New strategy for stable-isotope-aided, multidimensional NMR spectroscopy of DNA oligomers

Energy Technology Data Exchange (ETDEWEB)

Ono, Okira; Tate, Shin-Ichi; Kainosho, Masatsune [Tokyo Metropolitan Univ., Tokyo (Japan)

1994-12-01

Nuclear Magnetic Resonance (NMR) is the most efficient method for determining the solution structures of biomolecules. By applying multidimensional heteronuclear NMR techniques to {sup 13}C/{sup 15}N-labeled proteins, we can determine the solution structures of proteins with molecular mass of 20 to 30kDa at an accuracy similar to that of x-ray crystallography. Improvements in NMR instrumentation and techniques as well as the development of protein engineering methods for labeling proteins have rapidly advanced multidimensional heteronuclear NMR of proteins. In contrast, multidimensional heteronuclear NMR studies of nucleic acids is less advanced because there were no efficient methods for preparing large amounts of labeled DNA/RNA oligomers. In this report, we focused on the chemical synthesis of DNA oligomers labeled at specific residue(s). RNA oligomers with specific labels, which are difficult to synthesize by the enzyme method, can be synthesized by the chemical method. The specific labels are useful for conformational analysis of larger molecules such as protein-nucleic acid complexes.

Identification of peaks in multidimensional coincidence {gamma}-ray spectra

Energy Technology Data Exchange (ETDEWEB)

Morhac, Miroslav E-mail: fyzimiro@savba.sk; Kliman, Jan; Matousek, Vladislav; Veselsky, Martin; Turzo, Ivan

2000-03-21

In the paper a new algorithm to find peaks in two, three and multidimensional spectra, measured in large multidetector {gamma}-ray arrays, is derived. Given the dimension m, the algorithm is selective to m-fold coincidence peaks. It is insensitive to intersections of lower-fold coincidences, hereinafter called ridges.

Identification of peaks in multidimensional coincidence γ-ray spectra

International Nuclear Information System (INIS)

Morhac, Miroslav; Kliman, Jan; Matousek, Vladislav; Veselsky, Martin; Turzo, Ivan

2000-01-01

In the paper a new algorithm to find peaks in two, three and multidimensional spectra, measured in large multidetector γ-ray arrays, is derived. Given the dimension m, the algorithm is selective to m-fold coincidence peaks. It is insensitive to intersections of lower-fold coincidences, hereinafter called ridges

Multidimensional Raman spectroscopic signatures as a tool for forensic identification of body fluid traces: a review.

Science.gov (United States)

Sikirzhytski, Vitali; Sikirzhytskaya, Aliaksandra; Lednev, Igor K

2011-11-01

The analysis of body fluid traces during forensic investigations is a critical step in determining the key details of a crime. Several confirmatory and presumptive biochemical tests are currently utilized. However, these tests are all destructive, and no single method can be used to analyze all body fluids. This review outlines recent progress in the development of a novel universal approach for the nondestructive, confirmatory identification of body fluid traces using Raman spectroscopy. The method is based on the use of multidimensional spectroscopic signatures of body fluids and accounts for the intrinsic heterogeneity of dry traces and donor variation. The results presented here demonstrate that Raman spectroscopy has potential for identifying traces of semen, blood, saliva, sweat, and vaginal fluid with high confidence.

Resolution Improvement in Multidimensional Nuclear Magnetic Resonance Spectroscopy of Proteins; Amelioration de la resolution dans la resonance magnetique nucleaire multidimensionnelle des proteines

Energy Technology Data Exchange (ETDEWEB)

Duma, L

2004-07-01

The work presented in this thesis is concerned with both liquid-state and solid-state nuclear magnetic resonance (NMR) spectroscopy. Most of this work is devoted to the investigation by solid-state NMR of C{sup 13}-enriched compounds with the principal aim of presenting techniques devised for further improving the spectral resolution in multidimensional NMR of microcrystalline proteins. In fully C{sup 13}-labelled compounds, the J-coupling induces a broadening of the carbon lineshapes. We show that spin-state-selective technique called IPAP can be successfully combined with standard polarisation transfer schemes in order to remove the J-broadening in multidimensional solid-state NMR correlation experiments of fully C{sup 13}-enriched proteins. We present subsequently two techniques tailored for liquid-state NMR spectroscopy. The carbon directly detected techniques provide chemical shift information for all backbone hetero-nuclei. They are very attracting for the study of large bio-molecular systems or for the investigation of paramagnetic proteins. In the last part of this thesis, we study the spin-echo J-modulation for homonuclear two-spin 1/2 systems. Under magic-angle spinning, the theory of J-induced spin-echo modulation allows to derive a set of modulation regimes which give a spin-echo modulation exactly equal to the J-coupling. We show that the chemical-shift anisotropy and the dipolar interaction tend to stabilize the spin-echo J-modulation. The theoretical conclusions are supported by numerical simulations and experimental results obtained for three representative samples containing C{sup 13} spin pairs. (author)

Identification of Protein-Protein Interactions with Glutathione-S-Transferase (GST) Fusion Proteins.

Science.gov (United States)

Einarson, Margret B; Pugacheva, Elena N; Orlinick, Jason R

2007-08-01

INTRODUCTIONGlutathione-S-transferase (GST) fusion proteins have had a wide range of applications since their introduction as tools for synthesis of recombinant proteins in bacteria. GST was originally selected as a fusion moiety because of several desirable properties. First and foremost, when expressed in bacteria alone, or as a fusion, GST is not sequestered in inclusion bodies (in contrast to previous fusion protein systems). Second, GST can be affinity-purified without denaturation because it binds to immobilized glutathione, which provides the basis for simple purification. Consequently, GST fusion proteins are routinely used for antibody generation and purification, protein-protein interaction studies, and biochemical analysis. This article describes the use of GST fusion proteins as probes for the identification of protein-protein interactions.

Multidimensional protein fractionation of blood proteins coupled to data-independent nanoLC-MS/MS analysis.

Science.gov (United States)

Levin, Yishai; Jaros, Julian A J; Schwarz, Emanuel; Bahn, Sabine

2010-01-03

In order to exploit human blood as a source of protein disease biomarkers, robust analytical methods are needed to overcome the inherent molecular complexity of this bio-fluid. We present the coupling of label-free SAX chromatography and IMAC to a data-independent nanoLC-MS/MS (nanoLC-MS(E)) platform for analysis of blood plasma and serum proteins. The methods were evaluated using protein standards added at different concentrations to two groups of samples. The results demonstrate that both techniques enable accurate protein quantitation using low sample volumes and a minimal number of fractions. Combining both methods, 883 unique proteins were identified, of which 423 proteins showed high reproducibility. The two approaches resulted in identification of unique molecular signatures with an overlap of approximately 30%, thus providing complimentary information on sub-proteomes. These methods are potentially useful for systems biology, biomarker discovery, and investigation of phosphoproteins in blood. (c) 2009 Elsevier B.V. All rights reserved.

Computational methods for protein identification from mass spectrometry data.

Directory of Open Access Journals (Sweden)

Leo McHugh

2008-02-01

Full Text Available Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology.

Report order and identification of multidimensional stimuli: a study of event-related brain potentials.

Science.gov (United States)

Shieh, Kong-King; Shen, I-Hsuan

2004-06-01

An experiment was conducted to investigate the effect of order of report on multidimensional stimulus identification. Subjects were required to identify each two-dimensional symbol by pushing corresponding buttons on the keypad on which there were two columns representing the two dimensions. Order of report was manipulated for the dimension represented by the left or right column. Both behavioral data and event-related potentials were recorded from 14 college students. Behavioral data analysis showed that order of report had a significant effect on response times. Such results were consistent with those of previous studies. Analysis of event-related brain potentials showed significant differences in peak amplitude and mean amplitude at time windows of 120-250 msec. at Fz, F3, and F4 and of 350-750 msec. at Fz, F3, F4, Cz, and Pz. Data provided neurophysiological evidence that reporting dimensional values according to natural language habits was appropriate and less cognitively demanding.

Rapid identification of DNA-binding proteins by mass spectrometry

DEFF Research Database (Denmark)

Nordhoff, E.; Korgsdam, A.-M.; Jørgensen, H.F.

1999-01-01

We report a protocol for the rapid identification of DNA-binding proteins. Immobilized DNA probes harboring a specific sequence motif are incubated with cell or nuclear extract. Proteins are analyzed directly off the solid support by matrix-assisted laser desorption/ionization time-of-flight mass...... was validated by the identification of known prokaryotic and eukaryotic DNA-binding proteins, and its use provided evidence that poly(ADP-ribose) polymerase exhibits DNA sequence-specific binding to DNA....

Post-Electrophoretic Identification of Oxidized Proteins

Science.gov (United States)

Conrad, Craig C; Talent, John M; Malakowsky, Christina A

1999-01-01

The oxidative modification of proteins has been shown to play a major role in a number of human diseases. However, the ability to identify specific proteins that are most susceptible to oxidative modifications is difficult. Separation of proteins using polyacrylamide gel electrophoresis (PAGE) offers the analytical potential for the recovery, amino acid sequencing, and identification of thousands of individual proteins from cells and tissues. We have developed a method to allow underivatized proteins to be electroblotted onto PVDF membranes before derivatization and staining. Since both the protein and oxidation proteins are quantifiable, the specific oxidation index of each protein can be determined. The optimal sequence and conditions for the staining process are (a) electrophoresis, (b) electroblotting onto PVDF membranes, (c) derivatization of carbonyls with 2,4-DNP, (d) immunostaining with anti DNP antibody, and (e) protein staining with colloidal gold. PMID:12734585

Visualization and Dissemination of Multidimensional Proteomics Data Comparing Protein Abundance During Caenorhabditis elegans Development

Science.gov (United States)

Riffle, Michael; Merrihew, Gennifer E.; Jaschob, Daniel; Sharma, Vagisha; Davis, Trisha N.; Noble, William S.; MacCoss, Michael J.

2015-11-01

Regulation of protein abundance is a critical aspect of cellular function, organism development, and aging. Alternative splicing may give rise to multiple possible proteoforms of gene products where the abundance of each proteoform is independently regulated. Understanding how the abundances of these distinct gene products change is essential to understanding the underlying mechanisms of many biological processes. Bottom-up proteomics mass spectrometry techniques may be used to estimate protein abundance indirectly by sequencing and quantifying peptides that are later mapped to proteins based on sequence. However, quantifying the abundance of distinct gene products is routinely confounded by peptides that map to multiple possible proteoforms. In this work, we describe a technique that may be used to help mitigate the effects of confounding ambiguous peptides and multiple proteoforms when quantifying proteins. We have applied this technique to visualize the distribution of distinct gene products for the whole proteome across 11 developmental stages of the model organism Caenorhabditis elegans. The result is a large multidimensional dataset for which web-based tools were developed for visualizing how translated gene products change during development and identifying possible proteoforms. The underlying instrument raw files and tandem mass spectra may also be downloaded. The data resource is freely available on the web at http://www.yeastrc.org/wormpes/.

An Improved Methodology for Multidimensional High-Throughput Preformulation Characterization of Protein Conformational Stability

Science.gov (United States)

Maddux, Nathaniel R.; Rosen, Ilan T.; Hu, Lei; Olsen, Christopher M.; Volkin, David B.; Middaugh, C. Russell

2013-01-01

The Empirical Phase Diagram (EPD) technique is a vector-based multidimensional analysis method for summarizing large data sets from a variety of biophysical techniques. It can be used to provide comprehensive preformulation characterization of a macromolecule’s higher-order structural integrity and conformational stability. In its most common mode, it represents a type of stimulus-response diagram using environmental variables such as temperature, pH, and ionic strength as the stimulus, with alterations in macromolecular structure being the response. Until now EPD analysis has not been available in a high throughput mode because of the large number of experimental techniques and environmental stressor/stabilizer variables typically employed. A new instrument has been developed that combines circular dichroism, UV-absorbance, fluorescence spectroscopy and light scattering in a single unit with a 6-position temperature controlled cuvette turret. Using this multifunctional instrument and a new software system we have generated EPDs for four model proteins. Results confirm the reproducibility of the apparent phase boundaries and protein behavior within the boundaries. This new approach permits two EPDs to be generated per day using only 0.5 mg of protein per EPD. Thus, the new methodology generates reproducible EPDs in high-throughput mode, and represents the next step in making such determinations more routine. PMID:22447621

Multidimensional spectrometer

Science.gov (United States)

Zanni, Martin Thomas; Damrauer, Niels H.

2010-07-20

A multidimensional spectrometer for the infrared, visible, and ultraviolet regions of the electromagnetic spectrum, and a method for making multidimensional spectroscopic measurements in the infrared, visible, and ultraviolet regions of the electromagnetic spectrum. The multidimensional spectrometer facilitates measurements of inter- and intra-molecular interactions.

Identification and quantitation of signal molecule-dependent protein phosphorylation

KAUST Repository

Groen, Arnoud J.

2013-09-03

Phosphoproteomics is a fast-growing field that aims at characterizing phosphorylated proteins in a cell or a tissue at a given time. Phosphorylation of proteins is an important regulatory mechanism in many cellular processes. Gel-free phosphoproteome technique involving enrichment of phosphopeptide coupled with mass spectrometry has proven to be invaluable to detect and characterize phosphorylated proteins. In this chapter, a gel-free quantitative approach involving 15N metabolic labelling in combination with phosphopeptide enrichment by titanium dioxide (TiO2) and their identification by MS is described. This workflow can be used to gain insights into the role of signalling molecules such as cyclic nucleotides on regulatory networks through the identification and quantification of responsive phospho(proteins). © Springer Science+Business Media New York 2013.

Identification of marker proteins for the adulteration of meat products with soybean proteins by multidimensional liquid chromatography-tandem mass spectrometry.

Science.gov (United States)

Leitner, Alexander; Castro-Rubio, Florentina; Marina, Maria Luisa; Lindner, Wolfgang

2006-09-01

Soybean proteins are frequently added to processed meat products for economic reasons and to improve their functional properties. Monitoring of the addition of soybean protein to meat products is of high interest due to the existence of regulations forbidding or limiting the amount of soybean proteins that can be added during the processing of meat products. We have used chromatographic prefractionation on the protein level by perfusion liquid chromatography to isolate peaks of interest from extracts of soybean protein isolate (SPI) and of meat products containing SPI. After enzymatic digestion using trypsin, the collected fractions were analyzed by nanoflow liquid chromatography-tandem mass spectrometry. Several variants and subunits of the major seed proteins, glycinin and beta-conglycinin, were identified in SPI, along with two other proteins. In soybean-protein-containing meat samples, different glycinin A subunits could be identified from the peak discriminating between samples with and without soybean proteins added. Among those, glycinin G4 subunit A4 was consistently found in all samples. Consequently, this protein (subunit) can be used as a target for new analytical techniques in the course of identifying the addition of soybean protein to meat products.

Recent advances on multidimensional liquid chromatography–mass spectrometry for proteomics: From qualitative to quantitative analysis—A review

International Nuclear Information System (INIS)

Wu Qi; Yuan Huiming; Zhang Lihua; Zhang Yukui

2012-01-01

Highlights: ► We discuss progress of MDLC–MS systems in qualitative and quantitative proteomics. ► Both “Top-down” and “bottom-up” strategies are discussed in detail. ► On-line integrations of stable isotope labeling process are highlighted. ► This review gives insights into further directions for higher level integration. - Abstract: With the acceleration of proteome research, increasing attention has been paid to multidimensional liquid chromatography–mass spectrometry (MDLC–MS) due to its high peak capacity and separation efficiency. Recently, many efforts have been put to improve MDLC-based strategies including “top-down” and “bottom-up” to enable highly sensitive qualitative and quantitative analysis of proteins, as well as accelerate the whole analytical procedure. Integrated platforms with combination of sample pretreatment, multidimensional separations and identification were also developed to achieve high throughput and sensitive detection of proteomes, facilitating highly accurate and reproducible quantification. This review summarized the recent advances of such techniques and their applications in qualitative and quantitative analysis of proteomes.

Seed Storage Proteins as a System for Teaching Protein Identification by Mass Spectrometry in Biochemistry Laboratory

Science.gov (United States)

Wilson, Karl A.; Tan-Wilson, Anna

2013-01-01

Mass spectrometry (MS) has become an important tool in studying biological systems. One application is the identification of proteins and peptides by the matching of peptide and peptide fragment masses to the sequences of proteins in protein sequence databases. Often prior protein separation of complex protein mixtures by 2D-PAGE is needed,…

Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria

International Nuclear Information System (INIS)

Fritzsching, Keith J.; Hong, Mei; Schmidt-Rohr, Klaus

2016-01-01

We have determined refined multidimensional chemical shift ranges for intra-residue correlations ( 13 C– 13 C, 15 N– 13 C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 13 C chemical shifts and >3 million chemical shifts in total); these data were originally derived from the Biological Magnetic Resonance Data Bank. Using relatively simple non-parametric statistics to find peak maxima in the distributions of helix, sheet, coil and turn chemical shifts, and without the use of limited “hand-picked” data sets, we show that ∼94 % of the 13 C NMR data and almost all 15 N data are quite accurately referenced and assigned, with smaller standard deviations (0.2 and 0.8 ppm, respectively) than recognized previously. On the other hand, approximately 6 % of the 13 C chemical shift data in the PACSY database are shown to be clearly misreferenced, mostly by ca. −2.4 ppm. The removal of the misreferenced data and other outliers by this purging by intrinsic quality criteria (PIQC) allows for reliable identification of secondary maxima in the two-dimensional chemical-shift distributions already pre-separated by secondary structure. We demonstrate that some of these correspond to specific regions in the Ramachandran plot, including left-handed helix dihedral angles, reflect unusual hydrogen bonding, or are due to the influence of a following proline residue. With appropriate smoothing, significantly more tightly defined chemical shift ranges are obtained for each amino acid type in the different secondary structures. These chemical shift ranges, which may be defined at any statistical threshold, can be used for amino-acid type assignment and secondary-structure analysis of chemical shifts from intra-residue cross peaks by inspection or by using a

Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria

Energy Technology Data Exchange (ETDEWEB)

Fritzsching, Keith J., E-mail: kfritzsc@brandeis.edu [Brandeis University, Department of Chemistry (United States); Hong, Mei [Massachusetts Institute of Technology, Department of Chemistry (United States); Schmidt-Rohr, Klaus, E-mail: srohr@brandeis.edu [Brandeis University, Department of Chemistry (United States)

2016-02-15

We have determined refined multidimensional chemical shift ranges for intra-residue correlations ({sup 13}C–{sup 13}C, {sup 15}N–{sup 13}C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 {sup 13}C chemical shifts and >3 million chemical shifts in total); these data were originally derived from the Biological Magnetic Resonance Data Bank. Using relatively simple non-parametric statistics to find peak maxima in the distributions of helix, sheet, coil and turn chemical shifts, and without the use of limited “hand-picked” data sets, we show that ∼94 % of the {sup 13}C NMR data and almost all {sup 15}N data are quite accurately referenced and assigned, with smaller standard deviations (0.2 and 0.8 ppm, respectively) than recognized previously. On the other hand, approximately 6 % of the {sup 13}C chemical shift data in the PACSY database are shown to be clearly misreferenced, mostly by ca. −2.4 ppm. The removal of the misreferenced data and other outliers by this purging by intrinsic quality criteria (PIQC) allows for reliable identification of secondary maxima in the two-dimensional chemical-shift distributions already pre-separated by secondary structure. We demonstrate that some of these correspond to specific regions in the Ramachandran plot, including left-handed helix dihedral angles, reflect unusual hydrogen bonding, or are due to the influence of a following proline residue. With appropriate smoothing, significantly more tightly defined chemical shift ranges are obtained for each amino acid type in the different secondary structures. These chemical shift ranges, which may be defined at any statistical threshold, can be used for amino-acid type assignment and secondary-structure analysis of chemical shifts from intra

PDTD: a web-accessible protein database for drug target identification

Directory of Open Access Journals (Sweden)

Gao Zhenting

2008-02-01

Full Text Available Abstract Background Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking http://www.dddc.ac.cn/tarfisdock, which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD, and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation. Description PDTD is a web-accessible protein database for in silico target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores. Conclusion PDTD serves as a comprehensive and

Multi-dimensional Fuzzy Euler Approximation

Directory of Open Access Journals (Sweden)

Yangyang Hao

2017-05-01

Full Text Available Multi-dimensional Fuzzy differential equations driven by multi-dimen-sional Liu process, have been intensively applied in many fields. However, we can not obtain the analytic solution of every multi-dimensional fuzzy differential equation. Then, it is necessary for us to discuss the numerical results in most situations. This paper focuses on the numerical method of multi-dimensional fuzzy differential equations. The multi-dimensional fuzzy Taylor expansion is given, based on this expansion, a numerical method which is designed for giving the solution of multi-dimensional fuzzy differential equation via multi-dimensional Euler method will be presented, and its local convergence also will be discussed.

Identification of outer membrane proteins of Yersinia pestis through biotinylation

NARCIS (Netherlands)

Smither, S.J.; Hill, J.; Baar, B.L.M. van; Hulst, A.G.; Jong, A.L. de; Titball, R.W.

2007-01-01

The outer membrane of Gram-negative bacteria contains proteins that might be good targets for vaccines, antimicrobials or detection systems. The identification of surface located proteins using traditional methods is often difficult. Yersinia pestis, the causative agent of plague, was labelled with

Mass spectrometry allows direct identification of proteins in large genomes

DEFF Research Database (Denmark)

Küster, B; Mortensen, Peter V.; Andersen, Jens S.

2001-01-01

Proteome projects seek to provide systematic functional analysis of the genes uncovered by genome sequencing initiatives. Mass spectrometric protein identification is a key requirement in these studies but to date, database searching tools rely on the availability of protein sequences derived fro...

Analysis of Pseudomonas aeruginosa cell envelope proteome by capture of surface-exposed proteins on activated magnetic nanoparticles.

Directory of Open Access Journals (Sweden)

Davide Vecchietti

Full Text Available We report on specific magneto-capturing followed by Multidimensional Protein Identification Technology (MudPIT for the analysis of surface-exposed proteins of intact cells of the bacterial opportunistic pathogen Pseudomonas aeruginosa. The magneto-separation of cell envelope fragments from the soluble cytoplasmic fraction allowed the MudPIT identification of the captured and neighboring proteins. Remarkably, we identified 63 proteins captured directly by nanoparticles and 67 proteins embedded in the cell envelope fragments. For a high number of proteins, our analysis strongly indicates either surface exposure or localization in an envelope district. The localization of most identified proteins was only predicted or totally unknown. This novel approach greatly improves the sensitivity and specificity of the previous methods, such as surface shaving with proteases that was also tested on P. aeruginosa. The magneto-capture procedure is simple, safe, and rapid, and appears to be well-suited for envelope studies in highly pathogenic bacteria.

Analysis of Pseudomonas aeruginosa Cell Envelope Proteome by Capture of Surface-Exposed Proteins on Activated Magnetic Nanoparticles

Science.gov (United States)

Vecchietti, Davide; Di Silvestre, Dario; Miriani, Matteo; Bonomi, Francesco; Marengo, Mauro; Bragonzi, Alessandra; Cova, Lara; Franceschi, Eleonora; Mauri, Pierluigi; Bertoni, Giovanni

2012-01-01

We report on specific magneto-capturing followed by Multidimensional Protein Identification Technology (MudPIT) for the analysis of surface-exposed proteins of intact cells of the bacterial opportunistic pathogen Pseudomonas aeruginosa. The magneto-separation of cell envelope fragments from the soluble cytoplasmic fraction allowed the MudPIT identification of the captured and neighboring proteins. Remarkably, we identified 63 proteins captured directly by nanoparticles and 67 proteins embedded in the cell envelope fragments. For a high number of proteins, our analysis strongly indicates either surface exposure or localization in an envelope district. The localization of most identified proteins was only predicted or totally unknown. This novel approach greatly improves the sensitivity and specificity of the previous methods, such as surface shaving with proteases that was also tested on P. aeruginosa. The magneto-capture procedure is simple, safe, and rapid, and appears to be well-suited for envelope studies in highly pathogenic bacteria. PMID:23226459

Multidimensional Heat Conduction

DEFF Research Database (Denmark)

Rode, Carsten

1998-01-01

Analytical theory of multidimensional heat conduction. General heat conduction equation in three dimensions. Steay state, analytical solutions. The Laplace equation. Method of separation of variables. Principle of superposition. Shape factors. Transient, multidimensional heat conduction....

Molecular system analysis, multidimensional, dynamic, ultra-sensitive exploration of proteomes

International Nuclear Information System (INIS)

Scharattenholz, A.; Soski, V.; Stegmann, W.; Schroer, K.; Godovac-Zimmermann, J.; Cabuk, A.; Pejovi, V.; Wozny, W.; Cahill, M.A.; Drukier, A.K.; Volkovitsky, P.

2001-01-01

ProteoSys AG's holistic proteomics strategy extends beyond classical proteome research as a new paradigm. Our concept of multidimensional molecular systems analysis of complex model systems employs the innovative ProteoDyn TM approach. This enables us to correlate dynamic changes of proteomes with their biophysical and biochemical environment. Our supersensitive Multi Photon Detection (MPD) technology enables ultra-sensitive detection of proteins, deep into the low abundance domain. Our technology platform includes the affinity analysis of phospho- and glyco-proteomes, and with our 'fish hook' methods we can capture and fully characterize even serpentine G-coupled receptors and associated proteins, including routine comprehensive post-translational analyses performed by a well equipped mass spectrometry group. Throughput and quality is obtained by automation and high end robotics, with data management handled by a dedicated bioinformatics department. Thus ProteoSys AG has a range of state of the art and proprietary tools at its disposal to analyse even the most difficult complex model systems. MPD is an isotopic detection method proprietary to ProteoSys For MPD analysis we have implemented protocols where over 99% of proteins can be iodinated, and where the iodinated proteins can be identified by mass spectrometry. Because MPD measures the energy of detected particles, it can discriminate between signals originating from different isotopes co-electrophoresed by 2D-PAGE. Thus MPD imagers have a 'multicolour' functionality suitable for differential display and improved throughput, eliminating inter-gel variations. Importantly, MPD opens up not only the world of detection of low abundance proteins, but also identification and characterization. Radioactive low abundance protein spots containing less than one attomole of protein can be excised from a 2D-gel, mixed with unlabelled proteins, and 'tracked' by MPD. The identity of the labeled protein is determined by

Identification of protein binding in pictorial art Cuban

International Nuclear Information System (INIS)

Mendoza, Ariadna; Correa, Maurin; Maqueira, Isis

2011-01-01

In this paper were implemented microanalysis methodologies by histochemical analysis, and infrared spectroscopy to determine the nature of the binder in paintings and Gas Chromatography (GC) coupled to Mass Spectrometry (MS) for identification of protein binders of common use in tempera technique with the aim of having these methods as part of the identification of artistic materials in Cuban cultural heritage carried out by Archaeometry Laboratory of Havana city's Historian Cabinet. The methodologies implemented were evaluated using model samples of traditional painting techniques with variable protein binder: yolk, egg white, casein, nut oil and animal glue; ageing for 5 years. The models samples were correctly identified. It was determined the interference of pigments with the presence of nitrogen by histochemical analysis with Amido Black dye. IR spectroscopy technique allowed to differentiate between oily and mixed (oil plus protein) techniques and tempera with yolk. Oily technique was identified in wall paintings of the New San Francisco church (XIX century) and the Obrapia House (XVII century) and the technique of tempera with animal glue in the polychrome of the XVIII century which represents St. John the Evangelist belonging to the San Juan de Letran church

Computational identification of strain-, species- and genus-specific proteins

Directory of Open Access Journals (Sweden)

Thiagarajan Rathi

2005-11-01

Full Text Available Abstract Background The identification of unique proteins at different taxonomic levels has both scientific and practical value. Strain-, species- and genus-specific proteins can provide insight into the criteria that define an organism and its relationship with close relatives. Such proteins can also serve as taxon-specific diagnostic targets. Description A pipeline using a combination of computational and manual analyses of BLAST results was developed to identify strain-, species-, and genus-specific proteins and to catalog the closest sequenced relative for each protein in a proteome. Proteins encoded by a given strain are preliminarily considered to be unique if BLAST, using a comprehensive protein database, fails to retrieve (with an e-value better than 0.001 any protein not encoded by the query strain, species or genus (for strain-, species- and genus-specific proteins respectively, or if BLAST, using the best hit as the query (reverse BLAST, does not retrieve the initial query protein. Results are manually inspected for homology if the initial query is retrieved in the reverse BLAST but is not the best hit. Sequences unlikely to retrieve homologs using the default BLOSUM62 matrix (usually short sequences are re-tested using the PAM30 matrix, thereby increasing the number of retrieved homologs and increasing the stringency of the search for unique proteins. The above protocol was used to examine several food- and water-borne pathogens. We find that the reverse BLAST step filters out about 22% of proteins with homologs that would otherwise be considered unique at the genus and species levels. Analysis of the annotations of unique proteins reveals that many are remnants of prophage proteins, or may be involved in virulence. The data generated from this study can be accessed and further evaluated from the CUPID (Core and Unique Protein Identification system web site (updated semi-annually at http://pir.georgetown.edu/cupid. Conclusion CUPID

Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error.

Science.gov (United States)

Kazmierczak, Steven C; Leen, Todd K; Erdogmus, Deniz; Carreira-Perpinan, Miguel A

2007-01-01

The clinical laboratory generates large amounts of patient-specific data. Detection of errors that arise during pre-analytical, analytical, and post-analytical processes is difficult. We performed a pilot study, utilizing a multidimensional data reduction technique, to assess the utility of this method for identifying errors in laboratory data. We evaluated 13,670 individual patient records collected over a 2-month period from hospital inpatients and outpatients. We utilized those patient records that contained a complete set of 14 different biochemical analytes. We used two-dimensional generative topographic mapping to project the 14-dimensional record to a two-dimensional space. The use of a two-dimensional generative topographic mapping technique to plot multi-analyte patient data as a two-dimensional graph allows for the rapid identification of potentially anomalous data. Although we performed a retrospective analysis, this technique has the benefit of being able to assess laboratory-generated data in real time, allowing for the rapid identification and correction of anomalous data before they are released to the physician. In addition, serial laboratory multi-analyte data for an individual patient can also be plotted as a two-dimensional plot. This tool might also be useful for assessing patient wellbeing and prognosis.

Automated protein identification by the combination of MALDI MS and MS/MS spectra from different instruments.

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Levander, Fredrik; James, Peter

2005-01-01

The identification of proteins separated on two-dimensional gels is most commonly performed by trypsin digestion and subsequent matrix-assisted laser desorption ionization (MALDI) with time-of-flight (TOF). Recently, atmospheric pressure (AP) MALDI coupled to an ion trap (IT) has emerged as a convenient method to obtain tandem mass spectra (MS/MS) from samples on MALDI target plates. In the present work, we investigated the feasibility of using the two methodologies in line as a standard method for protein identification. In this setup, the high mass accuracy MALDI-TOF spectra are used to calibrate the peptide precursor masses in the lower mass accuracy AP-MALDI-IT MS/MS spectra. Several software tools were developed to automate the analysis process. Two sets of MALDI samples, consisting of 142 and 421 gel spots, respectively, were analyzed in a highly automated manner. In the first set, the protein identification rate increased from 61% for MALDI-TOF only to 85% for MALDI-TOF combined with AP-MALDI-IT. In the second data set the increase in protein identification rate was from 44% to 58%. AP-MALDI-IT MS/MS spectra were in general less effective than the MALDI-TOF spectra for protein identification, but the combination of the two methods clearly enhanced the confidence in protein identification.

Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes.

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Jiawei Luo

Full Text Available Computational approaches aided by computer science have been used to predict essential proteins and are faster than expensive, time-consuming, laborious experimental approaches. However, the performance of such approaches is still poor, making practical applications of computational approaches difficult in some fields. Hence, the development of more suitable and efficient computing methods is necessary for identification of essential proteins.In this paper, we propose a new method for predicting essential proteins in a protein interaction network, local interaction density combined with protein complexes (LIDC, based on statistical analyses of essential proteins and protein complexes. First, we introduce a new local topological centrality, local interaction density (LID, of the yeast PPI network; second, we discuss a new integration strategy for multiple bioinformatics. The LIDC method was then developed through a combination of LID and protein complex information based on our new integration strategy. The purpose of LIDC is discovery of important features of essential proteins with their neighbors in real protein complexes, thereby improving the efficiency of identification.Experimental results based on three different PPI(protein-protein interaction networks of Saccharomyces cerevisiae and Escherichia coli showed that LIDC outperformed classical topological centrality measures and some recent combinational methods. Moreover, when predicting MIPS datasets, the better improvement of performance obtained by LIDC is over all nine reference methods (i.e., DC, BC, NC, LID, PeC, CoEWC, WDC, ION, and UC.LIDC is more effective for the prediction of essential proteins than other recently developed methods.

Identification of cell wall proteins in the flax (Linum usitatissimum) stem.

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Day, Arnaud; Fénart, Stéphane; Neutelings, Godfrey; Hawkins, Simon; Rolando, Christian; Tokarski, Caroline

2013-03-01

Sequential salt (CaCl2 , LiCl) extractions were used to obtain fractions enriched in cell wall proteins (CWPs) from the stem of 60-day-old flax (Linum usitatissimum) plants. High-resolution FT-ICR MS analysis and the use of recently published genomic data allowed the identification of 11 912 peptides corresponding to a total of 1418 different proteins. Subcellular localization using TargetP, Predotar, and WoLF PSORT led to the identification of 152 putative flax CWPs that were classified into nine different functional classes previously established for Arabidopsis thaliana. Examination of different functional classes revealed the presence of a number of proteins known to be involved in, or potentially involved in cell-wall metabolism in plants. The flax stem cell wall proteome was also compared with transcriptomic data previously obtained on comparable samples. This study represents a major contribution to the identification of CWPs in flax and will lead to a better understanding of cell wall biology in this species. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multidimensional high harmonic spectroscopy

International Nuclear Information System (INIS)

Bruner, Barry D; Soifer, Hadas; Shafir, Dror; Dudovich, Nirit; Serbinenko, Valeria; Smirnova, Olga

2015-01-01

High harmonic generation (HHG) has opened up a new frontier in ultrafast science where attosecond time resolution and Angstrom spatial resolution are accessible in a single measurement. However, reconstructing the dynamics under study is limited by the multiple degrees of freedom involved in strong field interactions. In this paper we describe a new class of measurement schemes for resolving attosecond dynamics, integrating perturbative nonlinear optics with strong-field physics. These approaches serve as a basis for multidimensional high harmonic spectroscopy. Specifically, we show that multidimensional high harmonic spectroscopy can measure tunnel ionization dynamics with high precision, and resolves the interference between multiple ionization channels. In addition, we show how multidimensional HHG can function as a type of lock-in amplifier measurement. Similar to multi-dimensional approaches in nonlinear optical spectroscopy that have resolved correlated femtosecond dynamics, multi-dimensional high harmonic spectroscopy reveals the underlying complex dynamics behind attosecond scale phenomena. (paper)

Efficiency of Database Search for Identification of Mutated and Modified Proteins via Mass Spectrometry

OpenAIRE

Pevzner, Pavel A.; Mulyukov, Zufar; Dancik, Vlado; Tang, Chris L

2001-01-01

Although protein identification by matching tandem mass spectra (MS/MS) against protein databases is a widespread tool in mass spectrometry, the question about reliability of such searches remains open. Absence of rigorous significance scores in MS/MS database search makes it difficult to discard random database hits and may lead to erroneous protein identification, particularly in the case of mutated or post-translationally modified peptides. This problem is especially important for high-thr...

Numeric invariants from multidimensional persistence

Energy Technology Data Exchange (ETDEWEB)

Skryzalin, Jacek [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlsson, Gunnar [Stanford Univ., Stanford, CA (United States)

2017-05-19

In this paper, we analyze the space of multidimensional persistence modules from the perspectives of algebraic geometry. We first build a moduli space of a certain subclass of easily analyzed multidimensional persistence modules, which we construct specifically to capture much of the information which can be gained by using multidimensional persistence over one-dimensional persistence. We argue that the global sections of this space provide interesting numeric invariants when evaluated against our subclass of multidimensional persistence modules. Lastly, we extend these global sections to the space of all multidimensional persistence modules and discuss how the resulting numeric invariants might be used to study data.

Quantum and Multidimensional Explanations in a Neurobiological Context of Mind.

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Korf, Jakob

2015-08-01

This article examines the possible relevance of physical-mathematical multidimensional or quantum concepts aiming at understanding the (human) mind in a neurobiological context. Some typical features of the quantum and multidimensional concepts are briefly introduced, including entanglement, superposition, holonomic, and quantum field theories. Next, we consider neurobiological principles, such as the brain and its emerging (physical) mind, evolutionary and ontological origins, entropy, syntropy/neg-entropy, causation, and brain energy metabolism. In many biological processes, including biochemical conversions, protein folding, and sensory perception, the ubiquitous involvement of quantum mechanisms is well recognized. Quantum and multidimensional approaches might be expected to help describe and model both brain and mental processes, but an understanding of their direct involvement in mental activity, that is, without mediation by molecular processes, remains elusive. More work has to be done to bridge the gap between current neurobiological and physical-mathematical concepts with their associated quantum-mind theories. © The Author(s) 2014.

Identification of The Determinants of Enterpreneurial Success: A Multidimensional Framework

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Dyan Vidyatmoko

2017-12-01

Full Text Available Although the academics have discussed various topics related to the factors that influence the entrepreneurial success, but there are still many differences about which factors are very important. The most important characteristics of successful entrepreneurs often become a big question.  It is reasonable due to the increasing diversity of approaches used in a variety of disciplines on the study of entrepreneur. There were many literatures that discussed a variety of variables affecting the success of entrepreneurs, especially in developed countries. In an effort to fill the lack of research on the success of entrepreneurs in developing countries, especially in Indonesia,this paper tries to propose a theoretical framework to examine factors that affect the success of entrepreneurs,the proposed framework uses a multidimensional analysis of success factors whereby three factors are discussed simultaneously. These include the entrepreneur, the entrepreneurial firm and the external environment. Success is represented by three indicators which consist of employment growth, profitability and survival. This framework is the development of theoretical framework proposed by Kiggundu, and Lussier and Halabi. Compared to Kiggundu and Lussier and Halabi model, the proposed approach is expected to provide a comprehensive analysis of the factors affecting the success of entrepreneur in Indonesia. This multidimensional approach can illustrate the scope of various entrepreneurial phenomena in Indonesia.In addition, using the analytical technique to be used to test the relationship and the influence of independent variables, the concept of this framework will produce determinant variables and eliminate the variables that are not relevantThe study will use Structural Equation Model. It is relevant and useful both from the academic and practical points of view and has practical implications for policymakers in terms of conceptualizing and operationalizing factors

Pooled protein immunization for identification of cell surface antigens in Streptococcus sanguinis.

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Xiuchun Ge

2010-07-01

Full Text Available Available bacterial genomes provide opportunities for screening vaccines by reverse vaccinology. Efficient identification of surface antigens is required to reduce time and animal cost in this technology. We developed an approach to identify surface antigens rapidly in Streptococcus sanguinis, a common infective endocarditis causative species.We applied bioinformatics for antigen prediction and pooled antigens for immunization. Forty-seven surface-exposed proteins including 28 lipoproteins and 19 cell wall-anchored proteins were chosen based on computer algorithms and comparative genomic analyses. Eight proteins among these candidates and 2 other proteins were pooled together to immunize rabbits. The antiserum reacted strongly with each protein and with S. sanguinis whole cells. Affinity chromatography was used to purify the antibodies to 9 of the antigen pool components. Competitive ELISA and FACS results indicated that these 9 proteins were exposed on S. sanguinis cell surfaces. The purified antibodies had demonstrable opsonic activity.The results indicate that immunization with pooled proteins, in combination with affinity purification, and comprehensive immunological assays may facilitate cell surface antigen identification to combat infectious diseases.

Pooled protein immunization for identification of cell surface antigens in Streptococcus sanguinis.

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Ge, Xiuchun; Kitten, Todd; Munro, Cindy L; Conrad, Daniel H; Xu, Ping

2010-07-26

Available bacterial genomes provide opportunities for screening vaccines by reverse vaccinology. Efficient identification of surface antigens is required to reduce time and animal cost in this technology. We developed an approach to identify surface antigens rapidly in Streptococcus sanguinis, a common infective endocarditis causative species. We applied bioinformatics for antigen prediction and pooled antigens for immunization. Forty-seven surface-exposed proteins including 28 lipoproteins and 19 cell wall-anchored proteins were chosen based on computer algorithms and comparative genomic analyses. Eight proteins among these candidates and 2 other proteins were pooled together to immunize rabbits. The antiserum reacted strongly with each protein and with S. sanguinis whole cells. Affinity chromatography was used to purify the antibodies to 9 of the antigen pool components. Competitive ELISA and FACS results indicated that these 9 proteins were exposed on S. sanguinis cell surfaces. The purified antibodies had demonstrable opsonic activity. The results indicate that immunization with pooled proteins, in combination with affinity purification, and comprehensive immunological assays may facilitate cell surface antigen identification to combat infectious diseases.

DNA-Catalytically Active Gold Nanoparticle Conjugates-Based Colorimetric Multidimensional Sensor Array for Protein Discrimination.

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Wei, Xiangcong; Chen, Zhengbo; Tan, Lulu; Lou, Tianhong; Zhao, Yan

2017-01-03

A series of single-strand oligonucleotides functionalized catalytically active gold nanoparticle (AuNPs) as nonspecific receptors have been designed to build a protein sensing array. We take advantage of the correlation between the catalytic activity and the exposed surface area of AuNPs, i.e., DNA-proteins interactions mask the surface area of AuNPs, leading to poor catalytic performance of AuNPs. As the number of DNA-bound proteins increases, the surfaces of AuNPs become more masked; thus, the time of 4- nitrophenol/NaBH 4 reaction for color change (yellow → colorless) of the solution increases. Taking advantage of three nonspecific SH-labeled DNA sequences (A15, C15, and T15) as array sensing elements and the color-change time (CCT) of the solution as signal readout, colorimetric response patterns can be obtained on the array and identified via linear discriminant analysis (LDA). Eleven proteins have been completely distinguished with 100% accuracy with the naked eye at the 30 nM level. Remarkably, two similar proteins (bovine serum albumin and human serum albumin), two different proteins (bovine serum albumin and concanavalin) at the same concentration, and the mixtures of the two proteins with different molar ratios have been discriminated with 100%. The practicability of this sensor array is further validated by high accuracy (100%) identification of 11 proteins in human serum samples.

Identification of Arsenic Direct-Binding Proteins in Acute Promyelocytic Leukaemia Cells

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Tao Zhang

2015-11-01

Full Text Available The identification of arsenic direct-binding proteins is essential for determining the mechanism by which arsenic trioxide achieves its chemotherapeutic effects. At least two cysteines close together in the amino acid sequence are crucial to the binding of arsenic and essential to the identification of arsenic-binding proteins. In the present study, arsenic binding proteins were pulled down with streptavidin and identified using a liquid chromatograph-mass spectrometer (LC-MS/MS. More than 40 arsenic-binding proteins were separated, and redox-related proteins, glutathione S-transferase P1 (GSTP1, heat shock 70 kDa protein 9 (HSPA9 and pyruvate kinase M2 (PKM2, were further studied using binding assays in vitro. Notably, PKM2 has a high affinity for arsenic. In contrast to PKM2, GSTP1and HSPA9 did not combine with arsenic directly in vitro. These observations suggest that arsenic-mediated acute promyelocytic leukaemia (APL suppressive effects involve PKM2. In summary, we identified several arsenic binding proteins in APL cells and investigated the therapeutic mechanisms of arsenic trioxide for APL. Further investigation into specific signal pathways by which PKM2 mediates APL developments may lead to a better understanding of arsenic effects on APL.

Sequence-specific capture of protein-DNA complexes for mass spectrometric protein identification.

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Cheng-Hsien Wu

Full Text Available The regulation of gene transcription is fundamental to the existence of complex multicellular organisms such as humans. Although it is widely recognized that much of gene regulation is controlled by gene-specific protein-DNA interactions, there presently exists little in the way of tools to identify proteins that interact with the genome at locations of interest. We have developed a novel strategy to address this problem, which we refer to as GENECAPP, for Global ExoNuclease-based Enrichment of Chromatin-Associated Proteins for Proteomics. In this approach, formaldehyde cross-linking is employed to covalently link DNA to its associated proteins; subsequent fragmentation of the DNA, followed by exonuclease digestion, produces a single-stranded region of the DNA that enables sequence-specific hybridization capture of the protein-DNA complex on a solid support. Mass spectrometric (MS analysis of the captured proteins is then used for their identification and/or quantification. We show here the development and optimization of GENECAPP for an in vitro model system, comprised of the murine insulin-like growth factor-binding protein 1 (IGFBP1 promoter region and FoxO1, a member of the forkhead rhabdomyosarcoma (FoxO subfamily of transcription factors, which binds specifically to the IGFBP1 promoter. This novel strategy provides a powerful tool for studies of protein-DNA and protein-protein interactions.

Protein social behavior makes a stronger signal for partner identification than surface geometry

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Laine, Elodie

2016-01-01

ABSTRACT Cells are interactive living systems where proteins movements, interactions and regulation are substantially free from centralized management. How protein physico‐chemical and geometrical properties determine who interact with whom remains far from fully understood. We show that characterizing how a protein behaves with many potential interactors in a complete cross‐docking study leads to a sharp identification of its cellular/true/native partner(s). We define a sociability index, or S‐index, reflecting whether a protein likes or not to pair with other proteins. Formally, we propose a suitable normalization function that accounts for protein sociability and we combine it with a simple interface‐based (ranking) score to discriminate partners from non‐interactors. We show that sociability is an important factor and that the normalization permits to reach a much higher discriminative power than shape complementarity docking scores. The social effect is also observed with more sophisticated docking algorithms. Docking conformations are evaluated using experimental binding sites. These latter approximate in the best possible way binding sites predictions, which have reached high accuracy in recent years. This makes our analysis helpful for a global understanding of partner identification and for suggesting discriminating strategies. These results contradict previous findings claiming the partner identification problem being solvable solely with geometrical docking. Proteins 2016; 85:137–154. © 2016 Wiley Periodicals, Inc. PMID:27802579

Talent identification and development programmes in sport : current models and future directions.

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Vaeyens, Roel; Lenoir, Matthieu; Williams, A Mark; Philippaerts, Renaat M

2008-01-01

Many children strive to attain excellence in sport. However, although talent identification and development programmes have gained popularity in recent decades, there remains a lack of consensus in relation to how talent should be defined or identified and there is no uniformly accepted theoretical framework to guide current practice. The success rates of talent identification and development programmes have rarely been assessed and the validity of the models applied remains highly debated. This article provides an overview of current knowledge in this area with special focus on problems associated with the identification of gifted adolescents. There is a growing agreement that traditional cross-sectional talent identification models are likely to exclude many, especially late maturing, 'promising' children from development programmes due to the dynamic and multidimensional nature of sport talent. A conceptual framework that acknowledges both genetic and environmental influences and considers the dynamic and multidimensional nature of sport talent is presented. The relevance of this model is highlighted and recommendations for future work provided. It is advocated that talent identification and development programmes should be dynamic and interconnected taking into consideration maturity status and the potential to develop rather than to exclude children at an early age. Finally, more representative real-world tasks should be developed and employed in a multidimensional design to increase the efficacy of talent identification and development programmes.

Multidimensional proteomics analysis of amniotic fluid to provide insight into the mechanisms of idiopathic preterm birth.

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Irina A Buhimschi

2008-04-01

Full Text Available Though recent advancement in proteomics has provided a novel perspective on several distinct pathogenetic mechanisms leading to preterm birth (inflammation, bleeding, the etiology of most preterm births still remains elusive. We conducted a multidimensional proteomic analysis of the amniotic fluid to identify pathways related to preterm birth in the absence of inflammation or bleeding.A proteomic fingerprint was generated from fresh amniotic fluid using surface-enhanced laser desorbtion ionization time of flight (SELDI-TOF mass spectrometry in a total of 286 consecutive samples retrieved from women who presented with signs or symptoms of preterm labor or preterm premature rupture of the membranes. Inflammation and/or bleeding proteomic patterns were detected in 32% (92/286 of the SELDI tracings. In the remaining tracings, a hierarchical algorithm was applied based on descriptors quantifying similarity/dissimilarity among proteomic fingerprints. This allowed identification of a novel profile (Q-profile based on the presence of 5 SELDI peaks in the 10-12.5 kDa mass area. Women displaying the Q-profile (mean+/-SD, gestational age: 25+/-4 weeks, n = 40 were more likely to deliver preterm despite expectant management in the context of intact membranes and normal amniotic fluid clinical results. Utilizing identification-centered proteomics techniques (fluorescence two-dimensional differential gel electrophoresis, robotic tryptic digestion and mass spectrometry coupled with Protein ANalysis THrough Evolutionary Relationships (PANTHER ontological classifications, we determined that in amniotic fluids with Q-profile the differentially expressed proteins are primarily involved in non-inflammatory biological processes such as protein metabolism, signal transduction and transport.Proteomic profiling of amniotic fluid coupled with non-hierarchical bioinformatics algorithms identified a subgroup of patients at risk for preterm birth in the absence of intra

Identification of a novel Plasmopara halstedii elicitor protein combining de novo peptide sequencing algorithms and RACE-PCR

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Madlung Johannes

2010-05-01

Full Text Available Abstract Background Often high-quality MS/MS spectra of tryptic peptides do not match to any database entry because of only partially sequenced genomes and therefore, protein identification requires de novo peptide sequencing. To achieve protein identification of the economically important but still unsequenced plant pathogenic oomycete Plasmopara halstedii, we first evaluated the performance of three different de novo peptide sequencing algorithms applied to a protein digests of standard proteins using a quadrupole TOF (QStar Pulsar i. Results The performance order of the algorithms was PEAKS online > PepNovo > CompNovo. In summary, PEAKS online correctly predicted 45% of measured peptides for a protein test data set. All three de novo peptide sequencing algorithms were used to identify MS/MS spectra of tryptic peptides of an unknown 57 kDa protein of P. halstedii. We found ten de novo sequenced peptides that showed homology to a Phytophthora infestans protein, a closely related organism of P. halstedii. Employing a second complementary approach, verification of peptide prediction and protein identification was performed by creation of degenerate primers for RACE-PCR and led to an ORF of 1,589 bp for a hypothetical phosphoenolpyruvate carboxykinase. Conclusions Our study demonstrated that identification of proteins within minute amounts of sample material improved significantly by combining sensitive LC-MS methods with different de novo peptide sequencing algorithms. In addition, this is the first study that verified protein prediction from MS data by also employing a second complementary approach, in which RACE-PCR led to identification of a novel elicitor protein in P. halstedii.

Identification of ATM Protein Kinase Phosphorylation Sites by Mass Spectrometry.

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Graham, Mark E; Lavin, Martin F; Kozlov, Sergei V

2017-01-01

ATM (ataxia-telangiectasia mutated) protein kinase is a key regulator of cellular responses to DNA damage and oxidative stress. DNA damage triggers complex cascade of signaling events leading to numerous posttranslational modification on multitude of proteins. Understanding the regulation of ATM kinase is therefore critical not only for understanding the human genetic disorder ataxia-telangiectasia and potential treatment strategies, but essential for deciphering physiological responses of cells to stress. These responses play an important role in carcinogenesis, neurodegeneration, and aging. We focus here on the identification of DNA damage inducible ATM phosphorylation sites to understand the importance of autophosphorylation in the mechanism of ATM kinase activation. We demonstrate the utility of using immunoprecipitated ATM in quantitative LC-MS/MS workflow with stable isotope dimethyl labeling of ATM peptides for identification of phosphorylation sites.

Accelerated identification of proteins by mass spectrometry by employing covalent pre-gel staining with Uniblue A.

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Marco A Mata-Gómez

Full Text Available BACKGROUND: The identification of proteins by mass spectrometry is a standard method in biopharmaceutical quality control and biochemical research. Prior to identification by mass spectrometry, proteins are usually pre-separated by electrophoresis. However, current protein staining and de-staining protocols are tedious and time consuming, and therefore prolong the sample preparation time for mass spectrometry. METHODOLOGY AND PRINCIPAL FINDINGS: We developed a 1-minute covalent pre-gel staining protocol for proteins, which does not require de-staining before the mass spectrometry analysis. We investigated the electrophoretic properties of derivatized proteins and peptides and studied their behavior in mass spectrometry. Further, we elucidated the preferred reaction of proteins with Uniblue A and demonstrate the integration of the peptide derivatization into typical informatics tools. CONCLUSIONS AND SIGNIFICANCE: The Uniblue A staining method drastically speeds up the sample preparation for the mass spectrometry based identification of proteins. The application of this chemo-proteomic strategy will be advantageous for routine quality control of proteins and for time-critical tasks in protein analysis.

A multidimensional strategy to detect polypharmacological targets in the absence of structural and sequence homology.

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Durrant, Jacob D; Amaro, Rommie E; Xie, Lei; Urbaniak, Michael D; Ferguson, Michael A J; Haapalainen, Antti; Chen, Zhijun; Di Guilmi, Anne Marie; Wunder, Frank; Bourne, Philip E; McCammon, J Andrew

2010-01-22

Conventional drug design embraces the "one gene, one drug, one disease" philosophy. Polypharmacology, which focuses on multi-target drugs, has emerged as a new paradigm in drug discovery. The rational design of drugs that act via polypharmacological mechanisms can produce compounds that exhibit increased therapeutic potency and against which resistance is less likely to develop. Additionally, identifying multiple protein targets is also critical for side-effect prediction. One third of potential therapeutic compounds fail in clinical trials or are later removed from the market due to unacceptable side effects often caused by off-target binding. In the current work, we introduce a multidimensional strategy for the identification of secondary targets of known small-molecule inhibitors in the absence of global structural and sequence homology with the primary target protein. To demonstrate the utility of the strategy, we identify several targets of 4,5-dihydroxy-3-(1-naphthyldiazenyl)-2,7-naphthalenedisulfonic acid, a known micromolar inhibitor of Trypanosoma brucei RNA editing ligase 1. As it is capable of identifying potential secondary targets, the strategy described here may play a useful role in future efforts to reduce drug side effects and/or to increase polypharmacology.

Enhanced detection method for corneal protein identification using shotgun proteomics

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Schlager John J

2009-06-01

Full Text Available Abstract Background The cornea is a specialized transparent connective tissue responsible for the majority of light refraction and image focus for the retina. There are three main layers of the cornea: the epithelium that is exposed and acts as a protective barrier for the eye, the center stroma consisting of parallel collagen fibrils that refract light, and the endothelium that is responsible for hydration of the cornea from the aqueous humor. Normal cornea is an immunologically privileged tissue devoid of blood vessels, but injury can produce a loss of these conditions causing invasion of other processes that degrade the homeostatic properties resulting in a decrease in the amount of light refracted onto the retina. Determining a measure and drift of phenotypic cornea state from normal to an injured or diseased state requires knowledge of the existing protein signature within the tissue. In the study of corneal proteins, proteomics procedures have typically involved the pulverization of the entire cornea prior to analysis. Separation of the epithelium and endothelium from the core stroma and performing separate shotgun proteomics using liquid chromatography/mass spectrometry results in identification of many more proteins than previously employed methods using complete pulverized cornea. Results Rabbit corneas were purchased, the epithelium and endothelium regions were removed, proteins processed and separately analyzed using liquid chromatography/mass spectrometry. Proteins identified from separate layers were compared against results from complete corneal samples. Protein digests were separated using a six hour liquid chromatographic gradient and ion-trap mass spectrometry used for detection of eluted peptide fractions. The SEQUEST database search results were filtered to allow only proteins with match probabilities of equal or better than 10-3 and peptides with a probability of 10-2 or less with at least two unique peptides isolated within

Proteomics - a novel approach to the identification and characterisation of plasmodesmatal proteins

International Nuclear Information System (INIS)

Faulkner, C.R.; Blackman, L.M.; Lyon, B.R.; Overall, R.L.

2001-01-01

The development of proteomic methods, such as 2-dimensional gel electrophoresis (2-DE), has established a high resolution means of identifying and characterising proteins from a given protein mixture. The biochemical composition of plasmodesmata, the intercellular channels between plant cells, is poorly described despite extensive attempts to identify protemaceous plasmodesmatal components. These attempts have been confounded by the large number of proteins in the cell wall. We have exploited the anatomy of the alga Chara corallina to separate tissues with (nodal cells) and tissues without (internodal cells) plasmodesmata. Proteins specific to the cytoplasmic and wall protein extracts of nodal and internodal tissue were identified by comparison of 2-DE gels of these extracts. In particular, a 95 kDa protein was identified as specific to the nodal cells in both 1-dimensional and 2-dimensional comparisons of cytoplasmic nodal and internodal protein extracts. This protein was analysed by electron spray ionization time of flight tandem mass spectroscopy (ESI-TOF MS/MS) and the sequence obtained showed similarity to plant lipoxygenases. Further proteins of interest were identified in 2-DE resolution of extracts from the nodal cytoplasm, including two 49 kDa proteins and two 46 kDa proteins, and from the nodal cell walls, including a cluster of proteins around 30 kDa. Thus, a proteomic strategy for the identification and characterisation of proteins specific to different cell types in Chara corallina has been developed, with potential application to the identification and characterisation of plasmodesmatal proteins

Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering

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Li Weizhong

2008-04-01

Full Text Available Abstract Background The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, metagenomic datasets are characterized by the presence of organisms with varying GC composition, codon usage biases etc., and consequently gene identification is challenging. The vast amount of sequence data also requires faster protein family classification tools. Results We present a computational improvement to a sequence clustering approach that we developed previously to identify and classify protein coding genes in large microbial metagenomic datasets. The clustering approach can be used to identify protein coding genes in prokaryotes, viruses, and intron-less eukaryotes. The computational improvement is based on an incremental clustering method that does not require the expensive all-against-all compute that was required by the original approach, while still preserving the remote homology detection capabilities. We present evaluations of the clustering approach in protein-coding gene identification and classification, and also present the results of updating the protein clusters from our previous work with recent genomic and metagenomic sequences. The clustering results are available via CAMERA, (http://camera.calit2.net. Conclusion The clustering paradigm is shown to be a very useful tool in the analysis of microbial metagenomic data. The incremental clustering method is shown to be much faster than the original approach in identifying genes, grouping sequences into existing protein families, and also identifying novel families that have multiple members in a metagenomic dataset. These clusters provide a basis for further studies of protein families.

Are neutral loss and internal product ions useful for top-down protein identification?

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Xiao, Kaijie; Yu, Fan; Fang, Houqin; Xue, Bingbing; Liu, Yan; Li, Yunhui; Tian, Zhixin

2017-05-08

Neutral loss and internal product ions have been found to be significant in both peptide and protein tandem mass spectra and they have been proposed to be included in database search and for protein identification. In addition to common canonical b/y ions in collision-based dissociation or c/z ions in electron-based dissociation, inclusion of neutral loss and internal product ions would certainly make better use of tandem mass spectra data; however, their ultimate utility for protein identification with false discovery rate control remains unclear. Here we report our proteome-level utility benchmarking of neutral loss and internal product ions with tandem mass spectra of intact E. coli proteome. Utility of internal product ions was further evaluated at the protein level using selected tandem mass spectra of individual E. coli proteins. We found that both neutral loss and internal products ions do not have direct utility for protein identification when they were used for scoring of P Score; but they do have indirect utility for provision of more canonical b/y ions when they are included in the database search and overlapping ions between different ion types are resolved. Tandem mass spectrometry has evolved to be a state-of-the-art method for characterization of protein primary structures (including amino acid sequence, post-translational modifications (PTMs) as well as their site location), where full study and utilization tandem mass spectra and product ions are indispensable. This primary structure information is essential for higher order structure and eventual function study of proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification and analysis of multi-protein complexes in placenta.

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Fuqiang Wang

Full Text Available Placental malfunction induces pregnancy disorders which contribute to life-threatening complications for both the mother and the fetus. Identification and characterization of placental multi-protein complexes is an important step to integratedly understand the protein-protein interaction networks in placenta which determine placental function. In this study, blue native/sodium dodecyl sulfate polyacrylamide gel electrophoresis (BN/SDS-PAGE and Liquid chromatography-tandem mass spectrometry (LC-MS/MS were used to screen the multi-protein complexes in placenta. 733 unique proteins and 34 known and novel heterooligomeric multi-protein complexes including mitochondrial respiratory chain complexes, integrin complexes, proteasome complexes, histone complex, and heat shock protein complexes were identified. A novel protein complex, which involves clathrin and small conductance calcium-activated potassium (SK channel protein 2, was identified and validated by antibody based gel shift assay, co-immunoprecipitation and immunofluorescence staining. These results suggest that BN/SDS-PAGE, when integrated with LC-MS/MS, is a very powerful and versatile tool for the investigation of placental protein complexes. This work paves the way for deeper functional characterization of the placental protein complexes associated with pregnancy disorders.

Identification of Tobacco Topping Responsive Proteins in Roots

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Hongxiang eGuo

2016-04-01

Full Text Available Tobacco plant has many responses to topping, such as the increase in ability of nicotine synthesis and secondary growth of roots. Some topping responsive miRNAs and genes had been identified in our previous work, but it is not enough to elaborate mechanism of tobacco response to topping. Here, topping responsive proteins were screened from tobacco roots with two-dimensional electrophoresis. Of these proteins, calretulin (CRT and Auxin-responsive protein IAA9 were related to the secondary growth of roots, LRR disease resistance, heat shock protein 70 and farnesyl pyrophosphate synthase 1（FPPS）were involved in wounding stress response, and F-box protein played an important role in promoting the ability of nicotine synthesis after topping. In addition, there were five tobacco bHLH proteins (NtbHLH, NtMYC1a, NtMYC1b, NtMYC2a and NtMYC2b related to nicotine synthesis. It was suggested that NtMYC2 might be the main positive transcription factor and NtbHLH protein is a negative regulator in the JA-mediating activation of nicotine synthesis after topping. Tobacco topping activates some comprehensive biology processes involving IAA and JA signaling pathway, and the identification of these proteins will be helpful to understand the process of topping response.

Automated multi-dimensional purification of tagged proteins.

Science.gov (United States)

Sigrell, Jill A; Eklund, Pär; Galin, Markus; Hedkvist, Lotta; Liljedahl, Pia; Johansson, Christine Markeland; Pless, Thomas; Torstenson, Karin

2003-01-01

The capacity for high throughput purification (HTP) is essential in fields such as structural genomics where large numbers of protein samples are routinely characterized in, for example, studies of structural determination, functionality and drug development. Proteins required for such analysis must be pure and homogenous and available in relatively large amounts. AKTA 3D system is a powerful automated protein purification system, which minimizes preparation, run-time and repetitive manual tasks. It has the capacity to purify up to 6 different His6- or GST-tagged proteins per day and can produce 1-50 mg protein per run at >90% purity. The success of automated protein purification increases with careful experimental planning. Protocol, columns and buffers need to be chosen with the final application area for the purified protein in mind.

Multidimensional Models of Information Need

OpenAIRE

Yun-jie (Calvin) Xu; Kai Huang (Joseph) Tan

2009-01-01

User studies in information science have recognised relevance as a multidimensional construct. An implication of multidimensional relevance is that a user's information need should be modeled by multiple data structures to represent different relevance dimensions. While the extant literature has attempted to model multiple dimensions of a user's information need, the fundamental assumption that a multidimensional model is better than a uni-dimensional model has not been addressed. This study ...

Targeted nanodiamonds for identification of subcellular protein assemblies in mammalian cells

Science.gov (United States)

Lake, Michael P.; Bouchard, Louis-S.

2017-01-01

Transmission electron microscopy (TEM) can be used to successfully determine the structures of proteins. However, such studies are typically done ex situ after extraction of the protein from the cellular environment. Here we describe an application for nanodiamonds as targeted intensity contrast labels in biological TEM, using the nuclear pore complex (NPC) as a model macroassembly. We demonstrate that delivery of antibody-conjugated nanodiamonds to live mammalian cells using maltotriose-conjugated polypropylenimine dendrimers results in efficient localization of nanodiamonds to the intended cellular target. We further identify signatures of nanodiamonds under TEM that allow for unambiguous identification of individual nanodiamonds from a resin-embedded, OsO4-stained environment. This is the first demonstration of nanodiamonds as labels for nanoscale TEM-based identification of subcellular protein assemblies. These results, combined with the unique fluorescence properties and biocompatibility of nanodiamonds, represent an important step toward the use of nanodiamonds as markers for correlated optical/electron bioimaging. PMID:28636640

Targeted nanodiamonds for identification of subcellular protein assemblies in mammalian cells.

Directory of Open Access Journals (Sweden)

Michael P Lake

Full Text Available Transmission electron microscopy (TEM can be used to successfully determine the structures of proteins. However, such studies are typically done ex situ after extraction of the protein from the cellular environment. Here we describe an application for nanodiamonds as targeted intensity contrast labels in biological TEM, using the nuclear pore complex (NPC as a model macroassembly. We demonstrate that delivery of antibody-conjugated nanodiamonds to live mammalian cells using maltotriose-conjugated polypropylenimine dendrimers results in efficient localization of nanodiamonds to the intended cellular target. We further identify signatures of nanodiamonds under TEM that allow for unambiguous identification of individual nanodiamonds from a resin-embedded, OsO4-stained environment. This is the first demonstration of nanodiamonds as labels for nanoscale TEM-based identification of subcellular protein assemblies. These results, combined with the unique fluorescence properties and biocompatibility of nanodiamonds, represent an important step toward the use of nanodiamonds as markers for correlated optical/electron bioimaging.

Targeted nanodiamonds for identification of subcellular protein assemblies in mammalian cells.

Science.gov (United States)

Lake, Michael P; Bouchard, Louis-S

2017-01-01

Transmission electron microscopy (TEM) can be used to successfully determine the structures of proteins. However, such studies are typically done ex situ after extraction of the protein from the cellular environment. Here we describe an application for nanodiamonds as targeted intensity contrast labels in biological TEM, using the nuclear pore complex (NPC) as a model macroassembly. We demonstrate that delivery of antibody-conjugated nanodiamonds to live mammalian cells using maltotriose-conjugated polypropylenimine dendrimers results in efficient localization of nanodiamonds to the intended cellular target. We further identify signatures of nanodiamonds under TEM that allow for unambiguous identification of individual nanodiamonds from a resin-embedded, OsO4-stained environment. This is the first demonstration of nanodiamonds as labels for nanoscale TEM-based identification of subcellular protein assemblies. These results, combined with the unique fluorescence properties and biocompatibility of nanodiamonds, represent an important step toward the use of nanodiamonds as markers for correlated optical/electron bioimaging.

Identification of proteins from tuberculin purified protein derivative (PPD) by LC-MS/MS.

Science.gov (United States)

Borsuk, Sibele; Newcombe, Jane; Mendum, Tom A; Dellagostin, Odir A; McFadden, Johnjoe

2009-11-01

The tuberculin purified protein derivative (PPD) is a widely used diagnostic antigen for tuberculosis, however it is poorly defined. Most mycobacterial proteins are extensively denatured by the procedure employed in its preparation, which explains previous difficulties in identifying constituents from PPD to characterize their behaviour in B- and T-cell reactions. We here described a proteomics-based characterization of PPD from several different sources by LC-MS/MS, which combines the solute separation power of HPLC, with the detection power of a mass spectrometer. The technique is able to identify proteins from complex mixtures of peptide fragments. A total of 171 different proteins were identified among the four PPD samples (two bovine PPD and two avium PPD) from Brazil and UK. The majority of the proteins were cytoplasmic (77.9%) and involved in intermediary metabolism and respiration (24.25%) but there was a preponderance of proteins involved in lipid metabolism. We identified a group of 21 proteins that are present in both bovine PPD but were not detected in avium PPD preparation. In addition, four proteins found in bovine PPD are absent in Mycobacterium bovis BCG vaccine strain. This study provides a better understanding of the tuberculin PPD components leading to the identification of additional antigens useful as reagents for specific diagnosis of tuberculosis.

Leptospiral outer membrane protein microarray, a novel approach to identification of host ligand-binding proteins.

Science.gov (United States)

Pinne, Marija; Matsunaga, James; Haake, David A

2012-11-01

Leptospirosis is a zoonosis with worldwide distribution caused by pathogenic spirochetes belonging to the genus Leptospira. The leptospiral life cycle involves transmission via freshwater and colonization of the renal tubules of their reservoir hosts. Infection requires adherence to cell surfaces and extracellular matrix components of host tissues. These host-pathogen interactions involve outer membrane proteins (OMPs) expressed on the bacterial surface. In this study, we developed an Leptospira interrogans serovar Copenhageni strain Fiocruz L1-130 OMP microarray containing all predicted lipoproteins and transmembrane OMPs. A total of 401 leptospiral genes or their fragments were transcribed and translated in vitro and printed on nitrocellulose-coated glass slides. We investigated the potential of this protein microarray to screen for interactions between leptospiral OMPs and fibronectin (Fn). This approach resulted in the identification of the recently described fibronectin-binding protein, LIC10258 (MFn8, Lsa66), and 14 novel Fn-binding proteins, denoted Microarray Fn-binding proteins (MFns). We confirmed Fn binding of purified recombinant LIC11612 (MFn1), LIC10714 (MFn2), LIC11051 (MFn6), LIC11436 (MFn7), LIC10258 (MFn8, Lsa66), and LIC10537 (MFn9) by far-Western blot assays. Moreover, we obtained specific antibodies to MFn1, MFn7, MFn8 (Lsa66), and MFn9 and demonstrated that MFn1, MFn7, and MFn9 are expressed and surface exposed under in vitro growth conditions. Further, we demonstrated that MFn1, MFn4 (LIC12631, Sph2), and MFn7 enable leptospires to bind fibronectin when expressed in the saprophyte, Leptospira biflexa. Protein microarrays are valuable tools for high-throughput identification of novel host ligand-binding proteins that have the potential to play key roles in the virulence mechanisms of pathogens.

Applied multidimensional systems theory

CERN Document Server

Bose, Nirmal K

2017-01-01

Revised and updated, this concise new edition of the pioneering book on multidimensional signal processing is ideal for a new generation of students. Multidimensional systems or m-D systems are the necessary mathematical background for modern digital image processing with applications in biomedicine, X-ray technology and satellite communications. Serving as a firm basis for graduate engineering students and researchers seeking applications in mathematical theories, this edition eschews detailed mathematical theory not useful to students. Presentation of the theory has been revised to make it more readable for students, and introduce some new topics that are emerging as multidimensional DSP topics in the interdisciplinary fields of image processing. New topics include Groebner bases, wavelets, and filter banks.

SQL and Multidimensional Data

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Mihaela MUNTEAN

2006-01-01

Full Text Available Using SQL you can manipulate multidimensional data and extract that data into a relational table. There are many PL/SQL packages that you can use directly in SQL*Plus or indirectly in Analytic Workspace Manager and OLAP Worksheet. In this article I discussed about some methods that you can use for manipulating and extracting multidimensional data.

Identification of hierarchy of dynamic domains in proteins: comparison of HDWA and HCCP techniques

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Yesylevskyy S. O.

2010-07-01

Full Text Available Aim. There are several techniques for the identification of hierarchy of dynamic domains in proteins. The goal of this work is to compare systematically two recently developed techniques, HCCP and HDWA,on a set of proteins from diverse structural classes. Methods. HDWA and HCCP techniques are used. The HDWA technique is designed to identify hierarchically organized dynamic domains in proteins using the Molecular Dynamics (MD trajectories, while HCCP utilizes the normal modes of simplified elastic network models. Results. It is shown that the dynamic domains found by HDWA are consistent with the domains identified by HCCP and other techniques. At the same time HDWA identifies flexible mobile loops of proteins correctly, which is hard to achieve with other model-based domain identification techniques. Conclusion. HDWA is shown to be a powerful method of analysis of MD trajectories, which can be used in various areas of protein science.

Identification of proteins in the postsynaptic density fraction by mass spectrometry

DEFF Research Database (Denmark)

Walikonis, R S; Jensen, Ole Nørregaard; Mann, M

2000-01-01

Our understanding of the organization of postsynaptic signaling systems at excitatory synapses has been aided by the identification of proteins in the postsynaptic density (PSD) fraction, a subcellular fraction enriched in structures with the morphology of PSDs. In this study, we have completed...... not previously known to be constituents of the PSD fraction and 24 that had previously been associated with the PSD by other methods. The newly identified proteins include the heavy chain of myosin-Va (dilute myosin), a motor protein thought to be involved in vesicle trafficking, and the mammalian homolog...

Discovering functional interdependence relationship in PPI networks for protein complex identification.

Science.gov (United States)

Lam, Winnie W M; Chan, Keith C C

2012-04-01

Protein molecules interact with each other in protein complexes to perform many vital functions, and different computational techniques have been developed to identify protein complexes in protein-protein interaction (PPI) networks. These techniques are developed to search for subgraphs of high connectivity in PPI networks under the assumption that the proteins in a protein complex are highly interconnected. While these techniques have been shown to be quite effective, it is also possible that the matching rate between the protein complexes they discover and those that are previously determined experimentally be relatively low and the "false-alarm" rate can be relatively high. This is especially the case when the assumption of proteins in protein complexes being more highly interconnected be relatively invalid. To increase the matching rate and reduce the false-alarm rate, we have developed a technique that can work effectively without having to make this assumption. The name of the technique called protein complex identification by discovering functional interdependence (PCIFI) searches for protein complexes in PPI networks by taking into consideration both the functional interdependence relationship between protein molecules and the network topology of the network. The PCIFI works in several steps. The first step is to construct a multiple-function protein network graph by labeling each vertex with one or more of the molecular functions it performs. The second step is to filter out protein interactions between protein pairs that are not functionally interdependent of each other in the statistical sense. The third step is to make use of an information-theoretic measure to determine the strength of the functional interdependence between all remaining interacting protein pairs. Finally, the last step is to try to form protein complexes based on the measure of the strength of functional interdependence and the connectivity between proteins. For performance evaluation

Multidimensional Databases and Data Warehousing

CERN Document Server

Jensen, Christian

2010-01-01

The present book's subject is multidimensional data models and data modeling concepts as they are applied in real data warehouses. The book aims to present the most important concepts within this subject in a precise and understandable manner. The book's coverage of fundamental concepts includes data cubes and their elements, such as dimensions, facts, and measures and their representation in a relational setting; it includes architecture-related concepts; and it includes the querying of multidimensional databases.The book also covers advanced multidimensional concepts that are considered to b

The necessity-concerns framework: a multidimensional theory benefits from multidimensional analysis.

Science.gov (United States)

Phillips, L Alison; Diefenbach, Michael A; Kronish, Ian M; Negron, Rennie M; Horowitz, Carol R

2014-08-01

Patients' medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). We use polynomial regression to assess the multidimensional effect of stroke-event survivors' medication-related concerns and necessity beliefs on their adherence to stroke-prevention medication. Survivors (n = 600) rated their concerns, necessity beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. As posited by the necessity-concerns framework (NCF), the greatest and lowest adherence was reported by those necessity weak concerns and strong concerns/weak Necessity-Beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites.

Exploring and linking biomedical resources through multidimensional semantic spaces.

Science.gov (United States)

Berlanga, Rafael; Jiménez-Ruiz, Ernesto; Nebot, Victoria

2012-01-25

The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for

Identification of surface proteins in Enterococcus faecalis V583

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Eijsink Vincent GH

2011-03-01

Full Text Available Abstract Background Surface proteins are a key to a deeper understanding of the behaviour of Gram-positive bacteria interacting with the human gastro-intestinal tract. Such proteins contribute to cell wall synthesis and maintenance and are important for interactions between the bacterial cell and the human host. Since they are exposed and may play roles in pathogenicity, surface proteins are interesting targets for drug design. Results Using methods based on proteolytic "shaving" of bacterial cells and subsequent mass spectrometry-based protein identification, we have identified surface-located proteins in Enterococcus faecalis V583. In total 69 unique proteins were identified, few of which have been identified and characterized previously. 33 of these proteins are predicted to be cytoplasmic, whereas the other 36 are predicted to have surface locations (31 or to be secreted (5. Lipid-anchored proteins were the most dominant among the identified surface proteins. The seemingly most abundant surface proteins included a membrane protein with a potentially shedded extracellular sulfatase domain that could act on the sulfate groups in mucin and a lipid-anchored fumarate reductase that could contribute to generation of reactive oxygen species. Conclusions The present proteome analysis gives an experimental impression of the protein landscape on the cell surface of the pathogenic bacterium E. faecalis. The 36 identified secreted (5 and surface (31 proteins included several proteins involved in cell wall synthesis, pheromone-regulated processes, and transport of solutes, as well as proteins with unknown function. These proteins stand out as interesting targets for further investigation of the interaction between E. faecalis and its environment.

Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry

DEFF Research Database (Denmark)

Ho, Yuen; Gruhler, Albrecht; Heilbut, Adrian

2002-01-01

The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function. To date, generation of large-scale protein-protein interaction maps has relied on the yeast two-hybrid system, which detects...... as a test case, an example of this approach, which we term high-throughput mass spectrometric protein complex identification (HMS-PCI). Beginning with 10% of predicted yeast proteins as baits, we detected 3,617 associated proteins covering 25% of the yeast proteome. Numerous protein complexes were...... identified, including many new interactions in various signalling pathways and in the DNA damage response. Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two...

Identification of novel direct protein-protein interactions by irradiating living cells with femtosecond UV laser pulses.

Science.gov (United States)

Itri, Francesco; Monti, Daria Maria; Chino, Marco; Vinciguerra, Roberto; Altucci, Carlo; Lombardi, Angela; Piccoli, Renata; Birolo, Leila; Arciello, Angela

2017-10-07

The identification of protein-protein interaction networks in living cells is becoming increasingly fundamental to elucidate main biological processes and to understand disease molecular bases on a system-wide level. We recently described a method (LUCK, Laser UV Cross-linKing) to cross-link interacting protein surfaces in living cells by UV laser irradiation. By using this innovative methodology, that does not require any protein modification or cell engineering, here we demonstrate that, upon UV laser irradiation of HeLa cells, a direct interaction between GAPDH and alpha-enolase was "frozen" by a cross-linking event. We validated the occurrence of this direct interaction by co-immunoprecipitation and Immuno-FRET analyses. This represents a proof of principle of the LUCK capability to reveal direct protein interactions in their physiological environment. Copyright © 2017 Elsevier Inc. All rights reserved.

AFM-based identification of the dynamic properties of globular proteins: simulation study

International Nuclear Information System (INIS)

Kim, Deok Ho; Park, Jung Yul; Kim, Moon K.; Hong, Keum Shik

2008-01-01

Nowadays a mathematical model-based computational approach is getting more attention as an effective tool for understanding the mechanical behaviors of biological systems. To find the mechanical properties of the proteins required to build such a model, this paper investigates a real-time identification method based on an AFM nanomanipulation system. First, an AFM-based bio-characterization system is introduced. Second, a second-order time-varying linear model representing the interaction between an AFM cantilever and globular proteins in a solvent is presented. Finally, we address a real-time estimation method in which the results of AFM experiments are designed to be inputs of the state estimator proposed here. Our attention is restricted to a theoretical feasibility analysis of the proposed methodology. We simply set the mechanical properties of the particular protein such as mass, stiffness, and damping coefficient in the system model prior to running the simulation. Simulation results show very good agreement with the preset properties. We anticipate that the realization of the AFM-based bio-characterization system will also provide an experimental validation of the proposed identification procedure in the future. This methodology can be used to determine a model of protein motion for the purpose of computer simulation and for a real-time modification of protein deformation

Multi-dimensional imaging

CERN Document Server

Javidi, Bahram; Andres, Pedro

2014-01-01

Provides a broad overview of advanced multidimensional imaging systems with contributions from leading researchers in the field Multi-dimensional Imaging takes the reader from the introductory concepts through to the latest applications of these techniques. Split into 3 parts covering 3D image capture, processing, visualization and display, using 1) a Multi-View Approach and 2.) a Holographic Approach, followed by a 3rd part addressing other 3D systems approaches, applications and signal processing for advanced 3D imaging. This book describes recent developments, as well as the prospects and

Mass spectrometry based approach for identification and characterisation of fluorescent proteins from marine organisms

DEFF Research Database (Denmark)

Wojdyla, Katarzyna Iwona; Rogowska-Wrzesinska, Adelina; Wrzesinski, Krzysztof

2011-01-01

We present here a new analytical strategy for identification and characterisation of fluorescent proteins from marine organisms. By applying basic proteomics tools it is possible to screen large sample collections for fluorescent proteins of desired characteristics prior to gene cloning. Our...

Enhancing Membrane Protein Identification Using a Simplified Centrifugation and Detergent-Based Membrane Extraction Approach.

Science.gov (United States)

Zhou, Yanting; Gao, Jing; Zhu, Hongwen; Xu, Jingjing; He, Han; Gu, Lei; Wang, Hui; Chen, Jie; Ma, Danjun; Zhou, Hu; Zheng, Jing

2018-02-20

Membrane proteins may act as transporters, receptors, enzymes, and adhesion-anchors, accounting for nearly 70% of pharmaceutical drug targets. Difficulties in efficient enrichment, extraction, and solubilization still exist because of their relatively low abundance and poor solubility. A simplified membrane protein extraction approach with advantages of user-friendly sample processing procedures, good repeatability and significant effectiveness was developed in the current research for enhancing enrichment and identification of membrane proteins. This approach combining centrifugation and detergent along with LC-MS/MS successfully identified higher proportion of membrane proteins, integral proteins and transmembrane proteins in membrane fraction (76.6%, 48.1%, and 40.6%) than in total cell lysate (41.6%, 16.4%, and 13.5%), respectively. Moreover, our method tended to capture membrane proteins with high degree of hydrophobicity and number of transmembrane domains as 486 out of 2106 (23.0%) had GRAVY > 0 in membrane fraction, 488 out of 2106 (23.1%) had TMs ≥ 2. It also provided for improved identification of membrane proteins as more than 60.6% of the commonly identified membrane proteins in two cell samples were better identified in membrane fraction with higher sequence coverage. Data are available via ProteomeXchange with identifier PXD008456.

Proteome scale identification, classification and structural analysis of iron-binding proteins in bread wheat.

Science.gov (United States)

Verma, Shailender Kumar; Sharma, Ankita; Sandhu, Padmani; Choudhary, Neha; Sharma, Shailaja; Acharya, Vishal; Akhter, Yusuf

2017-05-01

Bread wheat is one of the major staple foods of worldwide population and iron plays a significant role in growth and development of the plant. In this report, we are presenting the genome wide identification of iron-binding proteins in bread wheat. The wheat genome derived putative proteome was screened for identification of iron-binding sequence motifs. Out of 602 putative iron-binding proteins, 130 were able to produce reliable structural models by homology techniques and further analyzed for the presence of iron-binding structural motifs. The computationally identified proteins appear to bind to ferrous and ferric ions and showed diverse coordination geometries. Glu, His, Asp and Cys amino acid residues were found to be mostly involved in iron binding. We have classified these proteins on the basis of their localization in the different cellular compartments. The identified proteins were further classified into their protein folds, families and functional classes ranging from structure maintenance of cellular components, regulation of gene expression, post translational modification, membrane proteins, enzymes, signaling and storage proteins. This comprehensive report regarding structural iron binding proteome provides useful insights into the diversity of iron binding proteins of wheat plants and further utilized to study their roles in plant growth, development and physiology. Copyright © 2017 Elsevier Inc. All rights reserved.

Semi-blind identification of wideband MIMO channels via stochastic sampling

OpenAIRE

Andrieu, Christophe; Piechocki, Robert J.; McGeehan, Joe P.; Armour, Simon M.

2003-01-01

In this paper we address the problem of wide-band multiple-input multiple-output (MIMO) channel (multidimensional time invariant FIR filter) identification using Markov chains Monte Carlo methods. Towards this end we develop a novel stochastic sampling technique that produces a sequence of multidimensional channel samples. The method is semi-blind in the sense that it uses a very short training sequence. In such a framework the problem is no longer analytically tractable; hence we resort to s...

Discovering Multidimensional Structure in Relational Data

DEFF Research Database (Denmark)

Jensen, Mikael Rune; Holmgren, Thomas; Pedersen, Torben Bach

2004-01-01

On-Line Analytical Processing (OLAP) systems based on multidimensional databases are essential elements of decision support. However, most existing data is stored in “ordinary” relational OLTP databases, i.e., data has to be (re-) modeled as multidimensional cubes before the advantages of OLAP to...... algorithms for discovering multidimensional schemas from relational databases. The algorithms take a wide range of available metadata into account in the discovery process, including functional and inclusion dependencies, and key and cardinality information....... tools are available. In this paper we present an approach for the automatic construction of multidimensional OLAP database schemas from existing relational OLTP databases, enabling easy OLAP design and analysis for most existing data sources. This is achieved through a set of practical and effective...

The Necessity-Concerns-Framework: A Multidimensional Theory Benefits from Multidimensional Analysis

Science.gov (United States)

Phillips, L. Alison; Diefenbach, Michael; Kronish, Ian M.; Negron, Rennie M.; Horowitz, Carol R.

2014-01-01

Background Patients’ medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). Purpose We use polynomial regression to assess the multidimensional effect of stroke-event survivors’ medication-related concerns and necessity-beliefs on their adherence to stroke-prevention medication. Methods Survivors (n=600) rated their concerns, necessity-beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. Results As posited by the Necessity-Concerns Framework (NCF), the greatest and lowest adherence was reported by those with strong necessity-beliefs/weak concerns and strong concerns/weak necessity-beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Conclusions Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites. PMID:24500078

Identification of Inhibitors of Biological Interactions Involving Intrinsically Disordered Proteins

Directory of Open Access Journals (Sweden)

Daniela Marasco

2015-04-01

Full Text Available Protein–protein interactions involving disordered partners have unique features and represent prominent targets in drug discovery processes. Intrinsically Disordered Proteins (IDPs are involved in cellular regulation, signaling and control: they bind to multiple partners and these high-specificity/low-affinity interactions play crucial roles in many human diseases. Disordered regions, terminal tails and flexible linkers are particularly abundant in DNA-binding proteins and play crucial roles in the affinity and specificity of DNA recognizing processes. Protein complexes involving IDPs are short-lived and typically involve short amino acid stretches bearing few “hot spots”, thus the identification of molecules able to modulate them can produce important lead compounds: in this scenario peptides and/or peptidomimetics, deriving from structure-based, combinatorial or protein dissection approaches, can play a key role as hit compounds. Here, we propose a panoramic review of the structural features of IDPs and how they regulate molecular recognition mechanisms focusing attention on recently reported drug-design strategies in the field of IDPs.

Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

Directory of Open Access Journals (Sweden)

Kevin R Ramkissoon

Full Text Available The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.

Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

Science.gov (United States)

Ojha, Sunil; Watson, Douglas S.; Bomar, Martha G.; Galande, Amit K.; Shearer, Alexander G.

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation. PMID:24386392

Adherence is a multi-dimensional construct in the POUNDS LOST trial

Science.gov (United States)

Williamson, Donald A.; Anton, Stephen D.; Han, Hongmei; Champagne, Catherine M.; Allen, Ray; LeBlanc, Eric; Ryan, Donna H.; McManus, Katherine; Laranjo, Nancy; Carey, Vincent J.; Loria, Catherine M.; Bray, George A.; Sacks, Frank M.

2011-01-01

Research on the conceptualization of adherence to treatment has not addressed a key question: Is adherence best defined as being a uni-dimensional or multi-dimensional behavioral construct? The primary aim of this study was to test which of these conceptual models best described adherence to a weight management program. This ancillary study was conducted as a part of the POUNDS LOST trial that tested the efficacy of four dietary macro-nutrient compositions for promoting weight loss. A sample of 811 overweight/obese adults was recruited across two clinical sites, and each participant was randomly assigned to one of four macronutrient prescriptions: (1) Low fat (20% of energy), average protein (15% of energy); (2) High fat (40%), average protein (15%); (3) Low fat (20%), high protein (25%); (4) High fat (40%), high protein (25%). Throughout the first 6 months of the study, a computer tracking system collected data on eight indicators of adherence. Computer tracking data from the initial 6 months of the intervention were analyzed using exploratory and confirmatory analyses. Two factors (accounting for 66% of the variance) were identified and confirmed: (1) behavioral adherence and (2) dietary adherence. Behavioral adherence did not differ across the four interventions, but prescription of a high fat diet (vs. a low fat diet) was found to be associated with higher levels of dietary adherence. The findings of this study indicated that adherence to a weight management program was best conceptualized as being multi-dimensional, with two dimensions: behavioral and dietary adherence. PMID:19856202

Identification of antigenic proteins of setaria cervi by immunoblotting technique

International Nuclear Information System (INIS)

Kaushal, N.A.; Kaushal, D.C.; Ghatak, S.

1987-01-01

Identification and characterization of antigenic proteins of Setaria cervi (bovine filarial parasite) adults and microfilariae was done by immunoblotting technique using hyperimmune rabbit sera against S. cervi and Brugia malayi. The antigens recognized by these sera were detected by using 125 I protein-A followed by autoradiography. Fifteen different antigens were observed to be common between adult and microfilarial stages of the parasite. Some stage specific antigens were also identified. Many antigens of S. cervi adults and microfilariae were also recognized by rabbit anti-B.malayi serum showing the existence of common antigenic determinants between the bovine and human filarial parasites

Identification of Novel Immunogenic Proteins of Neisseria gonorrhoeae by Phage Display.

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Daniel O Connor

Full Text Available Neisseria gonorrhoeae is one of the most prevalent sexually transmitted diseases worldwide with more than 100 million new infections per year. A lack of intense research over the last decades and increasing resistances to the recommended antibiotics call for a better understanding of gonococcal infection, fast diagnostics and therapeutic measures against N. gonorrhoeae. Therefore, the aim of this work was to identify novel immunogenic proteins as a first step to advance those unresolved problems. For the identification of immunogenic proteins, pHORF oligopeptide phage display libraries of the entire N. gonorrhoeae genome were constructed. Several immunogenic oligopeptides were identified using polyclonal rabbit antibodies against N. gonorrhoeae. Corresponding full-length proteins of the identified oligopeptides were expressed and their immunogenic character was verified by ELISA. The immunogenic character of six proteins was identified for the first time. Additional 13 proteins were verified as immunogenic proteins in N. gonorrhoeae.

Processed Meat Protein and Heat-Stable Peptide Marker Identification Using Microwave-Assisted Tryptic Digestion

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Magdalena Montowska

2016-01-01

Full Text Available New approaches to rapid examination of proteins and peptides in complex food matrices are of great interest to the community of food scientists. The aim of the study is to examine the influence of microwave irradiation on the acceleration of enzymatic cleavage and enzymatic digestion of denatured proteins in cooked meat of five species (cattle, horse, pig, chicken and turkey and processed meat products (coarsely minced, smoked, cooked and semi-dried sausages. Severe protein aggregation occurred not only in heated meat under harsh treatment at 190 °C but also in processed meat products. All the protein aggregates were thoroughly hydrolyzed aft er 1 h of trypsin treatment with short exposure times of 40 and 20 s to microwave irradiation at 138 and 303 W. There were much more missed cleavage sites observed in all microwave-assisted digestions. Despite the incompleteness of microwave-assisted digestion, six unique peptide markers were detected, which allowed unambiguous identification of processed meat derived from the examined species. Although the microwave-assisted tryptic digestion can serve as a tool for rapid and high-throughput protein identification, great caution and pre-evaluation of individual samples is recommended in protein quantitation.

Multidimensional singular integrals and integral equations

CERN Document Server

Mikhlin, Solomon Grigorievich; Stark, M; Ulam, S

1965-01-01

Multidimensional Singular Integrals and Integral Equations presents the results of the theory of multidimensional singular integrals and of equations containing such integrals. Emphasis is on singular integrals taken over Euclidean space or in the closed manifold of Liapounov and equations containing such integrals. This volume is comprised of eight chapters and begins with an overview of some theorems on linear equations in Banach spaces, followed by a discussion on the simplest properties of multidimensional singular integrals. Subsequent chapters deal with compounding of singular integrals

Combining metal oxide affinity chromatography (MOAC and selective mass spectrometry for robust identification of in vivo protein phosphorylation sites

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Weckwerth Wolfram

2005-11-01

Full Text Available Abstract Background Protein phosphorylation is accepted as a major regulatory pathway in plants. More than 1000 protein kinases are predicted in the Arabidopsis proteome, however, only a few studies look systematically for in vivo protein phosphorylation sites. Owing to the low stoichiometry and low abundance of phosphorylated proteins, phosphorylation site identification using mass spectrometry imposes difficulties. Moreover, the often observed poor quality of mass spectra derived from phosphopeptides results frequently in uncertain database hits. Thus, several lines of evidence have to be combined for a precise phosphorylation site identification strategy. Results Here, a strategy is presented that combines enrichment of phosphoproteins using a technique termed metaloxide affinity chromatography (MOAC and selective ion trap mass spectrometry. The complete approach involves (i enrichment of proteins with low phosphorylation stoichiometry out of complex mixtures using MOAC, (ii gel separation and detection of phosphorylation using specific fluorescence staining (confirmation of enrichment, (iii identification of phosphoprotein candidates out of the SDS-PAGE using liquid chromatography coupled to mass spectrometry, and (iv identification of phosphorylation sites of these enriched proteins using automatic detection of H3PO4 neutral loss peaks and data-dependent MS3-fragmentation of the corresponding MS2-fragment. The utility of this approach is demonstrated by the identification of phosphorylation sites in Arabidopsis thaliana seed proteins. Regulatory importance of the identified sites is indicated by conservation of the detected sites in gene families such as ribosomal proteins and sterol dehydrogenases. To demonstrate further the wide applicability of MOAC, phosphoproteins were enriched from Chlamydomonas reinhardtii cell cultures. Conclusion A novel phosphoprotein enrichment procedure MOAC was applied to seed proteins of A. thaliana and to

Multidimensional and multiscalar analisis of territorial rural development in Brazil

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Sergio Schneider

2013-09-01

Full Text Available Of late, there have been several political, practical and analytical changes to our understanding of rural development. Diverse efforts have emerged in the analysis and discussion of spatial dynamics such as “rurality”, territories, in the construction of a territorial perspective of rural development. These changes in the forms of identification and measurement of rural development lead us to question the validity and effectiveness of applied methods, inviting us to establish methodologies and analytical criteria coherent with the multiple manifestations and scales of development. This article offers a multidimensional and multi-scalar analytical model for territorial rural development, using our methodology tested in four rural territories of Brazil.

Identification Of Protein Vaccine Candidates Using Comprehensive Proteomic Analysis Strategies

Science.gov (United States)

2007-12-01

that fascinating fungus known as Coccidioides. I also want to thank the UA Mass Spectrometry Facility and the UA Proteomics Consortium, especially...W. & N. N. Kav. 2006. The proteome of the phytopathogenic fungus Sclerotinia sclerotiorum. Proteomics 6: 5995-6007. 127. de Godoy, L. M., J. V...IDENTIFICATION OF PROTEIN VACCINE CANDIDATES USING COMPREHENSIVE PROTEOMIC ANALYSIS STRATEGIES by James G. Rohrbough

Identification of Phosphorylated Proteins on a Global Scale.

Science.gov (United States)

Iliuk, Anton

2018-05-31

Liquid chromatography (LC) coupled with tandem mass spectrometry (MS/MS) has enabled researchers to analyze complex biological samples with unprecedented depth. It facilitates the identification and quantification of modifications within thousands of proteins in a single large-scale proteomic experiment. Analysis of phosphorylation, one of the most common and important post-translational modifications, has particularly benefited from such progress in the field. Here, detailed protocols are provided for a few well-regarded, common sample preparation methods for an effective phosphoproteomic experiment. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Working with Proteins in silico: A Review of Online Available Tools for Basic Identification of Proteins

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Caner Yavuz

2017-01-01

Full Text Available Increase in online available bioinformatics tools for protein research creates an important opportunity for scientists to reveal characteristics of the protein of interest by only starting from the predicted or known amino acid sequence without fully depending on experimental approaches. There are many sophisticated tools used for diverse purposes; however, there are not enough reviews covering the tips and tricks in selecting and using the correct tools as the literature mainly state the promotion of the new ones. In this review, with the aim of providing young scientists with no specific experience on protein work a reliable starting point for in silico analysis of the protein of interest, we summarized tools for annotation, identification of motifs and domains, determination isoelectric point, molecular weight, subcellular localization, and post-translational modifications by focusing on the important points to be considered while selecting from online available tools.

Multidimensional Riemann problem with self-similar internal structure - part III - a multidimensional analogue of the HLLI Riemann solver for conservative hyperbolic systems

Science.gov (United States)

Balsara, Dinshaw S.; Nkonga, Boniface

2017-10-01

Just as the quality of a one-dimensional approximate Riemann solver is improved by the inclusion of internal sub-structure, the quality of a multidimensional Riemann solver is also similarly improved. Such multidimensional Riemann problems arise when multiple states come together at the vertex of a mesh. The interaction of the resulting one-dimensional Riemann problems gives rise to a strongly-interacting state. We wish to endow this strongly-interacting state with physically-motivated sub-structure. The fastest way of endowing such sub-structure consists of making a multidimensional extension of the HLLI Riemann solver for hyperbolic conservation laws. Presenting such a multidimensional analogue of the HLLI Riemann solver with linear sub-structure for use on structured meshes is the goal of this work. The multidimensional MuSIC Riemann solver documented here is universal in the sense that it can be applied to any hyperbolic conservation law. The multidimensional Riemann solver is made to be consistent with constraints that emerge naturally from the Galerkin projection of the self-similar states within the wave model. When the full eigenstructure in both directions is used in the present Riemann solver, it becomes a complete Riemann solver in a multidimensional sense. I.e., all the intermediate waves are represented in the multidimensional wave model. The work also presents, for the very first time, an important analysis of the dissipation characteristics of multidimensional Riemann solvers. The present Riemann solver results in the most efficient implementation of a multidimensional Riemann solver with sub-structure. Because it preserves stationary linearly degenerate waves, it might also help with well-balancing. Implementation-related details are presented in pointwise fashion for the one-dimensional HLLI Riemann solver as well as the multidimensional MuSIC Riemann solver.

Multidimensional Data Model and Query Language for Informetrics.

Science.gov (United States)

Niemi, Timo; Hirvonen, Lasse; Jarvelin, Kalervo

2003-01-01

Discusses multidimensional data analysis, or online analytical processing (OLAP), which offer a single subject-oriented source for analyzing summary data based on various dimensions. Develops a conceptual/logical multidimensional model for supporting the needs of informetrics, including a multidimensional query language whose basic idea is to…

Identification and characterization of N-glycosylated proteins using proteomics

DEFF Research Database (Denmark)

Selby, David S; Larsen, Martin R; Calvano, Cosima Damiana

2008-01-01

and analysis of glycoproteins and glycopeptides. Combinations of affinity-enrichment techniques, chemical and biochemical protocols, and advanced mass spectrometry facilitate detailed glycoprotein analysis in proteomics, from fundamental biological studies to biomarker discovery in biomedicine....... is a complex task and is currently achieved by mass spectrometry-based methods that enable identification of glycoproteins and localization, classification, and analysis of individual glycan structures on proteins. In this chapter we briefly introduce a range of analytical technologies for recovery...

Peak picking multidimensional NMR spectra with the contour geometry based algorithm CYPICK

International Nuclear Information System (INIS)

Würz, Julia M.; Güntert, Peter

2017-01-01

The automated identification of signals in multidimensional NMR spectra is a challenging task, complicated by signal overlap, noise, and spectral artifacts, for which no universally accepted method is available. Here, we present a new peak picking algorithm, CYPICK, that follows, as far as possible, the manual approach taken by a spectroscopist who analyzes peak patterns in contour plots of the spectrum, but is fully automated. Human visual inspection is replaced by the evaluation of geometric criteria applied to contour lines, such as local extremality, approximate circularity (after appropriate scaling of the spectrum axes), and convexity. The performance of CYPICK was evaluated for a variety of spectra from different proteins by systematic comparison with peak lists obtained by other, manual or automated, peak picking methods, as well as by analyzing the results of automated chemical shift assignment and structure calculation based on input peak lists from CYPICK. The results show that CYPICK yielded peak lists that compare in most cases favorably to those obtained by other automated peak pickers with respect to the criteria of finding a maximal number of real signals, a minimal number of artifact peaks, and maximal correctness of the chemical shift assignments and the three-dimensional structure obtained by fully automated assignment and structure calculation.

Peak picking multidimensional NMR spectra with the contour geometry based algorithm CYPICK

Energy Technology Data Exchange (ETDEWEB)

Würz, Julia M.; Güntert, Peter, E-mail: guentert@em.uni-frankfurt.de [Goethe University Frankfurt am Main, Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance (Germany)

2017-01-15

The automated identification of signals in multidimensional NMR spectra is a challenging task, complicated by signal overlap, noise, and spectral artifacts, for which no universally accepted method is available. Here, we present a new peak picking algorithm, CYPICK, that follows, as far as possible, the manual approach taken by a spectroscopist who analyzes peak patterns in contour plots of the spectrum, but is fully automated. Human visual inspection is replaced by the evaluation of geometric criteria applied to contour lines, such as local extremality, approximate circularity (after appropriate scaling of the spectrum axes), and convexity. The performance of CYPICK was evaluated for a variety of spectra from different proteins by systematic comparison with peak lists obtained by other, manual or automated, peak picking methods, as well as by analyzing the results of automated chemical shift assignment and structure calculation based on input peak lists from CYPICK. The results show that CYPICK yielded peak lists that compare in most cases favorably to those obtained by other automated peak pickers with respect to the criteria of finding a maximal number of real signals, a minimal number of artifact peaks, and maximal correctness of the chemical shift assignments and the three-dimensional structure obtained by fully automated assignment and structure calculation.

Joint mapping of genes and conditions via multidimensional unfolding analysis

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Engelen Kristof

2007-06-01

Full Text Available Abstract Background Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding. Results We present a novel algorithm for multidimensional unfolding that overcomes both general problems and problems that are specific for the analysis of gene expression data sets. Applying the algorithm to two publicly available microarray compendia illustrates its power as a tool for exploratory data analysis: The unfolding analysis of a first data set resulted in a two-dimensional representation which clearly reveals temporal regulation patterns for the genes and a meaningful structure for the time points, while the analysis of a second data set showed the algorithm's ability to go beyond a mere identification of those genes that discriminate between different patient or tissue types. Conclusion Multidimensional unfolding offers a useful tool for preliminary explorations of microarray data: By relying on an easy-to-grasp low-dimensional geometric framework, relations among genes, among conditions and between genes and conditions are simultaneously represented in an accessible way which may reveal interesting patterns in the data. An additional advantage of the method is that it can be applied to the raw data without necessitating the choice of suitable genewise transformations of the data.

A Robust Identification of the Protein Standard Bands in Two-Dimensional Electrophoresis Gel Images

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Serackis Artūras

2017-12-01

Full Text Available The aim of the investigation presented in this paper was to develop a software-based assistant for the protein analysis workflow. The prior characterization of the unknown protein in two-dimensional electrophoresis gel images is performed according to the molecular weight and isoelectric point of each protein spot estimated from the gel image before further sequence analysis by mass spectrometry. The paper presents a method for automatic and robust identification of the protein standard band in a two-dimensional gel image. In addition, the method introduces the identification of the positions of the markers, prepared by using pre-selected proteins with known molecular mass. The robustness of the method was achieved by using special validation rules in the proposed original algorithms. In addition, a self-organizing map-based decision support algorithm is proposed, which takes Gabor coefficients as image features and searches for the differences in preselected vertical image bars. The experimental investigation proved the good performance of the new algorithms included into the proposed method. The detection of the protein standard markers works without modification of algorithm parameters on two-dimensional gel images obtained by using different staining and destaining procedures, which results in different average levels of intensity in the images.

Using context to improve protein domain identification

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Llinás Manuel

2011-03-01

Full Text Available Abstract Background Identifying domains in protein sequences is an important step in protein structural and functional annotation. Existing domain recognition methods typically evaluate each domain prediction independently of the rest. However, the majority of proteins are multidomain, and pairwise domain co-occurrences are highly specific and non-transitive. Results Here, we demonstrate how to exploit domain co-occurrence to boost weak domain predictions that appear in previously observed combinations, while penalizing higher confidence domains if such combinations have never been observed. Our framework, Domain Prediction Using Context (dPUC, incorporates pairwise "context" scores between domains, along with traditional domain scores and thresholds, and improves domain prediction across a variety of organisms from bacteria to protozoa and metazoa. Among the genomes we tested, dPUC is most successful at improving predictions for the poorly-annotated malaria parasite Plasmodium falciparum, for which over 38% of the genome is currently unannotated. Our approach enables high-confidence annotations in this organism and the identification of orthologs to many core machinery proteins conserved in all eukaryotes, including those involved in ribosomal assembly and other RNA processing events, which surprisingly had not been previously known. Conclusions Overall, our results demonstrate that this new context-based approach will provide significant improvements in domain and function prediction, especially for poorly understood genomes for which the need for additional annotations is greatest. Source code for the algorithm is available under a GPL open source license at http://compbio.cs.princeton.edu/dpuc/. Pre-computed results for our test organisms and a web server are also available at that location.

Multi-Dimensional Path Queries

DEFF Research Database (Denmark)

Bækgaard, Lars

1998-01-01

to create nested path structures. We present an SQL-like query language that is based on path expressions and we show how to use it to express multi-dimensional path queries that are suited for advanced data analysis in decision support environments like data warehousing environments......We present the path-relationship model that supports multi-dimensional data modeling and querying. A path-relationship database is composed of sets of paths and sets of relationships. A path is a sequence of related elements (atoms, paths, and sets of paths). A relationship is a binary path...

enDNA-Prot: Identification of DNA-Binding Proteins by Applying Ensemble Learning

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Ruifeng Xu

2014-01-01

Full Text Available DNA-binding proteins are crucial for various cellular processes, such as recognition of specific nucleotide, regulation of transcription, and regulation of gene expression. Developing an effective model for identifying DNA-binding proteins is an urgent research problem. Up to now, many methods have been proposed, but most of them focus on only one classifier and cannot make full use of the large number of negative samples to improve predicting performance. This study proposed a predictor called enDNA-Prot for DNA-binding protein identification by employing the ensemble learning technique. Experiential results showed that enDNA-Prot was comparable with DNA-Prot and outperformed DNAbinder and iDNA-Prot with performance improvement in the range of 3.97–9.52% in ACC and 0.08–0.19 in MCC. Furthermore, when the benchmark dataset was expanded with negative samples, the performance of enDNA-Prot outperformed the three existing methods by 2.83–16.63% in terms of ACC and 0.02–0.16 in terms of MCC. It indicated that enDNA-Prot is an effective method for DNA-binding protein identification and expanding training dataset with negative samples can improve its performance. For the convenience of the vast majority of experimental scientists, we developed a user-friendly web-server for enDNA-Prot which is freely accessible to the public.

CAMS: OLAPing Multidimensional Data Streams Efficiently

Science.gov (United States)

Cuzzocrea, Alfredo

In the context of data stream research, taming the multidimensionality of real-life data streams in order to efficiently support OLAP analysis/mining tasks is a critical challenge. Inspired by this fundamental motivation, in this paper we introduce CAMS (C ube-based A cquisition model for M ultidimensional S treams), a model for efficiently OLAPing multidimensional data streams. CAMS combines a set of data stream processing methodologies, namely (i) the OLAP dimension flattening process, which allows us to obtain dimensionality reduction of multidimensional data streams, and (ii) the OLAP stream aggregation scheme, which aggregates data stream readings according to an OLAP-hierarchy-based membership approach. We complete our analytical contribution by means of experimental assessment and analysis of both the efficiency and the scalability of OLAPing capabilities of CAMS on synthetic multidimensional data streams. Both analytical and experimental results clearly connote CAMS as an enabling component for next-generation Data Stream Management Systems.

Large deviations and queueing networks: Methods for rate function identification

OpenAIRE

Atar, Rami; Dupuis, Paul

1999-01-01

This paper considers the problem of rate function identification for multidimensional queueing models with feedback. A set of techniques are introduced which allow this identification when the model possesses certain structural properties. The main tools used are representation formulas for exponential integrals, weak convergence methods, and the regularity properties of associated Skorokhod Problems. Two examples are treated as special cases of the general theory: the classical Jackson netwo...

[Progress in the spectral library based protein identification strategy].

Science.gov (United States)

Yu, Derui; Ma, Jie; Xie, Zengyan; Bai, Mingze; Zhu, Yunping; Shu, Kunxian

2018-04-25

Exponential growth of the mass spectrometry (MS) data is exhibited when the mass spectrometry-based proteomics has been developing rapidly. It is a great challenge to develop some quick, accurate and repeatable methods to identify peptides and proteins. Nowadays, the spectral library searching has become a mature strategy for tandem mass spectra based proteins identification in proteomics, which searches the experiment spectra against a collection of confidently identified MS/MS spectra that have been observed previously, and fully utilizes the abundance in the spectrum, peaks from non-canonical fragment ions, and other features. This review provides an overview of the implement of spectral library search strategy, and two key steps, spectral library construction and spectral library searching comprehensively, and discusses the progress and challenge of the library search strategy.

Preliminary identification of secreted proteins by Leptospira interrogans serovar Kennewicki strain Pomona Fromm

International Nuclear Information System (INIS)

Ricardi, L.M.P.; Portaro, F.C.; Abreu, P.A.E.; Barbosa, A.S.; Morais, Z.M.; Vasconcellos, S.A.

2012-01-01

Full text: This project aimed to identify secreted proteins by pathogenic Leptospira interrogans serovar Kennewicki strain Pomona Fromm (LPF) by proteomic analyses. The strain LPF, whose virulence was maintained by passages in hamsters, were cultured in EMJH medium. The supernatants were centrifuged, dialyzed and subjected to lyophilization. Protein samples were resolved first by IEF at pH 3 to 10, immobilized pH gradient 13-cm strips. Strips were then processed for the second-dimension separation on SDS-polyacrylamide gels. Proteins from gel spots were subjected to reduction, cysteine-alkylation, and in-gel tryptic digestion, and analyzed by LC/MS/MS spectrometry. Liquid chromatography-based separation followed by automated tandem mass spectrometry was also used to identify secreted proteins. In silico analyses were performed using the PSORTbV.3.0 program and SignalP server. One major obstacle to secretome studies is the difficulty to obtain extracts of secreted proteins without citoplasmatic contamination. In addition, the extraction of low concentration proteins from large volumes of culture media, which are rich in salts, BSA and other compounds, frequently interfere with most proteomics techniques. For these reasons, several experimental approaches were used to optimize the protocol applied. In spite of this fact, our analysis resulted in the identification of 200 proteins with high confidence. Only 5 of 63 secreted proteins predicted by in silico analysis were found. Other classes identified included proteins that possess signal peptide but whose cellular localization prediction is unknown or may have multiple localization sites, and proteins that lack signal peptide and are thus thought to be secreted via non conventional mechanisms or resulting from cytoplasmic contamination by cell lysis. Many of these are hypothetical proteins with no putative conserved domains detected. To our knowledge, this is the first study to identify secreted proteins by

Preliminary identification of secreted proteins by Leptospira interrogans serovar Kennewicki strain Pomona Fromm

Energy Technology Data Exchange (ETDEWEB)

Ricardi, L.M.P.; Portaro, F.C.; Abreu, P.A.E.; Barbosa, A.S. [Instituto Butantan, Sao Paulo, SP (Brazil); Morais, Z.M.; Vasconcellos, S.A. [Universidade de Sao Paulo (USP), SP (Brazil)

2012-07-01

Full text: This project aimed to identify secreted proteins by pathogenic Leptospira interrogans serovar Kennewicki strain Pomona Fromm (LPF) by proteomic analyses. The strain LPF, whose virulence was maintained by passages in hamsters, were cultured in EMJH medium. The supernatants were centrifuged, dialyzed and subjected to lyophilization. Protein samples were resolved first by IEF at pH 3 to 10, immobilized pH gradient 13-cm strips. Strips were then processed for the second-dimension separation on SDS-polyacrylamide gels. Proteins from gel spots were subjected to reduction, cysteine-alkylation, and in-gel tryptic digestion, and analyzed by LC/MS/MS spectrometry. Liquid chromatography-based separation followed by automated tandem mass spectrometry was also used to identify secreted proteins. In silico analyses were performed using the PSORTbV.3.0 program and SignalP server. One major obstacle to secretome studies is the difficulty to obtain extracts of secreted proteins without citoplasmatic contamination. In addition, the extraction of low concentration proteins from large volumes of culture media, which are rich in salts, BSA and other compounds, frequently interfere with most proteomics techniques. For these reasons, several experimental approaches were used to optimize the protocol applied. In spite of this fact, our analysis resulted in the identification of 200 proteins with high confidence. Only 5 of 63 secreted proteins predicted by in silico analysis were found. Other classes identified included proteins that possess signal peptide but whose cellular localization prediction is unknown or may have multiple localization sites, and proteins that lack signal peptide and are thus thought to be secreted via non conventional mechanisms or resulting from cytoplasmic contamination by cell lysis. Many of these are hypothetical proteins with no putative conserved domains detected. To our knowledge, this is the first study to identify secreted proteins by

Effective Identification of Akt Interacting Proteins by Two-Step Chemical Crosslinking, Co-Immunoprecipitation and Mass Spectrometry

Science.gov (United States)

Huang, Bill X.; Kim, Hee-Yong

2013-01-01

Akt is a critical protein for cell survival and known to interact with various proteins. However, Akt binding partners that modulate or regulate Akt activation have not been fully elucidated. Identification of Akt-interacting proteins has been customarily achieved by co-immunoprecipitation combined with western blot and/or MS analysis. An intrinsic problem of the method is loss of interacting proteins during procedures to remove non-specific proteins. Moreover, antibody contamination often interferes with the detection of less abundant proteins. Here, we developed a novel two-step chemical crosslinking strategy to overcome these problems which resulted in a dramatic improvement in identifying Akt interacting partners. Akt antibody was first immobilized on protein A/G beads using disuccinimidyl suberate and allowed to bind to cellular Akt along with its interacting proteins. Subsequently, dithiobis[succinimidylpropionate], a cleavable crosslinker, was introduced to produce stable complexes between Akt and binding partners prior to the SDS-PAGE and nanoLC-MS/MS analysis. This approach enabled identification of ten Akt partners from cell lysates containing as low as 1.5 mg proteins, including two new potential Akt interacting partners. None of these but one protein was detectable without crosslinking procedures. The present method provides a sensitive and effective tool to probe Akt-interacting proteins. This strategy should also prove useful for other protein interactions, particularly those involving less abundant or weakly associating partners. PMID:23613850

Multidimensional poverty, household environment and short-term morbidity in India.

Science.gov (United States)

Dehury, Bidyadhar; Mohanty, Sanjay K

2017-01-01

Using the unit data from the second round of the Indian Human Development Survey (IHDS-II), 2011-2012, which covered 42,152 households, this paper examines the association between multidimensional poverty, household environmental deprivation and short-term morbidities (fever, cough and diarrhoea) in India. Poverty is measured in a multidimensional framework that includes the dimensions of education, health and income, while household environmental deprivation is defined as lack of access to improved sanitation, drinking water and cooking fuel. A composite index combining multidimensional poverty and household environmental deprivation has been computed, and households are classified as follows: multidimensional poor and living in a poor household environment, multidimensional non-poor and living in a poor household environment, multidimensional poor and living in a good household environment and multidimensional non-poor and living in a good household environment. Results suggest that about 23% of the population belonging to multidimensional poor households and living in a poor household environment had experienced short-term morbidities in a reference period of 30 days compared to 20% of the population belonging to multidimensional non-poor households and living in a poor household environment, 19% of the population belonging to multidimensional poor households and living in a good household environment and 15% of the population belonging to multidimensional non-poor households and living in a good household environment. Controlling for socioeconomic covariates, the odds of short-term morbidity was 1.47 [CI 1.40-1.53] among the multidimensional poor and living in a poor household environment, 1.28 [CI 1.21-1.37] among the multidimensional non-poor and living in a poor household environment and 1.21 [CI 1.64-1.28] among the multidimensional poor and living in a good household environment compared to the multidimensional non-poor and living in a good household

Identification of Differentially Abundant Proteins of Edwardsiella ictaluri during Iron Restriction.

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Pradeep R Dumpala

Full Text Available Edwardsiella ictaluri is a Gram-negative facultative anaerobe intracellular bacterium that causes enteric septicemia in channel catfish. Iron is an essential inorganic nutrient of bacteria and is crucial for bacterial invasion. Reduced availability of iron by the host may cause significant stress for bacterial pathogens and is considered a signal that leads to significant alteration in virulence gene expression. However, the precise effect of iron-restriction on E. ictaluri protein abundance is unknown. The purpose of this study was to identify differentially abundant proteins of E. ictaluri during in vitro iron-restricted conditions. We applied two-dimensional difference in gel electrophoresis (2D-DIGE for determining differentially abundant proteins and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF/TOF MS for protein identification. Gene ontology and pathway-based functional modeling of differentially abundant proteins was also conducted. A total of 50 unique differentially abundant proteins at a minimum of 2-fold (p ≤ 0.05 difference in abundance due to iron-restriction were detected. The numbers of up- and down-regulated proteins were 37 and 13, respectively. We noted several proteins, including EsrB, LamB, MalM, MalE, FdaA, and TonB-dependent heme/hemoglobin receptor family proteins responded to iron restriction in E. ictaluri.

MASCOT HTML and XML parser: an implementation of a novel object model for protein identification data.

Science.gov (United States)

Yang, Chunguang G; Granite, Stephen J; Van Eyk, Jennifer E; Winslow, Raimond L

2006-11-01

Protein identification using MS is an important technique in proteomics as well as a major generator of proteomics data. We have designed the protein identification data object model (PDOM) and developed a parser based on this model to facilitate the analysis and storage of these data. The parser works with HTML or XML files saved or exported from MASCOT MS/MS ions search in peptide summary report or MASCOT PMF search in protein summary report. The program creates PDOM objects, eliminates redundancy in the input file, and has the capability to output any PDOM object to a relational database. This program facilitates additional analysis of MASCOT search results and aids the storage of protein identification information. The implementation is extensible and can serve as a template to develop parsers for other search engines. The parser can be used as a stand-alone application or can be driven by other Java programs. It is currently being used as the front end for a system that loads HTML and XML result files of MASCOT searches into a relational database. The source code is freely available at http://www.ccbm.jhu.edu and the program uses only free and open-source Java libraries.

Multidimensional quantum entanglement with large-scale integrated optics.

Science.gov (United States)

Wang, Jianwei; Paesani, Stefano; Ding, Yunhong; Santagati, Raffaele; Skrzypczyk, Paul; Salavrakos, Alexia; Tura, Jordi; Augusiak, Remigiusz; Mančinska, Laura; Bacco, Davide; Bonneau, Damien; Silverstone, Joshua W; Gong, Qihuang; Acín, Antonio; Rottwitt, Karsten; Oxenløwe, Leif K; O'Brien, Jeremy L; Laing, Anthony; Thompson, Mark G

2018-04-20

The ability to control multidimensional quantum systems is central to the development of advanced quantum technologies. We demonstrate a multidimensional integrated quantum photonic platform able to generate, control, and analyze high-dimensional entanglement. A programmable bipartite entangled system is realized with dimensions up to 15 × 15 on a large-scale silicon photonics quantum circuit. The device integrates more than 550 photonic components on a single chip, including 16 identical photon-pair sources. We verify the high precision, generality, and controllability of our multidimensional technology, and further exploit these abilities to demonstrate previously unexplored quantum applications, such as quantum randomness expansion and self-testing on multidimensional states. Our work provides an experimental platform for the development of multidimensional quantum technologies. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Multidimensional Poverty and Child Survival in India

Science.gov (United States)

Mohanty, Sanjay K.

2011-01-01

Background Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. Objectives and Methodology Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. Results The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Conclusion Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population. PMID:22046384

Multidimensional poverty and child survival in India.

Directory of Open Access Journals (Sweden)

Sanjay K Mohanty

Full Text Available Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses.The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed.Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

Multidimensional poverty and child survival in India.

Science.gov (United States)

Mohanty, Sanjay K

2011-01-01

Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

The emergence and evolution of the multidimensional organization

OpenAIRE

Strikwerda, J.; Stoelhorst, J.W.

2009-01-01

The article discusses multidimensional organizations and the evolution of complex organizations. The six characteristics of multidimensional organizations, disadvantages of the successful organizational structure that is categorized as a multidivisional, multi-unit or M-form, research by the Foundation for Management Studies which suggests that synergies across business divisions can be exploited by the M-form, a team approach to creating economic value, examples of multidimensional firms suc...

Identification and characterization of RBM44 as a novel intercellular bridge protein.

Directory of Open Access Journals (Sweden)

Tokuko Iwamori

2011-02-01

Full Text Available Intercellular bridges are evolutionarily conserved structures that connect differentiating germ cells. We previously reported the identification of TEX14 as the first essential intercellular bridge protein, the demonstration that intercellular bridges are required for male fertility, and the finding that intercellular bridges utilize components of the cytokinesis machinery to form. Herein, we report the identification of RNA binding motif protein 44 (RBM44 as a novel germ cell intercellular bridge protein. RBM44 was identified by proteomic analysis after intercellular bridge enrichment using TEX14 as a marker protein. RBM44 is highly conserved between mouse and human and contains an RNA recognition motif of unknown function. RBM44 mRNA is enriched in testis, and immunofluorescence confirms that RBM44 is an intercellular bridge component. However, RBM44 only partially localizes to TEX14-positive intercellular bridges. RBM44 is expressed most highly in pachytene and secondary spermatocytes, but disappears abruptly in spermatids. We discovered that RBM44 interacts with itself and TEX14 using yeast two-hybrid, mammalian two-hybrid, and immunoprecipitation. To define the in vivo function of RBM44, we generated a targeted deletion of Rbm44 in mice. Rbm44 null male mice produce somewhat increased sperm, and show enhanced fertility of unknown etiology. Thus, although RBM44 localizes to intercellular bridges during meiosis, RBM44 is not required for fertility in contrast to TEX14.

Multidimensional protein fractionation using ProteomeLab PF 2D™ for profiling amyotrophic lateral sclerosis immunity: A preliminary report

Directory of Open Access Journals (Sweden)

Mosley R Lee

2008-09-01

Full Text Available Abstract Background The ProteomeLab™ PF 2D platform is a relatively new approach to global protein profiling. Herein, it was used for investigation of plasma proteome changes in amyotrophic lateral sclerosis (ALS patients before and during immunization with glatiramer acetate (GA in a clinical trial. Results The experimental design included immunoaffinity depletion of 12 most abundant proteins from plasma samples with the ProteomeLab™ IgY-12 LC10 column kit as first dimension separation, also referred to as immuno-partitioning. Second and third dimension separations of the enriched proteome were performed on the PF 2D platform utilizing 2D isoelectric focusing and RP-HPLC with the resulting fractions collected for analysis. 1D gel electrophoresis was added as a fourth dimension when sufficient protein was available. Protein identification from collected fractions was performed using nano-LC-MS/MS approach. Analysis of differences in the resulting two-dimensional maps of fractions obtained from the PF 2D and the ability to identify proteins from these fractions allowed sensitivity threshold measurements. Masked proteins in the PF 2D fractions are discussed. Conclusion We offer some insight into the strengths and limitations of this emerging proteomic platform.

Multi-Segment Direct Inject nano-ESI-LTQ-FT-ICR-MS/MS For Protein Identification

Directory of Open Access Journals (Sweden)

Neal Rachel E

2011-07-01

Full Text Available Abstract Reversed phase high performance liquid chromatography (HPLC interfaced to electrospray tandem mass spectrometry (MS/MS is commonly used for the identification of peptides from proteolytically cleaved proteins embedded in a polyacrylamide gel matrix as well as for metabolomics screening. HPLC separations are time consuming (30-60 min average, costly (columns and mobile phase reagents, and carry the risk of column carry over between samples. The use of a chip-based nano-ESI platform (Advion NanoMate based on replaceable nano-tips for sample introduction eliminates sample cross-contamination, provides unchanging sample matrix, and enhances spray stability with attendant increases in reproducibility. Recent papers have established direct infusion nano-ESI-MS/MS utilizing the NanoMate for protein identification of gel spots based on full range MS scans with data dependent MS/MS. In a full range scan, discontinuous ion suppression due to sample matrix can impair identification of putative mass features of interest in both the proteomic and metabolomic workflows. In the current study, an extension of an established direct inject nano-ESI-MS/MS method is described that utilizes the mass filtering capability of an ion-trap for ion packet separation into four narrow mass ranges (50 amu overlap with segment specific dynamic data dependent peak inclusion for MS/MS fragmentation (total acquisition time of 3 minutes. Comparison of this method with a more traditional nanoLC-MS/MS based protocol utilizing solvent/sample stream splitting to achieve nanoflow demonstrated comparable results for protein identification from polyacrylamide gel matrices. The advantages of this method include full automation, lack of cross-contamination, low cost, and high throughput.

Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

DEFF Research Database (Denmark)

Hjerrild, M.; Stensballe, A.; Rasmussen, T.E.

2004-01-01

Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...

Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

DEFF Research Database (Denmark)

Hjerrild, Majbrit; Stensballe, Allan; Rasmussen, Thomas E

2011-01-01

Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...

Identifying associations between pig pathologies using a multi-dimensional machine learning methodology.

Science.gov (United States)

Sanchez-Vazquez, Manuel J; Nielen, Mirjam; Edwards, Sandra A; Gunn, George J; Lewis, Fraser I

2012-08-31

Abattoir detected pathologies are of crucial importance to both pig production and food safety. Usually, more than one pathology coexist in a pig herd although it often remains unknown how these different pathologies interrelate to each other. Identification of the associations between different pathologies may facilitate an improved understanding of their underlying biological linkage, and support the veterinarians in encouraging control strategies aimed at reducing the prevalence of not just one, but two or more conditions simultaneously. Multi-dimensional machine learning methodology was used to identify associations between ten typical pathologies in 6485 batches of slaughtered finishing pigs, assisting the comprehension of their biological association. Pathologies potentially associated with septicaemia (e.g. pericarditis, peritonitis) appear interrelated, suggesting on-going bacterial challenges by pathogens such as Haemophilus parasuis and Streptococcus suis. Furthermore, hepatic scarring appears interrelated with both milk spot livers (Ascaris suum) and bacteria-related pathologies, suggesting a potential multi-pathogen nature for this pathology. The application of novel multi-dimensional machine learning methodology provided new insights into how typical pig pathologies are potentially interrelated at batch level. The methodology presented is a powerful exploratory tool to generate hypotheses, applicable to a wide range of studies in veterinary research.

Identification of Pentatricopeptide Repeat Proteins in the Model Organism Dictyostelium discoideum

Directory of Open Access Journals (Sweden)

Sam Manna

2013-01-01

Full Text Available Pentatricopeptide repeat (PPR proteins are RNA binding proteins with functions in organelle RNA metabolism. They are found in all eukaryotes but have been most extensively studied in plants. We report on the identification of 12 PPR-encoding genes in the genome of the protist Dictyostelium discoideum, with potential homologs in other members of the same lineage and some predicted novel functions for the encoded gene products in protists. For one of the gene products, we show that it localizes to the mitochondria, and we also demonstrate that antisense inhibition of its expression leads to slower growth, a phenotype associated with mitochondrial dysfunction.

Fundamentals of Protein NMR Spectroscopy

CERN Document Server

Rule, Gordon S

2006-01-01

NMR spectroscopy has proven to be a powerful technique to study the structure and dynamics of biological macromolecules. Fundamentals of Protein NMR Spectroscopy is a comprehensive textbook that guides the reader from a basic understanding of the phenomenological properties of magnetic resonance to the application and interpretation of modern multi-dimensional NMR experiments on 15N/13C-labeled proteins. Beginning with elementary quantum mechanics, a set of practical rules is presented and used to describe many commonly employed multi-dimensional, multi-nuclear NMR pulse sequences. A modular analysis of NMR pulse sequence building blocks also provides a basis for understanding and developing novel pulse programs. This text not only covers topics from chemical shift assignment to protein structure refinement, as well as the analysis of protein dynamics and chemical kinetics, but also provides a practical guide to many aspects of modern spectrometer hardware, sample preparation, experimental set-up, and data pr...

Isolation and identification of the human homolog of a new p53-binding protein, Mdmx

NARCIS (Netherlands)

Shvarts, A.; Bazuine, M.; Dekker, P.; Ramos, Y. F.; Steegenga, W. T.; Merckx, G.; van Ham, R. C.; van der Houven van Oordt, W.; van der Eb, A. J.; Jochemsen, A. G.

1997-01-01

We recently reported the identification of a mouse cDNA encoding a new p53-associating protein that we called Mdmx because of its structural similarity to Mdm2, a well-known p53-binding protein. Here we report the isolation of a cDNA encoding the human homolog of Mdmx. The ORF of the cDNA encodes a

Nucleos: a web server for the identification of nucleotide-binding sites in protein structures.

Science.gov (United States)

Parca, Luca; Ferré, Fabrizio; Ausiello, Gabriele; Helmer-Citterich, Manuela

2013-07-01

Nucleos is a web server for the identification of nucleotide-binding sites in protein structures. Nucleos compares the structure of a query protein against a set of known template 3D binding sites representing nucleotide modules, namely the nucleobase, carbohydrate and phosphate. Structural features, clustering and conservation are used to filter and score the predictions. The predicted nucleotide modules are then joined to build whole nucleotide-binding sites, which are ranked by their score. The server takes as input either the PDB code of the query protein structure or a user-submitted structure in PDB format. The output of Nucleos is composed of ranked lists of predicted nucleotide-binding sites divided by nucleotide type (e.g. ATP-like). For each ranked prediction, Nucleos provides detailed information about the score, the template structure and the structural match for each nucleotide module composing the nucleotide-binding site. The predictions on the query structure and the template-binding sites can be viewed directly on the web through a graphical applet. In 98% of the cases, the modules composing correct predictions belong to proteins with no homology relationship between each other, meaning that the identification of brand-new nucleotide-binding sites is possible using information from non-homologous proteins. Nucleos is available at http://nucleos.bio.uniroma2.it/nucleos/.

MULTI-DIMENSIONAL MASS SPECTROMETRY-BASED SHOTGUN LIPIDOMICS AND NOVEL STRATEGIES FOR LIPIDOMIC ANALYSES

Science.gov (United States)

Han, Xianlin; Yang, Kui; Gross, Richard W.

2011-01-01

Since our last comprehensive review on multi-dimensional mass spectrometry-based shotgun lipidomics (Mass Spectrom. Rev. 24 (2005), 367), many new developments in the field of lipidomics have occurred. These developments include new strategies and refinements for shotgun lipidomic approaches that use direct infusion, including novel fragmentation strategies, identification of multiple new informative dimensions for mass spectrometric interrogation, and the development of new bioinformatic approaches for enhanced identification and quantitation of the individual molecular constituents that comprise each cell’s lipidome. Concurrently, advances in liquid chromatography-based platforms and novel strategies for quantitative matrix-assisted laser desorption/ionization mass spectrometry for lipidomic analyses have been developed. Through the synergistic use of this repertoire of new mass spectrometric approaches, the power and scope of lipidomics has been greatly expanded to accelerate progress toward the comprehensive understanding of the pleiotropic roles of lipids in biological systems. PMID:21755525

A practical guide for the identification of membrane and plasma membrane proteins in human embryonic stem cells and human embryonal carcinoma cells.

Science.gov (United States)

Dormeyer, Wilma; van Hoof, Dennis; Mummery, Christine L; Krijgsveld, Jeroen; Heck, Albert J R

2008-10-01

The identification of (plasma) membrane proteins in cells can provide valuable insights into the regulation of their biological processes. Pluripotent cells such as human embryonic stem cells and embryonal carcinoma cells are capable of unlimited self-renewal and share many of the biological mechanisms that regulate proliferation and differentiation. The comparison of their membrane proteomes will help unravel the biological principles of pluripotency, and the identification of biomarker proteins in their plasma membranes is considered a crucial step to fully exploit pluripotent cells for therapeutic purposes. For these tasks, membrane proteomics is the method of choice, but as indicated by the scarce identification of membrane and plasma membrane proteins in global proteomic surveys it is not an easy task. In this minireview, we first describe the general challenges of membrane proteomics. We then review current sample preparation steps and discuss protocols that we found particularly beneficial for the identification of large numbers of (plasma) membrane proteins in human tumour- and embryo-derived stem cells. Our optimized assembled protocol led to the identification of a large number of membrane proteins. However, as the composition of cells and membranes is highly variable we still recommend adapting the sample preparation protocol for each individual system.

Multidimensional fatigue and its correlates in hospitalised advanced cancer patients.

NARCIS (Netherlands)

Echteld, M.A.; Passchier, J.; Teunissen, S.; Claessen, S.; Wit, R. de; Rijt, C.C.D. van der

2007-01-01

Although fatigue is a multidimensional concept, multidimensional fatigue is rarely investigated in hospitalised cancer patients. We determined the levels and correlates of multidimensional fatigue in 100 advanced cancer patients admitted for symptom control. Fatigue dimensions were general fatigue

P185-M Protein Identification and Validation of Results in Workflows that Integrate over Various Instruments, Datasets, Search Engines

Science.gov (United States)

Hufnagel, P.; Glandorf, J.; Körting, G.; Jabs, W.; Schweiger-Hufnagel, U.; Hahner, S.; Lubeck, M.; Suckau, D.

2007-01-01

Analysis of complex proteomes often results in long protein lists, but falls short in measuring the validity of identification and quantification results on a greater number of proteins. Biological and technical replicates are mandatory, as is the combination of the MS data from various workflows (gels, 1D-LC, 2D-LC), instruments (TOF/TOF, trap, qTOF or FTMS), and search engines. We describe a database-driven study that combines two workflows, two mass spectrometers, and four search engines with protein identification following a decoy database strategy. The sample was a tryptically digested lysate (10,000 cells) of a human colorectal cancer cell line. Data from two LC-MALDI-TOF/TOF runs and a 2D-LC-ESI-trap run using capillary and nano-LC columns were submitted to the proteomics software platform ProteinScape. The combined MALDI data and the ESI data were searched using Mascot (Matrix Science), Phenyx (GeneBio), ProteinSolver (Bruker and Protagen), and Sequest (Thermo) against a decoy database generated from IPI-human in order to obtain one protein list across all workflows and search engines at a defined maximum false-positive rate of 5%. ProteinScape combined the data to one LC-MALDI and one LC-ESI dataset. The initial separate searches from the two combined datasets generated eight independent peptide lists. These were compiled into an integrated protein list using the ProteinExtractor algorithm. An initial evaluation of the generated data led to the identification of approximately 1200 proteins. Result integration on a peptide level allowed discrimination of protein isoforms that would not have been possible with a mere combination of protein lists.

Intuitionistic fuzzy (IF) evaluations of multidimensional model

International Nuclear Information System (INIS)

Valova, I.

2012-01-01

There are different logical methods for data structuring, but no one is perfect enough. Multidimensional model-MD of data is presentation of data in a form of cube (referred also as info-cube or hypercube) with data or in form of 'star' type scheme (referred as multidimensional scheme), by use of F-structures (Facts) and set of D-structures (Dimensions), based on the notion of hierarchy of D-structures. The data, being subject of analysis in a specific multidimensional model is located in a Cartesian space, being restricted by D-structures. In fact, the data is either dispersed or 'concentrated', therefore the data cells are not distributed evenly within the respective space. The moment of occurrence of any event is difficult to be predicted and the data is concentrated as per time periods, location of performed business event, etc. To process such dispersed or concentrated data, various technical strategies are needed. The basic methods for presentation of such data should be selected. The approaches of data processing and respective calculations are connected with different options for data representation. The use of intuitionistic fuzzy evaluations (IFE) provide us new possibilities for alternative presentation and processing of data, subject of analysis in any OLAP application. The use of IFE at the evaluation of multidimensional models will result in the following advantages: analysts will dispose with more complete information for processing and analysis of respective data; benefit for the managers is that the final decisions will be more effective ones; enabling design of more functional multidimensional schemes. The purpose of this work is to apply intuitionistic fuzzy evaluations of multidimensional model of data. (authors)

Ribosomal proteins as biomarkers for bacterial identification by mass spectrometry in the clinical microbiology laboratory.

Science.gov (United States)

Suarez, Stéphanie; Ferroni, Agnès; Lotz, Aurélie; Jolley, Keith A; Guérin, Philippe; Leto, Julie; Dauphin, Brunhilde; Jamet, Anne; Maiden, Martin C J; Nassif, Xavier; Armengaud, Jean

2013-09-01

Whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a rapid method for identification of microorganisms that is increasingly used in microbiology laboratories. This identification is based on the comparison of the tested isolate mass spectrum with reference databases. Using Neisseria meningitidis as a model organism, we showed that in one of the available databases, the Andromas database, 10 of the 13 species-specific biomarkers correspond to ribosomal proteins. Remarkably, one biomarker, ribosomal protein L32, was subject to inter-strain variability. The analysis of the ribosomal protein patterns of 100 isolates for which whole genome sequences were available, confirmed the presence of inter-strain variability in the molecular weight of 29 ribosomal proteins, thus establishing a correlation between the sequence type (ST) and/or clonal complex (CC) of each strain and its ribosomal protein pattern. Since the molecular weight of three of the variable ribosomal proteins (L30, L31 and L32) was included in the spectral window observed by MALDI-TOF MS in clinical microbiology, i.e., 3640-12000 m/z, we were able by analyzing the molecular weight of these three ribosomal proteins to classify each strain in one of six subgroups, each of these subgroups corresponding to specific STs and/or CCs. Their detection by MALDI-TOF allows therefore a quick typing of N. meningitidis isolates. © 2013 Elsevier B.V. All rights reserved.

Identification of lipopolysaccharide-interacting plasma membrane-type proteins in Arabidopsis thaliana.

Science.gov (United States)

Vilakazi, Cornelius S; Dubery, Ian A; Piater, Lizelle A

2017-02-01

Lipopolysaccharide (LPS) is an amphiphatic bacterial glycoconjugate found on the external membrane of Gram-negative bacteria. This endotoxin is considered as a microbe-associated molecular pattern (MAMP) molecule and has been shown to elicit defense responses in plants. Here, LPS-interacting proteins from Arabidopsis thaliana plasma membrane (PM)-type fractions were captured and identified in order to investigate those involved in LPS perception and linked to triggering of innate immune responses. A novel proteomics-based affinity-capture strategy coupled to liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed for the enrichment and identification of LPS-interacting proteins. As such, LPS isolated from Burkholderia cepacia (LPS B.cep. ) was immobilized on three independent and distinct affinity-based matrices to serve as bait for interacting proteins from A. thaliana leaf and callus tissue. These were resolved by 1D electrophoresis and identified by mass spectrometry. Proteins specifically bound to LPS B.cep. have been implicated in membrane structure (e.g. COBRA-like and tubulin proteins), membrane trafficking and/or transport (e.g. soluble NSF attachment protein receptor (SNARE) proteins, patellin, aquaporin, PM instrinsic proteins (PIP) and H + -ATPase), signal transduction (receptor-like kinases and calcium-dependent protein kinases) as well as defense/stress responses (e.g. hypersensitive-induced response (HIR) proteins, jacalin-like lectin domain-containing protein and myrosinase-binding proteins). The novel affinity-capture strategy for the enrichment of LPS-interacting proteins proved to be effective, especially in the binding of proteins involved in plant defense responses, and can thus be used to elucidate LPS-mediated molecular recognition and disease mechanism(s). Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Efficient identification of critical residues based only on protein structure by network analysis.

Directory of Open Access Journals (Sweden)

Michael P Cusack

2007-05-01

Full Text Available Despite the increasing number of published protein structures, and the fact that each protein's function relies on its three-dimensional structure, there is limited access to automatic programs used for the identification of critical residues from the protein structure, compared with those based on protein sequence. Here we present a new algorithm based on network analysis applied exclusively on protein structures to identify critical residues. Our results show that this method identifies critical residues for protein function with high reliability and improves automatic sequence-based approaches and previous network-based approaches. The reliability of the method depends on the conformational diversity screened for the protein of interest. We have designed a web site to give access to this software at http://bis.ifc.unam.mx/jamming/. In summary, a new method is presented that relates critical residues for protein function with the most traversed residues in networks derived from protein structures. A unique feature of the method is the inclusion of the conformational diversity of proteins in the prediction, thus reproducing a basic feature of the structure/function relationship of proteins.

Proteomic platform for the identification of proteins in olive (Olea europaea) pulp.

Science.gov (United States)

Capriotti, Anna Laura; Cavaliere, Chiara; Foglia, Patrizia; Piovesana, Susy; Samperi, Roberto; Stampachiacchiere, Serena; Laganà, Aldo

2013-10-24

The nutritional and cancer-protective properties of the oil extracted mechanically from the ripe fruits of Olea europaea trees are attracting constantly more attention worldwide. The preparation of high-quality protein samples from plant tissues for proteomic analysis poses many challenging problems. In this study we employed a proteomic platform based on two different extraction methods, SDS and CHAPS based protocols, followed by two precipitation protocols, TCA/acetone and MeOH precipitation, in order to increase the final number of identified proteins. The use of advanced MS techniques in combination with the Swissprot and NCBI Viridiplantae databases and TAIR10 Arabidopsis database allowed us to identify 1265 proteins, of which 22 belong to O. europaea. The application of this proteomic platform for protein extraction and identification will be useful also for other proteomic studies on recalcitrant plant/fruit tissues. Copyright © 2013. Published by Elsevier B.V.

Symbolic Multidimensional Scaling

NARCIS (Netherlands)

P.J.F. Groenen (Patrick); Y. Terada

2015-01-01

markdownabstract__Abstract__ Multidimensional scaling (MDS) is a technique that visualizes dissimilarities between pairs of objects as distances between points in a low dimensional space. In symbolic MDS, a dissimilarity is not just a value but can represent an interval or even a histogram. Here,

Identification of a nuclear localization signal in the retinitis pigmentosa-mutated RP26 protein, ceramide kinase-like protein

International Nuclear Information System (INIS)

Inagaki, Yuichi; Mitsutake, Susumu; Igarashi, Yasuyuki

2006-01-01

Retinitis pigmentosa (RP) is a genetically heterogeneous disease characterized by degeneration of the retina. A mutation in a new ceramide kinase (CERK) homologous gene, named CERK-like protein (CERKL), was found to cause autosomal recessive retinitis pigmentosa (RP26). Here, we show a point mutation of one of two putative nuclear localization signal (NLS) sequences inhibited the nuclear localization of the protein. Furthermore, the tetra-GFP-tagged NLS, which cannot passively enter the nucleus, was observed not only in the nucleus but also in the nucleolus. Our results provide First evidence of the active nuclear import of CERKL and suggest that the identified NLS might be responsible for nucleolar retention of the protein. As recent studies have shown other RP-related proteins are localized in the nucleus or the nucleolus, our identification of NLS in CERKL suggests that CERKL likely plays important roles for retinal functions in the nucleus and the nucleolus

Identification of ZASP, a novel protein associated to Zona occludens-2

Energy Technology Data Exchange (ETDEWEB)

Lechuga, Susana; Alarcon, Lourdes; Solano, Jesus [Department of Physiology, Biophysics and Neuroscience, Center for Research and Advanced Studies (Cinvestav), Mexico, D.F. 07360 (Mexico); Huerta, Miriam; Lopez-Bayghen, Esther [Department of Genetics and Molecular Biology, Center for Research and Advanced Studies (Cinvestav), Mexico, D.F. 07360 (Mexico); Gonzalez-Mariscal, Lorenza, E-mail: lorenza@fisio.cinvestav.mx [Department of Physiology, Biophysics and Neuroscience, Center for Research and Advanced Studies (Cinvestav), Mexico, D.F. 07360 (Mexico)

2010-11-15

With the aim of discovering new molecular interactions of the tight junction protein ZO-2, a two-hybrid screen was performed on a human kidney cDNA library using as bait the middle segment of ZO-2. Through this assay we identified a 24-kDa novel protein herein named ZASP for ZO-2 associated speckle protein. ZO-2/ZASP interaction further confirmed by pull down and immunoprecipitation experiments, requires the presence of the intact PDZ binding motif SQV of ZASP and the third PDZ domain of ZO-2. ZASP mRNA and protein are present in the kidney and in several epithelial cell lines. Endogenous ZASP is expressed primarily in nuclear speckles in co-localization with splicing factor SC-35. Nocodazole treatment and wash out reveals that ZASP disappears from the nucleus during mitosis in accordance with speckle disassembly during metaphase. ZASP amino acid sequence exhibits a canonical nuclear exportation signal and in agreement the protein exits the nucleus through a process mediated by exportin/CRM1. ZASP over-expression blocks the inhibitory activity of ZO-2 on cyclin D1 gene transcription and protein expression. The identification of ZASP helps to unfold the complex nuclear molecular arrays that form on ZO-2 scaffolds.

Identification of ZASP, a novel protein associated to Zona occludens-2.

Science.gov (United States)

Lechuga, Susana; Alarcón, Lourdes; Solano, Jesús; Huerta, Miriam; Lopez-Bayghen, Esther; González-Mariscal, Lorenza

2010-11-15

With the aim of discovering new molecular interactions of the tight junction protein ZO-2, a two-hybrid screen was performed on a human kidney cDNA library using as bait the middle segment of ZO-2. Through this assay we identified a 24-kDa novel protein herein named ZASP for ZO-2 associated speckle protein. ZO-2/ZASP interaction further confirmed by pull down and immunoprecipitation experiments, requires the presence of the intact PDZ binding motif SQV of ZASP and the third PDZ domain of ZO-2. ZASP mRNA and protein are present in the kidney and in several epithelial cell lines. Endogenous ZASP is expressed primarily in nuclear speckles in co-localization with splicing factor SC-35. Nocodazole treatment and wash out reveals that ZASP disappears from the nucleus during mitosis in accordance with speckle disassembly during metaphase. ZASP amino acid sequence exhibits a canonical nuclear exportation signal and in agreement the protein exits the nucleus through a process mediated by exportin/CRM1. ZASP over-expression blocks the inhibitory activity of ZO-2 on cyclin D1 gene transcription and protein expression. The identification of ZASP helps to unfold the complex nuclear molecular arrays that form on ZO-2 scaffolds. Copyright © 2010 Elsevier Inc. All rights reserved.

Identification of ZASP, a novel protein associated to Zona occludens-2

International Nuclear Information System (INIS)

Lechuga, Susana; Alarcon, Lourdes; Solano, Jesus; Huerta, Miriam; Lopez-Bayghen, Esther; Gonzalez-Mariscal, Lorenza

2010-01-01

With the aim of discovering new molecular interactions of the tight junction protein ZO-2, a two-hybrid screen was performed on a human kidney cDNA library using as bait the middle segment of ZO-2. Through this assay we identified a 24-kDa novel protein herein named ZASP for ZO-2 associated speckle protein. ZO-2/ZASP interaction further confirmed by pull down and immunoprecipitation experiments, requires the presence of the intact PDZ binding motif SQV of ZASP and the third PDZ domain of ZO-2. ZASP mRNA and protein are present in the kidney and in several epithelial cell lines. Endogenous ZASP is expressed primarily in nuclear speckles in co-localization with splicing factor SC-35. Nocodazole treatment and wash out reveals that ZASP disappears from the nucleus during mitosis in accordance with speckle disassembly during metaphase. ZASP amino acid sequence exhibits a canonical nuclear exportation signal and in agreement the protein exits the nucleus through a process mediated by exportin/CRM1. ZASP over-expression blocks the inhibitory activity of ZO-2 on cyclin D1 gene transcription and protein expression. The identification of ZASP helps to unfold the complex nuclear molecular arrays that form on ZO-2 scaffolds.

An Improved Multidimensional MPA Procedure for Bidirectional Earthquake Excitations

OpenAIRE

Wang, Feng; Sun, Jian-Gang; Zhang, Ning

2014-01-01

Presently, the modal pushover analysis procedure is extended to multidimensional analysis of structures subjected to multidimensional earthquake excitations. an improved multidimensional modal pushover analysis (IMMPA) method is presented in the paper in order to estimate the response demands of structures subjected to bidirectional earthquake excitations, in which the unidirectional earthquake excitation applied on equivalent SDOF system is replaced by the direct superposition of two compone...

The emergence and evolution of the multidimensional organization

NARCIS (Netherlands)

Strikwerda, J.; Stoelhorst, J.W.

2009-01-01

The article discusses multidimensional organizations and the evolution of complex organizations. The six characteristics of multidimensional organizations, disadvantages of the successful organizational structure that is categorized as a multidivisional, multi-unit or M-form, research by the

Sequence protein identification by randomized sequence database and transcriptome mass spectrometry (SPIDER-TMS): from manual to automatic application of a 'de novo sequencing' approach.

Science.gov (United States)

Pascale, Raffaella; Grossi, Gerarda; Cruciani, Gabriele; Mecca, Giansalvatore; Santoro, Donatello; Sarli Calace, Renzo; Falabella, Patrizia; Bianco, Giuliana

Sequence protein identification by a randomized sequence database and transcriptome mass spectrometry software package has been developed at the University of Basilicata in Potenza (Italy) and designed to facilitate the determination of the amino acid sequence of a peptide as well as an unequivocal identification of proteins in a high-throughput manner with enormous advantages of time, economical resource and expertise. The software package is a valid tool for the automation of a de novo sequencing approach, overcoming the main limits and a versatile platform useful in the proteomic field for an unequivocal identification of proteins, starting from tandem mass spectrometry data. The strength of this software is that it is a user-friendly and non-statistical approach, so protein identification can be considered unambiguous.

Perceptual Salience and Children's Multidimensional Problem Solving

Science.gov (United States)

Odom, Richard D.; Corbin, David W.

1973-01-01

Uni- and multidimensional processing of 6- to 9-year olds was studied using recall tasks in which an array of stimuli was reconstructed to match a model array. Results indicated that both age groups were able to solve multidimensional problems, but that solution rate was retarded by the unidimensional processing of highly salient dimensions.…

Identification of a putative protein-profile associating with tamoxifen therapy-resistance in breast cancer

NARCIS (Netherlands)

A. Umar (Arzu); J.W.M. Martens (John); J.A. Foekens (John); L. Paša-Tolić (Ljiljana); H. Kang; A.M. Timmermans (Mieke); M.P. Look (Maxime); M.E. Meijer van Gelder (Marion); N. Jaitly (Navdeep); M.A. den Bakker (Michael)

2009-01-01

textabstractTamoxifen-resistance is a major cause of death in patients with recurrent breast cancer. Current clinical parameters can correctly predict therapy response in only half of the treated patients. Identification of proteins that associate with tamoxifen-resistance is a first step towards

A Conceptual Model for Multidimensional Analysis of Documents

Science.gov (United States)

Ravat, Franck; Teste, Olivier; Tournier, Ronan; Zurlfluh, Gilles

Data warehousing and OLAP are mainly used for the analysis of transactional data. Nowadays, with the evolution of Internet, and the development of semi-structured data exchange format (such as XML), it is possible to consider entire fragments of data such as documents as analysis sources. As a consequence, an adapted multidimensional analysis framework needs to be provided. In this paper, we introduce an OLAP multidimensional conceptual model without facts. This model is based on the unique concept of dimensions and is adapted for multidimensional document analysis. We also provide a set of manipulation operations.

Multidimensional Measurement of Poverty among Women in Sub-Saharan Africa

Science.gov (United States)

Batana, Yele Maweki

2013-01-01

Since the seminal work of Sen, poverty has been recognized as a multidimensional phenomenon. The recent availability of relevant databases renewed the interest in this approach. This paper estimates multidimensional poverty among women in fourteen Sub-Saharan African countries using the Alkire and Foster multidimensional poverty measures, whose…

Application of multidimensional IRT models to longitudinal data

NARCIS (Netherlands)

te Marvelde, J.M.; Glas, Cornelis A.W.; Van Landeghem, Georges; Van Damme, Jan

2006-01-01

The application of multidimensional item response theory (IRT) models to longitudinal educational surveys where students are repeatedly measured is discussed and exemplified. A marginal maximum likelihood (MML) method to estimate the parameters of a multidimensional generalized partial credit model

Multidimensional sexual perfectionism.

Science.gov (United States)

Stoeber, Joachim; Harvey, Laura N; Almeida, Isabel; Lyons, Emma

2013-11-01

Perfectionism is a multidimensional personality characteristic that can affect all areas of life. This article presents the first systematic investigation of multidimensional perfectionism in the domain of sexuality exploring the unique relationships that different forms of sexual perfectionism show with positive and negative aspects of sexuality. A sample of 272 university students (52 male, 220 female) completed measures of four forms of sexual perfectionism: self-oriented, partner-oriented, partner-prescribed, and socially prescribed. In addition, they completed measures of sexual esteem, sexual self-efficacy, sexual optimism, sex life satisfaction (capturing positive aspects of sexuality) and sexual problem self-blame, sexual anxiety, sexual depression, and negative sexual perfectionism cognitions during sex (capturing negative aspects). Results showed unique patterns of relationships for the four forms of sexual perfectionism, suggesting that partner-prescribed and socially prescribed sexual perfectionism are maladaptive forms of sexual perfectionism associated with negative aspects of sexuality whereas self-oriented and partner-oriented sexual perfectionism emerged as ambivalent forms associated with positive and negative aspects.

Multidimensional real analysis I differentiation

CERN Document Server

Duistermaat, J J; van Braam Houckgeest, J P

2004-01-01

Part one of the authors' comprehensive and innovative work on multidimensional real analysis. This book is based on extensive teaching experience at Utrecht University and gives a thorough account of differential analysis in multidimensional Euclidean space. It is an ideal preparation for students who wish to go on to more advanced study. The notation is carefully organized and all proofs are clean, complete and rigorous. The authors have taken care to pay proper attention to all aspects of the theory. In many respects this book presents an original treatment of the subject and it contains man

Multidimensional First-Order Dominance Comparisons of Population Wellbeing

DEFF Research Database (Denmark)

Siersbæk, Nikolaj; Østerdal, Lars Peter Raahave; Arndt, Thomas Channing

2017-01-01

This chapter conveys the concept of first-order dominance (FOD) with particular focus on applications to multidimensional population welfare comparisons. It gives an account of the fundamental equivalent definitions of FOD both in the one-dimensional and multidimensional setting, illustrated...

Bottom–up protein identifications from microliter quantities of individual human tear samples. Important steps towards clinical relevance.

Directory of Open Access Journals (Sweden)

Peter Raus

2015-12-01

With 375 confidently identified proteins in the healthy adult tear, the obtained results are comprehensive and in large agreement with previously published observations on pooled samples of multiple patients. We conclude that, to a limited extent, bottom–up tear protein identifications from individual patients may have clinical relevance.

Identifying associations between pig pathologies using a multi-dimensional machine learning methodology

Directory of Open Access Journals (Sweden)

Sanchez-Vazquez Manuel J

2012-08-01

Full Text Available Abstract Background Abattoir detected pathologies are of crucial importance to both pig production and food safety. Usually, more than one pathology coexist in a pig herd although it often remains unknown how these different pathologies interrelate to each other. Identification of the associations between different pathologies may facilitate an improved understanding of their underlying biological linkage, and support the veterinarians in encouraging control strategies aimed at reducing the prevalence of not just one, but two or more conditions simultaneously. Results Multi-dimensional machine learning methodology was used to identify associations between ten typical pathologies in 6485 batches of slaughtered finishing pigs, assisting the comprehension of their biological association. Pathologies potentially associated with septicaemia (e.g. pericarditis, peritonitis appear interrelated, suggesting on-going bacterial challenges by pathogens such as Haemophilus parasuis and Streptococcus suis. Furthermore, hepatic scarring appears interrelated with both milk spot livers (Ascaris suum and bacteria-related pathologies, suggesting a potential multi-pathogen nature for this pathology. Conclusions The application of novel multi-dimensional machine learning methodology provided new insights into how typical pig pathologies are potentially interrelated at batch level. The methodology presented is a powerful exploratory tool to generate hypotheses, applicable to a wide range of studies in veterinary research.

Identification of Newly Synthesized Proteins by Echinococcus granulosus Protoscoleces upon Induction of Strobilation.

Directory of Open Access Journals (Sweden)

João Antonio Debarba

2015-09-01

Full Text Available The proteins responsible for the key molecular events leading to the structural changes between the developmental stages of Echinococcus granulosus remain unknown. In this work, azidohomoalanine (AHA-specific labeling was used to identify proteins expressed by E. granulosus protoscoleces (PSCs upon the induction of strobilar development.The in vitro incorporation of AHA with different tags into newly synthesized proteins (NSPs by PSCs was analyzed using SDS-PAGE and confocal microscopy. The LC-MS/MS analysis of AHA-labeled NSPs by PSCs undergoing strobilation allowed for the identification of 365 proteins, of which 75 were differentially expressed in comparison between the presence or absence of strobilation stimuli and 51 were expressed exclusively in either condition. These proteins were mainly involved in metabolic, regulatory and signaling processes.After the controlled-labeling of proteins during the induction of strobilar development, we identified modifications in protein expression. The changes in the metabolism and the activation of control and signaling pathways may be important for the correct parasite development and be target for further studies.

A multidimensional subdiffusion model: An arbitrage-free market

International Nuclear Information System (INIS)

Li Guo-Hua; Zhang Hong; Luo Mao-Kang

2012-01-01

To capture the subdiffusive characteristics of financial markets, the subordinated process, directed by the inverse α-stale subordinator S α (t) for 0 < α < 1, has been employed as the model of asset prices. In this article, we introduce a multidimensional subdiffusion model that has a bond and K correlated stocks. The stock price process is a multidimensional subdiffusion process directed by the inverse α-stable subordinator. This model describes the period of stagnation for each stock and the behavior of the dependency between multiple stocks. Moreover, we derive the multidimensional fractional backward Kolmogorov equation for the subordinated process using the Laplace transform technique. Finally, using a martingale approach, we prove that the multidimensional subdiffusion model is arbitrage-free, and also gives an arbitrage-free pricing rule for contingent claims associated with the martingale measure. (interdisciplinary physics and related areas of science and technology)

Proteogenomic Analysis Greatly Expands the Identification of Proteins Related to Reproduction in the Apogamous Fern Dryopteris affinis ssp. affinis.

Science.gov (United States)

Grossmann, Jonas; Fernández, Helena; Chaubey, Pururawa M; Valdés, Ana E; Gagliardini, Valeria; Cañal, María J; Russo, Giancarlo; Grossniklaus, Ueli

2017-01-01

Performing proteomic studies on non-model organisms with little or no genomic information is still difficult. However, many specific processes and biochemical pathways occur only in species that are poorly characterized at the genomic level. For example, many plants can reproduce both sexually and asexually, the first one allowing the generation of new genotypes and the latter their fixation. Thus, both modes of reproduction are of great agronomic value. However, the molecular basis of asexual reproduction is not well understood in any plant. In ferns, it combines the production of unreduced spores (diplospory) and the formation of sporophytes from somatic cells (apogamy). To set the basis to study these processes, we performed transcriptomics by next-generation sequencing (NGS) and shotgun proteomics by tandem mass spectrometry in the apogamous fern D. affinis ssp. affinis . For protein identification we used the public viridiplantae database (VPDB) to identify orthologous proteins from other plant species and new transcriptomics data to generate a "species-specific transcriptome database" (SSTDB). In total 1,397 protein clusters with 5,865 unique peptide sequences were identified (13 decoy proteins out of 1,410, protFDR 0.93% on protein cluster level). We show that using the SSTDB for protein identification increases the number of identified peptides almost four times compared to using only the publically available VPDB. We identified homologs of proteins involved in reproduction of higher plants, including proteins with a potential role in apogamy. With the increasing availability of genomic data from non-model species, similar proteogenomics approaches will improve the sensitivity in protein identification for species only distantly related to models.

Multi-dimensional Laplace transforms and applications

International Nuclear Information System (INIS)

Mughrabi, T.A.

1988-01-01

In this dissertation we establish new theorems for computing certain types of multidimensional Laplace transform pairs from known one-dimensional Laplace transforms. The theorems are applied to the most commonly used special functions and so we obtain many two and three dimensional Laplace transform pairs. As applications, some boundary value problems involving linear partial differential equations are solved by the use of multi-dimensional Laplace transformation. Also we establish some relations between the Laplace transformation and other integral transformation in two variables

A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF

Directory of Open Access Journals (Sweden)

Laëtitia Théron

2016-10-01

Full Text Available Mass spectrometry imaging (MSI is a powerful tool to visualize the spatial distribution of molecules on a tissue section. The main limitation of MALDI-MSI of proteins is the lack of direct identification. Therefore, this study focuses on a MSI~LC-MS/MS-LF workflow to link the results from MALDI-MSI with potential peak identification and label-free quantitation, using only one tissue section. At first, we studied the impact of matrix deposition and laser ablation on protein extraction from the tissue section. Then, we did a back-correlation of the m/z of the proteins detected by MALDI-MSI to those identified by label-free quantitation. This allowed us to compare the label-free quantitation of proteins obtained in LC-MS/MS with the peak intensities observed in MALDI-MSI. We managed to link identification to nine peaks observed by MALDI-MSI. The results showed that the MSI~LC-MS/MS-LF workflow (i allowed us to study a representative muscle proteome compared to a classical bottom-up workflow; and (ii was sparsely impacted by matrix deposition and laser ablation. This workflow, performed as a proof-of-concept, suggests that a single tissue section can be used to perform MALDI-MSI and protein extraction, identification, and relative quantitation.

The protein network surrounding the human telomere repeat binding factors TRF1, TRF2, and POT1.

Directory of Open Access Journals (Sweden)

Richard J Giannone

2010-08-01

Full Text Available Telomere integrity (including telomere length and capping is critical in overall genomic stability. Telomere repeat binding factors and their associated proteins play vital roles in telomere length regulation and end protection. In this study, we explore the protein network surrounding telomere repeat binding factors, TRF1, TRF2, and POT1 using dual-tag affinity purification in combination with multidimensional protein identification technology liquid chromatography--tandem mass spectrometry (MudPIT LC-MS/MS. After control subtraction and data filtering, we found that TRF2 and POT1 co-purified all six members of the telomere protein complex, while TRF1 identified five of six components at frequencies that lend evidence towards the currently accepted telomere architecture. Many of the known TRF1 or TRF2 interacting proteins were also identified. Moreover, putative associating partners identified for each of the three core components fell into functional categories such as DNA damage repair, ubiquitination, chromosome cohesion, chromatin modification/remodeling, DNA replication, cell cycle and transcription regulation, nucleotide metabolism, RNA processing, and nuclear transport. These putative protein-protein associations may participate in different biological processes at telomeres or, intriguingly, outside telomeres.

Contributions to multidimensional quadrature formulas

International Nuclear Information System (INIS)

Guenther, C.

1976-11-01

The general objective of this paper is to construct multidimensional quadrature formulas similar to the Gaussian Quadrature Formulas in one dimension. The correspondence between these formulas and orthogonal and nonnegative polynomials is established. One part of the paper considers the construction of multidimensional quadrature formulas using only methods of algebraic geometry, on the other part it is tried to obtain results on quadrature formulas with real nodes and, if possible, with positive weights. The results include the existence of quadrature formulas, information on the number resp. on the maximum possible number of points in the formulas for given polynomial degree N and the construction of formulas. (orig.) [de

Supervised and Unsupervised Learning of Multidimensional Acoustic Categories

Science.gov (United States)

Goudbeek, Martijn; Swingley, Daniel; Smits, Roel

2009-01-01

Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributionally defined visual categories has shown that categories defined over 1 dimension are easy to learn and that learning multidimensional categories is…

Channel identification machines.

Science.gov (United States)

Lazar, Aurel A; Slutskiy, Yevgeniy B

2012-01-01

We present a formal methodology for identifying a channel in a system consisting of a communication channel in cascade with an asynchronous sampler. The channel is modeled as a multidimensional filter, while models of asynchronous samplers are taken from neuroscience and communications and include integrate-and-fire neurons, asynchronous sigma/delta modulators and general oscillators in cascade with zero-crossing detectors. We devise channel identification algorithms that recover a projection of the filter(s) onto a space of input signals loss-free for both scalar and vector-valued test signals. The test signals are modeled as elements of a reproducing kernel Hilbert space (RKHS) with a Dirichlet kernel. Under appropriate limiting conditions on the bandwidth and the order of the test signal space, the filter projection converges to the impulse response of the filter. We show that our results hold for a wide class of RKHSs, including the space of finite-energy bandlimited signals. We also extend our channel identification results to noisy circuits.

Channel Identification Machines

Directory of Open Access Journals (Sweden)

Aurel A. Lazar

2012-01-01

Full Text Available We present a formal methodology for identifying a channel in a system consisting of a communication channel in cascade with an asynchronous sampler. The channel is modeled as a multidimensional filter, while models of asynchronous samplers are taken from neuroscience and communications and include integrate-and-fire neurons, asynchronous sigma/delta modulators and general oscillators in cascade with zero-crossing detectors. We devise channel identification algorithms that recover a projection of the filter(s onto a space of input signals loss-free for both scalar and vector-valued test signals. The test signals are modeled as elements of a reproducing kernel Hilbert space (RKHS with a Dirichlet kernel. Under appropriate limiting conditions on the bandwidth and the order of the test signal space, the filter projection converges to the impulse response of the filter. We show that our results hold for a wide class of RKHSs, including the space of finite-energy bandlimited signals. We also extend our channel identification results to noisy circuits.

Binomial probability distribution model-based protein identification algorithm for tandem mass spectrometry utilizing peak intensity information.

Science.gov (United States)

Xiao, Chuan-Le; Chen, Xiao-Zhou; Du, Yang-Li; Sun, Xuesong; Zhang, Gong; He, Qing-Yu

2013-01-04

Mass spectrometry has become one of the most important technologies in proteomic analysis. Tandem mass spectrometry (LC-MS/MS) is a major tool for the analysis of peptide mixtures from protein samples. The key step of MS data processing is the identification of peptides from experimental spectra by searching public sequence databases. Although a number of algorithms to identify peptides from MS/MS data have been already proposed, e.g. Sequest, OMSSA, X!Tandem, Mascot, etc., they are mainly based on statistical models considering only peak-matches between experimental and theoretical spectra, but not peak intensity information. Moreover, different algorithms gave different results from the same MS data, implying their probable incompleteness and questionable reproducibility. We developed a novel peptide identification algorithm, ProVerB, based on a binomial probability distribution model of protein tandem mass spectrometry combined with a new scoring function, making full use of peak intensity information and, thus, enhancing the ability of identification. Compared with Mascot, Sequest, and SQID, ProVerB identified significantly more peptides from LC-MS/MS data sets than the current algorithms at 1% False Discovery Rate (FDR) and provided more confident peptide identifications. ProVerB is also compatible with various platforms and experimental data sets, showing its robustness and versatility. The open-source program ProVerB is available at http://bioinformatics.jnu.edu.cn/software/proverb/ .

Extended wavelength anisotropy resolved multidimensional emission spectroscopy (ARMES) measurements: better filters, validation standards, and Rayleigh scatter removal methods

Science.gov (United States)

Casamayou-Boucau, Yannick; Ryder, Alan G.

2017-09-01

Anisotropy resolved multidimensional emission spectroscopy (ARMES) provides valuable insights into multi-fluorophore proteins (Groza et al 2015 Anal. Chim. Acta 886 133-42). Fluorescence anisotropy adds to the multidimensional fluorescence dataset information about the physical size of the fluorophores and/or the rigidity of the surrounding micro-environment. The first ARMES studies used standard thin film polarizers (TFP) that had negligible transmission between 250 and 290 nm, preventing accurate measurement of intrinsic protein fluorescence from tyrosine and tryptophan. Replacing TFP with pairs of broadband wire grid polarizers enabled standard fluorescence spectrometers to accurately measure anisotropies between 250 and 300 nm, which was validated with solutions of perylene in the UV and Erythrosin B and Phloxine B in the visible. In all cases, anisotropies were accurate to better than ±1% when compared to literature measurements made with Glan Thompson or TFP polarizers. Better dual wire grid polarizer UV transmittance and the use of excitation-emission matrix measurements for ARMES required complete Rayleigh scatter elimination. This was achieved by chemometric modelling rather than classical interpolation, which enabled the acquisition of pure anisotropy patterns over wider spectral ranges. In combination, these three improvements permit the accurate implementation of ARMES for studying intrinsic protein fluorescence.

An approach to large scale identification of non-obvious structural similarities between proteins

Science.gov (United States)

Cherkasov, Artem; Jones, Steven JM

2004-01-01

Background A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy. Results The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors. The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity. Conclusion Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence. PMID:15147578

An approach to large scale identification of non-obvious structural similarities between proteins

Directory of Open Access Journals (Sweden)

Cherkasov Artem

2004-05-01

Full Text Available Abstract Background A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy. Results The method has been developed to identify pathogenic proteins with low sequence identity and high structural similarity to host analogues. Such protein structure relationships would be hypothesized to arise through convergent evolution or through ancient horizontal gene transfer events, now undetectable using current sequence alignment techniques. The pathogen proteins, which could mimic or interfere with host activities, would represent candidate virulence factors. The developed approach utilizes the numerical outputs from the sequence-structure threading. It identifies the potential structural similarity between a pair of proteins by correlating the threading scores of the corresponding two primary sequences against the library of the standard folds. This approach allowed up to 64% sensitivity and 99.9% specificity in distinguishing protein pairs with high structural similarity. Conclusion Preliminary results obtained by comparison of the genomes of Homo sapiens and several strains of Chlamydia trachomatis have demonstrated the potential usefulness of the method in the identification of bacterial proteins with known or potential roles in virulence.

Rapid identification of fluorochrome modification sites in proteins by LC ESI-Q-TOF mass spectrometry.

Science.gov (United States)

Manikwar, Prakash; Zimmerman, Tahl; Blanco, Francisco J; Williams, Todd D; Siahaan, Teruna J

2011-07-20

Conjugation of either a fluorescent dye or a drug molecule to the ε-amino groups of lysine residues of proteins has many applications in biology and medicine. However, this type of conjugation produces a heterogeneous population of protein conjugates. Because conjugation of fluorochrome or drug molecule to a protein may have deleterious effects on protein function, the identification of conjugation sites is necessary. Unfortunately, the identification process can be time-consuming and laborious; therefore, there is a need to develop a rapid and reliable way to determine the conjugation sites of the fluorescent label or drug molecule. In this study, the sites of conjugation of fluorescein-5'-isothiocyanate and rhodamine-B-isothiocyanate to free amino groups on the insert-domain (I-domain) protein derived from the α-subunit of lymphocyte function-associated antigen-1 (LFA-1) were determined by electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-Q-TOF MS) along with peptide mapping using trypsin digestion. A reporter fragment of the fluorochrome moiety that is generated in the collision cell of the Q-TOF without explicit MS/MS precursor selection was used to identify the conjugation site. Selected ion plots of the reporter ion readily mark modified peptides in chromatograms of the complex digest. Interrogation of theses spectra reveals a neutral loss/precursor pair that identifies the modified peptide. The results show that one to seven fluorescein molecules or one to four rhodamine molecules were attached to the lysine residue(s) of the I-domain protein. No modifications were found in the metal ion-dependent adhesion site (MIDAS), which is an important binding region of the I-domain.

Improving personality facet scores with multidimensional computer adaptive testing

DEFF Research Database (Denmark)

Makransky, Guido; Mortensen, Erik Lykke; Glas, Cees A W

2013-01-01

personality tests contain many highly correlated facets. This article investigates the possibility of increasing the precision of the NEO PI-R facet scores by scoring items with multidimensional item response theory and by efficiently administering and scoring items with multidimensional computer adaptive...

Top-Down and Bottom-Up Identification of Proteins by Liquid Extraction Surface Analysis Mass Spectrometry of Healthy and Diseased Human Liver Tissue

Science.gov (United States)

Sarsby, Joscelyn; Martin, Nicholas J.; Lalor, Patricia F.; Bunch, Josephine; Cooper, Helen J.

2014-09-01

Liquid extraction surface analysis mass spectrometry (LESA MS) has the potential to become a useful tool in the spatially-resolved profiling of proteins in substrates. Here, the approach has been applied to the analysis of thin tissue sections from human liver. The aim was to determine whether LESA MS was a suitable approach for the detection of protein biomarkers of nonalcoholic liver disease (nonalcoholic steatohepatitis, NASH), with a view to the eventual development of LESA MS for imaging NASH pathology. Two approaches were considered. In the first, endogenous proteins were extracted from liver tissue sections by LESA, subjected to automated trypsin digestion, and the resulting peptide mixture was analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS) (bottom-up approach). In the second (top-down approach), endogenous proteins were extracted by LESA, and analyzed intact. Selected protein ions were subjected to collision-induced dissociation (CID) and/or electron transfer dissociation (ETD) mass spectrometry. The bottom-up approach resulted in the identification of over 500 proteins; however identification of key protein biomarkers, liver fatty acid binding protein (FABP1), and its variant (Thr→Ala, position 94), was unreliable and irreproducible. Top-down LESA MS analysis of healthy and diseased liver tissue revealed peaks corresponding to multiple (~15-25) proteins. MS/MS of four of these proteins identified them as FABP1, its variant, α-hemoglobin, and 10 kDa heat shock protein. The reliable identification of FABP1 and its variant by top-down LESA MS suggests that the approach may be suitable for imaging NASH pathology in sections from liver biopsies.

Characterization of Atypical Off-Flavor Compounds in Natural Cork Stoppers by Multidimensional Gas Chromatographic Techniques.

Science.gov (United States)

Slabizki, Petra; Fischer, Claus; Legrum, Charlotte; Schmarr, Hans-Georg

2015-09-09

Natural cork stoppers with sensory deviations other than the typical cork taint were subgrouped according to their sensory descriptions and compared with unaffected control cork stoppers. The assessment of purge and trap extracts obtained from corresponding cork soaks was performed by heart-cut multidimensional gas chromatography-olfactometry (MDGC-O). The identification of compounds responsible for atypical cork taint detected in MDGC-O was further supported with additional multidimensional GC analysis in combination with mass spectrometric detection. Geosmin and 2-methylisoborneol were mainly found in cork stoppers described as moldy and cellarlike; 3-isopropyl-2-methoxypyrazine and 3-isobutyl-2-methoxypyrazine were found in cork stoppers described with green attributes. Across all cork subgroups, the impact compound for typical cork taint, 2,4,6-trichloroanisole (TCA), was present and is therefore a good marker for cork taint in general. Another potent aroma compound, 3,5-dimethyl-2-methoxypyrazine (MDMP), was also detected in each subgroup, obviously playing an important role with regard to the atypical cork taint. Sensory deviations possibly affecting the wine could be generated by MDMP and its presence should thus be monitored in routine quality control.

Identification of a tripartite import signal in the Ewing Sarcoma protein (EWS)

International Nuclear Information System (INIS)

Shaw, Debra J.; Morse, Robert; Todd, Adrian G.; Eggleton, Paul; Lorson, Christian L.; Young, Philip J.

2009-01-01

The Ewing Sarcoma (EWS) protein is a ubiquitously expressed RNA processing factor that localises predominantly to the nucleus. However, the mechanism through which EWS enters the nucleus remains unclear, with differing reports identifying three separate import signals within the EWS protein. Here we have utilized a panel of truncated EWS proteins to clarify the reported nuclear localisation signals. We describe three C-terminal domains that are important for efficient EWS nuclear localization: (1) the third RGG-motif; (2) the last 10 amino acids (known as the PY-import motif); and (3) the zinc-finger motif. Although these three domains are involved in nuclear import, they are not independently capable of driving the efficient import of a GFP-moiety. However, collectively they form a complex tripartite signal that efficiently drives GFP-import into the nucleus. This study helps clarify the EWS import signal, and the identification of the involvement of both the RGG- and zinc-finger motifs has wide reaching implications.

Identification of a tripartite import signal in the Ewing Sarcoma protein (EWS)

Energy Technology Data Exchange (ETDEWEB)

Shaw, Debra J.; Morse, Robert; Todd, Adrian G. [Clinical Neurobiology, IBCS, Peninsula College of Medicine and Dentistry, Exeter EX1 2LU (United Kingdom); Eggleton, Paul [Inflammation and Musculoskeletal Disease, IBCS, Peninsula College of Medicine and Dentistry, Exeter EX1 2LU (United Kingdom); MRC Immunochemistry Unit, University of Oxford, Oxford OX1 3QU (United Kingdom); Lorson, Christian L. [Department of Veterinary Pathobiology, Bond Life Sciences Center, 1201 Rollins Road, University of Missouri, Columbia, MO 65211 (United States); Young, Philip J., E-mail: philip.young@pms.ac.uk [Clinical Neurobiology, IBCS, Peninsula College of Medicine and Dentistry, Exeter EX1 2LU (United Kingdom)

2009-12-25

The Ewing Sarcoma (EWS) protein is a ubiquitously expressed RNA processing factor that localises predominantly to the nucleus. However, the mechanism through which EWS enters the nucleus remains unclear, with differing reports identifying three separate import signals within the EWS protein. Here we have utilized a panel of truncated EWS proteins to clarify the reported nuclear localisation signals. We describe three C-terminal domains that are important for efficient EWS nuclear localization: (1) the third RGG-motif; (2) the last 10 amino acids (known as the PY-import motif); and (3) the zinc-finger motif. Although these three domains are involved in nuclear import, they are not independently capable of driving the efficient import of a GFP-moiety. However, collectively they form a complex tripartite signal that efficiently drives GFP-import into the nucleus. This study helps clarify the EWS import signal, and the identification of the involvement of both the RGG- and zinc-finger motifs has wide reaching implications.

Multi-Dimensional Aggregation for Temporal Data

DEFF Research Database (Denmark)

Böhlen, M. H.; Gamper, J.; Jensen, Christian Søndergaard

2006-01-01

Business Intelligence solutions, encompassing technologies such as multi-dimensional data modeling and aggregate query processing, are being applied increasingly to non-traditional data. This paper extends multi-dimensional aggregation to apply to data with associated interval values that capture...... that the data holds for each point in the interval, as well as the case where the data holds only for the entire interval, but must be adjusted to apply to sub-intervals. The paper reports on an implementation of the new operator and on an empirical study that indicates that the operator scales to large data...

Executive Information Systems' Multidimensional Models

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available Executive Information Systems are design to improve the quality of strategic level of management in organization through a new type of technology and several techniques for extracting, transforming, processing, integrating and presenting data in such a way that the organizational knowledge filters can easily associate with this data and turn it into information for the organization. These technologies are known as Business Intelligence Tools. But in order to build analytic reports for Executive Information Systems (EIS in an organization we need to design a multidimensional model based on the business model from the organization. This paper presents some multidimensional models that can be used in EIS development and propose a new model that is suitable for strategic business requests.

The Tunneling Method for Global Optimization in Multidimensional Scaling.

Science.gov (United States)

Groenen, Patrick J. F.; Heiser, Willem J.

1996-01-01

A tunneling method for global minimization in multidimensional scaling is introduced and adjusted for multidimensional scaling with general Minkowski distances. The method alternates a local search step with a tunneling step in which a different configuration is sought with the same STRESS implementation. (SLD)

Identification of Proteins with Potential Osteogenic Activity Present in the Water-Soluble Matrix Proteins from Crassostrea gigas Nacre Using a Proteomic Approach

Directory of Open Access Journals (Sweden)

Daniel V. Oliveira

2012-01-01

Full Text Available Nacre, when implanted in vivo in bones of dogs, sheep, mice, and humans, induces a biological response that includes integration and osteogenic activity on the host tissue that seems to be activated by a set of proteins present in the nacre water-soluble matrix (WSM. We describe here an experimental approach that can accurately identify the proteins present in the WSM of shell mollusk nacre. Four proteins (three gigasin-2 isoforms and a cystatin A2 were for the first time identified in WSM of Crassostrea gigas nacre using 2DE and LC-MS/MS for protein identification. These proteins are thought to be involved in bone remodeling processes and could be responsible for the biocompatibility shown between bone and nacre grafts. These results represent a contribution to the study of shell biomineralization process and opens new perspectives for the development of new nacre biomaterials for orthopedic applications.

A study of multidimensional modeling approaches for data warehouse

Science.gov (United States)

Yusof, Sharmila Mat; Sidi, Fatimah; Ibrahim, Hamidah; Affendey, Lilly Suriani

2016-08-01

Data warehouse system is used to support the process of organizational decision making. Hence, the system must extract and integrate information from heterogeneous data sources in order to uncover relevant knowledge suitable for decision making process. However, the development of data warehouse is a difficult and complex process especially in its conceptual design (multidimensional modeling). Thus, there have been various approaches proposed to overcome the difficulty. This study surveys and compares the approaches of multidimensional modeling and highlights the issues, trend and solution proposed to date. The contribution is on the state of the art of the multidimensional modeling design.

Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression

DEFF Research Database (Denmark)

Bergholdt, Regine; Brorsson, Caroline; Palleja, Albert

2012-01-01

Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated with dis......-cells. Our results provide novel insight to the mechanisms behind type 1 diabetes pathogenesis and, thus, may provide the basis for the design of novel treatment strategies.......Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated...... with disease, and they do not typically inform the broader context in which the disease genes operate. Here, we integrated type 1 diabetes GWAS data with protein-protein interactions to construct biological networks of relevance for disease. A total of 17 networks were identified. To prioritize...

Identification of a multi-protein reductive dehalogenase complex in Dehalococcoides mccartyi strain CBDB1 suggests a protein-dependent respiratory electron transport chain obviating quinone involvement

DEFF Research Database (Denmark)

Kublik, Anja; Deobald, Darja; Hartwig, Stefanie

2016-01-01

electrophoresis (BN-PAGE), gel filtration and ultrafiltration an active dehalogenating protein complex with a molecular mass of 250–270 kDa was identified. The active subunit of reductive dehalogenase (RdhA) colocalised with a complex iron-sulfur molybdoenzyme (CISM) subunit (CbdbA195) and an iron-sulfur cluster...... of the dehalogenating complex prior to membrane solubilisation. Taken together, the identification of the respiratory dehalogenase protein complex and the absence of indications for quinone participation in the respiration suggest a quinone-independent protein-based respiratory electron transfer chain in D. mccartyi....

Fatigue and multidimensional disease severity in chronic obstructive pulmonary disease

Directory of Open Access Journals (Sweden)

Inal-Ince Deniz

2010-06-01

Full Text Available Abstract Background and aims Fatigue is associated with longitudinal ratings of health in patients with chronic obstructive pulmonary disease (COPD. Although the degree of airflow obstruction is often used to grade disease severity in patients with COPD, multidimensional grading systems have recently been developed. The aim of this study was to investigate the relationship between perceived and actual fatigue level and multidimensional disease severity in patients with COPD. Materials and methods Twenty-two patients with COPD (aged 52-74 years took part in the study. Multidimensional disease severity was measured using the SAFE and BODE indices. Perceived fatigue was assessed using the Fatigue Severity Scale (FSS and the Fatigue Impact Scale (FIS. Peripheral muscle endurance was evaluated using the number of sit-ups, squats, and modified push-ups that each patient could do. Results Thirteen patients (59% had severe fatigue, and their St George's Respiratory Questionnaire scores were significantly higher (p Conclusions Peripheral muscle endurance and fatigue perception in patients with COPD was related to multidimensional disease severity measured with both the SAFE and BODE indices. Improvements in perceived and actual fatigue levels may positively affect multidimensional disease severity and health status in COPD patients. Further research is needed to investigate the effects of fatigue perception and exercise training on patients with different stages of multidimensional COPD severity.

Identification of compounds with binding affinity to proteins via magnetization transfer from bulk water

International Nuclear Information System (INIS)

Dalvit, Claudio; Pevarello, Paolo; Tato, Marco; Veronesi, Marina; Vulpetti, Anna; Sundstroem, Michael

2000-01-01

A powerful screening by NMR methodology (WaterLOGSY), based on transfer of magnetization from bulk water, for the identification of compounds that interact with target biomolecules (proteins, RNA and DNA fragments) is described. The method exploits efficiently the large reservoir of H 2 O magnetization. The high sensitivity of the technique reduces the amount of biomolecule and ligands needed for the screening, which constitutes an important requirement for high throughput screening by NMR of large libraries of compounds. Application of the method to a compound mixture against the cyclin-dependent kinase 2 (cdk2) protein is presented

Multidimensional nonlinear descriptive analysis

CERN Document Server

Nishisato, Shizuhiko

2006-01-01

Quantification of categorical, or non-numerical, data is a problem that scientists face across a wide range of disciplines. Exploring data analysis in various areas of research, such as the social sciences and biology, Multidimensional Nonlinear Descriptive Analysis presents methods for analyzing categorical data that are not necessarily sampled randomly from a normal population and often involve nonlinear relations. This reference not only provides an overview of multidimensional nonlinear descriptive analysis (MUNDA) of discrete data, it also offers new results in a variety of fields. The first part of the book covers conceptual and technical preliminaries needed to understand the data analysis in subsequent chapters. The next two parts contain applications of MUNDA to diverse data types, with each chapter devoted to one type of categorical data, a brief historical comment, and basic skills peculiar to the data types. The final part examines several problems and then concludes with suggestions for futu...

Chromatin Immunoprecipitation Assay for the Identification of Arabidopsis Protein-DNA Interactions In Vivo.

Science.gov (United States)

Komar, Dorota N; Mouriz, Alfonso; Jarillo, José A; Piñeiro, Manuel

2016-01-14

Intricate gene regulatory networks orchestrate biological processes and developmental transitions in plants. Selective transcriptional activation and silencing of genes mediate the response of plants to environmental signals and developmental cues. Therefore, insights into the mechanisms that control plant gene expression are essential to gain a deep understanding of how biological processes are regulated in plants. The chromatin immunoprecipitation (ChIP) technique described here is a procedure to identify the DNA-binding sites of proteins in genes or genomic regions of the model species Arabidopsis thaliana. The interactions with DNA of proteins of interest such as transcription factors, chromatin proteins or posttranslationally modified versions of histones can be efficiently analyzed with the ChIP protocol. This method is based on the fixation of protein-DNA interactions in vivo, random fragmentation of chromatin, immunoprecipitation of protein-DNA complexes with specific antibodies, and quantification of the DNA associated with the protein of interest by PCR techniques. The use of this methodology in Arabidopsis has contributed significantly to unveil transcriptional regulatory mechanisms that control a variety of plant biological processes. This approach allowed the identification of the binding sites of the Arabidopsis chromatin protein EBS to regulatory regions of the master gene of flowering FT. The impact of this protein in the accumulation of particular histone marks in the genomic region of FT was also revealed through ChIP analysis.

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity

OpenAIRE

Barkla, Bronwyn J.

2016-01-01

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may cont...

Multidimensional Physical Self-Concept of Athletes with Physical Disabilities

Science.gov (United States)

Shapiro, Deborah R.; Martin, Jeffrey J.

2010-01-01

The purposes of this investigation were first to predict reported PA (physical activity) behavior and self-esteem using a multidimensional physical self-concept model and second to describe perceptions of multidimensional physical self-concept (e.g., strength, endurance, sport competence) among athletes with physical disabilities. Athletes (N =…

Development of Multidimensional Gap Conductance model using Virtual Link Gap Element

Energy Technology Data Exchange (ETDEWEB)

Kim, Hyo Chan; Yang, Yong Sik; Kim, Dae Ho; Bang, Je Geon; Kim, Sun Ki; Koo, Yang Hyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2013-10-15

The gap conductance that determines temperature gradient between pellet and cladding can be quite sensitive to gap thickness. For instance, once the gap size increases up to several micrometers in certain region, difference of pellet surface temperatures increases up to 100 Kelvin. Therefore, iterative thermo-mechanical coupled analysis is required to solve temperature distribution throughout pellet and cladding. Recently, multidimensional fuel performance codes have been being developed in the advanced countries to evaluate thermal behavior of fuel for off normal conditions and DBA(design based accident) conditions using the Finite Element Method (FEM). FRAPCON-FRAPTRAN code system, which is well known as the verified and reliable code, incorporates 1D thermal module and multidimensional mechanical module. In this code, multidimensional gap conductance model is not applied. ALCYONE developed by CEA introduces equivalent heat convection coefficient that represents multidimensional gap conductance as a function of gap thickness. BISON, which is multidimensional fuel performance code developed by INL, owns multidimensional gap conductance model using projected thermal contact. In general, thermal contact algorithm is nonlinear calculation which is expensive approach numerically. The gap conductance model for multi-dimension is difficult issue in terms of convergence and nonlinearity because gap conductance is function of gap thickness which depends on mechanical analysis at each iteration step. In this paper, virtual link gap (VLG) element has been proposed to resolve convergence issue and nonlinear characteristic of multidimensional gap conductance. In terms of calculation accuracy and convergence efficiency, the proposed VLG model was evaluated. LWR fuel performance codes should incorporate thermo-mechanical loop to solve gap conductance problem, iteratively. However, gap conductance in multidimensional model is difficult issue owing to its nonlinearity and

Conservative Initial Mapping For Multidimensional Simulations of Stellar Explosions

International Nuclear Information System (INIS)

Chen, Ke-Jung; Heger, Alexander; Almgren, Ann

2012-01-01

Mapping one-dimensional stellar profiles onto multidimensional grids as initial conditions for hydrodynamics calculations can lead to numerical artifacts, one of the most severe of which is the violation of conservation laws for physical quantities such as energy and mass. Here we introduce a numerical scheme for mapping one-dimensional spherically-symmetric data onto multidimensional meshes so that these physical quantities are conserved. We validate our scheme by porting a realistic 1D Lagrangian stellar profile to the new multidimensional Eulerian hydro code CASTRO. Our results show that all important features in the profiles are reproduced on the new grid and that conservation laws are enforced at all resolutions after mapping.

Balanced sensitivity functions for tuning multi-dimensional Bayesian network classifiers

NARCIS (Netherlands)

Bolt, J.H.; van der Gaag, L.C.

Multi-dimensional Bayesian network classifiers are Bayesian networks of restricted topological structure, which are tailored to classifying data instances into multiple dimensions. Like more traditional classifiers, multi-dimensional classifiers are typically learned from data and may include

The Identification and Validation of Novel Small Proteins in Pseudomonas Putida KT-2440

DEFF Research Database (Denmark)

Yang, Xiaochen; Long, Katherine

2014-01-01

and activities and may lead to the discovery of novel antimicrobial agents. Our project focuses on the identification, validation and characterization of novel s-­‐proteins in the bacterium Pseudomonas putida KT-­2440. As there is virtually no information on s-­‐proteins in pseudomonads, the first step......, total protein samples are prepared, fractionated, and analyzed with mass spectrometry (MS/MS). The MS/MS data are compared to a custom database containing >80000 putative sORF sequences to identify candidates for validation. A total of 56 and 22 putative sORFs were obtained from MS/MS data...... and bioinformatics prediction, respectively, where there is no overlap between the putative sORFs obtained from the two approaches. The sequences encoding the putative sORFs will be integrated onto the Tn7 site on the chromosome as well as on a plasmid expression vector for validation....

Cluster Oriented Spatio Temporal Multidimensional Data Visualization of Earthquakes in Indonesia

Directory of Open Access Journals (Sweden)

Mohammad Nur Shodiq

2016-03-01

Full Text Available Spatio temporal data clustering is challenge task. The result of clustering data are utilized to investigate the seismic parameters. Seismic parameters are used to describe the characteristics of earthquake behavior. One of the effective technique to study multidimensional spatio temporal data is visualization. But, visualization of multidimensional data is complicated problem. Because, this analysis consists of observed data cluster and seismic parameters. In this paper, we propose a visualization system, called as IES (Indonesia Earthquake System, for cluster analysis, spatio temporal analysis, and visualize the multidimensional data of seismic parameters. We analyze the cluster analysis by using automatic clustering, that consists of get optimal number of cluster and Hierarchical K-means clustering. We explore the visual cluster and multidimensional data in low dimensional space visualization. We made experiment with observed data, that consists of seismic data around Indonesian archipelago during 2004 to 2014. Keywords: Clustering, visualization, multidimensional data, seismic parameters.

Multidimensional filter banks and wavelets research developments and applications

CERN Document Server

Levy, Bernard

1997-01-01

Multidimensional Filter Banks and Wavelets: Reserach Developments and Applications brings together in one place important contributions and up-to-date research results in this important area. Multidimensional Filter Banks and Wavelets: Research Developments and Applications serves as an excellent reference, providing insight into some of the most important research issues in the field.

On new physics searches with multidimensional differential shapes

Science.gov (United States)

Ferreira, Felipe; Fichet, Sylvain; Sanz, Veronica

2018-03-01

In the context of upcoming new physics searches at the LHC, we investigate the impact of multidimensional differential rates in typical LHC analyses. We discuss the properties of shape information, and argue that multidimensional rates bring limited information in the scope of a discovery, but can have a large impact on model discrimination. We also point out subtleties about systematic uncertainties cancellations and the Cauchy-Schwarz bound on interference terms.

Multidimensional human dynamics in mobile phone communications.

Science.gov (United States)

Quadri, Christian; Zignani, Matteo; Capra, Lorenzo; Gaito, Sabrina; Rossi, Gian Paolo

2014-01-01

In today's technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages). Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today's information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process.

Multidimensional human dynamics in mobile phone communications.

Directory of Open Access Journals (Sweden)

Christian Quadri

Full Text Available In today's technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages. Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today's information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process.

Fast multi-dimensional NMR by minimal sampling

Science.gov (United States)

Kupče, Ēriks; Freeman, Ray

2008-03-01

A new scheme is proposed for very fast acquisition of three-dimensional NMR spectra based on minimal sampling, instead of the customary step-wise exploration of all of evolution space. The method relies on prior experiments to determine accurate values for the evolving frequencies and intensities from the two-dimensional 'first planes' recorded by setting t1 = 0 or t2 = 0. With this prior knowledge, the entire three-dimensional spectrum can be reconstructed by an additional measurement of the response at a single location (t1∗,t2∗) where t1∗ and t2∗ are fixed values of the evolution times. A key feature is the ability to resolve problems of overlap in the acquisition dimension. Applied to a small protein, agitoxin, the three-dimensional HNCO spectrum is obtained 35 times faster than systematic Cartesian sampling of the evolution domain. The extension to multi-dimensional spectroscopy is outlined.

Multiple pathways to identification: exploring the multidimensionality of academic identity formation in ethnic minority males.

Science.gov (United States)

Matthews, Jamaal S

2014-04-01

Empirical trends denote the academic underachievement of ethnic minority males across various academic domains. Identity-based explanations for this persistent phenomenon describe ethnic minority males as disidentified with academics, alienated, and oppositional. The present work interrogates these theoretical explanations and empirically substantiates a multidimensional lens for discussing academic identity formation within 330 African American and Latino early-adolescent males. Both hierarchical and iterative person-centered methods were utilized and reveal 5 distinct profiles derived from 6 dimensions of academic identity. These profiles predict self-reported classroom grades, mastery orientation, and self-handicapping in meaningful and varied ways. The results demonstrate multiple pathways to motivation and achievement, challenging previous oversimplified stereotypes of marginalized males. This exploratory study triangulates unique interpersonal and intrapersonal attributes for promoting healthy identity development and academic achievement among ethnic minority adolescent males.

Identification and quantification of major bovine milk proteins by liquid chromatography.

Science.gov (United States)

Bordin, G; Cordeiro Raposo, F; de la Calle, B; Rodriguez, A R

2001-08-31

In the field of food quality, bovine milk products are of particular interest due to the social and economic importance of the dairy products market. However, the risk of fraudulent manipulation is high in this area, for instance, replacing milk powder by whey is very interesting from an economic point of view. Therefore, there is a need to have suitable analytical methods available for the determination of all milk components, which is currently not the case, especially for the main proteins. The detection of potential manipulations requires then a clear analytical characterisation of each type of bovine milk, what constitutes the goal of this work. The separation of the major milk proteinic components has been carried out by ion-pair reversed-phase HPLC with photodiode array detection, using a C4 column. The overall optimisation has been achieved using a statistical experimental design procedure. The identification of each protein was ascertained using retention times, peak area ratios and second derivative UV spectra. Quantification was based on calibration curves drawn using purified proteins. Major sources of uncertainty were identified and the full uncertainty budget was established. The procedure was initially developed using the skimmed milk powder certified reference material CRM 063R and then applied to various types of commercial milks as well as to raw milk. The method is able to separate and quantify the seven major proteins (K-casein, alphas2-casein, alphas1-casein, beta-casein, alpha-lactalbumin, beta-lactoglobulin B and beta-lactoglobulin A) in one run and also to provide precise determinations of the total protein concentration. These are important results towards the further development of a reference method for major proteins in milk. In addition, the use of a certified material reference is suggested in order to make comparisons of method performances possible.

Identification of herpesvirus proteins that contribute to G1/S arrest.

Science.gov (United States)

Paladino, Patrick; Marcon, Edyta; Greenblatt, Jack; Frappier, Lori

2014-04-01

Lytic infection by herpesviruses induces cell cycle arrest at the G1/S transition. This appears to be a function of multiple herpesvirus proteins, but only a minority of herpesvirus proteins have been examined for cell cycle effects. To gain a more comprehensive understanding of the viral proteins that contribute to G1/S arrest, we screened a library of over 200 proteins from herpes simplex virus type 1, human cytomegalovirus, and Epstein-Barr virus (EBV) for effects on the G1/S interface, using HeLa fluorescent, ubiquitination-based cell cycle indicator (Fucci) cells in which G1/S can be detected colorimetrically. Proteins from each virus were identified that induce accumulation of G1/S cells, predominantly tegument, early, and capsid proteins. The identification of several capsid proteins in this screen suggests that incoming viral capsids may function to modulate cellular processes. The cell cycle effects of selected EBV proteins were further verified and examined for effects on p53 and p21 as regulators of the G1/S transition. Two EBV replication proteins (BORF2 and BMRF1) were found to induce p53 but not p21, while a previously uncharacterized tegument protein (BGLF2) was found to induce p21 protein levels in a p53-independent manner. Proteomic analyses of BGLF2-interacting proteins identified interactions with the NIMA-related protein kinase (NEK9) and GEM-interacting protein (GMIP). Silencing of either NEK9 or GMIP induced p21 without affecting p53 and abrogated the ability of BGLF2 to further induce p21. Collectively, these results suggest multiple viral proteins contribute to G1/S arrest, including BGLF2, which induces p21 levels likely by interfering with the functions of NEK9 and GMIP. Most people are infected with multiple herpesviruses, whose proteins alter the infected cells in several ways. During lytic infection, the viral proteins block cell proliferation just before the cellular DNA replicates. We used a novel screening method to identify proteins

Image matrix processor for fast multi-dimensional computations

Science.gov (United States)

Roberson, George P.; Skeate, Michael F.

1996-01-01

An apparatus for multi-dimensional computation which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination.

Identification and modification of dynamical regions in proteins for alteration of enzyme catalytic effect

Science.gov (United States)

Agarwal, Pratul K.

2013-04-09

A method for analysis, control, and manipulation for improvement of the chemical reaction rate of a protein-mediated reaction is provided. Enzymes, which typically comprise protein molecules, are very efficient catalysts that enhance chemical reaction rates by many orders of magnitude. Enzymes are widely used for a number of functions in chemical, biochemical, pharmaceutical, and other purposes. The method identifies key protein vibration modes that control the chemical reaction rate of the protein-mediated reaction, providing identification of the factors that enable the enzymes to achieve the high rate of reaction enhancement. By controlling these factors, the function of enzymes may be modulated, i.e., the activity can either be increased for faster enzyme reaction or it can be decreased when a slower enzyme is desired. This method provides an inexpensive and efficient solution by utilizing computer simulations, in combination with available experimental data, to build suitable models and investigate the enzyme activity.

Proteomic identification of early salicylate- and flg22-responsive redox-sensitive proteins in Arabidopsis

KAUST Repository

Liu, Peng

2015-02-27

Accumulation of reactive oxygen species (ROS) is one of the early defense responses against pathogen infection in plants. The mechanism about the initial and direct regulation of the defense signaling pathway by ROS remains elusive. Perturbation of cellular redox homeostasis by ROS is believed to alter functions of redox-sensitive proteins through their oxidative modifications. Here we report an OxiTRAQ-based proteomic study in identifying proteins whose cysteines underwent oxidative modifications in Arabidopsis cells during the early response to salicylate or flg22, two defense pathway elicitors that are known to disturb cellular redox homeostasis. Among the salicylate- and/or flg22-responsive redox-sensitive proteins are those involved in transcriptional regulation, chromatin remodeling, RNA processing, post-translational modifications, and nucleocytoplasmic shuttling. The identification of the salicylate-/flg22-responsive redox-sensitive proteins provides a foundation from which further study can be conducted toward understanding biological significance of their oxidative modifications during the plant defense response.

Detection of protein-protein interactions by ribosome display and protein in situ immobilisation.

Science.gov (United States)

He, Mingyue; Liu, Hong; Turner, Martin; Taussig, Michael J

2009-12-31

We describe a method for identification of protein-protein interactions by combining two cell-free protein technologies, namely ribosome display and protein in situ immobilisation. The method requires only PCR fragments as the starting material, the target proteins being made through cell-free protein synthesis, either associated with their encoding mRNA as ribosome complexes or immobilised on a solid surface. The use of ribosome complexes allows identification of interacting protein partners from their attached coding mRNA. To demonstrate the procedures, we have employed the lymphocyte signalling proteins Vav1 and Grb2 and confirmed the interaction between Grb2 and the N-terminal SH3 domain of Vav1. The method has promise for library screening of pairwise protein interactions, down to the analytical level of individual domain or motif mapping.

Use of ribosomal proteins as biomarkers for identification of Flavobacterium psychrophilum by MALDI-TOF mass spectrometry.

Science.gov (United States)

Fernández-Álvarez, Clara; Torres-Corral, Yolanda; Santos, Ysabel

2018-01-06

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) is a rapid methodology for identification of bacteria that is increasingly used in diagnostic laboratories. This work aimed at evaluating the potential of MALDI-TOF-MS for identification of the main serotypes of Flavobacterium psychrophilum isolated from salmonids, and its discrimination from closely related Flavobacterium spp. A mass spectra library was constructed by analysing 70 F. psychrophilum strains representing the serotypes O1, O2a, O2b and O3, including reference and clinical isolates. Peak mass lists were examined using the Mass-Up software for the detection of potential biomarkers, similarity and cluster analysis. Fourteen species-identifying biomarkers were detected in all the F. psychrophilum isolates tested, moreover, sets of serotype-identifying biomarkers ions were selected. F. psychrophilum-specific biomarkers were identified as ribosomal proteins by matching with protein databases. Furthermore, sequence variation corresponding to amino acid exchanges in several biomarker proteins were tentatively assigned. Closely related Flavobacterium species (F. flevense, F. succinicans, F. columnare, F. branchiophilum and F. johnsoniae) could be differentiated from F. psychrophilum by defining species identifying biomarkers and hierarchical cluster analysis. These results demonstrated that MALDI-TOF spectrometry represents a powerful tool for an accurate identification of the fish pathogen F. psychrophilum as well as for epidemiological studies. The results obtained in this study demonstrated that MALDI-TOF mass spectrometry represents a powerful tool that can be used by diagnostic laboratories for rapid identification of the fish pathogen Flavobacterium psychrophilum and its differentiation from other Flavobacterium-related species. Analysis of mass peak lists revealed the potential of the MALDI-TOF technique to identify epidemiologically important serotypes affecting

Structural studies of bacterial transcriptional regulatory proteins by multidimensional heteronuclear NMR

Energy Technology Data Exchange (ETDEWEB)

Volkman, Brian Finley [Univ. of California, Berkeley, CA (United States)

1995-02-01

Nuclear magnetic resonance spectroscopy was used to elucidate detailed structural information for peptide and protein molecules. A small peptide was designed and synthesized, and its three-dimensional structure was calculated using distance information derived from two-dimensional NMR measurements. The peptide was used to induce antibodies in mice, and the cross-reactivity of the antibodies with a related protein was analyzed with enzyme-linked immunosorbent assays. Two proteins which are involved in regulation of transcription in bacteria were also studied. The ferric uptake regulation (Fur) protein is a metal-dependent repressor which controls iron uptake in bacteria. Two- and three-dimensional NMR techniques, coupled with uniform and selective isotope labeling allowed the nearly complete assignment of the resonances of the metal-binding domain of the Fur protein. NTRC is a transcriptional enhancer binding protein whose N-terminal domain is a "receiver domain" in the family of "two-component" regulatory systems. Phosphorylation of the N-terminal domain of NTRC activates the initiation of transcription of aeries encoding proteins involved in nitrogen regulation. Three- and four-dimensional NMR spectroscopy methods have been used to complete the resonance assignments and determine the solution structure of the N-terminal receiver domain of the NTRC protein. Comparison of the solution structure of the NTRC receiver domain with the crystal structures of the homologous protein CheY reveals a very similar fold, with the only significant difference being the position of helix 4 relative to the rest of the protein. The determination of the structure of the NTRC receiver domain is the first step toward understanding a mechanism of signal transduction which is common to many bacterial regulatory systems.

Two multi-dimensional uncertainty relations

International Nuclear Information System (INIS)

Skala, L; Kapsa, V

2008-01-01

Two multi-dimensional uncertainty relations, one related to the probability density and the other one related to the probability density current, are derived and discussed. Both relations are stronger than the usual uncertainty relations for the coordinates and momentum

Benefits of Multidimensional Measures of Child Well Being in China.

Science.gov (United States)

Gatenio Gabel, Shirley; Zhang, Yiwei

2017-11-06

In recent decades, measures of child well-being have evolved from single dimension to multidimensional measures. Multi-dimensional measures deepen and broaden our understanding of child well-being and inform us of areas of neglect. Child well-being in China today is measured through proxy measures of household need. This paper discusses the evolution of child well-being measures more generally, explores the benefits of positive indicators and multiple dimensions in formulating policy, and then reviews efforts to date by the Chinese government, researchers, and non-governmental and intergovernmental organizations to develop comprehensive multidimensional measures of child well-being in China. The domains and their potential interactions, as well as data sources and availability, are presented. The authors believe that child well-being in China would benefit from the development of a multidimensional index and that there is sufficient data to develop such an index.

Identification of salivary mucin MUC7 binding proteins from Streptococcus gordonii

Directory of Open Access Journals (Sweden)

Thornton David J

2009-08-01

Full Text Available Abstract Background The salivary mucin MUC7 (previously known as MG2 can adhere to various strains of streptococci that are primary colonizers and predominant microorganisms of the oral cavity. Although there is a growing interest in interaction between oral pathogens and salivary mucins, studies reporting the specific binding sites on the bacteria are rather limited. Identification and characterization of the specific interacting proteins on the bacterial cell surface, termed adhesins, are crucial to further understand host-pathogen interactions. Results We demonstrate here, using purified MUC7 to overlay blots of SDS-extracts of Streptococcus gordonii cell surface proteins, 4 MUC7-binding bands, with apparent molecular masses of 62, 78, 84 and 133 kDa from the Streptococcus gordonii strain, PK488. Putative adhesins were identified by in-gel digestion and subsequent nanoLC-tandem mass spectrometry analysis of resultant peptides. The 62 kDa and 84 kDa bands were identified as elongation factor (EF Tu and EF-G respectively. The 78 kDa band was a hppA gene product; the 74 kDa oligopeptide-binding lipoprotein. The 133 kDa band contained two proteins; alpha enolase and DNA-directed RNA polymerase, beta' subunit. Some of these proteins, for example alpha enolase are expected to be intracellular, however, flow cytometric analysis confirmed its location on the bacterial surface. Conclusion Our data demonstrated that S. gordonii expressed a number of putative MUC7 recognizing proteins and these contribute to MUC7 mucin binding of this streptococcal strain.

Multivariate Identification of Background Contributions for the H ! tt

CERN Document Server

Andrejkovic, Janik Walter

2016-01-01

Within the H ! tt analysis it is very important to understand the background contamination in the signal region coming from events where a jet is misidentified as a hadronic tau (fake events). Currently, the fake rate method is used to estimate the number and distributions of fake events in the signal region. This method relies on the correct identification of different background types. The study presented in this report focuses on the use of boosted decision trees in order to identify different background types. It is shown how the addition of more input variables, leading to a multi-dimensional multi-classification task, improves the overall identification accuracy of the different background types.

Identification of active pocket and protein druggability within envelope glycoprotein GP2 from Ebola virus

Directory of Open Access Journals (Sweden)

Beuy Joob

2014-12-01

Full Text Available The drug searching for combating the present outbreak of Ebola virus infection is the urgent activity at present. Finding the new effective drug at present must base on the molecular analysis of the pathogenic virus. The in-depth analysis of the viral protein to find the binding site, active pocket is needed. Here, the authors analyzed the envelope glycoprotein GP2 from Ebola virus. Identification of active pocket and protein druggability within envelope glycoprotein GP2 from Ebola virus was done. According to this assessment, 7 active pockets with varied druggability could be identified.

Visual modeling in an analysis of multidimensional data

Science.gov (United States)

Zakharova, A. A.; Vekhter, E. V.; Shklyar, A. V.; Pak, A. J.

2018-01-01

The article proposes an approach to solve visualization problems and the subsequent analysis of multidimensional data. Requirements to the properties of visual models, which were created to solve analysis problems, are described. As a perspective direction for the development of visual analysis tools for multidimensional and voluminous data, there was suggested an active use of factors of subjective perception and dynamic visualization. Practical results of solving the problem of multidimensional data analysis are shown using the example of a visual model of empirical data on the current state of studying processes of obtaining silicon carbide by an electric arc method. There are several results of solving this problem. At first, an idea of possibilities of determining the strategy for the development of the domain, secondly, the reliability of the published data on this subject, and changes in the areas of attention of researchers over time.

Multidimensional Scaling Localization Algorithm in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Zhang Dongyang

2014-02-01

Full Text Available Due to the localization algorithm in large-scale wireless sensor network exists shortcomings both in positioning accuracy and time complexity compared to traditional localization algorithm, this paper presents a fast multidimensional scaling location algorithm. By positioning algorithm for fast multidimensional scaling, fast mapping initialization, fast mapping and coordinate transform can get schematic coordinates of node, coordinates Initialize of MDS algorithm, an accurate estimate of the node coordinates and using the PRORUSTES to analysis alignment of the coordinate and final position coordinates of nodes etc. There are four steps, and the thesis gives specific implementation steps of the algorithm. Finally, compared with stochastic algorithms and classical MDS algorithm experiment, the thesis takes application of specific examples. Experimental results show that: the proposed localization algorithm has fast multidimensional scaling positioning accuracy in ensuring certain circumstances, but also greatly improves the speed of operation.

Identification of Heat Shock Protein families and J-protein types by incorporating Dipeptide Composition into Chou's general PseAAC.

Science.gov (United States)

Ahmad, Saeed; Kabir, Muhammad; Hayat, Maqsood

2015-11-01

Heat Shock Proteins (HSPs) are the substantial ingredients for cell growth and viability, which are found in all living organisms. HSPs manage the process of folding and unfolding of proteins, the quality of newly synthesized proteins and protecting cellular homeostatic processes from environmental stress. On the basis of functionality, HSPs are categorized into six major families namely: (i) HSP20 or sHSP (ii) HSP40 or J-proteins types (iii) HSP60 or GroEL/ES (iv) HSP70 (v) HSP90 and (vi) HSP100. Identification of HSPs family and sub-family through conventional approaches is expensive and laborious. It is therefore, highly desired to establish an automatic, robust and accurate computational method for prediction of HSPs quickly and reliably. Regard, a computational model is developed for the prediction of HSPs family. In this model, protein sequences are formulated using three discrete methods namely: Split Amino Acid Composition, Pseudo Amino Acid Composition, and Dipeptide Composition. Several learning algorithms are utilized to choice the best one for high throughput computational model. Leave one out test is applied to assess the performance of the proposed model. The empirical results showed that support vector machine achieved quite promising results using Dipeptide Composition feature space. The predicted outcomes of proposed model are 90.7% accuracy for HSPs dataset and 97.04% accuracy for J-protein types, which are higher than existing methods in the literature so far. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Development of multi-dimensional body image scale for malaysian female adolescents.

Science.gov (United States)

Chin, Yit Siew; Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin

2008-01-01

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs.

Multidimensional Computerized Adaptive Testing for Indonesia Junior High School Biology

Science.gov (United States)

Kuo, Bor-Chen; Daud, Muslem; Yang, Chih-Wei

2015-01-01

This paper describes a curriculum-based multidimensional computerized adaptive test that was developed for Indonesia junior high school Biology. In adherence to the Indonesian curriculum of different Biology dimensions, 300 items was constructed, and then tested to 2238 students. A multidimensional random coefficients multinomial logit model was…

Identification of risks stemming from new communication technologies

DEFF Research Database (Denmark)

Lessis, Vasileios; Taylor, J.R.; Kozin, Igor

Advanced distributed communication technologies play an important role today in the control and maintenance of safety -critical systems. However, the excessively optimistic reliance on the new technology without ecognizing the threats against its successful functioning, being able to maintain...... proved to be effective tools in developing more reliable and robust systems. As technology is developing fast though, a new need for an effective hazard identification methodology has emerged. To enhance the predictive performance of hazard identification in advanced distributed communication systems, we...... have envisioned and currently developing a multilevel-multidimensional HAZOP methodology. The methodology introduces a new creative thinking stimulation model to substitute the conventional guideword-based approaches that is based on a multiple level and dimension exploration of the system under...

Analysis of Local Dependence and Multidimensionality in Graphical Loglinear Rasch Models

DEFF Research Database (Denmark)

Kreiner, Svend; Christensen, Karl Bang

2004-01-01

Local independence; Multidimensionality; Differential item functioning; Uniform local dependence and DIF; Graphical Rasch models; Loglinear Rasch model......Local independence; Multidimensionality; Differential item functioning; Uniform local dependence and DIF; Graphical Rasch models; Loglinear Rasch model...

Enhancing bioactive peptide release and identification using targeted enzymatic hydrolysis of milk proteins.

Science.gov (United States)

Nongonierma, Alice B; FitzGerald, Richard J

2018-06-01

Milk proteins have been extensively studied for their ability to yield a range of bioactive peptides following enzymatic hydrolysis/digestion. However, many hurdles still exist regarding the widespread utilization of milk protein-derived bioactive peptides as health enhancing agents for humans. These mostly arise from the fact that most milk protein-derived bioactive peptides are not highly potent. In addition, they may be degraded during gastrointestinal digestion and/or have a low intestinal permeability. The targeted release of bioactive peptides during the enzymatic hydrolysis of milk proteins may allow the generation of particularly potent bioactive hydrolysates and peptides. Therefore, the development of milk protein hydrolysates capable of improving human health requires, in the first instance, optimized targeted release of specific bioactive peptides. The targeted hydrolysis of milk proteins has been aided by a range of in silico tools. These include peptide cutters and predictive modeling linking bioactivity to peptide structure [i.e., molecular docking, quantitative structure activity relationship (QSAR)], or hydrolysis parameters [design of experiments (DOE)]. Different targeted enzymatic release strategies employed during the generation of milk protein hydrolysates are reviewed herein and their limitations are outlined. In addition, specific examples are provided to demonstrate how in silico tools may help in the identification and discovery of potent milk protein-derived peptides. It is anticipated that the development of novel strategies employing a range of in silico tools may help in the generation of milk protein hydrolysates containing potent and bioavailable peptides, which in turn may be used to validate their health promoting effects in humans. Graphical abstract The targeted enzymatic hydrolysis of milk proteins may allow the generation of highly potent and bioavailable bioactive peptides.

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

Energy Technology Data Exchange (ETDEWEB)

Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten [RWTH Aachen University, Chair for Nonlinear Dynamics, Steinbachstr. 15, 52047 Aachen (Germany); Gebhardt, Sascha [RWTH Aachen University, Virtual Reality Group, IT Center, Seffenter Weg 23, 52074 Aachen (Germany); Kuhlen, Torsten [Forschungszentrum Jülich GmbH, Institute for Advanced Simulation (IAS), Jülich Supercomputing Centre (JSC), Wilhelm-Johnen-Straße, 52425 Jülich (Germany); Schulz, Wolfgang [Fraunhofer, ILT Laser Technology, Steinbachstr. 15, 52047 Aachen (Germany)

2016-06-08

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.

Application of random coherence order selection in gradient-enhanced multidimensional NMR

International Nuclear Information System (INIS)

Bostock, Mark J.; Nietlispach, Daniel

2016-01-01

Development of multidimensional NMR is essential to many applications, for example in high resolution structural studies of biomolecules. Multidimensional techniques enable separation of NMR signals over several dimensions, improving signal resolution, whilst also allowing identification of new connectivities. However, these advantages come at a significant cost. The Fourier transform theorem requires acquisition of a grid of regularly spaced points to satisfy the Nyquist criterion, while frequency discrimination and acquisition of a pure phase spectrum require acquisition of both quadrature components for each time point in every indirect (non-acquisition) dimension, adding a factor of 2 N -1 to the number of free- induction decays which must be acquired, where N is the number of dimensions. Compressed sensing (CS) ℓ 1 -norm minimisation in combination with non-uniform sampling (NUS) has been shown to be extremely successful in overcoming the Nyquist criterion. Previously, maximum entropy reconstruction has also been used to overcome the limitation of frequency discrimination, processing data acquired with only one quadrature component at a given time interval, known as random phase detection (RPD), allowing a factor of two reduction in the number of points for each indirect dimension (Maciejewski et al. 2011 PNAS 108 16640). However, whilst this approach can be easily applied in situations where the quadrature components are acquired as amplitude modulated data, the same principle is not easily extended to phase modulated (P-/N-type) experiments where data is acquired in the form exp (iωt) or exp (-iωt), and which make up many of the multidimensional experiments used in modern NMR. Here we demonstrate a modification of the CS ℓ 1 -norm approach to allow random coherence order selection (RCS) for phase modulated experiments; we generalise the nomenclature for RCS and RPD as random quadrature detection (RQD). With this method, the power of RQD can be extended

Identification of immunogenic proteins and evaluation of four recombinant proteins as potential vaccine antigens from Vibrio anguillarum in flounder (Paralichthys olivaceus).

Science.gov (United States)

Xing, Jing; Xu, Hongsen; Wang, Yang; Tang, Xiaoqian; Sheng, Xiuzhen; Zhan, Wenbin

2017-05-31

Vibrio anguillarum is a severe bacterial pathogen that can infect a wide range of fish species. Identification of immunogenic proteins and development of vaccine are essential for disease prevention. In this study, immunogenic proteins were screened and identified from V. anguillarum, and then protective efficacy of the immunogenic proteins was evaluated. Immunogenic proteins in V. anguillarum whole cell were detected by Western blotting (WB) using immunized flounder (Paralichthys olivaceus) serum, and then identified by Mass spectrometry (MS). The recombinant proteins of four identified immunogenic proteins were produced and immunized to fish, and then percentages of surface membrane immunoglobulin-positive (sIg+) cells in peripheral blood lymphocytes (PBL), total antibodies, antibodies against V. anguillarum, antibodies against recombinant proteins and relative percent survival (RPS) were measured, respectively. The results showed that five immunogenic proteins, VAA, Groel, OmpU, PteF and SpK, were identified; their recombinant proteins, rOmpU, rGroel, rSpK and rVAA, could induce the proliferation of sIg+ cells in PBL and production of total antibodies, antibodies against V. anguillarum and antibodies against the recombinant proteins; their protection against V. anguillarum showed 64.86%, 72.97%, 21.62% and 78.38% RPS, respectively. The results revealed that the immunoproteomic technique using fish anti-V. anguillarum serum provided an efficient way to screen the immunogenic protein for vaccine antigen. Moreover, the rVAA, rGroel and rOmpU had potential to be vaccine candidates against V. anguillarum infection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multidimensional Databases and Data Warehousing

DEFF Research Database (Denmark)

Jensen, Christian S.; Pedersen, Torben Bach; Thomsen, Christian

The present book's subject is multidimensional data models and data modeling concepts as they are applied in real data warehouses. The book aims to present the most important concepts within this subject in a precise and understandable manner. The book's coverage of fundamental concepts includes...

A peptide affinity column for the identification of integrin alpha IIb-binding proteins.

Science.gov (United States)

Daxecker, Heide; Raab, Markus; Bernard, Elise; Devocelle, Marc; Treumann, Achim; Moran, Niamh

2008-03-01

To understand the regulation of integrin alpha(IIb)beta(3), a critical platelet adhesion molecule, we have developed a peptide affinity chromatography method using the known integrin regulatory motif, LAMWKVGFFKR. Using standard Fmoc chemistry, this peptide was synthesized onto a Toyopearl AF-Amino-650 M resin on a 6-aminohexanoic acid (Ahx) linker. Peptide density was controlled by acetylation of 83% of the Ahx amino groups. Four recombinant human proteins (CIB1, PP1, ICln and RN181), previously identified as binding to this integrin regulatory motif, were specifically retained by the column containing the integrin peptide but not by a column presenting an irrelevant peptide. Hemoglobin, creatine kinase, bovine serum albumin, fibrinogen and alpha-tubulin failed to bind under the chosen conditions. Immunodetection methods confirmed the binding of endogenous platelet proteins, including CIB1, PP1, ICln RN181, AUP-1 and beta3-integrin, from a detergent-free platelet lysate. Thus, we describe a reproducible method that facilitates the reliable extraction of specific integrin-binding proteins from complex biological matrices. This methodology may enable the sensitive and specific identification of proteins that interact with linear, membrane-proximal peptide motifs such as the integrin regulatory motif LAMWKVGFFKR.

Background elimination methods for multidimensional coincidence γ-ray spectra

International Nuclear Information System (INIS)

Morhac, M.

1997-01-01

In the paper new methods to separate useful information from background in one, two, three and multidimensional spectra (histograms) measured in large multidetector γ-ray arrays are derived. The sensitive nonlinear peak clipping algorithm is the basis of the methods for estimation of the background in multidimensional spectra. The derived procedures are simple and therefore have a very low cost in terms of computing time. (orig.)

Identification of Potential Plants Producing Tannin-protein Complex for a-amylase as Botanical Pesticide

Directory of Open Access Journals (Sweden)

Asriyah Firdausi

2013-05-01

Full Text Available Research  on  the  development  of  botanical  pesticides  should  be developed  through  new  methods,  such  as  by  inhibiting the  activity  of  digestive enzymes  by  secondary  metabolites.  The  aim  of  this  study  was  to  identify some  of  potential  plants  as  a  source  of  tannin-protein  complexes  to  inhibitthe  activity  of  - amylase.  The  study  of  identification  of  potential  plants producing  the  active  ingredient  tannin-protein  complex  was  divided  into  three stages,  1  identification  of  potential  plants  producing  tannin,  2  isolation  of tannin-protein  complexes,  and  3  in  vitro  test  of  tannin-protein  complexes effect  of  the  -amylase activity.  Some  of  the observed  plants  were  sidaguri  leaf (Sida rhombifolia, melinjo leaf (Gnetum gnemon, gamal leaf (Gliricidia sepium,lamtoro  leaf  (Leucaena  leucocephala ,  betel  nut  (Areca  catechu ,  and  crude gambier  (Uncaria  gambir a s  a  source of  tannins  and  melinjo  seed was  used  asprotein  source.  Betel  nut  and  melinjo  seed  were  the  best  source  of  tannin-protein  complex,  tannin  content  1.77  mg  TAE/mL  with  antioxidant  activity  of  90%,the  ability  to  inhibit  the  activity  of  -amylase by  95%  with  IC 50  values  of 10 mg/mL.Key words: Tannin, protein, -amylase, botanical pesticides,Areca catechu, Gnetum gnemon.

Multidimensional Poverty and Health Status as a Predictor of Chronic Income Poverty.

Science.gov (United States)

Callander, Emily J; Schofield, Deborah J

2015-12-01

Longitudinal analysis of Wave 5 to 10 of the nationally representative Household, Income and Labour Dynamics in Australia dataset was undertaken to assess whether multidimensional poverty status can predict chronic income poverty. Of those who were multidimensionally poor (low income plus poor health or poor health and insufficient education attainment) in 2007, and those who were in income poverty only (no other forms of disadvantage) in 2007, a greater proportion of those in multidimensional poverty continued to be in income poverty for the subsequent 5 years through to 2012. People who were multidimensionally poor in 2007 had 2.17 times the odds of being in income poverty each year through to 2012 than those who were in income poverty only in 2005 (95% CI: 1.23-3.83). Multidimensional poverty measures are a useful tool for policymakers to identify target populations for policies aiming to improve equity and reduce chronic disadvantage. Copyright © 2014 John Wiley & Sons, Ltd.

A high-quality catalog of the Drosophila melanogaster proteome

DEFF Research Database (Denmark)

Brunner, Erich; Ahrens, Christian H.; Mohanty, Sonaly

2007-01-01

% of the predicted Drosophila melanogaster proteome by detecting 9,124 proteins from 498,000 redundant and 72,281 distinct peptide identifications. This unprecedented high proteome coverage for a complex eukaryote was achieved by combining sample diversity, multidimensional biochemical fractionation and analysis...

FPGA Implementation for GMM-Based Speaker Identification

Directory of Open Access Journals (Sweden)

Phaklen EhKan

2011-01-01

Full Text Available In today's society, highly accurate personal identification systems are required. Passwords or pin numbers can be forgotten or forged and are no longer considered to offer a high level of security. The use of biological features, biometrics, is becoming widely accepted as the next level for security systems. Biometric-based speaker identification is a method of identifying persons from their voice. Speaker-specific characteristics exist in speech signals due to different speakers having different resonances of the vocal tract. These differences can be exploited by extracting feature vectors such as Mel-Frequency Cepstral Coefficients (MFCCs from the speech signal. A well-known statistical modelling process, the Gaussian Mixture Model (GMM, then models the distribution of each speaker's MFCCs in a multidimensional acoustic space. The GMM-based speaker identification system has features that make it promising for hardware acceleration. This paper describes the hardware implementation for classification of a text-independent GMM-based speaker identification system. The aim was to produce a system that can perform simultaneous identification of large numbers of voice streams in real time. This has important potential applications in security and in automated call centre applications. A speedup factor of ninety was achieved compared to a software implementation on a standard PC.

Serum protein identification and quantification of the corona of 5, 15 and 80 nm gold nanoparticles

International Nuclear Information System (INIS)

Schäffler, Martin; Semmler-Behnke, Manuela; Takenaka, Shinji; Wenk, Alexander; Schleh, Carsten; Johnston, Blair D; Kreyling, Wolfgang G; Sarioglu, Hakan; Hauck, Stefanie M

2013-01-01

When nanoparticles (NP) enter the body they come into contact with body fluids containing proteins which can adsorb to their surface. These proteins may influence the NP interactions with the biological vicinity, eventually determining their biological fate inside the body. Adsorption of the most abundantly binding proteins was studied after an in vitro 24 hr incubation of monodisperse, negatively charged 5, 15 and 80 nm gold spheres (AuNP) in mouse serum by a two-step analysis: proteomic protein identification and quantitative protein biochemistry. The adsorbed proteins were separated from non-adsorbed proteins by centrifugation and gel electrophoresis and identified using a MALDI-TOF-MS-Proteomics-Analyzer. Quantitative analysis of proteins in gel bands by protein densitometry, required the focus on predominantly binding serum proteins. Numerous proteins adsorbed to the AuNP depending on their size, e.g. apolipoproteins or complement C3. The qualitative and quantitative amount of adsorbed proteins differed between 5, 15 and 80 nm AuNP. Band intensities of adsorbed proteins decreased with increasing AuNP sizes based not only on their mass but also on their surface area. Summarizing, the AuNP surface is covered with serum proteins containing transport and immune related proteins among others. Hence, protein binding depends on the size, surface area and curvature of the AuNP. (paper)

Towards Optimal Multi-Dimensional Query Processing with BitmapIndices

Energy Technology Data Exchange (ETDEWEB)

Rotem, Doron; Stockinger, Kurt; Wu, Kesheng

2005-09-30

Bitmap indices have been widely used in scientific applications and commercial systems for processing complex, multi-dimensional queries where traditional tree-based indices would not work efficiently. This paper studies strategies for minimizing the access costs for processing multi-dimensional queries using bitmap indices with binning. Innovative features of our algorithm include (a) optimally placing the bin boundaries and (b) dynamically reordering the evaluation of the query terms. In addition, we derive several analytical results concerning optimal bin allocation for a probabilistic query model. Our experimental evaluation with real life data shows an average I/O cost improvement of at least a factor of 10 for multi-dimensional queries on datasets from two different applications. Our experiments also indicate that the speedup increases with the number of query dimensions.

On plate graphite supported sample processing for simultaneous lipid and protein identification by matrix assisted laser desorption ionization mass spectrometry.

Science.gov (United States)

Calvano, Cosima Damiana; van der Werf, Inez Dorothé; Sabbatini, Luigia; Palmisano, Francesco

2015-05-01

The simultaneous identification of lipids and proteins by matrix assisted laser desorption ionization-mass spectrometry (MALDI-MS) after direct on-plate processing of micro-samples supported on colloidal graphite is demonstrated. Taking advantages of large surface area and thermal conductivity, graphite provided an ideal substrate for on-plate proteolysis and lipid extraction. Indeed proteins could be efficiently digested on-plate within 15 min, providing sequence coverages comparable to those obtained by conventional in-solution overnight digestion. Interestingly, detection of hydrophilic phosphorylated peptides could be easily achieved without any further enrichment step. Furthermore, lipids could be simultaneously extracted/identified without any additional treatment/processing step as demonstrated for model complex samples such as milk and egg. The present approach is simple, efficient, of large applicability and offers great promise for protein and lipid identification in very small samples. Copyright © 2015 Elsevier B.V. All rights reserved.

High Resolution Spectrometer (HRS) particle-identification system

International Nuclear Information System (INIS)

Pratt, J.C.; Spencer, J.E.; Whitten, C.A.

1977-08-01

The functions of the particle-identification system (PIDS) designed for the High Resolution Spectrometer facility (HRS) at LAMPF are described, together with the mechanical layout, counter hardware, and associated electronics. The system was designed for easy use and to be applicable to currently proposed experiments at HRS. The several strobe signals that can be generated correspond to different event types or characteristics, and logic configuration and timing can be remotely controlled by computer. Concepts of discrete pattern recognition and multidimensional, analog pulse discrimination are used to distinguish between different event types

Bifactor Approach to Modeling Multidimensionality of Physical Self-Perception Profile

Science.gov (United States)

Chung, ChihMing; Liao, Xiaolan; Song, Hairong; Lee, Taehun

2016-01-01

The multi-dimensionality of Physical Self-Perception Profile (PSPP) has been acknowledged by the use of correlated-factor model and second-order model. In this study, the authors critically endorse the bifactor model, as a substitute to address the multi-dimensionality of PSPP. To cross-validate the models, analyses are conducted first in…

Maximizing Selective Cleavages at Aspartic Acid and Proline Residues for the Identification of Intact Proteins

Science.gov (United States)

Foreman, David J.; Dziekonski, Eric T.; McLuckey, Scott A.

2018-04-01

A new approach for the identification of intact proteins has been developed that relies on the generation of relatively few abundant products from specific cleavage sites. This strategy is intended to complement standard approaches that seek to generate many fragments relatively non-selectively. Specifically, this strategy seeks to maximize selective cleavage at aspartic acid and proline residues via collisional activation of precursor ions formed via electrospray ionization (ESI) under denaturing conditions. A statistical analysis of the SWISS-PROT database was used to predict the number of arginine residues for a given intact protein mass and predict a m/z range where the protein carries a similar charge to the number of arginine residues thereby enhancing cleavage at aspartic acid residues by limiting proton mobility. Cleavage at aspartic acid residues is predicted to be most favorable in the m/z range of 1500-2500, a range higher than that normally generated by ESI at low pH. Gas-phase proton transfer ion/ion reactions are therefore used for precursor ion concentration from relatively high charge states followed by ion isolation and subsequent generation of precursor ions within the optimal m/z range via a second proton transfer reaction step. It is shown that the majority of product ion abundance is concentrated into cleavages C-terminal to aspartic acid residues and N-terminal to proline residues for ions generated by this process. Implementation of a scoring system that weights both ion fragment type and ion fragment area demonstrated identification of standard proteins, ranging in mass from 8.5 to 29.0 kDa. [Figure not available: see fulltext.

Applications of MALDI-TOF MS in Microbiological identification

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Soner Yilmaz

2014-10-01

Full Text Available MALDI-TOF MS (Matriks assisted laser desorption ionization time of flight mass spectrometry is a new metohod for identification of microorganisms nowadays. This method is based revealing of microorganisms protein profile with ionization of protein structure and these ionized mass pass through the electrical field. Profiles which were obtained from microorganisms compare with database of system thus identification is made by this way. Ribosomal proteins are used in identification which are less affected by enviromental conditions. Fresh culture should preferably use in MALDI-TOF MS identification. Ribosomal proteins can be deteriorate in old cultures. The correct identification rates are changing between 84,1% to 95,2% in routine bacterial isolates. The correct identification rates in yeasts are changing between 85% to 100%. It makes identification in positive blood culture bottles without the need of subculture, also makes identification on urine samples without the need of culture which has greater than 105 microorganisms in a microliter. When it compared with conventional and molecular identification methods, it is more effective on per sample costs and elapsed time on working [TAF Prev Med Bull 2014; 13(5.000: 421-426

Multidimensional quantum entanglement with large-scale integrated optics

DEFF Research Database (Denmark)

Wang, Jianwei; Paesani, Stefano; Ding, Yunhong

2018-01-01

-dimensional entanglement. A programmable bipartite entangled system is realized with dimension up to 15 × 15 on a large-scale silicon-photonics quantum circuit. The device integrates more than 550 photonic components on a single chip, including 16 identical photon-pair sources. We verify the high precision, generality......The ability to control multidimensional quantum systems is key for the investigation of fundamental science and for the development of advanced quantum technologies. We demonstrate a multidimensional integrated quantum photonic platform able to generate, control and analyze high...

Identification, characterization and antigenicity of the Plasmodium vivax rhoptry neck protein 1 (PvRON1

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Patarroyo Manuel E

2011-10-01

Full Text Available Abstract Background Plasmodium vivax malaria remains a major health problem in tropical and sub-tropical regions worldwide. Several rhoptry proteins which are important for interaction with and/or invasion of red blood cells, such as PfRONs, Pf92, Pf38, Pf12 and Pf34, have been described during the last few years and are being considered as potential anti-malarial vaccine candidates. This study describes the identification and characterization of the P. vivax rhoptry neck protein 1 (PvRON1 and examine its antigenicity in natural P. vivax infections. Methods The PvRON1 encoding gene, which is homologous to that encoding the P. falciparum apical sushi protein (ASP according to the plasmoDB database, was selected as our study target. The pvron1 gene transcription was evaluated by RT-PCR using RNA obtained from the P. vivax VCG-1 strain. Two peptides derived from the deduced P. vivax Sal-I PvRON1 sequence were synthesized and inoculated in rabbits for obtaining anti-PvRON1 antibodies which were used to confirm the protein expression in VCG-1 strain schizonts along with its association with detergent-resistant microdomains (DRMs by Western blot, and its localization by immunofluorescence assays. The antigenicity of the PvRON1 protein was assessed using human sera from individuals previously exposed to P. vivax malaria by ELISA. Results In the P. vivax VCG-1 strain, RON1 is a 764 amino acid-long protein. In silico analysis has revealed that PvRON1 shares essential characteristics with different antigens involved in invasion, such as the presence of a secretory signal, a GPI-anchor sequence and a putative sushi domain. The PvRON1 protein is expressed in parasite's schizont stage, localized in rhoptry necks and it is associated with DRMs. Recombinant protein recognition by human sera indicates that this antigen can trigger an immune response during a natural infection with P. vivax. Conclusions This study shows the identification and characterization of

Evaluation of mass spectrometric data using principal component analysis for determination of the effects of organic lakes on protein binder identification.

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Hrdlickova Kuckova, Stepanka; Rambouskova, Gabriela; Hynek, Radovan; Cejnar, Pavel; Oltrogge, Doris; Fuchs, Robert

2015-11-01

Matrix-assisted laser desorption/ionisation-time of flight (MALDI-TOF) mass spectrometry is commonly used for the identification of proteinaceous binders and their mixtures in artworks. The determination of protein binders is based on a comparison between the m/z values of tryptic peptides in the unknown sample and a reference one (egg, casein, animal glues etc.), but this method has greater potential to study changes due to ageing and the influence of organic/inorganic components on protein identification. However, it is necessary to then carry out statistical evaluation on the obtained data. Before now, it has been complicated to routinely convert the mass spectrometric data into a statistical programme, to extract and match the appropriate peaks. Only several 'homemade' computer programmes without user-friendly interfaces are available for these purposes. In this paper, we would like to present our completely new, publically available, non-commercial software, ms-alone and multiMS-toolbox, for principal component analyses of MALDI-TOF MS data for R software, and their application to the study of the influence of heterogeneous matrices (organic lakes) for protein identification. Using this new software, we determined the main factors that influence the protein analyses of artificially aged model mixtures of organic lakes and fish glue, prepared according to historical recipes that were used for book illumination, using MALDI-TOF peptide mass mapping. Copyright © 2015 John Wiley & Sons, Ltd.

Simulation of a Multidimensional Input Quantum Perceptron

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Yamamoto, Alexandre Y.; Sundqvist, Kyle M.; Li, Peng; Harris, H. Rusty

2018-06-01

In this work, we demonstrate the improved data separation capabilities of the Multidimensional Input Quantum Perceptron (MDIQP), a fundamental cell for the construction of more complex Quantum Artificial Neural Networks (QANNs). This is done by using input controlled alterations of ancillary qubits in combination with phase estimation and learning algorithms. The MDIQP is capable of processing quantum information and classifying multidimensional data that may not be linearly separable, extending the capabilities of the classical perceptron. With this powerful component, we get much closer to the achievement of a feedforward multilayer QANN, which would be able to represent and classify arbitrary sets of data (both quantum and classical).

On multidimensional item response theory -- a coordinate free approach

OpenAIRE

Antal, Tamás

2007-01-01

A coordinate system free definition of complex structure multidimensional item response theory (MIRT) for dichotomously scored items is presented. The point of view taken emphasizes the possibilities and subtleties of understanding MIRT as a multidimensional extension of the ``classical'' unidimensional item response theory models. The main theorem of the paper is that every monotonic MIRT model looks the same; they are all trivial extensions of univariate item response theory.

An Analysis of Multi-dimensional Gender Inequality in Pakistan

OpenAIRE

Abdul Hamid; Aisha M. Ahmed

2011-01-01

Women make almost half of the population of Pakistan. They also contribute significantly to economic and social growth. However, in developing countries like Pakistan, women usually suffer from multidimensional inequality of opportunities leading to multidimensional poverty. The dimensions of family, women identity, health, education and women access to economic resources and employment contribute significantly to the discrimination of women. The provision of more opportunities to women in th...

Proteomic Investigation of Falciparum and Vivax Malaria for Identification of Surrogate Protein Markers

Science.gov (United States)

Ray, Sandipan; Renu, Durairaj; Srivastava, Rajneesh; Gollapalli, Kishore; Taur, Santosh; Jhaveri, Tulip; Dhali, Snigdha; Chennareddy, Srinivasarao; Potla, Ankit; Dikshit, Jyoti Bajpai; Srikanth, Rapole; Gogtay, Nithya; Thatte, Urmila; Patankar, Swati; Srivastava, Sanjeeva

2012-01-01

This study was conducted to analyze alterations in the human serum proteome as a consequence of infection by malaria parasites Plasmodium falciparum and P. vivax to obtain mechanistic insights about disease pathogenesis, host immune response, and identification of potential protein markers. Serum samples from patients diagnosed with falciparum malaria (FM) (n = 20), vivax malaria (VM) (n = 17) and healthy controls (HC) (n = 20) were investigated using multiple proteomic techniques and results were validated by employing immunoassay-based approaches. Specificity of the identified malaria related serum markers was evaluated by means of analysis of leptospirosis as a febrile control (FC). Compared to HC, 30 and 31 differentially expressed and statistically significant (p<0.05) serum proteins were identified in FM and VM respectively, and almost half (46.2%) of these proteins were commonly modulated due to both of the plasmodial infections. 13 proteins were found to be differentially expressed in FM compared to VM. Functional pathway analysis involving the identified proteins revealed the modulation of different vital physiological pathways, including acute phase response signaling, chemokine and cytokine signaling, complement cascades and blood coagulation in malaria. A panel of identified proteins consists of six candidates; serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I was used to build statistical sample class prediction models. By employing PLS-DA and other classification methods the clinical phenotypic classes (FM, VM, FC and HC) were predicted with over 95% prediction accuracy. Individual performance of three classifier proteins; haptoglobin, apolipoprotein A-I and retinol-binding protein in diagnosis of malaria was analyzed using receiver operating characteristic (ROC) curves. The discrimination of FM, VM, FC and HC groups on the basis of differentially expressed serum proteins demonstrates

Proteomic investigation of falciparum and vivax malaria for identification of surrogate protein markers.

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Sandipan Ray

Full Text Available This study was conducted to analyze alterations in the human serum proteome as a consequence of infection by malaria parasites Plasmodium falciparum and P. vivax to obtain mechanistic insights about disease pathogenesis, host immune response, and identification of potential protein markers. Serum samples from patients diagnosed with falciparum malaria (FM (n = 20, vivax malaria (VM (n = 17 and healthy controls (HC (n = 20 were investigated using multiple proteomic techniques and results were validated by employing immunoassay-based approaches. Specificity of the identified malaria related serum markers was evaluated by means of analysis of leptospirosis as a febrile control (FC. Compared to HC, 30 and 31 differentially expressed and statistically significant (p<0.05 serum proteins were identified in FM and VM respectively, and almost half (46.2% of these proteins were commonly modulated due to both of the plasmodial infections. 13 proteins were found to be differentially expressed in FM compared to VM. Functional pathway analysis involving the identified proteins revealed the modulation of different vital physiological pathways, including acute phase response signaling, chemokine and cytokine signaling, complement cascades and blood coagulation in malaria. A panel of identified proteins consists of six candidates; serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I was used to build statistical sample class prediction models. By employing PLS-DA and other classification methods the clinical phenotypic classes (FM, VM, FC and HC were predicted with over 95% prediction accuracy. Individual performance of three classifier proteins; haptoglobin, apolipoprotein A-I and retinol-binding protein in diagnosis of malaria was analyzed using receiver operating characteristic (ROC curves. The discrimination of FM, VM, FC and HC groups on the basis of differentially expressed serum proteins demonstrates

Purification, identification and preliminary crystallographic studies of Pru du amandin, an allergenic protein from Prunus dulcis

International Nuclear Information System (INIS)

Gaur, Vineet; Sethi, Dhruv K.; Salunke, Dinakar M.

2007-01-01

The purification, identification, crystallization and preliminary crystallographic studies of an allergy-related protein, Pru du amandin, from P. dulcis nuts are reported. Food allergies appear to be one of the foremost causes of hypersensitivity reactions. Nut allergies account for most food allergies and are often permanent. The 360 kDa hexameric protein Pru du amandin, a known allergen, was purified from almonds (Prunus dulcis) by ammonium sulfate fractionation and ion-exchange chromatography. The protein was identified by a BLAST homology search against the nonredundant sequence database. Pru du amandin belongs to the 11S legumin family of seed storage proteins characterized by the presence of a cupin motif. Crystals were obtained by the hanging-drop vapour-diffusion method. The crystals belong to space group P4 1 (or P4 3 ), with unit-cell parameters a = b = 150.7, c = 164.9 Å

Large-scale proteomic identification of S100 proteins in breast cancer tissues

International Nuclear Information System (INIS)

Cancemi, Patrizia; Di Cara, Gianluca; Albanese, Nadia Ninfa; Costantini, Francesca; Marabeti, Maria Rita; Musso, Rosa; Lupo, Carmelo; Roz, Elena; Pucci-Minafra, Ida

2010-01-01

Attempts to reduce morbidity and mortality in breast cancer is based on efforts to identify novel biomarkers to support prognosis and therapeutic choices. The present study has focussed on S100 proteins as a potentially promising group of markers in cancer development and progression. One reason of interest in this family of proteins is because the majority of the S100 genes are clustered on a region of human chromosome 1q21 that is prone to genomic rearrangements. Moreover, there is increasing evidence that S100 proteins are often up-regulated in many cancers, including breast, and this is frequently associated with tumour progression. Samples of breast cancer tissues were obtained during surgical intervention, according to the bioethical recommendations, and cryo-preserved until used. Tissue extracts were submitted to proteomic preparations for 2D-IPG. Protein identification was performed by N-terminal sequencing and/or peptide mass finger printing. The majority of the detected S100 proteins were absent, or present at very low levels, in the non-tumoral tissues adjacent to the primary tumor. This finding strengthens the role of S100 proteins as putative biomarkers. The proteomic screening of 100 cryo-preserved breast cancer tissues showed that some proteins were ubiquitously expressed in almost all patients while others appeared more sporadic. Most, if not all, of the detected S100 members appeared reciprocally correlated. Finally, from the perspective of biomarkers establishment, a promising finding was the observation that patients which developed distant metastases after a three year follow-up showed a general tendency of higher S100 protein expression, compared to the disease-free group. This article reports for the first time the comparative proteomic screening of several S100 protein members among a large group of breast cancer patients. The results obtained strongly support the hypothesis that a significant deregulation of multiple S100 protein members is

A Multidimensional Software Engineering Course

Science.gov (United States)

Barzilay, O.; Hazzan, O.; Yehudai, A.

2009-01-01

Software engineering (SE) is a multidimensional field that involves activities in various areas and disciplines, such as computer science, project management, and system engineering. Though modern SE curricula include designated courses that address these various subjects, an advanced summary course that synthesizes them is still missing. Such a…

A review of snapshot multidimensional optical imaging: Measuring photon tags in parallel

Energy Technology Data Exchange (ETDEWEB)

Gao, Liang, E-mail: gaol@illinois.edu [Department of Electrical and Computer Engineering, University of Illinois at Urbana–Champaign, 306 N. Wright St., Urbana, IL 61801 (United States); Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana–Champaign, 405 North Mathews Avenue, Urbana, IL 61801 (United States); Wang, Lihong V., E-mail: lhwang@wustl.edu [Optical imaging laboratory, Department of Biomedical Engineering, Washington University in St. Louis, One Brookings Dr., MO, 63130 (United States)

2016-02-29

Multidimensional optical imaging has seen remarkable growth in the past decade. Rather than measuring only the two-dimensional spatial distribution of light, as in conventional photography, multidimensional optical imaging captures light in up to nine dimensions, providing unprecedented information about incident photons’ spatial coordinates, emittance angles, wavelength, time, and polarization. Multidimensional optical imaging can be accomplished either by scanning or parallel acquisition. Compared with scanning-based imagers, parallel acquisition–also dubbed snapshot imaging–has a prominent advantage in maximizing optical throughput, particularly when measuring a datacube of high dimensions. Here, we first categorize snapshot multidimensional imagers based on their acquisition and image reconstruction strategies, then highlight the snapshot advantage in the context of optical throughput, and finally we discuss their state-of-the-art implementations and applications.

Talent Identification and Development in Male Football: A Systematic Review.

Science.gov (United States)

Sarmento, Hugo; Anguera, M Teresa; Pereira, Antonino; Araújo, Duarte

2018-04-01

Expertise has been extensively studied in several sports over recent years. The specificities of how excellence is achieved in Association Football, a sport practiced worldwide, are being repeatedly investigated by many researchers through a variety of approaches and scientific disciplines. The aim of this review was to identify and synthesise the most significant literature addressing talent identification and development in football. We identified the most frequently researched topics and characterised their methodologies. A systematic review of Web of Science™ Core Collection and Scopus databases was performed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. The following keywords were used: "football" and "soccer". Each word was associated with the terms "talent", "expert*", "elite", "elite athlete", "identification", "career transition" or "career progression". The selection was for the original articles in English containing relevant data about talent development/identification on male footballers. The search returned 2944 records. After screening against set criteria, a total of 70 manuscripts were fully reviewed. The quality of the evidence reviewed was generally excellent. The most common topics of analysis were (1) task constraints: (a) specificity and volume of practice; (2) performers' constraints: (a) psychological factors; (b) technical and tactical skills; (c) anthropometric and physiological factors; (3) environmental constraints: (a) relative age effect; (b) socio-cultural influences; and (4) multidimensional analysis. Results indicate that the most successful players present technical, tactical, anthropometric, physiological and psychological advantages that change non-linearly with age, maturational status and playing positions. These findings should be carefully considered by those involved in the identification and development of football players. This review highlights the need for coaches

Molecular cloning of the gene for the human placental GTP-binding protein Gp (G25K): Identification of this GTP-binding protein as the human homolog of the yeast cell-division-cycle protein CDC42

International Nuclear Information System (INIS)

Shinjo, K.; Koland, J.G.; Hart, M.J.; Narasimhan, V.; Cerione, R.A.; Johnson, D.I.; Evans, T.

1990-01-01

The authors have isolated cDNA clones from a human placental library that code for a low molecular weight GTP-binding protein originally designated G p (also called G25K). This identification is based on comparisons with the available peptide sequences for the purified human G p protein and the use of two highly specific anti-peptide antibodies. The predicted amino acid sequence of the protein is very similar to those of various members of the ras superfamily of low molecular weight GTP-binding proteins, including the N-, Ki-, and Ha-ras proteins (30-35% identical), the rho proteins and the rac proteins. The highest degree of sequence identity (80%) is found with the Saccharomyces cerevisiae cell division-cycle protein CDC42. The human placental gene, which they designate CDC42Hs, complements the cdc42-1 mutation in S. cerevisiae, which suggests that this GTP-binding protein is the human homolog of the yeast protein

Identification of membrane-associated proteins with pathogenic potential expressed by Corynebacterium pseudotuberculosis grown in animal serum.

Science.gov (United States)

Raynal, José Tadeu; Bastos, Bruno Lopes; Vilas-Boas, Priscilla Carolinne Bagano; Sousa, Thiago de Jesus; Costa-Silva, Marcos; de Sá, Maria da Conceição Aquino; Portela, Ricardo Wagner; Moura-Costa, Lília Ferreira; Azevedo, Vasco; Meyer, Roberto

2018-01-25

Previous works defining antigens that might be used as vaccine targets against Corynebacterium pseudotuberculosis, which is the causative agent of sheep and goat caseous lymphadenitis, have focused on secreted proteins produced in a chemically defined culture media. Considering that such antigens might not reflect the repertoire of proteins expressed during infection conditions, this experiment aimed to investigate the membrane-associated proteins with pathogenic potential expressed by C. pseudotuberculosis grown directly in animal serum. Its membrane-associated proteins have been extracted using an organic solvent enrichment methodology, followed by LC-MS/MS and bioinformatics analysis for protein identification and classification. The results revealed 22 membrane-associated proteins characterized as potentially pathogenic. An interaction network analysis indicated that the four potentially pathogenic proteins ciuA, fagA, OppA4 and OppCD were biologically connected within two distinct network pathways, which were both associated with the ABC Transporters KEGG pathway. These results suggest that C. pseudotuberculosis pathogenesis might be associated with the transport and uptake of nutrients; other seven identified potentially pathogenic membrane proteins also suggest that pathogenesis might involve events of bacterial resistance and adhesion. The proteins herein reported potentially reflect part of the protein repertoire expressed during real infection conditions and might be tested as vaccine antigens.

Identification of Tyrosine Phosphorylated Proteins by SH2 Domain Affinity Purification and Mass Spectrometry.

Science.gov (United States)

Buhs, Sophia; Gerull, Helwe; Nollau, Peter

2017-01-01

Phosphotyrosine signaling plays a major role in the control of many important biological functions such as cell proliferation and apoptosis. Deciphering of phosphotyrosine-dependent signaling is therefore of great interest paving the way for the understanding of physiological and pathological processes of signal transduction. On the basis of the specific binding of SH2 domains to phosphotyrosine residues, we here present an experimental workflow for affinity purification and subsequent identification of tyrosine phosphorylated proteins by mass spectrometry. In combination with SH2 profiling, a broadly applicable platform for the characterization of phosphotyrosine profiles in cell extracts, our pull down strategy enables researchers by now to identify proteins in signaling cascades which are differentially phosphorylated and selectively recognized by distinct SH2 domains.

Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions.

Science.gov (United States)

Su, Min-Gang; Weng, Julia Tzu-Ya; Hsu, Justin Bo-Kai; Huang, Kai-Yao; Chi, Yu-Hsiang; Lee, Tzong-Yi

2017-12-21

tools for exploring the structural characteristics of PTMs, is presented. In addition, all tertiary structures of PTM sites on proteins can be visualized using the JSmol program. Resolving the function of PTM sites is important for understanding the role that proteins play in biological mechanisms. Our work attempted to delineate the structural correlation between PTM sites and PPI or drug-target binding. CurxPTM could help scientists narrow the scope of their PTM research and enhance the efficiency of PTM identification in the face of big proteome data. CruxPTM is now available at http://csb.cse.yzu.edu.tw/CruxPTM/ .

Identification of an exported heat shock protein 70 in Plasmodium falciparum

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Grover Manish

2013-01-01

Full Text Available Host cell remodelling is a hallmark of malaria pathogenesis. It involves protein folding, unfolding and trafficking events and thus participation of chaperones such as Hsp70s and Hsp40s is well speculated. Until recently, only Hsp40s were thought to be the sole representative of the parasite chaperones in the exportome. However, based on the re-annotated Plasmodium falciparum genome sequence, a putative candidate for exported Hsp70 has been reported, which otherwise was known to be a pseudogene. We raised a specific antiserum against a C-terminal peptide uniquely present in PfHsp70-x. Immunoblotting and immunofluorescence-based approaches in combination with sub-cellular fractionation by saponin and streptolysin-O have been taken to determine the expression and localization of PfHsp70-x in infected erythrocyte. The re-annotated sequence of PfHsp70-x reveals it to be a functional protein with an endoplasmic reticulum signal peptide. It gets maximally expressed at the schizont stage of intra-erythrocytic life cycle. Majority of the protein localizes to the parasitophorous vacuole and some of it gets exported to the erythrocyte compartment where it associates with Maurer’s clefts. The identification of an exported parasite Hsp70 chaperone presents us with the fact that the parasite has evolved customized chaperones which might be playing crucial roles in aspects of trafficking and host cell remodelling.

An effective approach for identification of in vivo protein-DNA binding sites from paired-end ChIP-Seq data

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Wilson Zoe A

2010-02-01

Full Text Available Abstract Background ChIP-Seq, which combines chromatin immunoprecipitation (ChIP with high-throughput massively parallel sequencing, is increasingly being used for identification of protein-DNA interactions in vivo in the genome. However, to maximize the effectiveness of data analysis of such sequences requires the development of new algorithms that are able to accurately predict DNA-protein binding sites. Results Here, we present SIPeS (Site Identification from Paired-end Sequencing, a novel algorithm for precise identification of binding sites from short reads generated by paired-end solexa ChIP-Seq technology. In this paper we used ChIP-Seq data from the Arabidopsis basic helix-loop-helix transcription factor ABORTED MICROSPORES (AMS, which is expressed within the anther during pollen development, the results show that SIPeS has better resolution for binding site identification compared to two existing ChIP-Seq peak detection algorithms, Cisgenome and MACS. Conclusions When compared to Cisgenome and MACS, SIPeS shows better resolution for binding site discovery. Moreover, SIPeS is designed to calculate the mappable genome length accurately with the fragment length based on the paired-end reads. Dynamic baselines are also employed to effectively discriminate closely adjacent binding sites, for effective binding sites discovery, which is of particular value when working with high-density genomes.

Health, Wealth and Wisdom: Exploring Multidimensional Inequality in a Developing Country

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Nilsson, Therese

2010-01-01

Despite a broad theoretical literature on multidimensional inequality and a widespread belief that welfare is not synonymous to income--not the least in a developing context--empirical inequality examinations rarely includes several welfare attributes. We explore three techniques on how to evaluate multidimensional inequality using Zambian…

Identification of α(1,6)fucosylated proteins differentially expressed in human colorectal cancer

International Nuclear Information System (INIS)

Muinelo-Romay, Laura; Villar-Portela, Susana; Cuevas, Elisa; Gil-Martín, Emilio; Fernández-Briera, Almudena

2011-01-01

A universal hallmark of cancer cells is the change in their glycosylation phenotype. One of the most frequent alterations in the normal glycosylation pattern observed during carcinogenesis is the enhancement of α(1,6)linked fucose residues of glycoproteins, due to the up-regulation of the α(1,6)fucosyltransferase activity. Our previous results demonstrated the specific alteration of this enzyme activity and expression in colorectal cancer, suggesting its implication in tumour development and progression. In the current work we combined a LCA-affinity chromatography with SDS-PAGE and mass spectrometry in order to identify α(1,6)fucosylated proteins differentially expressed in colorectal cancer. This strategy allowed the identification of a group of α(1,6)fucosylated proteins candidates to be involved in CRC malignancy. The majority of the identified proteins take part in cell signaling and interaction processes as well as in modulation of the immunological response. Likewise, we confirmed the increased expression of GRP94 in colorectal cancer tissue and the significant down-regulation of the IgGFcBP expression in tumour cells. All these results validate the importance of core-fucosylated proteins profile analysis to understand the mechanisms which promote cancer onset and progression and to discover new tumour markers or therapeutic targets

Recycling Behavior: A Multidimensional Approach

Science.gov (United States)

Meneses, Gonzalo Diaz; Palacio, Asuncion Beerli

2005-01-01

This work centers on the study of consumer recycling roles to examine the sociodemographic and psychographic profile of the distribution of recycling tasks and roles within the household. With this aim in mind, an empirical work was carried out, the results of which suggest that recycling behavior is multidimensional and comprises the undertaking…

Separation and identification of Musa acuminate Colla (banana) leaf proteins by two-dimensional gel electrophoresis and mass spectrometry.

Science.gov (United States)

Lu, Y; Qi, Y X; Zhang, H; Zhang, H Q; Pu, J J; Xie, Y X

2013-12-19

To establish a proteomic reference map of Musa acuminate Colla (banana) leaf, we separated and identified leaf proteins using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry (MS). Tryptic digests of 44 spots were subjected to peptide mass fingerprinting (PMF) by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS. Three spots that were not identified by MALDI-TOF MS analysis were identified by searching against the NCBInr, SwissProt, and expressed sequence tag (EST) databases. We identified 41 unique proteins. The majority of the identified leaf proteins were found to be involved in energy metabolism. The results indicate that 2D-PAGE is a sensitive and powerful technique for the separation and identification of Musa leaf proteins. A summary of the identified proteins and their putative functions is discussed.

Purification, identification and preliminary crystallographic studies of Pru du amandin, an allergenic protein from Prunus dulcis

Energy Technology Data Exchange (ETDEWEB)

Gaur, Vineet; Sethi, Dhruv K.; Salunke, Dinakar M., E-mail: dinakar@nii.res.in [National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110 067 (India)

2008-01-01

The purification, identification, crystallization and preliminary crystallographic studies of an allergy-related protein, Pru du amandin, from P. dulcis nuts are reported. Food allergies appear to be one of the foremost causes of hypersensitivity reactions. Nut allergies account for most food allergies and are often permanent. The 360 kDa hexameric protein Pru du amandin, a known allergen, was purified from almonds (Prunus dulcis) by ammonium sulfate fractionation and ion-exchange chromatography. The protein was identified by a BLAST homology search against the nonredundant sequence database. Pru du amandin belongs to the 11S legumin family of seed storage proteins characterized by the presence of a cupin motif. Crystals were obtained by the hanging-drop vapour-diffusion method. The crystals belong to space group P4{sub 1} (or P4{sub 3}), with unit-cell parameters a = b = 150.7, c = 164.9 Å.

Experimental strategies for the identification and characterization of adhesive proteins in animals: a review

Science.gov (United States)

Hennebert, Elise; Maldonado, Barbara; Ladurner, Peter; Flammang, Patrick; Santos, Romana

2015-01-01

Adhesive secretions occur in both aquatic and terrestrial animals, in which they perform diverse functions. Biological adhesives can therefore be remarkably complex and involve a large range of components with different functions and interactions. However, being mainly protein based, biological adhesives can be characterized by classical molecular methods. This review compiles experimental strategies that were successfully used to identify, characterize and obtain the full-length sequence of adhesive proteins from nine biological models: echinoderms, barnacles, tubeworms, mussels, sticklebacks, slugs, velvet worms, spiders and ticks. A brief description and practical examples are given for a variety of tools used to study adhesive molecules at different levels from genes to secreted proteins. In most studies, proteins, extracted from secreted materials or from adhesive organs, are analysed for the presence of post-translational modifications and submitted to peptide sequencing. The peptide sequences are then used directly for a BLAST search in genomic or transcriptomic databases, or to design degenerate primers to perform RT-PCR, both allowing the recovery of the sequence of the cDNA coding for the investigated protein. These sequences can then be used for functional validation and recombinant production. In recent years, the dual proteomic and transcriptomic approach has emerged as the best way leading to the identification of novel adhesive proteins and retrieval of their complete sequences. PMID:25657842

Comprehensive identification of protein substrates of the Dot/Icm type IV transporter of Legionella pneumophila.

Directory of Open Access Journals (Sweden)

Wenhan Zhu

2011-03-01

Full Text Available A large number of proteins transferred by the Legionella pneumophila Dot/Icm system have been identified by various strategies. With no exceptions, these strategies are based on one or more characteristics associated with the tested proteins. Given the high level of diversity exhibited by the identified proteins, it is possible that some substrates have been missed in these screenings. In this study, we took a systematic method to survey the L. pneumophila genome by testing hypothetical orfs larger than 300 base pairs for Dot/Icm-dependent translocation. 798 of the 832 analyzed orfs were successfully fused to the carboxyl end of β-lactamase. The transfer of the fusions into mammalian cells was determined using the β-lactamase reporter substrate CCF4-AM. These efforts led to the identification of 164 proteins positive in translocation. Among these, 70 proteins are novel substrates of the Dot/Icm system. These results brought the total number of experimentally confirmed Dot/Icm substrates to 275. Sequence analysis of the C-termini of these identified proteins revealed that Lpg2844, which contains few features known to be important for Dot/Icm-dependent protein transfer can be translocated at a high efficiency. Thus, our efforts have identified a large number of novel substrates of the Dot/Icm system and have revealed the diverse features recognizable by this protein transporter.

A MULTIDIMENSIONAL AND MULTIPHYSICS APPROACH TO NUCLEAR FUEL BEHAVIOR SIMULATION

Energy Technology Data Exchange (ETDEWEB)

R. L. Williamson; J. D. Hales; S. R. Novascone; M. R. Tonks; D. R. Gaston; C. J. Permann; D. Andrs; R. C. Martineau

2012-04-01

Important aspects of fuel rod behavior, for example pellet-clad mechanical interaction (PCMI), fuel fracture, oxide formation, non-axisymmetric cooling, and response to fuel manufacturing defects, are inherently multidimensional in addition to being complicated multiphysics problems. Many current modeling tools are strictly 2D axisymmetric or even 1.5D. This paper outlines the capabilities of a new fuel modeling tool able to analyze either 2D axisymmetric or fully 3D models. These capabilities include temperature-dependent thermal conductivity of fuel; swelling and densification; fuel creep; pellet fracture; fission gas release; cladding creep; irradiation growth; and gap mechanics (contact and gap heat transfer). The need for multiphysics, multidimensional modeling is then demonstrated through a discussion of results for a set of example problems. The first, a 10-pellet rodlet, demonstrates the viability of the solution method employed. This example highlights the effect of our smeared cracking model and also shows the multidimensional nature of discrete fuel pellet modeling. The second example relies on our the multidimensional, multiphysics approach to analyze a missing pellet surface problem. As a final example, we show a lower-length-scale simulation coupled to a continuum-scale simulation.

Initiating heavy-atom-based phasing by multi-dimensional molecular replacement.

Science.gov (United States)

Pedersen, Bjørn Panyella; Gourdon, Pontus; Liu, Xiangyu; Karlsen, Jesper Lykkegaard; Nissen, Poul

2016-03-01

To obtain an electron-density map from a macromolecular crystal the phase problem needs to be solved, which often involves the use of heavy-atom derivative crystals and concomitant heavy-atom substructure determination. This is typically performed by dual-space methods, direct methods or Patterson-based approaches, which however may fail when only poorly diffracting derivative crystals are available. This is often the case for, for example, membrane proteins. Here, an approach for heavy-atom site identification based on a molecular-replacement parameter matrix (MRPM) is presented. It involves an n-dimensional search to test a wide spectrum of molecular-replacement parameters, such as different data sets and search models with different conformations. Results are scored by the ability to identify heavy-atom positions from anomalous difference Fourier maps. The strategy was successfully applied in the determination of a membrane-protein structure, the copper-transporting P-type ATPase CopA, when other methods had failed to determine the heavy-atom substructure. MRPM is well suited to proteins undergoing large conformational changes where multiple search models should be considered, and it enables the identification of weak but correct molecular-replacement solutions with maximum contrast to prime experimental phasing efforts.

Protein Correlation Profiles Identify Lipid Droplet Proteins with High Confidence*

Science.gov (United States)

Krahmer, Natalie; Hilger, Maximiliane; Kory, Nora; Wilfling, Florian; Stoehr, Gabriele; Mann, Matthias; Farese, Robert V.; Walther, Tobias C.

2013-01-01

Lipid droplets (LDs) are important organelles in energy metabolism and lipid storage. Their cores are composed of neutral lipids that form a hydrophobic phase and are surrounded by a phospholipid monolayer that harbors specific proteins. Most well-established LD proteins perform important functions, particularly in cellular lipid metabolism. Morphological studies show LDs in close proximity to and interacting with membrane-bound cellular organelles, including the endoplasmic reticulum, mitochondria, peroxisomes, and endosomes. Because of these close associations, it is difficult to purify LDs to homogeneity. Consequently, the confident identification of bona fide LD proteins via proteomics has been challenging. Here, we report a methodology for LD protein identification based on mass spectrometry and protein correlation profiles. Using LD purification and quantitative, high-resolution mass spectrometry, we identified LD proteins by correlating their purification profiles to those of known LD proteins. Application of the protein correlation profile strategy to LDs isolated from Drosophila S2 cells led to the identification of 111 LD proteins in a cellular LD fraction in which 1481 proteins were detected. LD localization was confirmed in a subset of identified proteins via microscopy of the expressed proteins, thereby validating the approach. Among the identified LD proteins were both well-characterized LD proteins and proteins not previously known to be localized to LDs. Our method provides a high-confidence LD proteome of Drosophila cells and a novel approach that can be applied to identify LD proteins of other cell types and tissues. PMID:23319140

The Dictyostelium discoideum cellulose synthase: Structure/function analysis and identification of interacting proteins

Energy Technology Data Exchange (ETDEWEB)

Richard L. Blanton

2004-02-19

OAK-B135 The major accomplishments of this project were: (1) the initial characterization of dcsA, the gene for the putative catalytic subunit of cellulose synthase in the cellular slime mold Dictyostelium discoideum; (2) the detection of a developmentally regulated event (unidentified, but perhaps a protein modification or association with a protein partner) that is required for cellulose synthase activity (i.e., the dcsA product is necessary, but not sufficient for cellulose synthesis); (3) the continued exploration of the developmental context of cellulose synthesis and DcsA; (4) the isolation of a GFP-DcsA-expressing strain (work in progress); and (5) the identification of Dictyostelium homologues for plant genes whose products play roles in cellulose biosynthesis. Although our progress was slow and many of our results negative, we did develop a number of promising avenues of investigation that can serve as the foundation for future projects.

Multidimensional poverty: an alternative measurement approach for the United States?

Science.gov (United States)

Waglé, Udaya R

2008-06-01

International poverty research has increasingly underscored the need to use multidimensional approaches to measure poverty. Largely embraced in Europe and elsewhere, this has not had much impact on the way poverty is measured in the United States. In this paper, I use a comprehensive multidimensional framework including economic well-being, capability, and social inclusion to examine poverty in the US. Data from the 2004 General Social Survey support the interconnectedness among these poverty dimensions, indicating that the multidimensional framework utilizing a comprehensive set of information provides a compelling value added to poverty measurement. The suggested demographic characteristics of the various categories of the poor are somewhat similar between this approach and other traditional approaches. But the more comprehensive and accurate measurement outcomes from this approach help policymakers target resources at the specific groups.

A new multidimensional model with text dimensions: definition and implementation

Directory of Open Access Journals (Sweden)

MariaJ. Martin-Bautista

2013-02-01

Full Text Available We present a new multidimensional model with textual dimensions based on a knowledge structure extracted from the texts, where any textual attribute in a database can be processed, and not only XML texts. This dimension allows to treat the textual data in the same way as the non-textual one in an automatic way, without user's intervention, so all the classical operations in the multidimensional model can been defined for this textual dimension. While most of the models dealing with texts that can be found in the literature are not implemented, in this proposal, the multidimensional model and the OLAP system have been implemented in a software tool, so it can be tested on real data. A case study with medical data is included in this work.

Multi-dimensional simulations of core-collapse supernova explosions with CHIMERA

Science.gov (United States)

Messer, O. E. B.; Harris, J. A.; Hix, W. R.; Lentz, E. J.; Bruenn, S. W.; Mezzacappa, A.

2018-04-01

Unraveling the core-collapse supernova (CCSN) mechanism is a problem that remains essentially unsolved despite more than four decades of effort. Spherically symmetric models with otherwise high physical fidelity generally fail to produce explosions, and it is widely accepted that CCSNe are inherently multi-dimensional. Progress in realistic modeling has occurred recently through the availability of petascale platforms and the increasing sophistication of supernova codes. We will discuss our most recent work on understanding neutrino-driven CCSN explosions employing multi-dimensional neutrino-radiation hydrodynamics simulations with the Chimera code. We discuss the inputs and resulting outputs from these simulations, the role of neutrino radiation transport, and the importance of multi-dimensional fluid flows in shaping the explosions. We also highlight the production of 48Ca in long-running Chimera simulations.

Multi-dimensional quasitoeplitz Markov chains

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Alexander N. Dudin

1999-01-01

Full Text Available This paper deals with multi-dimensional quasitoeplitz Markov chains. We establish a sufficient equilibrium condition and derive a functional matrix equation for the corresponding vector-generating function, whose solution is given algorithmically. The results are demonstrated in the form of examples and applications in queues with BMAP-input, which operate in synchronous random environment.

Multidimensional integral representations problems of analytic continuation

CERN Document Server

Kytmanov, Alexander M

2015-01-01

The monograph is devoted to integral representations for holomorphic functions in several complex variables, such as Bochner-Martinelli, Cauchy-Fantappiè, Koppelman, multidimensional logarithmic residue etc., and their boundary properties. The applications considered are problems of analytic continuation of functions from the boundary of a bounded domain in C^n. In contrast to the well-known Hartogs-Bochner theorem, this book investigates functions with the one-dimensional property of holomorphic extension along complex lines, and includes the problems of receiving multidimensional boundary analogs of the Morera theorem.   This book is a valuable resource for specialists in complex analysis, theoretical physics, as well as graduate and postgraduate students with an understanding of standard university courses in complex, real and functional analysis, as well as algebra and geometry.

Performance of VITEK mass spectrometry V3.0 for rapid identification of clinical Aspergillus fumigatus in different culture conditions based on ribosomal proteins

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Zhou L

2017-12-01

Full Text Available Longrong Zhou, Yongquan Chen, Yuanhong Xu Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Anhui, Hefei, People’s Republic of China Abstract: Fast and accurate discrimination of Aspergillus fumigatus is significant, since misidentification may lead to inappropriate clinical therapy. This study assessed VITEK mass spectrometry (MS V3.0 for A. fumigatus identification using extracted fungal ribosomal proteins. A total of 52 isolates preliminarily identified as A. fumigatus by traditional morphological methods were inoculated in three different culture media and cultured at two different temperatures. The specific spectral fingerprints of different culture time points (48, 72, 96, and 120 h were obtained. Of all strains, 88.5% (46/52 were discriminated as A. fumigatus, while the remaining 11.5% (6/52 produced results inconsistent with morphological analysis. Molecular sequencing, as a reference method for species identification, was used to validate the morphological analysis and matrix-assisted laser desorption/ionization time of flight MS. Chi-square tests (Χ2 test, P=0.05 demonstrated that the culture medium and incubation temperature had no effects on identification accuracy; however, identification accuracy of the strains in the 48-h group was lower than that in other groups. In addition, we found that ribosomal proteins extracted from A. fumigatus can be stored in different environments for at least 1 week, with their profiles remaining stable and strain identification results showing no change. This is beneficial for medical institutions with no mass spectrometer at hand. Overall, this study showed the powerful ability of VITEK MS V 3.0 in identifying A. fumigatus. Keywords: VITEK MS V 3.0, Aspergillus fumigatus, identification, ribosomal protein, spectral fingerprints, fungal, matrix assisted laser desorption ionization-time of flight mass spectrometry, MALDI-TOF MS

Using the Andrews Plotss to Visualize Multidimensional Data in Multi-criteria Optimization

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S. V. Groshev

2015-01-01

Full Text Available Currently, issues on processing of large data volumes are of great importance. Initially, the Andrews plots have been proposed to show multidimensional statistics on the plane. But as the Andrews plots retain information on the average values of the represented values, distances, and dispersion, the distances between the plots linearly indicate distances between the data points, and it becomes possible to use the plots under consideration for the graphical representation of multi-dimensional data of various kinds. The paper analyses a diversity of various mathematical apparatus for Andrews plotting to visualize multi-dimensional data.The first section provides basic information about the Andrews plots, as well as about a test set of multidimensional data in Iris Fischer’s literature. Analysis of the Andrews plot properties shows that they provide a limitlessly many one-dimensional projections on the vectors and, furthermore, the plots, which are nearer to each other, correspond to nearly points. All this makes it possible to use the plots under consideration for multi-dimensional data representation. The paper considers the Andrews plot formation based on Fourier transform functions, and from the analysis results of plotting based on a set of the test, it draws a conclusion that in this way it is possible to provide clustering of multidimensional data.The second section of the work deals with research of different ways to modify the Andrews plots in order to improve the perception of the graphical representation of multidimensional data. Different variants of the Andrews plot projections on the coordinate planes and arbitrary subspaces are considered. In addition, the paper studies an effect of the Andrews plot scaling on the visual perception of multidimensional data.The paper’s third section describes Andrews plotting based on different polynomials, in particular, Chebyshev and Legendre polynomials. It is shown that the resulting image is

Comparison of identification methods for oral asaccharolytic Eubacterium species.

Science.gov (United States)

Wade, W G; Slayne, M A; Aldred, M J

1990-12-01

Thirty one strains of oral, asaccharolytic Eubacterium spp. and the type strains of E. brachy, E. nodatum and E. timidum were subjected to three identification techniques--protein-profile analysis, determination of metabolic end-products, and the API ATB32A identification kit. Five clusters were obtained from numerical analysis of protein profiles and excellent correlations were seen with the other two methods. Protein profiles alone allowed unequivocal identification.

Development and application of computer codes for multidimensional thermalhydraulic analyses of nuclear reactor components

International Nuclear Information System (INIS)

Carver, M.B.

1983-01-01

Components of reactor systems and related equipment are identified in which multidimensional computational thermal hydraulics can be used to advantage to assess and improve design. Models of single- and two-phase flow are reviewed, and the governing equations for multidimensional analysis are discussed. Suitable computational algorithms are introduced, and sample results from the application of particular multidimensional computer codes are given

Pathways into chronic multidimensional poverty amongst older people: a longitudinal study.

Science.gov (United States)

Callander, Emily J; Schofield, Deborah J

2016-03-07

The use of multidimensional poverty measures is becoming more common for measuring the living standards of older people. However, the pathways into poverty are relatively unknown, nor is it known how this affects the length of time people are in poverty for. Using Waves 1 to 12 of the nationally representative Household, Income and Labour Dynamics in Australia (HILDA) survey, longitudinal analysis was undertaken to identify the order that key forms of disadvantage develop - poor health, low income and insufficient education attainment - amongst Australians aged 65 years and over in multidimensional poverty, and the relationship this has with chronic poverty. Path analysis and linear regression models were used. For all older people with at least a Year 10 level of education attainment earlier mental health was significantly related to later household income (p = 0.001) and wealth (p = 0.017). For all older people with at less than a Year 10 level of education attainment earlier household income was significantly related to later mental health (p = 0.021). When limited to those in multidimensional poverty who were in income poverty and also had poor health, older people generally fell into income poverty first and then developed poor health. The order in which income poverty and poor health were developed had a significant influence on the length of time older people with less than a Year 10 level of education attainment were in multidimensional poverty for. Those who developed poor health first then fell into income poverty spend significantly less time in multidimensional poverty (-4.90, p poverty then developed poor health. Knowing the order that different forms of disadvantage develop, and the influence this has on poverty entrenchment, is of use to policy makers wishing to provide interventions to prevent older people being in long-term multidimensional poverty.

Multi-dimensional database design and implementation of dam safety monitoring system

Directory of Open Access Journals (Sweden)

Zhao Erfeng

2008-09-01

Full Text Available To improve the effectiveness of dam safety monitoring database systems, the development process of a multi-dimensional conceptual data model was analyzed and a logic design was achieved in multi-dimensional database mode. The optimal data model was confirmed by identifying data objects, defining relations and reviewing entities. The conversion of relations among entities to external keys and entities and physical attributes to tables and fields was interpreted completely. On this basis, a multi-dimensional database that reflects the management and analysis of a dam safety monitoring system on monitoring data information has been established, for which factual tables and dimensional tables have been designed. Finally, based on service design and user interface design, the dam safety monitoring system has been developed with Delphi as the development tool. This development project shows that the multi-dimensional database can simplify the development process and minimize hidden dangers in the database structure design. It is superior to other dam safety monitoring system development models and can provide a new research direction for system developers.

A Multifaceted Study of Scedosporium boydii Cell Wall Changes during Germination and Identification of GPI-Anchored Proteins

Science.gov (United States)

Ghamrawi, Sarah; Gastebois, Amandine; Zykwinska, Agata; Vandeputte, Patrick; Marot, Agnès; Mabilleau, Guillaume; Cuenot, Stéphane; Bouchara, Jean-Philippe

2015-01-01

Scedosporium boydii is a pathogenic filamentous fungus that causes a wide range of human infections, notably respiratory infections in patients with cystic fibrosis. The development of new therapeutic strategies targeting S. boydii necessitates a better understanding of the physiology of this fungus and the identification of new molecular targets. In this work, we studied the conidium-to-germ tube transition using a variety of techniques including scanning and transmission electron microscopy, atomic force microscopy, two-phase partitioning, microelectrophoresis and cationized ferritin labeling, chemical force spectroscopy, lectin labeling, and nanoLC-MS/MS for cell wall GPI-anchored protein analysis. We demonstrated that the cell wall undergoes structural changes with germination accompanied with a lower hydrophobicity, electrostatic charge and binding capacity to cationized ferritin. Changes during germination also included a higher accessibility of some cell wall polysaccharides to lectins and less CH3/CH3 interactions (hydrophobic adhesion forces mainly due to glycoproteins). We also extracted and identified 20 GPI-anchored proteins from the cell wall of S. boydii, among which one was detected only in the conidial wall extract and 12 only in the mycelial wall extract. The identified sequences belonged to protein families involved in virulence in other fungi like Gelp/Gasp, Crhp, Bglp/Bgtp families and a superoxide dismutase. These results highlighted the cell wall remodeling during germination in S. boydii with the identification of a substantial number of cell wall GPI-anchored conidial or hyphal specific proteins, which provides a basis to investigate the role of these molecules in the host-pathogen interaction and fungal virulence. PMID:26038837

A systematic identification of species-specific protein succinylation sites using joint element features information

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Hasan MM

2017-08-01

Full Text Available Md Mehedi Hasan,1 Mst Shamima Khatun,2 Md Nurul Haque Mollah,2 Cao Yong,3 Dianjing Guo1 1School of Life Sciences and the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territory, Hong Kong, People’s Republic of China; 2Laboratory of Bioinformatics, Department of Statistics, University of Rajshahi, Rajshahi, Bangladesh; 3Department of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, People’s Republic of China Abstract: Lysine succinylation, an important type of protein posttranslational modification, plays significant roles in many cellular processes. Accurate identification of succinylation sites can facilitate our understanding about the molecular mechanism and potential roles of lysine succinylation. However, even in well-studied systems, a majority of the succinylation sites remain undetected because the traditional experimental approaches to succinylation site identification are often costly, time-consuming, and laborious. In silico approach, on the other hand, is potentially an alternative strategy to predict succinylation substrates. In this paper, a novel computational predictor SuccinSite2.0 was developed for predicting generic and species-specific protein succinylation sites. This predictor takes the composition of profile-based amino acid and orthogonal binary features, which were used to train a random forest classifier. We demonstrated that the proposed SuccinSite2.0 predictor outperformed other currently existing implementations on a complementarily independent dataset. Furthermore, the important features that make visible contributions to species-specific and cross-species-specific prediction of protein succinylation site were analyzed. The proposed predictor is anticipated to be a useful computational resource for lysine succinylation site prediction. The integrated species-specific online tool of SuccinSite2.0 is publicly

Multi-dimensional indoor location information model

NARCIS (Netherlands)

Xiong, Q.; Zhu, Q.; Zlatanova, S.; Huang, L.; Zhou, Y.; Du, Z.

2013-01-01

Aiming at the increasing requirements of seamless indoor and outdoor navigation and location service, a Chinese standard of Multidimensional Indoor Location Information Model is being developed, which defines ontology of indoor location. The model is complementary to 3D concepts like CityGML and

Frost Multidimensional Perfectionism Scale: the portuguese version

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Ana Paula Monteiro Amaral

2013-01-01

Full Text Available BACKGROUND: The Frost Multidimensional Perfectionism Scale is one of the most world widely used measures of perfectionism. OBJECTIVE: To analyze the psychometric properties of the Portuguese version of the Frost Multidimensional Perfectionism Scale. METHODS: Two hundred and seventeen (178 females students from two Portuguese Universities filled in the scale, and a subgroup (n = 166 completed a retest with a four weeks interval. RESULTS: The scale reliability was good (Cronbach alpha = .857. Corrected item-total correlations ranged from .019 to .548. The scale test-retest reliability suggested a good temporal stability with a test-retest correlation of .765. A principal component analysis with Varimax rotation was performed and based on the Scree plot, two robust factorial structures were found (four and six factors. The principal component analyses, using Monte Carlo PCA for parallel analyses confirmed the six factor solution. The concurrent validity with Hewitt and Flett MPS was high, as well as the discriminant validity of positive and negative affect (Profile of Mood Stats-POMS. DISCUSSION: The two factorial structures (of four and six dimensions of the Portuguese version of Frost Multidimensional Perfectionism Scale replicate the results from different authors, with different samples and cultures. This suggests this scale is a robust instrument to assess perfectionism, in several clinical and research settings as well as in transcultural studies.

The multidimensional nucleon structure

Directory of Open Access Journals (Sweden)

Pasquini Barbara

2016-01-01

Full Text Available We discuss different kinds of parton distributions, which allow one to obtain a multidimensional picture of the internal structure of the nucleon. We use the concept of generalized transverse momentum dependent parton distributions and Wigner distributions, which combine the features of transverse-momentum dependent parton distributions and generalized parton distributions. We show examples of these functions within a phenomenological quark model, with focus on the role of the spin-spin and spin-orbit correlations of quarks.

Multi-Dimensional Customer Data Analysis in Online Auctions

Institute of Scientific and Technical Information of China (English)

LAO Guoling; XIONG Kuan; QIN Zheng

2007-01-01

In this paper, we designed a customer-centered data warehouse system with five subjects: listing, bidding, transaction,accounts, and customer contact based on the business process of online auction companies. For each subject, we analyzed its fact indexes and dimensions. Then take transaction subject as example,analyzed the data warehouse model in detail, and got the multi-dimensional analysis structure of transaction subject. At last, using data mining to do customer segmentation, we divided customers into four types: impulse customer, prudent customer, potential customer, and ordinary customer. By the result of multi-dimensional customer data analysis, online auction companies can do more target marketing and increase customer loyalty.

Stealth proteins: in silico identification of a novel protein family rendering bacterial pathogens invisible to host immune defense.

Directory of Open Access Journals (Sweden)

Peter Sperisen

2005-11-01

Full Text Available There are a variety of bacterial defense strategies to survive in a hostile environment. Generation of extracellular polysaccharides has proved to be a simple but effective strategy against the host's innate immune system. A comparative genomics approach led us to identify a new protein family termed Stealth, most likely involved in the synthesis of extracellular polysaccharides. This protein family is characterized by a series of domains conserved across phylogeny from bacteria to eukaryotes. In bacteria, Stealth (previously characterized as SacB, XcbA, or WefC is encoded by subsets of strains mainly colonizing multicellular organisms, with evidence for a protective effect against the host innate immune defense. More specifically, integrating all the available information about Stealth proteins in bacteria, we propose that Stealth is a D-hexose-1-phosphoryl transferase involved in the synthesis of polysaccharides. In the animal kingdom, Stealth is strongly conserved across evolution from social amoebas to simple and complex multicellular organisms, such as Dictyostelium discoideum, hydra, and human. Based on the occurrence of Stealth in most Eukaryotes and a subset of Prokaryotes together with its potential role in extracellular polysaccharide synthesis, we propose that metazoan Stealth functions to regulate the innate immune system. Moreover, there is good reason to speculate that the acquisition and spread of Stealth could be responsible for future epidemic outbreaks of infectious diseases caused by a large variety of eubacterial pathogens. Our in silico identification of a homologous protein in the human host will help to elucidate the causes of Stealth-dependent virulence. At a more basic level, the characterization of the molecular and cellular function of Stealth proteins may shed light on fundamental mechanisms of innate immune defense against microbial invasion.

Stealth Proteins: In Silico Identification of a Novel Protein Family Rendering Bacterial Pathogens Invisible to Host Immune Defense.

Directory of Open Access Journals (Sweden)

2005-11-01

Full Text Available There are a variety of bacterial defense strategies to survive in a hostile environment. Generation of extracellular polysaccharides has proved to be a simple but effective strategy against the host's innate immune system. A comparative genomics approach led us to identify a new protein family termed Stealth, most likely involved in the synthesis of extracellular polysaccharides. This protein family is characterized by a series of domains conserved across phylogeny from bacteria to eukaryotes. In bacteria, Stealth (previously characterized as SacB, XcbA, or WefC is encoded by subsets of strains mainly colonizing multicellular organisms, with evidence for a protective effect against the host innate immune defense. More specifically, integrating all the available information about Stealth proteins in bacteria, we propose that Stealth is a D-hexose-1-phosphoryl transferase involved in the synthesis of polysaccharides. In the animal kingdom, Stealth is strongly conserved across evolution from social amoebas to simple and complex multicellular organisms, such as Dictyostelium discoideum, hydra, and human. Based on the occurrence of Stealth in most Eukaryotes and a subset of Prokaryotes together with its potential role in extracellular polysaccharide synthesis, we propose that metazoan Stealth functions to regulate the innate immune system. Moreover, there is good reason to speculate that the acquisition and spread of Stealth could be responsible for future epidemic outbreaks of infectious diseases caused by a large variety of eubacterial pathogens. Our in silico identification of a homologous protein in the human host will help to elucidate the causes of Stealth-dependent virulence. At a more basic level, the characterization of the molecular and cellular function of Stealth proteins may shed light on fundamental mechanisms of innate immune defense against microbial invasion.

Identification of TOEFAZ1-interacting proteins reveals key regulators of Trypanosoma brucei cytokinesis.

Science.gov (United States)

Hilton, Nicholas A; Sladewski, Thomas E; Perry, Jenna A; Pataki, Zemplen; Sinclair-Davis, Amy N; Muniz, Richard S; Tran, Holly L; Wurster, Jenna I; Seo, Jiwon; de Graffenried, Christopher L

2018-05-21

The protist parasite Trypanosoma brucei is an obligate extracellular pathogen that retains its highly-polarized morphology during cell division and has evolved a novel cytokinetic process independent of non-muscle myosin II. The polo-like kinase homolog TbPLK is essential for transmission of cell polarity during division and for cytokinesis. We previously identified a putative TbPLK substrate named Tip of the Extending FAZ 1 (TOEFAZ1) as an essential kinetoplastid-specific component of the T. brucei cytokinetic machinery. We performed a proximity-dependent biotinylation (BioID) screen using TOEFAZ1 as a means to identify additional proteins that are involved in cytokinesis. Using quantitative proteomic methods, we identified nearly 500 TOEFAZ1-proximal proteins and characterized 59 in further detail. Among the candidates, we identified an essential putative phosphatase that regulates the expression level and localization of both TOEFAZ1 and TbPLK, a previously uncharacterized protein that is necessary for the assembly of a new cell posterior, and a microtubule plus-end directed orphan kinesin that is required for completing cleavage furrow ingression. The identification of these proteins provides new insight into T. brucei cytokinesis and establishes TOEFAZ1 as a key component of this essential and uniquely-configured process in kinetoplastids. This article is protected by copyright. All rights reserved. © 2018 John Wiley & Sons Ltd.

Biotic stress protein markers of Aquilaria sp. for gaharu species identification in Malaysia

International Nuclear Information System (INIS)

Azhar Mohamad; Abdul Rahim Harun

2012-01-01

Gaharu trees (Aquilaria) is in danger of extinction in the wild due to illegal logging. Its resin (Gaharu) is used for the production of highly valued incense throughout Asia. In Aquilaria sp. systemic induction of defense genes in response to mechanical wounding in nature is regulated by an 18-amino-acid peptide signal protein called systemin. This protein is produced in response to the natural stress at the vicinity of the wound and is also influenced by its genetic background. As the protein can be differentiated by its locality, the protein expressed is also found to be significantly different which, in turn, can be used for identification of this plant species. In this work, A. malaccensis and A. hirta were evaluated based on the targeted genes related to systemin. Targeted gene refers to specific sequence in genomic DNA. Sequence mining from public databases is part of the crucial process in getting the specific genes. The sequences will go through alignment step to identify conserved region prior to primer design. The primers were used in Polymerase Chain Reaction (PCR) techniques to amplify the conserved regions. It was found that both samples can be differentiated. This would be useful for plant breeders, trader and planter in ensuring authentic planting materials. This paper will describe the use of targeted genes primers as markers in identifying the Aquilaria species. (author)

An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

Directory of Open Access Journals (Sweden)

Lockwood William W

2010-05-01

Full Text Available Abstract Background Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer. Results Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations. Conclusions Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.

Multidimensional artificial field embedding with spatial sensitivity

CSIR Research Space (South Africa)

Lunga, D

2013-06-01

Full Text Available Multidimensional embedding is a technique useful for characterizing spectral signature relations in hyperspectral images. However, such images consist of disjoint similar spectral classes that are spatially sensitive, thus presenting challenges...

Assessment of health surveys: fitting a multidimensional graded response model.

Science.gov (United States)

Depaoli, Sarah; Tiemensma, Jitske; Felt, John M

The multidimensional graded response model, an item response theory (IRT) model, can be used to improve the assessment of surveys, even when sample sizes are restricted. Typically, health-based survey development utilizes classical statistical techniques (e.g. reliability and factor analysis). In a review of four prominent journals within the field of Health Psychology, we found that IRT-based models were used in less than 10% of the studies examining scale development or assessment. However, implementing IRT-based methods can provide more details about individual survey items, which is useful when determining the final item content of surveys. An example using a quality of life survey for Cushing's syndrome (CushingQoL) highlights the main components for implementing the multidimensional graded response model. Patients with Cushing's syndrome (n = 397) completed the CushingQoL. Results from the multidimensional graded response model supported a 2-subscale scoring process for the survey. All items were deemed as worthy contributors to the survey. The graded response model can accommodate unidimensional or multidimensional scales, be used with relatively lower sample sizes, and is implemented in free software (example code provided in online Appendix). Use of this model can help to improve the quality of health-based scales being developed within the Health Sciences.

Identification of Secretory Proteins in Mycobacterium tuberculosis Using Pseudo Amino Acid Composition

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Huan Yang

2016-01-01

Full Text Available Tuberculosis is killing millions of lives every year and on the blacklist of the most appalling public health problems. Recent findings suggest that secretory protein of Mycobacterium tuberculosis may serve the purpose of developing specific vaccines and drugs due to their antigenicity. Responding to global infectious disease, we focused on the identification of secretory proteins in Mycobacterium tuberculosis. A novel method called MycoSec was designed by incorporating g-gap dipeptide compositions into pseudo amino acid composition. Analysis of variance-based technique was applied in the process of feature selection and a total of 374 optimal features were obtained and used for constructing the final predicting model. In the jackknife test, MycoSec yielded a good performance with the area under the receiver operating characteristic curve of 0.93, demonstrating that the proposed system is powerful and robust. For user’s convenience, the web server MycoSec was established and an obliging manual on how to use it was provided for getting around any trouble unnecessary.

Identification of small peptides arising from hydrolysis of meat proteins in dry fermented sausages.

Science.gov (United States)

López, Constanza M; Bru, Elena; Vignolo, Graciela M; Fadda, Silvina G

2015-06-01

In this study, proteolysis and low molecular weight (LMW) peptides (<3kDa) from commercial Argentinean fermented sausages were characterized by applying a peptidomic approach. Protein profiles and peptides obtained by Tricine-SDS-PAGE and RP-HPLC-MS, respectively, allowed distinguishing two different types of fermented sausages, although no specific biomarkers relating to commercial brands or quality were recognized. From electrophoresis, α-actin, myoglobin, creatine kinase M-type and L-lactate dehydrogenase were degraded at different intensities. In addition, a partial characterization of fermented sausage peptidome through the identification of 36 peptides, in the range of 1000-2100 Da, arising from sarcoplasmic (28) and myofibrillar (8) proteins was achieved. These peptides had been originated from α-actin, myoglobin, and creatine kinase M-type, but also from the hydrolysis of other proteins not previously reported. Although muscle enzymes exerted a major role on peptidogenesis, microbial contribution cannot be excluded as it was postulated herein. This work represents a first peptidomic approach for fermented sausages, thereby providing a baseline to define key peptides acting as potential biomarkers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identification of S-glutathionylation sites in species-specific proteins by incorporating five sequence-derived features into the general pseudo-amino acid composition.

Science.gov (United States)

Zhao, Xiaowei; Ning, Qiao; Ai, Meiyue; Chai, Haiting; Yang, Guifu

2016-06-07

As a selective and reversible protein post-translational modification, S-glutathionylation generates mixed disulfides between glutathione (GSH) and cysteine residues, and plays an important role in regulating protein activity, stability, and redox regulation. To fully understand S-glutathionylation mechanisms, identification of substrates and specific S-Glutathionylated sites is crucial. Experimental identification of S-glutathionylated sites is labor-intensive and time consuming, so establishing an effective computational method is much desirable due to their convenient and fast speed. Therefore, in this study, a new bioinformatics tool named SSGlu (Species-Specific identification of Protein S-glutathionylation Sites) was developed to identify species-specific protein S-glutathionylated sites, utilizing support vector machines that combine multiple sequence-derived features with a two-step feature selection. By 5-fold cross validation, the performance of SSGlu was measured with an AUC of 0.8105 and 0.8041 for Homo sapiens and Mus musculus, respectively. Additionally, SSGlu was compared with the existing methods, and the higher MCC and AUC of SSGlu demonstrated that SSGlu was very promising to predict S-glutathionylated sites. Furthermore, a site-specific analysis showed that S-glutathionylation intimately correlated with the features derived from its surrounding sites. The conclusions derived from this study might help to understand more of the S-glutathionylation mechanism and guide the related experimental validation. For public access, SSGlu is freely accessible at http://59.73.198.144:8080/SSGlu/. Copyright © 2016 Elsevier Ltd. All rights reserved.

MCMC estimation of multidimensional IRT models

NARCIS (Netherlands)

Beguin, Anton; Glas, Cornelis A.W.

1998-01-01

A Bayesian procedure to estimate the three-parameter normal ogive model and a generalization to a model with multidimensional ability parameters are discussed. The procedure is a generalization of a procedure by J. Albert (1992) for estimating the two-parameter normal ogive model. The procedure will

Implementation of multidimensional databases in column-oriented NoSQL systems

OpenAIRE

Chevalier, Max; El Malki, Mohammed; Kopliku, Arlind; Teste, Olivier; Tournier, Ronan

2015-01-01

International audience; NoSQL (Not Only SQL) systems are becoming popular due to known advantages such as horizontal scalability and elasticity. In this paper, we study the implementation of multidimensional data warehouses with columnoriented NoSQL systems. We define mapping rules that transform the conceptual multidimensional data model to logical column-oriented models. We consider three different logical models and we use them to instantiate data warehouses. We focus on data loading, mode...

Portable laser synthesizer for high-speed multi-dimensional spectroscopy

Science.gov (United States)

Demos, Stavros G [Livermore, CA; Shverdin, Miroslav Y [Sunnyvale, CA; Shirk, Michael D [Brentwood, CA

2012-05-29

Portable, field-deployable laser synthesizer devices designed for multi-dimensional spectrometry and time-resolved and/or hyperspectral imaging include a coherent light source which simultaneously produces a very broad, energetic, discrete spectrum spanning through or within the ultraviolet, visible, and near infrared wavelengths. The light output is spectrally resolved and each wavelength is delayed with respect to each other. A probe enables light delivery to a target. For multidimensional spectroscopy applications, the probe can collect the resulting emission and deliver this radiation to a time gated spectrometer for temporal and spectral analysis.

Protein identification from two-dimensional gel electrophoresis analysis of Klebsiella pneumoniae by combined use of mass spectrometry data and raw genome sequences

Directory of Open Access Journals (Sweden)

Zeng An-Ping

2003-12-01

Full Text Available Abstract Separation of proteins by two-dimensional gel electrophoresis (2-DE coupled with identification of proteins through peptide mass fingerprinting (PMF by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS is the widely used technique for proteomic analysis. This approach relies, however, on the presence of the proteins studied in public-accessible protein databases or the availability of annotated genome sequences of an organism. In this work, we investigated the reliability of using raw genome sequences for identifying proteins by PMF without the need of additional information such as amino acid sequences. The method is demonstrated for proteomic analysis of Klebsiella pneumoniae grown anaerobically on glycerol. For 197 spots excised from 2-DE gels and submitted for mass spectrometric analysis 164 spots were clearly identified as 122 individual proteins. 95% of the 164 spots can be successfully identified merely by using peptide mass fingerprints and a strain-specific protein database (ProtKpn constructed from the raw genome sequences of K. pneumoniae. Cross-species protein searching in the public databases mainly resulted in the identification of 57% of the 66 high expressed protein spots in comparison to 97% by using the ProtKpn database. 10 dha regulon related proteins that are essential for the initial enzymatic steps of anaerobic glycerol metabolism were successfully identified using the ProtKpn database, whereas none of them could be identified by cross-species searching. In conclusion, the use of strain-specific protein database constructed from raw genome sequences makes it possible to reliably identify most of the proteins from 2-DE analysis simply through peptide mass fingerprinting.

Identification of liver protein targets modified by tienilic acid metabolites using a two-dimensional Western blot-mass spectrometry approach

Science.gov (United States)

Methogo, Ruth Menque; Dansette, Patrick M.; Klarskov, Klaus

2007-12-01

A combined approach based on two-dimensional electrophoresis-immuno-blotting and nanoliquid chromatography coupled on-line with electrospray ionization mass spectrometry (nLC-MS/MS) was used to identify proteins modified by a reactive intermediate of tienilic acid (TA). Liver homogenates from rats exposed to TA were fractionated using ultra centrifugation; four fractions were obtained and subjected to 2D electrophoresis. Following transfer to PVDF membranes, modified proteins were visualized after India ink staining, using an anti-serum raised against TA and ECL detection. Immuno-reactive spots were localized on the PVDF membrane by superposition of the ECL image, protein spots of interest were excised, digested on the membrane with trypsin followed by nLC-MS/MS analysis and protein identification. A total of 15 proteins were identified as likely targets modified by a TA reactive metabolite. These include selenium binding protein 2, senescence marker protein SMP-30, adenosine kinase, Acy1 protein, adenosylhomocysteinase, capping protein (actin filament), protein disulfide isomerase, fumarylacetoacetase, arginase chain A, ketohexokinase, proteasome endopeptidase complex, triosephosphate isomerase, superoxide dismutase, dna-type molecular chaperone hsc73 and malate dehydrogenase.

Bacillus anthracis secretome time course under host-simulated conditions and identification of immunogenic proteins

Directory of Open Access Journals (Sweden)

Whittington Jessica

2007-07-01

accumulation may be relevant in elucidation of the progression of pathogenicity, identification of therapeutics and diagnostic markers, and vaccine development. This study also adds to the continuously growing list of identified Bacillus anthracis secretome proteins.

Testlet-Based Multidimensional Adaptive Testing.

Science.gov (United States)

Frey, Andreas; Seitz, Nicki-Nils; Brandt, Steffen

2016-01-01

Multidimensional adaptive testing (MAT) is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT). MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, and 1.5) and testlet sizes (3, 6, and 9 items) with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.

Testlet-based Multidimensional Adaptive Testing

Directory of Open Access Journals (Sweden)

Andreas Frey

2016-11-01

Full Text Available Multidimensional adaptive testing (MAT is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT. MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, 1.5 and testlet sizes (3 items, 6 items, 9 items with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.

Affinity purification combined with mass spectrometry to identify herpes simplex virus protein-protein interactions.

Science.gov (United States)

Meckes, David G

2014-01-01

The identification and characterization of herpes simplex virus protein interaction complexes are fundamental to understanding the molecular mechanisms governing the replication and pathogenesis of the virus. Recent advances in affinity-based methods, mass spectrometry configurations, and bioinformatics tools have greatly increased the quantity and quality of protein-protein interaction datasets. In this chapter, detailed and reliable methods that can easily be implemented are presented for the identification of protein-protein interactions using cryogenic cell lysis, affinity purification, trypsin digestion, and mass spectrometry.

Effect Size Measures for Differential Item Functioning in a Multidimensional IRT Model

Science.gov (United States)

Suh, Youngsuk

2016-01-01

This study adapted an effect size measure used for studying differential item functioning (DIF) in unidimensional tests and extended the measure to multidimensional tests. Two effect size measures were considered in a multidimensional item response theory model: signed weighted P-difference and unsigned weighted P-difference. The performance of…

Multidimensional Discriminative Factors for Unprotected Sex Among Adolescents in Southern Taiwan

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Cheng-Fang Yen

2009-04-01

Full Text Available Establishing the discriminative factors for unprotected sex among adolescents is essential for early identification of at-risk teens and for the prevention of unplanned pregnancy and sexually transmitted diseases. The aim of this study was to examine the discriminative effects of demographic, individual, family, peers, and school life factors on unprotected sex in a large-scale, representative adolescent population in Southern Taiwan. A total of 9,736 adolescent students were recruited into this study and completed the questionnaires. The multidimensional discriminative factors for unprotected sex were examined using χ2 automatic interaction detection analysis and logistic regression models. The results of the χ2 automatic interaction detection analysis revealed that having friends, using illicit drugs, being of an older age, suspension from school, and low family monitoring had discriminative effects on unprotected sex in adolescents. The logistic regression analysis further confirmed the discriminative effect of these factors. Because of the adverse effects of unprotected sex in adolescents, we suggest that parents and health professionals should pay attention to adolescents with the discriminative factors for unprotected sex identified in this study.

Identification of Protein Complexes from Tandem Affinity Purification/Mass Spectrometry Data via Biased Random Walk.

Science.gov (United States)

Cai, Bingjing; Wang, Haiying; Zheng, Huiru; Wang, Hui

2015-01-01

Systematic identification of protein complexes from protein-protein interaction networks (PPIs) is an important application of data mining in life science. Over the past decades, various new clustering techniques have been developed based on modelling PPIs as binary relations. Non-binary information of co-complex relations (prey/bait) in PPIs data derived from tandem affinity purification/mass spectrometry (TAP-MS) experiments has been unfairly disregarded. In this paper, we propose a Biased Random Walk based algorithm for detecting protein complexes from TAP-MS data, resulting in the random walk with restarting baits (RWRB). RWRB is developed based on Random walk with restart. The main contribution of RWRB is the incorporation of co-complex relations in TAP-MS PPI networks into the clustering process, by implementing a new restarting strategy during the process of random walk. Through experimentation on un-weighted and weighted TAP-MS data sets, we validated biological significance of our results by mapping them to manually curated complexes. Results showed that, by incorporating non-binary, co-membership information, significant improvement has been achieved in terms of both statistical measurements and biological relevance. Better accuracy demonstrates that the proposed method outperformed several state-of-the-art clustering algorithms for the detection of protein complexes in TAP-MS data.

Development and assessment of multi-dimensional flow model in MARS compared with the RPI air-water experiment

International Nuclear Information System (INIS)

Lee, Seok Min; Lee, Un Chul; Bae, Sung Won; Chung, Bub Dong

2004-01-01

The Multi-Dimensional flow models in system code have been developed during the past many years. RELAP5-3D, CATHARE and TRACE has its specific multi-dimensional flow models and successfully applied it to the system safety analysis. In KAERI, also, MARS(Multi-dimensional Analysis of Reactor Safety) code was developed by integrating RELAP5/MOD3 code and COBRA-TF code. Even though COBRA-TF module can analyze three-dimensional flow models, it has a limitation to apply 3D shear stress dominant phenomena or cylindrical geometry. Therefore, Multi-dimensional analysis models are newly developed by implementing three-dimensional momentum flux and diffusion terms. The multi-dimensional model has been assessed compared with multi-dimensional conceptual problems and CFD code results. Although the assessment results were reasonable, the multi-dimensional model has not been validated to two-phase flow using experimental data. In this paper, the multi-dimensional air-water two-phase flow experiment was simulated and analyzed

Protein Stable Isotope Fingerprinting (P-SIF): Multidimensional Protein Chromatography Coupled to Stable Isotope-Ratio Mass Spectrometry

Science.gov (United States)

Pearson, A.; Bovee, R. J.; Mohr, W.; Tang, T.

2012-12-01

As metagenomics increases our insight into microbial community diversity and metabolic potential, new approaches are required to determine the biogeochemical expression of this potential within ecosystems. Because stable isotopic analysis of the major bioactive elements (C, N) has been used historically to map flows of substrates and energy among macroscopic food webs, similar principles may apply to microbes. To address this challenge, we have developed a new analytical approach called Protein Stable Isotope Fingerprinting (P-SIF). P-SIF generates natural stable isotopic fingerprints of microbial individual or community proteomes. The main advantage of P-SIF is the potential to bridge the gap between diversity and function, thereby providing a window into the "black box" of environmental microbiology and helping to decipher the roles of uncultivated species. Our method implements a three-way, orthogonal scheme to separate mixtures of whole proteins into subfractions dominated by single or closely-related proteins. Protein extracts first are isoelectrically focused in a gel-free technique that yields 12 fractions separated over a gradient of pH 3-10. Each fraction then is separated by size-exclusion chromatography into 20 pools, ranging from >100kD to ~10kD. Finally, each of these pools is subjected to HPLC and collected in 40 time-slices based on protein hydrophobicity. Theoretical calculation reveals that the true chromatographic resolution of the total scheme is 5000, somewhat less than the 9600 resulting fractions. High-yielding fractions are subjected to δ13C analysis by spooling-wire microcombustion irMS (SWiM-irMS) optimized for samples containing 1-5 nmol carbon. Here we will present the method, results for a variety of pure cultures, and preliminary data for a sample of mixed environmental proteins. The data show the promise of this method for unraveling the metabolic complexity hidden within microbial communities.

Implementation of the Multidimensional Modeling Concepts into Object-Relational Databases

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available A key to survival in the business world is being able to analyze, plan and react to changing business conditions as fast as possible. With multidimensional models the managers can explore information at different levels of granularity and the decision makers at all levels can quickly respond to changes in the business climate-the ultimate goal of business intelligence. This paper focuses on the implementation of the multidimensional concepts into object-relational databases.

Evoking and Measuring Identification with Narrative Characters - A Linguistic Cues Framework.

Science.gov (United States)

van Krieken, Kobie; Hoeken, Hans; Sanders, José

2017-01-01

Current research on identification with narrative characters poses two problems. First, although identification is seen as a dynamic process of which the intensity varies during reading, it is usually measured by means of post-reading questionnaires containing self-report items. Second, it is not clear which linguistic characteristics evoke identification. The present paper proposes that an interdisciplinary framework allows for more precise manipulations and measurements of identification, which will ultimately advance our understanding of the antecedents and nature of this process. The central hypothesis of our Linguistic Cues Framework is that identification with a narrative character is a multidimensional experience for which different dimensions are evoked by different linguistic cues. The first part of the paper presents a literature review on identification, resulting in a renewed conceptualization of identification which distinguishes six dimensions: a spatiotemporal, a perceptual, a cognitive, a moral, an emotional, and an embodied dimension. The second part argues that each of these dimensions is influenced by specific linguistic cues which represent various aspects of the narrative character's perspective. The proposed relations between linguistic cues and identification dimensions are specified in six propositions. The third part discusses what psychological and neurocognitive methods enable the measurement of the various identification dimensions in order to test the propositions. By establishing explicit connections between the linguistic characteristics of narratives and readers' physical, psychological, and neurocognitive responses to narratives, this paper develops a research agenda for future empirical research on identification with narrative characters.

Multi-dimensional Bin Packing Problems with Guillotine Constraints

DEFF Research Database (Denmark)

Amossen, Rasmus Resen; Pisinger, David

2010-01-01

The problem addressed in this paper is the decision problem of determining if a set of multi-dimensional rectangular boxes can be orthogonally packed into a rectangular bin while satisfying the requirement that the packing should be guillotine cuttable. That is, there should exist a series of face...... parallel straight cuts that can recursively cut the bin into pieces so that each piece contains a box and no box has been intersected by a cut. The unrestricted problem is known to be NP-hard. In this paper we present a generalization of a constructive algorithm for the multi-dimensional bin packing...... problem, with and without the guillotine constraint, based on constraint programming....

Deriving Multidimensional Poverty Indicators: Methodological Issues and an Empirical Analysis for Italy

Science.gov (United States)

Coromaldi, Manuela; Zoli, Mariangela

2012-01-01

Theoretical and empirical studies have recently adopted a multidimensional concept of poverty. There is considerable debate about the most appropriate degree of multidimensionality to retain in the analysis. In this work we add to the received literature in two ways. First, we derive indicators of multiple deprivation by applying a particular…

Measures for a multidimensional multiverse

Science.gov (United States)

Chung, Hyeyoun

2015-04-01

We explore the phenomenological implications of generalizing the causal patch and fat geodesic measures to a multidimensional multiverse, where the vacua can have differing numbers of large dimensions. We consider a simple model in which the vacua are nucleated from a D -dimensional parent spacetime through dynamical compactification of the extra dimensions, and compute the geometric contribution to the probability distribution of observations within the multiverse for each measure. We then study how the shape of this probability distribution depends on the time scales for the existence of observers, for vacuum domination, and for curvature domination (tobs,tΛ , and tc, respectively.) In this work we restrict ourselves to bubbles with positive cosmological constant, Λ . We find that in the case of the causal patch cutoff, when the bubble universes have p +1 large spatial dimensions with p ≥2 , the shape of the probability distribution is such that we obtain the coincidence of time scales tobs˜tΛ˜tc . Moreover, the size of the cosmological constant is related to the size of the landscape. However, the exact shape of the probability distribution is different in the case p =2 , compared to p ≥3 . In the case of the fat geodesic measure, the result is even more robust: the shape of the probability distribution is the same for all p ≥2 , and we once again obtain the coincidence tobs˜tΛ˜tc . These results require only very mild conditions on the prior probability of the distribution of vacua in the landscape. Our work shows that the observed double coincidence of time scales is a robust prediction even when the multiverse is generalized to be multidimensional; that this coincidence is not a consequence of our particular Universe being (3 +1 )-dimensional; and that this observable cannot be used to preferentially select one measure over another in a multidimensional multiverse.

Multidimensional HAM-conditions

DEFF Research Database (Denmark)

Hansen, Ernst Jan de Place

Heat, Air and Moisture (HAM) conditions, experimental data are needed. Tests were performed in the large climate simulator at SBi involving full-scale wall elements. The elements were exposed for steady-state conditions, and temperature cycles simulating April and September climate in Denmark....... The effect on the moisture and temperature conditions of the addition of a vapour barrier and an outer cladding on timber frame walls was studied. The report contains comprehensive appendices documenting the full-scale tests. The tests were performed as a part of the project 'Model for Multidimensional Heat......, Air and Moisture Conditions in Building Envelope Components' carried out as a co-project between DTU Byg and SBi....

Proteomic tools for environmental microbiology--a roadmap from sample preparation to protein identification and quantification.

Science.gov (United States)

Wöhlbrand, Lars; Trautwein, Kathleen; Rabus, Ralf

2013-10-01

The steadily increasing amount of (meta-)genomic sequence information of diverse organisms and habitats has a strong impact on research in microbial physiology and ecology. In-depth functional understanding of metabolic processes and overall physiological adaptation to environmental changes, however, requires application of proteomics, as the context specific proteome constitutes the true functional output of a cell. Considering the enormous structural and functional diversity of proteins, only rational combinations of various analytical approaches allow a holistic view on the overall state of the cell. Within the past decade, proteomic methods became increasingly accessible to microbiologists mainly due to the robustness of analytical methods (e.g. 2DE), and affordability of mass spectrometers and their relative ease of use. This review provides an overview on the complex portfolio of state-of-the-art proteomics and highlights the basic principles of key methods, ranging from sample preparation of laboratory or environmental samples, via protein/peptide separation (gel-based or gel-free) and different types of mass spectrometric protein/peptide analyses, to protein identification and abundance determination. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SM4MQ: A Semantic Model for Multidimensional Queries

DEFF Research Database (Denmark)

Varga, Jovan; Dobrokhotova, Ekaterina; Romero, Oscar

2017-01-01

On-Line Analytical Processing (OLAP) is a data analysis approach to support decision-making. On top of that, Exploratory OLAP is a novel initiative for the convergence of OLAP and the Semantic Web (SW) that enables the use of OLAP techniques on SW data. Moreover, OLAP approaches exploit different......, sharing, and reuse on the SW. As OLAP is based on the underlying multidimensional (MD) data model we denote such queries as MD queries and define SM4MQ: A Semantic Model for Multidimensional Queries. Furthermore, we propose a method to automate the exploitation of queries by means of SPARQL. We apply...

Blind identification and separation of complex-valued signals

CERN Document Server

Moreau, Eric

2013-01-01

Blind identification consists of estimating a multi-dimensional system only through the use of its output, and source separation, the blind estimation of the inverse of the system. Estimation is generally carried out using different statistics of the output. The authors of this book consider the blind identification and source separation problem in the complex-domain, where the available statistical properties are richer and include non-circularity of the sources - underlying components. They define identifiability conditions and present state-of-the-art algorithms that are based on algebraic methods as well as iterative algorithms based on maximum likelihood theory. Contents 1. Mathematical Preliminaries. 2. Estimation by Joint Diagonalization. 3. Maximum Likelihood ICA. About the Authors Eric Moreau is Professor of Electrical Engineering at the University of Toulon, France. His research interests concern statistical signal processing, high order statistics and matrix/tensor decompositions with applic...

Modelling of multidimensional quantum systems by the numerical functional integration

International Nuclear Information System (INIS)

Lobanov, Yu.Yu.; Zhidkov, E.P.

1990-01-01

The employment of the numerical functional integration for the description of multidimensional systems in quantum and statistical physics is considered. For the multiple functional integrals with respect to Gaussian measures in the full separable metric spaces the new approximation formulas exact on a class of polynomial functionals of a given summary degree are constructed. The use of the formulas is demonstrated on example of computation of the Green function and the ground state energy in multidimensional Calogero model. 15 refs.; 2 tabs

A novel strategy for global mapping of O-GlcNAc proteins and peptides using selective enzymatic deglycosylation, HILIC enrichment and mass spectrometry identification.

Science.gov (United States)

Shen, Bingquan; Zhang, Wanjun; Shi, Zhaomei; Tian, Fang; Deng, Yulin; Sun, Changqing; Wang, Guangshun; Qin, Weijie; Qian, Xiaohong

2017-07-01

O-GlcNAcylation is a kind of dynamic O-linked glycosylation of nucleocytoplasmic and mitochondrial proteins. It serves as a major nutrient sensor to regulate numerous biological processes including transcriptional regulation, cell metabolism, cellular signaling, and protein degradation. Dysregulation of cellular O-GlcNAcylated levels contributes to the etiologies of many diseases such as diabetes, neurodegenerative disease and cancer. However, deeper insight into the biological mechanism of O-GlcNAcylation is hampered by its extremely low stoichiometry and the lack of efficient enrichment approaches for large-scale identification by mass spectrometry. Herein, we developed a novel strategy for the global identification of O-GlcNAc proteins and peptides using selective enzymatic deglycosylation, HILIC enrichment and mass spectrometry analysis. Standard O-GlcNAc peptides can be efficiently enriched even in the presence of 500-fold more abundant non-O-GlcNAc peptides and identified by mass spectrometry with a low nanogram detection sensitivity. This strategy successfully achieved the first large-scale enrichment and characterization of O-GlcNAc proteins and peptides in human urine. A total of 474 O-GlcNAc peptides corresponding to 457 O-GlcNAc proteins were identified by mass spectrometry analysis, which is at least three times more than that obtained by commonly used enrichment methods. A large number of unreported O-GlcNAc proteins related to cell cycle, biological regulation, metabolic and developmental process were found in our data. The above results demonstrated that this novel strategy is highly efficient in the global enrichment and identification of O-GlcNAc peptides. These data provide new insights into the biological function of O-GlcNAcylation in human urine, which is correlated with the physiological states and pathological changes of human body and therefore indicate the potential of this strategy for biomarker discovery from human urine. Copyright �

Multidimensional poverty and catastrophic health spending in the mountainous regions of Myanmar, Nepal and India.

Science.gov (United States)

Mohanty, Sanjay K; Agrawal, Nand Kishor; Mahapatra, Bidhubhusan; Choudhury, Dhrupad; Tuladhar, Sabarnee; Holmgren, E Valdemar

2017-01-18

Economic burden to households due to out-of-pocket expenditure (OOPE) is large in many Asian countries. Though studies suggest increasing household poverty due to high OOPE in developing countries, studies on association of multidimensional poverty and household health spending is limited. This paper tests the hypothesis that the multidimensionally poor are more likely to incur catastrophic health spending cutting across countries. Data from the Poverty and Vulnerability Assessment (PVA) Survey carried out by the International Center for Integrated Mountain Development (ICIMOD) has been used in the analyses. The PVA survey was a comprehensive household survey that covered the mountainous regions of India, Nepal and Myanmar. A total of 2647 households from India, 2310 households in Nepal and 4290 households in Myanmar covered under the PVA survey. Poverty is measured in a multidimensional framework by including the dimensions of education, income and energy, water and sanitation using the Alkire and Foster method. Health shock is measured using the frequency of illness, family sickness and death of any family member in a reference period of one year. Catastrophic health expenditure is defined as 40% above the household's capacity to pay. Results suggest that about three-fifths of the population in Myanmar, two-fifths of the population in Nepal and one-third of the population in India are multidimensionally poor. About 47% of the multidimensionally poor in India had incurred catastrophic health spending compared to 35% of the multidimensionally non-poor and the pattern was similar in both Nepal and Myanmar. The odds of incurring catastrophic health spending was 56% more among the multidimensionally poor than among the multidimensionally non-poor [95% CI: 1.35-1.76]. While health shocks to households are consistently significant predictors of catastrophic health spending cutting across country of residence, the educational attainment of the head of the household is

Identification of Increased Amounts of Eppin Protein Complex Components in Sperm Cells of Diabetic and Obese Individuals by Difference Gel Electrophoresis*

Science.gov (United States)

Paasch, Uwe; Heidenreich, Falk; Pursche, Theresia; Kuhlisch, Eberhard; Kettner, Karina; Grunewald, Sonja; Kratzsch, Jürgen; Dittmar, Gunnar; Glander, Hans-Jürgen; Hoflack, Bernard; Kriegel, Thomas M.

2011-01-01

Metabolic disorders like diabetes mellitus and obesity may compromise the fertility of men and women. To unveil disease-associated proteomic changes potentially affecting male fertility, the proteomes of sperm cells from type-1 diabetic, type-2 diabetic, non-diabetic obese and clinically healthy individuals were comparatively analyzed by difference gel electrophoresis. The adaptation of a general protein extraction procedure to the solubilization of proteins from sperm cells allowed for the resolution of 3187 fluorescent spots in the difference gel electrophoresis image of the master gel, which contained the entirety of solubilized sperm proteins. Comparison of the pathological and reference proteomes by applying an average abundance ratio setting of 1.6 and a p ≤ 0.05 criterion resulted in the identification of 79 fluorescent spots containing proteins that were present at significantly changed levels in the sperm cells. Biometric evaluation of the fluorescence data followed by mass spectrometric protein identification revealed altered levels of 12, 71, and 13 protein species in the proteomes of the type-1 diabetic, type-2 diabetic, and non-diabetic obese patients, respectively, with considerably enhanced amounts of the same set of one molecular form of semenogelin-1, one form of clusterin, and two forms of lactotransferrin in each group of pathologic samples. Remarkably, β-galactosidase-1-like protein was the only protein that was detected at decreased levels in all three pathologic situations. The former three proteins are part of the eppin (epididymal proteinase inhibitor) protein complex, which is thought to fulfill fertilization-related functions, such as ejaculate sperm protection, motility regulation and gain of competence for acrosome reaction, whereas the putative role of the latter protein to function as a glycosyl hydrolase during sperm maturation remains to be explored at the protein/enzyme level. The strikingly similar differences detected in the

Almost-sure identifiability of multidimensional harmonic retrieval

NARCIS (Netherlands)

Jiang, T; Sidiropoulos, ND; ten Berge, JMF

Two-dimensional (2-D) and, more generally, multidimensional harmonic retrieval is of interest in a variety of applications, including transmitter localization and joint time and frequency offset estimation in wireless communications. The associated identifiability problem is key in understanding the

Cell-Free Expression and In Situ Immobilization of Parasite Proteins from Clonorchis sinensis for Rapid Identification of Antigenic Candidates.

Directory of Open Access Journals (Sweden)

Christy Catherine

Full Text Available Progress towards genetic sequencing of human parasites has provided the groundwork for a post-genomic approach to develop novel antigens for the diagnosis and treatment of parasite infections. To fully utilize the genomic data, however, high-throughput methodologies are required for functional analysis of the proteins encoded in the genomic sequences. In this study, we investigated cell-free expression and in situ immobilization of parasite proteins as a novel platform for the discovery of antigenic proteins. PCR-amplified parasite DNA was immobilized on microbeads that were also functionalized to capture synthesized proteins. When the microbeads were incubated in a reaction mixture for cell-free synthesis, proteins expressed from the microbead-immobilized DNA were instantly immobilized on the same microbeads, providing a physical linkage between the genetic information and encoded proteins. This approach of in situ expression and isolation enables streamlined recovery and analysis of cell-free synthesized proteins and also allows facile identification of the genes coding antigenic proteins through direct PCR of the microbead-bound DNA.

A Genetic Algorithms Based Approach for Identification of Escherichia coli Fed-batch Fermentation

Directory of Open Access Journals (Sweden)

Olympia Roeva

2004-10-01

Full Text Available This paper presents the use of genetic algorithms for identification of Escherichia coli fed-batch fermentation process. Genetic algorithms are a directed random search technique, based on the mechanics of natural selection and natural genetics, which can find the global optimal solution in complex multidimensional search space. The dynamic behavior of considered process has known nonlinear structure, described with a system of deterministic nonlinear differential equations according to the mass balance. The parameters of the model are estimated using genetic algorithms. Simulation examples for demonstration of the effectiveness and robustness of the proposed identification scheme are included. As a result, the model accurately predicts the process of cultivation of E. coli.

Post-traumatic growth enhances social identification in liver transplant patients: A longitudinal study.

Science.gov (United States)

Scrignaro, Marta; Sani, Fabio; Wakefield, Juliet Ruth Helen; Bianchi, Elisabetta; Magrin, Maria Elena; Gangeri, Laura

2016-09-01

The main aim of this paper is to investigate the prediction that greater subjective identification with relevant groups and social categories (i.e. 'family' and 'transplantees') can be an outcome of post-traumatic growth (PTG). To date there are no studies that have explored these relationships. A longitudinal study was conducted with a group of 100 liver transplant patients from the outpatient populations of the participating centre. Data were collected by means of a self-report questionnaire, which was completed at two different time points (T1 and T2) that were 24months apart. PTG was assessed using the Post-Traumatic Growth Inventory, while both transplantee and family identification were assessed using group identification scales. A path model was tested, using a structural equation model (SEM) approach, to examine the reciprocal effects among family identification, transplantee identification, and PTG over time. As predicted, we found that greater PTG T1 predicted both greater family identification T2 and marginally greater transplantee identification T2. However, the two identification variables did not predict PTG over time. The results show that family identification and transplantee identification may be outcomes of the PTG process, confirming the importance of adopting a thriving multidimensional model of adjustment to medical illness, whereby people facing adverse life events, such as transplantation, may flourish rather than deteriorate psychologically. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2013-07-01

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

Identification of Host Defense-Related Proteins Using Label-Free Quantitative Proteomic Analysis of Milk Whey from Cows with Staphylococcus aureus Subclinical Mastitis

Directory of Open Access Journals (Sweden)

Shaimaa Abdelmegid

2017-12-01

Full Text Available Staphylococcus aureus is the most common contagious pathogen associated with bovine subclinical mastitis. Current diagnosis of S. aureus mastitis is based on bacteriological culture of milk samples and somatic cell counts, which lack either sensitivity or specificity. Identification of milk proteins that contribute to host defense and their variable responses to pathogenic stimuli would enable the characterization of putative biomarkers of subclinical mastitis. To accomplish this, milk whey samples from healthy and mastitic dairy cows were analyzed using a label-free quantitative proteomics approach. In total, 90 proteins were identified, of which 25 showed significant differential abundance between healthy and mastitic samples. In silico functional analyses indicated the involvement of the differentially abundant proteins in biological mechanisms and signaling pathways related to host defense including pathogen-recognition, direct antimicrobial function, and the acute-phase response. This proteomics and bioinformatics analysis not only facilitates the identification of putative biomarkers of S. aureus subclinical mastitis but also recapitulates previous findings demonstrating the abundance of host defense proteins in intramammary infection. All mass spectrometry data are available via ProteomeXchange with identifier PXD007516.

MODELO MULTIDIMENSIONAL

Directory of Open Access Journals (Sweden)

Alexis Cedeño Trujillo

2006-04-01

Full Text Available

Data Warehousing, es una tecnología para el almacenamiento de grandes volúmenes de datos en una amplia perspectiva de tiempo para el soporte a la toma de decisiones. Debido a su orientación analítica, impone un procesamiento distinto al de los sistemas operacionales y requiere de un diseño de base de datos más cercano a la visión de los usuarios finales, permitiendo que sea más fácil la recuperación de información y la navegación. Este diseño de base de datos se conoce como modelo multidimensional, este artículo, abordará sus características principales.

Efficient Isolation and Quantitative Proteomic Analysis of Cancer Cell Plasma Membrane Proteins for Identification of Metastasis-Associated Cell Surface Markers

DEFF Research Database (Denmark)

Lund, Rikke; Leth-Larsen, Rikke; Jensen, Ole N

2009-01-01

Cell surface membrane proteins are involved in central processes such as cell signaling, cell-cell interactions, ion and solute transport, and they seem to play a pivotal role in several steps of the metastatic process of cancer cells. The low abundance and hydrophobic nature of cell surface...... membrane proteins complicate their purification and identification by MS. We used two isogenic cell lines with opposite metastatic capabilities in nude mice to optimize cell surface membrane protein purification and to identify potential novel markers of metastatic cancer. The cell surface membrane...... proteins were isolated by centrifugation/ultracentrifugation steps, followed by membrane separation using a Percoll/sucrose density gradient. The gradient fractions containing the cell surface membrane proteins were identified by enzymatic assays. Stable isotope labeling of the proteome of the metastatic...

Decreasing the amount of trypsin in in-gel digestion leads to diminished chemical noise and improved protein identifications.

Science.gov (United States)

Hu, Mo; Liu, Yanhua; Yu, Kaiwen; Liu, Xiaoyun

2014-09-23

Pre-fractionation by gel electrophoresis is often combined with liquid chromatography-mass spectrometry (LC-MS) for large-scale profiling of complex protein samples. An essential component of this widely applied proteomic platform is in-gel protein digestion. In nearly two decades of practicing this approach, an extremely high level of trypsin has been utilized due to the consideration of slow enzyme diffusion into the gel matrix. Here we report that trypsin autolysis products contribute to the bulk of chemical noise in in-gel digestion and remarkably we found evidence that the amount of trypsin can be slashed by an order of magnitude with comparable digestion performance. By revising perhaps the most critical element of this decade-old digestion protocol, the proteomics community relying on gel separation prior to LC-MS analysis will benefit instantly from much lowered cost due to enzyme expenditure. More importantly, substantially reduced chemical noise (i.e., trypsin self-cleavage products) as a result of less enzyme usage translates into more protein identifications when limited amounts of samples are the interest of interrogation. In-gel digestion is one of the most widely used methods in proteomics. An exceedingly high level of trypsin has been utilized due to the consideration of slow enzyme diffusion into the gel matrix. This requirement has been faithfully kept in nearly two decades of practicing this approach. Here we report that trypsin concentration can be slashed by at least an order of magnitude while still providing comparable digestion performance. Thus the proteomics community relying on gel separation prior to LC-MS analysis will benefit instantly from much lowered enzyme cost. More importantly, substantially reduced chemical noise (i.e., trypsin autolysis products) due to less enzyme usage translates into ~30% more protein identifications when limited amounts of protein samples are analyzed. Copyright © 2014 Elsevier B.V. All rights reserved.

Disease candidate gene identification and prioritization using protein interaction networks

Directory of Open Access Journals (Sweden)

Aronow Bruce J

2009-02-01

Full Text Available Abstract Background Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN analyses. Results For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate genes in a training-test schema. Using a list of known disease-related genes from our earlier study as a training set ("seeds", and the rest of the known genes as a test list, we perform large-scale cross validation to rank the candidate genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Conclusion Even though network-based methods are generally not as effective as integrated functional annotation-based methods for disease candidate gene prioritization, in a one-to-one comparison, PPIN-based candidate gene prioritization performs better than all other gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate gene prioritization.

A human rights-consistent approach to multidimensional welfare measurement applied to sub-Saharan Africa

DEFF Research Database (Denmark)

Arndt, Channing; Mahrt, Kristi; Hussain, Azhar

2017-01-01

is in reality inconsistent with the Universal Declaration of Human Rights principles of indivisibility, inalienability, and equality. We show that a first-order dominance methodology maintains consistency with basic principles, discuss the properties of the multidimensional poverty index and first......The rights-based approach to development targets progress towards the realization of 30 articles set forth in the Universal Declaration of Human Rights. Progress is frequently measured using the multidimensional poverty index. While elegant and useful, the multidimensional poverty index...

MULTIDIMENSIONAL MODELING OF CORONAL RAIN DYNAMICS

Energy Technology Data Exchange (ETDEWEB)

Fang, X.; Xia, C.; Keppens, R. [Centre for mathematical Plasma Astrophysics, Department of Mathematics, KU Leuven, B-3001 Leuven (Belgium)

2013-07-10

We present the first multidimensional, magnetohydrodynamic simulations that capture the initial formation and long-term sustainment of the enigmatic coronal rain phenomenon. We demonstrate how thermal instability can induce a spectacular display of in situ forming blob-like condensations which then start their intimate ballet on top of initially linear force-free arcades. Our magnetic arcades host a chromospheric, transition region, and coronal plasma. Following coronal rain dynamics for over 80 minutes of physical time, we collect enough statistics to quantify blob widths, lengths, velocity distributions, and other characteristics which directly match modern observational knowledge. Our virtual coronal rain displays the deformation of blobs into V-shaped features, interactions of blobs due to mostly pressure-mediated levitations, and gives the first views of blobs that evaporate in situ or are siphoned over the apex of the background arcade. Our simulations pave the way for systematic surveys of coronal rain showers in true multidimensional settings to connect parameterized heating prescriptions with rain statistics, ultimately allowing us to quantify the coronal heating input.

MULTIDIMENSIONAL MODELING OF CORONAL RAIN DYNAMICS

International Nuclear Information System (INIS)

Fang, X.; Xia, C.; Keppens, R.

2013-01-01

We present the first multidimensional, magnetohydrodynamic simulations that capture the initial formation and long-term sustainment of the enigmatic coronal rain phenomenon. We demonstrate how thermal instability can induce a spectacular display of in situ forming blob-like condensations which then start their intimate ballet on top of initially linear force-free arcades. Our magnetic arcades host a chromospheric, transition region, and coronal plasma. Following coronal rain dynamics for over 80 minutes of physical time, we collect enough statistics to quantify blob widths, lengths, velocity distributions, and other characteristics which directly match modern observational knowledge. Our virtual coronal rain displays the deformation of blobs into V-shaped features, interactions of blobs due to mostly pressure-mediated levitations, and gives the first views of blobs that evaporate in situ or are siphoned over the apex of the background arcade. Our simulations pave the way for systematic surveys of coronal rain showers in true multidimensional settings to connect parameterized heating prescriptions with rain statistics, ultimately allowing us to quantify the coronal heating input.

A Multidimensional Theory of Suicide.

Science.gov (United States)

Leenaars, Antoon A; Dieserud, Gudrun; Wenckstern, Susanne; Dyregrov, Kari; Lester, David; Lyke, Jennifer

2018-04-05

Theory is the foundation of science; this is true in suicidology. Over decades of studies of suicide notes, Leenaars developed a multidimensional model of suicide, with international (crosscultural) studies and independent verification. To corroborate Leenaars's theory with a psychological autopsy (PA) study, examining age and sex of the decedent, and survivor's relationship to deceased. A PA study in Norway, with 120 survivors/informants was undertaken. Leenaars' theoretical-conceptual (protocol) analysis was undertaken of the survivors' narratives and in-depth interviews combined. Substantial interjudge reliability was noted (κ = .632). Overall, there was considerable confirmatory evidence of Leenaars's intrapsychic and interpersonal factors in suicide survivors' narratives. Differences were found in the age of the decedent, but not in sex, nor in the survivor's closeness of the relationship. Older deceased people were perceived to exhibit more heightened unbearable intrapsychic pain, associated with the suicide. Leenaars's theory has corroborative verification, through the decedents' suicide notes and the survivors' narratives. However, the multidimensional model needs further testing to develop a better evidence-based way of understanding suicide.

Confirmatory factor analysis and invariance testing between Blacks and Whites of the Multidimensional Health Locus of Control scale.

Science.gov (United States)

LaNoue, Marianna; Harvey, Abby; Mautner, Dawn; Ku, Bon; Scott, Kevin

2015-07-01

The factor structure of the Multidimensional Health Locus of Control scale remains in question. Additionally, research on health belief differences between Black and White respondents suggests that the Multidimensional Health Locus of Control scale may not be invariant. We reviewed the literature regarding the latent variable structure of the Multidimensional Health Locus of Control scale, used confirmatory factor analysis to confirm the three-factor structure of the Multidimensional Health Locus of Control, and analyzed between-group differences in the Multidimensional Health Locus of Control structure and means across Black and White respondents. Our results indicate differences in means and structure, indicating more research is needed to inform decisions regarding whether and how to deploy the Multidimensional Health Locus of Control appropriately.

A novel strategy for NMR resonance assignment and protein structure determination

International Nuclear Information System (INIS)

Lemak, Alexander; Gutmanas, Aleksandras; Chitayat, Seth; Karra, Murthy; Farès, Christophe; Sunnerhagen, Maria; Arrowsmith, Cheryl H.

2011-01-01

The quality of protein structures determined by nuclear magnetic resonance (NMR) spectroscopy is contingent on the number and quality of experimentally-derived resonance assignments, distance and angular restraints. Two key features of protein NMR data have posed challenges for the routine and automated structure determination of small to medium sized proteins; (1) spectral resolution – especially of crowded nuclear Overhauser effect spectroscopy (NOESY) spectra, and (2) the reliance on a continuous network of weak scalar couplings as part of most common assignment protocols. In order to facilitate NMR structure determination, we developed a semi-automated strategy that utilizes non-uniform sampling (NUS) and multidimensional decomposition (MDD) for optimal data collection and processing of selected, high resolution multidimensional NMR experiments, combined it with an ABACUS protocol for sequential and side chain resonance assignments, and streamlined this procedure to execute structure and refinement calculations in CYANA and CNS, respectively. Two graphical user interfaces (GUIs) were developed to facilitate efficient analysis and compilation of the data and to guide automated structure determination. This integrated method was implemented and refined on over 30 high quality structures of proteins ranging from 5.5 to 16.5 kDa in size.

Development and Validation of Multi-Dimensional Personality ...

African Journals Online (AJOL)

This study was carried out to establish the scientific processes for the development and validation of Multi-dimensional Personality Inventory (MPI). The process of development and validation occurred in three phases with five components of Agreeableness, Conscientiousness, Emotional stability, Extroversion, and ...

Analysis of Multidimensional Poverty: Theory and Case Studies ...

International Development Research Centre (IDRC) Digital Library (Canada)

2009-08-18

Aug 18, 2009 ... ... of applying a factorial technique, Multiple Correspondence Analysis, to poverty analysis. ... Analysis of Multidimensional Poverty: Theory and Case Studies ... agreement to support joint research projects in December 2017.

Magnetic resonance studies of isotopically labeled paramagnetic proteins: (2FE-2S) ferredoxins

Energy Technology Data Exchange (ETDEWEB)

Cheng, H.; Xia, B.; Chae, Y.K.; Westler, W.M.; Markley, J.L. [Univ. of Wisconsin, Madison, WI (United States)

1994-12-01

Recent developments in NMR spectroscopy, especially multidimensional, multinuclear NMR techniques, have made NMR the most versatile tool available for studying protein structure and function in solution. Unlike diamagnetic proteins, paramagnetic proteins contain centers with unpaired electrons. These unpaired electrons interact with magnetic nuclei either through chemical bonds by a contact mechanism or through space by a pseudocontact mechanism. Such interactions make the acquisition and analysis of NMR spectra of paramagnetic proteins more challenging than those of diamagnetic proteins. Some NMR signals from paramagnetic proteins are shifted outside the chemical shift region characteristic of diamagnetic proteins; these {open_quotes}hyperfine-shifted{close_quotes} resonances originate from nuclei that interact with unpaired electrons from the paramagnetic center. The large chemical shift dispersion in spectra of paramagnetic proteins makes it difficult to excite the entire spectral window and leads to distortions in the baseline. Interactions with paramagnetic centers shorten T{sub 1} and T{sub 2} relaxation times of nuclei; the consequences are line broadening and lower spectral sensitivity. Scalar (through bond) and dipolar (through space) interactions between pairs of nuclei are what give rise to crosspeak signals in multi-dimensional NMR spectra of small diamagnetic proteins. When such interactions involve a nucleus that is strongly relaxed by interaction with a paramagnetic center, specialized methods may be needed for its detection or it may be completely undetectable by present nD NMR methods.

Evaluation of a simple protein extraction method for species identification of clinically relevant staphylococci by matrix-assisted laser desorption ionization-time of flight mass spectrometry.

Science.gov (United States)

Matsuda, Naoto; Matsuda, Mari; Notake, Shigeyuki; Yokokawa, Hirohide; Kawamura, Yoshiaki; Hiramatsu, Keiichi; Kikuchi, Ken

2012-12-01

In clinical microbiology, bacterial identification is labor-intensive and time-consuming. A solution for this problem is the use of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). In this study, we evaluated a modified protein extraction method of identification performed on target plates (on-plate extraction method) with MALDI-TOF (Bruker Microflex LT with Biotyper version 3.0) and compared it to 2 previously described methods: the direct colony method and a standard protein extraction method (standard extraction method). We evaluated the species of 273 clinical strains and 14 reference strains of staphylococci. All isolates were characterized using the superoxide dismutase A sequence as a reference. For the species identification, the on-plate, standard extraction, and direct colony methods identified 257 isolates (89.5%), 232 isolates (80.8%), and 173 isolates (60.2%), respectively, with statistically significant differences among the three methods (P extraction method is at least as good as standard extraction in identification rate and has the advantage of a shorter processing time.

Temperature-induced transitions in disordered proteins probed by NMR spectroscopy

DEFF Research Database (Denmark)

Kjærgaard, Magnus; Poulsen, Flemming Martin; Kragelund, Birthe Brandt

2012-01-01

Intrinsically disordered proteins are abundant in nature and perform many important physiological functions. Multidimensional NMR spectroscopy has been crucial for the understanding of the conformational properties of disordered proteins and is increasingly used to probe their conformational...... ensembles. Compared to folded proteins, disordered proteins are more malleable and more easily perturbed by environmental factors. Accordingly, the experimental conditions and especially the temperature modify the structural and functional properties of disordered proteins. NMR spectroscopy allows analysis...... of temperature-induced structural changes at residue resolution using secondary chemical shift analysis, paramagnetic relaxation enhancement, and residual dipolar couplings. This chapter discusses practical aspects of NMR studies of temperature-induced structural changes in disordered proteins....

Translation and Validation of the Multidimensional Dyspnea-12 Questionnaire.

Science.gov (United States)

Amado Diago, Carlos Antonio; Puente Maestu, Luis; Abascal Bolado, Beatriz; Agüero Calvo, Juan; Hernando Hernando, Mercedes; Puente Bats, Irene; Agüero Balbín, Ramón

2018-02-01

Dyspnea is a multidimensional symptom, but this multidimensionality is not considered in most dyspnea questionnaires. The Dyspnea-12 takes a multidimensional approach to the assessment of dyspnea, specifically the sensory and the affective response. The objective of this study was to translate into Spanish and validate the Dyspnea-12 questionnaire. The original English version of the Dyspnea-12 questionnaire was translated into Spanish and backtranslated to analyze its equivalence. Comprehension of the text was verified by analyzing the responses of 10 patients. Reliability and validation of the questionnaire were studied in an independent group of COPD patients attending the pulmonology clinics of Hospital Universitario Marqués de Valdecilla, diagnosed and categorized according to GOLD guidelines. The mean age of the group (n=51) was 65 years and mean FEV1 was 50%. All patients understood all questions of the translated version of Dyspnea-12. Internal consistency of the questionnaire was α=0.937 and intraclass correlation coefficient was=.969; P<.001. Statistically significant correlations were found with HADS (anxiety r=.608 and depression r=.615), mMRC dyspnea (r=.592), 6MWT (r=-0.445), FEV1 (r=-0.312), all dimensions of CRQ-SAS (dyspnea r=-0.626; fatigue r=-0.718; emotional function r=-0.663; mastery r=-0.740), CAT (r=0.669), and baseline dyspnea index (r=-0.615). Dyspnea-12 scores were 10.32 points higher in symptomatic GOLD groups (B and D) (P<.001). The Spanish version of Dyspnea-12 is a valid and reliable instrument to study the multidimensional nature of dyspnea. Copyright © 2017 SEPAR. Publicado por Elsevier España, S.L.U. All rights reserved.

Multidimensional upwind hydrodynamics on unstructured meshes using graphics processing units - I. Two-dimensional uniform meshes

Science.gov (United States)

Paardekooper, S.-J.

2017-08-01

We present a new method for numerical hydrodynamics which uses a multidimensional generalization of the Roe solver and operates on an unstructured triangular mesh. The main advantage over traditional methods based on Riemann solvers, which commonly use one-dimensional flux estimates as building blocks for a multidimensional integration, is its inherently multidimensional nature, and as a consequence its ability to recognize multidimensional stationary states that are not hydrostatic. A second novelty is the focus on graphics processing units (GPUs). By tailoring the algorithms specifically to GPUs, we are able to get speedups of 100-250 compared to a desktop machine. We compare the multidimensional upwind scheme to a traditional, dimensionally split implementation of the Roe solver on several test problems, and we find that the new method significantly outperforms the Roe solver in almost all cases. This comes with increased computational costs per time-step, which makes the new method approximately a factor of 2 slower than a dimensionally split scheme acting on a structured grid.

Identification of Protein Pupylation Sites Using Bi-Profile Bayes Feature Extraction and Ensemble Learning

Directory of Open Access Journals (Sweden)

Xiaowei Zhao

2013-01-01

Full Text Available Pupylation, one of the most important posttranslational modifications of proteins, typically takes place when prokaryotic ubiquitin-like protein (Pup is attached to specific lysine residues on a target protein. Identification of pupylation substrates and their corresponding sites will facilitate the understanding of the molecular mechanism of pupylation. Comparing with the labor-intensive and time-consuming experiment approaches, computational prediction of pupylation sites is much desirable for their convenience and fast speed. In this study, a new bioinformatics tool named EnsemblePup was developed that used an ensemble of support vector machine classifiers to predict pupylation sites. The highlight of EnsemblePup was to utilize the Bi-profile Bayes feature extraction as the encoding scheme. The performance of EnsemblePup was measured with a sensitivity of 79.49%, a specificity of 82.35%, an accuracy of 85.43%, and a Matthews correlation coefficient of 0.617 using the 5-fold cross validation on the training dataset. When compared with other existing methods on a benchmark dataset, the EnsemblePup provided better predictive performance, with a sensitivity of 80.00%, a specificity of 83.33%, an accuracy of 82.00%, and a Matthews correlation coefficient of 0.629. The experimental results suggested that EnsemblePup presented here might be useful to identify and annotate potential pupylation sites in proteins of interest. A web server for predicting pupylation sites was developed.

Computational identification of binding energy hot spots in protein-RNA complexes using an ensemble approach.

Science.gov (United States)

Pan, Yuliang; Wang, Zixiang; Zhan, Weihua; Deng, Lei

2018-05-01

Identifying RNA-binding residues, especially energetically favored hot spots, can provide valuable clues for understanding the mechanisms and functional importance of protein-RNA interactions. Yet, limited availability of experimentally recognized energy hot spots in protein-RNA crystal structures leads to the difficulties in developing empirical identification approaches. Computational prediction of RNA-binding hot spot residues is still in its infant stage. Here, we describe a computational method, PrabHot (Prediction of protein-RNA binding hot spots), that can effectively detect hot spot residues on protein-RNA binding interfaces using an ensemble of conceptually different machine learning classifiers. Residue interaction network features and new solvent exposure characteristics are combined together and selected for classification with the Boruta algorithm. In particular, two new reference datasets (benchmark and independent) have been generated containing 107 hot spots from 47 known protein-RNA complex structures. In 10-fold cross-validation on the training dataset, PrabHot achieves promising performances with an AUC score of 0.86 and a sensitivity of 0.78, which are significantly better than that of the pioneer RNA-binding hot spot prediction method HotSPRing. We also demonstrate the capability of our proposed method on the independent test dataset and gain a competitive advantage as a result. The PrabHot webserver is freely available at http://denglab.org/PrabHot/. leideng@csu.edu.cn. Supplementary data are available at Bioinformatics online.

On simplified application of multidimensional Savitzky-Golay filters and differentiators

Science.gov (United States)

Shekhar, Chandra

2016-02-01

I propose a simplified approach for multidimensional Savitzky-Golay filtering, to enable its fast and easy implementation in scientific and engineering applications. The proposed method, which is derived from a generalized framework laid out by Thornley (D. J. Thornley, "Novel anisotropic multidimensional convolution filters for derivative estimation and reconstruction" in Proceedings of International Conference on Signal Processing and Communications, November 2007), first transforms any given multidimensional problem into a unique one, by transforming coordinates of the sampled data nodes to unity-spaced, uniform data nodes, and then performs filtering and calculates partial derivatives on the unity-spaced nodes. It is followed by transporting the calculated derivatives back onto the original data nodes by using the chain rule of differentiation. The burden to performing the most cumbersome task, which is to carry out the filtering and to obtain derivatives on the unity-spaced nodes, is almost eliminated by providing convolution coefficients for a number of convolution kernel sizes and polynomial orders, up to four spatial dimensions. With the availability of the convolution coefficients, the task of filtering at a data node reduces merely to multiplication of two known matrices. Simplified strategies to adequately address near-boundary data nodes and to calculate partial derivatives there are also proposed. Finally, the proposed methodologies are applied to a three-dimensional experimentally obtained data set, which shows that multidimensional Savitzky-Golay filters and differentiators perform well in both the internal and the near-boundary regions of the domain.

Evoking and Measuring Identification with Narrative Characters – A Linguistic Cues Framework

Science.gov (United States)

van Krieken, Kobie; Hoeken, Hans; Sanders, José

2017-01-01

Current research on identification with narrative characters poses two problems. First, although identification is seen as a dynamic process of which the intensity varies during reading, it is usually measured by means of post-reading questionnaires containing self-report items. Second, it is not clear which linguistic characteristics evoke identification. The present paper proposes that an interdisciplinary framework allows for more precise manipulations and measurements of identification, which will ultimately advance our understanding of the antecedents and nature of this process. The central hypothesis of our Linguistic Cues Framework is that identification with a narrative character is a multidimensional experience for which different dimensions are evoked by different linguistic cues. The first part of the paper presents a literature review on identification, resulting in a renewed conceptualization of identification which distinguishes six dimensions: a spatiotemporal, a perceptual, a cognitive, a moral, an emotional, and an embodied dimension. The second part argues that each of these dimensions is influenced by specific linguistic cues which represent various aspects of the narrative character’s perspective. The proposed relations between linguistic cues and identification dimensions are specified in six propositions. The third part discusses what psychological and neurocognitive methods enable the measurement of the various identification dimensions in order to test the propositions. By establishing explicit connections between the linguistic characteristics of narratives and readers’ physical, psychological, and neurocognitive responses to narratives, this paper develops a research agenda for future empirical research on identification with narrative characters. PMID:28751875

A Proteomic Approach for the Identification of Up-Regulated Proteins Involved in the Metabolic Process of the Leiomyoma.

Science.gov (United States)

Ura, Blendi; Scrimin, Federica; Arrigoni, Giorgio; Franchin, Cinzia; Monasta, Lorenzo; Ricci, Giuseppe

2016-04-09

Uterine leiomyoma is the most common benign smooth muscle cell tumor of the uterus. Proteomics is a powerful tool for the analysis of complex mixtures of proteins. In our study, we focused on proteins that were upregulated in the leiomyoma compared to the myometrium. Paired samples of eight leiomyomas and adjacent myometrium were obtained and submitted to two-dimensional gel electrophoresis (2-DE) and mass spectrometry for protein identification and to Western blotting for 2-DE data validation. The comparison between the patterns revealed 24 significantly upregulated (p leiomyoma and not with the normal myometrium. The overexpression of seven proteins involved in the metabolic processes of the leiomyoma was further validated by Western blotting and 2D Western blotting. Four of these proteins have never been associated with the leiomyoma before. The 2-DE approach coupled with mass spectrometry, which is among the methods of choice for comparative proteomic studies, identified a number of proteins overexpressed in the leiomyoma and involved in several biological processes, including metabolic processes. A better understanding of the mechanism underlying the overexpression of these proteins may be important for therapeutic purposes.

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity.

Science.gov (United States)

Barkla, Bronwyn J

2016-09-08

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity

Directory of Open Access Journals (Sweden)

Bronwyn J. Barkla

2016-09-01

Full Text Available Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

Lagrangian multiforms and multidimensional consistency

Energy Technology Data Exchange (ETDEWEB)

Lobb, Sarah; Nijhoff, Frank [Department of Applied Mathematics, University of Leeds, Leeds LS2 9JT (United Kingdom)

2009-10-30

We show that well-chosen Lagrangians for a class of two-dimensional integrable lattice equations obey a closure relation when embedded in a higher dimensional lattice. On the basis of this property we formulate a Lagrangian description for such systems in terms of Lagrangian multiforms. We discuss the connection of this formalism with the notion of multidimensional consistency, and the role of the lattice from the point of view of the relevant variational principle.

The 'thousand words' problem: Summarizing multi-dimensional data

International Nuclear Information System (INIS)

Scott, David M.

2011-01-01

Research highlights: → Sophisticated process sensors produce large multi-dimensional data sets. → Plant control systems cannot handle images or large amounts of data. → Various techniques reduce the dimensionality, extracting information from raw data. → Simple 1D and 2D methods can often be extended to 3D and 4D applications. - Abstract: An inherent difficulty in the application of multi-dimensional sensing to process monitoring and control is the extraction and interpretation of useful information. Ultimately the measured data must be collapsed into a relatively small number of values that capture the salient characteristics of the process. Although multiple dimensions are frequently necessary to isolate a particular physical attribute (such as the distribution of a particular chemical species in a reactor), plant control systems are not equipped to use such data directly. The production of a multi-dimensional data set (often displayed as an image) is not the final step of the measurement process, because information must still be extracted from the raw data. In the metaphor of one picture being equal to a thousand words, the problem becomes one of paraphrasing a lengthy description of the image with one or two well-chosen words. Various approaches to solving this problem are discussed using examples from the fields of particle characterization, image processing, and process tomography.

Multidimensional building objects in a Danish geo-information infrastructure perspective

DEFF Research Database (Denmark)

Schrøder, Lise

2002-01-01

The emerging multidimensional GI- and VR-technologies within the professional disciplines dealing with design, planning and management processes is leading to a demand for four-dimensional building objects as part of the public geo-information infrastructure. The other way around the recognition...... of the building as a four-dimensional geo-phenomenon will provide a reference between different data sets whether representing buildings in two, three or four dimensions. Finally a central issue is the potential in using frameworks of multidimensional representations as interfaces to the available data sets...

Identification of Surface Protein Biomarkers of Listeria monocytogenes via Bioinformatics and Antibody-Based Protein Detection Tools

Science.gov (United States)

Zhang, Cathy X. Y.; Brooks, Brian W.; Huang, Hongsheng; Pagotto, Franco

2016-01-01

ABSTRACT The Gram-positive bacterium Listeria monocytogenes causes a significant percentage of the fatalities among foodborne illnesses in humans. Surface proteins specifically expressed in a wide range of L. monocytogenes serotypes under selective enrichment culture conditions could serve as potential biomarkers for detection and isolation of this pathogen via antibody-based methods. Our study aimed to identify such biomarkers. Interrogation of the L. monocytogenes serotype 4b strain F2365 genome identified 130 putative or known surface proteins. The homologues of four surface proteins, LMOf2365_0578, LMOf2365_0581, LMOf2365_0639, and LMOf2365_2117, were assessed as biomarkers due to the presence of conserved regions among strains of L. monocytogenes which are variable among other Listeria species. Rabbit polyclonal antibodies against the four recombinant proteins revealed the expression of only LMOf2365_0639 on the surface of serotype 4b strain LI0521 cells despite PCR detection of mRNA transcripts for all four proteins in the organism. Three of 35 monoclonal antibodies (MAbs) to LMOf2365_0639, MAbs M3643, M3644, and M3651, specifically recognized 42 (91.3%) of 46 L. monocytogenes lineage I and II isolates grown in nonselective brain heart infusion medium. While M3644 and M3651 reacted with 14 to 15 (82.4 to 88.2%) of 17 L. monocytogenes lineage I and II isolates, M3643 reacted with 22 (91.7%) of 24 lineage I, II, and III isolates grown in selective enrichment media (UVM1, modified Fraser, Palcam, and UVM2 media). The three MAbs exhibited only weak reactivities (the optical densities at 414 nm were close to the cutoff value) to some other Listeria species grown in selective enrichment media. Collectively, the data indicate the potential of LMOf2365_0639 as a surface biomarker of L. monocytogenes, with the aid of specific MAbs, for pathogen detection, identification, and isolation in clinical, environmental, and food samples. IMPORTANCE L. monocytogenes is

Development, Content Validity, and User Review of a Web-based Multidimensional Pain Diary for Adolescent and Young Adults With Sickle Cell Disease.

Science.gov (United States)

Bakshi, Nitya; Stinson, Jennifer N; Ross, Diana; Lukombo, Ines; Mittal, Nonita; Joshi, Saumya V; Belfer, Inna; Krishnamurti, Lakshmanan

2015-06-01

Vaso-occlusive pain, the hallmark of sickle cell disease (SCD), is a major contributor to morbidity, poor health-related quality of life, and health care utilization associated with this disease. There is wide variation in the burden, frequency, and severity of pain experienced by patients with SCD. As compared with health care utilization for pain, a daily pain diary captures the breadth of the pain experience and is a superior measure of pain burden and its impact on patients. Electronic pain diaries based on real-time data capture methods overcome methodological barriers and limitations of paper pain diaries, but their psychometric properties have not been formally established in patients with SCD. To develop and establish the content validity of a web-based multidimensional pain diary for adolescents and young adults with SCD and conduct an end-user review to refine the prototype. Following identification of items, a conceptual model was developed. Interviews with adolescents and young adults with SCD were conducted. Subsequently, end-user review with use of the electronic pain diary prototype was conducted. Two iterative cycles of in-depth cognitive interviews in adolescents and young adults with SCD informed the design and guided the addition, removal, and modification of items in the multidimensional pain diary. Potential end-users provided positive feedback on the design and prototype of the electronic diary. A multidimensional web-based electronic pain diary for adolescents and young adults with SCD has been developed and content validity and initial end-user reviews have been completed.

pMD-Membrane: A Method for Ligand Binding Site Identification in Membrane-Bound Proteins.

Directory of Open Access Journals (Sweden)

Priyanka Prakash

2015-10-01

Full Text Available Probe-based or mixed solvent molecular dynamics simulation is a useful approach for the identification and characterization of druggable sites in drug targets. However, thus far the method has been applied only to soluble proteins. A major reason for this is the potential effect of the probe molecules on membrane structure. We have developed a technique to overcome this limitation that entails modification of force field parameters to reduce a few pairwise non-bonded interactions between selected atoms of the probe molecules and bilayer lipids. We used the resulting technique, termed pMD-membrane, to identify allosteric ligand binding sites on the G12D and G13D oncogenic mutants of the K-Ras protein bound to a negatively charged lipid bilayer. In addition, we show that differences in probe occupancy can be used to quantify changes in the accessibility of druggable sites due to conformational changes induced by membrane binding or mutation.

Prioritizing disease candidate proteins in cardiomyopathy-specific protein-protein interaction networks based on "guilt by association" analysis.

Directory of Open Access Journals (Sweden)

Wan Li

Full Text Available The cardiomyopathies are a group of heart muscle diseases which can be inherited (familial. Identifying potential disease-related proteins is important to understand mechanisms of cardiomyopathies. Experimental identification of cardiomyophthies is costly and labour-intensive. In contrast, bioinformatics approach has a competitive advantage over experimental method. Based on "guilt by association" analysis, we prioritized candidate proteins involving in human cardiomyopathies. We first built weighted human cardiomyopathy-specific protein-protein interaction networks for three subtypes of cardiomyopathies using the known disease proteins from Online Mendelian Inheritance in Man as seeds. We then developed a method in prioritizing disease candidate proteins to rank candidate proteins in the network based on "guilt by association" analysis. It was found that most candidate proteins with high scores shared disease-related pathways with disease seed proteins. These top ranked candidate proteins were related with the corresponding disease subtypes, and were potential disease-related proteins. Cross-validation and comparison with other methods indicated that our approach could be used for the identification of potentially novel disease proteins, which may provide insights into cardiomyopathy-related mechanisms in a more comprehensive and integrated way.

Identification of Open Stomata1-Interacting Proteins Reveals Interactions with Sucrose Non-fermenting1-Related Protein Kinases2 and with Type 2A Protein Phosphatases That Function in Abscisic Acid Responses1[OPEN

Science.gov (United States)

Waadt, Rainer; Manalansan, Bianca; Rauniyar, Navin; Munemasa, Shintaro; Booker, Matthew A.; Brandt, Benjamin; Waadt, Christian; Nusinow, Dmitri A.; Kay, Steve A.; Kunz, Hans-Henning; Schumacher, Karin; DeLong, Alison; Yates, John R.; Schroeder, Julian I.

2015-01-01

The plant hormone abscisic acid (ABA) controls growth and development and regulates plant water status through an established signaling pathway. In the presence of ABA, pyrabactin resistance/regulatory component of ABA receptor proteins inhibit type 2C protein phosphatases (PP2Cs). This, in turn, enables the activation of Sucrose Nonfermenting1-Related Protein Kinases2 (SnRK2). Open Stomata1 (OST1)/SnRK2.6/SRK2E is a major SnRK2-type protein kinase responsible for mediating ABA responses. Arabidopsis (Arabidopsis thaliana) expressing an epitope-tagged OST1 in the recessive ost1-3 mutant background was used for the copurification and identification of OST1-interacting proteins after osmotic stress and ABA treatments. These analyses, which were confirmed using bimolecular fluorescence complementation and coimmunoprecipitation, unexpectedly revealed homo- and heteromerization of OST1 with SnRK2.2, SnRK2.3, OST1, and SnRK2.8. Furthermore, several OST1-complexed proteins were identified as type 2A protein phosphatase (PP2A) subunits and as proteins involved in lipid and galactolipid metabolism. More detailed analyses suggested an interaction network between ABA-activated SnRK2-type protein kinases and several PP2A-type protein phosphatase regulatory subunits. pp2a double mutants exhibited a reduced sensitivity to ABA during seed germination and stomatal closure and an enhanced ABA sensitivity in root growth regulation. These analyses add PP2A-type protein phosphatases as another class of protein phosphatases to the interaction network of SnRK2-type protein kinases. PMID:26175513

Strategic Decision-Making: Research Mapping from Exploratory Factor Analysis and Multidimensional Scaling

Directory of Open Access Journals (Sweden)

Ivano Ribeiro

2017-04-01

Full Text Available To understand the connection between authors, concepts and theories that address strategic decision-making, in this article the citations and co-citations of works published up to 2014 were analyzed. The sample consists of 489 articles published in international periodicals included in the Web of Science-ISI Web of Knowledge database. The search was conducted using key words that enabled the identification of the highest possible number of articles on the subject in question. Through Multidimensional Scaling (MDS and Exploratory Factor Analysis (EFA, the conceptual and theoretical relationships involved in these studies were identified. The results show that from 1980 to 2014 three different factors are highlighted: the first has to do with studies on conflict; the second factor is the Top Management Team (TMT and decision-making; and the third is related to processes. More recently (2013-2014, studies on strategic decision-making are converging towards analysis of conflict and process, composition and control, with Upper Echelon Theory being maintained as the central theory in these studies. This finding is the main contribution of this article.

Identification of membrane proteins by tandem mass spectrometry of protein ions

Science.gov (United States)

Carroll, Joe; Altman, Matthew C.; Fearnley, Ian M.; Walker, John E.

2007-01-01

The most common way of identifying proteins in proteomic analyses is to use short segments of sequence (“tags”) determined by mass spectrometric analysis of proteolytic fragments. The approach is effective with globular proteins and with membrane proteins with significant polar segments between membrane-spanning α-helices, but it is ineffective with other hydrophobic proteins where protease cleavage sites are either infrequent or absent. By developing methods to purify hydrophobic proteins in organic solvents and by fragmenting ions of these proteins by collision induced dissociation with argon, we have shown that partial sequences of many membrane proteins can be deduced easily by manual inspection. The spectra from small proteolipids (1–4 transmembrane α-helices) are dominated usually by fragment ions arising from internal amide cleavages, from which internal sequences can be obtained, whereas the spectra from larger membrane proteins (5–18 transmembrane α-helices) often contain fragment ions from N- and/or C-terminal parts yielding sequences in those regions. With these techniques, we have, for example, identified an abundant protein of unknown function from inner membranes of mitochondria that to our knowledge has escaped detection in proteomic studies, and we have produced sequences from 10 of 13 proteins encoded in mitochondrial DNA. They include the ND6 subunit of complex I, the last of its 45 subunits to be analyzed. The procedures have the potential to be developed further, for example by using newly introduced methods for protein ion dissociation to induce fragmentation of internal regions of large membrane proteins, which may remain partially folded in the gas phase. PMID:17720804

Performance of VITEK mass spectrometry V3.0 for rapid identification of clinical Aspergillus fumigatus in different culture conditions based on ribosomal proteins.

Science.gov (United States)

Zhou, Longrong; Chen, Yongquan; Xu, Yuanhong

2017-01-01

Fast and accurate discrimination of Aspergillus fumigatus is significant, since misidentification may lead to inappropriate clinical therapy. This study assessed VITEK mass spectrometry (MS) V3.0 for A. fumigatus identification using extracted fungal ribosomal proteins. A total of 52 isolates preliminarily identified as A. fumigatus by traditional morphological methods were inoculated in three different culture media and cultured at two different temperatures. The specific spectral fingerprints of different culture time points (48, 72, 96, and 120 h) were obtained. Of all strains, 88.5% (46/52) were discriminated as A. fumigatus , while the remaining 11.5% (6/52) produced results inconsistent with morphological analysis. Molecular sequencing, as a reference method for species identification, was used to validate the morphological analysis and matrix-assisted laser desorption/ionization time of flight MS. Chi-square tests ( χ 2 test, P =0.05) demonstrated that the culture medium and incubation temperature had no effects on identification accuracy; however, identification accuracy of the strains in the 48-h group was lower than that in other groups. In addition, we found that ribosomal proteins extracted from A. fumigatus can be stored in different environments for at least 1 week, with their profiles remaining stable and strain identification results showing no change. This is beneficial for medical institutions with no mass spectrometer at hand. Overall, this study showed the powerful ability of VITEK MS V 3.0 in identifying A. fumigatus .

Recent developments in the theory of protein folding: searching for the global energy minimum.

Science.gov (United States)

Scheraga, H A

1996-04-16

Statistical mechanical theories and computer simulation are being used to gain an understanding of the fundamental features of protein folding. A major obstacle in the computation of protein structures is the multiple-minima problem arising from the existence of many local minima in the multidimensional energy landscape of the protein. This problem has been surmounted for small open-chain and cyclic peptides, and for regular-repeating sequences of models of fibrous proteins. Progress is being made in resolving this problem for globular proteins.

Nested element method in multidimensional neutron diffusion calculations

International Nuclear Information System (INIS)

Altiparmakov, D.V.

1983-01-01

A new numerical method is developed that is particularly efficient in solving the multidimensional neutron diffusion equation in geometrically complex systems. The needs for a generally applicable and fast running computer code have stimulated the inroad of a nonclassical (R-function) numerical method into the nuclear field. By using the R-functions, the geometrical components of the diffusion problem are a priori analytically implemented into the approximate solution. The class of functions, to which the approximate solution belongs, is chosen as close to the exact solution class as practically acceptable from the time consumption point of view. That implies a drastic reduction of the number of degrees of freedom, compared to the other methods. Furthermore, the reduced number of degrees of freedom enables calculation of large multidimensional problems on small computers

Optimal multi-dimensional poverty lines: The state of poverty in Iraq

Science.gov (United States)

Ameen, Jamal R. M.

2017-09-01

Poverty estimation based on calories intake is unrealistic. The established concept of multidimensional poverty has methodological weaknesses in the treatment of different dimensions and there is disagreement in methods of combining them into a single poverty line. This paper introduces a methodology to estimate optimal multidimensional poverty lines and uses the Iraqi household socio-economic survey data of 2012 to demonstrate the idea. The optimal poverty line for Iraq is found to be 170.5 Thousand Iraqi Dinars (TID).

Multidimensional Screening as a Pharmacology Laboratory Experience.

Science.gov (United States)

Malone, Marvin H.; And Others

1979-01-01

A multidimensional pharmacodynamic screening experiment that addresses drug interaction is included in the pharmacology-toxicology laboratory experience of pharmacy students at the University of the Pacific. The student handout with directions for the procedure is reproduced, drug compounds tested are listed, and laboratory evaluation results are…

Identification of a key structural element for protein folding within beta-hairpin turns.

Science.gov (United States)

Kim, Jaewon; Brych, Stephen R; Lee, Jihun; Logan, Timothy M; Blaber, Michael

2003-05-09

Specific residues in a polypeptide may be key contributors to the stability and foldability of the unique native structure. Identification and prediction of such residues is, therefore, an important area of investigation in solving the protein folding problem. Atypical main-chain conformations can help identify strains within a folded protein, and by inference, positions where unique amino acids may have a naturally high frequency of occurrence due to favorable contributions to stability and folding. Non-Gly residues located near the left-handed alpha-helical region (L-alpha) of the Ramachandran plot are a potential indicator of structural strain. Although many investigators have studied mutations at such positions, no consistent energetic or kinetic contributions to stability or folding have been elucidated. Here we report a study of the effects of Gly, Ala and Asn substitutions found within the L-alpha region at a characteristic position in defined beta-hairpin turns within human acidic fibroblast growth factor, and demonstrate consistent effects upon stability and folding kinetics. The thermodynamic and kinetic data are compared to available data for similar mutations in other proteins, with excellent agreement. The results have identified that Gly at the i+3 position within a subset of beta-hairpin turns is a key contributor towards increasing the rate of folding to the native state of the polypeptide while leaving the rate of unfolding largely unchanged.

Multidimensional Learner Model In Intelligent Learning System

Science.gov (United States)

Deliyska, B.; Rozeva, A.

2009-11-01

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

A PCA-Based Change Detection Framework for Multidimensional Data Streams

KAUST Repository

Qahtan, Abdulhakim Ali Ali

2015-08-10

Detecting changes in multidimensional data streams is an important and challenging task. In unsupervised change detection, changes are usually detected by comparing the distribution in a current (test) window with a reference window. It is thus essential to design divergence metrics and density estimators for comparing the data distributions, which are mostly done for univariate data. Detecting changes in multidimensional data streams brings difficulties to the density estimation and comparisons. In this paper, we propose a framework for detecting changes in multidimensional data streams based on principal component analysis, which is used for projecting data into a lower dimensional space, thus facilitating density estimation and change-score calculations. The proposed framework also has advantages over existing approaches by reducing computational costs with an efficient density estimator, promoting the change-score calculation by introducing effective divergence metrics, and by minimizing the efforts required from users on the threshold parameter setting by using the Page-Hinkley test. The evaluation results on synthetic and real data show that our framework outperforms two baseline methods in terms of both detection accuracy and computational costs.

Biosynthetically directed fractional 13C labeling facilitates identification of Phe and Tyr aromatic signals in proteins

International Nuclear Information System (INIS)

Jacob, Jaison; Louis, John M.; Nesheiwat, Issa; Torchia, Dennis A.

2002-01-01

Analysis of 2D [ 13 C, 1 H]-HSQC spectra of biosynthetic fractionally 13 C labeled proteins is a reliable, straightforward means to obtain stereospecific assignments of Val and Leu methyl sites in proteins. Herein we show that the same fractionally labeled protein sample facilitates observation and identification of Phe and Tyr aromatic signals. This is the case, in part, because the fractional 13 C labeling yields aromatic rings in which some of the 13 C- 13 C J-couplings, present in uniformly labeled samples, are absent. Also, the number of homonuclear J-coupling partners differs for the δ-, ε- and ζ-carbons. This enabled us to vary their signal intensities in distinctly different ways by appropriately setting the 13 C constant-time period in 2D [ 13 C, 1 H]-HSQC spectra. We illustrate the application of this approach to an 18 kDa protein, c-VIAF, a modulator of apoptosis. In addition, we show that cancellation of the aromatic 13 C CSA and 13 C- 1 H dipolar interactions can be fruitfully utilized in the case of the fractionally labeled sample to obtain high resolution 13 C constant-time spectra with good sensitivity

ContaMiner and ContaBase: a webserver and database for early identification of unwantedly crystallized protein contaminants

Science.gov (United States)

Hungler, Arnaud; Momin, Afaque; Diederichs, Kay; Arold, Stefan, T.

2016-01-01

Solving the phase problem in protein X-ray crystallography relies heavily on the identity of the crystallized protein, especially when molecular replacement (MR) methods are used. Yet, it is not uncommon that a contaminant crystallizes instead of the protein of interest. Such contaminants may be proteins from the expression host organism, protein fusion tags or proteins added during the purification steps. Many contaminants co-purify easily, crystallize and give good diffraction data. Identification of contaminant crystals may take time, since the presence of the contaminant is unexpected and its identity unknown. A webserver (ContaMiner) and a contaminant database (ContaBase) have been established, to allow fast MR-based screening of crystallographic data against currently 62 known contaminants. The web-based ContaMiner (available at http://strube.cbrc.kaust.edu.sa/contaminer/) currently produces results in 5 min to 4 h. The program is also available in a github repository and can be installed locally. ContaMiner enables screening of novel crystals at synchrotron beamlines, and it would be valuable as a routine safety check for ‘crystallization and preliminary X-ray analysis’ publications. Thus, in addition to potentially saving X-ray crystallographers much time and effort, ContaMiner might considerably lower the risk of publishing erroneous data. PMID:27980519

Heuristic learning parameter identification for surveillance and diagnostics of nuclear power plants

International Nuclear Information System (INIS)

Machado, E.L.

1983-01-01

A new method of heuristic reinforcement learning was developed for parameter identification purposes. In essence, this new parameter identification technique is based on the idea of breaking a multidimensional search for the minimum of a given functional into a set of unidirectional searches in parameter space. Each search situation is associated with one block in a memory organized into cells, where the information learned about the situations is stored (e.g. the optimal directions in parameter space). Whenever the search falls into an existing memory cell, the system chooses the learned direction. For new search situations, the system creates additional memory cells. This algorithm imitates the following cognitive process: 1) characterize a situation, 2) select an optimal action, 3) evaluate the consequences of the action, and 4) memorize the results for future use. As a result, this algorithm is trainable in the sense that it can learn from previous experience within a specific class of parameter identification problems

Multidimensionality of thinking in the context of creativity studies.

Directory of Open Access Journals (Sweden)

Belolutskaya A.K.

2015-03-01

Full Text Available This article describes the theoretical difference between the flexibility and the multidimensionality of thinking. Multidimensionality is discussed as a characteristic of thinking that is necessary for exploration of the variability of structural transformations of problematic situations. The objective of the study was to examine a number of theories concerning the correlative connection between the multidimensionality of thinking and other characteristics of creative, productive thinking: the flexibility of thinking; the formation of an operation of dialectical thinking such as “mediation”; the ability of a person to use a scheme as an abstraction for analysis of various specific content. A total of 85 people participated in the study: they were 15 to 17 years old, students at a senior school in Kaliningradskaya oblast, winners of different stages of the all-Russian academic competition in physics, chemistry, and mathematics. All respondents had a high level of academic success and of general intelligence. The following techniques were used in this study: (1 my technique for diagnostics of the multidimensionality of thinking; (2 my technique of “schemes and paintings,” designed for diagnostics of the ability to relate abstract schemes and various specific content; (3 the Torrance Tests of Creative Thinking (verbal battery; (4 a diagnostic technique for dialectical thinking: “What can be simultaneous?” All the hypotheses were confirmed. Confirmation was received of the existence of a correlation connection; this finding counts in favor of the assumption that the parameters of thinking my colleagues and I were working with can in aggregate be considered an integral characteristic of human thinking. It allows us to distinguish significant features of a situation from secondary ones—that is, to see a substantial contradiction and to propose several options for its transformation.

SPRED: A machine learning approach for the identification of classical and non-classical secretory proteins in mammalian genomes

Energy Technology Data Exchange (ETDEWEB)

Kandaswamy, Krishna Kumar [Institute for Neuro- and Bioinformatics, University of Luebeck, 23538 Luebeck (Germany); Graduate School for Computing in Medicine and Life Sciences, University of Luebeck, 23538 Luebeck (Germany); Pugalenthi, Ganesan [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore); Hartmann, Enno; Kalies, Kai-Uwe [Centre for Structural and Cell Biology in Medicine, Institute of Biology, University of Luebeck, 23538 Luebeck (Germany); Moeller, Steffen [Institute for Neuro- and Bioinformatics, University of Luebeck, 23538 Luebeck (Germany); Suganthan, P.N. [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore); Martinetz, Thomas, E-mail: martinetz@inb.uni-luebeck.de [Institute for Neuro- and Bioinformatics, University of Luebeck, 23538 Luebeck (Germany)

2010-01-15

Eukaryotic protein secretion generally occurs via the classical secretory pathway that traverses the ER and Golgi apparatus. Secreted proteins usually contain a signal sequence with all the essential information required to target them for secretion. However, some proteins like fibroblast growth factors (FGF-1, FGF-2), interleukins (IL-1 alpha, IL-1 beta), galectins and thioredoxin are exported by an alternative pathway. This is known as leaderless or non-classical secretion and works without a signal sequence. Most computational methods for the identification of secretory proteins use the signal peptide as indicator and are therefore not able to identify substrates of non-classical secretion. In this work, we report a random forest method, SPRED, to identify secretory proteins from protein sequences irrespective of N-terminal signal peptides, thus allowing also correct classification of non-classical secretory proteins. Training was performed on a dataset containing 600 extracellular proteins and 600 cytoplasmic and/or nuclear proteins. The algorithm was tested on 180 extracellular proteins and 1380 cytoplasmic and/or nuclear proteins. We obtained 85.92% accuracy from training and 82.18% accuracy from testing. Since SPRED does not use N-terminal signals, it can detect non-classical secreted proteins by filtering those secreted proteins with an N-terminal signal by using SignalP. SPRED predicted 15 out of 19 experimentally verified non-classical secretory proteins. By scanning the entire human proteome we identified 566 protein sequences potentially undergoing non-classical secretion. The dataset and standalone version of the SPRED software is available at (http://www.inb.uni-luebeck.de/tools-demos/spred/spred).

SPRED: A machine learning approach for the identification of classical and non-classical secretory proteins in mammalian genomes

International Nuclear Information System (INIS)

Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Hartmann, Enno; Kalies, Kai-Uwe; Moeller, Steffen; Suganthan, P.N.; Martinetz, Thomas

2010-01-01

Eukaryotic protein secretion generally occurs via the classical secretory pathway that traverses the ER and Golgi apparatus. Secreted proteins usually contain a signal sequence with all the essential information required to target them for secretion. However, some proteins like fibroblast growth factors (FGF-1, FGF-2), interleukins (IL-1 alpha, IL-1 beta), galectins and thioredoxin are exported by an alternative pathway. This is known as leaderless or non-classical secretion and works without a signal sequence. Most computational methods for the identification of secretory proteins use the signal peptide as indicator and are therefore not able to identify substrates of non-classical secretion. In this work, we report a random forest method, SPRED, to identify secretory proteins from protein sequences irrespective of N-terminal signal peptides, thus allowing also correct classification of non-classical secretory proteins. Training was performed on a dataset containing 600 extracellular proteins and 600 cytoplasmic and/or nuclear proteins. The algorithm was tested on 180 extracellular proteins and 1380 cytoplasmic and/or nuclear proteins. We obtained 85.92% accuracy from training and 82.18% accuracy from testing. Since SPRED does not use N-terminal signals, it can detect non-classical secreted proteins by filtering those secreted proteins with an N-terminal signal by using SignalP. SPRED predicted 15 out of 19 experimentally verified non-classical secretory proteins. By scanning the entire human proteome we identified 566 protein sequences potentially undergoing non-classical secretion. The dataset and standalone version of the SPRED software is available at (http://www.inb.uni-luebeck.de/tools-demos/spred/spred).

Cuba: Multidimensional numerical integration library

Science.gov (United States)

Hahn, Thomas

2016-08-01

The Cuba library offers four independent routines for multidimensional numerical integration: Vegas, Suave, Divonne, and Cuhre. The four algorithms work by very different methods, and can integrate vector integrands and have very similar Fortran, C/C++, and Mathematica interfaces. Their invocation is very similar, making it easy to cross-check by substituting one method by another. For further safeguarding, the output is supplemented by a chi-square probability which quantifies the reliability of the error estimate.

[Multidimensional family therapy: which influences, which specificities?].

Science.gov (United States)

Bonnaire, C; Bastard, N; Couteron, J-P; Har, A; Phan, O

2014-10-01

Among illegal psycho-active drugs, cannabis is the most consumed by French adolescents. Multidimensional family therapy (MDFT) is a family-based outpatient therapy which has been developed for adolescents with drug and behavioral problems. MDFT has shown its effectiveness in adolescents with substance abuse disorders (notably cannabis abuse) not only in the United States but also in Europe (International Cannabis Need of Treatment project). MDFT is a multidisciplinary approach and an evidence-based treatment, at the crossroads of developmental psychology, ecological theories and family therapy. Its psychotherapeutic techniques find its roots in a variety of approaches which include systemic family therapy and cognitive therapy. The aims of this paper are: to describe all the backgrounds of MDFT by highlighting its characteristics; to explain how structural and strategy therapies have influenced this approach; to explore the links between MDFT, brief strategic family therapy and multi systemic family therapy; and to underline the specificities of this family therapy method. The multidimensional family therapy was created on the bases of 1) the integration of multiple therapeutic techniques stemming from various family therapy theories; and 2) studies which have shown family therapy efficiency. Several trials have shown a better efficiency of MDFT compared to group treatment, cognitive-behavioral therapy and home-based treatment. Studies have also highlighted that MDFT led to superior treatment outcomes, especially among young people with severe drug use and psychiatric co-morbidities. In the field of systemic family therapies, MDFT was influenced by: 1) the structural family therapy (S. Minuchin), 2) the strategic family theory (J. Haley), and 3) the intergenerational family therapy (Bowen and Boszormenyi-Nagy). MDFT has specific aspects: MDFT therapists think in a multidimensional perspective (because an adolescent's drug abuse is a multidimensional disorder), they

Identification and quantification of protein S-nitrosation by nitrite in the mouse heart during ischemia.

Science.gov (United States)

Chouchani, Edward T; James, Andrew M; Methner, Carmen; Pell, Victoria R; Prime, Tracy A; Erickson, Brian K; Forkink, Marleen; Lau, Gigi Y; Bright, Thomas P; Menger, Katja E; Fearnley, Ian M; Krieg, Thomas; Murphy, Michael P

2017-09-01

Nitrate (NO 3 - ) and nitrite (NO 2 - ) are known to be cardioprotective and to alter energy metabolism in vivo NO 3 - action results from its conversion to NO 2 - by salivary bacteria, but the mechanism(s) by which NO 2 - affects metabolism remains obscure. NO 2 - may act by S -nitrosating protein thiols, thereby altering protein activity. But how this occurs, and the functional importance of S -nitrosation sites across the mammalian proteome, remain largely uncharacterized. Here we analyzed protein thiols within mouse hearts in vivo using quantitative proteomics to determine S -nitrosation site occupancy. We extended the thiol-redox proteomic technique, isotope-coded affinity tag labeling, to quantify the extent of NO 2 - -dependent S -nitrosation of proteins thiols in vivo Using this approach, called SNOxICAT ( S -nitrosothiol redox isotope-coded affinity tag), we found that exposure to NO 2 - under normoxic conditions or exposure to ischemia alone results in minimal S -nitrosation of protein thiols. However, exposure to NO 2 - in conjunction with ischemia led to extensive S -nitrosation of protein thiols across all cellular compartments. Several mitochondrial protein thiols exposed to the mitochondrial matrix were selectively S -nitrosated under these conditions, potentially contributing to the beneficial effects of NO 2 - on mitochondrial metabolism. The permeability of the mitochondrial inner membrane to HNO 2 , but not to NO 2 - , combined with the lack of S -nitrosation during anoxia alone or by NO 2 - during normoxia places constraints on how S -nitrosation occurs in vivo and on its mechanisms of cardioprotection and modulation of energy metabolism. Quantifying S -nitrosated protein thiols now allows determination of modified cysteines across the proteome and identification of those most likely responsible for the functional consequences of NO 2 - exposure. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering.

Science.gov (United States)

Almeida, Fernando R; Brayner, Angelo; Rodrigues, Joel J P C; Maia, Jose E Bessa

2017-06-07

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering . To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE).

Identification of one B-cell epitope from NS1 protein of duck Tembusu virus with monoclonal antibodies.

Directory of Open Access Journals (Sweden)

Jinfeng Ti

Full Text Available This study describes the identification of one linear B-cell epitope on TMUV NS1 protein with monoclonal antibody (mAb 3G2 by indirect enzyme-linked immunosorbent assay (ELISA. In this study, NS1 protein was expressed in prokaryotic expression system and purified. One mAb against NS1 protein was generated from Balb/c mice immunized with recombinant protein NS1. A set of 35 partially-overlapping polypeptides covering the entire NS1 protein was expressed with PGEX-6P-1 vector and screened with mAb 3G2. One polypeptide against the mAb was acquired and identified by indirect ELISA and western-blot. To map the epitope accurately, one or two amino acid residues were removed from the carboxy and amino terminal of polypeptide sequentially. A series of truncated oligopeptides were expressed and purified. The minimal determinant of the linear B cell epitope was recognized and identified with mAb 3G2. The accurate linear B-cell epitope was 269DEKEIV274 located in NS1 protein. Furthermore, sequence alignment showed that the epitope was highly conserved and specific among TMUV strains and other flavivirus respectively. The linear B-cell epitope of TMUV NS1 protein could benefit the development of new vaccines and diagnostic assays.

Protein identification and quantification from riverbank grape, Vitis riparia: Comparing SDS-PAGE and FASP-GPF techniques for shotgun proteomic analysis.

Science.gov (United States)

George, Iniga S; Fennell, Anne Y; Haynes, Paul A

2015-09-01

Protein sample preparation optimisation is critical for establishing reproducible high throughput proteomic analysis. In this study, two different fractionation sample preparation techniques (in-gel digestion and in-solution digestion) for shotgun proteomics were used to quantitatively compare proteins identified in Vitis riparia leaf samples. The total number of proteins and peptides identified were compared between filter aided sample preparation (FASP) coupled with gas phase fractionation (GPF) and SDS-PAGE methods. There was a 24% increase in the total number of reproducibly identified proteins when FASP-GPF was used. FASP-GPF is more reproducible, less expensive and a better method than SDS-PAGE for shotgun proteomics of grapevine samples as it significantly increases protein identification across biological replicates. Total peptide and protein information from the two fractionation techniques is available in PRIDE with the identifier PXD001399 (http://proteomecentral.proteomexchange.org/dataset/PXD001399). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Continued validation of the Multidimensional Perfectionism Scale.

Science.gov (United States)

Clavin, S L; Clavin, R H; Gayton, W F; Broida, J

1996-06-01

Scores on the Multidimensional Perfectionism Scale have been correlated with measures of obsessive-compulsive tendencies for women, so the validity of scores on this scale for 41 men was examined. Scores on the Perfectionism Scale were significantly correlated (.47-.03) with scores on the Maudsley Obsessive-Compulsive Inventory.

Multidimensional stochastic approximation using locally contractive functions

Science.gov (United States)

Lawton, W. M.

1975-01-01

A Robbins-Monro type multidimensional stochastic approximation algorithm which converges in mean square and with probability one to the fixed point of a locally contractive regression function is developed. The algorithm is applied to obtain maximum likelihood estimates of the parameters for a mixture of multivariate normal distributions.

An Improved Multidimensional MPA Procedure for Bidirectional Earthquake Excitations

Directory of Open Access Journals (Sweden)

Feng Wang

2014-01-01

Full Text Available Presently, the modal pushover analysis procedure is extended to multidimensional analysis of structures subjected to multidimensional earthquake excitations. an improved multidimensional modal pushover analysis (IMMPA method is presented in the paper in order to estimate the response demands of structures subjected to bidirectional earthquake excitations, in which the unidirectional earthquake excitation applied on equivalent SDOF system is replaced by the direct superposition of two components earthquake excitations, and independent analysis in each direction is not required and the application of simplified superposition formulas is avoided. The strength reduction factor spectra based on superposition of earthquake excitations are discussed and compared with the traditional strength reduction factor spectra. The step-by-step procedure is proposed to estimate seismic demands of structures. Two examples are implemented to verify the accuracy of the method, and the results of the examples show that (1 the IMMPA method can be used to estimate the responses of structure subjected to bidirectional earthquake excitations. (2 Along with increase of peak of earthquake acceleration, structural response deviation estimated with the IMMPA method may also increase. (3 Along with increase of the number of total floors of structures, structural response deviation estimated with the IMMPA method may also increase.

Discrete nodal integral transport-theory method for multidimensional reactor physics and shielding calculations

International Nuclear Information System (INIS)

Lawrence, R.D.; Dorning, J.J.

1980-01-01

A coarse-mesh discrete nodal integral transport theory method has been developed for the efficient numerical solution of multidimensional transport problems of interest in reactor physics and shielding applications. The method, which is the discrete transport theory analogue and logical extension of the nodal Green's function method previously developed for multidimensional neutron diffusion problems, utilizes the same transverse integration procedure to reduce the multidimensional equations to coupled one-dimensional equations. This is followed by the conversion of the differential equations to local, one-dimensional, in-node integral equations by integrating back along neutron flight paths. One-dimensional and two-dimensional transport theory test problems have been systematically studied to verify the superior computational efficiency of the new method

Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

Science.gov (United States)

Zhang, Jieru; Ju, Ying; Lu, Huijuan; Xuan, Ping; Zou, Quan

2016-01-01

Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.

Code Coupling for Multi-Dimensional Core Transient Analysis

International Nuclear Information System (INIS)

Park, Jin-Woo; Park, Guen-Tae; Park, Min-Ho; Ryu, Seok-Hee; Um, Kil-Sup; Lee Jae-Il

2015-01-01

After the CEA ejection, the nuclear power of the reactor dramatically increases in an exponential behavior until the Doppler effect becomes important and turns the reactivity balance and power down to lower levels. Although this happens in a very short period of time, only few seconds, the energy generated can be very significant and cause fuel failures. The current safety analysis methodology which is based on overly conservative assumptions with the point kinetics model results in quite adverse consequences. Thus, KEPCO Nuclear Fuel(KNF) is developing the multi-dimensional safety analysis methodology to mitigate the consequences of the single CEA ejection accident. For this purpose, three-dimensional core neutron kinetics code ASTRA, sub-channel analysis code THALES, and fuel performance analysis code FROST, which have transient calculation performance, were coupled using message passing interface (MPI). This paper presents the methodology used for code coupling and the preliminary simulation results with the coupled code system (CHASER). Multi-dimensional core transient analysis code system, CHASER, has been developed and it was applied to simulate a single CEA ejection accident. CHASER gave a good prediction of multi-dimensional core transient behaviors during transient. In the near future, the multi-dimension CEA ejection analysis methodology using CHASER is planning to be developed. CHASER is expected to be a useful tool to gain safety margin for reactivity initiated accidents (RIAs), such as a single CEA ejection accident

Code Coupling for Multi-Dimensional Core Transient Analysis

Energy Technology Data Exchange (ETDEWEB)

Park, Jin-Woo; Park, Guen-Tae; Park, Min-Ho; Ryu, Seok-Hee; Um, Kil-Sup; Lee Jae-Il [KEPCO NF, Daejeon (Korea, Republic of)

2015-05-15

After the CEA ejection, the nuclear power of the reactor dramatically increases in an exponential behavior until the Doppler effect becomes important and turns the reactivity balance and power down to lower levels. Although this happens in a very short period of time, only few seconds, the energy generated can be very significant and cause fuel failures. The current safety analysis methodology which is based on overly conservative assumptions with the point kinetics model results in quite adverse consequences. Thus, KEPCO Nuclear Fuel(KNF) is developing the multi-dimensional safety analysis methodology to mitigate the consequences of the single CEA ejection accident. For this purpose, three-dimensional core neutron kinetics code ASTRA, sub-channel analysis code THALES, and fuel performance analysis code FROST, which have transient calculation performance, were coupled using message passing interface (MPI). This paper presents the methodology used for code coupling and the preliminary simulation results with the coupled code system (CHASER). Multi-dimensional core transient analysis code system, CHASER, has been developed and it was applied to simulate a single CEA ejection accident. CHASER gave a good prediction of multi-dimensional core transient behaviors during transient. In the near future, the multi-dimension CEA ejection analysis methodology using CHASER is planning to be developed. CHASER is expected to be a useful tool to gain safety margin for reactivity initiated accidents (RIAs), such as a single CEA ejection accident.

Multidimensional Data Modeling For Location-Based Services

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Kligys, Augustas; Pedersen, Torben Bach

2004-01-01

and requests of their users in multidimensional databases, i.e., data warehouses, and content delivery may be based on the results of complex queries on these data warehouses. Such queries aggregate detailed data in order to find useful patterns, e.g., in the interaction of a particular user with the services...

Multidimensional Data Modeling For Location-Based Services

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Kligys, A.; Pedersen, Torben Bach

2003-01-01

and requests of their users in multidimensional databases, i.e., data warehouses; and content delivery may be based on the results of complex queries on these data warehouses. Such queries aggregate detailed data in order to find useful patterns, e.g., in the interaction of a particular user with the services...

Sequence Identification, Recombinant Production, and Analysis of the Self-Assembly of Egg Stalk Silk Proteins from Lacewing Chrysoperla carnea.

Science.gov (United States)

Neuenfeldt, Martin; Scheibel, Thomas

2017-06-13

Egg stalk silks of the common green lacewing Chrysoperla carnea likely comprise at least three different silk proteins. Based on the natural spinning process, it was hypothesized that these proteins self-assemble without shear stress, as adult lacewings do not use a spinneret. To examine this, the first sequence identification and determination of the gene expression profile of several silk proteins and various transcript variants thereof was conducted, and then the three major proteins were recombinantly produced in Escherichia coli encoded by their native complementary DNA (cDNA) sequences. Circular dichroism measurements indicated that the silk proteins in aqueous solutions had a mainly intrinsically disordered structure. The largest silk protein, which we named ChryC1, exhibited a lower critical solution temperature (LCST) behavior and self-assembled into fibers or film morphologies, depending on the conditions used. The second silk protein, ChryC2, self-assembled into nanofibrils and subsequently formed hydrogels. Circular dichroism and Fourier transform infrared spectroscopy confirmed conformational changes of both proteins into beta sheet rich structures upon assembly. ChryC3 did not self-assemble into any morphology under the tested conditions. Thereby, through this work, it could be shown that recombinant lacewing silk proteins can be produced and further used for studying the fiber formation of lacewing egg stalks.

A combinatorial perspective of the protein inference problem.

Science.gov (United States)

Yang, Chao; He, Zengyou; Yu, Weichuan

2013-01-01

In a shotgun proteomics experiment, proteins are the most biologically meaningful output. The success of proteomics studies depends on the ability to accurately and efficiently identify proteins. Many methods have been proposed to facilitate the identification of proteins from peptide identification results. However, the relationship between protein identification and peptide identification has not been thoroughly explained before. In this paper, we devote ourselves to a combinatorial perspective of the protein inference problem. We employ combinatorial mathematics to calculate the conditional protein probabilities (protein probability means the probability that a protein is correctly identified) under three assumptions, which lead to a lower bound, an upper bound, and an empirical estimation of protein probabilities, respectively. The combinatorial perspective enables us to obtain an analytical expression for protein inference. Our method achieves comparable results with ProteinProphet in a more efficient manner in experiments on two data sets of standard protein mixtures and two data sets of real samples. Based on our model, we study the impact of unique peptides and degenerate peptides (degenerate peptides are peptides shared by at least two proteins) on protein probabilities. Meanwhile, we also study the relationship between our model and ProteinProphet. We name our program ProteinInfer. Its Java source code, our supplementary document and experimental results are available at: >http://bioinformatics.ust.hk/proteininfer.

The Search Engine for Multi-Proteoform Complexes: An Online Tool for the Identification and Stoichiometry Determination of Protein Complexes.

Science.gov (United States)

Skinner, Owen S; Schachner, Luis F; Kelleher, Neil L

2016-12-08

Recent advances in top-down mass spectrometry using native electrospray now enable the analysis of intact protein complexes with relatively small sample amounts in an untargeted mode. Here, we describe how to characterize both homo- and heteropolymeric complexes with high molecular specificity using input data produced by tandem mass spectrometry of whole protein assemblies. The tool described is a "search engine for multi-proteoform complexes," (SEMPC) and is available for free online. The output is a list of candidate multi-proteoform complexes and scoring metrics, which are used to define a distinct set of one or more unique protein subunits, their overall stoichiometry in the intact complex, and their pre- and post-translational modifications. Thus, we present an approach for the identification and characterization of intact protein complexes from native mass spectrometry data. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

ComVisMD - compact visualization of multidimensional data: experimenting with cricket players data

Science.gov (United States)

Dandin, Shridhar B.; Ducassé, Mireille

2018-03-01

Database information is multidimensional and often displayed in tabular format (row/column display). Presented in aggregated form, multidimensional data can be used to analyze the records or objects. Online Analytical database Processing (OLAP) proposes mechanisms to display multidimensional data in aggregated forms. A choropleth map is a thematic map in which areas are colored in proportion to the measurement of a statistical variable being displayed, such as population density. They are used mostly for compact graphical representation of geographical information. We propose a system, ComVisMD inspired by choropleth map and the OLAP cube to visualize multidimensional data in a compact way. ComVisMD displays multidimensional data like OLAP Cube, where we are mapping an attribute a (first dimension, e.g. year started playing cricket) in vertical direction, object coloring based on b (second dimension, e.g. batting average), mapping varying-size circles based on attribute c (third dimension, e.g. highest score), mapping numbers based on attribute d (fourth dimension, e.g. matches played). We illustrate our approach on cricket players data, namely on two tables Country and Player. They have a large number of rows and columns: 246 rows and 17 columns for players of one country. ComVisMD’s visualization reduces the size of the tabular display by a factor of about 4, allowing users to grasp more information at a time than the bare table display.

Proteome analysis of barley seeds: Identification of major proteins from two-dimensional gels (pl 4-7)

DEFF Research Database (Denmark)

Østergaard, O.; Finnie, Christine; Laugesen, S.

2004-01-01

inhibitors), and proteins related to desiccation and oxidative stress. Sixty-four of the identifications were made using expressed sequence tags (ESTs). Numerous spots in the 2-D gel pattern changed during germination (micromalting) and an intensely stained area which contained large amounts of the serpin......Germination of monocotyledonous plants involves activation and de novo synthesis of enzymes that degrade cell walls and starch and mobilize stored endosperm reserves for embryo growth. Two-dimensional (2-D) gel electrophoresis and mass spectrometry were applied to identify major water...

Verification of Ribosomal Proteins of Aspergillus fumigatus for Use as Biomarkers in MALDI-TOF MS Identification.

Science.gov (United States)

Nakamura, Sayaka; Sato, Hiroaki; Tanaka, Reiko; Yaguchi, Takashi

2016-01-01

We have previously proposed a rapid identification method for bacterial strains based on the profiles of their ribosomal subunit proteins (RSPs), observed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). This method can perform phylogenetic characterization based on the mass of housekeeping RSP biomarkers, ideally calculated from amino acid sequence information registered in public protein databases. With the aim of extending its field of application to medical mycology, this study investigates the actual state of information of RSPs of eukaryotic fungi registered in public protein databases through the characterization of ribosomal protein fractions extracted from genome-sequenced Aspergillus fumigatus strains Af293 and A1163 as a model. In this process, we have found that the public protein databases harbor problems. The RSP names are in confusion, so we have provisionally unified them using the yeast naming system. The most serious problem is that many incorrect sequences are registered in the public protein databases. Surprisingly, more than half of the sequences are incorrect, due chiefly to mis-annotation of exon/intron structures. These errors could be corrected by a combination of in silico inspection by sequence homology analysis and MALDI-TOF MS measurements. We were also able to confirm conserved post-translational modifications in eleven RSPs. After these verifications, the masses of 31 expressed RSPs under 20,000 Da could be accurately confirmed. These RSPs have a potential to be useful biomarkers for identifying clinical isolates of A. fumigatus .

Testing the multidimensionality of the inventory of school motivation in a Dutch student sample.

Science.gov (United States)

Korpershoek, Hanke; Xu, Kun; Mok, Magdalena Mo Ching; McInerney, Dennis M; van der Werf, Greetje

2015-01-01

A factor analytic and a Rasch measurement approach were applied to evaluate the multidimensional nature of the school motivation construct among more than 7,000 Dutch secondary school students. The Inventory of School Motivation (McInerney and Ali, 2006) was used, which intends to measure four motivation dimensions (mastery, performance, social, and extrinsic motivation), each comprising of two first-order factors. One unidimensional model and three multidimensional models (4-factor, 8-factor, higher order) were fit to the data. Results of both approaches showed that the multidimensional models validly represented the school motivation among Dutch secondary school pupils, whereas model fit of the unidimensional model was poor. The differences in model fit between the three multidimensional models were small, although a different model was favoured by the two approaches. The need for improvement of some of the items and the need to increase measurement precision of several first-order factors are discussed.

Theory and application of deterministic multidimensional pointwise energy lattice physics methods

International Nuclear Information System (INIS)

Zerkle, M.L.

1999-01-01

The theory and application of deterministic, multidimensional, pointwise energy lattice physics methods are discussed. These methods may be used to solve the neutron transport equation in multidimensional geometries using near-continuous energy detail to calculate equivalent few-group diffusion theory constants that rigorously account for spatial and spectral self-shielding effects. A dual energy resolution slowing down algorithm is described which reduces the computer memory and disk storage requirements for the slowing down calculation. Results are presented for a 2D BWR pin cell depletion benchmark problem

Psychometric properties of the Multidimensional Students’ Life Satisfaction Scale in a sample of Chilean university students

Directory of Open Access Journals (Sweden)

Berta Schnettler

2017-07-01

Full Text Available The Multidimensional Students’ Life Satisfaction Scale is an instrument to assess life satisfaction in children and adolescents in five life domains. However, research on multidimensional life satisfaction in older students, such as those attending university, is still scarce. This paper undertook to evaluate the psychometric properties of the Multidimensional Students’ Life Satisfaction Scale in a sample of university students from five state universities in Chile. The Multidimensional Students’ Life Satisfaction Scale and Satisfaction with Life Scale were applied to 369 participants. Confirmatory factor analysis was used to evaluate the expected correlated five-factor model of the long version (40 items and the abbreviated version (30 items of the Multidimensional Students’ Life Satisfaction Scale. The goodness-of-fit values obtained from confirmatory factor analysis revealed that the data fit better to the 30-items and five-factor structure than to the 40-item structure. The convergent, concurrent and discriminant validity of the 30-item version was demonstrated. The 30-item version of the Multidimensional Students’ Life Satisfaction Scale may be a promising alternative to measure satisfaction in different life domains in university students, and a valuable tool for differential assessments that guide research and intervention on this population.

On fully multidimensional and high order non oscillatory finite volume methods, I

International Nuclear Information System (INIS)

Lafon, F.

1992-11-01

A fully multidimensional flux formulation for solving nonlinear conservation laws of hyperbolic type is introduced to perform calculations on unstructured grids made of triangular or quadrangular cells. Fluxes are computed across dual median cells with a multidimensional 2D Riemann Solver (R2D Solver) whose intermediate states depend on either a three (on triangle R2DT solver) of four (on quadrangle, R2DQ solver) state solutions prescribed on the three or four sides of a gravity cell. Approximate Riemann solutions are computed via a linearization process of Roe's type involving multidimensional effects. Moreover, a monotonous scheme using stencil and central Lax-Friedrichs corrections on sonic curves are built in. Finally, high order accurate ENO-like (Essentially Non Oscillatory) reconstructions using plane and higher degree polynomial limitations are defined in the set up of finite element Lagrange spaces P k and Q k for k≥0, on triangles and quadrangles, respectively. Numerical experiments involving both linear and nonlinear conservation laws to be solved on unstructured grids indicate the ability of our techniques when dealing with strong multidimensional effects. An application to Euler's equations for the Mach three step problem illustrates the robustness and usefulness of our techniques using triangular and quadrangular grids. (Author). 33 refs., 13 figs

DaqProVis, a toolkit for acquisition, interactive analysis, processing and visualization of multidimensional data

Energy Technology Data Exchange (ETDEWEB)

Morhac, M. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia)]. E-mail: fyzimiro@savba.sk; Matousek, V. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia); Turzo, I. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia); Kliman, J. [Institute of Physics, Slovak Academy of Sciences, Dubravska cesta 9, 845 11 Bratislava (Slovakia)

2006-04-01

Multidimensional data acquisition, processing and visualization system to analyze experimental data in nuclear physics is described. It includes a large number of sophisticated algorithms of the multidimensional spectra processing, including background elimination, deconvolution, peak searching and fitting.

Multidimensional first-order dominance comparisons of population wellbeing

DEFF Research Database (Denmark)

Arndt, Thomas Channing; Siersbæk, Nikolaj; Østerdal, Lars Peter Raahave

In this paper, we convey the concept of first-order dominance (FOD) with particular focus on applications to multidimensional population welfare comparisons. We give an account of the fundamental equivalent definitions of FOD, illustrated with simple numerical examples. An implementable method...

Identification of similar regions of protein structures using integrated sequence and structure analysis tools

Directory of Open Access Journals (Sweden)

Heiland Randy

2006-03-01

Full Text Available Abstract Background Understanding protein function from its structure is a challenging problem. Sequence based approaches for finding homology have broad use for annotation of both structure and function. 3D structural information of protein domains and their interactions provide a complementary view to structure function relationships to sequence information. We have developed a web site http://www.sblest.org/ and an API of web services that enables users to submit protein structures and identify statistically significant neighbors and the underlying structural environments that make that match using a suite of sequence and structure analysis tools. To do this, we have integrated S-BLEST, PSI-BLAST and HMMer based superfamily predictions to give a unique integrated view to prediction of SCOP superfamilies, EC number, and GO term, as well as identification of the protein structural environments that are associated with that prediction. Additionally, we have extended UCSF Chimera and PyMOL to support our web services, so that users can characterize their own proteins of interest. Results Users are able to submit their own queries or use a structure already in the PDB. Currently the databases that a user can query include the popular structural datasets ASTRAL 40 v1.69, ASTRAL 95 v1.69, CLUSTER50, CLUSTER70 and CLUSTER90 and PDBSELECT25. The results can be downloaded directly from the site and include function prediction, analysis of the most conserved environments and automated annotation of query proteins. These results reflect both the hits found with PSI-BLAST, HMMer and with S-BLEST. We have evaluated how well annotation transfer can be performed on SCOP ID's, Gene Ontology (GO ID's and EC Numbers. The method is very efficient and totally automated, generally taking around fifteen minutes for a 400 residue protein. Conclusion With structural genomics initiatives determining structures with little, if any, functional characterization

Equating Multidimensional Tests under a Random Groups Design: A Comparison of Various Equating Procedures

Science.gov (United States)

Lee, Eunjung

2013-01-01

The purpose of this research was to compare the equating performance of various equating procedures for the multidimensional tests. To examine the various equating procedures, simulated data sets were used that were generated based on a multidimensional item response theory (MIRT) framework. Various equating procedures were examined, including…

Using the Andrews Plotss to Visualize Multidimensional Data in Multi-criteria Optimization

OpenAIRE

S. V. Groshev; N. V. Pivovarova

2015-01-01

Currently, issues on processing of large data volumes are of great importance. Initially, the Andrews plots have been proposed to show multidimensional statistics on the plane. But as the Andrews plots retain information on the average values of the represented values, distances, and dispersion, the distances between the plots linearly indicate distances between the data points, and it becomes possible to use the plots under consideration for the graphical representation of multi-dimensional ...

Identification of the hemoglobin scavenger receptor/CD163 as a natural soluble protein in plasma

DEFF Research Database (Denmark)

Møller, Holger Jon; Peterslund, Niels Anker; Graversen, Jonas Heilskov

2002-01-01

enabled identification of a soluble plasma form of HbSR (sHbSR) having an electrophoretic mobility equal to that of recombinant HbSR consisting of the extracellular domain (scavenger receptor cysteine-rich 1-9). A sandwich enzyme-linked immunosorbent assay was established and used to measure the s...... a level of sHbSR above the range of healthy persons. Patients with myelomonocytic leukemias and pneumonia/sepsis exhibited the highest levels (up to 67.3 mg/L). In conclusion, sHbSR is an abundant plasma protein potentially valuable in monitoring patients with infections and myelomonocytic leukemia....

Multidimensional Rank Reduction Estimator for Parametric MIMO Channel Models

Directory of Open Access Journals (Sweden)

Marius Pesavento

2004-08-01

Full Text Available A novel algebraic method for the simultaneous estimation of MIMO channel parameters from channel sounder measurements is developed. We consider a parametric multipath propagation model with P discrete paths where each path is characterized by its complex path gain, its directions of arrival and departure, time delay, and Doppler shift. This problem is treated as a special case of the multidimensional harmonic retrieval problem. While the well-known ESPRIT-type algorithms exploit shift-invariance between specific partitions of the signal matrix, the rank reduction estimator (RARE algorithm exploits their internal Vandermonde structure. A multidimensional extension of the RARE algorithm is developed, analyzed, and applied to measurement data recorded with the RUSK vector channel sounder in the 2 GHz band.

A practical guide for the identification of membrane and plasma membrane proteins in human embryonic stem cells and human embryonal carcinoma cells.

NARCIS (Netherlands)

Dormeyer, W.; van Hoof, D.; Mummery, C.L.; Krijgsveld, J.; Heck, A.

2008-01-01

The identification of (plasma) membrane proteins in cells can provide valuable insights into the regulation of their biological processes. Pluripotent cells such as human embryonic stem cells and embryonal carcinoma cells are capable of unlimited self-renewal and share many of the biological

NMRNet: A deep learning approach to automated peak picking of protein NMR spectra.

Science.gov (United States)

Klukowski, Piotr; Augoff, Michal; Zieba, Maciej; Drwal, Maciej; Gonczarek, Adam; Walczak, Michal J

2018-03-14

Automated selection of signals in protein NMR spectra, known as peak picking, has been studied for over 20 years, nevertheless existing peak picking methods are still largely deficient. Accurate and precise automated peak picking would accelerate the structure calculation, and analysis of dynamics and interactions of macromolecules. Recent advancement in handling big data, together with an outburst of machine learning techniques, offer an opportunity to tackle the peak picking problem substantially faster than manual picking and on par with human accuracy. In particular, deep learning has proven to systematically achieve human-level performance in various recognition tasks, and thus emerges as an ideal tool to address automated identification of NMR signals. We have applied a convolutional neural network for visual analysis of multidimensional NMR spectra. A comprehensive test on 31 manually-annotated spectra has demonstrated top-tier average precision (AP) of 0.9596, 0.9058 and 0.8271 for backbone, side-chain and NOESY spectra, respectively. Furthermore, a combination of extracted peak lists with automated assignment routine, FLYA, outperformed other methods, including the manual one, and led to correct resonance assignment at the levels of 90.40%, 89.90% and 90.20% for three benchmark proteins. The proposed model is a part of a Dumpling software (platform for protein NMR data analysis), and is available at https://dumpling.bio/. michaljerzywalczak@gmail.compiotr.klukowski@pwr.edu.pl. Supplementary data are available at Bioinformatics online.

Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography.

Science.gov (United States)

Navarro-Reig, Meritxell; Bedia, Carmen; Tauler, Romà; Jaumot, Joaquim

2018-04-03

The increasing complexity of omics research has encouraged the development of new instrumental technologies able to deal with these challenging samples. In this way, the rise of multidimensional separations should be highlighted due to the massive amounts of information that provide with an enhanced analyte determination. Both proteomics and metabolomics benefit from this higher separation capacity achieved when different chromatographic dimensions are combined, either in LC or GC. However, this vast quantity of experimental information requires the application of chemometric data analysis strategies to retrieve this hidden knowledge, especially in the case of nontargeted studies. In this work, the most common chemometric tools and approaches for the analysis of this multidimensional chromatographic data are reviewed. First, different options for data preprocessing and enhancement of the instrumental signal are introduced. Next, the most used chemometric methods for the detection of chromatographic peaks and the resolution of chromatographic and spectral contributions (profiling) are presented. The description of these data analysis approaches is complemented with enlightening examples from omics fields that demonstrate the exceptional potential of the combination of multidimensional separation techniques and chemometric tools of data analysis. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Autoimmunity to Tropomyosin-Specific Peptides Induced by Mycobacterium leprae in Leprosy Patients: Identification of Mimicking Proteins.

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Singh, Itu; Yadav, Asha Ram; Mohanty, Keshar Kunja; Katoch, Kiran; Sharma, Prashant; Pathak, Vinay Kumar; Bisht, Deepa; Gupta, Umesh D; Sengupta, Utpal

2018-01-01

It has been shown earlier that there is a rise in the levels of autoantibodies and T cell response to cytoskeletal proteins in leprosy. Our group recently demonstrated a rise in both T and B cell responses to keratin and myelin basic protein in all types of leprosy patients and their associations in type 1 reaction (T1R) group of leprosy. In this study, we investigated the association of levels of autoantibodies and lymphoproliferation against myosin in leprosy patients across the spectrum and tried to find out the mimicking proteins or epitopes between host protein and protein/s of Mycobacterium leprae . One hundred and sixty-nine leprosy patients and 55 healthy controls (HC) were enrolled in the present study. Levels of anti-myosin antibodies and T-cell responses against myosin were measured by ELISA and lymphoproliferation assay, respectively. Using 2-D gel electrophoresis, western blot and MALDI-TOF/TOF antibody-reactive spots were identified. Three-dimensional structure of mimicking proteins was modeled by online server. B cell epitopes of the proteins were predicted by BCPREDS server 1.0 followed by identification of mimicking epitopes. Mice of inbred BALB/c strain were hyperimmunized with M. leprae soluble antigen (MLSA) and splenocytes and lymph node cells of these animals were adoptively transferred to naïve mice. Highest level of anti-myosin antibodies was noted in sera of T1R leprosy patients. We observed significantly higher levels of lymphoproliferative response ( p  leprae . We found four mimicking epitopes between these sequences. These data suggest that these mimicking proteins tropomyosin and ATP-dependent Clp protease ATP-binding subunit of M. leprae or more precisely mimicking epitopes (four B cell epitopes) might be responsible for extensive tissue damage during type1 reaction in leprosy.

Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data

DEFF Research Database (Denmark)

Brorsson, C.; Hansen, Niclas Tue; Hansen, Kasper Lage

2009-01-01

genes. We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein-protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC......To develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)-DRB1, -DQA1, -DQB1...... region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein...

Identification of protein tyrosine phosphatase 1B and casein as substrates for 124-v-Mos

Directory of Open Access Journals (Sweden)

Stabel Silvia

2002-04-01

Full Text Available Abstract Background The mos proto-oncogene encodes a cytoplasmic serine/threonine-specific protein kinase with crucial function during meiotic cell division in vertebrates. Based on oncogenic amino acid substitutions the viral derivative, 124-v-Mos, displays constitutive protein kinase activity and functions independent of unknown upstream effectors of mos protein kinase. We have utilized this property of 124-v-Mos and screened for novel mos substrates in immunocomplex kinase assays in vitro. Results We generated recombinant 124-v-Mos using the baculovirus expression system in Spodoptera frugiperda cells and demonstrated constitutive kinase activity by the ability of 124-v-Mos to auto-phosphorylate and to phosphorylate vimentin, a known substrate of c-Mos. Using this approach we analyzed a panel of acidic and basic substrates in immunocomplex protein kinase assays and identified novel in vitro substrates for 124-v-Mos, the protein tyrosine phosphatase 1B (PTP1B, alpha-casein and beta-casein. We controlled mos-specific phosphorylation of PTP1B and casein in comparative assays using a synthetic kinase-inactive 124-v-Mos mutant and further, tryptic digests of mos-phosphorylated beta-casein identified a phosphopeptide specifically targeted by wild-type 124-v-Mos. Two-dimensional phosphoamino acid analyses showed that 124-v-mos targets serine and threonine residues for phosphorylation in casein at a 1:1 ratio but auto-phosphorylation occurs predominantly on serine residues. Conclusion The mos substrates identified in this study represent a basis to approach the identification of the mos-consensus phosphorylation motif, important for the development of specific inhibitors of the Mos protein kinase.

Protein identification by peptide mass fingerprinting

DEFF Research Database (Denmark)

Hjernø, Karin

2007-01-01

  Peptide mass fingerprinting is an effective way of identifying, e.g., gel-separated proteins, by matching experimentally obtained peptide mass data against large databases. However, several factors are known to influence the quality of the resulting matches, such as proteins contaminating the s...

Ordinal Comparison of Multidimensional Deprivation

DEFF Research Database (Denmark)

Sonne-Schmidt, Christoffer Scavenius; Tarp, Finn; Østerdal, Lars Peter

This paper develops an ordinal method of comparison of multidimensional inequality. In our model, population distribution g is more unequal than f when the distributions have common median and can be obtained from f  by one or more shifts in population density that increase inequality. For our be...... benchmark 2x2 case (i.e. the case of two binary outcome variables), we derive an empirical method for making inequality comparisons. As an illustration, we apply the model to childhood poverty in Mozambique....

Multidimensional Risk Management for Underground Electricity Networks

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Garcez Thalles V.

2014-08-01

Full Text Available In the paper we consider an electricity provider company that makes decision on allocating resources on electric network maintenance. The investments decrease malfunction rate of network nodes. An accidental event (explosion, fire, etc. or a malfunctioning on underground system can have various consequences and in different perspectives, such as deaths and injuries of pedestrians, fires in nearby locations, disturbances in the flow of vehicular traffic, loss to the company image, operating and financial losses, etc. For this reason it is necessary to apply an approach of the risk management that considers the multidimensional view of the consequences. Furthermore an analysis of decision making should consider network dependencies between the nodes of the electricity distribution system. In the paper we propose the use of the simulation to assess the network effects (such as the increase of the probability of other accidental event and the occurrence of blackouts of the dependent nodes in the multidimensional risk assessment in electricity grid. The analyzed effects include node overloading due to malfunction of adjacent nodes and blackouts that take place where there is temporarily no path in the grid between the power plant and a node. The simulation results show that network effects have crucial role for decisions in the network maintenance – outcomes of decisions to repair a particular node in the network can have significant influence on performance of other nodes. However, those dependencies are non-linear. The effects of network connectivity (number of connections between nodes on its multidimensional performance assessment depend heavily on the overloading effect level. The simulation results do not depend on network type structure (random or small world – however simulation outcomes for random networks have shown higher variance compared to small-world networks.

Psychometric properties of the Multidimensional Anxiety Scale for ...

African Journals Online (AJOL)

Aim: To determine the psychometric properties of the Multidimensional Anxiety Scale for Children (MASC) in Nairobi public secondary school children, Kenya. Method: Concurrent self-administration of the MASC and Children's Depression Inventory (CDI) to students in Nairobi public secondary schools. Results: The MASC ...

Detecting protein-protein interactions in the intact cell of Bacillus subtilis (ATCC 6633).

Science.gov (United States)

Winters, Michael S; Day, R A

2003-07-01

The salt bridge, paired group-specific reagent cyanogen (ethanedinitrile; C(2)N(2)) converts naturally occurring pairs of functional groups into covalently linked products. Cyanogen readily permeates cell walls and membranes. When the paired groups are shared between associated proteins, isolation of the covalently linked proteins allows their identity to be assigned. Examination of organisms of known genome sequence permits identification of the linked proteins by mass spectrometric techniques applied to peptides derived from them. The cyanogen-linked proteins were isolated by polyacrylamide gel electrophoresis. Digestion of the isolated proteins with proteases of known specificity afforded sets of peptides that could be analyzed by mass spectrometry. These data were compared with those derived theoretically from the Swiss Protein Database by computer-based comparisons (Protein Prospector; http://prospector.ucsf.edu). Identification of associated proteins in the ribosome of Bacillus subtilis strain ATCC 6633 showed that there is an association homology with the association patterns of the ribosomal proteins of Haloarcula marismortui and Thermus thermophilus. In addition, other proteins involved in protein biosynthesis were shown to be associated with ribosomal proteins.

Identification of unknown protein complex members by radiolocalization and analysis of low-abundance complexes resolved using native polyacrylamide gel electrophoresis.

Science.gov (United States)

Bose, Mahuya; Adams, Brian P; Whittal, Randy M; Bose, Himangshu S

2008-02-01

Identification of unknown binding partners of a protein of interest can be a difficult process. Current strategies to determine protein binding partners result in a high amount of false-positives, requiring use of several different methods to confirm the accuracy of the apparent association. We have developed and utilized a method that is reliable and easily substantiated. Complexes are isolated from cell extract after exposure to the radiolabeled protein of interest, followed by resolution on a native polyacrylamide gel. Native conformations are preserved, allowing the complex members to maintain associations. By radiolabeling the protein of interest, the complex can be easily identified at detection levels below the threshold of Serva Blue, Coomassie, and silver stains. The visualized radioactive band is analyzed by MS to identify binding partners, which can be subsequently verified by antibody shift and immunoprecipitation of the complex. By using this method we have successfully identified binding partners of two proteins that reside in different locations of a cellular organelle.

Identification of StARD3 as a Lutein-binding Protein in the Macula of the Primate Retina†

Science.gov (United States)

Li, Binxing; Vachali, Preejith; Frederick, Jeanne M.; Bernstein, Paul S.

2011-01-01

Lutein, zeaxanthin and their metabolites are the xanthophyll carotenoids that form the macular pigment of the human retina. Epidemiological evidence suggests that high levels of these carotenoids in the diet, serum and macula are associated with decreased risk of age-related macular degeneration (AMD), and the AREDS2 study is prospectively testing this hypothesis. Understanding the biochemical mechanisms underlying the selective uptakes of lutein and zeaxanthin into the human macula may provide important insights into the physiology of the human macula in health and disease. GSTP1 is the macular zeaxanthin-binding protein, but the identity of the human macular lutein-binding protein has remained elusive. Prior identification of the silkworm lutein-binding protein (CBP) as a member of the steroidogenic acute regulatory domain (StARD) protein family, and selective labeling of monkey photoreceptor inner segments by anti-CBP antibody provided an important clue toward identifying the primate retina lutein-binding protein. Homology of CBP to all 15 human StARD proteins was analyzed using database searches, western blotting and immunohistochemistry, and we here provide evidence to identify StARD3 (also known as MLN64) as a human retinal lutein-binding protein. Further, recombinant StARD3 selectively binds lutein with high affinity (KD = 0.45 micromolar) when assessed by surface plasmon resonance (SPR) binding assays. Our results demonstrate previously unrecognized, specific interactions of StARD3 with lutein and provide novel avenues to explore its roles in human macular physiology and disease. PMID:21322544