAH RIVER SITE

Energy Technology Data Exchange (ETDEWEB)

Jannik, T.

2011-08-30

This report is an update to the analysis, Assessment of SRS Radiological Liquid and Airborne Contaminants and Pathways, that was performed in 1997. An electronic version of this large original report is included in the attached CD to this report. During the operational history (1954 to the present) of the Savannah River Site (SRS), many different radionuclides have been released to the environment from the various production facilities. However, as will be shown by this updated radiological critical contaminant/critical pathway analysis, only a small number of the released radionuclides have been significant contributors to potential doses and risks to offsite people. The analysis covers radiological releases to the atmosphere and to surface waters, the principal media that carry contaminants offsite. These releases potentially result in exposure to offsite people. The groundwater monitoring performed at the site shows that an estimated 5 to 10% of SRS has been contaminated by radionuclides, no evidence exists from the extensive monitoring performed that groundwater contaminated with these constituents has migrated off the site (SRS 2011). Therefore, with the notable exception of radiological source terms originating from shallow surface water migration into site streams, onsite groundwater was not considered as a potential exposure pathway to offsite people. In addition, in response to the Department of Energy's (DOE) Order 435.1, several Performance Assessments (WSRC 2008; LWO 2009; SRR 2010; SRR 2011) and a Comprehensive SRS Composite Analysis (SRNO 2010) have recently been completed at SRS. The critical radionuclides and pathways identified in these extensive reports are discussed and, where applicable, included in this analysis.

Energy pathway analysis - a hydrogen fuel cycle framework for system studies

International Nuclear Information System (INIS)

Badin, J.S.; Tagore, S.

1997-01-01

An analytical framework has been developed that can be used to estimate a range of life-cycle costs and impacts that result from the incremental production, storage, transport, and use of different fuels or energy carriers, such as hydrogen, electricity, natural gas, and gasoline. This information is used in a comparative analysis of energy pathways. The pathways provide the U.S. Department of Energy (DOE) with an indication of near-, mid-, and long-term technologies that have the greatest potential for advancement and can meet the cost goals. The methodology and conceptual issues are discussed. Also presented are results for selected pathways from the E3 (Energy, Economics, Emissions) Pathway Analysis Model. This model will be expanded to consider networks of pathways and to be compatible with a linear programming optimization processor. Scenarios and sets of constraints (energy demands, sources, emissions) will be defined so the effects on energy transformation activities included in the solution and on the total optimized system cost can be investigated. This evaluation will be used as a guide to eliminate technically feasible pathways if they are not cost effective or do not meet the threshold requirements for the market acceptance. (Author)

PathNet: a tool for pathway analysis using topological information

Directory of Open Access Journals (Sweden)

Dutta Bhaskar

2012-09-01

Full Text Available Abstract Background Identification of canonical pathways through enrichment of differentially expressed genes in a given pathway is a widely used method for interpreting gene lists generated from high-throughput experimental studies. However, most algorithms treat pathways as sets of genes, disregarding any inter- and intra-pathway connectivity information, and do not provide insights beyond identifying lists of pathways. Results We developed an algorithm (PathNet that utilizes the connectivity information in canonical pathway descriptions to help identify study-relevant pathways and characterize non-obvious dependencies and connections among pathways using gene expression data. PathNet considers both the differential expression of genes and their pathway neighbors to strengthen the evidence that a pathway is implicated in the biological conditions characterizing the experiment. As an adjunct to this analysis, PathNet uses the connectivity of the differentially expressed genes among all pathways to score pathway contextual associations and statistically identify biological relations among pathways. In this study, we used PathNet to identify biologically relevant results in two Alzheimer’s disease microarray datasets, and compared its performance with existing methods. Importantly, PathNet identified de-regulation of the ubiquitin-mediated proteolysis pathway as an important component in Alzheimer’s disease progression, despite the absence of this pathway in the standard enrichment analyses. Conclusions PathNet is a novel method for identifying enrichment and association between canonical pathways in the context of gene expression data. It takes into account topological information present in pathways to reveal biological information. PathNet is available as an R workspace image from http://www.bhsai.org/downloads/pathnet/.

Applying causal mediation analysis to personality disorder research.

Science.gov (United States)

Walters, Glenn D

2018-01-01

This article is designed to address fundamental issues in the application of causal mediation analysis to research on personality disorders. Causal mediation analysis is used to identify mechanisms of effect by testing variables as putative links between the independent and dependent variables. As such, it would appear to have relevance to personality disorder research. It is argued that proper implementation of causal mediation analysis requires that investigators take several factors into account. These factors are discussed under 5 headings: variable selection, model specification, significance evaluation, effect size estimation, and sensitivity testing. First, care must be taken when selecting the independent, dependent, mediator, and control variables for a mediation analysis. Some variables make better mediators than others and all variables should be based on reasonably reliable indicators. Second, the mediation model needs to be properly specified. This requires that the data for the analysis be prospectively or historically ordered and possess proper causal direction. Third, it is imperative that the significance of the identified pathways be established, preferably with a nonparametric bootstrap resampling approach. Fourth, effect size estimates should be computed or competing pathways compared. Finally, investigators employing the mediation method are advised to perform a sensitivity analysis. Additional topics covered in this article include parallel and serial multiple mediation designs, moderation, and the relationship between mediation and moderation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Concept analysis of culture applied to nursing.

Science.gov (United States)

Marzilli, Colleen

2014-01-01

Culture is an important concept, especially when applied to nursing. A concept analysis of culture is essential to understanding the meaning of the word. This article applies Rodgers' (2000) concept analysis template and provides a definition of the word culture as it applies to nursing practice. This article supplies examples of the concept of culture to aid the reader in understanding its application to nursing and includes a case study demonstrating components of culture that must be respected and included when providing health care.

Moving Forward: Positive Behavior Support and Applied Behavior Analysis

Science.gov (United States)

Tincani, Matt

2007-01-01

A controversy has emerged about the relationship between positive behavior support and applied behavior analysis. Some behavior analysts suggest that positive behavior support and applied behavior analysis are the same (e.g., Carr & Sidener, 2002). Others argue that positive behavior support is harmful to applied behavior analysis (e.g., Johnston,…

Pathway analysis concepts for radiological impact assessment

International Nuclear Information System (INIS)

Moroney, J.R.

1992-06-01

The concepts underlying exposure pathways analysis are outlined with reference to the features of the two broad types of radionuclide transport models now in use - dynamic and steady-state - and the methods for constructing and developing them. By way of illustration, representative radiation doses are estimated for the four main exposure pathways likely to be involved in the land application of effluent water from Retention Pond 2 of Ranger Uranium Mines. These include: external irradiation by 226 Ra and natural uranium (Un at) in soil, ingestion of 226 Ra and Un at in food, inhalation of 222 Rn daughter products from 226 Rn in soil, and inhalation of 226 Ra and Un at in airborne dust resuspended from soil. Consideration has been given to local residents pursuing a traditional lifestyle on conclusion of the land application program. Because of the possible importance of the contribution from resuspended dust, currently available data are explored in refining the methodology for the pathway and developing a more appropriate model for it. 37 refs., 9 tabs., 6 figs

Microarray Study of Pathway Analysis Expression Profile Associated with MicroRNA-29a with Regard to Murine Cholestatic Liver Injuries

Directory of Open Access Journals (Sweden)

Sung-Chou Li

2016-03-01

Full Text Available Accumulating evidence demonstrates that microRNA-29 (miR-29 expression is prominently decreased in patients with hepatic fibrosis, which consequently stimulates hepatic stellate cells’ (HSCs activation. We used a cDNA microarray study to gain a more comprehensive understanding of genome-wide gene expressions by adjusting miR-29a expression in a bile duct-ligation (BDL animal model. Methods: Using miR-29a transgenic mice and wild-type littermates and applying the BDL mouse model, we characterized the function of miR-29a with regard to cholestatic liver fibrosis. Pathway enrichment analysis and/or specific validation were performed for differentially expressed genes found within the comparisons. Results: Analysis of the microarray data identified a number of differentially expressed genes due to the miR-29a transgene, BDL, or both. Additional pathway enrichment analysis revealed that TGF-β signaling had a significantly differential activated pathway depending on the occurrence of miR-29a overexpression or the lack thereof. Furthermore, overexpression was found to elicit changes in Wnt/β-catenin after BDL. Conclusion: This study verified that an elevated miR-29a level could alleviate liver fibrosis caused by cholestasis. Furthermore, the protective effects of miR-29a correlate with the downregulation of TGF-β and associated with Wnt/β-catenin signal pathway following BDL.

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

Science.gov (United States)

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

Applied neuroanatomy elective to reinforce and promote engagement with neurosensory pathways using interactive and artistic activities.

Science.gov (United States)

Dao, Vinh; Yeh, Pon-Hsiu; Vogel, Kristine S; Moore, Charleen M

2015-01-01

One in six Americans is currently affected by neurologic disease. As the United States population ages, the number of neurologic complaints is expected to increase. Thus, there is a pressing need for more neurologists as well as more neurology training in other specialties. Often interest in neurology begins during medical school, so improving education in medical neural courses is a critical step toward producing more neurologists and better neurology training in other specialists. To this end, a novel applied neuroanatomy elective was designed at the University of Texas Health Science Center at San Antonio (UTHSCSA) to complement the traditional first-year medical neuroscience course and promote engagement and deep learning of the material with a focus on neurosensory pathways. The elective covered four neurosensory modalities (proprioception/balance, vision, auditory, and taste/olfaction) over four sessions, each with a short classroom component and a much longer activity component. At each session, students reviewed the neurosensory pathways through structured presentations and then applied them to preplanned interactive activities, many of which allowed students to utilize their artistic talents. Students were required to complete subjective pre-course and post-course surveys and reflections. The survey results and positive student comments suggest that the elective was a valuable tool when used in parallel with the traditional medical neuroscience course in promoting engagement and reinforcement of the neurosensory material. © 2014 American Association of Anatomists.

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

Science.gov (United States)

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.

Critical Radionuclide and Pathway Analysis for the Savannah River Site, 2016 Update

Energy Technology Data Exchange (ETDEWEB)

Jannik, Tim [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Hartman, Larry [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2016-09-08

During the operational history of Savannah River Site, many different radionuclides have been released from site facilities. However, as shown in this analysis, only a relatively small number of the released radionuclides have been significant contributors to doses to the offsite public. This report is an update to the 2011 analysis, Critical Radionuclide and Pathway Analysis for the Savannah River Site. SRS-based Performance Assessments for E-Area, Saltstone, F-Tank Farm, H-Tank Farm, and a Comprehensive SRS Composite Analysis have been completed. The critical radionuclides and pathways identified in those extensive reports are also detailed and included in this analysis.

Path analysis suggests phytoene accumulation is the key step limiting the carotenoid pathway in white carrot roots

Directory of Open Access Journals (Sweden)

Carlos Antonio Fernandes Santos

2005-01-01

Full Text Available Two F2 carrot (Daucus carota L. populations (orange rooted Brasilia x very dark orange rooted High Carotene Mass - HCM cross and the dark orange rooted cultivated variety B493 x white rooted wild carrot Queen Anne's Lace - QAL cross with very unrelated genetic backgrounds were used to investigate intrinsic factors limiting carotenoid accumulation in carrots by applying phenotypic correlation and path analysis to study the relationships between major root carotenes, root color and several other morphological traits. Most of the correlations between traits were close and agreed in sign between the two populations. Root weight had a moderate to highly significant positive correlation with leaf length, root length and top and middle root diameter. Although phenotypic correlations failed to identify the order of the substrates and products in the carotenoid pathway the correct order of substrates and products (phytoene -> zeta-carotene -> lycopene was identified in the causal diagram of beta-carotene for the Brasilia x HCM population. Path analysis of beta-carotene synthesis in the B493 x QAL population suggested that selection for root carotenes had little effect on plant morphological traits. Causal model of beta-carotene and lycopene in the B493 x QAL population suggested that phytoene synthesis is the key step limiting the carotenoid pathway in white carrots. Path analysis, first presented by Sewall Wright to study quantitative traits, appears to be a powerful statistical approach for the identification of key compounds in complex pathways.

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

Directory of Open Access Journals (Sweden)

Jordi Leno-Colorado

2017-07-01

Full Text Available 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 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 processes. Purifying selection was, nevertheless, stronger in significantly differentiated pathways than in random pathways, mainly in Europe. We conclude that pathway analysis facilitates the biological interpretation of genome-wide studies. Notably, in the case of pig, behavior played an important role, among other

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

Science.gov (United States)

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 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 processes. Purifying selection was, nevertheless, stronger in significantly differentiated pathways than in random pathways, mainly in Europe. We conclude that pathway analysis facilitates the biological interpretation of genome-wide studies. Notably, in the case of pig, behavior played an important role, among other physiological

Endocrine-disrupting Chemicals: Review of Toxicological Mechanisms Using Molecular Pathway Analysis

Science.gov (United States)

Yang, Oneyeol; Kim, Hye Lim; Weon, Jong-Il; Seo, Young Rok

2015-01-01

Endocrine disruptors are known to cause harmful effects to human through various exposure routes. These chemicals mainly appear to interfere with the endocrine or hormone systems. As importantly, numerous studies have demonstrated that the accumulation of endocrine disruptors can induce fatal disorders including obesity and cancer. Using diverse biological tools, the potential molecular mechanisms related with these diseases by exposure of endocrine disruptors. Recently, pathway analysis, a bioinformatics tool, is being widely used to predict the potential mechanism or biological network of certain chemicals. In this review, we initially summarize the major molecular mechanisms involved in the induction of the above mentioned diseases by endocrine disruptors. Additionally, we provide the potential markers and signaling mechanisms discovered via pathway analysis under exposure to representative endocrine disruptors, bisphenol, diethylhexylphthalate, and nonylphenol. The review emphasizes the importance of pathway analysis using bioinformatics to finding the specific mechanisms of toxic chemicals, including endocrine disruptors. PMID:25853100

Analysis of Geothermal Pathway in the Metamorphic Area, Northeastern Taiwan

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Pathway Distiller - multisource biological pathway consolidation.

Science.gov (United States)

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

Building an applied activation analysis centre

International Nuclear Information System (INIS)

Bartosek, J.; Kasparec, I.; Masek, J.

1972-01-01

Requirements are defined and all available background material is reported and discussed for the building up of a centre of applied activation analysis in Czechoslovakia. A detailed analysis of potential users and the centre's envisaged availability is also presented as part of the submitted study. A brief economic analysis is annexed. The study covers the situation up to the end of 1972. (J.K.)

Environmental-pathways analysis for evaluation of a low-level waste disposal site

International Nuclear Information System (INIS)

Lee, D.W.; Ketelle, R.H.; Pin, F.G.; Hill, G.S.

1983-01-01

The suitability of a site for the shallow land burial of low-level waste is evaluated by an environmental-pathways analysis. The environmental-pathways analysis considers the probable paths for the transport of contamination to man and models the long-term transport of contamination to determine the resulting dose-to-man. The model of the long-term transport of contamination is developed for a proposed site using data obtained from a comprehensive laboratory and field investigation. The proposed site is located at the US Department of Energy Portsmouth Reservation, Piketon, Ohio and is planned to accept low-level radioactive waste generated by the enrichment of uranium. Laboratory studies were performed to characterize the waste and determine the wastes' leaching and retardation characteristics with site soils and groundwater. Comprehensive drilling, sampling and laboratory investigations were performed to provide the necessary information for interpreting the site's geology and hydrology. Field tests were performed to further quantify the site's hydrology. The pathway of greatest concern is the migration of contaminated groundwater and subsequent consumption by man. This pathway was modeled using a numerical simulation of the long-term transport of contamination. Conservative scenarios were developed for leachate generation and migration through the geohydrologic system. The dose-to-man determined from the pathways analysis formed the basis for evaluating site acceptability and providing recommendations for site design and development

Environmental pathways analysis for evaluation of a low-level waste disposal site

International Nuclear Information System (INIS)

Lee, D.W.; Ketelle, R.H.; Pin, F.G.; Hill, G.S.

1984-01-01

The suitability of a site for the shallow land burial of low-level waste is evaluated by an environmental pathways analysis. The environmental pathways analysis considers the probable paths for the transport of contamination to man and models the long-term transport of contamination to determine the resulting dose to man. The model of the long-term transport of contamination is developed for a proposed site using data obtained from a comprehensive laboratory and field investigation. The proposed site is located at the US Department of Energy Portsmouth Reservation, Piketon, Ohio, and is planned to accept low-level radioactive waste generated by the enrichment of uranium. Laboratory studies were performed to characterize the waste and determine the wastes' leaching and retardation characteristics with site soils and groundwater. Comprehensive drilling, sampling and laboratory investigations were performed to provide the necessary information for interpreting the site's geology and hydrology. Field tests were performed to further quantify the site's hydrology. The pathway of greatest concern is the migration of contaminated groundwater and subsequent consumption by man. This pathway was modelled using a numerical simulation of the long-term transport of contamination. Conservative scenarios were developed for leachate generation and migration through the geohydrologic system. The dose to man determined from the pathways analysis formed the basis for evaluating site acceptability and providing recommendations for site design and development. (author)

Caldwell University's Department of Applied Behavior Analysis.

Science.gov (United States)

Reeve, Kenneth F; Reeve, Sharon A

2016-05-01

Since 2004, faculty members at Caldwell University have developed three successful graduate programs in Applied Behavior Analysis (i.e., PhD, MA, non-degree programs), increased program faculty from two to six members, developed and operated an on-campus autism center, and begun a stand-alone Applied Behavior Analysis Department. This paper outlines a number of strategies used to advance these initiatives, including those associated with an extensive public relations campaign. We also outline challenges that have limited our programs' growth. These strategies, along with a consideration of potential challenges, might prove useful in guiding academicians who are interested in starting their own programs in behavior analysis.

Integrated bioinformatics analysis reveals key candidate genes and pathways in breast cancer.

Science.gov (United States)

Wang, Yuzhi; Zhang, Yi; Huang, Qian; Li, Chengwen

2018-04-19

Breast cancer (BC) is the leading malignancy in women worldwide, yet relatively little is known about the genes and signaling pathways involved in BC tumorigenesis and progression. The present study aimed to elucidate potential key candidate genes and pathways in BC. Five gene expression profile data sets (GSE22035, GSE3744, GSE5764, GSE21422 and GSE26910) were downloaded from the Gene Expression Omnibus (GEO) database, which included data from 113 tumorous and 38 adjacent non‑tumorous tissue samples. Differentially expressed genes (DEGs) were identified using t‑tests in the limma R package. These DEGs were subsequently investigated by pathway enrichment analysis and a protein‑protein interaction (PPI) network was constructed. The most significant module from the PPI network was selected for pathway enrichment analysis. In total, 227 DEGs were identified, of which 82 were upregulated and 145 were downregulated. Pathway enrichment analysis results revealed that the upregulated DEGs were mainly enriched in 'cell division', the 'proteinaceous extracellular matrix (ECM)', 'ECM structural constituents' and 'ECM‑receptor interaction', whereas downregulated genes were mainly enriched in 'response to drugs', 'extracellular space', 'transcriptional activator activity' and the 'peroxisome proliferator‑activated receptor signaling pathway'. The PPI network contained 174 nodes and 1,257 edges. DNA topoisomerase 2‑a, baculoviral inhibitor of apoptosis repeat‑containing protein 5, cyclin‑dependent kinase 1, G2/mitotic‑specific cyclin‑B1 and kinetochore protein NDC80 homolog were identified as the top 5 hub genes. Furthermore, the genes in the most significant module were predominantly involved in 'mitotic nuclear division', 'mid‑body', 'protein binding' and 'cell cycle'. In conclusion, the DEGs, relative pathways and hub genes identified in the present study may aid in understanding of the molecular mechanisms underlying BC progression and provide

A techno-economic analysis of EU renewable electricity policy pathways in 2030

International Nuclear Information System (INIS)

Río, Pablo del; Resch, Gustav; Ortner, Andre; Liebmann, Lukas; Busch, Sebastian; Panzer, Christian

2017-01-01

The aim of this paper is to assess several pathways of a harmonised European policy framework for supporting renewable electricity (RES-E) in a 2030 horizon according to different criteria. The pathways combine two main dimensions: degrees of harmonisation and instruments and design elements. A quantitative model-based analysis with the Green-X model is provided. The results of the simulations show that there are small differences between the evaluated cases regarding effectiveness. All the policy pathways score similarly with respect to RES-E deployment, i.e., with different degrees of harmonisation and whether using a feed-in tariff, a feed-in premium, a quota system with banding or a quota without banding scheme. In contrast, the policy costs clearly differ across the pathways, but the differences can mostly be attributed to the instruments rather than to the degrees of harmonisation. This is also the case with other criteria (static and dynamic efficiency and the socioeconomic and environmental benefits in terms of CO2 emissions and fossil fuels avoided). Both the degree of harmonisation and the choice of instrument influence the distribution of support costs across countries. Finally, our findings suggest that keeping strengthened national support leads to similar results to other policy pathways. - Highlights: • Pathways of a harmonised European policy framework for renewable electricity in 2030. • Two main dimensions: degrees of harmonisation and instruments. • A quantitative model-based analysis based on the Green-X model. • Small differences between the pathways regarding the effectiveness criterion. • Important differences between pathways regarding other assessment criteria.

Analysis of the interaction between experimental and applied behavior analysis.

Science.gov (United States)

Virues-Ortega, Javier; Hurtado-Parrado, Camilo; Cox, Alison D; Pear, Joseph J

2014-01-01

To study the influences between basic and applied research in behavior analysis, we analyzed the coauthorship interactions of authors who published in JABA and JEAB from 1980 to 2010. We paid particular attention to authors who published in both JABA and JEAB (dual authors) as potential agents of cross-field interactions. We present a comprehensive analysis of dual authors' coauthorship interactions using social networks methodology and key word analysis. The number of dual authors more than doubled (26 to 67) and their productivity tripled (7% to 26% of JABA and JEAB articles) between 1980 and 2010. Dual authors stood out in terms of number of collaborators, number of publications, and ability to interact with multiple groups within the field. The steady increase in JEAB and JABA interactions through coauthors and the increasing range of topics covered by dual authors provide a basis for optimism regarding the progressive integration of basic and applied behavior analysis. © Society for the Experimental Analysis of Behavior.

Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

DEFF Research Database (Denmark)

Huang, Sijia; Chong, Nicole; Lewis, Nathan

2016-01-01

diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...... metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease...

Applied Behavior Analysis and Statistical Process Control?

Science.gov (United States)

Hopkins, B. L.

1995-01-01

Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

Science.gov (United States)

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

Tomographic phase analysis to detect the site of accessory conduction pathway in Wolff-Parkinson-White syndrome

International Nuclear Information System (INIS)

Nakajima, K.; Bunko, H.; Tada, A.; Tonami, N.; Taki, J.; Nanbu, I.; Hisada, K.; Misaki, T.; Iwa, T.

1984-01-01

Phase analysis has been applied to Wolff-Parkinson-White syndrome (WPW) to detect the site of accessory conduction pathway (ACP); however, there was a limitation to estimate the precise location of ACP by planar phase analysis. In this study, the authors applied phase analysis to gated blood pool tomography. Twelve patients with WPW who underwent epicardial mapping and surgical division of ACP were studied by both of gated emission computed tomography (GECT) and routine gated blood pool study (GBPS). The GBPS was performed with Tc-99m red blood cells in multiple projections; modified left anterior oblique, right anterior oblique and/or left lateral views. In GECT, short axial, horizontal and vertical long axial blood pool images were reconstructed. Phase analysis was performed using fundamental frequency of the Fourier transform in both GECT and GBPS images, and abnormal initial contractions on both the planar and tomographic phase analysis were compared with the location of surgically confirmed ACPs. In planar phase analysis, abnormal initial phase was identified in 7 out of 12 (58%) patients, while in tomographic phase analysis, the localization of ACP was predicted in 11 out of 12 (92%) patients. Tomographic phase analysis is superior to planar phase images in 8 out of 12 patients to estimate the location of ACP. Phase analysis by GECT can avoid overlap of blood pool in cardiac chambers and has advantage to identify the propagation of phase three-dimensionally. Tomographic phase analysis is a good adjunctive method for patients with WPW to estimate the site of ACP

Tomographic phase analysis to detect the site of accessory conduction pathway in Wolff-Parkinson-White syndrome

Energy Technology Data Exchange (ETDEWEB)

Nakajima, K.; Bunko, H.; Tada, A.; Tonami, N.; Taki, J.; Nanbu, I.; Hisada, K.; Misaki, T.; Iwa, T.

1984-01-01

Phase analysis has been applied to Wolff-Parkinson-White syndrome (WPW) to detect the site of accessory conduction pathway (ACP); however, there was a limitation to estimate the precise location of ACP by planar phase analysis. In this study, the authors applied phase analysis to gated blood pool tomography. Twelve patients with WPW who underwent epicardial mapping and surgical division of ACP were studied by both of gated emission computed tomography (GECT) and routine gated blood pool study (GBPS). The GBPS was performed with Tc-99m red blood cells in multiple projections; modified left anterior oblique, right anterior oblique and/or left lateral views. In GECT, short axial, horizontal and vertical long axial blood pool images were reconstructed. Phase analysis was performed using fundamental frequency of the Fourier transform in both GECT and GBPS images, and abnormal initial contractions on both the planar and tomographic phase analysis were compared with the location of surgically confirmed ACPs. In planar phase analysis, abnormal initial phase was identified in 7 out of 12 (58%) patients, while in tomographic phase analysis, the localization of ACP was predicted in 11 out of 12 (92%) patients. Tomographic phase analysis is superior to planar phase images in 8 out of 12 patients to estimate the location of ACP. Phase analysis by GECT can avoid overlap of blood pool in cardiac chambers and has advantage to identify the propagation of phase three-dimensionally. Tomographic phase analysis is a good adjunctive method for patients with WPW to estimate the site of ACP.

Applied multivariate statistical analysis

CERN Document Server

Härdle, Wolfgang Karl

2015-01-01

Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners.  It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added.  All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior.  All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...

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

Science.gov (United States)

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.

Metabolic-flux analysis of hydrogen production pathway in Citrobacter amalonaticus Y19

Energy Technology Data Exchange (ETDEWEB)

Oh, You-Kwan; Kim, Mi-Sun [Bioenergy Research Center, Korea Institute of Energy Research, Daejeon 305-343 (Korea); Kim, Heung-Joo; Park, Sunghoon [Department of Chemical and Biochemical Engineering and Institute for Environmental Technology and Industry, Pusan National University, Busan 609-735 (Korea); Ryu, Dewey D.Y. [Biochemical Engineering Program, Department of Chemical Engineering and Material Science, University of California, Davis, CA 95616 (United States)

2008-03-15

For the newly isolated chemoheterotrophic bacterium Citrobacter amalonaticus Y19, anaerobic glucose metabolism and hydrogen (H{sub 2}) production pathway were studied using batch cultivation and an in silico metabolic-flux analysis. Batch cultivation was conducted under varying initial glucose concentration between 1.5 and 9.5 g/L with quantitative measurement of major metabolites to obtain accurate carbon material balance. The metabolic flux of Y19 was analyzed using a metabolic-pathway model which was constructed from 81 biochemical reactions. The linear optimization program MetaFluxNet was employed for the analysis. When the specific growth rate of cells was chosen as an objective function, the model described the batch culture characteristics of Ci. amalonaticus Y19 reasonably well. When the specific H{sub 2} production rate was selected as an objective function, on the other hand, the achievable maximal H{sub 2} production yield (8.7molH{sub 2}/mol glucose) and the metabolic pathway enabling the high H{sub 2} yield were identified. The pathway involved non-native NAD(P)-linked hydrogenase and H{sub 2} production from NAD(P)H which were supplied at a high rate from glucose degradation through the pentose phosphate pathway. (author)

In vivo kinetic analysis of the penicillin biosynthesis pathway using PAA stimulus response experiments.

Science.gov (United States)

Deshmukh, Amit T; Verheijen, Peter J T; Maleki Seifar, Reza; Heijnen, Joseph J; van Gulik, Walter M

2015-11-01

In this study we combined experimentation with mathematical modeling to unravel the in vivo kinetic properties of the enzymes and transporters of the penicillin biosynthesis pathway in a high yielding Penicillium chrysogenum strain. The experiment consisted of a step response experiment with the side chain precursor phenyl acetic acid (PAA) in a glucose-limited chemostat. The metabolite data showed that in the absence of PAA all penicillin pathway enzymes were expressed, leading to the production of a significant amount of 6-aminopenicillanic acid (6APA) as end product. After the stepwise perturbation with PAA, the pathway produced PenG within seconds. From the extra- and intracellular metabolite measurements, hypotheses for the secretion mechanisms of penicillin pathway metabolites were derived. A dynamic model of the penicillin biosynthesis pathway was then constructed that included the formation and transport over the cytoplasmic membrane of pathway intermediates, PAA and the product penicillin-G (PenG). The model parameters and changes in the enzyme levels of the penicillin biosynthesis pathway under in vivo conditions were simultaneously estimated using experimental data obtained at three different timescales (seconds, minutes, hours). The model was applied to determine changes in the penicillin pathway enzymes in time, calculate fluxes and analyze the flux control of the pathway. This led to a reassessment of the in vivo behavior of the pathway enzymes and in particular Acyl-CoA:Isopenicillin N Acyltransferase (AT). Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.

Lessons learned in applying function analysis

International Nuclear Information System (INIS)

Mitchel, G.R.; Davey, E.; Basso, R.

2001-01-01

This paper summarizes the lessons learned in undertaking and applying function analysis based on the recent experience of utility, AECL and international design and assessment projects. Function analysis is an analytical technique that can be used to characterize and asses the functions of a system and is widely recognized as an essential component of a 'systematic' approach to design, on that integrated operational and user requirements into the standard design process. (author)

Applying homotopy analysis method for solving differential-difference equation

International Nuclear Information System (INIS)

Wang Zhen; Zou Li; Zhang Hongqing

2007-01-01

In this Letter, we apply the homotopy analysis method to solving the differential-difference equations. A simple but typical example is applied to illustrate the validity and the great potential of the generalized homotopy analysis method in solving differential-difference equation. Comparisons are made between the results of the proposed method and exact solutions. The results show that the homotopy analysis method is an attractive method in solving the differential-difference equations

Applying meta-pathway analyses through metagenomics to identify the functional properties of the major bacterial communities of a single spontaneous cocoa bean fermentation process sample.

Science.gov (United States)

Illeghems, Koen; Weckx, Stefan; De Vuyst, Luc

2015-09-01

A high-resolution functional metagenomic analysis of a representative single sample of a Brazilian spontaneous cocoa bean fermentation process was carried out to gain insight into its bacterial community functioning. By reconstruction of microbial meta-pathways based on metagenomic data, the current knowledge about the metabolic capabilities of bacterial members involved in the cocoa bean fermentation ecosystem was extended. Functional meta-pathway analysis revealed the distribution of the metabolic pathways between the bacterial members involved. The metabolic capabilities of the lactic acid bacteria present were most associated with the heterolactic fermentation and citrate assimilation pathways. The role of Enterobacteriaceae in the conversion of substrates was shown through the use of the mixed-acid fermentation and methylglyoxal detoxification pathways. Furthermore, several other potential functional roles for Enterobacteriaceae were indicated, such as pectinolysis and citrate assimilation. Concerning acetic acid bacteria, metabolic pathways were partially reconstructed, in particular those related to responses toward stress, explaining their metabolic activities during cocoa bean fermentation processes. Further, the in-depth metagenomic analysis unveiled functionalities involved in bacterial competitiveness, such as the occurrence of CRISPRs and potential bacteriocin production. Finally, comparative analysis of the metagenomic data with bacterial genomes of cocoa bean fermentation isolates revealed the applicability of the selected strains as functional starter cultures. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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

Network features and pathway analyses of a signal transduction cascade

Directory of Open Access Journals (Sweden)

Ryoji Yanashima

2009-05-01

Full Text Available The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path.

Applied electro-optics educational and training program with multiple entrance and exit pathways

Science.gov (United States)

Scott, Patricia; Zhou, Feng; Zilic, Dorothy

2007-06-01

This paper presents an innovative hands-on training program designed to create a pipeline of highly-skilled technical workers for today's workforce economy. The 2+2+2 Pennsylvania Integrated Workforce Leadership Program in Electro-Optics prepares students for a career in this new high-tech field. With seamless transition from high school into college, the program offers the versatility of multiple entrance and exit pathways. After completion of each educational level, students can exit the program with various skill levels, including certificates, an associate's degree, or a bachelor's degree. Launched by Indiana University of Pennsylvania (IUP) in partnership with Lenape Vocational School (Lenape), the 2+2+2 educational pathway program was implemented to promote early training of high-school students. During the first level, students in their junior and/or senior year enroll in four Electro-Optics courses at Lenape. Upon completion of these courses and an Advanced Placement Equivalency course with an appropriate exam score, students can earn a certificate from Lenape for the 15+ credits, which also can be articulated into IUP's associate degree program in Electro-Optics. During the second level, students can earn an associate's degree in Electro-Optics, offered only at the IUP Northpointe Campus. After completion of the Associate in Applied Science (A.A.S.), students are prepared to enter the workforce as senior technicians. During the third level, students who have completed the Associate of Science (A.S.) in Electro-Optics have the opportunity to matriculate at IUP's Indiana Campus to earn a Bachelor of Science (B.S.) degree in Applied Physics with a track in Electro-Optics. Hence, the name 2+2+2 refers to getting started in high school, continuing the educational experience with an associate's degree program, and optionally moving on to a bachelor's degree. Consequently, students move from one educational level to the next with advanced credits toward the next

Genome wide expression analysis in HPV16 Cervical Cancer: identification of altered metabolic pathways

Directory of Open Access Journals (Sweden)

Salcedo Mauricio

2007-09-01

Full Text Available Abstract Background Cervical carcinoma (CC is a leading cause of death among women worldwide. Human papilloma virus (HPV is a major etiological factor in CC and HPV 16 is the more frequent viral type present. Our aim was to characterize metabolic pathways altered in HPV 16 tumor samples by means of transcriptome wide analysis and bioinformatics tools for visualizing expression data in the context of KEGG biological pathways. Results We found 2,067 genes significantly up or down-modulated (at least 2-fold in tumor clinical samples compared to normal tissues, representing ~3.7% of analyzed genes. Cervical carcinoma was associated with an important up-regulation of Wnt signaling pathway, which was validated by in situ hybridization in clinical samples. Other up-regulated pathways were those of calcium signaling and MAPK signaling, as well as cell cycle-related genes. There was down-regulation of focal adhesion, TGF-β signaling, among other metabolic pathways. Conclusion This analysis of HPV 16 tumors transcriptome could be useful for the identification of genes and molecular pathways involved in the pathogenesis of cervical carcinoma. Understanding the possible role of these proteins in the pathogenesis of CC deserves further studies.

Proliferation Resistance: Acquisition/Diversion Pathway Analysis for the DUPIC Fuel Cycle

International Nuclear Information System (INIS)

Ko, Won Il; Chang, Hong Lae; Song, Dae Yong; Lee, Ho Hee; Kwon, Eun Ha; Jeong, Chang Joon; Kim, Ho Dong

2009-07-01

Within the International Project on Innovative Nuclear Reactors and Fuel Cycles (INPRO), a methodology for evaluating proliferation resistance (INPRO PR methodology) has been developed. However, it remains to develop the methodology to evaluate User Requirements (UR) 4 regarding multiplicity and robustness of barriers against proliferation - innovative nuclear energy systems should incorporate multiple proliferation resistance features and measures. Since this requires an acquisition/diversion pathway analysis, this report describes a systematic approach developed for the identification and analysis of pathways for the acquisition of weapons-usable nuclear material using the DUPIC fuel cycle system. At the first step, the objectives of the proliferation were identified, including the quality and quantity of the material, the time required to acquire the material for the proliferation, thr capability of the potential proliferant country, etc. At the second step, the possible strategies, which the potential proliferant country could adopt, were identified: undeclared removal of nuclear material from the fuel cycle facilities; and further treatment of the diverted nuclear materials needed to acquire weapons-usable materials. At the final step, a systematic approach to select the plausible pathways for the acquisition/diversion of nuclear material during the whole fuel cycle has been developed. The coarse material diversion pathways for the DUPIC fuel cycle and the approach developed was reviewed and discussed at the experts meeting at the IAEA for its appropriateness and comprehensiveness

DATE analysis: A general theory of biological change applied to microarray data.

Science.gov (United States)

Rasnick, David

2009-01-01

In contrast to conventional data mining, which searches for specific subsets of genes (extensive variables) to correlate with specific phenotypes, DATE analysis correlates intensive state variables calculated from the same datasets. At the heart of DATE analysis are two biological equations of state not dependent on genetic pathways. This result distinguishes DATE analysis from other bioinformatics approaches. The dimensionless state variable F quantifies the relative overall cellular activity of test cells compared to well-chosen reference cells. The variable pi(i) is the fold-change in the expression of the ith gene of test cells relative to reference. It is the fraction phi of the genome undergoing differential expression-not the magnitude pi-that controls biological change. The state variable phi is equivalent to the control strength of metabolic control analysis. For tractability, DATE analysis assumes a linear system of enzyme-connected networks and exploits the small average contribution of each cellular component. This approach was validated by reproducible values of the state variables F, RNA index, and phi calculated from random subsets of transcript microarray data. Using published microarray data, F, RNA index, and phi were correlated with: (1) the blood-feeding cycle of the malaria parasite, (2) embryonic development of the fruit fly, (3) temperature adaptation of Killifish, (4) exponential growth of cultured S. pneumoniae, and (5) human cancers. DATE analysis was applied to aCGH data from the great apes. A good example of the power of DATE analysis is its application to genomically unstable cancers, which have been refractory to data mining strategies. 2009 American Institute of Chemical Engineers Biotechnol.

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

Directory of Open Access Journals (Sweden)

Miranda van Uitert

Full Text Available 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.

Integrated GWAS and Pathway profiling for feed efficiency traits in pigs leads to novel genes and their molecular pathways

DEFF Research Database (Denmark)

Do, Duy Ngoc; Ostersen, Tage; Strathe, Anders Bjerring

2013-01-01

Genome wide association studies (GWAS) are being extensively used in revealing genetic architecture of complex traits. However, GWAS offer limited understanding of the biological role of significant single nucleotide polymorphisms (SNPs) affecting complex traits. Pathway analysis using GWAS results...... is an important step where we firstly detect genes located near GWAS-detected SNPs and subsequently we detect enrichment of these genes in various biological processes and pathways. The objective of this study was to apply these steps to identify relevant pathways involved in residual feed intake (RFI) in pigs....... Residual feed intake is a feed efficiency measure and is highly economically important in animal production. In our study, a total of 596 Yorkshire boars had phenotypic and genotypic records. After quality control, 37,915 SNPs were available for GWAS which was implemented in the DMU software package...

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

Science.gov (United States)

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.

Analysis of Stomatal Patterning in Selected Mutants of MAPK Pathways

KAUST Repository

Felemban, Abrar

2016-05-01

Stomata are cellular valves in plants that play an essential role in the regulation of gas exchange and are distributed in the epidermis of aerial organs. In Arabidopsis thaliana, stomatal production and development are coordinated by the mitogen-activated protein kinase (MAPK) signalling pathway, which modulates a variety of other processes, including cell proliferation, regulation of cytokinesis, programed cell death, and response to abiotic and biotic stress. The environment also plays a role in stomatal development, by influencing the frequency at which stomata develop in leaves. This thesis presents an analysis of stomatal development in Arabidopsis mutants in two MAPK pathways: MEKK1-MKK1/MKK2-MPK4, and MAP3K17/18-MKK3. Obtained results demonstrate the effect of stress conditions on stomatal development and specify the involvement of analysed MAPK in stomatal patterning. First, both analysed pathways modulate stomatal patterning in Arabidopsis cotyledons. Second, plant growth-promoting bacteria tested enhance stomatal density and affect guard cell morphology. Third, the sucrose or mannitol treatment increases defects in stomatal patterning. Finally, salt stress or high temperature can suppress stomatal defects in mutants of the MEKK1-MKK1/MKK2-MPK4 pathway.

Identification of differentially expressed genes and signaling pathways in ovarian cancer by integrated bioinformatics analysis

Directory of Open Access Journals (Sweden)

Yang X

2018-03-01

Full Text Available Xiao Yang,1 Shaoming Zhu,2 Li Li,3 Li Zhang,1 Shu Xian,1 Yanqing Wang,1 Yanxiang Cheng1 1Department of Obstetrics and Gynecology, 2Department of Urology, Renmin Hospital of Wuhan University, 3Department of Pharmacology, Wuhan University Health Science Center, Wuhan, Hubei, People’s Republic of China Background: The mortality rate associated with ovarian cancer ranks the highest among gynecological malignancies. However, the cause and underlying molecular events of ovarian cancer are not clear. Here, we applied integrated bioinformatics to identify key pathogenic genes involved in ovarian cancer and reveal potential molecular mechanisms. Results: The expression profiles of GDS3592, GSE54388, and GSE66957 were downloaded from the Gene Expression Omnibus (GEO database, which contained 115 samples, including 85 cases of ovarian cancer samples and 30 cases of normal ovarian samples. The three microarray datasets were integrated to obtain differentially expressed genes (DEGs and were deeply analyzed by bioinformatics methods. The gene ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichments of DEGs were performed by DAVID and KOBAS online analyses, respectively. The protein–protein interaction (PPI networks of the DEGs were constructed from the STRING database. A total of 190 DEGs were identified in the three GEO datasets, of which 99 genes were upregulated and 91 genes were downregulated. GO analysis showed that the biological functions of DEGs focused primarily on regulating cell proliferation, adhesion, and differentiation and intracellular signal cascades. The main cellular components include cell membranes, exosomes, the cytoskeleton, and the extracellular matrix. The molecular functions include growth factor activity, protein kinase regulation, DNA binding, and oxygen transport activity. KEGG pathway analysis showed that these DEGs were mainly involved in the Wnt signaling pathway, amino acid metabolism, and the

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

Science.gov (United States)

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.

Penalized differential pathway analysis of integrative oncogenomics studies.

Science.gov (United States)

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.

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

Science.gov (United States)

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

Survival associated pathway identification with group Lp penalized global AUC maximization

Directory of Open Access Journals (Sweden)

Liu Zhenqiu

2010-08-01

Full Text Available Abstract It has been demonstrated that genes in a cell do not act independently. They interact with one another to complete certain biological processes or to implement certain molecular functions. How to incorporate biological pathways or functional groups into the model and identify survival associated gene pathways is still a challenging problem. In this paper, we propose a novel iterative gradient based method for survival analysis with group Lp penalized global AUC summary maximization. Unlike LASSO, Lp (p 1. We first extend Lp for individual gene identification to group Lp penalty for pathway selection, and then develop a novel iterative gradient algorithm for penalized global AUC summary maximization (IGGAUCS. This method incorporates the genetic pathways into global AUC summary maximization and identifies survival associated pathways instead of individual genes. The tuning parameters are determined using 10-fold cross validation with training data only. The prediction performance is evaluated using test data. We apply the proposed method to survival outcome analysis with gene expression profile and identify multiple pathways simultaneously. Experimental results with simulation and gene expression data demonstrate that the proposed procedures can be used for identifying important biological pathways that are related to survival phenotype and for building a parsimonious model for predicting the survival times.

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

Energy Technology Data Exchange (ETDEWEB)

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

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. Evidence 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.

Genomes of rumen bacteria encode atypical pathways for fermenting hexoses to short-chain fatty acids.

Science.gov (United States)

Hackmann, Timothy J; Ngugi, David Kamanda; Firkins, Jeffrey L; Tao, Junyi

2017-11-01

Bacteria have been thought to follow only a few well-recognized biochemical pathways when fermenting glucose or other hexoses. These pathways have been chiseled in the stone of textbooks for decades, with most sources rendering them as they appear in the classic 1986 text by Gottschalk. Still, it is unclear how broadly these pathways apply, given that they were established and delineated biochemically with only a few model organisms. Here, we show that well-recognized pathways often cannot explain fermentation products formed by bacteria. In the most extensive analysis of its kind, we reconstructed pathways for glucose fermentation from genomes of 48 species and subspecies of bacteria from one environment (the rumen). In total, 44% of these bacteria had atypical pathways, including several that are completely unprecedented for bacteria or any organism. In detail, 8% of bacteria had an atypical pathway for acetate formation; 21% of bacteria had an atypical pathway for propionate or succinate formation; 6% of bacteria had an atypical pathway for butyrate formation and 33% of bacteria had an atypical or incomplete Embden-Meyerhof-Parnas pathway. This study shows that reconstruction of metabolic pathways - a common goal of omics studies - could be incorrect if well-recognized pathways are used for reference. Furthermore, it calls for renewed efforts to delineate fermentation pathways biochemically. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

New trends in applied harmonic analysis sparse representations, compressed sensing, and multifractal analysis

CERN Document Server

Cabrelli, Carlos; Jaffard, Stephane; Molter, Ursula

2016-01-01

This volume is a selection of written notes corresponding to courses taught at the CIMPA School: "New Trends in Applied Harmonic Analysis: Sparse Representations, Compressed Sensing and Multifractal Analysis". New interactions between harmonic analysis and signal and image processing have seen striking development in the last 10 years, and several technological deadlocks have been solved through the resolution of deep theoretical problems in harmonic analysis. New Trends in Applied Harmonic Analysis focuses on two particularly active areas that are representative of such advances: multifractal analysis, and sparse representation and compressed sensing. The contributions are written by leaders in these areas, and covers both theoretical aspects and applications. This work should prove useful not only to PhD students and postdocs in mathematics and signal and image processing, but also to researchers working in related topics.

Atmospheric Pathway Screening Analysis for Saltstone Disposal Facility Vault 4

International Nuclear Information System (INIS)

COOK, JAMES

2004-01-01

A sequential screening process using a methodology developed by the National Council on Radiation Protection and Measurements, professional judgment and process knowledge has been used to produce a list of radionuclides requiring detailed analysis to derive disposal limits for the Saltstone Disposal Facility based on the atmospheric pathway

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

Science.gov (United States)

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

Sensitivity analysis on a dose-calculation model for the terrestrial food-chain pathway

International Nuclear Information System (INIS)

Abdel-Aal, M.M.

1994-01-01

Parameter uncertainty and sensitivity were applied to the U.S. Regulatory Commission's (NRC) Regulatory Guide 1.109 (1977) models for calculating the ingestion dose via a terrestrial food-chain pathway in order to assess the transport of chronically released, low-level effluents from light-water reactors. In the analysis, we used the generation of latin hypercube samples (LHS) and employed a constrained sampling scheme. The generation of these samples is based on information supplied to the LHS program for variables or parameters. The actually sampled values are used to form vectors of variables that are commonly used as inputs to computer models for the purpose of sensitivity and uncertainty analysis. Regulatory models consider the concentrations of radionuclides that are deposited on plant tissues or lead to root uptake of nuclides initially deposited on soil. We also consider concentrations in milk and beef as a consequence of grazing on contaminated pasture or ingestion of contaminated feed by dairy and beef cattle. The radionuclides Sr-90 and Cs-137 were selected for evaluation. The most sensitive input parameters for the model were the ground-dispersion parameter, release rates of radionuclides, and soil-to-plant transfer coefficients of radionuclides. (Author)

Enhancement of Nucleoside Production in Hirsutella sinensis Based on Biosynthetic Pathway Analysis

Science.gov (United States)

Liu, Zhi-Qiang; Zhang, Bo; Lin, Shan; Baker, Peter James; Chen, Mao-Sheng; Xue, Ya-Ping; Wu, Hui; Xu, Feng; Yuan, Shui-Jin; Teng, Yi; Wu, Ling-Fang

2017-01-01

To enhance nucleoside production in Hirsutella sinensis, the biosynthetic pathways of purine and pyrimidine nucleosides were constructed and verified. The differential expression analysis showed that purine nucleoside phosphorylase, inosine monophosphate dehydrogenase, and guanosine monophosphate synthase genes involved in purine nucleotide biosynthesis were significantly upregulated 16.56-fold, 8-fold, and 5.43-fold, respectively. Moreover, dihydroorotate dehydrogenase, uridine nucleosidase, uridine/cytidine monophosphate kinase, and inosine triphosphate pyrophosphatase genes participating in pyrimidine nucleoside biosynthesis were upregulated 4.53-fold, 10.63-fold, 4.26-fold, and 5.98-fold, respectively. To enhance the nucleoside production, precursors for synthesis of nucleosides were added based on the analysis of biosynthetic pathways. Uridine and cytidine contents, respectively, reached 5.04 mg/g and 3.54 mg/g when adding 2 mg/mL of ribose, resulting in an increase of 28.6% and 296% compared with the control, respectively. Meanwhile, uridine and cytidine contents, respectively, reached 10.83 mg/g 2.12 mg/g when adding 0.3 mg/mL of uracil, leading to an increase of 176.3% and 137.1%, respectively. This report indicated that fermentation regulation was an effective way to enhance the nucleoside production in H. sinensis based on biosynthetic pathway analysis. PMID:29333435

Microarray analysis reveals genetic pathways modulated by tipifarnib in acute myeloid leukemia

International Nuclear Information System (INIS)

Raponi, Mitch; Belly, Robert T; Karp, Judith E; Lancet, Jeffrey E; Atkins, David; Wang, Yixin

2004-01-01

Farnesyl protein transferase inhibitors (FTIs) were originally developed to inhibit oncogenic ras, however it is now clear that there are several other potential targets for this drug class. The FTI tipifarnib (ZARNESTRA™, R115777) has recently demonstrated clinical responses in adults with refractory and relapsed acute leukemias. This study was conducted to identify genetic markers and pathways that are regulated by tipifarnib in acute myeloid leukemia (AML). Tipifarnib-mediated gene expression changes in 3 AML cell lines and bone marrow samples from two patients with AML were analyzed on a cDNA microarray containing approximately 7000 human genes. Pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis tool. The expression analysis identified a common set of genes that were regulated by tipifarnib in three leukemic cell lines and in leukemic blast cells isolated from two patients who had been treated with tipifarnib. Association of modulated genes with biological functional groups identified several pathways affected by tipifarnib including cell signaling, cytoskeletal organization, immunity, and apoptosis. Gene expression changes were verified in a subset of genes using real time RT-PCR. Additionally, regulation of apoptotic genes was found to correlate with increased Annexin V staining in the THP-1 cell line but not in the HL-60 cell line. The genetic networks derived from these studies illuminate some of the biological pathways affected by FTI treatment while providing a proof of principle for identifying candidate genes that might be used as surrogate biomarkers of drug activity

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

Science.gov (United States)

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.

Interleukin-2 signaling pathway analysis by quantitative phosphoproteomics

DEFF Research Database (Denmark)

Osinalde, Nerea; Moss, Helle; Arrizabalaga, Onetsine

2011-01-01

among which 79 were found with increased abundance in the tyrosine-phosphorylated complexes, including several previously not reported IL-2 downstream effectors. Combinatorial site-specific phosphoproteomic analysis resulted in identification of 99 phosphorylated sites mapping to the identified proteins...... with increased abundance in the tyrosine-phosphorylated complexes, of which 34 were not previously described. In addition, chemical inhibition of the identified IL-2-mediated JAK, PI3K and MAPK signaling pathways, resulted in distinct alteration on the IL-2 dependent proliferation....

Application of Monte Carlo cross-validation to identify pathway cross-talk in neonatal sepsis.

Science.gov (United States)

Zhang, Yuxia; Liu, Cui; Wang, Jingna; Li, Xingxia

2018-03-01

To explore genetic pathway cross-talk in neonates with sepsis, an integrated approach was used in this paper. To explore the potential relationships between differently expressed genes between normal uninfected neonates and neonates with sepsis and pathways, genetic profiling and biologic signaling pathway were first integrated. For different pathways, the score was obtained based upon the genetic expression by quantitatively analyzing the pathway cross-talk. The paired pathways with high cross-talk were identified by random forest classification. The purpose of the work was to find the best pairs of pathways able to discriminate sepsis samples versus normal samples. The results found 10 pairs of pathways, which were probably able to discriminate neonates with sepsis versus normal uninfected neonates. Among them, the best two paired pathways were identified according to analysis of extensive literature. Impact statement To find the best pairs of pathways able to discriminate sepsis samples versus normal samples, an RF classifier, the DS obtained by DEGs of paired pathways significantly associated, and Monte Carlo cross-validation were applied in this paper. Ten pairs of pathways were probably able to discriminate neonates with sepsis versus normal uninfected neonates. Among them, the best two paired pathways ((7) IL-6 Signaling and Phospholipase C Signaling (PLC); (8) Glucocorticoid Receptor (GR) Signaling and Dendritic Cell Maturation) were identified according to analysis of extensive literature.

Applied research of environmental monitoring using instrumental neutron activation analysis

Energy Technology Data Exchange (ETDEWEB)

Chung, Young Sam; Moon, Jong Hwa; Chung, Young Ju

1997-08-01

This technical report is written as a guide book for applied research of environmental monitoring using Instrumental Neutron Activation Analysis. The contents are as followings; sampling and sample preparation as a airborne particulate matter, analytical methodologies, data evaluation and interpretation, basic statistical methods of data analysis applied in environmental pollution studies. (author). 23 refs., 7 tabs., 9 figs.

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

Science.gov (United States)

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.

Cloning and Expression Analysis of MEP Pathway Enzyme-encoding Genes in Osmanthus fragrans

Directory of Open Access Journals (Sweden)

Chen Xu

2016-09-01

Full Text Available The 2-C-methyl-d-erythritol 4-phosphate (MEP pathway is responsible for the biosynthesis of many crucial secondary metabolites, such as carotenoids, monoterpenes, plastoquinone, and tocopherols. In this study, we isolated and identified 10 MEP pathway genes in the important aromatic plant sweet osmanthus (Osmanthus fragrans. Multiple sequence alignments revealed that 10 MEP pathway genes shared high identities with other reported proteins. The genes showed distinctive expression profiles in various tissues, or at different flower stages and diel time points. The qRT-PCR results demonstrated that these genes were highly expressed in inflorescences, which suggested a tissue-specific transcript pattern. Our results also showed that OfDXS1, OfDXS2, and OfHDR1 had a clear diurnal oscillation pattern. The isolation and expression analysis provides a strong foundation for further research on the MEP pathway involved in gene function and molecular evolution, and improves our understanding of the molecular mechanism underlying this pathway in plants.

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

Science.gov (United States)

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

Ensemble Modeling for Robustness Analysis in engineering non-native metabolic pathways.

Science.gov (United States)

Lee, Yun; Lafontaine Rivera, Jimmy G; Liao, James C

2014-09-01

Metabolic pathways in cells must be sufficiently robust to tolerate fluctuations in expression levels and changes in environmental conditions. Perturbations in expression levels may lead to system failure due to the disappearance of a stable steady state. Increasing evidence has suggested that biological networks have evolved such that they are intrinsically robust in their network structure. In this article, we presented Ensemble Modeling for Robustness Analysis (EMRA), which combines a continuation method with the Ensemble Modeling approach, for investigating the robustness issue of non-native pathways. EMRA investigates a large ensemble of reference models with different parameters, and determines the effects of parameter drifting until a bifurcation point, beyond which a stable steady state disappears and system failure occurs. A pathway is considered to have high bifurcational robustness if the probability of system failure is low in the ensemble. To demonstrate the utility of EMRA, we investigate the bifurcational robustness of two synthetic central metabolic pathways that achieve carbon conservation: non-oxidative glycolysis and reverse glyoxylate cycle. With EMRA, we determined the probability of system failure of each design and demonstrated that alternative designs of these pathways indeed display varying degrees of bifurcational robustness. Furthermore, we demonstrated that target selection for flux improvement should consider the trade-offs between robustness and performance. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

The Significance of Regional Analysis in Applied Geography.

Science.gov (United States)

Sommers, Lawrence M.

Regional analysis is central to applied geographic research, contributing to better planning and policy development for a variety of societal problems facing the United States. The development of energy policy serves as an illustration of the capabilities of this type of analysis. The United States has had little success in formulating a national…

Pathways analysis and radiation-dose estimates for radioactive residues at formerly utilized MED/AEC sites

Energy Technology Data Exchange (ETDEWEB)

Gilbert, T.L.; Chee, P.C.; Knight, M.J.; Peterson, J.M.; Roberts, C.J.; Robinson, J.E.; Tsai, S.Y.H.; Yuan, Y.C.

1983-03-01

Methods of analysis are developed for estimating the largest individual radiation dose that could result from residual radioactivity at sites identified by the Formerly Utilized Sites Remedial Action Program (FUSRAP) of the US Department of Energy. Two unique aspects of the methods are (1) a systematic structuring of the radiation pathways analysis into source terms, source-to-exposure analysis, and exposure-to-dose analysis, and (2) the systematic use of data on the average concentrations of naturally occurring radionuclides in soil, food, and the human body in order to assess the validity of model calculations and obtain more realistic values. The methods are applied to a typical FUSRAP site in order to obtain generic source-to-dose (D/S) conversion factors for estimating the radiation dose to the maximally exposed individual from a known concentration of radionuclides in the soil. The D/S factors are used to derive soil guidelines, i.e., the limiting concentrations of radionuclides at a typical FUSRAP site that are unlikely to result in individual dose limits that exceed generally accepted radiation protection standards. The results lead to the conclusion that the soil guidelines should not exceed 17, 75, and 300 pCi/g for Ra-226, U-238, and Th-230, respectively.

Pathways analysis and radiation-dose estimates for radioactive residues at formerly utilized MED/AEC sites

International Nuclear Information System (INIS)

Gilbert, T.L.; Chee, P.C.; Knight, M.J.; Peterson, J.M.; Roberts, C.J.; Robinson, J.E.; Tsai, S.Y.H.; Yuan, Y.C.

1983-03-01

Methods of analysis are developed for estimating the largest individual radiation dose that could result from residual radioactivity at sites identified by the Formerly Utilized Sites Remedial Action Program (FUSRAP) of the US Department of Energy. Two unique aspects of the methods are (1) a systematic structuring of the radiation pathways analysis into source terms, source-to-exposure analysis, and exposure-to-dose analysis, and (2) the systematic use of data on the average concentrations of naturally occurring radionuclides in soil, food, and the human body in order to assess the validity of model calculations and obtain more realistic values. The methods are applied to a typical FUSRAP site in order to obtain generic source-to-dose (D/S) conversion factors for estimating the radiation dose to the maximally exposed individual from a known concentration of radionuclides in the soil. The D/S factors are used to derive soil guidelines, i.e., the limiting concentrations of radionuclides at a typical FUSRAP site that are unlikely to result in individual dose limits that exceed generally accepted radiation protection standards. The results lead to the conclusion that the soil guidelines should not exceed 17, 75, and 300 pCi/g for Ra-226, U-238, and Th-230, respectively

Inference of miRNA targets using evolutionary conservation and pathway analysis

Directory of Open Access Journals (Sweden)

van Nimwegen Erik

2007-03-01

Full Text Available Abstract Background MicroRNAs have emerged as important regulatory genes in a variety of cellular processes and, in recent years, hundreds of such genes have been discovered in animals. In contrast, functional annotations are available only for a very small fraction of these miRNAs, and even in these cases only partially. Results We developed a general Bayesian method for the inference of miRNA target sites, in which, for each miRNA, we explicitly model the evolution of orthologous target sites in a set of related species. Using this method we predict target sites for all known miRNAs in flies, worms, fish, and mammals. By comparing our predictions in fly with a reference set of experimentally tested miRNA-mRNA interactions we show that our general method performs at least as well as the most accurate methods available to date, including ones specifically tailored for target prediction in fly. An important novel feature of our model is that it explicitly infers the phylogenetic distribution of functional target sites, independently for each miRNA. This allows us to infer species-specific and clade-specific miRNA targeting. We also show that, in long human 3' UTRs, miRNA target sites occur preferentially near the start and near the end of the 3' UTR. To characterize miRNA function beyond the predicted lists of targets we further present a method to infer significant associations between the sets of targets predicted for individual miRNAs and specific biochemical pathways, in particular those of the KEGG pathway database. We show that this approach retrieves several known functional miRNA-mRNA associations, and predicts novel functions for known miRNAs in cell growth and in development. Conclusion We have presented a Bayesian target prediction algorithm without any tunable parameters, that can be applied to sequences from any clade of species. The algorithm automatically infers the phylogenetic distribution of functional sites for each miRNA, and

Leading coordinate analysis of reaction pathways in proton chain transfer: Application to a two-proton transfer model for the green fluorescent protein

International Nuclear Information System (INIS)

Wang Sufan; Smith, Sean C.

2006-01-01

The 'leading coordinate' approach to computing an approximate reaction pathway, with subsequent determination of the true minimum energy profile, is applied to a two-proton chain transfer model based on the chromophore and its surrounding moieties within the green fluorescent protein (GFP). Using an ab initio quantum chemical method, a number of different relaxed energy profiles are found for several plausible guesses at leading coordinates. The results obtained for different trial leading coordinates are rationalized through the calculation of a two-dimensional relaxed potential energy surface (PES) for the system. Analysis of the 2-D relaxed PES reveals that two of the trial pathways are entirely spurious, while two others contain useful information and can be used to furnish starting points for successful saddle-point searches. Implications for selection of trial leading coordinates in this class of proton chain transfer reactions are discussed, and a simple diagnostic function is proposed for revealing whether or not a relaxed pathway based on a trial leading coordinate is likely to furnish useful information

Applied decision analysis and risk evaluation

International Nuclear Information System (INIS)

Ferse, W.; Kruber, S.

1995-01-01

During 1994 the workgroup 'Applied Decision Analysis and Risk Evaluation; continued the work on the knowledge based decision support system XUMA-GEFA for the evaluation of the hazard potential of contaminated sites. Additionally a new research direction was started which aims at the support of a later stage of the treatment of contaminated sites: The clean-up decision. For the support of decisions arising at this stage, the methods of decision analysis will be used. Computational aids for evaluation and decision support were implemented and a case study at a waste disposal site in Saxony which turns out to be a danger for the surrounding groundwater ressource was initiated. (orig.)

Pathway discovery in metabolic networks by subgraph extraction.

Science.gov (United States)

Faust, Karoline; Dupont, Pierre; Callut, Jérôme; van Helden, Jacques

2010-05-01

Subgraph extraction is a powerful technique to predict pathways from biological networks and a set of query items (e.g. genes, proteins, compounds, etc.). It can be applied to a variety of different data types, such as gene expression, protein levels, operons or phylogenetic profiles. In this article, we investigate different approaches to extract relevant pathways from metabolic networks. Although these approaches have been adapted to metabolic networks, they are generic enough to be adjusted to other biological networks as well. We comparatively evaluated seven sub-network extraction approaches on 71 known metabolic pathways from Saccharomyces cerevisiae and a metabolic network obtained from MetaCyc. The best performing approach is a novel hybrid strategy, which combines a random walk-based reduction of the graph with a shortest paths-based algorithm, and which recovers the reference pathways with an accuracy of approximately 77%. Most of the presented algorithms are available as part of the network analysis tool set (NeAT). The kWalks method is released under the GPL3 license.

Discriminating response groups in metabolic and regulatory pathway networks.

Science.gov (United States)

Van Hemert, John L; Dickerson, Julie A

2012-04-01

Analysis of omics experiments generates lists of entities (genes, metabolites, etc.) selected based on specific behavior, such as changes in response to stress or other signals. Functional interpretation of these lists often uses category enrichment tests using functional annotations like Gene Ontology terms and pathway membership. This approach does not consider the connected structure of biochemical pathways or the causal directionality of events. The Omics Response Group (ORG) method, described in this work, interprets omics lists in the context of metabolic pathway and regulatory networks using a statistical model for flow within the networks. Statistical results for all response groups are visualized in a novel Pathway Flow plot. The statistical tests are based on the Erlang distribution model under the assumption of independent and identically Exponential-distributed random walk flows through pathways. As a proof of concept, we applied our method to an Escherichia coli transcriptomics dataset where we confirmed common knowledge of the E.coli transcriptional response to Lipid A deprivation. The main response is related to osmotic stress, and we were also able to detect novel responses that are supported by the literature. We also applied our method to an Arabidopsis thaliana expression dataset from an abscisic acid study. In both cases, conventional pathway enrichment tests detected nothing, while our approach discovered biological processes beyond the original studies. We created a prototype for an interactive ORG web tool at http://ecoserver.vrac.iastate.edu/pathwayflow (source code is available from https://subversion.vrac.iastate.edu/Subversion/jlv/public/jlv/pathwayflow). The prototype is described along with additional figures and tables in Supplementary Material. julied@iastate.edu Supplementary data are available at Bioinformatics online.

Neurophysiology and itch pathways.

Science.gov (United States)

Schmelz, Martin

2015-01-01

As we all can easily differentiate the sensations of itch and pain, the most straightforward neurophysiologic concept would consist of two specific pathways that independently encode itch and pain. Indeed, a neuronal pathway for histamine-induced itch in the peripheral and central nervous system has been described in animals and humans, and recently several non-histaminergic pathways for itch have been discovered in rodents that support a dichotomous concept differentiated into a pain and an itch pathway, with both pathways being composed of different "flavors." Numerous markers and mediators have been found that are linked to itch processing pathways. Thus, the delineation of neuronal pathways for itch from pain pathways seemingly proves that all sensory aspects of itch are based on an itch-specific neuronal pathway. However, such a concept is incomplete as itch can also be induced by the activation of the pain pathway in particular when the stimulus is applied in a highly localized spatial pattern. These opposite views reflect the old dispute between specificity and pattern theories of itch. Rather than only being of theoretic interest, this conceptual problem has key implication for the strategy to treat chronic itch as key therapeutic targets would be either itch-specific pathways or unspecific nociceptive pathways.

Animal Research in the "Journal of Applied Behavior Analysis"

Science.gov (United States)

Edwards, Timothy L.; Poling, Alan

2011-01-01

This review summarizes the 6 studies with nonhuman animal subjects that have appeared in the "Journal of Applied Behavior Analysis" and offers suggestions for future research in this area. Two of the reviewed articles described translational research in which pigeons were used to illustrate and examine behavioral phenomena of applied significance…

Comparative expression pathway analysis of human and canine mammary tumors

Directory of Open Access Journals (Sweden)

Marconato Laura

2009-03-01

Full Text Available Abstract Background Spontaneous tumors in dog have been demonstrated to share many features with their human counterparts, including relevant molecular targets, histological appearance, genetics, biological behavior and response to conventional treatments. Mammary tumors in dog therefore provide an attractive alternative to more classical mouse models, such as transgenics or xenografts, where the tumour is artificially induced. To assess the extent to which dog tumors represent clinically significant human phenotypes, we performed the first genome-wide comparative analysis of transcriptional changes occurring in mammary tumors of the two species, with particular focus on the molecular pathways involved. Results We analyzed human and dog gene expression data derived from both tumor and normal mammary samples. By analyzing the expression levels of about ten thousand dog/human orthologous genes we observed a significant overlap of genes deregulated in the mammary tumor samples, as compared to their normal counterparts. Pathway analysis of gene expression data revealed a great degree of similarity in the perturbation of many cancer-related pathways, including the 'PI3K/AKT', 'KRAS', 'PTEN', 'WNT-beta catenin' and 'MAPK cascade'. Moreover, we show that the transcriptional relationships between different gene signatures observed in human breast cancer are largely maintained in the canine model, suggesting a close interspecies similarity in the network of cancer signalling circuitries. Conclusion Our data confirm and further strengthen the value of the canine mammary cancer model and open up new perspectives for the evaluation of novel cancer therapeutics and the development of prognostic and diagnostic biomarkers to be used in clinical studies.

Modern problems in applied analysis

CERN Document Server

Rogosin, Sergei

2018-01-01

This book features a collection of recent findings in Applied Real and Complex Analysis that were presented at the 3rd International Conference “Boundary Value Problems, Functional Equations and Applications” (BAF-3), held in Rzeszow, Poland on 20-23 April 2016. The contributions presented here develop a technique related to the scope of the workshop and touching on the fields of differential and functional equations, complex and real analysis, with a special emphasis on topics related to boundary value problems. Further, the papers discuss various applications of the technique, mainly in solid mechanics (crack propagation, conductivity of composite materials), biomechanics (viscoelastic behavior of the periodontal ligament, modeling of swarms) and fluid dynamics (Stokes and Brinkman type flows, Hele-Shaw type flows). The book is addressed to all readers who are interested in the development and application of innovative research results that can help solve theoretical and real-world problems.

Using Formal Concept Analysis to Create Pathways through Museum Collections

DEFF Research Database (Denmark)

Wray, Tim; Eklund, Peter

2014-01-01

This paper presents A Place for Art - an iPad app that allows users to explore an art collection via semantically linked pathways that are generated using Formal Concept Analysis. The app embraces the information seeking approach of exploration and is based on the idea that showing context...... and relationships among objects in a museum collection augments an interpretive experience. The fundamental interaction metaphor inherent in A Place for Art relies on Formal Concept Analysis so the interface has embedded within it the semantic clustering features of machine learning in artificial intelligence....

Thermodynamics of metabolic pathways for penicillin production: Analysis of thermodynamic feasibility and free energy changes during fed-batch cultivation

DEFF Research Database (Denmark)

Pissarra, P.D.; Nielsen, Jens Bredal

1997-01-01

This paper describes the thermodynamic analysis of pathways related to penicillin production in Penicillium chrysogenum. First a thermodynamic feasibility analysis is performed of the L-lysine pathway of which one of the precursors for penicillin biosynthesis (alpha-aminoadipic acid......) is an intermediate. It is found that the L-lysine pathway in P. chrysogenum is thermodynamically feasible and that the calculated standard Gibbs free energy values of the two enzymes controlling the pathway flux indicate that they operate far from equilibrium. It is therefore proposed that the regulation of alpha......-aminoadipate reductase by lysine is important to maintain a high concentration of alpha-aminoadipate in order to direct the carbon flux to penicillin production. Secondly the changes in Gibbs free energy in the penicillin biosynthetic pathway during fed-batch cultivation were studied. The analysis showed that all...

Fourier convergence analysis applied to neutron diffusion Eigenvalue problem

International Nuclear Information System (INIS)

Lee, Hyun Chul; Noh, Jae Man; Joo, Hyung Kook

2004-01-01

Fourier error analysis has been a standard technique for the stability and convergence analysis of linear and nonlinear iterative methods. Though the methods can be applied to Eigenvalue problems too, all the Fourier convergence analyses have been performed only for fixed source problems and a Fourier convergence analysis for Eigenvalue problem has never been reported. Lee et al proposed new 2-D/1-D coupling methods and they showed that the new ones are unconditionally stable while one of the two existing ones is unstable at a small mesh size and that the new ones are better than the existing ones in terms of the convergence rate. In this paper the convergence of method A in reference 4 for the diffusion Eigenvalue problem was analyzed by the Fourier analysis. The Fourier convergence analysis presented in this paper is the first one applied to a neutronics eigenvalue problem to the best of our knowledge

Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis

Directory of Open Access Journals (Sweden)

Xiaowen Tan

2017-01-01

Full Text Available Background. Coronary artery atherosclerosis is a chronic inflammatory disease. This study aimed to identify the key changes of gene expression between early and advanced carotid atherosclerotic plaque in human. Methods. Gene expression dataset GSE28829 was downloaded from Gene Expression Omnibus (GEO, including 16 advanced and 13 early stage atherosclerotic plaque samples from human carotid. Differentially expressed genes (DEGs were analyzed. Results. 42,450 genes were obtained from the dataset. Top 100 up- and downregulated DEGs were listed. Functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG identification were performed. The result of functional and pathway enrichment analysis indicted that the immune system process played a critical role in the progression of carotid atherosclerotic plaque. Protein-protein interaction (PPI networks were performed either. Top 10 hub genes were identified from PPI network and top 6 modules were inferred. These genes were mainly involved in chemokine signaling pathway, cell cycle, B cell receptor signaling pathway, focal adhesion, and regulation of actin cytoskeleton. Conclusion. The present study indicated that analysis of DEGs would make a deeper understanding of the molecular mechanisms of atherosclerosis development and they might be used as molecular targets and diagnostic biomarkers for the treatment of atherosclerosis.

Animal research in the Journal of Applied Behavior Analysis.

Science.gov (United States)

Edwards, Timothy L; Poling, Alan

2011-01-01

This review summarizes the 6 studies with nonhuman animal subjects that have appeared in the Journal of Applied Behavior Analysis and offers suggestions for future research in this area. Two of the reviewed articles described translational research in which pigeons were used to illustrate and examine behavioral phenomena of applied significance (say-do correspondence and fluency), 3 described interventions that changed animals' behavior (self-injury by a baboon, feces throwing and spitting by a chimpanzee, and unsafe trailer entry by horses) in ways that benefited the animals and the people in charge of them, and 1 described the use of trained rats that performed a service to humans (land-mine detection). We suggest that each of these general research areas merits further attention and that the Journal of Applied Behavior Analysis is an appropriate outlet for some of these publications.

Life cycle analysis of transportation fuel pathways

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-02-24

The purpose of this work is to improve the understanding of the concept of life cycle analysis (LCA) of transportation fuels and some of its pertinent issues among non-technical people, senior managers, and policy makers. This work should provide some guidance to nations considering LCA-based policies and to people who are affected by existing policies or those being developed. While the concept of employing LCA to evaluate fuel options is simple and straightforward, the act of putting the concept into practice is complex and fraught with issues. Policy makers need to understand the limitations inherent in carrying out LCA work for transportation fuel systems. For many systems, even those that have been employed for a 100 years, there is a lack of sound data on the performance of those systems. Comparisons between systems should ideally be made using the same tool, so that differences caused by system boundaries, allocation processes, and temporal issues can be minimized (although probably not eliminated). Comparing the results for fuel pathway 1 from tool A to those of fuel system 2 from tool B introduces significant uncertainty into the results. There is also the question of the scale of system changes. LCA will give more reliable estimates when it is used to examine small changes in transportation fuel pathways than when used to estimate large scale changes that replace current pathways with completely new pathways. Some LCA tools have been developed recently primarily for regulatory purposes. These tools may deviate from ISO principles in order to facilitate simplicity and ease of use. In a regulatory environment, simplicity and ease of use are worthy objectives and in most cases there is nothing inherently wrong with this approach, particularly for assessing relative performance. However, the results of these tools should not be confused with, or compared to, the results that are obtained from a more complex and rigorous ISO compliant LCA. It should be

Microarray analysis reveals key genes and pathways in Tetralogy of Fallot

Science.gov (United States)

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

Assembly of inflammation-related genes for pathway-focused genetic analysis.

Directory of Open Access Journals (Sweden)

Matthew J Loza

2007-10-01

Full Text Available Recent identifications of associations between novel variants in inflammation-related genes and several common diseases emphasize the need for systematic evaluations of these genes in disease susceptibility. Considering that many genes are involved in the complex inflammation responses and many genetic variants in these genes have the potential to alter the functions and expression of these genes, we assembled a list of key inflammation-related genes to facilitate the identification of genetic associations of diseases with an inflammation-related etiology. We first reviewed various phases of inflammation responses, including the development of immune cells, sensing of danger, influx of cells to sites of insult, activation and functional responses of immune and non-immune cells, and resolution of the immune response. Assisted by the Ingenuity Pathway Analysis, we then identified 17 functional sub-pathways that are involved in one or multiple phases. This organization would greatly increase the chance of detecting gene-gene interactions by hierarchical clustering of genes with their functional closeness in a pathway. Finally, as an example application, we have developed tagging single nucleotide polymorphism (tSNP arrays for populations of European and African descent to capture all the common variants of these key inflammation-related genes. Assays of these tSNPs have been designed and assembled into two Affymetrix ParAllele customized chips, one each for European (12,011 SNPs and African (21,542 SNPs populations. These tSNPs have greater coverage for these inflammation-related genes compared to the existing genome-wide arrays, particularly in the African population. These tSNP arrays can facilitate systematic evaluation of inflammation pathways in disease susceptibility. For additional applications, other genotyping platforms could also be employed. For existing genome-wide association data, this list of key inflammation-related genes and

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

Science.gov (United States)

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.

Pathway Relevance Ranking for Tumor Samples through Network-Based Data Integration.

Directory of Open Access Journals (Sweden)

Lieven P C Verbeke

Full Text Available The study of cancer, a highly heterogeneous disease with different causes and clinical outcomes, requires a multi-angle approach and the collection of large multi-omics datasets that, ideally, should be analyzed simultaneously. We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single comprehensive network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. We demonstrate the performance of the new method by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method's potential to identify key pathways involved in breast cancer development shared by different molecular subtypes is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi-genetic disturbances were diverse. Next to prioritizing universally high-scoring pathways, the pathway ranking method was able to identify subtype-specific pathways. Often the score of a pathway could not be motivated by a single mutation, copy number or methylation alteration, but rather by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method's ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad

Sensitivity analysis of intracellular signaling pathway kinetics predicts targets for stem cell fate control.

Directory of Open Access Journals (Sweden)

Alborz Mahdavi

2007-07-01

Full Text Available Directing stem cell fate requires knowledge of how signaling networks integrate temporally and spatially segregated stimuli. We developed and validated a computational model of signal transducer and activator of transcription-3 (Stat3 pathway kinetics, a signaling network involved in embryonic stem cell (ESC self-renewal. Our analysis identified novel pathway responses; for example, overexpression of the receptor glycoprotein-130 results in reduced pathway activation and increased ESC differentiation. We used a systematic in silico screen to identify novel targets and protein interactions involved in Stat3 activation. Our analysis demonstrates that signaling activation and desensitization (the inability to respond to ligand restimulation is regulated by balancing the activation state of a distributed set of parameters including nuclear export of Stat3, nuclear phosphatase activity, inhibition by suppressor of cytokine signaling, and receptor trafficking. This knowledge was used to devise a temporally modulated ligand delivery strategy that maximizes signaling activation and leads to enhanced ESC self-renewal.

Comprehensive analysis of schizophrenia-associated loci highlights ion channel pathways and biologically plausible candidate causal genes

DEFF Research Database (Denmark)

Pers, Tune H; Timshel, Pascal; Ripke, Stephan

2016-01-01

Over 100 associated genetic loci have been robustly associated with schizophrenia. Gene prioritization and pathway analysis have focused on a priori hypotheses and thus may have been unduly influenced by prior assumptions and missed important causal genes and pathways. Using a data-driven approac...

Applied Behavior Analysis: Beyond Discrete Trial Teaching

Science.gov (United States)

Steege, Mark W.; Mace, F. Charles; Perry, Lora; Longenecker, Harold

2007-01-01

We discuss the problem of autism-specific special education programs representing themselves as Applied Behavior Analysis (ABA) programs when the only ABA intervention employed is Discrete Trial Teaching (DTT), and often for limited portions of the school day. Although DTT has many advantages to recommend its use, it is not well suited to teach…

Reconstruction and flux analysis of coupling between metabolic pathways of astrocytes and neurons: application to cerebral hypoxia

Directory of Open Access Journals (Sweden)

Akιn Ata

2007-12-01

Full Text Available Abstract Background It is a daunting task to identify all the metabolic pathways of brain energy metabolism and develop a dynamic simulation environment that will cover a time scale ranging from seconds to hours. To simplify this task and make it more practicable, we undertook stoichiometric modeling of brain energy metabolism with the major aim of including the main interacting pathways in and between astrocytes and neurons. Model The constructed model includes central metabolism (glycolysis, pentose phosphate pathway, TCA cycle, lipid metabolism, reactive oxygen species (ROS detoxification, amino acid metabolism (synthesis and catabolism, the well-known glutamate-glutamine cycle, other coupling reactions between astrocytes and neurons, and neurotransmitter metabolism. This is, to our knowledge, the most comprehensive attempt at stoichiometric modeling of brain metabolism to date in terms of its coverage of a wide range of metabolic pathways. We then attempted to model the basal physiological behaviour and hypoxic behaviour of the brain cells where astrocytes and neurons are tightly coupled. Results The reconstructed stoichiometric reaction model included 217 reactions (184 internal, 33 exchange and 216 metabolites (183 internal, 33 external distributed in and between astrocytes and neurons. Flux balance analysis (FBA techniques were applied to the reconstructed model to elucidate the underlying cellular principles of neuron-astrocyte coupling. Simulation of resting conditions under the constraints of maximization of glutamate/glutamine/GABA cycle fluxes between the two cell types with subsequent minimization of Euclidean norm of fluxes resulted in a flux distribution in accordance with literature-based findings. As a further validation of our model, the effect of oxygen deprivation (hypoxia on fluxes was simulated using an FBA-derivative approach, known as minimization of metabolic adjustment (MOMA. The results show the power of the

Positive Behavior Support and Applied Behavior Analysis

Science.gov (United States)

Johnston, J. M.; Foxx, R. M.; Jacobson, J. W.; Green, G.; Mulick, J. A.

2006-01-01

This article reviews the origins and characteristics of the positive behavior support (PBS) movement and examines those features in the context of the field of applied behavior analysis (ABA). We raise a number of concerns about PBS as an approach to delivery of behavioral services and its impact on how ABA is viewed by those in human services. We…

Progressive-Ratio Schedules and Applied Behavior Analysis

Science.gov (United States)

Poling, Alan

2010-01-01

Establishing appropriate relations between the basic and applied areas of behavior analysis has been of long and persistent interest to the author. In this article, the author illustrates that there is a direct relation between how hard an organism will work for access to an object or activity, as indexed by the largest ratio completed under a…

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Strategic decision analysis applied to borehole seismology

International Nuclear Information System (INIS)

Menke, M.M.; Paulsson, B.N.P.

1994-01-01

Strategic Decision Analysis (SDA) is the evolving body of knowledge on how to achieve high quality in the decision that shapes an organization's future. SDA comprises philosophy, process concepts, methodology, and tools for making good decisions. It specifically incorporates many concepts and tools from economic evaluation and risk analysis. Chevron Petroleum Technology Company (CPTC) has applied SDA to evaluate and prioritize a number of its most important and most uncertain R and D projects, including borehole seismology. Before SDA, there were significant issues and concerns about the value to CPTC of continuing to work on borehole seismology. The SDA process created a cross-functional team of experts to structure and evaluate this project. A credible economic model was developed, discrete risks and continuous uncertainties were assessed, and an extensive sensitivity analysis was performed. The results, even applied to a very restricted drilling program for a few years, were good enough to demonstrate the value of continuing the project. This paper explains the SDA philosophy concepts, and process and demonstrates the methodology and tools using the borehole seismology project example. SDA is useful in the upstream industry not just in the R and D/technology decisions, but also in major exploration and production decisions. Since a major challenge for upstream companies today is to create and realize value, the SDA approach should have a very broad applicability

A practical guide to propensity score analysis for applied clinical research.

Science.gov (United States)

Lee, Jaehoon; Little, Todd D

2017-11-01

Observational studies are often the only viable options in many clinical settings, especially when it is unethical or infeasible to randomly assign participants to different treatment régimes. In such case propensity score (PS) analysis can be applied to accounting for possible selection bias and thereby addressing questions of causal inference. Many PS methods exist, yet few guidelines are available to aid applied researchers in their conduct and evaluation of a PS analysis. In this article we give an overview of available techniques for PS estimation and application, balance diagnostic, treatment effect estimation, and sensitivity assessment, as well as recent advances. We also offer a tutorial that can be used to emulate the steps of PS analysis. Our goal is to provide information that will bring PS analysis within the reach of applied clinical researchers and practitioners. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Energy Technology Data Exchange (ETDEWEB)

Morgans, D. L. [CH2M Hill Plateau Remediation Company, Richland, WA (United States); Lindberg, S. L. [Intera Inc., Austin, TX (United States)

2017-09-20

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.”

Multi-variant pathway association analysis reveals the importance of genetic determinants of estrogen metabolism in breast and endometrial cancer susceptibility.

Directory of Open Access Journals (Sweden)

Yen Ling Low

2010-07-01

Full Text Available Despite the central role of estrogen exposure in breast and endometrial cancer development and numerous studies of genes in the estrogen metabolic pathway, polymorphisms within the pathway have not been consistently associated with these cancers. We posit that this is due to the complexity of multiple weak genetic effects within the metabolic pathway that can only be effectively detected through multi-variant analysis. We conducted a comprehensive association analysis of the estrogen metabolic pathway by interrogating 239 tagSNPs within 35 genes of the pathway in three tumor samples. The discovery sample consisted of 1,596 breast cancer cases, 719 endometrial cancer cases, and 1,730 controls from Sweden; and the validation sample included 2,245 breast cancer cases and 1,287 controls from Finland. We performed admixture maximum likelihood (AML-based global tests to evaluate the cumulative effect from multiple SNPs within the whole metabolic pathway and three sub-pathways for androgen synthesis, androgen-to-estrogen conversion, and estrogen removal. In the discovery sample, although no single polymorphism was significant after correction for multiple testing, the pathway-based AML global test suggested association with both breast (p(global = 0.034 and endometrial (p(global = 0.052 cancers. Further testing revealed the association to be focused on polymorphisms within the androgen-to-estrogen conversion sub-pathway, for both breast (p(global = 0.008 and endometrial cancer (p(global = 0.014. The sub-pathway association was validated in the Finnish sample of breast cancer (p(global = 0.015. Further tumor subtype analysis demonstrated that the association of the androgen-to-estrogen conversion sub-pathway was confined to postmenopausal women with sporadic estrogen receptor positive tumors (p(global = 0.0003. Gene-based AML analysis suggested CYP19A1 and UGT2B4 to be the major players within the sub-pathway. Our study indicates that the composite

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

Directory of Open Access Journals (Sweden)

Paolo Cossu-Rocca

Full Text Available 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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Triple phase boundary specific pathway analysis for quantitative characterization of solid oxide cell electrode microstructure

DEFF Research Database (Denmark)

Jørgensen, Peter Stanley; Ebbehøj, Søren Lyng; Hauch, Anne

2015-01-01

of the pathways through which they can be reached. New methods for performing TPB specific pathway analysis on 3D image data are introduced, analyzing the pathway properties of each TPB site in the electrode structure. The methods seek to provide additional information beyond whether the TPB sites are percolating......The density and percolation of Triple phase boundary sites are important quantities in analyzing microstructures of solid oxide fuel cell electrodes from tomography data. However, these measures do not provide descriptions of the quality of the TPB sites in terms of the length and radius...... or not by also analyzing the pathway length to the TPB sites and the bottleneck radius of the pathway. We show how these methods can be utilized in quantifying and relating the TPB specific results to cell test data of an electrode reduction protocol study for Ni/Scandia-and-Yttria-doped-Zirconia (Ni...

Parallel imaging of Drosophila embryos for quantitative analysis of genetic perturbations of the Ras pathway

Directory of Open Access Journals (Sweden)

Yogesh Goyal

2017-07-01

Full Text Available The Ras pathway patterns the poles of the Drosophila embryo by downregulating the levels and activity of a DNA-binding transcriptional repressor Capicua (Cic. We demonstrate that the spatiotemporal pattern of Cic during this signaling event can be harnessed for functional studies of mutations in the Ras pathway in human diseases. Our approach relies on a new microfluidic device that enables parallel imaging of Cic dynamics in dozens of live embryos. We found that although the pattern of Cic in early embryos is complex, it can be accurately approximated by a product of one spatial profile and one time-dependent amplitude. Analysis of these functions of space and time alone reveals the differential effects of mutations within the Ras pathway. Given the highly conserved nature of Ras-dependent control of Cic, our approach provides new opportunities for functional analysis of multiple sequence variants from developmental abnormalities and cancers.

A gene pathway analysis highlights the role of cellular adhesion molecules in multiple sclerosis susceptibility

DEFF Research Database (Denmark)

Damotte, V; Guillot-Noel, L; Patsopoulos, N A

2014-01-01

adhesion molecule (CAMs) biological pathway using Cytoscape software. This network is a strong candidate, as it is involved in the crossing of the blood-brain barrier by the T cells, an early event in MS pathophysiology, and is used as an efficient therapeutic target. We drew up a list of 76 genes...... in interaction with other genes as a group. Pathway analysis is an alternative way to highlight such group of genes. Using SNP association P-values from eight multiple sclerosis (MS) GWAS data sets, we performed a candidate pathway analysis for MS susceptibility by considering genes interacting in the cell...... belonging to the CAM network. We highlighted 64 networks enriched with CAM genes with low P-values. Filtering by a percentage of CAM genes up to 50% and rejecting enriched signals mainly driven by transcription factors, we highlighted five networks associated with MS susceptibility. One of them, constituted...

An Inverse Kinematic Approach Using Groebner Basis Theory Applied to Gait Cycle Analysis

Science.gov (United States)

2013-03-01

AN INVERSE KINEMATIC APPROACH USING GROEBNER BASIS THEORY APPLIED TO GAIT CYCLE ANALYSIS THESIS Anum Barki AFIT-ENP-13-M-02 DEPARTMENT OF THE AIR...copyright protection in the United States. AFIT-ENP-13-M-02 AN INVERSE KINEMATIC APPROACH USING GROEBNER BASIS THEORY APPLIED TO GAIT CYCLE ANALYSIS THESIS...APPROACH USING GROEBNER BASIS THEORY APPLIED TO GAIT CYCLE ANALYSIS Anum Barki, BS Approved: Dr. Ronald F. Tuttle (Chairman) Date Dr. Kimberly Kendricks

Automated tool for virtual screening and pharmacology-based pathway prediction and analysis

Directory of Open Access Journals (Sweden)

Sugandh Kumar

2017-10-01

Full Text Available The virtual screening is an effective tool for the lead identification in drug discovery. However, there are limited numbers of crystal structures available as compared to the number of biological sequences which makes (Structure Based Drug Discovery SBDD a difficult choice. The current tool is an attempt to automate the protein structure modelling and automatic virtual screening followed by pharmacology-based prediction and analysis. Starting from sequence(s, this tool automates protein structure modelling, binding site identification, automated docking, ligand preparation, post docking analysis and identification of hits in the biological pathways that can be modulated by a group of ligands. This automation helps in the characterization of ligands selectivity and action of ligands on a complex biological molecular network as well as on individual receptor. The judicial combination of the ligands binding different receptors can be used to inhibit selective biological pathways in a disease. This tool also allows the user to systemically investigate network-dependent effects of a drug or drug candidate.

Functional analysis of the MAPK pathways in fungi.

Science.gov (United States)

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.

Applied spectrophotometry: analysis of a biochemical mixture.

Science.gov (United States)

Trumbo, Toni A; Schultz, Emeric; Borland, Michael G; Pugh, Michael Eugene

2013-01-01

Spectrophotometric analysis is essential for determining biomolecule concentration of a solution and is employed ubiquitously in biochemistry and molecular biology. The application of the Beer-Lambert-Bouguer Lawis routinely used to determine the concentration of DNA, RNA or protein. There is however a significant difference in determining the concentration of a given species (RNA, DNA, protein) in isolation (a contrived circumstance) as opposed to determining that concentration in the presence of other species (a more realistic situation). To present the student with a more realistic laboratory experience and also to fill a hole that we believe exists in student experience prior to reaching a biochemistry course, we have devised a three week laboratory experience designed so that students learn to: connect laboratory practice with theory, apply the Beer-Lambert-Bougert Law to biochemical analyses, demonstrate the utility and limitations of example quantitative colorimetric assays, demonstrate the utility and limitations of UV analyses for biomolecules, develop strategies for analysis of a solution of unknown biomolecular composition, use digital micropipettors to make accurate and precise measurements, and apply graphing software. Copyright © 2013 Wiley Periodicals, Inc.

Benchmarking pathway interaction network for colorectal cancer to identify dysregulated pathways

Directory of Open Access Journals (Sweden)

Q. Wang

Full Text Available 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.

Applied Drama and the Higher Education Learning Spaces: A Reflective Analysis

Science.gov (United States)

Moyo, Cletus

2015-01-01

This paper explores Applied Drama as a teaching approach in Higher Education learning spaces. The exploration takes a reflective analysis approach by first examining the impact that Applied Drama has had on my career as a Lecturer/Educator/Teacher working in Higher Education environments. My engagement with Applied Drama practice and theory is…

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

Science.gov (United States)

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

The cardiopulmonary effects of ambient air pollution and mechanistic pathways: a comparative hierarchical pathway analysis.

Directory of Open Access Journals (Sweden)

Ananya Roy

Full Text Available 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.

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

Science.gov (United States)

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.

Genetic variation in the TP53 pathway and bladder cancer risk. a comprehensive analysis.

Directory of Open Access Journals (Sweden)

Silvia Pineda

Full Text Available Germline variants in TP63 have been consistently associated with several tumors, including bladder cancer, indicating the importance of TP53 pathway in cancer genetic susceptibility. However, variants in other related genes, including TP53 rs1042522 (Arg72Pro, still present controversial results. We carried out an in depth assessment of associations between common germline variants in the TP53 pathway and bladder cancer risk.We investigated 184 tagSNPs from 18 genes in 1,058 cases and 1,138 controls from the Spanish Bladder Cancer/EPICURO Study. Cases were newly-diagnosed bladder cancer patients during 1998-2001. Hospital controls were age-gender, and area matched to cases. SNPs were genotyped in blood DNA using Illumina Golden Gate and TaqMan assays. Cases were subphenotyped according to stage/grade and tumor p53 expression. We applied classical tests to assess individual SNP associations and the Least Absolute Shrinkage and Selection Operator (LASSO-penalized logistic regression analysis to assess multiple SNPs simultaneously.Based on classical analyses, SNPs in BAK1 (1, IGF1R (5, P53AIP1 (1, PMAIP1 (2, SERINPB5 (3, TP63 (3, and TP73 (1 showed significant associations at p-value≤0.05. However, no evidence of association, either with overall risk or with specific disease subtypes, was observed after correction for multiple testing (p-value≥0.8. LASSO selected the SNP rs6567355 in SERPINB5 with 83% of reproducibility. This SNP provided an OR = 1.21, 95%CI 1.05-1.38, p-value = 0.006, and a corrected p-value = 0.5 when controlling for over-estimation.We found no strong evidence that common variants in the TP53 pathway are associated with bladder cancer susceptibility. Our study suggests that it is unlikely that TP53 Arg72Pro is implicated in the UCB in white Europeans. SERPINB5 and TP63 variation deserve further exploration in extended studies.

Boundary conditions for pathways, safety analysis and basic criteria for low-level radiation waste site selection

International Nuclear Information System (INIS)

Saverot, P.

1994-01-01

There are three successive periods in the life of a disposal facility: the operating period, the institutional control period and the unrestricted site access period. The purpose of safety analysis of the disposal facility is to ensure that the radiological impacts for each period in the life of the facility are acceptable under all circumstances. Founded on a deterministic approach, this analysis leads to a determination of the maximum quantity of each radionuclide present in the facility at the beginning of the institutional control period in order for the impacts to be considered acceptable. Safety analysis involves the calculation of the radiological impacts of a given radiological inventory under a selected scenario, from all plausible scenarios of radionuclide migration to the environment in both normal and accident conditions, and taking into account other specified variables. The calculation itself involves an assessment of the quantities of radionuclides that could be released to the environment under the specific scenario selected and following identified pathways, and a determination of the resultant exposure, both internal and external, to the public. An iterative approach is used in the performance of pathways analyses. If the pathways analyses result in unacceptable radiological impacts, either the radiological inventory of the site is reduced or barrier characteristics not previously factored into the analysis are taken into account. New pathways analyses are then performed until the results are within the acceptable range. Once accepted by the safety authorities, the radiological inventory becomes the radiological capacity, which is the approved quantities of specific radionuclides that may be disposed of at the site. The following elaborates on the boundary conditions used in safety analyses and describes the types of pathways analyses performed for a LLW disposal facility

Functional Data Analysis Applied in Chemometrics

DEFF Research Database (Denmark)

Muller, Martha

nutritional status and metabolic phenotype. We want to understand how metabolomic spectra can be analysed using functional data analysis to detect the in uence of dierent factors on specic metabolites. These factors can include, for example, gender, diet culture or dietary intervention. In Paper I we apply...... representation of each spectrum. Subset selection of wavelet coecients generates the input to mixed models. Mixed-model methodology enables us to take the study design into account while modelling covariates. Bootstrap-based inference preserves the correlation structure between curves and enables the estimation...

Dual activation of pathways regulated by steroid receptors and peptide growth factors in primary prostate cancer revealed by Factor Analysis of microarray data

Directory of Open Access Journals (Sweden)

Fernandez Pedro L

2005-08-01

Full Text Available Abstract Background We use an approach based on Factor Analysis to analyze datasets generated for transcriptional profiling. The method groups samples into biologically relevant categories, and enables the identification of genes and pathways most significantly associated to each phenotypic group, while allowing for the participation of a given gene in more than one cluster. Genes assigned to each cluster are used for the detection of pathways predominantly activated in that cluster by finding statistically significant associated GO terms. We tested the approach with a published dataset of microarray experiments in yeast. Upon validation with the yeast dataset, we applied the technique to a prostate cancer dataset. Results Two major pathways are shown to be activated in organ-confined, non-metastatic prostate cancer: those regulated by the androgen receptor and by receptor tyrosine kinases. A number of gene markers (HER3, IQGAP2 and POR1 highlighted by the software and related to the later pathway have been validated experimentally a posteriori on independent samples. Conclusion Using a new microarray analysis tool followed by a posteriori experimental validation of the results, we have confirmed several putative markers of malignancy associated with peptide growth factor signalling in prostate cancer and revealed others, most notably ERRB3 (HER3. Our study suggest that, in primary prostate cancer, HER3, together or not with HER4, rather than in receptor complexes involving HER2, could play an important role in the biology of these tumors. These results provide new evidence for the role of receptor tyrosine kinases in the establishment and progression of prostate cancer.

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

Directory of Open Access Journals (Sweden)

Harrisham Kaur

2017-11-01

Full Text Available 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.

Pathway-based analysis of a melanoma genome-wide association study: analysis of genes related to tumour-immunosuppression.

Directory of Open Access Journals (Sweden)

Nils Schoof

Full Text Available Systemic immunosuppression is a risk factor for melanoma, and sunburn-induced immunosuppression is thought to be causal. Genes in immunosuppression pathways are therefore candidate melanoma-susceptibility genes. If variants within these genes individually have a small effect on disease risk, the association may be undetected in genome-wide association (GWA studies due to low power to reach a high significance level. Pathway-based approaches have been suggested as a method of incorporating a priori knowledge into the analysis of GWA studies. In this study, the association of 1113 single nucleotide polymorphisms (SNPs in 43 genes (39 genomic regions related to immunosuppression have been analysed using a gene-set approach in 1539 melanoma cases and 3917 controls from the GenoMEL consortium GWA study. The association between melanoma susceptibility and the whole set of tumour-immunosuppression genes, and also predefined functional subgroups of genes, was considered. The analysis was based on a measure formed by summing the evidence from the most significant SNP in each gene, and significance was evaluated empirically by case-control label permutation. An association was found between melanoma and the complete set of genes (p(emp=0.002, as well as the subgroups related to the generation of tolerogenic dendritic cells (p(emp=0.006 and secretion of suppressive factors (p(emp=0.0004, thus providing preliminary evidence of involvement of tumour-immunosuppression gene polymorphisms in melanoma susceptibility. The analysis was repeated on a second phase of the GenoMEL study, which showed no evidence of an association. As one of the first attempts to replicate a pathway-level association, our results suggest that low power and heterogeneity may present challenges.

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

Science.gov (United States)

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.

Applied Behavior Analysis: Current Myths in Public Education

Science.gov (United States)

Fielding, Cheryl; Lowdermilk, John; Lanier, Lauren L.; Fannin, Abigail G.; Schkade, Jennifer L.; Rose, Chad A.; Simpson, Cynthia G.

2013-01-01

The effective use of behavior management strategies and related policies continues to be a debated issue in public education. Despite overwhelming evidence espousing the benefits of the implementation of procedures derived from principles based on the science of applied behavior analysis (ABA), educators often indicate many common misconceptions…

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

Science.gov (United States)

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.

Simplified life cycle assessment models: methodological framework and applications to energy pathways

International Nuclear Information System (INIS)

Padey, Pierryves

2013-01-01

The energy transition debate is a key issue for today and the coming years. One of the challenges is to limit the environmental impacts of electricity production. Decision support tools, sufficiently accurate, simple to use, accounting for environmental aspects and favoring future energetic choices, must be implemented. However, the environmental assessment of the energy pathways is complex, and it means considering a two levels characterization. The 'energy pathway' is the first level and corresponds to its environmental distribution, to compare overall pathways. The 'system pathway' is the 2. level and compares environmental impacts of systems within each pathway. We have devised a generic methodology covering both necessary characterization levels by estimating the energy pathways environmental profiles while allowing a simple comparison of its systems environmental impacts. This methodology is based on the definition of a parameterized Life Cycle Assessment model and considers, through a Global Sensitivity Analysis, the environmental impacts of a large sample of systems representative of an energy pathway. As a second step, this methodology defines simplified models based on few key parameters identified as inducing the largest variability in the energy pathway environmental impacts. These models assess in a simple way the systems environmental impacts, avoiding any complex LCAs. This reduction methodology has been applied to the onshore wind power energy pathway in Europe and the photovoltaic energy pathway in France. (author)

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

Science.gov (United States)

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

Independent component and pathway-based analysis of miRNA-regulated gene expression in a model of type 1 diabetes

DEFF Research Database (Denmark)

Bang-Berthelsen, Claus Heiner; Pedersen, Lykke; Fløyel, Tina

2011-01-01

enrichment of sequence predicted targets, compared to only four miRNAs when using simple negative correlation. The ICs were enriched for miRNA targets that function in diabetes-relevant pathways e.g. type 1 and type 2 diabetes and maturity onset diabetes of the young (MODY). CONCLUSIONS: In this study, ICA...... (ICA). Here, we developed a novel target prediction method based on ICA that incorporates both seed matching and expression profiling of miRNA and mRNA expressions. The method was applied on a cellular model of type 1 diabetes. RESULTS: Microrray profiling identified eight miRNAs (miR-124...... between the predicted miRNA targets. Applying the method on a model of type 1 diabetes resulted in identification of eight miRNAs that appear to affect pathways of relevance to disease mechanisms in diabetes....

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

Science.gov (United States)

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

Allowable residual contamination levels of radionuclides in soil from pathway analysis

International Nuclear Information System (INIS)

Nyquist, J.E.; Baes, C.F. III.

1987-01-01

The uncertainty regarding radionuclide distributions among Remedial Action Program (RAP) sites and long-term decommissioning and closure options for these sites requires a flexible approach capable of handling different levels of contamination, dose limits, and closure scenarios. We identified a commercially available pathway analysis model, DECOM, which had been used previously in support of remedial activities involving contaminated soil at the Savannah River Plant. The DECOM computer code, which estimates concentrations of radionuclides uniformly distributed in soil that correspond to an annual effective dose equivalent, is written in BASIC and runs on an IBM PC or compatible microcomputer. We obtained the latest version of DECOM and modified it to make it more user friendly and applicable to the Oak Ridge National Laboratory (ORNL) RAP. Some modifications involved changes in default parameters or changes in models based on approaches used by the EPA in regulating remedial actions for hazardous substances. We created a version of DECOM as a LOTUS spreadsheet, using the same models as the BASIC version of DECOM. We discuss the specific modeling approaches taken, the regulatory framework that guided our efforts, the strengths and limitations of each approach, and areas for improvement. We also demonstrate how the LOTUS version of DECOM can be applied to specific problems that may be encountered during ORNL RAP activities. 18 refs., 2 figs., 3 tabs

Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases

Science.gov (United States)

Arakelyan, Arsen; Nersisyan, Lilit; Petrek, Martin; Löffler-Wirth, Henry; Binder, Hans

2016-01-01

Lung diseases are described by a wide variety of developmental mechanisms and clinical manifestations. Accurate classification and diagnosis of lung diseases are the bases for development of effective treatments. While extensive studies are conducted toward characterization of various lung diseases at molecular level, no systematic approach has been developed so far. Here we have applied a methodology for pathway-centered mining of high throughput gene expression data to describe a wide range of lung diseases in the light of shared and specific pathway activity profiles. We have applied an algorithm combining a Pathway Signal Flow (PSF) algorithm for estimation of pathway activity deregulation states in lung diseases and malignancies, and a Self Organizing Maps algorithm for classification and clustering of the pathway activity profiles. The analysis results allowed clearly distinguish between cancer and non-cancer lung diseases. Lung cancers were characterized by pathways implicated in cell proliferation, metabolism, while non-malignant lung diseases were characterized by deregulations in pathways involved in immune/inflammatory response and fibrotic tissue remodeling. In contrast to lung malignancies, chronic lung diseases had relatively heterogeneous pathway deregulation profiles. We identified three groups of interstitial lung diseases and showed that the development of characteristic pathological processes, such as fibrosis, can be initiated by deregulations in different signaling pathways. In conclusion, this paper describes the pathobiology of lung diseases from systems viewpoint using pathway centered high-dimensional data mining approach. Our results contribute largely to current understanding of pathological events in lung cancers and non-malignant lung diseases. Moreover, this paper provides new insight into molecular mechanisms of a number of interstitial lung diseases that have been studied to a lesser extent. PMID:27200087

Genome-Based Construction of the Metabolic Pathways of Orientia tsutsugamushi and Comparative Analysis within the Rickettsiales Order

Directory of Open Access Journals (Sweden)

Chan-Ki Min

2008-01-01

Full Text Available Orientia tsutsugamushi, the causative agent of scrub typhus, is an obligate intracellular bacterium that belongs to the order of Rickettsiales. Recently, we have reported that O. tsutsugamushi has a unique genomic structure, consisting of highly repetitive sequences, and suggested that it may provide valuable insight into the evolution of intracellular bacteria. Here, we have used genomic information to construct the major metabolic pathways of O. tsutsugamushi and performed a comparative analysis of the metabolic genes and pathways of O. tsutsugamushi with other members of the Rickettsiales order. While O. tsutsugamushi has the largest genome among the members of this order, mainly due to the presence of repeated sequences, its metabolic pathways have been highly streamlined. Overall, the metabolic pathways of O. tsutsugamushi were similar to Rickettsia but there were notable differences in several pathways including carbohydrate metabolism, the TCA cycle, and the synthesis of cell wall components as well as in the transport systems. Our results will provide a useful guide to the postgenomic analysis of O. tsutsugamushi and lead to a better understanding of the virulence and physiology of this intracellular pathogen.

The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer

Directory of Open Access Journals (Sweden)

Rosa Aghdam

2017-12-01

Full Text Available Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/.

Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

DEFF Research Database (Denmark)

Thomassen, Mads; Tan, Qihua; Kruse, Torben

2008-01-01

ABSTRACT: BACKGROUND: Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent stud...

Spectral analysis and filter theory in applied geophysics

CERN Document Server

Buttkus, Burkhard

2000-01-01

This book is intended to be an introduction to the fundamentals and methods of spectral analysis and filter theory and their appli­ cations in geophysics. The principles and theoretical basis of the various methods are described, their efficiency and effectiveness eval­ uated, and instructions provided for their practical application. Be­ sides the conventional methods, newer methods arediscussed, such as the spectral analysis ofrandom processes by fitting models to the ob­ served data, maximum-entropy spectral analysis and maximum-like­ lihood spectral analysis, the Wiener and Kalman filtering methods, homomorphic deconvolution, and adaptive methods for nonstation­ ary processes. Multidimensional spectral analysis and filtering, as well as multichannel filters, are given extensive treatment. The book provides a survey of the state-of-the-art of spectral analysis and fil­ ter theory. The importance and possibilities ofspectral analysis and filter theory in geophysics for data acquisition, processing an...

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

Science.gov (United States)

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.

Integrative Analysis of Gene Expression Data Including an Assessment of Pathway Enrichment for Predicting Prostate Cancer

Directory of Open Access Journals (Sweden)

Pingzhao Hu

2006-01-01

Full Text Available Background: Microarray technology has been previously used to identify genes that are differentially expressed between tumour and normal samples in a single study, as well as in syntheses involving multiple studies. When integrating results from several Affymetrix microarray datasets, previous studies summarized probeset-level data, which may potentially lead to a loss of information available at the probe-level. In this paper, we present an approach for integrating results across studies while taking probe-level data into account. Additionally, we follow a new direction in the analysis of microarray expression data, namely to focus on the variation of expression phenotypes in predefined gene sets, such as pathways. This targeted approach can be helpful for revealing information that is not easily visible from the changes in the individual genes. Results: We used a recently developed method to integrate Affymetrix expression data across studies. The idea is based on a probe-level based test statistic developed for testing for differentially expressed genes in individual studies. We incorporated this test statistic into a classic random-effects model for integrating data across studies. Subsequently, we used a gene set enrichment test to evaluate the significance of enriched biological pathways in the differentially expressed genes identified from the integrative analysis. We compared statistical and biological significance of the prognostic gene expression signatures and pathways identified in the probe-level model (PLM with those in the probeset-level model (PSLM. Our integrative analysis of Affymetrix microarray data from 110 prostate cancer samples obtained from three studies reveals thousands of genes significantly correlated with tumour cell differentiation. The bioinformatics analysis, mapping these genes to the publicly available KEGG database, reveals evidence that tumour cell differentiation is significantly associated with many

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.

Science.gov (United States)

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.

Research in applied mathematics, numerical analysis, and computer science

Science.gov (United States)

1984-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering (ICASE) in applied mathematics, numerical analysis, and computer science is summarized and abstracts of published reports are presented. The major categories of the ICASE research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers.

Applied behavior analysis: understanding and changing behavior in the community-a representative review.

Science.gov (United States)

Luyben, Paul D

2009-01-01

Applied behavior analysis, a psychological discipline, has been characterized as the science of behavior change (Chance, 2006). Research in applied behavior analysis has been published for approximately 40 years since the initial publication of the Journal of Applied Behavior Analysis in 1968. The field now encompasses a wide range of human behavior. Although much of the published research centers on problem behaviors that occur in schools and among people with disabilities, a substantial body of knowledge has emerged in community settings. This article provides a review of the behavioral community research published in the Journal of Applied Behavior Analysis as representative of this work, including research in the areas of home and family, health, safety, community involvement and the environment, recreation and sports, crime and delinquency, and organizations. In the interest of space, research in schools and with people with disabilities has been excluded from this review.

B. F. Skinner's Contributions to Applied Behavior Analysis

Science.gov (United States)

Morris, Edward K.; Smith, Nathaniel G.; Altus, Deborah E.

2005-01-01

Our paper reviews and analyzes B. F. Skinner's contributions to applied behavior analysis in order to assess his role as the field's originator and founder. We found, first, that his contributions fall into five categorizes: the style and content of his science, his interpretations of typical and atypical human behavior, the implications he drew…

Applied research in uncertainty modeling and analysis

CERN Document Server

Ayyub, Bilal

2005-01-01

Uncertainty has been a concern to engineers, managers, and scientists for many years. For a long time uncertainty has been considered synonymous with random, stochastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous. In the past forty years numerous tools that model uncertainty, above and beyond statistics, have been proposed by several engineers and scientists. The tool/method to model uncertainty in a specific context should really be chosen by considering the features of the phenomenon under consideration, not independent of what is known about the system and what causes uncertainty. In this fascinating overview of the field, the authors provide broad coverage of uncertainty analysis/modeling and its application. Applied Research in Uncertainty Modeling and Analysis presents the perspectives of various researchers and practitioners on uncertainty analysis and modeling outside their own fields and domain expertise. Rather than focusing explicitly on...

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

Science.gov (United States)

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.

The Lived Experience of Applied Science Graduates Who Complete the Applied Baccalaureate

Science.gov (United States)

Kujawa, Tricia A.

2012-01-01

The enrollment and transfer behaviors of college students are diverse. As a result college students travel various pathways to the baccalaureate degree. The purpose of this qualitative study was to better understand the lived experience of students who entered higher education through an associate of applied science (AAS) program and then…

Quantitative Assays for RAS Pathway Proteins and Phosphorylation States

Science.gov (United States)

The NCI CPTAC program is applying its expertise in quantitative proteomics to develop assays for RAS pathway proteins. Targets include key phosphopeptides that should increase our understanding of how the RAS pathway is regulated.

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

Science.gov (United States)

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.

X-ray fluorescence spectrometry applied to soil analysis

International Nuclear Information System (INIS)

Salvador, Vera Lucia Ribeiro; Sato, Ivone Mulako; Scapin Junior, Wilson Santo; Scapin, Marcos Antonio; Imakima, Kengo

1997-01-01

This paper studies the X-ray fluorescence spectrometry applied to the soil analysis. A comparative study of the WD-XRFS and ED-XRFS techniques was carried out by using the following soil samples: SL-1, SOIL-7 and marine sediment SD-M-2/TM, from IAEA, and clay, JG-1a from Geological Survey of Japan (GSJ)

Neutron activation analysis applied to energy and environment

International Nuclear Information System (INIS)

Lyon, W.S.

1975-01-01

Neutron activation analysis was applied to a number of problems concerned with energy production and the environment. Burning of fossil fuel, the search for new sources of uranium, possible presence of toxic elements in food and water, and the relationship of trace elements to cardiovascular disease are some of the problems in which neutron activation was used. (auth)

Research in progress in applied mathematics, numerical analysis, and computer science

Science.gov (United States)

1990-01-01

Research conducted at the Institute in Science and Engineering in applied mathematics, numerical analysis, and computer science is summarized. The Institute conducts unclassified basic research in applied mathematics in order to extend and improve problem solving capabilities in science and engineering, particularly in aeronautics and space.

Applied data analysis and modeling for energy engineers and scientists

CERN Document Server

Reddy, T Agami

2011-01-01

""Applied Data Analysis and Modeling for Energy Engineers and Scientists"" discusses mathematical models, data analysis, and decision analysis in modeling. The approach taken in this volume focuses on the modeling and analysis of thermal systems in an engineering environment, while also covering a number of other critical areas. Other material covered includes the tools that researchers and engineering professionals will need in order to explore different analysis methods, use critical assessment skills and reach sound engineering conclusions. The book also covers process and system design and

Protein design for pathway engineering.

Science.gov (United States)

Eriksen, Dawn T; Lian, Jiazhang; Zhao, Huimin

2014-02-01

Design and construction of biochemical pathways has increased the complexity of biosynthetically-produced compounds when compared to single enzyme biocatalysis. However, the coordination of multiple enzymes can introduce a complicated set of obstacles to overcome in order to achieve a high titer and yield of the desired compound. Metabolic engineering has made great strides in developing tools to optimize the flux through a target pathway, but the inherent characteristics of a particular enzyme within the pathway can still limit the productivity. Thus, judicious protein design is critical for metabolic and pathway engineering. This review will describe various strategies and examples of applying protein design to pathway engineering to optimize the flux through the pathway. The proteins can be engineered for altered substrate specificity/selectivity, increased catalytic activity, reduced mass transfer limitations through specific protein localization, and reduced substrate/product inhibition. Protein engineering can also be expanded to design biosensors to enable high through-put screening and to customize cell signaling networks. These strategies have successfully engineered pathways for significantly increased productivity of the desired product or in the production of novel compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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 (number data, and causal mechanisms of the five pathways require further study.

Genomes of rumen bacteria encode atypical pathways for fermenting hexoses to short-chain fatty acids

KAUST Repository

Hackmann, Timothy J.

2017-09-11

Bacteria have been thought to follow only a few well-recognized biochemical pathways when fermenting glucose or other hexoses. These pathways have been chiseled in the stone of textbooks for decades, with most sources rendering them as they appear in the classic 1986 text by Gottschalk. Still, it is unclear how broadly these pathways apply, given that they were established and delineated biochemically with only a few model organisms. Here we show that well-recognized pathways often cannot explain fermentation products formed by bacteria. In the most extensive analysis of its kind, we reconstructed pathways for glucose fermentation from genomes of 48 species and subspecies of bacteria from one environment (the rumen). In total, 44% of these bacteria had atypical pathways, including several that are completely unprecedented for bacteria or any organism. In detail, 8% of bacteria had an atypical pathway for acetate formation; 21% for propionate or succinate formation; 6% for butyrate formation; and 33% had an atypical or incomplete Embden-Meyerhof-Parnas pathway. This study shows that reconstruction of metabolic pathways-a common goal of omics studies-could be incorrect if well-recognized pathways are used for reference. Further, it calls for renewed efforts to delineate fermentation pathways biochemically. This article is protected by copyright. All rights reserved.

Intruder dose pathway analysis for the onsite disposal of commercial radioactive waste

International Nuclear Information System (INIS)

Kennedy, W.E. Jr.; Peloquin, R.A.; Napier, B.A.

1984-10-01

Because of uncertainties associated with assessing the potential risks from onsite burials of commercial radioactive waste, the US Nuclear Regulatory Commission (NRC) has amended its regulations to provide greater assurance that buried radioactive material will not present a hazard to public health and safety. The amended regulations now require licensees to apply for approval of proposed procedures for onsite disposal pursuant to 10 CFR 20.302. The NRC technically reviews these requests on a case-by-case basis. These technical reviews require modeling potential pathways to man and projecting radiation dose commitments. This paper contains a summary of our efforts to develop human-intrusion scenarios and to modify a version of the MAXI computer program for potential use by the NRC in reviewing applications for onsite radioactive waste disposal. The ONSITE/MAXI1 computer software package contains four computer codes. ONSITE is the interactive user interface that allows the end-user to simply and efficiently create and use the radiation-exposure scenarios. MAXI1 is then used with the scenario information to calculate the maximum annual dose to the exposed individual from selected pathways. 1 figure

Analysis of concrete beams using applied element method

Science.gov (United States)

Lincy Christy, D.; Madhavan Pillai, T. M.; Nagarajan, Praveen

2018-03-01

The Applied Element Method (AEM) is a displacement based method of structural analysis. Some of its features are similar to that of Finite Element Method (FEM). In AEM, the structure is analysed by dividing it into several elements similar to FEM. But, in AEM, elements are connected by springs instead of nodes as in the case of FEM. In this paper, background to AEM is discussed and necessary equations are derived. For illustrating the application of AEM, it has been used to analyse plain concrete beam of fixed support condition. The analysis is limited to the analysis of 2-dimensional structures. It was found that the number of springs has no much influence on the results. AEM could predict deflection and reactions with reasonable degree of accuracy.

Branching points for transition pathways: assessing responses of actors to challenges on pathways to a low carbon future

International Nuclear Information System (INIS)

Foxon, Timothy J.; Pearson, Peter J.G.; Arapostathis, Stathis; Carlsson-Hyslop, Anna; Thornton, Judith

2013-01-01

This paper describes initial analysis of branching points on a set of transition pathways to a UK low carbon electricity future by 2050. As described in other papers in this special issue, we are exploring and analysing a set of core transition pathways, based on alternative governance patterns in which the ‘logics’ of market actors, government actors and civil society actors, respectively dominate. This core pathway analysis is enhanced by analyses of branching points within and across the pathways, which informs how competition between different logics plays out at key decision points. Branching points are defined as key decision points at which choices made by actors, in response to internal or external stresses or triggers, determine whether and in what ways the pathway is followed. A set of initial branching points for our three core transition pathways is identified through project and stakeholder workshops, and drawing on analysis of actors’ choices and responses at past branching points in energy system transitions. The potential responses of the actors are identified at these branching points, and risk mitigation strategies are formulated for the dominant actors to reinforce that pathway, as well as opportunities for actors to move away from the pathway. - Highlights: Transition Pathways is analysing three potential pathways to a low carbon future. ► Stresses lead to branching points, where actors make choices, creating pathways. ► These choices may lead to path-dependency. ► Differences in governance logics within transition pathways are also analysed. ► Studying branching points adds theoretical understanding and policy relevance to TP.

International publication trends in the Journal of Applied Behavior Analysis: 2000-2014.

Science.gov (United States)

Martin, Neil T; Nosik, Melissa R; Carr, James E

2016-06-01

Dymond, Clarke, Dunlap, and Steiner's (2000) analysis of international publication trends in the Journal of Applied Behavior Analysis (JABA) from 1970 to 1999 revealed low numbers of publications from outside North America, leading the authors to express concern about the lack of international involvement in applied behavior analysis. They suggested that a future review would be necessary to evaluate any changes in international authorship in the journal. As a follow-up, we analyzed non-U.S. publication trends in the most recent 15 years of JABA and found similar results. We discuss potential reasons for the relative paucity of international authors and suggest potential strategies for increasing non-U.S. contributions to the advancement of behavior analysis. © 2015 Society for the Experimental Analysis of Behavior.

Pathways of early fatherhood, marriage, and employment: a latent class growth analysis.

Science.gov (United States)

Dariotis, Jacinda K; Pleck, Joseph H; Astone, Nan M; Sonenstein, Freya L

2011-05-01

In the National Longitudinal Survey of Youth 1979 (NLSY79), young fathers include heterogeneous subgroups with varying early life pathways in terms of fatherhood timing, the timing of first marriage, and holding full-time employment. Using latent class growth analysis with 10 observations between ages 18 and 37, we derived five latent classes with median ages of first fatherhood below the cohort median (26.4), constituting distinct early fatherhood pathways representing 32.4% of NLSY men: (A) Young Married Fathers, (B) Teen Married Fathers, (C) Young Underemployed Married Fathers, (D) Young Underemployed Single Fathers, and (E) Young Later-Marrying Fathers. A sixth latent class of men who become fathers around the cohort median, following full-time employment and marriage (On-Time On-Sequence Fathers), is the comparison group. With sociodemographic background controlled, all early fatherhood pathways show disadvantage in at least some later-life circumstances (earnings, educational attainment, marital status, and incarceration). The extent of disadvantage is greater when early fatherhood occurs at relatively younger ages (before age 20), occurs outside marriage, or occurs outside full-time employment. The relative disadvantage associated with early fatherhood, unlike early motherhood, increases over the life course.

Novel degradation pathway and kinetic analysis for buprofezin removal by newly isolated Bacillus sp.

Science.gov (United States)

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.

The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer.

Science.gov (United States)

Aghdam, Rosa; Baghfalaki, Taban; Khosravi, Pegah; Saberi Ansari, Elnaz

2017-12-01

Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM) method was applied to detect the significant genes in rectal and lung cancers to showcase the utility of imputation approaches in preserving significant genes. To determine the impact of different imputation methods on the identification of important genes, the chi-squared test was used to compare the proportions of overlaps between significant genes detected from original data and those detected from the imputed datasets. Additionally, the significant genes are tested for their enrichment in important pathways, using the ConsensusPathDB. Our results showed that almost all the significant genes and pathways of the original dataset can be detected in all imputed datasets, indicating that there is no significant difference in the performance of various imputation methods tested. The source code and selected datasets are available on http://profiles.bs.ipm.ir/softwares/imputation_methods/. Copyright © 2017. Production and hosting by Elsevier B.V.

Model Proposition for the Fiscal Policies Analysis Applied in Economic Field

Directory of Open Access Journals (Sweden)

Larisa Preda

2007-05-01

Full Text Available This paper presents a study about fiscal policy applied in economic development. Correlations between macroeconomics and fiscal indicators signify the first steep in our analysis. Next step is a new model proposal for the fiscal and budgetary choices. This model is applied on the date of the Romanian case.

Compound-Specific Isotopic Analysis of Meteoritic Amino Acids as a Tool for Evaluating Potential Formation Pathways

Science.gov (United States)

Elsila, Jamie E.; Burton, Aaron S.; Callahan, Michael C.; Charnley, Steven B.; Glavin, Daniel P.; Dworkin, Jason P.

2012-01-01

Measurements of stable hydrogen, carbon, and nitrogen isotopic ratios (delta D, delta C-13, delta N-15) of organic compounds can reveal information about their origin and formation pathways. Several formation mechanisms and environments have been postulated for the amino acids detected in carbonaceous chondrites. As each proposed mechanism utilizes different precursor molecules, the isotopic signatures of the resulting amino acids may point towards the most likely of these proposed pathways. The technique of gas chromatography coupled with mass spectrometry and isotope ratio mass spectrometry provides compound-specific structural and isotopic information from a single splitless injection, enhancing the amount of information gained from small amounts of precious samples such as carbonaceous chondrites. We have applied this technique to measure the compound-specific C, N, and H isotopic ratios of amino acids from seven CM and CR carbonaceous chondrites. We are using these measurements to evaluate predictions of expected isotopic enrichments from potential formation pathways and environments, leading to a better understanding of the origin of these compounds.

Network reconstruction of the mouse secretory pathway applied on CHO cell transcriptome data

DEFF Research Database (Denmark)

Lund, Anne Mathilde; Kaas, Christian Schrøder; Brandl, Julian

2017-01-01

, counting 801 different components in mouse. By employing our mouse RECON to the CHO-K1 genome in a comparative genomic approach, we could reconstruct the protein secretory pathway of CHO cells counting 764 CHO components. This RECON furthermore facilitated the development of three alternative methods...... to study protein secretion through graphical visualizations of omics data. We have demonstrated the use of these methods to identify potential new and known targets for engineering improved growth and IgG production, as well as the general observation that CHO cells seem to have less strict transcriptional...... regulation of protein secretion than healthy mouse cells.  Conclusions: The RECON of the secretory pathway represents a strong tool for interpretation of data related to protein secretion as illustrated with transcriptomic data of Chinese Hamster Ovary (CHO) cells, the main platform for mammalian protein...

Pathway Analysis and Metabolites Identification by Metabolomics of Etiolation Substrate from Fresh-Cut Chinese Water Chestnut (Eleocharis tuberosa

Directory of Open Access Journals (Sweden)

Yi-Xiao Li

2016-12-01

Full Text Available Fresh-cut Chinese water chestnuts (CWC turn yellow after being peeled, reducing their shelf life and commercial value. Metabolomics, the systematic study of the full complement of small molecular metabolites, was useful for clarifying the mechanism of fresh-cut CWC etiolation and developing methods to inhibit yellowing. In this study, metabolic alterations associated with etiolation at different growth stages (0 day, 2 days, 3 days, 4 days, 5 days from fresh-cut CWC were investigated using LC–MS and analyzed by pattern recognition methods (principal component analysis (PCA, partial least squares-discriminant analysis (PLS-DA, and orthogonal projection to latent structures-discriminant analysis (OPLS-DA. The metabolic pathways of the etiolation molecules were elucidated. The main metabolic pathway appears to be the conversion of phenylalanine to p-coumaroyl-CoA, followed by conversion to naringenin chalcone, to naringenin, and naringenin then following different pathways. Firstly, it can transform into apigenin and its derivatives; secondly, it can produce eriodictyol and its derivatives; and thirdly it can produce dihydrokaempferol, quercetin, and myricetin. The eriodictyol can be further transformed to luteolin, cyanidin, dihydroquercetin, dihydrotricetin, and others. This is the first reported use of metabolomics to study the metabolic pathways of the etiolation of fresh-cut CWC.

Deregulation of purine pathway in Bacillus subtilis and its use in riboflavin biosynthesis

Science.gov (United States)

2014-01-01

Background Purine nucleotides are essential metabolites for living organisms because they are involved in many important processes, such as nucleic acid synthesis, energy supply, and biosynthesis of several amino acids and riboflavin. Owing to the pivotal roles of purines in cell physiology, the pool of intracellular purine nucleotides must be maintained under strict control, and hence the de novo purine biosynthetic pathway is tightly regulated by transcription repression and inhibition mechanism. Deregulation of purine pathway is essential for this pathway engineering in Bacillus subtilis. Results Deregulation of purine pathway was attempted to improve purine nucleotides supply, based on a riboflavin producer B. subtilis strain with modification of its rib operon. To eliminate transcription repression, the pur operon repressor PurR and the 5’-UTR of pur operon containing a guanine-sensing riboswitch were disrupted. Quantitative RT-PCR analysis revealed that the relative transcription levels of purine genes were up-regulated about 380 times. Furthermore, site-directed mutagenesis was successfully introduced into PRPP amidotransferase (encoded by purF) to remove feedback inhibition by homologous alignment and analysis. Overexpression of the novel mutant PurF (D293V, K316Q and S400W) significantly increased PRPP amidotransferase activity and triggered a strong refractory effect on purine nucleotides mediated inhibition. Intracellular metabolite target analysis indicated that the purine nucleotides supply in engineered strains was facilitated by a stepwise gene-targeted deregulation. With these genetic manipulations, we managed to enhance the metabolic flow through purine pathway and consequently increased riboflavin production 3-fold (826.52 mg/L) in the purF-VQW mutant strain. Conclusions A sequential optimization strategy was applied to deregulate the rib operon and purine pathway of B. subtilis to create genetic diversities and to improve riboflavin production

Introduction to applied statistical signal analysis guide to biomedical and electrical engineering applications

CERN Document Server

Shiavi, Richard

2007-01-01

Introduction to Applied Statistical Signal Analysis is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech.Introduction to Applied Statistical Signal Analysis intertwines theory and implementation with practical examples and exercises. Topics presented in detail include: mathematical

Uncertainty and sensitivity analysis of food pathway results with the MACCS Reactor Accident Consequence Model

International Nuclear Information System (INIS)

Helton, J.C.; Johnson, J.D.; Rollstin, J.A.; Shiver, A.W.; Sprung, J.L.

1995-01-01

Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the food pathways associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 87 imprecisely-known input variables on the following reactor accident consequences are studied: crop growing season dose, crop long-term dose, milk growing season dose, total food pathways dose, total ingestion pathways dose, total long-term pathways dose, area dependent cost, crop disposal cost, milk disposal cost, condemnation area, crop disposal area and milk disposal area. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: fraction of cesium deposition on grain fields that is retained on plant surfaces and transferred directly to grain, maximum allowable ground concentrations of Cs-137 and Sr-90 for production of crops, ground concentrations of Cs-134, Cs-137 and I-131 at which the disposal of milk will be initiated due to accidents that occur during the growing season, ground concentrations of Cs-134, I-131 and Sr-90 at which the disposal of crops will be initiated due to accidents that occur during the growing season, rate of depletion of Cs-137 and Sr-90 from the root zone, transfer of Sr-90 from soil to legumes, transfer of Cs-137 from soil to pasture, transfer of cesium from animal feed to meat, and the transfer of cesium, iodine and strontium from animal feed to milk

Uncertainty and sensitivity analysis of food pathway results with the MACCS reactor accident consequence model

International Nuclear Information System (INIS)

Helton, J.C.; Johnson, J.D.; Rollstin, J.A.; Shiver, A.W.; Sprung, J.L.

1995-01-01

Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis are used in an investigation with the MACCS model of the food pathways associated with a severe accident at a nuclear power station. The primary purpose of this study is to provide guidance on the variables to be considered in future review work to reduce the uncertainty in the important variables used in the calculation of reactor accident consequences. The effects of 87 imprecisely-known input variables on the following reactor accident consequences are studied: crop growing-season dose, crop long-term dose, milk growing-season dose, total food pathways dose, total ingestion pathways dose, total long-term pathways dose, area dependent cost, crop disposal cost, milk disposal cost, condemnation area, crop disposal area and milk disposal area. When the predicted variables are considered collectively, the following input variables were found to be the dominant contributors to uncertainty: fraction of cesium deposition on grain fields that is retained on plant surfaces and transferred directly to grain, maximum allowable ground concentrations of Cs-137 and Sr-90 for production of crops, ground concentrations of Cs-134, Cs-137 and I-131 at which the disposal of milk will be initiated due to accidents that occur during the growing season, ground concentrations of Cs-134, I-131 and Sr-90 at which the disposal of crops will be initiated due to accidents that occur during the growing season, rate of depletion of Cs-137 and Sr-90 from the root zone, transfer of Sr-90 from soil to legumes, transfer of Cs-137 from soil to pasture, transfer of cesium from animal feed to meat, and the transfer of cesium, iodine and strontium from animal feed to milk

Molecular pathways involved in neuronal cell adhesion and membrane scaffolding contribute to schizophrenia and bipolar disorder susceptibility.

LENUS (Irish Health Repository)

O'Dushlaine, C

2011-03-01

Susceptibility to schizophrenia and bipolar disorder may involve a substantial, shared contribution from thousands of common genetic variants, each of small effect. Identifying whether risk variants map to specific molecular pathways is potentially biologically informative. We report a molecular pathway analysis using the single-nucleotide polymorphism (SNP) ratio test, which compares the ratio of nominally significant (P<0.05) to nonsignificant SNPs in a given pathway to identify the \\'enrichment\\' for association signals. We applied this approach to the discovery (the International Schizophrenia Consortium (n=6909)) and validation (Genetic Association Information Network (n=2729)) of schizophrenia genome-wide association study (GWAS) data sets. We investigated each of the 212 experimentally validated pathways described in the Kyoto Encyclopaedia of Genes and Genomes in the discovery sample. Nominally significant pathways were tested in the validation sample, and five pathways were found to be significant (P=0.03-0.001); only the cell adhesion molecule (CAM) pathway withstood conservative correction for multiple testing. Interestingly, this pathway was also significantly associated with bipolar disorder (Wellcome Trust Case Control Consortium (n=4847)) (P=0.01). At a gene level, CAM genes associated in all three samples (NRXN1 and CNTNAP2), which were previously implicated in specific language disorder, autism and schizophrenia. The CAM pathway functions in neuronal cell adhesion, which is critical for synaptic formation and normal cell signaling. Similar pathways have also emerged from a pathway analysis of autism, suggesting that mechanisms involved in neuronal cell adhesion may contribute broadly to neurodevelopmental psychiatric phenotypes.

Applied Behavior Analysis Is a Science And, Therefore, Progressive

Science.gov (United States)

Leaf, Justin B.; Leaf, Ronald; McEachin, John; Taubman, Mitchell; Ala'i-Rosales, Shahla; Ross, Robert K.; Smith, Tristram; Weiss, Mary Jane

2016-01-01

Applied behavior analysis (ABA) is a science and, therefore, involves progressive approaches and outcomes. In this commentary we argue that the spirit and the method of science should be maintained in order to avoid reductionist procedures, stifled innovation, and rote, unresponsive protocols that become increasingly removed from meaningful…

WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research.

Science.gov (United States)

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.

DEGAS: de novo discovery of dysregulated pathways in human diseases.

Directory of Open Access Journals (Sweden)

Igor Ulitsky

Full Text Available BACKGROUND: Molecular studies of the human disease transcriptome typically involve a search for genes whose expression is significantly dysregulated in sick individuals compared to healthy controls. Recent studies have found that only a small number of the genes in human disease-related pathways show consistent dysregulation in sick individuals. However, those studies found that some pathway genes are affected in most sick individuals, but genes can differ among individuals. While a pathway is usually defined as a set of genes known to share a specific function, pathway boundaries are frequently difficult to assign, and methods that rely on such definition cannot discover novel pathways. Protein interaction networks can potentially be used to overcome these problems. METHODOLOGY/PRINCIPAL FINDINGS: We present DEGAS (DysrEgulated Gene set Analysis via Subnetworks, a method for identifying connected gene subnetworks significantly enriched for genes that are dysregulated in specimens of a disease. We applied DEGAS to seven human diseases and obtained statistically significant results that appear to home in on compact pathways enriched with hallmarks of the diseases. In Parkinson's disease, we provide novel evidence for involvement of mRNA splicing, cell proliferation, and the 14-3-3 complex in the disease progression. DEGAS is available as part of the MATISSE software package (http://acgt.cs.tau.ac.il/matisse. CONCLUSIONS/SIGNIFICANCE: The subnetworks identified by DEGAS can provide a signature of the disease potentially useful for diagnosis, pinpoint possible pathways affected by the disease, and suggest targets for drug intervention.

Applying Evolutionary Genetics to Developmental Toxicology and Risk Assessment

Science.gov (United States)

Leung, Maxwell C. K.; Procter, Andrew C.; Goldstone, Jared V.; Foox, Jonathan; DeSalle, Robert; Mattingly, Carolyn J.; Siddall, Mark E.; Timme-Laragy, Alicia R.

2018-01-01

Evolutionary thinking continues to challenge our views on health and disease. Yet, there is a communication gap between evolutionary biologists and toxicologists in recognizing the connections among developmental pathways, high-throughput screening, and birth defects in humans. To increase our capability in identifying potential developmental toxicants in humans, we propose to apply evolutionary genetics to improve the experimental design and data interpretation with various in vitro and whole-organism models. We review five molecular systems of stress response and update 18 consensual cell-cell signaling pathways that are the hallmark for early development, organogenesis, and differentiation; and revisit the principles of teratology in light of recent advances in high-throughput screening, big data techniques, and systems toxicology. Multiscale systems modeling plays an integral role in the evolutionary approach to cross-species extrapolation. Phylogenetic analysis and comparative bioinformatics are both valuable tools in identifying and validating the molecular initiating events that account for adverse developmental outcomes in humans. The discordance of susceptibility between test species and humans (ontogeny) reflects their differences in evolutionary history (phylogeny). This synthesis not only can lead to novel applications in developmental toxicity and risk assessment, but also can pave the way for applying an evo-devo perspective to the study of developmental origins of health and disease. PMID:28267574

Exploration of molecular pathways mediating electric field-directed Schwann cell migration by RNA-Seq

Science.gov (United States)

Yao, Li; Li, Yongchao; Knapp, Jennifer; Smith, Peter

2015-01-01

In peripheral nervous systems, Schwann cells wrap around axons of motor and sensory neurons to form the myelin sheath. Following spinal cord injury, Schwann cells regenerate and migrate to the lesion and are involved in the spinal cord regeneration process. Transplantation of Schwann cells into injured neural tissue results in enhanced spinal axonal regeneration. Effective directional migration of Schwann cells is critical in the neural regeneration process. In this study, we report that Schwann cells migrate anodally in an applied electric field (EF). The directedness and displacement of anodal migration increased significantly when the strength of the EF increased from 50 mV/mm to 200 mV/mm. The EF did not significantly affect the cell migration speed. To explore the genes and signaling pathways that regulate cell migration in EFs, we performed a comparative analysis of differential gene expression between cells stimulated with an EF (100 mV/mm) and those without using next-generation RNA sequencing, verified by RT-qPCR. Based on the cut-off criteria (FC > 1.2, q cells versus EF-stimulated cells. A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis found that compared to the control group, 21 pathways are down-regulated, while 10 pathways are up-regulated. Differentially expressed genes participate in multiple cellular signaling pathways involved in the regulation of cell migration, including pathways of regulation of actin cytoskeleton, focal adhesion, and PI3K-Akt. PMID:25557037

Putative drug and vaccine target protein identification using comparative genomic analysis of KEGG annotated metabolic pathways of Mycoplasma hyopneumoniae.

Science.gov (United States)

Damte, Dereje; Suh, Joo-Won; Lee, Seung-Jin; Yohannes, Sileshi Belew; Hossain, Md Akil; Park, Seung-Chun

2013-07-01

In the present study, a computational comparative and subtractive genomic/proteomic analysis aimed at the identification of putative therapeutic target and vaccine candidate proteins from Kyoto Encyclopedia of Genes and Genomes (KEGG) annotated metabolic pathways of Mycoplasma hyopneumoniae was performed for drug design and vaccine production pipelines against M.hyopneumoniae. The employed comparative genomic and metabolic pathway analysis with a predefined computational systemic workflow extracted a total of 41 annotated metabolic pathways from KEGG among which five were unique to M. hyopneumoniae. A total of 234 proteins were identified to be involved in these metabolic pathways. Although 125 non homologous and predicted essential proteins were found from the total that could serve as potential drug targets and vaccine candidates, additional prioritizing parameters characterize 21 proteins as vaccine candidate while druggability of each of the identified proteins evaluated by the DrugBank database prioritized 42 proteins suitable for drug targets. Copyright © 2013 Elsevier Inc. All rights reserved.

Aligning ontologies and integrating textual evidence for pathway analysis of microarray data

Energy Technology Data Exchange (ETDEWEB)

Gopalan, Banu; Posse, Christian; Sanfilippo, Antonio P.; Stenzel-Poore, Mary; Stevens, S.L.; Castano, Jose; Beagley, Nathaniel; Riensche, Roderick M.; Baddeley, Bob; Simon, R.P.; Pustejovsky, James

2006-10-08

Expression arrays are introducing a paradigmatic change in biology by shifting experimental approaches from single gene studies to genome-level analysis, monitoring the ex-pression levels of several thousands of genes in parallel. The massive amounts of data obtained from the microarray data needs to be integrated and interpreted to infer biological meaning within the context of information-rich pathways. In this paper, we present a methodology that integrates textual information with annotations from cross-referenced ontolo-gies to map genes to pathways in a semi-automated way. We illustrate this approach and compare it favorably to other tools by analyzing the gene expression changes underlying the biological phenomena related to stroke. Stroke is the third leading cause of death and a major disabler in the United States. Through years of study, researchers have amassed a significant knowledge base about stroke, and this knowledge, coupled with new technologies, is providing a wealth of new scientific opportunities. The potential for neu-roprotective stroke therapy is enormous. However, the roles of neurogenesis, angiogenesis, and other proliferative re-sponses in the recovery process following ischemia and the molecular mechanisms that lead to these processes still need to be uncovered. Improved annotation of genomic and pro-teomic data, including annotation of pathways in which genes and proteins are involved, is required to facilitate their interpretation and clinical application. While our approach is not aimed at replacing existing curated pathway databases, it reveals multiple hidden relationships that are not evident with the way these databases analyze functional groupings of genes from the Gene Ontology.

GEP analysis validates high risk MDS and acute myeloid leukemia post MDS mice models and highlights novel dysregulated pathways.

Science.gov (United States)

Guerenne, Laura; Beurlet, Stéphanie; Said, Mohamed; Gorombei, Petra; Le Pogam, Carole; Guidez, Fabien; de la Grange, Pierre; Omidvar, Nader; Vanneaux, Valérie; Mills, Ken; Mufti, Ghulam J; Sarda-Mantel, Laure; Noguera, Maria Elena; Pla, Marika; Fenaux, Pierre; Padua, Rose Ann; Chomienne, Christine; Krief, Patricia

2016-01-27

In spite of the recent discovery of genetic mutations in most myelodysplasic (MDS) patients, the pathophysiology of these disorders still remains poorly understood, and only few in vivo models are available to help unravel the disease. We performed global specific gene expression profiling and functional pathway analysis in purified Sca1+ cells of two MDS transgenic mouse models that mimic human high-risk MDS (HR-MDS) and acute myeloid leukemia (AML) post MDS, with NRASD12 and BCL2 transgenes under the control of different promoters MRP8NRASD12/tethBCL-2 or MRP8[NRASD12/hBCL-2], respectively. Analysis of dysregulated genes that were unique to the diseased HR-MDS and AML post MDS mice and not their founder mice pointed first to pathways that had previously been reported in MDS patients, including DNA replication/damage/repair, cell cycle, apoptosis, immune responses, and canonical Wnt pathways, further validating these models at the gene expression level. Interestingly, pathways not previously reported in MDS were discovered. These included dysregulated genes of noncanonical Wnt pathways and energy and lipid metabolisms. These dysregulated genes were not only confirmed in a different independent set of BM and spleen Sca1+ cells from the MDS mice but also in MDS CD34+ BM patient samples. These two MDS models may thus provide useful preclinical models to target pathways previously identified in MDS patients and to unravel novel pathways highlighted by this study.

Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

Directory of Open Access Journals (Sweden)

Jesús Lascorz

2011-01-01

Full Text Available Background: A large number of gene expression profiling (GEP studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-regulated in colorectal carcinogenesis. Materials and Methods: We started the analysis with 242 unique annotated genes that had been reported by any of three recent meta-analyses covering GEP studies on genes differentially expressed in carcinoma vs normal mucosa. Most of these genes (218, 91.9% had been reported in at least three GEP studies. These 242 genes were submitted to bioinformatic analysis using a total of nine tools to detect enrichment of Gene Ontology (GO categories or Kyoto Encyclopedia of Genes and Genomes (KEGG pathways. As a final consistency criterion the pathway categories had to be enriched by several tools to be taken into consideration. Results: Our pathway-based enrichment analysis identified the categories of ribosomal protein constituents, extracellular matrix receptor interaction, carbonic anhydrase isozymes, and a general category related to inflammation and cellular response as significantly and consistently overrepresented entities. Conclusions: We triaged the genes covered by the published GEP literature on colorectal carcinogenesis and subjected them to multiple enrichment tools in order to identify the consistently enriched gene categories. These turned out to have known functional relationships to cancer development and thus deserve further investigation.

Yeast glucose pathways converge on the transcriptional regulation of trehalose biosynthesis

Directory of Open Access Journals (Sweden)

Apweiler Eva

2012-06-01

Full Text Available Abstract Background Cellular glucose availability is crucial for the functioning of most biological processes. Our understanding of the glucose regulatory system has been greatly advanced by studying the model organism Saccharomyces cerevisiae, but many aspects of this system remain elusive. To understand the organisation of the glucose regulatory system, we analysed 91 deletion mutants of the different glucose signalling and metabolic pathways in Saccharomyces cerevisiae using DNA microarrays. Results In general, the mutations do not induce pathway-specific transcriptional responses. Instead, one main transcriptional response is discerned, which varies in direction to mimic either a high or a low glucose response. Detailed analysis uncovers established and new relationships within and between individual pathways and their members. In contrast to signalling components, metabolic components of the glucose regulatory system are transcriptionally more frequently affected. A new network approach is applied that exposes the hierarchical organisation of the glucose regulatory system. Conclusions The tight interconnection between the different pathways of the glucose regulatory system is reflected by the main transcriptional response observed. Tps2 and Tsl1, two enzymes involved in the biosynthesis of the storage carbohydrate trehalose, are predicted to be the most downstream transcriptional components. Epistasis analysis of tps2Δ double mutants supports this prediction. Although based on transcriptional changes only, these results suggest that all changes in perceived glucose levels ultimately lead to a shift in trehalose biosynthesis.

Dimensional Analysis with space discrimination applied to Fickian difussion phenomena

International Nuclear Information System (INIS)

Diaz Sanchidrian, C.; Castans, M.

1989-01-01

Dimensional Analysis with space discrimination is applied to Fickian difussion phenomena in order to transform its partial differen-tial equations into ordinary ones, and also to obtain in a dimensionl-ess fom the Ficks second law. (Author)

KeyPathwayMinerWeb

DEFF Research Database (Denmark)

List, Markus; Alcaraz, Nicolas; Dissing-Hansen, Martin

2016-01-01

, for instance), KeyPathwayMiner extracts connected sub-networks containing a high number of active or differentially regulated genes (proteins, metabolites) in the molecular profiles. The web interface at (http://keypathwayminer.compbio.sdu.dk) implements all core functionalities of the KeyPathwayMiner tool set......We present KeyPathwayMinerWeb, the first online platform for de novo pathway enrichment analysis directly in the browser. Given a biological interaction network (e.g. protein-protein interactions) and a series of molecular profiles derived from one or multiple OMICS studies (gene expression...... such as data integration, input of background knowledge, batch runs for parameter optimization and visualization of extracted pathways. In addition to an intuitive web interface, we also implemented a RESTful API that now enables other online developers to integrate network enrichment as a web service...

Ontology modeling for generation of clinical pathways

Directory of Open Access Journals (Sweden)

Jasmine Tehrani

2012-12-01

Full Text Available Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the

Beyond Time out and Table Time: Today's Applied Behavior Analysis for Students with Autism

Science.gov (United States)

Boutot, E. Amanda; Hume, Kara

2012-01-01

Recent mandates related to the implementation of evidence-based practices for individuals with autism spectrum disorder (ASD) require that autism professionals both understand and are able to implement practices based on the science of applied behavior analysis (ABA). The use of the term "applied behavior analysis" and its related concepts…

Conversation Analysis and Applied Linguistics.

Science.gov (United States)

Schegloff, Emanuel A.; Koshik, Irene; Jacoby, Sally; Olsher, David

2002-01-01

Offers biographical guidance on several major areas of conversation-analytic work--turn-taking, repair, and word selection--and indicates past or potential points of contact with applied linguistics. Also discusses areas of applied linguistic work. (Author/VWL)

Elucidating Turnover Pathways of Bioactive Small Molecules by Isotopomer Analysis: The Persistent Organic Pollutant DDT

Science.gov (United States)

Ehlers, Ina; Betson, Tatiana R.; Vetter, Walter; Schleucher, Jürgen

2014-01-01

The persistent organic pollutant DDT (1,1,1-trichloro-2,2-bis(4-chlorophenyl)ethane) is still indispensable in the fight against malaria, although DDT and related compounds pose toxicological hazards. Technical DDT contains the dichloro congener DDD (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethyl]benzene) as by-product, but DDD is also formed by reductive degradation of DDT in the environment. To differentiate between DDD formation pathways, we applied deuterium NMR spectroscopy to measure intramolecular deuterium distributions (2H isotopomer abundances) of DDT and DDD. DDD formed in the technical DDT synthesis was strongly deuterium-enriched at one intramolecular position, which we traced back to 2H/1H fractionation of a chlorination step in the technical synthesis. In contrast, DDD formed by reductive degradation was strongly depleted at the same position, which was due to the incorporation of 2H-depleted hydride equivalents during reductive degradation. Thus, intramolecular isotope distributions give mechanistic information on reaction pathways, and explain a puzzling difference in the whole-molecule 2H/1H ratio between DDT and DDD. In general, our results highlight that intramolecular isotope distributions are essential to interpret whole-molecule isotope ratios. Intramolecular isotope information allows distinguishing pathways of DDD formation, which is important to identify polluters or to assess DDT turnover in the environment. Because intramolecular isotope data directly reflect isotope fractionation of individual chemical reactions, they are broadly applicable to elucidate transformation pathways of small bioactive molecules in chemistry, physiology and environmental science. PMID:25350380

Microarray analysis of peripheral blood lymphocytes from ALS patients and the SAFE detection of the KEGG ALS pathway

Science.gov (United States)

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

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

Science.gov (United States)

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

Inclusive Elementary Classroom Teacher Knowledge of and Attitudes toward Applied Behavior Analysis and Autism Spectrum Disorder and Their Use of Applied Behavior Analysis

Science.gov (United States)

McCormick, Jennifer A.

2011-01-01

The purpose of this study was to examine inclusive elementary teacher knowledge and attitude toward Autism Spectrum Disorder (ASD) and applied behavior analysis (ABA) and their use of ABA. Furthermore, this study examined if knowledge and attitude predicted use of ABA. A survey was developed and administered through a web-based program. Of the…

Transcriptome analysis of bitter acid biosynthesis and precursor pathways in hop (Humulus lupulus

Directory of Open Access Journals (Sweden)

Clark Shawn M

2013-01-01

Full Text Available Abstract Background Bitter acids (e.g. humulone are prenylated polyketides synthesized in lupulin glands of the hop plant (Humulus lupulus which are important contributors to the bitter flavour and stability of beer. Bitter acids are formed from acyl-CoA precursors derived from branched-chain amino acid (BCAA degradation and C5 prenyl diphosphates from the methyl-D-erythritol 4-phosphate (MEP pathway. We used RNA sequencing (RNA-seq to obtain the transcriptomes of isolated lupulin glands, cones with glands removed and leaves from high α-acid hop cultivars, and analyzed these datasets for genes involved in bitter acid biosynthesis including the supply of major precursors. We also measured the levels of BCAAs, acyl-CoA intermediates, and bitter acids in glands, cones and leaves. Results Transcripts encoding all the enzymes of BCAA metabolism were significantly more abundant in lupulin glands, indicating that BCAA biosynthesis and subsequent degradation occurs in these specialized cells. Branched-chain acyl-CoAs and bitter acids were present at higher levels in glands compared with leaves and cones. RNA-seq analysis showed the gland-specific expression of the MEP pathway, enzymes of sucrose degradation and several transcription factors that may regulate bitter acid biosynthesis in glands. Two branched-chain aminotransferase (BCAT enzymes, HlBCAT1 and HlBCAT2, were abundant, with gene expression quantification by RNA-seq and qRT-PCR indicating that HlBCAT1 was specific to glands while HlBCAT2 was present in glands, cones and leaves. Recombinant HlBCAT1 and HlBCAT2 catalyzed forward (biosynthetic and reverse (catabolic reactions with similar kinetic parameters. HlBCAT1 is targeted to mitochondria where it likely plays a role in BCAA catabolism. HlBCAT2 is a plastidial enzyme likely involved in BCAA biosynthesis. Phylogenetic analysis of the hop BCATs and those from other plants showed that they group into distinct biosynthetic (plastidial and

GEP analysis validates high risk MDS and acute myeloid leukemia post MDS mice models and highlights novel dysregulated pathways

Directory of Open Access Journals (Sweden)

Laura Guerenne

2016-01-01

Full Text Available Abstract Background In spite of the recent discovery of genetic mutations in most myelodysplasic (MDS patients, the pathophysiology of these disorders still remains poorly understood, and only few in vivo models are available to help unravel the disease. Methods We performed global specific gene expression profiling and functional pathway analysis in purified Sca1+ cells of two MDS transgenic mouse models that mimic human high-risk MDS (HR-MDS and acute myeloid leukemia (AML post MDS, with NRASD12 and BCL2 transgenes under the control of different promoters MRP8NRASD12/tethBCL-2 or MRP8[NRASD12/hBCL-2], respectively. Results Analysis of dysregulated genes that were unique to the diseased HR-MDS and AML post MDS mice and not their founder mice pointed first to pathways that had previously been reported in MDS patients, including DNA replication/damage/repair, cell cycle, apoptosis, immune responses, and canonical Wnt pathways, further validating these models at the gene expression level. Interestingly, pathways not previously reported in MDS were discovered. These included dysregulated genes of noncanonical Wnt pathways and energy and lipid metabolisms. These dysregulated genes were not only confirmed in a different independent set of BM and spleen Sca1+ cells from the MDS mice but also in MDS CD34+ BM patient samples. Conclusions These two MDS models may thus provide useful preclinical models to target pathways previously identified in MDS patients and to unravel novel pathways highlighted by this study.

Nonradiological chemical pathway analysis and identification of chemicals of concern for environmental monitoring at the Hanford Site

International Nuclear Information System (INIS)

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 the 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

Automated SEM Modal Analysis Applied to the Diogenites

Science.gov (United States)

Bowman, L. E.; Spilde, M. N.; Papike, James J.

1996-01-01

Analysis of volume proportions of minerals, or modal analysis, is routinely accomplished by point counting on an optical microscope, but the process, particularly on brecciated samples such as the diogenite meteorites, is tedious and prone to error by misidentification of very small fragments, which may make up a significant volume of the sample. Precise volume percentage data can be gathered on a scanning electron microscope (SEM) utilizing digital imaging and an energy dispersive spectrometer (EDS). This form of automated phase analysis reduces error, and at the same time provides more information than could be gathered using simple point counting alone, such as particle morphology statistics and chemical analyses. We have previously studied major, minor, and trace-element chemistry of orthopyroxene from a suite of diogenites. This abstract describes the method applied to determine the modes on this same suite of meteorites and the results of that research. The modal abundances thus determined add additional information on the petrogenesis of the diogenites. In addition, low-abundance phases such as spinels were located for further analysis by this method.

Synergy between methylerythritol phosphate pathway and mevalonate pathway for isoprene production in Escherichia coli.

Science.gov (United States)

Yang, Chen; Gao, Xiang; Jiang, Yu; Sun, Bingbing; Gao, Fang; Yang, Sheng

2016-09-01

Isoprene, a key building block of synthetic rubber, is currently produced entirely from petrochemical sources. In this work, we engineered both the methylerythritol phosphate (MEP) pathway and the mevalonate (MVA) pathway for isoprene production in E. coli. The synergy between the MEP pathway and the MVA pathway was demonstrated by the production experiment, in which overexpression of both pathways improved the isoprene yield about 20-fold and 3-fold, respectively, compared to overexpression of the MEP pathway or the MVA pathway alone. The (13)C metabolic flux analysis revealed that simultaneous utilization of the two pathways resulted in a 4.8-fold increase in the MEP pathway flux and a 1.5-fold increase in the MVA pathway flux. The synergy of the dual pathway was further verified by quantifying intracellular flux responses of the MEP pathway and the MVA pathway to fosmidomycin treatment and mevalonate supplementation. Our results strongly suggest that coupling of the complementary reducing equivalent demand and ATP requirement plays an important role in the synergy of the dual pathway. Fed-batch cultivation of the engineered strain overexpressing the dual pathway resulted in production of 24.0g/L isoprene with a yield of 0.267g/g of glucose. The synergy of the MEP pathway and the MVA pathway also successfully increased the lycopene productivity in E. coli, which demonstrates that it can be used to improve the production of a broad range of terpenoids in microorganisms. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Applied research and development of neutron activation analysis

International Nuclear Information System (INIS)

Chung, Yong Sam; Moon, Jong Hwa; Kim, Sun Ha; Baek, Sung Ryel; Kim, Young Gi; Jung, Hwan Sung; Park, Kwang Won; Kang, Sang Hun; Lim, Jong Myoung

2003-05-01

The aims of this project are to establish the quality control system of Neutron Activation Analysis(NAA) due to increase of industrial needs for standard analytical method and to prepare and identify the standard operation procedure of NAA through practical testing for different analytical items. R and D implementations of analytical quality system using neutron irradiation facility and gamma-ray measurement system and automation of NAA facility in HANARO research reactor are as following ; 1) Establishment of NAA quality control system for the maintenance of best measurement capability and the promotion of utilization of HANARO research reactor 2) Improvement of analytical sensitivity for industrial applied technologies and establishment of certified standard procedures 3) Standardization and development of Prompt Gamma-ray Activation Analysis (PGAA) technology

Functional pathway analysis of genes associated with response to treatment for chronic hepatitis C.

Science.gov (United States)

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. �

From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline.

Science.gov (United States)

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.

Identification and pathway analysis of microRNAs with no previous involvement in breast cancer.

Directory of Open Access Journals (Sweden)

Sandra Romero-Cordoba

Full Text Available 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.

An Analysis of Methods Section of Research Reports in Applied Linguistics

OpenAIRE

Patrícia Marcuzzo

2011-01-01

This work aims at identifying analytical categories and research procedures adopted in the analysis of research article in Applied Linguistics/EAP in order to propose a systematization of the research procedures in Genre Analysis. For that purpose, 12 research reports and interviews with four authors were analyzed. The analysis showed that the studies are concentrated on the investigation of the macrostructure or on the microstructure of research articles in different fields. Studies about th...

Identification of key pathways and genes influencing prognosis in bladder urothelial carcinoma

Directory of Open Access Journals (Sweden)

Ning X

2017-03-01

Full Text Available Xin Ning, Yaoliang Deng Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Province, People’s Republic of China Background: Genomic profiling can be used to identify the predictive effect of genomic subsets for determining prognosis in bladder urothelial carcinoma (BUC after radical cystectomy. This study aimed to investigate potential gene and pathway markers associated with prognosis in BUC.Methods: A microarray dataset of BUC was obtained from The Cancer Genome Atlas database. Differentially expressed genes (DEGs were identified by DESeq of the R platform. Kaplan–Meier analysis was applied for prognostic markers. Key pathways and genes were identified using bioinformatics tools, such as gene set enrichment analysis, gene ontology, the Kyoto Encyclopedia of Genes and Genomes, gene multiple association network integration algorithm (GeneMANIA, Search Tool for the Retrieval of Interacting Genes/Proteins, and Molecular Complex Detection.Results: A comparative gene set enrichment analysis of tumor and adjacent normal tissues suggested BUC tumorigenesis resulted mainly from enrichment of cell cycle and DNA damage and repair-related biological processes and pathways, including TP53 and mitotic recombination. Two hundred and fifty-six genes were identified as potential prognosis-related DEGs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that the potential prognosis-related DEGs were enriched in angiogenesis, including the cyclic adenosine monophosphate biosynthetic process, cyclic guanosine monophosphate-protein kinase G, mitogen-activated protein kinase, Rap1, and phosphoinositide-3-kinase-AKT signaling pathway. Nine hub genes, TAGLN, ACTA2, MYH11, CALD1, MYLK, GEM, PRELP, TPM2, and OGN, were identified from the intersection of protein–protein interaction and GeneMANIA networks. Module analysis of protein–protein interaction and GeneMANIA networks mainly showed

Analysis of Brick Masonry Wall using Applied Element Method

Science.gov (United States)

Lincy Christy, D.; Madhavan Pillai, T. M.; Nagarajan, Praveen

2018-03-01

The Applied Element Method (AEM) is a versatile tool for structural analysis. Analysis is done by discretising the structure as in the case of Finite Element Method (FEM). In AEM, elements are connected by a set of normal and shear springs instead of nodes. AEM is extensively used for the analysis of brittle materials. Brick masonry wall can be effectively analyzed in the frame of AEM. The composite nature of masonry wall can be easily modelled using springs. The brick springs and mortar springs are assumed to be connected in series. The brick masonry wall is analyzed and failure load is determined for different loading cases. The results were used to find the best aspect ratio of brick to strengthen brick masonry wall.

Applied Fourier analysis from signal processing to medical imaging

CERN Document Server

Olson, Tim

2017-01-01

The first of its kind, this focused textbook serves as a self-contained resource for teaching from scratch the fundamental mathematics of Fourier analysis and illustrating some of its most current, interesting applications, including medical imaging and radar processing. Developed by the author from extensive classroom teaching experience, it provides a breadth of theory that allows students to appreciate the utility of the subject, but at as accessible a depth as possible. With myriad applications included, this book can be adapted to a one or two semester course in Fourier Analysis or serve as the basis for independent study. Applied Fourier Analysis assumes no prior knowledge of analysis from its readers, and begins by making the transition from linear algebra to functional analysis. It goes on to cover basic Fourier series and Fourier transforms before delving into applications in sampling and interpolation theory, digital communications, radar processing, medical i maging, and heat and wave equations. Fo...

PathNet: A Tool for Pathway Analysis Using Topological Information

Science.gov (United States)

2012-09-24

potentiation (4720) 0.00 [31,32] 4 Neurotrophin signal. . . (4722) 0.01 [31,48] 4 Oocyte meiosis (4114) 0.00 NA 4 Pathways in cancer (5200) 0.71 [35-37...McKeel D, Morris JC, et al: Gene expression profiles in anatomically and functionally distinct regions of the normal aged human brain. Physiol...Background: Identification of canonical pathways through enrichment of differentially expressed genes in a given pathway is a widely used method for

Two Pathways to Stimulus Encoding in Category Learning?

Science.gov (United States)

Davis, Tyler; Love, Bradley C.; Maddox, W. Todd

2008-01-01

Category learning theorists tacitly assume that stimuli are encoded by a single pathway. Motivated by theories of object recognition, we evaluate a dual-pathway account of stimulus encoding. The part-based pathway establishes mappings between sensory input and symbols that encode discrete stimulus features, whereas the image-based pathway applies holistic templates to sensory input. Our experiments use rule-plus-exception structures in which one exception item in each category violates a salient regularity and must be distinguished from other items. In Experiment 1, we find that discrete representations are crucial for recognition of exceptions following brief training. Experiments 2 and 3 involve multi-session training regimens designed to encourage either part or image-based encoding. We find that both pathways are able to support exception encoding, but have unique characteristics. We speculate that one advantage of the part-based pathway is the ability to generalize across domains, whereas the image-based pathway provides faster and more effortless recognition. PMID:19460948

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

Science.gov (United States)

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

Following User Pathways: Cross Platform and Mixed Methods Analysis in Social Media Studies

DEFF Research Database (Denmark)

Hall, Margeret; Mazarakis, Athanasios; Peters, Isabella

2016-01-01

is the mixed method approach (e.g. qualitative and quantitative methods) in order to better understand how users and society interacts online. The workshop 'Following User Pathways' brings together a community of researchers and professionals to address methodological, analytical, conceptual, and technological......Social media and the resulting tidal wave of available data have changed the ways and methods researchers analyze communities at scale. But the full potential for social scientists (and others) is not yet achieved. Despite the popularity of social media analysis in the past decade, few researchers...... challenges and opportunities of cross-platform, mixed method analysis in social media ecosystems....

Pathway-related modules involved in the application of sevoflurane or propofol in off-pump coronary artery bypass graft surgery.

Science.gov (United States)

Bu, Xiangmei; Wang, Bo; Wang, Yaoqi; Wang, Zhigang; Gong, Chunzhi; Qi, Feng; Zhang, Caixia

2017-07-01

Off-pump coronary artery bypass graft (CABG) surgery has recently emerged as a means to avoid the sequelae of extracorporeal circulation, including the whole-body inflammatory response, coagulation disorders and multiple organ dysfunction. At present, gas anesthesia, sevoflurane and intravenous anesthesia and propofol have been widely used during the CABG. To further understand the underlying mechanisms of these anesthetics on the gene level, the present study conducted pathway-related module analysis based on a co-expression network. This was performed in order to identify significant pathways in coronary artery disease patients who had undergone off-pump CABG surgery before and after applying sevoflurane or propofol. A total of 269 and 129 differentially expressed genes were obtained in the sevoflurane and propofol groups, respectively. In total, eight and seven pathways (P<0.05) in the sevoflurane and propofol groups were separately obtained via Kyoto Encyclopedia of Genes and Genome pathway analysis. Finally, eight and seven pathway-related modules in the sevoflurane and propofol groups were obtained, respectively. Furthermore, the mean degree of complement and coagulation cascades pathway-related module in both of the groups was the highest. It was predicted that during the CABG, the anesthetics might activate the complement and coagulation systems in order to possess some cardioprotective properties.

Emergence of differentially regulated pathways associated with the development of regional specificity in chicken skin.

Science.gov (United States)

Chang, Kai-Wei; Huang, Nancy A; Liu, I-Hsuan; Wang, Yi-Hui; Wu, Ping; Tseng, Yen-Tzu; Hughes, Michael W; Jiang, Ting Xin; Tsai, Mong-Hsun; Chen, Chien-Yu; Oyang, Yen-Jen; Lin, En-Chung; Chuong, Cheng-Ming; Lin, Shau-Ping

2015-01-23

Regional specificity allows different skin regions to exhibit different characteristics, enabling complementary functions to make effective use of the integumentary surface. Chickens exhibit a high degree of regional specificity in the skin and can serve as a good model for when and how these regional differences begin to emerge. We used developing feather and scale regions in embryonic chickens as a model to gauge the differences in their molecular pathways. We employed cosine similarity analysis to identify the differentially regulated and co-regulated genes. We applied low cell techniques for expression validation and chromatin immunoprecipitation (ChIP)-based enhancer identification to overcome limited cell availabilities from embryonic chicken skin. We identified a specific set of genes demonstrating a high correlation as being differentially expressed during feather and scale development and maturation. Some members of the WNT, TGF-beta/BMP, and Notch family known to be involved in feathering skin differentiation were found to be differentially regulated. Interestingly, we also found genes along calcium channel pathways that are differentially regulated. From the analysis of differentially regulated pathways, we used calcium signaling pathways as an example for further verification. Some voltage-gated calcium channel subunits, particularly CACNA1D, are expressed spatio-temporally in the skin epithelium. These calcium signaling pathway members may be involved in developmental decisions, morphogenesis, or epithelial maturation. We further characterized enhancers associated with histone modifications, including H3K4me1, H3K27ac, and H3K27me3, near calcium channel-related genes and identified signature intensive hotspots that may be correlated with certain voltage-gated calcium channel genes. We demonstrated the applicability of cosine similarity analysis for identifying novel regulatory pathways that are differentially regulated during development. Our study

Positive Behavior Support and Applied Behavior Analysis: A Familial Alliance

Science.gov (United States)

Dunlap, Glen; Carr, Edward G.; Horner, Robert H.; Zarcone, Jennifer R.; Schwartz, Ilene

2008-01-01

Positive behavior support (PBS) emerged in the mid-1980s as an approach for understanding and addressing problem behaviors. PBS was derived primarily from applied behavior analysis (ABA). Over time, however, PBS research and practice has incorporated evaluative methods, assessment and intervention procedures, and conceptual perspectives associated…

Evolution of the TOR Pathway.

NARCIS (Netherlands)

Dam, T.J.P. van; Zwartkruis, F.J.; Bos, J.L.; Snel, B.

2011-01-01

The TOR kinase is a major regulator of growth in eukaryotes. Many components of the TOR pathway are implicated in cancer and metabolic diseases in humans. Analysis of the evolution of TOR and its pathway may provide fundamental insight into the evolution of growth regulation in eukaryotes and

The Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-Life.

Directory of Open Access Journals (Sweden)

Yu-Hang Zhang

Full Text Available 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.

Supply Chain Sustainability Analysis of Three Biofuel Pathways

Energy Technology Data Exchange (ETDEWEB)

Jacob J. Jacobson; Erin Searcy; Kara Cafferty; Jennifer B. Dunn; Michael Johnson; Zhichao Wang; Michael Wang; Mary Biddy; Abhijit Dutta; Daniel Inman; Eric Tan; Sue Jones; Lesley Snowden-Swan

2013-11-01

The Department of Energy’s (DOE) Bioenergy Technologies Office (BETO) collaborates with industrial, agricultural, and non-profit partners to develop and deploy biofuels and other biologically-derived products. As part of this effort, BETO and its national laboratory teams conduct in-depth techno-economic assessments (TEA) of technologies to produce biofuels as part state of technology (SOT) analyses. An SOT assesses progress within and across relevant technology areas based on actual experimental results relative to technical targets and cost goals from design cases and includes technical, economic, and environmental criteria as available. Overall assessments of biofuel pathways begin with feedstock production and the logistics of transporting the feedstock from the farm or plantation to the conversion facility or biorefinery. The conversion process itself is modeled in detail as part of the SOT analysis. The teams then develop an estimate of the biofuel minimum selling price (MSP) and assess the cost competitiveness of the biofuel with conventional fuels such as gasoline.

Targetome Analysis Revealed Involvement of MiR-126 in Neurotrophin Signaling Pathway: A Possible Role in Prevention of Glioma Development.

Science.gov (United States)

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.

Source identification of nitrous oxide emission pathways from a single-stage nitritation-anammox granular reactor

KAUST Repository

Ali, Muhammad; Rathnayake, Rathnayake M.L.D.; Zhang, Lei; Ishii, Satoshi; Kindaichi, Tomonori; Satoh, Hisashi; Toyoda, Sakae; Yoshida, Naohiro; Okabe, Satoshi

2016-01-01

Nitrous oxide (N2O) production pathway in a signal-stage nitritation-anammox sequencing batch reactor (SBR) was investigated based on a multilateral approach including real-time N2O monitoring, N2O isotopic composition analysis, and in-situ analyses of spatial distribution of N2O production rate and microbial populations in granular biomass. N2O emission rate was high in the initial phase of the operation cycle and gradually decreased with decreasing NH4+ concentration. The average emission of N2O was 0.98 ± 0.42% and 1.35 ± 0.72% of the incoming nitrogen load and removed nitrogen, respectively. The N2O isotopic composition analysis revealed that N2O was produced via NH2OH oxidation and NO2− reduction pathways equally, although there is an unknown influence from N2O reduction and/or anammox N2O production. However, the N2O isotopomer analysis could not discriminate the relative contribution of nitrifier denitrification and heterotrophic denitrification in the NO2− reduction pathway. Various in-situ techniques (e.g. microsensor measurements and FISH (fluorescent in-situ hybridization) analysis) were therefore applied to further identify N2O producers. Microsensor measurements revealed that approximately 70% of N2O was produced in the oxic surface zone, where nitrifiers were predominantly localized. Thus, NH2OH oxidation and NO2 reduction by nitrifiers (nitrifier-denitrification) could be responsible for the N2O production in the oxic zone. The rest of N2O (ca. 30%) was produced in the anammox bacteria-dominated anoxic zone, probably suggesting that NO2− reduction by coexisting putative heterotrophic denitrifiers and some other unknown pathway(s) including the possibility of anammox process account for the anaerobic N2O production. Further study is required to identify the anaerobic N2O production pathways. Our multilateral approach can be useful to quantitatively examine the relative contributions of N2O production pathways. Good understanding of the key N2O

Source identification of nitrous oxide emission pathways from a single-stage nitritation-anammox granular reactor

KAUST Repository

Ali, Muhammad

2016-06-16

Nitrous oxide (N2O) production pathway in a signal-stage nitritation-anammox sequencing batch reactor (SBR) was investigated based on a multilateral approach including real-time N2O monitoring, N2O isotopic composition analysis, and in-situ analyses of spatial distribution of N2O production rate and microbial populations in granular biomass. N2O emission rate was high in the initial phase of the operation cycle and gradually decreased with decreasing NH4+ concentration. The average emission of N2O was 0.98 ± 0.42% and 1.35 ± 0.72% of the incoming nitrogen load and removed nitrogen, respectively. The N2O isotopic composition analysis revealed that N2O was produced via NH2OH oxidation and NO2− reduction pathways equally, although there is an unknown influence from N2O reduction and/or anammox N2O production. However, the N2O isotopomer analysis could not discriminate the relative contribution of nitrifier denitrification and heterotrophic denitrification in the NO2− reduction pathway. Various in-situ techniques (e.g. microsensor measurements and FISH (fluorescent in-situ hybridization) analysis) were therefore applied to further identify N2O producers. Microsensor measurements revealed that approximately 70% of N2O was produced in the oxic surface zone, where nitrifiers were predominantly localized. Thus, NH2OH oxidation and NO2 reduction by nitrifiers (nitrifier-denitrification) could be responsible for the N2O production in the oxic zone. The rest of N2O (ca. 30%) was produced in the anammox bacteria-dominated anoxic zone, probably suggesting that NO2− reduction by coexisting putative heterotrophic denitrifiers and some other unknown pathway(s) including the possibility of anammox process account for the anaerobic N2O production. Further study is required to identify the anaerobic N2O production pathways. Our multilateral approach can be useful to quantitatively examine the relative contributions of N2O production pathways. Good understanding of the key N2O

Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

Science.gov (United States)

Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

2016-06-01

Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Understanding pathways of exposure using site-specific habits surveys, particularly new pathways and methodologies

International Nuclear Information System (INIS)

Grzechnik, M.; McTaggart, K.; Clyne, F.

2006-01-01

public to establish the extent of exposure to various pathways. Some interviewees are known in advance (from previous investigations) and specifically targeted at their residence, whereas others are interviewed whilst undertaking a specific activity of a known pathway. For example, walkers over sediment may be queried to determine their yearly exposure times. Uncommon pathways may be discovered with skilled interview techniques either from the individual that they apply to or by hearing reports of activities taking place (e.g. poaching). Some examples of uncommon aquatic pathways include consumption of razor shell or sea mice, and the use of seaweed as a soil conditioner. Surveys into terrestrial pathways have led to the inclusion of additional food groups in assessments, including goat meat, freshwater plants and algae, freshwater crustaceans and terrestrial molluscs. Once obtained, survey data are input into a purpose-built database and analysed. Critical rates are derived and may be subsequently applied in dose assessments for regulation purposes. (authors)

Tissue Microarray Analysis Applied to Bone Diagenesis.

Science.gov (United States)

Mello, Rafael Barrios; Silva, Maria Regina Regis; Alves, Maria Teresa Seixas; Evison, Martin Paul; Guimarães, Marco Aurelio; Francisco, Rafaella Arrabaca; Astolphi, Rafael Dias; Iwamura, Edna Sadayo Miazato

2017-01-04

Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens. Standard hematoxylin and eosin, periodic acid-Schiff and silver methenamine, and picrosirius red staining, and CD31 and CD34 immunohistochemistry were applied to TMA sections. Osteocyte and osteocyte lacuna counts, percent bone matrix loss, and fungal spheroid element counts could be measured and collagen fibre bundles observed in all specimens. Decalcification with 7% nitric acid proceeded more rapidly than with 0.5 M EDTA and may offer better preservation of histological and cellular structure. No endothelial cells could be detected using CD31 and CD34 immunohistochemistry. Correlation between osteocytes per lacuna and age at death may reflect reported age-related responses to microdamage. Methodological limitations and caveats, and results of the TMA analysis of post mortem diagenesis in bone are discussed, and implications for DNA survival and recovery considered.

Genome-Wide Gene Set Analysis for Identification of Pathways Associated with Alcohol Dependence

Science.gov (United States)

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

Apply Functional Modelling to Consequence Analysis in Supervision Systems

DEFF Research Database (Denmark)

Zhang, Xinxin; Lind, Morten; Gola, Giulio

2013-01-01

This paper will first present the purpose and goals of applying functional modelling approach to consequence analysis by adopting Multilevel Flow Modelling (MFM). MFM Models describe a complex system in multiple abstraction levels in both means-end dimension and whole-part dimension. It contains...... consequence analysis to practical or online applications in supervision systems. It will also suggest a multiagent solution as the integration architecture for developing tools to facilitate the utilization results of functional consequence analysis. Finally a prototype of the multiagent reasoning system...... causal relations between functions and goals. A rule base system can be developed to trace the causal relations and perform consequence propagations. This paper will illustrate how to use MFM for consequence reasoning by using rule base technology and describe the challenges for integrating functional...

Pathways-driven sparse regression identifies pathways and genes associated with high-density lipoprotein cholesterol in two Asian cohorts.

Directory of Open Access Journals (Sweden)

Matt Silver

2013-11-01

Full Text Available 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

Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

Science.gov (United States)

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

Allowable residual contamination levels of radionuclides in soil from pathway analysis

International Nuclear Information System (INIS)

Nyquist, J.E.; Baes, C.F. III

1987-01-01

The Remedial Action Program (RAP) at Oak Ridge National Laboratory will include well drilling, facility upgrades, and other waste management operations likely to involve soils contaminated with radionuclides. A preliminary protocol and generalized criteria for handling contaminated soils is needed to coordinate and plan RAP activities, but there exists only limited information on contaminate nature and distribution at ORNL RAP sites. Furthermore, projections of long-term decommissioning and closure options for these sites are preliminary. They have adapted a pathway analysis model, DECOM, to quantify risks to human health from radionuclides in soil and used it to outline preliminary criteria for determining the fate of contaminated soil produced during RAP activities. They assumed that the site could be available for unrestricted use immediately upon decontamination. The pathways considered are consumption of food grown on the contaminated soil, including direct ingestion of soil from poorly washed vegetables, direct radiation from the ground surface, inhalation of resuspended radioactive soil, and drinking water from a well drilled through or near the contaminated soil. We will discuss the assumptions and simplifications implicit in DECOM, the site-specific data required, and the results of initial calculations for the Oak Ridge Reservation

In silico tools for the analysis of antibiotic biosynthetic pathways

DEFF Research Database (Denmark)

Weber, Tilmann

2014-01-01

Natural products of bacteria and fungi are the most important source for antimicrobial drug leads. For decades, such compounds were exclusively found by chemical/bioactivity-guided screening approaches. The rapid progress in sequencing technologies only recently allowed the development of novel...... screening methods based on the genome sequences of potential producing organisms. The basic principle of such genome mining approaches is to identify genes, which are involved in the biosynthesis of such molecules, and to predict the products of the identified pathways. Thus, bioinformatics methods...... and tools are crucial for genome mining. In this review, a comprehensive overview is given on programs and databases for the identification and analysis of antibiotic biosynthesis gene clusters in genomic data....

Comparative study on gene set and pathway topology-based enrichment methods.

Science.gov (United States)

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

Exploratory Factor Analysis as a Construct Validation Tool: (Mis)applications in Applied Linguistics Research

Science.gov (United States)

Karami, Hossein

2015-01-01

Factor analysis has been frequently exploited in applied research to provide evidence about the underlying factors in various measurement instruments. A close inspection of a large number of studies published in leading applied linguistic journals shows that there is a misconception among applied linguists as to the relative merits of exploratory…

Thermodynamic analysis of computed pathways integrated into the metabolic networks of E. coli and Synechocystis reveals contrasting expansion potential.

Science.gov (United States)

Asplund-Samuelsson, Johannes; Janasch, Markus; Hudson, Elton P

2018-01-01

Introducing biosynthetic pathways into an organism is both reliant on and challenged by endogenous biochemistry. Here we compared the expansion potential of the metabolic network in the photoautotroph Synechocystis with that of the heterotroph E. coli using the novel workflow POPPY (Prospecting Optimal Pathways with PYthon). First, E. coli and Synechocystis metabolomic and fluxomic data were combined with metabolic models to identify thermodynamic constraints on metabolite concentrations (NET analysis). Then, thousands of automatically constructed pathways were placed within each network and subjected to a network-embedded variant of the max-min driving force analysis (NEM). We found that the networks had different capabilities for imparting thermodynamic driving forces toward certain compounds. Key metabolites were constrained differently in Synechocystis due to opposing flux directions in glycolysis and carbon fixation, the forked tri-carboxylic acid cycle, and photorespiration. Furthermore, the lysine biosynthesis pathway in Synechocystis was identified as thermodynamically constrained, impacting both endogenous and heterologous reactions through low 2-oxoglutarate levels. Our study also identified important yet poorly covered areas in existing metabolomics data and provides a reference for future thermodynamics-based engineering in Synechocystis and beyond. The POPPY methodology represents a step in making optimal pathway-host matches, which is likely to become important as the practical range of host organisms is diversified. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Bioinformatic evaluation of L-arginine catabolic pathways in 24 cyanobacteria and transcriptional analysis of genes encoding enzymes of L-arginine catabolism in the cyanobacterium Synechocystis sp. PCC 6803

Directory of Open Access Journals (Sweden)

Pistorius Elfriede K

2007-11-01

Full Text Available Abstract Background So far very limited knowledge exists on L-arginine catabolism in cyanobacteria, although six major L-arginine-degrading pathways have been described for prokaryotes. Thus, we have performed a bioinformatic analysis of possible L-arginine-degrading pathways in cyanobacteria. Further, we chose Synechocystis sp. PCC 6803 for a more detailed bioinformatic analysis and for validation of the bioinformatic predictions on L-arginine catabolism with a transcript analysis. Results We have evaluated 24 cyanobacterial genomes of freshwater or marine strains for the presence of putative L-arginine-degrading enzymes. We identified an L-arginine decarboxylase pathway in all 24 strains. In addition, cyanobacteria have one or two further pathways representing either an arginase pathway or L-arginine deiminase pathway or an L-arginine oxidase/dehydrogenase pathway. An L-arginine amidinotransferase pathway as a major L-arginine-degrading pathway is not likely but can not be entirely excluded. A rather unusual finding was that the cyanobacterial L-arginine deiminases are substantially larger than the enzymes in non-photosynthetic bacteria and that they are membrane-bound. A more detailed bioinformatic analysis of Synechocystis sp. PCC 6803 revealed that three different L-arginine-degrading pathways may in principle be functional in this cyanobacterium. These are (i an L-arginine decarboxylase pathway, (ii an L-arginine deiminase pathway, and (iii an L-arginine oxidase/dehydrogenase pathway. A transcript analysis of cells grown either with nitrate or L-arginine as sole N-source and with an illumination of 50 μmol photons m-2 s-1 showed that the transcripts for the first enzyme(s of all three pathways were present, but that the transcript levels for the L-arginine deiminase and the L-arginine oxidase/dehydrogenase were substantially higher than that of the three isoenzymes of L-arginine decarboxylase. Conclusion The evaluation of 24

Pathway analysis for intracellular Porphyromonas gingivalis using a strain ATCC 33277 specific database

Directory of Open Access Journals (Sweden)

Wang Tiansong

2009-09-01

Full Text Available Abstract Background Porphyromonas gingivalis is a Gram-negative intracellular pathogen associated with periodontal disease. We have previously reported on whole-cell quantitative proteomic analyses to investigate the differential expression of virulence factors as the organism transitions from an extracellular to intracellular lifestyle. The original results with the invasive strain P. gingivalis ATCC 33277 were obtained using the genome sequence available at the time, strain W83 [GenBank: AE015924]. We present here a re-processed dataset using the recently published genome annotation specific for strain ATCC 33277 [GenBank: AP009380] and an analysis of differential abundance based on metabolic pathways rather than individual proteins. Results Qualitative detection was observed for 1266 proteins using the strain ATCC 33277 annotation for 18 hour internalized P. gingivalis within human gingival epithelial cells and controls exposed to gingival cell culture medium, an improvement of 7% over the W83 annotation. Internalized cells showed increased abundance of proteins in the energy pathway from asparagine/aspartate amino acids to ATP. The pathway producing one short chain fatty acid, propionate, showed increased abundance, while that of another, butyrate, trended towards decreased abundance. The translational machinery, including ribosomal proteins and tRNA synthetases, showed a significant increase in protein relative abundance, as did proteins responsible for transcription. Conclusion Use of the ATCC 33277 specific genome annotation resulted in improved proteome coverage with respect to the number of proteins observed both qualitatively in terms of protein identifications and quantitatively in terms of the number of calculated abundance ratios. Pathway analysis showed a significant increase in overall protein synthetic and transcriptional machinery in the absence of significant growth. These results suggest that the interior of host cells

KEGGParser: parsing and editing KEGG pathway maps in Matlab.

Science.gov (United States)

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.

Identification of key nitrous oxide production pathways in aerobic partial nitrifying granules.

Science.gov (United States)

Ishii, Satoshi; Song, Yanjun; Rathnayake, Lashitha; Tumendelger, Azzaya; Satoh, Hisashi; Toyoda, Sakae; Yoshida, Naohiro; Okabe, Satoshi

2014-10-01

The identification of the key nitrous oxide (N2O) production pathways is important to establish a strategy to mitigate N2O emission. In this study, we combined real-time gas-monitoring analysis, (15)N stable isotope analysis, denitrification functional gene transcriptome analysis and microscale N2O concentration measurements to identify the main N2O producers in a partial nitrification (PN) aerobic granule reactor, which was fed with ammonium and acetate. Our results suggest that heterotrophic denitrification was the main contributor to N2O production in our PN aerobic granule reactor. The heterotrophic denitrifiers were probably related to Rhodocyclales bacteria, although different types of bacteria were active in the initial and latter stages of the PN reaction cycles, most likely in response to the presence of acetate. Hydroxylamine oxidation and nitrifier denitrification occurred, but their contribution to N2O emission was relatively small (20-30%) compared with heterotrophic denitrification. Our approach can be useful to quantitatively examine the relative contributions of the three pathways (hydroxylamine oxidation, nitrifier denitrification and heterotrophic denitrification) to N2O emission in mixed microbial populations. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Multi-criteria decision analysis of energy system transformation pathways: A case study for Switzerland

International Nuclear Information System (INIS)

Volkart, Kathrin; Weidmann, Nicolas; Bauer, Christian; Hirschberg, Stefan

2017-01-01

Two recent political decisions are expected to frame the development of the Swiss energy system in the coming decades: the nuclear phase-out and the greenhouse gas (GHG) emission reduction target. To accomplish both of them, low-carbon technologies based on renewable energy and Carbon Capture and Storage (CCS) are expected to gain importance. The objective of the present work is to support prospective Swiss energy policy-making by providing a detailed sustainability analysis of possible energy system transformation pathways. For this purpose, the results of the scenario quantification with an energy system model are coupled with multi-criteria sustainability analysis. Two climate protection and one reference scenario are addressed, and the trade-offs between the scenarios are analysed based on a set of 12 interdisciplinary indicators. Implementing a stringent climate policy in Switzerland is associated with co-benefits such as less fossil resource use, less fatalities in severe accidents in the energy sector, less societal conflicts and higher resource autonomy. The availability and implementation of CCS allows for achieving the GHG emission reduction target at lower costs, but at the expense of a more fossil fuel-based energy system. - Highlights: • Three energy system transformation pathways for Switzerland are analysed. • A set of policy-relevant sustainability indicators are quantified for each pathway. • Implementing a stringent climate policy in Switzerland is associated with co-benefits. • In the CCS scenario fossil fuel use increases, but the total system costs are lower. • Fossil-fuelled transport substantially contributes to most of the addressed criteria.

Applied linear algebra and matrix analysis

CERN Document Server

Shores, Thomas S

2018-01-01

In its second edition, this textbook offers a fresh approach to matrix and linear algebra. Its blend of theory, computational exercises, and analytical writing projects is designed to highlight the interplay between these aspects of an application. This approach places special emphasis on linear algebra as an experimental science that provides tools for solving concrete problems. The second edition’s revised text discusses applications of linear algebra like graph theory and network modeling methods used in Google’s PageRank algorithm. Other new materials include modeling examples of diffusive processes, linear programming, image processing, digital signal processing, and Fourier analysis. These topics are woven into the core material of Gaussian elimination and other matrix operations; eigenvalues, eigenvectors, and discrete dynamical systems; and the geometrical aspects of vector spaces. Intended for a one-semester undergraduate course without a strict calculus prerequisite, Applied Linear Algebra and M...

Global developmental gene expression and pathway analysis of normal brain development and mouse models of human neuronal migration defects.

Directory of Open Access Journals (Sweden)

Tiziano Pramparo

2011-03-01

Full Text Available Heterozygous LIS1 mutations are the most common cause of human lissencephaly, a human neuronal migration defect, and DCX mutations are the most common cause of X-linked lissencephaly. LIS1 is part of a protein complex including NDEL1 and 14-3-3ε that regulates dynein motor function and microtubule dynamics, while DCX stabilizes microtubules and cooperates with LIS1 during neuronal migration and neurogenesis. Targeted gene mutations of Lis1, Dcx, Ywhae (coding for 14-3-3ε, and Ndel1 lead to neuronal migration defects in mouse and provide models of human lissencephaly, as well as aid the study of related neuro-developmental diseases. Here we investigated the developing brain of these four mutants and wild-type mice using expression microarrays, bioinformatic analyses, and in vivo/in vitro experiments to address whether mutations in different members of the LIS1 neuronal migration complex lead to similar and/or distinct global gene expression alterations. Consistent with the overall successful development of the mutant brains, unsupervised clustering and co-expression analysis suggested that cell cycle and synaptogenesis genes are similarly expressed and co-regulated in WT and mutant brains in a time-dependent fashion. By contrast, focused co-expression analysis in the Lis1 and Ndel1 mutants uncovered substantial differences in the correlation among pathways. Differential expression analysis revealed that cell cycle, cell adhesion, and cytoskeleton organization pathways are commonly altered in all mutants, while synaptogenesis, cell morphology, and inflammation/immune response are specifically altered in one or more mutants. We found several commonly dysregulated genes located within pathogenic deletion/duplication regions, which represent novel candidates of human mental retardation and neurocognitive disabilities. Our analysis suggests that gene expression and pathway analysis in mouse models of a similar disorder or within a common pathway can

Metabolic pathways for the whole community.

Science.gov (United States)

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.

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma.

Science.gov (United States)

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

Hierarchically organized layout for visualization of biochemical pathways.

Science.gov (United States)

Tsay, Jyh-Jong; Wu, Bo-Liang; Jeng, Yu-Sen

2010-01-01

Many complex pathways are described as hierarchical structures in which a pathway is recursively partitioned into several sub-pathways, and organized hierarchically as a tree. The hierarchical structure provides a natural way to visualize the global structure of a complex pathway. However, none of the previous research on pathway visualization explores the hierarchical structures provided by many complex pathways. In this paper, we aim to develop algorithms that can take advantages of hierarchical structures, and give layouts that explore the global structures as well as local structures of pathways. We present a new hierarchically organized layout algorithm to produce layouts for hierarchically organized pathways. Our algorithm first decomposes a complex pathway into sub-pathway groups along the hierarchical organization, and then partition each sub-pathway group into basic components. It then applies conventional layout algorithms, such as hierarchical layout and force-directed layout, to compute the layout of each basic component. Finally, component layouts are joined to form a final layout of the pathway. Our main contribution is the development of algorithms for decomposing pathways and joining layouts. Experiment shows that our algorithm is able to give comprehensible visualization for pathways with hierarchies, cycles as well as complex structures. It clearly renders the global component structures as well as the local structure in each component. In addition, it runs very fast, and gives better visualization for many examples from previous related research. 2009 Elsevier B.V. All rights reserved.

An Objective Comparison of Applied Behavior Analysis and Organizational Behavior Management Research

Science.gov (United States)

Culig, Kathryn M.; Dickinson, Alyce M.; McGee, Heather M.; Austin, John

2005-01-01

This paper presents an objective review, analysis, and comparison of empirical studies targeting the behavior of adults published in Journal of Applied Behavior Analysis (JABA) and Journal of Organizational Behavior Management (JOBM) between 1997 and 2001. The purpose of the comparisons was to identify similarities and differences with respect to…

Analysis of acyl CoA ester intermediates of the mevalonate pathway in Saccharomyces cerevisiae

DEFF Research Database (Denmark)

Seker, Tamay; Møller, Kasper; Nielsen, Jens

2005-01-01

The mevalonate pathway plays an important role in providing the cell with a number of essential precursors for the synthesis of biomass constituents. With respect to their chemical structure, the metabolites of this pathway can be divided into two groups: acyl esters [acetoacetyl CoA, acetyl Co......A, hydroxymethylglutaryl (HMG) CoA] and phosphorylated metabolites (isopentenyl pyrophosphate, dimethylallyl pyrophosphate, geranyl pyrophosphate, farnesyl pyrophosphate). In this study, we developed a method for the precise analysis of the intracellular concentration of acetoacetyl CoA, acetyl CoA and HMG CoA; and we...... used this method for quantification of these metabolites in Saccharomyces cerevisiae, both during batch growth on glucose and on galactose and in glucose-limited chemostat cultures operated at three different dilution rates. The level of the metabolites changed depending on the growth phase...

Integrated bioinformatic analysis unveils significant genes and pathways in the pathogenesis of supratentorial primitive neuroectodermal tumor

Directory of Open Access Journals (Sweden)

Wang G

2018-04-01

Full Text Available Guang-Yu Wang,1,* Ling Li,2,* Bo Liu,1 Xiao Han,1 Chun-Hua Wang,1 Ji-Wen Wang3 1Department of Neurosurgery, 2Department of Pediatrics, Qilu Children’s Hospital of Shandong University, Jinan, Shandong, 3Department of Neurology, Shanghai Children’s Medical Center, Shanghai Jiaotong University School of Medicine, Pudong New District, Shanghai, People’s Republic of China *These authors contributed equally to this work Purpose: This study aimed to explore significant genes and pathways involved in the pathogenesis of supratentorial primitive neuroectodermal tumor (sPNET. Materials and methods: Gene expression profile of GSE14295 was downloaded from publicly available Gene Expression Omnibus (GEO database. Differentially expressed genes (DEGs were screened out in primary sPNET samples compared with normal fetal and adult brain reference samples (sPNET vs fetal brain and sPNET vs adult brain. Pathway enrichment analysis of these DEGs was conducted, followed by protein–protein interaction (PPI network construction and significant module selection. Additionally, transcription factors (TFs regulating the common DEGs in the two comparison groups were identified, and the regulatory network was constructed. Results: In total, 526 DEGs (99 up- and 427 downregulated in sPNET vs fetal brain and 815 DEGs (200 up- and 615 downregulated in sPNET vs adult brain were identified. DEGs in sPNET vs fetal brain and sPNET vs adult brain were associated with calcium signaling pathway, cell cycle, and p53 signaling pathway. CDK1, CDC20, BUB1B, and BUB1 were hub nodes in the PPI networks of DEGs in sPNET vs fetal brain and sPNET vs adult brain. Significant modules were extracted from the PPI networks. In addition, 64 upregulated and 200 downregulated overlapping DEGs were identified in both sPNET vs fetal brain and sPNET vs adult brain. The genes involved in the regulatory network upon overlapping DEGs and the TFs were correlated with calcium signaling pathway

Integrated analysis of DNA methylation and gene expression reveals specific signaling pathways associated with platinum resistance in ovarian cancer

Directory of Open Access Journals (Sweden)

Chung Jae

2009-06-01

Full Text Available Abstract Background Cisplatin and carboplatin are the primary first-line therapies for the treatment of ovarian cancer. However, resistance to these platinum-based drugs occurs in the large majority of initially responsive tumors, resulting in fully chemoresistant, fatal disease. Although the precise mechanism(s underlying the development of platinum resistance in late-stage ovarian cancer patients currently remains unknown, CpG-island (CGI methylation, a phenomenon strongly associated with aberrant gene silencing and ovarian tumorigenesis, may contribute to this devastating condition. Methods To model the onset of drug resistance, and investigate DNA methylation and gene expression alterations associated with platinum resistance, we treated clonally derived, drug-sensitive A2780 epithelial ovarian cancer cells with increasing concentrations of cisplatin. After several cycles of drug selection, the isogenic drug-sensitive and -resistant pairs were subjected to global CGI methylation and mRNA expression microarray analyses. To identify chemoresistance-associated, biological pathways likely impacted by DNA methylation, promoter CGI methylation and mRNA expression profiles were integrated and subjected to pathway enrichment analysis. Results Promoter CGI methylation revealed a positive association (Spearman correlation of 0.99 between the total number of hypermethylated CGIs and GI50 values (i.e., increased drug resistance following successive cisplatin treatment cycles. In accord with that result, chemoresistance was reversible by DNA methylation inhibitors. Pathway enrichment analysis revealed hypermethylation-mediated repression of cell adhesion and tight junction pathways and hypomethylation-mediated activation of the cell growth-promoting pathways PI3K/Akt, TGF-beta, and cell cycle progression, which may contribute to the onset of chemoresistance in ovarian cancer cells. Conclusion Selective epigenetic disruption of distinct biological

In response to 'Can sugars be produced from fatty acids? A test case for pathway analysis tools'.

Science.gov (United States)

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.

iTRAQ proteomics analysis reveals that PI3K is highly associated with bupivacaine-induced neurotoxicity pathways.

Science.gov (United States)

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.

Variant allele frequency enrichment analysis in vitro reveals sonic hedgehog pathway to impede sustained temozolomide response in GBM.

Science.gov (United States)

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.

PRO-ELICERE: A Hazard Analysis Automation Process Applied to Space Systems

Directory of Open Access Journals (Sweden)

Tharcius Augusto Pivetta

2016-07-01

Full Text Available In the last decades, critical systems have increasingly been developed using computers and software even in space area, where the project approach is usually very conservative. In the projects of rockets, satellites and its facilities, like ground support systems, simulators, among other critical operations for the space mission, it must be applied a hazard analysis. The ELICERE process was created to perform a hazard analysis mainly over computer critical systems, in order to define or evaluate its safety and dependability requirements, strongly based on Hazards and Operability Study and Failure Mode and Effect Analysis techniques. It aims to improve the project design or understand the potential hazards of existing systems improving their functions related to functional or non-functional requirements. Then, the main goal of the ELICERE process is to ensure the safety and dependability goals of a space mission. The process, at the beginning, was created to operate manually in a gradual way. Nowadays, a software tool called PRO-ELICERE was developed, in such a way to facilitate the analysis process and store the results for reuse in another system analysis. To understand how ELICERE works and its tool, a small example of space study case was applied, based on a hypothetical rocket of the Cruzeiro do Sul family, developed by the Instituto de Aeronáutica e Espaço in Brazil.

August Dvorak (1894-1975): Early expressions of applied behavior analysis and precision teaching

Science.gov (United States)

Joyce, Bonnie; Moxley, Roy A.

1988-01-01

August Dvorak is best known for his development of the Dvorak keyboard. However, Dvorak also adapted and applied many behavioral and scientific management techniques to the field of education. Taken collectively, these techniques are representative of many of the procedures currently used in applied behavior analysis, in general, and especially in precision teaching. The failure to consider Dvorak's instructional methods may explain some of the discrepant findings in studies which compare the efficiency of the Dvorak to the standard keyboard. This article presents a brief background on the development of the standard (QWERTY) and Dvorak keyboards, describes parallels between Dvorak's teaching procedures and those used in precision teaching, reviews some of the comparative research on the Dvorak keyboard, and suggests some implications for further research in applying the principles of behavior analysis. PMID:22477993

How Has Applied Behavior Analysis and Behavior Therapy Changed?: An Historical Analysis of Journals

Science.gov (United States)

O'Donohue, William; Fryling, Mitch

2007-01-01

Applied behavior analysis and behavior therapy are now nearly a half century old. It is interesting to ask if and how these disciplines have changed over time, particularly regarding some of their key internal controversies (e.g., role of cognitions). We examined the first five years and the 2000-2004 five year period of the "Journal of Applied…

Well-to-wheels analysis of hydrogen based fuel-cell vehicle pathways in Shanghai

International Nuclear Information System (INIS)

Huang Zhijia; Zhang Xu

2006-01-01

Due to high energy efficiency and zero emissions, some believe fuel cell vehicles (FCVs) could revolutionize the automobile industry by replacing internal combustion engine technology, and first boom in China. However, hydrogen infrastructure is one of the major barriers. Because different H 2 pathways have very different energy and emissions effects, the well-to-wheels (WTW) analyses are necessary for adequately evaluating fuel/vehicle systems. The pathways used to supply H 2 for FCVs must be carefully examined by their WTW energy use, greenhouse gases (GHGs) emissions, total criteria pollutions emissions, and urban criteria pollutions emissions. Ten hydrogen pathways in Shanghai have been simulated. The results include well-to-wheels energy use, GHGs emissions, total criteria pollutions and urban criteria pollutions. A fuel-cycle model developed at Argonne National Laboratory-called the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model-was used to evaluate well-to-wheels energy and emissions impacts of hydrogen pathways in this study. Because the initial GREET model had no coal and naphtha-based hydrogen pathways, four hydrogen pathway computer programs were added to GREET in the research. To analyze uncertain impacts, commercial software, Crystal Ball(TM) was used to conduct Monte Carlo simulations. Hence, instead of point estimates, the results of this study were probability distributions. Through the research of H 2 pathways in Shanghai, the following conclusions were achieved:(1)All the pathways have significant reductions in WTW petroleum use, except two H 2 pathways from naphtha, which achieve about 20% reductions in WTW petroleum. (2)All the pathways have significant reductions in WTW urban criteria pollutions emissions, except two H 2 pathways from coal, which result in significant increases in WTW urban SO X emissions. (3)The NG-based H 2 pathways have the best WTW energy efficiencies, and the electrolysis H 2 pathways

Preliminary Hazard Analysis applied to Uranium Hexafluoride - UF6 production plant

International Nuclear Information System (INIS)

Tomzhinsky, David; Bichmacher, Ricardo; Braganca Junior, Alvaro; Peixoto, Orpet Jose

1996-01-01

The purpose of this paper is to present the results of the Preliminary hazard Analysis applied to the UF 6 Production Process, which is part of the UF 6 Conversion Plant. The Conversion Plant has designed to produce a high purified UF 6 in accordance with the nuclear grade standards. This Preliminary Hazard Analysis is the first step in the Risk Management Studies, which are under current development. The analysis evaluated the impact originated from the production process in the plant operators, members of public, equipment, systems and installations as well as the environment. (author)

Unveiling the excited state energy transfer pathways in peridinin-chlorophyll a-protein by ultrafast multi-pulse transient absorption spectroscopy.

Science.gov (United States)

Redeckas, Kipras; Voiciuk, Vladislava; Zigmantas, Donatas; Hiller, Roger G; Vengris, Mikas

2017-04-01

Time-resolved multi-pulse methods were applied to investigate the excited state dynamics, the interstate couplings, and the excited state energy transfer pathways between the light-harvesting pigments in peridinin-chlorophyll a-protein (PCP). The utilized pump-dump-probe techniques are based on perturbation of the regular PCP energy transfer pathway. The PCP complexes were initially excited with an ultrashort pulse, resonant to the S 0 →S 2 transition of the carotenoid peridinin. A portion of the peridinin-based emissive intramolecular charge transfer (ICT) state was then depopulated by applying an ultrashort NIR pulse that perturbed the interaction between S 1 and ICT states and the energy flow from the carotenoids to the chlorophylls. The presented data indicate that the peridinin S 1 and ICT states are spectrally distinct and coexist in an excited state equilibrium in the PCP complex. Moreover, numeric analysis of the experimental data asserts ICT→Chl-a as the main energy transfer pathway in the photoexcited PCP systems. Copyright © 2017 Elsevier B.V. All rights reserved.

TSLP signaling pathway map: a platform for analysis of TSLP-mediated signaling.

Science.gov (United States)

Zhong, Jun; Sharma, Jyoti; Raju, Rajesh; Palapetta, Shyam Mohan; Prasad, T S Keshava; Huang, Tai-Chung; Yoda, Akinori; Tyner, Jeffrey W; van Bodegom, Diederik; Weinstock, David M; Ziegler, Steven F; Pandey, Akhilesh

2014-01-01

Thymic stromal lymphopoietin (TSLP) is a four-helix bundle cytokine that plays a critical role in the regulation of immune responses and in the differentiation of hematopoietic cells. TSLP signals through a heterodimeric receptor complex consisting of an interleukin-7 receptor α chain and a unique TSLP receptor (TSLPR) [also known as cytokine receptor-like factor 2 (CRLF2)]. Cellular targets of TSLP include dendritic cells, B cells, mast cells, regulatory T (Treg) cells and CD4+ and CD8+ T cells. The TSLP/TSLPR axis can activate multiple signaling transduction pathways including the JAK/STAT pathway and the PI-3 kinase pathway. Aberrant TSLP/TSLPR signaling has been associated with a variety of human diseases including asthma, atopic dermatitis, nasal polyposis, inflammatory bowel disease, eosinophilic eosophagitis and, most recently, acute lymphoblastic leukemia. A centralized resource of the TSLP signaling pathway cataloging signaling events is not yet available. In this study, we present a literature-annotated resource of reactions in the TSLP signaling pathway. This pathway map is publicly available through NetPath (http://www.netpath.org/), an open access signal transduction pathway resource developed previously by our group. This map includes 236 molecules and 252 reactions that are involved in TSLP/TSLPR signaling pathway. We expect that the TSLP signaling pathway map will provide a rich resource to study the biology of this important cytokine as well as to identify novel therapeutic targets for diseases associated with dysregulated TSLP/TSLPR signaling. Database URL: http://www.netpath.org/pathways?path_id=NetPath_24.

Integrative analysis of RUNX1 downstream pathways and target genes

Directory of Open Access Journals (Sweden)

Liu Marjorie

2008-07-01

Full Text Available Abstract 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

Evaluating the effect of clinical care pathways on quality of cancer care: analysis of breast, colon and rectal cancer pathways.

Science.gov (United States)

Bao, Han; Yang, Fengjuan; Su, Shaofei; Wang, Xinyu; Zhang, Meiqi; Xiao, Yaming; Jiang, Hao; Wang, Jiaying; Liu, Meina

2016-05-01

Substantial gaps exist between clinical practice and evidence-based cancer care, potentially leading to adverse clinical outcomes and decreased quality of life for cancer patients. This study aimed to evaluate the usefulness of clinical pathways as a tool for improving quality of cancer care, using breast, colon, and rectal cancer pathways as demonstrations. Newly diagnosed patients with invasive breast, colon, and rectal cancer were enrolled as pre-pathway groups, while patients with the same diagnoses treated according to clinical pathways were recruited for post-pathway groups. Compliance with preoperative core biopsy or fine-needle aspiration, utilization of sentinel lymph node biopsy, and proportion of patients whose tumor hormone receptor status was stated in pathology report were significantly increased after implementation of clinical pathway for breast cancer. For colon cancer, compliance with two care processes was significantly improved: surgical resection with anastomosis and resection of at least 12 lymph nodes. Regarding rectal cancer, there was a significant increase in compliance with preoperative evaluation of depth of tumor invasion, total mesorectal excision treatment of middle- or low-position rectal cancer, and proportion of patients who had undergone rectal cancer surgery whose pathology report included margin status. Moreover, total length of hospital stay was decreased remarkably for all three cancer types, and postoperative complications remained unchanged following implementation of the clinical pathways. Clinical pathways can improve compliance with standard care by implementing evidence-based quality indicators in daily practice, which could serve as a useful tool for narrowing the gap between clinical practice and evidence-based care.

Fatigue Analysis of Tubesheet/Shell Juncture Applying the Mitigation Factor for Over-conservatism

International Nuclear Information System (INIS)

Kang, Deog Ji; Kim, Kyu Hyoung; Lee, Jae Gon

2009-01-01

If the environmental fatigue requirements are applied to the primary components of a nuclear power plant, to which the present ASME Code fatigue curves are applied, some locations with high level CUF (Cumulative Usage Factor) are anticipated not to meet the code criteria. The application of environmental fatigue damage is still particularly controversial for plants with 60-year design lives. Therefore, it is need to develop a detailed fatigue analysis procedure to identify the conservatisms in the procedure and to lower the cumulative usage factor. Several factors are being considered to mitigate the conservatism such as three-dimensional finite element modeling. In the present analysis, actual pressure transient data instead of conservative maximum and minimum pressure data was applied as one of mitigation factors. Unlike in the general method, individual transient events were considered instead of the grouped transient events. The tubesheet/shell juncture in the steam generator assembly is the one of the weak locations and was, therefore, selected as a target to evaluate the mitigation factor in the present analysis

Applied environmetrics. Simulation applied to the physical environment

Energy Technology Data Exchange (ETDEWEB)

Beer, T

1988-02-01

Environmetrics is the application of quantitative methods to all aspects of the social and natural environment. This includes forecasting, mathematical modelling, data analysis, and statistics. Applied Environmetrics as a discipline involves the analysis of environmental data through the use of packaged, or specially designed computer software. Two case studies of recent implementations of applied environmetrics within the Australian mining industry are dealt with. 3 figs., 5 refs.

Pathway-based analysis of genome-wide siRNA screens reveals the regulatory landscape of APP processing.

Directory of Open Access Journals (Sweden)

Luiz Miguel Camargo

Full Text Available 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.

Pathway analysis for a contaminated landfill in Middlesex, New Jersey

International Nuclear Information System (INIS)

Yu, C.; Merry-Libby, P.; Yang, J.Y.

1985-01-01

Under the Formerly Utilized Sites Remedial Action Program, the US Department of Energy began excavating contaminated materials from the Middlesex Municipal landfill in 1984. A total of 16,000 m 3 of landfill materials covering a 0.2-ha area was excavated, of which 11,000 m 3 was contaminated and has been transported to the nearby sampling plant site for interim storage. Based on the pathway analysis for the onsite and near-site resident scenarios, the radiation dose rates and radionuclide concentrations in groundwater would be below the regulatory requirements for both the short-term and long-term scenarios. Hence, the potential health risks to maximally exposed individuals due to radioactive releases from the Middlesex landfill would be insignificant

Degenerative Pathways of Lumbar Motion Segments

DEFF Research Database (Denmark)

Jensen, Rikke K.; Kjaer, Per; Jensen, Tue S.

2016-01-01

pathways of degeneration based on scientific knowledge of disco-vertebral degeneration, and (iii) compare these clusters and degenerative pathways between samples. METHODS: We performed a secondary cross-sectional analysis on two dissimilar MRI samples collected in a hospital department: (1) data from...... pathways of degeneration. RESULTS: Six clusters of MRI findings were identified in each of the two samples. The content of the clusters in the two samples displayed some differences but had the same overall pattern of MRI findings. Although the hypothetical degenerative pathways identified in the two...... samples were not identical, the overall pattern of increasing degeneration within the pathways was the same. CONCLUSIONS: It was expected that different clusters could emerge from different samples, however, when organised into hypothetical pathways of degeneration, the overall pattern of increasing...

Assessing invasion process through pathway and vector analysis: case of saltcedar (Tamarix spp.

Directory of Open Access Journals (Sweden)

Evangelina Natale

2012-12-01

Full Text Available Biological invasions are one of the most pervasive environmental threats to native ecosystems worldwide. The spontaneous spread ofsaltcedar is a particular threat to biodiversity conservation in arid and semiarid environments. In Argentina, three species belonging to this genus have been recognized as invaders. The aim of the present study was to identify main dispersal vectors and pathways to refine risk analysis and increase our ability to predict new areas at risk of Tamarix establishment. We surveyed and categorized 223 populations, 39% as invasive, 26% as established, 21% as contained and 14% as detected in nature. Dispersion of saltcedar was found to be associated with watercourses and human-driven disturbances; in addition roads were found to be relevant for the introduction of propagules in newenvironments. Considering the potential impact of saltcedar invasion and that it is an easily wind-dispersed invasive, it is necessary toimplement strategies to monitor dispersal pathways and take actions to eliminate invasion foci, particularly in vulnerable and highconservation value areas.

Integrated Enrichment Analysis of Variants and Pathways in Genome-Wide Association Studies Indicates Central Role for IL-2 Signaling Genes in Type 1 Diabetes, and Cytokine Signaling Genes in Crohn's Disease

Science.gov (United States)

Carbonetto, Peter; Stephens, Matthew

2013-01-01

Pathway analyses of genome-wide association studies aggregate information over sets of related genes, such as genes in common pathways, to identify gene sets that are enriched for variants associated with disease. We develop a model-based approach to pathway analysis, and apply this approach to data from the Wellcome Trust Case Control Consortium (WTCCC) studies. Our method offers several benefits over existing approaches. First, our method not only interrogates pathways for enrichment of disease associations, but also estimates the level of enrichment, which yields a coherent way to promote variants in enriched pathways, enhancing discovery of genes underlying disease. Second, our approach allows for multiple enriched pathways, a feature that leads to novel findings in two diseases where the major histocompatibility complex (MHC) is a major determinant of disease susceptibility. Third, by modeling disease as the combined effect of multiple markers, our method automatically accounts for linkage disequilibrium among variants. Interrogation of pathways from eight pathway databases yields strong support for enriched pathways, indicating links between Crohn's disease (CD) and cytokine-driven networks that modulate immune responses; between rheumatoid arthritis (RA) and “Measles” pathway genes involved in immune responses triggered by measles infection; and between type 1 diabetes (T1D) and IL2-mediated signaling genes. Prioritizing variants in these enriched pathways yields many additional putative disease associations compared to analyses without enrichment. For CD and RA, 7 of 8 additional non-MHC associations are corroborated by other studies, providing validation for our approach. For T1D, prioritization of IL-2 signaling genes yields strong evidence for 7 additional non-MHC candidate disease loci, as well as suggestive evidence for several more. Of the 7 strongest associations, 4 are validated by other studies, and 3 (near IL-2 signaling genes RAF1, MAPK14

RAMM: a system of computer programs for radionuclide pathway analysis calculations

International Nuclear Information System (INIS)

Lyon, R.B.

1976-09-01

A generalized system of computer programs, designated RAMM (Radioactive Materials Management) system, has been developed to assist in the analysis of the movement of radionuclides through the environment to man. RAMM incorporates the GASP IV continuous/discrete simulation system. A nodal approach is used whereby the system to be analyzed is split up into parts small enough that the distribution of nuclides within the node may be taken to be homogeneous. Pathways are defined between nodes, and appropriate transfer coefficients are input or generated. Output includes the time dependent contents of the nodes and dose rates, integrated doses and dose commitments of selected nodes. (author)

Modelling plant invasion pathways in protected areas under climate change: implication for invasion management

Directory of Open Access Journals (Sweden)

C.-J. Wang

2017-12-01

Full Text Available Global climate change may enable invasive plant species (IPS to invade protected areas (PAs, but plant invasion on a global scale has not yet been explicitly addressed. Here, we mapped the potential invasion pathways for IPS in PAs across the globe and explored potential factors determining the pathways of plant invasion under climate change. We used species distribution modelling to estimate the suitable habitats of 386 IPS and applied a corridor analysis to compute the potential pathways of IPS in PAs under climate change. Subsequently, we analysed the potential factors affecting the pathways in PAs. According to our results, the main potential pathways of IPS in PAs are in Europe, eastern Australia, New Zealand, southern Africa, and eastern regions of South America and are strongly influenced by changes in temperature and precipitation. Protected areas can play an important role in preventing and controlling the spread of IPS under climate change. This is due to the fact that measures are taken to monitor climate change in detail, to provide effective management near or inside PAs, and to control the introduction of IPS with a high capacity for natural dispersal. A review of conservation policies in PAs is urgently needed.

On a Generalized Entropy Measure Leading to the Pathway Model with a Preliminary Application to Solar Neutrino Data

Directory of Open Access Journals (Sweden)

Hans J. Haubold

2013-09-01

Full Text Available An entropy for the scalar variable case, parallel to Havrda-Charvat entropy, was introduced by the first author, and the properties and its connection to Tsallis non-extensive statistical mechanics and the Mathai pathway model were examined by the authors in previous papers. In the current paper, we extend the entropy to cover the scalar case, multivariable case, and matrix variate case. Then, this measure is optimized under different types of restrictions, and a number of models in the multivariable case and matrix variable case are obtained. Connections of these models to problems in statistical and physical sciences are pointed out. An application of the simplest case of the pathway model to the interpretation of solar neutrino data by applying standard deviation analysis and diffusion entropy analysis is provided.

Use of critical pathway models and log-normal frequency distributions for siting nuclear facilities

International Nuclear Information System (INIS)

Waite, D.A.; Denham, D.H.

1975-01-01

The advantages and disadvantages of potential sites for nuclear facilities are evaluated through the use of environmental pathway and log-normal distribution analysis. Environmental considerations of nuclear facility siting are necessarily geared to the identification of media believed to be sifnificant in terms of dose to man or to be potential centres for long-term accumulation of contaminants. To aid in meeting the scope and purpose of this identification, an exposure pathway diagram must be developed. This type of diagram helps to locate pertinent environmental media, points of expected long-term contaminant accumulation, and points of population/contaminant interface for both radioactive and non-radioactive contaminants. Confirmation of facility siting conclusions drawn from pathway considerations must usually be derived from an investigatory environmental surveillance programme. Battelle's experience with environmental surveillance data interpretation using log-normal techniques indicates that this distribution has much to offer in the planning, execution and analysis phases of such a programme. How these basic principles apply to the actual siting of a nuclear facility is demonstrated for a centrifuge-type uranium enrichment facility as an example. A model facility is examined to the extent of available data in terms of potential contaminants and facility general environmental needs. A critical exposure pathway diagram is developed to the point of prescribing the characteristics of an optimum site for such a facility. Possible necessary deviations from climatic constraints are reviewed and reconciled with conclusions drawn from the exposure pathway analysis. Details of log-normal distribution analysis techniques are presented, with examples of environmental surveillance data to illustrate data manipulation techniques and interpretation procedures as they affect the investigatory environmental surveillance programme. Appropriate consideration is given these

GeneAnalytics Pathway Analysis and Genetic Overlap among Autism Spectrum Disorder, Bipolar Disorder and Schizophrenia

Directory of Open Access Journals (Sweden)

Naveen S. Khanzada

2017-02-01

Full Text Available Bipolar disorder (BPD and schizophrenia (SCH show similar neuropsychiatric behavioral disturbances, including impaired social interaction and communication, seen in autism spectrum disorder (ASD with multiple overlapping genetic and environmental influences implicated in risk and course of illness. GeneAnalytics software was used for pathway analysis and genetic profiling to characterize common susceptibility genes obtained from published lists for ASD (792 genes, BPD (290 genes and SCH (560 genes. Rank scores were derived from the number and nature of overlapping genes, gene-disease association, tissue specificity and gene functions subdivided into categories (e.g., diseases, tissues or functional pathways. Twenty-three genes were common to all three disorders and mapped to nine biological Superpathways including Circadian entrainment (10 genes, score = 37.0, Amphetamine addiction (five genes, score = 24.2, and Sudden infant death syndrome (six genes, score = 24.1. Brain tissues included the medulla oblongata (11 genes, score = 2.1, thalamus (10 genes, score = 2.0 and hypothalamus (nine genes, score = 2.0 with six common genes (BDNF, DRD2, CHRNA7, HTR2A, SLC6A3, and TPH2. Overlapping genes impacted dopamine and serotonin homeostasis and signal transduction pathways, impacting mood, behavior and physical activity level. Converging effects on pathways governing circadian rhythms support a core etiological relationship between neuropsychiatric illnesses and sleep disruption with hypoxia and central brain stem dysfunction.

Pathway confirmation and flux analysis of central metabolic pathways in Desulfovibrio vulgaris Hildenborough using gas chromatography-mass spectrometry and fourier transform-ion cyclotron resonance mass spectrometry

International Nuclear Information System (INIS)

Tang, Yinjie; Pingitore, Francesco; Mukhopadhyay, Aindrila; Phan, Richard; Hazen, Terry C.; Keasling, Jay D.

2006-01-01

It has been proposed that during growth under anaerobic or oxygen-limited conditions Shewanella oneidensis MR-1 uses the serine-isocitrate lyase pathway common to many methylotrophic anaerobes, in which formaldehyde produced from pyruvate is condensed with glycine to form serine. The serine is then transformed through hydroxypyruvate and glycerate to enter central metabolism at phosphoglycerate. To examine its use of the serine-isocitrate lyase pathway under anaerobic conditions, we grew S. oneidensis MR-1 on [1-13C] lactate as the sole carbon source with either trimethylamine N-oxide (TMAO) or fumarate as an electron acceptor. Analysis of cellular metabolites indicates that a large percentage (>75 percent) of lactate was partially oxidized to either acetate or pyruvate. The 13C isotope distributions in amino acids and other key metabolites indicate that, under anaerobic conditions, a complete serine pathway is not present, and lactate is oxidized via a highly reversible serine degradation pathway. The labeling data also suggest significant activity in the anaplerotic (malic enzyme and phosphoenolpyruvatecarboxylase) and glyoxylate shunt (isocitrate lyase and malate synthase) reactions. Although the tricarboxylic acid (TCA) cycle is often observed to be incomplete in many other anaerobes (absence of 2-oxoglutaratede hydrogenase activity), isotopic labeling supports the existence of a complete TCA cycle in S. oneidensis MR-1 under TMAO reduction condition

Profiling conserved biological pathways in Autosomal Dominant Polycystic Kidney Disorder (ADPKD) to elucidate key transcriptomic alterations regulating cystogenesis: A cross-species meta-analysis approach.

Science.gov (United States)

Chatterjee, Shatakshee; Verma, Srikant Prasad; Pandey, Priyanka

2017-09-05

Initiation and progression of fluid filled cysts mark Autosomal Dominant Polycystic Kidney Disease (ADPKD). Thus, improved therapeutics targeting cystogenesis remains a constant challenge. Microarray studies in single ADPKD animal models species with limited sample sizes tend to provide scattered views on underlying ADPKD pathogenesis. Thus we aim to perform a cross species meta-analysis to profile conserved biological pathways that might be key targets for therapy. Nine ADPKD microarray datasets on rat, mice and human fulfilled our study criteria and were chosen. Intra-species combined analysis was performed after considering removal of batch effect. Significantly enriched GO biological processes and KEGG pathways were computed and their overlap was observed. For the conserved pathways, biological modules and gene regulatory networks were observed. Additionally, Gene Set Enrichment Analysis (GSEA) using Molecular Signature Database (MSigDB) was performed for genes found in conserved pathways. We obtained 28 modules of significantly enriched GO processes and 5 major functional categories from significantly enriched KEGG pathways conserved in human, mice and rats that in turn suggest a global transcriptomic perturbation affecting cyst - formation, growth and progression. Significantly enriched pathways obtained from up-regulated genes such as Genomic instability, Protein localization in ER and Insulin Resistance were found to regulate cyst formation and growth whereas cyst progression due to increased cell adhesion and inflammation was suggested by perturbations in Angiogenesis, TGF-beta, CAMs, and Infection related pathways. Additionally, networks revealed shared genes among pathways e.g. SMAD2 and SMAD7 in Endocytosis and TGF-beta. Our study suggests cyst formation and progression to be an outcome of interplay between a set of several key deregulated pathways. Thus, further translational research is warranted focusing on developing a combinatorial therapeutic

Extending and Applying Spartan to Perform Temporal Sensitivity Analyses for Predicting Changes in Influential Biological Pathways in Computational Models.

Science.gov (United States)

Alden, Kieran; Timmis, Jon; Andrews, Paul S; Veiga-Fernandes, Henrique; Coles, Mark

2017-01-01

Through integrating real time imaging, computational modelling, and statistical analysis approaches, previous work has suggested that the induction of and response to cell adhesion factors is the key initiating pathway in early lymphoid tissue development, in contrast to the previously accepted view that the process is triggered by chemokine mediated cell recruitment. These model derived hypotheses were developed using spartan, an open-source sensitivity analysis toolkit designed to establish and understand the relationship between a computational model and the biological system that model captures. Here, we extend the functionality available in spartan to permit the production of statistical analyses that contrast the behavior exhibited by a computational model at various simulated time-points, enabling a temporal analysis that could suggest whether the influence of biological mechanisms changes over time. We exemplify this extended functionality by using the computational model of lymphoid tissue development as a time-lapse tool. By generating results at twelve- hour intervals, we show how the extensions to spartan have been used to suggest that lymphoid tissue development could be biphasic, and predict the time-point when a switch in the influence of biological mechanisms might occur.

Applying Authentic Data Analysis in Learning Earth Atmosphere

Science.gov (United States)

Johan, H.; Suhandi, A.; Samsudin, A.; Wulan, A. R.

2017-09-01

The aim of this research was to develop earth science learning material especially earth atmosphere supported by science research with authentic data analysis to enhance reasoning through. Various earth and space science phenomenon require reasoning. This research used experimental research with one group pre test-post test design. 23 pre-service physics teacher participated in this research. Essay test was conducted to get data about reason ability. Essay test was analyzed quantitatively. Observation sheet was used to capture phenomena during learning process. The results showed that student’s reasoning ability improved from unidentified and no reasoning to evidence based reasoning and inductive/deductive rule-based reasoning. Authentic data was considered using Grid Analysis Display System (GrADS). Visualization from GrADS facilitated students to correlate the concepts and bring out real condition of nature in classroom activity. It also helped student to reason the phenomena related to earth and space science concept. It can be concluded that applying authentic data analysis in learning process can help to enhance students reasoning. This study is expected to help lecture to bring out result of geoscience research in learning process and facilitate student understand concepts.

Applying DEA sensitivity analysis to efficiency measurement of Vietnamese universities

Directory of Open Access Journals (Sweden)

Thi Thanh Huyen Nguyen

2015-11-01

Full Text Available The primary purpose of this study is to measure the technical efficiency of 30 doctorate-granting universities, the universities or the higher education institutes with PhD training programs, in Vietnam, applying the sensitivity analysis of data envelopment analysis (DEA. The study uses eight sets of input-output specifications using the replacement as well as aggregation/disaggregation of variables. The measurement results allow us to examine the sensitivity of the efficiency of these universities with the sets of variables. The findings also show the impact of variables on their efficiency and its “sustainability”.

The x-rays fluorescence applied to the analysis of alloys

International Nuclear Information System (INIS)

Gutierrez, D.A.

1997-01-01

This work is based on the utilization of the Fluorescence of X Rays. This technique of non destructive trial, has the purpose to establish a routine method, for the control of the conformation of industrial samples used. It makes an analysis with a combination of the algorithms of Rasberry-Heinrich and Claisse-Thinh. Besides, the numerical implementation of non usual techniques in this type of analysis. Such as the Linear Programming applied to the solution of super determined systems, of equations and the utilization of methods of relaxation to facilitate the convergence to the solutions. (author) [es

Global Expression Profiling and Pathway Analysis of Mouse Mammary Tumor Reveals Strain and Stage Specific Dysregulated Pathways in Breast Cancer Progression.

Science.gov (United States)

Mei, Yan; Yang, Jun-Ping; Lang, Yan-Hong; Peng, Li-Xia; Yang, Ming-Ming; Liu, Qin; Meng, Dong-Fang; Zheng, Li-Sheng; Qiang, Yuan-Yuan; Xu, Liang; Li, Chang-Zhi; Wei, Wen-Wen; Niu, Ting; Peng, Xing-Si; Yang, Qin; Lin, Fen; Hu, Hao; Xu, Hong-Fa; Huang, Bi-Jun; Wang, Li-Jing; Qian, Chao-Nan

2018-05-01

It is believed that the alteration of tissue microenvironment would affect cancer initiation and progression. However, little is known in terms of the underlying molecular mechanisms that would affect the initiation and progression of breast cancer. In the present study, we use two murine mammary tumor models with different speeds of tumor initiation and progression for whole genome expression profiling to reveal the involved genes and signaling pathways. The pathways regulating PI3K-Akt signaling and Ras signaling were activated in Fvb mice and promoted tumor progression. Contrastingly, the pathways regulating apoptosis and cellular senescence were activated in Fvb.B6 mice and suppressed tumor progression. We identified distinct patterns of oncogenic pathways activation at different stages of breast cancer, and uncovered five oncogenic pathways that were activated in both human and mouse breast cancers. The genes and pathways discovered in our study would be useful information for other researchers and drug development.

A Case Study in the Misrepresentation of Applied Behavior Analysis in Autism: The Gernsbacher Lectures

Science.gov (United States)

Morris, Edward K

2009-01-01

I know that most men, including those at ease with problems of the greatest complexity, can seldom accept the simplest and most obvious truth if it be such as would oblige them to admit the falsity of conclusions which they have proudly taught to others, and which they have woven, thread by thread, into the fabrics of their life. (Tolstoy, 1894) This article presents a case study in the misrepresentation of applied behavior analysis for autism based on Morton Ann Gernsbacher's presentation of a lecture titled “The Science of Autism: Beyond the Myths and Misconceptions.” Her misrepresentations involve the characterization of applied behavior analysis, descriptions of practice guidelines, reviews of the treatment literature, presentations of the clinical trials research, and conclusions about those trials (e.g., children's improvements are due to development, not applied behavior analysis). The article also reviews applied behavior analysis' professional endorsements and research support, and addresses issues in professional conduct. It ends by noting the deleterious effects that misrepresenting any research on autism (e.g., biological, developmental, behavioral) have on our understanding and treating it in a transdisciplinary context. PMID:22478522

Prognostic value of hedgehog signaling pathway in digestive system cancers: A systematic review and meta-analysis.

Science.gov (United States)

Wang, Yihan; Peng, Qian; Jia, Hongyuan; Du, Xiao

2016-01-01

The Hedgehog (Hh) signaling pathway has recently been reported to be associated with the prognosis of digestive system cancers. However, the results are inconsistent. This study aimed to investigate the association between Hh pathway components and survival outcomes in patients with digestive system cancers. We conducted a comprehensive retrieval in PubMed, EMBASE and Cochrane library for relevant literatures until May 1st, 2015. The pooled hazard ratios (HRs) for overall survival (OS) and disease-free survival (DFS) with 95% confidence intervals (CIs) were calculated to clarify the prognostic value of Hh pathway components, including Shh, Gli1, Gli2, Smo and Ptch1. A total of 16 eligible articles with 3222 patients were included in the meta-analysis. Pooled HR suggested that over-expression of Shh and Gli1 were both associated with poor OS (HR = 1.87, 95% CI: 1.14-3.07 and HR = 1.96, 95% CI: 1.66-2.32, respectively) and DFS (HR = 2.37, 95% CI: 1.19-4.72 and HR = 2.18, 95% CI: 1.61-2.96, respectively). In addition, over-expression of Smo was associated with poor DFS (HR = 1.38, 95% CI: 1.08-1.75). This study reveals that over-expressed Hh pathway components, including Shh, Gli1 and Smo, are associated with poor prognosis in digestive system cancer patients. Hh signaling pathway may become a potential therapeutic target in digestive system cancers.

Proteomics-based network analysis characterizes biological processes and pathways activated by preconditioned mesenchymal stem cells in cardiac repair mechanisms.

Science.gov (United States)

Di Silvestre, Dario; Brambilla, Francesca; Scardoni, Giovanni; Brunetti, Pietro; Motta, Sara; Matteucci, Marco; Laudanna, Carlo; Recchia, Fabio A; Lionetti, Vincenzo; Mauri, Pierluigi

2017-05-01

We have demonstrated that intramyocardial delivery of human mesenchymal stem cells preconditioned with a hyaluronan mixed ester of butyric and retinoic acid (MSCp + ) is more effective in preventing the decay of regional myocardial contractility in a swine model of myocardial infarction (MI). However, the understanding of the role of MSCp + in proteomic remodeling of cardiac infarcted tissue is not complete. We therefore sought to perform a comprehensive analysis of the proteome of infarct remote (RZ) and border zone (BZ) of pigs treated with MSCp + or unconditioned stem cells. Heart tissues were analyzed by MudPIT and differentially expressed proteins were selected by a label-free approach based on spectral counting. Protein profiles were evaluated by using PPI networks and their topological analysis. The proteomic remodeling was largely prevented in MSCp + group. Extracellular proteins involved in fibrosis were down-regulated, while energetic pathways were globally up-regulated. Cardioprotectant pathways involved in the production of keto acid metabolites were also activated. Additionally, we found that new hub proteins support the cardioprotective phenotype characterizing the left ventricular BZ treated with MSCp + . In fact, the up-regulation of angiogenic proteins NCL and RAC1 can be explained by the increase of capillary density induced by MSCp + . Our results show that angiogenic pathways appear to be uniquely positioned to integrate signaling with energetic pathways involving cardiac repair. Our findings prompt the use of proteomics-based network analysis to optimize new approaches preventing the post-ischemic proteomic remodeling that may underlie the limited self-repair ability of adult heart. Copyright © 2017 Elsevier B.V. All rights reserved.

Acidic preparations of lysed platelets upregulate proliferative pathways in osteoblast-like cells as demonstrated by genome-wide microarray analysis.

Science.gov (United States)

Wahlström, Ola; Linder, Cecilia Halling; Ansell, Anna; Kalén, Anders; Söderström, Mats; Magnusson, Per

2011-01-01

Platelets contain numerous growth factors essential for wound and fracture healing. We investigated the gene expression in human osteoblast-like cells stimulated with lysed platelets prepared in acidic, neutral, or alkaline buffers. Lysed platelets prepared in buffers at pH 5.4, 7.4, and 7.9, were added after neutralization to hFOB 1.19 cells. Genome-wide microarray analysis was performed using the Affymetrix GeneChip 7G Scanner. Biometric, cluster, and pathway analyses were performed with GeneSpring GX. Biometric analyses demonstrated that 53 genes were differentially regulated (p ≤ 0.005, ≥2-fold increase). Pathway analysis revealed 10 significant pathways of which eight are common ones regulating bone formation and cancer growth. Eleven genes were selected for quantitative real-time polymerase chain reaction (PCR) based on the microarray analysis of the lysed platelets prepared in the pH 5.4 experiments. In conclusion, acidic preparations of lysed platelet concentrates release factors essential for cell proliferation and particularly cell metabolism under hypoxic conditions. The genetic response from these factors was dominated by genes associated with the same pathways observed in bone formation and cancer growth. Activation of TGF-β in the acidic preparation could be a stimulatory key factor of cell proliferation. These results support the hypothesis that acidification of platelets modifies the stimulatory response of mesenchymal cells in vitro, which is analogous with the observed milieu of a low pH present in wound and fracture sites, as well as in growing tumors.

Application of benchmark dose modeling to protein expression data in the development and analysis of mode of action/adverse outcome pathways for testicular toxicity.

Science.gov (United States)

Chepelev, Nikolai L; Meek, M E Bette; Yauk, Carole Lyn

2014-11-01

Reliable quantification of gene and protein expression has potential to contribute significantly to the characterization of hypothesized modes of action (MOA) or adverse outcome pathways for critical effects of toxicants. Quantitative analysis of gene expression by benchmark dose (BMD) modeling has been facilitated by the development of effective software tools. In contrast, protein expression is still generally quantified by a less robust effect level (no or lowest [adverse] effect levels) approach, which minimizes its potential utility in the consideration of dose-response and temporal concordance for key events in hypothesized MOAs. BMD modeling is applied here to toxicological data on testicular toxicity to investigate its potential utility in analyzing protein expression relevant to the proposed MOA to inform human health risk assessment. The results illustrate how the BMD analysis of protein expression in animal tissues in response to toxicant exposure: (1) complements other toxicity data, and (2) contributes to consideration of the empirical concordance of dose-response relationships, as part of the weight of evidence for hypothesized MOAs to facilitate consideration and application in regulatory risk assessment. Lack of BMD analysis in proteomics has likely limited its use for these purposes. This paper illustrates the added value of BMD modeling to support and strengthen hypothetical MOAs as a basis to facilitate the translation and uptake of the results of proteomic research into risk assessment. Copyright © 2014 Her Majesty the Queen in Right of Canada. Journal of Applied Toxicology © 2014 John Wiley & Sons, Ltd.

A Cross-Cancer Genetic Association Analysis of the DNA Repair and DNA Damage Signaling Pathways for Lung, Ovary, Prostate, Breast, and Colorectal Cancer.

Science.gov (United States)

Scarbrough, Peter M; Weber, Rachel Palmieri; Iversen, Edwin S; Brhane, Yonathan; Amos, Christopher I; Kraft, Peter; Hung, Rayjean J; Sellers, Thomas A; Witte, John S; Pharoah, Paul; Henderson, Brian E; Gruber, Stephen B; Hunter, David J; Garber, Judy E; Joshi, Amit D; McDonnell, Kevin; Easton, Doug F; Eeles, Ros; Kote-Jarai, Zsofia; Muir, Kenneth; Doherty, Jennifer A; Schildkraut, Joellen M

2016-01-01

DNA damage is an established mediator of carcinogenesis, although genome-wide association studies (GWAS) have identified few significant loci. This cross-cancer site, pooled analysis was performed to increase the power to detect common variants of DNA repair genes associated with cancer susceptibility. We conducted a cross-cancer analysis of 60,297 single nucleotide polymorphisms, at 229 DNA repair gene regions, using data from the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) Network. Our analysis included data from 32 GWAS and 48,734 controls and 51,537 cases across five cancer sites (breast, colon, lung, ovary, and prostate). Because of the unavailability of individual data, data were analyzed at the aggregate level. Meta-analysis was performed using the Association analysis for SubSETs (ASSET) software. To test for genetic associations that might escape individual variant testing due to small effect sizes, pathway analysis of eight DNA repair pathways was performed using hierarchical modeling. We identified three susceptibility DNA repair genes, RAD51B (P cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways. Only three susceptibility loci were identified, which had all been previously reported. In contrast, hierarchical modeling identified several pleiotropic cancer risk associations in key DNA repair pathways. Results suggest that many common variants in DNA repair genes are likely associated with cancer susceptibility through small effect sizes that do not meet stringent significance testing criteria. ©2015 American Association for Cancer Research.

Final Report: Hydrogen Production Pathways Cost Analysis (2013 – 2016)

Energy Technology Data Exchange (ETDEWEB)

James, Brian David [Strategic Analysis Inc., Arlington, VA (United States); DeSantis, Daniel Allan [Strategic Analysis Inc., Arlington, VA (United States); Saur, Genevieve [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2016-09-30

This report summarizes work conducted under a three year Department of Energy (DOE) funded project to Strategic Analysis, Inc. (SA) to analyze multiple hydrogen (H₂) production technologies and project their corresponding levelized production cost of H₂. 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 H₂ production methods was conducted. These TEAs developed projections for capital costs, fuel/feedstock usage, energy usage, indirect capital costs, land usage, labor requirements, and other parameters, for each H₂ 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 H₂ ($/kgH₂). 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 H₂ production, H₂ 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).

Common cause evaluations in applied risk analysis of nuclear power plants

International Nuclear Information System (INIS)

Taniguchi, T.; Ligon, D.; Stamatelatos, M.

1983-04-01

Qualitative and quantitative approaches were developed for the evaluation of common cause failures (CCFs) in nuclear power plants and were applied to the analysis of the auxiliary feedwater systems of several pressurized water reactors (PWRs). Key CCF variables were identified through a survey of experts in the field and a review of failure experience in operating PWRs. These variables were classified into categories of high, medium, and low defense against a CCF. Based on the results, a checklist was developed for analyzing CCFs of systems. Several known techniques for quantifying CCFs were also reviewed. The information provided valuable insights in the development of a new model for estimating CCF probabilities, which is an extension of and improvement over the Beta Factor method. As applied to the analysis of the PWR auxiliary feedwater systems, the method yielded much more realistic values than the original Beta Factor method for a one-out-of-three system

Conversation after Right Hemisphere Brain Damage: Motivations for Applying Conversation Analysis

Science.gov (United States)

Barnes, Scott; Armstrong, Elizabeth

2010-01-01

Despite the well documented pragmatic deficits that can arise subsequent to Right Hemisphere Brain Damage (RHBD), few researchers have directly studied everyday conversations involving people with RHBD. In recent years, researchers have begun applying Conversation Analysis (CA) to the everyday talk of people with aphasia. This research programme…

Novel genes and pathways modulated by syndecan-1: implications for the proliferation and cell-cycle regulation of malignant mesothelioma cells.

Directory of Open Access Journals (Sweden)

Tünde Szatmári

Full Text Available Malignant pleural mesothelioma is a highly malignant tumor, originating from mesothelial cells of the serous cavities. In mesothelioma the expression of syndecan-1 correlates to epithelioid morphology and inhibition of growth and migration. Our previous data suggest a complex role of syndecan-1 in mesothelioma cell proliferation although the exact underlying molecular mechanisms are not completely elucidated. The aim of this study is therefore to disclose critical genes and pathways affected by syndecan-1 in mesothelioma; in order to better understand its importance for tumor cell growth and proliferation. We modulated the expression of syndecan-1 in a human mesothelioma cell line via both overexpression and silencing, and followed the transcriptomic responses with microarray analysis. To project the transcriptome analysis on the full-dimensional picture of cellular regulation, we applied pathway analysis using Ingenuity Pathway Analysis (IPA and a novel method of network enrichment analysis (NEA which elucidated signaling relations between differentially expressed genes and pathways acting via various molecular mechanisms. Syndecan-1 overexpression had profound effects on genes involved in regulation of cell growth, cell cycle progression, adhesion, migration and extracellular matrix organization. In particular, expression of several growth factors, interleukins, and enzymes of importance for heparan sulfate sulfation pattern, extracellular matrix proteins and proteoglycans were significantly altered. Syndecan-1 silencing had less powerful effect on the transcriptome compared to overexpression, which can be explained by the already low initial syndecan-1 level of these cells. Nevertheless, 14 genes showed response to both up- and downregulation of syndecan-1. The "cytokine - cytokine-receptor interaction", the TGF-β, EGF, VEGF and ERK/MAPK pathways were enriched in both experimental settings. Most strikingly, nearly all analyzed pathways

Metabolome analysis-based design and engineering of a metabolic pathway in Corynebacterium glutamicum to match rates of simultaneous utilization of D-glucose and L-arabinose.

Science.gov (United States)

Kawaguchi, Hideo; Yoshihara, Kumiko; Hara, Kiyotaka Y; Hasunuma, Tomohisa; Ogino, Chiaki; Kondo, Akihiko

2018-05-17

L-Arabinose is the second most abundant component of hemicellulose in lignocellulosic biomass, next to D-xylose. However, few microorganisms are capable of utilizing pentoses, and catabolic genes and operons enabling bacterial utilization of pentoses are typically subject to carbon catabolite repression by more-preferred carbon sources, such as D-glucose, leading to a preferential utilization of D-glucose over pentoses. In order to simultaneously utilize both D-glucose and L-arabinose at the same rate, a modified metabolic pathway was rationally designed based on metabolome analysis. Corynebacterium glutamicum ATCC 31831 utilized D-glucose and L-arabinose simultaneously at a low concentration (3.6 g/L each) but preferentially utilized D-glucose over L-arabinose at a high concentration (15 g/L each), although L-arabinose and D-glucose were consumed at comparable rates in the absence of the second carbon source. Metabolome analysis revealed that phosphofructokinase and pyruvate kinase were major bottlenecks for D-glucose and L-arabinose metabolism, respectively. Based on the results of metabolome analysis, a metabolic pathway was engineered by overexpressing pyruvate kinase in combination with deletion of araR, which encodes a repressor of L-arabinose uptake and catabolism. The recombinant strain utilized high concentrations of D-glucose and L-arabinose (15 g/L each) at the same consumption rate. During simultaneous utilization of both carbon sources at high concentrations, intracellular levels of phosphoenolpyruvate declined and acetyl-CoA levels increased significantly as compared with the wild-type strain that preferentially utilized D-glucose. These results suggest that overexpression of pyruvate kinase in the araR deletion strain increased the specific consumption rate of L-arabinose and that citrate synthase activity becomes a new bottleneck in the engineered pathway during the simultaneous utilization of D-glucose and L-arabinose. Metabolome analysis

Techno-economic analysis of biofuel production considering logistic configurations.

Science.gov (United States)

Li, Qi; Hu, Guiping

2016-04-01

In the study, a techno-economic analysis method considering logistic configurations is proposed. The economic feasibility of a low temperature biomass gasification pathway and an integrated pathway with fast pyrolysis and bio-oil gasification are evaluated and compared with the proposed method in Iowa. The results show that both pathways are profitable, biomass gasification pathway could achieve an Internal Rate of Return (IRR) of 10.00% by building a single biorefinery and integrated bio-oil gasification pathway could achieve an IRR of 3.32% by applying decentralized supply chain structure. A Monte-Carlo simulation considering interactions among parameters is also proposed and conducted, which indicates that both pathways are at high risk currently. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modularized TGFbeta-Smad Signaling Pathway

Science.gov (United States)

Li, Yongfeng; Wang, M.; Carra, C.; Cucinotta, F. A.

2011-01-01

The Transforming Growth Factor beta (TGFbeta) signaling pathway is a prominent regulatory signaling pathway controlling various important cellular processes. It can be induced by several factors, including ionizing radiation. It is regulated by Smads in a negative feedback loop through promoting increases in the regulatory Smads in the cell nucleus, and subsequent expression of inhibitory Smad, Smad7 to form a ubiquitin ligase with Smurf targeting active TGF receptors for degradation. In this work, we proposed a mathematical model to study the radiation-induced Smad-regulated TGF signaling pathway. By modularization, we are able to analyze each module (subsystem) and recover the nonlinear dynamics of the entire network system. Meanwhile the excitability, a common feature observed in the biological systems, along the TGF signaling pathway is discussed by mathematical analysis and numerical simulation.

Pathway enrichment and co-expression cluster analysis - FANTOM5 | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us FANTOM...lusters File URL: ftp://ftp.biosciencedbc.jp/archive/fantom5/datafiles/phase1.3/extra/Co-expression_clusters...ite Policy | Contact Us Pathway enrichment and co-expression cluster analysis - FANTOM5 | LSDB Archive ...

Analysis of porcine granulosa cell death signaling pathways induced by vinclozolin.

Science.gov (United States)

Knet, Malgorzata; Wartalski, Kamil; Hoja-Lukowicz, Dorota; Tabarowski, Zbigniew; Slomczynska, Maria; Duda, Malgorzata

2015-10-01

Recent studies suggest that disturbing androgen-signaling pathways in porcine ovarian follicles may cause granulosa cell (GC) death. For this reason, we investigated which apoptotic pathway is initiated after GC exposure to an environmental antiandrogen, vinclozolin (Vnz), in vitro. Immunocytochemistry, Western blots, and fluorometric assays were used to quantify caspase-3 and -9 expression and activity. To elucidate the specific mechanism of Vnz action and toxicity, GCs were assessed for viability, cytotoxicity, and apoptotic activity using the ApoTox-Glo Triplex Assay. To further determine the mechanism of GC death induced by Vnz, we used the Apoptosis Antibody Array Kit. In response to Vnz stimulus, we found an increased level of caspase-3 protein expression (P ≤ 0.001) and an increase in caspase-3 proteolytic activity (P ≤ 0.001), confirming that Vnz is a potent proapoptotic factor. The strong immunoreaction of caspase-9 after Vnz treatment (P ≤ 0.001) suggests that intrinsic mitochondrial apoptosis pathway was activated during GC death. On the other hand, caspase-8, being a part of the extrinsic receptor pathway, was also activated (P ≤ 0.001). Therefore, it is possible that Vnz induces porcine granulosal apoptosis also through a parallel pathway. Activation of these two pathways was confirmed by the Apoptosis Antibody Array Kit. In conclusion, it is possible that the intrinsic signaling pathway may not act as an initial trigger for GC apoptosis but might contribute to the amplification and propagation of apoptotic cell death in the granulosa layer after treatment with this antiandrogen. Moreover, Vnz disturbs the physiological process of programmed cell death. Consequently, this could explain why atretic follicles are rapidly removed and suggests that normal function of the ovarian follicle may be destroyed. Copyright © 2015 Elsevier Inc. All rights reserved.