Molecular initiating events of the intersex phenotype: Low-dose exposure to 17α-ethinylestradiol rapidly regulates molecular networks associated with gonad differentiation in the adult fathead minnow testis

International Nuclear Information System (INIS)

Feswick, April; Loughery, Jennifer R.; Isaacs, Meghan A.; Munkittrick, Kelly R.; Martyniuk, Christopher J.

2016-01-01

Highlights: • Male fathead minnow were exposed to 17alpha ethinylestradiol (EE2). • Both 11-ketotestosterone and testosterone production was decreased relative to controls. • A gene network associated with doublesex and mab-3 related transcription factor 1 were suppressed. • Genes involved in granulosa cell development were increased and sensitive to EE2 exposure. • Molecular initiating events that may be related to the intersex condition were identified. - Abstract: Intersex, or the presence of oocytes in the testes, has been documented in fish following exposure to wastewater effluent and estrogenic compounds. However, the molecular networks underlying the intersex condition are not completely known. To address this, we exposed male fathead minnows to a low, environmentally-relevant concentration of 17alpha-ethinylestradiol (EE2) (15 ng/L) and measured the transcriptome response in the testis after 96 h to identify early molecular initiating events that may proceed the intersex condition. The short-term exposure to EE2 did not affect gonadosomatic index and proportion of gametes within the testes. However, the production of 11-ketotestosterone and testosterone from the testis in vitro was decreased relative to controls. Expression profiling using a 8 × 60 K fathead minnow microarray identified 10 transcripts that were differentially expressed in the testes, the most dramatic change being that of coagulation factor XIII A chain (20-fold increase). Transcripts that included guanine nucleotide binding protein (Beta Polypeptide 2), peroxisome proliferator-activated receptor delta, and WNK lysine deficient protein kinase 1a, were down-regulated by EE2. Subnetwork enrichment analysis revealed that EE2 suppressed transcriptional networks associated with steroid metabolism, hormone biosynthesis, and sperm mobility. Most interesting was that gene networks associated with doublesex and mab-3 related transcription factor 1 (dmrt1) were suppressed in the adult

Molecular initiating events of the intersex phenotype: Low-dose exposure to 17α-ethinylestradiol rapidly regulates molecular networks associated with gonad differentiation in the adult fathead minnow testis

Energy Technology Data Exchange (ETDEWEB)

Feswick, April; Loughery, Jennifer R.; Isaacs, Meghan A.; Munkittrick, Kelly R.; Martyniuk, Christopher J., E-mail: cmartyni@yahoo.ca

2016-12-15

Highlights: • Male fathead minnow were exposed to 17alpha ethinylestradiol (EE2). • Both 11-ketotestosterone and testosterone production was decreased relative to controls. • A gene network associated with doublesex and mab-3 related transcription factor 1 were suppressed. • Genes involved in granulosa cell development were increased and sensitive to EE2 exposure. • Molecular initiating events that may be related to the intersex condition were identified. - Abstract: Intersex, or the presence of oocytes in the testes, has been documented in fish following exposure to wastewater effluent and estrogenic compounds. However, the molecular networks underlying the intersex condition are not completely known. To address this, we exposed male fathead minnows to a low, environmentally-relevant concentration of 17alpha-ethinylestradiol (EE2) (15 ng/L) and measured the transcriptome response in the testis after 96 h to identify early molecular initiating events that may proceed the intersex condition. The short-term exposure to EE2 did not affect gonadosomatic index and proportion of gametes within the testes. However, the production of 11-ketotestosterone and testosterone from the testis in vitro was decreased relative to controls. Expression profiling using a 8 × 60 K fathead minnow microarray identified 10 transcripts that were differentially expressed in the testes, the most dramatic change being that of coagulation factor XIII A chain (20-fold increase). Transcripts that included guanine nucleotide binding protein (Beta Polypeptide 2), peroxisome proliferator-activated receptor delta, and WNK lysine deficient protein kinase 1a, were down-regulated by EE2. Subnetwork enrichment analysis revealed that EE2 suppressed transcriptional networks associated with steroid metabolism, hormone biosynthesis, and sperm mobility. Most interesting was that gene networks associated with doublesex and mab-3 related transcription factor 1 (dmrt1) were suppressed in the adult

Microarray Analysis of the Molecular Mechanism Involved in Parkinson’s Disease

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Cheng Tan

2018-01-01

Full Text Available Purpose. This study aimed to investigate the underlying molecular mechanisms of Parkinson’s disease (PD by bioinformatics. Methods. Using the microarray dataset GSE72267 from the Gene Expression Omnibus database, which included 40 blood samples from PD patients and 19 matched controls, differentially expressed genes (DEGs were identified after data preprocessing, followed by Gene Ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichment analyses. Protein-protein interaction (PPI network, microRNA- (miRNA- target regulatory network, and transcription factor- (TF- target regulatory networks were constructed. Results. Of 819 DEGs obtained, 359 were upregulated and 460 were downregulated. Two GO terms, “rRNA processing” and “cytoplasm,” and two KEGG pathways, “metabolic pathways” and “TNF signaling pathway,” played roles in PD development. Intercellular adhesion molecule 1 (ICAM1 was the hub node in the PPI network; hsa-miR-7-5p, hsa-miR-433-3p, and hsa-miR-133b participated in PD pathogenesis. Six TFs, including zinc finger and BTB domain-containing 7A, ovo-like transcriptional repressor 1, GATA-binding protein 3, transcription factor dp-1, SMAD family member 1, and quiescin sulfhydryl oxidase 1, were related to PD. Conclusions. “rRNA processing,” “cytoplasm,” “metabolic pathways,” and “TNF signaling pathway” were key pathways involved in PD. ICAM1, hsa-miR-7-5p, hsa-miR-433-3p, hsa-miR-133b, and the abovementioned six TFs might play important roles in PD development.

Early brain response to low-dose radiation exposure involves molecular networks and pathways associated with cognitive functions, advanced aging and Alzheimer's disease.

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Lowe, Xiu R; Bhattacharya, Sanchita; Marchetti, Francesco; Wyrobek, Andrew J

2009-01-01

Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy and environmental nuclear contamination as well as for Earth-orbit and space missions. Analyses of transcriptome profiles of mouse brain tissue after whole-body irradiation showed that low-dose exposures (10 cGy) induced genes not affected by high-dose radiation (2 Gy) and that low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues and pathways that were specific for brain tissue. Low-dose genes clustered into a saturated network (P < 10(-53)) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified nine neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose irradiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down-regulated in normal human aging and Alzheimer's disease.

Early Brain Response to Low-Dose Radiation Exposure Involves Molecular Networks and Pathways Associated with Cognitive Functions, Advanced Aging and Alzheimer's Disease

International Nuclear Information System (INIS)

Lowe, Xiu R.; Bhattacharya, Sanchita; Marchetti, Francesco; Wyrobek, Andrew J.

2008-01-01

Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy, environmental nuclear contamination, as well as earth orbit and space missions. Analyses of transcriptome profiles of murine brain tissue after whole-body radiation showed that low-dose exposures (10 cGy) induced genes not affected by high dose (2 Gy), and low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues, and pathways that were brain tissue specific. Low-dose genes clustered into a saturated network (p -53 ) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified 9 neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose radiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down regulated in normal human aging and Alzheimer's disease

DyNet: visualization and analysis of dynamic molecular interaction networks.

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Goenawan, Ivan H; Bryan, Kenneth; Lynn, David J

2016-09-01

: The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction networks are physically rewired in response to different stimuli and in disease. Dynamic interaction data presents a special challenge in network biology. Here, we present DyNet, a Cytoscape application that provides a range of functionalities for the visualization, real-time synchronization and analysis of large multi-state dynamic molecular interaction networks enabling users to quickly identify and analyze the most 'rewired' nodes across many network states. DyNet is available at the Cytoscape (3.2+) App Store (http://apps.cytoscape.org/apps/dynet). david.lynn@sahmri.com Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Faciobrachial dystonic seizures result from fronto-temporo-basalganglial network involvement.

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Iyer, Rajesh Shankar; Ramakrishnan, T C R; Karunakaran; Shinto, Ajit; Kamaleshwaran, Koramadai Karuppuswamy

2017-01-01

•Faciobrachial dystonic seizures (FBDS) are caused by autoantibodies to leucine-rich glioma-inactivated1 proteins, a component of the voltage-gated potassium channel complex (VGKC-complex) and precede the clinical presentation of limbic encephalitis.•The exact pathophysiology of FBDS is not known and whether they are seizures or movement disorder is still debated.•We suggest the fronto-temporo-basal ganglia network involving the medial frontal and temporal regions along with the corpus striatum and substantia nigra being responsible for the clinical phenomenon of FBDS.•The varied clinical, electrical and imaging features of FBDS in our cases and in the literature are best explained by involvement of this network.•Entrainment from any part of this network will result in similar clinical expression of FBDS, whereas other electro-clinical associations and duration depends on the extent of involvement of the network.

VitisNet: "Omics" integration through grapevine molecular networks.

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Jérôme Grimplet

Full Text Available BACKGROUND: Genomic data release for the grapevine has increased exponentially in the last five years. The Vitis vinifera genome has been sequenced and Vitis EST, transcriptomic, proteomic, and metabolomic tools and data sets continue to be developed. The next critical challenge is to provide biological meaning to this tremendous amount of data by annotating genes and integrating them within their biological context. We have developed and validated a system of Grapevine Molecular Networks (VitisNet. METHODOLOGY/PRINCIPAL FINDINGS: The sequences from the Vitis vinifera (cv. Pinot Noir PN40024 genome sequencing project and ESTs from the Vitis genus have been paired and the 39,424 resulting unique sequences have been manually annotated. Among these, 13,145 genes have been assigned to 219 networks. The pathway sets include 88 "Metabolic", 15 "Genetic Information Processing", 12 "Environmental Information Processing", 3 "Cellular Processes", 21 "Transport", and 80 "Transcription Factors". The quantitative data is loaded onto molecular networks, allowing the simultaneous visualization of changes in the transcriptome, proteome, and metabolome for a given experiment. CONCLUSIONS/SIGNIFICANCE: VitisNet uses manually annotated networks in SBML or XML format, enabling the integration of large datasets, streamlining biological functional processing, and improving the understanding of dynamic processes in systems biology experiments. VitisNet is grounded in the Vitis vinifera genome (currently at 8x coverage and can be readily updated with subsequent updates of the genome or biochemical discoveries. The molecular network files can be dynamically searched by pathway name or individual genes, proteins, or metabolites through the MetNet Pathway database and web-portal at http://metnet3.vrac.iastate.edu/. All VitisNet files including the manual annotation of the grape genome encompassing pathway names, individual genes, their genome identifier, and chromosome

Scanning number and brightness yields absolute protein concentrations in live cells: a crucial parameter controlling functional bio-molecular interaction networks.

Science.gov (United States)

Papini, Christina; Royer, Catherine A

2018-02-01

Biological function results from properly timed bio-molecular interactions that transduce external or internal signals, resulting in any number of cellular fates, including triggering of cell-state transitions (division, differentiation, transformation, apoptosis), metabolic homeostasis and adjustment to changing physical or nutritional environments, amongst many more. These bio-molecular interactions can be modulated by chemical modifications of proteins, nucleic acids, lipids and other small molecules. They can result in bio-molecular transport from one cellular compartment to the other and often trigger specific enzyme activities involved in bio-molecular synthesis, modification or degradation. Clearly, a mechanistic understanding of any given high level biological function requires a quantitative characterization of the principal bio-molecular interactions involved and how these may change dynamically. Such information can be obtained using fluctation analysis, in particular scanning number and brightness, and used to build and test mechanistic models of the functional network to define which characteristics are the most important for its regulation.

Inferring causal molecular networks: empirical assessment through a community-based effort.

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Hill, Steven M; Heiser, Laura M; Cokelaer, Thomas; Unger, Michael; Nesser, Nicole K; Carlin, Daniel E; Zhang, Yang; Sokolov, Artem; Paull, Evan O; Wong, Chris K; Graim, Kiley; Bivol, Adrian; Wang, Haizhou; Zhu, Fan; Afsari, Bahman; Danilova, Ludmila V; Favorov, Alexander V; Lee, Wai Shing; Taylor, Dane; Hu, Chenyue W; Long, Byron L; Noren, David P; Bisberg, Alexander J; Mills, Gordon B; Gray, Joe W; Kellen, Michael; Norman, Thea; Friend, Stephen; Qutub, Amina A; Fertig, Elana J; Guan, Yuanfang; Song, Mingzhou; Stuart, Joshua M; Spellman, Paul T; Koeppl, Heinz; Stolovitzky, Gustavo; Saez-Rodriguez, Julio; Mukherjee, Sach

2016-04-01

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense.

Molecular codes in biological and chemical reaction networks.

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Dennis Görlich

Full Text Available Shannon's theory of communication has been very successfully applied for the analysis of biological information. However, the theory neglects semantic and pragmatic aspects and thus cannot directly be applied to distinguish between (bio- chemical systems able to process "meaningful" information from those that do not. Here, we present a formal method to assess a system's semantic capacity by analyzing a reaction network's capability to implement molecular codes. We analyzed models of chemical systems (martian atmosphere chemistry and various combustion chemistries, biochemical systems (gene expression, gene translation, and phosphorylation signaling cascades, an artificial chemistry, and random reaction networks. Our study suggests that different chemical systems possess different semantic capacities. No semantic capacity was found in the model of the martian atmosphere chemistry, the studied combustion chemistries, and highly connected random networks, i.e. with these chemistries molecular codes cannot be implemented. High semantic capacity was found in the studied biochemical systems and in random reaction networks where the number of second order reactions is twice the number of species. We conclude that our approach can be applied to evaluate the information processing capabilities of a chemical system and may thus be a useful tool to understand the origin and evolution of meaningful information, e.g. in the context of the origin of life.

A Systems Approach to Refine Disease Taxonomy by Integrating Phenotypic and Molecular Networks

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Xuezhong Zhou

2018-05-01

Full Text Available The International Classification of Diseases (ICD relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in ICD should be further investigated. Here, we propose a new classification of diseases (NCD by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles. With statistical validations from phenotype-genotype associations and interactome networks, we demonstrate that NCD improves disease specificity owing to its overlapping categories and polyhierarchical structure. Furthermore, NCD captures the molecular diversity of diseases and defines clearer boundaries in terms of both phenotypic similarity and molecular associations, establishing a rational strategy to reform disease taxonomy. Keywords: Disease taxonomy, Network medicine, Disease phenotypes, Molecular profiles, Precision medicine

Nonlinear microrheology and molecular imaging to map microscale deformations of entangled DNA networks

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Wu, Tsai-Chin; Anderson, Rae

We use active microrheology coupled to single-molecule fluorescence imaging to elucidate the microscale dynamics of entangled DNA. DNA naturally exists in a wide range of lengths and topologies, and is often confined in cell nucleui, forming highly concentrated and entangled biopolymer networks. Thus, DNA is the model polymer for understanding entangled polymer dynamics as well as the crowded environment of cells. These networks display complex viscoelastic properties that are not well understood, especially at the molecular-level and in response to nonlinear perturbations. Specifically, how microscopic stresses and strains propagate through entangled networks, and what molecular deformations lead to the network stress responses are unknown. To answer these important questions, we optically drive a microsphere through entangled DNA, perturbing the system far from equilibrium, while measuring the resistive force the DNA exerts on the bead during and after bead motion. We simultaneously image single fluorescent-labeled DNA molecules throughout the network to directly link the microscale stress response to molecular deformations. We characterize the deformation of the network from the molecular-level to the mesoscale, and map the stress propagation throughout the network. We further study the impact of DNA length (11 - 115 kbp) and topology (linear vs ring DNA) on deformation and propagation dynamics, exploring key nonlinear features such as tube dilation and power-law relaxation.

PPARγ population shift produces disease-related changes in molecular networks associated with metabolic syndrome.

Science.gov (United States)

Jurkowski, W; Roomp, K; Crespo, I; Schneider, J G; Del Sol, A

2011-08-11

Peroxisome proliferator-activated receptor gamma (PPARγ) is a key regulator of adipocyte differentiation and has an important role in metabolic syndrome. Phosphorylation of the receptor's ligand-binding domain at serine 273 has been shown to change the expression of a large number of genes implicated in obesity. The difference in gene expression seen when comparing wild-type phosphorylated with mutant non-phosphorylated PPARγ may have important consequences for the cellular molecular network, the state of which can be shifted from the healthy to a stable diseased state. We found that a group of differentially expressed genes are involved in bi-stable switches and form a core network, the state of which changes with disease progression. These findings support the idea that bi-stable switches may be a mechanism for locking the core gene network into a diseased state and for efficiently propagating perturbations to more distant regions of the network. A structural analysis of the PPARγ-RXRα dimer complex supports the hypothesis of a major structural change between the two states, and this may represent an important mechanism leading to the differential expression observed in the core network.

Early Brain Response to Low-Dose Radiation Exposure Involves Molecular Networks and Pathways Associated with Cognitive Functions, Advanced Aging and Alzheimer's Disease

Energy Technology Data Exchange (ETDEWEB)

Lowe, Xiu R; Bhattacharya, Sanchita; Marchetti, Francesco; Wyrobek, Andrew J.

2008-06-06

Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy, environmental nuclear contamination, as well as earth orbit and space missions. Analyses of transcriptome profiles of murine brain tissue after whole-body radiation showed that low-dose exposures (10 cGy) induced genes not affected by high dose (2 Gy), and low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues, and pathways that were brain tissue specific. Low-dose genes clustered into a saturated network (p < 10{sup -53}) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified 9 neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose radiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down regulated in normal human aging and Alzheimer's disease.

A neural network approach to the study of dynamics and structure of molecular systems

International Nuclear Information System (INIS)

Getino, C.; Sumpter, B.G.; Noid, D.W.

1994-01-01

Neural networks are used to study intramolecular energy flow in molecular systems (tetratomics to macromolecules), developing new techniques for efficient analysis of data obtained from molecular-dynamics and quantum mechanics calculations. Neural networks can map phase space points to intramolecular vibrational energies along a classical trajectory (example of complicated coordinate transformation), producing reasonably accurate values for any region of the multidimensional phase space of a tetratomic molecule. Neural network energy flow predictions are found to significantly enhance the molecular-dynamics method to longer time-scales and extensive averaging of trajectories for macromolecular systems. Pattern recognition abilities of neural networks can be used to discern phase space features. Neural networks can also expand model calculations by interpolation of costly quantum mechanical ab initio data, used to develop semiempirical potential energy functions

LARGE-SCALE TOPOLOGICAL PROPERTIES OF MOLECULAR NETWORKS.

Energy Technology Data Exchange (ETDEWEB)

MASLOV,S.SNEPPEN,K.

2003-11-17

Bio-molecular networks lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as gene duplications and single gene mutations. As a result individual connections in these networks are characterized by a large degree of randomness. One may wonder which connectivity patterns are indeed random, while which arose due to the network growth, evolution, and/or its fundamental design principles and limitations? Here we introduce a general method allowing one to construct a random null-model version of a given network while preserving the desired set of its low-level topological features, such as, e.g., the number of neighbors of individual nodes, the average level of modularity, preferential connections between particular groups of nodes, etc. Such a null-model network can then be used to detect and quantify the non-random topological patterns present in large networks. In particular, we measured correlations between degrees of interacting nodes in protein interaction and regulatory networks in yeast. It was found that in both these networks, links between highly connected proteins are systematically suppressed. This effect decreases the likelihood of cross-talk between different functional modules of the cell, and increases the overall robustness of a network by localizing effects of deleterious perturbations. It also teaches us about the overall computational architecture of such networks and points at the origin of large differences in the number of neighbors of individual nodes.

Long-term oil contamination alters the molecular ecological networks of soil microbial functional genes

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Yuting eLiang

2016-02-01

Full Text Available With knowledge on microbial composition and diversity, investigation of within-community interactions is a further step to elucidate microbial ecological functions, such as the biodegradation of hazardous contaminants. In this work, microbial functional molecular ecological networks were studied in both contaminated and uncontaminated soils to determine the possible influences of oil contamination on microbial interactions and potential functions. Soil samples were obtained from an oil-exploring site located in South China, and the microbial functional genes were analyzed with GeoChip, a high-throughput functional microarray. By building random networks based on null model, we demonstrated that overall network structures and properties were significantly different between contaminated and uncontaminated soils (P < 0.001. Network connectivity, module numbers, and modularity were all reduced with contamination. Moreover, the topological roles of the genes (module hub and connectors were altered with oil contamination. Subnetworks of genes involved in alkane and polycyclic aromatic hydrocarbon degradation were also constructed. Negative co-occurrence patterns prevailed among functional genes, thereby indicating probable competition relationships. The potential keystone genes, defined as either hubs or genes with highest connectivities in the network, were further identified. The network constructed in this study predicted the potential effects of anthropogenic contamination on microbial community co-occurrence interactions.

Evaluation of hydrogen bond networks in cellulose Iβ and II crystals using density functional theory and Car-Parrinello molecular dynamics.

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Hayakawa, Daichi; Nishiyama, Yoshiharu; Mazeau, Karim; Ueda, Kazuyoshi

2017-09-08

Crystal models of cellulose Iβ and II, which contain various hydrogen bonding (HB) networks, were analyzed using density functional theory and Car-Parrinello molecular dynamics (CPMD) simulations. From the CPMD trajectories, the power spectra of the velocity correlation functions of hydroxyl groups involved in hydrogen bonds were calculated. For the Iβ allomorph, HB network A, which is dominant according to the neutron diffraction data, was stable, and the power spectrum represented the essential features of the experimental IR spectra. In contrast, network B, which is a minor structure, was unstable because its hydroxymethyl groups reoriented during the CPMD simulation, yielding a different crystal structure to that determined by experiments. For the II allomorph, a HB network A is proposed based on diffraction data, whereas molecular modeling identifies an alternative network B. Our simulations showed that the interaction energies of the cellulose II (B) model are slightly more favorable than model II(A). However, the evaluation of the free energy should be waited for the accurate determination from the energy point of view. For the IR calculation, cellulose II (B) model reproduces the spectra better than model II (A). Copyright © 2017 Elsevier Ltd. All rights reserved.

A molecular quantum spin network controlled by a single qubit.

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Schlipf, Lukas; Oeckinghaus, Thomas; Xu, Kebiao; Dasari, Durga Bhaktavatsala Rao; Zappe, Andrea; de Oliveira, Felipe Fávaro; Kern, Bastian; Azarkh, Mykhailo; Drescher, Malte; Ternes, Markus; Kern, Klaus; Wrachtrup, Jörg; Finkler, Amit

2017-08-01

Scalable quantum technologies require an unprecedented combination of precision and complexity for designing stable structures of well-controllable quantum systems on the nanoscale. It is a challenging task to find a suitable elementary building block, of which a quantum network can be comprised in a scalable way. We present the working principle of such a basic unit, engineered using molecular chemistry, whose collective control and readout are executed using a nitrogen vacancy (NV) center in diamond. The basic unit we investigate is a synthetic polyproline with electron spins localized on attached molecular side groups separated by a few nanometers. We demonstrate the collective readout and coherent manipulation of very few (≤ 6) of these S = 1/2 electronic spin systems and access their direct dipolar coupling tensor. Our results show that it is feasible to use spin-labeled peptides as a resource for a molecular qubit-based network, while at the same time providing simple optical readout of single quantum states through NV magnetometry. This work lays the foundation for building arbitrary quantum networks using well-established chemistry methods, which has many applications ranging from mapping distances in single molecules to quantum information processing.

Mathematical inference and control of molecular networks from perturbation experiments

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Mohammed-Rasheed, Mohammed

One of the main challenges facing biologists and mathematicians in the post genomic era is to understand the behavior of molecular networks and harness this understanding into an educated intervention of the cell. The cell maintains its function via an elaborate network of interconnecting positive and negative feedback loops of genes, RNA and proteins that send different signals to a large number of pathways and molecules. These structures are referred to as genetic regulatory networks (GRNs) or molecular networks. GRNs can be viewed as dynamical systems with inherent properties and mechanisms, such as steady-state equilibriums and stability, that determine the behavior of the cell. The biological relevance of the mathematical concepts are important as they may predict the differentiation of a stem cell, the maintenance of a normal cell, the development of cancer and its aberrant behavior, and the design of drugs and response to therapy. Uncovering the underlying GRN structure from gene/protein expression data, e.g., microarrays or perturbation experiments, is called inference or reverse engineering of the molecular network. Because of the high cost and time consuming nature of biological experiments, the number of available measurements or experiments is very small compared to the number of molecules (genes, RNA and proteins). In addition, the observations are noisy, where the noise is due to the measurements imperfections as well as the inherent stochasticity of genetic expression levels. Intra-cellular activities and extra-cellular environmental attributes are also another source of variability. Thus, the inference of GRNs is, in general, an under-determined problem with a highly noisy set of observations. The ultimate goal of GRN inference and analysis is to be able to intervene within the network, in order to force it away from undesirable cellular states and into desirable ones. However, it remains a major challenge to design optimal intervention strategies

Integrative Network Analysis Unveils Convergent Molecular Pathways in Parkinson's Disease and Diabetes

OpenAIRE

Santiago, Jose A.; Potashkin, Judith A.

2013-01-01

Background 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. ...

Online social networks for crowdsourced multimedia-involved behavioral testing: An empirical study

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Jun-Ho eChoi

2016-01-01

Full Text Available Online social networks have emerged as effective crowdsourcing media to recruit participants in recent days. However, issues regarding how to effectively exploit them have not been adequately addressed yet. In this paper, we investigate the reliability and effectiveness of multimedia-involved behavioral testing via social network-based crowdsourcing, especially focused on Facebook as a medium to recruit participants. We conduct a crowdsourcing-based experiment for a music recommendation problem. It is shown that different advertisement methods yield different degrees of efficiency and there exist significant differences in behavioral patterns across different genders and different age groups. In addition, we perform a comparison of our experiment with other multimedia-involved crowdsourcing experiments built on Amazon Mechanical Turk (MTurk, which suggests that crowdsourcing-based experiments using social networks for recruitment can achieve comparable efficiency. Based on the analysis results, advantages and disadvantages of social network-based crowdsourcing and suggestions for successful experiments are also discussed. We conclude that social networks have the potential to support multimedia-involved behavioral tests to gather in-depth data even for long-term periods.

Online Social Networks for Crowdsourced Multimedia-Involved Behavioral Testing: An Empirical Study

Science.gov (United States)

Choi, Jun-Ho; Lee, Jong-Seok

2016-01-01

Online social networks have emerged as effective crowdsourcing media to recruit participants in recent days. However, issues regarding how to effectively exploit them have not been adequately addressed yet. In this paper, we investigate the reliability and effectiveness of multimedia-involved behavioral testing via social network-based crowdsourcing, especially focused on Facebook as a medium to recruit participants. We conduct a crowdsourcing-based experiment for a music recommendation problem. It is shown that different advertisement methods yield different degrees of efficiency and there exist significant differences in behavioral patterns across different genders and different age groups. In addition, we perform a comparison of our experiment with other multimedia-involved crowdsourcing experiments built on Amazon Mechanical Turk (MTurk), which suggests that crowdsourcing-based experiments using social networks for recruitment can achieve comparable efficiency. Based on the analysis results, advantages and disadvantages of social network-based crowdsourcing and suggestions for successful experiments are also discussed. We conclude that social networks have the potential to support multimedia-involved behavioral tests to gather in-depth data even for long-term periods. PMID:26793137

Online Social Networks for Crowdsourced Multimedia-Involved Behavioral Testing: An Empirical Study.

Science.gov (United States)

Choi, Jun-Ho; Lee, Jong-Seok

2015-01-01

Online social networks have emerged as effective crowdsourcing media to recruit participants in recent days. However, issues regarding how to effectively exploit them have not been adequately addressed yet. In this paper, we investigate the reliability and effectiveness of multimedia-involved behavioral testing via social network-based crowdsourcing, especially focused on Facebook as a medium to recruit participants. We conduct a crowdsourcing-based experiment for a music recommendation problem. It is shown that different advertisement methods yield different degrees of efficiency and there exist significant differences in behavioral patterns across different genders and different age groups. In addition, we perform a comparison of our experiment with other multimedia-involved crowdsourcing experiments built on Amazon Mechanical Turk (MTurk), which suggests that crowdsourcing-based experiments using social networks for recruitment can achieve comparable efficiency. Based on the analysis results, advantages and disadvantages of social network-based crowdsourcing and suggestions for successful experiments are also discussed. We conclude that social networks have the potential to support multimedia-involved behavioral tests to gather in-depth data even for long-term periods.

Switching dynamics in reaction networks induced by molecular discreteness

International Nuclear Information System (INIS)

Togashi, Yuichi; Kaneko, Kunihiko

2007-01-01

To study the fluctuations and dynamics in chemical reaction processes, stochastic differential equations based on the rate equation involving chemical concentrations are often adopted. When the number of molecules is very small, however, the discreteness in the number of molecules cannot be neglected since the number of molecules must be an integer. This discreteness can be important in biochemical reactions, where the total number of molecules is not significantly larger than the number of chemical species. To elucidate the effects of such discreteness, we study autocatalytic reaction systems comprising several chemical species through stochastic particle simulations. The generation of novel states is observed; it is caused by the extinction of some molecular species due to the discreteness in their number. We demonstrate that the reaction dynamics are switched by a single molecule, which leads to the reconstruction of the acting network structure. We also show the strong dependence of the chemical concentrations on the system size, which is caused by transitions to discreteness-induced novel states

Molecular Recognition Involving Anthraquinone Derivatives and Molecular Clips

Science.gov (United States)

Alaparthi, Madhubabu

In the past, we have demonstrated that 1,8-anthraquinone-18-crown-5 (1) and its heterocyclic derivatives act as luminescent hosts for a variety of cations of environmental and clinical concern. We report here a series of heteroatom-substituted macrocycles containing an anthraquinone moiety as a fluorescent signaling unit and a cyclic polyheteroether chain as the receptor. Sulfur, selenium, and tellurium derivatives of 1,8-anthraquinone-18-crown-5 (1) were synthesized by reacting sodium sulfide (Na2S), sodium selenide (Na2Se) and sodium telluride (Na2Te) with 1,8-bis(2-bromoethylethyleneoxy)anthracene - 9,10-dione in a 1:1 ratio (2,3, and 6). These sensors bind metal ions in a 1:1 ratio (7 and 8), and the optical properties of the new complexes were examined and the sulfur and selenium analogues show that selectivity for Pb(II) is markedly improved as compared to the oxygen analogue 1 which was competitive for Ca(II) ion. Selective reduction of 1 yields secondary alcohols where either one or both of the anthraquinone carbonyl groups has been reduced ( 15 and 9). A new mechanism for the fluorescence detection of metal cations in solution is introduced involving a unique keto-enol tautomerization. Reduction of 1 yields the doubly reduced secondary alcohol, 9. 9 acts as a chemodosimeter for Al(III) ion producing a strong blue emission due to the formation of the anthracene fluorophore, 10, via dehydration of the internal secondary alcohol in DMSO/aqueous solution. The enol form is not the most thermodynamically stable form under these conditions however, and slowly converts to the keto form 11.. Currently we are focusing on cucurbituril derivatives, also described as molecular clips due to their folded geometry used as molecular recognition hosts. We first investigated the synthesis and characterization of aromatic methoxy/catechol terminated cucurbituril units that act as hosts for small solvent molecules, such as CH2Cl2, CH3CN, DMF, and MeOH, through dual pi...H-C T

Quantum and semiclassical spin networks: from atomic and molecular physics to quantum computing and gravity

Science.gov (United States)

Aquilanti, Vincenzo; Bitencourt, Ana Carla P.; Ferreira, Cristiane da S.; Marzuoli, Annalisa; Ragni, Mirco

2008-11-01

The mathematical apparatus of quantum-mechanical angular momentum (re)coupling, developed originally to describe spectroscopic phenomena in atomic, molecular, optical and nuclear physics, is embedded in modern algebraic settings which emphasize the underlying combinatorial aspects. SU(2) recoupling theory, involving Wigner's 3nj symbols, as well as the related problems of their calculations, general properties, asymptotic limits for large entries, nowadays plays a prominent role also in quantum gravity and quantum computing applications. We refer to the ingredients of this theory—and of its extension to other Lie and quantum groups—by using the collective term of 'spin networks'. Recent progress is recorded about the already established connections with the mathematical theory of discrete orthogonal polynomials (the so-called Askey scheme), providing powerful tools based on asymptotic expansions, which correspond on the physical side to various levels of semi-classical limits. These results are useful not only in theoretical molecular physics but also in motivating algorithms for the computationally demanding problems of molecular dynamics and chemical reaction theory, where large angular momenta are typically involved. As for quantum chemistry, applications of these techniques include selection and classification of complete orthogonal basis sets in atomic and molecular problems, either in configuration space (Sturmian orbitals) or in momentum space. In this paper, we list and discuss some aspects of these developments—such as for instance the hyperquantization algorithm—as well as a few applications to quantum gravity and topology, thus providing evidence of a unifying background structure.

Multiscale Quantum Mechanics/Molecular Mechanics Simulations with Neural Networks.

Science.gov (United States)

Shen, Lin; Wu, Jingheng; Yang, Weitao

2016-10-11

Molecular dynamics simulation with multiscale quantum mechanics/molecular mechanics (QM/MM) methods is a very powerful tool for understanding the mechanism of chemical and biological processes in solution or enzymes. However, its computational cost can be too high for many biochemical systems because of the large number of ab initio QM calculations. Semiempirical QM/MM simulations have much higher efficiency. Its accuracy can be improved with a correction to reach the ab initio QM/MM level. The computational cost on the ab initio calculation for the correction determines the efficiency. In this paper we developed a neural network method for QM/MM calculation as an extension of the neural-network representation reported by Behler and Parrinello. With this approach, the potential energy of any configuration along the reaction path for a given QM/MM system can be predicted at the ab initio QM/MM level based on the semiempirical QM/MM simulations. We further applied this method to three reactions in water to calculate the free energy changes. The free-energy profile obtained from the semiempirical QM/MM simulation is corrected to the ab initio QM/MM level with the potential energies predicted with the constructed neural network. The results are in excellent accordance with the reference data that are obtained from the ab initio QM/MM molecular dynamics simulation or corrected with direct ab initio QM/MM potential energies. Compared with the correction using direct ab initio QM/MM potential energies, our method shows a speed-up of 1 or 2 orders of magnitude. It demonstrates that the neural network method combined with the semiempirical QM/MM calculation can be an efficient and reliable strategy for chemical reaction simulations.

Permanent Set of Cross-Linking Networks: Comparison of Theory with Molecular Dynamics Simulations

DEFF Research Database (Denmark)

Rottach, Dana R.; Curro, John G.; Budzien, Joanne

2006-01-01

The permanent set of cross-linking networks is studied by molecular dynamics. The uniaxial stress for a bead-spring polymer network is investigated as a function of strain and cross-link density history, where cross-links are introduced in unstrained and strained networks. The permanent set...

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

Directory of Open Access Journals (Sweden)

Jose A Santiago

Full Text Available 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

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

Science.gov (United States)

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

Proposal for Alzheimer’s diagnosis using molecular buffer and bus network

Directory of Open Access Journals (Sweden)

Mitatha S

2011-06-01

Full Text Available S Mitatha1, N Moongfangklang1, MA Jalil2, N Suwanpayak3, T Saktioto4, J Ali4, PP Yupapin31Hybrid Computing Research Laboratory, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand; 2Ibnu Sina Institute of Fundamental Science Studies, Nanotechnology Research Alliance, Universiti Teknologi Malaysia, Johor Bahru, Malaysia; 3Nanoscale Science and Engineering Research Alliance (N'SERA, Advanced Research Center for Photonics, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand; 4Institute of Advanced Photonics Science, Nanotechnology Research Alliance, Universiti Teknologi Malaysia, Johor Bahru, MalaysiaAbstract: A novel design of an optical trapping tool for tangle protein (tau tangles, ß-amyloid plaques and molecular motor storage and delivery using a PANDA ring resonator is proposed. The optical vortices can be generated and controlled to form the trapping tools in the same way as the optical tweezers. In theory, the trapping force is formed by the combination between the gradient field and scattering photons, and is reviewed. By using the intense optical vortices generated within the PANDA ring resonator, the required molecular volumes can be trapped and moved dynamically within the molecular buffer and bus network. The tangle protein and molecular motor can transport and connect to the required destinations, enabling availability for Alzheimer’s diagnosis.Keywords: Alzheimer’s disease, molecular diagnosis, optical trapping tool, molecular networks

Endogenous molecular network reveals two mechanisms of heterogeneity within gastric cancer

Science.gov (United States)

Li, Site; Zhu, Xiaomei; Liu, Bingya; Wang, Gaowei; Ao, Ping

2015-01-01

Intratumor heterogeneity is a common phenomenon and impedes cancer therapy and research. Gastric cancer (GC) cells have generally been classified into two heterogeneous cellular phenotypes, the gastric and intestinal types, yet the mechanisms of maintaining two phenotypes and controlling phenotypic transition are largely unknown. A qualitative systematic framework, the endogenous molecular network hypothesis, has recently been proposed to understand cancer genesis and progression. Here, a minimal network corresponding to such framework was found for GC and was quantified via a stochastic nonlinear dynamical system. We then further extended the framework to address the important question of intratumor heterogeneity quantitatively. The working network characterized main known features of normal gastric epithelial and GC cell phenotypes. Our results demonstrated that four positive feedback loops in the network are critical for GC cell phenotypes. Moreover, two mechanisms that contribute to GC cell heterogeneity were identified: particular positive feedback loops are responsible for the maintenance of intestinal and gastric phenotypes; GC cell progression routes that were revealed by the dynamical behaviors of individual key components are heterogeneous. In this work, we constructed an endogenous molecular network of GC that can be expanded in the future and would broaden the known mechanisms of intratumor heterogeneity. PMID:25962957

Molecular inspired models for prediction and control of directional FSO/RF wireless networks

Science.gov (United States)

Llorca, Jaime; Milner, Stuart D.; Davis, Christopher C.

2010-08-01

Directional wireless networks using FSO and RF transmissions provide wireless backbone support for mobile communications in dynamic environments. The heterogeneous and dynamic nature of such networks challenges their robustness and requires self-organization mechanisms to assure end-to-end broadband connectivity. We developed a framework based on the definition of a potential energy function to characterize robustness in communication networks and the study of first and second order variations of the potential energy to provide prediction and control strategies for network performance optimization. In this paper, we present non-convex molecular potentials such as the Morse Potential, used to describe the potential energy of bonds within molecules, for the characterization of communication links in the presence of physical constraints such as the power available at the network nodes. The inclusion of the Morse Potential translates into adaptive control strategies where forces on network nodes drive the release, retention or reconfiguration of communication links for network performance optimization. Simulation results show the effectiveness of our self-organized control mechanism, where the physical topology reorganizes to maximize the number of source to destination communicating pairs. Molecular Normal Mode Analysis (NMA) techniques for assessing network performance degradation in dynamic networks are also presented. Preliminary results show correlation between peaks in the eigenvalues of the Hessian of the network potential and network degradation.

Endogenous Molecular-Cellular Network Cancer Theory: A Systems Biology Approach.

Science.gov (United States)

Wang, Gaowei; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

2018-01-01

In light of ever apparent limitation of the current dominant cancer mutation theory, a quantitative hypothesis for cancer genesis and progression, endogenous molecular-cellular network hypothesis has been proposed from the systems biology perspective, now for more than 10 years. It was intended to include both the genetic and epigenetic causes to understand cancer. Its development enters the stage of meaningful interaction with experimental and clinical data and the limitation of the traditional cancer mutation theory becomes more evident. Under this endogenous network hypothesis, we established a core working network of hepatocellular carcinoma (HCC) according to the hypothesis and quantified the working network by a nonlinear dynamical system. We showed that the two stable states of the working network reproduce the main known features of normal liver and HCC at both the modular and molecular levels. Using endogenous network hypothesis and validated working network, we explored genetic mutation pattern in cancer and potential strategies to cure or relieve HCC from a totally new perspective. Patterns of genetic mutations have been traditionally analyzed by posteriori statistical association approaches in light of traditional cancer mutation theory. One may wonder the possibility of a priori determination of any mutation regularity. Here, we found that based on the endogenous network theory the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. Normal hepatocyte and cancerous hepatocyte stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable

"Intelligent" design of molecular materials: Understanding the concepts of design in supramolecular synthesis of network solids

Science.gov (United States)

Moulton, Brian D.

This work endeavors to delineate modern paradigms for crystal engineering, i.e. the design and supramolecular synthesis of functional molecular materials. Paradigms predicated on an understanding of the geometry of polygons and polyhedra are developed. The primary focus is on structural determination by single crystal X-ray crystallography, structural interpretation using a suite of graphical visualization and molecular modeling software, and on the importance of proper graphical representation in the presentation and explanation of crystal structures. A detailed analysis of a selected series of crystal structures is presented. The reduction of these molecular networks to schematic representations that illustrate their fundamental connectivity facilitates the understanding of otherwise complex supramolecular solids. Circuit symbols and Schlafli notation are used to describe the network topologies, which enables networks of different composition and metrics to be easily compared. This reveals that molecular orientations in the crystals and networks are commensurate with networks that can be derived from spherical close packed lattices. The development of a logical design strategy for a new class of materials based on our understanding of the chemical composition and topology of these networks is described. The synthesis and crystal structure of a series of new materials generated by exploitation of this design strategy is presented, in addition to a detailed analysis of the topology of these materials and their relationship to a 'parent' structure. In summary, this dissertation demonstrates that molecular polygons can self-assemble at their vertexes to produce molecular architectures and crystal structures that are consistent with long established geometric dogma. The design strategy represents a potentially broad ranging approach to the design of nanoporous structures from a wide range of chemical components that are based on molecular shape rather than chemical

Mechanosensitive molecular networks involved in transducing resistance exercise-signals into muscle protein accretion

Directory of Open Access Journals (Sweden)

Emil Rindom

2016-11-01

Full Text Available Loss of skeletal muscle myofibrillar protein with disease and/or inactivity can severely deteriorate muscle strength and function. Strategies to counteract wasting of muscle myofibrillar protein are therefore desirable and invite for considerations on the potential superiority of specific modes of resistance exercise and/or the adequacy of low load resistance exercise regimens as well as underlying mechanisms. In this regard, delineation of the potentially mechanosensitive molecular mechanisms underlying muscle protein synthesis (MPS, may contribute to understanding on how differentiated resistance exercise can transduce a mechanical signal into stimulation of muscle accretion. Recent findings suggest specific upstream exercise-induced mechano-sensitive myocellular signaling pathways to converge on mammalian target of rapamycin complex 1 (mTORC1, to influence MPS. This may e.g. implicate mechanical activation of signaling through a diacylglycerol kinase (DGKζ-phosphatidic acid (PA axis or implicate integrin deformation to signal through a Focal adhesion kinase (FAK-Tuberous Sclerosis Complex 2TSC2-Ras homolog enriched in brain (Rheb axis. Moreover, since initiation of translation is reliant on mRNA, it is also relevant to consider potentially mechanosensitive signaling pathways involved in muscle myofibrillar gene transcription and whether some of these pathways converge with those affecting mTORC1 activation for MPS. In this regard, recent findings suggest how mechanical stress may implicate integrin deformation and/or actin dynamics to signal through a Ras homolog gene family member A protein (RhoA-striated muscle activator of Rho signaling (STARS axis or how it may implicate deformation of Notch to affect Bone Morphogenetic Protein (BMP signaling through a small mother of decapentaplegic (Smad axis.

A neural network approach to the study of internal energy flow in molecular systems

International Nuclear Information System (INIS)

Sumpter, B.G.; Getino, C.; Noid, D.W.

1992-01-01

Neural networks are used to develop a new technique for efficient analysis of data obtained from molecular-dynamics calculations and is applied to the study of mode energy flow in molecular systems. The methodology is based on teaching an appropriate neural network the relationship between phase-space points along a classical trajectory and mode energies for stretch, bend, and torsion vibrations. Results are discussed for reactive and nonreactive classical trajectories of hydrogen peroxide (H 2 O 2 ) on a semiempirical potential-energy surface. The neural-network approach is shown to produce reasonably accurate values for the mode energies, with average errors between 1% and 12%, and is applicable to any region within the 24-dimensional phase space of H 2 O 2 . In addition, the generic knowledge learned by the neural network allows calculations to be made for other molecular systems. Results are discussed for a series of tetratomic molecules: H 2 X 2 , X=C, N, O, Si, S, or Se, and preliminary results are given for energy flow predictions in macromolecules

The mechanism of selective molecular capture in carbon nanotube networks.

Science.gov (United States)

Wan, Yu; Guan, Jun; Yang, Xudong; Zheng, Quanshui; Xu, Zhiping

2014-07-28

Recently, air pollution issues have drawn significant attention to the development of efficient air filters, and one of the most promising materials for this purpose is nanofibers. We explore here the mechanism of selective molecular capture of volatile organic compounds in carbon nanotube networks by performing atomistic simulations. The results are discussed with respect to the two key parameters that define the performance of nanofiltration, i.e. the capture efficiency and flow resistance, which demonstrate the advantages of carbon nanotube networks with high surface-to-volume ratio and atomistically smooth surfaces. We also reveal the important roles of interfacial adhesion and diffusion that govern selective gas transport through the network.

The Interaction between Personality, Social Network Position and Involvement in Innovation Process

NARCIS (Netherlands)

E. Dolgova (Evgenia); W. van Olffen (Woody); F.A.J. van den Bosch (Frans); H.W. Volberda (Henk)

2010-01-01

textabstractAbstract This dissertation proposal investigates how personality and individuals’ social network position affect individuals’ involvement into the innovation process. It posits that people would feel inclined to become involved into the different phases of the innovation process

Molecular transport network security using multi-wavelength optical spins.

Science.gov (United States)

Tunsiri, Surachai; Thammawongsa, Nopparat; Mitatha, Somsak; Yupapin, Preecha P

2016-01-01

Multi-wavelength generation system using an optical spin within the modified add-drop optical filter known as a PANDA ring resonator for molecular transport network security is proposed. By using the dark-bright soliton pair control, the optical capsules can be constructed and applied to securely transport the trapped molecules within the network. The advantage is that the dark and bright soliton pair (components) can securely propagate for long distance without electromagnetic interference. In operation, the optical intensity from PANDA ring resonator is fed into gold nano-antenna, where the surface plasmon oscillation between soliton pair and metallic waveguide is established.

Tailoring the mechanical properties by molecular integration of flexible and stiff polymer networks.

Science.gov (United States)

Wan, Haixiao; Shen, Jianxiang; Gao, Naishen; Liu, Jun; Gao, Yangyang; Zhang, Liqun

2018-03-28

Designing a multiple-network structure at the molecular level to tailor the mechanical properties of polymeric materials is of great scientific and technological importance. Through the coarse-grained molecular dynamics simulation, we successfully construct an interpenetrating polymer network (IPN) composed of a flexible polymer network and a stiff polymer network. First, we find that there is an optimal chain stiffness for a single network (SN) to achieve the best stress-strain behavior. Then we turn to study the mechanical behaviors of IPNs. The result shows that the stress-strain behaviors of the IPNs appreciably exceed the sum of that of the corresponding single flexible and stiff network, which highlights the advantage of the IPN structure. By systematically varying the stiffness of the stiff polymer network of the IPNs, optimal stiffness also exists to achieve the best performance. We attribute this to a much larger contribution of the non-bonded interaction energy. Last, the effect of the component concentration ratio is probed. With the increase of the concentration of the flexible network, the stress-strain behavior of the IPNs is gradually enhanced, while an optimized concentration (around 60% molar ration) of the stiff network occurs, which could result from the dominant role of the enthalpy rather than the entropy. In general, our work is expected to provide some guidelines to better tailor the mechanical properties of the IPNs made of a flexible network and a stiff network, by manipulating the stiffness of the stiff polymer network and the component concentration ratio.

Models and algorithms for biomolecules and molecular networks

CERN Document Server

DasGupta, Bhaskar

2016-01-01

By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms. * Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithms * Sampling techniques for estimating evolutionary rates and generating molecular structures * Accurate computation of probability landscape of stochastic networks, solving discrete chemical master equations * End-of-chapter exercises

Consideration of analogies between magnetic and quantum notices for molecular network

Directory of Open Access Journals (Sweden)

Piech Henryk

2018-01-01

Full Text Available Magnetic properties of spin glass materials [9,13] are close to quantum interpretation in their nature description [17]. Therefore, we can look for possible kinds of analogies in process of defining theoretic and practice conventions, rules and applications of the specific characteristics in elaboration quantum calculation strategies. We have not investigated possibilities to create directly quantum calculation units and practice calculation structures like qubits, registers, gates etc. [4,18], but dealing with spin and quantum definitions and descriptions we can try to involve these notices from different domains. Such a pragmatic approach only intuitively gives chances to create the transition theory and implement it even partially. Obviously, almost all of us have heard about quantum factorization, cryptography or teleportation but it is obtained as a result of exploration casually selected quantum properties and adapting them to mathematic problems. In our approach, we carefully investigate involutions among spin and quantum nature looking at possible implementation in molecular network.

On the stability of surface-confined nanoporous molecular networks

Energy Technology Data Exchange (ETDEWEB)

Ghijsens, Elke; Adisoejoso, Jinne, E-mail: Jinne.adisoejoso@chem.kuleuven.be, E-mail: tobe@chem.es.osaka-u.ac.jp, E-mail: Steven.DeFeyter@chem.kuleuven.be; Van Gorp, Hans; Destoop, Iris; Ivasenko, Oleksandr; Van der Auweraer, Mark; De Feyter, Steven, E-mail: Jinne.adisoejoso@chem.kuleuven.be, E-mail: tobe@chem.es.osaka-u.ac.jp, E-mail: Steven.DeFeyter@chem.kuleuven.be [Department of Chemistry, Division of Molecular Imaging and Photonics, KU Leuven—University of Leuven, Celestijnenlaan 200 F, B-3001 Leuven (Belgium); Noguchi, Aya; Tahara, Kazukuni; Tobe, Yoshito, E-mail: Jinne.adisoejoso@chem.kuleuven.be, E-mail: tobe@chem.es.osaka-u.ac.jp, E-mail: Steven.DeFeyter@chem.kuleuven.be [Graduate School of Engineering Science, Division of Frontier Materials Science, Osaka University, Toyonaka, Osaka 560-8531 (Japan)

2015-03-14

Self-assembly of molecular building blocks into two-dimensional nanoporous networks has been a topic of broad interest for many years. However, various factors govern the specific outcome of the self-assembly process, and understanding and controlling these are key to successful creation. In this work, the self-assembly of two alkylated dehydrobenzo[12]annulene building blocks was compared at the liquid-solid interface. It turned out that only a small chemical modification within the building blocks resulted in enhanced domain sizes and stability of the porous packing relative to the dense linear packing. Applying a thermodynamic model for phase transition revealed some key aspects for network formation.

Confinement properties of 2D porous molecular networks on metal surfaces

International Nuclear Information System (INIS)

Müller, Kathrin; Enache, Mihaela; Stöhr, Meike

2016-01-01

Quantum effects that arise from confinement of electronic states have been extensively studied for the surface states of noble metals. Utilizing small artificial structures for confinement allows tailoring of the surface properties and offers unique opportunities for applications. So far, examples of surface state confinement include thin films, artificial nanoscale structures, vacancy and adatom islands, self-assembled 1D chains, vicinal surfaces, quantum dots and quantum corrals. In this review we summarize recent achievements in changing the electronic structure of surfaces by adsorption of nanoporous networks whose design principles are based on the concepts of supramolecular chemistry. Already in 1993, it was shown that quantum corrals made from Fe atoms on a Cu(1 1 1) surface using single atom manipulation with a scanning tunnelling microscope confine the Shockley surface state. However, since the atom manipulation technique for the construction of corral structures is a relatively time consuming process, the fabrication of periodic two-dimensional (2D) corral structures is practically impossible. On the other side, by using molecular self-assembly extended 2D porous structures can be achieved in a parallel process, i.e. all pores are formed at the same time. The molecular building blocks are usually held together by non-covalent interactions like hydrogen bonding, metal coordination or dipolar coupling. Due to the reversibility of the bond formation defect-free and long-range ordered networks can be achieved. However, recently also examples of porous networks formed by covalent coupling on the surface have been reported. By the choice of the molecular building blocks, the dimensions of the network (pore size and pore to pore distance) can be controlled. In this way, the confinement properties of the individual pores can be tuned. In addition, the effect of the confined state on the hosting properties of the pores will be discussed in this review article

Identification and analysis of signaling networks potentially involved in breast carcinoma metastasis to the brain.

Directory of Open Access Journals (Sweden)

Feng Li

Full Text Available Brain is a common site of breast cancer metastasis associated with significant neurologic morbidity, decreased quality of life, and greatly shortened survival. However, the molecular and cellular mechanisms underpinning brain colonization by breast carcinoma cells are poorly understood. Here, we used 2D-DIGE (Difference in Gel Electrophoresis proteomic analysis followed by LC-tandem mass spectrometry to identify the proteins differentially expressed in brain-targeting breast carcinoma cells (MB231-Br compared with parental MDA-MB-231 cell line. Between the two cell lines, we identified 12 proteins consistently exhibiting greater than 2-fold (p<0.05 difference in expression, which were associated by the Ingenuity Pathway Analysis (IPA with two major signaling networks involving TNFα/TGFβ-, NFκB-, HSP-70-, TP53-, and IFNγ-associated pathways. Remarkably, highly related networks were revealed by the IPA analysis of a list of 19 brain-metastasis-associated proteins identified recently by the group of Dr. A. Sierra using MDA-MB-435-based experimental system (Martin et al., J Proteome Res 2008 7:908-20, or a 17-gene classifier associated with breast cancer brain relapse reported by the group of Dr. J. Massague based on a microarray analysis of clinically annotated breast tumors from 368 patients (Bos et al., Nature 2009 459: 1005-9. These findings, showing that different experimental systems and approaches (2D-DIGE proteomics used on brain targeting cell lines or gene expression analysis of patient samples with documented brain relapse yield highly related signaling networks, suggest strongly that these signaling networks could be essential for a successful colonization of the brain by metastatic breast carcinoma cells.

7. meeting of the Atomic and Molecular Data Centre Network, Oak Ridge National Laboratory, Oak Ridge, TN, 9-11 November 1987

International Nuclear Information System (INIS)

Smith, J.J.

1988-02-01

This is a brief summary report of the Seventh Atomic and Molecular Data Centre Network Meeting convened by the IAEA at the Oak Ridge National Laboratory, Oak Ridge, Tennessee, 9-11 November 1987. The goal of the Centre is to provide coordination of the international management of atomic and molecular data pertinent to controlled fusion research and technology. The meeting was attended by twelve representatives of centres from six member states. The meeting resulted in five conclusions: (i) the establishment of a single international atomic and molecular collision data base was stressed to be the short-term priority for the data centre network; (ii) the Specialists' Meeting on ''Atomic and Molecular Data for Plasma Edge Studies'' was reviewed, and the proposal for the formation of a coordinated research programme on the production and evaluation of atomic and molecular data for plasma edge studies as a means of generating the needed data for fusion research was endorsed; (iii) it was recommended that the recent report entitled ''Recommended Data on Atomic Collision Processes Involving Iron Ions'' be published as a special supplement to the Nuclear Fusion journal, 1987. This unit was asked to investigate the possibility to provide data covering recombination processes for iron ions which were not included in the recommended data base; (iv) the participants felt that a meeting covering the Atomic and Molecular and fusion data base was timely and important for maximizing the efficient usage of the Atomic and Molecular collision data base. The convening of a Specialists' Meeting on carbon and oxygen ion collision data was also discussed. Finally, (v) it was proposed that the Atomic and Molecular Data Unit should fully address all discrepancies within the recommended data base. Nine status and progress reports are summarized in the Appendices to the present summary report. Refs, 1 fig., tabs

Dissecting molecular stress networks: identifying nodes of divergence between life-history phenotypes.

Science.gov (United States)

Schwartz, Tonia S; Bronikowski, Anne M

2013-02-01

The complex molecular network that underlies physiological stress response is comprised of nodes (proteins, metabolites, mRNAs, etc.) whose connections span cells, tissues and organs. Variable nodes are points in the network upon which natural selection may act. Thus, identifying variable nodes will reveal how this molecular stress network may evolve among populations in different habitats and how it might impact life-history evolution. Here, we use physiological and genetic assays to test whether laboratory-born juveniles from natural populations of garter snakes (Thamnophis elegans), which have diverged in their life-history phenotypes, vary concomitantly at candidate nodes of the stress response network, (i) under unstressed conditions and (ii) in response to an induced stress. We found that two common measures of stress (plasma corticosterone and liver gene expression of heat shock proteins) increased under stress in both life-history phenotypes. In contrast, the phenotypes diverged at four nodes both under unstressed conditions and in response to stress: circulating levels of reactive oxygen species (superoxide, H(2)O(2)); liver gene expression of GPX1 and erythrocyte DNA damage. Additionally, allele frequencies for SOD2 diverge from neutral markers, suggesting diversifying selection on SOD2 alleles. This study supports the hypothesis that these life-history phenotypes have diverged at the molecular level in how they respond to stress, particularly in nodes regulating oxidative stress. Furthermore, the differences between the life-history phenotypes were more pronounced in females. We discuss the responses to stress in the context of the associated life-history phenotype and the evolutionary pressures thought to be responsible for divergence between the phenotypes. © 2012 Blackwell Publishing Ltd.

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

Science.gov (United States)

Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

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

LENUS (Irish Health Repository)

O'Dushlaine, C

2011-03-01

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

Spontaneous chiral symmetry breaking in early molecular networks

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Markovitch Omer

2010-05-01

Full Text Available Abstract Background An important facet of early biological evolution is the selection of chiral enantiomers for molecules such as amino acids and sugars. The origin of this symmetry breaking is a long-standing question in molecular evolution. Previous models addressing this question include particular kinetic properties such as autocatalysis or negative cross catalysis. Results We propose here a more general kinetic formalism for early enantioselection, based on our previously described Graded Autocatalysis Replication Domain (GARD model for prebiotic evolution in molecular assemblies. This model is adapted here to the case of chiral molecules by applying symmetry constraints to mutual molecular recognition within the assembly. The ensuing dynamics shows spontaneous chiral symmetry breaking, with transitions towards stationary compositional states (composomes enriched with one of the two enantiomers for some of the constituent molecule types. Furthermore, one or the other of the two antipodal compositional states of the assembly also shows time-dependent selection. Conclusion It follows that chiral selection may be an emergent consequence of early catalytic molecular networks rather than a prerequisite for the initiation of primeval life processes. Elaborations of this model could help explain the prevalent chiral homogeneity in present-day living cells. Reviewers This article was reviewed by Boris Rubinstein (nominated by Arcady Mushegian, Arcady Mushegian, Meir Lahav (nominated by Yitzhak Pilpel and Sergei Maslov.

Molecular networks of human muscle adaptation to exercise and age.

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Bethan E Phillips

2013-03-01

Full Text Available Physical activity and molecular ageing presumably interact to precipitate musculoskeletal decline in humans with age. Herein, we have delineated molecular networks for these two major components of sarcopenic risk using multiple independent clinical cohorts. We generated genome-wide transcript profiles from individuals (n = 44 who then undertook 20 weeks of supervised resistance-exercise training (RET. Expectedly, our subjects exhibited a marked range of hypertrophic responses (3% to +28%, and when applying Ingenuity Pathway Analysis (IPA up-stream analysis to ~580 genes that co-varied with gain in lean mass, we identified rapamycin (mTOR signaling associating with growth (P = 1.4 × 10(-30. Paradoxically, those displaying most hypertrophy exhibited an inhibited mTOR activation signature, including the striking down-regulation of 70 rRNAs. Differential analysis found networks mimicking developmental processes (activated all-trans-retinoic acid (ATRA, Z-score = 4.5; P = 6 × 10(-13 and inhibited aryl-hydrocarbon receptor signaling (AhR, Z-score = -2.3; P = 3 × 10(-7 with RET. Intriguingly, as ATRA and AhR gene-sets were also a feature of endurance exercise training (EET, they appear to represent "generic" physical activity responsive gene-networks. For age, we found that differential gene-expression methods do not produce consistent molecular differences between young versus old individuals. Instead, utilizing two independent cohorts (n = 45 and n = 52, with a continuum of subject ages (18-78 y, the first reproducible set of age-related transcripts in human muscle was identified. This analysis identified ~500 genes highly enriched in post-transcriptional processes (P = 1 × 10(-6 and with negligible links to the aforementioned generic exercise regulated gene-sets and some overlap with ribosomal genes. The RNA signatures from multiple compounds all targeting serotonin, DNA topoisomerase antagonism, and RXR activation were significantly related to

Architecture of transcriptional regulatory circuits is knitted over the topology of bio-molecular interaction networks

DEFF Research Database (Denmark)

Soberano de Oliveira, Ana Paula; Patil, Kiran Raosaheb; Nielsen, Jens

2008-01-01

is to use the topology of bio-molecular interaction networks in order to constrain the solution space. Such approaches systematically integrate the existing biological knowledge with the 'omics' data. Results: Here we introduce a hypothesis-driven method that integrates bio-molecular network topology......Background: Uncovering the operating principles underlying cellular processes by using 'omics' data is often a difficult task due to the high-dimensionality of the solution space that spans all interactions among the bio-molecules under consideration. A rational way to overcome this problem...... with transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated. We have combined transcriptome data with different biological networks in order to identify Reporter Gene Ontologies, Reporter Transcription...

Neisseria gonorrhoeae molecular typing for understanding sexual networks and antimicrobial resistance transmission: A systematic review.

Science.gov (United States)

Town, Katy; Bolt, Hikaru; Croxford, Sara; Cole, Michelle; Harris, Simon; Field, Nigel; Hughes, Gwenda

2018-06-01

Neisseria gonorrhoeae (NG) is a significant global public health concern due to rising diagnoses rates and antimicrobial resistance. Molecular combined with epidemiological data have been used to understand the distribution and spread of NG, as well as relationships between cases in sexual networks, but the public health value gained from these studies is unclear. We conducted a systematic review to examine how molecular epidemiological studies have informed understanding of sexual networks and NG transmission, and subsequent public health interventions. Five research databases were systematically searched up to 31st March 2017 for studies that used sequence-based DNA typing methods, including whole genome sequencing, and linked molecular data to patient-level epidemiological data. Data were extracted and summarised to identify common themes. Of the 49 studies included, 82% used NG Multi-antigen Sequence Typing. Gender and sexual orientation were commonly used to characterise sexual networks that were inferred using molecular clusters; clusters predominantly of one patient group often contained a small number of isolates from other patient groups. Suggested public health applications included using these data to target interventions at specific populations, confirm outbreaks, and inform partner management, but these were mainly untested. Combining molecular and epidemiological data has provided insight into sexual mixing patterns, and dissemination of NG, but few studies have applied these findings to design or evaluate public health interventions. Future studies should focus on the application of molecular epidemiology in public health practice to provide evidence for how to prevent and control NG. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integrative analysis for finding genes and networks involved in diabetes and other complex diseases

DEFF Research Database (Denmark)

Bergholdt, R.; Størling, Zenia, Marian; Hansen, Kasper Lage

2007-01-01

We have developed an integrative analysis method combining genetic interactions, identified using type 1 diabetes genome scan data, and a high-confidence human protein interaction network. Resulting networks were ranked by the significance of the enrichment of proteins from interacting regions. We...... identified a number of new protein network modules and novel candidate genes/proteins for type 1 diabetes. We propose this type of integrative analysis as a general method for the elucidation of genes and networks involved in diabetes and other complex diseases....

New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

Science.gov (United States)

Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

2012-01-21

Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction

Functional brain networks involved in decision-making under certain and uncertain conditions

Energy Technology Data Exchange (ETDEWEB)

Farrar, Danielle C.; Moss, Mark B.; Killiany, Ronald J. [Boston University School of Medicine, Department of Anatomy and Neurobiology, Boston, MA (United States); Mian, Asim Z. [Boston University School of Medicine, Department of Radiology, Boston, MA (United States); Budson, Andrew E. [VA Boston Healthcare System, Boston, MA (United States)

2018-01-15

The aim of this study was to describe imaging markers of decision-making under uncertain conditions in normal individuals, in order to provide baseline activity to compare to impaired decision-making in pathological states. In this cross-sectional study, 19 healthy subjects ages 18-35 completed a novel decision-making card-matching task using a Phillips T3 Scanner and a 32-channel head coil. Functional data were collected in six functional runs. In one condition of the task, the participant was certain of the rule to apply to match the cards; in the other condition, the participant was uncertain. We performed cluster-based comparison of the two conditions using FSL fMRI Expert Analysis Tool and network-based analysis using MATLAB. The uncertain > certain comparison yielded three clusters - a midline cluster that extended through the midbrain, the thalamus, bilateral prefrontal cortex, the striatum, and bilateral parietal/occipital clusters. The certain > uncertain comparison yielded bilateral clusters in the insula, parietal and temporal lobe, as well as a medial frontal cluster. A larger, more connected functional network was found in the uncertain condition. The involvement of the insula, parietal cortex, temporal cortex, ventromedial prefrontal cortex, and orbitofrontal cortex of the certain condition reinforces the notion that certainty is inherently rewarding. For the uncertain condition, the involvement of the prefrontal cortex, parietal cortex, striatum, thalamus, amygdala, and hippocampal involvement was expected, as these are areas involved in resolving uncertainty and rule updating. The involvement of occipital cortical involvement and midbrain involvement may be attributed to increased visual attention and increased motor control. (orig.)

Functional brain networks involved in decision-making under certain and uncertain conditions

International Nuclear Information System (INIS)

Farrar, Danielle C.; Moss, Mark B.; Killiany, Ronald J.; Mian, Asim Z.; Budson, Andrew E.

2018-01-01

The aim of this study was to describe imaging markers of decision-making under uncertain conditions in normal individuals, in order to provide baseline activity to compare to impaired decision-making in pathological states. In this cross-sectional study, 19 healthy subjects ages 18-35 completed a novel decision-making card-matching task using a Phillips T3 Scanner and a 32-channel head coil. Functional data were collected in six functional runs. In one condition of the task, the participant was certain of the rule to apply to match the cards; in the other condition, the participant was uncertain. We performed cluster-based comparison of the two conditions using FSL fMRI Expert Analysis Tool and network-based analysis using MATLAB. The uncertain > certain comparison yielded three clusters - a midline cluster that extended through the midbrain, the thalamus, bilateral prefrontal cortex, the striatum, and bilateral parietal/occipital clusters. The certain > uncertain comparison yielded bilateral clusters in the insula, parietal and temporal lobe, as well as a medial frontal cluster. A larger, more connected functional network was found in the uncertain condition. The involvement of the insula, parietal cortex, temporal cortex, ventromedial prefrontal cortex, and orbitofrontal cortex of the certain condition reinforces the notion that certainty is inherently rewarding. For the uncertain condition, the involvement of the prefrontal cortex, parietal cortex, striatum, thalamus, amygdala, and hippocampal involvement was expected, as these are areas involved in resolving uncertainty and rule updating. The involvement of occipital cortical involvement and midbrain involvement may be attributed to increased visual attention and increased motor control. (orig.)

Molecular System Dynamics for Self-Organization in Heterogeneous Wireless Networks

Directory of Open Access Journals (Sweden)

Milner StuartD

2010-01-01

Full Text Available We have been looking at the properties of physical configurations that occur in nature in order to characterize, predict, and control network robustness in dynamic communication networks. Our framework is based on the definition of a potential energy function to characterize robustness in communication networks and the study of first- and second-order variations of the potential energy to provide prediction and control strategies for network-performance optimization. This paper describes novel investigations within this framework that draw from molecular system dynamics. The Morse potential, which governs the energy stored in bonds within molecules, is considered for the characterization of the potential energy of communication links in the presence of physical constraints such as the power available at the transmitters in a network. The inclusion of the Morse potential translates into improved control strategies, where forces on network nodes drive the release, retention, or reconfiguration of communication links based on their role within the network architecture. The performance of the proposed approach is measured in terms of the number of source-to-destination connections that have an end-to-end communications path. Simulation results show the effectiveness of our control mechanism, where the physical topology reorganizes to maximize the number of source-to-destination communicating pairs. The algorithms developed are completely distributed, show constant time complexity and produce optimal solutions from local interactions, thus preserving the system's self-organizing capability.

Information theory and signal transduction systems: from molecular information processing to network inference.

Science.gov (United States)

Mc Mahon, Siobhan S; Sim, Aaron; Filippi, Sarah; Johnson, Robert; Liepe, Juliane; Smith, Dominic; Stumpf, Michael P H

2014-11-01

Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design. Copyright © 2014 Elsevier Ltd. All rights reserved.

Tough Self-Healing Elastomers by Molecular Enforced Integration of Covalent and Reversible Networks.

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Wu, Jinrong; Cai, Li-Heng; Weitz, David A

2017-10-01

Self-healing polymers crosslinked by solely reversible bonds are intrinsically weaker than common covalently crosslinked networks. Introducing covalent crosslinks into a reversible network would improve mechanical strength. It is challenging, however, to apply this concept to "dry" elastomers, largely because reversible crosslinks such as hydrogen bonds are often polar motifs, whereas covalent crosslinks are nonpolar motifs. These two types of bonds are intrinsically immiscible without cosolvents. Here, we design and fabricate a hybrid polymer network by crosslinking randomly branched polymers carrying motifs that can form both reversible hydrogen bonds and permanent covalent crosslinks. The randomly branched polymer links such two types of bonds and forces them to mix on the molecular level without cosolvents. This enables a hybrid "dry" elastomer that is very tough with fracture energy 13500 Jm -2 comparable to that of natural rubber. Moreover, the elastomer can self-heal at room temperature with a recovered tensile strength 4 MPa, which is 30% of its original value, yet comparable to the pristine strength of existing self-healing polymers. The concept of forcing covalent and reversible bonds to mix at molecular scale to create a homogenous network is quite general and should enable development of tough, self-healing polymers of practical usage. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Informatic parcellation of the network involved in the computation of subjective value

Science.gov (United States)

Rangel, Antonio

2014-01-01

Understanding how the brain computes value is a basic question in neuroscience. Although individual studies have driven this progress, meta-analyses provide an opportunity to test hypotheses that require large collections of data. We carry out a meta-analysis of a large set of functional magnetic resonance imaging studies of value computation to address several key questions. First, what is the full set of brain areas that reliably correlate with stimulus values when they need to be computed? Second, is this set of areas organized into dissociable functional networks? Third, is a distinct network of regions involved in the computation of stimulus values at decision and outcome? Finally, are different brain areas involved in the computation of stimulus values for different reward modalities? Our results demonstrate the centrality of ventromedial prefrontal cortex (VMPFC), ventral striatum and posterior cingulate cortex (PCC) in the computation of value across tasks, reward modalities and stages of the decision-making process. We also find evidence of distinct subnetworks of co-activation within VMPFC, one involving central VMPFC and dorsal PCC and another involving more anterior VMPFC, left angular gyrus and ventral PCC. Finally, we identify a posterior-to-anterior gradient of value representations corresponding to concrete-to-abstract rewards. PMID:23887811

Classifying the molecular functions of Rab GTPases in membrane trafficking using deep convolutional neural networks.

Science.gov (United States)

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2018-06-13

Deep learning has been increasingly used to solve a number of problems with state-of-the-art performance in a wide variety of fields. In biology, deep learning can be applied to reduce feature extraction time and achieve high levels of performance. In our present work, we apply deep learning via two-dimensional convolutional neural networks and position-specific scoring matrices to classify Rab protein molecules, which are main regulators in membrane trafficking for transferring proteins and other macromolecules throughout the cell. The functional loss of specific Rab molecular functions has been implicated in a variety of human diseases, e.g., choroideremia, intellectual disabilities, cancer. Therefore, creating a precise model for classifying Rabs is crucial in helping biologists understand the molecular functions of Rabs and design drug targets according to such specific human disease information. We constructed a robust deep neural network for classifying Rabs that achieved an accuracy of 99%, 99.5%, 96.3%, and 97.6% for each of four specific molecular functions. Our approach demonstrates superior performance to traditional artificial neural networks. Therefore, from our proposed study, we provide both an effective tool for classifying Rab proteins and a basis for further research that can improve the performance of biological modeling using deep neural networks. Copyright © 2018 Elsevier Inc. All rights reserved.

Hierarchical modeling of molecular energies using a deep neural network

Science.gov (United States)

Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

2018-06-01

We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

A network-based biomarker approach for molecular investigation and diagnosis of lung cancer

Directory of Open Access Journals (Sweden)

Chen Bor-Sen

2011-01-01

Full Text Available Abstract Background Lung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, based on the research dedicated to this field, there is no highly sensitive network-based method for carcinogenesis characterization and diagnosis from the systems perspective. Methods In this study, a systems biology approach integrating microarray gene expression profiles and protein-protein interaction information was proposed to develop a network-based biomarker for molecular investigation into the network mechanism of lung carcinogenesis and diagnosis of lung cancer. The network-based biomarker consists of two protein association networks constructed for cancer samples and non-cancer samples. Results Based on the network-based biomarker, a total of 40 significant proteins in lung carcinogenesis were identified with carcinogenesis relevance values (CRVs. In addition, the network-based biomarker, acting as the screening test, proved to be effective in diagnosing smokers with signs of lung cancer. Conclusions A network-based biomarker using constructed protein association networks is a useful tool to highlight the pathways and mechanisms of the lung carcinogenic process and, more importantly, provides potential therapeutic targets to combat cancer.

Towards a Better Understanding of the Molecular Mechanisms Involved in Sunlight-Induced Melanoma

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Williams Mandy

2005-01-01

Full Text Available Although much less prevalent than its nonmelanoma skin cancer counterparts, cutaneous malignant melanoma (CMM is the most lethal human skin cancer. Epidemiological and biological studies have established a strong link between lifetime exposure to ultraviolet (UV light, particularly sunburn in childhood, and the development of melanoma. However, the specific molecular targets of this environmental carcinogen are not known. Data obtained from genetic and molecular studies over the last few years have identified the INK4a/ARF locus as the “gatekeeper” melanoma suppressor, encoding two tumour suppressor proteins in human, p16 INK4a and p14 ARF . Recent developments in molecular biotechnology and research using laboratory animals have made a significant gene breakthrough identifying the components of the p16 INK4a /Rb pathway as the principal and rate-limiting targets of UV radiation actions in melanoma formation. This review summarizes the current knowledge of the molecular mechanisms involved in melanoma development and its relationship to sunlight UV radiation.

Molecular genetic analysis of activation-tagged transcription factors thought to be involved in photomorphogenesis

Energy Technology Data Exchange (ETDEWEB)

Neff, Michael M.

2011-06-23

This is a final report for Department of Energy Grant No. DE-FG02-08ER15927 entitled “Molecular Genetic Analysis of Activation-Tagged Transcription Factors Thought to be Involved in Photomorphogenesis”. Based on our preliminary photobiological and genetic analysis of the sob1-D mutant, we hypothesized that OBP3 is a transcription factor involved in both phytochrome and cryptochrome-mediated signal transduction. In addition, we hypothesized that OBP3 is involved in auxin signaling and root development. Based on our preliminary photobiological and genetic analysis of the sob2-D mutant, we also hypothesized that a related gene, LEP, is involved in hormone signaling and seedling development.

Cambodian Parental Involvement: The Role of Parental Beliefs, Social Networks, and Trust

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Eng, Sothy; Szmodis, Whitney; Mulsow, Miriam

2014-01-01

The role of social capital (parental beliefs, social networks, and trust) as a predictor of parental involvement in Cambodian children's education was examined, controlling for human capital (family socioeconomic status). Parents of elementary students (n = 273) were interviewed face to face in Cambodia. Teacher contact scored highest, followed by…

Predicting Genes Involved in Human Cancer Using Network Contextual Information

Directory of Open Access Journals (Sweden)

Rahmani Hossein

2012-03-01

Full Text Available Protein-Protein Interaction (PPI networks have been widely used for the task of predicting proteins involved in cancer. Previous research has shown that functional information about the protein for which a prediction is made, proximity to specific other proteins in the PPI network, as well as local network structure are informative features in this respect. In this work, we introduce two new types of input features, reflecting additional information: (1 Functional Context: the functions of proteins interacting with the target protein (rather than the protein itself; and (2 Structural Context: the relative position of the target protein with respect to specific other proteins selected according to a novel ANOVA (analysis of variance based measure. We also introduce a selection strategy to pinpoint the most informative features. Results show that the proposed feature types and feature selection strategy yield informative features. A standard machine learning method (Naive Bayes that uses the features proposed here outperforms the current state-of-the-art methods by more than 5% with respect to F-measure. In addition, manual inspection confirms the biological relevance of the top-ranked features.

A Systems Biology Approach to the Coordination of Defensive and Offensive Molecular Mechanisms in the Innate and Adaptive Host-Pathogen Interaction Networks.

Science.gov (United States)

Wu, Chia-Chou; Chen, Bor-Sen

2016-01-01

Infected zebrafish coordinates defensive and offensive molecular mechanisms in response to Candida albicans infections, and invasive C. albicans coordinates corresponding molecular mechanisms to interact with the host. However, knowledge of the ensuing infection-activated signaling networks in both host and pathogen and their interspecific crosstalk during the innate and adaptive phases of the infection processes remains incomplete. In the present study, dynamic network modeling, protein interaction databases, and dual transcriptome data from zebrafish and C. albicans during infection were used to infer infection-activated host-pathogen dynamic interaction networks. The consideration of host-pathogen dynamic interaction systems as innate and adaptive loops and subsequent comparisons of inferred innate and adaptive networks indicated previously unrecognized crosstalk between known pathways and suggested roles of immunological memory in the coordination of host defensive and offensive molecular mechanisms to achieve specific and powerful defense against pathogens. Moreover, pathogens enhance intraspecific crosstalk and abrogate host apoptosis to accommodate enhanced host defense mechanisms during the adaptive phase. Accordingly, links between physiological phenomena and changes in the coordination of defensive and offensive molecular mechanisms highlight the importance of host-pathogen molecular interaction networks, and consequent inferences of the host-pathogen relationship could be translated into biomedical applications.

Quality control in mutation analysis: the European Molecular Genetics Quality Network (EMQN).

Science.gov (United States)

Müller, C R

2001-08-01

The demand for clinical molecular genetics testing has steadily grown since its introduction in the 1980s. In order to reach and maintain the agreed quality standards of laboratory medicine, the same internal and external quality assurance (IQA/EQA) criteria have to be applied as for "conventional" clinical chemistry or pathology. In 1996 the European Molecular Genetics Quality Network (EMQN) was established in order to spread QA standards across Europe and to harmonise the existing national activities. EMQN is operated by a central co-ordinator and 17 national partners from 15 EU countries; since 1998 it is being funded by the EU commission for a 3-year period. EMQN promotes QA by two tools: by providing disease-specific best practice meetings (BPM) and EQA schemes. A typical BPM is focussed on one disease or group of related disorders. International experts report on the latest news of gene characterisation and function and the state-of-the-art techniques for mutation detection. Disease-specific EQA schemes are provided by experts in the field. DNA samples are sent out together with mock clinical referrals and a diagnostic question is asked. Written reports must be returned which are marked for genotyping and interpretation. So far, three BPMs have been held and six EQA schemes are in operation at various stages. Although mutation types and diagnostic techniques varied considerably between schemes, the overall technical performance showed a high diagnostic standard. Nevertheless, serious genotyping errors have been occurred in some schemes which underline the necessity of quality assurance efforts. The European Molecular Genetics Quality Network provides a necessary platform for the internal and external quality assurance of molecular genetic testing.

Rapid molecular evolution across amniotes of the IIS/TOR network.

Science.gov (United States)

McGaugh, Suzanne E; Bronikowski, Anne M; Kuo, Chih-Horng; Reding, Dawn M; Addis, Elizabeth A; Flagel, Lex E; Janzen, Fredric J; Schwartz, Tonia S

2015-06-02

The insulin/insulin-like signaling and target of rapamycin (IIS/TOR) network regulates lifespan and reproduction, as well as metabolic diseases, cancer, and aging. Despite its vital role in health, comparative analyses of IIS/TOR have been limited to invertebrates and mammals. We conducted an extensive evolutionary analysis of the IIS/TOR network across 66 amniotes with 18 newly generated transcriptomes from nonavian reptiles and additional available genomes/transcriptomes. We uncovered rapid and extensive molecular evolution between reptiles (including birds) and mammals: (i) the IIS/TOR network, including the critical nodes insulin receptor substrate (IRS) and phosphatidylinositol 3-kinase (PI3K), exhibit divergent evolutionary rates between reptiles and mammals; (ii) compared with a proxy for the rest of the genome, genes of the IIS/TOR extracellular network exhibit exceptionally fast evolutionary rates; and (iii) signatures of positive selection and coevolution of the extracellular network suggest reptile- and mammal-specific interactions between members of the network. In reptiles, positively selected sites cluster on the binding surfaces of insulin-like growth factor 1 (IGF1), IGF1 receptor (IGF1R), and insulin receptor (INSR); whereas in mammals, positively selected sites clustered on the IGF2 binding surface, suggesting that these hormone-receptor binding affinities are targets of positive selection. Further, contrary to reports that IGF2R binds IGF2 only in marsupial and placental mammals, we found positively selected sites clustered on the hormone binding surface of reptile IGF2R that suggest that IGF2R binds to IGF hormones in diverse taxa and may have evolved in reptiles. These data suggest that key IIS/TOR paralogs have sub- or neofunctionalized between mammals and reptiles and that this network may underlie fundamental life history and physiological differences between these amniote sister clades.

Technical aspects of atomic and molecular data processing and exchange. 19. meeting of the A+M Data Centres and ALADDIN Network. Summary report of an IAEA technical meeting

International Nuclear Information System (INIS)

Humbert, D.

2008-05-01

The proceedings of the IAEA Technical Meeting on Technical Aspects of Atomic and Molecular Data Processing and Exchange (19th Meeting of A+M Data Centres and ALADDIN Network), held on 3-5 October, 2007 in Vienna, Austria, are briefly described. Conclusions and recommendations are presented concerning various proposed projects and their priorities involving A+M data compilation and evaluation and technical aspects of data processing, exchange, and distribution. (author)

Neuron-Like Networks Between Ribosomal Proteins Within the Ribosome

Science.gov (United States)

Poirot, Olivier; Timsit, Youri

2016-05-01

From brain to the World Wide Web, information-processing networks share common scale invariant properties. Here, we reveal the existence of neural-like networks at a molecular scale within the ribosome. We show that with their extensions, ribosomal proteins form complex assortative interaction networks through which they communicate through tiny interfaces. The analysis of the crystal structures of 50S eubacterial particles reveals that most of these interfaces involve key phylogenetically conserved residues. The systematic observation of interactions between basic and aromatic amino acids at the interfaces and along the extension provides new structural insights that may contribute to decipher the molecular mechanisms of signal transmission within or between the ribosomal proteins. Similar to neurons interacting through “molecular synapses”, ribosomal proteins form a network that suggest an analogy with a simple molecular brain in which the “sensory-proteins” innervate the functional ribosomal sites, while the “inter-proteins” interconnect them into circuits suitable to process the information flow that circulates during protein synthesis. It is likely that these circuits have evolved to coordinate both the complex macromolecular motions and the binding of the multiple factors during translation. This opens new perspectives on nanoscale information transfer and processing.

Molecular Correlates of Cortical Network Modulation by Long-Term Sensory Experience in the Adult Rat Barrel Cortex

Science.gov (United States)

Vallès, Astrid; Granic, Ivica; De Weerd, Peter; Martens, Gerard J. M.

2014-01-01

Modulation of cortical network connectivity is crucial for an adaptive response to experience. In the rat barrel cortex, long-term sensory stimulation induces cortical network modifications and neuronal response changes of which the molecular basis is unknown. Here, we show that long-term somatosensory stimulation by enriched environment…

Gene Prioritization by Integrated Analysis of Protein Structural and Network Topological Properties for the Protein-Protein Interaction Network of Neurological Disorders

Directory of Open Access Journals (Sweden)

Yashna Paul

2016-01-01

Full Text Available Neurological disorders are known to show similar phenotypic manifestations like anxiety, depression, and cognitive impairment. There is a need to identify shared genetic markers and molecular pathways in these diseases, which lead to such comorbid conditions. Our study aims to prioritize novel genetic markers that might increase the susceptibility of patients affected with one neurological disorder to other diseases with similar manifestations. Identification of pathways involving common candidate markers will help in the development of improved diagnosis and treatments strategies for patients affected with neurological disorders. This systems biology study for the first time integratively uses 3D-structural protein interface descriptors and network topological properties that characterize proteins in a neurological protein interaction network, to aid the identification of genes that are previously not known to be shared between these diseases. Results of protein prioritization by machine learning have identified known as well as new genetic markers which might have direct or indirect involvement in several neurological disorders. Important gene hubs have also been identified that provide an evidence for shared molecular pathways in the neurological disease network.

Students' Involvement in Social Networking and Attitudes towards Its Integration into Teaching

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Umoh, Ukeme Ekpedeme; Etuk, Etuk Nssien

2016-01-01

The study examined Students' Involvement in Social Networking and attitudes towards its Integration into Teaching. The study was carried out in the University of Uyo, Akwa Ibom State, Nigeria. The population of the study consisted of 17,618 undergraduate students enrolled into full time degree programmes in the University of Uyo for 2014/2015…

Computational analyses of synergism in small molecular network motifs.

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Yili Zhang

2014-03-01

Full Text Available Cellular functions and responses to stimuli are controlled by complex regulatory networks that comprise a large diversity of molecular components and their interactions. However, achieving an intuitive understanding of the dynamical properties and responses to stimuli of these networks is hampered by their large scale and complexity. To address this issue, analyses of regulatory networks often focus on reduced models that depict distinct, reoccurring connectivity patterns referred to as motifs. Previous modeling studies have begun to characterize the dynamics of small motifs, and to describe ways in which variations in parameters affect their responses to stimuli. The present study investigates how variations in pairs of parameters affect responses in a series of ten common network motifs, identifying concurrent variations that act synergistically (or antagonistically to alter the responses of the motifs to stimuli. Synergism (or antagonism was quantified using degrees of nonlinear blending and additive synergism. Simulations identified concurrent variations that maximized synergism, and examined the ways in which it was affected by stimulus protocols and the architecture of a motif. Only a subset of architectures exhibited synergism following paired changes in parameters. The approach was then applied to a model describing interlocked feedback loops governing the synthesis of the CREB1 and CREB2 transcription factors. The effects of motifs on synergism for this biologically realistic model were consistent with those for the abstract models of single motifs. These results have implications for the rational design of combination drug therapies with the potential for synergistic interactions.

Analysis of the enzyme network involved in cattle milk production using graph theory.

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Ghorbani, Sholeh; Tahmoorespur, Mojtaba; Masoudi Nejad, Ali; Nasiri, Mohammad; Asgari, Yazdan

2015-06-01

Understanding cattle metabolism and its relationship with milk products is important in bovine breeding. A systemic view could lead to consequences that will result in a better understanding of existing concepts. Topological indices and quantitative characterizations mostly result from the application of graph theory on biological data. In the present work, the enzyme network involved in cattle milk production was reconstructed and analyzed based on available bovine genome information using several public datasets (NCBI, Uniprot, KEGG, and Brenda). The reconstructed network consisted of 3605 reactions named by KEGG compound numbers and 646 enzymes that catalyzed the corresponding reactions. The characteristics of the directed and undirected network were analyzed using Graph Theory. The mean path length was calculated to be4.39 and 5.41 for directed and undirected networks, respectively. The top 11 hub enzymes whose abnormality could harm bovine health and reduce milk production were determined. Therefore, the aim of constructing the enzyme centric network was twofold; first to find out whether such network followed the same properties of other biological networks, and second, to find the key enzymes. The results of the present study can improve our understanding of milk production in cattle. Also, analysis of the enzyme network can help improve the modeling and simulation of biological systems and help design desired phenotypes to increase milk production quality or quantity.

Applied molecular simulations over FER-, TON- and AEL-type zeolites

NARCIS (Netherlands)

Domokos, L.; Lefferts, Leonardus; Seshan, Kulathuiyer; Lercher, J.A.

2001-01-01

Interaction and transport of representative (un)saturated hydrocarbon molecules involved in the proposed reaction network of n-butene isomerization in zeolites FER, TON, and AEL have been studied by classic molecular modeling calculations. Docking of the guest molecules into the zeolite frameworks

Knots Untie: Molecular Determinants Involved in Knot Formation Induced by Pseudomonas savastanoi in Woody Hosts

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Eloy Caballo-Ponce

2017-06-01

Full Text Available The study of the molecular basis of tree diseases is lately receiving a renewed attention, especially with the emerging perception that pathogens require specific pathogenicity and virulence factors to successfully colonize woody hosts. Pathosystems involving woody plants are notoriously difficult to study, although the use of model bacterial strains together with genetically homogeneous micropropagated plant material is providing a significant impetus to our understanding of the molecular determinants leading to disease. The gammaproteobacterium Pseudomonas savastanoi belongs to the intensively studied Pseudomonas syringae complex, and includes three pathogenic lineages causing tumorous overgrowths (knots in diverse economically relevant trees and shrubs. As it occurs with many other bacteria, pathogenicity of P. savastanoi is dependent on a type III secretion system, which is accompanied by a core set of at least 20 effector genes shared among strains isolated from olive, oleander, and ash. The induction of knots of wild-type size requires that the pathogen maintains adequate levels of diverse metabolites, including the phytohormones indole-3-acetic acid and cytokinins, as well as cyclic-di-GMP, some of which can also regulate the expression of other pathogenicity and virulence genes and participate in bacterial competitiveness. In a remarkable example of social networking, quorum sensing molecules allow for the communication among P. savastanoi and other members of the knot microbiome, while at the same time are essential for tumor formation. Additionally, a distinguishing feature of bacteria from the P. syringae complex isolated from woody organs is the possession of a 15 kb genomic island (WHOP carrying four operons and three other genes involved in degradation of phenolic compounds. Two of these operons mediate the catabolism of anthranilate and catechol and, together with another operon, are required for the induction of full-size tumors

An expanding universe of circadian networks in higher plants.

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Pruneda-Paz, Jose L; Kay, Steve A

2010-05-01

Extensive circadian clock networks regulate almost every biological process in plants. Clock-controlled physiological responses are coupled with daily oscillations in environmental conditions resulting in enhanced fitness and growth vigor. Identification of core clock components and their associated molecular interactions has established the basic network architecture of plant clocks, which consists of multiple interlocked feedback loops. A hierarchical structure of transcriptional feedback overlaid with regulated protein turnover sets the pace of the clock and ultimately drives all clock-controlled processes. Although originally described as linear entities, increasing evidence suggests that many signaling pathways can act as both inputs and outputs within the overall network. Future studies will determine the molecular mechanisms involved in these complex regulatory loops. 2010 Elsevier Ltd. All rights reserved.

Loss surface of XOR artificial neural networks

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Mehta, Dhagash; Zhao, Xiaojun; Bernal, Edgar A.; Wales, David J.

2018-05-01

Training an artificial neural network involves an optimization process over the landscape defined by the cost (loss) as a function of the network parameters. We explore these landscapes using optimization tools developed for potential energy landscapes in molecular science. The number of local minima and transition states (saddle points of index one), as well as the ratio of transition states to minima, grow rapidly with the number of nodes in the network. There is also a strong dependence on the regularization parameter, with the landscape becoming more convex (fewer minima) as the regularization term increases. We demonstrate that in our formulation, stationary points for networks with Nh hidden nodes, including the minimal network required to fit the XOR data, are also stationary points for networks with Nh+1 hidden nodes when all the weights involving the additional node are zero. Hence, smaller networks trained on XOR data are embedded in the landscapes of larger networks. Our results clarify certain aspects of the classification and sensitivity (to perturbations in the input data) of minima and saddle points for this system, and may provide insight into dropout and network compression.

PDMS Network Structure-Property Relationships: Influence of Molecular Architecture on Mechanical and Wetting Properties

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Melillo, Matthew Joseph

Poly(dimethylsiloxane) (PDMS) is one of the most common elastomers, with applications ranging from sealants and marine-antifouling coatings to medical devices and absorbents for water treatment. Fundamental understanding of how liquids spread on the surface of and absorb into and leach out of PDMS networks is of critical importance for the design and use in another application - microfluidic devices. The growing use of PDMS in microfluidic devices raises the concern that some researchers may use this material without fully understanding all of its advantages, drawbacks, and intricacies. The primary goal of this Ph.D. dissertation is to elucidate PDMS network molecular structure to macroscopic property relationships and to demonstrate how molecular architecture can alter dynamic mechanical and wetting characteristics. We prepare PDMS materials by using vinyl/ tetrakis(dimethylsiloxy)silane (TDSS) and silanol/ tetraethylorthosilicate (TEOS) combinations of PDMS end-groups and crosslinkers as two model systems. Under constant curing conditions, we systematically study the effects of polymer molecular weight, loading of crosslinker, and end-group chemical functionality on the extent of gelation and the dynamic mechanical and water wetting properties of end-linked PDMS networks. The extent of the gelation reaction is determined using the Soxhlet extraction to quantify the amount of material that did and did not participate in the crosslinking reactions, termed the gel and sol fractions, respectively. We use the Miller-Macosko model in conjunction with the gel fraction and precise chemical composition (i.e., stoichiometric ratio and molecular weight) to determine the fractions of elastic and pendant material, the molecular weight between chemical crosslinks, and the average effective functionality of the crosslinker molecule. Based on dynamic mechanical testing, we find that the maximum storage moduli are achieved at optimal stoichiometric conditions in the vinyl

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses.

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Luo, Jie; Xu, Pei; Cao, Peijian; Wan, Hongjian; Lv, Xiaonan; Xu, Shengchun; Wang, Gangjun; Cook, Melloni N; Jones, Byron C; Lu, Lu; Wang, Xusheng

2018-01-01

Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses

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Jie Luo

2018-04-01

Full Text Available Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1, down-regulation in NOE but rescue in RSE (pattern 2, up-regulation in both restraint stress followed by a saline injection (RSS and NOE, and further amplification in RSE (pattern 3, and up-regulation in RSS but reduction in both NOE and RSE (pattern 4. We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome.

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Rzhetsky, A; Gomez, S M

2001-10-01

Current growth in the field of genomics has provided a number of exciting approaches to the modeling of evolutionary mechanisms within the genome. Separately, dynamical and statistical analyses of networks such as the World Wide Web and the social interactions existing between humans have shown that these networks can exhibit common fractal properties-including the property of being scale-free. This work attempts to bridge these two fields and demonstrate that the fractal properties of molecular networks are linked to the fractal properties of their underlying genomes. We suggest a stochastic model capable of describing the evolutionary growth of metabolic or signal-transduction networks. This model generates networks that share important statistical properties (so-called scale-free behavior) with real molecular networks. In particular, the frequency of vertices connected to exactly k other vertices follows a power-law distribution. The shape of this distribution remains invariant to changes in network scale: a small subgraph has the same distribution as the complete graph from which it is derived. Furthermore, the model correctly predicts that the frequencies of distinct DNA and protein domains also follow a power-law distribution. Finally, the model leads to a simple equation linking the total number of different DNA and protein domains in a genome with both the total number of genes and the overall network topology. MatLab (MathWorks, Inc.) programs described in this manuscript are available on request from the authors. ar345@columbia.edu.

Decreasing Risky Behavior on Social Network Sites: The Impact of Parental Involvement in Secondary Education Interventions.

Science.gov (United States)

Vanderhoven, Ellen; Schellens, Tammy; Valcke, Martin

2016-06-01

Teenagers face significant risks when using increasingly popular social network sites. Prevention and intervention efforts to raise awareness about these risks and to change risky behavior (so-called "e-safety" interventions) are essential for the wellbeing of these minors. However, several studies have revealed that while school interventions often affect awareness, they have only a limited impact on pupils' unsafe behavior. Utilizing the Theory of Planned Behavior and theories about parental involvement, we hypothesized that involving parents in an e-safety intervention would positively influence pupils' intentions and behavior. In a quasi-experimental study with pre- and post-test measures involving 207 pupils in secondary education, we compared the impact of an intervention without parental involvement with one that included active parental involvement by means of a homework task. We found that whereas parental involvement was not necessary to improve the intervention's impact on risk awareness, it did change intentions to engage in certain unsafe behavior, such as posting personal and sexual information on the profile page of a social network site, and in reducing existing problematic behavior. This beneficial impact was particularly evident for boys. These findings suggest that developing prevention campaigns with active parental involvement is well worth the effort. Researchers and developers should therefore focus on other efficient strategies to involve parents.

Molecular Dynamics Simulations with Quantum Mechanics/Molecular Mechanics and Adaptive Neural Networks.

Science.gov (United States)

Shen, Lin; Yang, Weitao

2018-03-13

Direct molecular dynamics (MD) simulation with ab initio quantum mechanical and molecular mechanical (QM/MM) methods is very powerful for studying the mechanism of chemical reactions in a complex environment but also very time-consuming. The computational cost of QM/MM calculations during MD simulations can be reduced significantly using semiempirical QM/MM methods with lower accuracy. To achieve higher accuracy at the ab initio QM/MM level, a correction on the existing semiempirical QM/MM model is an attractive idea. Recently, we reported a neural network (NN) method as QM/MM-NN to predict the potential energy difference between semiempirical and ab initio QM/MM approaches. The high-level results can be obtained using neural network based on semiempirical QM/MM MD simulations, but the lack of direct MD samplings at the ab initio QM/MM level is still a deficiency that limits the applications of QM/MM-NN. In the present paper, we developed a dynamic scheme of QM/MM-NN for direct MD simulations on the NN-predicted potential energy surface to approximate ab initio QM/MM MD. Since some configurations excluded from the database for NN training were encountered during simulations, which may cause some difficulties on MD samplings, an adaptive procedure inspired by the selection scheme reported by Behler [ Behler Int. J. Quantum Chem. 2015 , 115 , 1032 ; Behler Angew. Chem., Int. Ed. 2017 , 56 , 12828 ] was employed with some adaptions to update NN and carry out MD iteratively. We further applied the adaptive QM/MM-NN MD method to the free energy calculation and transition path optimization on chemical reactions in water. The results at the ab initio QM/MM level can be well reproduced using this method after 2-4 iteration cycles. The saving in computational cost is about 2 orders of magnitude. It demonstrates that the QM/MM-NN with direct MD simulations has great potentials not only for the calculation of thermodynamic properties but also for the characterization of

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Science.gov (United States)

Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

2003-11-01

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data.

Science.gov (United States)

Narimani, Zahra; Beigy, Hamid; Ahmad, Ashar; Masoudi-Nejad, Ali; Fröhlich, Holger

2017-01-01

Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell. Causal network structure inference has been approached using different methods in the past. Most causal network inference techniques, such as Dynamic Bayesian Networks and ordinary differential equations, are limited by their computational complexity and thus make large scale inference infeasible. This is specifically true if a Bayesian framework is applied in order to deal with the unavoidable uncertainty about the correct model. We devise a novel Bayesian network reverse engineering approach using ordinary differential equations with the ability to include non-linearity. Besides modeling arbitrary, possibly combinatorial and time dependent perturbations with unknown targets, one of our main contributions is the use of Expectation Propagation, an algorithm for approximate Bayesian inference over large scale network structures in short computation time. We further explore the possibility of integrating prior knowledge into network inference. We evaluate the proposed model on DREAM4 and DREAM8 data and find it competitive against several state-of-the-art existing network inference methods.

Membrane Fusion Involved in Neurotransmission: Glimpse from Electron Microscope and Molecular Simulation

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Zhiwei Yang

2017-06-01

Full Text Available Membrane fusion is one of the most fundamental physiological processes in eukaryotes for triggering the fusion of lipid and content, as well as the neurotransmission. However, the architecture features of neurotransmitter release machinery and interdependent mechanism of synaptic membrane fusion have not been extensively studied. This review article expounds the neuronal membrane fusion processes, discusses the fundamental steps in all fusion reactions (membrane aggregation, membrane association, lipid rearrangement and lipid and content mixing and the probable mechanism coupling to the delivery of neurotransmitters. Subsequently, this work summarizes the research on the fusion process in synaptic transmission, using electron microscopy (EM and molecular simulation approaches. Finally, we propose the future outlook for more exciting applications of membrane fusion involved in synaptic transmission, with the aid of stochastic optical reconstruction microscopy (STORM, cryo-EM (cryo-EM, and molecular simulations.

Membrane Fusion Involved in Neurotransmission: Glimpse from Electron Microscope and Molecular Simulation

Science.gov (United States)

Yang, Zhiwei; Gou, Lu; Chen, Shuyu; Li, Na; Zhang, Shengli; Zhang, Lei

2017-01-01

Membrane fusion is one of the most fundamental physiological processes in eukaryotes for triggering the fusion of lipid and content, as well as the neurotransmission. However, the architecture features of neurotransmitter release machinery and interdependent mechanism of synaptic membrane fusion have not been extensively studied. This review article expounds the neuronal membrane fusion processes, discusses the fundamental steps in all fusion reactions (membrane aggregation, membrane association, lipid rearrangement and lipid and content mixing) and the probable mechanism coupling to the delivery of neurotransmitters. Subsequently, this work summarizes the research on the fusion process in synaptic transmission, using electron microscopy (EM) and molecular simulation approaches. Finally, we propose the future outlook for more exciting applications of membrane fusion involved in synaptic transmission, with the aid of stochastic optical reconstruction microscopy (STORM), cryo-EM (cryo-EM), and molecular simulations. PMID:28638320

Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors.

Science.gov (United States)

Kierczak, Marcin; Dramiński, Michał; Koronacki, Jacek; Komorowski, Jan

2010-12-12

Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm.

Globally homochiral assembly of two-dimensional molecular networks triggered by co-absorbers.

Science.gov (United States)

Chen, Ting; Yang, Wen-Hong; Wang, Dong; Wan, Li-Jun

2013-01-01

Understanding the chirality induction and amplification processes, and the construction of globally homochiral surfaces, represent essential challenges in surface chirality studies. Here we report the induction of global homochirality in two-dimensional enantiomorphous networks of achiral molecules via co-assembly with chiral co-absorbers. The scanning tunnelling microscopy investigations and molecular mechanics simulations demonstrate that the point chirality of the co-absorbers transfers to organizational chirality of the assembly units via enantioselective supramolecular interactions, and is then hierarchically amplified to the global homochirality of two-dimensional networks. The global homochirality of the network assembly shows nonlinear dependence on the enantiomeric excess of chiral co-absorber in the solution phase, demonstrating, for the first time, the validation of the 'majority rules' for the homochirality control of achiral molecules at the liquid/solid interface. Such an induction and nonlinear chirality amplification effect promises a new approach towards two-dimensional homochirality control and may reveal important insights into asymmetric heterogeneous catalysis, chiral separation and chiral crystallization.

A molecular network of the aging human brain provides insights into the pathology and cognitive decline of Alzheimer's disease.

Science.gov (United States)

Mostafavi, Sara; Gaiteri, Chris; Sullivan, Sarah E; White, Charles C; Tasaki, Shinya; Xu, Jishu; Taga, Mariko; Klein, Hans-Ulrich; Patrick, Ellis; Komashko, Vitalina; McCabe, Cristin; Smith, Robert; Bradshaw, Elizabeth M; Root, David E; Regev, Aviv; Yu, Lei; Chibnik, Lori B; Schneider, Julie A; Young-Pearse, Tracy L; Bennett, David A; De Jager, Philip L

2018-06-01

There is a need for new therapeutic targets with which to prevent Alzheimer's disease (AD), a major contributor to aging-related cognitive decline. Here we report the construction and validation of a molecular network of the aging human frontal cortex. Using RNA sequence data from 478 individuals, we first build a molecular network using modules of coexpressed genes and then relate these modules to AD and its neuropathologic and cognitive endophenotypes. We confirm these associations in two independent AD datasets. We also illustrate the use of the network in prioritizing amyloid- and cognition-associated genes for in vitro validation in human neurons and astrocytes. These analyses based on unique cohorts enable us to resolve the role of distinct cortical modules that have a direct effect on the accumulation of AD pathology from those that have a direct effect on cognitive decline, exemplifying a network approach to complex diseases.

Structural Approaches to Sequence Evolution Molecules, Networks, Populations

CERN Document Server

Bastolla, Ugo; Roman, H. Eduardo; Vendruscolo, Michele

2007-01-01

Structural requirements constrain the evolution of biological entities at all levels, from macromolecules to their networks, right up to populations of biological organisms. Classical models of molecular evolution, however, are focused at the level of the symbols - the biological sequence - rather than that of their resulting structure. Now recent advances in understanding the thermodynamics of macromolecules, the topological properties of gene networks, the organization and mutation capabilities of genomes, and the structure of populations make it possible to incorporate these key elements into a broader and deeply interdisciplinary view of molecular evolution. This book gives an account of such a new approach, through clear tutorial contributions by leading scientists specializing in the different fields involved.

Chain networking revealed by molecular dynamics simulation

Science.gov (United States)

Zheng, Yexin; Tsige, Mesfin; Wang, Shi-Qing

Based on Kremer-Grest model for entangled polymer melts, we demonstrate how the response of a polymer glass depends critically on the chain length. After quenching two melts of very different chain lengths (350 beads per chain and 30 beads per chain) into deeply glassy states, we subject them to uniaxial extension. Our MD simulations show that the glass of long chains undergoes stable necking after yielding whereas the system of short chains is unable to neck and breaks up after strain localization. During ductile extension of the polymer glass made of long chain significant chain tension builds up in the load-bearing strands (LBSs). Further analysis is expected to reveal evidence of activation of the primary structure during post-yield extension. These results lend support to the recent molecular model 1 and are the simulations to demonstrate the role of chain networking. This work is supported, in part, by a NSF Grant (DMR-EAGER-1444859)

Genomic analyses identify molecular subtypes of pancreatic cancer.

Science.gov (United States)

Bailey, Peter; Chang, David K; Nones, Katia; Johns, Amber L; Patch, Ann-Marie; Gingras, Marie-Claude; Miller, David K; Christ, Angelika N; Bruxner, Tim J C; Quinn, Michael C; Nourse, Craig; Murtaugh, L Charles; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourbakhsh, Ehsan; Wani, Shivangi; Fink, Lynn; Holmes, Oliver; Chin, Venessa; Anderson, Matthew J; Kazakoff, Stephen; Leonard, Conrad; Newell, Felicity; Waddell, Nick; Wood, Scott; Xu, Qinying; Wilson, Peter J; Cloonan, Nicole; Kassahn, Karin S; Taylor, Darrin; Quek, Kelly; Robertson, Alan; Pantano, Lorena; Mincarelli, Laura; Sanchez, Luis N; Evers, Lisa; Wu, Jianmin; Pinese, Mark; Cowley, Mark J; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chantrill, Lorraine A; Mawson, Amanda; Humphris, Jeremy; Chou, Angela; Pajic, Marina; Scarlett, Christopher J; Pinho, Andreia V; Giry-Laterriere, Marc; Rooman, Ilse; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Merrett, Neil D; Toon, Christopher W; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Moran-Jones, Kim; Jamieson, Nigel B; Graham, Janet S; Duthie, Fraser; Oien, Karin; Hair, Jane; Grützmann, Robert; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Corbo, Vincenzo; Bassi, Claudio; Rusev, Borislav; Capelli, Paola; Salvia, Roberto; Tortora, Giampaolo; Mukhopadhyay, Debabrata; Petersen, Gloria M; Munzy, Donna M; Fisher, William E; Karim, Saadia A; Eshleman, James R; Hruban, Ralph H; Pilarsky, Christian; Morton, Jennifer P; Sansom, Owen J; Scarpa, Aldo; Musgrove, Elizabeth A; Bailey, Ulla-Maja Hagbo; Hofmann, Oliver; Sutherland, Robert L; Wheeler, David A; Gill, Anthony J; Gibbs, Richard A; Pearson, John V; Waddell, Nicola; Biankin, Andrew V; Grimmond, Sean M

2016-03-03

Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.

Musical Imagery Involves Wernicke's Area in Bilateral and Anti-Correlated Network Interactions in Musicians.

Science.gov (United States)

Zhang, Yizhen; Chen, Gang; Wen, Haiguang; Lu, Kun-Han; Liu, Zhongming

2017-12-06

Musical imagery is the human experience of imagining music without actually hearing it. The neural basis of this mental ability is unclear, especially for musicians capable of engaging in accurate and vivid musical imagery. Here, we created a visualization of an 8-minute symphony as a silent movie and used it as real-time cue for musicians to continuously imagine the music for repeated and synchronized sessions during functional magnetic resonance imaging (fMRI). The activations and networks evoked by musical imagery were compared with those elicited by the subjects directly listening to the same music. Musical imagery and musical perception resulted in overlapping activations at the anterolateral belt and Wernicke's area, where the responses were correlated with the auditory features of the music. Whereas Wernicke's area interacted within the intrinsic auditory network during musical perception, it was involved in much more complex networks during musical imagery, showing positive correlations with the dorsal attention network and the motor-control network and negative correlations with the default-mode network. Our results highlight the important role of Wernicke's area in forming vivid musical imagery through bilateral and anti-correlated network interactions, challenging the conventional view of segregated and lateralized processing of music versus language.

Efficient Construction of Mesostate Networks from Molecular Dynamics Trajectories.

Science.gov (United States)

Vitalis, Andreas; Caflisch, Amedeo

2012-03-13

The coarse-graining of data from molecular simulations yields conformational space networks that may be used for predicting the system's long time scale behavior, to discover structural pathways connecting free energy basins in the system, or simply to represent accessible phase space regions of interest and their connectivities in a two-dimensional plot. In this contribution, we present a tree-based algorithm to partition conformations of biomolecules into sets of similar microstates, i.e., to coarse-grain trajectory data into mesostates. On account of utilizing an architecture similar to that of established tree-based algorithms, the proposed scheme operates in near-linear time with data set size. We derive expressions needed for the fast evaluation of mesostate properties and distances when employing typical choices for measures of similarity between microstates. Using both a pedagogically useful and a real-word application, the algorithm is shown to be robust with respect to tree height, which in addition to mesostate threshold size is the main adjustable parameter. It is demonstrated that the derived mesostate networks can preserve information regarding the free energy basins and barriers by which the system is characterized.

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

DEFF Research Database (Denmark)

Wang, Mingxun; Carver, Jeremy J.; Pevzner, Pavel

2016-01-01

are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization...... and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations...

Molecular dynamics simulations of disordered materials from network glasses to phase-change memory alloys

CERN Document Server

Massobrio, Carlo; Bernasconi, Marco; Salmon, Philip S

2015-01-01

This book is a unique reference work in the area of atomic-scale simulation of glasses. For the first time, a highly selected panel of about 20 researchers provides, in a single book, their views, methodologies and applications on the use of molecular dynamics as a tool to describe glassy materials. The book covers a wide range of systems covering ""traditional"" network glasses, such as chalcogenides and oxides, as well as glasses for applications in the area of phase change materials. The novelty of this work is the interplay between molecular dynamics methods (both at the classical and firs

Sirtuins as regulators of the yeast metabolic network

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Markus eRalser

2012-03-01

Full Text Available There is growing evidence that the metabolic network is an integral regulator of cellularphysiology. Dynamic changes in metabolite concentrations, metabolic flux, or networktopology act as reporters of biological or environmental signals, and are required for the cellto trigger an appropriate biological reaction. Changes in the metabolic network are recognizedby specific sensory macromolecules and translated into a transcriptional or translationalresponse. The protein family of sirtuins, discovered more than 30 years ago as regulators ofsilent chromatin, seems to fulfill the role of a metabolic sensor during aging and conditions ofcaloric restriction. NAD+/NADH interconverting metabolic enzymes glyceraldehyde-3-phosphate dehydrogenase and alcohol dehydrogenase, as well as enzymes involved inNAD(H, synthesis provide or deprive NAD+ in close proximity to Sir2. This influence sirtuinactivity, and facilitates a dynamic response of the metabolic network to changes inmetabolism with effects on physiology and aging. The molecular network downstream Sir2,however, is complex. In just two orders, Sir2’s metabolism-related interactions span half ofthe yeast proteome, and are connected with virtually every physiological process. Thus,although it is fundamental to analyze single molecular mechanisms, it is at the same timecrucial to consider this genome-scale complexity when correlating single molecular eventswith phenotypes such as aging, cell growth, or stress resistance.

Molecular network considerations in the deformation of glassy polymers

International Nuclear Information System (INIS)

Henkee, C.S.

1985-01-01

Thin films of polystyrene (PS) are crosslinked with electron irradiation and are strained in tension until regions of local plastic deformation, either crazes or plane stress deformation zones (DZ's), have grown. The behavior of the PS glass is consistent with its being a network of molecular strands of total density nu = nu/sub x/ + nu/sub e/, where nu/sub e/ is the entangled strand density, and nu/sub x/ is the density of crosslinked strands. When nu is less than 4 x 10 25 m -3 only crazes are observed. As nu increases from 4 x 10 25 to 8 x 10 -5 m -3 , only shear DZ's are observed. The local extension ratio, lambda, in the crazes and DZ's correlate well with lambda/sub max/, the maximum extension ratio of a strand in a network of density nu computed using the Porod-Kratky model. Crosslinking to still higher crosslink densities, e.g. nu = 14nu/sub e/, results in cracks that propagate in a catastrophic manner at low applied strains. An optimum nu thus exists, one not too high to suppress local shear ductility but high enough to suppress crazes which can act as crack nucleation sites. Comparison of the results in crosslinked PS with those in other linear, but entangled polymer systems implies that chain scission is the major mechanism by which strands in the entanglement network are removed in forming fibril surfaces. Craze suppression by increasing nu is due to the extra energy required to break more main chain bonds to form these surfaces

An Atomic Force Microscopy Study of the Interactions Involving Polymers and Silane Networks

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Rodrigo L. Oréfice

1998-12-01

Full Text Available ABSTRACT: Silane coupling agents have been frequently used as interfacial agents in polymer composites to improve interfacial strength and resistance to fluid migration. Although the capability of these agents in improving properties and performance of composites has been reported, there are still many uncertainties regarding the processing-structure-property relationships and the mechanisms of coupling developed by silane agents. In this work, an Atomic Force Microscope (AFM was used to measure interactions between polymers and silica substrates, where silane networks with a series of different structures were processed. The influence of the structure of silane networks on the interactions with polymers was studied and used to determine the mechanisms involved in the coupling phenomenon. The AFM results showed that phenomena such as chain penetration, entanglements, intersegment bonding, chain conformation in the vicinities of rigid surfaces were identified as being relevant for the overall processes of adhesion and adsorption of polymeric chains within a silane network. AFM adhesion curves showed that penetration of polymeric chains through a more open silane network can lead to higher levels of interactions between polymer and silane agents.

Shared molecular pathways and gene networks for cardiovascular disease and type 2 diabetes mellitus in women across diverse ethnicities.

Science.gov (United States)

Chan, Kei Hang K; Huang, Yen-Tsung; Meng, Qingying; Wu, Chunyuan; Reiner, Alexander; Sobel, Eric M; Tinker, Lesley; Lusis, Aldons J; Yang, Xia; Liu, Simin

2014-12-01

Although cardiovascular disease (CVD) and type 2 diabetes mellitus (T2D) share many common risk factors, potential molecular mechanisms that may also be shared for these 2 disorders remain unknown. Using an integrative pathway and network analysis, we performed genome-wide association studies in 8155 blacks, 3494 Hispanic American, and 3697 Caucasian American women who participated in the national Women's Health Initiative single-nucleotide polymorphism (SNP) Health Association Resource and the Genomics and Randomized Trials Network. Eight top pathways and gene networks related to cardiomyopathy, calcium signaling, axon guidance, cell adhesion, and extracellular matrix seemed to be commonly shared between CVD and T2D across all 3 ethnic groups. We also identified ethnicity-specific pathways, such as cell cycle (specific for Hispanic American and Caucasian American) and tight junction (CVD and combined CVD and T2D in Hispanic American). In network analysis of gene-gene or protein-protein interactions, we identified key drivers that included COL1A1, COL3A1, and ELN in the shared pathways for both CVD and T2D. These key driver genes were cross-validated in multiple mouse models of diabetes mellitus and atherosclerosis. Our integrative analysis of American women of 3 ethnicities identified multiple shared biological pathways and key regulatory genes for the development of CVD and T2D. These prospective findings also support the notion that ethnicity-specific susceptibility genes and process are involved in the pathogenesis of CVD and T2D. © 2014 American Heart Association, Inc.

The influence of molecular mobility on the properties of networks of gold nanoparticles and organic ligands.

Science.gov (United States)

Devid, Edwin J; Martinho, Paulo N; Kamalakar, M Venkata; Prendergast, Úna; Kübel, Christian; Lemma, Tibebe; Dayen, Jean-François; Keyes, Tia E; Doudin, Bernard; Ruben, Mario; van der Molen, Sense Jan

2014-01-01

We prepare and investigate two-dimensional (2D) single-layer arrays and multilayered networks of gold nanoparticles derivatized with conjugated hetero-aromatic molecules, i.e., S-(4-{[2,6-bipyrazol-1-yl)pyrid-4-yl]ethynyl}phenyl)thiolate (herein S-BPP), as capping ligands. These structures are fabricated by a combination of self-assembly and microcontact printing techniques, and are characterized by electron microscopy, UV-visible spectroscopy and Raman spectroscopy. Selective binding of the S-BPP molecules to the gold nanoparticles through Au-S bonds is found, with no evidence for the formation of N-Au bonds between the pyridine or pyrazole groups of BPP and the gold surface. Subtle, but significant shifts with temperature of specific Raman S-BPP modes are also observed. We attribute these to dynamic changes in the orientation and/or increased mobility of the molecules on the gold nanoparticle facets. As for their conductance, the temperature-dependence for S-BPP networks differs significantly from standard alkanethiol-capped networks, especially above 220 K. Relating the latter two observations, we propose that dynamic changes in the molecular layers effectively lower the molecular tunnel barrier for BPP-based arrays at higher temperatures.

The influence of molecular mobility on the properties of networks of gold nanoparticles and organic ligands

Directory of Open Access Journals (Sweden)

Edwin J. Devid

2014-09-01

Full Text Available We prepare and investigate two-dimensional (2D single-layer arrays and multilayered networks of gold nanoparticles derivatized with conjugated hetero-aromatic molecules, i.e., S-(4-{[2,6-bipyrazol-1-ylpyrid-4-yl]ethynyl}phenylthiolate (herein S-BPP, as capping ligands. These structures are fabricated by a combination of self-assembly and microcontact printing techniques, and are characterized by electron microscopy, UV–visible spectroscopy and Raman spectroscopy. Selective binding of the S-BPP molecules to the gold nanoparticles through Au–S bonds is found, with no evidence for the formation of N–Au bonds between the pyridine or pyrazole groups of BPP and the gold surface. Subtle, but significant shifts with temperature of specific Raman S-BPP modes are also observed. We attribute these to dynamic changes in the orientation and/or increased mobility of the molecules on the gold nanoparticle facets. As for their conductance, the temperature-dependence for S-BPP networks differs significantly from standard alkanethiol-capped networks, especially above 220 K. Relating the latter two observations, we propose that dynamic changes in the molecular layers effectively lower the molecular tunnel barrier for BPP-based arrays at higher temperatures.

Surface tectonics of nanoporous networks of melamine-capped molecular building blocks formed through interface Schiff-base reactions.

Science.gov (United States)

Liu, Xuan-He; Wang, Dong; Wan, Li-Jun

2013-10-01

Control over the assembly of molecules on a surface is of great importance for the fabrication of molecule-based miniature devices. Melamine (MA) and molecules with terminal MA units are promising candidates for supramolecular interfacial packing patterning, owing to their multiple hydrogen-bonding sites. Herein, we report the formation of self-assembled structures of MA-capped molecules through a simple on-surface synthetic route. MA terminal groups were successfully fabricated onto rigid molecular cores with 2-fold and 3-fold symmetry through interfacial Schiff-base reactions between MA and aldehyde groups. Sub-molecular scanning tunneling microscopy (STM) imaging of the resultant adlayer revealed the formation of nanoporous networks. Detailed structural analysis indicated that strong hydrogen-bonding interactions between the MA groups persistently drove the formation of nanoporous networks. Herein, we demonstrate that functional groups with strong hydrogen-bond-formation ability are promising building blocks for the guided assembly of nanoporous networks and other hierarchical 2D assemblies. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An overview of potential molecular mechanisms involved in VSMC phenotypic modulation.

Science.gov (United States)

Zhang, Ming-Jie; Zhou, Yi; Chen, Lei; Wang, Yan-Qin; Wang, Xu; Pi, Yan; Gao, Chang-Yue; Li, Jing-Cheng; Zhang, Li-Li

2016-02-01

The fully differentiated medial vascular smooth muscle cells (VSMCs) of mature vessels keep quiescent and contractile. However, VSMC can exhibit the plasticity in phenotype switching from a differentiated and contractile phenotype to a dedifferentiated state in response to alterations in local environmental cues, which is called phenotypic modulation or switching. Distinguishing from its differentiated state expressing more smooth muscle (SM)-specific/selective proteins, the phenotypic modulation in VSMC is characterized by an increased rate of proliferation, migration, synthesis of extracellular matrix proteins and decreased expression of SM contractile proteins. Although it has been well demonstrated that phenotypic modulation of VSMC contributes to the occurrence and progression of many proliferative vascular diseases, little is known about the details of the molecular mechanisms of VSMC phenotypic modulation. Growing evidence suggests that variety of molecules including microRNAs, cytokines and biochemical factors, membrane receptors, ion channels, cytoskeleton and extracellular matrix play important roles in controlling VSMC phenotype. The focus of the present review is to provide an overview of potential molecular mechanisms involved in VSMC phenotypic modulation in recent years. To clarify VSMC differentiation and phenotypic modulation mechanisms will contribute to producing cell-based therapeutic interventions for aberrant VSMC differentiation-related diseases.

Systems biology integration of proteomic data in rodent models of depression reveals involvement of the immune response and glutamatergic signaling.

Science.gov (United States)

Carboni, Lucia; Nguyen, Thanh-Phuong; Caberlotto, Laura

2016-12-01

The pathophysiological basis of major depression is incompletely understood. Recently, numerous proteomic studies have been performed in rodent models of depression to investigate the molecular underpinnings of depressive-like behaviours with an unbiased approach. The objective of the study is to integrate the results of these proteomic studies in depression models to shed light on the most relevant molecular pathways involved in the disease. Network analysis is performed integrating preexisting proteomic data from rodent models of depression. The IntAct mouse and the HRPD are used as reference protein-protein interaction databases. The functionality analyses of the networks are then performed by testing overrepresented GO biological process terms and pathways. Functional enrichment analyses of the networks revealed an association with molecular processes related to depression in humans, such as those involved in the immune response. Pathways impacted by clinically effective antidepressants are modulated, including glutamatergic signaling and neurotrophic responses. Moreover, dysregulations of proteins regulating energy metabolism and circadian rhythms are implicated. The comparison with protein pathways modulated in depressive patients revealed significant overlapping. This systems biology study supports the notion that animal models can contribute to the research into the biology and therapeutics of depression. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease

Science.gov (United States)

Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel

2013-01-01

Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk. PMID:23539213

Single-cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks involved In the Central Circadian Clock

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James Park

2016-10-01

Full Text Available Single-cell heterogeneity confounds efforts to understand how a population of cells organizes into cellular networks that underlie tissue-level function. This complexity is prominent in the mammalian suprachiasmatic nucleus (SCN. Here, individual neurons exhibit a remarkable amount of asynchronous behavior and transcriptional heterogeneity. However, SCN neurons are able to generate precisely coordinated synaptic and molecular outputs that synchronize the body to a common circadian cycle by organizing into cellular networks. To understand this emergent cellular network property, it is important to reconcile single-neuron heterogeneity with network organization. In light of recent studies suggesting that transcriptionally heterogeneous cells organize into distinct cellular phenotypes, we characterized the transcriptional, spatial, and functional organization of 352 SCN neurons from mice experiencing phase-shifts in their circadian cycle. Using the community structure detection method and multivariate analytical techniques, we identified previously undescribed neuronal phenotypes that are likely to participate in regulatory networks with known SCN cell types. Based on the newly discovered neuronal phenotypes, we developed a data-driven neuronal network structure in which multiple cell types interact through known synaptic and paracrine signaling mechanisms. These results provide a basis from which to interpret the functional variability of SCN neurons and describe methodologies towards understanding how a population of heterogeneous single cells organizes into cellular networks that underlie tissue-level function.

Identification of Resting State Networks Involved in Executive Function.

Science.gov (United States)

Connolly, Joanna; McNulty, Jonathan P; Boran, Lorraine; Roche, Richard A P; Delany, David; Bokde, Arun L W

2016-06-01

The structural networks in the human brain are consistent across subjects, and this is reflected also in that functional networks across subjects are relatively consistent. These findings are not only present during performance of a goal oriented task but there are also consistent functional networks during resting state. It suggests that goal oriented activation patterns may be a function of component networks identified using resting state. The current study examines the relationship between resting state networks measured and patterns of neural activation elicited during a Stroop task. The association between the Stroop-activated networks and the resting state networks was quantified using spatial linear regression. In addition, we investigated if the degree of spatial association of resting state networks with the Stroop task may predict performance on the Stroop task. The results of this investigation demonstrated that the Stroop activated network can be decomposed into a number of resting state networks, which were primarily associated with attention, executive function, visual perception, and the default mode network. The close spatial correspondence between the functional organization of the resting brain and task-evoked patterns supports the relevance of resting state networks in cognitive function.

DMPD: The involvement of the interleukin-1 receptor-associated kinases (IRAKs) incellular signaling networks controlling inflammation. [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available ncellular signaling networks controlling inflammation. Ringwood L, Li L. Cytokine. 2008 Apr;42(1):1-7. Epub ...ases (IRAKs) incellular signaling networks controlling inflammation. PubmedID 182...49132 Title The involvement of the interleukin-1 receptor-associated kinases (IRAKs) incellular signaling networks controlling

Integrated network analysis reveals potentially novel molecular mechanisms and therapeutic targets of refractory epilepsies.

Directory of Open Access Journals (Sweden)

Hongwei Chu

Full Text Available 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.

AMES, NESC and ENIQ: European networks in the field of structural integrity involving NDE and inspection effectiveness assessment

International Nuclear Information System (INIS)

Crutzen, S.; Hurst, R.; Debarberis, L.; Lemaitre, P.; Eriksen, B.

1999-01-01

Three European networks on structural integrity aspects of ageing nuclear components are presently managed by the Institute for Advanced Materials of the Joint Research Centre of the European Commission: AMES (Ageing Materials Evaluation and Studies), ENIQ (European Network for Inspection Qualification) and NESC (Network for Evaluating Steel Components). All three networks involve actions, which aim at the effectiveness and reliability assessment of NDE techniques and of inspection procedures: Either for materials damage detection and characterisation or for defect detection and evaluation. This paper is describing very generally the objectives of the three networks and is then concentrating on the results obtained in ENIQ, which are relevant with ISI and regulatory issues. (orig./DGE)

Comparing culture and molecular methods for the identification of microorganisms involved in necrotizing soft tissue infections

DEFF Research Database (Denmark)

Rudkjøbing, Vibeke Børsholt; Thomsen, Trine Rolighed; Xu, Yijuan

2016-01-01

BACKGROUND: Necrotizing soft tissue infections (NSTIs) are a group of infections affecting all soft tissues. NSTI involves necrosis of the afflicted tissue and is potentially life threatening due to major and rapid destruction of tissue, which often leads to septic shock and organ failure. The gold...... to culture. Although the molecular methods generally gave concordant results, our results indicate that Microseq may misidentify or overlook microorganisms that can be detected by other molecular methods. Half of the patients were found to be infected with S. pyogenes, but several atypical findings were also...... that clinicians should be prepared to diagnose and treat any combination of microbial pathogens. Some of the tested molecular methods offer a faster turnaround time combined with a high specificity, which makes supplemental use of such methods attractive for identification of microorganisms, especially...

A gene network bioinformatics analysis for pemphigoid autoimmune blistering diseases.

Science.gov (United States)

Barone, Antonio; Toti, Paolo; Giuca, Maria Rita; Derchi, Giacomo; Covani, Ugo

2015-07-01

In this theoretical study, a text mining search and clustering analysis of data related to genes potentially involved in human pemphigoid autoimmune blistering diseases (PAIBD) was performed using web tools to create a gene/protein interaction network. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was employed to identify a final set of PAIBD-involved genes and to calculate the overall significant interactions among genes: for each gene, the weighted number of links, or WNL, was registered and a clustering procedure was performed using the WNL analysis. Genes were ranked in class (leader, B, C, D and so on, up to orphans). An ontological analysis was performed for the set of 'leader' genes. Using the above-mentioned data network, 115 genes represented the final set; leader genes numbered 7 (intercellular adhesion molecule 1 (ICAM-1), interferon gamma (IFNG), interleukin (IL)-2, IL-4, IL-6, IL-8 and tumour necrosis factor (TNF)), class B genes were 13, whereas the orphans were 24. The ontological analysis attested that the molecular action was focused on extracellular space and cell surface, whereas the activation and regulation of the immunity system was widely involved. Despite the limited knowledge of the present pathologic phenomenon, attested by the presence of 24 genes revealing no protein-protein direct or indirect interactions, the network showed significant pathways gathered in several subgroups: cellular components, molecular functions, biological processes and the pathologic phenomenon obtained from the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database. The molecular basis for PAIBD was summarised and expanded, which will perhaps give researchers promising directions for the identification of new therapeutic targets.

Molecular Network-Based Identification of Competing Endogenous RNAs in Thyroid Carcinoma

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Minjia Lu

2018-01-01

Full Text Available RNAs may act as competing endogenous RNAs (ceRNAs, a critical mechanism in determining gene expression regulations in many cancers. However, the roles of ceRNAs in thyroid carcinoma remains elusive. In this study, we have developed a novel pipeline called Molecular Network-based Identification of ceRNA (MNIceRNA to identify ceRNAs in thyroid carcinoma. MNIceRNA first constructs micro RNA (miRNA–messenger RNA (mRNAlong non-coding RNA (lncRNA networks from miRcode database and weighted correlation network analysis (WGCNA, based on which to identify key drivers of differentially expressed RNAs between normal and tumor samples. It then infers ceRNAs of the identified key drivers using the long non-coding competing endogenous database (lnCeDB. We applied the pipeline into The Cancer Genome Atlas (TCGA thyroid carcinoma data. As a result, 598 lncRNAs, 1025 mRNAs, and 90 microRNA (miRNAs were inferred to be differentially expressed between normal and thyroid cancer samples. We then obtained eight key driver miRNAs, among which hsa-mir-221 and hsa-mir-222 were key driver RNAs identified by both miRNA–mRNA–lncRNA and WGCNA network. In addition, hsa-mir-375 was inferred to be significant for patients’ survival with 34 associated ceRNAs, among which RUNX2, DUSP6 and SEMA3D are known oncogenes regulating cellular proliferation and differentiation in thyroid cancer. These ceRNAs are critical in revealing the secrets behind thyroid cancer progression and may serve as future therapeutic biomarkers.

Network-based integration of molecular and physiological data elucidates regulatory mechanisms underlying adaptation to high-fat diet

NARCIS (Netherlands)

Derous, D.; Kelder, T.; Schothorst, E.M. van; Erk, M. van; Voigt, A.; Klaus, S.; Keijer, J.; Radonjic, M.

2015-01-01

Health is influenced by interplay of molecular, physiological and environmental factors. To effectively maintain health and prevent disease, health-relevant relations need to be understood at multiple levels of biological complexity. Network-based methods provide a powerful platform for integration

Evidence for systems-level molecular mechanisms of tumorigenesis

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Capellá Gabriel

2007-06-01

Full Text Available Abstract Background Cancer arises from the consecutive acquisition of genetic alterations. Increasing evidence suggests that as a consequence of these alterations, molecular interactions are reprogrammed in the context of highly connected and regulated cellular networks. Coordinated reprogramming would allow the cell to acquire the capabilities for malignant growth. Results Here, we determine the coordinated function of cancer gene products (i.e., proteins encoded by differentially expressed genes in tumors relative to healthy tissue counterparts, hereafter referred to as "CGPs" defined as their topological properties and organization in the interactome network. We show that CGPs are central to information exchange and propagation and that they are specifically organized to promote tumorigenesis. Centrality is identified by both local (degree and global (betweenness and closeness measures, and systematically appears in down-regulated CGPs. Up-regulated CGPs do not consistently exhibit centrality, but both types of cancer products determine the overall integrity of the network structure. In addition to centrality, down-regulated CGPs show topological association that correlates with common biological processes and pathways involved in tumorigenesis. Conclusion Given the current limited coverage of the human interactome, this study proposes that tumorigenesis takes place in a specific and organized way at the molecular systems-level and suggests a model that comprises the precise down-regulation of groups of topologically-associated proteins involved in particular functions, orchestrated with the up-regulation of specific proteins.

A Network Biology Approach to Discover the Molecular Biomarker Associated with Hepatocellular Carcinoma

Directory of Open Access Journals (Sweden)

Liwei Zhuang

2014-01-01

Full Text Available In recent years, high throughput technologies such as microarray platform have provided a new avenue for hepatocellular carcinoma (HCC investigation. Traditionally, gene sets enrichment analysis of survival related genes is commonly used to reveal the underlying functional mechanisms. However, this approach usually produces too many candidate genes and cannot discover detailed signaling transduction cascades, which greatly limits their clinical application such as biomarker development. In this study, we have proposed a network biology approach to discover novel biomarkers from multidimensional omics data. This approach effectively combines clinical survival data with topological characteristics of human protein interaction networks and patients expression profiling data. It can produce novel network based biomarkers together with biological understanding of molecular mechanism. We have analyzed eighty HCC expression profiling arrays and identified that extracellular matrix and programmed cell death are the main themes related to HCC progression. Compared with traditional enrichment analysis, this approach can provide concrete and testable hypothesis on functional mechanism. Furthermore, the identified subnetworks can potentially be used as suitable targets for therapeutic intervention in HCC.

Network analysis of genes involved in the enhancement of hyperthermia sensitivity by the knockdown of BAG3 in human oral squamous cell carcinoma cells.

Science.gov (United States)

Yunoki, Tatsuya; Tabuchi, Yoshiaki; Hayashi, Atsushi; Kondo, Takashi

2016-07-01

BCL2-associated athanogene 3 (BAG3), a co-chaperone of the heat shock 70 kDa protein (HSPA) family of proteins, is a cytoprotective protein that acts against various stresses, including heat stress. The aim of the present study was to identify gene networks involved in the enhancement of hyperthermia (HT) sensitivity by the knockdown (KD) of BAG3 in human oral squamous cell carcinoma (OSCC) cells. Although a marked elevation in the protein expression of BAG3 was detected in human the OSCC HSC-3 cells exposed to HT at 44˚C for 90 min, its expression was almost completely suppressed in the cells transfected with small interfering RNA against BAG3 (siBAG) under normal and HT conditions. The silencing of BAG3 also enhanced the cell death that was increased in the HSC-3 cells by exposure to HT. Global gene expression analysis revealed many genes that were differentially expressed by >2-fold in the cells exposed to HT and transfected with siBAG. Moreover, Ingenuity® pathways analysis demonstrated two unique gene networks, designated as Pro-cell death and Anti-cell death, which were obtained from upregulated genes and were mainly associated with the biological functions of induction and the prevention of cell death, respectively. Of note, the expression levels of genes in the Pro-cell death and Anti-cell death gene networks were significantly elevated and reduced in the HT + BAG3-KD group compared to those in the HT control group, respectively. These results provide further insight into the molecular mechanisms involved in the enhancement of HT sensitivity by the silencing of BAG3 in human OSCC cells.

Dynamic functional brain networks involved in simple visual discrimination learning.

Science.gov (United States)

Fidalgo, Camino; Conejo, Nélida María; González-Pardo, Héctor; Arias, Jorge Luis

2014-10-01

Visual discrimination tasks have been widely used to evaluate many types of learning and memory processes. However, little is known about the brain regions involved at different stages of visual discrimination learning. We used cytochrome c oxidase histochemistry to evaluate changes in regional brain oxidative metabolism during visual discrimination learning in a water-T maze at different time points during training. As compared with control groups, the results of the present study reveal the gradual activation of cortical (prefrontal and temporal cortices) and subcortical brain regions (including the striatum and the hippocampus) associated to the mastery of a simple visual discrimination task. On the other hand, the brain regions involved and their functional interactions changed progressively over days of training. Regions associated with novelty, emotion, visuo-spatial orientation and motor aspects of the behavioral task seem to be relevant during the earlier phase of training, whereas a brain network comprising the prefrontal cortex was found along the whole learning process. This study highlights the relevance of functional interactions among brain regions to investigate learning and memory processes. Copyright © 2014 Elsevier Inc. All rights reserved.

Phenotypic and Molecular Identification of Bacteria Involved in Decubitus Ulcers

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Mehran Dolati

2017-07-01

Full Text Available Background:    Bacterial secondary infection of pressure ulcers (bedsores, so called as decubitus ulcers, leads to ulcer development and it interferes with the healing process. Thus, such infections can be lethal due to the sepsis if no constructive medicinal measures regarded. Drug resistance of bacteria in pressure ulcers leads to healing inhibition. Molecular identification of bacteria involved in such infections seem necessary as culture and phenotypic approaches may result in misidentification. . The purpose of this study was to isolate and identify aerobic bacteria detected in bedsores in three Hospitals: Rasool-e-Akram, Imam Hossein and Tajrish Shohada Hospitals, Tehran, Iran.Methods:    To this end, decubitus ulcer samples of 49 patients were obtained using sterile swabs. After direct microscopic examination, the swabs were used to streak BHI agar plates supplemented with %5 defibrinated sheep blood for enrichment of probable aerobic cultures. Bacterial isolates diagnosed by biochemical tests. Antibiotic susceptibility of the isolates determined based on CLSI guideline. For molecular identification, PCR amplification of the 16S rRNA gene performed using Eubacterial universal primers. Then, the PCR products were sequenced and the nucleotide sequences of the PCR products were analyzed by BLASTN similarity search program available at NCBI. Results:   Among the isolates, Pseudomonas aeruginosa (36% had the highest frequency, followed by Staphylococcus aureus (32% and Escherichia coli (30%. The frequencies of Klebsiella pneumonia and Proteus spp. were 10% and 8%, respectively. Most of the isolated bacteria showed a widespread antibiotic resistance. Molecular identification of the bacterial isolates resulted in 6 isolates of Escherichia coli, two isolates of each of Proteus mirabilis and Shigella spp., 4 isolates of Enterobacter cloacae, and 1 isolate of each of Cronobacter sakazakii and Morganella morganii.Conclusion: �

An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

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Liu Lili

2013-06-01

Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

GenCLiP 2.0: a web server for functional clustering of genes and construction of molecular networks based on free terms.

Science.gov (United States)

Wang, Jia-Hong; Zhao, Ling-Feng; Lin, Pei; Su, Xiao-Rong; Chen, Shi-Jun; Huang, Li-Qiang; Wang, Hua-Feng; Zhang, Hai; Hu, Zhen-Fu; Yao, Kai-Tai; Huang, Zhong-Xi

2014-09-01

Identifying biological functions and molecular networks in a gene list and how the genes may relate to various topics is of considerable value to biomedical researchers. Here, we present a web-based text-mining server, GenCLiP 2.0, which can analyze human genes with enriched keywords and molecular interactions. Compared with other similar tools, GenCLiP 2.0 offers two unique features: (i) analysis of gene functions with free terms (i.e. any terms in the literature) generated by literature mining or provided by the user and (ii) accurate identification and integration of comprehensive molecular interactions from Medline abstracts, to construct molecular networks and subnetworks related to the free terms. http://ci.smu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A systems biology-based approach to uncovering the molecular mechanisms underlying the effects of dragon's blood tablet in colitis, involving the integration of chemical analysis, ADME prediction, and network pharmacology.

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Haiyu Xu

Full Text Available Traditional Chinese medicine (TCM is one of the oldest East Asian medical systems. The present study adopted a systems biology-based approach to provide new insights relating to the active constituents and molecular mechanisms underlying the effects of dragon's blood (DB tablets for the treatment of colitis. This study integrated chemical analysis, prediction of absorption, distribution, metabolism, and excretion (ADME, and network pharmacology. Firstly, a rapid, reliable, and accurate ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry method was employed to identify 48 components of DB tablets. In silico prediction of the passive absorption of these compounds, based on Caco-2 cell permeability, and their P450 metabolism enabled the identification of 22 potentially absorbed components and 8 metabolites. Finally, networks were constructed to analyze interactions between these DB components/metabolites absorbed and their putative targets, and between the putative DB targets and known therapeutic targets for colitis. This study provided a great opportunity to deepen the understanding of the complex pharmacological mechanisms underlying the effects of DB in colitis treatment.

Occipital and occipital "plus" epilepsies: A study of involved epileptogenic networks through SEEG quantification.

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Marchi, Angela; Bonini, Francesca; Lagarde, Stanislas; McGonigal, Aileen; Gavaret, Martine; Scavarda, Didier; Carron, Romain; Aubert, Sandrine; Villeneuve, Nathalie; Médina Villalon, Samuel; Bénar, Christian; Trebuchon, Agnes; Bartolomei, Fabrice

2016-09-01

Compared with temporal or frontal lobe epilepsies, the occipital lobe epilepsies (OLE) remain poorly characterized. In this study, we aimed at classifying the ictal networks involving OLE and investigated clinical features of the OLE network subtypes. We studied 194 seizures from 29 consecutive patients presenting with OLE and investigated by stereoelectroencephalography (SEEG). Epileptogenicity of occipital and extraoccipital regions was quantified according to the 'epileptogenicity index' (EI) method. We found that 79% of patients showed widespread epileptogenic zone organization, involving parietal or temporal regions in addition to the occipital lobe. Two main groups of epileptogenic zone organization within occipital lobe seizures were identified: a pure occipital group and an occipital "plus" group, the latter including two further subgroups, occipitotemporal and occipitoparietal. In 29% of patients, the epileptogenic zone was found to have a bilateral organization. The most epileptogenic structure was the fusiform gyrus (mean EI: 0.53). Surgery was proposed in 18/29 patients, leading to seizure freedom in 55% (Engel Class I). Results suggest that, in patient candidates for surgery, the majority of cases are characterized by complex organization of the EZ, corresponding to the occipital plus group. Copyright © 2016 Elsevier Inc. All rights reserved.

Steady state analysis of Boolean molecular network models via model reduction and computational algebra.

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Veliz-Cuba, Alan; Aguilar, Boris; Hinkelmann, Franziska; Laubenbacher, Reinhard

2014-06-26

A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for

Are Adolescents Engaged in the Problematic Use of Social Networking Sites More Involved in Peer Aggression and Victimization?

Science.gov (United States)

Martínez-Ferrer, Belén; Moreno, David; Musitu, Gonzalo

2018-01-01

The problematic use of social networking sites is becoming a major public health concern. Previous research has found that adolescents who engage in a problematic use of social networking sites are likely to show maladjustment problems. However, little is known about its links with peer aggression and victimization. The main goal of this study was to analyze the relationship between problematic use of online social networking sites, peer aggression -overt vs. relational and reactive vs. instrumental-, and peer victimization -overt physical and verbal, and relational-, taking into account gender and age (in early and mid-adolescence). Participants were selected using randomized cluster sampling considering school and class as clusters. A battery of instruments was applied to 1,952 adolescents' secondary students from Spain (Andalusia) (50.4% boys), aged 11 to 16 ( M = 14.07, SD = 1.39). Results showed that girls and 14-16 adolescents were more involved in a problematic use of online social networking sites. Furthermore, adolescents with high problematic use of online social networking sites were more involved in overt-reactive and instrumental-and relational-reactive and instrumental-aggressive behaviors, and self-reported higher levels of overt-physical and verbal-and relational victimization. Even though boys indicated higher levels of all types of victimization, girls with high problematic use of online social networking sites scored the highest on relational victimization. Relating to age, early adolescents (aged 11-14) with higher problematic use of online social networking sites reported the highest levels of overt verbal and relational victimization. Overall, results suggested the co-occurrence of problematic use of online social networking sites, peer aggression and victimization. In addition, results showed the influence that gender and age had on peer victimization. This study highlights the continuity between offline and online domains with regard to

Are Adolescents Engaged in the Problematic Use of Social Networking Sites More Involved in Peer Aggression and Victimization?

Directory of Open Access Journals (Sweden)

Belén Martínez-Ferrer

2018-05-01

Full Text Available The problematic use of social networking sites is becoming a major public health concern. Previous research has found that adolescents who engage in a problematic use of social networking sites are likely to show maladjustment problems. However, little is known about its links with peer aggression and victimization. The main goal of this study was to analyze the relationship between problematic use of online social networking sites, peer aggression –overt vs. relational and reactive vs. instrumental–, and peer victimization –overt physical and verbal, and relational–, taking into account gender and age (in early and mid-adolescence. Participants were selected using randomized cluster sampling considering school and class as clusters. A battery of instruments was applied to 1,952 adolescents' secondary students from Spain (Andalusia (50.4% boys, aged 11 to 16 (M = 14.07, SD = 1.39. Results showed that girls and 14–16 adolescents were more involved in a problematic use of online social networking sites. Furthermore, adolescents with high problematic use of online social networking sites were more involved in overt—reactive and instrumental—and relational—reactive and instrumental—aggressive behaviors, and self-reported higher levels of overt—physical and verbal—and relational victimization. Even though boys indicated higher levels of all types of victimization, girls with high problematic use of online social networking sites scored the highest on relational victimization. Relating to age, early adolescents (aged 11–14 with higher problematic use of online social networking sites reported the highest levels of overt verbal and relational victimization. Overall, results suggested the co-occurrence of problematic use of online social networking sites, peer aggression and victimization. In addition, results showed the influence that gender and age had on peer victimization. This study highlights the continuity between offline

Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics

DEFF Research Database (Denmark)

Papaleo, Elena

2015-01-01

that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome...... with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties...... simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations....

Suppressed Expression of T-Box Transcription Factors is Involved in Senescence in Chronic Obstructive Pulmonary Disease

Energy Technology Data Exchange (ETDEWEB)

Acquaah-Mensah, George; Malhotra, Deepti; Vulimiri, Madhulika; McDermott, Jason E.; Biswal, Shyam

2012-06-19

Chronic obstructive pulmonary disease (COPD) is a major global health problem. The etiology of COPD has been associated with apoptosis, oxidative stress, and inflammation. However, understanding of the molecular interactions that modulate COPD pathogenesis remains only partly resolved. We conducted an exploratory study on COPD etiology to identify the key molecular participants. We used information-theoretic algorithms including Context Likelihood of Relatedness (CLR), Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNE), and Inferelator. We captured direct functional associations among genes, given a compendium of gene expression profiles of human lung epithelial cells. A set of genes differentially expressed in COPD, as reported in a previous study were superposed with the resulting transcriptional regulatory networks. After factoring in the properties of the networks, an established COPD susceptibility locus and domain-domain interactions involving protein products of genes in the generated networks, several molecular candidates were predicted to be involved in the etiology of COPD. These include COL4A3, CFLAR, GULP1, PDCD1, CASP10, PAX3, BOK, HSPD1, PITX2, and PML. Furthermore, T-box (TBX) genes and cyclin-dependent kinase inhibitor 2A (CDKN2A), which are in a direct transcriptional regulatory relationship, emerged as preeminent participants in the etiology of COPD by means of senescence. Contrary to observations in neoplasms, our study reveals that the expression of genes and proteins in the lung samples from patients with COPD indicate an increased tendency towards cellular senescence. The expression of the anti-senescence mediators TBX transcription factors, chromatin modifiers histone deacetylases, and sirtuins was suppressed; while the expression of TBX-regulated cellular senescence markers such as CDKN2A, CDKN1A, and CAV1 was elevated in the peripheral lung tissue samples from patients with COPD. The critical balance between senescence

The AMPK enzyme-complex: From the regulation of cellular energy homeostasis to a possible new molecular target in the management of chronic inflammatory disorders

NARCIS (Netherlands)

Antonioli, Luca; Colucci, Rocchina; Pellegrini, Carolina; Giustarini, Giulio; Sacco, Deborah; Tirotta, Erika; Caputi, Valentina; Marsilio, Ilaria; Giron, Maria Cecilia; Németh, Zoltán H; Blandizzi, Corrado; Fornai, Matteo

2016-01-01

Introduction: Adenosine monophosphate-activated protein kinase (AMPK), known as an enzymatic complex that regulates the energetic metabolism, is emerging as a pivotal enzyme and enzymatic pathway involved in the regulation of immune homeostatic networks. It is also involved in the molecular

Placental gene-expression profiles of intrahepatic cholestasis of pregnancy reveal involvement of multiple molecular pathways in blood vessel formation and inflammation.

Science.gov (United States)

Du, QiaoLing; Pan, YouDong; Zhang, YouHua; Zhang, HaiLong; Zheng, YaJuan; Lu, Ling; Wang, JunLei; Duan, Tao; Chen, JianFeng

2014-07-07

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-associated liver disease with potentially deleterious consequences for the fetus, particularly when maternal serum bile-acid concentration >40 μM. However, the etiology and pathogenesis of ICP remain elusive. To reveal the underlying molecular mechanisms for the association of maternal serum bile-acid level and fetal outcome in ICP patients, DNA microarray was applied to characterize the whole-genome expression profiles of placentas from healthy women and women diagnosed with ICP. Thirty pregnant women recruited in this study were categorized evenly into three groups: healthy group; mild ICP, with serum bile-acid concentration ranging from 10-40 μM; and severe ICP, with bile-acid concentration >40 μM. Gene Ontology analysis in combination with construction of gene-interaction and gene co-expression networks were applied to identify the core regulatory genes associated with ICP pathogenesis, which were further validated by quantitative real-time PCR and histological staining. The core regulatory genes were mainly involved in immune response, VEGF signaling pathway and G-protein-coupled receptor signaling, implying essential roles of immune response, vasculogenesis and angiogenesis in ICP pathogenesis. This implication was supported by the observed aggregated immune-cell infiltration and deficient blood vessel formation in ICP placentas. Our study provides a system-level insight into the placental gene-expression profiles of women with mild or severe ICP, and reveals multiple molecular pathways in immune response and blood vessel formation that might contribute to ICP pathogenesis.

Molecular evolution of a peptide GPCR ligand driven by artificial neural networks.

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Sebastian Bandholtz

Full Text Available Peptide ligands of G protein-coupled receptors constitute valuable natural lead structures for the development of highly selective drugs and high-affinity tools to probe ligand-receptor interaction. Currently, pharmacological and metabolic modification of natural peptides involves either an iterative trial-and-error process based on structure-activity relationships or screening of peptide libraries that contain many structural variants of the native molecule. Here, we present a novel neural network architecture for the improvement of metabolic stability without loss of bioactivity. In this approach the peptide sequence determines the topology of the neural network and each cell corresponds one-to-one to a single amino acid of the peptide chain. Using a training set, the learning algorithm calculated weights for each cell. The resulting network calculated the fitness function in a genetic algorithm to explore the virtual space of all possible peptides. The network training was based on gradient descent techniques which rely on the efficient calculation of the gradient by back-propagation. After three consecutive cycles of sequence design by the neural network, peptide synthesis and bioassay this new approach yielded a ligand with 70fold higher metabolic stability compared to the wild type peptide without loss of the subnanomolar activity in the biological assay. Combining specialized neural networks with an exploration of the combinatorial amino acid sequence space by genetic algorithms represents a novel rational strategy for peptide design and optimization.

Parallel computation with molecular-motor-propelled agents in nanofabricated networks.

Science.gov (United States)

Nicolau, Dan V; Lard, Mercy; Korten, Till; van Delft, Falco C M J M; Persson, Malin; Bengtsson, Elina; Månsson, Alf; Diez, Stefan; Linke, Heiner; Nicolau, Dan V

2016-03-08

The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.

PPAR? population shift produces disease-related changes in molecular networks associated with metabolic syndrome

OpenAIRE

Jurkowski, W; Roomp, K; Crespo, I; Schneider, J G; del Sol, A

2011-01-01

Peroxisome proliferator-activated receptor gamma (PPARγ) is a key regulator of adipocyte differentiation and has an important role in metabolic syndrome. Phosphorylation of the receptor's ligand-binding domain at serine 273 has been shown to change the expression of a large number of genes implicated in obesity. The difference in gene expression seen when comparing wild-type phosphorylated with mutant non-phosphorylated PPARγ may have important consequences for the cellular molecular network,...

Community (in) Colleges: The Relationship Between Online Network Involvement and Academic Outcomes at a Community College

Science.gov (United States)

Evans, Eliza D.; McFarland, Daniel A.; Rios-Aguilar, Cecilia; Deil-Amen, Regina

2016-01-01

Objective: This study explores the relationship between online social network involvement and academic outcomes among community college students. Prior theory hypothesizes that socio-academic moments are especially important for the integration of students into community colleges and that integration is related to academic outcomes. Online social…

Molecular mechanisms involved in the production of chromosomal aberrations. I

International Nuclear Information System (INIS)

Natarajan, A.T.; Obe, G.

1978-01-01

Chinese hamster ovary cells (CHO) were X-irradiated in G2 stage of the cell cycle and immediately treated, in the presence of inactivated Sendai virus, with Neurospora endonuclease (E.C. 3.1.4.), an enzyme which is specific for cleaving single-stranded DNA. With this treatment, the frequencies of all types of chromosome aberrations increased when compared to X-irradiated controls. These results are interpreted as due to the conversion of some of the X-ray induced single-stranded DNA breaks into double-strand breaks by this enzyme. Similar enhancement due to this enzyme was found following treatment with methyl methanesulfonate (MMS) and bleomycin, but not following UV and mitomycin C. Addition of Micrococcus endonuclease and Neurospora endonuclease to the cells did not alter the frequencies of aberrations induced by UV. The introduction of enzymes with specific DNA-repair function offers possibilities to probe into the molecular events involved in the formation of structural chromosome aberrations induced by different classes of physical and chemical mutagens. (Auth.)

Resilient Amorphous Networks Prepared by Photo-Crosslinking High-Molecular-Weight D,L-Lactide and Trimethylene Carbonate Macromers: Mechanical Properties and Shape-Memory Behavior

NARCIS (Netherlands)

Sharifi, Shahriar; Grijpma, Dirk W.

2012-01-01

Tough networks are prepared by photo-crosslinking high-molecular-weight DLLA and TMC macromers. These amorphous networks exhibit tunable thermal and mechanical properties and have excellent shape-memory features. Variation of the monomer ratio allows adjustment of Tg between approximately −13 and

A Computational and Theoretical Study of Conductance in Hydrogen-bonded Molecular Junctions

Science.gov (United States)

Wimmer, Michael

This thesis is devoted to the theoretical and computational study of electron transport in molecular junctions where one or more hydrogen bonds are involved in the process. While electron transport through covalent bonds has been extensively studied, in recent work the focus has been shifted towards hydrogen-bonded systems due to their ubiquitous presence in biological systems and their potential in forming nano-junctions between molecular electronic devices and biological systems. This analysis allows us to significantly expand our comprehension of the experimentally observed result that the inclusion of hydrogen bonding in a molecular junction significantly impacts its transport properties, a fact that has important implications for our understanding of transport through DNA, and nano-biological interfaces in general. In part of this work I have explored the implications of quasiresonant transport in short chains of weakly-bonded molecular junctions involving hydrogen bonds. I used theoretical and computational analysis to interpret recent experiments and explain the role of Fano resonances in the transmission properties of the junction. In a different direction, I have undertaken the study of the transversal conduction through nucleotide chains that involve a variable number of different hydrogen bonds, e.g. NH˙˙˙O, OH˙˙˙O, and NH˙˙˙N, which are the three most prevalent hydrogen bonds in biological systems and organic electronics. My effort here has focused on the analysis of electronic descriptors that allow a simplified conceptual and computational understanding of transport properties. Specifically, I have expanded our previous work where the molecular polarizability was used as a conductance descriptor to include the possibility of atomic and bond partitions of the molecular polarizability. This is important because it affords an alternative molecular description of conductance that is not based on the conventional view of molecular orbitals as

Local stakeholder involvement in the perspective of nuclear waste management: lessons form the Cowam network

International Nuclear Information System (INIS)

Heriard Dubreuil, G.; Gadbois, S.

2004-01-01

The management of high level radioactive waste is nowadays recognised as a complex decision-making process entailing technical, environmental, ethical, social, political and economic dimensions where no solution can be reached solely on the basis of technical considerations. While this issue is acknowledged as a problem for the community as a whole, waste management remains a global problem looking for a local solution. Starting from this view, COWAM network (Community Waste Management), developed under the Fifth Framework Programme of the European Commission, addressed the following objectives: 1) To empower local actors through a networking process; 2) To gather and discuss the available experiences of decision-making processes at the local level within their national context in Europe; 3) To set up an arena for balanced exchanges between local actors, NGOs, regulators and implementers; 4) To promote new approaches to decision-making in national contexts in Europe. COWAM network comprises 230 delegates from 10 European countries, involving in priority local communities and NGOs. The emphasis put on the local participation enabled members of COWAM network to overcome distrust and to build common lessons and views beyond usual stakeholder positions. Through the analysis of case studies different issues were identified, among them two relate more specifically to: 1) Expertise what is the purpose of expertise on environmental impact in the decision-making process? How is this expertise linked with other scientific and non scientific issues? What is the role of stakeholders in expertise? 2) Environmental quality in the long term and sustainable development how is the impact of radioactive waste management facilities on the environment in the long term taken into account? how is this associated with the sustainable development of the hosting community? How are local stakeholders involved in these issues and what is the expected benefit from their participation? (author)

Communication: Fitting potential energy surfaces with fundamental invariant neural network

Energy Technology Data Exchange (ETDEWEB)

Shao, Kejie; Chen, Jun; Zhao, Zhiqiang; Zhang, Dong H., E-mail: zhangdh@dicp.ac.cn [State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, People’s Republic of China and University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China. (China)

2016-08-21

A more flexible neural network (NN) method using the fundamental invariants (FIs) as the input vector is proposed in the construction of potential energy surfaces for molecular systems involving identical atoms. Mathematically, FIs finitely generate the permutation invariant polynomial (PIP) ring. In combination with NN, fundamental invariant neural network (FI-NN) can approximate any function to arbitrary accuracy. Because FI-NN minimizes the size of input permutation invariant polynomials, it can efficiently reduce the evaluation time of potential energy, in particular for polyatomic systems. In this work, we provide the FIs for all possible molecular systems up to five atoms. Potential energy surfaces for OH{sub 3} and CH{sub 4} were constructed with FI-NN, with the accuracy confirmed by full-dimensional quantum dynamic scattering and bound state calculations.

[Motivation and Emotional States: Structural Systemic, Neurochemical, Molecular and Cellular Mechanisms].

Science.gov (United States)

Bazyan, A S

2016-01-01

The structural, systemic, neurochemical, molecular and cellular mechanisms of organization and coding motivation and emotional states are describe. The GABA and glutamatergic synaptic systems of basal ganglia form a neural network and participate in the implementation of voluntary behavior. Neuropeptides, neurohormones and paracrine neuromodulators involved in the organization of motivation and emotional states, integrated with synaptic systems, controlled by neural networks and organizing goal-directed behavior. Structural centers for united and integrated of information in voluntary and goal-directed behavior are globus pallidus. Substantia nigra pars reticulata switches the information from corticobasal networks to thalamocortical networks, induces global dopaminergic (DA) signal and organize interaction of mesolimbic and nigostriatnoy DA systems controlled by prefrontal and motor cortex. Together with the motor cortex, substantia nigra displays information in the brainstem and spinal cord to implementation of behavior. Motivation states are formed in the interaction of neurohormonal and neuropeptide systems by monoaminergic systems of brain. Emotional states are formed by monoaminergic systems of the mid-brain, where the leading role belongs to the mesolimbic DA system. The emotional and motivation state of the encoded specific epigenetic molecular and chemical pattern of neuron.

Biological network extraction from scientific literature: state of the art and challenges.

Science.gov (United States)

Li, Chen; Liakata, Maria; Rebholz-Schuhmann, Dietrich

2014-09-01

Networks of molecular interactions explain complex biological processes, and all known information on molecular events is contained in a number of public repositories including the scientific literature. Metabolic and signalling pathways are often viewed separately, even though both types are composed of interactions involving proteins and other chemical entities. It is necessary to be able to combine data from all available resources to judge the functionality, complexity and completeness of any given network overall, but especially the full integration of relevant information from the scientific literature is still an ongoing and complex task. Currently, the text-mining research community is steadily moving towards processing the full body of the scientific literature by making use of rich linguistic features such as full text parsing, to extract biological interactions. The next step will be to combine these with information from scientific databases to support hypothesis generation for the discovery of new knowledge and the extension of biological networks. The generation of comprehensive networks requires technologies such as entity grounding, coordination resolution and co-reference resolution, which are not fully solved and are required to further improve the quality of results. Here, we analyse the state of the art for the extraction of network information from the scientific literature and the evaluation of extraction methods against reference corpora, discuss challenges involved and identify directions for future research. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

School, Friends, and Substance Use: Gender Differences on the Influence of Attitudes Toward School and Close Friend Networks on Cannabis Involvement.

Science.gov (United States)

Zaharakis, Nikola; Mason, Michael J; Mennis, Jeremy; Light, John; Rusby, Julie C; Westling, Erika; Crewe, Stephanie; Flay, Brian R; Way, Thomas

2018-02-01

The school environment is extremely salient in young adolescents' lives. Adolescents who have unfavorable attitudes toward school and teachers are at elevated risk for dropping out of school and engaging in behavioral health risks. Peer network health-a summation of the positive and negative behaviors in which one's close friend group engages-may be one way by which attitudes toward school exert influence on youth substance use. Utilizing a sample of 248 primarily African-American young urban adolescents, we tested a moderated mediation model to determine if the indirect effect of attitude to school on cannabis involvement through peer network health was conditioned on gender. Attitude toward school measured at baseline was the predictor (X), peer network health measured at 6 months was the mediator (M), cannabis involvement (including use, offers to use, and refusals to use) measured at 24 months was the outcome (Y), and gender was the moderator (W). Results indicated that negative attitudes toward school were indirectly associated with increased cannabis involvement through peer network health. This relationship was not moderated by gender. Adolescents in our sample with negative attitudes toward school were more likely to receive more offers to use cannabis and to use cannabis more frequently through the perceived health behaviors of their close friends. Implications from these results point to opportunities to leverage the dynamic associations among school experiences, friends, and cannabis involvement, such as offers and use.

Multi-tissue omics analyses reveal molecular regulatory networks for puberty in composite beef cattle

Science.gov (United States)

Puberty is a complex physiological event by which animals mature into an adult capable of sexual reproduction. In order to enhance our understanding of the genes and regulatory pathways and networks involved in puberty, we characterized the transcriptome of five reproductive tissues (i.e., hypothal...

Molecular mechanisms involved in convergent crop domestication.

Science.gov (United States)

Lenser, Teresa; Theißen, Günter

2013-12-01

Domestication has helped to understand evolution. We argue that, vice versa, novel insights into evolutionary principles could provide deeper insights into domestication. Molecular analyses have demonstrated that convergent phenotypic evolution is often based on molecular changes in orthologous genes or pathways. Recent studies have revealed that during plant domestication the causal mutations for convergent changes in key traits are likely to be located in particular genes. These insights may contribute to defining candidate genes for genetic improvement during the domestication of new plant species. Such efforts may help to increase the range of arable crops available, thus increasing crop biodiversity and food security to help meet the predicted demands of the continually growing global population under rapidly changing environmental conditions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Functioning and nonfunctioning thyroid adenomas involve different molecular pathogenetic mechanisms.

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Tonacchera, M; Vitti, P; Agretti, P; Ceccarini, G; Perri, A; Cavaliere, R; Mazzi, B; Naccarato, A G; Viacava, P; Miccoli, P; Pinchera, A; Chiovato, L

1999-11-01

The molecular biology of follicular cell growth in thyroid nodules is still poorly understood. Because gain-of-function (activating) mutations of the thyroid-stimulating hormone receptor (TShR) and/or Gs alpha genes may confer TSh-independent growth advantage to neoplastic thyroid cells, we searched for somatic mutations of these genes in a series of hyperfunctioning and nonfunctioning follicular thyroid adenomas specifically selected for their homogeneous gross anatomy (single nodule in an otherwise normal thyroid gland). TShR gene mutations were identified by direct sequencing of exons 9 and 10 of the TShR gene in genomic DNA obtained from surgical specimens. Codons 201 and 227 of the Gs alpha gene were also analyzed. At histology, all hyperfunctioning nodules and 13 of 15 nonfunctioning nodules were diagnosed as follicular adenomas. Two nonfunctioning thyroid nodules, although showing a prevalent microfollicular pattern of growth, had histological features indicating malignant transformation (a minimally invasive follicular carcinoma and a focal papillary carcinoma). Activating mutations of the TShR gene were found in 12 of 15 hyperfunctioning follicular thyroid adenomas. In one hyperfunctioning adenoma, which was negative for TShR mutations, a mutation in codon 227 of the Gs alpha gene was identified. At variance with hyperfunctioning thyroid adenomas, no mutation of the TShR or Gs alpha genes was detected in nonfunctioning thyroid nodules. In conclusion, our findings clearly define a different molecular pathogenetic mechanism in hyperfunctioning and nonfunctioning follicular thyroid adenomas. Activation of the cAMP cascade, which leads to proliferation but maintains differentiation of follicular thyroid cells, typically occurs in hyperfunctioning thyroid adenomas. Oncogenes other than the TShR and Gs alpha genes are probably involved in nonfunctioning follicular adenomas.

Releasing 'brakes' to nerve regeneration: intrinsic molecular targets.

Science.gov (United States)

Krishnan, Anand; Duraikannu, Arul; Zochodne, Douglas W

2016-02-01

Restoring critical neuronal architecture after peripheral nerve injury is challenging. Although immediate regenerative responses to peripheral axon injury involve the synthesis of regeneration-associated proteins in neurons and Schwann cells, an unfavorable balance between growth facilitatory and growth inhibitory signaling impairs the growth continuum of injured peripheral nerves. Molecules involved with the signaling network of tumor suppressors play crucial roles in shifting the balance between growth and restraint during axon regeneration. An understanding of the molecular framework of tumor suppressor molecules in injured neurons and its impact on stage-specific regeneration events may expose therapeutic intervention points. In this review we discuss how signaling networks of the specific tumor suppressors PTEN, Rb1, p53, p27 and p21 are altered in injured peripheral nerves and how this impacts peripheral nerve regeneration. Insights into the roles and importance of these pathways may open new avenues for improving the neurological deficits associated with nerve injury. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Investigation of naphthofuran moiety as potential dual inhibitor against BACE-1 and GSK-3β: molecular dynamics simulations, binding energy, and network analysis to identify first-in-class dual inhibitors against Alzheimer's disease.

Science.gov (United States)

Kumar, Akhil; Srivastava, Gaurava; Srivastava, Swati; Verma, Seema; Negi, Arvind S; Sharma, Ashok

2017-08-01

BACE-1 and GSK-3β are potential therapeutic drug targets for Alzheimer's disease. Recently, both the targets received attention for designing dual inhibitors for Alzheimer's disease. Until now, only two-scaffold triazinone and curcumin have been reported as BACE-1 and GSK-3β dual inhibitors. Docking, molecular dynamics, clustering, binding energy, and network analysis of triazinone derivatives with BACE-1 and GSK-3β was performed to get molecular insight into the first reported dual inhibitor. Further, we designed and evaluated a naphthofuran series for its ability to inhibit BACE-1 and GSK-3β with the computational approaches. Docking study of naphthofuran series showed a good binding affinity towards both the targets. Molecular dynamics, binding energy, and network analysis were performed to compare their binding with the targets and amino acids responsible for binding. Naphthofuran series derivatives showed good interaction within the active site residues of both of the targets. Hydrogen bond occupancy and binding energy suggested strong binding with the targets. Dual-inhibitor binding was mostly governed by the hydrophobic interactions for both of the targets. Per residue energy decomposition and network analysis identified the key residues involved in the binding and inhibiting BACE-1 and GSK-3β. The results indicated that naphthofuran series derivative 11 may be a promising first-in-class dual inhibitor against BACE-1 and GSK-3β. This naphthofuran series may be further explored to design better dual inhibitors. Graphical abstract Naphthofuran derivative as a dual inhibitor for BACE-1 and GSK-3β.

A NETWORK-THEORETICAL APPROACH TO UNDERSTANDING INTERSTELLAR CHEMISTRY

International Nuclear Information System (INIS)

Jolley, Craig C.; Douglas, Trevor

2010-01-01

Recent years have seen dramatic advances in computational models of chemical processes in the interstellar medium (ISM). Typically, these models have been used to calculate changes in chemical abundances with time; the calculated abundances can then be compared with chemical abundances derived from observations. In this study, the output from an astrochemical simulation has been used to generate directed graphs with weighted edges; these have been analyzed with the tools of network theory to uncover whole-network properties of reaction systems in dark molecular clouds. The results allow the development of a model in which global network properties can be rationalized in terms of the basic physical properties of the reaction system. The ISM network exhibits an exponential degree distribution, which is likely to be a generic feature of chemical networks involving a broad range of reaction rate constants. While species abundances span several orders of magnitude, the formation and destruction rates for most species are approximately balanced-departures from this rule indicate species (such as CO) that play a critical role in shaping the dynamics of the system. Future theoretical or observational studies focusing on individual molecular species will be able to situate them in terms of their role in the complete system or quantify the degree to which they deviate from the typical system behavior.

Synthesis of Polyimides in Molecular-Scale Confinement for Low-Density Hybrid Nanocomposites.

Science.gov (United States)

Isaacson, Scott G; Fostvedt, Jade I; Koerner, Hilmar; Baur, Jeffery W; Lionti, Krystelle; Volksen, Willi; Dubois, Geraud; Dauskardt, Reinhold H

2017-11-08

In this work, we exploit a confinement-induced molecular synthesis and a resulting bridging mechanism to create confined polyimide thermoset nanocomposites that couple molecular confinement-enhanced toughening with an unprecedented combination of high-temperature properties at low density. We describe a synthesis strategy that involves the infiltration of individual polymer chains through a nanoscale porous network while simultaneous imidization reactions increase the molecular backbone stiffness. In the extreme limit where the confinement length scale is much smaller than the polymer's molecular size, confinement-induced molecular mechanisms give rise to exceptional mechanical properties. We find that polyimide oligomers can undergo cross-linking reactions even in such molecular-scale confinement, increasing the molecular weight of the organic phase and toughening the nanocomposite through a confinement-induced energy dissipation mechanism. This work demonstrates that the confinement-induced molecular bridging mechanism can be extended to thermoset polymers with multifunctional properties, such as excellent thermo-oxidative stability and high service temperatures (>350 °C).

Pulsed NMR studies of crosslinking and entanglements in high molecular weight linear polydimethylsiloxanes

International Nuclear Information System (INIS)

Folland, R.; Charlesby, A.

1977-01-01

Pulsed NMR studies of proton spin relaxation are used to investigate both radiation-induced cross linking and entanglements in three high molecular weight linear polydimethylsiloxanes (Msub(w) = 26,000, 63,000 and 110,000). Particular emphasis is placed on the spin-spin relaxation since this is determined by the slower relative translational motions of the polymer chains and hence profoundly affected by the presence of intermolecular couplings such as crosslinks or entanglements. The spin-lattice relaxation times, T 1 , are determined by the fast anisotropic chain rotations and are rather insensitive to such intermolecular couplings. The spin-spin relaxation in these materials is represented by a double exponential decay involving two time constants, Tsub(2S) and Tsub(2L). The shorter component, Tsub(2S), is attributed to network material, which may be either of a dynamic form arising from temporary entanglements or of a permanent nature due to crosslinks. The concentration of entanglements depends on the initial molecular weight of the sample whereas the concentration of crosslinks is a function of the radiation dose. The longer component, Tsub(2L), is attributed to the non-network molecules. On the time scale of the NMR measurements the entanglements are shown to act in the same way as crosslinks. The variation of the relative proportions of network and non-network material with dose is shown to be accounted for by using standard gelation theory when allowance is made for the initial effective crosslink density due to entanglements. The analysis provides a value for the average molecular weight per entanglement point of 27,000 +- 1000 which is consistent with the critical molecular weight for entanglements of 29,000. The dependences of Tsub(2S) and Tsub(2L) on dose and molecular weight are also discussed in terms of the molecular motion. (author)

Integration Strategy Is a Key Step in Network-Based Analysis and Dramatically Affects Network Topological Properties and Inferring Outcomes

Science.gov (United States)

Jin, Nana; Wu, Deng; Gong, Yonghui; Bi, Xiaoman; Jiang, Hong; Li, Kongning; Wang, Qianghu

2014-01-01

An increasing number of experiments have been designed to detect intracellular and intercellular molecular interactions. Based on these molecular interactions (especially protein interactions), molecular networks have been built for using in several typical applications, such as the discovery of new disease genes and the identification of drug targets and molecular complexes. Because the data are incomplete and a considerable number of false-positive interactions exist, protein interactions from different sources are commonly integrated in network analyses to build a stable molecular network. Although various types of integration strategies are being applied in current studies, the topological properties of the networks from these different integration strategies, especially typical applications based on these network integration strategies, have not been rigorously evaluated. In this paper, systematic analyses were performed to evaluate 11 frequently used methods using two types of integration strategies: empirical and machine learning methods. The topological properties of the networks of these different integration strategies were found to significantly differ. Moreover, these networks were found to dramatically affect the outcomes of typical applications, such as disease gene predictions, drug target detections, and molecular complex identifications. The analysis presented in this paper could provide an important basis for future network-based biological researches. PMID:25243127

Stakeholder involvement in the management of rural areas following a nuclear accident: the farming network

International Nuclear Information System (INIS)

Mercer, J.; Nisbet, A.F.

2002-01-01

The importance of the participation of stakeholders in the formulation of strategies for maintaining agricultural production and food safety following a nuclear accident, has been successfully demonstrated by the Agriculture and Food Countermeasures Working Group (AFCWG). This group was set up in the UK by the National Radiological Protection Board (NRPB) and the then Ministry of Agriculture, Fisheries and Food in 1997 (Nisbet and Mondon, 2001). Before this time stakeholder organisations had not collectively considered the implications of contamination of the foodchain in the event of an accidental release of radioactivity. With funding from the European Commission (EC) the UK approach to stakeholder engagement is being taken forward on a European basis during the period 2000-2004 through a project given the acronym FARMING (Food and Agriculture Restoration Management Involving Networked Groups). The overall objective of this project is to create a network of stakeholder working groups in 5 member states (UK, Belgium, Finland, France and Greece) to assist in the development of robust and practicable strategies for restoring and managing contaminated agricultural land and food products in a sustainable way. The initial intention was to involve at least 50 individual stakeholders

Genes and Gene Networks Involved in Sodium Fluoride-Elicited Cell Death Accompanying Endoplasmic Reticulum Stress in Oral Epithelial Cells

Directory of Open Access Journals (Sweden)

Yoshiaki Tabuchi

2014-05-01

Full Text Available Here, to understand the molecular mechanisms underlying cell death induced by sodium fluoride (NaF, we analyzed gene expression patterns in rat oral epithelial ROE2 cells exposed to NaF using global-scale microarrays and bioinformatics tools. A relatively high concentration of NaF (2 mM induced cell death concomitant with decreases in mitochondrial membrane potential, chromatin condensation and caspase-3 activation. Using 980 probe sets, we identified 432 up-regulated and 548 down-regulated genes, that were differentially expressed by >2.5-fold in the cells treated with 2 mM of NaF and categorized them into 4 groups by K-means clustering. Ingenuity® pathway analysis revealed several gene networks from gene clusters. The gene networks Up-I and Up-II included many up-regulated genes that were mainly associated with the biological function of induction or prevention of cell death, respectively, such as Atf3, Ddit3 and Fos (for Up-I and Atf4 and Hspa5 (for Up-II. Interestingly, knockdown of Ddit3 and Hspa5 significantly increased and decreased the number of viable cells, respectively. Moreover, several endoplasmic reticulum (ER stress-related genes including, Ddit3, Atf4 and Hapa5, were observed in these gene networks. These findings will provide further insight into the molecular mechanisms of NaF-induced cell death accompanying ER stress in oral epithelial cells.

Molecular interactions involved in proton-dependent gating in KcsA potassium channels

Science.gov (United States)

Posson, David J.; Thompson, Ameer N.; McCoy, Jason G.

2013-01-01

The bacterial potassium channel KcsA is gated open by the binding of protons to amino acids on the intracellular side of the channel. We have identified, via channel mutagenesis and x-ray crystallography, two pH-sensing amino acids and a set of nearby residues involved in molecular interactions that influence gating. We found that the minimal mutation of one histidine (H25) and one glutamate (E118) near the cytoplasmic gate completely abolished pH-dependent gating. Mutation of nearby residues either alone or in pairs altered the channel’s response to pH. In addition, mutations of certain pairs of residues dramatically increased the energy barriers between the closed and open states. We proposed a Monod–Wyman–Changeux model for proton binding and pH-dependent gating in KcsA, where H25 is a “strong” sensor displaying a large shift in pKa between closed and open states, and E118 is a “weak” pH sensor. Modifying model parameters that are involved in either the intrinsic gating equilibrium or the pKa values of the pH-sensing residues was sufficient to capture the effects of all mutations. PMID:24218397

Network-based identification of biomarkers coexpressed with multiple pathways.

Science.gov (United States)

Guo, Nancy Lan; Wan, Ying-Wooi

2014-01-01

Unraveling complex molecular interactions and networks and incorporating clinical information in modeling will present a paradigm shift in molecular medicine. Embedding biological relevance via modeling molecular networks and pathways has become increasingly important for biomarker identification in cancer susceptibility and metastasis studies. Here, we give a comprehensive overview of computational methods used for biomarker identification, and provide a performance comparison of several network models used in studies of cancer susceptibility, disease progression, and prognostication. Specifically, we evaluated implication networks, Boolean networks, Bayesian networks, and Pearson's correlation networks in constructing gene coexpression networks for identifying lung cancer diagnostic and prognostic biomarkers. The results show that implication networks, implemented in Genet package, identified sets of biomarkers that generated an accurate prediction of lung cancer risk and metastases; meanwhile, implication networks revealed more biologically relevant molecular interactions than Boolean networks, Bayesian networks, and Pearson's correlation networks when evaluated with MSigDB database.

Mechanisms and neuronal networks involved in reactive and proactive cognitive control of interference in working memory.

Science.gov (United States)

Irlbacher, Kerstin; Kraft, Antje; Kehrer, Stefanie; Brandt, Stephan A

2014-10-01

Cognitive control can be reactive or proactive in nature. Reactive control mechanisms, which support the resolution of interference, start after its onset. Conversely, proactive control involves the anticipation and prevention of interference prior to its occurrence. The interrelation of both types of cognitive control is currently under debate: Are they mediated by different neuronal networks? Or are there neuronal structures that have the potential to act in a proactive as well as in a reactive manner? This review illustrates the way in which integrating knowledge gathered from behavioral studies, functional imaging, and human electroencephalography proves useful in answering these questions. We focus on studies that investigate interference resolution at the level of working memory representations. In summary, different mechanisms are instrumental in supporting reactive and proactive control. Distinct neuronal networks are involved, though some brain regions, especially pre-SMA, possess functions that are relevant to both control modes. Therefore, activation of these brain areas could be observed in reactive, as well as proactive control, but at different times during information processing. Copyright © 2014 Elsevier Ltd. All rights reserved.

CommWalker: correctly evaluating modules in molecular networks in light of annotation bias.

Science.gov (United States)

Luecken, M D; Page, M J T; Crosby, A J; Mason, S; Reinert, G; Deane, C M

2018-03-15

Detecting novel functional modules in molecular networks is an important step in biological research. In the absence of gold standard functional modules, functional annotations are often used to verify whether detected modules/communities have biological meaning. However, as we show, the uneven distribution of functional annotations means that such evaluation methods favor communities of well-studied proteins. We propose a novel framework for the evaluation of communities as functional modules. Our proposed framework, CommWalker, takes communities as inputs and evaluates them in their local network environment by performing short random walks. We test CommWalker's ability to overcome annotation bias using input communities from four community detection methods on two protein interaction networks. We find that modules accepted by CommWalker are similarly co-expressed as those accepted by current methods. Crucially, CommWalker performs well not only in well-annotated regions, but also in regions otherwise obscured by poor annotation. CommWalker community prioritization both faithfully captures well-validated communities and identifies functional modules that may correspond to more novel biology. The CommWalker algorithm is freely available at opig.stats.ox.ac.uk/resources or as a docker image on the Docker Hub at hub.docker.com/r/lueckenmd/commwalker/. deane@stats.ox.ac.uk. Supplementary data are available at Bioinformatics online.

Characterization of transcription factor networks involved in umbilical cord blood CD34+ stem cells-derived erythropoiesis.

Directory of Open Access Journals (Sweden)

Biaoru Li

Full Text Available Fetal stem cells isolated from umbilical cord blood (UCB possess a great capacity for proliferation and differentiation and serve as a valuable model system to study gene regulation. Expanded knowledge of the molecular control of hemoglobin synthesis will provide a basis for rational design of therapies for β-hemoglobinopathies. Transcriptome data are available for erythroid progenitors derived from adult stem cells, however studies to define molecular mechanisms controlling globin gene regulation during fetal erythropoiesis are limited. Here, we utilize UCB-CD34+ stem cells induced to undergo erythroid differentiation to characterize the transcriptome and transcription factor networks (TFNs associated with the γ/β-globin switch during fetal erythropoiesis. UCB-CD34+ stem cells grown in the one-phase liquid culture system displayed a higher proliferative capacity than adult CD34+ stem cells. The γ/β-globin switch was observed after day 42 during fetal erythropoiesis in contrast to adult progenitors where the switch occurred around day 21. To gain insights into transcription factors involved in globin gene regulation, microarray analysis was performed on RNA isolated from UCB-CD34+ cell-derived erythroid progenitors harvested on day 21, 42, 49 and 56 using the HumanHT-12 Expression BeadChip. After data normalization, Gene Set Enrichment Analysis identified transcription factors (TFs with significant changes in expression during the γ/β-globin switch. Forty-five TFs were silenced by day 56 (Profile-1 and 30 TFs were activated by day 56 (Profile-2. Both GSEA datasets were analyzed using the MIMI Cytoscape platform, which discovered TFNs centered on KLF4 and GATA2 (Profile-1 and KLF1 and GATA1 for Profile-2 genes. Subsequent shRNA studies in KU812 leukemia cells and human erythroid progenitors generated from UCB-CD34+ cells supported a negative role of MAFB in γ-globin regulation. The characteristics of erythroblasts derived from UCB-CD34

Reconstruction, visualization and explorative analysis of human pluripotency network

Directory of Open Access Journals (Sweden)

Priyanka Narad

2017-09-01

Full Text Available Identification of genes/proteins involved in pluripotency and their inter-relationships is important for understanding the induction/loss and maintenance of pluripotency. With the availability of large volume of data on interaction/regulation of pluripotency scattered across a large number of biological databases and hundreds of scientific journals, it is required a systematic integration of data which will create a complete view of pluripotency network. Describing and interpreting such a network of interaction and regulation (i.e., stimulation and inhibition links are essential tasks of computational biology, an important first step in systems-level understanding of the underlying mechanisms of pluripotency. To address this, we have assembled a network of 166 molecular interactions, stimulations and inhibitions, based on a collection of research data from 147 publications, involving 122 human genes/proteins, all in a standard electronic format, enabling analyses by readily available software such as Cytoscape and its Apps (formerly called "Plugins". The network includes the core circuit of OCT4 (POU5F1, SOX2 and NANOG, its periphery (such as STAT3, KLF4, UTF1, ZIC3, and c-MYC, connections to upstream signaling pathways (such as ACTIVIN, WNT, FGF, and BMP, and epigenetic regulators (such as L1TD1, LSD1 and PRC2. We describe the general properties of the network and compare it with other literature-based networks. Gene Ontology (GO analysis is being performed to find out the over-represented GO terms in the network. We use several expression datasets to condense the network to a set of network links that identify the key players (genes/proteins and the pathways involved in transition from one state of pluripotency to other state (i.e., native to primed state, primed to non-pluripotent state and pluripotent to non-pluripotent state.

Reconstructing consensus Bayesian network structures with application to learning molecular interaction networks

NARCIS (Netherlands)

Fröhlich, H.; Klau, G.W.

2013-01-01

Bayesian Networks are an established computational approach for data driven network inference. However, experimental data is limited in its availability and corrupted by noise. This leads to an unavoidable uncertainty about the correct network structure. Thus sampling or bootstrap based strategies

Functional connectivity profile of the human inferior frontal junction: involvement in a cognitive control network

Directory of Open Access Journals (Sweden)

Sundermann Benedikt

2012-10-01

Full Text Available Abstract Background The human inferior frontal junction area (IFJ is critically involved in three main component processes of cognitive control (working memory, task switching and inhibitory control. As it overlaps with several areas in established anatomical labeling schemes, it is considered to be underreported as a functionally distinct location in the neuroimaging literature. While recent studies explicitly focused on the IFJ's anatomical organization and functional role as a single brain area, it is usually not explicitly denominated in studies on cognitive networks. However based on few analyses in small datasets constrained by specific a priori assumptions on its functional specialization, the IFJ has been postulated to be part of a cognitive control network. Goal of this meta-analysis was to establish the IFJ’s connectivity profile on a high formal level of evidence by aggregating published implicit knowledge about its co-activations. We applied meta-analytical connectivity modeling (MACM based on the activation likelihood estimation (ALE method without specific assumptions regarding functional specialization on 180 (reporting left IFJ activity and 131 (right IFJ published functional neuroimaging experiments derived from the BrainMap database. This method is based on coordinates in stereotaxic space, not on anatomical descriptors. Results The IFJ is significantly co-activated with areas in the dorsolateral and ventrolateral prefrontal cortex, anterior insula, medial frontal gyrus / pre-SMA, posterior parietal cortex, occipitotemporal junction / cerebellum, thalamus and putamen as well as language and motor areas. Results are corroborated by an independent resting-state fMRI analysis. Conclusions These results support the assumption that the IFJ is part of a previously described cognitive control network. They also highlight the involvement of subcortical structures in this system. A direct line is drawn from works on the functional

Effect of lifelong football training on the expression of muscle molecular markers involved in healthy longevity

DEFF Research Database (Denmark)

Mancini, A; Vitucci, D; Labruna, G

2017-01-01

PURPOSE: We investigated whether lifelong football training affects the expression of healthy longevity-related muscle molecular markers. METHODS: Biopsies were collected from the vastus lateralis muscle of 10 lifelong football-trained men (68.2 ± 3.0 years) and of 10 active untrained healthy men...... the expression of key markers involved in muscle oxidative metabolism, and in the DNA repair and senescence suppression pathways, thus providing the molecular basis for healthy longevity....... (66.7 ± 1.3 years). Gene and protein expression was measured by RTqPCR on RNA and by western blotting on protein extracts from muscle biopsies, respectively. RESULTS: The expression of AMPKα1/α2, NAMPT, TFAM and PGC1α, which are markers of oxidative metabolism, and MyHC β isoform expression was higher...

The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

Science.gov (United States)

Agnati, Luigi F; Marcoli, Manuela; Maura, Guido; Woods, Amina; Guidolin, Diego

2018-06-01

Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

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

Science.gov (United States)

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.

Influence of Bulk PDMS Network Properties on Water Wettability

Science.gov (United States)

Melillo, Matthew; Walker, Edwin; Klein, Zoe; Efimenko, Kirill; Genzer, Jan

Poly(dimethylsiloxane) (PDMS) is one of the most common elastomers, with applications ranging from sealants and marine antifouling coatings to absorbents for water treatment. Fundamental understanding of how liquids spread on the surface of and absorb into PDMS networks is of critical importance for the design and use of another application - medical devices. We have systematically studied the effects of polymer molecular weight, loading of tetra-functional crosslinker, and end-group chemical functionality on the mechanical and surface properties of end-linked PDMS networks. Wettability was investigated through the sessile drop technique, wherein a DI water droplet was placed on the bulk network surface and droplet volume, shape, surface area, and contact angle were monitored as a function of time. Various silicone substrates ranging from incredibly soft and flexible materials (E' 50 kPa) to highly rigid networks (E' 5 MPa) were tested. The dynamic behavior of the droplet on the surfaces demonstrated equilibration times between the droplet and surface on the order of 5 minutes. Similar trends were observed for the commercial PDMS material, Sylgard-184. Our results have provided new evidence for the strong influence that substrate modulus and molecular network structure have on the wettability of PDMS elastomers. These findings will aid in the design and implementation of efficient, accurate, and safe PDMS-based medical devices and microfluidic materials that involve aqueous media.

An integrated approach of network-based systems biology, molecular docking, and molecular dynamics approach to unravel the role of existing antiviral molecules against AIDS-associated cancer.

Science.gov (United States)

Omer, Ankur; Singh, Poonam

2017-05-01

A serious challenge in cancer treatment is to reposition the activity of various already known drug candidates against cancer. There is a need to rewrite and systematically analyze the detailed mechanistic aspect of cellular networks to gain insight into the novel role played by various molecules. Most Human Immunodeficiency Virus infection-associated cancers are caused by oncogenic viruses like Human Papilloma Viruses and Epstein-Bar Virus. As the onset of AIDS-associated cancers marks the severity of AIDS, there might be possible interconnections between the targets and mechanism of both the diseases. We have explored the possibility of certain antiviral compounds to act against major AIDS-associated cancers: Kaposi's Sarcoma, Non-Hodgkin Lymphoma, and Cervical Cancer with the help of systems pharmacology approach that includes screening for targets and molecules through the construction of a series of drug-target and drug-target-diseases network. Two molecules (Calanolide A and Chaetochromin B) and the target "HRAS" were finally screened with the help of molecular docking and molecular dynamics simulation. The results provide novel antiviral molecules against HRAS target to treat AIDS defining cancers and an insight for understanding the pharmacological, therapeutic aspects of similar unexplored molecules against various cancers.

Convergent Evolution of Hemoglobin Function in High-Altitude Andean Waterfowl Involves Limited Parallelism at the Molecular Sequence Level.

Directory of Open Access Journals (Sweden)

Chandrasekhar Natarajan

2015-12-01

Full Text Available A fundamental question in evolutionary genetics concerns the extent to which adaptive phenotypic convergence is attributable to convergent or parallel changes at the molecular sequence level. Here we report a comparative analysis of hemoglobin (Hb function in eight phylogenetically replicated pairs of high- and low-altitude waterfowl taxa to test for convergence in the oxygenation properties of Hb, and to assess the extent to which convergence in biochemical phenotype is attributable to repeated amino acid replacements. Functional experiments on native Hb variants and protein engineering experiments based on site-directed mutagenesis revealed the phenotypic effects of specific amino acid replacements that were responsible for convergent increases in Hb-O2 affinity in multiple high-altitude taxa. In six of the eight taxon pairs, high-altitude taxa evolved derived increases in Hb-O2 affinity that were caused by a combination of unique replacements, parallel replacements (involving identical-by-state variants with independent mutational origins in different lineages, and collateral replacements (involving shared, identical-by-descent variants derived via introgressive hybridization. In genome scans of nucleotide differentiation involving high- and low-altitude populations of three separate species, function-altering amino acid polymorphisms in the globin genes emerged as highly significant outliers, providing independent evidence for adaptive divergence in Hb function. The experimental results demonstrate that convergent changes in protein function can occur through multiple historical paths, and can involve multiple possible mutations. Most cases of convergence in Hb function did not involve parallel substitutions and most parallel substitutions did not affect Hb-O2 affinity, indicating that the repeatability of phenotypic evolution does not require parallelism at the molecular level.

The neural network involved in a bimanual tactile-tactile matching discrimination task: a functional imaging study at 3 T

Energy Technology Data Exchange (ETDEWEB)

Habas, Christophe; Cabanis, Emmanuel A. [UPMC Paris 6, Service de NeuroImagerie, Hopital des Quinze-Vingts, Paris (France)

2007-08-15

The cerebral and cerebellar network involved in a bimanual object recognition was studied in blood oxygenation dependent level functional magnetic resonance imaging (fMRI). Nine healthy right-handed volunteers were scanned (1) while performing bilateral finger movements (nondiscrimination motor task), and (2) while performing a bimanual tactile-tactile matching discrimination task using small chess pieces (tactile discrimination task). Extensive activations were specifically observed in the parietal (SII, superior lateral lobule), insular, prefrontal, cingulate and neocerebellar cortices (HVIII), with a left predominance in motor areas, during the tactile discrimination task in contrast to the findings during the nondiscrimination motor task. Bimanual tactile-tactile matching discrimination recruits multiple sensorimotor and associative cerebral and neocerebellar networks (including the cerebellar second homunculus, HVIII), comparable to the neural circuits involved in unimanual tactile object recognition. (orig.)

An equal force theory for network models of soft materials with arbitrary molecular weight distribution

Science.gov (United States)

Verron, E.; Gros, A.

2017-09-01

Most network models for soft materials, e.g. elastomers and gels, are dedicated to idealized materials: all chains admit the same number of Kuhn segments. Nevertheless, such standard models are not appropriate for materials involving multiple networks, and some specific constitutive equations devoted to these materials have been derived in the last few years. In nearly all cases, idealized networks of different chain lengths are assembled following an equal strain assumption; only few papers adopt an equal stress assumption, although some authors argue that such hypothesis would reflect the equilibrium of the different networks in contact. In this work, a full-network model with an arbitrary chain length distribution is derived by considering that chains of different lengths satisfy the equal force assumption in each direction of the unit sphere. The derivation is restricted to non-Gaussian freely jointed chains and to affine deformation of the sphere. Firstly, after a proper definition of the undeformed configuration of the network, we demonstrate that the equal force assumption leads to the equality of a normalized stretch in chains of different lengths. Secondly, we establish that the network with chain length distribution behaves as an idealized full-network of which both chain length and density of are provided by the chain length distribution. This approach is finally illustrated with two examples: the derivation of a new expression for the Young modulus of bimodal interpenetrated polymer networks, and the prediction of the change in fluorescence during deformation of mechanochemically responsive elastomers.

A network-based classification model for deriving novel drug-disease associations and assessing their molecular actions.

Directory of Open Access Journals (Sweden)

Min Oh

Full Text Available The growing number and variety of genetic network datasets increases the feasibility of understanding how drugs and diseases are associated at the molecular level. Properly selected features of the network representations of existing drug-disease associations can be used to infer novel indications of existing drugs. To find new drug-disease associations, we generated an integrative genetic network using combinations of interactions, including protein-protein interactions and gene regulatory network datasets. Within this network, network adjacencies of drug-drug and disease-disease were quantified using a scored path between target sets of them. Furthermore, the common topological module of drugs or diseases was extracted, and thereby the distance between topological drug-module and disease (or disease-module and drug was quantified. These quantified scores were used as features for the prediction of novel drug-disease associations. Our classifiers using Random Forest, Multilayer Perceptron and C4.5 showed a high specificity and sensitivity (AUC score of 0.855, 0.828 and 0.797 respectively in predicting novel drug indications, and displayed a better performance than other methods with limited drug and disease properties. Our predictions and current clinical trials overlap significantly across the different phases of drug development. We also identified and visualized the topological modules of predicted drug indications for certain types of cancers, and for Alzheimer's disease. Within the network, those modules show potential pathways that illustrate the mechanisms of new drug indications, including propranolol as a potential anticancer agent and telmisartan as treatment for Alzheimer's disease.

[Prediction of the molecular response to pertubations from single cell measurements].

Science.gov (United States)

Remacle, Françoise; Levine, Raphael D

2014-12-01

The response of protein signalization networks to perturbations is analysed from single cell measurements. This experimental approach allows characterizing the fluctuations in protein expression levels from cell to cell. The analysis is based on an information theoretic approach grounded in thermodynamics leading to a quantitative version of Le Chatelier principle which allows to predict the molecular response. Two systems are investigated: human macrophages subjected to lipopolysaccharide challenge, analogous to the immune response against Gram-negative bacteria and the response of the proteins involved in the mTOR signalizing network of GBM cancer cells to changes in partial oxygen pressure. © 2014 médecine/sciences – Inserm.

2D-HB-Network at the air-water interface: A structural and dynamical characterization by means of ab initio and classical molecular dynamics simulations

Science.gov (United States)

Pezzotti, Simone; Serva, Alessandra; Gaigeot, Marie-Pierre

2018-05-01

Following our previous work where the existence of a special 2-Dimensional H-Bond (2D-HB)-Network was revealed at the air-water interface [S. Pezzotti et al., J. Phys. Chem. Lett. 8, 3133 (2017)], we provide here a full structural and dynamical characterization of this specific arrangement by means of both Density Functional Theory based and Force Field based molecular dynamics simulations. We show in particular that water at the interface with air reconstructs to maximize H-Bonds formed between interfacial molecules, which leads to the formation of an extended and non-interrupted 2-Dimensional H-Bond structure involving on average ˜90% of water molecules at the interface. We also show that the existence of such an extended structure, composed of H-Bonds all oriented parallel to the surface, constrains the reorientional dynamics of water that is hence slower at the interface than in the bulk. The structure and dynamics of the 2D-HB-Network provide new elements to possibly rationalize several specific properties of the air-water interface, such as water surface tension, anisotropic reorientation of interfacial water under an external field, and proton hopping.

A systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.

Science.gov (United States)

Yu, Chenggang; Boutté, Angela; Yu, Xueping; Dutta, Bhaskar; Feala, Jacob D; Schmid, Kara; Dave, Jitendra; Tawa, Gregory J; Wallqvist, Anders; Reifman, Jaques

2015-02-01

The multifactorial nature of traumatic brain injury (TBI), especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior, has confounded attempts to elucidate the pathology underlying the progression of TBI. Here, systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury. To this end, we performed a meta-analysis of four distinct high-throughput gene expression studies involving different animal models of TBI. By using canonical pathways and a large human protein-interaction network as a scaffold, we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies. At 24 hr after injury, the significantly activated molecular signatures were nonspecific to TBI, whereas the significantly suppressed molecular signatures were specific to the nervous system. In particular, we identified a suppressed subnetwork consisting of 58 highly interacting, coregulated proteins associated with synaptic function. We selected three proteins from this subnetwork, postsynaptic density protein 95, nitric oxide synthase 1, and disrupted in schizophrenia 1, and hypothesized that their abundance would be significantly reduced after TBI. In a penetrating ballistic-like brain injury rat model of severe TBI, Western blot analysis confirmed our hypothesis. In addition, our analysis recovered 12 previously identified protein biomarkers of TBI. The results suggest that systems biology may provide an efficient, high-yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI. © 2014 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

A novel heat shock protein alpha 8 (Hspa8) molecular network mediating responses to stress- and ethanol-related behaviors.

Science.gov (United States)

Urquhart, Kyle R; Zhao, Yinghong; Baker, Jessica A; Lu, Ye; Yan, Lei; Cook, Melloni N; Jones, Byron C; Hamre, Kristin M; Lu, Lu

2016-04-01

Genetic differences mediate individual differences in susceptibility and responses to stress and ethanol, although, the specific molecular pathways that control these responses are not fully understood. Heat shock protein alpha 8 (Hspa8) is a molecular chaperone and member of the heat shock protein family that plays an integral role in the stress response and that has been implicated as an ethanol-responsive gene. Therefore, we assessed its role in mediating responses to stress and ethanol across varying genetic backgrounds. The hippocampus is an important mediator of these responses, and thus, was examined in the BXD family of mice in this study. We conducted bioinformatic analyses to dissect genetic factors modulating Hspa8 expression, identify downstream targets of Hspa8, and examined its role. Hspa8 is trans-regulated by a gene or genes on chromosome 14 and is part of a molecular network that regulates stress- and ethanol-related behaviors. To determine additional components of this network, we identified direct or indirect targets of Hspa8 and show that these genes, as predicted, participate in processes such as protein folding and organic substance metabolic processes. Two phenotypes that map to the Hspa8 locus are anxiety-related and numerous other anxiety- and/or ethanol-related behaviors significantly correlate with Hspa8 expression. To more directly assay this relationship, we examined differences in gene expression following exposure to stress or alcohol and showed treatment-related differential expression of Hspa8 and a subset of the members of its network. Our findings suggest that Hspa8 plays a vital role in genetic differences in responses to stress and ethanol and their interactions.

Competing dynamic phases of active polymer networks

Science.gov (United States)

Freedman, Simon; Banerjee, Shiladitya; Dinner, Aaron R.

Recent experiments on in-vitro reconstituted assemblies of F-actin, myosin-II motors, and cross-linking proteins show that tuning local network properties can changes the fundamental biomechanical behavior of the system. For example, by varying cross-linker density and actin bundle rigidity, one can switch between contractile networks useful for reshaping cells, polarity sorted networks ideal for directed molecular transport, and frustrated networks with robust structural properties. To efficiently investigate the dynamic phases of actomyosin networks, we developed a coarse grained non-equilibrium molecular dynamics simulation of model semiflexible filaments, molecular motors, and cross-linkers with phenomenologically defined interactions. The simulation's accuracy was verified by benchmarking the mechanical properties of its individual components and collective behavior against experimental results at the molecular and network scales. By adjusting the model's parameters, we can reproduce the qualitative phases observed in experiment and predict the protein characteristics where phase crossovers could occur in collective network dynamics. Our model provides a framework for understanding cells' multiple uses of actomyosin networks and their applicability in materials research. Supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

High-Throughput Sequencing and Linkage Mapping of a Clownfish Genome Provide Insights on the Distribution of Molecular Players Involved in Sex Change.

Science.gov (United States)

Casas, Laura; Saenz-Agudelo, Pablo; Irigoien, Xabier

2018-03-06

Clownfishes are an excellent model system for investigating the genetic mechanism governing hermaphroditism and socially-controlled sex change in their natural environment because they are broadly distributed and strongly site-attached. Genomic tools, such as genetic linkage maps, allow fine-mapping of loci involved in molecular pathways underlying these reproductive processes. In this study, a high-density genetic map of Amphiprion bicinctus was constructed with 3146 RAD markers in a full-sib family organized in 24 robust linkage groups which correspond to the haploid chromosome number of the species. The length of the map was 4294.71 cM, with an average marker interval of 1.38 cM. The clownfish linkage map showed various levels of conserved synteny and collinearity with the genomes of Asian and European seabass, Nile tilapia and stickleback. The map provided a platform to investigate the genomic position of genes with differential expression during sex change in A. bicinctus. This study aims to bridge the gap of genome-scale information for this iconic group of species to facilitate the study of the main gene regulatory networks governing social sex change and gonadal restructuring in protandrous hermaphrodites.

High-Throughput Sequencing and Linkage Mapping of a Clownfish Genome Provide Insights on the Distribution of Molecular Players Involved in Sex Change

KAUST Repository

Casas, Laura

2018-02-28

Clownfishes are an excellent model system for investigating the genetic mechanism governing hermaphroditism and socially-controlled sex change in their natural environment because they are broadly distributed and strongly site-attached. Genomic tools, such as genetic linkage maps, allow fine-mapping of loci involved in molecular pathways underlying these reproductive processes. In this study, a high-density genetic map of Amphiprion bicinctus was constructed with 3146 RAD markers in a full-sib family organized in 24 robust linkage groups which correspond to the haploid chromosome number of the species. The length of the map was 4294.71 cM, with an average marker interval of 1.38 cM. The clownfish linkage map showed various levels of conserved synteny and collinearity with the genomes of Asian and European seabass, Nile tilapia and stickleback. The map provided a platform to investigate the genomic position of genes with differential expression during sex change in A. bicinctus. This study aims to bridge the gap of genome-scale information for this iconic group of species to facilitate the study of the main gene regulatory networks governing social sex change and gonadal restructuring in protandrous hermaphrodites.

Second meeting of the Atomic and Molecular Data Centre network. Fontenay aux Roses, 23-24 May 1980

International Nuclear Information System (INIS)

Katsonis, K.

1980-11-01

Summary report of the Second A+M Data Centre Network (DCN) meeting convened by the IAEA Nuclear Data Section at the CEA Laboratory at Fontenay-aux-Roses, France, 23-24 May 1980. The meeting was attended by 20 representatives from centres and groups from six Member States concerned with the coordinated international management of atomic and molecular data pertinent to controlled fusion research and technology

When Sharing Is a Bad Idea: The Effects of Online Social Network Engagement and Sharing Passwords with Friends on Cyberbullying Involvement.

Science.gov (United States)

Meter, Diana J; Bauman, Sheri

2015-08-01

Every day, children and adolescents communicate online via social networking sites (SNSs). They also report sharing passwords with peers and friends, a potentially risky behavior in regard to cyber safety. This longitudinal study tested the hypotheses that social network engagement in multiple settings would predict more cyberbullying involvement over time, and that youth who reported sharing passwords would also experience an increase in cyberbullying involvement. Data were collected at two time points one year apart from 1,272 third through eighth grade students. In line with the first study hypothesis, participating in more online SNSs was associated with increased cyberbullying involvement over time, as well as sharing passwords over time. Cyberbullying involvement at T1 predicted decreases in sharing passwords over time, suggesting that youth become aware of the dangers of sharing passwords as a result of their experience. Sharing passwords at T1 was unrelated to cyberbullying involvement at T2. Although it seems that youth may be learning from their previous mistakes, due to the widespread use of social media and normality of sharing passwords among young people, it is important to continue to educate youth about cyber safety and risky online behavior.

Decoding network dynamics in cancer

DEFF Research Database (Denmark)

Linding, Rune

2014-01-01

Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language and with an accur......Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language...... and with an accuracy that parallels our characterisation of other physical systems such as Jumbo-jets. Decades of targeted molecular and biological studies have led to numerous pathway models of developmental and disease related processes. However, so far no global models have been derived from pathways, capable...

Molecular scale

Directory of Open Access Journals (Sweden)

Christopher H. Childers

2016-03-01

Full Text Available This manuscript demonstrates the molecular scale cure rate dependence of di-functional epoxide based thermoset polymers cured with amines. A series of cure heating ramp rates were used to determine the influence of ramp rate on the glass transition temperature (Tg and sub-Tg transitions and the average free volume hole size in these systems. The networks were comprised of 3,3′-diaminodiphenyl sulfone (33DDS and diglycidyl ether of bisphenol F (DGEBF and were cured at ramp rates ranging from 0.5 to 20 °C/min. Differential scanning calorimetry (DSC and NIR spectroscopy were used to explore the cure ramp rate dependence of the polymer network growth, whereas broadband dielectric spectroscopy (BDS and free volume hole size measurements were used to interrogate networks’ molecular level structural variations upon curing at variable heating ramp rates. It was found that although the Tg of the polymer matrices was similar, the NIR and DSC measurements revealed a strong correlation for how these networks grow in relation to the cure heating ramp rate. The free volume analysis and BDS results for the cured samples suggest differences in the molecular architecture of the matrix polymers due to cure heating rate dependence.

Assessing the heritability of attentional networks

Directory of Open Access Journals (Sweden)

Fossella John A

2001-09-01

Full Text Available Abstract Background Current efforts to study the genetics of higher functions have been lacking appropriate phenotypes to describe cognition. One of the problems is that many cognitive concepts for which there is a single word (e.g. attention have been shown to be related to several anatomical networks. Recently we have developed an Attention Network Test (ANT that provides a separate measure for each of three anatomically defined attention networks. In this small scale study, we ran 26 pairs of MZ and DZ twins in an effort to determine if any of these networks show sufficient evidence of heritability to warrant further exploration of their genetic basis. Results The efficiency of the executive attention network, that mediates stimulus and response conflict, shows sufficient heritability to warrant further study. Alerting and overall reaction time show some evidence for heritability and in our study the orienting network shows no evidence of heritability. Conclusions These results suggest that genetic variation contributes to normal individual differences in higher order executive attention involving dopamine rich frontal areas including the anterior cingulate. At least the executive portion of the ANT may serve as a valid endophenotype for larger twin studies and subsequent molecular genetic analysis in normal subject populations.

Heat exchanger network retrofit optimization involving heat transfer enhancement

International Nuclear Information System (INIS)

Wang Yufei; Smith, Robin; Kim, Jin-Kuk

2012-01-01

Heat exchanger network retrofit plays an important role in energy saving in process industry. Many design methods for the retrofit of heat exchanger networks have been proposed during the last three decades. Conventional retrofit methods rely heavily on topology modifications which often result in a long retrofit duration and high initial costs. Moreover, the addition of extra surface area to the heat exchanger can prove difficult due to topology, safety and downtime constraints. Both of these problems can be avoided through the use of heat transfer enhancement in heat exchanger network retrofit. This paper presents a novel design approach to solve heat exchanger network retrofit problems based on heat transfer enhancement. An optimisation method based on simulated annealing has been developed to find the appropriate heat exchangers to be enhanced and to calculate the level of enhancement required. The physical insight of enhanced exchangers is also analysed. The new methodology allows several possible retrofit strategies using different retrofit methods be determined. Comparison of these retrofit strategies demonstrates that retrofit modification duration and payback time are reduced when heat transfer enhancement is utilised. Heat transfer enhancement can be also used as a substitute for increased heat exchanger network surface area to reduce retrofit investment costs.

Current update on established and novel biomarkers in salivary gland carcinoma pathology and the molecular pathways involved.

Science.gov (United States)

Stenner, Markus; Klussmann, J Peter

2009-03-01

This review aims to take stock of the new information that has accumulated over the past decade on the molecular pathology of salivary gland cancer. Emphasis will be placed on established and novel immunohistochemical markers, the pathways involved, and on findings of prognostic importance as well as new therapeutic concepts. Whenever reasonable, analogies to tumors of better explored, histologically related glandular organs such as pancreas and breast are established.

Optimality principles in the regulation of metabolic networks

NARCIS (Netherlands)

Berkhout, J.; Bruggeman, F.J.; Teusink, B.

2012-01-01

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks

Molecular mechanisms of aging and immune system regulation in Drosophila.

Science.gov (United States)

Eleftherianos, Ioannis; Castillo, Julio Cesar

2012-01-01

Aging is a complex process that involves the accumulation of deleterious changes resulting in overall decline in several vital functions, leading to the progressive deterioration in physiological condition of the organism and eventually causing disease and death. The immune system is the most important host-defense mechanism in humans and is also highly conserved in insects. Extensive research in vertebrates has concluded that aging of the immune function results in increased susceptibility to infectious disease and chronic inflammation. Over the years, interest has grown in studying the molecular interaction between aging and the immune response to pathogenic infections. The fruit fly Drosophila melanogaster is an excellent model system for dissecting the genetic and genomic basis of important biological processes, such as aging and the innate immune system, and deciphering parallel mechanisms in vertebrate animals. Here, we review the recent advances in the identification of key players modulating the relationship between molecular aging networks and immune signal transduction pathways in the fly. Understanding the details of the molecular events involved in aging and immune system regulation will potentially lead to the development of strategies for decreasing the impact of age-related diseases, thus improving human health and life span.

A spiking network model of cerebellar Purkinje cells and molecular layer interneurons exhibiting irregular firing

Directory of Open Access Journals (Sweden)

William eLennon

2014-12-01

Full Text Available While the anatomy of the cerebellar microcircuit is well studied, how it implements cerebellar function is not understood. A number of models have been proposed to describe this mechanism but few emphasize the role of the vast network Purkinje cells (PKJs form with the molecular layer interneurons (MLIs – the stellate and basket cells. We propose a model of the MLI-PKJ network composed of simple spiking neurons incorporating the major anatomical and physiological features. In computer simulations, the model reproduces the irregular firing patterns observed in PKJs and MLIs in vitro and a shift toward faster, more regular firing patterns when inhibitory synaptic currents are blocked. In the model, the time between PKJ spikes is shown to be proportional to the amount of feedforward inhibition from an MLI on average. The two key elements of the model are: (1 spontaneously active PKJs and MLIs due to an endogenous depolarizing current, and (2 adherence to known anatomical connectivity along a parasagittal strip of cerebellar cortex. We propose this model to extend previous spiking network models of the cerebellum and for further computational investigation into the role of irregular firing and MLIs in cerebellar learning and function.

Comparative MiRNA Expressional Profiles and Molecular Networks in Human Small Bowel Tissues of Necrotizing Enterocolitis and Spontaneous Intestinal Perforation.

Directory of Open Access Journals (Sweden)

Pak Cheung Ng

Full Text Available Necrotizing enterocolitis (NEC and spontaneous intestinal perforation (SIP are acute intestinal conditions which could result in mortality and severe morbidity in preterm infants. Our objective was to identify dysregulated micro-RNAs (miRNAs in small bowel tissues of NEC and SIP, and their possible roles in disease pathophysiology.We performed differential miRNA arrays on tissues of NEC (n = 4, SIP (n = 4 and surgical-control (Surg-CTL; n = 4, and validated target miRNAs by qPCR (n = 10 each group. The association of target miRNAs with 52 dysregulated mRNAs was investigated by bioinformatics on functional and base-pair sequence algorithms, and correlation in same tissue samples.We presented the first miRNA profiles of NEC, SIP and Surg-CTL intestinal tissues in preterm infants. Of 28 validated miRNAs, 21 were significantly different between NEC or SIP and Surg-CTL. Limited overlapping in the aberrant expression of miRNAs between NEC and SIP indicated their distinct molecular mechanisms. A proposed network of dysregulated miRNA/mRNA pairs in NEC suggested interaction at bacterial receptor TLR4 (miR-31, miR-451, miR-203, miR-4793-3p, mediated via key transcription factors NFKB2 (miR-203, AP-1/FOSL1 (miR-194-3p, FOXA1 (miR-21-3p, miR-431 and miR-1290 and HIF1A (miR-31, and extended downstream to pathways of angiogenesis, arginine metabolism, cell adhesion and chemotaxis, extracellular matrix remodeling, hypoxia/oxidative stress, inflammation and muscle contraction. In contrast, upregulation of miR-451 and miR-223 in SIP suggested modulation of G-protein-mediated muscle contraction.The robust response of miRNA dysregulation in NEC and SIP, and concerted involvement of specific miRNAs in the molecular networks indicated their crucial roles in mucosa integrity and disease pathophysiology.

Flow network QSAR for the prediction of physicochemical properties by mapping an electrical resistance network onto a chemical reaction poset.

Science.gov (United States)

Ivanciuc, Ovidiu; Ivanciuc, Teodora; Klein, Douglas J

2013-06-01

Usual quantitative structure-activity relationship (QSAR) models are computed from unstructured input data, by using a vector of molecular descriptors for each chemical in the dataset. Another alternative is to consider the structural relationships between the chemical structures, such as molecular similarity, presence of certain substructures, or chemical transformations between compounds. We defined a class of network-QSAR models based on molecular networks induced by a sequence of substitution reactions on a chemical structure that generates a partially ordered set (or poset) oriented graph that may be used to predict various molecular properties with quantitative superstructure-activity relationships (QSSAR). The network-QSAR interpolation models defined on poset graphs, namely average poset, cluster expansion, and spline poset, were tested with success for the prediction of several physicochemical properties for diverse chemicals. We introduce the flow network QSAR, a new poset regression model in which the dataset of chemicals, represented as a reaction poset, is transformed into an oriented network of electrical resistances in which the current flow results in a potential at each node. The molecular property considered in the QSSAR model is represented as the electrical potential, and the value of this potential at a particular node is determined by the electrical resistances assigned to each edge and by a system of batteries. Each node with a known value for the molecular property is attached to a battery that sets the potential on that node to the value of the respective molecular property, and no external battery is attached to nodes from the prediction set, representing chemicals for which the values of the molecular property are not known or are intended to be predicted. The flow network QSAR algorithm determines the values of the molecular property for the prediction set of molecules by applying Ohm's law and Kirchhoff's current law to the poset

Analysis of molecular markers as predictive factors of lymph node involvement in breast carcinoma.

Science.gov (United States)

Paula, Luciana Marques; De Moraes, Luis Henrique Ferreira; Do Canto, Abaeté Leite; Dos Santos, Laurita; Martin, Airton Abrahão; Rogatto, Silvia Regina; De Azevedo Canevari, Renata

2017-01-01

Nodal status is the most significant independent prognostic factor in breast cancer. Identification of molecular markers would allow stratification of patients who require surgical assessment of lymph nodes from the large numbers of patients for whom this surgical procedure is unnecessary, thus leading to a more accurate prognosis. However, up to now, the reported studies are preliminary and controversial, and although hundreds of markers have been assessed, few of them have been used in clinical practice for treatment or prognosis in breast cancer. The purpose of the present study was to determine whether protein phosphatase Mg2+/Mn2+ dependent 1D, β-1,3-N-acetylglucosaminyltransferase, neural precursor cell expressed, developmentally down-regulated 9, prohibitin, phosphoinositide-3-kinase regulatory subunit 5 (PIK3R5), phosphatidylinositol-5-phosphate 4-kinase type IIα, TRF1-interacting ankyrin-related ADP-ribose polymerase 2, BCL2 associated agonist of cell death, G2 and S-phase expressed 1 and PAX interacting protein 1 genes, described as prognostic markers in breast cancer in a previous microarray study, are also predictors of lymph node involvement in breast carcinoma Reverse transcription-quantitative polymerase chain reaction analysis was performed on primary breast tumor tissues from women with negative lymph node involvement (n=27) compared with primary tumor tissues from women with positive lymph node involvement (n=23), and was also performed on primary tumors and paired lymph node metastases (n=11). For all genes analyzed, only the PIK3R5 gene exhibited differential expression in samples of primary tumors with positive lymph node involvement compared with primary tumors with negative lymph node involvement (P=0.0347). These results demonstrate that the PIK3R5 gene may be considered predictive of lymph node involvement in breast carcinoma. Although the other genes evaluated in the present study have been previously characterized to be involved with

Structuring an integrated care system: interpreted through the enacted diversity of the actors involved – the case of a French healthcare network

Directory of Open Access Journals (Sweden)

Corinne Grenier

2011-02-01

Full Text Available Research question: We are looking at the process of structuring an integrated care system as an innovative process that swings back and forth between the diversity of the actors involved, local aspirations and national and regional regulations. We believe that innovation is enriched by the variety of the actors involved, but may also be blocked or disrupted by that diversity. Our research aims to add to other research, which, when questioning these integrated systems, analyses how the actors involved deal with diversity without really questioning it. Case study: The empirical basis of the paper is provided by case study analysis. The studied integrated care system is a French healthcare network that brings together healthcare professionals and various organisations in order to improve the way in which interventions are coordinated and formalised, in order to promote better detection and diagnosis procedures and the implementation of a care protocol. We consider this case as instrumental in developing theoretical proposals for structuring an integrated care system in light of the diversity of the actors involved. Results and discussion: We are proposing a model for structuring an integrated care system in light of the enacted diversity of the actors involved. This model is based on three factors: the diversity enacted by the leaders, three stances for considering the contribution made by diversity in the structuring process and the specific leading role played by those in charge of the structuring process.  Through this process, they determined how the actors involved in the project were differentiated, and on what basis those actors were involved. By mobilizing enacted diversity, the leaders are seeking to channel the emergence of a network in light of their own representation of that network. This model adds to published research on the structuring of integrated care systems.

Structuring an integrated care system: interpreted through the enacted diversity of the actors involved – the case of a French healthcare network

Directory of Open Access Journals (Sweden)

Corinne Grenier

2011-02-01

Full Text Available Research question: We are looking at the process of structuring an integrated care system as an innovative process that swings back and forth between the diversity of the actors involved, local aspirations and national and regional regulations. We believe that innovation is enriched by the variety of the actors involved, but may also be blocked or disrupted by that diversity. Our research aims to add to other research, which, when questioning these integrated systems, analyses how the actors involved deal with diversity without really questioning it.Case study: The empirical basis of the paper is provided by case study analysis. The studied integrated care system is a French healthcare network that brings together healthcare professionals and various organisations in order to improve the way in which interventions are coordinated and formalised, in order to promote better detection and diagnosis procedures and the implementation of a care protocol. We consider this case as instrumental in developing theoretical proposals for structuring an integrated care system in light of the diversity of the actors involved.Results and discussion: We are proposing a model for structuring an integrated care system in light of the enacted diversity of the actors involved. This model is based on three factors: the diversity enacted by the leaders, three stances for considering the contribution made by diversity in the structuring process and the specific leading role played by those in charge of the structuring process.  Through this process, they determined how the actors involved in the project were differentiated, and on what basis those actors were involved. By mobilizing enacted diversity, the leaders are seeking to channel the emergence of a network in light of their own representation of that network. This model adds to published research on the structuring of integrated care systems.

Molecular hydrogen is involved in phytohormone signaling and stress responses in plants.

Directory of Open Access Journals (Sweden)

Jiqing Zeng

Full Text Available Molecular hydrogen (H2 metabolism in bacteria and algae has been well studied from an industrial perspective because H2 is viewed as a potential future energy source. A number of clinical trials have recently reported that H2 is a therapeutic antioxidant and signaling molecule. Although H2 metabolism in higher plants was reported in some early studies, its biological effects remain unclear. In this report, the biological effects of H2 and its involvement in plant hormone signaling pathways and stress responses were determined. Antioxidant enzyme activity was found to be increased and the transcription of corresponding genes altered when the effects of H2 on the germination of mung bean seeds treated with phytohormones was investigated. In addition, upregulation of several phytohormone receptor genes and genes that encode a few key factors involved in plant signaling pathways was detected in rice seedlings treated with HW. The transcription of putative rice hydrogenase genes, hydrogenase activity, and endogenous H2 production were also determined. H2 production was found to be induced by abscisic acid, ethylene, and jasmonate acid, salt, and drought stress and was consistent with hydrogenase activity and the expression of putative hydrogenase genes in rice seedlings. Together, these results suggest that H2 may have an effect on rice stress tolerance by modulating the output of hormone signaling pathways.

A comparative modeling and molecular docking study on Mycobacterium tuberculosis targets involved in peptidoglycan biosynthesis.

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Fakhar, Zeynab; Naiker, Suhashni; Alves, Claudio N; Govender, Thavendran; Maguire, Glenn E M; Lameira, Jeronimo; Lamichhane, Gyanu; Kruger, Hendrik G; Honarparvar, Bahareh

2016-11-01

An alarming rise of multidrug-resistant Mycobacterium tuberculosis strains and the continuous high global morbidity of tuberculosis have reinvigorated the need to identify novel targets to combat the disease. The enzymes that catalyze the biosynthesis of peptidoglycan in M. tuberculosis are essential and noteworthy therapeutic targets. In this study, the biochemical function and homology modeling of MurI, MurG, MraY, DapE, DapA, Alr, and Ddl enzymes of the CDC1551 M. tuberculosis strain involved in the biosynthesis of peptidoglycan cell wall are reported. Generation of the 3D structures was achieved with Modeller 9.13. To assess the structural quality of the obtained homology modeled targets, the models were validated using PROCHECK, PDBsum, QMEAN, and ERRAT scores. Molecular dynamics simulations were performed to calculate root mean square deviation (RMSD) and radius of gyration (Rg) of MurI and MurG target proteins and their corresponding templates. For further model validation, RMSD and Rg for selected targets/templates were investigated to compare the close proximity of their dynamic behavior in terms of protein stability and average distances. To identify the potential binding mode required for molecular docking, binding site information of all modeled targets was obtained using two prediction algorithms. A docking study was performed for MurI to determine the potential mode of interaction between the inhibitor and the active site residues. This study presents the first accounts of the 3D structural information for the selected M. tuberculosis targets involved in peptidoglycan biosynthesis.

A proposal to establish an international network in molecular microbiology and genetic engineering for scientific cooperation and prevention of misuse of biological sciences in the framework of science for peace

International Nuclear Information System (INIS)

Becker, Y.

1998-01-01

The conference on 'Science and Technology for Construction of Peace' which was organized by the Landau Network Coordination Center and A. Volta Center for Scientific Culture dealt with conversion of military and technological capacities into sustainable civilian application. The ideas regarding the conversion of nuclear warheads into nuclear energy for civilian-use led to the idea that the extension of this trend of thought to molecular biology and genetic engineering, will be a useful contribution to Science for Peace. This idea of developing a Cooperation Network in Molecular Biology and Genetic Engineering that will function parallel to and with the Landau Network Coordination in the 'A. Volta' Center was discussed in the Second International Symposium on Science for Peace, Jerusalem, January 1997. It is the reason for the inclusion of the biological aspects in the deliberations of our Forum. It is hoped that the establishment of an international network in molecular biology and genetic engineering, similar to the Landau Network in physics, will support and achieve the decommissioning of biological weapons. Such a network in microbiology and genetic engineering will contribute to the elimination of biological weapons and to contributions to Science for Peace and to Culture of Peace activities of UNESCO. (author)

An Unprecedented Blue Chromophore Found in Nature using a "Chemistry First" and Molecular Networking Approach: Discovery of Dactylocyanines A-H.

Science.gov (United States)

Bonneau, Natacha; Chen, Guanming; Lachkar, David; Boufridi, Asmaa; Gallard, Jean-François; Retailleau, Pascal; Petek, Sylvain; Debitus, Cécile; Evanno, Laurent; Beniddir, Mehdi A; Poupon, Erwan

2017-10-17

Guided by a "chemistry first" approach using molecular networking, eight new bright-blue colored natural compounds, namely dactylocyanines A-H (3-10), were isolated from the Polynesian marine sponge Dactylospongia metachromia. Starting from ilimaquinone (1), an hemisynthetic phishing probe (2) was prepared for annotating and matching structurally related natural substances in D. metachromia crude extract network. This strategy allowed characterizing for the first time in Nature the blue zwitterionic quinonoid chromophore. The solvatochromic properties of the latter are reported. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Final Report: Photo-Directed Molecular Assembly of Multifunctional Inorganic Materials

Energy Technology Data Exchange (ETDEWEB)

B.G. Potter, Jr.

2010-10-15

This final report details results, conclusions, and opportunities for future effort derived from the study. The work involved combining the molecular engineering of photoactive Ti-alkoxide systems and the optical excitation of hydrolysis and condensation reactions to influence the development of the metal-oxygen-metal network at the onset of material formation. Selective excitation of the heteroleptic alkoxides, coupled with control of alkoxide local chemical environment, enabled network connectivity to be influenced and formed the basis for direct deposition and patterning of Ti-oxide-based materials. The research provided new insights into the intrinsic photoresponse and assembly of these complex, alkoxide molecules. Using a suite of electronic, vibrational, and nuclear spectroscopic probes, coupled with quantum chemical computation, the excitation wavelength and fluence dependence of molecular photoresponse and the nature of subsequent hydrolysis and condensation processes were probed in pyridine-carbinol-based Ti-alkoxides with varied counter ligand groups. Several methods for the patterning of oxide material formation were demonstrated, including the integration of this photoprocessing approach with conventional, dip-coating methodologies.

Discrete dynamic modeling of cellular signaling networks.

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Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Molecular dynamics study on the evolution of interfacial dislocation network and mechanical properties of Ni-based single crystal superalloys

Science.gov (United States)

Li, Nan-Lin; Wu, Wen-Ping; Nie, Kai

2018-05-01

The evolution of misfit dislocation network at γ /γ‧ phase interface and tensile mechanical properties of Ni-based single crystal superalloys at various temperatures and strain rates are studied by using molecular dynamics (MD) simulations. From the simulations, it is found that with the increase of loading, the dislocation network effectively inhibits dislocations emitted in the γ matrix cutting into the γ‧ phase and absorbs the matrix dislocations to strengthen itself which increases the stability of structure. Under the influence of the temperature, the initial mosaic structure of dislocation network gradually becomes irregular, and the initial misfit stress and the elastic modulus slowly decline as temperature increasing. On the other hand, with the increase of the strain rate, it almost has no effect on the elastic modulus and the way of evolution of dislocation network, but contributes to the increases of the yield stress and tensile strength. Moreover, tension-compression asymmetry of Ni-based single crystal superalloys is also presented based on MD simulations.

In silico transcriptional regulatory networks involved in tomato fruit ripening

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Stilianos Arhondakis

2016-08-01

Full Text Available ABSTRACTTomato fruit ripening is a complex developmental programme partly mediated by transcriptional regulatory networks. Several transcription factors (TFs which are members of gene families such as MADS-box and ERF were shown to play a significant role in ripening through interconnections into an intricate network. The accumulation of large datasets of expression profiles corresponding to different stages of tomato fruit ripening and the availability of bioinformatics tools for their analysis provide an opportunity to identify TFs which might regulate gene clusters with similar co-expression patterns. We identified two TFs, a SlWRKY22-like and a SlER24 transcriptional activator which were shown to regulate modules by using the LeMoNe algorithm for the analysis of our microarray datasets representing four stages of fruit ripening, breaker, turning, pink and red ripe. The WRKY22-like module comprised a subgroup of six various calcium sensing transcripts with similar to the TF expression patterns according to real time PCR validation. A promoter motif search identified a cis acting element, the W-box, recognized by WRKY TFs that was present in the promoter region of all six calcium sensing genes. Moreover, publicly available microarray datasets of similar ripening stages were also analyzed with LeMoNe resulting in TFs such as SlERF.E1, SlERF.C1, SlERF.B2, SLERF.A2, SlWRKY24, SLWRKY37 and MADS-box/TM29 which might also play an important role in regulation of ripening. These results suggest that the SlWRKY22-like might be involved in the coordinated regulation of expression of the six calcium sensing genes. Conclusively the LeMoNe tool might lead to the identification of putative TF targets for further physiological analysis as regulators of tomato fruit ripening.

Obesity is marked by distinct functional connectivity in brain networks involved in food reward and salience.

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Wijngaarden, M A; Veer, I M; Rombouts, S A R B; van Buchem, M A; Willems van Dijk, K; Pijl, H; van der Grond, J

2015-01-01

We hypothesized that brain circuits involved in reward and salience respond differently to fasting in obese versus lean individuals. We compared functional connectivity networks related to food reward and saliency after an overnight fast (baseline) and after a prolonged fast of 48 h in lean versus obese subjects. We included 13 obese (2 males, 11 females, BMI 35.4 ± 1.2 kg/m(2), age 31 ± 3 years) and 11 lean subjects (2 males, 9 females, BMI 23.2 ± 0.5 kg/m(2), age 28 ± 3 years). Resting-state functional magnetic resonance imaging scans were made after an overnight fast (baseline) and after a prolonged 48 h fast. Functional connectivity of the amygdala, hypothalamus and posterior cingulate cortex (default-mode) networks was assessed using seed-based correlations. At baseline, we found a stronger connectivity between hypothalamus and left insula in the obese subjects. This effect diminished upon the prolonged fast. After prolonged fasting, connectivity of the hypothalamus with the dorsal anterior cingulate cortex (dACC) increased in lean subjects and decreased in obese subjects. Amygdala connectivity with the ventromedial prefrontal cortex was stronger in lean subjects at baseline, which did not change upon the prolonged fast. No differences in posterior cingulate cortex connectivity were observed. In conclusion, obesity is marked by alterations in functional connectivity networks involved in food reward and salience. Prolonged fasting differentially affected hypothalamic connections with the dACC and the insula between obese and lean subjects. Our data support the idea that food reward and nutrient deprivation are differently perceived and/or processed in obesity. Copyright © 2015 Elsevier B.V. All rights reserved.

Molecular networks related to the immune system and mitochondria are targets for the pesticide dieldrin in the zebrafish (Danio rerio) central nervous system.

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Cowie, Andrew M; Sarty, Kathleena I; Mercer, Angella; Koh, Jin; Kidd, Karen A; Martyniuk, Christopher J

2017-03-22

The objectives of this study were to determine the behavioral and molecular responses in the adult zebrafish (Danio rerio) central nervous system (CNS) following a dietary exposure to the pesticide dieldrin. Zebrafish were fed pellets spiked with 0.03, 0.15, or 1.8μg/g dieldrin for 21days. Behavioral analysis revealed no difference in exploratory behaviors or those related to anxiety. Transcriptional networks for T-cell aggregation and selection were decreased in expression suggesting an immunosuppressive effect of dieldrin, consistent with other studies investigating organochlorine pesticides. Processes related to oxidative phosphorylation were also differentially affected by dieldrin. Quantitative proteomics (iTRAQ) using a hybrid quadrupole-Orbitrap identified 226 proteins that were different following one or more doses. These proteins included ATP synthase subunits (mitochondrial) and hypoxia up-regulated protein 1 which were decreased and NADH dehydrogenases (mitochondrial) and signal recognition particle 9 which were up-regulated. Thus, proteins affected were functionally associated with the mitochondria and a protein network analysis implicated Parkinson's disease (PD) and Huntington's disease as diseases associated with altered proteins. Molecular networks related to mitochondrial dysfunction and T-cell regulation are hypothesized to underlie the association between dieldrin and PD. These data contribute to a comprehensive transcriptomic and proteomic biomarker framework for pesticide exposures and neurodegenerative diseases. Dieldrin is a persistent organochlorine pesticide that has been associated with human neurodegenerative disease such as Parkinson's disease. Dieldrin is ranked 18th on the 2015 U.S. Agency for Toxic Substances and Disease Registry and continues to be a pesticide of concern for human health. Transcriptomics and quantitative proteomics (ITRAQ) were employed to characterize the molecular networks in the central nervous system that are

Trauma histories among justice-involved youth: findings from the National Child Traumatic Stress Network

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Carly B. Dierkhising

2013-07-01

Full Text Available Background: Up to 90% of justice-involved youth report exposure to some type of traumatic event. On average, 70% of youth meet criteria for a mental health disorder with approximately 30% of youth meeting criteria for post-traumatic stress disorder (PTSD. Justice-involved youth are also at risk for substance use and academic problems, and child welfare involvement. Yet, less is known about the details of their trauma histories, and associations among trauma details, mental health problems, and associated risk factors. Objective: This study describes detailed trauma histories, mental health problems, and associated risk factors (i.e., academic problems, substance/alcohol use, and concurrent child welfare involvement among adolescents with recent involvement in the juvenile justice system. Method: The National Child Traumatic Stress Network Core Data Set (NCTSN-CDS is used to address these aims, among which 658 adolescents report recent involvement in the juvenile justice system as indexed by being detained or under community supervision by the juvenile court. Results: Age of onset of trauma exposure was within the first 5 years of life for 62% of youth and approximately one-third of youth report exposure to multiple or co-occurring trauma types each year into adolescence. Mental health problems are prevalent with 23.6% of youth meeting criteria for PTSD, 66.1% in the clinical range for externalizing problems, and 45.5% in the clinical range for internalizing problems. Early age of onset of trauma exposure was differentially associated with mental health problems and related risk factors among males and females. Conclusions: The results indicate that justice-involved youth report high rates of trauma exposure and that this trauma typically begins early in life, is often in multiple contexts, and persists over time. Findings provide support for establishing trauma-informed juvenile justice systems that can respond to the needs of traumatized youth.

Industrial Networks

DEFF Research Database (Denmark)

Karlsson, Christer

2015-01-01

Companies organize in a way that involves many activities that are external to the traditional organizational boundaries. This presents challenges to operations management and managing operations involves many issues and actions dealing with external networks. Taking a network perspective changes...

Revealing molecular mechanisms by integrating high-dimensional functional screens with protein interaction data.

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Angela Simeone

2014-09-01

Full Text Available Functional genomics screens using multi-parametric assays are powerful approaches for identifying genes involved in particular cellular processes. However, they suffer from problems like noise, and often provide little insight into molecular mechanisms. A bottleneck for addressing these issues is the lack of computational methods for the systematic integration of multi-parametric phenotypic datasets with molecular interactions. Here, we present Integrative Multi Profile Analysis of Cellular Traits (IMPACT. The main goal of IMPACT is to identify the most consistent phenotypic profile among interacting genes. This approach utilizes two types of external information: sets of related genes (IMPACT-sets and network information (IMPACT-modules. Based on the notion that interacting genes are more likely to be involved in similar functions than non-interacting genes, this data is used as a prior to inform the filtering of phenotypic profiles that are similar among interacting genes. IMPACT-sets selects the most frequent profile among a set of related genes. IMPACT-modules identifies sub-networks containing genes with similar phenotype profiles. The statistical significance of these selections is subsequently quantified via permutations of the data. IMPACT (1 handles multiple profiles per gene, (2 rescues genes with weak phenotypes and (3 accounts for multiple biases e.g. caused by the network topology. Application to a genome-wide RNAi screen on endocytosis showed that IMPACT improved the recovery of known endocytosis-related genes, decreased off-target effects, and detected consistent phenotypes. Those findings were confirmed by rescreening 468 genes. Additionally we validated an unexpected influence of the IGF-receptor on EGF-endocytosis. IMPACT facilitates the selection of high-quality phenotypic profiles using different types of independent information, thereby supporting the molecular interpretation of functional screens.

PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

Science.gov (United States)

Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z

2017-02-03

The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular genetics of dyslexia: an overview.

Science.gov (United States)

Carrion-Castillo, Amaia; Franke, Barbara; Fisher, Simon E

2013-11-01

Dyslexia is a highly heritable learning disorder with a complex underlying genetic architecture. Over the past decade, researchers have pinpointed a number of candidate genes that may contribute to dyslexia susceptibility. Here, we provide an overview of the state of the art, describing how studies have moved from mapping potential risk loci, through identification of associated gene variants, to characterization of gene function in cellular and animal model systems. Work thus far has highlighted some intriguing mechanistic pathways, such as neuronal migration, axon guidance, and ciliary biology, but it is clear that we still have much to learn about the molecular networks that are involved. We end the review by highlighting the past, present, and future contributions of the Dutch Dyslexia Programme to studies of genetic factors. In particular, we emphasize the importance of relating genetic information to intermediate neurobiological measures, as well as the value of incorporating longitudinal and developmental data into molecular designs. Copyright © 2013 John Wiley & Sons, Ltd.

Selective excitation, relaxation, and energy channeling in molecular systems

International Nuclear Information System (INIS)

Rhodes, W.C.

1993-08-01

Research involves theoretical studies of response, relaxation, and correlated motion in time-dependent behavior of large molecular systems ranging from polyatomic molecules to protein molecules in their natural environment. Underlying theme is subsystem modulation dynamics. Main idea is that quantum mechanical correlations between components of a system develop with time, playing a major role in determining the balance between coherent and dissipative forces. Central theme is interplay of coherence and dissipation in determining the nature of dynamic structuring and energy flow in molecular transformation mechanisms. Subsystem equations of motion are being developed to show how nonlinear, dissipative dynamics of a particular subsystem arise from correlated interactions with the rest of the system (substituent groups, solvent, lattice modes, etc.); one consequence is resonance structures and networks. Quantum dynamics and thermodynamics are being applied to understand control and energy transfer mechanisms in biological functions of protein molecules; these mechanisms are both global and local. Besides the above theory, the research deals with phenomenological aspects of molecular systems

Altered expression pattern of molecular factors involved in colonic smooth muscle functions: an immunohistochemical study in patients with diverticular disease.

Science.gov (United States)

Mattii, Letizia; Ippolito, Chiara; Segnani, Cristina; Battolla, Barbara; Colucci, Rocchina; Dolfi, Amelio; Bassotti, Gabrio; Blandizzi, Corrado; Bernardini, Nunzia

2013-01-01

The pathogenesis of diverticular disease (DD) is thought to result from complex interactions among dietary habits, genetic factors and coexistence of other bowel abnormalities. These conditions lead to alterations in colonic pressure and motility, facilitating the formation of diverticula. Although electrophysiological studies on smooth muscle cells (SMCs) have investigated colonic motor dysfunctions, scarce attention has been paid to their molecular abnormalities, and data on SMCs in DD are lacking. Accordingly, the main purpose of this study was to evaluate the expression patterns of molecular factors involved in the contractile functions of SMCs in the tunica muscularis of colonic specimens from patients with DD. By means of immunohistochemistry and image analysis, we examined the expression of Cx26 and Cx43, which are prominent components of gap junctions in human colonic SMCs, as well as pS368-Cx43, PKCps, RhoA and αSMA, all known to regulate the functions of gap junctions and the contractile activity of SMCs. The immunohistochemical analysis revealed significant abnormalities in DD samples, concerning both the expression and distribution patterns of most of the investigated molecular factors. This study demonstrates, for the first time, that an altered pattern of factors involved in SMC contractility is present at level of the tunica muscularis of DD patients. Moreover, considering that our analysis was conducted on colonic tissues not directly affected by diverticular lesions or inflammatory reactions, it is conceivable that these molecular alterations may precede and predispose to the formation of diverticula, rather than being mere consequences of the disease.

Novel transcriptional networks regulated by CLOCK in human neurons.

Science.gov (United States)

Fontenot, Miles R; Berto, Stefano; Liu, Yuxiang; Werthmann, Gordon; Douglas, Connor; Usui, Noriyoshi; Gleason, Kelly; Tamminga, Carol A; Takahashi, Joseph S; Konopka, Genevieve

2017-11-01

The molecular mechanisms underlying human brain evolution are not fully understood; however, previous work suggested that expression of the transcription factor CLOCK in the human cortex might be relevant to human cognition and disease. In this study, we investigated this novel transcriptional role for CLOCK in human neurons by performing chromatin immunoprecipitation sequencing for endogenous CLOCK in adult neocortices and RNA sequencing following CLOCK knockdown in differentiated human neurons in vitro. These data suggested that CLOCK regulates the expression of genes involved in neuronal migration, and a functional assay showed that CLOCK knockdown increased neuronal migratory distance. Furthermore, dysregulation of CLOCK disrupts coexpressed networks of genes implicated in neuropsychiatric disorders, and the expression of these networks is driven by hub genes with human-specific patterns of expression. These data support a role for CLOCK-regulated transcriptional cascades involved in human brain evolution and function. © 2017 Fontenot et al.; Published by Cold Spring Harbor Laboratory Press.

Microsecond molecular dynamics simulations of intrinsically disordered proteins involved in the oxidative stress response.

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Elio A Cino

Full Text Available Intrinsically disordered proteins (IDPs are abundant in cells and have central roles in protein-protein interaction networks. Interactions between the IDP Prothymosin alpha (ProTα and the Neh2 domain of Nuclear factor erythroid 2-related factor 2 (Nrf2, with a common binding partner, Kelch-like ECH-associated protein 1(Keap1, are essential for regulating cellular response to oxidative stress. Misregulation of this pathway can lead to neurodegenerative diseases, premature aging and cancer. In order to understand the mechanisms these two disordered proteins employ to bind to Keap1, we performed extensive 0.5-1.0 microsecond atomistic molecular dynamics (MD simulations and isothermal titration calorimetry experiments to investigate the structure/dynamics of free-state ProTα and Neh2 and their thermodynamics of bindings. The results show that in their free states, both ProTα and Neh2 have propensities to form bound-state-like β-turn structures but to different extents. We also found that, for both proteins, residues outside the Keap1-binding motifs may play important roles in stabilizing the bound-state-like structures. Based on our findings, we propose that the binding of disordered ProTα and Neh2 to Keap1 occurs synergistically via preformed structural elements (PSEs and coupled folding and binding, with a heavy bias towards PSEs, particularly for Neh2. Our results provide insights into the molecular mechanisms Neh2 and ProTα bind to Keap1, information that is useful for developing therapeutics to enhance the oxidative stress response.

The emission of α,ω-diphenylpolyenes: A model involving several molecular structures

International Nuclear Information System (INIS)

Catalan, Javier

2007-01-01

Available photophysical evidence for the emission of α,ω-diphenylpolyenes is shown to be consistent with a previously reported model [J. Catalan, J.L.G. de Paz, J. Chem. Phys. 124 (2006) 034306] involving two electronically excited molecular structures of 1B u and C s symmetry, respectively. The 1B u structure is produced by direct light absorption from the all-trans form of the α,ω-diphenylpolyene in the ground state and its emission exhibits mirror symmetry with respect to the absorption of the compound. On the other hand, the C s structure is generated from the 1B u structure of the α,ω-diphenylpolyene by rotation about a C-C single bond in the polyene chain, its emission being red-shifted with respect to the previous one and exhibiting markedly decreased vibrational structure. At room temperature, both emissions give the excitation spectrum, which are ascribed to the first absorption band for the compound. It is shown that some polyenes may exist in more than one structure of C s symmetry in the excited electronic state with lower energy than that of the 1B u state, from which the C s structures are produced. Hence, more than one electronic structure may be involved in the deactivation processes of the 1B u state, which is initially populated upon photo-excitation of the polyene molecule in the ground electronic state

Molecular mechanisms involved in Bacillus subtilis biofilm formation

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Mielich-Süss, Benjamin; Lopez, Daniel

2014-01-01

Summary Biofilms are the predominant lifestyle of bacteria in natural environments, and they severely impact our societies in many different fashions. Therefore, biofilm formation is a topic of growing interest in microbiology, and different bacterial models are currently studied to better understand the molecular strategies that bacteria undergo to build biofilms. Among those, biofilms of the soil-dwelling bacterium Bacillus subtilis are commonly used for this purpose. Bacillus subtilis biofilms show remarkable architectural features that are a consequence of sophisticated programs of cellular specialization and cell-cell communication within the community. Many laboratories are trying to unravel the biological role of the morphological features of biofilms, as well as exploring the molecular basis underlying cellular differentiation. In this review, we present a general perspective of the current state of knowledge of biofilm formation in B. subtilis. In particular, a special emphasis is placed on summarizing the most recent discoveries in the field and integrating them into the general view of these truly sophisticated microbial communities. PMID:24909922

Impaired clock output by altered connectivity in the circadian network.

Science.gov (United States)

Fernández, María de la Paz; Chu, Jessie; Villella, Adriana; Atkinson, Nigel; Kay, Steve A; Ceriani, María Fernanda

2007-03-27

Substantial progress has been made in elucidating the molecular processes that impart a temporal control to physiology and behavior in most eukaryotes. In Drosophila, dorsal and ventral neuronal networks act in concert to convey rhythmicity. Recently, the hierarchical organization among the different circadian clusters has been addressed, but how molecular oscillations translate into rhythmic behavior remains unclear. The small ventral lateral neurons can synchronize certain dorsal oscillators likely through the release of pigment dispersing factor (PDF), a neuropeptide central to the control of rhythmic rest-activity cycles. In the present study, we have taken advantage of flies exhibiting a distinctive arrhythmic phenotype due to mutation of the potassium channel slowpoke (slo) to examine the relevance of specific neuronal populations involved in the circadian control of behavior. We show that altered neuronal function associated with the null mutation specifically impaired PDF accumulation in the dorsal protocerebrum and, in turn, desynchronized molecular oscillations in the dorsal clusters. However, molecular oscillations in the small ventral lateral neurons are properly running in the null mutant, indicating that slo is acting downstream of these core pacemaker cells, most likely in the output pathway. Surprisingly, disrupted PDF signaling by slo dysfunction directly affects the structure of the underlying circuit. Our observations demonstrate that subtle structural changes within the circadian network are responsible for behavioral arrhythmicity.

Brain network involved in visual processing of movement stimuli used in upper limb robotic training: an fMRI study.

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Nocchi, Federico; Gazzellini, Simone; Grisolia, Carmela; Petrarca, Maurizio; Cannatà, Vittorio; Cappa, Paolo; D'Alessio, Tommaso; Castelli, Enrico

2012-07-24

The potential of robot-mediated therapy and virtual reality in neurorehabilitation is becoming of increasing importance. However, there is limited information, using neuroimaging, on the neural networks involved in training with these technologies. This study was intended to detect the brain network involved in the visual processing of movement during robotic training. The main aim was to investigate the existence of a common cerebral network able to assimilate biological (human upper limb) and non-biological (abstract object) movements, hence testing the suitability of the visual non-biological feedback provided by the InMotion2 Robot. A visual functional Magnetic Resonance Imaging (fMRI) task was administered to 22 healthy subjects. The task required observation and retrieval of motor gestures and of the visual feedback used in robotic training. Functional activations of both biological and non-biological movements were examined to identify areas activated in both conditions, along with differential activity in upper limb vs. abstract object trials. Control of response was also tested by administering trials with congruent and incongruent reaching movements. The observation of upper limb and abstract object movements elicited similar patterns of activations according to a caudo-rostral pathway for the visual processing of movements (including specific areas of the occipital, temporal, parietal, and frontal lobes). Similarly, overlapping activations were found for the subsequent retrieval of the observed movement. Furthermore, activations of frontal cortical areas were associated with congruent trials more than with the incongruent ones. This study identified the neural pathway associated with visual processing of movement stimuli used in upper limb robot-mediated training and investigated the brain's ability to assimilate abstract object movements with human motor gestures. In both conditions, activations were elicited in cerebral areas involved in visual

Brain network involved in visual processing of movement stimuli used in upper limb robotic training: an fMRI study

Directory of Open Access Journals (Sweden)

Nocchi Federico

2012-07-01

Full Text Available Abstract Background The potential of robot-mediated therapy and virtual reality in neurorehabilitation is becoming of increasing importance. However, there is limited information, using neuroimaging, on the neural networks involved in training with these technologies. This study was intended to detect the brain network involved in the visual processing of movement during robotic training. The main aim was to investigate the existence of a common cerebral network able to assimilate biological (human upper limb and non-biological (abstract object movements, hence testing the suitability of the visual non-biological feedback provided by the InMotion2 Robot. Methods A visual functional Magnetic Resonance Imaging (fMRI task was administered to 22 healthy subjects. The task required observation and retrieval of motor gestures and of the visual feedback used in robotic training. Functional activations of both biological and non-biological movements were examined to identify areas activated in both conditions, along with differential activity in upper limb vs. abstract object trials. Control of response was also tested by administering trials with congruent and incongruent reaching movements. Results The observation of upper limb and abstract object movements elicited similar patterns of activations according to a caudo-rostral pathway for the visual processing of movements (including specific areas of the occipital, temporal, parietal, and frontal lobes. Similarly, overlapping activations were found for the subsequent retrieval of the observed movement. Furthermore, activations of frontal cortical areas were associated with congruent trials more than with the incongruent ones. Conclusions This study identified the neural pathway associated with visual processing of movement stimuli used in upper limb robot-mediated training and investigated the brain’s ability to assimilate abstract object movements with human motor gestures. In both conditions

The molecular kink paradigm for rubber elasticity: Numerical simulations of explicit polyisoprene networks at low to moderate tensile strains

Science.gov (United States)

Hanson, David E.

2011-08-01

Based on recent molecular dynamics and ab initio simulations of small isoprene molecules, we propose a new ansatz for rubber elasticity. We envision a network chain as a series of independent molecular kinks, each comprised of a small number of backbone units, and the strain as being imposed along the contour of the chain. We treat chain extension in three distinct force regimes: (Ia) near zero strain, where we assume that the chain is extended within a well defined tube, with all of the kinks participating simultaneously as entropic elastic springs, (II) when the chain becomes sensibly straight, giving rise to a purely enthalpic stretching force (until bond rupture occurs) and, (Ib) a linear entropic regime, between regimes Ia and II, in which a force limit is imposed by tube deformation. In this intermediate regime, the molecular kinks are assumed to be gradually straightened until the chain becomes a series of straight segments between entanglements. We assume that there exists a tube deformation tension limit that is inversely proportional to the chain path tortuosity. Here we report the results of numerical simulations of explicit three-dimensional, periodic, polyisoprene networks, using these extension-only force models. At low strain, crosslink nodes are moved affinely, up to an arbitrary node force limit. Above this limit, non-affine motion of the nodes is allowed to relax unbalanced chain forces. Our simulation results are in good agreement with tensile stress vs. strain experiments.

The European network of excellence Emil

International Nuclear Information System (INIS)

2006-01-01

The network of excellence EMIL (European Molecular Imaging Laboratories ) is the only European network of excellence in molecular imaging for oncology. It was set up and is coordinated by the 'in vivo imaging of gene expression' group of CEA Orsay. Included in Priority Thematic Area 1 (life sciences, genomics and biotechnology for health) of the European Commission's 6. Framework Programme for Research and Technological Development (FP6), this five-year project (2004-2009) aims t o merge the leading European research teams in molecular imaging, in universities, research centres and small and medium enterprises, to focus on early diagnosis, prognosis and therapeutic evaluation of cancer. The EMIL network brings together 58 partners representing 43 bodies in 13 European countries, and integrates 6 technological facilities: Orsay (France), Turin (Italy), Cologne (Germany), Leiden (Netherlands), Milan (Italy) and Antwerpen (Belgium).The research and training activities of the EMIL network are based on 9 thematic working groups or 'work packages' (wp), forming a common activity programme including : Integration activities: creation of a network of technological and training facilities favouring the mobility of researchers and the integration of small and medium enterprises into the EMIL network. Dissemination of expertise activities: training, communication, common knowledge management and intellectual property rights. Research activities: a common research programme with a horizontal dimension, making use of methodological tools of physics, biology and chemistry necessary for the further development of molecular imaging (instrument techniques, molecular probes, biological engineering), and a vertical integrative dimension, bringing together cancer imaging applications (early diagnostic imaging, development of new therapies imaging for drug development). (author)

Molecular Determinants Underlying Binding Specificities of the ABL Kinase Inhibitors: Combining Alanine Scanning of Binding Hot Spots with Network Analysis of Residue Interactions and Coevolution.

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Amanda Tse

Full Text Available Quantifying binding specificity and drug resistance of protein kinase inhibitors is of fundamental importance and remains highly challenging due to complex interplay of structural and thermodynamic factors. In this work, molecular simulations and computational alanine scanning are combined with the network-based approaches to characterize molecular determinants underlying binding specificities of the ABL kinase inhibitors. The proposed theoretical framework unveiled a relationship between ligand binding and inhibitor-mediated changes in the residue interaction networks. By using topological parameters, we have described the organization of the residue interaction networks and networks of coevolving residues in the ABL kinase structures. This analysis has shown that functionally critical regulatory residues can simultaneously embody strong coevolutionary signal and high network centrality with a propensity to be energetic hot spots for drug binding. We have found that selective (Nilotinib and promiscuous (Bosutinib, Dasatinib kinase inhibitors can use their energetic hot spots to differentially modulate stability of the residue interaction networks, thus inhibiting or promoting conformational equilibrium between inactive and active states. According to our results, Nilotinib binding may induce a significant network-bridging effect and enhance centrality of the hot spot residues that stabilize structural environment favored by the specific kinase form. In contrast, Bosutinib and Dasatinib can incur modest changes in the residue interaction network in which ligand binding is primarily coupled only with the identity of the gate-keeper residue. These factors may promote structural adaptability of the active kinase states in binding with these promiscuous inhibitors. Our results have related ligand-induced changes in the residue interaction networks with drug resistance effects, showing that network robustness may be compromised by targeted mutations

Molecular Determinants Underlying Binding Specificities of the ABL Kinase Inhibitors: Combining Alanine Scanning of Binding Hot Spots with Network Analysis of Residue Interactions and Coevolution

Science.gov (United States)

Tse, Amanda; Verkhivker, Gennady M.

2015-01-01

Quantifying binding specificity and drug resistance of protein kinase inhibitors is of fundamental importance and remains highly challenging due to complex interplay of structural and thermodynamic factors. In this work, molecular simulations and computational alanine scanning are combined with the network-based approaches to characterize molecular determinants underlying binding specificities of the ABL kinase inhibitors. The proposed theoretical framework unveiled a relationship between ligand binding and inhibitor-mediated changes in the residue interaction networks. By using topological parameters, we have described the organization of the residue interaction networks and networks of coevolving residues in the ABL kinase structures. This analysis has shown that functionally critical regulatory residues can simultaneously embody strong coevolutionary signal and high network centrality with a propensity to be energetic hot spots for drug binding. We have found that selective (Nilotinib) and promiscuous (Bosutinib, Dasatinib) kinase inhibitors can use their energetic hot spots to differentially modulate stability of the residue interaction networks, thus inhibiting or promoting conformational equilibrium between inactive and active states. According to our results, Nilotinib binding may induce a significant network-bridging effect and enhance centrality of the hot spot residues that stabilize structural environment favored by the specific kinase form. In contrast, Bosutinib and Dasatinib can incur modest changes in the residue interaction network in which ligand binding is primarily coupled only with the identity of the gate-keeper residue. These factors may promote structural adaptability of the active kinase states in binding with these promiscuous inhibitors. Our results have related ligand-induced changes in the residue interaction networks with drug resistance effects, showing that network robustness may be compromised by targeted mutations of key mediating

Bioinformatics Analysis Reveals Genes Involved in the Pathogenesis of Ameloblastoma and Keratocystic Odontogenic Tumor.

Science.gov (United States)

Santos, Eliane Macedo Sobrinho; Santos, Hércules Otacílio; Dos Santos Dias, Ivoneth; Santos, Sérgio Henrique; Batista de Paula, Alfredo Maurício; Feltenberger, John David; Sena Guimarães, André Luiz; Farias, Lucyana Conceição

2016-01-01

Pathogenesis of odontogenic tumors is not well known. It is important to identify genetic deregulations and molecular alterations. This study aimed to investigate, through bioinformatic analysis, the possible genes involved in the pathogenesis of ameloblastoma (AM) and keratocystic odontogenic tumor (KCOT). Genes involved in the pathogenesis of AM and KCOT were identified in GeneCards. Gene list was expanded, and the gene interactions network was mapped using the STRING software. "Weighted number of links" (WNL) was calculated to identify "leader genes" (highest WNL). Genes were ranked by K-means method and Kruskal-Wallis test was used (Preview data was used to corroborate the bioinformatics data. CDK1 was identified as leader gene for AM. In KCOT group, results show PCNA and TP53 . Both tumors exhibit a power law behavior. Our topological analysis suggested leader genes possibly important in the pathogenesis of AM and KCOT, by clustering coefficient calculated for both odontogenic tumors (0.028 for AM, zero for KCOT). The results obtained in the scatter diagram suggest an important relationship of these genes with the molecular processes involved in AM and KCOT. Ontological analysis for both AM and KCOT demonstrated different mechanisms. Bioinformatics analyzes were confirmed through literature review. These results may suggest the involvement of promising genes for a better understanding of the pathogenesis of AM and KCOT.

Mining protein interactomes to improve their reliability and support the advancement of network medicine

KAUST Repository

Alanis Lobato, Gregorio

2015-09-23

High-throughput detection of protein interactions has had a major impact in our understanding of the intricate molecular machinery underlying the living cell, and has permitted the construction of very large protein interactomes. The protein networks that are currently available are incomplete and a significant percentage of their interactions are false positives. Fortunately, the structural properties observed in good quality social or technological networks are also present in biological systems. This has encouraged the development of tools, to improve the reliability of protein networks and predict new interactions based merely on the topological characteristics of their components. Since diseases are rarely caused by the malfunction of a single protein, having a more complete and reliable interactome is crucial in order to identify groups of inter-related proteins involved in disease etiology. These system components can then be targeted with minimal collateral damage. In this article, an important number of network mining tools is reviewed, together with resources from which reliable protein interactomes can be constructed. In addition to the review, a few representative examples of how molecular and clinical data can be integrated to deepen our understanding of pathogenesis are discussed.

Mining protein interactomes to improve their reliability and support the advancement of network medicine

Directory of Open Access Journals (Sweden)

Gregorio eAlanis-Lobato

2015-09-01

Full Text Available High-throughput detection of protein interactions has had a major impact in our understanding of the intricate molecular machinery underlying the living cell, and has permitted the construction of very large protein interactomes. The protein networks that are currently available are incomplete and a significant percentage of their interactions are false positives. Fortunately, the structural properties observed in good quality social or technological networks are also present in biological systems. This has encouraged the development of tools, to improve the reliability of protein networks and predict new interactions based merely on the topological characteristics of their components. Since diseases are rarely caused by the malfunction of a single protein, having a more complete and reliable interactome is crucial in order to identify groups of inter-related proteins involved in disease aetiology. These system components can then be targeted with minimal collateral damage. In this article, an important number of network mining tools is reviewed, together with resources from which reliable protein interactomes can be constructed. In addition to the review, a few representative examples of how molecular and clinical data can be integrated to deepen our understanding of pathogenesis are discussed.

Force Exertion and Transmission in Cross-Linked Actin Networks

Science.gov (United States)

Stam, Samantha

Cells are responsive to external cues in their environment telling them to proliferate or migrate within their surrounding tissue. Sensing of cues that are mechanical in nature, such stiffness of a tissue or forces transmitted from other cells, is believed to involve the cytoskeleton of a cell. The cytoskeleton is a complex network of proteins consisting of polymers that provide structural support, motor proteins that remodel these structures, and many others. We do not yet have a complete understanding of how cytoskeletal components respond to either internal or external mechanical force and stiffness. Such an understanding should involve mechanisms by which constituent molecules, such as motor proteins, are responsive to mechanics. Additionally, physical models of how forces are transmitted through biopolymer networks are necessary. My research has focused on networks formed by the cytoskeletal filament actin and the molecular motor protein myosin II. Actin filaments form networks and bundles that form a structural framework of the cell, and myosin II slides actin filaments. In this thesis, we show that stiffness of an elastic load that opposes myosin-generated actin sliding has a very sharp effect on the myosin force output in simulations. Secondly, we show that the stiffness and connectivity of cytoskeletal filaments regulates the contractility and anisotropy of network deformations that transmit force on material length scales. Together, these results have implications for predicting and interpreting the deformations and forces in biopolymeric active materials.

Learning surface molecular structures via machine vision

Science.gov (United States)

Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

2017-08-01

Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (`read out') all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds and thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. The method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.

Algorithmic Complexity and Reprogrammability of Chemical Structure Networks

KAUST Repository

Zenil, Hector; Kiani, Narsis A.; Shang, Ming-mei; Tegner, Jesper

2018-01-01

Here we address the challenge of profiling causal properties and tracking the transformation of chemical compounds from an algorithmic perspective. We explore the potential of applying a computational interventional calculus based on the principles of algorithmic probability to chemical structure networks. We profile the sensitivity of the elements and covalent bonds in a chemical structure network algorithmically, asking whether reprogrammability affords information about thermodynamic and chemical processes involved in the transformation of different compound classes. We arrive at numerical results suggesting a correspondence between some physical, structural and functional properties. Our methods are capable of separating chemical classes that reflect functional and natural differences without considering any information about atomic and molecular properties. We conclude that these methods, with their links to chemoinformatics via algorithmic, probability hold promise for future research.

Algorithmic Complexity and Reprogrammability of Chemical Structure Networks

KAUST Repository

Zenil, Hector

2018-02-16

Here we address the challenge of profiling causal properties and tracking the transformation of chemical compounds from an algorithmic perspective. We explore the potential of applying a computational interventional calculus based on the principles of algorithmic probability to chemical structure networks. We profile the sensitivity of the elements and covalent bonds in a chemical structure network algorithmically, asking whether reprogrammability affords information about thermodynamic and chemical processes involved in the transformation of different compound classes. We arrive at numerical results suggesting a correspondence between some physical, structural and functional properties. Our methods are capable of separating chemical classes that reflect functional and natural differences without considering any information about atomic and molecular properties. We conclude that these methods, with their links to chemoinformatics via algorithmic, probability hold promise for future research.

Algorithmic Complexity and Reprogrammability of Chemical Structure Networks

KAUST Repository

Zenil, Hector

2018-04-02

Here we address the challenge of profiling causal properties and tracking the transformation of chemical compounds from an algorithmic perspective. We explore the potential of applying a computational interventional calculus based on the principles of algorithmic probability to chemical structure networks. We profile the sensitivity of the elements and covalent bonds in a chemical structure network algorithmically, asking whether reprogrammability affords information about thermodynamic and chemical processes involved in the transformation of different compound classes. We arrive at numerical results suggesting a correspondence between some physical, structural and functional properties. Our methods are capable of separating chemical classes that reflect functional and natural differences without considering any information about atomic and molecular properties. We conclude that these methods, with their links to chemoinformatics via algorithmic, probability hold promise for future research.

Structural, optical, and hydrogenation properties of ZnO nanowall networks grown on a Si (1 1 1) substrate by plasma-assisted molecular beam epitaxy

International Nuclear Information System (INIS)

Su, S.C.; Lu, Y.M.; Zhang, Z.Z.; Li, B.H.; Shen, D.Z.; Yao, B.; Zhang, J.Y.; Zhao, D.X.; Fan, X.W.

2008-01-01

ZnO nanowall networks were grown on a Si (1 1 1) substrate by plasma-assisted molecular beam epitaxy (P-MBE) without using catalysts. Scanning electronic microscopy (FE-SEM) confirmed the formation of nanowalls with a thickness of about 10-20 nm. X-ray diffraction (XRD) showed that the ZnO nanowall networks were crystallized in a wurtzite structure with their height parallel to the direction. Photoluminescence (PL) of the ZnO nanowall networks exhibited free excitons (FEs), donor-bound exciton (D 0 X), donor-acceptor pair (DAP), and free exciton to acceptor (FA) emissions. The growth mechanism of the ZnO nanowall networks was discussed, and their hydrogenation was also studied

Optimality principles in the regulation of metabolic networks.

Science.gov (United States)

Berkhout, Jan; Bruggeman, Frank J; Teusink, Bas

2012-08-29

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular "task" of the network-its function-should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

Applications of neural networks to real-time data processing at the Environmental and Molecular Sciences Laboratory (EMSL)

International Nuclear Information System (INIS)

Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

1993-06-01

Detailed design of the Environmental and Molecular Sciences Laboratory (EMSL) at the Pacific Northwest Laboratory (PNL) is nearing completion and construction is scheduled to begin later this year. This facility will assist in the environmental restoration and waste management mission at the Hanford Site. This paper identifies several real-time data processing applications within the EMSL where neural networks can potentially be beneficial. These applications include real-time sensor data acquisition and analysis, spectral analysis, process control, theoretical modeling, and data compression

Biochemical and molecular characterization of Coriolopsis rigida laccases involved in transformation of the solid waste from olive oil production.

Science.gov (United States)

Díaz, Rosario; Saparrat, Mario C N; Jurado, Miguel; García-Romera, Inmaculada; Ocampo, Juan Antonio; Martínez, María Jesús

2010-09-01

Two laccase isoenzymes were purified and characterized from the basidiomycete Coriolopsis rigida during transformation of the water-soluble fraction of "alpeorujo" (WSFA), a solid residue derived from the olive oil production containing high levels of toxic compounds. Zymogram assays of laccases secreted by the fungus growing on WSFA and WSFA supplemented with glucose showed two bands with isoelectric points of 3.3 and 3.4. The kinetic studies of the two purified isoenzymes showed similar affinity on 2,6-dimethoxyphenol and 2,2'-azinobis-(3-ethylbenzthiazoline-6-sulfonic acid), used as phenolic and non-phenolic model substrate, respectively. The molecular mass of both proteins was 66 kDa with 9% N-linked carbohydrate. Physico-chemical properties of the purified laccases from media containing WSFA were similar to those obtained from medium with glucose as the main carbon source. In-vitro studies performed with the purified laccases revealed a 42% phenol reduction of WSFA, as well as changes in the molecular mass distribution. These findings indicate that these laccases are involved in the process of transformation, via polymerization by the oxidation of phenolic compounds present in WSFA. A single laccase gene, containing an open reading frame of 1,488 bp, was obtained in PCR amplifications performed with cDNA extracted from mycelia grown on WSFA. The product of the gene shares 90% identity (95% similarity) with a laccase from Trametes trogii and 89% identity (95% similarity) with a laccase from Coriolopsis gallica. This is the first report on purification and molecular characterization of laccases directly involved in the transformation of olive oil residues.

NAC Transcription Factors in Senescence: From Molecular Structure to Function in Crops

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Dagmara Podzimska-Sroka

2015-07-01

Full Text Available Within the last decade, NAC transcription factors have been shown to play essential roles in senescence, which is the focus of this review. Transcriptome analyses associate approximately one third of Arabidopsis NAC genes and many crop NAC genes with senescence, thereby implicating NAC genes as important regulators of the senescence process. The consensus DNA binding site of the NAC domain is used to predict NAC target genes, and protein interaction sites can be predicted for the intrinsically disordered transcription regulatory domains of NAC proteins. The molecular characteristics of these domains determine the interactions in gene regulatory networks. Emerging local NAC-centered gene regulatory networks reveal complex molecular mechanisms of stress- and hormone-regulated senescence and basic physiological steps of the senescence process. For example, through molecular interactions involving the hormone abscisic acid, Arabidopsis NAP promotes chlorophyll degradation, a hallmark of senescence. Furthermore, studies of the functional rice ortholog, OsNAP, suggest that NAC genes can be targeted to obtain specific changes in lifespan control and nutrient remobilization in crop plants. This is also exemplified by the wheat NAM1 genes which promote senescence and increase grain zinc, iron, and protein content. Thus, NAC genes are promising targets for fine-tuning senescence for increased yield and quality.

A Modified Glycosaminoglycan, GM-0111, Inhibits Molecular Signaling Involved in Periodontitis.

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Justin R Savage

Full Text Available Periodontitis is characterized by microbial infection, inflammation, tissue breakdown, and accelerated loss of alveolar bone matrix. Treatment targeting these multiple stages of the disease provides ways to treat or prevent periodontitis. Certain glycosaminoglycans (GAGs block multiple inflammatory mediators as well as suppress bacterial growth, suggesting that these GAGs may be exploited as a therapeutic for periodontitis.We investigated the effects of a synthetic GAG, GM-0111, on various molecular events associated with periodontitis: growth of Porphyromonas gingivalis (P. gingivalis and Aggregatibacter actinomycetemcomitans (A. actinomycetemcomitans pathogenic bacteria associated with periodontitis; activation of pro-inflammatory signaling through TLR2 and TLR4 in mouse macrophage RAW 264.7 cells and heterologously expressed HEK 293 cells; osteoclast formation and bone matrix resorption in cultured mouse pre-osteoclasts.(1 GM-0111 suppressed the growth of P. gingivalis and A. actinomycetemcomitans even at 1% (w/v solution. The antibacterial effects of GM-0111 were stronger than hyaluronic acid (HA or xylitol in P. gingivalis at all concentrations and comparable to xylitol in A. actinomycetemcomitans at ≥2% (w/v solution. We also observed that GM-0111 suppressed biofilm formation of P. gingivalis and these effects were much stronger than HA. (2 GM-0111 inhibited TLR-mediated pro-inflammatory cellular signaling both in macrophage and HEK 293 cells with higher selectivity for TLR2 than TLR4 (IC50 of 1-10 ng/mL vs. > 100 μg/mL, respectively. (3 GM-0111 blocked RANKL-induced osteoclast formation (as low as 300 ng/mL and bone matrix resorption. While GM-0111 showed high affinity binding to RANKL, it did not interfere with RANKL/RANK/NF-κB signaling, suggesting that GM-0111 inhibits osteoclast formation by a RANKL-RANK-independent mechanism.We report that GM-0111 inhibits multiple molecular events involved in periodontitis, spanning from the

Spectroscopic study of uracil, 1-methyluracil and 1-methyl-4-thiouracil: Hydrogen bond interactions in crystals and ab-initio molecular dynamics

Science.gov (United States)

Brela, Mateusz Z.; Boczar, Marek; Malec, Leszek M.; Wójcik, Marek J.; Nakajima, Takahito

2018-05-01

Hydrogen bond networks in uracil, 1-methyluracil and 1-methyl-4-thiouracil were studied by ab initio molecular dynamics as well as analysis of the orbital interactions. The power spectra calculated by ab initio molecular dynamics for atoms involved in hydrogen bonds were analyzed. We calculated spectra by using anharmonic approximation based on the autocorrelation function of the atom positions obtained from the Born-Oppenheimer simulations. Our results show the differences between hydrogen bond networks in uracil and its methylated derivatives. The studied methylated derivatives, 1-methyluracil as well as 1-methyl-4-thiouracil, form dimeric structures in the crystal phase, while uracil does not form that kind of structures. The presence of sulfur atom instead oxygen atom reflects weakness of the hydrogen bonds that build dimers.

Hydrogen-bond network and pH sensitivity in human transthyretin

Energy Technology Data Exchange (ETDEWEB)

Yokoyama, Takeshi, E-mail: tyokoya3@pha.u-toyama.ac.jp; Mizuguchi, Mineyuki; Nabeshima, Yuko [University of Toyama, 2630 Sugitani, Toyama 930-0914 (Japan); Kusaka, Katsuhiro; Yamada, Taro [Ibaraki University, 162-1 Shirakata, Tokai, Ibaraki 319-1106 (Japan); Hosoya, Takaaki [Ibaraki University, 162-1 Shirakata, Tokai, Ibaraki 319-1106 (Japan); Ibaraki University, 4-12-1 Naka-Narusawa, Hitachi, Ibaraki 316-8511 (Japan); Ohhara, Takashi [Comprehensive Research Organization for Science and Society, 162-1 Shirakata, Tokai, Ibaraki 319-1106 (Japan); Kurihara, Kazuo [Japan Atomic Energy Agency, 2-4 Shirakata, Tokai, Ibaraki 319-1195 (Japan); Tanaka, Ichiro [Ibaraki University, 162-1 Shirakata, Tokai, Ibaraki 319-1106 (Japan); Ibaraki University, 4-12-1 Naka-Narusawa, Hitachi, Ibaraki 316-8511 (Japan); Niimura, Nobuo [Ibaraki University, 162-1 Shirakata, Tokai, Ibaraki 319-1106 (Japan)

2013-11-01

The neutron crystal structure of human transthyretin is presented. Transthyretin (TTR) is a tetrameric protein. TTR misfolding and aggregation are associated with human amyloid diseases. Dissociation of the TTR tetramer is believed to be the rate-limiting step in the amyloid fibril formation cascade. Low pH is known to promote dissociation into monomer and the formation of amyloid fibrils. In order to reveal the molecular mechanisms underlying pH sensitivity and structural stabilities of TTR, neutron diffraction studies were conducted using the IBARAKI Biological Crystal Diffractometer with the time-of-flight method. Crystals for the neutron diffraction experiments were grown up to 2.5 mm{sup 3} for four months. The neutron crystal structure solved at 2.0 Å revealed the protonation states of His88 and the detailed hydrogen-bond network depending on the protonation states of His88. This hydrogen-bond network is involved in monomer–monomer and dimer–dimer interactions, suggesting that the double protonation of His88 by acidification breaks the hydrogen-bond network and causes the destabilization of the TTR tetramer. Structural comparison with the X-ray crystal structure at acidic pH identified the three amino acid residues responsible for the pH sensitivity of TTR. Our neutron model provides insights into the molecular stability related to amyloidosis.

Network based transcription factor analysis of regenerating axolotl limbs

Directory of Open Access Journals (Sweden)

Cameron Jo Ann

2011-03-01

Full Text Available Abstract Background Studies on amphibian limb regeneration began in the early 1700's but we still do not completely understand the cellular and molecular events of this unique process. Understanding a complex biological process such as limb regeneration is more complicated than the knowledge of the individual genes or proteins involved. Here we followed a systems biology approach in an effort to construct the networks and pathways of protein interactions involved in formation of the accumulation blastema in regenerating axolotl limbs. Results We used the human orthologs of proteins previously identified by our research team as bait to identify the transcription factor (TF pathways and networks that regulate blastema formation in amputated axolotl limbs. The five most connected factors, c-Myc, SP1, HNF4A, ESR1 and p53 regulate ~50% of the proteins in our data. Among these, c-Myc and SP1 regulate 36.2% of the proteins. c-Myc was the most highly connected TF (71 targets. Network analysis showed that TGF-β1 and fibronectin (FN lead to the activation of these TFs. We found that other TFs known to be involved in epigenetic reprogramming, such as Klf4, Oct4, and Lin28 are also connected to c-Myc and SP1. Conclusions Our study provides a systems biology approach to how different molecular entities inter-connect with each other during the formation of an accumulation blastema in regenerating axolotl limbs. This approach provides an in silico methodology to identify proteins that are not detected by experimental methods such as proteomics but are potentially important to blastema formation. We found that the TFs, c-Myc and SP1 and their target genes could potentially play a central role in limb regeneration. Systems biology has the potential to map out numerous other pathways that are crucial to blastema formation in regeneration-competent limbs, to compare these to the pathways that characterize regeneration-deficient limbs and finally, to identify stem

The European network of excellence Emil

Energy Technology Data Exchange (ETDEWEB)

NONE

2006-07-01

The network of excellence EMIL (European Molecular Imaging Laboratories ) is the only European network of excellence in molecular imaging for oncology. It was set up and is coordinated by the 'in vivo imaging of gene expression' group of CEA Orsay. Included in Priority Thematic Area 1 (life sciences, genomics and biotechnology for health) of the European Commission's 6. Framework Programme for Research and Technological Development (FP6), this five-year project (2004-2009) aims t o merge the leading European research teams in molecular imaging, in universities, research centres and small and medium enterprises, to focus on early diagnosis, prognosis and therapeutic evaluation of cancer. The EMIL network brings together 58 partners representing 43 bodies in 13 European countries, and integrates 6 technological facilities: Orsay (France), Turin (Italy), Cologne (Germany), Leiden (Netherlands), Milan (Italy) and Antwerpen (Belgium).The research and training activities of the EMIL network are based on 9 thematic working groups or 'work packages' (wp), forming a common activity programme including : Integration activities: creation of a network of technological and training facilities favouring the mobility of researchers and the integration of small and medium enterprises into the EMIL network. Dissemination of expertise activities: training, communication, common knowledge management and intellectual property rights. Research activities: a common research programme with a horizontal dimension, making use of methodological tools of physics, biology and chemistry necessary for the further development of molecular imaging (instrument techniques, molecular probes, biological engineering), and a vertical integrative dimension, bringing together cancer imaging applications (early diagnostic imaging, development of new therapies imaging for drug development). (author)

Online social networks for patient involvement and recruitment in clinical research.

Science.gov (United States)

Ryan, Gemma Sinead

2013-01-01

To review current literature and discuss the potential of online social networking to engage patients and the public and recruit and retain participants in clinical research. Online social networking is becoming a large influence on people's daily lives. Clinical research faces several challenges, with an increasing need to engage with patients and the public and for studies to recruit and retain increasing numbers of participants, particularly in under-served, under-represented and hard to reach groups and communities. Searches were conducted using EMBASE, BNI, ERIC, CINAHL, PSYCHinfo online databases and Google Scholar to identify any grey or unpublished literature that may be available. Review methods This is a methodology paper. Online social networking is a successful, cost-effective and efficient method by which to target and recruit a wide range of communities, adolescents, young people and underserved populations into quantitative and qualitative research. Retention of participants in longitudinal studies could be improved using social networks such as Facebook. Evidence indicates that a mixed approach to recruitment using social networking and traditional methods is most effective. Further research is required to strengthen the evidence available, especially in dissemination of research through online social networks. Researchers should consider using online social networking as a method of engaging the public, and also for the recruitment and follow up of participants.

A network approach to predict pathogenic genes for Fusarium graminearum.

Science.gov (United States)

Liu, Xiaoping; Tang, Wei-Hua; Zhao, Xing-Ming; Chen, Luonan

2010-10-04

Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB), which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN) of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other pathogenic fungi, which

A network approach to predict pathogenic genes for Fusarium graminearum.

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Xiaoping Liu

Full Text Available Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB, which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other

Designing heavy metal oxide glasses with threshold properties from network rigidity.

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Chakraborty, Shibalik; Boolchand, P; Malki, M; Micoulaut, M

2014-01-07

Here, we show that a new class of glasses composed of heavy metal oxides involving transition metals (V2O5-TeO2) can surprisingly be designed from very basic tools using topology and rigidity of their underlying molecular networks. When investigated as a function of composition, such glasses display abrupt changes in network packing and enthalpy of relaxation at Tg, underscoring presence of flexible to rigid elastic phase transitions. We find that these elastic phases are fully consistent with polaronic nature of electronic conductivity at high V2O5 content. Such observations have new implications for designing electronic glasses which differ from the traditional amorphous electrolytes having only mobile ions as charge carriers.

Weighted gene co-expression network analysis reveals potential genes involved in early metamorphosis process in sea cucumber Apostichopus japonicus.

Science.gov (United States)

Li, Yongxin; Kikuchi, Mani; Li, Xueyan; Gao, Qionghua; Xiong, Zijun; Ren, Yandong; Zhao, Ruoping; Mao, Bingyu; Kondo, Mariko; Irie, Naoki; Wang, Wen

2018-01-01

Sea cucumbers, one main class of Echinoderms, have a very fast and drastic metamorphosis process during their development. However, the molecular basis under this process remains largely unknown. Here we systematically examined the gene expression profiles of Japanese common sea cucumber (Apostichopus japonicus) for the first time by RNA sequencing across 16 developmental time points from fertilized egg to juvenile stage. Based on the weighted gene co-expression network analysis (WGCNA), we identified 21 modules. Among them, MEdarkmagenta was highly expressed and correlated with the early metamorphosis process from late auricularia to doliolaria larva. Furthermore, gene enrichment and differentially expressed gene analysis identified several genes in the module that may play key roles in the metamorphosis process. Our results not only provide a molecular basis for experimentally studying the development and morphological complexity of sea cucumber, but also lay a foundation for improving its emergence rate. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimality Principles in the Regulation of Metabolic Networks

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Jan Berkhout

2012-08-01

Full Text Available One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular “task” of the network—its function—should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

Neural Networks Involved in Adolescent Reward Processing: An Activation Likelihood Estimation Meta-Analysis of Functional Neuroimaging Studies

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Silverman, Merav H.; Jedd, Kelly; Luciana, Monica

2015-01-01

Behavioral responses to, and the neural processing of, rewards change dramatically during adolescence and may contribute to observed increases in risk-taking during this developmental period. Functional MRI (fMRI) studies suggest differences between adolescents and adults in neural activation during reward processing, but findings are contradictory, and effects have been found in non-predicted directions. The current study uses an activation likelihood estimation (ALE) approach for quantitative meta-analysis of functional neuroimaging studies to: 1) confirm the network of brain regions involved in adolescents’ reward processing, 2) identify regions involved in specific stages (anticipation, outcome) and valence (positive, negative) of reward processing, and 3) identify differences in activation likelihood between adolescent and adult reward-related brain activation. Results reveal a subcortical network of brain regions involved in adolescent reward processing similar to that found in adults with major hubs including the ventral and dorsal striatum, insula, and posterior cingulate cortex (PCC). Contrast analyses find that adolescents exhibit greater likelihood of activation in the insula while processing anticipation relative to outcome and greater likelihood of activation in the putamen and amygdala during outcome relative to anticipation. While processing positive compared to negative valence, adolescents show increased likelihood for activation in the posterior cingulate cortex (PCC) and ventral striatum. Contrasting adolescent reward processing with the existing ALE of adult reward processing (Liu et al., 2011) reveals increased likelihood for activation in limbic, frontolimbic, and striatal regions in adolescents compared with adults. Unlike adolescents, adults also activate executive control regions of the frontal and parietal lobes. These findings support hypothesized elevations in motivated activity during adolescence. PMID:26254587

An improved correlation to predict molecular weight between crosslinks based on equilibrium degree of swelling of hydrogel networks.

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Jimenez-Vergara, Andrea C; Lewis, John; Hahn, Mariah S; Munoz-Pinto, Dany J

2018-04-01

Accurate characterization of hydrogel diffusional properties is of substantial importance for a range of biotechnological applications. The diffusional capacity of hydrogels has commonly been estimated using the average molecular weight between crosslinks (M c ), which is calculated based on the equilibrium degree of swelling. However, the existing correlation linking M c and equilibrium swelling fails to accurately reflect the diffusional properties of highly crosslinked hydrogel networks. Also, as demonstrated herein, the current model fails to accurately predict the diffusional properties of hydrogels when polymer concentration and molecular weight are varied simultaneously. To address these limitations, we evaluated the diffusional properties of 48 distinct hydrogel formulations using two different photoinitiator systems, employing molecular size exclusion as an alternative methodology to calculate average hydrogel mesh size. The resulting data were then utilized to develop a revised correlation between M c and hydrogel equilibrium swelling that substantially reduces the limitations associated with the current correlation. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 1339-1348, 2018. © 2017 Wiley Periodicals, Inc.

Albumin is synthesized in epididymis and aggregates in a high molecular mass glycoprotein complex involved in sperm-egg fertilization.

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Kélen Fabíola Arroteia

Full Text Available The epididymis has an important role in the maturation of sperm for fertilization, but little is known about the epididymal molecules involved in sperm modifications during this process. We have previously described the expression pattern for an antigen in epididymal epithelial cells that reacts with the monoclonal antibody (mAb TRA 54. Immunohistochemical and immunoblotting analyses suggest that the epitope of the epididymal antigen probably involves a sugar moiety that is released into the epididymal lumen in an androgen-dependent manner and subsequently binds to luminal sperm. Using column chromatography, SDS-PAGE with in situ digestion and mass spectrometry, we have identified the protein recognized by mAb TRA 54 in mouse epididymal epithelial cells. The ∼65 kDa protein is part of a high molecular mass complex (∼260 kDa that is also present in the sperm acrosomal vesicle and is completely released after the acrosomal reaction. The amino acid sequence of the protein corresponded to that of albumin. Immunoprecipitates with anti-albumin antibody contained the antigen recognized by mAb TRA 54, indicating that the epididymal molecule recognized by mAb TRA 54 is albumin. RT-PCR detected albumin mRNA in the epididymis and fertilization assays in vitro showed that the glycoprotein complex containing albumin was involved in the ability of sperm to recognize and penetrate the egg zona pellucida. Together, these results indicate that epididymal-derived albumin participates in the formation of a high molecular mass glycoprotein complex that has an important role in egg fertilization.

Early molecular events involved in Pinus pinaster Ait. somatic embryo development under reduced water availability: transcriptomic and proteomic analyses.

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Morel, Alexandre; Teyssier, Caroline; Trontin, Jean-François; Eliášová, Kateřina; Pešek, Bedřich; Beaufour, Martine; Morabito, Domenico; Boizot, Nathalie; Le Metté, Claire; Belal-Bessai, Leila; Reymond, Isabelle; Harvengt, Luc; Cadene, Martine; Corbineau, Françoise; Vágner, Martin; Label, Philippe; Lelu-Walter, Marie-Anne

2014-09-01

Maritime pine somatic embryos (SEs) require a reduction in water availability (high gellan gum concentration in the maturation medium) to reach the cotyledonary stage. This key switch, reported specifically for pine species, is not yet well understood. To facilitate the use of somatic embryogenesis for mass propagation of conifers, we need a better understanding of embryo development. Comparison of both transcriptome (Illumina RNA sequencing) and proteome [two-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis with mass spectrometry (MS) identification] of immature SEs, cultured on either high (9G) or low (4G) gellan gum concentration, was performed, together with analysis of water content, fresh and dry mass, endogenous abscisic acid (ABA; gas chromatography-MS), soluble sugars (high-pressure liquid chromatography), starch and confocal laser microscope observations. This multiscale, integrated analysis was used to unravel early molecular and physiological events involved in SE development. Under unfavorable conditions (4G), the glycolytic pathway was enhanced, possibly in relation to cell proliferation that may be antagonistic to SE development. Under favorable conditions (9G), SEs adapted to culture constraint by activating specific protective pathways, and ABA-mediated molecular and physiological responses promoting embryo development. Our results suggest that on 9G, germin-like protein and ubiquitin-protein ligase could be used as predictive markers of SE development, whereas protein phosphatase 2C could be a biomarker for culture adaptive responses. This is the first characterization of early molecular mechanisms involved in the development of pine SEs following an increase in gellan gum concentration in the maturation medium, and it is also the first report on somatic embryogenesis in conifers combining transcriptomic and proteomic datasets. © 2014 Scandinavian Plant Physiology Society.

Dehydrogenation involved Coulomb explosion of molecular C2H4FBr in an intense laser field

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Pei, Minjie; Yang, Yan; Zhang, Jian; Sun, Zhenrong

2018-04-01

The dissociative double ionization (DDI) of molecular 1-fluo-2-bromoethane (FBE) in an intense laser field has been investigated by dc-slice imaging technology. The DDI channels involved with dehydrogenation are revealed and it's believed both the charge distribution and the bound character of real potential energy surfaces of parent ions play important roles in the dissociation process. The relationship between the potential energy surfaces of the precursor species and the photofragment ejection angles are also discussed and analyzed. Furthermore, the competition between the DDI channels has been studied and the Csbnd C bond cleavages dominate the DDI process at relative higher laser intensity.

System Design for Nano-Network Communications

Science.gov (United States)

ShahMohammadian, Hoda

The potential applications of nanotechnology in a wide range of areas necessities nano-networking research. Nano-networking is a new type of networking which has emerged by applying nanotechnology to communication theory. Therefore, this dissertation presents a framework for physical layer communications in a nano-network and addresses some of the pressing unsolved challenges in designing a molecular communication system. The contribution of this dissertation is proposing well-justified models for signal propagation, noise sources, optimum receiver design and synchronization in molecular communication channels. The design of any communication system is primarily based on the signal propagation channel and noise models. Using the Brownian motion and advection molecular statistics, separate signal propagation and noise models are presented for diffusion-based and flow-based molecular communication channels. It is shown that the corrupting noise of molecular channels is uncorrelated and non-stationary with a signal dependent magnitude. The next key component of any communication system is the reception and detection process. This dissertation provides a detailed analysis of the effect of the ligand-receptor binding mechanism on the received signal, and develops the first optimal receiver design for molecular communications. The bit error rate performance of the proposed receiver is evaluated and the impact of medium motion on the receiver performance is investigated. Another important feature of any communication system is synchronization. In this dissertation, the first blind synchronization algorithm is presented for the molecular communication channels. The proposed algorithm uses a non-decision directed maximum likelihood criterion for estimating the channel delay. The Cramer-Rao lower bound is also derived and the performance of the proposed synchronization algorithm is evaluated by investigating its mean square error.

gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations.

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Serçinoglu, Onur; Ozbek, Pemra

2018-05-25

Atomistic molecular dynamics (MD) simulations generate a wealth of information related to the dynamics of proteins. If properly analyzed, this information can lead to new insights regarding protein function and assist wet-lab experiments. Aiming to identify interactions between individual amino acid residues and the role played by each in the context of MD simulations, we present a stand-alone software called gRINN (get Residue Interaction eNergies and Networks). gRINN features graphical user interfaces (GUIs) and a command-line interface for generating and analyzing pairwise residue interaction energies and energy correlations from protein MD simulation trajectories. gRINN utilizes the features of NAMD or GROMACS MD simulation packages and automatizes the steps necessary to extract residue-residue interaction energies from user-supplied simulation trajectories, greatly simplifying the analysis for the end-user. A GUI, including an embedded molecular viewer, is provided for visualization of interaction energy time-series, distributions, an interaction energy matrix, interaction energy correlations and a residue correlation matrix. gRINN additionally offers construction and analysis of Protein Energy Networks, providing residue-based metrics such as degrees, betweenness-centralities, closeness centralities as well as shortest path analysis. gRINN is free and open to all users without login requirement at http://grinn.readthedocs.io.

Postischemic revascularization: from cellular and molecular mechanisms to clinical applications.

Science.gov (United States)

Silvestre, Jean-Sébastien; Smadja, David M; Lévy, Bernard I

2013-10-01

After the onset of ischemia, cardiac or skeletal muscle undergoes a continuum of molecular, cellular, and extracellular responses that determine the function and the remodeling of the ischemic tissue. Hypoxia-related pathways, immunoinflammatory balance, circulating or local vascular progenitor cells, as well as changes in hemodynamical forces within vascular wall trigger all the processes regulating vascular homeostasis, including vasculogenesis, angiogenesis, arteriogenesis, and collateral growth, which act in concert to establish a functional vascular network in ischemic zones. In patients with ischemic diseases, most of the cellular (mainly those involving bone marrow-derived cells and local stem/progenitor cells) and molecular mechanisms involved in the activation of vessel growth and vascular remodeling are markedly impaired by the deleterious microenvironment characterized by fibrosis, inflammation, hypoperfusion, and inhibition of endogenous angiogenic and regenerative programs. Furthermore, cardiovascular risk factors, including diabetes, hypercholesterolemia, hypertension, diabetes, and aging, constitute a deleterious macroenvironment that participates to the abrogation of postischemic revascularization and tissue regeneration observed in these patient populations. Thus stimulation of vessel growth and/or remodeling has emerged as a new therapeutic option in patients with ischemic diseases. Many strategies of therapeutic revascularization, based on the administration of growth factors or stem/progenitor cells from diverse sources, have been proposed and are currently tested in patients with peripheral arterial disease or cardiac diseases. This review provides an overview from our current knowledge regarding molecular and cellular mechanisms involved in postischemic revascularization, as well as advances in the clinical application of such strategies of therapeutic revascularization.

Combined analysis of mRNA and miRNA identifies dehydration and salinity responsive key molecular players in citrus roots.

Science.gov (United States)

Xie, Rangjin; Zhang, Jin; Ma, Yanyan; Pan, Xiaoting; Dong, Cuicui; Pang, Shaoping; He, Shaolan; Deng, Lie; Yi, Shilai; Zheng, Yongqiang; Lv, Qiang

2017-02-06

Citrus is one of the most economically important fruit crops around world. Drought and salinity stresses adversely affected its productivity and fruit quality. However, the genetic regulatory networks and signaling pathways involved in drought and salinity remain to be elucidated. With RNA-seq and sRNA-seq, an integrative analysis of miRNA and mRNA expression profiling and their regulatory networks were conducted using citrus roots subjected to dehydration and salt treatment. Differentially expressed (DE) mRNA and miRNA profiles were obtained according to fold change analysis and the relationships between miRNAs and target mRNAs were found to be coherent and incoherent in the regulatory networks. GO enrichment analysis revealed that some crucial biological processes related to signal transduction (e.g. 'MAPK cascade'), hormone-mediated signaling pathways (e.g. abscisic acid- activated signaling pathway'), reactive oxygen species (ROS) metabolic process (e.g. 'hydrogen peroxide catabolic process') and transcription factors (e.g., 'MYB, ZFP and bZIP') were involved in dehydration and/or salt treatment. The molecular players in response to dehydration and salt treatment were partially overlapping. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-seq and sRNA-seq analysis. This study provides new insights into the molecular mechanisms how citrus roots respond to dehydration and salt treatment.

The emerging paradigm of network medicine in the study of human disease.

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Chan, Stephen Y; Loscalzo, Joseph

2012-07-20

The molecular pathways that govern human disease consist of molecular circuits that coalesce into complex, overlapping networks. These network pathways are presumably regulated in a coordinated fashion, but such regulation has been difficult to decipher using only reductionistic principles. The emerging paradigm of "network medicine" proposes to utilize insights garnered from network topology (eg, the static position of molecules in relation to their neighbors) as well as network dynamics (eg, the unique flux of information through the network) to understand better the pathogenic behavior of complex molecular interconnections that traditional methods fail to recognize. As methodologies evolve, network medicine has the potential to capture the molecular complexity of human disease while offering computational methods to discern how such complexity controls disease manifestations, prognosis, and therapy. This review introduces the fundamental concepts of network medicine and explores the feasibility and potential impact of network-based methods for predicting individual manifestations of human disease and designing rational therapies. Wherever possible, we emphasize the application of these principles to cardiovascular disease.

Bioinformatics analysis on molecular mechanism of rheum officinale in treatment of jaundice

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Shan, Si; Tu, Jun; Nie, Peng; Yan, Xiaojun

2017-01-01

Objective: To study the molecular mechanism of Rheum officinale in the treatment of Jaundice by building molecular networks and comparing canonical pathways. Methods: Target proteins of Rheum officinale and related genes of Jaundice were searched from Pubchem and Gene databases online respectively. Molecular networks and canonical pathways comparison analyses were performed by Ingenuity Pathway Analysis (IPA). Results: The molecular networks of Rheum officinale and Jaundice were complex and multifunctional. The 40 target proteins of Rheum officinale and 33 Homo sapiens genes of Jaundice were found in databases. There were 19 common pathways both related networks. Rheum officinale could regulate endothelial differentiation, Interleukin-1B (IL-1B) and Tumor Necrosis Factor (TNF) in these pathways. Conclusions: Rheum officinale treat Jaundice by regulating many effective nodes of Apoptotic pathway and cellular immunity related pathways.

Specificity and evolvability in eukaryotic protein interaction networks.

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Pedro Beltrao

2007-02-01

Full Text Available Progress in uncovering the protein interaction networks of several species has led to questions of what underlying principles might govern their organization. Few studies have tried to determine the impact of protein interaction network evolution on the observed physiological differences between species. Using comparative genomics and structural information, we show here that eukaryotic species have rewired their interactomes at a fast rate of approximately 10(-5 interactions changed per protein pair, per million years of divergence. For Homo sapiens this corresponds to 10(3 interactions changed per million years. Additionally we find that the specificity of binding strongly determines the interaction turnover and that different biological processes show significantly different link dynamics. In particular, human proteins involved in immune response, transport, and establishment of localization show signs of positive selection for change of interactions. Our analysis suggests that a small degree of molecular divergence can give rise to important changes at the network level. We propose that the power law distribution observed in protein interaction networks could be partly explained by the cell's requirement for different degrees of protein binding specificity.

Lightweight computational steering of very large scale molecular dynamics simulations

International Nuclear Information System (INIS)

Beazley, D.M.

1996-01-01

We present a computational steering approach for controlling, analyzing, and visualizing very large scale molecular dynamics simulations involving tens to hundreds of millions of atoms. Our approach relies on extensible scripting languages and an easy to use tool for building extensions and modules. The system is extremely easy to modify, works with existing C code, is memory efficient, and can be used from inexpensive workstations and networks. We demonstrate how we have used this system to manipulate data from production MD simulations involving as many as 104 million atoms running on the CM-5 and Cray T3D. We also show how this approach can be used to build systems that integrate common scripting languages (including Tcl/Tk, Perl, and Python), simulation code, user extensions, and commercial data analysis packages

The use of artificial neural network modeling to represent the process of concentration by molecular distillation of omega-3 from squid oil

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Rossi, P.

2014-12-01

Full Text Available The concentration of omega-3 compounds obtained for the esterification of squid oil by molecular distillation was carried out in two stages. This operation can process these thermolabile and high molecular weight components at very low temperatures. Given the mathematical complexity of the theoretical model, artificial neural networks (ANN have provided an alternative to a classical computing analysis. The objective of this study was to create a predictive model using artificial neural network techniques to represent the concentration process of omega-3 compounds obtained from squid oil using molecular distillation. Another objective of this study was to analyze the performance of two different alternatives of ANN modeling; one of them is a model that represents all variables in the process and the other is a global model that simulates only the input and output variables of the process. The alternative of the ANN global model showed the best fit to the experimental data.La concentración de compuestos omega-3, obtenidos de la esterificación de aceite de calamar, por destilación molecular fue llevada a cabo en dos etapas. Esta operación permite procesar componentes termolábiles y de alto peso molecular a muy bajas temperaturas. Dada la alta complejidad de los modelos teóricos, las redes neuronales artificiales (RNA conforman una alternativa al análisis computacional clásico. El objetivo de este estudio fue crear un modelo predictivo usando modelos de redes neuronales artificiales para representar el proceso de concentración de compuestos omega-3 obtenidos del aceite de calamar por destilación molecular. Otro objetivo de este estudio fue analizar el desenvolvimiento de dos alternativas de modelos RNA; uno de ellos es un modelo que representa todas las variables en el proceso y otro es un modelo global que simula solo las variables de entrada y de salida del proceso. La alternativa de un modelo RNA global mostró el mejor ajuste de los

ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

KAUST Repository

Kuwahara, Hiroyuki; Umarov, Ramzan; Almasri, Islam; Gao, Xin

2017-01-01

To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

KAUST Repository

Kuwahara, Hiroyuki

2017-03-01

To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells.

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Aurélien Naldi

2017-03-01

Full Text Available The ability to build in-depth cell signaling networks from vast experimental data is a key objective of computational biology. The spleen tyrosine kinase (Syk protein, a well-characterized key player in immune cell signaling, was surprisingly first shown by our group to exhibit an onco-suppressive function in mammary epithelial cells and corroborated by many other studies, but the molecular mechanisms of this function remain largely unsolved. Based on existing proteomic data, we report here the generation of an interaction-based network of signaling pathways controlled by Syk in breast cancer cells. Pathway enrichment of the Syk targets previously identified by quantitative phospho-proteomics indicated that Syk is engaged in cell adhesion, motility, growth and death. Using the components and interactions of these pathways, we bootstrapped the reconstruction of a comprehensive network covering Syk signaling in breast cancer cells. To generate in silico hypotheses on Syk signaling propagation, we developed a method allowing to rank paths between Syk and its targets. We first annotated the network according to experimental datasets. We then combined shortest path computation with random walk processes to estimate the importance of individual interactions and selected biologically relevant pathways in the network. Molecular and cell biology experiments allowed to distinguish candidate mechanisms that underlie the impact of Syk on the regulation of cortactin and ezrin, both involved in actin-mediated cell adhesion and motility. The Syk network was further completed with the results of our biological validation experiments. The resulting Syk signaling sub-networks can be explored via an online visualization platform.

A shear-induced network of aligned wormlike micelles in a sugar-based molecular gel. From gelation to biocompatibility assays.

Science.gov (United States)

Fitremann, Juliette; Lonetti, Barbara; Fratini, Emiliano; Fabing, Isabelle; Payré, Bruno; Boulé, Christelle; Loubinoux, Isabelle; Vaysse, Laurence; Oriol, Luis

2017-10-15

A new low molecular weight hydrogelator with a saccharide (lactobionic) polar head linked by azide-alkyne click chemistry was prepared in three steps. It was obtained in high purity without chromatography, by phase separation and ultrafiltration of the aqueous gel. Gelation was not obtained reproducibly by conventional heating-cooling cycles and instead was obtained by shearing the aqueous solutions, from 2 wt% to 0.25 wt%. This method of preparation favored the formation of a quite unusual network of interconnected large but thin 2D-sheets (7nm-thick) formed by the association side-by-side of long and aligned 7nm diameter wormlike micelles. It was responsible for the reproducible gelation at the macroscopic scale. A second network made of helical fibres with a 10-13nm diameter, more or less intertwined was also formed but was scarcely able to sustain a macroscopic gel on its own. The gels were analysed by TEM (Transmission Electronic Microscopy), cryo-TEM and SAXS (Small Angle X-ray Scattering). Molecular modelling was also used to highlight the possible conformations the hydrogelator can take. The gels displayed a weak and reversible transition near 20°C, close to room temperature, ascribed to the wormlike micelles 2D-sheets network. Heating over 30°C led to the loss of the gel macroscopic integrity, but gel fragments were still observed in suspension. A second transition near 50°C, ascribed to the network of helical fibres, finally dissolved completely these fragments. The gels showed thixotropic behaviour, recovering slowly their initial elastic modulus, in few hours, after injection through a needle. Stable gels were tested as scaffold for neural cell line culture, showing a reduced biocompatibility. This new gelator is a clear illustration of how controlling the pathway was critical for gel formation and how a new kind of self-assembly was obtained by shearing. Copyright © 2017 Elsevier Inc. All rights reserved.

Structural networks involved in attention and executive functions in multiple sclerosis

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Sara Llufriu

2017-01-01

Full Text Available Attention and executive deficits are disabling symptoms in multiple sclerosis (MS that have been related to disconnection mechanisms. We aimed to investigate changes in structural connectivity in MS and their association with attention and executive performance applying an improved framework that combines high order probabilistic tractography and anatomical exclusion criteria postprocessing. We compared graph theory metrics of structural networks and fractional anisotropy (FA of white matter (WM connections or edges between 72 MS subjects and 38 healthy volunteers (HV and assessed their correlation with cognition. Patients displayed decreased network transitivity, global efficiency and increased path length compared with HV (p < 0.05, corrected. Also, nodal strength was decreased in 26 of 84 gray matter regions. The distribution of nodes with stronger connections or hubs of the network was similar among groups except for the right pallidum and left insula, which became hubs in patients. MS subjects presented reduced edge FA widespread in the network, while FA was increased in 24 connections (p < 0.05, corrected. Decreased integrity of frontoparietal networks, deep gray nuclei and insula correlated with worse attention and executive performance (r between 0.38 and 0.55, p < 0.05, corrected. Contrarily, higher strength in the right transverse temporal cortex and increased FA of several connections (mainly from cingulate, frontal and occipital cortices were associated with worse functioning (r between −0.40 and −0.47, p < 0.05 corrected. In conclusion, structural brain connectivity is disturbed in MS due to widespread impairment of WM connections and gray matter structures. The increased edge connectivity suggests the presence of reorganization mechanisms at the structural level. Importantly, attention and executive performance relates to frontoparietal networks, deep gray nuclei and insula. These results support the relevance of

Conductance with stochastic resonance in Mn{sub 12} redox network without tuning

Energy Technology Data Exchange (ETDEWEB)

Hirano, Yoshiaki [Department of Chemistry, Graduate School of Science, Osaka University, 1-1 Machikaneyama-cho, Toyonaka, Osaka 560-0043 (Japan); Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui 910-8507 (Japan); Segawa, Yuji; Kawai, Tomoji [Institute of Scientific and Industrial Research (ISIR), Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka 567-0047 (Japan); Kuroda-Sowa, Takayoshi [Department of Chemistry, Faculty of Science and Engineering, Kinki University, 3-4-1 Kowakae, Higashi-Osaka, Osaka 577-8502 (Japan); Matsumoto, Takuya, E-mail: matsumoto-t@chem.sci.osaka-u.ac.jp [Department of Chemistry, Graduate School of Science, Osaka University, 1-1 Machikaneyama-cho, Toyonaka, Osaka 560-0043 (Japan)

2014-06-09

Artificial neuron-based information processing is one of the attractive approaches of molecular-scale electronics, which can exploit the ability of molecular system for self-assembling or self-organization. The self-organized Mn{sub 12}/DNA redox network shows nonlinear current-voltage characteristics that can be described by the Coulomb blockade network model. As a demonstration of the nonlinear network system, we have observed stochastic resonance without tuning for weak periodic input signals and thermal noise, which suggests a route to neural network composed of molecular materials.

Animal Hairs as Water-stimulated Shape Memory Materials: Mechanism and Structural Networks in Molecular Assemblies

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Xiao, Xueliang; Hu, Jinlian

2016-05-01

Animal hairs consisting of α-keratin biopolymers existing broadly in nature may be responsive to water for recovery to the innate shape from their fixed deformation, thus possess smart behavior, namely shape memory effect (SME). In this article, three typical animal hair fibers were first time investigated for their water-stimulated SME, and therefrom to identify the corresponding net-points and switches in their molecular and morphological structures. Experimentally, the SME manifested a good stability of high shape fixation ratio and reasonable recovery rate after many cycles of deformation programming under water stimulation. The effects of hydration on hair lateral size, recovery kinetics, dynamic mechanical behaviors and structural components (crystal, disulfide and hydrogen bonds) were then systematically studied. SME mechanisms were explored based on the variations of structural components in molecular assemblies of such smart fibers. A hybrid structural network model with single-switch and twin-net-points was thereafter proposed to interpret the water-stimulated shape memory mechanism of animal hairs. This original work is expected to provide inspiration for exploring other natural materials to reveal their smart functions and natural laws in animals including human as well as making more remarkable synthetic smart materials.

The Transmission of Gun and Other Weapon-Involved Violence Within Social Networks.

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Tracy, Melissa; Braga, Anthony A; Papachristos, Andrew V

2016-01-01

Fatal and nonfatal injuries resulting from gun violence remain a persistent problem in the United States. The available research suggests that gun violence diffuses among people and across places through social relationships. Understanding the relationship between gun violence within social networks and individual gun violence risk is critical in preventing the spread of gun violence within populations. This systematic review examines the existing scientific evidence on the transmission of gun and other weapon-related violence in household, intimate partner, peer, and co-offending networks. Our review identified 16 studies published between 1996 and 2015 that suggest that exposure to a victim or perpetrator of violence in one's interpersonal relationships and social networks increases the risk of individual victimization and perpetration. Formal network analyses find high concentrations of gun violence in small networks and that exposure to gun violence in one's networks is highly correlated with one's own probability of being a gunshot victim. Physical violence by parents and weapon use by intimate partners also increase risk for victimization and perpetration. Additional work is needed to better characterize the mechanisms through which network exposures increase individual risk for violence and to evaluate interventions aimed at disrupting the spread of gun and other weapon violence in high-risk social networks. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

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Oyang Yen-Jen

2010-10-01

Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

Neural Network Models for Free Radical Polymerization of Methyl Methacrylate

International Nuclear Information System (INIS)

Curteanu, S.; Leon, F.; Galea, D.

2003-01-01

In this paper, a neural network modeling of the batch bulk methyl methacrylate polymerization is performed. To obtain conversion, number and weight average molecular weights, three neural networks were built. Each was a multilayer perception with one or two hidden layers. The choice of network topology, i.e. the number of hidden layers and the number of neurons in these layers, was based on achieving a compromise between precision and complexity. Thus, it was intended to have an error as small as possible at the end of back-propagation training phases, while using a network with reduced complexity. The performances of the networks were evaluated by comparing network predictions with training data, validation data (which were not uses for training), and with the results of a mechanistic model. The accurate predictions of neural networks for monomer conversion, number average molecular weight and weight average molecular weight proves that this modeling methodology gives a good representation and generalization of the batch bulk methyl methacrylate polymerization. (author)

Review and application of group theory to molecular systems biology.

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Rietman, Edward A; Karp, Robert L; Tuszynski, Jack A

2011-06-22

In this paper we provide a review of selected mathematical ideas that can help us better understand the boundary between living and non-living systems. We focus on group theory and abstract algebra applied to molecular systems biology. Throughout this paper we briefly describe possible open problems. In connection with the genetic code we propose that it may be possible to use perturbation theory to explore the adjacent possibilities in the 64-dimensional space-time manifold of the evolving genome. With regards to algebraic graph theory, there are several minor open problems we discuss. In relation to network dynamics and groupoid formalism we suggest that the network graph might not be the main focus for understanding the phenotype but rather the phase space of the network dynamics. We show a simple case of a C6 network and its phase space network. We envision that the molecular network of a cell is actually a complex network of hypercycles and feedback circuits that could be better represented in a higher-dimensional space. We conjecture that targeting nodes in the molecular network that have key roles in the phase space, as revealed by analysis of the automorphism decomposition, might be a better way to drug discovery and treatment of cancer.

Understanding emergent functions in self-assembled fibrous networks

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Sinko, Robert; Keten, Sinan

2015-09-01

Understanding self-assembly processes of nanoscale building blocks and characterizing their properties are both imperative for designing new hierarchical, network materials for a wide range of structural, optoelectrical, and transport applications. Although the characterization and choices of these material building blocks have been well studied, our understanding of how to precisely program a specific morphology through self-assembly still must be significantly advanced. In the recent study by Xie et al (2015 Nanotechnology 26 205602), the self-assembly of end-functionalized nanofibres is investigated using a coarse-grained molecular model and offers fundamental insight into how to control the structural morphology of nanofibrous networks. Varying nanoscale networks are observed when the molecular interaction strength is changed and the findings suggest that self-assembly through the tuning of molecular interactions is a key strategy for designing nanostructured networks with specific topologies.

Linear network theory

CERN Document Server

Sander, K F

1964-01-01

Linear Network Theory covers the significant algebraic aspect of network theory, with minimal reference to practical circuits. The book begins the presentation of network analysis with the exposition of networks containing resistances only, and follows it up with a discussion of networks involving inductance and capacity by way of the differential equations. Classification and description of certain networks, equivalent networks, filter circuits, and network functions are also covered. Electrical engineers, technicians, electronics engineers, electricians, and students learning the intricacies

M-Polynomials and Topological Indices of Dominating David Derived Networks

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Kang Shin Min

2018-03-01

Full Text Available There is a strong relationship between the chemical characteristics of chemical compounds and their molecular structures. Topological indices are numerical values associated with the chemical molecular graphs that help to understand the physical features, chemical reactivity, and biological activity of chemical compound. Thus, the study of the topological indices is important. M-polynomial helps to recover many degree-based topological indices for example Zagreb indices, Randic index, symmetric division idex, inverse sum index etc. In this article we compute M-polynomials of dominating David derived networks of the first type, second type and third type of dimension n and find some topological properties by using these M-polynomials. The results are plotted using Maple to see the dependence of topological indices on the involved parameters.

Molecular regulation of plant cell wall extensibility

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Cosgrove, D. J.

1998-01-01

Gravity responses in plants often involve spatial and temporal changes in cell growth, which is regulated primarily by controlling the ability of the cell wall to extend. The wall is thought to be a cellulose-hemicellulose network embedded in a hydrated matrix of complex polysaccharides and a small amount of structural protein. The wall extends by a form of polymer creep, which is mediated by expansins, a novel group of wall-loosening proteins. Expansins were discovered during a molecular dissection of the "acid growth" behavior of cell walls. Expansin alters the rheology of plant walls in profound ways, yet its molecular mechanism of action is still uncertain. It lacks detectable hydrolytic activity against the major components of the wall, but it is able to disrupt noncovalent adhesion between wall polysaccharides. The discovery of a second family of expansins (beta-expansins) sheds light on the biological role of a major group of pollen allergens and implies that expansins have evolved for diverse developmental functions. Finally, the contribution of other processes to wall extensibility is briefly summarized.

Characterization of molecular associations involving L-ornithine and α-ketoglutaric acid: crystal structure of L-ornithinium α-ketoglutarate.

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Allouchi, H; Céolin, R; Berthon, L; Tombret, F; Rietveld, I B

2014-07-01

The crystal structure of L-ornithinium α-ketoglutarate (C5H13N2O2, C5H5O5) has been solved by direct methods using single crystal X-ray diffraction data. It crystallizes in the monoclinic system, space group P21, unit cell parameters a=15.4326(3), b=5.2015(1), c=16.2067(3) Å and β=91.986(1)°, containing two independent pairs of molecular ions in the asymmetric unit. An extensive hydrogen-bond network and electrostatic charges due to proton transfer provide an important part of the cohesive energy of the crystal. The conformational versatility of L-ornithine and α-ketoglutaric acid is illustrated by the present results and crystal structures available from the Cambridge Structural Database. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Network Pharmacology-Based Approach to Investigate the Analgesic Efficacy and Molecular Targets of Xuangui Dropping Pill for Treating Primary Dysmenorrhea

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Jihan Huang

2017-01-01

Full Text Available This study aimed to evaluate the clinical analgesic efficacy and identify the molecular targets of XGDP for treating primary dysmenorrhea (PD by a network pharmacology approach. Analysis of pain disappearance rate of XGDP in PD treatment was conducted based on data from phase II and III randomized, double-blind, double-simulation, and positive parallel controlled clinical trials. The bioactive compounds were obtained by the absorption, distribution, metabolism, and excretion processes with oral bioavailability (OB and drug-likeness (DL evaluation. Subsequently, target prediction, pathway identification, and network construction were employed to clarify the mechanisms of the analgesic effect of XGDP on PD. The pain disappearance rates in phase II and III clinical trials of XGDP in PD treatment were 62.5% and 55.8%, respectively, yielding a significant difference (P<0.05 when compared with the control group using Tongjingbao granules (TJBG. Among 331 compounds, 53 compounds in XGDP were identified as the active compounds related to PD through OB, DL, and target prediction. The active compounds and molecular targets of XGDP were identified, and our study showed that XGDP may exert its therapeutic effects on PD through the regulation of the targets related to anti-inflammation analgesia and central analgesia and relieving smooth muscle contraction.

The Prediction of Key Cytoskeleton Components Involved in Glomerular Diseases Based on a Protein-Protein Interaction Network.

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Ding, Fangrui; Tan, Aidi; Ju, Wenjun; Li, Xuejuan; Li, Shao; Ding, Jie

2016-01-01

Maintenance of the physiological morphologies of different types of cells and tissues is essential for the normal functioning of each system in the human body. Dynamic variations in cell and tissue morphologies depend on accurate adjustments of the cytoskeletal system. The cytoskeletal system in the glomerulus plays a key role in the normal process of kidney filtration. To enhance the understanding of the possible roles of the cytoskeleton in glomerular diseases, we constructed the Glomerular Cytoskeleton Network (GCNet), which shows the protein-protein interaction network in the glomerulus, and identified several possible key cytoskeletal components involved in glomerular diseases. In this study, genes/proteins annotated to the cytoskeleton were detected by Gene Ontology analysis, and glomerulus-enriched genes were selected from nine available glomerular expression datasets. Then, the GCNet was generated by combining these two sets of information. To predict the possible key cytoskeleton components in glomerular diseases, we then examined the common regulation of the genes in GCNet in the context of five glomerular diseases based on their transcriptomic data. As a result, twenty-one cytoskeleton components as potential candidate were highlighted for consistently down- or up-regulating in all five glomerular diseases. And then, these candidates were examined in relation to existing known glomerular diseases and genes to determine their possible functions and interactions. In addition, the mRNA levels of these candidates were also validated in a puromycin aminonucleoside(PAN) induced rat nephropathy model and were also matched with existing Diabetic Nephropathy (DN) transcriptomic data. As a result, there are 15 of 21 candidates in PAN induced nephropathy model were consistent with our predication and also 12 of 21 candidates were matched with differentially expressed genes in the DN transcriptomic data. By providing a novel interaction network and prediction, GCNet

Perceived Conventionality in Co-speech Gestures Involves the Fronto-Temporal Language Network

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Dhana Wolf

2017-11-01

Full Text Available Face-to-face communication is multimodal; it encompasses spoken words, facial expressions, gaze, and co-speech gestures. In contrast to linguistic symbols (e.g., spoken words or signs in sign language relying on mostly explicit conventions, gestures vary in their degree of conventionality. Bodily signs may have a general accepted or conventionalized meaning (e.g., a head shake or less so (e.g., self-grooming. We hypothesized that subjective perception of conventionality in co-speech gestures relies on the classical language network, i.e., the left hemispheric inferior frontal gyrus (IFG, Broca's area and the posterior superior temporal gyrus (pSTG, Wernicke's area and studied 36 subjects watching video-recorded story retellings during a behavioral and an functional magnetic resonance imaging (fMRI experiment. It is well documented that neural correlates of such naturalistic videos emerge as intersubject covariance (ISC in fMRI even without involving a stimulus (model-free analysis. The subjects attended either to perceived conventionality or to a control condition (any hand movements or gesture-speech relations. Such tasks modulate ISC in contributing neural structures and thus we studied ISC changes to task demands in language networks. Indeed, the conventionality task significantly increased covariance of the button press time series and neuronal synchronization in the left IFG over the comparison with other tasks. In the left IFG, synchronous activity was observed during the conventionality task only. In contrast, the left pSTG exhibited correlated activation patterns during all conditions with an increase in the conventionality task at the trend level only. Conceivably, the left IFG can be considered a core region for the processing of perceived conventionality in co-speech gestures similar to spoken language. In general, the interpretation of conventionalized signs may rely on neural mechanisms that engage during language comprehension.

MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

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Wasserman Wyeth W

2011-03-01

Full Text Available Abstract Background To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs, microRNAs (miRNAs and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. Results To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs. Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL. In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT, an evolutionary-conserved process which is implicated in embryonic development and disease. Conclusions MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http

Molecular interactions and residues involved in force generation in the T4 viral DNA packaging motor.

Science.gov (United States)

Migliori, Amy D; Smith, Douglas E; Arya, Gaurav

2014-12-12

Many viruses utilize molecular motors to package their genomes into preformed capsids. A striking feature of these motors is their ability to generate large forces to drive DNA translocation against entropic, electrostatic, and bending forces resisting DNA confinement. A model based on recently resolved structures of the bacteriophage T4 motor protein gp17 suggests that this motor generates large forces by undergoing a conformational change from an extended to a compact state. This transition is proposed to be driven by electrostatic interactions between complementarily charged residues across the interface between the N- and C-terminal domains of gp17. Here we use atomistic molecular dynamics simulations to investigate in detail the molecular interactions and residues involved in such a compaction transition of gp17. We find that although electrostatic interactions between charged residues contribute significantly to the overall free energy change of compaction, interactions mediated by the uncharged residues are equally if not more important. We identify five charged residues and six uncharged residues at the interface that play a dominant role in the compaction transition and also reveal salt bridging, van der Waals, and solvent hydrogen-bonding interactions mediated by these residues in stabilizing the compact form of gp17. The formation of a salt bridge between Glu309 and Arg494 is found to be particularly crucial, consistent with experiments showing complete abrogation in packaging upon Glu309Lys mutation. The computed contributions of several other residues are also found to correlate well with single-molecule measurements of impairments in DNA translocation activity caused by site-directed mutations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Protein Machineries Involved in the Attachment of Heme to Cytochrome c: Protein Structures and Molecular Mechanisms

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Carlo Travaglini-Allocatelli

2013-01-01

Full Text Available Cytochromes c (Cyt c are ubiquitous heme-containing proteins, mainly involved in electron transfer processes, whose structure and functions have been and still are intensely studied. Surprisingly, our understanding of the molecular mechanism whereby the heme group is covalently attached to the apoprotein (apoCyt in the cell is still largely unknown. This posttranslational process, known as Cyt c biogenesis or Cyt c maturation, ensures the stereospecific formation of the thioether bonds between the heme vinyl groups and the cysteine thiols of the apoCyt heme binding motif. To accomplish this task, prokaryotic and eukaryotic cells have evolved distinctive protein machineries composed of different proteins. In this review, the structural and functional properties of the main maturation apparatuses found in gram-negative and gram-positive bacteria and in the mitochondria of eukaryotic cells will be presented, dissecting the Cyt c maturation process into three functional steps: (i heme translocation and delivery, (ii apoCyt thioreductive pathway, and (iii apoCyt chaperoning and heme ligation. Moreover, current hypotheses and open questions about the molecular mechanisms of each of the three steps will be discussed, with special attention to System I, the maturation apparatus found in gram-negative bacteria.

Residue Geometry Networks: A Rigidity-Based Approach to the Amino Acid Network and Evolutionary Rate Analysis

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Fokas, Alexander S.; Cole, Daniel J.; Ahnert, Sebastian E.; Chin, Alex W.

2016-01-01

Amino acid networks (AANs) abstract the protein structure by recording the amino acid contacts and can provide insight into protein function. Herein, we describe a novel AAN construction technique that employs the rigidity analysis tool, FIRST, to build the AAN, which we refer to as the residue geometry network (RGN). We show that this new construction can be combined with network theory methods to include the effects of allowed conformal motions and local chemical environments. Importantly, this is done without costly molecular dynamics simulations required by other AAN-related methods, which allows us to analyse large proteins and/or data sets. We have calculated the centrality of the residues belonging to 795 proteins. The results display a strong, negative correlation between residue centrality and the evolutionary rate. Furthermore, among residues with high closeness, those with low degree were particularly strongly conserved. Random walk simulations using the RGN were also successful in identifying allosteric residues in proteins involved in GPCR signalling. The dynamic function of these residues largely remain hidden in the traditional distance-cutoff construction technique. Despite being constructed from only the crystal structure, the results in this paper suggests that the RGN can identify residues that fulfil a dynamical function. PMID:27623708

Improving Patient Involvement in the Drug Development Process: Case Study of Potential Applications from an Online Peer Support Network.

Science.gov (United States)

Anand, Amrutha; Brandwood, Helen Jane; Jameson Evans, Matt

2017-11-01

To date, social media has been used predominantly by the pharmaceutical industry to market products and to gather feedback and comments on products from consumers, a process termed social listening. However, social media has only been used cautiously in the drug development cycle, mainly because of regulations, restrictions on engagement with patients, or a lack of guidelines for social media use from regulatory bodies. Despite this cautious approach, there is a clear drive, from both the industry and consumers, for increased patient participation in various stages of the drug development process. The authors use the example of HealthUnlocked, one of the world's largest health networks, to illustrate the potential applications of online health communities as a means of increasing patient involvement at various stages of the drug development process. Having identified the willingness of the user population to be involved in research, numerous ways to engage users on the platform have been identified and explored. This commentary describes some of these approaches and reports how online health networks that encourage people to share their experiences in managing their health can, in turn, enable rapid patient engagement for clinical research within the constraints of industry regulation. Copyright © 2017 Elsevier HS Journals, Inc. All rights reserved.

Introductory note on Emergent Unconscious Knowledge Networks (Asygnodic Networks

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Henry Bakis

2016-05-01

Full Text Available This note introduces the following paper on the concept of Emergent Unconscious Knowledge Networks (Asygnodic Networks created by E. Roche and M. Blaine. The concept of asyngnosis explains a large number of diverse phenomena involving organizations, groups and decision making. It will present the genesis and definition of Asygnodic Networks and will focus on how they raise challenges to traditional theories of decision making and emerging social networks.

Nanoscale molecular communication networks: a game-theoretic perspective

Science.gov (United States)

Jiang, Chunxiao; Chen, Yan; Ray Liu, K. J.

2015-12-01

Currently, communication between nanomachines is an important topic for the development of novel devices. To implement a nanocommunication system, diffusion-based molecular communication is considered as a promising bio-inspired approach. Various technical issues about molecular communications, including channel capacity, noise and interference, and modulation and coding, have been studied in the literature, while the resource allocation problem among multiple nanomachines has not been well investigated, which is a very important issue since all the nanomachines share the same propagation medium. Considering the limited computation capability of nanomachines and the expensive information exchange cost among them, in this paper, we propose a game-theoretic framework for distributed resource allocation in nanoscale molecular communication systems. We first analyze the inter-symbol and inter-user interference, as well as bit error rate performance, in the molecular communication system. Based on the interference analysis, we formulate the resource allocation problem as a non-cooperative molecule emission control game, where the Nash equilibrium is found and proved to be unique. In order to improve the system efficiency while guaranteeing fairness, we further model the resource allocation problem using a cooperative game based on the Nash bargaining solution, which is proved to be proportionally fair. Simulation results show that the Nash bargaining solution can effectively ensure fairness among multiple nanomachines while achieving comparable social welfare performance with the centralized scheme.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

Science.gov (United States)

Lepoivre, Cyrille; Bergon, Aurélie; Lopez, Fabrice; Perumal, Narayanan B; Nguyen, Catherine; Imbert, Jean; Puthier, Denis

2012-01-31

Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information

Integration of Structural Dynamics and Molecular Evolution via Protein Interaction Networks: A New Era in Genomic Medicine

Science.gov (United States)

Kumar, Avishek; Butler, Brandon M.; Kumar, Sudhir; Ozkan, S. Banu

2016-01-01

Summary Sequencing technologies are revealing many new non-synonymous single nucleotide variants (nsSNVs) in each personal exome. To assess their functional impacts, comparative genomics is frequently employed to predict if they are benign or not. However, evolutionary analysis alone is insufficient, because it misdiagnoses many disease-associated nsSNVs, such as those at positions involved in protein interfaces, and because evolutionary predictions do not provide mechanistic insights into functional change or loss. Structural analyses can aid in overcoming both of these problems by incorporating conformational dynamics and allostery in nSNV diagnosis. Finally, protein-protein interaction networks using systems-level methodologies shed light onto disease etiology and pathogenesis. Bridging these network approaches with structurally resolved protein interactions and dynamics will advance genomic medicine. PMID:26684487

Shape-Shifting Droplet Networks.

Science.gov (United States)

Zhang, T; Wan, Duanduan; Schwarz, J M; Bowick, M J

2016-03-11

We consider a three-dimensional network of aqueous droplets joined by single lipid bilayers to form a cohesive, tissuelike material. The droplets in these networks can be programed to have distinct osmolarities so that osmotic gradients generate internal stresses via local fluid flows to cause the network to change shape. We discover, using molecular dynamics simulations, a reversible folding-unfolding process by adding an osmotic interaction with the surrounding environment which necessarily evolves dynamically as the shape of the network changes. This discovery is the next important step towards osmotic robotics in this system. We also explore analytically and numerically how the networks become faceted via buckling and how quasi-one-dimensional networks become three dimensional.

IAEA consultants' meeting: 9th meeting of atomic and molecular data centres and ALADDIN network, Vienna, September 20 and 21, 1990

International Nuclear Information System (INIS)

Janev, R.K.

1990-11-01

This Summary Report contains the proceedings and the conclusions of the IAEA Consultants' Meeting: 9th Meeting of Atomic and Molecular Data Centres and ALADDIN Network, convened on September 20 and 21, 1990, at the IAEA Headquarters in Vienna. The Progress Reports of national atomic data centres and reports on the ALADDIN status and developments are also included as appendices to the present Report. (author). Refs, figs and tabs

Regulatory network analysis of Epstein-Barr virus identifies functional modules and hub genes involved in infectious mononucleosis.

Science.gov (United States)

Poorebrahim, Mansour; Salarian, Ali; Najafi, Saeideh; Abazari, Mohammad Foad; Aleagha, Maryam Nouri; Dadras, Mohammad Nasr; Jazayeri, Seyed Mohammad; Ataei, Atousa; Poortahmasebi, Vahdat

2017-05-01

Epstein-Barr virus (EBV) is the most common cause of infectious mononucleosis (IM) and establishes lifetime infection associated with a variety of cancers and autoimmune diseases. The aim of this study was to develop an integrative gene regulatory network (GRN) approach and overlying gene expression data to identify the representative subnetworks for IM and EBV latent infection (LI). After identifying differentially expressed genes (DEGs) in both IM and LI gene expression profiles, functional annotations were applied using gene ontology (GO) and BiNGO tools, and construction of GRNs, topological analysis and identification of modules were carried out using several plugins of Cytoscape. In parallel, a human-EBV GRN was generated using the Hu-Vir database for further analyses. Our analysis revealed that the majority of DEGs in both IM and LI were involved in cell-cycle and DNA repair processes. However, these genes showed a significant negative correlation in the IM and LI states. Furthermore, cyclin-dependent kinase 2 (CDK2) - a hub gene with the highest centrality score - appeared to be the key player in cell cycle regulation in IM disease. The most significant functional modules in the IM and LI states were involved in the regulation of the cell cycle and apoptosis, respectively. Human-EBV network analysis revealed several direct targets of EBV proteins during IM disease. Our study provides an important first report on the response to IM/LI EBV infection in humans. An important aspect of our data was the upregulation of genes associated with cell cycle progression and proliferation.

Network methods to support user involvement in qualitative data analyses: an introduction to Participatory Theme Elicitation.

Science.gov (United States)

Best, Paul; Badham, Jennifer; Corepal, Rekesh; O'Neill, Roisin F; Tully, Mark A; Kee, Frank; Hunter, Ruth F

2017-11-23

While Patient and Public Involvement (PPI) is encouraged throughout the research process, engagement is typically limited to intervention design and post-analysis stages. There are few approaches to participatory data analyses within complex health interventions. Using qualitative data from a feasibility randomised controlled trial (RCT), this proof-of-concept study tests the value of a new approach to participatory data analysis called Participatory Theme Elicitation (PTE). Forty excerpts were given to eight members of a youth advisory PPI panel to sort into piles based on their perception of related thematic content. Using algorithms to detect communities in networks, excerpts were then assigned to a thematic cluster that combined the panel members' perspectives. Network analysis techniques were also used to identify key excerpts in each grouping that were then further explored qualitatively. While PTE analysis was, for the most part, consistent with the researcher-led analysis, young people also identified new emerging thematic content. PTE appears promising for encouraging user led identification of themes arising from qualitative data collected during complex interventions. Further work is required to validate and extend this method. ClinicalTrials.gov, ID: NCT02455986 . Retrospectively Registered on 21 May 2015.

Molecular genetics

International Nuclear Information System (INIS)

Parkinson, D.R.; Krontiris, T.G.

1986-01-01

In this chapter the authors review new findings concerning the molecular genetics of malignant melanoma in the context of other information obtained from clinical, epidemiologic, and cytogenetic studies in this malignancy. These new molecular approaches promise to provide a more complete understanding of the mechanisms involved in the development of melanoma, thereby suggesting new methods for its treatment and prevention

Role of a Water Network around the Mn4CaO5 Cluster in Photosynthetic Water Oxidation: A Fourier Transform Infrared Spectroscopy and Quantum Mechanics/Molecular Mechanics Calculation Study.

Science.gov (United States)

Nakamura, Shin; Ota, Kai; Shibuya, Yuichi; Noguchi, Takumi

2016-01-26

Photosynthetic water oxidation takes place at the Mn4CaO5 cluster in photosystem II. Around the Mn4CaO5 cluster, a hydrogen bond network is formed by several water molecules, including four water ligands. To clarify the role of this water network in the mechanism of water oxidation, we investigated the effects of the removal of Ca(2+) and substitution with metal ions on the vibrations of water molecules coupled to the Mn4CaO5 cluster by means of Fourier transform infrared (FTIR) difference spectroscopy and quantum mechanics/molecular mechanics (QM/MM) calculations. The OH stretching vibrations of nine water molecules forming a network between D1-D61 and YZ were calculated using the QM/MM method. On the the calculated normal modes, a broad positive feature at 3200-2500 cm(-1) in an S2-minus-S1 FTIR spectrum was attributed to the vibrations of strongly hydrogen-bonded OH bonds of water involving the vibrations of water ligands to a Mn ion and the in-phase coupled vibration of a water network connected to YZ, while bands in the 3700-3500 cm(-1) region were assigned to the coupled vibrations of weakly hydrogen-bonded OH bonds of water. All the water bands were lost upon Ca(2+) depletion and Ba(2+) substitution, which inhibit the S2 → S3 transition, indicating that a solid water network was broken by these treatments. By contrast, Sr(2+) substitution slightly altered the water bands around 3600 cm(-1), reflecting minor modification in water interactions, consistent with the retention of water oxidation activity with a decreased efficiency. These results suggest that the water network around the Mn4CaO5 cluster plays an essential role in the water oxidation mechanism particularly in a concerted process of proton transfer and water insertion during the S2 → S3 transition.

Protein diffusion in photopolymerized poly(ethylene glycol) hydrogel networks

International Nuclear Information System (INIS)

Engberg, Kristin; Frank, Curtis W

2011-01-01

In this study, protein diffusion through swollen hydrogel networks prepared from end-linked poly(ethylene glycol)-diacrylate (PEG-DA) was investigated. Hydrogels were prepared via photopolymerization from PEG-DA macromonomer solutions of two molecular weights, 4600 Da and 8000 Da, with three initial solid contents: 20, 33 and 50 wt/wt% PEG. Diffusion coefficients for myoglobin traveling across the hydrogel membrane were determined for all PEG network compositions. The diffusion coefficient depended on PEG molecular weight and initial solid content, with the slowest diffusion occurring through lower molecular weight, high-solid-content networks (D gel = 0.16 ± 0.02 x 10 -8 cm 2 s -1 ) and the fastest diffusion occurring through higher molecular weight, low-solid-content networks (D gel = 11.05 ± 0.43 x 10 -8 cm 2 s -1 ). Myoglobin diffusion coefficients increased linearly with the increase of water content within the hydrogels. The permeability of three larger model proteins (horseradish peroxidase, bovine serum albumin and immunoglobulin G) through PEG(8000) hydrogel membranes was also examined, with the observation that globular molecules as large as 10.7 nm in hydrodynamic diameter can diffuse through the PEG network. Protein diffusion coefficients within the PEG hydrogels ranged from one to two orders of magnitude lower than the diffusion coefficients in free water. Network defects were determined to be a significant contributing factor to the observed protein diffusion.

Community Structure Analysis of Transcriptional Networks Reveals Distinct Molecular Pathways for Early- and Late-Onset Temporal Lobe Epilepsy with Childhood Febrile Seizures

Science.gov (United States)

Moreira-Filho, Carlos Alberto; Bando, Silvia Yumi; Bertonha, Fernanda Bernardi; Iamashita, Priscila; Silva, Filipi Nascimento; Costa, Luciano da Fontoura; Silva, Alexandre Valotta; Castro, Luiz Henrique Martins; Wen, Hung-Tzu

2015-01-01

Age at epilepsy onset has a broad impact on brain plasticity and epilepsy pathomechanisms. Prolonged febrile seizures in early childhood (FS) constitute an initial precipitating insult (IPI) commonly associated with mesial temporal lobe epilepsy (MTLE). FS-MTLE patients may have early disease onset, i.e. just after the IPI, in early childhood, or late-onset, ranging from mid-adolescence to early adult life. The mechanisms governing early (E) or late (L) disease onset are largely unknown. In order to unveil the molecular pathways underlying E and L subtypes of FS-MTLE we investigated global gene expression in hippocampal CA3 explants of FS-MTLE patients submitted to hippocampectomy. Gene coexpression networks (GCNs) were obtained for the E and L patient groups. A network-based approach for GCN analysis was employed allowing: i) the visualization and analysis of differentially expressed (DE) and complete (CO) - all valid GO annotated transcripts - GCNs for the E and L groups; ii) the study of interactions between all the system’s constituents based on community detection and coarse-grained community structure methods. We found that the E-DE communities with strongest connection weights harbor highly connected genes mainly related to neural excitability and febrile seizures, whereas in L-DE communities these genes are not only involved in network excitability but also playing roles in other epilepsy-related processes. Inversely, in E-CO the strongly connected communities are related to compensatory pathways (seizure inhibition, neuronal survival and responses to stress conditions) while in L-CO these communities harbor several genes related to pro-epileptic effects, seizure-related mechanisms and vulnerability to epilepsy. These results fit the concept, based on fMRI and behavioral studies, that early onset epilepsies, although impacting more severely the hippocampus, are associated to compensatory mechanisms, while in late MTLE development the brain is less able to

Dynamics of associating networks

Science.gov (United States)

Tang, Shengchang; Habicht, Axel; Wang, Muzhou; Li, Shuaili; Seiffert, Sebastian; Olsen, Bradley

Associating polymers offer important technological solutions to renewable and self-healing materials, conducting electrolytes for energy storage and transport, and vehicles for cell and protein deliveries. The interplay between polymer topologies and association chemistries warrants new interesting physics from associating networks, yet poses significant challenges to study these systems over a wide range of time and length scales. In a series of studies, we explored self-diffusion mechanisms of associating polymers above the percolation threshold, by combining experimental measurements using forced Rayleigh scattering and analytical insights from a two-state model. Despite the differences in molecular structures, a universal super-diffusion phenomenon is observed when diffusion of molecular species is hindered by dissociation kinetics. The molecular dissociation rate can be used to renormalize shear rheology data, which yields an unprecedented time-temperature-concentration superposition. The obtained shear rheology master curves provide experimental evidence of the relaxation hierarchy in associating networks.

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

Science.gov (United States)

Trevino, Victor; Cassese, Alberto; Nagy, Zsuzsanna; Zhuang, Xiaodong; Herbert, John; Antczak, Philipp; Clarke, Kim; Davies, Nicholas; Rahman, Ayesha; Campbell, Moray J; Guindani, Michele; Bicknell, Roy; Vannucci, Marina; Falciani, Francesco

2016-04-01

The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks

A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

Directory of Open Access Journals (Sweden)

Victor Trevino

2016-04-01

Full Text Available The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell

Astroglial Metabolic Networks Sustain Hippocampal Synaptic Transmission

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Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

2008-12-01

Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

Astroglial metabolic networks sustain hippocampal synaptic transmission.

Science.gov (United States)

Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

2008-12-05

Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

Transcriptome profiling of the Plutella xylostella (Lepidoptera: Plutellidae) ovary reveals genes involved in oogenesis.

Science.gov (United States)

Peng, Lu; Wang, Lei; Yang, Yi-Fan; Zou, Ming-Min; He, Wei-Yi; Wang, Yue; Wang, Qing; Vasseur, Liette; You, Min-Sheng

2017-12-30

As a specialized organ, the insect ovary performs valuable functions by ensuring fecundity and population survival. Oogenesis is the complex physiological process resulting in the production of mature eggs, which are involved in epigenetic programming, germ cell behavior, cell cycle regulation, etc. Identification of the genes involved in ovary development and oogenesis is critical to better understand the reproductive biology and screening for the potential molecular targets in Plutella xylostella, a worldwide destructive pest of economically major crops. Based on transcriptome sequencing, a total of 7.88Gb clean nucleotides was obtained, with 19,934 genes and 1861 new transcripts being identified. Expression profiling indicated that 61.7% of the genes were expressed (FPKM≥1) in the P. xylostella ovary. GO annotation showed that the pathways of multicellular organism reproduction and multicellular organism reproduction process, as well as gamete generation and chorion were significantly enriched. Processes that were most likely relevant to reproduction included the spliceosome, ubiquitin mediated proteolysis, endocytosis, PI3K-Akt signaling pathway, insulin signaling pathway, cAMP signaling pathway, and focal adhesion were identified in the top 20 'highly represented' KEGG pathways. Functional genes involved in oogenesis were further analyzed and validated by qRT-PCR to show their potential predominant roles in P. xylostella reproduction. Our newly developed P. xylostella ovary transcriptome provides an overview of the gene expression profiling in this specialized tissue and the functional gene network closely related to the ovary development and oogenesis. This is the first genome-wide transcriptome dataset of P. xylostella ovary that includes a subset of functionally activated genes. This global approach will be the basis for further studies on molecular mechanisms of P. xylostella reproduction aimed at screening potential molecular targets for integrated pest

Exponential growth for self-reproduction in a catalytic reaction network: relevance of a minority molecular species and crowdedness

Science.gov (United States)

Kamimura, Atsushi; Kaneko, Kunihiko

2018-03-01

Explanation of exponential growth in self-reproduction is an important step toward elucidation of the origins of life because optimization of the growth potential across rounds of selection is necessary for Darwinian evolution. To produce another copy with approximately the same composition, the exponential growth rates for all components have to be equal. How such balanced growth is achieved, however, is not a trivial question, because this kind of growth requires orchestrated replication of the components in stochastic and nonlinear catalytic reactions. By considering a mutually catalyzing reaction in two- and three-dimensional lattices, as represented by a cellular automaton model, we show that self-reproduction with exponential growth is possible only when the replication and degradation of one molecular species is much slower than those of the others, i.e., when there is a minority molecule. Here, the synergetic effect of molecular discreteness and crowding is necessary to produce the exponential growth. Otherwise, the growth curves show superexponential growth because of nonlinearity of the catalytic reactions or subexponential growth due to replication inhibition by overcrowding of molecules. Our study emphasizes that the minority molecular species in a catalytic reaction network is necessary for exponential growth at the primitive stage of life.

Commentary: Biochemistry and Molecular Biology Educators Launch National Network

Science.gov (United States)

Bailey, Cheryl; Bell, Ellis; Johnson, Margaret; Mattos, Carla; Sears, Duane; White, Harold B.

2010-01-01

The American Society of Biochemistry and Molecular Biology (ASBMB) has launched an National Science Foundation (NSF)-funded 5 year project to support biochemistry and molecular biology educators learning what and how students learn. As a part of this initiative, hundreds of life scientists will plan and develop a rich central resource for…

Network coding at different layers in wireless networks

CERN Document Server

2016-01-01

This book focuses on how to apply network coding at different layers in wireless networks – including MAC, routing, and TCP – with special focus on cognitive radio networks. It discusses how to select parameters in network coding (e.g., coding field, number of packets involved, and redundant information ration) in order to be suitable for the varying wireless environments. The book explores how to deploy network coding in MAC to improve network performance and examines joint network coding with opportunistic routing to improve the successful rate of routing. In regards to TCP and network coding, the text considers transport layer protocol working with network coding to overcome the transmission error rate, particularly with how to use the ACK feedback of TCP to enhance the efficiency of network coding. The book pertains to researchers and postgraduate students, especially whose interests are in opportunistic routing and TCP in cognitive radio networks.

First meeting of the atomic and molecular data centre network, Vienna, 9-13 May 1977. Summary report

International Nuclear Information System (INIS)

Lorenz, A.; Seamon, R.E.

1977-08-01

The general objective of the effort started at this meeting is the formation of an internationally coordinated network of centres and groups for the systematic world-wide compilation, evaluation, exchange and dissemination of bibliographic and numerical A+M data required by the fusion community. The specific accomplishments of this meeting were the establishment of agreements for the cooperation between existing A+M data centres and groups and the IAEA Nuclear Data Section/A+M Data Unit with regard to the Quarterly Bulletin on Atomic and Molecular Data for Fusion, the Bibliographic Index to Atomic Collision Data, and the exchange of evaluated atomic collision data

A novel strategy involved in [corrected] anti-oxidative defense: the conversion of NADH into NADPH by a metabolic network.

Directory of Open Access Journals (Sweden)

Ranji Singh

Full Text Available The reduced nicotinamide adenine dinucleotide phosphate (NADPH is pivotal to the cellular anti-oxidative defence strategies in most organisms. Although its production mediated by different enzyme systems has been relatively well-studied, metabolic networks dedicated to the biogenesis of NADPH have not been fully characterized. In this report, a metabolic pathway that promotes the conversion of reduced nicotinamide adenine dinucleotide (NADH, a pro-oxidant into NADPH has been uncovered in Pseudomonas fluorescens exposed to oxidative stress. Enzymes such as pyruvate carboxylase (PC, malic enzyme (ME, malate dehydrogenase (MDH, malate synthase (MS, and isocitrate lyase (ICL that are involved in disparate metabolic modules, converged to create a metabolic network aimed at the transformation of NADH into NADPH. The downregulation of phosphoenol carboxykinase (PEPCK and the upregulation of pyruvate kinase (PK ensured that this metabolic cycle fixed NADH into NADPH to combat the oxidative stress triggered by the menadione insult. This is the first demonstration of a metabolic network invoked to generate NADPH from NADH, a process that may be very effective in combating oxidative stress as the increase of an anti-oxidant is coupled to the decrease of a pro-oxidant.

Modular co-evolution of metabolic networks

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Yu Zhong-Hao

2007-08-01

Full Text Available Abstract Background The architecture of biological networks has been reported to exhibit high level of modularity, and to some extent, topological modules of networks overlap with known functional modules. However, how the modular topology of the molecular network affects the evolution of its member proteins remains unclear. Results In this work, the functional and evolutionary modularity of Homo sapiens (H. sapiens metabolic network were investigated from a topological point of view. Network decomposition shows that the metabolic network is organized in a highly modular core-periphery way, in which the core modules are tightly linked together and perform basic metabolism functions, whereas the periphery modules only interact with few modules and accomplish relatively independent and specialized functions. Moreover, over half of the modules exhibit co-evolutionary feature and belong to specific evolutionary ages. Peripheral modules tend to evolve more cohesively and faster than core modules do. Conclusion The correlation between functional, evolutionary and topological modularity suggests that the evolutionary history and functional requirements of metabolic systems have been imprinted in the architecture of metabolic networks. Such systems level analysis could demonstrate how the evolution of genes may be placed in a genome-scale network context, giving a novel perspective on molecular evolution.

Retrofitting of heat exchanger networks involving streams with variable heat capacity: Application of single and multi-objective optimization

International Nuclear Information System (INIS)

Sreepathi, Bhargava Krishna; Rangaiah, G.P.

2015-01-01

Heat exchanger network (HEN) retrofitting improves the energy efficiency of the current process by reducing external utilities. In this work, HEN retrofitting involving streams having variable heat capacity is studied. For this, enthalpy values of a stream are fitted to a continuous cubic polynomial instead of a stepwise approach employed in the previous studies [1,2]. The former methodology is closer to reality as enthalpy or heat capacity changes gradually instead of step changes. Using the polynomial fitting formulation, single objective optimization (SOO) and multi-objective optimization (MOO) of a HEN retrofit problem are investigated. The results obtained show an improvement in the utility savings, and MOO provides many Pareto-optimal solutions to choose from. Also, Pareto-optimal solutions involving area addition in existing heat exchangers only (but no new exchangers and no structural modifications) are found and provided for comparison with those involving new exchangers and structural modifications as well. - Highlights: • HEN retrofitting involving streams with variable heat capacities is studied. • A continuous approach to handle variable heat capacity is proposed and tested. • Better and practical solutions are obtained for HEN retrofitting in process plants. • Pareto-optimal solutions provide many alternate choices for HEN retrofitting

Molecular simulation strategy for mechanical modeling of amorphous/porous low-dielectric constant materials

NARCIS (Netherlands)

Yuan, C.A.; Sluis, van der O.; Zhang, G.Q.; Ernst, L.J.; Driel, van W.D.; Flower, A.E.; Silfhout, van R.B.R.

2008-01-01

We propose an amorphous/porous molecular connection network generation algorithm for simulating the material stiffness of a low-k material (SiOC:H). Based on a given concentration of the basic building blocks, this algorithm will generate an approximate and large amorphous network. The molecular

Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

Directory of Open Access Journals (Sweden)

Liang Jinghang

2012-08-01

Full Text Available Abstract Background Various computational models have been of interest due to their use in the modelling of gene regulatory networks (GRNs. As a logical model, probabilistic Boolean networks (PBNs consider molecular and genetic noise, so the study of PBNs provides significant insights into the understanding of the dynamics of GRNs. This will ultimately lead to advances in developing therapeutic methods that intervene in the process of disease development and progression. The applications of PBNs, however, are hindered by the complexities involved in the computation of the state transition matrix and the steady-state distribution of a PBN. For a PBN with n genes and N Boolean networks, the complexity to compute the state transition matrix is O(nN22n or O(nN2n for a sparse matrix. Results This paper presents a novel implementation of PBNs based on the notions of stochastic logic and stochastic computation. This stochastic implementation of a PBN is referred to as a stochastic Boolean network (SBN. An SBN provides an accurate and efficient simulation of a PBN without and with random gene perturbation. The state transition matrix is computed in an SBN with a complexity of O(nL2n, where L is a factor related to the stochastic sequence length. Since the minimum sequence length required for obtaining an evaluation accuracy approximately increases in a polynomial order with the number of genes, n, and the number of Boolean networks, N, usually increases exponentially with n, L is typically smaller than N, especially in a network with a large number of genes. Hence, the computational efficiency of an SBN is primarily limited by the number of genes, but not directly by the total possible number of Boolean networks. Furthermore, a time-frame expanded SBN enables an efficient analysis of the steady-state distribution of a PBN. These findings are supported by the simulation results of a simplified p53 network, several randomly generated networks and a

Cancerology: to see and to treat with molecular imaging

International Nuclear Information System (INIS)

2004-01-01

By allowing to visualize, beyond the organs and tissues structure, the molecules present inside cells and their action in cell functioning, to the genome level, the molecular imaging opens a new era in biology and medicine and creates the conditions for the perfecting of targeting and personalised treatments of cancers. The E.M.I.L. network is the only European network in molecular imaging for the cancer. It has been initiated and is coordinated by 'the genes expression in vivo imaging group' of the Cea at Orsay. The E.M.I.L network represents 43 organisms of 13 european countries with 6 technological platforms. (N.C.)

Design alternatives for wavelength routing networks

Science.gov (United States)

Miliotis, K.; Papadimitriou, G. I.; Pomportsis, A. S.

2003-03-01

This paper attempts to provide a high level overview of many of the technologies employed in optical networks with a focus on wavelength-routing networks. Optical networks involve a number of technologies from the physics of light through protocols and networks architectures. In fact there is so much technology and know-how that most people involved with optical networks only have a full understanding of the narrow area they deal with. We start first examining the principles that govern light and its use as a wave guide, and then turn our focus to the various components that constitute an optical network and conclude with the description of all optical networks and wavelength-routed networks in greater detail.

Integration of structural dynamics and molecular evolution via protein interaction networks: a new era in genomic medicine.

Science.gov (United States)

Kumar, Avishek; Butler, Brandon M; Kumar, Sudhir; Ozkan, S Banu

2015-12-01

Sequencing technologies are revealing many new non-synonymous single nucleotide variants (nsSNVs) in each personal exome. To assess their functional impacts, comparative genomics is frequently employed to predict if they are benign or not. However, evolutionary analysis alone is insufficient, because it misdiagnoses many disease-associated nsSNVs, such as those at positions involved in protein interfaces, and because evolutionary predictions do not provide mechanistic insights into functional change or loss. Structural analyses can aid in overcoming both of these problems by incorporating conformational dynamics and allostery in nSNV diagnosis. Finally, protein-protein interaction networks using systems-level methodologies shed light onto disease etiology and pathogenesis. Bridging these network approaches with structurally resolved protein interactions and dynamics will advance genomic medicine. Copyright © 2015 Elsevier Ltd. All rights reserved.

Stochastic thermodynamics, fluctuation theorems and molecular machines

International Nuclear Information System (INIS)

Seifert, Udo

2012-01-01

Stochastic thermodynamics as reviewed here systematically provides a framework for extending the notions of classical thermodynamics such as work, heat and entropy production to the level of individual trajectories of well-defined non-equilibrium ensembles. It applies whenever a non-equilibrium process is still coupled to one (or several) heat bath(s) of constant temperature. Paradigmatic systems are single colloidal particles in time-dependent laser traps, polymers in external flow, enzymes and molecular motors in single molecule assays, small biochemical networks and thermoelectric devices involving single electron transport. For such systems, a first-law like energy balance can be identified along fluctuating trajectories. For a basic Markovian dynamics implemented either on the continuum level with Langevin equations or on a discrete set of states as a master equation, thermodynamic consistency imposes a local-detailed balance constraint on noise and rates, respectively. Various integral and detailed fluctuation theorems, which are derived here in a unifying approach from one master theorem, constrain the probability distributions for work, heat and entropy production depending on the nature of the system and the choice of non-equilibrium conditions. For non-equilibrium steady states, particularly strong results hold like a generalized fluctuation–dissipation theorem involving entropy production. Ramifications and applications of these concepts include optimal driving between specified states in finite time, the role of measurement-based feedback processes and the relation between dissipation and irreversibility. Efficiency and, in particular, efficiency at maximum power can be discussed systematically beyond the linear response regime for two classes of molecular machines, isothermal ones such as molecular motors, and heat engines such as thermoelectric devices, using a common framework based on a cycle decomposition of entropy production. (review article)

Profiling spermatogenic failure in adult testes bearing Sox9-deficient Sertoli cells identifies genes involved in feminization, inflammation and stress

Directory of Open Access Journals (Sweden)

Barrionuevo Francisco

2010-12-01

Full Text Available Abstract Background Sox9 (Sry box containing gene 9 is a DNA-binding transcription factor involved in chondrocyte development and sex determination. The protein's absence in testicular Sertoli nurse cells has been shown to disrupt testicular function in adults but little is known at the genome-wide level about molecular events concomitant with testicular break-down. Methods To determine the genome-wide effect on mRNA concentrations triggered by the absence of Sox9 in Sertoli cells we analysed adult testicular tissue from wild-type versus mutant mice with high-density oligonucleotide microarrays and integrated the output of this experiment with regulatory motif predictions and protein-protein network data. Results We report the genome-wide mRNA signature of adult testes lacking Sox9 in Sertoli cells before and after the onset of late spermatogenic failure as compared to fertile controls. The GeneChip data integrated with evolutionarily conserved Sox9 DNA binding motifs and regulatory network data identified genes involved in feminization, stress response and inflammation. Conclusions Our results extend previous observations that genes required for female gonadogenesis are up-regulated in the absence of Sox9 in fetal Sertoli cells to the adult stage. Importantly, we identify gene networks involved in immunological processes and stress response which is reminiscent of a phenomenon occurring in a sub-group of infertile men. This suggests mice lacking Sox9 in their Sertoli cells to be a potentially useful model for adult human testicular failure.

Viral Disease Networks?

Science.gov (United States)

Gulbahce, Natali; Yan, Han; Vidal, Marc; Barabasi, Albert-Laszlo

2010-03-01

Viral infections induce multiple perturbations that spread along the links of the biological networks of the host cells. Understanding the impact of these cascading perturbations requires an exhaustive knowledge of the cellular machinery as well as a systems biology approach that reveals how individual components of the cellular system function together. Here we describe an integrative method that provides a new approach to studying virus-human interactions and its correlations with diseases. Our method involves the combined utilization of protein - protein interactions, protein -- DNA interactions, metabolomics and gene - disease associations to build a ``viraldiseasome''. By solely using high-throughput data, we map well-known viral associated diseases and predict new candidate viral diseases. We use microarray data of virus-infected tissues and patient medical history data to further test the implications of the viral diseasome. We apply this method to Epstein-Barr virus and Human Papillomavirus and shed light into molecular development of viral diseases and disease pathways.

Social Network Sites, Friends, and Celebrities: The Roles of Social Comparison and Celebrity Involvement in Adolescents’ Body Image Dissatisfaction

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Shirley S. Ho

2016-08-01

Full Text Available This study applies the social comparison theory to examine the effects of adolescents’ engagement in comparison with friends and celebrities on social network sites (SNSs on (a their body image dissatisfaction (BID and (b their drive to be thin (DT or muscular (DM. The study also examines celebrity involvement as an antecedent of the outcome variables. Data were collected through a survey of 1,059 adolescents in Singapore. Regression analyses indicate that SNSs use was related to adolescents’ BID. Specifically, social comparison with friends on SNSs was significantly associated with adolescents’ BID, DT, and DM. Gender differences were also observed—social comparison with celebrities was significantly associated with BID and DT among female adolescents. Celebrity involvement was significantly associated with male BID. Theoretical and practical implications were discussed.

A lateralized functional auditory network is involved in anuran ...

Indian Academy of Sciences (India)

2016-10-05

Oct 5, 2016 ... menting a statistical, predictive notion of causality whereby causes precede to help ... GCCA methods provides a chance to investigate the brain networks ...... by the grants from the National Natural Science Foundation of China (No. .... vocal competition is dynamic and strongly affected by social contexts in ...

Catalysis and communication in dynamic molecular networks

NARCIS (Netherlands)

Fanlo Virgos, Hugo

2015-01-01

The interactions of a Dynamic Combinatorial Library (DCL) of molecules with specific targets leads to composition changes of the library which can reveal potential guests and / or catalysts. In this thesis some chemical systems have been proposed to achieve a certain level of molecular complexity

Hydration of excess electrons trapped in charge pockets on molecular surfaces

Science.gov (United States)

Jalbout, Abraham F.; Del Castillo, R.; Adamowicz, Ludwik

2007-01-01

In this work we strive to design a novel electron trap located on a molecular surface. The process of electron trapping involves hydration of the trapped electron. Previous calculations on surface electron trapping revealed that clusters of OH groups can form stable hydrogen-bonded networks on one side of a hydrocarbon surface (i.e. cyclohexane sheets), while the hydrogen atoms on the opposite side of the surface form pockets of positive charge that can attract extra negative charge. The excess electron density on such surfaces can be further stabilized by interactions with water molecules. Our calculations show that these anionic systems are stable with respect to vertical electron detachment (VDE).

Expression profiling of Crambe abyssinica under arsenate stress identifies genes and gene networks involved in arsenic metabolism and detoxification

Directory of Open Access Journals (Sweden)

Kandasamy Suganthi

2010-06-01

Full Text Available Abstract Background Arsenic contamination is widespread throughout the world and this toxic metalloid is known to cause cancers of organs such as liver, kidney, skin, and lung in human. In spite of a recent surge in arsenic related studies, we are still far from a comprehensive understanding of arsenic uptake, detoxification, and sequestration in plants. Crambe abyssinica, commonly known as 'abyssinian mustard', is a non-food, high biomass oil seed crop that is naturally tolerant to heavy metals. Moreover, it accumulates significantly higher levels of arsenic as compared to other species of the Brassicaceae family. Thus, C. abyssinica has great potential to be utilized as an ideal inedible crop for phytoremediation of heavy metals and metalloids. However, the mechanism of arsenic metabolism in higher plants, including C. abyssinica, remains elusive. Results To identify the differentially expressed transcripts and the pathways involved in arsenic metabolism and detoxification, C. abyssinica plants were subjected to arsenate stress and a PCR-Select Suppression Subtraction Hybridization (SSH approach was employed. A total of 105 differentially expressed subtracted cDNAs were sequenced which were found to represent 38 genes. Those genes encode proteins functioning as antioxidants, metal transporters, reductases, enzymes involved in the protein degradation pathway, and several novel uncharacterized proteins. The transcripts corresponding to the subtracted cDNAs showed strong upregulation by arsenate stress as confirmed by the semi-quantitative RT-PCR. Conclusions Our study revealed novel insights into the plant defense mechanisms and the regulation of genes and gene networks in response to arsenate toxicity. The differential expression of transcripts encoding glutathione-S-transferases, antioxidants, sulfur metabolism, heat-shock proteins, metal transporters, and enzymes in the ubiquitination pathway of protein degradation as well as several unknown

Expression profiling of Crambe abyssinica under arsenate stress identifies genes and gene networks involved in arsenic metabolism and detoxification

Science.gov (United States)

2010-01-01

Background Arsenic contamination is widespread throughout the world and this toxic metalloid is known to cause cancers of organs such as liver, kidney, skin, and lung in human. In spite of a recent surge in arsenic related studies, we are still far from a comprehensive understanding of arsenic uptake, detoxification, and sequestration in plants. Crambe abyssinica, commonly known as 'abyssinian mustard', is a non-food, high biomass oil seed crop that is naturally tolerant to heavy metals. Moreover, it accumulates significantly higher levels of arsenic as compared to other species of the Brassicaceae family. Thus, C. abyssinica has great potential to be utilized as an ideal inedible crop for phytoremediation of heavy metals and metalloids. However, the mechanism of arsenic metabolism in higher plants, including C. abyssinica, remains elusive. Results To identify the differentially expressed transcripts and the pathways involved in arsenic metabolism and detoxification, C. abyssinica plants were subjected to arsenate stress and a PCR-Select Suppression Subtraction Hybridization (SSH) approach was employed. A total of 105 differentially expressed subtracted cDNAs were sequenced which were found to represent 38 genes. Those genes encode proteins functioning as antioxidants, metal transporters, reductases, enzymes involved in the protein degradation pathway, and several novel uncharacterized proteins. The transcripts corresponding to the subtracted cDNAs showed strong upregulation by arsenate stress as confirmed by the semi-quantitative RT-PCR. Conclusions Our study revealed novel insights into the plant defense mechanisms and the regulation of genes and gene networks in response to arsenate toxicity. The differential expression of transcripts encoding glutathione-S-transferases, antioxidants, sulfur metabolism, heat-shock proteins, metal transporters, and enzymes in the ubiquitination pathway of protein degradation as well as several unknown novel proteins serve as

Northern emporia and maritime networks. Modelling past communication using archaeological network analysis

DEFF Research Database (Denmark)

Sindbæk, Søren Michael

2015-01-01

preserve patterns of thisinteraction. Formal network analysis and modelling holds the potential to identify anddemonstrate such patterns, where traditional methods often prove inadequate. Thearchaeological study of communication networks in the past, however, calls for radically different analytical...... this is not a problem of network analysis, but network synthesis: theclassic problem of cracking codes or reconstructing black-box circuits. It is proposedthat archaeological approaches to network synthesis must involve a contextualreading of network data: observations arising from individual contexts, morphologies...

Systems analysis of chaperone networks in the malarial parasite Plasmodium falciparum.

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Soundara Raghavan Pavithra

2007-09-01

Full Text Available Molecular chaperones participate in the maintenance of cellular protein homeostasis, cell growth and differentiation, signal transduction, and development. Although a vast body of information is available regarding individual chaperones, few studies have attempted a systems level analysis of chaperone function. In this paper, we have constructed a chaperone interaction network for the malarial parasite, Plasmodium falciparum. P. falciparum is responsible for several million deaths every year, and understanding the biology of the parasite is a top priority. The parasite regularly experiences heat shock as part of its life cycle, and chaperones have often been implicated in parasite survival and growth. To better understand the participation of chaperones in cellular processes, we created a parasite chaperone network by combining experimental interactome data with in silico analysis. We used interolog mapping to predict protein-protein interactions for parasite chaperones based on the interactions of corresponding human chaperones. This data was then combined with information derived from existing high-throughput yeast two-hybrid assays. Analysis of the network reveals the broad range of functions regulated by chaperones. The network predicts involvement of chaperones in chromatin remodeling, protein trafficking, and cytoadherence. Importantly, it allows us to make predictions regarding the functions of hypothetical proteins based on their interactions. It allows us to make specific predictions about Hsp70-Hsp40 interactions in the parasite and assign functions to members of the Hsp90 and Hsp100 families. Analysis of the network provides a rational basis for the anti-malarial activity of geldanamycin, a well-known Hsp90 inhibitor. Finally, analysis of the network provides a theoretical basis for further experiments designed toward understanding the involvement of this important class of molecules in parasite biology.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks

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Lepoivre Cyrille

2012-01-01

Full Text Available Abstract Background Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. Results We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices, (ii potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii regulatory interactions curated from the literature, (iv predicted post-transcriptional regulation by micro-RNA, (v protein kinase-substrate interactions and (vi physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration

Molecular beam epitaxial growth of graphene and ridge-structure networks of graphene

International Nuclear Information System (INIS)

Maeda, Fumihiko; Hibino, Hiroki

2011-01-01

By gas-source molecular beam epitaxy (MBE) using cracked ethanol, we grew graphene at substrate temperatures between 600 and 915 °C on graphene formed on SiC(0 0 0 1) by thermal decomposition. To investigate the substrate temperature dependence of graphene growth we analysed the MBE-grown graphene by Raman spectroscopy and in situ x-ray photoelectron spectroscopy (XPS) and observed it by atomic force microscopy (AFM) and cross-sectional transmission electron microscopy (TEM). Analyses using the G-band peak and the peak intensity ratio between D- and G-band peaks in the Raman spectra revealed that growth at higher temperatures improved the crystallinity and increased the domain size. Although the growth rate decreased at higher temperatures, as revealed by XPS, these results indicated that growth at a higher temperature is effective in obtaining graphene of higher quality. Furthermore, the AFM and TEM observations revealed a network of fin-like ridge structures of graphene sticking out from the surface. The presence of these 'graphene nanofins' indicated that two-dimensional islands of graphene are surrounded by the nanofins, and the island size was estimated to be 67 nm using the average distance between the nanofins.

EMQN/CMGS best practice guidelines for the molecular genetic testing of Huntington disease.

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Losekoot, Monique; van Belzen, Martine J; Seneca, Sara; Bauer, Peter; Stenhouse, Susan A R; Barton, David E

2013-05-01

Huntington disease (HD) is caused by the expansion of an unstable polymorphic trinucleotide (CAG)n repeat in exon 1 of the HTT gene, which translates into an extended polyglutamine tract in the protein. Laboratory diagnosis of HD involves estimation of the number of CAG repeats. Molecular genetic testing for HD is offered in a wide range of laboratories both within and outside the European community. In order to measure the quality and raise the standard of molecular genetic testing in these laboratories, the European Molecular Genetics Quality Network has organized a yearly external quality assessment (EQA) scheme for molecular genetic testing of HD for over 10 years. EQA compares a laboratory's output with a fixed standard both for genotyping and reporting of the results to the referring physicians. In general, the standard of genotyping is very high but the clarity of interpretation and reporting of the test result varies more widely. This emphasizes the need for best practice guidelines for this disorder. We have therefore developed these best practice guidelines for genetic testing for HD to assist in testing and reporting of results. The analytical methods and the potential pitfalls of molecular genetic testing are highlighted and the implications of the different test outcomes for the consultand and his or her family members are discussed.

Posttransplantation lymphoproliferative disease involving the pituitary gland.

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Meriden, Zina; Bullock, Grant C; Bagg, Adam; Bonatti, Hugo; Cousar, John B; Lopes, M Beatriz; Robbins, Mark K; Cathro, Helen P

2010-11-01

Posttransplantation lymphoproliferative disorders (PTLD) are heterogeneous lesions with variable morphology, immunophenotype, and molecular characteristics. Multiple distinct primary lesions can occur in PTLD, rarely with both B-cell and T-cell characteristics. Lesions can involve both grafted organs and other sites; however, PTLD involving the pituitary gland has not been previously reported. We describe a patient who developed Epstein-Barr virus-negative PTLD 13 years posttransplantation involving the terminal ileum and pituitary, which was simultaneously involved by a pituitary adenoma. Immunohistochemistry of the pituitary lesion showed expression of CD79a, CD3, and CD7 with clonal rearrangements of both T-cell receptor gamma chain (TRG@) and immunoglobulin heavy chain (IGH@) genes. The terminal ileal lesion was immunophenotypically and molecularly distinct. This is the first report of pituitary PTLD and illustrates the potentially complex nature of PTLD. Copyright © 2010 Elsevier Inc. All rights reserved.

Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules

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Bersanelli, Matteo; Mosca, Ettore; Remondini, Daniel; Castellani, Gastone; Milanesi, Luciano

2016-01-01

A relation exists between network proximity of molecular entities in interaction networks, functional similarity and association with diseases. The identification of network regions associated with biological functions and pathologies is a major goal in systems biology. We describe a network diffusion-based pipeline for the interpretation of different types of omics in the context of molecular interaction networks. We introduce the network smoothing index, a network-based quantity that allows to jointly quantify the amount of omics information in genes and in their network neighbourhood, using network diffusion to define network proximity. The approach is applicable to both descriptive and inferential statistics calculated on omics data. We also show that network resampling, applied to gene lists ranked by quantities derived from the network smoothing index, indicates the presence of significantly connected genes. As a proof of principle, we identified gene modules enriched in somatic mutations and transcriptional variations observed in samples of prostate adenocarcinoma (PRAD). In line with the local hypothesis, network smoothing index and network resampling underlined the existence of a connected component of genes harbouring molecular alterations in PRAD. PMID:27731320

Time-Series Analyses of Transcriptomes and Proteomes Reveal Molecular Networks Underlying Oil Accumulation in Canola.

Science.gov (United States)

Wan, Huafang; Cui, Yixin; Ding, Yijuan; Mei, Jiaqin; Dong, Hongli; Zhang, Wenxin; Wu, Shiqi; Liang, Ying; Zhang, Chunyu; Li, Jiana; Xiong, Qing; Qian, Wei

2016-01-01

Understanding the regulation of lipid metabolism is vital for genetic engineering of canola ( Brassica napus L.) to increase oil yield or modify oil composition. We conducted time-series analyses of transcriptomes and proteomes to uncover the molecular networks associated with oil accumulation and dynamic changes in these networks in canola. The expression levels of genes and proteins were measured at 2, 4, 6, and 8 weeks after pollination (WAP). Our results show that the biosynthesis of fatty acids is a dominant cellular process from 2 to 6 WAP, while the degradation mainly happens after 6 WAP. We found that genes in almost every node of fatty acid synthesis pathway were significantly up-regulated during oil accumulation. Moreover, significant expression changes of two genes, acetyl-CoA carboxylase and acyl-ACP desaturase, were detected on both transcriptomic and proteomic levels. We confirmed the temporal expression patterns revealed by the transcriptomic analyses using quantitative real-time PCR experiments. The gene set association analysis show that the biosynthesis of fatty acids and unsaturated fatty acids are the most significant biological processes from 2-4 WAP and 4-6 WAP, respectively, which is consistent with the results of time-series analyses. These results not only provide insight into the mechanisms underlying lipid metabolism, but also reveal novel candidate genes that are worth further investigation for their values in the genetic engineering of canola.

EXTERNALITIES IN EXCHANGE NETWORKS AN ADAPTATION OF EXISTING THEORIES OF EXCHANGE NETWORKS

NARCIS (Netherlands)

Dijkstra, Jacob

2009-01-01

The present paper extends the focus of network exchange research to externalities in exchange networks. Externalities of exchange are defined as direct effects on an actor's utility, of an exchange in which this actor is not involved. Existing theories in the field of network exchange do not inform

Combination of Markov state models and kinetic networks for the analysis of molecular dynamics simulations of peptide folding.

Science.gov (United States)

Radford, Isolde H; Fersht, Alan R; Settanni, Giovanni

2011-06-09

Atomistic molecular dynamics simulations of the TZ1 beta-hairpin peptide have been carried out using an implicit model for the solvent. The trajectories have been analyzed using a Markov state model defined on the projections along two significant observables and a kinetic network approach. The Markov state model allowed for an unbiased identification of the metastable states of the system, and provided the basis for commitment probability calculations performed on the kinetic network. The kinetic network analysis served to extract the main transition state for folding of the peptide and to validate the results from the Markov state analysis. The combination of the two techniques allowed for a consistent and concise characterization of the dynamics of the peptide. The slowest relaxation process identified is the exchange between variably folded and denatured species, and the second slowest process is the exchange between two different subsets of the denatured state which could not be otherwise identified by simple inspection of the projected trajectory. The third slowest process is the exchange between a fully native and a partially folded intermediate state characterized by a native turn with a proximal backbone H-bond, and frayed side-chain packing and termini. The transition state for the main folding reaction is similar to the intermediate state, although a more native like side-chain packing is observed.

Molecular partners of hNOT/ALG3, the human counterpart of the Drosophila NOT and yeast ALG3 gene, suggest its involvement in distinct cellular processes relevant to congenital disorders of glycosylation, cancer, neurodegeneration and a variety of further pathologies.

Science.gov (United States)

Hacker, Benedikt; Schultheiß, Christoph; Döring, Michael; Kurzik-Dumke, Ursula

2018-06-01

This study provides first insights into the involvement of hNOT/ALG3, the human counterpart of the Drosophila Neighbour of TID and yeast ALG3 gene, in various putative molecular networks. HNOT/ALG3 encodes two translated transcripts encoding precursor proteins differing in their N-terminus and showing 33% identity with the yeast asparagine-linked glycosylation 3 (ALG3) protein. Experimental evidence for the functional homology of the proteins of fly and man in the N-glycosylation has still to be provided. In this study, using the yeast two-hybrid technique we identify 17 molecular partners of hNOT-1/ALG3-1. We disclose the building of hNOT/ALG3 homodimers and provide experimental evidence for its in vivo interaction with the functionally linked proteins OSBP, OSBPL9 and LRP1, the SYPL1 protein and the transcription factor CREB3. Regarding the latter, we show that the 55 kDa N-glycosylated hNOT-1/ALG3-1 molecule binds the N-glycosylated CREB3 precursor but does not interact with CREB3's proteolytic products specific to the endoplasmic reticulum and to the nucleus. The interaction between the two partners is a prerequisite for the proteolytic activation of CREB3. In case of the further binding partners, our data suggest that hNOT-1/ALG3-1 interacts with both OSBPs and with their direct targets LRP1 and VAMP/VAP-A. Moreover, our results show that various partners of hNOT-1/ALG3-1 interact with its diverse post translationally processed products destined to distinct cellular compartments. Generally, our data suggest the involvement of hNOT-1/ALG3-1 in various molecular contexts determining essential processes associated with distinct cellular machineries and related to various pathologies, such as cancer, viral infections, neuronal and immunological disorders and CDG.

A molecular switch driving inactivation in the cardiac K+ channel HERG.

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David A Köpfer

Full Text Available K(+ channels control transmembrane action potentials by gating open or closed in response to external stimuli. Inactivation gating, involving a conformational change at the K(+ selectivity filter, has recently been recognized as a major K(+ channel regulatory mechanism. In the K(+ channel hERG, inactivation controls the length of the human cardiac action potential. Mutations impairing hERG inactivation cause life-threatening cardiac arrhythmia, which also occur as undesired side effects of drugs. In this paper, we report atomistic molecular dynamics simulations, complemented by mutational and electrophysiological studies, which suggest that the selectivity filter adopts a collapsed conformation in the inactivated state of hERG. The selectivity filter is gated by an intricate hydrogen bond network around residues S620 and N629. Mutations of this hydrogen bond network are shown to cause inactivation deficiency in electrophysiological measurements. In addition, drug-related conformational changes around the central cavity and pore helix provide a functional mechanism for newly discovered hERG activators.

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

Science.gov (United States)

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

2015-01-01

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

Omics analysis of human bone to identify genes and molecular networks regulating skeletal remodeling in health and disease.

Science.gov (United States)

Reppe, Sjur; Datta, Harish K; Gautvik, Kaare M

2017-08-01

The skeleton is a metabolically active organ throughout life where specific bone cell activity and paracrine/endocrine factors regulate its morphogenesis and remodeling. In recent years, an increasing number of reports have used multi-omics technologies to characterize subsets of bone biological molecular networks. The skeleton is affected by primary and secondary disease, lifestyle and many drugs. Therefore, to obtain relevant and reliable data from well characterized patient and control cohorts are vital. Here we provide a brief overview of omics studies performed on human bone, of which our own studies performed on trans-iliacal bone biopsies from postmenopausal women with osteoporosis (OP) and healthy controls are among the first and largest. Most other studies have been performed on smaller groups of patients, undergoing hip replacement for osteoarthritis (OA) or fracture, and without healthy controls. The major findings emerging from the combined studies are: 1. Unstressed and stressed bone show profoundly different gene expression reflecting differences in bone turnover and remodeling and 2. Omics analyses comparing healthy/OP and control/OA cohorts reveal characteristic changes in transcriptomics, epigenomics (DNA methylation), proteomics and metabolomics. These studies, together with genome-wide association studies, in vitro observations and transgenic animal models have identified a number of genes and gene products that act via Wnt and other signaling systems and are highly associated to bone density and fracture. Future challenge is to understand the functional interactions between bone-related molecular networks and their significance in OP and OA pathogenesis, and also how the genomic architecture is affected in health and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

NABIC marker database: A molecular markers information network of agricultural crops.

Science.gov (United States)

Kim, Chang-Kug; Seol, Young-Joo; Lee, Dong-Jun; Jeong, In-Seon; Yoon, Ung-Han; Lee, Gang-Seob; Hahn, Jang-Ho; Park, Dong-Suk

2013-01-01

In 2013, National Agricultural Biotechnology Information Center (NABIC) reconstructs a molecular marker database for useful genetic resources. The web-based marker database consists of three major functional categories: map viewer, RSN marker and gene annotation. It provides 7250 marker locations, 3301 RSN marker property, 3280 molecular marker annotation information in agricultural plants. The individual molecular marker provides information such as marker name, expressed sequence tag number, gene definition and general marker information. This updated marker-based database provides useful information through a user-friendly web interface that assisted in tracing any new structures of the chromosomes and gene positional functions using specific molecular markers. The database is available for free at http://nabic.rda.go.kr/gere/rice/molecularMarkers/

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

Science.gov (United States)

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

Network Diffusion-Based Prioritization of Autism Risk Genes Identifies Significantly Connected Gene Modules

Directory of Open Access Journals (Sweden)

Ettore Mosca

2017-09-01

Full Text Available Autism spectrum disorder (ASD is marked by a strong genetic heterogeneity, which is underlined by the low overlap between ASD risk gene lists proposed in different studies. In this context, molecular networks can be used to analyze the results of several genome-wide studies in order to underline those network regions harboring genetic variations associated with ASD, the so-called “disease modules.” In this work, we used a recent network diffusion-based approach to jointly analyze multiple ASD risk gene lists. We defined genome-scale prioritizations of human genes in relation to ASD genes from multiple studies, found significantly connected gene modules associated with ASD and predicted genes functionally related to ASD risk genes. Most of them play a role in synapsis and neuronal development and function; many are related to syndromes that can be in comorbidity with ASD and the remaining are involved in epigenetics, cell cycle, cell adhesion and cancer.

Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

Science.gov (United States)

Rodius, Sophie; Androsova, Ganna; Götz, Lou; Liechti, Robin; Crespo, Isaac; Merz, Susanne; Nazarov, Petr V.; de Klein, Niek; Jeanty, Céline; González-Rosa, Juan M.; Muller, Arnaud; Bernardin, Francois; Niclou, Simone P.; Vallar, Laurent; Mercader, Nadia; Ibberson, Mark; Xenarios, Ioannis; Azuaje, Francisco

2016-05-01

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration.

Structure-Activity Relationship in TLR4 Mutations: Atomistic Molecular Dynamics Simulations and Residue Interaction Network Analysis

Science.gov (United States)

Anwar, Muhammad Ayaz; Choi, Sangdun

2017-03-01

Toll-like receptor 4 (TLR4), a vital innate immune receptor present on cell surfaces, initiates a signaling cascade during danger and bacterial intrusion. TLR4 needs to form a stable hexamer complex, which is necessary to dimerize the cytoplasmic domain. However, D299G and T399I polymorphism may abrogate the stability of the complex, leading to compromised TLR4 signaling. Crystallography provides valuable insights into the structural aspects of the TLR4 ectodomain; however, the dynamic behavior of polymorphic TLR4 is still unclear. Here, we employed molecular dynamics simulations (MDS), as well as principal component and residue network analyses, to decipher the structural aspects and signaling propagation associated with mutations in TLR4. The mutated complexes were less cohesive, displayed local and global variation in the secondary structure, and anomalous decay in rotational correlation function. Principal component analysis indicated that the mutated complexes also exhibited distinct low-frequency motions, which may be correlated to the differential behaviors of these TLR4 variants. Moreover, residue interaction networks (RIN) revealed that the mutated TLR4/myeloid differentiation factor (MD) 2 complex may perpetuate abnormal signaling pathways. Cumulatively, the MDS and RIN analyses elucidated the mutant-specific conformational alterations, which may help in deciphering the mechanism of loss-of-function mutations.

PyPathway: Python Package for Biological Network Analysis and Visualization.

Science.gov (United States)

Xu, Yang; Luo, Xiao-Chun

2018-05-01

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

Prospects of engineering thermotolerance in crops through modulation of heat stress transcription factor and heat shock protein networks.

Science.gov (United States)

Fragkostefanakis, Sotirios; Röth, Sascha; Schleiff, Enrico; Scharf, Klaus-Dieter

2015-09-01

Cell survival under high temperature conditions involves the activation of heat stress response (HSR), which in principle is highly conserved among different organisms, but shows remarkable complexity and unique features in plant systems. The transcriptional reprogramming at higher temperatures is controlled by the activity of the heat stress transcription factors (Hsfs). Hsfs allow the transcriptional activation of HSR genes, among which heat shock proteins (Hsps) are best characterized. Hsps belong to multigene families encoding for molecular chaperones involved in various processes including maintenance of protein homeostasis as a requisite for optimal development and survival under stress conditions. Hsfs form complex networks to activate downstream responses, but are concomitantly subjected to cell-type-dependent feedback regulation through factor-specific physical and functional interactions with chaperones belonging to Hsp90, Hsp70 and small Hsp families. There is increasing evidence that the originally assumed specialized function of Hsf/chaperone networks in the HSR turns out to be a complex central stress response system that is involved in the regulation of a broad variety of other stress responses and may also have substantial impact on various developmental processes. Understanding in detail the function of such regulatory networks is prerequisite for sustained improvement of thermotolerance in important agricultural crops. © 2014 John Wiley & Sons Ltd.

Deciphering metabonomics biomarkers-targets interactions for psoriasis vulgaris by network pharmacology.

Science.gov (United States)

Gu, Jiangyong; Li, Li; Wang, Dongmei; Zhu, Wei; Han, Ling; Zhao, Ruizhi; Xu, Xiaojie; Lu, Chuanjian

2018-06-01

Psoriasis vulgaris is a chronic inflammatory and immune-mediated skin disease. 44 metabonomics biomarkers were identified by high-throughput liquid chromatography coupled to mass spectrometry in our previous work, but the roles of metabonomics biomarkers in the pathogenesis of psoriasis is unclear. The metabonomics biomarker-enzyme network was constructed. The key metabonomics biomarkers and enzymes were screened out by network analysis. The binding affinity between each metabonomics biomarker and target was calculated by molecular docking. A binding energy-weighted polypharmacological index was introduced to evaluate the importance of target-related pathways. Long-chain fatty acids, phospholipids, Estradiol and NADH were the most important metabonomics biomarkers. Most key enzymes belonged hydrolase, thioesterase and acyltransferase. Six proteins (TNF-alpha, MAPK3, iNOS, eNOS, COX2 and mTOR) were extensively involved in inflammatory reaction, immune response and cell proliferation, and might be drug targets for psoriasis. PI3K-Akt signaling pathway and five other pathways had close correlation with the pathogenesis of psoriasis and could deserve further research. The inflammatory reaction, immune response and cell proliferation are mainly involved in psoriasis. Network pharmacology provide a new insight into the relationships between metabonomics biomarkers and the pathogenesis of psoriasis. KEY MESSAGES   • Network pharmacology was adopted to identify key metabonomics biomarkers and enzymes.   • Six proteins were screened out as important drug targets for psoriasis.   • A binding energy-weighted polypharmacological index was introduced to evaluate the importance of target-related pathways.

Effect of chain rigidity on network architecture and deformation behavior of glassy polymer networks

Science.gov (United States)

Knowles, Kyler Reser

Processing carbon fiber composite laminates creates molecular-level strains in the thermoset matrix upon curing and cooling which can lead to failures such as geometry deformations, micro-cracking, and other issues. It is known strain creation is attributed to the significant volume and physical state changes undergone by the polymer matrix throughout the curing process, though storage and relaxation of cure-induced strains remain poorly understood. This dissertation establishes two approaches to address the issue. The first establishes testing methods to simultaneously measure key volumetric properties of a carbon fiber composite laminate and its polymer matrix. The second approach considers the rigidity of the polymer matrix in regards to strain storage and relaxation mechanisms which ultimately control composite performance throughout manufacturing and use. Through the use of a non-contact, full-field strain measurement technique known as digital image correlation (DIC), we describe and implement useful experiments which quantify matrix and composite parameters necessary for simulation efforts and failure models. The methods are compared to more traditional techniques and show excellent correlation. Further, we established relationships which represent matrix-fiber compatibility in regards to critical processing constraints. The second approach involves a systematic study of epoxy-amine networks which are chemically-similar but differ in chain segment rigidity. Prior research has investigated the isomer effect of glassy polymers, showing sizeable differences in thermal, volumetric, physical, and mechanical properties. This work builds on these themes and shows the apparent isomer effect is rather an effect of chain rigidity. Indeed, it was found that structurally-dissimilar polymer networks exhibit very similar properties as a consequence of their shared average network rigidity. Differences in chain packing, as a consequence of chain rigidity, were shown to

Dominating biological networks.

Directory of Open Access Journals (Sweden)

Tijana Milenković

Full Text Available Proteins are essential macromolecules of life that carry out most cellular processes. Since proteins aggregate to perform function, and since protein-protein interaction (PPI networks model these aggregations, one would expect to uncover new biology from PPI network topology. Hence, using PPI networks to predict protein function and role of protein pathways in disease has received attention. A debate remains open about whether network properties of "biologically central (BC" genes (i.e., their protein products, such as those involved in aging, cancer, infectious diseases, or signaling and drug-targeted pathways, exhibit some topological centrality compared to the rest of the proteins in the human PPI network.To help resolve this debate, we design new network-based approaches and apply them to get new insight into biological function and disease. We hypothesize that BC genes have a topologically central (TC role in the human PPI network. We propose two different concepts of topological centrality. We design a new centrality measure to capture complex wirings of proteins in the network that identifies as TC those proteins that reside in dense extended network neighborhoods. Also, we use the notion of domination and find dominating sets (DSs in the PPI network, i.e., sets of proteins such that every protein is either in the DS or is a neighbor of the DS. Clearly, a DS has a TC role, as it enables efficient communication between different network parts. We find statistically significant enrichment in BC genes of TC nodes and outperform the existing methods indicating that genes involved in key biological processes occupy topologically complex and dense regions of the network and correspond to its "spine" that connects all other network parts and can thus pass cellular signals efficiently throughout the network. To our knowledge, this is the first study that explores domination in the context of PPI networks.

Hierarchical Network Design

DEFF Research Database (Denmark)

Thomadsen, Tommy

2005-01-01

Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks...

Effect of lifelong football training on the expression of muscle molecular markers involved in healthy longevity.

Science.gov (United States)

Mancini, A; Vitucci, D; Labruna, G; Imperlini, E; Randers, M B; Schmidt, J F; Hagman, M; Andersen, T R; Russo, R; Orrù, S; Krustrup, P; Salvatore, F; Buono, P

2017-04-01

We investigated whether lifelong football training affects the expression of healthy longevity-related muscle molecular markers. Biopsies were collected from the vastus lateralis muscle of 10 lifelong football-trained men (68.2 ± 3.0 years) and of 10 active untrained healthy men (66.7 ± 1.3 years). Gene and protein expression was measured by RTqPCR on RNA and by western blotting on protein extracts from muscle biopsies, respectively. The expression of AMPKα1/α2, NAMPT, TFAM and PGC1α, which are markers of oxidative metabolism, and MyHC β isoform expression was higher in the muscle of football-trained men vs untrained men. Also citrate synthase activity was higher in trained than in untrained men (109.3 ± 9.2 vs 75.1 ± 9.2 mU/mg). These findings were associated with a healthier body composition in trained than in untrained men [body weight: 78.2 ± 6.5 vs 91.2 ± 11.2 kg; body mass index BMI: 24.4 ± 1.6 vs 28.8 ± 4.0 kg m -2 ; fat%: 22.6 ± 8.0 vs 31.4 ± 5.0%)] and with a higher maximal oxygen uptake (VO 2 max: 34.7 ± 3.8 vs 27.3 ± 4.0 ml/min/kg). Also the expression of proteins involved in DNA repair and in senescence suppression (Erk1/2, Akt and FoxM1) was higher in trained than in untrained men. At BMI- and age-adjusted multiple linear regression analysis, fat percentage was independently associated with Akt protein expression, and VO 2 max was independently associated with TFAM mRNA and with Erk1/2 protein expression. Lifelong football training increases the expression of key markers involved in muscle oxidative metabolism, and in the DNA repair and senescence suppression pathways, thus providing the molecular basis for healthy longevity.

Network Learning and Innovation in SME Formal Networks

Directory of Open Access Journals (Sweden)

Jivka Deiters

2013-02-01

Full Text Available The driver for this paper is the need to better understand the potential for learning and innovation that networks canprovide especially for small and medium sized enterprises (SMEs which comprise by far the majority of enterprises in the food sector. With the challenges the food sector is facing in the near future, learning and innovation or more focused, as it is being discussed in the paper, ‘learning for innovation’ are not just opportunities but pre‐conditions for the sustainability of the sector. Network initiatives that could provide appropriate support involve social interaction and knowledge exchange, learning, competence development, and coordination (organization and management of implementation. The analysis identifies case studies in any of these orientations which serve different stages of the innovation process: invention and implementation. The variety of network case studies cover networks linked to a focus group for training, research, orconsulting, networks dealing with focused market oriented product or process development, promotional networks, and networks for open exchange and social networking.

Environmentally Friendly Procedure Based on Supercritical Fluid Chromatography and Tandem Mass Spectrometry Molecular Networking for the Discovery of Potent Antiviral Compounds from Euphorbia semiperfoliata.

Science.gov (United States)

Nothias, Louis-Félix; Boutet-Mercey, Stéphanie; Cachet, Xavier; De La Torre, Erick; Laboureur, Laurent; Gallard, Jean-François; Retailleau, Pascal; Brunelle, Alain; Dorrestein, Pieter C; Costa, Jean; Bedoya, Luis M; Roussi, Fanny; Leyssen, Pieter; Alcami, José; Paolini, Julien; Litaudon, Marc; Touboul, David

2017-10-27

A supercritical fluid chromatography-based targeted purification procedure using tandem mass spectrometry and molecular networking was developed to analyze, annotate, and isolate secondary metabolites from complex plant extract mixture. This approach was applied for the targeted isolation of new antiviral diterpene esters from Euphorbia semiperfoliata whole plant extract. The analysis of bioactive fractions revealed that unknown diterpene esters, including jatrophane esters and phorbol esters, were present in the samples. The purification procedure using semipreparative supercritical fluid chromatography led to the isolation and identification of two new jatrophane esters (13 and 14) and one known (15) and three new 4-deoxyphorbol esters (16-18). The structure and absolute configuration of compound 16 were confirmed by X-ray crystallography. This compound was found to display antiviral activity against Chikungunya virus (EC 50 = 0.45 μM), while compound 15 proved to be a potent and selective inhibitor of HIV-1 replication in a recombinant virus assay (EC 50 = 13 nM). This study showed that a supercritical fluid chromatography-based protocol and molecular networking can facilitate and accelerate the discovery of bioactive small molecules by targeting molecules of interest, while minimizing the use of toxic solvents.

Cortical networks involved in visual awareness independent of visual attention.

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Webb, Taylor W; Igelström, Kajsa M; Schurger, Aaron; Graziano, Michael S A

2016-11-29

It is now well established that visual attention, as measured with standard spatial attention tasks, and visual awareness, as measured by report, can be dissociated. It is possible to attend to a stimulus with no reported awareness of the stimulus. We used a behavioral paradigm in which people were aware of a stimulus in one condition and unaware of it in another condition, but the stimulus drew a similar amount of spatial attention in both conditions. The paradigm allowed us to test for brain regions active in association with awareness independent of level of attention. Participants performed the task in an MRI scanner. We looked for brain regions that were more active in the aware than the unaware trials. The largest cluster of activity was obtained in the temporoparietal junction (TPJ) bilaterally. Local independent component analysis (ICA) revealed that this activity contained three distinct, but overlapping, components: a bilateral, anterior component; a left dorsal component; and a right dorsal component. These components had brain-wide functional connectivity that partially overlapped the ventral attention network and the frontoparietal control network. In contrast, no significant activity in association with awareness was found in the banks of the intraparietal sulcus, a region connected to the dorsal attention network and traditionally associated with attention control. These results show the importance of separating awareness and attention when testing for cortical substrates. They are also consistent with a recent proposal that awareness is associated with ventral attention areas, especially in the TPJ.

Boolean network model for cancer pathways: predicting carcinogenesis and targeted therapy outcomes.

Directory of Open Access Journals (Sweden)

Herman F Fumiã

Full Text Available A Boolean dynamical system integrating the main signaling pathways involved in cancer is constructed based on the currently known protein-protein interaction network. This system exhibits stationary protein activation patterns--attractors--dependent on the cell's microenvironment. These dynamical attractors were determined through simulations and their stabilities against mutations were tested. In a higher hierarchical level, it was possible to group the network attractors into distinct cell phenotypes and determine driver mutations that promote phenotypic transitions. We find that driver nodes are not necessarily central in the network topology, but at least they are direct regulators of central components towards which converge or through which crosstalk distinct cancer signaling pathways. The predicted drivers are in agreement with those pointed out by diverse census of cancer genes recently performed for several human cancers. Furthermore, our results demonstrate that cell phenotypes can evolve towards full malignancy through distinct sequences of accumulated mutations. In particular, the network model supports routes of carcinogenesis known for some tumor types. Finally, the Boolean network model is employed to evaluate the outcome of molecularly targeted cancer therapies. The major find is that monotherapies were additive in their effects and that the association of targeted drugs is necessary for cancer eradication.

Network analysis of microRNAs and their regulation in human ovarian cancer

KAUST Repository

Schmeier, Sebastian

2011-11-03

Background: MicroRNAs (miRNAs) are small non-coding RNA molecules that repress the translation of messenger RNAs (mRNAs) or degrade mRNAs. These functions of miRNAs allow them to control key cellular processes such as development, differentiation and apoptosis, and they have also been implicated in several cancers such as leukaemia, lung, pancreatic and ovarian cancer (OC). Unfortunately, the specific machinery of miRNA regulation, involving transcription factors (TFs) and transcription co-factors (TcoFs), is not well understood. In the present study we focus on computationally deciphering the underlying network of miRNAs, their targets, and their control mechanisms that have an influence on OC development.Results: We analysed experimentally verified data from multiple sources that describe miRNA influence on diseases, miRNA targeting of mRNAs, and on protein-protein interactions, and combined this data with ab initio transcription factor binding site predictions within miRNA promoter regions. From these analyses, we derived a network that describes the influence of miRNAs and their regulation in human OC. We developed a methodology to analyse the network in order to find the nodes that have the largest potential of influencing the network\\'s behaviour (network hubs). We further show the potentially most influential miRNAs, TFs and TcoFs, showing subnetworks illustrating the involved mechanisms as well as regulatory miRNA network motifs in OC. We find an enrichment of miRNA targeted OC genes in the highly relevant pathways cell cycle regulation and apoptosis.Conclusions: We combined several sources of interaction and association data to analyse and place miRNAs within regulatory pathways that influence human OC. These results represent the first comprehensive miRNA regulatory network analysis for human OC. This suggests that miRNAs and their regulation may play a major role in OC and that further directed research in this area is of utmost importance to enhance

Mathematical Modelling Plant Signalling Networks

KAUST Repository

Muraro, D.

2013-01-01

During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

Abnormal binding and disruption in large scale networks involved in human partial seizures

Directory of Open Access Journals (Sweden)

Bartolomei Fabrice

2013-12-01

Full Text Available There is a marked increase in the amount of electrophysiological and neuroimaging works dealing with the study of large scale brain connectivity in the epileptic brain. Our view of the epileptogenic process in the brain has largely evolved over the last twenty years from the historical concept of “epileptic focus” to a more complex description of “Epileptogenic networks” involved in the genesis and “propagation” of epileptic activities. In particular, a large number of studies have been dedicated to the analysis of intracerebral EEG signals to characterize the dynamic of interactions between brain areas during temporal lobe seizures. These studies have reported that large scale functional connectivity is dramatically altered during seizures, particularly during temporal lobe seizure genesis and development. Dramatic changes in neural synchrony provoked by epileptic rhythms are also responsible for the production of ictal symptoms or changes in patient’s behaviour such as automatisms, emotional changes or consciousness alteration. Beside these studies dedicated to seizures, large-scale network connectivity during the interictal state has also been investigated not only to define biomarkers of epileptogenicity but also to better understand the cognitive impairments observed between seizures.

Transcriptome and network changes in climbers at extreme altitudes.

Directory of Open Access Journals (Sweden)

Fang Chen

Full Text Available Extreme altitude can induce a range of cellular and systemic responses. Although it is known that hypoxia underlies the major changes and that the physiological responses include hemodynamic changes and erythropoiesis, the molecular mechanisms and signaling pathways mediating such changes are largely unknown. To obtain a more complete picture of the transcriptional regulatory landscape and networks involved in extreme altitude response, we followed four climbers on an expedition up Mount Xixiabangma (8,012 m, and collected blood samples at four stages during the climb for mRNA and miRNA expression assays. By analyzing dynamic changes of gene networks in response to extreme altitudes, we uncovered a highly modular network with 7 modules of various functions that changed in response to extreme altitudes. The erythrocyte differentiation module is the most prominently up-regulated, reflecting increased erythrocyte differentiation from hematopoietic stem cells, probably at the expense of differentiation into other cell lineages. These changes are accompanied by coordinated down-regulation of general translation. Network topology and flow analyses also uncovered regulators known to modulate hypoxia responses and erythrocyte development, as well as unknown regulators, such as the OCT4 gene, an important regulator in stem cells and assumed to only function in stem cells. We predicted computationally and validated experimentally that increased OCT4 expression at extreme altitude can directly elevate the expression of hemoglobin genes. Our approach established a new framework for analyzing the transcriptional regulatory network from a very limited number of samples.

Bladder Cancer Advocacy Network

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... Grants Bladder Cancer Think Tank Bladder Cancer Research Network Bladder Cancer Genomics Consortium Get Involved Ways to ... us? Who we are The Bladder Cancer Advocacy Network (BCAN) is a community of patients, caregivers, survivors, ...

Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.).

Science.gov (United States)

Moschen, Sebastián; Di Rienzo, Julio A; Higgins, Janet; Tohge, Takayuki; Watanabe, Mutsumi; González, Sergio; Rivarola, Máximo; García-García, Francisco; Dopazo, Joaquin; Hopp, H Esteban; Hoefgen, Rainer; Fernie, Alisdair R; Paniego, Norma; Fernández, Paula; Heinz, Ruth A

2017-07-01

By integration of transcriptional and metabolic profiles we identified pathways and hubs transcription factors regulated during drought conditions in sunflower, useful for applications in molecular and/or biotechnological breeding. Drought is one of the most important environmental stresses that effects crop productivity in many agricultural regions. Sunflower is tolerant to drought conditions but the mechanisms involved in this tolerance remain unclear at the molecular level. The aim of this study was to characterize and integrate transcriptional and metabolic pathways related to drought stress in sunflower plants, by using a system biology approach. Our results showed a delay in plant senescence with an increase in the expression level of photosynthesis related genes as well as higher levels of sugars, osmoprotectant amino acids and ionic nutrients under drought conditions. In addition, we identified transcription factors that were upregulated during drought conditions and that may act as hubs in the transcriptional network. Many of these transcription factors belong to families implicated in the drought response in model species. The integration of transcriptomic and metabolomic data in this study, together with physiological measurements, has improved our understanding of the biological responses during droughts and contributes to elucidate the molecular mechanisms involved under this environmental condition. These findings will provide useful biotechnological tools to improve stress tolerance while maintaining crop yield under restricted water availability.

Identification of Phytophthora sojae genes involved in asexual ...

Indian Academy of Sciences (India)

ual sporulation or germination. But molecular details about asexual spore development in P. sojae are limited (Tyler et al. 2006). In the present study, to understand the molecular basis of asexual spore development in P. sojae, we investigated gene expression changes involved in asexual sporulation after ul- traviolet (UV) ...

A flood-based information flow analysis and network minimization method for gene regulatory networks.

Science.gov (United States)

Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias

2013-04-24

Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.

The Molecular Biology Capstone Assessment: A Concept Assessment for Upper-Division Molecular Biology Students

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Couch, Brian A.; Wood, William B.; Knight, Jennifer K.

2015-01-01

Measuring students' conceptual understandings has become increasingly important to biology faculty members involved in evaluating and improving departmental programs. We developed the Molecular Biology Capstone Assessment (MBCA) to gauge comprehension of fundamental concepts in molecular and cell biology and the ability to apply these concepts in…

Fixed Access Network Sharing

Science.gov (United States)

Cornaglia, Bruno; Young, Gavin; Marchetta, Antonio

2015-12-01

Fixed broadband network deployments are moving inexorably to the use of Next Generation Access (NGA) technologies and architectures. These NGA deployments involve building fiber infrastructure increasingly closer to the customer in order to increase the proportion of fiber on the customer's access connection (Fibre-To-The-Home/Building/Door/Cabinet… i.e. FTTx). This increases the speed of services that can be sold and will be increasingly required to meet the demands of new generations of video services as we evolve from HDTV to "Ultra-HD TV" with 4k and 8k lines of video resolution. However, building fiber access networks is a costly endeavor. It requires significant capital in order to cover any significant geographic coverage. Hence many companies are forming partnerships and joint-ventures in order to share the NGA network construction costs. One form of such a partnership involves two companies agreeing to each build to cover a certain geographic area and then "cross-selling" NGA products to each other in order to access customers within their partner's footprint (NGA coverage area). This is tantamount to a bi-lateral wholesale partnership. The concept of Fixed Access Network Sharing (FANS) is to address the possibility of sharing infrastructure with a high degree of flexibility for all network operators involved. By providing greater configuration control over the NGA network infrastructure, the service provider has a greater ability to define the network and hence to define their product capabilities at the active layer. This gives the service provider partners greater product development autonomy plus the ability to differentiate from each other at the active network layer.

Cellular and molecular effect of MEHP Involving LXRα in human fetal testis and ovary.

Science.gov (United States)

Muczynski, Vincent; Lecureuil, Charlotte; Messiaen, Sébastien; Guerquin, Marie-Justine; N'tumba-Byn, Thierry; Moison, Delphine; Hodroj, Wassim; Benjelloun, Hinde; Baijer, Jan; Livera, Gabriel; Frydman, René; Benachi, Alexandra; Habert, René; Rouiller-Fabre, Virginie

2012-01-01

Phthalates have been shown to have reprotoxic effects in rodents and human during fetal life. Previous studies indicate that some members of the nuclear receptor (NR) superfamilly potentially mediate phthalate effects. This study aimed to assess if expression of these nuclear receptors are modulated in the response to MEHP exposure on the human fetal gonads in vitro. Testes and ovaries from 7 to 12 gestational weeks human fetuses were exposed to 10(-4)M MEHP for 72 h in vitro. Transcriptional level of NRs and of downstream genes was then investigated using TLDA (TaqMan Low Density Array) and qPCR approaches. To determine whether somatic or germ cells of the testis are involved in the response to MEHP exposure, we developed a highly efficient cytometric germ cell sorting approach. In vitro exposure of fetal testes and ovaries to MEHP up-regulated the expression of LXRα, SREBP members and of downstream genes involved in the lipid and cholesterol synthesis in the whole gonad. In sorted testicular cells, this effect is only observable in somatic cells but not in the gonocytes. Moreover, the germ cell loss induced by MEHP exposure, that we previously described, is restricted to the male gonad as oogonia density is not affected in vitro. We evidenced for the first time that phthalate increases the levels of mRNA for LXRα, and SREBP members potentially deregulating lipids/cholesterol synthesis in human fetal gonads. Interestingly, this novel effect is observable in both male and female whereas the germ cell apoptosis is restricted to the male gonad. Furthermore, we presented here a novel and potentially very useful flow cytometric cell sorting method to analyse molecular changes in germ cells versus somatic cells.

Cellular and molecular effect of MEHP Involving LXRα in human fetal testis and ovary.

Directory of Open Access Journals (Sweden)

Vincent Muczynski

Full Text Available Phthalates have been shown to have reprotoxic effects in rodents and human during fetal life. Previous studies indicate that some members of the nuclear receptor (NR superfamilly potentially mediate phthalate effects. This study aimed to assess if expression of these nuclear receptors are modulated in the response to MEHP exposure on the human fetal gonads in vitro.Testes and ovaries from 7 to 12 gestational weeks human fetuses were exposed to 10(-4M MEHP for 72 h in vitro. Transcriptional level of NRs and of downstream genes was then investigated using TLDA (TaqMan Low Density Array and qPCR approaches. To determine whether somatic or germ cells of the testis are involved in the response to MEHP exposure, we developed a highly efficient cytometric germ cell sorting approach. In vitro exposure of fetal testes and ovaries to MEHP up-regulated the expression of LXRα, SREBP members and of downstream genes involved in the lipid and cholesterol synthesis in the whole gonad. In sorted testicular cells, this effect is only observable in somatic cells but not in the gonocytes. Moreover, the germ cell loss induced by MEHP exposure, that we previously described, is restricted to the male gonad as oogonia density is not affected in vitro.We evidenced for the first time that phthalate increases the levels of mRNA for LXRα, and SREBP members potentially deregulating lipids/cholesterol synthesis in human fetal gonads. Interestingly, this novel effect is observable in both male and female whereas the germ cell apoptosis is restricted to the male gonad. Furthermore, we presented here a novel and potentially very useful flow cytometric cell sorting method to analyse molecular changes in germ cells versus somatic cells.

Gross anatomy of network security

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Siu, Thomas J.

2002-01-01

Information security involves many branches of effort, including information assurance, host level security, physical security, and network security. Computer network security methods and implementations are given a top-down description to permit a medically focused audience to anchor this information to their daily practice. The depth of detail of network functionality and security measures, like that of the study of human anatomy, can be highly involved. Presented at the level of major gross anatomical systems, this paper will focus on network backbone implementation and perimeter defenses, then diagnostic tools, and finally the user practices (the human element). Physical security measures, though significant, have been defined as beyond the scope of this presentation.

Plasticity of gene-regulatory networks controlling sex determination: of masters, slaves, usual suspects, newcomers, and usurpators.

Science.gov (United States)

Herpin, Amaury; Schartl, Manfred

2015-10-01

Sexual dimorphism is one of the most pervasive and diverse features of animal morphology, physiology, and behavior. Despite the generality of the phenomenon itself, the mechanisms controlling how sex is determined differ considerably among various organismic groups, have evolved repeatedly and independently, and the underlying molecular pathways can change quickly during evolution. Even within closely related groups of organisms for which the development of gonads on the morphological, histological, and cell biological level is undistinguishable, the molecular control and the regulation of the factors involved in sex determination and gonad differentiation can be substantially different. The biological meaning of the high molecular plasticity of an otherwise common developmental program is unknown. While comparative studies suggest that the downstream effectors of sex-determining pathways tend to be more stable than the triggering mechanisms at the top, it is still unclear how conserved the downstream networks are and how all components work together. After many years of stasis, when the molecular basis of sex determination was amenable only in the few classical model organisms (fly, worm, mouse), recently, sex-determining genes from several animal species have been identified and new studies have elucidated some novel regulatory interactions and biological functions of the downstream network, particularly in vertebrates. These data have considerably changed our classical perception of a simple linear developmental cascade that makes the decision for the embryo to develop as male or female, and how it evolves. © 2015 The Authors.

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

NARCIS (Netherlands)

Dam, van J.C.J.; Schaap, P.J.; Martins dos Santos, V.A.P.; Suarez Diez, M.

2014-01-01

Background: 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

Introduction to focus issue: quantitative approaches to genetic networks.

Science.gov (United States)

Albert, Réka; Collins, James J; Glass, Leon

2013-06-01

All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

Biological Networks Entropies: Examples in Neural Memory Networks, Genetic Regulation Networks and Social Epidemic Networks

Directory of Open Access Journals (Sweden)

Jacques Demongeot

2018-01-01

Full Text Available Networks used in biological applications at different scales (molecule, cell and population are of different types: neuronal, genetic, and social, but they share the same dynamical concepts, in their continuous differential versions (e.g., non-linear Wilson-Cowan system as well as in their discrete Boolean versions (e.g., non-linear Hopfield system; in both cases, the notion of interaction graph G(J associated to its Jacobian matrix J, and also the concepts of frustrated nodes, positive or negative circuits of G(J, kinetic energy, entropy, attractors, structural stability, etc., are relevant and useful for studying the dynamics and the robustness of these systems. We will give some general results available for both continuous and discrete biological networks, and then study some specific applications of three new notions of entropy: (i attractor entropy, (ii isochronal entropy and (iii entropy centrality; in three domains: a neural network involved in the memory evocation, a genetic network responsible of the iron control and a social network accounting for the obesity spread in high school environment.

A reactive, scalable, and transferable model for molecular energies from a neural network approach based on local information

Science.gov (United States)

Unke, Oliver T.; Meuwly, Markus

2018-06-01

Despite the ever-increasing computer power, accurate ab initio calculations for large systems (thousands to millions of atoms) remain infeasible. Instead, approximate empirical energy functions are used. Most current approaches are either transferable between different chemical systems, but not particularly accurate, or they are fine-tuned to a specific application. In this work, a data-driven method to construct a potential energy surface based on neural networks is presented. Since the total energy is decomposed into local atomic contributions, the evaluation is easily parallelizable and scales linearly with system size. With prediction errors below 0.5 kcal mol-1 for both unknown molecules and configurations, the method is accurate across chemical and configurational space, which is demonstrated by applying it to datasets from nonreactive and reactive molecular dynamics simulations and a diverse database of equilibrium structures. The possibility to use small molecules as reference data to predict larger structures is also explored. Since the descriptor only uses local information, high-level ab initio methods, which are computationally too expensive for large molecules, become feasible for generating the necessary reference data used to train the neural network.

Managerial Challenges Within Networks - Emphasizing the Paradox of Network Participation

DEFF Research Database (Denmark)

Jakobsen, Morten

2003-01-01

Flexibility and access to numerous resources are essential benefits associated with network participation. An important aspect of managing the network participation of a company is to maintain a dynamic portfolio of partners, and thereby keep up the strategic opportunities for development. However......, maintaining the dynamics within a network seems to be a complex challenge. There is a risk that the network ends up in The Paradox of Network Participation. The desired renewal and flexibility are not utilised because the involved parties preserve the existing networks structure consisting of the same...... and thereby sort out the paradox of network participation. Trust and information are mechanisms employed to absorb uncertainty. The relationship between trust and the requirement for information depends on the maturity of the relationship. When trust becomes too important as uncertainty absorption mechanism...

Managerial challenges within networks: emphasizing the paradox of network participation

DEFF Research Database (Denmark)

Jakobsen, Morten

Flexibility and access to numerous resources are essential benefits associated with network participation. An important aspect of managing the network participation of a company is to maintain a dynamic portfolio of partners, and thereby keep up the strategic opportunities for development. However......, maintaining the dynamics within a network seems to be a complex challenge. There is a risk that the network ends up in The Paradox of Network Participation. The desired renewal and flexibility are not utilised because the involved parties preserve the existing networks structure consisting of the same...... and thereby sort out the paradox of network participation. Trust and information are mechanisms employed to absorb uncertainty. The relationship between trust and the requirement for information depends on the maturity of the relationship. When trust becomes too important as uncertainty absorption mechanism...

Transcriptome analysis reveals key differentially expressed genes involved in wheat grain development

Directory of Open Access Journals (Sweden)

Yonglong Yu

2016-04-01

Full Text Available Wheat seed development is an important physiological process of seed maturation and directly affects wheat yield and quality. In this study, we performed dynamic transcriptome microarray analysis of an elite Chinese bread wheat cultivar (Jimai 20 during grain development using the GeneChip Wheat Genome Array. Grain morphology and scanning electron microscope observations showed that the period of 11–15 days post-anthesis (DPA was a key stage for the synthesis and accumulation of seed starch. Genome-wide transcriptional profiling and significance analysis of microarrays revealed that the period from 11 to 15 DPA was more important than the 15–20 DPA stage for the synthesis and accumulation of nutritive reserves. Series test of cluster analysis of differential genes revealed five statistically significant gene expression profiles. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes, and MapMan analysis revealed expression changes within functional groups during seed development. Metabolic pathway network analysis showed that major and minor metabolic pathways regulate one another to ensure regular seed development and nutritive reserve accumulation. We performed gene co-expression network analysis to identify genes that play vital roles in seed development and identified several key genes involved in important metabolic pathways. The transcriptional expression of eight key genes involved in starch and protein synthesis and stress defense was further validated by qRT-PCR. Our results provide new insight into the molecular mechanisms of wheat seed development and the determinants of yield and quality.

Network Security: What Non-Technical Administrators Must Know

Science.gov (United States)

Council, Chip

2005-01-01

Now it is increasingly critical that community college leaders become involved in network security and partner with their directors of information technology (IT). Network security involves more than just virus protection software and firewalls. It involves vigilance and requires top executive support. Leaders can help their IT directors to…

Managing Interorganizational Networks

DEFF Research Database (Denmark)

Gustafsson, Jeppe

bold enough to predict that networks will become the dominant organisation form in future. Several authors maintain that the shift from traditional hierarchical structures to networks involves dramatic changes for managers and employees (Champy 2002, Rohlin 1994, Kanter 2002). This article seeks...... organisation theories and theories about strategic management....

Temporal Databases in Network Management

National Research Council Canada - National Science Library

Gupta, Ajay

1998-01-01

.... This thesis discusses issues involved with performing network management, specifically with means of reducing and storing the large quantity of data that networks management tools and systems generate...

Molecular farming

NARCIS (Netherlands)

Merck, K.B.; Vereijken, J.M.

2006-01-01

Molecular Farming is a new and emerging technology that promises relatively cheap and flexible production of large quantities of pharmaceuticals in genetically modified plants. Many stakeholders are involved in the production of pharmaceuticals in plants, which complicates the discussion on the

Not single brain areas but a network is involved in language: Applications in presurgical planning.

Science.gov (United States)

Alemi, Razieh; Batouli, Seyed Amir Hossein; Behzad, Ebrahim; Ebrahimpoor, Mitra; Oghabian, Mohammad Ali

2018-02-01

Language is an important human function, and is a determinant of the quality of life. In conditions such as brain lesions, disruption of the language function may occur, and lesion resection is a solution for that. Presurgical planning to determine the language-related brain areas would enhance the chances of language preservation after the operation; however, availability of a normative language template is essential. In this study, using data from 60 young individuals who were meticulously checked for mental and physical health, and using fMRI and robust imaging and data analysis methods, functional brain maps for the language production, perception and semantic were produced. The obtained templates showed that the language function should be considered as the product of the collaboration of a network of brain regions, instead of considering only few brain areas to be involved in that. This study has important clinical applications, and extends our knowledge on the neuroanatomy of the language function. Copyright © 2018 Elsevier B.V. All rights reserved.

Molecular digital pathology: progress and potential of exchanging molecular data.

Science.gov (United States)

Roy, Somak; Pfeifer, John D; LaFramboise, William A; Pantanowitz, Liron

2016-09-01

Many of the demands to perform next generation sequencing (NGS) in the clinical laboratory can be resolved using the principles of telepathology. Molecular telepathology can allow facilities to outsource all or a portion of their NGS operation such as cloud computing, bioinformatics pipelines, variant data management, and knowledge curation. Clinical pathology laboratories can electronically share diverse types of molecular data with reference laboratories, technology service providers, and/or regulatory agencies. Exchange of electronic molecular data allows laboratories to perform validation of rare diseases using foreign data, check the accuracy of their test results against benchmarks, and leverage in silico proficiency testing. This review covers the emerging subject of molecular telepathology, describes clinical use cases for the appropriate exchange of molecular data, and highlights key issues such as data integrity, interoperable formats for massive genomic datasets, security, malpractice and emerging regulations involved with this novel practice.

Risk aversion and social networks

NARCIS (Netherlands)

Kovarik, J.; van der Leij, M.J.

2011-01-01

Agents involved in the formation of a social or economic network typically face uncertainty about the benefits of creating a link. However, the interplay of such uncertainty and risk attitudes has been neglected in the network formation literature. We propose a dynamic network formation model that

Risk aversion and social networks

NARCIS (Netherlands)

Kovářík, J.; van der Leij, M.J.

2012-01-01

Agents involved in the formation of a social or economic network typically face uncertainty about the benefits of creating a link. However, the interplay of such uncertainty and risk attitudes has been neglected in the network formation literature. We propose a dynamic network formation model that

The Annotation, Mapping, Expression and Network (AMEN suite of tools for molecular systems biology

Directory of Open Access Journals (Sweden)

Primig Michael

2008-02-01

Full Text Available Abstract Background High-throughput genome biological experiments yield large and multifaceted datasets that require flexible and user-friendly analysis tools to facilitate their interpretation by life scientists. Many solutions currently exist, but they are often limited to specific steps in the complex process of data management and analysis and some require extensive informatics skills to be installed and run efficiently. Results We developed the Annotation, Mapping, Expression and Network (AMEN software as a stand-alone, unified suite of tools that enables biological and medical researchers with basic bioinformatics training to manage and explore genome annotation, chromosomal mapping, protein-protein interaction, expression profiling and proteomics data. The current version provides modules for (i uploading and pre-processing data from microarray expression profiling experiments, (ii detecting groups of significantly co-expressed genes, and (iii searching for enrichment of functional annotations within those groups. Moreover, the user interface is designed to simultaneously visualize several types of data such as protein-protein interaction networks in conjunction with expression profiles and cellular co-localization patterns. We have successfully applied the program to interpret expression profiling data from budding yeast, rodents and human. Conclusion AMEN is an innovative solution for molecular systems biological data analysis freely available under the GNU license. The program is available via a website at the Sourceforge portal which includes a user guide with concrete examples, links to external databases and helpful comments to implement additional functionalities. We emphasize that AMEN will continue to be developed and maintained by our laboratory because it has proven to be extremely useful for our genome biological research program.

Network models provide insights into how oriens–lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations

Directory of Open Access Journals (Sweden)

Katie A Ferguson

2015-08-01

Full Text Available Hippocampal theta is a 4-12 Hz rhythm associated with episodic memory, and although it has been studied extensively, the cellular mechanisms underlying its generation are unclear. The complex interactions between different interneuron types, such as those between oriens--lacunosum-moleculare (OLM interneurons and bistratified cells (BiCs, make their contribution to network rhythms difficult to determine experimentally. We created network models that are tied to experimental work at both cellular and network levels to explore how these interneuron interactions affect the power of local oscillations. Our cellular models were constrained with properties from patch clamp recordings in the CA1 region of an intact hippocampus preparation in vitro. Our network models are composed of three different types of interneurons: parvalbumin-positive (PV+ basket and axo-axonic cells (BC/AACs, PV+ BiCs, and somatostatin-positive OLM cells. Also included is a spatially extended pyramidal cell model to allow for a simplified local field potential representation, as well as experimentally-constrained, theta frequency synaptic inputs to the interneurons. The network size, connectivity, and synaptic properties were constrained with experimental data. To determine how the interactions between OLM cells and BiCs could affect local theta power, we explored a number of OLM-BiC connections and connection strengths.We found that our models operate in regimes in which OLM cells minimally or strongly affected the power of network theta oscillations due to balances that, respectively, allow compensatory effects or not. Inactivation of OLM cells could result in no change or even an increase in theta power. We predict that the dis-inhibitory effect of OLM cells to BiCs to pyramidal cell interactions plays a critical role in the power of network theta oscillations. Our network models reveal a dynamic interplay between different classes of interneurons in influencing local theta

Network analysis of microRNAs and their regulation in human ovarian cancer

KAUST Repository

Schmeier, Sebastian; Schaefer, Ulf; Essack, Magbubah; Bajic, Vladimir B.

2011-01-01

Background: MicroRNAs (miRNAs) are small non-coding RNA molecules that repress the translation of messenger RNAs (mRNAs) or degrade mRNAs. These functions of miRNAs allow them to control key cellular processes such as development, differentiation and apoptosis, and they have also been implicated in several cancers such as leukaemia, lung, pancreatic and ovarian cancer (OC). Unfortunately, the specific machinery of miRNA regulation, involving transcription factors (TFs) and transcription co-factors (TcoFs), is not well understood. In the present study we focus on computationally deciphering the underlying network of miRNAs, their targets, and their control mechanisms that have an influence on OC development.Results: We analysed experimentally verified data from multiple sources that describe miRNA influence on diseases, miRNA targeting of mRNAs, and on protein-protein interactions, and combined this data with ab initio transcription factor binding site predictions within miRNA promoter regions. From these analyses, we derived a network that describes the influence of miRNAs and their regulation in human OC. We developed a methodology to analyse the network in order to find the nodes that have the largest potential of influencing the network's behaviour (network hubs). We further show the potentially most influential miRNAs, TFs and TcoFs, showing subnetworks illustrating the involved mechanisms as well as regulatory miRNA network motifs in OC. We find an enrichment of miRNA targeted OC genes in the highly relevant pathways cell cycle regulation and apoptosis.Conclusions: We combined several sources of interaction and association data to analyse and place miRNAs within regulatory pathways that influence human OC. These results represent the first comprehensive miRNA regulatory network analysis for human OC. This suggests that miRNAs and their regulation may play a major role in OC and that further directed research in this area is of utmost importance to enhance our

Combined metabolomic and correlation networks analyses reveal fumarase insufficiency altered amino acid metabolism.

Science.gov (United States)

Hou, Entai; Li, Xian; Liu, Zerong; Zhang, Fuchang; Tian, Zhongmin

2018-04-01

Fumarase catalyzes the interconversion of fumarate and l-malate in the tricarboxylic acid cycle. Fumarase insufficiencies were associated with increased levels of fumarate, decreased levels of malate and exacerbated salt-induced hypertension. To gain insights into the metabolism profiles induced by fumarase insufficiency and identify key regulatory metabolites, we applied a GC-MS based metabolomics platform coupled with a network approach to analyze fumarase insufficient human umbilical vein endothelial cells (HUVEC) and negative controls. A total of 24 altered metabolites involved in seven metabolic pathways were identified as significantly altered, and enriched for the biological module of amino acids metabolism. In addition, Pearson correlation network analysis revealed that fumaric acid, l-malic acid, l-aspartic acid, glycine and l-glutamic acid were hub metabolites according to Pagerank based on their three centrality indices. Alanine aminotransferase and glutamate dehydrogenase activities increased significantly in fumarase deficiency HUVEC. These results confirmed that fumarase insufficiency altered amino acid metabolism. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism at metabolomics level. Copyright © 2017 John Wiley & Sons, Ltd.

From Molecular Classification to Targeted Therapeutics: The Changing Face of Systemic Therapy in Metastatic Gastroesophageal Cancer

Directory of Open Access Journals (Sweden)

Adrian Murphy

2015-01-01

Full Text Available Histological classification of adenocarcinoma or squamous cell carcinoma for esophageal cancer or using the Lauren classification for intestinal and diffuse type gastric cancer has limited clinical utility in the management of advanced disease. Germline mutations in E-cadherin (CDH1 or mismatch repair genes (Lynch syndrome were identified many years ago but given their rarity, the identification of these molecular alterations does not substantially impact treatment in the advanced setting. Recent molecular profiling studies of upper GI tumors have added to our knowledge of the underlying biology but have not led to an alternative classification system which can guide clinician’s therapeutic decisions. Recently the Cancer Genome Atlas Research Network has proposed four subtypes of gastric cancer dividing tumors into those positive for Epstein-Barr virus, microsatellite unstable tumors, genomically stable tumors, and tumors with chromosomal instability. Unfortunately to date, many phase III clinical trials involving molecularly targeted agents have failed to meet their survival endpoints due to their use in unselected populations. Future clinical trials should utilize molecular profiling of individual tumors in order to determine the optimal use of targeted therapies in preselected patients.

VirHostNet 2.0: surfing on the web of virus/host molecular interactions data.

Science.gov (United States)

Guirimand, Thibaut; Delmotte, Stéphane; Navratil, Vincent

2015-01-01

VirHostNet release 2.0 (http://virhostnet.prabi.fr) is a knowledgebase dedicated to the network-based exploration of virus-host protein-protein interactions. Since the previous VirhostNet release (2009), a second run of manual curation was performed to annotate the new torrent of high-throughput protein-protein interactions data from the literature. This resource is shared publicly, in PSI-MI TAB 2.5 format, using a PSICQUIC web service. The new interface of VirHostNet 2.0 is based on Cytoscape web library and provides a user-friendly access to the most complete and accurate resource of virus-virus and virus-host protein-protein interactions as well as their projection onto their corresponding host cell protein interaction networks. We hope that the VirHostNet 2.0 system will facilitate systems biology and gene-centered analysis of infectious diseases and will help to identify new molecular targets for antiviral drugs design. This resource will also continue to help worldwide scientists to improve our knowledge on molecular mechanisms involved in the antiviral response mediated by the cell and in the viral strategies selected by viruses to hijack the host immune system. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Application of network methods for understanding evolutionary dynamics in discrete habitats.

Science.gov (United States)

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

The paradox of caffeine-zolpidem interaction: a network analysis.

Science.gov (United States)

Myslobodsky, Michael

2009-10-01

A widely prescribed and potent short-acting hypnotic, zolpidem has become the mainstay for the treatment of middle-of-the-night sleeplessness. It is expected to be antagonized by caffeine. Paradoxically, in some cases caffeine appears to slightly enhance zolpidem sedation. The pharmacokinetic and pharmacodynamic nature of this odd effect remains unexplored. The purpose of this study is to reproduce a hypothetical molecular network recruited by caffeine when co-administered with zolpidem using Ingenuity Pathway Analysis. Thus generated, network drew attention to several possible contributors to caffeine sedation, such as tachykinin precursor 1, cannabinoid, and GABA receptors. The present overview is centered on the possibility that caffeine potentiation of zolpidem sedation does not involve a centralized interaction of specific neurotransmitters, but rather is contributed by its antioxidant capacity. It is proposed that by modifying the cellular redox state, caffeine ultimately reduces the pool of reactive oxygen species, thereby increasing the bioavailability of endogenous melatonin for interaction with zolpidem. This side effect of caffeine encourages further studies of multiple antioxidants as an attractive way to potentially increasing somnolence.

Pseudogenes regulate parental gene expression via ceRNA network.

Science.gov (United States)

An, Yang; Furber, Kendra L; Ji, Shaoping

2017-01-01

The concept of competitive endogenous RNA (ceRNA) was first proposed by Salmena and colleagues. Evidence suggests that pseudogene RNAs can act as a 'sponge' through competitive binding of common miRNA, releasing or attenuating repression through sequestering miRNAs away from parental mRNA. In theory, ceRNAs refer to all transcripts such as mRNA, tRNA, rRNA, long non-coding RNA, pseudogene RNA and circular RNA, because all of them may become the targets of miRNA depending on spatiotemporal situation. As binding of miRNA to the target RNA is not 100% complementary, it is possible that one miRNA can bind to multiple target RNAs and vice versa. All RNAs crosstalk through competitively binding to miRNAvia miRNA response elements (MREs) contained within the RNA sequences, thus forming a complex regulatory network. The ratio of a subset of miRNAs to the corresponding number of MREs determines repression strength on a given mRNA translation or stability. An increase in pseudogene RNA level can sequester miRNA and release repression on the parental gene, leading to an increase in parental gene expression. A massive number of transcripts constitute a complicated network that regulates each other through this proposed mechanism, though some regulatory significance may be mild or even undetectable. It is possible that the regulation of gene and pseudogene expression occurring in this manor involves all RNAs bearing common MREs. In this review, we will primarily discuss how pseudogene transcripts regulate expression of parental genes via ceRNA network and biological significance of regulation. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.

Science.gov (United States)

Siletz, Anaar; Schnabel, Michael; Kniazeva, Ekaterina; Schumacher, Andrew J; Shin, Seungjin; Jeruss, Jacqueline S; Shea, Lonnie D

2013-01-01

The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy.

Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.

Directory of Open Access Journals (Sweden)

Anaar Siletz

Full Text Available The epithelial-mesenchymal transition (EMT is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy.

Effective professional networking.