Functional Analyses of NSF1 in Wine Yeast Using Interconnected Correlation Clustering and Molecular Analyses

PubMed Central

Bessonov, Kyrylo; Walkey, Christopher J.; Shelp, Barry J.; van Vuuren, Hennie J. J.; Chiu, David; van der Merwe, George

2013-01-01

Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of correlation values related to gene expression profiles extracted from given microarray datasets. ICC can be applied to any microarray dataset and any target gene. We applied this method to microarray data generated from wine fermentations and selected NSF1, which encodes a C2H2 zinc finger-type transcription factor, as the target gene. The validity of the method was verified by accurate identifications of the previously known functional roles of NSF1. In addition, we identified and verified potential new functions for this gene; specifically, NSF1 is a negative regulator for the expression of sulfur metabolism genes, the nuclear localization of Nsf1 protein (Nsf1p) is controlled in a sulfur-dependent manner, and the transcription of NSF1 is regulated by Met4p, an important transcriptional activator of sulfur metabolism genes. The inter-disciplinary approach adopted here highlighted the accuracy and relevancy of the ICC method in mining for novel gene functions using complex microarray datasets with a limited number of samples. PMID:24130853

Missing value imputation for microarray data: a comprehensive comparison study and a web tool.

PubMed

Chiu, Chia-Chun; Chan, Shih-Yao; Wang, Chung-Ching; Wu, Wei-Sheng

2013-01-01

Microarray data are usually peppered with missing values due to various reasons. However, most of the downstream analyses for microarray data require complete datasets. Therefore, accurate algorithms for missing value estimation are needed for improving the performance of microarray data analyses. Although many algorithms have been developed, there are many debates on the selection of the optimal algorithm. The studies about the performance comparison of different algorithms are still incomprehensive, especially in the number of benchmark datasets used, the number of algorithms compared, the rounds of simulation conducted, and the performance measures used. In this paper, we performed a comprehensive comparison by using (I) thirteen datasets, (II) nine algorithms, (III) 110 independent runs of simulation, and (IV) three types of measures to evaluate the performance of each imputation algorithm fairly. First, the effects of different types of microarray datasets on the performance of each imputation algorithm were evaluated. Second, we discussed whether the datasets from different species have different impact on the performance of different algorithms. To assess the performance of each algorithm fairly, all evaluations were performed using three types of measures. Our results indicate that the performance of an imputation algorithm mainly depends on the type of a dataset but not on the species where the samples come from. In addition to the statistical measure, two other measures with biological meanings are useful to reflect the impact of missing value imputation on the downstream data analyses. Our study suggests that local-least-squares-based methods are good choices to handle missing values for most of the microarray datasets. In this work, we carried out a comprehensive comparison of the algorithms for microarray missing value imputation. Based on such a comprehensive comparison, researchers could choose the optimal algorithm for their datasets easily. Moreover, new imputation algorithms could be compared with the existing algorithms using this comparison strategy as a standard protocol. In addition, to assist researchers in dealing with missing values easily, we built a web-based and easy-to-use imputation tool, MissVIA (http://cosbi.ee.ncku.edu.tw/MissVIA), which supports many imputation algorithms. Once users upload a real microarray dataset and choose the imputation algorithms, MissVIA will determine the optimal algorithm for the users' data through a series of simulations, and then the imputed results can be downloaded for the downstream data analyses.

Release of Severe Acute Respiratory Syndrome Coronavirus Nuclear Import Block Enhances Host Transcription in Human Lung Cells

PubMed Central

Tilton, Susan C.; Menachery, Vineet D.; Gralinski, Lisa E.; Schäfer, Alexandra; Matzke, Melissa M.; Webb-Robertson, Bobbie-Jo M.; Chang, Jean; Luna, Maria L.; Long, Casey E.; Shukla, Anil K.; Bankhead, Armand R.; Burkett, Susan E.; Zornetzer, Gregory; Tseng, Chien-Te Kent; Metz, Thomas O.; Pickles, Raymond; McWeeney, Shannon; Smith, Richard D.; Katze, Michael G.; Waters, Katrina M.; Baric, Ralph S.

2013-01-01

The severe acute respiratory syndrome coronavirus accessory protein ORF6 antagonizes interferon signaling by blocking karyopherin-mediated nuclear import processes. Viral nuclear import antagonists, expressed by several highly pathogenic RNA viruses, likely mediate pleiotropic effects on host gene expression, presumably interfering with transcription factors, cytokines, hormones, and/or signaling cascades that occur in response to infection. By bioinformatic and systems biology approaches, we evaluated the impact of nuclear import antagonism on host expression networks by using human lung epithelial cells infected with either wild-type virus or a mutant that does not express ORF6 protein. Microarray analysis revealed significant changes in differential gene expression, with approximately twice as many upregulated genes in the mutant virus samples by 48 h postinfection, despite identical viral titers. Our data demonstrated that ORF6 protein expression attenuates the activity of numerous karyopherin-dependent host transcription factors (VDR, CREB1, SMAD4, p53, EpasI, and Oct3/4) that are critical for establishing antiviral responses and regulating key host responses during virus infection. Results were confirmed by proteomic and chromatin immunoprecipitation assay analyses and in parallel microarray studies using infected primary human airway epithelial cell cultures. The data strongly support the hypothesis that viral antagonists of nuclear import actively manipulate host responses in specific hierarchical patterns, contributing to the viral pathogenic potential in vivo. Importantly, these studies and modeling approaches not only provide templates for evaluating virus antagonism of nuclear import processes but also can reveal candidate cellular genes and pathways that may significantly influence disease outcomes following severe acute respiratory syndrome coronavirus infection in vivo. PMID:23365422

Missing value imputation for microarray data: a comprehensive comparison study and a web tool

PubMed Central

2013-01-01

Background Microarray data are usually peppered with missing values due to various reasons. However, most of the downstream analyses for microarray data require complete datasets. Therefore, accurate algorithms for missing value estimation are needed for improving the performance of microarray data analyses. Although many algorithms have been developed, there are many debates on the selection of the optimal algorithm. The studies about the performance comparison of different algorithms are still incomprehensive, especially in the number of benchmark datasets used, the number of algorithms compared, the rounds of simulation conducted, and the performance measures used. Results In this paper, we performed a comprehensive comparison by using (I) thirteen datasets, (II) nine algorithms, (III) 110 independent runs of simulation, and (IV) three types of measures to evaluate the performance of each imputation algorithm fairly. First, the effects of different types of microarray datasets on the performance of each imputation algorithm were evaluated. Second, we discussed whether the datasets from different species have different impact on the performance of different algorithms. To assess the performance of each algorithm fairly, all evaluations were performed using three types of measures. Our results indicate that the performance of an imputation algorithm mainly depends on the type of a dataset but not on the species where the samples come from. In addition to the statistical measure, two other measures with biological meanings are useful to reflect the impact of missing value imputation on the downstream data analyses. Our study suggests that local-least-squares-based methods are good choices to handle missing values for most of the microarray datasets. Conclusions In this work, we carried out a comprehensive comparison of the algorithms for microarray missing value imputation. Based on such a comprehensive comparison, researchers could choose the optimal algorithm for their datasets easily. Moreover, new imputation algorithms could be compared with the existing algorithms using this comparison strategy as a standard protocol. In addition, to assist researchers in dealing with missing values easily, we built a web-based and easy-to-use imputation tool, MissVIA (http://cosbi.ee.ncku.edu.tw/MissVIA), which supports many imputation algorithms. Once users upload a real microarray dataset and choose the imputation algorithms, MissVIA will determine the optimal algorithm for the users' data through a series of simulations, and then the imputed results can be downloaded for the downstream data analyses. PMID:24565220

An analysis of the impact of LHC Run I proton-lead data on nuclear parton densities.

PubMed

Armesto, Néstor; Paukkunen, Hannu; Penín, José Manuel; Salgado, Carlos A; Zurita, Pía

2016-01-01

We report on an analysis of the impact of available experimental data on hard processes in proton-lead collisions during Run I at the large hadron collider on nuclear modifications of parton distribution functions. Our analysis is restricted to the EPS09 and DSSZ global fits. The measurements that we consider comprise production of massive gauge bosons, jets, charged hadrons and pions. This is the first time a study of nuclear PDFs includes this number of different observables. The goal of the paper is twofold: (i) checking the description of the data by nPDFs, as well as the relevance of these nuclear effects, in a quantitative manner; (ii) testing the constraining power of these data in eventual global fits, for which we use the Bayesian reweighting technique. We find an overall good, even too good, description of the data, indicating that more constraining power would require a better control over the systematic uncertainties and/or the proper proton-proton reference from LHC Run II. Some of the observables, however, show sizeable tension with specific choices of proton and nuclear PDFs. We also comment on the corresponding improvements as regards the theoretical treatment.

geneCommittee: a web-based tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification.

PubMed

Reboiro-Jato, Miguel; Arrais, Joel P; Oliveira, José Luis; Fdez-Riverola, Florentino

2014-01-30

The diagnosis and prognosis of several diseases can be shortened through the use of different large-scale genome experiments. In this context, microarrays can generate expression data for a huge set of genes. However, to obtain solid statistical evidence from the resulting data, it is necessary to train and to validate many classification techniques in order to find the best discriminative method. This is a time-consuming process that normally depends on intricate statistical tools. geneCommittee is a web-based interactive tool for routinely evaluating the discriminative classification power of custom hypothesis in the form of biologically relevant gene sets. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. Provided with a straightforward and intuitive interface, geneCommittee is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research. geneCommittee allows the enrichment of microarrays raw data with gene functional annotations, producing integrated datasets that simplify the construction of better discriminative hypothesis, and allows the creation of a set of complementary classifiers. The trained committees can then be used for clinical research and diagnosis. Full documentation including common use cases and guided analysis workflows is freely available at http://sing.ei.uvigo.es/GC/.

Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor β2 immunohistochemistry in prostate cancer.

PubMed

Rizzardi, Anthony E; Zhang, Xiaotun; Vogel, Rachel Isaksson; Kolb, Suzanne; Geybels, Milan S; Leung, Yuet-Kin; Henriksen, Jonathan C; Ho, Shuk-Mei; Kwak, Julianna; Stanford, Janet L; Schmechel, Stephen C

2016-07-11

Digital image analysis offers advantages over traditional pathologist visual scoring of immunohistochemistry, although few studies examining the correlation and reproducibility of these methods have been performed in prostate cancer. We evaluated the correlation between digital image analysis (continuous variable data) and pathologist visual scoring (quasi-continuous variable data), reproducibility of each method, and association of digital image analysis methods with outcomes using prostate cancer tissue microarrays (TMAs) stained for estrogen receptor-β2 (ERβ2). Prostate cancer TMAs were digitized and evaluated by pathologist visual scoring versus digital image analysis for ERβ2 staining within tumor epithelium. Two independent analysis runs were performed to evaluate reproducibility. Image analysis data were evaluated for associations with recurrence-free survival and disease specific survival following radical prostatectomy. We observed weak/moderate Spearman correlation between digital image analysis and pathologist visual scores of tumor nuclei (Analysis Run A: 0.42, Analysis Run B: 0.41), and moderate/strong correlation between digital image analysis and pathologist visual scores of tumor cytoplasm (Analysis Run A: 0.70, Analysis Run B: 0.69). For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99). Further, ERβ2 staining was significantly associated with increased risk of prostate cancer-specific mortality (PCSM) when quantified by cytoplasmic digital image analysis (HR 2.16, 95 % CI 1.02-4.57, p = 0.045), nuclear image analysis (HR 2.67, 95 % CI 1.20-5.96, p = 0.016), and total malignant epithelial area analysis (HR 5.10, 95 % CI 1.70-15.34, p = 0.004). After adjusting for clinicopathologic factors, only total malignant epithelial area ERβ2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012). Digital methods of immunohistochemical quantification are more reproducible than pathologist visual scoring in prostate cancer, suggesting that digital methods are preferable and especially warranted for studies involving large sample sizes.

MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data

PubMed Central

2014-01-01

Background Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. Results We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila. MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. Conclusions MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons. PMID:24621103

Release of (and lessons learned from mining) a pioneering large toxicogenomics database.

PubMed

Sandhu, Komal S; Veeramachaneni, Vamsi; Yao, Xiang; Nie, Alex; Lord, Peter; Amaratunga, Dhammika; McMillian, Michael K; Verheyen, Geert R

2015-07-01

We release the Janssen Toxicogenomics database. This rat liver gene-expression database was generated using Codelink microarrays, and has been used over the past years within Janssen to derive signatures for multiple end points and to classify proprietary compounds. The release consists of gene-expression responses to 124 compounds, selected to give a broad coverage of liver-active compounds. A selection of the compounds were also analyzed on Affymetrix microarrays. The release includes results of an in-house reannotation pipeline to Entrez gene annotations, to classify probes into different confidence classes. High confidence unambiguously annotated probes were used to create gene-level data which served as starting point for cross-platform comparisons. Connectivity map-based similarity methods show excellent agreement between Codelink and Affymetrix runs of the same samples. We also compared our dataset with the Japanese Toxicogenomics Project and observed reasonable agreement, especially for compounds with stronger gene signatures. We describe an R-package containing the gene-level data and show how it can be used for expression-based similarity searches. Comparing the same biological samples run on the Affymetrix and the Codelink platform, good correspondence is observed using connectivity mapping approaches. As expected, this correspondence is smaller when the data are compared with an independent dataset such as TG-GATE. We hope that this collection of gene-expression profiles will be incorporated in toxicogenomics pipelines of users.

Identification and characterization of nuclear genes involved in photosynthesis in Populus

PubMed Central

2014-01-01

Background The gap between the real and potential photosynthetic rate under field conditions suggests that photosynthesis could potentially be improved. Nuclear genes provide possible targets for improving photosynthetic efficiency. Hence, genome-wide identification and characterization of the nuclear genes affecting photosynthetic traits in woody plants would provide key insights on genetic regulation of photosynthesis and identify candidate processes for improvement of photosynthesis. Results Using microarray and bulked segregant analysis strategies, we identified differentially expressed nuclear genes for photosynthesis traits in a segregating population of poplar. We identified 515 differentially expressed genes in this population (FC ≥ 2 or FC ≤ 0.5, P < 0.05), 163 up-regulated and 352 down-regulated. Real-time PCR expression analysis confirmed the microarray data. Singular Enrichment Analysis identified 48 significantly enriched GO terms for molecular functions (28), biological processes (18) and cell components (2). Furthermore, we selected six candidate genes for functional examination by a single-marker association approach, which demonstrated that 20 SNPs in five candidate genes significantly associated with photosynthetic traits, and the phenotypic variance explained by each SNP ranged from 2.3% to 12.6%. This revealed that regulation of photosynthesis by the nuclear genome mainly involves transport, metabolism and response to stimulus functions. Conclusions This study provides new genome-scale strategies for the discovery of potential candidate genes affecting photosynthesis in Populus, and for identification of the functions of genes involved in regulation of photosynthesis. This work also suggests that improving photosynthetic efficiency under field conditions will require the consideration of multiple factors, such as stress responses. PMID:24673936

Ogura-CMS in Chinese cabbage (Brassica rapa ssp. pekinensis) causes delayed expression of many nuclear genes.

PubMed

Dong, Xiangshu; Kim, Wan Kyu; Lim, Yong-Pyo; Kim, Yeon-Ki; Hur, Yoonkang

2013-02-01

We investigated the mechanism regulating cytoplasmic male sterility (CMS) in Brassica rapa ssp. pekinensis using floral bud transcriptome analyses of Ogura-CMS Chinese cabbage and its maintainer line in B. rapa 300-K oligomeric probe (Br300K) microarrays. Ogura-CMS Chinese cabbage produced few and infertile pollen grains on indehiscent anthers. Compared to the maintainer line, CMS plants had shorter filaments and plant growth, and delayed flowering and pollen development. In microarray analysis, 4646 genes showed different expression, depending on floral bud size, between Ogura-CMS and its maintainer line. We found 108 and 62 genes specifically expressed in Ogura-CMS and its maintainer line, respectively. Ogura-CMS line-specific genes included stress-related, redox-related, and B. rapa novel genes. In the maintainer line, genes related to pollen coat and germination were specifically expressed in floral buds longer than 3mm, suggesting insufficient expression of these genes in Ogura-CMS is directly related to dysfunctional pollen. In addition, many nuclear genes associated with auxin response, ATP synthesis, pollen development and stress response had delayed expression in Ogura-CMS plants compared to the maintainer line, which is consistent with the delay in growth and development of Ogura-CMS plants. Delayed expression may reduce pollen grain production and/or cause sterility, implying that mitochondrial, retrograde signaling delays nuclear gene expression. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

First limits on WIMP nuclear recoil signals in ZEPLIN-II: A two-phase xenon detector for dark matter detection

NASA Astrophysics Data System (ADS)

Alner, G. J.; Araújo, H. M.; Bewick, A.; Bungau, C.; Camanzi, B.; Carson, M. J.; Cashmore, R. J.; Chagani, H.; Chepel, V.; Cline, D.; Davidge, D.; Davies, J. C.; Daw, E.; Dawson, J.; Durkin, T.; Edwards, B.; Gamble, T.; Gao, J.; Ghag, C.; Howard, A. S.; Jones, W. G.; Joshi, M.; Korolkova, E. V.; Kudryavtsev, V. A.; Lawson, T.; Lebedenko, V. N.; Lewin, J. D.; Lightfoot, P.; Lindote, A.; Liubarsky, I.; Lopes, M. I.; Lüscher, R.; Majewski, P.; Mavrokoridis, K.; McMillan, J. E.; Morgan, B.; Muna, D.; Murphy, A. St. J.; Neves, F.; Nicklin, G. G.; Ooi, W.; Paling, S. M.; Pinto da Cunha, J.; Plank, S. J. S.; Preece, R. M.; Quenby, J. J.; Robinson, M.; Salinas, G.; Sergiampietri, F.; Silva, C.; Solovov, V. N.; Smith, N. J. T.; Smith, P. F.; Spooner, N. J. C.; Sumner, T. J.; Thorne, C.; Tovey, D. R.; Tziaferi, E.; Walker, R. J.; Wang, H.; White, J. T.; Wolfs, F. L. H.

2007-11-01

Results are presented from the first underground data run of ZEPLIN-II, a 31 kg two-phase xenon detector developed to observe nuclear recoils from hypothetical weakly interacting massive dark matter particles. Discrimination between nuclear recoils and background electron recoils is afforded by recording both the scintillation and ionisation signals generated within the liquid xenon, with the ratio of these signals being different for the two classes of event. This ratio is calibrated for different incident species using an AmBe neutron source and 60Co γ-ray sources. From our first 31 live days of running ZEPLIN-II, the total exposure following the application of fiducial and stability cuts was 225 kg × days. A background population of radon progeny events was observed in this run, arising from radon emission in the gas purification getters, due to radon daughter ion decays on the surfaces of the walls of the chamber. An acceptance window, defined by the neutron calibration data, of 50% nuclear recoil acceptance between 5 keV ee and 20 keV ee, had an observed count of 29 events, with a summed expectation of 28.6 ± 4.3 γ-ray and radon progeny induced background events. These figures provide a 90% c.l. upper limit to the number of nuclear recoils of 10.4 events in this acceptance window, which converts to a WIMP-nucleon spin-independent cross-section with a minimum of 6.6 × 10 -7 pb following the inclusion of an energy-dependent, calibrated, efficiency. A second run is currently underway in which the radon progeny will be eliminated, thereby removing the background population, with a projected sensitivity of 2 × 10 -7 pb for similar exposures as the first run.

Enhanced Component Performance Study: Turbine-Driven Pumps 1998–2014

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

Schroeder, John Alton

2015-11-01

This report presents an enhanced performance evaluation of turbine-driven pumps (TDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from fiscal year 1998 through 2014 for the component reliability as reported in the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The TDP failure modes considered are failure to start (FTS), failure to run less than or equal to one hour (FTR=1H), failure to run more than one hour (FTR>1H), and normally running systems FTS and failure to run (FTR). The component reliability estimates and themore » reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire active period. Statistically significant increasing trends were identified for TDP unavailability, for frequency of start demands for standby TDPs, and for run hours in the first hour after start. Statistically significant decreasing trends were identified for start demands for normally running TDPs, and for run hours per reactor critical year for normally running TDPs.« less

The Journal Microarrays

PubMed Central

Lin, Shu-Kun

2011-01-01

Our publishing company MDPI AG has its headquarters in Basel, Switzerland where there are thousands of scientists working in the laboratories of pharmaceutical companies and institutes including Novartis [1], F. Hoffmann-La Roche [2] and institutes affiliated with University of Basel [3]. In 1996, the first annual microplate conference MipTec was held in Basel, and the MipTec 2011 was held a few days ago in Basel [4]. I published a paper on microplate standardization presented at MipTec 1996 in MDPI’s longest-running journal Molecules [5-7]. [....] PMID:27605331

The Journal Microarrays.

PubMed

Lin, Shu-Kun

2011-10-14

Our publishing company MDPI AG has its headquarters in Basel, Switzerland where there are thousands of scientists working in the laboratories of pharmaceutical companies and institutes including Novartis [1], F. Hoffmann-La Roche [2] and institutes affiliated with University of Basel [3]. In 1996, the first annual microplate conference MipTec was held in Basel, and the MipTec 2011 was held a few days ago in Basel [4]. I published a paper on microplate standardization presented at MipTec 1996 in MDPI's longest-running journal Molecules [5-7]. [....].

Nuclear shell model code CRUNCHER

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

Resler, D.A.; Grimes, S.M.

1988-05-01

A new nuclear shell model code CRUNCHER, patterned after the code VLADIMIR, has been developed. While CRUNCHER and VLADIMIR employ the techniques of an uncoupled basis and the Lanczos process, improvements in the new code allow it to handle much larger problems than the previous code and to perform them more efficiently. Tests involving a moderately sized calculation indicate that CRUNCHER running on a SUN 3/260 workstation requires approximately one-half the central processing unit (CPU) time required by VLADIMIR running on a CRAY-1 supercomputer.

HZEFRG1 - SEMIEMPIRICAL NUCLEAR FRAGMENTATION MODEL

NASA Technical Reports Server (NTRS)

Townsend, L. W.

1994-01-01

The high charge and energy (HZE), Semiempirical Nuclear Fragmentation Model, HZEFRG1, was developed to provide a computationally efficient, user-friendly, physics-based program package for generating nuclear fragmentation databases. These databases can then be used in radiation transport applications such as space radiation shielding and dosimetry, cancer therapy with laboratory heavy ion beams, and simulation studies of detector design in nuclear physics experiments. The program provides individual element and isotope production cross sections for the breakup of high energy heavy ions by the combined nuclear and Coulomb fields of the interacting nuclei. The nuclear breakup contributions are estimated using an energy-dependent abrasion-ablation model of heavy ion fragmentation. The abrasion step involves removal of nucleons by direct knockout in the overlap region of the colliding nuclei. The abrasions are treated on a geometric basis and uniform spherical nuclear density distributions are assumed. Actual experimental nuclear radii obtained from tabulations of electron scattering data are incorporated. Nuclear transparency effects are included by using an energy-dependent, impact-parameter-dependent average transmission factor for the projectile and target nuclei, which accounts for the finite mean free path of nucleons in nuclear matter. The ablation step, as implemented by Bowman, Swiatecki, and Tsang (LBL report no. LBL-2908, July 1973), was treated as a single-nucleon emission for every 10 MeV of excitation energy. Fragmentation contributions from electromagnetic dissociation (EMD) processes, arising from the interacting Coulomb fields, are estimated by using the Weiszacker-Williams theory, extended to include electric dipole and electric quadrupole contributions to one-nucleon removal cross sections. HZEFRG1 consists of a main program, seven function subprograms, and thirteen subroutines. Each is fully commented and begins with a brief description of its functionality. The inputs, which are provided interactively by the user in response to on-screen questions, consist of the projectile kinetic energy in units of MeV/nucleon and the masses and charges of the projectile and target nuclei. With proper inputs, HZEFRG1 first calculates the EMD cross sections and then begins the calculations for nuclear fragmentation by searching through a specified number of isotopes for each charge number (Z) from Z=1 (hydrogen) to the charge of the incident fragmenting nucleus (Zp). After completing the nuclear fragmentation cross sections, HZEFRG1 sorts through the results and writes the sorted output to a file in descending order, based on the charge number of the fragmented nucleus. Details of the theory, extensive comparisons of its predictions with available experimental cross section data, and a complete description of the code implementing it are given in the program documentation. HZEFRG1 is written in ANSI FORTRAN 77 to be machine independent. It was originally developed on a DEC VAX series computer, and has been successfully implemented on a DECstation running RISC ULTRIX 4.3, a Sun4 series computer running SunOS 4.1, an HP 9000 series computer running HP-UX 8.0.1, a Cray Y-MP series computer running UNICOS, and IBM PC series computers running MS-DOS 3.3 and higher. HZEFRG1 requires 1Mb of RAM for execution. In addition, a FORTRAN 77 compiler is required to create an executable. A sample output run is included on the distribution medium for numerical comparison. The standard distribution medium for this program is a 3.5 inch 1.44Mb MS-DOS format diskette. Alternate distribution media and formats are available upon request. HZEFRG1 was completed in 1992.

Operate a Nuclear Power Plant.

ERIC Educational Resources Information Center

Frimpter, Bonnie J.; And Others

1983-01-01

Describes classroom use of a computer program originally published in Creative Computing magazine. "The Nuclear Power Plant" (runs on Apple II with 48K memory) simulates the operating of a nuclear generating station, requiring students to make decisions as they assume the task of managing the plant. (JN)

Research on pressure control of pressurizer in pressurized water reactor nuclear power plant

NASA Astrophysics Data System (ADS)

Dai, Ling; Yang, Xuhong; Liu, Gang; Ye, Jianhua; Qian, Hong; Xue, Yang

2010-07-01

Pressurizer is one of the most important components in the nuclear reactor system. Its function is to keep the pressure of the primary circuit. It can prevent shutdown of the system from the reactor accident under the normal transient state while keeping the setting value in the normal run-time. This paper is mainly research on the pressure system which is running in the Daya Bay Nuclear Power Plant. A conventional PID controller and a fuzzy controller are designed through analyzing the dynamic characteristics and calculating the transfer function. Then a fuzzy PID controller is designed by analyzing the results of two controllers. The fuzzy PID controller achieves the optimal control system finally.

Powering the Nuclear Navy (U.S. Department of Energy)

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

None

Secretary Perry toured the USS Harry Truman with Admiral Caldwell. The Truman is powered by the Department of Energy’s Nuclear Propulsion Program. These ships can run 25 years with a single nuclear-powered reactor. Secretary Perry was briefed on the importance of nuclear propulsion to the carrier’s capabilities. The Naval Nuclear Propulsion Program provides power plants that ensure safety, reliability, and extended deployment capacity.

Advances in analytical methodologies to guide bioprocess engineering for bio-therapeutics.

PubMed

Saldova, Radka; Kilcoyne, Michelle; Stöckmann, Henning; Millán Martín, Silvia; Lewis, Amanda M; Tuite, Catherine M E; Gerlach, Jared Q; Le Berre, Marie; Borys, Michael C; Li, Zheng Jian; Abu-Absi, Nicholas R; Leister, Kirk; Joshi, Lokesh; Rudd, Pauline M

2017-03-01

This study was performed to monitor the glycoform distribution of a recombinant antibody fusion protein expressed in CHO cells over the course of fed-batch bioreactor runs using high-throughput methods to accurately determine the glycosylation status of the cell culture and its product. Three different bioreactors running similar conditions were analysed at the same five time-points using the advanced methods described here. N-glycans from cell and secreted glycoproteins from CHO cells were analysed by HILIC-UPLC and MS, and the total glycosylation (both N- and O-linked glycans) secreted from the CHO cells were analysed by lectin microarrays. Cell glycoproteins contained mostly high mannose type N-linked glycans with some complex glycans; sialic acid was α-(2,3)-linked, galactose β-(1,4)-linked, with core fucose. Glycans attached to secreted glycoproteins were mostly complex with sialic acid α-(2,3)-linked, galactose β-(1,4)-linked, with mostly core fucose. There were no significant differences noted among the bioreactors in either the cell pellets or supernatants using the HILIC-UPLC method and only minor differences at the early time-points of days 1 and 3 by the lectin microarray method. In comparing different time-points, significant decreases in sialylation and branching with time were observed for glycans attached to both cell and secreted glycoproteins. Additionally, there was a significant decrease over time in high mannose type N-glycans from the cell glycoproteins. A combination of the complementary methods HILIC-UPLC and lectin microarrays could provide a powerful and rapid HTP profiling tool capable of yielding qualitative and quantitative data for a defined biopharmaceutical process, which would allow valuable near 'real-time' monitoring of the biopharmaceutical product. Copyright © 2016 Elsevier Inc. All rights reserved.

MVIAeval: a web tool for comprehensively evaluating the performance of a new missing value imputation algorithm.

PubMed

Wu, Wei-Sheng; Jhou, Meng-Jhun

2017-01-13

Missing value imputation is important for microarray data analyses because microarray data with missing values would significantly degrade the performance of the downstream analyses. Although many microarray missing value imputation algorithms have been developed, an objective and comprehensive performance comparison framework is still lacking. To solve this problem, we previously proposed a framework which can perform a comprehensive performance comparison of different existing algorithms. Also the performance of a new algorithm can be evaluated by our performance comparison framework. However, constructing our framework is not an easy task for the interested researchers. To save researchers' time and efforts, here we present an easy-to-use web tool named MVIAeval (Missing Value Imputation Algorithm evaluator) which implements our performance comparison framework. MVIAeval provides a user-friendly interface allowing users to upload the R code of their new algorithm and select (i) the test datasets among 20 benchmark microarray (time series and non-time series) datasets, (ii) the compared algorithms among 12 existing algorithms, (iii) the performance indices from three existing ones, (iv) the comprehensive performance scores from two possible choices, and (v) the number of simulation runs. The comprehensive performance comparison results are then generated and shown as both figures and tables. MVIAeval is a useful tool for researchers to easily conduct a comprehensive and objective performance evaluation of their newly developed missing value imputation algorithm for microarray data or any data which can be represented as a matrix form (e.g. NGS data or proteomics data). Thus, MVIAeval will greatly expedite the progress in the research of missing value imputation algorithms.

Genome-wide investigation of the role of the tRNA nuclear-cytoplasmic trafficking pathway in regulation of the yeast Saccharomyces cerevisiae transcriptome and proteome.

PubMed

Chu, Hui-Yi; Hopper, Anita K

2013-11-01

In eukaryotic cells, tRNAs are transcribed and partially processed in the nucleus before they are exported to the cytoplasm, where they have an essential role in protein synthesis. Surprisingly, mature cytoplasmic tRNAs shuttle between nucleus and cytoplasm, and tRNA subcellular distribution is nutrient dependent. At least three members of the β-importin family, Los1, Mtr10, and Msn5, function in tRNA nuclear-cytoplasmic intracellular movement. To test the hypothesis that the tRNA retrograde pathway regulates the translation of particular transcripts, we compared the expression profiles from nontranslating mRNAs and polyribosome-associated translating mRNAs collected from msn5Δ, mtr10Δ, and wild-type cells under fed or acute amino acid depletion conditions. Our microarray data revealed that the methionine, arginine, and leucine biosynthesis pathways are targets of the tRNA retrograde process. We confirmed the microarray data by Northern and Western blot analyses. The levels of some of the particular target mRNAs were reduced, while others appeared not to be affected. However, the protein levels of all tested targets in these pathways were greatly decreased when tRNA nuclear import or reexport to the cytoplasm was disrupted. This study provides information that tRNA nuclear-cytoplasmic dynamics is connected to the biogenesis of proteins involved in amino acid biosynthesis.

Genome-Wide Investigation of the Role of the tRNA Nuclear-Cytoplasmic Trafficking Pathway in Regulation of the Yeast Saccharomyces cerevisiae Transcriptome and Proteome

PubMed Central

Chu, Hui-Yi

2013-01-01

In eukaryotic cells, tRNAs are transcribed and partially processed in the nucleus before they are exported to the cytoplasm, where they have an essential role in protein synthesis. Surprisingly, mature cytoplasmic tRNAs shuttle between nucleus and cytoplasm, and tRNA subcellular distribution is nutrient dependent. At least three members of the β-importin family, Los1, Mtr10, and Msn5, function in tRNA nuclear-cytoplasmic intracellular movement. To test the hypothesis that the tRNA retrograde pathway regulates the translation of particular transcripts, we compared the expression profiles from nontranslating mRNAs and polyribosome-associated translating mRNAs collected from msn5Δ, mtr10Δ, and wild-type cells under fed or acute amino acid depletion conditions. Our microarray data revealed that the methionine, arginine, and leucine biosynthesis pathways are targets of the tRNA retrograde process. We confirmed the microarray data by Northern and Western blot analyses. The levels of some of the particular target mRNAs were reduced, while others appeared not to be affected. However, the protein levels of all tested targets in these pathways were greatly decreased when tRNA nuclear import or reexport to the cytoplasm was disrupted. This study provides information that tRNA nuclear-cytoplasmic dynamics is connected to the biogenesis of proteins involved in amino acid biosynthesis. PMID:23979602

Genome Expression Pathway Analysis Tool – Analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

PubMed Central

Weniger, Markus; Engelmann, Julia C; Schultz, Jörg

2007-01-01

Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at . PMID:17543125

Remote monitoring of the Gravelly Run thermal plume at Hopewell and the thermal plume at the Surry Nuclear Power Plant on the James River

NASA Technical Reports Server (NTRS)

Talay, T. A.; Sykes, K. W.; Kuo, C. Y.

1979-01-01

On May 17, 1977, a remote sensing experiment was conducted on the James River, Virginia, whereby thermal spectrometer and near-infrared photography data of thermal discharges at Hopewell and the Surry nuclear power plant were obtained by an aircraft for one tidal cycle. These data were used in subsequent investigations into the near field discharge trajectories. For the Gravelly Run thermal plume at Hopewell, several empirical expressions for the plume centerline were evaluated by comparisons of the computed trajectories and those observed in the remote sensing images.

An introduction to using the FORTRAN programs provided with Computational Nuclear Physics 1 Nuclear Structure

NASA Technical Reports Server (NTRS)

Boytos, Matthew A.; Norbury, John W.

1992-01-01

The authors of this paper have provided a set of ready-to-run FORTRAN programs that should be useful in the field of theoretical nuclear physics. The purpose of this document is to provide a simple synopsis of the programs and their use. A separate section is devoted to each program set and includes: abstract; files; compiling, linking, and running; obtaining results; and a tutorial.

A Novel Plasmid-Based Microarray Screen Identifies Suppressors of rrp6Δ in Saccharomyces cerevisiae▿†

PubMed Central

Abruzzi, Katharine; Denome, Sylvia; Olsen, Jens Raabjerg; Assenholt, Jannie; Haaning, Line Lindegaard; Jensen, Torben Heick; Rosbash, Michael

2007-01-01

Genetic screens in Saccharomyces cerevisiae provide novel information about interacting genes and pathways. We screened for high-copy-number suppressors of a strain with the gene encoding the nuclear exosome component Rrp6p deleted, with either a traditional plate screen for suppressors of rrp6Δ temperature sensitivity or a novel microarray enhancer/suppressor screening (MES) strategy. MES combines DNA microarray technology with high-copy-number plasmid expression in liquid media. The plate screen and MES identified overlapping, but also different, suppressor genes. Only MES identified the novel mRNP protein Nab6p and the tRNA transporter Los1p, which could not have been identified in a traditional plate screen; both genes are toxic when overexpressed in rrp6Δ strains at 37°C. Nab6p binds poly(A)+ RNA, and the functions of Nab6p and Los1p suggest that mRNA metabolism and/or protein synthesis are growth rate limiting in rrp6Δ strains. Microarray analyses of gene expression in rrp6Δ strains and a number of suppressor strains support this hypothesis. PMID:17101774

Gene expression profiling of porcine skeletal muscle in the early recovery phase following acute physical activity.

PubMed

Jensen, Jeanette H; Conley, Lene N; Hedegaard, Jakob; Nielsen, Mathilde; Young, Jette F; Oksbjerg, Niels; Hornshøj, Henrik; Bendixen, Christian; Thomsen, Bo

2012-07-01

Acute physical activity elicits changes in gene expression in skeletal muscles to promote metabolic changes and to repair exercise-induced muscle injuries. In the present time-course study, pigs were submitted to an acute bout of treadmill running until near exhaustion to determine the impact of unaccustomed exercise on global transcriptional profiles in porcine skeletal muscles. Using a combined microarray and candidate gene approach, we identified a suite of genes that are differentially expressed in muscles during postexercise recovery. Several members of the heat shock protein family and proteins associated with proteolytic events, such as the muscle-specific E3 ubiquitin ligase atrogin-1, were significantly upregulated, suggesting that protein breakdown, prevention of protein aggregation and stabilization of unfolded proteins are important processes for restoration of cellular homeostasis. We also detected an upregulation of genes that are associated with muscle cell proliferation and differentiation, including MUSTN1, ASB5 and CSRP3, possibly reflecting activation, differentiation and fusion of satellite cells to facilitate repair of muscle damage. In addition, exercise increased expression of the orphan nuclear hormone receptor NR4A3, which regulates metabolic functions associated with lipid, carbohydrate and energy homeostasis. Finally, we observed an unanticipated induction of the long non-coding RNA transcript NEAT1, which has been implicated in RNA processing and nuclear retention of adenosine-to-inosine edited mRNAs in the ribonucleoprotein bodies called paraspeckles. These findings expand the complexity of pathways affected by acute contractile activity of skeletal muscle, contributing to a better understanding of the molecular processes that occur in muscle tissue in the recovery phase.

Enhanced Component Performance Study: Motor-Driven Pumps 1998–2014

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

Schroeder, John Alton

2016-02-01

This report presents an enhanced performance evaluation of motor-driven pumps at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from fiscal year 1998 through 2014 for the component reliability as reported in the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The motor-driven pump failure modes considered for standby systems are failure to start, failure to run less than or equal to one hour, and failure to run more than one hour; for normally running systems, the failure modes considered are failure to start and failure tomore » run. An eight hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire active period. Statistically significant increasing trends were identified in pump run hours per reactor year. Statistically significant decreasing trends were identified for standby systems industry-wide frequency of start demands, and run hours per reactor year for runs of less than or equal to one hour.« less

Sustainability of industrial yeast serial repitching practice studied by gene expression and correlation analysis.

PubMed

Bühligen, Franziska; Rüdinger, Philipp; Fetzer, Ingo; Stahl, Frank; Scheper, Thomas; Harms, Hauke; Müller, Susann

2013-12-01

Bottom-fermenting Saccharomyces pastorianus strains driving brewing fermentation processes are usually reused several times. It is still unclear, whether the number of successions may have an impact on cell physiology prompting consequences for brewing quality. In this study, fermentation performance of up to twenty consecutive runs in a brewery was investigated. For each run mRNA expression levels of cellular marker molecules, which are known to correlate with metabolism, hexose transport, aging processes, stress response mechanisms and flocculation capability was estimated to obtain information on changes in cell physiology over the successive runs. Low-density microarrays were used for this purpose and the resulting gene expression profiles were finally correlated with changes in the abiotic micro-environments. A surprising stability of the marker molecule expression profiles within each specific serial repitching was stated. Loss of flocculation or an advanced aging could not be detected during serial repitching in the analyzed brewery. However, certain runs of the serial repitchings showed high variation in stress response which was found to be caused by perturbations of the abiotic conditions. Regardless, the study showed that S. pastorianus can be used repeatedly in serial repitching processes without loss of prominent physiological characteristics. Copyright © 2013 Elsevier B.V. All rights reserved.

Status of nuclear PDFs after the first LHC p-Pb run

NASA Astrophysics Data System (ADS)

Paukkunen, Hannu

2017-11-01

In this talk, I overview the recent progress on the global analysis of nuclear parton distribution functions (nuclear PDFs). After first introducing the contemporary fits, the analysis procedures are quickly recalled and the ambiguities in the use of experimental data outlined. Various nuclear-PDF parametrizations are compared and the main differences explained. The effects of nuclear PDFs in the LHC p-Pb hard-process observables are discussed and some future prospects sketched.

hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine.

PubMed

Falgreen, Steffen; Ellern Bilgrau, Anders; Brøndum, Rasmus Froberg; Hjort Jakobsen, Lasse; Have, Jonas; Lindblad Nielsen, Kasper; El-Galaly, Tarec Christoffer; Bødker, Julie Støve; Schmitz, Alexander; H Young, Ken; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

2016-01-01

Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically. The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

PubMed Central

Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher

2016-01-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

Met Nuclear Localization and Signaling in Breast Cancer

DTIC Science & Technology

2006-05-01

and in germinal regions of many tissues using 4 unique antibodies . Cell fractionation reveals a 60kDa band recognized by C-terminal Met antibodies ...cascades such as Gab1 , Grb2 and PI3K, leading to proliferation, scattering, increased motility, invasion and branching morphogenesis (reviewed in (2...Identification of Met antibodies for use on tissue microarray of normal and cancerous cells, Months 12-24 Task 2. Definition of the domain

ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses

PubMed Central

Stokes, Todd H; Torrance, JT; Li, Henry; Wang, May D

2008-01-01

Background A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. Results To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers (Semantic Agents) such as Google to further enhance data discovery. Conclusions Microarray data and meta information in ArrayWiki are distributed and visualized using a novel and compact data storage format, BioPNG. Also, they are open to the research community for curation, modification, and contribution. By making a small investment of time to learn the syntax and structure common to all sites running MediaWiki software, domain scientists and practioners can all contribute to make better use of microarray technologies in research and medical practices. ArrayWiki is available at . PMID:18541053

Low carbon and clean energy scenarios for India: Analysis of targets approach

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

Shukla, Priyadarshi R.; Chaturvedi, Vaibhav

2012-12-01

Low carbon energy technologies are gaining increasing importance in India for reducing emissions as well as diversifying its energy supply mix. The present paper presents and analyses a targeted approach for pushing solar, wind and nuclear technologies in the Indian energy market. Targets for these technologies have been constructed on the basis of Indian government documents, policy announcements and expert opinion. Different targets have been set for the reference scenario and the carbon price scenario. In the reference scenario it is found that in the long run all solar, wind and nuclear will achieve their targets without any subsidy push.more » In the short run however, nuclear and solar energy require significant subsidy push. Nuclear energy requires a much higher subsidy allocation as compared to solar because the targets assumed are also higher for nuclear energy. Under a carbon price scenario, the carbon price drives the penetration of these technologies significantly. Still subsidy is required especially in the short run when the carbon price is low. It is also found that pushing solar, wind and nuclear technologies might lead to decrease in share of CCS under the price scenario and biomass under both BAU and price scenario, which implies that one set of low carbon technologies is substituted by other set of low carbon technologies. Thus the objective of emission mitigation might not be achieved due to this substitution. Moreover sensitivity on nuclear energy cost was done to represent risk mitigation for this technology and it was found that higher cost can significantly decrease the share of this technology under both the BAU and carbon price scenario.« less

Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

PubMed Central

Howat, William J; Blows, Fiona M; Provenzano, Elena; Brook, Mark N; Morris, Lorna; Gazinska, Patrycja; Johnson, Nicola; McDuffus, Leigh‐Anne; Miller, Jodi; Sawyer, Elinor J; Pinder, Sarah; van Deurzen, Carolien H M; Jones, Louise; Sironen, Reijo; Visscher, Daniel; Caldas, Carlos; Daley, Frances; Coulson, Penny; Broeks, Annegien; Sanders, Joyce; Wesseling, Jelle; Nevanlinna, Heli; Fagerholm, Rainer; Blomqvist, Carl; Heikkilä, Päivi; Ali, H Raza; Dawson, Sarah‐Jane; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli‐Matti; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W; Couch, Fergus J; Olson, Janet E; Devillee, Peter; Mesker, Wilma E; Seyaneve, Caroline M; Hollestelle, Antoinette; Benitez, Javier; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Bolla, Manjeet K; Easton, Douglas F; Schmidt, Marjanka K; Pharoah, Paul D; Sherman, Mark E

2014-01-01

Abstract Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker‐specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results. PMID:27499890

Evaluation of external RNA controls for the standardisation of gene expression biomarker measurements.

PubMed

Devonshire, Alison S; Elaswarapu, Ramnath; Foy, Carole A

2010-11-24

Gene expression profiling is an important approach for detecting diagnostic and prognostic biomarkers, and predicting drug safety. The development of a wide range of technologies and platforms for measuring mRNA expression makes the evaluation and standardization of transcriptomic data problematic due to differences in protocols, data processing and analysis methods. Thus, universal RNA standards, such as those developed by the External RNA Controls Consortium (ERCC), are proposed to aid validation of research findings from diverse platforms such as microarrays and RT-qPCR, and play a role in quality control (QC) processes as transcriptomic profiling becomes more commonplace in the clinical setting. Panels of ERCC RNA standards were constructed in order to test the utility of these reference materials (RMs) for performance characterization of two selected gene expression platforms, and for discrimination of biomarker profiles between groups. The linear range, limits of detection and reproducibility of microarray and RT-qPCR measurements were evaluated using panels of RNA standards. Transcripts of low abundance (≤ 10 copies/ng total RNA) showed more than double the technical variability compared to higher copy number transcripts on both platforms. Microarray profiling of two simulated 'normal' and 'disease' panels, each consisting of eight different RNA standards, yielded robust discrimination between the panels and between standards with varying fold change ratios, showing no systematic effects due to different labelling and hybridization runs. Also, comparison of microarray and RT-qPCR data for fold changes showed agreement for the two platforms. ERCC RNA standards provide a generic means of evaluating different aspects of platform performance, and can provide information on the technical variation associated with quantification of biomarkers expressed at different levels of physiological abundance. Distinct panels of standards serve as an ideal quality control tool kit for determining the accuracy of fold change cut-off threshold and the impact of experimentally-derived noise on the discrimination of normal and disease profiles.

A python module to normalize microarray data by the quantile adjustment method.

PubMed

Baber, Ibrahima; Tamby, Jean Philippe; Manoukis, Nicholas C; Sangaré, Djibril; Doumbia, Seydou; Traoré, Sekou F; Maiga, Mohamed S; Dembélé, Doulaye

2011-06-01

Microarray technology is widely used for gene expression research targeting the development of new drug treatments. In the case of a two-color microarray, the process starts with labeling DNA samples with fluorescent markers (cyanine 635 or Cy5 and cyanine 532 or Cy3), then mixing and hybridizing them on a chemically treated glass printed with probes, or fragments of genes. The level of hybridization between a strand of labeled DNA and a probe present on the array is measured by scanning the fluorescence of spots in order to quantify the expression based on the quality and number of pixels for each spot. The intensity data generated from these scans are subject to errors due to differences in fluorescence efficiency between Cy5 and Cy3, as well as variation in human handling and quality of the sample. Consequently, data have to be normalized to correct for variations which are not related to the biological phenomena under investigation. Among many existing normalization procedures, we have implemented the quantile adjustment method using the python computer language, and produced a module which can be run via an HTML dynamic form. This module is composed of different functions for data files reading, intensity and ratio computations and visualization. The current version of the HTML form allows the user to visualize the data before and after normalization. It also gives the option to subtract background noise before normalizing the data. The output results of this module are in agreement with the results of other normalization tools. Published by Elsevier B.V.

Exercise-mimetic AICAR transiently benefits brain function

PubMed Central

Guerrieri, Davide; van Praag, Henriette

2015-01-01

Exercise enhances learning and memory in animals and humans. The role of peripheral factors that may trigger the beneficial effects of running on brain function has been sparsely examined. In particular, it is unknown whether AMP-kinase (AMPK) activation in muscle can predict enhancement of brain plasticity. Here we compare the effects of running and administration of AMPK agonist 5-Aminoimidazole-4-carboxamide 1-β-D-ribofuranoside (AICAR, 500 mg/kg), for 3, 7 or 14 days in one-month-old male C57BL/6J mice, on muscle AMPK signaling. At the time-points where we observed equivalent running- and AICAR-induced muscle pAMPK levels (7 and 14 days), cell proliferation, synaptic plasticity and gene expression, as well as markers of oxidative stress and inflammation in the dentate gyrus (DG) of the hippocampus and lateral entorhinal cortex (LEC) were evaluated. At the 7-day time-point, both regimens increased new DG cell number and brain-derived neurotrophic factor (BDNF) protein levels. Furthermore, microarray analysis of DG and LEC tissue showed a remarkable overlap between running and AICAR in the regulation of neuronal, mitochondrial and metabolism related gene classes. Interestingly, while similar outcomes for both treatments were stable over time in muscle, in the brain an inversion occurred at fourteen days. The compound no longer increased DG cell proliferation or neurotrophin levels, and upregulated expression of apoptotic genes and inflammatory cytokine interleukin-1β. Thus, an exercise mimetic that produces changes in muscle consistent with those of exercise does not have the same sustainable positive effects on the brain, indicating that only running consistently benefits brain function. PMID:26286955

Exercise-mimetic AICAR transiently benefits brain function.

PubMed

Guerrieri, Davide; van Praag, Henriette

2015-07-30

Exercise enhances learning and memory in animals and humans. The role of peripheral factors that may trigger the beneficial effects of running on brain function has been sparsely examined. In particular, it is unknown whether AMP-kinase (AMPK) activation in muscle can predict enhancement of brain plasticity. Here we compare the effects of running and administration of AMPK agonist 5-Aminoimidazole-4-carboxamide 1-β-D-ribofuranoside (AICAR, 500 mg/kg), for 3, 7 or 14 days in one-month-old male C57BL/6J mice, on muscle AMPK signaling. At the time-points where we observed equivalent running- and AICAR-induced muscle pAMPK levels (7 and 14 days), cell proliferation, synaptic plasticity and gene expression, as well as markers of oxidative stress and inflammation in the dentate gyrus (DG) of the hippocampus and lateral entorhinal cortex (LEC) were evaluated. At the 7-day time-point, both regimens increased new DG cell number and brain-derived neurotrophic factor (BDNF) protein levels. Furthermore, microarray analysis of DG and LEC tissue showed a remarkable overlap between running and AICAR in the regulation of neuronal, mitochondrial and metabolism related gene classes. Interestingly, while similar outcomes for both treatments were stable over time in muscle, in the brain an inversion occurred at fourteen days. The compound no longer increased DG cell proliferation or neurotrophin levels, and upregulated expression of apoptotic genes and inflammatory cytokine interleukin-1β. Thus, an exercise mimetic that produces changes in muscle consistent with those of exercise does not have the same sustainable positive effects on the brain, indicating that only running consistently benefits brain function.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium.

PubMed

Ryan, Natalia; Chorley, Brian; Tice, Raymond R; Judson, Richard; Corton, J Christopher

2016-05-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies

PubMed Central

Zlobec, Inti; Suter, Guido; Perren, Aurel; Lugli, Alessandro

2014-01-01

Biomarker research relies on tissue microarrays (TMA). TMAs are produced by repeated transfer of small tissue cores from a ‘donor’ block into a ‘recipient’ block and then used for a variety of biomarker applications. The construction of conventional TMAs is labor intensive, imprecise, and time-consuming. Here, a protocol using next-generation Tissue Microarrays (ngTMA) is outlined. ngTMA is based on TMA planning and design, digital pathology, and automated tissue microarraying. The protocol is illustrated using an example of 134 metastatic colorectal cancer patients. Histological, statistical and logistical aspects are considered, such as the tissue type, specific histological regions, and cell types for inclusion in the TMA, the number of tissue spots, sample size, statistical analysis, and number of TMA copies. Histological slides for each patient are scanned and uploaded onto a web-based digital platform. There, they are viewed and annotated (marked) using a 0.6-2.0 mm diameter tool, multiple times using various colors to distinguish tissue areas. Donor blocks and 12 ‘recipient’ blocks are loaded into the instrument. Digital slides are retrieved and matched to donor block images. Repeated arraying of annotated regions is automatically performed resulting in an ngTMA. In this example, six ngTMAs are planned containing six different tissue types/histological zones. Two copies of the ngTMAs are desired. Three to four slides for each patient are scanned; 3 scan runs are necessary and performed overnight. All slides are annotated; different colors are used to represent the different tissues/zones, namely tumor center, invasion front, tumor/stroma, lymph node metastases, liver metastases, and normal tissue. 17 annotations/case are made; time for annotation is 2-3 min/case. 12 ngTMAs are produced containing 4,556 spots. Arraying time is 15-20 hr. Due to its precision, flexibility and speed, ngTMA is a powerful tool to further improve the quality of TMAs used in clinical and translational research. PMID:25285857

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

Lourdais, J.P.

The second Maxi-Marathon for the defense of the environment organized by the World Council of Nuclear Workers will take place on May 9 and 10, 1997 between Paris and Brussels. this second running, the runners will hand over to Jacques Santer, President of the European Commission, a manifesto reminding the European Union of the advantages of nuclear energy.

Voluntary Running Suppresses Tumor Growth through Epinephrine- and IL-6-Dependent NK Cell Mobilization and Redistribution.

PubMed

Pedersen, Line; Idorn, Manja; Olofsson, Gitte H; Lauenborg, Britt; Nookaew, Intawat; Hansen, Rasmus Hvass; Johannesen, Helle Hjorth; Becker, Jürgen C; Pedersen, Katrine S; Dethlefsen, Christine; Nielsen, Jens; Gehl, Julie; Pedersen, Bente K; Thor Straten, Per; Hojman, Pernille

2016-03-08

Regular exercise reduces the risk of cancer and disease recurrence. Yet the mechanisms behind this protection remain to be elucidated. In this study, tumor-bearing mice randomized to voluntary wheel running showed over 60% reduction in tumor incidence and growth across five different tumor models. Microarray analysis revealed training-induced upregulation of pathways associated with immune function. NK cell infiltration was significantly increased in tumors from running mice, whereas depletion of NK cells enhanced tumor growth and blunted the beneficial effects of exercise. Mechanistic analyses showed that NK cells were mobilized by epinephrine, and blockade of β-adrenergic signaling blunted training-dependent tumor inhibition. Moreover, epinephrine induced a selective mobilization of IL-6-sensitive NK cells, and IL-6-blocking antibodies blunted training-induced tumor suppression, intratumoral NK cell infiltration, and NK cell activation. Together, these results link exercise, epinephrine, and IL-6 to NK cell mobilization and redistribution, and ultimately to control of tumor growth. Copyright © 2016 Elsevier Inc. All rights reserved.

Normal uniform mixture differential gene expression detection for cDNA microarrays

PubMed Central

Dean, Nema; Raftery, Adrian E

2005-01-01

Background One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the thousands of tests run make some of the more popular methods for doing this problematic. Results We propose a simple method, Normal Uniform Differential Gene Expression (NUDGE) detection for finding differentially expressed genes in cDNA microarrays. The method uses a simple univariate normal-uniform mixture model, in combination with new normalization methods for spread as well as mean that extend the lowess normalization of Dudoit, Yang, Callow and Speed (2002) [1]. It takes account of multiple testing, and gives probabilities of differential expression as part of its output. It can be applied to either single-slide or replicated experiments, and it is very fast. Three datasets are analyzed using NUDGE, and the results are compared to those given by other popular methods: unadjusted and Bonferroni-adjusted t tests, Significance Analysis of Microarrays (SAM), and Empirical Bayes for microarrays (EBarrays) with both Gamma-Gamma and Lognormal-Normal models. Conclusion The method gives a high probability of differential expression to genes known/suspected a priori to be differentially expressed and a low probability to the others. In terms of known false positives and false negatives, the method outperforms all multiple-replicate methods except for the Gamma-Gamma EBarrays method to which it offers comparable results with the added advantages of greater simplicity, speed, fewer assumptions and applicability to the single replicate case. An R package called nudge to implement the methods in this paper will be made available soon at . PMID:16011807

Bioinformatics on the cloud computing platform Azure.

PubMed

Shanahan, Hugh P; Owen, Anne M; Harrison, Andrew P

2014-01-01

We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress. We provide a walk through to demonstrate explicitly how Azure can be used to perform these analyses in Appendix S1 and we offer a comparison with a local computation. We note that the use of the Platform as a Service (PaaS) offering of Azure can represent a steep learning curve for bioinformatics developers who will usually have a Linux and scripting language background. On the other hand, the presence of an additional set of libraries makes it easier to deploy software in a parallel (scalable) fashion and explicitly manage such a production run with only a few hundred lines of code, most of which can be incorporated from a template. We propose that this environment is best suited for running stable bioinformatics software by users not involved with its development.

Bioinformatics on the Cloud Computing Platform Azure

PubMed Central

Shanahan, Hugh P.; Owen, Anne M.; Harrison, Andrew P.

2014-01-01

We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress. We provide a walk through to demonstrate explicitly how Azure can be used to perform these analyses in Appendix S1 and we offer a comparison with a local computation. We note that the use of the Platform as a Service (PaaS) offering of Azure can represent a steep learning curve for bioinformatics developers who will usually have a Linux and scripting language background. On the other hand, the presence of an additional set of libraries makes it easier to deploy software in a parallel (scalable) fashion and explicitly manage such a production run with only a few hundred lines of code, most of which can be incorporated from a template. We propose that this environment is best suited for running stable bioinformatics software by users not involved with its development. PMID:25050811

Lawrence Livermore National Laboratory and Sandia National Laboratory Nuclear Accident Dosimetry Support of IER 252 and the Dose Characterization of the Flattop Reactor at the DAF

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

Hickman, D. P.; Jeffers, K. L.; Radev, R. P.

In support of IER 252 “Characterization of the Flattop Reactor at the NCERC”, LLNL performed ROSPEC measurements of the neutron spectrum and deployed 129 Personnel Nuclear Accident Dosimeters (PNAD) to establish the need for height corrections and verification of neutron spectrum evaluation of the fluences and dose. A very limited number of heights (typically only one or two heights) can be measured using neutron spectrometers, therefore it was important to determine if any height correction would be needed in future intercomparisons and studies. Specific measurement positions around the Flatttop reactor are provided in Figure 1. Table 1 provides run andmore » position information for LLNL measurements. The LLNL ROSPEC (R2) was used for run numbers 1 – 7, and vi. PNADs were positioned on trees during run numbers 9, 11, and 13.« less

Identification of modulators of the nuclear receptor peroxisome proliferator-activated receptor α (PPARα) in a mouse liver gene expression compendium.

PubMed

Oshida, Keiyu; Vasani, Naresh; Thomas, Russell S; Applegate, Dawn; Rosen, Mitch; Abbott, Barbara; Lau, Christopher; Guo, Grace; Aleksunes, Lauren M; Klaassen, Curtis; Corton, J Christopher

2015-01-01

The nuclear receptor family member peroxisome proliferator-activated receptor α (PPARα) is activated by therapeutic hypolipidemic drugs and environmentally-relevant chemicals to regulate genes involved in lipid transport and catabolism. Chronic activation of PPARα in rodents increases liver cancer incidence, whereas suppression of PPARα activity leads to hepatocellular steatosis. Analytical approaches were developed to identify biosets (i.e., gene expression differences between two conditions) in a genomic database in which PPARα activity was altered. A gene expression signature of 131 PPARα-dependent genes was built using microarray profiles from the livers of wild-type and PPARα-null mice after exposure to three structurally diverse PPARα activators (WY-14,643, fenofibrate and perfluorohexane sulfonate). A fold-change rank-based test (Running Fisher's test (p-value ≤ 10(-4))) was used to evaluate the similarity between the PPARα signature and a test set of 48 and 31 biosets positive or negative, respectively for PPARα activation; the test resulted in a balanced accuracy of 98%. The signature was then used to identify factors that activate or suppress PPARα in an annotated mouse liver/primary hepatocyte gene expression compendium of ~1850 biosets. In addition to the expected activation of PPARα by fibrate drugs, di(2-ethylhexyl) phthalate, and perfluorinated compounds, PPARα was activated by benzofuran, galactosamine, and TCDD and suppressed by hepatotoxins acetaminophen, lipopolysaccharide, silicon dioxide nanoparticles, and trovafloxacin. Additional factors that activate (fasting, caloric restriction) or suppress (infections) PPARα were also identified. This study 1) developed methods useful for future screening of environmental chemicals, 2) identified chemicals that activate or suppress PPARα, and 3) identified factors including diets and infections that modulate PPARα activity and would be hypothesized to affect chemical-induced PPARα activity.

Identification of Modulators of the Nuclear Receptor Peroxisome Proliferator-Activated Receptor α (PPARα) in a Mouse Liver Gene Expression Compendium

PubMed Central

Oshida, Keiyu; Vasani, Naresh; Thomas, Russell S.; Applegate, Dawn; Rosen, Mitch; Abbott, Barbara; Lau, Christopher; Guo, Grace; Aleksunes, Lauren M.; Klaassen, Curtis; Corton, J. Christopher

2015-01-01

The nuclear receptor family member peroxisome proliferator-activated receptor α (PPARα) is activated by therapeutic hypolipidemic drugs and environmentally-relevant chemicals to regulate genes involved in lipid transport and catabolism. Chronic activation of PPARα in rodents increases liver cancer incidence, whereas suppression of PPARα activity leads to hepatocellular steatosis. Analytical approaches were developed to identify biosets (i.e., gene expression differences between two conditions) in a genomic database in which PPARα activity was altered. A gene expression signature of 131 PPARα-dependent genes was built using microarray profiles from the livers of wild-type and PPARα-null mice after exposure to three structurally diverse PPARα activators (WY-14,643, fenofibrate and perfluorohexane sulfonate). A fold-change rank-based test (Running Fisher’s test (p-value ≤ 10-4)) was used to evaluate the similarity between the PPARα signature and a test set of 48 and 31 biosets positive or negative, respectively for PPARα activation; the test resulted in a balanced accuracy of 98%. The signature was then used to identify factors that activate or suppress PPARα in an annotated mouse liver/primary hepatocyte gene expression compendium of ~1850 biosets. In addition to the expected activation of PPARα by fibrate drugs, di(2-ethylhexyl) phthalate, and perfluorinated compounds, PPARα was activated by benzofuran, galactosamine, and TCDD and suppressed by hepatotoxins acetaminophen, lipopolysaccharide, silicon dioxide nanoparticles, and trovafloxacin. Additional factors that activate (fasting, caloric restriction) or suppress (infections) PPARα were also identified. This study 1) developed methods useful for future screening of environmental chemicals, 2) identified chemicals that activate or suppress PPARα, and 3) identified factors including diets and infections that modulate PPARα activity and would be hypothesized to affect chemical-induced PPARα activity. PMID:25689681

Microarray analysis of miRNA expression profiles following whole body irradiation in a mouse model.

PubMed

Aryankalayil, Molykutty J; Chopra, Sunita; Makinde, Adeola; Eke, Iris; Levin, Joel; Shankavaram, Uma; MacMillan, Laurel; Vanpouille-Box, Claire; Demaria, Sandra; Coleman, C Norman

2018-06-19

Accidental exposure to life-threatening radiation in a nuclear event is a major concern; there is an enormous need for identifying biomarkers for radiation biodosimetry to triage populations and treat critically exposed individuals. To identify dose-differentiating miRNA signatures from whole blood samples of whole body irradiated mice. Mice were whole body irradiated with X-rays (2 Gy-15 Gy); blood was collected at various time-points post-exposure; total RNA was isolated; miRNA microarrays were performed; miRNAs differentially expressed in irradiated vs. unirradiated controls were identified; feature extraction and classification models were applied to predict dose-differentiating miRNA signature. We observed a time and dose responsive alteration in the expression levels of miRNAs. Maximum number of miRNAs were altered at 24-h and 48-h time-points post-irradiation. A 23-miRNA signature was identified using feature selection algorithms and classifier models. An inverse correlation in the expression level changes of miR-17 members, and their targets were observed in whole body irradiated mice and non-human primates. Whole blood-based miRNA expression signatures might be used for predicting radiation exposures in a mass casualty nuclear incident.

Modelling of nuclear power plant decommissioning financing.

PubMed

Bemš, J; Knápek, J; Králík, T; Hejhal, M; Kubančák, J; Vašíček, J

2015-06-01

Costs related to the decommissioning of nuclear power plants create a significant financial burden for nuclear power plant operators. This article discusses the various methodologies employed by selected European countries for financing of the liabilities related to the nuclear power plant decommissioning. The article also presents methodology of allocation of future decommissioning costs to the running costs of nuclear power plant in the form of fee imposed on each megawatt hour generated. The application of the methodology is presented in the form of a case study on a new nuclear power plant with installed capacity 1000 MW. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

oneChannelGUI: a graphical interface to Bioconductor tools, designed for life scientists who are not familiar with R language.

PubMed

Sanges, Remo; Cordero, Francesca; Calogero, Raffaele A

2007-12-15

OneChannelGUI is an add-on Bioconductor package providing a new set of functions extending the capability of the affylmGUI package. This library provides a graphical interface (GUI) for Bioconductor libraries to be used for quality control, normalization, filtering, statistical validation and data mining for single channel microarrays. Affymetrix 3' expression (IVT) arrays as well as the new whole transcript expression arrays, i.e. gene/exon 1.0 ST, are actually implemented. oneChannelGUI is available for most platforms on which R runs, i.e. Windows and Unix-like machines. http://www.bioconductor.org/packages/2.0/bioc/html/oneChannelGUI.html

LncRNA-FEZF1-AS1 promotes tumor proliferation and metastasis in colorectal cancer by regulating PKM2 signaling.

PubMed

Bian, Zehua; Zhang, Jiwei; Li, Min; Feng, Yuyang; Wang, Xue; Zhang, Jia; Yao, Surui; Jin, Guoying; Du, Jun; Han, Weifeng; Yin, Yuan; Huang, Shenglin; Fei, Bojian; Zou, Jian; Huang, Zhaohui

2018-06-18

Long non-coding RNAs (lncRNAs) play key roles in human cancers. Here, FEZF1-AS1, a highly overexpressed lncRNA in colorectal cancer (CRC), was identified by lncRNA microarrays. We aimed to explore the roles and possible molecular mechanisms of FEZF1-AS1 in CRC. LncRNA expression in CRC tissues was measured by lncRNA microarray and qRT-PCR. The functional roles of FEZF1-AS1 in CRC were demonstrated by a series of in vitro and in vivo experiments. RNA pull-down, RNA immunoprecipitation and luciferase analyses were used to demonstrate the potential mechanisms of FEZF1-AS1. We identified a series of differentially expressed lncRNAs in CRC using lncRNA microarrays, and revealed that FEZF1-AS1 is one of the most overexpressed. Further validation in two expanded CRC cohorts confirmed the upregulation of FEZF1-AS1 in CRC, and revealed that increased FEZF1-AS1 expression is associated with poor survival. Functional assays revealed that FEZF1-AS1 promotes CRC cell proliferation and metastasis. Mechanistically, FEZF1-AS1 could bind and increase the stability of the pyruvate kinase 2 (PKM2) protein, resulting in increased cytoplasmic and nuclear PKM2 levels. Increased cytoplasmic PKM2 promoted pyruvate kinase activity and lactate production (aerobic glycolysis), whereas FEZF1-AS1-induced nuclear PKM2 upregulation further activated STAT3 signaling. In addition, PKM2 was upregulated in CRC tissues and correlated with FEZF1-AS1 expression and patient survival. Together, these data provide mechanistic insights into the regulation of FEZF1-AS1 on both STAT3 signaling and glycolysis by binding PKM2 and increasing its stability. Copyright ©2018, American Association for Cancer Research.

Cold nuclear matter effects on J/ψ and Y production in p + Pb collisions at 5 TeV and Pb + Pb collisions at 5.1 TeV

DOE PAGES

Vogt, R.

2016-10-05

We make a systematic study of the modifications of and production in p+Pb collisions atmore » $$\\sqrt{s}$$$_ {NN}$$ = 5 TeV at the LHC. Here, we compare the uncertainties in the EPS09 shadowing parameterization to the calculated mass and scale uncertainties obtained employing the EPS09 NLO central set. We study the dependence of the results on the proton parton density and the choice of the nuclear modifications. We check whether the results obtained are consistent at leading and next-to-leading order. The calculations are compared to the available ALICE and LHCb data on the nuclear modification factors, R pA (y) and R pA (p T) , as well as the forward-backward asymmetries, R FB (y) and R FB (p T) . Finally, we make predictions for the next Pb+Pb run at $$\\sqrt{s}$$$_ {NN}$$ = 5.1 TeV in Run 2 of the LHC.« less

Japan’s Nuclear Future: Policy Debate, Prospects, and U.S. Interests

DTIC Science & Technology

2008-05-09

raised in particular over the construction of an industrial- scale reprocessing facility in Japan,. Additionally, fast breeder reactors also produce more...Nuclear Fuel Cycle Engineering Laboratories. 10 A fast breeder reactor is a fast neutron reactor that produces more plutonium than it consumes, which can...Japan Nuclear Fuel Limited (JNFL) has built and is currently running active testing on a large - scale commercial reprocessing plant at Rokkasho-mura

Evaluation and Numerical Simulation of Tsunami for Coastal Nuclear Power Plants of India

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

Sharma, Pavan K.; Singh, R.K.; Ghosh, A.K.

2006-07-01

Recent tsunami generated on December 26, 2004 due to Sumatra earthquake of magnitude 9.3 resulted in inundation at the various coastal sites of India. The site selection and design of Indian nuclear power plants demand the evaluation of run up and the structural barriers for the coastal plants: Besides it is also desirable to evaluate the early warning system for tsunami-genic earthquakes. The tsunamis originate from submarine faults, underwater volcanic activities, sub-aerial landslides impinging on the sea and submarine landslides. In case of a submarine earthquake-induced tsunami the wave is generated in the fluid domain due to displacement of themore » seabed. There are three phases of tsunami: generation, propagation, and run-up. Reactor Safety Division (RSD) of Bhabha Atomic Research Centre (BARC), Trombay has initiated computational simulation for all the three phases of tsunami source generation, its propagation and finally run up evaluation for the protection of public life, property and various industrial infrastructures located on the coastal regions of India. These studies could be effectively utilized for design and implementation of early warning system for coastal region of the country apart from catering to the needs of Indian nuclear installations. This paper presents some results of tsunami waves based on different analytical/numerical approaches with shallow water wave theory. (authors)« less

Reactor physics teaching and research in the Swiss nuclear engineering master

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

Chawla, R.; Paul Scherrer Inst., CH-5232 Villigen PSI

Since 2008, a Master of Science program in Nuclear Engineering (NE) has been running in Switzerland, thanks to the combined efforts of the country's key players in nuclear teaching and research, viz. the Swiss Federal Inst.s of Technology at Lausanne (EPFL) and at Zurich (ETHZ), the Paul Scherrer Inst. (PSI) at Villigen and the Swiss Nuclear Utilities (Swissnuclear). The present paper, while outlining the academic program as a whole, lays emphasis on the reactor physics teaching and research training accorded to the students in the framework of the developed curriculum. (authors)

Leadership Class Configuration Interaction Code - Status and Opportunities

NASA Astrophysics Data System (ADS)

Vary, James

2011-10-01

With support from SciDAC-UNEDF (www.unedf.org) nuclear theorists have developed and are continuously improving a Leadership Class Configuration Interaction Code (LCCI) for forefront nuclear structure calculations. The aim of this project is to make state-of-the-art nuclear structure tools available to the entire community of researchers including graduate students. The project includes codes such as NuShellX, MFDn and BIGSTICK that run a range of computers from laptops to leadership class supercomputers. Codes, scripts, test cases and documentation have been assembled, are under continuous development and are scheduled for release to the entire research community in November 2011. A covering script that accesses the appropriate code and supporting files is under development. In addition, a Data Base Management System (DBMS) that records key information from large production runs and archived results of those runs has been developed (http://nuclear.physics.iastate.edu/info/) and will be released. Following an outline of the project, the code structure, capabilities, the DBMS and current efforts, I will suggest a path forward that would benefit greatly from a significant partnership between researchers who use the codes, code developers and the National Nuclear Data efforts. This research is supported in part by DOE under grant DE-FG02-87ER40371 and grant DE-FC02-09ER41582 (SciDAC-UNEDF).

Identification and characterization of an oocyte factor required for development of porcine nuclear transfer embryos

PubMed Central

Miyamoto, Kei; Nagai, Kouhei; Kitamura, Naoya; Nishikawa, Tomoaki; Ikegami, Haruka; Binh, Nguyen T.; Tsukamoto, Satoshi; Matsumoto, Mai; Tsukiyama, Tomoyuki; Minami, Naojiro; Yamada, Masayasu; Ariga, Hiroyoshi; Miyake, Masashi; Kawarasaki, Tatsuo; Matsumoto, Kazuya; Imai, Hiroshi

2011-01-01

Nuclear reprogramming of differentiated cells can be induced by oocyte factors. Despite numerous attempts, these factors and mechanisms responsible for successful reprogramming remain elusive. Here, we identify one such factor, necessary for the development of nuclear transfer embryos, using porcine oocyte extracts in which some reprogramming events are recapitulated. After incubating somatic nuclei in oocyte extracts from the metaphase II stage, the oocyte proteins that were specifically and abundantly incorporated into the nuclei were identified by mass spectrometry. Among 25 identified proteins, we especially focused on a multifunctional protein, DJ-1. DJ-1 is present at a high concentration in oocytes from the germinal vesicle stage until embryos at the four-cell stage. Inhibition of DJ-1 function compromises the development of nuclear transfer embryos but not that of fertilized embryos. Microarray analysis of nuclear transfer embryos in which DJ-1 function is inhibited shows perturbed expression of P53 pathway components. In addition, embryonic arrest of nuclear transfer embryos injected with anti–DJ-1 antibody is rescued by P53 inhibition. We conclude that DJ-1 is an oocyte factor that is required for development of nuclear transfer embryos. This study presents a means for identifying natural reprogramming factors in mammalian oocytes and a unique insight into the mechanisms underlying reprogramming by nuclear transfer. PMID:21482765

Myeloid leukemia factor 1 associates with a novel heterogeneous nuclear ribonucleoprotein U-like molecule.

PubMed

Winteringham, Louise N; Endersby, Raelene; Kobelke, Simon; McCulloch, Ross K; Williams, James H; Stillitano, Justin; Cornwall, Scott M; Ingley, Evan; Klinken, S Peter

2006-12-15

Myeloid leukemia factor 1 (MLF1) is an oncoprotein associated with hemopoietic lineage commitment and acute myeloid leukemia. Here we show that Mlf1 associated with a novel binding partner, Mlf1-associated nuclear protein (Manp), a new heterogeneous nuclear ribonucleoprotein (hnRNP) family member, related to hnRNP-U. Manp localized exclusively in the nucleus and could redirect Mlf1 from the cytoplasm into the nucleus. The nuclear content of Mlf1 was also regulated by 14-3-3 binding to a canonical 14-3-3 binding motif within the N terminus of Mlf1. Significantly Mlf1 contains a functional nuclear export signal and localized primarily to the nuclei of hemopoietic cells. Mlf1 was capable of binding DNA, and microarray analysis revealed that it affected the expression of several genes, including transcription factors. In summary, this study reveals that Mlf1 translocates between nucleus and cytoplasm, associates with a novel hnRNP, and influences gene expression.

Bioinformatic analysis of the effects and mechanisms of decitabine and cytarabine on acute myeloid leukemia

PubMed Central

Zhou, Shiyong; Liu, Pengfei; Zhang, Huilai

2017-01-01

Acute myeloid leukemia (AML) is a frequently occurring malignant disease of the blood and may result from a variety of genetic disorders. The present study aimed to identify the underlying mechanisms associated with the therapeutic effects of decitabine and cytarabine on AML, using microarray analysis. The microarray datasets GSE40442 and GSE40870 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine via the Linear Models for Microarray Data package, following data pre-processing. Gene Ontology (GO) analysis of DEGs was performed using the Database for Annotation, Visualization and Integrated Analysis Discovery. Genes corresponding to the differentially methylated sites were obtained using the annotation package of the methylation microarray platform. The overlapping genes were identified, which exhibited the opposite variation trend between gene expression and DNA methylation. Important transcription factor (TF)-gene pairs were screened out, and a regulated network subsequently constructed. A total of 190 DEGs and 540 differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine. A total of 36 GO terms of DEGs were enriched, including nucleosomes, protein-DNA complexes and the nucleosome assembly. The 540 differentially methylated sites were located on 240 genes, including the acid-repeat containing protein (ACRC) gene that was additionally differentially expressed. In addition, 60 TF pairs and overlapped methylated sites, and 140 TF-pairs and DEGs were screened out. The regulated network included 68 nodes and 140 TF-gene pairs. The present study identified various genes including ACRC and proliferating cell nuclear antigen, in addition to various TFs, including TATA-box binding protein associated factor 1 and CCCTC-binding factor, which may be potential therapeutic targets of AML. PMID:28498449

Bioinformatic analysis of the effects and mechanisms of decitabine and cytarabine on acute myeloid leukemia.

PubMed

Zhou, Shiyong; Liu, Pengfei; Zhang, Huilai

2017-07-01

Acute myeloid leukemia (AML) is a frequently occurring malignant disease of the blood and may result from a variety of genetic disorders. The present study aimed to identify the underlying mechanisms associated with the therapeutic effects of decitabine and cytarabine on AML, using microarray analysis. The microarray datasets GSE40442 and GSE40870 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine via the Linear Models for Microarray Data package, following data pre‑processing. Gene Ontology (GO) analysis of DEGs was performed using the Database for Annotation, Visualization and Integrated Analysis Discovery. Genes corresponding to the differentially methylated sites were obtained using the annotation package of the methylation microarray platform. The overlapping genes were identified, which exhibited the opposite variation trend between gene expression and DNA methylation. Important transcription factor (TF)‑gene pairs were screened out, and a regulated network subsequently constructed. A total of 190 DEGs and 540 differentially methylated sites were identified in AML cells treated with decitabine compared with those treated with cytarabine. A total of 36 GO terms of DEGs were enriched, including nucleosomes, protein‑DNA complexes and the nucleosome assembly. The 540 differentially methylated sites were located on 240 genes, including the acid‑repeat containing protein (ACRC) gene that was additionally differentially expressed. In addition, 60 TF pairs and overlapped methylated sites, and 140 TF‑pairs and DEGs were screened out. The regulated network included 68 nodes and 140 TF‑gene pairs. The present study identified various genes including ACRC and proliferating cell nuclear antigen, in addition to various TFs, including TATA‑box binding protein associated factor 1 and CCCTC‑binding factor, which may be potential therapeutic targets of AML.

Atypical nuclear localization of VIP receptors in glioma cell lines and patients

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

Barbarin, Alice; Séité, Paule; Godet, Julie

Highlights: • The VIP receptor VPAC1 contains a putative NLS signal. • VPAC1 is predominantly nuclear in GBM cell lines but not VPAC2. • Non-nuclear VPAC1/2 protein expression is correlated with glioma grade. • Nuclear VPAC1 is observed in 50% of stage IV glioma (GBM). - Abstract: An increasing number of G protein-coupled receptors, like receptors for vasoactive intestinal peptide (VIP), are found in cell nucleus. As VIP receptors are involved in the regulation of glioma cell proliferation and migration, we investigated the expression and the nuclear localization of the VIP receptors VPAC1 and VPAC2 in this cancer. First, bymore » applying Western blot and immunofluorescence detection in three human glioblastoma (GBM) cell lines, we observed a strong nuclear staining for the VPAC1 receptor and a weak nuclear VPAC2 receptor staining. Second, immunohistochemical staining of VPAC1 and VPAC2 on tissue microarrays (TMA) showed that the two receptors were expressed in normal brain and glioma tissues. Expression in the non-nuclear compartment of the two receptors significantly increased with the grade of the tumors. Analysis of nuclear staining revealed a significant increase of VPAC1 staining with glioma grade, with up to 50% of GBM displaying strong VPAC1 nuclear staining, whereas nuclear VPAC2 staining remained marginal. The increase in VPAC receptor expression with glioma grades and the enhanced nuclear localization of the VPAC1 receptors in GBM might be of importance for glioma progression.« less

Access and use of the GUDMAP database of genitourinary development.

PubMed

Davies, Jamie A; Little, Melissa H; Aronow, Bruce; Armstrong, Jane; Brennan, Jane; Lloyd-MacGilp, Sue; Armit, Chris; Harding, Simon; Piu, Xinjun; Roochun, Yogmatee; Haggarty, Bernard; Houghton, Derek; Davidson, Duncan; Baldock, Richard

2012-01-01

The Genitourinary Development Molecular Atlas Project (GUDMAP) aims to document gene expression across time and space in the developing urogenital system of the mouse, and to provide access to a variety of relevant practical and educational resources. Data come from microarray gene expression profiling (from laser-dissected and FACS-sorted samples) and in situ hybridization at both low (whole-mount) and high (section) resolutions. Data are annotated to a published, high-resolution anatomical ontology and can be accessed using a variety of search interfaces. Here, we explain how to run typical queries on the database, by gene or anatomical location, how to view data, how to perform complex queries, and how to submit data.

Gene selection for microarray cancer classification using a new evolutionary method employing artificial intelligence concepts.

PubMed

Dashtban, M; Balafar, Mohammadali

2017-03-01

Gene selection is a demanding task for microarray data analysis. The diverse complexity of different cancers makes this issue still challenging. In this study, a novel evolutionary method based on genetic algorithms and artificial intelligence is proposed to identify predictive genes for cancer classification. A filter method was first applied to reduce the dimensionality of feature space followed by employing an integer-coded genetic algorithm with dynamic-length genotype, intelligent parameter settings, and modified operators. The algorithmic behaviors including convergence trends, mutation and crossover rate changes, and running time were studied, conceptually discussed, and shown to be coherent with literature findings. Two well-known filter methods, Laplacian and Fisher score, were examined considering similarities, the quality of selected genes, and their influences on the evolutionary approach. Several statistical tests concerning choice of classifier, choice of dataset, and choice of filter method were performed, and they revealed some significant differences between the performance of different classifiers and filter methods over datasets. The proposed method was benchmarked upon five popular high-dimensional cancer datasets; for each, top explored genes were reported. Comparing the experimental results with several state-of-the-art methods revealed that the proposed method outperforms previous methods in DLBCL dataset. Copyright © 2017 Elsevier Inc. All rights reserved.

Chemiluminescence microarrays in analytical chemistry: a critical review.

PubMed

Seidel, Michael; Niessner, Reinhard

2014-09-01

Multi-analyte immunoassays on microarrays and on multiplex DNA microarrays have been described for quantitative analysis of small organic molecules (e.g., antibiotics, drugs of abuse, small molecule toxins), proteins (e.g., antibodies or protein toxins), and microorganisms, viruses, and eukaryotic cells. In analytical chemistry, multi-analyte detection by use of analytical microarrays has become an innovative research topic because of the possibility of generating several sets of quantitative data for different analyte classes in a short time. Chemiluminescence (CL) microarrays are powerful tools for rapid multiplex analysis of complex matrices. A wide range of applications for CL microarrays is described in the literature dealing with analytical microarrays. The motivation for this review is to summarize the current state of CL-based analytical microarrays. Combining analysis of different compound classes on CL microarrays reduces analysis time, cost of reagents, and use of laboratory space. Applications are discussed, with examples from food safety, water safety, environmental monitoring, diagnostics, forensics, toxicology, and biosecurity. The potential and limitations of research on multiplex analysis by use of CL microarrays are discussed in this review.

Renewables cannot be stored economically on a well-run power system

NASA Astrophysics Data System (ADS)

Swift-Hook, Donald

2017-11-01

Economic storage on a power system must rely on arbitrage, buying electrical power when it is cheap and selling when it is dear. In practice, this means a store must buy power at night and sell it during the day. There is no solar power at night [by definition], so solar power cannot be stored economically on a well-run power system. Also renewables [and nuclear] are installed commercially to save fuel but fuel costs the same at night as it does during the day, so there is no arbitrage on fuel-saving to justify storage. Pumped water storage has always been widely used on power systems and is still the only method that is economic today, although many others have been tried, including fuels cells, compressed air and batteries. Devices for power correction and balancing [e.g. capacitor banks and batteries] may physically involve the storage of energy [just as a mobile phone does] but it is misleading to describe them as methods of power system storage, [just as it would be misleading to call a School bus a fuel transportation system, even though it does transport fuel]. When a power system has different sorts of plant generating - coal, gas, nuclear, wind etc - any power being put into storage is from the plant that would need to be switched off [because less power was needed] if storage ceased [e.g. because the store became full or failed]. On a well-run power system, that always has the highest fuel/running cost, but the wind blows free and has zero fuel/running cost, so wind is never [normally] stored unless there is no other plant on line i.e. wind power is the last to be stored.

Development of a cell-based high throughput luciferase enzyme fragment complementation assay to identify nuclear-factor-e2-related transcription factor 2 activators.

PubMed

Xie, Wensheng; Pao, Christina; Graham, Taylor; Dul, Ed; Lu, Quinn; Sweitzer, Thomas D; Ames, Robert S; Li, Hu

2012-12-01

Nuclear-factor-E2-related transcription factor 2 (Nrf2) regulates a large panel of Phase II genes and plays an important role in cell survival. Nrf2 activation has been shown as preventing cigarette smoke-induced alveolar enlargement in mice. Therefore, activation of the Nrf2 protein by small-molecule activators represents an attractive therapeutic strategy that is used for chronic obstructive pulmonary disease. In this article, we describe a cell-based luciferase enzyme fragment complementation assay that identifies Nrf2 activators. This assay is based on the interaction of Nrf2 with its nuclear partner MafK or runt-related transcription factor 2 (RunX2) and is dependent on the reconstitution of a "split" luciferase. Firefly luciferase is split into two fragments, which are genetically fused to Nrf2 and MafK or RunX2, respectively. BacMam technology was used to deliver the fusion constructs into cells for expression of the tagged proteins. When the BacMam-transduced cells were treated with Nrf2 activators, the Nrf2 protein was stabilized and translocated into the nucleus where it interacted with MafK or RunX2. The interaction of Nrf2 and MafK or RunX2 brought together the two luciferase fragments that form an active luciferase. The assay was developed in a 384-well format and was optimized by titrating the BacMam concentration, transduction time, cell density, and fetal bovine serum concentration. It was further validated with known Nrf2 activators. Our data show that this assay is robust, sensitive, and amenable to high throughput screening of a large compound collection for the identification of novel Nrf2 activators.

Manufacturing of microarrays.

PubMed

Petersen, David W; Kawasaki, Ernest S

2007-01-01

DNA microarray technology has become a powerful tool in the arsenal of the molecular biologist. Capitalizing on high precision robotics and the wealth of DNA sequences annotated from the genomes of a large number of organisms, the manufacture of microarrays is now possible for the average academic laboratory with the funds and motivation. Microarray production requires attention to both biological and physical resources, including DNA libraries, robotics, and qualified personnel. While the fabrication of microarrays is a very labor-intensive process, production of quality microarrays individually tailored on a project-by-project basis will help researchers shed light on future scientific questions.

Cloud Computing for Complex Performance Codes.

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

Appel, Gordon John; Hadgu, Teklu; Klein, Brandon Thorin

This report describes the use of cloud computing services for running complex public domain performance assessment problems. The work consisted of two phases: Phase 1 was to demonstrate complex codes, on several differently configured servers, could run and compute trivial small scale problems in a commercial cloud infrastructure. Phase 2 focused on proving non-trivial large scale problems could be computed in the commercial cloud environment. The cloud computing effort was successfully applied using codes of interest to the geohydrology and nuclear waste disposal modeling community.

Iowa State University – Final Report for SciDAC3/NUCLEI

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

Vary, James P

The Iowa State University (ISU) contributions to the NUCLEI project are focused on developing, implementing and running an efficient and scalable configuration interaction code (Many-Fermion Dynamics – nuclear or MFDn) for leadership class supercomputers addressing forefront research problems in low-energy nuclear physics. We investigate nuclear structure and reactions with realistic nucleon-nucleon (NN) and three-nucleon (3N) interactions. We select a few highlights from our work that has produced a total of more than 82 refereed publications and more than 109 invited talks under SciDAC3/NUCLEI.

SPIRE Data Evaluation and Nuclear IR Fluorescence Processes.

DTIC Science & Technology

1982-11-30

so that all isotopes can be dealt with in a single run rather than a number of separate runs. At lower altitudes the radiance calculation needs to be...approximation can be inferred from the work of Neuendorffer (1982) on developing an analytic expression for the absorption of a single non-overlapping line...personnel by using prominent atmospheric infrared features such as the OH maximum, the HNO3 maximum, the CO3 4.3 um knee, etc. The azimuth however

A CAMAC-VME-Macintosh data acquisition system for nuclear experiments

NASA Astrophysics Data System (ADS)

Anzalone, A.; Giustolisi, F.

1989-10-01

A multiprocessor system for data acquisition and analysis in low-energy nuclear physics has been realized. The system is built around CAMAC, the VMEbus, and the Macintosh PC. Multiprocessor software has been developed, using RTF, MACsys, and CERN cross-software. The execution of several programs that run on several VME CPUs and on an external PC is coordinated by a mailbox protocol. No operating system is used on the VME CPUs. The hardware, software, and system performance are described.

Development of a Digital Microarray with Interferometric Reflectance Imaging

NASA Astrophysics Data System (ADS)

Sevenler, Derin

This dissertation describes a new type of molecular assay for nucleic acids and proteins. We call this technique a digital microarray since it is conceptually similar to conventional fluorescence microarrays, yet it performs enumerative ('digital') counting of the number captured molecules. Digital microarrays are approximately 10,000-fold more sensitive than fluorescence microarrays, yet maintain all of the strengths of the platform including low cost and high multiplexing (i.e., many different tests on the same sample simultaneously). Digital microarrays use gold nanorods to label the captured target molecules. Each gold nanorod on the array is individually detected based on its light scattering, with an interferometric microscopy technique called SP-IRIS. Our optimized high-throughput version of SP-IRIS is able to scan a typical array of 500 spots in less than 10 minutes. Digital DNA microarrays may have utility in applications where sequencing is prohibitively expensive or slow. As an example, we describe a digital microarray assay for gene expression markers of bacterial drug resistance.

Transcriptomic response of the red tide dinoflagellate, Karenia brevis, to nitrogen and phosphorus depletion and addition.

PubMed

Morey, Jeanine S; Monroe, Emily A; Kinney, Amanda L; Beal, Marion; Johnson, Jillian G; Hitchcock, Gary L; Van Dolah, Frances M

2011-07-05

The role of coastal nutrient sources in the persistence of Karenia brevis red tides in coastal waters of Florida is a contentious issue that warrants investigation into the regulation of nutrient responses in this dinoflagellate. In other phytoplankton studied, nutrient status is reflected by the expression levels of N- and P-responsive gene transcripts. In dinoflagellates, however, many processes are regulated post-transcriptionally. All nuclear encoded gene transcripts studied to date possess a 5' trans-spliced leader (SL) sequence suggestive, based on the trypanosome model, of post-transcriptional regulation. The current study therefore sought to determine if the transcriptome of K. brevis is responsive to nitrogen and phosphorus and is informative of nutrient status. Microarray analysis of N-depleted K. brevis cultures revealed an increase in the expression of transcripts involved in N-assimilation (nitrate and ammonium transporters, glutamine synthetases) relative to nutrient replete cells. In contrast, a transcriptional signal of P-starvation was not apparent despite evidence of P-starvation based on their rapid growth response to P-addition. To study transcriptome responses to nutrient addition, the limiting nutrient was added to depleted cells and changes in global gene expression were assessed over the first 48 hours following nutrient addition. Both N- and P-addition resulted in significant changes in approximately 4% of genes on the microarray, using a significance cutoff of 1.7-fold and p ≤ 10-4. By far, the earliest responding genes were dominated in both nutrient treatments by pentatricopeptide repeat (PPR) proteins, which increased in expression up to 3-fold by 1 h following nutrient addition. PPR proteins are nuclear encoded proteins involved in chloroplast and mitochondria RNA processing. Correspondingly, other functions enriched in response to both nutrients were photosystem and ribosomal genes. Microarray analysis provided transcriptomic evidence for N- but not P-limitation in K. brevis. Transcriptomic responses to the addition of either N or P suggest a concerted program leading to the reactivation of chloroplast functions. Even the earliest responding PPR protein transcripts possess a 5' SL sequence that suggests post-transcriptional control. Given the current state of knowledge of dinoflagellate gene regulation, it is currently unclear how these rapid changes in such transcript levels are achieved.

Nuclear Factor Kappa B Activation Occurs in the Amnion Prior to Labour Onset and Modulates the Expression of Numerous Labour Associated Genes

PubMed Central

Lim, Sheri; MacIntyre, David A.; Lee, Yun S.; Khanjani, Shirin; Terzidou, Vasso; Teoh, T. G.; Bennett, Phillip R.

2012-01-01

Background Prior to the onset of human labour there is an increase in the synthesis of prostaglandins, cytokines and chemokines in the fetal membranes, particular the amnion. This is associated with activation of the transcription factor nuclear factor kappa B (NFκB). In this study we characterised the level of NFκB activity in amnion epithelial cells as a measure of amnion activation in samples collected from women undergoing caesarean section at 39 weeks gestation prior to the onset of labour. Methodology/Principal Findings We found that a proportion of women exhibit low or moderate NFκB activity while other women exhibit high levels of NFκB activity (n = 12). This activation process does not appear to involve classical pathways of NFκB activation but rather is correlated with an increase in nuclear p65-Rel-B dimers. To identify the full range of genes upregulated in association with amnion activation, microarray analysis was performed on carefully characterised non-activated amnion (n = 3) samples and compared to activated samples (n = 3). A total of 919 genes were upregulated in response to amnion activation including numerous inflammatory genes such cyclooxygenase-2 (COX-2, 44-fold), interleukin 8 (IL-8, 6-fold), IL-1 receptor accessory protein (IL-1RAP, 4.5-fold), thrombospondin 1 (TSP-1, 3-fold) and, unexpectedly, oxytocin receptor (OTR, 24-fold). Ingenuity Pathway Analysis of the microarray data reveal the two main gene networks activated concurrently with amnion activation are i) cell death, cancer and morphology and ii) cell cycle, embryonic development and tissue development. Conclusions/Significance Our results indicate that assessment of amnion NFκB activation is critical for accurate sample classification and subsequent interpretation of data. Collectively, our data suggest amnion activation is largely an inflammatory event that occurs in the amnion epithelial layer as a prelude to the onset of labour. PMID:22485186

Comparative gene expression analysis of bovine nuclear-transferred embryos with different developmental potential by cDNA microarray and real-time PCR to determine genes that might reflect calf normality.

PubMed

Kato, Yoko; Li, Xiangping; Amarnath, Dasari; Ushizawa, Koichi; Hashizume, Kazuyoshi; Tokunaga, Tomoyuki; Taniguchi, Masanori; Tsunoda, Yukio

2007-01-01

Placental abnormalities are the main factor in the high incidence of somatic cell clone abnormalities. The expression of several trophoblast cell-specific molecules is enhanced during gestational days 7 to 14. To determine the possible genes whose expression patterns might reflect calf normality, we first compared the gene expression profiles on day 15 between in vitro-fertilized (IVF) embryos and two types of somatic cell nuclear-transferred embryos with either a high (FNT) or low (CNT) incidence of neonatal abnormalities using a cDNA microarray containing 16 of 21 placenta-specific genes developed from tissues collected across gestation. To identify significant genes from the screening of day 15 embryos, genes with a less than two-fold difference in expression between IVF and CNT embryos, and those with a greater than two-fold difference between IVF and FNT and between CNT and FNT were considered to contribute to clone abnormalities. These two comparisons revealed 18 down-regulated and 18 upregulated genes of the 1722 genes examined. We then examined the expression levels of 10 genes with known functions in eight-cell and blastocyst-stage embryos by real-time PCR. The mRNA expression pattern of interferon (IFN)-tau, a trophectoderm-related gene, differed between IVF, CNT, and FNT eight-cell embryos; few or none of the IVF or CNT eight-cell embryos expressed IFN-tau mRNA, but all eight-cell FNT embryos expressed IFN-tau. IFN-tau mRNA expression was significantly higher in IVF blastocysts, however, than in nuclear-transferred blastocysts. Average IFN-tau mRNA expression in FNT blastocysts was not different from that in CNT blastocysts, due to one CNT blastocyst with high expression. The precise relation between early expression of IFN-tau mRNA and inferior developmental potential in cloned embryos should be examined further.

Reliability assessment of MVP-BURN and JENDL-4.0 related to nuclear transmutation of light platinum group elements

NASA Astrophysics Data System (ADS)

Terashima, Atsunori; Nilsson, Mikael; Ozawa, Masaki; Chiba, Satoshi

2017-09-01

The Aprés ORIENT research program, as a concept of advanced nuclear fuel cycle, was initiated in FY2011 aiming at creating stable, highly-valuable elements by nuclear transmutation from ↓ssion products. In order to simulate creation of such elements by (n, γ) reaction succeeded by β- decay in reactors, a continuous-energy Monte Carlo burnup calculation code MVP-BURN was employed. Then, it is one of the most important tasks to con↓rm the reliability of MVP-BURN code and evaluated neutron cross section library. In this study, both an experiment of neutron activation analysis in TRIGA Mark I reactor at University of California, Irvine and the corresponding burnup calculation using MVP-BURN code were performed for validation of the simulation on transmutation of light platinum group elements. Especially, some neutron capture reactions such as 102Ru(n, γ)103Ru, 104Ru(n, γ)105Ru, and 108Pd(n, γ)109Pd were dealt with in this study. From a comparison between the calculation (C) and the experiment (E) about 102Ru(n, γ)103Ru, the deviation (C/E-1) was signi↓cantly large. Then, it is strongly suspected that not MVP-BURN code but the neutron capture cross section of 102Ru belonging to JENDL-4.0 used in this simulation have made the big di↑erence as (C/E-1) >20%.

gemcWeb: A Cloud Based Nuclear Physics Simulation Software

NASA Astrophysics Data System (ADS)

Markelon, Sam

2017-09-01

gemcWeb allows users to run nuclear physics simulations from the web. Being completely device agnostic, scientists can run simulations from anywhere with an Internet connection. Having a full user system, gemcWeb allows users to revisit and revise their projects, and share configurations and results with collaborators. gemcWeb is based on simulation software gemc, which is based on standard GEant4. gemcWeb requires no C++, gemc, or GEant4 knowledge. Using a simple but powerful GUI allows users to configure their project from geometries and configurations stored on the deployment server. Simulations are then run on the server, with results being posted to the user, and then securely stored. Python based and open-source, the main version of gemcWeb is hosted internally at Jefferson National Labratory and used by the CLAS12 and Electron-Ion Collider Project groups. However, as the software is open-source, and hosted as a GitHub repository, an instance can be deployed on the open web, or any institution's intra-net. An instance can be configured to host experiments specific to an institution, and the code base can be modified by any individual or group. Special thanks to: Maurizio Ungaro, PhD., creator of gemc; Markus Diefenthaler, PhD., advisor; and Kyungseon Joo, PhD., advisor.

On-Chip Synthesis of Protein Microarrays from DNA Microarrays Via Coupled In Vitro Transcription and Translation for Surface Plasmon Resonance Imaging Biosensor Applications

PubMed Central

Seefeld, Ting H.; Halpern, Aaron R.; Corn, Robert M.

2012-01-01

Protein microarrays are fabricated from double-stranded DNA (dsDNA) microarrays by a one-step, multiplexed enzymatic synthesis in an on-chip microfluidic format and then employed for antibody biosensing measurements with surface plasmon resonance imaging (SPRI). A microarray of dsDNA elements (denoted as generator elements) that encode either a His-tagged green fluorescent protein (GFP) or a His-tagged luciferase protein is utilized to create multiple copies of messenger RNA (mRNA) in a surface RNA polymerase reaction; the mRNA transcripts are then translated into proteins by cell-free protein synthesis in a microfluidic format. The His-tagged proteins diffuse to adjacent Cu(II)-NTA microarray elements (denoted as detector elements) and are specifically adsorbed. The net result is the on-chip, cell-free synthesis of a protein microarray that can be used immediately for SPRI protein biosensing. The dual element format greatly reduces any interference from the nonspecific adsorption of enzyme or proteins. SPRI measurements for the detection of the antibodies anti-GFP and anti-luciferase were used to verify the formation of the protein microarray. This convenient on-chip protein microarray fabrication method can be implemented for multiplexed SPRI biosensing measurements in both clinical and research applications. PMID:22793370

Microarray analyses reveal novel targets of exercise-induced stress resistance in the dorsal raphe nucleus

PubMed Central

Loughridge, Alice B.; Greenwood, Benjamin N.; Day, Heidi E. W.; McQueen, Matthew B.; Fleshner, Monika

2013-01-01

Serotonin (5-HT) is implicated in the development of stress-related mood disorders in humans. Physical activity reduces the risk of developing stress-related mood disorders, such as depression and anxiety. In rats, 6 weeks of wheel running protects against stress-induced behaviors thought to resemble symptoms of human anxiety and depression. The mechanisms by which exercise confers protection against stress-induced behaviors, however, remain unknown. One way by which exercise could generate stress resistance is by producing plastic changes in gene expression in the dorsal raphe nucleus (DRN). The DRN has a high concentration of 5-HT neurons and is implicated in stress-related mood disorders. The goal of the current experiment was to identify changes in the expression of genes that could be novel targets of exercise-induced stress resistance in the DRN. Adult, male F344 rats were allowed voluntary access to running wheels for 6 weeks; exposed to inescapable stress or no stress; and sacrificed immediately and 2 h after stressor termination. Laser capture micro dissection selectively sampled the DRN. mRNA expression was measured using the whole genome Affymetrix microarray. Comprehensive data analyses of gene expression included differential gene expression, log fold change (LFC) contrast analyses with False Discovery Rate correction, KEGG and Wiki Web Gestalt pathway enrichment analyses, and Weighted Gene Correlational Network Analysis (WGCNA). Our results suggest that physically active rats exposed to stress modulate expression of twice the number of genes, and display a more rapid and strongly coordinated response, than sedentary rats. Bioinformatics analyses revealed several potential targets of stress resistance including genes that are related to immune processes, tryptophan metabolism, and circadian/diurnal rhythms. PMID:23717271

SevenOperators, a Mathematica script for harmonic oscillator nuclear matrix elements arising in semileptonic electroweak interactions

NASA Astrophysics Data System (ADS)

Haxton, Wick; Lunardini, Cecilia

2008-09-01

Semi-leptonic electroweak interactions in nuclei—such as β decay, μ capture, charged- and neutral-current neutrino reactions, and electron scattering—are described by a set of multipole operators carrying definite parity and angular momentum, obtained by projection from the underlying nuclear charge and three-current operators. If these nuclear operators are approximated by their one-body forms and expanded in the nucleon velocity through order |p→|/M, where p→ and M are the nucleon momentum and mass, a set of seven multipole operators is obtained. Nuclear structure calculations are often performed in a basis of Slater determinants formed from harmonic oscillator orbitals, a choice that allows translational invariance to be preserved. Harmonic-oscillator single-particle matrix elements of the multipole operators can be evaluated analytically and expressed in terms of finite polynomials in q, where q is the magnitude of the three-momentum transfer. While results for such matrix elements are available in tabular form, with certain restriction on quantum numbers, the task of determining the analytic form of a response function can still be quite tedious, requiring the folding of the tabulated matrix elements with the nuclear density matrix, and subsequent algebra to evaluate products of operators. Here we provide a Mathematica script for generating these matrix elements, which will allow users to carry out all such calculations by symbolic manipulation. This will eliminate the errors that may accompany hand calculations and speed the calculation of electroweak nuclear cross sections and rates. We illustrate the use of the new script by calculating the cross sections for charged- and neutral-current neutrino scattering in 12C. Program summaryProgram title: SevenOperators Catalogue identifier: AEAY_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAY_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2227 No. of bytes in distributed program, including test data, etc.: 19 382 Distribution format: tar.gz Programming language: Mathematica Computer: Any computer running Mathematica; tested on Mac OS X PowerPC (32-bit) running Mathematica 6.0.0 Operating system: Any running Mathematica RAM: Memory requirements determined by Mathematica; 512 MB or greater RAM and hard drive space of at least 3.0 GB recommended Classification: 17.16, 17.19 Nature of problem: Algebraic evaluation of harmonic oscillator nuclear matrix elements for the one-body multipole operators governing semi-leptonic weak interactions, such as charged- or neutral-current neutrino scattering off nuclei. Solution method: Mathematica evaluation of associated angular momentum algebra and spherical Bessel function radial integrals. Running time: Depends on the complexity of the one-body density matrix employed, but times of a few seconds are typical.

Widespread cerebellar transcriptome changes in Ts65Dn Down syndrome mouse model after lifelong running.

PubMed

Walus, Marius; Kida, Elizabeth; Rabe, Ausma; Albertini, Giorgio; Golabek, Adam A

2016-01-01

Our previous study showed an improvement in locomotor deficits after voluntary lifelong running in Ts65Dn mice, an animal model for Down syndrome (DS). In the present study, we employed mouse microarrays printed with 55,681 probes in an attempt to identify molecular changes in the cerebellar transcriptome that might contribute to the observed behavioral benefits of voluntary long-term running in Ts65Dn mice. Euploid mice were processed in parallel for comparative purposes in some analyses. We found that running significantly changed the expression of 4,315 genes in the cerebellum of Ts65Dn mice, over five times more than in euploid animals, up-regulating 1,991 and down-regulating 2,324 genes. Functional analysis of these genes revealed a significant enrichment of 92 terms in the biological process category, including regulation of biosynthesis and metabolism, protein modification, phosphate metabolism, synaptic transmission, development, regulation of cell death/apoptosis, protein transport, development, neurogenesis and neuron differentiation. The KEGG pathway database identified 18 pathways that are up-regulated and two that are down-regulated by running that were associated with learning, memory, cell signaling, proteolysis, regeneration, cell cycle, proliferation, growth, migration, and survival. Of six mRNA protein products we tested by immunoblotting, four showed significant running-associated changes in their levels, the most prominent in glutaminergic receptor metabotropic 1, and two showed changes that were close to significant. Thus, unexpectedly, our data point to the high molecular plasticity of Ts65Dn mouse cerebellum, which translated into humans with DS, suggests that the motor deficits of individuals with DS could markedly benefit from prolonged exercise. Copyright © 2015 Elsevier B.V. All rights reserved.

Highlight on the dynamic organization of the nucleus.

PubMed

Thorpe, Stephen D; Charpentier, Myriam

2017-01-02

The last decade has seen rapid advances in our understanding of the proteins of the nuclear envelope, which have multiple roles including positioning the nucleus, maintaining its structural organization, and in events ranging from mitosis and meiosis to chromatin positioning and gene expression. Diverse new and stimulating results relating to nuclear organization and genome function from across kingdoms were presented in a session stream entitled "Dynamic Organization of the Nucleus" at this year's Society of Experimental Biology (SEB) meeting in Brighton, UK (July 2016). This was the first session stream run by the Nuclear Dynamics Special Interest Group, which was organized by David Evans, Katja Graumann (both Oxford Brookes University, UK) and Iris Meier (Ohio State University, USA). The session featured presentations on areas relating to nuclear organization across kingdoms including the nuclear envelope, chromatin organization, and genome function.

THE ABRF MARG MICROARRAY SURVEY 2005: TAKING THE PULSE ON THE MICROARRAY FIELD

EPA Science Inventory

Over the past several years microarray technology has evolved into a critical component of any discovery based program. Since 1999, the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) has conducted biennial surveys designed to generate a pr...

The effect of transverse flow on the nuclear modification factor at RHIC and LHC

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

Betz, Barbara; Gyulassy, Miklos

2016-01-22

We determine the nuclear modification factor at RHIC and LHC energies using a generic jet-energy loss model that is expanded by an additional flow factor accounting for the impact of transverse flow. We consider a pQCD-based ansatz with and without jet-energy loss fluctuations that is coupled to a state-of-the-art hydrodynamic prescription and includes a running coupling effect. We show that the nuclear modification factor is a rather insensitive quantity that is barely affected by the flow dynamics of the medium created in a heavy-ion collision.

cDNA microarray analysis of esophageal cancer: discoveries and prospects.

PubMed

Shimada, Yutaka; Sato, Fumiaki; Shimizu, Kazuharu; Tsujimoto, Gozoh; Tsukada, Kazuhiro

2009-07-01

Recent progress in molecular biology has revealed many genetic and epigenetic alterations that are involved in the development and progression of esophageal cancer. Microarray analysis has also revealed several genetic networks that are involved in esophageal cancer. However, clinical application of microarray techniques and use of microarray data have not yet occurred. In this review, we focus on the recent developments and problems with microarray analysis of esophageal cancer.

Parallel, confocal, and complete spectrum imager for fluorescent detection of high-density microarray

NASA Astrophysics Data System (ADS)

Bogdanov, Valery L.; Boyce-Jacino, Michael

1999-05-01

Confined arrays of biochemical probes deposited on a solid support surface (analytical microarray or 'chip') provide an opportunity to analysis multiple reactions simultaneously. Microarrays are increasingly used in genetics, medicine and environment scanning as research and analytical instruments. A power of microarray technology comes from its parallelism which grows with array miniaturization, minimization of reagent volume per reaction site and reaction multiplexing. An optical detector of microarray signals should combine high sensitivity, spatial and spectral resolution. Additionally, low-cost and a high processing rate are needed to transfer microarray technology into biomedical practice. We designed an imager that provides confocal and complete spectrum detection of entire fluorescently-labeled microarray in parallel. Imager uses microlens array, non-slit spectral decomposer, and high- sensitive detector (cooled CCD). Two imaging channels provide a simultaneous detection of localization, integrated and spectral intensities for each reaction site in microarray. A dimensional matching between microarray and imager's optics eliminates all in moving parts in instrumentation, enabling highly informative, fast and low-cost microarray detection. We report theory of confocal hyperspectral imaging with microlenses array and experimental data for implementation of developed imager to detect fluorescently labeled microarray with a density approximately 103 sites per cm2.

Ethical dilemmas of nuclear deterrence

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

Russett, B.M.

An analysis of the May 1983 Pastoral Letter on War and Peace of the US Catholic Bishops examines their ethical arguments, which were critical of accepted policy while failing to change the underlying principles of acceptable deterrence and a just war. The author concludes that there is no easy solution to the problem of nuclear deterrence because there is no way to bridge the extremes of war-winning counterforce and possession without use. The Bishops' central problem was deterrence of attack on US allies or neutrals, but he finds merit in their positions that deterrence need not rely on nuclear threatsmore » and that new ways of thinking are needed for the long run. 20 references. (DCK)« less

The expression of Toll-like receptors 2, 4, 5, 7 and 9 in Merkel cell carcinoma.

PubMed

Jouhi, Lauri; Koljonen, Virve; Böhling, Tom; Haglund, Caj; Hagström, Jaana

2015-04-01

We sought to clarify whether the expression of toll-like receptors (TLR) in Merkel cell carcinoma (MCC) is linked to tumor and patient characteristics, especially the presence of Merkel cell polyoma virus (MCV). The study comprised of 128 patients with data on Merkel cell polyomavirus (MCV) status and clinical features were included in the study. Immunohistochemistry for TLR expression was performed on tissue microarray (TMA) slides. TLR 2, 4, 5, 7 and 9 expression was noted in most of the tumor specimens. Decreased expression of TLR 9 correlated strongly with MCV positivity. Cytoplasmic TLR 2 expression correlated with small tumor size, while nuclear TLR 2 and TLR 5 expressions with larger tumors. Increased nuclear TLR 4 expression and decreased TLR 7 expression were associated with older age. TLR 2, 4, 5, 7 and 9 appear to reflect certain clinicopathological variables and prognostic markers of MCC tumors. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

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

Markidis, S.; Rizwan, U.

The use of virtual nuclear control room can be an effective and powerful tool for training personnel working in the nuclear power plants. Operators could experience and simulate the functioning of the plant, even in critical situations, without being in a real power plant or running any risk. 3D models can be exported to Virtual Reality formats and then displayed in the Virtual Reality environment providing an immersive 3D experience. However, two major limitations of this approach are that 3D models exhibit static textures, and they are not fully interactive and therefore cannot be used effectively in training personnel. Inmore » this paper we first describe a possible solution for embedding the output of a computer application in a 3D virtual scene, coupling real-world applications and VR systems. The VR system reported here grabs the output of an application running on an X server; creates a texture with the output and then displays it on a screen or a wall in the virtual reality environment. We then propose a simple model for providing interaction between the user in the VR system and the running simulator. This approach is based on the use of internet-based application that can be commanded by a laptop or tablet-pc added to the virtual environment. (authors)« less

The nuclear weapons inheritance project: student-to-student dialogues and interactive peer education in disarmament activism.

PubMed

Buhmann, Caecilie Böck

2007-01-01

The Nuclear Weapons Inheritance Project is a student run and student initiated project founded in 2001 with the purpose of increasing awareness of health effects of nuclear policies and empowering university students to take action in a local and international context. The project uses dialogues to discuss nuclear disarmament with university students and a method of interactive peer education to train new trainers. The project has met more than 1500 students in nuclear weapon states in dialogue and trained about 400 students from all over the world. This article describes the methods and results of the project and discuss how the experience of the project can be used in other projects seeking to increase awareness of a topic and to initiate action on social injustice.

The Longhorn Array Database (LAD): An Open-Source, MIAME compliant implementation of the Stanford Microarray Database (SMD)

PubMed Central

Killion, Patrick J; Sherlock, Gavin; Iyer, Vishwanath R

2003-01-01

Background The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. Description The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at Conclusions Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. PMID:12930545

A gain-of-function mutation of plastidic invertase alters nuclear gene expression with sucrose treatment partially via GENOMES UNCOUPLED1-mediated signaling.

PubMed

Maruta, Takanori; Miyazaki, Nozomi; Nosaka, Ryota; Tanaka, Hiroyuki; Padilla-Chacon, Daniel; Otori, Kumi; Kimura, Ayako; Tanabe, Noriaki; Yoshimura, Kazuya; Tamoi, Masahiro; Shigeoka, Shigeru

2015-05-01

Plastid gene expression (PGE) is one of the signals that regulate the expression of photosynthesis-associated nuclear genes (PhANGs) via GENOMES UNCOUPLED1 (GUN1)-dependent retrograde signaling. We recently isolated Arabidopsis sugar-inducible cotyledon yellow-192 (sicy-192), a gain-of-function mutant of plastidic invertase, and showed that following the treatment of this mutant with sucrose, the expression of PhANGs as well as PGE decreased, suggesting that the sicy-192 mutation activates a PGE-evoked and GUN1-mediated retrograde pathway. To clarify the relationship between the sicy-192 mutation, PGE, and GUN1-mediated pathway, plastid and nuclear gene expression in a double mutant of sicy-192 and gun1-101, a null mutant of GUN1 was studied. Plastid-encoded RNA polymerase (PEP)-dependent PGE was markedly suppressed in the sicy-192 mutant by the sucrose treatment, but the suppression as well as cotyledon yellow phenotype was not mitigated by GUN1 disruption. Microarray analysis revealed that the altered expression of nuclear genes such as PhANG in the sucrose-treated sicy-192 mutant was largely dependent on GUN1. The present findings demonstrated that the sicy-192 mutation alters nuclear gene expression with sucrose treatment via GUN1, which is possibly followed by inhibiting PEP-dependent PGE, providing a new insight into the role of plastid sugar metabolism in nuclear gene expression. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Gene-Expression Biomarkers for Application to High-Throughput Radiation Biodosimetry

DTIC Science & Technology

2005-01-01

nuclear disaster . Even with the delayed onset of symptoms, sometimes several days after exposure, gene-expression biomarkers can identify these exposed individuals very early after exposure, allowing for prompt medical intervention. This early assessment of a radiation dose after exposure would enhance the operational commander’s situational awareness of the radiation exposure status of deployed units and increase the prospect of reduced morbidity and mortality through early medical intervention. Candidate gene targets were selected from microarray studies of ex

Extracellular vesicles from Paracoccidioides pathogenic species transport polysaccharide and expose ligands for DC-SIGN receptors

DOE PAGES

da Silva, Roberta Peres; Heiss, Christian; Black, Ian; ...

2015-09-21

Extracellular vesicles (EVs) mediate non-conventional transport of molecules across the fungal cell wall. We aimed at describing the carbohydrate composition and surface carbohydrate epitopes of EVs isolated from the pathogenic fungi Paracoccidioides brasiliensis and P. lutzii using standard procedures. Total EV carbohydrates were ethanol-precipitated from preparations depleted of lipids and proteins, then analyzed by chemical degradation, gas chromatography-mass spectrometry, nuclear magnetic resonance and size-exclusion chromatography. EV glycosyl residues of Glc, Man, and Gal comprised most probably two major components: a high molecular mass 4,6-α-glucan and a galactofuranosylmannan, possibly an oligomer, bearing a 2-α-Manp main chain linked to β-Galf (1,3) andmore » α-Manp (1,6) end units. The results also suggested the presence of small amounts of a (1→6)- Manp polymer, (1→3)-glucan and (1→6)-glucan. Glycan microarrays allowed identification of EV surface lectin(s), while plant lectin microarray profiling revealed terminal Man and GlcNAc residues exposed at the EVs surface. Mammalian lectin microarray profiling showed that DC-SIGN receptors recognized surface carbohydrate in Paracoccidioides EVs. Our results suggest that oligosaccharides, cytoplasmic storage, and cell wall polysaccharides can be exported in fungal EVs, which also expose surface PAMPs and lectins. As a result, the role of these newly identified components in the interaction with the host remains to be unraveled.« less

Extracellular vesicles from Paracoccidioides pathogenic species transport polysaccharide and expose ligands for DC-SIGN receptors

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

da Silva, Roberta Peres; Heiss, Christian; Black, Ian

Extracellular vesicles (EVs) mediate non-conventional transport of molecules across the fungal cell wall. We aimed at describing the carbohydrate composition and surface carbohydrate epitopes of EVs isolated from the pathogenic fungi Paracoccidioides brasiliensis and P. lutzii using standard procedures. Total EV carbohydrates were ethanol-precipitated from preparations depleted of lipids and proteins, then analyzed by chemical degradation, gas chromatography-mass spectrometry, nuclear magnetic resonance and size-exclusion chromatography. EV glycosyl residues of Glc, Man, and Gal comprised most probably two major components: a high molecular mass 4,6-α-glucan and a galactofuranosylmannan, possibly an oligomer, bearing a 2-α-Manp main chain linked to β-Galf (1,3) andmore » α-Manp (1,6) end units. The results also suggested the presence of small amounts of a (1→6)- Manp polymer, (1→3)-glucan and (1→6)-glucan. Glycan microarrays allowed identification of EV surface lectin(s), while plant lectin microarray profiling revealed terminal Man and GlcNAc residues exposed at the EVs surface. Mammalian lectin microarray profiling showed that DC-SIGN receptors recognized surface carbohydrate in Paracoccidioides EVs. Our results suggest that oligosaccharides, cytoplasmic storage, and cell wall polysaccharides can be exported in fungal EVs, which also expose surface PAMPs and lectins. As a result, the role of these newly identified components in the interaction with the host remains to be unraveled.« less

Evolution of the MIDTAL microarray: the adaption and testing of oligonucleotide 18S and 28S rDNA probes and evaluation of subsequent microarray generations with Prymnesium spp. cultures and field samples.

PubMed

McCoy, Gary R; Touzet, Nicolas; Fleming, Gerard T A; Raine, Robin

2015-07-01

The toxic microalgal species Prymnesium parvum and Prymnesium polylepis are responsible for numerous fish kills causing economic stress on the aquaculture industry and, through the consumption of contaminated shellfish, can potentially impact on human health. Monitoring of toxic phytoplankton is traditionally carried out by light microscopy. However, molecular methods of identification and quantification are becoming more common place. This study documents the optimisation of the novel Microarrays for the Detection of Toxic Algae (MIDTAL) microarray from its initial stages to the final commercial version now available from Microbia Environnement (France). Existing oligonucleotide probes used in whole-cell fluorescent in situ hybridisation (FISH) for Prymnesium species from higher group probes to species-level probes were adapted and tested on the first-generation microarray. The combination and interaction of numerous other probes specific for a whole range of phytoplankton taxa also spotted on the chip surface caused high cross reactivity, resulting in false-positive results on the microarray. The probe sequences were extended for the subsequent second-generation microarray, and further adaptations of the hybridisation protocol and incubation temperatures significantly reduced false-positive readings from the first to the second-generation chip, thereby increasing the specificity of the MIDTAL microarray. Additional refinement of the subsequent third-generation microarray protocols with the addition of a poly-T amino linker to the 5' end of each probe further enhanced the microarray performance but also highlighted the importance of optimising RNA labelling efficiency when testing with natural seawater samples from Killary Harbour, Ireland.

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies.

PubMed

Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

2006-09-20

High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option.GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike.

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies

PubMed Central

Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

2006-01-01

Background High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option. GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. Results MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. Conclusion MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike. PMID:16987406

Microarray-integrated optoelectrofluidic immunoassay system

PubMed Central

Han, Dongsik

2016-01-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection. PMID:27190571

Microarray-integrated optoelectrofluidic immunoassay system.

PubMed

Han, Dongsik; Park, Je-Kyun

2016-05-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection.

A highly efficient multi-core algorithm for clustering extremely large datasets

PubMed Central

2010-01-01

Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer. Results We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization. Conclusions Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer. PMID:20370922

Microarray platform for omics analysis

NASA Astrophysics Data System (ADS)

Mecklenburg, Michael; Xie, Bin

2001-09-01

Microarray technology has revolutionized genetic analysis. However, limitations in genome analysis has lead to renewed interest in establishing 'omic' strategies. As we enter the post-genomic era, new microarray technologies are needed to address these new classes of 'omic' targets, such as proteins, as well as lipids and carbohydrates. We have developed a microarray platform that combines self- assembling monolayers with the biotin-streptavidin system to provide a robust, versatile immobilization scheme. A hydrophobic film is patterned on the surface creating an array of tension wells that eliminates evaporation effects thereby reducing the shear stress to which biomolecules are exposed to during immobilization. The streptavidin linker layer makes it possible to adapt and/or develop microarray based assays using virtually any class of biomolecules including: carbohydrates, peptides, antibodies, receptors, as well as them ore traditional DNA based arrays. Our microarray technology is designed to furnish seamless compatibility across the various 'omic' platforms by providing a common blueprint for fabricating and analyzing arrays. The prototype microarray uses a microscope slide footprint patterned with 2 by 96 flat wells. Data on the microarray platform will be presented.

Measuring O-GlcNAc cleavage by OGA and cell lysates on a peptide microarray.

PubMed

Sharif, Suhela; Shi, Jie; Bourakba, Mostafa; Ruijtenbeek, Rob; Pieters, Roland J

2017-09-01

O-GlcNAcylation is a post-translational modification resulting from the addition of an N-acetylglucosamine moiety to the hydroxyl groups of serine and threonine residues of nuclear and cytoplasmic proteins. In addition, O-GlcNAcylated proteins can be phosphorylated, which suggests the possibility for crosstalk between O-GlcNAcylation and phosphorylation. Dysregulation of O-GlcNAcylation affects cell signaling, transcriptional regulation, cell cycle control and can e.g. lead to tumorigenesis and tumor metastasis. There is a strong demand for efficient analytical techniques to better detect and investigate this abundant modification and its role in cancer. Herein we demonstrated the utility of an O-GlcNAcylated peptide array to examine O-GlcNAcase (OGA) activity and substrate specificity of both purified protein as well cell lysates of different cancer cell lines. Using this microarray, we clearly observed OGA activity and also inhibition thereof by OGA inhibitor thiamet G. Interestingly, different levels of OGA activity were observed of lysates derived from different cancer cell lines. This suggests that the tool may be useful in cancer research and biomarker development. Copyright © 2017 Elsevier Inc. All rights reserved.

The genome-wide expression profile of Curcuma longa-treated cisplatin-stimulated HEK293 cells

PubMed Central

Sohn, Sung-Hwa; Ko, Eunjung; Chung, Hwan-Suck; Lee, Eun-Young; Kim, Sung-Hoon; Shin, Minkyu; Hong, Moochang; Bae, Hyunsu

2010-01-01

AIM The rhizome of turmeric, Curcuma longa (CL), is a herbal medicine used in many traditional prescriptions. It has previously been shown that CL treatment showed greater than 47% recovery from cisplatin-induced cell damage in human kidney HEK 293 cells. This study was conducted to evaluate the recovery mechanisms of CL that occur during cisplatin induced nephrotoxicity by examining the genome wide mRNA expression profiles of HEK 293 -cells. METHOD Recovery mechanisms of CL that occur during cisplatin-induced nephrotoxicity were determined by microarray, real-time PCR, immunofluorescent confocal microscopy and Western blot analysis. RESULTS The results of microarray analysis and real-time PCR revealed that NFκB pathway-related genes and apoptosis-related genes were down-regulated in CL-treated HEK 293 cells. In addition, immunofluorescent confocal microscopy and Western blot analysis revealed that NFκB p65 nuclear translocation was inhibited in CL-treated HEK 293 cells. Therefore, the mechanism responsible for the effects of CL on HEK 293 cells is closely associated with regulation of the NFκB pathway. CONCLUSION CL possesses novel therapeutic agents that can be used for the prevention or treatment of cisplatin-induced renal disorders. PMID:20840446

Flowing gas, non-nuclear experiments on the gas core reactor

NASA Technical Reports Server (NTRS)

Kunze, J. F.; Suckling, D. H.; Copper, C. G.

1972-01-01

Flow tests were conducted on models of the gas core (cavity) reactor. Variations in cavity wall and injection configurations were aimed at establishing flow patterns that give a maximum of the nuclear criticality eigenvalue. Correlation with the nuclear effect was made using multigroup diffusion theory normalized by previous benchmark critical experiments. Air was used to simulate the hydrogen propellant in the flow tests, and smoked air, argon, or freon to simulate the central nuclear fuel gas. All tests were run in the down-firing direction so that gravitational effects simulated the acceleration effect of a rocket. Results show that acceptable flow patterns with high volume fraction for the simulated nuclear fuel gas and high flow rate ratios of propellant to fuel can be obtained. Using a point injector for the fuel, good flow patterns are obtained by directing the outer gas at high velocity along the cavity wall, using louvered or oblique-angle-honeycomb injection schemes.

Using the Time-Correlated Induced Fission Method to Simultaneously Measure the 235U Content and the Burnable Poison Content in LWR Fuel Assemblies

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

Root, M. A.; Menlove, H. O.; Lanza, R. C.

The uranium neutron coincidence collar uses thermal neutron interrogation to verify the 235U mass in low-enriched uranium (LEU) fuel assemblies in fuel fabrication facilities. Burnable poisons are commonly added to nuclear fuel to increase the lifetime of the fuel. The high thermal neutron absorption by these poisons reduces the active neutron signal produced by the fuel. Burnable poison correction factors or fast-mode runs with Cd liners can help compensate for this effect, but the correction factors rely on operator declarations of burnable poison content, and fast-mode runs are time-consuming. Finally, this paper describes a new analysis method to measure themore » 235U mass and burnable poison content in LEU nuclear fuel simultaneously in a timely manner, without requiring additional hardware.« less

Using the Time-Correlated Induced Fission Method to Simultaneously Measure the 235U Content and the Burnable Poison Content in LWR Fuel Assemblies

DOE PAGES

Root, M. A.; Menlove, H. O.; Lanza, R. C.; ...

2018-03-21

The uranium neutron coincidence collar uses thermal neutron interrogation to verify the 235U mass in low-enriched uranium (LEU) fuel assemblies in fuel fabrication facilities. Burnable poisons are commonly added to nuclear fuel to increase the lifetime of the fuel. The high thermal neutron absorption by these poisons reduces the active neutron signal produced by the fuel. Burnable poison correction factors or fast-mode runs with Cd liners can help compensate for this effect, but the correction factors rely on operator declarations of burnable poison content, and fast-mode runs are time-consuming. Finally, this paper describes a new analysis method to measure themore » 235U mass and burnable poison content in LEU nuclear fuel simultaneously in a timely manner, without requiring additional hardware.« less

Integration of Dakota into the NEAMS Workbench

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

Swiler, Laura Painton; Lefebvre, Robert A.; Langley, Brandon R.

2017-07-01

This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on integrating Dakota into the NEAMS Workbench. The NEAMS Workbench, developed at Oak Ridge National Laboratory, is a new software framework that provides a graphical user interface, input file creation, parsing, validation, job execution, workflow management, and output processing for a variety of nuclear codes. Dakota is a tool developed at Sandia National Laboratories that provides a suite of uncertainty quantification and optimization algorithms. Providing Dakota within the NEAMS Workbench allows users of nuclear simulation codes to perform uncertainty and optimization studies on their nuclear codes frommore » within a common, integrated environment. Details of the integration and parsing are provided, along with an example of Dakota running a sampling study on the fuels performance code, BISON, from within the NEAMS Workbench.« less

NUREBASE: database of nuclear hormone receptors.

PubMed

Duarte, Jorge; Perrière, Guy; Laudet, Vincent; Robinson-Rechavi, Marc

2002-01-01

Nuclear hormone receptors are an abundant class of ligand activated transcriptional regulators, found in varying numbers in all animals. Based on our experience of managing the official nomenclature of nuclear receptors, we have developed NUREBASE, a database containing protein and DNA sequences, reviewed protein alignments and phylogenies, taxonomy and annotations for all nuclear receptors. The reviewed NUREBASE is completed by NUREBASE_DAILY, automatically updated every 24 h. Both databases are organized under a client/server architecture, with a client written in Java which runs on any platform. This client, named FamFetch, integrates a graphical interface allowing selection of families, and manipulation of phylogenies and alignments. NUREBASE sequence data is also accessible through a World Wide Web server, allowing complex queries. All information on accessing and installing NUREBASE may be found at http://www.ens-lyon.fr/LBMC/laudet/nurebase.html.

MHSS: a material handling system simulator

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

Pomernacki, L.; Hollstien, R.B.

1976-04-07

A Material Handling System Simulator (MHSS) program is described that provides specialized functional blocks for modeling and simulation of nuclear material handling systems. Models of nuclear fuel fabrication plants may be built using functional blocks that simulate material receiving, storage, transport, inventory, processing, and shipping operations as well as the control and reporting tasks of operators or on-line computers. Blocks are also provided that allow the user to observe and gather statistical information on the dynamic behavior of simulated plants over single or replicated runs. Although it is currently being developed for the nuclear materials handling application, MHSS can bemore » adapted to other industries in which material accountability is important. In this paper, emphasis is on the simulation methodology of the MHSS program with application to the nuclear material safeguards problem. (auth)« less

Living Cell Microarrays: An Overview of Concepts

PubMed Central

Jonczyk, Rebecca; Kurth, Tracy; Lavrentieva, Antonina; Walter, Johanna-Gabriela; Scheper, Thomas; Stahl, Frank

2016-01-01

Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays. PMID:27600077

Interim report on updated microarray probes for the LLNL Burkholderia pseudomallei SNP array

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

Gardner, S; Jaing, C

2012-03-27

The overall goal of this project is to forensically characterize 100 unknown Burkholderia isolates in the US-Australia collaboration. We will identify genome-wide single nucleotide polymorphisms (SNPs) from B. pseudomallei and near neighbor species including B. mallei, B. thailandensis and B. oklahomensis. We will design microarray probes to detect these SNP markers and analyze 100 Burkholderia genomic DNAs extracted from environmental, clinical and near neighbor isolates from Australian collaborators on the Burkholderia SNP microarray. We will analyze the microarray genotyping results to characterize the genetic diversity of these new isolates and triage the samples for whole genome sequencing. In this interimmore » report, we described the SNP analysis and the microarray probe design for the Burkholderia SNP microarray.« less

Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.

PubMed

Saberkari, Hamidreza; Bahrami, Sheyda; Shamsi, Mousa; Amoshahy, Mohammad Javad; Ghavifekr, Habib Badri; Sedaaghi, Mohammad Hossein

2015-01-01

DNA microarray is a powerful approach to study simultaneously, the expression of 1000 of genes in a single experiment. The average value of the fluorescent intensity could be calculated in a microarray experiment. The calculated intensity values are very close in amount to the levels of expression of a particular gene. However, determining the appropriate position of every spot in microarray images is a main challenge, which leads to the accurate classification of normal and abnormal (cancer) cells. In this paper, first a preprocessing approach is performed to eliminate the noise and artifacts available in microarray cells using the nonlinear anisotropic diffusion filtering method. Then, the coordinate center of each spot is positioned utilizing the mathematical morphology operations. Finally, the position of each spot is exactly determined through applying a novel hybrid model based on the principle component analysis and the spatial fuzzy c-means clustering (SFCM) algorithm. Using a Gaussian kernel in SFCM algorithm will lead to improving the quality in complementary DNA microarray segmentation. The performance of the proposed algorithm has been evaluated on the real microarray images, which is available in Stanford Microarray Databases. Results illustrate that the accuracy of microarray cells segmentation in the proposed algorithm reaches to 100% and 98% for noiseless/noisy cells, respectively.

The Glycan Microarray Story from Construction to Applications.

PubMed

Hyun, Ji Young; Pai, Jaeyoung; Shin, Injae

2017-04-18

Not only are glycan-mediated binding processes in cells and organisms essential for a wide range of physiological processes, but they are also implicated in various pathological processes. As a result, elucidation of glycan-associated biomolecular interactions and their consequences is of great importance in basic biological research and biomedical applications. In 2002, we and others were the first to utilize glycan microarrays in efforts aimed at the rapid analysis of glycan-associated recognition events. Because they contain a number of glycans immobilized in a dense and orderly manner on a solid surface, glycan microarrays enable multiple parallel analyses of glycan-protein binding events while utilizing only small amounts of glycan samples. Therefore, this microarray technology has become a leading edge tool in studies aimed at elucidating roles played by glycans and glycan binding proteins in biological systems. In this Account, we summarize our efforts on the construction of glycan microarrays and their applications in studies of glycan-associated interactions. Immobilization strategies of functionalized and unmodified glycans on derivatized glass surfaces are described. Although others have developed immobilization techniques, our efforts have focused on improving the efficiencies and operational simplicity of microarray construction. The microarray-based technology has been most extensively used for rapid analysis of the glycan binding properties of proteins. In addition, glycan microarrays have been employed to determine glycan-protein interactions quantitatively, detect pathogens, and rapidly assess substrate specificities of carbohydrate-processing enzymes. More recently, the microarrays have been employed to identify functional glycans that elicit cell surface lectin-mediated cellular responses. Owing to these efforts, it is now possible to use glycan microarrays to expand the understanding of roles played by glycans and glycan binding proteins in biological systems.

Parallelization and automatic data distribution for nuclear reactor simulations

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

Liebrock, L.M.

1997-07-01

Detailed attempts at realistic nuclear reactor simulations currently take many times real time to execute on high performance workstations. Even the fastest sequential machine can not run these simulations fast enough to ensure that the best corrective measure is used during a nuclear accident to prevent a minor malfunction from becoming a major catastrophe. Since sequential computers have nearly reached the speed of light barrier, these simulations will have to be run in parallel to make significant improvements in speed. In physical reactor plants, parallelism abounds. Fluids flow, controls change, and reactions occur in parallel with only adjacent components directlymore » affecting each other. These do not occur in the sequentialized manner, with global instantaneous effects, that is often used in simulators. Development of parallel algorithms that more closely approximate the real-world operation of a reactor may, in addition to speeding up the simulations, actually improve the accuracy and reliability of the predictions generated. Three types of parallel architecture (shared memory machines, distributed memory multicomputers, and distributed networks) are briefly reviewed as targets for parallelization of nuclear reactor simulation. Various parallelization models (loop-based model, shared memory model, functional model, data parallel model, and a combined functional and data parallel model) are discussed along with their advantages and disadvantages for nuclear reactor simulation. A variety of tools are introduced for each of the models. Emphasis is placed on the data parallel model as the primary focus for two-phase flow simulation. Tools to support data parallel programming for multiple component applications and special parallelization considerations are also discussed.« less

A gene expression biomarker accurately predicts estrogen ...

EPA Pesticide Factsheets

The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1 screening tests. The ToxCast program currently includes 18 HTS in vitro assays that evaluate the ability of chemicals to modulate estrogen receptor α (ERα), an important endocrine target. We propose microarray-based gene expression profiling as a complementary approach to predict ERα modulation and have developed computational methods to identify ERα modulators in an existing database of whole-genome microarray data. The ERα biomarker consisted of 46 ERα-regulated genes with consistent expression patterns across 7 known ER agonists and 3 known ER antagonists. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments in MCF-7 cells. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% or 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) OECD ER reference chemicals including “very weak” agonists and replicated predictions based on 18 in vitro ER-associated HTS assays. For 114 chemicals present in both the HTS data and the MCF-7 c

Results and Outlook of The Aluminum Capture Experiment (AlCap)

NASA Astrophysics Data System (ADS)

Quirk, John R.; Miller, James; ALCap Collaboration Collaboration

2016-03-01

Observation of neutrinoless muon-to-electron conversion in the presence of a nucleus would be unambiguous evidence of physics Beyond the Standard Model. Two experiments, COMET at J-PARC and Mu2e at Fermilab, will search for this process in the coming decade. Barring discovery, these experiments will provide upper-limits on this branching ratio up to 10,000 times better than previously published. COMET/Mu2e developed a joint venture, the AlCap Experiment, to measure particle emission spectra from muonic interactions in a number of materials. As a major source of background hits in COMET/Mu2e detectors, AlCap sought to measure the charged particle and neutron spectra following nuclear capture on the candidate target materials aluminum and titanium. Additionally, COMET/Mu2e are exploring normalization schemes via AlCap's measurement of the photon spectra following both atomic and nuclear capture. Over the course of 2013 and 2015, AlCap performed three runs at the Paul Scherrer Institut in Switzerland. The first acquired preliminary data for all spectra, the second run collected only neutron and photon data, and the third primarily charged particle data. Preliminary analyses of the first two runs, already impactful for COMET/Mu2e, is presented along with a summary of the third.

Proposal for grid computing for nuclear applications

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

Idris, Faridah Mohamad; Ismail, Saaidi; Haris, Mohd Fauzi B.

2014-02-12

The use of computer clusters for computational sciences including computational physics is vital as it provides computing power to crunch big numbers at a faster rate. In compute intensive applications that requires high resolution such as Monte Carlo simulation, the use of computer clusters in a grid form that supplies computational power to any nodes within the grid that needs computing power, has now become a necessity. In this paper, we described how the clusters running on a specific application could use resources within the grid, to run the applications to speed up the computing process.

S100a8/a9 released by CD11b+Gr1+ neutrophils activates cardiac fibroblasts to initiate angiotensin II-Induced cardiac inflammation and injury.

PubMed

Wu, Yina; Li, Yulin; Zhang, Congcong; A, Xi; Wang, Yueli; Cui, Wei; Li, Huihua; Du, Jie

2014-06-01

Angiotensin II induces cardiovascular injury, in part, by activating inflammatory response; however, the initial factors that trigger the inflammatory cascade remain unclear. Microarray analysis of cardiac tissue exposed to systemic angiotensin II infusion revealed that extracellular heterodimeric proteins S100a8/a9 were highly upregulated. The increase in S100a8/a9 mRNA of CD11b(+)Gr1(+) neutrophils isolated from both the peripheral blood and heart was highest on day 1 of angiotensin II infusion and decreased to baseline at day 7. Immunostaining showed that S100a8/a9 was primarily present in infiltrating CD11b(+)Gr1(+) neutrophils in the heart. The receptor for advanced glycation end products, an S100a8/a9 receptor, was expressed in cardiac fibroblasts (CFs). Microarray analysis and Bio-Plex protein array showed that treatment of CFs with recombinant S100a8/a9 activated multiple chemokine and cytokines released. Luciferase reporter assay indicated S100a8/a9-activated nuclear factor-κ B pathway in CFs. Consequently, recombinant S100a8/a9-treated CFs promoted migration of monocytes and CFs, whereas neutralizing S100a9 antibody blocked S100a9 or receptor for advanced glycation end products-suppressed cellular migration. Finally, administration of a neutralizing S100a9 antibody prevented angiotensin II infusion-induced nuclear factor-κ B activation, inflammatory cell infiltration, cytokine production, subsequent perivascular and interstitial fibrosis, and hypertrophy in heart. Our findings identify neutrophil-produced S100a8/a9 as an initial proinflammatory factor needed to trigger inflammation and cardiac injury during acute hypertension.

A Platform for Combined DNA and Protein Microarrays Based on Total Internal Reflection Fluorescence

PubMed Central

Asanov, Alexander; Zepeda, Angélica; Vaca, Luis

2012-01-01

We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax. PMID:22438738

Thermodynamically optimal whole-genome tiling microarray design and validation.

PubMed

Cho, Hyejin; Chou, Hui-Hsien

2016-06-13

Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

EPA Science Inventory

DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

GRIZZLY

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

2012-12-17

Grizzly is a simulation tool for assessing the effects of age-related degradation on systems, structures, and components of nuclear power plants. Grizzly is built on the MOOSE framework, and uses a Jacobian-free Newton Krylov method to obtain solutions to tightly coupled thermo-mechanical simulations. Grizzly runs on a wide range of hardware, from a single processor to massively parallel machines.

Polysaccharide Microarray Technology for the Detection of Burkholderia Pseudomallei and Burkholderia Mallei Antibodies

DTIC Science & Technology

2006-04-27

polysaccharide microarray platform was prepared by immobilizing Burkholderia pseudomallei and Burkholderia mallei polysaccharides . This... polysaccharide array was tested with success for detecting B. pseudomallei and B. mallei serum (human and animal) antibodies. The advantages of this microarray... Polysaccharide microarrays; Burkholderia pseudomallei; Burkholderia mallei; Glanders; Melioidosis1. Introduction There has been a great deal of emphasis on the

QRAP: A numerical code for projected (Q)uasiparticle (RA)ndom (P)hase approximation

NASA Astrophysics Data System (ADS)

Samana, A. R.; Krmpotić, F.; Bertulani, C. A.

2010-06-01

A computer code for quasiparticle random phase approximation - QRPA and projected quasiparticle random phase approximation - PQRPA models of nuclear structure is explained in details. The residual interaction is approximated by a simple δ-force. An important application of the code consists in evaluating nuclear matrix elements involved in neutrino-nucleus reactions. As an example, cross sections for 56Fe and 12C are calculated and the code output is explained. The application to other nuclei and the description of other nuclear and weak decay processes are also discussed. Program summaryTitle of program: QRAP ( Quasiparticle RAndom Phase approximation) Computers: The code has been created on a PC, but also runs on UNIX or LINUX machines Operating systems: WINDOWS or UNIX Program language used: Fortran-77 Memory required to execute with typical data: 16 Mbytes of RAM memory and 2 MB of hard disk space No. of lines in distributed program, including test data, etc.: ˜ 8000 No. of bytes in distributed program, including test data, etc.: ˜ 256 kB Distribution format: tar.gz Nature of physical problem: The program calculates neutrino- and antineutrino-nucleus cross sections as a function of the incident neutrino energy, and muon capture rates, using the QRPA or PQRPA as nuclear structure models. Method of solution: The QRPA, or PQRPA, equations are solved in a self-consistent way for even-even nuclei. The nuclear matrix elements for the neutrino-nucleus interaction are treated as the beta inverse reaction of odd-odd nuclei as function of the transfer momentum. Typical running time: ≈ 5 min on a 3 GHz processor for Data set 1.

Recent progress in making protein microarray through BioLP

NASA Astrophysics Data System (ADS)

Yang, Rusong; Wei, Lian; Feng, Ying; Li, Xiujian; Zhou, Quan

2017-02-01

Biological laser printing (BioLP) is a promising biomaterial printing technique. It has the advantage of high resolution, high bioactivity, high printing frequency and small transported liquid amount. In this paper, a set of BioLP device is design and made, and protein microarrays are printed by this device. It's found that both laser intensity and fluid layer thickness have an influence on the microarrays acquired. Besides, two kinds of the fluid layer coating methods are compared, and the results show that blade coating method is better than well-coating method in BioLP. A microarray of 0.76pL protein microarray and a "NUDT" patterned microarray are printed to testify the printing ability of BioLP.

Microarrays in brain research: the good, the bad and the ugly.

PubMed

Mirnics, K

2001-06-01

Making sense of microarray data is a complex process, in which the interpretation of findings will depend on the overall experimental design and judgement of the investigator performing the analysis. As a result, differences in tissue harvesting, microarray types, sample labelling and data analysis procedures make post hoc sharing of microarray data a great challenge. To ensure rapid and meaningful data exchange, we need to create some order out of the existing chaos. In these ground-breaking microarray standardization and data sharing efforts, NIH agencies should take a leading role

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

PubMed Central

Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Relative impact of key sources of systematic noise in Affymetrix and Illumina gene-expression microarray experiments.

PubMed

Kitchen, Robert R; Sabine, Vicky S; Simen, Arthur A; Dixon, J Michael; Bartlett, John M S; Sims, Andrew H

2011-12-01

Systematic processing noise, which includes batch effects, is very common in microarray experiments but is often ignored despite its potential to confound or compromise experimental results. Compromised results are most likely when re-analysing or integrating datasets from public repositories due to the different conditions under which each dataset is generated. To better understand the relative noise-contributions of various factors in experimental-design, we assessed several Illumina and Affymetrix datasets for technical variation between replicate hybridisations of Universal Human Reference (UHRR) and individual or pooled breast-tumour RNA. A varying degree of systematic noise was observed in each of the datasets, however in all cases the relative amount of variation between standard control RNA replicates was found to be greatest at earlier points in the sample-preparation workflow. For example, 40.6% of the total variation in reported expressions were attributed to replicate extractions, compared to 13.9% due to amplification/labelling and 10.8% between replicate hybridisations. Deliberate probe-wise batch-correction methods were effective in reducing the magnitude of this variation, although the level of improvement was dependent on the sources of noise included in the model. Systematic noise introduced at the chip, run, and experiment levels of a combined Illumina dataset were found to be highly dependent upon the experimental design. Both UHRR and pools of RNA, which were derived from the samples of interest, modelled technical variation well although the pools were significantly better correlated (4% average improvement) and better emulated the effects of systematic noise, over all probes, than the UHRRs. The effect of this noise was not uniform over all probes, with low GC-content probes found to be more vulnerable to batch variation than probes with a higher GC-content. The magnitude of systematic processing noise in a microarray experiment is variable across probes and experiments, however it is generally the case that procedures earlier in the sample-preparation workflow are liable to introduce the most noise. Careful experimental design is important to protect against noise, detailed meta-data should always be provided, and diagnostic procedures should be routinely performed prior to downstream analyses for the detection of bias in microarray studies.

Relative impact of key sources of systematic noise in Affymetrix and Illumina gene-expression microarray experiments

PubMed Central

2011-01-01

Background Systematic processing noise, which includes batch effects, is very common in microarray experiments but is often ignored despite its potential to confound or compromise experimental results. Compromised results are most likely when re-analysing or integrating datasets from public repositories due to the different conditions under which each dataset is generated. To better understand the relative noise-contributions of various factors in experimental-design, we assessed several Illumina and Affymetrix datasets for technical variation between replicate hybridisations of Universal Human Reference (UHRR) and individual or pooled breast-tumour RNA. Results A varying degree of systematic noise was observed in each of the datasets, however in all cases the relative amount of variation between standard control RNA replicates was found to be greatest at earlier points in the sample-preparation workflow. For example, 40.6% of the total variation in reported expressions were attributed to replicate extractions, compared to 13.9% due to amplification/labelling and 10.8% between replicate hybridisations. Deliberate probe-wise batch-correction methods were effective in reducing the magnitude of this variation, although the level of improvement was dependent on the sources of noise included in the model. Systematic noise introduced at the chip, run, and experiment levels of a combined Illumina dataset were found to be highly dependant upon the experimental design. Both UHRR and pools of RNA, which were derived from the samples of interest, modelled technical variation well although the pools were significantly better correlated (4% average improvement) and better emulated the effects of systematic noise, over all probes, than the UHRRs. The effect of this noise was not uniform over all probes, with low GC-content probes found to be more vulnerable to batch variation than probes with a higher GC-content. Conclusions The magnitude of systematic processing noise in a microarray experiment is variable across probes and experiments, however it is generally the case that procedures earlier in the sample-preparation workflow are liable to introduce the most noise. Careful experimental design is important to protect against noise, detailed meta-data should always be provided, and diagnostic procedures should be routinely performed prior to downstream analyses for the detection of bias in microarray studies. PMID:22133085

Nuclear Cryogenic Propulsion Stage (NCPS) Fuel Element Testing in the Nuclear Thermal Rocket Element Environmental Simulator (NTREES)

NASA Technical Reports Server (NTRS)

Emrich, William J., Jr.

2017-01-01

To satisfy the Nuclear Cryogenic Propulsion Stage (NCPS) testing milestone, a graphite composite fuel element using a uranium simulant was received from the Oakridge National Lab and tested in the Nuclear Thermal Rocket Element Environmental Simulator (NTREES) at various operating conditions. The nominal operating conditions required to satisfy the milestone consisted of running the fuel element for a few minutes at a temperature of at least 2000 K with flowing hydrogen. This milestone test was successfully accomplished without incident.

An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

PubMed Central

2012-01-01

Background The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. Results We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. Conclusion T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially. PMID:22276688

Multi-canister overpack project -- verification and validation, MCNP 4A

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

Goldmann, L.H.

This supporting document contains the software verification and validation (V and V) package used for Phase 2 design of the Spent Nuclear Fuel Multi-Canister Overpack. V and V packages for both ANSYS and MCNP are included. Description of Verification Run(s): This software requires that it be compiled specifically for the machine it is to be used on. Therefore to facilitate ease in the verification process the software automatically runs 25 sample problems to ensure proper installation and compilation. Once the runs are completed the software checks for verification by performing a file comparison on the new output file and themore » old output file. Any differences between any of the files will cause a verification error. Due to the manner in which the verification is completed a verification error does not necessarily indicate a problem. This indicates that a closer look at the output files is needed to determine the cause of the error.« less

Up-Regulation of Follistatin-Like 1 By the Androgen Receptor and Melanoma Antigen-A11 in Prostate Cancer.

PubMed

Su, Shifeng; Parris, Amanda B; Grossman, Gail; Mohler, James L; Wang, Zengjun; Wilson, Elizabeth M

2017-04-01

High affinity androgen binding to the androgen receptor (AR) activates genes required for male sex differentiation and promotes the development and progression of prostate cancer. Human AR transcriptional activity involves interactions with coregulatory proteins that include primate-specific melanoma antigen-A11 (MAGE-A11), a coactivator that increases AR transcriptional activity during prostate cancer progression to castration-resistant/recurrent prostate cancer (CRPC). Microarray analysis and quantitative RT-PCR were performed to identify androgen-regulated MAGE-A11-dependent genes in LAPC-4 prostate cancer cells after lentivirus shRNA knockdown of MAGE-A11. Chromatin immunoprecipitation was used to assess androgen-dependent AR recruitment, and immunocytochemistry to localize an androgen-dependent protein in prostate cancer cells and tissue and in the CWR22 human prostate cancer xenograft. Microarray analysis of androgen-treated LAPC-4 prostate cancer cells indicated follistatin-like 1 (FSTL1) is up-regulated by MAGE-A11. Androgen-dependent up-regulation of FSTL1 was inhibited in LAPC-4 cells by lentivirus shRNA knockdown of AR or MAGE-A11. Chromatin immunoprecipitation demonstrated AR recruitment to intron 10 of the FSTL1 gene that contains a classical consensus androgen response element. Increased levels of FSTL1 protein in LAPC-4 cells correlated with higher levels of MAGE-A11 relative to other prostate cancer cells. FSTL1 mRNA levels increased in CRPC and castration-recurrent CWR22 xenografts in association with predominantly nuclear FSTL1. Increased nuclear localization of FSTL1 in prostate cancer was suggested by predominantly cytoplasmic FSTL1 in benign prostate epithelial cells and predominantly nuclear FSTL1 in epithelial cells in CRPC tissue and the castration-recurrent CWR22 xenograft. AR expression studies showed nuclear colocalization of AR and endogenous FSTL1 in response to androgen. AR and MAGE-A11 cooperate in the up-regulation of FSTL1 to promote growth and progression of CRPC. Prostate 77:505-516, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Lorentz-violating contributions to the nuclear Schiff moment and nuclear EDM

NASA Astrophysics Data System (ADS)

Araujo, Jonas B.; Casana, Rodolfo; Ferreira, Manoel M.

2018-03-01

In the context of an atom endowed with nuclear electric dipole moments (EDM), we consider the effects on the Schiff moment of C P T -even Lorentz-violating (LV) terms that modify the Coulomb potential. First, we study the modifications on the Schiff moment when the nucleus interacts with the electronic cloud by means of a Coulomb potential altered only by the P -even LV components. Next, by supposing the existence of an additional intrinsic LV EDM generated by other LV sources, we assess the corrections to the Schiff moment when the interaction nucleus-electrons runs mediated by a Coulomb potential modified by both the P -odd and P -even LV components. We then use known estimates and EDM measurements to discuss upper bounds on the new Schiff moment components and the possibility of a nuclear EDM component ascribed to LV effects.

Strange Particles and Heavy Ion Physics

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

Bassalleck, Bernd; Fields, Douglas

This very long-running grant has supported many experiments in nuclear and particle physics by a group from the University of New Mexico. The gamut of these experiments runs from many aspects of Strangeness Nuclear Physics, to rare Kaon decays, to searches for exotic Hadrons such as Pentaquark or H-Dibaryon, and finally to Spin Physics within the PHENIX collaboration at RHIC. These experiments were performed at a number of laboratories worldwide: first and foremost at Brookhaven National Lab (BNL), but also at CERN, KEK, and most recently at J-PARC. In this Final Technical Report we summarize progress and achievements for thismore » award since our last Progress Report, i.e. for the period of fall 2013 until the award’s termination on November 30, 2015. The report consists of two parts, representing our two most recent experimental efforts, participation in the Nucleon Spin Physics program of the PHENIX experiment at RHIC, the Relativistic Heavy Ion Collider at BNL – Task 1, led by Douglas Fields; and participation in several Strangeness Nuclear Physics experiments at J-PARC, the Japan Proton Accelerator Research Center in Tokai-mura, Japan – Task 2, led by Bernd Bassalleck.« less

Liver phantom for quality control and training in nuclear medicine

NASA Astrophysics Data System (ADS)

Lima Ferreira, Fernanda Carla; Souza, Divanizia do Nascimento

2011-10-01

In nuclear medicine, liver scintigraphy aims to verify organ function based on the radionuclide concentration in the liver and bile flow and is also used to detect tumors. Therefore it is necessary to perform quality control tests in the gamma camera before running the exam to prevent false results. Quality control tests of the gamma camera should thus be performed before running the exam to prevent false results. Such tests generally use radioactive material inside phantoms for evaluation of gamma camera parameters in quality control procedures. Phantoms can also be useful for training doctors and technicians in nuclear medicine procedures. The phantom proposed here has artifacts that simulate nodules; it may take on different quantities, locations and sizes and it may also be mounted without the introduction of nodules. Thus, its images may show hot or cold nodules or no nodules. The phantom consists of acrylic plates hollowed out in the centre, with the geometry of an adult liver. Images for analyses of simulated liver scintigraphy were obtained with the detector device at 5 cm from the anterior surface of the phantom. These simulations showed that this object is suitable for quality control in nuclear medicine because it was possible to visualize artifacts larger than 7.9 mm using a 256×256 matrix and 1000 kcpm. The phantom constructed in this work will also be useful for training practitioners and technicians in order to prevent patients from repeat testing caused by error during examinations.

Alteration of synaptic activity-regulating genes underlying functional improvement by long-term exposure to an enriched environment in the adult brain.

PubMed

Lee, Min-Young; Yu, Ji Hea; Kim, Ji Yeon; Seo, Jung Hwa; Park, Eun Sook; Kim, Chul Hoon; Kim, Hyongbum; Cho, Sung-Rae

2013-01-01

Housing animals in an enriched environment (EE) enhances behavioral function. However, the mechanism underlying this EE-mediated functional improvement and the resultant changes in gene expression have yet to be elucidated. We attempted to investigate the underlying mechanisms associated with long-term exposure to an EE by evaluating gene expression patterns. We housed 6-week-old CD-1 (ICR) mice in standard cages or an EE comprising a running wheel, novel objects, and social interaction for 2 months. Motor and cognitive performances were evaluated using the rotarod test and passive avoidance test, and gene expression profile was investigated in the cerebral hemispheres using microarray and gene set enrichment analysis (GSEA). In behavioral assessment, an EE significantly enhanced rotarod performance and short-term working memory. Microarray analysis revealed that genes associated with neuronal activity were significantly altered by an EE. GSEA showed that genes involved in synaptic transmission and postsynaptic signal transduction were globally upregulated, whereas those associated with reuptake by presynaptic neurotransmitter transporters were downregulated. In particular, both microarray and GSEA demonstrated that EE exposure increased opioid signaling, acetylcholine release cycle, and postsynaptic neurotransmitter receptors but decreased Na+ / Cl- -dependent neurotransmitter transporters, including dopamine transporter Slc6a3 in the brain. Western blotting confirmed that SLC6A3, DARPP32 (PPP1R1B), and P2RY12 were largely altered in a region-specific manner. An EE enhanced motor and cognitive function through the alteration of synaptic activity-regulating genes, improving the efficient use of neurotransmitters and synaptic plasticity by the upregulation of genes associated with postsynaptic receptor activity and downregulation of presynaptic reuptake by neurotransmitter transporters.

Split-plot microarray experiments: issues of design, power and sample size.

PubMed

Tsai, Pi-Wen; Lee, Mei-Ling Ting

2005-01-01

This article focuses on microarray experiments with two or more factors in which treatment combinations of the factors corresponding to the samples paired together onto arrays are not completely random. A main effect of one (or more) factor(s) is confounded with arrays (the experimental blocks). This is called a split-plot microarray experiment. We utilise an analysis of variance (ANOVA) model to assess differentially expressed genes for between-array and within-array comparisons that are generic under a split-plot microarray experiment. Instead of standard t- or F-test statistics that rely on mean square errors of the ANOVA model, we use a robust method, referred to as 'a pooled percentile estimator', to identify genes that are differentially expressed across different treatment conditions. We illustrate the design and analysis of split-plot microarray experiments based on a case application described by Jin et al. A brief discussion of power and sample size for split-plot microarray experiments is also presented.

xQTL workbench: a scalable web environment for multi-level QTL analysis.

PubMed

Arends, Danny; van der Velde, K Joeri; Prins, Pjotr; Broman, Karl W; Möller, Steffen; Jansen, Ritsert C; Swertz, Morris A

2012-04-01

xQTL workbench is a scalable web platform for the mapping of quantitative trait loci (QTLs) at multiple levels: for example gene expression (eQTL), protein abundance (pQTL), metabolite abundance (mQTL) and phenotype (phQTL) data. Popular QTL mapping methods for model organism and human populations are accessible via the web user interface. Large calculations scale easily on to multi-core computers, clusters and Cloud. All data involved can be uploaded and queried online: markers, genotypes, microarrays, NGS, LC-MS, GC-MS, NMR, etc. When new data types come available, xQTL workbench is quickly customized using the Molgenis software generator. xQTL workbench runs on all common platforms, including Linux, Mac OS X and Windows. An online demo system, installation guide, tutorials, software and source code are available under the LGPL3 license from http://www.xqtl.org. m.a.swertz@rug.nl.

xQTL workbench: a scalable web environment for multi-level QTL analysis

PubMed Central

Arends, Danny; van der Velde, K. Joeri; Prins, Pjotr; Broman, Karl W.; Möller, Steffen; Jansen, Ritsert C.; Swertz, Morris A.

2012-01-01

Summary: xQTL workbench is a scalable web platform for the mapping of quantitative trait loci (QTLs) at multiple levels: for example gene expression (eQTL), protein abundance (pQTL), metabolite abundance (mQTL) and phenotype (phQTL) data. Popular QTL mapping methods for model organism and human populations are accessible via the web user interface. Large calculations scale easily on to multi-core computers, clusters and Cloud. All data involved can be uploaded and queried online: markers, genotypes, microarrays, NGS, LC-MS, GC-MS, NMR, etc. When new data types come available, xQTL workbench is quickly customized using the Molgenis software generator. Availability: xQTL workbench runs on all common platforms, including Linux, Mac OS X and Windows. An online demo system, installation guide, tutorials, software and source code are available under the LGPL3 license from http://www.xqtl.org. Contact: m.a.swertz@rug.nl PMID:22308096

Tumor Necrosis Factor-α Regulates Distinct Molecular Pathways and Gene Networks in Cultured Skeletal Muscle Cells

PubMed Central

Gupta, Sanjay K.; Dahiya, Saurabh; Lundy, Robert F.; Kumar, Ashok

2010-01-01

Background Skeletal muscle wasting is a debilitating consequence of large number of disease states and conditions. Tumor necrosis factor-α (TNF-α) is one of the most important muscle-wasting cytokine, elevated levels of which cause significant muscular abnormalities. However, the underpinning molecular mechanisms by which TNF-α causes skeletal muscle wasting are less well-understood. Methodology/Principal Findings We have used microarray, quantitative real-time PCR (QRT-PCR), Western blot, and bioinformatics tools to study the effects of TNF-α on various molecular pathways and gene networks in C2C12 cells (a mouse myoblastic cell line). Microarray analyses of C2C12 myotubes treated with TNF-α (10 ng/ml) for 18h showed differential expression of a number of genes involved in distinct molecular pathways. The genes involved in nuclear factor-kappa B (NF-kappaB) signaling, 26s proteasome pathway, Notch1 signaling, and chemokine networks are the most important ones affected by TNF-α. The expression of some of the genes in microarray dataset showed good correlation in independent QRT-PCR and Western blot assays. Analysis of TNF-treated myotubes showed that TNF-α augments the activity of both canonical and alternative NF-κB signaling pathways in myotubes. Bioinformatics analyses of microarray dataset revealed that TNF-α affects the activity of several important pathways including those involved in oxidative stress, hepatic fibrosis, mitochondrial dysfunction, cholesterol biosynthesis, and TGF-β signaling. Furthermore, TNF-α was found to affect the gene networks related to drug metabolism, cell cycle, cancer, neurological disease, organismal injury, and abnormalities in myotubes. Conclusions TNF-α regulates the expression of multiple genes involved in various toxic pathways which may be responsible for TNF-induced muscle loss in catabolic conditions. Our study suggests that TNF-α activates both canonical and alternative NF-κB signaling pathways in a time-dependent manner in skeletal muscle cells. The study provides novel insight into the mechanisms of action of TNF-α in skeletal muscle cells. PMID:20967264

New Features in the Computational Infrastructure for Nuclear Astrophysics

NASA Astrophysics Data System (ADS)

Smith, M. S.; Lingerfelt, E. J.; Scott, J. P.; Hix, W. R.; Nesaraja, C. D.; Koura, H.; Roberts, L. F.

2006-04-01

The Computational Infrastructure for Nuclear Astrophysics is a suite of computer codes online at nucastrodata.org that streamlines the incorporation of recent nuclear physics results into astrophysical simulations. The freely-available, cross- platform suite enables users to upload cross sections and s-factors, convert them into reaction rates, parameterize the rates, store the rates in customizable libraries, setup and run custom post-processing element synthesis calculations, and visualize the results. New features include the ability for users to comment on rates or libraries using an email-type interface, a nuclear mass model evaluator, enhanced techniques for rate parameterization, better treatment of rate inverses, and creation and exporting of custom animations of simulation results. We also have online animations of r- process, rp-process, and neutrino-p process element synthesis occurring in stellar explosions.

DNA Microarray-based Ecotoxicological Biomarker Discovery in a Small Fish Model Species

EPA Science Inventory

This paper addresses several issues critical to use of zebrafish oligonucleotide microarrays for computational toxicology research on endocrine disrupting chemicals using small fish models, and more generally, the use of microarrays in aquatic toxicology.

A perspective on microarrays: current applications, pitfalls, and potential uses

PubMed Central

Jaluria, Pratik; Konstantopoulos, Konstantinos; Betenbaugh, Michael; Shiloach, Joseph

2007-01-01

With advances in robotics, computational capabilities, and the fabrication of high quality glass slides coinciding with increased genomic information being available on public databases, microarray technology is increasingly being used in laboratories around the world. In fact, fields as varied as: toxicology, evolutionary biology, drug development and production, disease characterization, diagnostics development, cellular physiology and stress responses, and forensics have benefiting from its use. However, for many researchers not familiar with microarrays, current articles and reviews often address neither the fundamental principles behind the technology nor the proper designing of experiments. Although, microarray technology is relatively simple, conceptually, its practice does require careful planning and detailed understanding of the limitations inherently present. Without these considerations, it can be exceedingly difficult to ascertain valuable information from microarray data. Therefore, this text aims to outline key features in microarray technology, paying particular attention to current applications as outlined in recent publications, experimental design, statistical methods, and potential uses. Furthermore, this review is not meant to be comprehensive, but rather substantive; highlighting important concepts and detailing steps necessary to conduct and interpret microarray experiments. Collectively, the information included in this text will highlight the versatility of microarray technology and provide a glimpse of what the future may hold. PMID:17254338

Variance stabilization and normalization for one-color microarray data using a data-driven multiscale approach.

PubMed

Motakis, E S; Nason, G P; Fryzlewicz, P; Rutter, G A

2006-10-15

Many standard statistical techniques are effective on data that are normally distributed with constant variance. Microarray data typically violate these assumptions since they come from non-Gaussian distributions with a non-trivial mean-variance relationship. Several methods have been proposed that transform microarray data to stabilize variance and draw its distribution towards the Gaussian. Some methods, such as log or generalized log, rely on an underlying model for the data. Others, such as the spread-versus-level plot, do not. We propose an alternative data-driven multiscale approach, called the Data-Driven Haar-Fisz for microarrays (DDHFm) with replicates. DDHFm has the advantage of being 'distribution-free' in the sense that no parametric model for the underlying microarray data is required to be specified or estimated; hence, DDHFm can be applied very generally, not just to microarray data. DDHFm achieves very good variance stabilization of microarray data with replicates and produces transformed intensities that are approximately normally distributed. Simulation studies show that it performs better than other existing methods. Application of DDHFm to real one-color cDNA data validates these results. The R package of the Data-Driven Haar-Fisz transform (DDHFm) for microarrays is available in Bioconductor and CRAN.

Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

PubMed Central

Biyani, Manish; Ichiki, Takanori

2015-01-01

Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA)-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing) a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density), ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era. PMID:27600226

Signal amplification by rolling circle amplification on DNA microarrays

PubMed Central

Nallur, Girish; Luo, Chenghua; Fang, Linhua; Cooley, Stephanie; Dave, Varshal; Lambert, Jeremy; Kukanskis, Kari; Kingsmore, Stephen; Lasken, Roger; Schweitzer, Barry

2001-01-01

While microarrays hold considerable promise in large-scale biology on account of their massively parallel analytical nature, there is a need for compatible signal amplification procedures to increase sensitivity without loss of multiplexing. Rolling circle amplification (RCA) is a molecular amplification method with the unique property of product localization. This report describes the application of RCA signal amplification for multiplexed, direct detection and quantitation of nucleic acid targets on planar glass and gel-coated microarrays. As few as 150 molecules bound to the surface of microarrays can be detected using RCA. Because of the linear kinetics of RCA, nucleic acid target molecules may be measured with a dynamic range of four orders of magnitude. Consequently, RCA is a promising technology for the direct measurement of nucleic acids on microarrays without the need for a potentially biasing preamplification step. PMID:11726701

NRF2-regulated metabolic gene signature as a prognostic biomarker in non-small cell lung cancer

PubMed Central

Namani, Akhileshwar; Cui, Qin Qin; Wu, Yihe; Wang, Hongyan; Wang, Xiu Jun; Tang, Xiuwen

2017-01-01

Mutations in Kelch-like ECH-associated protein 1 (KEAP1) cause the aberrant activation of nuclear factor erythroid-derived 2-like 2 (NRF2), which leads to oncogenesis and drug resistance in lung cancer cells. Our study was designed to identify the genes involved in lung cancer progression targeted by NRF2. A series of microarray experiments in normal and cancer cells, as well as in animal models, have revealed regulatory genes downstream of NRF2 that are involved in wide variety of pathways. Specifically, we carried out individual and combinatorial microarray analysis of KEAP1 overexpression and NRF2 siRNA-knockdown in a KEAP1 mutant-A549 non-small cell lung cancer (NSCLC) cell line. As a result, we identified a list of genes which were mainly involved in metabolic functions in NSCLC by using functional annotation analysis. In addition, we carried out in silico analysis to characterize the antioxidant responsive element sequences in the promoter regions of known and putative NRF2-regulated metabolic genes. We further identified an NRF2-regulated metabolic gene signature (NRMGS) by correlating the microarray data with lung adenocarcinoma RNA-Seq gene expression data from The Cancer Genome Atlas followed by qRT-PCR validation, and finally showed that higher expression of the signature conferred a poor prognosis in 8 independent NSCLC cohorts. Our findings provide novel prognostic biomarkers for NSCLC. PMID:29050246

Identification of differentially expressed genes and false discovery rate in microarray studies.

PubMed

Gusnanto, Arief; Calza, Stefano; Pawitan, Yudi

2007-04-01

To highlight the development in microarray data analysis for the identification of differentially expressed genes, particularly via control of false discovery rate. The emergence of high-throughput technology such as microarrays raises two fundamental statistical issues: multiplicity and sensitivity. We focus on the biological problem of identifying differentially expressed genes. First, multiplicity arises due to testing tens of thousands of hypotheses, rendering the standard P value meaningless. Second, known optimal single-test procedures such as the t-test perform poorly in the context of highly multiple tests. The standard approach of dealing with multiplicity is too conservative in the microarray context. The false discovery rate concept is fast becoming the key statistical assessment tool replacing the P value. We review the false discovery rate approach and argue that it is more sensible for microarray data. We also discuss some methods to take into account additional information from the microarrays to improve the false discovery rate. There is growing consensus on how to analyse microarray data using the false discovery rate framework in place of the classical P value. Further research is needed on the preprocessing of the raw data, such as the normalization step and filtering, and on finding the most sensitive test procedure.

Best practices for hybridization design in two-colour microarray analysis.

PubMed

Knapen, Dries; Vergauwen, Lucia; Laukens, Kris; Blust, Ronny

2009-07-01

Two-colour microarrays are a popular platform of choice in gene expression studies. Because two different samples are hybridized on a single microarray, and several microarrays are usually needed in a given experiment, there are many possible ways to combine samples on different microarrays. The actual combination employed is commonly referred to as the 'hybridization design'. Different types of hybridization designs have been developed, all aimed at optimizing the experimental setup for the detection of differentially expressed genes while coping with technical noise. Here, we first provide an overview of the different classes of hybridization designs, discussing their advantages and limitations, and then we illustrate the current trends in the use of different hybridization design types in contemporary research.

Strengthening safety compliance in nuclear power operations: a role-based approach.

PubMed

Martínez-Córcoles, Mario; Gracia, Francisco J; Tomás, Inés; Peiró, José M

2014-07-01

Safety compliance is of paramount importance in guaranteeing the safe running of nuclear power plants. However, it depends mostly on procedures that do not always involve the safest outcomes. This article introduces an empirical model based on the organizational role theory to analyze the influence of legitimate sources of expectations (procedures formalization and leadership) on workers' compliance behaviors. The sample was composed of 495 employees from two Spanish nuclear power plants. Structural equation analysis showed that, in spite of some problematic effects of proceduralization (such as role conflict and role ambiguity), procedure formalization along with an empowering leadership style lead to safety compliance by clarifying a worker's role in safety. Implications of these findings for safety research are outlined, as well as their practical implications. © 2014 Society for Risk Analysis.

Initial Genomics of the Human Nucleolus

PubMed Central

Németh, Attila; Conesa, Ana; Santoyo-Lopez, Javier; Medina, Ignacio; Montaner, David; Péterfia, Bálint; Solovei, Irina; Cremer, Thomas; Dopazo, Joaquin; Längst, Gernot

2010-01-01

We report for the first time the genomics of a nuclear compartment of the eukaryotic cell. 454 sequencing and microarray analysis revealed the pattern of nucleolus-associated chromatin domains (NADs) in the linear human genome and identified different gene families and certain satellite repeats as the major building blocks of NADs, which constitute about 4% of the genome. Bioinformatic evaluation showed that NAD–localized genes take part in specific biological processes, like the response to other organisms, odor perception, and tissue development. 3D FISH and immunofluorescence experiments illustrated the spatial distribution of NAD–specific chromatin within interphase nuclei and its alteration upon transcriptional changes. Altogether, our findings describe the nature of DNA sequences associated with the human nucleolus and provide insights into the function of the nucleolus in genome organization and establishment of nuclear architecture. PMID:20361057

Applications of Neutron Radiography for the Nuclear Power Industry

NASA Astrophysics Data System (ADS)

Craft, Aaron E.; Barton, John P.

The World Conference on Neutron Radiography (WCNR) and International Topical Meeting on Neutron Radiography (ITMNR) series have been running over 35 years. The most recent event, ITMNR-8, focused on industrial applications and was the first time this series was hosted in China. In China, more than twenty new nuclear power plants are under construction and plans have been announced to increase the nuclear capacity by a factor of three within fifteen years. There are additional prospects in many other nations. Neutron tests were vital during previous developments of materials and components for nuclear power applications, as reported in the WCNR and ITMNR conference series. For example a majority of the 140 papers in the Proceedings of the First WCNR are for the benefit of the nuclear power industry. Many of those techniques are being utilized and advanced to the present time. Neutron radiography of irradiated nuclear fuel provides more comprehensive information about the internal condition of irradiated nuclear fuel than any other non-destructive technique to date. Applications include examination of nuclear waste, nuclear fuels, cladding, control elements, and other critical components. In this paper, applications of neutron radiography techniques developed and applied internationally for the nuclear power industry since the earliest years are reviewed, and the question is asked whether neutron test techniques, in general, can be of value in development of the present and future generations of nuclear power plants world-wide.

Advantages of RNA-seq compared to RNA microarrays for transcriptome profiling of anterior cruciate ligament tears.

PubMed

Rai, Muhammad Farooq; Tycksen, Eric D; Sandell, Linda J; Brophy, Robert H

2018-01-01

Microarrays and RNA-seq are at the forefront of high throughput transcriptome analyses. Since these methodologies are based on different principles, there are concerns about the concordance of data between the two techniques. The concordance of RNA-seq and microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed in clinically derived ligament tissues. To demonstrate the concordance between RNA-seq and microarrays and to assess potential benefits of RNA-seq over microarrays, we assessed differences in transcript expression in anterior cruciate ligament (ACL) tissues based on time-from-injury. ACL remnants were collected from patients with an ACL tear at the time of ACL reconstruction. RNA prepared from torn ACL remnants was subjected to Agilent microarrays (N = 24) and RNA-seq (N = 8). The correlation of biological replicates in RNA-seq and microarrays data was similar (0.98 vs. 0.97), demonstrating that each platform has high internal reproducibility. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarrays values were moderate. The cross-platform concordance for differentially expressed transcripts or enriched pathways was linearly correlated (r = 0.64). RNA-Seq was superior in detecting low abundance transcripts and differentiating biologically critical isoforms. Additional independent validation of transcript expression was undertaken using microfluidic PCR for selected genes. PCR data showed 100% concordance (in expression pattern) with RNA-seq and microarrays data. These findings demonstrate that RNA-seq has advantages over microarrays for transcriptome profiling of ligament tissues when available and affordable. Furthermore, these findings are likely transferable to other musculoskeletal tissues where tissue collection is challenging and cells are in low abundance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:484-497, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Considerations of Alloy 617 Application in the Gen IV Nuclear Reactor Systems - Part I: Mechanical Property Challenges

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

Ren, Weiju

2010-01-01

Alloy 617 is currently considered as a leading candidate material for high temperature components in the Gen IV Nuclear Reactor Systems. Because of the unprecedented severe working conditions beyond its commercial service experience required by the Gen IV systems, the alloy faces various challenges in both mechanical and metallurgical properties. This paper, as Part I of the discussion, is focused on the challenges and issues in the mechanical properties of Alloy 617 for the intended nuclear application. Considerations are given in details in its mechanical property data scatter, low creep strength in the desired high temperature range, lack of longtermmore » creep curves, high loading rate dependency, and preponderant tertiary creep. Some research and development activities are suggested with discussions on their viability to satisfy the Gen IV Nuclear Reactor System needs in near future and in the long run.« less

The effect of static magnetic fields and tat peptides on cellular and nuclear uptake of magnetic nanoparticles.

PubMed

Smith, Carol-Anne M; de la Fuente, Jesus; Pelaz, Beatriz; Furlani, Edward P; Mullin, Margaret; Berry, Catherine C

2010-05-01

Magnetic nanoparticles are widely used in bioapplications such as imaging (MRI), targeted delivery (drugs/genes) and cell transfection (magnetofection). Historically, the impermeable nature of both the plasma and nuclear membranes hinder potential. Researchers combat this by developing techniques to enhance cellular and nuclear uptake. Two current popular methods are using external magnetic fields to remotely control particle direction or functionalising the nanoparticles with a cell penetrating peptide (e.g. tat); both of which facilitate cell entry. This paper compares the success of both methods in terms of nanoparticle uptake, analysing the type of magnetic forces the particles experience, and determines gross cell response in terms of morphology and structure and changes at the gene level via microarray analysis. Results indicated that both methods enhanced uptake via a caveolin dependent manner, with tat peptide being the more efficient and achieving nuclear uptake. On comparison to control cells, many groups of gene changes were observed in response to the particles. Importantly, the magnetic field also caused many change in gene expression, regardless of the nanoparticles, and appeared to cause F-actin alignment in the cells. Results suggest that static fields should be modelled and analysed prior to application in culture as cells clearly respond appropriately. Furthermore, the use of cell penetrating peptides may prove more beneficial in terms of enhancing uptake and maintaining cell homeostasis than a magnetic field. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Results of the engineering run of the Coherent Neutrino Nucleus Interaction Experiment (CONNIE)

NASA Astrophysics Data System (ADS)

Aguilar-Arevalo, A.; Bertou, X.; Bonifazi, C.; Butner, M.; Cancelo, G.; Castañeda Vázquez, A.; Cervantes Vergara, B.; Chavez, C. R.; Da Motta, H.; D'Olivo, J. C.; Dos Anjos, J.; Estrada, J.; Fernandez Moroni, G.; Ford, R.; Foguel, A.; Hernández Torres, K. P.; Izraelevitch, F.; Kavner, A.; Kilminster, B.; Kuk, K.; Lima, H. P., Jr.; Makler, M.; Molina, J.; Moreno-Granados, G.; Moro, J. M.; Paolini, E. E.; Sofo Haro, M.; Tiffenberg, J.; Trillaud, F.; Wagner, S.

2016-07-01

The CONNIE detector prototype is operating at a distance of 30 m from the core of a 3.8 GWth nuclear reactor with the goal of establishing Charge-Coupled Devices (CCD) as a new technology for the detection of coherent elastic neutrino-nucleus scattering. We report on the results of the engineering run with an active mass of 4 g of silicon. The CCD array is described, and the performance observed during the first year is discussed. A compact passive shield was deployed around the detector, producing an order of magnitude reduction in the background rate. The remaining background observed during the run was stable, and dominated by internal contamination in the detector packaging materials. The in-situ calibration of the detector using X-ray lines from fluorescence demonstrates good stability of the readout system. The event rates with the reactor ON and OFF are compared, and no excess is observed coming from nuclear fission at the power plant. The upper limit for the neutrino event rate is set two orders of magnitude above the expectations for the standard model. The results demonstrate the cryogenic CCD-based detector can be remotely operated at the reactor site with stable noise below 2 e- RMS and stable background rates. The success of the engineering test provides a clear path for the upgraded 100 g detector to be deployed during 2016.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

PubMed

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

An Undergraduate Laboratory Exercise to Study the Effect of Darkness on Plant Gene Expression Using DNA Microarray

ERIC Educational Resources Information Center

Chang, Ming-Mei; Briggs, George M.

2007-01-01

DNA microarrays are microscopic arrays on a solid surface, typically a glass slide, on which DNA oligonucleotides are deposited or synthesized in a high-density matrix with a predetermined spatial order. Several types of DNA microarrays have been developed and used for various biological studies. Here, we developed an undergraduate laboratory…

The use of open source bioinformatics tools to dissect transcriptomic data.

PubMed

Nitsche, Benjamin M; Ram, Arthur F J; Meyer, Vera

2012-01-01

Microarrays are a valuable technology to study fungal physiology on a transcriptomic level. Various microarray platforms are available comprising both single and two channel arrays. Despite different technologies, preprocessing of microarray data generally includes quality control, background correction, normalization, and summarization of probe level data. Subsequently, depending on the experimental design, diverse statistical analysis can be performed, including the identification of differentially expressed genes and the construction of gene coexpression networks.We describe how Bioconductor, a collection of open source and open development packages for the statistical programming language R, can be used for dissecting microarray data. We provide fundamental details that facilitate the process of getting started with R and Bioconductor. Using two publicly available microarray datasets from Aspergillus niger, we give detailed protocols on how to identify differentially expressed genes and how to construct gene coexpression networks.

Methods to study legionella transcriptome in vitro and in vivo.

PubMed

Faucher, Sebastien P; Shuman, Howard A

2013-01-01

The study of transcriptome responses can provide insight into the regulatory pathways and genetic factors that contribute to a specific phenotype. For bacterial pathogens, it can identify putative new virulence systems and shed light on the mechanisms underlying the regulation of virulence factors. Microarrays have been previously used to study gene regulation in Legionella pneumophila. In the past few years a sharp reduction of the costs associated with microarray experiments together with the availability of relatively inexpensive custom-designed commercial microarrays has made microarray technology an accessible tool for the majority of researchers. Here we describe the methodologies to conduct microarray experiments from in vitro and in vivo samples.

Reusable conductimetric array of interdigitated microelectrodes for the readout of low-density microarrays.

PubMed

Mallén, Maria; Díaz-González, María; Bonilla, Diana; Salvador, Juan P; Marco, María P; Baldi, Antoni; Fernández-Sánchez, César

2014-06-17

Low-density protein microarrays are emerging tools in diagnostics whose deployment could be primarily limited by the cost of fluorescence detection schemes. This paper describes an electrical readout system of microarrays comprising an array of gold interdigitated microelectrodes and an array of polydimethylsiloxane microwells, which enabled multiplexed detection of up to thirty six biological events on the same substrate. Similarly to fluorescent readout counterparts, the microarray can be developed on disposable glass slide substrates. However, unlike them, the presented approach is compact and requires a simple and inexpensive instrumentation. The system makes use of urease labeled affinity reagents for developing the microarrays and is based on detection of conductivity changes taking place when ionic species are generated in solution due to the catalytic hydrolysis of urea. The use of a polydimethylsiloxane microwell array facilitates the positioning of the measurement solution on every spot of the microarray. Also, it ensures the liquid tightness and isolation from the surrounding ones during the microarray readout process, thereby avoiding evaporation and chemical cross-talk effects that were shown to affect the sensitivity and reliability of the system. The performance of the system is demonstrated by carrying out the readout of a microarray for boldenone anabolic androgenic steroid hormone. Analytical results are comparable to those obtained by fluorescent scanner detection approaches. The estimated detection limit is 4.0 ng mL(-1), this being below the threshold value set by the World Anti-Doping Agency and the European Community. Copyright © 2014 Elsevier B.V. All rights reserved.

Development of a DNA microarray for species identification of quarantine aphids.

PubMed

Lee, Won Sun; Choi, Hwalran; Kang, Jinseok; Kim, Ji-Hoon; Lee, Si Hyeock; Lee, Seunghwan; Hwang, Seung Yong

2013-12-01

Aphid pests are being brought into Korea as a result of increased crop trading. Aphids exist on growth areas of plants, and thus plant growth is seriously affected by aphid pests. However, aphids are very small and have several sexual morphs and life stages, so it is difficult to identify species on the basis of morphological features. This problem was approached using DNA microarray technology. DNA targets of the cytochrome c oxidase subunit I gene were generated with a fluorescent dye-labelled primer and were hybridised onto a DNA microarray consisting of specific probes. After analysing the signal intensity of the specific probes, the unique patterns from the DNA microarray, consisting of 47 species-specific probes, were obtained to identify 23 aphid species. To confirm the accuracy of the developed DNA microarray, ten individual blind samples were used in blind trials, and the identifications were completely consistent with the sequencing data of all individual blind samples. A microarray has been developed to distinguish aphid species. DNA microarray technology provides a rapid, easy, cost-effective and accurate method for identifying aphid species for pest control management. © 2013 Society of Chemical Industry.

Multiplex cDNA quantification method that facilitates the standardization of gene expression data

PubMed Central

Gotoh, Osamu; Murakami, Yasufumi; Suyama, Akira

2011-01-01

Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations. These requirements impose limitations on the extensive comparison of gene expression data. Here, we report an effective approach to removing the unfavorable limitations by measuring the absolute amounts of gene expression levels on common DNA microarrays. We have developed a multiplex cDNA quantification method called GEP-DEAN (Gene expression profiling by DCN-encoding-based analysis). The method was validated by using chemically synthesized DNA strands of known quantities and cDNA samples prepared from mouse liver, demonstrating that the absolute amounts of cDNA strands were successfully measured with a sensitivity of 18 zmol in a highly multiplexed manner in 7 h. PMID:21415008

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

PubMed Central

2012-01-01

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings. PMID:16964229

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

You can hide but you have to run: direct detection with vector mediators

NASA Astrophysics Data System (ADS)

D'Eramo, Francesco; Kavanagh, Bradley J.; Panci, Paolo

2016-08-01

We study direct detection in simplified models of Dark Matter (DM) in which interactions with Standard Model (SM) fermions are mediated by a heavy vector boson. We consider fully general, gauge-invariant couplings between the SM, the mediator and both scalar and fermion DM. We account for the evolution of the couplings between the energy scale of the mediator mass and the nuclear energy scale. This running arises from virtual effects of SM particles and its inclusion is not optional. We compare bounds on the mediator mass from direct detection experiments with and without accounting for the running. In some cases the inclusion of these effects changes the bounds by several orders of magnitude, as a consequence of operator mixing which generates new interactions at low energy. We also highlight the importance of these effects when translating LHC limits on the mediator mass into bounds on the direct detection cross section. For an axial-vector mediator, the running can alter the derived bounds on the spin-dependent DM-nucleon cross section by a factor of two or more. Finally, we provide tools to facilitate the inclusion of these effects in future studies: general approximate expressions for the low energy couplings and a public code runDM to evolve the couplings between arbitrary energy scales.

Concurrent nuclear ERG and MYC protein overexpression defines a subset of locally advanced prostate cancer: Potential opportunities for synergistic targeted therapeutics.

PubMed

Udager, Aaron M; DeMarzo, Angelo M; Shi, Yang; Hicks, Jessica L; Cao, Xuhong; Siddiqui, Javed; Jiang, Hui; Chinnaiyan, Arul M; Mehra, Rohit

2016-06-01

Recurrent ERG gene fusions, the most common genetic alterations in prostate cancer, drive overexpression of the nuclear transcription factor ERG, and are early clonal events in prostate cancer progression. The nuclear transcription factor MYC is also frequently overexpressed in prostate cancer and may play a role in tumor initiation and/or progression. The relationship between nuclear ERG and MYC protein overexpression in prostate cancer, as well as the clinicopathologic characteristics and prognosis of ERG-positive/MYC high tumors, is not well understood. Immunohistochemistry (IHC) for ERG and MYC was performed on formalin-fixed, paraffin-embedded tissue from prostate cancer tissue microarrays (TMAs), and nuclear staining was scored semi-quantitatively (IHC product score range = 0-300). Correlation between nuclear ERG and MYC protein expression and association with clinicopathologic parameters and biochemical recurrence after radical prostatectomy was assessed. 29.1% of all tumor nodules showed concurrent nuclear ERG and MYC protein overexpression (i.e., ERG-positive/MYC high), including 35.0% of secondary nodules. Overall, there was weak positive correlation between ERG and MYC expression across all tumor nodules (rpb  = 0.149, P = 0.045), although this correlation was strongest in secondary nodules (rpb  = 0.520, P = 0.019). In radical prostatectomy specimens, ERG-positive/MYC high tumors were positively associated with the presence of extraprostatic extension (EPE), relative to all other ERG/MYC expression subgroups, however, there was no significant association between concurrent nuclear ERG and MYC protein overexpression and time to biochemical recurrence. Concurrent nuclear ERG and MYC protein overexpression is common in prostate cancer and defines a subset of locally advanced tumors. Recent data indicates that BET bromodomain proteins regulate ERG gene fusion and MYC gene expression in prostate cancer, suggesting possible synergistic targeted therapeutics in ERG-positive/MYC high tumors. Prostate 76:845-853, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Power Plant Construction

NASA Technical Reports Server (NTRS)

1985-01-01

Stone & Webster Engineering Corporation utilized TAP-A, a COSMIC program originally developed as part of a NASA investigation into the potential of nuclear power for space launch vehicles. It is useful in nuclear power plant design to qualify safety-related equipment at the temperatures it would experience should an accident occur. The program is easy to use, produces accurate results, and is inexpensive to run.

Profiling In Situ Microbial Community Structure with an Amplification Microarray

PubMed Central

Knickerbocker, Christopher; Bryant, Lexi; Golova, Julia; Wiles, Cory; Williams, Kenneth H.; Peacock, Aaron D.; Long, Philip E.

2013-01-01

The objectives of this study were to unify amplification, labeling, and microarray hybridization chemistries within a single, closed microfluidic chamber (an amplification microarray) and verify technology performance on a series of groundwater samples from an in situ field experiment designed to compare U(VI) mobility under conditions of various alkalinities (as HCO3−) during stimulated microbial activity accompanying acetate amendment. Analytical limits of detection were between 2 and 200 cell equivalents of purified DNA. Amplification microarray signatures were well correlated with 16S rRNA-targeted quantitative PCR results and hybridization microarray signatures. The succession of the microbial community was evident with and consistent between the two microarray platforms. Amplification microarray analysis of acetate-treated groundwater showed elevated levels of iron-reducing bacteria (Flexibacter, Geobacter, Rhodoferax, and Shewanella) relative to the average background profile, as expected. Identical molecular signatures were evident in the transect treated with acetate plus NaHCO3, but at much lower signal intensities and with a much more rapid decline (to nondetection). Azoarcus, Thaurea, and Methylobacterium were responsive in the acetate-only transect but not in the presence of bicarbonate. Observed differences in microbial community composition or response to bicarbonate amendment likely had an effect on measured rates of U reduction, with higher rates probable in the part of the field experiment that was amended with bicarbonate. The simplification in microarray-based work flow is a significant technological advance toward entirely closed-amplicon microarray-based tests and is generally extensible to any number of environmental monitoring applications. PMID:23160129

Fabrication of Carbohydrate Microarrays by Boronate Formation.

PubMed

Adak, Avijit K; Lin, Ting-Wei; Li, Ben-Yuan; Lin, Chun-Cheng

2017-01-01

The interactions between soluble carbohydrates and/or surface displayed glycans and protein receptors are essential to many biological processes and cellular recognition events. Carbohydrate microarrays provide opportunities for high-throughput quantitative analysis of carbohydrate-protein interactions. Over the past decade, various techniques have been implemented for immobilizing glycans on solid surfaces in a microarray format. Herein, we describe a detailed protocol for fabricating carbohydrate microarrays that capitalizes on the intrinsic reactivity of boronic acid toward carbohydrates to form stable boronate diesters. A large variety of unprotected carbohydrates ranging in structure from simple disaccharides and trisaccharides to considerably more complex human milk and blood group (oligo)saccharides have been covalently immobilized in a single step on glass slides, which were derivatized with high-affinity boronic acid ligands. The immobilized ligands in these microarrays maintain the receptor-binding activities including those of lectins and antibodies according to the structures of their pendant carbohydrates for rapid analysis of a number of carbohydrate-recognition events within 30 h. This method facilitates the direct construction of otherwise difficult to obtain carbohydrate microarrays from underivatized glycans.

Two-Dimensional VO2 Mesoporous Microarrays for High-Performance Supercapacitor

NASA Astrophysics Data System (ADS)

Fan, Yuqi; Ouyang, Delong; Li, Bao-Wen; Dang, Feng; Ren, Zongming

2018-05-01

Two-dimensional (2D) mesoporous VO2 microarrays have been prepared using an organic-inorganic liquid interface. The units of microarrays consist of needle-like VO2 particles with a mesoporous structure, in which crack-like pores with a pore size of about 2 nm and depth of 20-100 nm are distributed on the particle surface. The liquid interface acts as a template for the formation of the 2D microarrays, as identified from the kinetic observation. Due to the mesoporous structure of the units and high conductivity of the microarray, such 2D VO2 microarrays exhibit a high specific capacitance of 265 F/g at 1 A/g and excellent rate capability (182 F/g at 10 A/g) and cycling stability, suggesting the effect of unique microstructure for improving the electrochemical performance.

Advances in cell-free protein array methods.

PubMed

Yu, Xiaobo; Petritis, Brianne; Duan, Hu; Xu, Danke; LaBaer, Joshua

2018-01-01

Cell-free protein microarrays represent a special form of protein microarray which display proteins made fresh at the time of the experiment, avoiding storage and denaturation. They have been used increasingly in basic and translational research over the past decade to study protein-protein interactions, the pathogen-host relationship, post-translational modifications, and antibody biomarkers of different human diseases. Their role in the first blood-based diagnostic test for early stage breast cancer highlights their value in managing human health. Cell-free protein microarrays will continue to evolve to become widespread tools for research and clinical management. Areas covered: We review the advantages and disadvantages of different cell-free protein arrays, with an emphasis on the methods that have been studied in the last five years. We also discuss the applications of each microarray method. Expert commentary: Given the growing roles and impact of cell-free protein microarrays in research and medicine, we discuss: 1) the current technical and practical limitations of cell-free protein microarrays; 2) the biomarker discovery and verification pipeline using protein microarrays; and 3) how cell-free protein microarrays will advance over the next five years, both in their technology and applications.

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

EPA Science Inventory

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, ...

ROBNCA: robust network component analysis for recovering transcription factor activities.

PubMed

Noor, Amina; Ahmad, Aitzaz; Serpedin, Erchin; Nounou, Mohamed; Nounou, Hazem

2013-10-01

Network component analysis (NCA) is an efficient method of reconstructing the transcription factor activity (TFA), which makes use of the gene expression data and prior information available about transcription factor (TF)-gene regulations. Most of the contemporary algorithms either exhibit the drawback of inconsistency and poor reliability, or suffer from prohibitive computational complexity. In addition, the existing algorithms do not possess the ability to counteract the presence of outliers in the microarray data. Hence, robust and computationally efficient algorithms are needed to enable practical applications. We propose ROBust Network Component Analysis (ROBNCA), a novel iterative algorithm that explicitly models the possible outliers in the microarray data. An attractive feature of the ROBNCA algorithm is the derivation of a closed form solution for estimating the connectivity matrix, which was not available in prior contributions. The ROBNCA algorithm is compared with FastNCA and the non-iterative NCA (NI-NCA). ROBNCA estimates the TF activity profiles as well as the TF-gene control strength matrix with a much higher degree of accuracy than FastNCA and NI-NCA, irrespective of varying noise, correlation and/or amount of outliers in case of synthetic data. The ROBNCA algorithm is also tested on Saccharomyces cerevisiae data and Escherichia coli data, and it is observed to outperform the existing algorithms. The run time of the ROBNCA algorithm is comparable with that of FastNCA, and is hundreds of times faster than NI-NCA. The ROBNCA software is available at http://people.tamu.edu/∼amina/ROBNCA

Progress in the application of DNA microarrays.

PubMed Central

Lobenhofer, E K; Bushel, P R; Afshari, C A; Hamadeh, H K

2001-01-01

Microarray technology has been applied to a variety of different fields to address fundamental research questions. The use of microarrays, or DNA chips, to study the gene expression profiles of biologic samples began in 1995. Since that time, the fundamental concepts behind the chip, the technology required for making and using these chips, and the multitude of statistical tools for analyzing the data have been extensively reviewed. For this reason, the focus of this review will be not on the technology itself but on the application of microarrays as a research tool and the future challenges of the field. PMID:11673116

Plastic Polymers for Efficient DNA Microarray Hybridization: Application to Microbiological Diagnostics▿

PubMed Central

Zhao, Zhengshan; Peytavi, Régis; Diaz-Quijada, Gerardo A.; Picard, Francois J.; Huletsky, Ann; Leblanc, Éric; Frenette, Johanne; Boivin, Guy; Veres, Teodor; Dumoulin, Michel M.; Bergeron, Michel G.

2008-01-01

Fabrication of microarray devices using traditional glass slides is not easily adaptable to integration into microfluidic systems. There is thus a need for the development of polymeric materials showing a high hybridization signal-to-background ratio, enabling sensitive detection of microbial pathogens. We have developed such plastic supports suitable for highly sensitive DNA microarray hybridizations. The proof of concept of this microarray technology was done through the detection of four human respiratory viruses that were amplified and labeled with a fluorescent dye via a sensitive reverse transcriptase PCR (RT-PCR) assay. The performance of the microarray hybridization with plastic supports made of PMMA [poly(methylmethacrylate)]-VSUVT or Zeonor 1060R was compared to that with high-quality glass slide microarrays by using both passive and microfluidic hybridization systems. Specific hybridization signal-to-background ratios comparable to that obtained with high-quality commercial glass slides were achieved with both polymeric substrates. Microarray hybridizations demonstrated an analytical sensitivity equivalent to approximately 100 viral genome copies per RT-PCR, which is at least 100-fold higher than the sensitivities of previously reported DNA hybridizations on plastic supports. Testing of these plastic polymers using a microfluidic microarray hybridization platform also showed results that were comparable to those with glass supports. In conclusion, PMMA-VSUVT and Zeonor 1060R are both suitable for highly sensitive microarray hybridizations. PMID:18784318

Development and application of a microarray meter tool to optimize microarray experiments

PubMed Central

Rouse, Richard JD; Field, Katrine; Lapira, Jennifer; Lee, Allen; Wick, Ivan; Eckhardt, Colleen; Bhasker, C Ramana; Soverchia, Laura; Hardiman, Gary

2008-01-01

Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies. PMID:18710498

SIMULATION AND VISUALIZATION OF FLOW PATTERN IN MICROARRAYS FOR LIQUID PHASE OLIGONUCLEOTIDE AND PEPTIDE SYNTHESIS

PubMed Central

O-Charoen, Sirimon; Srivannavit, Onnop; Gulari, Erdogan

2008-01-01

Microfluidic microarrays have been developed for economical and rapid parallel synthesis of oligonucleotide and peptide libraries. For a synthesis system to be reproducible and uniform, it is crucial to have a uniform reagent delivery throughout the system. Computational fluid dynamics (CFD) is used to model and simulate the microfluidic microarrays to study geometrical effects on flow patterns. By proper design geometry, flow uniformity could be obtained in every microreactor in the microarrays. PMID:17480053

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

PubMed

Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Temperature Gradient Effect on Gas Discrimination Power of a Metal-Oxide Thin-Film Sensor Microarray

PubMed Central

Sysoev, Victor V.; Kiselev, Ilya; Frietsch, Markus; Goschnick, Joachim

2004-01-01

The paper presents results concerning the effect of spatial inhomogeneous operating temperature on the gas discrimination power of a gas-sensor microarray, with the latter based on a thin SnO2 film employed in the KAMINA electronic nose. Three different temperature distributions over the substrate are discussed: a nearly homogeneous one and two temperature gradients, equal to approx. 3.3 °C/mm and 6.7 °C/mm, applied across the sensor elements (segments) of the array. The gas discrimination power of the microarray is judged by using the Mahalanobis distance in the LDA (Linear Discrimination Analysis) coordinate system between the data clusters obtained by the response of the microarray to four target vapors: ethanol, acetone, propanol and ammonia. It is shown that the application of a temperature gradient increases the gas discrimination power of the microarray by up to 35 %.

The NIFFTE Data Acquisition System

NASA Astrophysics Data System (ADS)

Qu, Hai; Niffte Collaboration

2011-10-01

The Neutron Induced Fission Fragment Tracking Experiment (NIFFTE) will employ a novel, high granularity, pressurized Time Projection Chamber to measure fission cross-sections of the major actinides to high precision over a wide incident neutron energy range. These results will improve nuclear data accuracy and benefit the fuel cycle in the future. The NIFFTE data acquisition system (DAQ) has been designed and implemented on the prototype TPC. Lessons learned from engineering runs have been incorporated into some design changes that are being implemented before the next run cycle. A fully instrumented sextant of EtherDAQ cards (16 sectors, 496 channels) will be used for the next run cycle. The Maximum Integrated Data Acquisition System (MIDAS) has been chosen and customized to configure and run the experiment. It also meets the requirement for remote control and monitoring of the system. The integration of the MIDAS online database with the persistent PostgreSQL database has been implemented for experiment usage. The detailed design and current status of the DAQ system will be presented.

A chi-square goodness-of-fit test for non-identically distributed random variables: with application to empirical Bayes

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

Conover, W.J.; Cox, D.D.; Martz, H.F.

1997-12-01

When using parametric empirical Bayes estimation methods for estimating the binomial or Poisson parameter, the validity of the assumed beta or gamma conjugate prior distribution is an important diagnostic consideration. Chi-square goodness-of-fit tests of the beta or gamma prior hypothesis are developed for use when the binomial sample sizes or Poisson exposure times vary. Nine examples illustrate the application of the methods, using real data from such diverse applications as the loss of feedwater flow rates in nuclear power plants, the probability of failure to run on demand and the failure rates of the high pressure coolant injection systems atmore » US commercial boiling water reactors, the probability of failure to run on demand of emergency diesel generators in US commercial nuclear power plants, the rate of failure of aircraft air conditioners, baseball batting averages, the probability of testing positive for toxoplasmosis, and the probability of tumors in rats. The tests are easily applied in practice by means of corresponding Mathematica{reg_sign} computer programs which are provided.« less

Use of Microarray to Analyze Gene Expression Profiles of Acute Effects of Prochloraz on Fathead Minnows Pimephales promelas

EPA Science Inventory

Microarray technology is a powerful tool to investigate the gene expression profiles for thousands of genes simultaneously. In recent years, microarrays have been used to characterize environmental pollutants and identify molecular mode(s) of action of chemicals including endocri...

MICROARRAY QUALITY CONTROL PROJECT: A COMPREHENSIVE GENE EXPRESSION TECHNOLOGY SURVEY DEMONSTRATES MEASURABLE CONSISTENCY AND CONCORDANT RESULTS BETWEEN PLATFORMS

EPA Science Inventory

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, h...

Direct labeling of serum proteins by fluorescent dye for antibody microarray.

PubMed

Klimushina, M V; Gumanova, N G; Metelskaya, V A

2017-05-06

Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum. Copyright © 2017 Elsevier Inc. All rights reserved.

Determination of Minimum Training Sample Size for Microarray-Based Cancer Outcome Prediction–An Empirical Assessment

PubMed Central

Cheng, Ningtao; Wu, Leihong; Cheng, Yiyu

2013-01-01

The promise of microarray technology in providing prediction classifiers for cancer outcome estimation has been confirmed by a number of demonstrable successes. However, the reliability of prediction results relies heavily on the accuracy of statistical parameters involved in classifiers. It cannot be reliably estimated with only a small number of training samples. Therefore, it is of vital importance to determine the minimum number of training samples and to ensure the clinical value of microarrays in cancer outcome prediction. We evaluated the impact of training sample size on model performance extensively based on 3 large-scale cancer microarray datasets provided by the second phase of MicroArray Quality Control project (MAQC-II). An SSNR-based (scale of signal-to-noise ratio) protocol was proposed in this study for minimum training sample size determination. External validation results based on another 3 cancer datasets confirmed that the SSNR-based approach could not only determine the minimum number of training samples efficiently, but also provide a valuable strategy for estimating the underlying performance of classifiers in advance. Once translated into clinical routine applications, the SSNR-based protocol would provide great convenience in microarray-based cancer outcome prediction in improving classifier reliability. PMID:23861920

Microarray-based screening of heat shock protein inhibitors.

PubMed

Schax, Emilia; Walter, Johanna-Gabriela; Märzhäuser, Helene; Stahl, Frank; Scheper, Thomas; Agard, David A; Eichner, Simone; Kirschning, Andreas; Zeilinger, Carsten

2014-06-20

Based on the importance of heat shock proteins (HSPs) in diseases such as cancer, Alzheimer's disease or malaria, inhibitors of these chaperons are needed. Today's state-of-the-art techniques to identify HSP inhibitors are performed in microplate format, requiring large amounts of proteins and potential inhibitors. In contrast, we have developed a miniaturized protein microarray-based assay to identify novel inhibitors, allowing analysis with 300 pmol of protein. The assay is based on competitive binding of fluorescence-labeled ATP and potential inhibitors to the ATP-binding site of HSP. Therefore, the developed microarray enables the parallel analysis of different ATP-binding proteins on a single microarray. We have demonstrated the possibility of multiplexing by immobilizing full-length human HSP90α and HtpG of Helicobacter pylori on microarrays. Fluorescence-labeled ATP was competed by novel geldanamycin/reblastatin derivatives with IC50 values in the range of 0.5 nM to 4 μM and Z(*)-factors between 0.60 and 0.96. Our results demonstrate the potential of a target-oriented multiplexed protein microarray to identify novel inhibitors for different members of the HSP90 family. Copyright © 2014 Elsevier B.V. All rights reserved.

DNA Microarray for Rapid Detection and Identification of Food and Water Borne Bacteria: From Dry to Wet Lab.

PubMed

Ranjbar, Reza; Behzadi, Payam; Najafi, Ali; Roudi, Raheleh

2017-01-01

A rapid, accurate, flexible and reliable diagnostic method may significantly decrease the costs of diagnosis and treatment. Designing an appropriate microarray chip reduces noises and probable biases in the final result. The aim of this study was to design and construct a DNA Microarray Chip for a rapid detection and identification of 10 important bacterial agents. In the present survey, 10 unique genomic regions relating to 10 pathogenic bacterial agents including Escherichia coli (E.coli), Shigella boydii, Sh.dysenteriae, Sh.flexneri, Sh.sonnei, Salmonella typhi, S.typhimurium, Brucella sp., Legionella pneumophila, and Vibrio cholera were selected for designing specific long oligo microarray probes. For this reason, the in-silico operations including utilization of the NCBI RefSeq database, Servers of PanSeq and Gview, AlleleID 7.7 and Oligo Analyzer 3.1 was done. On the other hand, the in-vitro part of the study comprised stages of robotic microarray chip probe spotting, bacterial DNAs extraction and DNA labeling, hybridization and microarray chip scanning. In wet lab section, different tools and apparatus such as Nexterion® Slide E, Qarray mini spotter, NimbleGen kit, TrayMix TM S4, and Innoscan 710 were used. A DNA microarray chip including 10 long oligo microarray probes was designed and constructed for detection and identification of 10 pathogenic bacteria. The DNA microarray chip was capable to identify all 10 bacterial agents tested simultaneously. The presence of a professional bioinformatician as a probe designer is needed to design appropriate multifunctional microarray probes to increase the accuracy of the outcomes.

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

PubMed

Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

2014-08-04

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

Functional comparison of microarray data across multiple platforms using the method of percentage of overlapping functions.

PubMed

Li, Zhiguang; Kwekel, Joshua C; Chen, Tao

2012-01-01

Functional comparison across microarray platforms is used to assess the comparability or similarity of the biological relevance associated with the gene expression data generated by multiple microarray platforms. Comparisons at the functional level are very important considering that the ultimate purpose of microarray technology is to determine the biological meaning behind the gene expression changes under a specific condition, not just to generate a list of genes. Herein, we present a method named percentage of overlapping functions (POF) and illustrate how it is used to perform the functional comparison of microarray data generated across multiple platforms. This method facilitates the determination of functional differences or similarities in microarray data generated from multiple array platforms across all the functions that are presented on these platforms. This method can also be used to compare the functional differences or similarities between experiments, projects, or laboratories.

Importing MAGE-ML format microarray data into BioConductor.

PubMed

Durinck, Steffen; Allemeersch, Joke; Carey, Vincent J; Moreau, Yves; De Moor, Bart

2004-12-12

The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA microarray data stored in MAGE-ML format and the Bioconductor framework for preprocessing, visualization and analysis of microarray experiments. http://www.bioconductor.org. Open Source.

Chromosomal Microarray versus Karyotyping for Prenatal Diagnosis

PubMed Central

Wapner, Ronald J.; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C.; Eng, Christine M.; Zachary, Julia M.; Savage, Melissa; Platt, Lawrence D.; Saltzman, Daniel; Grobman, William A.; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S.; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N.; Thom, Elizabeth A.; Beaudet, Arthur L.; Ledbetter, David H.; Shaffer, Lisa G.; Jackson, Laird

2013-01-01

Background Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Methods Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. Results We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down’s syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. Conclusions In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.) PMID:23215555

Future Power Production by LENR with Thin-Film Electrodes

NASA Astrophysics Data System (ADS)

Miley, George H.; Hora, Heinz; Lipson, Andrei; Luo, Nie; Shrestha, P. Joshi

2007-03-01

PdD cluster reaction theory was recently proposed to explain a wide range of Low energy Nuclear Reaction (LENR) experiments. If understood and optimized, cluster reactions could lead to a revolutionary new power source of nuclear energy. The route is two-fold. First, the excess heat must be obtained reproducibly and over extended run times. Second, the percentage of excess must be significantly (order of magnitude or more) higher than the 20-50% typically today. The thin film methods described here have proven to be quite reproducible, e.g. providing excess heat of 20-30% in nine consecutive runs of several weeks each. However, mechanical separation of the films occurs over long runs due to the severe mechanical stresses created.. Techniques to overcome these problems are possible using graded bonding techniques similar to that used in high temperature solid oxide fuel cells. Thus the remaining key issue is to increase the excess heat. The cluster model provides import insight into this. G. H. Miley, H. Hora, et al., 233rd Amer Chem Soc Meeting, Chicago, IL, March 25-29, 2007.

GeneXplorer: an interactive web application for microarray data visualization and analysis.

PubMed

Rees, Christian A; Demeter, Janos; Matese, John C; Botstein, David; Sherlock, Gavin

2004-10-01

When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.

Fluorescence-based bioassays for the detection and evaluation of food materials.

PubMed

Nishi, Kentaro; Isobe, Shin-Ichiro; Zhu, Yun; Kiyama, Ryoiti

2015-10-13

We summarize here the recent progress in fluorescence-based bioassays for the detection and evaluation of food materials by focusing on fluorescent dyes used in bioassays and applications of these assays for food safety, quality and efficacy. Fluorescent dyes have been used in various bioassays, such as biosensing, cell assay, energy transfer-based assay, probing, protein/immunological assay and microarray/biochip assay. Among the arrays used in microarray/biochip assay, fluorescence-based microarrays/biochips, such as antibody/protein microarrays, bead/suspension arrays, capillary/sensor arrays, DNA microarrays/polymerase chain reaction (PCR)-based arrays, glycan/lectin arrays, immunoassay/enzyme-linked immunosorbent assay (ELISA)-based arrays, microfluidic chips and tissue arrays, have been developed and used for the assessment of allergy/poisoning/toxicity, contamination and efficacy/mechanism, and quality control/safety. DNA microarray assays have been used widely for food safety and quality as well as searches for active components. DNA microarray-based gene expression profiling may be useful for such purposes due to its advantages in the evaluation of pathway-based intracellular signaling in response to food materials.

Fluorescence-Based Bioassays for the Detection and Evaluation of Food Materials

PubMed Central

Nishi, Kentaro; Isobe, Shin-Ichiro; Zhu, Yun; Kiyama, Ryoiti

2015-01-01

We summarize here the recent progress in fluorescence-based bioassays for the detection and evaluation of food materials by focusing on fluorescent dyes used in bioassays and applications of these assays for food safety, quality and efficacy. Fluorescent dyes have been used in various bioassays, such as biosensing, cell assay, energy transfer-based assay, probing, protein/immunological assay and microarray/biochip assay. Among the arrays used in microarray/biochip assay, fluorescence-based microarrays/biochips, such as antibody/protein microarrays, bead/suspension arrays, capillary/sensor arrays, DNA microarrays/polymerase chain reaction (PCR)-based arrays, glycan/lectin arrays, immunoassay/enzyme-linked immunosorbent assay (ELISA)-based arrays, microfluidic chips and tissue arrays, have been developed and used for the assessment of allergy/poisoning/toxicity, contamination and efficacy/mechanism, and quality control/safety. DNA microarray assays have been used widely for food safety and quality as well as searches for active components. DNA microarray-based gene expression profiling may be useful for such purposes due to its advantages in the evaluation of pathway-based intracellular signaling in response to food materials. PMID:26473869

ELM - A SIMPLE TOOL FOR THERMAL-HYDRAULIC ANALYSIS OF SOLID-CORE NUCLEAR ROCKET FUEL ELEMENTS

NASA Technical Reports Server (NTRS)

Walton, J. T.

1994-01-01

ELM is a simple computational tool for modeling the steady-state thermal-hydraulics of propellant flow through fuel element coolant channels in nuclear thermal rockets. Written for the nuclear propulsion project of the Space Exploration Initiative, ELM evaluates the various heat transfer coefficient and friction factor correlations available for turbulent pipe flow with heat addition. In the past, these correlations were found in different reactor analysis codes, but now comparisons are possible within one program. The logic of ELM is based on the one-dimensional conservation of energy in combination with Newton's Law of Cooling to determine the bulk flow temperature and the wall temperature across a control volume. Since the control volume is an incremental length of tube, the corresponding pressure drop is determined by application of the Law of Conservation of Momentum. The size, speed, and accuracy of ELM make it a simple tool for use in fuel element parametric studies. ELM is a machine independent program written in FORTRAN 77. It has been successfully compiled on an IBM PC compatible running MS-DOS using Lahey FORTRAN 77, a DEC VAX series computer running VMS, and a Sun4 series computer running SunOS UNIX. ELM requires 565K of RAM under SunOS 4.1, 360K of RAM under VMS 5.4, and 406K of RAM under MS-DOS. Because this program is machine independent, no executable is provided on the distribution media. The standard distribution medium for ELM is one 5.25 inch 360K MS-DOS format diskette. ELM was developed in 1991. DEC, VAX, and VMS are trademarks of Digital Equipment Corporation. Sun4 and SunOS are trademarks of Sun Microsystems, Inc. IBM PC is a registered trademark of International Business Machines. MS-DOS is a registered trademark of Microsoft Corporation.

Severe Nuclear Accident Program (SNAP) - a real time model for accidental releases

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

Saltbones, J.; Foss, A.; Bartnicki, J.

1996-12-31

The model: Several Nuclear Accident Program (SNAP) has been developed at the Norwegian Meteorological Institute (DNMI) in Oslo to provide decision makers and Government officials with real-time tool for simulating large accidental releases of radioactivity from nuclear power plants or other sources. SNAP is developed in the Lagrangian framework in which atmospheric transport of radioactive pollutants is simulated by emitting a large number of particles from the source. The main advantage of the Lagrangian approach is a possibility of precise parameterization of advection processes, especially close to the source. SNAP can be used to predict the transport and deposition ofmore » a radioactive cloud in e future (up to 48 hours, in the present version) or to analyze the behavior of the cloud in the past. It is also possible to run the model in the mixed mode (partly analysis and partly forecast). In the routine run we assume unit (1 g s{sup -1}) emission in each of three classes. This assumption is very convenient for the main user of the model output in case of emergency: Norwegian Radiation Protection Agency. Due to linearity of the model equations, user can test different emission scenarios as a post processing task by assigning different weights to concentration and deposition fields corresponding to each of three emission classes. SNAP is fully operational and can be run by the meteorologist on duty at any time. The output from SNAP has two forms: First on the maps of Europe, or selected parts of Europe, individual particles are shown during the simulation period. Second, immediately after the simulation, concentration/deposition fields can be shown every three hours of the simulation period as isoline maps for each emission class. In addition, concentration and deposition maps, as well as some meteorological data, are stored on a public accessible disk for further processing by the model users.« less

ImpulseDE: detection of differentially expressed genes in time series data using impulse models.

PubMed

Sander, Jil; Schultze, Joachim L; Yosef, Nir

2017-03-01

Perturbations in the environment lead to distinctive gene expression changes within a cell. Observed over time, those variations can be characterized by single impulse-like progression patterns. ImpulseDE is an R package suited to capture these patterns in high throughput time series datasets. By fitting a representative impulse model to each gene, it reports differentially expressed genes across time points from a single or between two time courses from two experiments. To optimize running time, the code uses clustering and multi-threading. By applying ImpulseDE , we demonstrate its power to represent underlying biology of gene expression in microarray and RNA-Seq data. ImpulseDE is available on Bioconductor ( https://bioconductor.org/packages/ImpulseDE/ ). niryosef@berkeley.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Hypoxia induces a HIF-1α dependent signaling cascade to make a complex metabolic switch in SGBS-adipocytes☆

PubMed Central

Leiherer, Andreas; Geiger, Kathrin; Muendlein, Axel; Drexel, Heinz

2014-01-01

To elucidate the complex impact of hypoxia on adipose tissue, resulting in biased metabolism, insulin resistance and finally diabetes we used mature adipocytes derived from a Simpson-Golabi-Behmel syndrome patient for microarray analysis. We found a significantly increased transcription rate of genes involved in glycolysis and a striking association between the pattern of upregulated genes and disease biomarkers for diabetes mellitus and insulin resistance. Although their upregulation turned out to be HIF-1α-dependent, we identified further transcription factors mainly AP-1 components to play also an important role in hypoxia response. Analyzing the regulatory network of mentioned transcription factors and glycolysis targets we revealed a clear hint for directing glycolysis to glutathione and glycogen synthesis. This metabolic switch in adipocytes enables the cell to prevent oxidative damage in the short term but might induce lipogenesis and establish systemic metabolic disorders in the long run. PMID:24275182

EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

PubMed Central

Barton, G; Abbott, J; Chiba, N; Huang, DW; Huang, Y; Krznaric, M; Mack-Smith, J; Saleem, A; Sherman, BT; Tiwari, B; Tomlinson, C; Aitman, T; Darlington, J; Game, L; Sternberg, MJE; Butcher, SA

2008-01-01

Background Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. Results EMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. Conclusion EMAAS enables users to track and perform microarray data management and analysis tasks through a single easy-to-use web application. The system architecture is flexible and scalable to allow new array types, analysis algorithms and tools to be added with relative ease and to cope with large increases in data volume. PMID:19032776

Gene selection for microarray data classification via subspace learning and manifold regularization.

PubMed

Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

2017-12-19

With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

PubMed

Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

2016-04-01

Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.

Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results.

PubMed

Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

2012-06-08

Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

Nuclear overexpression of the overexpressed in lung cancer 1 predicts worse prognosis in gastric adenocarcinoma.

PubMed

Wang, Jue; Shen, Hongchang; Fu, Guobin; Zhao, Dandan; Wang, Weibo

2017-02-07

We have performed this retrospective study to elucidate whether elevated expression of the overexpressed in lung cancer 1 (OLC1) was related to the clinicopathological parameters and prognosis of patients with gastric adenocarcinoma. Additionally, different effects of various subcellular OLC1 expression on gastric adeno-carcinogenesis were focused on in our study. Both overall and subcellular expression of OLC1 was evaluated by immunohistochemistry(IHC) via tissue microarrays from total 393 samples. The Kaplan-Meier method and Cox's proportional hazard model were exerted to further explore the correlation between OLC1 and prognosis. Total overexpression of OLC1 was significantly associated with stage (P = 0.004) and differentiation (P = 0.009), and only the strong total expression could predict a poor prognosis (HR = 1.31, P = 0.04). There were significant associations found between nuclear overexpression and tumor invasion depth(P = 0.002), lymph node (P < 0.001), stage (P = 0.004), differentiation (P < 0.001) and smoking history (P = 0.045). Furthermore, over-expressed nuclear OLC1 protein could be an independent risk factor for gastric adenocarcinoma (univariate: HR = 1.43, P = 0.003; multivariate: HR = 1.39, P = 0.011). In general, both total and nuclear overexpression of OLC1 could be the signs of gastric adeno-carcinogenesis, which might be served as the biomarkers for diagnosis at an early stage, even at the onset of tumorigenesis. Rather than the total expression, nuclear overexpression of OLC1 was correlated with most clinicopathological parameters and could predict a poor overall survival as an independent factor for prognosis, which made it a more effective and sensitive biomarker for gastric adenocarcinoma.

Analysis of aging in lager brewing yeast during serial repitching.

PubMed

Bühligen, Franziska; Lindner, Patrick; Fetzer, Ingo; Stahl, Frank; Scheper, Thomas; Harms, Hauke; Müller, Susann

2014-10-10

Serial repitching of brewing yeast inoculates is an important economic factor in the brewing industry, as their propagation is time and resource intensive. Here, we investigated whether replicative aging and/or the population distribution status changed during serial repitching in three different breweries with the same brewing yeast strain but different abiotic backgrounds and repitching regimes with varying numbers of reuses. Next to bud scar numbers the DNA content of the Saccharomyces pastorianus HEBRU cells was analyzed. Gene expression patterns were investigated using low-density microarrays with genes for aging, stress, storage compound metabolism and cell cycle. Two breweries showed a stable rejuvenation rate during serial repitching. In a third brewery the fraction of virgin cells varied, which could be explained with differing wort aeration rates. Furthermore, the number of bud scars per cell and cell size correlated in all 3 breweries throughout all runs. Transcriptome analyses revealed that from the 6th run on, mainly for the cells positive gene expression could be seen, for example up-regulation of trehalose and glycogen metabolism genes. Additionally, the cells' settling in the cone was dependent on cell size, with the lowest and the uppermost cone layers showing the highest amount of dead cells. In general, cells do not progressively age during extended serial repitching. Copyright © 2014 Elsevier B.V. All rights reserved.

Securing Nuclear Materials: The 2010 Summit and Issues for Congress

DTIC Science & Technology

2011-04-27

Nigeria, Norway, Pakistan, Philippines, Poland, the Republic of Korea, the Russian Federation, Saudi Arabia, Singapore, Switzerland, South Africa...Spain, Sweden, Thailand, Turkey , United Arab Emirates, the United Kingdom, Ukraine, and Vietnam. White House Press Briefing, April 6, 2010. 8 “ The ...Non-Aligned Movement, where skepticism of the nuclear terrorism threat runs highest. In addition, the Russian Federation said it would be helping the

Applications of neutron radiography for the nuclear power industry

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

Craft, Aaron E.; Barton, John P.

The World Conference on Neutron Radiography (WCNR) and International Topical Meeting on Neutron Radiography (ITMNR) series have been running over 35 years. The most recent event, ITMNR-8, focused on industrial applications and was the first time this series was hosted in China. In China, more than twenty new nuclear power plants are in construction and plans have been announced to increase the nuclear capacity further by a factor of three within fifteen years. There are additional prospects in many other nations. Neutron tests were vital during previous developments of materials and components for nuclear power applications, as reported in thismore » conference series. For example a majority of the 140 papers in the Proceedings of the First WCNR are for the benefit of the nuclear power industry. Included are reviews of the diverse techniques being applied in Europe, Japan, the United States, and at many other centers. Many of those techniques are being utilized and advanced to the present time. Neutron radiography of irradiated nuclear fuel provides more comprehensive information about the internal condition of irradiated nuclear fuel than any other non-destructive technique to date. Applications include examination of nuclear waste, nuclear fuels, cladding, control elements, and other critical components. In this paper, the techniques developed and applied internationally for the nuclear power industry since the earliest years are reviewed, and the question is asked whether neutron test techniques can be of value in development of the present and future generations of nuclear power plants world-wide.« less

Research resource: Tissue-specific transcriptomics and cistromics of nuclear receptor signaling: a web research resource.

PubMed

Ochsner, Scott A; Watkins, Christopher M; LaGrone, Benjamin S; Steffen, David L; McKenna, Neil J

2010-10-01

Nuclear receptors (NRs) are ligand-regulated transcription factors that recruit coregulators and other transcription factors to gene promoters to effect regulation of tissue-specific transcriptomes. The prodigious rate at which the NR signaling field has generated high content gene expression and, more recently, genome-wide location analysis datasets has not been matched by a committed effort to archiving this information for routine access by bench and clinical scientists. As a first step towards this goal, we searched the MEDLINE database for studies, which referenced either expression microarray and/or genome-wide location analysis datasets in which a NR or NR ligand was an experimental variable. A total of 1122 studies encompassing 325 unique organs, tissues, primary cells, and cell lines, 35 NRs, and 91 NR ligands were retrieved and annotated. The data were incorporated into a new section of the Nuclear Receptor Signaling Atlas Molecule Pages, Transcriptomics and Cistromics, for which we designed an intuitive, freely accessible user interface to browse the studies. Each study links to an abstract, the MEDLINE record, and, where available, Gene Expression Omnibus and ArrayExpress records. The resource will be updated on a regular basis to provide a current and comprehensive entrez into the sum of transcriptomic and cistromic research in this field.

Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

PubMed Central

2012-01-01

Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA) with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO) correctly identified (p < 0.05) microarray data in which genes annotated to differentially expressed GO terms are upregulated. We found that GSEA + MIMGO was slightly less effective than, or comparable to, GSEA (Pearson), a method that uses Pearson’s correlation as a metric, at detecting true differentially expressed GO terms. However, unlike other methods including GSEA (Pearson), GSEA + MIMGO can comprehensively identify the microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively. PMID:23232071

EDRN Biomarker Reference Lab: Pacific Northwest National Laboratory — EDRN Public Portal

Cancer.gov

The purpose of this project is to develop antibody microarrays incorporating three major improvements compared to previous antibody microarray platforms, and to produce and disseminate these antibody microarray technologies for the Early Detection Research Network (EDRN) and the research community focusing on early detection, and risk assessment of cancer.

Strategies for comparing gene expression profiles from different microarray platforms: application to a case-control experiment.

PubMed

Severgnini, Marco; Bicciato, Silvio; Mangano, Eleonora; Scarlatti, Francesca; Mezzelani, Alessandra; Mattioli, Michela; Ghidoni, Riccardo; Peano, Clelia; Bonnal, Raoul; Viti, Federica; Milanesi, Luciano; De Bellis, Gianluca; Battaglia, Cristina

2006-06-01

Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.

A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

PubMed

Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S

2010-05-21

Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Electromagnetic pulse (EMP), Part II: Field-expedient ways to minimize its effects on field medical treatment facilities.

PubMed

Vandre, R H; Klebers, J; Tesche, F M; Blanchard, J P

1993-05-01

Part I of this paper showed that a field commander can expect approximately 65% of his unprotected electronic medical equipment to be damaged by the electromagnetic pulse (EMP) from a single nuclear detonation as far as 2200 km away. Using computer modeling, field-expedient ways to minimize the effects of EMP were studied. The results were: (1) keep wiring near the ground, (2) keep wiring short, (3) unplug unused equipment, (4) run power cabling and tents in a magnetic north-south direction (avoid running power cabling in the east-west direction), and (5) place sensitive equipment in International Organization for Standardization shelters.

Nuclear Computational Low Energy Initiative (NUCLEI)

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

Reddy, Sanjay K.

This is the final report for University of Washington for the NUCLEI SciDAC-3. The NUCLEI -project, as defined by the scope of work, will develop, implement and run codes for large-scale computations of many topics in low-energy nuclear physics. Physics to be studied include the properties of nuclei and nuclear decays, nuclear structure and reactions, and the properties of nuclear matter. The computational techniques to be used include Quantum Monte Carlo, Configuration Interaction, Coupled Cluster, and Density Functional methods. The research program will emphasize areas of high interest to current and possible future DOE nuclear physics facilities, including ATLAS andmore » FRIB (nuclear structure and reactions, and nuclear astrophysics), TJNAF (neutron distributions in nuclei, few body systems, and electroweak processes), NIF (thermonuclear reactions), MAJORANA and FNPB (neutrino-less double-beta decay and physics beyond the Standard Model), and LANSCE (fission studies).« less

The effects of exercise and stress on the survival and maturation of adult-generated granule cells

PubMed Central

Snyder, Jason S.; Glover, Lucas R.; Sanzone, Kaitlin M.; Kamhi, J. Frances; Cameron, Heather A.

2009-01-01

Stress strongly inhibits proliferation of granule cell precursors in the dentate gyrus, while voluntary running has the opposite effect. Few studies, however, have examined the possible effects of these environmental manipulations on the maturation and survival of young granule cells. We examined number of surviving granule cells and the proportion of young neurons that were functionally mature, as defined by seizure-induced immediate-early gene expression, in 14 and 21 day-old granule cells in mice that were given access to a running wheel, restrained daily for 2 hours, or given no treatment during this period. Importantly, treatments began two days after BrdU injection, to isolate effects on survival from those on cell proliferation. We found a large increase in granule cell survival in running mice compared with controls at both time points. In addition, running increased the proportion of granule cells expressing the immediate-early gene Arc in response to seizures, suggesting that it speeds incorporation into circuits, i.e., functional maturation. Stressed mice showed no change in Arc expression, compared to control animals, but, surprisingly, showed a transient increase in survival of 14-day-old granule cells, which was gone 7 days later. Examination of cell proliferation, using the endogenous mitotic marker proliferating cell nuclear antigen (PCNA) showed an increase in cell proliferation after 12 days of running but not after 19 days of running. The number of proliferating cells was unchanged 24 hours after the 12th or 19th episode of daily restraint stress. These findings demonstrate that running has strong effects on survival and maturation of young granule cells as well as their birth and that stress can have positive but short-lived effects on granule cell survival. PMID:19156854

A Perspective on DNA Microarrays in Pathology Research and Practice

PubMed Central

Pollack, Jonathan R.

2007-01-01

DNA microarray technology matured in the mid-1990s, and the past decade has witnessed a tremendous growth in its application. DNA microarrays have provided powerful tools for pathology researchers seeking to describe, classify, and understand human disease. There has also been great expectation that the technology would advance the practice of pathology. This review highlights some of the key contributions of DNA microarrays to experimental pathology, focusing in the area of cancer research. Also discussed are some of the current challenges in translating utility to clinical practice. PMID:17600117

Improvement in the amine glass platform by bubbling method for a DNA microarray

PubMed Central

Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool. PMID:26468293

Improvement in the amine glass platform by bubbling method for a DNA microarray.

PubMed

Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool.

The effect of column purification on cDNA indirect labelling for microarrays

PubMed Central

Molas, M Lia; Kiss, John Z

2007-01-01

Background The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. Results We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Conclusion Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays. PMID:17597522

The effect of column purification on cDNA indirect labelling for microarrays.

PubMed

Molas, M Lia; Kiss, John Z

2007-06-27

The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays.

MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

PubMed

Huerta, Mario; Munyi, Marc; Expósito, David; Querol, Enric; Cedano, Juan

2014-06-15

The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Marker-gene database tool: http://ibb.uab.es/mgdb © The Author 2014. Published by Oxford University Press.

Use of diagnostic accuracy as a metric for evaluating laboratory proficiency with microarray assays using mixed-tissue RNA reference samples.

PubMed

Pine, P S; Boedigheimer, M; Rosenzweig, B A; Turpaz, Y; He, Y D; Delenstarr, G; Ganter, B; Jarnagin, K; Jones, W D; Reid, L H; Thompson, K L

2008-11-01

Effective use of microarray technology in clinical and regulatory settings is contingent on the adoption of standard methods for assessing performance. The MicroArray Quality Control project evaluated the repeatability and comparability of microarray data on the major commercial platforms and laid the groundwork for the application of microarray technology to regulatory assessments. However, methods for assessing performance that are commonly applied to diagnostic assays used in laboratory medicine remain to be developed for microarray assays. A reference system for microarray performance evaluation and process improvement was developed that includes reference samples, metrics and reference datasets. The reference material is composed of two mixes of four different rat tissue RNAs that allow defined target ratios to be assayed using a set of tissue-selective analytes that are distributed along the dynamic range of measurement. The diagnostic accuracy of detected changes in expression ratios, measured as the area under the curve from receiver operating characteristic plots, provides a single commutable value for comparing assay specificity and sensitivity. The utility of this system for assessing overall performance was evaluated for relevant applications like multi-laboratory proficiency testing programs and single-laboratory process drift monitoring. The diagnostic accuracy of detection of a 1.5-fold change in signal level was found to be a sensitive metric for comparing overall performance. This test approaches the technical limit for reliable discrimination of differences between two samples using this technology. We describe a reference system that provides a mechanism for internal and external assessment of laboratory proficiency with microarray technology and is translatable to performance assessments on other whole-genome expression arrays used for basic and clinical research.

2008 Microarray Research Group (MARG Survey): Sensing the State of Microarray Technology

EPA Science Inventory

Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution and transformation, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. Th...

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

Collins, Benjamin S.; Hamilton, Steven P.; Jarrett, Michael G.

This report describes the performance improvements made to the VERA Core Simulator (VERA-CS) during FY2016. The development of the VERA Core Simulator has focused on the capability needed to deplete physical reactors and help solve various problems; this capability required the accurate simulation of many operating cycles of a nuclear power plant. The first section of this report introduces two test problems used to assess the run-time performance of VERA-CS using a source dated February 2016. The next section provides a brief overview of the major modifications made to decrease the computational cost. Following the descriptions of the major improvements,more » the run-time for each improvement is shown. Conclusions on the work are presented, and further follow-on performance improvements are suggested.« less

Impact of genetic strain on body fat loss, food consumption, metabolism, ventilation, and motor activity in free running female rats

EPA Science Inventory

Nuclear magnetic resonance (NMR) based body composition analysis is an idea means of assessing changes in relative proportions of fat, lean, and fluid in rodents non­ invasively. While the data are not as accurate as convent ional chemical analysis, the systems allow one to follo...

Geotechnical studies relevant to the containment of underground nuclear explosions at the Nevada Test Site

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

Heuze, F.E.

1982-05-01

The Department of Energy and the Department of Defense are actively pursuing a program of nuclear weapons testing by underground explosions at the Nevada Test Site (NTS). Over the past 11 years, scores of tests have been conducted and the safety record is very good. In the short run, emphasis is put on preventing the release of radioactive materials into the atmosphere. In the long run, the subsidence and collapse of the ground above the nuclear cavities also are matters of interest. Currently, estimation of containment is based mostly on empiricism derived from extensive experience and on a combination ofmore » physical/mechanical testing and numerical modeling. When measured directly, the mechanical material properties are obtained from short-term laboratory tests on small, conventional samples. This practice does not determine the large effects of scale and time on measured stiffnesses and strengths of geological materials. Because of the limited data base of properties and in situ conditions, the input to otherwise fairly sophisticated computer programs is subject to several simplifying assumptions; some of them can have a nonconservative impact on the calculated results. As for the long-term, subsidence and collapse phenomena simply have not been studied to any significant degree. This report examines the geomechanical aspects of procedures currently used to estimate containment of undergroung explosions at NTS. Based on this examination, it is concluded that state-of-the-art geological engineering practice in the areas of field testing, large scale laboratory measurements, and numerical modeling can be drawn upon to complement the current approach.« less

THE ABRF-MARG MICROARRAY SURVEY 2004: TAKING THE PULSE OF THE MICROARRAY FIELD

EPA Science Inventory

Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. The goal of the surve...

Contributions to Statistical Problems Related to Microarray Data

ERIC Educational Resources Information Center

Hong, Feng

2009-01-01

Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

PubMed Central

2010-01-01

Background The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems'-level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log2- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets. PMID:20128918

You can hide but you have to run: Direct detection with vector mediators

DOE PAGES

D’Eramo, Francesco; Kavanagh, Bradley J.; Panci, Paolo

2016-08-18

We study direct detection in simplified models of Dark Matter (DM) in which interactions with Standard Model (SM) fermions are mediated by a heavy vector boson. We consider fully general, gauge-invariant couplings between the SM, the mediator and both scalar and fermion DM. We account for the evolution of the couplings between the energy scale of the mediator mass and the nuclear energy scale. This running arises from virtual effects of SM particles and its inclusion is not optional. We compare bounds on the mediator mass from direct detection experiments with and without accounting for the running. In some casesmore » the inclusion of these effects changes the bounds by several orders of magnitude, as a consequence of operator mixing which generates new interactions at low energy. We also highlight the importance of these effects when translating LHC limits on the mediator mass into bounds on the direct detection cross section. For an axial-vector mediator, the running can alter the derived bounds on the spin-dependent DM-nucleon cross section by a factor of two or more. Lastly, we provide tools to facilitate the inclusion of these effects in future studies: general approximate expressions for the low energy couplings and a public code runDM to evolve the couplings between arbitrary energy scales.« less

You can hide but you have to run: Direct detection with vector mediators

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

D’Eramo, Francesco; Kavanagh, Bradley J.; Panci, Paolo

We study direct detection in simplified models of Dark Matter (DM) in which interactions with Standard Model (SM) fermions are mediated by a heavy vector boson. We consider fully general, gauge-invariant couplings between the SM, the mediator and both scalar and fermion DM. We account for the evolution of the couplings between the energy scale of the mediator mass and the nuclear energy scale. This running arises from virtual effects of SM particles and its inclusion is not optional. We compare bounds on the mediator mass from direct detection experiments with and without accounting for the running. In some casesmore » the inclusion of these effects changes the bounds by several orders of magnitude, as a consequence of operator mixing which generates new interactions at low energy. We also highlight the importance of these effects when translating LHC limits on the mediator mass into bounds on the direct detection cross section. For an axial-vector mediator, the running can alter the derived bounds on the spin-dependent DM-nucleon cross section by a factor of two or more. Lastly, we provide tools to facilitate the inclusion of these effects in future studies: general approximate expressions for the low energy couplings and a public code runDM to evolve the couplings between arbitrary energy scales.« less

A proposed metric for assessing the measurement quality of individual microarrays

PubMed Central

Kim, Kyoungmi; Page, Grier P; Beasley, T Mark; Barnes, Stephen; Scheirer, Katherine E; Allison, David B

2006-01-01

Background High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface. Results We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets. Conclusion We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements. PMID:16430768

Evaluation of a Field-Portable DNA Microarray Platform and Nucleic Acid Amplification Strategies for the Detection of Arboviruses, Arthropods, and Bloodmeals

PubMed Central

Grubaugh, Nathan D.; Petz, Lawrence N.; Melanson, Vanessa R.; McMenamy, Scott S.; Turell, Michael J.; Long, Lewis S.; Pisarcik, Sarah E.; Kengluecha, Ampornpan; Jaichapor, Boonsong; O'Guinn, Monica L.; Lee, John S.

2013-01-01

Highly multiplexed assays, such as microarrays, can benefit arbovirus surveillance by allowing researchers to screen for hundreds of targets at once. We evaluated amplification strategies and the practicality of a portable DNA microarray platform to analyze virus-infected mosquitoes. The prototype microarray design used here targeted the non-structural protein 5, ribosomal RNA, and cytochrome b genes for the detection of flaviviruses, mosquitoes, and bloodmeals, respectively. We identified 13 of 14 flaviviruses from virus inoculated mosquitoes and cultured cells. Additionally, we differentiated between four mosquito genera and eight whole blood samples. The microarray platform was field evaluated in Thailand and successfully identified flaviviruses (Culex flavivirus, dengue-3, and Japanese encephalitis viruses), differentiated between mosquito genera (Aedes, Armigeres, Culex, and Mansonia), and detected mammalian bloodmeals (human and dog). We showed that the microarray platform and amplification strategies described here can be used to discern specific information on a wide variety of viruses and their vectors. PMID:23249687

A molecular beacon microarray based on a quantum dot label for detecting single nucleotide polymorphisms.

PubMed

Guo, Qingsheng; Bai, Zhixiong; Liu, Yuqian; Sun, Qingjiang

2016-03-15

In this work, we report the application of streptavidin-coated quantum dot (strAV-QD) in molecular beacon (MB) microarray assays by using the strAV-QD to label the immobilized MB, avoiding target labeling and meanwhile obviating the use of amplification. The MBs are stem-loop structured oligodeoxynucleotides, modified with a thiol and a biotin at two terminals of the stem. With the strAV-QD labeling an "opened" MB rather than a "closed" MB via streptavidin-biotin reaction, a sensitive and specific detection of label-free target DNA sequence is demonstrated by the MB microarray, with a signal-to-background ratio of 8. The immobilized MBs can be perfectly regenerated, allowing the reuse of the microarray. The MB microarray also is able to detect single nucleotide polymorphisms, exhibiting genotype-dependent fluorescence signals. It is demonstrated that the MB microarray can perform as a 4-to-2 encoder, compressing the genotype information into two outputs. Copyright © 2015 Elsevier B.V. All rights reserved.

Securing Nuclear Materials: The 2012 Summit and Issues for Congress

DTIC Science & Technology

2012-03-07

Republic of Korea, the Russian Federation, Saudi Arabia, Singapore, Switzerland, South Africa, Spain, Sweden, Thailand, Turkey , United Arab Emirates, the ...of the nuclear terrorism threat runs highest. In addition, the Russian Federation said it would be helping the United States prepare the groundwork...Minister Netanyahu. Press reports quote an Israeli official as saying that the Prime Minister decided not to attend due to concerns that Egypt or Turkey

Evaluating concentration estimation errors in ELISA microarray experiments

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

Daly, Don S.; White, Amanda M.; Varnum, Susan M.

Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to predict a protein concentration in a sample. Deploying ELISA in a microarray format permits simultaneous prediction of the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Evaluating prediction error is critical to interpreting biological significance and improving the ELISA microarray process. Evaluating prediction error must be automated to realize a reliable high-throughput ELISA microarray system. Methods: In this paper, we present a statistical method based on propagation of error to evaluate prediction errors in the ELISA microarray process. Althoughmore » propagation of error is central to this method, it is effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization and statistical diagnostics when evaluating ELISA microarray prediction errors. We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of prediction errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error.« less

Simulations of the Neutron Gas in the Inner Crust of Neutron Stars

NASA Astrophysics Data System (ADS)

Vandegriff, Elizabeth; Horowitz, Charles; Caplan, Matthew

2017-09-01

Inside neutron stars, the structures known as `nuclear pasta' are found in the crust. This pasta forms near nuclear density as nucleons arrange in spaghetti- or lasagna-like structures to minimize their energy. We run classical molecular dynamics simulations to visualize the geometry of this pasta and study the distribution of nucleons. In the simulations, we observe that the pasta is embedded in a gas of neutrons, which we call the `sauce'. In this work, we developed two methods for determining the density of neutrons in the gas, one which is accurate at low temperatures and a second which justifies an extrapolation at high temperatures. Running simulations with no Coulomb interactions, we find that the neutron density increases linearly with temperature for every proton fraction we simulated. NSF REU Grant PHY-1460882 at Indiana University.

Constructing Tissue Microarrays: Protocols and Methods Considering Potential Advantages and Disadvantages for Downstream Use.

PubMed

Bingle, Lynne; Fonseca, Felipe P; Farthing, Paula M

2017-01-01

Tissue microarrays were first constructed in the 1980s but were used by only a limited number of researchers for a considerable period of time. In the last 10 years there has been a dramatic increase in the number of publications describing the successful use of tissue microarrays in studies aimed at discovering and validating biomarkers. This, along with the increased availability of both manual and automated microarray builders on the market, has encouraged even greater use of this novel and powerful tool. This chapter describes the basic techniques required to build a tissue microarray using a manual method in order that the theory behind the practical steps can be fully explained. Guidance is given to ensure potential disadvantages of the technique are fully considered.

A Human Lectin Microarray for Sperm Surface Glycosylation Analysis *

PubMed Central

Sun, Yangyang; Cheng, Li; Gu, Yihua; Xin, Aijie; Wu, Bin; Zhou, Shumin; Guo, Shujuan; Liu, Yin; Diao, Hua; Shi, Huijuan; Wang, Guangyu; Tao, Sheng-ce

2016-01-01

Glycosylation is one of the most abundant and functionally important protein post-translational modifications. As such, technology for efficient glycosylation analysis is in high demand. Lectin microarrays are a powerful tool for such investigations and have been successfully applied for a variety of glycobiological studies. However, most of the current lectin microarrays are primarily constructed from plant lectins, which are not well suited for studies of human glycosylation because of the extreme complexity of human glycans. Herein, we constructed a human lectin microarray with 60 human lectin and lectin-like proteins. All of the lectins and lectin-like proteins were purified from yeast, and most showed binding to human glycans. To demonstrate the applicability of the human lectin microarray, human sperm were probed on the microarray and strong bindings were observed for several lectins, including galectin-1, 7, 8, GalNAc-T6, and ERGIC-53 (LMAN1). These bindings were validated by flow cytometry and fluorescence immunostaining. Further, mass spectrometry analysis showed that galectin-1 binds several membrane-associated proteins including heat shock protein 90. Finally, functional assays showed that binding of galectin-8 could significantly enhance the acrosome reaction within human sperms. To our knowledge, this is the first construction of a human lectin microarray, and we anticipate it will find wide use for a range of human or mammalian studies, alone or in combination with plant lectin microarrays. PMID:27364157

Emerging Use of Gene Expression Microarrays in Plant Physiology

DOE PAGES

Wullschleger, Stan D.; Difazio, Stephen P.

2003-01-01

Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology weremore » selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.« less

Possible Improvements to MCNP6 and its CEM/LAQGSM Event-Generators

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

Mashnik, Stepan Georgievich

2015-08-04

This report is intended to the MCNP6 developers and sponsors of MCNP6. It presents a set of suggested possible future improvements to MCNP6 and to its CEM03.03 and LAQGSM03.03 event-generators. A few suggested modifications of MCNP6 are quite simple, aimed at avoiding possible problems with running MCNP6 on various computers, i.e., these changes are not expected to change or improve any results, but should make the use of MCNP6 easier; such changes are expected to require limited man-power resources. On the other hand, several other suggested improvements require a serious further development of nuclear reaction models, are expected to improvemore » significantly the predictive power of MCNP6 for a number of nuclear reactions; but, such developments require several years of work by real experts on nuclear reactions.« less

"Hit-and-Run" transcription: de novo transcription initiated by a transient bZIP1 "hit" persists after the "run".

PubMed

Doidy, Joan; Li, Ying; Neymotin, Benjamin; Edwards, Molly B; Varala, Kranthi; Gresham, David; Coruzzi, Gloria M

2016-02-03

Dynamic transcriptional regulation is critical for an organism's response to environmental signals and yet remains elusive to capture. Such transcriptional regulation is mediated by master transcription factors (TF) that control large gene regulatory networks. Recently, we described a dynamic mode of TF regulation named "hit-and-run". This model proposes that master TF can interact transiently with a set of targets, but the transcription of these transient targets continues after the TF dissociation from the target promoter. However, experimental evidence validating active transcription of the transient TF-targets is still lacking. Here, we show that active transcription continues after transient TF-target interactions by tracking de novo synthesis of RNAs made in response to TF nuclear import. To do this, we introduced an affinity-labeled 4-thiouracil (4tU) nucleobase to specifically isolate newly synthesized transcripts following conditional TF nuclear import. Thus, we extended the TARGET system (Transient Assay Reporting Genome-wide Effects of Transcription factors) to include 4tU-labeling and named this new technology TARGET-tU. Our proof-of-principle example is the master TF Basic Leucine Zipper 1 (bZIP1), a central integrator of metabolic signaling in plants. Using TARGET-tU, we captured newly synthesized mRNAs made in response to bZIP1 nuclear import at a time when bZIP1 is no longer detectably bound to its target. Thus, the analysis of de novo transcripomics demonstrates that bZIP1 may act as a catalyst TF to initiate a transcriptional complex ("hit"), after which active transcription by RNA polymerase continues without the TF being bound to the gene promoter ("run"). Our findings provide experimental proof for active transcription of transient TF-targets supporting a "hit-and-run" mode of action. This dynamic regulatory model allows a master TF to catalytically propagate rapid and broad transcriptional responses to changes in environment. Thus, the functional read-out of de novo transcripts produced by transient TF-target interactions allowed us to capture new models for genome-wide transcriptional control.

Improved dark matter search results from PICO-2L Run 2

DOE PAGES

Amole, C.

2016-03-01

New data are reported from a second run of the 2-liter PICO-2L C 3F 8 bubble chamber with a total exposure of 129 kg-days at a thermodynamic threshold energy of 3.3 keV. These data show that measures taken to control particulate contamination in the superheated fluid resulted in the absence of the anomalous background events observed in the first run of this bubble chamber. One single nuclear-recoil event was observed in the data, consistent both with the predicted background rate from neutrons and with the observed rate of unambiguous multiple-bubble neutron scattering events. The chamber exhibits the same excellent electron-recoil and alphamore » decay rejection as was previously reported. These data provide the most stringent direct detection constraints on weakly interacting massive particle (WIMP)-proton spin-dependent scattering to date for WIMP masses <50 GeV/c 2.« less

Liver kinase B1 inhibits the expression of inflammation-related genes postcontraction in skeletal muscle

PubMed Central

Chen, Ting; Moore, Timothy M.; Ebbert, Mark T. W.; McVey, Natalie L.; Madsen, Steven R.; Hallowell, David M.; Harris, Alexander M.; Char, Robin E.; Mackay, Ryan P.; Hancock, Chad R.; Hansen, Jason M.; Kauwe, John S.

2016-01-01

Skeletal muscle-specific liver kinase B1 (LKB1) knockout mice (skmLKB1-KO) exhibit elevated mitogen-activated protein kinase (MAPK) signaling after treadmill running. MAPK activation is also associated with inflammation-related signaling in skeletal muscle. Since exercise can induce muscle damage, and inflammation is a response triggered by damaged tissue, we therefore hypothesized that LKB1 plays an important role in dampening the inflammatory response to muscle contraction, and that this may be due in part to increased susceptibility to muscle damage with contractions in LKB1-deficient muscle. Here we studied the inflammatory response and muscle damage with in situ muscle contraction or downhill running. After in situ muscle contractions, the phosphorylation of both NF-κB and STAT3 was increased more in skmLKB1-KO vs. wild-type (WT) muscles. Analysis of gene expression via microarray and RT-PCR shows that expression of many inflammation-related genes increased after contraction only in skmLKB1-KO muscles. This was associated with mild skeletal muscle fiber membrane damage in skmLKB1-KO muscles. Gene markers of oxidative stress were also elevated in skmLKB1-KO muscles after contraction. Using the downhill running model, we observed significantly more muscle damage after running in skmLKB1-KO mice, and this was associated with greater phosphorylation of both Jnk and STAT3 and increased expression of SOCS3 and Fos. In conclusion, we have shown that the lack of LKB1 in skeletal muscle leads to an increased inflammatory state in skeletal muscle that is exacerbated by muscle contraction. Increased susceptibility of the muscle to damage may underlie part of this response. PMID:26796753

Analysis of High-Throughput ELISA Microarray Data

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

White, Amanda M.; Daly, Don S.; Zangar, Richard C.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

Enhancing Results of Microarray Hybridizations Through Microagitation

PubMed Central

Toegl, Andreas; Kirchner, Roland; Gauer, Christoph; Wixforth, Achim

2003-01-01

Protein and DNA microarrays have become a standard tool in proteomics/genomics research. In order to guarantee fast and reproducible hybridization results, the diffusion limit must be overcome. Surface acoustic wave (SAW) micro-agitation chips efficiently agitate the smallest sample volumes (down to 10 μL and below) without introducing any dead volume. The advantages are reduced reaction time, increased signal-to-noise ratio, improved homogeneity across the microarray, and better slide-to-slide reproducibility. The SAW micromixer chips are the heart of the Advalytix ArrayBooster, which is compatible with all microarrays based on the microscope slide format. PMID:13678150

Contributions to the NUCLEI SciDAC-3 Project

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

Bogner, Scott; Nazarewicz, Witek

This is the Final Report for Michigan State University for the NUCLEI SciDAC-3 project. The NUCLEI project, as defined by the scope of work, has developed, implemented and run codes for large-scale computations of many topics in low-energy nuclear physics. Physics studied included the properties of nuclei and nuclear decays, nuclear structure and reactions, and the properties of nuclear matter. The computational techniques used included Configuration Interaction, Coupled Cluster, and Density Functional methods. The research program emphasized areas of high interest to current and possible future DOE nuclear physics facilities, including ATLAS at ANL and FRIB at MSU (nuclear structuremore » and reactions, and nuclear astrophysics), TJNAF (neutron distributions in nuclei, few body systems, and electroweak processes), NIF (thermonuclear reactions), MAJORANA and FNPB (neutrinoless double-beta decay and physics beyond the Standard Model), and LANSCE (fission studies).« less

Optimal Control of Shock Wave Turbulent Boundary Layer Interactions Using Micro-Array Actuation

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Tinapple, Jon; Surber, Lewis

2006-01-01

The intent of this study on micro-array flow control is to demonstrate the viability and economy of Response Surface Methodology (RSM) to determine optimal designs of micro-array actuation for controlling the shock wave turbulent boundary layer interactions within supersonic inlets and compare these concepts to conventional bleed performance. The term micro-array refers to micro-actuator arrays which have heights of 25 to 40 percent of the undisturbed supersonic boundary layer thickness. This study covers optimal control of shock wave turbulent boundary layer interactions using standard micro-vane, tapered micro-vane, and standard micro-ramp arrays at a free stream Mach number of 2.0. The effectiveness of the three micro-array devices was tested using a shock pressure rise induced by the 10 shock generator, which was sufficiently strong as to separate the turbulent supersonic boundary layer. The overall design purpose of the micro-arrays was to alter the properties of the supersonic boundary layer by introducing a cascade of counter-rotating micro-vortices in the near wall region. In this manner, the impact of the shock wave boundary layer (SWBL) interaction on the main flow field was minimized without boundary bleed.

Enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines.

PubMed

Tra, Yolande V; Evans, Irene M

2010-01-01

BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.

Creation of antifouling microarrays by photopolymerization of zwitterionic compounds for protein assay and cell patterning.

PubMed

Sun, Xiuhua; Wang, Huaixin; Wang, Yuanyuan; Gui, Taijiang; Wang, Ke; Gao, Changlu

2018-04-15

Nonspecific binding or adsorption of biomolecules presents as a major obstacle to higher sensitivity, specificity and reproducibility in microarray technology. We report herein a method to fabricate antifouling microarray via photopolymerization of biomimetic betaine compounds. In brief, carboxybetaine methacrylate was polymerized as arrays for protein sensing, while sulfobetaine methacrylate was polymerized as background. With the abundant carboxyl groups on array surfaces and zwitterionic polymers on the entire surfaces, this microarray allows biomolecular immobilization and recognition with low nonspecific interactions due to its antifouling property. Therefore, low concentration of target molecules can be captured and detected by this microarray. It was proved that a concentration of 10ngmL -1 bovine serum albumin in the sample matrix of bovine serum can be detected by the microarray derivatized with anti-bovine serum albumin. Moreover, with proper hydrophilic-hydrophobic designs, this approach can be applied to fabricate surface-tension droplet arrays, which allows surface-directed cell adhesion and growth. These light controllable approaches constitute a clear improvement in the design of antifouling interfaces, which may lead to greater flexibility in the development of interfacial architectures and wider application in blood contact microdevices. Copyright © 2017 Elsevier B.V. All rights reserved.

Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

PubMed Central

Evans, Irene M.

2010-01-01

BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954

A highly oriented hybrid microarray modified electrode fabricated by a template-free method for ultrasensitive electrochemical DNA recognition

NASA Astrophysics Data System (ADS)

Shi, Lei; Chu, Zhenyu; Dong, Xueliang; Jin, Wanqin; Dempsey, Eithne

2013-10-01

Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and influence the morphologies of hybrid films. A highly oriented hybrid microarray was formed on the highly aligned and vertical SAMs of 1,4-benzenedithiol molecules with rigid backbones, which afforded an intense structure-directing power for the oriented growth of hybrid crystals. Additionally, the density of the microarray could be adjusted by controlling the surface coverage of assembled molecules. Based on the hybrid microarray modified electrode with a large specific area (ca. 10 times its geometrical area), a label-free electrochemical DNA biosensor was constructed for the detection of an oligonucleotide fragment of the avian flu virus H5N1. The DNA biosensor displayed a significantly low detection limit of 5 pM (S/N = 3), a wide linear response from 10 pM to 10 nM, as well as excellent selectivity, good regeneration and high stability. We expect that the proposed template-free method can provide a new reference for the fabrication of a highly oriented hybrid array and the as-prepared microarray modified electrode will be a promising paradigm in constructing highly sensitive and selective biosensors.Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and influence the morphologies of hybrid films. A highly oriented hybrid microarray was formed on the highly aligned and vertical SAMs of 1,4-benzenedithiol molecules with rigid backbones, which afforded an intense structure-directing power for the oriented growth of hybrid crystals. Additionally, the density of the microarray could be adjusted by controlling the surface coverage of assembled molecules. Based on the hybrid microarray modified electrode with a large specific area (ca. 10 times its geometrical area), a label-free electrochemical DNA biosensor was constructed for the detection of an oligonucleotide fragment of the avian flu virus H5N1. The DNA biosensor displayed a significantly low detection limit of 5 pM (S/N = 3), a wide linear response from 10 pM to 10 nM, as well as excellent selectivity, good regeneration and high stability. We expect that the proposed template-free method can provide a new reference for the fabrication of a highly oriented hybrid array and the as-prepared microarray modified electrode will be a promising paradigm in constructing highly sensitive and selective biosensors. Electronic supplementary information (ESI) available: Four-probe method for determining the conductivity of the hybrid crystal (Fig. S1); stability comparisons of the hybrid films (Fig. S2); FESEM images of the hybrid microarray (Fig. S3); electrochemical characterizations of the hybrid films (Fig. S4); DFT simulations (Fig. S5); cross-sectional FESEM image of the hybrid microarray (Fig. S6); regeneration and stability tests of the DNA biosensor (Fig. S7). See DOI: 10.1039/c3nr03097k

Hybridization chain reaction amplification for highly sensitive fluorescence detection of DNA with dextran coated microarrays.

PubMed

Chao, Jie; Li, Zhenhua; Li, Jing; Peng, Hongzhen; Su, Shao; Li, Qian; Zhu, Changfeng; Zuo, Xiaolei; Song, Shiping; Wang, Lianhui; Wang, Lihua

2016-07-15

Microarrays of biomolecules hold great promise in the fields of genomics, proteomics, and clinical assays on account of their remarkably parallel and high-throughput assay capability. However, the fluorescence detection used in most conventional DNA microarrays is still limited by sensitivity. In this study, we have demonstrated a novel universal and highly sensitive platform for fluorescent detection of sequence specific DNA at the femtomolar level by combining dextran-coated microarrays with hybridization chain reaction (HCR) signal amplification. Three-dimensional dextran matrix was covalently coated on glass surface as the scaffold to immobilize DNA recognition probes to increase the surface binding capacity and accessibility. DNA nanowire tentacles were formed on the matrix surface for efficient signal amplification by capturing multiple fluorescent molecules in a highly ordered way. By quantifying microscopic fluorescent signals, the synergetic effects of dextran and HCR greatly improved sensitivity of DNA microarrays, with a detection limit of 10fM (1×10(5) molecules). This detection assay could recognize one-base mismatch with fluorescence signals dropped down to ~20%. This cost-effective microarray platform also worked well with samples in serum and thus shows great potential for clinical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

PubMed Central

2010-01-01

Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions. PMID:20509979

Application of photogrammetry to work in nuclear power plants in operation

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

Abella, A.P.; Balsalobre, F.S.

1987-01-01

In the evolution of requirements applicable to nuclear safety-related components and the obtainment of as-built data for a great variety of jobs performed in nuclear power plants, photogrammetry proves to be a very useful tool for design, manufacture, erection, maintenance, and operation. The METADAT data acquisition system developed by Empresarios Agrupados has a wide range of applications, depending on the degree of precision required. The F-3 system is capable of obtaining a precision of 1:10.000, to 0.10 mm in determined zones, through the use of wide-angle lenses without optical distortions or aberrations. In cases where such a high degree ofmore » precision is not necessary, as in piping run modifications, conduits, or cable trays, the F-2 system can be used.« less

Human Endometriosis Tissue Microarray Reveals Site-specific Expression of Estrogen Receptors, Progesterone Receptor, and Ki67.

PubMed

Colón-Caraballo, Mariano; García, Miosotis; Mendoza, Adalberto; Flores, Idhaliz

2018-04-07

Most available therapies for endometriosis are hormone-based and generally broadly used without taking into consideration the ovarian hormone receptor expression status. This contrasts strikingly with the standard of care for other hormone-based conditions such as breast cancer. We therefore aimed to characterize the expression of ovarian steroid hormone receptors for estrogen alpha (ESR1), estrogen beta (ESR2), and progesterone (PGR) in different types of endometriotic lesions and eutopic endometrium from women with endometriosis and controls using a tissue microarray (TMA). Nuclear expression levels of the receptors were analyzed by tissue (ie, ectopic vs. eutopic endometrium) and cell type (ie, glands vs. stroma). Ovarian lesions showed the lowest expression of ESR1 and PGR, and the highest expression of ESR2, whereas the fallopian tube lesions showed high expression of the 3 receptors. Differences among endometria included lower expression of ESR1 and higher expression of ESR2 in stroma of proliferative endometrium from patients versus patients, and a trend towards loss of PGR nuclear positivity in proliferative endometrium from patients. The largest ESR2:ESR1 ratios were observed in ovarian lesions and secretory endometrium. The highest proportion of samples with >10% Ki67 positive nuclei was in glands of fallopian tube (54%) and extrapelvic lesions (75%); 60% of glands of secretory endometrium from patients had >10% Ki67 positivity compared with only 15% in controls. Our results provide a better understanding of endometriosis heterogeneity by revealing lesion type-specific differences and case-by-case variability in the expression of ovarian hormone receptors. This knowledge could potentially predict individual responses to hormone therapies, and set the basis for the application of personalized medicine approaches for women with endometriosis.

DNA microarray‐based analysis of voluntary resistance wheel running reveals novel transcriptome leading robust hippocampal plasticity

PubMed Central

Lee, Min Chul; Rakwal, Randeep; Shibato, Junko; Inoue, Koshiro; Chang, Hyukki; Soya, Hideaki

2014-01-01

Abstract In two separate experiments, voluntary resistance wheel running with 30% of body weight (RWR), rather than wheel running (WR), led to greater enhancements, including adult hippocampal neurogenesis and cognitive functions, in conjunction with hippocampal brain‐derived neurotrophic factor (BDNF) signaling (Lee et al., J Appl Physiol, 2012; Neurosci Lett., 2013). Here we aimed to unravel novel molecular factors and gain insight into underlying molecular mechanisms for RWR‐enhanced hippocampal functions; a high‐throughput whole‐genome DNA microarray approach was applied to rats performing voluntary running for 4 weeks. RWR rats showed a significant decrease in average running distances although average work levels increased immensely, by about 11‐fold compared to WR, resulting in muscular adaptation for the fast‐twitch plantaris muscle. Global transcriptome profiling analysis identified 128 (sedentary × WR) and 169 (sedentary × RWR) up‐regulated (>1.5‐fold change), and 97 (sedentary × WR) and 468 (sedentary × RWR) down‐regulated (<0.75‐fold change) genes. Functional categorization using both pathway‐ or specific‐disease‐state‐focused gene classifications and Ingenuity Pathway Analysis (IPA) revealed expression pattern changes in the major categories of disease and disorders, molecular functions, and physiological system development and function. Genes specifically regulated with RWR include the newly identified factors of NFATc1, AVPR1A, and FGFR4, as well as previously known factors, BDNF and CREB mRNA. Interestingly, RWR down‐regulated multiple inflammatory cytokines (IL1B, IL2RA, and TNF) and chemokines (CXCL1, CXCL10, CCL2, and CCR4) with the SYCP3, PRL genes, which are potentially involved in regulating hippocampal neuroplastic changes. These results provide understanding of the voluntary‐RWR‐related hippocampal transcriptome, which will open a window to the underlying mechanisms of the positive effects of exercise, with therapeutic value for enhancing hippocampal functions. PMID:25413326

geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research.

PubMed

Glez-Peña, Daniel; Díaz, Fernando; Hernández, Jesús M; Corchado, Juan M; Fdez-Riverola, Florentino

2009-06-18

Bioinformatics and medical informatics are two research fields that serve the needs of different but related communities. Both domains share the common goal of providing new algorithms, methods and technological solutions to biomedical research, and contributing to the treatment and cure of diseases. Although different microarray techniques have been successfully used to investigate useful information for cancer diagnosis at the gene expression level, the true integration of existing methods into day-to-day clinical practice is still a long way off. Within this context, case-based reasoning emerges as a suitable paradigm specially intended for the development of biomedical informatics applications and decision support systems, given the support and collaboration involved in such a translational development. With the goals of removing barriers against multi-disciplinary collaboration and facilitating the dissemination and transfer of knowledge to real practice, case-based reasoning systems have the potential to be applied to translational research mainly because their computational reasoning paradigm is similar to the way clinicians gather, analyze and process information in their own practice of clinical medicine. In addressing the issue of bridging the existing gap between biomedical researchers and clinicians who work in the domain of cancer diagnosis, prognosis and treatment, we have developed and made accessible a common interactive framework. Our geneCBR system implements a freely available software tool that allows the use of combined techniques that can be applied to gene selection, clustering, knowledge extraction and prediction for aiding diagnosis in cancer research. For biomedical researches, geneCBR expert mode offers a core workbench for designing and testing new techniques and experiments. For pathologists or oncologists, geneCBR diagnostic mode implements an effective and reliable system that can diagnose cancer subtypes based on the analysis of microarray data using a CBR architecture. For programmers, geneCBR programming mode includes an advanced edition module for run-time modification of previous coded techniques. geneCBR is a new translational tool that can effectively support the integrative work of programmers, biomedical researches and clinicians working together in a common framework. The code is freely available under the GPL license and can be obtained at http://www.genecbr.org.

Characterization and simulation of cDNA microarray spots using a novel mathematical model

PubMed Central

Kim, Hye Young; Lee, Seo Eun; Kim, Min Jung; Han, Jin Il; Kim, Bo Kyung; Lee, Yong Sung; Lee, Young Seek; Kim, Jin Hyuk

2007-01-01

Background The quality of cDNA microarray data is crucial for expanding its application to other research areas, such as the study of gene regulatory networks. Despite the fact that a number of algorithms have been suggested to increase the accuracy of microarray gene expression data, it is necessary to obtain reliable microarray images by improving wet-lab experiments. As the first step of a cDNA microarray experiment, spotting cDNA probes is critical to determining the quality of spot images. Results We developed a governing equation of cDNA deposition during evaporation of a drop in the microarray spotting process. The governing equation included four parameters: the surface site density on the support, the extrapolated equilibrium constant for the binding of cDNA molecules with surface sites on glass slides, the macromolecular interaction factor, and the volume constant of a drop of cDNA solution. We simulated cDNA deposition from the single model equation by varying the value of the parameters. The morphology of the resulting cDNA deposit can be classified into three types: a doughnut shape, a peak shape, and a volcano shape. The spot morphology can be changed into a flat shape by varying the experimental conditions while considering the parameters of the governing equation of cDNA deposition. The four parameters were estimated by fitting the governing equation to the real microarray images. With the results of the simulation and the parameter estimation, the phenomenon of the formation of cDNA deposits in each type was investigated. Conclusion This study explains how various spot shapes can exist and suggests which parameters are to be adjusted for obtaining a good spot. This system is able to explore the cDNA microarray spotting process in a predictable, manageable and descriptive manner. We hope it can provide a way to predict the incidents that can occur during a real cDNA microarray experiment, and produce useful data for several research applications involving cDNA microarrays. PMID:18096047

Screening Mammalian Cells on a Hydrogel: Functionalized Small Molecule Microarray.

PubMed

Zhu, Biwei; Jiang, Bo; Na, Zhenkun; Yao, Shao Q

2017-01-01

Mammalian cell-based microarray technology has gained wide attention, for its plethora of promising applications. The platform is able to provide simultaneous information on multiple parameters for a given target, or even multiple target proteins, in a complex biological system. Here we describe the preparation of mammalian cell-based microarrays using selectively captured of human prostate cancer cells (PC-3). This platform was then used in controlled drug release and measuring the associated drug effects on these cancer cells.

Single-Nucleotide Polymorphism-Microarray Ploidy Analysis of Paraffin-Embedded Products of Conception in Recurrent Pregnancy Loss Evaluations.

PubMed

Maslow, Bat-Sheva L; Budinetz, Tara; Sueldo, Carolina; Anspach, Erica; Engmann, Lawrence; Benadiva, Claudio; Nulsen, John C

2015-07-01

To compare the analysis of chromosome number from paraffin-embedded products of conception using single-nucleotide polymorphism (SNP) microarray with the recommended screening for the evaluation of couples presenting with recurrent pregnancy loss who do not have previous fetal cytogenetic data. We performed a retrospective cohort study including all women who presented for a new evaluation of recurrent pregnancy loss over a 2-year period (January 1, 2012, to December 31, 2013). All participants had at least two documented first-trimester losses and both the recommended screening tests and SNP microarray performed on at least one paraffin-embedded products of conception sample. Single-nucleotide polymorphism microarray identifies all 24 chromosomes (22 autosomes, X, and Y). Forty-two women with a total of 178 losses were included in the study. Paraffin-embedded products of conception from 62 losses were sent for SNP microarray. Single-nucleotide polymorphism microarray successfully diagnosed fetal chromosome number in 71% (44/62) of samples, of which 43% (19/44) were euploid and 57% (25/44) were noneuploid. Seven of 42 (17%) participants had abnormalities on recurrent pregnancy loss screening. The per-person detection rate for a cause of pregnancy loss was significantly higher in the SNP microarray (0.50; 95% confidence interval [CI] 0.36-0.64) compared with recurrent pregnancy loss evaluation (0.17; 95% CI 0.08-0.31) (P=.002). Participants with one or more euploid loss identified on paraffin-embedded products of conception were significantly more likely to have an abnormality on recurrent pregnancy loss screening than those with only noneuploid results (P=.028). The significance remained when controlling for age, number of losses, number of samples, and total pregnancies. These results suggest that SNP microarray testing of paraffin-embedded products of conception is a valuable tool for the evaluation of recurrent pregnancy loss in patients without prior fetal cytogenetic results. Recommended recurrent pregnancy loss screening was unnecessary in almost half the patients in our study. II.

The Choice of the Filtering Method in Microarrays Affects the Inference Regarding Dosage Compensation of the Active X-Chromosome

PubMed Central

Zeller, Tanja; Wild, Philipp S.; Truong, Vinh; Trégouët, David-Alexandre; Munzel, Thomas; Ziegler, Andreas; Cambien, François; Blankenberg, Stefan; Tiret, Laurence

2011-01-01

Background The hypothesis of dosage compensation of genes of the X chromosome, supported by previous microarray studies, was recently challenged by RNA-sequencing data. It was suggested that microarray studies were biased toward an over-estimation of X-linked expression levels as a consequence of the filtering of genes below the detection threshold of microarrays. Methodology/Principal Findings To investigate this hypothesis, we used microarray expression data from circulating monocytes in 1,467 individuals. In total, 25,349 and 1,156 probes were unambiguously assigned to autosomes and the X chromosome, respectively. Globally, there was a clear shift of X-linked expressions toward lower levels than autosomes. We compared the ratio of expression levels of X-linked to autosomal transcripts (X∶AA) using two different filtering methods: 1. gene expressions were filtered out using a detection threshold irrespective of gene chromosomal location (the standard method in microarrays); 2. equal proportions of genes were filtered out separately on the X and on autosomes. For a wide range of filtering proportions, the X∶AA ratio estimated with the first method was not significantly different from 1, the value expected if dosage compensation was achieved, whereas it was significantly lower than 1 with the second method, leading to the rejection of the hypothesis of dosage compensation. We further showed in simulated data that the choice of the most appropriate method was dependent on biological assumptions regarding the proportion of actively expressed genes on the X chromosome comparative to the autosomes and the extent of dosage compensation. Conclusion/Significance This study shows that the method used for filtering out lowly expressed genes in microarrays may have a major impact according to the hypothesis investigated. The hypothesis of dosage compensation of X-linked genes cannot be firmly accepted or rejected using microarray-based data. PMID:21912656

Soy consumption and histopathologic markers in breast tissue using tissue microarrays.

PubMed

Maskarinec, Gertraud; Erber, Eva; Verheus, Martijn; Hernandez, Brenda Y; Killeen, Jeffrey; Cashin, Suzanne; Cline, J Mark

2009-01-01

This study examined the relation of soy intake with hormonal and proliferation markers in benign and malignant breast tissue using tissue microarrays (TMAs). TMAs with up to 4 malignant and 4 benign tissue samples for 268 breast cancer cases were constructed. Soy intake in early life and in adulthood was assessed by questionnaire. The TMAs were stained for estrogen receptor (ER) alpha, ERbeta, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2/neu), proliferating cell nuclear antigen (PCNA), and Ki-67 using standard immunohistochemical methods. Logistic regression was applied for statistical analysis. A higher percentage of women showed positive marker expression in malignant than in benign tissue. With one exception, HER2/neu, no significant associations between soy intake and pathologic markers were observed. Early life soy intake was associated with lower HER2/neu and PCNA staining of malignant tissue. In benign tissue, early life soy intake showed higher ER and PR expression, but no difference in proliferation markers. The results of this investigation provide some assurance that soy intake does not adversely affect markers of proliferation. TMAs were shown to be a useful tool for epidemiologic research.

Generating unstructured nuclear reactor core meshes in parallel

DOE PAGES

Jain, Rajeev; Tautges, Timothy J.

2014-10-24

Recent advances in supercomputers and parallel solver techniques have enabled users to run large simulations problems using millions of processors. Techniques for multiphysics nuclear reactor core simulations are under active development in several countries. Most of these techniques require large unstructured meshes that can be hard to generate in a standalone desktop computers because of high memory requirements, limited processing power, and other complexities. We have previously reported on a hierarchical lattice-based approach for generating reactor core meshes. Here, we describe efforts to exploit coarse-grained parallelism during reactor assembly and reactor core mesh generation processes. We highlight several reactor coremore » examples including a very high temperature reactor, a full-core model of the Korean MONJU reactor, a ¼ pressurized water reactor core, the fast reactor Experimental Breeder Reactor-II core with a XX09 assembly, and an advanced breeder test reactor core. The times required to generate large mesh models, along with speedups obtained from running these problems in parallel, are reported. A graphical user interface to the tools described here has also been developed.« less

Long Duration Hot Hydrogen Exposure of Nuclear Thermal Rocket Materials

NASA Technical Reports Server (NTRS)

Litchford, Ron J.; Foote, John P.; Hickman, Robert; Dobson, Chris; Clifton, Scooter

2007-01-01

An arc-heater driven hyper-thermal convective environments simulator was recently developed and commissioned for long duration hot hydrogen exposure of nuclear thermal rocket materials. This newly established non-nuclear testing capability uses a high-power, multi-gas, wall-stabilized constricted arc-heater to .produce high-temperature pressurized hydrogen flows representative of nuclear reactor core environments, excepting radiation effects, and is intended to serve as a low cost test facility for the purpose of investigating and characterizing candidate fuel/structural materials and improving associated processing/fabrication techniques. Design and engineering development efforts are fully summarized, and facility operating characteristics are reported as determined from a series of baseline performance mapping runs and long duration capability demonstration tests.

EDGE3: A web-based solution for management and analysis of Agilent two color microarray experiments

PubMed Central

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-01-01

Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE3 provides a means for managing RNA samples and arrays during the hybridization process. EDGE3 is freely available for download at . PMID:19732451

EDGE(3): a web-based solution for management and analysis of Agilent two color microarray experiments.

PubMed

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-09-04

The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE(3) was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. EDGE(3) has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE(3) is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Here, we present EDGE(3), an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE(3) provides a means for managing RNA samples and arrays during the hybridization process. EDGE(3) is freely available for download at http://edge.oncology.wisc.edu/.

Cambridge Healthtech Institute's Third Annual Conference on Lab-on-a-Chip and Microarrays. 22-24 January 2001, Zurich, Switzerland.

PubMed

Jain, K K

2001-02-01

Cambridge Healthtech Institute's Third Annual Conference on Lab-on-a-Chip and Microarray technology covered the latest advances in this technology and applications in life sciences. Highlights of the meetings are reported briefly with emphasis on applications in genomics, drug discovery and molecular diagnostics. There was an emphasis on microfluidics because of the wide applications in laboratory and drug discovery. The lab-on-a-chip provides the facilities of a complete laboratory in a hand-held miniature device. Several microarray systems have been used for hybridisation and detection techniques. Oligonucleotide scanning arrays provide a versatile tool for the analysis of nucleic acid interactions and provide a platform for improving the array-based methods for investigation of antisense therapeutics. A method for analysing combinatorial DNA arrays using oligonucleotide-modified gold nanoparticle probes and a conventional scanner has considerable potential in molecular diagnostics. Various applications of microarray technology for high-throughput screening in drug discovery and single nucleotide polymorphisms (SNP) analysis were discussed. Protein chips have important applications in proteomics. With the considerable amount of data generated by the different technologies using microarrays, it is obvious that the reading of the information and its interpretation and management through the use of bioinformatics is essential. Various techniques for data analysis were presented. Biochip and microarray technology has an essential role to play in the evolving trends in healthcare, which integrate diagnosis with prevention/treatment and emphasise personalised medicines.

Temperature-controlled microintaglio printing for high-resolution micropatterning of RNA molecules.

PubMed

Kobayashi, Ryo; Biyani, Manish; Ueno, Shingo; Kumal, Subhashini Raj; Kuramochi, Hiromi; Ichiki, Takanori

2015-05-15

We have developed an advanced microintaglio printing method for fabricating fine and high-density micropatterns and applied it to the microarraying of RNA molecules. The microintaglio printing of RNA reported here is based on the hybridization of RNA with immobilized complementary DNA probes. The hybridization was controlled by switching the RNA conformation via the temperature, and an RNA microarray with a diameter of 1.5 µm and a density of 40,000 spots/mm(2) with high contrast was successfully fabricated. Specifically, no size effects were observed in the uniformity of patterned signals over a range of microarray feature sizes spanning one order of magnitude. Additionally, we have developed a microintaglio printing method for transcribed RNA microarrays on demand using DNA-immobilized magnetic beads. The beads were arrayed on wells fabricated on a printing mold and the wells were filled with in vitro transcription reagent and sealed with a DNA-immobilized glass substrate. Subsequently, RNA was in situ synthesized using the bead-immobilized DNA as a template and printed onto the substrate via hybridization. Since the microintaglio printing of RNA using DNA-immobilized beads enables the fabrication of a microarray of spots composed of multiple RNA sequences, it will be possible to screen or analyze RNA functions using an RNA microarray fabricated by temperature-controlled microintaglio printing (TC-µIP). Copyright © 2014 Elsevier B.V. All rights reserved.

Quantifying protein-protein interactions in high throughput using protein domain microarrays.

PubMed

Kaushansky, Alexis; Allen, John E; Gordus, Andrew; Stiffler, Michael A; Karp, Ethan S; Chang, Bryan H; MacBeath, Gavin

2010-04-01

Protein microarrays provide an efficient way to identify and quantify protein-protein interactions in high throughput. One drawback of this technique is that proteins show a broad range of physicochemical properties and are often difficult to produce recombinantly. To circumvent these problems, we have focused on families of protein interaction domains. Here we provide protocols for constructing microarrays of protein interaction domains in individual wells of 96-well microtiter plates, and for quantifying domain-peptide interactions in high throughput using fluorescently labeled synthetic peptides. As specific examples, we will describe the construction of microarrays of virtually every human Src homology 2 (SH2) and phosphotyrosine binding (PTB) domain, as well as microarrays of mouse PDZ domains, all produced recombinantly in Escherichia coli. For domains that mediate high-affinity interactions, such as SH2 and PTB domains, equilibrium dissociation constants (K(D)s) for their peptide ligands can be measured directly on arrays by obtaining saturation binding curves. For weaker binding domains, such as PDZ domains, arrays are best used to identify candidate interactions, which are then retested and quantified by fluorescence polarization. Overall, protein domain microarrays provide the ability to rapidly identify and quantify protein-ligand interactions with minimal sample consumption. Because entire domain families can be interrogated simultaneously, they provide a powerful way to assess binding selectivity on a proteome-wide scale and provide an unbiased perspective on the connectivity of protein-protein interaction networks.

Cell-Based Microarrays for In Vitro Toxicology

NASA Astrophysics Data System (ADS)

Wegener, Joachim

2015-07-01

DNA/RNA and protein microarrays have proven their outstanding bioanalytical performance throughout the past decades, given the unprecedented level of parallelization by which molecular recognition assays can be performed and analyzed. Cell microarrays (CMAs) make use of similar construction principles. They are applied to profile a given cell population with respect to the expression of specific molecular markers and also to measure functional cell responses to drugs and chemicals. This review focuses on the use of cell-based microarrays for assessing the cytotoxicity of drugs, toxins, or chemicals in general. It also summarizes CMA construction principles with respect to the cell types that are used for such microarrays, the readout parameters to assess toxicity, and the various formats that have been established and applied. The review ends with a critical comparison of CMAs and well-established microtiter plate (MTP) approaches.

Intra-Platform Repeatability and Inter-Platform Comparability of MicroRNA Microarray Technology

PubMed Central

Sato, Fumiaki; Tsuchiya, Soken; Terasawa, Kazuya; Tsujimoto, Gozoh

2009-01-01

Over the last decade, DNA microarray technology has provided a great contribution to the life sciences. The MicroArray Quality Control (MAQC) project demonstrated the way to analyze the expression microarray. Recently, microarray technology has been utilized to analyze a comprehensive microRNA expression profiling. Currently, several platforms of microRNA microarray chips are commercially available. Thus, we compared repeatability and comparability of five different microRNA microarray platforms (Agilent, Ambion, Exiqon, Invitrogen and Toray) using 309 microRNAs probes, and the Taqman microRNA system using 142 microRNA probes. This study demonstrated that microRNA microarray has high intra-platform repeatability and comparability to quantitative RT-PCR of microRNA. Among the five platforms, Agilent and Toray array showed relatively better performances than the others. However, the current lineup of commercially available microRNA microarray systems fails to show good inter-platform concordance, probably because of lack of an adequate normalization method and severe divergence in stringency of detection call criteria between different platforms. This study provided the basic information about the performance and the problems specific to the current microRNA microarray systems. PMID:19436744

Hierarchical Parallelization of Gene Differential Association Analysis

PubMed Central

2011-01-01

Background Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication) parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Results Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. Conclusions The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels. PMID:21936916

Hierarchical parallelization of gene differential association analysis.

PubMed

Needham, Mark; Hu, Rui; Dwarkadas, Sandhya; Qiu, Xing

2011-09-21

Microarray gene differential expression analysis is a widely used technique that deals with high dimensional data and is computationally intensive for permutation-based procedures. Microarray gene differential association analysis is even more computationally demanding and must take advantage of multicore computing technology, which is the driving force behind increasing compute power in recent years. In this paper, we present a two-layer hierarchical parallel implementation of gene differential association analysis. It takes advantage of both fine- and coarse-grain (with granularity defined by the frequency of communication) parallelism in order to effectively leverage the non-uniform nature of parallel processing available in the cutting-edge systems of today. Our results show that this hierarchical strategy matches data sharing behavior to the properties of the underlying hardware, thereby reducing the memory and bandwidth needs of the application. The resulting improved efficiency reduces computation time and allows the gene differential association analysis code to scale its execution with the number of processors. The code and biological data used in this study are downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm. The performance sweet spot occurs when using a number of threads per MPI process that allows the working sets of the corresponding MPI processes running on the multicore to fit within the machine cache. Hence, we suggest that practitioners follow this principle in selecting the appropriate number of MPI processes and threads within each MPI process for their cluster configurations. We believe that the principles of this hierarchical approach to parallelization can be utilized in the parallelization of other computationally demanding kernels.

Multi-task feature selection in microarray data by binary integer programming.

PubMed

Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

Stochastic models for inferring genetic regulation from microarray gene expression data.

PubMed

Tian, Tianhai

2010-03-01

Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information. 2009 Elsevier Ireland Ltd. All rights reserved.

DNA microarrays and their use in dermatology.

PubMed

Mlakar, Vid; Glavac, Damjan

2007-03-01

Multiple different DNA microarray technologies are available on the market today. They can be used for studying either DNA or RNA with the purpose of identifying and explaining the role of genes involved in different processes. This paper reviews different DNA microarray platforms available for such studies and their usage in cases of malignant melanomas, psoriasis, and exposure of keratinocytes and melanocytes to UV illumination.

mRNA-Based Parallel Detection of Active Methanotroph Populations by Use of a Diagnostic Microarray

PubMed Central

Bodrossy, Levente; Stralis-Pavese, Nancy; Konrad-Köszler, Marianne; Weilharter, Alexandra; Reichenauer, Thomas G.; Schöfer, David; Sessitsch, Angela

2006-01-01

A method was developed for the mRNA-based application of microbial diagnostic microarrays to detect active microbial populations. DNA- and mRNA-based analyses of environmental samples were compared and confirmed via quantitative PCR. Results indicated that mRNA-based microarray analyses may provide additional information on the composition and functioning of microbial communities. PMID:16461725

DNA Microarray Wet Lab Simulation Brings Genomics into the High School Curriculum

ERIC Educational Resources Information Center

Campbell, A. Malcolm; Zanta, Carolyn A.; Heyer, Laurie J.; Kittinger, Ben; Gabric, Kathleen M.; Adler, Leslie

2006-01-01

We have developed a wet lab DNA microarray simulation as part of a complete DNA microarray module for high school students. The wet lab simulation has been field tested with high school students in Illinois and Maryland as well as in workshops with high school teachers from across the nation. Instead of using DNA, our simulation is based on pH…

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards.

PubMed

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Laegreid, Astrid

2007-10-18

The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards

PubMed Central

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Lægreid, Astrid

2007-01-01

Background The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. Results We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. Conclusion The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish. PMID:17949480

ELISA-BASE: An Integrated Bioinformatics Tool for Analyzing and Tracking ELISA Microarray Data

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

White, Amanda M.; Collett, James L.; Seurynck-Servoss, Shannon L.

ELISA-BASE is an open-source database for capturing, organizing and analyzing protein enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Soft-ware Environment (BASE) database system, which was developed for DNA microarrays. In order to make BASE suitable for protein microarray experiments, we developed several plugins for importing and analyzing quantitative ELISA microarray data. Most notably, our Protein Microarray Analysis Tool (ProMAT) for processing quantita-tive ELISA data is now available as a plugin to the database.

High-throughput screening in two dimensions: binding intensity and off-rate on a peptide microarray.

PubMed

Greving, Matthew P; Belcher, Paul E; Cox, Conor D; Daniel, Douglas; Diehnelt, Chris W; Woodbury, Neal W

2010-07-01

We report a high-throughput two-dimensional microarray-based screen, incorporating both target binding intensity and off-rate, which can be used to analyze thousands of compounds in a single binding assay. Relative binding intensities and time-resolved dissociation are measured for labeled tumor necrosis factor alpha (TNF-alpha) bound to a peptide microarray. The time-resolved dissociation is fitted to a one-component exponential decay model, from which relative dissociation rates are determined for all peptides with binding intensities above background. We show that most peptides with the slowest off-rates on the microarray also have the slowest off-rates when measured by surface plasmon resonance (SPR). 2010 Elsevier Inc. All rights reserved.

Characterization and Performance Evaluation of an HPXe Detector for Nuclear Explosion Monitoring Applications

DTIC Science & Technology

2007-09-01

performance of the detector, and to compare the performance with sodium iodide and germanium detectors. Monte Carlo ( MCNP ) simulation was used to...aluminum ~50% more efficient), and to estimate optimum shield dimensions for an HPXe based nuclear explosion monitor. MCNP modeling was also used to...detector were calculated with MCNP by using input activity levels as measured in routine NEM runs at Pacific Northwest National Laboratory (PNNL

Sensitivity of a Bayesian atmospheric-transport inversion model to spatio-temporal sensor resolution applied to the 2006 North Korean nuclear test

NASA Astrophysics Data System (ADS)

Lundquist, K. A.; Jensen, D. D.; Lucas, D. D.

2017-12-01

Atmospheric source reconstruction allows for the probabilistic estimate of source characteristics of an atmospheric release using observations of the release. Performance of the inversion depends partially on the temporal frequency and spatial scale of the observations. The objective of this study is to quantify the sensitivity of the source reconstruction method to sparse spatial and temporal observations. To this end, simulations of atmospheric transport of noble gasses are created for the 2006 nuclear test at the Punggye-ri nuclear test site. Synthetic observations are collected from the simulation, and are taken as "ground truth". Data denial techniques are used to progressively coarsen the temporal and spatial resolution of the synthetic observations, while the source reconstruction model seeks to recover the true input parameters from the synthetic observations. Reconstructed parameters considered here are source location, source timing and source quantity. Reconstruction is achieved by running an ensemble of thousands of dispersion model runs that sample from a uniform distribution of the input parameters. Machine learning is used to train a computationally-efficient surrogate model from the ensemble simulations. Monte Carlo sampling and Bayesian inversion are then used in conjunction with the surrogate model to quantify the posterior probability density functions of source input parameters. This research seeks to inform decision makers of the tradeoffs between more expensive, high frequency observations and less expensive, low frequency observations.

Screening small-molecule compound microarrays for protein ligands without fluorescence labeling with a high-throughput scanning microscope.

PubMed

Fei, Yiyan; Landry, James P; Sun, Yungshin; Zhu, Xiangdong; Wang, Xiaobing; Luo, Juntao; Wu, Chun-Yi; Lam, Kit S

2010-01-01

We describe a high-throughput scanning optical microscope for detecting small-molecule compound microarrays on functionalized glass slides. It is based on measurements of oblique-incidence reflectivity difference and employs a combination of a y-scan galvometer mirror and an x-scan translation stage with an effective field of view of 2 cm x 4 cm. Such a field of view can accommodate a printed small-molecule compound microarray with as many as 10,000 to 20,000 targets. The scanning microscope is capable of measuring kinetics as well as endpoints of protein-ligand reactions simultaneously. We present the experimental results on solution-phase protein reactions with small-molecule compound microarrays synthesized from one-bead, one-compound combinatorial chemistry and immobilized on a streptavidin-functionalized glass slide.

Screening small-molecule compound microarrays for protein ligands without fluorescence labeling with a high-throughput scanning microscope

PubMed Central

Fei, Yiyan; Landry, James P.; Sun, Yungshin; Zhu, Xiangdong; Wang, Xiaobing; Luo, Juntao; Wu, Chun-Yi; Lam, Kit S.

2010-01-01

We describe a high-throughput scanning optical microscope for detecting small-molecule compound microarrays on functionalized glass slides. It is based on measurements of oblique-incidence reflectivity difference and employs a combination of a y-scan galvometer mirror and an x-scan translation stage with an effective field of view of 2 cm×4 cm. Such a field of view can accommodate a printed small-molecule compound microarray with as many as 10,000 to 20,000 targets. The scanning microscope is capable of measuring kinetics as well as endpoints of protein-ligand reactions simultaneously. We present the experimental results on solution-phase protein reactions with small-molecule compound microarrays synthesized from one-bead, one-compound combinatorial chemistry and immobilized on a streptavidin-functionalized glass slide. PMID:20210464

The Fukushima Nuclear Event and its Implications for Nuclear Power

NASA Astrophysics Data System (ADS)

Golay, Michael

2011-11-01

The combined strong earthquake and super tsunami of 12 March 2011 at the Fukushima nuclear power plant imposed the most severe challenges ever experienced at such a facility. Information regarding the plant response and status remains uncertain, but it is clear that severe damage has been sustained, that the plant staff have responded creatively and that the offsite implications are unlikely to be seriously threatening to the health, if not the prosperity, of the surrounding population. Reexamination of the regulatory constraints of nuclear power will occur worldwide, and some changes are likely; particularly concerning reliance upon active systems for achieving critical safety functions and concerning treatments of used reactor fuel. Whether worldwide expansion of the nuclear power economy will be slowed in the long run is perhaps unlikely and worth discussion.

Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

PubMed

Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

2013-01-01

Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially expressed genes is large for both normally and non-normally distributed data. Finally, the Resampling-based empirical Bayes Methods are generalizable to next generation sequencing RNA-seq data analysis.

Mapping the affinity landscape of Thrombin-binding aptamers on 2΄F-ANA/DNA chimeric G-Quadruplex microarrays

PubMed Central

Abou Assi, Hala; Gómez-Pinto, Irene; González, Carlos

2017-01-01

Abstract In situ fabricated nucleic acids microarrays are versatile and very high-throughput platforms for aptamer optimization and discovery, but the chemical space that can be probed against a given target has largely been confined to DNA, while RNA and non-natural nucleic acid microarrays are still an essentially uncharted territory. 2΄-Fluoroarabinonucleic acid (2΄F-ANA) is a prime candidate for such use in microarrays. Indeed, 2΄F-ANA chemistry is readily amenable to photolithographic microarray synthesis and its potential in high affinity aptamers has been recently discovered. We thus synthesized the first microarrays containing 2΄F-ANA and 2΄F-ANA/DNA chimeric sequences to fully map the binding affinity landscape of the TBA1 thrombin-binding G-quadruplex aptamer containing all 32 768 possible DNA-to-2΄F-ANA mutations. The resulting microarray was screened against thrombin to identify a series of promising 2΄F-ANA-modified aptamer candidates with Kds significantly lower than that of the unmodified control and which were found to adopt highly stable, antiparallel-folded G-quadruplex structures. The solution structure of the TBA1 aptamer modified with 2΄F-ANA at position T3 shows that fluorine substitution preorganizes the dinucleotide loop into the proper conformation for interaction with thrombin. Overall, our work strengthens the potential of 2΄F-ANA in aptamer research and further expands non-genomic applications of nucleic acids microarrays. PMID:28100695

Development of a rapid microarray-based DNA subtyping assay for the alleles of Shiga toxins 1 and 2 of Escherichia coli.

PubMed

Geue, Lutz; Stieber, Bettina; Monecke, Stefan; Engelmann, Ines; Gunzer, Florian; Slickers, Peter; Braun, Sascha D; Ehricht, Ralf

2014-08-01

In this study, we developed a new rapid, economic, and automated microarray-based genotyping test for the standardized subtyping of Shiga toxins 1 and 2 of Escherichia coli. The microarrays from Alere Technologies can be used in two different formats, the ArrayTube and the ArrayStrip (which enables high-throughput testing in a 96-well format). One microarray chip harbors all the gene sequences necessary to distinguish between all Stx subtypes, facilitating the identification of single and multiple subtypes within a single isolate in one experiment. Specific software was developed to automatically analyze all data obtained from the microarray. The assay was validated with 21 Shiga toxin-producing E. coli (STEC) reference strains that were previously tested by the complete set of conventional subtyping PCRs. The microarray results showed 100% concordance with the PCR results. Essentially identical results were detected when the standard DNA extraction method was replaced by a time-saving heat lysis protocol. For further validation of the microarray, we identified the Stx subtypes or combinations of the subtypes in 446 STEC field isolates of human and animal origin. In summary, this oligonucleotide array represents an excellent diagnostic tool that provides some advantages over standard PCR-based subtyping. The number of the spotted probes on the microarrays can be increased by additional probes, such as for novel alleles, species markers, or resistance genes, should the need arise. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

[Oligonucleotide microarray for subtyping avian influenza virus].

PubMed

Xueqing, Han; Xiangmei, Lin; Yihong, Hou; Shaoqiang, Wu; Jian, Liu; Lin, Mei; Guangle, Jia; Zexiao, Yang

2008-09-01

Avian influenza viruses are important human and animal respiratory pathogens and rapid diagnosis of novel emerging avian influenza viruses is vital for effective global influenza surveillance. We developed an oligonucleotide microarray-based method for subtyping all avian influenza virus (16 HA and 9 NA subtypes). In total 25 pairs of primers specific for different subtypes and 1 pair of universal primers were carefully designed based on the genomic sequences of influenza A viruses retrieved from GenBank database. Several multiplex RT-PCR methods were then developed, and the target cDNAs of 25 subtype viruses were amplified by RT-PCR or overlapping PCR for evaluating the microarray. Further 52 oligonucleotide probes specific for all 25 subtype viruses were designed according to published gene sequences of avian influenza viruses in amplified target cDNAs domains, and a microarray for subtyping influenza A virus was developed. Then its specificity and sensitivity were validated by using different subtype strains and 2653 samples from 49 different areas. The results showed that all the subtypes of influenza virus could be identified simultaneously on this microarray with high sensitivity, which could reach to 2.47 pfu/mL virus or 2.5 ng target DNA. Furthermore, there was no cross reaction with other avian respiratory virus. An oligonucleotide microarray-based strategy for detection of avian influenza viruses has been developed. Such a diagnostic microarray will be useful in discovering and identifying all subtypes of avian influenza virus.

Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion.

PubMed

Steger, Doris; Berry, David; Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander

2011-01-01

The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.

Systematic Spatial Bias in DNA Microarray Hybridization Is Caused by Probe Spot Position-Dependent Variability in Lateral Diffusion

PubMed Central

Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander

2011-01-01

Background The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. Methodology/Principal Findings This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Conclusions Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization. PMID:21858215

The detection and differentiation of canine respiratory pathogens using oligonucleotide microarrays.

PubMed

Wang, Lih-Chiann; Kuo, Ya-Ting; Chueh, Ling-Ling; Huang, Dean; Lin, Jiunn-Horng

2017-05-01

Canine respiratory diseases are commonly seen in dogs along with co-infections with multiple respiratory pathogens, including viruses and bacteria. Virus infections in even vaccinated dogs were also reported. The clinical signs caused by different respiratory etiological agents are similar, which makes differential diagnosis imperative. An oligonucleotide microarray system was developed in this study. The wild type and vaccine strains of canine distemper virus (CDV), influenza virus, canine herpesvirus (CHV), Bordetella bronchiseptica and Mycoplasma cynos were detected and differentiated simultaneously on a microarray chip. The detection limit is 10, 10, 100, 50 and 50 copy numbers for CDV, influenza virus, CHV, B. bronchiseptica and M. cynos, respectively. The clinical test results of nasal swab samples showed that the microarray had remarkably better efficacy than the multiplex PCR-agarose gel method. The positive detection rate of microarray and agarose gel was 59.0% (n=33) and 41.1% (n=23) among the 56 samples, respectively. CDV vaccine strain and pathogen co-infections were further demonstrated by the microarray but not by the multiplex PCR-agarose gel. The oligonucleotide microarray provides a highly efficient diagnosis alternative that could be applied to clinical usage, greatly assisting in disease therapy and control. Copyright © 2017 Elsevier B.V. All rights reserved.

Sequoia, a tramtrack-related zinc finger protein, functions as a pan-neural regulator for dendrite and axon morphogenesis in Drosophila.

PubMed

Brenman, J E; Gao, F B; Jan, L Y; Jan, Y N

2001-11-01

Morphological complexity of neurons contributes to their functional complexity. How neurons generate different dendritic patterns is not known. We identified the sequoia mutant from a previous screen for dendrite mutants. Here we report that Sequoia is a pan-neural nuclear protein containing two putative zinc fingers homologous to the DNA binding domain of Tramtrack. sequoia mutants affect the cell fate decision of a small subset of neurons but have global effects on axon and dendrite morphologies of most and possibly all neurons. In support of sequoia as a specific regulator of neuronal morphogenesis, microarray experiments indicate that sequoia may regulate downstream genes that are important for executing neurite development rather than altering a variety of molecules that specify cell fates.

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Linking empowering leadership to safety participation in nuclear power plants: a structural equation model.

PubMed

Martínez-Córcoles, Mario; Schöbel, Markus; Gracia, Francisco J; Tomás, Inés; Peiró, José M

2012-07-01

Safety participation is of paramount importance in guaranteeing the safe running of nuclear power plants. The present study examined the effects of empowering leadership on safety participation. Based on a sample of 495 employees from two Spanish nuclear power plants, structural equation modeling showed that empowering leadership has a significant relationship with safety participation, which is mediated by collaborative team learning. In addition, the results revealed that the relationship between empowering leadership and collaborative learning is partially mediated by the promotion of dialogue and open communication. The implications of these findings for safety research and their practical applications are outlined. An empowering leadership style enhances workers' safety performance, particularly safety participation behaviors. Safety participation is recommended to detect possible rule inconsistencies or misunderstood procedures and make workers aware of critical safety information and issues. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Teaching And Training Tools For The Undergraduate: Experience With A Rebuilt AN-400 Accelerator

NASA Astrophysics Data System (ADS)

Roberts, Andrew D.

2011-06-01

There is an increasingly recognized need for people trained in a broad range of applied nuclear science techniques, indicated by reports from the American Physical Society and elsewhere. Anecdotal evidence suggests that opportunities for hands-on training with small particle accelerators have diminished in the US, as development programs established in the 1960's and 1970's have been decommissioned over recent decades. Despite the reduced interest in the use of low energy accelerators in fundamental research, these machines can offer a powerful platform for bringing unique training opportunities to the undergraduate curriculum in nuclear physics, engineering and technology. We report here on the new MSU Applied Nuclear Science Lab, centered around the rebuild of an AN400 electrostatic accelerator. This machine is run entirely by undergraduate students under faculty supervision, allowing a great deal of freedom in its use without restrictions from graduate or external project demands.

Double stranded nucleic acid biochips

DOEpatents

Chernov, Boris; Golova, Julia

2006-05-23

This invention describes a new method of constructing double-stranded DNA (dsDNA) microarrays based on the use of pre-synthesized or natural DNA duplexes without a stem-loop structure. The complementary oligonucleotide chains are bonded together by a novel connector that includes a linker for immobilization on a matrix. A non-enzymatic method for synthesizing double-stranded nucleic acids with this novel connector enables the construction of inexpensive and robust dsDNA/dsRNA microarrays. DNA-DNA and DNA-protein interactions are investigated using the microarrays.

The Use of Atomic Force Microscopy for 3D Analysis of Nucleic Acid Hybridization on Microarrays.

PubMed

Dubrovin, E V; Presnova, G V; Rubtsova, M Yu; Egorov, A M; Grigorenko, V G; Yaminsky, I V

2015-01-01

Oligonucleotide microarrays are considered today to be one of the most efficient methods of gene diagnostics. The capability of atomic force microscopy (AFM) to characterize the three-dimensional morphology of single molecules on a surface allows one to use it as an effective tool for the 3D analysis of a microarray for the detection of nucleic acids. The high resolution of AFM offers ways to decrease the detection threshold of target DNA and increase the signal-to-noise ratio. In this work, we suggest an approach to the evaluation of the results of hybridization of gold nanoparticle-labeled nucleic acids on silicon microarrays based on an AFM analysis of the surface both in air and in liquid which takes into account of their three-dimensional structure. We suggest a quantitative measure of the hybridization results which is based on the fraction of the surface area occupied by the nanoparticles.

The relationship between pollutant emissions, renewable energy, nuclear energy and GDP: empirical evidence from 18 developed and developing countries

NASA Astrophysics Data System (ADS)

Ben Mbarek, Mounir; Saidi, Kais; Amamri, Mounira

2018-07-01

This document investigates the causal relationship between nuclear energy (NE), pollutant emissions (CO2 emissions), gross domestic product (GDP) and renewable energy (RE) using dynamic panel data models for a global panel consisting of 18 countries (developed and developing) covering the 1990-2013 period. Our results indicate that there is a co-integration between variables. The unit root test suggests that all the variables are stationary in first differences. The paper further examines the link using the Granger causality analysis of vector error correction model, which indicates a unidirectional relationship running from GDP per capita to pollutant emissions for the developed and developing countries. However, there is a unidirectional causality from GDP per capita to RE in the short and long run. This finding confirms the conservation hypothesis. Similarly, there is no causality between NE and GDP per capita.

'Systems toxicology' approach identifies coordinated metabolic responses to copper in a terrestrial non-model invertebrate, the earthworm Lumbricus rubellus.

PubMed

Bundy, Jacob G; Sidhu, Jasmin K; Rana, Faisal; Spurgeon, David J; Svendsen, Claus; Wren, Jodie F; Stürzenbaum, Stephen R; Morgan, A John; Kille, Peter

2008-06-03

New methods are needed for research into non-model organisms, to monitor the effects of toxic disruption at both the molecular and functional organism level. We exposed earthworms (Lumbricus rubellus Hoffmeister) to sub-lethal levels of copper (10-480 mg/kg soil) for 70 days as a real-world situation, and monitored both molecular (cDNA transcript microarrays and nuclear magnetic resonance-based metabolic profiling: metabolomics) and ecological/functional endpoints (reproduction rate and weight change, which have direct relevance to population-level impacts). Both of the molecular endpoints, metabolomics and transcriptomics, were highly sensitive, with clear copper-induced differences even at levels below those that caused a reduction in reproductive parameters. The microarray and metabolomic data provided evidence that the copper exposure led to a disruption of energy metabolism: transcripts of enzymes from oxidative phosphorylation were significantly over-represented, and increases in transcripts of carbohydrate metabolising enzymes (maltase-glucoamylase, mannosidase) had corresponding decreases in small-molecule metabolites (glucose, mannose). Treating both enzymes and metabolites as functional cohorts led to clear inferences about changes in energetic metabolism (carbohydrate use and oxidative phosphorylation), which would not have been possible by taking a 'biomarker' approach to data analysis. Multiple post-genomic techniques can be combined to provide mechanistic information about the toxic effects of chemical contaminants, even for non-model organisms with few additional mechanistic toxicological data. With 70-day no-observed-effect and lowest-observed-effect concentrations (NOEC and LOEC) of 10 and 40 mg kg-1 for metabolomic and microarray profiles, copper is shown to interfere with energy metabolism in an important soil organism at an ecologically and functionally relevant level.

Run II of the LHC: The Accelerator Science

NASA Astrophysics Data System (ADS)

Redaelli, Stefano

2015-04-01

In 2015 the Large Hadron Collider (LHC) at the European Organization for Nuclear Research (CERN) starts its Run II operation. After the successful Run I at 3.5 TeV and 4 TeV in the 2010-2013 period, a first long shutdown (LS1) was mainly dedicated to the consolidation of the LHC magnet interconnections, to allow the LHC to operate at its design beam energy of 7 TeV. Other key accelerator systems have also been improved to optimize the performance reach at higher beam energies. After a review of the LS1 activities, the status of the LHC start-up progress is reported, addressing in particular the status of the LHC hardware commissioning and of the training campaign of superconducting magnets that will determine the operation beam energy in 2015. Then, the plans for the Run II operation are reviewed in detail, covering choice of initial machine parameters and strategy to improve the Run II performance. Future prospects of the LHC and its upgrade plans are also presented.

Prediction of protein orientation upon immobilization on biological and nonbiological surfaces

NASA Astrophysics Data System (ADS)

Talasaz, Amirali H.; Nemat-Gorgani, Mohsen; Liu, Yang; Ståhl, Patrik; Dutton, Robert W.; Ronaghi, Mostafa; Davis, Ronald W.

2006-10-01

We report on a rapid simulation method for predicting protein orientation on a surface based on electrostatic interactions. New methods for predicting protein immobilization are needed because of the increasing use of biosensors and protein microarrays, two technologies that use protein immobilization onto a solid support, and because the orientation of an immobilized protein is important for its function. The proposed simulation model is based on the premise that the protein interacts with the electric field generated by the surface, and this interaction defines the orientation of attachment. Results of this model are in agreement with experimental observations of immobilization of mitochondrial creatine kinase and type I hexokinase on biological membranes. The advantages of our method are that it can be applied to any protein with a known structure; it does not require modeling of the surface at atomic resolution and can be run relatively quickly on readily available computing resources. Finally, we also propose an orientation of membrane-bound cytochrome c, a protein for which the membrane orientation has not been unequivocally determined. electric double layer | electrostatic simulations | orientation flexibility

The effects of tether placement on antibody stability on surfaces

NASA Astrophysics Data System (ADS)

Grawe, Rebecca W.; Knotts, Thomas A.

2017-06-01

Despite their potential benefits, antibody microarrays have fallen short of performing reliably and have not found widespread use outside of the research setting. Experimental techniques have been unable to determine what is occurring on the surface of an atomic level, so molecular simulation has emerged as the primary method of investigating protein/surface interactions. Simulations of small proteins have indicated that the stability of the protein is a function of the residue on the protein where a tether is placed. The purpose of this research is to see whether these findings also apply to antibodies, with their greater size and complexity. To determine this, 24 tethering locations were selected on the antibody Protein Data Bank (PDB) ID: 1IGT. Replica exchange simulations were run on two different surfaces, one hydrophobic and one hydrophilic, to determine the degree to which these tethering sites stabilize or destabilize the antibody. Results showed that antibodies tethered to hydrophobic surfaces were in general less stable than antibodies tethered to hydrophilic surfaces. Moreover, the stability of the antibody was a function of the tether location on hydrophobic surfaces but not hydrophilic surfaces.

Using NERSC High-Performance Computing (HPC) systems for high-energy nuclear physics applications with ALICE

NASA Astrophysics Data System (ADS)

Fasel, Markus

2016-10-01

High-Performance Computing Systems are powerful tools tailored to support large- scale applications that rely on low-latency inter-process communications to run efficiently. By design, these systems often impose constraints on application workflows, such as limited external network connectivity and whole node scheduling, that make more general-purpose computing tasks, such as those commonly found in high-energy nuclear physics applications, more difficult to carry out. In this work, we present a tool designed to simplify access to such complicated environments by handling the common tasks of job submission, software management, and local data management, in a framework that is easily adaptable to the specific requirements of various computing systems. The tool, initially constructed to process stand-alone ALICE simulations for detector and software development, was successfully deployed on the NERSC computing systems, Carver, Hopper and Edison, and is being configured to provide access to the next generation NERSC system, Cori. In this report, we describe the tool and discuss our experience running ALICE applications on NERSC HPC systems. The discussion will include our initial benchmarks of Cori compared to other systems and our attempts to leverage the new capabilities offered with Cori to support data-intensive applications, with a future goal of full integration of such systems into ALICE grid operations.

Where statistics and molecular microarray experiments biology meet.

PubMed

Kelmansky, Diana M

2013-01-01

This review chapter presents a statistical point of view to microarray experiments with the purpose of understanding the apparent contradictions that often appear in relation to their results. We give a brief introduction of molecular biology for nonspecialists. We describe microarray experiments from their construction and the biological principles the experiments rely on, to data acquisition and analysis. The role of epidemiological approaches and sample size considerations are also discussed.

Controlling false-negative errors in microarray differential expression analysis: a PRIM approach.

PubMed

Cole, Steve W; Galic, Zoran; Zack, Jerome A

2003-09-22

Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed 'false negative' error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements. Monte Carlo analyses based on four empirical data sets show that conventional statistical models and their microarray-adapted variants overlook more than 50% of genes showing significant up-regulation. Conjoint PRIM prediction rules recover approximately twice as many differentially expressed transcripts while maintaining strong control over false-positive (Type I) errors. As a result, experimental replication rates increase and total analytic error rates decline. RT-PCR studies confirm that gene inductions detected by PRIM but overlooked by other methods represent true changes in mRNA levels. PRIM-based conjoint inference rules thus represent an improved strategy for high-sensitivity screening of DNA microarrays. Freestanding JAVA application at http://microarray.crump.ucla.edu/focus

Self-directed student research through analysis of microarray datasets: a computer-based functional genomics practical class for masters-level students.

PubMed

Grenville-Briggs, Laura J; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate active learning through experience of current research methods in bioinformatics and functional genomics. They seek to closely mimic a realistic research environment, and require the students first to propose research hypotheses, then test those hypotheses using specific sections of the microarray dataset. The complexity of the microarray data provides students with the freedom to propose their own unique hypotheses, tested using appropriate sections of the microarray data. This research latitude was highly regarded by students and is a strength of this practical. In addition, the focus on DNA damage by radiation and mutagenic chemicals allows them to place their results in a human medical context, and successfully sparks broad interest in the subject material. In evaluation, 79% of students scored the practical workshops on a five-point scale as 4 or 5 (totally effective) for student learning. More broadly, the general use of microarray data as a "student research playground" is also discussed. Copyright © 2011 Wiley Periodicals, Inc.

Microarray platform affords improved product analysis in mammalian cell growth studies

PubMed Central

Li, Lingyun; Migliore, Nicole; Schaefer, Eugene; Sharfstein, Susan T.; Dordick, Jonathan S.; Linhardt, Robert J.

2014-01-01

High throughput (HT) platforms serve as cost-efficient and rapid screening method for evaluating the effect of cell culture conditions and screening of chemicals. The aim of the current study was to develop a high-throughput cell-based microarray platform to assess the effect of culture conditions on Chinese hamster ovary (CHO) cells. Specifically, growth, transgene expression and metabolism of a GS/MSX CHO cell line, which produces a therapeutic monoclonal antibody, was examined using microarray system in conjunction with conventional shake flask platform in a non-proprietary medium. The microarray system consists of 60 nl spots of cells encapsulated in alginate and separated in groups via an 8-well chamber system attached to the chip. Results show the non-proprietary medium developed allows cell growth, production and normal glycosylation of recombinant antibody and metabolism of the recombinant CHO cells in both the microarray and shake flask platforms. In addition, 10.3 mM glutamate addition to the defined base media results in lactate metabolism shift in the recombinant GS/MSX CHO cells in the shake flask platform. Ultimately, the results demonstrate that the high-throughput microarray platform has the potential to be utilized for evaluating the impact of media additives on cellular processes, such as, cell growth, metabolism and productivity. PMID:24227746

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

Gentry, T.; Schadt, C.; Zhou, J.

Microarray technology has the unparalleled potential tosimultaneously determine the dynamics and/or activities of most, if notall, of the microbial populations in complex environments such as soilsand sediments. Researchers have developed several types of arrays thatcharacterize the microbial populations in these samples based on theirphylogenetic relatedness or functional genomic content. Several recentstudies have used these microarrays to investigate ecological issues;however, most have only analyzed a limited number of samples withrelatively few experiments utilizing the full high-throughput potentialof microarray analysis. This is due in part to the unique analyticalchallenges that these samples present with regard to sensitivity,specificity, quantitation, and data analysis. Thismore » review discussesspecific applications of microarrays to microbial ecology research alongwith some of the latest studies addressing the difficulties encounteredduring analysis of complex microbial communities within environmentalsamples. With continued development, microarray technology may ultimatelyachieve its potential for comprehensive, high-throughput characterizationof microbial populations in near real-time.« less

2011 Tohoku Earthquake and Japan's Nuclear Disaster - Implications for Indian Ocean Rim countries

NASA Astrophysics Data System (ADS)

Chadha, R. K.

2011-12-01

The Nuclear disaster in Japan after the M9.0 Tohoku earthquake on March 11, 2011 has elicited global response to have a relook at the safety aspects of the nuclear power plants from all angles including natural hazards like earthquakes and tsunami. Several countries have gone into safety audits of their nuclear programs in view of the experience in Japan. Tectonically speaking, countries located close to subduction zones or in direct line of impact of the subduction zones are the most vulnerable to earthquake or tsunami hazard, as these regions are the locale of great tsunamigenic earthquakes. The Japan disaster has also cautioned to the possibility of great impact to the critical structures along the coasts due to other ocean processes caused by ocean-atmosphere interactions and also due to global warming and sea level rise phenomena in future. This is particular true for island countries. The 2011 Tohoku earthquake in Japan will be remembered more because of its nuclear tragedy and tsunami rather than the earthquake itself. The disaster happened as a direct impact of a tsunami generated by the earthquake 130 km off the coast of Sendai in the Honshu region of Japan. The depth of the earthquake was about 25 km below the ocean floor and it occurred on a thrust fault causing a displacement of more than 20 meters. At few places, water is reported to have inundated areas up to 8-10 km inland. The height of the tsunami varied between 10 and 3 meters along the coast. Generally, during an earthquake damage to buildings or other structures occur due to strong shaking which is expressed in the form of ground accelerations 'g'. Although, Peak Ground Accelerations (PGA) consistently exceeded 2g at several places from Sendai down south, structures at the Fukushima Daiichi Nuclear Power Plant did not collapse due to the earthquake. In the Indian Ocean Rim countries, Indian, Pakistan and South Africa are the three countries where Nuclear power plants are operational, few of them along the coasts. There are a few countries where nuclear installations are planned and hence, a critical analysis is required to know the realistic hazard due to earthquakes and tsunami in these countries. The December 2004 Indian Ocean tsunami generated due to Sumatra earthquake of M9.3 claimed more than 250,000 lives but did not caused a situation like in Japan. We studied the tsunami run-up heights and inundation along the east coast of India. The maximum run-up height of 5.2 meters was observed at Nagapattinam with lateral inundation up to 800 meters and the minimum was at Devanaampatnam with a lateral inundation up to 340 meters. At Kalpakkam Nuclear Power Plant, the tsunami run-up height was 4.1 meters and water entered up to 360 meters inside the campus. Using the observed data we modeled several scenarios for Indian coast line for different earthquakes along the subduction zone of Andaman-Sumatra in the east and Makran in south Pakistan in the western side using N2 Tsunami Model. The results obtained for few critical structures will be presented with an overview of scenarios for other countries.

Development of a low-cost detection method for miRNA microarray.

PubMed

Li, Wei; Zhao, Botao; Jin, Youxin; Ruan, Kangcheng

2010-04-01

MicroRNA (miRNA) microarray is a powerful tool to explore the expression profiling of miRNA. The current detection method used in miRNA microarray is mainly fluorescence based, which usually requires costly detection system such as laser confocal scanner of tens of thousands of dollars. Recently, we developed a low-cost yet sensitive detection method for miRNA microarray based on enzyme-linked assay. In this approach, the biotinylated miRNAs were captured by the corresponding oligonucleotide probes immobilized on microarray slide; and then the biotinylated miRNAs would capture streptavidin-conjugated alkaline phosphatase. A purple-black precipitation on each biotinylated miRNA spot was produced by the enzyme catalytic reaction. It could be easily detected by a charge-coupled device digital camera mounted on a microscope, which lowers the detection cost more than 100 fold compared with that of fluorescence method. Our data showed that signal intensity of the spot correlates well with the biotinylated miRNA concentration and the detection limit for miRNAs is at least 0.4 fmol and the detection dynamic range spans about 2.5 orders of magnitude, which is comparable to that of fluorescence method.

A study of metaheuristic algorithms for high dimensional feature selection on microarray data

NASA Astrophysics Data System (ADS)

Dankolo, Muhammad Nasiru; Radzi, Nor Haizan Mohamed; Sallehuddin, Roselina; Mustaffa, Noorfa Haszlinna

2017-11-01

Microarray systems enable experts to examine gene profile at molecular level using machine learning algorithms. It increases the potentials of classification and diagnosis of many diseases at gene expression level. Though, numerous difficulties may affect the efficiency of machine learning algorithms which includes vast number of genes features comprised in the original data. Many of these features may be unrelated to the intended analysis. Therefore, feature selection is necessary to be performed in the data pre-processing. Many feature selection algorithms are developed and applied on microarray which including the metaheuristic optimization algorithms. This paper discusses the application of the metaheuristics algorithms for feature selection in microarray dataset. This study reveals that, the algorithms have yield an interesting result with limited resources thereby saving computational expenses of machine learning algorithms.

Expression profiling of nuclear receptors in breast cancer identifies TLX as a mediator of growth and invasion in triple-negative breast cancer.

PubMed

Lin, Meng-Lay; Patel, Hetal; Remenyi, Judit; Banerji, Christopher R S; Lai, Chun-Fui; Periyasamy, Manikandan; Lombardo, Ylenia; Busonero, Claudia; Ottaviani, Silvia; Passey, Alun; Quinlan, Philip R; Purdie, Colin A; Jordan, Lee B; Thompson, Alastair M; Finn, Richard S; Rueda, Oscar M; Caldas, Carlos; Gil, Jesus; Coombes, R Charles; Fuller-Pace, Frances V; Teschendorff, Andrew E; Buluwela, Laki; Ali, Simak

2015-08-28

The Nuclear Receptor (NR) superfamily of transcription factors comprises 48 members, several of which have been implicated in breast cancer. Most important is estrogen receptor-α (ERα), which is a key therapeutic target. ERα action is facilitated by co-operativity with other NR and there is evidence that ERα function may be recapitulated by other NRs in ERα-negative breast cancer. In order to examine the inter-relationships between nuclear receptors, and to obtain evidence for previously unsuspected roles for any NRs, we undertook quantitative RT-PCR and bioinformatics analysis to examine their expression in breast cancer. While most NRs were expressed, bioinformatic analyses differentiated tumours into distinct prognostic groups that were validated by analyzing public microarray data sets. Although ERα and progesterone receptor were dominant in distinguishing prognostic groups, other NR strengthened these groups. Clustering analysis identified several family members with potential importance in breast cancer. Specifically, RORγ is identified as being co-expressed with ERα, whilst several NRs are preferentially expressed in ERα-negative disease, with TLX expression being prognostic in this subtype. Functional studies demonstrated the importance of TLX in regulating growth and invasion in ERα-negative breast cancer cells.

Glucocorticoid receptor interacts with PNRC2 in a ligand-dependent manner to recruit UPF1 for rapid mRNA degradation.

PubMed

Cho, Hana; Park, Ok Hyun; Park, Joori; Ryu, Incheol; Kim, Jeonghan; Ko, Jesang; Kim, Yoon Ki

2015-03-31

Glucocorticoid receptor (GR), which was originally known to function as a nuclear receptor, plays a role in rapid mRNA degradation by acting as an RNA-binding protein. The mechanism by which this process occurs remains unknown. Here, we demonstrate that GR, preloaded onto the 5'UTR of a target mRNA, recruits UPF1 through proline-rich nuclear receptor coregulatory protein 2 (PNRC2) in a ligand-dependent manner, so as to elicit rapid mRNA degradation. We call this process GR-mediated mRNA decay (GMD). Although GMD, nonsense-mediated mRNA decay (NMD), and staufen-mediated mRNA decay (SMD) share upstream frameshift 1 (UPF1) and PNRC2, we find that GMD is mechanistically distinct from NMD and SMD. We also identify de novo cellular GMD substrates using microarray analysis. Intriguingly, GMD functions in the chemotaxis of human monocytes by targeting chemokine (C-C motif) ligand 2 (CCL2) mRNA. Thus, our data provide molecular evidence of a posttranscriptional role of the well-studied nuclear hormone receptor, GR, which is traditionally considered a transcription factor.

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

PubMed Central

Zhu, Yuerong; Zhu, Yuelin; Xu, Wei

2008-01-01

Background Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand. Results EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data. Conclusion EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from . PMID:18218103

Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences.

PubMed

Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki

2010-06-01

Tests of differentially expressed genes (DEGs) from microarray experiments are based on the null hypothesis that genes that are irrelevant to the phenotype/stimulus are expressed equally in the target and control samples. However, this strict hypothesis is not always true, as there can be several transcriptomic background differences between target and control samples, including different cell/tissue types, different cell cycle stages and different biological donors. These differences lead to increased false positives, which have little biological/medical significance. In this article, we propose a statistical framework to identify DEGs between target and control samples from expression microarray data allowing transcriptomic background differences between these samples by introducing a modified null hypothesis that the gene expression background difference is normally distributed. We use an iterative procedure to perform robust estimation of the null hypothesis and identify DEGs as outliers. We evaluated our method using our own triplicate microarray experiment, followed by validations with reverse transcription-polymerase chain reaction (RT-PCR) and on the MicroArray Quality Control dataset. The evaluations suggest that our technique (i) results in less false positive and false negative results, as measured by the degree of agreement with RT-PCR of the same samples, (ii) can be applied to different microarray platforms and results in better reproducibility as measured by the degree of DEG identification concordance both intra- and inter-platforms and (iii) can be applied efficiently with only a few microarray replicates. Based on these evaluations, we propose that this method not only identifies more reliable and biologically/medically significant DEG, but also reduces the power-cost tradeoff problem in the microarray field. Source code and binaries freely available for download at http://comonca.org.cn/fdca/resources/softwares/deg.zip.

Differential correlation for sequencing data.

PubMed

Siska, Charlotte; Kechris, Katerina

2017-01-19

Several methods have been developed to identify differential correlation (DC) between pairs of molecular features from -omics studies. Most DC methods have only been tested with microarrays and other platforms producing continuous and Gaussian-like data. Sequencing data is in the form of counts, often modeled with a negative binomial distribution making it difficult to apply standard correlation metrics. We have developed an R package for identifying DC called Discordant which uses mixture models for correlations between features and the Expectation Maximization (EM) algorithm for fitting parameters of the mixture model. Several correlation metrics for sequencing data are provided and tested using simulations. Other extensions in the Discordant package include additional modeling for different types of differential correlation, and faster implementation, using a subsampling routine to reduce run-time and address the assumption of independence between molecular feature pairs. With simulations and breast cancer miRNA-Seq and RNA-Seq data, we find that Spearman's correlation has the best performance among the tested correlation methods for identifying differential correlation. Application of Spearman's correlation in the Discordant method demonstrated the most power in ROC curves and sensitivity/specificity plots, and improved ability to identify experimentally validated breast cancer miRNA. We also considered including additional types of differential correlation, which showed a slight reduction in power due to the additional parameters that need to be estimated, but more versatility in applications. Finally, subsampling within the EM algorithm considerably decreased run-time with negligible effect on performance. A new method and R package called Discordant is presented for identifying differential correlation with sequencing data. Based on comparisons with different correlation metrics, this study suggests Spearman's correlation is appropriate for sequencing data, but other correlation metrics are available to the user depending on the application and data type. The Discordant method can also be extended to investigate additional DC types and subsampling with the EM algorithm is now available for reduced run-time. These extensions to the R package make Discordant more robust and versatile for multiple -omics studies.

Three Generations of FPGA DAQ Development for the ATLAS Pixel Detector

NASA Astrophysics Data System (ADS)

Mayer, Joseph A., II

The Large Hadron Collider (LHC) at the European Center for Nuclear Research (CERN) tracks a schedule of long physics runs, followed by periods of inactivity known as Long Shutdowns (LS). During these LS phases both the LHC, and the experiments around its ring, undergo maintenance and upgrades. For the LHC these upgrades improve their ability to create data for physicists; the more data the LHC can create the more opportunities there are for rare events to appear that physicists will be interested in. The experiments upgrade so they can record the data and ensure the event won't be missed. Currently the LHC is in Run 2 having completed the first LS of three. This thesis focuses on the development of Field-Programmable Gate Array (FPGA)-based readout systems that span across three major tasks of the ATLAS Pixel data acquisition (DAQ) system. The evolution of Pixel DAQ's Readout Driver (ROD) card is presented. Starting from improvements made to the new Insertable B-Layer (IBL) ROD design, which was part of the LS1 upgrade; to upgrading the old RODs from Run 1 to help them run more efficiently in Run 2. It also includes the research and development of FPGA based DAQs and integrated circuit emulators for the ITk upgrade which will occur during LS3 in 2025.

A Java-based tool for the design of classification microarrays.

PubMed

Meng, Da; Broschat, Shira L; Call, Douglas R

2008-08-04

Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes.

Implementation of mutual information and bayes theorem for classification microarray data

NASA Astrophysics Data System (ADS)

Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda

2018-03-01

Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.

Protein microarray with horseradish peroxidase chemiluminescence for quantification of serum α-fetoprotein.

PubMed

Zhao, Yuanshun; Zhang, Yonghong; Lin, Dongdong; Li, Kang; Yin, Chengzeng; Liu, Xiuhong; Jin, Boxun; Sun, Libo; Liu, Jinhua; Zhang, Aiying; Li, Ning

2015-10-01

To develop and evaluate a protein microarray assay with horseradish peroxidase (HRP) chemiluminescence for quantification of α-fetoprotein (AFP) in serum from patients with hepatocellular carcinoma (HCC). A protein microarray assay for AFP was developed. Serum was collected from patients with HCC and healthy control subjects. AFP was quantified using protein microarray and enzyme-linked immunosorbent assay (ELISA). Serum AFP concentrations determined via protein microarray were positively correlated (r = 0.973) with those determined via ELISA in patients with HCC (n = 60) and healthy control subjects (n = 30). Protein microarray showed 80% sensitivity and 100% specificity for HCC diagnosis. ELISA had 83.3% sensitivity and 100% specificity. Protein microarray effectively distinguished between patients with HCC and healthy control subjects (area under ROC curve 0.974; 95% CI 0.000, 1.000). Protein microarray is a rapid, simple and low-cost alternative to ELISA for detecting AFP in human serum. © The Author(s) 2015.

DNA Microarray Detection of 18 Important Human Blood Protozoan Species

PubMed Central

Chen, Jun-Hu; Feng, Xin-Yu; Chen, Shao-Hong; Cai, Yu-Chun; Lu, Yan; Zhou, Xiao-Nong; Chen, Jia-Xu; Hu, Wei

2016-01-01

Background Accurate detection of blood protozoa from clinical samples is important for diagnosis, treatment and control of related diseases. In this preliminary study, a novel DNA microarray system was assessed for the detection of Plasmodium, Leishmania, Trypanosoma, Toxoplasma gondii and Babesia in humans, animals, and vectors, in comparison with microscopy and PCR data. Developing a rapid, simple, and convenient detection method for protozoan detection is an urgent need. Methodology/Principal Findings The microarray assay simultaneously identified 18 species of common blood protozoa based on the differences in respective target genes. A total of 20 specific primer pairs and 107 microarray probes were selected according to conserved regions which were designed to identify 18 species in 5 blood protozoan genera. The positive detection rate of the microarray assay was 91.78% (402/438). Sensitivity and specificity for blood protozoan detection ranged from 82.4% (95%CI: 65.9% ~ 98.8%) to 100.0% and 95.1% (95%CI: 93.2% ~ 97.0%) to 100.0%, respectively. Positive predictive value (PPV) and negative predictive value (NPV) ranged from 20.0% (95%CI: 2.5% ~ 37.5%) to 100.0% and 96.8% (95%CI: 95.0% ~ 98.6%) to 100.0%, respectively. Youden index varied from 0.82 to 0.98. The detection limit of the DNA microarrays ranged from 200 to 500 copies/reaction, similar to PCR findings. The concordance rate between microarray data and DNA sequencing results was 100%. Conclusions/Significance Overall, the newly developed microarray platform provides a convenient, highly accurate, and reliable clinical assay for the determination of blood protozoan species. PMID:27911895

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays

PubMed Central

Goodman, Corey W.; Major, Heather J.; Walls, William D.; Sheffield, Val C.; Casavant, Thomas L.; Darbro, Benjamin W.

2016-01-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. PMID:25595567

High-Throughput Nano-Biofilm Microarray for Antifungal Drug Discovery

DTIC Science & Technology

2013-06-25

High-Throughput Nano-Biofilm Microarray for Antifungal Drug Discovery Anand Srinivasan,a, c Kai P. Leung,d Jose L. Lopez-Ribot,b, c Anand K...Ramasubramaniana, c Departments of Biomedical Engineeringa and Biologyb and South Texas Center for Emerging Infectious Diseases, c The University of Texas at San...of the opportunistic fungal pathogen Candida albicans on a microarray platform. The mi- croarray consists of 1,200 individual cultures of 30 nl of C

Improvements of the target lifetime in the RHIC polarimeter

NASA Astrophysics Data System (ADS)

Steski, D. B.; Huang, H.; Kewisch, J.; Sukhanova, L.; Zelenski, A.

2018-05-01

The Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory (BNL) is the only collider in the world to collide polarized protons. It is critical to the RHIC experimental program that the polarization of the proton beam is measured. This is accomplished with the Coulomb Nuclear Interference (CNI) polarimeter. The targets used in the RHIC CNI polarimeter are 50 nm thick, 25 mm long and <10 µm wide. As the beam intensity in RHIC has increased and the beam size has decreased, the lifetime of these targets has decreased dramatically. During the 2013 polarized proton experimental run, the targets needed to be replaced twice. This resulted in additional work and lost beam time. Before the 2015 experimental run, metal shields were installed around the ends of the targets which greatly improved the target lifetime. The results from the 2015 experimental run and plans for the 2017 experimental run will be discussed.

Multiplexed Analysis of Serum Breast and Ovarian Cancer Markers by Means of Suspension Bead-quantum Dot Microarrays

NASA Astrophysics Data System (ADS)

Brazhnik, Kristina; Sokolova, Zinaida; Baryshnikova, Maria; Bilan, Regina; Nabiev, Igor; Sukhanova, Alyona

Multiplexed analysis of cancer markers is crucial for early tumor diagnosis and screening. We have designed lab-on-a-bead microarray for quantitative detection of three breast cancer markers in human serum. Quantum dots were used as bead-bound fluorescent tags for identifying each marker by means of flow cytometry. Antigen-specific beads reliably detected CA 15-3, CEA, and CA 125 in serum samples, providing clear discrimination between the samples with respect to the antigen levels. The novel microarray is advantageous over the routine single-analyte ones due to the simultaneous detection of various markers. Therefore the developed microarray is a promising tool for serum tumor marker profiling.

Potassium Channel Interacting Protein 2 (KChIP2) is not a transcriptional regulator of cardiac electrical remodeling

PubMed Central

Winther, Sine V.; Tuomainen, Tomi; Borup, Rehannah; Tavi, Pasi; Antoons, Gudrun; Thomsen, Morten B.

2016-01-01

The heart-failure relevant Potassium Channel Interacting Protein 2 (KChIP2) augments CaV1.2 and KV4.3. KChIP3 represses CaV1.2 transcription in cardiomyocytes via interaction with regulatory DNA elements. Hence, we tested nuclear presence of KChIP2 and if KChIP2 translocates into the nucleus in a Ca2+ dependent manner. Cardiac biopsies from human heart-failure patients and healthy donor controls showed that nuclear KChIP2 abundance was significantly increased in heart failure; however, this was secondary to a large variation of total KChIP2 content. Administration of ouabain did not increase KChIP2 content in nuclear protein fractions in anesthetized mice. KChIP2 was expressed in cell lines, and Ca2+ ionophores were applied in a concentration- and time-dependent manner. The cell lines had KChIP2-immunoreactive protein in the nucleus in the absence of treatments to modulate intracellular Ca2+ concentration. Neither increasing nor decreasing intracellular Ca2+ concentrations caused translocation of KChIP2. Microarray analysis did not identify relief of transcriptional repression in murine KChIP2−/− heart samples. We conclude that although there is a baseline presence of KChIP2 in the nucleus both in vivo and in vitro, KChIP2 does not directly regulate transcriptional activity. Moreover, the nuclear transport of KChIP2 is not dependent on Ca2+. Thus, KChIP2 does not function as a conventional transcription factor in the heart. PMID:27349185

Solanum torvum responses to the root-knot nematode Meloidogyne incognita

PubMed Central

2013-01-01

Background Solanum torvum Sw is worldwide employed as rootstock for eggplant cultivation because of its vigour and resistance/tolerance to the most serious soil-borne diseases as bacterial, fungal wilts and root-knot nematodes. The little information on Solanum torvum (hereafter Torvum) resistance mechanisms, is mostly attributable to the lack of genomic tools (e.g. dedicated microarray) as well as to the paucity of database information limiting high-throughput expression studies in Torvum. Results As a first step towards transcriptome profiling of Torvum inoculated with the nematode M. incognita, we built a Torvum 3’ transcript catalogue. One-quarter of a 454 full run resulted in 205,591 quality-filtered reads. De novo assembly yielded 24,922 contigs and 11,875 singletons. Similarity searches of the S. torvum transcript tags catalogue produced 12,344 annotations. A 30,0000 features custom combimatrix chip was then designed and microarray hybridizations were conducted for both control and 14 dpi (day post inoculation) with Meloidogyne incognita-infected roots samples resulting in 390 differentially expressed genes (DEG). We also tested the chip with samples from the phylogenetically-related nematode-susceptible eggplant species Solanum melongena. An in-silico validation strategy was developed based on assessment of sequence similarity among Torvum probes and eggplant expressed sequences available in public repositories. GO term enrichment analyses with the 390 Torvum DEG revealed enhancement of several processes as chitin catabolism and sesquiterpenoids biosynthesis, while no GO term enrichment was found with eggplant DEG. The genes identified from S. torvum catalogue, bearing high similarity to known nematode resistance genes, were further investigated in view of their potential role in the nematode resistance mechanism. Conclusions By combining 454 pyrosequencing and microarray technology we were able to conduct a cost-effective global transcriptome profiling in a non-model species. In addition, the development of an in silico validation strategy allowed to further extend the use of the custom chip to a related species and to assess by comparison the expression of selected genes without major concerns of artifacts. The expression profiling of S. torvum responses to nematode infection points to sesquiterpenoids and chitinases as major effectors of nematode resistance. The availability of the long sequence tags in S. torvum catalogue will allow precise identification of active nematocide/nematostatic compounds and associated enzymes posing the basis for exploitation of these resistance mechanisms in other species. PMID:23937585

Usefulness of a break-apart FISH assay in the diagnosis of Xp11.2 translocation renal cell carcinoma.

PubMed

Kim, Soo Hee; Choi, Yoomi; Jeong, Hae Yeon; Lee, Kyoungbun; Chae, Ji Youn; Moon, Kyung Chul

2011-09-01

Xp11.2 translocation renal cell carcinoma (RCC) is a rare subtype of RCC predominantly reported in young patients. It results from gene fusions between the transcription factor E3 (TFE3) gene, which is located on chromosome Xp11.2, and various fusion partners. Recently, a dual color, break-apart fluorescence in situ hybridization (FISH) assay to detect Xp11.2 translocation was reported. We performed this study to evaluate the usefulness of the FISH assay in the diagnosis of Xp11.2 translocation RCC using a commercially available TFE3 break-apart probe. We immunohistochemically analyzed TFE3 nuclear expression in 809 cases of RCCs using 14 tissue microarray blocks and selected nine cases those showed moderate to strong positive nuclear immunoreactivity for TFE3. The extent of TFE3 nuclear expression was variable. The TFE3 FISH assay was performed in these 9 selected cases and 44 negative control cases. Only four out of nine selected cases showed the TFE3 break-apart signal. TFE3 FISH-positive cases mainly showed diffuse and strong TFE3 immunopositivity, but one case revealed focal and moderate TFE3 staining. On the contrary, TFE3 FISH-negative cases mainly revealed focal and moderate TFE3 immunoreactivity, however, one FISH-negative case revealed diffuse and strong TFE3 nuclear immunopositivity. All negative control cases revealed normal TFE3 FISH results. Our results reveal that TFE3 immunohistochemistry can show false-positive results, and that the TFE3 break-apart FISH assay is a useful complementary method for confirming the diagnosis of Xp11.2 translocation RCC.

The solid state physics programme at ISOLDE: recent developments and perspectives

NASA Astrophysics Data System (ADS)

Johnston, Karl; Schell, Juliana; Correia, J. G.; Deicher, M.; Gunnlaugsson, H. P.; Fenta, A. S.; David-Bosne, E.; Costa, A. R. G.; Lupascu, Doru C.

2017-10-01

Solid state physics (SSP) research at ISOLDE has been running since the mid-1970s and accounts for about 10%-15% of the overall physics programme. ISOLDE is the world flagship for the on-line production of exotic radioactive isotopes, with high yields, high elemental selectivity and isotopic purity. Consequently, it hosts a panoply of state-of-the-art nuclear techniques which apply nuclear methods to research on life sciences, material science and bio-chemical physics. The ease of detecting radioactivity—<1 ppm concentrations—is one of the features which distinguishes the use of radioisotopes for materials science research. The manner in which nuclear momenta of excited nuclear states interact with their local electronic and magnetic environment, or how charged emitted particles interact with the crystalline lattices allow the determination of the location, its action and the role of the selected impurity element at the nanoscopic state. ISOLDE offers an unrivalled range of available radioactive elements and this is attracting an increasing user community in the field of nuclear SSP research and brings together a community of materials scientists and specialists in nuclear solid state techniques. This article describes the current status of this programme along with recent illustrative results, predicting a bright future for these unique research methods and collaborations.

A multiplex reverse transcription PCR and automated electronic microarray assay for detection and differentiation of seven viruses affecting swine.

PubMed

Erickson, A; Fisher, M; Furukawa-Stoffer, T; Ambagala, A; Hodko, D; Pasick, J; King, D P; Nfon, C; Ortega Polo, R; Lung, O

2018-04-01

Microarray technology can be useful for pathogen detection as it allows simultaneous interrogation of the presence or absence of a large number of genetic signatures. However, most microarray assays are labour-intensive and time-consuming to perform. This study describes the development and initial evaluation of a multiplex reverse transcription (RT)-PCR and novel accompanying automated electronic microarray assay for simultaneous detection and differentiation of seven important viruses that affect swine (foot-and-mouth disease virus [FMDV], swine vesicular disease virus [SVDV], vesicular exanthema of swine virus [VESV], African swine fever virus [ASFV], classical swine fever virus [CSFV], porcine respiratory and reproductive syndrome virus [PRRSV] and porcine circovirus type 2 [PCV2]). The novel electronic microarray assay utilizes a single, user-friendly instrument that integrates and automates capture probe printing, hybridization, washing and reporting on a disposable electronic microarray cartridge with 400 features. This assay accurately detected and identified a total of 68 isolates of the seven targeted virus species including 23 samples of FMDV, representing all seven serotypes, and 10 CSFV strains, representing all three genotypes. The assay successfully detected viruses in clinical samples from the field, experimentally infected animals (as early as 1 day post-infection (dpi) for FMDV and SVDV, 4 dpi for ASFV, 5 dpi for CSFV), as well as in biological material that were spiked with target viruses. The limit of detection was 10 copies/μl for ASFV, PCV2 and PRRSV, 100 copies/μl for SVDV, CSFV, VESV and 1,000 copies/μl for FMDV. The electronic microarray component had reduced analytical sensitivity for several of the target viruses when compared with the multiplex RT-PCR. The integration of capture probe printing allows custom onsite array printing as needed, while electrophoretically driven hybridization generates results faster than conventional microarrays that rely on passive hybridization. With further refinement, this novel, rapid, highly automated microarray technology has potential applications in multipathogen surveillance of livestock diseases. © 2017 Her Majesty the Queen in Right of Canada • Transboundary and Emerging Diseases.

The use of nuclear data in the field of nuclear fuel recycling

NASA Astrophysics Data System (ADS)

Martin, Julie-Fiona; Launay, Agnès; Grassi, Gabriele; Binet, Christophe; Lelandais, Jacques; Lecampion, Erick

2017-09-01

AREVA NC La Hague facility is the first step of the nuclear fuel recycling process implemented in France. The processing of the used fuel is governed by high standards of criticality-safety, and strong expectations on the quality of end-products. From the received used fuel assemblies, the plutonium and the uranium are extracted for further energy production purposes within the years following the reprocessing. Furthermore, the ultimate waste - fission products and minor actinides on the one hand, and hulls and end-pieces on the other hand - is adequately packaged for long term disposal. The used fuel is therefore separated into very different materials, and time scales which come into account may be longer than in some other nuclear fields of activity. Given the variety of the handled nuclear materials, as well as the time scales at stake, the importance given to some radionuclides, and hence to the associated nuclear data, can also be specific to the AREVA NC La Hague plant. A study has thus been led to identify a list of the most important radionuclides for the AREVA NC La Hague plant applications, relying on the running constraints of the facility, and the end-products expectations. The activities at the AREVA NC La Hague plant are presented, and the methodology to extract the most important radionuclides for the reprocessing process is detailed.

Pasta Nucleosynthesis: Molecular dynamics simulations of nuclear statistical equilibrium

NASA Astrophysics Data System (ADS)

Caplan, Matthew; Horowitz, Charles; da Silva Schneider, Andre; Berry, Donald

2014-09-01

We simulate the decompression of cold dense nuclear matter, near the nuclear saturation density, in order to study the role of nuclear pasta in r-process nucleosynthesis in neutron star mergers. Our simulations are performed using a classical molecular dynamics model with 51 200 and 409 600 nucleons, and are run on GPUs. We expand our simulation region to decompress systems from initial densities of 0.080 fm-3 down to 0.00125 fm-3. We study proton fractions of YP = 0.05, 0.10, 0.20, 0.30, and 0.40 at T = 0.5, 0.75, and 1 MeV. We calculate the composition of the resulting systems using a cluster algorithm. This composition is in good agreement with nuclear statistical equilibrium models for temperatures of 0.75 and 1 MeV. However, for proton fractions greater than YP = 0.2 at a temperature of T = 0.5 MeV, the MD simulations produce non-equilibrium results with large rod-like nuclei. Our MD model is valid at higher densities than simple nuclear statistical equilibrium models and may help determine the initial temperatures and proton fractions of matter ejected in mergers.

Nonadiabatic dynamics in intense continuous wave laser fields and real-time observation of the associated wavepacket bifurcation in terms of spectrogram of induced photon emission.

PubMed

Mizuno, Yuta; Arasaki, Yasuki; Takatsuka, Kazuo

2016-11-14

We propose a theoretical principle to directly monitor the bifurcation of quantum wavepackets passing through nonadiabatic regions of a molecule that is placed in intense continuous wave (CW) laser fields. This idea makes use of the phenomenon of laser-driven photon emission from molecules that can undergo nonadiabatic transitions between ionic and covalent potential energy surfaces like Li + F - and LiF. The resultant photon emission spectra are of anomalous yet characteristic frequency and intensity, if pumped to an energy level in which the nonadiabatic region is accessible and placed in a CW laser field. The proposed method is designed to take the time-frequency spectrogram with an appropriate time-window from this photon emission to detect the time evolution of the frequency and intensity, which depends on the dynamics and location of the relevant nuclear wavepackets. This method is specifically designed for the study of dynamics in intense CW laser fields and is rather limited in scope than other techniques for femtosecond chemical dynamics in vacuum. The following characteristic features of dynamics can be mapped onto the spectrogram: (1) the period of driven vibrational motion (temporally confined vibrational states in otherwise dissociative channels, the period and other states of which dramatically vary depending on the CW driving lasers applied), (2) the existence of multiple nuclear wavepackets running individually on the field-dressed potential energy surfaces, (3) the time scale of coherent interaction between the nuclear wavepackets running on ionic and covalent electronic states after their branching (the so-called coherence time in the terminology of the theory of nonadiabatic interaction), and so on.

Nonadiabatic dynamics in intense continuous wave laser fields and real-time observation of the associated wavepacket bifurcation in terms of spectrogram of induced photon emission

NASA Astrophysics Data System (ADS)

Mizuno, Yuta; Arasaki, Yasuki; Takatsuka, Kazuo

2016-11-01

We propose a theoretical principle to directly monitor the bifurcation of quantum wavepackets passing through nonadiabatic regions of a molecule that is placed in intense continuous wave (CW) laser fields. This idea makes use of the phenomenon of laser-driven photon emission from molecules that can undergo nonadiabatic transitions between ionic and covalent potential energy surfaces like Li+ F- and LiF. The resultant photon emission spectra are of anomalous yet characteristic frequency and intensity, if pumped to an energy level in which the nonadiabatic region is accessible and placed in a CW laser field. The proposed method is designed to take the time-frequency spectrogram with an appropriate time-window from this photon emission to detect the time evolution of the frequency and intensity, which depends on the dynamics and location of the relevant nuclear wavepackets. This method is specifically designed for the study of dynamics in intense CW laser fields and is rather limited in scope than other techniques for femtosecond chemical dynamics in vacuum. The following characteristic features of dynamics can be mapped onto the spectrogram: (1) the period of driven vibrational motion (temporally confined vibrational states in otherwise dissociative channels, the period and other states of which dramatically vary depending on the CW driving lasers applied), (2) the existence of multiple nuclear wavepackets running individually on the field-dressed potential energy surfaces, (3) the time scale of coherent interaction between the nuclear wavepackets running on ionic and covalent electronic states after their branching (the so-called coherence time in the terminology of the theory of nonadiabatic interaction), and so on.

The Microarray Revolution: Perspectives from Educators

ERIC Educational Resources Information Center

Brewster, Jay L.; Beason, K. Beth; Eckdahl, Todd T.; Evans, Irene M.

2004-01-01

In recent years, microarray analysis has become a key experimental tool, enabling the analysis of genome-wide patterns of gene expression. This review approaches the microarray revolution with a focus upon four topics: 1) the early development of this technology and its application to cancer diagnostics; 2) a primer of microarray research,…

Identification of apoptosis-related PLZF target genes

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

Bernardo, Maria Victoria; Yelo, Estefania; Gimeno, Lourdes

2007-07-27

The PLZF gene encodes a BTB/POZ-zinc finger-type transcription factor, involved in physiological development, proliferation, differentiation, and apoptosis. In this paper, we investigate proliferation, survival, and gene expression regulation in stable clones from the human haematopoietic K562, DG75, and Jurkat cell lines with inducible expression of PLZF. In Jurkat cells, but not in K562 and DG75 cells, PLZF induced growth suppression and apoptosis in a cell density-dependent manner. Deletion of the BTB/POZ domain of PLZF abrogated growth suppression and apoptosis. PLZF was expressed with a nuclear speckled pattern distinctively in the full-length PLZF-expressing Jurkat clones, suggesting that the nuclear speckled localizationmore » is required for PLZF-induced apoptosis. By microarray analysis, we identified that the apoptosis-inducer TP53INP1, ID1, and ID3 genes were upregulated, and the apoptosis-inhibitor TERT gene was downregulated. The identification of apoptosis-related PLZF target genes may have biological and clinical relevance in cancer typified by altered PLZF expression.« less

Glycan microarray screening assay for glycosyltransferase specificities.

PubMed

Peng, Wenjie; Nycholat, Corwin M; Razi, Nahid

2013-01-01

Glycan microarrays represent a high-throughput approach to determining the specificity of glycan-binding proteins against a large set of glycans in a single format. This chapter describes the use of a glycan microarray platform for evaluating the activity and substrate specificity of glycosyltransferases (GTs). The methodology allows simultaneous screening of hundreds of immobilized glycan acceptor substrates by in situ incubation of a GT and its appropriate donor substrate on the microarray surface. Using biotin-conjugated donor substrate enables direct detection of the incorporated sugar residues on acceptor substrates on the array. In addition, the feasibility of the method has been validated using label-free donor substrate combined with lectin-based detection of product to assess enzyme activity. Here, we describe the application of both procedures to assess the specificity of a recombinant human α2-6 sialyltransferase. This technique is readily adaptable to studying other glycosyltransferases.

LS-CAP: an algorithm for identifying cytogenetic aberrations in hepatocellular carcinoma using microarray data.

PubMed

He, Xianmin; Wei, Qing; Sun, Meiqian; Fu, Xuping; Fan, Sichang; Li, Yao

2006-05-01

Biological techniques such as Array-Comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH) and affymetrix single nucleotide pleomorphism (SNP) array have been used to detect cytogenetic aberrations. However, on genomic scale, these techniques are labor intensive and time consuming. Comparative genomic microarray analysis (CGMA) has been used to identify cytogenetic changes in hepatocellular carcinoma (HCC) using gene expression microarray data. However, CGMA algorithm can not give precise localization of aberrations, fails to identify small cytogenetic changes, and exhibits false negatives and positives. Locally un-weighted smoothing cytogenetic aberrations prediction (LS-CAP) based on local smoothing and binomial distribution can be expected to address these problems. LS-CAP algorithm was built and used on HCC microarray profiles. Eighteen cytogenetic abnormalities were identified, among them 5 were reported previously, and 12 were proven by CGH studies. LS-CAP effectively reduced the false negatives and positives, and precisely located small fragments with cytogenetic aberrations.

A remark on copy number variation detection methods.

PubMed

Li, Shuo; Dou, Xialiang; Gao, Ruiqi; Ge, Xinzhou; Qian, Minping; Wan, Lin

2018-01-01

Copy number variations (CNVs) are gain and loss of DNA sequence of a genome. High throughput platforms such as microarrays and next generation sequencing technologies (NGS) have been applied for genome wide copy number losses. Although progress has been made in both approaches, the accuracy and consistency of CNV calling from the two platforms remain in dispute. In this study, we perform a deep analysis on copy number losses on 254 human DNA samples, which have both SNP microarray data and NGS data publicly available from Hapmap Project and 1000 Genomes Project respectively. We show that the copy number losses reported from Hapmap Project and 1000 Genome Project only have < 30% overlap, while these reports are required to have cross-platform (e.g. PCR, microarray and high-throughput sequencing) experimental supporting by their corresponding projects, even though state-of-art calling methods were employed. On the other hand, copy number losses are found directly from HapMap microarray data by an accurate algorithm, i.e. CNVhac, almost all of which have lower read mapping depth in NGS data; furthermore, 88% of which can be supported by the sequences with breakpoint in NGS data. Our results suggest the ability of microarray calling CNVs and the possible introduction of false negatives from the unessential requirement of the additional cross-platform supporting. The inconsistency of CNV reports from Hapmap Project and 1000 Genomes Project might result from the inadequate information containing in microarray data, the inconsistent detection criteria, or the filtration effect of cross-platform supporting. The statistical test on CNVs called from CNVhac show that the microarray data can offer reliable CNV reports, and majority of CNV candidates can be confirmed by raw sequences. Therefore, the CNV candidates given by a good caller could be highly reliable without cross-platform supporting, so additional experimental information should be applied in need instead of necessarily.

RELAP5-3D Resolution of Known Restart/Backup Issues

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

Mesina, George L.; Anderson, Nolan A.

2014-12-01

The state-of-the-art nuclear reactor system safety analysis computer program developed at the Idaho National Laboratory (INL), RELAP5-3D, continues to adapt to changes in computer hardware and software and to develop to meet the ever-expanding needs of the nuclear industry. To continue at the forefront, code testing must evolve with both code and industry developments, and it must work correctly. To best ensure this, the processes of Software Verification and Validation (V&V) are applied. Verification compares coding against its documented algorithms and equations and compares its calculations against analytical solutions and the method of manufactured solutions. A form of this, sequentialmore » verification, checks code specifications against coding only when originally written then applies regression testing which compares code calculations between consecutive updates or versions on a set of test cases to check that the performance does not change. A sequential verification testing system was specially constructed for RELAP5-3D to both detect errors with extreme accuracy and cover all nuclear-plant-relevant code features. Detection is provided through a “verification file” that records double precision sums of key variables. Coverage is provided by a test suite of input decks that exercise code features and capabilities necessary to model a nuclear power plant. A matrix of test features and short-running cases that exercise them is presented. This testing system is used to test base cases (called null testing) as well as restart and backup cases. It can test RELAP5-3D performance in both standalone and coupled (through PVM to other codes) runs. Application of verification testing revealed numerous restart and backup issues in both standalone and couple modes. This document reports the resolution of these issues.« less

How a tertiary medical nuclear medicine department at the Himalayan area in India can be established and function in an exemplary manner. Basic rules revisited.

PubMed

Dhingra, Vandana Kumar; Saini, Sunil; Basu, Sandip

2015-01-01

We describe and discuss the various medical, social and financial aspects of setting up, and optimizing, working conditions of a tertiary Nuclear Medicine Department. This department was established in a North Indian state which comprises 93% of hilly area. During the first three years after establishment we have developed infrastructure, cooperation with other departments, improved radiation safety and cost effectiveness of our work and designed future perspectives. The facility was established in a cancer center of a tertiary care hospital where a medical college infrastructure was developed. National guidelines formulated by the Atomic Energy Regulatory Board (AERB) were followed. Our department served a population area of 10.08 million inhabitants. Over the first three years 2,400 patients underwent diagnostic scans and 106 patients underwent low dose radioiodine treatment for thyrotoxicosis. To optimize resources and at the same time, enhance their effectivity, we procured our (99)Mo/ (99m)Tc generator every other week and arranged our daily programme accordingly. Fractionation of cold kits allowed us to perform low cost in-vivo procedures on a daily basis and to save the department's running costs by 30%-50%. We run continuing education nuclear medicine programmes for referring physicians, medical students and paramedical workers which were included in routine practice which led to a consistent growth in patients referral. The need for a positron emission tomography/computed tomography (PET/CT) scan and high dose treatment department for thyroid cancer was strongly felt. Our nuclear medicine department in a peripheral region of a developing country applied better logistics by procuring new generator every fortnight, fractionating the cold kits and by organizing complete teaching programmes.

Recognition of multiple imbalanced cancer types based on DNA microarray data using ensemble classifiers.

PubMed

Yu, Hualong; Hong, Shufang; Yang, Xibei; Ni, Jun; Dan, Yuanyuan; Qin, Bin

2013-01-01

DNA microarray technology can measure the activities of tens of thousands of genes simultaneously, which provides an efficient way to diagnose cancer at the molecular level. Although this strategy has attracted significant research attention, most studies neglect an important problem, namely, that most DNA microarray datasets are skewed, which causes traditional learning algorithms to produce inaccurate results. Some studies have considered this problem, yet they merely focus on binary-class problem. In this paper, we dealt with multiclass imbalanced classification problem, as encountered in cancer DNA microarray, by using ensemble learning. We utilized one-against-all coding strategy to transform multiclass to multiple binary classes, each of them carrying out feature subspace, which is an evolving version of random subspace that generates multiple diverse training subsets. Next, we introduced one of two different correction technologies, namely, decision threshold adjustment or random undersampling, into each training subset to alleviate the damage of class imbalance. Specifically, support vector machine was used as base classifier, and a novel voting rule called counter voting was presented for making a final decision. Experimental results on eight skewed multiclass cancer microarray datasets indicate that unlike many traditional classification approaches, our methods are insensitive to class imbalance.

16S rRNA gene-based phylogenetic microarray for simultaneous identification of members of the genus Burkholderia.

PubMed

Schönmann, Susan; Loy, Alexander; Wimmersberger, Céline; Sobek, Jens; Aquino, Catharine; Vandamme, Peter; Frey, Beat; Rehrauer, Hubert; Eberl, Leo

2009-04-01

For cultivation-independent and highly parallel analysis of members of the genus Burkholderia, an oligonucleotide microarray (phylochip) consisting of 131 hierarchically nested 16S rRNA gene-targeted oligonucleotide probes was developed. A novel primer pair was designed for selective amplification of a 1.3 kb 16S rRNA gene fragment of Burkholderia species prior to microarray analysis. The diagnostic performance of the microarray for identification and differentiation of Burkholderia species was tested with 44 reference strains of the genera Burkholderia, Pandoraea, Ralstonia and Limnobacter. Hybridization patterns based on presence/absence of probe signals were interpreted semi-automatically using the novel likelihood-based strategy of the web-tool Phylo- Detect. Eighty-eight per cent of the reference strains were correctly identified at the species level. The evaluated microarray was applied to investigate shifts in the Burkholderia community structure in acidic forest soil upon addition of cadmium, a condition that selected for Burkholderia species. The microarray results were in agreement with those obtained from phylogenetic analysis of Burkholderia 16S rRNA gene sequences recovered from the same cadmiumcontaminated soil, demonstrating the value of the Burkholderia phylochip for determinative and environmental studies.

Development and characterization of a disposable plastic microarray printhead.

PubMed

Griessner, Matthias; Hartig, Dave; Christmann, Alexander; Pohl, Carsten; Schellhase, Michaela; Ehrentreich-Förster, Eva

2011-06-01

During the last decade microarrays have become a powerful analytical tool. Commonly microarrays are produced in a non-contact manner using silicone printheads. However, silicone printheads are expensive and not able to be used as a disposable. Here, we show the development and functional characterization of 8-channel plastic microarray printheads that overcome both disadvantages of their conventional silicone counterparts. A combination of injection-molding and laser processing allows us to produce a high quantity of cheap, customizable and disposable microarray printheads. The use of plastics (e.g., polystyrene) minimizes the need for surface modifications required previously for proper printing results. Time-consuming regeneration processes, cleaning procedures and contaminations caused by residual samples are avoided. The utilization of plastic printheads for viscous liquids, such as cell suspensions or whole blood, is possible. Furthermore, functional parts within the plastic printhead (e.g., particle filters) can be included. Our printhead is compatible with commercially available TopSpot devices but provides additional economic and technical benefits as compared to conventional TopSpot printheads, while fulfilling all requirements demanded on the latter. All in all, this work describes how the field of traditional microarray spotting can be extended significantly by low cost plastic printheads.

Design of microarray experiments for genetical genomics studies.

PubMed

Bueno Filho, Júlio S S; Gilmour, Steven G; Rosa, Guilherme J M

2006-10-01

Microarray experiments have been used recently in genetical genomics studies, as an additional tool to understand the genetic mechanisms governing variation in complex traits, such as for estimating heritabilities of mRNA transcript abundances, for mapping expression quantitative trait loci, and for inferring regulatory networks controlling gene expression. Several articles on the design of microarray experiments discuss situations in which treatment effects are assumed fixed and without any structure. In the case of two-color microarray platforms, several authors have studied reference and circular designs. Here, we discuss the optimal design of microarray experiments whose goals refer to specific genetic questions. Some examples are used to illustrate the choice of a design for comparing fixed, structured treatments, such as genotypic groups. Experiments targeting single genes or chromosomic regions (such as with transgene research) or multiple epistatic loci (such as within a selective phenotyping context) are discussed. In addition, microarray experiments in which treatments refer to families or to subjects (within family structures or complex pedigrees) are presented. In these cases treatments are more appropriately considered to be random effects, with specific covariance structures, in which the genetic goals relate to the estimation of genetic variances and the heritability of transcriptional abundances.

Analysis of Protein-DNA Interaction by Chromatin Immunoprecipitation and DNA Tiling Microarray (ChIP-on-chip).

PubMed

Gao, Hui; Zhao, Chunyan

2018-01-01

Chromatin immunoprecipitation (ChIP) has become the most effective and widely used tool to study the interactions between specific proteins or modified forms of proteins and a genomic DNA region. Combined with genome-wide profiling technologies, such as microarray hybridization (ChIP-on-chip) or massively parallel sequencing (ChIP-seq), ChIP could provide a genome-wide mapping of in vivo protein-DNA interactions in various organisms. Here, we describe a protocol of ChIP-on-chip that uses tiling microarray to obtain a genome-wide profiling of ChIPed DNA.

Microarray slide hybridization using fluorescently labeled cDNA.

PubMed

Ares, Manuel

2014-01-01

Microarray hybridization is used to determine the amount and genomic origins of RNA molecules in an experimental sample. Unlabeled probe sequences for each gene or gene region are printed in an array on the surface of a slide, and fluorescently labeled cDNA derived from the RNA target is hybridized to it. This protocol describes a blocking and hybridization protocol for microarray slides. The blocking step is particular to the chemistry of "CodeLink" slides, but it serves to remind us that almost every kind of microarray has a treatment step that occurs after printing but before hybridization. We recommend making sure of the precise treatment necessary for the particular chemistry used in the slides to be hybridized because the attachment chemistries differ significantly. Hybridization is similar to northern or Southern blots, but on a much smaller scale.

BIOPHYSICAL PROPERTIES OF NUCLEIC ACIDS AT SURFACES RELEVANT TO MICROARRAY PERFORMANCE.

PubMed

Rao, Archana N; Grainger, David W

2014-04-01

Both clinical and analytical metrics produced by microarray-based assay technology have recognized problems in reproducibility, reliability and analytical sensitivity. These issues are often attributed to poor understanding and control of nucleic acid behaviors and properties at solid-liquid interfaces. Nucleic acid hybridization, central to DNA and RNA microarray formats, depends on the properties and behaviors of single strand (ss) nucleic acids (e.g., probe oligomeric DNA) bound to surfaces. ssDNA's persistence length, radius of gyration, electrostatics, conformations on different surfaces and under various assay conditions, its chain flexibility and curvature, charging effects in ionic solutions, and fluorescent labeling all influence its physical chemistry and hybridization under assay conditions. Nucleic acid (e.g., both RNA and DNA) target interactions with immobilized ssDNA strands are highly impacted by these biophysical states. Furthermore, the kinetics, thermodynamics, and enthalpic and entropic contributions to DNA hybridization reflect global probe/target structures and interaction dynamics. Here we review several biophysical issues relevant to oligomeric nucleic acid molecular behaviors at surfaces and their influences on duplex formation that influence microarray assay performance. Correlation of biophysical aspects of single and double-stranded nucleic acids with their complexes in bulk solution is common. Such analysis at surfaces is not commonly reported, despite its importance to microarray assays. We seek to provide further insight into nucleic acid-surface challenges facing microarray diagnostic formats that have hindered their clinical adoption and compromise their research quality and value as genomics tools.

BIOPHYSICAL PROPERTIES OF NUCLEIC ACIDS AT SURFACES RELEVANT TO MICROARRAY PERFORMANCE

PubMed Central

Rao, Archana N.; Grainger, David W.

2014-01-01

Both clinical and analytical metrics produced by microarray-based assay technology have recognized problems in reproducibility, reliability and analytical sensitivity. These issues are often attributed to poor understanding and control of nucleic acid behaviors and properties at solid-liquid interfaces. Nucleic acid hybridization, central to DNA and RNA microarray formats, depends on the properties and behaviors of single strand (ss) nucleic acids (e.g., probe oligomeric DNA) bound to surfaces. ssDNA’s persistence length, radius of gyration, electrostatics, conformations on different surfaces and under various assay conditions, its chain flexibility and curvature, charging effects in ionic solutions, and fluorescent labeling all influence its physical chemistry and hybridization under assay conditions. Nucleic acid (e.g., both RNA and DNA) target interactions with immobilized ssDNA strands are highly impacted by these biophysical states. Furthermore, the kinetics, thermodynamics, and enthalpic and entropic contributions to DNA hybridization reflect global probe/target structures and interaction dynamics. Here we review several biophysical issues relevant to oligomeric nucleic acid molecular behaviors at surfaces and their influences on duplex formation that influence microarray assay performance. Correlation of biophysical aspects of single and double-stranded nucleic acids with their complexes in bulk solution is common. Such analysis at surfaces is not commonly reported, despite its importance to microarray assays. We seek to provide further insight into nucleic acid-surface challenges facing microarray diagnostic formats that have hindered their clinical adoption and compromise their research quality and value as genomics tools. PMID:24765522

The GlueX Experiment: First Results

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

Fanelli, Cristiano

GlueX is a nuclear physics experiment located at the Thomas Jefferson National Accelerator Facility designed to study and understand the nature of confinement in QCD by mapping the spectrum of exotic mesons. The experiment will be able to probe new areas by using photoproduction, i.e. the scattering on nucleon of ~9 GeV linearly polarized photons derived from the recently upgraded CEBAF with a 12 GeV electron beam. Spring 2016 has been characterized by a continued detector commissioning and initial running at the full design energy. The current status of the GlueX detector performance and data collection will be discussed, withmore » a brief overview of first physics results, future run plans, and long term upgrades.« less

Performance Assessments of Generic Nuclear Waste Repositories in Shale

NASA Astrophysics Data System (ADS)

Stein, E. R.; Sevougian, S. D.; Mariner, P. E.; Hammond, G. E.; Frederick, J.

2017-12-01

Simulations of deep geologic disposal of nuclear waste in a generic shale formation showcase Geologic Disposal Safety Assessment (GDSA) Framework, a toolkit for repository performance assessment (PA) whose capabilities include domain discretization (Cubit), multiphysics simulations (PFLOTRAN), uncertainty and sensitivity analysis (Dakota), and visualization (Paraview). GDSA Framework is used to conduct PAs of two generic repositories in shale. The first considers the disposal of 22,000 metric tons heavy metal of commercial spent nuclear fuel. The second considers disposal of defense-related spent nuclear fuel and high level waste. Each PA accounts for the thermal load and radionuclide inventory of applicable waste types, components of the engineered barrier system, and components of the natural barrier system including the host rock shale and underlying and overlying stratigraphic units. Model domains are half-symmetry, gridded with Cubit, and contain between 7 and 22 million grid cells. Grid refinement captures the detail of individual waste packages, emplacement drifts, access drifts, and shafts. Simulations are run in a high performance computing environment on as many as 2048 processes. Equations describing coupled heat and fluid flow and reactive transport are solved with PFLOTRAN, an open-source, massively parallel multiphase flow and reactive transport code. Additional simulated processes include waste package degradation, waste form dissolution, radioactive decay and ingrowth, sorption, solubility, advection, dispersion, and diffusion. Simulations are run to 106 y, and radionuclide concentrations are observed within aquifers at a point approximately 5 km downgradient of the repository. Dakota is used to sample likely ranges of input parameters including waste form and waste package degradation rates and properties of engineered and natural materials to quantify uncertainty in predicted concentrations and sensitivity to input parameters. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525. SAND2017- 8305 A

Fiber-optic microarray for simultaneous detection of multiple harmful algal bloom species.

PubMed

Ahn, Soohyoun; Kulis, David M; Erdner, Deana L; Anderson, Donald M; Walt, David R

2006-09-01

Harmful algal blooms (HABs) are a serious threat to coastal resources, causing a variety of impacts on public health, regional economies, and ecosystems. Plankton analysis is a valuable component of many HAB monitoring and research programs, but the diversity of plankton poses a problem in discriminating toxic from nontoxic species using conventional detection methods. Here we describe a sensitive and specific sandwich hybridization assay that combines fiber-optic microarrays with oligonucleotide probes to detect and enumerate the HAB species Alexandrium fundyense, Alexandrium ostenfeldii, and Pseudo-nitzschia australis. Microarrays were prepared by loading oligonucleotide probe-coupled microspheres (diameter, 3 mum) onto the distal ends of chemically etched imaging fiber bundles. Hybridization of target rRNA from HAB cells to immobilized probes on the microspheres was visualized using Cy3-labeled secondary probes in a sandwich-type assay format. We applied these microarrays to the detection and enumeration of HAB cells in both cultured and field samples. Our study demonstrated a detection limit of approximately 5 cells for all three target organisms within 45 min, without a separate amplification step, in both sample types. We also developed a multiplexed microarray to detect the three HAB species simultaneously, which successfully detected the target organisms, alone and in combination, without cross-reactivity. Our study suggests that fiber-optic microarrays can be used for rapid and sensitive detection and potential enumeration of HAB species in the environment.

Hypoxia induces a HIF-1α dependent signaling cascade to make a complex metabolic switch in SGBS-adipocytes.

PubMed

Leiherer, Andreas; Geiger, Kathrin; Muendlein, Axel; Drexel, Heinz

2014-03-05

To elucidate the complex impact of hypoxia on adipose tissue, resulting in biased metabolism, insulin resistance and finally diabetes we used mature adipocytes derived from a Simpson-Golabi-Behmel syndrome patient for microarray analysis. We found a significantly increased transcription rate of genes involved in glycolysis and a striking association between the pattern of upregulated genes and disease biomarkers for diabetes mellitus and insulin resistance. Although their upregulation turned out to be HIF-1α-dependent, we identified further transcription factors mainly AP-1 components to play also an important role in hypoxia response. Analyzing the regulatory network of mentioned transcription factors and glycolysis targets we revealed a clear hint for directing glycolysis to glutathione and glycogen synthesis. This metabolic switch in adipocytes enables the cell to prevent oxidative damage in the short term but might induce lipogenesis and establish systemic metabolic disorders in the long run. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Transcriptome meta-analysis reveals common differential and global gene expression profiles in cystic fibrosis and other respiratory disorders and identifies CFTR regulators.

PubMed

Clarke, Luka A; Botelho, Hugo M; Sousa, Lisete; Falcao, Andre O; Amaral, Margarida D

2015-11-01

A meta-analysis of 13 independent microarray data sets was performed and gene expression profiles from cystic fibrosis (CF), similar disorders (COPD: chronic obstructive pulmonary disease, IPF: idiopathic pulmonary fibrosis, asthma), environmental conditions (smoking, epithelial injury), related cellular processes (epithelial differentiation/regeneration), and non-respiratory "control" conditions (schizophrenia, dieting), were compared. Similarity among differentially expressed (DE) gene lists was assessed using a permutation test, and a clustergram was constructed, identifying common gene markers. Global gene expression values were standardized using a novel approach, revealing that similarities between independent data sets run deeper than shared DE genes. Correlation of gene expression values identified putative gene regulators of the CF transmembrane conductance regulator (CFTR) gene, of potential therapeutic significance. Our study provides a novel perspective on CF epithelial gene expression in the context of other lung disorders and conditions, and highlights the contribution of differentiation/EMT and injury to gene signatures of respiratory disease. Copyright © 2015 Elsevier Inc. All rights reserved.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

EPA Science Inventory

The second phase of the MicroArray Quality Control (MAQC-II) project evaluated common practices for developing and validating microarray-based models aimed at predicting toxicological and clinical endpoints. Thirty-six teams developed classifiers for 13 endpoints - some easy, som...

Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray

PubMed Central

Ramirez, Lisa S.; Wang, Jun

2016-01-01

Antibody microarray as a well-developed technology is currently challenged by a few other established or emerging high-throughput technologies. In this report, we renovate the antibody microarray technology by using a novel approach for manufacturing and by introducing new features. The fabrication of our high-density antibody microarray is accomplished through perpendicularly oriented flow-patterning of single stranded DNAs and subsequent conversion mediated by DNA-antibody conjugates. This protocol outlines the critical steps in flow-patterning DNA, producing and purifying DNA-antibody conjugates, and assessing the quality of the fabricated microarray. The uniformity and sensitivity are comparable with conventional microarrays, while our microarray fabrication does not require the assistance of an array printer and can be performed in most research laboratories. The other major advantage is that the size of our microarray units is 10 times smaller than that of printed arrays, offering the unique capability of analyzing functional proteins from single cells when interfacing with generic microchip designs. This barcode technology can be widely employed in biomarker detection, cell signaling studies, tissue engineering, and a variety of clinical applications. PMID:26780370

Initial state nuclear effects for jet production measured in s=200GeV d+Au collisions by STAR

NASA Astrophysics Data System (ADS)

STAR Collaboration; Kapitán, Jan; STAR Collaboration

2009-11-01

Full jet reconstruction in heavy-ion collisions is a promising tool for quantitative study of properties of the dense medium produced at RHIC. Measurements of d+Au collisions are important to disentangle initial state nuclear effects from medium-induced k broadening and jet quenching. We report measurements of mid-rapidity (|η|<0.4|) di-jet correlations in d+Au using high-statistics run 8 RHIC data at s=200GeV.

System Study: Emergency Power System 1998–2013

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

Schroeder, John Alton

2015-02-01

This report presents an unreliability evaluation of the emergency power system (EPS) at 104 U.S. commercial nuclear power plants. Demand, run hours, and failure data from fiscal year 1998 through 2013 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10-year period, while yearly estimates for system unreliability are provided for the entire active period. No statistically significant trends were identified in the EPS results.

System Study: Auxiliary Feedwater 1998-2014

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

Schroeder, John Alton

2015-12-01

This report presents an unreliability evaluation of the auxiliary feedwater (AFW) system at 69 U.S. commercial nuclear power plants. Demand, run hours, and failure data from fiscal year 1998 through 2014 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period, while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the AFW results.

Development and application of a fluorescence protein microarray for detecting serum alpha-fetoprotein in patients with hepatocellular carcinoma.

PubMed

Zhang, Aiying; Yin, Chengzeng; Wang, Zhenshun; Zhang, Yonghong; Zhao, Yuanshun; Li, Ang; Sun, Huanqin; Lin, Dongdong; Li, Ning

2016-12-01

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC ( n = 65) and healthy control subjects ( n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC.

Development and application of a fluorescence protein microarray for detecting serum alpha-fetoprotein in patients with hepatocellular carcinoma

PubMed Central

Zhang, Aiying; Yin, Chengzeng; Wang, Zhenshun; Zhang, Yonghong; Zhao, Yuanshun; Li, Ang; Sun, Huanqin; Lin, Dongdong

2016-01-01

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC (n = 65) and healthy control subjects (n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC. PMID:27885040

Genotyping microarray: Mutation screening in Spanish families with autosomal dominant retinitis pigmentosa

PubMed Central

García-Hoyos, María; Cortón, Marta; Ávila-Fernández, Almudena; Riveiro-Álvarez, Rosa; Giménez, Ascensión; Hernan, Inma; Carballo, Miguel; Ayuso, Carmen

2012-01-01

Purpose Presently, 22 genes have been described in association with autosomal dominant retinitis pigmentosa (adRP); however, they explain only 50% of all cases, making genetic diagnosis of this disease difficult and costly. The aim of this study was to evaluate a specific genotyping microarray for its application to the molecular diagnosis of adRP in Spanish patients. Methods We analyzed 139 unrelated Spanish families with adRP. Samples were studied by using a genotyping microarray (adRP). All mutations found were further confirmed with automatic sequencing. Rhodopsin (RHO) sequencing was performed in all negative samples for the genotyping microarray. Results The adRP genotyping microarray detected the mutation associated with the disease in 20 of the 139 families with adRP. As in other populations, RHO was found to be the most frequently mutated gene in these families (7.9% of the microarray genotyped families). The rate of false positives (microarray results not confirmed with sequencing) and false negatives (mutations in RHO detected with sequencing but not with the genotyping microarray) were established, and high levels of analytical sensitivity (95%) and specificity (100%) were found. Diagnostic accuracy was 15.1%. Conclusions The adRP genotyping microarray is a quick, cost-efficient first step in the molecular diagnosis of Spanish patients with adRP. PMID:22736939

A meta-data based method for DNA microarray imputation.

PubMed

Jörnsten, Rebecka; Ouyang, Ming; Wang, Hui-Yu

2007-03-29

DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting. We download all cDNA microarray data of Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans from the Stanford Microarray Database. Through cross-validation and simulation, we find that, for all three species, our proposed imputation using data from public databases is far superior to imputation within a logical set, sometimes to an astonishing degree. Furthermore, the imputation root mean square error for significant genes is generally a lot less than that of non-significant ones. Since downstream analysis of significant genes, such as clustering and network analysis, can be very sensitive to small perturbations of estimated gene effects, it is highly recommended that researchers apply reliable data imputation prior to further analysis. Our method can also be applied to cDNA microarray experiments from other species, provided good reference data are available.

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays.

PubMed

Goodman, Corey W; Major, Heather J; Walls, William D; Sheffield, Val C; Casavant, Thomas L; Darbro, Benjamin W

2015-04-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. Copyright © 2015 Elsevier Inc. All rights reserved.

Use of Network Inference to Elucidate Common and Chemical-specific Effects on Steoidogenesis

EPA Science Inventory

Microarray data is a key source for modeling gene regulatory interactions. Regulatory network models based on multiple datasets are potentially more robust and can provide greater confidence. In this study, we used network modeling on microarray data generated by exposing the fat...

The Legnaro National Laboratories and the SPES facility: nuclear structure and reactions today and tomorrow

NASA Astrophysics Data System (ADS)

de Angelis, Giacomo; Fiorentini, Gianni

2016-11-01

There is a very long tradition of studying nuclear structure and reactions at the Legnaro National Laboratories (LNL) of the Istituto Nazionale di Fisica Nucleare (Italian Institute of Nuclear Physics). The wide expertise acquired in building and running large germanium arrays has made the laboratories one of the most advanced research centers in γ-ray spectroscopy. The ’gamma group’ has been deeply involved in all the national and international developments of the last 20 years and is currently one of the major contributors to the AGATA project, the first (together with its American counterpart GRETINA) γ-detector array based on γ-ray tracking. This line of research is expected to be strongly boosted by the coming into operation of the SPES radioactive ion beam project, currently under construction at LNL. In this report, written on the occasion of the 40th anniversary of the Nobel prize awarded to Aage Bohr, Ben R Mottelson and Leo Rainwater and particularly focused on the physics of nuclear structure, we intend to summarize the different lines of research that have guided nuclear structure and reaction research at LNL in the last decades. The results achieved have paved the way for the present SPES facility, a new laboratories infrastructure producing and accelerating radioactive ion beams of fission fragments and other isotopes.

Preferential magnetic orientation in amorphous alloys determined by NFS and Mössbauer spectroscopy

NASA Astrophysics Data System (ADS)

Procházka, Vít; Vrba, Vlastimil; Šretrová, Pavla; Smrčka, David; Miglierini, Marcel

2016-10-01

Amorphous and nanocrystalline alloys frequently exhibit anisotropic behavior, which is a consequence of magnetic moments preferential orientation. This study reports the results obtained from a set of nuclear forward scattering experiments and transmission Mössbauer spectroscopy experiments that we have run in order to determine the degree of crystallization and the preferential orientation of magnetic moments in the material. The nuclear forward scattering of synchrotron radiation and the transmission Mössbauer spectroscopy were performed on the nanocrystalline alloy of the composition Fe79Mo8Cu1B12. The experimental data were evaluated and magnetic texture was determined. Relevance of the results was confronted with transmission Mössbauer experiments.

Developing and applying modern methods of leakage monitoring and state estimation of fuel at the Novovoronezh nuclear power plant

NASA Astrophysics Data System (ADS)

Povarov, V. P.; Tereshchenko, A. B.; Kravchenko, Yu. N.; Pozychanyuk, I. V.; Gorobtsov, L. I.; Golubev, E. I.; Bykov, V. I.; Likhanskii, V. V.; Evdokimov, I. A.; Zborovskii, V. G.; Sorokin, A. A.; Kanyukova, V. D.; Aliev, T. N.

2014-02-01

The results of developing and implementing the modernized fuel leakage monitoring methods at the shut-down and running reactor of the Novovoronezh nuclear power plant (NPP) are presented. An automated computerized expert system integrated with an in-core monitoring system (ICMS) and installed at the Novovoronezh NPP unit no. 5 is described. If leaky fuel elements appear in the core, the system allows one to perform on-line assessment of the parameters of leaky fuel assemblies (FAs). The computer expert system units designed for optimizing the operating regimes and enhancing the fuel usage efficiency at the Novovoronezh NPP unit no. 5 are now being developed.

Equalizer reduces SNP bias in Affymetrix microarrays.

PubMed

Quigley, David

2015-07-30

Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans. By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings. The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.

Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

PubMed

Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

2017-08-07

High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

A DNA microarray-based methylation-sensitive (MS)-AFLP hybridization method for genetic and epigenetic analyses.

PubMed

Yamamoto, F; Yamamoto, M

2004-07-01

We previously developed a PCR-based DNA fingerprinting technique named the Methylation Sensitive (MS)-AFLP method, which permits comparative genome-wide scanning of methylation status with a manageable number of fingerprinting experiments. The technique uses the methylation sensitive restriction enzyme NotI in the context of the existing Amplified Fragment Length Polymorphism (AFLP) method. Here we report the successful conversion of this gel electrophoresis-based DNA fingerprinting technique into a DNA microarray hybridization technique (DNA Microarray MS-AFLP). By performing a total of 30 (15 x 2 reciprocal labeling) DNA Microarray MS-AFLP hybridization experiments on genomic DNA from two breast and three prostate cancer cell lines in all pairwise combinations, and Southern hybridization experiments using more than 100 different probes, we have demonstrated that the DNA Microarray MS-AFLP is a reliable method for genetic and epigenetic analyses. No statistically significant differences were observed in the number of differences between the breast-prostate hybridization experiments and the breast-breast or prostate-prostate comparisons.

HDBStat!: a platform-independent software suite for statistical analysis of high dimensional biology data.

PubMed

Trivedi, Prinal; Edwards, Jode W; Wang, Jelai; Gadbury, Gary L; Srinivasasainagendra, Vinodh; Zakharkin, Stanislav O; Kim, Kyoungmi; Mehta, Tapan; Brand, Jacob P L; Patki, Amit; Page, Grier P; Allison, David B

2005-04-06

Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg_content.asp?id=1164.

Applications of nanotechnology, next generation sequencing and microarrays in biomedical research.

PubMed

Elingaramil, Sauli; Li, Xiaolong; He, Nongyue

2013-07-01

Next-generation sequencing technologies, microarrays and advances in bio nanotechnology have had an enormous impact on research within a short time frame. This impact appears certain to increase further as many biomedical institutions are now acquiring these prevailing new technologies. Beyond conventional sampling of genome content, wide-ranging applications are rapidly evolving for next-generation sequencing, microarrays and nanotechnology. To date, these technologies have been applied in a variety of contexts, including whole-genome sequencing, targeted re sequencing and discovery of transcription factor binding sites, noncoding RNA expression profiling and molecular diagnostics. This paper thus discusses current applications of nanotechnology, next-generation sequencing technologies and microarrays in biomedical research and highlights the transforming potential these technologies offer.

Polyadenylation state microarray (PASTA) analysis.

PubMed

Beilharz, Traude H; Preiss, Thomas

2011-01-01

Nearly all eukaryotic mRNAs terminate in a poly(A) tail that serves important roles in mRNA utilization. In the cytoplasm, the poly(A) tail promotes both mRNA stability and translation, and these functions are frequently regulated through changes in tail length. To identify the scope of poly(A) tail length control in a transcriptome, we developed the polyadenylation state microarray (PASTA) method. It involves the purification of mRNA based on poly(A) tail length using thermal elution from poly(U) sepharose, followed by microarray analysis of the resulting fractions. In this chapter we detail our PASTA approach and describe some methods for bulk and mRNA-specific poly(A) tail length measurements of use to monitor the procedure and independently verify the microarray data.

Computed inundation heights of the 2011 Tohoku tsunami compared to measured run-up data: hints for tsunami source inversion

NASA Astrophysics Data System (ADS)

Pagnoni, G.; Tinti, S.; Armigliato, A.

2012-04-01

The 11 March 2011 earthquake that took place off the Pacific coast of Tohoku, North Honshu, with Mw = 9.0, is the largest earthquake ever occurred in Japan, and generated a big tsunami that spread across the Pacific Ocean, causing devastating effects in the prefectures of Aomori, Iwate, Miyagi and Fukushima. It caused more than 15,000 casualties, swept away the low-land quarters of several villages and moreover was the primary cause of the severe nuclear accident in the Fukushima Nuclear Power Plant. There is a very large set of observations covering both the earthquake and the tsunami, and almost certainly this is the case with the most abundant dataset of high-quality data in the history of seismology and of tsunami science. Local and global seismic networks, continuous GPS networks, coastal tide gauges in Japan ports and across the Pacific, local buoys cabled deep ocean-bottom pressure gauges (OBPG) and deep-ocean buoys (such as DART) mainly along the foot of the margins of the pacific continents, all contributed essential data to constrain the source of the earthquake and of the tsunami. In this paper we will use also the observed run-up data to put further constraints on the source and to better determine the distribution of the slip on the offshore fault. This will be done through trial-and-error forward modeling, that is by comparing inundation data calculated by means of numerical tsunami simulations in the near field to tsunami run-up heights measured during field surveys conducted by several teams and made available on the net. Major attention will be devoted to reproduce observations in the prefectures that were more affected and where run-up heights are very large (namely Iwate and Miyagi). The simulations are performed by means of the finite-difference code UBO-TSUFD, developed and maintained by the Tsunami Research Team of the University of Bologna, Italy, that can solve both the linear and non-linear versions of the shallow-water equations on nested grids and with dynamically moving shorelines.

Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experiments

PubMed Central

Brodsky, Leonid; Leontovich, Andrei; Shtutman, Michael; Feinstein, Elena

2004-01-01

Mathematical methods of analysis of microarray hybridizations deal with gene expression profiles as elementary units. However, some of these profiles do not reflect a biologically relevant transcriptional response, but rather stem from technical artifacts. Here, we describe two technically independent but rationally interconnected methods for identification of such artifactual profiles. Our diagnostics are based on detection of deviations from uniformity, which is assumed as the main underlying principle of microarray design. Method 1 is based on detection of non-uniformity of microarray distribution of printed genes that are clustered based on the similarity of their expression profiles. Method 2 is based on evaluation of the presence of gene-specific microarray spots within the slides’ areas characterized by an abnormal concentration of low/high differential expression values, which we define as ‘patterns of differentials’. Applying two novel algorithms, for nested clustering (method 1) and for pattern detection (method 2), we can make a dual estimation of the profile’s quality for almost every printed gene. Genes with artifactual profiles detected by method 1 may then be removed from further analysis. Suspicious differential expression values detected by method 2 may be either removed or weighted according to the probabilities of patterns that cover them, thus diminishing their input in any further data analysis. PMID:14999086

Body Mass Index Influences the Prognostic Impact of Combined Nuclear Insulin Receptor and Estrogen Receptor Expression in Primary Breast Cancer.

PubMed

Björner, Sofie; Rosendahl, Ann H; Simonsson, Maria; Markkula, Andrea; Jirström, Karin; Borgquist, Signe; Rose, Carsten; Ingvar, Christian; Jernström, Helena

2017-01-01

The prognostic importance of tumor-specific nuclear insulin receptor (InsR) expression in breast cancer is unclear, while membrane and cytoplasmic localization of InsR is better characterized. The insulin signaling network is influenced by obesity and may interact with the estrogen receptor α (ERα) signaling. The purpose was to investigate the interplay between nuclear InsR, ER, body mass index (BMI), and prognosis. Tumor-specific expression of nuclear InsR was evaluated by immunohistochemistry in tissue microarrays from 900 patients with primary invasive breast cancer without preoperative treatment, included in a population-based cohort in Sweden (2002-2012) in relation to prognosis. Patients were followed for up to 11 years during which 107 recurrences were observed. Nuclear InsR + expression was present in 214 patients (23.8%) and increased with longer time between surgery and staining ( P  < 0.001). There were significant effect modifications by ER status and BMI in relation to clinical outcomes. Nuclear InsR + conferred higher recurrence-risk in patients with ER + tumors, but lower risk in patients with ER - tumors ( P interaction  = 0.003). Normal-weight patients with nuclear InsR + tumors had higher recurrence-risk, while overweight or obese patients had half the recurrence-risk compared to patients with nuclear InsR - tumors ( P interaction  = 0.007). Normal-weight patients with a nuclear InsR - /ER + tumor had the lowest risk for recurrence compared to all other nuclear InsR/ER combinations [HR adj 0.50, 95% confidence interval (CI): 0.25-0.97], while overweight or obese patients with nuclear InsR - /ER - tumors had the worst prognosis (HR adj 7.75, 95% CI: 2.04-29.48). Nuclear InsR was more prognostic than ER among chemotherapy-treated patients. In summary, nuclear InsR may have prognostic impact among normal-weight patients with ER + tumors and in overweight or obese patients with ER - tumors. Normal-weight patients with nuclear InsR - /ER + tumors may benefit from less treatment than normal-weight patients with other nuclear InsR/ER combinations. Overweight or obese patients with nuclear InsR - /ER - tumors may benefit from more tailored treatment or weight management.

The effect of forced exercise on knee joints in Dio2(-/-) mice: type II iodothyronine deiodinase-deficient mice are less prone to develop OA-like cartilage damage upon excessive mechanical stress.

PubMed

Bomer, Nils; Cornelis, Frederique M F; Ramos, Yolande F M; den Hollander, Wouter; Storms, Lies; van der Breggen, Ruud; Lakenberg, Nico; Slagboom, P Eline; Meulenbelt, Ingrid; Lories, Rik J L

2016-03-01

To further explore deiodinase iodothyronine type 2 (DIO2) as a therapeutic target in osteoarthritis (OA) by studying the effects of forced mechanical loading on in vivo joint cartilage tissue homeostasis and the modulating effect herein of Dio2 deficiency. Wild-type and C57BL/6-Dio2(-/-) -mice were subjected to a forced running regime for 1 h per day for 3 weeks. Severity of OA was assessed by histological scoring for cartilage damage and synovitis. Genome-wide gene expression was determined in knee cartilage by microarray analysis (Illumina MouseWG-6 v2). STRING-db analyses were applied to determine enrichment for specific pathways and to visualise protein-protein interactions. In total, 158 probes representing 147 unique genes showed significantly differential expression with a fold-change ≥1.5 upon forced exercise. Among these are genes known for their association with OA (eg, Mef2c, Egfr, Ctgf, Prg4 and Ctnnb1), supporting the use of forced running as an OA model in mice. Dio2-deficient mice showed significantly less cartilage damage and signs of synovitis. Gene expression response upon exercise between wild-type and knockout mice was significantly different for 29 genes. Mice subjected to a running regime have significant increased cartilage damage and synovitis scores. Lack of Dio2 protected against cartilage damage in this model and was reflected in a specific gene expression profile, and either mark a favourable effect in the Dio2 knockout (eg, Gnas) or an unfavourable effect in wild-type cartilage homeostasis (eg, Hmbg2 and Calr). These data further support DIO2 activity as a therapeutic target in OA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

NHR-23 dependent collagen and hedgehog-related genes required for molting.

PubMed

Kouns, Nathaniel A; Nakielna, Johana; Behensky, Frantisek; Krause, Michael W; Kostrouch, Zdenek; Kostrouchova, Marta

2011-10-07

NHR-23, a conserved member of the nuclear receptor family of transcription factors, is required for normal development in Caenorhabditis elegans where it plays a critical role in growth and molting. In a search for NHR-23 dependent genes, we performed whole genome comparative expression microarrays on both control and nhr-23 inhibited synchronized larvae. Genes that decreased in response to nhr-23 RNAi included several collagen genes. Unexpectedly, several hedgehog-related genes were also down-regulated after nhr-23 RNAi. A homozygous nhr-23 deletion allele was used to confirm the RNAi knockdown phenotypes and the changes in gene expression. Our results indicate that NHR-23 is a critical co-regulator of functionally linked genes involved in growth and molting and reveal evolutionary parallels among the ecdysozoa. Copyright © 2011 Elsevier Inc. All rights reserved.

Level-2 Milestone 3244: Deploy Dawn ID Machine for Initial Science Runs

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

Fox, D

2009-09-21

This report documents the delivery, installation, integration, testing, and acceptance of the Dawn system, ASC L2 milestone 3244: Deploy Dawn ID Machine for Initial Science Runs, due September 30, 2009. The full text of the milestone is included in Attachment 1. The description of the milestone is: This milestone will be a result of work started three years ago with the planning for a multi-petaFLOPS UQ-focused platform (Sequoia) and will be satisfied when a smaller ID version of the final system is delivered, installed, integrated, tested, accepted, and deployed at LLNL for initial science runs in support of SSP mission.more » The deliverable for this milestone will be a LA petascale computing system (named Dawn) usable for code development and scaling necessary to ensure effective use of a final Sequoia platform (expected in 2011-2012), and for urgent SSP program needs. Allocation and scheduling of Dawn as an LA system will likely be performed informally, similar to what has been used for BlueGene/L. However, provision will be made to allow for dedicated access times for application scaling studies across the entire Dawn resource. The milestone was completed on April 1, 2009, when science runs began running on the Dawn system. The following sections describe the Dawn system architecture, current status, installation and integration time line, and testing and acceptance process. A project plan is included as Attachment 2. Attachment 3 is a letter certifying the handoff of the system to a nuclear weapons stockpile customer. Attachment 4 presents the results of science runs completed on the system.« less

Convolutional neural networks for prostate cancer recurrence prediction

NASA Astrophysics Data System (ADS)

Kumar, Neeraj; Verma, Ruchika; Arora, Ashish; Kumar, Abhay; Gupta, Sanchit; Sethi, Amit; Gann, Peter H.

2017-03-01

Accurate prediction of the treatment outcome is important for cancer treatment planning. We present an approach to predict prostate cancer (PCa) recurrence after radical prostatectomy using tissue images. We used a cohort whose case vs. control (recurrent vs. non-recurrent) status had been determined using post-treatment follow up. Further, to aid the development of novel biomarkers of PCa recurrence, cases and controls were paired based on matching of other predictive clinical variables such as Gleason grade, stage, age, and race. For this cohort, tissue resection microarray with up to four cores per patient was available. The proposed approach is based on deep learning, and its novelty lies in the use of two separate convolutional neural networks (CNNs) - one to detect individual nuclei even in the crowded areas, and the other to classify them. To detect nuclear centers in an image, the first CNN predicts distance transform of the underlying (but unknown) multi-nuclear map from the input HE image. The second CNN classifies the patches centered at nuclear centers into those belonging to cases or controls. Voting across patches extracted from image(s) of a patient yields the probability of recurrence for the patient. The proposed approach gave 0.81 AUC for a sample of 30 recurrent cases and 30 non-recurrent controls, after being trained on an independent set of 80 case-controls pairs. If validated further, such an approach might help in choosing between a combination of treatment options such as active surveillance, radical prostatectomy, radiation, and hormone therapy. It can also generalize to the prediction of treatment outcomes in other cancers.

NHE10, a novel osteoclast-specific member of the Na{sup +}/H{sup +} exchanger family, regulates osteoclast differentiation and survival

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

Lee, Seoung Hoon; Kim, Taesoo; Park, Eui-Soon

2008-05-02

Bone homeostasis is tightly regulated by the balanced actions of osteoblasts (OBs) and osteoclasts (OCs). We previously analyzed the gene expression profile of OC differentiation using a cDNA microarray, and identified a novel osteoclastogenic gene candidate, clone OCL-1-E7 [J. Rho, C.R. Altmann, N.D. Socci, L. Merkov, N. Kim, H. So, O. Lee, M. Takami, A.H. Brivanlou, Y. Choi, Gene expression profiling of osteoclast differentiation by combined suppression subtractive hybridization (SSH) and cDNA microarray analysis, DNA Cell Biol. 21 (2002) 541-549]. In this study, we have isolated full-length cDNAs corresponding to this clone from mice and humans to determine the functionalmore » roles of this gene in osteoclastogenesis. The full-length cDNA of OCL-1-E7 encodes 12 membrane-spanning domains that are typical of isoforms of the Na{sup +}/H{sup +} exchangers (NHEs), indicating that this clone is a novel member of the NHE family (hereafter referred to as NHE10). Here, we show that NHE10 is highly expressed in OCs in response to receptor activator of nuclear factor-{kappa}B ligand signaling and is required for OC differentiation and survival.« less

Identification of differentially expressed genes affecting hair and cashmere growth in the Laiwu black goat by microarray.

PubMed

Zhao, Jinshan; Li, Hegang; Liu, Kaidong; Zhang, Baoxun; Li, Peipei; He, Jianning; Cheng, Ming; De, Wei; Liu, Jifeng; Zhao, Yaofeng; Yang, Lihua; Liu, Nan

2016-10-01

Goats are an important source of fibers. In the present study microarray technology was used to investigate the potential genes primarily involved in hair and cashmere growth in the Laiwu black goat. A total of 655 genes differentially expressed in body (hair‑growing) and groin (hairless) skin were identified, and their potential association with hair and cashmere growth was analyzed. The majority of genes associated with hair growth regulation could be assigned to intracellular, intracellular organelle, membrane‑bound vesicle, cytoplasmic vesicle, pattern binding, heparin binding, polysaccharide binding, glycosaminoglycan binding and cytoplasmic membrane‑bound vesicle categories. Numerous genes upregulated in body compared with groin skin contained common motifs for nuclear factor 1A, Yi, E2 factor (E2F) and cyclic adenosine monophosphate response element binding (CREB)/CREBβ binding sites in their promoter region. The promoter region of certain genes downregulated in body compared with groin skin contained three common regions with LF‑A1, Yi, E2F, Collier/Olfactory‑1/early B‑cell factor 1, peroxisome proliferator‑activated receptor α or U sites. Thus, the present study identified molecules in the cashmere‑bearing skin area of the Laiwu black goat, which may contribute to hair and cashmere traits.

Increased expression of protein kinase A inhibitor alpha (PKI-alpha) and decreased PKA-regulated genes in chronic intermittent alcohol exposure.

PubMed

Repunte-Canonigo, Vez; Lutjens, Robert; van der Stap, Lena D; Sanna, Pietro Paolo

2007-03-23

Intermittent models of alcohol exposure that mimic human patterns of alcohol consumption produce profound physiological and biochemical changes and induce rapid increases in alcohol self-administration. We used high-density oligonucleotide microarrays to investigate gene expression changes during chronic intermittent alcohol exposure in three brain regions that receive mesocorticolimbic dopaminergic projections and that are believed to be involved in alcohol's reinforcing actions: the medial prefrontal cortex, the nucleus accumbens and the amygdala. An independent replication of the experiment was used for RT-PCR validation of the microarray results. The protein kinase A inhibitor alpha (PKI-alpha, Pkia), a member of the endogenous PKI family implicated in reducing nuclear PKA activity, was found to be increased in all three regions tested. Conversely, we observed a downregulation of the expression of several PKA-regulated transcripts in one or more of the brain regions studied, including the activity and neurotransmitter-regulated early gene (Ania) - 1, -3, -7, -8, the transcription factors Egr1 and NGFI-B (Nr4a1) and the neuropeptide NPY. Reduced expression of PKA-regulated genes in mesocorticolimbic projection areas may have motivational significance in the rapid increase in alcohol self-administration induced by intermittent alcohol exposure.

Analysis of developmental gene conservation in the Actinomycetales using DNA/DNA microarray comparisons.

PubMed

Kirby, Ralph; Herron, Paul; Hoskisson, Paul

2011-02-01

Based on available genome sequences, Actinomycetales show significant gene synteny across a wide range of species and genera. In addition, many genera show varying degrees of complex morphological development. Using the presence of gene synteny as a basis, it is clear that an analysis of gene conservation across the Streptomyces and various other Actinomycetales will provide information on both the importance of genes and gene clusters and the evolution of morphogenesis in these bacteria. Genome sequencing, although becoming cheaper, is still relatively expensive for comparing large numbers of strains. Thus, a heterologous DNA/DNA microarray hybridization dataset based on a Streptomyces coelicolor microarray allows a cheaper and greater depth of analysis of gene conservation. This study, using both bioinformatical and microarray approaches, was able to classify genes previously identified as involved in morphogenesis in Streptomyces into various subgroups in terms of conservation across species and genera. This will allow the targeting of genes for further study based on their importance at the species level and at higher evolutionary levels.

Teaching And Training Tools For The Undergraduate: Experience With A Rebuilt AN-400 Accelerator

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

Roberts, Andrew D.

2011-06-01

There is an increasingly recognized need for people trained in a broad range of applied nuclear science techniques, indicated by reports from the American Physical Society and elsewhere. Anecdotal evidence suggests that opportunities for hands-on training with small particle accelerators have diminished in the US, as development programs established in the 1960's and 1970's have been decommissioned over recent decades. Despite the reduced interest in the use of low energy accelerators in fundamental research, these machines can offer a powerful platform for bringing unique training opportunities to the undergraduate curriculum in nuclear physics, engineering and technology. We report here onmore » the new MSU Applied Nuclear Science Lab, centered around the rebuild of an AN400 electrostatic accelerator. This machine is run entirely by undergraduate students under faculty supervision, allowing a great deal of freedom in its use without restrictions from graduate or external project demands.« less

Straight SU-8 pins

NASA Astrophysics Data System (ADS)

Safavieh, R.; Pla Roca, M.; Qasaimeh, M. A.; Mirzaei, M.; Juncker, D.

2010-05-01

SU-8 can be patterned with high resolution, is flexible and tough. These characteristics qualify SU-8 as a material for making spotting pins for printing DNA and protein microarrays, and it can potentially replace the commonly used silicon and steel pins that are expensive, brittle in the case of silicon and can damage the substrate during the printing process. SU-8, however, accumulates large internal stress during fabrication and, as a consequence, thin and long SU-8 structures bend and coil up, which precludes using it for long, freestanding structures such as pins. Here we introduce (i) a novel fabrication process that allows the making of 30 mm long, straight spotting pins that feature (ii) a new design and surface chemistry treatments for better capillary flow control and more homogeneous spotting. A key innovation for the fabrication is a post-processing annealing step with slow temperature ramping and mechanical clamping between two identical substrates to minimize stress buildup and render it symmetric, respectively, which together yield a straight SU-8 structure. SU-8 pins fabricated using this process are compliant and resilient and can buckle without damage during printing. The pins comprise a novel flow stop valve for accurate metering of fluids, and their surface was chemically patterned to render the outside of the pin hydrophobic while the inside of the slit is hydrophilic, and the slit thus spontaneously fills when dipped into a solution while preventing droplet attachment on the outside. A single SU-8 pin was used to print 1392 protein spots in one run. SU-8 pins are inexpensive, straightforward to fabricate, robust and may be used as disposable pins for microarray fabrication. These pins serve as an illustration of the potential application of ultralow stress SU-8 for making freestanding microfabricated polymer microstructures.

UPD detection using homozygosity profiling with a SNP genotyping microarray.

PubMed

Papenhausen, Peter; Schwartz, Stuart; Risheg, Hiba; Keitges, Elisabeth; Gadi, Inder; Burnside, Rachel D; Jaswaney, Vikram; Pappas, John; Pasion, Romela; Friedman, Kenneth; Tepperberg, James

2011-04-01

Single nucleotide polymorphism (SNP) based chromosome microarrays provide both a high-density whole genome analysis of copy number and genotype. In the past 21 months we have analyzed over 13,000 samples primarily referred for developmental delay using the Affymetrix SNP/CN 6.0 version array platform. In addition to copy number, we have focused on the relative distribution of allele homozygosity (HZ) throughout the genome to confirm a strong association of uniparental disomy (UPD) with regions of isoallelism found in most confirmed cases of UPD. We sought to determine whether a long contiguous stretch of HZ (LCSH) greater than a threshold value found only in a single chromosome would correlate with UPD of that chromosome. Nine confirmed UPD cases were retrospectively analyzed with the array in the study, each showing the anticipated LCSH with the smallest 13.5 Mb in length. This length is well above the average longest run of HZ in a set of control patients and was then set as the prospective threshold for reporting possible UPD correlation. Ninety-two cases qualified at that threshold, 46 of those had molecular UPD testing and 29 were positive. Including retrospective cases, 16 showed complete HZ across the chromosome, consistent with total isoUPD. The average size LCSH in the 19 cases that were not completely HZ was 46.3 Mb with a range of 13.5-127.8 Mb. Three patients showed only segmental UPD. Both the size and location of the LCSH are relevant to correlation with UPD. Further studies will continue to delineate an optimal threshold for LCSH/UPD correlation. Copyright © 2011 Wiley-Liss, Inc.

Identification of Androgen Receptor-Specific Enhancer RNAs

DTIC Science & Technology

2016-06-01

Release; Distribution Unlimited The views, opinions and/or findings contained in this report are those of the author(s) and should not be construed as...There are two Tasks in this application. First, we will perform global run-on assay and deep sequencing to identify AR -specific enhancer RNAs. Second...1 Introduction The androgen receptor ( AR ) is a nuclear receptor transcription factor required for normal prostate development and prostate

Rapid and simultaneous detection of ricin, staphylococcal enterotoxin B and saxitoxin by chemiluminescence-based microarray immunoassay.

PubMed

Szkola, A; Linares, E M; Worbs, S; Dorner, B G; Dietrich, R; Märtlbauer, E; Niessner, R; Seidel, M

2014-11-21

Simultaneous detection of small and large molecules on microarray immunoassays is a challenge that limits some applications in multiplex analysis. This is the case for biosecurity, where fast, cheap and reliable simultaneous detection of proteotoxins and small toxins is needed. Two highly relevant proteotoxins, ricin (60 kDa) and bacterial toxin staphylococcal enterotoxin B (SEB, 30 kDa) and the small phycotoxin saxitoxin (STX, 0.3 kDa) are potential biological warfare agents and require an analytical tool for simultaneous detection. Proteotoxins are successfully detected by sandwich immunoassays, whereas competitive immunoassays are more suitable for small toxins (<1 kDa). Based on this need, this work provides a novel and efficient solution based on anti-idiotypic antibodies for small molecules to combine both assay principles on one microarray. The biotoxin measurements are performed on a flow-through chemiluminescence microarray platform MCR3 in 18 minutes. The chemiluminescence signal was amplified by using a poly-horseradish peroxidase complex (polyHRP), resulting in low detection limits: 2.9 ± 3.1 μg L(-1) for ricin, 0.1 ± 0.1 μg L(-1) for SEB and 2.3 ± 1.7 μg L(-1) for STX. The developed multiplex system for the three biotoxins is completely novel, relevant in the context of biosecurity and establishes the basis for research on anti-idiotypic antibodies for microarray immunoassays.

Mining microarrays for metabolic meaning: nutritional regulation of hypothalamic gene expression.

PubMed

Mobbs, Charles V; Yen, Kelvin; Mastaitis, Jason; Nguyen, Ha; Watson, Elizabeth; Wurmbach, Elisa; Sealfon, Stuart C; Brooks, Andrew; Salton, Stephen R J

2004-06-01

DNA microarray analysis has been used to investigate relative changes in the level of gene expression in the CNS, including changes that are associated with disease, injury, psychiatric disorders, drug exposure or withdrawal, and memory formation. We have used oligonucleotide microarrays to identify hypothalamic genes that respond to nutritional manipulation. In addition to commonly used microarray analysis based on criteria such as fold-regulation, we have also found that simply carrying out multiple t tests then sorting by P value constitutes a highly reliable method to detect true regulation, as assessed by real-time polymerase chain reaction (PCR), even for relatively low abundance genes or relatively low magnitude of regulation. Such analyses directly suggested novel mechanisms that mediate effects of nutritional state on neuroendocrine function and are being used to identify regulated gene products that may elucidate the metabolic pathology of obese ob/ob, lean Vgf-/Vgf-, and other models with profound metabolic impairments.

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

Hsia, Chu Chieh; Chizhikov, Vladimir E.; Yang, Amy X.

Hepatitis B virus (HBV), hepatitis C virus (HCV), and human immunodeficiency virus type-1 (HIV-1) are transfusion-transmitted human pathogens that have a major impact on blood safety and public health worldwide. We developed a microarray multiplex assay for the simultaneous detection and discrimination of these three viruses. The microarray consists of 16 oligonucleotide probes, immobilized on a silylated glass slide. Amplicons from multiplex PCR were labeled with Cy-5 and hybridized to the microarray. The assay detected 1 International Unit (IU), 10 IU, 20 IU of HBV, HCV, and HIV-1, respectively, in a single multiplex reaction. The assay also detected and discriminatedmore » the presence of two or three of these viruses in a single sample. Our data represent a proof-of-concept for the possible use of highly sensitive multiplex microarray assay to screen and confirm the presence of these viruses in blood donors and patients.« less

Altered Gene Expression Patterns During the Initiation and Promotion Stages of Neonatally Diethylstilbestrol-Induced Hyperplasia/Dysplasia/Neoplasia in the Hamster Uterus

PubMed Central

Hendry, William J.; Hariri, Hussam Y.; Alwis, Imala D.; Gunewardena, Sumedha S.; Hendry, Isabel R.

2014-01-01

Neonatal treatment of hamsters with diethylstilbestrol (DES) induces uterine hyperplasia/dysplasia/neoplasia (endometrial adenocarcinoma) in adult animals. We subsequently determined that the neonatal DES exposure event directly and permanently disrupts the developing hamster uterus (initiation stage) so that it responds abnormally when it is stimulated with estrogen in adulthood (promotion stage). To identify candidate molecular elements involved in progression of the disruption/neoplastic process, we performed: 1) immunoblot analyses and 2) microarray profiling (Affymetrix Gene Chip System) on sets of uterine protein and RNA extracts, respectively, and 3) immunohistochemical analysis on uterine sections; all from both initiation stage and promotion stage groups of animals. Here we report that: 1) progression of the neonatal DES-induced hyperplasia/dysplasia/neoplasia phenomenon in the hamster uterus involves a wide spectrum of specific gene expression alterations and 2) the gene products involved and their manner of altered expression differ dramatically during the initiation vs. promotion stages of the phenomenon. Particularly interesting changes included members in the functional categories of nuclear receptors (progesterone receptor), cell-cell interactions (E-cadherin, connexins), cytokine action (IRF-1, Stat5A), growth factor action (IRS-1), extracellular matrix component (tenascin-C), transcription factors (Nrf2, Sp1), and multi-functional nuclear protein (SAFB1). PMID:25242112

See what you eat--broad GMO screening with microarrays.

PubMed

von Götz, Franz

2010-03-01

Despite the controversy of whether genetically modified organisms (GMOs) are beneficial or harmful for humans, animals, and/or ecosystems, the number of cultivated GMOs is increasing every year. Many countries and federations have implemented safety and surveillance systems for GMOs. Potent testing technologies need to be developed and implemented to monitor the increasing number of GMOs. First, these GMO tests need to be comprehensive, i.e., should detect all, or at least the most important, GMOs on the market. This type of GMO screening requires a high degree of parallel tests or multiplexing. To date, DNA microarrays have the highest number of multiplexing capabilities when nucleic acids are analyzed. This trend article focuses on the evolution of DNA microarrays for GMO testing. Over the last 7 years, combinations of multiplex PCR detection and microarray detection have been developed to qualitatively assess the presence of GMOs. One example is the commercially available DualChip GMO (Eppendorf, Germany; http://www.eppendorf-biochip.com), which is the only GMO screening system successfully validated in a multicenter study. With use of innovative amplification techniques, promising steps have recently been taken to make GMO detection with microarrays quantitative.

Genome Consortium for Active Teaching: Meeting the Goals of BIO2010

PubMed Central

Ledbetter, Mary Lee S.; Hoopes, Laura L.M.; Eckdahl, Todd T.; Heyer, Laurie J.; Rosenwald, Anne; Fowlks, Edison; Tonidandel, Scott; Bucholtz, Brooke; Gottfried, Gail

2007-01-01

The Genome Consortium for Active Teaching (GCAT) facilitates the use of modern genomics methods in undergraduate education. Initially focused on microarray technology, but with an eye toward diversification, GCAT is a community working to improve the education of tomorrow's life science professionals. GCAT participants have access to affordable microarrays, microarray scanners, free software for data analysis, and faculty workshops. Microarrays provided by GCAT have been used by 141 faculty on 134 campuses, including 21 faculty that serve large numbers of underrepresented minority students. An estimated 9480 undergraduates a year will have access to microarrays by 2009 as a direct result of GCAT faculty workshops. Gains for students include significantly improved comprehension of topics in functional genomics and increased interest in research. Faculty reported improved access to new technology and gains in understanding thanks to their involvement with GCAT. GCAT's network of supportive colleagues encourages faculty to explore genomics through student research and to learn a new and complex method with their undergraduates. GCAT is meeting important goals of BIO2010 by making research methods accessible to undergraduates, training faculty in genomics and bioinformatics, integrating mathematics into the biology curriculum, and increasing participation by underrepresented minority students. PMID:17548873

Genome Consortium for Active Teaching: meeting the goals of BIO2010.

PubMed

Campbell, A Malcolm; Ledbetter, Mary Lee S; Hoopes, Laura L M; Eckdahl, Todd T; Heyer, Laurie J; Rosenwald, Anne; Fowlks, Edison; Tonidandel, Scott; Bucholtz, Brooke; Gottfried, Gail

2007-01-01

The Genome Consortium for Active Teaching (GCAT) facilitates the use of modern genomics methods in undergraduate education. Initially focused on microarray technology, but with an eye toward diversification, GCAT is a community working to improve the education of tomorrow's life science professionals. GCAT participants have access to affordable microarrays, microarray scanners, free software for data analysis, and faculty workshops. Microarrays provided by GCAT have been used by 141 faculty on 134 campuses, including 21 faculty that serve large numbers of underrepresented minority students. An estimated 9480 undergraduates a year will have access to microarrays by 2009 as a direct result of GCAT faculty workshops. Gains for students include significantly improved comprehension of topics in functional genomics and increased interest in research. Faculty reported improved access to new technology and gains in understanding thanks to their involvement with GCAT. GCAT's network of supportive colleagues encourages faculty to explore genomics through student research and to learn a new and complex method with their undergraduates. GCAT is meeting important goals of BIO2010 by making research methods accessible to undergraduates, training faculty in genomics and bioinformatics, integrating mathematics into the biology curriculum, and increasing participation by underrepresented minority students.

GPFrontend and GPGraphics: graphical analysis tools for genetic association studies.

PubMed

Uebe, Steffen; Pasutto, Francesca; Krumbiegel, Mandy; Schanze, Denny; Ekici, Arif B; Reis, André

2010-09-21

Most software packages for whole genome association studies are non-graphical, purely text based programs originally designed to run with UNIX-like operating systems. Graphical output is often not intended or supposed to be performed with other command line tools, e.g. gnuplot. Using the Microsoft .NET 2.0 platform and Visual Studio 2005, we have created a graphical software package to analyze data from microarray whole genome association studies, both for a DNA-pooling based approach as well as regular single sample data. Part of this package was made to integrate with GenePool 0.8.2, a previously existing software suite for GNU/Linux systems, which we have modified to run in a Microsoft Windows environment. Further modifications cause it to generate some additional data. This enables GenePool to interact with the .NET parts created by us. The programs we developed are GPFrontend, a graphical user interface and frontend to use GenePool and create metadata files for it, and GPGraphics, a program to further analyze and graphically evaluate output of different WGA analysis programs, among them also GenePool. Our programs enable regular MS Windows users without much experience in bioinformatics to easily visualize whole genome data from a variety of sources.

A Web-Based Multi-Database System Supporting Distributed Collaborative Management and Sharing of Microarray Experiment Information

PubMed Central

Burgarella, Sarah; Cattaneo, Dario; Masseroli, Marco

2006-01-01

We developed MicroGen, a multi-database Web based system for managing all the information characterizing spotted microarray experiments. It supports information gathering and storing according to the Minimum Information About Microarray Experiments (MIAME) standard. It also allows easy sharing of information and data among all multidisciplinary actors involved in spotted microarray experiments. PMID:17238488

Carbohydrate Microarray Technology Applied to High-Throughput Mapping of Plant Cell Wall Glycans Using Comprehensive Microarray Polymer Profiling (CoMPP).

PubMed

Kračun, Stjepan Krešimir; Fangel, Jonatan Ulrik; Rydahl, Maja Gro; Pedersen, Henriette Lodberg; Vidal-Melgosa, Silvia; Willats, William George Tycho

2017-01-01

Cell walls are an important feature of plant cells and a major component of the plant glycome. They have both structural and physiological functions and are critical for plant growth and development. The diversity and complexity of these structures demand advanced high-throughput techniques to answer questions about their structure, functions and roles in both fundamental and applied scientific fields. Microarray technology provides both the high-throughput and the feasibility aspects required to meet that demand. In this chapter, some of the most recent microarray-based techniques relating to plant cell walls are described together with an overview of related contemporary techniques applied to carbohydrate microarrays and their general potential in glycoscience. A detailed experimental procedure for high-throughput mapping of plant cell wall glycans using the comprehensive microarray polymer profiling (CoMPP) technique is included in the chapter and provides a good example of both the robust and high-throughput nature of microarrays as well as their applicability to plant glycomics.

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

PubMed

Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

2011-01-01

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

AccuTyping: new algorithms for automated analysis of data from high-throughput genotyping with oligonucleotide microarrays

PubMed Central

Hu, Guohong; Wang, Hui-Yun; Greenawalt, Danielle M.; Azaro, Marco A.; Luo, Minjie; Tereshchenko, Irina V.; Cui, Xiangfeng; Yang, Qifeng; Gao, Richeng; Shen, Li; Li, Honghua

2006-01-01

Microarray-based analysis of single nucleotide polymorphisms (SNPs) has many applications in large-scale genetic studies. To minimize the influence of experimental variation, microarray data usually need to be processed in different aspects including background subtraction, normalization and low-signal filtering before genotype determination. Although many algorithms are sophisticated for these purposes, biases are still present. In the present paper, new algorithms for SNP microarray data analysis and the software, AccuTyping, developed based on these algorithms are described. The algorithms take advantage of a large number of SNPs included in each assay, and the fact that the top and bottom 20% of SNPs can be safely treated as homozygous after sorting based on their ratios between the signal intensities. These SNPs are then used as controls for color channel normalization and background subtraction. Genotype calls are made based on the logarithms of signal intensity ratios using two cutoff values, which were determined after training the program with a dataset of ∼160 000 genotypes and validated by non-microarray methods. AccuTyping was used to determine >300 000 genotypes of DNA and sperm samples. The accuracy was shown to be >99%. AccuTyping can be downloaded from . PMID:16982644

A hybrid approach to device integration on a genetic analysis platform

NASA Astrophysics Data System (ADS)

Brennan, Des; Jary, Dorothee; Kurg, Ants; Berik, Evgeny; Justice, John; Aherne, Margaret; Macek, Milan; Galvin, Paul

2012-10-01

Point-of-care (POC) systems require significant component integration to implement biochemical protocols associated with molecular diagnostic assays. Hybrid platforms where discrete components are combined in a single platform are a suitable approach to integration, where combining multiple device fabrication steps on a single substrate is not possible due to incompatible or costly fabrication steps. We integrate three devices each with a specific system functionality: (i) a silicon electro-wetting-on-dielectric (EWOD) device to move and mix sample and reagent droplets in an oil phase, (ii) a polymer microfluidic chip containing channels and reservoirs and (iii) an aqueous phase glass microarray for fluorescence microarray hybridization detection. The EWOD device offers the possibility of fully integrating on-chip sample preparation using nanolitre sample and reagent volumes. A key challenge is sample transfer from the oil phase EWOD device to the aqueous phase microarray for hybridization detection. The EWOD device, waveguide performance and functionality are maintained during the integration process. An on-chip biochemical protocol for arrayed primer extension (APEX) was implemented for single nucleotide polymorphism (SNiP) analysis. The prepared sample is aspirated from the EWOD oil phase to the aqueous phase microarray for hybridization. A bench-top instrumentation system was also developed around the integrated platform to drive the EWOD electrodes, implement APEX sample heating and image the microarray after hybridization.

A universal reference sample derived from clone vector for improved detection of differential gene expression

PubMed Central

Khan, Rishi L; Gonye, Gregory E; Gao, Guang; Schwaber, James S

2006-01-01

Background Using microarrays by co-hybridizing two samples labeled with different dyes enables differential gene expression measurements and comparisons across slides while controlling for within-slide variability. Typically one dye produces weaker signal intensities than the other often causing signals to be undetectable. In addition, undetectable spots represent a large problem for two-color microarray designs and most arrays contain at least 40% undetectable spots even when labeled with reference samples such as Stratagene's Universal Reference RNAs™. Results We introduce a novel universal reference sample that produces strong signal for all spots on the array, increasing the average fraction of detectable spots to 97%. Maximizing detectable spots on the reference image channel also decreases the variability of microarray data allowing for reliable detection of smaller differential gene expression changes. The reference sample is derived from sequence contained in the parental EST clone vector pT7T3D-Pac and is called vector RNA (vRNA). We show that vRNA can also be used for quality control of microarray printing and PCR product quality, detection of hybridization anomalies, and simplification of spot finding and segmentation tasks. This reference sample can be made inexpensively in large quantities as a renewable resource that is consistent across experiments. Conclusion Results of this study show that vRNA provides a useful universal reference that yields high signal for almost all spots on a microarray, reduces variation and allows for comparisons between experiments and laboratories. Further, it can be used for quality control of microarray printing and PCR product quality, detection of hybridization anomalies, and simplification of spot finding and segmentation tasks. This type of reference allows for detection of small changes in differential expression while reference designs in general allow for large-scale multivariate experimental designs. vRNA in combination with reference designs enable systems biology microarray experiments of small physiologically relevant changes. PMID:16677381

On the classification techniques in data mining for microarray data classification

NASA Astrophysics Data System (ADS)

Aydadenta, Husna; Adiwijaya

2018-03-01

Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

PREFACE: 30th Winter Workshop on Nuclear Dynamics (WWND2014)

NASA Astrophysics Data System (ADS)

Bellwied, Rene; Geurts, Frank; Timmins, Anthony

2014-09-01

These are the proceedings of the 30th Winter Workshop on Nuclear Dynamics, which was held in Galveston, Texas, in April 2014. As in previous years, the unique character of this conference series has allowed us to bring together nuclear scientists with very different interests to discuss recent progress and scientific achievements. Out of the 67 contributions at WWND 2014 we have selected these 34 manuscripts. The topics capture the range of theoretical and experimental advances in our field. On the experimental side we saw very exciting results from the RHIC beam energy scan program and the p-p, p-Pb and Pb-Pb runs at the highest collision energies at the LHC. On the theory side the system size dependence of the experimental measurements led to a detailed evaluation of the initial conditions and plasma propagation using a wide variety of phenomenological approaches. These results were complemented by the most recent continuum extrapolated data from lattice in order to model the complete evolution of the relativistic heavy ion system. These proceedings of the 30th Winter Workshop on Nuclear Dynamics again provide a snapshot of the status of the field. The articles, many of which were written by some of the most promising young scientists in the field, are documenting the excitement and achievements that are characteristic for modern day nuclear science. Rene Bellwied (University of Houston) Frank Geurts (Rice University) Anthony Timmins (University of Houston)

Hybrid genetic algorithm-neural network: feature extraction for unpreprocessed microarray data.

PubMed

Tong, Dong Ling; Schierz, Amanda C

2011-09-01

Suitable techniques for microarray analysis have been widely researched, particularly for the study of marker genes expressed to a specific type of cancer. Most of the machine learning methods that have been applied to significant gene selection focus on the classification ability rather than the selection ability of the method. These methods also require the microarray data to be preprocessed before analysis takes place. The objective of this study is to develop a hybrid genetic algorithm-neural network (GANN) model that emphasises feature selection and can operate on unpreprocessed microarray data. The GANN is a hybrid model where the fitness value of the genetic algorithm (GA) is based upon the number of samples correctly labelled by a standard feedforward artificial neural network (ANN). The model is evaluated by using two benchmark microarray datasets with different array platforms and differing number of classes (a 2-class oligonucleotide microarray data for acute leukaemia and a 4-class complementary DNA (cDNA) microarray dataset for SRBCTs (small round blue cell tumours)). The underlying concept of the GANN algorithm is to select highly informative genes by co-evolving both the GA fitness function and the ANN weights at the same time. The novel GANN selected approximately 50% of the same genes as the original studies. This may indicate that these common genes are more biologically significant than other genes in the datasets. The remaining 50% of the significant genes identified were used to build predictive models and for both datasets, the models based on the set of genes extracted by the GANN method produced more accurate results. The results also suggest that the GANN method not only can detect genes that are exclusively associated with a single cancer type but can also explore the genes that are differentially expressed in multiple cancer types. The results show that the GANN model has successfully extracted statistically significant genes from the unpreprocessed microarray data as well as extracting known biologically significant genes. We also show that assessing the biological significance of genes based on classification accuracy may be misleading and though the GANN's set of extra genes prove to be more statistically significant than those selected by other methods, a biological assessment of these genes is highly recommended to confirm their functionality. Copyright © 2011 Elsevier B.V. All rights reserved.

Pipeline Processing with an Iterative, Context-based Detection Model

DTIC Science & Technology

2014-04-19

stripping the incoming data stream of repeating and irrelevant signals prior to running primary detectors , adaptive beamforming and matched field processing...framework, pattern detectors , correlation detectors , subspace detectors , matched field detectors , nuclear explosion monitoring 16. SECURITY CLASSIFICATION...10 5. Teleseismic paths from earthquakes in

Crowdsourcing for translational research: analysis of biomarker expression using cancer microarrays

PubMed Central

Lawson, Jonathan; Robinson-Vyas, Rupesh J; McQuillan, Janette P; Paterson, Andy; Christie, Sarah; Kidza-Griffiths, Matthew; McDuffus, Leigh-Anne; Moutasim, Karwan A; Shaw, Emily C; Kiltie, Anne E; Howat, William J; Hanby, Andrew M; Thomas, Gareth J; Smittenaar, Peter

2017-01-01

Background: Academic pathology suffers from an acute and growing lack of workforce resource. This especially impacts on translational elements of clinical trials, which can require detailed analysis of thousands of tissue samples. We tested whether crowdsourcing – enlisting help from the public – is a sufficiently accurate method to score such samples. Methods: We developed a novel online interface to train and test lay participants on cancer detection and immunohistochemistry scoring in tissue microarrays. Lay participants initially performed cancer detection on lung cancer images stained for CD8, and we measured how extending a basic tutorial by annotated example images and feedback-based training affected cancer detection accuracy. We then applied this tutorial to additional cancer types and immunohistochemistry markers – bladder/ki67, lung/EGFR, and oesophageal/CD8 – to establish accuracy compared with experts. Using this optimised tutorial, we then tested lay participants' accuracy on immunohistochemistry scoring of lung/EGFR and bladder/p53 samples. Results: We observed that for cancer detection, annotated example images and feedback-based training both improved accuracy compared with a basic tutorial only. Using this optimised tutorial, we demonstrate highly accurate (>0.90 area under curve) detection of cancer in samples stained with nuclear, cytoplasmic and membrane cell markers. We also observed high Spearman correlations between lay participants and experts for immunohistochemistry scoring (0.91 (0.78, 0.96) and 0.97 (0.91, 0.99) for lung/EGFR and bladder/p53 samples, respectively). Conclusions: These results establish crowdsourcing as a promising method to screen large data sets for biomarkers in cancer pathology research across a range of cancers and immunohistochemical stains. PMID:27959886

Metadata management and semantics in microarray repositories.

PubMed

Kocabaş, F; Can, T; Baykal, N

2011-12-01

The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework.

DNA Microarray Wet Lab Simulation Brings Genomics into the High School Curriculum

PubMed Central

Zanta, Carolyn A.; Heyer, Laurie J.; Kittinger, Ben; Gabric, Kathleen M.; Adler, Leslie

2006-01-01

We have developed a wet lab DNA microarray simulation as part of a complete DNA microarray module for high school students. The wet lab simulation has been field tested with high school students in Illinois and Maryland as well as in workshops with high school teachers from across the nation. Instead of using DNA, our simulation is based on pH indicators, which offer many ideal teaching characteristics. The simulation requires no specialized equipment, is very inexpensive, is very reliable, and takes very little preparation time. Student and teacher assessment data indicate the simulation is popular with both groups, and students show significant learning gains. We include many resources with this publication, including all prelab introductory materials (e.g., a paper microarray activity), the student handouts, teachers notes, and pre- and postassessment tools. We did not test the simulation on other student populations, but based on teacher feedback, the simulation also may fit well in community college and in introductory and nonmajors' college biology curricula. PMID:17146040

DNA microarray wet lab simulation brings genomics into the high school curriculum.

PubMed

Campbell, A Malcolm; Zanta, Carolyn A; Heyer, Laurie J; Kittinger, Ben; Gabric, Kathleen M; Adler, Leslie; Schulz, Barbara

2006-01-01

We have developed a wet lab DNA microarray simulation as part of a complete DNA microarray module for high school students. The wet lab simulation has been field tested with high school students in Illinois and Maryland as well as in workshops with high school teachers from across the nation. Instead of using DNA, our simulation is based on pH indicators, which offer many ideal teaching characteristics. The simulation requires no specialized equipment, is very inexpensive, is very reliable, and takes very little preparation time. Student and teacher assessment data indicate the simulation is popular with both groups, and students show significant learning gains. We include many resources with this publication, including all prelab introductory materials (e.g., a paper microarray activity), the student handouts, teachers notes, and pre- and postassessment tools. We did not test the simulation on other student populations, but based on teacher feedback, the simulation also may fit well in community college and in introductory and nonmajors' college biology curricula.

Reverse phase protein microarrays: fluorometric and colorimetric detection.

PubMed

Gallagher, Rosa I; Silvestri, Alessandra; Petricoin, Emanuel F; Liotta, Lance A; Espina, Virginia

2011-01-01

The Reverse Phase Protein Microarray (RPMA) is an array platform used to quantitate proteins and their posttranslationally modified forms. RPMAs are applicable for profiling key cellular signaling pathways and protein networks, allowing direct comparison of the activation state of proteins from multiple samples within the same array. The RPMA format consists of proteins immobilized directly on a nitrocellulose substratum. The analyte is subsequently probed with a primary antibody and a series of reagents for signal amplification and detection. Due to the diversity, low concentration, and large dynamic range of protein analytes, RPMAs require stringent signal amplification methods, high quality image acquisition, and software capable of precisely analyzing spot intensities on an array. Microarray detection strategies can be either fluorescent or colorimetric. The choice of a detection system depends on (a) the expected analyte concentration, (b) type of microarray imaging system, and (c) type of sample. The focus of this chapter is to describe RPMA detection and imaging using fluorescent and colorimetric (diaminobenzidine (DAB)) methods.

Derivation of Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Teleost Reproductive Axis.

EPA Science Inventory

Oligonucleotide microarrays are a powerful tool for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-based analyses to detect diffe...

Deterring Nuclear Proliferation: The Importance of IAEA Safeguards: A TEXTBOOK

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

Rosenthal, M.D.; Fishbone, L.G.; Gallini, L.

2012-03-13

Nuclear terrorism and nuclear proliferation are among the most pressing challenges to international peace and security that we face today. Iran and Syria remain in non-compliance with the safeguards requirements of the NPT, and the nuclear ambitions of North Korea remain unchecked. Despite these challenges, the NPT remains a cornerstone of the nuclear non-proliferation regime, and the safeguards implemented by the International Atomic Energy Agency (IAEA) under the NPT play a critical role in deterring nuclear proliferation.How do they work? Where did they come from? And what is their future? This book answers these questions. Anyone studying the field ofmore » nuclear non-proliferation will benefit from reading this book, and for anyone entering the field, the book will enable them to get a running start. Part I describes the foundations of the international safeguards system: its origins in the 1930s - when new discoveries in physics made it clear immediately that nuclear energy held both peril and promise - through the entry into force in 1970 of the NPT, which codified the role of IAEA safeguards as a means to verify states NPT commitments not to acquire nuclear weapons. Part II describes the NPT safeguards system, which is based on a model safeguards agreement developed specifically for the NPT, The Structure and Content of Agreements between the Agency and States required in connection with the Treaty on the Non-Proliferation of Nuclear Weapons, which has been published by the IAEA as INFCIRC/153. Part III describes events, especially in South Africa, the DPRK, and Iraq in the early 1990s, that triggered a transformation in the way in which safeguards were conceptualized and implemented.« less

A genome-wide 20 K citrus microarray for gene expression analysis

PubMed Central

Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

2008-01-01

Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in citrus globular embryos. PMID:18598343

Running SW4 On New Commodity Technology Systems (CTS-1) Platform

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

Rodgers, Arthur J.; Petersson, N. Anders; Pitarka, Arben

We have recently been running earthquake ground motion simulations with SW4 on the new capacity computing systems, called the Commodity Technology Systems - 1 (CTS-1) at Lawrence Livermore National Laboratory (LLNL). SW4 is a fourth order time domain finite difference code developed by LLNL and distributed by the Computational Infrastructure for Geodynamics (CIG). SW4 simulates seismic wave propagation in complex three-dimensional Earth models including anelasticity and surface topography. We are modeling near-fault earthquake strong ground motions for the purposes of evaluating the response of engineered structures, such as nuclear power plants and other critical infrastructure. Engineering analysis of structures requiresmore » the inclusion of high frequencies which can cause damage, but are often difficult to include in simulations because of the need for large memory to model fine grid spacing on large domains.« less

ATMAD: robust image analysis for Automatic Tissue MicroArray De-arraying.

PubMed

Nguyen, Hoai Nam; Paveau, Vincent; Cauchois, Cyril; Kervrann, Charles

2018-04-19

Over the last two decades, an innovative technology called Tissue Microarray (TMA), which combines multi-tissue and DNA microarray concepts, has been widely used in the field of histology. It consists of a collection of several (up to 1000 or more) tissue samples that are assembled onto a single support - typically a glass slide - according to a design grid (array) layout, in order to allow multiplex analysis by treating numerous samples under identical and standardized conditions. However, during the TMA manufacturing process, the sample positions can be highly distorted from the design grid due to the imprecision when assembling tissue samples and the deformation of the embedding waxes. Consequently, these distortions may lead to severe errors of (histological) assay results when the sample identities are mismatched between the design and its manufactured output. The development of a robust method for de-arraying TMA, which localizes and matches TMA samples with their design grid, is therefore crucial to overcome the bottleneck of this prominent technology. In this paper, we propose an Automatic, fast and robust TMA De-arraying (ATMAD) approach dedicated to images acquired with brightfield and fluorescence microscopes (or scanners). First, tissue samples are localized in the large image by applying a locally adaptive thresholding on the isotropic wavelet transform of the input TMA image. To reduce false detections, a parametric shape model is considered for segmenting ellipse-shaped objects at each detected position. Segmented objects that do not meet the size and the roundness criteria are discarded from the list of tissue samples before being matched with the design grid. Sample matching is performed by estimating the TMA grid deformation under the thin-plate model. Finally, thanks to the estimated deformation, the true tissue samples that were preliminary rejected in the early image processing step are recognized by running a second segmentation step. We developed a novel de-arraying approach for TMA analysis. By combining wavelet-based detection, active contour segmentation, and thin-plate spline interpolation, our approach is able to handle TMA images with high dynamic, poor signal-to-noise ratio, complex background and non-linear deformation of TMA grid. In addition, the deformation estimation produces quantitative information to asset the manufacturing quality of TMAs.

Transcriptome analysis of salinity stress responses in common wheat using a 22k oligo-DNA microarray.

PubMed

Kawaura, Kanako; Mochida, Keiichi; Yamazaki, Yukiko; Ogihara, Yasunari

2006-04-01

In this study, we constructed a 22k wheat oligo-DNA microarray. A total of 148,676 expressed sequence tags of common wheat were collected from the database of the Wheat Genomics Consortium of Japan. These were grouped into 34,064 contigs, which were then used to design an oligonucleotide DNA microarray. Following a multistep selection of the sense strand, 21,939 60-mer oligo-DNA probes were selected for attachment on the microarray slide. This 22k oligo-DNA microarray was used to examine the transcriptional response of wheat to salt stress. More than 95% of the probes gave reproducible hybridization signals when targeted with RNAs extracted from salt-treated wheat shoots and roots. With the microarray, we identified 1,811 genes whose expressions changed more than 2-fold in response to salt. These included genes known to mediate response to salt, as well as unknown genes, and they were classified into 12 major groups by hierarchical clustering. These gene expression patterns were also confirmed by real-time reverse transcription-PCR. Many of the genes with unknown function were clustered together with genes known to be involved in response to salt stress. Thus, analysis of gene expression patterns combined with gene ontology should help identify the function of the unknown genes. Also, functional analysis of these wheat genes should provide new insight into the response to salt stress. Finally, these results indicate that the 22k oligo-DNA microarray is a reliable method for monitoring global gene expression patterns in wheat.

MADGE: scalable distributed data management software for cDNA microarrays.

PubMed

McIndoe, Richard A; Lanzen, Aaron; Hurtz, Kimberly

2003-01-01

The human genome project and the development of new high-throughput technologies have created unparalleled opportunities to study the mechanism of diseases, monitor the disease progression and evaluate effective therapies. Gene expression profiling is a critical tool to accomplish these goals. The use of nucleic acid microarrays to assess the gene expression of thousands of genes simultaneously has seen phenomenal growth over the past five years. Although commercial sources of microarrays exist, investigators wanting more flexibility in the genes represented on the array will turn to in-house production. The creation and use of cDNA microarrays is a complicated process that generates an enormous amount of information. Effective data management of this information is essential to efficiently access, analyze, troubleshoot and evaluate the microarray experiments. We have developed a distributable software package designed to track and store the various pieces of data generated by a cDNA microarray facility. This includes the clone collection storage data, annotation data, workflow queues, microarray data, data repositories, sample submission information, and project/investigator information. This application was designed using a 3-tier client server model. The data access layer (1st tier) contains the relational database system tuned to support a large number of transactions. The data services layer (2nd tier) is a distributed COM server with full database transaction support. The application layer (3rd tier) is an internet based user interface that contains both client and server side code for dynamic interactions with the user. This software is freely available to academic institutions and non-profit organizations at http://www.genomics.mcg.edu/niddkbtc.

Validation of the Swine Protein-Annotated Oligonucleotide Microarray

USDA-ARS?s Scientific Manuscript database

The specificity and utility of the Swine Protein-Annotated Oligonucleotide Microarray, or Pigoligoarray (www.pigoligoarray.org), has been evaluated by profiling the expression of transcripts from four porcine tissues. Tools for comparative analyses of expression on the Pigoligoarray were developed i...

HANSF 1.3 Users Manual FAI/98-40-R2 Hanford Spent Nuclear Fuel (SNF) Safety Analysis Model [SEC 1 and 2

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

DUNCAN, D.R.

The HANSF analysis tool is an integrated model considering phenomena inside a multi-canister overpack (MCO) spent nuclear fuel container such as fuel oxidation, convective and radiative heat transfer, and the potential for fission product release. This manual reflects the HANSF version 1.3.2, a revised version of 1.3.1. HANSF 1.3.2 was written to correct minor errors and to allow modeling of condensate flow on the MCO inner surface. HANSF 1.3.2 is intended for use on personal computers such as IBM-compatible machines with Intel processors running under Lahey TI or digital Visual FORTRAN, Version 6.0, but this does not preclude operation inmore » other environments.« less

Workflows for microarray data processing in the Kepler environment.

PubMed

Stropp, Thomas; McPhillips, Timothy; Ludäscher, Bertram; Bieda, Mark

2012-05-17

Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or R/BioConductor scripting approaches to pipeline design. Finally, we suggest that microarray data processing task workflows may provide a basis for future example-based comparison of different workflow systems. We provide a set of tools and complete workflows for microarray data analysis in the Kepler environment, which has the advantages of offering graphical, clear display of conceptual steps and parameters and the ability to easily integrate other resources such as remote data and web services.

The Oncogene PDRG1 Is an Interaction Target of Methionine Adenosyltransferases

PubMed Central

Garrido, Francisco; Reytor, Edel; Portillo, Francisco; Pajares, María A.

2016-01-01

Methionine adenosyltransferases MAT I and MAT III (encoded by Mat1a) catalyze S-adenosylmethionine synthesis in normal liver. Major hepatic diseases concur with reduced levels of this essential methyl donor, which are primarily due to an expression switch from Mat1a towards Mat2a. Additional changes in the association state and even in subcellular localization of these isoenzymes are also detected. All these alterations result in a reduced content of the moderate (MAT I) and high Vmax (MAT III) isoenzymes, whereas the low Vmax (MAT II) isoenzyme increases and nuclear accumulation of MAT I is observed. These changes derive in a reduced availability of cytoplasmic S-adenosylmethionine, together with an effort to meet its needs in the nucleus of damaged cells, rendering enhanced levels of certain epigenetic modifications. In this context, the putative role of protein-protein interactions in the control of S-adenosylmethionine synthesis has been scarcely studied. Using yeast two hybrid and a rat liver library we identified PDRG1 as an interaction target for MATα1 (catalytic subunit of MAT I and MAT III), further confirmation being obtained by immunoprecipitation and pull-down assays. Nuclear MATα interacts physically and functionally with the PDRG1 oncogene, resulting in reduced DNA methylation levels. Increased Pdrg1 expression is detected in acute liver injury and hepatoma cells, together with decreased Mat1a expression and nuclear accumulation of MATα1. Silencing of Pdrg1 expression in hepatoma cells alters their steady-state expression profile on microarrays, downregulating genes associated with tumor progression according to GO pathway analysis. Altogether, the results unveil the role of PDRG1 in the control of the nuclear methylation status through methionine adenosyltransferase binding and its putative collaboration in the progression of hepatic diseases. PMID:27548429

Plant-pathogen interactions: what microarray tells about it?

PubMed

Lodha, T D; Basak, J

2012-01-01

Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant-pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant-pathogen interaction, and ends with the future prospects of this technology.

Maskless localized patterning of biomolecules on carbon nanotube microarray functionalized by ultrafine atmospheric pressure plasma jet using biotin-avidin system

NASA Astrophysics Data System (ADS)

Abuzairi, Tomy; Okada, Mitsuru; Purnamaningsih, Retno Wigajatri; Poespawati, Nji Raden; Iwata, Futoshi; Nagatsu, Masaaki

2016-07-01

Ultrafine plasma jet is a promising technology with great potential for nano- or micro-scale surface modification. In this letter, we demonstrated the use of ultrafine atmospheric pressure plasma jet (APPJ) for patterning bio-immobilization on vertically aligned carbon nanotube (CNT) microarray platform without a physical mask. The biotin-avidin system was utilized to demonstrate localized biomolecule patterning on the biosensor devices. Using ±7.5 kV square-wave pulses, the optimum condition of plasma jet with He/NH3 gas mixture and 2.5 s treatment period has been obtained to functionalize CNTs. The functionalized CNTs were covalently linked to biotin, bovine serum albumin (BSA), and avidin-(fluorescein isothiocyanate) FITC, sequentially. BSA was necessary as a blocking agent to protect the untreated CNTs from avidin adsorption. The localized patterning results have been evaluated from avidin-FITC fluorescence signals analyzed using a fluorescence microscope. The patterning of biomolecules on the CNT microarray platform using ultrafine APPJ provides a means for potential application of microarray biosensors based on CNTs.

Improved porous silicon (P-Si) microarray based PSA (prostate specific antigen) immunoassay by optimized surface density of the capture antibody

PubMed Central

Lee, SangWook; Kim, Soyoun; Malm, Johan; Jeong, Ok Chan; Lilja, Hans; Laurell, Thomas

2014-01-01

Enriching the surface density of immobilized capture antibodies enhances the detection signal of antibody sandwich microarrays. In this study, we improved the detection sensitivity of our previously developed P-Si (porous silicon) antibody microarray by optimizing concentrations of the capturing antibody. We investigated immunoassays using a P-Si microarray at three different capture antibody (PSA - prostate specific antigen) concentrations, analyzing the influence of the antibody density on the assay detection sensitivity. The LOD (limit of detection) for PSA was 2.5ngmL−1, 80pgmL−1, and 800fgmL−1 when arraying the PSA antibody, H117 at the concentration 15µgmL−1, 35µgmL−1 and 154µgmL−1, respectively. We further investigated PSA spiked into human female serum in the range of 800fgmL−1 to 500ngmL−1. The microarray showed a LOD of 800fgmL−1 and a dynamic range of 800 fgmL−1 to 80ngmL−1 in serum spiked samples. PMID:24016590

Specific Discrimination of Three Pathogenic Salmonella enterica subsp. enterica Serotypes by carB-Based Oligonucleotide Microarray

PubMed Central

Shin, Hwa Hui; Hwang, Byeong Hee; Seo, Jeong Hyun

2014-01-01

It is important to rapidly and selectively detect and analyze pathogenic Salmonella enterica subsp. enterica in contaminated food to reduce the morbidity and mortality of Salmonella infection and to guarantee food safety. In the present work, we developed an oligonucleotide microarray containing duplicate specific capture probes based on the carB gene, which encodes the carbamoyl phosphate synthetase large subunit, as a competent biomarker evaluated by genetic analysis to selectively and efficiently detect and discriminate three S. enterica subsp. enterica serotypes: Choleraesuis, Enteritidis, and Typhimurium. Using the developed microarray system, three serotype targets were successfully analyzed in a range as low as 1.6 to 3.1 nM and were specifically discriminated from each other without nonspecific signals. In addition, the constructed microarray did not have cross-reactivity with other common pathogenic bacteria and even enabled the clear discrimination of the target Salmonella serotype from a bacterial mixture. Therefore, these results demonstrated that our novel carB-based oligonucleotide microarray can be used as an effective and specific detection system for S. enterica subsp. enterica serotypes. PMID:24185846

Specific discrimination of three pathogenic Salmonella enterica subsp. enterica serotypes by carB-based oligonucleotide microarray.

PubMed

Shin, Hwa Hui; Hwang, Byeong Hee; Seo, Jeong Hyun; Cha, Hyung Joon

2014-01-01

It is important to rapidly and selectively detect and analyze pathogenic Salmonella enterica subsp. enterica in contaminated food to reduce the morbidity and mortality of Salmonella infection and to guarantee food safety. In the present work, we developed an oligonucleotide microarray containing duplicate specific capture probes based on the carB gene, which encodes the carbamoyl phosphate synthetase large subunit, as a competent biomarker evaluated by genetic analysis to selectively and efficiently detect and discriminate three S. enterica subsp. enterica serotypes: Choleraesuis, Enteritidis, and Typhimurium. Using the developed microarray system, three serotype targets were successfully analyzed in a range as low as 1.6 to 3.1 nM and were specifically discriminated from each other without nonspecific signals. In addition, the constructed microarray did not have cross-reactivity with other common pathogenic bacteria and even enabled the clear discrimination of the target Salmonella serotype from a bacterial mixture. Therefore, these results demonstrated that our novel carB-based oligonucleotide microarray can be used as an effective and specific detection system for S. enterica subsp. enterica serotypes.

Expression profiling of nuclear receptors in breast cancer identifies TLX as a mediator of growth and invasion in triple-negative breast cancer

PubMed Central

Remenyi, Judit; Banerji, Christopher R.S.; Lai, Chun-Fui; Periyasamy, Manikandan; Lombardo, Ylenia; Busonero, Claudia; Ottaviani, Silvia; Passey, Alun; Quinlan, Philip R.; Purdie, Colin A.; Jordan, Lee B.; Thompson, Alastair M.; Finn, Richard S.; Rueda, Oscar M.; Caldas, Carlos; Gil, Jesus; Coombes, R. Charles; Fuller-Pace, Frances V.; Teschendorff, Andrew E.; Buluwela, Laki; Ali, Simak

2015-01-01

The Nuclear Receptor (NR) superfamily of transcription factors comprises 48 members, several of which have been implicated in breast cancer. Most important is estrogen receptor-α (ERα), which is a key therapeutic target. ERα action is facilitated by co-operativity with other NR and there is evidence that ERα function may be recapitulated by other NRs in ERα-negative breast cancer. In order to examine the inter-relationships between nuclear receptors, and to obtain evidence for previously unsuspected roles for any NRs, we undertook quantitative RT-PCR and bioinformatics analysis to examine their expression in breast cancer. While most NRs were expressed, bioinformatic analyses differentiated tumours into distinct prognostic groups that were validated by analyzing public microarray data sets. Although ERα and progesterone receptor were dominant in distinguishing prognostic groups, other NR strengthened these groups. Clustering analysis identified several family members with potential importance in breast cancer. Specifically, RORγ is identified as being co-expressed with ERα, whilst several NRs are preferentially expressed in ERα-negative disease, with TLX expression being prognostic in this subtype. Functional studies demonstrated the importance of TLX in regulating growth and invasion in ERα-negative breast cancer cells. PMID:26280373

Power Spectrum Analysis of Physikalisch-Technische Bundesanstalt Decay-Rate Data: Evidence for Solar Rotational Modulation

NASA Astrophysics Data System (ADS)

Sturrock, P. A.; Buncher, J. B.; Fischbach, E.; Gruenwald, J. T.; Javorsek, D.; Jenkins, J. H.; Lee, R. H.; Mattes, J. J.; Newport, J. R.

2010-12-01

Evidence for an anomalous annual periodicity in certain nuclear-decay data has led to speculation on a possible solar influence on nuclear processes. We have recently analyzed data concerning the decay rates of 36Cl and 32Si, acquired at the Brookhaven National Laboratory (BNL), to search for evidence that might be indicative of a process involving solar rotation. Smoothing of the power spectrum by weighted-running-mean analysis leads to a significant peak at frequency 11.18 year-1, which is lower than the equatorial synodic rotation rates of the convection and radiative zones. This article concerns measurements of the decay rates of 226Ra acquired at the Physikalisch-Technische Bundesanstalt (PTB) in Germany. We find that a similar (but not identical) analysis yields a significant peak in the PTB dataset at frequency 11.21 year-1, and a peak in the BNL dataset at 11.25 year-1. The change in the BNL result is not significant, since the uncertainties in the BNL and PTB analyses are estimated to be 0.13 year-1 and 0.07 year-1, respectively. Combining the two running means by forming the joint power statistic leads to a highly significant peak at frequency 11.23 year-1. We will briefly comment on the possible implications of these results for solar physics and for particle physics.

Clustering-based spot segmentation of cDNA microarray images.

PubMed

Uslan, Volkan; Bucak, Ihsan Ömür

2010-01-01

Microarrays are utilized as that they provide useful information about thousands of gene expressions simultaneously. In this study segmentation step of microarray image processing has been implemented. Clustering-based methods, fuzzy c-means and k-means, have been applied for the segmentation step that separates the spots from the background. The experiments show that fuzzy c-means have segmented spots of the microarray image more accurately than the k-means.

A biomimetic algorithm for the improved detection of microarray features

NASA Astrophysics Data System (ADS)

Nicolau, Dan V., Jr.; Nicolau, Dan V.; Maini, Philip K.

2007-02-01

One the major difficulties of microarray technology relate to the processing of large and - importantly - error-loaded images of the dots on the chip surface. Whatever the source of these errors, those obtained in the first stage of data acquisition - segmentation - are passed down to the subsequent processes, with deleterious results. As it has been demonstrated recently that biological systems have evolved algorithms that are mathematically efficient, this contribution attempts to test an algorithm that mimics a bacterial-"patented" algorithm for the search of available space and nutrients to find, "zero-in" and eventually delimitate the features existent on the microarray surface.

Averting the Nuclear Option

ERIC Educational Resources Information Center

Tierney, William G.

2007-01-01

Recently, some presidents of colleges and universities have run into serious trouble because of conflicts with their faculty. When such conflicts arise, faculty senates frequently precipitate an institutional crisis by voting (or threatening to vote) no confidence in the president. But whether one agrees or disagrees that a particular president…

Implementation of the direct S ( α , β ) method in the KENO Monte Carlo code

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

Hart, Shane W. D.; Maldonado, G. Ivan

The Monte Carlo code KENO contains thermal scattering data for a wide variety of thermal moderators. These data are processed from Evaluated Nuclear Data Files (ENDF) by AMPX and stored as double differential probability distribution functions. The method examined in this study uses S(α,β) probability distribution functions derived from the ENDF data files directly instead of being converted to double differential cross sections. This allows the size of the cross section data on the disk to be reduced substantially amount. KENO has also been updated to allow interpolation in temperature on these data so that problems can be run atmore » any temperature. Results are shown for several simplified problems for a variety of moderators. In addition, benchmark models based on the KRITZ reactor in Sweden were run, and the results are compared with the previous versions of KENO without the direct S(α,β) method. Results from the direct S(α,β) method compare favorably with the original results obtained using the double differential cross sections. Finally, sampling the data increases the run-time of the Monte Carlo calculation, but memory usage is decreased substantially.« less

Implementation of the direct S ( α , β ) method in the KENO Monte Carlo code

DOE PAGES

Hart, Shane W. D.; Maldonado, G. Ivan

2016-11-25

The Monte Carlo code KENO contains thermal scattering data for a wide variety of thermal moderators. These data are processed from Evaluated Nuclear Data Files (ENDF) by AMPX and stored as double differential probability distribution functions. The method examined in this study uses S(α,β) probability distribution functions derived from the ENDF data files directly instead of being converted to double differential cross sections. This allows the size of the cross section data on the disk to be reduced substantially amount. KENO has also been updated to allow interpolation in temperature on these data so that problems can be run atmore » any temperature. Results are shown for several simplified problems for a variety of moderators. In addition, benchmark models based on the KRITZ reactor in Sweden were run, and the results are compared with the previous versions of KENO without the direct S(α,β) method. Results from the direct S(α,β) method compare favorably with the original results obtained using the double differential cross sections. Finally, sampling the data increases the run-time of the Monte Carlo calculation, but memory usage is decreased substantially.« less

Long-term characteristics of nuclear emulsion

NASA Astrophysics Data System (ADS)

Naganawa, N.; Kuwabara, K.

2010-02-01

Long-term characteristics of the nuclear emulsion so called ``OPERA film'' used in the neutrino oscillation experiment, OPERA, has been studied for 8 years since its production or refreshing after it. In the results, it turned out to be excellent in sensitivity, amount of random noise, and refreshing characteristics. The retention capacity of latent image of tracks was also studied. The result will open the way to the recycling of 7,000,000 emulsion films which will remain not developed after 5 years of OPERA's run, and other long-term experiments with emulsion.

System Study: High-Pressure Safety Injection 1998-2014

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

Schroeder, John Alton

2015-12-01

This report presents an unreliability evaluation of the high-pressure safety injection system (HPSI) at 69 U.S. commercial nuclear power plants. Demand, run hours, and failure data from fiscal year 1998 through 2014 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period, while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPSI results.

Loss of Nuclear Localized and Tyrosine Phosphorylated Stat5 in Breast Cancer Predicts Poor Clinical Outcome and Increased Risk of Antiestrogen Therapy Failure

PubMed Central

Peck, Amy R.; Witkiewicz, Agnieszka K.; Liu, Chengbao; Stringer, Ginger A.; Klimowicz, Alexander C.; Pequignot, Edward; Freydin, Boris; Tran, Thai H.; Yang, Ning; Rosenberg, Anne L.; Hooke, Jeffrey A.; Kovatich, Albert J.; Nevalainen, Marja T.; Shriver, Craig D.; Hyslop, Terry; Sauter, Guido; Rimm, David L.; Magliocco, Anthony M.; Rui, Hallgeir

2011-01-01

Purpose To investigate nuclear localized and tyrosine phosphorylated Stat5 (Nuc-pYStat5) as a marker of prognosis in node-negative breast cancer and as a predictor of response to antiestrogen therapy. Patients and Methods Levels of Nuc-pYStat5 were analyzed in five archival cohorts of breast cancer by traditional diaminobenzidine-chromogen immunostaining and pathologist scoring of whole tissue sections or by immunofluorescence and automated quantitative analysis (AQUA) of tissue microarrays. Results Nuc-pYStat5 was an independent prognostic marker as measured by cancer-specific survival (CSS) in patients with node-negative breast cancer who did not receive systemic adjuvant therapy, when adjusted for common pathology parameters in multivariate analyses both by standard chromogen detection with pathologist scoring of whole tissue sections (cohort I; n = 233) and quantitative immunofluorescence of a tissue microarray (cohort II; n = 291). Two distinct monoclonal antibodies gave concordant results. A progression array (cohort III; n = 180) revealed frequent loss of Nuc-pYStat5 in invasive carcinoma compared to normal breast epithelia or ductal carcinoma in situ, and general loss of Nuc-pYStat5 in lymph node metastases. In cohort IV (n = 221), loss of Nuc-pYStat5 was associated with increased risk of antiestrogen therapy failure as measured by univariate CSS and time to recurrence (TTR). More sensitive AQUA quantification of Nuc-pYStat5 in antiestrogen-treated patients (cohort V; n = 97) identified by multivariate analysis patients with low Nuc-pYStat5 at elevated risk for therapy failure (CSS hazard ratio [HR], 21.55; 95% CI, 5.61 to 82.77; P < .001; TTR HR, 7.30; 95% CI, 2.34 to 22.78; P = .001). Conclusion Nuc-pYStat5 is an independent prognostic marker in node-negative breast cancer. If confirmed in prospective studies, Nuc-pYStat5 may become a useful predictive marker of response to adjuvant hormone therapy. PMID:21576635

Genome-wide identification of novel expression signatures reveal distinct patterns and prevalence of binding motifs for p53, nuclear factor-κB and other signal transcription factors in head and neck squamous cell carcinoma

PubMed Central

Yan, Bin; Yang, Xinping; Lee, Tin-Lap; Friedman, Jay; Tang, Jun; Van Waes, Carter; Chen, Zhong

2007-01-01

Background Differentially expressed gene profiles have previously been observed among pathologically defined cancers by microarray technologies, including head and neck squamous cell carcinomas (HNSCCs). However, the molecular expression signatures and transcriptional regulatory controls that underlie the heterogeneity in HNSCCs are not well defined. Results Genome-wide cDNA microarray profiling of ten HNSCC cell lines revealed novel gene expression signatures that distinguished cancer cell subsets associated with p53 status. Three major clusters of over-expressed genes (A to C) were defined through hierarchical clustering, Gene Ontology, and statistical modeling. The promoters of genes in these clusters exhibited different patterns and prevalence of transcription factor binding sites for p53, nuclear factor-κB (NF-κB), activator protein (AP)-1, signal transducer and activator of transcription (STAT)3 and early growth response (EGR)1, as compared with the frequency in vertebrate promoters. Cluster A genes involved in chromatin structure and function exhibited enrichment for p53 and decreased AP-1 binding sites, whereas clusters B and C, containing cytokine and antiapoptotic genes, exhibited a significant increase in prevalence of NF-κB binding sites. An increase in STAT3 and EGR1 binding sites was distributed among the over-expressed clusters. Novel regulatory modules containing p53 or NF-κB concomitant with other transcription factor binding motifs were identified, and experimental data supported the predicted transcriptional regulation and binding activity. Conclusion The transcription factors p53, NF-κB, and AP-1 may be important determinants of the heterogeneous pattern of gene expression, whereas STAT3 and EGR1 may broadly enhance gene expression in HNSCCs. Defining these novel gene signatures and regulatory mechanisms will be important for establishing new molecular classifications and subtyping, which in turn will promote development of targeted therapeutics for HNSCC. PMID:17498291

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

PubMed

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

[Lung cancer in survivors of radiation exposure at the Chernobyl nuclear disaster].

PubMed

Zubovskiĭ, G A; Khrisanfov, S A

2003-01-01

Epidemiology, diagnostics and therapy of lung cancer in the aftermath of Chernobyl nuclear disaster are discussed on the basis of the data released by the Federal Expert Committee. Lung cancer appeared to be the main death-causing factor. The disease was far advanced (stage IIIb and IV) in 85% of cases. The effectiveness of diagnosis can be raised if such compulsory measures as annual bronchoscopic screenings and sputum counts are carried out. Atypical cell counts have to be run in the sputum samples from all the survivors who took part in the salvaging operations of 1986-1987 and are suffering acute and chronic respiratory diseases. Particular attention should be paid to those who were working under severe dust-pollution conditions in summer.

Computing Properties of Hadrons, Nuclei and Nuclear Matter from Quantum Chromodynamics

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

Savage, Martin J.

This project was part of a coordinated software development effort which the nuclear physics lattice QCD community pursues in order to ensure that lattice calculations can make optimal use of present, and forthcoming leadership-class and dedicated hardware, including those of the national laboratories, and prepares for the exploitation of future computational resources in the exascale era. The UW team improved and extended software libraries used in lattice QCD calculations related to multi-nucleon systems, enhanced production running codes related to load balancing multi-nucleon production on large-scale computing platforms, and developed SQLite (addressable database) interfaces to efficiently archive and analyze multi-nucleon datamore » and developed a Mathematica interface for the SQLite databases.« less

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Genome-wide analysis of murine renal distal convoluted tubular cells for the target genes of mineralocorticoid receptor

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

Ueda, Kohei; Fujiki, Katsunori; Shirahige, Katsuhiko

Highlights: • We define a target gene of MR as that with MR-binding to the adjacent region of DNA. • We use ChIP-seq analysis in combination with microarray. • We, for the first time, explore the genome-wide binding profile of MR. • We reveal 5 genes as the direct target genes of MR in the renal epithelial cell-line. - Abstract: Background and objective: Mineralocorticoid receptor (MR) is a member of nuclear receptor family proteins and contributes to fluid homeostasis in the kidney. Although aldosterone-MR pathway induces several gene expressions in the kidney, it is often unclear whether the gene expressionsmore » are accompanied by direct regulations of MR through its binding to the regulatory region of each gene. The purpose of this study is to identify the direct target genes of MR in a murine distal convoluted tubular epithelial cell-line (mDCT). Methods: We analyzed the DNA samples of mDCT cells overexpressing 3xFLAG-hMR after treatment with 10{sup −7} M aldosterone for 1 h by chromatin immunoprecipitation with deep-sequence (ChIP-seq) and mRNA of the cell-line with treatment of 10{sup −7} M aldosterone for 3 h by microarray. Results: 3xFLAG-hMR overexpressed in mDCT cells accumulated in the nucleus in response to 10{sup −9} M aldosterone. Twenty-five genes were indicated as the candidate target genes of MR by ChIP-seq and microarray analyses. Five genes, Sgk1, Fkbp5, Rasl12, Tns1 and Tsc22d3 (Gilz), were validated as the direct target genes of MR by quantitative RT-qPCR and ChIP-qPCR. MR binding regions adjacent to Ctgf and Serpine1 were also validated. Conclusions: We, for the first time, captured the genome-wide distribution of MR in mDCT cells and, furthermore, identified five MR target genes in the cell-line. These results will contribute to further studies on the mechanisms of kidney diseases.« less

Gene expression profiling of whole blood: Comparison of target preparation methods for accurate and reproducible microarray analysis

PubMed Central

Vartanian, Kristina; Slottke, Rachel; Johnstone, Timothy; Casale, Amanda; Planck, Stephen R; Choi, Dongseok; Smith, Justine R; Rosenbaum, James T; Harrington, Christina A

2009-01-01

Background Peripheral blood is an accessible and informative source of transcriptomal information for many human disease and pharmacogenomic studies. While there can be significant advantages to analyzing RNA isolated from whole blood, particularly in clinical studies, the preparation of samples for microarray analysis is complicated by the need to minimize artifacts associated with highly abundant globin RNA transcripts. The impact of globin RNA transcripts on expression profiling data can potentially be reduced by using RNA preparation and labeling methods that remove or block globin RNA during the microarray assay. We compared four different methods for preparing microarray hybridization targets from human whole blood collected in PAXGene tubes. Three of the methods utilized the Affymetrix one-cycle cDNA synthesis/in vitro transcription protocol but varied treatment of input RNA as follows: i. no treatment; ii. treatment with GLOBINclear; or iii. treatment with globin PNA oligos. In the fourth method cDNA targets were prepared with the Ovation amplification and labeling system. Results We find that microarray targets generated with labeling methods that reduce globin mRNA levels or minimize the impact of globin transcripts during hybridization detect more transcripts in the microarray assay compared with the standard Affymetrix method. Comparison of microarray results with quantitative PCR analysis of a panel of genes from the NF-kappa B pathway shows good correlation of transcript measurements produced with all four target preparation methods, although method-specific differences in overall correlation were observed. The impact of freezing blood collected in PAXGene tubes on data reproducibility was also examined. Expression profiles show little or no difference when RNA is extracted from either fresh or frozen blood samples. Conclusion RNA preparation and labeling methods designed to reduce the impact of globin mRNA transcripts can significantly improve the sensitivity of the DNA microarray expression profiling assay for whole blood samples. While blockage of globin transcripts during first strand cDNA synthesis with globin PNAs resulted in the best overall performance in this study, we conclude that selection of a protocol for expression profiling studies in blood should depend on several factors, including implementation requirements of the method and study design. RNA isolated from either freshly collected or frozen blood samples stored in PAXGene tubes can be used without altering gene expression profiles. PMID:19123946

Autoregressive-model-based missing value estimation for DNA microarray time series data.

PubMed

Choong, Miew Keen; Charbit, Maurice; Yan, Hong

2009-01-01

Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

Epigenetic modification with trichostatin A does not correct specific errors of somatic cell nuclear transfer at the transcriptomic level; highlighting the non-random nature of oocyte-mediated reprogramming errors.

PubMed

Hosseini, Sayyed Morteza; Dufort, Isabelle; Nieminen, Julie; Moulavi, Fariba; Ghanaei, Hamid Reza; Hajian, Mahdi; Jafarpour, Farnoosh; Forouzanfar, Mohsen; Gourbai, Hamid; Shahverdi, Abdol Hossein; Nasr-Esfahani, Mohammad Hossein; Sirard, Marc-André

2016-01-04

The limited duration and compromised efficiency of oocyte-mediated reprogramming, which occurs during the early hours following somatic cell nuclear transfer (SCNT), may significantly interfere with epigenetic reprogramming, contributing to the high incidence of ill/fatal transcriptional phenotypes and physiological anomalies occurring later during pre- and post-implantation events. A potent histone deacetylase inhibitor, trichostatin A (TSA), was used to understand the effects of assisted epigenetic modifications on transcriptional profiles of SCNT blastocysts and to identify specific or categories of genes affected. TSA improved the yield and quality of in vitro embryo development compared to control (CTR-NT). Significance analysis of microarray results revealed that of 37,238 targeted gene transcripts represented on the microarray slide, a relatively small number of genes were differentially expressed in CTR-NT (1592 = 4.3 %) and TSA-NT (1907 = 5.1 %) compared to IVF embryos. For both SCNT groups, the majority of downregulated and more than half of upregulated genes were common and as much as 15 % of all deregulated transcripts were located on chromosome X. Correspondence analysis clustered CTR-NT and IVF transcriptomes close together regardless of the embryo production method, whereas TSA changed SCNT transcriptome to a very clearly separated cluster. Ontological classification of deregulated genes using IPA uncovered a variety of functional categories similarly affected in both SCNT groups with a preponderance of genes required for biological processes. Examination of genes involved in different canonical pathways revealed that the WNT and FGF pathways were similarly affected in both SCNT groups. Although TSA markedly changed epigenetic reprogramming of donor cells (DNA-methylation, H3K9 acetylation), reconstituted oocytes (5mC, 5hmC), and blastocysts (DNA-methylation, H3K9 acetylation), these changes did not recapitulate parallel marked changes in chromatin remodeling, and nascent mRNA and OCT4-EGFP expression of TSA-NT vs. CRT-NT embryos. The results obtained suggest that despite the extensive reprogramming of donor cells that occurred by the blastocyst stage, SCNT-specific errors are of a non-random nature in bovine and are not responsive to epigenetic modifications by TSA.

Multi-state trajectory approach to non-adiabatic dynamics: General formalism and the active state trajectory approximation

NASA Astrophysics Data System (ADS)

Tao, Guohua

2017-07-01

A general theoretical framework is derived for the recently developed multi-state trajectory (MST) approach from the time dependent Schrödinger equation, resulting in equations of motion for coupled nuclear-electronic dynamics equivalent to Hamilton dynamics or Heisenberg equation based on a new multistate Meyer-Miller (MM) model. The derived MST formalism incorporates both diabatic and adiabatic representations as limiting cases and reduces to Ehrenfest or Born-Oppenheimer dynamics in the mean-field or the single-state limits, respectively. In the general multistate formalism, nuclear dynamics is represented in terms of a set of individual state-specific trajectories, while in the active state trajectory (AST) approximation, only one single nuclear trajectory on the active state is propagated with its augmented images running on all other states. The AST approximation combines the advantages of consistent nuclear-coupled electronic dynamics in the MM model and the single nuclear trajectory in the trajectory surface hopping (TSH) treatment and therefore may provide a potential alternative to both Ehrenfest and TSH methods. The resulting algorithm features in a consistent description of coupled electronic-nuclear dynamics and excellent numerical stability. The implementation of the MST approach to several benchmark systems involving multiple nonadiabatic transitions and conical intersection shows reasonably good agreement with exact quantum calculations, and the results in both representations are similar in accuracy. The AST treatment also reproduces the exact results reasonably, sometimes even quantitatively well, with a better performance in the adiabatic representation.

Nonobservable nature of the nuclear shell structure: Meaning, illustrations, and consequences

NASA Astrophysics Data System (ADS)

Duguet, T.; Hergert, H.; Holt, J. D.; Somà, V.

2015-09-01

Background: The concept of single-nucleon shells constitutes a basic pillar of our understanding of nuclear structure. Effective single-particle energies (ESPEs) introduced by French [Proceedings of the International School of Physics "Enrico Fermi," Course XXXVI, Varenna 1965, edited by C. Bloch (Academic Press, New York, 1966)] and Baranger [Nucl. Phys. A 149, 225 (1970), 10.1016/0375-9474(70)90692-5] represent the most appropriate tool to relate many-body observables to a single-nucleon shell structure. As briefly discussed in Duguet and Hagen [Phys. Rev. C 85, 034330 (2012), 10.1103/PhysRevC.85.034330], the dependence of ESPEs on one-nucleon transfer probability matrices makes them purely theoretical quantities that "run" with the nonobservable resolution scale λ employed in the calculation. Purpose: Given that ESPEs provide a way to interpret the many-body problem in terms of simpler theoretical ingredients, the goal is to specify the terms, i.e., the exact sense and conditions, in which this interpretation can be conducted meaningfully. Methods: While the nuclear shell structure is both scale and scheme dependent, the present study focuses on the former. A detailed discussion is provided to illustrate the scale (in)dependence of observables and nonobservables and the reasons why ESPEs, i.e., the shell structure, belong to the latter category. State-of-the-art multireference in-medium similarity renormalization group and self-consistent Gorkov Green's function many-body calculations are employed to corroborate the formal analysis. This is done by comparing the behavior of several observables and of nonobservable ESPEs (and spectroscopic factors) under (quasi) unitary similarity renormalization group transformations of the Hamiltonian parametrized by the resolution scale λ . Results: The formal proofs are confirmed by the results of ab initio many-body calculations in their current stage of implementation. In practice, the unitarity of the similarity transformations is broken owing to the omission of induced many-body interactions beyond three-body operators and to the nonexact treatment of the many-body Schrödinger equation. The impact of this breaking is first characterized by quantifying the artificial running of observables over a (necessarily) finite interval of λ values. Then the genuine running of ESPEs is characterized and shown to be convincingly larger than the one of observables (which would be zero in an exact calculation). Conclusions: The nonobservable nature of the nuclear shell structure, i.e., the fact that it constitutes an intrinsically theoretical object with no counterpart in the empirical world, must be recognized and assimilated. Indeed, the shell structure cannot be determined uniquely from experimental data and cannot be talked about in an absolute sense as it depends on the nonobservable resolution scale employed in the theoretical calculation. It is only at the price of fixing arbitrarily (but conveniently) such a scale that one can establish correlations between observables and the shell structure. To some extent, fixing the resolution scale provides ESPEs (and spectroscopic factors) with a quasi-observable character. Eventually, practitioners can refer to nuclear shells and spectroscopic factors in their analyses of nuclear phenomena if, and only if, they use consistent structure and reaction theoretical schemes based on a fixed resolution scale they have agreed on prior to performing their analysis and comparisons.

Evaluation of the skin irritation using a DNA microarray on a reconstructed human epidermal model.

PubMed

Niwa, Makoto; Nagai, Kanji; Oike, Hideaki; Kobori, Masuko

2009-02-01

To avoid the need to use animals to test the skin irritancy potential of chemicals and cosmetics, it is important to establish an in vitro method based on the reconstructed human epidermal model. To evaluate skin irritancy efficiently and sensitively, we determined the gene expression induced by a topically-applied mild irritant sodium dodecyl sulfate (SDS) in a reconstructed human epidermal model LabCyte EPI-MODEL (LabCyte) using a DNA microarray carrying genes that were related to inflammation, immunity, stress and housekeeping. The expression and secretion of IL-1alpha in reconstructed human epidermal culture is known to be induced by irritation. We detected the induction of IL-1alpha expression and its secretion into the cell culture medium by treatment with 0.075% SDS for 18 h in LabCyte culture using DNA microarray, quantitative reverse-transcription polymerase chain reaction (RT-PCR) and ELISA. DNA microarray analysis indicated that the expression of 10 of the 205 genes carried on the DNA microarray was significantly induced in a LabCyte culture by 0.05% or 0.075% SDS irritation for 18 h. RT-PCR analysis confirmed that SDS treatment significantly induced the expressions of interleukin-1 receptor antagonist (IL-1RN), FOS-like antigen 1 (FOSL1), heat shock 70 kDa protein 1A (HSPA1) and myeloid differentiation primary response gene (88) (MYD88), as well as the known marker genes for irritation IL-1beta and IL-8 in a LabCyte culture. Our results showed that a DNA microarray is a useful tool for efficiently evaluating mild skin irritation using a reconstructed human epidermal model.

Sensitive immunoassay detection of multiple environmental chemicals on protein microarrays using DNA/dye conjugate as a fluorescent label.

PubMed

Fan, Ziyan; Keum, Young Soo; Li, Qing X; Shelver, Weilin L; Guo, Liang-Hong

2012-05-01

Indirect competitive immunoassays were developed on protein microarrays for the sensitive and simultaneous detection of multiple environmental chemicals in one sample. In this assay, a DNA/SYTOX Orange conjugate was employed as an antibody label to increase the fluorescence signal and sensitivity of the immunoassays. Epoxy-modified glass slides were selected as the substrate for the production of 4 × 4 coating antigen microarrays. With this signal-enhancing system, competition curves for 17β-estradiol (E2), benzo[a]pyrene (BaP) and 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) were obtained individually on the protein microarray. The IC(50) and calculated limit of detection (LOD) are 0.32 μg L(-1) and 0.022 μg L(-1) for E2, 37.2 μg L(-1) and 24.5 μg L(-1) for BaP, and 31.6 μg L(-1) and 2.8 μg L(-1) for BDE-47, respectively. LOD of E2 is 14-fold lower than the value reported in a previous study using Cy3 labeled antibody (Du et al., Clin. Chem, 2005, 51, 368-375). The results of the microarray immunoassay were within 15% of chromatographic analysis for all three pollutants in spiked river water samples, thus verifying the immunoassay. Simultaneous detection of E2, BaP and BDE-47 in one sample was demonstrated. There was no cross-reaction in the immunoassay between these three environmental chemicals. These results suggest that microarray-based immunoassays with DNA/dye conjugate labels are useful tools for the rapid, sensitive, and high throughput screening of multiple environmental contaminants.

A Graphical Systems Model and Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Female Teleost Reproductive Axis

EPA Science Inventory

Oligonucleotide microarrays and other ‘omics’ approaches are powerful tools for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-b...

Fully automated analysis of multi-resolution four-channel micro-array genotyping data

NASA Astrophysics Data System (ADS)

Abbaspour, Mohsen; Abugharbieh, Rafeef; Podder, Mohua; Tebbutt, Scott J.

2006-03-01

We present a fully-automated and robust microarray image analysis system for handling multi-resolution images (down to 3-micron with sizes up to 80 MBs per channel). The system is developed to provide rapid and accurate data extraction for our recently developed microarray analysis and quality control tool (SNP Chart). Currently available commercial microarray image analysis applications are inefficient, due to the considerable user interaction typically required. Four-channel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals. It plays an important role in the state of the art trend where traditional medical treatments are to be replaced by personalized genetic medicine, i.e. individualized therapy based on the patient's genetic heritage. However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in clinical practice, which require a turn-around timeline compatible with clinical decision-making. In this paper we have developed a fully-automated image analysis platform for the rapid investigation of hundreds of genetic variations across multiple genes. Validation tests indicate very high accuracy levels for genotyping results. Our method achieves a significant reduction in analysis time, from several hours to just a few minutes, and is completely automated requiring no manual interaction or guidance.

MALDI-TOF mass spectrometry for quantitative gene expression analysis of acid responses in Staphylococcus aureus.

PubMed

Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild

2009-07-01

Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions.

Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

PubMed

Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

2015-01-01

Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

Development and assessment of whole-genome oligonucleotide microarrays to analyze an anaerobic microbial community and its responses to oxidative stress.

PubMed

Scholten, Johannes C M; Culley, David E; Nie, Lei; Munn, Kyle J; Chow, Lely; Brockman, Fred J; Zhang, Weiwen

2007-06-29

The application of DNA microarray technology to investigate multiple-species microbial communities presents great challenges. In this study, we reported the design and quality assessment of four whole genome oligonucleotide microarrays for two syntroph bacteria, Desulfovibrio vulgaris and Syntrophobacter fumaroxidans, and two archaeal methanogens, Methanosarcina barkeri, and Methanospirillum hungatei, and their application to analyze global gene expression in a four-species microbial community in response to oxidative stress. In order to minimize the possibility of cross-hybridization, cross-genome comparison was performed to assure all probes unique to each genome so that the microarrays could provide species-level resolution. Microarray quality was validated by the good reproducibility of experimental measurements of multiple biological and analytical replicates. This study showed that S. fumaroxidans and M. hungatei responded to the oxidative stress with up-regulation of several genes known to be involved in reactive oxygen species (ROS) detoxification, such as catalase and rubrerythrin in S. fumaroxidans and thioredoxin and heat shock protein Hsp20 in M. hungatei. However, D. vulgaris seemed to be less sensitive to the oxidative stress as a member of a four-species community, since no gene involved in ROS detoxification was up-regulated. Our work demonstrated the successful application of microarrays to a multiple-species microbial community, and our preliminary results indicated that this approach could provide novel insights on the metabolism within microbial communities.

Porous Silicon Antibody Microarrays for Quantitative Analysis: Measurement of Free and Total PSA in Clinical Plasma Samples

PubMed Central

Tojo, Axel; Malm, Johan; Marko-Varga, György; Lilja, Hans; Laurell, Thomas

2014-01-01

The antibody microarrays have become widespread, but their use for quantitative analyses in clinical samples has not yet been established. We investigated an immunoassay based on nanoporous silicon antibody microarrays for quantification of total prostate-specific-antigen (PSA) in 80 clinical plasma samples, and provide quantitative data from a duplex microarray assay that simultaneously quantifies free and total PSA in plasma. To further develop the assay the porous silicon chips was placed into a standard 96-well microtiter plate for higher throughput analysis. The samples analyzed by this quantitative microarray were 80 plasma samples obtained from men undergoing clinical PSA testing (dynamic range: 0.14-44ng/ml, LOD: 0.14ng/ml). The second dataset, measuring free PSA (dynamic range: 0.40-74.9ng/ml, LOD: 0.47ng/ml) and total PSA (dynamic range: 0.87-295ng/ml, LOD: 0.76ng/ml), was also obtained from the clinical routine. The reference for the quantification was a commercially available assay, the ProStatus PSA Free/Total DELFIA. In an analysis of 80 plasma samples the microarray platform performs well across the range of total PSA levels. This assay might have the potential to substitute for the large-scale microtiter plate format in diagnostic applications. The duplex assay paves the way for a future quantitative multiplex assay, which analyses several prostate cancer biomarkers simultaneously. PMID:22921878

Systematic evaluation of RNA quality, microarray data reliability and pathway analysis in fresh, fresh frozen and formalin-fixed paraffin-embedded tissue samples.

PubMed

Wimmer, Isabella; Tröscher, Anna R; Brunner, Florian; Rubino, Stephen J; Bien, Christian G; Weiner, Howard L; Lassmann, Hans; Bauer, Jan

2018-04-20

Formalin-fixed paraffin-embedded (FFPE) tissues are valuable resources commonly used in pathology. However, formalin fixation modifies nucleic acids challenging the isolation of high-quality RNA for genetic profiling. Here, we assessed feasibility and reliability of microarray studies analysing transcriptome data from fresh, fresh-frozen (FF) and FFPE tissues. We show that reproducible microarray data can be generated from only 2 ng FFPE-derived RNA. For RNA quality assessment, fragment size distribution (DV200) and qPCR proved most suitable. During RNA isolation, extending tissue lysis time to 10 hours reduced high-molecular-weight species, while additional incubation at 70 °C markedly increased RNA yields. Since FF- and FFPE-derived microarrays constitute different data entities, we used indirect measures to investigate gene signal variation and relative gene expression. Whole-genome analyses revealed high concordance rates, while reviewing on single-genes basis showed higher data variation in FFPE than FF arrays. Using an experimental model, gene set enrichment analysis (GSEA) of FFPE-derived microarrays and fresh tissue-derived RNA-Seq datasets yielded similarly affected pathways confirming the applicability of FFPE tissue in global gene expression analysis. Our study provides a workflow comprising RNA isolation, quality assessment and microarray profiling using minimal RNA input, thus enabling hypothesis-generating pathway analyses from limited amounts of precious, pathologically significant FFPE tissues.

Cytoplasmic Drosha Is Aberrant in Precancerous Lesions of Gastric Carcinoma and Its Loss Predicts Worse Outcome for Gastric Cancer Patients.

PubMed

Zhang, Hailong; Hou, Yixuan; Xu, Liyun; Zeng, Zongyue; Wen, Siyang; Du, Yan-E; Sun, Kexin; Yin, Jiali; Lang, Lei; Tang, Xiaoli; Liu, Manran

2016-04-01

The nuclear localization of Drosha is critical for its function as a microRNA maturation regulator. Dephosphorylation of Drosha at serine 300 and serine 302 disrupts its nuclear localization, and aberrant distribution of Drosha has been detected in some tumors. The purpose of the present study was to assess cytoplasmic/nuclear Drosha expression in gastric cancer carcinogenesis and progression. Drosha expression and its subcellular location was investigated by immunohistochemical staining of a set of tissue microarrays composed of normal adjacent tissues (374), chronic gastritis (137), precancerous lesions (94), and gastric adenocarcinoma (829) samples, and in gastric cancer cell lines with varying differentiation by immunofluorescence and western blot assay. Gradual loss of cytoplasmic Drosha was accompanied by tumor progression in both gastric cancer tissues and cell lines, and was inversely associated with tumor volume (P = 0.002), tumor grade (P < 0.001), tumor stage (P = 0.018), and distant metastasis (P = 0.026). Aberrant high levels of cytoplasmic Drosha were apparent in intestinal metaplasia and dysplasia tissues. The levels of nuclear Drosha were sharply decreased in chronic gastritis and maintained through precancerous lesions to gastric cancer. High levels of cytoplasmic Drosha predicted longer survival (LR = 7.088, P = 0.008) in gastric cancer patients. Our data provide novel insights into gastric cancer that cytoplasmic Drosha potentially plays a role in preventing carcinogenesis and tumor progression, and may be an independent predictor of patient outcome.

Microfluidic microarray systems and methods thereof

DOEpatents

West, Jay A. A. [Castro Valley, CA; Hukari, Kyle W [San Ramon, CA; Hux, Gary A [Tracy, CA

2009-04-28

Disclosed are systems that include a manifold in fluid communication with a microfluidic chip having a microarray, an illuminator, and a detector in optical communication with the microarray. Methods for using these systems for biological detection are also disclosed.

cDNA Microarray Screening in Food Safety

PubMed Central

ROY, SASHWATI; SEN, CHANDAN K

2009-01-01

The cDNA microarray technology and related bioinformatics tools presents a wide range of novel application opportunities. The technology may be productively applied to address food safety. In this mini-review article, we present an update highlighting the late breaking discoveries that demonstrate the vitality of cDNA microarray technology as a tool to analyze food safety with reference to microbial pathogens and genetically modified foods. In order to bring the microarray technology to mainstream food safety, it is important to develop robust user-friendly tools that may be applied in a field setting. In addition, there needs to be a standardized process for regulatory agencies to interpret and act upon microarray-based data. The cDNA microarray approach is an emergent technology in diagnostics. Its values lie in being able to provide complimentary molecular insight when employed in addition to traditional tests for food safety, as part of a more comprehensive battery of tests. PMID:16466843

ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.

PubMed

Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B

2016-01-01

Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. © 2016 Elsevier Inc. All rights reserved.

Multiclass classification of microarray data samples with a reduced number of genes

PubMed Central

2011-01-01

Background Multiclass classification of microarray data samples with a reduced number of genes is a rich and challenging problem in Bioinformatics research. The problem gets harder as the number of classes is increased. In addition, the performance of most classifiers is tightly linked to the effectiveness of mandatory gene selection methods. Critical to gene selection is the availability of estimates about the maximum number of genes that can be handled by any classification algorithm. Lack of such estimates may lead to either computationally demanding explorations of a search space with thousands of dimensions or classification models based on gene sets of unrestricted size. In the former case, unbiased but possibly overfitted classification models may arise. In the latter case, biased classification models unable to support statistically significant findings may be obtained. Results A novel bound on the maximum number of genes that can be handled by binary classifiers in binary mediated multiclass classification algorithms of microarray data samples is presented. The bound suggests that high-dimensional binary output domains might favor the existence of accurate and sparse binary mediated multiclass classifiers for microarray data samples. Conclusions A comprehensive experimental work shows that the bound is indeed useful to induce accurate and sparse multiclass classifiers for microarray data samples. PMID:21342522

A detailed transcript-level probe annotation reveals alternative splicing based microarray platform differences

PubMed Central

Lee, Joseph C; Stiles, David; Lu, Jun; Cam, Margaret C

2007-01-01

Background Microarrays are a popular tool used in experiments to measure gene expression levels. Improving the reproducibility of microarray results produced by different chips from various manufacturers is important to create comparable and combinable experimental results. Alternative splicing has been cited as a possible cause of differences in expression measurements across platforms, though no study to this point has been conducted to show its influence in cross-platform differences. Results Using probe sequence data, a new microarray probe/transcript annotation was created based on the AceView Aug05 release that allowed for the categorization of genes based on their expression measurements' susceptibility to alternative splicing differences across microarray platforms. Examining gene expression data from multiple platforms in light of the new categorization, genes unsusceptible to alternative splicing differences showed higher signal agreement than those genes most susceptible to alternative splicing differences. The analysis gave rise to a different probe-level visualization method that can highlight probe differences according to transcript specificity. Conclusion The results highlight the need for detailed probe annotation at the transcriptome level. The presence of alternative splicing within a given sample can affect gene expression measurements and is a contributing factor to overall technical differences across platforms. PMID:17708771

Analysis of host response to bacterial infection using error model based gene expression microarray experiments

PubMed Central

Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco

2005-01-01

A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204

Integrated in silico and biological validation of the blocking effect of Cot-1 DNA on Microarray-CGH.

PubMed

Kang, Seung-Hui; Park, Chan Hee; Jeung, Hei Cheul; Kim, Ki-Yeol; Rha, Sun Young; Chung, Hyun Cheol

2007-06-01

In array-CGH, various factors may act as variables influencing the result of experiments. Among them, Cot-1 DNA, which has been used as a repetitive sequence-blocking agent, may become an artifact-inducing factor in BAC array-CGH. To identify the effect of Cot-1 DNA on Microarray-CGH experiments, Cot-1 DNA was labeled directly and Microarray-CGH experiments were performed. The results confirmed that probes which hybridized more completely with Cot-1 DNA had a higher sequence similarity to the Alu element. Further, in the sex-mismatched Microarray-CGH experiments, the variation and intensity in the fluorescent signal were reduced in the high intensity probe group in which probes were better hybridized with Cot-1 DNA. Otherwise, those of the low intensity probe group showed no alterations regardless of Cot-1 DNA. These results confirmed by in silico methods that Cot-1 DNA could block repetitive sequences in gDNA and probes. In addition, it was confirmed biologically that the blocking effect of Cot-1 DNA could be presented via its repetitive sequences, especially Alu elements. Thus, in contrast to BAC-array CGH, the use of Cot-1 DNA is advantageous in controlling experimental variation in Microarray-CGH.

sigReannot: an oligo-set re-annotation pipeline based on similarities with the Ensembl transcripts and Unigene clusters.

PubMed

Casel, Pierrot; Moreews, François; Lagarrigue, Sandrine; Klopp, Christophe

2009-07-16

Microarray is a powerful technology enabling to monitor tens of thousands of genes in a single experiment. Most microarrays are now using oligo-sets. The design of the oligo-nucleotides is time consuming and error prone. Genome wide microarray oligo-sets are designed using as large a set of transcripts as possible in order to monitor as many genes as possible. Depending on the genome sequencing state and on the assembly state the knowledge of the existing transcripts can be very different. This knowledge evolves with the different genome builds and gene builds. Once the design is done the microarrays are often used for several years. The biologists working in EADGENE expressed the need of up-to-dated annotation files for the oligo-sets they share including information about the orthologous genes of model species, the Gene Ontology, the corresponding pathways and the chromosomal location. The results of SigReannot on a chicken micro-array used in the EADGENE project compared to the initial annotations show that 23% of the oligo-nucleotide gene annotations were not confirmed, 2% were modified and 1% were added. The interest of this up-to-date annotation procedure is demonstrated through the analysis of real data previously published. SigReannot uses the oligo-nucleotide design procedure criteria to validate the probe-gene link and the Ensembl transcripts as reference for annotation. It therefore produces a high quality annotation based on reference gene sets.

Recurrent pregnancy loss evaluation combined with 24-chromosome microarray of miscarriage tissue provides a probable or definite cause of pregnancy loss in over 90% of patients.

PubMed

Popescu, F; Jaslow, C R; Kutteh, W H

2018-04-01

Will the addition of 24-chromosome microarray analysis on miscarriage tissue combined with the standard American Society for Reproductive Medicine (ASRM) evaluation for recurrent miscarriage explain most losses? Over 90% of patients with recurrent pregnancy loss (RPL) will have a probable or definitive cause identified when combining genetic testing on miscarriage tissue with the standard ASRM evaluation for recurrent miscarriage. RPL is estimated to occur in 2-4% of reproductive age couples. A probable cause can be identified in approximately 50% of patients after an ASRM recommended workup including an evaluation for parental chromosomal abnormalities, congenital and acquired uterine anomalies, endocrine imbalances and autoimmune factors including antiphospholipid syndrome. Single-center, prospective cohort study that included 100 patients seen in a private RPL clinic from 2014 to 2017. All 100 women had two or more pregnancy losses, a complete evaluation for RPL as defined by the ASRM, and miscarriage tissue evaluated by 24-chromosome microarray analysis after their second or subsequent miscarriage. Frequencies of abnormal results for evidence-based diagnostic tests considered definite or probable causes of RPL (karyotyping for parental chromosomal abnormalities, and 24-chromosome microarray evaluation for products of conception (POC); pelvic sonohysterography, hysterosalpingogram, or hysteroscopy for uterine anomalies; immunological tests for lupus anticoagulant and anticardiolipin antibodies; and blood tests for thyroid stimulating hormone (TSH), prolactin and hemoglobin A1c) were evaluated. We excluded cases where there was maternal cell contamination of the miscarriage tissue or if the ASRM evaluation was incomplete. A cost analysis for the evaluation of RPL was conducted to determine whether a proposed procedure of 24-chromome microarray evaluation followed by an ASRM RPL workup (for those RPL patients who had a normal 24-chromosome microarray evaluation) was more cost-efficient than conducting ASRM RPL workups on RPL patients followed by 24-chromosome microarray analysis (for those RPL patients who had a normal RPL workup). A definite or probable cause of pregnancy loss was identified in the vast majority (95/100; 95%) of RPL patients when a 24-chromosome pair microarray evaluation of POC testing is combined with the standard ASRM RPL workup evaluation at the time of the second or subsequent loss. The ASRM RPL workup identified an abnormality and a probable explanation for pregnancy loss in only 45/100 or 45% of all patients. A definite abnormality was identified in 67/100 patients or 67% when initial testing was performed using 24-chromosome microarray analyses on the miscarriage tissue. Only 5/100 (5%) patients, who had a euploid loss and a normal ASRM RPL workup, had a pregnancy loss without a probable or definitive cause identified. All other losses were explained by an abnormal 24-chromosome microarray analysis of the miscarriage tissue, an abnormal finding of the RPL workup, or a combination of both. Results from the cost analysis indicated that an initial approach of using a 24-chromosome microarray analysis on miscarriage tissue resulted in a 50% savings in cost to the health care system and to the patient. This is a single-center study on a small group of well-characterized women with RPL. There was an incomplete follow-up on subsequent pregnancy outcomes after evaluation, however this should not affect our principal results. The maternal age of patients varied from 26 to 45 years old. More aneuploid pregnancy losses would be expected in older women, particularly over the age of 35 years old. Evaluation of POC using 24-chromosome microarray analysis adds significantly to the ASRM recommended evaluation of RPL. Genetic evaluation on miscarriage tissue obtained at the time of the second and subsequent pregnancy losses should be offered to all couples with two or more consecutive pregnancy losses. The combination of a genetic evaluation on miscarriage tissue with an evidence-based evaluation for RPL will identify a probable or definitive cause in over 90% of miscarriages. No funding was received for this study and there are no conflicts of interest to declare. Not applicable.