i-PI: A Python interface for ab initio path integral molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Ceriotti, Michele; More, Joshua; Manolopoulos, David E.

2014-03-01

Recent developments in path integral methodology have significantly reduced the computational expense of including quantum mechanical effects in the nuclear motion in ab initio molecular dynamics simulations. However, the implementation of these developments requires a considerable programming effort, which has hindered their adoption. Here we describe i-PI, an interface written in Python that has been designed to minimise the effort required to bring state-of-the-art path integral techniques to an electronic structure program. While it is best suited to first principles calculations and path integral molecular dynamics, i-PI can also be used to perform classical molecular dynamics simulations, and can just as easily be interfaced with an empirical forcefield code. To give just one example of the many potential applications of the interface, we use it in conjunction with the CP2K electronic structure package to showcase the importance of nuclear quantum effects in high-pressure water. Catalogue identifier: AERN_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AERN_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 138626 No. of bytes in distributed program, including test data, etc.: 3128618 Distribution format: tar.gz Programming language: Python. Computer: Multiple architectures. Operating system: Linux, Mac OSX, Windows. RAM: Less than 256 Mb Classification: 7.7. External routines: NumPy Nature of problem: Bringing the latest developments in the modelling of nuclear quantum effects with path integral molecular dynamics to ab initio electronic structure programs with minimal implementational effort. Solution method: State-of-the-art path integral molecular dynamics techniques are implemented in a Python interface. Any electronic structure code can be patched to receive the atomic

OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.

PubMed

Antanaviciute, Agne; Watson, Christopher M; Harrison, Sally M; Lascelles, Carolina; Crinnion, Laura; Markham, Alexander F; Bonthron, David T; Carr, Ian M

2015-12-01

Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task. Here we describe a new variant prioritization tool, OVA (ontology variant analysis), in which user-provided phenotypic information is exploited to infer deeper biological context. OVA combines a knowledge-based approach with a variant-filtering framework. It reduces the number of candidate variants by considering genotype and predicted effect on protein sequence, and scores the remainder on biological relevance to the query phenotype.We take advantage of several ontologies in order to bridge knowledge across multiple biomedical domains and facilitate computational analysis of annotations pertaining to genes, diseases, phenotypes, tissues and pathways. In this way, OVA combines information regarding molecular and physical phenotypes and integrates both human and model organism data to effectively prioritize variants. By assessing performance on both known and novel disease mutations, we show that OVA performs biologically meaningful candidate variant prioritization and can be more accurate than another recently published candidate variant prioritization tool. OVA is freely accessible at http://dna2.leeds.ac.uk:8080/OVA/index.jsp. Supplementary data are available at Bioinformatics online. umaan@leeds.ac.uk. © The Author 2015. Published by Oxford University Press.

Integrative prescreening in analysis of multiple cancer genomic studies

PubMed Central

2012-01-01

Background In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost. Results An integrative prescreening approach is developed for the analysis of multiple cancer genomic datasets. Simulation shows that the proposed integrative prescreening has better performance than alternatives, particularly including prescreening with individual datasets, an intensity approach and meta-analysis. We also analyze multiple microarray gene profiling studies on liver and pancreatic cancers using the proposed approach. Conclusions The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies. It can be coupled with existing analysis methods to identify cancer markers. PMID:22799431

High throughput gene expression profiling: a molecular approach to integrative physiology

PubMed Central

Liang, Mingyu; Cowley, Allen W; Greene, Andrew S

2004-01-01

Integrative physiology emphasizes the importance of understanding multiple pathways with overlapping, complementary, or opposing effects and their interactions in the context of intact organisms. The DNA microarray technology, the most commonly used method for high-throughput gene expression profiling, has been touted as an integrative tool that provides insights into regulatory pathways. However, the physiology community has been slow in acceptance of these techniques because of early failure in generating useful data and the lack of a cohesive theoretical framework in which experiments can be analysed. With recent advances in both technology and analysis, we propose a concept of multidimensional integration of physiology that incorporates data generated by DNA microarray and other functional, genomic, and proteomic approaches to achieve a truly integrative understanding of physiology. Analysis of several studies performed in simpler organisms or in mammalian model animals supports the feasibility of such multidimensional integration and demonstrates the power of DNA microarray as an indispensable molecular tool for such integration. Evaluation of DNA microarray techniques indicates that these techniques, despite limitations, have advanced to a point where the question-driven profiling research has become a feasible complement to the conventional, hypothesis-driven research. With a keen sense of homeostasis, global regulation, and quantitative analysis, integrative physiologists are uniquely positioned to apply these techniques to enhance the understanding of complex physiological functions. PMID:14678487

MultiDK: A Multiple Descriptor Multiple Kernel Approach for Molecular Discovery and Its Application to Organic Flow Battery Electrolytes.

PubMed

Kim, Sungjin; Jinich, Adrián; Aspuru-Guzik, Alán

2017-04-24

We propose a multiple descriptor multiple kernel (MultiDK) method for efficient molecular discovery using machine learning. We show that the MultiDK method improves both the speed and accuracy of molecular property prediction. We apply the method to the discovery of electrolyte molecules for aqueous redox flow batteries. Using multiple-type-as opposed to single-type-descriptors, we obtain more relevant features for machine learning. Following the principle of "wisdom of the crowds", the combination of multiple-type descriptors significantly boosts prediction performance. Moreover, by employing multiple kernels-more than one kernel function for a set of the input descriptors-MultiDK exploits nonlinear relations between molecular structure and properties better than a linear regression approach. The multiple kernels consist of a Tanimoto similarity kernel and a linear kernel for a set of binary descriptors and a set of nonbinary descriptors, respectively. Using MultiDK, we achieve an average performance of r 2 = 0.92 with a test set of molecules for solubility prediction. We also extend MultiDK to predict pH-dependent solubility and apply it to a set of quinone molecules with different ionizable functional groups to assess their performance as flow battery electrolytes.

Multiple methods integration for structural mechanics analysis and design

NASA Technical Reports Server (NTRS)

Housner, J. M.; Aminpour, M. A.

1991-01-01

A new research area of multiple methods integration is proposed for joining diverse methods of structural mechanics analysis which interact with one another. Three categories of multiple methods are defined: those in which a physical interface are well defined; those in which a physical interface is not well-defined, but selected; and those in which the interface is a mathematical transformation. Two fundamental integration procedures are presented that can be extended to integrate various methods (e.g., finite elements, Rayleigh Ritz, Galerkin, and integral methods) with one another. Since the finite element method will likely be the major method to be integrated, its enhanced robustness under element distortion is also examined and a new robust shell element is demonstrated.

Evaluation of atomic pressure in the multiple time-step integration algorithm.

PubMed

Andoh, Yoshimichi; Yoshii, Noriyuki; Yamada, Atsushi; Okazaki, Susumu

2017-04-15

In molecular dynamics (MD) calculations, reduction in calculation time per MD loop is essential. A multiple time-step (MTS) integration algorithm, the RESPA (Tuckerman and Berne, J. Chem. Phys. 1992, 97, 1990-2001), enables reductions in calculation time by decreasing the frequency of time-consuming long-range interaction calculations. However, the RESPA MTS algorithm involves uncertainties in evaluating the atomic interaction-based pressure (i.e., atomic pressure) of systems with and without holonomic constraints. It is not clear which intermediate forces and constraint forces in the MTS integration procedure should be used to calculate the atomic pressure. In this article, we propose a series of equations to evaluate the atomic pressure in the RESPA MTS integration procedure on the basis of its equivalence to the Velocity-Verlet integration procedure with a single time step (STS). The equations guarantee time-reversibility even for the system with holonomic constrants. Furthermore, we generalize the equations to both (i) arbitrary number of inner time steps and (ii) arbitrary number of force components (RESPA levels). The atomic pressure calculated by our equations with the MTS integration shows excellent agreement with the reference value with the STS, whereas pressures calculated using the conventional ad hoc equations deviated from it. Our equations can be extended straightforwardly to the MTS integration algorithm for the isothermal NVT and isothermal-isobaric NPT ensembles. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

jAMVLE, a New Integrated Molecular Visualization Learning Environment

ERIC Educational Resources Information Center

Bottomley, Steven; Chandler, David; Morgan, Eleanor; Helmerhorst, Erik

2006-01-01

A new computer-based molecular visualization tool has been developed for teaching, and learning, molecular structure. This java-based jmol Amalgamated Molecular Visualization Learning Environment (jAMVLE) is platform-independent, integrated, and interactive. It has an overall graphical user interface that is intuitive and easy to use. The…

inTB - a data integration platform for molecular and clinical epidemiological analysis of tuberculosis

PubMed Central

2013-01-01

Background Tuberculosis is currently the second highest cause of death from infectious diseases worldwide. The emergence of multi and extensive drug resistance is threatening to make tuberculosis incurable. There is growing evidence that the genetic diversity of Mycobacterium tuberculosis may have important clinical consequences. Therefore, combining genetic, clinical and socio-demographic data is critical to understand the epidemiology of this infectious disease, and how virulence and other phenotypic traits evolve over time. This requires dedicated bioinformatics platforms, capable of integrating and enabling analyses of this heterogeneous data. Results We developed inTB, a web-based system for integrated warehousing and analysis of clinical, socio-demographic and molecular data for Mycobacterium sp. isolates. As a database it can organize and display data from any of the standard genotyping methods (SNP, MIRU-VNTR, RFLP and spoligotype), as well as an extensive array of clinical and socio-demographic variables that are used in multiple countries to characterize the disease. Through the inTB interface it is possible to insert and download data, browse the database and search specific parameters. New isolates are automatically classified into strains according to an internal reference, and data uploaded or typed in is checked for internal consistency. As an analysis framework, the system provides simple, point and click analysis tools that allow multiple types of data plotting, as well as simple ways to download data for external analysis. Individual trees for each genotyping method are available, as well as a super tree combining all of them. The integrative nature of inTB grants the user the ability to generate trees for filtered subsets of data crossing molecular and clinical/socio-demografic information. inTB is built on open source software, can be easily installed locally and easily adapted to other diseases. Its design allows for use by research

inTB - a data integration platform for molecular and clinical epidemiological analysis of tuberculosis.

PubMed

Soares, Patrícia; Alves, Renato J; Abecasis, Ana B; Penha-Gonçalves, Carlos; Gomes, M Gabriela M; Pereira-Leal, José B

2013-08-30

Tuberculosis is currently the second highest cause of death from infectious diseases worldwide. The emergence of multi and extensive drug resistance is threatening to make tuberculosis incurable. There is growing evidence that the genetic diversity of Mycobacterium tuberculosis may have important clinical consequences. Therefore, combining genetic, clinical and socio-demographic data is critical to understand the epidemiology of this infectious disease, and how virulence and other phenotypic traits evolve over time. This requires dedicated bioinformatics platforms, capable of integrating and enabling analyses of this heterogeneous data. We developed inTB, a web-based system for integrated warehousing and analysis of clinical, socio-demographic and molecular data for Mycobacterium sp. isolates. As a database it can organize and display data from any of the standard genotyping methods (SNP, MIRU-VNTR, RFLP and spoligotype), as well as an extensive array of clinical and socio-demographic variables that are used in multiple countries to characterize the disease. Through the inTB interface it is possible to insert and download data, browse the database and search specific parameters. New isolates are automatically classified into strains according to an internal reference, and data uploaded or typed in is checked for internal consistency. As an analysis framework, the system provides simple, point and click analysis tools that allow multiple types of data plotting, as well as simple ways to download data for external analysis. Individual trees for each genotyping method are available, as well as a super tree combining all of them. The integrative nature of inTB grants the user the ability to generate trees for filtered subsets of data crossing molecular and clinical/socio-demografic information. inTB is built on open source software, can be easily installed locally and easily adapted to other diseases. Its design allows for use by research laboratories, hospitals or

Engineering integrated digital circuits with allosteric ribozymes for scaling up molecular computation and diagnostics.

PubMed

Penchovsky, Robert

2012-10-19

Here we describe molecular implementations of integrated digital circuits, including a three-input AND logic gate, a two-input multiplexer, and 1-to-2 decoder using allosteric ribozymes. Furthermore, we demonstrate a multiplexer-decoder circuit. The ribozymes are designed to seek-and-destroy specific RNAs with a certain length by a fully computerized procedure. The algorithm can accurately predict one base substitution that alters the ribozyme's logic function. The ability to sense the length of RNA molecules enables single ribozymes to be used as platforms for multiple interactions. These ribozymes can work as integrated circuits with the functionality of up to five logic gates. The ribozyme design is universal since the allosteric and substrate domains can be altered to sense different RNAs. In addition, the ribozymes can specifically cleave RNA molecules with triplet-repeat expansions observed in genetic disorders such as oculopharyngeal muscular dystrophy. Therefore, the designer ribozymes can be employed for scaling up computing and diagnostic networks in the fields of molecular computing and diagnostics and RNA synthetic biology.

Logic integration of mRNA signals by an RNAi-based molecular computer.

PubMed

Xie, Zhen; Liu, Siyuan John; Bleris, Leonidas; Benenson, Yaakov

2010-05-01

Synthetic in vivo molecular 'computers' could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that 'transduce' mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi 'computational' module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting.

Logic integration of mRNA signals by an RNAi-based molecular computer

PubMed Central

Xie, Zhen; Liu, Siyuan John; Bleris, Leonidas; Benenson, Yaakov

2010-01-01

Synthetic in vivo molecular ‘computers’ could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that ‘transduce’ mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi ‘computational’ module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting. PMID:20194121

Smart wheelchair: integration of multiple sensors

NASA Astrophysics Data System (ADS)

Gassara, H. E.; Almuhamed, S.; Moukadem, A.; Schacher, L.; Dieterlen, A.; Adolphe, D.

2017-10-01

The aim of the present work is to develop a smart wheelchair by integrating multiple sensors for measuring user’s physiological signals and subsequently transmitting and monitoring the treated signals to the user, a designated person or institution. Among other sensors, force, accelerometer, and temperature sensors are successfully integrated within both the backrest and the seat cushions of the wheelchair; while a pulse sensor is integrated within the armrest. The pulse sensor is connected to an amplification circuit board that is, in turn, placed within the armrest. The force and temperature sensors are integrated into a textile cover of the cushions by means of embroidery and sewing techniques. The signal from accelerometer is transmitted through Wi-Fi connection. The electrical connections needed for power supplying of sensors are made by embroidered conductive threads.

Noninvasive imaging of multiple myeloma using near infrared fluorescent molecular probe

NASA Astrophysics Data System (ADS)

Hathi, Deep; Zhou, Haiying; Bollerman-Nowlis, Alex; Shokeen, Monica; Akers, Walter J.

2016-03-01

Multiple myeloma is a plasma cell malignancy characterized by monoclonal gammopathy and osteolytic bone lesions. Multiple myeloma is most commonly diagnosed in late disease stages, presenting with pathologic fracture. Early diagnosis and monitoring of disease status may improve quality of life and long-term survival for multiple myeloma patients from what is now a devastating and fatal disease. We have developed a near-infrared targeted fluorescent molecular probe with high affinity to the α4β1 integrin receptor (VLA-4)overexpressed by a majority of multiple myeloma cells as a non-radioactive analog to PET/CT tracer currently being developed for human diagnostics. A near-infrared dye that emits about 700 nm was conjugated to a high affinity peptidomimmetic. Binding affinity and specificity for multiple myeloma cells was investigated in vitro by tissue staining and flow cytometry. After demonstration of sensitivity and specificity, preclinical optical imaging studies were performed to evaluate tumor specificity in murine subcutaneous and metastatic multiple myeloma models. The VLA-4-targeted molecular probe showed high affinity for subcutaneous MM tumor xenografts. Importantly, tumor cells specific accumulation in the bone marrow of metastatic multiple myeloma correlated with GFP signal from transfected cells. Ex vivo flow cytometry of tumor tissue and bone marrow further corroborated in vivo imaging data, demonstrating the specificity of the novel agent and potential for quantitative imaging of multiple myeloma burden in these models.

Integrated analysis of microRNAs, transcription factors and target genes expression discloses a specific molecular architecture of hyperdiploid multiple myeloma

PubMed Central

Caracciolo, Daniele; Agnelli, Luca; Neri, Antonino; Walker, Brian A.; Morgan, Gareth J.; Cannataro, Mario

2015-01-01

Multiple Myeloma (MM) is a malignancy characterized by the hyperdiploid (HD-MM) and the non-hyperdiploid (nHD-MM) subtypes. To shed light within the molecular architecture of these subtypes, we used a novel integromics approach. By annotated MM patient mRNA/microRNA (miRNA) datasets, we investigated mRNAs and miRNAs profiles with relation to changes in transcriptional regulators expression. We found that HD-MM displays specific gene and miRNA expression profiles, involving the Signal Transducer and Activator of Transcription (STAT)3 pathway as well as the Transforming Growth Factor–beta (TGFβ) and the transcription regulator Nuclear Protein-1 (NUPR1). Our data define specific molecular features of HD-MM that may translate in the identification of novel relevant druggable targets. PMID:26056083

Multiple Time-Step Dual-Hamiltonian Hybrid Molecular Dynamics — Monte Carlo Canonical Propagation Algorithm

PubMed Central

Weare, Jonathan; Dinner, Aaron R.; Roux, Benoît

2016-01-01

A multiple time-step integrator based on a dual Hamiltonian and a hybrid method combining molecular dynamics (MD) and Monte Carlo (MC) is proposed to sample systems in the canonical ensemble. The Dual Hamiltonian Multiple Time-Step (DHMTS) algorithm is based on two similar Hamiltonians: a computationally expensive one that serves as a reference and a computationally inexpensive one to which the workload is shifted. The central assumption is that the difference between the two Hamiltonians is slowly varying. Earlier work has shown that such dual Hamiltonian multiple time-step schemes effectively precondition nonlinear differential equations for dynamics by reformulating them into a recursive root finding problem that can be solved by propagating a correction term through an internal loop, analogous to RESPA. Of special interest in the present context, a hybrid MD-MC version of the DHMTS algorithm is introduced to enforce detailed balance via a Metropolis acceptance criterion and ensure consistency with the Boltzmann distribution. The Metropolis criterion suppresses the discretization errors normally associated with the propagation according to the computationally inexpensive Hamiltonian, treating the discretization error as an external work. Illustrative tests are carried out to demonstrate the effectiveness of the method. PMID:26918826

Propagating Molecular Recognition Events through Highly Integrated Sense-Response Chemical Systems

DTIC Science & Technology

2017-08-01

Propagating Molecular Recognition Events through Highly Integrated Sense-Response Chemical Systems The views, opinions and/or findings contained in...University of California - San Diego Title: Propagating Molecular Recognition Events through Highly Integrated Sense-Response Chemical Systems Report Term...including enzymatic reactions , occurring at the aqueous interfaces of thermotropic LCs show promise as the basis of biomolecular triggers of LC

Web-TCGA: an online platform for integrated analysis of molecular cancer data sets.

PubMed

Deng, Mario; Brägelmann, Johannes; Schultze, Joachim L; Perner, Sven

2016-02-06

The Cancer Genome Atlas (TCGA) is a pool of molecular data sets publicly accessible and freely available to cancer researchers anywhere around the world. However, wide spread use is limited since an advanced knowledge of statistics and statistical software is required. In order to improve accessibility we created Web-TCGA, a web based, freely accessible online tool, which can also be run in a private instance, for integrated analysis of molecular cancer data sets provided by TCGA. In contrast to already available tools, Web-TCGA utilizes different methods for analysis and visualization of TCGA data, allowing users to generate global molecular profiles across different cancer entities simultaneously. In addition to global molecular profiles, Web-TCGA offers highly detailed gene and tumor entity centric analysis by providing interactive tables and views. As a supplement to other already available tools, such as cBioPortal (Sci Signal 6:pl1, 2013, Cancer Discov 2:401-4, 2012), Web-TCGA is offering an analysis service, which does not require any installation or configuration, for molecular data sets available at the TCGA. Individual processing requests (queries) are generated by the user for mutation, methylation, expression and copy number variation (CNV) analyses. The user can focus analyses on results from single genes and cancer entities or perform a global analysis (multiple cancer entities and genes simultaneously).

Unsupervised multiple kernel learning for heterogeneous data integration.

PubMed

Mariette, Jérôme; Villa-Vialaneix, Nathalie

2018-03-15

Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

Information Integration in Multiple Cue Judgment: A Division of Labor Hypothesis

ERIC Educational Resources Information Center

Juslin, Peter; Karlsson, Linnea; Olsson, Henrik

2008-01-01

There is considerable evidence that judgment is constrained to additive integration of information. The authors propose an explanation of why serial and additive cognitive integration can produce accurate multiple cue judgment both in additive and non-additive environments in terms of an adaptive division of labor between multiple representations.…

Geometric integration in Born-Oppenheimer molecular dynamics.

PubMed

Odell, Anders; Delin, Anna; Johansson, Börje; Cawkwell, Marc J; Niklasson, Anders M N

2011-12-14

Geometric integration schemes for extended Lagrangian self-consistent Born-Oppenheimer molecular dynamics, including a weak dissipation to remove numerical noise, are developed and analyzed. The extended Lagrangian framework enables the geometric integration of both the nuclear and electronic degrees of freedom. This provides highly efficient simulations that are stable and energy conserving even under incomplete and approximate self-consistent field (SCF) convergence. We investigate three different geometric integration schemes: (1) regular time reversible Verlet, (2) second order optimal symplectic, and (3) third order optimal symplectic. We look at energy conservation, accuracy, and stability as a function of dissipation, integration time step, and SCF convergence. We find that the inclusion of dissipation in the symplectic integration methods gives an efficient damping of numerical noise or perturbations that otherwise may accumulate from finite arithmetics in a perfect reversible dynamics. © 2011 American Institute of Physics

An integrated molecular cytogenetic map of Cucumis sativus L. chromosome 2.

PubMed

Han, Yonghua; Zhang, Zhonghua; Huang, Sanwen; Jin, Weiwei

2011-01-27

Integration of molecular, genetic and cytological maps is still a challenge for most plant species. Recent progress in molecular and cytogenetic studies created a basis for developing integrated maps in cucumber (Cucumis sativus L.). In this study, eleven fosmid clones and three plasmids containing 45S rDNA, the centromeric satellite repeat Type III and the pericentriomeric repeat CsRP1 sequences respectively were hybridized to cucumber metaphase chromosomes to assign their cytological location on chromosome 2. Moreover, an integrated molecular cytogenetic map of cucumber chromosomes 2 was constructed by fluorescence in situ hybridization (FISH) mapping of 11 fosmid clones together with the cucumber centromere-specific Type III sequence on meiotic pachytene chromosomes. The cytogenetic map was fully integrated with genetic linkage map since each fosmid clone was anchored by a genetically mapped simple sequence repeat marker (SSR). The relationship between the genetic and physical distances along chromosome was analyzed. Recombination was not evenly distributed along the physical length of chromosome 2. Suppression of recombination was found in centromeric and pericentromeric regions. Our results also indicated that the molecular markers composing the linkage map for chromosome 2 provided excellent coverage of the chromosome.

Molecular profiling of multiple myeloma: from gene expression analysis to next-generation sequencing.

PubMed

Agnelli, Luca; Tassone, Pierfrancesco; Neri, Antonino

2013-06-01

Multiple myeloma is a fatal malignant proliferation of clonal bone marrow Ig-secreting plasma cells, characterized by wide clinical, biological, and molecular heterogeneity. Herein, global gene and microRNA expression, genome-wide DNA profilings, and next-generation sequencing technology used to investigate the genomic alterations underlying the bio-clinical heterogeneity in multiple myeloma are discussed. High-throughput technologies have undoubtedly allowed a better comprehension of the molecular basis of the disease, a fine stratification, and early identification of high-risk patients, and have provided insights toward targeted therapy studies. However, such technologies are at risk of being affected by laboratory- or cohort-specific biases, and are moreover influenced by high number of expected false positives. This aspect has a major weight in myeloma, which is characterized by large molecular heterogeneity. Therefore, meta-analysis as well as multiple approaches are desirable if not mandatory to validate the results obtained, in line with commonly accepted recommendation for tumor diagnostic/prognostic biomarker studies.

Multiple biomarkers in molecular oncology. I. Molecular diagnostics applications in cervical cancer detection.

PubMed

Malinowski, Douglas P

2007-03-01

The screening for cervical carcinoma and its malignant precursors (cervical neoplasia) currently employs morphology-based detection methods (Papanicolaou [Pap] smear) in addition to the detection of high-risk human papillomavirus. The combination of the Pap smear with human papillomavirus testing has achieved significant improvements in sensitivity for the detection of cervical disease. Diagnosis of cervical neoplasia is dependent upon histology assessment of cervical biopsy specimens. Attempts to improve the specificity of cervical disease screening have focused on the investigation of molecular biomarkers for adjunctive use in combination with the Pap smear. Active research into the genomic and proteomic alterations that occur during human papillomavirus-induced neoplastic transformation have begun to characterize some of the basic mechanisms inherent to the disease process of cervical cancer development. This research continues to demonstrate the complexity of multiple genomic and proteomic alterations that accumulate during the tumorigenesis process. Despite this diversity, basic patterns of uncontrolled signal transduction, cell cycle deregulation, activation of DNA replication and altered extracellular matrix interactions are beginning to emerge as common features inherent to cervical cancer development. Some of these gene or protein expression alterations have been investigated as potential biomarkers for screening and diagnostics applications. The contribution of multiple gene alterations in the development of cervical cancer suggests that the application of multiple biomarker panels has the potential to develop clinically useful molecular diagnostics. In this review, the application of biomarkers for the improvement of sensitivity and specificity of the detection of cervical neoplasia within cytology specimens will be discussed.

Integrable generalizations of non-linear multiple three-wave interaction models

NASA Astrophysics Data System (ADS)

Jurčo, Branislav

1989-07-01

Integrable generalizations of multiple three-wave interaction models in terms of r-matrix formulation are investigated. The Lax representations, complete sets of first integrals in involution are constructed, the quantization leading to Gaudin's models is discussed.

Molecular biological analysis in a patient with multiple lung adenocarcinomas.

PubMed

Wakayama, Tomoshige; Hirata, Hirokuni; Suka, Shunsuke; Sato, Kozo; Tatewaki, Masamitsu; Souma, Ryosuke; Satoh, Hideyuki; Tamura, Motohiko; Matsumura, Yuji; Imada, Hiroki; Sugiyama, Kumiya; Arima, Masafumi; Kurasawa, Kazuhiro; Fukuda, Takeshi; Fukushima, Yasutsugu

2018-05-01

The utility of molecular biological analysis in lung adenocarcinoma has been demonstrated. Herein we report a rare case presenting as multiple lung adenocarcinomas with four different EGFR gene mutations detected in three lung tumors. After opacification was detected by routine chest X-ray, the patient, a 64-year-old woman, underwent chest computed tomography which revealed a right lung segment S4 ground-glass nodule (GGN). Follow-up computed tomography revealed a 42 mm GGN nodule with a 26 mm nodule (S6) and a 20 mm GGN (S10). Histopathology of resected specimens from the right middle and lower lobes revealed all three nodules were adenocarcinomas. Four EGFR mutations were detected; no three tumors had the same mutations. Molecular biological analysis is a promising tool for the diagnosis of primary tumors in patients with multiple lung carcinomas of the same histotype, enabling appropriate treatment. © 2018 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

High sensitivity detection of NO2 employing off-axis integrated cavity output spectroscopy coupled with multiple line integrated spectroscopy

NASA Astrophysics Data System (ADS)

Rao, Gottipaty N.; Karpf, Andreas

2011-05-01

We report on the development of a new sensor for NO2 with ultrahigh sensitivity of detection. This has been accomplished by combining off-axis integrated cavity output spectroscopy (OA-ICOS) (which can provide large path lengths of the order of several km in a small volume cell) with multiple line integrated absorption spectroscopy (MLIAS) (where we integrate the absorption spectra over a large number of rotational-vibrational transitions of the molecular species to further improve the sensitivity). Employing an external cavity tunable quantum cascade laser operating in the 1601 - 1670 cm-1 range and a high-finesse optical cavity, the absorption spectra of NO2 over 100 transitions in the R-band have been recorded. From the observed linear relationship between the integrated absorption vs. concentration of NO2, we report an effective sensitivity of detection of 10 ppt for NO2. To the best of our knowledge, this is among the most sensitive levels of detection of NO2 to date. A sensitive sensor for the detection of NO2 will be helpful to monitor the ambient air quality, combustion emissions from the automobiles, power plants, aircraft and for the detection of nitrate based explosives (which are commonly used in improvised explosives (IEDs)). Additionally such a sensor would be valuable for the study of complex chemical reactions that undergo in the atmosphere resulting in the formation of photochemical smog, tropospheric ozone and acid rain.

A Targeted "Capture" and "Removal" Scavenger toward Multiple Pollutants for Water Remediation based on Molecular Recognition.

PubMed

Wang, Jie; Shen, Haijing; Hu, Xiaoxia; Li, Yan; Li, Zhihao; Xu, Jinfan; Song, Xiufeng; Zeng, Haibo; Yuan, Quan

2016-03-01

For the water remediation techniques based on adsorption, the long-standing contradictories between selectivity and multiple adsorbability, as well as between affinity and recyclability, have put it on weak defense amid more and more severe environment crisis. Here, a pollutant-targeting hydrogel scavenger is reported for water remediation with both high selectivity and multiple adsorbability for several pollutants, and with strong affinity and good recyclability through rationally integrating the advantages of multiple functional materials. In the scavenger, aptamers fold into binding pockets to accommodate the molecular structure of pollutants to afford perfect selectivity, and Janus nanoparticles with antibacterial function as well as anisotropic surfaces to immobilize multiple aptamers allow for simultaneously handling different kinds of pollutants. The scavenger exhibits high efficiencies in removing pollutants from water and it can be easily recycled for many times without significant loss of loading capacities. Moreover, the residual concentrations of each contaminant are well below the drinking water standards. Thermodynamic behavior of the adsorption process is investigated and the rate-controlling process is determined. Furthermore, a point of use device is constructed and it displays high efficiency in removing pollutants from environmental water. The scavenger exhibits great promise to be applied in the next generation of water purification systems.

Integration of Molecular Pathology, Epidemiology, and Social Science for Global Precision Medicine

PubMed Central

Nishi, Akihiro; Milner, Danny A; Giovannucci, Edward L.; Nishihara, Reiko; Tan, Andy S.; Kawachi, Ichiro; Ogino, Shuji

2015-01-01

Summary The precision medicine concept and the unique disease principle imply that each patient has unique pathogenic processes resulting from heterogeneous cellular genetic and epigenetic alterations, and interactions between cells (including immune cells) and exposures, including dietary, environmental, microbial, and lifestyle factors. As a core method field in population health science and medicine, epidemiology is a growing scientific discipline that can analyze disease risk factors, and develop statistical methodologies to maximize utilization of big data on populations and disease pathology. The evolving transdisciplinary field of molecular pathological epidemiology (MPE) can advance biomedical and health research by linking exposures to molecular pathologic signatures, enhancing causal inference, and identifying potential biomarkers for clinical impact. The MPE approach can be applied to any diseases, although it has been most commonly used in neoplastic diseases (including breast, lung and colorectal cancers) because of availability of various molecular diagnostic tests. However, use of state-of-the-art genomic, epigenomic and other omic technologies and expensive drugs in modern healthcare systems increases racial, ethnic and socioeconomic disparities. To address this, we propose to integrate molecular pathology, epidemiology, and social science. Social epidemiology integrates the latter two fields. The integrative social MPE model can embrace sociology, economics and precision medicine, address global health disparities and inequalities, and elucidate biological effects of social environments, behaviors, and networks. We foresee advancements of molecular medicine, including molecular diagnostics, biomedical imaging, and targeted therapeutics, which should benefit individuals in a global population, by means of an interdisciplinary approach of integrative MPE and social health science. PMID:26636627

Integration of molecular pathology, epidemiology and social science for global precision medicine.

PubMed

Nishi, Akihiro; Milner, Danny A; Giovannucci, Edward L; Nishihara, Reiko; Tan, Andy S; Kawachi, Ichiro; Ogino, Shuji

2016-01-01

The precision medicine concept and the unique disease principle imply that each patient has unique pathogenic processes resulting from heterogeneous cellular genetic and epigenetic alterations and interactions between cells (including immune cells) and exposures, including dietary, environmental, microbial and lifestyle factors. As a core method field in population health science and medicine, epidemiology is a growing scientific discipline that can analyze disease risk factors and develop statistical methodologies to maximize utilization of big data on populations and disease pathology. The evolving transdisciplinary field of molecular pathological epidemiology (MPE) can advance biomedical and health research by linking exposures to molecular pathologic signatures, enhancing causal inference and identifying potential biomarkers for clinical impact. The MPE approach can be applied to any diseases, although it has been most commonly used in neoplastic diseases (including breast, lung and colorectal cancers) because of availability of various molecular diagnostic tests. However, use of state-of-the-art genomic, epigenomic and other omic technologies and expensive drugs in modern healthcare systems increases racial, ethnic and socioeconomic disparities. To address this, we propose to integrate molecular pathology, epidemiology and social science. Social epidemiology integrates the latter two fields. The integrative social MPE model can embrace sociology, economics and precision medicine, address global health disparities and inequalities, and elucidate biological effects of social environments, behaviors and networks. We foresee advancements of molecular medicine, including molecular diagnostics, biomedical imaging and targeted therapeutics, which should benefit individuals in a global population, by means of an interdisciplinary approach of integrative MPE and social health science.

Disease gene prioritization by integrating tissue-specific molecular networks using a robust multi-network model.

PubMed

Ni, Jingchao; Koyuturk, Mehmet; Tong, Hanghang; Haines, Jonathan; Xu, Rong; Zhang, Xiang

2016-11-10

Accurately prioritizing candidate disease genes is an important and challenging problem. Various network-based methods have been developed to predict potential disease genes by utilizing the disease similarity network and molecular networks such as protein interaction or gene co-expression networks. Although successful, a common limitation of the existing methods is that they assume all diseases share the same molecular network and a single generic molecular network is used to predict candidate genes for all diseases. However, different diseases tend to manifest in different tissues, and the molecular networks in different tissues are usually different. An ideal method should be able to incorporate tissue-specific molecular networks for different diseases. In this paper, we develop a robust and flexible method to integrate tissue-specific molecular networks for disease gene prioritization. Our method allows each disease to have its own tissue-specific network(s). We formulate the problem of candidate gene prioritization as an optimization problem based on network propagation. When there are multiple tissue-specific networks available for a disease, our method can automatically infer the relative importance of each tissue-specific network. Thus it is robust to the noisy and incomplete network data. To solve the optimization problem, we develop fast algorithms which have linear time complexities in the number of nodes in the molecular networks. We also provide rigorous theoretical foundations for our algorithms in terms of their optimality and convergence properties. Extensive experimental results show that our method can significantly improve the accuracy of candidate gene prioritization compared with the state-of-the-art methods. In our experiments, we compare our methods with 7 popular network-based disease gene prioritization algorithms on diseases from Online Mendelian Inheritance in Man (OMIM) database. The experimental results demonstrate that our methods

Molecular Testing in Multiple Synchronous Lung Adenocarcinomas: Case Report and Literature Review.

PubMed

Rafael, Oana C; Lazzaro, Richard; Hasanovic, Adnan

2016-02-01

Discovery of driver mutations in pulmonary adenocarcinoma has revolutionized the field of thoracic oncology with major impact on therapy and diagnosis. Testing for EGFR, ALK, and KRAS mutations has become part of everyday practice. We report a case with multiple synchronous primary pulmonary adenocarcinomas in a 72-year-old female with previous history of smoking. The patient presented with cough and bilateral lung ground glass opacities. A positron emission tomography/computed tomography scan showed no activity in mediastinal lymph nodes. She underwent a left upper lobe biopsy and a right upper lobe wedge resection. Pathology revealed 4 morphologically distinct adenocarcinoma foci, suggestive of synchronous primary lung tumors. Molecular testing demonstrated no mutation in the left tumor. Three different driver mutations were present in the right lung tumors: KRAS codon 12 G12D and G12V and EGFR exon 21 L858R mutation, confirming the initial histologic impression. Subsequently, left upper lobe lobectomy showed 3 additional foci of adenocarcinoma with different morphologies, suggestive of synchronous primaries as well. No additional molecular testing was performed. Synchronous pulmonary adenocarcinomas are not uncommon; however, 4 or more synchronous tumors are rare. Distinguishing multiple primary tumors from intrapulmonary metastases is a common problem in thoracic oncology with major implications for staging, prognosis, and treatment. Lung adenocarcinoma subclassification based on predominant and coexisting histologic patterns can greatly facilitate differentiation between intrapulmonary metastases and multiple synchronous tumors. Use of molecular profiling is recommended since it further increases confidence in the diagnostic workup of multiple pulmonary adenocarcinomas and helps guiding therapy. © The Author(s) 2015.

Validating Measurement of Knowledge Integration in Science Using Multiple-Choice and Explanation Items

ERIC Educational Resources Information Center

Lee, Hee-Sun; Liu, Ou Lydia; Linn, Marcia C.

2011-01-01

This study explores measurement of a construct called knowledge integration in science using multiple-choice and explanation items. We use construct and instructional validity evidence to examine the role multiple-choice and explanation items plays in measuring students' knowledge integration ability. For construct validity, we analyze item…

Integral Methodological Pluralism in Science Education Research: Valuing Multiple Perspectives

ERIC Educational Resources Information Center

Davis, Nancy T.; Callihan, Laurie P.

2013-01-01

This article examines the multiple methodologies used in educational research and proposes a model that includes all of them as contributing to understanding educational contexts and research from multiple perspectives. The model, based on integral theory (Wilber in a theory of everything. Shambhala, Boston, 2000) values all forms of research as…

Integrated software environment based on COMKAT for analyzing tracer pharmacokinetics with molecular imaging.

PubMed

Fang, Yu-Hua Dean; Asthana, Pravesh; Salinas, Cristian; Huang, Hsuan-Ming; Muzic, Raymond F

2010-01-01

An integrated software package, Compartment Model Kinetic Analysis Tool (COMKAT), is presented in this report. COMKAT is an open-source software package with many functions for incorporating pharmacokinetic analysis in molecular imaging research and has both command-line and graphical user interfaces. With COMKAT, users may load and display images, draw regions of interest, load input functions, select kinetic models from a predefined list, or create a novel model and perform parameter estimation, all without having to write any computer code. For image analysis, COMKAT image tool supports multiple image file formats, including the Digital Imaging and Communications in Medicine (DICOM) standard. Image contrast, zoom, reslicing, display color table, and frame summation can be adjusted in COMKAT image tool. It also displays and automatically registers images from 2 modalities. Parametric imaging capability is provided and can be combined with the distributed computing support to enhance computation speeds. For users without MATLAB licenses, a compiled, executable version of COMKAT is available, although it currently has only a subset of the full COMKAT capability. Both the compiled and the noncompiled versions of COMKAT are free for academic research use. Extensive documentation, examples, and COMKAT itself are available on its wiki-based Web site, http://comkat.case.edu. Users are encouraged to contribute, sharing their experience, examples, and extensions of COMKAT. With integrated functionality specifically designed for imaging and kinetic modeling analysis, COMKAT can be used as a software environment for molecular imaging and pharmacokinetic analysis.

Integrative set enrichment testing for multiple omics platforms

PubMed Central

2011-01-01

Background Enrichment testing assesses the overall evidence of differential expression behavior of the elements within a defined set. When we have measured many molecular aspects, e.g. gene expression, metabolites, proteins, it is desirable to assess their differential tendencies jointly across platforms using an integrated set enrichment test. In this work we explore the properties of several methods for performing a combined enrichment test using gene expression and metabolomics as the motivating platforms. Results Using two simulation models we explored the properties of several enrichment methods including two novel methods: the logistic regression 2-degree of freedom Wald test and the 2-dimensional permutation p-value for the sum-of-squared statistics test. In relation to their univariate counterparts we find that the joint tests can improve our ability to detect results that are marginal univariately. We also find that joint tests improve the ranking of associated pathways compared to their univariate counterparts. However, there is a risk of Type I error inflation with some methods and self-contained methods lose specificity when the sets are not representative of underlying association. Conclusions In this work we show that consideration of data from multiple platforms, in conjunction with summarization via a priori pathway information, leads to increased power in detection of genomic associations with phenotypes. PMID:22118224

Sarcoptes-World Molecular Network (Sarcoptes-WMN): integrating research on scabies.

PubMed

Alasaad, Samer; Walton, Shelley; Rossi, Luca; Bornstein, Set; Abu-Madi, Marawan; Soriguer, Ramón C; Fitzgerald, Scott; Zhu, Xing-Quan; Zimmermann, Werner; Ugbomoiko, Uade Samuel; Pei, Kurtis Jai-Chyi; Heukelbach, Jörg

2011-05-01

Parasites threaten human and animal health globally. It is estimated that more than 60% of people on planet Earth carry at least one parasite, many of them several different species. Unfortunately, parasite studies suffer from duplications and inconsistencies between different investigator groups. Hence, groups need to collaborate in an integrated manner in areas including parasite control, improved therapy strategies, diagnostic and surveillance tools, and public awareness. Parasite studies will be better served if there is coordinated management of field data and samples across multidisciplinary approach plans, among academic and non-academic organizations worldwide. In this paper we report the first 'Living organism-World Molecular Network', with the cooperation of 167 parasitologists from 88 countries on all continents. This integrative approach, the 'Sarcoptes-World Molecular Network', seeks to harmonize Sarcoptes epidemiology, diagnosis, treatment, and molecular studies from all over the world, with the aim of decreasing mite infestations in humans and animals. Copyright © 2011 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

A microfluidic system with integrated molecular imprinting polymer films for surface plasmon resonance detection

NASA Astrophysics Data System (ADS)

Huang, Shih-Chiang; Lee, Gwo-Bin; Chien, Fan-Ching; Chen, Shean-Jen; Chen, Wen-Janq; Yang, Ming-Chang

2006-07-01

This paper presents a novel microfluidic system with integrated molecular imprinting polymer (MIP) films designed for surface plasmon resonance (SPR) biosensing of multiple nanoscale biomolecules. The innovative microfluidic chip uses pneumatic microvalves and micropumps to transport a precise amount of the biosample through multiple microchannels to sensing regions containing the locally spin-coated MIP films. The signals of SPR biosensing are basically proportional to the number of molecules adsorbed on the MIP films. Hence, a precise control of flow rates inside microchannels is important to determine the adsorption amount of the molecules in the SPR/MIP chips. The integration of micropumps and microvalves can automate the sample introduction process and precisely control the amount of the sample injection to the microfluidic system. The proposed biochip enables the label-free biosensing of biomolecules in an automatic format, and provides a highly sensitive, highly specific and high-throughput detection performance. Three samples, i.e. progesterone, cholesterol and testosterone, are successfully detected using the developed system. The experimental results show that the proposed SPR/MIP microfluidic chip provides a comparable sensitivity to that of large-scale SPR techniques, but with reduced sample consumption and an automatic format. As such, the developed biochip has significant potential for a wide variety of nanoscale biosensing applications. The preliminary results of the current paper were presented at Transducers 2005, Seoul, Korea, 5-9 June 2005.

The Effects of Tasks on Integrating Information from Multiple Documents

ERIC Educational Resources Information Center

Cerdan, Raquel; Vidal-Abarca, Eduardo

2008-01-01

The authors examine 2 issues: (a) how students integrate information from multiple scientific documents to describe and explain a physical phenomenon that represents a subset of the information in the documents; and (b) the role of 2 sorts of tasks to achieve this type of integration, either writing an essay on a question requiring integration…

A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

ERIC Educational Resources Information Center

Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…

Integration of molecular typing results into tuberculosis surveillance in Germany—A pilot study

PubMed Central

Fiebig, Lena; Priwitzer, Martin; Richter, Elvira; Rüsch-Gerdes, Sabine; Haas, Walter; Niemann, Stefan; Brodhun, Bonita

2017-01-01

An integrated molecular surveillance for tuberculosis (TB) improves the understanding of ongoing TB transmission by combining molecular typing and epidemiological data. However, the implementation of an integrated molecular surveillance for TB is complex and requires thoughtful consideration of feasibility, demand, public health benefits and legal issues. We aimed to pilot the integration of molecular typing results between 2008 and 2010 in the German Federal State of Baden-Württemberg (population 10.88 Million) as preparation for a nationwide implementation. Culture positive TB cases were typed by IS6110 DNA fingerprinting and results were integrated into routine notification data. Demographic and clinical characteristics of cases and clusters were described and new epidemiological links detected after integrating typing data were calculated. Furthermore, a cross-sectional survey was performed among local public health offices to evaluate their perception and experiences. Overall, typing results were available for 83% of notified culture positive TB cases, out of which 25% were clustered. Age <15 years (OR = 4.96, 95% CI: 1.69–14.55) and being born in Germany (OR = 2.01, 95% CI: 1.44–2.80) were associated with clustering. At cluster level, molecular typing information allowed the identification of previously unknown epidemiological links in 11% of the clusters. In 59% of the clusters it was not possible to identify any epidemiological link. Clusters extending over different counties were less likely to have epidemiological links identified among their cases (OR = 11.53, 95% CI: 3.48–98.23). The majority of local public health offices found molecular typing useful for their work. Our study illustrates the feasibility of integrating typing data into the German TB notification system and depicts its added public health value as complementary strategy in TB surveillance, especially to uncover transmission events among geographically separated TB patients. It

Integration of molecular typing results into tuberculosis surveillance in Germany-A pilot study.

PubMed

Andrés, Marta; Göhring-Zwacka, Elke; Fiebig, Lena; Priwitzer, Martin; Richter, Elvira; Rüsch-Gerdes, Sabine; Haas, Walter; Niemann, Stefan; Brodhun, Bonita

2017-01-01

An integrated molecular surveillance for tuberculosis (TB) improves the understanding of ongoing TB transmission by combining molecular typing and epidemiological data. However, the implementation of an integrated molecular surveillance for TB is complex and requires thoughtful consideration of feasibility, demand, public health benefits and legal issues. We aimed to pilot the integration of molecular typing results between 2008 and 2010 in the German Federal State of Baden-Württemberg (population 10.88 Million) as preparation for a nationwide implementation. Culture positive TB cases were typed by IS6110 DNA fingerprinting and results were integrated into routine notification data. Demographic and clinical characteristics of cases and clusters were described and new epidemiological links detected after integrating typing data were calculated. Furthermore, a cross-sectional survey was performed among local public health offices to evaluate their perception and experiences. Overall, typing results were available for 83% of notified culture positive TB cases, out of which 25% were clustered. Age <15 years (OR = 4.96, 95% CI: 1.69-14.55) and being born in Germany (OR = 2.01, 95% CI: 1.44-2.80) were associated with clustering. At cluster level, molecular typing information allowed the identification of previously unknown epidemiological links in 11% of the clusters. In 59% of the clusters it was not possible to identify any epidemiological link. Clusters extending over different counties were less likely to have epidemiological links identified among their cases (OR = 11.53, 95% CI: 3.48-98.23). The majority of local public health offices found molecular typing useful for their work. Our study illustrates the feasibility of integrating typing data into the German TB notification system and depicts its added public health value as complementary strategy in TB surveillance, especially to uncover transmission events among geographically separated TB patients. It also

Integrating evolutionary and molecular genetics of aging.

PubMed

Flatt, Thomas; Schmidt, Paul S

2009-10-01

Aging or senescence is an age-dependent decline in physiological function, demographically manifest as decreased survival and fecundity with increasing age. Since aging is disadvantageous it should not evolve by natural selection. So why do organisms age and die? In the 1940s and 1950s evolutionary geneticists resolved this paradox by positing that aging evolves because selection is inefficient at maintaining function late in life. By the 1980s and 1990s this evolutionary theory of aging had received firm empirical support, but little was known about the mechanisms of aging. Around the same time biologists began to apply the tools of molecular genetics to aging and successfully identified mutations that affect longevity. Today, the molecular genetics of aging is a burgeoning field, but progress in evolutionary genetics of aging has largely stalled. Here we argue that some of the most exciting and unresolved questions about aging require an integration of molecular and evolutionary approaches. Is aging a universal process? Why do species age at different rates? Are the mechanisms of aging conserved or lineage-specific? Are longevity genes identified in the laboratory under selection in natural populations? What is the genetic basis of plasticity in aging in response to environmental cues and is this plasticity adaptive? What are the mechanisms underlying trade-offs between early fitness traits and life span? To answer these questions evolutionary biologists must adopt the tools of molecular biology, while molecular biologists must put their experiments into an evolutionary framework. The time is ripe for a synthesis of molecular biogerontology and the evolutionary biology of aging.

Integrated optics to improve resolution on multiple configuration

NASA Astrophysics Data System (ADS)

Liu, Hua; Ding, Quanxin; Guo, Chunjie; Zhou, Liwei

2015-04-01

Inspired to in order to reveal the structure to improve imaging resolution, further technical requirement is proposed in some areas of the function and influence on the development of multiple configuration. To breakthrough diffraction limit, smart structures are recommended as the most efficient and economical method, while by used to improve the system performance, especially on signal to noise ratio and resolution. Integrated optics were considered in the selection, with which typical multiple configuration, by use the method of simulation experiment. Methodology can change traditional design concept and to develop the application space. Our calculations using multiple matrix transfer method, also the correlative algorithm and full calculations, show the expected beam shaping through system and, in particular, the experimental results will support our argument, which will be reported in the presentation.

Integrating Evolutionary and Molecular Genetics of Aging

PubMed Central

Flatt, Thomas; Schmidt, Paul S.

2010-01-01

Aging or senescence is an age-dependent decline in physiological function, demographically manifest as decreased survival and fecundity with increasing age. Since aging is disadvantageous it should not evolve by natural selection. So why do organisms age and die? In the 1940’s and 1950’s evolutionary geneticists resolved this paradox by positing that aging evolves because selection is inefficient at maintaining function late in life. By the 1980’s and 1990’s this evolutionary theory of aging had received firm empirical support, but little was known about the mechanisms of aging. Around the same time biologists began to apply the tools of molecular genetics to aging and successfully identified mutations that affect longevity. Today, the molecular genetics of aging is a burgeoning field, but progress in evolutionary genetics of aging has largely stalled. Here we argue that some of the most exciting and unresolved questions about aging require an integration of molecular and evolutionary approaches. Is aging a universal process? Why do species age at different rates? Are the mechanisms of aging conserved or lineage-specific? Are longevity genes identified in the laboratory under selection in natural populations? What is the genetic basis of plasticity in aging in response to environmental cues and is this plasticity adaptive? What are the mechanisms underlying trade-offs between early fitness traits and life span? To answer these questions evolutionary biologists must adopt the tools of molecular biology, while molecular biologists must put their experiments into an evolutionary framework. The time is ripe for a synthesis of molecular biogerontology and the evolutionary biology of aging. PMID:19619612

HMC algorithm with multiple time scale integration and mass preconditioning

NASA Astrophysics Data System (ADS)

Urbach, C.; Jansen, K.; Shindler, A.; Wenger, U.

2006-01-01

We present a variant of the HMC algorithm with mass preconditioning (Hasenbusch acceleration) and multiple time scale integration. We have tested this variant for standard Wilson fermions at β=5.6 and at pion masses ranging from 380 to 680 MeV. We show that in this situation its performance is comparable to the recently proposed HMC variant with domain decomposition as preconditioner. We give an update of the "Berlin Wall" figure, comparing the performance of our variant of the HMC algorithm to other published performance data. Advantages of the HMC algorithm with mass preconditioning and multiple time scale integration are that it is straightforward to implement and can be used in combination with a wide variety of lattice Dirac operators.

Quantum molecular dynamics and multistep-direct analyses of multiple preequilibrium emission

NASA Astrophysics Data System (ADS)

Chadwick, M. B.; Chiba, S.; Niita, K.; Maruyama, T.; Iwamoto, A.

1995-11-01

We study multiple preequilibrium emission in nucleon induced reactions at intermediate energies, and compare quantum molecular dynamics (QMD) calculations with multistep-direct Feshbach-Kerman-Koonin results [M. B. Chadwick, P. G. Young, D. C. George, and Y. Watanabe, Phys. Rev. C 50, 996 (1994)]. When the theoretical expressions of this reference are reformulated so that the definitions of primary and multiple emission correspond to those used in QMD, the two theories yield similar results for primary and multiple preequilibrium emission. We use QMD as a tool to determine the multiplicities of fast preequilibrium nucleons as a function of incident energy. For fast particle cross sections to exceed 5% of the inclusive preequilibrium emission cross sections we find that two particles should be included in reactions above 50 MeV, three above about 180 MeV, and four are only needed when the incident energy exceeds about 400 MeV.

Integrating molecular diagnostics into histopathology training: the Belfast model.

PubMed

Flynn, C; James, J; Maxwell, P; McQuaid, S; Ervine, A; Catherwood, M; Loughrey, M B; McGibben, D; Somerville, J; McManus, D T; Gray, M; Herron, B; Salto-Tellez, M

2014-07-01

Molecular medicine is transforming modern clinical practice, from diagnostics to therapeutics. Discoveries in research are being incorporated into the clinical setting with increasing rapidity. This transformation is also deeply changing the way we practise pathology. The great advances in cell and molecular biology which have accelerated our understanding of the pathogenesis of solid tumours have been embraced with variable degrees of enthusiasm by diverse medical professional specialties. While histopathologists have not been prompt to adopt molecular diagnostics to date, the need to incorporate molecular pathology into the training of future histopathologists is imperative. Our goal is to create, within an existing 5-year histopathology training curriculum, the structure for formal substantial teaching of molecular diagnostics. This specialist training has two main goals: (1) to equip future practising histopathologists with basic knowledge of molecular diagnostics and (2) to create the option for those interested in a subspecialty experience in tissue molecular diagnostics to pursue this training. It is our belief that this training will help to maintain in future the role of the pathologist at the centre of patient care as the integrator of clinical, morphological and molecular information. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Content Integration across Multiple Documents Reduces Memory for Sources

ERIC Educational Resources Information Center

Braasch, Jason L. G.; McCabe, Rebecca M.; Daniel, Frances

2016-01-01

The current experiments systematically examined semantic content integration as a mechanism for explaining source inattention and forgetting when reading-to-remember multiple texts. For all 3 experiments, degree of semantic overlap was manipulated amongst messages provided by various information sources. In Experiment 1, readers' source…

Integrated genomic and molecular characterization of cervical cancer.

PubMed

2017-03-16

Cervical cancer remains one of the leading causes of cancer-related deaths worldwide. Here we report the extensive molecular characterization of 228 primary cervical cancers, one of the largest comprehensive genomic studies of cervical cancer to date. We observed notable APOBEC mutagenesis patterns and identified SHKBP1, ERBB3, CASP8, HLA-A and TGFBR2 as novel significantly mutated genes in cervical cancer. We also discovered amplifications in immune targets CD274 (also known as PD-L1) and PDCD1LG2 (also known as PD-L2), and the BCAR4 long non-coding RNA, which has been associated with response to lapatinib. Integration of human papilloma virus (HPV) was observed in all HPV18-related samples and 76% of HPV16-related samples, and was associated with structural aberrations and increased target-gene expression. We identified a unique set of endometrial-like cervical cancers, comprised predominantly of HPV-negative tumours with relatively high frequencies of KRAS, ARID1A and PTEN mutations. Integrative clustering of 178 samples identified keratin-low squamous, keratin-high squamous and adenocarcinoma-rich subgroups. These molecular analyses reveal new potential therapeutic targets for cervical cancers.

Simplifying Differential Equations for Multiscale Feynman Integrals beyond Multiple Polylogarithms.

PubMed

Adams, Luise; Chaubey, Ekta; Weinzierl, Stefan

2017-04-07

In this Letter we exploit factorization properties of Picard-Fuchs operators to decouple differential equations for multiscale Feynman integrals. The algorithm reduces the differential equations to blocks of the size of the order of the irreducible factors of the Picard-Fuchs operator. As a side product, our method can be used to easily convert the differential equations for Feynman integrals which evaluate to multiple polylogarithms to an ϵ form.

On the method of Ermakov and Zolotukhin for multiple integration

NASA Technical Reports Server (NTRS)

Cranley, R.; Patterson, T. N. L.

1971-01-01

By introducing the idea of pseudo-implementation, a practical assessment of the method for multiple integration is made. The performance of the method is found to be unimpressive in comparison with a recent regression method.

Integrated presentation of ecological risk from multiple stressors

NASA Astrophysics Data System (ADS)

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-10-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Integrated presentation of ecological risk from multiple stressors.

PubMed

Goussen, Benoit; Price, Oliver R; Rendal, Cecilie; Ashauer, Roman

2016-10-26

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Integrated presentation of ecological risk from multiple stressors

PubMed Central

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-01-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic. PMID:27782171

NEXT Propellant Management System Integration With Multiple Ion Thrusters

NASA Technical Reports Server (NTRS)

Sovey, James S.; Soulas, George C.; Herman, Daniel A.

2011-01-01

As a critical part of the NEXT test validation process, a multiple-string integration test was performed on the NEXT propellant management system and ion thrusters. The objectives of this test were to verify that the PMS is capable of providing stable flow control to multiple thrusters operating over the NEXT system throttling range and to demonstrate to potential users that the NEXT PMS is ready for transition to flight. A test plan was developed for the sub-system integration test for verification of PMS and thruster system performance and functionality requirements. Propellant management system calibrations were checked during the single and multi-thruster testing. The low pressure assembly total flow rates to the thruster(s) were within 1.4 percent of the calibrated support equipment flow rates. The inlet pressures to the main, cathode, and neutralizer ports of Thruster PM1R were measured as the PMS operated in 1-thruster, 2-thruster, and 3-thruster configurations. It was found that the inlet pressures to Thruster PM1R for 2-thruster and 3-thruster operation as well as single thruster operation with the PMS compare very favorably indicating that flow rates to Thruster PM1R were similar in all cases. Characterizations of discharge losses, accelerator grid current, and neutralizer performance were performed as more operating thrusters were added to the PMS. There were no variations in these parameters as thrusters were throttled and single and multiple thruster operations were conducted. The propellant management system power consumption was at a fixed voltage to the DCIU and a fixed thermal throttle temperature of 75 C. The total power consumed by the PMS was 10.0, 17.9, and 25.2 W, respectively, for single, 2-thruster, and 3-thruster operation with the PMS. These sub-system integration tests of the PMS, the DCIU Simulator, and multiple thrusters addressed, in part, the NEXT PMS and propulsion system performance and functionality requirements.

Can the meaning of multiple words be integrated unconsciously?

PubMed

van Gaal, Simon; Naccache, Lionel; Meuwese, Julia D I; van Loon, Anouk M; Leighton, Alexandra H; Cohen, Laurent; Dehaene, Stanislas

2014-05-05

What are the limits of unconscious language processing? Can language circuits process simple grammatical constructions unconsciously and integrate the meaning of several unseen words? Using behavioural priming and electroencephalography (EEG), we studied a specific rule-based linguistic operation traditionally thought to require conscious cognitive control: the negation of valence. In a masked priming paradigm, two masked words were successively (Experiment 1) or simultaneously presented (Experiment 2), a modifier ('not'/'very') and an adjective (e.g. 'good'/'bad'), followed by a visible target noun (e.g. 'peace'/'murder'). Subjects indicated whether the target noun had a positive or negative valence. The combination of these three words could either be contextually consistent (e.g. 'very bad - murder') or inconsistent (e.g. 'not bad - murder'). EEG recordings revealed that grammatical negations could unfold partly unconsciously, as reflected in similar occipito-parietal N400 effects for conscious and unconscious three-word sequences forming inconsistent combinations. However, only conscious word sequences elicited P600 effects, later in time. Overall, these results suggest that multiple unconscious words can be rapidly integrated and that an unconscious negation can automatically 'flip the sign' of an unconscious adjective. These findings not only extend the limits of subliminal combinatorial language processes, but also highlight how consciousness modulates the grammatical integration of multiple words.

Multiple Roles of Integrin-Linked Kinase in Epidermal Development, Maturation and Pigmentation Revealed by Molecular Profiling

PubMed Central

Judah, David; Rudkouskaya, Alena; Wilson, Ryan; Carter, David E.; Dagnino, Lina

2012-01-01

Integrin-linked kinase (ILK) is an important scaffold protein that mediates a variety of cellular responses to integrin stimulation by extracellular matrix proteins. Mice with epidermis-restricted inactivation of the Ilk gene exhibit pleiotropic phenotypic defects, including impaired hair follicle morphogenesis, reduced epidermal adhesion to the basement membrane, compromised epidermal integrity, as well as wasting and failure to thrive leading to perinatal death. To better understand the underlying molecular mechanisms that cause such a broad range of alterations, we investigated the impact of Ilk gene inactivation on the epidermis transcriptome. Microarray analysis showed over 700 differentially regulated mRNAs encoding proteins involved in multiple aspects of epidermal function, including keratinocyte differentiation and barrier formation, inflammation, regeneration after injury, and fundamental epidermal developmental pathways. These studies also revealed potential effects on genes not previously implicated in ILK functions, including those important for melanocyte and melanoblast development and function, regulation of cytoskeletal dynamics, and homeobox genes. This study shows that ILK is a critical regulator of multiple aspects of epidermal function and homeostasis, and reveals the previously unreported involvement of ILK not only in epidermal differentiation and barrier formation, but also in melanocyte genesis and function. PMID:22574216

Multiple roles of integrin-linked kinase in epidermal development, maturation and pigmentation revealed by molecular profiling.

PubMed

Judah, David; Rudkouskaya, Alena; Wilson, Ryan; Carter, David E; Dagnino, Lina

2012-01-01

Integrin-linked kinase (ILK) is an important scaffold protein that mediates a variety of cellular responses to integrin stimulation by extracellular matrix proteins. Mice with epidermis-restricted inactivation of the Ilk gene exhibit pleiotropic phenotypic defects, including impaired hair follicle morphogenesis, reduced epidermal adhesion to the basement membrane, compromised epidermal integrity, as well as wasting and failure to thrive leading to perinatal death. To better understand the underlying molecular mechanisms that cause such a broad range of alterations, we investigated the impact of Ilk gene inactivation on the epidermis transcriptome. Microarray analysis showed over 700 differentially regulated mRNAs encoding proteins involved in multiple aspects of epidermal function, including keratinocyte differentiation and barrier formation, inflammation, regeneration after injury, and fundamental epidermal developmental pathways. These studies also revealed potential effects on genes not previously implicated in ILK functions, including those important for melanocyte and melanoblast development and function, regulation of cytoskeletal dynamics, and homeobox genes. This study shows that ILK is a critical regulator of multiple aspects of epidermal function and homeostasis, and reveals the previously unreported involvement of ILK not only in epidermal differentiation and barrier formation, but also in melanocyte genesis and function.

Lambda Red recombinase-mediated integration of the high molecular weight DNA into the Escherichia coli chromosome.

PubMed

Juhas, Mario; Ajioka, James W

2016-10-05

Escherichia coli K-12 is a frequently used host for a number of synthetic biology and biotechnology applications and chassis for the development of the minimal cell factories. Novel approaches for integrating high molecular weight DNA into the E. coli chromosome would therefore greatly facilitate engineering efforts in this bacterium. We developed a reliable and flexible lambda Red recombinase-based system, which utilizes overlapping DNA fragments for integration of the high molecular weight DNA into the E. coli chromosome. Our chromosomal integration strategy can be used to integrate high molecular weight DNA of variable length into any non-essential locus in the E. coli chromosome. Using this approach we integrated 15 kb DNA encoding sucrose catabolism and lactose metabolism and transport operons into the fliK locus of the flagellar region 3b in the E. coli K12 MG1655 chromosome. Furthermore, with this system we integrated 50 kb of Bacillus subtilis 168 DNA into two target sites in the E. coli K12 MG1655 chromosome. The chromosomal integrations into the fliK locus occurred with high efficiency, inhibited motility, and did not have a negative effect on the growth of E. coli. In addition to the rational design of synthetic biology devices, our high molecular weight DNA chromosomal integration system will facilitate metabolic and genome-scale engineering of E. coli.

The roles of integration in molecular systems biology.

PubMed

O'Malley, Maureen A; Soyer, Orkun S

2012-03-01

A common way to think about scientific practice involves classifying it as hypothesis- or data-driven. We argue that although such distinctions might illuminate scientific practice very generally, they are not sufficient to understand the day-to-day dynamics of scientific activity and the development of programmes of research. One aspect of everyday scientific practice that is beginning to gain more attention is integration. This paper outlines what is meant by this term and how it has been discussed from scientific and philosophical points of view. We focus on methodological, data and explanatory integration, and show how they are connected. Then, using some examples from molecular systems biology, we will show how integration works in a range of inquiries to generate surprising insights and even new fields of research. From these examples we try to gain a broader perspective on integration in relation to the contexts of inquiry in which it is implemented. In today's environment of data-intensive large-scale science, integration has become both a practical and normative requirement with corresponding implications for meta-methodological accounts of scientific practice. We conclude with a discussion of why an understanding of integration and its dynamics is useful for philosophy of science and scientific practice in general. Copyright © 2011 Elsevier Ltd. All rights reserved.

Accelerated sampling by infinite swapping of path integral molecular dynamics with surface hopping

NASA Astrophysics Data System (ADS)

Lu, Jianfeng; Zhou, Zhennan

2018-02-01

To accelerate the thermal equilibrium sampling of multi-level quantum systems, the infinite swapping limit of a recently proposed multi-level ring polymer representation is investigated. In the infinite swapping limit, the ring polymer evolves according to an averaged Hamiltonian with respect to all possible surface index configurations of the ring polymer and thus connects the surface hopping approach to the mean-field path-integral molecular dynamics. A multiscale integrator for the infinite swapping limit is also proposed to enable efficient sampling based on the limiting dynamics. Numerical results demonstrate the huge improvement of sampling efficiency of the infinite swapping compared with the direct simulation of path-integral molecular dynamics with surface hopping.

A Pivotal Role of DELLAs in Regulating Multiple Hormone Signals.

PubMed

Davière, Jean-Michel; Achard, Patrick

2016-01-04

Plant phenotypic plasticity is controlled by diverse hormone pathways, which integrate and convey information from multiple developmental and environmental signals. Moreover, in plants many processes such as growth, development, and defense are regulated in similar ways by multiple hormones. Among them, gibberellins (GAs) are phytohormones with pleiotropic actions, regulating various growth processes throughout the plant life cycle. Previous work has revealed extensive interplay between GAs and other hormones, but the molecular mechanism became apparent only recently. Molecular and physiological studies have demonstrated that DELLA proteins, considered as master negative regulators of GA signaling, integrate multiple hormone signaling pathways through physical interactions with transcription factors or regulatory proteins from different families. In this review, we summarize the latest progress in GA signaling and its direct crosstalk with the main phytohormone signaling, emphasizing the multifaceted role of DELLA proteins with key components of major hormone signaling pathways. Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.

Vertical resonant tunneling transistors with molecular quantum dots for large-scale integration.

PubMed

Hayakawa, Ryoma; Chikyow, Toyohiro; Wakayama, Yutaka

2017-08-10

Quantum molecular devices have a potential for the construction of new data processing architectures that cannot be achieved using current complementary metal-oxide-semiconductor (CMOS) technology. The relevant basic quantum transport properties have been examined by specific methods such as scanning probe and break-junction techniques. However, these methodologies are not compatible with current CMOS applications, and the development of practical molecular devices remains a persistent challenge. Here, we demonstrate a new vertical resonant tunneling transistor for large-scale integration. The transistor channel is comprised of a MOS structure with C 60 molecules as quantum dots, and the structure behaves like a double tunnel junction. Notably, the transistors enabled the observation of stepwise drain currents, which originated from resonant tunneling via the discrete molecular orbitals. Applying side-gate voltages produced depletion layers in Si substrates, to achieve effective modulation of the drain currents and obvious peak shifts in the differential conductance curves. Our device configuration thus provides a promising means of integrating molecular functions into future CMOS applications.

Multiple loop conformations of peptides predicted by molecular dynamics simulations are compatible with nuclear magnetic resonance.

PubMed

Carstens, Heiko; Renner, Christian; Milbradt, Alexander G; Moroder, Luis; Tavan, Paul

2005-03-29

The affinity and selectivity of protein-protein interactions can be fine-tuned by varying the size, flexibility, and amino acid composition of involved surface loops. As a model for such surface loops, we study the conformational landscape of an octapeptide, whose flexibility is chemically steered by a covalent ring closure integrating an azobenzene dye into and by a disulfide bridge additionally constraining the peptide backbone. Because the covalently integrated azobenzene dyes can be switched by light between a bent cis state and an elongated trans state, six cyclic peptide models of strongly different flexibilities are obtained. The conformational states of these peptide models are sampled by NMR and by unconstrained molecular dynamics (MD) simulations. Prototypical conformations and the free-energy landscapes in the high-dimensional space spanned by the phi/psi angles at the peptide backbone are obtained by clustering techniques from the MD trajectories. Multiple open-loop conformations are shown to be predicted by MD particularly in the very flexible cases and are shown to comply with the NMR data despite the fact that such open-loop conformations are missing in the refined NMR structures.

Multiple-time-scale motion in molecularly linked nanoparticle arrays.

PubMed

George, Christopher; Szleifer, Igal; Ratner, Mark

2013-01-22

We explore the transport of electrons between electrodes that encase a two-dimensional array of metallic quantum dots linked by molecular bridges (such as α,ω alkaline dithiols). Because the molecules can move at finite temperatures, the entire transport structure comprising the quantum dots and the molecules is in dynamical motion while the charge is being transported. There are then several physical processes (physical excursions of molecules and quantum dots, electronic migration, ordinary vibrations), all of which influence electronic transport. Each can occur on a different time scale. It is therefore not appropriate to use standard approaches to this sort of electron transfer problem. Instead, we present a treatment in which three different theoretical approaches-kinetic Monte Carlo, classical molecular dynamics, and quantum transport-are all employed. In certain limits, some of the dynamical effects are unimportant. But in general, the transport seems to follow a sort of dynamic bond percolation picture, an approach originally introduced as formal models and later applied to polymer electrolytes. Different rate-determining steps occur in different limits. This approach offers a powerful scheme for dealing with multiple time scale transport problems, as will exist in many situations with several pathways through molecular arrays or even individual molecules that are dynamically disordered.

Integrative pathway knowledge bases as a tool for systems molecular medicine.

PubMed

Liang, Mingyu

2007-08-20

There exists a sense of urgency to begin to generate a cohesive assembly of biomedical knowledge as the pace of knowledge accumulation accelerates. The urgency is in part driven by the emergence of systems molecular medicine that emphasizes the combination of systems analysis and molecular dissection in the future of medical practice and research. A potentially powerful approach is to build integrative pathway knowledge bases that link organ systems function with molecules.

[Establishment and Management of Multiple Myeloma Specimen Bank Applied for Molecular Biological Researches].

PubMed

Li, Han-Qing; Mei, Jian-Gang; Cao, Hong-Qin; Shao, Liang-Jing; Zhai, Yong-Ping

2017-12-01

To establish a multiple myeloma specimen bank applied for molecular biological researches and to explore the methods of specimen collection, transportation, storage, quality control and the management of specimen bank. Bone marrow and blood samples were collected from multiple myeloma patients, plasma cell sorting were operated after the separation of mononuclear cells from bone marrow specimens. The plasma cells were divided into 2 parts, one was added with proper amount of TRIzol and then kept in -80 °C refrigerator for subsequent RNA extraction, the other was added with proper amount of calf serum cell frozen liquid and then kept in -80 °C refrigerator for subsequent cryopreservation of DNA extraction after numbered respectively. Serum and plasma were separated from peripheral blood, specimens of serum and plasma were then stored at -80 °C refrigerator after registration. Meantime, the myeloma specimen information management system was established, managed and maintained by specially-assigned persons and continuous modification and improvement in the process of use as to facilitate the rapid collection, management, query of the effective samples and clinical data. A total of 244 portions plasma cells, 564 portions of serum, and 1005 portions of plasma were collected, clinical characters were documented. A multiple myeloma specimen bank have been established initially, which can provide quality samples and related clinical information for molecular biological research on multiple myeloma.

A DICOM-based 2nd generation Molecular Imaging Data Grid implementing the IHE XDS-i integration profile.

PubMed

Lee, Jasper; Zhang, Jianguo; Park, Ryan; Dagliyan, Grant; Liu, Brent; Huang, H K

2012-07-01

A Molecular Imaging Data Grid (MIDG) was developed to address current informatics challenges in archival, sharing, search, and distribution of preclinical imaging studies between animal imaging facilities and investigator sites. This manuscript presents a 2nd generation MIDG replacing the Globus Toolkit with a new system architecture that implements the IHE XDS-i integration profile. Implementation and evaluation were conducted using a 3-site interdisciplinary test-bed at the University of Southern California. The 2nd generation MIDG design architecture replaces the initial design's Globus Toolkit with dedicated web services and XML-based messaging for dedicated management and delivery of multi-modality DICOM imaging datasets. The Cross-enterprise Document Sharing for Imaging (XDS-i) integration profile from the field of enterprise radiology informatics was adopted into the MIDG design because streamlined image registration, management, and distribution dataflow are likewise needed in preclinical imaging informatics systems as in enterprise PACS application. Implementation of the MIDG is demonstrated at the University of Southern California Molecular Imaging Center (MIC) and two other sites with specified hardware, software, and network bandwidth. Evaluation of the MIDG involves data upload, download, and fault-tolerance testing scenarios using multi-modality animal imaging datasets collected at the USC Molecular Imaging Center. The upload, download, and fault-tolerance tests of the MIDG were performed multiple times using 12 collected animal study datasets. Upload and download times demonstrated reproducibility and improved real-world performance. Fault-tolerance tests showed that automated failover between Grid Node Servers has minimal impact on normal download times. Building upon the 1st generation concepts and experiences, the 2nd generation MIDG system improves accessibility of disparate animal-model molecular imaging datasets to users outside a molecular

Drug Repositioning by Kernel-Based Integration of Molecular Structure, Molecular Activity, and Phenotype Data

PubMed Central

Wang, Yongcui; Chen, Shilong; Deng, Naiyang; Wang, Yong

2013-01-01

Computational inference of novel therapeutic values for existing drugs, i.e., drug repositioning, offers the great prospect for faster and low-risk drug development. Previous researches have indicated that chemical structures, target proteins, and side-effects could provide rich information in drug similarity assessment and further disease similarity. However, each single data source is important in its own way and data integration holds the great promise to reposition drug more accurately. Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases. Then we train a support vector machine (SVM) to computationally predict novel drug-disease interactions. PreDR is validated on a well-established drug-disease network with 1,933 interactions among 593 drugs and 313 diseases. By cross-validation, we find that chemical structure, drug target, and side-effects information are all predictive for drug-disease relationships. More experimentally observed drug-disease interactions can be revealed by integrating these three data sources. Comparison with existing methods demonstrates that PreDR is competitive both in accuracy and coverage. Follow-up database search and pathway analysis indicate that our new predictions are worthy of further experimental validation. Particularly several novel predictions are supported by clinical trials databases and this shows the significant prospects of PreDR in future drug treatment. In conclusion, our new method, PreDR, can serve as a useful tool in drug discovery to efficiently identify novel drug-disease interactions. In addition, our heterogeneous data integration framework can be applied to other problems. PMID:24244318

Path integral molecular dynamic simulation of flexible molecular systems in their ground state: Application to the water dimer

NASA Astrophysics Data System (ADS)

Schmidt, Matthew; Roy, Pierre-Nicholas

2018-03-01

We extend the Langevin equation Path Integral Ground State (LePIGS), a ground state quantum molecular dynamics method, to simulate flexible molecular systems and calculate both energetic and structural properties. We test the approach with the H2O and D2O monomers and dimers. We systematically optimize all simulation parameters and use a unity trial wavefunction. We report ground state energies, dissociation energies, and structural properties using three different water models, two of which are empirically based, q-TIP4P/F and q-SPC/Fw, and one which is ab initio, MB-pol. We demonstrate that our energies calculated from LePIGS can be merged seamlessly with low temperature path integral molecular dynamics calculations and note the similarities between the two methods. We also benchmark our energies against previous diffusion Monte Carlo calculations using the same potentials and compare to experimental results. We further demonstrate that accurate vibrational energies of the H2O and D2O monomer can be calculated from imaginary time correlation functions generated from the LePIGS simulations using solely the unity trial wavefunction.

Integral criteria for large-scale multiple fingerprint solutions

NASA Astrophysics Data System (ADS)

Ushmaev, Oleg S.; Novikov, Sergey O.

2004-08-01

We propose the definition and analysis of the optimal integral similarity score criterion for large scale multmodal civil ID systems. Firstly, the general properties of score distributions for genuine and impostor matches for different systems and input devices are investigated. The empirical statistics was taken from the real biometric tests. Then we carry out the analysis of simultaneous score distributions for a number of combined biometric tests and primary for ultiple fingerprint solutions. The explicit and approximate relations for optimal integral score, which provides the least value of the FRR while the FAR is predefined, have been obtained. The results of real multiple fingerprint test show good correspondence with the theoretical results in the wide range of the False Acceptance and the False Rejection Rates.

Method and system of integrating information from multiple sources

DOEpatents

Alford, Francine A [Livermore, CA; Brinkerhoff, David L [Antioch, CA

2006-08-15

A system and method of integrating information from multiple sources in a document centric application system. A plurality of application systems are connected through an object request broker to a central repository. The information may then be posted on a webpage. An example of an implementation of the method and system is an online procurement system.

Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations

PubMed Central

Zhou, Meng; Cheng, Liang; Yang, Haixiu; Wang, Jing; Sun, Jie; Wang, Zhenzhen

2016-01-01

MicroRNAs (miRNAs) play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene ontology data, experimentally verified miRNA-target relationships, disease phenotype information and known miRNA-disease connections. The performance of CHNmiRD was evaluated by experimentally verified miRNA-disease associations, which achieved an area under the ROC curve (AUC) of 0.834 for 5-fold cross-validation. In particular, CHNmiRD displayed excellent performance for diseases without any known related miRNAs. The results of case studies for three human diseases (glioblastoma, myocardial infarction and type 1 diabetes) showed that all of the top 10 ranked miRNAs having no known associations with these three diseases in existing miRNA-disease databases were directly or indirectly confirmed by our latest literature mining. All these results demonstrated the reliability and efficiency of CHNmiRD, and it is anticipated that CHNmiRD will serve as a powerful bioinformatics method for mining novel disease-related miRNAs and providing a new perspective into molecular mechanisms underlying human diseases at the post-transcriptional level. CHNmiRD is freely available at http://www.bio-bigdata.com/CHNmiRD. PMID:26849207

Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.

PubMed

Shi, Hongbo; Zhang, Guangde; Zhou, Meng; Cheng, Liang; Yang, Haixiu; Wang, Jing; Sun, Jie; Wang, Zhenzhen

2016-01-01

MicroRNAs (miRNAs) play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene ontology data, experimentally verified miRNA-target relationships, disease phenotype information and known miRNA-disease connections. The performance of CHNmiRD was evaluated by experimentally verified miRNA-disease associations, which achieved an area under the ROC curve (AUC) of 0.834 for 5-fold cross-validation. In particular, CHNmiRD displayed excellent performance for diseases without any known related miRNAs. The results of case studies for three human diseases (glioblastoma, myocardial infarction and type 1 diabetes) showed that all of the top 10 ranked miRNAs having no known associations with these three diseases in existing miRNA-disease databases were directly or indirectly confirmed by our latest literature mining. All these results demonstrated the reliability and efficiency of CHNmiRD, and it is anticipated that CHNmiRD will serve as a powerful bioinformatics method for mining novel disease-related miRNAs and providing a new perspective into molecular mechanisms underlying human diseases at the post-transcriptional level. CHNmiRD is freely available at http://www.bio-bigdata.com/CHNmiRD.

Multiple core-hole formation by free-electron laser radiation in molecular nitrogen

NASA Astrophysics Data System (ADS)

Banks, H. I. B.; Little, D. A.; Emmanouilidou, A.

2018-05-01

We investigate the formation of multiple-core-hole states of molecular nitrogen interacting with a free-electron laser pulse. In previous work, we obtained bound and continuum molecular orbitals in the single-center expansion scheme and used these orbitals to calculate photo-ionization and auger decay rates. We extend our formulation to track the proportion of the population that accesses single-site versus two-site double-core-hole (TSDCH) states, before the formation of the final atomic ions. We investigate the pulse parameters that favor the formation of the single-site and TSDCH as well as triple-core-hole states for 525 and 1100 eV photons.

The Eyes Have It: A Problem-Based Learning Exercise in Molecular Evolution

ERIC Educational Resources Information Center

White, Harold B.

2007-01-01

Molecular evolution provides an interesting context in which to use problem-based learning because it integrates a variety of topics in biology, biochemistry, and molecular biology. This three-stage problem for advanced students deals with the structure, multiple functions, and properties of lactate dehydrogenase isozymes, and the related…

Chemistry integrated circuit: chemical system on a complementary metal oxide semiconductor integrated circuit.

PubMed

Nakazato, Kazuo

2014-03-28

By integrating chemical reactions on a large-scale integration (LSI) chip, new types of device can be created. For biomedical applications, monolithically integrated sensor arrays for potentiometric, amperometric and impedimetric sensing of biomolecules have been developed. The potentiometric sensor array detects pH and redox reaction as a statistical distribution of fluctuations in time and space. For the amperometric sensor array, a microelectrode structure for measuring multiple currents at high speed has been proposed. The impedimetric sensor array is designed to measure impedance up to 10 MHz. The multimodal sensor array will enable synthetic analysis and make it possible to standardize biosensor chips. Another approach is to create new functional devices by integrating molecular systems with LSI chips, for example image sensors that incorporate biological materials with a sensor array. The quantum yield of the photoelectric conversion of photosynthesis is 100%, which is extremely difficult to achieve by artificial means. In a recently developed process, a molecular wire is plugged directly into a biological photosynthetic system to efficiently conduct electrons to a gold electrode. A single photon can be detected at room temperature using such a system combined with a molecular single-electron transistor.

Integrated molecular portrait of non-small cell lung cancers

PubMed Central

2013-01-01

Background Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC. Methods Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC. Results At DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of ~800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944. Conclusions Integrated molecular characterization of AC and SCC helped identify clinically relevant markers

Fabrication of reproducible, integration-compatible hybrid molecular/si electronics.

PubMed

Yu, Xi; Lovrinčić, Robert; Kraynis, Olga; Man, Gabriel; Ely, Tal; Zohar, Arava; Toledano, Tal; Cahen, David; Vilan, Ayelet

2014-12-29

Reproducible molecular junctions can be integrated within standard CMOS technology. Metal-molecule-semiconductor junctions are fabricated by direct Si-C binding of hexadecane or methyl-styrene onto oxide-free H-Si(111) surfaces, with the lateral size of the junctions defined by an etched SiO2 well and with evaporated Pb as the top contact. The current density, J, is highly reproducible with a standard deviation in log(J) of 0.2 over a junction diameter change from 3 to 100 μm. Reproducibility over such a large range indicates that transport is truly across the molecules and does not result from artifacts like edge effects or defects in the molecular monolayer. Device fabrication is tested for two n-Si doping levels. With highly doped Si, transport is dominated by tunneling and reveals sharp conductance onsets at room temperature. Using the temperature dependence of current across medium-doped n-Si, the molecular tunneling barrier can be separated from the Si-Schottky one, which is a 0.47 eV, in agreement with the molecular-modified surface dipole and quite different from the bare Si-H junction. This indicates that Pb evaporation does not cause significant chemical changes to the molecules. The ability to manufacture reliable devices constitutes important progress toward possible future hybrid Si-based molecular electronics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Curriculum Integration in Arts Education: Connecting Multiple Art Forms through the Idea of "Space"

ERIC Educational Resources Information Center

Bautista, Alfredo; Tan, Liang See; Ponnusamy, Letchmi Devi; Yau, Xenia

2016-01-01

Arts integration research has focused on documenting how the teaching of specific art forms can be integrated with "core" academic subject matters (e.g. science, mathematics and literacy). However, the question of how the teaching of multiple art forms themselves can be integrated in schools remains to be explored by educational…

Empathetic, Critical Integrations of Multiple Perspectives: A Core Practice for Language Teacher Education?

ERIC Educational Resources Information Center

Daniel, Shannon M.

2015-01-01

In this self-study, the author reflects on her implementation of empathetic, critical integrations of multiple perspectives (ECI), which she designed to afford preservice teachers the opportunity to discuss and collectively reflect upon the oft-diverging multiple perspectives, values, and practices they experience during their practicum (Daniel,…

Shared mental models of integrated care: aligning multiple stakeholder perspectives.

PubMed

Evans, Jenna M; Baker, G Ross

2012-01-01

Health service organizations and professionals are under increasing pressure to work together to deliver integrated patient care. A common understanding of integration strategies may facilitate the delivery of integrated care across inter-organizational and inter-professional boundaries. This paper aims to build a framework for exploring and potentially aligning multiple stakeholder perspectives of systems integration. The authors draw from the literature on shared mental models, strategic management and change, framing, stakeholder management, and systems theory to develop a new construct, Mental Models of Integrated Care (MMIC), which consists of three types of mental models, i.e. integration-task, system-role, and integration-belief. The MMIC construct encompasses many of the known barriers and enablers to integrating care while also providing a comprehensive, theory-based framework of psychological factors that may influence inter-organizational and inter-professional relations. While the existing literature on integration focuses on optimizing structures and processes, the MMIC construct emphasizes the convergence and divergence of stakeholders' knowledge and beliefs, and how these underlying cognitions influence interactions (or lack thereof) across the continuum of care. MMIC may help to: explain what differentiates effective from ineffective integration initiatives; determine system readiness to integrate; diagnose integration problems; and develop interventions for enhancing integrative processes and ultimately the delivery of integrated care. Global interest and ongoing challenges in integrating care underline the need for research on the mental models that characterize the behaviors of actors within health systems; the proposed framework offers a starting point for applying a cognitive perspective to health systems integration.

A coupling of homology modeling with multiple molecular dynamics simulation for identifying representative conformation of GPCR structures: a case study on human bombesin receptor subtype-3.

PubMed

Nowroozi, Amin; Shahlaei, Mohsen

2017-02-01

In this study, a computational pipeline was therefore devised to overcome homology modeling (HM) bottlenecks. The coupling of HM with molecular dynamics (MD) simulation is useful in that it tackles the sampling deficiency of dynamics simulations by providing good-quality initial guesses for the native structure. Indeed, HM also relaxes the severe requirement of force fields to explore the huge conformational space of protein structures. In this study, the interaction between the human bombesin receptor subtype-3 and MK-5046 was investigated integrating HM, molecular docking, and MD simulations. To improve conformational sampling in typical MD simulations of GPCRs, as in other biomolecules, multiple trajectories with different initial conditions can be employed rather than a single long trajectory. Multiple MD simulations of human bombesin receptor subtype-3 with different initial atomic velocities are applied to sample conformations in the vicinity of the structure generated by HM. The backbone atom conformational space distribution of replicates is analyzed employing principal components analysis. As a result, the averages of structural and dynamic properties over the twenty-one trajectories differ significantly from those obtained from individual trajectories.

Analysis of multiple scattering contributions in electron-impact ionization of molecular hydrogen

NASA Astrophysics Data System (ADS)

Ren, Xueguang; Hossen, Khokon; Wang, Enliang; Pindzola, M. S.; Dorn, Alexander; Colgan, James

2017-10-01

We report a combined experimental and theoretical study on the low-energy (E 0 = 31.5 eV) electron-impact ionization of molecular hydrogen (H2). Triple differential cross sections are measured for a range of fixed emission angles of one outgoing electron between {θ }1=-70^\\circ and -130° covering the full 4π solid angle of the second electron. The energy sharing of the outgoing electrons varies from symmetric ({E}1={E}2=8 eV) to highly asymmetric (E 1 = 1 eV and E 2 = 15 eV). In addition to the binary and recoil lobes, a structure is observed perpendicular to the incoming beam direction which is due to multiple scattering of the projectile inside the molecular potential. The absolutely normalized experimental cross sections are compared with results from the time-dependent close-coupling (TDCC) calculations. Molecular alignment dependent TDCC results demonstrate that these structures are only present if the molecule axis is lying in the scattering plane.

Efficient algorithms for fast integration on large data sets from multiple sources.

PubMed

Mi, Tian; Rajasekaran, Sanguthevar; Aseltine, Robert

2012-06-28

Recent large scale deployments of health information technology have created opportunities for the integration of patient medical records with disparate public health, human service, and educational databases to provide comprehensive information related to health and development. Data integration techniques, which identify records belonging to the same individual that reside in multiple data sets, are essential to these efforts. Several algorithms have been proposed in the literatures that are adept in integrating records from two different datasets. Our algorithms are aimed at integrating multiple (in particular more than two) datasets efficiently. Hierarchical clustering based solutions are used to integrate multiple (in particular more than two) datasets. Edit distance is used as the basic distance calculation, while distance calculation of common input errors is also studied. Several techniques have been applied to improve the algorithms in terms of both time and space: 1) Partial Construction of the Dendrogram (PCD) that ignores the level above the threshold; 2) Ignoring the Dendrogram Structure (IDS); 3) Faster Computation of the Edit Distance (FCED) that predicts the distance with the threshold by upper bounds on edit distance; and 4) A pre-processing blocking phase that limits dynamic computation within each block. We have experimentally validated our algorithms on large simulated as well as real data. Accuracy and completeness are defined stringently to show the performance of our algorithms. In addition, we employ a four-category analysis. Comparison with FEBRL shows the robustness of our approach. In the experiments we conducted, the accuracy we observed exceeded 90% for the simulated data in most cases. 97.7% and 98.1% accuracy were achieved for the constant and proportional threshold, respectively, in a real dataset of 1,083,878 records.

Equilibrium fractionation of H and O isotopes in water from path integral molecular dynamics

NASA Astrophysics Data System (ADS)

Pinilla, Carlos; Blanchard, Marc; Balan, Etienne; Ferlat, Guillaume; Vuilleumier, Rodolphe; Mauri, Francesco

2014-06-01

The equilibrium fractionation factor between two phases is of importance for the understanding of many planetary and environmental processes. Although thermodynamic equilibrium can be achieved between minerals at high temperature, many natural processes involve reactions between liquids or aqueous solutions and solids. For crystals, the fractionation factor α can be theoretically determined using a statistical thermodynamic approach based on the vibrational properties of the phases. These calculations are mostly performed in the harmonic approximation, using empirical or ab-initio force fields. In the case of aperiodic and dynamic systems such as liquids or solutions, similar calculations can be done using finite-size molecular clusters or snapshots obtained from molecular dynamics (MD) runs. It is however difficult to assess the effect of these approximate models on the isotopic fractionation properties. In this work we present a systematic study of the calculation of the D/H and 18O/16O equilibrium fractionation factors in water for the liquid/vapour and ice/vapour phases using several levels of theory within the simulations. Namely, we use a thermodynamic integration approach based on Path Integral MD calculations (PIMD) and an empirical potential model of water. Compared with standard MD, PIMD takes into account quantum effects in the thermodynamic modeling of systems and the exact fractionation factor for a given potential can be obtained. We compare these exact results with those of modeling strategies usually used, which involve the mapping of the quantum system on its harmonic counterpart. The results show the importance of including configurational disorder for the estimation of isotope fractionation in liquid phases. In addition, the convergence of the fractionation factor as a function of parameters such as the size of the simulated system and multiple isotope substitution is analyzed, showing that isotope fractionation is essentially a local effect in

Quadrature rules with multiple nodes for evaluating integrals with strong singularities

NASA Astrophysics Data System (ADS)

Milovanovic, Gradimir V.; Spalevic, Miodrag M.

2006-05-01

We present a method based on the Chakalov-Popoviciu quadrature formula of Lobatto type, a rather general case of quadrature with multiple nodes, for approximating integrals defined by Cauchy principal values or by Hadamard finite parts. As a starting point we use the results obtained by L. Gori and E. Santi (cf. On the evaluation of Hilbert transforms by means of a particular class of Turan quadrature rules, Numer. Algorithms 10 (1995), 27-39; Quadrature rules based on s-orthogonal polynomials for evaluating integrals with strong singularities, Oberwolfach Proceedings: Applications and Computation of Orthogonal Polynomials, ISNM 131, Birkhauser, Basel, 1999, pp. 109-119). We generalize their results by using some of our numerical procedures for stable calculation of the quadrature formula with multiple nodes of Gaussian type and proposed methods for estimating the remainder term in such type of quadrature formulae. Numerical examples, illustrations and comparisons are also shown.

Molecular Profiling of Glatiramer Acetate Early Treatment Effects in Multiple Sclerosis

PubMed Central

Achiron, Anat; Feldman, Anna; Gurevich, Michael

2009-01-01

Background: Glatiramer acetate (GA, Copaxone®) has beneficial effects on the clinical course of relapsing-remitting multiple sclerosis (RRMS). However, the exact molecular mechanisms of GA effects are only partially understood. Objective: To characterized GA molecular effects in RRMS patients within 3 months of treatment by microarray profiling of peripheral blood mononuclear cells (PBMC). Methods: Gene-expression profiles were determined in RRMS patients before and at 3 months after initiation of GA treatment using Affimetrix (U133A-2) microarrays containing 14,500 well-characterized human genes. Most informative genes (MIGs) of GA-induced biological convergent pathways operating in RRMS were constructed using gene functional annotation, enrichment analysis and pathway reconstruction bioinformatic softwares. Verification at the mRNA and protein level was performed by qRT-PCR and FACS. Results: GA induced a specific gene expression molecular signature that included altered expression of 480 genes within 3 months of treatment; 262 genes were up-regulated, and 218 genes were down-regulated. The main convergent mechanisms of GA effects were related to antigen-activated apoptosis, inflammation, adhesion, and MHC class-I antigen presentation. Conclusions: Our findings demonstrate that GA treatment induces alternations of immunomodulatory gene expression patterns that are important for suppression of disease activity already at three months of treatment and can be used as molecular markers of GA activity. PMID:19893201

Numerical solution of boundary-integral equations for molecular electrostatics.

PubMed

Bardhan, Jaydeep P

2009-03-07

Numerous molecular processes, such as ion permeation through channel proteins, are governed by relatively small changes in energetics. As a result, theoretical investigations of these processes require accurate numerical methods. In the present paper, we evaluate the accuracy of two approaches to simulating boundary-integral equations for continuum models of the electrostatics of solvation. The analysis emphasizes boundary-element method simulations of the integral-equation formulation known as the apparent-surface-charge (ASC) method or polarizable-continuum model (PCM). In many numerical implementations of the ASC/PCM model, one forces the integral equation to be satisfied exactly at a set of discrete points on the boundary. We demonstrate in this paper that this approach to discretization, known as point collocation, is significantly less accurate than an alternative approach known as qualocation. Furthermore, the qualocation method offers this improvement in accuracy without increasing simulation time. Numerical examples demonstrate that electrostatic part of the solvation free energy, when calculated using the collocation and qualocation methods, can differ significantly; for a polypeptide, the answers can differ by as much as 10 kcal/mol (approximately 4% of the total electrostatic contribution to solvation). The applicability of the qualocation discretization to other integral-equation formulations is also discussed, and two equivalences between integral-equation methods are derived.

From hatching to dispatching: the multiple cellular roles of the Hsp70 molecular chaperone machinery.

PubMed

Meimaridou, Eirini; Gooljar, Sakina B; Chapple, J Paul

2009-01-01

Molecular chaperones are best recognized for their roles in de novo protein folding and the cellular response to stress. However, many molecular chaperones, and in particular the Hsp70 chaperone machinery, have multiple diverse cellular functions. At the molecular level, chaperones are mediators of protein conformational change. To facilitate conformational change of client/substrate proteins, in manifold contexts, chaperone power must be closely regulated and harnessed to specific cellular locales--this is controlled by cochaperones. This review considers specialized functions of the Hsp70 chaperone machinery mediated by its cochaperones. We focus on vesicular trafficking, protein degradation and a potential role in G protein-coupled receptor processing.

Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles.

PubMed

Farshidfar, Farshad; Zheng, Siyuan; Gingras, Marie-Claude; Newton, Yulia; Shih, Juliann; Robertson, A Gordon; Hinoue, Toshinori; Hoadley, Katherine A; Gibb, Ewan A; Roszik, Jason; Covington, Kyle R; Wu, Chia-Chin; Shinbrot, Eve; Stransky, Nicolas; Hegde, Apurva; Yang, Ju Dong; Reznik, Ed; Sadeghi, Sara; Pedamallu, Chandra Sekhar; Ojesina, Akinyemi I; Hess, Julian M; Auman, J Todd; Rhie, Suhn K; Bowlby, Reanne; Borad, Mitesh J; Zhu, Andrew X; Stuart, Josh M; Sander, Chris; Akbani, Rehan; Cherniack, Andrew D; Deshpande, Vikram; Mounajjed, Taofic; Foo, Wai Chin; Torbenson, Michael S; Kleiner, David E; Laird, Peter W; Wheeler, David A; McRee, Autumn J; Bathe, Oliver F; Andersen, Jesper B; Bardeesy, Nabeel; Roberts, Lewis R; Kwong, Lawrence N

2017-03-14

Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahepatic CCA cases and propose a molecular classification scheme. We identified an IDH mutant-enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Multiple positive solutions for a class of integral inclusions

NASA Astrophysics Data System (ADS)

Hong, Shihuang

2008-04-01

This paper deals with sufficient conditions for the existence of at least two positive solutions for a class of integral inclusions arising in the traffic theory. To show our main results, we apply a norm-type expansion and compression fixed point theorem for multivalued map due to Agarwal and O'Regan [A note on the existence of multiple fixed points for multivalued maps with applications, J. Differential Equation 160 (2000) 389-403].

Respiromics - An integrative analysis linking mitochondrial bioenergetics to molecular signatures.

PubMed

Walheim, Ellen; Wiśniewski, Jacek R; Jastroch, Martin

2018-03-01

Energy metabolism is challenged upon nutrient stress, eventually leading to a variety of metabolic diseases that represent a major global health burden. Here, we combine quantitative mitochondrial respirometry (Seahorse technology) and proteomics (LC-MS/MS-based total protein approach) to understand how molecular changes translate to changes in mitochondrial energy transduction during diet-induced obesity (DIO) in the liver. The integrative analysis reveals that significantly increased palmitoyl-carnitine respiration is supported by an array of proteins enriching lipid metabolism pathways. Upstream of the respiratory chain, the increased capacity for ATP synthesis during DIO associates strongest to mitochondrial uptake of pyruvate, which is routed towards carboxylation. At the respiratory chain, robust increases of complex I are uncovered by cumulative analysis of single subunit concentrations. Specifically, nuclear-encoded accessory subunits, but not mitochondrial-encoded or core units, appear to be permissive for enhanced lipid oxidation. Our integrative analysis, that we dubbed "respiromics", represents an effective tool to link molecular changes to functional mechanisms in liver energy metabolism, and, more generally, can be applied for mitochondrial analysis in a variety of metabolic and mitochondrial disease models. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms.

PubMed

Kobayashi, Chigusa; Jung, Jaewoon; Matsunaga, Yasuhiro; Mori, Takaharu; Ando, Tadashi; Tamura, Koichi; Kamiya, Motoshi; Sugita, Yuji

2017-09-30

GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

XML-based approaches for the integration of heterogeneous bio-molecular data.

PubMed

Mesiti, Marco; Jiménez-Ruiz, Ernesto; Sanz, Ismael; Berlanga-Llavori, Rafael; Perlasca, Paolo; Valentini, Giorgio; Manset, David

2009-10-15

The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing. In this paper we survey the most interesting and novel approaches for the representation, integration and management of different kinds of biological data by exploiting XML and the related recommendations and approaches. Moreover, we present new and interesting cutting edge approaches for the appropriate management of heterogeneous biological data represented through XML. XML has succeeded in the integration of heterogeneous biomolecular information, and has established itself as the syntactic glue for biological data sources. Nevertheless, a large variety of XML-based data formats have been proposed, thus resulting in a difficult effective integration of bioinformatics data schemes. The adoption of a few semantic-rich standard formats is urgent to achieve a seamless integration of the current biological resources.

77 FR 74027 - Certain Integrated Circuit Packages Provided with Multiple Heat-Conducting Paths and Products...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-12

... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-851] Certain Integrated Circuit Packages Provided with Multiple Heat- Conducting Paths and Products Containing Same; Commission Determination Not To... provided with multiple heat-conducting paths and products containing same by reason of infringement of...

The Effect of Sensory Integration Treatment on Children with Multiple Disabilities.

ERIC Educational Resources Information Center

Din, Feng S.; Lodato, Donna M.

Six children with multiple disabilities (ages 5 to 8) participated in this evaluation of the effect of sensory integration treatment on sensorimotor function and academic learning. The children had cognitive abilities ranging from sub-average to significantly sub-average, three were non-ambulatory, one had severe behavioral problems, and each…

A retrospective likelihood approach for efficient integration of multiple omics factors in case-control association studies.

PubMed

Balliu, Brunilda; Tsonaka, Roula; Boehringer, Stefan; Houwing-Duistermaat, Jeanine

2015-03-01

Integrative omics, the joint analysis of outcome and multiple types of omics data, such as genomics, epigenomics, and transcriptomics data, constitute a promising approach for powerful and biologically relevant association studies. These studies often employ a case-control design, and often include nonomics covariates, such as age and gender, that may modify the underlying omics risk factors. An open question is how to best integrate multiple omics and nonomics information to maximize statistical power in case-control studies that ascertain individuals based on the phenotype. Recent work on integrative omics have used prospective approaches, modeling case-control status conditional on omics, and nonomics risk factors. Compared to univariate approaches, jointly analyzing multiple risk factors with a prospective approach increases power in nonascertained cohorts. However, these prospective approaches often lose power in case-control studies. In this article, we propose a novel statistical method for integrating multiple omics and nonomics factors in case-control association studies. Our method is based on a retrospective likelihood function that models the joint distribution of omics and nonomics factors conditional on case-control status. The new method provides accurate control of Type I error rate and has increased efficiency over prospective approaches in both simulated and real data. © 2015 Wiley Periodicals, Inc.

Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions.

PubMed

Viana, Joana; Hannon, Eilis; Dempster, Emma; Pidsley, Ruth; Macdonald, Ruby; Knox, Olivia; Spiers, Helen; Troakes, Claire; Al-Saraj, Safa; Turecki, Gustavo; Schalkwyk, Leonard C; Mill, Jonathan

2017-01-01

Genetic association studies provide evidence for a substantial polygenic component to schizophrenia, although the neurobiological mechanisms underlying the disorder remain largely undefined. Building on recent studies supporting a role for developmentally regulated epigenetic variation in the molecular aetiology of schizophrenia, this study aimed to identify epigenetic variation associated with both a diagnosis of schizophrenia and elevated polygenic risk burden for the disease across multiple brain regions. Genome-wide DNA methylation was quantified in 262 post-mortem brain samples, representing tissue from four brain regions (prefrontal cortex, striatum, hippocampus and cerebellum) from 41 schizophrenia patients and 47 controls. We identified multiple disease-associated and polygenic risk score-associated differentially methylated positions and regions, which are not enriched in genomic regions identified in genetic studies of schizophrenia and do not reflect direct genetic effects on DNA methylation. Our study represents the first analysis of epigenetic variation associated with schizophrenia across multiple brain regions and highlights the utility of polygenic risk scores for identifying molecular pathways associated with aetiological variation in complex disease. © The Author 2016. Published by Oxford University Press.

Integrated Molecular Characterization of Testicular Germ Cell Tumors.

PubMed

Shen, Hui; Shih, Juliann; Hollern, Daniel P; Wang, Linghua; Bowlby, Reanne; Tickoo, Satish K; Thorsson, Vésteinn; Mungall, Andrew J; Newton, Yulia; Hegde, Apurva M; Armenia, Joshua; Sánchez-Vega, Francisco; Pluta, John; Pyle, Louise C; Mehra, Rohit; Reuter, Victor E; Godoy, Guilherme; Jones, Jeffrey; Shelley, Carl S; Feldman, Darren R; Vidal, Daniel O; Lessel, Davor; Kulis, Tomislav; Cárcano, Flavio M; Leraas, Kristen M; Lichtenberg, Tara M; Brooks, Denise; Cherniack, Andrew D; Cho, Juok; Heiman, David I; Kasaian, Katayoon; Liu, Minwei; Noble, Michael S; Xi, Liu; Zhang, Hailei; Zhou, Wanding; ZenKlusen, Jean C; Hutter, Carolyn M; Felau, Ina; Zhang, Jiashan; Schultz, Nikolaus; Getz, Gad; Meyerson, Matthew; Stuart, Joshua M; Akbani, Rehan; Wheeler, David A; Laird, Peter W; Nathanson, Katherine L; Cortessis, Victoria K; Hoadley, Katherine A

2018-06-12

We studied 137 primary testicular germ cell tumors (TGCTs) using high-dimensional assays of genomic, epigenomic, transcriptomic, and proteomic features. These tumors exhibited high aneuploidy and a paucity of somatic mutations. Somatic mutation of only three genes achieved significance-KIT, KRAS, and NRAS-exclusively in samples with seminoma components. Integrated analyses identified distinct molecular patterns that characterized the major recognized histologic subtypes of TGCT: seminoma, embryonal carcinoma, yolk sac tumor, and teratoma. Striking differences in global DNA methylation and microRNA expression between histology subtypes highlight a likely role of epigenomic processes in determining histologic fates in TGCTs. We also identified a subset of pure seminomas defined by KIT mutations, increased immune infiltration, globally demethylated DNA, and decreased KRAS copy number. We report potential biomarkers for risk stratification, such as miRNA specifically expressed in teratoma, and others with molecular diagnostic potential, such as CpH (CpA/CpC/CpT) methylation identifying embryonal carcinomas. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Integrity Verification for Multiple Data Copies in Cloud Storage Based on Spatiotemporal Chaos

NASA Astrophysics Data System (ADS)

Long, Min; Li, You; Peng, Fei

Aiming to strike for a balance between the security, efficiency and availability of the data verification in cloud storage, a novel integrity verification scheme based on spatiotemporal chaos is proposed for multiple data copies. Spatiotemporal chaos is implemented for node calculation of the binary tree, and the location of the data in the cloud is verified. Meanwhile, dynamic operation can be made to the data. Furthermore, blind information is used to prevent a third-party auditor (TPA) leakage of the users’ data privacy in a public auditing process. Performance analysis and discussion indicate that it is secure and efficient, and it supports dynamic operation and the integrity verification of multiple copies of data. It has a great potential to be implemented in cloud storage services.

Multiplicity and Self-Identity: Trauma and Integration in Shirley Mason's Art

ERIC Educational Resources Information Center

Thompson, Geoffrey

2011-01-01

This viewpoint appeared in its original form as the catalogue essay that accompanied the exhibition "Multiplicity and Self-Identity: Trauma and Integration in Shirley Mason's Art," curated by the author for Gallery 2110, Sacramento, CA, and the 2010 Annual Conference of the American Art Therapy Association. The exhibition featured 17 artworks by…

Real object-based 360-degree integral-floating display using multiple depth camera

NASA Astrophysics Data System (ADS)

Erdenebat, Munkh-Uchral; Dashdavaa, Erkhembaatar; Kwon, Ki-Chul; Wu, Hui-Ying; Yoo, Kwan-Hee; Kim, Young-Seok; Kim, Nam

2015-03-01

A novel 360-degree integral-floating display based on the real object is proposed. The general procedure of the display system is similar with conventional 360-degree integral-floating displays. Unlike previously presented 360-degree displays, the proposed system displays the 3D image generated from the real object in 360-degree viewing zone. In order to display real object in 360-degree viewing zone, multiple depth camera have been utilized to acquire the depth information around the object. Then, the 3D point cloud representations of the real object are reconstructed according to the acquired depth information. By using a special point cloud registration method, the multiple virtual 3D point cloud representations captured by each depth camera are combined as single synthetic 3D point cloud model, and the elemental image arrays are generated for the newly synthesized 3D point cloud model from the given anamorphic optic system's angular step. The theory has been verified experimentally, and it shows that the proposed 360-degree integral-floating display can be an excellent way to display real object in the 360-degree viewing zone.

Adaptive Estimation of Multiple Fading Factors for GPS/INS Integrated Navigation Systems.

PubMed

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2017-06-01

The Kalman filter has been widely applied in the field of dynamic navigation and positioning. However, its performance will be degraded in the presence of significant model errors and uncertain interferences. In the literature, the fading filter was proposed to control the influences of the model errors, and the H-infinity filter can be adopted to address the uncertainties by minimizing the estimation error in the worst case. In this paper, a new multiple fading factor, suitable for the Global Positioning System (GPS) and the Inertial Navigation System (INS) integrated navigation system, is proposed based on the optimization of the filter, and a comprehensive filtering algorithm is constructed by integrating the advantages of the H-infinity filter and the proposed multiple fading filter. Measurement data of the GPS/INS integrated navigation system are collected under actual conditions. Stability and robustness of the proposed filtering algorithm are tested with various experiments and contrastive analysis are performed with the measurement data. Results demonstrate that both the filter divergence and the influences of outliers are restrained effectively with the proposed filtering algorithm, and precision of the filtering results are improved simultaneously.

A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

NASA Technical Reports Server (NTRS)

Kautzmann, Frank N., III

1988-01-01

Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.

77 FR 33486 - Certain Integrated Circuit Packages Provided With Multiple Heat-Conducting Paths and Products...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-06

... INTERNATIONAL TRADE COMMISSION [Docket No. 2899] Certain Integrated Circuit Packages Provided With... complaint entitled Certain Integrated Circuit Packages Provided With Multiple Heat-Conducting Paths and..., telephone (202) 205-2000. The public version of the complaint can be accessed on the Commission's electronic...

Multiple-component covalent organic frameworks

PubMed Central

Huang, Ning; Zhai, Lipeng; Coupry, Damien E.; Addicoat, Matthew A.; Okushita, Keiko; Nishimura, Katsuyuki; Heine, Thomas; Jiang, Donglin

2016-01-01

Covalent organic frameworks are a class of crystalline porous polymers that integrate molecular building blocks into periodic structures and are usually synthesized using two-component [1+1] condensation systems comprised of one knot and one linker. Here we report a general strategy based on multiple-component [1+2] and [1+3] condensation systems that enable the use of one knot and two or three linker units for the synthesis of hexagonal and tetragonal multiple-component covalent organic frameworks. Unlike two-component systems, multiple-component covalent organic frameworks feature asymmetric tiling of organic units into anisotropic skeletons and unusually shaped pores. This strategy not only expands the structural complexity of skeletons and pores but also greatly enhances their structural diversity. This synthetic platform is also widely applicable to multiple-component electron donor–acceptor systems, which lead to electronic properties that are not simply linear summations of those of the conventional [1+1] counterparts. PMID:27460607

Multiple-component covalent organic frameworks

NASA Astrophysics Data System (ADS)

Huang, Ning; Zhai, Lipeng; Coupry, Damien E.; Addicoat, Matthew A.; Okushita, Keiko; Nishimura, Katsuyuki; Heine, Thomas; Jiang, Donglin

2016-07-01

Covalent organic frameworks are a class of crystalline porous polymers that integrate molecular building blocks into periodic structures and are usually synthesized using two-component [1+1] condensation systems comprised of one knot and one linker. Here we report a general strategy based on multiple-component [1+2] and [1+3] condensation systems that enable the use of one knot and two or three linker units for the synthesis of hexagonal and tetragonal multiple-component covalent organic frameworks. Unlike two-component systems, multiple-component covalent organic frameworks feature asymmetric tiling of organic units into anisotropic skeletons and unusually shaped pores. This strategy not only expands the structural complexity of skeletons and pores but also greatly enhances their structural diversity. This synthetic platform is also widely applicable to multiple-component electron donor-acceptor systems, which lead to electronic properties that are not simply linear summations of those of the conventional [1+1] counterparts.

Real-time trace gas sensor using a multimode diode laser and multiple-line integrated cavity enhanced absorption spectroscopy.

PubMed

Karpf, Andreas; Rao, Gottipaty N

2015-07-01

We describe and demonstrate a highly sensitive trace gas sensor based on a simplified design that is capable of measuring sub-ppb concentrations of NO2 in tens of milliseconds. The sensor makes use of a relatively inexpensive Fabry-Perot diode laser to conduct off-axis cavity enhanced spectroscopy. The broad frequency range of a multimode Fabry-Perot diode laser spans a large number of absorption lines, thereby removing the need for a single-frequency tunable laser source. The use of cavity enhanced absorption spectroscopy enhances the sensitivity of the sensor by providing a pathlength on the order of 1 km in a small volume. Off-axis alignment excites a large number of cavity modes simultaneously, thereby reducing the sensor's susceptibility to vibration. Multiple-line integrated absorption spectroscopy (where one integrates the absorption spectra over a large number of rovibronic transitions of the molecular species) further improves the sensitivity of detection. Relatively high laser power (∼400  mW) is used to compensate for the low coupling efficiency of a broad linewidth laser to the optical cavity. The approach was demonstrated using a 407 nm diode laser to detect trace quantities of NO2 in zero air. Sensitivities of 750 ppt, 110 ppt, and 65 ppt were achieved using integration times of 50 ms, 5 s, and 20 s respectively.

Sensory integration balance training in patients with multiple sclerosis: A randomized, controlled trial.

PubMed

Gandolfi, Marialuisa; Munari, Daniele; Geroin, Christian; Gajofatto, Alberto; Benedetti, Maria Donata; Midiri, Alessandro; Carla, Fontana; Picelli, Alessandro; Waldner, Andreas; Smania, Nicola

2015-10-01

Impaired sensory integration contributes to balance disorders in patients with multiple sclerosis (MS). The objective of this paper is to compare the effects of sensory integration balance training against conventional rehabilitation on balance disorders, the level of balance confidence perceived, quality of life, fatigue, frequency of falls, and sensory integration processing on a large sample of patients with MS. This single-blind, randomized, controlled trial involved 80 outpatients with MS (EDSS: 1.5-6.0) and subjective symptoms of balance disorders. The experimental group (n = 39) received specific training to improve central integration of afferent sensory inputs; the control group (n = 41) received conventional rehabilitation (15 treatment sessions of 50 minutes each). Before, after treatment, and at one month post-treatment, patients were evaluated by a blinded rater using the Berg Balance Scale (BBS), Activities-specific Balance Confidence Scale (ABC), Multiple Sclerosis Quality of Life-54, Fatigue Severity Scale (FSS), number of falls and the Sensory Organization Balance Test (SOT). The experimental training program produced greater improvements than the control group training on the BBS (p < 0.001), the FSS (p < 0.002), number of falls (p = 0.002) and SOT (p < 0.05). Specific training to improve central integration of afferent sensory inputs may ameliorate balance disorders in patients with MS. Clinical Trial Registration (NCT01040117). © The Author(s), 2015.

The molecular basis of nutritional intervention in multiple sclerosis: a narrative review.

PubMed

Riccio, P

2011-08-01

It is commonly accepted that nutrition is one of the possible environmental factors involved in the pathogenesis of multiple sclerosis (MS), but its role as complementary MS treatment is unclear and largely disregarded. At present, MS therapy is not associated to a particular diet, probably due to lack of information on the effects of nutrition on the disease. To overcome the distrust of the usefulness of dietary control in MS and to encourage nutritional interventions in the course of the disease, it is necessary to assess the nature and the role of bioactive dietary molecules and their targets, and establish how a dietary control can influence cell metabolism and improve the wellness of MS patients. The aim of this review is to provide a rationale for a nutritional intervention in MS by evaluating at the molecular level the effects of dietary molecules on the inflammatory and autoimmune processes involved in the disease. Present data reveal that healthy dietary molecules have a pleiotropic role and are able to change cell metabolism from anabolism to catabolism and down-regulate inflammation by interacting with enzymes, nuclear receptors and transcriptional factors. The control of gut dysbiosis and the combination of hypo-caloric, low-fat diets with specific vitamins, oligoelements and dietary integrators, including fish oil and polyphenols, may slow-down the progression of the disease and ameliorate the wellness of MS patients. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multiplicity and molecular epidemiology of Plasmodium vivax and Plasmodium falciparum infections in East Africa.

PubMed

Zhong, Daibin; Lo, Eugenia; Wang, Xiaoming; Yewhalaw, Delenasaw; Zhou, Guofa; Atieli, Harrysone E; Githeko, Andrew; Hemming-Schroeder, Elizabeth; Lee, Ming-Chieh; Afrane, Yaw; Yan, Guiyun

2018-05-02

Parasite genetic diversity and multiplicity of infection (MOI) affect clinical outcomes, response to drug treatment and naturally-acquired or vaccine-induced immunity. Traditional methods often underestimate the frequency and diversity of multiclonal infections due to technical sensitivity and specificity. Next-generation sequencing techniques provide a novel opportunity to study complexity of parasite populations and molecular epidemiology. Symptomatic and asymptomatic Plasmodium vivax samples were collected from health centres/hospitals and schools, respectively, from 2011 to 2015 in Ethiopia. Similarly, both symptomatic and asymptomatic Plasmodium falciparum samples were collected, respectively, from hospitals and schools in 2005 and 2015 in Kenya. Finger-pricked blood samples were collected and dried on filter paper. Long amplicon (> 400 bp) deep sequencing of merozoite surface protein 1 (msp1) gene was conducted to determine multiplicity and molecular epidemiology of P. vivax and P. falciparum infections. The results were compared with those based on short amplicon (117 bp) deep sequencing. A total of 139 P. vivax and 222 P. falciparum samples were pyro-sequenced for pvmsp1 and pfmsp1, yielding a total of 21 P. vivax and 99 P. falciparum predominant haplotypes. The average MOI for P. vivax and P. falciparum were 2.16 and 2.68, respectively, which were significantly higher than that of microsatellite markers and short amplicon (117 bp) deep sequencing. Multiclonal infections were detected in 62.2% of the samples for P. vivax and 74.8% of the samples for P. falciparum. Four out of the five subjects with recurrent P. vivax malaria were found to be a relapse 44-65 days after clearance of parasites. No difference was observed in MOI among P. vivax patients of different symptoms, ages and genders. Similar patterns were also observed in P. falciparum except for one study site in Kenyan lowland areas with significantly higher MOI. The study used a novel method

Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes.

PubMed

Santiago, Jose A; Potashkin, Judith A

2013-01-01

Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP), previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Prognostic Biomarker Study (PROBE), revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients. These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first time that

Molecular radiotherapy: the NUKFIT software for calculating the time-integrated activity coefficient.

PubMed

Kletting, P; Schimmel, S; Kestler, H A; Hänscheid, H; Luster, M; Fernández, M; Bröer, J H; Nosske, D; Lassmann, M; Glatting, G

2013-10-01

Calculation of the time-integrated activity coefficient (residence time) is a crucial step in dosimetry for molecular radiotherapy. However, available software is deficient in that it is either not tailored for the use in molecular radiotherapy and/or does not include all required estimation methods. The aim of this work was therefore the development and programming of an algorithm which allows for an objective and reproducible determination of the time-integrated activity coefficient and its standard error. The algorithm includes the selection of a set of fitting functions from predefined sums of exponentials and the choice of an error model for the used data. To estimate the values of the adjustable parameters an objective function, depending on the data, the parameters of the error model, the fitting function and (if required and available) Bayesian information, is minimized. To increase reproducibility and user-friendliness the starting values are automatically determined using a combination of curve stripping and random search. Visual inspection, the coefficient of determination, the standard error of the fitted parameters, and the correlation matrix are provided to evaluate the quality of the fit. The functions which are most supported by the data are determined using the corrected Akaike information criterion. The time-integrated activity coefficient is estimated by analytically integrating the fitted functions. Its standard error is determined assuming Gaussian error propagation. The software was implemented using MATLAB. To validate the proper implementation of the objective function and the fit functions, the results of NUKFIT and SAAM numerical, a commercially available software tool, were compared. The automatic search for starting values was successfully tested for reproducibility. The quality criteria applied in conjunction with the Akaike information criterion allowed the selection of suitable functions. Function fit parameters and their standard

Use of multiple picosecond high-mass molecular dynamics simulations to predict crystallographic B-factors of folded globular proteins.

PubMed

Pang, Yuan-Ping

2016-09-01

Predicting crystallographic B-factors of a protein from a conventional molecular dynamics simulation is challenging, in part because the B-factors calculated through sampling the atomic positional fluctuations in a picosecond molecular dynamics simulation are unreliable, and the sampling of a longer simulation yields overly large root mean square deviations between calculated and experimental B-factors. This article reports improved B-factor prediction achieved by sampling the atomic positional fluctuations in multiple picosecond molecular dynamics simulations that use uniformly increased atomic masses by 100-fold to increase time resolution. Using the third immunoglobulin-binding domain of protein G, bovine pancreatic trypsin inhibitor, ubiquitin, and lysozyme as model systems, the B-factor root mean square deviations (mean ± standard error) of these proteins were 3.1 ± 0.2-9 ± 1 Å 2 for Cα and 7.3 ± 0.9-9.6 ± 0.2 Å 2 for Cγ, when the sampling was done for each of these proteins over 20 distinct, independent, and 50-picosecond high-mass molecular dynamics simulations with AMBER forcefield FF12MC or FF14SB. These results suggest that sampling the atomic positional fluctuations in multiple picosecond high-mass molecular dynamics simulations may be conducive to a priori prediction of crystallographic B-factors of a folded globular protein.

Toward an integrative molecular approach to wildlife disease.

PubMed

DeCandia, Alexandra L; Dobson, Andrew P; vonHoldt, Bridgett M

2018-01-29

Pathogens pose serious threats to human health, agricultural investment, and biodiversity conservation through the emergence of zoonoses, spillover to domestic livestock, and epizootic outbreaks. As such, wildlife managers are often tasked with mitigating the negative effects of disease. Yet, parasites form a major component of biodiversity that often persist. This is due to logistical challenges of implementing management strategies and to insufficient understanding of host-parasite dynamics. We advocate for an inclusive understanding of molecular diversity in driving parasite infection and variable host disease states in wildlife systems. More specifically, we examine the roles of genetic, epigenetic, and commensal microbial variation in disease pathogenesis. These include mechanisms underlying parasite virulence and host resistance and tolerance, and the development, regulation, and parasite subversion of immune pathways, among other processes. Case studies of devil facial tumor disease in Tasmanian devils (Sarcophilus harrisii) and chytridiomycosis in globally distributed amphibians exemplify the broad range of questions that can be addressed by examining different facets of molecular diversity. For particularly complex systems, integrative molecular analyses present a promising frontier that can provide critical insights necessary to elucidate disease dynamics operating across scales. These insights enable more accurate risk assessment, reconstruction of transmission pathways, discernment of optimal intervention strategies, and development of more effective and ecologically sound treatments that minimize damage to the host population and environment. Such measures are crucial when mitigating threats posed by wildlife disease to humans, domestic animals, and species of conservation concern. © 2018 Society for Conservation Biology.

A method for integrating multiple components in a decision support system

Treesearch

Donald Nute; Walter D. Potter; Zhiyuan Cheng; Mayukh Dass; Astrid Glende; Frederick Maierv; Cy Routh; Hajime Uchiyama; Jin Wang; Sarah Witzig; Mark Twery; Peter Knopp; Scott Thomasma; H. Michael Rauscher

2005-01-01

We present a flexible, extensible method for integrating multiple tools into a single large decision support system (DSS) using a forest ecosystem management DSS (NED-2) as an example. In our approach, a rich ontology for the target domain is developed and implemented in the internal data model for the DSS. Semi-autonomous agents control external components and...

Nonlinear multiplicative dendritic integration in neuron and network models

PubMed Central

Zhang, Danke; Li, Yuanqing; Rasch, Malte J.; Wu, Si

2013-01-01

Neurons receive inputs from thousands of synapses distributed across dendritic trees of complex morphology. It is known that dendritic integration of excitatory and inhibitory synapses can be highly non-linear in reality and can heavily depend on the exact location and spatial arrangement of inhibitory and excitatory synapses on the dendrite. Despite this known fact, most neuron models used in artificial neural networks today still only describe the voltage potential of a single somatic compartment and assume a simple linear summation of all individual synaptic inputs. We here suggest a new biophysical motivated derivation of a single compartment model that integrates the non-linear effects of shunting inhibition, where an inhibitory input on the route of an excitatory input to the soma cancels or “shunts” the excitatory potential. In particular, our integration of non-linear dendritic processing into the neuron model follows a simple multiplicative rule, suggested recently by experiments, and allows for strict mathematical treatment of network effects. Using our new formulation, we further devised a spiking network model where inhibitory neurons act as global shunting gates, and show that the network exhibits persistent activity in a low firing regime. PMID:23658543

Structural Refinement of Proteins by Restrained Molecular Dynamics Simulations with Non-interacting Molecular Fragments.

PubMed

Shen, Rong; Han, Wei; Fiorin, Giacomo; Islam, Shahidul M; Schulten, Klaus; Roux, Benoît

2015-10-01

The knowledge of multiple conformational states is a prerequisite to understand the function of membrane transport proteins. Unfortunately, the determination of detailed atomic structures for all these functionally important conformational states with conventional high-resolution approaches is often difficult and unsuccessful. In some cases, biophysical and biochemical approaches can provide important complementary structural information that can be exploited with the help of advanced computational methods to derive structural models of specific conformational states. In particular, functional and spectroscopic measurements in combination with site-directed mutations constitute one important source of information to obtain these mixed-resolution structural models. A very common problem with this strategy, however, is the difficulty to simultaneously integrate all the information from multiple independent experiments involving different mutations or chemical labels to derive a unique structural model consistent with the data. To resolve this issue, a novel restrained molecular dynamics structural refinement method is developed to simultaneously incorporate multiple experimentally determined constraints (e.g., engineered metal bridges or spin-labels), each treated as an individual molecular fragment with all atomic details. The internal structure of each of the molecular fragments is treated realistically, while there is no interaction between different molecular fragments to avoid unphysical steric clashes. The information from all the molecular fragments is exploited simultaneously to constrain the backbone to refine a three-dimensional model of the conformational state of the protein. The method is illustrated by refining the structure of the voltage-sensing domain (VSD) of the Kv1.2 potassium channel in the resting state and by exploring the distance histograms between spin-labels attached to T4 lysozyme. The resulting VSD structures are in good agreement with

Integrative Analysis of Prognosis Data on Multiple Cancer Subtypes

PubMed Central

Liu, Jin; Huang, Jian; Zhang, Yawei; Lan, Qing; Rothman, Nathaniel; Zheng, Tongzhang; Ma, Shuangge

2014-01-01

Summary In cancer research, profiling studies have been extensively conducted, searching for genes/SNPs associated with prognosis. Cancer is diverse. Examining the similarity and difference in the genetic basis of multiple subtypes of the same cancer can lead to a better understanding of their connections and distinctions. Classic meta-analysis methods analyze each subtype separately and then compare analysis results across subtypes. Integrative analysis methods, in contrast, analyze the raw data on multiple subtypes simultaneously and can outperform meta-analysis methods. In this study, prognosis data on multiple subtypes of the same cancer are analyzed. An AFT (accelerated failure time) model is adopted to describe survival. The genetic basis of multiple subtypes is described using the heterogeneity model, which allows a gene/SNP to be associated with prognosis of some subtypes but not others. A compound penalization method is developed to identify genes that contain important SNPs associated with prognosis. The proposed method has an intuitive formulation and is realized using an iterative algorithm. Asymptotic properties are rigorously established. Simulation shows that the proposed method has satisfactory performance and outperforms a penalization-based meta-analysis method and a regularized thresholding method. An NHL (non-Hodgkin lymphoma) prognosis study with SNP measurements is analyzed. Genes associated with the three major subtypes, namely DLBCL, FL, and CLL/SLL, are identified. The proposed method identifies genes that are different from alternatives and have important implications and satisfactory prediction performance. PMID:24766212

May Diet and Dietary Supplements Improve the Wellness of Multiple Sclerosis Patients? A Molecular Approach

PubMed Central

Riccio, Paolo; Rossano, Rocco; Liuzzi, Grazia Maria

2010-01-01

Multiple sclerosis is a complex and multifactorial neurological disease, and nutrition is one of the environmental factors possibly involved in its pathogenesis. At present, the role of nutrition is unclear, and MS therapy is not associated to a particular diet. MS clinical trials based on specific diets or dietary supplements are very few and in some cases controversial. To understand how diet can influence the course of MS and improve the wellness of MS patients, it is necessary to identify the dietary molecules, their targets and the molecular mechanisms involved in the control of the disease. The aim of this paper is to provide a molecular basis for the nutritional intervention in MS by evaluating at molecular level the effect of dietary molecules on the inflammatory and autoimmune processes involved in the disease. PMID:21461338

Variational path integral molecular dynamics and hybrid Monte Carlo algorithms using a fourth order propagator with applications to molecular systems

NASA Astrophysics Data System (ADS)

Kamibayashi, Yuki; Miura, Shinichi

2016-08-01

In the present study, variational path integral molecular dynamics and associated hybrid Monte Carlo (HMC) methods have been developed on the basis of a fourth order approximation of a density operator. To reveal various parameter dependence of physical quantities, we analytically solve one dimensional harmonic oscillators by the variational path integral; as a byproduct, we obtain the analytical expression of the discretized density matrix using the fourth order approximation for the oscillators. Then, we apply our methods to realistic systems like a water molecule and a para-hydrogen cluster. In the HMC, we adopt two level description to avoid the time consuming Hessian evaluation. For the systems examined in this paper, the HMC method is found to be about three times more efficient than the molecular dynamics method if appropriate HMC parameters are adopted; the advantage of the HMC method is suggested to be more evident for systems described by many body interaction.

Trade-offs in thermal adaptation: the need for a molecular to ecological integration.

PubMed

Pörtner, Hans O; Bennett, Albert F; Bozinovic, Francisco; Clarke, Andrew; Lardies, Marco A; Lucassen, Magnus; Pelster, Bernd; Schiemer, Fritz; Stillman, Jonathon H

2006-01-01

Through functional analyses, integrative physiology is able to link molecular biology with ecology as well as evolutionary biology and is thereby expected to provide access to the evolution of molecular, cellular, and organismic functions; the genetic basis of adaptability; and the shaping of ecological patterns. This paper compiles several exemplary studies of thermal physiology and ecology, carried out at various levels of biological organization from single genes (proteins) to ecosystems. In each of those examples, trade-offs and constraints in thermal adaptation are addressed; these trade-offs and constraints may limit species' distribution and define their level of fitness. For a more comprehensive understanding, the paper sets out to elaborate the functional and conceptual connections among these independent studies and the various organizational levels addressed. This effort illustrates the need for an overarching concept of thermal adaptation that encompasses molecular, organellar, cellular, and whole-organism information as well as the mechanistic links between fitness, ecological success, and organismal physiology. For this data, the hypothesis of oxygen- and capacity-limited thermal tolerance in animals provides such a conceptual framework and allows interpreting the mechanisms of thermal limitation of animals as relevant at the ecological level. While, ideally, evolutionary studies over multiple generations, illustrated by an example study in bacteria, are necessary to test the validity of such complex concepts and underlying hypotheses, animal physiology frequently is constrained to functional studies within one generation. Comparisons of populations in a latitudinal cline, closely related species from different climates, and ontogenetic stages from riverine clines illustrate how evolutionary information can still be gained. An understanding of temperature-dependent shifts in energy turnover, associated with adjustments in aerobic scope and performance

Multiple-source spatial data fusion and integration research in the region unified planning management information system

NASA Astrophysics Data System (ADS)

Liu, Zhijun; Zhang, Liangpei; Liu, Zhenmin; Jiao, Hongbo; Chen, Liqun

2008-12-01

In order to manage the internal resources of Gulf of Tonkin and integrate multiple-source spatial data, the establishment of region unified plan management system is needed. The data fusion and the integrated research should be carried on because there are some difficulties in the course of the system's establishment. For example, kinds of planning and the project data format are different, and data criterion is not unified. Besides, the time state property is strong, and spatial reference is inconsistent, etc. In this article the ARCGIS ENGINE is introduced as the developing platform, key technologies are researched, such as multiple-source data transformation and fusion, remote sensing data and DEM fusion and integrated, plan and project data integration, and so on. Practice shows that the system improves the working efficiency of Guangxi Gulf of Tonkin Economic Zone Management Committee significantly and promotes planning construction work of the economic zone remarkably.

Sparse Group Penalized Integrative Analysis of Multiple Cancer Prognosis Datasets

PubMed Central

Liu, Jin; Huang, Jian; Xie, Yang; Ma, Shuangge

2014-01-01

SUMMARY In cancer research, high-throughput profiling studies have been extensively conducted, searching for markers associated with prognosis. Because of the “large d, small n” characteristic, results generated from the analysis of a single dataset can be unsatisfactory. Recent studies have shown that integrative analysis, which simultaneously analyzes multiple datasets, can be more effective than single-dataset analysis and classic meta-analysis. In most of existing integrative analysis, the homogeneity model has been assumed, which postulates that different datasets share the same set of markers. Several approaches have been designed to reinforce this assumption. In practice, different datasets may differ in terms of patient selection criteria, profiling techniques, and many other aspects. Such differences may make the homogeneity model too restricted. In this study, we assume the heterogeneity model, under which different datasets are allowed to have different sets of markers. With multiple cancer prognosis datasets, we adopt the AFT (accelerated failure time) model to describe survival. This model may have the lowest computational cost among popular semiparametric survival models. For marker selection, we adopt a sparse group MCP (minimax concave penalty) approach. This approach has an intuitive formulation and can be computed using an effective group coordinate descent algorithm. Simulation study shows that it outperforms the existing approaches under both the homogeneity and heterogeneity models. Data analysis further demonstrates the merit of heterogeneity model and proposed approach. PMID:23938111

Macroscopic contraction of a gel induced by the integrated motion of light-driven molecular motors

NASA Astrophysics Data System (ADS)

Li, Quan; Fuks, Gad; Moulin, Emilie; Maaloum, Mounir; Rawiso, Michel; Kulic, Igor; Foy, Justin T.; Giuseppone, Nicolas

2015-02-01

Making molecular machines that can be useful in the macroscopic world is a challenging long-term goal of nanoscience. Inspired by the protein machinery found in biological systems, and based on the theoretical understanding of the physics of motion at the nanoscale, organic chemists have developed a number of molecules that can produce work by contraction or rotation when triggered by various external chemical or physical stimuli. In particular, basic molecular switches that commute between at least two thermodynamic minima and more advanced molecular motors that behave as dissipative units working far from equilibrium when fuelled with external energy have been reported. However, despite recent progress, the ultimate challenge of coordinating individual molecular motors in a continuous mechanical process that can have a measurable effect at the macroscale has remained elusive. Here, we show that by integrating light-driven unidirectional molecular rotors as reticulating units in a polymer gel, it is possible to amplify their individual motions to achieve macroscopic contraction of the material. Our system uses the incoming light to operate under far-from-equilibrium conditions, and the work produced by the motor in the photostationary state is used to twist the entangled polymer chains up to the collapse of the gel. Our design could be a starting point to integrate nanomotors in metastable materials to store energy and eventually to convert it.

MSblender: A probabilistic approach for integrating peptide identifications from multiple database search engines.

PubMed

Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I; Marcotte, Edward M

2011-07-01

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for every possible PSM and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for most proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses.

MSblender: a probabilistic approach for integrating peptide identifications from multiple database search engines

PubMed Central

Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I.; Marcotte, Edward M.

2011-01-01

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for all possible PSMs and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for all detected proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses. PMID:21488652

Cellular and molecular specificity of pituitary gland physiology.

PubMed

Perez-Castro, Carolina; Renner, Ulrich; Haedo, Mariana R; Stalla, Gunter K; Arzt, Eduardo

2012-01-01

The anterior pituitary gland has the ability to respond to complex signals derived from central and peripheral systems. Perception of these signals and their integration are mediated by cell interactions and cross-talk of multiple signaling transduction pathways and transcriptional regulatory networks that cooperate for hormone secretion, cell plasticity, and ultimately specific pituitary responses that are essential for an appropriate physiological response. We discuss the physiopathological and molecular mechanisms related to this integrative regulatory system of the anterior pituitary gland and how it contributes to modulate the gland functions and impacts on body homeostasis.

Molecular Approach to Targeted Therapy for Multiple Sclerosis.

PubMed

Sherbet, Gajanan V

2016-01-01

The development and evolution of targeted therapy to any disease require the identification of targets amenable to treatment of patients. Here the pathogenetic signalling systems involved in multiple sclerosis are scrutinised to locate nodes of deregulation and dysfunction in order to devise strategies of drug development for targeted intervention. Oliogoclonal bands (OCB) are isoelectric focusing profiles of immunoglobulins synthesised in the central nervous system. OCBs enable the diagnosis of multiple sclerosis with high sensitivity and specificity and are related to the course of the disease and progression. The OCB patterns can be linked with the expression of angiogenic molecular species. Angiogenic signalling which has also been implicated in demyelination provides the option of using angiogenesis inhibitors in disease control. The PI3K (phosphoinositide 3-kinase)/Akt axis has emerged with a key role in myelination with its demonstrable links with mTOR mediated transcription of downstream target genes. Inflammatory signals and innate and acquired immunity from the activation of NF-κB (nuclear factor κB) responsive genes are considered. NF-κB signalling could be implicated in myelination. The transcription factor STAT (signal transducers and activators of transcription) and the EBV (Epstein- Barr virus) transcription factor BZLF1 contributing significantly to the disease process are a major environmental factor linked to MS. EBV can activate TGF (transforming growth factor) and VEGF (vascular endothelial growth factor) signalling. EBV microRNAs are reviewed as signalling mediators of pathogenesis. Stem cell transplantation therapy has lately gained much credence, so the current status of mesenchymal and hematopoietic stem cell therapy is reviewed with emphasis on the differential expression immune-related genes and operation of signalling systems.

Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.

PubMed

Wu, Dingming; Wang, Dongfang; Zhang, Michael Q; Gu, Jin

2015-12-01

One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data. In this study, we proposed a novel low-rank approximation based integrative probabilistic model to fast find the shared principal subspace across multiple data types: the convexity of the low-rank regularized likelihood function of the probabilistic model ensures efficient and stable model fitting. Candidate molecular subtypes can be identified by unsupervised clustering hundreds of cancer samples in the reduced low-dimensional subspace. On testing datasets, our method LRAcluster (low-rank approximation based multi-omics data clustering) runs much faster with better clustering performances than the existing method. Then, we applied LRAcluster on large-scale cancer multi-omics data from TCGA. The pan-cancer analysis results show that the cancers of different tissue origins are generally grouped as independent clusters, except squamous-like carcinomas. While the single cancer type analysis suggests that the omics data have different subtyping abilities for different cancer types. LRAcluster is a very useful method for fast dimension reduction and unsupervised clustering of large-scale multi-omics data. LRAcluster is implemented in R and freely available via http://bioinfo.au.tsinghua.edu.cn/software/lracluster/ .

Plasma DNA integrity index as a potential molecular diagnostic marker for breast cancer.

PubMed

Kamel, Azza M; Teama, Salwa; Fawzy, Amal; El Deftar, Mervat

2016-06-01

Plasma DNA integrity index is increased in various malignancies including breast cancer, the most common cancer in women worldwide; early detection is crucial for successful treatment. Current screening methods fail to detect many cases of breast cancer at an early stage. In this study, we evaluated the level of plasma DNA integrity index in 260 females (95 with breast cancer, 95 with benign breast lesions, and 70 healthy controls) to verify its potential value in discriminating malignant from benign breast lesions. The criteria of the American Joint Committee on Cancer were used for staging of breast cancer patients. DNA integrity index was measured by real-time PCR. DNA integrity index was significantly higher in breast cancer than in benign breast patients and healthy subjects (P = <0.001). DNA integrity index is correlated with TNM stage. Given 100 % specificity, the highest sensitivity achieved in detecting cancer group was 85.3 % at 0.55 DNA integrity index cutoff. In conclusion, the plasma DNA integrity index may be a promising molecular diagnostic marker of malignancy in breast lesions.

Modulation of C. elegans Touch Sensitivity Is Integrated at Multiple Levels

PubMed Central

Chen, Xiaoyin

2014-01-01

Sensory systems can adapt to different environmental signals. Here we identify four conditions that modulate anterior touch sensitivity in Caenorhabditis elegans after several hours and demonstrate that such sensory modulation is integrated at multiple levels to produce a single output. Prolonged vibration involving integrin signaling directly sensitizes the touch receptor neurons (TRNs). In contrast, hypoxia, the dauer state, and high salt reduce touch sensitivity by preventing the release of long-range neuroregulators, including two insulin-like proteins. Integration of these latter inputs occurs at upstream neurohormonal cells and at the insulin signaling cascade within the TRNs. These signals and those from integrin signaling converge to modulate touch sensitivity by regulating AKT kinases and DAF-16/FOXO. Thus, activation of either the integrin or insulin pathways can compensate for defects in the other pathway. This modulatory system integrates conflicting signals from different modalities, and adapts touch sensitivity to both mechanical and non-mechanical conditions. PMID:24806678

Integrating molecular markers into the World Health Organization classification of CNS tumors: a survey of the neuro-oncology community.

PubMed

Aldape, Kenneth; Nejad, Romina; Louis, David N; Zadeh, Gelareh

2017-03-01

Molecular markers provide important biological and clinical information related to the classification of brain tumors, and the integration of relevant molecular parameters into brain tumor classification systems has been a widely discussed topic in neuro-oncology over the past decade. With recent advances in the development of clinically relevant molecular signatures and the 2016 World Health Organization (WHO) update, the views of the neuro-oncology community on such changes would be informative for implementing this process. A survey with 8 questions regarding molecular markers in tumor classification was sent to an email list of Society for Neuro-Oncology members and attendees of prior meetings (n=5065). There were 403 respondents. Analysis was performed using whole group response, based on self-reported subspecialty. The survey results show overall strong support for incorporating molecular knowledge into the classification and clinical management of brain tumors. Across all 7 subspecialty groups, ≥70% of respondents agreed to this integration. Interestingly, some variability is seen among subspecialties, notably with lowest support from neuropathologists, which may reflect their roles in implementing such diagnostic technologies. Based on a survey provided to the neuro-oncology community, we report strong support for the integration of molecular markers into the WHO classification of brain tumors, as well as for using an integrated "layered" diagnostic format. While membership from each specialty showed support, there was variation by specialty in enthusiasm regarding proposed changes. The initial results of this survey influenced the deliberations underlying the 2016 WHO classification of tumors of the central nervous system. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.

Chapter 5 Multiple, Localized, and Delocalized/Conjugated Bonds in the Orbital Communication Theory of Molecular Systems

NASA Astrophysics Data System (ADS)

Nalewajski, Roman F.

molecular fragments, for example, localized bonds, functional groups, and forward and back donations accompanying the bond formation, and so on, can be extracted. The flow of information in such molecular communication networks is investigated in several prototype molecules. These illustrative (model) applications of the orbital communication theory of chemical bonds (CTCB) deal with several classical issues in the electronic structure theory: atom hybridization/promotion, single and multiple chemical bonds, bond conjugation, and so on. The localized bonds in hydrides and delocalized [pi]-bonds in simple hydrocarbons, as well as the multiple bonds in CO and CO2, are diagnosed using the entropy/information descriptors of CTCB. The atom promotion in hydrides and bond conjugation in [pi]-electron systems are investigated in more detail. A major drawback of the previous two-electron approach to molecular channels, namely, two weak bond differentiation in aromatic systems, has been shown to be remedied in the one-electron approach.

Integrative analysis of signaling pathways and diseases associated with the miR-106b/25 cluster and their function study in berberine-induced multiple myeloma cells.

PubMed

Gu, Chunming; Li, Tianfu; Yin, Zhao; Chen, Shengting; Fei, Jia; Shen, Jianping; Zhang, Yuan

2017-05-01

Berberine (BBR), a traditional Chinese herbal medicine compound, has emerged as a novel class of anti-tumor agent. Our previous microRNA (miRNA) microarray demonstrated that miR-106b/25 was significantly down-regulated in BBR-treated multiple myeloma (MM) cells. Here, systematic integration showed that miR-106b/25 cluster is involved in multiple cancer-related signaling pathways and tumorigenesis. MiREnvironment database revealed that multiple environmental factors (drug, ionizing radiation, hypoxia) affected the miR-106b/25 cluster expression. By targeting the seed region in the miRNA, tiny anti-mir106b/25 cluster (t-anti-mir106b/25 cluster) significantly induced suppression in cell viability and colony formation. Western blot validated that t-anti-miR-106b/25 cluster effectively inhibited the expression of P38 MAPK and phospho-P38 MAPK in MM cells. These findings indicated the miR-106b/25 cluster functioned as oncogene and might provide a novel molecular insight into MM.

Integrated argument-based inquiry with multiple representation approach to promote scientific argumentation skill

NASA Astrophysics Data System (ADS)

Suminar, Iin; Muslim, Liliawati, Winny

2017-05-01

The purpose of this research was to identify student's written argument embedded in scientific inqury investigation and argumentation skill using integrated argument-based inquiry with multiple representation approach. This research was using quasi experimental method with the nonequivalent pretest-posttest control group design. Sample ot this research was 10th grade students at one of High School in Bandung using two classes, they were 26 students of experiment class and 26 students of control class. Experiment class using integrated argument-based inquiry with multiple representation approach, while control class using argument-based inquiry. This study was using argumentation worksheet and argumentation test. Argumentation worksheet encouraged students to formulate research questions, design experiment, observe experiment and explain the data as evidence, construct claim, warrant, embedded multiple modus representation and reflection. Argumentation testinclude problem which asks students to explain evidence, warrants, and backings support of each claim. The result of this research show experiment class students's argumentation skill performed better than control class students that of experiment class was 0.47 and control class was 0.31. The results of unequal variance t-test for independent means show that students'sargumentationskill of experiment class performed better significantly than students'sargumentationskill of control class.

Handling missing rows in multi-omics data integration: multiple imputation in multiple factor analysis framework.

PubMed

Voillet, Valentin; Besse, Philippe; Liaubet, Laurence; San Cristobal, Magali; González, Ignacio

2016-10-03

In omics data integration studies, it is common, for a variety of reasons, for some individuals to not be present in all data tables. Missing row values are challenging to deal with because most statistical methods cannot be directly applied to incomplete datasets. To overcome this issue, we propose a multiple imputation (MI) approach in a multivariate framework. In this study, we focus on multiple factor analysis (MFA) as a tool to compare and integrate multiple layers of information. MI involves filling the missing rows with plausible values, resulting in M completed datasets. MFA is then applied to each completed dataset to produce M different configurations (the matrices of coordinates of individuals). Finally, the M configurations are combined to yield a single consensus solution. We assessed the performance of our method, named MI-MFA, on two real omics datasets. Incomplete artificial datasets with different patterns of missingness were created from these data. The MI-MFA results were compared with two other approaches i.e., regularized iterative MFA (RI-MFA) and mean variable imputation (MVI-MFA). For each configuration resulting from these three strategies, the suitability of the solution was determined against the true MFA configuration obtained from the original data and a comprehensive graphical comparison showing how the MI-, RI- or MVI-MFA configurations diverge from the true configuration was produced. Two approaches i.e., confidence ellipses and convex hulls, to visualize and assess the uncertainty due to missing values were also described. We showed how the areas of ellipses and convex hulls increased with the number of missing individuals. A free and easy-to-use code was proposed to implement the MI-MFA method in the R statistical environment. We believe that MI-MFA provides a useful and attractive method for estimating the coordinates of individuals on the first MFA components despite missing rows. MI-MFA configurations were close to the true

A hybrid framework of first principles molecular orbital calculations and a three-dimensional integral equation theory for molecular liquids: Multi-center molecular Ornstein-Zernike self-consistent field approach

NASA Astrophysics Data System (ADS)

Kido, Kentaro; Kasahara, Kento; Yokogawa, Daisuke; Sato, Hirofumi

2015-07-01

In this study, we reported the development of a new quantum mechanics/molecular mechanics (QM/MM)-type framework to describe chemical processes in solution by combining standard molecular-orbital calculations with a three-dimensional formalism of integral equation theory for molecular liquids (multi-center molecular Ornstein-Zernike (MC-MOZ) method). The theoretical procedure is very similar to the 3D-reference interaction site model self-consistent field (RISM-SCF) approach. Since the MC-MOZ method is highly parallelized for computation, the present approach has the potential to be one of the most efficient procedures to treat chemical processes in solution. Benchmark tests to check the validity of this approach were performed for two solute (solute water and formaldehyde) systems and a simple SN2 reaction (Cl- + CH3Cl → ClCH3 + Cl-) in aqueous solution. The results for solute molecular properties and solvation structures obtained by the present approach were in reasonable agreement with those obtained by other hybrid frameworks and experiments. In particular, the results of the proposed approach are in excellent agreements with those of 3D-RISM-SCF.

A hybrid framework of first principles molecular orbital calculations and a three-dimensional integral equation theory for molecular liquids: multi-center molecular Ornstein-Zernike self-consistent field approach.

PubMed

Kido, Kentaro; Kasahara, Kento; Yokogawa, Daisuke; Sato, Hirofumi

2015-07-07

In this study, we reported the development of a new quantum mechanics/molecular mechanics (QM/MM)-type framework to describe chemical processes in solution by combining standard molecular-orbital calculations with a three-dimensional formalism of integral equation theory for molecular liquids (multi-center molecular Ornstein-Zernike (MC-MOZ) method). The theoretical procedure is very similar to the 3D-reference interaction site model self-consistent field (RISM-SCF) approach. Since the MC-MOZ method is highly parallelized for computation, the present approach has the potential to be one of the most efficient procedures to treat chemical processes in solution. Benchmark tests to check the validity of this approach were performed for two solute (solute water and formaldehyde) systems and a simple SN2 reaction (Cl(-) + CH3Cl → ClCH3 + Cl(-)) in aqueous solution. The results for solute molecular properties and solvation structures obtained by the present approach were in reasonable agreement with those obtained by other hybrid frameworks and experiments. In particular, the results of the proposed approach are in excellent agreements with those of 3D-RISM-SCF.

Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

PubMed

Adhikari, Badri; Hou, Jie; Cheng, Jianlin

2018-03-01

In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on contact prediction. The first method (MULTICOM-NOVEL) uses only traditional features (sequence profile, secondary structure, and solvent accessibility) with deep learning to predict contacts and serves as a baseline. The second method (MULTICOM-CONSTRUCT) uses our new alignment algorithm to generate deep multiple sequence alignment to derive coevolution-based features, which are integrated by a neural network method to predict contacts. The third method (MULTICOM-CLUSTER) is a consensus combination of the predictions of the first two methods. We evaluated our methods on 94 CASP12 domains. On a subset of 38 free-modeling domains, our methods achieved an average precision of up to 41.7% for top L/5 long-range contact predictions. The comparison of the three methods shows that the quality and effective depth of multiple sequence alignments, coevolution-based features, and machine learning integration of coevolution-based features and traditional features drive the quality of predicted protein contacts. On the full CASP12 dataset, the coevolution-based features alone can improve the average precision from 28.4% to 41.6%, and the machine learning integration of all the features further raises the precision to 56.3%, when top L/5 predicted long-range contacts are evaluated. And the correlation between the precision of contact prediction and the logarithm of the number of effective sequences in alignments is 0.66. © 2017 Wiley Periodicals, Inc.

Integrated multiple patch-clamp array chip via lateral cell trapping junctions

NASA Astrophysics Data System (ADS)

Seo, J.; Ionescu-Zanetti, C.; Diamond, J.; Lal, R.; Lee, L. P.

2004-03-01

We present an integrated multiple patch-clamp array chip by utilizing lateral cell trapping junctions. The intersectional design of a microfluidic network provides multiple cell addressing and manipulation sites for efficient electrophysiological measurements at a number of patch sites. The patch pores consist of openings in the sidewall of a main fluidic channel, and a membrane patch is drawn into a smaller horizontal channel. This device geometry not only minimizes capacitive coupling between the cell reservoir and the patch channel, but also allows simultaneous optical and electrical measurements of ion channel proteins. Evidence of the hydrodynamic placement of mammalian cells at the patch sites as well as measurements of patch sealing resistance is presented. Device fabrication is based on micromolding of polydimethylsiloxane, thus allowing inexpensive mass production of disposable high-throughput biochips.

Observation of ambipolar switching in a silver nanoparticle single-electron transistor with multiple molecular floating gates

NASA Astrophysics Data System (ADS)

Yamamoto, Makoto; Shinohara, Shuhei; Tamada, Kaoru; Ishii, Hisao; Noguchi, Yutaka

2016-03-01

Ambipolar switching behavior was observed in a silver nanoparticle (AgNP)-based single-electron transistor (SET) with tetra-tert-butyl copper phthalocyanine (ttbCuPc) as a molecular floating gate. Depending on the wavelength of the incident light, the stability diagram shifted to the negative and positive directions along the gate voltage axis. These results were explained by the photoinduced charging of ttbCuPc molecules in the vicinity of AgNPs. Moreover, multiple device states were induced by the light irradiation at a wavelength of 600 nm, suggesting that multiple ttbCuPc molecules individually worked as a floating gate.

Three-dimensional molecular mapping of a multiple emulsion by means of CARS microscopy.

PubMed

Meyer, Tobias; Akimov, Denis; Tarcea, Nicolae; Chatzipapadopoulos, Susana; Muschiolik, Gerald; Kobow, Jens; Schmitt, Michael; Popp, Jürgen

2008-02-07

Multiple emulsions consisting of water droplets dispersed in an oil phase containing emulsifier which is emulsified in an outer water phase (W/O/W) are of great interest in pharmacology for developing new drugs, in the nutrition sciences for designing functional food, and in biology as model systems for cell organelles such as liposomes. In the food industry multiple emulsions with high sugar content in the aqueous phase can be used for the production of sweets, because the high sugar content prevents deterioration. However, for these emulsions the refractive indexes of oil and aqueous phase are very similar. This seriously impedes the analysis of these emulsions, e.g., for process monitoring, because microscopic techniques based on transmission or reflection do not provide sufficient contrast. We have characterized the inner dispersed phase of concentrated W/O/W emulsions with the same refractive index of the three phases by micro Raman spectroscopy and investigated the composition and molecular distribution in water-oil-water emulsions by means of three-dimensional laser scanning CARS (coherent anti-Stokes Raman scattering) microscopy. CARS microscopy has been used to study water droplets dispersed in oil droplets at different Raman resonances to visualize different molecular species. Water droplets with a diameter of about 700 nm could clearly be visualized. The advantages of CARS microscopy for studying this particular system are emphasized by comparing this microscopic technique with conventional confocal reflection and transmission microscopies.

Integration of multiple determinants in the neuronal computation of economic values.

PubMed

Raghuraman, Anantha P; Padoa-Schioppa, Camillo

2014-08-27

Economic goods may vary on multiple dimensions (determinants). A central conjecture in decision neuroscience is that choices between goods are made by comparing subjective values computed through the integration of all relevant determinants. Previous work identified three groups of neurons in the orbitofrontal cortex (OFC) of monkeys engaged in economic choices: (1) offer value cells, which encode the value of individual offers; (2) chosen value cells, which encode the value of the chosen good; and (3) chosen juice cells, which encode the identity of the chosen good. In principle, these populations could be sufficient to generate a decision. Critically, previous work did not assess whether offer value cells (the putative input to the decision) indeed encode subjective values as opposed to physical properties of the goods, and/or whether offer value cells integrate multiple determinants. To address these issues, we recorded from the OFC while monkeys chose between risky outcomes. Confirming previous observations, three populations of neurons encoded the value of individual offers, the value of the chosen option, and the value-independent choice outcome. The activity of both offer value cells and chosen value cells encoded values defined by the integration of juice quantity and probability. Furthermore, both populations reflected the subjective risk attitude of the animals. We also found additional groups of neurons encoding the risk associated with a particular option, the risky nature of the chosen option, and whether the trial outcome was positive or negative. These results provide substantial support for the conjecture described above and for the involvement of OFC in good-based decisions. Copyright © 2014 the authors 0270-6474/14/3311583-21$15.00/0.

Multiple Sclerosis: Molecular Mechanisms and Therapeutic Opportunities

PubMed Central

Miljković, Djordje; Spasojević, Ivan

2013-01-01

Abstract The pathophysiology of multiple sclerosis (MS) involves several components: redox, inflammatory/autoimmune, vascular, and neurodegenerative. All of them are supported by the intertwined lines of evidence, and none of them should be written off. However, the exact mechanisms of MS initiation, its development, and progression are still elusive, despite the impressive pace by which the data on MS are accumulating. In this review, we will try to integrate the current facts and concepts, focusing on the role of redox changes and various reactive species in MS. Knowing the schedule of initial changes in pathogenic factors and the key turning points, as well as understanding the redox processes involved in MS pathogenesis is the way to enable MS prevention, early treatment, and the development of therapies that target specific pathophysiological components of the heterogeneous mechanisms of MS, which could alleviate the symptoms and hopefully stop MS. Pertinent to this, we will outline (i) redox processes involved in MS initiation; (ii) the role of reactive species in inflammation; (iii) prooxidative changes responsible for neurodegeneration; and (iv) the potential of antioxidative therapy. Antioxid. Redox Signal. 19, 2286–2334. PMID:23473637

THE MOLECULAR PATHOLOGY OF MELANOMA: AN INTEGRATED TAXONOMY OF MELANOCYTIC NEOPLASIA

PubMed Central

Bastian, Boris C.

2016-01-01

Melanomas are comprised of multiple biologically distinct categories, which differ in cell of origin, age of onset, clinical and histologic presentation, pattern of metastasis, ethnic distribution, causative role of UV radiation, predisposing germ line alterations, mutational processes, and patterns of somatic mutations. Neoplasms are initiated by gain of function mutations in one of several primary oncogenes, typically leading to benign melanocytic nevi with characteristic histologic features. The progression of nevi is restrained by multiple tumor suppressive mechanisms. Secondary genetic alterations override these barriers and promote intermediate or overtly malignant tumors along distinct progression trajectories. The current knowledge about pathogenesis, clinical, histological and genetic features of primary melanocytic neoplasms is reviewed and integrated into a taxonomic framework. PMID:24460190

Calcium Dysregulation and Homeostasis of Neural Calcium in the Molecular Mechanisms of Neurodegenerative Diseases Provide Multiple Targets for Neuroprotection

PubMed Central

Zündorf, Gregor

2011-01-01

Abstract The intracellular free calcium concentration subserves complex signaling roles in brain. Calcium cations (Ca2+) regulate neuronal plasticity underlying learning and memory and neuronal survival. Homo- and heterocellular control of Ca2+ homeostasis supports brain physiology maintaining neural integrity. Ca2+ fluxes across the plasma membrane and between intracellular organelles and compartments integrate diverse cellular functions. A vast array of checkpoints controls Ca2+, like G protein-coupled receptors, ion channels, Ca2+ binding proteins, transcriptional networks, and ion exchangers, in both the plasma membrane and the membranes of mitochondria and endoplasmic reticulum. Interactions between Ca2+ and reactive oxygen species signaling coordinate signaling, which can be either beneficial or detrimental. In neurodegenerative disorders, cellular Ca2+-regulating systems are compromised. Oxidative stress, perturbed energy metabolism, and alterations of disease-related proteins result in Ca2+-dependent synaptic dysfunction, impaired plasticity, and neuronal demise. We review Ca2+ control processes relevant for physiological and pathophysiological conditions in brain tissue. Dysregulation of Ca2+ is decisive for brain cell death and degeneration after ischemic stroke, long-term neurodegeneration in Alzheimer's disease, Parkinson's disease, Huntington's disease, inflammatory processes, such as in multiple sclerosis, epileptic sclerosis, and leucodystrophies. Understanding the underlying molecular processes is of critical importance for the development of novel therapeutic strategies to prevent neurodegeneration and confer neuroprotection. Antioxid. Redox Signal. 14, 1275–1288. PMID:20615073

Smart Phase Tuning in Microwave Photonic Integrated Circuits Toward Automated Frequency Multiplication by Design

NASA Astrophysics Data System (ADS)

Nabavi, N.

2018-07-01

The author investigates the monitoring methods for fine adjustment of the previously proposed on-chip architecture for frequency multiplication and translation of harmonics by design. Digital signal processing (DSP) algorithms are utilized to create an optimized microwave photonic integrated circuit functionality toward automated frequency multiplication. The implemented DSP algorithms are formed on discrete Fourier transform and optimization-based algorithms (Greedy and gradient-based algorithms), which are analytically derived and numerically compared based on the accuracy and speed of convergence criteria.

An Integrative Framework for the Analysis of Multiple and Multimodal Representations for Meaning-Making in Science Education

ERIC Educational Resources Information Center

Tang, Kok-Sing; Delgado, Cesar; Moje, Elizabeth Birr

2014-01-01

This paper presents an integrative framework for analyzing science meaning-making with representations. It integrates the research on multiple representations and multimodal representations by identifying and leveraging the differences in their units of analysis in two dimensions: timescale and compositional grain size. Timescale considers the…

Surface induced molecular dynamics of thin lipid films confined to submicron cavities: A 1H multiple-quantum NMR study

NASA Astrophysics Data System (ADS)

Jagadeesh, B.; Prabhakar, A.; Demco, D. E.; Buda, A.; Blümich, B.

2005-03-01

The dynamics and molecular order of thin lipid (lecithin) films confined to 200, 100 and 20 nm cylindrical pores with varying surface coverage, were investigated by 1H multiple-quantum NMR. The results show that the molecular dynamics in the surface controlled layers are less hindered compared to those in the bulk. Dynamic heterogeneity among terminal CH 3 groups is evident. Enhanced dynamic freedom is observed for films with area per molecule, ˜ 128 Å 2. The results are discussed in terms of changes in the lipid molecular organization with respect to surface concentration, its plausible motional modes and dynamic heterogeneity.

Assessing District Energy Systems Performance Integrated with Multiple Thermal Energy Storages

NASA Astrophysics Data System (ADS)

Rezaie, Behnaz

The goal of this study is to examine various energy resources in district energy (DE) systems and then DE system performance development by means of multiple thermal energy storages (TES) application. This study sheds light on areas not yet investigated precisely in detail. Throughout the research, major components of the heat plant, energy suppliers of the DE systems, and TES characteristics are separately examined; integration of various configurations of the multiple TESs in the DE system is then analysed. In the first part of the study, various sources of energy are compared, in a consistent manner, financially and environmentally. The TES performance is then assessed from various aspects. Then, TES(s) and DE systems with several sources of energy are integrated, and are investigated as a heat process centre. The most efficient configurations of the multiple TESs integrated with the DE system are investigated. Some of the findings of this study are applied on an actual DE system. The outcomes of this study provide insight for researchers and engineers who work in this field, as well as policy makers and project managers who are decision-makers. The accomplishments of the study are original developments TESs and DE systems. As an original development the Enviro-Economic Function, to balance the economic and environmental aspects of energy resources technologies in DE systems, is developed; various configurations of multiple TESs, including series, parallel, and general grid, are developed. The developed related functions are discharge temperature and energy of the TES, and energy and exergy efficiencies of the TES. The TES charging and discharging behavior of TES instantaneously is also investigated to obtain the charging temperature, the maximum charging temperature, the charging energy flow, maximum heat flow capacity, the discharging temperature, the minimum charging temperature, the discharging energy flow, the maximum heat flow capacity, and performance

Massively Parallel, Molecular Analysis Platform Developed Using a CMOS Integrated Circuit With Biological Nanopores

PubMed Central

Roever, Stefan

2012-01-01

A massively parallel, low cost molecular analysis platform will dramatically change the nature of protein, molecular and genomics research, DNA sequencing, and ultimately, molecular diagnostics. An integrated circuit (IC) with 264 sensors was fabricated using standard CMOS semiconductor processing technology. Each of these sensors is individually controlled with precision analog circuitry and is capable of single molecule measurements. Under electronic and software control, the IC was used to demonstrate the feasibility of creating and detecting lipid bilayers and biological nanopores using wild type α-hemolysin. The ability to dynamically create bilayers over each of the sensors will greatly accelerate pore development and pore mutation analysis. In addition, the noise performance of the IC was measured to be 30fA(rms). With this noise performance, single base detection of DNA was demonstrated using α-hemolysin. The data shows that a single molecule, electrical detection platform using biological nanopores can be operationalized and can ultimately scale to millions of sensors. Such a massively parallel platform will revolutionize molecular analysis and will completely change the field of molecular diagnostics in the future.

Multiple Simulated Annealing-Molecular Dynamics (MSA-MD) for Conformational Space Search of Peptide and Miniprotein

PubMed Central

Hao, Ge-Fei; Xu, Wei-Fang; Yang, Sheng-Gang; Yang, Guang-Fu

2015-01-01

Protein and peptide structure predictions are of paramount importance for understanding their functions, as well as the interactions with other molecules. However, the use of molecular simulation techniques to directly predict the peptide structure from the primary amino acid sequence is always hindered by the rough topology of the conformational space and the limited simulation time scale. We developed here a new strategy, named Multiple Simulated Annealing-Molecular Dynamics (MSA-MD) to identify the native states of a peptide and miniprotein. A cluster of near native structures could be obtained by using the MSA-MD method, which turned out to be significantly more efficient in reaching the native structure compared to continuous MD and conventional SA-MD simulation. PMID:26492886

Integrating Multiple Teaching Methods into a General Chemistry Classroom

NASA Astrophysics Data System (ADS)

Francisco, Joseph S.; Nicoll, Gayle; Trautmann, Marcella

1998-02-01

In addition to the traditional lecture format, three other teaching strategies (class discussions, concept maps, and cooperative learning) were incorporated into a freshman level general chemistry course. Student perceptions of their involvement in each of the teaching methods, as well as their perceptions of the utility of each method were used to assess the effectiveness of the integration of the teaching strategies as received by the students. Results suggest that each strategy serves a unique purpose for the students and increased student involvement in the course. These results indicate that the multiple teaching strategies were well received by the students and that all teaching strategies are necessary for students to get the most out of the course.

Integrative taxonomy by molecular species delimitation: multi-locus data corroborate a new species of Balkan Drusinae micro-endemics.

PubMed

Vitecek, Simon; Kučinić, Mladen; Previšić, Ana; Živić, Ivana; Stojanović, Katarina; Keresztes, Lujza; Bálint, Miklós; Hoppeler, Felicitas; Waringer, Johann; Graf, Wolfram; Pauls, Steffen U

2017-06-06

Taxonomy offers precise species identification and delimitation and thus provides basic information for biological research, e.g. through assessment of species richness. The importance of molecular taxonomy, i.e., the identification and delimitation of taxa based on molecular markers, has increased in the past decade. Recently developed exploratory tools now allow estimating species-level diversity in multi-locus molecular datasets. Here we use molecular species delimitation tools that either quantify differences in intra- and interspecific variability of loci, or divergence times within and between species, or perform coalescent species tree inference to estimate species-level entities in molecular genetic datasets. We benchmark results from these methods against 14 morphologically readily differentiable species of a well-defined subgroup of the diverse Drusinae subfamily (Trichoptera, Limnephilidae). Using a 3798 bp (6 loci) molecular data set we aim to corroborate a geographically isolated new species by integrating comparative morphological studies and molecular taxonomy. Our results indicate that only multi-locus species delimitation provides taxonomically relevant information. The data further corroborate the new species Drusus zivici sp. nov. We provide differential diagnostic characters and describe the male, female and larva of this new species and discuss diversity patterns of Drusinae in the Balkans. We further discuss potential and significance of molecular species delimitation. Finally we argue that enhancing collaborative integrative taxonomy will accelerate assessment of global diversity and completion of reference libraries for applied fields, e.g., conservation and biomonitoring.

Evidence for nucleosynthetic enrichment of the protosolar molecular cloud core by multiple supernova events.

PubMed

Schiller, Martin; Paton, Chad; Bizzarro, Martin

2015-01-15

The presence of isotope heterogeneity of nucleosynthetic origin amongst meteorites and their components provides a record of the diverse stars that contributed matter to the protosolar molecular cloud core. Understanding how and when the solar system's nucleosynthetic heterogeneity was established and preserved within the solar protoplanetary disk is critical for unraveling the earliest formative stages of the solar system. Here, we report calcium and magnesium isotope measurements of primitive and differentiated meteorites as well as various types of refractory inclusions, including refractory inclusions (CAIs) formed with the canonical 26 Al/ 27 Al of ~5 × 10 -5 ( 26 Al decays to 26 Mg with a half-life of ~0.73 Ma) and CAIs that show fractionated and unidentified nuclear effects (FUN-CAIs) to understand the origin of the solar system's nucleosynthetic heterogeneity. Bulk analyses of primitive and differentiated meteorites along with canonical and FUN-CAIs define correlated, mass-independent variations in 43 Ca, 46 Ca and 48 Ca. Moreover, sequential dissolution experiments of the Ivuna carbonaceous chondrite aimed at identifying the nature and number of presolar carriers of isotope anomalies within primitive meteorites have detected the presence of multiple carriers of the short-lived 26 Al nuclide as well as carriers of anomalous and uncorrelated 43 Ca, 46 Ca and 48 Ca compositions, which requires input from multiple and recent supernovae sources. We infer that the solar system's correlated nucleosynthetic variability reflects unmixing of old, galactically-inherited homogeneous dust from a new, supernovae-derived dust component formed shortly prior to or during the evolution of the giant molecular cloud parental to the protosolar molecular cloud core. This implies that similarly to 43 Ca, 46 Ca and 48 Ca, the short-lived 26 Al nuclide was heterogeneously distributed in the inner solar system at the time of CAI formation.

Photometric Detection of Multiple Populations in Globular Clusters Using Integrated Light

NASA Astrophysics Data System (ADS)

Bowman, William P.; Pilachowski, Catherine A.; van Zee, Liese; Winans, Amanda; Ciardullo, Robin; Gronwall, Caryl

2017-10-01

We investigate the multiple stellar populations of the globular clusters (GCs) M3, M5, M13, and M71 using {g}{\\prime } and intermediate-band CN-λ 3883 photometry obtained with the WIYN 0.9 m telescope on Kitt Peak. We find a strong correlation between red giant stars’ CN-{g}{\\prime } colors and their spectroscopic sodium abundances, thus demonstrating the efficacy of the two-filter system for stellar population studies. In all four clusters, the observed spread in red giant branch CN-{g}{\\prime } colors is wider than that expected from photometric uncertainty, confirming the well-known chemical inhomogeneity of these systems. M3 and M13 show clear evidence for a radial dependence in the CN-band strengths of its red giants, while the evidence for such a radial dependence of CN strengths in M5 is ambiguous. Our data suggest that the dynamically old, relatively metal-rich M71 system is well mixed, as it shows no evidence for chemical segregation. Finally, we measure the radial gradients in the integrated CN-{g}{\\prime } color of the clusters and find that such gradients are easily detectable in the integrated light. We suggest that photometric observations of color gradients within GCs throughout the Local Group can be used to characterize their multiple populations, and thereby constrain the formation history of GCs in different galactic environments.

Integration of multi-omics data for integrative gene regulatory network inference.

PubMed

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun; Kang, Mingon

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called 'multi-omics data', that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN's capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed.

Integration of multi-omics data for integrative gene regulatory network inference

PubMed Central

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called ‘multi-omics data’, that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN’s capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed. PMID:29354189

Penalized differential pathway analysis of integrative oncogenomics studies.

PubMed

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

2014-04-01

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

BubbleGUM: automatic extraction of phenotype molecular signatures and comprehensive visualization of multiple Gene Set Enrichment Analyses.

PubMed

Spinelli, Lionel; Carpentier, Sabrina; Montañana Sanchis, Frédéric; Dalod, Marc; Vu Manh, Thien-Phong

2015-10-19

Recent advances in the analysis of high-throughput expression data have led to the development of tools that scaled-up their focus from single-gene to gene set level. For example, the popular Gene Set Enrichment Analysis (GSEA) algorithm can detect moderate but coordinated expression changes of groups of presumably related genes between pairs of experimental conditions. This considerably improves extraction of information from high-throughput gene expression data. However, although many gene sets covering a large panel of biological fields are available in public databases, the ability to generate home-made gene sets relevant to one's biological question is crucial but remains a substantial challenge to most biologists lacking statistic or bioinformatic expertise. This is all the more the case when attempting to define a gene set specific of one condition compared to many other ones. Thus, there is a crucial need for an easy-to-use software for generation of relevant home-made gene sets from complex datasets, their use in GSEA, and the correction of the results when applied to multiple comparisons of many experimental conditions. We developed BubbleGUM (GSEA Unlimited Map), a tool that allows to automatically extract molecular signatures from transcriptomic data and perform exhaustive GSEA with multiple testing correction. One original feature of BubbleGUM notably resides in its capacity to integrate and compare numerous GSEA results into an easy-to-grasp graphical representation. We applied our method to generate transcriptomic fingerprints for murine cell types and to assess their enrichments in human cell types. This analysis allowed us to confirm homologies between mouse and human immunocytes. BubbleGUM is an open-source software that allows to automatically generate molecular signatures out of complex expression datasets and to assess directly their enrichment by GSEA on independent datasets. Enrichments are displayed in a graphical output that helps

Integrating different data types by regularized unsupervised multiple kernel learning with application to cancer subtype discovery.

PubMed

Speicher, Nora K; Pfeifer, Nico

2015-06-15

Despite ongoing cancer research, available therapies are still limited in quantity and effectiveness, and making treatment decisions for individual patients remains a hard problem. Established subtypes, which help guide these decisions, are mainly based on individual data types. However, the analysis of multidimensional patient data involving the measurements of various molecular features could reveal intrinsic characteristics of the tumor. Large-scale projects accumulate this kind of data for various cancer types, but we still lack the computational methods to reliably integrate this information in a meaningful manner. Therefore, we apply and extend current multiple kernel learning for dimensionality reduction approaches. On the one hand, we add a regularization term to avoid overfitting during the optimization procedure, and on the other hand, we show that one can even use several kernels per data type and thereby alleviate the user from having to choose the best kernel functions and kernel parameters for each data type beforehand. We have identified biologically meaningful subgroups for five different cancer types. Survival analysis has revealed significant differences between the survival times of the identified subtypes, with P values comparable or even better than state-of-the-art methods. Moreover, our resulting subtypes reflect combined patterns from the different data sources, and we demonstrate that input kernel matrices with only little information have less impact on the integrated kernel matrix. Our subtypes show different responses to specific therapies, which could eventually assist in treatment decision making. An executable is available upon request. © The Author 2015. Published by Oxford University Press.

Multiscale Integration of -Omic, Imaging, and Clinical Data in Biomedical Informatics

PubMed Central

Phan, John H.; Quo, Chang F.; Cheng, Chihwen; Wang, May Dongmei

2016-01-01

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data. PMID:23231990

Multiscale integration of -omic, imaging, and clinical data in biomedical informatics.

PubMed

Phan, John H; Quo, Chang F; Cheng, Chihwen; Wang, May Dongmei

2012-01-01

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.

A modified precise integration method for transient dynamic analysis in structural systems with multiple damping models

NASA Astrophysics Data System (ADS)

Ding, Zhe; Li, Li; Hu, Yujin

2018-01-01

Sophisticated engineering systems are usually assembled by subcomponents with significantly different levels of energy dissipation. Therefore, these damping systems often contain multiple damping models and lead to great difficulties in analyzing. This paper aims at developing a time integration method for structural systems with multiple damping models. The dynamical system is first represented by a generally damped model. Based on this, a new extended state-space method for the damped system is derived. A modified precise integration method with Gauss-Legendre quadrature is then proposed. The numerical stability and accuracy of the proposed integration method are discussed in detail. It is verified that the method is conditionally stable and has inherent algorithmic damping, period error and amplitude decay. Numerical examples are provided to assess the performance of the proposed method compared with other methods. It is demonstrated that the method is more accurate than other methods with rather good efficiency and the stable condition is easy to be satisfied in practice.

Detectable states, cycle fluxes, and motility scaling of molecular motor kinesin: An integrative kinetic graph theory analysis

NASA Astrophysics Data System (ADS)

Ren, Jie

2017-12-01

The process by which a kinesin motor couples its ATPase activity with concerted mechanical hand-over-hand steps is a foremost topic of molecular motor physics. Two major routes toward elucidating kinesin mechanisms are the motility performance characterization of velocity and run length, and single-molecular state detection experiments. However, these two sets of experimental approaches are largely uncoupled to date. Here, we introduce an integrative motility state analysis based on a theorized kinetic graph theory for kinesin, which, on one hand, is validated by a wealth of accumulated motility data, and, on the other hand, allows for rigorous quantification of state occurrences and chemomechanical cycling probabilities. An interesting linear scaling for kinesin motility performance across species is discussed as well. An integrative kinetic graph theory analysis provides a powerful tool to bridge motility and state characterization experiments, so as to forge a unified effort for the elucidation of the working mechanisms of molecular motors.

Tools and Models for Integrating Multiple Cellular Networks

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

Gerstein, Mark

2015-11-06

In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novelmore » algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have

Integration of Molecular Dynamics Based Predictions into the Optimization of De Novo Protein Designs: Limitations and Benefits.

PubMed

Carvalho, Henrique F; Barbosa, Arménio J M; Roque, Ana C A; Iranzo, Olga; Branco, Ricardo J F

2017-01-01

Recent advances in de novo protein design have gained considerable insight from the intrinsic dynamics of proteins, based on the integration of molecular dynamics simulations protocols on the state-of-the-art de novo protein design protocols used nowadays. With this protocol we illustrate how to set up and run a molecular dynamics simulation followed by a functional protein dynamics analysis. New users will be introduced to some useful open-source computational tools, including the GROMACS molecular dynamics simulation software package and ProDy for protein structural dynamics analysis.

Modern drug design: the implication of using artificial neuronal networks and multiple molecular dynamic simulations

NASA Astrophysics Data System (ADS)

Yakovenko, Oleksandr; Jones, Steven J. M.

2018-01-01

We report the implementation of molecular modeling approaches developed as a part of the 2016 Grand Challenge 2, the blinded competition of computer aided drug design technologies held by the D3R Drug Design Data Resource (https://drugdesigndata.org/). The challenge was focused on the ligands of the farnesoid X receptor (FXR), a highly flexible nuclear receptor of the cholesterol derivative chenodeoxycholic acid. FXR is considered an important therapeutic target for metabolic, inflammatory, bowel and obesity related diseases (Expert Opin Drug Metab Toxicol 4:523-532, 2015), but in the context of this competition it is also interesting due to the significant ligand-induced conformational changes displayed by the protein. To deal with these conformational changes we employed multiple simulations of molecular dynamics (MD). Our MD-based protocols were top-ranked in estimating the free energy of binding of the ligands and FXR protein. Our approach was ranked second in the prediction of the binding poses where we also combined MD with molecular docking and artificial neural networks. Our approach showed mediocre results for high-throughput scoring of interactions.

Integrating Multiple Criteria Evaluation and GIS in Ecotourism: a Review

NASA Astrophysics Data System (ADS)

Mohd, Z. H.; Ujang, U.

2016-09-01

The concept of 'Eco-tourism' is increasingly heard in recent decades. Ecotourism is one adventure that environmentally responsible intended to appreciate the nature experiences and cultures. Ecotourism should have low impact on environment and must contribute to the prosperity of local residents. This article reviews the use of Multiple Criteria Evaluation (MCE) and Geographic Information System (GIS) in ecotourism. Multiple criteria evaluation mostly used to land suitability analysis or fulfill specific objectives based on various attributes that exist in the selected area. To support the process of environmental decision making, the application of GIS is used to display and analysis the data through Analytic Hierarchy Process (AHP). Integration between MCE and GIS tool is important to determine the relative weight for the criteria used objectively. With the MCE method, it can resolve the conflict between recreation and conservation which is to minimize the environmental and human impact. Most studies evidences that the GIS-based AHP as a multi criteria evaluation is a strong and effective in tourism planning which can aid in the development of ecotourism industry effectively.

Rapid and selective extraction of multiple macrolide antibiotics in foodstuff samples based on magnetic molecularly imprinted polymers.

PubMed

Zhou, Yusun; Zhou, Tingting; Jin, Hua; Jing, Tao; Song, Bin; Zhou, Yikai; Mei, Surong; Lee, Yong-Ill

2015-05-01

Magnetic molecularly imprinted polymers (MMIPs) were prepared based on surface molecular imprinting using erythromycin (ERY) as template molecule and Fe3O4 nanoparticles as support substrate. The MMIPs possessed high adsorption capacity of 94.1 mg/g for ERY and the imprinting factor was 11.9 indicating good imprinted effect for ERY. Selective evaluation demonstrated favorable selectivity of MMIPs for multiple macrolide antibiotics (MACs). Using MMIPs as adsorptive material, a rapid and convenient magnetic solid-phase extraction (MSPE) procedure was established for simultaneous and selective separation of six MACs in pork, fish and shrimp samples, then the MACs was subjected to high-performance liquid chromatography-ultraviolet (HPLC-UV) analysis. At different fortified concentrations, the extraction recoveries could reach 89.1% and the relative standard deviations were lower than 12.4%. Chromatogram revealed the response signals of MACs in spiked samples were greatly enhanced and matrix interferences were effectively eliminated after treatment with MSPE. The proposed MSPE procedure coupled with HPLC-UV realized selective and sensitive determination of multiple MACs in foodstuff samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Multiple-clone infections of Plasmodium vivax: definition of a panel of markers for molecular epidemiology.

PubMed

de Souza, Aracele M; de Araújo, Flávia C F; Fontes, Cor J F; Carvalho, Luzia H; de Brito, Cristiana F A; de Sousa, Taís N

2015-08-25

Plasmodium vivax infections commonly contain multiple genetically distinct parasite clones. The detection of multiple-clone infections depends on several factors, such as the accuracy of the genotyping method, and the type and number of the molecular markers analysed. Characterizing the multiplicity of infection has broad implications that range from population genetic studies of the parasite to malaria treatment and control. This study compared and evaluated the efficiency of neutral and non-neutral markers that are widely used in studies of molecular epidemiology to detect the multiplicity of P. vivax infection. The performance of six markers was evaluated using 11 mixtures of DNA with well-defined proportions of two different parasite genotypes for each marker. These mixtures were generated by mixing cloned PCR products or patient-derived genomic DNA. In addition, 51 samples of natural infections from the Brazil were genotyped for all markers. The PCR-capillary electrophoresis-based method was used to permit direct comparisons among the markers. The criteria for differentiating minor peaks from artifacts were also evaluated. The analysis of DNA mixtures showed that the tandem repeat MN21 and the polymorphic blocks 2 (msp1B2) and 10 (msp1B10) of merozoite surface protein-1 allowed for the estimation of the expected ratio of both alleles in the majority of preparations. Nevertheless, msp1B2 was not able to detect the majority of multiple-clone infections in field samples; it identified only 6 % of these infections. The merozoite surface protein-3 alpha and microsatellites (PvMS6 and PvMS7) did not accurately estimate the relative clonal proportions in artificial mixtures, but the microsatellites performed well in detecting natural multiple-clone infections. Notably, the use of a less stringent criterion to score rare alleles significantly increased the sensitivity of the detection of multi-clonal infections. Depending on the type of marker used, a considerable

Integrated modeling and analysis of the multiple electromechanical couplings for the direct driven feed system in machine tools

NASA Astrophysics Data System (ADS)

Yang, Xiaojun; Lu, Dun; Liu, Hui; Zhao, Wanhua

2018-06-01

The complicated electromechanical coupling phenomena due to different kinds of causes have significant influences on the dynamic precision of the direct driven feed system in machine tools. In this paper, a novel integrated modeling and analysis method of the multiple electromechanical couplings for the direct driven feed system in machine tools is presented. At first, four different kinds of electromechanical coupling phenomena in the direct driven feed system are analyzed systematically. Then a novel integrated modeling and analysis method of the electromechanical coupling which is influenced by multiple factors is put forward. In addition, the effects of multiple electromechanical couplings on the dynamic precision of the feed system and their main influencing factors are compared and discussed, respectively. Finally, the results of modeling and analysis are verified by the experiments. It finds out that multiple electromechanical coupling loops, which are overlapped and influenced by each other, are the main reasons of the displacement fluctuations in the direct driven feed system.

A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets.

PubMed

Carrig, Madeline M; Manrique-Vallier, Daniel; Ranby, Krista W; Reiter, Jerome P; Hoyle, Rick H

2015-01-01

Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches.

A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets

PubMed Central

Carrig, Madeline M.; Manrique-Vallier, Daniel; Ranby, Krista W.; Reiter, Jerome P.; Hoyle, Rick H.

2015-01-01

Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches. PMID:26257437

Quantum Chemically Estimated Abraham Solute Parameters Using Multiple Solvent-Water Partition Coefficients and Molecular Polarizability.

PubMed

Liang, Yuzhen; Xiong, Ruichang; Sandler, Stanley I; Di Toro, Dominic M

2017-09-05

Polyparameter Linear Free Energy Relationships (pp-LFERs), also called Linear Solvation Energy Relationships (LSERs), are used to predict many environmentally significant properties of chemicals. A method is presented for computing the necessary chemical parameters, the Abraham parameters (AP), used by many pp-LFERs. It employs quantum chemical calculations and uses only the chemical's molecular structure. The method computes the Abraham E parameter using density functional theory computed molecular polarizability and the Clausius-Mossotti equation relating the index refraction to the molecular polarizability, estimates the Abraham V as the COSMO calculated molecular volume, and computes the remaining AP S, A, and B jointly with a multiple linear regression using sixty-five solvent-water partition coefficients computed using the quantum mechanical COSMO-SAC solvation model. These solute parameters, referred to as Quantum Chemically estimated Abraham Parameters (QCAP), are further adjusted by fitting to experimentally based APs using QCAP parameters as the independent variables so that they are compatible with existing Abraham pp-LFERs. QCAP and adjusted QCAP for 1827 neutral chemicals are included. For 24 solvent-water systems including octanol-water, predicted log solvent-water partition coefficients using adjusted QCAP have the smallest root-mean-square errors (RMSEs, 0.314-0.602) compared to predictions made using APs estimated using the molecular fragment based method ABSOLV (0.45-0.716). For munition and munition-like compounds, adjusted QCAP has much lower RMSE (0.860) than does ABSOLV (4.45) which essentially fails for these compounds.

Integration of a Radiosensitivity Molecular Signature Into the Assessment of Local Recurrence Risk in Breast Cancer

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

Torres-Roca, Javier F., E-mail: javier.torresroca@moffitt.org; Department of Chemical Biology and Molecular Medicine, Moffitt Cancer Center, Tampa, Florida; Fulp, William J.

Purpose: Recently, we developed radiosensitivity (RSI), a clinically validated molecular signature that estimates tumor radiosensitivity. In the present study, we tested whether integrating RSI with the molecular subtype refines the classification of local recurrence (LR) risk in breast cancer. Methods and Materials: RSI and molecular subtype were evaluated in 343 patients treated with breast-conserving therapy that included whole-breast radiation therapy with or without a tumor bed boost (dose range 45-72 Gy). The follow-up period for patients without recurrence was 10 years. The clinical endpoint was LR-free survival. Results: Although RSI did not uniformly predict for LR across the entire cohort, combining RSImore » and the molecular subtype identified a subpopulation with an increased risk of LR: triple negative (TN) and radioresistant (reference TN-radioresistant, hazard ratio [HR] 0.37, 95% confidence interval [CI] 0.15-0.92, P=.02). TN patients who were RSI-sensitive/intermediate had LR rates similar to those of luminal (LUM) patients (HR 0.86, 95% CI 0.47-1.57, P=.63). On multivariate analysis, combined RSI and molecular subtype (P=.004) and age (P=.001) were the most significant predictors of LR. In contrast, integrating RSI into the LUM subtype did not identify additional risk groups. We hypothesized that radiation dose escalation was affecting radioresistance in the LUM subtype and serving as a confounder. An increased radiation dose decreased LR only in the luminal-resistant (LUM-R) subset (HR 0.23, 95% CI 0.05-0.98, P=.03). On multivariate analysis, the radiation dose was an independent variable only in the LUMA/B-RR subset (HR 0.025, 95% CI 0.001-0.946, P=.046), along with age (P=.008), T stage (P=.004), and chemotherapy (P=.008). Conclusions: The combined molecular subtype–RSI identified a novel molecular subpopulation (TN and radioresistant) with an increased risk of LR after breast-conserving therapy. We propose that the combination of RSI

Technology Integration in a One-to-One Laptop Initiative: A Multiple Case Study Analysis

ERIC Educational Resources Information Center

Jones, Marsha B.

2013-01-01

The purpose of this multiple case study analysis was to examine teachers' experiences and perceptions in order to understand what actions and interactions supported or inhibited technology integration during a one-to-one laptop initiative. This research sought to gain teachers' perspectives on the challenges and successes they faced as classroom…

Origin of multiple band gap values in single width nanoribbons

PubMed Central

Goyal, Deepika; Kumar, Shailesh; Shukla, Alok; Kumar, Rakesh

2016-01-01

Deterministic band gap in quasi-one-dimensional nanoribbons is prerequisite for their integrated functionalities in high performance molecular-electronics based devices. However, multiple band gaps commonly observed in graphene nanoribbons of the same width, fabricated in same slot of experiments, remain unresolved, and raise a critical concern over scalable production of pristine and/or hetero-structure nanoribbons with deterministic properties and functionalities for plethora of applications. Here, we show that a modification in the depth of potential wells in the periodic direction of a supercell on relative shifting of passivating atoms at the edges is the origin of multiple band gap values in nanoribbons of the same width in a crystallographic orientation, although they carry practically the same ground state energy. The results are similar when calculations are extended from planar graphene to buckled silicene nanoribbons. Thus, the findings facilitate tuning of the electronic properties of quasi-one-dimensional materials such as bio-molecular chains, organic and inorganic nanoribbons by performing edge engineering. PMID:27808172

Antibody-controlled actuation of DNA-based molecular circuits.

PubMed

Engelen, Wouter; Meijer, Lenny H H; Somers, Bram; de Greef, Tom F A; Merkx, Maarten

2017-02-17

DNA-based molecular circuits allow autonomous signal processing, but their actuation has relied mostly on RNA/DNA-based inputs, limiting their application in synthetic biology, biomedicine and molecular diagnostics. Here we introduce a generic method to translate the presence of an antibody into a unique DNA strand, enabling the use of antibodies as specific inputs for DNA-based molecular computing. Our approach, antibody-templated strand exchange (ATSE), uses the characteristic bivalent architecture of antibodies to promote DNA-strand exchange reactions both thermodynamically and kinetically. Detailed characterization of the ATSE reaction allowed the establishment of a comprehensive model that describes the kinetics and thermodynamics of ATSE as a function of toehold length, antibody-epitope affinity and concentration. ATSE enables the introduction of complex signal processing in antibody-based diagnostics, as demonstrated here by constructing molecular circuits for multiplex antibody detection, integration of multiple antibody inputs using logic gates and actuation of enzymes and DNAzymes for signal amplification.

Antibody-controlled actuation of DNA-based molecular circuits

NASA Astrophysics Data System (ADS)

Engelen, Wouter; Meijer, Lenny H. H.; Somers, Bram; de Greef, Tom F. A.; Merkx, Maarten

2017-02-01

DNA-based molecular circuits allow autonomous signal processing, but their actuation has relied mostly on RNA/DNA-based inputs, limiting their application in synthetic biology, biomedicine and molecular diagnostics. Here we introduce a generic method to translate the presence of an antibody into a unique DNA strand, enabling the use of antibodies as specific inputs for DNA-based molecular computing. Our approach, antibody-templated strand exchange (ATSE), uses the characteristic bivalent architecture of antibodies to promote DNA-strand exchange reactions both thermodynamically and kinetically. Detailed characterization of the ATSE reaction allowed the establishment of a comprehensive model that describes the kinetics and thermodynamics of ATSE as a function of toehold length, antibody-epitope affinity and concentration. ATSE enables the introduction of complex signal processing in antibody-based diagnostics, as demonstrated here by constructing molecular circuits for multiplex antibody detection, integration of multiple antibody inputs using logic gates and actuation of enzymes and DNAzymes for signal amplification.

Understanding and Integrating Multiple Science Texts: Summary Tasks Are Sometimes Better than Argument Tasks

ERIC Educational Resources Information Center

Gil, Laura; Braten, Ivar; Vidal-Abarca, Eduardo; Stromso, Helge I.

2010-01-01

One of the major challenges of a knowledge society is that students as well as other citizens must learn to understand and integrate information from multiple textual sources. Still, task and reader characteristics that may facilitate or constrain such intertextual processes are not well understood by researchers. In this study, we compare the…

Enhanced sampling by multiple molecular dynamics trajectories: carbonmonoxy myoglobin 10 micros A0-->A(1-3) transition from ten 400 picosecond simulations.

PubMed

Loccisano, Anne E; Acevedo, Orlando; DeChancie, Jason; Schulze, Brita G; Evanseck, Jeffrey D

2004-05-01

The utility of multiple trajectories to extend the time scale of molecular dynamics simulations is reported for the spectroscopic A-states of carbonmonoxy myoglobin (MbCO). Experimentally, the A0-->A(1-3) transition has been observed to be 10 micros at 300 K, which is beyond the time scale of standard molecular dynamics simulations. To simulate this transition, 10 short (400 ps) and two longer time (1.2 ns) molecular dynamics trajectories, starting from five different crystallographic and solution phase structures with random initial velocities centered in a 37 A radius sphere of water, have been used to sample the native-fold of MbCO. Analysis of the ensemble of structures gathered over the cumulative 5.6 ns reveals two biomolecular motions involving the side chains of His64 and Arg45 to explain the spectroscopic states of MbCO. The 10 micros A0-->A(1-3) transition involves the motion of His64, where distance between His64 and CO is found to vary up to 8.8 +/- 1.0 A during the transition of His64 from the ligand (A(1-3)) to bulk solvent (A0). The His64 motion occurs within a single trajectory only once, however the multiple trajectories populate the spectroscopic A-states fully. Consequently, multiple independent molecular dynamics simulations have been found to extend biomolecular motion from 5 ns of total simulation to experimental phenomena on the microsecond time scale.

The Need for Integrated Approaches in Metabolic Engineering

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

Lechner, Anna; Brunk, Elizabeth; Keasling, Jay D.

This review highlights state-of-the-art procedures for heterologous small-molecule biosynthesis, the associated bottlenecks, and new strategies that have the potential to accelerate future accomplishments in metabolic engineering. We emphasize that a combination of different approaches over multiple time and size scales must b e considered for successful pathway engineering in a heterologous host. We have classified these optimization procedures based on the "system" that is being manipulated: transcriptome, translatome, proteome, or reactome. By bridging multiple disciplines, including molecular biology, biochemistry, biophysics, and computational sciences, we can create an integral framework for the discovery and implementation of novel biosynthetic production routes.

The Need for Integrated Approaches in Metabolic Engineering

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

Lechner, Anna; Brunk, Elizabeth; Keasling, Jay D.

Highlights include state-of-the-art procedures for heterologous small-molecule biosynthesis, the associated bottlenecks, and new strategies that have the potential to accelerate future accomplishments in metabolic engineering. A combination of different approaches over multiple time and size scales must be considered for successful pathway engineering in a heterologous host. We have classified these optimization procedures based on the “system” that is being manipulated: transcriptome, translatome, proteome, or reactome. Here, by bridging multiple disciplines, including molecular biology, biochemistry, biophysics, and computational sciences, we can create an integral framework for the discovery and implementation of novel biosynthetic production routes.

The Need for Integrated Approaches in Metabolic Engineering

DOE PAGES

Lechner, Anna; Brunk, Elizabeth; Keasling, Jay D.

2016-08-15

Highlights include state-of-the-art procedures for heterologous small-molecule biosynthesis, the associated bottlenecks, and new strategies that have the potential to accelerate future accomplishments in metabolic engineering. A combination of different approaches over multiple time and size scales must be considered for successful pathway engineering in a heterologous host. We have classified these optimization procedures based on the “system” that is being manipulated: transcriptome, translatome, proteome, or reactome. Here, by bridging multiple disciplines, including molecular biology, biochemistry, biophysics, and computational sciences, we can create an integral framework for the discovery and implementation of novel biosynthetic production routes.

A multiple index integrating different levels of organization.

PubMed

Cortes, Rui; Hughes, Samantha; Coimbra, Ana; Monteiro, Sandra; Pereira, Vítor; Lopes, Marisa; Pereira, Sandra; Pinto, Ana; Sampaio, Ana; Santos, Cátia; Carrola, João; de Jesus, Joaquim; Varandas, Simone

2016-10-01

Many methods in freshwater biomonitoring tend to be restricted to a few levels of biological organization, limiting the potential spectrum of measurable of cause-effect responses to different anthropogenic impacts. We combined distinct organisational levels, covering biological biomarkers (histopathological and biochemical reactions in liver and fish gills), community based bioindicators (fish guilds, invertebrate metrics/traits and chironomid pupal exuviae) and ecosystem functional indicators (decomposition rates) to assess ecological status at designated Water Framework Directive monitoring sites, covering a gradient of human impact across several rivers in northern Portugal. We used Random Forest to rank the variables that contributed more significantly to successfully predict the different classes of ecological status and also to provide specific cut levels to discriminate each WFD class based on reference condition. A total of 59 Biological Quality Elements and functional indicators were determined using this procedure and subsequently applied to develop the integrated Multiple Ecological Level Index (MELI Index), a potentially powerful bioassessment tool. Copyright © 2016 Elsevier Inc. All rights reserved.

Enhancement Of Reading Accuracy By Multiple Data Integration

NASA Astrophysics Data System (ADS)

Lee, Kangsuk

1989-07-01

In this paper, a multiple sensor integration technique with neural network learning algorithms is presented which can enhance the reading accuracy of the hand-written numerals. Many document reading applications involve hand-written numerals in a predetermined location on a form, and in many cases, critical data is redundantly described. The amount of a personal check is one such case which is written redundantly in numerals and in alphabetical form. Information from two optical character recognition modules, one specialized for digits and one for words, is combined to yield an enhanced recognition of the amount. The combination can be accomplished by a decision tree with "if-then" rules, but by simply fusing two or more sets of sensor data in a single expanded neural net, the same functionality can be expected with a much reduced system cost. Experimental results of fusing two neural nets to enhance overall recognition performance using a controlled data set are presented.

Integration of Chinese medicine with Western medicine could lead to future medicine: molecular module medicine.

PubMed

Zhang, Chi; Zhang, Ge; Chen, Ke-ji; Lu, Ai-ping

2016-04-01

The development of an effective classification method for human health conditions is essential for precise diagnosis and delivery of tailored therapy to individuals. Contemporary classification of disease systems has properties that limit its information content and usability. Chinese medicine pattern classification has been incorporated with disease classification, and this integrated classification method became more precise because of the increased understanding of the molecular mechanisms. However, we are still facing the complexity of diseases and patterns in the classification of health conditions. With continuing advances in omics methodologies and instrumentation, we are proposing a new classification approach: molecular module classification, which is applying molecular modules to classifying human health status. The initiative would be precisely defining the health status, providing accurate diagnoses, optimizing the therapeutics and improving new drug discovery strategy. Therefore, there would be no current disease diagnosis, no disease pattern classification, and in the future, a new medicine based on this classification, molecular module medicine, could redefine health statuses and reshape the clinical practice.

An integrative system biology approach to unravel potential drug candidates for multiple age related disorders.

PubMed

Srivastava, Isha; Khurana, Pooja; Yadav, Mohini; Hasija, Yasha

2017-12-01

Aging, though an inevitable part of life, is becoming a worldwide social and economic problem. Healthy aging is usually marked by low probability of age related disorders. Good therapeutic approaches are still in need to cure age related disorders. Occurrence of more than one ARD in an individual, expresses the need of discovery of such target proteins, which can affect multiple ARDs. Advanced scientific and medical research technologies throughout last three decades have arrived to the point where lots of key molecular determinants affect human disorders can be examined thoroughly. In this study, we designed and executed an approach to prioritize drugs that may target multiple age related disorders. Our methodology, focused on the analysis of biological pathways and protein protein interaction networks that may contribute to the pharmacology of age related disorders, included various steps such as retrieval and analysis of data, protein-protein interaction network analysis, and statistical and comparative analysis of topological coefficients, pathway, and functional enrichment analysis, and identification of drug-target proteins. We assume that the identified molecular determinants may be prioritized for further screening as novel drug targets to cure multiple ARDs. Based on the analysis, an online tool named as 'ARDnet' has been developed to construct and demonstrate ARD interactions at the level of PPI, ARDs and ARDs protein interaction, ARDs pathway interaction and drug-target interaction. The tool is freely made available at http://genomeinformatics.dtu.ac.in/ARDNet/Index.html. Copyright © 2017 Elsevier B.V. All rights reserved.

DNA Sequences from Formalin-Fixed Nematodes: Integrating Molecular and Morphological Approaches to Taxonomy

PubMed Central

Thomas, W. Kelley; Vida, J. T.; Frisse, Linda M.; Mundo, Manuel; Baldwin, James G.

1997-01-01

To effectively integrate DNA sequence analysis and classical nematode taxonomy, we must be able to obtain DNA sequences from formalin-fixed specimens. Microdissected sections of nematodes were removed from specimens fixed in formalin, using standard protocols and without destroying morphological features. The fixed sections provided sufficient template for multiple polymerase chain reaction-based DNA sequence analyses. PMID:19274156

Systems and methods for integrating ion mobility and ion trap mass spectrometers

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

Ibrahim, Yehia M.; Garimella, Sandilya; Prost, Spencer A.

Described herein are examples of systems and methods for integrating IMS and MS systems. In certain examples, systems and methods for decoding double multiplexed data are described. The systems and methods can also perform multiple refining procedures in order to minimize the demultiplexing artifacts. The systems and methods can be used, for example, for the analysis of proteomic and petroleum samples, where the integration of IMS and high mass resolution are used for accurate assignment of molecular formulae.

Spatiotemporal integration of molecular and anatomical data in virtual reality using semantic mapping.

PubMed

Soh, Jung; Turinsky, Andrei L; Trinh, Quang M; Chang, Jasmine; Sabhaney, Ajay; Dong, Xiaoli; Gordon, Paul Mk; Janzen, Ryan Pw; Hau, David; Xia, Jianguo; Wishart, David S; Sensen, Christoph W

2009-01-01

We have developed a computational framework for spatiotemporal integration of molecular and anatomical datasets in a virtual reality environment. Using two case studies involving gene expression data and pharmacokinetic data, respectively, we demonstrate how existing knowledge bases for molecular data can be semantically mapped onto a standardized anatomical context of human body. Our data mapping methodology uses ontological representations of heterogeneous biomedical datasets and an ontology reasoner to create complex semantic descriptions of biomedical processes. This framework provides a means to systematically combine an increasing amount of biomedical imaging and numerical data into spatiotemporally coherent graphical representations. Our work enables medical researchers with different expertise to simulate complex phenomena visually and to develop insights through the use of shared data, thus paving the way for pathological inference, developmental pattern discovery and biomedical hypothesis testing.

Clustering the Orion B giant molecular cloud based on its molecular emission

PubMed Central

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H.; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R.; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2017-01-01

Context Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). Aims We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. Methods We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional Probability Density Function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. Results A clustering analysis based only on the J = 1 – 0 lines of three isotopologues of CO proves suffcient to reveal distinct density/column density regimes (nH ~ 100 cm−3, ~ 500 cm−3, and > 1000 cm−3), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1 − 0 line of HCO+ and the N = 1 − 0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO+ and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO+ intensity ratio in UV-illuminated regions. Finer distinctions in density classes (nH ~ 7 × 103 cm−3 ~ 4 × 104 cm−3) for the

Clustering the Orion B giant molecular cloud based on its molecular emission.

PubMed

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2018-02-01

Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional Probability Density Function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. A clustering analysis based only on the J = 1 - 0 lines of three isotopologues of CO proves suffcient to reveal distinct density/column density regimes ( n H ~ 100 cm -3 , ~ 500 cm -3 , and > 1000 cm -3 ), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1 - 0 line of HCO + and the N = 1 - 0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO + and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO + intensity ratio in UV-illuminated regions. Finer distinctions in density classes ( n H ~ 7 × 10 3 cm -3 ~ 4 × 10 4 cm -3 ) for the densest regions are also

[Ginseng prescription rules and molecular mechanism in treating coronary heart disease based on data mining and integrative pharmacology].

PubMed

Li, Sen; Tang, Shi-Huan; Liu, Jin-Ling; Su, Jin; He, Fu-Yuan

2018-04-01

The ancient dragon Materia Medica, Compendium of Materia Medica and other works recorded that the main effect of ginseng is tonifying qi. It is reported that the main active ingredient of ginseng is ginsenoside. Modern studies have found that ginseng mono saponins are effective for cardiovascular related diseases. This paper preliminary clarified the efficacy of traditional ginseng-nourishing qi and cardiovascular disease through the traditional Chinese medicine (TCM) inheritance auxiliary platform and integration platform of association of pharmacology. With the help of TCM inheritance auxiliary platform-analysis of "Chinese medicine database", Chinese medicine treatment of modern diseases that ginseng rules, so the traditional effect associated with modern medicine and pharmacology; application integration platform enrichment analysis on the target of drug and gene function, metabolic pathway, to further explore the molecular mechanism of ginseng in the treatment of coronary heart disease, aimed at mining the molecular mechanism of ginseng in the treatment of coronary heart disease. Chinese medicine containing ginseng 307 prescriptions, 87 kinds of disease indications, western medicine disease Chinese medicine therapy for ginseng main coronary heart disease; analysis of molecular mechanism of ginseng pharmacology integration platform for the treatment of coronary heart disease. Ginsenosides（Ra₁, Ra₂, Rb₁, Rb₂, Rg₁, Ro) bind these targets, PRKAA1, PRKAA2, NDUFA4, COX5B, UQCRC1, affect chemokines, non-alcoholic fatty liver, gonadotropin, carbon metabolism, glucose metabolism and other pathways to treat coronary heart disease indirectly. The molecular mechanism of Panax ginseng's multi-component, multi-target and synergistic action is preliminarily elucidated in this paper. Copyright© by the Chinese Pharmaceutical Association.

Shared and unique responses of plants to multiple individual stresses and stress combinations: physiological and molecular mechanisms

PubMed Central

Pandey, Prachi; Ramegowda, Venkategowda; Senthil-Kumar, Muthappa

2015-01-01

In field conditions, plants are often simultaneously exposed to multiple biotic and abiotic stresses resulting in substantial yield loss. Plants have evolved various physiological and molecular adaptations to protect themselves under stress combinations. Emerging evidences suggest that plant responses to a combination of stresses are unique from individual stress responses. In addition, plants exhibit shared responses which are common to individual stresses and stress combination. In this review, we provide an update on the current understanding of both unique and shared responses. Specific focus of this review is on heat–drought stress as a major abiotic stress combination and, drought–pathogen and heat–pathogen as examples of abiotic–biotic stress combinations. We also comprehend the current understanding of molecular mechanisms of cross talk in relation to shared and unique molecular responses for plant survival under stress combinations. Thus, the knowledge of shared responses of plants from individual stress studies and stress combinations can be utilized to develop varieties with broad spectrum stress tolerance. PMID:26442037

ALMA Multiple-transition Observations of High-density Molecular Tracers in Ultraluminous Infrared Galaxies

NASA Astrophysics Data System (ADS)

Imanishi, Masatoshi; Nakanishi, Kouichiro; Izumi, Takuma

2018-04-01

We present the results of our ALMA observations of 11 (ultra)luminous infrared galaxies ((U)LIRGs) at J = 4–3 of HCN, HCO+, and HNC and J = 3–2 of HNC. This is an extension of our previously published HCN and HCO+ J = 3–2 observations to multiple rotational J-transitions of multiple molecules, to investigate how molecular emission line flux ratios vary at different J-transitions. We confirm that ultraluminous infrared galaxies (ULIRGs) that contain or may contain luminous obscured active galactic nuclei (AGNs) tend to show higher HCN-to-HCO+ flux ratios than starburst galaxies, both at J = 4–3 and J = 3–2. For selected HCN-flux-enhanced AGN-important ULIRGs, our isotopologue H13CN, H13CO+, and HN13C J = 3–2 line observations suggest a higher abundance of HCN than HCO+ and HNC, which is interpreted to be primarily responsible for the elevated HCN flux in AGN-important galaxies. For such sources, the intrinsic HCN-to-HCO+ flux ratios after line opacity correction will be higher than the observed ratios, making the separation between AGNs and starbursts even larger. The signature of the vibrationally excited (v 2 = 1f) HCN J = 4–3 emission line is seen in one ULIRG, IRAS 12112‑0305 NE. P Cygni profiles are detected in the HCO+ J = 4–3 and J = 3–2 lines toward IRAS 15250+3609, with an estimated molecular outflow rate of ∼250–750 M ⊙ yr‑1. The SiO J = 6–5 line also exhibits a P Cygni profile in IRAS 12112+0305 NE, suggesting the presence of shocked outflow activity. Shock tracers are detected in many sources, suggesting ubiquitous shock activity in the nearby ULIRG population.

Right-Brain/Left-Brain Integrated Associative Processor Employing Convertible Multiple-Instruction-Stream Multiple-Data-Stream Elements

NASA Astrophysics Data System (ADS)

Hayakawa, Hitoshi; Ogawa, Makoto; Shibata, Tadashi

2005-04-01

A very large scale integrated circuit (VLSI) architecture for a multiple-instruction-stream multiple-data-stream (MIMD) associative processor has been proposed. The processor employs an architecture that enables seamless switching from associative operations to arithmetic operations. The MIMD element is convertible to a regular central processing unit (CPU) while maintaining its high performance as an associative processor. Therefore, the MIMD associative processor can perform not only on-chip perception, i.e., searching for the vector most similar to an input vector throughout the on-chip cache memory, but also arithmetic and logic operations similar to those in ordinary CPUs, both simultaneously in parallel processing. Three key technologies have been developed to generate the MIMD element: associative-operation-and-arithmetic-operation switchable calculation units, a versatile register control scheme within the MIMD element for flexible operations, and a short instruction set for minimizing the memory size for program storage. Key circuit blocks were designed and fabricated using 0.18 μm complementary metal-oxide-semiconductor (CMOS) technology. As a result, the full-featured MIMD element is estimated to be 3 mm2, showing the feasibility of an 8-parallel-MIMD-element associative processor in a single chip of 5 mm× 5 mm.

Evaluation of Kirkwood-Buff integrals via finite size scaling: a large scale molecular dynamics study

NASA Astrophysics Data System (ADS)

Dednam, W.; Botha, A. E.

2015-01-01

Solvation of bio-molecules in water is severely affected by the presence of co-solvent within the hydration shell of the solute structure. Furthermore, since solute molecules can range from small molecules, such as methane, to very large protein structures, it is imperative to understand the detailed structure-function relationship on the microscopic level. For example, it is useful know the conformational transitions that occur in protein structures. Although such an understanding can be obtained through large-scale molecular dynamic simulations, it is often the case that such simulations would require excessively large simulation times. In this context, Kirkwood-Buff theory, which connects the microscopic pair-wise molecular distributions to global thermodynamic properties, together with the recently developed technique, called finite size scaling, may provide a better method to reduce system sizes, and hence also the computational times. In this paper, we present molecular dynamics trial simulations of biologically relevant low-concentration solvents, solvated by aqueous co-solvent solutions. In particular we compare two different methods of calculating the relevant Kirkwood-Buff integrals. The first (traditional) method computes running integrals over the radial distribution functions, which must be obtained from large system-size NVT or NpT simulations. The second, newer method, employs finite size scaling to obtain the Kirkwood-Buff integrals directly by counting the particle number fluctuations in small, open sub-volumes embedded within a larger reservoir that can be well approximated by a much smaller simulation cell. In agreement with previous studies, which made a similar comparison for aqueous co-solvent solutions, without the additional solvent, we conclude that the finite size scaling method is also applicable to the present case, since it can produce computationally more efficient results which are equivalent to the more costly radial distribution

Harnessing Integrative Omics to Facilitate Molecular Imaging of the Human Epidermal Growth Factor Receptor Family for Precision Medicine.

PubMed

Pool, Martin; de Boer, H Rudolf; Hooge, Marjolijn N Lub-de; van Vugt, Marcel A T M; de Vries, Elisabeth G E

2017-01-01

Cancer is a growing problem worldwide. The cause of death in cancer patients is often due to treatment-resistant metastatic disease. Many molecularly targeted anticancer drugs have been developed against 'oncogenic driver' pathways. However, these treatments are usually only effective in properly selected patients. Resistance to molecularly targeted drugs through selective pressure on acquired mutations or molecular rewiring can hinder their effectiveness. This review summarizes how molecular imaging techniques can potentially facilitate the optimal implementation of targeted agents. Using the human epidermal growth factor receptor (HER) family as a model in (pre)clinical studies, we illustrate how molecular imaging may be employed to characterize whole body target expression as well as monitor drug effectiveness and the emergence of tumor resistance. We further discuss how an integrative omics discovery platform could guide the selection of 'effect sensors' - new molecular imaging targets - which are dynamic markers that indicate treatment effectiveness or resistance.

A fast and high performance multiple data integration algorithm for identifying human disease genes

PubMed Central

2015-01-01

Background Integrating multiple data sources is indispensable in improving disease gene identification. It is not only due to the fact that disease genes associated with similar genetic diseases tend to lie close with each other in various biological networks, but also due to the fact that gene-disease associations are complex. Although various algorithms have been proposed to identify disease genes, their prediction performances and the computational time still should be further improved. Results In this study, we propose a fast and high performance multiple data integration algorithm for identifying human disease genes. A posterior probability of each candidate gene associated with individual diseases is calculated by using a Bayesian analysis method and a binary logistic regression model. Two prior probability estimation strategies and two feature vector construction methods are developed to test the performance of the proposed algorithm. Conclusions The proposed algorithm is not only generated predictions with high AUC scores, but also runs very fast. When only a single PPI network is employed, the AUC score is 0.769 by using F2 as feature vectors. The average running time for each leave-one-out experiment is only around 1.5 seconds. When three biological networks are integrated, the AUC score using F3 as feature vectors increases to 0.830, and the average running time for each leave-one-out experiment takes only about 12.54 seconds. It is better than many existing algorithms. PMID:26399620

Measurement Frontiers in Molecular Biology

NASA Astrophysics Data System (ADS)

Laderman, Stephen

2009-03-01

Developments of molecular measurements and manipulations have long enabled forefront research in evolution, genetics, biological development and its dysfunction, and the impact of external factors on the behavior of cells. Measurement remains at the heart of exciting and challenging basic and applied problems in molecular and cell biology. Methods to precisely determine the identity and abundance of particular molecules amongst a complex mixture of similar and dissimilar types require the successful design and integration of multiple steps involving biochemical manipulations, separations, physical probing, and data processing. Accordingly, today's most powerful methods for characterizing life at the molecular level depend on coordinated advances in applied physics, biochemistry, chemistry, computer science, and engineering. This is well illustrated by recent approaches to the measurement of DNA, RNA, proteins, and intact cells. Such successes underlie well founded visions of how molecular biology can further assist in answering compelling scientific questions and in enabling the development of remarkable advances in human health. These visions, in turn, are motivating the interdisciplinary creation of even more comprehensive measurements. As a further and closely related consequence, they are motivating innovations in the conceptual and practical approaches to organizing and visualizing large, complex sets of interrelated experimental results and distilling from those data compelling, informative conclusions.

Network-based drug discovery by integrating systems biology and computational technologies

PubMed Central

Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua

2013-01-01

Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768

Molecular Surveillance Identifies Multiple Transmissions of Typhoid in West Africa

PubMed Central

Wong, Vanessa K.; Holt, Kathryn E.; Okoro, Chinyere; Baker, Stephen; Pickard, Derek J.; Marks, Florian; Page, Andrew J.; Olanipekun, Grace; Munir, Huda; Alter, Roxanne; Fey, Paul D.; Feasey, Nicholas A.; Weill, Francois-Xavier; Le Hello, Simon; Hart, Peter J.; Kariuki, Samuel; Breiman, Robert F.; Gordon, Melita A.; Heyderman, Robert S.; Jacobs, Jan; Lunguya, Octavie; Msefula, Chisomo; MacLennan, Calman A.; Keddy, Karen H.; Smith, Anthony M.; Onsare, Robert S.; De Pinna, Elizabeth; Nair, Satheesh; Amos, Ben; Dougan, Gordon; Obaro, Stephen

2016-01-01

Background The burden of typhoid in sub-Saharan African (SSA) countries has been difficult to estimate, in part, due to suboptimal laboratory diagnostics. However, surveillance blood cultures at two sites in Nigeria have identified typhoid associated with Salmonella enterica serovar Typhi (S. Typhi) as an important cause of bacteremia in children. Methods A total of 128 S. Typhi isolates from these studies in Nigeria were whole-genome sequenced, and the resulting data was used to place these Nigerian isolates into a worldwide context based on their phylogeny and carriage of molecular determinants of antibiotic resistance. Results Several distinct S. Typhi genotypes were identified in Nigeria that were related to other clusters of S. Typhi isolates from north, west and central regions of Africa. The rapidly expanding S. Typhi clade 4.3.1 (H58) previously associated with multiple antimicrobial resistances in Asia and in east, central and southern Africa, was not detected in this study. However, antimicrobial resistance was common amongst the Nigerian isolates and was associated with several plasmids, including the IncHI1 plasmid commonly associated with S. Typhi. Conclusions These data indicate that typhoid in Nigeria was established through multiple independent introductions into the country, with evidence of regional spread. MDR typhoid appears to be evolving independently of the haplotype H58 found in other typhoid endemic countries. This study highlights an urgent need for routine surveillance to monitor the epidemiology of typhoid and evolution of antimicrobial resistance within the bacterial population as a means to facilitate public health interventions to reduce the substantial morbidity and mortality of typhoid. PMID:27657909

The integration of occupational therapy into primary care: a multiple case study design

PubMed Central

2013-01-01

Background For over two decades occupational therapists have been encouraged to enhance their roles within primary care and focus on health promotion and prevention activities. While there is a clear fit between occupational therapy and primary care, there have been few practice examples, despite a growing body of evidence to support the role. In 2010, the province of Ontario, Canada provided funding to include occupational therapists as members of Family Health Teams, an interprofessional model of primary care. The integration of occupational therapists into this model of primary care is one of the first large scale initiatives of its kind in North America. The objective of the study was to examine how occupational therapy services are being integrated into primary care teams and understand the structures supporting the integration. Methods A multiple case study design was used to provide an in-depth description of the integration of occupational therapy. Four Family Health Teams with occupational therapists as part of the team were identified. Data collection included in-depth interviews, document analyses, and questionnaires. Results Each Family Health Team had a unique organizational structure that contributed to the integration of occupational therapy. Communication, trust and understanding of occupational therapy were key elements in the integration of occupational therapy into Family Health Teams, and were supported by a number of strategies including co-location, electronic medical records and team meetings. An understanding of occupational therapy was critical for integration into the team and physicians were less likely to understand the occupational therapy role than other health providers. Conclusion With an increased emphasis on interprofessional primary care, new professions will be integrated into primary healthcare teams. The study found that explicit strategies and structures are required to facilitate the integration of a new professional group

Molecular dynamics based enhanced sampling of collective variables with very large time steps.

PubMed

Chen, Pei-Yang; Tuckerman, Mark E

2018-01-14

Enhanced sampling techniques that target a set of collective variables and that use molecular dynamics as the driving engine have seen widespread application in the computational molecular sciences as a means to explore the free-energy landscapes of complex systems. The use of molecular dynamics as the fundamental driver of the sampling requires the introduction of a time step whose magnitude is limited by the fastest motions in a system. While standard multiple time-stepping methods allow larger time steps to be employed for the slower and computationally more expensive forces, the maximum achievable increase in time step is limited by resonance phenomena, which inextricably couple fast and slow motions. Recently, we introduced deterministic and stochastic resonance-free multiple time step algorithms for molecular dynamics that solve this resonance problem and allow ten- to twenty-fold gains in the large time step compared to standard multiple time step algorithms [P. Minary et al., Phys. Rev. Lett. 93, 150201 (2004); B. Leimkuhler et al., Mol. Phys. 111, 3579-3594 (2013)]. These methods are based on the imposition of isokinetic constraints that couple the physical system to Nosé-Hoover chains or Nosé-Hoover Langevin schemes. In this paper, we show how to adapt these methods for collective variable-based enhanced sampling techniques, specifically adiabatic free-energy dynamics/temperature-accelerated molecular dynamics, unified free-energy dynamics, and by extension, metadynamics, thus allowing simulations employing these methods to employ similarly very large time steps. The combination of resonance-free multiple time step integrators with free-energy-based enhanced sampling significantly improves the efficiency of conformational exploration.

Molecular dynamics based enhanced sampling of collective variables with very large time steps

NASA Astrophysics Data System (ADS)

Chen, Pei-Yang; Tuckerman, Mark E.

2018-01-01

Enhanced sampling techniques that target a set of collective variables and that use molecular dynamics as the driving engine have seen widespread application in the computational molecular sciences as a means to explore the free-energy landscapes of complex systems. The use of molecular dynamics as the fundamental driver of the sampling requires the introduction of a time step whose magnitude is limited by the fastest motions in a system. While standard multiple time-stepping methods allow larger time steps to be employed for the slower and computationally more expensive forces, the maximum achievable increase in time step is limited by resonance phenomena, which inextricably couple fast and slow motions. Recently, we introduced deterministic and stochastic resonance-free multiple time step algorithms for molecular dynamics that solve this resonance problem and allow ten- to twenty-fold gains in the large time step compared to standard multiple time step algorithms [P. Minary et al., Phys. Rev. Lett. 93, 150201 (2004); B. Leimkuhler et al., Mol. Phys. 111, 3579-3594 (2013)]. These methods are based on the imposition of isokinetic constraints that couple the physical system to Nosé-Hoover chains or Nosé-Hoover Langevin schemes. In this paper, we show how to adapt these methods for collective variable-based enhanced sampling techniques, specifically adiabatic free-energy dynamics/temperature-accelerated molecular dynamics, unified free-energy dynamics, and by extension, metadynamics, thus allowing simulations employing these methods to employ similarly very large time steps. The combination of resonance-free multiple time step integrators with free-energy-based enhanced sampling significantly improves the efficiency of conformational exploration.

Data integration to prioritize drugs using genomics and curated data.

PubMed

Louhimo, Riku; Laakso, Marko; Belitskin, Denis; Klefström, Juha; Lehtonen, Rainer; Hautaniemi, Sampsa

2016-01-01

Genomic alterations affecting drug target proteins occur in several tumor types and are prime candidates for patient-specific tailored treatments. Increasingly, patients likely to benefit from targeted cancer therapy are selected based on molecular alterations. The selection of a precision therapy benefiting most patients is challenging but can be enhanced with integration of multiple types of molecular data. Data integration approaches for drug prioritization have successfully integrated diverse molecular data but do not take full advantage of existing data and literature. We have built a knowledge-base which connects data from public databases with molecular results from over 2200 tumors, signaling pathways and drug-target databases. Moreover, we have developed a data mining algorithm to effectively utilize this heterogeneous knowledge-base. Our algorithm is designed to facilitate retargeting of existing drugs by stratifying samples and prioritizing drug targets. We analyzed 797 primary tumors from The Cancer Genome Atlas breast and ovarian cancer cohorts using our framework. FGFR, CDK and HER2 inhibitors were prioritized in breast and ovarian data sets. Estrogen receptor positive breast tumors showed potential sensitivity to targeted inhibitors of FGFR due to activation of FGFR3. Our results suggest that computational sample stratification selects potentially sensitive samples for targeted therapies and can aid in precision medicine drug repositioning. Source code is available from http://csblcanges.fimm.fi/GOPredict/.

New methods for accelerating the convergence of molecular electronic integrals over exponential type orbitals

NASA Astrophysics Data System (ADS)

Safouhi, Hassan; Hoggan, Philip

2003-01-01

This review on molecular integrals for large electronic systems (MILES) places the problem of analytical integration over exponential-type orbitals (ETOs) in a historical context. After reference to the pioneering work, particularly by Barnett, Shavitt and Yoshimine, it focuses on recent progress towards rapid and accurate analytic solutions of MILES over ETOs. Software such as the hydrogenlike wavefunction package Alchemy by Yoshimine and collaborators is described. The review focuses on convergence acceleration of these highly oscillatory integrals and in particular it highlights suitable nonlinear transformations. Work by Levin and Sidi is described and applied to MILES. A step by step description of progress in the use of nonlinear transformation methods to obtain efficient codes is provided. The recent approach developed by Safouhi is also presented. The current state of the art in this field is summarized to show that ab initio analytical work over ETOs is now a viable option.

Synthetic Biology Platform for Sensing and Integrating Endogenous Transcriptional Inputs in Mammalian Cells.

PubMed

Angelici, Bartolomeo; Mailand, Erik; Haefliger, Benjamin; Benenson, Yaakov

2016-08-30

One of the goals of synthetic biology is to develop programmable artificial gene networks that can transduce multiple endogenous molecular cues to precisely control cell behavior. Realizing this vision requires interfacing natural molecular inputs with synthetic components that generate functional molecular outputs. Interfacing synthetic circuits with endogenous mammalian transcription factors has been particularly difficult. Here, we describe a systematic approach that enables integration and transduction of multiple mammalian transcription factor inputs by a synthetic network. The approach is facilitated by a proportional amplifier sensor based on synergistic positive autoregulation. The circuits efficiently transduce endogenous transcription factor levels into RNAi, transcriptional transactivation, and site-specific recombination. They also enable AND logic between pairs of arbitrary transcription factors. The results establish a framework for developing synthetic gene networks that interface with cellular processes through transcriptional regulators. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Development of a modularized two-step (M2S) chromosome integration technique for integration of multiple transcription units in Saccharomyces cerevisiae.

PubMed

Li, Siwei; Ding, Wentao; Zhang, Xueli; Jiang, Huifeng; Bi, Changhao

2016-01-01

Saccharomyces cerevisiae has already been used for heterologous production of fuel chemicals and valuable natural products. The establishment of complicated heterologous biosynthetic pathways in S. cerevisiae became the research focus of Synthetic Biology and Metabolic Engineering. Thus, simple and efficient genomic integration techniques of large number of transcription units are demanded urgently. An efficient DNA assembly and chromosomal integration method was created by combining homologous recombination (HR) in S. cerevisiae and Golden Gate DNA assembly method, designated as modularized two-step (M2S) technique. Two major assembly steps are performed consecutively to integrate multiple transcription units simultaneously. In Step 1, Modularized scaffold containing a head-to-head promoter module and a pair of terminators was assembled with two genes. Thus, two transcription units were assembled with Golden Gate method into one scaffold in one reaction. In Step 2, the two transcription units were mixed with modules of selective markers and integration sites and transformed into S. cerevisiae for assembly and integration. In both steps, universal primers were designed for identification of correct clones. Establishment of a functional β-carotene biosynthetic pathway in S. cerevisiae within 5 days demonstrated high efficiency of this method, and a 10-transcriptional-unit pathway integration illustrated the capacity of this method. Modular design of transcription units and integration elements simplified assembly and integration procedure, and eliminated frequent designing and synthesis of DNA fragments in previous methods. Also, by assembling most parts in Step 1 in vitro, the number of DNA cassettes for homologous integration in Step 2 was significantly reduced. Thus, high assembly efficiency, high integration capacity, and low error rate were achieved.

The VLA Nascent Disk and Multiplicity Survey of Perseus Protostars (VANDAM). II. Multiplicity of Protostars in the Perseus Molecular Cloud

NASA Astrophysics Data System (ADS)

Tobin, John J.; Looney, Leslie W.; Li, Zhi-Yun; Chandler, Claire J.; Dunham, Michael M.; Segura-Cox, Dominique; Sadavoy, Sarah I.; Melis, Carl; Harris, Robert J.; Kratter, Kaitlin; Perez, Laura

2016-02-01

We present a multiplicity study of all known protostars (94) in the Perseus molecular cloud from a Karl G. Jansky Very Large Array survey at Ka-band (8 mm and 1 cm) and C-band (4 and 6.6 cm). The observed sample has a bolometric luminosity range between 0.1 L⊙ and ˜33 L⊙, with a median of 0.7 L⊙. This multiplicity study is based on the Ka-band data, having a best resolution of ˜0.″065 (15 au) and separations out to ˜43″ (10,000 au) can be probed. The overall multiplicity fraction (MF) is found to be 0.40 ± 0.06 and the companion star fraction (CSF) is 0.71 ± 0.06. The MF and CSF of the Class 0 protostars are 0.57 ± 0.09 and 1.2 ± 0.2, and the MF and CSF of Class I protostars are both 0.23 ± 0.08. The distribution of companion separations appears bi-modal, with a peak at ˜75 au and another peak at ˜3000 au. Turbulent fragmentation is likely the dominant mechanism on >1000 au scales and disk fragmentation is likely to be the dominant mechanism on <200 au scales. Toward three Class 0 sources we find companions separated by <30 au. These systems have the smallest separations of currently known Class 0 protostellar binary systems. Moreover, these close systems are embedded within larger (50-400 au) structures and may be candidates for ongoing disk fragmentation.

An investigation of multidisciplinary complex health care interventions - steps towards an integrative treatment model in the rehabilitation of People with Multiple Sclerosis

PubMed Central

2012-01-01

Background The Danish Multiple Sclerosis Society initiated a large-scale bridge building and integrative treatment project to take place from 2004–2010 at a specialized Multiple Sclerosis (MS) hospital. In this project, a team of five conventional health care practitioners and five alternative practitioners was set up to work together in developing and offering individualized treatments to 200 people with MS. The purpose of this paper is to present results from the six year treatment collaboration process regarding the development of an integrative treatment model. Discussion The collaborative work towards an integrative treatment model for people with MS, involved six steps: 1) Working with an initial model 2) Unfolding the different treatment philosophies 3) Discussing the elements of the Intervention-Mechanism-Context-Outcome-scheme (the IMCO-scheme) 4) Phrasing the common assumptions for an integrative MS program theory 5) Developing the integrative MS program theory 6) Building the integrative MS treatment model. The model includes important elements of the different treatment philosophies represented in the team and thereby describes a common understanding of the complexity of the courses of treatment. Summary An integrative team of practitioners has developed an integrative model for combined treatments of People with Multiple Sclerosis. The model unites different treatment philosophies and focuses on process-oriented factors and the strengthening of the patients’ resources and competences on a physical, an emotional and a cognitive level. PMID:22524586

The blackboard model - A framework for integrating multiple cooperating expert systems

NASA Technical Reports Server (NTRS)

Erickson, W. K.

1985-01-01

The use of an artificial intelligence (AI) architecture known as the blackboard model is examined as a framework for designing and building distributed systems requiring the integration of multiple cooperating expert systems (MCXS). Aerospace vehicles provide many examples of potential systems, ranging from commercial and military aircraft to spacecraft such as satellites, the Space Shuttle, and the Space Station. One such system, free-flying, spaceborne telerobots to be used in construction, servicing, inspection, and repair tasks around NASA's Space Station, is examined. The major difficulties found in designing and integrating the individual expert system components necessary to implement such a robot are outlined. The blackboard model, a general expert system architecture which seems to address many of the problems found in designing and building such a system, is discussed. A progress report on a prototype system under development called DBB (Distributed BlackBoard model) is given. The prototype will act as a testbed for investigating the feasibility, utility, and efficiency of MCXS-based designs developed under the blackboard model.

Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks.

PubMed

D'Souza, Mark; Sulakhe, Dinanath; Wang, Sheng; Xie, Bing; Hashemifar, Somaye; Taylor, Andrew; Dubchak, Inna; Conrad Gilliam, T; Maltsev, Natalia

2017-01-01

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

A novel approach for data integration and disease subtyping

PubMed Central

Tagett, Rebecca; Diaz, Diana

2017-01-01

Advances in high-throughput technologies allow for measurements of many types of omics data, yet the meaningful integration of several different data types remains a significant challenge. Another important and difficult problem is the discovery of molecular disease subtypes characterized by relevant clinical differences, such as survival. Here we present a novel approach, called perturbation clustering for data integration and disease subtyping (PINS), which is able to address both challenges. The framework has been validated on thousands of cancer samples, using gene expression, DNA methylation, noncoding microRNA, and copy number variation data available from the Gene Expression Omnibus, the Broad Institute, The Cancer Genome Atlas (TCGA), and the European Genome-Phenome Archive. This simultaneous subtyping approach accurately identifies known cancer subtypes and novel subgroups of patients with significantly different survival profiles. The results were obtained from genome-scale molecular data without any other type of prior knowledge. The approach is sufficiently general to replace existing unsupervised clustering approaches outside the scope of bio-medical research, with the additional ability to integrate multiple types of data. PMID:29066617

Future Directions in Vulnerability to Depression among Youth: Integrating Risk Factors and Processes across Multiple Levels of Analysis

PubMed Central

Hankin, Benjamin L.

2014-01-01

Depression is a developmental phenomenon. Considerable progress has been made in describing the syndrome, establishing its prevalence and features, providing clues as to its etiology, and developing evidence-based treatment and prevention options. Despite considerable headway in distinct lines of vulnerability research, there is an explanatory gap in the field ability to more comprehensively explain and predict who is likely to become depressed, when, and why. Still, despite clear success in predicting moderate variance for future depression, especially with empirically rigorous methods and designs, the heterogeneous and multi-determined nature of depression suggests that additional etiologies need to be included to advance knowledge on developmental pathways to depression. This paper advocates for a multiple levels of analysis approach to investigating vulnerability to depression across the lifespan and providing a more comprehensive understanding of its etiology. One example of a multiple levels of analysis model of vulnerabilities to depression is provided that integrates the most accessible, observable factors (e.g., cognitive and temperament risks), intermediate processes and endophenotypes (e.g., information processing biases, biological stress physiology, and neural activation and connectivity), and genetic influences (e.g., candidate genes and epigenetics). Evidence for each of these factors as well as their cross-level integration is provided. Methodological and conceptual considerations important for conducting integrative, multiple levels of depression vulnerability research are discussed. Finally, translational implications for how a multiple levels of analysis perspective may confer additional leverage to reduce the global burden of depression and improve care are considered. PMID:22900513

The eyes have it: A Problem-Based Learning Exercise in Molecular Evolution.

PubMed

White, Harold B

2007-05-01

Molecular evolution provides an interesting context in which to use problem-based learning because it integrates a variety of topics in biology, biochemistry, and molecular biology. This three-stage problem for advanced students deals with the structure, multiple functions, and properties of lactate dehydrogenase isozymes, and the related evolutionary trade offs of gene sharing versus gene duplication among their corresponding genes. It has directive elements that require students to find and read classic articles, review thermodynamic principles, and apply their understanding to a mythical world wherein dinosaurs continued to evolve. The science fiction writing assignment that brings closure to the problem transformed the problem with respect to student interest and engagement. Copyright © 2007 International Union of Biochemistry and Molecular Biology, Inc.

Integrated Modules Analysis to Explore the Molecular Mechanisms of Phlegm-Stasis Cementation Syndrome with Ischemic Heart Disease.

PubMed

Xu, Wei-Ming; Yang, Kuo; Jiang, Li-Jie; Hu, Jing-Qing; Zhou, Xue-Zhong

2018-01-01

Background: Ischemic heart disease (IHD) has been the leading cause of death for several decades globally, IHD patients usually hold the symptoms of phlegm-stasis cementation syndrome (PSCS) as significant complications. However, the underlying molecular mechanisms of PSCS complicated with IHD have not yet been fully elucidated. Materials and Methods: Network medicine methods were utilized to elucidate the underlying molecular mechanisms of IHD phenotypes. Firstly, high-quality IHD-associated genes from both human curated disease-gene association database and biomedical literatures were integrated. Secondly, the IHD disease modules were obtained by dissecting the protein-protein interaction (PPI) topological modules in the String V9.1 database and the mapping of IHD-associated genes to the PPI topological modules. After that, molecular functional analyses (e.g., Gene Ontology and pathway enrichment analyses) for these IHD disease modules were conducted. Finally, the PSCS syndrome modules were identified by mapping the PSCS related symptom-genes to the IHD disease modules, which were further validated by both pharmacological and physiological evidences derived from published literatures. Results: The total of 1,056 high-quality IHD-associated genes were integrated and evaluated. In addition, eight IHD disease modules (the PPI sub-networks significantly relevant to IHD) were identified, in which two disease modules were relevant to PSCS syndrome (i.e., two PSCS syndrome modules). These two modules had enriched pathways on Toll-like receptor signaling pathway (hsa04620) and Renin-angiotensin system (hsa04614), with the molecular functions of angiotensin maturation (GO:0002003) and response to bacterium (GO:0009617), which had been validated by classical Chinese herbal formulas-related targets, IHD-related drug targets, and the phenotype features derived from human phenotype ontology (HPO) and published biomedical literatures. Conclusion: A network medicine

Integrated Modules Analysis to Explore the Molecular Mechanisms of Phlegm-Stasis Cementation Syndrome with Ischemic Heart Disease

PubMed Central

Xu, Wei-Ming; Yang, Kuo; Jiang, Li-Jie; Hu, Jing-Qing; Zhou, Xue-Zhong

2018-01-01

Background: Ischemic heart disease (IHD) has been the leading cause of death for several decades globally, IHD patients usually hold the symptoms of phlegm-stasis cementation syndrome (PSCS) as significant complications. However, the underlying molecular mechanisms of PSCS complicated with IHD have not yet been fully elucidated. Materials and Methods: Network medicine methods were utilized to elucidate the underlying molecular mechanisms of IHD phenotypes. Firstly, high-quality IHD-associated genes from both human curated disease-gene association database and biomedical literatures were integrated. Secondly, the IHD disease modules were obtained by dissecting the protein-protein interaction (PPI) topological modules in the String V9.1 database and the mapping of IHD-associated genes to the PPI topological modules. After that, molecular functional analyses (e.g., Gene Ontology and pathway enrichment analyses) for these IHD disease modules were conducted. Finally, the PSCS syndrome modules were identified by mapping the PSCS related symptom-genes to the IHD disease modules, which were further validated by both pharmacological and physiological evidences derived from published literatures. Results: The total of 1,056 high-quality IHD-associated genes were integrated and evaluated. In addition, eight IHD disease modules (the PPI sub-networks significantly relevant to IHD) were identified, in which two disease modules were relevant to PSCS syndrome (i.e., two PSCS syndrome modules). These two modules had enriched pathways on Toll-like receptor signaling pathway (hsa04620) and Renin-angiotensin system (hsa04614), with the molecular functions of angiotensin maturation (GO:0002003) and response to bacterium (GO:0009617), which had been validated by classical Chinese herbal formulas-related targets, IHD-related drug targets, and the phenotype features derived from human phenotype ontology (HPO) and published biomedical literatures. Conclusion: A network medicine

Pragmatic Metadata Management for Integration into Multiple Spatial Data Infrastructure Systems and Platforms

NASA Astrophysics Data System (ADS)

Benedict, K. K.; Scott, S.

2013-12-01

While there has been a convergence towards a limited number of standards for representing knowledge (metadata) about geospatial (and other) data objects and collections, there exist a variety of community conventions around the specific use of those standards and within specific data discovery and access systems. This combination of limited (but multiple) standards and conventions creates a challenge for system developers that aspire to participate in multiple data infrastrucutres, each of which may use a different combination of standards and conventions. While Extensible Markup Language (XML) is a shared standard for encoding most metadata, traditional direct XML transformations (XSLT) from one standard to another often result in an imperfect transfer of information due to incomplete mapping from one standard's content model to another. This paper presents the work at the University of New Mexico's Earth Data Analysis Center (EDAC) in which a unified data and metadata management system has been developed in support of the storage, discovery and access of heterogeneous data products. This system, the Geographic Storage, Transformation and Retrieval Engine (GSTORE) platform has adopted a polyglot database model in which a combination of relational and document-based databases are used to store both data and metadata, with some metadata stored in a custom XML schema designed as a superset of the requirements for multiple target metadata standards: ISO 19115-2/19139/19110/19119, FGCD CSDGM (both with and without remote sensing extensions) and Dublin Core. Metadata stored within this schema is complemented by additional service, format and publisher information that is dynamically "injected" into produced metadata documents when they are requested from the system. While mapping from the underlying common metadata schema is relatively straightforward, the generation of valid metadata within each target standard is necessary but not sufficient for integration into

Biogeography of soil organic matter molecular structure across multiple soil size fractions

NASA Astrophysics Data System (ADS)

Meier, C. L.; Neff, J.

2009-12-01

Recent work suggests that there is a common soil decomposition sequence whereby plant inputs are metabolized into a physiologically constrained set of compounds originating from microbes that may persist in soil over relatively long time-scales. Plant inputs tend to be found in coarse particulate fractions (>180 μm) with relatively fast turnover times, while microbially derived compounds tend to accrue in the finer silt + clay fractions (<53 μm) with relatively long turnover times. To investigate whether a common decomposition sequence exists, we used pyrolysis gas chromatography/mass spectrometry (py-GC/MS) to characterize the molecular structure of soil organic matter (SOM) in three size fractions (590-180 μm, 180-53 μm, and <53 μm), using soils sampled from multiple biomes (alpine tundra, sub-alpine forest, boreal forest, temperate coniferous, temperate deciduous, dry desert/savannah, and tropical forest). We hypothesized that: 1) regardless of biome, fractions >180 μm would be chemically similar, and would be characterized by lignin and other plant-derived compounds; and 2) fractions <53 μm would also be similar across biomes but would be dominated by microbially-derived compounds like polysaccharides. Across all biomes, we found that there was significantly less lignin in <53 μm fractions compared to >180 μm fractions (p<0.0001), providing some support for the idea that plant material is not incorporated into soil C pools with relatively long turnover times. However, a principal components analysis (PCA) showed that the >180 μm coarse particulate fractions also contained compounds associated with microbial origins, indicating that microbial C is not limited to <53 μm size fractions. The PCA also revealed that samples within each of the three size fractions did not cluster together (i.e. they did not share a common molecular structure), but we did note that: 1) cold alpine and sub-alpine sites were unique and chemically similar; and 2) tropical

Integrating management strategies for the mountain pine beetle with multiple-resource management of lodgepole pine forests

Treesearch

Mark D. McGregor; Dennis M. Cole

1985-01-01

Provides guidelines for integrating practices for managing mountain pine beetle populations with silvicultural practices for enhancing multiple resource values of lodgepole pine forests. Summarizes published and unpublished technical information and recent research on the ecology of pest and host and presents visual and classification criteria for recognizing...

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data.

PubMed

Cha, Kihoon; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

2015-01-01

It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

PubMed Central

2015-01-01

Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation. PMID:26043779

Integrated amateur band and ultra-wide band monopole antenna with multiple band-notched

NASA Astrophysics Data System (ADS)

Srivastava, Kunal; Kumar, Ashwani; Kanaujia, B. K.; Dwari, Santanu

2018-05-01

This paper presents the integrated amateur band and ultra-wide band (UWB) monopole antenna with integrated multiple band-notched characteristics. It is designed for avoiding the potential interference of frequencies 3.99 GHz (3.83 GHz-4.34 GHz), 4.86 GHz (4.48 GHz-5.63 GHz), 7.20 GHz (6.10 GHz-7.55 GHz) and 8.0 GHz (7.62 GHz-8.47 GHz) with VSWR 4.9, 11.5, 6.4 and 5.3, respectively. Equivalent parallel resonant circuits have been presented for each band-notched frequencies of the antenna. Antenna operates in amateur band 1.2 GHz (1.05 GHz-1.3 GHz) and UWB band from 3.2 GHz-13.9 GHz. Different substrates are used to verify the working of the proposed antenna. Integrated GSM band from 0.6 GHz to 1.8 GHz can also be achieved by changing the radius of the radiating patch. Antenna gain varied from 1.4 dBi to 9.8 dBi. Measured results are presented to validate the antenna performances.

Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease.

PubMed

Ogino, Shuji; Lochhead, Paul; Chan, Andrew T; Nishihara, Reiko; Cho, Eunyoung; Wolpin, Brian M; Meyerhardt, Jeffrey A; Meissner, Alexander; Schernhammer, Eva S; Fuchs, Charles S; Giovannucci, Edward

2013-04-01

Epigenetics acts as an interface between environmental/exogenous factors, cellular responses, and pathological processes. Aberrant epigenetic signatures are a hallmark of complex multifactorial diseases (including neoplasms and malignancies such as leukemias, lymphomas, sarcomas, and breast, lung, prostate, liver, and colorectal cancers). Epigenetic signatures (DNA methylation, mRNA and microRNA expression, etc) may serve as biomarkers for risk stratification, early detection, and disease classification, as well as targets for therapy and chemoprevention. In particular, DNA methylation assays are widely applied to formalin-fixed, paraffin-embedded archival tissue specimens as clinical pathology tests. To better understand the interplay between etiological factors, cellular molecular characteristics, and disease evolution, the field of 'molecular pathological epidemiology (MPE)' has emerged as an interdisciplinary integration of 'molecular pathology' and 'epidemiology'. In contrast to traditional epidemiological research including genome-wide association studies (GWAS), MPE is founded on the unique disease principle, that is, each disease process results from unique profiles of exposomes, epigenomes, transcriptomes, proteomes, metabolomes, microbiomes, and interactomes in relation to the macroenvironment and tissue microenvironment. MPE may represent a logical evolution of GWAS, termed 'GWAS-MPE approach'. Although epigenome-wide association study attracts increasing attention, currently, it has a fundamental problem in that each cell within one individual has a unique, time-varying epigenome. Having a similar conceptual framework to systems biology, the holistic MPE approach enables us to link potential etiological factors to specific molecular pathology, and gain novel pathogenic insights on causality. The widespread application of epigenome (eg, methylome) analyses will enhance our understanding of disease heterogeneity, epigenotypes (CpG island methylator

Multiple molecular dynamics simulations of human LOX-1 and Trp150Ala mutant reveal the structural determinants causing the full deactivation of the receptor.

PubMed

Iacovelli, Federico; Tucci, Fabio Giovanni; Macari, Gabriele; Falconi, Mattia

2017-10-01

Multiple classical molecular dynamics simulations have been applied to the human LOX-1 receptor to clarify the role of the Trp150Ala mutation in the loss of binding activity. Results indicate that the substitution of this crucial residue, located at the dimer interface, markedly disrupts the wild-type receptor dynamics. The mutation causes an irreversible rearrangement of the subunits interaction pattern that in the wild-type protein allows the maintaining of a specific symmetrical motion of the monomers. The subunits dislocation determines a loss of linearity of the arginines residues composing the basic spine and a consequent alteration of the long-range electrostatic attraction of the substrate. Moreover, the anomalous subunits arrangement observed in the mutated receptor also affects the integrity of the hydrophobic tunnel, actively involved in the short-range hydrophobic recognition of the substrate. The combined effect of these structural rearrangements generates the impairing of the receptor function. © 2017 Wiley Periodicals, Inc.

POLYVIEW-MM: web-based platform for animation and analysis of molecular simulations

PubMed Central

Porollo, Aleksey; Meller, Jaroslaw

2010-01-01

Molecular simulations offer important mechanistic and functional clues in studies of proteins and other macromolecules. However, interpreting the results of such simulations increasingly requires tools that can combine information from multiple structural databases and other web resources, and provide highly integrated and versatile analysis tools. Here, we present a new web server that integrates high-quality animation of molecular motion (MM) with structural and functional analysis of macromolecules. The new tool, dubbed POLYVIEW-MM, enables animation of trajectories generated by molecular dynamics and related simulation techniques, as well as visualization of alternative conformers, e.g. obtained as a result of protein structure prediction methods or small molecule docking. To facilitate structural analysis, POLYVIEW-MM combines interactive view and analysis of conformational changes using Jmol and its tailored extensions, publication quality animation using PyMol, and customizable 2D summary plots that provide an overview of MM, e.g. in terms of changes in secondary structure states and relative solvent accessibility of individual residues in proteins. Furthermore, POLYVIEW-MM integrates visualization with various structural annotations, including automated mapping of known inter-action sites from structural homologs, mapping of cavities and ligand binding sites, transmembrane regions and protein domains. URL: http://polyview.cchmc.org/conform.html. PMID:20504857

Resolving the molecular mechanism of cadherin catch bond formation

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

Manibog, Kristine; Li, Hui; Rakshit, Sabyasachi

2014-06-02

Classical cadherin Ca(2+)-dependent cell-cell adhesion proteins play key roles in embryogenesis and in maintaining tissue integrity. Cadherins mediate robust adhesion by binding in multiple conformations. One of these adhesive states, called an X-dimer, forms catch bonds that strengthen and become longer lived in the presence of mechanical force. Here we use single-molecule force-clamp spectroscopy with an atomic force microscope along with molecular dynamics and steered molecular dynamics simulations to resolve the molecular mechanisms underlying catch bond formation and the role of Ca(2+) ions in this process. Our data suggest that tensile force bends the cadherin extracellular region such that theymore » form long-lived, force-induced hydrogen bonds that lock X-dimers into tighter contact. When Ca(2+) concentration is decreased, fewer de novo hydrogen bonds are formed and catch bond formation is eliminated« less

Mass spectrometric characterization of membrane integral low molecular weight proteins from photosystem II in barley etioplasts.

PubMed

Plöscher, Matthias; Granvogl, Bernhard; Zoryan, Mikael; Reisinger, Veronika; Eichacker, Lutz Andreas

2009-02-01

In Photosystem II (PSII), a high number of plastid encoded and membrane integral low molecular weight proteins smaller than 10 kDa, the proteins PsbE, F, H, I, J, K, L, M, N, Tc, Z and the nuclear encoded PsbW, X, Y1, Y2 proteins have been described. Here we show that all low molecular weight proteins of PSII already accumulate in the etioplast membrane fraction in darkness, whereas PsaI and PsaJ of photosystem I (PSI) represent the only low molecular weight proteins that do not accumulate in darkness. We found by BN-PAGE separation of membrane protein complexes and selective MS that the accumulation of one-helix proteins from PSII is light independent and occurs in etioplasts. In contrast, in chloroplasts isolated from light-grown plants, low molecular weight proteins were found to specifically accumulate in PSI and II complexes. Our results demonstrate how plants grown in darkness prepare for the induction of chlorophyll dependent photosystem assembly upon light perception. We anticipate that our investigation will provide the essential means for the analysis of protein assembly in any membrane utilizing low molecular weight protein subunits.

Integrative harm reduction psychotherapy: a case of substance use, multiple trauma, and suicidality.

PubMed

Tatarsky, Andrew; Kellogg, Scott

2010-02-01

Harm reduction is a new paradigm that seeks to reduce the harmful consequences of substance use and other risky behaviors without requiring abstinence. This article discusses integrative harm reduction psychotherapy, one application of harm reduction principles to psychotherapy. Seven therapeutic tasks are described with attention to clinical process, skills, and strategies. A case is presented that illustrates the application of this approach with life-threatening substance use that was related to multiple trauma and suicidal depression. (c) 2010 Wiley Periodicals, Inc.

Integrating Multiple Data Sources for Combinatorial Marker Discovery: A Study in Tumorigenesis.

PubMed

Bandyopadhyay, Sanghamitra; Mallik, Saurav

2018-01-01

Identification of combinatorial markers from multiple data sources is a challenging task in bioinformatics. Here, we propose a novel computational framework for identifying significant combinatorial markers ( s) using both gene expression and methylation data. The gene expression and methylation data are integrated into a single continuous data as well as a (post-discretized) boolean data based on their intrinsic (i.e., inverse) relationship. A novel combined score of methylation and expression data (viz., ) is introduced which is computed on the integrated continuous data for identifying initial non-redundant set of genes. Thereafter, (maximal) frequent closed homogeneous genesets are identified using a well-known biclustering algorithm applied on the integrated boolean data of the determined non-redundant set of genes. A novel sample-based weighted support ( ) is then proposed that is consecutively calculated on the integrated boolean data of the determined non-redundant set of genes in order to identify the non-redundant significant genesets. The top few resulting genesets are identified as potential s. Since our proposed method generates a smaller number of significant non-redundant genesets than those by other popular methods, the method is much faster than the others. Application of the proposed technique on an expression and a methylation data for Uterine tumor or Prostate Carcinoma produces a set of significant combination of markers. We expect that such a combination of markers will produce lower false positives than individual markers.

A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions.

PubMed

Abidi, Samina

2017-10-26

Clinical management of comorbidities is a challenge, especially in a clinical decision support setting, as it requires the safe and efficient reconciliation of multiple disease-specific clinical procedures to formulate a comorbid therapeutic plan that is both effective and safe for the patient. In this paper we pursue the integration of multiple disease-specific Clinical Practice Guidelines (CPG) in order to manage co-morbidities within a computerized Clinical Decision Support System (CDSS). We present a CPG integration framework-termed as COMET (Comorbidity Ontological Modeling & ExecuTion) that manifests a knowledge management approach to model, computerize and integrate multiple CPG to yield a comorbid CPG knowledge model that upon execution can provide evidence-based recommendations for handling comorbid patients. COMET exploits semantic web technologies to achieve (a) CPG knowledge synthesis to translate a paper-based CPG to disease-specific clinical pathways (CP) that include specialized co-morbidity management procedures based on input from domain experts; (b) CPG knowledge modeling to computerize the disease-specific CP using a Comorbidity CPG ontology; (c) CPG knowledge integration by aligning multiple ontologically-modeled CP to develop a unified comorbid CPG knowledge model; and (e) CPG knowledge execution using reasoning engines to derive CPG-mediated recommendations for managing patients with comorbidities. We present a web-accessible COMET CDSS that provides family physicians with CPG-mediated comorbidity decision support to manage Atrial Fibrillation and Chronic Heart Failure. We present our qualitative and quantitative analysis of the knowledge content and usability of COMET CDSS.

Integrated packaging of multiple double sided cooling planar bond power modules

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

Liang, Zhenxian

An integrated double sided cooled power module has one or multiple phase legs configuration including one or more planar power packages, each planar power package having an upper power switch unit and a lower power switch unit directly bonded and interconnected between two insulated power substrates, and further sandwiched between two heat exchangers via direct bonds. A segmented coolant manifold is interposed with the one or more planar power packages and creates a sealed enclosure that defines a coolant inlet, a coolant outlet and a coolant flow path between the inlet and the outlet. A coolant circulates along the flowmore » path to remove heat and increase the power density of the power module.« less

An integrative model links multiple inputs and signaling pathways to the onset of DNA synthesis in hepatocytes

PubMed Central

Huard, Jérémy; Mueller, Stephanie; Gilles, Ernst D; Klingmüller, Ursula; Klamt, Steffen

2012-01-01

During liver regeneration, quiescent hepatocytes re-enter the cell cycle to proliferate and compensate for lost tissue. Multiple signals including hepatocyte growth factor, epidermal growth factor, tumor necrosis factor α, interleukin-6, insulin and transforming growth factor β orchestrate these responses and are integrated during the G1 phase of the cell cycle. To investigate how these inputs influence DNA synthesis as a measure for proliferation, we established a large-scale integrated logical model connecting multiple signaling pathways and the cell cycle. We constructed our model based upon established literature knowledge, and successively improved and validated its structure using hepatocyte-specific literature as well as experimental DNA synthesis data. Model analyses showed that activation of the mitogen-activated protein kinase and phosphatidylinositol 3-kinase pathways was sufficient and necessary for triggering DNA synthesis. In addition, we identified key species in these pathways that mediate DNA replication. Our model predicted oncogenic mutations that were compared with the COSMIC database, and proposed intervention targets to block hepatocyte growth factor-induced DNA synthesis, which we validated experimentally. Our integrative approach demonstrates that, despite the complexity and size of the underlying interlaced network, logical modeling enables an integrative understanding of signaling-controlled proliferation at the cellular level, and thus can provide intervention strategies for distinct perturbation scenarios at various regulatory levels. PMID:22443451

Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis.

PubMed

Liu, Mingyuan; Hou, Xiaojun; Zhang, Ping; Hao, Yong; Yang, Yiting; Wu, Xiongfeng; Zhu, Desheng; Guan, Yangtai

2013-05-01

Multiple sclerosis (MS) is the most prevalent demyelinating disease and the principal cause of neurological disability in young adults. Recent microarray gene expression profiling studies have identified several genetic variants contributing to the complex pathogenesis of MS, however, expressional and functional studies are still required to further understand its molecular mechanism. The present study aimed to analyze the molecular mechanism of MS using microarray analysis combined with bioinformatics techniques. We downloaded the gene expression profile of MS from Gene Expression Omnibus (GEO) and analysed the microarray data using the differentially coexpressed genes (DCGs) and links package in R and Database for Annotation, Visualization and Integrated Discovery. The regulatory impact factor (RIF) algorithm was used to measure the impact factor of transcription factor. A total of 1,297 DCGs between MS patients and healthy controls were identified. Functional annotation indicated that these DCGs were associated with immune and neurological functions. Furthermore, the RIF result suggested that IKZF1, BACH1, CEBPB, EGR1, FOS may play central regulatory roles in controlling gene expression in the pathogenesis of MS. Our findings confirm the presence of multiple molecular alterations in MS and indicate the possibility for identifying prognostic factors associated with MS pathogenesis.

Integrative, multimodal analysis of glioblastoma using TCGA molecular data, pathology images, and clinical outcomes.

PubMed

Kong, Jun; Cooper, Lee A D; Wang, Fusheng; Gutman, David A; Gao, Jingjing; Chisolm, Candace; Sharma, Ashish; Pan, Tony; Van Meir, Erwin G; Kurc, Tahsin M; Moreno, Carlos S; Saltz, Joel H; Brat, Daniel J

2011-12-01

Multimodal, multiscale data synthesis is becoming increasingly critical for successful translational biomedical research. In this letter, we present a large-scale investigative initiative on glioblastoma, a high-grade brain tumor, with complementary data types using in silico approaches. We integrate and analyze data from The Cancer Genome Atlas Project on glioblastoma that includes novel nuclear phenotypic data derived from microscopic slides, genotypic signatures described by transcriptional class and genetic alterations, and clinical outcomes defined by response to therapy and patient survival. Our preliminary results demonstrate numerous clinically and biologically significant correlations across multiple data types, revealing the power of in silico multimodal data integration for cancer research.

Move to learn: Integrating spatial information from multiple viewpoints.

PubMed

Holmes, Corinne A; Newcombe, Nora S; Shipley, Thomas F

2018-05-11

Recalling a spatial layout from multiple orientations - spatial flexibility - is challenging, even when the global configuration can be viewed from a single vantage point, but more so when it must be viewed piecemeal. In the current study, we examined whether experiencing the transition between multiple viewpoints enhances spatial memory and flexible recall for a spatial configuration viewed simultaneously (Exp. 1) and sequentially (Exp. 2), whether the type of transition matters, and whether action provides an additional advantage over passive experience. In Experiment 1, participants viewed an array of dollhouse furniture from four viewpoints, but with all furniture simultaneously visible. In Experiment 2, participants viewed the same array piecemeal, from four partitioned viewpoints that allowed for viewing only a segment at a time. The transition between viewpoints involved rotation of the array or participant movement around it. Rotation and participant movement were passively experienced or actively generated. The control condition presented the dollhouse as a series of static views. Across both experiments, participant movement significantly enhanced spatial memory relative to array rotation or static views. However, in Exp. 2, there was a further advantage for actively walking around the array compared to being passively pushed. These findings suggest that movement around a stable environment is key to spatial memory and flexible recall, with action providing an additional boost to the integration of temporally segmented spatial events. Thus, spatial memory may be more flexible than prior data indicate, when studied under more natural acquisition conditions. Copyright © 2018 Elsevier B.V. All rights reserved.

Integrated Millimeter-Wave Frequency Multiplers

NASA Astrophysics Data System (ADS)

Schoenthal, Gerhard S.; Deaver, B. S.; Crowe, T. W.; Bishop, W. L.; Saini, K.; Bradley, R. F.

2001-11-01

Many of the molecules of interest to radio astronomers and atmospheric chemists resonate at frequencies in the millimeter and submillimeter wavelength bands. To measure the spectra of these molecules scientists rely on heterodyne receivers that convert the high frequency signal to the GHz band where it is readily amplified and analyzed. One of the challenges of developing suitable receiver systems is the development of compact, reliable and affordable sources of local oscillator power at frequencies in excess of 100 GHz. One useful solution is to use GaAs Schottky diodes, in their varactor mode, to generate high frequency harmonics of lower frequency sources such as Gunn oscillators. As a part of a multi-national radio astronomy project, the Atacama Millimeter Large Array (ALMA), we have designed and fabricated a broadband frequency tripler with an output centered at 240 GHz. It is integrated on a quartz substrate to greatly reduce the parasitic capacitance and thereby improve electrical performance. The integrated circuit was designed to require no oxides or ohmic contacts, thereby easing fabrication. This talk will discuss the novel millimeter-wave integrated circuit fabrication process and the initial results.

3D plasmonic nanoantennas integrated with MEA biosensors

NASA Astrophysics Data System (ADS)

Dipalo, Michele; Messina, Gabriele C.; Amin, Hayder; La Rocca, Rosanna; Shalabaeva, Victoria; Simi, Alessandro; Maccione, Alessandro; Zilio, Pierfrancesco; Berdondini, Luca; de Angelis, Francesco

2015-02-01

Neuronal signaling in brain circuits occurs at multiple scales ranging from molecules and cells to large neuronal assemblies. However, current sensing neurotechnologies are not designed for parallel access of signals at multiple scales. With the aim of combining nanoscale molecular sensing with electrical neural activity recordings within large neuronal assemblies, in this work three-dimensional (3D) plasmonic nanoantennas are integrated with multielectrode arrays (MEA). Nanoantennas are fabricated by fast ion beam milling on optical resist; gold is deposited on the nanoantennas in order to connect them electrically to the MEA microelectrodes and to obtain plasmonic behavior. The optical properties of these 3D nanostructures are studied through finite elements method (FEM) simulations that show a high electromagnetic field enhancement. This plasmonic enhancement is confirmed by surface enhancement Raman spectroscopy of a dye performed in liquid, which presents an enhancement of almost 100 times the incident field amplitude at resonant excitation. Finally, the reported MEA devices are tested on cultured rat hippocampal neurons. Neurons develop by extending branches on the nanostructured electrodes and extracellular action potentials are recorded over multiple days in vitro. Raman spectra of living neurons cultured on the nanoantennas are also acquired. These results highlight that these nanostructures could be potential candidates for combining electrophysiological measures of large networks with simultaneous spectroscopic investigations at the molecular level.Neuronal signaling in brain circuits occurs at multiple scales ranging from molecules and cells to large neuronal assemblies. However, current sensing neurotechnologies are not designed for parallel access of signals at multiple scales. With the aim of combining nanoscale molecular sensing with electrical neural activity recordings within large neuronal assemblies, in this work three-dimensional (3D) plasmonic

The Need for Integrated Approaches in Metabolic Engineering.

PubMed

Lechner, Anna; Brunk, Elizabeth; Keasling, Jay D

2016-11-01

This review highlights state-of-the-art procedures for heterologous small-molecule biosynthesis, the associated bottlenecks, and new strategies that have the potential to accelerate future accomplishments in metabolic engineering. We emphasize that a combination of different approaches over multiple time and size scales must be considered for successful pathway engineering in a heterologous host. We have classified these optimization procedures based on the "system" that is being manipulated: transcriptome, translatome, proteome, or reactome. By bridging multiple disciplines, including molecular biology, biochemistry, biophysics, and computational sciences, we can create an integral framework for the discovery and implementation of novel biosynthetic production routes. Copyright © 2016 Cold Spring Harbor Laboratory Press; all rights reserved.

An integrated modelling framework for neural circuits with multiple neuromodulators.

PubMed

Joshi, Alok; Youssofzadeh, Vahab; Vemana, Vinith; McGinnity, T M; Prasad, Girijesh; Wong-Lin, KongFatt

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. © 2017 The Authors.

An integrated modelling framework for neural circuits with multiple neuromodulators

PubMed Central

Vemana, Vinith

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. PMID:28100828

Spiers Memorial Lecture. Molecular mechanics and molecular electronics.

PubMed

Beckman, Robert; Beverly, Kris; Boukai, Akram; Bunimovich, Yuri; Choi, Jang Wook; DeIonno, Erica; Green, Johnny; Johnston-Halperin, Ezekiel; Luo, Yi; Sheriff, Bonnie; Stoddart, Fraser; Heath, James R

2006-01-01

We describe our research into building integrated molecular electronics circuitry for a diverse set of functions, and with a focus on the fundamental scientific issues that surround this project. In particular, we discuss experiments aimed at understanding the function of bistable rotaxane molecular electronic switches by correlating the switching kinetics and ground state thermodynamic properties of those switches in various environments, ranging from the solution phase to a Langmuir monolayer of the switching molecules sandwiched between two electrodes. We discuss various devices, low bit-density memory circuits, and ultra-high density memory circuits that utilize the electrochemical switching characteristics of these molecules in conjunction with novel patterning methods. We also discuss interconnect schemes that are capable of bridging the micrometre to submicrometre length scales of conventional patterning approaches to the near-molecular length scales of the ultra-dense memory circuits. Finally, we discuss some of the challenges associated with fabricated ultra-dense molecular electronic integrated circuits.

Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

PubMed

Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

2015-10-01

This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mid-infrared integrated optics: versatile hot embossing of mid-infrared glasses for on-chip planar waveguides for molecular sensing

NASA Astrophysics Data System (ADS)

Seddon, Angela B.; Abdel-Moneim, Nabil S.; Zhang, Lian; Pan, Wei J.; Furniss, David; Mellor, Christopher J.; Kohoutek, Tomas; Orava, Jiri; Wagner, Tomas; Benson, Trevor M.

2014-07-01

The versatility of hot embossing for shaping photonic components on-chip for mid-infrared (IR) integrated optics, using a hard mold, is demonstrated. Hot embossing via fiber-on-glass (FOG), thermally evaporated films, and radio frequency (RF)-sputtered films on glass are described. Mixed approaches of combined plasma etching and hot embossing increase the versatility still further for engineering optical circuits on a single platform. Application of these methodologies for fabricating molecular-sensing devices on-chip is discussed with a view to biomedical sensing. Future prospects for using photonic integration for the new field of mid-IR molecular sensing are appraised. Also, common methods of measuring waveguide optical loss are critically compared, regarding their susceptibility to artifacts which tend artificially to depress, or enhance, the waveguide optical loss.

Molecular Pathological Epidemiology of Epigenetics: Emerging Integrative Science to Analyze Environment, Host, and Disease

PubMed Central

Ogino, Shuji; Lochhead, Paul; Chan, Andrew T.; Nishihara, Reiko; Cho, Eunyoung; Wolpin, Brian M.; Meyerhardt, Jeffrey A.; Meissner, Alexander; Schernhammer, Eva S.; Fuchs, Charles S.; Giovannucci, Edward

2013-01-01

Epigenetics acts as an interface between environmental / exogenous factors, cellular responses and pathological processes. Aberrant epigenetic signatures are a hallmark of complex multifactorial diseases, including non-neoplastic disorders (e.g., cardiovascular diseases, hypertension, diabetes mellitus, autoimmune diseases, and some infectious diseases) and neoplasms (e.g., leukemias, lymphomas, sarcomas, and breast, lung, prostate, liver and colorectal cancers). Epigenetic signatures (DNA methylation, mRNA and microRNA expression, etc.) may serve as biomarkers for risk stratification, early detection, and disease classification, as well as targets for therapy and chemoprevention. DNA methylation assays are widely applied to formalin-fixed paraffin-embedded archival tissue specimens as clinical pathology tests. To better understand the interplay between etiologic factors, cellular molecular characteristics, and disease evolution, the field of “Molecular Pathological Epidemiology (MPE)” has emerged as an interdisciplinary integration of “molecular pathology” and “epidemiology”, with a similar conceptual framework to systems biology and network medicine. In contrast to traditional epidemiologic research including genome-wide association studies (GWAS), MPE is founded on the unique disease principle; that is, each disease process results from unique profiles of exposomes, epigenomes, transcriptomes, proteomes, metabolomes, microbiomes, and interactomes in relation to the macro-environment and tissue microenvironment. The widespread application of epigenomics (e.g., methylome) analyses will enhance our understanding of disease heterogeneity, epigenotypes (CpG island methylator phenotype, LINE-1 hypomethylation, etc.), and host-disease interactions. MPE may represent a logical evolution of GWAS, termed “GWAS-MPE approach”. Though epigenome-wide association study attracts increasing attention, currently, it has a fundamental problem in that each cell

Delimiting species of Protaphorura (Collembola: Onychiuridae): integrative evidence based on morphology, DNA sequences and geography.

PubMed

Sun, Xin; Zhang, Feng; Ding, Yinhuan; Davies, Thomas W; Li, Yu; Wu, Donghui

2017-08-15

Species delimitation remains a significant challenge when the diagnostic morphological characters are limited. Integrative taxonomy was applied to the genus Protaphorura (Collembola: Onychiuridae), which is one of most difficult soil animals to distinguish taxonomically. Three delimitation approaches (morphology, molecular markers and geography) were applied providing rigorous species validation criteria with an acceptably low error rate. Multiple molecular approaches, including distance- and evolutionary model-based methods, were used to determine species boundaries based on 144 standard barcode sequences. Twenty-two molecular putative species were consistently recovered across molecular and geographical analyses. Geographic criteria were was proved to be an efficient delimitation method for onychiurids. Further morphological examination, based on the combination of the number of pseudocelli, parapseudocelli and ventral mesothoracic chaetae, confirmed 18 taxa of 22 molecular units, with six of them described as new species. These characters were found to be of high taxonomical value. This study highlights the potential benefits of integrative taxonomy, particularly simultaneous use of molecular/geographical tools, as a powerful way of ascertaining the true diversity of the Onychiuridae. Our study also highlights that discovering new morphological characters remains central to achieving a full understanding of collembolan taxonomy.

Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection

PubMed Central

Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio

2017-01-01

Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung. PMID:28912729

Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection.

PubMed

Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio

2017-01-01

Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung.

Isothermal multiple displacement amplification: a methodical approach enhancing molecular routine diagnostics of microcarcinomas and small biopsies.

PubMed

Mairinger, Fabian D; Walter, Robert Fh; Vollbrecht, Claudia; Hager, Thomas; Worm, Karl; Ting, Saskia; Wohlschläger, Jeremias; Zarogoulidis, Paul; Zarogoulidis, Konstantinos; Schmid, Kurt W

2014-01-01

Isothermal multiple displacement amplification (IMDA) can be a powerful tool in molecular routine diagnostics for homogeneous and sequence-independent whole-genome amplification of notably small tumor samples, eg, microcarcinomas and biopsies containing a small amount of tumor. Currently, this method is not well established in pathology laboratories. We designed a study to confirm the feasibility and convenience of this method for routine diagnostics with formalin-fixed, paraffin-embedded samples prepared by laser-capture microdissection. A total of 250 μg DNA (concentration 5 μg/μL) was generated by amplification over a period of 8 hours with a material input of approximately 25 cells, approximately equivalent to 175 pg of genomic DNA. In the generated DNA, a representation of all chromosomes could be shown and the presence of elected genes relevant for diagnosis in clinical samples could be proven. Mutational analysis of clinical samples could be performed without any difficulty and showed concordance with earlier diagnostic findings. We established the feasibility and convenience of IMDA for routine diagnostics. We also showed that small amounts of DNA, which were not analyzable with current molecular methods, could be sufficient for a wide field of applications in molecular routine diagnostics when they are preamplified with IMDA.

Semantic Web meets Integrative Biology: a survey.

PubMed

Chen, Huajun; Yu, Tong; Chen, Jake Y

2013-01-01

Integrative Biology (IB) uses experimental or computational quantitative technologies to characterize biological systems at the molecular, cellular, tissue and population levels. IB typically involves the integration of the data, knowledge and capabilities across disciplinary boundaries in order to solve complex problems. We identify a series of bioinformatics problems posed by interdisciplinary integration: (i) data integration that interconnects structured data across related biomedical domains; (ii) ontology integration that brings jargons, terminologies and taxonomies from various disciplines into a unified network of ontologies; (iii) knowledge integration that integrates disparate knowledge elements from multiple sources; (iv) service integration that build applications out of services provided by different vendors. We argue that IB can benefit significantly from the integration solutions enabled by Semantic Web (SW) technologies. The SW enables scientists to share content beyond the boundaries of applications and websites, resulting into a web of data that is meaningful and understandable to any computers. In this review, we provide insight into how SW technologies can be used to build open, standardized and interoperable solutions for interdisciplinary integration on a global basis. We present a rich set of case studies in system biology, integrative neuroscience, bio-pharmaceutics and translational medicine, to highlight the technical features and benefits of SW applications in IB.

Molecular implementation of molecular shift register memories

NASA Technical Reports Server (NTRS)

Beratan, David N. (Inventor); Onuchic, Jose N. (Inventor)

1991-01-01

An electronic shift register memory (20) at the molecular level is described. The memory elements are based on a chain of electron transfer molecules (22) and the information is shifted by photoinduced (26) electron transfer reactions. Thus, multi-step sequences of charge transfer reactions are used to move charge with high efficiency down a molecular chain. The device integrates compositions of the invention onto a VLSI substrate (36), providing an example of a molecular electronic device which may be fabricated. Three energy level schemes, molecular implementation of these schemes, optical excitation strategies, charge amplification strategies, and error correction strategies are described.

Circadian enhancers coordinate multiple phases of rhythmic gene transcription in vivo.

PubMed

Fang, Bin; Everett, Logan J; Jager, Jennifer; Briggs, Erika; Armour, Sean M; Feng, Dan; Roy, Ankur; Gerhart-Hines, Zachary; Sun, Zheng; Lazar, Mitchell A

2014-11-20

Mammalian transcriptomes display complex circadian rhythms with multiple phases of gene expression that cannot be accounted for by current models of the molecular clock. We have determined the underlying mechanisms by measuring nascent RNA transcription around the clock in mouse liver. Unbiased examination of enhancer RNAs (eRNAs) that cluster in specific circadian phases identified functional enhancers driven by distinct transcription factors (TFs). We further identify on a global scale the components of the TF cistromes that function to orchestrate circadian gene expression. Integrated genomic analyses also revealed mechanisms by which a single circadian factor controls opposing transcriptional phases. These findings shed light on the diversity and specificity of TF function in the generation of multiple phases of circadian gene transcription in a mammalian organ.

Multiple templates-based homology modeling enhances structure quality of AT1 receptor: validation by molecular dynamics and antagonist docking.

PubMed

Sokkar, Pandian; Mohandass, Shylajanaciyar; Ramachandran, Murugesan

2011-07-01

We present a comparative account on 3D-structures of human type-1 receptor (AT1) for angiotensin II (AngII), modeled using three different methodologies. AngII activates a wide spectrum of signaling responses via the AT1 receptor that mediates physiological control of blood pressure and diverse pathological actions in cardiovascular, renal, and other cell types. Availability of 3D-model of AT1 receptor would significantly enhance the development of new drugs for cardiovascular diseases. However, templates of AT1 receptor with low sequence similarity increase the complexity in straightforward homology modeling, and hence there is a need to evaluate different modeling methodologies in order to use the models for sensitive applications such as rational drug design. Three models were generated for AT1 receptor by, (1) homology modeling with bovine rhodopsin as template, (2) homology modeling with multiple templates and (3) threading using I-TASSER web server. Molecular dynamics (MD) simulation (15 ns) of models in explicit membrane-water system, Ramachandran plot analysis and molecular docking with antagonists led to the conclusion that multiple template-based homology modeling outweighs other methodologies for AT1 modeling.

Planarian shows decision-making behavior in response to multiple stimuli by integrative brain function.

PubMed

Inoue, Takeshi; Hoshino, Hajime; Yamashita, Taiga; Shimoyama, Seira; Agata, Kiyokazu

2015-01-01

Planarians belong to an evolutionarily early group of organisms that possess a central nervous system including a well-organized brain with a simple architecture but many types of neurons. Planarians display a number of behaviors, such as phototaxis and thermotaxis, in response to external stimuli, and it has been shown that various molecules and neural pathways in the brain are involved in controlling these behaviors. However, due to the lack of combinatorial assay methods, it remains obscure whether planarians possess higher brain functions, including integration in the brain, in which multiple signals coming from outside are coordinated and used in determining behavioral strategies. In the present study, we designed chemotaxis and thigmotaxis/kinesis tracking assays to measure several planarian behaviors in addition to those measured by phototaxis and thermotaxis assays previously established by our group, and used these tests to analyze planarian chemotactic and thigmotactic/kinetic behaviors. We found that headless planarian body fragments and planarians that had specifically lost neural activity following regeneration-dependent conditional gene knockdown (Readyknock) of synaptotagmin in the brain lost both chemotactic and thigmotactic behaviors, suggesting that neural activity in the brain is required for the planarian's chemotactic and thigmotactic behaviors. Furthermore, we compared the strength of phototaxis, chemotaxis, thigmotaxis/kinesis, and thermotaxis by presenting simultaneous binary stimuli to planarians. We found that planarians showed a clear order of predominance of these behaviors. For example, when planarians were simultaneously exposed to 400 lux of light and a chemoattractant, they showed chemoattractive behavior irrespective of the direction of the light source, although exposure to light of this intensity alone induces evasive behavior away from the light source. In contrast, when the light intensity was increased to 800 or 1600 lux and

Using Images, Metaphor, and Hypnosis in Integrating Multiple Personality and Dissociative States: A Review of the Literature.

ERIC Educational Resources Information Center

Crawford, Carrie L.

1990-01-01

Reviews literature on hypnosis, imagery, and metaphor as applied to the treatment and integration of those with multiple personality disorder (MPD) and dissociative states. Considers diagnostic criteria of MPD; explores current theories of etiology and treatment; and suggests specific examples of various clinical methods of treatment using…

The IBD interactome: an integrated view of aetiology, pathogenesis and therapy.

PubMed

de Souza, Heitor S P; Fiocchi, Claudio; Iliopoulos, Dimitrios

2017-12-01

Crohn's disease and ulcerative colitis are prototypical complex diseases characterized by chronic and heterogeneous manifestations, induced by interacting environmental, genomic, microbial and immunological factors. These interactions result in an overwhelming complexity that cannot be tackled by studying the totality of each pathological component (an '-ome') in isolation without consideration of the interaction among all relevant -omes that yield an overall 'network effect'. The outcome of this effect is the 'IBD interactome', defined as a disease network in which dysregulation of individual -omes causes intestinal inflammation mediated by dysfunctional molecular modules. To define the IBD interactome, new concepts and tools are needed to implement a systems approach; an unbiased data-driven integration strategy that reveals key players of the system, pinpoints the central drivers of inflammation and enables development of targeted therapies. Powerful bioinformatics tools able to query and integrate multiple -omes are available, enabling the integration of genomic, epigenomic, transcriptomic, proteomic, metabolomic and microbiome information to build a comprehensive molecular map of IBD. This approach will enable identification of IBD molecular subtypes, correlations with clinical phenotypes and elucidation of the central hubs of the IBD interactome that will aid discovery of compounds that can specifically target the hubs that control the disease.

Molecular therapy for acute myeloid leukaemia

PubMed Central

Coombs, Catherine C.; Tallman, Martin S.; Levine, Ross L.

2017-01-01

Acute myeloid leukaemia (AML) is a heterogeneous disease that is, in general, associated with a very poor prognosis. Multiple cytogenetic and molecular abnormalities that characterize different forms of AML have been used to better prognosticate patients and inform treatment decisions. Indeed, risk status in patients with this disease has classically been based on cytogenetic findings; however, additional molecular characteristics have been shown to inform risk assessment, including FLT3, NPM1, KIT, and CEBPA mutation status. Advances in sequencing technology have led to the discovery of novel somatic mutations in tissue samples from patients with AML, providing deeper insight into the mutational landscape of the disease. The majority of patients with AML (>97%) are found to have a clonal somatic abnormality on mutational profiling. Nevertheless, our understanding of the utility of mutation profiling in clinical practice remains incomplete and is continually evolving, and evidence-based approaches to application of these data are needed. In this Review, we discuss the evidence-base for integrating mutational data into treatment decisions for patients with AML, and propose novel therapeutic algorithms in the era of molecular medicine. PMID:26620272

Integration of multiple DICOM Web servers into an enterprise-wide Web-based electronic medical record

NASA Astrophysics Data System (ADS)

Stewart, Brent K.; Langer, Steven G.; Martin, Kelly P.

1999-07-01

The purpose of this paper is to integrate multiple DICOM image webservers into the currently existing enterprises- wide web-browsable electronic medical record. Over the last six years the University of Washington has created a clinical data repository combining in a distributed relational database information from multiple departmental databases (MIND). A character cell-based view of this data called the Mini Medical Record (MMR) has been available for four years, MINDscape, unlike the text-based MMR. provides a platform independent, dynamic, web browser view of the MIND database that can be easily linked with medical knowledge resources on the network, like PubMed and the Federated Drug Reference. There are over 10,000 MINDscape user accounts at the University of Washington Academic Medical Centers. The weekday average number of hits to MINDscape is 35,302 and weekday average number of individual users is 1252. DICOM images from multiple webservers are now being viewed through the MINDscape electronic medical record.

Monolithic integration of InGaAs/InP multiple quantum wells on SOI substrates for photonic devices

NASA Astrophysics Data System (ADS)

Li, Zhibo; Wang, Mengqi; Fang, Xin; Li, Yajie; Zhou, Xuliang; Yu, Hongyan; Wang, Pengfei; Wang, Wei; Pan, Jiaoqing

2018-02-01

A direct epitaxy of III-V nanowires with InGaAs/InP multiple quantum wells on v-shaped trenches patterned silicon on insulator (SOI) substrates was realized by combining the standard semiconductor fabrication process with the aspect ratio trapping growth technique. Silicon thickness as well as the width and gap of each nanowire were carefully designed to accommodate essential optical properties and appropriate growth conditions. The III-V element ingredient, crystalline quality, and surface topography of the grown nanowires were characterized by X-ray diffraction spectroscopy, photoluminescence, and scanning electron microscope. Geometrical details and chemical information of multiple quantum wells were revealed by transmission electron microscopy and energy dispersive spectroscopy. Numerical simulations confirmed that the optical guided mode supported by one single nanowire was able to propagate 50 μm with ˜30% optical loss. This proposed integration scheme opens up an alternative pathway for future photonic integrations of III-V devices on the SOI platform at nanoscale.

An integrated modeling approach to support management decisions of coupled groundwater-agricultural systems under multiple uncertainties

NASA Astrophysics Data System (ADS)

Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens

2015-04-01

The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.

ePRISM: A case study in multiple proxy and mixed temporal resolution integration

USGS Publications Warehouse

Robinson, Marci M.; Dowsett, Harry J.

2010-01-01

As part of the Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project, we present the ePRISM experiment designed I) to provide climate modelers with a reconstruction of an early Pliocene warm period that was warmer than the PRISM interval (similar to 3.3 to 3.0 Ma), yet still similar in many ways to modern conditions and 2) to provide an example of how best to integrate multiple-proxy sea surface temperature (SST) data from time series with varying degrees of temporal resolution and age control as we begin to build the next generation of PRISM, the PRISM4 reconstruction, spanning a constricted time interval. While it is possible to tie individual SST estimates to a single light (warm) oxygen isotope event, we find that the warm peak average of SST estimates over a narrowed time interval is preferential for paleoclimate reconstruction as it allows for the inclusion of more records of multiple paleotemperature proxies.

Quantifying multiple telecouplings using an integrated suite of spatially-explicit tools

NASA Astrophysics Data System (ADS)

Tonini, F.; Liu, J.

2016-12-01

Telecoupling is an interdisciplinary research umbrella concept that enables natural and social scientists to understand and generate information for managing how humans and nature can sustainably coexist worldwide. To systematically study telecoupling, it is essential to build a comprehensive set of spatially-explicit tools for describing and quantifying multiple reciprocal socioeconomic and environmental interactions between a focal area and other areas. Here we introduce the Telecoupling Toolbox, a new free and open-source set of tools developed to map and identify the five major interrelated components of the telecoupling framework: systems, flows, agents, causes, and effects. The modular design of the toolbox allows the integration of existing tools and software (e.g. InVEST) to assess synergies and tradeoffs associated with policies and other local to global interventions. We show applications of the toolbox using a number of representative studies that address a variety of scientific and management issues related to telecouplings throughout the world. The results suggest that the toolbox can thoroughly map and quantify multiple telecouplings under various contexts while providing users with an easy-to-use interface. It provides a powerful platform to address globally important issues, such as land use and land cover change, species invasion, migration, flows of ecosystem services, and international trade of goods and products.

Neural Plasticity in Multiple Sclerosis: The Functional and Molecular Background

PubMed Central

Glabinski, Andrzej

2015-01-01

Multiple sclerosis is an autoimmune neurodegenerative disorder resulting in motor dysfunction and cognitive decline. The inflammatory and neurodegenerative changes seen in the brains of MS patients lead to progressive disability and increasing brain atrophy. The most common type of MS is characterized by episodes of clinical exacerbations and remissions. This suggests the presence of compensating mechanisms for accumulating damage. Apart from the widely known repair mechanisms like remyelination, another important phenomenon is neuronal plasticity. Initially, neuroplasticity was connected with the developmental stages of life; however, there is now growing evidence confirming that structural and functional reorganization occurs throughout our lifetime. Several functional studies, utilizing such techniques as fMRI, TBS, or MRS, have provided valuable data about the presence of neuronal plasticity in MS patients. CNS ability to compensate for neuronal damage is most evident in RR-MS; however it has been shown that brain plasticity is also preserved in patients with substantial brain damage. Regardless of the numerous studies, the molecular background of neuronal plasticity in MS is still not well understood. Several factors, like IL-1β, BDNF, PDGF, or CB1Rs, have been implicated in functional recovery from the acute phase of MS and are thus considered as potential therapeutic targets. PMID:26229689

Integrated genomics and molecular breeding approaches for dissecting the complex quantitative traits in crop plants.

PubMed

Kujur, Alice; Saxena, Maneesha S; Bajaj, Deepak; Laxmi; Parida, Swarup K

2013-12-01

The enormous population growth, climate change and global warming are now considered major threats to agriculture and world's food security. To improve the productivity and sustainability of agriculture, the development of highyielding and durable abiotic and biotic stress-tolerant cultivars and/climate resilient crops is essential. Henceforth, understanding the molecular mechanism and dissection of complex quantitative yield and stress tolerance traits is the prime objective in current agricultural biotechnology research. In recent years, tremendous progress has been made in plant genomics and molecular breeding research pertaining to conventional and next-generation whole genome, transcriptome and epigenome sequencing efforts, generation of huge genomic, transcriptomic and epigenomic resources and development of modern genomics-assisted breeding approaches in diverse crop genotypes with contrasting yield and abiotic stress tolerance traits. Unfortunately, the detailed molecular mechanism and gene regulatory networks controlling such complex quantitative traits is not yet well understood in crop plants. Therefore, we propose an integrated strategies involving available enormous and diverse traditional and modern -omics (structural, functional, comparative and epigenomics) approaches/resources and genomics-assisted breeding methods which agricultural biotechnologist can adopt/utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in crop plants. This would provide clues and much needed inputs for rapid selection of novel functionally relevant molecular tags regulating such complex traits to expedite traditional and modern marker-assisted genetic enhancement studies in target crop species for developing high-yielding stress-tolerant varieties.

Investigation of interference in multiple-input multiple-output wireless transmission at W band for an optical wireless integration system.

PubMed

Li, Xinying; Yu, Jianjun; Dong, Ze; Zhang, Junwen; Chi, Nan; Yu, Jianguo

2013-03-01

We experimentally investigate the interference in multiple-input multiple-output (MIMO) wireless transmission by adjusting the relative locations of horn antennas (HAs) in a 100 GHz optical wireless integration system, which can deliver a 50 Gb/s polarization-division-multiplexing quadrature-phase-shift-keying signal over 80 km single-mode fiber-28 and a 2×2 MIMO wireless link. For the parallel 2×2 MIMO wireless link, each receiver HA can only get wireless power from the corresponding transmitter HA, while for the crossover ones, the receiver HA can get wireless power from two transmitter HAs. At the wireless receiver, polarization demultiplexing is realized by the constant modulus algorithm (CMA) in the digital-signal-processing part. Compared to the parallel case, wireless interference causes about 2 dB optical signal-to-noise ratio penalty at a bit-error ratio (BER) of 3.8×10(-3) for the crossover cases if similar CMA taps are employed. The increase in CMA tap length can reduce wireless interference and improve BER performance. Furthermore, more CMA taps should be adopted to overcome the severe wireless interference when two pairs of transmitter and receiver HAs have different wireless distances.

Control of aliphatic halogenated DBP precursors with multiple drinking water treatment processes: Formation potential and integrated toxicity.

PubMed

Zhang, Yimeng; Chu, Wenhai; Yao, Dechang; Yin, Daqiang

2017-08-01

The comprehensive control efficiency for the formation potentials (FPs) of a range of regulated and unregulated halogenated disinfection by-products (DBPs) (including carbonaceous DBPs (C-DBPs), nitrogenous DBPs (N-DBPs), and iodinated DBPs (I-DBPs)) with the multiple drinking water treatment processes, including pre-ozonation, conventional treatment (coagulation-sedimentation, pre-sand filtration), ozone-biological activated carbon (O 3 -BAC) advanced treatment, and post-sand filtration, was investigated. The potential toxic risks of DBPs by combing their FPs and toxicity values were also evaluated. The results showed that the multiple drinking water treatment processes had superior performance in removing organic/inorganic precursors and reducing the formation of a range of halogenated DBPs. Therein, ozonation significantly removed bromide and iodide, and thus reduced the formation of brominated and iodinated DBPs. The removal of organic carbon and nitrogen precursors by the conventional treatment processes was substantially improved by O 3 -BAC advanced treatment, and thus prevented the formation of chlorinated C-DBPs and N-DBPs. However, BAC filtration leads to the increased formation of brominated C-DBPs and N-DBPs due to the increase of bromide/DOC and bromide/DON. After the whole multiple treatment processes, the rank order for integrated toxic risk values caused by these halogenated DBPs was haloacetonitriles (HANs)≫haloacetamides (HAMs)>haloacetic acids (HAAs)>trihalomethanes (THMs)>halonitromethanes (HNMs)≫I-DBPs (I-HAMs and I-THMs). I-DBPs failed to cause high integrated toxic risk because of their very low FPs. The significant higher integrated toxic risk value caused by HANs than other halogenated DBPs cannot be ignored. Copyright © 2017. Published by Elsevier B.V.

Pathview Web: user friendly pathway visualization and data integration

PubMed Central

Pant, Gaurav; Bhavnasi, Yeshvant K.; Blanchard, Steven G.; Brouwer, Cory

2017-01-01

Abstract Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/. PMID:28482075

Fully 3D printed integrated reactor array for point-of-care molecular diagnostics.

PubMed

Kadimisetty, Karteek; Song, Jinzhao; Doto, Aoife M; Hwang, Young; Peng, Jing; Mauk, Michael G; Bushman, Frederic D; Gross, Robert; Jarvis, Joseph N; Liu, Changchun

2018-06-30

Molecular diagnostics that involve nucleic acid amplification tests (NAATs) are crucial for prevention and treatment of infectious diseases. In this study, we developed a simple, inexpensive, disposable, fully 3D printed microfluidic reactor array that is capable of carrying out extraction, concentration and isothermal amplification of nucleic acids in variety of body fluids. The method allows rapid molecular diagnostic tests for infectious diseases at point of care. A simple leak-proof polymerization strategy was developed to integrate flow-through nucleic acid isolation membranes into microfluidic devices, yielding a multifunctional diagnostic platform. Static coating technology was adopted to improve the biocompatibility of our 3D printed device. We demonstrated the suitability of our device for both end-point colorimetric qualitative detection and real-time fluorescence quantitative detection. We applied our diagnostic device to detection of Plasmodium falciparum in plasma samples and Neisseria meningitides in cerebrospinal fluid (CSF) samples by loop-mediated, isothermal amplification (LAMP) within 50 min. The detection limits were 100 fg for P. falciparum and 50 colony-forming unit (CFU) for N. meningitidis per reaction, which are comparable to that of benchtop instruments. This rapid and inexpensive 3D printed device has great potential for point-of-care molecular diagnosis of infectious disease in resource-limited settings. Copyright © 2018 Elsevier B.V. All rights reserved.

Integration of heterogeneous molecular networks to unravel gene-regulation in Mycobacterium tuberculosis.

PubMed

van Dam, Jesse C J; Schaap, Peter J; Martins dos Santos, Vitor A P; Suárez-Diez, María

2014-09-26

Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each separate set has an intrinsic value that is diluted and partly lost when building a consensus network. Here we present a methodology to generate co-expression networks and, instead of a consensus network, we propose an integration framework where the different networks are kept and analysed with additional tools to efficiently combine the information extracted from each network. We developed a workflow to efficiently analyse information generated by different inference and prediction methods. Our methodology relies on providing the user the means to simultaneously visualise and analyse the coexisting networks generated by different algorithms, heterogeneous datasets, and a suite of analysis tools. As a show case, we have analysed the gene co-expression networks of Mycobacterium tuberculosis generated using over 600 expression experiments. Regarding DNA damage repair, we identified SigC as a key control element, 12 new targets for LexA, an updated LexA binding motif, and a potential mismatch repair system. We expanded the DevR regulon with 27 genes while identifying 9 targets wrongly assigned to this regulon. We discovered 10 new genes linked to zinc uptake and a new regulatory mechanism for ZuR. The use of co-expression networks to perform system level analysis allows the development of custom made methodologies. As show cases we implemented a pipeline to integrate ChIP-seq data and another method to uncover multiple regulatory layers. Our workflow is based on representing the multiple types of information as network representations and presenting these networks in a synchronous framework that allows their simultaneous visualization while keeping specific associations from the different

Clustering the Orion B giant molecular cloud based on its molecular emission

NASA Astrophysics Data System (ADS)

Bron, Emeric; Daudon, Chloé; Pety, Jérôme; Levrier, François; Gerin, Maryvonne; Gratier, Pierre; Orkisz, Jan H.; Guzman, Viviana; Bardeau, Sébastien; Goicoechea, Javier R.; Liszt, Harvey; Öberg, Karin; Peretto, Nicolas; Sievers, Albrecht; Tremblin, Pascal

2018-02-01

Context. Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). Aims: We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. Methods: We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional probability density function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. Results: A clustering analysis based only on the J = 1-0 lines of three isotopologues of CO proves sufficient to reveal distinct density/column density regimes (nH 100 cm-3, 500 cm-3, and >1000 cm-3), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1-0 line of HCO+ and the N = 1-0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO+ and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO+ intensity ratio in UV-illuminated regions. Finer distinctions in density classes (nH 7 × 103 cm-3, 4 × 104 cm-3) for the densest regions are also

Coherent coupling between Vanadyl Phthalocyanine spin ensemble and microwave photons: towards integration of molecular spin qubits into quantum circuits.

PubMed

Bonizzoni, C; Ghirri, A; Atzori, M; Sorace, L; Sessoli, R; Affronte, M

2017-10-12

Electron spins are ideal two-level systems that may couple with microwave photons so that, under specific conditions, coherent spin-photon states can be realized. This represents a fundamental step for the transfer and the manipulation of quantum information. Along with spin impurities in solids, molecular spins in concentrated phases have recently shown coherent dynamics under microwave stimuli. Here we show that it is possible to obtain high cooperativity regime between a molecular Vanadyl Phthalocyanine (VOPc) spin ensemble and a high quality factor superconducting YBa 2 Cu 3 O 7 (YBCO) coplanar resonator at 0.5 K. This demonstrates that molecular spin centers can be successfully integrated in hybrid quantum devices.

Comprehensive Molecular Characterization of Urothelial Bladder Carcinoma

PubMed Central

2014-01-01

Urothelial carcinoma of the bladder is a common malignancy that causes approximately 150,000 deaths per year worldwide. To date, no molecularly targeted agents have been approved for the disease. As part of The Cancer Genome Atlas project, we report here an integrated analysis of 131 urothelial carcinomas to provide a comprehensive landscape of molecular alterations. There were statistically significant recurrent mutations in 32 genes, including multiple genes involved in cell cycle regulation, chromatin regulation, and kinase signaling pathways, as well as 9 genes not previously reported as significantly mutated in any cancer. RNA sequencing revealed four expression subtypes, two of which (papillary-like and basal/squamous-like) were also evident in miRNA sequencing and protein data. Whole-genome and RNA sequencing identified recurrent in-frame activating FGFR3-TACC3 fusions and expression or integration of several viruses (including HPV16) that are associated with gene inactivation. Our analyses identified potential therapeutic targets in 69% of the tumours, including 42% with targets in the PI3K/AKT/mTOR pathway and 45% with targets (including ERBB2) in the RTK/MAPK pathway. Chromatin regulatory genes were more frequently mutated in urothelial carcinoma than in any common cancer studied to date, suggesting the future possibility of targeted therapy for chromatin abnormalities. PMID:24476821

Current DOT research on the effect of multiple site damage on structural integrity

NASA Technical Reports Server (NTRS)

Tong, P.; Arin, Kemal; Jeong, David Y.; Greif, R.; Brewer, John C.; Bobo, Stephan N.; Sampath, Sam N.

1992-01-01

Multiple site damage (MSD) is a type of cracking that may be found in aging airplanes and which may adversely affect their continuing airworthiness. The Volpe National Transportation Systems Center has supported the Federal Aviation Administration Technical Center on structural integrity research for the past two and half years. The work has focused on understanding the behavior of MSD, detection of MSD during airframe inspection, and the avoidance of MSD in future designs. These three elements of the MSD problem are addressed and a summary of the completed work, the current status, and requirements for future research is provided.

Pitfalls in lung cancer molecular pathology: how to limit them in routine practice?

PubMed

Ilie, M; Hofman, P

2012-01-01

New treatment options in advanced non-small cell lung carcinoma (NSCLC) targeting activating epidermal growth factor receptor (EGFR) gene mutations and other genetic alterations demonstrated the clinical significance of the molecular features of specific subsets of tumors. Therefore, the development of personalized medicine has stimulated the routine integration into pathology departments of somatic mutation testing. However, clinical mutation testing must be optimized and standardized with regard to histological profile, type of samples, pre-analytical steps, methodology and result reporting. Routine molecular testing in NSCLC is currently moving beyond EGFR mutational analysis. Recent progress of targeted therapies will require molecular testing for a wide panel of mutations for a personalized molecular diagnosis. As a consequence, efficient testing of multiple molecular abnormalities is an urgent requirement in thoracic oncology. Moreover, increasingly limited tumor sample becomes a major challenge for molecular pathology. Continuous efforts should be made for safe, effective and specific molecular analyses. This must be based on close collaboration between the departments involved in the management of lung cancer. In this review we explored the practical issues and pitfalls surrounding the routine implementation of molecular testing in NSCLC in a pathology laboratory.

Fuzzy adaptive interacting multiple model nonlinear filter for integrated navigation sensor fusion.

PubMed

Tseng, Chien-Hao; Chang, Chih-Wen; Jwo, Dah-Jing

2011-01-01

In this paper, the application of the fuzzy interacting multiple model unscented Kalman filter (FUZZY-IMMUKF) approach to integrated navigation processing for the maneuvering vehicle is presented. The unscented Kalman filter (UKF) employs a set of sigma points through deterministic sampling, such that a linearization process is not necessary, and therefore the errors caused by linearization as in the traditional extended Kalman filter (EKF) can be avoided. The nonlinear filters naturally suffer, to some extent, the same problem as the EKF for which the uncertainty of the process noise and measurement noise will degrade the performance. As a structural adaptation (model switching) mechanism, the interacting multiple model (IMM), which describes a set of switching models, can be utilized for determining the adequate value of process noise covariance. The fuzzy logic adaptive system (FLAS) is employed to determine the lower and upper bounds of the system noise through the fuzzy inference system (FIS). The resulting sensor fusion strategy can efficiently deal with the nonlinear problem for the vehicle navigation. The proposed FUZZY-IMMUKF algorithm shows remarkable improvement in the navigation estimation accuracy as compared to the relatively conventional approaches such as the UKF and IMMUKF.

Prion-Protein-interacting Amyloid-β Oligomers of High Molecular Weight Are Tightly Correlated with Memory Impairment in Multiple Alzheimer Mouse Models*

PubMed Central

Kostylev, Mikhail A.; Kaufman, Adam C.; Nygaard, Haakon B.; Patel, Pujan; Haas, Laura T.; Gunther, Erik C.; Vortmeyer, Alexander; Strittmatter, Stephen M.

2015-01-01

Alzheimer disease (AD) is characterized by amyloid-β accumulation, with soluble oligomers (Aβo) being the most synaptotoxic. However, the multivalent and unstable nature of Aβo limits molecular characterization and hinders research reproducibility. Here, we characterized multiple Aβo forms throughout the life span of various AD mice and in post-mortem human brain. Aβo exists in several populations, where prion protein (PrPC)-interacting Aβo is a high molecular weight Aβ assembly present in multiple mice and humans with AD. Levels of PrPC-interacting Aβo match closely with mouse memory and are equal or superior to other Aβ measures in predicting behavioral impairment. However, Aβo metrics vary considerably between mouse strains. Deleting PrPC expression in mice with relatively low PrPC-interacting Aβo (Tg2576) results in partial rescue of cognitive performance as opposed to complete recovery in animals with a high percentage of PrPC-interacting Aβo (APP/PSEN1). These findings highlight the relative contributions and interplay of Aβo forms in AD. PMID:26018073

Circadian Enhancers Coordinate Multiple Phases of Rhythmic Gene Transcription In Vivo

PubMed Central

Fang, Bin; Everett, Logan J.; Jager, Jennifer; Briggs, Erika; Armour, Sean M.; Feng, Dan; Roy, Ankur; Gerhart-Hines, Zachary; Sun, Zheng; Lazar, Mitchell A.

2014-01-01

SUMMARY Mammalian transcriptomes display complex circadian rhythms with multiple phases of gene expression that cannot be accounted for by current models of the molecular clock. We have determined the underlying mechanisms by measuring nascent RNA transcription around the clock in mouse liver. Unbiased examination of eRNAs that cluster in specific circadian phases identified functional enhancers driven by distinct transcription factors (TFs). We further identify on a global scale the components of the TF cistromes that function to orchestrate circadian gene expression. Integrated genomic analyses also revealed novel mechanisms by which a single circadian factor controls opposing transcriptional phases. These findings shed new light on the diversity and specificity of TF function in the generation of multiple phases of circadian gene transcription in a mammalian organ. PMID:25416951

Current dichotomy between traditional molecular biological and omic research in cancer biology and pharmacology.

PubMed

Reinhold, William C

2015-12-10

There is currently a split within the cancer research community between traditional molecular biological hypothesis-driven and the more recent "omic" forms or research. While the molecular biological approach employs the tried and true single alteration-single response formulations of experimentation, the omic employs broad-based assay or sample collection approaches that generate large volumes of data. How to integrate the benefits of these two approaches in an efficient and productive fashion remains an outstanding issue. Ideally, one would merge the understandability, exactness, simplicity, and testability of the molecular biological approach, with the larger amounts of data, simultaneous consideration of multiple alterations, consideration of genes both of known interest along with the novel, cross-sample comparisons among cell lines and patient samples, and consideration of directed questions while simultaneously gaining exposure to the novel provided by the omic approach. While at the current time integration of the two disciplines remains problematic, attempts to do so are ongoing, and will be necessary for the understanding of the large cell line screens including the Developmental Therapeutics Program's NCI-60, the Broad Institute's Cancer Cell Line Encyclopedia, and the Wellcome Trust Sanger Institute's Cancer Genome Project, as well as the the Cancer Genome Atlas clinical samples project. Going forward there is significant benefit to be had from the integration of the molecular biological and the omic forms or research, with the desired goal being improved translational understanding and application.

Brief Integrative Multiple Behavior Intervention Effects and Mediators for Adolescents

PubMed Central

(Chad) Werch, Chudley E.; Bian, Hui; Carlson, Joan; Moore, Michele J.; DiClemente, Carlo C.; Huang, I-Chan; Ames, Steven C.; Thombs, Dennis; Weiler, Robert M.; Pokorny, Steven B.

2015-01-01

This study evaluated the efficacy of a brief integrative multiple behavior intervention and assessed risk factors as mediators of behavioral outcomes among older adolescents. A randomized controlled trial was conducted with participants randomly assigned to either a brief intervention or standard care control with 3-month follow-up. A total of 479 students attending two public high schools participated. Participants receiving the intervention showed a significant reduction in quantity x frequency of alcohol use, and increases in fruit and vegetable consumption and frequency of relaxation activities, compared to those receiving the control, p’s =.01. No effects were found on cigarette and marijuana use, exercise and sleep. Effect sizes were small with alcohol use cessation effects reaching medium size. Intervention effects were mediated by changes in peer influenceability for alcohol use, and self-efficacy and self-image for health promoting behaviors. Findings suggest that the brief intervention resulted in health risk and promoting behavior improvements for adolescents, with outcomes mediated by several risk factors. PMID:20661637

Molecular coordination of Staphylococcus aureus cell division

PubMed Central

Cotterell, Bryony E; Walther, Christa G; Fenn, Samuel J; Grein, Fabian; Wollman, Adam JM; Leake, Mark C; Olivier, Nicolas; Cadby, Ashley; Mesnage, Stéphane; Jones, Simon

2018-01-01

The bacterial cell wall is essential for viability, but despite its ability to withstand internal turgor must remain dynamic to permit growth and division. Peptidoglycan is the major cell wall structural polymer, whose synthesis requires multiple interacting components. The human pathogen Staphylococcus aureus is a prolate spheroid that divides in three orthogonal planes. Here, we have integrated cellular morphology during division with molecular level resolution imaging of peptidoglycan synthesis and the components responsible. Synthesis occurs across the developing septal surface in a diffuse pattern, a necessity of the observed septal geometry, that is matched by variegated division component distribution. Synthesis continues after septal annulus completion, where the core division component FtsZ remains. The novel molecular level information requires re-evaluation of the growth and division processes leading to a new conceptual model, whereby the cell cycle is expedited by a set of functionally connected but not regularly distributed components. PMID:29465397

Molecular mechanisms of retroviral integration site selection

PubMed Central

Kvaratskhelia, Mamuka; Sharma, Amit; Larue, Ross C.; Serrao, Erik; Engelman, Alan

2014-01-01

Retroviral replication proceeds through an obligate integrated DNA provirus, making retroviral vectors attractive vehicles for human gene-therapy. Though most of the host cell genome is available for integration, the process of integration site selection is not random. Retroviruses differ in their choice of chromatin-associated features and also prefer particular nucleotide sequences at the point of insertion. Lentiviruses including HIV-1 preferentially integrate within the bodies of active genes, whereas the prototypical gammaretrovirus Moloney murine leukemia virus (MoMLV) favors strong enhancers and active gene promoter regions. Integration is catalyzed by the viral integrase protein, and recent research has demonstrated that HIV-1 and MoMLV targeting preferences are in large part guided by integrase-interacting host factors (LEDGF/p75 for HIV-1 and BET proteins for MoMLV) that tether viral intasomes to chromatin. In each case, the selectivity of epigenetic marks on histones recognized by the protein tether helps to determine the integration distribution. In contrast, nucleotide preferences at integration sites seem to be governed by the ability for the integrase protein to locally bend the DNA duplex for pairwise insertion of the viral DNA ends. We discuss approaches to alter integration site selection that could potentially improve the safety of retroviral vectors in the clinic. PMID:25147212

Microarray-integrated optoelectrofluidic immunoassay system

PubMed Central

Han, Dongsik

2016-01-01

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

Microarray-integrated optoelectrofluidic immunoassay system.

PubMed

Han, Dongsik; Park, Je-Kyun

2016-05-01

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

Integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control for Lead-Wing close formation systems

NASA Astrophysics Data System (ADS)

Liu, Chun; Jiang, Bin; Zhang, Ke

2018-03-01

This paper investigates the attitude and position tracking control problem for Lead-Wing close formation systems in the presence of loss of effectiveness and lock-in-place or hardover failure. In close formation flight, Wing unmanned aerial vehicle movements are influenced by vortex effects of the neighbouring Lead unmanned aerial vehicle. This situation allows modelling of aerodynamic coupling vortex-effects and linearisation based on optimal close formation geometry. Linearised Lead-Wing close formation model is transformed into nominal robust H-infinity models with respect to Mach hold, Heading hold, and Altitude hold autopilots; static feedback H-infinity controller is designed to guarantee effective tracking of attitude and position while manoeuvring Lead unmanned aerial vehicle. Based on H-infinity control design, an integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control scheme is developed to guarantee asymptotic stability of close-loop systems, error signal boundedness, and attitude and position tracking properties. Simulation results for Lead-Wing close formation systems validate the efficiency of the proposed integrated multiple-model adaptive control algorithm.

A modular cell-based biosensor using engineered genetic logic circuits to detect and integrate multiple environmental signals

PubMed Central

Wang, Baojun; Barahona, Mauricio; Buck, Martin

2013-01-01

Cells perceive a wide variety of cellular and environmental signals, which are often processed combinatorially to generate particular phenotypic responses. Here, we employ both single and mixed cell type populations, pre-programmed with engineered modular cell signalling and sensing circuits, as processing units to detect and integrate multiple environmental signals. Based on an engineered modular genetic AND logic gate, we report the construction of a set of scalable synthetic microbe-based biosensors comprising exchangeable sensory, signal processing and actuation modules. These cellular biosensors were engineered using distinct signalling sensory modules to precisely identify various chemical signals, and combinations thereof, with a quantitative fluorescent output. The genetic logic gate used can function as a biological filter and an amplifier to enhance the sensing selectivity and sensitivity of cell-based biosensors. In particular, an Escherichia coli consortium-based biosensor has been constructed that can detect and integrate three environmental signals (arsenic, mercury and copper ion levels) via either its native two-component signal transduction pathways or synthetic signalling sensors derived from other bacteria in combination with a cell-cell communication module. We demonstrate how a modular cell-based biosensor can be engineered predictably using exchangeable synthetic gene circuit modules to sense and integrate multiple-input signals. This study illustrates some of the key practical design principles required for the future application of these biosensors in broad environmental and healthcare areas. PMID:22981411

Integrated analysis of phenome, genome, and transcriptome of hybrid rice uncovered multiple heterosis-related loci for yield increase

PubMed Central

Li, Dayong; Huang, Zhiyuan; Song, Shuhui; Xin, Yeyun; Mao, Donghai; Lv, Qiming; Zhou, Ming; Tian, Dongmei; Tang, Mingfeng; Wu, Qi; Liu, Xue; Chen, Tingting; Song, Xianwei; Fu, Xiqin; Zhao, Bingran; Liang, Chengzhi; Li, Aihong; Liu, Guozhen; Li, Shigui; Hu, Songnian; Cao, Xiaofeng; Yu, Jun; Yuan, Longping; Chen, Caiyan; Zhu, Lihuang

2016-01-01

Hybrid rice is the dominant form of rice planted in China, and its use has extended worldwide since the 1970s. It offers great yield advantages and has contributed greatly to the world’s food security. However, the molecular mechanisms underlying heterosis have remained a mystery. In this study we integrated genetics and omics analyses to determine the candidate genes for yield heterosis in a model two-line rice hybrid system, Liang-you-pei 9 (LYP9) and its parents. Phenomics study revealed that the better parent heterosis (BPH) of yield in hybrid is not ascribed to BPH of all the yield components but is specific to the BPH of spikelet number per panicle (SPP) and paternal parent heterosis (PPH) of effective panicle number (EPN). Genetic analyses then identified multiple quantitative trait loci (QTLs) for these two components. Moreover, a number of differentially expressed genes and alleles in the hybrid were mapped by transcriptome profiling to the QTL regions as possible candidate genes. In parallel, a major QTL for yield heterosis, rice heterosis 8 (RH8), was found to be the DTH8/Ghd8/LHD1 gene. Based on the shared allelic heterozygosity of RH8 in many hybrid rice cultivars, a common mechanism for yield heterosis in the present commercial hybrid rice is proposed. PMID:27663737

Ultrasensitive response motifs: basic amplifiers in molecular signalling networks

PubMed Central

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E.

2013-01-01

Multi-component signal transduction pathways and gene regulatory circuits underpin integrated cellular responses to perturbations. A recurring set of network motifs serve as the basic building blocks of these molecular signalling networks. This review focuses on ultrasensitive response motifs (URMs) that amplify small percentage changes in the input signal into larger percentage changes in the output response. URMs generally possess a sigmoid input–output relationship that is steeper than the Michaelis–Menten type of response and is often approximated by the Hill function. Six types of URMs can be commonly found in intracellular molecular networks and each has a distinct kinetic mechanism for signal amplification. These URMs are: (i) positive cooperative binding, (ii) homo-multimerization, (iii) multistep signalling, (iv) molecular titration, (v) zero-order covalent modification cycle and (vi) positive feedback. Multiple URMs can be combined to generate highly switch-like responses. Serving as basic signal amplifiers, these URMs are essential for molecular circuits to produce complex nonlinear dynamics, including multistability, robust adaptation and oscillation. These dynamic properties are in turn responsible for higher-level cellular behaviours, such as cell fate determination, homeostasis and biological rhythm. PMID:23615029

Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2014-01-01

Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. This study illustrates that we can

Molecular evolution of multiple arylalkylamine N-acetyltransferase (AANAT) in fish.

PubMed

Zilberman-Peled, Bina; Bransburg-Zabary, Sharron; Klein, David C; Gothilf, Yoav

2011-01-01

Arylalkylamine N-acetyltransferase (AANAT) catalyzes the transfer of an acetyl group from acetyl coenzyme A (AcCoA) to arylalkylamines, including indolethylamines and phenylethylamines. Multiple aanats are present in teleost fish as a result of whole genome and gene duplications. Fish aanat1a and aanat2 paralogs display different patterns of tissue expression and encode proteins with different substrate preference: AANAT1a is expressed in the retina, and acetylates both indolethylamines and phenylethylamines; while AANAT2 is expressed in the pineal gland, and preferentially acetylates indolethylamines. The two enzymes are therefore thought to serve different roles. Here, the molecular changes that led to their specialization were studied by investigating the structure-function relationships of AANATs in the gilthead seabream (sb, Sperus aurata). Acetylation activity of reciprocal mutated enzymes pointed to specific residues that contribute to substrate specificity of the enzymes. Inhibition tests followed by complementary analyses of the predicted three-dimensional models of the enzymes, suggested that both phenylethylamines and indolethylamines bind to the catalytic pocket of both enzymes. These results suggest that substrate selectivity of AANAT1a and AANAT2 is determined by the positioning of the substrate within the catalytic pocket, and its accessibility to catalysis. This illustrates the evolutionary process by which enzymes encoded by duplicated genes acquire different activities and play different biological roles.

Ab initio molecular dynamics with nuclear quantum effects at classical cost: Ring polymer contraction for density functional theory.

PubMed

Marsalek, Ondrej; Markland, Thomas E

2016-02-07

Path integral molecular dynamics simulations, combined with an ab initio evaluation of interactions using electronic structure theory, incorporate the quantum mechanical nature of both the electrons and nuclei, which are essential to accurately describe systems containing light nuclei. However, path integral simulations have traditionally required a computational cost around two orders of magnitude greater than treating the nuclei classically, making them prohibitively costly for most applications. Here we show that the cost of path integral simulations can be dramatically reduced by extending our ring polymer contraction approach to ab initio molecular dynamics simulations. By using density functional tight binding as a reference system, we show that our ring polymer contraction scheme gives rapid and systematic convergence to the full path integral density functional theory result. We demonstrate the efficiency of this approach in ab initio simulations of liquid water and the reactive protonated and deprotonated water dimer systems. We find that the vast majority of the nuclear quantum effects are accurately captured using contraction to just the ring polymer centroid, which requires the same number of density functional theory calculations as a classical simulation. Combined with a multiple time step scheme using the same reference system, which allows the time step to be increased, this approach is as fast as a typical classical ab initio molecular dynamics simulation and 35× faster than a full path integral calculation, while still exactly including the quantum sampling of nuclei. This development thus offers a route to routinely include nuclear quantum effects in ab initio molecular dynamics simulations at negligible computational cost.

Integrated ozone and biotreatment of pulp mill effluent and changes in biodegradability and molecular weight distribution of organic compounds.

PubMed

Bijan, Leila; Mohseni, Madjid

2005-10-01

The overall effectiveness of integrating ozonation with biological treatment on the biodegradability enhancement and recalcitrant organic matter (ROM) removal from pulp mill alkaline bleach plant effluent was investigated. Ozonation was performed in a semi-batch bubble column reactor at pH of 11 and 4.5. Batch biological treatment was conducted in shake flasks. Samples obtained during the treatments were monitored for BOD5, COD, TOC, and molecular weight distribution. At an ozone dosage of 0.7-0.8 mg O3/mL wastewater, integrated treatment showed about 30% higher TOC mineralization compared to individual ozonation or biotreatment. Ozone treatment enhanced the biodegradability of the effluent (monitored as 21% COD reduction and 13% BOD5 enhancement), allowing for a higher removal of pollutants. The conversion of high molecular weight (HMW) to low molecular weight (LMW) compounds was an important factor in the overall biodegradability enhancement of the alkaline effluent. The overall biodegradability of the LMW compounds did not change over the course of ozonation, but it increased from 5% to 50% (measured as COD removal) for the HMW portion. Ozonation at pH of 11 was more effective than that at pH of 4.5 in terms of generating more biodegradable compounds.

Multilevel functional genomics data integration as a tool for understanding physiology: a network biology perspective.

PubMed

Davidsen, Peter K; Turan, Nil; Egginton, Stuart; Falciani, Francesco

2016-02-01

The overall aim of physiological research is to understand how living systems function in an integrative manner. Consequently, the discipline of physiology has since its infancy attempted to link multiple levels of biological organization. Increasingly this has involved mathematical and computational approaches, typically to model a small number of components spanning several levels of biological organization. With the advent of "omics" technologies, which can characterize the molecular state of a cell or tissue (intended as the level of expression and/or activity of its molecular components), the number of molecular components we can quantify has increased exponentially. Paradoxically, the unprecedented amount of experimental data has made it more difficult to derive conceptual models underlying essential mechanisms regulating mammalian physiology. We present an overview of state-of-the-art methods currently used to identifying biological networks underlying genomewide responses. These are based on a data-driven approach that relies on advanced computational methods designed to "learn" biology from observational data. In this review, we illustrate an application of these computational methodologies using a case study integrating an in vivo model representing the transcriptional state of hypoxic skeletal muscle with a clinical study representing muscle wasting in chronic obstructive pulmonary disease patients. The broader application of these approaches to modeling multiple levels of biological data in the context of modern physiology is discussed. Copyright © 2016 the American Physiological Society.

Young LMC clusters: the role of red supergiants and multiple stellar populations in their integrated light and CMDs

NASA Astrophysics Data System (ADS)

Asa'd, Randa S.; Vazdekis, Alexandre; Cerviño, Miguel; Noël, Noelia E. D.; Beasley, Michael A.; Kassab, Mahmoud

2017-11-01

The optical integrated spectra of three Large Magellanic Cloud young stellar clusters (NGC 1984, NGC 1994 and NGC 2011) exhibit concave continua and prominent molecular bands which deviate significantly from the predictions of single stellar population (SSP) models. In order to understand the appearance of these spectra, we create a set of young stellar population (MILES) models, which we make available to the community. We use archival International Ultraviolet Explorer integrated UV spectra to independently constrain the cluster masses and extinction, and rule out strong stochastic effects in the optical spectra. In addition, we also analyse deep colour-magnitude diagrams of the clusters to provide independent age determinations based on isochrone fitting. We explore hypotheses, including age spreads in the clusters, a top-heavy initial mass function, different SSP models and the role of red supergiant stars (RSG). We find that the strong molecular features in the optical spectra can be only reproduced by modelling an increased fraction of about ˜20 per cent by luminosity of RSG above what is predicted by canonical stellar evolution models. Given the uncertainties in stellar evolution at Myr ages, we cannot presently rule out the presence of Myr age spreads in these clusters. Our work combines different wavelengths as well as different approaches (resolved data as well as integrated spectra for the same sample) in order to reveal the complete picture. We show that each approach provides important information but in combination we can better understand the cluster stellar populations.

An integrated computational approach of molecular dynamics simulations, receptor binding studies and pharmacophore mapping analysis in search of potent inhibitors against tuberculosis.

PubMed

Agarwal, Shivangi; Verma, Ekta; Kumar, Vivek; Lall, Namrita; Sau, Samaresh; Iyer, Arun K; Kashaw, Sushil K

2018-05-03

Tuberculosis is an infectious chronic disease caused by obligate pathogen Mycobacterium tuberculosis that affects millions of people worldwide. Although many first and second line drugs are available for its treatment, but their irrational use has adversely lead to the emerging cases of multiple drug resistant and extensively drug-resistant tuberculosis. Therefore, there is an intense need to develop novel potent analogues for its treatment. This has prompted us to develop potent analogues against TB. The Mycobacterium tuberculosis genome provides us with number of validated targets to combat against TB. Study of Mtb genome disclosed six epoxide hydrolases (A to F) which convert harmful epoxide into diols and act as a potential drug target for rational drug design. Our current strategy is to develop such analogues which inhibits epoxide hydrolase enzyme present in Mtb genome. To achieve this, we adopted an integrated computational approach involving QSAR, pharmacophore mapping, molecular docking and molecular dynamics simulation studies. The approach envisaged vital information about the role of molecular descriptors, essential pharmacophoric features and binding energy for compounds to bind into the active site of epoxide hydrolase. Molecular docking analysis revealed that analogues exhibited significant binding to Mtb epoxide hydrolase. Further, three docked complexes 2s, 37s and 15s with high, moderate and low docking scores respectively were selected for molecular dynamics simulation studies. RMSD analysis revealed that all complexes are stable with average RMSD below 2 Å throughout the 10 ns simulations. The B-factor analysis showed that the active site residues of epoxide hydrolase are flexible enough to interact with inhibitor. Moreover, to confirm the binding of these urea derivatives, MM-GBSA binding energy analysis were performed. The calculations showed that 37s has more binding affinity (ΔGtotal = -52.24 kcal/mol) towards epoxide hydrolase

The continuous end-state comfort effect: weighted integration of multiple biases.

PubMed

Herbort, Oliver; Butz, Martin V

2012-05-01

The grasp orientation when grasping an object is frequently aligned in anticipation of the intended rotation of the object (end-state comfort effect). We analyzed grasp orientation selection in a continuous task to determine the mechanisms underlying the end-state comfort effect. Participants had to grasp a box by a circular handle-which allowed for arbitrary grasp orientations-and then had to rotate the box by various angles. Experiments 1 and 2 revealed both that the rotation's direction considerably determined grasp orientations and that end-postures varied considerably. Experiments 3 and 4 further showed that visual stimuli and initial arm postures biased grasp orientations if the intended rotation could be easily achieved. The data show that end-state comfort but also other factors determine grasp orientation selection. A simple mechanism that integrates multiple weighted biases can account for the data.

shinyGISPA: A web application for characterizing phenotype by gene sets using multiple omics data combinations.

PubMed

Dwivedi, Bhakti; Kowalski, Jeanne

2018-01-01

While many methods exist for integrating multi-omics data or defining gene sets, there is no one single tool that defines gene sets based on merging of multiple omics data sets. We present shinyGISPA, an open-source application with a user-friendly web-based interface to define genes according to their similarity in several molecular changes that are driving a disease phenotype. This tool was developed to help facilitate the usability of a previously published method, Gene Integrated Set Profile Analysis (GISPA), among researchers with limited computer-programming skills. The GISPA method allows the identification of multiple gene sets that may play a role in the characterization, clinical application, or functional relevance of a disease phenotype. The tool provides an automated workflow that is highly scalable and adaptable to applications that go beyond genomic data merging analysis. It is available at http://shinygispa.winship.emory.edu/shinyGISPA/.

shinyGISPA: A web application for characterizing phenotype by gene sets using multiple omics data combinations

PubMed Central

Dwivedi, Bhakti

2018-01-01

While many methods exist for integrating multi-omics data or defining gene sets, there is no one single tool that defines gene sets based on merging of multiple omics data sets. We present shinyGISPA, an open-source application with a user-friendly web-based interface to define genes according to their similarity in several molecular changes that are driving a disease phenotype. This tool was developed to help facilitate the usability of a previously published method, Gene Integrated Set Profile Analysis (GISPA), among researchers with limited computer-programming skills. The GISPA method allows the identification of multiple gene sets that may play a role in the characterization, clinical application, or functional relevance of a disease phenotype. The tool provides an automated workflow that is highly scalable and adaptable to applications that go beyond genomic data merging analysis. It is available at http://shinygispa.winship.emory.edu/shinyGISPA/. PMID:29415010

QwikMD — Integrative Molecular Dynamics Toolkit for Novices and Experts

PubMed Central

Ribeiro, João V.; Bernardi, Rafael C.; Rudack, Till; Stone, John E.; Phillips, James C.; Freddolino, Peter L.; Schulten, Klaus

2016-01-01

The proper functioning of biomolecules in living cells requires them to assume particular structures and to undergo conformational changes. Both biomolecular structure and motion can be studied using a wide variety of techniques, but none offers the level of detail as do molecular dynamics (MD) simulations. Integrating two widely used modeling programs, namely NAMD and VMD, we have created a robust, user-friendly software, QwikMD, which enables novices and experts alike to address biomedically relevant questions, where often only molecular dynamics simulations can provide answers. Performing both simple and advanced MD simulations interactively, QwikMD automates as many steps as necessary for preparing, carrying out, and analyzing simulations while checking for common errors and enabling reproducibility. QwikMD meets also the needs of experts in the field, increasing the efficiency and quality of their work by carrying out tedious or repetitive tasks while enabling easy control of every step. Whether carrying out simulations within the live view mode on a small laptop or performing complex and large simulations on supercomputers or Cloud computers, QwikMD uses the same steps and user interface. QwikMD is freely available by download on group and personal computers. It is also available on the cloud at Amazon Web Services. PMID:27216779

QwikMD — Integrative Molecular Dynamics Toolkit for Novices and Experts

NASA Astrophysics Data System (ADS)

Ribeiro, João V.; Bernardi, Rafael C.; Rudack, Till; Stone, John E.; Phillips, James C.; Freddolino, Peter L.; Schulten, Klaus

2016-05-01

The proper functioning of biomolecules in living cells requires them to assume particular structures and to undergo conformational changes. Both biomolecular structure and motion can be studied using a wide variety of techniques, but none offers the level of detail as do molecular dynamics (MD) simulations. Integrating two widely used modeling programs, namely NAMD and VMD, we have created a robust, user-friendly software, QwikMD, which enables novices and experts alike to address biomedically relevant questions, where often only molecular dynamics simulations can provide answers. Performing both simple and advanced MD simulations interactively, QwikMD automates as many steps as necessary for preparing, carrying out, and analyzing simulations while checking for common errors and enabling reproducibility. QwikMD meets also the needs of experts in the field, increasing the efficiency and quality of their work by carrying out tedious or repetitive tasks while enabling easy control of every step. Whether carrying out simulations within the live view mode on a small laptop or performing complex and large simulations on supercomputers or Cloud computers, QwikMD uses the same steps and user interface. QwikMD is freely available by download on group and personal computers. It is also available on the cloud at Amazon Web Services.

ULTIMATE: a deployable multiple integral field unit for Subaru

NASA Astrophysics Data System (ADS)

Ellis, S. C.; Zhelem, Ross; Brown, David; Staszak, Nicholas F.; Lidman, Chris; Nataf, David M.; Casey, Andrew R.; Xavier, Pascal; Sheinis, Andrew; Gillingham, Peter; Tims, Julia; Lawrence, Jon; Bryant, Julia; Sharp, Rob

2016-08-01

ULTIMATE is an instrument concept under development at the AAO, for the Subaru Telescope, which will have the unique combination of ground layer adaptive optics feeding multiple deployable integral field units. This will allow ULTIMATE to probe unexplored parameter space, enabling science cases such as the evolution of galaxies at z 0:5 to 1.5, and the dark matter content of the inner part of our Galaxy. ULTIMATE will use Starbugs to position between 7 and 13 IFUs over a 14 × 8 arcmin field-of-view, pro- vided by a new wide-field corrector. All Starbugs can be positioned simultaneously, to an accuracy of better than 5 milli-arcsec within the typical slew-time of the telescope, allowing for very efficient re-configuration between observations. The IFUs will feed either the near-infrared nuMOIRCS or the visible/ near-infrared PFS spectrographs, or both. Future possible upgrades include the possibility of purpose built spectrographs and incorporating OH suppression using fibre Bragg gratings. We describe the science case and resulting design requirements, the baseline instrument concept, and the expected performance of the instrument.

Disease-specific molecular events in cortical multiple sclerosis lesions

PubMed Central

Wimmer, Isabella; Höftberger, Romana; Gerlach, Susanna; Haider, Lukas; Zrzavy, Tobias; Hametner, Simon; Mahad, Don; Binder, Christoph J.; Krumbholz, Markus; Bauer, Jan; Bradl, Monika

2013-01-01

Cortical lesions constitute an important part of multiple sclerosis pathology. Although inflammation appears to play a role in their formation, the mechanisms leading to demyelination and neurodegeneration are poorly understood. We aimed to identify some of these mechanisms by combining gene expression studies with neuropathological analysis. In our study, we showed that the combination of inflammation, plaque-like primary demyelination and neurodegeneration in the cortex is specific for multiple sclerosis and is not seen in other chronic inflammatory diseases mediated by CD8-positive T cells (Rasmussen’s encephalitis), B cells (B cell lymphoma) or complex chronic inflammation (tuberculous meningitis, luetic meningitis or chronic purulent meningitis). In addition, we performed genome-wide microarray analysis comparing micro-dissected active cortical multiple sclerosis lesions with those of tuberculous meningitis (inflammatory control), Alzheimer’s disease (neurodegenerative control) and with cortices of age-matched controls. More than 80% of the identified multiple sclerosis-specific genes were related to T cell-mediated inflammation, microglia activation, oxidative injury, DNA damage and repair, remyelination and regenerative processes. Finally, we confirmed by immunohistochemistry that oxidative damage in cortical multiple sclerosis lesions is associated with oligodendrocyte and neuronal injury, the latter also affecting axons and dendrites. Our study provides new insights into the complex mechanisms of neurodegeneration and regeneration in the cortex of patients with multiple sclerosis. PMID:23687122

Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

PubMed Central

Chen, Tianle; Zeng, Donglin

2015-01-01

Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

Personalizing Chinese medicine by integrating molecular features of diseases and herb ingredient information: application to acute myeloid leukemia

PubMed Central

Xie, Duoli; Shi, Tieliu; Wen, Chengping

2017-01-01

Traditional Chinese Medicine (TCM) has been widely used as a complementary medicine in Acute Myeloid Leukemia (AML) treatment. In this study, we proposed a new classification of Chinese Medicines (CMs) by integrating the latest discoveries in disease molecular mechanisms and traditional medicine theory. We screened out a set of chemical compounds on basis of AML differential expression genes and chemical-protein interactions and then mapped them to Traditional Chinese Medicine Integrated Database. 415 CMs contain those compounds and they were categorized into 8 groups according to the Traditional Chinese Pharmacology. Pathway analysis and synthetic lethality gene pairs were applied to analyze the dissimilarity, generality and intergroup relations of different groups. We defined hub CM pairs and alternative CM groups based on the analysis result and finally proposed a formula to form an effective anti-AML prescription which combined the hub CM pairs with alternative CMs according to patients’ molecular features. Our method of formulating CMs based on patients’ stratification provides novel insights into the new usage of conventional CMs and will promote TCM modernization. PMID:28454110

Personalizing Chinese medicine by integrating molecular features of diseases and herb ingredient information: application to acute myeloid leukemia.

PubMed

Huang, Lin; Li, Haichang; Xie, Duoli; Shi, Tieliu; Wen, Chengping

2017-06-27

Traditional Chinese Medicine (TCM) has been widely used as a complementary medicine in Acute Myeloid Leukemia (AML) treatment. In this study, we proposed a new classification of Chinese Medicines (CMs) by integrating the latest discoveries in disease molecular mechanisms and traditional medicine theory. We screened out a set of chemical compounds on basis of AML differential expression genes and chemical-protein interactions and then mapped them to Traditional Chinese Medicine Integrated Database. 415 CMs contain those compounds and they were categorized into 8 groups according to the Traditional Chinese Pharmacology. Pathway analysis and synthetic lethality gene pairs were applied to analyze the dissimilarity, generality and intergroup relations of different groups. We defined hub CM pairs and alternative CM groups based on the analysis result and finally proposed a formula to form an effective anti-AML prescription which combined the hub CM pairs with alternative CMs according to patients' molecular features. Our method of formulating CMs based on patients' stratification provides novel insights into the new usage of conventional CMs and will promote TCM modernization.

Accurate and efficient integration for molecular dynamics simulations at constant temperature and pressure

NASA Astrophysics Data System (ADS)

Lippert, Ross A.; Predescu, Cristian; Ierardi, Douglas J.; Mackenzie, Kenneth M.; Eastwood, Michael P.; Dror, Ron O.; Shaw, David E.

2013-10-01

In molecular dynamics simulations, control over temperature and pressure is typically achieved by augmenting the original system with additional dynamical variables to create a thermostat and a barostat, respectively. These variables generally evolve on timescales much longer than those of particle motion, but typical integrator implementations update the additional variables along with the particle positions and momenta at each time step. We present a framework that replaces the traditional integration procedure with separate barostat, thermostat, and Newtonian particle motion updates, allowing thermostat and barostat updates to be applied infrequently. Such infrequent updates provide a particularly substantial performance advantage for simulations parallelized across many computer processors, because thermostat and barostat updates typically require communication among all processors. Infrequent updates can also improve accuracy by alleviating certain sources of error associated with limited-precision arithmetic. In addition, separating the barostat, thermostat, and particle motion update steps reduces certain truncation errors, bringing the time-average pressure closer to its target value. Finally, this framework, which we have implemented on both general-purpose and special-purpose hardware, reduces software complexity and improves software modularity.

An integrated voice and data multiple-access scheme for a land-mobile satellite system

NASA Technical Reports Server (NTRS)

Li, V. O. K.; Yan, T.-Y.

1984-01-01

An analytical study is performed of the satellite requirements for a land mobile satellite system (LMSS). The spacecraft (MSAT-X) would be in GEO and would be compatible with multiple access by mobile radios and antennas and fixed stations. The FCC has received a petition from NASA to reserve the 821-825 and 866-870 MHz frequencies for the LMSS, while communications with fixed earth stations would be in the Ku band. MSAT-X transponders would alter the frequencies of signal and do no processing in the original configuration considered. Channel use would be governed by an integrated demand-assigned, multiple access protocol, which would divide channels into reservation and information channels, governed by a network management center. Further analyses will cover tradeoffs between data and voice users, probability of blocking, and the performance impacts of on-board switching and variable bandwidth assignment. Initial calculations indicate that a large traffic volume can be handled with acceptable delays and voice blocking probabilities.

An integrated voice and data multiple-access scheme for a land-mobile satellite system

NASA Astrophysics Data System (ADS)

Li, V. O. K.; Yan, T.-Y.

1984-11-01

An analytical study is performed of the satellite requirements for a land mobile satellite system (LMSS). The spacecraft (MSAT-X) would be in GEO and would be compatible with multiple access by mobile radios and antennas and fixed stations. The FCC has received a petition from NASA to reserve the 821-825 and 866-870 MHz frequencies for the LMSS, while communications with fixed earth stations would be in the Ku band. MSAT-X transponders would alter the frequencies of signal and do no processing in the original configuration considered. Channel use would be governed by an integrated demand-assigned, multiple access protocol, which would divide channels into reservation and information channels, governed by a network management center. Further analyses will cover tradeoffs between data and voice users, probability of blocking, and the performance impacts of on-board switching and variable bandwidth assignment. Initial calculations indicate that a large traffic volume can be handled with acceptable delays and voice blocking probabilities.

Optimal Operation System of the Integrated District Heating System with Multiple Regional Branches

NASA Astrophysics Data System (ADS)

Kim, Ui Sik; Park, Tae Chang; Kim, Lae-Hyun; Yeo, Yeong Koo

This paper presents an optimal production and distribution management for structural and operational optimization of the integrated district heating system (DHS) with multiple regional branches. A DHS consists of energy suppliers and consumers, district heating pipelines network and heat storage facilities in the covered region. In the optimal management system, production of heat and electric power, regional heat demand, electric power bidding and sales, transport and storage of heat at each regional DHS are taken into account. The optimal management system is formulated as a mixed integer linear programming (MILP) where the objectives is to minimize the overall cost of the integrated DHS while satisfying the operation constraints of heat units and networks as well as fulfilling heating demands from consumers. Piecewise linear formulation of the production cost function and stairwise formulation of the start-up cost function are used to compute nonlinear cost function approximately. Evaluation of the total overall cost is based on weekly operations at each district heat branches. Numerical simulations show the increase of energy efficiency due to the introduction of the present optimal management system.

Optimized breeding strategies for multiple trait integration: II. Process efficiency in event pyramiding and trait fixation.

PubMed

Peng, Ting; Sun, Xiaochun; Mumm, Rita H

2014-01-01

Multiple trait integration (MTI) is a multi-step process of converting an elite variety/hybrid for value-added traits (e.g. transgenic events) through backcross breeding. From a breeding standpoint, MTI involves four steps: single event introgression, event pyramiding, trait fixation, and version testing. This study explores the feasibility of marker-aided backcross conversion of a target maize hybrid for 15 transgenic events in the light of the overall goal of MTI of recovering equivalent performance in the finished hybrid conversion along with reliable expression of the value-added traits. Using the results to optimize single event introgression (Peng et al. Optimized breeding strategies for multiple trait integration: I. Minimizing linkage drag in single event introgression. Mol Breed, 2013) which produced single event conversions of recurrent parents (RPs) with ≤8 cM of residual non-recurrent parent (NRP) germplasm with ~1 cM of NRP germplasm in the 20 cM regions flanking the event, this study focused on optimizing process efficiency in the second and third steps in MTI: event pyramiding and trait fixation. Using computer simulation and probability theory, we aimed to (1) fit an optimal breeding strategy for pyramiding of eight events into the female RP and seven in the male RP, and (2) identify optimal breeding strategies for trait fixation to create a 'finished' conversion of each RP homozygous for all events. In addition, next-generation seed needs were taken into account for a practical approach to process efficiency. Building on work by Ishii and Yonezawa (Optimization of the marker-based procedures for pyramiding genes from multiple donor lines: I. Schedule of crossing between the donor lines. Crop Sci 47:537-546, 2007a), a symmetric crossing schedule for event pyramiding was devised for stacking eight (seven) events in a given RP. Options for trait fixation breeding strategies considered selfing and doubled haploid approaches to achieve homozygosity

Molecular Mechanics of the Moisture Effect on Epoxy/Carbon Nanotube Nanocomposites.

PubMed

Tam, Lik-Ho; Wu, Chao

2017-10-13

The strong structural integrity of polymer nanocomposite is influenced in the moist environment; but the fundamental mechanism is unclear, including the basis for the interactions between the absorbed water molecules and the structure, which prevents us from predicting the durability of its applications across multiple scales. In this research, a molecular dynamics model of the epoxy/single-walled carbon nanotube (SWCNT) nanocomposite is constructed to explore the mechanism of the moisture effect, and an analysis of the molecular interactions is provided by focusing on the hydrogen bond (H-bond) network inside the nanocomposite structure. The simulations show that at low moisture concentration, the water molecules affect the molecular interactions by favorably forming the water-nanocomposite H-bonds and the small cluster, while at high concentration the water molecules predominantly form the water-water H-bonds and the large cluster. The water molecules in the epoxy matrix and the epoxy-SWCNT interface disrupt the molecular interactions and deteriorate the mechanical properties. Through identifying the link between the water molecules and the nanocomposite structure and properties, it is shown that the free volume in the nanocomposite is crucial for its structural integrity, which facilitates the moisture accumulation and the distinct material deteriorations. This study provides insights into the moisture-affected structure and properties of the nanocomposite from the nanoscale perspective, which contributes to the understanding of the nanocomposite long-term performance under the moisture effect.

Molecular Mechanics of the Moisture Effect on Epoxy/Carbon Nanotube Nanocomposites

PubMed Central

2017-01-01

The strong structural integrity of polymer nanocomposite is influenced in the moist environment; but the fundamental mechanism is unclear, including the basis for the interactions between the absorbed water molecules and the structure, which prevents us from predicting the durability of its applications across multiple scales. In this research, a molecular dynamics model of the epoxy/single-walled carbon nanotube (SWCNT) nanocomposite is constructed to explore the mechanism of the moisture effect, and an analysis of the molecular interactions is provided by focusing on the hydrogen bond (H-bond) network inside the nanocomposite structure. The simulations show that at low moisture concentration, the water molecules affect the molecular interactions by favorably forming the water-nanocomposite H-bonds and the small cluster, while at high concentration the water molecules predominantly form the water-water H-bonds and the large cluster. The water molecules in the epoxy matrix and the epoxy-SWCNT interface disrupt the molecular interactions and deteriorate the mechanical properties. Through identifying the link between the water molecules and the nanocomposite structure and properties, it is shown that the free volume in the nanocomposite is crucial for its structural integrity, which facilitates the moisture accumulation and the distinct material deteriorations. This study provides insights into the moisture-affected structure and properties of the nanocomposite from the nanoscale perspective, which contributes to the understanding of the nanocomposite long-term performance under the moisture effect. PMID:29027979

An ICT infrastructure to integrate clinical and molecular data in oncology research

PubMed Central

2012-01-01

Background The ONCO-i2b2 platform is a bioinformatics tool designed to integrate clinical and research data and support translational research in oncology. It is implemented by the University of Pavia and the IRCCS Fondazione Maugeri hospital (FSM), and grounded on the software developed by the Informatics for Integrating Biology and the Bedside (i2b2) research center. I2b2 has delivered an open source suite based on a data warehouse, which is efficiently interrogated to find sets of interesting patients through a query tool interface. Methods Onco-i2b2 integrates data coming from multiple sources and allows the users to jointly query them. I2b2 data are then stored in a data warehouse, where facts are hierarchically structured as ontologies. Onco-i2b2 gathers data from the FSM pathology unit (PU) database and from the hospital biobank and merges them with the clinical information from the hospital information system. Our main effort was to provide a robust integrated research environment, giving a particular emphasis to the integration process and facing different challenges, consecutively listed: biospecimen samples privacy and anonymization; synchronization of the biobank database with the i2b2 data warehouse through a series of Extract, Transform, Load (ETL) operations; development and integration of a Natural Language Processing (NLP) module, to retrieve coded information, such as SNOMED terms and malignant tumors (TNM) classifications, and clinical tests results from unstructured medical records. Furthermore, we have developed an internal SNOMED ontology rested on the NCBO BioPortal web services. Results Onco-i2b2 manages data of more than 6,500 patients with breast cancer diagnosis collected between 2001 and 2011 (over 390 of them have at least one biological sample in the cancer biobank), more than 47,000 visits and 96,000 observations over 960 medical concepts. Conclusions Onco-i2b2 is a concrete example of how integrated Information and Communication

Integrated data analysis for genome-wide research.

PubMed

Steinfath, Matthias; Repsilber, Dirk; Scholz, Matthias; Walther, Dirk; Selbig, Joachim

2007-01-01

Integrated data analysis is introduced as the intermediate level of a systems biology approach to analyse different 'omics' datasets, i.e., genome-wide measurements of transcripts, protein levels or protein-protein interactions, and metabolite levels aiming at generating a coherent understanding of biological function. In this chapter we focus on different methods of correlation analyses ranging from simple pairwise correlation to kernel canonical correlation which were recently applied in molecular biology. Several examples are presented to illustrate their application. The input data for this analysis frequently originate from different experimental platforms. Therefore, preprocessing steps such as data normalisation and missing value estimation are inherent to this approach. The corresponding procedures, potential pitfalls and biases, and available software solutions are reviewed. The multiplicity of observations obtained in omics-profiling experiments necessitates the application of multiple testing correction techniques.

Development of Integrative STEM Curriculum: A Multiple Case Study of Multi-Disciplinary Teams in Two Pennsylvania High Schools

ERIC Educational Resources Information Center

Rider-Bertrand, Joey H.

2017-01-01

At the start of the 21st century, STEM education was a new priority in many schools as the focus shifted from separate disciplines to integrative STEM education. Unfortunately, there was limited research to offer guidance to practitioners (Brown, 2012; Honey, Pearson & Schweingruber, 2014). This qualitative, multiple case study explored the…

An integrative computational approach for prioritization of genomic variants

DOE PAGES

Dubchak, Inna; Balasubramanian, Sandhya; Wang, Sheng; ...

2014-12-15

An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidatemore » genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. This study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.« less

3D plasmonic nanoantennas integrated with MEA biosensors.

PubMed

Dipalo, Michele; Messina, Gabriele C; Amin, Hayder; La Rocca, Rosanna; Shalabaeva, Victoria; Simi, Alessandro; Maccione, Alessandro; Zilio, Pierfrancesco; Berdondini, Luca; De Angelis, Francesco

2015-02-28

Neuronal signaling in brain circuits occurs at multiple scales ranging from molecules and cells to large neuronal assemblies. However, current sensing neurotechnologies are not designed for parallel access of signals at multiple scales. With the aim of combining nanoscale molecular sensing with electrical neural activity recordings within large neuronal assemblies, in this work three-dimensional (3D) plasmonic nanoantennas are integrated with multielectrode arrays (MEA). Nanoantennas are fabricated by fast ion beam milling on optical resist; gold is deposited on the nanoantennas in order to connect them electrically to the MEA microelectrodes and to obtain plasmonic behavior. The optical properties of these 3D nanostructures are studied through finite elements method (FEM) simulations that show a high electromagnetic field enhancement. This plasmonic enhancement is confirmed by surface enhancement Raman spectroscopy of a dye performed in liquid, which presents an enhancement of almost 100 times the incident field amplitude at resonant excitation. Finally, the reported MEA devices are tested on cultured rat hippocampal neurons. Neurons develop by extending branches on the nanostructured electrodes and extracellular action potentials are recorded over multiple days in vitro. Raman spectra of living neurons cultured on the nanoantennas are also acquired. These results highlight that these nanostructures could be potential candidates for combining electrophysiological measures of large networks with simultaneous spectroscopic investigations at the molecular level.

Accelerating ab initio path integral molecular dynamics with multilevel sampling of potential surface

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

Geng, Hua Y., E-mail: huay.geng@gmail.com; Department of Chemistry and Chemical Biology, Cornell University, Baker Laboratory, Ithaca, NY 14853

A multilevel approach to sample the potential energy surface in a path integral formalism is proposed. The purpose is to reduce the required number of ab initio evaluations of energy and forces in ab initio path integral molecular dynamics (AI-PIMD) simulation, without compromising the overall accuracy. To validate the method, the internal energy and free energy of an Einstein crystal are calculated and compared with the analytical solutions. As a preliminary application, we assess the performance of the method in a realistic model—the FCC phase of dense atomic hydrogen, in which the calculated result shows that the acceleration rate ismore » about 3 to 4-fold for a two-level implementation, and can be increased up to 10 times if extrapolation is used. With only 16 beads used for the ab initio potential sampling, this method gives a well converged internal energy. The residual error in pressure is just about 3 GPa, whereas it is about 20 GPa for a plain AI-PIMD calculation with the same number of beads. The vibrational free energy of the FCC phase of dense hydrogen at 300 K is also calculated with an AI-PIMD thermodynamic integration method, which gives a result of about 0.51 eV/proton at a density of r{sub s}=0.912.« less

Gene integrated set profile analysis: a context-based approach for inferring biological endpoints

PubMed Central

Kowalski, Jeanne; Dwivedi, Bhakti; Newman, Scott; Switchenko, Jeffery M.; Pauly, Rini; Gutman, David A.; Arora, Jyoti; Gandhi, Khanjan; Ainslie, Kylie; Doho, Gregory; Qin, Zhaohui; Moreno, Carlos S.; Rossi, Michael R.; Vertino, Paula M.; Lonial, Sagar; Bernal-Mizrachi, Leon; Boise, Lawrence H.

2016-01-01

The identification of genes with specific patterns of change (e.g. down-regulated and methylated) as phenotype drivers or samples with similar profiles for a given gene set as drivers of clinical outcome, requires the integration of several genomic data types for which an ‘integrate by intersection’ (IBI) approach is often applied. In this approach, results from separate analyses of each data type are intersected, which has the limitation of a smaller intersection with more data types. We introduce a new method, GISPA (Gene Integrated Set Profile Analysis) for integrated genomic analysis and its variation, SISPA (Sample Integrated Set Profile Analysis) for defining respective genes and samples with the context of similar, a priori specified molecular profiles. With GISPA, the user defines a molecular profile that is compared among several classes and obtains ranked gene sets that satisfy the profile as drivers of each class. With SISPA, the user defines a gene set that satisfies a profile and obtains sample groups of profile activity. Our results from applying GISPA to human multiple myeloma (MM) cell lines contained genes of known profiles and importance, along with several novel targets, and their further SISPA application to MM coMMpass trial data showed clinical relevance. PMID:26826710

iASeq: integrative analysis of allele-specificity of protein-DNA interactions in multiple ChIP-seq datasets

PubMed Central

2012-01-01

Background ChIP-seq provides new opportunities to study allele-specific protein-DNA binding (ASB). However, detecting allelic imbalance from a single ChIP-seq dataset often has low statistical power since only sequence reads mapped to heterozygote SNPs are informative for discriminating two alleles. Results We develop a new method iASeq to address this issue by jointly analyzing multiple ChIP-seq datasets. iASeq uses a Bayesian hierarchical mixture model to learn correlation patterns of allele-specificity among multiple proteins. Using the discovered correlation patterns, the model allows one to borrow information across datasets to improve detection of allelic imbalance. Application of iASeq to 77 ChIP-seq samples from 40 ENCODE datasets and 1 genomic DNA sample in GM12878 cells reveals that allele-specificity of multiple proteins are highly correlated, and demonstrates the ability of iASeq to improve allelic inference compared to analyzing each individual dataset separately. Conclusions iASeq illustrates the value of integrating multiple datasets in the allele-specificity inference and offers a new tool to better analyze ASB. PMID:23194258

High Spectral Resolution Lidar Measurements of Multiple Scattering

NASA Technical Reports Server (NTRS)

Eloranta, E. W.; Piironen, P.

1996-01-01

The University of Wisconsin High Spectral Resolution Lidar (HSRL) provides unambiguous measurements of backscatter cross section, backscatter phase function, depolarization, and optical depth. This is accomplished by dividing the lidar return into separate particulate and molecular contributions. The molecular return is then used as a calibration target. We have modified the HSRL to use an I2 molecular absorption filter to separate aerosol and molecular signals. This allows measurement in dense clouds. Useful profiles extend above the cloud base until the two way optical depth reaches values between 5 and 6; beyond this, photon counting errors become large. In order to observe multiple scattering, the HSRL includes a channel which records the combined aerosol and molecular lidar return simultaneously with the spectrometer channel measurements of optical properties. This paper describes HSRL multiple scattering measurements from both water and ice clouds. These include signal strengths and depolarizations as a function of receiver field of view. All observations include profiles of extinction and backscatter cross sections. Measurements are also compared to predictions of a multiple scattering model based on small angle approximations.

Path-integral molecular dynamics simulations of hydrated hydrogen chloride cluster HCl(H 2O) 4 on a semiempirical potential energy surface

NASA Astrophysics Data System (ADS)

Takayanagi, Toshiyuki; Takahashi, Kenta; Kakizaki, Akira; Shiga, Motoyuki; Tachikawa, Masanori

2009-04-01

Path-integral molecular dynamics simulations for the HCl(H 2O) 4 cluster have been performed on the ground-state potential energy surface directly obtained on-the-fly from semiempirical PM3-MAIS molecular orbital calculations. It is found that the HCl(H 2O) 4 cluster has structural rearrangement above the temperature of 300 K showing a liquid-like behavior. Quantum mechanical fluctuation of hydrogen nuclei plays a significant role in structural arrangement processes in this cluster.

Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

Two-step relaxation mode analysis with multiple evolution times applied to all-atom molecular dynamics protein simulation.

PubMed

Karasawa, N; Mitsutake, A; Takano, H

2017-12-01

Proteins implement their functionalities when folded into specific three-dimensional structures, and their functions are related to the protein structures and dynamics. Previously, we applied a relaxation mode analysis (RMA) method to protein systems; this method approximately estimates the slow relaxation modes and times via simulation and enables investigation of the dynamic properties underlying the protein structural fluctuations. Recently, two-step RMA with multiple evolution times has been proposed and applied to a slightly complex homopolymer system, i.e., a single [n]polycatenane. This method can be applied to more complex heteropolymer systems, i.e., protein systems, to estimate the relaxation modes and times more accurately. In two-step RMA, we first perform RMA and obtain rough estimates of the relaxation modes and times. Then, we apply RMA with multiple evolution times to a small number of the slowest relaxation modes obtained in the previous calculation. Herein, we apply this method to the results of principal component analysis (PCA). First, PCA is applied to a 2-μs molecular dynamics simulation of hen egg-white lysozyme in aqueous solution. Then, the two-step RMA method with multiple evolution times is applied to the obtained principal components. The slow relaxation modes and corresponding relaxation times for the principal components are much improved by the second RMA.

Two-step relaxation mode analysis with multiple evolution times applied to all-atom molecular dynamics protein simulation

NASA Astrophysics Data System (ADS)

Karasawa, N.; Mitsutake, A.; Takano, H.

2017-12-01

Proteins implement their functionalities when folded into specific three-dimensional structures, and their functions are related to the protein structures and dynamics. Previously, we applied a relaxation mode analysis (RMA) method to protein systems; this method approximately estimates the slow relaxation modes and times via simulation and enables investigation of the dynamic properties underlying the protein structural fluctuations. Recently, two-step RMA with multiple evolution times has been proposed and applied to a slightly complex homopolymer system, i.e., a single [n ] polycatenane. This method can be applied to more complex heteropolymer systems, i.e., protein systems, to estimate the relaxation modes and times more accurately. In two-step RMA, we first perform RMA and obtain rough estimates of the relaxation modes and times. Then, we apply RMA with multiple evolution times to a small number of the slowest relaxation modes obtained in the previous calculation. Herein, we apply this method to the results of principal component analysis (PCA). First, PCA is applied to a 2-μ s molecular dynamics simulation of hen egg-white lysozyme in aqueous solution. Then, the two-step RMA method with multiple evolution times is applied to the obtained principal components. The slow relaxation modes and corresponding relaxation times for the principal components are much improved by the second RMA.

A Bio-Inspired Two-Layer Sensing Structure of Polypeptide and Multiple-Walled Carbon Nanotube to Sense Small Molecular Gases

PubMed Central

Wang, Li-Chun; Su, Tseng-Hsiung; Ho, Cheng-Long; Yang, Shang-Ren; Chiu, Shih-Wen; Kuo, Han-Wen; Tang, Kea-Tiong

2015-01-01

In this paper, we propose a bio-inspired, two-layer, multiple-walled carbon nanotube (MWCNT)-polypeptide composite sensing device. The MWCNT serves as a responsive and conductive layer, and the nonselective polypeptide (40 mer) coating the top of the MWCNT acts as a filter into which small molecular gases pass. Instead of using selective peptides to sense specific odorants, we propose using nonselective, peptide-based sensors to monitor various types of volatile organic compounds. In this study, depending on gas interaction and molecular sizes, the randomly selected polypeptide enabled the recognition of certain polar volatile chemical vapors, such as amines, and the improved discernment of low-concentration gases. The results of our investigation demonstrated that the polypeptide-coated sensors can detect ammonia at a level of several hundred ppm and barely responded to triethylamine. PMID:25751078

Pathview Web: user friendly pathway visualization and data integration.

PubMed

Luo, Weijun; Pant, Gaurav; Bhavnasi, Yeshvant K; Blanchard, Steven G; Brouwer, Cory

2017-07-03

Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and related model species

PubMed Central

Modise, David M.; Gemeildien, Junaid; Ndimba, Bongani K.; Christoffels, Alan

2018-01-01

Background Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations. Methods In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO), Trait Ontology (TO), Plant Ontology (PO), Growth Ontology (GRO) and Environment Ontology (EO) were used to semantically integrate drought related information. Results Target genes linked to Quantitative Trait Loci (QTLs) controlling yield and stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%), salt (32%), cold (20%), heat (8%) and oxidative stress (25%) were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co

Time step rescaling recovers continuous-time dynamical properties for discrete-time Langevin integration of nonequilibrium systems.

PubMed

Sivak, David A; Chodera, John D; Crooks, Gavin E

2014-06-19

When simulating molecular systems using deterministic equations of motion (e.g., Newtonian dynamics), such equations are generally numerically integrated according to a well-developed set of algorithms that share commonly agreed-upon desirable properties. However, for stochastic equations of motion (e.g., Langevin dynamics), there is still broad disagreement over which integration algorithms are most appropriate. While multiple desiderata have been proposed throughout the literature, consensus on which criteria are important is absent, and no published integration scheme satisfies all desiderata simultaneously. Additional nontrivial complications stem from simulating systems driven out of equilibrium using existing stochastic integration schemes in conjunction with recently developed nonequilibrium fluctuation theorems. Here, we examine a family of discrete time integration schemes for Langevin dynamics, assessing how each member satisfies a variety of desiderata that have been enumerated in prior efforts to construct suitable Langevin integrators. We show that the incorporation of a novel time step rescaling in the deterministic updates of position and velocity can correct a number of dynamical defects in these integrators. Finally, we identify a particular splitting (related to the velocity Verlet discretization) that has essentially universally appropriate properties for the simulation of Langevin dynamics for molecular systems in equilibrium, nonequilibrium, and path sampling contexts.

Molecularly Engineered Organic-Inorganic Hybrid Perovskite with Multiple Quantum Well Structure for Multicolored Light-Emitting Diodes

PubMed Central

Hu, Hongwei; Salim, Teddy; Chen, Bingbing; Lam, Yeng Ming

2016-01-01

Organic-inorganic hybrid perovskites have the potential to be used as a new class of emitters with tunable emission, high color purity and good ease of fabrication. Recent studies have so far been focused on three-dimensional (3D) perovskites, such as CH3NH3PbBr3 and CH3NH3PbI3 for green and infrared emission. Here, we explore a new series of hybrid perovskite emitters with a general formula of (C4H9NH3)2(CH3NH3)n−1PbnI3n+1 (where n = 1, 2, 3), which possesses a multiple quantum well structure. The quantum well thickness of these materials is adjustable through simple molecular engineering which results in a continuously tunable bandgap and emission spectra. Deep saturated red emission was obtained with a peak external quantum efficiency of 2.29% and a maximum luminance of 214 cd/m2. Green and blue LEDs were also demonstrated through halogen substitutions in these hybrid perovskites. We expect these results to open up the way towards high performance perovskite LEDs through molecular-structure engineering of these perovskite emitters. PMID:27633084

Fingolimod in relapsing multiple sclerosis: An integrated analysis of safety findings.

PubMed

Kappos, Ludwig; Cohen, Jeffrey; Collins, William; de Vera, Ana; Zhang-Auberson, Lixin; Ritter, Shannon; von Rosenstiel, Philipp; Francis, Gordon

2014-07-01

Fingolimod 0.5mg once daily is the first approved oral therapy for relapsing multiple sclerosis (MS). To report integrated long-term safety data from phase 2/3 fingolimod studies. Descriptive safety data are reported from the FTY720 Research Evaluating Effects of Daily Oral Therapy in Multiple Sclerosis (FREEDOMS) study, a 24-month, randomized, double-blind study comparing fingolimod 0.5mg and 1.25mg with placebo, and an All Studies group (patients who received fingolimod 0.5mg (n=1640) or 1.25-0.5mg (n=1776) in phase 2/3 studies and associated extensions). Relevant post-marketing experience, up to December 2011, is included. The incidence of adverse events (AEs) and serious AEs (SAEs) was similar with fingolimod and placebo in FREEDOMS. In the All Studies group, fingolimod 0.5mg was associated with transient, rarely symptomatic (0.5%), bradycardia and second-degree atrioventricular block on treatment initiation, minor blood pressure increases, frequent (9%) but generally asymptomatic liver enzyme elevations, and macular oedema (0.4%). The incidences of infections (including serious and herpes infections), malignancies, SAEs and treatment discontinuations due to AEs were similar with fingolimod 0.5mg and placebo. The safety profile of fingolimod has been well characterized in this large combined trial population. Although infrequent SAEs can occur, there is no increased risk of infections, malignancies or serious cardiovascular events versus placebo. Copyright © 2014. Published by Elsevier B.V.

A novel integrated framework and improved methodology of computer-aided drug design.

PubMed

Chen, Calvin Yu-Chian

2013-01-01

Computer-aided drug design (CADD) is a critical initiating step of drug development, but a single model capable of covering all designing aspects remains to be elucidated. Hence, we developed a drug design modeling framework that integrates multiple approaches, including machine learning based quantitative structure-activity relationship (QSAR) analysis, 3D-QSAR, Bayesian network, pharmacophore modeling, and structure-based docking algorithm. Restrictions for each model were defined for improved individual and overall accuracy. An integration method was applied to join the results from each model to minimize bias and errors. In addition, the integrated model adopts both static and dynamic analysis to validate the intermolecular stabilities of the receptor-ligand conformation. The proposed protocol was applied to identifying HER2 inhibitors from traditional Chinese medicine (TCM) as an example for validating our new protocol. Eight potent leads were identified from six TCM sources. A joint validation system comprised of comparative molecular field analysis, comparative molecular similarity indices analysis, and molecular dynamics simulation further characterized the candidates into three potential binding conformations and validated the binding stability of each protein-ligand complex. The ligand pathway was also performed to predict the ligand "in" and "exit" from the binding site. In summary, we propose a novel systematic CADD methodology for the identification, analysis, and characterization of drug-like candidates.

Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology

PubMed Central

Cowled, Brendan D.; Ward, Michael P.; Laffan, Shawn W.; Galea, Francesca; Garner, M. Graeme; MacDonald, Anna J.; Marsh, Ian; Muellner, Petra; Negus, Katherine; Quasim, Sumaiya; Woolnough, Andrew P.; Sarre, Stephen D.

2012-01-01

Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was to better understand how infectious disease persists in wildlife populations by integrating genetics, ecology and epidemiology approaches. Specifically, we aimed to determine whether environmental or host factors were stronger drivers of Salmonella persistence or transmission within a remote and isolated wild pig (Sus scrofa) population. We determined the Salmonella infection status of wild pigs. Salmonella isolates were genotyped and a range of data was collected on putative risk factors for Salmonella transmission. We a priori identified several plausible biological hypotheses for Salmonella prevalence (cross sectional study design) versus transmission (molecular case series study design) and fit the data to these models. There were 543 wild pig Salmonella observations, sampled at 93 unique locations. Salmonella prevalence was 41% (95% confidence interval [CI]: 37–45%). The median Salmonella DICE coefficient (or Salmonella genetic similarity) was 52% (interquartile range [IQR]: 42–62%). Using the traditional cross sectional prevalence study design, the only supported model was based on the hypothesis that abundance of available ecological resources determines Salmonella prevalence in wild pigs. In the molecular study design, spatial proximity and herd membership as well as some individual risk factors (sex, condition score and relative density) determined transmission between pigs. Traditional cross sectional surveys and molecular epidemiological approaches are complementary and together can enhance understanding of disease ecology: abundance of ecological resources critical for wildlife influences Salmonella prevalence, whereas Salmonella transmission is driven by

Attention to Multiple Objects Facilitates Their Integration in Prefrontal and Parietal Cortex.

PubMed

Kim, Yee-Joon; Tsai, Jeffrey J; Ojemann, Jeffrey; Verghese, Preeti

2017-05-10

Selective attention is known to interact with perceptual organization. In visual scenes, individual objects that are distinct and discriminable may occur on their own, or in groups such as a stack of books. The main objective of this study is to probe the neural interaction that occurs between individual objects when attention is directed toward one or more objects. Here we record steady-state visual evoked potentials via electrocorticography to directly assess the responses to individual stimuli and to their interaction. When human participants attend to two adjacent stimuli, prefrontal and parietal cortex shows a selective enhancement of only the neural interaction between stimuli, but not the responses to individual stimuli. When only one stimulus is attended, the neural response to that stimulus is selectively enhanced in prefrontal and parietal cortex. In contrast, early visual areas generally manifest responses to individual stimuli and to their interaction regardless of attentional task, although a subset of the responses is modulated similarly to prefrontal and parietal cortex. Thus, the neural representation of the visual scene as one progresses up the cortical hierarchy becomes more highly task-specific and represents either individual stimuli or their interaction, depending on the behavioral goal. Attention to multiple objects facilitates an integration of objects akin to perceptual grouping. SIGNIFICANCE STATEMENT Individual objects in a visual scene are seen as distinct entities or as parts of a whole. Here we examine how attention to multiple objects affects their neural representation. Previous studies measured single-cell or fMRI responses and obtained only aggregate measures that combined the activity to individual stimuli as well as their potential interaction. Here, we directly measure electrocorticographic steady-state responses corresponding to individual objects and to their interaction using a frequency-tagging technique. Attention to two

Assessment of multiple constructs of social integration for older adults living in nursing homes.

PubMed

Leedahl, Skye N; Sellon, Alicia; Chapin, Rosemary K

2018-07-01

A variety of terms and measures have been used in the literature to denote being socially integrated, and many studies of older adults focus on only social networks or social support and often only include those living in the community. The purpose of this study was to assess multiple constructs of social integration (i.e., social networks, social capital, social support, and social engagement) for older adults in nursing homes. Data were collected from 140 older adults at 30 nursing homes in Kansas. We interviewed older adults' in-person using a survey questionnaire, and used multilevel confirmatory factor analysis to analyze the data. The final model that included the four constructs had acceptable fit (χ 2  = 174.71; df = 112; p < .01; CFI = .93; RMSEA = .06; SRMR-W = .06; SRMR-B = .12). The results showed that the proposed model was supported at the individual level. At the between-level, social networks and social support were supported. Study results have methodological and practice/policy implications for the study of older adults in long term care settings. In particular, this study contributes to understanding how to operationally define and differentiate social integration variables in studies of older adults, particularly when study data are hierarchical.

Method for Visually Integrating Multiple Data Acquisition Technologies for Real Time and Retrospective Analysis

NASA Technical Reports Server (NTRS)

Bogart, Edward H. (Inventor); Pope, Alan T. (Inventor)

2000-01-01

A system for display on a single video display terminal of multiple physiological measurements is provided. A subject is monitored by a plurality of instruments which feed data to a computer programmed to receive data, calculate data products such as index of engagement and heart rate, and display the data in a graphical format simultaneously on a single video display terminal. In addition live video representing the view of the subject and the experimental setup may also be integrated into the single data display. The display may be recorded on a standard video tape recorder for retrospective analysis.

A Microfluidic Localized, Multiple Cell Culture Array using Vacuum Actuated Cell Seeding: Integrated Anticancer Drug Testing

PubMed Central

Gao, Yan; Li, Peng

2013-01-01

In this study, we introduced a novel and convenient approach to culture multiple cells in localized arrays of microfluidic chambers using one-step vacuum actuation. In one device, we integrated 8 individually addressable regions of culture chambers, each only requiring one simple vacuum operation to seed cells lines. Four cell lines were seeded in designated regions in one device via sequential injection with high purity (99.9%-100%) and cultured for long-term. The on-chip simultaneous culture of HuT 78, Ramos, PC-3 and C166-GFP cells for 48 h was demonstrated with viabilities of 92%+/−2%, 94%+/−4%, 96%+/−2% and 97%+/−2%, respectively. The longest culture period for C166-GFP cells in this study was 168 h with a viability of 96%+/−10%. Cell proliferation in each individual side channel can be tracked. Mass transport between the main channel and side channels was achieved through diffusion and studied using fluorescein solution. The main advantage of this device is the capability to perform multiple cell-based assays on the same device for better comparative studies. After treating cells with staurosporine or anti-human CD95 for 16 h, the apoptotic cell percentage of HuT 78, CCRF-CEM, PC-3 and Ramos cells were 36%+/−3%, 24%+/−4%, 12%+/−2%, 18%+/−4% for staurosporine, and 63%+/−2%, 45%+/−1%, 3%+/−3%, 27%+/−12% for anti-human CD95, respectively. With the advantages of enhanced integration, ease of use and fabrication, and flexibility, this device will be suitable for long-term multiple cell monitoring and cell based assays. PMID:23813077

Orchestrating Multiple Intelligences

ERIC Educational Resources Information Center

Moran, Seana; Kornhaber, Mindy; Gardner, Howard

2006-01-01

Education policymakers often go astray when they attempt to integrate multiple intelligences theory into schools, according to the originator of the theory, Howard Gardner, and his colleagues. The greatest potential of a multiple intelligences approach to education grows from the concept of a profile of intelligences. Each learner's intelligence…

Ab initio molecular dynamics with nuclear quantum effects at classical cost: Ring polymer contraction for density functional theory

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

Marsalek, Ondrej; Markland, Thomas E., E-mail: tmarkland@stanford.edu

Path integral molecular dynamics simulations, combined with an ab initio evaluation of interactions using electronic structure theory, incorporate the quantum mechanical nature of both the electrons and nuclei, which are essential to accurately describe systems containing light nuclei. However, path integral simulations have traditionally required a computational cost around two orders of magnitude greater than treating the nuclei classically, making them prohibitively costly for most applications. Here we show that the cost of path integral simulations can be dramatically reduced by extending our ring polymer contraction approach to ab initio molecular dynamics simulations. By using density functional tight binding asmore » a reference system, we show that our ring polymer contraction scheme gives rapid and systematic convergence to the full path integral density functional theory result. We demonstrate the efficiency of this approach in ab initio simulations of liquid water and the reactive protonated and deprotonated water dimer systems. We find that the vast majority of the nuclear quantum effects are accurately captured using contraction to just the ring polymer centroid, which requires the same number of density functional theory calculations as a classical simulation. Combined with a multiple time step scheme using the same reference system, which allows the time step to be increased, this approach is as fast as a typical classical ab initio molecular dynamics simulation and 35× faster than a full path integral calculation, while still exactly including the quantum sampling of nuclei. This development thus offers a route to routinely include nuclear quantum effects in ab initio molecular dynamics simulations at negligible computational cost.« less

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Analyzing and Integrating Models of Multiple Text Comprehension

ERIC Educational Resources Information Center

List, Alexandra; Alexander, Patricia A.

2017-01-01

We introduce a special issue featuring four theoretical models of multiple text comprehension. We present a central framework for conceptualizing the four models in this special issue. Specifically, we chart the models according to how they consider learner, texts, task, and context factors in explaining multiple text comprehension. In addition,…

A low molecular weight artificial RNA of unique size with multiple probe target regions

NASA Technical Reports Server (NTRS)

Pitulle, C.; Dsouza, L.; Fox, G. E.

1997-01-01

Artificial RNAs (aRNAs) containing novel sequence segments embedded in a deletion mutant of Vibrio proteolyticus 5S rRNA have previously been shown to be expressed from a plasmid borne growth rate regulated promoter in E. coli. These aRNAs accumulate to high levels and their detection is a promising tool for studies in molecular microbial ecology and in environmental monitoring. Herein a new construct is described which illustrates the versatility of detection that is possible with aRNAs. This 3xPen aRNA construct carries a 72 nucleotide insert with three copies of a unique 17 base probe target sequence. This aRNA is 160 nucleotides in length and again accumulates to high levels in the E. coli cytoplasm without incorporating into ribosomes. The 3xPen aRNA illustrates two improvements in detection. First, by appropriate selection of insert size, we obtained an aRNA which provides a unique and hence, easily quantifiable peak, on a high resolution gel profile of low molecular weight RNAs. Second, the existence of multiple probe targets results in a nearly commensurate increase in signal when detection is by hybridization. These aRNAs are naturally amplified and carry sequence segments that are not found in known rRNA sequences. It thus may be possible to detect them directly. An experimental step involving RT-PCR or PCR amplification of the gene could therefore be avoided.

GROMACS 4:  Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation.

PubMed

Hess, Berk; Kutzner, Carsten; van der Spoel, David; Lindahl, Erik

2008-03-01

Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems. Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines. The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel. To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions. Not only does this combination of algorithms enable extremely long simulations of large systems but also it provides that simulation performance on quite modest numbers of standard cluster nodes.

Integrated analysis of miRNA and mRNA expression data identifies multiple miRNAs regulatory networks for the tumorigenesis of colorectal cancer.

PubMed

Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang

2018-06-15

Investigating the potential biological function of differential changed genes through integrating multiple omics data including miRNA and mRNA expression profiles, is always hot topic. However, how to evaluate the repression effect on target genes integrating miRNA and mRNA expression profiles are not fully solved. In this study, we provide an analyzing method by integrating both miRNAs and mRNAs expression data simultaneously. Difference analysis was adopted based on the repression score, then significantly repressed mRNAs were screened out by DEGseq. Pathway analysis for the significantly repressed mRNAs shows that multiple pathways such as MAPK signaling pathway, TGF-beta signaling pathway and so on, may correlated to the colorectal cancer(CRC). Focusing on the MAPK signaling pathway, a miRNA-mRNA network that centering the cell fate genes was constructed. Finally, the miRNA-mRNAs that potentially important in the CRC carcinogenesis were screened out and scored by impact index. Copyright © 2018 Elsevier B.V. All rights reserved.

Pan-Cancer Molecular Classes Transcending Tumor Lineage Across 32 Cancer Types, Multiple Data Platforms, and over 10,000 Cases.

PubMed

Chen, Fengju; Zhang, Yiqun; Gibbons, Don L; Deneen, Benjamin; Kwiatkowski, David J; Ittmann, Michael; Creighton, Chad J

2018-05-01

Purpose: The Cancer Genome Atlas data resources represent an opportunity to explore commonalities across cancer types involving multiple molecular levels, but tumor lineage and histology can represent a barrier in moving beyond differences related to cancer type. Experimental Design: On the basis of gene expression data, we classified 10,224 cancers, representing 32 major types, into 10 molecular-based "classes." Molecular patterns representing tissue or histologic dominant effects were first removed computationally, with the resulting classes representing emergent themes across tumor lineages. Results: Key differences involving mRNAs, miRNAs, proteins, and DNA methylation underscored the pan-cancer classes. One class expressing neuroendocrine and cancer-testis antigen markers represented ∼4% of cancers surveyed. Basal-like breast cancers segregated into an exclusive class, distinct from all other cancers. Immune checkpoint pathway markers and molecular signatures of immune infiltrates were most strongly manifested within a class representing ∼13% of cancers. Pathway-level differences involving hypoxia, NRF2-ARE, Wnt, and Notch were manifested in two additional classes enriched for mesenchymal markers and miR200 silencing. Conclusions: All pan-cancer molecular classes uncovered here, with the important exception of the basal-like breast cancer class, involve a wide range of cancer types and would facilitate understanding the molecular underpinnings of cancers beyond tissue-oriented domains. Numerous biological processes associated with cancer in the laboratory setting were found here to be coordinately manifested across large subsets of human cancers. The number of cancers manifesting features of neuroendocrine tumors may be much higher than previously thought, which disease is known to occur in many different tissues. Clin Cancer Res; 24(9); 2182-93. ©2018 AACR . ©2018 American Association for Cancer Research.

Integration and scaling of UV-B radiation effects on plants: from molecular interactions to whole plant responses.

PubMed

Suchar, Vasile Alexandru; Robberecht, Ronald

2016-07-01

A process based model integrating the effects of UV-B radiation to molecular level processes and their consequences to whole plant growth and development was developed from key parameters in the published literature. Model simulations showed that UV-B radiation induced changes in plant metabolic and/or photosynthesis rates can result in plant growth inhibitions. The costs of effective epidermal UV-B radiation absorptive compounds did not result in any significant changes in plant growth, but any associated metabolic costs effectively reduced the potential plant biomass. The model showed significant interactions between UV-B radiation effects and temperature and any factor leading to inhibition of photosynthetic production or plant growth during the midday, but the effects were not cumulative for all factors. Vegetative growth were significantly delayed in species that do not exhibit reproductive cycles during a growing season, but vegetative growth and reproductive yield in species completing their life cycle in one growing season did not appear to be delayed more than 2-5 days, probably within the natural variability of the life cycles for many species. This is the first model to integrate the effects of increased UV-B radiation through molecular level processes and their consequences to whole plant growth and development.

Crosstalk between intracellular and extracellular signals regulating interneuron production, migration and integration into the cortex.

PubMed

Peyre, Elise; Silva, Carla G; Nguyen, Laurent

2015-01-01

During embryogenesis, cortical interneurons are generated by ventral progenitors located in the ganglionic eminences of the telencephalon. They travel along multiple tangential paths to populate the cortical wall. As they reach this structure they undergo intracortical dispersion to settle in their final destination. At the cellular level, migrating interneurons are highly polarized cells that extend and retract processes using dynamic remodeling of microtubule and actin cytoskeleton. Different levels of molecular regulation contribute to interneuron migration. These include: (1) Extrinsic guidance cues distributed along migratory streams that are sensed and integrated by migrating interneurons; (2) Intrinsic genetic programs driven by specific transcription factors that grant specification and set the timing of migration for different subtypes of interneurons; (3) Adhesion molecules and cytoskeletal elements/regulators that transduce molecular signalings into coherent movement. These levels of molecular regulation must be properly integrated by interneurons to allow their migration in the cortex. The aim of this review is to summarize our current knowledge of the interplay between microenvironmental signals and cell autonomous programs that drive cortical interneuron porduction, tangential migration, and intergration in the developing cerebral cortex.

Pervasive pleiotropy between psychiatric disorders and immune disorders revealed by integrative analysis of multiple GWAS

PubMed Central

Wang, Qian; Yang, Can; Gelernter, Joel; Zhao, Hongyu

2015-01-01

Although some existing epidemiological observations and molecular experiments suggested that brain disorders in the realm of psychiatry may be influenced by immune dysregulation, the degree of genetic overlap between psychiatric disorders and immune disorders has not been well established. We investigated this issue by integrative analysis of genome-wide association studies of 18 complex human traits/diseases (five psychiatric disorders, seven immune disorders, and others) and multiple genome-wide annotation resources (Central nervous system genes, immune-related expression-quantitative trait loci (eQTL) and DNase I hypertensive sites from 98 cell-lines). We detected pleiotropy in 24 of the 35 psychiatric-immune disorder pairs. The strongest pleiotropy was observed for schizophrenia-rheumatoid arthritis with MHC region included in the analysis (p = 3.9 × 10−285), and schizophrenia-Crohns disease with MHC region excluded (p = 1.1 × 10−36). Significant enrichment (>1.4 fold) of immune-related eQTL was observed in four psychiatric disorders. Genomic regions responsible for pleiotropy between psychiatric disorders and immune disorders were detected. The MHC region on chromosome 6 appears to be the most important with other regions, such as cytoband 1p13.2, also playing significant roles in pleiotropy. We also found that most alleles shared between schizophrenia and Crohns disease have the same effect direction, with similar trend found for other disorder pairs, such as bipolar-Crohn’s disease. Our results offer a novel birds-eye view of the genetic relationship and demonstrate strong evidence for pervasive pleiotropy between psychiatric disorders and immune disorders. Our findings might open new routes for prevention and treatment strategies for these disorders based on a new appreciation of the importance of immunological mechanisms in mediating risk of many psychiatric diseases. PMID:26340901

Double path integral method for obtaining the mobility of the one-dimensional charge transport in molecular chain.

PubMed

Yoo-Kong, Sikarin; Liewrian, Watchara

2015-12-01

We report on a theoretical investigation concerning the polaronic effect on the transport properties of a charge carrier in a one-dimensional molecular chain. Our technique is based on the Feynman's path integral approach. Analytical expressions for the frequency-dependent mobility and effective mass of the carrier are obtained as functions of electron-phonon coupling. The result exhibits the crossover from a nearly free particle to a heavily trapped particle. We find that the mobility depends on temperature and decreases exponentially with increasing temperature at low temperature. It exhibits large polaronic-like behaviour in the case of weak electron-phonon coupling. These results agree with the phase transition (A.S. Mishchenko et al., Phys. Rev. Lett. 114, 146401 (2015)) of transport phenomena related to polaron motion in the molecular chain.

Library of molecular associations: curating the complex molecular basis of liver diseases.

PubMed

Buchkremer, Stefan; Hendel, Jasmin; Krupp, Markus; Weinmann, Arndt; Schlamp, Kai; Maass, Thorsten; Staib, Frank; Galle, Peter R; Teufel, Andreas

2010-03-20

Systems biology approaches offer novel insights into the development of chronic liver diseases. Current genomic databases supporting systems biology analyses are mostly based on microarray data. Although these data often cover genome wide expression, the validity of single microarray experiments remains questionable. However, for systems biology approaches addressing the interactions of molecular networks comprehensive but also highly validated data are necessary. We have therefore generated the first comprehensive database for published molecular associations in human liver diseases. It is based on PubMed published abstracts and aimed to close the gap between genome wide coverage of low validity from microarray data and individual highly validated data from PubMed. After an initial text mining process, the extracted abstracts were all manually validated to confirm content and potential genetic associations and may therefore be highly trusted. All data were stored in a publicly available database, Library of Molecular Associations http://www.medicalgenomics.org/databases/loma/news, currently holding approximately 1260 confirmed molecular associations for chronic liver diseases such as HCC, CCC, liver fibrosis, NASH/fatty liver disease, AIH, PBC, and PSC. We furthermore transformed these data into a powerful resource for molecular liver research by connecting them to multiple biomedical information resources. Together, this database is the first available database providing a comprehensive view and analysis options for published molecular associations on multiple liver diseases.

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

PubMed

Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

2016-09-09

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators

Multiple-stage integrating accelerometer

DOEpatents

Devaney, H.F.

1984-06-27

An accelerometer assembly is provided for use in activating a switch in response to multiple acceleration pulses in series. The accelerometer includes a housing forming a chamber. An inertial mass or piston is slidably disposed in the chamber and spring biased toward a first or reset position. A damping system is also provided to damp piston movement in response to first and subsequent acceleration pulses. Additionally, a cam, including a Z-shaped slot, and cooperating follower pin slidably received therein are mounted to the piston and the housing. The middle or cross-over leg of the Z-shaped slot cooperates with the follower pin to block or limit piston movement and prevent switch activation in response to a lone acceleration pulse. The switch of the assembly is only activated after two or more separate acceleration pulses are sensed and the piston reaches the end of the chamber opposite the reset position.

vECTlab—A fully integrated multi-modality Monte Carlo simulation framework for the radiological imaging sciences

NASA Astrophysics Data System (ADS)

Peter, Jörg; Semmler, Wolfhard

2007-10-01

Alongside and in part motivated by recent advances in molecular diagnostics, the development of dual-modality instruments for patient and dedicated small animal imaging has gained attention by diverse research groups. The desire for such systems is high not only to link molecular or functional information with the anatomical structures, but also for detecting multiple molecular events simultaneously at shorter total acquisition times. While PET and SPECT have been integrated successfully with X-ray CT, the advance of optical imaging approaches (OT) and the integration thereof into existing modalities carry a high application potential, particularly for imaging small animals. A multi-modality Monte Carlo (MC) simulation approach at present has been developed that is able to trace high-energy (keV) as well as optical (eV) photons concurrently within identical phantom representation models. We show that the involved two approaches for ray-tracing keV and eV photons can be integrated into a unique simulation framework which enables both photon classes to be propagated through various geometry models representing both phantoms and scanners. The main advantage of such integrated framework for our specific application is the investigation of novel tomographic multi-modality instrumentation intended for in vivo small animal imaging through time-resolved MC simulation upon identical phantom geometries. Design examples are provided for recently proposed SPECT-OT and PET-OT imaging systems.

Cellular and molecular mechanisms of tooth root development

PubMed Central

Li, Jingyuan; Parada, Carolina

2017-01-01

ABSTRACT The tooth root is an integral, functionally important part of our dentition. The formation of a functional root depends on epithelial-mesenchymal interactions and integration of the root with the jaw bone, blood supply and nerve innervations. The root development process therefore offers an attractive model for investigating organogenesis. Understanding how roots develop and how they can be bioengineered is also of great interest in the field of regenerative medicine. Here, we discuss recent advances in understanding the cellular and molecular mechanisms underlying tooth root formation. We review the function of cellular structure and components such as Hertwig's epithelial root sheath, cranial neural crest cells and stem cells residing in developing and adult teeth. We also highlight how complex signaling networks together with multiple transcription factors mediate tissue-tissue interactions that guide root development. Finally, we discuss the possible role of stem cells in establishing the crown-to-root transition, and provide an overview of root malformations and diseases in humans. PMID:28143844

Integrated Anaerobic-Aerobic Biodegradation of Multiple Contaminants Including Chlorinated Ethylenes, Benzene, Toluene, and Dichloromethane.

PubMed

Yoshikawa, Miho; Zhang, Ming; Toyota, Koki

2017-01-01

Complete bioremediation of soils containing multiple volatile organic compounds (VOCs) remains a challenge. To explore the possibility of complete bioremediation through integrated anaerobic-aerobic biodegradation, laboratory feasibility tests followed by alternate anaerobic-aerobic and aerobic-anaerobic biodegradation tests were performed. Chlorinated ethylenes, including tetrachloroethylene (PCE), trichloroethylene (TCE), cis -dichloroethylene ( cis -DCE), and vinyl chloride (VC), and dichloromethane (DCM) were used for anaerobic biodegradation, whereas benzene, toluene, and DCM were used for aerobic biodegradation tests. Microbial communities involved in the biodegradation tests were analyzed to characterize the major bacteria that may contribute to biodegradation. The results demonstrated that integrated anaerobic-aerobic biodegradation was capable of completely degrading the seven VOCs with initial concentration of each VOC less than 30 mg/L. Benzene and toluene were degraded within 8 days, and DCM was degraded within 20 to 27 days under aerobic conditions when initial oxygen concentrations in the headspaces of test bottles were set to 5.3% and 21.0%. Dehalococcoides sp., generally considered sensitive to oxygen, survived aerobic conditions for 28 days and was activated during the subsequent anaerobic biodegradation. However, degradation of cis -DCE was suppressed after oxygen exposure for more than 201 days, suggesting the loss of viability of Dehalococcoides sp., as they are the only known anaerobic bacteria that can completely biodegrade chlorinated ethylenes to ethylene. Anaerobic degradation of DCM following previous aerobic degradation was complete, and yet-unknown microbes may be involved in the process. The findings may provide a scientific and practical basis for the complete bioremediation of multiple contaminants in situ and a subject for further exploration.

Integrating Multiple Autonomous Underwater Vessels, Surface Vessels and Aircraft into Oceanographic Research Vessel Operations

NASA Astrophysics Data System (ADS)

McGillivary, P. A.; Borges de Sousa, J.; Martins, R.; Rajan, K.

2012-12-01

Autonomous platforms are increasingly used as components of Integrated Ocean Observing Systems and oceanographic research cruises. Systems deployed can include gliders or propeller-driven autonomous underwater vessels (AUVs), autonomous surface vessels (ASVs), and unmanned aircraft systems (UAS). Prior field campaigns have demonstrated successful communication, sensor data fusion and visualization for studies using gliders and AUVs. However, additional requirements exist for incorporating ASVs and UASs into ship operations. For these systems to be optimally integrated into research vessel data management and operational planning systems involves addressing three key issues: real-time field data availability, platform coordination, and data archiving for later analysis. A fleet of AUVs, ASVs and UAS deployed from a research vessel is best operated as a system integrated with the ship, provided communications among them can be sustained. For this purpose, Disruptive Tolerant Networking (DTN) software protocols for operation in communication-challenged environments help ensure reliable high-bandwidth communications. Additionally, system components need to have considerable onboard autonomy, namely adaptive sampling capabilities using their own onboard sensor data stream analysis. We discuss Oceanographic Decision Support System (ODSS) software currently used for situational awareness and planning onshore, and in the near future event detection and response will be coordinated among multiple vehicles. Results from recent field studies from oceanographic research vessels using AUVs, ASVs and UAS, including the Rapid Environmental Picture (REP-12) cruise, are presented describing methods and results for use of multi-vehicle communication and deliberative control networks, adaptive sampling with single and multiple platforms, issues relating to data management and archiving, and finally challenges that remain in addressing these technological issues. Significantly, the

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics.

PubMed

Armen, Roger S; Chen, Jianhan; Brooks, Charles L

2009-10-13

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.

Integration of multiple theories for the simulation of laser interference lithography processes

NASA Astrophysics Data System (ADS)

Lin, Te-Hsun; Yang, Yin-Kuang; Fu, Chien-Chung

2017-11-01

The periodic structure of laser interference lithography (LIL) fabrication is superior to other lithography technologies. In contrast to traditional lithography, LIL has the advantages of being a simple optical system with no mask requirements, low cost, high depth of focus, and large patterning area in a single exposure. Generally, a simulation pattern for the periodic structure is obtained through optical interference prior to its fabrication through LIL. However, the LIL process is complex and combines the fields of optical and polymer materials; thus, a single simulation theory cannot reflect the real situation. Therefore, this research integrates multiple theories, including those of optical interference, standing waves, and photoresist characteristics, to create a mathematical model for the LIL process. The mathematical model can accurately estimate the exposure time and reduce the LIL process duration through trial and error.

Integration of multiple theories for the simulation of laser interference lithography processes.

PubMed

Lin, Te-Hsun; Yang, Yin-Kuang; Fu, Chien-Chung

2017-11-24

The periodic structure of laser interference lithography (LIL) fabrication is superior to other lithography technologies. In contrast to traditional lithography, LIL has the advantages of being a simple optical system with no mask requirements, low cost, high depth of focus, and large patterning area in a single exposure. Generally, a simulation pattern for the periodic structure is obtained through optical interference prior to its fabrication through LIL. However, the LIL process is complex and combines the fields of optical and polymer materials; thus, a single simulation theory cannot reflect the real situation. Therefore, this research integrates multiple theories, including those of optical interference, standing waves, and photoresist characteristics, to create a mathematical model for the LIL process. The mathematical model can accurately estimate the exposure time and reduce the LIL process duration through trial and error.

Microcanonical molecular simulations of methane hydrate nucleation and growth: evidence that direct nucleation to sI hydrate is among the multiple nucleation pathways.

PubMed

Zhang, Zhengcai; Walsh, Matthew R; Guo, Guang-Jun

2015-04-14

The results of six high-precision constant energy molecular dynamics (MD) simulations initiated from methane-water systems equilibrated at 80 MPa and 250 K indicate that methane hydrates can nucleate via multiple pathways. Five trajectories nucleate to an amorphous solid. One trajectory nucleates to a structure-I hydrate template with long-range order which spans the simulation box across periodic boundaries despite the presence of several defects. While experimental and simulation data for hydrate nucleation with different time- and length-scales suggest that there may exist multiple pathways for nucleation, including metastable intermediates and the direct formation of the globally-stable phase, this work provides the most compelling evidence that direct formation to the globally stable crystalline phase is one of the multiple pathways available for hydrate nucleation.

[Being cared for and caring: living with multiple chronic diseases (Leila)-a qualitative study about APN contributions to integrated care].

PubMed

Müller-Staub, Maria; Zigan, Nicole; Händler-Schuster, Daniela; Probst, Sebastian; Monego, Renate; Imhof, Lorenz

2015-04-01

Living with multiple chronic diseases is complex and leads to enhanced care needs. To foster integrated care a project called "Living with chronic disease" (Leila) was initiated. The aim was to develop an Advanced Practice Nursing (APN) service in collaboration with medical centers for persons who are living with multiple chronic diseases. The following research questions were addressed: 1. What are patients' experiences, referring physicians and APNs with the Leila-Service? 2. How are referral processes performed? 3. How do the involved groups experience collaboration and APN role development? A qualitative approach according grounded theory of Corbin and Strauss was used to explore the experiences with the Leila project and the interaction of the persons involved. 38 interviews were conducted with patients who are living with multiple chronic diseases, their APN's and the referring physicians. The findings revealed "Being cared for and caring" as main category. The data demonstrated how patients responded to their involvement into care and that they were taken as serious partners in the care process. The category "organizing everyday life" describes how patients learned to cope with the consequences of living with multiple chronic diseases. "Using all resources" as another category demonstrates how capabilities and strengths were adopted. The results of the cooperation- and allocation processes showed that the APN recognition and APN role performance have to be negotiated. Prospective APN-services for this patient population should be integrated along with physician networks and other service providers including community health nursing.

Assessment of BTEX-induced health risk under multiple uncertainties at a petroleum-contaminated site: An integrated fuzzy stochastic approach

NASA Astrophysics Data System (ADS)

Zhang, Xiaodong; Huang, Guo H.

2011-12-01

Groundwater pollution has gathered more and more attention in the past decades. Conducting an assessment of groundwater contamination risk is desired to provide sound bases for supporting risk-based management decisions. Therefore, the objective of this study is to develop an integrated fuzzy stochastic approach to evaluate risks of BTEX-contaminated groundwater under multiple uncertainties. It consists of an integrated interval fuzzy subsurface modeling system (IIFMS) and an integrated fuzzy second-order stochastic risk assessment (IFSOSRA) model. The IIFMS is developed based on factorial design, interval analysis, and fuzzy sets approach to predict contaminant concentrations under hybrid uncertainties. Two input parameters (longitudinal dispersivity and porosity) are considered to be uncertain with known fuzzy membership functions, and intrinsic permeability is considered to be an interval number with unknown distribution information. A factorial design is conducted to evaluate interactive effects of the three uncertain factors on the modeling outputs through the developed IIFMS. The IFSOSRA model can systematically quantify variability and uncertainty, as well as their hybrids, presented as fuzzy, stochastic and second-order stochastic parameters in health risk assessment. The developed approach haw been applied to the management of a real-world petroleum-contaminated site within a western Canada context. The results indicate that multiple uncertainties, under a combination of information with various data-quality levels, can be effectively addressed to provide supports in identifying proper remedial efforts. A unique contribution of this research is the development of an integrated fuzzy stochastic approach for handling various forms of uncertainties associated with simulation and risk assessment efforts.

The multiple infrared source GL 437

NASA Technical Reports Server (NTRS)

Wynn-Williams, C. G.; Becklin, E. E.; Beichman, C. A.; Capps, R.; Shakeshaft, J. R.

1981-01-01

Infrared and radio continuum observations of the multiple infrared source GL 437 show that it consists of a compact H II region plus two objects which are probably early B stars undergoing rapid mass loss. The group of sources appears to be a multiple system of young stars that have recently emerged from the near side of a molecular cloud. Emission in the unidentified 3.3 micron feature is associated with, but more extended than, the emission from the compact H II region; it probably arises from hot dust grains at the interface between the H II region and the molecular cloud.

The 5S rDNA in two Abracris grasshoppers (Ommatolampidinae: Acrididae): molecular and chromosomal organization.

PubMed

Bueno, Danilo; Palacios-Gimenez, Octavio Manuel; Martí, Dardo Andrea; Mariguela, Tatiane Casagrande; Cabral-de-Mello, Diogo Cavalcanti

2016-08-01

The 5S ribosomal DNA (rDNA) sequences are subject of dynamic evolution at chromosomal and molecular levels, evolving through concerted and/or birth-and-death fashion. Among grasshoppers, the chromosomal location for this sequence was established for some species, but little molecular information was obtained to infer evolutionary patterns. Here, we integrated data from chromosomal and nucleotide sequence analysis for 5S rDNA in two Abracris species aiming to identify evolutionary dynamics. For both species, two arrays were identified, a larger sequence (named type-I) that consisted of the entire 5S rDNA gene plus NTS (non-transcribed spacer) and a smaller (named type-II) with truncated 5S rDNA gene plus short NTS that was considered a pseudogene. For type-I sequences, the gene corresponding region contained the internal control region and poly-T motif and the NTS presented partial transposable elements. Between the species, nucleotide differences for type-I were noticed, while type-II was identical, suggesting pseudogenization in a common ancestor. At chromosomal point to view, the type-II was placed in one bivalent, while type-I occurred in multiple copies in distinct chromosomes. In Abracris, the evolution of 5S rDNA was apparently influenced by the chromosomal distribution of clusters (single or multiple location), resulting in a mixed mechanism integrating concerted and birth-and-death evolution depending on the unit.

Mining and integration of pathway diagrams from imaging data.

PubMed

Kozhenkov, Sergey; Baitaluk, Michael

2012-03-01

Pathway diagrams from PubMed and World Wide Web (WWW) contain valuable highly curated information difficult to reach without tools specifically designed and customized for the biological semantics and high-content density of the images. There is currently no search engine or tool that can analyze pathway images, extract their pathway components (molecules, genes, proteins, organelles, cells, organs, etc.) and indicate their relationships. Here, we describe a resource of pathway diagrams retrieved from article and web-page images through optical character recognition, in conjunction with data mining and data integration methods. The recognized pathways are integrated into the BiologicalNetworks research environment linking them to a wealth of data available in the BiologicalNetworks' knowledgebase, which integrates data from >100 public data sources and the biomedical literature. Multiple search and analytical tools are available that allow the recognized cellular pathways, molecular networks and cell/tissue/organ diagrams to be studied in the context of integrated knowledge, experimental data and the literature. BiologicalNetworks software and the pathway repository are freely available at www.biologicalnetworks.org. Supplementary data are available at Bioinformatics online.

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org. PMID:21190573

Whole-Brain Radiotherapy With Simultaneous Integrated Boost to Multiple Brain Metastases Using Volumetric Modulated Arc Therapy

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

Lagerwaard, Frank J.; Hoorn, Elles A.P. van der; Verbakel, Wilko

2009-09-01

Purpose: Volumetric modulated arc therapy (RapidArc [RA]; Varian Medical Systems, Palo Alto, CA) allows for the generation of intensity-modulated dose distributions by use of a single gantry rotation. We used RA to plan and deliver whole-brain radiotherapy (WBRT) with a simultaneous integrated boost in patients with multiple brain metastases. Methods and Materials: Composite RA plans were generated for 8 patients, consisting of WBRT (20 Gy in 5 fractions) with an integrated boost, also 20 Gy in 5 fractions, to Brain metastases, and clinically delivered in 3 patients. Summated gross tumor volumes were 1.0 to 37.5 cm{sup 3}. RA plans weremore » measured in a solid water phantom by use of Gafchromic films (International Specialty Products, Wayne, NJ). Results: Composite RA plans could be generated within 1 hour. Two arcs were needed to deliver the mean of 1,600 monitor units with a mean 'beam-on' time of 180 seconds. RA plans showed excellent coverage of planning target volume for WBRT and planning target volume for the boost, with mean volumes receiving at least 95% of the prescribed dose of 100% and 99.8%, respectively. The mean conformity index was 1.36. Composite plans showed much steeper dose gradients outside Brain metastases than plans with a conventional summation of WBRT and radiosurgery. Comparison of calculated and measured doses showed a mean gamma for double-arc plans of 0.30, and the area with a gamma larger than 1 was 2%. In-room times for clinical RA sessions were approximately 20 minutes for each patient. Conclusions: RA treatment planning and delivery of integrated plans of WBRT and boosts to multiple brain metastases is a rapid and accurate technique that has a higher conformity index than conventional summation of WBRT and radiosurgery boost.« less

FDRAnalysis: a tool for the integrated analysis of tandem mass spectrometry identification results from multiple search engines.

PubMed

Wedge, David C; Krishna, Ritesh; Blackhurst, Paul; Siepen, Jennifer A; Jones, Andrew R; Hubbard, Simon J

2011-04-01

Confident identification of peptides via tandem mass spectrometry underpins modern high-throughput proteomics. This has motivated considerable recent interest in the postprocessing of search engine results to increase confidence and calculate robust statistical measures, for example through the use of decoy databases to calculate false discovery rates (FDR). FDR-based analyses allow for multiple testing and can assign a single confidence value for both sets and individual peptide spectrum matches (PSMs). We recently developed an algorithm for combining the results from multiple search engines, integrating FDRs for sets of PSMs made by different search engine combinations. Here we describe a web-server and a downloadable application that makes this routinely available to the proteomics community. The web server offers a range of outputs including informative graphics to assess the confidence of the PSMs and any potential biases. The underlying pipeline also provides a basic protein inference step, integrating PSMs into protein ambiguity groups where peptides can be matched to more than one protein. Importantly, we have also implemented full support for the mzIdentML data standard, recently released by the Proteomics Standards Initiative, providing users with the ability to convert native formats to mzIdentML files, which are available to download.

FDRAnalysis: A tool for the integrated analysis of tandem mass spectrometry identification results from multiple search engines

PubMed Central

Wedge, David C; Krishna, Ritesh; Blackhurst, Paul; Siepen, Jennifer A; Jones, Andrew R.; Hubbard, Simon J.

2013-01-01

Confident identification of peptides via tandem mass spectrometry underpins modern high-throughput proteomics. This has motivated considerable recent interest in the post-processing of search engine results to increase confidence and calculate robust statistical measures, for example through the use of decoy databases to calculate false discovery rates (FDR). FDR-based analyses allow for multiple testing and can assign a single confidence value for both sets and individual peptide spectrum matches (PSMs). We recently developed an algorithm for combining the results from multiple search engines, integrating FDRs for sets of PSMs made by different search engine combinations. Here we describe a web-server, and a downloadable application, which makes this routinely available to the proteomics community. The web server offers a range of outputs including informative graphics to assess the confidence of the PSMs and any potential biases. The underlying pipeline provides a basic protein inference step, integrating PSMs into protein ambiguity groups where peptides can be matched to more than one protein. Importantly, we have also implemented full support for the mzIdentML data standard, recently released by the Proteomics Standards Initiative, providing users with the ability to convert native formats to mzIdentML files, which are available to download. PMID:21222473

Simultaneous reconstruction of multiple depth images without off-focus points in integral imaging using a graphics processing unit.

PubMed

Yi, Faliu; Lee, Jieun; Moon, Inkyu

2014-05-01

The reconstruction of multiple depth images with a ray back-propagation algorithm in three-dimensional (3D) computational integral imaging is computationally burdensome. Further, a reconstructed depth image consists of a focus and an off-focus area. Focus areas are 3D points on the surface of an object that are located at the reconstructed depth, while off-focus areas include 3D points in free-space that do not belong to any object surface in 3D space. Generally, without being removed, the presence of an off-focus area would adversely affect the high-level analysis of a 3D object, including its classification, recognition, and tracking. Here, we use a graphics processing unit (GPU) that supports parallel processing with multiple processors to simultaneously reconstruct multiple depth images using a lookup table containing the shifted values along the x and y directions for each elemental image in a given depth range. Moreover, each 3D point on a depth image can be measured by analyzing its statistical variance with its corresponding samples, which are captured by the two-dimensional (2D) elemental images. These statistical variances can be used to classify depth image pixels as either focus or off-focus points. At this stage, the measurement of focus and off-focus points in multiple depth images is also implemented in parallel on a GPU. Our proposed method is conducted based on the assumption that there is no occlusion of the 3D object during the capture stage of the integral imaging process. Experimental results have demonstrated that this method is capable of removing off-focus points in the reconstructed depth image. The results also showed that using a GPU to remove the off-focus points could greatly improve the overall computational speed compared with using a CPU.

Integrated network analysis reveals potentially novel molecular mechanisms and therapeutic targets of refractory epilepsies

PubMed Central

Liu, Guangming; Wang, Yiwei; Zhao, Pengyao; Zhu, Yizhun; Yang, Xiaohan; Zheng, Tiezheng; Zhou, Xuezhong; Jin, Weilin; Sun, Changkai

2017-01-01

Epilepsy is a complex neurological disorder and a significant health problem. The pathogenesis of epilepsy remains obscure in a significant number of patients and the current treatment options are not adequate in about a third of individuals which were known as refractory epilepsies (RE). Network medicine provides an effective approach for studying the molecular mechanisms underlying complex diseases. Here we integrated 1876 disease-gene associations of RE and located those genes to human protein-protein interaction (PPI) network to obtain 42 significant RE-associated disease modules. The functional analysis of these disease modules showed novel molecular pathological mechanisms of RE, such as the novel enriched pathways (e.g., “presynaptic nicotinic acetylcholine receptors”, “signaling by insulin receptor”). Further analysis on the relationships between current drug targets and the RE-related disease genes showed the rational mechanisms of most antiepileptic drugs. In addition, we detected ten potential novel drug targets (e.g., KCNA1, KCNA4-6, KCNC3, KCND2, KCNMA1, CAMK2G, CACNB4 and GRM1) located in three RE related disease modules, which might provide novel insights into the new drug discovery for RE therapy. PMID:28388656

Development of Integrative STEM Curriculum: A Multiple Case Study of Multi-Disciplinary Teams in Two Pennsylvania High Schools

NASA Astrophysics Data System (ADS)

Rider-Bertrand, Joey H.

At the start of the 21st century, STEM education was a new priority in many schools as the focus shifted from separate disciplines to integrative STEM education. Unfortunately, there was limited research to offer guidance to practitioners (Brown, 2012; Honey, Pearson & Schweingruber, 2014). This qualitative, multiple case study explored the experiences of two multi-disciplinary teams of secondary teachers from Pennsylvania who developed and implemented integrative STEM curriculum. Four teachers from a rural high school and four teachers from a suburban high school participated in the study. A document review of integrative STEM curriculum and semi-structured interviews were conducted to learn about the curriculum development process and teachers' perceptions regarding conditions that support or hinder success. Individual and cross-case analyses were performed to establish findings and themes. Although the individual case themes varied slightly, the cross-case themes and assertions that emerged provided highly sought after guidance to practitioners and added to the limited body of research on integrative STEM education. This study found that current curriculum models do not fit integrative STEM curriculum, the development process is fluid, and substantial administrative support and resources are necessary to develop, implement, and sustain integrative STEM education programs. The results offered implications for all educators, as well as two examples of how teachers navigated the terrain of integrative STEM curriculum.

Molecular evolution of multiple-level control of heme biosynthesis pathway in animal kingdom.

PubMed

Tzou, Wen-Shyong; Chu, Ying; Lin, Tzung-Yi; Hu, Chin-Hwa; Pai, Tun-Wen; Liu, Hsin-Fu; Lin, Han-Jia; Cases, Ildeofonso; Rojas, Ana; Sanchez, Mayka; You, Zong-Ye; Hsu, Ming-Wei

2014-01-01

Adaptation of enzymes in a metabolic pathway can occur not only through changes in amino acid sequences but also through variations in transcriptional activation, mRNA splicing and mRNA translation. The heme biosynthesis pathway, a linear pathway comprised of eight consecutive enzymes in animals, provides researchers with ample information for multiple types of evolutionary analyses performed with respect to the position of each enzyme in the pathway. Through bioinformatics analysis, we found that the protein-coding sequences of all enzymes in this pathway are under strong purifying selection, from cnidarians to mammals. However, loose evolutionary constraints are observed for enzymes in which self-catalysis occurs. Through comparative genomics, we found that in animals, the first intron of the enzyme-encoding genes has been co-opted for transcriptional activation of the genes in this pathway. Organisms sense the cellular content of iron, and through iron-responsive elements in the 5' untranslated regions of mRNAs and the intron-exon boundary regions of pathway genes, translational inhibition and exon choice in enzymes may be enabled, respectively. Pathway product (heme)-mediated negative feedback control can affect the transport of pathway enzymes into the mitochondria as well as the ubiquitin-mediated stability of enzymes. Remarkably, the positions of these controls on pathway activity are not ubiquitous but are biased towards the enzymes in the upstream portion of the pathway. We revealed that multiple-level controls on the activity of the heme biosynthesis pathway depend on the linear depth of the enzymes in the pathway, indicating a new strategy for discovering the molecular constraints that shape the evolution of a metabolic pathway.

Actin Immobilization on Chitin for Purifying Myosin II: A Laboratory Exercise That Integrates Concepts of Molecular Cell Biology and Protein Chemistry

ERIC Educational Resources Information Center

de Souza, Marcelle Gomes; Grossi, Andre Luiz; Pereira, Elisangela Lima Bastos; da Cruz, Carolina Oliveira; Mendes, Fernanda Machado; Cameron, Luiz Claudio; Paiva, Carmen Lucia Antao

2008-01-01

This article presents our experience on teaching biochemical sciences through an innovative approach that integrates concepts of molecular cell biology and protein chemistry. This original laboratory exercise is based on the preparation of an affinity chromatography column containing F-actin molecules immobilized on chitin particles for purifying…

Integrated structural biology and molecular ecology of N-cycling enzymes from ammonia-oxidizing archaea

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

Tolar, Bradley B.; Herrmann, Jonathan; Bargar, John R.

In this paper, knowledge of the molecular ecology and environmental determinants of ammonia-oxidizing organisms is critical to understanding and predicting the global nitrogen (N) and carbon cycles, but an incomplete biochemical picture hinders in vitro studies of N-cycling enzymes. Although an integrative structural and dynamic characterization at the atomic scale would advance our understanding of function tremendously, structural knowlede of key N-cycling enzymes from ecologically-relevant ammonia oxidizers is unfortunately extremely limited. Here, we discuss the challenges and opportunities for examining the ecology of ammonia-oxidizing organisms, particularly uncultivated Thaumarchaeota, though (meta)genome-driven structural biology of the enzymes ammonia monooxygenase (AMO) andmore » nitrite reductase (NirK).« less

Integrated structural biology and molecular ecology of N-cycling enzymes from ammonia-oxidizing archaea

DOE PAGES

Tolar, Bradley B.; Herrmann, Jonathan; Bargar, John R.; ...

2017-07-05

In this paper, knowledge of the molecular ecology and environmental determinants of ammonia-oxidizing organisms is critical to understanding and predicting the global nitrogen (N) and carbon cycles, but an incomplete biochemical picture hinders in vitro studies of N-cycling enzymes. Although an integrative structural and dynamic characterization at the atomic scale would advance our understanding of function tremendously, structural knowlede of key N-cycling enzymes from ecologically-relevant ammonia oxidizers is unfortunately extremely limited. Here, we discuss the challenges and opportunities for examining the ecology of ammonia-oxidizing organisms, particularly uncultivated Thaumarchaeota, though (meta)genome-driven structural biology of the enzymes ammonia monooxygenase (AMO) andmore » nitrite reductase (NirK).« less

Integrated structural biology and molecular ecology of N-cycling enzymes from ammonia-oxidizing archaea.

PubMed

Tolar, Bradley B; Herrmann, Jonathan; Bargar, John R; van den Bedem, Henry; Wakatsuki, Soichi; Francis, Christopher A

2017-10-01

Knowledge of the molecular ecology and environmental determinants of ammonia-oxidizing organisms is critical to understanding and predicting the global nitrogen (N) and carbon cycles, but an incomplete biochemical picture hinders in vitro studies of N-cycling enzymes. Although an integrative structural and dynamic characterization at the atomic scale would advance our understanding of function tremendously, structural knowledge of key N-cycling enzymes from ecologically relevant ammonia oxidizers is unfortunately extremely limited. Here, we discuss the challenges and opportunities for examining the ecology of ammonia-oxidizing organisms, particularly uncultivated Thaumarchaeota, through (meta)genome-driven structural biology of the enzymes ammonia monooxygenase (AMO) and nitrite reductase (NirK). © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

A sampling-based method for ranking protein structural models by integrating multiple scores and features.

PubMed

Shi, Xiaohu; Zhang, Jingfen; He, Zhiquan; Shang, Yi; Xu, Dong

2011-09-01

One of the major challenges in protein tertiary structure prediction is structure quality assessment. In many cases, protein structure prediction tools generate good structural models, but fail to select the best models from a huge number of candidates as the final output. In this study, we developed a sampling-based machine-learning method to rank protein structural models by integrating multiple scores and features. First, features such as predicted secondary structure, solvent accessibility and residue-residue contact information are integrated by two Radial Basis Function (RBF) models trained from different datasets. Then, the two RBF scores and five selected scoring functions developed by others, i.e., Opus-CA, Opus-PSP, DFIRE, RAPDF, and Cheng Score are synthesized by a sampling method. At last, another integrated RBF model ranks the structural models according to the features of sampling distribution. We tested the proposed method by using two different datasets, including the CASP server prediction models of all CASP8 targets and a set of models generated by our in-house software MUFOLD. The test result shows that our method outperforms any individual scoring function on both best model selection, and overall correlation between the predicted ranking and the actual ranking of structural quality.

Design and construction of a first-generation high-throughput integrated robotic molecular biology platform for bioenergy applications.

PubMed

Hughes, Stephen R; Butt, Tauseef R; Bartolett, Scott; Riedmuller, Steven B; Farrelly, Philip

2011-08-01

The molecular biological techniques for plasmid-based assembly and cloning of gene open reading frames are essential for elucidating the function of the proteins encoded by the genes. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly clone and express heterologous gene open reading frames in bacteria and yeast and to screen large numbers of expressed proteins for optimized function are an important technology for improving microbial strains for biofuel production. The process involves the production of full-length complementary DNA libraries as a source of plasmid-based clones to express the desired proteins in active form for determination of their functions. Proteins that were identified by high-throughput screening as having desired characteristics are overexpressed in microbes to enable them to perform functions that will allow more cost-effective and sustainable production of biofuels. Because the plasmid libraries are composed of several thousand unique genes, automation of the process is essential. This review describes the design and implementation of an automated integrated programmable robotic workcell capable of producing complementary DNA libraries, colony picking, isolating plasmid DNA, transforming yeast and bacteria, expressing protein, and performing appropriate functional assays. These operations will allow tailoring microbial strains to use renewable feedstocks for production of biofuels, bioderived chemicals, fertilizers, and other coproducts for profitable and sustainable biorefineries. Published by Elsevier Inc.

Uncovering the molecular secrets of inflammatory breast cancer biology: an integrated analysis of three distinct affymetrix gene expression datasets.

PubMed

Van Laere, Steven J; Ueno, Naoto T; Finetti, Pascal; Vermeulen, Peter; Lucci, Anthony; Robertson, Fredika M; Marsan, Melike; Iwamoto, Takayuki; Krishnamurthy, Savitri; Masuda, Hiroko; van Dam, Peter; Woodward, Wendy A; Viens, Patrice; Cristofanilli, Massimo; Birnbaum, Daniel; Dirix, Luc; Reuben, James M; Bertucci, François

2013-09-01

Inflammatory breast cancer (IBC) is a poorly characterized form of breast cancer. So far, the results of expression profiling in IBC are inconclusive due to various reasons including limited sample size. Here, we present the integration of three Affymetrix expression datasets collected through the World IBC Consortium allowing us to interrogate the molecular profile of IBC using the largest series of IBC samples ever reported. Affymetrix profiles (HGU133-series) from 137 patients with IBC and 252 patients with non-IBC (nIBC) were analyzed using unsupervised and supervised techniques. Samples were classified according to the molecular subtypes using the PAM50-algorithm. Regression models were used to delineate IBC-specific and molecular subtype-independent changes in gene expression, pathway, and transcription factor activation. Four robust IBC-sample clusters were identified, associated with the different molecular subtypes (P<0.001), all of which were identified in IBC with a similar prevalence as in nIBC, except for the luminal A subtype (19% vs. 42%; P<0.001) and the HER2-enriched subtype (22% vs. 9%; P<0.001). Supervised analysis identified and validated an IBC-specific, molecular subtype-independent 79-gene signature, which held independent prognostic value in a series of 871 nIBCs. Functional analysis revealed attenuated TGF-β signaling in IBC. We show that IBC is transcriptionally heterogeneous and that all molecular subtypes described in nIBC are detectable in IBC, albeit with a different frequency. The molecular profile of IBC, bearing molecular traits of aggressive breast tumor biology, shows attenuation of TGF-β signaling, potentially explaining the metastatic potential of IBC tumor cells in an unexpected manner. ©2013 AACR.

Community integration outcomes of people with spinal cord injury and multiple matched controls: A pilot study.

PubMed

Callaway, Libby; Enticott, Joanne; Farnworth, Louise; McDonald, Rachael; Migliorini, Christine; Willer, Barry

2017-06-01

Australia's National Disability Insurance Scheme (NDIS) is designed to influence home, social and economic participation for Scheme participants. Given the major disability reform underway, this pilot study aimed to: (i) examine community integration outcomes of people with spinal cord injury (SCI); (ii) compare findings with multiple matched controls and (iii) consider findings within the context of Australia's NDIS. Setting: Victoria, Australia. Matched analysis (people with and without SCI). Community Integration Questionnaire (CIQ). n = 40 adults with SCI (M age = 52.8 years; 61% male; 77% traumatic SCI). Matched analyses from each SCI subject aged <70 years (n = 31) with four CIQ normative data subjects (from n = 1927) was undertaken, with key demographic variables matched (age range, gender, living location and living situation). Risk of low CIQ score as a function of SCI was also examined using conditional Poisson regression. With key demographic variables held constant, small to medium effect sizes were found in favour of the normative sample, with statistically significant differences in home (ρ = 0.003) and productivity integration (ρ = 0.02). Relative risk of low home integration was significant in the SCI cohort (conditional RR (95% CI) = 3.1 (1.5-6.3), ρ = 0.001). Relative risk of low CIQ total, social integration and productivity scores did not reach significance. This cohort of SCI participants was less integrated into home and productive occupations than matched norms, holding implications for planning and allocation of supports to influence outcomes within an NDIS. Further research is necessary to understand community integration outcomes in larger matched samples. © 2016 Occupational Therapy Australia.

Bulk and integrated acousto-optic spectrometers for molecular astronomy with heterodyne spectrometers

NASA Technical Reports Server (NTRS)

Chin, G.; Buhl, D.; Florez, J. M.

1981-01-01

A survey of acousto-optic spectrometers for molecular astronomy is presented, noting a technique of combining the acoustic bending of a collimated coherent light beam with a Bragg cell followed by an array of sensitive photodetectors. This acousto-optic spectrometer has a large bandwidth, a large number of channels, high resolution, and is energy efficient. Receiver development has concentrated on high-frequency heterodyne systems for the study of the chemical composition of the interstellar medium. RF spectrometers employing acousto-optic diffraction cells are described. Acousto-optic techniques have been suggested for applications to electronic warfare, electronic countermeasures and electronic support systems. Plans to use integrated optics for the further miniaturization of acousto-optic spectrometers are described. Bulk acousto-optic spectrometers with 300 MHz and 1 GHz bandwidths are being developed for use in the back-end of high-frequency heterodyne receivers for astronomical research.

Integrated structural biology to unravel molecular mechanisms of protein-RNA recognition.

PubMed

Schlundt, Andreas; Tants, Jan-Niklas; Sattler, Michael

2017-04-15

Recent advances in RNA sequencing technologies have greatly expanded our knowledge of the RNA landscape in cells, often with spatiotemporal resolution. These techniques identified many new (often non-coding) RNA molecules. Large-scale studies have also discovered novel RNA binding proteins (RBPs), which exhibit single or multiple RNA binding domains (RBDs) for recognition of specific sequence or structured motifs in RNA. Starting from these large-scale approaches it is crucial to unravel the molecular principles of protein-RNA recognition in ribonucleoprotein complexes (RNPs) to understand the underlying mechanisms of gene regulation. Structural biology and biophysical studies at highest possible resolution are key to elucidate molecular mechanisms of RNA recognition by RBPs and how conformational dynamics, weak interactions and cooperative binding contribute to the formation of specific, context-dependent RNPs. While large compact RNPs can be well studied by X-ray crystallography and cryo-EM, analysis of dynamics and weak interaction necessitates the use of solution methods to capture these properties. Here, we illustrate methods to study the structure and conformational dynamics of protein-RNA complexes in solution starting from the identification of interaction partners in a given RNP. Biophysical and biochemical techniques support the characterization of a protein-RNA complex and identify regions relevant in structural analysis. Nuclear magnetic resonance (NMR) is a powerful tool to gain information on folding, stability and dynamics of RNAs and characterize RNPs in solution. It provides crucial information that is complementary to the static pictures derived from other techniques. NMR can be readily combined with other solution techniques, such as small angle X-ray and/or neutron scattering (SAXS/SANS), electron paramagnetic resonance (EPR), and Förster resonance energy transfer (FRET), which provide information about overall shapes, internal domain

Visual feature integration and focused attention: response competition from multiple distractor features.

PubMed

Lavie, N

1997-05-01

Predictions from Treisman's feature integration theory of attention were tested in a variant of the response-competition paradigm. Subjects made choice responses to particular color-shape conjunctions (e.g., a purple cross vs. a green circle) while withholding their responses to the opposite conjunctions (i.e., a purple circle vs. a green cross). The results showed that compatibility effects were based on both distractor color and shape. For unattended distractors in preknown irrelevant positions, compatibility effects were equivalent for conjunctive distractors (e.g., a purple cross and a blue triangle) and for disjunctive distractors (e.g., a purple triangle and a blue cross). Manipulation of attention to the distractors positions resulted in larger compatibility effects from conjoined features. These results accord with Treisman's claim that correct conjunction information is unavailable under conditions of inattention, and they provide new information on response-competition effects from multiple features.

The implementation of multiple interprofessional integrated modules by health sciences faculty in Chile.

PubMed

Castillo-Parra, Silvana; Oyarzo Torres, Sandra; Espinoza Barrios, Mónica; Rojas-Serey, Ana María; Maya, Juan Diego; Sabaj Diez, Valeria; Aliaga Castillo, Verónica; Castillo Niño, Manuel; Romero Romero, Luis; Foster, Jennifer; Hawes Barrios, Gustavo

2017-11-01

Multiple interprofessional integrated modules (MIIM) 1 and 2 are two required, cross-curricular courses developed by a team of health professions faculty, as well as experts in education, within the Faculty of Medicine of the University of Chile. MIIM 1 focused on virtual cases requiring team decision-making in real time. MIIM 2 focused on a team-based community project. The evaluation of MIIM included student, teacher, and coordinator perspectives. To explore the perceptions of this interprofessional experience quantitative data in the form of standardised course evaluations regarding teaching methodology, interpersonal relations and the course organisation and logistics were gathered. In addition, qualitative perceptions were collected from student focus groups and meetings with tutors and coordinators. Between 2010 and 2014, 881 students enrolled in MIIM. Their evaluation scores rated interpersonal relations most highly, followed by organisation and logistics, and then teaching methodology. A key result was the learning related to interprofessional team work by the teaching coordinators, as well as the participating faculty. The strengths of this experience included student integration and construction of new knowledge, skill development in making decisions, and collective self-learning. Challenges included additional time management and tutors' role. This work requires valuation of an alternative way of learning, which is critical for the performance of future health professionals.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics

PubMed Central

Armen, Roger S.; Chen, Jianhan; Brooks, Charles L.

2009-01-01

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and “noise” that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds. PMID:20160879

Host-Guest Chemistry in Integrated Porous Space Formed by Molecular Self-Assembly at Liquid-Solid Interfaces.

PubMed

Iritani, Kohei; Tahara, Kazukuni; De Feyter, Steven; Tobe, Yoshito

2017-05-16

Host-guest chemistry in two-dimensional (2D) space, that is, physisorbed monolayers of a single atom or a single molecular thickness on surfaces, has become a subject of intense current interest because of perspectives for various applications in molecular-scale electronics, selective sensors, and tailored catalysis. Scanning tunneling microscopy has been used as a powerful tool for the visualization of molecules in real space on a conducting substrate surface. For more than a decade, we have been investigating the self-assembly of a series of triangle-shaped phenylene-ethynylene macrocycles called dehydrobenzo[12]annulenes (DBAs). These molecules are substituted with six alkyl chains and are capable of forming hexagonal porous 2D molecular networks via van der Waals interactions between interdigitated alkyl chains at the interface of organic solvents and graphite. The dimension of the nanoporous space or nanowell formed by the self-assembly of DBAs can be controlled from 1.6 to 4.7 nm by simply changing the alkyl chain length from C 6 to C 20 . Single molecules as well as homoclusters and heteroclusters are capable of coadsorbing within the host matrix using shape- and size-complementarity principles. Moreover, on the basis of the versatility of the DBA molecules that allows chemical modification of the alkyl chain terminals, we were able to decorate the interior space of the nanoporous networks with functional groups such as azobenzenedicarboxylic acid for photoresponsive guest adsorption/desorption or fluoroalkanes and tetraethylene glycol groups for selective guest binding by electrostatic interactions and zinc-porphyrin units for complexation with a guest by charge-transfer interactions. In this Feature Article, we describe the general aspects of molecular self-assembly at liquid/solid interfaces, followed by the formation of programmed porous molecular networks using rationally designed molecular building blocks. We focus on our own work involving host

Communication: Phase diagram of C36 by atomistic molecular dynamics and thermodynamic integration through coexistence regions

NASA Astrophysics Data System (ADS)

Abramo, M. C.; Caccamo, C.; Costa, D.; Munaò, G.

2014-09-01

We report an atomistic molecular dynamics determination of the phase diagram of a rigid-cage model of C36. We first show that free energies obtained via thermodynamic integrations along isotherms displaying "van der Waals loops," are fully reproduced by those obtained via isothermal-isochoric integration encompassing only stable states. We find that a similar result also holds for isochoric paths crossing van der Waals regions of the isotherms, and for integrations extending to rather high densities where liquid-solid coexistence can be expected to occur. On such a basis we are able to map the whole phase diagram of C36, with resulting triple point and critical temperatures about 1770 K and 2370 K, respectively. We thus predict a 600 K window of existence of a stable liquid phase. Also, at the triple point density, we find that the structural functions and the diffusion coefficient maintain a liquid-like character down to 1400-1300 K, this indicating a wide region of possible supercooling. We discuss why all these features might render possible the observation of the melting of C36 fullerite and of its liquid state, at variance with what previously experienced for C60.

MutAid: Sanger and NGS Based Integrated Pipeline for Mutation Identification, Validation and Annotation in Human Molecular Genetics.

PubMed

Pandey, Ram Vinay; Pabinger, Stephan; Kriegner, Albert; Weinhäusel, Andreas

2016-01-01

Traditional Sanger sequencing as well as Next-Generation Sequencing have been used for the identification of disease causing mutations in human molecular research. The majority of currently available tools are developed for research and explorative purposes and often do not provide a complete, efficient, one-stop solution. As the focus of currently developed tools is mainly on NGS data analysis, no integrative solution for the analysis of Sanger data is provided and consequently a one-stop solution to analyze reads from both sequencing platforms is not available. We have therefore developed a new pipeline called MutAid to analyze and interpret raw sequencing data produced by Sanger or several NGS sequencing platforms. It performs format conversion, base calling, quality trimming, filtering, read mapping, variant calling, variant annotation and analysis of Sanger and NGS data under a single platform. It is capable of analyzing reads from multiple patients in a single run to create a list of potential disease causing base substitutions as well as insertions and deletions. MutAid has been developed for expert and non-expert users and supports four sequencing platforms including Sanger, Illumina, 454 and Ion Torrent. Furthermore, for NGS data analysis, five read mappers including BWA, TMAP, Bowtie, Bowtie2 and GSNAP and four variant callers including GATK-HaplotypeCaller, SAMTOOLS, Freebayes and VarScan2 pipelines are supported. MutAid is freely available at https://sourceforge.net/projects/mutaid.

MutAid: Sanger and NGS Based Integrated Pipeline for Mutation Identification, Validation and Annotation in Human Molecular Genetics

PubMed Central

Pandey, Ram Vinay; Pabinger, Stephan; Kriegner, Albert; Weinhäusel, Andreas

2016-01-01

Traditional Sanger sequencing as well as Next-Generation Sequencing have been used for the identification of disease causing mutations in human molecular research. The majority of currently available tools are developed for research and explorative purposes and often do not provide a complete, efficient, one-stop solution. As the focus of currently developed tools is mainly on NGS data analysis, no integrative solution for the analysis of Sanger data is provided and consequently a one-stop solution to analyze reads from both sequencing platforms is not available. We have therefore developed a new pipeline called MutAid to analyze and interpret raw sequencing data produced by Sanger or several NGS sequencing platforms. It performs format conversion, base calling, quality trimming, filtering, read mapping, variant calling, variant annotation and analysis of Sanger and NGS data under a single platform. It is capable of analyzing reads from multiple patients in a single run to create a list of potential disease causing base substitutions as well as insertions and deletions. MutAid has been developed for expert and non-expert users and supports four sequencing platforms including Sanger, Illumina, 454 and Ion Torrent. Furthermore, for NGS data analysis, five read mappers including BWA, TMAP, Bowtie, Bowtie2 and GSNAP and four variant callers including GATK-HaplotypeCaller, SAMTOOLS, Freebayes and VarScan2 pipelines are supported. MutAid is freely available at https://sourceforge.net/projects/mutaid. PMID:26840129

Comprehensive molecular profiling of 718 Multiple Myelomas reveals significant differences in mutation frequencies between African and European descent cases

PubMed Central

Christofferson, Austin; Aldrich, Jessica; Jewell, Scott; Kittles, Rick A.; Derome, Mary; Craig, David Wesley; Carpten, John D.

2017-01-01

Multiple Myeloma (MM) is a plasma cell malignancy with significantly greater incidence and mortality rates among African Americans (AA) compared to Caucasians (CA). The overall goal of this study is to elucidate differences in molecular alterations in MM as a function of self-reported race and genetic ancestry. Our study utilized somatic whole exome, RNA-sequencing, and correlated clinical data from 718 MM patients from the Multiple Myeloma Research Foundation CoMMpass study Interim Analysis 9. Somatic mutational analyses based upon self-reported race corrected for ancestry revealed significant differences in mutation frequency between groups. Of interest, BCL7A, BRWD3, and AUTS2 demonstrate significantly higher mutation frequencies among AA cases. These genes are all involved in translocations in B-cell malignancies. Moreover, we detected a significant difference in mutation frequency of TP53 and IRF4 with frequencies higher among CA cases. Our study provides rationale for interrogating diverse tumor cohorts to best understand tumor genomics across populations. PMID:29166413

Generating nonlinear FM chirp radar signals by multiple integrations

DOEpatents

Doerry, Armin W [Albuquerque, NM

2011-02-01

A phase component of a nonlinear frequency modulated (NLFM) chirp radar pulse can be produced by performing digital integration operations over a time interval defined by the pulse width. Each digital integration operation includes applying to a respectively corresponding input parameter value a respectively corresponding number of instances of digital integration.

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks.

PubMed

Shen, Yiwen; Hattink, Maarten H N; Samadi, Payman; Cheng, Qixiang; Hu, Ziyiz; Gazman, Alexander; Bergman, Keren

2018-04-16

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. We present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly network testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 µs control plane latency for data-center and high performance computing platforms.

Integrated systems analysis reveals a molecular network underlying autism spectrum disorders

PubMed Central

Li, Jingjing; Shi, Minyi; Ma, Zhihai; Zhao, Shuchun; Euskirchen, Ghia; Ziskin, Jennifer; Urban, Alexander; Hallmayer, Joachim; Snyder, Michael

2014-01-01

Autism is a complex disease whose etiology remains elusive. We integrated previously and newly generated data and developed a systems framework involving the interactome, gene expression and genome sequencing to identify a protein interaction module with members strongly enriched for autism candidate genes. Sequencing of 25 patients confirmed the involvement of this module in autism, which was subsequently validated using an independent cohort of over 500 patients. Expression of this module was dichotomized with a ubiquitously expressed subcomponent and another subcomponent preferentially expressed in the corpus callosum, which was significantly affected by our identified mutations in the network center. RNA-sequencing of the corpus callosum from patients with autism exhibited extensive gene mis-expression in this module, and our immunochemical analysis showed that the human corpus callosum is predominantly populated by oligodendrocyte cells. Analysis of functional genomic data further revealed a significant involvement of this module in the development of oligodendrocyte cells in mouse brain. Our analysis delineates a natural network involved in autism, helps uncover novel candidate genes for this disease and improves our understanding of its molecular pathology. PMID:25549968

Molecular Profiling of Multiple Human Cancers Defines an Inflammatory Cancer-Associated Molecular Pattern and Uncovers KPNA2 as a Uniform Poor Prognostic Cancer Marker

PubMed Central

Rachidi, Saleh M.; Qin, Tingting; Sun, Shaoli; Zheng, W. Jim; Li, Zihai

2013-01-01

Background Immune evasion is one of the recognized hallmarks of cancer. Inflammatory responses to cancer can also contribute directly to oncogenesis. Since the immune system is hardwired to protect the host, there is a possibility that cancers, regardless of their histological origins, endow themselves with a common and shared inflammatory cancer-associated molecular pattern (iCAMP) to promote oncoinflammation. However, the definition of iCAMP has not been conceptually and experimentally investigated. Methods and Findings Genome-wide cDNA expression data was analyzed for 221 normal and 324 cancer specimens from 7 cancer types: breast, prostate, lung, colon, gastric, oral and pancreatic. A total of 96 inflammatory genes with consistent dysregulation were identified, including 44 up-regulated and 52 down-regulated genes. Protein expression was confirmed by immunohistochemistry for some of these genes. The iCAMP contains proteins whose roles in cancer have been implicated and others which are yet to be appreciated. The clinical significance of many iCAMP genes was confirmed in multiple independent cohorts of colon and ovarian cancer patients. In both cases, better prognosis correlated strongly with high CXCL13 and low level of GREM1, LOX, TNFAIP6, CD36, and EDNRA. An “Inflammatory Gene Integrated Score” was further developed from the combination of 18 iCAMP genes in ovarian cancer, which predicted overall survival. Noticeably, as a selective nuclear import protein whose immuno-regulatory function just begins to emerge, karyopherin alpha 2 (KPNA2) is uniformly up-regulated across cancer types. For the first time, the cancer-specific up-regulation of KPNA2 and its clinical significance were verified by tissue microarray analysis in colon and head-neck cancers. Conclusion This work defines an inflammatory signature shared by seven epithelial cancer types and KPNA2 as a consistently up-regulated protein in cancer. Identification of iCAMP may not only serve as a novel

Recurrent Innovation at Genes Required for Telomere Integrity in Drosophila.

PubMed

Lee, Yuh Chwen G; Leek, Courtney; Levine, Mia T

2017-02-01

Telomeres are nucleoprotein complexes at the ends of linear chromosomes. These specialized structures ensure genome integrity and faithful chromosome inheritance. Recurrent addition of repetitive, telomere-specific DNA elements to chromosome ends combats end-attrition, while specialized telomere-associated proteins protect naked, double-stranded chromosome ends from promiscuous repair into end-to-end fusions. Although telomere length homeostasis and end-protection are ubiquitous across eukaryotes, there is sporadic but building evidence that the molecular machinery supporting these essential processes evolves rapidly. Nevertheless, no global analysis of the evolutionary forces that shape these fast-evolving proteins has been performed on any eukaryote. The abundant population and comparative genomic resources of Drosophila melanogaster and its close relatives offer us a unique opportunity to fill this gap. Here we leverage population genetics, molecular evolution, and phylogenomics to define the scope and evolutionary mechanisms driving fast evolution of genes required for telomere integrity. We uncover evidence of pervasive positive selection across multiple evolutionary timescales. We also document prolific expansion, turnover, and expression evolution in gene families founded by telomeric proteins. Motivated by the mutant phenotypes and molecular roles of these fast-evolving genes, we put forward four alternative, but not mutually exclusive, models of intra-genomic conflict that may play out at very termini of eukaryotic chromosomes. Our findings set the stage for investigating both the genetic causes and functional consequences of telomere protein evolution in Drosophila and beyond. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Rembrandt: Helping Personalized Medicine Become a Reality Through Integrative Translational Research

PubMed Central

Madhavan, Subha; Zenklusen, Jean-Claude; Kotliarov, Yuri; Sahni, Himanso; Fine, Howard A.; Buetow, Kenneth

2009-01-01

Finding better therapies for the treatment of brain tumors is hampered by the lack of consistently obtained molecular data in a large sample set, and ability to integrate biomedical data from disparate sources enabling translation of therapies from bench to bedside. Hence, a critical factor in the advancement of biomedical research and clinical translation is the ease with which data can be integrated, redistributed and analyzed both within and across functional domains. Novel biomedical informatics infrastructure and tools are essential for developing individualized patient treatment based on the specific genomic signatures in each patient’s tumor. Here we present Rembrandt, Repository of Molecular BRAin Neoplasia DaTa, a cancer clinical genomics database and a web-based data mining and analysis platform aimed at facilitating discovery by connecting the dots between clinical information and genomic characterization data. To date, Rembrandt contains data generated through the Glioma Molecular Diagnostic Initiative from 874 glioma specimens comprising nearly 566 gene expression arrays, 834 copy number arrays and 13,472 clinical phenotype data points. Data can be queried and visualized for a selected gene across all data platforms or for multiple genes in a selected platform. Additionally, gene sets can be limited to clinically important annotations including secreted, kinase, membrane, and known gene-anomaly pairs to facilitate the discovery of novel biomarkers and therapeutic targets. We believe that REMBRANDT represents a prototype of how high throughput genomic and clinical data can be integrated in a way that will allow expeditious and efficient translation of laboratory discoveries to the clinic. PMID:19208739

Integrated photoacoustic, ultrasound and fluorescence platform for diagnostic medical imaging-proof of concept study with a tissue mimicking phantom.

PubMed

James, Joseph; Murukeshan, Vadakke Matham; Woh, Lye Sun

2014-07-01

The structural and molecular heterogeneities of biological tissues demand the interrogation of the samples with multiple energy sources and provide visualization capabilities at varying spatial resolution and depth scales for obtaining complementary diagnostic information. A novel multi-modal imaging approach that uses optical and acoustic energies to perform photoacoustic, ultrasound and fluorescence imaging at multiple resolution scales from the tissue surface and depth is proposed in this paper. The system comprises of two distinct forms of hardware level integration so as to have an integrated imaging system under a single instrumentation set-up. The experimental studies show that the system is capable of mapping high resolution fluorescence signatures from the surface, optical absorption and acoustic heterogeneities along the depth (>2cm) of the tissue at multi-scale resolution (<1µm to <0.5mm).

Formulation of an explicit-multiple-time-step time integration method for use in a global primitive equation grid model

NASA Technical Reports Server (NTRS)

Chao, W. C.

1982-01-01

With appropriate modifications, a recently proposed explicit-multiple-time-step scheme (EMTSS) is incorporated into the UCLA model. In this scheme, the linearized terms in the governing equations that generate the gravity waves are split into different vertical modes. Each mode is integrated with an optimal time step, and at periodic intervals these modes are recombined. The other terms are integrated with a time step dictated by the CFL condition for low-frequency waves. This large time step requires a special modification of the advective terms in the polar region to maintain stability. Test runs for 72 h show that EMTSS is a stable, efficient and accurate scheme.

Integrating Nanostructured Artificial Receptors with Whispering Gallery Mode Optical Microresonators via Inorganic Molecular Imprinting Techniques

PubMed Central

Hammond, G. Denise; Vojta, Adam L.; Grant, Sheila A.; Hunt, Heather K.

2016-01-01

The creation of label-free biosensors capable of accurately detecting trace contaminants, particularly small organic molecules, is of significant interest for applications in environmental monitoring. This is achieved by pairing a high-sensitivity signal transducer with a biorecognition element that imparts selectivity towards the compound of interest. However, many environmental pollutants do not have corresponding biorecognition elements. Fortunately, biomimetic chemistries, such as molecular imprinting, allow for the design of artificial receptors with very high selectivity for the target. Here, we perform a proof-of-concept study to show how artificial receptors may be created from inorganic silanes using the molecular imprinting technique and paired with high-sensitivity transducers without loss of device performance. Silica microsphere Whispering Gallery Mode optical microresonators are coated with a silica thin film templated by a small fluorescent dye, fluorescein isothiocyanate, which serves as our model target. Oxygen plasma degradation and solvent extraction of the template are compared. Extracted optical devices are interacted with the template molecule to confirm successful sorption of the template. Surface characterization is accomplished via fluorescence and optical microscopy, ellipsometry, optical profilometry, and contact angle measurements. The quality factors of the devices are measured to evaluate the impact of the coating on device sensitivity. The resulting devices show uniform surface coating with no microstructural damage with Q factors above 106. This is the first report demonstrating the integration of these devices with molecular imprinting techniques, and could lead to new routes to biosensor creation for environmental monitoring. PMID:27314397

Unmasking molecular profiles of bladder cancer.

PubMed

Piao, Xuan-Mei; Byun, Young Joon; Kim, Wun-Jae; Kim, Jayoung

2018-03-01

Precision medicine is designed to tailor treatments for individual patients by factoring in each person's specific biology and mechanism of disease. This paradigm shifted from a "one size fits all" approach to "personalized and precision care" requires multiple layers of molecular profiling of biomarkers for accurate diagnosis and prediction of treatment responses. Intensive studies are also being performed to understand the complex and dynamic molecular profiles of bladder cancer. These efforts involve looking bladder cancer mechanism at the multiple levels of the genome, epigenome, transcriptome, proteome, lipidome, metabolome etc. The aim of this short review is to outline the current technologies being used to investigate molecular profiles and discuss biomarker candidates that have been investigated as possible diagnostic and prognostic indicators of bladder cancer.

Magnetic particles for in vitro molecular diagnosis: From sample preparation to integration into microsystems.

PubMed

Tangchaikeeree, Tienrat; Polpanich, Duangporn; Elaissari, Abdelhamid; Jangpatarapongsa, Kulachart

2017-10-01

Colloidal magnetic particles (MPs) have been developed in association with molecular diagnosis for several decades. MPs have the great advantage of easy manipulation using a magnet. In nucleic acid detection, these particles can act as a capture support for rapid and simple biomolecule separation. The surfaces of MPs can be modified by coating with various polymer materials to provide functionalization for different applications. The use of MPs enhances the sensitivity and specificity of detection due to the specific activity on the surface of the particles. Practical applications of MPs demonstrate greater efficiency than conventional methods. Beyond traditional detection, MPs have been successfully adopted as a smart carrier in microfluidic and lab-on-a-chip biosensors. The versatility of MPs has enabled their integration into small single detection units. MPs-based biosensors can facilitate rapid and highly sensitive detection of very small amounts of a sample. In this review, the application of MPs to the detection of nucleic acids, from sample preparation to analytical readout systems, is described. State-of-the-art integrated microsystems containing microfluidic and lab-on-a-chip biosensors for the nucleic acid detection are also addressed. Copyright © 2017 Elsevier B.V. All rights reserved.

An integrated decision making approach for assessing healthcare waste treatment technologies from a multiple stakeholder.

PubMed

Shi, Hua; Liu, Hu-Chen; Li, Ping; Xu, Xue-Guo

2017-01-01

With increased worldwide awareness of environmental issues, healthcare waste (HCW) management has received much attention from both researchers and practitioners over the past decade. The task of selecting the optimum treatment technology for HCWs is a challenging decision making problem involving conflicting evaluation criteria and multiple stakeholders. In this paper, we develop an integrated decision making framework based on cloud model and MABAC method for evaluating and selecting the best HCW treatment technology from a multiple stakeholder perspective. The introduced framework deals with uncertain linguistic assessments of alternatives by using interval 2-tuple linguistic variables, determines decision makers' relative weights based on the uncertainty and divergence degrees of every decision maker, and obtains the ranking of all HCW disposal alternatives with the aid of an extended MABAC method. Finally, an empirical example from Shanghai, China, is provided to illustrate the feasibility and effectiveness of the proposed approach. Results indicate that the methodology being proposed is more suitable and effective to handle the HCW treatment technology selection problem under vague and uncertain information environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Developing molecular tools for Chlamydomonas reinhardtii

NASA Astrophysics Data System (ADS)

Noor-Mohammadi, Samaneh

Microalgae have garnered increasing interest over the years for their ability to produce compounds ranging from biofuels to neutraceuticals. A main focus of researchers has been to use microalgae as a natural bioreactor for the production of valuable and complex compounds. Recombinant protein expression in the chloroplasts of green algae has recently become more routine; however, the heterologous expression of multiple proteins or complete biosynthetic pathways remains a significant challenge. To take full advantage of these organisms' natural abilities, sophisticated molecular tools are needed to be able to introduce and functionally express multiple gene biosynthetic pathways in its genome. To achieve the above objective, we have sought to establish a method to construct, integrate and express multigene operons in the chloroplast and nuclear genome of the model microalgae Chlamydomonas reinhardtii. Here we show that a modified DNA Assembler approach can be used to rapidly assemble multiple-gene biosynthetic pathways in yeast and then integrate these assembled pathways at a site-specific location in the chloroplast, or by random integration in the nuclear genome of C. reinhardtii. As a proof of concept, this method was used to successfully integrate and functionally express up to three reporter proteins (AphA6, AadA, and GFP) in the chloroplast of C. reinhardtii and up to three reporter proteins (Ble, AphVIII, and GFP) in its nuclear genome. An analysis of the relative gene expression of the engineered strains showed significant differences in the mRNA expression levels of the reporter genes and thus highlights the importance of proper promoter/untranslated-region selection when constructing a target pathway. In addition, this work focuses on expressing the cofactor regeneration enzyme phosphite dehydrogenase (PTDH) in the chloroplast and nuclear genomes of C. reinhardtii. The PTDH enzyme converts phosphite into phosphate and NAD(P)+ into NAD(P)H. The reduced

Multiple gastrointestinal stromal tumors in type I neurofibromatosis: a pathologic and molecular study.

PubMed

Yantiss, Rhonda K; Rosenberg, Andrew E; Sarran, Lisa; Besmer, Peter; Antonescu, Cristina R

2005-04-01

Multiple gastrointestinal stromal tumors typically occur in familial form associated with KIT receptor tyrosine kinase or platelet-derived growth factor receptor-alpha (PDGFRA) germline mutations, but may also develop in the setting of type 1 neurofibromatosis. The molecular abnormalities of gastrointestinal stromal tumors arising in neurofibromatosis have not been extensively studied. We identified three patients with type 1 neuro-fibromatosis and multiple small intestinal stromal tumors. Immunostains for CD117, CD34, desmin, actins, S-100 protein, and keratins were performed on all of the tumors. DNA was extracted from representative paraffin blocks from separate tumor nodules in each case and subjected to a nested polymerase chain reaction, using primers for KIT exons 9, 11, 13, and 17 and PDGFRA exons 12 and 18, followed by direct sequencing. The mean patient age was 56 years (range: 37-86 years, male/female ratio: 2/1). One patient had three tumors, one had five, and one had greater than 10 tumor nodules, all of which demonstrated histologic features characteristic of gastrointestinal stromal tumors and stained strongly for CD117 and CD34. One patient died of disease at 35 months, one was disease free at 12 months and one was lost to follow-up. DNA extracts from 10 gastrointestinal stromal tumors (three from each of two patients and four from one patient) were subjected to polymerase chain reactions and assessed for mutations. All of the tumors were wild type for KIT exons 9, 13, and 17 and PDGFRA exons 12 and 18. Three tumors from one patient had identical point mutations in KIT exon 11, whereas the other tumors were wild type at this locus. We conclude that, although most patients with type 1 neurofibromatosis and gastrointestinal stromal tumors do not have KIT or PDGFRA mutations, KIT germline mutations might be implicated in the pathogenesis of gastrointestinal stromal tumors in some patients.

Ensemble-Biased Metadynamics: A Molecular Simulation Method to Sample Experimental Distributions

PubMed Central

Marinelli, Fabrizio; Faraldo-Gómez, José D.

2015-01-01

We introduce an enhanced-sampling method for molecular dynamics (MD) simulations referred to as ensemble-biased metadynamics (EBMetaD). The method biases a conventional MD simulation to sample a molecular ensemble that is consistent with one or more probability distributions known a priori, e.g., experimental intramolecular distance distributions obtained by double electron-electron resonance or other spectroscopic techniques. To this end, EBMetaD adds an adaptive biasing potential throughout the simulation that discourages sampling of configurations inconsistent with the target probability distributions. The bias introduced is the minimum necessary to fulfill the target distributions, i.e., EBMetaD satisfies the maximum-entropy principle. Unlike other methods, EBMetaD does not require multiple simulation replicas or the introduction of Lagrange multipliers, and is therefore computationally efficient and straightforward in practice. We demonstrate the performance and accuracy of the method for a model system as well as for spin-labeled T4 lysozyme in explicit water, and show how EBMetaD reproduces three double electron-electron resonance distance distributions concurrently within a few tens of nanoseconds of simulation time. EBMetaD is integrated in the open-source PLUMED plug-in (www.plumed-code.org), and can be therefore readily used with multiple MD engines. PMID:26083917

MIDG-Emerging grid technologies for multi-site preclinical molecular imaging research communities.

PubMed

Lee, Jasper; Documet, Jorge; Liu, Brent; Park, Ryan; Tank, Archana; Huang, H K

2011-03-01

Molecular imaging is the visualization and identification of specific molecules in anatomy for insight into metabolic pathways, tissue consistency, and tracing of solute transport mechanisms. This paper presents the Molecular Imaging Data Grid (MIDG) which utilizes emerging grid technologies in preclinical molecular imaging to facilitate data sharing and discovery between preclinical molecular imaging facilities and their collaborating investigator institutions to expedite translational sciences research. Grid-enabled archiving, management, and distribution of animal-model imaging datasets help preclinical investigators to monitor, access and share their imaging data remotely, and promote preclinical imaging facilities to share published imaging datasets as resources for new investigators. The system architecture of the Molecular Imaging Data Grid is described in a four layer diagram. A data model for preclinical molecular imaging datasets is also presented based on imaging modalities currently used in a molecular imaging center. The MIDG system components and connectivity are presented. And finally, the workflow steps for grid-based archiving, management, and retrieval of preclincial molecular imaging data are described. Initial performance tests of the Molecular Imaging Data Grid system have been conducted at the USC IPILab using dedicated VMware servers. System connectivity, evaluated datasets, and preliminary results are presented. The results show the system's feasibility, limitations, direction of future research. Translational and interdisciplinary research in medicine is increasingly interested in cellular and molecular biology activity at the preclinical levels, utilizing molecular imaging methods on animal models. The task of integrated archiving, management, and distribution of these preclinical molecular imaging datasets at preclinical molecular imaging facilities is challenging due to disparate imaging systems and multiple off-site investigators. A

Interventional Molecular Imaging.

PubMed

Solomon, Stephen B; Cornelis, Francois

2016-04-01

Although molecular imaging has had a dramatic impact on diagnostic imaging, it has only recently begun to be integrated into interventional procedures. Its significant impact is attributed to its ability to provide noninvasive, physiologic information that supplements conventional morphologic imaging. The four major interventional opportunities for molecular imaging are, first, to provide guidance to localize a target; second, to provide tissue analysis to confirm that the target has been reached; third, to provide in-room, posttherapy assessment; and fourth, to deliver targeted therapeutics. With improved understanding and application of(18)F-FDG, as well as the addition of new molecular probes beyond(18)F-FDG, the future holds significant promise for the expansion of molecular imaging into the realm of interventional procedures. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Crosstalk between intracellular and extracellular signals regulating interneuron production, migration and integration into the cortex

PubMed Central

Peyre, Elise; Silva, Carla G.; Nguyen, Laurent

2015-01-01

During embryogenesis, cortical interneurons are generated by ventral progenitors located in the ganglionic eminences of the telencephalon. They travel along multiple tangential paths to populate the cortical wall. As they reach this structure they undergo intracortical dispersion to settle in their final destination. At the cellular level, migrating interneurons are highly polarized cells that extend and retract processes using dynamic remodeling of microtubule and actin cytoskeleton. Different levels of molecular regulation contribute to interneuron migration. These include: (1) Extrinsic guidance cues distributed along migratory streams that are sensed and integrated by migrating interneurons; (2) Intrinsic genetic programs driven by specific transcription factors that grant specification and set the timing of migration for different subtypes of interneurons; (3) Adhesion molecules and cytoskeletal elements/regulators that transduce molecular signalings into coherent movement. These levels of molecular regulation must be properly integrated by interneurons to allow their migration in the cortex. The aim of this review is to summarize our current knowledge of the interplay between microenvironmental signals and cell autonomous programs that drive cortical interneuron porduction, tangential migration, and intergration in the developing cerebral cortex. PMID:25926769

Integrative molecular network analysis identifies emergent enzalutamide resistance mechanisms in prostate cancer

PubMed Central

King, Carly J.; Woodward, Josha; Schwartzman, Jacob; Coleman, Daniel J.; Lisac, Robert; Wang, Nicholas J.; Van Hook, Kathryn; Gao, Lina; Urrutia, Joshua; Dane, Mark A.; Heiser, Laura M.; Alumkal, Joshi J.

2017-01-01

Recent work demonstrates that castration-resistant prostate cancer (CRPC) tumors harbor countless genomic aberrations that control many hallmarks of cancer. While some specific mutations in CRPC may be actionable, many others are not. We hypothesized that genomic aberrations in cancer may operate in concert to promote drug resistance and tumor progression, and that organization of these genomic aberrations into therapeutically targetable pathways may improve our ability to treat CRPC. To identify the molecular underpinnings of enzalutamide-resistant CRPC, we performed transcriptional and copy number profiling studies using paired enzalutamide-sensitive and resistant LNCaP prostate cancer cell lines. Gene networks associated with enzalutamide resistance were revealed by performing an integrative genomic analysis with the PAthway Representation and Analysis by Direct Reference on Graphical Models (PARADIGM) tool. Amongst the pathways enriched in the enzalutamide-resistant cells were those associated with MEK, EGFR, RAS, and NFKB. Functional validation studies of 64 genes identified 10 candidate genes whose suppression led to greater effects on cell viability in enzalutamide-resistant cells as compared to sensitive parental cells. Examination of a patient cohort demonstrated that several of our functionally-validated gene hits are deregulated in metastatic CRPC tumor samples, suggesting that they may be clinically relevant therapeutic targets for patients with enzalutamide-resistant CRPC. Altogether, our approach demonstrates the potential of integrative genomic analyses to clarify determinants of drug resistance and rational co-targeting strategies to overcome resistance. PMID:29340039

Harnessing the Power of Integrated Mitochondrial Biology and Physiology: A Special Report on the NHLBI Mitochondria in Heart Diseases Initiative

PubMed Central

Ping, Peipei; Gustafsson, Åsa B.; Bers, Don M.; Blatter, Lothar; Cai, Hua; Jahangir, Arshad; Kelly, Daniel; Muoio, Deborah; O'Rourke, Brian; Rabinovitch, Peter; Trayanova, Natalia; Van Eyk, Jennifer; Weiss, James N.; Wong, Renee; Longacre, Lisa Schwartz

2015-01-01

Summary Mitochondrial biology is the sum of diverse phenomena from molecular profiles to physiological functions. A mechanistic understanding of mitochondria in disease development, and hence the future prospect of clinical translations, relies on a systems-level integration of expertise from multiple fields of investigation. Upon the successful completion of a recent National Institutes of Health, National Heart, Lung, and Blood Institute initiative on integrative mitochondrial biology in cardiovascular diseases, we reflect on the accomplishments made possible by this unique interdisciplinary collaboration effort and exciting new fronts on the study of these remarkable organelles. PMID:26185209

Cooperation and coexpression: How coexpression networks shift in response to multiple mutualists.

PubMed

Palakurty, Sathvik X; Stinchcombe, John R; Afkhami, Michelle E

2018-04-01

A mechanistic understanding of community ecology requires tackling the nonadditive effects of multispecies interactions, a challenge that necessitates integration of ecological and molecular complexity-namely moving beyond pairwise ecological interaction studies and the "gene at a time" approach to mechanism. Here, we investigate the consequences of multispecies mutualisms for the structure and function of genomewide differential coexpression networks for the first time, using the tractable and ecologically important interaction between legume Medicago truncatula, rhizobia and mycorrhizal fungi. First, we found that genes whose expression is affected nonadditively by multiple mutualists are more highly connected in gene networks than expected by chance and had 94% greater network centrality than genes showing additive effects, suggesting that nonadditive genes may be key players in the widespread transcriptomic responses to multispecies symbioses. Second, multispecies mutualisms substantially changed coexpression network structure of 18 modules of host plant genes and 22 modules of the fungal symbionts' genes, indicating that third-party mutualists can cause significant rewiring of plant and fungal molecular networks. Third, we found that 60% of the coexpressed gene sets that explained variation in plant performance had coexpression structures that were altered by interactive effects of rhizobia and fungi. Finally, an "across-symbiosis" approach identified sets of plant and mycorrhizal genes whose coexpression structure was unique to the multiple mutualist context and suggested coupled responses across the plant-mycorrhizal interaction to rhizobial mutualists. Taken together, these results show multispecies mutualisms have substantial effects on the molecular interactions in host plants, microbes and across symbiotic boundaries. © 2018 John Wiley & Sons Ltd.

Pooling Data from Multiple Longitudinal Studies: The Role of Item Response Theory in Integrative Data Analysis

PubMed Central

Curran, Patrick J.; Hussong, Andrea M.; Cai, Li; Huang, Wenjing; Chassin, Laurie; Sher, Kenneth J.; Zucker, Robert A.

2010-01-01

There are a number of significant challenges encountered when studying development over an extended period of time including subject attrition, changing measurement structures across group and developmental period, and the need to invest substantial time and money. Integrative data analysis is an emerging set of methodologies that overcomes many of the challenges of single sample designs through the pooling of data drawn from multiple existing developmental studies. This approach is characterized by a host of advantages, but this also introduces several new complexities that must be addressed prior to broad adoption by developmental researchers. In this paper we focus on methods for fitting measurement models and creating scale scores using data drawn from multiple longitudinal studies. We present findings from the analysis of repeated measures of internalizing symptomatology that were pooled from three existing developmental studies. We describe and demonstrate each step in the analysis and we conclude with a discussion of potential limitations and directions for future research. PMID:18331129

PosMed-plus: an intelligent search engine that inferentially integrates cross-species information resources for molecular breeding of plants.

PubMed

Makita, Yuko; Kobayashi, Norio; Mochizuki, Yoshiki; Yoshida, Yuko; Asano, Satomi; Heida, Naohiko; Deshpande, Mrinalini; Bhatia, Rinki; Matsushima, Akihiro; Ishii, Manabu; Kawaguchi, Shuji; Iida, Kei; Hanada, Kosuke; Kuromori, Takashi; Seki, Motoaki; Shinozaki, Kazuo; Toyoda, Tetsuro

2009-07-01

Molecular breeding of crops is an efficient way to upgrade plant functions useful to mankind. A key step is forward genetics or positional cloning to identify the genes that confer useful functions. In order to accelerate the whole research process, we have developed an integrated database system powered by an intelligent data-retrieval engine termed PosMed-plus (Positional Medline for plant upgrading science), allowing us to prioritize highly promising candidate genes in a given chromosomal interval(s) of Arabidopsis thaliana and rice, Oryza sativa. By inferentially integrating cross-species information resources including genomes, transcriptomes, proteomes, localizomes, phenomes and literature, the system compares a user's query, such as phenotypic or functional keywords, with the literature associated with the relevant genes located within the interval. By utilizing orthologous and paralogous correspondences, PosMed-plus efficiently integrates cross-species information to facilitate the ranking of rice candidate genes based on evidence from other model species such as Arabidopsis. PosMed-plus is a plant science version of the PosMed system widely used by mammalian researchers, and provides both a powerful integrative search function and a rich integrative display of the integrated databases. PosMed-plus is the first cross-species integrated database that inferentially prioritizes candidate genes for forward genetics approaches in plant science, and will be expanded for wider use in plant upgrading in many species.

Statistical Methods in Integrative Genomics

PubMed Central

Richardson, Sylvia; Tseng, George C.; Sun, Wei

2016-01-01

Statistical methods in integrative genomics aim to answer important biology questions by jointly analyzing multiple types of genomic data (vertical integration) or aggregating the same type of data across multiple studies (horizontal integration). In this article, we introduce different types of genomic data and data resources, and then review statistical methods of integrative genomics, with emphasis on the motivation and rationale of these methods. We conclude with some summary points and future research directions. PMID:27482531

Intelligent multi-sensor integrations

NASA Technical Reports Server (NTRS)

Volz, Richard A.; Jain, Ramesh; Weymouth, Terry

1989-01-01

Growth in the intelligence of space systems requires the use and integration of data from multiple sensors. Generic tools are being developed for extracting and integrating information obtained from multiple sources. The full spectrum is addressed for issues ranging from data acquisition, to characterization of sensor data, to adaptive systems for utilizing the data. In particular, there are three major aspects to the project, multisensor processing, an adaptive approach to object recognition, and distributed sensor system integration.

Integration of Multiple Data Sources to Simulate the Dynamics of Land Systems

PubMed Central

Deng, Xiangzheng; Su, Hongbo; Zhan, Jinyan

2008-01-01

In this paper we present and develop a new model, which we have called Dynamics of Land Systems (DLS). The DLS model is capable of integrating multiple data sources to simulate the dynamics of a land system. Three main modules are incorporated in DLS: a spatial regression module, to explore the relationship between land uses and influencing factors, a scenario analysis module of the land uses of a region during the simulation period and a spatial disaggregation module, to allocate land use changes from a regional level to disaggregated grid cells. A case study on Taips County in North China is incorporated in this paper to test the functionality of DLS. The simulation results under the baseline, economic priority and environmental scenarios help to understand the land system dynamics and project near future land-use trajectories of a region, in order to focus management decisions on land uses and land use planning. PMID:27879726

Path integral molecular dynamics for exact quantum statistics of multi-electronic-state systems.

PubMed

Liu, Xinzijian; Liu, Jian

2018-03-14

An exact approach to compute physical properties for general multi-electronic-state (MES) systems in thermal equilibrium is presented. The approach is extended from our recent progress on path integral molecular dynamics (PIMD), Liu et al. [J. Chem. Phys. 145, 024103 (2016)] and Zhang et al. [J. Chem. Phys. 147, 034109 (2017)], for quantum statistical mechanics when a single potential energy surface is involved. We first define an effective potential function that is numerically favorable for MES-PIMD and then derive corresponding estimators in MES-PIMD for evaluating various physical properties. Its application to several representative one-dimensional and multi-dimensional models demonstrates that MES-PIMD in principle offers a practical tool in either of the diabatic and adiabatic representations for studying exact quantum statistics of complex/large MES systems when the Born-Oppenheimer approximation, Condon approximation, and harmonic bath approximation are broken.