CellMap visualizes protein-protein interactions and subcellular localization

PubMed Central

Dallago, Christian; Goldberg, Tatyana; Andrade-Navarro, Miguel Angel; Alanis-Lobato, Gregorio; Rost, Burkhard

2018-01-01

Many tools visualize protein-protein interaction (PPI) networks. The tool introduced here, CellMap, adds one crucial novelty by visualizing PPI networks in the context of subcellular localization, i.e. the location in the cell or cellular component in which a PPI happens. Users can upload images of cells and define areas of interest against which PPIs for selected proteins are displayed (by default on a cartoon of a cell). Annotations of localization are provided by the user or through our in-house database. The visualizer and server are written in JavaScript, making CellMap easy to customize and to extend by researchers and developers. PMID:29497493

Reverse-engineering of gene networks for regulating early blood development from single-cell measurements.

PubMed

Wei, Jiangyong; Hu, Xiaohua; Zou, Xiufen; Tian, Tianhai

2017-12-28

Recent advances in omics technologies have raised great opportunities to study large-scale regulatory networks inside the cell. In addition, single-cell experiments have measured the gene and protein activities in a large number of cells under the same experimental conditions. However, a significant challenge in computational biology and bioinformatics is how to derive quantitative information from the single-cell observations and how to develop sophisticated mathematical models to describe the dynamic properties of regulatory networks using the derived quantitative information. This work designs an integrated approach to reverse-engineer gene networks for regulating early blood development based on singel-cell experimental observations. The wanderlust algorithm is initially used to develop the pseudo-trajectory for the activities of a number of genes. Since the gene expression data in the developed pseudo-trajectory show large fluctuations, we then use Gaussian process regression methods to smooth the gene express data in order to obtain pseudo-trajectories with much less fluctuations. The proposed integrated framework consists of both bioinformatics algorithms to reconstruct the regulatory network and mathematical models using differential equations to describe the dynamics of gene expression. The developed approach is applied to study the network regulating early blood cell development. A graphic model is constructed for a regulatory network with forty genes and a dynamic model using differential equations is developed for a network of nine genes. Numerical results suggests that the proposed model is able to match experimental data very well. We also examine the networks with more regulatory relations and numerical results show that more regulations may exist. We test the possibility of auto-regulation but numerical simulations do not support the positive auto-regulation. In addition, robustness is used as an importantly additional criterion to select candidate networks. The research results in this work shows that the developed approach is an efficient and effective method to reverse-engineer gene networks using single-cell experimental observations.

A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

PubMed Central

Sung, Myong-Hee

2013-01-01

Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701

Importance of being Nernst: Synaptic activity and functional relevance in stem cell-derived neurons

PubMed Central

Bradford, Aaron B; McNutt, Patrick M

2015-01-01

Functional synaptogenesis and network emergence are signature endpoints of neurogenesis. These behaviors provide higher-order confirmation that biochemical and cellular processes necessary for neurotransmitter release, post-synaptic detection and network propagation of neuronal activity have been properly expressed and coordinated among cells. The development of synaptic neurotransmission can therefore be considered a defining property of neurons. Although dissociated primary neuron cultures readily form functioning synapses and network behaviors in vitro, continuously cultured neurogenic cell lines have historically failed to meet these criteria. Therefore, in vitro-derived neuron models that develop synaptic transmission are critically needed for a wide array of studies, including molecular neuroscience, developmental neurogenesis, disease research and neurotoxicology. Over the last decade, neurons derived from various stem cell lines have shown varying ability to develop into functionally mature neurons. In this review, we will discuss the neurogenic potential of various stem cells populations, addressing strengths and weaknesses of each, with particular attention to the emergence of functional behaviors. We will propose methods to functionally characterize new stem cell-derived neuron (SCN) platforms to improve their reliability as physiological relevant models. Finally, we will review how synaptically active SCNs can be applied to accelerate research in a variety of areas. Ultimately, emphasizing the critical importance of synaptic activity and network responses as a marker of neuronal maturation is anticipated to result in in vitro findings that better translate to efficacious clinical treatments. PMID:26240679

The NIH Library of Integrated Network-Based Cellular Signatures (LINCS) Program | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

By generating and making public data that indicates how cells respond to various genetic and environmental stressors, the LINCS project will help us gain a more detailed understanding of cell pathways and aid efforts to develop therapies that might restore perturbed pathways and networks to their normal states. The LINCS website is a source of information for the research community and general public about the LINCS project. This website along with the LINCS Data Portal contains details about the assays, cell types, and perturbagens that are currently part of the library, as well as links to participating sites, data releases from the sites, and software that can be used for analyzing the data.

Spatial and temporal structure of the clinical research based on mesenchymal stromal cells: A network analysis.

PubMed

Monsarrat, Paul; Kemoun, Philippe; Vergnes, Jean-Noel; Sensebe, Luc; Casteilla, Louis; Planat-Benard, Valerie

2017-01-01

Using innovative tools derived from social network analysis, the aims of this study were (i) to decipher the spatial and temporal structure of the research centers network dedicated to the therapeutic uses of mesenchymal stromal cells (MSCs) and (ii) to measure the influence of fields of applications, cellular sources and industry funding on network topography. From each trial using MSCs reported on ClinicalTrials.gov, all research centers were extracted. Networks were generated using Cytoscape 3.2.2, where each center was assimilated to a node, and one trial to an edge connecting two nodes. The analysis included 563 studies. An independent segregation was obvious between continents. Asian, South American and African centers were significantly more isolated than other centers. Isolated centers had fewer advanced phases (P <0.001), completed studies (P = 0.01) and industry-supported studies (P <0.001). Various thematic priorities among continents were identified: the cardiovascular, digestive and nervous system diseases were strongly studied by North America, Europe and Asia, respectively. The choice of cellular sources also affected the network topography; North America was primarily involved in bone-marrow-derived MSC research, whereas Europe and Asia dominated the use of adipose-derived MSCs. Industrial funding was the highest for North American centers (90.5%). Strengthening of international standards and statements with institutional, federal and industrial partners is necessary. More connections would facilitate the transfer of knowledge, sharing of resources, mobility of researchers and advancement of trials. Developing partnerships between industry and academic centers seems beneficial to the advancement of trials across different phases and would facilitate the translation of research discoveries. Copyright © 2017 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Geometric control of capillary architecture via cell-matrix mechanical interactions.

PubMed

Sun, Jian; Jamilpour, Nima; Wang, Fei-Yue; Wong, Pak Kin

2014-03-01

Capillary morphogenesis is a multistage, multicellular activity that plays a pivotal role in various developmental and pathological situations. In-depth understanding of the regulatory mechanism along with the capability of controlling the morphogenic process will have direct implications on tissue engineering and therapeutic angiogenesis. Extensive research has been devoted to elucidate the biochemical factors that regulate capillary morphogenesis. The roles of geometric confinement and cell-matrix mechanical interactions on the capillary architecture, nevertheless, remain largely unknown. Here, we show geometric control of endothelial network topology by creating physical confinements with microfabricated fences and wells. Decreasing the thickness of the matrix also results in comparable modulation of the network architecture, supporting the boundary effect is mediated mechanically. The regulatory role of cell-matrix mechanical interaction on the network topology is further supported by alternating the matrix stiffness by a cell-inert PEG-dextran hydrogel. Furthermore, reducing the cell traction force with a Rho-associated protein kinase inhibitor diminishes the boundary effect. Computational biomechanical analysis delineates the relationship between geometric confinement and cell-matrix mechanical interaction. Collectively, these results reveal a mechanoregulation scheme of endothelial cells to regulate the capillary network architecture via cell-matrix mechanical interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cell-Type-Specific Predictive Network Yields Novel Insights into Mouse Embryonic Stem Cell Self-Renewal and Cell Fate

PubMed Central

Dowell, Karen G.; Simons, Allen K.; Wang, Zack Z.; Yun, Kyuson; Hibbs, Matthew A.

2013-01-01

Self-renewal, the ability of a stem cell to divide repeatedly while maintaining an undifferentiated state, is a defining characteristic of all stem cells. Here, we clarify the molecular foundations of mouse embryonic stem cell (mESC) self-renewal by applying a proven Bayesian network machine learning approach to integrate high-throughput data for protein function discovery. By focusing on a single stem-cell system, at a specific developmental stage, within the context of well-defined biological processes known to be active in that cell type, we produce a consensus predictive network that reflects biological reality more closely than those made by prior efforts using more generalized, context-independent methods. In addition, we show how machine learning efforts may be misled if the tissue specific role of mammalian proteins is not defined in the training set and circumscribed in the evidential data. For this study, we assembled an extensive compendium of mESC data: ∼2.2 million data points, collected from 60 different studies, under 992 conditions. We then integrated these data into a consensus mESC functional relationship network focused on biological processes associated with embryonic stem cell self-renewal and cell fate determination. Computational evaluations, literature validation, and analyses of predicted functional linkages show that our results are highly accurate and biologically relevant. Our mESC network predicts many novel players involved in self-renewal and serves as the foundation for future pluripotent stem cell studies. This network can be used by stem cell researchers (at http://StemSight.org) to explore hypotheses about gene function in the context of self-renewal and to prioritize genes of interest for experimental validation. PMID:23468881

Flow cytometry in the post fluorescence era.

PubMed

Nolan, Garry P

2011-12-01

While flow cytometry once enabled researchers to examine 10--15 cell surface parameters, new mass flow cytometry technology enables interrogation of up to 45 parameters on a single cell. This new technology has increased understanding of cell expression and how cells differentiate during hematopoiesis. Using this information, knowledge of leukemia cell biology has also increased. Other new technologies, such as SPADE analysis and single cell network profiling (SCNP), are enabling researchers to put different cancers into more biologically similar categories and have the potential to enable more personalized medicine. Copyright © 2011. Published by Elsevier Ltd.

Network inference and network response identification: moving genome-scale data to the next level of biological discovery

PubMed Central

Veiga, Diogo F. T.; Dutta, Bhaskar; Balaźsi, Gábor

2011-01-01

The escalating amount of genome-scale data demands a pragmatic stance from the research community. How can we utilize this deluge of information to better understand biology, cure diseases, or engage cells in bioremediation or biomaterial production for various purposes? A research pipeline moving new sequence, expression and binding data towards practical end goals seems to be necessary. While most individual researchers are not motivated by such well-articulated pragmatic end goals, the scientific community has already self-organized itself to successfully convert genomic data into fundamentally new biological knowledge and practical applications. Here we review two important steps in this workflow: network inference and network response identification, applied to transcriptional regulatory networks. Among network inference methods, we concentrate on relevance networks due to their conceptual simplicity. We classify and discuss network response identification approaches as either data-centric or network-centric. Finally, we conclude with an outlook on what is still missing from these approaches and what may be ahead on the road to biological discovery. PMID:20174676

NaviCell Web Service for network-based data visualization.

PubMed

Bonnet, Eric; Viara, Eric; Kuperstein, Inna; Calzone, Laurence; Cohen, David P A; Barillot, Emmanuel; Zinovyev, Andrei

2015-07-01

Data visualization is an essential element of biological research, required for obtaining insights and formulating new hypotheses on mechanisms of health and disease. NaviCell Web Service is a tool for network-based visualization of 'omics' data which implements several data visual representation methods and utilities for combining them together. NaviCell Web Service uses Google Maps and semantic zooming to browse large biological network maps, represented in various formats, together with different types of the molecular data mapped on top of them. For achieving this, the tool provides standard heatmaps, barplots and glyphs as well as the novel map staining technique for grasping large-scale trends in numerical values (such as whole transcriptome) projected onto a pathway map. The web service provides a server mode, which allows automating visualization tasks and retrieving data from maps via RESTful (standard HTTP) calls. Bindings to different programming languages are provided (Python and R). We illustrate the purpose of the tool with several case studies using pathway maps created by different research groups, in which data visualization provides new insights into molecular mechanisms involved in systemic diseases such as cancer and neurodegenerative diseases. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Globalization of Stem Cell Science: An Examination of Current and Past Collaborative Research Networks

PubMed Central

Luo, Jingyuan; Matthews, Kirstin R. W.

2013-01-01

Science and engineering research has becoming an increasingly international phenomenon. Traditional bibliometric studies have not captured the evolution of collaborative partnerships between countries, particularly in emerging technologies such as stem cell science, in which an immense amount of investment has been made in the past decade. Analyzing over 2,800 articles from the top journals that include stem cell research in their publications, this study demonstrates the globalization of stem cell science. From 2000 to 2010, international collaborations increased from 20.9% to 36% of all stem cell publications analyzed. The United States remains the most prolific and the most dominant country in the field in terms of publications in high impact journals. But Asian countries, particularly China are steadily gaining ground. Exhibiting the largest relative growth, the percent of Chinese-authored stem cell papers grew more than ten-fold, while the percent of Chinese-authored international papers increased over seven times from 2000 to 2010. And while the percent of total stem cell publications exhibited modest growth for European countries, the percent of international publications increased more substantially, particularly in the United Kingdom. Overall, the data indicated that traditional networks of collaboration extant in 2000 still predominate in stem cell science. Although more nations are becoming involved in international collaborations and undertaking stem cell research, many of these efforts, with the exception of those in certain Asian countries, have yet to translate into publications in high impact journals. PMID:24069210

Globalization of stem cell science: an examination of current and past collaborative research networks.

PubMed

Luo, Jingyuan; Matthews, Kirstin R W

2013-01-01

Science and engineering research has becoming an increasingly international phenomenon. Traditional bibliometric studies have not captured the evolution of collaborative partnerships between countries, particularly in emerging technologies such as stem cell science, in which an immense amount of investment has been made in the past decade. Analyzing over 2,800 articles from the top journals that include stem cell research in their publications, this study demonstrates the globalization of stem cell science. From 2000 to 2010, international collaborations increased from 20.9% to 36% of all stem cell publications analyzed. The United States remains the most prolific and the most dominant country in the field in terms of publications in high impact journals. But Asian countries, particularly China are steadily gaining ground. Exhibiting the largest relative growth, the percent of Chinese-authored stem cell papers grew more than ten-fold, while the percent of Chinese-authored international papers increased over seven times from 2000 to 2010. And while the percent of total stem cell publications exhibited modest growth for European countries, the percent of international publications increased more substantially, particularly in the United Kingdom. Overall, the data indicated that traditional networks of collaboration extant in 2000 still predominate in stem cell science. Although more nations are becoming involved in international collaborations and undertaking stem cell research, many of these efforts, with the exception of those in certain Asian countries, have yet to translate into publications in high impact journals.

TCGA's Testicular Germ Cell Tumor Study - TCGA

Cancer.gov

TCGA network researchers identify molecular characteristics that classify testicular germ cell tumor types, including a separate subset of seminomas defined by KIT mutations. This provides a set of candidate biomarkers for risk stratification and potential therapeutic targeting.

Application of Multilayer Feedforward Neural Networks to Precipitation Cell-Top Altitude Estimation

NASA Technical Reports Server (NTRS)

Spina, Michelle S.; Schwartz, Michael J.; Staelin, David H.; Gasiewski, Albin J.

1998-01-01

The use of passive 118-GHz O2 observations of rain cells for precipitation cell-top altitude estimation is demonstrated by using a multilayer feed forward neural network retrieval system. Rain cell observations at 118 GHz were compared with estimates of the cell-top altitude obtained by optical stereoscopy. The observations were made with 2 4 km horizontal spatial resolution by using the Millimeter-wave Temperature Sounder (MTS) scanning spectrometer aboard the NASA ER-2 research aircraft during the Genesis of Atlantic Lows Experiment (GALE) and the COoperative Huntsville Meteorological EXperiment (COHMEX) in 1986. The neural network estimator applied to MTS spectral differences between clouds, and nearby clear air yielded an rms discrepancy of 1.76 km for a combined cumulus, mature, and dissipating cell set and 1.44 km for the cumulus-only set. An improvement in rms discrepancy to 1.36 km was achieved by including additional MTS information on the absolute atmospheric temperature profile. An incremental method for training neural networks was developed that yielded robust results, despite the use of as few as 56 training spectra. Comparison of these results with a nonlinear statistical estimator shows that superior results can be obtained with a neural network retrieval system. Imagery of estimated cell-top altitudes was created from 118-GHz spectral imagery gathered from CAMEX, September through October 1993, and from cyclone Oliver, February 7, 1993.

An FD-LC-MS/MS Proteomic Strategy for Revealing Cellular Protein Networks: A Conditional Superoxide Dismutase 1 Knockout Cells

PubMed Central

Ichibangase, Tomoko; Sugawara, Yasuhiro; Yamabe, Akio; Koshiyama, Akiyo; Yoshimura, Akari; Enomoto, Takemi; Imai, Kazuhiro

2012-01-01

Systems biology aims to understand biological phenomena in terms of complex biological and molecular interactions, and thus proteomics plays an important role in elucidating protein networks. However, many proteomic methods have suffered from their high variability, resulting in only showing altered protein names. Here, we propose a strategy for elucidating cellular protein networks based on an FD-LC-MS/MS proteomic method. The strategy permits reproducible relative quantitation of differences in protein levels between different cell populations and allows for integration of the data with those obtained through other methods. We demonstrate the validity of the approach through a comparison of differential protein expression in normal and conditional superoxide dismutase 1 gene knockout cells and believe that beginning with an FD-LC-MS/MS proteomic approach will enable researchers to elucidate protein networks more easily and comprehensively. PMID:23029042

Fuel Cells | Climate Neutral Research Campuses | NREL

Science.gov Websites

to develop fuel cells on campus. Does your campus support telecommunications networks where there is captures waste heat to generate hot water. Additionally, the exhaust carbon dioxide is routed to an energy conversion calculation methodologies. U.S. Department of Energy - Fuel Cell Animation: Provides an

Introduction to focus issue: quantitative approaches to genetic networks.

PubMed

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 using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

NASA Astrophysics Data System (ADS)

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 using field-programmable gate arrays. Mathematical analyses will be essential for understanding naturally occurring genetic networks in diverse organisms and for providing a foundation for the improved development of synthetic genetic networks.

Vascular Procr+ stem cells: Finding new branches while looking for the roots.

PubMed

Gur-Cohen, Shiri; Lapidot, Tsvee

2016-10-01

Generation and growth of the blood vasculature network is a highly synchronized process, requiring coordinated efforts of endothelial cells and pericytes to maintain blood vessel integrity and regeneration. In a recent paper published in Cell Research, Yu et al. identified and characterized bipotent Procr-expressing vascular endothelial stem cells, which give rise to both endothelial cells and pericytes.

Detection and Elimination of Oncogenic Signalling Networks in Premalignant and Malignant Cells with Magnetic Resonance Imaging

DTIC Science & Technology

2015-10-01

DATE : October 2015 TYPE OF REPORT: Annual Report PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702...not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE October 2015 2. REPORT TYPE...Annual 3. DATES COVERED 30Sep2014 - 29Sep2015 Detection and Elimination of Oncogenic Signaling Networks in Premalignant and Malignant Cells with

Detection and Elimination of Oncogenic Signaling Networks in Premalignant and Malignant Cells with Magnetic Resonance Imaging

DTIC Science & Technology

2015-10-01

DATE : October 2015 TYPE OF REPORT: Annual Report PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702...not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE October 2015 2. REPORT TYPE...Annual 3. DATES COVERED 30Sep2014 - 29Sep2015 Detection and Elimination of Oncogenic Signaling Networks in Premalignant and Malignant Cells with

Biological mechanisms beyond network analysis via mathematical modeling. Comment on "Network science of biological systems at different scales: A review" by Marko Gosak et al.

NASA Astrophysics Data System (ADS)

Pedersen, Morten Gram

2018-03-01

Methods from network theory are increasingly used in research spanning from engineering and computer science to psychology and the social sciences. In this issue, Gosak et al. [1] provide a thorough review of network science applications to biological systems ranging from the subcellular world via neuroscience to ecosystems, with special attention to the insulin-secreting beta-cells in pancreatic islets.

Topographical maps as complex networks

NASA Astrophysics Data System (ADS)

da Fontoura Costa, Luciano; Diambra, Luis

2005-02-01

The neuronal networks in the mammalian cortex are characterized by the coexistence of hierarchy, modularity, short and long range interactions, spatial correlations, and topographical connections. Particularly interesting, the latter type of organization implies special demands on developing systems in order to achieve precise maps preserving spatial adjacencies, even at the expense of isometry. Although the object of intensive biological research, the elucidation of the main anatomic-functional purposes of the ubiquitous topographical connections in the mammalian brain remains an elusive issue. The present work reports on how recent results from complex network formalism can be used to quantify and model the effect of topographical connections between neuronal cells over the connectivity of the network. While the topographical mapping between two cortical modules is achieved by connecting nearest cells from each module, four kinds of network models are adopted for implementing intramodular connections, including random, preferential-attachment, short-range, and long-range networks. It is shown that, though spatially uniform and simple, topographical connections between modules can lead to major changes in the network properties in some specific cases, depending on intramodular connections schemes, fostering more effective intercommunication between the involved neuronal cells and modules. The possible implications of such effects on cortical operation are discussed.

Sensorimotor Functional and Structural Networks after Intracerebral Stem Cell Grafts in the Ischemic Mouse Brain.

PubMed

Green, Claudia; Minassian, Anuka; Vogel, Stefanie; Diedenhofen, Michael; Beyrau, Andreas; Wiedermann, Dirk; Hoehn, Mathias

2018-02-14

Past investigations on stem cell-mediated recovery after stroke have limited their focus on the extent and morphological development of the ischemic lesion itself over time or on the integration capacity of the stem cell graft ex vivo However, an assessment of the long-term functional and structural improvement in vivo is essential to reliably quantify the regenerative capacity of cell implantation after stroke. We induced ischemic stroke in nude mice and implanted human neural stem cells (H9 derived) into the ipsilateral cortex in the acute phase. Functional and structural connectivity changes of the sensorimotor network were noninvasively monitored using magnetic resonance imaging for 3 months after stem cell implantation. A sharp decrease of the functional sensorimotor network extended even to the contralateral hemisphere, persisting for the whole 12 weeks of observation. In mice with stem cell implantation, functional networks were stabilized early on, pointing to a paracrine effect as an early supportive mechanism of the graft. This stabilization required the persistent vitality of the stem cells, monitored by bioluminescence imaging. Thus, we also observed deterioration of the early network stabilization upon vitality loss of the graft after a few weeks. Structural connectivity analysis showed fiber-density increases between the cortex and white matter regions occurring predominantly on the ischemic hemisphere. These fiber-density changes were nearly the same for both study groups. This motivated us to hypothesize that the stem cells can influence, via early paracrine effect, the functional networks, while observed structural changes are mainly stimulated by the ischemic event. SIGNIFICANCE STATEMENT In recent years, research on strokes has made a shift away from a focus on immediate ischemic effects and towards an emphasis on the long-range effects of the lesion on the whole brain. Outcome improvements in stem cell therapies also require the understanding of their influence on the whole-brain networks. Here, we have longitudinally and noninvasively monitored the structural and functional network alterations in the mouse model of focal cerebral ischemia. Structural changes of fiber-density increases are stimulated in the endogenous tissue without further modulation by the stem cells, while functional networks are stabilized by the stem cells via a paracrine effect. These results will help decipher the underlying networks of brain plasticity in response to cerebral lesions and offer clues to unravelling the mystery of how stem cells mediate regeneration. Copyright © 2018 the authors 0270-6474/18/381648-14$15.00/0.

XUNET experimental high-speed network testbed CRADA 1136, DOE TTI No. 92-MULT-020-B2

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

Palmer, R.E.

1996-04-01

XUNET is a research program with AT&T and other partners to study high-speed wide area communication between local area networks over a backbone using Asynchronous Transfer Mode (ATM) switches. Important goals of the project are to develop software techniques for network control and management, and applications for high-speed networks. The project entails building a testbed between member sites to explore performance issues for mixed network traffic such as congestion control, multimedia communications protocols, segmentation and reassembly of ATM cells, and overall data throughput rates.

Gene network inference and visualization tools for biologists: application to new human transcriptome datasets

PubMed Central

Hurley, Daniel; Araki, Hiromitsu; Tamada, Yoshinori; Dunmore, Ben; Sanders, Deborah; Humphreys, Sally; Affara, Muna; Imoto, Seiya; Yasuda, Kaori; Tomiyasu, Yuki; Tashiro, Kosuke; Savoie, Christopher; Cho, Vicky; Smith, Stephen; Kuhara, Satoru; Miyano, Satoru; Charnock-Jones, D. Stephen; Crampin, Edmund J.; Print, Cristin G.

2012-01-01

Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions. PMID:22121215

A network approach to the geometric structure of shallow cloud fields

NASA Astrophysics Data System (ADS)

Glassmeier, F.; Feingold, G.

2017-12-01

The representation of shallow clouds and their radiative impact is one of the largest challenges for global climate models. While the bulk properties of cloud fields, including effects of organization, are a very active area of research, the potential of the geometric arrangement of cloud fields for the development of new parameterizations has hardly been explored. Self-organized patterns are particularly evident in the cellular structure of Stratocumulus (Sc) clouds so readily visible in satellite imagery. Inspired by similar patterns in biology and physics, we approach pattern formation in Sc fields from the perspective of natural cellular networks. Our network analysis is based on large-eddy simulations of open- and closed-cell Sc cases. We find the network structure to be neither random nor characteristic to natural convection. It is independent of macroscopic cloud fields properties like the Sc regime (open vs closed) and its typical length scale (boundary layer height). The latter is a consequence of entropy maximization (Lewis's Law with parameter 0.16). The cellular pattern is on average hexagonal, where non-6 sided cells occur according to a neighbor-number distribution variance of about 2. Reflecting the continuously renewing dynamics of Sc fields, large (many-sided) cells tend to neighbor small (few-sided) cells (Aboav-Weaire Law with parameter 0.9). These macroscopic network properties emerge independent of the Sc regime because the different processes governing the evolution of closed as compared to open cells correspond to topologically equivalent network dynamics. By developing a heuristic model, we show that open and closed cell dynamics can both be mimicked by versions of cell division and cell disappearance and are biased towards the expansion of smaller cells. This model offers for the first time a fundamental and universal explanation for the geometric pattern of Sc clouds. It may contribute to the development of advanced Sc parameterizations. As an outlook, we discuss how a similar network approach can be applied to describe and quantify the geometric structure of shallow cumulus cloud fields.

Competing dynamic phases of active polymer networks

NASA Astrophysics Data System (ADS)

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.

Novel insights into embryonic stem cell self-renewal revealed through comparative human and mouse systems biology networks.

PubMed

Dowell, Karen G; Simons, Allen K; Bai, Hao; Kell, Braden; Wang, Zack Z; Yun, Kyuson; Hibbs, Matthew A

2014-05-01

Embryonic stem cells (ESCs), characterized by their ability to both self-renew and differentiate into multiple cell lineages, are a powerful model for biomedical research and developmental biology. Human and mouse ESCs share many features, yet have distinctive aspects, including fundamental differences in the signaling pathways and cell cycle controls that support self-renewal. Here, we explore the molecular basis of human ESC self-renewal using Bayesian network machine learning to integrate cell-type-specific, high-throughput data for gene function discovery. We integrated high-throughput ESC data from 83 human studies (~1.8 million data points collected under 1,100 conditions) and 62 mouse studies (~2.4 million data points collected under 1,085 conditions) into separate human and mouse predictive networks focused on ESC self-renewal to analyze shared and distinct functional relationships among protein-coding gene orthologs. Computational evaluations show that these networks are highly accurate, literature validation confirms their biological relevance, and reverse transcriptase polymerase chain reaction (RT-PCR) validation supports our predictions. Our results reflect the importance of key regulatory genes known to be strongly associated with self-renewal and pluripotency in both species (e.g., POU5F1, SOX2, and NANOG), identify metabolic differences between species (e.g., threonine metabolism), clarify differences between human and mouse ESC developmental signaling pathways (e.g., leukemia inhibitory factor (LIF)-activated JAK/STAT in mouse; NODAL/ACTIVIN-A-activated fibroblast growth factor in human), and reveal many novel genes and pathways predicted to be functionally associated with self-renewal in each species. These interactive networks are available online at www.StemSight.org for stem cell researchers to develop new hypotheses, discover potential mechanisms involving sparsely annotated genes, and prioritize genes of interest for experimental validation. © 2013 AlphaMed Press.

Study reveals potentially prognostic gene, metabolism changes in kidney cancers | Center for Cancer Research

Cancer.gov

The Cancer Genome Atlas Research Network investigators, including CCR scientists, identified genetic and metabolic pathway changes linked to reduced survival of patients within and across subtypes of renal cell carcinoma (RCC), a type of kidney cancer. The study, published April 5, 2018, in Cell Reports, is part of The Cancer Genome Atlas (TCGA) Program, a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI).

Study reveals potentially prognostic gene, metabolism changes in kidney cancers | Center for Cancer Research

Cancer.gov

The Cancer Genome Atlas Research Network investigators, including CCR scientists, identified genetic and metabolic pathway changes linked to reduced survival of patients within and across subtypes of renal cell carcinoma (RCC), a type of kidney cancer. The study, published April 5, 2018, in Cell Reports, is part of The Cancer Genome Atlas (TCGA) Program, a joint effort of the

Catching the ’Network Science’ Bug: Insight and Opportunity for the Operations Researcher

DTIC Science & Technology

2008-01-21

publication: Operations Research agents often interface in a decentralized and asynchronous manner, and where the interaction of “ selfish ” agents...interaction of the two. For example, in a metabolic network, the activation of a gene may alter the biochemical pathways that in turn can alter other genes , and...people, computers, vehicles, cells, or genes . In these systems, all configurations are not feasible, simply because survival for these systems means

Measuring Networking as an Outcome Variable in Undergraduate Research Experiences.

PubMed

Hanauer, David I; Hatfull, Graham

2015-01-01

The aim of this paper is to propose, present, and validate a simple survey instrument to measure student conversational networking. The tool consists of five items that cover personal and professional social networks, and its basic principle is the self-reporting of degrees of conversation, with a range of specific discussion partners. The networking instrument was validated in three studies. The basic psychometric characteristics of the scales were established by conducting a factor analysis and evaluating internal consistency using Cronbach's alpha. The second study used a known-groups comparison and involved comparing outcomes for networking scales between two different undergraduate laboratory courses (one involving a specific effort to enhance networking). The final study looked at potential relationships between specific networking items and the established psychosocial variable of project ownership through a series of binary logistic regressions. Overall, the data from the three studies indicate that the networking scales have high internal consistency (α = 0.88), consist of a unitary dimension, can significantly differentiate between research experiences with low and high networking designs, and are related to project ownership scales. The ramifications of the networking instrument for student retention, the enhancement of public scientific literacy, and the differentiation of laboratory courses are discussed. © 2015 D. I. Hanauer and G. Hatfull. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Fake news portrayals of stem cells and stem cell research.

PubMed

Marcon, Alessandro R; Murdoch, Blake; Caulfield, Timothy

2017-10-01

This study examines how stem cells and stem cell research are portrayed on websites deemed to be purveyors of distorted and dubious information. Content analysis was conducted on 224 articles from 2015 to 2016, compiled by searching with the keywords 'stem cell(s)' on a list of websites flagged for containing either 'fake' or 'junk science' news. Articles contained various exaggerated positive and negative claims about stem cells and stem cell science, health and science related conspiracy theories, and statements promoting fear and mistrust of conventional medicine. Findings demonstrate the existence of organized misinformation networks, which may lead the public away from accurate information and facilitate a polarization of public discourse.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

Spinning a stem cell ethics web.

PubMed

McDonald, Michael; Longstaff, Holly

2013-01-01

The goal of this study was to provide an ethics education resource for trainees and researchers in the Canadian Stem Cell Network that would address the multiple ethical challenges in stem cell research including accountability in and for research across its multiple dimensions. The website was built using a bottom-up type approach based on an ethics needs assessment in combination with a top-down expert-driven component. There have been 3,615 visitors to the website since it was launched in July, 2011. The ongoing rate of returning visitors (20%) indicates that the website is becoming a valuable tool used multiple times.

Chronic occupational exposure to arsenic induces carcinogenic gene signaling networks and neoplastic transformation in human lung epithelial cells

PubMed Central

Stueckle, Todd A.; Lu, Yongju; Davis, Mary E.; Wang, Liying; Jiang, Bing-Hua; Holaskova, Ida; Schafer, Rosana; Barnett, John B.; Rojanasakul, Yon

2012-01-01

Chronic arsenic exposure remains a human health risk; however a clear mode of action to understand gene signaling-driven arsenic carcinogenesis is currently lacking. This study chronically exposed human lung epithelial BEAS-2B cells to low-dose arsenic trioxide to elucidate cancer promoting gene signaling networks associated with arsenic-transformed (B-As) cells. Following a six month exposure, exposed cells were assessed for enhanced cell proliferation, colony formation, invasion ability and in vivo tumor formation compared to control cell lines. Collected mRNA was subjected to whole genome expression microarray profiling followed by in silico Ingenuity Pathway Analysis (IPA) to identify lung carcinogenesis modes of action. B-As cells displayed significant increases in proliferation, colony formation and invasion ability compared to BEAS-2B cells. B-As injections into nude mice resulted in development of primary and secondary metastatic tumors. Arsenic exposure resulted in widespread up-regulation of genes associated with mitochondrial metabolism and increased reactive oxygen species protection suggesting mitochondrial dysfunction. Carcinogenic initiation via reactive oxygen species and epigenetic mechanisms was further supported by altered DNA repair, histone, and ROS-sensitive signaling. NF-κB, MAPK and NCOR1 signaling disrupted PPARα/δ-mediated lipid homeostasis. A ‘pro-cancer’ gene signaling network identified increased survival, proliferation, inflammation, metabolism, anti-apoptosis and mobility signaling. IPA-ranked signaling networks identified altered p21, EF1α, Akt, MAPK, and NF-κB signaling networks promoting genetic disorder, altered cell cycle, cancer and changes in nucleic acid and energy metabolism. In conclusion, transformed B-As cells with their whole genome expression profile provide an in vitro arsenic model for future lung cancer signaling research and data for chronic arsenic exposure risk assessment. PMID:22521957

Network Medicine for Alzheimer's Disease and Traditional Chinese Medicine.

PubMed

Jarrell, Juliet T; Gao, Li; Cohen, David S; Huang, Xudong

2018-05-11

Alzheimer’s Disease (AD) is a neurodegenerative condition that currently has no known cure. The principles of the expanding field of network medicine (NM) have recently been applied to AD research. The main principle of NM proposes that diseases are much more complicated than one mutation in one gene, and incorporate different genes, connections between genes, and pathways that may include multiple diseases to create full scale disease networks. AD research findings as a result of the application of NM principles have suggested that functional network connectivity, myelination, myeloid cells, and genes and pathways may play an integral role in AD progression, and may be integral to the search for a cure. Different aspects of the AD pathology could be potential targets for drug therapy to slow down or stop the disease from advancing, but more research is needed to reach definitive conclusions. Additionally, the holistic approaches of network pharmacology in traditional Chinese medicine (TCM) research may be viable options for the AD treatment, and may lead to an effective cure for AD in the future.

On the cutting edge of organ renewal: Identification, regulation, and evolution of incisor stem cells.

PubMed

Kuang-Hsien Hu, Jimmy; Mushegyan, Vagan; Klein, Ophir D

2014-02-01

The rodent incisor is one of a number of organs that grow continuously throughout the life of an animal. Continuous growth of the incisor arose as an evolutionary adaptation to compensate for abrasion at the distal end of the tooth. The sustained turnover of cells that deposit the mineralized dental tissues is made possible by epithelial and mesenchymal stem cells residing at the proximal end of the incisor. A complex network of signaling pathways and transcription factors regulates the formation, maintenance, and differentiation of these stem cells during development and throughout adulthood. Research over the past 15 years has led to significant progress in our understanding of this network, which includes FGF, BMP, Notch, and Hh signaling, as well as cell adhesion molecules and micro-RNAs. This review surveys key historical experiments that laid the foundation of the field and discusses more recent findings that definitively identified the stem cell population, elucidated the regulatory network, and demonstrated possible genetic mechanisms for the evolution of continuously growing teeth. Copyright © 2013 Wiley Periodicals, Inc.

On the cutting edge of organ renewal: identification, regulation and evolution of incisor stem cells

PubMed Central

Hu, Jimmy Kuang-Hsien; Mushegyan, Vagan; Klein, Ophir D.

2014-01-01

The rodent incisor is one of a number of organs that grow continuously throughout the life of an animal. Continuous growth of the incisor arose as an evolutionary adaptation to compensate for abrasion at the distal end of the tooth. The sustained turnover of cells that deposit the mineralized dental tissues is made possible by epithelial and mesenchymal stem cells residing at the proximal end of the incisor. A complex network of signaling pathways and transcription factors regulates the formation, maintenance, and differentiation of these stem cells during development and throughout adulthood. Research over the past 15 years has led to significant progress in our understanding of this network, which includes FGF, BMP, Notch, and Hh signaling, as well as cell adhesion molecules and microRNAs. This review surveys key historical experiments that laid the foundation of the field and discusses more recent findings that definitively identified the stem cell population, elucidated the regulatory network, and demonstrated possible genetic mechanisms for the evolution of continuously growing teeth. PMID:24307456

Inference of genetic network of Xenopus frog egg: improved genetic algorithm.

PubMed

Wu, Shinq-Jen; Chou, Chia-Hsien; Wu, Cheng-Tao; Lee, Tsu-Tian

2006-01-01

An improved genetic algorithm (IGA) is proposed to achieve S-system gene network modeling of Xenopus frog egg. Via the time-courses training datasets from Michaelis-Menten model, the optimal parameters are learned. The S-system can clearly describe activative and inhibitory interaction between genes as generating and consuming process. We concern the mitotic control in cell-cycle of Xenopus frog egg to realize cyclin-Cdc2 and Cdc25 for MPF activity. The proposed IGA can achieve global search with migration and keep the best chromosome with elitism operation. The generated gene regulatory networks can provide biological researchers for further experiments in Xenopus frog egg cell cycle control.

ATM encryption testing

NASA Astrophysics Data System (ADS)

Capell, Joyce; Deeth, David

1996-01-01

This paper describes why encryption was selected by Lockheed Martin Missiles & Space as the means for securing ATM networks. The ATM encryption testing program is part of an ATM network trial provided by Pacific Bell under the California Research Education Network (CalREN). The problem being addressed is the threat to data security which results when changing from a packet switched network infrastructure to a circuit switched ATM network backbone. As organizations move to high speed cell-based networks, there is a break down in the traditional security model which is designed to protect packet switched data networks from external attacks. This is due to the fact that most data security firewalls filter IP packets, restricting inbound and outbound protocols, e.g. ftp. ATM networks, based on cell-switching over virtual circuits, does not support this method for restricting access since the protocol information is not carried by each cell. ATM switches set up multiple virtual connections, thus there is no longer a single point of entry into the internal network. The problem is further complicated by the fact that ATM networks support high speed multi-media applications, including real time video and video teleconferencing which are incompatible with packet switched networks. The ability to restrict access to Lockheed Martin networks in support of both unclassified and classified communications is required before ATM network technology can be fully deployed. The Lockheed Martin CalREN ATM testbed provides the opportunity to test ATM encryption prototypes with actual applications to assess the viability of ATM encryption methodologies prior to installing large scale ATM networks. Two prototype ATM encryptors are being tested: (1) `MILKBUSH' a prototype encryptor developed by NSA for transmission of government classified data over ATM networks, and (2) a prototype ATM encryptor developed by Sandia National Labs in New Mexico, for the encryption of proprietary data.

Force Exertion and Transmission in Cross-Linked Actin Networks

NASA Astrophysics Data System (ADS)

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.

Model-based design of RNA hybridization networks implemented in living cells.

PubMed

Rodrigo, Guillermo; Prakash, Satya; Shen, Shensi; Majer, Eszter; Daròs, José-Antonio; Jaramillo, Alfonso

2017-09-19

Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Trials in the prevention of type 1 diabetes: current and future.

PubMed

Wherrett, Diane K

2014-08-01

A major thrust in type 1 diabetes research is stopping the destruction of beta cells that leads to type 1 diabetes. Research over the past 30 years has defined genetic factors and evidence of autoimmunity that have led to the development of robust prediction models in those at high risk for type 1 diabetes. The ability to identify those at risk and the development of new agents and of collaborative research networks has led to multiple trials aimed at preventing beta cell loss. Trials at all stages of beta cell loss have been conducted: primary prevention (prior to the development of autoimmunity); secondary prevention (after autoantibodies are found) and tertiary prevention (intervening after diagnosis to maintain remaining beta cells). Studies have shown mixed results; evidence of maintained insulin secretion after the time of diagnosis has been described in a number of studies, and primary and secondary prevention is proving to be elusive. Much has been learned from the increasing number of studies in the field in terms of network creation, study design and choice of intervention that will facilitate new avenues of investigation. Copyright © 2014 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data.

PubMed

Woodhouse, Steven; Piterman, Nir; Wintersteiger, Christoph M; Göttgens, Berthold; Fisher, Jasmin

2018-05-25

Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge. The Single Cell Network Synthesis toolkit (SCNS) is a general-purpose computational tool for the reconstruction and analysis of executable models from single-cell gene expression data. Through a graphical user interface, SCNS takes single-cell qPCR or RNA-sequencing data taken across a time course, and searches for logical rules that drive transitions from early cell states towards late cell states. Because the resulting reconstructed models are executable, they can be used to make predictions about the effect of specific gene perturbations on the generation of specific lineages. SCNS should be of broad interest to the growing number of researchers working in single-cell genomics and will help further facilitate the generation of valuable mechanistic insights into developmental, homeostatic and disease processes.

Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps

PubMed Central

Kuperstein, I; Bonnet, E; Nguyen, H-A; Cohen, D; Viara, E; Grieco, L; Fourquet, S; Calzone, L; Russo, C; Kondratova, M; Dutreix, M; Barillot, E; Zinovyev, A

2015-01-01

Cancerogenesis is driven by mutations leading to aberrant functioning of a complex network of molecular interactions and simultaneously affecting multiple cellular functions. Therefore, the successful application of bioinformatics and systems biology methods for analysis of high-throughput data in cancer research heavily depends on availability of global and detailed reconstructions of signalling networks amenable for computational analysis. We present here the Atlas of Cancer Signalling Network (ACSN), an interactive and comprehensive map of molecular mechanisms implicated in cancer. The resource includes tools for map navigation, visualization and analysis of molecular data in the context of signalling network maps. Constructing and updating ACSN involves careful manual curation of molecular biology literature and participation of experts in the corresponding fields. The cancer-oriented content of ACSN is completely original and covers major mechanisms involved in cancer progression, including DNA repair, cell survival, apoptosis, cell cycle, EMT and cell motility. Cell signalling mechanisms are depicted in detail, together creating a seamless ‘geographic-like' map of molecular interactions frequently deregulated in cancer. The map is browsable using NaviCell web interface using the Google Maps engine and semantic zooming principle. The associated web-blog provides a forum for commenting and curating the ACSN content. ACSN allows uploading heterogeneous omics data from users on top of the maps for visualization and performing functional analyses. We suggest several scenarios for ACSN application in cancer research, particularly for visualizing high-throughput data, starting from small interfering RNA-based screening results or mutation frequencies to innovative ways of exploring transcriptomes and phosphoproteomes. Integration and analysis of these data in the context of ACSN may help interpret their biological significance and formulate mechanistic hypotheses. ACSN may also support patient stratification, prediction of treatment response and resistance to cancer drugs, as well as design of novel treatment strategies. PMID:26192618

Excavation of attractor modules for nasopharyngeal carcinoma via integrating systemic module inference with attract method.

PubMed

Jiang, T; Jiang, C-Y; Shu, J-H; Xu, Y-J

2017-07-10

The molecular mechanism of nasopharyngeal carcinoma (NPC) is poorly understood and effective therapeutic approaches are needed. This research aimed to excavate the attractor modules involved in the progression of NPC and provide further understanding of the underlying mechanism of NPC. Based on the gene expression data of NPC, two specific protein-protein interaction networks for NPC and control conditions were re-weighted using Pearson correlation coefficient. Then, a systematic tracking of candidate modules was conducted on the re-weighted networks via cliques algorithm, and a total of 19 and 38 modules were separately identified from NPC and control networks, respectively. Among them, 8 pairs of modules with similar gene composition were selected, and 2 attractor modules were identified via the attract method. Functional analysis indicated that these two attractor modules participate in one common bioprocess of cell division. Based on the strategy of integrating systemic module inference with the attract method, we successfully identified 2 attractor modules. These attractor modules might play important roles in the molecular pathogenesis of NPC via affecting the bioprocess of cell division in a conjunct way. Further research is needed to explore the correlations between cell division and NPC.

NaviCell Web Service for network-based data visualization

PubMed Central

Bonnet, Eric; Viara, Eric; Kuperstein, Inna; Calzone, Laurence; Cohen, David P. A.; Barillot, Emmanuel; Zinovyev, Andrei

2015-01-01

Data visualization is an essential element of biological research, required for obtaining insights and formulating new hypotheses on mechanisms of health and disease. NaviCell Web Service is a tool for network-based visualization of ‘omics’ data which implements several data visual representation methods and utilities for combining them together. NaviCell Web Service uses Google Maps and semantic zooming to browse large biological network maps, represented in various formats, together with different types of the molecular data mapped on top of them. For achieving this, the tool provides standard heatmaps, barplots and glyphs as well as the novel map staining technique for grasping large-scale trends in numerical values (such as whole transcriptome) projected onto a pathway map. The web service provides a server mode, which allows automating visualization tasks and retrieving data from maps via RESTful (standard HTTP) calls. Bindings to different programming languages are provided (Python and R). We illustrate the purpose of the tool with several case studies using pathway maps created by different research groups, in which data visualization provides new insights into molecular mechanisms involved in systemic diseases such as cancer and neurodegenerative diseases. PMID:25958393

ANALYSIS OF CLINICAL AND DERMOSCOPIC FEATURES FOR BASAL CELL CARCINOMA NEURAL NETWORK CLASSIFICATION

PubMed Central

Cheng, Beibei; Stanley, R. Joe; Stoecker, William V; Stricklin, Sherea M.; Hinton, Kristen A.; Nguyen, Thanh K.; Rader, Ryan K.; Rabinovitz, Harold S.; Oliviero, Margaret; Moss, Randy H.

2012-01-01

Background Basal cell carcinoma (BCC) is the most commonly diagnosed cancer in the United States. In this research, we examine four different feature categories used for diagnostic decisions, including patient personal profile (patient age, gender, etc.), general exam (lesion size and location), common dermoscopic (blue-gray ovoids, leaf-structure dirt trails, etc.), and specific dermoscopic lesion (white/pink areas, semitranslucency, etc.). Specific dermoscopic features are more restricted versions of the common dermoscopic features. Methods Combinations of the four feature categories are analyzed over a data set of 700 lesions, with 350 BCCs and 350 benign lesions, for lesion discrimination using neural network-based techniques, including Evolving Artificial Neural Networks and Evolving Artificial Neural Network Ensembles. Results Experiment results based on ten-fold cross validation for training and testing the different neural network-based techniques yielded an area under the receiver operating characteristic curve as high as 0.981 when all features were combined. The common dermoscopic lesion features generally yielded higher discrimination results than other individual feature categories. Conclusions Experimental results show that combining clinical and image information provides enhanced lesion discrimination capability over either information source separately. This research highlights the potential of data fusion as a model for the diagnostic process. PMID:22724561

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

PubMed Central

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

2016-01-01

Abstract 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 in a wide spectrum of biological systems. PMID:27124473

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

PubMed

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 in a wide spectrum of biological systems.

NCI 1st International Workshop on the Biology, Prevention, and Treatment of Relapse After Allogeneic Hematopoietic Stem Cell Transplantation: Summary and Recommendations from the Organizing Committee

PubMed Central

Bishop, Michael R.; Alyea, Edwin P.; Cairo, Mitchell S.; Falkenburg, J.H. Frederik; June, Carl H.; Kröger, Nicolaus; Little, Richard F.; Miller, Jeffrey S.; Pavletic, Steven Z.; Porter, David L.; Riddell, Stanley R.; van Besien, Koen; Wayne, Alan S.; Weisdorf, Daniel J.; Wu, Roy S.; Giralt, Sergio

2011-01-01

The First International Workshop on The Biology, Prevention, and Treatment of Relapse After Allogeneic Hematopoietic Stem Cell Transplantation was organized and convened to identify, prioritize, and coordinate future research activities related to relapse after allogeneic hematopoietic stem cell transplantation (alloHSCT). Each of the Workshop’s six working committees have published individual reports of ongoing basic, translational and clinical research and recommended areas for future research related to the areas of relapse biology, epidemiology, prevention and treatment. This document summarizes each of the committees’ recommendations and suggests three major initiatives for a coordinated research effort to address the problem of relapse after alloHSCT. The first is the need to establish multi-center correlative and clinical trials networks for basic/translational, epidemiological, and clinical research. Second, there is a need for a network of biorepositories for the collection of samples pre- and post-alloHSCT to aid in laboratory and clinical studies. Third, there should be further refinement, implementation, and study of the proposed Workshop disease-specific response and relapse definitions and the recommendations for monitoring of minimal residual disease. These recommendations, in coordination with ongoing research initiatives and transplant organizations, provide a research framework to rapidly and efficiently address the significant problem of relapse following alloHSCT. PMID:21224011

78 FR 37837 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-24

...: Basic Research on Human Embryonic Stem Cells. Date: July 16-17, 2013. Time: 8:00 a.m. to 5:00 p.m... Panel; RFA-RM-13-002: Planning Grants for the NIH National Research Mentoring Network (NRMN) P20. Date... and Related Research Integrated Review Group; NeuroAIDS and other End-Organ Diseases Study Section...

CIAN - Cell Imaging and Analysis Network at the Biology Department of McGill University

PubMed Central

Lacoste, J.; Lesage, G.; Bunnell, S.; Han, H.; Küster-Schöck, E.

2010-01-01

CF-31 The Cell Imaging and Analysis Network (CIAN) provides services and tools to researchers in the field of cell biology from within or outside Montreal's McGill University community. CIAN is composed of six scientific platforms: Cell Imaging (confocal and fluorescence microscopy), Proteomics (2-D protein gel electrophoresis and DiGE, fluorescent protein analysis), Automation and High throughput screening (Pinning robot and liquid handler), Protein Expression for Antibody Production, Genomics (real-time PCR), and Data storage and analysis (cluster, server, and workstations). Users submit project proposals, and can obtain training and consultation in any aspect of the facility, or initiate projects with the full-service platforms. CIAN is designed to facilitate training, enhance interactions, as well as share and maintain resources and expertise.

Multicenter Cell Processing for Cardiovascular Regenerative Medicine Applications - The Cardiovascular Cell Therapy Research Network (CCTRN) Experience

PubMed Central

Gee, Adrian P.; Richman, Sara; Durett, April; McKenna, David; Traverse, Jay; Henry, Timothy; Fisk, Diann; Pepine, Carl; Bloom, Jeannette; Willerson, James; Prater, Karen; Zhao, David; Koç, Jane Reese; Ellis, Steven; Taylor, Doris; Cogle, Christopher; Moyé, Lemuel; Simari, Robert; Skarlatos, Sonia

2013-01-01

Background Aims Multi-center cellular therapy clinical trials require the establishment and implementation of standardized cell processing protocols and associated quality control mechanisms. The aims here were to develop such an infrastructure in support of the Cardiovascular Cell Therapy Research Network (CCTRN) and to report on the results of processing for the first 60 patients. Methods Standardized cell preparations, consisting of autologous bone marrow mononuclear cells, prepared using the Sepax device were manufactured at each of the five processing facilities that supported the clinical treatment centers. Processing staff underwent centralized training that included proficiency evaluation. Quality was subsequently monitored by a central quality control program that included product evaluation by the CCTRN biorepositories. Results Data from the first 60 procedures demonstrate that uniform products, that met all release criteria, could be manufactured at all five sites within 7 hours of receipt of the bone marrow. Uniformity was facilitated by use of the automated systems (the Sepax for processing and the Endosafe device for endotoxin testing), standardized procedures and centralized quality control. Conclusions Complex multicenter cell therapy and regenerative medicine protocols can, where necessary, successfully utilize local processing facilities once an effective infrastructure is in place to provide training, and quality control. PMID:20524773

A theoretical and computational framework for mechanics of the cortex

NASA Astrophysics Data System (ADS)

Torres-SáNchez, Alejandro; Arroyo, Marino

The cell cortex is a thin network of actin filaments lying beneath the cell surface of animal cells. Myosin motors exert contractile forces in this network leading to active stresses, which play a key role in processes such as cytokinesis or cell migration. Thus, understanding the mechanics of the cortex is fundamental to understand the mechanics of animal cells. Due to the dynamic remodeling of the actin network, the cortex behaves as a viscoelastic fluid. Furthermore, due to the difference between its thickness (tens of nanometers) and its dimensions (tens of microns), the cortex can be regarded a surface. Thus, we can model the cortex as a viscoelastic fluid, confined to a surface, that generates active stresses. Interestingly, geometric confinement results in the coupling between shape generation and material flows. In this work we present a theoretical framework to model the mechanics of the cortex that couples elasticity, hydrodynamics and force generation. We complement our theoretical description with a computational setting to simulate the resulting non-linear equations. We use this methodology to understand different processes such as asymmetric cell division or experimental probing of the rheology of the cortex We acknowledge the support of the Europen Research Council through Grant ERC CoG-681434.

Scientists' perspectives on the ethical issues of stem cell research.

PubMed

Longstaff, Holly; Schuppli, Catherine A; Preto, Nina; Lafrenière, Darquise; McDonald, Michael

2009-06-01

This paper describes findings from an ethics education project funded by the Canadian Stem Cell Network (SCN). The project is part of a larger research initiative entitled "The Stem Cell Research Environment: Drawing the Evidence and Experience Together". The ethics education study began with a series of focus groups with SCN researchers and trainees as part of a "needs assessment" effort. The purpose of these discussions was to identify the main ethical issues associated with stem cell (SC) research from the perspective of the stem cell community. This paper will focus on five prominent themes that emerged from the focus group data including: (1) the source of stem cells; (2) the power of stem cells; (3) working within a charged research environment; (4) the regulatory context; and (5) ethics training for scientists. Additional discussions are planned with others involved in Canadian stem cell research (e.g., research ethics board members, policy makers) to supplement initial findings. These assessment results combined with existing bioethics literature will ultimately inform a web-based ethics education module for the SCN. We believe that our efforts are important for those analyzing the ethical, legal, and social issues (ELSI) in this area because our in depth understanding of stem cell researcher perspectives will enable us to develop more relevant and effective education material, which in turn should help SC researchers address the important ethical challenges in their area.

GIANT API: an application programming interface for functional genomics.

PubMed

Roberts, Andrew M; Wong, Aaron K; Fisk, Ian; Troyanskaya, Olga G

2016-07-08

GIANT API provides biomedical researchers programmatic access to tissue-specific and global networks in humans and model organisms, and associated tools, which includes functional re-prioritization of existing genome-wide association study (GWAS) data. Using tissue-specific interaction networks, researchers are able to predict relationships between genes specific to a tissue or cell lineage, identify the changing roles of genes across tissues and uncover disease-gene associations. Additionally, GIANT API enables computational tools like NetWAS, which leverages tissue-specific networks for re-prioritization of GWAS results. The web services covered by the API include 144 tissue-specific functional gene networks in human, global functional networks for human and six common model organisms and the NetWAS method. GIANT API conforms to the REST architecture, which makes it stateless, cacheable and highly scalable. It can be used by a diverse range of clients including web browsers, command terminals, programming languages and standalone apps for data analysis and visualization. The API is freely available for use at http://giant-api.princeton.edu. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Synthetic biology in mammalian cells: Next generation research tools and therapeutics

PubMed Central

Lienert, Florian; Lohmueller, Jason J; Garg, Abhishek; Silver, Pamela A

2014-01-01

Recent progress in DNA manipulation and gene circuit engineering has greatly improved our ability to programme and probe mammalian cell behaviour. These advances have led to a new generation of synthetic biology research tools and potential therapeutic applications. Programmable DNA-binding domains and RNA regulators are leading to unprecedented control of gene expression and elucidation of gene function. Rebuilding complex biological circuits such as T cell receptor signalling in isolation from their natural context has deepened our understanding of network motifs and signalling pathways. Synthetic biology is also leading to innovative therapeutic interventions based on cell-based therapies, protein drugs, vaccines and gene therapies. PMID:24434884

Multicell migration tracking within angiogenic networks by deep learning-based segmentation and augmented Bayesian filtering.

PubMed

Wang, Mengmeng; Ong, Lee-Ling Sharon; Dauwels, Justin; Asada, H Harry

2018-04-01

Cell migration is a key feature for living organisms. Image analysis tools are useful in studying cell migration in three-dimensional (3-D) in vitro environments. We consider angiogenic vessels formed in 3-D microfluidic devices (MFDs) and develop an image analysis system to extract cell behaviors from experimental phase-contrast microscopy image sequences. The proposed system initializes tracks with the end-point confocal nuclei coordinates. We apply convolutional neural networks to detect cell candidates and combine backward Kalman filtering with multiple hypothesis tracking to link the cell candidates at each time step. These hypotheses incorporate prior knowledge on vessel formation and cell proliferation rates. The association accuracy reaches 86.4% for the proposed algorithm, indicating that the proposed system is able to associate cells more accurately than existing approaches. Cell culture experiments in 3-D MFDs have shown considerable promise for improving biology research. The proposed system is expected to be a useful quantitative tool for potential microscopy problems of MFDs.

Cell Phones: Rule-Setting, Rule-Breaking, and Relationships in Classrooms

ERIC Educational Resources Information Center

Charles, Anita S.

2012-01-01

Based on a small qualitative study, this article focuses on understanding the rules for cell phones and other social networking media in schools, an aspect of broader research that led to important understandings of teacher-student negotiations. It considers the rules that schools and teachers make, the rampant breaking of these rules, the…

Constructing Smart Protocells with Built-In DNA Computational Core to Eliminate Exogenous Challenge.

PubMed

Lyu, Yifan; Wu, Cuichen; Heinke, Charles; Han, Da; Cai, Ren; Teng, I-Ting; Liu, Yuan; Liu, Hui; Zhang, Xiaobing; Liu, Qiaoling; Tan, Weihong

2018-06-06

A DNA reaction network is like a biological algorithm that can respond to "molecular input signals", such as biological molecules, while the artificial cell is like a microrobot whose function is powered by the encapsulated DNA reaction network. In this work, we describe the feasibility of using a DNA reaction network as the computational core of a protocell, which will perform an artificial immune response in a concise way to eliminate a mimicked pathogenic challenge. Such a DNA reaction network (RN)-powered protocell can realize the connection of logical computation and biological recognition due to the natural programmability and biological properties of DNA. Thus, the biological input molecules can be easily involved in the molecular computation and the computation process can be spatially isolated and protected by artificial bilayer membrane. We believe the strategy proposed in the current paper, i.e., using DNA RN to power artificial cells, will lay the groundwork for understanding the basic design principles of DNA algorithm-based nanodevices which will, in turn, inspire the construction of artificial cells, or protocells, that will find a place in future biomedical research.

75 FR 18512 - National Institute of Mental Health; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-12

... U.S.C. App.), notice is hereby given of an Interagency Autism Coordinating Committee (IACC) meeting... several presentations on a variety of topics: the Autism Treatment Network, changes in the DSM-V related to autism, stem cell research, non-verbal autism and comparative effectiveness research. The meeting...

Real-time transmission of full-motion echocardiography over a high-speed data network: impact of data rate and network quality of service.

PubMed

Main, M L; Foltz, D; Firstenberg, M S; Bobinsky, E; Bailey, D; Frantz, B; Pleva, D; Baldizzi, M; Meyers, D P; Jones, K; Spence, M C; Freeman, K; Morehead, A; Thomas, J D

2000-08-01

With high-resolution network transmission required for telemedicine, education, and guided-image acquisition, the impact of errors and transmission rates on image quality needs evaluation. We transmitted clinical echocardiograms from 2 National Aeronautics and Space Administration (NASA) research centers with the use of Motion Picture Expert Group-2 (MPEG-2) encoding and asynchronous transmission mode (ATM) network protocol over the NASA Research and Education Network. Data rates and network quality (cell losses [CLR], errors [CER], and delay variability [CVD]) were altered and image quality was judged. At speeds of 3 to 5 megabits per second (Mbps), digital images were superior to those on videotape; at 2 Mbps, images were equivalent. Increasing CLR caused occasional, brief pauses. Extreme CER and CDV increases still yielded high-quality images. Real-time echocardiographic acquisition, guidance, and transmission is feasible with the use of MPEG-2 and ATM with broadcast quality seen above 3 Mbps, even with severe network quality degradation. These techniques can be applied to telemedicine and used for planned echocardiography aboard the International Space Station.

Real-time transmission of full-motion echocardiography over a high-speed data network: impact of data rate and network quality of service

NASA Technical Reports Server (NTRS)

Main, M. L.; Foltz, D.; Firstenberg, M. S.; Bobinsky, E.; Bailey, D.; Frantz, B.; Pleva, D.; Baldizzi, M.; Meyers, D. P.; Jones, K.;

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org. PMID:21190573

Microfluidics-based in vivo mimetic systems for the study of cellular biology.

PubMed

Kim, Donghyuk; Wu, Xiaojie; Young, Ashlyn T; Haynes, Christy L

2014-04-15

The human body is a complex network of molecules, organelles, cells, tissues, and organs: an uncountable number of interactions and transformations interconnect all the system's components. In addition to these biochemical components, biophysical components, such as pressure, flow, and morphology, and the location of all of these interactions play an important role in the human body. Technical difficulties have frequently limited researchers from observing cellular biology as it occurs within the human body, but some state-of-the-art analytical techniques have revealed distinct cellular behaviors that occur only in the context of the interactions. These types of findings have inspired bioanalytical chemists to provide new tools to better understand these cellular behaviors and interactions. What blocks us from understanding critical biological interactions in the human body? Conventional approaches are often too naïve to provide realistic data and in vivo whole animal studies give complex results that may or may not be relevant for humans. Microfluidics offers an opportunity to bridge these two extremes: while these studies will not model the complexity of the in vivo human system, they can control the complexity so researchers can examine critical factors of interest carefully and quantitatively. In addition, the use of human cells, such as cells isolated from donated blood, captures human-relevant data and limits the use of animals in research. In addition, researchers can adapt these systems easily and cost-effectively to a variety of high-end signal transduction mechanisms, facilitating high-throughput studies that are also spatially, temporally, or chemically resolved. These strengths should allow microfluidic platforms to reveal critical parameters in the human body and provide insights that will help with the translation of pharmacological advances to clinical trials. In this Account, we describe selected microfluidic innovations within the last 5 years that focus on modeling both biophysical and biochemical interactions in cellular communication, such as flow and cell-cell networks. We also describe more advanced systems that mimic higher level biological networks, such as organ on-a-chip and animal on-a-chip models. Since the first papers in the early 1990s, interest in the bioanalytical use of microfluidics has grown significantly. Advances in micro-/nanofabrication technology have allowed researchers to produce miniaturized, biocompatible assay platforms suitable for microfluidic studies in biochemistry and chemical biology. Well-designed microfluidic platforms can achieve quick, in vitro analyses on pico- and femtoliter volume samples that are temporally, spatially, and chemically resolved. In addition, controlled cell culture techniques using a microfluidic platform have produced biomimetic systems that allow researchers to replicate and monitor physiological interactions. Pioneering work has successfully created cell-fluid, cell-cell, cell-tissue, tissue-tissue, even organ-like level interfaces. Researchers have monitored cellular behaviors in these biomimetic microfluidic environments, producing validated model systems to understand human pathophysiology and to support the development of new therapeutics.

Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks | Center for Cancer Research

Cancer.gov

The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancers belong to four distinct diagnostic categories and often present diagnostic dilemmas in

Cell segmentation in histopathological images with deep learning algorithms by utilizing spatial relationships.

PubMed

Hatipoglu, Nuh; Bilgin, Gokhan

2017-10-01

In many computerized methods for cell detection, segmentation, and classification in digital histopathology that have recently emerged, the task of cell segmentation remains a chief problem for image processing in designing computer-aided diagnosis (CAD) systems. In research and diagnostic studies on cancer, pathologists can use CAD systems as second readers to analyze high-resolution histopathological images. Since cell detection and segmentation are critical for cancer grade assessments, cellular and extracellular structures should primarily be extracted from histopathological images. In response, we sought to identify a useful cell segmentation approach with histopathological images that uses not only prominent deep learning algorithms (i.e., convolutional neural networks, stacked autoencoders, and deep belief networks), but also spatial relationships, information of which is critical for achieving better cell segmentation results. To that end, we collected cellular and extracellular samples from histopathological images by windowing in small patches with various sizes. In experiments, the segmentation accuracies of the methods used improved as the window sizes increased due to the addition of local spatial and contextual information. Once we compared the effects of training sample size and influence of window size, results revealed that the deep learning algorithms, especially convolutional neural networks and partly stacked autoencoders, performed better than conventional methods in cell segmentation.

Three levels of neuroelectronic interfacing: silicon chips with ion channels, nerve cells, and brain tissue.

PubMed

Fromherz, Peter

2006-12-01

We consider the direct electrical interfacing of semiconductor chips with individual nerve cells and brain tissue. At first, the structure of the cell-chip contact is studied. Then we characterize the electrical coupling of ion channels--the electrical elements of nerve cells--with transistors and capacitors in silicon chips. On that basis it is possible to implement signal transmission between microelectronics and the microionics of nerve cells in both directions. Simple hybrid neuroelectronic systems are assembled with neuron pairs and with small neuronal networks. Finally, the interfacing with capacitors and transistors is extended to brain tissue cultured on silicon chips. The application of highly integrated silicon chips allows an imaging of neuronal activity with high spatiotemporal resolution. The goal of the work is an integration of neuronal network dynamics with digital electronics on a microscopic level with respect to experiments in brain research, medical prosthetics, and information technology.

Immune intervention in type 1 diabetes.

PubMed

Michels, Aaron W; Eisenbarth, George S

2011-06-01

Type 1 diabetes (T1D) is a chronic autoimmune disease that results in the specific immune destruction of insulin producing beta cells. Currently there is no cure for T1D and treatment for the disease consists of lifelong administration of insulin. Immunotherapies aimed at preventing beta cell destruction in T1D patients with residual c-peptide or in individuals developing T1D are being evaluated. Networks of researchers such as TrialNet and the Immune Tolerance Network in the U.S. and similar networks in Europe have been established to evaluate such immunotherapies. This review focuses on immune intervention for the prevention and amelioration of human T1D with a focus on potential immune suppressive, antigen specific and environmental therapies. Copyright © 2011 Elsevier Ltd. All rights reserved.

Microscale Mechanics of Actin Networks During Dynamic Assembly and Dissociation

NASA Astrophysics Data System (ADS)

Gurmessa, Bekele; Robertson-Anderson, Rae; Ross, Jennifer; Nguyen, Dan; Saleh, Omar

Actin is one of the key components of the cytoskeleton, enabling cells to move and divide while maintaining shape by dynamic polymerization, dissociation and crosslinking. Actin polymerization and network formation is driven by ATP hydrolysis and varies depending on the concentrations of actin monomers and crosslinking proteins. The viscoelastic properties of steady-state actin networks have been well-characterized, yet the mechanical properties of these non-equilibrium systems during dynamic assembly and disassembly remain to be understood. We use semipermeable microfluidic devices to induce in situ dissolution and re-polymerization of entangled and crosslinked actin networks, by varying ATP concentrations in real-time, while measuring the mechanical properties during disassembly and re-assembly. We use optical tweezers to sinusoidally oscillate embedded microspheres and measure the resulting force at set time-intervals and in different regions of the network during cyclic assembly/disassembly. We determine the time-dependent viscoelastic properties of non-equilibrium network intermediates and the reproducibility and homogeneity of network formation and dissolution. Results inform the role that cytoskeleton reorganization plays in the dynamic multifunctional mechanics of cells. NSF CAREER Award (DMR-1255446) and a Scialog Collaborative Innovation Award funded by Research Corporation for Scientific Advancement (Grant No. 24192).

ACTH (Adrenocorticotropic Hormone) Test

MedlinePlus

... Time and International Normalized Ratio (PT/INR) PSEN1 Quantitative Immunoglobulins Red Blood Cell (RBC) Antibody Identification Red ... Health Network KidsHealth.org: Endocrine System Cushing's Support & Research Foundation See More See Less Related Images View ...

The Influence of Neuronal Density and Maturation on Network Activity of Hippocampal Cell Cultures: A Methodological Study

PubMed Central

Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2013-01-01

It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm2 cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm2 cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm2 are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are intended to be a reference for the planning of in vitro neurophysiological and neuropharmacological experiments with MEAs. PMID:24386305

The influence of neuronal density and maturation on network activity of hippocampal cell cultures: a methodological study.

PubMed

Biffi, Emilia; Regalia, Giulia; Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2013-01-01

It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm(2) cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm(2) cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm(2) are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are intended to be a reference for the planning of in vitro neurophysiological and neuropharmacological experiments with MEAs.

[Sporulation or competence development? A genetic regulatory network model of cell-fate determination in Bacillus subtilis].

PubMed

Lu, Zhenghui; Zhou, Yuling; Zhang, Xiaozhou; Zhang, Guimin

2015-11-01

Bacillus subtilis is a generally recognized as safe (GRAS) strain that has been widely used in industries including fodder, food, and biological control. In addition, B. subtilis expression system also plays a significant role in the production of industrial enzymes. However, its application is limited by its low sporulation frequency and transformation efficiency. Immense studies have been done on interpreting the molecular mechanisms of sporulation and competence development, whereas only few of them were focused on improving sporulation frequency and transformation efficiency of B. subtilis by genetic modification. The main challenge is that sporulation and competence development, as the two major developmental events in the stationary phase of B. subtilis, are regulated by the complicated intracellular genetic regulatory systems. In addition, mutual regulatory mechanisms also exist in these two developmental events. With the development of genetic and metabolic engineering, constructing genetic regulatory networks is currently one of the most attractive research fields, together with the genetic information of cell growth, metabolism, and development, to guide the industrial application. In this review, the mechanisms of sporulation and competence development of B. subtilis, their interactions, and the genetic regulation of cell growth were interpreted. In addition, the roles of these regulatory networks in guiding basic and applied research of B. subtilis and its related species were discussed.

Human neural stem cell-derived cultures in three-dimensional substrates form spontaneously functional neuronal networks.

PubMed

Smith, Imogen; Silveirinha, Vasco; Stein, Jason L; de la Torre-Ubieta, Luis; Farrimond, Jonathan A; Williamson, Elizabeth M; Whalley, Benjamin J

2017-04-01

Differentiated human neural stem cells were cultured in an inert three-dimensional (3D) scaffold and, unlike two-dimensional (2D) but otherwise comparable monolayer cultures, formed spontaneously active, functional neuronal networks that responded reproducibly and predictably to conventional pharmacological treatments to reveal functional, glutamatergic synapses. Immunocytochemical and electron microscopy analysis revealed a neuronal and glial population, where markers of neuronal maturity were observed in the former. Oligonucleotide microarray analysis revealed substantial differences in gene expression conferred by culturing in a 3D vs a 2D environment. Notable and numerous differences were seen in genes coding for neuronal function, the extracellular matrix and cytoskeleton. In addition to producing functional networks, differentiated human neural stem cells grown in inert scaffolds offer several significant advantages over conventional 2D monolayers. These advantages include cost savings and improved physiological relevance, which make them better suited for use in the pharmacological and toxicological assays required for development of stem cell-based treatments and the reduction of animal use in medical research. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Hydrogels for Engineering of Perfusable Vascular Networks

PubMed Central

Liu, Juan; Zheng, Huaiyuan; Poh, Patrina S. P.; Machens, Hans-Günther; Schilling, Arndt F.

2015-01-01

Hydrogels are commonly used biomaterials for tissue engineering. With their high-water content, good biocompatibility and biodegradability they resemble the natural extracellular environment and have been widely used as scaffolds for 3D cell culture and studies of cell biology. The possible size of such hydrogel constructs with embedded cells is limited by the cellular demand for oxygen and nutrients. For the fabrication of large and complex tissue constructs, vascular structures become necessary within the hydrogels to supply the encapsulated cells. In this review, we discuss the types of hydrogels that are currently used for the fabrication of constructs with embedded vascular networks, the key properties of hydrogels needed for this purpose and current techniques to engineer perfusable vascular structures into these hydrogels. We then discuss directions for future research aimed at engineering of vascularized tissue for implantation. PMID:26184185

Efficient spiking neural network model of pattern motion selectivity in visual cortex.

PubMed

Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

2014-07-01

Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

Effect of Transcranial Magnetic Stimulation on Neuronal Networks

NASA Astrophysics Data System (ADS)

Unsal, Ahmet; Hadimani, Ravi; Jiles, David

2013-03-01

The human brain contains around 100 billion nerve cells controlling our day to day activities. Consequently, brain disorders often result in impairments such as paralysis, loss of coordination and seizure. It has been said that 1 in 5 Americans suffer some diagnosable mental disorder. There is an urgent need to understand the disorders, prevent them and if possible, develop permanent cure for them. As a result, a significant amount of research activities is being directed towards brain research. Transcranial Magnetic Stimulation (TMS) is a promising tool for diagnosing and treating brain disorders. It is a non-invasive treatment method that produces a current flow in the brain which excites the neurons. Even though TMS has been verified to have advantageous effects on various brain related disorders, there have not been enough studies on the impact of TMS on cells. In this study, we are investigating the electrophysiological effects of TMS on one dimensional neuronal culture grown in a circular pathway. Electrical currents are produced on the neuronal networks depending on the directionality of the applied field. This aids in understanding how neuronal networks react under TMS treatment.

One-to-one neuron-electrode interfacing.

PubMed

Greenbaum, Alon; Anava, Sarit; Ayali, Amir; Shein, Mark; David-Pur, Moshe; Ben-Jacob, Eshel; Hanein, Yael

2009-09-15

The question of neuronal network development and organization is a principle one, which is closely related to aspects of neuronal and network form-function interactions. In-vitro two-dimensional neuronal cultures have proved to be an attractive and successful model for the study of these questions. Research is constraint however by the search for techniques aimed at culturing stable networks, whose electrical activity can be reliably and consistently monitored. A simple approach to form small interconnected neuronal circuits while achieving one-to-one neuron-electrode interfacing is presented. Locust neurons were cultured on a novel bio-chip consisting of carbon-nanotube multi-electrode-arrays. The cells self-organized to position themselves in close proximity to the bio-chip electrodes. The organization of the cells on the electrodes was analyzed using time lapse microscopy, fluorescence imaging and scanning electron microscopy. Electrical recordings from well identified cells is presented and discussed. The unique properties of the bio-chip and the specific neuron-nanotube interactions, together with the use of relatively large insect ganglion cells, allowed long-term stabilization (as long as 10 days) of predefined neural network topology as well as high fidelity electrical recording of individual neuron firing. This novel preparation opens ample opportunity for future investigation into key neurobiological questions and principles.

The effects of PI3K-mediated signalling on glioblastoma cell behaviour.

PubMed

Langhans, Julia; Schneele, Lukas; Trenkler, Nancy; von Bandemer, Hélène; Nonnenmacher, Lisa; Karpel-Massler, Georg; Siegelin, Markus D; Zhou, Shaoxia; Halatsch, Marc-Eric; Debatin, Klaus-Michael; Westhoff, Mike-Andrew

2017-11-29

The PI3K/Akt/mTOR signalling network is activated in almost 90% of all glioblastoma, the most common primary brain tumour, which is almost invariably lethal within 15 months of diagnosis. Despite intensive research, modulation of this signalling cascade has so far yielded little therapeutic benefit, suggesting that the role of the PI3K network as a pro-survival factor in glioblastoma and therefore a potential target in combination therapy should be re-evaluated. Therefore, we used two distinct pharmacological inhibitors that block signalling at different points of the cascade, namely, GDC-0941 (Pictilisib), a direct inhibitor of the near apical PI3K, and Rapamycin which blocks the side arm of the network that is regulated by mTOR complex 1. While both substances, at concentrations where they inhibit their primary target, have similar effects on proliferation and sensitisation for temozolomide-induced apoptosis, GDC-0941 appears to have a stronger effect on cellular motility than Rapamycin. In vivo GDC-0941 effectively retards growth of orthotopic transplanted human tumours in murine brains and significantly prolongs mouse survival. However, when looking at genetically identical cell populations that are in alternative states of differentiation, i.e. stem cell-like cells and their differentiated progeny, a more complex picture regarding the PI3K/Akt/mTOR pathway emerges. The pathway is differently regulated in the alternative cell populations and, while it contributes to the increased chemo-resistance of stem cell-like cells compared to differentiated cells, it only contributes to the motility of the latter. Our findings are the first to suggest that within a glioblastoma tumour the PI3K network can have distinct, cell-specific functions. These have to be carefully considered when incorporating inhibition of PI3K-mediated signals into complex combination therapies.

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

A postdoctoral position is available in Dr. Efsun Arda’s Developmental Genomics Group within the Laboratory of Receptor Biology and Gene Expression Branch at the National Cancer Institute (NCI), National Institutes of Health (NIH). Our research is focused on understanding the regulatory networks that govern pancreas cell identity and function in the context of diabetes and

GIANT API: an application programming interface for functional genomics

PubMed Central

Roberts, Andrew M.; Wong, Aaron K.; Fisk, Ian; Troyanskaya, Olga G.

2016-01-01

GIANT API provides biomedical researchers programmatic access to tissue-specific and global networks in humans and model organisms, and associated tools, which includes functional re-prioritization of existing genome-wide association study (GWAS) data. Using tissue-specific interaction networks, researchers are able to predict relationships between genes specific to a tissue or cell lineage, identify the changing roles of genes across tissues and uncover disease-gene associations. Additionally, GIANT API enables computational tools like NetWAS, which leverages tissue-specific networks for re-prioritization of GWAS results. The web services covered by the API include 144 tissue-specific functional gene networks in human, global functional networks for human and six common model organisms and the NetWAS method. GIANT API conforms to the REST architecture, which makes it stateless, cacheable and highly scalable. It can be used by a diverse range of clients including web browsers, command terminals, programming languages and standalone apps for data analysis and visualization. The API is freely available for use at http://giant-api.princeton.edu. PMID:27098035

Inference of developmental gene regulatory networks beyond classical model systems: new approaches in the post-genomic era.

PubMed

Fernandez-Valverde, Selene L; Aguilera, Felipe; Ramos-Díaz, René Alexander

2018-06-18

The advent of high-throughput sequencing technologies has revolutionized the way we understand the transformation of genetic information into morphological traits. Elucidating the network of interactions between genes that govern cell differentiation through development is one of the core challenges in genome research. These networks are known as developmental gene regulatory networks (dGRNs) and consist largely of the functional linkage between developmental control genes, cis-regulatory modules and differentiation genes, which generate spatially and temporally refined patterns of gene expression. Over the last 20 years, great advances have been made in determining these gene interactions mainly in classical model systems, including human, mouse, sea urchin, fruit fly, and worm. This has brought about a radical transformation in the fields of developmental biology and evolutionary biology, allowing the generation of high-resolution gene regulatory maps to analyse cell differentiation during animal development. Such maps have enabled the identification of gene regulatory circuits and have led to the development of network inference methods that can recapitulate the differentiation of specific cell-types or developmental stages. In contrast, dGRN research in non-classical model systems has been limited to the identification of developmental control genes via the candidate gene approach and the characterization of their spatiotemporal expression patterns, as well as to the discovery of cis-regulatory modules via patterns of sequence conservation and/or predicted transcription-factor binding sites. However, thanks to the continuous advances in high-throughput sequencing technologies, this scenario is rapidly changing. Here, we give a historical overview on the architecture and elucidation of the dGRNs. Subsequently, we summarize the approaches available to unravel these regulatory networks, highlighting the vast range of possibilities of integrating multiple technical advances and theoretical approaches to expand our understanding on the global of gene regulation during animal development in non-classical model systems. Such new knowledge will not only lead to greater insights into the evolution of molecular mechanisms underlying cell identity and animal body plans, but also into the evolution of morphological key innovations in animals.

An Energy Model of Place Cell Network in Three Dimensional Space.

PubMed

Wang, Yihong; Xu, Xuying; Wang, Rubin

2018-01-01

Place cells are important elements in the spatial representation system of the brain. A considerable amount of experimental data and classical models are achieved in this area. However, an important question has not been addressed, which is how the three dimensional space is represented by the place cells. This question is preliminarily surveyed by energy coding method in this research. Energy coding method argues that neural information can be expressed by neural energy and it is convenient to model and compute for neural systems due to the global and linearly addable properties of neural energy. Nevertheless, the models of functional neural networks based on energy coding method have not been established. In this work, we construct a place cell network model to represent three dimensional space on an energy level. Then we define the place field and place field center and test the locating performance in three dimensional space. The results imply that the model successfully simulates the basic properties of place cells. The individual place cell obtains unique spatial selectivity. The place fields in three dimensional space vary in size and energy consumption. Furthermore, the locating error is limited to a certain level and the simulated place field agrees to the experimental results. In conclusion, this is an effective model to represent three dimensional space by energy method. The research verifies the energy efficiency principle of the brain during the neural coding for three dimensional spatial information. It is the first step to complete the three dimensional spatial representing system of the brain, and helps us further understand how the energy efficiency principle directs the locating, navigating, and path planning function of the brain.

The gammaTuRC Nanomachine Mechanism and Future Applications

NASA Astrophysics Data System (ADS)

Riehlman, Timothy D.

The complexity and precision of the eukaryotic cell's cytoskeletal network is unrivaled by any man-made systems, perfected by billions of years of evolution, mastering elegant processes of self-assembly, error correction, and self-repair. Understanding the capabilities of these networks will have important and far reaching applications in human medicine by aiding our understanding of developmental processes, cellular division, and disease mechanisms, and through biomimicry will provide insights for biosynthetic manufacturing at the nanoscale and across scales. My research utilizes cross species techniques from Human to the model organism of Fission Yeast to investigate the structure and mechanisms of the g-tubulin ring complex (gTuRC). The gTuRC is a highly conserved eukaryotic multiprotein complex serving as a microtubule organizing center (MTOC) responsible for microtubule nucleation through templating, regulation of dynamics, and establishment of microtubule polarity. Microtubules are 25 nm diameter dynamic flexible polymers of a/b-tubulin heterodimers that function as scaffolds, force generators, distributors, and intracellular highways. The microtubule cytoskeleton is essential for numerous fundamental cellular processes such as mitotic division of chromosomes and cell division, organelle distribution within the cell, cell signaling, and cell shape. This incredible diversity in functions is made possible in part due to molecular motor Kinesin-like proteins (Klps), which allow expansion into more specialized neural, immune, and ciliated cell functions. Combined, the MTOC, microtubules, and Klps represent ideal microtubule cytoskeleton protein (MCP) modular components for in vitro biomimicry towards generation of adaptable patterned networks for human designed applications. My research investigates the hypothesis that a mechanistic understanding of conserved MTOC gTuRC mechanisms will help us understand dynamic cellular nanomachines and their ability to self-assemble complex structures for applications in biomedicine and new roles in biomimetic nanotechnologies.

Microscale force response and morphology of tunable co-polymerized cytoskeleton networks

NASA Astrophysics Data System (ADS)

Ricketts, Shea; Yadav, Vikrant; Ross, Jennifer L.; Robertson-Anderson, Rae M.

The cytoskeleton is largely comprised of actin and microtubules that entangle and crosslink to form complex networks and structures, giving rise to nonlinear multifunctional mechanics in cells. The relative concentrations of semiflexible actin filaments and rigid microtubules tune cytoskeleton function, allowing cells to move and divide while maintaining rigidity and resilience. To elucidate this complex tunability, we create in vitro composites of co-polymerized actin and microtubules with actin:microtubule molar ratios of 0:1-1:0. We use optical tweezers and confocal microscopy to characterize the nonlinear microscale force response and morphology of the composites. We optically drag a microsphere 30 μm through varying actin-microtubule networks at 10 μm/s and 20 μm/s, and measure the force the networks exerts to resist the strain and the force relaxation following strain. We use dual-color confocal microscopy to image distinctly-labeled filaments in the networks, and characterize the integration of actin and microtubules, network connectivity, and filament rigidity. We find that increasing the fraction of microtubules in networks non-monotonically increases elasticity and stiffness, and hinders force relaxation by suppressing network mobility and fluctuations. NSF CAREER Award (DMR-1255446), Scialog Collaborative Innovation Award funded by Research Corporation for Scientific Advancement (Grant No. 24192).

Meeting report of the International Consortium of Stem Cell Networks' Workshop Towards Clinical Trials Using Stem Cells for Amyotrophic Lateral Sclerosis/Motor Neuron Disease.

PubMed

Chaddah, Maya R; Dickie, Brian G; Lyall, Drew; Marshall, Caroline J; Sykes, J Ben; Bruijn, Lucie I

2011-09-01

The International Consortium of Stem Cell Networks' (ICSCN) Workshop Towards Clinical Trials Using Stem Cells for Amyotrophic Lateral Sclerosis (ALS)/Motor Neuron Disease (MND) was held on 24-25 January 2011. Twenty scientific talks addressed aspects of cell derivation and characterization; preclinical research and phased clinical trials involving stem cells; latest developments in induced pluripotent (iPS) cell technology; industry involvement and investment. Three moderated panel discussions focused on unregulated ALS/MND treatments, and the state of the art and barriers to future progress in using stem cells for ALS/MND. This review highlights the major insights that emanated from the workshop around the lessons learned and barriers to progress for using stem cells for understanding disease mechanism, drug discovery, and as therapy for ALS/MND. The full meeting report is only available in the online version of the journal. Please find this material with the following direct link to the article: http://www.informahealthcare.com/als/doi/10.3109/17482968.2011.590992 .

Social networks help to infer causality in the tumor microenvironment.

PubMed

Crespo, Isaac; Doucey, Marie-Agnès; Xenarios, Ioannis

2016-03-15

Networks have become a popular way to conceptualize a system of interacting elements, such as electronic circuits, social communication, metabolism or gene regulation. Network inference, analysis, and modeling techniques have been developed in different areas of science and technology, such as computer science, mathematics, physics, and biology, with an active interdisciplinary exchange of concepts and approaches. However, some concepts seem to belong to a specific field without a clear transferability to other domains. At the same time, it is increasingly recognized that within some biological systems--such as the tumor microenvironment--where different types of resident and infiltrating cells interact to carry out their functions, the complexity of the system demands a theoretical framework, such as statistical inference, graph analysis and dynamical models, in order to asses and study the information derived from high-throughput experimental technologies. In this article we propose to adopt and adapt the concepts of influence and investment from the world of social network analysis to biological problems, and in particular to apply this approach to infer causality in the tumor microenvironment. We showed that constructing a bidirectional network of influence between cell and cell communication molecules allowed us to determine the direction of inferred regulations at the expression level and correctly recapitulate cause-effect relationships described in literature. This work constitutes an example of a transfer of knowledge and concepts from the world of social network analysis to biomedical research, in particular to infer network causality in biological networks. This causality elucidation is essential to model the homeostatic response of biological systems to internal and external factors, such as environmental conditions, pathogens or treatments.

An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

PubMed

Mallik, Mrinmay Kumar

2018-02-07

Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that is indicative of their strong influence in the protein protein interaction network. Similarly the newly proposed GEADCA helped identify the transcription factors with high centrality values indicative of their key roles in transcriptional regulation. The enrichment studies provided a list of molecular functions, biological processes and biochemical pathways associated with the constructed network. The study shows how pathway based databases may be used to create and analyze a relevant protein interaction network in glioma cancer stem cells and identify the essential elements within it to gather insights into the molecular interactions that regulate the properties of glioma stem cells. How these insights may be utilized to help the development of future research towards formulation of new management strategies have been discussed from a theoretical standpoint. Copyright © 2017 Elsevier Ltd. All rights reserved.

Kinome-wide transcriptional profiling of uveal melanoma reveals new vulnerabilities to targeted therapeutics.

PubMed

Bailey, Fiona P; Clarke, Kim; Kalirai, Helen; Kenyani, Jenna; Shahidipour, Haleh; Falciani, Francesco; Coulson, Judy M; Sacco, Joseph J; Coupland, Sarah E; Eyers, Patrick A

2018-03-01

Metastatic uveal melanoma (UM) is invariably fatal, usually within a year of diagnosis. There are currently no effective therapies, and clinical studies employing kinase inhibitors have so far demonstrated limited success. This is despite common activating mutations in GNAQ/11 genes, which trigger signalling pathways that might predispose tumours to a variety of targeted drugs. In this study, we have profiled kinome expression network dynamics in various human ocular melanomas. We uncovered a shared transcriptional profile in human primary UM samples and across a variety of experimental cell-based models. The poor overall response of UM cells to FDA-approved kinase inhibitors contrasted with much higher sensitivity to the bromodomain inhibitor JQ1, a broad transcriptional repressor. Mechanistically, we identified a repressed FOXM1-dependent kinase subnetwork in JQ1-exposed cells that contained multiple cell cycle-regulated protein kinases. Consistently, we demonstrated vulnerability of UM cells to inhibitors of mitotic protein kinases within this network, including the investigational PLK1 inhibitor BI6727. We conclude that analysis of kinome-wide signalling network dynamics has the potential to reveal actionable drug targets and inhibitors of potential therapeutic benefit for UM patients. © 2017 The Authors. Pigment Cell & Melanoma Research Published by John Wiley & Sons.

Outside-out "sniffer-patch" clamp technique for in situ measures of neurotransmitter release.

PubMed

Muller-Chrétien, Emilie

2014-01-01

The mechanism underlying neurotransmitter release is a critical research domain for the understanding of neuronal network function; however, few techniques are available for the direct detection and measurement of neurotransmitter release. To date, the sniffer-patch clamp technique is mainly used to investigate these mechanisms from individual cultured cells. In this study, we propose to adapt the sniffer-patch clamp technique to in situ detection of neurosecretion. Using outside-out patches from donor cells as specific biosensors plunged in acute cerebral slices, this technique allows for proper detection and quantification of neurotransmitter release at the level of the neuronal network.

Enhancing Situational Awareness When Addressing Critical Incidents at Suburban and Rural Schools

DTIC Science & Technology

2012-12-01

121 Amanda Lenhart, “ Teens , Cell Phones and Texting,” in Pew Internet & American Life Project (Washington, DC: Pew...Research Center, 2010), accessed July 22, 2012, http://pewresearch.org/pubs/1572/ teens -cell-phones-text-messages. 122 Dan Costa, “One Cell Phone Per Child...if a video camera were to be disabled, damaged or occluded by smoke, fire, or vandalism .132 The networking between BOCES, the school district, and

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays.

PubMed

Gertz, Monica L; Baker, Zachary; Jose, Sharon; Peixoto, Nathalia

2017-05-29

Micro-electrode arrays (MEAs) can be used to investigate drug toxicity, design paradigms for next-generation personalized medicine, and study network dynamics in neuronal cultures. In contrast with more traditional methods, such as patch-clamping, which can only record activity from a single cell, MEAs can record simultaneously from multiple sites in a network, without requiring the arduous task of placing each electrode individually. Moreover, numerous control and stimulation configurations can be easily applied within the same experimental setup, allowing for a broad range of dynamics to be explored. One of the key dynamics of interest in these in vitro studies has been the extent to which cultured networks display properties indicative of learning. Mouse neuronal cells cultured on MEAs display an increase in response following training induced by electrical stimulation. This protocol demonstrates how to culture neuronal cells on MEAs; successfully record from over 95% of the plated dishes; establish a protocol to train the networks to respond to patterns of stimulation; and sort, plot, and interpret the results from such experiments. The use of a proprietary system for stimulating and recording neuronal cultures is demonstrated. Software packages are also used to sort neuronal units. A custom-designed graphical user interface is used to visualize post-stimulus time histograms, inter-burst intervals, and burst duration, as well as to compare the cellular response to stimulation before and after a training protocol. Finally, representative results and future directions of this research effort are discussed.

The shortest path is not the one you know: application of biological network resources in precision oncology research.

PubMed

Kuperstein, Inna; Grieco, Luca; Cohen, David P A; Thieffry, Denis; Zinovyev, Andrei; Barillot, Emmanuel

2015-03-01

Several decades of molecular biology research have delivered a wealth of detailed descriptions of molecular interactions in normal and tumour cells. This knowledge has been functionally organised and assembled into dedicated biological pathway resources that serve as an invaluable tool, not only for structuring the information about molecular interactions but also for making it available for biological, clinical and computational studies. With the advent of high-throughput molecular profiling of tumours, close to complete molecular catalogues of mutations, gene expression and epigenetic modifications are available and require adequate interpretation. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular profiles of tumours. Making sense out of these descriptions requires biological pathway resources for functional interpretation of the data. In this review, we describe the available biological pathway resources, their characteristics in terms of construction mode, focus, aims and paradigms of biological knowledge representation. We present a new resource that is focused on cancer-related signalling, the Atlas of Cancer Signalling Networks. We briefly discuss current approaches for data integration, visualisation and analysis, using biological networks, such as pathway scoring, guilt-by-association and network propagation. Finally, we illustrate with several examples the added value of data interpretation in the context of biological networks and demonstrate that it may help in analysis of high-throughput data like mutation, gene expression or small interfering RNA screening and can guide in patients stratification. Finally, we discuss perspectives for improving precision medicine using biological network resources and tools. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular patterns of tumours and enable to put precision oncology into general clinical practice. © The Author 2015. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A mathematical model for mesenchymal and chemosensitive cell dynamics.

PubMed

Häcker, Anita

2012-01-01

The structure of an underlying tissue network has a strong impact on cell dynamics. If, in addition, cells alter the network by mechanical and chemical interactions, their movement is called mesenchymal. Important examples for mesenchymal movement include fibroblasts in wound healing and metastatic tumour cells. This paper is focused on the latter. Based on the anisotropic biphasic theory of Barocas and Tranquillo, which models a fibre network and interstitial solution as two-component fluid, a mathematical model for the interactions of cells with a fibre network is developed. A new description for fibre reorientation is given and orientation-dependent proteolysis is added to the model. With respect to cell dynamics, the equation, based on anisotropic diffusion, is extended by haptotaxis and chemotaxis. The chemoattractants are the solute network fragments, emerging from proteolysis, and the epidermal growth factor which may guide the cells to a blood vessel. Moreover the cell migration is impeded at either high or low network density. This new model enables us to study chemotactic cell migration in a complex fibre network and the consequential network deformation. Numerical simulations for the cell migration and network deformation are carried out in two space dimensions. Simulations of cell migration in underlying tissue networks visualise the impact of the network structure on cell dynamics. In a scenario for fibre reorientation between cell clusters good qualitative agreement with experimental results is achieved. The invasion speeds of cells in an aligned and an isotropic fibre network are compared. © Springer-Verlag 2011

CAREST—Multilingual Regional Integration for Health Promotion and Research on Sickle Cell Disease and Thalassemia

PubMed Central

Knight-Madden, Jennifer; Romana, Marc; Villaescusa, Rinaldo; Reid, Marvin; Etienne-Julan, Maryse; Boutin, Laurence; Elana, Gisèle; Elenga, Narcisse; Wheeler, Gillian; Lee, Ketty; Nieves, Rosa; Jones Lecointe, Althea; Lalanne-Mistrih, Marie-Laure; Loko, Gylna; Keclard-Christophe, Lisiane

2016-01-01

Sickle cell disease (SCD) is a significant problem in the Caribbean, where many individuals have African and Asian forebears. However, reliable prevalence data and specific health care programs for SCD are often missing in this region. Closer collaboration between Caribbean territories initiated in 2006 to set up strategies to promote better equity in the health care system for SCD patients led to the formation of CAREST: the Caribbean Network of Researchers on Sickle Cell Disease and Thalassemia. We present the effectiveness of collaborations established by CAREST to promote SCD newborn screening programs and early childhood care, to facilitate health worker training and approaches for prevention and treatment of SCD complications, and to carry out inter-Caribbean research studies. PMID:26999505

An overview on ethical considerations in stem cell research in Iran and ethical recommendations: A review.

PubMed

Farajkhoda, Tahmineh

2017-02-01

Conducting research on the stem cell lines might bring some worthy good to public. Human Stem Cells (hSCs) research has provided opportunities for scientific progresses and new therapies, but some complex ethical matters should be noticed to ensure that stem cell research is carried out in an ethically appropriate manner. The aim of this review article is to discuss the importance of stem cell research, code of ethics for stem cell research in Iran and ethical recommendation. Generation of stem cells for research from human embryo or adult stem cells, saving, maintenance and using of them are the main ethical, legal and jurisprudence concerns in Iran. Concerns regarding human reproduction or human cloning, breach of human dignity, genetic manipulation and probability of tumorogenisity are observed in adult/somatic stem cells. Destruction of embryo to generate stem cell is an important matter in Iran. In this regards, obtaining stem cell from donated frozen embryos through infertility treatment that would be discarded is an acceptable solution in Iran for generation of embryo for research. Ethical, legal, and jurisprudence strategies for using adult/somatic stem cells are determination of ownership of stem cells, trade prohibition of human body, supervision on bio banks and information of Oversight Committee on Stem Cell Research. Recommendations to handle ethical issues for conducting stem cell research are well-designed studies, compliance codes of ethics in biomedical research (specifically codes of ethics on stem cell research, codes of ethics on clinical trials studies and codes of ethics on animals studies), appropriate collaboration with ethics committees and respecting of rights of participants (including both of human and animal rights) in research. In addition, there is a necessity for extending global networks of bioethics for strengthening communications within organizations at both the regional and international level, strengthening legislation systems, designing and establishing convenient collaborative educational courses at different levels.

An overview on ethical considerations in stem cell research in Iran and ethical recommendations: A review

PubMed Central

Farajkhoda, Tahmineh

2017-01-01

Conducting research on the stem cell lines might bring some worthy good to public. Human Stem Cells (hSCs) research has provided opportunities for scientific progresses and new therapies, but some complex ethical matters should be noticed to ensure that stem cell research is carried out in an ethically appropriate manner. The aim of this review article is to discuss the importance of stem cell research, code of ethics for stem cell research in Iran and ethical recommendation. Generation of stem cells for research from human embryo or adult stem cells, saving, maintenance and using of them are the main ethical, legal and jurisprudence concerns in Iran. Concerns regarding human reproduction or human cloning, breach of human dignity, genetic manipulation and probability of tumorogenisity are observed in adult/somatic stem cells. Destruction of embryo to generate stem cell is an important matter in Iran. In this regards, obtaining stem cell from donated frozen embryos through infertility treatment that would be discarded is an acceptable solution in Iran for generation of embryo for research. Ethical, legal, and jurisprudence strategies for using adult/somatic stem cells are determination of ownership of stem cells, trade prohibition of human body, supervision on bio banks and information of Oversight Committee on Stem Cell Research. Recommendations to handle ethical issues for conducting stem cell research are well-designed studies, compliance codes of ethics in biomedical research (specifically codes of ethics on stem cell research, codes of ethics on clinical trials studies and codes of ethics on animals studies), appropriate collaboration with ethics committees and respecting of rights of participants (including both of human and animal rights) in research. In addition, there is a necessity for extending global networks of bioethics for strengthening communications within organizations at both the regional and international level, strengthening legislation systems, designing and establishing convenient collaborative educational courses at different levels. PMID:28462397

Organ reconstruction: Dream or reality for the future.

PubMed

Stoltz, J-F; Zhang, L; Ye, J S; De Isla, N

2017-01-01

The relevance of research on reconstructed organs is justified by the lack of organs available for transplant and the growing needs for the ageing population. The development of a reconstructed organ involves two parallel complementary steps: de-cellularization of the organ with the need to maintain the structural integrity of the extracellular matrix and vascular network and re-cellularization of the scaffold with stem cells or resident cells.Whole organ engineering for liver, heart, lung or kidneys, is particularly difficult because of the structural complexity of organs and heterogeneity of cells. Rodent, porcine and rhesus monkey organs have been de-cellularized to obtain a scaffold with preserved extracellular matrix and vascular network. As concern the cells for re-cellularization, embryonic, foetal, adult, progenitor stem cells and also iPS have been proposed.Heart construction could be an alternative option for the treatment of cardiac insufficiency. It is based on the use of an extra-cellular matrix coming from an animal's heart and seeded with cells likely to reconstruct a normal cardiac function. Though de-cellularization techniques now seem controlled, the issues posed by the selection of cells capable of generating the various components of cardiac tissue are not settled yet. In addition, the recolonisation of the matrix does not only depend on the phenotype of cells that are used, but it is also impacted by the nature of biochemical signals emitted.Recent researches have shown that it is possible to use decellularized whole liver treated by detergents as scaffold, which keeps the entire network of blood vessels and the integrated extracellular matrix (ECM). Beside of decellularized whole organ scaffold seeding cells selected to repopulate a decellularized liver scaffold are critical for the function of the bioengineered liver. At present, potential cell sources are hepatocyte, and mesenchymal stem cells.Pulmonary regeneration using engineering approaches is complex. In fact, several types of local progenitor cells that contribute to cell repair have been described at different levels of the respiratory tract. Moving towards the alveoles, one finds bronchioalveolar stem cells as well as epithelial cells and pneumocytes. A promising option to increase the donor organ pool is to use allogeneic or xenogeneic decellularized lungs as a scaffold to engineer functional lung tissue ex vivo.The kidney is certainly one of the most difficult organs to reconstruct due to its complex nature and the heterogeneous nature of the cells. There is relatively little research on auto-construction, and experiments have been performed on rats, pigs and monkeys.Nevertheless, before these therapeutic approaches can be applied in clinical practice, many researches are necessary to understand and in particular the behaviour of cells on the decellularized organs as well as the mechanisms of their interaction with the microenvironment. Current knowledges allow optimism for the future but definitive answers can only be given after long term animal studies and controlled clinical studies.

NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities.

PubMed

da Rocha, Edroaldo Lummertz; Ung, Choong Yong; McGehee, Cordelia D; Correia, Cristina; Li, Hu

2016-06-02

The sequential chain of interactions altering the binary state of a biomolecule represents the 'information flow' within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein-protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes-network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code (http://www.NetDecoder.org) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Stem cell research and policy in India: current scenario and future perspective.

PubMed

Sharma, Alka

2009-01-01

Stem cell research is an exciting area of biomedical research, with potential to advance cell biology, and other new modalities of treatment for many untreatable diseases. The potential resides in the ability of these cells to develop into many different cell types in the body. In India, efforts are being made on several fronts to promote this area in an integrated way. The main features of the strategy are: explore the full potential of adult and embryonic stem cells (ESCs) through basic and translational research; generate patient specific human ESC lines; enhance creation of animal models for pre-clinical studies; virtual network of Centres; creation institutions; generation of well trained manpower; build partnership with large companies in path-breaking areas; promote closer interactions amongst basic scientists, clinical researchers and the industry. Newer initiatives include: establishment of a dedicated institute for stem cell science and regenerative medicine with its translational units; GMP and clean room facilities in medical schools; creation of a system for multi-centric clinical studies using autologous adult stem cells; national and international training courses for providing training to the students and the young scientists in the both embryonic and adult stem cells; and formulation of guidelines to conduct stem cell research in a responsible and ethically sensitive manner in the country. The core capacity must be nurtured and built to create the required critical mass to have impact.

A probabilistic approach to identify putative drug targets in biochemical networks.

PubMed

Murabito, Ettore; Smallbone, Kieran; Swinton, Jonathan; Westerhoff, Hans V; Steuer, Ralf

2011-06-06

Network-based drug design holds great promise in clinical research as a way to overcome the limitations of traditional approaches in the development of drugs with high efficacy and low toxicity. This novel strategy aims to study how a biochemical network as a whole, rather than its individual components, responds to specific perturbations in different physiological conditions. Proteins exerting little control over normal cells and larger control over altered cells may be considered as good candidates for drug targets. The application of network-based drug design would greatly benefit from using an explicit computational model describing the dynamics of the system under investigation. However, creating a fully characterized kinetic model is not an easy task, even for relatively small networks, as it is still significantly hampered by the lack of data about kinetic mechanisms and parameters values. Here, we propose a Monte Carlo approach to identify the differences between flux control profiles of a metabolic network in different physiological states, when information about the kinetics of the system is partially or totally missing. Based on experimentally accessible information on metabolic phenotypes, we develop a novel method to determine probabilistic differences in the flux control coefficients between the two observable phenotypes. Knowledge of how differences in flux control are distributed among the different enzymatic steps is exploited to identify points of fragility in one of the phenotypes. Using a prototypical cancerous phenotype as an example, we demonstrate how our approach can assist researchers in developing compounds with high efficacy and low toxicity. © 2010 The Royal Society

Accurate analytic solution of chemical master equations for gene regulation networks in a single cell

NASA Astrophysics Data System (ADS)

Huang, Guan-Rong; Saakian, David B.; Hu, Chin-Kun

2018-01-01

Studying gene regulation networks in a single cell is an important, interesting, and hot research topic of molecular biology. Such process can be described by chemical master equations (CMEs). We propose a Hamilton-Jacobi equation method with finite-size corrections to solve such CMEs accurately at the intermediate region of switching, where switching rate is comparable to fast protein production rate. We applied this approach to a model of self-regulating proteins [H. Ge et al., Phys. Rev. Lett. 114, 078101 (2015), 10.1103/PhysRevLett.114.078101] and found that as a parameter related to inducer concentration increases the probability of protein production changes from unimodal to bimodal, then to unimodal, consistent with phenotype switching observed in a single cell.

World Sounds through Universal Fellowship: Linking African Sounds through Collaborative Networking

ERIC Educational Resources Information Center

Klopper, Christopher

2005-01-01

The Pan African Society of Musical Arts Education (PASMAE) initiated the concept of Music Action Research Teams (MAT cells) at the grass-roots level for the collaborative sharing and learning of educators throughout Africa. The current number of 27 cells in Africa is a modest realization of the society's aims. However, it is strongly felt that if…

Social Skills Training for Students of Color with Disabilities through the Use of Social Networking

ERIC Educational Resources Information Center

Aldridge, Patricia R.; Jeffrey, Peter; Taylor, Gertrude; Barringer-Brown, Charletta H.

2017-01-01

The phenomenon of the use of cell phones as a primary source of communication among teens is having an impact on our society in profound ways. Children are creating and utilizing a different language and mechanism of communication--texting. The authors conducted research to determine if this cell phone phenomenon is as prevalent among students…

Patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks.

PubMed

Aguiar, Manuela A D; Dias, Ana Paula S; Ferreira, Flora

2017-01-01

We consider feed-forward and auto-regulation feed-forward neural (weighted) coupled cell networks. In feed-forward neural networks, cells are arranged in layers such that the cells of the first layer have empty input set and cells of each other layer receive only inputs from cells of the previous layer. An auto-regulation feed-forward neural coupled cell network is a feed-forward neural network where additionally some cells of the first layer have auto-regulation, that is, they have a self-loop. Given a network structure, a robust pattern of synchrony is a space defined in terms of equalities of cell coordinates that is flow-invariant for any coupled cell system (with additive input structure) associated with the network. In this paper, we describe the robust patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks. Regarding feed-forward neural networks, we show that only cells in the same layer can synchronize. On the other hand, in the presence of auto-regulation, we prove that cells in different layers can synchronize in a robust way and we give a characterization of the possible patterns of synchrony that can occur for auto-regulation feed-forward neural networks.

Using radar-derived parameters to forecast lightning cessation for nonisolated storms

NASA Astrophysics Data System (ADS)

Davey, Matthew J.; Fuelberg, Henry E.

2017-03-01

Lightning impacts operations at the Kennedy Space Center (KSC) and other outdoor venues leading to injuries, inconvenience, and detrimental economic impacts. This research focuses on cases of "nonisolated" lightning which we define as one cell whose flashes have ceased although it is still embedded in weak composite reflectivity (Z ≥ 15 dBZ) with another cell that is still producing flashes. The objective is to determine if any radar-derived parameters provide useful information about the occurrence of lightning cessation in remnant storms. The data set consists of 50 warm season (May-September) nonisolated storms near KSC during 2013. The research utilizes the National Lightning Detection Network, the second generation Lightning Detection and Ranging network, and polarized radar data. These data are merged and analyzed using the Warning Decision Support System-Integrated Information at 1 min intervals. Our approach only considers 62 parameters, most of which are related to the noninductive charging mechanism. They included the presence of graupel at various thermal altitudes, maximum reflectivity of the decaying storm at thermal altitudes, maximum connecting composite reflectivity between the decaying cell and active cell, minutes since the previous flash, and several others. Results showed that none of the parameters reliably indicated lightning cessation for even our restrictive definition of nonisolated storms. Additional research is needed before cessation can be determined operationally with the high degree of accuracy required for safety.

Invasive cancer cells and metastasis

NASA Astrophysics Data System (ADS)

Mierke, Claudia Tanja

2013-12-01

The physics of cancer is a relatively new emerging field of cancer research. In the last decade it has become a focus of biophysical research as well as becoming a novel focus for classical cancer research. This special section of Physical Biology focusing on invasive cancer cells and metastasis (physical oncology) will give greater insight into the different subfields where physical approaches are being applied to cancer research. This focus on the physical aspects of cancer is necessary because novel approaches in the field of genomics and proteomics have not altered the field of cancer research dramatically, due to the fact that few breakthroughs have been made. It is still not understood why some primary tumors metastasize and thus have a worse outcome compared to others that do not metastasize. As biophysicists, we and others suggest that the mechanical properties of the cancer cells, which possess the ability to transmigrate, are quite different compared to non-metastatic and non-invasive cancer cells. Furthermore, we hypothesize that these cancer cells undergo a selection process within the primary tumor that enables them to weaken their cell-cell adhesions and to alter their cell-matrix adhesions in order to be able to cross the outermost boundary of the primary tumor, as well as the surrounding basement membrane, and to invade the connective tissue. This prerequisite may also help the cancer cells to enter blood or lymph vessels, get transported with the vessel flow and form secondary tumors either within the vessel, directly on the endothelium, or in a different organ after crossing the endothelial lining a second time. This special section begins with a paper by Mark F Coughlin and Jeffrey J Fredberg on the changes in cytoskeletal dynamics and nonlinear rheology due to the metastatic capability of cancer cells from different cancer tissue types such as skin, bladder, prostate and kidney [1]. The hypothesis was that the metastatic outcome is impacted by the biophysical state of the primary tumor cell. To determine the cytoskeletal dynamics they chose magnetic twisting cytometry, where the spontaneous motion of surface bound marker beads was measured, which is a measure for the cytoskeletal remodeling dynamics. The group of Katarina Wolf measured the stiffness of the cell nucleus because it is the largest and stiffest organelle, which may hinder the migration of invasive tumor cells through dense connective tissue [2]. They combined atomic force confocal microscopy for measurement of bulk nuclear stiffness (the inverse of the compressibility) with simultaneous visualization of the cantilever-nucleus contact as well as monitoring of the cell's fate. The dynamics of tissue topology such as the mixing of compartments during cancer invasion and metastasis were theoretically analyzed by Lance L Munn [3]. In particular, he presented a mathematical model of tissue repair and tumor growth based on collective cell migration that simulates a wide range of tumor behaviors using correct tissue compartmentalization and connectivity. In the future, the topological analysis could be helpful for tumor diagnosis or monitoring tumor therapy. The group of Cynthia A Reinhart-King analyzed how the topological guidance of a 3D tumor cell migration at an interface of collagen densities affects cell motility [4]. In particular, they mimicked the heterogeneities in density of the tumor stroma by preparing gels with an interface of high and low density collagen gels and investigated how this affects cell motility. The author's review paper details the effect of focal adhesion proteins such as focal adhesion kinase (FAK) on cell motility and how this effect is driven by mechanical alterations of cells expressing FAK compared to cells with FAK knock-out [5]. In particular, it focused on mechanical properties regulated by FAK in comparison to the mechano-regulating protein vinculin. This article highlights that both focal adhesion proteins, vinculin and FAK synergize their functions to regulate the mechanical properties of cells such as stiffness and contractile forces. Finally, the knowledge of the mechanical properties of invasive and non-invasive cells could provide a source for future drug developments to inhibit formation of metastases. This special section also includes two papers from the group of Martin Herrmann, a research paper and a review paper. The research paper by Janko et al deals with the cooperative binding of Annexin A5 to phosphatidylserines on apoptotic cell membranes [6]. This could not alone serve as an 'eat me' signal for macrophages as healthy cells also express Annexin A5 on their cell surface. The authors suggest that the cooperative binding is altered and subsequently the fluidity of Annexin A5 on the membrane. Together this may serve as a signal for phagocytic cells to eat apoptotic cells and leave healthy ones untouched. The paper by Biermann et al reviews the role of biophysical signals in the clearance of apoptotic cells [7]. In addition to the acto-myosin cytoskeleton, the keratin network seems to play a role in cancer research. The paper from the Beil and the Marti group demonstrates that microrheology is a valuable tool to determine the viscoelastic properties of polymer networks such as the keratin network in cells and an arbitrary in vitro network [8]. They describe how the topology of the keratin network affects the overall mechanical behavior of cells. It seems that the field of physical oncology will continue to grow in the future and more research will address the mechanical properties of cancer cells and whole tissues. Biophysical methods will need to be further improved and adapted to the needs of cancer research. References [1] Coughlin M F and Fredberg J J 2013 Phys. Biol. 10 065001 [2] Krause M, te Riet J and Wolf K 2013 Phys. Biol. 10 065002 [3] Munn L L 2013 Phys. Biol. 10 065003 [4] Bordeleau F, Tang L N and Reinhart-King C A 2013 Phys. Biol. 10 065004 [5] Mierke C T 2013 Phys. Biol. 10 065005 [6] Janko C, Jeremic I, Biermann M, Chaurio R, Schorn C, Muñoz L E and Herrmann M 2013 Phys. Biol. 10 065006 [7] Biermann M, Maueröder C, Brauner J M, Chaurio R, Janko C, Herrmann M and Muñoz L E 2013 Phys. Biol. 10 065007 [8] Paust T, Paschke S, Beil M and Marti O 2013 Phys. Biol. 10 065008

Rheology of Soft Materials

NASA Astrophysics Data System (ADS)

Chen, Daniel T. N.; Wen, Qi; Janmey, Paul A.; Crocker, John C.; Yodh, Arjun G.

2010-04-01

Research on soft materials, including colloidal suspensions, glasses, pastes, emulsions, foams, polymer networks, liquid crystals, granular materials, and cells, has captured the interest of scientists and engineers in fields ranging from physics and chemical engineering to materials science and cell biology. Recent advances in rheological methods to probe mechanical responses of these complex media have been instrumental for producing new understanding of soft matter and for generating novel technological applications. This review surveys these technical developments and current work in the field, with partial aim to illustrate open questions for future research.

Stigmergy

PubMed Central

Gloag, Erin S; Javed, Muhammad A; Wang, Huabin; Gee, Michelle L; Wade, Scott A; Turnbull, Lynne; Whitchurch, Cynthia B

2013-01-01

Bacterial biofilms are complex multicellular communities that are often associated with the emergence of large-scale patterns across the biofilm. How bacteria self-organize to form these structured communities is an area of active research. We have recently determined that the emergence of an intricate network of trails that forms during the twitching motility mediated expansion of Pseudomonas aeruginosa biofilms is attributed to an interconnected furrow system that is forged in the solidified nutrient media by aggregates of cells as they migrate across the media surface. This network acts as a means for self-organization of collective behavior during biofilm expansion as the cells following these vanguard aggregates were preferentially confined within the furrow network resulting in the formation of an intricate network of trails of cells. Here we further explore the process by which the intricate network of trails emerges. We have determined that the formation of the intricate network of furrows is associated with significant remodeling of the sub-stratum underlying the biofilm. The concept of stigmergy has been used to describe a variety of self-organization processes observed in higher organisms and abiotic systems that involve indirect communication via persistent cues in the environment left by individuals that influence the behavior of other individuals of the group at a later point in time. We propose that the concept of stigmergy can also be applied to describe self-organization of bacterial biofilms and can be included in the repertoire of systems used by bacteria to coordinate complex multicellular behaviors. PMID:24753789

Contextualization of drug-mediator relations using evidence networks.

PubMed

Tran, Hai Joey; Speyer, Gil; Kiefer, Jeff; Kim, Seungchan

2017-05-31

Genomic analysis of drug response can provide unique insights into therapies that can be used to match the "right drug to the right patient." However, the process of discovering such therapeutic insights using genomic data is not straightforward and represents an area of active investigation. EDDY (Evaluation of Differential DependencY), a statistical test to detect differential statistical dependencies, is one method that leverages genomic data to identify differential genetic dependencies. EDDY has been used in conjunction with the Cancer Therapeutics Response Portal (CTRP), a dataset with drug-response measurements for more than 400 small molecules, and RNAseq data of cell lines in the Cancer Cell Line Encyclopedia (CCLE) to find potential drug-mediator pairs. Mediators were identified as genes that showed significant change in genetic statistical dependencies within annotated pathways between drug sensitive and drug non-sensitive cell lines, and the results are presented as a public web-portal (EDDY-CTRP). However, the interpretability of drug-mediator pairs currently hinders further exploration of these potentially valuable results. In this study, we address this challenge by constructing evidence networks built with protein and drug interactions from the STITCH and STRING interaction databases. STITCH and STRING are sister databases that catalog known and predicted drug-protein interactions and protein-protein interactions, respectively. Using these two databases, we have developed a method to construct evidence networks to "explain" the relation between a drug and a mediator.  RESULTS: We applied this approach to drug-mediator relations discovered in EDDY-CTRP analysis and identified evidence networks for ~70% of drug-mediator pairs where most mediators were not known direct targets for the drug. Constructed evidence networks enable researchers to contextualize the drug-mediator pair with current research and knowledge. Using evidence networks, we were able to improve the interpretability of the EDDY-CTRP results by linking the drugs and mediators with genes associated with both the drug and the mediator. We anticipate that these evidence networks will help inform EDDY-CTRP results and enhance the generation of important insights to drug sensitivity that will lead to improved precision medicine applications.

How to train your microbe: methods for dynamically characterizing gene networks

PubMed Central

Castillo-Hair, Sebastian M.; Igoshin, Oleg A.; Tabor, Jeffrey J.

2015-01-01

Gene networks regulate biological processes dynamically. However, researchers have largely relied upon static perturbations, such as growth media variations and gene knockouts, to elucidate gene network structure and function. Thus, much of the regulation on the path from DNA to phenotype remains poorly understood. Recent studies have utilized improved genetic tools, hardware, and computational control strategies to generate precise temporal perturbations outside and inside of live cells. These experiments have, in turn, provided new insights into the organizing principles of biology. Here, we introduce the major classes of dynamical perturbations that can be used to study gene networks, and discuss technologies available for creating them in a wide range of microbial pathways. PMID:25677419

Nanostructured cavity devices for extracellular stimulation of HL-1 cells

NASA Astrophysics Data System (ADS)

Czeschik, Anna; Rinklin, Philipp; Derra, Ulrike; Ullmann, Sabrina; Holik, Peter; Steltenkamp, Siegfried; Offenhäusser, Andreas; Wolfrum, Bernhard

2015-05-01

Microelectrode arrays (MEAs) are state-of-the-art devices for extracellular recording and stimulation on biological tissue. Furthermore, they are a relevant tool for the development of biomedical applications like retina, cochlear and motor prostheses, cardiac pacemakers and drug screening. Hence, research on functional cell-sensor interfaces, as well as the development of new surface structures and modifications for improved electrode characteristics, is a vivid and well established field. However, combining single-cell resolution with sufficient signal coupling remains challenging due to poor cell-electrode sealing. Furthermore, electrodes with diameters below 20 µm often suffer from a high electrical impedance affecting the noise during voltage recordings. In this study, we report on a nanocavity sensor array for voltage-controlled stimulation and extracellular action potential recordings on cellular networks. Nanocavity devices combine the advantages of low-impedance electrodes with small cell-chip interfaces, preserving a high spatial resolution for recording and stimulation. A reservoir between opening aperture and electrode is provided, allowing the cell to access the structure for a tight cell-sensor sealing. We present the well-controlled fabrication process and the effect of cavity formation and electrode patterning on the sensor's impedance. Further, we demonstrate reliable voltage-controlled stimulation using nanostructured cavity devices by capturing the pacemaker of an HL-1 cell network.Microelectrode arrays (MEAs) are state-of-the-art devices for extracellular recording and stimulation on biological tissue. Furthermore, they are a relevant tool for the development of biomedical applications like retina, cochlear and motor prostheses, cardiac pacemakers and drug screening. Hence, research on functional cell-sensor interfaces, as well as the development of new surface structures and modifications for improved electrode characteristics, is a vivid and well established field. However, combining single-cell resolution with sufficient signal coupling remains challenging due to poor cell-electrode sealing. Furthermore, electrodes with diameters below 20 µm often suffer from a high electrical impedance affecting the noise during voltage recordings. In this study, we report on a nanocavity sensor array for voltage-controlled stimulation and extracellular action potential recordings on cellular networks. Nanocavity devices combine the advantages of low-impedance electrodes with small cell-chip interfaces, preserving a high spatial resolution for recording and stimulation. A reservoir between opening aperture and electrode is provided, allowing the cell to access the structure for a tight cell-sensor sealing. We present the well-controlled fabrication process and the effect of cavity formation and electrode patterning on the sensor's impedance. Further, we demonstrate reliable voltage-controlled stimulation using nanostructured cavity devices by capturing the pacemaker of an HL-1 cell network. Electronic supplementary information (ESI) available: Comparison of non-filtered and Savitzky-Golay filtered action potential recordings, electrical signals and corresponding optical signals. See DOI: 10.1039/c5nr01690h

Tendon Functional Extracellular Matrix

PubMed Central

Screen, H.R.C.; Birk, D.E.; Kadler, K.E.; Ramirez, F; Young, M.F.

2015-01-01

This article is one of a series, summarising views expressed at the Orthopaedic Research Society New Frontiers in Tendon Research Conference. This particular article reviews the three workshops held under the “Functional Extracellular Matrix” stream. The workshops focused on the roles of the tendon extracellular matrix, such as performing the mechanical functions of tendon, creating the local cell environment and providing cellular cues. Tendon is a complex network of matrix and cells, and its biological functions are influenced by widely-varying extrinsic and intrinsic factors such as age, nutrition, exercise levels and biomechanics. Consequently, tendon adapts dynamically during development, ageing and injury. The workshop discussions identified research directions associated with understanding cell-matrix interactions to be of prime importance for developing novel strategies to target tendon healing or repair. PMID:25640030

Active DNA gels

NASA Astrophysics Data System (ADS)

Saleh, Omar A.; Fygenson, Deborah K.; Bertrand, Olivier J. N.; Park, Chang Young

2013-02-01

Research into the mechanics and fluctuations of living cells has revealed the key role played by the cytoskeleton, a gel of stiff filaments driven out of equilibrium by force-generating motor proteins. Inspired by the extraordinary mechanical functions that the cytoskeleton imparts to the cell, we sought to create an artificial gel with similar characteristics. We identified DNA, and DNA-based motor proteins, as functional counterparts to the constituents of the cytoskeleton. We used DNA selfassembly to create a gel, and characterized its fluctuations and mechanics both before and after activation by the motor. We found that certain aspects of the DNA gel quantitatively match those of cytoskeletal networks, indicating the universal features of motor-driven, non-equilibrium networks.

A toolbox for discrete modelling of cell signalling dynamics.

PubMed

Paterson, Yasmin Z; Shorthouse, David; Pleijzier, Markus W; Piterman, Nir; Bendtsen, Claus; Hall, Benjamin A; Fisher, Jasmin

2018-06-18

In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data.

Rapid cell-free forward engineering of novel genetic ring oscillators

PubMed Central

Niederholtmeyer, Henrike; Sun, Zachary Z; Hori, Yutaka; Yeung, Enoch; Verpoorte, Amanda; Murray, Richard M; Maerkl, Sebastian J

2015-01-01

While complex dynamic biological networks control gene expression in all living organisms, the forward engineering of comparable synthetic networks remains challenging. The current paradigm of characterizing synthetic networks in cells results in lengthy design-build-test cycles, minimal data collection, and poor quantitative characterization. Cell-free systems are appealing alternative environments, but it remains questionable whether biological networks behave similarly in cell-free systems and in cells. We characterized in a cell-free system the ‘repressilator’, a three-node synthetic oscillator. We then engineered novel three, four, and five-gene ring architectures, from characterization of circuit components to rapid analysis of complete networks. When implemented in cells, our novel 3-node networks produced population-wide oscillations and 95% of 5-node oscillator cells oscillated for up to 72 hr. Oscillation periods in cells matched the cell-free system results for all networks tested. An alternate forward engineering paradigm using cell-free systems can thus accurately capture cellular behavior. DOI: http://dx.doi.org/10.7554/eLife.09771.001 PMID:26430766

Cyberbullying and Academic Achievement: Research into the Rates of Incidence, Knowledge of Consequences, and Behavioral Patterns of Cyberbullying

ERIC Educational Resources Information Center

Mitchell, Melissa Sue

2011-01-01

Cyberbullying takes place through the information technology that students access every day: cell phones, text messages, email, Internet messaging, social networks, pictures, and video clips. With the world paying more attention to this new form of bullying, scholars have been researching the topic in an attempt to learn more about this…

Mechanical Cell-Cell Communication in Fibrous Networks: The Importance of Network Geometry.

PubMed

Humphries, D L; Grogan, J A; Gaffney, E A

2017-03-01

Cells contracting in extracellular matrix (ECM) can transmit stress over long distances, communicating their position and orientation to cells many tens of micrometres away. Such phenomena are not observed when cells are seeded on substrates with linear elastic properties, such as polyacrylamide (PA) gel. The ability for fibrous substrates to support far reaching stress and strain fields has implications for many physiological processes, while the mechanical properties of ECM are central to several pathological processes, including tumour invasion and fibrosis. Theoretical models have investigated the properties of ECM in a variety of network geometries. However, the effects of network architecture on mechanical cell-cell communication have received little attention. This work investigates the effects of geometry on network mechanics, and thus the ability for cells to communicate mechanically through different networks. Cell-derived displacement fields are quantified for various network geometries while controlling for network topology, cross-link density and micromechanical properties. We find that the heterogeneity of response, fibre alignment, and substrate displacement fields are sensitive to network choice. Further, we show that certain geometries support mechanical communication over longer distances than others. As such, we predict that the choice of network geometry is important in fundamental modelling of cell-cell interactions in fibrous substrates, as well as in experimental settings, where mechanical signalling at the cellular scale plays an important role. This work thus informs the construction of theoretical models for substrate mechanics and experimental explorations of mechanical cell-cell communication.

50 years of Arabidopsis research: highlights and future directions

DOE PAGES

Provart, Nicholas J.; Alonso, Jose; Assmann, Sarah M.; ...

2015-10-14

The year 2014 marked the 25 th International Conference on Arabidopsis Research. In the 50 yr since the first International Conference on Arabidopsis Research, held in 1965 in Göttingen, Germany, > 54 000 papers that mention Arabidopsis thaliana in the title, abstract or keywords have been published. In this paper, we present herein a citational network analysis of these papers, and touch on some of the important discoveries in plant biology that have been made in this powerful model system, and highlight how these discoveries have then had an impact in crop species. We also look to the future, highlightingmore » some outstanding questions that can be readily addressed in Arabidopsis. Topics that are discussed include Arabidopsis reverse genetic resources, stock centers, databases and online tools, cell biology, development, hormones, plant immunity, signaling in response to abiotic stress, transporters, biosynthesis of cells walls and macromolecules such as starch and lipids, epigenetics and epigenomics, genome-wide association studies and natural variation, gene regulatory networks, modeling and systems biology, and synthetic biology.« less

50 years of Arabidopsis research: highlights and future directions

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

Provart, Nicholas J.; Alonso, Jose; Assmann, Sarah M.

The year 2014 marked the 25 th International Conference on Arabidopsis Research. In the 50 yr since the first International Conference on Arabidopsis Research, held in 1965 in Göttingen, Germany, > 54 000 papers that mention Arabidopsis thaliana in the title, abstract or keywords have been published. In this paper, we present herein a citational network analysis of these papers, and touch on some of the important discoveries in plant biology that have been made in this powerful model system, and highlight how these discoveries have then had an impact in crop species. We also look to the future, highlightingmore » some outstanding questions that can be readily addressed in Arabidopsis. Topics that are discussed include Arabidopsis reverse genetic resources, stock centers, databases and online tools, cell biology, development, hormones, plant immunity, signaling in response to abiotic stress, transporters, biosynthesis of cells walls and macromolecules such as starch and lipids, epigenetics and epigenomics, genome-wide association studies and natural variation, gene regulatory networks, modeling and systems biology, and synthetic biology.« less

Microenvironment Influences Interaction of Signaling Molecules | Center for Cancer Research

Cancer.gov

Tumor progression depends not only on events that occur within cancer cells but also on the interaction of cancer cells with their environment, which can regulate tumor growth and metastasis and modulate the formation of new blood vessels to nourish the tumor. All cells communicate with other cells around them, including endothelial cells (the cells that make up blood vessels). They also interact with the extracellular matrix (ECM), a network of sugars and proteins that supports cells. Communication between neighboring cells and molecules often occurs through interaction among and between molecules on the cell surface and molecules of the ECM. Defining these interactions should facilitate the development of novel approaches to limit tumor progression.

Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)

NASA Technical Reports Server (NTRS)

Niewoehner, Kevin R.; Carter, John (Technical Monitor)

2001-01-01

The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.

Cell phone use among homeless youth: potential for new health interventions and research.

PubMed

Rice, Eric; Lee, Alex; Taitt, Sean

2011-12-01

Cell phone use has become nearly ubiquitous among adolescents in the United States. Despite the potential for cell phones to facilitate intervention, research, and care for homeless youth, no data exists to date on cell phone use among this population. In 2009, a survey of cell phone use was conducted among a non-probability sample of 169 homeless youth in Los Angeles, CA. Levels of ownership and use, instrumental uses (connecting to case workers, employers) and patterns of connecting to various network types were assessed (family, home-based peers, street-based peers). Differences in socio-demographic characteristics and cell phone ownership were assessed via t test and chi-square statistics. Sixty-two percent of homeless youth own a cell phone; 40% have a working phone. Seventeen percent used their phone to call a case manager, 36% to call either a potential or current employer. Fifty-one percent of youth connected with home-based peers on the phone and 41% connected to parents. Cell phones present new opportunities for intervention research, connecting homeless youth to family and home-based peers who can be sources of social support in times of need. Moreover, cell phones provide researchers and providers with new avenues to maintain connections with these highly transient youth.

From network structure to network reorganization: implications for adult neurogenesis

NASA Astrophysics Data System (ADS)

Schneider-Mizell, Casey M.; Parent, Jack M.; Ben-Jacob, Eshel; Zochowski, Michal R.; Sander, Leonard M.

2010-12-01

Networks can be dynamical systems that undergo functional and structural reorganization. One example of such a process is adult hippocampal neurogenesis, in which new cells are continuously born and incorporate into the existing network of the dentate gyrus region of the hippocampus. Many of these introduced cells mature and become indistinguishable from established neurons, joining the existing network. Activity in the network environment is known to promote birth, survival and incorporation of new cells. However, after epileptogenic injury, changes to the connectivity structure around the neurogenic niche are known to correlate with aberrant neurogenesis. The possible role of network-level changes in the development of epilepsy is not well understood. In this paper, we use a computational model to investigate how the structural and functional outcomes of network reorganization, driven by addition of new cells during neurogenesis, depend on the original network structure. We find that there is a stable network topology that allows the network to incorporate new neurons in a manner that enhances activity of the persistently active region, but maintains global network properties. In networks having other connectivity structures, new cells can greatly alter the distribution of firing activity and destroy the initial activity patterns. We thus find that new cells are able to provide focused enhancement of network only for small-world networks with sufficient inhibition. Network-level deviations from this topology, such as those caused by epileptogenic injury, can set the network down a path that develops toward pathological dynamics and aberrant structural integration of new cells.

Holographically generated structured illumination for cell stimulation in optogenetics

NASA Astrophysics Data System (ADS)

Schmieder, Felix; Büttner, Lars; Czarske, Jürgen; Torres, Maria Leilani; Heisterkamp, Alexander; Klapper, Simon; Busskamp, Volker

2017-06-01

In Optogenetics, cells, e.g. neurons or cardiac cells, are genetically altered to produce for example the lightsensitive protein Channelrhodopsin-2. Illuminating these cells induces action potentials or contractions and therefore allows to control electrical activity. Thus, light-induced cell stimulation can be used to gain insight to various biological processes. Many optogenetics studies, however, use only full field illumination and thus gain no local information about their specimen. But using modern spatial light modulators (SLM) in conjunction with computer-generated holograms (CGH), cells may be stimulated locally, thus enabling the research of the foundations of cell networks and cell communications. In our contribution, we present a digital holographic system for the patterned, spatially resolved stimulation of cell networks. We employ a fast ferroelectric liquid crystal on silicon SLM to display CGH at up to 1.7 kHz. With an effective working distance of 33 mm, we achieve a focus of 10 μm at a positioning accuracy of the individual foci of about 8 μm. We utilized our setup for the optogenetic stimulation of clusters of cardiac cells derived from induced pluripotent stem cells and were able to observe contractions correlated to both temporal frequency and spatial power distribution of the light incident on the cell clusters.

Network embedding-based representation learning for single cell RNA-seq data.

PubMed

Li, Xiangyu; Chen, Weizheng; Chen, Yang; Zhang, Xuegong; Gu, Jin; Zhang, Michael Q

2017-11-02

Single cell RNA-seq (scRNA-seq) techniques can reveal valuable insights of cell-to-cell heterogeneities. Projection of high-dimensional data into a low-dimensional subspace is a powerful strategy in general for mining such big data. However, scRNA-seq suffers from higher noise and lower coverage than traditional bulk RNA-seq, hence bringing in new computational difficulties. One major challenge is how to deal with the frequent drop-out events. The events, usually caused by the stochastic burst effect in gene transcription and the technical failure of RNA transcript capture, often render traditional dimension reduction methods work inefficiently. To overcome this problem, we have developed a novel Single Cell Representation Learning (SCRL) method based on network embedding. This method can efficiently implement data-driven non-linear projection and incorporate prior biological knowledge (such as pathway information) to learn more meaningful low-dimensional representations for both cells and genes. Benchmark results show that SCRL outperforms other dimensional reduction methods on several recent scRNA-seq datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Cell-microenvironment interactions and architectures in microvascular systems

PubMed Central

Bersini, Simone; Yazdi, Iman K.; Talò, Giuseppe; Shin, Su Ryon; Moretti, Matteo; Khademhosseini, Ali

2016-01-01

In the past decade, significant advances have been made in the design and optimization of novel biomaterials and microfabrication techniques to generate vascularized tissues. Novel microfluidic systems have facilitated the development and optimization of in vitro models for exploring the complex pathophysiological phenomena that occur inside a microvascular environment. To date, most of these models have focused on engineering of increasingly complex systems, rather than analyzing the molecular and cellular mechanisms that drive microvascular network morphogenesis and remodeling. In fact, mutual interactions among endothelial cells (ECs), supporting mural cells and organ-specific cells, as well as between ECs and the extracellular matrix, are key driving forces for vascularization. This review focuses on the integration of materials science, microengineering and vascular biology for the development of in vitro microvascular systems. Various approaches currently being applied to study cell-cell/cell-matrix interactions, as well as biochemical/biophysical cues promoting vascularization and their impact on microvascular network formation, will be identified and discussed. Finally, this review will explore in vitro applications of microvascular systems, in vivo integration of transplanted vascularized tissues, and the important challenges for vascularization and controlling the microcirculatory system within the engineered tissues, especially for microfabrication approaches. It is likely that existing models and more complex models will further our understanding of the key elements of vascular network growth, stabilization and remodeling to translate basic research principles into functional, vascularized tissue constructs for regenerative medicine applications, drug screening and disease models. PMID:27417066

Cell-microenvironment interactions and architectures in microvascular systems.

PubMed

Bersini, Simone; Yazdi, Iman K; Talò, Giuseppe; Shin, Su Ryon; Moretti, Matteo; Khademhosseini, Ali

2016-11-01

In the past decade, significant advances have been made in the design and optimization of novel biomaterials and microfabrication techniques to generate vascularized tissues. Novel microfluidic systems have facilitated the development and optimization of in vitro models for exploring the complex pathophysiological phenomena that occur inside a microvascular environment. To date, most of these models have focused on engineering of increasingly complex systems, rather than analyzing the molecular and cellular mechanisms that drive microvascular network morphogenesis and remodeling. In fact, mutual interactions among endothelial cells (ECs), supporting mural cells and organ-specific cells, as well as between ECs and the extracellular matrix, are key driving forces for vascularization. This review focuses on the integration of materials science, microengineering and vascular biology for the development of in vitro microvascular systems. Various approaches currently being applied to study cell-cell/cell-matrix interactions, as well as biochemical/biophysical cues promoting vascularization and their impact on microvascular network formation, will be identified and discussed. Finally, this review will explore in vitro applications of microvascular systems, in vivo integration of transplanted vascularized tissues, and the important challenges for vascularization and controlling the microcirculatory system within the engineered tissues, especially for microfabrication approaches. It is likely that existing models and more complex models will further our understanding of the key elements of vascular network growth, stabilization and remodeling to translate basic research principles into functional, vascularized tissue constructs for regenerative medicine applications, drug screening and disease models. Copyright © 2016 Elsevier Inc. All rights reserved.

Columella cells revisited: novel structures, novel properties, and a novel gravisensing model

NASA Technical Reports Server (NTRS)

Staehelin, L. A.; Zheng, H. Q.; Yoder, T. L.; Smith, J. D.; Todd, P.

2000-01-01

A hundred years of research has not produced a clear understanding of the mechanism that transduces the energy associated with the sedimentation of starch-filled amyloplast statoliths in root cap columella cells into a growth response. Most models postulate that the statoliths interact with microfilaments (MF) to transmit signals to the plasma membrane (or ER), or that sedimentation onto these organelles produces the signals. However, no direct evidence for statolith-MF links has been reported, and no asymmetric structures of columella cells have been identified that might explain how a root turned by 90 degrees knows which side is up. To address these and other questions, we have (1) quantitatively examined the effects of microgravity on the size, number, and spatial distribution of statoliths; (2) re-evaluated the ultrastructure of columella cells in high-pressure frozen/freeze-substituted roots; and (3) followed the sedimentation dynamics of statolith movements in reoriented root tips. The findings have led to the formulation of a new model for the gravity-sensing apparatus of roots, which envisages the cytoplasm pervaded by an actin-based cytoskeletal network. This network is denser in the ER-devoid central region of the cell than in the ER-rich cell cortex and is coupled to receptors in the plasma membrane. Statolith sedimentation is postulated to disrupt the network and its links to receptors in some regions of the cell cortex, while allowing them to reform in other regions and thereby produce a directional signal.

The use of large scale datasets for understanding traffic network state.

DOT National Transportation Integrated Search

2013-09-01

The goal of this proposal is to develop novel modeling techniques to infer individual activity patterns from the large scale cell phone : datasets and taxi data from NYC. As such this research offers a paradigm shift from traditional transportation m...

Rare kidney tumor provides insight on metabolic changes

Cancer.gov

Researchers in The Cancer Genome Atlas (TCGA) Network have uncovered a number of new findings about the biology and development of a rare form of kidney cancer. They found that the disease – chromophobe renal cell carcinoma – stems in part from alteratio

The EuroBioBank Network: 10 years of hands-on experience of collaborative, transnational biobanking for rare diseases

PubMed Central

Mora, Marina; Angelini, Corrado; Bignami, Fabrizia; Bodin, Anne-Mary; Crimi, Marco; Di Donato, Jeanne- Hélène; Felice, Alex; Jaeger, Cécile; Karcagi, Veronika; LeCam, Yann; Lynn, Stephen; Meznaric, Marija; Moggio, Maurizio; Monaco, Lucia; Politano, Luisa; de la Paz, Manuel Posada; Saker, Safaa; Schneiderat, Peter; Ensini, Monica; Garavaglia, Barbara; Gurwitz, David; Johnson, Diana; Muntoni, Francesco; Puymirat, Jack; Reza, Mojgan; Voit, Thomas; Baldo, Chiara; Bricarelli, Franca Dagna; Goldwurm, Stefano; Merla, Giuseppe; Pegoraro, Elena; Renieri, Alessandra; Zatloukal, Kurt; Filocamo, Mirella; Lochmüller, Hanns

2015-01-01

The EuroBioBank (EBB) network (www.eurobiobank.org) is the first operating network of biobanks in Europe to provide human DNA, cell and tissue samples as a service to the scientific community conducting research on rare diseases (RDs). The EBB was established in 2001 to facilitate access to RD biospecimens and associated data; it obtained funding from the European Commission in 2002 (5th framework programme) and started operation in 2003. The set-up phase, during the EC funding period 2003–2006, established the basis for running the network; the following consolidation phase has seen the growth of the network through the joining of new partners, better network cohesion, improved coordination of activities, and the development of a quality-control system. During this phase the network participated in the EC-funded TREAT-NMD programme and was involved in planning of the European Biobanking and Biomolecular Resources Research Infrastructure. Recently, EBB became a partner of RD-Connect, an FP7 EU programme aimed at linking RD biobanks, registries, and bioinformatics data. Within RD-Connect, EBB contributes expertise, promotes high professional standards, and best practices in RD biobanking, is implementing integration with RD patient registries and ‘omics' data, thus challenging the fragmentation of international cooperation on the field. PMID:25537360

Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data.

PubMed

Chen, Shuonan; Mar, Jessica C

2018-06-19

A fundamental fact in biology states that genes do not operate in isolation, and yet, methods that infer regulatory networks for single cell gene expression data have been slow to emerge. With single cell sequencing methods now becoming accessible, general network inference algorithms that were initially developed for data collected from bulk samples may not be suitable for single cells. Meanwhile, although methods that are specific for single cell data are now emerging, whether they have improved performance over general methods is unknown. In this study, we evaluate the applicability of five general methods and three single cell methods for inferring gene regulatory networks from both experimental single cell gene expression data and in silico simulated data. Standard evaluation metrics using ROC curves and Precision-Recall curves against reference sets sourced from the literature demonstrated that most of the methods performed poorly when they were applied to either experimental single cell data, or simulated single cell data, which demonstrates their lack of performance for this task. Using default settings, network methods were applied to the same datasets. Comparisons of the learned networks highlighted the uniqueness of some predicted edges for each method. The fact that different methods infer networks that vary substantially reflects the underlying mathematical rationale and assumptions that distinguish network methods from each other. This study provides a comprehensive evaluation of network modeling algorithms applied to experimental single cell gene expression data and in silico simulated datasets where the network structure is known. Comparisons demonstrate that most of these assessed network methods are not able to predict network structures from single cell expression data accurately, even if they are specifically developed for single cell methods. Also, single cell methods, which usually depend on more elaborative algorithms, in general have less similarity to each other in the sets of edges detected. The results from this study emphasize the importance for developing more accurate optimized network modeling methods that are compatible for single cell data. Newly-developed single cell methods may uniquely capture particular features of potential gene-gene relationships, and caution should be taken when we interpret these results.

Endothelial network formed with human dermal microvascular endothelial cells in autologous multicellular skin substitutes.

PubMed

Ponec, Maria; El Ghalbzouri, Abdoelwaheb; Dijkman, Remco; Kempenaar, Johanna; van der Pluijm, Gabri; Koolwijk, Pieter

2004-01-01

A human skin equivalent from a single skin biopsy harboring keratinocytes and melanocytes in the epidermal compartment, and fibroblasts and microvascular dermal endothelial cells in the dermal compartment was developed. The results of the study revealed that the nature of the extracellular matrix of the dermal compartments plays an important role in establishment of endothelial network in vitro. With rat-tail type I collagen matrices only lateral but not vertical expansion of endothelial networks was observed. In contrast, the presence of extracellular matrix of entirely human origin facilitated proper spatial organization of the endothelial network. Namely, when human dermal fibroblasts and microvascular endothelial cells were seeded on the bottom of an inert filter and subsequently epidermal cells were seeded on top of it, fibroblasts produced extracellular matrix throughout which numerous branched tubes were spreading three-dimensionally. Fibroblasts also facilitated the formation of basement membrane at the epidermal/matrix interface. Under all culture conditions, fully differentiated epidermis was formed with numerous melanocytes present in the basal epidermal cell layer. The results of the competitive RT-PCR revealed that both keratinocytes and fibroblasts expressed VEGF-A, -B, -C, aFGF and bFGF mRNA, whereas fibroblasts also expressed VEGF-D mRNA. At protein level, keratinocytes produced 10 times higher amounts of VEGF-A than fibroblasts did. The generation of multicellular skin equivalent from a single human skin biopsy will stimulate further developments for its application in the treatment of full-thickness skin defects. The potential development of biodegradable, biocompatible material suitable for these purposes is a great challenge for future research.

An analysis of the gene interaction networks identifying the role of PARP1 in metastasis of non-small cell lung cancer.

PubMed

Chen, Kai; Li, Yajie; Xu, Hui; Zhang, Chunfeng; Li, Zhiqiang; Wang, Wei; Wang, Baofeng

2017-10-20

Though there were many researches about the effects of cancer cells on non-small cell lung cancer (NSCLC) currently, it has been rarely reported completed oncogene and its mechanism in tumors by far. Here, we used biological methods with known oncogene of NSCLC to find new oncogene and explore its functionary mechanism in NSCLC. The study firstly built NSCLC genetic interaction network based on bioinformatics methods and then combined shortest path algorithm with significance test to confirmed core genes that were closely involved with given genes; real-time qPCR was conducted to detect expression levels between patients with NSCLC and normal people; additionally, detection of PARP1's role in migration and invasion was performed by trans-well assays and wound-healing. Through gene interaction network, it was found that, core genes like PARP1, EGFR and ALK had a direct interaction. TCGA database showed that PARP1 presented strong expression in NSCLC and the expression level of metastatic NSCLC was significantly higher than that of non-metastatic NSCLC. Cell migration of NSCLC in accordance to the scratch test was suppressed by PARP1 silence but stimulated noticeably by PARP1 overexpression. According to Kaplan-meier survival curve, the higher PARP1 expression, the poorer patient survival rate and prognosis. Thus, PARP1 expression had a negative correction with patient survival rate and prognosis. New oncogene PARP1 was found from known NSCLC oncogene in terms of gene interaction network, demonstrating PARP1's impact on NSCLC cell migration.

The 150 most important questions in cancer research and clinical oncology series: questions 50-56.

PubMed

2017-08-29

Since the beginning of 2017, Chinese Journal of Cancer has published a series of important questions in cancer research and clinical oncology, which sparkle diverse thoughts, interesting communications, and potential collaborations among researchers all over the world. In this article, seven more questions are presented as followed. Question 50. When tumor cells spread from primary site to distant sites, are they required to be "trained" or "armed" in the bone marrow niche prior to colonizing soft tissues? Question 51. Are there tipping points during cancer progression which can be identified for manipulation? Question 52. Can we replace molecular biomarkers by network biomarkers? Question 53. Are conventional inhibitors of key cellular processes such as cell proliferation and differentiation more effective than targeted chemotherapeutics that antagonize the downstream cell signaling network via cell-surface receptors such as epidermal growth factor receptor (EGFR), vascular endothelial growth factor receptor (VEGFR) and c-Met, or intracellular receptors such as androgen receptor (AR) and estrogen receptor (ER), by drugs like erlotinib, sunitinib and cabozantinib, or enzalutamide and tomoxifen? Question 54. How can we robustly identify the candidate causal event of somatic genome alteration (SGA) by using computational approach? Question 55. How can we systematically reveal the immune evasion mechanism exploited by each tumor and utilize such information to guide targeted therapy to restore immune sensitivity? Question 56. Can the nasopharyngeal carcinoma (NPC) patients with sarcomatoid carcinoma (SC) subtype benefit from more specific targeted therapy?

Targeting cancer stem-like cells in glioblastoma and colorectal cancer through metabolic pathways.

PubMed

Kahlert, U D; Mooney, S M; Natsumeda, M; Steiger, H-J; Maciaczyk, J

2017-01-01

Cancer stem-like cells (CSCs) are thought to be the main cause of tumor occurrence, progression and therapeutic resistance. Strong research efforts in the last decade have led to the development of several tailored approaches to target CSCs with some very promising clinical trials underway; however, until now no anti-CSC therapy has been approved for clinical use. Given the recent improvement in our understanding of how onco-proteins can manipulate cellular metabolic networks to promote tumorigenesis, cancer metabolism research may well lead to innovative strategies to identify novel regulators and downstream mediators of CSC maintenance. Interfering with distinct stages of CSC-associated metabolics may elucidate novel, more efficient strategies to target this highly malignant cell population. Here recent discoveries regarding the metabolic properties attributed to CSCs in glioblastoma (GBM) and malignant colorectal cancer (CRC) were summarized. The association between stem cell markers, the response to hypoxia and other environmental stresses including therapeutic insults as well as developmentally conserved signaling pathways with alterations in cellular bioenergetic networks were also discussed. The recent developments in metabolic imaging to identify CSCs were also summarized. This summary should comprehensively update basic and clinical scientists on the metabolic traits of CSCs in GBM and malignant CRC. © 2016 UICC.

Mass-action equilibrium and non-specific interactions in protein binding networks

NASA Astrophysics Data System (ADS)

Maslov, Sergei

2009-03-01

Large-scale protein binding networks serve as a paradigm of complex properties of living cells. These networks are naturally weighted with edges characterized by binding strength and protein-nodes -- by their concentrations. However, the state-of-the-art high-throughput experimental techniques generate just a binary (yes or no) information about individual interactions. As a result, most of the previous research concentrated just on topology of these networks. In a series of recent publications [1-4] my collaborators and I went beyond purely topological studies and calculated the mass-action equilibrium of a genome-wide binding network using experimentally determined protein concentrations, localizations, and reliable binding interactions in baker's yeast. We then studied how this equilibrium responds to large perturbations [1-2] and noise [3] in concentrations of proteins. We demonstrated that the change in the equilibrium concentration of a protein exponentially decays (and sign-alternates) with its network distance away from the perturbed node. This explains why, despite a globally connected topology, individual functional modules in such networks are able to operate fairly independently. In a separate study [4] we quantified the interplay between specific and non-specific binding interactions under crowded conditions inside living cells. We show how the need to limit the waste of resources constrains the number of types and concentrations of proteins that are present at the same time and at the same place in yeast cells. [1] S Maslov, I. Ispolatov, PNAS 104:13655 (2007). [2] S. Maslov, K. Sneppen, I. Ispolatov, New J. of Phys. 9: 273 (2007). [3] K-K. Yan, D. Walker, S. Maslov, PRL accepted (2008). [4] J. Zhang, S. Maslov, and E. I. Shakhnovich, Mol Syst Biol 4, 210 (2008).

Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks.

PubMed

Valletta, Elisa; Kučera, Lukáš; Prokeš, Lubomír; Amato, Filippo; Pivetta, Tiziana; Hampl, Aleš; Havel, Josef; Vaňhara, Petr

2016-01-01

Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, and commercially available technique to authenticate cell lines. However, it provides only qualitative information that depends on the extent of reference databases for interpretation. In this work, we developed and validated a rapid and routinely applicable method for evaluation of cell culture cross-contamination levels based on mass spectrometric fingerprints of intact mammalian cells coupled with artificial neural networks (ANNs). We used human embryonic stem cells (hESCs) contaminated by either mouse embryonic stem cells (mESCs) or mouse embryonic fibroblasts (MEFs) as a model. We determined the contamination level using a mass spectra database of known calibration mixtures that served as training input for an ANN. The ANN was then capable of correct quantification of the level of contamination of hESCs by mESCs or MEFs. We demonstrate that MS analysis, when linked to proper mathematical instruments, is a tangible tool for unraveling and quantifying heterogeneity in cell cultures. The analysis is applicable in routine scenarios for cell authentication and/or cell phenotyping in general.

Multivariate Calibration Approach for Quantitative Determination of Cell-Line Cross Contamination by Intact Cell Mass Spectrometry and Artificial Neural Networks

PubMed Central

Prokeš, Lubomír; Amato, Filippo; Pivetta, Tiziana; Hampl, Aleš; Havel, Josef; Vaňhara, Petr

2016-01-01

Cross-contamination of eukaryotic cell lines used in biomedical research represents a highly relevant problem. Analysis of repetitive DNA sequences, such as Short Tandem Repeats (STR), or Simple Sequence Repeats (SSR), is a widely accepted, simple, and commercially available technique to authenticate cell lines. However, it provides only qualitative information that depends on the extent of reference databases for interpretation. In this work, we developed and validated a rapid and routinely applicable method for evaluation of cell culture cross-contamination levels based on mass spectrometric fingerprints of intact mammalian cells coupled with artificial neural networks (ANNs). We used human embryonic stem cells (hESCs) contaminated by either mouse embryonic stem cells (mESCs) or mouse embryonic fibroblasts (MEFs) as a model. We determined the contamination level using a mass spectra database of known calibration mixtures that served as training input for an ANN. The ANN was then capable of correct quantification of the level of contamination of hESCs by mESCs or MEFs. We demonstrate that MS analysis, when linked to proper mathematical instruments, is a tangible tool for unraveling and quantifying heterogeneity in cell cultures. The analysis is applicable in routine scenarios for cell authentication and/or cell phenotyping in general. PMID:26821236

Cellular therapies for heart disease: unveiling the ethical and public policy challenges.

PubMed

Raval, Amish N; Kamp, Timothy J; Hogle, Linda F

2008-10-01

Cellular therapies have emerged as a potential revolutionary treatment for cardiovascular disease. Promising preclinical results have resulted in a flurry of basic research activity and spawned multiple clinical trials worldwide. However, the optimal cell type and delivery mode have not been determined for target patient populations. Nor have the mechanisms of benefit for the range of cellular interventions been clearly defined. Experiences to date have unveiled a myriad of ethical and public policy challenges which will affect the way researchers and clinicians make decisions for both basic and clinical research. Stem cells derived from embryos are at the forefront of the ethical and political debate, raising issues of which derivation methods are morally and socially permissible to pursue, as much as which are technically feasible. Adult stem cells are less controversial; however, important challenges exist in determining study design, cell processing, delivery mode, and target patient population. Pathways to successful commercialization and hence broad accessibility of cellular therapies for heart disease are only beginning to be explored. Comprehensive, multi-disciplinary and collaborative networks involving basic researchers, clinicians, regulatory officials and policymakers are required to share information, develop research, regulatory and policy standards and enable rational and ethical cell-based treatment approaches.

Dynamics of biological systems: role of systems biology in medical research.

PubMed

Assmus, Heike E; Herwig, Ralf; Cho, Kwang-Hyun; Wolkenhauer, Olaf

2006-11-01

Cellular systems are networks of interacting components that change with time in response to external and internal events. Studying the dynamic behavior of these networks is the basis for an understanding of cellular functions and disease mechanisms. Quantitative time-series data leading to meaningful models can improve our knowledge of human physiology in health and disease, and aid the search for earlier diagnoses, better therapies and a healthier life. The advent of systems biology is about to take the leap into clinical research and medical applications. This review emphasizes the importance of a dynamic view and understanding of cell function. We discuss the potential for computer-aided mathematical modeling of biological systems in medical research with examples from some of the major therapeutic areas: cancer, cardiovascular, diabetic and neurodegenerative medicine.

Challenges in Reproducibility, Replicability, and Comparability of Computational Models and Tools for Neuronal and Glial Networks, Cells, and Subcellular Structures.

PubMed

Manninen, Tiina; Aćimović, Jugoslava; Havela, Riikka; Teppola, Heidi; Linne, Marja-Leena

2018-01-01

The possibility to replicate and reproduce published research results is one of the biggest challenges in all areas of science. In computational neuroscience, there are thousands of models available. However, it is rarely possible to reimplement the models based on the information in the original publication, let alone rerun the models just because the model implementations have not been made publicly available. We evaluate and discuss the comparability of a versatile choice of simulation tools: tools for biochemical reactions and spiking neuronal networks, and relatively new tools for growth in cell cultures. The replicability and reproducibility issues are considered for computational models that are equally diverse, including the models for intracellular signal transduction of neurons and glial cells, in addition to single glial cells, neuron-glia interactions, and selected examples of spiking neuronal networks. We also address the comparability of the simulation results with one another to comprehend if the studied models can be used to answer similar research questions. In addition to presenting the challenges in reproducibility and replicability of published results in computational neuroscience, we highlight the need for developing recommendations and good practices for publishing simulation tools and computational models. Model validation and flexible model description must be an integral part of the tool used to simulate and develop computational models. Constant improvement on experimental techniques and recording protocols leads to increasing knowledge about the biophysical mechanisms in neural systems. This poses new challenges for computational neuroscience: extended or completely new computational methods and models may be required. Careful evaluation and categorization of the existing models and tools provide a foundation for these future needs, for constructing multiscale models or extending the models to incorporate additional or more detailed biophysical mechanisms. Improving the quality of publications in computational neuroscience, enabling progressive building of advanced computational models and tools, can be achieved only through adopting publishing standards which underline replicability and reproducibility of research results.

Challenges in Reproducibility, Replicability, and Comparability of Computational Models and Tools for Neuronal and Glial Networks, Cells, and Subcellular Structures

PubMed Central

Manninen, Tiina; Aćimović, Jugoslava; Havela, Riikka; Teppola, Heidi; Linne, Marja-Leena

2018-01-01

The possibility to replicate and reproduce published research results is one of the biggest challenges in all areas of science. In computational neuroscience, there are thousands of models available. However, it is rarely possible to reimplement the models based on the information in the original publication, let alone rerun the models just because the model implementations have not been made publicly available. We evaluate and discuss the comparability of a versatile choice of simulation tools: tools for biochemical reactions and spiking neuronal networks, and relatively new tools for growth in cell cultures. The replicability and reproducibility issues are considered for computational models that are equally diverse, including the models for intracellular signal transduction of neurons and glial cells, in addition to single glial cells, neuron-glia interactions, and selected examples of spiking neuronal networks. We also address the comparability of the simulation results with one another to comprehend if the studied models can be used to answer similar research questions. In addition to presenting the challenges in reproducibility and replicability of published results in computational neuroscience, we highlight the need for developing recommendations and good practices for publishing simulation tools and computational models. Model validation and flexible model description must be an integral part of the tool used to simulate and develop computational models. Constant improvement on experimental techniques and recording protocols leads to increasing knowledge about the biophysical mechanisms in neural systems. This poses new challenges for computational neuroscience: extended or completely new computational methods and models may be required. Careful evaluation and categorization of the existing models and tools provide a foundation for these future needs, for constructing multiscale models or extending the models to incorporate additional or more detailed biophysical mechanisms. Improving the quality of publications in computational neuroscience, enabling progressive building of advanced computational models and tools, can be achieved only through adopting publishing standards which underline replicability and reproducibility of research results. PMID:29765315

Stability of distributed MPC in an intersection scenario

NASA Astrophysics Data System (ADS)

Sprodowski, T.; Pannek, J.

2015-11-01

The research topic of autonomous cars and the communication among them has attained much attention in the last years and is developing quickly. Among others, this research area spans fields such as image recognition, mathematical control theory, communication networks, and sensor fusion. We consider an intersection scenario where we divide the shared road space in different cells. These cells form a grid. The cars are modelled as an autonomous multi-agent system based on the Distributed Model Predictive Control algorithm (DMPC). We prove that the overall system reaches stability using Optimal Control for each multi-agent and demonstrate that by numerical results.

Anti-Hassle Chip

NASA Technical Reports Server (NTRS)

1998-01-01

With assistance from NASA's Ames Research Center, the iTV Corporation has developed a full custom microprocessor that enables access to the Internet through a $49 device. The microprocessor is supported with a compliment of design tools for customization and adaptation as either a licensable core or as a complete microprocessor. Other uses include cell phones, DVD (digital versatile disk) players, cable modems, video conferencing equipment, digital cameras, wireless LANs (Local Area Network) and WANs (Wide Area Network). iTV continues to design new, low-cost consumer products.

Mining and integration of pathway diagrams from imaging data.

PubMed

Kozhenkov, Sergey; Baitaluk, Michael

2012-03-01

Pathway diagrams from PubMed and World Wide Web (WWW) contain valuable highly curated information difficult to reach without tools specifically designed and customized for the biological semantics and high-content density of the images. There is currently no search engine or tool that can analyze pathway images, extract their pathway components (molecules, genes, proteins, organelles, cells, organs, etc.) and indicate their relationships. Here, we describe a resource of pathway diagrams retrieved from article and web-page images through optical character recognition, in conjunction with data mining and data integration methods. The recognized pathways are integrated into the BiologicalNetworks research environment linking them to a wealth of data available in the BiologicalNetworks' knowledgebase, which integrates data from >100 public data sources and the biomedical literature. Multiple search and analytical tools are available that allow the recognized cellular pathways, molecular networks and cell/tissue/organ diagrams to be studied in the context of integrated knowledge, experimental data and the literature. BiologicalNetworks software and the pathway repository are freely available at www.biologicalnetworks.org. Supplementary data are available at Bioinformatics online.

The signaling petri net-based simulator: a non-parametric strategy for characterizing the dynamics of cell-specific signaling networks.

PubMed

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T

2008-02-29

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using this method, we studied a MAPK1,2 and AKT signaling network downstream from EGFR in two breast tumor cell lines. We analyzed, both experimentally and computationally, the activity level of several molecules in response to a targeted manipulation of TSC2 and mTOR-Raptor. The results from our method agreed with experimental results in greater than 90% of the cases considered, and in those where they did not agree, our approach provided valuable insights into discrepancies between known network connectivities and experimental observations.

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

PubMed Central

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T.

2008-01-01

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using this method, we studied a MAPK1,2 and AKT signaling network downstream from EGFR in two breast tumor cell lines. We analyzed, both experimentally and computationally, the activity level of several molecules in response to a targeted manipulation of TSC2 and mTOR-Raptor. The results from our method agreed with experimental results in greater than 90% of the cases considered, and in those where they did not agree, our approach provided valuable insights into discrepancies between known network connectivities and experimental observations. PMID:18463702

Biphasic response of cell invasion to matrix stiffness in 3-dimensional biopolymer networks

PubMed Central

Lang, Nadine R.; Skodzek, Kai; Hurst, Sebastian; Mainka, Astrid; Steinwachs, Julian; Schneider, Julia; Aifantis, Katerina E.; Fabry, Ben

2015-01-01

When cells come in contact with an adhesive matrix, they begin to spread and migrate with a speed that depends on the stiffness of the extracellular matrix. On a flat surface, migration speed decreases with matrix stiffness mainly due to an increased stability of focal adhesions. In a 3-dimensional (3D) environment, cell migration is thought to be additionally impaired by the steric hindrance imposed by the surrounding matrix. For porous 3D biopolymer networks such as collagen gels, however, the effect of matrix stiffness on cell migration is difficult to separate from effects of matrix pore size and adhesive ligand density, and is therefore unknown. Here we used glutaraldehyde as a crosslinker to increase the stiffness of self-assembled collagen biopolymer networks independently of collagen concentration or pore size. Breast carcinoma cells were seeded onto the surface of 3D collagen gels, and the invasion depth was measured after 3 days of culture. Cell invasion in gels with pore sizes larger than 5 μm increased with higher gel stiffness, whereas invasion in gels with smaller pores decreased with higher gel stiffness. These data show that 3D cell invasion is enhanced by higher matrix stiffness, opposite to cell behavior in 2D, as long as the pore size does not fall below a critical value where it causes excessive steric hindrance. These findings may be important for optimizing the recellularization of soft tissue implants or for the design of 3D invasion models in cancer research. PMID:25462839

Single-cell recording and stimulation with a 16k micro-nail electrode array integrated on a 0.18 μm CMOS chip.

PubMed

Huys, Roeland; Braeken, Dries; Jans, Danny; Stassen, Andim; Collaert, Nadine; Wouters, Jan; Loo, Josine; Severi, Simone; Vleugels, Frank; Callewaert, Geert; Verstreken, Kris; Bartic, Carmen; Eberle, Wolfgang

2012-04-07

To cope with the growing needs in research towards the understanding of cellular function and network dynamics, advanced micro-electrode arrays (MEAs) based on integrated complementary metal oxide semiconductor (CMOS) circuits have been increasingly reported. Although such arrays contain a large number of sensors for recording and/or stimulation, the size of the electrodes on these chips are often larger than a typical mammalian cell. Therefore, true single-cell recording and stimulation remains challenging. Single-cell resolution can be obtained by decreasing the size of the electrodes, which inherently increases the characteristic impedance and noise. Here, we present an array of 16,384 active sensors monolithically integrated on chip, realized in 0.18 μm CMOS technology for recording and stimulation of individual cells. Successful recording of electrical activity of cardiac cells with the chip, validated with intracellular whole-cell patch clamp recordings are presented, illustrating single-cell readout capability. Further, by applying a single-electrode stimulation protocol, we could pace individual cardiac cells, demonstrating single-cell addressability. This novel electrode array could help pave the way towards solving complex interactions of mammalian cellular networks. This journal is © The Royal Society of Chemistry 2012

Techno Generation: Social Networking amongst Youth in South Africa

NASA Astrophysics Data System (ADS)

Basson, Antoinette; Makhasi, Yoliswa; van Vuuren, Daan

Internet and cell phones can be considered as new media compared to traditional media types and have become a fundamental part of the lives of many young people across the globe. The exploratory research study investigated the diffusion and adoption of new media innovations among adolescents. It was found that new media have diffused at a high rate among South African adolescents who are not only the innovators in this area, but also changing their life styles to adapt to the new media. Social networking grew to prominence in South Africa especially among the youth. The protection of children from potential harmful exposure and other risks remain a concern and adequate measures need to be initiated and implemented for children to enjoy social networks and other forms of new media. The exploratory research study provided worthwhile and interesting insights into the role of the new media, in the lives of adolescents in South Africa.

Intercellular and systemic spread of RNA and RNAi in plants.

PubMed

Nazim Uddin, Mohammad; Kim, Jae-Yean

2013-01-01

Plants possess dynamic networks of intercellular communication that are crucial for plant development and physiology. In plants, intercellular communication involves a combination of ligand-receptor-based apoplasmic signaling, and plasmodesmata and phloem-mediated symplasmic signaling. The intercellular trafficking of macromolecules, including RNAs and proteins, has emerged as a novel mechanism of intercellular communication in plants. Various forms of regulatory RNAs move over distinct cellular boundaries through plasmodesmata and phloem. This plant-specific, non-cell-autonomous RNA trafficking network is also involved in development, nutrient homeostasis, gene silencing, pathogen defense, and many other physiological processes. However, the mechanism underlying macromolecular trafficking in plants remains poorly understood. Current progress made in RNA trafficking research and its biological relevance to plant development will be summarized. Diverse plant regulatory mechanisms of cell-to-cell and systemic long-distance transport of RNAs, including mRNAs, viral RNAs, and small RNAs, will also be discussed. Copyright © 2013 John Wiley & Sons, Ltd.

Cell dynamic morphology classification using deep convolutional neural networks.

PubMed

Li, Heng; Pang, Fengqian; Shi, Yonggang; Liu, Zhiwen

2018-05-15

Cell morphology is often used as a proxy measurement of cell status to understand cell physiology. Hence, interpretation of cell dynamic morphology is a meaningful task in biomedical research. Inspired by the recent success of deep learning, we here explore the application of convolutional neural networks (CNNs) to cell dynamic morphology classification. An innovative strategy for the implementation of CNNs is introduced in this study. Mouse lymphocytes were collected to observe the dynamic morphology, and two datasets were thus set up to investigate the performances of CNNs. Considering the installation of deep learning, the classification problem was simplified from video data to image data, and was then solved by CNNs in a self-taught manner with the generated image data. CNNs were separately performed in three installation scenarios and compared with existing methods. Experimental results demonstrated the potential of CNNs in cell dynamic morphology classification, and validated the effectiveness of the proposed strategy. CNNs were successfully applied to the classification problem, and outperformed the existing methods in the classification accuracy. For the installation of CNNs, transfer learning was proved to be a promising scheme. © 2018 International Society for Advancement of Cytometry. © 2018 International Society for Advancement of Cytometry.

ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

PubMed

Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2017-07-20

Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.

Microfluidics-Based in Vivo Mimetic Systems for the Study of Cellular Biology

PubMed Central

2015-01-01

Conspectus The human body is a complex network of molecules, organelles, cells, tissues, and organs: an uncountable number of interactions and transformations interconnect all the system’s components. In addition to these biochemical components, biophysical components, such as pressure, flow, and morphology, and the location of all of these interactions play an important role in the human body. Technical difficulties have frequently limited researchers from observing cellular biology as it occurs within the human body, but some state-of-the-art analytical techniques have revealed distinct cellular behaviors that occur only in the context of the interactions. These types of findings have inspired bioanalytical chemists to provide new tools to better understand these cellular behaviors and interactions. What blocks us from understanding critical biological interactions in the human body? Conventional approaches are often too naïve to provide realistic data and in vivo whole animal studies give complex results that may or may not be relevant for humans. Microfluidics offers an opportunity to bridge these two extremes: while these studies will not model the complexity of the in vivo human system, they can control the complexity so researchers can examine critical factors of interest carefully and quantitatively. In addition, the use of human cells, such as cells isolated from donated blood, captures human-relevant data and limits the use of animals in research. In addition, researchers can adapt these systems easily and cost-effectively to a variety of high-end signal transduction mechanisms, facilitating high-throughput studies that are also spatially, temporally, or chemically resolved. These strengths should allow microfluidic platforms to reveal critical parameters in the human body and provide insights that will help with the translation of pharmacological advances to clinical trials. In this Account, we describe selected microfluidic innovations within the last 5 years that focus on modeling both biophysical and biochemical interactions in cellular communication, such as flow and cell–cell networks. We also describe more advanced systems that mimic higher level biological networks, such as organ on-a-chip and animal on-a-chip models. Since the first papers in the early 1990s, interest in the bioanalytical use of microfluidics has grown significantly. Advances in micro-/nanofabrication technology have allowed researchers to produce miniaturized, biocompatible assay platforms suitable for microfluidic studies in biochemistry and chemical biology. Well-designed microfluidic platforms can achieve quick, in vitro analyses on pico- and femtoliter volume samples that are temporally, spatially, and chemically resolved. In addition, controlled cell culture techniques using a microfluidic platform have produced biomimetic systems that allow researchers to replicate and monitor physiological interactions. Pioneering work has successfully created cell–fluid, cell–cell, cell–tissue, tissue–tissue, even organ-like level interfaces. Researchers have monitored cellular behaviors in these biomimetic microfluidic environments, producing validated model systems to understand human pathophysiology and to support the development of new therapeutics. PMID:24555566

NANOG Plays a Hierarchical Role in the Transcription Network Regulating the Pluripotency and Plasticity of Adipose Tissue-Derived Stem Cells

PubMed Central

Pitrone, Maria; Pizzolanti, Giuseppe; Tomasello, Laura; Coppola, Antonina; Morini, Lorenzo; Pantuso, Gianni; Ficarella, Romina; Guarnotta, Valentina; Perrini, Sebastio; Giorgino, Francesco; Giordano, Carla

2017-01-01

The stromal vascular cell fraction (SVF) of visceral and subcutaneous adipose tissue (VAT and SAT) has increasingly come into focus in stem cell research, since these compartments represent a rich source of multipotent adipose-derived stem cells (ASCs). ASCs exhibit a self-renewal potential and differentiation capacity. Our aim was to study the different expression of the embryonic stem cell markers NANOG (homeobox protein NANOG), SOX2 (SRY (sex determining region Y)-box 2) and OCT4 (octamer-binding transcription factor 4) and to evaluate if there exists a hierarchal role in this network in ASCs derived from both SAT and VAT. ASCs were isolated from SAT and VAT biopsies of 72 consenting patients (23 men, 47 women; age 45 ± 10; BMI between 25 ± 5 and 30 ± 5 range) undergoing elective open-abdominal surgery. Sphere-forming capability was evaluated by plating cells in low adhesion plastic. Stem cell markers CD90, CD105, CD29, CD31, CD45 and CD146 were analyzed by flow cytometry, and the stem cell transcription factors NANOG, SOX2 and OCT4 were detected by immunoblotting and real-time PCR. NANOG, SOX2 and OCT4 interplay was explored by gene silencing. ASCs from VAT and SAT confirmed their mesenchymal stem cell (MSC) phenotype expressing the specific MSC markers CD90, CD105, NANOG, SOX2 and OCT4. NANOG silencing induced a significant OCT4 (70 ± 0.05%) and SOX2 (75 ± 0.03%) downregulation, whereas SOX2 silencing did not affect NANOG gene expression. Adipose tissue is an important source of MSC, and siRNA experiments endorse a hierarchical role of NANOG in the complex transcription network that regulates pluripotency. PMID:28545230

Checkpoints couple transcription network oscillator dynamics to cell-cycle progression.

PubMed

Bristow, Sara L; Leman, Adam R; Simmons Kovacs, Laura A; Deckard, Anastasia; Harer, John; Haase, Steven B

2014-09-05

The coupling of cyclin dependent kinases (CDKs) to an intrinsically oscillating network of transcription factors has been proposed to control progression through the cell cycle in budding yeast, Saccharomyces cerevisiae. The transcription network regulates the temporal expression of many genes, including cyclins, and drives cell-cycle progression, in part, by generating successive waves of distinct CDK activities that trigger the ordered program of cell-cycle events. Network oscillations continue autonomously in mutant cells arrested by depletion of CDK activities, suggesting the oscillator can be uncoupled from cell-cycle progression. It is not clear what mechanisms, if any, ensure that the network oscillator is restrained when progression in normal cells is delayed or arrested. A recent proposal suggests CDK acts as a master regulator of cell-cycle processes that have the potential for autonomous oscillatory behavior. Here we find that mitotic CDK is not sufficient for fully inhibiting transcript oscillations in arrested cells. We do find that activation of the DNA replication and spindle assembly checkpoints can fully arrest the network oscillator via overlapping but distinct mechanisms. Further, we demonstrate that the DNA replication checkpoint effector protein, Rad53, acts to arrest a portion of transcript oscillations in addition to its role in halting cell-cycle progression. Our findings indicate that checkpoint mechanisms, likely via phosphorylation of network transcription factors, maintain coupling of the network oscillator to progression during cell-cycle arrest.

Advanced Ring-Shaped Microelectrode Assay Combined with Small Rectangular Electrode for Quasi-In vivo Measurement of Cell-to-Cell Conductance in Cardiomyocyte Network

NASA Astrophysics Data System (ADS)

Nomura, Fumimasa; Kaneko, Tomoyuki; Hamada, Tomoyo; Hattori, Akihiro; Yasuda, Kenji

2013-06-01

To predict the risk of fatal arrhythmia induced by cardiotoxicity in the highly complex human heart system, we have developed a novel quasi-in vivo electrophysiological measurement assay, which combines a ring-shaped human cardiomyocyte network and a set of two electrodes that form a large single ring-shaped electrode for the direct measurement of irregular cell-to-cell conductance occurrence in a cardiomyocyte network, and a small rectangular microelectrode for forced pacing of cardiomyocyte beating and for acquiring the field potential waveforms of cardiomyocytes. The advantages of this assay are as follows. The electrophysiological signals of cardiomyocytes in the ring-shaped network are superimposed directly on a single loop-shaped electrode, in which the information of asynchronous behavior of cell-to-cell conductance are included, without requiring a set of huge numbers of microelectrode arrays, a set of fast data conversion circuits, or a complex analysis in a computer. Another advantage is that the small rectangular electrode can control the position and timing of forced beating in a ring-shaped human induced pluripotent stem cell (hiPS)-derived cardiomyocyte network and can also acquire the field potentials of cardiomyocytes. First, we constructed the human iPS-derived cardiomyocyte ring-shaped network on the set of two electrodes, and acquired the field potential signals of particular cardiomyocytes in the ring-shaped cardiomyocyte network during simultaneous acquisition of the superimposed signals of whole-cardiomyocyte networks representing cell-to-cell conduction. Using the small rectangular electrode, we have also evaluated the response of the cell network to electrical stimulation. The mean and SD of the minimum stimulation voltage required for pacing (VMin) at the small rectangular electrode was 166+/-74 mV, which is the same as the magnitude of amplitude for the pacing using the ring-shaped electrode (179+/-33 mV). The results showed that the addition of a small rectangular electrode into the ring-shaped electrode was effective for the simultaneous measurement of whole-cell-network signals and single-cell/small-cluster signals on a local site in the cell network, and for the pacing by electrical stimulation of cardiomyocyte networks.

An Interference Mitigation Scheme of Device-to-Device Communications for Sensor Networks Underlying LTE-A

PubMed Central

Kim, Jeehyeong; Karim, Nzabanita Abdoul; Cho, Sunghyun

2017-01-01

Device-to-Device (D2D) communication technology has become a key factor in wireless sensor networks to form autonomous communication links among sensor nodes. Many research results for D2D have been presented to resolve different technical issues of D2D. Nevertheless, the previous works have not resolved the shortage of data rate and limited coverage of wireless sensor networks. Due to bandwidth shortages and limited communication coverage, 3rd Generation Partnership Project (3GPP) has introduced a new Device-to-Device (D2D) communication technique underlying cellular networks, which can improve spectral efficiencies by enabling the direct communication of devices in proximity without passing through enhanced-NodeB (eNB). However, to enable D2D communication in a cellular network presents a challenge with regard to radio resource management since D2D links reuse the uplink radio resources of cellular users and it can cause interference to the receiving channels of D2D user equipment (DUE). In this paper, a hybrid mechanism is proposed that uses Fractional Frequency Reuse (FFR) and Almost Blank Sub-frame (ABS) schemes to handle inter-cell interference caused by cellular user equipments (CUEs) to D2D receivers (DUE-Rxs), reusing the same resources at the cell edge area. In our case, DUE-Rxs are considered as victim nodes and CUEs as aggressor nodes, since our primary target is to minimize inter-cell interference in order to increase the signal to interference and noise ratio (SINR) of the target DUE-Rx at the cell edge area. The numerical results show that the interference level of the target D2D receiver (DUE-Rx) decreases significantly compared to the conventional FFR at the cell edge. In addition, the system throughput of the proposed scheme can be increased up to 60% compared to the conventional FFR. PMID:28489064

An Interference Mitigation Scheme of Device-to-Device Communications for Sensor Networks Underlying LTE-A.

PubMed

Kim, Jeehyeong; Karim, Nzabanita Abdoul; Cho, Sunghyun

2017-05-10

Device-to-Device (D2D) communication technology has become a key factor in wireless sensor networks to form autonomous communication links among sensor nodes. Many research results for D2D have been presented to resolve different technical issues of D2D. Nevertheless, the previous works have not resolved the shortage of data rate and limited coverage of wireless sensor networks. Due to bandwidth shortages and limited communication coverage, 3rd Generation Partnership Project (3GPP) has introduced a new Device-to-Device (D2D) communication technique underlying cellular networks, which can improve spectral efficiencies by enabling the direct communication of devices in proximity without passing through enhanced-NodeB (eNB). However, to enable D2D communication in a cellular network presents a challenge with regard to radio resource management since D2D links reuse the uplink radio resources of cellular users and it can cause interference to the receiving channels of D2D user equipment (DUE). In this paper, a hybrid mechanism is proposed that uses Fractional Frequency Reuse (FFR) and Almost Blank Sub-frame (ABS) schemes to handle inter-cell interference caused by cellular user equipments (CUEs) to D2D receivers (DUE-Rxs), reusing the same resources at the cell edge area. In our case, DUE-Rxs are considered as victim nodes and CUEs as aggressor nodes, since our primary target is to minimize inter-cell interference in order to increase the signal to interference and noise ratio (SINR) of the target DUE-Rx at the cell edge area. The numerical results show that the interference level of the target D2D receiver (DUE-Rx) decreases significantly compared to the conventional FFR at the cell edge. In addition, the system throughput of the proposed scheme can be increased up to 60% compared to the conventional FFR.

WONOEP appraisal: new genetic approaches to study epilepsy

PubMed Central

Rossignol, Elsa; Kobow, Katja; Simonato, Michele; Loeb, Jeffrey A.; Grisar, Thierry; Gilby, Krista L.; Vinet, Jonathan; Kadam, Shilpa D.; Becker, Albert J.

2014-01-01

Objective New genetic investigation techniques, including next-generation sequencing, epigenetic profiling, cell lineage mapping, targeted genetic manipulation of specific neuronal cell types, stem cell reprogramming and optogenetic manipulations within epileptic networks are progressively unravelling the mysteries of epileptogenesis and ictogenesis. These techniques have opened new avenues to discover the molecular basis of epileptogenesis and to study the physiological impacts of mutations in epilepsy-associated genes on a multilayer level, from cells to circuits. Methods This manuscript reviews recently published applications of these new genetic technologies in the study of epilepsy, as well as work presented by the authors at the genetic session of the XII Workshop on the Neurobiology of Epilepsy in Quebec, Canada. Results Next-generation sequencing is providing investigators with an unbiased means to assess the molecular causes of sporadic forms of epilepsy and have revealed the complexity and genetic heterogeneity of sporadic epilepsy disorders. To assess the functional impact of mutations in these newly identified genes on specific neuronal cell-types during brain development, new modeling strategies in animals, including conditional genetics in mice and in utero knockdown approaches, are enabling functional validation with exquisite cell-type and temporal specificity. In addition, optogenetics, using cell-type specific Cre recombinase driver lines, is enabling investigators to dissect networks involved in epilepsy. Genetically-encoded cell-type labeling is also providing new means to assess the role of the non-neuronal components of epileptic networks such as glial cells. Furthermore, beyond its role in revealing coding variants involved in epileptogenesis, next-generation sequencing can be used to assess the epigenetic modifications that lead to sustained network hyperexcitability in epilepsy, including methylation changes in gene promoters and non-coding RNAs involved in modifying gene expression following seizures. In addition, genetically-based bioluminescent reporters are providing new opportunities to assess neuronal activity and neurotransmitter levels both in vitro and in vivo in the context of epilepsy. Finally, genetically rederived neurons generated from patient iPS cells and genetically-modified zebrafish have become high-throughput means to investigate disease mechanisms and potential new therapies. Significance Genetics has considerably changed the field of epilepsy research and is paving the way for better diagnosis and therapies for patients with epilepsy. PMID:24965021

Signalling maps in cancer research: construction and data analysis

PubMed Central

Kondratova, Maria; Sompairac, Nicolas; Barillot, Emmanuel; Zinovyev, Andrei

2018-01-01

Abstract Generation and usage of high-quality molecular signalling network maps can be augmented by standardizing notations, establishing curation workflows and application of computational biology methods to exploit the knowledge contained in the maps. In this manuscript, we summarize the major aims and challenges of assembling information in the form of comprehensive maps of molecular interactions. Mainly, we share our experience gained while creating the Atlas of Cancer Signalling Network. In the step-by-step procedure, we describe the map construction process and suggest solutions for map complexity management by introducing a hierarchical modular map structure. In addition, we describe the NaviCell platform, a computational technology using Google Maps API to explore comprehensive molecular maps similar to geographical maps and explain the advantages of semantic zooming principles for map navigation. We also provide the outline to prepare signalling network maps for navigation using the NaviCell platform. Finally, several examples of cancer high-throughput data analysis and visualization in the context of comprehensive signalling maps are presented. PMID:29688383

From Saccharomyces cerevisiae to human: The important gene co-expression modules.

PubMed

Liu, Wei; Li, Li; Ye, Hua; Chen, Haiwei; Shen, Weibiao; Zhong, Yuexian; Tian, Tian; He, Huaqin

2017-08-01

Network-based systems biology has become an important method for analyzing high-throughput gene expression data and gene function mining. Yeast has long been a popular model organism for biomedical research. In the current study, a weighted gene co-expression network analysis algorithm was applied to construct a gene co-expression network in Saccharomyces cerevisiae . Seventeen stable gene co-expression modules were detected from 2,814 S. cerevisiae microarray data. Further characterization of these modules with the Database for Annotation, Visualization and Integrated Discovery tool indicated that these modules were associated with certain biological processes, such as heat response, cell cycle, translational regulation, mitochondrion oxidative phosphorylation, amino acid metabolism and autophagy. Hub genes were also screened by intra-modular connectivity. Finally, the module conservation was evaluated in a human disease microarray dataset. Functional modules were identified in budding yeast, some of which are associated with patient survival. The current study provided a paradigm for single cell microorganisms and potentially other organisms.

Stability of Control Networks in Autonomous Homeostatic Regulation of Stem Cell Lineages.

PubMed

Komarova, Natalia L; van den Driessche, P

2018-05-01

Design principles of biological networks have been studied extensively in the context of protein-protein interaction networks, metabolic networks, and regulatory (transcriptional) networks. Here we consider regulation networks that occur on larger scales, namely the cell-to-cell signaling networks that connect groups of cells in multicellular organisms. These are the feedback loops that orchestrate the complex dynamics of cell fate decisions and are necessary for the maintenance of homeostasis in stem cell lineages. We focus on "minimal" networks that are those that have the smallest possible numbers of controls. For such minimal networks, the number of controls must be equal to the number of compartments, and the reducibility/irreducibility of the network (whether or not it can be split into smaller independent sub-networks) is defined by a matrix comprised of the cell number increments induced by each of the controlled processes in each of the compartments. Using the formalism of digraphs, we show that in two-compartment lineages, reducible systems must contain two 1-cycles, and irreducible systems one 1-cycle and one 2-cycle; stability follows from the signs of the controls and does not require magnitude restrictions. In three-compartment systems, irreducible digraphs have a tree structure or have one 3-cycle and at least two more shorter cycles, at least one of which is a 1-cycle. With further work and proper biological validation, our results may serve as a first step toward an understanding of ways in which these networks become dysregulated in cancer.

Teaching the bioinformatics of signaling networks: an integrated approach to facilitate multi-disciplinary learning.

PubMed

Korcsmaros, Tamas; Dunai, Zsuzsanna A; Vellai, Tibor; Csermely, Peter

2013-09-01

The number of bioinformatics tools and resources that support molecular and cell biology approaches is continuously expanding. Moreover, systems and network biology analyses are accompanied more and more by integrated bioinformatics methods. Traditional information-centered university teaching methods often fail, as (1) it is impossible to cover all existing approaches in the frame of a single course, and (2) a large segment of the current bioinformation can become obsolete in a few years. Signaling network offers an excellent example for teaching bioinformatics resources and tools, as it is both focused and complex at the same time. Here, we present an outline of a university bioinformatics course with four sample practices to demonstrate how signaling network studies can integrate biochemistry, genetics, cell biology and network sciences. We show that several bioinformatics resources and tools, as well as important concepts and current trends, can also be integrated to signaling network studies. The research-type hands-on experiences we show enable the students to improve key competences such as teamworking, creative and critical thinking and problem solving. Our classroom course curriculum can be re-formulated as an e-learning material or applied as a part of a specific training course. The multi-disciplinary approach and the mosaic setup of the course have the additional benefit to support the advanced teaching of talented students.

Lewis Information Network (LINK): Background and overview

NASA Technical Reports Server (NTRS)

Schulte, Roger R.

1987-01-01

The NASA Lewis Research Center supports many research facilities with many isolated buildings, including wind tunnels, test cells, and research laboratories. These facilities are all located on a 350 acre campus adjacent to the Cleveland Hopkins Airport. The function of NASA-Lewis is to do basic and applied research in all areas of aeronautics, fluid mechanics, materials and structures, space propulsion, and energy systems. These functions require a great variety of remote high speed, high volume data communications for computing and interactive graphic capabilities. In addition, new requirements for local distribution of intercenter video teleconferencing and data communications via satellite have developed. To address these and future communications requirements for the next 15 yrs, a project team was organized to design and implement a new high speed communication system that would handle both data and video information in a common lab-wide Local Area Network. The project team selected cable television broadband coaxial cable technology as the communications medium and first installation of in-ground cable began in the summer of 1980. The Lewis Information Network (LINK) became operational in August 1982 and has become the backbone of all data communications and video.

Music for Their Minds

ERIC Educational Resources Information Center

Shore, Rebecca; Strasser, Janis

2006-01-01

Hearing causes brain cells (neurons) to connect and neural networks to form. Advanced brain-scan technology and neuroscience research reveal that when children participate in music, the brain "light[s] up like a Christmas tree" in many different areas (Parr, Radford, & Snyder 1998, cited in Isenberg & Jalongo 2001, 159). The growing neural…

A Location-Based Duplex Scheme for Cost Effective Rural Broadband Connectivity Using IEEE 802.22 Cognitive Radio Based Wireless Regional Area Networks

NASA Astrophysics Data System (ADS)

Kalidoss, R.; Bhagyaveni, M. A.; Vishvaksenan, K. S.

2014-08-01

The search for a method of utilizing the scarce spectrum in an efficient manner is an active area of research in both academic and industrial communities. IEEE 802.22 is a standard for wireless regional area network (WRAN) based on cognitive radio (CR) that operates over underutilized portions of TV bands (54-862 MHz). Time division duplex (TDD)-based WRAN cells have such advantages as dynamic traffic allocation, traffic asymmetry to users and ease of spectrum allocation. However, these cells suffer from severe cross time slot (CTS) interference when the frames of the cells are not synchronized with adjacent WRAN cells. In this paper, we evaluate the location-based duplex (LBD) scheme for eliminating the CTS interference. The proposed LBD system is much more flexible and efficient in providing asymmetric data service and eliminating CTS interference by exploiting the advantages of both TDD and frequency division duplex (FDD) schemes. We also compare the performance of LBD systems with virtual cell concepts. Furthermore, our simulation results reveal that LBD-based systems outperform the virtual cell approach in terms of the low signal-to-interference (SIR) ratio requirement by mitigating the effects of CTS.

A Multi-Method Approach for Proteomic Network Inference in 11 Human Cancers.

PubMed

Şenbabaoğlu, Yasin; Sümer, Selçuk Onur; Sánchez-Vega, Francisco; Bemis, Debra; Ciriello, Giovanni; Schultz, Nikolaus; Sander, Chris

2016-02-01

Protein expression and post-translational modification levels are tightly regulated in neoplastic cells to maintain cellular processes known as 'cancer hallmarks'. The first Pan-Cancer initiative of The Cancer Genome Atlas (TCGA) Research Network has aggregated protein expression profiles for 3,467 patient samples from 11 tumor types using the antibody based reverse phase protein array (RPPA) technology. The resultant proteomic data can be utilized to computationally infer protein-protein interaction (PPI) networks and to study the commonalities and differences across tumor types. In this study, we compare the performance of 13 established network inference methods in their capacity to retrieve the curated Pathway Commons interactions from RPPA data. We observe that no single method has the best performance in all tumor types, but a group of six methods, including diverse techniques such as correlation, mutual information, and regression, consistently rank highly among the tested methods. We utilize the high performing methods to obtain a consensus network; and identify four robust and densely connected modules that reveal biological processes as well as suggest antibody-related technical biases. Mapping the consensus network interactions to Reactome gene lists confirms the pan-cancer importance of signal transduction pathways, innate and adaptive immune signaling, cell cycle, metabolism, and DNA repair; and also suggests several biological processes that may be specific to a subset of tumor types. Our results illustrate the utility of the RPPA platform as a tool to study proteomic networks in cancer.

Optimization Study of Hydrogen Gas Adsorption on Zig-zag Single-walled Carbon Nanotubes: The Artificial Neural Network Analysis

NASA Astrophysics Data System (ADS)

Nasruddin; Lestari, M.; Supriyadi; Sholahudin

2018-03-01

The use of hydrogen gas in fuel cell technology has a huge opportunity to be applied in upcoming vehicle technology. One of the most important problems in fuel cell technology is the hydrogen storage. The adsorption of hydrogen in carbon-based materials attracts a lot of attention because of its reliability. This study investigated the adsorption of hydrogen gas in Single-walled Carbon Nano Tubes (SWCNT) with chilarity of (0, 12), (0, 15), and (0, 18) to find the optimum chilarity. Artificial Neural Networks (ANN) can be used to predict the hydrogen storage capacity at different pressure and temperature conditions appropriately, using simulated series of data. The Artificial Neural Network is modeled as a predictor of the hydrogen adsorption capacity which provides solutions to some deficiencies in molecular dynamics (MD) simulations. In a previous study, ANN configurations have been developed for 77k, 233k, and 298k temperatures in hydrogen gas storage. To prepare this prediction, ANN is modeled to find out the configurations that exist in the set of training and validation of specified data selection, the distance between data, and the number of neurons that produce the smallest error. This configuration is needed to make an accurate artificial neural network. The configuration of neural network was then applied to this research. The neural network analysis results show that the best configuration of artificial neural network in hydrogen storage is at 233K temperature i.e. on SWCNT with chilarity of (0.12).

Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research.

PubMed

Grunspan, Daniel Z; Wiggins, Benjamin L; Goodreau, Steven M

2014-01-01

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. We conduct descriptive analyses of the structure of the network of costudying relationships. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We also cover practical issues, such as the unique aspects of human subjects review for network studies. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data. © 2014 D. Z. Grunspan et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Nanostructured cavity devices for extracellular stimulation of HL-1 cells.

PubMed

Czeschik, Anna; Rinklin, Philipp; Derra, Ulrike; Ullmann, Sabrina; Holik, Peter; Steltenkamp, Siegfried; Offenhäusser, Andreas; Wolfrum, Bernhard

2015-01-01

Microelectrode arrays (MEAs) are state-of-the-art devices for extracellular recording and stimulation on biological tissue. Furthermore, they are a relevant tool for the development of biomedical applications like retina, cochlear and motor prostheses, cardiac pacemakers and drug screening. Hence, research on functional cell-sensor interfaces, as well as the development of new surface structures and modifications for improved electrode characteristics, is a vivid and well established field. However, combining single-cell resolution with sufficient signal coupling remains challenging due to poor cell-electrode sealing. Furthermore, electrodes with diameters below 20 µm often suffer from a high electrical impedance affecting the noise during voltage recordings. In this study, we report on a nanocavity sensor array for voltage-controlled stimulation and extracellular action potential recordings on cellular networks. Nanocavity devices combine the advantages of low-impedance electrodes with small cell-chip interfaces, preserving a high spatial resolution for recording and stimulation. A reservoir between opening aperture and electrode is provided, allowing the cell to access the structure for a tight cell-sensor sealing. We present the well-controlled fabrication process and the effect of cavity formation and electrode patterning on the sensor's impedance. Further, we demonstrate reliable voltage-controlled stimulation using nanostructured cavity devices by capturing the pacemaker of an HL-1 cell network.

CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components.

PubMed

Heberle, Henry; Carazzolle, Marcelo Falsarella; Telles, Guilherme P; Meirelles, Gabriela Vaz; Minghim, Rosane

2017-09-13

The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability. Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB. CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

Automated live cell screening system based on a 24-well-microplate with integrated micro fluidics.

PubMed

Lob, V; Geisler, T; Brischwein, M; Uhl, R; Wolf, B

2007-11-01

In research, pharmacologic drug-screening and medical diagnostics, the trend towards the utilization of functional assays using living cells is persisting. Research groups working with living cells are confronted with the problem, that common endpoint measurement methods are not able to map dynamic changes. With consideration of time as a further dimension, the dynamic and networked molecular processes of cells in culture can be monitored. These processes can be investigated by measuring several extracellular parameters. This paper describes a high-content system that provides real-time monitoring data of cell parameters (metabolic and morphological alterations), e.g., upon treatment with drug compounds. Accessible are acidification rates, the oxygen consumption and changes in adhesion forces within 24 cell cultures in parallel. Addressing the rising interest in biomedical and pharmacological high-content screening assays, a concept has been developed, which integrates multi-parametric sensor readout, automated imaging and probe handling into a single embedded platform. A life-maintenance system keeps important environmental parameters (gas, humidity, sterility, temperature) constant.

ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

PubMed

Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

2008-08-12

New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges according to associated data values. We demonstrated the advantages of these new capabilities through three biological network visualization case studies: human disease association network, drug-target interaction network and protein-peptide mapping network. The architectural design of ProteoLens makes it suitable for bioinformatics expert data analysts who are experienced with relational database management to perform large-scale integrated network visual explorations. ProteoLens is a promising visual analytic platform that will facilitate knowledge discoveries in future network and systems biology studies.

Chemical Proteomic Approaches Targeting Cancer Stem Cells: A Review of Current Literature.

PubMed

Jung, Hye Jin

2017-01-01

Cancer stem cells (CSCs) have been proposed as central drivers of tumor initiation, progression, recurrence, and therapeutic resistance. Therefore, identifying stem-like cells within cancers and understanding their properties is crucial for the development of effective anticancer therapies. Recently, chemical proteomics has become a powerful tool to efficiently determine protein networks responsible for CSC pathophysiology and comprehensively elucidate molecular mechanisms of drug action against CSCs. This review provides an overview of major methodologies utilized in chemical proteomic approaches. In addition, recent successful chemical proteomic applications targeting CSCs are highlighted. Future direction of potential CSC research by integrating chemical genomic and proteomic data obtained from a single biological sample of CSCs are also suggested in this review. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy.

PubMed

Dreyer, Florian S; Cantone, Martina; Eberhardt, Martin; Jaitly, Tanushree; Walter, Lisa; Wittmann, Jürgen; Gupta, Shailendra K; Khan, Faiz M; Wolkenhauer, Olaf; Pützer, Brigitte M; Jäck, Hans-Martin; Heinzerling, Lucie; Vera, Julio

2018-06-01

Cellular phenotypes are established and controlled by complex and precisely orchestrated molecular networks. In cancer, mutations and dysregulations of multiple molecular factors perturb the regulation of these networks and lead to malignant transformation. High-throughput technologies are a valuable source of information to establish the complex molecular relationships behind the emergence of malignancy, but full exploitation of this massive amount of data requires bioinformatics tools that rely on network-based analyses. In this report we present the Virtual Melanoma Cell, an online tool developed to facilitate the mining and interpretation of high-throughput data on melanoma by biomedical researches. The platform is based on a comprehensive, manually generated and expert-validated regulatory map composed of signaling pathways important in malignant melanoma. The Virtual Melanoma Cell is a tool designed to accept, visualize and analyze user-generated datasets. It is available at: https://www.vcells.net/melanoma. To illustrate the utilization of the web platform and the regulatory map, we have analyzed a large publicly available dataset accounting for anti-PD1 immunotherapy treatment of malignant melanoma patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Effects of Neuromodulation on Excitatory-Inhibitory Neural Network Dynamics Depend on Network Connectivity Structure

NASA Astrophysics Data System (ADS)

Rich, Scott; Zochowski, Michal; Booth, Victoria

2018-01-01

Acetylcholine (ACh), one of the brain's most potent neuromodulators, can affect intrinsic neuron properties through blockade of an M-type potassium current. The effect of ACh on excitatory and inhibitory cells with this potassium channel modulates their membrane excitability, which in turn affects their tendency to synchronize in networks. Here, we study the resulting changes in dynamics in networks with inter-connected excitatory and inhibitory populations (E-I networks), which are ubiquitous in the brain. Utilizing biophysical models of E-I networks, we analyze how the network connectivity structure in terms of synaptic connectivity alters the influence of ACh on the generation of synchronous excitatory bursting. We investigate networks containing all combinations of excitatory and inhibitory cells with high (Type I properties) or low (Type II properties) modulatory tone. To vary network connectivity structure, we focus on the effects of the strengths of inter-connections between excitatory and inhibitory cells (E-I synapses and I-E synapses), and the strengths of intra-connections among excitatory cells (E-E synapses) and among inhibitory cells (I-I synapses). We show that the presence of ACh may or may not affect the generation of network synchrony depending on the network connectivity. Specifically, strong network inter-connectivity induces synchronous excitatory bursting regardless of the cellular propensity for synchronization, which aligns with predictions of the PING model. However, when a network's intra-connectivity dominates its inter-connectivity, the propensity for synchrony of either inhibitory or excitatory cells can determine the generation of network-wide bursting.

Multimedia information processing in the SWAN mobile networked computing system

NASA Astrophysics Data System (ADS)

Agrawal, Prathima; Hyden, Eoin; Krzyzanowsji, Paul; Srivastava, Mani B.; Trotter, John

1996-03-01

Anytime anywhere wireless access to databases, such as medical and inventory records, can simplify workflow management in a business, and reduce or even eliminate the cost of moving paper documents. Moreover, continual progress in wireless access technology promises to provide per-user bandwidths of the order of a few Mbps, at least in indoor environments. When combined with the emerging high-speed integrated service wired networks, it enables ubiquitous and tetherless access to and processing of multimedia information by mobile users. To leverage on this synergy an indoor wireless network based on room-sized cells and multimedia mobile end-points is being developed at AT&T Bell Laboratories. This research network, called SWAN (Seamless Wireless ATM Networking), allows users carrying multimedia end-points such as PDAs, laptops, and portable multimedia terminals, to seamlessly roam while accessing multimedia data streams from the wired backbone network. A distinguishing feature of the SWAN network is its use of end-to-end ATM connectivity as opposed to the connectionless mobile-IP connectivity used by present day wireless data LANs. This choice allows the wireless resource in a cell to be intelligently allocated amongst various ATM virtual circuits according to their quality of service requirements. But an efficient implementation of ATM in a wireless environment requires a proper mobile network architecture. In particular, the wireless link and medium-access layers need to be cognizant of the ATM traffic, while the ATM layers need to be cognizant of the mobility enabled by the wireless layers. This paper presents an overview of SWAN's network architecture, briefly discusses the issues in making ATM mobile and wireless, and describes initial multimedia applications for SWAN.

VirtualLeaf: an open-source framework for cell-based modeling of plant tissue growth and development.

PubMed

Merks, Roeland M H; Guravage, Michael; Inzé, Dirk; Beemster, Gerrit T S

2011-02-01

Plant organs, including leaves and roots, develop by means of a multilevel cross talk between gene regulation, patterned cell division and cell expansion, and tissue mechanics. The multilevel regulatory mechanisms complicate classic molecular genetics or functional genomics approaches to biological development, because these methodologies implicitly assume a direct relation between genes and traits at the level of the whole plant or organ. Instead, understanding gene function requires insight into the roles of gene products in regulatory networks, the conditions of gene expression, etc. This interplay is impossible to understand intuitively. Mathematical and computer modeling allows researchers to design new hypotheses and produce experimentally testable insights. However, the required mathematics and programming experience makes modeling poorly accessible to experimental biologists. Problem-solving environments provide biologically intuitive in silico objects ("cells", "regulation networks") required for setting up a simulation and present those to the user in terms of familiar, biological terminology. Here, we introduce the cell-based computer modeling framework VirtualLeaf for plant tissue morphogenesis. The current version defines a set of biologically intuitive C++ objects, including cells, cell walls, and diffusing and reacting chemicals, that provide useful abstractions for building biological simulations of developmental processes. We present a step-by-step introduction to building models with VirtualLeaf, providing basic example models of leaf venation and meristem development. VirtualLeaf-based models provide a means for plant researchers to analyze the function of developmental genes in the context of the biophysics of growth and patterning. VirtualLeaf is an ongoing open-source software project (http://virtualleaf.googlecode.com) that runs on Windows, Mac, and Linux.

Study on Fuel Cell Network System Considering Reduction in Fuel Cell Capacity Using Load Leveling and Heat Release Loss

NASA Astrophysics Data System (ADS)

Obara, Shin'ya; Kudo, Kazuhiko

Reduction in fuel cell capacity linked to a fuel cell network system is considered. When the power demand of the whole network is small, some of the electric power generated by the fuel cell is supplied to a water electrolysis device, and hydrogen and oxygen gases are generated. Both gases are compressed with each compressor and they are stored in cylinders. When the electric demand of the whole network is large, both gases are supplied to the network, and fuel cells are operated by these hydrogen and oxygen gases. Furthermore, an optimization plan is made to minimize the quantity of heat release of the hot water piping that connects each building. Such an energy network is analyzed assuming connection of individual houses, a hospital, a hotel, a convenience store, an office building, and a factory. Consequently, compared with the conventional system, a reduction of 46% of fuel cell capacity is expected.

Numerical Simulation of Sickle Cell Blood Flow in the Microcirculation

NASA Astrophysics Data System (ADS)

Berger, Stanley A.; Carlson, Brian E.

2001-11-01

A numerical simulation of normal and sickle cell blood flow through the transverse arteriole-capillary microcirculation is carried out to model the dominant mechanisms involved in the onset of vascular stasis in sickle cell disease. The transverse arteriole-capillary network is described by Strahler's network branching method, and the oxygen and blood transport in the capillaries is modeled by a Krogh cylinder analysis utilizing Lighthill's lubrication theory, as developed by Berger and King. Poiseuille's law is used to represent blood flow in the arterioles. Applying this flow and transport model and utilizing volumetric flow continuity at each network bifurcation, a nonlinear system of equations is obtained, which is solved iteratively using a steepest descent algorithm coupled with a Newton solver. Ten different networks are generated and flow results are calculated for normal blood and sickle cell blood without and with precapillary oxygen loss. We find that total volumetric blood flow through the network is greater in the two sickle cell blood simulations than for normal blood owing to the anemia associated with sickle cell disease. The percentage of capillary blockage in the network increases dramatically with decreasing pressure drop across the network in the sickle cell cases while there is no blockage when normal blood flows through simulated networks. It is concluded that, in sickle cell disease, without any vasomotor dilation response to decreasing oxygen concentrations in the blood, capillary blockage will occur in the microvasculature even at average pressure drops across the transverse arteriole-capillary networks.

Electrophysiologic studies of neronal activities under ischemia condition.

PubMed

Huang, Shun-Ho; Wang, Ping-Hsien; Chen, Jia-Jin Jason

2008-01-01

Substrate with integrated microelectrode arrays (MEAs) provides an alternative electrophysiological method. With MEAS, one can measure the impedance and elicit electrical stimulation from multiple sites of MEAs to determine the electrophysiological conditions of cells. The aims of this research were to construct an impedance and action potential measurement system for neurons cultured on MEAs for observing the electrophysiological signal transmission in neuronal network during glucose and oxygen deprivation (OGD). An extracellular stimulator producing the biphasic micro-current pulse for neuron stimulation was built in this study. From the time-course recording of impedance, OGD condition effectively induced damage in neurons in vitro. It is known that the results of cell stimulation are affected by electrode impedance, so does the result of neuron cells covered on the electrode can measure the sealing resistance. For extracellular stimulation study, cortical neuronal activity was recorded and the suitable stimulation window was determined. However, the stimulation results were affected by electrode impedance as well as sealing impedance resulting from neuron cells covering the electrode. Further development of surface modification for cultured neuron network should provide a better way for in vitro impedance and electrophysiological measurements.

Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

PubMed Central

Li, Xia; Rao, Shaoqi; Jiang, Wei; Li, Chuanxing; Xiao, Yun; Guo, Zheng; Zhang, Qingpu; Wang, Lihong; Du, Lei; Li, Jing; Li, Li; Zhang, Tianwen; Wang, Qing K

2006-01-01

Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network) to address the underlying regulations of genes that can span any unit(s) of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex gene regulations related to the development, aging and progressive pathogenesis of a complex disease where potential dependences between different experiment units might occurs. PMID:16420705

Cell cycle gene expression networks discovered using systems biology: Significance in carcinogenesis

PubMed Central

Scott, RE; Ghule, PN; Stein, JL; Stein, GS

2015-01-01

The early stages of carcinogenesis are linked to defects in the cell cycle. A series of cell cycle checkpoints are involved in this process. The G1/S checkpoint that serves to integrate the control of cell proliferation and differentiation is linked to carcinogenesis and the mitotic spindle checkpoint with the development of chromosomal instability. This paper presents the outcome of systems biology studies designed to evaluate if networks of covariate cell cycle gene transcripts exist in proliferative mammalian tissues including mice, rats and humans. The GeneNetwork website that contains numerous gene expression datasets from different species, sexes and tissues represents the foundational resource for these studies (www.genenetwork.org). In addition, WebGestalt, a gene ontology tool, facilitated the identification of expression networks of genes that co-vary with key cell cycle targets, especially Cdc20 and Plk1 (www.bioinfo.vanderbilt.edu/webgestalt). Cell cycle expression networks of such covariate mRNAs exist in multiple proliferative tissues including liver, lung, pituitary, adipose and lymphoid tissues among others but not in brain or retina that have low proliferative potential. Sixty-three covariate cell cycle gene transcripts (mRNAs) compose the average cell cycle network with p = e−13 to e−36. Cell cycle expression networks show species, sex and tissue variability and they are enriched in mRNA transcripts associated with mitosis many of which are associated with chromosomal instability. PMID:25808367

Evidence-Based Clinical Use of Nanoscale Extracellular Vesicles in Nanomedicine.

PubMed

Fais, Stefano; O'Driscoll, Lorraine; Borras, Francesc E; Buzas, Edit; Camussi, Giovanni; Cappello, Francesco; Carvalho, Joana; Cordeiro da Silva, Anabela; Del Portillo, Hernando; El Andaloussi, Samir; Ficko Trček, Tanja; Furlan, Roberto; Hendrix, An; Gursel, Ihsan; Kralj-Iglic, Veronika; Kaeffer, Bertrand; Kosanovic, Maja; Lekka, Marilena E; Lipps, Georg; Logozzi, Mariantonia; Marcilla, Antonio; Sammar, Marei; Llorente, Alicia; Nazarenko, Irina; Oliveira, Carla; Pocsfalvi, Gabriella; Rajendran, Lawrence; Raposo, Graça; Rohde, Eva; Siljander, Pia; van Niel, Guillaume; Vasconcelos, M Helena; Yáñez-Mó, María; Yliperttula, Marjo L; Zarovni, Natasa; Zavec, Apolonija Bedina; Giebel, Bernd

2016-04-26

Recent research has demonstrated that all body fluids assessed contain substantial amounts of vesicles that range in size from 30 to 1000 nm and that are surrounded by phospholipid membranes containing different membrane microdomains such as lipid rafts and caveolae. The most prominent representatives of these so-called extracellular vesicles (EVs) are nanosized exosomes (70-150 nm), which are derivatives of the endosomal system, and microvesicles (100-1000 nm), which are produced by outward budding of the plasma membrane. Nanosized EVs are released by almost all cell types and mediate targeted intercellular communication under physiological and pathophysiological conditions. Containing cell-type-specific signatures, EVs have been proposed as biomarkers in a variety of diseases. Furthermore, according to their physical functions, EVs of selected cell types have been used as therapeutic agents in immune therapy, vaccination trials, regenerative medicine, and drug delivery. Undoubtedly, the rapidly emerging field of basic and applied EV research will significantly influence the biomedicinal landscape in the future. In this Perspective, we, a network of European scientists from clinical, academic, and industry settings collaborating through the H2020 European Cooperation in Science and Technology (COST) program European Network on Microvesicles and Exosomes in Health and Disease (ME-HAD), demonstrate the high potential of nanosized EVs for both diagnostic and therapeutic (i.e., theranostic) areas of nanomedicine.

Ubiquitous Indoor Geolocation: a Case Study of Jewellery Management System

NASA Astrophysics Data System (ADS)

Nikparvar, B.; Sadeghi-Niaraki, A.; Azari, P.

2014-10-01

Addressing and geolocation for indoor environments are important fields of research in the recent years. The problem of finding location of objects in indoor spaces is proposed to solve in two ways. The first, is to assign coordinates to objects and second is to divide space into cells and detect the presence or absence of objects in each cell to track them. In this paper the second approach is discussed by using Radio Frequency Identification technology to identify and track high value objects in jewellery retail industry. In Ubiquitous Sensor Networks, the reactivity or proactivity of the environment are important issues. Reactive environments wait for a request to response to it. Instead, in proactive spaces, the environment acts in advance to deal with an expected action. In this research, a geo-sensor network containing RFID readers, tags, and antennas which continuously exchange radio frequency signal streams is proposed to manage and monitor jewellery galleries ubiquitously. The system is also equipped with a GIS representation which provides a more user-friendly system to manage a jewellery gallery.

Study on Improving Partial Load by Connecting Geo-thermal Heat Pump System to Fuel Cell Network

NASA Astrophysics Data System (ADS)

Obara, Shinya; Kudo, Kazuhiko

Hydrogen piping, the electric power line, and exhaust heat recovery piping of the distributed fuel cells are connected with network, and operational planning is carried out. Reduction of the efficiency in partial load is improved by operation of the geo-thermal heat pump linked to the fuel cell network. The energy demand pattern of the individual houses in Sapporo was introduced. And the analysis method aiming at minimization of the fuel rate by the genetic algorithm was described. The fuel cell network system of an analysis example assumed connecting the fuel cell co-generation of five houses. When geo-thermal heat pump was introduced into fuel cell network system stated in this paper, fuel consumption was reduced 6% rather than the conventional method

Exploring the Therapeutic Mechanism of Desmodium styracifolium on Oxalate Crystal-Induced Kidney Injuries Using Comprehensive Approaches Based on Proteomics and Network Pharmacology.

PubMed

Hou, Jiebin; Chen, Wei; Lu, Hongtao; Zhao, Hongxia; Gao, Songyan; Liu, Wenrui; Dong, Xin; Guo, Zhiyong

2018-01-01

Purpose: As a Chinese medicinal herb, Desmodium styracifolium (Osb.) Merr (DS) has been applied clinically to alleviate crystal-induced kidney injuries, but its effective components and their specific mechanisms still need further exploration. This research first combined the methods of network pharmacology and proteomics to explore the therapeutic protein targets of DS on oxalate crystal-induced kidney injuries to provide a reference for relevant clinical use. Methods: Oxalate-induced kidney injury mouse, rat, and HK-2 cell models were established. Proteins differentially expressed between the oxalate and control groups were respectively screened using iTRAQ combined with MALDI-TOF-MS. The common differential proteins of the three models were further analyzed by molecular docking with DS compounds to acquire differential targets. The inverse docking targets of DS were predicted through the platform of PharmMapper. The protein-protein interaction (PPI) relationship between the inverse docking targets and the differential proteins was established by STRING. Potential targets were further validated by western blot based on a mouse model with DS treatment. The effects of constituent compounds, including luteolin, apigenin, and genistein, were investigated based on an oxalate-stimulated HK-2 cell model. Results: Thirty-six common differentially expressed proteins were identified by proteomic analysis. According to previous research, the 3D structures of 15 major constituents of DS were acquired. Nineteen differential targets, including cathepsin D (CTSD), were found using molecular docking, and the component-differential target network was established. Inverse-docking targets including p38 MAPK and CDK-2 were found, and the network of component-reverse docking target was established. Through PPI analysis, 17 inverse-docking targets were linked to differential proteins. The combined network of component-inverse docking target-differential proteins was then constructed. The expressions of CTSD, p-p38 MAPK, and p-CDK-2 were shown to be increased in the oxalate group and decreased in kidney tissue by the DS treatment. Luteolin, apigenin, and genistein could protect oxalate-stimulated tubular cells as active components of DS. Conclusion: The potential targets including the CTSD, p38 MAPK, and CDK2 of DS in oxalate-induced kidney injuries and the active components (luteolin, apigenin, and genistein) of DS were successfully identified in this study by combining proteomics analysis, network pharmacology prediction, and experimental validation.

BioASF: a framework for automatically generating executable pathway models specified in BioPAX.

PubMed

Haydarlou, Reza; Jacobsen, Annika; Bonzanni, Nicola; Feenstra, K Anton; Abeln, Sanne; Heringa, Jaap

2016-06-15

Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model. To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language. The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF CONTACT: j.heringa@vu.nl. © The Author 2016. Published by Oxford University Press.

p21(WAF1) Mediates Cell-Cycle Inhibition, Relevant to Cancer Suppression and Therapy.

PubMed

El-Deiry, Wafik S

2016-09-15

p21 (WAF1/CIP1; CDKN1a) is a universal cell-cycle inhibitor directly controlled by p53 and p53-independent pathways. Knowledge of the regulation and function of p21 in normal and cancer cells has opened up several areas of investigation and has led to novel therapeutic strategies. The discovery in 1993 and subsequent work on p21 has illuminated basic cellular growth control, stem cell phenotypes, the physiology of differentiation, as well as how cells respond to stress. There remain open questions in the signaling networks, the ultimate role of p21 in the p53-deficiency phenotype in the context of other p53 target defects, and therapeutic strategies continue to be a work in progress. Cancer Res; 76(18); 5189-91. ©2016 AACRSee related article by El-Deiry et al., Cancer Res 1994;54:1169-74Visit the Cancer Research 75(th) Anniversary timeline. ©2016 American Association for Cancer Research.

Graph Theory-Based Analysis of the Lymph Node Fibroblastic Reticular Cell Network.

PubMed

Novkovic, Mario; Onder, Lucas; Bocharov, Gennady; Ludewig, Burkhard

2017-01-01

Secondary lymphoid organs have developed segregated niches that are able to initiate and maintain effective immune responses. Such global organization requires tight control of diverse cellular components, specifically those that regulate lymphocyte trafficking. Fibroblastic reticular cells (FRCs) form a densely interconnected network in lymph nodes and provide key factors necessary for T cell migration and retention, and foster subsequent interactions between T cells and dendritic cells. Development of integrative systems biology approaches has made it possible to elucidate this multilevel complexity of the immune system. Here, we present a graph theory-based analysis of the FRC network in murine lymph nodes, where generation of the network topology is performed using high-resolution confocal microscopy and 3D reconstruction. This approach facilitates the analysis of physical cell-to-cell connectivity, and estimation of topological robustness and global behavior of the network when it is subjected to perturbation in silico.

The dynamic and geometric phase transition in the cellular network of pancreatic islet

NASA Astrophysics Data System (ADS)

Wang, Xujing

2013-03-01

The pancreatic islet is a micro-organ that contains several thousands of endocrine cells, majority of which being the insulin releasing β - cells . - cellsareexcitablecells , andarecoupledtoeachother through gap junctional channels. Here, using percolation theory, we investigate the role of network structure in determining the dynamics of the β-cell network. We show that the β-cell synchronization depends on network connectivity. More specifically, as the site occupancy is reducing, initially the β-cell synchronization is barely affected, until it reaches around a critical value, where the synchronization exhibit a sudden rapid decline, followed by an slow exponential tail. This critical value coincides with the critical site open probability for percolation transition. The dependence over bond strength is similar, exhibiting critical-behavior like dependence around a certain value of bond strength. These results suggest that the β-cell network undergoes a dynamic phase transition when the network is percolated. We further apply the findings to study diabetes. During the development of diabetes, the β - cellnetworkconnectivitydecreases . Siteoccupancyreducesfromthe reducing β-cell mass, and the bond strength is increasingly impaired from β-cell stress and chronic hyperglycemia. We demonstrate that the network dynamics around the percolation transition explain the disease dynamics around onset, including a long time mystery in diabetes, the honeymoon phenomenon.

Modification of a neuronal network direction using stepwise photo-thermal etching of an agarose architecture.

PubMed

Suzuki, Ikurou; Sugio, Yoshihiro; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Yasuda, Kenji

2004-07-01

Control over spatial distribution of individual neurons and the pattern of neural network provides an important tool for studying information processing pathways during neural network formation. Moreover, the knowledge of the direction of synaptic connections between cells in each neural network can provide detailed information on the relationship between the forward and feedback signaling. We have developed a method for topographical control of the direction of synaptic connections within a living neuronal network using a new type of individual-cell-based on-chip cell-cultivation system with an agarose microchamber array (AMCA). The advantages of this system include the possibility to control positions and number of cultured cells as well as flexible control of the direction of elongation of axons through stepwise melting of narrow grooves. Such micrometer-order microchannels are obtained by photo-thermal etching of agarose where a portion of the gel is melted with a 1064-nm infrared laser beam. Using this system, we created neural network from individual Rat hippocampal cells. We were able to control elongation of individual axons during cultivation (from cells contained within the AMCA) by non-destructive stepwise photo-thermal etching. We have demonstrated the potential of our on-chip AMCA cell cultivation system for the controlled development of individual cell-based neural networks.

The California Central Coast Research Partnership: Building Relationships, Partnerships, and Paradigms for University-Industry Research Collaboration

DTIC Science & Technology

2009-12-18

Networks of Co-Expressed Proteins 492 Adaptation of the Bardo Airway to the Intraoral Mask: Innovative Airway Management Devices Working in...has expressed interest in working with us and possibly hiring students associated with this project. Additionally this system will be adapted for...line. Additionally MS student Tom Harper will carry on Stephanie’s work and adapt the system to explore spectra for cell differentiation. A new

A modular network for legged locomotion

NASA Astrophysics Data System (ADS)

Golubitsky, Martin; Stewart, Ian; Buono, Pietro-Luciano; Collins, J. J.

1998-04-01

In this paper we use symmetry methods to study networks of coupled cells, which are models for central pattern generators (CPGs). In these models the cells obey identical systems of differential equations and the network specifies how cells are coupled. Previously, Collins and Stewart showed that the phase relations of many of the standard gaits of quadrupeds and hexapods can be obtained naturally via Hopf bifurcation in small networks. For example, the networks they used to study quadrupeds all had four cells, with the understanding that each cell determined the phase of the motion of one leg. However, in their work it seemed necessary to employ several different four-oscillator networks to obtain all of the standard quadrupedal gaits. We show that this difficulty with four-oscillator networks is unavoidable, but that the problems can be overcome by using a larger network. Specifically, we show that the standard gaits of a quadruped, including walk, trot and pace, cannot all be realized by a single four-cell network without introducing unwanted conjugacies between trot and pace - conjugacies that imply a dynamic equivalence between these gaits that seems inconsistent with observations. In this sense a single network with four cells cannot model the CPG of a quadruped. We also introduce a single eight-cell network that can model all of the primary gaits of quadrupeds without these unwanted conjugacies. Moreover, this network is modular in that it naturally generalizes to provide models of gaits in hexapods, centipedes, and millipedes. The analysis of models for many-legged animals shows that wave-like motions, similar to those obtained by Kopell and Ermentrout, can be expected. However, our network leads to a prediction that the wavelength of the wave motion will divide twice the length of the animal. Indeed, we reproduce illustrations of wave-like motions in centipedes where the animal is approximately one-and-a-half wavelength long - motions that are consistent with this prediction. We discuss the implications of these results for the development of modular control networks for adaptive legged robots.

Tensegrity II. How structural networks influence cellular information processing networks

NASA Technical Reports Server (NTRS)

Ingber, Donald E.

2003-01-01

The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.

Neural network processing of microbial fuel cell signals for the identification of chemicals present in water.

PubMed

Feng, Yinghua; Barr, William; Harper, W F

2013-05-15

Biosensing is emerging as an important element of water quality monitoring. This research demonstrated that microbial fuel cell (MFC)-based biosensing can be integrated with artificial neural networks (ANNs) to identify specific chemicals present in water samples. The non-fermentable substrates, acetate and butyrate, induced peak areas (PA) and peak heights (PH) that were generally larger than those caused by the injection of fermentable substrates, glucose and corn starch. The ANN successfully identified peaks associated with these four chemicals under a variety of experimental conditions and for two MFCs that had different levels of sensitivity. ANNs that employ the hyperbolic tangent sigmoid transfer function performed better than those using non-continuous transfer functions. ANNs should be integrated into water quality monitoring efforts for smart biosensing. Published by Elsevier Ltd.

Medical education practice-based research networks: Facilitating collaborative research.

PubMed

Schwartz, Alan; Young, Robin; Hicks, Patricia J

2016-01-01

Research networks formalize and institutionalize multi-site collaborations by establishing an infrastructure that enables network members to participate in research, propose new studies, and exploit study data to move the field forward. Although practice-based clinical research networks are now widespread, medical education research networks are rapidly emerging. In this article, we offer a definition of the medical education practice-based research network, a brief description of networks in existence in July 2014 and their features, and a more detailed case study of the emergence and early growth of one such network, the Association of Pediatric Program Directors Longitudinal Educational Assessment Research Network (APPD LEARN). We searched for extant networks through peer-reviewed literature and the world-wide web. We identified 15 research networks in medical education founded since 2002 with membership ranging from 8 to 120 programs. Most focus on graduate medical education in primary care or emergency medicine specialties. We offer four recommendations for the further development and spread of medical education research networks: increasing faculty development, obtaining central resources, studying networks themselves, and developing networks of networks.

Medical education practice-based research networks: Facilitating collaborative research

PubMed Central

Schwartz, Alan; Young, Robin; Hicks, Patricia J.; APPD LEARN, For

2016-01-01

Abstract Background: Research networks formalize and institutionalize multi-site collaborations by establishing an infrastructure that enables network members to participate in research, propose new studies, and exploit study data to move the field forward. Although practice-based clinical research networks are now widespread, medical education research networks are rapidly emerging. Aims: In this article, we offer a definition of the medical education practice-based research network, a brief description of networks in existence in July 2014 and their features, and a more detailed case study of the emergence and early growth of one such network, the Association of Pediatric Program Directors Longitudinal Educational Assessment Research Network (APPD LEARN). Methods: We searched for extant networks through peer-reviewed literature and the world-wide web. Results: We identified 15 research networks in medical education founded since 2002 with membership ranging from 8 to 120 programs. Most focus on graduate medical education in primary care or emergency medicine specialties. Conclusions: We offer four recommendations for the further development and spread of medical education research networks: increasing faculty development, obtaining central resources, studying networks themselves, and developing networks of networks. PMID:25319404

Hyperspectral Polymer Solar Cells, Integrated Power for Microsystems

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

Stiebitz, Paul

2014-05-27

The purpose of this research is to address a critical technology barrier to the deployment of next generation autonomous microsystems – the availability of efficient and reliable power sources. The vast majority of research on microsystems has been directed toward the development and miniaturization of sensors and other devices that enhance their intelligence, physical, and networking capabilities. However, the research into power generating and power storage technologies has not keep pace with this development. This research leveraged the capabilities of RIT’s NanoPower Research Laboratories (NPRL) in materials for advanced lithium ion batteries, nanostructured photovoltaics, and hybrid betavoltaics to develop reliablemore » power sources for microsystems.« less

Base Station Placement Algorithm for Large-Scale LTE Heterogeneous Networks.

PubMed

Lee, Seungseob; Lee, SuKyoung; Kim, Kyungsoo; Kim, Yoon Hyuk

2015-01-01

Data traffic demands in cellular networks today are increasing at an exponential rate, giving rise to the development of heterogeneous networks (HetNets), in which small cells complement traditional macro cells by extending coverage to indoor areas. However, the deployment of small cells as parts of HetNets creates a key challenge for operators' careful network planning. In particular, massive and unplanned deployment of base stations can cause high interference, resulting in highly degrading network performance. Although different mathematical modeling and optimization methods have been used to approach various problems related to this issue, most traditional network planning models are ill-equipped to deal with HetNet-specific characteristics due to their focus on classical cellular network designs. Furthermore, increased wireless data demands have driven mobile operators to roll out large-scale networks of small long term evolution (LTE) cells. Therefore, in this paper, we aim to derive an optimum network planning algorithm for large-scale LTE HetNets. Recently, attempts have been made to apply evolutionary algorithms (EAs) to the field of radio network planning, since they are characterized as global optimization methods. Yet, EA performance often deteriorates rapidly with the growth of search space dimensionality. To overcome this limitation when designing optimum network deployments for large-scale LTE HetNets, we attempt to decompose the problem and tackle its subcomponents individually. Particularly noting that some HetNet cells have strong correlations due to inter-cell interference, we propose a correlation grouping approach in which cells are grouped together according to their mutual interference. Both the simulation and analytical results indicate that the proposed solution outperforms the random-grouping based EA as well as an EA that detects interacting variables by monitoring the changes in the objective function algorithm in terms of system throughput performance.

Development of dielectrophoresis MEMS device for PC12 cell patterning to elucidate nerve-network generation

NASA Astrophysics Data System (ADS)

Nakamachi, Eiji; Koga, Hirotaka; Morita, Yusuke; Yamamoto, Koji; Sakamoto, Hidetoshi

2018-01-01

We developed a PC12 cell trapping and patterning device by combining the dielectrophoresis (DEP) methodology and the micro electro mechanical systems (MEMS) technology for time-lapse observation of morphological change of nerve network to elucidate the generation mechanism of neural network. We succeeded a neural network generation, which consisted of cell body, axon and dendrites by using tetragonal and hexagonal cell patterning. Further, the time laps observations was carried out to evaluate the axonal extension rate. The axon extended in the channel and reached to the target cell body. We found that the shorter the PC12 cell distance, the less the axonal connection time in both tetragonal and hexagonal structures. After 48 hours culture, a maximum success rate of network formation was 85% in the case of 40 μm distance tetragonal structure.

Construction of Injectable Double-Network Hydrogels for Cell Delivery.

PubMed

Yan, Yan; Li, Mengnan; Yang, Di; Wang, Qian; Liang, Fuxin; Qu, Xiaozhong; Qiu, Dong; Yang, Zhenzhong

2017-07-10

Herein we present a unique method of using dynamic cross-links, which are dynamic covalent bonding and ionic interaction, for the construction of injectable double-network (DN) hydrogels, with the objective of cell delivery for cartilage repair. Glycol chitosan and dibenzaldhyde capped poly(ethylene oxide) formed the first network, while calcium alginate formed the second one, and in the resultant DN hydrogel, either of the networks could be selectively removed. The moduli of the DN hydrogel were significantly improved compared to that of the parent single-network hydrogels and were tunable by changing the chemical components. In situ 3D cell encapsulation could be easily performed by mixing cell suspension to the polymer solutions and transferred through a syringe needle before sol-gel transition. Cell proliferation and mediated differentiation of mouse chondrogenic cells were achieved in the DN hydrogel extracellular matrix.

EuroStemCell: A European infrastructure for communication and engagement with stem cell research.

PubMed

Barfoot, Jan; Doherty, Kate; Blackburn, C Clare

2017-10-01

EuroStemCell is a large and growing network of organizations and individuals focused on public engagement with stem cells and regenerative medicine - a fluid and contested domain, where scientific, political, ethical, legal and societal perspectives intersect. Rooted in the European stem cell research community, this project has developed collaborative and innovative approaches to information provision and direct and online engagement, that reflect and respond to the dynamic growth of the field itself. EuroStemCell started as the communication and outreach component of a research consortium and subsequently continued as a stand-alone engagement initiative. The involvement of established European stem cell scientists has grown year-on-year, facilitating their participation in public engagement by allowing them to make high-value contributions with broad reach. The project has now had sustained support by partners and funders for over twelve years, and thus provides a model for longevity in public engagement efforts. This paper considers the evolution of the EuroStemCell project in response to - and in dialogue with - its evolving environment. In it, we aim to reveal the mechanisms and approaches taken by EuroStemCell, such that others within the scientific community can explore these ideas and be further enabled in their own public engagement endeavours. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Synthetic Tumor Networks for Screening Drug Delivery Systems

PubMed Central

Prabhakarpandian, Balabhaskar; Shen, Ming-Che; Nichols, Joseph B.; Garson, Charles J.; Mills, Ivy R.; Matar, Majed M.; Fewell, Jason G.; Pant, Kapil

2015-01-01

Tumor drug delivery is a complex phenomenon affected by several elements in addition to drug or delivery vehicle’s physico-chemical properties. A key factor is tumor microvasculature with complex effects including convective transport, high interstitial pressure and enhanced vascular permeability due to the presence of “leaky vessels”. Current in vitro models of the tumor microenvironment for evaluating drug delivery are oversimplified and, as a result, show poor correlation with in vivo performance. In this study, we report on the development of a novel microfluidic platform that models the tumor microenvironment more accurately, with physiologically and morphologically realistic microvasculature including endothelial cell lined leaky capillary vessels along with 3D solid tumors. Endothelial cells and 3D spheroids of cervical tumor cells were co-cultured in the networks. Drug vehicle screening was demonstrated using GFP gene delivery by different formulations of nanopolymers. The synthetic tumor network was successful in predicting in vivo delivery efficiencies of the drug vehicles. The developed assay will have critical applications both in basic research, where it can be used to develop next generation delivery vehicles, and in drug discovery where it can be used to study drug transport and delivery efficacy in realistic tumor microenvironment, thereby enabling drug compound and/or delivery vehicle screening. PMID:25599856

Additive Manufacturing of Biomedical Constructs with Biomimetic Structural Organizations.

PubMed

Li, Xiao; He, Jiankang; Zhang, Weijie; Jiang, Nan; Li, Dichen

2016-11-09

Additive manufacturing (AM), sometimes called three-dimensional (3D) printing, has attracted a lot of research interest and is presenting unprecedented opportunities in biomedical fields, because this technology enables the fabrication of biomedical constructs with great freedom and in high precision. An important strategy in AM of biomedical constructs is to mimic the structural organizations of natural biological organisms. This can be done by directly depositing cells and biomaterials, depositing biomaterial structures before seeding cells, or fabricating molds before casting biomaterials and cells. This review organizes the research advances of AM-based biomimetic biomedical constructs into three major directions: 3D constructs that mimic tubular and branched networks of vasculatures; 3D constructs that contains gradient interfaces between different tissues; and 3D constructs that have different cells positioned to create multicellular systems. Other recent advances are also highlighted, regarding the applications of AM for organs-on-chips, AM-based micro/nanostructures, and functional nanomaterials. Under this theme, multiple aspects of AM including imaging/characterization, material selection, design, and printing techniques are discussed. The outlook at the end of this review points out several possible research directions for the future.

Personalized targeted therapy for esophageal squamous cell carcinoma

PubMed Central

Kang, Xiaozheng; Chen, Keneng; Li, Yicheng; Li, Jianying; D'Amico, Thomas A; Chen, Xiaoxin

2015-01-01

Esophageal squamous cell carcinoma continues to heavily burden clinicians worldwide. Researchers have discovered the genomic landscape of esophageal squamous cell carcinoma, which holds promise for an era of personalized oncology care. One of the most pressing problems facing this issue is to improve the understanding of the newly available genomic data, and identify the driver-gene mutations, pathways, and networks. The emergence of a legion of novel targeted agents has generated much hope and hype regarding more potent treatment regimens, but the accuracy of drug selection is still arguable. Other problems, such as cancer heterogeneity, drug resistance, exceptional responders, and side effects, have to be surmounted. Evolving topics in personalized oncology, such as interpretation of genomics data, issues in targeted therapy, research approaches for targeted therapy, and future perspectives, will be discussed in this editorial. PMID:26167067

Cell-based assays in GPCR drug discovery.

PubMed

Siehler, Sandra

2008-04-01

G protein-coupled receptors (GPCRs) transmit extracellular signals into the intracellular space, and play key roles in the physiological regulation of virtually every cell and tissue. Characteristic for the GPCR superfamily of cell surface receptors are their seven transmembrane-spanning alpha-helices, an extracellular N terminus and intracellular C-terminal tail. Besides transmission of extracellular signals, their activity is modulated by cellular signals in an auto- or transregulatory fashion. The molecular complexity of GPCRs and their regulated signaling networks triggered the interest in academic research groups to explore them further, and their drugability and role in pathophysiology triggers pharmaceutical research towards small molecular weight ligands and therapeutic antibodies. About 30% of marketed drugs target GPCRs, which underlines the importance of this target class. This review describes current and emerging cellular assays for the ligand discovery of GPCRs.

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

A postdoctoral position is available in Dr. Efsun Arda’s Developmental Genomics Group within the Laboratory of Receptor Biology and Gene Expression Branch at the National Cancer Institute (NCI), National Institutes of Health (NIH). Our research is focused on understanding the regulatory networks that govern pancreas cell identity and function in the context of diabetes and cancer. The lab is highly interdisciplinary and uses state-of-the-art technologies to address outstanding questions in human pancreas biology. The appointment is renewed annually upon performance evaluation for a maximum of five years. The candidate will be fully funded by a competitive intramural Center for Cancer Research (CCR) fellowship. Other fellowship opportunities outside NIH are also available and applications will be supported. CCR provides a highly collaborative, enabling environment for research fellows with more than 40 core facilities ranging from bioinformatics and computing, chemistry and structural biology, flow cytometry, genomics, imaging and microscopy, pharmacology, proteomics and single cell analysis.

Large-size, high-uniformity, random silver nanowire networks as transparent electrodes for crystalline silicon wafer solar cells.

PubMed

Xie, Shouyi; Ouyang, Zi; Jia, Baohua; Gu, Min

2013-05-06

Metal nanowire networks are emerging as next generation transparent electrodes for photovoltaic devices. We demonstrate the application of random silver nanowire networks as the top electrode on crystalline silicon wafer solar cells. The dependence of transmittance and sheet resistance on the surface coverage is measured. Superior optical and electrical properties are observed due to the large-size, highly-uniform nature of these networks. When applying the nanowire networks on the solar cells with an optimized two-step annealing process, we achieved as large as 19% enhancement on the energy conversion efficiency. The detailed analysis reveals that the enhancement is mainly caused by the improved electrical properties of the solar cells due to the silver nanowire networks. Our result reveals that this technology is a promising alternative transparent electrode technology for crystalline silicon wafer solar cells.

Cell Assembly Dynamics of Sparsely-Connected Inhibitory Networks: A Simple Model for the Collective Activity of Striatal Projection Neurons.

PubMed

Angulo-Garcia, David; Berke, Joshua D; Torcini, Alessandro

2016-02-01

Striatal projection neurons form a sparsely-connected inhibitory network, and this arrangement may be essential for the appropriate temporal organization of behavior. Here we show that a simplified, sparse inhibitory network of Leaky-Integrate-and-Fire neurons can reproduce some key features of striatal population activity, as observed in brain slices. In particular we develop a new metric to determine the conditions under which sparse inhibitory networks form anti-correlated cell assemblies with time-varying activity of individual cells. We find that under these conditions the network displays an input-specific sequence of cell assembly switching, that effectively discriminates similar inputs. Our results support the proposal that GABAergic connections between striatal projection neurons allow stimulus-selective, temporally-extended sequential activation of cell assemblies. Furthermore, we help to show how altered intrastriatal GABAergic signaling may produce aberrant network-level information processing in disorders such as Parkinson's and Huntington's diseases.

Secretory granule formation and membrane recycling by the trans-Golgi network in adipokinetic cells of Locusta migratoria in relation to flight and rest.

PubMed

Diederen, J H; Vullings, H G

1995-03-01

The influence of flight activity on the formation of secretory granules and the concomitant membrane recycling by the trans-Golgi network in the peptidergic neurosecretory adipokinetic cells of Locusta migratoria was investigated by means of ultrastructural morphometric methods. The patterns of labelling of the trans-Golgi network by the exogenous adsorptive endocytotic tracer wheat-germ agglutinin-conjugated horse-radish peroxidase and by the endogenous marker enzyme acid phosphatase were used as parameters and were measured by an automatic image analysis system. The results show that endocytosed fragments of plasma membrane with bound peroxidase label were transported to the trans-Golgi network and used to build new secretory granules. The amounts of peroxidase and especially of acid phosphatase within the trans-Golgi network showed a strong tendency to be smaller in flight-stimulated cells than in non-stimulated cells. The amounts of acid phosphatase in the immature secretory granules originating from the trans-Golgi network were significantly smaller in stimulated cells. The number of immature secretory granules positive for acid phosphatase tended to be higher in stimulated cells. Thus, flight stimulation of adipokinetic cells for 1 h influences the functioning of the trans-Golgi network; this most probably results in a slight enhancement of the production of secretory granules by the trans-Golgi network.

Bitter gourd (Momordica charantia) as a rich source of bioactive components to combat cancer naturally: Are we on the right track to fully unlock its potential as inhibitor of deregulated signaling pathways.

PubMed

Farooqi, Ammad Ahmad; Khalid, Sumbul; Tahir, Fatima; Sabitaliyevich, Uteuliev Yerzhan; Yaylim, Ilhan; Attar, Rukset; Xu, Baojun

2018-05-10

Research over decades has progressively explored pharmacological actions of bitter gourd (Momordica charantia). Biologically and pharmacologically active molecules isolated from M. charantia have shown significant anti-cancer activity in cancer cell lines and xenografted mice. In this review spotlight was set on the bioactive compounds isolated from M. charantia that effectively inhibited cancer development and progression via regulation of protein network in cancer cells. We summarize most recent high-quality research work in cancer cell lines and xenografted mice related to tumor suppressive role-play of M. charantia and its bioactive compounds. Although M. charantia mediated health promoting, anti-diabetic, hepatoprotective, anti-inflammatory effects have been extensively investigated, there is insufficient information related to regulation of signaling networks by bioactive molecules obtained from M. charantia in different cancers. M. charantia has been shown to modulate AKT/mTOR/p70S6K signaling, p38MAPK-MAPKAPK-2/HSP-27 pathway, cell cycle regulatory proteins and apoptosis-associated proteins in different cancers. However, still there are visible knowledge gaps related to the drug targets in different cancers because we have not yet developed comprehensive understanding of the M. charantia mediated regulation of signal transduction pathways. To explore these questions, experimental platforms are needed that can prove to be helpful in getting a step closer to personalized medicine. Copyright © 2018 Elsevier Ltd. All rights reserved.

Plant stem cell niches.

PubMed

Aichinger, Ernst; Kornet, Noortje; Friedrich, Thomas; Laux, Thomas

2012-01-01

Multicellular organisms possess pluripotent stem cells to form new organs, replenish the daily loss of cells, or regenerate organs after injury. Stem cells are maintained in specific environments, the stem cell niches, that provide signals to block differentiation. In plants, stem cell niches are situated in the shoot, root, and vascular meristems-self-perpetuating units of organ formation. Plants' lifelong activity-which, as in the case of trees, can extend over more than a thousand years-requires that a robust regulatory network keep the balance between pluripotent stem cells and differentiating descendants. In this review, we focus on current models in plant stem cell research elaborated during the past two decades, mainly in the model plant Arabidopsis thaliana. We address the roles of mobile signals on transcriptional modules involved in balancing cell fates. In addition, we discuss shared features of and differences between the distinct stem cell niches of Arabidopsis.

Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks

NASA Astrophysics Data System (ADS)

Liu, Jun; Wang, Gang; Duan, Ling-Yu; Abdiyeva, Kamila; Kot, Alex C.

2018-04-01

Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, Long Short-Term Memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynamics in sequential data. As not all skeletal joints are informative for action recognition, and the irrelevant joints often bring noise which can degrade the performance, we need to pay more attention to the informative ones. However, the original LSTM network does not have explicit attention ability. In this paper, we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for skeleton based action recognition. This network is capable of selectively focusing on the informative joints in each frame of each skeleton sequence by using a global context memory cell. To further improve the attention capability of our network, we also introduce a recurrent attention mechanism, with which the attention performance of the network can be enhanced progressively. Moreover, we propose a stepwise training scheme in order to train our network effectively. Our approach achieves state-of-the-art performance on five challenging benchmark datasets for skeleton based action recognition.

The cerebellar Golgi cell and spatiotemporal organization of granular layer activity

PubMed Central

D'Angelo, Egidio; Solinas, Sergio; Mapelli, Jonathan; Gandolfi, Daniela; Mapelli, Lisa; Prestori, Francesca

2013-01-01

The cerebellar granular layer has been suggested to perform a complex spatiotemporal reconfiguration of incoming mossy fiber signals. Central to this role is the inhibitory action exerted by Golgi cells over granule cells: Golgi cells inhibit granule cells through both feedforward and feedback inhibitory loops and generate a broad lateral inhibition that extends beyond the afferent synaptic field. This characteristic connectivity has recently been investigated in great detail and been correlated with specific functional properties of these neurons. These include theta-frequency pacemaking, network entrainment into coherent oscillations and phase resetting. Important advances have also been made in terms of determining the membrane and synaptic properties of the neuron, and clarifying the mechanisms of activation by input bursts. Moreover, voltage sensitive dye imaging and multi-electrode array (MEA) recordings, combined with mathematical simulations based on realistic computational models, have improved our understanding of the impact of Golgi cell activity on granular layer circuit computations. These investigations have highlighted the critical role of Golgi cells in: generating dense clusters of granule cell activity organized in center-surround structures, implementing combinatorial operations on multiple mossy fiber inputs, regulating transmission gain, and cut-off frequency, controlling spike timing and burst transmission, and determining the sign, intensity and duration of long-term synaptic plasticity at the mossy fiber-granule cell relay. This review considers recent advances in the field, highlighting the functional implications of Golgi cells for granular layer network computation and indicating new challenges for cerebellar research. PMID:23730271

Reproductive Toxicity of T Cells in Early Life: Abnormal Immune Development and Postnatal Diseases.

PubMed

Liu, Han-Xiao; Jiang, Aifang; Chen, Ting; Qu, Wen; Yan, Hui-Yi; Ping, Jie

2017-01-01

Immunity is a balanced status with adequate biological defenses to recognize and fight "non-self", as well as adequate tolerance to recognize "self". To maintain this immune homeostasis, a well-organized T cell immune network is required, which in part depends on the well-controlled development of alternative effector T cells, with different cytokine repertoires. Recent researches have pointed that developing fetal T cells network is a remarkably sensitive toxicological target for adverse factors in early life. Epidemiological and experimental studies showed an inseparable relationship between T cell developmental toxicity and immune diseases in adults. Considering that the inflammatory and immune disorders have become a growing health problem worldwide, increasing attention is now being paid to the T cell developmental toxicity. We propose that adverse factors may have programming effects on the crucial functions of immune system during early life which is critical for fetal T cell development and the establishment of the distinct T cell repertoires balance. The permanently disturbed intrathymic or peripheral T cell development may in turn lead to the immune disorders in later life. In this manuscript, we reviewed how adverse factors affected T cell development in early-life with the consequence of the immune dysfunction and immune diseases, and further elucidate the mechanisms. These mechanisms will be helpful in prevention and treatment of the increased prevalence of immune diseases by interfering those pathways. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A new bio-inspired stimulator to suppress hyper-synchronized neural firing in a cortical network.

PubMed

Amiri, Masoud; Amiri, Mahmood; Nazari, Soheila; Faez, Karim

2016-12-07

Hyper-synchronous neural oscillations are the character of several neurological diseases such as epilepsy. On the other hand, glial cells and particularly astrocytes can influence neural synchronization. Therefore, based on the recent researches, a new bio-inspired stimulator is proposed which basically is a dynamical model of the astrocyte biophysical model. The performance of the new stimulator is investigated on a large-scale, cortical network. Both excitatory and inhibitory synapses are also considered in the simulated spiking neural network. The simulation results show that the new stimulator has a good performance and is able to reduce recurrent abnormal excitability which in turn avoids the hyper-synchronous neural firing in the spiking neural network. In this way, the proposed stimulator has a demand controlled characteristic and is a good candidate for deep brain stimulation (DBS) technique to successfully suppress the neural hyper-synchronization. Copyright © 2016 Elsevier Ltd. All rights reserved.

Systematic identification and comparison of expressed profiles of lncRNAs and circRNAs with associated co-expression and ceRNA networks in mouse germline stem cells

PubMed Central

Wu, Ji

2017-01-01

Accumulating evidence indicates that long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) involve in germ cell development. However, little is known about the functions and mechanisms of lncRNAs and circRNAs in self-renewal and differentiation of germline stem cells. Therefore, we explored the expression profiles of mRNAs, lncRNAs, and circRNAs in male and female mouse germline stem cells by high-throughput sequencing. We identified 18573 novel lncRNAs and 18822 circRNAs in the germline stem cells and further confirmed the existence of these lncRNAs and circRNAs by RT-PCR. The results showed that male and female germline stem cells had similar GDNF signaling mechanism. Subsequently, 8115 mRNAs, 3996 lncRNAs, and 921 circRNAs exhibited sex-biased expression that may be associated with germline stem cell acquisition of the sex-specific properties required for differentiation into gametes. Gene Ontology (GO) and KEGG pathway enrichment analyses revealed different functions for these sex-biased lncRNAs and circRNAs. We further constructed correlated expression networks including coding–noncoding co-expression and competing endogenous RNAs with bioinformatics. Co-expression analysis showed hundreds of lncRNAs were correlated with sex differences in mouse germline stem cells, including lncRNA Gm11851, lncRNA Gm12840, lncRNA 4930405O22Rik, and lncRNA Atp10d. CeRNA network inferred that lncRNA Meg3 and cirRNA Igf1r could bind competitively with miRNA-15a-5p increasing target gene Inha, Acsl3, Kif21b, and Igfbp2 expressions. These findings provide novel perspectives on lncRNAs and circRNAs and lay a foundation for future research into the regulating mechanisms of lncRNAs and circRNAs in germline stem cells. PMID:28404936

An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions

USGS Publications Warehouse

Stanislawski, Larry V.; Survila, Kornelijus; Wendel, Jeffrey; Liu, Yan; Buttenfield, Barbara P.

2018-01-01

This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utility of open source tools with parallel computing support for extracting connected drainage network patterns and handling depressions in 30 subbasins distributed across humid, dry, and transitional climate regions and in terrain conditions exhibiting a range of slopes. Special attention is given to low-slope terrain, where network connectivity is preserved by generating synthetic stream channels through lake and waterbody polygons. Conflation analysis compares the extracted streams with a 1:24,000-scale National Hydrography Dataset flowline network and shows that similarities are greatest for second- and higher-order tributaries.

SLC9A9 Co-expression modules in autism-associated brain regions.

PubMed

Patak, Jameson; Hess, Jonathan L; Zhang-James, Yanli; Glatt, Stephen J; Faraone, Stephen V

2017-03-01

SLC9A9 is a sodium hydrogen exchanger present in the recycling endosome and highly expressed in the brain. It is implicated in neuropsychiatric disorders, including autism spectrum disorders (ASDs). Little research concerning its gene expression patterns and biological pathways has been conducted. We sought to investigate its possible biological roles in autism-associated brain regions throughout development. We conducted a weighted gene co-expression network analysis on RNA-seq data downloaded from Brainspan. We compared prenatal and postnatal gene expression networks for three ASD-associated brain regions known to have high SLC9A9 gene expression. We also performed an ASD-associated single nucleotide polymorphism enrichment analysis and a cell signature enrichment analysis. The modules showed differences in gene constituents (membership), gene number, and connectivity throughout time. SLC9A9 was highly associated with immune system functions, metabolism, apoptosis, endocytosis, and signaling cascades. Gene list comparison with co-immunoprecipitation data was significant for multiple modules. We found a disproportionately high autism risk signal among genes constituting the prenatal hippocampal module. The modules were enriched with astrocyte and oligodendrocyte markers. SLC9A9 is potentially involved in the pathophysiology of ASDs. Our investigation confirmed proposed functions for SLC9A9, such as endocytosis and immune regulation, while also revealing potential roles in mTOR signaling and cell survival.. By providing a concise molecular map and interactions, evidence of cell type and implicated brain regions we hope this will guide future research on SLC9A9. Autism Res 2017, 10: 414-429. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Transcriptional Regulatory Networks in Saccharomyces cerevisiae

NASA Astrophysics Data System (ADS)

Lee, Tong Ihn; Rinaldi, Nicola J.; Robert, François; Odom, Duncan T.; Bar-Joseph, Ziv; Gerber, Georg K.; Hannett, Nancy M.; Harbison, Christopher T.; Thompson, Craig M.; Simon, Itamar; Zeitlinger, Julia; Jennings, Ezra G.; Murray, Heather L.; Gordon, D. Benjamin; Ren, Bing; Wyrick, John J.; Tagne, Jean-Bosco; Volkert, Thomas L.; Fraenkel, Ernest; Gifford, David K.; Young, Richard A.

2002-10-01

We have determined how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells. Just as maps of metabolic networks describe the potential pathways that may be used by a cell to accomplish metabolic processes, this network of regulator-gene interactions describes potential pathways yeast cells can use to regulate global gene expression programs. We use this information to identify network motifs, the simplest units of network architecture, and demonstrate that an automated process can use motifs to assemble a transcriptional regulatory network structure. Our results reveal that eukaryotic cellular functions are highly connected through networks of transcriptional regulators that regulate other transcriptional regulators.

Network models provide insights into how oriens–lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations

PubMed Central

Ferguson, Katie A.; Huh, Carey Y. L.; Amilhon, Bénédicte; Manseau, Frédéric; Williams, Sylvain; Skinner, Frances K.

2015-01-01

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 how the number of OLM-BiC connections and connection strength affected local theta power. We found that our models operate in regimes that could be distinguished by whether 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 resulting power of network theta oscillations. Overall, our network models reveal a dynamic interplay between different classes of interneurons in influencing local theta power. PMID:26300744

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

Zhang Bo; Huang Bo; School of Public Health, University of South China, Hengyang, Hunan 421001

Mitotic catastrophe, a form of cell death resulting from abnormal mitosis, is a cytotoxic death pathway as well as an appealing mechanistic strategy for the development of anti-cancer drugs. In this study, 6-bromine-5-hydroxy-4-methoxybenzaldehyde was demonstrated to induce DNA double-strand break, multipolar spindles, sustain mitotic arrest and generate multinucleated cells, all of which indicate mitotic catastrophe, in human hepatoma HepG2 cells. We used proteomic profiling to identify the differentially expressed proteins underlying mitotic catastrophe. A total of 137 differentially expressed proteins (76 upregulated and 61 downregulated proteins) were identified. Some of the changed proteins have previously been associated with mitotic catastrophe,more » such as DNA-PKcs, FoxM1, RCC1, cyclin E, PLK1-pT210, 14-3-3{sigma} and HSP70. Multiple isoforms of 14-3-3, heat-shock proteins and tubulin were upregulated. Analysis of functional significance revealed that the 14-3-3-mediated signaling network was the most significantly enriched for the differentially expressed proteins. The modulated proteins were found to be involved in macromolecule complex assembly, cell death, cell cycle, chromatin remodeling and DNA repair, tubulin and cytoskeletal organization. These findings revealed the overall molecular events and functional signaling networks associated with spindle disruption and mitotic catastrophe. - Graphical abstract: Display Omitted Research highlights: > 6-bromoisovanillin induced spindle disruption and sustained mitotic arrest, consequently resulted in mitotic catastrophe. > Proteomic profiling identified 137 differentially expressed proteins associated mitotic catastrophe. > The 14-3-3-mediated signaling network was the most significantly enriched for the altered proteins. > The macromolecule complex assembly, cell cycle, chromatin remodeling and DNA repair, tubulin organization were also shown involved in mitotic catastrophe.« less

Connectivity of Multi-Channel Fluvial Systems: A Comparison of Topology Metrics for Braided Rivers and Delta Networks

NASA Astrophysics Data System (ADS)

Tejedor, A.; Marra, W. A.; Addink, E. A.; Foufoula-Georgiou, E.; Kleinhans, M. G.

2016-12-01

Advancing quantitative understanding of the structure and dynamics of complex networks has transformed research in many fields as diverse as protein interactions in a cell to page connectivity in the World Wide Web and relationships in human societies. However, Geosciences have not benefited much from this new conceptual framework, although connectivity is at the center of many processes in hydro-geomorphology. One of the first efforts in this direction was the seminal work of Smart and Moruzzi (1971), proposing the use of graph theory for studying the intricate structure of delta channel networks. In recent years, this preliminary work has precipitated in a body of research that examines the connectivity of multiple-channel fluvial systems, such as delta networks and braided rivers. In this work, we compare two approaches recently introduced in the literature: (1) Marra et al. (2014) utilized network centrality measures to identify important channels in a braided section of the Jamuna River, and used the changes of bifurcations within the network over time to explain the overall river evolution; and (2) Tejedor et al. (2015a,b) developed a set of metrics to characterize the complexity of deltaic channel networks, as well as defined a vulnerability index that quantifies the relative change of sediment and water delivery to the shoreline outlets in response to upstream perturbations. Here we present a comparative analysis of metrics of centrality and vulnerability applied to both braided and deltaic channel networks to depict critical channels in those systems, i.e., channels where a change would contribute more substantially to overall system changes, and to understand what attributes of interest in a channel network are most succinctly depicted in what metrics. Marra, W. A., Kleinhans, M. G., & Addink, E. A. (2014). Earth Surface Processes and Landforms, doi:10.1002/esp.3482Smart, J. S., and V. L. Moruzzi (1971), Quantitative properties of delta channel networks, Tech. Rep. 3, 27 pp., IBM Thomas J. Watson Res. Cent., Yorktown, NYTejedor, A., Longjas, A., Zaliapin, I., & Foufoula-Georgiou, E. (2015a/b). Water Resources Research, doi:10.1002/2014WR016259 & doi:10.1002/2014WR016604

A synthetic mammalian network to compute population borders based on engineered reciprocal cell-cell communication.

PubMed

Kolar, Katja; Wischhusen, Hanna M; Müller, Konrad; Karlsson, Maria; Weber, Wilfried; Zurbriggen, Matias D

2015-12-30

Multicellular organisms depend on the exchange of information between specialized cells. This communication is often difficult to decipher in its native context, but synthetic biology provides tools to engineer well-defined systems that allow the convenient study and manipulation of intercellular communication networks. Here, we present the first mammalian synthetic network for reciprocal cell-cell communication to compute the border between a sender/receiver and a processing cell population. The two populations communicate via L-tryptophan and interleukin-4 to highlight the population border by the production of a fluorescent protein. The sharpness of that visualized edge can be adjusted by modulating key parameters of the network. We anticipate that this network will on the one hand be a useful tool to gain deeper insights into the mechanisms of tissue formation in nature and will on the other hand contribute to our ability to engineer artificial tissues.

T-cell movement on the reticular network.

PubMed

Donovan, Graham M; Lythe, Grant

2012-02-21

The idea that the apparently random motion of T cells in lymph nodes is a result of movement on a reticular network (RN) has received support from dynamic imaging experiments and theoretical studies. We present a mathematical representation of the RN consisting of edges connecting vertices that are randomly distributed in three-dimensional space, and models of lymphocyte movement on such networks including constant speed motion along edges and Brownian motion, not in three-dimensions, but only along edges. The simplest model, in which a cell moves with a constant speed along edges, is consistent with mean-squared displacement proportional to time over intervals long enough to include several changes of direction. A non-random distribution of turning angles is one consequence of motion on a preformed network. Confining cell movement to a network does not, in itself, increase the frequency of cell-cell encounters. Copyright © 2011 Elsevier Ltd. All rights reserved.

Cell Fate Reprogramming by Control of Intracellular Network Dynamics

PubMed Central

Zañudo, Jorge G. T.; Albert, Réka

2015-01-01

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell’s fate, such as disease therapeutics and stem cell reprogramming. Here we develop a novel network control framework that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our approach drives any initial state to the target state with 100% effectiveness and needs to be applied only transiently for the network to reach and stay in the desired state. We illustrate our method’s potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of helper T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. PMID:25849586

Determining Regulatory Networks Governing the Differentiation of Embryonic Stem Cells to Pancreatic Lineage

NASA Astrophysics Data System (ADS)

Banerjee, Ipsita

2009-03-01

Knowledge of pathways governing cellular differentiation to specific phenotype will enable generation of desired cell fates by careful alteration of the governing network by adequate manipulation of the cellular environment. With this aim, we have developed a novel method to reconstruct the underlying regulatory architecture of a differentiating cell population from discrete temporal gene expression data. We utilize an inherent feature of biological networks, that of sparsity, in formulating the network reconstruction problem as a bi-level mixed-integer programming problem. The formulation optimizes the network topology at the upper level and the network connectivity strength at the lower level. The method is first validated by in-silico data, before applying it to the complex system of embryonic stem (ES) cell differentiation. This formulation enables efficient identification of the underlying network topology which could accurately predict steps necessary for directing differentiation to subsequent stages. Concurrent experimental verification demonstrated excellent agreement with model prediction.

Physiological β-catenin signaling controls self-renewal networks and generation of stem-like cells from nasopharyngeal carcinoma.

PubMed

Cheng, Yue; Cheung, Arthur Kwok Leung; Ko, Josephine Mun Yee; Phoon, Yee Peng; Chiu, Pui Man; Lo, Paulisally Hau Yi; Waterman, Marian L; Lung, Maria Li

2013-09-27

A few reports suggested that low levels of Wnt signaling might drive cell reprogramming, but these studies could not establish a clear relationship between Wnt signaling and self-renewal networks. There are ongoing debates as to whether and how the Wnt/β-catenin signaling is involved in the control of pluripotency gene networks. Additionally, whether physiological β-catenin signaling generates stem-like cells through interactions with other pathways is as yet unclear. The nasopharyngeal carcinoma HONE1 cells have low expression of β-catenin and wild-type expression of p53, which provided a possibility to study regulatory mechanism of stemness networks induced by physiological levels of Wnt signaling in these cells. Introduction of increased β-catenin signaling, haploid expression of β-catenin under control by its natural regulators in transferred chromosome 3, resulted in activation of Wnt/β-catenin networks and dedifferentiation in HONE1 hybrid cell lines, but not in esophageal carcinoma SLMT1 hybrid cells that had high levels of endogenous β-catenin expression. HONE1 hybrid cells displayed stem cell-like properties, including enhancement of CD24(+) and CD44(+) populations and generation of spheres that were not observed in parental HONE1 cells. Signaling cascades were detected in HONE1 hybrid cells, including activation of p53- and RB1-mediated tumor suppressor pathways, up-regulation of Nanog-, Oct4-, Sox2-, and Klf4-mediated pluripotency networks, and altered E-cadherin expression in both in vitro and in vivo assays. qPCR array analyses further revealed interactions of physiological Wnt/β-catenin signaling with other pathways such as epithelial-mesenchymal transition, TGF-β, Activin, BMPR, FGFR2, and LIFR- and IL6ST-mediated cell self-renewal networks. Using β-catenin shRNA inhibitory assays, a dominant role for β-catenin in these cellular network activities was observed. The expression of cell surface markers such as CD9, CD24, CD44, CD90, and CD133 in generated spheres was progressively up-regulated compared to HONE1 hybrid cells. Thirty-four up-regulated components of the Wnt pathway were identified in these spheres. Wnt/β-catenin signaling regulates self-renewal networks and plays a central role in the control of pluripotency genes, tumor suppressive pathways and expression of cancer stem cell markers. This current study provides a novel platform to investigate the interaction of physiological Wnt/β-catenin signaling with stemness transition networks.

Attractor Metabolic Networks

PubMed Central

De la Fuente, Ildefonso M.; Cortes, Jesus M.; Pelta, David A.; Veguillas, Juan

2013-01-01

Background The experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity. Methodology/Principal Findings In order to research the systemic mechanisms involved in the regulation of the cellular enzymatic activity we have studied different catalytic activities of a dissipative metabolic network under different external stimuli. The emergent biochemical data have been analysed using statistical mechanic tools, studying some macroscopic properties such as the global information and the energy of the system. We have also obtained an equivalent Hopfield network using a Boltzmann machine. Our main result shows that the dissipative metabolic network can behave as an attractor metabolic network. Conclusions/Significance We have found that the systemic enzymatic activities are governed by attractors with capacity to store functional metabolic patterns which can be correctly recovered from specific input stimuli. The network attractors regulate the catalytic patterns, modify the efficiency in the connection between the multienzymatic complexes, and stably retain these modifications. Here for the first time, we have introduced the general concept of attractor metabolic network, in which this dynamic behavior is observed. PMID:23554883

Stabilization of perturbed Boolean network attractors through compensatory interactions

PubMed Central

2014-01-01

Background Understanding and ameliorating the effects of network damage are of significant interest, due in part to the variety of applications in which network damage is relevant. For example, the effects of genetic mutations can cascade through within-cell signaling and regulatory networks and alter the behavior of cells, possibly leading to a wide variety of diseases. The typical approach to mitigating network perturbations is to consider the compensatory activation or deactivation of system components. Here, we propose a complementary approach wherein interactions are instead modified to alter key regulatory functions and prevent the network damage from triggering a deregulatory cascade. Results We implement this approach in a Boolean dynamic framework, which has been shown to effectively model the behavior of biological regulatory and signaling networks. We show that the method can stabilize any single state (e.g., fixed point attractors or time-averaged representations of multi-state attractors) to be an attractor of the repaired network. We show that the approach is minimalistic in that few modifications are required to provide stability to a chosen attractor and specific in that interventions do not have undesired effects on the attractor. We apply the approach to random Boolean networks, and further show that the method can in some cases successfully repair synchronous limit cycles. We also apply the methodology to case studies from drought-induced signaling in plants and T-LGL leukemia and find that it is successful in both stabilizing desired behavior and in eliminating undesired outcomes. Code is made freely available through the software package BooleanNet. Conclusions The methodology introduced in this report offers a complementary way to manipulating node expression levels. A comprehensive approach to evaluating network manipulation should take an "all of the above" perspective; we anticipate that theoretical studies of interaction modification, coupled with empirical advances, will ultimately provide researchers with greater flexibility in influencing system behavior. PMID:24885780

Emerging trends and new developments in regenerative medicine: a scientometric update (2000 - 2014).

PubMed

Chen, Chaomei; Dubin, Rachael; Kim, Meen Chul

2014-09-01

Our previous scientometric review of regenerative medicine provides a snapshot of the fast-growing field up to the end of 2011. The new review identifies emerging trends and new developments appearing in the literature of regenerative medicine based on relevant articles and reviews published between 2000 and the first month of 2014. Multiple datasets of publications relevant to regenerative medicine are constructed through topic search and citation expansion to ensure adequate coverage of the field. Networks of co-cited references representing the literature of regenerative medicine are constructed and visualized based on a combined dataset of 71,393 articles published between 2000 and 2014. Structural and temporal dynamics are identified in terms of most active topical areas and cited references. New developments are identified in terms of newly emerged clusters and research areas. Disciplinary-level patterns are visualized in dual-map overlays. While research in induced pluripotent stem cells remains the most prominent area in the field of regenerative medicine, research related to clinical and therapeutic applications in regenerative medicine has experienced a considerable growth. In addition, clinical and therapeutic developments in regenerative medicine have demonstrated profound connections with the induced pluripotent stem cell research and stem cell research in general. A rapid adaptation of graphene-based nanomaterials in regenerative medicine is evident. Both basic research represented by stem cell research and application-oriented research typically found in tissue engineering are now increasingly integrated in the scientometric landscape of regenerative medicine. Tissue engineering is an interdisciplinary field in its own right. Advances in multiple disciplines such as stem cell research and graphene research have strengthened the connections between tissue engineering and regenerative medicine.

Cellular network entropy as the energy potential in Waddington's differentiation landscape

PubMed Central

Banerji, Christopher R. S.; Miranda-Saavedra, Diego; Severini, Simone; Widschwendter, Martin; Enver, Tariq; Zhou, Joseph X.; Teschendorff, Andrew E.

2013-01-01

Differentiation is a key cellular process in normal tissue development that is significantly altered in cancer. Although molecular signatures characterising pluripotency and multipotency exist, there is, as yet, no single quantitative mark of a cellular sample's position in the global differentiation hierarchy. Here we adopt a systems view and consider the sample's network entropy, a measure of signaling pathway promiscuity, computable from a sample's genome-wide expression profile. We demonstrate that network entropy provides a quantitative, in-silico, readout of the average undifferentiated state of the profiled cells, recapitulating the known hierarchy of pluripotent, multipotent and differentiated cell types. Network entropy further exhibits dynamic changes in time course differentiation data, and in line with a sample's differentiation stage. In disease, network entropy predicts a higher level of cellular plasticity in cancer stem cell populations compared to ordinary cancer cells. Importantly, network entropy also allows identification of key differentiation pathways. Our results are consistent with the view that pluripotency is a statistical property defined at the cellular population level, correlating with intra-sample heterogeneity, and driven by the degree of signaling promiscuity in cells. In summary, network entropy provides a quantitative measure of a cell's undifferentiated state, defining its elevation in Waddington's landscape. PMID:24154593

B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis

PubMed Central

Towfic, Fadi; Gupta, Shakti; Honavar, Vasant; Subramaniam, Shankar

2012-01-01

The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Collectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG pathways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches (e.g., gene coexpression network alignment algorithms) in elucidating biochemical pathways involved in complex signaling events in cells. PMID:22917187

Functional Connectivity in Islets of Langerhans from Mouse Pancreas Tissue Slices

PubMed Central

Stožer, Andraž; Gosak, Marko; Dolenšek, Jurij; Perc, Matjaž; Marhl, Marko; Rupnik, Marjan Slak; Korošak, Dean

2013-01-01

We propose a network representation of electrically coupled beta cells in islets of Langerhans. Beta cells are functionally connected on the basis of correlations between calcium dynamics of individual cells, obtained by means of confocal laser-scanning calcium imaging in islets from acute mouse pancreas tissue slices. Obtained functional networks are analyzed in the light of known structural and physiological properties of islets. Focusing on the temporal evolution of the network under stimulation with glucose, we show that the dynamics are more correlated under stimulation than under non-stimulated conditions and that the highest overall correlation, largely independent of Euclidean distances between cells, is observed in the activation and deactivation phases when cells are driven by the external stimulus. Moreover, we find that the range of interactions in networks during activity shows a clear dependence on the Euclidean distance, lending support to previous observations that beta cells are synchronized via calcium waves spreading throughout islets. Most interestingly, the functional connectivity patterns between beta cells exhibit small-world properties, suggesting that beta cells do not form a homogeneous geometric network but are connected in a functionally more efficient way. Presented results provide support for the existing knowledge of beta cell physiology from a network perspective and shed important new light on the functional organization of beta cell syncitia whose structural topology is probably not as trivial as believed so far. PMID:23468610

Environmentally induced amplitude death and firing provocation in large-scale networks of neuronal systems

NASA Astrophysics Data System (ADS)

Pankratova, Evgeniya V.; Kalyakulina, Alena I.

2016-12-01

We study the dynamics of multielement neuronal systems taking into account both the direct interaction between the cells via linear coupling and nondiffusive cell-to-cell communication via common environment. For the cells exhibiting individual bursting behavior, we have revealed the dependence of the network activity on its scale. Particularly, we show that small-scale networks demonstrate the inability to maintain complicated oscillations: for a small number of elements in an ensemble, the phenomenon of amplitude death is observed. The existence of threshold network scales and mechanisms causing firing in artificial and real multielement neural networks, as well as their significance for biological applications, are discussed.

TPPII, MYBBP1A and CDK2 form a protein-protein interaction network.

PubMed

Nahálková, Jarmila; Tomkinson, Birgitta

2014-12-15

Tripeptidyl-peptidase II (TPPII) is an aminopeptidase with suggested regulatory effects on cell cycle, apoptosis and senescence. A protein-protein interaction study revealed that TPPII physically interacts with the tumor suppressor MYBBP1A and the cell cycle regulator protein CDK2. Mutual protein-protein interaction was detected between MYBBP1A and CDK2 as well. In situ Proximity Ligation Assay (PLA) using HEK293 cells overexpressing TPPII forming highly enzymatically active oligomeric complexes showed that the cytoplasmic interaction frequency of TPPII with MYBBP1A increased with the protein expression of TPPII and using serum-free cell growth conditions. A specific reversible inhibitor of TPPII, butabindide, suppressed the cytoplasmic interactions of TPPII and MYBBP1A both in control HEK293 and the cells overexpressing murine TPPII. The interaction of MYBBP1A with CDK2 was confirmed by in situ PLA in two different mammalian cell lines. Functional link between TPPII and MYBBP1A has been verified by gene expression study during anoikis, where overexpression of TPP II decreased mRNA expression level of MYBBP1A at the cell detachment conditions. All three interacting proteins TPPII, MYBBP1A and CDK2 have been previously implicated in the research for development of tumor-suppressing agents. This is the first report presenting mutual protein-protein interaction network of these proteins. Copyright © 2014 Elsevier Inc. All rights reserved.

The founding charter of the Genomic Observatories Network.

PubMed

Davies, Neil; Field, Dawn; Amaral-Zettler, Linda; Clark, Melody S; Deck, John; Drummond, Alexei; Faith, Daniel P; Geller, Jonathan; Gilbert, Jack; Glöckner, Frank Oliver; Hirsch, Penny R; Leong, Jo-Ann; Meyer, Chris; Obst, Matthias; Planes, Serge; Scholin, Chris; Vogler, Alfried P; Gates, Ruth D; Toonen, Rob; Berteaux-Lecellier, Véronique; Barbier, Michèle; Barker, Katherine; Bertilsson, Stefan; Bicak, Mesude; Bietz, Matthew J; Bobe, Jason; Bodrossy, Levente; Borja, Angel; Coddington, Jonathan; Fuhrman, Jed; Gerdts, Gunnar; Gillespie, Rosemary; Goodwin, Kelly; Hanson, Paul C; Hero, Jean-Marc; Hoekman, David; Jansson, Janet; Jeanthon, Christian; Kao, Rebecca; Klindworth, Anna; Knight, Rob; Kottmann, Renzo; Koo, Michelle S; Kotoulas, Georgios; Lowe, Andrew J; Marteinsson, Viggó Thór; Meyer, Folker; Morrison, Norman; Myrold, David D; Pafilis, Evangelos; Parker, Stephanie; Parnell, John Jacob; Polymenakou, Paraskevi N; Ratnasingham, Sujeevan; Roderick, George K; Rodriguez-Ezpeleta, Naiara; Schonrogge, Karsten; Simon, Nathalie; Valette-Silver, Nathalie J; Springer, Yuri P; Stone, Graham N; Stones-Havas, Steve; Sansone, Susanna-Assunta; Thibault, Kate M; Wecker, Patricia; Wichels, Antje; Wooley, John C; Yahara, Tetsukazu; Zingone, Adriana

2014-03-07

The co-authors of this paper hereby state their intention to work together to launch the Genomic Observatories Network (GOs Network) for which this document will serve as its Founding Charter. We define a Genomic Observatory as an ecosystem and/or site subject to long-term scientific research, including (but not limited to) the sustained study of genomic biodiversity from single-celled microbes to multicellular organisms.An international group of 64 scientists first published the call for a global network of Genomic Observatories in January 2012. The vision for such a network was expanded in a subsequent paper and developed over a series of meetings in Bremen (Germany), Shenzhen (China), Moorea (French Polynesia), Oxford (UK), Pacific Grove (California, USA), Washington (DC, USA), and London (UK). While this community-building process continues, here we express our mutual intent to establish the GOs Network formally, and to describe our shared vision for its future. The views expressed here are ours alone as individual scientists, and do not necessarily represent those of the institutions with which we are affiliated.

Sign: large-scale gene network estimation environment for high performance computing.

PubMed

Tamada, Yoshinori; Shimamura, Teppei; Yamaguchi, Rui; Imoto, Seiya; Nagasaki, Masao; Miyano, Satoru

2011-01-01

Our research group is currently developing software for estimating large-scale gene networks from gene expression data. The software, called SiGN, is specifically designed for the Japanese flagship supercomputer "K computer" which is planned to achieve 10 petaflops in 2012, and other high performance computing environments including Human Genome Center (HGC) supercomputer system. SiGN is a collection of gene network estimation software with three different sub-programs: SiGN-BN, SiGN-SSM and SiGN-L1. In these three programs, five different models are available: static and dynamic nonparametric Bayesian networks, state space models, graphical Gaussian models, and vector autoregressive models. All these models require a huge amount of computational resources for estimating large-scale gene networks and therefore are designed to be able to exploit the speed of 10 petaflops. The software will be available freely for "K computer" and HGC supercomputer system users. The estimated networks can be viewed and analyzed by Cell Illustrator Online and SBiP (Systems Biology integrative Pipeline). The software project web site is available at http://sign.hgc.jp/ .

The founding charter of the Genomic Observatories Network

PubMed Central

2014-01-01

The co-authors of this paper hereby state their intention to work together to launch the Genomic Observatories Network (GOs Network) for which this document will serve as its Founding Charter. We define a Genomic Observatory as an ecosystem and/or site subject to long-term scientific research, including (but not limited to) the sustained study of genomic biodiversity from single-celled microbes to multicellular organisms. An international group of 64 scientists first published the call for a global network of Genomic Observatories in January 2012. The vision for such a network was expanded in a subsequent paper and developed over a series of meetings in Bremen (Germany), Shenzhen (China), Moorea (French Polynesia), Oxford (UK), Pacific Grove (California, USA), Washington (DC, USA), and London (UK). While this community-building process continues, here we express our mutual intent to establish the GOs Network formally, and to describe our shared vision for its future. The views expressed here are ours alone as individual scientists, and do not necessarily represent those of the institutions with which we are affiliated. PMID:24606731

Charge Recombination, Transport Dynamics, and Interfacial Effects in Organic Solar Cells

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

Heeger, Alan; Bazan, Guillermo; Nguyen, Thuc-Quyen

The need for renewable sources of energy is well known. Conversion of sunlight to electricity using solar cells is one of the most important opportunities for creating renewable energy sources. The research carried out under DE-FG02-08ER46535 focused on the science and technology of “Plastic” solar cells comprised of organic (i.e. carbon based) semiconductors. The Bulk Heterojunction concept involves a phase separated blend of two organic semiconductors each with dimensions in the nano-meter length scale --- one a material that functions as a donor for electrons and the other a material that functions as an acceptor for electrons. The nano-scale inter-penetratingmore » network concept for “Plastic” solar cells was created at UC Santa Barbara. A simple measure of the impact of this concept can be obtained from a Google search which gives 244,000 “hits” for the Bulk Heterojunction solar cell. Research funded through this program focused on four major areas: 1. Interfacial effects in organic photovoltaics, 2. Charge transfer and photogeneration of mobile charge carriers in organic photovoltaics, 3. Transport and recombination of the photogenerated charge carriers in organic photovoltaics, 4. Synthesis of novel organic semiconducting polymers and semiconducting small molecules, including conjugated polyelectrolytes. Following the discovery of ultrafast charge transfer at UC Santa Barbara in 1992, the nano-organic (Bulk Heterojunction) concept was formulated. The need for a morphology comprising two interpenetrating bicontinuous networks was clear: one network to carry the photogenerated electrons (negative charge) to the cathode and one network to carry the photo-generated holes (positive charge) to the anode. This remarkable self-assembled network morphology has now been established using Transmission electron Microscopy (TEM) either in the Phase Contrast mode or via TEM-Tomography. The steps involved in delivering power from a solar cell to an external circuit are the following: • Photo-excitation of the donor (or the acceptor). • Charge transfer with holes in the donor domain and electrons in the acceptor domain. • Sweep-out to electrodes prior to recombination by the internal electric field. • Energy delivered to the external circuit. Each of these four steps was studied in detail using a wide variety of organic semiconductors with different molecular structures. This UC Santa Barbara group was the first to clarify the origin and the mechanism involved in the ultrafast charge transfer process. The ultrafast charge transfer (time scale approximately 100 times faster than the first step in the photo-synthesis of green plants) is the fundamental reason for the potential for high power conversion efficiency of sunlight to electricity from plastic solar cells. The UCSB group was the first to emphasize, clarify and demonstrate the need for sweep-out to electrodes prior to recombination by the internal electric field. The UCSB group was the first to synthesize small molecule organic semiconductors capable of high power conversion efficiencies. The results of this research were published in high impact peer-reviewed journals. Our published papers (40 in number) provide answers to fundamental questions that have been heavily discussed and debated in the field of Bulk Heterojunction Solar Cells; scientific questions that must be resolved before this technology can be ready for commercialization in large scale for production of renewable energy. Of the forty publications listed, nineteen were co-authored by two or more of the PIs, consistent with the multi-investigator approach described in the original proposal. The specific advantages of this “plastic” solar cell technology are the following: a. Manufacturing by low-cost printing technology using soluble organic semiconductors; this approach can be implemented in large scale by roll-to-roll printing on plastic substrates. b. Low energy cost in manufacturing; all steps carried out at room temperature (approx. a factor of ten less than the use of Silicon which requires high temperature processing). c. Low carbon footprint d. Lightweight, flexible and rugged Because of the resolution of many scientific issues, a significant fraction of which were addressed in the research results of DE-FG02-08ER46535, the power conversion efficiencies are improving at an ever increasing rate. During the funding period of DE-FG02-08ER46535, the power conversion efficiencies of plastic solar cells improved from just a few per cent to values greater than 11% with contributions from our group and from researchers all over the world.« less

Nonlinear Dynamic Theory of Acute Cell Injuries and Brain Ischemia

NASA Astrophysics Data System (ADS)

Taha, Doaa; Anggraini, Fika; Degracia, Donald; Huang, Zhi-Feng

2015-03-01

Cerebral ischemia in the form of stroke and cardiac arrest brain damage affect over 1 million people per year in the USA alone. In spite of close to 200 clinical trials and decades of research, there are no treatments to stop post-ischemic neuron death. We have argued that a major weakness of current brain ischemia research is lack of a deductive theoretical framework of acute cell injury to guide empirical studies. A previously published autonomous model based on the concept of nonlinear dynamic network was shown to capture important facets of cell injury, linking the concept of therapeutic to bistable dynamics. Here we present an improved, non-autonomous formulation of the nonlinear dynamic model of cell injury that allows multiple acute injuries over time, thereby allowing simulations of both therapeutic treatment and preconditioning. Our results are connected to the experimental data of gene expression and proteomics of neuron cells. Importantly, this new model may be construed as a novel approach to pharmacodynamics of acute cell injury. The model makes explicit that any pro-survival therapy is always a form of sub-lethal injury. This insight is expected to widely influence treatment of acute injury conditions that have defied successful treatment to date. This work is supported by NIH NINDS (NS081347) and Wayne State University President's Research Enhancement Award.

Intercellular communication via gap junctions affected by mechanical load in the bovine annulus fibrosus.

PubMed

Desrochers, Jane; Duncan, Neil A

2014-01-01

Cells in the intervertebral disc, as in other connective tissues including tendon, ligament and bone, form interconnected cellular networks that are linked via functional gap junctions. These cellular networks may be necessary to affect a coordinated response to mechanical and environmental stimuli. Using confocal microscopy with fluorescence recovery after photobleaching methods, we explored the in situ strain environment of the outer annulus of an intact bovine disc and the effect of high-level flexion on gap junction signalling. The in situ strain environment in the extracellular matrix of the outer annulus under high flexion load was observed to be non-uniform with the extensive cellular processes remaining crimped sometimes at flexion angles greater than 25°. A significant transient disruption of intercellular communication via functional gap junctions was measured after 10 and 20 min under high flexion load. This study illustrates that in healthy annulus fibrosus tissue, high mechanical loads can impede the functioning of the gap junctions. Future studies will explore more complex loading conditions to determine whether losses in intercellular communication can be permanent and whether gap junctions in aged and degenerated tissues become more susceptible to load. The current research suggests that cellular structures such as gap junctions and intercellular networks, as well as other cell-cell and cell-matrix interconnections, need to be considered in computational models in order to fully understand how macroscale mechanical signals are transmitted across scales to the microscale and ultimately into a cellular biosynthetic response in collagenous tissues.

IRE1: ER stress sensor and cell fate executor

PubMed Central

Chen, Yani; Brandizzi, Federica

2013-01-01

Cells operate a signaling network termed unfolded protein response (UPR) to monitor protein-folding capacity in the endoplasmic reticulum (ER). IRE1 is an ER transmembrane sensor that activates UPR to maintain ER and cellular function. While mammalian IRE1 promotes cell survive, it can initiate apoptosis via decay of anti-apoptotic microRNAs. Convergent and divergent IRE1 characteristics between plants and animals underscore its significance in cellular homeostasis. This review provides an updated scenario of IRE1 signaling model, discusses emerging IRE1 sensing mechanisms, compares IRE1 features among species, and outlines exciting future directions in UPR research. PMID:23880584

Putting Neutrophils in Motion | Center for Cancer Research

Cancer.gov

During chemotaxis, immune cells such as neutrophils orient themselves and move along a chemical gradient that is induced by chemicals called chemoattractants. Chemoattractants bind to specific G-protein linked receptors to put things in motion. The binding triggers the dissociation of the Gα-subunit from the Gβγ-subunit, which activate several downstream signaling cascades. This ultimately leads to the polarization of actin and myosin filament networks at the front and back of cells, respectively. The end result is directed cell migration, which is important in a wide range of physiological responses including wound healing and leukocyte trafficking, as well as in pathological processes such as metastasis.

Modeling Endoplasmic Reticulum Network Maintenance in a Plant Cell.

PubMed

Lin, Congping; White, Rhiannon R; Sparkes, Imogen; Ashwin, Peter

2017-07-11

The endoplasmic reticulum (ER) in plant cells forms a highly dynamic network of complex geometry. ER network morphology and dynamics are influenced by a number of biophysical processes, including filament/tubule tension, viscous forces, Brownian diffusion, and interactions with many other organelles and cytoskeletal elements. Previous studies have indicated that ER networks can be thought of as constrained minimal-length networks acted on by a variety of forces that perturb and/or remodel the network. Here, we study two specific biophysical processes involved in remodeling. One is the dynamic relaxation process involving a combination of tubule tension and viscous forces. The other is the rapid creation of cross-connection tubules by direct or indirect interactions with cytoskeletal elements. These processes are able to remodel the ER network: the first reduces network length and complexity whereas the second increases both. Using live cell imaging of ER network dynamics in tobacco leaf epidermal cells, we examine these processes on ER network dynamics. Away from regions of cytoplasmic streaming, we suggest that the dynamic network structure is a balance between the two processes, and we build an integrative model of the two processes for network remodeling. This model produces quantitatively similar ER networks to those observed in experiments. We use the model to explore the effect of parameter variation on statistical properties of the ER network. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Beyond bread and beer: whole cell protein extracts from baker's yeast as a bulk source for 3D cell culture matrices.

PubMed

Bodenberger, Nicholas; Kubiczek, Dennis; Paul, Patrick; Preising, Nico; Weber, Lukas; Bosch, Ramona; Hausmann, Rudolf; Gottschalk, Kay-Eberhard; Rosenau, Frank

2017-03-01

Here, we present a novel approach to form hydrogels from yeast whole cell protein. Countless hydrogels are available for sophisticated research, but their fabrication is often difficult to reproduce, with the gels being complicated to handle or simply too expensive. The yeast hydrogels presented here are polymerized using a four-armed, amine reactive crosslinker and show a high chemical and thermal resistance. The free water content was determined by measuring swelling ratios for different protein concentrations, and in a freeze-drying approach, pore sizes of up to 100 μm in the gel could be created without destabilizing the 3D network. Elasticity was proofed to be adjustable with the help of atomic force microscopy by merely changing the amount of used protein. Furthermore, the material was tested for possible cell culture applications; diffusion rates in the network are high enough for sufficient supply of human breast cancer cells and adenocarcinomic human alveolar basal epithelial cells with nutrition, and cells showed high viabilities when tested for compatibility with the material. Furthermore, hydrogels could be functionalized with RGD peptide and the optimal concentration for sufficient cell adhesion was determined to be 150 μM. Given that yeast protein is one of the cheapest and easiest available protein sources and that hydrogels are extremely easy to handle, the developed material has highly promising potential for both sophisticated cell culture techniques as well as for larger scale industrial applications.

Cell fate reprogramming by control of intracellular network dynamics

NASA Astrophysics Data System (ADS)

Zanudo, Jorge G. T.; Albert, Reka

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Although the topic of controlling the dynamics of a system has a long history in control theory, most of this work is not directly applicable to intracellular networks. Here we present a network control method that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our control method takes advantage of certain function-dependent network components and their relation to steady states in order to identify control targets, which are guaranteed to drive any initial state to the target state with 100% effectiveness and need to be applied only transiently for the system to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. This work was supported by NSF Grant PHY 1205840.

Representing perturbed dynamics in biological network models

NASA Astrophysics Data System (ADS)

Stoll, Gautier; Rougemont, Jacques; Naef, Felix

2007-07-01

We study the dynamics of gene activities in relatively small size biological networks (up to a few tens of nodes), e.g., the activities of cell-cycle proteins during the mitotic cell-cycle progression. Using the framework of deterministic discrete dynamical models, we characterize the dynamical modifications in response to structural perturbations in the network connectivities. In particular, we focus on how perturbations affect the set of fixed points and sizes of the basins of attraction. Our approach uses two analytical measures: the basin entropy H and the perturbation size Δ , a quantity that reflects the distance between the set of fixed points of the perturbed network and that of the unperturbed network. Applying our approach to the yeast-cell-cycle network introduced by Li [Proc. Natl. Acad. Sci. U.S.A. 101, 4781 (2004)] provides a low-dimensional and informative fingerprint of network behavior under large classes of perturbations. We identify interactions that are crucial for proper network function, and also pinpoint functionally redundant network connections. Selected perturbations exemplify the breadth of dynamical responses in this cell-cycle model.

Tissue procurement system in Japan: the role of a tissue bank in medical center for translational research, Osaka University Hospital.

PubMed

Ohkawara, H; Fukushima, N; Kitagawa, T; Ito, T; Masutani, Y; Sawa, Y

2010-01-01

Although organ procurement has been regulated by The Organ Transplantation Law (brain-dead donors since 1997, donors after cardiac death since 1979), there has been no law or governmental procurement network (except for cornea) in Japan. Since the late 1980s, some university hospitals have developed original banks. Finally, in 2001 guidelines for tissue procurement were established by The Japanese Society of Tissue Transplantation and Japan Tissue Transplant Network (JTTN) to coordinate tissue harvesting. Five tissue banks were joined to the tissue transplant network (skin in one, heart valves in two, and bone in two). As the number of tissue banks is small, each bank cooperates on procurement, but cannot cover the entire country. With regard to skin transplantation, only one skin bank-The Japan Skin Bank Network (JSBN), which is located in Tokyo-has organized skin procurement. Therefore, it has been difficult to procure skin in areas distant from Tokyo, especially around Osaka. In order to improve such a situation, a tissue bank collaborating with the JSBN was established at The Medical Center for Translational Research (MTR), Osaka University Hospital in April 2008. The bank has played a role in skin procurement center in western Japan and supported procurement and preservation at the time of the skin procurement. Between April 2008 and September 2009, the bank participated in eight tissue procurements in the western area. In the future, the bank is planning to procure and preserve pancreatic islets and bones. Moreover, there is a plan to set up an induced pluripotent stem cells center and stem cell bank in MTR. This tissue bank may play a role to increase tissue procurement in Japan, especially in the western area. .

Predicting efficiency of solar cells based on transparent conducting electrodes

NASA Astrophysics Data System (ADS)

Kumar, Ankush

2017-01-01

Efficiency of a solar cell is directly correlated with the performance of its transparent conducting electrodes (TCEs) which dictates its two core processes, viz., absorption and collection efficiencies. Emerging designs of a TCE involve active networks of carbon nanotubes, silver nanowires and various template-based techniques providing diverse structures; here, voids are transparent for optical transmittance while the conducting network acts as a charge collector. However, it is still not well understood as to which kind of network structure leads to an optimum solar cell performance; therefore, mostly an arbitrary network is chosen as a solar cell electrode. Herein, we propose a new generic approach for understanding the role of TCEs in determining the solar cell efficiency based on analysis of shadowing and recombination losses. A random network of wires encloses void regions of different sizes and shapes which permit light transmission; two terms, void fraction and equivalent radius, are defined to represent the TCE transmittance and wire spacings, respectively. The approach has been applied to various literature examples and their solar cell performance has been compared. To obtain high-efficiency solar cells, optimum density of the wires and their aspect ratio as well as active layer thickness are calculated. Our findings show that a TCE well suitable for one solar cell may not be suitable for another. For high diffusion length based solar cells, the void fraction of the network should be low while for low diffusion length based solar cells, the equivalent radius should be lower. The network with less wire spacing compared to the diffusion length behaves similar to continuous film based TCEs (such as indium tin oxide). The present work will be useful for architectural as well as material engineering of transparent electrodes for improvisation of solar cell performance.

Continuous time Bayesian networks identify Prdm1 as a negative regulator of TH17 cell differentiation in humans

PubMed Central

Acerbi, Enzo; Viganò, Elena; Poidinger, Michael; Mortellaro, Alessandra; Zelante, Teresa; Stella, Fabio

2016-01-01

T helper 17 (TH17) cells represent a pivotal adaptive cell subset involved in multiple immune disorders in mammalian species. Deciphering the molecular interactions regulating TH17 cell differentiation is particularly critical for novel drug target discovery designed to control maladaptive inflammatory conditions. Using continuous time Bayesian networks over a time-course gene expression dataset, we inferred the global regulatory network controlling TH17 differentiation. From the network, we identified the Prdm1 gene encoding the B lymphocyte-induced maturation protein 1 as a crucial negative regulator of human TH17 cell differentiation. The results have been validated by perturbing Prdm1 expression on freshly isolated CD4+ naïve T cells: reduction of Prdm1 expression leads to augmentation of IL-17 release. These data unravel a possible novel target to control TH17 polarization in inflammatory disorders. Furthermore, this study represents the first in vitro validation of continuous time Bayesian networks as gene network reconstruction method and as hypothesis generation tool for wet-lab biological experiments. PMID:26976045

A General Map of Iron Metabolism and Tissue-specific Subnetworks

PubMed Central

Hower, Valerie; Mendes, Pedro; Torti, Frank M.; Laubenbacher, Reinhard; Akman, Steven; Shulaev, Vladmir; Torti, Suzy V.

2009-01-01

Iron is required for survival of mammalian cells. Recently, understanding of iron metabolism and trafficking has increased dramatically, revealing a complex, interacting network largely unknown just a few years ago. This provides an excellent model for systems biology development and analysis. The first step in such an analysis is the construction of a structural network of iron metabolism, which we present here. This network was created using CellDesigner version 3.5.2 and includes reactions occurring in mammalian cells of numerous tissue types. The iron metabolic network contains 151 chemical species and 107 reactions and transport steps. Starting from this general model, we construct iron networks for specific tissues and cells that are fundamental to maintaining body iron homeostasis. We include subnetworks for cells of the intestine and liver, tissues important in iron uptake and storage, respectively; as well as the reticulocyte and macrophage, key cells in iron utilization and recycling. The addition of kinetic information to our structural network will permit the simulation of iron metabolism in different tissues as well as in health and disease. PMID:19381358

Mechanically induced intercellular calcium communication in confined endothelial structures.

PubMed

Junkin, Michael; Lu, Yi; Long, Juexuan; Deymier, Pierre A; Hoying, James B; Wong, Pak Kin

2013-03-01

Calcium signaling in the diverse vascular structures is regulated by a wide range of mechanical and biochemical factors to maintain essential physiological functions of the vasculature. To properly transmit information, the intercellular calcium communication mechanism must be robust against various conditions in the cellular microenvironment. Using plasma lithography geometric confinement, we investigate mechanically induced calcium wave propagation in networks of human umbilical vein endothelial cells organized. Endothelial cell networks with confined architectures were stimulated at the single cell level, including using capacitive force probes. Calcium wave propagation in the network was observed using fluorescence calcium imaging. We show that mechanically induced calcium signaling in the endothelial networks is dynamically regulated against a wide range of probing forces and repeated stimulations. The calcium wave is able to propagate consistently in various dimensions from monolayers to individual cell chains, and in different topologies from linear patterns to cell junctions. Our results reveal that calcium signaling provides a robust mechanism for cell-cell communication in networks of endothelial cells despite the diversity of the microenvironmental inputs and complexity of vascular structures. Copyright © 2012 Elsevier Ltd. All rights reserved.

Chemical Approaches to Probe Metabolic Networks

PubMed Central

Medina-Cleghorn, Daniel; Nomura, Daniel K.

2013-01-01

One of the more provocative realizations that have come out of the genome sequencing projects is that organisms possess a large number of uncharacterized or poorly characterized enzymes. This finding belies the commonly held notion that our knowledge of cell metabolism is nearly complete, underscoring the vast landscape of unannotated metabolic and signaling networks that operate under normal physiological conditions, let alone in disease states where metabolic networks may be rewired, dysregulated, or altered to drive disease progression. Consequently, the functional annotation of enzymatic pathways represents a grand challenge for researchers in the post-genomic era. This review will highlight the chemical technologies that have been successfully used to characterize metabolism, and put forth some of the challenges we face as we expand our map of metabolic pathways. PMID:23296751

Modeling microcirculatory blood flow: current state and future perspectives.

PubMed

Gompper, Gerhard; Fedosov, Dmitry A

2016-01-01

Microvascular blood flow determines a number of important physiological processes of an organism in health and disease. Therefore, a detailed understanding of microvascular blood flow would significantly advance biophysical and biomedical research and its applications. Current developments in modeling of microcirculatory blood flow already allow to go beyond available experimental measurements and have a large potential to elucidate blood flow behavior in normal and diseased microvascular networks. There exist detailed models of blood flow on a single cell level as well as simplified models of the flow through microcirculatory networks, which are reviewed and discussed here. The combination of these models provides promising prospects for better understanding of blood flow behavior and transport properties locally as well as globally within large microvascular networks. © 2015 Wiley Periodicals, Inc.

Brain rhythms and neural syntax: implications for efficient coding of cognitive content and neuropsychiatric disease.

PubMed Central

Buzsáki, György; Watson, Brendon O.

2012-01-01

The perpetual activity of the cerebral cortex is largely supported by the variety of oscillations the brain generates, spanning a number of frequencies and anatomical locations, as well as behavioral correlates. First, we review findings from animal studies showing that most forms of brain rhythms are inhibition-based, producing rhythmic volleys of inhibitory inputs to principal cell populations, thereby providing alternating temporal windows of relatively reduced and enhanced excitability in neuronal networks. These inhibition-based mechanisms offer natural temporal frames to group or “chunk” neuronal activity into cell assemblies and sequences of assemblies, with more complex multi-oscillation interactions creating syntactical rules for the effective exchange of information among cortical networks. We then review recent studies in human psychiatric patients demonstrating a variety alterations in neural oscillations across all major psychiatric diseases, and suggest possible future research directions and treatment approaches based on the fundamental properties of brain rhythms. PMID:23393413

Pathways of cellular proteostasis in aging and disease.

PubMed

Klaips, Courtney L; Jayaraj, Gopal Gunanathan; Hartl, F Ulrich

2018-01-02

Ensuring cellular protein homeostasis, or proteostasis, requires precise control of protein synthesis, folding, conformational maintenance, and degradation. A complex and adaptive proteostasis network coordinates these processes with molecular chaperones of different classes and their regulators functioning as major players. This network serves to ensure that cells have the proteins they need while minimizing misfolding or aggregation events that are hallmarks of age-associated proteinopathies, including neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. It is now clear that the capacity of cells to maintain proteostasis undergoes a decline during aging, rendering the organism susceptible to these pathologies. Here we discuss the major proteostasis pathways in light of recent research suggesting that their age-dependent failure can both contribute to and result from disease. We consider different strategies to modulate proteostasis capacity, which may help develop urgently needed therapies for neurodegeneration and other age-dependent pathologies. © 2018 Klaips et al.

A brewing understanding of the regulation of Bax function by Bcl-xL and Bcl-2.

PubMed

Renault, Thibaud T; Dejean, Laurent M; Manon, Stéphen

2017-01-01

Bcl-2 family members form a network of protein-protein interactions that regulate apoptosis through permeabilization of the mitochondrial outer membrane. Deciphering this intricate network requires streamlined experimental models, including the heterologous expression in yeast. This approach had previously enabled researchers to identify domains and residues that underlie the conformational changes driving the translocation, the insertion and the oligomerization of the pro-apoptotic protein Bax at the level of the mitochondrial outer membrane. Recent studies that combine experiments in yeast and in mammalian cells have shown the unexpected effect of the anti-apoptotic protein Bcl-xL on the priming of Bax. As demonstrated with the BH3-mimetic molecule ABT-737, this property of Bcl-xL, and of Bcl-2, is crucial to elaborate about how apoptosis could be reactivated in tumoral cells. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The Immune System in the Pathogenesis of Ovarian Cancer

PubMed Central

Charbonneau, Bridget; Goode, Ellen L.; Kalli, Kimberly R.; Knutson, Keith L.; DeRycke, Melissa S.

2014-01-01

Clinical outcomes in ovarian cancer are heterogeneous even when considering common features such as stage, response to therapy, and grade. This disparity in outcomes warrants further exploration into tumor and host characteristics. One compelling host characteristic is the immune response to ovarian cancer. While several studies have confirmed a prominent role for the immune system in modifying the clinical course of the disease, recent genetic and protein analyses also suggest a role in disease incidence. Recent studies also show that anti-tumor immunity is often negated by immune suppressive cells present in the tumor microenvironment. These suppressive immune cells also directly enhance the pathogenesis through the release of various cytokines and chemokines, which together form an integrated pathologic network. Thus, future research into immunotherapy targeting ovarian cancer will likely become increasingly focused on combination approaches that simultaneously augment immunity while preventing local immune suppression or by disrupting critical cytokine networks. PMID:23582060

Robustness and flexibility in nematode vulva development.

PubMed

Félix, Marie-Anne; Barkoulas, Michalis

2012-04-01

The Caenorhabditis elegans vulva has served as a paradigm for how conserved developmental pathways, such as EGF-Ras-MAPK, Notch and Wnt signaling, participate in networks driving animal organogenesis. Here, we discuss an emerging direction in the field, which places vulva research in a quantitative and microevolutionary framework. The final vulval cell fate pattern is known to be robust to change, but only recently has the variation of vulval traits been measured under stochastic, environmental or genetic variation. Whereas the resulting cell fate pattern is invariant among rhabditid nematodes, recent studies indicate that the developmental system has accumulated cryptic variation, even among wild C. elegans isolates. Quantitative differences in the signaling network have emerged through experiments and modeling as the driving force behind cryptic variation in Caenorhabditis species. On a wider evolutionary scale, the establishment of new model species has informed about the presence of qualitative variation in vulval signaling pathways. Copyright © 2012 Elsevier Ltd. All rights reserved.

GraphCrunch 2: Software tool for network modeling, alignment and clustering.

PubMed

Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

2011-01-19

Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an algorithm for clustering nodes within a network based solely on their topological similarities. Using GraphCrunch 2, we demonstrate that eukaryotic and viral PPI networks may belong to different graph model families and show that topology-based clustering can reveal important functional similarities between proteins within yeast and human PPI networks. GraphCrunch 2 is a software tool that implements the latest research on biological network analysis. It parallelizes computationally intensive tasks to fully utilize the potential of modern multi-core CPUs. It is open-source and freely available for research use. It runs under the Windows and Linux platforms.

Adducin in tumorigenesis and metastasis.

PubMed

Luo, Cong; Shen, Jiayu

2017-07-18

Adducin is a membrane-skeletal protein localized at spectrin-actin junctions, involving in the formation of the network of cytoskeleton, cellular signal transduction, ionic transportation, cell motility and cell proliferation. While previous researches focused mainly on the relationship between adducin and hypertension, there are few studies focusing on the role of adducin in tumor. Previous studies showed that adducin played a role in the evolution and progression of neoplasm. This review makes a brief summary on the structure, function and mechanism of adducin and how adducin functions in tumorigenesis and metastasis.

Real time data acquisition of a countrywide commercial microwave link network

NASA Astrophysics Data System (ADS)

Chwala, Christian; Keis, Felix; Kunstmann, Harald

2015-04-01

Research in recent years has shown that data from commercial microwave link networks can provide very valuable precipitation information. Since these networks comprise the backbone of the cell phone network, they provide countrywide coverage. However acquiring the necessary data from the network operators is still difficult. Data is usually made available for researchers with a large time delay and often at irregular basis. This of course hinders the exploitation of commercial microwave link data in operational applications like QPE forecasts running at national meteorological services. To overcome this, we have developed a custom software in joint cooperation with our industry partner Ericsson. The software is installed on a dedicated server at Ericsson and is capable of acquiring data from the countrywide microwave link network in Germany. In its current first operational testing phase, data from several hundred microwave links in southern Germany is recorded. All data is instantaneously sent to our server where it is stored and organized in an emerging database. Time resolution for the Ericsson data is one minute. The custom acquisition software, however, is capable of processing higher sampling rates. Additionally we acquire and manage 1 Hz data from four microwave links operated by the skiing resort in Garmisch-Partenkirchen. We will present the concept of the data acquisition and show details of the custom-built software. Additionally we will showcase the accessibility and basic processing of real time microwave link data via our database web frontend.

Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

PubMed

Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

2016-07-01

Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences.

International stem cell collaboration: how disparate policies between the United States and the United Kingdom impact research.

PubMed

Luo, Jingyuan; Flynn, Jesse M; Solnick, Rachel E; Ecklund, Elaine Howard; Matthews, Kirstin R W

2011-03-08

As the scientific community globalizes, it is increasingly important to understand the effects of international collaboration on the quality and quantity of research produced. While it is generally assumed that international collaboration enhances the quality of research, this phenomenon is not well examined. Stem cell research is unique in that it is both politically charged and a research area that often generates international collaborations, making it an ideal case through which to examine international collaborations. Furthermore, with promising medical applications, the research area is dynamic and responsive to a globalizing science environment. Thus, studying international collaborations in stem cell research elucidates the role of existing international networks in promoting quality research, as well as the effects that disparate national policies might have on research. This study examined the impact of collaboration on publication significance in the United States and the United Kingdom, world leaders in stem cell research with disparate policies. We reviewed publications by US and UK authors from 2008, along with their citation rates and the political factors that may have contributed to the number of international collaborations. The data demonstrated that international collaborations significantly increased an article's impact for UK and US investigators. While this applied to UK authors whether they were corresponding or secondary, this effect was most significant for US authors who were corresponding authors. While the UK exhibited a higher proportion of international publications than the US, this difference was consistent with overall trends in international scientific collaboration. The findings suggested that national stem cell policy differences and regulatory mechanisms driving international stem cell research in the US and UK did not affect the frequency of international collaborations, or even the countries with which the US and UK most often collaborated. Geographical and traditional collaborative relationships were the predominate considerations in establishing international collaborations.

International Stem Cell Collaboration: How Disparate Policies between the United States and the United Kingdom Impact Research

PubMed Central

Solnick, Rachel E.; Ecklund, Elaine Howard; Matthews, Kirstin R. W.

2011-01-01

As the scientific community globalizes, it is increasingly important to understand the effects of international collaboration on the quality and quantity of research produced. While it is generally assumed that international collaboration enhances the quality of research, this phenomenon is not well examined. Stem cell research is unique in that it is both politically charged and a research area that often generates international collaborations, making it an ideal case through which to examine international collaborations. Furthermore, with promising medical applications, the research area is dynamic and responsive to a globalizing science environment. Thus, studying international collaborations in stem cell research elucidates the role of existing international networks in promoting quality research, as well as the effects that disparate national policies might have on research. This study examined the impact of collaboration on publication significance in the United States and the United Kingdom, world leaders in stem cell research with disparate policies. We reviewed publications by US and UK authors from 2008, along with their citation rates and the political factors that may have contributed to the number of international collaborations. The data demonstrated that international collaborations significantly increased an article's impact for UK and US investigators. While this applied to UK authors whether they were corresponding or secondary, this effect was most significant for US authors who were corresponding authors. While the UK exhibited a higher proportion of international publications than the US, this difference was consistent with overall trends in international scientific collaboration. The findings suggested that national stem cell policy differences and regulatory mechanisms driving international stem cell research in the US and UK did not affect the frequency of international collaborations, or even the countries with which the US and UK most often collaborated. Geographical and traditional collaborative relationships were the predominate considerations in establishing international collaborations. PMID:21408134

A Scalable Approach for Discovering Conserved Active Subnetworks across Species

PubMed Central

Verfaillie, Catherine M.; Hu, Wei-Shou; Myers, Chad L.

2010-01-01

Overlaying differential changes in gene expression on protein interaction networks has proven to be a useful approach to interpreting the cell's dynamic response to a changing environment. Despite successes in finding active subnetworks in the context of a single species, the idea of overlaying lists of differentially expressed genes on networks has not yet been extended to support the analysis of multiple species' interaction networks. To address this problem, we designed a scalable, cross-species network search algorithm, neXus (Network - cross(X)-species - Search), that discovers conserved, active subnetworks based on parallel differential expression studies in multiple species. Our approach leverages functional linkage networks, which provide more comprehensive coverage of functional relationships than physical interaction networks by combining heterogeneous types of genomic data. We applied our cross-species approach to identify conserved modules that are differentially active in stem cells relative to differentiated cells based on parallel gene expression studies and functional linkage networks from mouse and human. We find hundreds of conserved active subnetworks enriched for stem cell-associated functions such as cell cycle, DNA repair, and chromatin modification processes. Using a variation of this approach, we also find a number of species-specific networks, which likely reflect mechanisms of stem cell function that have diverged between mouse and human. We assess the statistical significance of the subnetworks by comparing them with subnetworks discovered on random permutations of the differential expression data. We also describe several case examples that illustrate the utility of comparative analysis of active subnetworks. PMID:21170309

An agronomic field-scale sensor network for monitoring soil water and temperature variation

NASA Astrophysics Data System (ADS)

Brown, D. J.; Gasch, C.; Brooks, E. S.; Huggins, D. R.; Campbell, C. S.; Cobos, D. R.

2014-12-01

Environmental sensor networks have been deployed in a variety of contexts to monitor plant, air, water and soil properties. To date, there have been relatively few such networks deployed to monitor dynamic soil properties in cropped fields. Here we report on experience with a distributed soil sensor network that has been deployed for seven years in a research farm with ongoing agronomic field operations. The Washington State University R. J. Cook Agronomy Farm (CAF), Pullman, WA, USA has recently been designated a United States Department of Agriculture (USDA) Long-Term Agro-Ecosystem Research (LTAR) site. In 2007, 12 geo-referenced locations at CAF were instrumented, then in 2009 this network was expended to 42 locations distributed across the 37-ha farm. At each of this locations, Decagon 5TE probes (Decagon Devices Inc., Pullman, WA, USA) were installed at five depths (30, 60, 90, 120, and 150 cm), with temperature and volumetric soil moisture content recorded hourly. Initially, data loggers were wirelessly connected to a data station that could be accessed through a cell connection, but due to the logistics of agronomic field operations, we later buried the dataloggers at each site and now periodically download data via local radio transmission. In this presentation, we share our experience with the installation, maintenance, calibration and data processing associated with an agronomic soil monitoring network. We also present highlights of data derived from this network, including seasonal fluctuations of soil temperature and volumetric water content at each depth, and how these measurements are influenced by crop type, soil properties, landscape position, and precipitation events.

Genome network medicine: innovation to overcome huge challenges in cancer therapy.

PubMed

Roukos, Dimitrios H

2014-01-01

The post-ENCODE era shapes now a new biomedical research direction for understanding transcriptional and signaling networks driving gene expression and core cellular processes such as cell fate, survival, and apoptosis. Over the past half century, the Francis Crick 'central dogma' of single n gene/protein-phenotype (trait/disease) has defined biology, human physiology, disease, diagnostics, and drugs discovery. However, the ENCODE project and several other genomic studies using high-throughput sequencing technologies, computational strategies, and imaging techniques to visualize regulatory networks, provide evidence that transcriptional process and gene expression are regulated by highly complex dynamic molecular and signaling networks. This Focus article describes the linear experimentation-based limitations of diagnostics and therapeutics to cure advanced cancer and the need to move on from reductionist to network-based approaches. With evident a wide genomic heterogeneity, the power and challenges of next-generation sequencing (NGS) technologies to identify a patient's personal mutational landscape for tailoring the best target drugs in the individual patient are discussed. However, the available drugs are not capable of targeting aberrant signaling networks and research on functional transcriptional heterogeneity and functional genome organization is poorly understood. Therefore, the future clinical genome network medicine aiming at overcoming multiple problems in the new fields of regulatory DNA mapping, noncoding RNA, enhancer RNAs, and dynamic complexity of transcriptional circuitry are also discussed expecting in new innovation technology and strong appreciation of clinical data and evidence-based medicine. The problematic and potential solutions in the discovery of next-generation, molecular, and signaling circuitry-based biomarkers and drugs are explored. © 2013 Wiley Periodicals, Inc.

Gene Expression Correlated with Severe Asthma Characteristics Reveals Heterogeneous Mechanisms of Severe Disease.

PubMed

Modena, Brian D; Bleecker, Eugene R; Busse, William W; Erzurum, Serpil C; Gaston, Benjamin M; Jarjour, Nizar N; Meyers, Deborah A; Milosevic, Jadranka; Tedrow, John R; Wu, Wei; Kaminski, Naftali; Wenzel, Sally E

2017-06-01

Severe asthma (SA) is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of bronchial epithelial cells in individuals with asthma have provided biological insight and underscored possible mechanistic differences between individuals. Identify networks of genes reflective of underlying biological processes that define SA. Airway epithelial cell gene expression from 155 subjects with asthma and healthy control subjects in the Severe Asthma Research Program was analyzed by weighted gene coexpression network analysis to identify gene networks and profiles associated with SA and its specific characteristics (i.e., pulmonary function tests, quality of life scores, urgent healthcare use, and steroid use), which potentially identified underlying biological processes. A linear model analysis confirmed these findings while adjusting for potential confounders. Weighted gene coexpression network analysis constructed 64 gene network modules, including modules corresponding to T1 and T2 inflammation, neuronal function, cilia, epithelial growth, and repair mechanisms. Although no network selectively identified SA, genes in modules linked to epithelial growth and repair and neuronal function were markedly decreased in SA. Several hub genes of the epithelial growth and repair module were found located at the 17q12-21 locus, near a well-known asthma susceptibility locus. T2 genes increased with severity in those treated with corticosteroids but were also elevated in untreated, mild-to-moderate disease compared with healthy control subjects. T1 inflammation, especially when associated with increased T2 gene expression, was elevated in a subgroup of younger patients with SA. In this hypothesis-generating analysis, gene expression networks in relation to asthma severity provided potentially new insight into biological mechanisms associated with the development of SA and its phenotypes.

Gene Expression Correlated with Severe Asthma Characteristics Reveals Heterogeneous Mechanisms of Severe Disease

PubMed Central

Modena, Brian D.; Bleecker, Eugene R.; Busse, William W.; Erzurum, Serpil C.; Gaston, Benjamin M.; Jarjour, Nizar N.; Meyers, Deborah A.; Milosevic, Jadranka; Tedrow, John R.; Wu, Wei; Kaminski, Naftali

2017-01-01

Rationale: Severe asthma (SA) is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of bronchial epithelial cells in individuals with asthma have provided biological insight and underscored possible mechanistic differences between individuals. Objectives: Identify networks of genes reflective of underlying biological processes that define SA. Methods: Airway epithelial cell gene expression from 155 subjects with asthma and healthy control subjects in the Severe Asthma Research Program was analyzed by weighted gene coexpression network analysis to identify gene networks and profiles associated with SA and its specific characteristics (i.e., pulmonary function tests, quality of life scores, urgent healthcare use, and steroid use), which potentially identified underlying biological processes. A linear model analysis confirmed these findings while adjusting for potential confounders. Measurements and Main Results: Weighted gene coexpression network analysis constructed 64 gene network modules, including modules corresponding to T1 and T2 inflammation, neuronal function, cilia, epithelial growth, and repair mechanisms. Although no network selectively identified SA, genes in modules linked to epithelial growth and repair and neuronal function were markedly decreased in SA. Several hub genes of the epithelial growth and repair module were found located at the 17q12–21 locus, near a well-known asthma susceptibility locus. T2 genes increased with severity in those treated with corticosteroids but were also elevated in untreated, mild-to-moderate disease compared with healthy control subjects. T1 inflammation, especially when associated with increased T2 gene expression, was elevated in a subgroup of younger patients with SA. Conclusions: In this hypothesis-generating analysis, gene expression networks in relation to asthma severity provided potentially new insight into biological mechanisms associated with the development of SA and its phenotypes. PMID:27984699

Human astrocytic grid networks patterned in parylene-C inlayed SiO2 trenches.

PubMed

Jordan, M D; Raos, B J; Bunting, A S; Murray, A F; Graham, E S; Unsworth, C P

2016-10-01

Recent literature suggests that glia, and in particular astrocytes, should be studied as organised networks which communicate through gap junctions. Astrocytes, however, adhere to most surfaces and are highly mobile cells. In order to study, such organised networks effectively in vitro it is necessary to influence them to pattern to certain substrates whilst being repelled from others and to immobilise the astrocytes sufficiently such that they do not continue to migrate further whilst under study. In this article, we demonstrate for the first time how it is possible to facilitate the study of organised patterned human astrocytic networks using hNT astrocytes in a SiO2 trench grid network that is inlayed with the biocompatible material, parylene-C. We demonstrate how the immobilisation of astrocytes lies in the depth of the SiO2 trench, determining an optimum trench depth and that the optimum patterning of astrocytes is a consequence of the parylene-C inlay and the grid node spacing. We demonstrate high fidelity of the astrocytic networks and demonstrate that functionality of the hNT astrocytes through ATP evoked calcium signalling is also dependent on the grid node spacing. Finally, we demonstrate that the location of the nuclei on the grid nodes is also a function of the grid node spacing. The significance of this work, is to describe a suitable platform to facilitate the study of hNT astrocytes from the single cell level to the network level to improve knowledge and understanding of how communication links to spatial organisation at these higher order scales and trigger in vitro research further in this area with clinical applications in the area of epilepsy, stroke and focal cerebral ischemia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Systematical analysis of cutaneous squamous cell carcinoma network of microRNAs, transcription factors, and target and host genes.

PubMed

Wang, Ning; Xu, Zhi-Wen; Wang, Kun-Hao

2014-01-01

MicroRNAs (miRNAs) are small non-coding RNA molecules found in multicellular eukaryotes which are implicated in development of cancer, including cutaneous squamous cell carcinoma (cSCC). Expression is controlled by transcription factors (TFs) that bind to specific DNA sequences, thereby controlling the flow (or transcription) of genetic information from DNA to messenger RNA. Interactions result in biological signal control networks. Molecular components involved in cSCC were here assembled at abnormally expressed, related and global levels. Networks at these three levels were constructed with corresponding biological factors in term of interactions between miRNAs and target genes, TFs and miRNAs, and host genes and miRNAs. Up/down regulation or mutation of the factors were considered in the context of the regulation and significant patterns were extracted. Participants of the networks were evaluated based on their expression and regulation of other factors. Sub-networks with two core TFs, TP53 and EIF2C2, as the centers are identified. These share self-adapt feedback regulation in which a mutual restraint exists. Up or down regulation of certain genes and miRNAs are discussed. Some, for example the expression of MMP13, were in line with expectation while others, including FGFR3, need further investigation of their unexpected behavior. The present research suggests that dozens of components, miRNAs, TFs, target genes and host genes included, unite as networks through their regulation to function systematically in human cSCC. Networks built under the currently available sources provide critical signal controlling pathways and frequent patterns. Inappropriate controlling signal flow from abnormal expression of key TFs may push the system into an incontrollable situation and therefore contributes to cSCC development.

TFmiR: a web server for constructing and analyzing disease-specific transcription factor and miRNA co-regulatory networks.

PubMed

Hamed, Mohamed; Spaniol, Christian; Nazarieh, Maryam; Helms, Volkhard

2015-07-01

TFmiR is a freely available web server for deep and integrative analysis of combinatorial regulatory interactions between transcription factors, microRNAs and target genes that are involved in disease pathogenesis. Since the inner workings of cells rely on the correct functioning of an enormously complex system of activating and repressing interactions that can be perturbed in many ways, TFmiR helps to better elucidate cellular mechanisms at the molecular level from a network perspective. The provided topological and functional analyses promote TFmiR as a reliable systems biology tool for researchers across the life science communities. TFmiR web server is accessible through the following URL: http://service.bioinformatik.uni-saarland.de/tfmir. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

How does investment in research training affect the development of research networks and collaborations?

PubMed

Paina, Ligia; Ssengooba, Freddie; Waswa, Douglas; M'imunya, James M; Bennett, Sara

2013-05-20

Whether and how research training programs contribute to research network development is underexplored. The Fogarty International Center (FIC) has supported overseas research training programs for over two decades. FIC programs could provide an entry point in the development of research networks and collaborations. We examine whether FIC's investment in research training contributed to the development of networks and collaborations in two countries with longstanding FIC investments - Uganda and Kenya - and the factors which facilitated this process. As part of two case studies at Uganda's Makerere University and Kenya's University of Nairobi, we conducted 53 semi-structured in-depth interviews and nine focus group discussions. To expand on our case study findings, we conducted a focused bibliometric analysis on two purposively selected topic areas to examine scientific productivity and used online network illustration tools to examine the resulting network structures. FIC support made important contributions to network development. Respondents from both Uganda and Kenya confirmed that FIC programs consistently provided trainees with networking skills and exposure to research collaborations, primarily within the institutions implementing FIC programs. In both countries, networks struggled with inclusiveness, particularly in HIV/AIDS research. Ugandan respondents perceived their networks to be more cohesive than Kenyan respondents did. Network cohesiveness was positively correlated with the magnitude and longevity of FIC's programs. Support from FIC grants to local and regional research network development and networking opportunities, such as conferences, was rare. Synergies between FIC programs and research grants helped to solidify and maintain research collaborations. Networks developed where FIC's programs focused on a particular institution, there was a critical mass of trainees with similar interests, and investments for network development were available from early implementation. Networks were less likely to emerge where FIC efforts were thinly scattered across multiple institutions. The availability of complementary research grants created opportunities for researchers to collaborate in grant writing, research implementation, and publications. FIC experiences in Uganda and Kenya showcase the important role of research training programs in creating and sustaining research networks. FIC programs should consider including support to research networks more systematically in their capacity development agenda.

The informational architecture of the cell.

PubMed

Walker, Sara Imari; Kim, Hyunju; Davies, Paul C W

2016-03-13

We compare the informational architecture of biological and random networks to identify informational features that may distinguish biological networks from random. The study presented here focuses on the Boolean network model for regulation of the cell cycle of the fission yeast Schizosaccharomyces pombe. We compare calculated values of local and global information measures for the fission yeast cell cycle to the same measures as applied to two different classes of random networks: Erdös-Rényi and scale-free. We report patterns in local information processing and storage that do indeed distinguish biological from random, associated with control nodes that regulate the function of the fission yeast cell-cycle network. Conversely, we find that integrated information, which serves as a global measure of 'emergent' information processing, does not differ from random for the case presented. We discuss implications for our understanding of the informational architecture of the fission yeast cell-cycle network in particular, and more generally for illuminating any distinctive physics that may be operative in life. © 2016 The Author(s).

Compact Microscope Imaging System With Intelligent Controls Improved

NASA Technical Reports Server (NTRS)

McDowell, Mark

2004-01-01

The Compact Microscope Imaging System (CMIS) with intelligent controls is a diagnostic microscope analysis tool with intelligent controls for use in space, industrial, medical, and security applications. This compact miniature microscope, which can perform tasks usually reserved for conventional microscopes, has unique advantages in the fields of microscopy, biomedical research, inline process inspection, and space science. Its unique approach integrates a machine vision technique with an instrumentation and control technique that provides intelligence via the use of adaptive neural networks. The CMIS system was developed at the NASA Glenn Research Center specifically for interface detection used for colloid hard spheres experiments; biological cell detection for patch clamping, cell movement, and tracking; and detection of anode and cathode defects for laboratory samples using microscope technology.

Immobilized Metal Affinity Chromatography Coupled to Multiple Reaction Monitoring Enables Reproducible Quantification of Phospho-signaling*

PubMed Central

Kennedy, Jacob J.; Yan, Ping; Zhao, Lei; Ivey, Richard G.; Voytovich, Uliana J.; Moore, Heather D.; Lin, Chenwei; Pogosova-Agadjanyan, Era L.; Stirewalt, Derek L.; Reding, Kerryn W.; Whiteaker, Jeffrey R.; Paulovich, Amanda G.

2016-01-01

A major goal in cell signaling research is the quantification of phosphorylation pharmacodynamics following perturbations. Traditional methods of studying cellular phospho-signaling measure one analyte at a time with poor standardization, rendering them inadequate for interrogating network biology and contributing to the irreproducibility of preclinical research. In this study, we test the feasibility of circumventing these issues by coupling immobilized metal affinity chromatography (IMAC)-based enrichment of phosphopeptides with targeted, multiple reaction monitoring (MRM) mass spectrometry to achieve precise, specific, standardized, multiplex quantification of phospho-signaling responses. A multiplex immobilized metal affinity chromatography- multiple reaction monitoring assay targeting phospho-analytes responsive to DNA damage was configured, analytically characterized, and deployed to generate phospho-pharmacodynamic curves from primary and immortalized human cells experiencing genotoxic stress. The multiplexed assays demonstrated linear ranges of ≥3 orders of magnitude, median lower limit of quantification of 0.64 fmol on column, median intra-assay variability of 9.3%, median inter-assay variability of 12.7%, and median total CV of 16.0%. The multiplex immobilized metal affinity chromatography- multiple reaction monitoring assay enabled robust quantification of 107 DNA damage-responsive phosphosites from human cells following DNA damage. The assays have been made publicly available as a resource to the community. The approach is generally applicable, enabling wide interrogation of signaling networks. PMID:26621847

ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network1[OPEN

PubMed Central

Gloaguen, Pauline; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves

2017-01-01

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis (Arabidopsis thaliana) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. PMID:28442501

Shear Stress Induced Reorganization of the Keratin Intermediate Filament Network Requires Phosphorylation by Protein Kinase C ζ

PubMed Central

Sivaramakrishnan, Sivaraj; Schneider, Jaime L.; Sitikov, Albert; Goldman, Robert D.

2009-01-01

Keratin intermediate filaments (KIFs) form a fibrous polymer network that helps epithelial cells withstand external mechanical forces. Recently, we established a correlation between the structure of the KIF network and its local mechanical properties in alveolar epithelial cells. Shear stress applied across the cell surface resulted in the structural remodeling of KIF and a substantial increase in the elastic modulus of the network. This study examines the mechanosignaling that regulates the structural remodeling of the KIF network. We report that the shear stress–mediated remodeling of the KIF network is facilitated by a twofold increase in the dynamic exchange rate of KIF subunits, which is regulated in a PKC ζ and 14-3-3–dependent manner. PKC ζ phosphorylates K18pSer33, and this is required for the structural reorganization because the KIF network in A549 cells transfected with a dominant negative PKC ζ, or expressing the K18Ser33Ala mutation, is unchanged. Blocking the shear stress–mediated reorganization results in reduced cellular viability and increased apoptotic levels. These data suggest that shear stress mediates the phosphorylation of K18pSer33, which is required for the reorganization of the KIF network, resulting in changes in mechanical properties of the cell that help maintain the integrity of alveolar epithelial cells. PMID:19357195

A bipartite graph of Neuroendocrine System

NASA Astrophysics Data System (ADS)

Guo, Zhong-Wei; Zou, Sheng-Rong; Peng, Yu-Jing; Zhou, Ta; Gu, Chang-Gui; He, Da-Ren

2008-03-01

We present an empirical investigation on the neuroendocrine system and suggest describe it by a bipartite graph. In the net the cells can be regarded as collaboration acts and the mediators can be regarded as collaboration actors. The act degree stands for the number of the cells that secrete a single mediator. Among them bFGF (the basic fibroblast growth factor) has the largest node act degree. It is the most important mitogenic cytokine, followed by TGF-beta, IL-6, IL1-beta, VEGF, IGF-1and so on. They are critical in neuroendocrine system to maintain bodily healthiness, emotional stabilization and endocrine harmony. The act degree distribution shows a shifted power law (SPL) function forms [1]. The average act degree of neuroendocrine network is h=3.01, It means that each mediator is secreted by three cells on average. The similarity, which stands for the average probability of secreting the same mediators by all neuroendocrine cells, is observed as s=0.14. Our results may be used in the research of the medical treatment of neuroendocrine diseases. [1] Assortativity and act degree distribution of some collaboration networks, Hui Chang, Bei-Bei Su, Yue-Ping Zhou, Daren He, Physica A, 383 (2007) 687-702

Computer Simulation of Embryonic Systems: What can a ...

EPA Pesticide Factsheets

(1) Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative pr

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative predic

Systems biology of host-mycobiota interactions: dissecting Dectin-1 and Dectin-2 signalling in immune cells with DC-ATLAS.

PubMed

Rizzetto, Lisa; De Filippo, Carlotta; Rivero, Damariz; Riccadonna, Samantha; Beltrame, Luca; Cavalieri, Duccio

2013-11-01

Modelling the networks sustaining the fruitful coexistence between fungi and their mammalian hosts is becoming increasingly important to control emerging fungal pathogens. The C-type lectins Dectin-1 and Dectin-2 are involved in host defense mechanisms against fungal infection driving inflammatory and adaptive immune responses and complement in containing fungal burdens. Recognizing carbohydrate structures in pathogens, their engagement induces maturation of dendritic cells (DCs) into potent immuno-stimulatory cells endowed with the capacity to efficiently prime T cells. Owing to these properties, Dectin-1 and Dectin-2 agonists are currently under investigation as promising adjuvants in vaccination procedures for the treatment of fungal infection. Thus, a detailed understanding of events' cascade specifically triggered in DCs upon engagement is of great interest in translational research. Here, we summarize the current knowledge on Dectin-1 and Dectin-2 signalling in DCs highlighting similarities and differences. Detailed maps are annotated, using the Biological Connection Markup Language (BCML) data model, and stored in DC-ATLAS, a versatile resource for the interpretation of high-throughput data generated perturbing the signalling network of DCs. Copyright © 2013 Elsevier GmbH. All rights reserved.

The pluralization of the international: Resistance and alter-standardization in regenerative stem cell medicine

PubMed Central

Rosemann, Achim; Chaisinthop, Nattaka

2016-01-01

The article explores the formation of an international politics of resistance and ‘alter-standardization’ in regenerative stem cell medicine. The absence of internationally harmonized regulatory frameworks in the clinical stem cell field and the presence of lucrative business opportunities have resulted in the formation of transnational networks adopting alternative research standards and practices. These oppose, as a universal global standard, strict evidence-based medicine clinical research protocols as defined by scientists and regulatory agencies in highly developed countries. The emergence of transnational spaces of alter-standardization is closely linked to scientific advances in rapidly developing countries such as China and India, but calls for more flexible regulatory frameworks, and the legitimization of experimental for-profit applications outside of evidence-based medical care, are emerging increasingly also within more stringently regulated countries, such as the United States and countries in the European Union. We can observe, then, a trend toward the pluralization of the standards, practices, and concepts in the stem cell field. PMID:26983174

Dependences of the geometrical parameters of cell community on stimulation voltage and frequency in chick embryonic cardiomyocytes

NASA Astrophysics Data System (ADS)

Fujii, Koki; Nomura, Fumimasa; Kaneko, Tomoyuki

2018-03-01

To investigate the optimal conditions for electrical stimulation, communities of lined-up chick embryonic cardiomyocytes were evaluated in terms of their threshold voltage for pacing (PVMin) and the half-maximum paced frequency (PF50), with a focus on the following factors: (1) the orientation of the major axis of cell communities to the electric field (EF) direction as the external factor; (2) the number of cells in a cell community, the length of the cell community, and the mean length of cells comprising the community as the internal factors. Firstly, PVMin decreased with increasing length of the cell network oriented parallel to the EF. PVMin was approximately 0.041 ± 0.025 V/mm when the community was sufficiently long. On the other hand, PVMin in the orthogonal orientation was constant at 1.7 ± 0.047 V/mm with no dependence on the length of the cell network. Secondly, we found that PF50 increased with increasing length of the cell network or the number of cells in the network; the PF50 values were 2.03 ± 0.05 and 3.39 ± 0.05 Hz when the respective cell network lengths were 100 µm (n = 43) and more than 300 µm (n = 6) and the cells were oriented parallel to the EF. These findings indicate that it is important to suppress ventricular fibrillation with minimal efficient stimulation by considering the EF direction with respect to the orientation of cardiomyocytes. Furthermore, expanded cells showed the loss of ability to respond to stimulation at higher frequencies. Cardiomyocytes combined with seeded fibroblasts as a cell network at a low density are a possible model of a ventricular remodeling heart.

Global profiling of proteolytically modified proteins in human metastatic hepatocellular carcinoma cell lines reveals CAPN2 centered network.

PubMed

Shen, Chengpin; Yu, Yanyan; Li, Hong; Yan, Guoquan; Liu, Mingqi; Shen, Huali; Yang, Pengyuan

2012-06-01

Proteolysis affects every protein at some point in its life cycle. Many biomarkers of disease or cancer are stable proteolytic fragments in biological fluids. There is great interest and a challenge in proteolytically modified protein study to identify physiologic protease-substrate relationships and find potential biomarkers. In this study, two human hepatocellular carcinoma (HCC) cell lines with different metastasis potential, MHCC97L, and HCCLM6, were researched with a high-throughput and sensitive PROTOMAP platform. In total 391 proteins were found to be proteolytically processed and many of them were cleaved into persistent fragments instead of completely degraded. Fragments related to 161 proteins had different expressions in these two cell lines. Through analyzing these significantly changed fragments with bio-informatic tools, several bio-functions such as tumor cell migration and anti-apoptosis were enriched. A proteolysis network was also built up, of which the CAPN2 centered subnetwork, including SPTBN1, ATP5B, and VIM, was more active in highly metastatic HCC cell line. Interestingly, proteolytic modifications of CD44 and FN1 were found to affect their secretion. This work suggests that proteolysis plays an important role in human HCC metastasis. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ovarian Cancer Differential Interactome and Network Entropy Analysis Reveal New Candidate Biomarkers.

PubMed

Ayyildiz, Dilara; Gov, Esra; Sinha, Raghu; Arga, Kazim Yalcin

2017-05-01

Ovarian cancer is one of the most common cancers and has a high mortality rate due to insidious symptoms and lack of robust diagnostics. A hitherto understudied concept in cancer pathogenesis may offer new avenues for innovation in ovarian cancer biomarker development. Cancer cells are characterized by an increase in network entropy, and several studies have exploited this concept to identify disease-associated gene and protein modules. We report in this study the changes in protein-protein interactions (PPIs) in ovarian cancer within a differential network (interactome) analysis framework utilizing the entropy concept and gene expression data. A compendium of six transcriptome datasets that included 140 samples from laser microdissected epithelial cells of ovarian cancer patients and 51 samples from healthy population was obtained from Gene Expression Omnibus, and the high confidence human protein interactome (31,465 interactions among 10,681 proteins) was used. The uncertainties of the up- or downregulation of PPIs in ovarian cancer were estimated through an entropy formulation utilizing combined expression levels of genes, and the interacting protein pairs with minimum uncertainty were identified. We identified 105 proteins with differential PPI patterns scattered in 11 modules, each indicating significantly affected biological pathways in ovarian cancer such as DNA repair, cell proliferation-related mechanisms, nucleoplasmic translocation of estrogen receptor, extracellular matrix degradation, and inflammation response. In conclusion, we suggest several PPIs as biomarker candidates for ovarian cancer and discuss their future biological implications as potential molecular targets for pharmaceutical development as well. In addition, network entropy analysis is a concept that deserves greater research attention for diagnostic innovation in oncology and tumor pathogenesis.

Learning Boolean Networks in HepG2 cells using ToxCast High-Content Imaging Data (SOT annual meeting)

EPA Science Inventory

Cells adapt to their environment via homeostatic processes that are regulated by complex molecular networks. Our objective was to learn key elements of these networks in HepG2 cells using ToxCast High-content imaging (HCI) measurements taken over three time points (1, 24, and 72h...

Resource Allocation Algorithms for the Next Generation Cellular Networks

NASA Astrophysics Data System (ADS)

Amzallag, David; Raz, Danny

This chapter describes recent results addressing resource allocation problems in the context of current and future cellular technologies. We present models that capture several fundamental aspects of planning and operating these networks, and develop new approximation algorithms providing provable good solutions for the corresponding optimization problems. We mainly focus on two families of problems: cell planning and cell selection. Cell planning deals with choosing a network of base stations that can provide the required coverage of the service area with respect to the traffic requirements, available capacities, interference, and the desired QoS. Cell selection is the process of determining the cell(s) that provide service to each mobile station. Optimizing these processes is an important step towards maximizing the utilization of current and future cellular networks.

Autocatalytic polymerization generates persistent random walk of crawling cells.

PubMed

Sambeth, R; Baumgaertner, A

2001-05-28

The autocatalytic polymerization kinetics of the cytoskeletal actin network provides the basic mechanism for a persistent random walk of a crawling cell. It is shown that network remodeling by branching processes near the cell membrane is essential for the bimodal spatial stability of the network which induces a spontaneous breaking of isotropic cell motion. Details of the phenomena are analyzed using a simple polymerization model studied by analytical and simulation methods.

Older and Newer Media: Patterns of Use and Effects on Adolescents' Health and Well-Being

ERIC Educational Resources Information Center

Brown, Jane D.; Bobkowski, Piotr S.

2011-01-01

The past decade's research on the use and effects of older (television, music, movies, magazines) and newer media (the Internet, cell phones, social networking) on adolescents' health and well-being is reviewed. A portrait of patterns of use of the media is provided and then the predictors and effects of those patterns on adolescents' mental…

Open Source Initiative Powers Real-Time Data Streams

NASA Technical Reports Server (NTRS)

2014-01-01

Under an SBIR contract with Dryden Flight Research Center, Creare Inc. developed a data collection tool called the Ring Buffered Network Bus. The technology has now been released under an open source license and is hosted by the Open Source DataTurbine Initiative. DataTurbine allows anyone to stream live data from sensors, labs, cameras, ocean buoys, cell phones, and more.

Exploring the Influence of Emerging Media Technologies on Public High School Teachers

ERIC Educational Resources Information Center

Eldridge, John A.

2010-01-01

The purpose of this research is to better understand the influence emerging media technologies such as MP3 players, cell phones, and social networking sites are having on teachers in public high schools. Through the experiences teachers and staff members shared with us, the reader will gain a better understanding of how teachers and staff members…

What Are Young People Doing on Internet? Use of ICT, Parental Supervision Strategies and Exposure to Risks

ERIC Educational Resources Information Center

Giménez, Ana M.; Luengo, José A.; Bartrina, M. José

2017-01-01

Introduction: Current research emphasizes young people's access to and use of social networks, chat and WhatsApp. However, this situation is not associated with active parental mediation to protect them from the risks involved. This study analyzes Murcian students' perception of cell phone and computer use, parental mediation strategies and their…

New clinical advances in immunotherapy for the treatment of solid tumours

PubMed Central

Zavala, Valentina A; Kalergis, Alexis M

2015-01-01

Advances in understanding the mechanisms of cancer cells for evading the immune system surveillance, including how the immune system modulates the phenotype of tumours, have allowed the development of new therapies that benefit from this complex cellular network to specifically target and destroy cancer cells. Immunotherapy researchers have mainly focused on the discovery of tumour antigens that could confer specificity to immune cells to detect and destroy cancer cells, as well as on the mechanisms leading to an improved activation of effector immune cells. The Food and Drug Administration approval in 2010 of ipilumumab for melanoma treatment and of pembrolizumab in 2014, monoclonal antibodies against T-lymphocyte-associated antigen 4 and programmed cell death 1, respectively, are encouraging examples of how research in this area can successfully translate into clinical use with promising results. Currently, several ongoing clinical trials are in progress testing new anti-cancer therapies based on the enhancement of immune cell activity against tumour antigens. Here we discuss the general concepts related to immunotherapy and the recent application to the treatment of cancer with positive results that support their consideration of clinical application to patients. PMID:25826229

The morphological classification of normal and abnormal red blood cell using Self Organizing Map

NASA Astrophysics Data System (ADS)

Rahmat, R. F.; Wulandari, F. S.; Faza, S.; Muchtar, M. A.; Siregar, I.

2018-02-01

Blood is an essential component of living creatures in the vascular space. For possible disease identification, it can be tested through a blood test, one of which can be seen from the form of red blood cells. The normal and abnormal morphology of the red blood cells of a patient is very helpful to doctors in detecting a disease. With the advancement of digital image processing technology can be used to identify normal and abnormal blood cells of a patient. This research used self-organizing map method to classify the normal and abnormal form of red blood cells in the digital image. The use of self-organizing map neural network method can be implemented to classify the normal and abnormal form of red blood cells in the input image with 93,78% accuracy testing.

Accurate path integration in continuous attractor network models of grid cells.

PubMed

Burak, Yoram; Fiete, Ila R

2009-02-01

Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.

Mechanisms of leading edge protrusion in interstitial migration

PubMed Central

Wilson, Kerry; Lewalle, Alexandre; Fritzsche, Marco; Thorogate, Richard; Duke, Tom; Charras, Guillaume

2013-01-01

While the molecular and biophysical mechanisms underlying cell protrusion on two-dimensional substrates are well understood, our knowledge of the actin structures driving protrusion in three-dimensional environments is poor, despite relevance to inflammation, development and cancer. Here we report that, during chemotactic migration through microchannels with 5 μm × 5 μm cross-sections, HL60 neutrophil-like cells assemble an actin-rich slab filling the whole channel cross-section at their front. This leading edge comprises two distinct F-actin networks: an adherent network that polymerizes perpendicular to cell-wall interfaces and a ‘free’ network that grows from the free membrane at the cell front. Each network is polymerized by a distinct nucleator and, due to their geometrical arrangement, the networks interact mechanically. On the basis of our experimental data, we propose that, during interstitial migration, medial growth of the adherent network compresses the free network preventing its retrograde movement and enabling new polymerization to be converted into forward protrusion. PMID:24305616

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

PubMed

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.

Comment on "A dynamic network model of mTOR signaling reveals TSC-independent mTORC2 regulation": building a model of the mTOR signaling network with a potentially faulty tool.

PubMed

Manning, Brendan D

2012-07-10

In their study published in Science Signaling (Research Article, 27 March 2012, DOI: 10.1126/scisignal.2002469), Dalle Pezze et al. tackle the dynamic and complex wiring of the signaling network involving the protein kinase mTOR, which exists within two distinct protein complexes (mTORC1 and mTORC2) that differ in their regulation and function. The authors use a combination of immunoblotting for specific phosphorylation events and computational modeling. The primary experimental tool employed is to monitor the autophosphorylation of mTOR on Ser(2481) in cell lysates as a surrogate for mTOR activity, which the authors conclude is a specific readout for mTORC2. However, Ser(2481) phosphorylation occurs on both mTORC1 and mTORC2 and will dynamically change as the network through which these two complexes are connected is manipulated. Therefore, models of mTOR network regulation built using this tool are inherently imperfect and open to alternative explanations. Specific issues with the main conclusion made in this study, involving the TSC1-TSC2 (tuberous sclerosis complex 1 and 2) complex and its potential regulation of mTORC2, are discussed here. A broader goal of this Letter is to clarify to other investigators the caveats of using mTOR Ser(2481) phosphorylation in cell lysates as a specific readout for either of the two mTOR complexes.

Exploiting Self-organization in Bioengineered Systems: A Computational Approach.

PubMed

Davis, Delin; Doloman, Anna; Podgorski, Gregory J; Vargis, Elizabeth; Flann, Nicholas S

2017-01-01

The productivity of bioengineered cell factories is limited by inefficiencies in nutrient delivery and waste and product removal. Current solution approaches explore changes in the physical configurations of the bioreactors. This work investigates the possibilities of exploiting self-organizing vascular networks to support producer cells within the factory. A computational model simulates de novo vascular development of endothelial-like cells and the resultant network functioning to deliver nutrients and extract product and waste from the cell culture. Microbial factories with vascular networks are evaluated for their scalability, robustness, and productivity compared to the cell factories without a vascular network. Initial studies demonstrate that at least an order of magnitude increase in production is possible, the system can be scaled up, and the self-organization of an efficient vascular network is robust. The work suggests that bioengineered multicellularity may offer efficiency improvements difficult to achieve with physical engineering approaches.

Decoding the Regulatory Network for Blood Development from Single-Cell Gene Expression Measurements

PubMed Central

Haghverdi, Laleh; Lilly, Andrew J.; Tanaka, Yosuke; Wilkinson, Adam C.; Buettner, Florian; Macaulay, Iain C.; Jawaid, Wajid; Diamanti, Evangelia; Nishikawa, Shin-Ichi; Piterman, Nir; Kouskoff, Valerie; Theis, Fabian J.; Fisher, Jasmin; Göttgens, Berthold

2015-01-01

Here we report the use of diffusion maps and network synthesis from state transition graphs to better understand developmental pathways from single cell gene expression profiling. We map the progression of mesoderm towards blood in the mouse by single-cell expression analysis of 3,934 cells, capturing cells with blood-forming potential at four sequential developmental stages. By adapting the diffusion plot methodology for dimensionality reduction to single-cell data, we reconstruct the developmental journey to blood at single-cell resolution. Using transitions between individual cellular states as input, we develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model that recapitulates blood development. Model predictions were validated by showing that Sox7 inhibits primitive erythropoiesis, and that Sox and Hox factors control early expression of Erg. We therefore demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that control organogenesis. PMID:25664528

Predicting gene regulatory networks by combining spatial and temporal gene expression data in Arabidopsis root stem cells

PubMed Central

de Luis Balaguer, Maria Angels; Fisher, Adam P.; Clark, Natalie M.; Fernandez-Espinosa, Maria Guadalupe; Möller, Barbara K.; Weijers, Dolf; Williams, Cranos; Lorenzo, Oscar; Sozzani, Rosangela

2017-01-01

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is essential for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. To accomplish this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network inference algorithm that combines clustering with dynamic Bayesian network inference. We leveraged the topology of our networks to infer potential major regulators. Specifically, through mathematical modeling and experimental validation, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center function. The results presented in this work show that our combination of molecular biology, computational biology, and mathematical modeling is an efficient approach to identify candidate factors that function in the stem cells. PMID:28827319

Geometry and network connectivity govern the mechanics of stress fibers.

PubMed

Kassianidou, Elena; Brand, Christoph A; Schwarz, Ulrich S; Kumar, Sanjay

2017-03-07

Actomyosin stress fibers (SFs) play key roles in driving polarized motility and generating traction forces, yet little is known about how tension borne by an individual SF is governed by SF geometry and its connectivity to other cytoskeletal elements. We now address this question by combining single-cell micropatterning with subcellular laser ablation to probe the mechanics of single, geometrically defined SFs. The retraction length of geometrically isolated SFs after cutting depends strongly on SF length, demonstrating that longer SFs dissipate more energy upon incision. Furthermore, when cell geometry and adhesive spacing are fixed, cell-to-cell heterogeneities in SF dissipated elastic energy can be predicted from varying degrees of physical integration with the surrounding network. We apply genetic, pharmacological, and computational approaches to demonstrate a causal and quantitative relationship between SF connectivity and mechanics for patterned cells and show that similar relationships hold for nonpatterned cells allowed to form cell-cell contacts in monolayer culture. Remarkably, dissipation of a single SF within a monolayer induces cytoskeletal rearrangements in cells long distances away. Finally, stimulation of cell migration leads to characteristic changes in network connectivity that promote SF bundling at the cell rear. Our findings demonstrate that SFs influence and are influenced by the networks in which they reside. Such higher order network interactions contribute in unexpected ways to cell mechanics and motility.

Direct lifts of coupled cell networks

NASA Astrophysics Data System (ADS)

Dias, A. P. S.; Moreira, C. S.

2018-04-01

In networks of dynamical systems, there are spaces defined in terms of equalities of cell coordinates which are flow-invariant under any dynamical system that has a form consistent with the given underlying network structure—the network synchrony subspaces. Given a network and one of its synchrony subspaces, any system with a form consistent with the network, restricted to the synchrony subspace, defines a new system which is consistent with a smaller network, called the quotient network of the original network by the synchrony subspace. Moreover, any system associated with the quotient can be interpreted as the restriction to the synchrony subspace of a system associated with the original network. We call the larger network a lift of the smaller network, and a lift can be interpreted as a result of the cellular splitting of the smaller network. In this paper, we address the question of the uniqueness in this lifting process in terms of the networks’ topologies. A lift G of a given network Q is said to be direct when there are no intermediate lifts of Q between them. We provide necessary and sufficient conditions for a lift of a general network to be direct. Our results characterize direct lifts using the subnetworks of all splitting cells of Q and of all split cells of G. We show that G is a direct lift of Q if and only if either the split subnetwork is a direct lift or consists of two copies of the splitting subnetwork. These results are then applied to the class of regular uniform networks and to the special classes of ring networks and acyclic networks. We also illustrate that one of the applications of our results is to the lifting bifurcation problem.

Network dynamics of 3D engineered neuronal cultures: a new experimental model for in-vitro electrophysiology.

PubMed

Frega, Monica; Tedesco, Mariateresa; Massobrio, Paolo; Pesce, Mattia; Martinoia, Sergio

2014-06-30

Despite the extensive use of in-vitro models for neuroscientific investigations and notwithstanding the growing field of network electrophysiology, all studies on cultured cells devoted to elucidate neurophysiological mechanisms and computational properties, are based on 2D neuronal networks. These networks are usually grown onto specific rigid substrates (also with embedded electrodes) and lack of most of the constituents of the in-vivo like environment: cell morphology, cell-to-cell interaction and neuritic outgrowth in all directions. Cells in a brain region develop in a 3D space and interact with a complex multi-cellular environment and extracellular matrix. Under this perspective, 3D networks coupled to micro-transducer arrays, represent a new and powerful in-vitro model capable of better emulating in-vivo physiology. In this work, we present a new experimental paradigm constituted by 3D hippocampal networks coupled to Micro-Electrode-Arrays (MEAs) and we show how the features of the recorded network dynamics differ from the corresponding 2D network model. Further development of the proposed 3D in-vitro model by adding embedded functionalized scaffolds might open new prospects for manipulating, stimulating and recording the neuronal activity to elucidate neurophysiological mechanisms and to design bio-hybrid microsystems.

Network dynamics of 3D engineered neuronal cultures: a new experimental model for in-vitro electrophysiology

PubMed Central

Frega, Monica; Tedesco, Mariateresa; Massobrio, Paolo; Pesce, Mattia; Martinoia, Sergio

2014-01-01

Despite the extensive use of in-vitro models for neuroscientific investigations and notwithstanding the growing field of network electrophysiology, all studies on cultured cells devoted to elucidate neurophysiological mechanisms and computational properties, are based on 2D neuronal networks. These networks are usually grown onto specific rigid substrates (also with embedded electrodes) and lack of most of the constituents of the in-vivo like environment: cell morphology, cell-to-cell interaction and neuritic outgrowth in all directions. Cells in a brain region develop in a 3D space and interact with a complex multi-cellular environment and extracellular matrix. Under this perspective, 3D networks coupled to micro-transducer arrays, represent a new and powerful in-vitro model capable of better emulating in-vivo physiology. In this work, we present a new experimental paradigm constituted by 3D hippocampal networks coupled to Micro-Electrode-Arrays (MEAs) and we show how the features of the recorded network dynamics differ from the corresponding 2D network model. Further development of the proposed 3D in-vitro model by adding embedded functionalized scaffolds might open new prospects for manipulating, stimulating and recording the neuronal activity to elucidate neurophysiological mechanisms and to design bio-hybrid microsystems. PMID:24976386

Mechanical Detection of a Long-Range Actin Network Emanating from a Biomimetic Cortex

PubMed Central

Bussonnier, Matthias; Carvalho, Kevin; Lemière, Joël; Joanny, Jean-François; Sykes, Cécile; Betz, Timo

2014-01-01

Actin is ubiquitous globular protein that polymerizes into filaments and forms networks that participate in the force generation of eukaryotic cells. Such forces are used for cell motility, cytokinesis, and tissue remodeling. Among those actin networks, we focus on the actin cortex, a dense branched network beneath the plasma membrane that is of particular importance for the mechanical properties of the cell. Here we reproduce the cellular cortex by activating actin filament growth on a solid surface. We unveil the existence of a sparse actin network that emanates from the surface and extends over a distance that is at least 10 times larger than the cortex itself. We call this sparse actin network the “actin cloud” and characterize its mechanical properties with optical tweezers. We show, both experimentally and theoretically, that the actin cloud is mechanically relevant and that it should be taken into account because it can sustain forces as high as several picoNewtons (pN). In particular, it is known that in plant cells, actin networks similar to the actin cloud have a role in positioning the nucleus; in large oocytes, they play a role in driving chromosome movement. Recent evidence shows that such networks even prevent granule condensation in large cells. PMID:25140420

Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists.

PubMed

Zhu, Xun; Wolfgruber, Thomas K; Tasato, Austin; Arisdakessian, Cédric; Garmire, David G; Garmire, Lana X

2017-12-05

Single-cell RNA sequencing (scRNA-Seq) is an increasingly popular platform to study heterogeneity at the single-cell level. Computational methods to process scRNA-Seq data are not very accessible to bench scientists as they require a significant amount of bioinformatic skills. We have developed Granatum, a web-based scRNA-Seq analysis pipeline to make analysis more broadly accessible to researchers. Without a single line of programming code, users can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface. Granatum conveniently walks users through various steps of scRNA-Seq analysis. It has a comprehensive list of modules, including plate merging and batch-effect removal, outlier-sample removal, gene-expression normalization, imputation, gene filtering, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein network interaction visualization, and pseudo-time cell series construction. Granatum enables broad adoption of scRNA-Seq technology by empowering bench scientists with an easy-to-use graphical interface for scRNA-Seq data analysis. The package is freely available for research use at http://garmiregroup.org/granatum/app.

Cell type-selective disease-association of genes under high regulatory load.

PubMed

Galhardo, Mafalda; Berninger, Philipp; Nguyen, Thanh-Phuong; Sauter, Thomas; Sinkkonen, Lasse

2015-10-15

We previously showed that disease-linked metabolic genes are often under combinatorial regulation. Using the genome-wide ChIP-Seq binding profiles for 93 transcription factors in nine different cell lines, we show that genes under high regulatory load are significantly enriched for disease-association across cell types. We find that transcription factor load correlates with the enhancer load of the genes and thereby allows the identification of genes under high regulatory load by epigenomic mapping of active enhancers. Identification of the high enhancer load genes across 139 samples from 96 different cell and tissue types reveals a consistent enrichment for disease-associated genes in a cell type-selective manner. The underlying genes are not limited to super-enhancer genes and show several types of disease-association evidence beyond genetic variation (such as biomarkers). Interestingly, the high regulatory load genes are involved in more KEGG pathways than expected by chance, exhibit increased betweenness centrality in the interaction network of liver disease genes, and carry longer 3' UTRs with more microRNA (miRNA) binding sites than genes on average, suggesting a role as hubs integrating signals within regulatory networks. In summary, epigenetic mapping of active enhancers presents a promising and unbiased approach for identification of novel disease genes in a cell type-selective manner. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Neural stem cells and neuro/gliogenesis in the central nervous system: understanding the structural and functional plasticity of the developing, mature, and diseased brain.

PubMed

Yamaguchi, Masahiro; Seki, Tatsunori; Imayoshi, Itaru; Tamamaki, Nobuaki; Hayashi, Yoshitaka; Tatebayashi, Yoshitaka; Hitoshi, Seiji

2016-05-01

Neurons and glia in the central nervous system (CNS) originate from neural stem cells (NSCs). Knowledge of the mechanisms of neuro/gliogenesis from NSCs is fundamental to our understanding of how complex brain architecture and function develop. NSCs are present not only in the developing brain but also in the mature brain in adults. Adult neurogenesis likely provides remarkable plasticity to the mature brain. In addition, recent progress in basic research in mental disorders suggests an etiological link with impaired neuro/gliogenesis in particular brain regions. Here, we review the recent progress and discuss future directions in stem cell and neuro/gliogenesis biology by introducing several topics presented at a joint meeting of the Japanese Association of Anatomists and the Physiological Society of Japan in 2015. Collectively, these topics indicated that neuro/gliogenesis from NSCs is a common event occurring in many brain regions at various ages in animals. Given that significant structural and functional changes in cells and neural networks are accompanied by neuro/gliogenesis from NSCs and the integration of newly generated cells into the network, stem cell and neuro/gliogenesis biology provides a good platform from which to develop an integrated understanding of the structural and functional plasticity that underlies the development of the CNS, its remodeling in adulthood, and the recovery from diseases that affect it.

The Haematological Malignancy Research Network (HMRN): a new information strategy for population based epidemiology and health service research

PubMed Central

Smith, Alexandra; Roman, Eve; Howell, Debra; Jones, Richard; Patmore, Russell; Jack, Andrew

2010-01-01

The Haematological Malignancy Research Network (HMRN) was established in 2004 to provide robust generalizable data to inform clinical practice and research. It comprises an ongoing population-based cohort of patients newly diagnosed by a single integrated haematopathology laboratory in two adjacent UK Cancer Networks (population 3·6 million). With an emphasis on primary-source data, prognostic factors, sequential treatment/response history, and socio-demographic details are recorded to clinical trial standards. Data on 8131 patients diagnosed over the 4 years 2004–08 are examined here using the latest World Health Organization classification. HMRN captures all diagnoses (adult and paediatric) and the diagnostic age ranged from 4 weeks to 99 years (median 70·4 years). In line with published estimates, first-line clinical trial entry varied widely by disease subtype and age, falling from 59·5% in those aged <15 years to 1·9% in those aged over 75 years – underscoring the need for contextual population-based treatment and response data of the type collected by HMRN. The critical importance of incorporating molecular and prognostic markers into comparative survival analyses is illustrated with reference to diffuse-large B-cell lymphoma, acute myeloid leukaemia and myeloma. With respect to aetiology, several descriptive factors are highlighted and discussed, including the unexplained male predominance evident for most subtypes across all ages. PMID:19958356

Automated Deep Learning-Based System to Identify Endothelial Cells Derived from Induced Pluripotent Stem Cells.

PubMed

Kusumoto, Dai; Lachmann, Mark; Kunihiro, Takeshi; Yuasa, Shinsuke; Kishino, Yoshikazu; Kimura, Mai; Katsuki, Toshiomi; Itoh, Shogo; Seki, Tomohisa; Fukuda, Keiichi

2018-06-05

Deep learning technology is rapidly advancing and is now used to solve complex problems. Here, we used deep learning in convolutional neural networks to establish an automated method to identify endothelial cells derived from induced pluripotent stem cells (iPSCs), without the need for immunostaining or lineage tracing. Networks were trained to predict whether phase-contrast images contain endothelial cells based on morphology only. Predictions were validated by comparison to immunofluorescence staining for CD31, a marker of endothelial cells. Method parameters were then automatically and iteratively optimized to increase prediction accuracy. We found that prediction accuracy was correlated with network depth and pixel size of images to be analyzed. Finally, K-fold cross-validation confirmed that optimized convolutional neural networks can identify endothelial cells with high performance, based only on morphology. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Dynamic assembly of ultrasoft colloidal networks enables cell invasion within restrictive fibrillar polymers

PubMed Central

Douglas, Alison M.; Fragkopoulos, Alexandros A.; Gaines, Michelle K.; Lyon, L. Andrew; Fernandez-Nieves, Alberto

2017-01-01

In regenerative medicine, natural protein-based polymers offer enhanced endogenous bioactivity and potential for seamless integration with tissue, yet form weak hydrogels that lack the physical robustness required for surgical manipulation, making them difficult to apply in practice. The use of higher concentrations of protein, exogenous cross-linkers, and blending synthetic polymers has all been applied to form more mechanically robust networks. Each relies on generating a smaller network mesh size, which increases the elastic modulus and robustness, but critically inhibits cell spreading and migration, hampering tissue regeneration. Here we report two unique observations; first, that colloidal suspensions, at sufficiently high volume fraction (ϕ), dynamically assemble into a fully percolated 3D network within high-concentration protein polymers. Second, cells appear capable of leveraging these unique domains for highly efficient cell migration throughout the composite construct. In contrast to porogens, the particles in our system remain embedded within the bulk polymer, creating a network of particle-filled tunnels. Whereas this would normally physically restrict cell motility, when the particulate network is created using ultralow cross-linked microgels, the colloidal suspension displays viscous behavior on the same timescale as cell spreading and migration and thus enables efficient cell infiltration of the construct through the colloidal-filled tunnels. PMID:28100492

Network approach to patterns in stratocumulus clouds

NASA Astrophysics Data System (ADS)

Glassmeier, Franziska; Feingold, Graham

2017-10-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Dynamic assembly of ultrasoft colloidal networks enables cell invasion within restrictive fibrillar polymers

NASA Astrophysics Data System (ADS)

Douglas, Alison M.; Fragkopoulos, Alexandros A.; Gaines, Michelle K.; Lyon, L. Andrew; Fernandez-Nieves, Alberto; Barker, Thomas H.

2017-01-01

In regenerative medicine, natural protein-based polymers offer enhanced endogenous bioactivity and potential for seamless integration with tissue, yet form weak hydrogels that lack the physical robustness required for surgical manipulation, making them difficult to apply in practice. The use of higher concentrations of protein, exogenous cross-linkers, and blending synthetic polymers has all been applied to form more mechanically robust networks. Each relies on generating a smaller network mesh size, which increases the elastic modulus and robustness, but critically inhibits cell spreading and migration, hampering tissue regeneration. Here we report two unique observations; first, that colloidal suspensions, at sufficiently high volume fraction (ϕ), dynamically assemble into a fully percolated 3D network within high-concentration protein polymers. Second, cells appear capable of leveraging these unique domains for highly efficient cell migration throughout the composite construct. In contrast to porogens, the particles in our system remain embedded within the bulk polymer, creating a network of particle-filled tunnels. Whereas this would normally physically restrict cell motility, when the particulate network is created using ultralow cross-linked microgels, the colloidal suspension displays viscous behavior on the same timescale as cell spreading and migration and thus enables efficient cell infiltration of the construct through the colloidal-filled tunnels.

Network approach to patterns in stratocumulus clouds.

PubMed

Glassmeier, Franziska; Feingold, Graham

2017-10-03

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth's climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis's Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Network approach to patterns in stratocumulus clouds

PubMed Central

Feingold, Graham

2017-01-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav–Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes. PMID:28904097

The small world of osteocytes: connectomics of the lacuno-canalicular network in bone

NASA Astrophysics Data System (ADS)

Kollmannsberger, Philip; Kerschnitzki, Michael; Repp, Felix; Wagermaier, Wolfgang; Weinkamer, Richard; Fratzl, Peter

2017-07-01

Osteocytes and their cell processes reside in a large, interconnected network of voids pervading the mineralized bone matrix of most vertebrates. This osteocyte lacuno-canalicular network (OLCN) is believed to play important roles in mechanosensing, mineral homeostasis, and for the mechanical properties of bone. While the extracellular matrix structure of bone is extensively studied on ultrastructural and macroscopic scales, there is a lack of quantitative knowledge on how the cellular network is organized. Using a recently introduced imaging and quantification approach, we analyze the OLCN in different bone types from mouse and sheep that exhibit different degrees of structural organization not only of the cell network but also of the fibrous matrix deposited by the cells. We define a number of robust, quantitative measures that are derived from the theory of complex networks. These measures enable us to gain insights into how efficient the network is organized with regard to intercellular transport and communication. Our analysis shows that the cell network in regularly organized, slow-growing bone tissue from sheep is less connected, but more efficiently organized compared to irregular and fast-growing bone tissue from mice. On the level of statistical topological properties (edges per node, edge length and degree distribution), both network types are indistinguishable, highlighting that despite pronounced differences at the tissue level, the topological architecture of the osteocyte canalicular network at the subcellular level may be independent of species and bone type. Our results suggest a universal mechanism underlying the self-organization of individual cells into a large, interconnected network during bone formation and mineralization.

The effect of cell phones on human health

NASA Astrophysics Data System (ADS)

Abu-Isbeih, Ibrahim N.; Saad, Dina

2011-10-01

The effect of cell phone radiation on human health is the subject of recent interest and study, as a result of the enormous increase in cell phone usage throughout the world. Cell phones use electromagnetic radiation in the microwave range, which some believe may be harmful to human health. Other digital wireless systems, such as data communication networks, produce similar radiation. The objective of this survey is to review the effects of cell phones on human health: A large body of research exists, both epidemiological and experimental, in non-human animals and in humans, of which the majority shows no definite causative relationship between exposure to cell phones and harmful biological effects in humans. This is often paraphrased simply as the balance of evidence showing no harm to humans from cell phones, although a significant number of individual studies do suggest such a relationship, or are inconclusive.

Trans-species learning of cellular signaling systems with bimodal deep belief networks

PubMed Central

Chen, Lujia; Cai, Chunhui; Chen, Vicky; Lu, Xinghua

2015-01-01

Motivation: Model organisms play critical roles in biomedical research of human diseases and drug development. An imperative task is to translate information/knowledge acquired from model organisms to humans. In this study, we address a trans-species learning problem: predicting human cell responses to diverse stimuli, based on the responses of rat cells treated with the same stimuli. Results: We hypothesized that rat and human cells share a common signal-encoding mechanism but employ different proteins to transmit signals, and we developed a bimodal deep belief network and a semi-restricted bimodal deep belief network to represent the common encoding mechanism and perform trans-species learning. These ‘deep learning’ models include hierarchically organized latent variables capable of capturing the statistical structures in the observed proteomic data in a distributed fashion. The results show that the models significantly outperform two current state-of-the-art classification algorithms. Our study demonstrated the potential of using deep hierarchical models to simulate cellular signaling systems. Availability and implementation: The software is available at the following URL: http://pubreview.dbmi.pitt.edu/TransSpeciesDeepLearning/. The data are available through SBV IMPROVER website, https://www.sbvimprover.com/challenge-2/overview, upon publication of the report by the organizers. Contact: xinghua@pitt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25995230

Trans-species learning of cellular signaling systems with bimodal deep belief networks.

PubMed

Chen, Lujia; Cai, Chunhui; Chen, Vicky; Lu, Xinghua

2015-09-15

Model organisms play critical roles in biomedical research of human diseases and drug development. An imperative task is to translate information/knowledge acquired from model organisms to humans. In this study, we address a trans-species learning problem: predicting human cell responses to diverse stimuli, based on the responses of rat cells treated with the same stimuli. We hypothesized that rat and human cells share a common signal-encoding mechanism but employ different proteins to transmit signals, and we developed a bimodal deep belief network and a semi-restricted bimodal deep belief network to represent the common encoding mechanism and perform trans-species learning. These 'deep learning' models include hierarchically organized latent variables capable of capturing the statistical structures in the observed proteomic data in a distributed fashion. The results show that the models significantly outperform two current state-of-the-art classification algorithms. Our study demonstrated the potential of using deep hierarchical models to simulate cellular signaling systems. The software is available at the following URL: http://pubreview.dbmi.pitt.edu/TransSpeciesDeepLearning/. The data are available through SBV IMPROVER website, https://www.sbvimprover.com/challenge-2/overview, upon publication of the report by the organizers. xinghua@pitt.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Cell-cell bioelectrical interactions and local heterogeneities in genetic networks: a model for the stabilization of single-cell states and multicellular oscillations.

PubMed

Cervera, Javier; Manzanares, José A; Mafe, Salvador

2018-04-04

Genetic networks operate in the presence of local heterogeneities in single-cell transcription and translation rates. Bioelectrical networks and spatio-temporal maps of cell electric potentials can influence multicellular ensembles. Could cell-cell bioelectrical interactions mediated by intercellular gap junctions contribute to the stabilization of multicellular states against local genetic heterogeneities? We theoretically analyze this question on the basis of two well-established experimental facts: (i) the membrane potential is a reliable read-out of the single-cell electrical state and (ii) when the cells are coupled together, their individual cell potentials can be influenced by ensemble-averaged electrical potentials. We propose a minimal biophysical model for the coupling between genetic and bioelectrical networks that associates the local changes occurring in the transcription and translation rates of an ion channel protein with abnormally low (depolarized) cell potentials. We then analyze the conditions under which the depolarization of a small region (patch) in a multicellular ensemble can be reverted by its bioelectrical coupling with the (normally polarized) neighboring cells. We show also that the coupling between genetic and bioelectric networks of non-excitable cells, modulated by average electric potentials at the multicellular ensemble level, can produce oscillatory phenomena. The simulations show the importance of single-cell potentials characteristic of polarized and depolarized states, the relative sizes of the abnormally polarized patch and the rest of the normally polarized ensemble, and intercellular coupling.

Cooperation among cancer cells as public goods games on Voronoi networks.

PubMed

Archetti, Marco

2016-05-07

Cancer cells produce growth factors that diffuse and sustain tumour proliferation, a form of cooperation that can be studied using mathematical models of public goods in the framework of evolutionary game theory. Cell populations, however, form heterogeneous networks that cannot be described by regular lattices or scale-free networks, the types of graphs generally used in the study of cooperation. To describe the dynamics of growth factor production in populations of cancer cells, I study public goods games on Voronoi networks, using a range of non-linear benefits that account for the known properties of growth factors, and different types of diffusion gradients. The results are surprisingly similar to those obtained on regular graphs and different from results on scale-free networks, revealing that network heterogeneity per se does not promote cooperation when public goods diffuse beyond one-step neighbours. The exact shape of the diffusion gradient is not crucial, however, whereas the type of non-linear benefit is an essential determinant of the dynamics. Public goods games on Voronoi networks can shed light on intra-tumour heterogeneity, the evolution of resistance to therapies that target growth factors, and new types of cell therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Phenotypic stability and plasticity in GMP-derived cells as determined by their underlying regulatory network.

PubMed

Ramírez, Carlos; Mendoza, Luis

2018-04-01

Blood cell formation has been recognized as a suitable system to study celular differentiation mainly because of its experimental accessibility, and because it shows characteristics such as hierarchical and gradual bifurcated patterns of commitment, which are present in several developmental processes. Although hematopoiesis has been extensively studied and there is a wealth of molecular and cellular data about it, it is not clear how the underlying molecular regulatory networks define or restrict cellular differentiation processes. Here, we infer the molecular regulatory network that controls the differentiation of a blood cell subpopulation derived from the granulocyte-monocyte precursor (GMP), comprising monocytes, neutrophils, eosinophils, basophils and mast cells. We integrate published qualitative experimental data into a model to describe temporal expression patterns observed in GMP-derived cells. The model is implemented as a Boolean network, and its dynamical behavior is studied. Steady states of the network can be clearly identified with the expression profiles of monocytes, mast cells, neutrophils, basophils, and eosinophils, under wild-type and mutant backgrounds. All scripts are publicly available at https://github.com/caramirezal/RegulatoryNetworkGMPModel. lmendoza@biomedicas.unam.mx. Supplementary data are available at Bioinformatics online.

[Social networks in drinking behaviors among Japanese: support network, drinking network, and intervening network].

PubMed

Yoshihara, Chika; Shimizu, Shinji

2005-10-01

The national representative sample was analyzed to examine the relationship between respondents' drinking practice and the social network which was constructed of three different types of network: support network, drinking network, and intervening network. Non-parametric statistical analysis was conducted with chi square method and ANOVA analysis, due to the risk of small samples in some basic tabulation cells. The main results are as follows: (1) In the support network of workplace associates, moderate drinkers enjoyed much more sociable support care than both nondrinkers and hard drinkers, which might suggest a similar effect as the French paradox. Meanwhile in the familial and kinship network, the more intervening care support was provided, the harder respondents' drinking practice. (2) The drinking network among Japanese people for both sexes is likely to be convergent upon certain types of network categories and not decentralized in various categories. This might reflect of the drinking culture of Japan, which permits people to drink everyday as a practice, especially male drinkers. Subsequently, solitary drinking is not optional for female drinkers. (3) Intervening network analysis showed that the harder the respondents' drinking practices, the more frequently their drinking behaviors were checked in almost all the categories of network. A rather complicated gender double-standard was found in the network of hard drinkers with their friends, particularly for female drinkers. Medical professionals played a similar intervening role for men as family and kinship networks but to a less degree than friends for females. The social network is considerably associated with respondents' drinking, providing both sociability for moderate drinkers and intervention for hard drinkers, depending on network categories. To minimize the risk of hard drinking and advance self-healthy drinking there should be more research development on drinking practice and the social network.

Intrinsic protective mechanisms of the neuron-glia network against glioma invasion.

PubMed

Iwadate, Yasuo; Fukuda, Kazumasa; Matsutani, Tomoo; Saeki, Naokatsu

2016-04-01

Gliomas arising in the brain parenchyma infiltrate into the surrounding brain and break down established complex neuron-glia networks. However, mounting evidence suggests that initially the network microenvironment of the adult central nervous system (CNS) is innately non-permissive to glioma cell invasion. The main players are inhibitory molecules in CNS myelin, as well as proteoglycans associated with astrocytes. Neural stem cells, and neurons themselves, possess inhibitory functions against neighboring tumor cells. These mechanisms have evolved to protect the established neuron-glia network, which is necessary for brain function. Greater insight into the interaction between glioma cells and the surrounding neuron-glia network is crucial for developing new therapies for treating these devastating tumors while preserving the important and complex neural functions of patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

Progress and Prospects for Stem Cell Engineering

PubMed Central

Ashton, Randolph S.; Keung, Albert J.; Peltier, Joseph; Schaffer, David V.

2018-01-01

Stem cells offer tremendous biomedical potential owing to their abilities to self-renew and differentiate into cell types of multiple adult tissues. Researchers and engineers have increasingly developed novel discovery technologies, theoretical approaches, and cell culture systems to investigate microenvironmental cues and cellular signaling events that control stem cell fate. Many of these technologies facilitate high-throughput investigation of microenvironmental signals and the intracellular signaling networks and machinery processing those signals into cell fate decisions. As our aggregate empirical knowledge of stem cell regulation grows, theoretical modeling with systems and computational biology methods has and will continue to be important for developing our ability to analyze and extract important conceptual features of stem cell regulation from complex data. Based on this body of knowledge, stem cell engineers will continue to develop technologies that predictably control stem cell fate with the ultimate goal of being able to accurately and economically scale up these systems for clinical-grade production of stem cell therapeutics. PMID:22432628

50 years of Arabidopsis research: highlights and future directions.

PubMed

Provart, Nicholas J; Alonso, Jose; Assmann, Sarah M; Bergmann, Dominique; Brady, Siobhan M; Brkljacic, Jelena; Browse, John; Chapple, Clint; Colot, Vincent; Cutler, Sean; Dangl, Jeff; Ehrhardt, David; Friesner, Joanna D; Frommer, Wolf B; Grotewold, Erich; Meyerowitz, Elliot; Nemhauser, Jennifer; Nordborg, Magnus; Pikaard, Craig; Shanklin, John; Somerville, Chris; Stitt, Mark; Torii, Keiko U; Waese, Jamie; Wagner, Doris; McCourt, Peter

2016-02-01

922 I. 922 II. 922 III. 925 IV. 925 V. 926 VI. 927 VII. 928 VIII. 929 IX. 930 X. 931 XI. 932 XII. 933 XIII. Natural variation and genome-wide association studies 934 XIV. 934 XV. 935 XVI. 936 XVII. 937 937 References 937 SUMMARY: The year 2014 marked the 25(th) International Conference on Arabidopsis Research. In the 50 yr since the first International Conference on Arabidopsis Research, held in 1965 in Göttingen, Germany, > 54 000 papers that mention Arabidopsis thaliana in the title, abstract or keywords have been published. We present herein a citational network analysis of these papers, and touch on some of the important discoveries in plant biology that have been made in this powerful model system, and highlight how these discoveries have then had an impact in crop species. We also look to the future, highlighting some outstanding questions that can be readily addressed in Arabidopsis. Topics that are discussed include Arabidopsis reverse genetic resources, stock centers, databases and online tools, cell biology, development, hormones, plant immunity, signaling in response to abiotic stress, transporters, biosynthesis of cells walls and macromolecules such as starch and lipids, epigenetics and epigenomics, genome-wide association studies and natural variation, gene regulatory networks, modeling and systems biology, and synthetic biology. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Colleagues as Change Agents: How Department Networks and Opinion Leaders Influence Teaching at a Single Research University.

PubMed

Andrews, T C; Conaway, E P; Zhao, J; Dolan, E L

2016-01-01

Relationships with colleagues have the potential to be a source of support for faculty to make meaningful change in how they teach, but the impact of these relationships is poorly understood. We used a mixed-methods approach to investigate the characteristics of faculty who provide colleagues with teaching resources and facilitate change in teaching, how faculty influence one another. Our exploratory investigation was informed by social network theory and research on the impact of opinion leaders within organizations. We used surveys and interviews to examine collegial interactions about undergraduate teaching in life sciences departments at one research university. Each department included discipline-based education researchers (DBERs). Quantitative and qualitative analyses indicate that DBERs promote changes in teaching to a greater degree than other departmental colleagues. The influence of DBERs derives, at least partly, from a perception that they have unique professional expertise in education. DBERs facilitated change through coteaching, offering ready and approachable access to education research, and providing teaching training and mentoring. Faculty who had participated in a team based-teaching professional development program were also credited with providing more support for teaching than nonparticipants. Further research will be necessary to determine whether these results generalize beyond the studied institution. © 2016 T. C. Andrews et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Network reconstruction and systems analysis of plant cell wall deconstruction by Neurospora crassa.

PubMed

Samal, Areejit; Craig, James P; Coradetti, Samuel T; Benz, J Philipp; Eddy, James A; Price, Nathan D; Glass, N Louise

2017-01-01

Plant biomass degradation by fungal-derived enzymes is rapidly expanding in economic importance as a clean and efficient source for biofuels. The ability to rationally engineer filamentous fungi would facilitate biotechnological applications for degradation of plant cell wall polysaccharides. However, incomplete knowledge of biomolecular networks responsible for plant cell wall deconstruction impedes experimental efforts in this direction. To expand this knowledge base, a detailed network of reactions important for deconstruction of plant cell wall polysaccharides into simple sugars was constructed for the filamentous fungus Neurospora crassa . To reconstruct this network, information was integrated from five heterogeneous data types: functional genomics, transcriptomics, proteomics, genetics, and biochemical characterizations. The combined information was encapsulated into a feature matrix and the evidence weighted to assign annotation confidence scores for each gene within the network. Comparative analyses of RNA-seq and ChIP-seq data shed light on the regulation of the plant cell wall degradation network, leading to a novel hypothesis for degradation of the hemicellulose mannan. The transcription factor CLR-2 was subsequently experimentally shown to play a key role in the mannan degradation pathway of N. crassa . Here we built a network that serves as a scaffold for integration of diverse experimental datasets. This approach led to the elucidation of regulatory design principles for plant cell wall deconstruction by filamentous fungi and a novel function for the transcription factor CLR-2. This expanding network will aid in efforts to rationally engineer industrially relevant hyper-production strains.

Modeling extracellular fields for a three-dimensional network of cells using NEURON.

PubMed

Appukuttan, Shailesh; Brain, Keith L; Manchanda, Rohit

2017-10-01

Computational modeling of biological cells usually ignores their extracellular fields, assuming them to be inconsequential. Though such an assumption might be justified in certain cases, it is debatable for networks of tightly packed cells, such as in the central nervous system and the syncytial tissues of cardiac and smooth muscle. In the present work, we demonstrate a technique to couple the extracellular fields of individual cells within the NEURON simulation environment. The existing features of the simulator are extended by explicitly defining current balance equations, resulting in the coupling of the extracellular fields of adjacent cells. With this technique, we achieved continuity of extracellular space for a network model, thereby allowing the exploration of extracellular interactions computationally. Using a three-dimensional network model, passive and active electrical properties were evaluated under varying levels of extracellular volumes. Simultaneous intracellular and extracellular recordings for synaptic and action potentials were analyzed, and the potential of ephaptic transmission towards functional coupling of cells was explored. We have implemented a true bi-domain representation of a network of cells, with the extracellular domain being continuous throughout the entire model. This has hitherto not been achieved using NEURON, or other compartmental modeling platforms. We have demonstrated the coupling of the extracellular field of every cell in a three-dimensional model to obtain a continuous uniform extracellular space. This technique provides a framework for the investigation of interactions in tightly packed networks of cells via their extracellular fields. Copyright © 2017 Elsevier B.V. All rights reserved.

Additive Manufacturing of Biomedical Constructs with Biomimetic Structural Organizations

PubMed Central

Li, Xiao; He, Jiankang; Zhang, Weijie; Jiang, Nan; Li, Dichen

2016-01-01

Additive manufacturing (AM), sometimes called three-dimensional (3D) printing, has attracted a lot of research interest and is presenting unprecedented opportunities in biomedical fields, because this technology enables the fabrication of biomedical constructs with great freedom and in high precision. An important strategy in AM of biomedical constructs is to mimic the structural organizations of natural biological organisms. This can be done by directly depositing cells and biomaterials, depositing biomaterial structures before seeding cells, or fabricating molds before casting biomaterials and cells. This review organizes the research advances of AM-based biomimetic biomedical constructs into three major directions: 3D constructs that mimic tubular and branched networks of vasculatures; 3D constructs that contains gradient interfaces between different tissues; and 3D constructs that have different cells positioned to create multicellular systems. Other recent advances are also highlighted, regarding the applications of AM for organs-on-chips, AM-based micro/nanostructures, and functional nanomaterials. Under this theme, multiple aspects of AM including imaging/characterization, material selection, design, and printing techniques are discussed. The outlook at the end of this review points out several possible research directions for the future. PMID:28774030

Geometry and network connectivity govern the mechanics of stress fibers

PubMed Central

Kassianidou, Elena; Brand, Christoph A.; Kumar, Sanjay

2017-01-01

Actomyosin stress fibers (SFs) play key roles in driving polarized motility and generating traction forces, yet little is known about how tension borne by an individual SF is governed by SF geometry and its connectivity to other cytoskeletal elements. We now address this question by combining single-cell micropatterning with subcellular laser ablation to probe the mechanics of single, geometrically defined SFs. The retraction length of geometrically isolated SFs after cutting depends strongly on SF length, demonstrating that longer SFs dissipate more energy upon incision. Furthermore, when cell geometry and adhesive spacing are fixed, cell-to-cell heterogeneities in SF dissipated elastic energy can be predicted from varying degrees of physical integration with the surrounding network. We apply genetic, pharmacological, and computational approaches to demonstrate a causal and quantitative relationship between SF connectivity and mechanics for patterned cells and show that similar relationships hold for nonpatterned cells allowed to form cell–cell contacts in monolayer culture. Remarkably, dissipation of a single SF within a monolayer induces cytoskeletal rearrangements in cells long distances away. Finally, stimulation of cell migration leads to characteristic changes in network connectivity that promote SF bundling at the cell rear. Our findings demonstrate that SFs influence and are influenced by the networks in which they reside. Such higher order network interactions contribute in unexpected ways to cell mechanics and motility. PMID:28213499

An integrated approach to characterize transcription factor and microRNA regulatory networks involved in Schwann cell response to peripheral nerve injury

PubMed Central

2013-01-01

Background The regenerative response of Schwann cells after peripheral nerve injury is a critical process directly related to the pathophysiology of a number of neurodegenerative diseases. This SC injury response is dependent on an intricate gene regulatory program coordinated by a number of transcription factors and microRNAs, but the interactions among them remain largely unknown. Uncovering the transcriptional and post-transcriptional regulatory networks governing the Schwann cell injury response is a key step towards a better understanding of Schwann cell biology and may help develop novel therapies for related diseases. Performing such comprehensive network analysis requires systematic bioinformatics methods to integrate multiple genomic datasets. Results In this study we present a computational pipeline to infer transcription factor and microRNA regulatory networks. Our approach combined mRNA and microRNA expression profiling data, ChIP-Seq data of transcription factors, and computational transcription factor and microRNA target prediction. Using mRNA and microRNA expression data collected in a Schwann cell injury model, we constructed a regulatory network and studied regulatory pathways involved in Schwann cell response to injury. Furthermore, we analyzed network motifs and obtained insights on cooperative regulation of transcription factors and microRNAs in Schwann cell injury recovery. Conclusions This work demonstrates a systematic method for gene regulatory network inference that may be used to gain new information on gene regulation by transcription factors and microRNAs. PMID:23387820

Identifying the architecture of a supracellular actomyosin network that induces tissue folding

NASA Astrophysics Data System (ADS)

Yevick, Hannah; Stoop, Norbert; Dunkel, Jorn; Martin, Adam

During embryonic development, the establishment of correct tissue form ensures proper tissue function. Yet, how the thousands of cells within a tissue coordinate force production to sculpt tissue shape is poorly understood. One important tissue shape change is tissue folding where a cell sheet bends to form a closed tube. Drosophila (fruit fly) embryos undergo such a folding event, called ventral furrow formation. The ventral furrow is associated with a supracellular network of actin and myosin, where actin-myosin fibers assemble and connect between cells. It is not known how this tissue-wide network grows and connects over time, how reproducible it is between embryos, and what determines its architecture. Here, we used topological feature analysis to quantitatively and dynamically map the connections and architecture of this supracellular network across hundreds of cells in the folding tissue. We identified the importance of the cell unit in setting up the tissue-scale architecture of the network. Our mathematical framework allows us to explore stereotypic properties of the myosin network such that we can investigate the reproducibility of mechanical connections for a morphogenetic process. NIH F32.

Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters

NASA Astrophysics Data System (ADS)

Munsky, Brian; Trinh, Brooke; Khammash, Mustafa

2010-03-01

The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations exhibit cell-to-cell variability that can manifest significant prototypical differences. Noise induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified using flow cytometry, single molecule fluorescence in situ hybridization, time lapse fluorescence microscopy and other single cell and single molecule measurement techniques. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We demonstrate that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. We use theoretical investigations to establish experimental guidelines for the identification of gene regulatory networks, and we apply these guideline to experimentally identify predictive models for different regulatory mechanisms in bacteria and yeast.

Towards a Framework for Evolvable Network Design

NASA Astrophysics Data System (ADS)

Hassan, Hoda; Eltarras, Ramy; Eltoweissy, Mohamed

The layered Internet architecture that had long guided network design and protocol engineering was an “interconnection architecture” defining a framework for interconnecting networks rather than a model for generic network structuring and engineering. We claim that the approach of abstracting the network in terms of an internetwork hinders the thorough understanding of the network salient characteristics and emergent behavior resulting in impeding design evolution required to address extreme scale, heterogeneity, and complexity. This paper reports on our work in progress that aims to: 1) Investigate the problem space in terms of the factors and decisions that influenced the design and development of computer networks; 2) Sketch the core principles for designing complex computer networks; and 3) Propose a model and related framework for building evolvable, adaptable and self organizing networks We will adopt a bottom up strategy primarily focusing on the building unit of the network model, which we call the “network cell”. The model is inspired by natural complex systems. A network cell is intrinsically capable of specialization, adaptation and evolution. Subsequently, we propose CellNet; a framework for evolvable network design. We outline scenarios for using the CellNet framework to enhance legacy Internet protocol stack.

Extracting grid cell characteristics from place cell inputs using non-negative principal component analysis

PubMed Central

Dordek, Yedidyah; Soudry, Daniel; Meir, Ron; Derdikman, Dori

2016-01-01

Many recent models study the downstream projection from grid cells to place cells, while recent data have pointed out the importance of the feedback projection. We thus asked how grid cells are affected by the nature of the input from the place cells. We propose a single-layer neural network with feedforward weights connecting place-like input cells to grid cell outputs. Place-to-grid weights are learned via a generalized Hebbian rule. The architecture of this network highly resembles neural networks used to perform Principal Component Analysis (PCA). Both numerical results and analytic considerations indicate that if the components of the feedforward neural network are non-negative, the output converges to a hexagonal lattice. Without the non-negativity constraint, the output converges to a square lattice. Consistent with experiments, grid spacing ratio between the first two consecutive modules is −1.4. Our results express a possible linkage between place cell to grid cell interactions and PCA. DOI: http://dx.doi.org/10.7554/eLife.10094.001 PMID:26952211

Fundamental trade-offs between information flow in single cells and cellular populations.

PubMed

Suderman, Ryan; Bachman, John A; Smith, Adam; Sorger, Peter K; Deeds, Eric J

2017-05-30

Signal transduction networks allow eukaryotic cells to make decisions based on information about intracellular state and the environment. Biochemical noise significantly diminishes the fidelity of signaling: networks examined to date seem to transmit less than 1 bit of information. It is unclear how networks that control critical cell-fate decisions (e.g., cell division and apoptosis) can function with such low levels of information transfer. Here, we use theory, experiments, and numerical analysis to demonstrate an inherent trade-off between the information transferred in individual cells and the information available to control population-level responses. Noise in receptor-mediated apoptosis reduces information transfer to approximately 1 bit at the single-cell level but allows 3-4 bits of information to be transmitted at the population level. For processes such as eukaryotic chemotaxis, in which single cells are the functional unit, we find high levels of information transmission at a single-cell level. Thus, low levels of information transfer are unlikely to represent a physical limit. Instead, we propose that signaling networks exploit noise at the single-cell level to increase population-level information transfer, allowing extracellular ligands, whose levels are also subject to noise, to incrementally regulate phenotypic changes. This is particularly critical for discrete changes in fate (e.g., life vs. death) for which the key variable is the fraction of cells engaged. Our findings provide a framework for rationalizing the high levels of noise in metazoan signaling networks and have implications for the development of drugs that target these networks in the treatment of cancer and other diseases.

Differential network entropy reveals cancer system hallmarks

PubMed Central

West, James; Bianconi, Ginestra; Severini, Simone; Teschendorff, Andrew E.

2012-01-01

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network we here demonstrate that cancer cells are characterised by an increase in network entropy. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local network entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local correlation patterns. In particular, we find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in network entropy. These findings may have potential implications for identifying novel drug targets. PMID:23150773

IRE1: ER stress sensor and cell fate executor.

PubMed

Chen, Yani; Brandizzi, Federica

2013-11-01

Cells operate a signaling network termed the unfolded protein response (UPR) to monitor protein-folding capacity in the endoplasmic reticulum (ER). Inositol-requiring enzyme 1 (IRE1) is an ER transmembrane sensor that activates the UPR to maintain the ER and cellular function. Although mammalian IRE1 promotes cell survival, it can initiate apoptosis via decay of antiapoptotic miRNAs. Convergent and divergent IRE1 characteristics between plants and animals underscore its significance in cellular homeostasis. This review provides an updated scenario of the IRE1 signaling model, discusses emerging IRE1 sensing mechanisms, compares IRE1 features among species, and outlines exciting future directions in UPR research. Copyright © 2013 Elsevier Ltd. All rights reserved.

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

A new Postdoctoral Fellow position is immediately available in the laboratory of Dr. Terry Yamaguchi at the National Cancer Institute. Dr.Yamaguchi's lab investigates how secreted growth factors regulate the gene regulatory networks that control the fate of embryonic and adult stem cells. Current projects focus on understanding how Wnts and Fgfs regulate the formation and differentiation of the neuromesodermal progenitor (NMP), a multipotent embryonic cell that generates the spinal cord neurons and musculoskeletal system of the body. Using a combination of mouse genetics, mouse and human embryonic stem cell in vitro differentiation, and genomic, proteomic and biochemical approaches, Dr. Yamaguchi’s lab is investigating the molecular mechanisms underlying the activity of key transcriptional determinants of NMP development.

A Minimal Regulatory Network of Extrinsic and Intrinsic Factors Recovers Observed Patterns of CD4+ T Cell Differentiation and Plasticity

PubMed Central

Martinez-Sanchez, Mariana Esther; Mendoza, Luis; Villarreal, Carlos; Alvarez-Buylla, Elena R.

2015-01-01

CD4+ T cells orchestrate the adaptive immune response in vertebrates. While both experimental and modeling work has been conducted to understand the molecular genetic mechanisms involved in CD4+ T cell responses and fate attainment, the dynamic role of intrinsic (produced by CD4+ T lymphocytes) versus extrinsic (produced by other cells) components remains unclear, and the mechanistic and dynamic understanding of the plastic responses of these cells remains incomplete. In this work, we studied a regulatory network for the core transcription factors involved in CD4+ T cell-fate attainment. We first show that this core is not sufficient to recover common CD4+ T phenotypes. We thus postulate a minimal Boolean regulatory network model derived from a larger and more comprehensive network that is based on experimental data. The minimal network integrates transcriptional regulation, signaling pathways and the micro-environment. This network model recovers reported configurations of most of the characterized cell types (Th0, Th1, Th2, Th17, Tfh, Th9, iTreg, and Foxp3-independent T regulatory cells). This transcriptional-signaling regulatory network is robust and recovers mutant configurations that have been reported experimentally. Additionally, this model recovers many of the plasticity patterns documented for different T CD4+ cell types, as summarized in a cell-fate map. We tested the effects of various micro-environments and transient perturbations on such transitions among CD4+ T cell types. Interestingly, most cell-fate transitions were induced by transient activations, with the opposite behavior associated with transient inhibitions. Finally, we used a novel methodology was used to establish that T-bet, TGF-β and suppressors of cytokine signaling proteins are keys to recovering observed CD4+ T cell plastic responses. In conclusion, the observed CD4+ T cell-types and transition patterns emerge from the feedback between the intrinsic or intracellular regulatory core and the micro-environment. We discuss the broader use of this approach for other plastic systems and possible therapeutic interventions. PMID:26090929

Communications Network Design, Simulation, and Analysis for an Autonomous Unmanned Vehicle System

DTIC Science & Technology

2011-06-01

of which type to use depends on the type of demands placed on the network. 1. Central Control Network Architecture Cell phones, the IEEE 802.11, and...distances that do not exceed the wireless transmission distances of the BS and SSs. This BS coverage region is sometimes referred to as a cell . To...In this manner, multiple cells can be connected together by connecting the cell BSs. In so doing, a large geographical area can be covered by a

Mechanisms of the epithelial-to-mesenchymal transition in sea urchin embryos

PubMed Central

Katow, Hideki

2015-01-01

Sea urchin mesenchyme is composed of the large micromere-derived spiculogenetic primary mesenchyme cells (PMC), veg2-tier macromere-derived non-spiculogenetic mesenchyme cells, the small micromere-derived germ cells, and the macro- and mesomere-derived neuronal mesenchyme cells. They are formed through the epithelial-to-mesenchymal transition (EMT) and possess multipotency, except PMCs that solely differentiate larval spicules. The process of EMT is associated with modification of epithelial cell surface property that includes loss of affinity to the apical and basal extracellular matrices, inter-epithelial cell adherens junctions and epithelial cell surface-specific proteins. These cell surface structures and molecules are endocytosed during EMT and utilized as initiators of cytoplasmic signaling pathways that often initiate protein phosphorylation to activate the gene regulatory networks. Acquisition of cell motility after EMT in these mesenchyme cells is associated with the expression of proteins such as Lefty, Snail and Seawi. Structural simplicity and genomic database of this model will further promote detailed EMT research. PMID:26716069

DeepPap: Deep Convolutional Networks for Cervical Cell Classification.

PubMed

Zhang, Ling; Le Lu; Nogues, Isabella; Summers, Ronald M; Liu, Shaoxiong; Yao, Jianhua

2017-11-01

Automation-assisted cervical screening via Pap smear or liquid-based cytology (LBC) is a highly effective cell imaging based cancer detection tool, where cells are partitioned into "abnormal" and "normal" categories. However, the success of most traditional classification methods relies on the presence of accurate cell segmentations. Despite sixty years of research in this field, accurate segmentation remains a challenge in the presence of cell clusters and pathologies. Moreover, previous classification methods are only built upon the extraction of hand-crafted features, such as morphology and texture. This paper addresses these limitations by proposing a method to directly classify cervical cells-without prior segmentation-based on deep features, using convolutional neural networks (ConvNets). First, the ConvNet is pretrained on a natural image dataset. It is subsequently fine-tuned on a cervical cell dataset consisting of adaptively resampled image patches coarsely centered on the nuclei. In the testing phase, aggregation is used to average the prediction scores of a similar set of image patches. The proposed method is evaluated on both Pap smear and LBC datasets. Results show that our method outperforms previous algorithms in classification accuracy (98.3%), area under the curve (0.99) values, and especially specificity (98.3%), when applied to the Herlev benchmark Pap smear dataset and evaluated using five-fold cross validation. Similar superior performances are also achieved on the HEMLBC (H&E stained manual LBC) dataset. Our method is promising for the development of automation-assisted reading systems in primary cervical screening.

A smartphone-based platform to test the performance of wireless mobile networks and preliminary findings

NASA Astrophysics Data System (ADS)

Geng, Xinli; Xu, Hao; Qin, Xiaowei

2016-10-01

During the last several years, the amount of wireless network traffic data increased fast and relative technologies evolved rapidly. In order to improve the performance and Quality of Experience (QoE) of wireless network services, the analysis of field network data and existing delivery mechanisms comes to be a promising research topic. In order to achieve this goal, a smartphone based platform named Monitor and Diagnosis of Mobile Applications (MDMA) was developed to collect field data. Based on this tool, the web browsing service of High Speed Downlink Packet Access (HSDPA) network was tested. The top 200 popular websites in China were selected and loaded on smartphone for thousands times automatically. Communication packets between the smartphone and the cell station were captured for various scenarios (e.g. residential area, urban roads, bus station etc.) in the selected city. A cross-layer database was constructed to support the off-line analysis. Based on the results of client-side experiments and analysis, the usability of proposed portable tool was verified. The preliminary findings and results for existing web browsing service were also presented.

Identifying protein complexes based on brainstorming strategy.

PubMed

Shen, Xianjun; Zhou, Jin; Yi, Li; Hu, Xiaohua; He, Tingting; Yang, Jincai

2016-11-01

Protein complexes comprising of interacting proteins in protein-protein interaction network (PPI network) play a central role in driving biological processes within cells. Recently, more and more swarm intelligence based algorithms to detect protein complexes have been emerging, which have become the research hotspot in proteomics field. In this paper, we propose a novel algorithm for identifying protein complexes based on brainstorming strategy (IPC-BSS), which is integrated into the main idea of swarm intelligence optimization and the improved K-means algorithm. Distance between the nodes in PPI network is defined by combining the network topology and gene ontology (GO) information. Inspired by human brainstorming process, IPC-BSS algorithm firstly selects the clustering center nodes, and then they are separately consolidated with the other nodes with short distance to form initial clusters. Finally, we put forward two ways of updating the initial clusters to search optimal results. Experimental results show that our IPC-BSS algorithm outperforms the other classic algorithms on yeast and human PPI networks, and it obtains many predicted protein complexes with biological significance. Copyright © 2016 Elsevier Inc. All rights reserved.

Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images.

PubMed

Spagnolo, Daniel M; Al-Kofahi, Yousef; Zhu, Peihong; Lezon, Timothy R; Gough, Albert; Stern, Andrew M; Lee, Adrian V; Ginty, Fiona; Sarachan, Brion; Taylor, D Lansing; Chennubhotla, S Chakra

2017-11-01

We introduce THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment), an open-source tool developed to assist cancer researchers in interactive hypothesis testing. The focus of this tool is to quantify spatial intratumoral heterogeneity (ITH), and the interactions between different cell phenotypes and noncellular constituents. Specifically, we foresee applications in phenotyping cells within tumor microenvironments, recognizing tumor boundaries, identifying degrees of immune infiltration and epithelial/stromal separation, and identification of heterotypic signaling networks underlying microdomains. The THRIVE platform provides an integrated workflow for analyzing whole-slide immunofluorescence images and tissue microarrays, including algorithms for segmentation, quantification, and heterogeneity analysis. THRIVE promotes flexible deployment, a maintainable code base using open-source libraries, and an extensible framework for customizing algorithms with ease. THRIVE was designed with highly multiplexed immunofluorescence images in mind, and, by providing a platform to efficiently analyze high-dimensional immunofluorescence signals, we hope to advance these data toward mainstream adoption in cancer research. Cancer Res; 77(21); e71-74. ©2017 AACR . ©2017 American Association for Cancer Research.

Networking among young global health researchers through an intensive training approach: a mixed methods exploratory study.

PubMed

Lenters, Lindsey M; Cole, Donald C; Godoy-Ruiz, Paula

2014-01-25

Networks are increasingly regarded as essential in health research aimed at influencing practice and policies. Less research has focused on the role networking can play in researchers' careers and its broader impacts on capacity strengthening in health research. We used the Canadian Coalition for Global Health Research (CCGHR) annual Summer Institute for New Global Health Researchers (SIs) as an opportunity to explore networking among new global health researchers. A mixed-methods exploratory study was conducted among SI alumni and facilitators who had participated in at least one SI between 2004 and 2010. Alumni and facilitators completed an online short questionnaire, and a subset participated in an in-depth interview. Thematic analysis of the qualitative data was triangulated with quantitative results and CCGHR reports on SIs. Synthesis occurred through the development of a process model relevant to networking through the SIs. Through networking at the SIs, participants experienced decreased isolation and strengthened working relationships. Participants accessed new knowledge, opportunities, and resources through networking during the SI. Post-SI, participants reported ongoing contact and collaboration, although most participants desired more opportunities for interaction. They made suggestions for structural supports to networking among new global health researchers. Networking at the SI contributed positively to opportunities for individuals, and contributed to the formation of a network of global health researchers. Intentional inclusion of networking in health research capacity strengthening initiatives, with supportive resources and infrastructure could create dynamic, sustainable networks accessible to global health researchers around the world.

An ultrastructural analysis of platelets, erythrocytes, white blood cells, and fibrin network in systemic lupus erythematosus.

PubMed

Pretorius, Etheresia; du Plooy, Jenny; Soma, Prashilla; Gasparyan, Armen Yuri

2014-07-01

The study suggests that patients with systemic lupus erythematosus (SLE) present with distinct inflammatory ultrastructural changes such as platelets blebbing, generation of platelet-derived microparticles, spontaneous formation of massive fibrin network and fusion of the erythrocytes membranes. Lupoid platelets actively interact with other inflammatory cells, particularly with white blood cells (WBCs), and the massive fibrin network facilitates such an interaction. It is possible that the concerted actions of platelets, erythrocytes and WBC, caught in the inflammatory fibrin network, predispose to pro-thrombotic states in patients with SLE.

Ion and lipid signaling in apical growth-a dynamic machinery responding to extracellular cues.

PubMed

Malhó, Rui; Serrazina, Susana; Saavedra, Laura; Dias, Fernando V; Ul-Rehman, Reiaz

2015-01-01

Apical cell growth seems to have independently evolved throughout the major lineages of life. To a certain extent, so does our body of knowledge on the mechanisms regulating this morphogenetic process. Studies on pollen tubes, root hairs, rhizoids, fungal hyphae, even nerve cells, have highlighted tissue and cell specificities but also common regulatory characteristics (e.g., ions, proteins, phospholipids) that our focused research sometimes failed to grasp. The working hypothesis to test how apical cell growth is established and maintained have thus been shaped by the model organism under study and the type of methods used to study them. The current picture is one of a dynamic and adaptative process, based on a spatial segregation of components that network to achieve growth and respond to environmental (extracellular) cues. Here, we explore some examples of our live imaging research, namely on cyclic nucleotide gated ion channels, lipid kinases and syntaxins involved in exocytosis. We discuss how their spatial distribution, activity and concentration suggest that the players regulating apical cell growth may display more mobility than previously thought. Furthermore, we speculate on the implications of such perspective in our understanding of the mechanisms regulating apical cell growth and their responses to extracellular cues.

SCENERY: a web application for (causal) network reconstruction from cytometry data.

PubMed

Papoutsoglou, Georgios; Athineou, Giorgos; Lagani, Vincenzo; Xanthopoulos, Iordanis; Schmidt, Angelika; Éliás, Szabolcs; Tegnér, Jesper; Tsamardinos, Ioannis

2017-07-03

Flow and mass cytometry technologies can probe proteins as biological markers in thousands of individual cells simultaneously, providing unprecedented opportunities for reconstructing networks of protein interactions through machine learning algorithms. The network reconstruction (NR) problem has been well-studied by the machine learning community. However, the potentials of available methods remain largely unknown to the cytometry community, mainly due to their intrinsic complexity and the lack of comprehensive, powerful and easy-to-use NR software implementations specific for cytometry data. To bridge this gap, we present Single CEll NEtwork Reconstruction sYstem (SCENERY), a web server featuring several standard and advanced cytometry data analysis methods coupled with NR algorithms in a user-friendly, on-line environment. In SCENERY, users may upload their data and set their own study design. The server offers several data analysis options categorized into three classes of methods: data (pre)processing, statistical analysis and NR. The server also provides interactive visualization and download of results as ready-to-publish images or multimedia reports. Its core is modular and based on the widely-used and robust R platform allowing power users to extend its functionalities by submitting their own NR methods. SCENERY is available at scenery.csd.uoc.gr or http://mensxmachina.org/en/software/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Cytobank: providing an analytics platform for community cytometry data analysis and collaboration.

PubMed

Chen, Tiffany J; Kotecha, Nikesh

2014-01-01

Cytometry is used extensively in clinical and laboratory settings to diagnose and track cell subsets in blood and tissue. High-throughput, single-cell approaches leveraging cytometry are developed and applied in the computational and systems biology communities by researchers, who seek to improve the diagnosis of human diseases, map the structures of cell signaling networks, and identify new cell types. Data analysis and management present a bottleneck in the flow of knowledge from bench to clinic. Multi-parameter flow and mass cytometry enable identification of signaling profiles of patient cell samples. Currently, this process is manual, requiring hours of work to summarize multi-dimensional data and translate these data for input into other analysis programs. In addition, the increase in the number and size of collaborative cytometry studies as well as the computational complexity of analytical tools require the ability to assemble sufficient and appropriately configured computing capacity on demand. There is a critical need for platforms that can be used by both clinical and basic researchers who routinely rely on cytometry. Recent advances provide a unique opportunity to facilitate collaboration and analysis and management of cytometry data. Specifically, advances in cloud computing and virtualization are enabling efficient use of large computing resources for analysis and backup. An example is Cytobank, a platform that allows researchers to annotate, analyze, and share results along with the underlying single-cell data.

An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability

PubMed Central

Schütte, Judith; Wang, Huange; Antoniou, Stella; Jarratt, Andrew; Wilson, Nicola K; Riepsaame, Joey; Calero-Nieto, Fernando J; Moignard, Victoria; Basilico, Silvia; Kinston, Sarah J; Hannah, Rebecca L; Chan, Mun Chiang; Nürnberg, Sylvia T; Ouwehand, Willem H; Bonzanni, Nicola; de Bruijn, Marella FTR; Göttgens, Berthold

2016-01-01

Transcription factor (TF) networks determine cell-type identity by establishing and maintaining lineage-specific expression profiles, yet reconstruction of mammalian regulatory network models has been hampered by a lack of comprehensive functional validation of regulatory interactions. Here, we report comprehensive ChIP-Seq, transgenic and reporter gene experimental data that have allowed us to construct an experimentally validated regulatory network model for haematopoietic stem/progenitor cells (HSPCs). Model simulation coupled with subsequent experimental validation using single cell expression profiling revealed potential mechanisms for cell state stabilisation, and also how a leukaemogenic TF fusion protein perturbs key HSPC regulators. The approach presented here should help to improve our understanding of both normal physiological and disease processes. DOI: http://dx.doi.org/10.7554/eLife.11469.001 PMID:26901438

Lineage-specific enhancers activate self-renewal genes in macrophages and embryonic stem cells

PubMed Central

Soucie, Erinn L.; Weng, Ziming; Geirsdóttir, Laufey; Molawi, Kaaweh; Maurizio, Julien; Fenouil, Romain; Mossadegh-Keller, Noushine; Gimenez, Gregory; VanHille, Laurent; Beniazza, Meryam; Favret, Jeremy; Berruyer, Carole; Perrin, Pierre; Hacohen, Nir; Andrau, J.-C.; Ferrier, Pierre; Dubreuil, Patrice; Sidow, Arend; Sieweke, Michael H.

2016-01-01

Differentiated macrophages can self-renew in tissues and expand long-term in culture, but the gene regulatory mechanisms that accomplish self-renewal in the differentiated state have remained unknown. Here we show that in mice, the transcription factors MafB and c-Maf repress a macrophage-specific enhancer repertoire associated with a gene network controlling self-renewal. Single cell analysis revealed that, in vivo, proliferating resident macrophages can access this network by transient down-regulation of Maf transcription factors. The network also controls embryonic stem cell self-renewal but is associated with distinct embryonic stem cell-specific enhancers. This indicates that distinct lineage-specific enhancer platforms regulate a shared network of genes that control self-renewal potential in both stem and mature cells. PMID:26797145

Prestressed F-actin networks cross-linked by hinged filamins replicate mechanical properties of cells

NASA Astrophysics Data System (ADS)

Gardel, M. L.; Nakamura, F.; Hartwig, J. H.; Crocker, J. C.; Stossel, T. P.; Weitz, D. A.

2006-02-01

We show that actin filaments, shortened to physiological lengths by gelsolin and cross-linked with recombinant human filamins (FLNs), exhibit dynamic elastic properties similar to those reported for live cells. To achieve elasticity values of comparable magnitude to those of cells, the in vitro network must be subjected to external prestress, which directly controls network elasticity. A molecular requirement for the strain-related behavior at physiological conditionsis a flexible hinge found in FLNa and some FLNb molecules. Basic physical properties of the in vitro filamin-F-actin network replicate the essential mechanical properties of living cells. This physical behavior could accommodate passive deformation and internal organelle trafficking at low strains yet resist externally or internally generated high shear forces. cytoskeleton | cell mechanics | nonlinear rheology

Exploring Practice-Research Networks for Critical Professional Learning

ERIC Educational Resources Information Center

Appleby, Yvon; Hillier, Yvonne

2012-01-01

This paper discusses the contribution that practice-research networks can make to support critical professional development in the Learning and Skills sector in England. By practice-research networks we mean groups or networks which maintain a connection between research and professional practice. These networks stem from the philosophy of…

LTAR linkages with other research networks: Capitalizing on network interconnections

USDA-ARS?s Scientific Manuscript database

The USDA ARS Research Unit based at the Jornada Experimental Range outside of Las Cruces, NM, is a member of the USDA’s Long Term Agro-ecosystem Research (LTAR) Network, the National Science Foundation’s Long Term Ecological Research (LTER) Network, the National Ecological Observation Network (NEON)...

From neural-based object recognition toward microelectronic eyes

NASA Technical Reports Server (NTRS)

Sheu, Bing J.; Bang, Sa Hyun

1994-01-01

Engineering neural network systems are best known for their abilities to adapt to the changing characteristics of the surrounding environment by adjusting system parameter values during the learning process. Rapid advances in analog current-mode design techniques have made possible the implementation of major neural network functions in custom VLSI chips. An electrically programmable analog synapse cell with large dynamic range can be realized in a compact silicon area. New designs of the synapse cells, neurons, and analog processor are presented. A synapse cell based on Gilbert multiplier structure can perform the linear multiplication for back-propagation networks. A double differential-pair synapse cell can perform the Gaussian function for radial-basis network. The synapse cells can be biased in the strong inversion region for high-speed operation or biased in the subthreshold region for low-power operation. The voltage gain of the sigmoid-function neurons is externally adjustable which greatly facilitates the search of optimal solutions in certain networks. Various building blocks can be intelligently connected to form useful industrial applications. Efficient data communication is a key system-level design issue for large-scale networks. We also present analog neural processors based on perceptron architecture and Hopfield network for communication applications. Biologically inspired neural networks have played an important role towards the creation of powerful intelligent machines. Accuracy, limitations, and prospects of analog current-mode design of the biologically inspired vision processing chips and cellular neural network chips are key design issues.

Global Gene Expression Profiles Identify Metastasis Regulatory Networks | Center for Cancer Research

Cancer.gov

Metastasis is a systemic disease in which cancer cells break away from a tumor and migrate to other parts of the body, usually via the blood or lymphatic systems, to form new tumors. Metastatic tumors are difficult to treat and account for the majority of cancer-related deaths. Susceptibility to metastasis is known to have a genetic component, with some individuals more

A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

Sig2BioPAX: Java tool for converting flat files to BioPAX Level 3 format.

PubMed

Webb, Ryan L; Ma'ayan, Avi

2011-03-21

The World Wide Web plays a critical role in enabling molecular, cell, systems and computational biologists to exchange, search, visualize, integrate, and analyze experimental data. Such efforts can be further enhanced through the development of semantic web concepts. The semantic web idea is to enable machines to understand data through the development of protocol free data exchange formats such as Resource Description Framework (RDF) and the Web Ontology Language (OWL). These standards provide formal descriptors of objects, object properties and their relationships within a specific knowledge domain. However, the overhead of converting datasets typically stored in data tables such as Excel, text or PDF into RDF or OWL formats is not trivial for non-specialists and as such produces a barrier to seamless data exchange between researchers, databases and analysis tools. This problem is particularly of importance in the field of network systems biology where biochemical interactions between genes and their protein products are abstracted to networks. For the purpose of converting biochemical interactions into the BioPAX format, which is the leading standard developed by the computational systems biology community, we developed an open-source command line tool that takes as input tabular data describing different types of molecular biochemical interactions. The tool converts such interactions into the BioPAX level 3 OWL format. We used the tool to convert several existing and new mammalian networks of protein interactions, signalling pathways, and transcriptional regulatory networks into BioPAX. Some of these networks were deposited into PathwayCommons, a repository for consolidating and organizing biochemical networks. The software tool Sig2BioPAX is a resource that enables experimental and computational systems biologists to contribute their identified networks and pathways of molecular interactions for integration and reuse with the rest of the research community.

Distal gap junctions and active dendrites can tune network dynamics.

PubMed

Saraga, Fernanda; Ng, Leo; Skinner, Frances K

2006-03-01

Gap junctions allow direct electrical communication between CNS neurons. From theoretical and modeling studies, it is well known that although gap junctions can act to synchronize network output, they can also give rise to many other dynamic patterns including antiphase and other phase-locked states. The particular network pattern that arises depends on cellular, intrinsic properties that affect firing frequencies as well as the strength and location of the gap junctions. Interneurons or GABAergic neurons in hippocampus are diverse in their cellular characteristics and have been shown to have active dendrites. Furthermore, parvalbumin-positive GABAergic neurons, also known as basket cells, can contact one another via gap junctions on their distal dendrites. Using two-cell network models, we explore how distal electrical connections affect network output. We build multi-compartment models of hippocampal basket cells using NEURON and endow them with varying amounts of active dendrites. Two-cell networks of these model cells as well as reduced versions are explored. The relationship between intrinsic frequency and the level of active dendrites allows us to define three regions based on what sort of network dynamics occur with distal gap junction coupling. Weak coupling theory is used to predict the delineation of these regions as well as examination of phase response curves and distal dendritic polarization levels. We find that a nonmonotonic dependence of network dynamic characteristics (phase lags) on gap junction conductance occurs. This suggests that distal electrical coupling and active dendrite levels can control how sensitive network dynamics are to gap junction modulation. With the extended geometry, gap junctions located at more distal locations must have larger conductances for pure synchrony to occur. Furthermore, based on simulations with heterogeneous networks, it may be that one requires active dendrites if phase-locking is to occur in networks formed with distal gap junctions.

Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis.

PubMed

Frey, Olivier; Misun, Patrick M; Fluri, David A; Hengstler, Jan G; Hierlemann, Andreas

2014-06-30

Integration of multiple three-dimensional microtissues into microfluidic networks enables new insights in how different organs or tissues of an organism interact. Here, we present a platform that extends the hanging-drop technology, used for multi-cellular spheroid formation, to multifunctional complex microfluidic networks. Engineered as completely open, 'hanging' microfluidic system at the bottom of a substrate, the platform features high flexibility in microtissue arrangements and interconnections, while fabrication is simple and operation robust. Multiple spheroids of different cell types are formed in parallel on the same platform; the different tissues are then connected in physiological order for multi-tissue experiments through reconfiguration of the fluidic network. Liquid flow is precisely controlled through the hanging drops, which enable nutrient supply, substance dosage and inter-organ metabolic communication. The possibility to perform parallelized microtissue formation on the same chip that is subsequently used for complex multi-tissue experiments renders the developed platform a promising technology for 'body-on-a-chip'-related research.

Graph theory findings in the pathophysiology of temporal lobe epilepsy

PubMed Central

Chiang, Sharon; Haneef, Zulfi

2014-01-01

Temporal lobe epilepsy (TLE) is the most common form of adult epilepsy. Accumulating evidence has shown that TLE is a disorder of abnormal epileptogenic networks, rather than focal sources. Graph theory allows for a network-based representation of TLE brain networks, and has potential to illuminate characteristics of brain topology conducive to TLE pathophysiology, including seizure initiation and spread. We review basic concepts which we believe will prove helpful in interpreting results rapidly emerging from graph theory research in TLE. In addition, we summarize the current state of graph theory findings in TLE as they pertain its pathophysiology. Several common findings have emerged from the many modalities which have been used to study TLE using graph theory, including structural MRI, diffusion tensor imaging, surface EEG, intracranial EEG, magnetoencephalography, functional MRI, cell cultures, simulated models, and mouse models, involving increased regularity of the interictal network configuration, altered local segregation and global integration of the TLE network, and network reorganization of temporal lobe and limbic structures. As different modalities provide different views of the same phenomenon, future studies integrating data from multiple modalities are needed to clarify findings and contribute to the formation of a coherent theory on the pathophysiology of TLE. PMID:24831083

Impact of branching on the elasticity of actin networks

PubMed Central

Pujol, Thomas; du Roure, Olivia; Fermigier, Marc; Heuvingh, Julien

2012-01-01

Actin filaments play a fundamental role in cell mechanics: assembled into networks by a large number of partners, they ensure cell integrity, deformability, and migration. Here we focus on the mechanics of the dense branched network found at the leading edge of a crawling cell. We develop a new technique based on the dipolar attraction between magnetic colloids to measure mechanical properties of branched actin gels assembled around the colloids. This technique allows us to probe a large number of gels and, through the study of different networks, to access fundamental relationships between their microscopic structure and their mechanical properties. We show that the architecture does regulate the elasticity of the network: increasing both capping and branching concentrations strongly stiffens the networks. These effects occur at protein concentrations that can be regulated by the cell. In addition, the dependence of the elastic modulus on the filaments’ flexibility and on increasing internal stress has been studied. Our overall results point toward an elastic regime dominated by enthalpic rather than entropic deformations. This result strongly differs from the elasticity of diluted cross-linked actin networks and can be explained by the dense dendritic structure of lamellipodium-like networks. PMID:22689953

A multiple case study of intersectoral public health networks: experiences and benefits of using research.

PubMed

Kothari, Anita; McPherson, Charmaine; Gore, Dana; Cohen, Benita; MacDonald, Marjorie; Sibbald, Shannon L

2016-02-11

Network partnerships between public health and third sector organisations are being used to address the complexities of population level social determinants of health and health equity. An understanding of how these networks use research and knowledge is crucial to effective network design and outcome evaluation. There is, however, a gap in the literature regarding how public health networks use research and knowledge. The purpose of this paper is to report on the qualitative findings from a larger study that explored (1) the experiences of public health networks with using research and knowledge, and (2) the perceived benefits of using research and knowledge. A multiple case study approach framed this study. Focus group data were collected from participants through a purposive sample of four public health networks. Data were analyzed using Framework Analysis and Nvivo software supported data management. Each network had the opportunity to participate in data interpretation. All networks used published research studies and other types of knowledge to accomplish their work, although in each network research and knowledge played different but complementary roles. Neither research nor other types of knowledge were privileged, and an approach that blended varied knowledge types was typically used. Network experiences with research and knowledge produced individual and collective benefits. A novel finding was that research and knowledge were both important in shaping network function. This study shifts the focus in the current literature from public health departments to the community setting where public health collaborates with a broader spectrum of actors to ameliorate health inequities. Both formal research and informal knowledge were found to be important for collaborative public health networks. Examining the benefits of research and knowledge use within public health networks may help us to better understand the relationships among process (the collaborative use of research and knowledge), structure (networks) and outcomes (benefits).

A programmable synthetic lineage-control network that differentiates human IPSCs into glucose-sensitive insulin-secreting beta-like cells

PubMed Central

Saxena, Pratik; Heng, Boon Chin; Bai, Peng; Folcher, Marc; Zulewski, Henryk; Fussenegger, Martin

2016-01-01

Synthetic biology has advanced the design of standardized transcription control devices that programme cellular behaviour. By coupling synthetic signalling cascade- and transcription factor-based gene switches with reverse and differential sensitivity to the licensed food additive vanillic acid, we designed a synthetic lineage-control network combining vanillic acid-triggered mutually exclusive expression switches for the transcription factors Ngn3 (neurogenin 3; OFF-ON-OFF) and Pdx1 (pancreatic and duodenal homeobox 1; ON-OFF-ON) with the concomitant induction of MafA (V-maf musculoaponeurotic fibrosarcoma oncogene homologue A; OFF-ON). This designer network consisting of different network topologies orchestrating the timely control of transgenic and genomic Ngn3, Pdx1 and MafA variants is able to programme human induced pluripotent stem cells (hIPSCs)-derived pancreatic progenitor cells into glucose-sensitive insulin-secreting beta-like cells, whose glucose-stimulated insulin-release dynamics are comparable to human pancreatic islets. Synthetic lineage-control networks may provide the missing link to genetically programme somatic cells into autologous cell phenotypes for regenerative medicine. PMID:27063289

Cell transmission model of dynamic assignment for urban rail transit networks.

PubMed

Xu, Guangming; Zhao, Shuo; Shi, Feng; Zhang, Feilian

2017-01-01

For urban rail transit network, the space-time flow distribution can play an important role in evaluating and optimizing the space-time resource allocation. For obtaining the space-time flow distribution without the restriction of schedules, a dynamic assignment problem is proposed based on the concept of continuous transmission. To solve the dynamic assignment problem, the cell transmission model is built for urban rail transit networks. The priority principle, queuing process, capacity constraints and congestion effects are considered in the cell transmission mechanism. Then an efficient method is designed to solve the shortest path for an urban rail network, which decreases the computing cost for solving the cell transmission model. The instantaneous dynamic user optimal state can be reached with the method of successive average. Many evaluation indexes of passenger flow can be generated, to provide effective support for the optimization of train schedules and the capacity evaluation for urban rail transit network. Finally, the model and its potential application are demonstrated via two numerical experiments using a small-scale network and the Beijing Metro network.

Brain tumour cells interconnect to a functional and resistant network.

PubMed

Osswald, Matthias; Jung, Erik; Sahm, Felix; Solecki, Gergely; Venkataramani, Varun; Blaes, Jonas; Weil, Sophie; Horstmann, Heinz; Wiestler, Benedikt; Syed, Mustafa; Huang, Lulu; Ratliff, Miriam; Karimian Jazi, Kianush; Kurz, Felix T; Schmenger, Torsten; Lemke, Dieter; Gömmel, Miriam; Pauli, Martin; Liao, Yunxiang; Häring, Peter; Pusch, Stefan; Herl, Verena; Steinhäuser, Christian; Krunic, Damir; Jarahian, Mostafa; Miletic, Hrvoje; Berghoff, Anna S; Griesbeck, Oliver; Kalamakis, Georgios; Garaschuk, Olga; Preusser, Matthias; Weiss, Samuel; Liu, Haikun; Heiland, Sabine; Platten, Michael; Huber, Peter E; Kuner, Thomas; von Deimling, Andreas; Wick, Wolfgang; Winkler, Frank

2015-12-03

Astrocytic brain tumours, including glioblastomas, are incurable neoplasms characterized by diffusely infiltrative growth. Here we show that many tumour cells in astrocytomas extend ultra-long membrane protrusions, and use these distinct tumour microtubes as routes for brain invasion, proliferation, and to interconnect over long distances. The resulting network allows multicellular communication through microtube-associated gap junctions. When damage to the network occurred, tumour microtubes were used for repair. Moreover, the microtube-connected astrocytoma cells, but not those remaining unconnected throughout tumour progression, were protected from cell death inflicted by radiotherapy. The neuronal growth-associated protein 43 was important for microtube formation and function, and drove microtube-dependent tumour cell invasion, proliferation, interconnection, and radioresistance. Oligodendroglial brain tumours were deficient in this mechanism. In summary, astrocytomas can develop functional multicellular network structures. Disconnection of astrocytoma cells by targeting their tumour microtubes emerges as a new principle to reduce the treatment resistance of this disease.

ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network.

PubMed

Gloaguen, Pauline; Bournais, Sylvain; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Tardif, Marianne; Kuntz, Marcel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves; Curien, Gilles

2017-06-01

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis ( Arabidopsis thaliana ) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. © 2017 American Society of Plant Biologists. All Rights Reserved.

Revealing the potential pathogenesis of glioma by utilizing a glioma associated protein-protein interaction network.

PubMed

Pan, Weiran; Li, Gang; Yang, Xiaoxiao; Miao, Jinming

2015-04-01

This study aims to explore the potential mechanism of glioma through bioinformatic approaches. The gene expression profile (GSE4290) of glioma tumor and non-tumor samples was downloaded from Gene Expression Omnibus database. A total of 180 samples were available, including 23 non-tumor and 157 tumor samples. Then the raw data were preprocessed using robust multiarray analysis, and 8,890 differentially expressed genes (DEGs) were identified by using t-test (false discovery rate < 0.0005). Furthermore, 16 known glioma related genes were abstracted from Genetic Association Database. After mapping 8,890 DEGs and 16 known glioma related genes to Human Protein Reference Database, a glioma associated protein-protein interaction network (GAPN) was constructed. In addition, 51 sub-networks in GAPN were screened out through Molecular Complex Detection (score ≥ 1), and sub-network 1 was found to have the closest interaction (score = 3). What' more, for the top 10 sub-networks, Gene Ontology (GO) enrichment analysis (p value < 0.05) was performed, and DEGs involved in sub-network 1 and 2, such as BRMS1L and CCNA1, were predicted to regulate cell growth, cell cycle, and DNA replication via interacting with known glioma related genes. Finally, the overlaps of DEGs and human essential, housekeeping, tissue-specific genes were calculated (p value = 1.0, 1.0, and 0.00014, respectively) and visualized by Venn Diagram package in R. About 61% of human tissue-specific genes were DEGs as well. This research shed new light on the pathogenesis of glioma based on DEGs and GAPN, and our findings might provide potential targets for clinical glioma treatment.

Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks

PubMed Central

Li, Ming; Chen, Pengpeng; Gao, Shouwan

2016-01-01

Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes. PMID:27649170

Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks.

PubMed

Li, Ming; Chen, Pengpeng; Gao, Shouwan

2016-09-13

Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes.

System-wide analysis of the transcriptional network of human myelomonocytic leukemia cells predicts attractor structure and phorbol-ester-induced differentiation and dedifferentiation transitions

NASA Astrophysics Data System (ADS)

Sakata, Katsumi; Ohyanagi, Hajime; Sato, Shinji; Nobori, Hiroya; Hayashi, Akiko; Ishii, Hideshi; Daub, Carsten O.; Kawai, Jun; Suzuki, Harukazu; Saito, Toshiyuki

2015-02-01

We present a system-wide transcriptional network structure that controls cell types in the context of expression pattern transitions that correspond to cell type transitions. Co-expression based analyses uncovered a system-wide, ladder-like transcription factor cluster structure composed of nearly 1,600 transcription factors in a human transcriptional network. Computer simulations based on a transcriptional regulatory model deduced from the system-wide, ladder-like transcription factor cluster structure reproduced expression pattern transitions when human THP-1 myelomonocytic leukaemia cells cease proliferation and differentiate under phorbol myristate acetate stimulation. The behaviour of MYC, a reprogramming Yamanaka factor that was suggested to be essential for induced pluripotent stem cells during dedifferentiation, could be interpreted based on the transcriptional regulation predicted by the system-wide, ladder-like transcription factor cluster structure. This study introduces a novel system-wide structure to transcriptional networks that provides new insights into network topology.

[Advances in the research of application of hydrogels in three-dimensional bioprinting].

PubMed

Yang, J; Zhao, Y; Li, H H; Zhu, S H

2016-08-20

Hydrogels are three-dimensional networks made of hydrophilic polymer crosslinked through covalent bonds or physical intermolecular attractions, which can contain growth media and growth factors to support cell growth. In bioprinting, hydrogels are used to provide accurate control over cellular microenvironment and to dramatically reduce experimental repetition times, meanwhile we can obtain three-dimensional cell images of high quality. Hydrogels in three-dimensional bioprinting have received a considerable interest due to their structural similarities to the natural extracellular matrix and polyporous frameworks which can support the cellular proliferation and survival. Meanwhile, they are accompanied by many challenges.

Power plants development in Romania

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

Tanasescu, F.T.; Olariu, N.

1994-12-31

The Romanian PV research program initiated in 1980 has as its aim the development of the Romanian own PV network from solar cells production to demonstration projects and commercial applications. Concerning the PV grid connected systems the Romanian research program is financed by the Romanian Ministry for Research and Technology. Setting out the main objectives and the related stages of this project, in the paper are presented aspects concerning the plant configuration, its component characteristics and preliminary achieved results. The aspects which are going to be developed in the following stages of the grid-connected PV plant implementation in Romania aremore » also underlined.« less

Toward Omics-Based, Systems Biomedicine, and Path and Drug Discovery Methodologies for Depression-Inflammation Research.

PubMed

Maes, Michael; Nowak, Gabriel; Caso, Javier R; Leza, Juan Carlos; Song, Cai; Kubera, Marta; Klein, Hans; Galecki, Piotr; Noto, Cristiano; Glaab, Enrico; Balling, Rudi; Berk, Michael

2016-07-01

Meta-analyses confirm that depression is accompanied by signs of inflammation including increased levels of acute phase proteins, e.g., C-reactive protein, and pro-inflammatory cytokines, e.g., interleukin-6. Supporting the translational significance of this, a meta-analysis showed that anti-inflammatory drugs may have antidepressant effects. Here, we argue that inflammation and depression research needs to get onto a new track. Firstly, the choice of inflammatory biomarkers in depression research was often too selective and did not consider the broader pathways. Secondly, although mild inflammatory responses are present in depression, other immune-related pathways cannot be disregarded as new drug targets, e.g., activation of cell-mediated immunity, oxidative and nitrosative stress (O&NS) pathways, autoimmune responses, bacterial translocation, and activation of the toll-like receptor and neuroprogressive pathways. Thirdly, anti-inflammatory treatments are sometimes used without full understanding of their effects on the broader pathways underpinning depression. Since many of the activated immune-inflammatory pathways in depression actually confer protection against an overzealous inflammatory response, targeting these pathways may result in unpredictable and unwanted results. Furthermore, this paper discusses the required improvements in research strategy, i.e., path and drug discovery processes, omics-based techniques, and systems biomedicine methodologies. Firstly, novel methods should be employed to examine the intracellular networks that control and modulate the immune, O&NS and neuroprogressive pathways using omics-based assays, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, immunoproteomics and metagenomics. Secondly, systems biomedicine analyses are essential to unravel the complex interactions between these cellular networks, pathways, and the multifactorial trigger factors and to delineate new drug targets in the cellular networks or pathways. Drug discovery processes should delineate new drugs targeting the intracellular networks and immune-related pathways.

A strain-cue hypothesis for biological network formation

PubMed Central

Cox, Brian N.

2011-01-01

The direction of migration of a cell invading a host population is assumed to be controlled by the magnitude of the strains in the host medium (cells plus extracellular matrix) that arise as the host medium deforms to accommodate the invader. The single assumption that invaders are cued by strains external to themselves is sufficient to generate network structures. The strain induced by a line of invaders is greatest at the extremity of the line and thus the strain field breaks symmetry, stabilizing branch formation. The strain cue also triggers sprouting from existing branches, with no further model assumption. Network characteristics depend primarily on the ratio of the rate of advance of the invaders to the rate of relaxation of the host cells after their initial deformation. Intra-cell mechanisms that govern these two rates control network morphology. The strain field that cues an individual invader is a collective response of the combined cell populations, involving the nearest 100 cells, to order of magnitude, to any invader. The mechanism does not rely on the pre-existence of the entire host medium prior to invasion; the host cells need only maintain a layer several cells thick around each invader. Consistent with recent experiments, networks result only from a strain cue that is based on strain magnitudes. Spatial strain gradients do not break symmetry and therefore cannot stabilize branch formation. The theory recreates most of the geometrical features of the nervous network in the mouse gut when the most influential adjustable parameter takes a value consistent with one inferred from human and mouse amelogenesis. Because of similarity in the guiding local strain fields, strain cues could also be a participating factor in the formation of vascular networks. PMID:20671068

Connecting the Dots: Understanding the Flow of Research Knowledge within a Research Brokering Network

ERIC Educational Resources Information Center

Rodway, Joelle

2015-01-01

Networks are frequently cited as an important knowledge mobilization strategy; however, there is little empirical research that considers how they connect research and practice. Taking a social network perspective, I explore how central office personnel find, understand and share research knowledge within a research brokering network. This mixed…

Sustaining Research Networks: the Twenty-Year Experience of the HMO Research Network

PubMed Central

Steiner, John F.; Paolino, Andrea R.; Thompson, Ella E.; Larson, Eric B.

2014-01-01

Purpose: As multi-institutional research networks assume a central role in clinical research, they must address the challenge of sustainability. Despite its importance, the concept of network sustainability has received little attention in the literature, and the sustainability strategies of durable scientific networks have not been described. Innovation: The Health Maintenance Organization Research Network (HMORN) is a consortium of 18 research departments in integrated health care delivery systems with over 15 million members in the United States and Israel. The HMORN has coordinated federally funded scientific networks and studies since 1994. This case study describes the HMORN approach to sustainability, proposes an operational definition of network sustainability, and identifies 10 essential elements that can enhance sustainability. Credibility: The sustainability framework proposed here is drawn from prior publications on organizational issues by HMORN investigators and from the experience of recent HMORN leaders and senior staff. Conclusion and Discussion: Network sustainability can be defined as (1) the development and enhancement of shared research assets to facilitate a sequence of research studies in a specific content area or multiple areas, and (2) a community of researchers and other stakeholders who reuse and develop those assets. Essential elements needed to develop the shared assets of a network include: network governance; trustworthy data and processes for sharing data; shared knowledge about research tools; administrative efficiency; physical infrastructure; and infrastructure funding. The community of researchers within a network is enhanced by: a clearly defined mission, vision and values; protection of human subjects; a culture of collaboration; and strong relationships with host organizations. While the importance of these elements varies based on the membership and goals of a network, this framework for sustainability can enhance strategic planning within the network and can guide relationships with external stakeholders. PMID:25848605

Importance of Thickness in Human Cardiomyocyte Network for Effective Electrophysiological Stimulation Using On-Chip Extracellular Microelectrodes

NASA Astrophysics Data System (ADS)

Hamada, Tomoyo; Nomura, Fumimasa; Kaneko, Tomoyuki; Yasuda, Kenji

2012-06-01

We have developed a three-dimensionally controlled in vitro human cardiomyocyte network assay for the measurements of drug-induced conductivity changes and the appearance of fatal arrhythmia such as ventricular tachycardia/fibrillation for more precise in vitro predictive cardiotoxicity. To construct an artificial conductance propagation model of a human cardiomyocyte network, first, we examined the cell concentration dependence of the cell network heights and found the existence of a height limit of cell networks, which was double-layer height, whereas the cardiomyocytes were effectively and homogeneously cultivated within the microchamber maintaining their spatial distribution constant and their electrophysiological conductance and propagation were successfully recorded using a microelectrode array set on the bottom of the microchamber. The pacing ability of a cardiomyocyte's electrophysiological response has been evaluated using microelectrode extracellular stimulation, and the stimulation for pacing also successfully regulated the beating frequencies of two-layered cardiomyocyte networks, whereas monolayered cardiomyocyte networks were hardly stimulated by the external electrodes using the two-layered cardiomyocyte stimulation condition. The stability of the lined-up shape of human cardiomyocytes within the rectangularly arranged agarose microchambers was limited for a two-layered cardiomyocyte network because their stronger force generation shrunk those cells after peeling off the substrate. The results indicate the importance of fabrication technology of thickness control of cellular networks for effective extracellular stimulation and the potential concerning thick cardiomyocyte networks for long-term cultivation.

[Networks and genesis of living beings: epistemologic perspectives].

PubMed

Perru, Olivier

2007-01-01

Our paper focuses on Stuart Kauffman's theory from 1993 to 2004. Kauffman is looking for an explanation of the genesis of living beings by genetic networks. From interactions to cell types, Kauffman's viewpoint is concerned with differentiation and self-organization as network's properties. His approach of morphogenetic processes is interesting but it is insufficient. According to Sole, Fernandez and Kauffman [2003], networks would give an explanation of the diversity in patterns and cell types. Some other authors [as Perkins et al., 2004] consider that it is necessary to explore interactions, not with logical methods only, but non-linear systems too. Network's structure is related to biological diversity. It supposes genes' power's mediators within the cells and between them.

Dynamics of Bacterial Gene Regulatory Networks.

PubMed

Shis, David L; Bennett, Matthew R; Igoshin, Oleg A

2018-05-20

The ability of bacterial cells to adjust their gene expression program in response to environmental perturbation is often critical for their survival. Recent experimental advances allowing us to quantitatively record gene expression dynamics in single cells and in populations coupled with mathematical modeling enable mechanistic understanding on how these responses are shaped by the underlying regulatory networks. Here, we review how the combination of local and global factors affect dynamical responses of gene regulatory networks. Our goal is to discuss the general principles that allow extrapolation from a few model bacteria to less understood microbes. We emphasize that, in addition to well-studied effects of network architecture, network dynamics are shaped by global pleiotropic effects and cell physiology.

Cancer Cytokines and the Relevance of 3D Cultures for Studying Those Implicated in Human Cancers.

PubMed

Maddaly, Ravi; Subramaniyan, Aishwarya; Balasubramanian, Harini

2017-09-01

Cancers are complex conditions and involve several factors for oncogenesis and progression. Of the various factors influencing the physiology of cancers, cytokines are known to play significant roles as mediators of functions. Intricate cytokine networks have been identified in cancers and interest in cytokines associated with cancers has been gaining ground. Of late, some of these cytokines are even identified as potential targets for cancer therapy apart from a few others such as IL-6 being identified as markers for disease prognosis. Of the major contributors to cancer research, cancer cell lines occupy the top slot as the most widely used material in vitro. In vitro cell cultures have seen significant evolution by the introduction of 3-dimensional (3D) culture systems. 3D cell cultures are now widely accepted as excellent material for cancer research which surpass the traditional monolayer cultures. Cancer research has benefited from 3D cell cultures for understanding the various hallmarks of cancers. However, the potential of these culture systems are still unexploited for cancer cytokine research compared to the other aspects of cancers such as gene expression changes, drug-induced toxicity, morphology, angiogenesis, and invasion. Considering the importance of cancer cytokines, 3D cell cultures can be better utilized in understanding their roles and functions. Some of the possibilities where 3D cell cultures can contribute to cancer cytokine research arise from the distinct morphology of the tumor spheroids, the extracellular matrix (ECM), and the spontaneous occurrence of nutrient and oxygen gradients. Also, the 3D culture models enable one to co-culture different types of cells as a simulation of in vivo conditions, enhancing their utility to study cancer cytokines. We review here the cancer associated cytokines and the contributions of 3D cancer cell cultures for studying cancer cytokines. J. Cell. Biochem. 118: 2544-2558, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Optimal occlusion uniformly partitions red blood cells fluxes within a microvascular network

PubMed Central

Tu, Shenyinying; Liu, Yu-Hsiu; Savage, Van M.; Hsiai, Tzung K.; Roper, Marcus

2017-01-01

In animals, gas exchange between blood and tissues occurs in narrow vessels, whose diameter is comparable to that of a red blood cell. Red blood cells must deform to squeeze through these narrow vessels, transiently blocking or occluding the vessels they pass through. Although the dynamics of vessel occlusion have been studied extensively, it remains an open question why microvessels need to be so narrow. We study occlusive dynamics within a model microvascular network: the embryonic zebrafish trunk. We show that pressure feedbacks created when red blood cells enter the finest vessels of the trunk act together to uniformly partition red blood cells through the microvasculature. Using mathematical models as well as direct observation, we show that these occlusive feedbacks are tuned throughout the trunk network to prevent the vessels closest to the heart from short-circuiting the network. Thus occlusion is linked with another open question of microvascular function: how are red blood cells delivered at the same rate to each micro-vessel? Our analysis shows that tuning of occlusive feedbacks increase the total dissipation within the network by a factor of 11, showing that uniformity of flows rather than minimization of transport costs may be prioritized by the microvascular network. PMID:29244812

SERS investigations and electrical recording of neuronal networks with three-dimensional plasmonic nanoantennas (Conference Presentation)

NASA Astrophysics Data System (ADS)

De Angelis, Francesco

2017-06-01

SERS investigations and electrical recording of neuronal networks with three-dimensional plasmonic nanoantennas Michele Dipalo, Valeria Caprettini, Anbrea Barbaglia, Laura Lovato, Francesco De Angelis e-mail: francesco.deangelis@iit.it Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genova Biological systems are analysed mainly by optical, chemical or electrical methods. Normally each of these techniques provides only partial information about the environment, while combined investigations could reveal new phenomena occurring in complex systems such as in-vitro neuronal networks. Aiming at the merging of optical and electrical investigations of biological samples, we introduced three-dimensional plasmonic nanoantennas on CMOS-based electrical sensors [1]. The overall device is then capable of enhanced Raman Analysis of cultured cells combined with electrical recording of neuronal activity. The Raman measurements show a much higher sensitivity when performed on the tip of the nanoantenna in respect to the flat substrate [2]; this effect is a combination of the high plasmonic field enhancement and of the tight adhesion of cells on the nanoantenna tip. Furthermore, when plasmonic opto-poration is exploited [3] the 3D nanoelectrodes are able to penetrate through the cell membrane thus accessing the intracellular environment. Our latest results (unpublished) show that the technique is completely non-invasive and solves many problems related to state-of-the-art intracellular recording approaches on large neuronal networks. This research received funding from ERC-IDEAS Program: "Neuro-Plasmonics" [Grant n. 616213]. References: [1] M. Dipalo, G. C. Messina, H. Amin, R. La Rocca, V. Shalabaeva, A. Simi, A. Maccione, P. Zilio, L. Berdondini, F. De Angelis, Nanoscale 2015, 7, 3703. [2] R. La Rocca, G. C. Messina, M. Dipalo, V. Shalabaeva, F. De Angelis, Small 2015, 11, 4632. [3] G. C. Messina et al., Spatially, Temporally, and Quantitatively Controlled Delivery of Broad Range of Molecules into Selected Cells through Plasmonic Nanotubes. Advanced Materials 2015.

Isotropic actomyosin dynamics promote organization of the apical cell cortex in epithelial cells.

PubMed

Klingner, Christoph; Cherian, Anoop V; Fels, Johannes; Diesinger, Philipp M; Aufschnaiter, Roland; Maghelli, Nicola; Keil, Thomas; Beck, Gisela; Tolić-Nørrelykke, Iva M; Bathe, Mark; Wedlich-Soldner, Roland

2014-10-13

Although cortical actin plays an important role in cellular mechanics and morphogenesis, there is surprisingly little information on cortex organization at the apical surface of cells. In this paper, we characterize organization and dynamics of microvilli (MV) and a previously unappreciated actomyosin network at the apical surface of Madin-Darby canine kidney cells. In contrast to short and static MV in confluent cells, the apical surfaces of nonconfluent epithelial cells (ECs) form highly dynamic protrusions, which are often oriented along the plane of the membrane. These dynamic MV exhibit complex and spatially correlated reorganization, which is dependent on myosin II activity. Surprisingly, myosin II is organized into an extensive network of filaments spanning the entire apical membrane in nonconfluent ECs. Dynamic MV, myosin filaments, and their associated actin filaments form an interconnected, prestressed network. Interestingly, this network regulates lateral mobility of apical membrane probes such as integrins or epidermal growth factor receptors, suggesting that coordinated actomyosin dynamics contributes to apical cell membrane organization. © 2014 Klingner et al.

Earthquake Complex Network Analysis Before and After the Mw 8.2 Earthquake in Iquique, Chile

NASA Astrophysics Data System (ADS)

Pasten, D.

2017-12-01

The earthquake complex networks have shown that they are abble to find specific features in seismic data set. In space, this networkshave shown a scale-free behavior for the probability distribution of connectivity, in directed networks and theyhave shown a small-world behavior, for the undirected networks.In this work, we present an earthquake complex network analysis for the large earthquake Mw 8.2 in the north ofChile (near to Iquique) in April, 2014. An earthquake complex network is made dividing the three dimensional space intocubic cells, if one of this cells contain an hypocenter, we name this cell like a node. The connections between nodes aregenerated in time. We follow the time sequence of seismic events and we are making the connections betweennodes. Now, we have two different networks: a directed and an undirected network. Thedirected network takes in consideration the time-direction of the connections, that is very important for the connectivityof the network: we are considering the connectivity, ki of the i-th node, like the number of connections going out ofthe node i plus the self-connections (if two seismic events occurred successive in time in the same cubic cell, we havea self-connection). The undirected network is made removing the direction of the connections and the self-connectionsfrom the directed network. For undirected networks, we are considering only if two nodes are or not connected.We have built a directed complex network and an undirected complex network, before and after the large earthquake in Iquique. We have used magnitudes greater than Mw = 1.0 and Mw = 3.0. We found that this method can recognize the influence of thissmall seismic events in the behavior of the network and we found that the size of the cell used to build the network isanother important factor to recognize the influence of the large earthquake in this complex system. This method alsoshows a difference in the values of the critical exponent γ (for the probability distribution of connectivity in the directednetwork) before and after the large earthquake, but this method does not show a change in the clustering behavior ofthe undirected network, before and after the large earthquake, showing a small-world behavior for the network beforeand after of this large seismic event.

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments.

PubMed

Van Valen, David A; Kudo, Takamasa; Lane, Keara M; Macklin, Derek N; Quach, Nicolas T; DeFelice, Mialy M; Maayan, Inbal; Tanouchi, Yu; Ashley, Euan A; Covert, Markus W

2016-11-01

Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a microscope image correspond to which individual cells. Current approaches require many hours of manual curation and depend on approaches that are difficult to share between labs. They are also unable to robustly segment the cytoplasms of mammalian cells. Here, we show that deep convolutional neural networks, a supervised machine learning method, can solve this challenge for multiple cell types across the domains of life. We demonstrate that this approach can robustly segment fluorescent images of cell nuclei as well as phase images of the cytoplasms of individual bacterial and mammalian cells from phase contrast images without the need for a fluorescent cytoplasmic marker. These networks also enable the simultaneous segmentation and identification of different mammalian cell types grown in co-culture. A quantitative comparison with prior methods demonstrates that convolutional neural networks have improved accuracy and lead to a significant reduction in curation time. We relay our experience in designing and optimizing deep convolutional neural networks for this task and outline several design rules that we found led to robust performance. We conclude that deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems.

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments

DOE PAGES

Van Valen, David A.; Kudo, Takamasa; Lane, Keara M.; ...

2016-11-04

Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a microscope image correspond to which individual cells. Current approaches require many hours of manual curation and depend on approaches that are difficult to share between labs. They are also unable to robustly segment the cytoplasms of mammalian cells. Here, we show that deep convolutional neural networks, a supervised machine learning method, can solve this challenge for multiple cell types across the domainsmore » of life. We demonstrate that this approach can robustly segment fluorescent images of cell nuclei as well as phase images of the cytoplasms of individual bacterial and mammalian cells from phase contrast images without the need for a fluorescent cytoplasmic marker. These networks also enable the simultaneous segmentation and identification of different mammalian cell types grown in co-culture. A quantitative comparison with prior methods demonstrates that convolutional neural networks have improved accuracy and lead to a significant reduction in curation time. We relay our experience in designing and optimizing deep convolutional neural networks for this task and outline several design rules that we found led to robust performance. We conclude that deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems.« less

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments

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

Van Valen, David A.; Kudo, Takamasa; Lane, Keara M.

Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a microscope image correspond to which individual cells. Current approaches require many hours of manual curation and depend on approaches that are difficult to share between labs. They are also unable to robustly segment the cytoplasms of mammalian cells. Here, we show that deep convolutional neural networks, a supervised machine learning method, can solve this challenge for multiple cell types across the domainsmore » of life. We demonstrate that this approach can robustly segment fluorescent images of cell nuclei as well as phase images of the cytoplasms of individual bacterial and mammalian cells from phase contrast images without the need for a fluorescent cytoplasmic marker. These networks also enable the simultaneous segmentation and identification of different mammalian cell types grown in co-culture. A quantitative comparison with prior methods demonstrates that convolutional neural networks have improved accuracy and lead to a significant reduction in curation time. We relay our experience in designing and optimizing deep convolutional neural networks for this task and outline several design rules that we found led to robust performance. We conclude that deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems.« less

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments

PubMed Central

Van Valen, David A.; Lane, Keara M.; Quach, Nicolas T.; Maayan, Inbal

2016-01-01

Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a microscope image correspond to which individual cells. Current approaches require many hours of manual curation and depend on approaches that are difficult to share between labs. They are also unable to robustly segment the cytoplasms of mammalian cells. Here, we show that deep convolutional neural networks, a supervised machine learning method, can solve this challenge for multiple cell types across the domains of life. We demonstrate that this approach can robustly segment fluorescent images of cell nuclei as well as phase images of the cytoplasms of individual bacterial and mammalian cells from phase contrast images without the need for a fluorescent cytoplasmic marker. These networks also enable the simultaneous segmentation and identification of different mammalian cell types grown in co-culture. A quantitative comparison with prior methods demonstrates that convolutional neural networks have improved accuracy and lead to a significant reduction in curation time. We relay our experience in designing and optimizing deep convolutional neural networks for this task and outline several design rules that we found led to robust performance. We conclude that deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems. PMID:27814364

Differentiation and Application of Induced Pluripotent Stem Cell-Derived Vascular Smooth Muscle Cells.

PubMed

Maguire, Eithne Margaret; Xiao, Qingzhong; Xu, Qingbo

2017-11-01

Vascular smooth muscle cells (VSMCs) play a role in the development of vascular disease, for example, neointimal formation, arterial aneurysm, and Marfan syndrome caused by genetic mutations in VSMCs, but little is known about the mechanisms of the disease process. Advances in induced pluripotent stem cell technology have now made it possible to derive VSMCs from several different somatic cells using a selection of protocols. As such, researchers have set out to delineate key signaling processes involved in triggering VSMC gene expression to grasp the extent of gene regulatory networks involved in phenotype commitment. This technology has also paved the way for investigations into diseases affecting VSMC behavior and function, which may be treatable once an identifiable culprit molecule or gene has been repaired. Moreover, induced pluripotent stem cell-derived VSMCs are also being considered for their use in tissue-engineered blood vessels as they may prove more beneficial than using autologous vessels. Finally, while several issues remains to be clarified before induced pluripotent stem cell-derived VSMCs can become used in regenerative medicine, they do offer both clinicians and researchers hope for both treating and understanding vascular disease. In this review, we aim to update the recent progress on VSMC generation from stem cells and the underlying molecular mechanisms of VSMC differentiation. We will also explore how the use of induced pluripotent stem cell-derived VSMCs has changed the game for regenerative medicine by offering new therapeutic avenues to clinicians, as well as providing researchers with a new platform for modeling of vascular disease. © 2017 American Heart Association, Inc.

Signed weighted gene co-expression network analysis of transcriptional regulation in murine embryonic stem cells

PubMed Central

Mason, Mike J; Fan, Guoping; Plath, Kathrin; Zhou, Qing; Horvath, Steve

2009-01-01

Background Recent work has revealed that a core group of transcription factors (TFs) regulates the key characteristics of embryonic stem (ES) cells: pluripotency and self-renewal. Current efforts focus on identifying genes that play important roles in maintaining pluripotency and self-renewal in ES cells and aim to understand the interactions among these genes. To that end, we investigated the use of unsigned and signed network analysis to identify pluripotency and differentiation related genes. Results We show that signed networks provide a better systems level understanding of the regulatory mechanisms of ES cells than unsigned networks, using two independent murine ES cell expression data sets. Specifically, using signed weighted gene co-expression network analysis (WGCNA), we found a pluripotency module and a differentiation module, which are not identified in unsigned networks. We confirmed the importance of these modules by incorporating genome-wide TF binding data for key ES cell regulators. Interestingly, we find that the pluripotency module is enriched with genes related to DNA damage repair and mitochondrial function in addition to transcriptional regulation. Using a connectivity measure of module membership, we not only identify known regulators of ES cells but also show that Mrpl15, Msh6, Nrf1, Nup133, Ppif, Rbpj, Sh3gl2, and Zfp39, among other genes, have important roles in maintaining ES cell pluripotency and self-renewal. We also report highly significant relationships between module membership and epigenetic modifications (histone modifications and promoter CpG methylation status), which are known to play a role in controlling gene expression during ES cell self-renewal and differentiation. Conclusion Our systems biologic re-analysis of gene expression, transcription factor binding, epigenetic and gene ontology data provides a novel integrative view of ES cell biology. PMID:19619308

SPIKE – a database, visualization and analysis tool of cellular signaling pathways

PubMed Central

Elkon, Ran; Vesterman, Rita; Amit, Nira; Ulitsky, Igor; Zohar, Idan; Weisz, Mali; Mass, Gilad; Orlev, Nir; Sternberg, Giora; Blekhman, Ran; Assa, Jackie; Shiloh, Yosef; Shamir, Ron

2008-01-01

Background Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level. Results To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1) A database (DB) of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2) A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3) An algorithmic inference engine that analyzes the networks for novel functional interplays between network components. SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise. Conclusion The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data. PMID:18289391

Trainable Gene Regulation Networks with Applications to Drosophila Pattern Formation

NASA Technical Reports Server (NTRS)

Mjolsness, Eric

2000-01-01

This chapter will very briefly introduce and review some computational experiments in using trainable gene regulation network models to simulate and understand selected episodes in the development of the fruit fly, Drosophila melanogaster. For details the reader is referred to the papers introduced below. It will then introduce a new gene regulation network model which can describe promoter-level substructure in gene regulation. As described in chapter 2, gene regulation may be thought of as a combination of cis-acting regulation by the extended promoter of a gene (including all regulatory sequences) by way of the transcription complex, and of trans-acting regulation by the transcription factor products of other genes. If we simplify the cis-action by using a phenomenological model which can be tuned to data, such as a unit or other small portion of an artificial neural network, then the full transacting interaction between multiple genes during development can be modelled as a larger network which can again be tuned or trained to data. The larger network will in general need to have recurrent (feedback) connections since at least some real gene regulation networks do. This is the basic modeling approach taken, which describes how a set of recurrent neural networks can be used as a modeling language for multiple developmental processes including gene regulation within a single cell, cell-cell communication, and cell division. Such network models have been called "gene circuits", "gene regulation networks", or "genetic regulatory networks", sometimes without distinguishing the models from the actual modeled systems.

The use of human cells in biomedical research and testing.

PubMed

Combes, Robert D

2004-06-01

The ability to use human cells in biomedical research and testing has the obvious advantage over the use of laboratory animals that the need for species extrapolation is obviated, due to the presence of more-relevant morphological, physiological and biochemical properties, including receptors. Moreover, human cells exhibit the same advantages as animal cells in culture in that different cell types can be used, from different tissues, with a wide range of techniques, to investigate a wide variety of biological phenomena in tissue culture. Human cells can also be grown as organotypic cultures to facilitate the extrapolation from cells to whole organisms. Human cell lines have been available for many years on an ad hoc basis from individual researchers, and also from recognised sources, such as the European Collection of Animal Cell Cultures (ECACC) and, in the USA, the Human Cell Culture Centre (HCCC). Such cells have usually been derived from tumours and this has restricted the variety of types of cells available. This problem has been addressed by using primary human cells that can be obtained from a variety of sources, such as cadavers, diseased tissue, skin strips, peripheral blood, buccal cavity smears, hair follicles and surgical waste from biopsy material that is unsuitable for transplantation purposes. However, primary human cells need to be obtained, processed, distributed and handled in a safe and ethical manner. They also have to be made available at the correct time to researchers very shortly after they become available. It is only comparatively recently that the safe and controlled acquisition of surgical waste and non-transplantable human tissues has become feasible with the establishment of several human tissue banks. Recently, the formation of a UK and European centralised network for human tissue supply has been initiated. The problems of short longevity and loss of specialisation in culture are being approached by: a) cell immortalisation to generate a cell type possessing the properties of both primary cells and cell lines; b) the inhibition of intracellular activities resulting in oxidative stress; and c) the use of stem cells, both of embryonic and adult origin.

Stories in Networks and Networks in Stories: A Tri-Modal Model for Mixed-Methods Social Network Research on Teachers

ERIC Educational Resources Information Center

Baker-Doyle, Kira J.

2015-01-01

Social network research on teachers and schools has risen exponentially in recent years as an innovative method to reveal the role of social networks in education. However, scholars are still exploring ways to incorporate traditional quantitative methods of Social Network Analysis (SNA) with qualitative approaches to social network research. This…

Self-organization of network dynamics into local quantized states.

PubMed

Nicolaides, Christos; Juanes, Ruben; Cueto-Felgueroso, Luis

2016-02-17

Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model-a minimal-ingredients model of nodal activation and interaction within a complex network-is able to produce a complex suite of localized patterns. Hence, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.

Edge usage, motifs, and regulatory logic for cell cycling genetic networks

NASA Astrophysics Data System (ADS)

Zagorski, M.; Krzywicki, A.; Martin, O. C.

2013-01-01

The cell cycle is a tightly controlled process, yet it shows marked differences across species. Which of its structural features follow solely from the ability to control gene expression? We tackle this question in silico by examining the ensemble of all regulatory networks which satisfy the constraint of producing a given sequence of gene expressions. We focus on three cell cycle profiles coming from baker's yeast, fission yeast, and mammals. First, we show that the networks in each of the ensembles use just a few interactions that are repeatedly reused as building blocks. Second, we find an enrichment in network motifs that is similar in the two yeast cell cycle systems investigated. These motifs do not have autonomous functions, yet they reveal a regulatory logic for cell cycling based on a feed-forward cascade of activating interactions.

Lineage-specific enhancers activate self-renewal genes in macrophages and embryonic stem cells.

PubMed

Soucie, Erinn L; Weng, Ziming; Geirsdóttir, Laufey; Molawi, Kaaweh; Maurizio, Julien; Fenouil, Romain; Mossadegh-Keller, Noushine; Gimenez, Gregory; VanHille, Laurent; Beniazza, Meryam; Favret, Jeremy; Berruyer, Carole; Perrin, Pierre; Hacohen, Nir; Andrau, J-C; Ferrier, Pierre; Dubreuil, Patrice; Sidow, Arend; Sieweke, Michael H

2016-02-12

Differentiated macrophages can self-renew in tissues and expand long term in culture, but the gene regulatory mechanisms that accomplish self-renewal in the differentiated state have remained unknown. Here we show that in mice, the transcription factors MafB and c-Maf repress a macrophage-specific enhancer repertoire associated with a gene network that controls self-renewal. Single-cell analysis revealed that, in vivo, proliferating resident macrophages can access this network by transient down-regulation of Maf transcription factors. The network also controls embryonic stem cell self-renewal but is associated with distinct embryonic stem cell-specific enhancers. This indicates that distinct lineage-specific enhancer platforms regulate a shared network of genes that control self-renewal potential in both stem and mature cells. Copyright © 2016, American Association for the Advancement of Science.

Network motifs that stabilize the hybrid epithelial/mesenchymal phenotype

NASA Astrophysics Data System (ADS)

Jolly, Mohit Kumar; Jia, Dongya; Tripathi, Satyendra; Hanash, Samir; Mani, Sendurai; Ben-Jacob, Eshel; Levine, Herbert

Epithelial to Mesenchymal Transition (EMT) and its reverse - MET - are hallmarks of cancer metastasis. While transitioning between E and M phenotypes, cells can also attain a hybrid epithelial/mesenchymal (E/M) phenotype that enables collective cell migration as a cluster of Circulating Tumor Cells (CTCs). These clusters can form 50-times more tumors than individually migrating CTCs, underlining their importance in metastasis. However, this hybrid E/M phenotype has been hypothesized to be only a transient one that is attained en route EMT. Here, via mathematically modeling, we identify certain `phenotypic stability factors' that couple with the core three-way decision-making circuit (miR-200/ZEB) and can maintain or stabilize the hybrid E/M phenotype. Further, we show experimentally that this phenotype can be maintained stably at a single-cell level, and knockdown of these factors impairs collective cell migration. We also show that these factors enable the association of hybrid E/M with high stemness or tumor-initiating potential. Finally, based on these factors, we deduce specific network motifs that can maintain the E/M phenotype. Our framework can be used to elucidate the effect of other players in regulating cellular plasticity during metastasis. This work was supported by NSF PHY-1427654 (Center for Theoretical Biological Physics) and the CPRIT Scholar in Cancer Research of the State of Texas at Rice University.

Innate and adaptive immunity at Mucosal Surfaces of the Female Reproductive Tract: Stratification and Integration of Immune Protection against the Transmission of Sexually Transmitted Infections

PubMed Central

Hickey, DK; Patel, MV; Fahey, JV; Wira, CR

2011-01-01

This review examines the multiple levels of pre-existing immunity in the upper and lower female reproductive tract. In addition, we highlight the need for further research of innate and adaptive immune protection of mucosal surfaces in the female reproductive tract. Innate mechanisms include the mucus lining, a tight epithelial barrier and the secretion of antimicrobial peptides and cytokines by epithelial and innate immune cells. Stimulation of the innate immune system also serves to bridge the adaptive arm resulting in the generation of pathogen-specific humoral and cell-mediated immunity. Less understood are the multiple components that act in a coordinated way to provide a network of ongoing protection. Innate and adaptive immunity in the human female reproductive tract are influenced by the stage of menstrual cycle and are directly regulated by the sex steroid hormones, progesterone and estradiol. Furthermore, the effect of hormones on immunity is mediated both directly on immune and epithelial cells and indirectly by stimulating growth factor secretion from stromal cells. The goal of this review is to focus on the diverse aspects of the innate and adaptive immune systems that contribute to a unique network of protection throughout the female reproductive tract. PMID:21353708

Graph clustering techniques applied to the glycomic response in glioblastoma cells to treatments with STAT3 phosphorylation inhibition and fetal bovine serum

NASA Astrophysics Data System (ADS)

Görke, Robert; Meyer-Bäse, Anke; Plant, Claudia; He, Huan; Emmett, Mark R.; Nilsson, Carol; Colman, Howard; Conrad, Charles A.

2011-06-01

Cancer stem cells (CSC) represent a very small percentage of the total tumor population however they pose a big challenge in treating cancer. Glycans play a key role in cancer therapeutics since overexpression of them depending on the glycan type can lead either to cell death or more invasive metastasis. Two major components, fetal bovine serum (FBS) and STAT3, are known to up- or down-regulate certain glycolipid or phospholipid compositions found in glioblastoma CSCs. The analysis and the understanding of the global interactional behavior of lipidomic networks remains a challenging task and can not be accomplished solely based on intuitive reasoning. The present contribution aims at applying graph clustering networks to analyze the functional aspects of certain activators or inhibitors at the molecular level in glioblastoma stem cells (GSCs). This research enhances our understanding of the differences in phenotype changes and determining the responses of glycans to certain treatments for the aggressive GSCs, and represents together with a quantitative phosphoproteomic study1 the most detailed systems biology study of GSCs differentiation known so far. Thus, these new paradigms are providing unique understanding of the mechanisms involved in GSC maintenance and tumorigenicity and are thus opening a new window to biomedical frontiers.

The functional basis of adaptive evolution in chemostats.

PubMed

Gresham, David; Hong, Jungeui

2015-01-01

Two of the central problems in biology are determining the molecular basis of adaptive evolution and understanding how cells regulate their growth. The chemostat is a device for culturing cells that provides great utility in tackling both of these problems: it enables precise control of the selective pressure under which organisms evolve and it facilitates experimental control of cell growth rate. The aim of this review is to synthesize results from studies of the functional basis of adaptive evolution in long-term chemostat selections using Escherichia coli and Saccharomyces cerevisiae. We describe the principle of the chemostat, provide a summary of studies of experimental evolution in chemostats, and use these studies to assess our current understanding of selection in the chemostat. Functional studies of adaptive evolution in chemostats provide a unique means of interrogating the genetic networks that control cell growth, which complements functional genomic approaches and quantitative trait loci (QTL) mapping in natural populations. An integrated approach to the study of adaptive evolution that accounts for both molecular function and evolutionary processes is critical to advancing our understanding of evolution. By renewing efforts to integrate these two research programs, experimental evolution in chemostats is ideally suited to extending the functional synthesis to the study of genetic networks. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Local immunological mechanisms of sublingual immunotherapy.

PubMed

Allam, Jean-Pierre; Novak, Natalija

2011-12-01

To summarize novel insights into the immunological mechanisms of sublingual immunotherapy (SLIT). Within the recent decades, several alternative noninvasive allergen application strategies have been investigated in allergen-specific immunotherapy (AIT), of which intra-oral allergen application to sublingual mucosa has been proven to be well tolerated and effective. To date, SLIT is widely accepted by most allergists as an alternative option to conventional subcutaneous immunotherapy (SCIT). Although detailed immunological mechanisms remain to be elucidated, much scientific effort has been made to shed some light on local and systemic immunological responses to SLIT in mice as well as humans. Only a few studies focused on the detailed mechanisms following allergen application to the oral mucosa as part of the sophisticated mucosal immunological network. Within this network, the pro-tolerogenic properties of local antigen-presenting cells (APCs) such as dendritic cells - which are able to enforce tolerogenic mechanisms and to induce T-cell immune responses - play a central role. Further on, basic research focused not only on the immune response in nasal and bronchial mucosa but also on the systemic T-cell immune response. Thus, much exiting data have been published providing a better understanding of immunological features of SLIT but far more investigations are necessary to uncover further exciting details on the key mechanisms of SLIT.

Physical limits to biomechanical sensing in disordered fibre networks

NASA Astrophysics Data System (ADS)

Beroz, Farzan; Jawerth, Louise M.; Münster, Stefan; Weitz, David A.; Broedersz, Chase P.; Wingreen, Ned S.

2017-07-01

Cells actively probe and respond to the stiffness of their surroundings. Since mechanosensory cells in connective tissue are surrounded by a disordered network of biopolymers, their in vivo mechanical environment can be extremely heterogeneous. Here we investigate how this heterogeneity impacts mechanosensing by modelling the cell as an idealized local stiffness sensor inside a disordered fibre network. For all types of networks we study, including experimentally-imaged collagen and fibrin architectures, we find that measurements applied at different points yield a strikingly broad range of local stiffnesses, spanning roughly two decades. We verify via simulations and scaling arguments that this broad range of local stiffnesses is a generic property of disordered fibre networks. Finally, we show that to obtain optimal, reliable estimates of global tissue stiffness, a cell must adjust its size, shape, and position to integrate multiple stiffness measurements over extended regions of space.

Steroid Resistant CD8+CD28null NKT-Like Pro-inflammatory Cytotoxic Cells in Chronic Obstructive Pulmonary Disease.

PubMed

Hodge, Greg; Hodge, Sandra

2016-01-01

Corticosteroid resistance is a major barrier to effective treatment in chronic obstructive pulmonary disease (COPD), and failure to suppress systemic inflammation in these patients may result in increased comorbidity. Although much of the research to date has focused on the role of macrophages and neutrophils involved in inflammation in the airways in COPD, recent evidence suggests that CD8 + T cells may be central regulators of the inflammatory network in this disease. CD8 + cytotoxic pro-inflammatory T cells have been shown to be increased in the peripheral blood and airways in patients with COPD, whereas smokers that have not progressed to COPD only show an increase in the lungs. Although the mechanisms underlying steroid resistance in these lymphocytes is largely unknown, new research has identified a role for cytotoxic pro-inflammatory CD8 + T-cells and CD8 + natural killer T-like (NKT-like) cells. Increased numbers of these cells and their significant loss of the co-stimulatory molecule CD28 have been shown in COPD, consistent with findings in the elderly and in clinical conditions involving chronic activation of the immune system. In COPD, these senescent cells expressed increased levels of the cytotoxic mediators, perforin and granzyme b, and the pro-inflammatory cytokines, IFNγ and TNFα. They also demonstrated increased cytotoxicity toward lung epithelial cells and importantly were resistant to immunosuppression by corticosteroids compared with their CD28 + counterparts. Further research has shown these cells evade the immunosuppressive effects of steroids via multiple mechanisms. This mini review will focus on cytotoxic pro-inflammatory CD8 + CD28 null NKT-like cells involved in COPD and novel approaches to reverse steroid resistance in these cells.

Steroid Resistant CD8+CD28null NKT-Like Pro-inflammatory Cytotoxic Cells in Chronic Obstructive Pulmonary Disease

PubMed Central

Hodge, Greg; Hodge, Sandra

2016-01-01

Corticosteroid resistance is a major barrier to effective treatment in chronic obstructive pulmonary disease (COPD), and failure to suppress systemic inflammation in these patients may result in increased comorbidity. Although much of the research to date has focused on the role of macrophages and neutrophils involved in inflammation in the airways in COPD, recent evidence suggests that CD8+ T cells may be central regulators of the inflammatory network in this disease. CD8+ cytotoxic pro-inflammatory T cells have been shown to be increased in the peripheral blood and airways in patients with COPD, whereas smokers that have not progressed to COPD only show an increase in the lungs. Although the mechanisms underlying steroid resistance in these lymphocytes is largely unknown, new research has identified a role for cytotoxic pro-inflammatory CD8+ T-cells and CD8+ natural killer T-like (NKT-like) cells. Increased numbers of these cells and their significant loss of the co-stimulatory molecule CD28 have been shown in COPD, consistent with findings in the elderly and in clinical conditions involving chronic activation of the immune system. In COPD, these senescent cells expressed increased levels of the cytotoxic mediators, perforin and granzyme b, and the pro-inflammatory cytokines, IFNγ and TNFα. They also demonstrated increased cytotoxicity toward lung epithelial cells and importantly were resistant to immunosuppression by corticosteroids compared with their CD28+ counterparts. Further research has shown these cells evade the immunosuppressive effects of steroids via multiple mechanisms. This mini review will focus on cytotoxic pro-inflammatory CD8+CD28null NKT-like cells involved in COPD and novel approaches to reverse steroid resistance in these cells. PMID:28066427

Networking among young global health researchers through an intensive training approach: a mixed methods exploratory study

PubMed Central

2014-01-01

Background Networks are increasingly regarded as essential in health research aimed at influencing practice and policies. Less research has focused on the role networking can play in researchers’ careers and its broader impacts on capacity strengthening in health research. We used the Canadian Coalition for Global Health Research (CCGHR) annual Summer Institute for New Global Health Researchers (SIs) as an opportunity to explore networking among new global health researchers. Methods A mixed-methods exploratory study was conducted among SI alumni and facilitators who had participated in at least one SI between 2004 and 2010. Alumni and facilitators completed an online short questionnaire, and a subset participated in an in-depth interview. Thematic analysis of the qualitative data was triangulated with quantitative results and CCGHR reports on SIs. Synthesis occurred through the development of a process model relevant to networking through the SIs. Results Through networking at the SIs, participants experienced decreased isolation and strengthened working relationships. Participants accessed new knowledge, opportunities, and resources through networking during the SI. Post-SI, participants reported ongoing contact and collaboration, although most participants desired more opportunities for interaction. They made suggestions for structural supports to networking among new global health researchers. Conclusions Networking at the SI contributed positively to opportunities for individuals, and contributed to the formation of a network of global health researchers. Intentional inclusion of networking in health research capacity strengthening initiatives, with supportive resources and infrastructure could create dynamic, sustainable networks accessible to global health researchers around the world. PMID:24460819

Evolution of the research collaboration network in a productive department.

PubMed

Katerndahl, David

2012-02-01

Understanding collaboration networks can facilitate the research growth of new or developing departments. The purpose of this study was to use social network analysis to understand how the research collaboration network evolved within a productive department. Over a 13-year period, a departmental faculty completed an annual survey describing their research collaborations. Data were analyzed using social network analysis. Network measures focused on connectedness, distance, groupings and heterogeneity of distribution, while measures for the research director and external collaboration focused on centrality and roles within the network. Longitudinal patterns of network collaboration were assessed using Simulation Investigation for Empirical Network Analysis software (University of Groningen, Groningen, Netherlands). Based upon the number of active research projects, research development can be divided into three phases. The initial development phase was characterized by increasing centralization and collaboration focused within a single subject area. During the maintenance phase, measures went through cycles, possibly because of changes in faculty composition. While the research director was not a 'key player' within the network during the first several years, external collaboration played a central role during all phases. Longitudinal analysis found that forming ties was more likely when the opportunity for network closure existed and when those around you are principal investigators (PIs). Initial development of research relied heavily upon a centralized network involving external collaboration; a central position of the research director during research development was not important. Changes in collaboration depended upon faculty gender and tenure track as well as transitivity and the 'popularity of PIs'. © 2011 Blackwell Publishing Ltd.

Multiple Independent Oscillatory Networks in the Degenerating Retina

PubMed Central

Euler, Thomas; Schubert, Timm

2015-01-01

During neuronal degenerative diseases, microcircuits undergo severe structural alterations, leading to remodeling of synaptic connectivity. This can be particularly well observed in the retina, where photoreceptor degeneration triggers rewiring of connections in the retina’s first synaptic layer (e.g., Strettoi et al., 2003; Haq et al., 2014), while the synaptic organization of inner retinal circuits appears to be little affected (O’Brien et al., 2014; Figures 1A,B). Remodeling of (outer) retinal circuits and diminishing light-driven activity due to the loss of functional photoreceptors lead to spontaneous activity that can be observed at different retinal levels (Figure 1C), including the retinal ganglion cells, which display rhythmic spiking activity in the degenerative retina (Margolis et al., 2008; Stasheff, 2008; Menzler and Zeck, 2011; Stasheff et al., 2011). Two networks have been suggested to drive the oscillatory activity in the degenerating retina: a network of remnant cone photoreceptors, rod bipolar cells (RBCs) and horizontal cells in the outer retina (Haq et al., 2014), and the AII amacrine cell-cone bipolar cell network in the inner retina (Borowska et al., 2011). Notably, spontaneous rhythmic activity in the inner retinal network can be triggered in the absence of synaptic remodeling in the outer retina, for example, in the healthy retina after photo-bleaching (Menzler et al., 2014). In addition, the two networks show remarkable differences in their dominant oscillation frequency range as well as in the types and numbers of involved cells (Menzler and Zeck, 2011; Haq et al., 2014). Taken together this suggests that the two networks are self-sustained and can be active independently from each other. However, it is not known if and how they modulate each other. In this mini review, we will discuss: (i) commonalities and differences between these two oscillatory networks as well as possible interaction pathways; (ii) how multiple self-sustained networks may hamper visual restoration strategies employing, for example, microelectronic implants, optogenetics or stem cells, and briefly; and (iii) how the finding of diverse (independent) networks in the degenerative retina may relate to other parts of the neurodegenerative central nervous system. PMID:26617491

A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks.

PubMed

Laomettachit, Teeraphan; Chen, Katherine C; Baumann, William T; Tyson, John J

2016-01-01

To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a "standard component" modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with "standard components" can capture in quantitative detail many essential properties of cell cycle control in budding yeast.

A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks

PubMed Central

Laomettachit, Teeraphan; Chen, Katherine C.; Baumann, William T.

2016-01-01

To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a “standard component” modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with “standard components” can capture in quantitative detail many essential properties of cell cycle control in budding yeast. PMID:27187804

Cell-cell and cell-extracellular matrix adhesions cooperate to organize actomyosin networks and maintain force transmission during dorsal closure.

PubMed

Goodwin, Katharine; Lostchuck, Emily E; Cramb, Kaitlyn M L; Zulueta-Coarasa, Teresa; Fernandez-Gonzalez, Rodrigo; Tanentzapf, Guy

2017-05-15

Tissue morphogenesis relies on the coordinated action of actin networks, cell-cell adhesions, and cell-extracellular matrix (ECM) adhesions. Such coordination can be achieved through cross-talk between cell-cell and cell-ECM adhesions. Drosophila dorsal closure (DC), a morphogenetic process in which an extraembryonic tissue called the amnioserosa contracts and ingresses to close a discontinuity in the dorsal epidermis of the embryo, requires both cell-cell and cell-ECM adhesions. However, whether the functions of these two types of adhesions are coordinated during DC is not known. Here we analyzed possible interdependence between cell-cell and cell-ECM adhesions during DC and its effect on the actomyosin network. We find that loss of cell-ECM adhesion results in aberrant distributions of cadherin-mediated adhesions and actin networks in the amnioserosa and subsequent disruption of myosin recruitment and dynamics. Moreover, loss of cell-cell adhesion caused up-regulation of cell-ECM adhesion, leading to reduced cell deformation and force transmission across amnioserosa cells. Our results show how interdependence between cell-cell and cell-ECM adhesions is important in regulating cell behaviors, force generation, and force transmission critical for tissue morphogenesis. © 2017 Goodwin, Lostchuck, et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Construction of stable capillary networks using a microfluidic device.

PubMed

Sudo, Ryo

2015-01-01

Construction of stable capillary networks is required to provide sufficient oxygen and nutrients to the deep region of thick tissues, which is important in the context of 3D tissue engineering. Although conventional in vitro culture models have been used to investigate the mechanism of capillary formation, recent advances in microfluidics technologies allowed us to control biophysical and biochemical culture environments more precisely, which led to the construction of functional and stable capillary networks. In this study, endothelial cells and mesenchymal stem cells were co-cultured in microfluidic devices to construct stable capillary networks, which resulted in the construction of luminal structures covered by pericytes. Interactions between endothelial cells and mesenchymal stem cells are also discussed in the context of capillary formation.

Formation of Polymer Networks for Fast In-Plane Switching of Liquid Crystals at Low Temperatures

NASA Astrophysics Data System (ADS)

Yu, Byeong-Hun; Song, Dong Han; Kim, Ki-Han; Wok Park, Byung; Choi, Sun-Wook; Park, Sung Il; Kang, Sung Gu; Yoon, Jeong Hwan; Kim, Byeong Koo; Yoon, Tae-Hoon

2013-09-01

We formed a polymer structure to enable fast in-plane switching of liquid crystals at low temperatures. The problem of the inevitable slow response at low temperatures was reduced by the formation of in-cell polymer networks in in-plane switching (IPS) cells. The electro-optic characteristics of polymer-networked IPS cells were measured at temperatures ranging from -10 to 20 °C. The turn-on and turn-off times of an IPS cell were reduced by 44.5 and 47.2% at -10 °C by the formation of polymer networks. We believe that the proposed technology can be applied to emerging display devices such as mobile phones and automotive displays that may be used at low temperatures.

Multi-level characterization of balanced inhibitory-excitatory cortical neuron network derived from human pluripotent stem cells.

PubMed

Nadadhur, Aishwarya G; Emperador Melero, Javier; Meijer, Marieke; Schut, Desiree; Jacobs, Gerbren; Li, Ka Wan; Hjorth, J J Johannes; Meredith, Rhiannon M; Toonen, Ruud F; Van Kesteren, Ronald E; Smit, August B; Verhage, Matthijs; Heine, Vivi M

2017-01-01

Generation of neuronal cultures from induced pluripotent stem cells (hiPSCs) serve the studies of human brain disorders. However we lack neuronal networks with balanced excitatory-inhibitory activities, which are suitable for single cell analysis. We generated low-density networks of hPSC-derived GABAergic and glutamatergic cortical neurons. We used two different co-culture models with astrocytes. We show that these cultures have balanced excitatory-inhibitory synaptic identities using confocal microscopy, electrophysiological recordings, calcium imaging and mRNA analysis. These simple and robust protocols offer the opportunity for single-cell to multi-level analysis of patient hiPSC-derived cortical excitatory-inhibitory networks; thereby creating advanced tools to study disease mechanisms underlying neurodevelopmental disorders.

Transparent Electrodes Based on Silver Nanowire Networks: From Physical Considerations towards Device Integration

PubMed Central

Bellet, Daniel; Lagrange, Mélanie; Sannicolo, Thomas; Aghazadehchors, Sara; Nguyen, Viet Huong; Langley, Daniel P.; Muñoz-Rojas, David; Jiménez, Carmen; Bréchet, Yves; Nguyen, Ngoc Duy

2017-01-01

The past few years have seen a considerable amount of research devoted to nanostructured transparent conducting materials (TCM), which play a pivotal role in many modern devices such as solar cells, flexible light-emitting devices, touch screens, electromagnetic devices, and flexible transparent thin film heaters. Currently, the most commonly used TCM for such applications (ITO: Indium Tin oxide) suffers from two major drawbacks: brittleness and indium scarcity. Among emerging transparent electrodes, silver nanowire (AgNW) networks appear to be a promising substitute to ITO since such electrically percolating networks exhibit excellent properties with sheet resistance lower than 10 Ω/sq and optical transparency of 90%, fulfilling the requirements of most applications. In addition, AgNW networks also exhibit very good mechanical flexibility. The fabrication of these electrodes involves low-temperature processing steps and scalable methods, thus making them appropriate for future use as low-cost transparent electrodes in flexible electronic devices. This contribution aims to briefly present the main properties of AgNW based transparent electrodes as well as some considerations relating to their efficient integration in devices. The influence of network density, nanowire sizes, and post treatments on the properties of AgNW networks will also be evaluated. In addition to a general overview of AgNW networks, we focus on two important aspects: (i) network instabilities as well as an efficient Atomic Layer Deposition (ALD) coating which clearly enhances AgNW network stability and (ii) modelling to better understand the physical properties of these networks. PMID:28772931

Praxis-based research networks: An emerging paradigm for research that is rigorous, relevant, and inclusive.

PubMed

Werner, James J; Stange, Kurt C

2014-01-01

Practice-based research networks (PBRNs) have developed a grounded approach to conducting practice-relevant and translational research in community practice settings. Seismic shifts in the health care landscape are shaping PBRNs that work across organizational and institutional margins to address complex problems. Praxis-based research networks combine PBRN knowledge generation with multistakeholder learning, experimentation, and application of practical knowledge. The catalytic processes in praxis-based research networks are cycles of action and reflection based on experience, observation, conceptualization, and experimentation by network members and partners. To facilitate co-learning and solution-building, these networks have a flexible architecture that allows pragmatic inclusion of stakeholders based on the demands of the problem and the needs of the network. Praxis-based research networks represent an evolving trend that combines the core values of PBRNs with new opportunities for relevance, rigor, and broad participation. © Copyright 2014 by the American Board of Family Medicine.

Adiabatic superconducting cells for ultra-low-power artificial neural networks.

PubMed

Schegolev, Andrey E; Klenov, Nikolay V; Soloviev, Igor I; Tereshonok, Maxim V

2016-01-01

We propose the concept of using superconducting quantum interferometers for the implementation of neural network algorithms with extremely low power dissipation. These adiabatic elements are Josephson cells with sigmoid- and Gaussian-like activation functions. We optimize their parameters for application in three-layer perceptron and radial basis function networks.

Iterative design of peptide-based hydrogels and the effect of network electrostatics on primary chondrocyte behavior

PubMed Central

Sinthuvanich, Chomdao; Haines-Butterick, Lisa A.; Nagy, Katelyn J.; Schneider, Joel P.

2012-01-01

Iterative peptide design was used to generate two peptide-based hydrogels to study the effect of network electrostatics on primary chondrocyte behavior. MAX8 and HLT2 peptides have formal charge states of +7 and +5 per monomer, respectively. These peptides undergo triggered folding and self-assembly to afford hydrogel networks having similar rheological behavior and local network morphologies, yet different electrostatic character. Each gel can be used to directly encapsulate and syringe-deliver cells. The influence of network electrostatics on cell viability after encapsulation and delivery, extracellular matrix deposition, gene expression, and the bulk mechanical properties of the gel-cell constructs as a function of culture time was assessed. The less electropositive HLT2 gel provides a microenvironment more conducive to chondrocyte encapsulation, delivery, and phenotype maintenance. Cell viability was higher for this gel and although a moderate number of cells dedifferentiated to a fibroblast-like phenotype, many retained their chondrocytic behavior. As a result, gel-cell constructs prepared with HLT2, cultured under static in vitro conditions, contained more GAG and type II collagen resulting in mechanically superior constructs. Chondrocytes delivered in the more electropositive MAX8 gel experienced a greater degree of cell death during encapsulation and delivery and the remaining viable cells were less prone to maintain their phenotype. As a result, MAX8 gel-cell constructs had fewer cells, of which a limited number were capable of laying down cartilage-specific ECM. PMID:22841922

Iterative design of peptide-based hydrogels and the effect of network electrostatics on primary chondrocyte behavior.

PubMed

Sinthuvanich, Chomdao; Haines-Butterick, Lisa A; Nagy, Katelyn J; Schneider, Joel P

2012-10-01

Iterative peptide design was used to generate two peptide-based hydrogels to study the effect of network electrostatics on primary chondrocyte behavior. MAX8 and HLT2 peptides have formal charge states of +7 and +5 per monomer, respectively. These peptides undergo triggered folding and self-assembly to afford hydrogel networks having similar rheological behavior and local network morphologies, yet different electrostatic character. Each gel can be used to directly encapsulate and syringe-deliver cells. The influence of network electrostatics on cell viability after encapsulation and delivery, extracellular matrix deposition, gene expression, and the bulk mechanical properties of the gel-cell constructs as a function of culture time was assessed. The less electropositive HLT2 gel provides a microenvironment more conducive to chondrocyte encapsulation, delivery, and phenotype maintenance. Cell viability was higher for this gel and although a moderate number of cells dedifferentiated to a fibroblast-like phenotype, many retained their chondrocytic behavior. As a result, gel-cell constructs prepared with HLT2, cultured under static in vitro conditions, contained more GAG and type II collagen resulting in mechanically superior constructs. Chondrocytes delivered in the more electropositive MAX8 gel experienced a greater degree of cell death during encapsulation and delivery and the remaining viable cells were less prone to maintain their phenotype. As a result, MAX8 gel-cell constructs had fewer cells, of which a limited number were capable of laying down cartilage-specific ECM. Published by Elsevier Ltd.

Towards a comprehensive understanding of emerging dynamics and function of pancreatic islets: A complex network approach. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

Loppini, Alessandro

2018-03-01

Complex network theory represents a comprehensive mathematical framework to investigate biological systems, ranging from sub-cellular and cellular scales up to large-scale networks describing species interactions and ecological systems. In their exhaustive and comprehensive work [1], Gosak et al. discuss several scenarios in which the network approach was able to uncover general properties and underlying mechanisms of cells organization and regulation, tissue functions and cell/tissue failure in pathology, by the study of chemical reaction networks, structural networks and functional connectivities.

Key factors of clinical research network capacity building.

PubMed

Li, Guowei; Wu, Qianyu; Jin, Yanling; Vanniyasingam, Thuva; Thabane, Lehana

2018-01-01

In general, clinical research network capacity building refers to programs aimed at enhancing networks of researchers to conduct clinical research. Although in the literature there is a large body of research on how to develop and build capacity in clinical research networks, the conceptualizations and implementations remain controversial and challenging. Moreover, the experiences learnt from the past accomplishments and failures can assist in the future capacity building efforts to be more practical, effective and efficient. In this paper, we aim to provide an overview of capacity building in clinical research network by (1) identifying the key barriers to clinical research network capacity building, (2) providing insights into how to overcome those obstacles, and (3) sharing our experiences in collaborating with national and international partners to build capacity in clinical research networks. In conclusion, we have provided some insight into how to address the key factors of clinical research network capacity building and shared some empirical experiences. A successful capacity building practice requires a joint endeavor to procure sufficient resources and support from the relevant stakeholders, to ensure its efficiency, cost-effectiveness, and sustainability.

Exploring the retinal connectome

PubMed Central

Anderson, James R.; Jones, Bryan W.; Watt, Carl B.; Shaw, Margaret V.; Yang, Jia-Hui; DeMill, David; Lauritzen, James S.; Lin, Yanhua; Rapp, Kevin D.; Mastronarde, David; Koshevoy, Pavel; Grimm, Bradley; Tasdizen, Tolga; Whitaker, Ross

2011-01-01

Purpose A connectome is a comprehensive description of synaptic connectivity for a neural domain. Our goal was to produce a connectome data set for the inner plexiform layer of the mammalian retina. This paper describes our first retinal connectome, validates the method, and provides key initial findings. Methods We acquired and assembled a 16.5 terabyte connectome data set RC1 for the rabbit retina at ≈2 nm resolution using automated transmission electron microscope imaging, automated mosaicking, and automated volume registration. RC1 represents a column of tissue 0.25 mm in diameter, spanning the inner nuclear, inner plexiform, and ganglion cell layers. To enhance ultrastructural tracing, we included molecular markers for 4-aminobutyrate (GABA), glutamate, glycine, taurine, glutamine, and the in vivo activity marker, 1-amino-4-guanidobutane. This enabled us to distinguish GABAergic and glycinergic amacrine cells; to identify ON bipolar cells coupled to glycinergic cells; and to discriminate different kinds of bipolar, amacrine, and ganglion cells based on their molecular signatures and activity. The data set was explored and annotated with Viking, our multiuser navigation tool. Annotations were exported to additional applications to render cells, visualize network graphs, and query the database. Results Exploration of RC1 showed that the 2 nm resolution readily recapitulated well known connections and revealed several new features of retinal organization: (1) The well known AII amacrine cell pathway displayed more complexity than previously reported, with no less than 17 distinct signaling modes, including ribbon synapse inputs from OFF bipolar cells, wide-field ON cone bipolar cells and rod bipolar cells, and extensive input from cone-pathway amacrine cells. (2) The axons of most cone bipolar cells formed a distinct signal integration compartment, with ON cone bipolar cell axonal synapses targeting diverse cell types. Both ON and OFF bipolar cells receive axonal veto synapses. (3) Chains of conventional synapses were very common, with intercalated glycinergic-GABAergic chains and very long chains associated with starburst amacrine cells. Glycinergic amacrine cells clearly play a major role in ON-OFF crossover inhibition. (4) Molecular and excitation mapping clearly segregates ultrastructurally defined bipolar cell groups into different response clusters. (5) Finally, low-resolution electron or optical imaging cannot reliably map synaptic connections by process geometry, as adjacency without synaptic contact is abundant in the retina. Only direct visualization of synapses and gap junctions suffices. Conclusions Connectome assembly and analysis using conventional transmission electron microscopy is now practical for network discovery. Our surveys of volume RC1 demonstrate that previously studied systems such as the AII amacrine cell network involve more network motifs than previously known. The AII network, primarily considered a scotopic pathway, clearly derives ribbon synapse input from photopic ON and OFF cone bipolar cell networks and extensive photopic GABAergic amacrine cell inputs. Further, bipolar cells show extensive inputs and outputs along their axons, similar to multistratified nonmammalian bipolar cells. Physiologic evidence of significant ON-OFF channel crossover is strongly supported by our anatomic data, showing alternating glycine-to-GABA paths. Long chains of amacrine cell networks likely arise from homocellular GABAergic synapses between starburst amacrine cells. Deeper analysis of RC1 offers the opportunity for more complete descriptions of specific networks. PMID:21311605

Exploring the retinal connectome.

PubMed

Anderson, James R; Jones, Bryan W; Watt, Carl B; Shaw, Margaret V; Yang, Jia-Hui; Demill, David; Lauritzen, James S; Lin, Yanhua; Rapp, Kevin D; Mastronarde, David; Koshevoy, Pavel; Grimm, Bradley; Tasdizen, Tolga; Whitaker, Ross; Marc, Robert E

2011-02-03

A connectome is a comprehensive description of synaptic connectivity for a neural domain. Our goal was to produce a connectome data set for the inner plexiform layer of the mammalian retina. This paper describes our first retinal connectome, validates the method, and provides key initial findings. We acquired and assembled a 16.5 terabyte connectome data set RC1 for the rabbit retina at ≈ 2 nm resolution using automated transmission electron microscope imaging, automated mosaicking, and automated volume registration. RC1 represents a column of tissue 0.25 mm in diameter, spanning the inner nuclear, inner plexiform, and ganglion cell layers. To enhance ultrastructural tracing, we included molecular markers for 4-aminobutyrate (GABA), glutamate, glycine, taurine, glutamine, and the in vivo activity marker, 1-amino-4-guanidobutane. This enabled us to distinguish GABAergic and glycinergic amacrine cells; to identify ON bipolar cells coupled to glycinergic cells; and to discriminate different kinds of bipolar, amacrine, and ganglion cells based on their molecular signatures and activity. The data set was explored and annotated with Viking, our multiuser navigation tool. Annotations were exported to additional applications to render cells, visualize network graphs, and query the database. Exploration of RC1 showed that the 2 nm resolution readily recapitulated well known connections and revealed several new features of retinal organization: (1) The well known AII amacrine cell pathway displayed more complexity than previously reported, with no less than 17 distinct signaling modes, including ribbon synapse inputs from OFF bipolar cells, wide-field ON cone bipolar cells and rod bipolar cells, and extensive input from cone-pathway amacrine cells. (2) The axons of most cone bipolar cells formed a distinct signal integration compartment, with ON cone bipolar cell axonal synapses targeting diverse cell types. Both ON and OFF bipolar cells receive axonal veto synapses. (3) Chains of conventional synapses were very common, with intercalated glycinergic-GABAergic chains and very long chains associated with starburst amacrine cells. Glycinergic amacrine cells clearly play a major role in ON-OFF crossover inhibition. (4) Molecular and excitation mapping clearly segregates ultrastructurally defined bipolar cell groups into different response clusters. (5) Finally, low-resolution electron or optical imaging cannot reliably map synaptic connections by process geometry, as adjacency without synaptic contact is abundant in the retina. Only direct visualization of synapses and gap junctions suffices. Connectome assembly and analysis using conventional transmission electron microscopy is now practical for network discovery. Our surveys of volume RC1 demonstrate that previously studied systems such as the AII amacrine cell network involve more network motifs than previously known. The AII network, primarily considered a scotopic pathway, clearly derives ribbon synapse input from photopic ON and OFF cone bipolar cell networks and extensive photopic GABAergic amacrine cell inputs. Further, bipolar cells show extensive inputs and outputs along their axons, similar to multistratified nonmammalian bipolar cells. Physiologic evidence of significant ON-OFF channel crossover is strongly supported by our anatomic data, showing alternating glycine-to-GABA paths. Long chains of amacrine cell networks likely arise from homocellular GABAergic synapses between starburst amacrine cells. Deeper analysis of RC1 offers the opportunity for more complete descriptions of specific networks.

Sparse Regression Based Structure Learning of Stochastic Reaction Networks from Single Cell Snapshot Time Series.

PubMed

Klimovskaia, Anna; Ganscha, Stefan; Claassen, Manfred

2016-12-01

Stochastic chemical reaction networks constitute a model class to quantitatively describe dynamics and cell-to-cell variability in biological systems. The topology of these networks typically is only partially characterized due to experimental limitations. Current approaches for refining network topology are based on the explicit enumeration of alternative topologies and are therefore restricted to small problem instances with almost complete knowledge. We propose the reactionet lasso, a computational procedure that derives a stepwise sparse regression approach on the basis of the Chemical Master Equation, enabling large-scale structure learning for reaction networks by implicitly accounting for billions of topology variants. We have assessed the structure learning capabilities of the reactionet lasso on synthetic data for the complete TRAIL induced apoptosis signaling cascade comprising 70 reactions. We find that the reactionet lasso is able to efficiently recover the structure of these reaction systems, ab initio, with high sensitivity and specificity. With only < 1% false discoveries, the reactionet lasso is able to recover 45% of all true reactions ab initio among > 6000 possible reactions and over 102000 network topologies. In conjunction with information rich single cell technologies such as single cell RNA sequencing or mass cytometry, the reactionet lasso will enable large-scale structure learning, particularly in areas with partial network structure knowledge, such as cancer biology, and thereby enable the detection of pathological alterations of reaction networks. We provide software to allow for wide applicability of the reactionet lasso.

Low Crossover Polymer Electrolyte Membranes for Direct Methanol Fuel Cells

NASA Technical Reports Server (NTRS)

Prakash, G. K. Surya; Smart, Marshall; Atti, Anthony R.; Olah, George A.; Narayanan, S. R.; Valdez, T.; Surampudi, S.

1996-01-01

Direct Methanol Fuel Cells (DMFC's) using polymer electrolyte membranes are promising power sources for portable and vehicular applications. State of the art technology using Nafion(R) 117 membranes (Dupont) are limited by high methanol permeability and cost, resulting in reduced fuel cell efficiencies and impractical commercialization. Therefore, much research in the fuel cell field is focused on the preparation and testing of low crossover and cost efficient polymer electrolyte membranes. The University of Southern California in cooperation with the Jet Propulsion Laboratory is focused on development of such materials. Interpenetrating polymer networks are an effective method used to blend polymer systems without forming chemical links. They provide the ability to modify physical and chemical properties of polymers by optimizing blend compositions. We have developed a novel interpenetrating polymer network based on poly (vinyl - difluoride)/cross-linked polystyrenesulfonic acid polymer composites (PVDF PSSA). Sulfonation of polystyrene accounts for protonic conductivity while the non-polar, PVDF backbone provides structural integrity in addition to methanol rejection. Precursor materials were prepared and analyzed to characterize membrane crystallinity, stability and degree of interpenetration. USC JPL PVDF-PSSA membranes were also characterized to determine methanol permeability, protonic conductivity and sulfur distribution. Membranes were fabricated into membrane electrode assemblies (MEA) and tested for single cell performance. Tests include cell performance over a wide range of temperatures (20 C - 90 C) and cathode conditions (ambient Air/O2). Methanol crossover values are measured in situ using an in-line CO2 analyzer.

Degradation behavior of, and tissue response to photo-crosslinked poly(trimethylene carbonate) networks.

PubMed

Rongen, Jan J; van Bochove, Bas; Hannink, Gerjon; Grijpma, Dirk W; Buma, Pieter

2016-11-01

Photo-crosslinked networks prepared from three-armed methacrylate functionalized PTMC oligomers (PTMC-tMA macromers) are attractive materials for developing an anatomically correct meniscus scaffold. In this study, we evaluated cell specific biocompatibility, in vitro and in vivo degradation behavior of, and tissue response to, such PTMC networks. By evaluating PTMC networks prepared from PTMC-tMA macromers of different molecular weights, we were able to assess the effect of macromer molecular weight on the degradation rate of the PTMC network obtained after photo-crosslinking. Three photo-crosslinked networks with different crosslinking densities were prepared using PTMC-tMA macromers with molecular weights 13.3, 17.8, and 26.7 kg/mol. Good cell biocompatibility was demonstrated in a proliferation assay with synovium derived cells. PTMC networks degraded slowly, but statistically significant, both in vitro as well as subcutaneously in rats. Networks prepared from macromers with higher molecular weights demonstrated increased degradation rates compared to networks prepared from initial macromers of lowest molecular weight. The degradation process took place via surface erosion. The PTMC networks showed good tissue tolerance during subcutaneous implantation, to which the tissue response was characterized by the presence of fibrous tissue and encapsulation of the implants. Concluding, we developed cell and tissue biocompatible, photo-crosslinked PTMC networks using PTMC-tMA macromers with relatively high molecular weights. These photo-crosslinked PTMC networks slowly degrade by a surface erosion process. Increasing the crosslinking density of these networks decreases the rate of surface degradation. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 2823-2832, 2016. © 2016 Wiley Periodicals, Inc.

What we can learn from a tadpole about ciliopathies and airway diseases: Using systems biology in Xenopus to study cilia and mucociliary epithelia.

PubMed

Walentek, Peter; Quigley, Ian K

2017-01-01

Over the past years, the Xenopus embryo has emerged as an incredibly useful model organism for studying the formation and function of cilia and ciliated epithelia in vivo. This has led to a variety of findings elucidating the molecular mechanisms of ciliated cell specification, basal body biogenesis, cilia assembly, and ciliary motility. These findings also revealed the deep functional conservation of signaling, transcriptional, post-transcriptional, and protein networks employed in the formation and function of vertebrate ciliated cells. Therefore, Xenopus research can contribute crucial insights not only into developmental and cell biology, but also into the molecular mechanisms underlying cilia related diseases (ciliopathies) as well as diseases affecting the ciliated epithelium of the respiratory tract in humans (e.g., chronic lung diseases). Additionally, systems biology approaches including transcriptomics, genomics, and proteomics have been rapidly adapted for use in Xenopus, and broaden the applications for current and future translational biomedical research. This review aims to present the advantages of using Xenopus for cilia research, highlight some of the evolutionarily conserved key concepts and mechanisms of ciliated cell biology that were elucidated using the Xenopus model, and describe the potential for Xenopus research to address unresolved questions regarding the molecular mechanisms of ciliopathies and airway diseases. © 2017 Wiley Periodicals, Inc.

Realizations of highly heterogeneous collagen networks via stochastic reconstruction for micromechanical analysis of tumor cell invasion

NASA Astrophysics Data System (ADS)

Nan, Hanqing; Liang, Long; Chen, Guo; Liu, Liyu; Liu, Ruchuan; Jiao, Yang

2018-03-01

Three-dimensional (3D) collective cell migration in a collagen-based extracellular matrix (ECM) is among one of the most significant topics in developmental biology, cancer progression, tissue regeneration, and immune response. Recent studies have suggested that collagen-fiber mediated force transmission in cellularized ECM plays an important role in stress homeostasis and regulation of collective cellular behaviors. Motivated by the recent in vitro observation that oriented collagen can significantly enhance the penetration of migrating breast cancer cells into dense Matrigel which mimics the intravasation process in vivo [Han et al. Proc. Natl. Acad. Sci. USA 113, 11208 (2016), 10.1073/pnas.1610347113], we devise a procedure for generating realizations of highly heterogeneous 3D collagen networks with prescribed microstructural statistics via stochastic optimization. Specifically, a collagen network is represented via the graph (node-bond) model and the microstructural statistics considered include the cross-link (node) density, valence distribution, fiber (bond) length distribution, as well as fiber orientation distribution. An optimization problem is formulated in which the objective function is defined as the squared difference between a set of target microstructural statistics and the corresponding statistics for the simulated network. Simulated annealing is employed to solve the optimization problem by evolving an initial network via random perturbations to generate realizations of homogeneous networks with randomly oriented fibers, homogeneous networks with aligned fibers, heterogeneous networks with a continuous variation of fiber orientation along a prescribed direction, as well as a binary system containing a collagen region with aligned fibers and a dense Matrigel region with randomly oriented fibers. The generation and propagation of active forces in the simulated networks due to polarized contraction of an embedded ellipsoidal cell and a small group of cells are analyzed by considering a nonlinear fiber model incorporating strain hardening upon large stretching and buckling upon compression. Our analysis shows that oriented fibers can significantly enhance long-range force transmission in the network. Moreover, in the oriented-collagen-Matrigel system, the forces generated by a polarized cell in collagen can penetrate deeply into the Matrigel region. The stressed Matrigel fibers could provide contact guidance for the migrating cell cells, and thus enhance their penetration into Matrigel. This suggests a possible mechanism for the observed enhanced intravasation by oriented collagen.

SPANNER: A Self-Repairing Spiking Neural Network Hardware Architecture.

PubMed

Liu, Junxiu; Harkin, Jim; Maguire, Liam P; McDaid, Liam J; Wade, John J

2018-04-01

Recent research has shown that a glial cell of astrocyte underpins a self-repair mechanism in the human brain, where spiking neurons provide direct and indirect feedbacks to presynaptic terminals. These feedbacks modulate the synaptic transmission probability of release (PR). When synaptic faults occur, the neuron becomes silent or near silent due to the low PR of synapses; whereby the PRs of remaining healthy synapses are then increased by the indirect feedback from the astrocyte cell. In this paper, a novel hardware architecture of Self-rePAiring spiking Neural NEtwoRk (SPANNER) is proposed, which mimics this self-repairing capability in the human brain. This paper demonstrates that the hardware can self-detect and self-repair synaptic faults without the conventional components for the fault detection and fault repairing. Experimental results show that SPANNER can maintain the system performance with fault densities of up to 40%, and more importantly SPANNER has only a 20% performance degradation when the self-repairing architecture is significantly damaged at a fault density of 80%.

Research in network management techniques for tactical data communications networks

NASA Astrophysics Data System (ADS)

Boorstyn, R.; Kershenbaum, A.; Maglaris, B.; Sarachik, P.

1982-09-01

This is the final technical report for work performed on network management techniques for tactical data networks. It includes all technical papers that have been published during the control period. Research areas include Packet Network modelling, adaptive network routing, network design algorithms, network design techniques, and local area networks.

Using Cell-Phone Tower Signals for Detecting the Precursors of Fog

NASA Astrophysics Data System (ADS)

David, N.; Gao, H. O.

2018-01-01

In the last decade, published research has indicated the potential of commercial microwave links that comprise the data transmission infrastructure of cellular communication networks as an environmental monitoring technology. Different weather phenomena cause interference in the wireless communication links that can therefore essentially act as a low-cost sensor network, already deployed worldwide, for atmospheric monitoring. In this study we focus on the attenuation effect caused in commercial microwave networks due to gradients in the atmospheric refractive index with altitude as a result of the combination of temperature inversions and falls in the atmospheric humidity trapped beneath them. These conditions, when combined with high relative humidity near ground level, are precursors to the creation of fog. The current work utilizes this novel approach to demonstrate the potential for detecting these preconditions of fog, a phenomenon associated with severe visibility limitations that can lead to dangerous accidents, injuries, and loss of lives.

Paper-based Synthetic Gene Networks

PubMed Central

Pardee, Keith; Green, Alexander A.; Ferrante, Tom; Cameron, D. Ewen; DaleyKeyser, Ajay; Yin, Peng; Collins, James J.

2014-01-01

Synthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides a new venue for synthetic biologists to operate, and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze-dried onto paper, enabling the inexpensive, sterile and abiotic distribution of synthetic biology-based technologies for the clinic, global health, industry, research and education. For field use, we create circuits with colorimetric outputs for detection by eye, and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors. PMID:25417167

Microvascular Guidance: A Challenge to Support the Development of Vascularised Tissue Engineering Construct

PubMed Central

Sukmana, Irza

2012-01-01

The guidance of endothelial cell organization into a capillary network has been a long-standing challenge in tissue engineering. Some research efforts have been made to develop methods to promote capillary networks inside engineered tissue constructs. Capillary and vascular networks that would mimic blood microvessel function can be used to subsequently facilitate oxygen and nutrient transfer as well as waste removal. Vascularization of engineering tissue construct is one of the most favorable strategies to overpass nutrient and oxygen supply limitation, which is often the major hurdle in developing thick and complex tissue and artificial organ. This paper addresses recent advances and future challenges in developing three-dimensional culture systems to promote tissue construct vascularization allowing mimicking blood microvessel development and function encountered in vivo. Bioreactors systems that have been used to create fully vascularized functional tissue constructs will also be outlined. PMID:22623881

Paper-based synthetic gene networks.

PubMed

Pardee, Keith; Green, Alexander A; Ferrante, Tom; Cameron, D Ewen; DaleyKeyser, Ajay; Yin, Peng; Collins, James J

2014-11-06

Synthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides an alternate, versatile venue for synthetic biologists to operate and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze dried onto paper, enabling the inexpensive, sterile, and abiotic distribution of synthetic-biology-based technologies for the clinic, global health, industry, research, and education. For field use, we create circuits with colorimetric outputs for detection by eye and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small-molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors.

Mechanics of biological networks: from the cell cytoskeleton to connective tissue.

PubMed

Pritchard, Robyn H; Huang, Yan Yan Shery; Terentjev, Eugene M

2014-03-28

From the cell cytoskeleton to connective tissues, fibrous networks are ubiquitous in metazoan life as the key promoters of mechanical strength, support and integrity. In recent decades, the application of physics to biological systems has made substantial strides in elucidating the striking mechanical phenomena observed in such networks, explaining strain stiffening, power law rheology and cytoskeletal fluidisation - all key to the biological function of individual cells and tissues. In this review we focus on the current progress in the field, with a primer into the basic physics of individual filaments and the networks they form. This is followed by a discussion of biological networks in the context of a broad spread of recent in vitro and in vivo experiments.

Focus issue: series on computational and systems biology.

PubMed

Gough, Nancy R

2011-09-06

The application of computational biology and systems biology is yielding quantitative insight into cellular regulatory phenomena. For the month of September, Science Signaling highlights research featuring computational approaches to understanding cell signaling and investigation of signaling networks, a series of Teaching Resources from a course in systems biology, and various other articles and resources relevant to the application of computational biology and systems biology to the study of signal transduction.

Three dimensional microstructural network of elastin, collagen, and cells in Achilles tendons.

PubMed

Pang, Xin; Wu, Jian-Ping; Allison, Garry T; Xu, Jiake; Rubenson, Jonas; Zheng, Ming-Hao; Lloyd, David G; Gardiner, Bruce; Wang, Allan; Kirk, Thomas Brett

2017-06-01

Similar to most biological tissues, the biomechanical, and functional characteristics of the Achilles tendon are closely related to its composition and microstructure. It is commonly reported that type I collagen is the predominant component of tendons and is mainly responsible for the tissue's function. Although elastin has been found in varying proportions in other connective tissues, previous studies report that tendons contain very small quantities of elastin. However, the morphology and the microstructural relationship among the elastic fibres, collagen, and cells in tendon tissue have not been well examined. We hypothesize the elastic fibres, as another fibrillar component in the extracellular matrix, have a unique role in mechanical function and microstructural arrangement in Achilles tendons. It has been shown that elastic fibres present a close connection with the tenocytes. The close relationship of the three components has been revealed as a distinct, integrated and complex microstructural network. Notably, a "spiral" structure within fibril bundles in Achilles tendons was observed in some samples in specialized regions. This study substantiates the hierarchical system of the spatial microstructure of tendon, including the mapping of collagen, elastin and tenocytes, with 3-dimensional confocal images. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:1203-1214, 2017. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Sexy again: the renaissance of neutrophils in psoriasis.

PubMed

Schön, Michael P; Broekaert, Sigrid M C; Erpenbeck, Luise

2017-04-01

Notwithstanding their prominent presence in psoriatic skin, the functional role of neutrophilic granulocytes still remains somewhat enigmatic. Sparked by exciting scientific discoveries regarding neutrophil functions within the last years, the interest in these short-lived cells of the innate immune system has been boosted recently. While it had been known for some time that neutrophils produce and respond to a number of inflammatory mediators, recent research has linked neutrophils with the pathogenic functions of IL-17, possibly in conjunction with the formation of NETs (neutrophil extracellular traps). Antipsoriatic therapies exert their effects, at least in part, through interference with neutrophils. Neutrophils also appear to connect psoriasis with comorbid diseases. However, directly tampering with neutrophil functions is not trivial as evinced by the failure of therapeutic approaches targeting redundantly regulated cellular communication networks. It has also become apparent that neutrophils link important pathogenic functions of the innate and the adaptive immune system and that they are intricately involved in regulatory networks underlying the pathophysiology of psoriasis. In order to advocate intensified research into the role of this interesting cell population, we here highlight some features of neutrophils and put them into perspective with our current view of the pathophysiology of psoriasis. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Gene expression profiling of single cells on large-scale oligonucleotide arrays

PubMed Central

Hartmann, Claudia H.; Klein, Christoph A.

2006-01-01

Over the last decade, important insights into the regulation of cellular responses to various stimuli were gained by global gene expression analyses of cell populations. More recently, specific cell functions and underlying regulatory networks of rare cells isolated from their natural environment moved to the center of attention. However, low cell numbers still hinder gene expression profiling of rare ex vivo material in biomedical research. Therefore, we developed a robust method for gene expression profiling of single cells on high-density oligonucleotide arrays with excellent coverage of low abundance transcripts. The protocol was extensively tested with freshly isolated single cells of very low mRNA content including single epithelial, mature and immature dendritic cells and hematopoietic stem cells. Quantitative PCR confirmed that the PCR-based global amplification method did not change the relative ratios of transcript abundance and unsupervised hierarchical cluster analysis revealed that the histogenetic origin of an individual cell is correctly reflected by the gene expression profile. Moreover, the gene expression data from dendritic cells demonstrate that cellular differentiation and pathway activation can be monitored in individual cells. PMID:17071717

A Three-Dimensional Computational Model of Collagen Network Mechanics

PubMed Central

Lee, Byoungkoo; Zhou, Xin; Riching, Kristin; Eliceiri, Kevin W.; Keely, Patricia J.; Guelcher, Scott A.; Weaver, Alissa M.; Jiang, Yi

2014-01-01

Extracellular matrix (ECM) strongly influences cellular behaviors, including cell proliferation, adhesion, and particularly migration. In cancer, the rigidity of the stromal collagen environment is thought to control tumor aggressiveness, and collagen alignment has been linked to tumor cell invasion. While the mechanical properties of collagen at both the single fiber scale and the bulk gel scale are quite well studied, how the fiber network responds to local stress or deformation, both structurally and mechanically, is poorly understood. This intermediate scale knowledge is important to understanding cell-ECM interactions and is the focus of this study. We have developed a three-dimensional elastic collagen fiber network model (bead-and-spring model) and studied fiber network behaviors for various biophysical conditions: collagen density, crosslinker strength, crosslinker density, and fiber orientation (random vs. prealigned). We found the best-fit crosslinker parameter values using shear simulation tests in a small strain region. Using this calibrated collagen model, we simulated both shear and tensile tests in a large linear strain region for different network geometry conditions. The results suggest that network geometry is a key determinant of the mechanical properties of the fiber network. We further demonstrated how the fiber network structure and mechanics evolves with a local formation, mimicking the effect of pulling by a pseudopod during cell migration. Our computational fiber network model is a step toward a full biomechanical model of cellular behaviors in various ECM conditions. PMID:25386649

GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

PubMed Central

Mäkinen, Meeri Eeva-Liisa; Ylä-Outinen, Laura; Narkilahti, Susanna

2018-01-01

The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC)-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA) and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging) and temporal resolution microelectrode array (MEA). We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling. PMID:29559893

Neuronal replacement therapy: previous achievements and challenges ahead

NASA Astrophysics Data System (ADS)

Grade, Sofia; Götz, Magdalena

2017-10-01

Lifelong neurogenesis and incorporation of newborn neurons into mature neuronal circuits operates in specialized niches of the mammalian brain and serves as role model for neuronal replacement strategies. However, to which extent can the remaining brain parenchyma, which never incorporates new neurons during the adulthood, be as plastic and readily accommodate neurons in networks that suffered neuronal loss due to injury or neurological disease? Which microenvironment is permissive for neuronal replacement and synaptic integration and which cells perform best? Can lost function be restored and how adequate is the participation in the pre-existing circuitry? Could aberrant connections cause malfunction especially in networks dominated by excitatory neurons, such as the cerebral cortex? These questions show how important connectivity and circuitry aspects are for regenerative medicine, which is the focus of this review. We will discuss the impressive advances in neuronal replacement strategies and success from exogenous as well as endogenous cell sources. Both have seen key novel technologies, like the groundbreaking discovery of induced pluripotent stem cells and direct neuronal reprogramming, offering alternatives to the transplantation of fetal neurons, and both herald great expectations. For these to become reality, neuronal circuitry analysis is key now. As our understanding of neuronal circuits increases, neuronal replacement therapy should fulfill those prerequisites in network structure and function, in brain-wide input and output. Now is the time to incorporate neural circuitry research into regenerative medicine if we ever want to truly repair brain injury.

Modelling fuel cell performance using artificial intelligence

NASA Astrophysics Data System (ADS)

Ogaji, S. O. T.; Singh, R.; Pilidis, P.; Diacakis, M.

Over the last few years, fuel cell technology has been increasing promisingly its share in the generation of stationary power. Numerous pilot projects are operating worldwide, continuously increasing the amount of operating hours either as stand-alone devices or as part of gas turbine combined cycles. An essential tool for the adequate and dynamic analysis of such systems is a software model that enables the user to assess a large number of alternative options in the least possible time. On the other hand, the sphere of application of artificial neural networks has widened covering such endeavours of life such as medicine, finance and unsurprisingly engineering (diagnostics of faults in machines). Artificial neural networks have been described as diagrammatic representation of a mathematical equation that receives values (inputs) and gives out results (outputs). Artificial neural networks systems have the capacity to recognise and associate patterns and because of their inherent design features, they can be applied to linear and non-linear problem domains. In this paper, the performance of the fuel cell is modelled using artificial neural networks. The inputs to the network are variables that are critical to the performance of the fuel cell while the outputs are the result of changes in any one or all of the fuel cell design variables, on its performance. Critical parameters for the cell include the geometrical configuration as well as the operating conditions. For the neural network, various network design parameters such as the network size, training algorithm, activation functions and their causes on the effectiveness of the performance modelling are discussed. Results from the analysis as well as the limitations of the approach are presented and discussed.

CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms.

PubMed

Terfve, Camille; Cokelaer, Thomas; Henriques, David; MacNamara, Aidan; Goncalves, Emanuel; Morris, Melody K; van Iersel, Martijn; Lauffenburger, Douglas A; Saez-Rodriguez, Julio

2012-10-18

Cells process signals using complex and dynamic networks. Studying how this is performed in a context and cell type specific way is essential to understand signaling both in physiological and diseased situations. Context-specific medium/high throughput proteomic data measured upon perturbation is now relatively easy to obtain but formalisms that can take advantage of these features to build models of signaling are still comparatively scarce. Here we present CellNOptR, an open-source R software package for building predictive logic models of signaling networks by training networks derived from prior knowledge to signaling (typically phosphoproteomic) data. CellNOptR features different logic formalisms, from Boolean models to differential equations, in a common framework. These different logic model representations accommodate state and time values with increasing levels of detail. We provide in addition an interface via Cytoscape (CytoCopteR) to facilitate use and integration with Cytoscape network-based capabilities. Models generated with this pipeline have two key features. First, they are constrained by prior knowledge about the network but trained to data. They are therefore context and cell line specific, which results in enhanced predictive and mechanistic insights. Second, they can be built using different logic formalisms depending on the richness of the available data. Models built with CellNOptR are useful tools to understand how signals are processed by cells and how this is altered in disease. They can be used to predict the effect of perturbations (individual or in combinations), and potentially to engineer therapies that have differential effects/side effects depending on the cell type or context.

CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms

PubMed Central

2012-01-01

Background Cells process signals using complex and dynamic networks. Studying how this is performed in a context and cell type specific way is essential to understand signaling both in physiological and diseased situations. Context-specific medium/high throughput proteomic data measured upon perturbation is now relatively easy to obtain but formalisms that can take advantage of these features to build models of signaling are still comparatively scarce. Results Here we present CellNOptR, an open-source R software package for building predictive logic models of signaling networks by training networks derived from prior knowledge to signaling (typically phosphoproteomic) data. CellNOptR features different logic formalisms, from Boolean models to differential equations, in a common framework. These different logic model representations accommodate state and time values with increasing levels of detail. We provide in addition an interface via Cytoscape (CytoCopteR) to facilitate use and integration with Cytoscape network-based capabilities. Conclusions Models generated with this pipeline have two key features. First, they are constrained by prior knowledge about the network but trained to data. They are therefore context and cell line specific, which results in enhanced predictive and mechanistic insights. Second, they can be built using different logic formalisms depending on the richness of the available data. Models built with CellNOptR are useful tools to understand how signals are processed by cells and how this is altered in disease. They can be used to predict the effect of perturbations (individual or in combinations), and potentially to engineer therapies that have differential effects/side effects depending on the cell type or context. PMID:23079107

Ensemble methods for stochastic networks with special reference to the biological clock of Neurospora crassa.

PubMed

Caranica, C; Al-Omari, A; Deng, Z; Griffith, J; Nilsen, R; Mao, L; Arnold, J; Schüttler, H-B

2018-01-01

A major challenge in systems biology is to infer the parameters of regulatory networks that operate in a noisy environment, such as in a single cell. In a stochastic regime it is hard to distinguish noise from the real signal and to infer the noise contribution to the dynamical behavior. When the genetic network displays oscillatory dynamics, it is even harder to infer the parameters that produce the oscillations. To address this issue we introduce a new estimation method built on a combination of stochastic simulations, mass action kinetics and ensemble network simulations in which we match the average periodogram and phase of the model to that of the data. The method is relatively fast (compared to Metropolis-Hastings Monte Carlo Methods), easy to parallelize, applicable to large oscillatory networks and large (~2000 cells) single cell expression data sets, and it quantifies the noise impact on the observed dynamics. Standard errors of estimated rate coefficients are typically two orders of magnitude smaller than the mean from single cell experiments with on the order of ~1000 cells. We also provide a method to assess the goodness of fit of the stochastic network using the Hilbert phase of single cells. An analysis of phase departures from the null model with no communication between cells is consistent with a hypothesis of Stochastic Resonance describing single cell oscillators. Stochastic Resonance provides a physical mechanism whereby intracellular noise plays a positive role in establishing oscillatory behavior, but may require model parameters, such as rate coefficients, that differ substantially from those extracted at the macroscopic level from measurements on populations of millions of communicating, synchronized cells.

Co-authorship network analysis in health research: method and potential use.

PubMed

Fonseca, Bruna de Paula Fonseca E; Sampaio, Ricardo Barros; Fonseca, Marcus Vinicius de Araújo; Zicker, Fabio

2016-04-30

Scientific collaboration networks are a hallmark of contemporary academic research. Researchers are no longer independent players, but members of teams that bring together complementary skills and multidisciplinary approaches around common goals. Social network analysis and co-authorship networks are increasingly used as powerful tools to assess collaboration trends and to identify leading scientists and organizations. The analysis reveals the social structure of the networks by identifying actors and their connections. This article reviews the method and potential applications of co-authorship network analysis in health. The basic steps for conducting co-authorship studies in health research are described and common network metrics are presented. The application of the method is exemplified by an overview of the global research network for Chikungunya virus vaccines.

Social network analysis: Presenting an underused method for nursing research.

PubMed

Parnell, James Michael; Robinson, Jennifer C

2018-06-01

This paper introduces social network analysis as a versatile method with many applications in nursing research. Social networks have been studied for years in many social science fields. The methods continue to advance but remain unknown to most nursing scholars. Discussion paper. English language and interpreted literature was searched from Ovid Healthstar, CINAHL, PubMed Central, Scopus and hard copy texts from 1965 - 2017. Social network analysis first emerged in nursing literature in 1995 and appears minimally through present day. To convey the versatility and applicability of social network analysis in nursing, hypothetical scenarios are presented. The scenarios are illustrative of three approaches to social network analysis and include key elements of social network research design. The methods of social network analysis are underused in nursing research, primarily because they are unknown to most scholars. However, there is methodological flexibility and epistemological versatility capable of supporting quantitative and qualitative research. The analytic techniques of social network analysis can add new insight into many areas of nursing inquiry, especially those influenced by cultural norms. Furthermore, visualization techniques associated with social network analysis can be used to generate new hypotheses. Social network analysis can potentially uncover findings not accessible through methods commonly used in nursing research. Social networks can be analysed based on individual-level attributes, whole networks and subgroups within networks. Computations derived from social network analysis may stand alone to answer a research question or incorporated as variables into robust statistical models. © 2018 John Wiley & Sons Ltd.

Reverse Engineering Validation using a Benchmark Synthetic Gene Circuit in Human Cells

PubMed Central

Kang, Taek; White, Jacob T.; Xie, Zhen; Benenson, Yaakov; Sontag, Eduardo; Bleris, Leonidas

2013-01-01

Multi-component biological networks are often understood incompletely, in large part due to the lack of reliable and robust methodologies for network reverse engineering and characterization. As a consequence, developing automated and rigorously validated methodologies for unraveling the complexity of biomolecular networks in human cells remains a central challenge to life scientists and engineers. Today, when it comes to experimental and analytical requirements, there exists a great deal of diversity in reverse engineering methods, which renders the independent validation and comparison of their predictive capabilities difficult. In this work we introduce an experimental platform customized for the development and verification of reverse engineering and pathway characterization algorithms in mammalian cells. Specifically, we stably integrate a synthetic gene network in human kidney cells and use it as a benchmark for validating reverse engineering methodologies. The network, which is orthogonal to endogenous cellular signaling, contains a small set of regulatory interactions that can be used to quantify the reconstruction performance. By performing successive perturbations to each modular component of the network and comparing protein and RNA measurements, we study the conditions under which we can reliably reconstruct the causal relationships of the integrated synthetic network. PMID:23654266

Reverse engineering validation using a benchmark synthetic gene circuit in human cells.

PubMed

Kang, Taek; White, Jacob T; Xie, Zhen; Benenson, Yaakov; Sontag, Eduardo; Bleris, Leonidas

2013-05-17

Multicomponent biological networks are often understood incompletely, in large part due to the lack of reliable and robust methodologies for network reverse engineering and characterization. As a consequence, developing automated and rigorously validated methodologies for unraveling the complexity of biomolecular networks in human cells remains a central challenge to life scientists and engineers. Today, when it comes to experimental and analytical requirements, there exists a great deal of diversity in reverse engineering methods, which renders the independent validation and comparison of their predictive capabilities difficult. In this work we introduce an experimental platform customized for the development and verification of reverse engineering and pathway characterization algorithms in mammalian cells. Specifically, we stably integrate a synthetic gene network in human kidney cells and use it as a benchmark for validating reverse engineering methodologies. The network, which is orthogonal to endogenous cellular signaling, contains a small set of regulatory interactions that can be used to quantify the reconstruction performance. By performing successive perturbations to each modular component of the network and comparing protein and RNA measurements, we study the conditions under which we can reliably reconstruct the causal relationships of the integrated synthetic network.

Hopping Diffusion of Nanoparticles in Polymer Matrices

PubMed Central

2016-01-01

We propose a hopping mechanism for diffusion of large nonsticky nanoparticles subjected to topological constraints in both unentangled and entangled polymer solids (networks and gels) and entangled polymer liquids (melts and solutions). Probe particles with size larger than the mesh size ax of unentangled polymer networks or tube diameter ae of entangled polymer liquids are trapped by the network or entanglement cells. At long time scales, however, these particles can diffuse by overcoming free energy barrier between neighboring confinement cells. The terminal particle diffusion coefficient dominated by this hopping diffusion is appreciable for particles with size moderately larger than the network mesh size ax or tube diameter ae. Much larger particles in polymer solids will be permanently trapped by local network cells, whereas they can still move in polymer liquids by waiting for entanglement cells to rearrange on the relaxation time scales of these liquids. Hopping diffusion in entangled polymer liquids and networks has a weaker dependence on particle size than that in unentangled networks as entanglements can slide along chains under polymer deformation. The proposed novel hopping model enables understanding the motion of large nanoparticles in polymeric nanocomposites and the transport of nano drug carriers in complex biological gels such as mucus. PMID:25691803

System analysis identifies distinct and common functional networks governed by transcription factor ASCL1, in glioma and small cell lung cancer.

PubMed

Donakonda, Sainitin; Sinha, Swati; Dighe, Shrinivas Nivrutti; Rao, Manchanahalli R Satyanarayana

2017-07-25

ASCL1 is a basic Helix-Loop-Helix transcription factor (TF), which is involved in various cellular processes like neuronal development and signaling pathways. Transcriptome profiling has shown that ASCL1 overexpression plays an important role in the development of glioma and Small Cell Lung Carcinoma (SCLC), but distinct and common molecular mechanisms regulated by ASCL1 in these cancers are unknown. In order to understand how it drives the cellular functional network in these two tumors, we generated a gene expression profile in a glioma cell line (U87MG) to identify ASCL1 gene targets by an si RNA silencing approach and then compared this with a publicly available dataset of similarly silenced SCLC (NCI-H1618 cells). We constructed TF-TF and gene-gene interactions, as well as protein interaction networks of ASCL1 regulated genes in glioma and SCLC cells. Detailed network analysis uncovered various biological processes governed by ASCL1 target genes in these two tumor cell lines. We find that novel ASCL1 functions related to mitosis and signaling pathways influencing development and tumor growth are affected in both glioma and SCLC cells. In addition, we also observed ASCL1 governed functional networks that are distinct to glioma and SCLC.

Structure and organization of Stratocumulus fields: A network approach

NASA Astrophysics Data System (ADS)

Glassmeier, Franziska; Feingold, Graham

2017-04-01

The representation of Stratocumulus (Sc) clouds and their radiative impact is one of the large challenges for global climate models. Aerosol-cloud-precipitation interactions greatly contribute to this challenge by influencing the morphology of Sc fields: In the absence of rain, Sc are arranged in a relatively regular pattern of cloudy cells separated by cloud-free rings of down welling air ('closed cells'). Raining cloud fields, in contrast, exhibit an oscillating pattern of cloudy rings surrounding cloud free cells of negatively buoyant air caused by sedimentation and evaporation of rain ('open cells'). Surprisingly, these regular structures of open and closed cellular Sc fields and their potential for the development of new parameterizations have hardly been explored. In this contribution, we approach the organization of Sc from the perspective of a 2-dimensional random network. We find that cellular networks derived from LES simulations of open- and closed-cell Sc cases are almost indistinguishable and share the following features: (i) The distributions of nearest neighbors, or cell degree, are centered at six. This corresponds to approximately hexagonal cloud cells and is a direct mathematical consequence (Euler formula) of the triple junctions featured by Sc organization. (ii) The degree of individual cells is found to be proportional to the normalized size of the cells. This means that cell arrangement is independent of the typical cell size. (iii) Reflecting the continuously renewing dynamics of Sc fields, large (high-degree) cells tend to be neighbored by small (low-degree) cells and vice versa. These macroscopic network properties emerge independent of the state of the Sc field because the different processes governing the evolution of closed as compared to open cells correspond to topologically equivalent network dynamics. By developing a heuristic model, we show that open and closed cell dynamics can both be mimicked by versions of cell division and cell disappearance and are biased towards the expansion of smaller cells. As a conclusion of our network analysis, Sc organization can be characterized by a typical length scale and a scale-independent cell arrangement. While the typical length scale emerges from the full complexity of aerosol-cloud-precipitation-radiation interactions, cell arrangement is independent of cloud processes and its evolution could be parameterized based on our heuristic model.

Study on activity measurement of Nostoc flagelliforme cells based on color identification

NASA Astrophysics Data System (ADS)

Wang, Yizhong; Su, Jianyu; Liu, Tiegen; Kong, Fanzhi; Jia, Shiru

2008-12-01

In order to measure the activities of Nostoc flagelliforme cells, a new method based on color identification was proposed in this paper. N. flagelliforme cells were colored with fluoreseein diaeetate. Then, an image of colored N. flagelliforme cells was taken, and changed from RGB model to HIS model. Its histogram of hue H was calculated, which was used as the input of a designed BP network. The output of the BP network was the description of measured activity of N. flagelliforme cells. After training, the activity of N. flagelliforme cells was identified by the BP network according to the histogram of H of their colored image. Experiments were conducted with satisfied results to show the feasibility and usefulness of activity measurement of N. flagelliforme cells based on color identification.

A stochastic and dynamical view of pluripotency in mouse embryonic stem cells

PubMed Central

Lee, Esther J.

2018-01-01

Pluripotent embryonic stem cells are of paramount importance for biomedical sciences because of their innate ability for self-renewal and differentiation into all major cell lines. The fateful decision to exit or remain in the pluripotent state is regulated by complex genetic regulatory networks. The rapid growth of single-cell sequencing data has greatly stimulated applications of statistical and machine learning methods for inferring topologies of pluripotency regulating genetic networks. The inferred network topologies, however, often only encode Boolean information while remaining silent about the roles of dynamics and molecular stochasticity inherent in gene expression. Herein we develop a framework for systematically extending Boolean-level network topologies into higher resolution models of networks which explicitly account for the promoter architectures and gene state switching dynamics. We show the framework to be useful for disentangling the various contributions that gene switching, external signaling, and network topology make to the global heterogeneity and dynamics of transcription factor populations. We find the pluripotent state of the network to be a steady state which is robust to global variations of gene switching rates which we argue are a good proxy for epigenetic states of individual promoters. The temporal dynamics of exiting the pluripotent state, on the other hand, is significantly influenced by the rates of genetic switching which makes cells more responsive to changes in extracellular signals. PMID:29451874

A three-dimensional neural spheroid model for capillary-like network formation.

PubMed

Boutin, Molly E; Kramer, Liana L; Livi, Liane L; Brown, Tyler; Moore, Christopher; Hoffman-Kim, Diane

2018-04-01

In vitro three-dimensional neural spheroid models have an in vivo-like cell density, and have the potential to reduce animal usage and increase experimental throughput. The aim of this study was to establish a spheroid model to study the formation of capillary-like networks in a three-dimensional environment that incorporates both neuronal and glial cell types, and does not require exogenous vasculogenic growth factors. We created self-assembled, scaffold-free cellular spheroids using primary-derived postnatal rodent cortex as a cell source. The interactions between relevant neural cell types, basement membrane proteins, and endothelial cells were characterized by immunohistochemistry. Transmission electron microscopy was used to determine if endothelial network structures had lumens. Endothelial cells within cortical spheroids assembled into capillary-like networks with lumens. Networks were surrounded by basement membrane proteins, including laminin, fibronectin and collagen IV, as well as key neurovascular cell types. Existing in vitro models of the cortical neurovascular environment study monolayers of endothelial cells, either on transwell inserts or coating cellular spheroids. These models are not well suited to study vasculogenesis, a process hallmarked by endothelial cell cord formation and subsequent lumenization. The neural spheroid is a new model to study the formation of endothelial cell capillary-like structures in vitro within a high cell density three-dimensional environment that contains both neuronal and glial populations. This model can be applied to investigate vascular assembly in healthy or disease states, such as stroke, traumatic brain injury, or neurodegenerative disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

Differential localization of cytoplasmic myosin II isoforms A and B in avian interphase and dividing embryonic and immortalized cardiomyocytes and other cell types in vitro

NASA Technical Reports Server (NTRS)

Conrad, A. H.; Jaffredo, T.; Conrad, G. W.; Spooner, B. S. (Principal Investigator)

1995-01-01

Two principal isoforms of cytoplasmic myosin II, A and B (CMIIA and CMIIB), are present in different proportions in different tissues. Isoform-specific monoclonal and polyclonal antibodies to avian CMIIA and CMIIB reveal the cellular distributions of these isoforms in interphase and dividing embryonic avian cardiac, intestinal epithelial, spleen, and dorsal root ganglia cells in primary cell culture. Embryonic cardiomyocytes react with antibodies to CMIIB but not to CMIIA, localize CMIIB in stress-fiber-like-structures during interphase, and markedly concentrate CMIIB in networks in the cleavage furrow during cytokinesis. In contrast, cardiac fibroblasts localize both CMIIA and CMIIB in stress fibers and networks during interphase, and demonstrate slight and independently regulated concentration of CMIIA and CMIIB in networks in their cleavage furrows. V-myc-immortalized cardiomyocytes, an established cell line, have regained the ability to express CMIIA, as well as CMIIB, and localize both CMIIA and CMIIB in stress fibers and networks in interphase cells and in cleavage furrows in dividing cells. Conversely, some intestinal epithelial, spleen, and dorsal root ganglia interphase cells express only CMIIA, organized primarily in networks. Of these, intestinal epithelial cells express both CMIIA and CMIIB when they divide, whereas some dividing cells from both spleen and dorsal root ganglia express only CMIIA and concentrate it in their cleavage furrows. These results suggest that within a given tissue, different cell types express different isoforms of CMII, and that cells expressing either CMIIA or CMIIB alone, or simultaneously, can form a cleavage furrow and divide.

Critical role of CD4 T cells in maintaining lymphoid tissue structure for immune cell homeostasis and reconstitution.

PubMed

Zeng, Ming; Paiardini, Mirko; Engram, Jessica C; Beilman, Greg J; Chipman, Jeffrey G; Schacker, Timothy W; Silvestri, Guido; Haase, Ashley T

2012-08-30

Loss of the fibroblastic reticular cell (FRC) network in lymphoid tissues during HIV-1 infection has been shown to impair the survival of naive T cells and limit immune reconstitution after antiretroviral therapy. What causes this FRC loss is unknown. Because FRC loss correlates with loss of both naive CD4 and CD8 T-cell subsets and decreased lymphotoxin-β, a key factor for maintenance of FRC network, we hypothesized that loss of naive T cells is responsible for loss of the FRC network. To test this hypothesis, we assessed the consequences of antibody-mediated depletion of CD4 and CD8 T cells in rhesus macaques and sooty mangabeys. We found that only CD4 T-cell depletion resulted in FRC loss in both species and that this loss was caused by decreased lymphotoxin-β mainly produced by the CD4 T cells. We further found the same dependence of the FRC network on CD4 T cells in HIV-1-infected patients before and after antiretroviral therapy and in other immunodeficiency conditions, such as CD4 depletion in cancer patients induced by chemotherapy and irradiation. CD4 T cells thus play a central role in the maintenance of lymphoid tissue structure necessary for their own homeostasis and reconstitution.

Toxicogenomic investigation of Tetrahymena thermophila exposed to dichlorodiphenyltrichloroethane (DDT), tributyltin (TBT), and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD).

PubMed

Chang, Yue; Feng, LiFang; Miao, Wei

2011-07-01

Dichlorodiphenyltrichloroethane (DDT), tributyltin (TBT), and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) are persistent in the environment and cause continuous toxic effects in humans and aquatic life. Tetrahymena thermophila has the potential for use as a model for research regarding toxicants. In this study, this organism was used to analyze a genome-wide microarray generated from cells exposed to DDT, TBT and TCDD. To accomplish this, genes differentially expressed when treated with each toxicant were identified, after which their functions were categorized using GO enrichment analysis. The results suggested that the responses of T. thermophila were similar to those of multicellular organisms. Additionally, the context likelihood of relatedness method (CLR) was applied to construct a TCDD-relevant network. The T-shaped network obtained could be functionally divided into two subnetworks. The general functions of both subnetworks were related to the epigenetic mechanism of TCDD. Based on analysis of the networks, a model of the TCDD effect on T. thermophila was inferred. Thus, Tetrahymena has the potential to be a good unicellular eukaryotic model for toxic mechanism research at the genome level.

Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

PubMed Central

Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

2011-01-01

Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

Three-dimensional Organization of Layered Apical Cytoskeletal Networks Associated with Mouse Airway Tissue Development

NASA Astrophysics Data System (ADS)

Tateishi, Kazuhiro; Nishida, Tomoki; Inoue, Kanako; Tsukita, Sachiko

2017-03-01

The cytoskeleton is an essential cellular component that enables various sophisticated functions of epithelial cells by forming specialized subcellular compartments. However, the functional and structural roles of cytoskeletons in subcellular compartmentalization are still not fully understood. Here we identified a novel network structure consisting of actin filaments, intermediate filaments, and microtubules directly beneath the apical membrane in mouse airway multiciliated cells and in cultured epithelial cells. Three-dimensional imaging by ultra-high voltage electron microscopy and immunofluorescence revealed that the morphological features of each network depended on the cell type and were spatiotemporally integrated in association with tissue development. Detailed analyses using Odf2 mutant mice, which lack ciliary basal feet and apical microtubules, suggested a novel contribution of the intermediate filaments to coordinated ciliary beating. These findings provide a new perspective for viewing epithelial cell differentiation and tissue morphogenesis through the structure and function of apical cytoskeletal networks.

Digital photocontrol of the network of live excitable cells

NASA Astrophysics Data System (ADS)

Erofeev, I. S.; Magome, N.; Agladze, K. I.

2011-11-01

Recent development of tissue engineering techniques allows creating and maintaining almost indefinitely networks of excitable cells with desired architecture. We coupled the network of live excitable cardiac cells with a common computer by sensitizing them to light, projecting a light pattern on the layer of cells, and monitoring excitation with the aid of fluorescent probes (optical mapping). As a sensitizing substance we used azobenzene trimethylammonium bromide (AzoTAB). This substance undergoes cis-trans-photoisomerization and trans-isomer of AzoTAB inhibits excitation in the cardiac cells, while cis-isomer does not. AzoTAB-mediated sensitization allows, thus, reversible and dynamic control of the excitation waves through the entire cardiomyocyte network either uniformly, or in a preferred spatial pattern. Technically, it was achieved by coupling a common digital projector with a macroview microscope and using computer graphic software for creating the projected pattern of conducting pathways. This approach allows real time interactive photocontrol of the heart tissue.

Computer-aided design of biological circuits using TinkerCell

PubMed Central

Bergmann, Frank T; Sauro, Herbert M

2010-01-01

Synthetic biology is an engineering discipline that builds on modeling practices from systems biology and wet-lab techniques from genetic engineering. As synthetic biology advances, efficient procedures will be developed that will allow a synthetic biologist to design, analyze and build biological networks. In this idealized pipeline, computer-aided design (CAD) is a necessary component. The role of a CAD application would be to allow efficient transition from a general design to a final product. TinkerCell is a design tool for serving this purpose in synthetic biology. In TinkerCell, users build biological networks using biological parts and modules. The network can be analyzed using one of several functions provided by TinkerCell or custom programs from third-party sources. Since best practices for modeling and constructing synthetic biology networks have not yet been established, TinkerCell is designed as a flexible and extensible application that can adjust itself to changes in the field. PMID:21327060