Function of dynamic models in systems biology: linking structure to behaviour.

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Knüpfer, Christian; Beckstein, Clemens

2013-10-08

Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. In this paper we describe different functional aspects of dynamic models. This description is conceptually embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models. We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process

Mass spectrometry in structural biology and biophysics architecture, dynamics, and interaction of biomolecules

CERN Document Server

Kaltashov, Igor A; Desiderio, Dominic M; Nibbering, Nico M

2012-01-01

The definitive guide to mass spectrometry techniques in biology and biophysics The use of mass spectrometry (MS) to study the architecture and dynamics of proteins is increasingly common within the biophysical community, and Mass Spectrometry in Structural Biology and Biophysics: Architecture, Dynamics, and Interaction of Biomolecules, Second Edition provides readers with detailed, systematic coverage of the current state of the art. Offering an unrivalled overview of modern MS-based armamentarium that can be used to solve the most challenging problems in biophysics, structural biol

Applications of dynamical systems in biology and medicine

CERN Document Server

Radunskaya, Ami

2015-01-01

This volume highlights problems from a range of biological and medical applications that can be interpreted as questions about system behavior or control.  Topics include drug resistance in cancer and malaria, biological fluid dynamics, auto-regulation in the kidney, anti-coagulation therapy, evolutionary diversification and photo-transduction.  Mathematical techniques used to describe and investigate these biological and medical problems include ordinary, partial and stochastic differentiation equations, hybrid discrete-continuous approaches, as well as 2 and 3D numerical simulation. .

Dynamic Open Inquiry Performances of High-School Biology Students

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Zion, Michal; Sadeh, Irit

2010-01-01

In examining open inquiry projects among high-school biology students, we found dynamic inquiry performances expressed in two criteria: "changes occurring during inquiry" and "procedural understanding". Characterizing performances in a dynamic open inquiry project can shed light on both the procedural and epistemological…

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

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Villaverde, Alejandro F; Banga, Julio R

2017-11-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

The collective biology of the gene: Towards genetic dynamics engineering

International Nuclear Information System (INIS)

Chela-Flores, J.

1985-11-01

Chromatin dynamics is studied in terms of coupled vibrations (phonon pairing); this is shown to lead to a collective variable Δ, interpreted as a gene inhibition factor, which behaves as a biological switch turned off, not only by enzymatic action or metabolic energy, but also by means of an external probe:irradiation. We discuss the inactivation of the X chromosome and puffing. The relevance of being able to modulate Δ is emphasized, since it is equivalent to controlling chromatin dynamics without interfering with chromatin structure, unlike in the usual recombinant DNA techniques. (author)

Studies on biological macromolecules by neutron inelastic scattering

International Nuclear Information System (INIS)

Fujiwara, Satoru; Nakagawa, Hiroshi

2013-01-01

Neutron inelastic scattering techniques, including quasielastic and elastic incoherent neutron scattering, provide unique tools to directly measure the protein dynamics at a picosecond time scale. Since the protein dynamics at this time scale is indispensable to the protein functions, elucidation of the protein dynamics is indispensable for ultimate understanding of the protein functions. There are two complementary directions of the protein dynamics studies: one is to explore the physical basis of the protein dynamics using 'model' proteins, and the other is more biology-oriented. Examples of the studies on the protein dynamics with neutron inelastic scattering are described. The examples of the studies in the former direction include the studies on the dynamical transitions of the proteins, the relationship between the protein dynamics and the hydration water dynamics, and combined analysis of the protein dynamics with molecular dynamics simulation. The examples of the studies in the latter direction include the elastic incoherent and quasielastic neutrons scattering studies of actin. Future prospects of the studies on the protein dynamics with neutron scattering are briefly described. (author)

Molecular dynamics simulation studies of transmembrane transport of chemical components in Chinese herbs and the function of platycodin D in a biological membrane

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Shufang Yang

2017-04-01

Conclusion: The Martini force field was successfully applied to the study of the interaction between herbal compounds and a biological membrane. By combining the dynamics equilibrium morphology, the distribution of drugs inside and outside the biomembrane, and the interaction sites of drugs on the DPPC bilayer, factors influencing transmembrane transport of drugs were elucidated and the function of platycodin D in a biological membrane was reproduced.

Dynamical 'in situ' observation of biological samples using variable pressure scanning electron microscope

International Nuclear Information System (INIS)

Nedela, V

2008-01-01

Possibilities of 'in-situ' observation of non-conductive biological samples free of charging artefacts in dynamically changed surrounding conditions are the topic of this work. The observed biological sample, the tongue of a rat, was placed on a cooled Peltier stage. We studied the visibility of topographical structure depending on transition between liquid and gas state of water in the specimen chamber of VP SEM.

Mammalian synthetic biology for studying the cell.

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Mathur, Melina; Xiang, Joy S; Smolke, Christina D

2017-01-02

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. © 2017 Mathur et al.

Quantum mechanical simulation methods for studying biological systems

International Nuclear Information System (INIS)

Bicout, D.; Field, M.

1996-01-01

Most known biological mechanisms can be explained using fundamental laws of physics and chemistry and a full understanding of biological processes requires a multidisciplinary approach in which all the tools of biology, chemistry and physics are employed. An area of research becoming increasingly important is the theoretical study of biological macromolecules where numerical experimentation plays a double role of establishing a link between theoretical models and predictions and allowing a quantitative comparison between experiments and models. This workshop brought researchers working on different aspects of the development and application of quantum mechanical simulation together, assessed the state-of-the-art in the field and highlighted directions for future research. Fourteen lectures (theoretical courses and specialized seminars) deal with following themes: 1) quantum mechanical calculations of large systems, 2) ab initio molecular dynamics where the calculation of the wavefunction and hence the energy and forces on the atoms for a system at a single nuclear configuration are combined with classical molecular dynamics algorithms in order to perform simulations which use a quantum mechanical potential energy surface, 3) quantum dynamical simulations, electron and proton transfer processes in proteins and in solutions and finally, 4) free seminars that helped to enlarge the scope of the workshop. (N.T.)

Overshoot in biological systems modelled by Markov chains: a non-equilibrium dynamic phenomenon.

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Jia, Chen; Qian, Minping; Jiang, Daquan

2014-08-01

A number of biological systems can be modelled by Markov chains. Recently, there has been an increasing concern about when biological systems modelled by Markov chains will perform a dynamic phenomenon called overshoot. In this study, the authors found that the steady-state behaviour of the system will have a great effect on the occurrence of overshoot. They showed that overshoot in general cannot occur in systems that will finally approach an equilibrium steady state. They further classified overshoot into two types, named as simple overshoot and oscillating overshoot. They showed that except for extreme cases, oscillating overshoot will occur if the system is far from equilibrium. All these results clearly show that overshoot is a non-equilibrium dynamic phenomenon with energy consumption. In addition, the main result in this study is validated with real experimental data.

How input fluctuations reshape the dynamics of a biological switching system

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Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert

2012-12-01

An important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.148101 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable. Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions. We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.

High-speed AFM for Studying Dynamic Biomolecular Processes

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Ando, Toshio

2008-03-01

Biological molecules show their vital activities only in aqueous solutions. It had been one of dreams in biological sciences to directly observe biological macromolecules (protein, DNA) at work under a physiological condition because such observation is straightforward to understanding their dynamic behaviors and functional mechanisms. Optical microscopy has no sufficient spatial resolution and electron microscopy is not applicable to in-liquid samples. Atomic force microscopy (AFM) can visualize molecules in liquids at high resolution but its imaging rate was too low to capture dynamic biological processes. This slow imaging rate is because AFM employs mechanical probes (cantilevers) and mechanical scanners to detect the sample height at each pixel. It is quite difficult to quickly move a mechanical device of macroscopic size with sub-nanometer accuracy without producing unwanted vibrations. It is also difficult to maintain the delicate contact between a probe tip and fragile samples. Two key techniques are required to realize high-speed AFM for biological research; fast feedback control to maintain a weak tip-sample interaction force and a technique to suppress mechanical vibrations of the scanner. Various efforts have been carried out in the past decade to materialize high-speed AFM. The current high-speed AFM can capture images on video at 30-60 frames/s for a scan range of 250nm and 100 scan lines, without significantly disturbing week biomolecular interaction. Our recent studies demonstrated that this new microscope can reveal biomolecular processes such as myosin V walking along actin tracks and association/dissociation dynamics of chaperonin GroEL-GroES that occurs in a negatively cooperative manner. The capacity of nanometer-scale visualization of dynamic processes in liquids will innovate on biological research. In addition, it will open a new way to study dynamic chemical/physical processes of various phenomena that occur at the liquid-solid interfaces.

Dynamic models in research and management of biological invasions.

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Buchadas, Ana; Vaz, Ana Sofia; Honrado, João P; Alagador, Diogo; Bastos, Rita; Cabral, João A; Santos, Mário; Vicente, Joana R

2017-07-01

Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales. Copyright © 2017 Elsevier Ltd. All rights reserved.

Zebrafish as a visual and dynamic model to study the transport of nanosized drug delivery systems across the biological barriers.

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Li, Ye; Miao, Xiaoqing; Chen, Tongkai; Yi, Xiang; Wang, Ruibing; Zhao, Haitao; Lee, Simon Ming-Yuen; Wang, Xueqing; Zheng, Ying

2017-08-01

With the wide application of nanotechnology to drug delivery systems, a simple, dynamic and visual in vivo model for high-throughput screening of novel formulations with fluorescence markers across biological barriers is desperately needed. In vitro cell culture models have been widely used, although they are far from a complimentary in vivo system. Mammalian animal models are common predictive models to study transport, but they are costly and time consuming. Zebrafish (Danio rerio), a small vertebrate model, have the potential to be developed as an "intermediate" model for quick evaluations. Based on our previously established coumarin 6 nanocrystals (C6-NCs), which have two different sizes, the present study investigates the transportation of C6-NCs across four biological barriers, including the chorion, blood brain barrier (BBB), blood retinal barrier (BRB) and gastrointestinal (GI) barrier, using zebrafish embryos and larvae as in vivo models. The biodistribution and elimination of C6 from different organs were quantified in adult zebrafish. The results showed that compared to 200nm C6-NCs, 70nm C6-NCs showed better permeability across these biological barriers. A FRET study suggested that intact C6-NCs together with the free dissolved form of C6 were absorbed into the larval zebrafish. More C6 was accumulated in different organs after incubation with small sized NCs via lipid raft-mediated endocytosis in adult zebrafish, which is consistent with the findings from in vitro cell monolayers and the zebrafish larvae model. C6-NCs could be gradually eliminated in each organ over time. This study demonstrated the successful application of zebrafish as a simple and dynamic model to simultaneously assess the transport of nanosized drug delivery systems across several biological barriers and biodistribution in different organs, especially in the brain, which could be used for central nervous system (CNS) drug and delivery system screening. Copyright © 2017 Elsevier B

The biology and dynamics of mammalian cortical granules

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Liu Min

2011-11-01

Full Text Available Abstract Cortical granules are membrane bound organelles located in the cortex of unfertilized oocytes. Following fertilization, cortical granules undergo exocytosis to release their contents into the perivitelline space. This secretory process, which is calcium dependent and SNARE protein-mediated pathway, is known as the cortical reaction. After exocytosis, the released cortical granule proteins are responsible for blocking polyspermy by modifying the oocytes' extracellular matrices, such as the zona pellucida in mammals. Mammalian cortical granules range in size from 0.2 um to 0.6 um in diameter and different from most other regulatory secretory organelles in that they are not renewed once released. These granules are only synthesized in female germ cells and transform an egg upon sperm entry; therefore, this unique cellular structure has inherent interest for our understanding of the biology of fertilization. Cortical granules are long thought to be static and awaiting in the cortex of unfertilized oocytes to be stimulated undergoing exocytosis upon gamete fusion. Not till recently, the dynamic nature of cortical granules is appreciated and understood. The latest studies of mammalian cortical granules document that this organelle is not only biochemically heterogeneous, but also displays complex distribution during oocyte development. Interestingly, some cortical granules undergo exocytosis prior to fertilization; and a number of granule components function beyond the time of fertilization in regulating embryonic cleavage and preimplantation development, demonstrating their functional significance in fertilization as well as early embryonic development. The following review will present studies that investigate the biology of cortical granules and will also discuss new findings that uncover the dynamic aspect of this organelle in mammals.

A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology.

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Jafari, Mohieddin; Ansari-Pour, Naser; Azimzadeh, Sadegh; Mirzaie, Mehdi

It is nearly half a century past the age of the introduction of the Central Dogma (CD) of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology.

A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology.

Directory of Open Access Journals (Sweden)

Mohieddin Jafari

Full Text Available It is nearly half a century past the age of the introduction of the Central Dogma (CD of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology.

Dynamic neuronal ensembles: Issues in representing structure change in object-oriented, biologically-based brain models

Energy Technology Data Exchange (ETDEWEB)

Vahie, S.; Zeigler, B.P.; Cho, H. [Univ. of Arizona, Tucson, AZ (United States)

1996-12-31

This paper describes the structure of dynamic neuronal ensembles (DNEs). DNEs represent a new paradigm for learning, based on biological neural networks that use variable structures. We present a computational neural element that demonstrates biological neuron functionality such as neurotransmitter feedback absolute refractory period and multiple output potentials. More specifically, we will develop a network of neural elements that have the ability to dynamically strengthen, weaken, add and remove interconnections. We demonstrate that the DNE is capable of performing dynamic modifications to neuron connections and exhibiting biological neuron functionality. In addition to its applications for learning, DNEs provide an excellent environment for testing and analysis of biological neural systems. An example of habituation and hyper-sensitization in biological systems, using a neural circuit from a snail is presented and discussed. This paper provides an insight into the DNE paradigm using models developed and simulated in DEVS.

Separating intrinsic from extrinsic fluctuations in dynamic biological systems.

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Hilfinger, Andreas; Paulsson, Johan

2011-07-19

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems.

Dynamic optimization of distributed biological systems using robust and efficient numerical techniques.

Science.gov (United States)

Vilas, Carlos; Balsa-Canto, Eva; García, Maria-Sonia G; Banga, Julio R; Alonso, Antonio A

2012-07-02

Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations.This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of

Application of Solution NMR Spectroscopy to Study Protein Dynamics

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Christoph Göbl

2012-03-01

Full Text Available Recent advances in spectroscopic methods allow the identification of minute fluctuations in a protein structure. These dynamic properties have been identified as keys to some biological processes. The consequences of this structural flexibility can be far‑reaching and they add a new dimension to the structure-function relationship of biomolecules. Nuclear Magnetic Resonance (NMR spectroscopy allows the study of structure as well as dynamics of biomolecules in a very broad range of timescales at atomic level. A number of new NMR methods have been developed recently to allow the measurements of time scales and spatial fluctuations, which in turn provide the thermodynamics associated with the biological processes. Since NMR parameters reflect ensemble measurements, structural ensemble approaches in analyzing NMR data have also been developed. These new methods in some instances can even highlight previously hidden conformational features of the biomolecules. In this review we describe several solution NMR methods to study protein dynamics and discuss their impact on important biological processes.

General method to find the attractors of discrete dynamic models of biological systems

Science.gov (United States)

Gan, Xiao; Albert, Réka

2018-04-01

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

General method to find the attractors of discrete dynamic models of biological systems.

Science.gov (United States)

Gan, Xiao; Albert, Réka

2018-04-01

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

Female juvenile murderers: Biological and psychological dynamics leading to homicide.

Science.gov (United States)

Heide, Kathleen M; Solomon, Eldra P

2009-01-01

The increasing involvement of girls under 18 in violent crime has been a matter of growing concern in the United States in recent years. This article reviews the arrests of female juveniles for violent crime and then focuses specifically on their involvement in homicide. Arrests of girls for murder, unlike arrests for assault, have not risen over the last 30 years, suggesting that the dynamics that propel female juveniles to engage in lethal violence differ from those contributing to assaultive behavior by this same group. A review of the literature indicates that theories as to why female adolescents kill do not take into account recent scientific findings on brain development and the biological effects of early trauma in explaining serious violent behavior by girls. Three cases, evaluated by the authors, involving female adolescents charged with murder or attempted murder, are presented. The authors focus on the biological and psychological dynamics that help explain their violent behavior. They discuss the effects of insecure attachment and child maltreatment, and trace a critical pathway between these early experiences and future risk of violent behavior. The dynamics of child maltreatment in fostering rage and violence are discussed thereafter in terms of offender accountability. The article concludes with a discussion of treatment and recommendations for future research.

Robust and efficient parameter estimation in dynamic models of biological systems.

Science.gov (United States)

Gábor, Attila; Banga, Julio R

2015-10-29

Dynamic modelling provides a systematic framework to understand function in biological systems. Parameter estimation in nonlinear dynamic models remains a very challenging inverse problem due to its nonconvexity and ill-conditioning. Associated issues like overfitting and local solutions are usually not properly addressed in the systems biology literature despite their importance. Here we present a method for robust and efficient parameter estimation which uses two main strategies to surmount the aforementioned difficulties: (i) efficient global optimization to deal with nonconvexity, and (ii) proper regularization methods to handle ill-conditioning. In the case of regularization, we present a detailed critical comparison of methods and guidelines for properly tuning them. Further, we show how regularized estimations ensure the best trade-offs between bias and variance, reducing overfitting, and allowing the incorporation of prior knowledge in a systematic way. We illustrate the performance of the presented method with seven case studies of different nature and increasing complexity, considering several scenarios of data availability, measurement noise and prior knowledge. We show how our method ensures improved estimations with faster and more stable convergence. We also show how the calibrated models are more generalizable. Finally, we give a set of simple guidelines to apply this strategy to a wide variety of calibration problems. Here we provide a parameter estimation strategy which combines efficient global optimization with a regularization scheme. This method is able to calibrate dynamic models in an efficient and robust way, effectively fighting overfitting and allowing the incorporation of prior information.

Quantum and classical dynamics in biologically inspired systems

International Nuclear Information System (INIS)

Guerreschi, G.

2012-01-01

Quantum biology is an emerging field in which traditional believes and paradigms are under examination. Typically, quantum effects are witnessed inside quantum optics or atomic physics laboratories in systems which are kept under control and isolated from any noise source by means of very advanced technology. Biological systems exhibit opposite characteristics: They are usually constituted of macromolecules continuously exposed to a warm and wet environment, well beyond our control; but at the same time, they operate far away from equilibrium. Recently, the experimental observation of excitonic coherence in photosynthetic complexes has con firmed that, in non-equilibrium scenarios, quantum phenomena can survive even in presence of a noisy environment. The challenge faced by the ongoing research is twofold: On one side, considering biological molecules as effective nanomachines, one has to address questions of principle regarding their design and functioning; on the other side, one has to investigate real systems which are experimentally accessible and identify such features in these concrete scenarios. The present thesis contributes to both of these aspects. In Part I, we demonstrate how entanglement can be persistently generated even under unfavorable environmental conditions. The physical mechanism is modeled after the idea of conformational changes, and it relies on the interplay of classical oscillations of large structures with the quantum dynamics of a few interacting degrees of freedom. In a similar context, we show that the transfer of an excitation through a linear chain of sites can be enhanced when the inter-site distances oscillate periodically. This enhancement is present even in comparison with the static con figuration which is optimal in the classical case and, therefore, it constitutes a clear signature of the underlying quantum dynamics. In Part II of this thesis, we study the radical pair mechanism from the perspective of quantum control and

River, delta and coastal morphological response accounting for biological dynamics

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Goldsmith, W.; Bernardi, D.; Schippa, L.

2015-03-01

Management and construction can increase resilience in the face of climate change, and benefits can be enhanced through integration of biogenic materials including shells and vegetation. Rivers and coastal landforms are dynamic systems that respond to intentional and unintended manipulation of critical factors, often with unforeseen and/or undesirable resulting effects. River management strategies have impacts that include deltas and coastal areas which are increasingly vulnerable to climate change with reference to sea level rise and storm intensity. Whereas conventional assessment and analysis of rivers and coasts has relied on modelling of hydrology, hydraulics and sediment transport, incorporating additional biological factors can offer more comprehensive, beneficial and realistic alternatives. Suitable modelling tools can provide improved decision support. The question has been whether current models can effectively address biological responses with suitable reliability and efficiency. Since morphodynamic evolution exhibits its effects on a large timescale, the choice of mathematical model is not trivial and depends upon the availability of data, as well as the spatial extent, timelines and computation effort desired. The ultimate goal of the work is to set up a conveniently simplified river morphodynamic model, coupled with a biological dynamics plant population model able to predict the long-term evolution of large alluvial river systems managed through bioengineering. This paper presents the first step of the work related to the application of the model accounting for stationary vegetation condition. Sensitivity analysis has been performed on the main hydraulic, sedimentology, and biological parameters. The model has been applied to significant river training in Europe, Asia and North America, and comparative analysis has been used to validate analytical solutions. Data gaps and further areas for investigation are identified.

Dynamic respiration index as a descriptor of the biological stability of organic wastes.

Science.gov (United States)

Adani, Fabrizio; Confalonieri, Roberto; Tambone, Fulvia

2004-01-01

Analytical methods applicable to different organic wastes are needed to establish the extent to which readily biodegradable organic matter has decomposed (i.e., biological stability). The objective of this study was to test a new respirometric method for biological stability determination of organic wastes. Dynamic respiration index (DRI) measurements were performed on 16 organic wastes of different origin, composition, and biological stability degree to validate the test method and result expression, and to propose biological stability limits. In addition, theoretical DRI trends were obtained by using a mathematical model. Each test lasted 96 h in a 148-L-capacity respirometer apparatus, and DRI was monitored every hour. The biological stability was expressed as both single and cumulative DRI values. Results obtained indicated that DRI described biological stability in relation to waste typology and age well, revealing lower-stability waste characterized by a well-pronounced DRI profile (a marked peak was evident) that became practically flat for samples with higher biological stability. Fitting indices showed good model prediction compared with the experimental data, indicating that the method was able to reproduce the aerobic process, providing a reliable indication of the biological stability. The DRI can therefore be proposed as a useful method to measure the biological stability of organic wastes, and DRI values, calculated as a mean of 24 h of the highest microbial activity, of 1000 and 500 mg O(2) kg(-1) volatile solids (VS) h(-1) are proposed to indicate medium (e.g., fresh compost) and high (e.g., mature compost) biological stabilities, respectively.

Modeling dynamics of biological and chemical components of aquatic ecosystems

International Nuclear Information System (INIS)

Lassiter, R.R.

1975-05-01

To provide capability to model aquatic ecosystems or their subsystems as needed for particular research goals, a modeling strategy was developed. Submodels of several processes common to aquatic ecosystems were developed or adapted from previously existing ones. Included are submodels for photosynthesis as a function of light and depth, biological growth rates as a function of temperature, dynamic chemical equilibrium, feeding and growth, and various types of losses to biological populations. These submodels may be used as modules in the construction of models of subsystems or ecosystems. A preliminary model for the nitrogen cycle subsystem was developed using the modeling strategy and applicable submodels. (U.S.)

Modeling biological pathway dynamics with timed automata.

Science.gov (United States)

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

Dynamics of problem setting and framing in citizen discussions on synthetic biology.

Science.gov (United States)

Betten, Afke Wieke; Broerse, Jacqueline E W; Kupper, Frank

2018-04-01

Synthetic biology is an emerging scientific field where engineers and biologists design and build biological systems for various applications. Developing synthetic biology responsibly in the public interest necessitates a meaningful societal dialogue. In this article, we argue that facilitating such a dialogue requires an understanding of how people make sense of synthetic biology. We performed qualitative research to unravel the underlying dynamics of problem setting and framing in citizen discussions on synthetic biology. We found that most people are not inherently for or against synthetic biology as a technology or development in itself, but that their perspectives are framed by core values about our relationships with science and technology and that sensemaking is much dependent on the context and general feelings of (dis)content. Given that there are many assumptions focused on a more binary idea of the public's view, we emphasize the need for frame awareness and understanding in a meaningful dialogue.

Disentangling physical and biological drivers of phytoplankton dynamics in a coastal system.

Science.gov (United States)

Cianelli, Daniela; D'Alelio, Domenico; Uttieri, Marco; Sarno, Diana; Zingone, Adriana; Zambianchi, Enrico; d'Alcalà, Maurizio Ribera

2017-11-20

This proof-of-concept study integrates the surface currents measured by high-frequency coastal radars with plankton time-series data collected at a fixed sampling point from the Mediterranean Sea (MareChiara Long Term Ecological Research site in the Gulf of Naples) to characterize the spatial origin of phytoplankton assemblages and to scrutinize the processes ruling their dynamics. The phytoplankton community generally originated from the coastal waters whereby species succession was mainly regulated by biological factors (life-cycle processes, species-specific physiological performances and inter-specific interactions). Physical factors, e.g. the alternation between coastal and offshore waters and the horizontal mixing, were also important drivers of phytoplankton dynamics promoting diversity maintenance by i) advecting species from offshore and ii) diluting the resident coastal community so as to dampen resource stripping by dominant species and thereby increase the numerical importance of rarer species. Our observations highlight the resilience of coastal communities, which may favour their persistence over time and the prevalence of successional events over small time and space scales. Although coastal systems may act differently from one another, our findings provide a conceptual framework to address physical-biological interactions occurring in coastal basins, which can be generalised to other areas.

River, delta and coastal morphological response accounting for biological dynamics

Directory of Open Access Journals (Sweden)

W. Goldsmith

2015-03-01

Full Text Available Management and construction can increase resilience in the face of climate change, and benefits can be enhanced through integration of biogenic materials including shells and vegetation. Rivers and coastal landforms are dynamic systems that respond to intentional and unintended manipulation of critical factors, often with unforeseen and/or undesirable resulting effects. River management strategies have impacts that include deltas and coastal areas which are increasingly vulnerable to climate change with reference to sea level rise and storm intensity. Whereas conventional assessment and analysis of rivers and coasts has relied on modelling of hydrology, hydraulics and sediment transport, incorporating additional biological factors can offer more comprehensive, beneficial and realistic alternatives. Suitable modelling tools can provide improved decision support. The question has been whether current models can effectively address biological responses with suitable reliability and efficiency. Since morphodynamic evolution exhibits its effects on a large timescale, the choice of mathematical model is not trivial and depends upon the availability of data, as well as the spatial extent, timelines and computation effort desired. The ultimate goal of the work is to set up a conveniently simplified river morphodynamic model, coupled with a biological dynamics plant population model able to predict the long-term evolution of large alluvial river systems managed through bioengineering. This paper presents the first step of the work related to the application of the model accounting for stationary vegetation condition. Sensitivity analysis has been performed on the main hydraulic, sedimentology, and biological parameters. The model has been applied to significant river training in Europe, Asia and North America, and comparative analysis has been used to validate analytical solutions. Data gaps and further areas for investigation are identified.

Biology as population dynamics: heuristics for transmission risk.

Science.gov (United States)

Keebler, Daniel; Walwyn, David; Welte, Alex

2013-02-01

Population-type models, accounting for phenomena such as population lifetimes, mixing patterns, recruitment patterns, genetic evolution and environmental conditions, can be usefully applied to the biology of HIV infection and viral replication. A simple dynamic model can explore the effect of a vaccine-like stimulus on the mortality and infectiousness, which formally looks like fertility, of invading virions; the mortality of freshly infected cells; and the availability of target cells, all of which impact on the probability of infection. Variations on this model could capture the importance of the timing and duration of different key events in viral transmission, and hence be applied to questions of mucosal immunology. The dynamical insights and assumptions of such models are compatible with the continuum of between- and within-individual risks in sexual violence and may be helpful in making sense of the sparse data available on the association between HIV transmission and sexual violence. © 2012 John Wiley & Sons A/S.

Quantum Processes and Dynamic Networks in Physical and Biological Systems.

Science.gov (United States)

Dudziak, Martin Joseph

Quantum theory since its earliest formulations in the Copenhagen Interpretation has been difficult to integrate with general relativity and with classical Newtonian physics. There has been traditionally a regard for quantum phenomena as being a limiting case for a natural order that is fundamentally classical except for microscopic extrema where quantum mechanics must be applied, more as a mathematical reconciliation rather than as a description and explanation. Macroscopic sciences including the study of biological neural networks, cellular energy transports and the broad field of non-linear and chaotic systems point to a quantum dimension extending across all scales of measurement and encompassing all of Nature as a fundamentally quantum universe. Theory and observation lead to a number of hypotheses all of which point to dynamic, evolving networks of fundamental or elementary processes as the underlying logico-physical structure (manifestation) in Nature and a strongly quantized dimension to macroscalar processes such as are found in biological, ecological and social systems. The fundamental thesis advanced and presented herein is that quantum phenomena may be the direct consequence of a universe built not from objects and substance but from interacting, interdependent processes collectively operating as sets and networks, giving rise to systems that on microcosmic or macroscopic scales function wholistically and organically, exhibiting non-locality and other non -classical phenomena. The argument is made that such effects as non-locality are not aberrations or departures from the norm but ordinary consequences of the process-network dynamics of Nature. Quantum processes are taken to be the fundamental action-events within Nature; rather than being the exception quantum theory is the rule. The argument is also presented that the study of quantum physics could benefit from the study of selective higher-scale complex systems, such as neural processes in the brain

Protein electron transfer: is biology (thermo)dynamic?

International Nuclear Information System (INIS)

Matyushov, Dmitry V

2015-01-01

Simple physical mechanisms are behind the flow of energy in all forms of life. Energy comes to living systems through electrons occupying high-energy states, either from food (respiratory chains) or from light (photosynthesis). This energy is transformed into the cross-membrane proton-motive force that eventually drives all biochemistry of the cell. Life’s ability to transfer electrons over large distances with nearly zero loss of free energy is puzzling and has not been accomplished in synthetic systems. The focus of this review is on how this energetic efficiency is realized. General physical mechanisms and interactions that allow proteins to fold into compact water-soluble structures are also responsible for a rugged landscape of energy states and a broad distribution of relaxation times. Specific to a protein as a fluctuating thermal bath is the protein-water interface, which is heterogeneous both dynamically and structurally. The spectrum of interfacial fluctuations is a consequence of protein’s elastic flexibility combined with a high density of surface charges polarizing water dipoles into surface nanodomains. Electrostatics is critical to the protein function and the relevant questions are: (i) What is the spectrum of interfacial electrostatic fluctuations? (ii) Does the interfacial biological water produce electrostatic signatures specific to proteins? (iii) How is protein-mediated chemistry affected by electrostatics? These questions connect the fluctuation spectrum to the dynamical control of chemical reactivity, i.e. the dependence of the activation free energy of the reaction on the dynamics of the bath. Ergodicity is often broken in protein-driven reactions and thermodynamic free energies become irrelevant. Continuous ergodicity breaking in a dense spectrum of relaxation times requires using dynamically restricted ensembles to calculate statistical averages. When applied to the calculation of the rates, this formalism leads to the nonergodic

Pseudorandom numbers: evolutionary models in image processing, biology, and nonlinear dynamic systems

Science.gov (United States)

Yaroslavsky, Leonid P.

1996-11-01

We show that one can treat pseudo-random generators, evolutionary models of texture images, iterative local adaptive filters for image restoration and enhancement and growth models in biology and material sciences in a unified way as special cases of dynamic systems with a nonlinear feedback.

6,7-dimethoxy-coumarin as a probe of hydration dynamics in biologically relevant systems

Science.gov (United States)

Ghose, Avisek; Amaro, Mariana; Kovaricek, Petr; Hof, Martin; Sykora, Jan

2018-04-01

Coumarin derivatives are well known fluorescence reporters for investigating biological systems due to their strong micro-environment sensitivity. Despite having wide range of environment sensitive fluorescence probes, the potential of 6,7-dimethoxy-coumarin has not been studied extensively so far. With a perspective of its use in protein studies, namely using the unnatural amino acid technology or as a substrate for hydrolase enzymes, we study acetyloxymethyl-6,7-dimethoxycoumarin (Ac-DMC). We investigate the photophysics and hydration dynamics of this dye in aerosol-OT (AOT) reverse micelles at various water contents using the time dependent fluorescence shift (TDFS) method. The TDFS response in AOT reverse micelles from water/surfactant ratio of 0 to 20 confirms its sensitivity towards the hydration and mobility of its microenvironment. Moreover, we show that the fluorophore can be efficiently quenched by halide ions. Hence, we conclude that the 6,7-dimethoxy-methylcoumarin fluorophore is useful for studying hydration parameters in biologically relevant systems.

New sources and instrumentation for neutrons in biology

DEFF Research Database (Denmark)

Teixeira, S. C. M.; Zaccai, G.; Ankner, J.

2008-01-01

Neutron radiation offers significant advantages for the study of biological molecular structure and dynamics. A broad and significant effort towards instrumental and methodological development to facilitate biology experiments at neutron sources worldwide is reviewed.......Neutron radiation offers significant advantages for the study of biological molecular structure and dynamics. A broad and significant effort towards instrumental and methodological development to facilitate biology experiments at neutron sources worldwide is reviewed....

Chemical and biological activity in open flows: A dynamical system approach

International Nuclear Information System (INIS)

Tel, Tamas; Moura, Alessandro de; Grebogi, Celso; Karolyi, Gyoergy

2005-01-01

Chemical and biological processes often take place in fluid flows. Many of them, like environmental or microfluidical ones, generate filamentary patterns which have a fractal structure, due to the presence of chaos in the underlying advection dynamics. In such cases, hydrodynamical stirring strongly couples to the reactivity of the advected species: the outcome of the reaction is then typically different from that of the same reaction taking place in a well-mixed environment. Here we review recent progress in this field, which became possible due to the application of methods taken from dynamical system theory. We place special emphasis on the derivation of effective rate equations which contain singular terms expressing the fact that the reaction takes place on a moving fractal catalyst, on the unstable foliation of the reaction free advection dynamics

Structure and dynamics of photosynthetic proteins studied by neutron scattering and molecular dynamic simulation

International Nuclear Information System (INIS)

Dellerue, Serge

2000-01-01

Understand the structure-dynamics-function relation in the case of proteins is essential. But few experimental techniques allow to have access to knowledge of fast internal movements of biological macromolecules. With the neutron scattering method, it has been possible to study the reorientation dynamics of side chains and of polypeptide skeleton for two proteins in terms of water or detergent and of temperature. With the use of the molecular dynamics method, essential for completing and interpreting the experimental data, it has been possible to assess the different contributions of the whole structure of proteins to the overall dynamics. It has been shown that the polypeptide skeleton presents an energy relaxation comparable to those of the side chains. Moreover, it has been explained that the protein dynamics can only be understood in terms of relaxation time distribution. (author) [fr

Life at extreme conditions: neutron scattering studies of biological molecules suggest that evolution selected dynamics

International Nuclear Information System (INIS)

Zaccai, Joseph Giuseppe

2008-01-01

The short review concentrates on recent work performed at the neutrons in biology laboratories of the Institut Laue Langevin and Institut de Biologie Structurale in Grenoble. Extremophile organisms have been discovered that require extreme conditions of temperature, pressure or solvent environment for survival. The existence of such organisms poses a significant challenge in understanding the physical chemistry of their proteins, in view of the great sensitivity of protein structure and stability to the aqueous environment and to external conditions in general. Results of neutron scattering measurements on the dynamics of proteins from extremophile organisms, in vitro as well as in vivo, indicated remarkably how adaptation to extreme conditions involves forces and fluctuation amplitudes that have been selected specifically, suggesting that evolutionary macromolecular selection proceeded via dynamics. The experiments were performed on a halophilic protein, and membrane adapted to high salt, a thermophilic enzyme adapted to high temperature and its mesophilic (adapted to 37 degC) homologue; and in vivo for psychrophilic, mesophilic, thermophilic and hyperthermophilic bacteria, adapted respectively to temperatures of 4 degC, 37 degC, 75 degC and 85 degC. Further work demonstrated the existence of a water component of exceptionally low mobility in an extreme halophile from the Dead Sea, which is not present in mesophile bacterial cells. (author)

Aging in a Relativistic Biological Space-Time

Directory of Open Access Journals (Sweden)

Davide Maestrini

2018-05-01

Full Text Available Here we present a theoretical and mathematical perspective on the process of aging. We extend the concepts of physical space and time to an abstract, mathematically-defined space, which we associate with a concept of “biological space-time” in which biological dynamics may be represented. We hypothesize that biological dynamics, represented as trajectories in biological space-time, may be used to model and study different rates of biological aging. As a consequence of this hypothesis, we show how dilation or contraction of time analogous to relativistic corrections of physical time resulting from accelerated or decelerated biological dynamics may be used to study precipitous or protracted aging. We show specific examples of how these principles may be used to model different rates of aging, with an emphasis on cancer in aging. We discuss how this theory may be tested or falsified, as well as novel concepts and implications of this theory that may improve our interpretation of biological aging.

Remote Sensing Dynamic Monitoring of Biological Invasive Species Based on Adaptive PCNN and Improved C-V Model

Directory of Open Access Journals (Sweden)

PENG Gang

2014-12-01

Full Text Available Biological species invasion problem bring serious damage to the ecosystem, and have become one of the six major enviromental problems that affect the future economic development, also have become one of the hot topic in domestic and foreign scholars. Remote sensing technology has been successfully used in the investigation of coastal zone resources, dynamic monitoring of the resources and environment, and other fields. It will cite a new remote sensing image change detection algorithm based on adaptive pulse coupled neural network (PCNN and improved C-V model, for remote sensing dynamic monitoring of biological species invasion. The experimental results show that the algorithm is effective in the test results of biological species invasions.

BETAview: a digital {beta}-imaging system for dynamic studies of biological phenomena

Energy Technology Data Exchange (ETDEWEB)

Bertolucci, E.; Conti, M.; Mettivier, G.; Montesi, M.C. E-mail: montesi@na.infn.it; Russo, P

2002-02-01

We present a digital autoradiography (DAR) system, named BETAview, based on semiconductor pixel detectors and a single particle counting chip, for quantitative analysis of {beta}-emitting radioactive tracers in biological samples. The system is able to perform a real time monitoring of time-dependent biological phenomena. BETAview could be equipped either with GaAs or with Si semiconductor pixellated detectors. In this paper, we describe the results obtained with an assembly based on a Si detector, 300 {mu}m thick, segmented into 64x64 170 {mu}m size square pixels. The detector is bump-bonded to the low threshold, single particle counting chip named Medipix1, developed by a CERN-based European collaboration. The sensitive area is about 1 cm{sup 2}. Studies of background noise and detection efficiency have been performed. Moreover, time-resolved cellular uptake studies with radiolabelled molecules have been monitored. Specifically, we have followed in vivo and in real time, the [{sup 14}C]L-leucine amino acid uptake by eggs of Octopus vulgaris confirming the preliminary results of a previous paper. This opens the field of biomolecular kynetic studies with this new class of semiconductor DAR systems, whose evolution (using the Medipix2 chip, 256x256 pixels, 55 {mu}m pixel size) is soon to come.

BETAview: a digital β-imaging system for dynamic studies of biological phenomena

International Nuclear Information System (INIS)

Bertolucci, E.; Conti, M.; Mettivier, G.; Montesi, M.C.; Russo, P.

2002-01-01

We present a digital autoradiography (DAR) system, named BETAview, based on semiconductor pixel detectors and a single particle counting chip, for quantitative analysis of β-emitting radioactive tracers in biological samples. The system is able to perform a real time monitoring of time-dependent biological phenomena. BETAview could be equipped either with GaAs or with Si semiconductor pixellated detectors. In this paper, we describe the results obtained with an assembly based on a Si detector, 300 μm thick, segmented into 64x64 170 μm size square pixels. The detector is bump-bonded to the low threshold, single particle counting chip named Medipix1, developed by a CERN-based European collaboration. The sensitive area is about 1 cm 2 . Studies of background noise and detection efficiency have been performed. Moreover, time-resolved cellular uptake studies with radiolabelled molecules have been monitored. Specifically, we have followed in vivo and in real time, the [ 14 C]L-leucine amino acid uptake by eggs of Octopus vulgaris confirming the preliminary results of a previous paper. This opens the field of biomolecular kynetic studies with this new class of semiconductor DAR systems, whose evolution (using the Medipix2 chip, 256x256 pixels, 55 μm pixel size) is soon to come

Interferometric scattering (iSCAT) microscopy: studies of biological membrane dynamics

Science.gov (United States)

Reina, Francesco; Galiani, Silvia; Shrestha, Dilip; Sezgin, Erdinc; Lagerholm, B. Christoffer; Cole, Daniel; Kukura, Philipp; Eggeling, Christian

2018-02-01

The study of the organization and dynamics of molecules in model and cellular membranes is an important topic in contemporary biophysics. Imaging and single particle tracking in this particular field, however, proves particularly demanding, as it requires simultaneously high spatio-temporal resolution and high signal-to-noise ratios. A remedy to this challenge might be Interferometric Scattering (iSCAT) microscopy, due to its fast sampling rates, label-free imaging capabilities and, most importantly, tuneable signal level output. Here we report our recent advances in the imaging and molecular tracking on phase-separated model membrane systems and live-cell membranes using this technique.

Oscillation and stability of delay models in biology

CERN Document Server

Agarwal, Ravi P; Saker, Samir H

2014-01-01

Environmental variation plays an important role in many biological and ecological dynamical systems. This monograph focuses on the study of oscillation and the stability of delay models occurring in biology. The book presents recent research results on the qualitative behavior of mathematical models under different physical and environmental conditions, covering dynamics including the distribution and consumption of food. Researchers in the fields of mathematical modeling, mathematical biology, and population dynamics will be particularly interested in this material.

Negotiating the dynamics of uncomfortable knowledge: The case of dual use and synthetic biology

Science.gov (United States)

Marris, Claire; Jefferson, Catherine; Lentzos, Filippa

2014-01-01

Institutions need to ignore some knowledge in order to function. This is “uncomfortable knowledge” because it undermines the ability of those institutions to pursue their goals (Rayner, 2012). We identify three bodies of knowledge that are relevant to understandings of the dual use threat posed by synthetic biology but are excluded from related policy discussions. We demonstrate how these “unknown knowns” constitute uncomfortable knowledge because they disrupt the simplified worldview that underpins contemporary discourse on the potential misuse of synthetic biology by malign actors. We describe how these inconvenient truths have been systematically ignored and argue that this is because they are perceived as a threat by organisations involved in the promotion of synthetic biology as well as by those involved in managing biosecurity risks. This has led to a situation where concerns about the biosecurity threat posed by synthetic biology are not only exaggerated, but are, more importantly, misplaced. This, in turn, means that related policies are misdirected and unlikely to have much impact. We focus on the dynamics of discussions about synthetic biology and dual use to demonstrate how the same “knowns” that are denied or dismissed as “unknown knowns” in certain circumstances are sometimes mobilised as “known knowns” by the same category of actors in a different context, when this serves to sustain the goals of the individuals and institutions involved. Based on our own experience, we argue that negotiating the dynamics of uncomfortable knowledge is a difficult, but necessary, component of meaningful transdisciplinary collaborations. PMID:25484910

Structural Studies of Biological Solids Using NMR

Science.gov (United States)

Ramamoorthy, Ayyalusamy

2011-03-01

High-resolution structure and dynamics of biological molecules are important in understanding their function. While studies have been successful in solving the structures of water-soluble biomolecules, it has been proven difficult to determine the structures of membrane proteins and fibril systems. Recent studies have shown that solid-state NMR is a promising technique and could be highly valuable in studying such non-crystalline and non-soluble biosystems. I will present strategies to study the structures of such challenging systems and also about the applications of solid-state NMR to study the modes of membrane-peptide interactions for a better assessment of the prospects of antimicrobial peptides as substitutes to antibiotics in the control of human disease. Our studies on the mechanism of membrane disruption by LL-37 (a human antimicrobial peptide), analogs of the naturally occurring antimicrobial peptide magainin2 extracted from the skin of the African frog Xenopus Laevis, and pardaxin will be presented. Solid-state NMR experiments were used to determine the secondary structure, dynamics and topology of these peptides in lipid bilayers. Similarities and difference in the cell-lysing mechanism, and their dependence on the membrane composition, of these peptides will be discussed. Atomic-level resolution NMR structures of amyloidogenic proteins revealing the misfolding pathway and early intermediates that play key roles in amyloid toxicity will also be presented.

Dynamic light scattering with applications to chemistry, biology, and physics

CERN Document Server

Berne, Bruce J

2000-01-01

Lasers play an increasingly important role in a variety of detection techniques, making inelastic light scattering a tool of growing value in the investigation of dynamic and structural problems in chemistry, biology, and physics. Until the initial publication of this work, however, no monograph treated the principles behind current developments in the field.This volume presents a comprehensive introduction to the principles underlying laser light scattering, focusing on the time dependence of fluctuations in fluid systems; it also serves as an introduction to the theory of time correlation f

A spatial-dynamic value transfer model of economic losses from a biological invasion

Science.gov (United States)

Thomas P. Holmes; Andrew M. Liebhold; Kent F. Kovacs; Betsy. Von Holle

2010-01-01

Rigorous assessments of the economic impacts of introduced species at broad spatial scales are required to provide credible information to policy makers. We propose that economic models of aggregate damages induced by biological invasions need to link microeconomic analyses of site-specific economic damages with spatial-dynamic models of value change associated with...

Parallel computing and molecular dynamics of biological membranes

International Nuclear Information System (INIS)

La Penna, G.; Letardi, S.; Minicozzi, V.; Morante, S.; Rossi, G.C.; Salina, G.

1998-01-01

In this talk I discuss the general question of the portability of molecular dynamics codes for diffusive systems on parallel computers of the APE family. The intrinsic single precision of the today available platforms does not seem to affect the numerical accuracy of the simulations, while the absence of integer addressing from CPU to individual nodes puts strong constraints on possible programming strategies. Liquids can be satisfactorily simulated using the ''systolic'' method. For more complex systems, like the biological ones at which we are ultimately interested in, the ''domain decomposition'' approach is best suited to beat the quadratic growth of the inter-molecular computational time with the number of atoms of the system. The promising perspectives of using this strategy for extensive simulations of lipid bilayers are briefly reviewed. (orig.)

Network Analyses in Systems Biology: New Strategies for Dealing with Biological Complexity

DEFF Research Database (Denmark)

Green, Sara; Serban, Maria; Scholl, Raphael

2018-01-01

of biological networks using tools from graph theory to the application of dynamical systems theory to understand the behavior of complex biological systems. We show how network approaches support and extend traditional mechanistic strategies but also offer novel strategies for dealing with biological...... strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from the investigation of organizational properties...

Static and dynamic light scattering by red blood cells: A numerical study.

Science.gov (United States)

Mauer, Johannes; Peltomäki, Matti; Poblete, Simón; Gompper, Gerhard; Fedosov, Dmitry A

2017-01-01

Light scattering is a well-established experimental technique, which gains more and more popularity in the biological field because it offers the means for non-invasive imaging and detection. However, the interpretation of light-scattering signals remains challenging due to the complexity of most biological systems. Here, we investigate static and dynamic scattering properties of red blood cells (RBCs) using two mesoscopic hydrodynamics simulation methods-multi-particle collision dynamics and dissipative particle dynamics. Light scattering is studied for various membrane shear elasticities, bending rigidities, and RBC shapes (e.g., biconcave and stomatocyte). Simulation results from the two simulation methods show good agreement, and demonstrate that the static light scattering of a diffusing RBC is not very sensitive to the changes in membrane properties and moderate alterations in cell shapes. We also compute dynamic light scattering of a diffusing RBC, from which dynamic properties of RBCs such as diffusion coefficients can be accessed. In contrast to static light scattering, the dynamic measurements can be employed to differentiate between the biconcave and stomatocytic RBC shapes and generally allow the differentiation based on the membrane properties. Our simulation results can be used for better understanding of light scattering by RBCs and the development of new non-invasive methods for blood-flow monitoring.

Structural biology by NMR: structure, dynamics, and interactions.

Directory of Open Access Journals (Sweden)

Phineus R L Markwick

2008-09-01

Full Text Available The function of bio-macromolecules is determined by both their 3D structure and conformational dynamics. These molecules are inherently flexible systems displaying a broad range of dynamics on time-scales from picoseconds to seconds. Nuclear Magnetic Resonance (NMR spectroscopy has emerged as the method of choice for studying both protein structure and dynamics in solution. Typically, NMR experiments are sensitive both to structural features and to dynamics, and hence the measured data contain information on both. Despite major progress in both experimental approaches and computational methods, obtaining a consistent view of structure and dynamics from experimental NMR data remains a challenge. Molecular dynamics simulations have emerged as an indispensable tool in the analysis of NMR data.

Mathematical methods in biology and neurobiology

CERN Document Server

Jost, Jürgen

2014-01-01

Mathematical models can be used to meet many of the challenges and opportunities offered by modern biology. The description of biological phenomena requires a range of mathematical theories. This is the case particularly for the emerging field of systems biology. Mathematical Methods in Biology and Neurobiology introduces and develops these mathematical structures and methods in a systematic manner. It studies:   • discrete structures and graph theory • stochastic processes • dynamical systems and partial differential equations • optimization and the calculus of variations.   The biological applications range from molecular to evolutionary and ecological levels, for example:   • cellular reaction kinetics and gene regulation • biological pattern formation and chemotaxis • the biophysics and dynamics of neurons • the coding of information in neuronal systems • phylogenetic tree reconstruction • branching processes and population genetics • optimal resource allocation • sexual recombi...

Dynamical "in situ" observation of biological samples using variable pressure scanning electron microscope

Czech Academy of Sciences Publication Activity Database

Neděla, Vilém

2008-01-01

Roč. 126, - (2008), 012046:1-4 ISSN 1742-6588. [Electron Microscopy and Analysis Group Conference 2007 (EMAG 2007). Glasgow, 03.09.2007-07.09.2007] R&D Projects: GA ČR(CZ) GA102/05/0886; GA AV ČR KJB200650602 Institutional research plan: CEZ:AV0Z20650511 Keywords : biological sample * VP-SEM * dynamical experiments Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering

Network Reconstruction of Dynamic Biological Systems

OpenAIRE

Asadi, Behrang

2013-01-01

Inference of network topology from experimental data is a central endeavor in biology, since knowledge of the underlying signaling mechanisms a requirement for understanding biological phenomena. As one of the most important tools in bioinformatics area, development of methods to reconstruct biological networks has attracted remarkable attention in the current decade. Integration of different data types can lead to remarkable improvements in our ability to identify the connectivity of differe...

Effects of N-glycosylation on protein conformation and dynamics: Protein Data Bank analysis and molecular dynamics simulation study.

Science.gov (United States)

Lee, Hui Sun; Qi, Yifei; Im, Wonpil

2015-03-09

N-linked glycosylation is one of the most important, chemically complex, and ubiquitous post-translational modifications in all eukaryotes. The N-glycans that are covalently linked to proteins are involved in numerous biological processes. There is considerable interest in developments of general approaches to predict the structural consequences of site-specific glycosylation and to understand how these effects can be exploited in protein design with advantageous properties. In this study, the impacts of N-glycans on protein structure and dynamics are systematically investigated using an integrated computational approach of the Protein Data Bank structure analysis and atomistic molecular dynamics simulations of glycosylated and deglycosylated proteins. Our study reveals that N-glycosylation does not induce significant changes in protein structure, but decreases protein dynamics, likely leading to an increase in protein stability. Overall, these results suggest not only a common role of glycosylation in proteins, but also a need for certain proteins to be properly glycosylated to gain their intrinsic dynamic properties.

Integrating atomistic molecular dynamics simulations, experiments and network analysis to study protein dynamics: strength in unity

Directory of Open Access Journals (Sweden)

Elena ePapaleo

2015-05-01

Full Text Available In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations.

Informing biological design by integration of systems and synthetic biology.

Science.gov (United States)

Smolke, Christina D; Silver, Pamela A

2011-03-18

Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields. Copyright © 2011 Elsevier Inc. All rights reserved.

Quantum Information Biology: From Theory of Open Quantum Systems to Adaptive Dynamics

Science.gov (United States)

Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

This chapter reviews quantum(-like) information biology (QIB). Here biology is treated widely as even covering cognition and its derivatives: psychology and decision making, sociology, and behavioral economics and finances. QIB provides an integrative description of information processing by bio-systems at all scales of life: from proteins and cells to cognition, ecological and social systems. Mathematically QIB is based on the theory of adaptive quantum systems (which covers also open quantum systems). Ideologically QIB is based on the quantum-like (QL) paradigm: complex bio-systems process information in accordance with the laws of quantum information and probability. This paradigm is supported by plenty of statistical bio-data collected at all bio-scales. QIB re ects the two fundamental principles: a) adaptivity; and, b) openness (bio-systems are fundamentally open). In addition, quantum adaptive dynamics provides the most generally possible mathematical representation of these principles.

Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering.

Science.gov (United States)

He, Fei; Murabito, Ettore; Westerhoff, Hans V

2016-04-01

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways. © 2016 The Author(s).

On the structural affinity of macromolecules with different biological properties: Molecular dynamics simulations of a series of TEM-1 mutants

Energy Technology Data Exchange (ETDEWEB)

Giampaolo, Alessia Di [Dipartimento di Scienze Fisiche e Chimiche, Universita’ degli Studi di l’Aquila, Via Vetoio snc, 67100 Coppito (AQ) (Italy); Mazza, Fernando [Department of Health Sciences, Univ. of L’Aquila, 67010 L’Aquila (Italy); Daidone, Isabella [Dipartimento di Scienze Fisiche e Chimiche, Universita’ degli Studi di l’Aquila, Via Vetoio snc, 67100 Coppito (AQ) (Italy); Amicosante, Gianfranco; Perilli, Mariagrazia [Dipartimento di Scienze Cliniche Applicate e Biotecnologiche, Università degli Studi di l’Aquila, Via Vetoio snc, 67100 Coppito (AQ) (Italy); Aschi, Massimiliano, E-mail: massimiliano.aschi@univaq.it [Dipartimento di Scienze Fisiche e Chimiche, Universita’ degli Studi di l’Aquila, Via Vetoio snc, 67100 Coppito (AQ) (Italy)

2013-07-12

Highlights: •We have performed molecular dynamics simulations of TEM-1 mutants. •Mutations effects on the mechanical properties are considered. •Mutants do not significantly alter the average enzymes structure. •Mutants produce sharp alterations in enzyme conformational repertoire. •Mutants also produce changes in the active site volume. -- Abstract: Molecular Dynamics simulations have been carried out in order to provide a molecular rationalization of the biological and thermodynamic differences observed for a class of TEM β-lactamases. In particular we have considered the TEM-1(wt), the single point mutants TEM-40 and TEM-19 representative of IRT and ESBL classes respectively, and TEM-1 mutant M182T, TEM-32 and TEM-20 which differ from the first three for the additional of M182T mutation. Results indicate that most of the thermodynamic, and probably biological behaviour of these systems arise from subtle effects which, starting from the alterations of the local interactions, produce drastic modifications of the conformational space spanned by the enzymes. The present study suggests that systems showing essentially the same secondary and tertiary structure may differentiate their chemical–biological activity essentially (and probably exclusively) on the basis of the thermal fluctuations occurring in their physiological environment.

On the structural affinity of macromolecules with different biological properties: Molecular dynamics simulations of a series of TEM-1 mutants

International Nuclear Information System (INIS)

Giampaolo, Alessia Di; Mazza, Fernando; Daidone, Isabella; Amicosante, Gianfranco; Perilli, Mariagrazia; Aschi, Massimiliano

2013-01-01

Highlights: •We have performed molecular dynamics simulations of TEM-1 mutants. •Mutations effects on the mechanical properties are considered. •Mutants do not significantly alter the average enzymes structure. •Mutants produce sharp alterations in enzyme conformational repertoire. •Mutants also produce changes in the active site volume. -- Abstract: Molecular Dynamics simulations have been carried out in order to provide a molecular rationalization of the biological and thermodynamic differences observed for a class of TEM β-lactamases. In particular we have considered the TEM-1(wt), the single point mutants TEM-40 and TEM-19 representative of IRT and ESBL classes respectively, and TEM-1 mutant M182T, TEM-32 and TEM-20 which differ from the first three for the additional of M182T mutation. Results indicate that most of the thermodynamic, and probably biological behaviour of these systems arise from subtle effects which, starting from the alterations of the local interactions, produce drastic modifications of the conformational space spanned by the enzymes. The present study suggests that systems showing essentially the same secondary and tertiary structure may differentiate their chemical–biological activity essentially (and probably exclusively) on the basis of the thermal fluctuations occurring in their physiological environment

Nonlinear dynamics new directions models and applications

CERN Document Server

Ugalde, Edgardo

2015-01-01

This book, along with its companion volume, Nonlinear Dynamics New Directions: Theoretical Aspects, covers topics ranging from fractal analysis to very specific applications of the theory of dynamical systems to biology. This second volume contains mostly new applications of the theory of dynamical systems to both engineering and biology. The first volume is devoted to fundamental aspects and includes a number of important new contributions as well as some review articles that emphasize new development prospects. The topics addressed in the two volumes include a rigorous treatment of fluctuations in dynamical systems, topics in fractal analysis, studies of the transient dynamics in biological networks, synchronization in lasers, and control of chaotic systems, among others. This book also: ·         Develops applications of nonlinear dynamics on a diversity of topics such as patterns of synchrony in neuronal networks, laser synchronization, control of chaotic systems, and the study of transient dynam...

Host-parasitoid dynamics and the success of biological control when parasitoids are prone to allee effects.

Directory of Open Access Journals (Sweden)

Anaïs Bompard

Full Text Available In sexual organisms, low population density can result in mating failures and subsequently yields a low population growth rate and high chance of extinction. For species that are in tight interaction, as in host-parasitoid systems, population dynamics are primarily constrained by demographic interdependences, so that mating failures may have much more intricate consequences. Our main objective is to study the demographic consequences of parasitoid mating failures at low density and its consequences on the success of biological control. For this, we developed a deterministic host-parasitoid model with a mate-finding Allee effect, allowing to tackle interactions between the Allee effect and key determinants of host-parasitoid demography such as the distribution of parasitoid attacks and host competition. Our study shows that parasitoid mating failures at low density result in an extinction threshold and increase the domain of parasitoid deterministic extinction. When proned to mate finding difficulties, parasitoids with cyclic dynamics or low searching efficiency go extinct; parasitoids with high searching efficiency may either persist or go extinct, depending on host intraspecific competition. We show that parasitoids suitable as biocontrol agents for their ability to reduce host populations are particularly likely to suffer from mate-finding Allee effects. This study highlights novel perspectives for understanding of the dynamics observed in natural host-parasitoid systems and improving the success of parasitoid introductions.

Aquatic biology studies

International Nuclear Information System (INIS)

Anon.

1976-01-01

Aquatic biology studies focused on studying the hydrothermal effects of Par Pond reservoir on periphyton, plankton, zooplankton, macrophytes, human pathogens, and microbial activity; the variability between the artificial streams of the Flowing Streams Laboratory and Upper Three Runs Creek; and the bacterial production of methane in Savannah River Plant aquatic systems

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

DEFF Research Database (Denmark)

Papaleo, Elena

2015-01-01

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

Novel nuclear magnetic resonance techniques for studying biological molecules

International Nuclear Information System (INIS)

Laws, David D.

2000-01-01

Over the fifty-five year history of Nuclear Magnetic Resonance (NMR), considerable progress has been made in the development of techniques for studying the structure, function, and dynamics of biological molecules. The majority of this research has involved the development of multi-dimensional NMR experiments for studying molecules in solution, although in recent years a number of groups have begun to explore NMR methods for studying biological systems in the solid-state. Despite this new effort, a need still exists for the development of techniques that improve sensitivity, maximize information, and take advantage of all the NMR interactions available in biological molecules. In this dissertation, a variety of novel NMR techniques for studying biomolecules are discussed. A method for determining backbone (φ/ψ) dihedral angles by comparing experimentally determined 13 C a , chemical-shift anisotropies with theoretical calculations is presented, along with a brief description of the theory behind chemical-shift computation in proteins and peptides. The utility of the Spin-Polarization Induced Nuclear Overhauser Effect (SPINOE) to selectively enhance NMR signals in solution is examined in a variety of systems, as are methods for extracting structural information from cross-relaxation rates that can be measured in SPINOE experiments. Techniques for the production of supercritical and liquid laser-polarized xenon are discussed, as well as the prospects for using optically pumped xenon as a polarizing solvent. In addition, a detailed study of the structure of PrP 89-143 is presented. PrP 89-143 is a 54 residue fragment of the prion proteins which, upon mutation and aggregation, can induce prion diseases in transgenic mice. Whereas the structure of the wild-type PrP 89-143 is a generally unstructured mixture of α-helical and β-sheet conformers in the solid state, the aggregates formed from the PrP 89-143 mutants appear to be mostly β-sheet.

Decoding network dynamics in cancer

DEFF Research Database (Denmark)

Linding, Rune

2014-01-01

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

Feasibility study for a recirculating linac-based facility for femtosecond dynamics

CERN Document Server

Corlett, J N; Barry, W; Byrd, J M; De Santis, S; Doolittle, L; Fawley, W; Green, M A; Hartman, N; Heimann, P A; Kairan, D; Kujawski, E; Li, D; Lidia, S M; Luft, P; McClure, R; Parmigiani, F; Petroff, Y; Pirkl, Werner; Placidi, Massimo; Ratti, A; Reavill, D; Reichel, I; Rimmer, R A; Robinson, K E; Sannibale, F; Schönlein, R W; Staples, J; Tanabe, J; Truchlikova, D; Wan, W; Wang, S; Wells, R; Wolski, A; Zholents, A

2002-01-01

LBNL is pursuing design studies and the scientific program for a facility of the production of x-ray pulses with ultra-short time duration, for application in dynamical studies of processes in physics, biology, and chemistry. The proposed x-ray facility has the short x-ray pulse length (approx 60 fs FWHM) necessary to study very fast dynamics, high flux (up to approximately 10E11 photons/sec/0.1 percentBW) to study weakly scattering systems, and tuneability over 1-12 keV photon energy. The hard x-ray photon production section of the machine accommodates seven 2-m long undulators. Design studies for longer wavelength sources, using high-gain harmonic generation, are in progress. The x-ray pulse repetition rate of 10 kHz is matched to studies of dynamical processes (initiated by ultra-short laser pulses) that typically have a long recovery time or are not generally cyclic or reversible and need time to allow relaxation, replacement, or flow of the sample. The technique for producing ultra-short x-ray pulses use...

Biological sensing and control of emission dynamics of quantum dot bioconjugates using arrays of long metallic nanorods.

Science.gov (United States)

Sadeghi, Seyed M; Gutha, Rithvik R; Wing, Waylin J; Sharp, Christina; Capps, Lucas; Mao, Chuanbin

2017-01-01

We study biological sensing using plasmonic and photonic-plasmonic resonances of arrays of ultralong metallic nanorods and analyze the impact of these resonances on emission dynamics of quantum dot bioconjugates. We demonstrate that the LSPRs and plasmonic lattice modes of such array can be used to detect a single self-assembled monolayer of alkanethiol at the visible (550 nm) and near infrared (770 nm) range with well resolved shifts. We study adsorption of streptavidin-quantum dot conjugates to this monolayer, demonstrating that formation of nearly two dimensional arrays of quantum dots with limited emission blinking can lead to extra well-defined wavelength shifts in these modes. Using spectrally-resolved lifetime measurements we study the emission dynamics of such quantum dot bioconjugates within their monodispersed size distribution. We show that, despite their close vicinity to the nanorods, the rate of energy transfer from these quantum dots to nanorods is rather weak, while the plasmon field enhancement can be strong. Our results reveal that the nanorods present a strongly wavelength or size-dependent non-radiative decay channel to the quantum dot bioconjugates.

Ultrafast relaxation dynamics of a biologically relevant probe dansyl at the micellar surface.

Science.gov (United States)

Sarkar, Rupa; Ghosh, Manoranjan; Pal, Samir Kumar

2005-02-01

We report picosecond-resolved measurement of the fluorescence of a well-known biologically relevant probe, dansyl chromophore at the surface of a cationic micelle (cetyltrimethylammonium bromide, CTAB). The dansyl chromophore has environmentally sensitive fluorescence quantum yields and emission maxima, along with large Stokes shift. In order to study the solvation dynamics of the micellar environment, we measured the fluorescence of dansyl chromophore attached to the micellar surface. The fluorescence transients were observed to decay (with time constant approximately 350 ps) in the blue end and rise with similar timescale in the red end, indicative of solvation dynamics of the environment. The solvation correlation function is measured to decay with time constant 338 ps, which is much slower than that of ordinary bulk water. Time-resolved anisotropy of the dansyl chromophore shows a bi-exponential decay with time constants 413 ps (23%) and 1.3 ns (77%), which is considerably slower than that in free solvents revealing the rigidity of the dansyl-micelle complex. Time-resolved area-normalized emission spectroscopic (TRANES) analysis of the time dependent emission spectra of the dansyl chromophore in the micellar environment shows an isoemissive point at 21066 cm-1. This indicates the fluorescence of the chromophore contains emission from two kinds of excited states namely locally excited state (prior to charge transfer) and charge transfer state. The nature of the solvation dynamics in the micellar environments is therefore explored from the time-resolved anisotropy measurement coupled with the TRANES analysis of the fluorescence transients. The time scale of the solvation is important for the mechanism of molecular recognition.

Workshop on High-Field NMR and Biological Applications

Science.gov (United States)

Scientists at the Pacific Northwest Laboratory have been working toward the establishment of a new Molecular Science Research Center (MSRC). The primary scientific thrust of this new research center is in the areas of theoretical chemistry, chemical dynamics, surface and interfacial science, and studies on the structure and interactions of biological macromolecules. The MSRC will provide important new capabilities for studies on the structure of biological macromolecules. The MSRC program includes several types of advanced spectroscopic techniques for molecular structure analysis, and a theory and modeling laboratory for molecular mechanics/dynamics calculations and graphics. It is the goal to closely integrate experimental and theoretical studies on macromolecular structure, and to join these research efforts with those of the molecular biological programs to provide new insights into the structure/function relationships of biological macromolecules. One of the areas of structural biology on which initial efforts in the MSRC will be focused is the application of high field, 2-D NMR to the study of biological macromolecules. First, there is interest in obtaining 3-D structural information on large proteins and oligonucleotides. Second, one of the primary objectives is to closely link theoretical approaches to molecular structure analysis with the results obtained in experimental research using NMR and other spectroscopies.

Application of magnetic resonance imaging and spectroscopy in studying the biological effects of manufactured nanoparticles

International Nuclear Information System (INIS)

Lei Hao; Wei Li; Liu Maili

2006-01-01

With the rapid development of nanoscience and nanotechnology in recent years, growing research interest and efforts have been directed to study the biological effects of manufactured nanoparticles and substances alike. Despite the fact that significant progress has been made, this is still largely an uncharted field. Any advances in this field would certainly require thorough multi-disciplinary collaboration, in which the expertise and tools in nanoscience/nanotechnoloogy, physics, chemistry and biomedicine have to be combined. Due to their wide range of applications in physics, chemistry and biomedicine, magnetic resonance (MR) imaging and spectroscopy are among the most important and powerful research tools currently in use, mainly because these techniques can be used in situ and noninvasively to acquire dynamic and real-time information in various samples ranging from protein solution to the human brain. In this paper, the application of MR imaging and spectroscopy in studying the biological effects of manufactured nanoparticles is discussed. It is expected that these techniques will play important roles in 1) detecting the presence of nanoparticles in biological tissues and in vivo, 2) studying the interactions between the nanoparticles and biomolecules and 3) investigating the metabonomic aspect of the biological effects of nanoparticles. (authors)

A canonical correlation analysis-based dynamic bayesian network prior to infer gene regulatory networks from multiple types of biological data.

Science.gov (United States)

Baur, Brittany; Bozdag, Serdar

2015-04-01

One of the challenging and important computational problems in systems biology is to infer gene regulatory networks (GRNs) of biological systems. Several methods that exploit gene expression data have been developed to tackle this problem. In this study, we propose the use of copy number and DNA methylation data to infer GRNs. We developed an algorithm that scores regulatory interactions between genes based on canonical correlation analysis. In this algorithm, copy number or DNA methylation variables are treated as potential regulator variables, and expression variables are treated as potential target variables. We first validated that the canonical correlation analysis method is able to infer true interactions in high accuracy. We showed that the use of DNA methylation or copy number datasets leads to improved inference over steady-state expression. Our results also showed that epigenetic and structural information could be used to infer directionality of regulatory interactions. Additional improvements in GRN inference can be gleaned from incorporating the result in an informative prior in a dynamic Bayesian algorithm. This is the first study that incorporates copy number and DNA methylation into an informative prior in dynamic Bayesian framework. By closely examining top-scoring interactions with different sources of epigenetic or structural information, we also identified potential novel regulatory interactions.

Some nonlinear challenges in biology

International Nuclear Information System (INIS)

Mosconi, Francesco; Julou, Thomas; Desprat, Nicolas; Sinha, Deepak Kumar; Allemand, Jean-François; Croquette, Vincent; Bensimon, David

2008-01-01

Driven by a deluge of data, biology is undergoing a transition to a more quantitative science. Making sense of the data, building new models, asking the right questions and designing smart experiments to answer them are becoming ever more relevant. In this endeavour, nonlinear approaches can play a fundamental role. The biochemical reactions that underlie life are very often nonlinear. The functional features exhibited by biological systems at all levels (from the activity of an enzyme to the organization of a colony of ants, via the development of an organism or a functional module like the one responsible for chemotaxis in bacteria) are dynamically robust. They are often unaffected by order of magnitude variations in the dynamical parameters, in the number or concentrations of actors (molecules, cells, organisms) or external inputs (food, temperature, pH, etc). This type of structural robustness is also a common feature of nonlinear systems, exemplified by the fundamental role played by dynamical fixed points and attractors and by the use of generic equations (logistic map, Fisher–Kolmogorov equation, the Stefan problem, etc.) in the study of a plethora of nonlinear phenomena. However, biological systems differ from these examples in two important ways: the intrinsic stochasticity arising from the often very small number of actors and the role played by evolution. On an evolutionary time scale, nothing in biology is frozen. The systems observed today have evolved from solutions adopted in the past and they will have to adapt in response to future conditions. The evolvability of biological system uniquely characterizes them and is central to biology. As the great biologist T Dobzhansky once wrote: 'nothing in biology makes sense except in the light of evolution'. (open problem)

Using chemistry and microfluidics to understand the spatial dynamics of complex biological networks.

Science.gov (United States)

Kastrup, Christian J; Runyon, Matthew K; Lucchetta, Elena M; Price, Jessica M; Ismagilov, Rustem F

2008-04-01

Understanding the spatial dynamics of biochemical networks is both fundamentally important for understanding life at the systems level and also has practical implications for medicine, engineering, biology, and chemistry. Studies at the level of individual reactions provide essential information about the function, interactions, and localization of individual molecular species and reactions in a network. However, analyzing the spatial dynamics of complex biochemical networks at this level is difficult. Biochemical networks are nonequilibrium systems containing dozens to hundreds of reactions with nonlinear and time-dependent interactions, and these interactions are influenced by diffusion, flow, and the relative values of state-dependent kinetic parameters. To achieve an overall understanding of the spatial dynamics of a network and the global mechanisms that drive its function, networks must be analyzed as a whole, where all of the components and influential parameters of a network are simultaneously considered. Here, we describe chemical concepts and microfluidic tools developed for network-level investigations of the spatial dynamics of these networks. Modular approaches can be used to simplify these networks by separating them into modules, and simple experimental or computational models can be created by replacing each module with a single reaction. Microfluidics can be used to implement these models as well as to analyze and perturb the complex network itself with spatial control on the micrometer scale. We also describe the application of these network-level approaches to elucidate the mechanisms governing the spatial dynamics of two networkshemostasis (blood clotting) and early patterning of the Drosophila embryo. To investigate the dynamics of the complex network of hemostasis, we simplified the network by using a modular mechanism and created a chemical model based on this mechanism by using microfluidics. Then, we used the mechanism and the model to

Nonlinear dynamics new directions theoretical aspects

CERN Document Server

Ugalde, Edgardo

2015-01-01

This book, along with its companion volume, Nonlinear Dynamics New Directions: Models and Applications, covers topics ranging from fractal analysis to very specific applications of the theory of dynamical systems to biology. This first volume is devoted to fundamental aspects and includes a number of important new contributions as well as some review articles that emphasize new development prospects. The second volume contains mostly new applications of the theory of dynamical systems to both engineering and biology. The topics addressed in the two volumes include a rigorous treatment of fluctuations in dynamical systems, topics in fractal analysis, studies of the transient dynamics in biological networks, synchronization in lasers, and control of chaotic systems, among others. This book also: ·         Presents a rigorous treatment of fluctuations in dynamical systems and explores a range of topics in fractal analysis, among other fundamental topics ·         Features recent developments on...

Novel recurrent neural network for modelling biological networks: oscillatory p53 interaction dynamics.

Science.gov (United States)

Ling, Hong; Samarasinghe, Sandhya; Kulasiri, Don

2013-12-01

Understanding the control of cellular networks consisting of gene and protein interactions and their emergent properties is a central activity of Systems Biology research. For this, continuous, discrete, hybrid, and stochastic methods have been proposed. Currently, the most common approach to modelling accurate temporal dynamics of networks is ordinary differential equations (ODE). However, critical limitations of ODE models are difficulty in kinetic parameter estimation and numerical solution of a large number of equations, making them more suited to smaller systems. In this article, we introduce a novel recurrent artificial neural network (RNN) that addresses above limitations and produces a continuous model that easily estimates parameters from data, can handle a large number of molecular interactions and quantifies temporal dynamics and emergent systems properties. This RNN is based on a system of ODEs representing molecular interactions in a signalling network. Each neuron represents concentration change of one molecule represented by an ODE. Weights of the RNN correspond to kinetic parameters in the system and can be adjusted incrementally during network training. The method is applied to the p53-Mdm2 oscillation system - a crucial component of the DNA damage response pathways activated by a damage signal. Simulation results indicate that the proposed RNN can successfully represent the behaviour of the p53-Mdm2 oscillation system and solve the parameter estimation problem with high accuracy. Furthermore, we presented a modified form of the RNN that estimates parameters and captures systems dynamics from sparse data collected over relatively large time steps. We also investigate the robustness of the p53-Mdm2 system using the trained RNN under various levels of parameter perturbation to gain a greater understanding of the control of the p53-Mdm2 system. Its outcomes on robustness are consistent with the current biological knowledge of this system. As more

Applications of thermal neutron scattering in biology, biochemistry and biophysics

International Nuclear Information System (INIS)

Worcester, D.L.

1977-01-01

Biological applications of thermal neutron scattering have increased rapidly in recent years. The following categories of biological research with thermal neutron scattering are presently identified: crystallography of biological molecules; neutron small-angle scattering of biological molecules in solution (these studies have already included numerous measurements of proteins, lippoproteins, viruses, ribosomal subunits and chromatin subunit particles); neutron small-angle diffraction and scattering from biological membranes and membrane components; and neutron quasielastic and inelastic scattering studies of the dynamic properties of biological molecules and materials. (author)

Evolutionary game theory for physical and biological scientists. I. Training and validating population dynamics equations.

Science.gov (United States)

Liao, David; Tlsty, Thea D

2014-08-06

Failure to understand evolutionary dynamics has been hypothesized as limiting our ability to control biological systems. An increasing awareness of similarities between macroscopic ecosystems and cellular tissues has inspired optimism that game theory will provide insights into the progression and control of cancer. To realize this potential, the ability to compare game theoretic models and experimental measurements of population dynamics should be broadly disseminated. In this tutorial, we present an analysis method that can be used to train parameters in game theoretic dynamics equations, used to validate the resulting equations, and used to make predictions to challenge these equations and to design treatment strategies. The data analysis techniques in this tutorial are adapted from the analysis of reaction kinetics using the method of initial rates taught in undergraduate general chemistry courses. Reliance on computer programming is avoided to encourage the adoption of these methods as routine bench activities.

A Friendly-Biological Reactor SIMulator (BioReSIM for studying biological processes in wastewater treatment processes

Directory of Open Access Journals (Sweden)

Raul Molina

2014-12-01

Full Text Available Biological processes for wastewater treatments are inherently dynamic systems because of the large variations in the influent wastewater flow rate, concentration composition and the adaptive behavior of the involved microorganisms. Moreover, the sludge retention time (SRT is a critical factor to understand the bioreactor performances when changes in the influent or in the operation conditions take place. Since SRT are usually in the range of 10-30 days, the performance of biological reactors needs a long time to be monitored in a regular laboratory demonstration, limiting the knowledge that can be obtained in the experimental lab practice. In order to overcome this lack, mathematical models and computer simulations are useful tools to describe biochemical processes and predict the overall performance of bioreactors under different working operation conditions and variations of the inlet wastewater composition. The mathematical solution of the model could be difficult as numerous biochemical processes can be considered. Additionally, biological reactors description (mass balance, etc. needs models represented by partial or/and ordinary differential equations associated to algebraic expressions, that require complex computational codes to obtain the numerical solutions. Different kind of software for mathematical modeling can be used, from large degree of freedom simulators capable of free models definition (as AQUASIM, to closed predefined model structure programs (as BIOWIN. The first ones usually require long learning curves, whereas the second ones could be excessively rigid for specific wastewater treatment systems. As alternative, we present Biological Reactor SIMulator (BioReSIM, a MATLAB code for the simulation of sequencing batch reactors (SBR and rotating biological contactors (RBC as biological systems of suspended and attached biomass for wastewater treatment, respectively. This BioReSIM allows the evaluation of simple and complex

Studying language change using price equation and Pólya-urn dynamics.

Science.gov (United States)

Gong, Tao; Shuai, Lan; Tamariz, Mónica; Jäger, Gerhard

2012-01-01

Language change takes place primarily via diffusion of linguistic variants in a population of individuals. Identifying selective pressures on this process is important not only to construe and predict changes, but also to inform theories of evolutionary dynamics of socio-cultural factors. In this paper, we advocate the Price equation from evolutionary biology and the Pólya-urn dynamics from contagion studies as efficient ways to discover selective pressures. Using the Price equation to process the simulation results of a computer model that follows the Pólya-urn dynamics, we analyze theoretically a variety of factors that could affect language change, including variant prestige, transmission error, individual influence and preference, and social structure. Among these factors, variant prestige is identified as the sole selective pressure, whereas others help modulate the degree of diffusion only if variant prestige is involved. This multidisciplinary study discerns the primary and complementary roles of linguistic, individual learning, and socio-cultural factors in language change, and offers insight into empirical studies of language change.

Study of biological compartments

International Nuclear Information System (INIS)

Rocha, A.F.G. da

1976-01-01

The several types of biological compartments are studied such as monocompartmental system, one-compartment balanced system irreversible fluxes, two closed compartment system, three compartment systems, catenary systems and mammilary systems [pt

Novel nuclear magnetic resonance techniques for studying biological molecules

Energy Technology Data Exchange (ETDEWEB)

Laws, David Douglas [Univ. of California, Berkeley, CA (United States)

2000-06-01

Over the fifty-five year history of Nuclear Magnetic Resonance (NMR), considerable progress has been made in the development of techniques for studying the structure, function, and dynamics of biological molecules. The majority of this research has involved the development of multi-dimensional NMR experiments for studying molecules in solution, although in recent years a number of groups have begun to explore NMR methods for studying biological systems in the solid-state. Despite this new effort, a need still exists for the development of techniques that improve sensitivity, maximize information, and take advantage of all the NMR interactions available in biological molecules. In this dissertation, a variety of novel NMR techniques for studying biomolecules are discussed. A method for determining backbone (Φ/Ψ) dihedral angles by comparing experimentally determined ¹³C_a, chemical-shift anisotropies with theoretical calculations is presented, along with a brief description of the theory behind chemical-shift computation in proteins and peptides. The utility of the Spin-Polarization Induced Nuclear Overhauser Effect (SPINOE) to selectively enhance NMR signals in solution is examined in a variety of systems, as are methods for extracting structural information from cross-relaxation rates that can be measured in SPINOE experiments. Techniques for the production of supercritical and liquid laser-polarized xenon are discussed, as well as the prospects for using optically pumped xenon as a polarizing solvent. In addition, a detailed study of the structure of PrP 89-143 is presented. PrP 89-143 is a 54 residue fragment of the prion proteins which, upon mutation and aggregation, can induce prion diseases in transgenic mice. Whereas the structure of the wild-type PrP 89-143 is a generally unstructured mixture of α-helical and β-sheet conformers in the solid state, the aggregates formed from the PrP 89-143 mutants appear to be mostly β-sheet.

Inference problems in structural biology

DEFF Research Database (Denmark)

Olsson, Simon

The structure and dynamics of biological molecules are essential for their function. Consequently, a wealth of experimental techniques have been developed to study these features. However, while experiments yield detailed information about geometrical features of molecules, this information is of...

A Non-Homogeneous Dynamic Bayesian Network with Sequentially Coupled Interaction Parameters for Applications in Systems and Synthetic Biology

NARCIS (Netherlands)

Grzegorczyk, Marco; Husmeier, Dirk

2012-01-01

An important and challenging problem in systems biology is the inference of gene regulatory networks from short non-stationary time series of transcriptional profiles. A popular approach that has been widely applied to this end is based on dynamic Bayesian networks (DBNs), although traditional

VISUALIZATION OF BIOLOGICAL TISSUE IMPEDANCE PARAMETERS

Directory of Open Access Journals (Sweden)

V. I. Bankov

2016-01-01

Full Text Available Objective. Investigation the opportunity for measurement of biological tissue impedance to visualize its parameters.Materials and methods. Studies were undertook on the experimental facility, consists of registrating measuring cell, constructed from flat inductors system, formed in oscillatory circuit, herewith investigated biological tissue is the part of this oscillatory circuit. An excitation of oscillatory circuit fulfilled by means of exciter inductor which forms impulse complex modulated electromagnetic field (ICM EMF. The measurement process and visualizations provided by set of certificated instruments: a digital oscillograph AKTAKOM ADS-2221MV, a digital generator АКТАКОМ AWG-4150 (both with software and a gauge RLC E7-22. Comparative dynamic studies of fixed volume and weight pig’s blood, adipose tissue, muscular tissue impedance were conducted by contact versus contactless methods. Contactless method in contrast to contact method gives opportunity to obtain the real morphological visualization of biological tissue irrespective of their nature.Results. Comparison of contact and contactless methods of impedance measurement shows that the inductance to capacitance ratio X(L / X(C was equal: 17 – for muscular tissue, 4 – for blood, 1 – for adipose tissue. It demonstrates the technical correspondence of both impedance registration methods. If propose the base relevance of X (L and X (C parameters for biological tissue impedance so contactless measurement method for sure shows insulating properties of adipose tissue and high conductivity for blood and muscular tissue in fixed volume-weight parameters. Registration of biological tissue impedance complex parameters by contactless method with the help of induced ICM EMF in fixed volume of biological tissue uncovers the most important informative volumes to characterize morphofunctional condition of biological tissue namely X (L / X (C.Conclusion. Contactless method of biological

The Dominance Behavioral System and Psychopathology: Evidence from Self-Report, Observational, and Biological Studies

Science.gov (United States)

Johnson, Sheri L.; Leedom, Liane J.; Muhtadie, Luma

2012-01-01

The dominance behavioral system (DBS) can be conceptualized as a biologically-based system which guides dominance motivation, dominant and subordinate behavior, and responsivity to perceptions of power and subordination. A growing body of research suggests that problems with the DBS are evident across a broad range of psychopathologies. We begin by describing psychological, social, and biological correlates of the dominance behavioral system (DBS). Extensive research suggests that externalizing disorders, mania-proneness, and narcissistic traits are related to heightened dominance motivation and behaviors. Mania and narcissistic traits also appear related to inflated self-perceptions of power. Anxiety and depression are related to subordination and submissiveness, as well as a desire to avoid subordination. Models of the DBS have received support from research with humans and animals; from self-report, observational, and biological methods; and using naturalistic and experimental paradigms. Limitations of available research include the relative lack of longitudinal studies using multiple measures of the DBS and the absence of relevant studies using diagnosed samples to study narcissistic personality disorder and bipolar disorder. We provide suggestions for future research on the DBS and psychopathology, including investigations of whether the DBS can be used to differentiate specific disorder outcomes; the need for more sophisticated biological research; and the value of longitudinal dynamical research. Implications of using the DBS as a tool in clinical assessment and treatment are discussed. PMID:22506751

OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.

Directory of Open Access Journals (Sweden)

C Brandon Ogbunugafor

Full Text Available Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL. Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features.

OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.

Science.gov (United States)

Ogbunugafor, C Brandon; Robinson, Sean P

2016-01-01

Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs) by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL.) Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative) abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features.

Tritium biological effects and perspective of the biological study

International Nuclear Information System (INIS)

Komatsu, Kenshi

1998-01-01

Since tritium is an emitter of weak β-rays (5.7keV) and is able to bind to DNA, i.e., the most important genome component, the biological effects should be expected to be more profound than that of X-rays and γ-rays. When carcinogenesis, genetical effects and the detriments for fetus and embryo were used as a biological endpoint, most of tritium RBE (relative biological effectiveness) ranged from 1 to 2. The tritium risk in man could be calculated from these RBEs and γ-ray risk for human exposure, which are obtained mainly from the data on Atomic Bomb survivors. However, the exposure modality from environmental tritium should be a chronic irradiation with ultra low dose rate or a fractionated irradiation. We must estimate the tritium effect in man based on biological experiments alone, due to lack of such epidemiological data. Low dose rate experiment should be always accompanied by the statistical problem of data, since their biological effects are fairy low, and they should involve a possible repair system, such as adaptive response (or hormesis effect) and 'Kada effect' observed in bacteria. Here we discuss future works for the tritium assessment in man, such as (1) developing a high radiation sensitive assay system with rodent hybrid cells containing a single human chromosome and also (2) study on mammal DNA repair at molecular levels using a radiosensitive hereditary disease, Nijmegen Breakage Syndrome. (author)

Fusion of biological membranes

Indian Academy of Sciences (India)

Home; Journals; Pramana – Journal of Physics; Volume 64; Issue 6. Fusion of biological membranes. K Katsov M Müller M Schick. Invited Talks:- Topic 11. Biologically motivated problems (protein-folding models, dynamics at the scale of the cell; biological networks, evolution models, etc.) Volume 64 Issue 6 June 2005 pp ...

Speckle dynamics under ergodicity breaking

Science.gov (United States)

Sdobnov, Anton; Bykov, Alexander; Molodij, Guillaume; Kalchenko, Vyacheslav; Jarvinen, Topias; Popov, Alexey; Kordas, Krisztian; Meglinski, Igor

2018-04-01

Laser speckle contrast imaging (LSCI) is a well-known and versatile approach for the non-invasive visualization of flows and microcirculation localized in turbid scattering media, including biological tissues. In most conventional implementations of LSCI the ergodic regime is typically assumed valid. However, most composite turbid scattering media, especially biological tissues, are non-ergodic, containing a mixture of dynamic and static centers of light scattering. In the current study, we examined the speckle contrast in different dynamic conditions with the aim of assessing limitations in the quantitative interpretation of speckle contrast images. Based on a simple phenomenological approach, we introduced a coefficient of speckle dynamics to quantitatively assess the ratio of the dynamic part of a scattering medium to the static one. The introduced coefficient allows one to distinguish real changes in motion from the mere appearance of static components in the field of view. As examples of systems with static/dynamic transitions, thawing and heating of Intralipid samples were studied by the LSCI approach.

Concise Review: Stem Cell Population Biology: Insights from Hematopoiesis.

Science.gov (United States)

MacLean, Adam L; Lo Celso, Cristina; Stumpf, Michael P H

2017-01-01

Stem cells are fundamental to human life and offer great therapeutic potential, yet their biology remains incompletely-or in cases even poorly-understood. The field of stem cell biology has grown substantially in recent years due to a combination of experimental and theoretical contributions: the experimental branch of this work provides data in an ever-increasing number of dimensions, while the theoretical branch seeks to determine suitable models of the fundamental stem cell processes that these data describe. The application of population dynamics to biology is amongst the oldest applications of mathematics to biology, and the population dynamics perspective continues to offer much today. Here we describe the impact that such a perspective has made in the field of stem cell biology. Using hematopoietic stem cells as our model system, we discuss the approaches that have been used to study their key properties, such as capacity for self-renewal, differentiation, and cell fate lineage choice. We will also discuss the relevance of population dynamics in models of stem cells and cancer, where competition naturally emerges as an influential factor on the temporal evolution of cell populations. Stem Cells 2017;35:80-88. © 2016 AlphaMed Press.

Studying cell biology in the skin.

Science.gov (United States)

Morrow, Angel; Lechler, Terry

2015-11-15

Advances in cell biology have often been driven by studies in diverse organisms and cell types. Although there are technical reasons for why different cell types are used, there are also important physiological reasons. For example, ultrastructural studies of vesicle transport were aided by the use of professional secretory cell types. The use of tissues/primary cells has the advantage not only of using cells that are adapted to the use of certain cell biological machinery, but also of highlighting the physiological roles of this machinery. Here we discuss advantages of the skin as a model system. We discuss both advances in cell biology that used the skin as a driving force and future prospects for use of the skin to understand basic cell biology. A unique combination of characteristics and tools makes the skin a useful in vivo model system for many cell biologists. © 2015 Morrow and Lechler. 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).

Synthetic biological networks

International Nuclear Information System (INIS)

Archer, Eric; Süel, Gürol M

2013-01-01

Despite their obvious relationship and overlap, the field of physics is blessed with many insightful laws, while such laws are sadly absent in biology. Here we aim to discuss how the rise of a more recent field known as synthetic biology may allow us to more directly test hypotheses regarding the possible design principles of natural biological networks and systems. In particular, this review focuses on synthetic gene regulatory networks engineered to perform specific functions or exhibit particular dynamic behaviors. Advances in synthetic biology may set the stage to uncover the relationship of potential biological principles to those developed in physics. (review article)

Dynamics of biopolymers on nanomaterials studied by quasielastic neutron scattering and MD simulations

Science.gov (United States)

Dhindsa, Gurpreet K.

Neutron scattering has been proved to be a powerful tool to study the dynamics of biological systems under various conditions. This thesis intends to utilize neutron scattering techniques, combining with MD simulations, to develop fundamental understanding of several biologically interesting systems. Our systems include a drug delivery system containing Nanodiamonds with nucleic acid (RNA), and two specific model proteins, beta-Casein and Inorganic Pyrophosphatase (IPPase). RNA and nanodiamond (ND) both are suitable for drug-delivery applications in nano-biotechnology. The architecturally flexible RNA with catalytic functionality forms nanocomposites that can treat life-threatening diseases. The non-toxic ND has excellent mechanical and optical properties and functionalizable high surface area, and thus actively considered for biomedical applications. In this thesis, we utilized two tools, quasielastic neutron scattering (QENS) and Molecular Dynamics Simulations to probe the effect of ND on RNA dynamics. Our work provides fundamental understanding of how hydrated RNA motions are affected in the RNA-ND nanocomposites. From the experimental and Molecular Dynamics Simulation (MD), we found that hydrated RNA motion is faster on ND surface than a freestanding one. MD Simulation results showed that the failure of Stokes Einstein relation results the presence of dynamic heterogeneities in the biomacromolecules. Radial pair distribution function from MD Simulation confirmed that the hydrophilic nature of ND attracts more water than RNA results the de-confinement of RNA on ND. Therefore, RNA exhibits faster motion in the presence of ND than freestanding RNA. In the second project, we studied the dynamics of a natively disordered protein beta-Casein which lacks secondary structures. In this study, the temperature and hydration effects on the dynamics of beta-Casein are explored by Quasielastic Neutron Scattering (QENS). We investigated the mean square displacement (MSD) of

Biological methanation of hydrogen within biogas plants: A model-based feasibility study

International Nuclear Information System (INIS)

Bensmann, A.; Hanke-Rauschenbach, R.; Heyer, R.; Kohrs, F.; Benndorf, D.; Reichl, U.; Sundmacher, K.

2014-01-01

Highlights: • Simulation study about direct methanation of hydrogen within biogas plants. • In stationary operation two limitations, namely biological and transfer limit. • Biological limit at 4m H2 3 /m CO2 3 due to stoichiometry. • Dynamic behaviour shows three qualitatively different step responses. • A simple control scheme to meet the output quality was developed. - Abstract: One option to utilize excess electric energy is its conversion to hydrogen and the subsequent methanation. An alternative to the classical chemical Sabatier process is the biological methanation (methanogenesis) within biogas plants. In conventional biogas plants methane and carbon dioxide is produced. The latter can be directly converted to methane by feeding hydrogen into the reactor, since hydrogenotrophic bacteria are present. In the present contribution, a comprehensive simulation study with respect to stationary operating conditions and disturbances is presented. It reveals two qualitative different limitations, namely a biological limit (appr. at 4m H2 3 /m CO2 3 corresponds to 4.2m H2,STP 3 /m liq 3 /d) as well as a transfer limit. A parameter region for a safe operation was defined. The temporary operation with stationary unfeasible conditions was analysed and thereby three qualitatively different disturbances can be distinguished. In one of these the operation for several days is possible. On the basis of these results, a controller was proposed and tested that meets the demands on the conversion of hydrogen and also prevents the washout of the microbial community due to hydrogen overload

A New Theoretical Approach to Single-Molecule Fluorescence Optical Studies of RNA Dynamics

International Nuclear Information System (INIS)

Zhao Xinghai; Shan Guangcun; Bao Shuying

2011-01-01

Single-molecule fluorescence spectroscopy in condensed phases has many important chemical and biological applications. The single-molecule fluorescence measurements contain information about conformational dynamics on a vast range of time scales. Based on the data analysis protocols methodology proposed by X. Sunney Xie, the theoretical study here mainly focuses on the single-molecule studies of single RNA with interconversions among different conformational states, to with a single FRET pair attached. We obtain analytical expressions for fluorescence lifetime correlation functions that relate changes in fluorescence lifetime to the distance-dependent FRET mechanism within the context of the Smoluchowski diffusion model. The present work establishes useful guideline for the single-molecule studies of biomolecules to reveal the complicated folding dynamics of single RNA molecules at nanometer scale.

Application of Wavelet-Based Tools to Study the Dynamics of Biological Processes

DEFF Research Database (Denmark)

Pavlov, A. N.; Makarov, V. A.; Mosekilde, Erik

2006-01-01

The article makes use of three different examples (sensory information processing in the rat trigeminal complex, intracellular interaction in snail neurons and multimodal dynamics in nephron autoregulation) to demonstrate how modern approaches to time-series analysis based on the wavelet-transfor...

Biology-inspired AMO physics

Science.gov (United States)

Mathur, Deepak

2015-01-01

This Topical Review presents an overview of increasingly robust interconnects that are being established between atomic, molecular and optical (AMO) physics and the life sciences. AMO physics, outgrowing its historical role as a facilitator—a provider of optical methodologies, for instance—now seeks to partner biology in its quest to link systems-level descriptions of biological entities to insights based on molecular processes. Of course, perspectives differ when AMO physicists and biologists consider various processes. For instance, while AMO physicists link molecular properties and dynamics to potential energy surfaces, these have to give way to energy landscapes in considerations of protein dynamics. But there are similarities also: tunnelling and non-adiabatic transitions occur both in protein dynamics and in molecular dynamics. We bring to the fore some such differences and similarities; we consider imaging techniques based on AMO concepts, like 4D fluorescence microscopy which allows access to the dynamics of cellular processes, multiphoton microscopy which offers a built-in confocality, and microscopy with femtosecond laser beams to saturate the suppression of fluorescence in spatially controlled fashion so as to circumvent the diffraction limit. Beyond imaging, AMO physics contributes with optical traps that probe the mechanical and dynamical properties of single ‘live’ cells, highlighting differences between healthy and diseased cells. Trap methodologies have also begun to probe the dynamics governing of neural stem cells adhering to each other to form neurospheres and, with squeezed light to probe sub-diffusive motion of yeast cells. Strong field science contributes not only by providing a source of energetic electrons and γ-rays via laser-plasma accelerations schemes, but also via filamentation and supercontinuum generation, enabling mainstream collision physics into play in diverse processes like DNA damage induced by low-energy collisions to

Scaling for Dynamical Systems in Biology.

Science.gov (United States)

Ledder, Glenn

2017-11-01

Asymptotic methods can greatly simplify the analysis of all but the simplest mathematical models and should therefore be commonplace in such biological areas as ecology and epidemiology. One essential difficulty that limits their use is that they can only be applied to a suitably scaled dimensionless version of the original dimensional model. Many books discuss nondimensionalization, but with little attention given to the problem of choosing the right scales and dimensionless parameters. In this paper, we illustrate the value of using asymptotics on a properly scaled dimensionless model, develop a set of guidelines that can be used to make good scaling choices, and offer advice for teaching these topics in differential equations or mathematical biology courses.

Correlative and dynamic imaging of the hatching biology of Schistosoma japonicum from eggs prepared by high pressure freezing.

Directory of Open Access Journals (Sweden)

Malcolm K Jones

Full Text Available BACKGROUND: Schistosome eggs must traverse tissues of the intestine or bladder to escape the human host and further the life cycle. Escape from host tissues is facilitated by secretion of immuno-reactive molecules by eggs and the formation of an intense strong granulomatous response by the host which acts to exclude the egg into gut or bladder lumens. Schistosome eggs hatch on contact with freshwater, but the mechanisms of activation and hatching are poorly understood. In view of the lack of knowledge of the behaviour of egg hatching in schistosomes, we undertook a detailed dynamic and correlative study of the hatching biology of Schistosoma japonicum. METHODOLOGY/PRINCIPAL FINDINGS: Hatching eggs of S. japonicum were studied using correlative light and electron microscopy (EM. The hatching behaviour was recorded by video microscopy. EM preparative methods incorporating high pressure freezing and cryo-substitution were used to investigate ultrastructural features of the miracidium and extra-embryonic envelopes in pre-activated and activated eggs, and immediately after eggshell rupture. Lectin cytochemistry was performed on egg tissues to investigate subcellular location of specific carbohydrate groups. CONCLUSIONS/SIGNIFICANCE: The hatching of S. japonicum eggs is a striking phenomenon, whereby the larva is liberated explosively while still encapsulated within its sub-shell envelopes. The major alterations that occur in the egg during activation are scission of the outer envelope-eggshell boundary, autolysis of the cellular inner envelope, and likely hydration of abundant complex and simple polysaccharides in the lacunal space between the miracidial larva and surrounding envelopes. These observations on hatching provide insight into the dynamic activity of the eggs and the biology of schistosomes within the host.

A Molecular Dynamics Study of the Structural and Dynamical Properties of Putative Arsenic Substituted Lipid Bilayers

Directory of Open Access Journals (Sweden)

Ratna Juwita

2013-04-01

Full Text Available Cell membranes are composed mainly of phospholipids which are in turn, composed of five major chemical elements: carbon, hydrogen, nitrogen, oxygen, and phosphorus. Recent studies have suggested the possibility of sustaining life if the phosphorus is substituted by arsenic. Although this issue is still controversial, it is of interest to investigate the properties of arsenated-lipid bilayers to evaluate this possibility. In this study, we simulated arsenated-lipid, 1-palmitoyl-2-oleoyl-sn-glycero-3-arsenocholine (POAC, lipid bilayers using all-atom molecular dynamics to understand basic structural and dynamical properties, in particular, the differences from analogous 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine, (POPC lipid bilayers. Our simulations showed that POAC lipid bilayers have distinct structural and dynamical properties from those of native POPC lipid bilayers. Relative to POPC lipid bilayers, POAC lipid bilayers have a more compact structure with smaller lateral areas and greater order. The compact structure of POAC lipid bilayers is due to the fact that more inter-lipid salt bridges are formed with arsenate-choline compared to the phosphate-choline of POPC lipid bilayers. These inter-lipid salt bridges bind POAC lipids together and also slow down the head group rotation and lateral diffusion of POAC lipids. Thus, it would be anticipated that POAC and POPC lipid bilayers would have different biological implications.

Granulometry use for the study of dynamics speckles patterns

International Nuclear Information System (INIS)

Mavilioa, Adriana; Fernandez, Margarita; Trivi, Marcelo; Rabal, Hector; Arizaga, Ricardo

2009-01-01

Dynamic speckle patterns are generated by laser light scattering on surfaces that exhibit some kind of activity, due to physical or biological processes that take place in the illuminated object. The characterization of this dynamic process is carried out by studying the texture changes of auxiliary images: temporal history of the speckle pattern (THSP) obtained from this speckles patterns. The drying process of water borne paint is studied through a method based on mathematical morphology applied to the THSP image processing. It is based on obtaining the granulometry of these images and their characteristic granulometric spectrum. From the granulometric size distribution of each THSP image four parameters are obtained: mean length, standard deviation, asymmetry and kurtosis. These parameters are found to be suitable as texture features. The Mahalanobis distance is calculated between the texture features of the THSP images representative of the temporary stages of the drying process and the features of the final stage or pattern texture. The behavior of the distance function describes satisfactorily the drying process of the water borne paint. Finally, these results are compared with the obtained by other methods. Compared with others, the granulometric method reported in this work distinguished by its simplicity and easy implementation and can be used to characterize the evolution of any process recorded through dynamic speckles. (Author)

Advanced models of neural networks nonlinear dynamics and stochasticity in biological neurons

CERN Document Server

Rigatos, Gerasimos G

2015-01-01

This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews the main findings in the modelling of neural dynamics in terms of electrical circuits and examines their stability properties with the use of dynamical systems theory. It is suitable for researchers and postgraduate students engaged with neural networks and dynamical systems theory.

LASER BIOLOGY: Optomechanical tests of hydrated biological tissues subjected to laser shaping

Science.gov (United States)

Omel'chenko, A. I.; Sobol', E. N.

2008-03-01

The mechanical properties of a matrix are studied upon changing the size and shape of biological tissues during dehydration caused by weak laser-induced heating. The cartilage deformation, dehydration dynamics, and hydraulic conductivity are measured upon laser heating. The hydrated state and the shape of samples of separated fascias and cartilaginous tissues were controlled by using computer-aided processing of tissue images in polarised light.

Ultrafast spectroscopy of model biological membranes

NARCIS (Netherlands)

Ghosh, Avishek

2009-01-01

In this PhD thesis, I have described the novel time-resolved sum-frequency generation (TR-SFG) spectroscopic technique that I developed during the course of my PhD research and used it study the ultrafast vibrational, structural and orientational dynamics of water molecules at model biological

Viscoelastic characterization of soft biological materials

Science.gov (United States)

Nayar, Vinod Timothy

Progressive and irreversible retinal diseases are among the primary causes of blindness in the United States, attacking the cells in the eye that transform environmental light into neural signals for the optic pathway. Medical implants designed to restore visual function to afflicted patients can cause mechanical stress and ultimately damage to the host tissues. Research shows that an accurate understanding of the mechanical properties of the biological tissues can reduce damage and lead to designs with improved safety and efficacy. Prior studies on the mechanical properties of biological tissues show characterization of these materials can be affected by environmental, length-scale, time, mounting, stiffness, size, viscoelastic, and methodological conditions. Using porcine sclera tissue, the effects of environmental, time, and mounting conditions are evaluated when using nanoindentation. Quasi-static tests are used to measure reduced modulus during extended exposure to phosphate-buffered saline (PBS), as well as the chemical and mechanical analysis of mounting the sample to a solid substrate using cyanoacrylate. The less destructive nature of nanoindentation tests allows for variance of tests within a single sample to be compared to the variance between samples. The results indicate that the environmental, time, and mounting conditions can be controlled for using modified nanoindentation procedures for biological samples and are in line with averages modulus values from previous studies but with increased precision. By using the quasi-static and dynamic characterization capabilities of the nanoindentation setup, the additional stiffness and viscoelastic variables are measured. Different quasi-static control methods were evaluated along with maximum load parameters and produced no significant difference in reported reduced modulus values. Dynamic characterization tests varied frequency and quasi-static load, showing that the agar could be modeled as a linearly

Detecting subnetwork-level dynamic correlations.

Science.gov (United States)

Yan, Yan; Qiu, Shangzhao; Jin, Zhuxuan; Gong, Sihong; Bai, Yun; Lu, Jianwei; Yu, Tianwei

2017-01-15

The biological regulatory system is highly dynamic. The correlations between many functionally related genes change over different biological conditions. Finding dynamic relations on the existing biological network may reveal important regulatory mechanisms. Currently no method is available to detect subnetwork-level dynamic correlations systematically on the genome-scale network. Two major issues hampered the development. The first is gene expression profiling data usually do not contain time course measurements to facilitate the analysis of dynamic relations, which can be partially addressed by using certain genes as indicators of biological conditions. Secondly, it is unclear how to effectively delineate subnetworks, and define dynamic relations between them. Here we propose a new method named LANDD (Liquid Association for Network Dynamics Detection) to find subnetworks that show substantial dynamic correlations, as defined by subnetwork A is concentrated with Liquid Association scouting genes for subnetwork B. The method produces easily interpretable results because of its focus on subnetworks that tend to comprise functionally related genes. Also, the collective behaviour of genes in a subnetwork is a much more reliable indicator of underlying biological conditions compared to using single genes as indicators. We conducted extensive simulations to validate the method's ability to detect subnetwork-level dynamic correlations. Using a real gene expression dataset and the human protein-protein interaction network, we demonstrate the method links subnetworks of distinct biological processes, with both confirmed relations and plausible new functional implications. We also found signal transduction pathways tend to show extensive dynamic relations with other functional groups. The R package is available at https://cran.r-project.org/web/packages/LANDD CONTACTS: yunba@pcom.edu, jwlu33@hotmail.com or tianwei.yu@emory.eduSupplementary information: Supplementary data

Biology-inspired AMO physics

International Nuclear Information System (INIS)

Mathur, Deepak

2015-01-01

This Topical Review presents an overview of increasingly robust interconnects that are being established between atomic, molecular and optical (AMO) physics and the life sciences. AMO physics, outgrowing its historical role as a facilitator—a provider of optical methodologies, for instance—now seeks to partner biology in its quest to link systems-level descriptions of biological entities to insights based on molecular processes. Of course, perspectives differ when AMO physicists and biologists consider various processes. For instance, while AMO physicists link molecular properties and dynamics to potential energy surfaces, these have to give way to energy landscapes in considerations of protein dynamics. But there are similarities also: tunnelling and non-adiabatic transitions occur both in protein dynamics and in molecular dynamics. We bring to the fore some such differences and similarities; we consider imaging techniques based on AMO concepts, like 4D fluorescence microscopy which allows access to the dynamics of cellular processes, multiphoton microscopy which offers a built-in confocality, and microscopy with femtosecond laser beams to saturate the suppression of fluorescence in spatially controlled fashion so as to circumvent the diffraction limit. Beyond imaging, AMO physics contributes with optical traps that probe the mechanical and dynamical properties of single ‘live’ cells, highlighting differences between healthy and diseased cells. Trap methodologies have also begun to probe the dynamics governing of neural stem cells adhering to each other to form neurospheres and, with squeezed light to probe sub-diffusive motion of yeast cells. Strong field science contributes not only by providing a source of energetic electrons and γ-rays via laser-plasma accelerations schemes, but also via filamentation and supercontinuum generation, enabling mainstream collision physics into play in diverse processes like DNA damage induced by low-energy collisions to

Neutron scattering studies of the dynamics of biological systems as a function of hydration, temperature and pressure

International Nuclear Information System (INIS)

Trapp, Marcus

2010-01-01

Incoherent elastic and quasi-elastic neutron scattering were used to measure membrane and protein dynamics in the nano- to picosecond time and Angstrom length scale. The hydration dependent dynamics of DMPC model membranes was studied using elastic and quasi-elastic neutron scattering. The elastic experiments showed a clear shift of the temperature of the main phase transition to higher temperatures with decreasing hydration level. The performed quasi-elastic measurements demonstrated nicely the influence, hydration has on the diffusive motions of the head lipid groups. Different models are necessary to fit the Q-dependence of the elastic incoherent structure factor and show therefore the reduced mobility as a result of reduced water content. In addition to temperature, pressure as a second thermodynamic variable was used to explore dynamics of DMPC membranes. The ordering introduced by applying pressure has similar effect to decreased hydration, therefore both approaches are complementary. Covering three orders of magnitude in observation time, the dynamics of native AChE and its complexed counterpart in presence of Huperzin A was investigated in the range from 1 ns to 100 ps. The mean square displacements obtained from the elastic data allowed the determination of activation energies and gave evidence that a hierarchy of motions contributes to the enzymatic activity. Diffusion constants and residence times were extracted from the quasi-elastic broadening. (author) [fr

A consensus approach for estimating the predictive accuracy of dynamic models in biology.

Science.gov (United States)

Villaverde, Alejandro F; Bongard, Sophia; Mauch, Klaus; Müller, Dirk; Balsa-Canto, Eva; Schmid, Joachim; Banga, Julio R

2015-04-01

Mathematical models that predict the complex dynamic behaviour of cellular networks are fundamental in systems biology, and provide an important basis for biomedical and biotechnological applications. However, obtaining reliable predictions from large-scale dynamic models is commonly a challenging task due to lack of identifiability. The present work addresses this challenge by presenting a methodology for obtaining high-confidence predictions from dynamic models using time-series data. First, to preserve the complex behaviour of the network while reducing the number of estimated parameters, model parameters are combined in sets of meta-parameters, which are obtained from correlations between biochemical reaction rates and between concentrations of the chemical species. Next, an ensemble of models with different parameterizations is constructed and calibrated. Finally, the ensemble is used for assessing the reliability of model predictions by defining a measure of convergence of model outputs (consensus) that is used as an indicator of confidence. We report results of computational tests carried out on a metabolic model of Chinese Hamster Ovary (CHO) cells, which are used for recombinant protein production. Using noisy simulated data, we find that the aggregated ensemble predictions are on average more accurate than the predictions of individual ensemble models. Furthermore, ensemble predictions with high consensus are statistically more accurate than ensemble predictions with large variance. The procedure provides quantitative estimates of the confidence in model predictions and enables the analysis of sufficiently complex networks as required for practical applications. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Molecular dynamics modeling the synthetic and biological polymers interactions pre-studied via docking

Science.gov (United States)

Tsvetkov, Vladimir B.; Serbin, Alexander V.

2014-06-01

In previous works we reported the design, synthesis and in vitro evaluations of synthetic anionic polymers modified by alicyclic pendant groups (hydrophobic anchors), as a novel class of inhibitors of the human immunodeficiency virus type 1 ( HIV-1) entry into human cells. Recently, these synthetic polymers interactions with key mediator of HIV-1 entry-fusion, the tri-helix core of the first heptad repeat regions [ HR1]3 of viral envelope protein gp41, were pre-studied via docking in terms of newly formulated algorithm for stepwise approximation from fragments of polymeric backbone and side-group models toward real polymeric chains. In the present article the docking results were verified under molecular dynamics ( MD) modeling. In contrast with limited capabilities of the docking, the MD allowed of using much more large models of the polymeric ligands, considering flexibility of both ligand and target simultaneously. Among the synthesized polymers the dinorbornen anchors containing alternating copolymers of maleic acid were selected as the most representative ligands (possessing the top anti-HIV activity in vitro in correlation with the highest binding energy in the docking). To verify the probability of binding of the polymers with the [HR1]3 in the sites defined via docking, various starting positions of polymer chains were tried. The MD simulations confirmed the main docking-predicted priority for binding sites, and possibilities for axial and belting modes of the ligands-target interactions. Some newly MD-discovered aspects of the ligand's backbone and anchor units dynamic cooperation in binding the viral target clarify mechanisms of the synthetic polymers anti-HIV activity and drug resistance prevention.

Biologically inspired technologies in NASA's morphing project

Science.gov (United States)

McGowan, Anna-Maria R.; Cox, David E.; Lazos, Barry S.; Waszak, Martin R.; Raney, David L.; Siochi, Emilie J.; Pao, S. Paul

2003-07-01

For centuries, biology has provided fertile ground for hypothesis, discovery, and inspiration. Time-tested methods used in nature are being used as a basis for several research studies conducted at the NASA Langley Research Center as a part of Morphing Project, which develops and assesses breakthrough vehicle technologies. These studies range from low drag airfoil design guided by marine and avian morphologies to soaring techniques inspired by birds and the study of small flexible wing vehicles. Biology often suggests unconventional yet effective approaches such as non-planar wings, dynamic soaring, exploiting aeroelastic effects, collaborative control, flapping, and fibrous active materials. These approaches and other novel technologies for future flight vehicles are being studied in NASA's Morphing Project. This paper will discuss recent findings in the aeronautics-based, biologically-inspired research in the project.

Ruminant Metabolic Systems Biology: Reconstruction and Integration of Transcriptome Dynamics Underlying Functional Responses of Tissues to Nutrition and Physiological Statea

Science.gov (United States)

Bionaz, Massimo; Loor, Juan J.

2012-01-01

High-throughput ‘omics’ data analysis via bioinformatics is one key component of the systems biology approach. The systems approach is particularly well-suited for the study of the interactions between nutrition and physiological state with tissue metabolism and functions during key life stages of organisms such as the transition from pregnancy to lactation in mammals, ie, the peripartal period. In modern dairy cows with an unprecedented genetic potential for milk synthesis, the nature of the physiologic and metabolic adaptations during the peripartal period is multifaceted and involves key tissues such as liver, adipose, and mammary. In order to understand such adaptation, we have reviewed several works performed in our and other labs. In addition, we have used a novel bioinformatics approach, Dynamic Impact Approach (DIA), in combination with partly previously published data to help interpret longitudinal biological adaptations of bovine liver, adipose, and mammary tissue to lactation using transcriptomics datasets. Use of DIA with transcriptomic data from those tissues during normal physiological adaptations and in animals fed different levels of energy prepartum allowed visualization and integration of most-impacted metabolic pathways around the time of parturition. The DIA is a suitable tool for applying the integrative systems biology approach. The ultimate goal is to visualize the complexity of the systems at study and uncover key molecular players involved in the tissue’s adaptations to physiological state or nutrition. PMID:22807626

Novel tendencies in developing small-angle neutron scattering methods for studying the structure of biological macromolecules

International Nuclear Information System (INIS)

Serdyuk, I.

1995-01-01

In recent 20 years thermal neutron scattering has been acknowledged an important instrument for structural studies in molecular biology. The methods of neutron diffraction of high resolution, which are not discussed in this paper, have already permitted to obtain a detailed representation of the course of proteolytic reactions and have arisen a number of new problems connected with the localization of water molecules and the H-D exchange. The methods of low resolution widely used due to a relative simplicity of the experiment have been successfully applied for both solving structural problems per se and investigating the changes in the structure when macromolecules perform their biological functions. The most promising are novel experimental approaches: the triple isotopic substitution method and the method of spin dynamic polarization. These methods ensure solving structural problems at a higher resolution than the dimensions of the macromolecules studied. Installation of new experimental instruments makes neutron measurements more accessible, and development of direct methods for interpretation of experimental data using the apparatus of spherical harmonics opens new possibilities for small-angle neutron scattering making it a necessary element for interpretation of diffraction data of monocrystals of intricate biological macromolecules. The paper presents a brief account of the tendencies in theoretical development and practical use of small-angle scattering for studying biological macromolecules. Special attention is given to the studies carried out in the Laboratory of Neutron Physics on a unique pulse IBR-2 reactor. (author) 14 refs

Perspective: Differential dynamic microscopy extracts multi-scale activity in complex fluids and biological systems

Science.gov (United States)

Cerbino, Roberto; Cicuta, Pietro

2017-09-01

Differential dynamic microscopy (DDM) is a technique that exploits optical microscopy to obtain local, multi-scale quantitative information about dynamic samples, in most cases without user intervention. It is proving extremely useful in understanding dynamics in liquid suspensions, soft materials, cells, and tissues. In DDM, image sequences are analyzed via a combination of image differences and spatial Fourier transforms to obtain information equivalent to that obtained by means of light scattering techniques. Compared to light scattering, DDM offers obvious advantages, principally (a) simplicity of the setup; (b) possibility of removing static contributions along the optical path; (c) power of simultaneous different microscopy contrast mechanisms; and (d) flexibility of choosing an analysis region, analogous to a scattering volume. For many questions, DDM has also advantages compared to segmentation/tracking approaches and to correlation techniques like particle image velocimetry. The very straightforward DDM approach, originally demonstrated with bright field microscopy of aqueous colloids, has lately been used to probe a variety of other complex fluids and biological systems with many different imaging methods, including dark-field, differential interference contrast, wide-field, light-sheet, and confocal microscopy. The number of adopting groups is rapidly increasing and so are the applications. Here, we briefly recall the working principles of DDM, we highlight its advantages and limitations, we outline recent experimental breakthroughs, and we provide a perspective on future challenges and directions. DDM can become a standard primary tool in every laboratory equipped with a microscope, at the very least as a first bias-free automated evaluation of the dynamics in a system.

Feasibility study for a recirculating linac-based facility for femtosecond dynamics

Energy Technology Data Exchange (ETDEWEB)

Corlett, J.N.; Barry, W.; Barletta, W.A.; Byrd, J.M.; DeSantis, S.; Doolittle, L.; Fawley, W.; Green, M.A.; Hartman, N.; Heimann, P.; Kairan, D.; Kujawski, E.; Li, D.; Lidia, S.; Luft, P.; McClure, R.; Parmigiani, F.; Petroff, Y.; Pirkl, W.; Placidi, M.; Reavill, D.; Reichel, I.; Rimmer, R.A.; Ratti, A.; Robinson, K.E.; Sannibale, F.; Schoenlein, R.; Staples, J.; Tanabe, J.; Truchlikova, D.; Wan, W.; Wang, S.; Wells, R.; Wolski, A.; Zholents, A.

2002-12-21

LBNL is pursuing design studies and the scientific program for a facility dedicated to the production of x-ray pulses with ultra-short time duration, for application in dynamical studies of processes in physics, biology, and chemistry. The proposed x-ray facility has the short x-ray pulse length ({approx}60 fs FWHM) necessary to study very fast dynamics, high flux (up to approximately 10E11 photons/sec/0.1 percentBW) to study weakly scattering systems, and tuneability over 1-12 keV photon energy. The hard x-ray photon production section of the machine accommodates seven 2-m long undulators. Design studies for longer wavelength sources, using high-gain harmonic generation, are in progress. The x-ray pulse repetition rate of 10 kHz is matched to studies of dynamical processes (initiated by ultra-short laser pulses) that typically have a long recovery time or are not generally cyclic or reversible and need time to allow relaxation, replacement, or flow of the sample. The technique for producing ultra-short x-ray pulses uses relatively long electron bunches to minimize high-peak-current collective effects, and the ultimate x-ray duration is achieved by a combination of bunch manipulation and optical compression. Synchronization of x-ray pulses to sample excitation signals is expected to be of order 50 - 100 fs. Techniques for making use of the recirculating geometry to provide beam-based signals from early passes through the machine are being studied.

Feasibility study for a recirculating linac-based facility for femtosecond dynamics

International Nuclear Information System (INIS)

Corlett, J.N.; Barry, W.; Barletta, W.A.; Byrd, J.M.; DeSantis, S.; Doolittle, L.; Fawley, W.; Green, M.A.; Hartman, N.; Heimann, P.; Kairan, D.; Kujawski, E.; Li, D.; Lidia, S.; Luft, P.; McClure, R.; Parmigiani, F.; Petroff, Y.; Pirkl, W.; Placidi, M.; Reavill, D.; Reichel, I.; Rimmer, R.A.; Ratti, A.; Robinson, K.E.; Sannibale, F.; Schoenlein, R.; Staples, J.; Tanabe, J.; Truchlikova, D.; Wan, W.; Wang, S.; Wells, R.; Wolski, A.; Zholents, A.

2002-01-01

LBNL is pursuing design studies and the scientific program for a facility dedicated to the production of x-ray pulses with ultra-short time duration, for application in dynamical studies of processes in physics, biology, and chemistry. The proposed x-ray facility has the short x-ray pulse length (∼60 fs FWHM) necessary to study very fast dynamics, high flux (up to approximately 10E11 photons/sec/0.1 percentBW) to study weakly scattering systems, and tuneability over 1-12 keV photon energy. The hard x-ray photon production section of the machine accommodates seven 2-m long undulators. Design studies for longer wavelength sources, using high-gain harmonic generation, are in progress. The x-ray pulse repetition rate of 10 kHz is matched to studies of dynamical processes (initiated by ultra-short laser pulses) that typically have a long recovery time or are not generally cyclic or reversible and need time to allow relaxation, replacement, or flow of the sample. The technique for producing ultra-short x-ray pulses uses relatively long electron bunches to minimize high-peak-current collective effects, and the ultimate x-ray duration is achieved by a combination of bunch manipulation and optical compression. Synchronization of x-ray pulses to sample excitation signals is expected to be of order 50 - 100 fs. Techniques for making use of the recirculating geometry to provide beam-based signals from early passes through the machine are being studied

Dynamics of forest ecosystems regenerated on burned and harvested areas in mountain regions of Siberia: characteristics of biological diversity, structure and productivity

Directory of Open Access Journals (Sweden)

I. M. Danilin

2016-12-01

Full Text Available Complex estimation of forest ecosystems dynamics based on detailing characteristics of structure, growth and productivity of the stands and describing general geographical and biological management options for preserving their biodiversity and sustaining stability are discussed in the paper by describing examples of tree stands restored on burned and logged areas in mountain regions of Siberia. On vast areas in Siberia, characterized as sub-boreal, subarid and with a strongly continental climate, forests grow on seasonally frozen soils and in many cases are surrounded by vast steppe and forest-steppe areas and uplands. Developing criteria for sustainability of mountain forest ecosystems is necessary for forest resource management and conservation. It is therefore important to obtain complex biometric characteristics on forest stands and landscapes and to thoroughly study their structure, biological diversity and productivity. Morphometric methods, Weibull simulation and allometric equations were used to determine the dimensional hierarchies of coenopopulation individuals. Structure and productivity of the aboveground stand components were also studied.

Synthetic biology: programming cells for biomedical applications.

Science.gov (United States)

Hörner, Maximilian; Reischmann, Nadine; Weber, Wilfried

2012-01-01

The emerging field of synthetic biology is a novel biological discipline at the interface between traditional biology, chemistry, and engineering sciences. Synthetic biology aims at the rational design of complex synthetic biological devices and systems with desired properties by combining compatible, modular biological parts in a systematic manner. While the first engineered systems were mainly proof-of-principle studies to demonstrate the power of the modular engineering approach of synthetic biology, subsequent systems focus on applications in the health, environmental, and energy sectors. This review describes recent approaches for biomedical applications that were developed along the synthetic biology design hierarchy, at the level of individual parts, of devices, and of complex multicellular systems. It describes how synthetic biological parts can be used for the synthesis of drug-delivery tools, how synthetic biological devices can facilitate the discovery of novel drugs, and how multicellular synthetic ecosystems can give insight into population dynamics of parasites and hosts. These examples demonstrate how this new discipline could contribute to novel solutions in the biopharmaceutical industry.

Biological oscillations: Fluorescence monitoring by confocal microscopy

Science.gov (United States)

Chattoraj, Shyamtanu; Bhattacharyya, Kankan

2016-09-01

Fluctuations play a vital role in biological systems. Single molecule spectroscopy has recently revealed many new kinds of fluctuations in biological molecules. In this account, we focus on structural fluctuations of an antigen-antibody complex, conformational dynamics of a DNA quadruplex, effects of taxol on dynamics of microtubules, intermittent red-ox oscillations at different organelles in a live cell (mitochondria, lipid droplets, endoplasmic reticulum and cell membrane) and stochastic resonance in gene silencing. We show that there are major differences in these dynamics between a cancer cell and the corresponding non-cancer cell.

Micro/nanofabricated environments for synthetic biology.

Science.gov (United States)

Collier, C Patrick; Simpson, Michael L

2011-08-01

A better understanding of how confinement, crowding and reduced dimensionality modulate reactivity and reaction dynamics will aid in the rational and systematic discovery of functionality in complex biological systems. Artificial microfabricated and nanofabricated structures have helped elucidate the effects of nanoscale spatial confinement and segregation on biological behavior, particularly when integrated with microfluidics, through precise control in both space and time of diffusible signals and binding interactions. Examples of nanostructured interfaces for synthetic biology include the development of cell-like compartments for encapsulating biochemical reactions, nanostructured environments for fundamental studies of diffusion, molecular transport and biochemical reaction kinetics, and regulation of biomolecular interactions as functions of microfabricated and nanofabricated topological constraints. Copyright © 2011 Elsevier Ltd. All rights reserved.

Dynamics of Soft Matter

CERN Document Server

García Sakai, Victoria; Chen, Sow-Hsin

2012-01-01

Dynamics of Soft Matter: Neutron Applications provides an overview of neutron scattering techniques that measure temporal and spatial correlations simultaneously, at the microscopic and/or mesoscopic scale. These techniques offer answers to new questions arising at the interface of physics, chemistry, and biology. Knowledge of the dynamics at these levels is crucial to understanding the soft matter field, which includes colloids, polymers, membranes, biological macromolecules, foams, emulsions towards biological & biomimetic systems, and phenomena involving wetting, friction, adhesion, or micr

Modelling Protein Dynamics on the Microsecond Time Scale

DEFF Research Database (Denmark)

Siuda, Iwona Anna

Recent years have shown an increase in coarse-grained (CG) molecular dynamics simulations, providing structural and dynamic details of large proteins and enabling studies of self-assembly of biological materials. It is not easy to acquire such data experimentally, and access is also still limited...... in atomistic simulations. During her PhD studies, Iwona Siuda used MARTINI CG models to study the dynamics of different globular and membrane proteins. In several cases, the MARTINI model was sufficient to study conformational changes of small, purely alpha-helical proteins. However, in studies of larger......ELNEDIN was therefore proposed as part of the work. Iwona Siuda’s results from the CG simulations had biological implications that provide insights into possible mechanisms of the periplasmic leucine-binding protein, the sarco(endo)plasmic reticulum calcium pump, and several proteins from the saposin-like proteins...

Dissipative particle dynamics simulations for biological tissues: rheology and competition

International Nuclear Information System (INIS)

Basan, Markus; Prost, Jacques; Joanny, Jean-François; Elgeti, Jens

2011-01-01

In this work, we model biological tissues using a simple, mechanistic simulation based on dissipative particle dynamics. We investigate the continuum behavior of the simulated tissue and determine its dependence on the properties of the individual cell. Cells in our simulation adhere to each other, expand in volume, divide after reaching a specific size checkpoint and undergo apoptosis at a constant rate, leading to a steady-state homeostatic pressure in the tissue. We measure the dependence of the homeostatic state on the microscopic parameters of our model and show that homeostatic pressure, rather than the unconfined rate of cell division, determines the outcome of tissue competitions. Simulated cell aggregates are cohesive and round up due to the effect of tissue surface tension, which we measure for different tissues. Furthermore, mixtures of different cells unmix according to their adhesive properties. Using a variety of shear and creep simulations, we study tissue rheology by measuring yield stresses, shear viscosities, complex viscosities as well as the loss tangents as a function of model parameters. We find that cell division and apoptosis lead to a vanishing yield stress and fluid-like tissues. The effects of different adhesion strengths and levels of noise on the rheology of the tissue are also measured. In addition, we find that the level of cell division and apoptosis drives the diffusion of cells in the tissue. Finally, we present a method for measuring the compressibility of the tissue and its response to external stress via cell division and apoptosis

Biologic targets identified from dynamic 18FDG-PET and implications for image-guided therapy

International Nuclear Information System (INIS)

Rusten, Espen; Malinen, Eirik; Roedal, Jan; Bruland, Oeyvind S.

2013-01-01

Purpose: The outcome of biologic image-guided radiotherapy depends on the definition of the biologic target. The purpose of the current work was to extract hyper perfused and hypermetabolic regions from dynamic positron emission tomography (D-PET) images, to dose escalate either region and to discuss implications of such image guided strategies. Methods: Eleven patients with soft tissue sarcomas were investigated with D-PET. The images were analyzed using a two-compartment model producing parametric maps of perfusion and metabolic rate. The two image series were segmented and exported to a treatment planning system, and biological target volumes BTV per and BTV met (perfusion and metabolism, respectively) were generated. Dice's similarity coefficient was used to compare the two biologic targets. Intensity-modulated radiation therapy (IMRT) plans were generated for a dose painting by contours regime, where planning target volume (PTV) was planned to 60 Gy and BTV to 70 Gy. Thus, two separate plans were created for each patient with dose escalation of either BTV per or BTV met . Results: BTV per was somewhat smaller than BTV met (209 ±170 cm 3 against 243 ±143 cm 3 , respectively; population-based mean and s.d.). Dice's coefficient depended on the applied margin, and was 0.72 ±0.10 for a margin of 10 mm. Boosting BTV per resulted in mean dose of 69 ±1.0 Gy to this region, while BTV met received 67 ±3.2 Gy. Boosting BTV met gave smaller dose differences between the respective non-boost DVHs (such as D 98 ). Conclusions: Dose escalation of one of the BTVs results in a partial dose escalation of the other BTV as well. If tumor aggressiveness is equally pronounced in hyper perfused and hypermetabolic regions, this should be taken into account in the treatment planning

Revisit of Machine Learning Supported Biological and Biomedical Studies.

Science.gov (United States)

Yu, Xiang-Tian; Wang, Lu; Zeng, Tao

2018-01-01

Generally, machine learning includes many in silico methods to transform the principles underlying natural phenomenon to human understanding information, which aim to save human labor, to assist human judge, and to create human knowledge. It should have wide application potential in biological and biomedical studies, especially in the era of big biological data. To look through the application of machine learning along with biological development, this review provides wide cases to introduce the selection of machine learning methods in different practice scenarios involved in the whole biological and biomedical study cycle and further discusses the machine learning strategies for analyzing omics data in some cutting-edge biological studies. Finally, the notes on new challenges for machine learning due to small-sample high-dimension are summarized from the key points of sample unbalance, white box, and causality.

Quantum Biology

Directory of Open Access Journals (Sweden)

Alessandro Sergi

2009-06-01

Full Text Available A critical assessment of the recent developmentsof molecular biology is presented.The thesis that they do not lead to a conceptualunderstanding of life and biological systems is defended.Maturana and Varela's concept of autopoiesis is briefly sketchedand its logical circularity avoided by postulatingthe existence of underlying living processes,entailing amplification from the microscopic to the macroscopic scale,with increasing complexity in the passage from one scale to the other.Following such a line of thought, the currently accepted model of condensed matter, which is based on electrostatics and short-ranged forces,is criticized. It is suggested that the correct interpretationof quantum dispersion forces (van der Waals, hydrogen bonding, and so onas quantum coherence effects hints at the necessity of includinglong-ranged forces (or mechanisms for them incondensed matter theories of biological processes.Some quantum effects in biology are reviewedand quantum mechanics is acknowledged as conceptually important to biology since withoutit most (if not all of the biological structuresand signalling processes would not even exist. Moreover, it is suggested that long-rangequantum coherent dynamics, including electron polarization,may be invoked to explain signal amplificationprocess in biological systems in general.

Boolean Models of Biological Processes Explain Cascade-Like Behavior.

Science.gov (United States)

Chen, Hao; Wang, Guanyu; Simha, Rahul; Du, Chenghang; Zeng, Chen

2016-01-29

Biological networks play a key role in determining biological function and therefore, an understanding of their structure and dynamics is of central interest in systems biology. In Boolean models of such networks, the status of each molecule is either "on" or "off" and along with the molecules interact with each other, their individual status changes from "on" to "off" or vice-versa and the system of molecules in the network collectively go through a sequence of changes in state. This sequence of changes is termed a biological process. In this paper, we examine the common perception that events in biomolecular networks occur sequentially, in a cascade-like manner, and ask whether this is likely to be an inherent property. In further investigations of the budding and fission yeast cell-cycle, we identify two generic dynamical rules. A Boolean system that complies with these rules will automatically have a certain robustness. By considering the biological requirements in robustness and designability, we show that those Boolean dynamical systems, compared to an arbitrary dynamical system, statistically present the characteristics of cascadeness and sequentiality, as observed in the budding and fission yeast cell- cycle. These results suggest that cascade-like behavior might be an intrinsic property of biological processes.

The mathematics behind biological invasions

CERN Document Server

Lewis, Mark A; Potts, Jonathan R

2016-01-01

This book investigates the mathematical analysis of biological invasions. Unlike purely qualitative treatments of ecology, it draws on mathematical theory and methods, equipping the reader with sharp tools and rigorous methodology. Subjects include invasion dynamics, species interactions, population spread, long-distance dispersal, stochastic effects, risk analysis, and optimal responses to invaders. While based on the theory of dynamical systems, including partial differential equations and integrodifference equations, the book also draws on information theory, machine learning, Monte Carlo methods, optimal control, statistics, and stochastic processes. Applications to real biological invasions are included throughout. Ultimately, the book imparts a powerful principle: that by bringing ecology and mathematics together, researchers can uncover new understanding of, and effective response strategies to, biological invasions. It is suitable for graduate students and established researchers in mathematical ecolo...

From globally coupled maps to complex-systems biology

Energy Technology Data Exchange (ETDEWEB)

Kaneko, Kunihiko, E-mail: kaneko@complex.c.u-tokyo.ac.jp [Research Center for Complex Systems Biology, Graduate School of Arts and Sciences, The University of Tokyo 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902 (Japan)

2015-09-15

Studies of globally coupled maps, introduced as a network of chaotic dynamics, are briefly reviewed with an emphasis on novel concepts therein, which are universal in high-dimensional dynamical systems. They include clustering of synchronized oscillations, hierarchical clustering, chimera of synchronization and desynchronization, partition complexity, prevalence of Milnor attractors, chaotic itinerancy, and collective chaos. The degrees of freedom necessary for high dimensionality are proposed to equal the number in which the combinatorial exceeds the exponential. Future analysis of high-dimensional dynamical systems with regard to complex-systems biology is briefly discussed.

Nonlinear dynamics in ecosystem response to climatic change: Case studies and policy implications

Science.gov (United States)

Burkett, Virginia R.; Wilcox, Douglas A.; Stottlemyer, Robert; Barrow, Wylie; Fagre, Dan; Baron, Jill S.; Price, Jeff; Nielsen, Jennifer L.; Allen, Craig D.; Peterson, David L.; Ruggerone, Greg; Doyle, Thomas

2005-01-01

Many biological, hydrological, and geological processes are interactively linked in ecosystems. These ecological phenomena normally vary within bounded ranges, but rapid, nonlinear changes to markedly different conditions can be triggered by even small differences if threshold values are exceeded. Intrinsic and extrinsic ecological thresholds can lead to effects that cascade among systems, precluding accurate modeling and prediction of system response to climate change. Ten case studies from North America illustrate how changes in climate can lead to rapid, threshold-type responses within ecological communities; the case studies also highlight the role of human activities that alter the rate or direction of system response to climate change. Understanding and anticipating nonlinear dynamics are important aspects of adaptation planning since responses of biological resources to changes in the physical climate system are not necessarily proportional and sometimes, as in the case of complex ecological systems, inherently nonlinear.

Structural Identifiability of Dynamic Systems Biology Models.

Science.gov (United States)

Villaverde, Alejandro F; Barreiro, Antonio; Papachristodoulou, Antonis

2016-10-01

A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas.

Identify Dynamic Network Modules with Temporal and Spatial Constraints

Energy Technology Data Exchange (ETDEWEB)

Jin, R; McCallen, S; Liu, C; Almaas, E; Zhou, X J

2007-09-24

Despite the rapid accumulation of systems-level biological data, understanding the dynamic nature of cellular activity remains a difficult task. The reason is that most biological data are static, or only correspond to snapshots of cellular activity. In this study, we explicitly attempt to detangle the temporal complexity of biological networks by using compilations of time-series gene expression profiling data.We define a dynamic network module to be a set of proteins satisfying two conditions: (1) they form a connected component in the protein-protein interaction (PPI) network; and (2) their expression profiles form certain structures in the temporal domain. We develop the first efficient mining algorithm to discover dynamic modules in a temporal network, as well as frequently occurring dynamic modules across many temporal networks. Using yeast as a model system, we demonstrate that the majority of the identified dynamic modules are functionally homogeneous. Additionally, many of them provide insight into the sequential ordering of molecular events in cellular systems. We further demonstrate that identifying frequent dynamic network modules can significantly increase the signal to noise separation, despite the fact that most dynamic network modules are highly condition-specific. Finally, we note that the applicability of our algorithm is not limited to the study of PPI systems, instead it is generally applicable to the combination of any type of network and time-series data.

Dynamic cell culture system: a new cell cultivation instrument for biological experiments in space

Science.gov (United States)

Gmunder, F. K.; Nordau, C. G.; Tschopp, A.; Huber, B.; Cogoli, A.

1988-01-01

The prototype of a miniaturized cell cultivation instrument for animal cell culture experiments aboard Spacelab is presented (Dynamic cell culture system: DCCS). The cell chamber is completely filled and has a working volume of 200 microliters. Medium exchange is achieved with a self-powered osmotic pump (flowrate 1 microliter h-1). The reservoir volume of culture medium is 230 microliters. The system is neither mechanically stirred nor equipped with sensors. Hamster kidney (Hak) cells growing on Cytodex 3 microcarriers were used to test the biological performance of the DCCS. Growth characteristics in the DCCS, as judged by maximal cell density, glucose consumption, lactic acid secretion and pH, were similar to those in cell culture tubes.

Architecture and dynamics of proteins and aqueous solvation complexes

NARCIS (Netherlands)

Lotze, S.M.

2015-01-01

For this thesis, the molecular dynamics of water and biological (model) systems have been studied with advanced nonlinear optical techniques. In chapters 4-5, the technique of femtosecond mid-infrared pump probe spectroscopy has been used to study the energy transfer and the reorientational dynamics

Biological Membrane Ion Channels Dynamics, Structure, and Applications

CERN Document Server

Chung, Shin-Ho; Krishnamurthy, Vikram

2007-01-01

Ion channels are biological nanotubes that are formed by membrane proteins. Because ion channels regulate all electrical activities in living cells, understanding their mechanisms at a molecular level is a fundamental problem in biology. This book deals with recent breakthroughs in ion-channel research that have been brought about by the combined effort of experimental biophysicists and computational physicists, who together are beginning to unravel the story of these exquisitely designed biomolecules. With chapters by leading experts, the book is aimed at researchers in nanodevices and biosensors, as well as advanced undergraduate and graduate students in biology and the physical sciences. Key Features Presents the latest information on the molecular mechanisms of ion permeation through membrane ion channels Uses schematic diagrams to illustrate important concepts in biophysics Written by leading researchers in the area of ion channel investigations

Environmental biology

International Nuclear Information System (INIS)

Tschumi, P.A.

1981-01-01

Environmental biology illustrates the functioning of ecosystems and the dynamics of populations with many examples from limnology and terrestrial ecology. On this basis, present environmental problems are analyzed. The present environmental crisis is seen as a result of the failure to observe ecological laws. (orig.) [de

Systems biology approach to bioremediation

Energy Technology Data Exchange (ETDEWEB)

Chakraborty, Romy; Wu, Cindy H.; Hazen, Terry C.

2012-06-01

Bioremediation has historically been approached as a ‘black box’ in terms of our fundamental understanding. Thus it succeeds and fails, seldom without a complete understanding of why. Systems biology is an integrated research approach to study complex biological systems, by investigating interactions and networks at the molecular, cellular, community, and ecosystem level. The knowledge of these interactions within individual components is fundamental to understanding the dynamics of the ecosystem under investigation. Finally, understanding and modeling functional microbial community structure and stress responses in environments at all levels have tremendous implications for our fundamental understanding of hydrobiogeochemical processes and the potential for making bioremediation breakthroughs and illuminating the ‘black box’.

Catalytic performances of chemically immobilized urease under static and dynamic conditions: A comparative study

OpenAIRE

Yürekli, Yılmaz; Alsoy Altınkaya, Sacide

2011-01-01

Immobilized urease has been used for direct removal of urea from aqueous solution and as biological sensing material in the preparation of urea biosensors. The former application is carried out under dynamic condition using ultrafiltration membrane either in tubular form or in flat sheet, while the latter is used in static condition. In this study, the performance of chemically immobilized urease on poly(acrylonitrile-co-sodium methallyl sulfonate) ultrafiltration membrane was determined unde...

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

International Nuclear Information System (INIS)

Lewis, Daniel D.; Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng

2014-01-01

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

Energy Technology Data Exchange (ETDEWEB)

Lewis, Daniel D. [Integrative Genetics and Genomics, University of California Davis, Davis, CA (United States); Department of Biomedical Engineering, University of California Davis, Davis, CA (United States); Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng, E-mail: cmtan@ucdavis.edu [Department of Biomedical Engineering, University of California Davis, Davis, CA (United States)

2014-12-09

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology

CERN Document Server

2017-01-01

This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...

Receptor studies in biological psychiatry

International Nuclear Information System (INIS)

Fujiwara, Yutaka

1992-01-01

Recent advances in the pharmacological treatment of endogenous psychosis have led to the development of biological studies in psychiatry. Studies on neurotransmitter receptors were reviewed in order to apply positron-emission tomograph (PET) for biological psychiatry. The dopamine (DA) hypothesis for schizophrenia was advanced on the basis of the observed effects of neuroleptics and methamphetamine, and DA(D 2 ) receptor supersensitivity measured by PET and receptor binding in the schizophrenic brain. The clinical potencies of neuroleptics for schizophrenia were correlated with their abilities to inhibit the D 2 receptor, and not other receptors. The σ receptor was expected to be a site of antipsychotic action. However, the potency of drugs action on it was not correlated with clinical efficacy. Haloperidol binds with high affinity to the σ receptor, which may mediate acute dystonia, an extrapyramidal side effect of neuroleptics. Behavioral and neurochemical changes induced by methamphetamine treatment were studied as an animal model of schizophrenia, and both a decrease of D 2 receptor density and an increase of DA release were detected. The monoamine hypothesis for manic-depressive psychosis was advanced on the basis of the effect of reserpine, monoamine oxidase inhibitor and antidepressants. 3 H-clonidine binding sites were increased in platelet membranes of depressive patients, 3 H-imipramine binding sites were decreased. The GABA A receptor is the target site for the action of anxiolytics and antiepileptics such as benzodiazepines and barbiturates. Recent developments in molecular biology techniques have revealed the structure of receptor proteins, which are classified into two receptor families, the G-protein coupled type (D 2 ) and the ion-channel type (GABA A ). (J.P.N.)

Biological Motion Preference in Humans at Birth: Role of Dynamic and Configural Properties

Science.gov (United States)

Bardi, Lara; Regolin, Lucia; Simion, Francesca

2011-01-01

The present study addresses the hypothesis that detection of biological motion is an intrinsic capacity of the visual system guided by a non-species-specific predisposition for the pattern of vertebrate movement and investigates the role of global vs. local information in biological motion detection. Two-day-old babies exposed to a biological…

Nanomaterials under extreme environments: A study of structural and dynamic properties using reactive molecular dynamics simulations

Science.gov (United States)

Shekhar, Adarsh

nanoporous silica are different from that of bulk water, and insight into the properties of confined water is important for our understanding of many geological and biological processes. Nanoporous silica has a wide range of technological applications because it is easy to tune the size of pores and their morphologies and to functionalize pore surfaces with a variety of molecular moieties. Nanoporous silica is used in catalysis, chromatography, anticorrosion coatings, desalination membranes, and as drug delivery vehicles. We use reactive molecular dynamics to study the structure and dynamics of nanoconfined water between 100 and 300 K

An introduction to biological NMR spectroscopy

International Nuclear Information System (INIS)

Marion, Dominique

2013-01-01

NMR spectroscopy is a powerful tool for biologists interested in the structure, dynamics, and interactions of biological macromolecules. This review aims at presenting in an accessible manner the requirements and limitations of this technique. As an introduction, the history of NMR will highlight how the method evolved from physics to chemistry and finally to biology over several decades. We then introduce the NMR spectral parameters used in structural biology, namely the chemical shift, the J-coupling, nuclear Overhauser effects, and residual dipolar couplings. Resonance assignment, the required step for any further NMR study, bears a resemblance to jigsaw puzzle strategy. The NMR spectral parameters are then converted into angle and distances and used as input using restrained molecular dynamics to compute a bundle of structures. When interpreting a NMR-derived structure, the biologist has to judge its quality on the basis of the statistics provided. When the 3D structure is a priori known by other means, the molecular interaction with a partner can be mapped by NMR: information on the binding interface as well as on kinetic and thermodynamic constants can be gathered. NMR is suitable to monitor, over a wide range of frequencies, protein fluctuations that play a crucial role in their biological function. In the last section of this review, intrinsically disordered proteins, which have escaped the attention of classical structural biology, are discussed in the perspective of NMR, one of the rare available techniques able to describe structural ensembles. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 16 MCP). (authors)

Optomechanical tests of hydrated biological tissues subjected to laser shaping

International Nuclear Information System (INIS)

Omel'chenko, A I; Sobol', E N

2008-01-01

The mechanical properties of a matrix are studied upon changing the size and shape of biological tissues during dehydration caused by weak laser-induced heating. The cartilage deformation, dehydration dynamics, and hydraulic conductivity are measured upon laser heating. The hydrated state and the shape of samples of separated fascias and cartilaginous tissues were controlled by using computer-aided processing of tissue images in polarised light. (laser biology)

Modeling Cancer Metastasis using Global, Quantitative and Integrative Network Biology

DEFF Research Database (Denmark)

Schoof, Erwin; Erler, Janine

understanding of molecular processes which are fundamental to tumorigenesis. In Article 1, we propose a novel framework for how cancer mutations can be studied by taking into account their effect at the protein network level. In Article 2, we demonstrate how global, quantitative data on phosphorylation dynamics...... can be generated using MS, and how this can be modeled using a computational framework for deciphering kinase-substrate dynamics. This framework is described in depth in Article 3, and covers the design of KinomeXplorer, which allows the prediction of kinases responsible for modulating observed...... phosphorylation dynamics in a given biological sample. In Chapter III, we move into Integrative Network Biology, where, by combining two fundamental technologies (MS & NGS), we can obtain more in-depth insights into the links between cellular phenotype and genotype. Article 4 describes the proof...

Biological soil crusts exhibit a dynamic response to seasonal rain and release from grazing with implications for soil stability

Science.gov (United States)

Jimenez, Aguilar A.; Huber-Sannwald, E.; Belnap, J.; Smart, D.R.; Arredondo, Moreno J.T.

2009-01-01

In Northern Mexico, long-term grazing has substantially degraded semiarid landscapes. In semiarid systems, ecological and hydrological processes are strongly coupled by patchy plant distribution and biological soil crust (BSC) cover in plant-free interspaces. In this study, we asked: 1) how responsive are BSC cover/composition to a drying/wetting cycle and two-year grazing removal, and 2) what are the implications for soil erosion? We characterized BSC morphotypes and their influence on soil stability under grazed/non-grazed conditions during a dry and wet season. Light- and dark-colored cyanobacteria were dominant at the plant tussock and community level. Cover changes in these two groups differed after a rainy season and in response to grazing removal. Lichens with continuous thalli were more vulnerable to grazing than those with semi-continuous/discontinuous thalli after the dry season. Microsites around tussocks facilitated BSC colonization compared to interspaces. Lichen and cyanobacteria morphotypes differentially enhanced resistance to soil erosion; consequently, surface soil stability depends on the spatial distribution of BSC morphotypes, suggesting soil stability may be as dynamic as changes in the type of BSC cover. Longer-term spatially detailed studies are necessary to elicit spatiotemporal dynamics of BSC communities and their functional role in biotically and abiotically variable environments. ?? 2009 Elsevier Ltd.

A new methodology for studying nanoparticle interactions in biological systems: Dispersing titania in biocompatible media using chemical stabilisers

Science.gov (United States)

Ramirez-Garcia, Sonia; Chen, Lan; Morris, Michael A.; Dawson, Kenneth A.

2011-11-01

We report here a highly successful and original protocol for the dispersion of nanoparticles in biocompatible fluids for in vitro and in vivo studies of the nanoparticle-biology interaction. Titania is chosen as a suitable model as it is one of the priority materials listed by the OECD and small particles of the anatase structure are extensively used as e.g. photocatalysts in solar cells. Consequently, its delivery into the environment and its interaction with biological organisms is unavoidable. Therefore, its biological effect needs to be understood. In this work, we prepared stable nanoparticle dispersions of anatase aggregates using citrate stabilisations between 45 and 55 nm at concentrations of up to 10 mg mL-1. The optimum pH for this type of suspension was 7, resulting in ζ-potentials of approximately -50 mV. The stabilised aggregates were the subject of dialysis to produce stable dispersions without the chemical stabiliser, thus allowing studies in the absence of potentially toxic chemicals. Different sizing techniques such as Dynamic Light Scattering (DLS), Nanoparticle Tracking Analysis (NTA) and Differential Centrifuge Sedimentation (DCS) were used to characterise the different suspensions. The results obtained with each of these techniques are compared and a critical analysis of the suitability of each technique is given.We report here a highly successful and original protocol for the dispersion of nanoparticles in biocompatible fluids for in vitro and in vivo studies of the nanoparticle-biology interaction. Titania is chosen as a suitable model as it is one of the priority materials listed by the OECD and small particles of the anatase structure are extensively used as e.g. photocatalysts in solar cells. Consequently, its delivery into the environment and its interaction with biological organisms is unavoidable. Therefore, its biological effect needs to be understood. In this work, we prepared stable nanoparticle dispersions of anatase aggregates

Correlativity study on MRI morphologic features, pathology, and molecular biology of breast cancer

International Nuclear Information System (INIS)

Chen Rong; Gong Shuigen; Zhang Weiguo; Chen Jinhua; He Shuangwu; Liu Baohua; Li Zengpeng

2004-01-01

Objective: To investigate the correlation among MRI morphologic features, pathology, and molecular biology of breast cancer. Methods: MR scanning was performed in 78 patients with breast cancer before operation and MRI morphologic features of breast cancer were analyzed. The mastectomy specimens of the breast neoplasm were stained with immunohistochemistry, and the expression of estrogen receptor (ER), progesterone receptor (PR), C-erbB-2, p53, and the distribution of microvessel density (MVD) was measured. The pathologic results were compared with MRI features. Results: Among the 80 breast cancers, ER positive expression was positively correlated with the spiculate margin of breast cancer (P 0.05). Among the 41 breast cancers with dynamic MR scans, there was positive correlation between the spatial distribution of contrast agent and MVD (P<0.01). Conclusion: There exists some correlation among MRI morphologic features, pathology, and molecular biology factors in breast cancer to certain extent. The biologic behavior and prognosis of the breast cancer can be assessed according to MRI features

Mathematical modeling of biological processes

CERN Document Server

Friedman, Avner

2014-01-01

This book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.

A microfluidic flow-cell for the study of the ultrafast dynamics of biological systems

Energy Technology Data Exchange (ETDEWEB)

Chauvet, Adrien, E-mail: adrien.chauvet@epfl.ch; Chergui, Majed [Ecole Polytechnique Fédérale de Lausanne (EPFL), Laboratoire de Spectroscopie Ultrarapide, ISIC, Faculté des Sciences de Base, Station 6, 1015 Lausanne (Switzerland); Tibiletti, Tania; Caffarri, Stefano [Aix Marseille Université, CNRS, CEA, UMR 7265 Biologie Végétale et Microbiologie Environnementales, 13009 Marseille (France)

2014-10-01

The study of biochemical dynamics by ultrafast spectroscopic methods is often restricted by the limited amount of liquid sample available, while the high repetition rate of light sources can induce photodamage. In order to overcome these limitations, we designed a high flux, sub-ml, capillary flow-cell. While the 0.1 mm thin window of the 0.5 mm cross-section capillary ensures an optimal temporal resolution and a steady beam deviation, the cell-pump generates flows up to ~0.35 ml/s that are suitable to pump laser repetition rates up to ~14 kHz, assuming a focal spot-diameter of 100 μm. In addition, a decantation chamber efficiently removes bubbles and allows, via septum, for the addition of chemicals while preserving the closed atmosphere. The minimal useable amount of sample is ~250 μl.

Recommendations for designing and conducting veterinary clinical pathology biologic variation studies

DEFF Research Database (Denmark)

Freeman, Kathleen P; Baral, Randolph M; Dhand, Navneet K

2017-01-01

The recent creation of a veterinary clinical pathology biologic variation website has highlighted the need to provide recommendations for future studies of biologic variation in animals in order to help standardize and improve the quality of published information and to facilitate review......). These recommendations provide a valuable resource for clinicians, laboratorians, and researchers interested in conducting studies of biologic variation and in determining the quality of studies of biologic variation in veterinary laboratory testing....

Modular analysis of biological networks.

Science.gov (United States)

Kaltenbach, Hans-Michael; Stelling, Jörg

2012-01-01

The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.

Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

Science.gov (United States)

Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing

2014-01-15

A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

Nuclear magnetic resonance applications in biological systems

International Nuclear Information System (INIS)

Jiang Ling; Liu Maili

2011-01-01

Nuclear magnetic resonance (NMR) spectroscopy is a state-of-the-art technology which has been widely applied in biological systems over the past decades. It is a powerful tool for macromolecular structure determination in solution, and has the unique advantage of being capable of elucidating the structure and dynamic behavior of proteins during vital biomedical processes. In this review, we introduce the recent progress in NMR techniques for studying the structure, interaction and dynamics of proteins. The methods for NMR based drug discovery and metabonomics are also briefly introduced. (authors)

The bottom-up approach to defining life : deciphering the functional organization of biological cells via multi-objective representation of biological complexity from molecules to cells

Directory of Open Access Journals (Sweden)

Sathish ePeriyasamy

2013-12-01

Full Text Available In silico representation of cellular systems needs to represent the adaptive dynamics of biological cells, recognizing a cell’s multi-objective topology formed by spatially and temporally cohesive intracellular structures. The design of these models needs to address the hierarchical and concurrent nature of cellular functions and incorporate the ability to self-organise in response to transitions between healthy and pathological phases, and adapt accordingly. The functions of biological systems are constantly evolving, due to the ever changing demands of their environment. Biological systems meet these demands by pursuing objectives, aided by their constituents, giving rise to biological functions. A biological cell is organised into an objective/task hierarchy. These objective hierarchy corresponds to the nested nature of temporally cohesive structures and representing them will facilitate in studying pleiotropy and polygeny by modeling causalities propagating across multiple interconnected intracellular processes. Although biological adaptations occur in physiological, developmental and reproductive timescales, the paper is focused on adaptations that occur within physiological timescales, where the biomolecular activities contributing to functional organisation, play a key role in cellular physiology. The paper proposes a multi-scale and multi-objective modelling approach from the bottom-up by representing temporally cohesive structures for multi-tasking of intracellular processes. Further the paper characterises the properties and constraints that are consequential to the organisational and adaptive dynamics in biological cells.

Independent alignment of RNA for dynamic studies using residual dipolar couplings

Energy Technology Data Exchange (ETDEWEB)

Bardaro, Michael F.; Varani, Gabriele, E-mail: varani@chem.washington.edu [University of Washington, Department of Chemistry (United States)

2012-09-15

Molecular motion and dynamics play an essential role in the biological function of many RNAs. An important source of information on biomolecular motion can be found in residual dipolar couplings which contain dynamics information over the entire ms-ps timescale. However, these methods are not fully applicable to RNA because nucleic acid molecules tend to align in a highly collinear manner in different alignment media. As a consequence, information on dynamics that can be obtained with this method is limited. In order to overcome this limitation, we have generated a chimeric RNA containing both the wild type TAR RNA, the target of our investigation of dynamics, as well as the binding site for U1A protein. When U1A protein was bound to the portion of the chimeric RNA containing its binding site, we obtained independent alignment of TAR by exploiting the physical chemical characteristics of this protein. This technique can allow the extraction of new information on RNA dynamics, which is particularly important for time scales not covered by relaxation methods where important RNA motions occur.

On the interplay between mathematics and biology: hallmarks toward a new systems biology.

Science.gov (United States)

Bellomo, Nicola; Elaiw, Ahmed; Althiabi, Abdullah M; Alghamdi, Mohammed Ali

2015-03-01

This paper proposes a critical analysis of the existing literature on mathematical tools developed toward systems biology approaches and, out of this overview, develops a new approach whose main features can be briefly summarized as follows: derivation of mathematical structures suitable to capture the complexity of biological, hence living, systems, modeling, by appropriate mathematical tools, Darwinian type dynamics, namely mutations followed by selection and evolution. Moreover, multiscale methods to move from genes to cells, and from cells to tissue are analyzed in view of a new systems biology approach. Copyright © 2014 Elsevier B.V. All rights reserved.

The dynamic ocean biological pump: Insights from a global compilation of particulate organic carbon, CaCO3, and opal concentration profiles from the mesopelagic

Science.gov (United States)

Lam, Phoebe J.; Doney, Scott C.; Bishop, James K. B.

2011-09-01

We have compiled a global data set of 62 open ocean profiles of particulate organic carbon (POC), CaCO3, and opal concentrations collected by large volume in situ filtration in the upper 1000 m over the last 30 years. We define concentration-based metrics for the strength (POC concentration at depth) and efficiency (attenuation of POC with depth in the mesopelagic) of the biological pump. We show that the strength and efficiency of the biological pump are dynamic and are characterized by a regime of constant and high transfer efficiency at low to moderate surface POC and a bloom regime where the height of the bloom is characterized by a weak deep biological pump and low transfer efficiency. The variability in POC attenuation length scale manifests in a clear decoupling between the strength of the shallow biological pump (e.g., POC at the export depth) and the strength of the deep biological pump (POC at 500 m). We suggest that the paradigm of diatom-driven export production is driven by a too restrictive perspective on upper mesopelagic dynamics. Indeed, our full mesopelagic analysis suggests that large, blooming diatoms have low transfer efficiency and thus may not export substantially to depth; rather, our analysis suggests that ecosystems characterized by smaller cells and moderately high %CaCO3 have a high mesopelagic transfer efficiency and can have higher POC concentrations in the deep mesopelagic even with relatively low surface or near-surface POC. This has negative implications for the carbon sequestration prospects of deliberate iron fertilization.

Recommendations for designing and conducting veterinary clinical pathology biologic variation studies.

Science.gov (United States)

Freeman, Kathleen P; Baral, Randolph M; Dhand, Navneet K; Nielsen, Søren Saxmose; Jensen, Asger L

2017-06-01

The recent creation of a veterinary clinical pathology biologic variation website has highlighted the need to provide recommendations for future studies of biologic variation in animals in order to help standardize and improve the quality of published information and to facilitate review and selection of publications as standard references. The following recommendations are provided in the format and order commonly found in veterinary publications. A checklist is provided to aid in planning, implementing, and evaluating veterinary studies on biologic variation (Appendix S1). These recommendations provide a valuable resource for clinicians, laboratorians, and researchers interested in conducting studies of biologic variation and in determining the quality of studies of biologic variation in veterinary laboratory testing. © 2017 American Society for Veterinary Clinical Pathology.

Biological Indicators in Studies of Earthquake Precursors

Science.gov (United States)

Sidorin, A. Ya.; Deshcherevskii, A. V.

2012-04-01

Time series of data on variations in the electric activity (EA) of four species of weakly electric fish Gnathonemus leopoldianus and moving activity (MA) of two cat-fishes Hoplosternum thoracatum and two groups of Columbian cockroaches Blaberus craniifer were analyzed. The observations were carried out in the Garm region of Tajikistan within the frameworks of the experiments aimed at searching for earthquake precursors. An automatic recording system continuously recorded EA and DA over a period of several years. Hourly means EA and MA values were processed. Approximately 100 different parameters were calculated on the basis of six initial EA and MA time series, which characterize different variations in the EA and DA structure: amplitude of the signal and fluctuations of activity, parameters of diurnal rhythms, correlated changes in the activity of various biological indicators, and others. A detailed analysis of the statistical structure of the total array of parametric time series obtained in the experiment showed that the behavior of all animals shows a strong temporal variability. All calculated parameters are unstable and subject to frequent changes. A comparison of the data obtained with seismicity allow us to make the following conclusions: (1) The structure of variations in the studied parameters is represented by flicker noise or even a more complex process with permanent changes in its characteristics. Significant statistics are required to prove the cause-and-effect relationship of the specific features of such time series with seismicity. (2) The calculation of the reconstruction statistics in the EA and MA series structure demonstrated an increase in their frequency in the last hours or a few days before the earthquake if the hypocenter distance is comparable to the source size. Sufficiently dramatic anomalies in the behavior of catfishes and cockroaches (changes in the amplitude of activity variation, distortions of diurnal rhythms, increase in the

Mathematical models in biology bringing mathematics to life

CERN Document Server

Ferraro, Maria; Guarracino, Mario

2015-01-01

This book presents an exciting collection of contributions based on the workshop “Bringing Maths to Life” held October 27-29, 2014 in Naples, Italy.  The state-of-the art research in biology and the statistical and analytical challenges facing huge masses of data collection are treated in this Work. Specific topics explored in depth surround the sessions and special invited sessions of the workshop and include genetic variability via differential expression, molecular dynamics and modeling, complex biological systems viewed from quantitative models, and microscopy images processing, to name several. In depth discussions of the mathematical analysis required to extract insights from complex bodies of biological datasets, to aid development in the field novel algorithms, methods and software tools for genetic variability, molecular dynamics, and complex biological systems are presented in this book. Researchers and graduate students in biology, life science, and mathematics/statistics will find the content...

Pattern dynamics of the reaction-diffusion immune system.

Science.gov (United States)

Zheng, Qianqian; Shen, Jianwei; Wang, Zhijie

2018-01-01

In this paper, we will investigate the effect of diffusion, which is ubiquitous in nature, on the immune system using a reaction-diffusion model in order to understand the dynamical behavior of complex patterns and control the dynamics of different patterns. Through control theory and linear stability analysis of local equilibrium, we obtain the optimal condition under which the system loses stability and a Turing pattern occurs. By combining mathematical analysis and numerical simulation, we show the possible patterns and how these patterns evolve. In addition, we establish a bridge between the complex patterns and the biological mechanism using the results from a previous study in Nature Cell Biology. The results in this paper can help us better understand the biological significance of the immune system.

Microfluidic Technologies for Synthetic Biology

Directory of Open Access Journals (Sweden)

Sung Kuk Lee

2011-06-01

Full Text Available Microfluidic technologies have shown powerful abilities for reducing cost, time, and labor, and at the same time, for increasing accuracy, throughput, and performance in the analysis of biological and biochemical samples compared with the conventional, macroscale instruments. Synthetic biology is an emerging field of biology and has drawn much attraction due to its potential to create novel, functional biological parts and systems for special purposes. Since it is believed that the development of synthetic biology can be accelerated through the use of microfluidic technology, in this review work we focus our discussion on the latest microfluidic technologies that can provide unprecedented means in synthetic biology for dynamic profiling of gene expression/regulation with high resolution, highly sensitive on-chip and off-chip detection of metabolites, and whole-cell analysis.

A systems biology approach to study systemic inflammation.

Science.gov (United States)

Chen, Bor-Sen; Wu, Chia-Chou

2014-01-01

Systemic inflammation needs a precise control on the sequence and magnitude of occurring events. The high throughput data on the host-pathogen interactions gives us an opportunity to have a glimpse on the systemic inflammation. In this article, a dynamic Candida albicans-zebrafish interactive infectious network is built as an example to demonstrate how systems biology approach can be used to study systematic inflammation. In particular, based on microarray data of C. albicans and zebrafish during infection, the hyphal growth, zebrafish, and host-pathogen intercellular PPI networks were combined to form an integrated infectious PPI network that helps us understand the systematic mechanisms underlying the pathogenicity of C. albicans and the immune response of the host. The signaling pathways for morphogenesis and hyphal growth of C. albicans were 2 significant interactions found in the intercellular PPI network. Two cellular networks were also developed corresponding to the different infection stages (adhesion and invasion), and then compared with each other to identify proteins to gain more insight into the pathogenic role of hyphal development in the C. albicans infection process. Important defense-related proteins in zebrafish were predicted using the same approach. This integrated network consisting of intercellular invasion and cellular defense processes during infection can improve medical therapies and facilitate development of new antifungal drugs.

An Axiomatic Representation of System Dynamics

CERN Document Server

Baianu, I

2004-01-01

An axiomatic representation of system dynamics is introduced in terms of categories, functors, organismal supercategories, limits and colimits of diagrams. Specific examples are considered in Complex Systems Biology, such as ribosome biogenesis and Hormonal Control in human subjects. "Fuzzy" Relational Structures are also proposed for flexible representations of biological system dynamics and organization.

DMPD: Lysophospholipid receptors: signaling and biology. [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available 15189145 Lysophospholipid receptors: signaling and biology. Ishii I, Fukushima N, Y...e X, Chun J. Annu Rev Biochem. 2004;73:321-54. (.png) (.svg) (.html) (.csml) Show Lysophospholipid receptors...: signaling and biology. PubmedID 15189145 Title Lysophospholipid receptors: signaling and biology. Authors

A Comparative Study of Biologically Inspired Walking Gaits through Waypoint Navigation

Directory of Open Access Journals (Sweden)

Umar Asif

2011-01-01

Full Text Available This paper investigates the locomotion of a walking robot by delivering a comparative study of three different biologically inspired walking gaits, namely: tripod, ripple, and wave, in terms of ground slippage they experience while walking. The objective of this study is to identify the gait model which experiences the minimum slippage while walking on a ground with a specific coefficient of friction. To accomplish this feat, the robot is steered over a reference path using a waypoint navigation algorithm, and the divergence of the robot from the reference path is investigated in terms of slip errors. Experiments are conducted through closed-loop simulations using an open dynamics engine which emphasizes the fact that due to uneven and unsymmetrical distribution of payload in tripod and ripple gait models, the robot experiences comparatively larger drift in these gaits than when using the wave gait model in which the distribution of payload is even and symmetrical on both sides of the robot body. The paper investigates this phenomenon on the basis of force distribution of supporting legs in each gait model.

The Integrin Receptor in Biologically Relevant Bilayers

DEFF Research Database (Denmark)

Kalli, Antreas C.; Róg, Tomasz; Vattulainen, Ilpo

2017-01-01

/talin complex was inserted in biologically relevant bilayers that resemble the cell plasma membrane containing zwitterionic and charged phospholipids, cholesterol and sphingolipids to study the dynamics of the integrin receptor and its effect on bilayer structure and dynamics. The results of this study...... demonstrate the dynamic nature of the integrin receptor and suggest that the presence of the integrin receptor alters the lipid organization between the two leaflets of the bilayer. In particular, our results suggest elevated density of cholesterol and of phosphatidylserine lipids around the integrin....../talin complex and a slowing down of lipids in an annulus of ~30 Å around the protein due to interactions between the lipids and the integrin/talin F2–F3 complex. This may in part regulate the interactions of integrins with other related proteins or integrin clustering thus facilitating signal transduction...

Soil and terrestrial biology studies

International Nuclear Information System (INIS)

Anon.

1976-01-01

Soil and terrestrial biology studies focused on developing an understanding of the uptake of gaseous substances from the atmosphere by plants, biodegradation of oil, and the movement of Pu in the terrestrial ecosystems of the southeastern United States. Mathematical models were developed for SO 2 and tritium uptake from the atmosphere by plants; the uptake of tritium by soil microorganisms was measured; and the relationships among the Pu content of soil, plants, and animals of the Savannah River Plant area were studied. Preliminary results are reported for studies on the biodegradation of waste oil on soil surfaces

Biological soil crusts across disturbance–recovery scenarios: effect of grazing regime on community dynamics.

Science.gov (United States)

Concostrina-Zubiri, L; Huber-Sannwald, E; Martínez, I; Flores Flores, J L; Reyes-Agüero, J A; Escude, A; Belnap, J

Grazing represents one of the most common disturbances in drylands worldwide, affecting both ecosystem structure and functioning. Despite the efforts to understand the nature and magnitude of grazing effects on ecosystem components and processes, contrasting results continue to arise. This is particularly remarkable for the biological soil crust (BSC) communities (i.e., cyanobacteria, lichens, and bryophytes), which play an important role in soil dynamics. Here we evaluated simultaneously the effect of grazing impact on BSC communities (resistance) and recovery after livestock exclusion (resilience) in a semiarid grassland of Central Mexico. In particular, we examined BSC species distribution, species richness, taxonomical group cover (i.e., cyanobacteria, lichen, bryophyte), and composition along a disturbance gradient with different grazing regimes (low, medium, high impact) and along a recovery gradient with differently aged livestock exclosures (short-, medium-, long-term exclusion). Differences in grazing impact and time of recovery from grazing both resulted in slight changes in species richness; however, there were pronounced shifts in species composition and group cover. We found we could distinguish four highly diverse and dynamic BSC species groups: (1) species with high resistance and resilience to grazing, (2) species with high resistance but low resilience, (3) species with low resistance but high resilience, and (4) species with low resistance and resilience. While disturbance resulted in a novel diversity configuration, which may profoundly affect ecosystem functioning, we observed that 10 years of disturbance removal did not lead to the ecosystem structure found after 27 years of recovery. These findings are an important contribution to our understanding of BCS dynamics from a species and community perspective placed in a land use change context.

Biological soil crusts across disturbance-recovery scenarios: effect of grazing regime on community dynamics

Science.gov (United States)

Concostrina-Zubiri, L.; Huber-Sannwald, E.; Martínez, I.; Flores Flores, J. L.; Reyes-Agüero, J. A.; Escudero, A.; Belnap, Jayne

2014-01-01

Grazing represents one of the most common disturbances in drylands worldwide, affecting both ecosystem structure and functioning. Despite the efforts to understand the nature and magnitude of grazing effects on ecosystem components and processes, contrasting results continue to arise. This is particularly remarkable for the biological soil crust (BSC) communities (i.e., cyanobacteria, lichens, and bryophytes), which play an important role in soil dynamics. Here we evaluated simultaneously the effect of grazing impact on BSC communities (resistance) and recovery after livestock exclusion (resilience) in a semiarid grassland of Central Mexico. In particular, we examined BSC species distribution, species richness, taxonomical group cover (i.e., cyanobacteria, lichen, bryophyte), and composition along a disturbance gradient with different grazing regimes (low, medium, high impact) and along a recovery gradient with differently aged livestock exclosures (short-, medium-, long-term exclusion). Differences in grazing impact and time of recovery from grazing both resulted in slight changes in species richness; however, there were pronounced shifts in species composition and group cover. We found we could distinguish four highly diverse and dynamic BSC species groups: (1) species with high resistance and resilience to grazing, (2) species with high resistance but low resilience, (3) species with low resistance but high resilience, and (4) species with low resistance and resilience. While disturbance resulted in a novel diversity configuration, which may profoundly affect ecosystem functioning, we observed that 10 years of disturbance removal did not lead to the ecosystem structure found after 27 years of recovery. These findings are an important contribution to our understanding of BCS dynamics from a species and community perspective placed in a land use change context.

Studying Dynamics in Business Networks

DEFF Research Database (Denmark)

Andersen, Poul Houman; Anderson, Helen; Havila, Virpi

1998-01-01

This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland......This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland...

Modeling systems-level dynamics: Understanding without mechanistic explanation in integrative systems biology.

Science.gov (United States)

MacLeod, Miles; Nersessian, Nancy J

2015-02-01

In this paper we draw upon rich ethnographic data of two systems biology labs to explore the roles of explanation and understanding in large-scale systems modeling. We illustrate practices that depart from the goal of dynamic mechanistic explanation for the sake of more limited modeling goals. These processes use abstract mathematical formulations of bio-molecular interactions and data fitting techniques which we call top-down abstraction to trade away accurate mechanistic accounts of large-scale systems for specific information about aspects of those systems. We characterize these practices as pragmatic responses to the constraints many modelers of large-scale systems face, which in turn generate more limited pragmatic non-mechanistic forms of understanding of systems. These forms aim at knowledge of how to predict system responses in order to manipulate and control some aspects of them. We propose that this analysis of understanding provides a way to interpret what many systems biologists are aiming for in practice when they talk about the objective of a "systems-level understanding." Copyright © 2014 Elsevier Ltd. All rights reserved.

2nd International Symposium "Atomic Cluster Collisions : Structure and Dynamics from the Nuclear to the Biological Scale"

CERN Document Server

Solov'yov, Andrey; ISACC 2007; Latest advances in atomic cluster collisions

2008-01-01

This book presents a 'snapshot' of the most recent and significant advances in the field of cluster physics. It is a comprehensive review based on contributions by the participants of the 2nd International Symposium on Atomic Cluster Collisions (ISACC 2007) held in July 19-23, 2007 at GSI, Darmstadt, Germany. The purpose of the Symposium is to promote the growth and exchange of scientific information on the structure and properties of nuclear, atomic, molecular, biological and complex cluster systems studied by means of photonic, electronic, heavy particle and atomic collisions. Particular attention is devoted to dynamic phenomena, many-body effects taking place in cluster systems of a different nature - these include problems of fusion and fission, fragmentation, collective electron excitations, phase transitions, etc.Both the experimental and theoretical aspects of cluster physics, uniquely placed between nuclear physics on the one hand and atomic, molecular and solid state physics on the other, are discuss...

Systems Biology as an Integrated Platform for Bioinformatics, Systems Synthetic Biology, and Systems Metabolic Engineering

Science.gov (United States)

Chen, Bor-Sen; Wu, Chia-Chou

2013-01-01

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering. PMID:24709875

Systems Biology as an Integrated Platform for Bioinformatics, Systems Synthetic Biology, and Systems Metabolic Engineering

Directory of Open Access Journals (Sweden)

Bor-Sen Chen

2013-10-01

Full Text Available Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

Fast "Feast/Famine" Cycles for Studying Microbial Physiology Under Dynamic Conditions: A Case Study with Saccharomyces cerevisiae.

Science.gov (United States)

Suarez-Mendez, Camilo A; Sousa, Andre; Heijnen, Joseph J; Wahl, Aljoscha

2014-05-15

Microorganisms are constantly exposed to rapidly changing conditions, under natural as well as industrial production scale environments, especially due to large-scale substrate mixing limitations. In this work, we present an experimental approach based on a dynamic feast/famine regime (400 s) that leads to repetitive cycles with moderate changes in substrate availability in an aerobic glucose cultivation of Saccharomyces cerevisiae. After a few cycles, the feast/famine produced a stable and repetitive pattern with a reproducible metabolic response in time, thus providing a robust platform for studying the microorganism's physiology under dynamic conditions. We found that the biomass yield was slightly reduced (-5%) under the feast/famine regime, while the averaged substrate and oxygen consumption as well as the carbon dioxide production rates were comparable. The dynamic response of the intracellular metabolites showed specific differences in comparison to other dynamic experiments (especially stimulus-response experiments, SRE). Remarkably, the frequently reported ATP paradox observed in single pulse experiments was not present during the repetitive perturbations applied here. We found that intracellular dynamic accumulations led to an uncoupling of the substrate uptake rate (up to 9-fold change at 20 s.) Moreover, the dynamic profiles of the intracellular metabolites obtained with the feast/famine suggest the presence of regulatory mechanisms that resulted in a delayed response. With the feast famine setup many cellular states can be measured at high frequency given the feature of reproducible cycles. The feast/famine regime is thus a versatile platform for systems biology approaches, which can help us to identify and investigate metabolite regulations under realistic conditions (e.g., large-scale bioreactors or natural environments).

Fluctuating Thermodynamics for Biological Processes

Science.gov (United States)

Ham, Sihyun

Because biomolecular processes are largely under thermodynamic control, dynamic extension of thermodynamics is necessary to uncover the mechanisms and driving factors of fluctuating processes. The fluctuating thermodynamics technology presented in this talk offers a practical means for the thermodynamic characterization of conformational dynamics in biomolecules. The use of fluctuating thermodynamics has the potential to provide a comprehensive picture of fluctuating phenomena in diverse biological processes. Through the application of fluctuating thermodynamics, we provide a thermodynamic perspective on the misfolding and aggregation of the various proteins associated with human diseases. In this talk, I will present the detailed concepts and applications of the fluctuating thermodynamics technology for elucidating biological processes. This work was supported by Samsung Science and Technology Foundation under Project Number SSTF-BA1401-13.

Nonlinear dynamics based digital logic and circuits.

Science.gov (United States)

Kia, Behnam; Lindner, John F; Ditto, William L

2015-01-01

We discuss the role and importance of dynamics in the brain and biological neural networks and argue that dynamics is one of the main missing elements in conventional Boolean logic and circuits. We summarize a simple dynamics based computing method, and categorize different techniques that we have introduced to realize logic, functionality, and programmability. We discuss the role and importance of coupled dynamics in networks of biological excitable cells, and then review our simple coupled dynamics based method for computing. In this paper, for the first time, we show how dynamics can be used and programmed to implement computation in any given base, including but not limited to base two.

Structured population models in biology and epidemiology

CERN Document Server

Ruan, Shigui

2008-01-01

This book consists of six chapters written by leading researchers in mathematical biology. These chapters present recent and important developments in the study of structured population models in biology and epidemiology. Topics include population models structured by age, size, and spatial position; size-structured models for metapopulations, macroparasitc diseases, and prion proliferation; models for transmission of microparasites between host populations living on non-coincident spatial domains; spatiotemporal patterns of disease spread; method of aggregation of variables in population dynamics; and biofilm models. It is suitable as a textbook for a mathematical biology course or a summer school at the advanced undergraduate and graduate level. It can also serve as a reference book for researchers looking for either interesting and specific problems to work on or useful techniques and discussions of some particular problems.

Computerised modelling for developmental biology : an exploration with case studies

NARCIS (Netherlands)

Bertens, Laura M.F.

2012-01-01

Many studies in developmental biology rely on the construction and analysis of models. This research presents a broad view of modelling approaches for developmental biology, with a focus on computational methods. An overview of modelling techniques is given, followed by several case studies. Using

Photo fragmentation dynamics of small argon clusters and biological molecular: new tools by trapping and vectorial correlation

International Nuclear Information System (INIS)

Lepere, V.

2006-09-01

The present work concerns the building up of a complex set-up whose aim being the investigation of the photo fragmentation of ionised clusters and biological molecules. This new tool is based on the association of several techniques. Two ion sources are available: clusters produced in a supersonic beam are ionised by 70 eV electrons while ions of biological interest are produced in an 'electro-spray'. Ro-vibrational cooling is achieved in a 'Zajfman' electrostatic ion trap. The lifetime of ions can also be measured using the trap. Two types of lasers are used to excite the ionised species: the femtosecond laser available at the ELYSE facilities and a nanosecond laser. Both lasers have a repetition rate of 1 kHz. The neutral and ionised fragments are detected in coincidence using a sophisticated detection system allowing time and localisation of the various fragments to be determined. With such a tool, I was able to investigate in details the fragmentation dynamics of ionised clusters and bio-molecules. The first experiments deal with the measurement of the lifetime of the Ar 2+ dimer II(1/2)u metastable state. The relative population of this state was also determined. The Ar 2+ and Ar 3+ photo-fragmentation was then studied and electronic transitions responsible for their dissociation identified. The detailed analysis of our data allowed to distinguish the various fragmentation mechanisms. Finally, a preliminary investigation of the protonated tryptamine fragmentation is presented. (author)

Understanding dynamics using sensitivity analysis: caveat and solution

Science.gov (United States)

2011-01-01

Background Parametric sensitivity analysis (PSA) has become one of the most commonly used tools in computational systems biology, in which the sensitivity coefficients are used to study the parametric dependence of biological models. As many of these models describe dynamical behaviour of biological systems, the PSA has subsequently been used to elucidate important cellular processes that regulate this dynamics. However, in this paper, we show that the PSA coefficients are not suitable in inferring the mechanisms by which dynamical behaviour arises and in fact it can even lead to incorrect conclusions. Results A careful interpretation of parametric perturbations used in the PSA is presented here to explain the issue of using this analysis in inferring dynamics. In short, the PSA coefficients quantify the integrated change in the system behaviour due to persistent parametric perturbations, and thus the dynamical information of when a parameter perturbation matters is lost. To get around this issue, we present a new sensitivity analysis based on impulse perturbations on system parameters, which is named impulse parametric sensitivity analysis (iPSA). The inability of PSA and the efficacy of iPSA in revealing mechanistic information of a dynamical system are illustrated using two examples involving switch activation. Conclusions The interpretation of the PSA coefficients of dynamical systems should take into account the persistent nature of parametric perturbations involved in the derivation of this analysis. The application of PSA to identify the controlling mechanism of dynamical behaviour can be misleading. By using impulse perturbations, introduced at different times, the iPSA provides the necessary information to understand how dynamics is achieved, i.e. which parameters are essential and when they become important. PMID:21406095

Physics of biological membranes

Science.gov (United States)

Mouritsen, Ole G.

The biological membrane is a complex system consisting of an aqueous biomolecular planar aggregate of predominantly lipid and protein molecules. At physiological temperatures, the membrane may be considered a thin (˜50Å) slab of anisotropic fluid characterized by a high lateral mobility of the various molecular components. A substantial fraction of biological activity takes place in association with membranes. As a very lively piece of condensed matter, the biological membrane is a challenging research topic for both the experimental and theoretical physicists who are facing a number of fundamental physical problems including molecular self-organization, macromolecular structure and dynamics, inter-macromolecular interactions, structure-function relationships, transport of energy and matter, and interfacial forces. This paper will present a brief review of recent theoretical and experimental progress on such problems, with special emphasis on lipid bilayer structure and dynamics, lipid phase transitions, lipid-protein and lipid-cholesterol interactions, intermembrane forces, and the physical constraints imposed on biomembrane function and evolution. The paper advocates the dual point of view that there are a number of interesting physics problems in membranology and, at the same time, that the physical properties of biomembranes are important regulators of membrane function.

Neutron structural biology

International Nuclear Information System (INIS)

Niimura, Nobuo

1999-01-01

Neutron structural biology will be one of the most important fields in the life sciences which will interest human beings in the 21st century because neutrons can provide not only the position of hydrogen atoms in biological macromolecules but also the dynamic molecular motion of hydrogen atoms and water molecules. However, there are only a few examples experimentally determined at present because of the lack of neutron source intensity. Next generation neutron source scheduled in JAERI (Performance of which is 100 times better than that of JRR-3M) opens the life science of the 21st century. (author)

Neutrons in Biology. A satellite meeting of the IUPAB/EBSA biophysics congress

Energy Technology Data Exchange (ETDEWEB)

Koji, Yoshida; Longeville, St.; Motomu, Tanaka; Blackledge, M.; Ebel, Ch.; Cooper, J.B.; Curmi, P.; Ferrand, M.; Gutberlet, T.; Huang, Huey Hang; Haub, T.; Mitsuhiro, Hirai; Geoff, Kneale; Langan, P.; Masahisa, Wada; Junji, Sugiyama; Yoshiharu, Nishiyama; Chanzy, H.; Leckband, D.; Meilleur, F.; Nawroth, Th.; Paciaroni, A.; Parak, F.; Gaede, H.C.; Soubias, O.; Luckett, K.M.; Polozov, I.V.; Wong, K.K.Y.; Yeliseev, A.A.; Gawrisch, K.; Deme, B.; Marchal, D.; Hanson, L.; Podjarny, A.; Mitschler, A.; Hazemann, I.; Blakeley, M.; Dauvergne, M.T.; Meilleur, F.; Budayova-Spano, M.; Van Zandt, M.; Ginell, S.; Joachimiak, A.; Myles, D.; Timmins, P.A.; Pebay-Peyroula, E; Welte, W.; Prince, S.M.; Howard, T.D.; Myles, D.A.A.; Wilkinson, C.; Papiz, M.Z.; Freer, A.A.; Cogdell, R.J.; Isaacs, N.W.; Papiz, M.Z.; Prince, S.M.; Howard, T.D.; Cogdell, R.J.; Isaacs, N.W.; Rheinstaedter, M.; Sapede, D.; Svergun, D.; Tarek, M.; Tehei, M.; Trewhella, J.; Watts, A.; Zaccai, G.J

2005-07-01

This meeting focussed on the study of the structure and dynamics of biological molecules, with particular emphasis on neutron and complementary methods as well as related enabling technologies. The program covered biological problems that are being addressed by neutron scattering and those where there is the potential to do so in the future. This document provides the abstracts of the different presentations. (A.L.B.)

Neutrons in Biology. A satellite meeting of the IUPAB/EBSA biophysics congress

International Nuclear Information System (INIS)

Koji, Yoshida; Longeville, St.; Motomu, Tanaka; Blackledge, M.; Ebel, Ch.; Cooper, J.B.; Curmi, P.; Ferrand, M.; Gutberlet, T.; Huang, Huey Hang; Haub, T.; Mitsuhiro, Hirai; Geoff, Kneale; Langan, P.; Masahisa, Wada; Junji, Sugiyama; Yoshiharu, Nishiyama; Chanzy, H.; Leckband, D.; Meilleur, F.; Nawroth, Th.; Paciaroni, A.; Parak, F.; Gaede, H.C.; Soubias, O.; Luckett, K.M.; Polozov, I.V.; Wong, K.K.Y.; Yeliseev, A.A.; Gawrisch, K.; Deme, B.; Marchal, D.; Hanson, L.; Podjarny, A.; Mitschler, A.; Hazemann, I.; Blakeley, M.; Dauvergne, M.T.; Meilleur, F.; Budayova-Spano, M.; Van Zandt, M.; Ginell, S.; Joachimiak, A.; Myles, D.; Timmins, P.A.; Pebay-Peyroula, E; Welte, W.; Prince, S.M.; Howard, T.D.; Myles, D.A.A.; Wilkinson, C.; Papiz, M.Z.; Freer, A.A.; Cogdell, R.J.; Isaacs, N.W.; Papiz, M.Z.; Prince, S.M.; Howard, T.D.; Cogdell, R.J.; Isaacs, N.W.; Rheinstaedter, M.; Sapede, D.; Svergun, D.; Tarek, M.; Tehei, M.; Trewhella, J.; Watts, A.; Zaccai, G.J.

2005-01-01

This meeting focussed on the study of the structure and dynamics of biological molecules, with particular emphasis on neutron and complementary methods as well as related enabling technologies. The program covered biological problems that are being addressed by neutron scattering and those where there is the potential to do so in the future. This document provides the abstracts of the different presentations. (A.L.B.)

Adsorption properties of biologically active derivatives of quaternary ammonium surfactants and their mixtures at aqueous/air interface II. Dynamics of adsorption, micelles dissociation and cytotoxicity of QDLS.

Science.gov (United States)

Rojewska, Monika; Prochaska, Krystyna; Olejnik, Anna; Rychlik, Joanna

2014-07-01

The main aim of our study was analysis of adsorption dynamics of mixtures containing quaternary derivatives of lysosomotropic substance (QDLS). Two types of equimolar mixtures were considered: the ones containing two derivatives of lysosomotropic substances (DMALM-12 and DMGM-12) as well as the catanionic mixtures i.e. the systems containing QDLS and DBSNa. Dynamic surface tension measurements of surfactant mixtures were made. The results suggested that the diffusivity of the mixed system could be treated as the average value of rates of diffusion of individual components, micelles and ion pairs, which are present in the mixtures studied. Moreover, an attempt was made to explain the influence of the presence of micelles in the mixtures on their adsorption dynamics. The compounds examined show interesting biological properties which can be useful, especially for drug delivery in medical treatment. In vitro cytotoxic activities of the mixtures studied towards human cancer cells were evaluated. Most of the mixtures showed a high antiproliferative potential, especially the ones containing DMALM-12. Each cancer cell line used demonstrated different sensitivity to the same dose of the mixtures tested. Copyright © 2014 Elsevier B.V. All rights reserved.

Dimension reduction for stochastic dynamical systems forced onto a manifold by large drift: a constructive approach with examples from theoretical biology

International Nuclear Information System (INIS)

Parsons, Todd L; Rogers, Tim

2017-01-01

Systems composed of large numbers of interacting agents often admit an effective coarse-grained description in terms of a multidimensional stochastic dynamical system, driven by small-amplitude intrinsic noise. In applications to biological, ecological, chemical and social dynamics it is common for these models to posses quantities that are approximately conserved on short timescales, in which case system trajectories are observed to remain close to some lower-dimensional subspace. Here, we derive explicit and general formulae for a reduced-dimension description of such processes that is exact in the limit of small noise and well-separated slow and fast dynamics. The Michaelis–Menten law of enzyme-catalysed reactions, and the link between the Lotka–Volterra and Wright–Fisher processes are explored as a simple worked examples. Extensions of the method are presented for infinite dimensional systems and processes coupled to non-Gaussian noise sources. (paper)

Dimension reduction for stochastic dynamical systems forced onto a manifold by large drift: a constructive approach with examples from theoretical biology

Science.gov (United States)

Parsons, Todd L.; Rogers, Tim

2017-10-01

Systems composed of large numbers of interacting agents often admit an effective coarse-grained description in terms of a multidimensional stochastic dynamical system, driven by small-amplitude intrinsic noise. In applications to biological, ecological, chemical and social dynamics it is common for these models to posses quantities that are approximately conserved on short timescales, in which case system trajectories are observed to remain close to some lower-dimensional subspace. Here, we derive explicit and general formulae for a reduced-dimension description of such processes that is exact in the limit of small noise and well-separated slow and fast dynamics. The Michaelis-Menten law of enzyme-catalysed reactions, and the link between the Lotka-Volterra and Wright-Fisher processes are explored as a simple worked examples. Extensions of the method are presented for infinite dimensional systems and processes coupled to non-Gaussian noise sources.

Stochastic Methods in Biology

CERN Document Server

Kallianpur, Gopinath; Hida, Takeyuki

1987-01-01

The use of probabilistic methods in the biological sciences has been so well established by now that mathematical biology is regarded by many as a distinct dis­ cipline with its own repertoire of techniques. The purpose of the Workshop on sto­ chastic methods in biology held at Nagoya University during the week of July 8-12, 1985, was to enable biologists and probabilists from Japan and the U. S. to discuss the latest developments in their respective fields and to exchange ideas on the ap­ plicability of the more recent developments in stochastic process theory to problems in biology. Eighteen papers were presented at the Workshop and have been grouped under the following headings: I. Population genetics (five papers) II. Measure valued diffusion processes related to population genetics (three papers) III. Neurophysiology (two papers) IV. Fluctuation in living cells (two papers) V. Mathematical methods related to other problems in biology, epidemiology, population dynamics, etc. (six papers) An important f...

Dynamical systems, attractors, and neural circuits.

Science.gov (United States)

Miller, Paul

2016-01-01

Biology is the study of dynamical systems. Yet most of us working in biology have limited pedagogical training in the theory of dynamical systems, an unfortunate historical fact that can be remedied for future generations of life scientists. In my particular field of systems neuroscience, neural circuits are rife with nonlinearities at all levels of description, rendering simple methodologies and our own intuition unreliable. Therefore, our ideas are likely to be wrong unless informed by good models. These models should be based on the mathematical theories of dynamical systems since functioning neurons are dynamic-they change their membrane potential and firing rates with time. Thus, selecting the appropriate type of dynamical system upon which to base a model is an important first step in the modeling process. This step all too easily goes awry, in part because there are many frameworks to choose from, in part because the sparsely sampled data can be consistent with a variety of dynamical processes, and in part because each modeler has a preferred modeling approach that is difficult to move away from. This brief review summarizes some of the main dynamical paradigms that can arise in neural circuits, with comments on what they can achieve computationally and what signatures might reveal their presence within empirical data. I provide examples of different dynamical systems using simple circuits of two or three cells, emphasizing that any one connectivity pattern is compatible with multiple, diverse functions.

Two Dogmas of Biology

Directory of Open Access Journals (Sweden)

Leonore Fleming

2017-01-01

Full Text Available The problem with reductionism in biology is not the reduction, but the implicit attitude of determinism that usually accompanies it. Methodological reductionism is supported by deterministic beliefs, but making such a connection is problematic when it is based on an idea of determinism as fixed predictability. Conflating determinism with predictability gives rise to inaccurate models that overlook the dynamic complexity of our world, as well as ignore our epistemic limitations when we try to model it. Furthermore, the assumption of a strictly deterministic framework is unnecessarily hindering to biology. By removing the dogma of determinism, biological methods, including reductive methods, can be expanded to include stochastic models and probabilistic interpretations. Thus, the dogma of reductionism can be saved once its ties with determinism are severed. In this paper, I analyze two problems that have faced molecular biology for the last 50 years—protein folding and cancer. Both cases demonstrate the long influence of reductionism and determinism on molecular biology, as well as how abandoning determinism has opened the door to more probabilistic and unconstrained reductive methods in biology.

Biological Studies of Posttraumatic Stress Disorder

Science.gov (United States)

Pitman, Roger K.; Rasmusson, Ann M.; Koenen, Karestan C.; Shin, Lisa M.; Orr, Scott P.; Gilbertson, Mark W.; Milad, Mohammed R.; Liberzon, Israel

2016-01-01

Preface Posttraumatic stress disorder (PTSD) is the only major mental disorder for which a cause is considered to be known, viz., an event that involves threat to the physical integrity of oneself or others and induces a response of intense fear, helplessness, or horror. Although PTSD is still largely regarded as a psychological phenomenon, over the past three decades the growth of the biological PTSD literature has been explosive, and thousands of references now exist. Ultimately, the impact of an environmental event, such as a psychological trauma, must be understood at organic, cellular, and molecular levels. The present review attempts to present the current state of this understanding, based upon psychophysiological, structural and functional neuroimaging, endocrinological, genetic, and molecular biological studies in humans and in animal models. PMID:23047775

Cholera dynamics with Bacteriophage infection: A mathematical study

International Nuclear Information System (INIS)

Misra, A.K.; Gupta, Alok; Venturino, Ezio

2016-01-01

Highlights: • A mathematical model for the biological control of cholera has been proposed. • The feasibility and stability of all the equilibria have been investigated. • The ODE model is found to exhibit Hopf-bifurcation. • Conditions of global asymptotic stability have been obtained. • The impact of important parameters on cholera spread has been shown. - Abstract: Mathematical modeling of waterborne diseases, such as cholera, including a biological control using Bacteriophage viruses in the aquatic reservoirs is of great relevance in epidemiology. In this paper, our aim is twofold: at first, to understand the cholera dynamics in the region around a water body; secondly, to understand how the spread of Bacteriophage infection in the cholera bacterium V. cholerae controls the disease in the human population. For this purpose, we modify the model proposed by Codeço, for the spread of cholera infection in human population and the one proposed by Beretta and Kuang, for the spread of Bacteriophage infection in the bacteria population [1, 2]. We first discuss the feasibility and local asymptotic stability of all the possible equilibria of the proposed model. Further, in the numerical investigation, we have found that the parameter ϕ, called the phage adsorption rate, plays an important role. There is a critical value, ϕ c , at which the model possess Hopf-bifurcation. For lower values than ϕ c , the equilibrium E * is unstable and periodic solutions are observed, while above ϕ c , the equilibrium E * is locally asymptotically stable, and further shown to be also globally asymptotically stable. We investigate the effect of the various parameters on the dynamics of the infected humans by means of numerical simulations.

Dissipative structures and biological rhythms

Science.gov (United States)

Goldbeter, Albert

2017-10-01

Sustained oscillations abound in biological systems. They occur at all levels of biological organization over a wide range of periods, from a fraction of a second to years, and with a variety of underlying mechanisms. They control major physiological functions, and their dysfunction is associated with a variety of physiological disorders. The goal of this review is (i) to give an overview of the main rhythms observed at the cellular and supracellular levels, (ii) to briefly describe how the study of biological rhythms unfolded in the course of time, in parallel with studies on chemical oscillations, (iii) to present the major roles of biological rhythms in the control of physiological functions, and (iv) the pathologies associated with the alteration, disappearance, or spurious occurrence of biological rhythms. Two tables present the main examples of cellular and supracellular rhythms ordered according to their period, and their role in physiology and pathophysiology. Among the rhythms discussed are neural and cardiac rhythms, metabolic oscillations such as those occurring in glycolysis in yeast, intracellular Ca++ oscillations, cyclic AMP oscillations in Dictyostelium amoebae, the segmentation clock that controls somitogenesis, pulsatile hormone secretion, circadian rhythms which occur in all eukaryotes and some bacteria with a period close to 24 h, the oscillatory dynamics of the enzymatic network driving the cell cycle, and oscillations in transcription factors such as NF-ΚB and tumor suppressors such as p53. Ilya Prigogine's concept of dissipative structures applies to temporal oscillations and allows us to unify within a common framework the various rhythms observed at different levels of biological organization, regardless of their period and underlying mechanism.

Entropy for the Complexity of Physiological Signal Dynamics.

Science.gov (United States)

Zhang, Xiaohua Douglas

2017-01-01

Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

An individual-based model of Zebrafish population dynamics accounting for energy dynamics

DEFF Research Database (Denmark)

Beaudouin, Remy; Goussen, Benoit; Piccini, Benjamin

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model...

Chemical structure and dynamics: Annual report 1993

Energy Technology Data Exchange (ETDEWEB)

Colson, S.D.

1994-07-01

The Chemical Structure and Dynamics program responds to the need for a fundamental, molecular-level understanding of chemistry at the wide variety of environmentally-important interfaces. The research program is built around the established relationship between structure, thermodynamics, and kinetics. This research effort continues to evolve into a program of rigorous studies of fundamental molecular processes in model systems (e.g., well-characterized surfaces, single-component solutions, clusters, and biological molecules), and studies of complex systems found in the environment. Experimental studies of molecular and supramolecular structures and thermodynamics are key to understanding the nature of matter, and lead to direct comparison with computational results. Kinetic and mechanistic measurements, combined with real-time dynamics measurements of atomic and molecular motions during chemical reactions, provide for a molecular-level description of chemical reactions. The anticipated results of this work are the achievement of a quantitative understanding of chemical processes at complex interfaces, the development of new techniques for the detection and measurement of species at such interfaces, and the interpretation and extrapolation of the observations in terms of models of interfacial chemistry. The Chemical Structure and Dynamics research program includes five areas described in detail in this report: Reaction mechanisms at solid interfaces; Solution and solution interfaces; Structure and dynamics of biological systems; Analytical methods development; and atmospheric chemistry. Extended abstracts are presented for 23 studies.

A submesoscale coherent vortex in the Ligurian Sea: From dynamical barriers to biological implications

Science.gov (United States)

Bosse, Anthony; Testor, Pierre; Mayot, Nicolas; Prieur, Louis; D'Ortenzio, Fabrizio; Mortier, Laurent; Le Goff, Hervé; Gourcuff, Claire; Coppola, Laurent; Lavigne, Héloïse; Raimbault, Patrick

2017-08-01

In June 2013, a glider equipped with oxygen and fluorescence sensors has been used to extensively sample an anticyclonic Submesoscale Coherent Vortex (SCV) in the Ligurian Sea (NW Mediterranean Sea). Those measurements are complemented by full-depth CTD casts (T, S, and oxygen) and water samples documenting nutrients and phytoplankton pigments within the SCV and outside. The SCV has a very homogeneous core of oxygenated waters between 300 and 1200 m formed 4.5 months earlier during the winter deep convection event. It has a strong dynamical signature with peak velocities at 700 m depth of 13.9 cm s-1 in cyclogeostrophic balance. The eddy has a small radius of 6.2 km corresponding to high Rossby number of -0.45. The vorticity at the eddy center reaches -0.8f. Cross-stream isopycnic diffusion of tracers between the eddy core and the surroundings is found to be very limited due to dynamical barriers set by the SCV associated with a diffusivity coefficient of about 0.2 m2 s-1. The deep core is nutrients-depleted with concentrations of nitrate, phosphate, and silicate, 13-18% lower than the rich surrounding waters. However, the nutriclines are shifted of about 20-50 m toward the surface thus increasing the nutrients availability for phytoplankton. Chlorophyll-a concentrations at the deep chlorophyll maximum are subsequently about twice bigger as compared to outside. Pigments further reveal the predominance of nanophytoplankton inside the eddy and an enhancement of the primary productivity. This study demonstrates the important impact of postconvective SCVs on nutrients distribution and phytoplankton community, as well as on the subsequent primary production and carbon sequestration.Plain Language SummaryDue to harsh meteorological conditions in winter, a few places of the world's ocean experience an intense cooling of their surface waters that start to sink in a process called oceanic deep convection. It is crucial for the functioning of the ocean, but also the marine

Biological sulphide removal from anaerobically treated domestic sewage: reactor performance and microbial community dynamics.

Science.gov (United States)

Garcia, Graziella Patrício Pereira; Diniz, Renata Côrtes Oliveira; Bicalho, Sarah Kinaip; Franco, Vitor Araujo de Souza; Gontijo, Eider Max de Oliveira; Toscano, Rodrigo Argolo; Canhestro, Kenia Oliveira; Santos, Merly Rita Dos; Carmo, Ana Luiza Rodrigues Dias; Lobato, Livia Cristina S; Brandt, Emanuel Manfred F; Chernicharo, Carlos A L; Calabria de Araujo, Juliana

2015-01-01

We developed a biological sulphide oxidation system and evaluated two reactors (shaped similar to the settler compartment of an up-flow anaerobic sludge blanket [UASB] reactor) with different support materials for biomass retention: polypropylene rings and polyurethane foam. The start-up reaction was achieved using microorganisms naturally occurring on the open surface of UASB reactors treating domestic wastewater. Sulphide removal efficiencies of 65% and 90% were achieved with hydraulic retention times (HRTs) of 24 and 12 h, respectively, in both reactors. However, a higher amount of elemental sulphur was formed and accumulated in the biomass from reactor 1 (20 mg S(0) g(-1) VTS) than in that from reactor 2 (2.9 mg S(0) g(-1) VTS) with an HRT of 24 h. Denaturing gradient gel electrophoresis (DGGE) results revealed that the the pink and green biomass that developed in both reactors comprised a diverse bacterial community and had sequences related to phototrophic green and purple-sulphur bacteria such as Chlorobium sp., Chloronema giganteum, and Chromatiaceae. DGGE band patterns also demonstrated that bacterial community was dynamic over time within the same reactor and that different support materials selected for distinct bacterial communities. Taken together, these results indicated that sulphide concentrations of 1-6 mg L(-1) could be efficiently removed from the effluent of a pilot-scale UASB reactor in two sulphide biological oxidation reactors at HRTs of 12 and 24 h, showing the potential for sulphur recovery from anaerobically treated domestic wastewater.

The Implementation of Research-based Learning on Biology Seminar Course in Biology Education Study Program of FKIP UMRAH

Science.gov (United States)

Amelia, T.

2018-04-01

Biology Seminar is a course in Biology Education Study Program of Faculty of Teacher Training and Education University of Maritim Raja Ali Haji (FKIP UMRAH) that requires students to have the ability to apply scientific attitudes, perform scientific writing and undertake scientific publications on a small scale. One of the learning strategies that can drive the achievement of learning outcomes in this course is Research-Based Learning. Research-Based Learning principles are considered in accordance with learning outcomes in Biology Seminar courses and generally in accordance with the purpose of higher education. On this basis, this article which is derived from a qualitative research aims at describing Research-based Learning on Biology Seminar course. Based on a case study research, it was known that Research-Based Learning on Biology Seminar courses is applied through: designing learning activities around contemporary research issues; teaching research methods, techniques and skills explicitly within program; drawing on personal research in designing and teaching courses; building small-scale research activities into undergraduate assignment; and infusing teaching with the values of researchers.

Fast “Feast/Famine” Cycles for Studying Microbial Physiology Under Dynamic Conditions: A Case Study with Saccharomyces cerevisiae

Science.gov (United States)

Suarez-Mendez, Camilo A.; Sousa, Andre; Heijnen, Joseph J.; Wahl, Aljoscha

2014-01-01

Microorganisms are constantly exposed to rapidly changing conditions, under natural as well as industrial production scale environments, especially due to large-scale substrate mixing limitations. In this work, we present an experimental approach based on a dynamic feast/famine regime (400 s) that leads to repetitive cycles with moderate changes in substrate availability in an aerobic glucose cultivation of Saccharomyces cerevisiae. After a few cycles, the feast/famine produced a stable and repetitive pattern with a reproducible metabolic response in time, thus providing a robust platform for studying the microorganism’s physiology under dynamic conditions. We found that the biomass yield was slightly reduced (−5%) under the feast/famine regime, while the averaged substrate and oxygen consumption as well as the carbon dioxide production rates were comparable. The dynamic response of the intracellular metabolites showed specific differences in comparison to other dynamic experiments (especially stimulus-response experiments, SRE). Remarkably, the frequently reported ATP paradox observed in single pulse experiments was not present during the repetitive perturbations applied here. We found that intracellular dynamic accumulations led to an uncoupling of the substrate uptake rate (up to 9-fold change at 20 s.) Moreover, the dynamic profiles of the intracellular metabolites obtained with the feast/famine suggest the presence of regulatory mechanisms that resulted in a delayed response. With the feast famine setup many cellular states can be measured at high frequency given the feature of reproducible cycles. The feast/famine regime is thus a versatile platform for systems biology approaches, which can help us to identify and investigate metabolite regulations under realistic conditions (e.g., large-scale bioreactors or natural environments). PMID:24957030

Development and performance evaluation of a dynamic phantom for biological dosimetry of moving targets

Science.gov (United States)

Gemmel, A.; Bert, C.; Saito, N.; von Neubeck, C.; Iancu, G.; K-Weyrather, W.; Durante, M.; Rietzel, E.

2010-06-01

A dynamic phantom has been developed to allow for measurement of 3D cell survival distributions and the corresponding distributions of the RBE-weighted dose (RBED) in the presence of motion. The phantom consists of two 96-microwell plates holding Chinese hamster ovary cells inside a container filled with culture medium and is placed on a movable stage. Basic biological properties of the phantom were investigated without irradiation and after irradiation with a carbon ion beam, using both a stationary (reference) exposure and exposure during motion of the phantom perpendicular to the beam with beam tracking. There was no statistically significant difference between plating efficiency measured in the microwells with and without motion (0.75) and values reported in the literature. Mean differences between measured and calculated cell survival for these two irradiation modes were within ±5% of the target dose of 6 Gy (RBE).

Development and performance evaluation of a dynamic phantom for biological dosimetry of moving targets

Energy Technology Data Exchange (ETDEWEB)

Gemmel, A; Bert, C; Saito, N; Von Neubeck, C; Iancu, G; K-Weyrather, W; Durante, M; Rietzel, E, E-mail: alexander.ag.gemmel@siemens.co [GSI Helmholtzzentrum fuer Schwerionenforschung, Planckstr 1, 64291 Darmstadt (Germany)

2010-06-07

A dynamic phantom has been developed to allow for measurement of 3D cell survival distributions and the corresponding distributions of the RBE-weighted dose (RBED) in the presence of motion. The phantom consists of two 96-microwell plates holding Chinese hamster ovary cells inside a container filled with culture medium and is placed on a movable stage. Basic biological properties of the phantom were investigated without irradiation and after irradiation with a carbon ion beam, using both a stationary (reference) exposure and exposure during motion of the phantom perpendicular to the beam with beam tracking. There was no statistically significant difference between plating efficiency measured in the microwells with and without motion (0.75) and values reported in the literature. Mean differences between measured and calculated cell survival for these two irradiation modes were within {+-}5% of the target dose of 6 Gy (RBE).

Dynamics robustness of cascading systems.

Directory of Open Access Journals (Sweden)

Jonathan T Young

2017-03-01

Full Text Available A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1 Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2 Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it

Chemoradiotherapy and molecular biology

International Nuclear Information System (INIS)

Hasegawa, Masatoshi; Mitsuhashi, Norio; Niibe, Hideo

2000-01-01

The current status of chemoradiotherapy was reviewed from the standpoint of molecular biology. Chemoradiotherapy was conducted to achieve systemic tumor control, to intensify the response to irradiation, and to reduce adverse reactions. The mechanisms of the efficacy of chemoradiotherapy were: modification of dose-response relationships, inhibition of tumor cell recovery from sublethal damage or potential lethal damage, effects on cell dynamics and the cell cycle, improvement of blood flow or reoxygenation, recruitment, improvement of drug uptake, increased cell damage. Cell death (necrosis and apoptosis) and cancer-related genes were described, as the essential points, because they are involved in the response to chemoradiotherapy. Cisplatin (platinum compound), 5-fluorouracil, etoposide, and taxoid (paclitaxel, docetaxel) were the principal anticancer agents used for chemoradiotherapy, and they enhanced the effects of irradiation. However, even when good responses or synergism between anticancer drug and radiotherapy was observed in in vitro studies, there was little therapeutic advantage clinically. Data from in vitro and in vivo studies should be collected and systemized, and ''molecular biology in chemotherapy'' that can be applied clinically may become established. (K.H.)

Compartmental study of biological systems

International Nuclear Information System (INIS)

Moretti, J.L.

1975-01-01

The compartmental analysis of biological system is dealt with on several chapters devoted successively to: terminology; a mathematical and symbolic account of a system at equilibrium; different compartment systems; analysis of the experimental results. For this it is pointed out that the application of compartmental systems to biological phenomena is not always without danger. Sometimes the compartmental system established in a reference subject fails to conform in the patient. The compartments can divide into two or join together, completely changing the aspect of the system so that parameters calculated with the old model become entirely false. The conclusion is that the setting up of a compartmental system to represent a biological phenomenon is a tricky undertaking and the results must be constantly criticized and questioned [fr

Robustness: confronting lessons from physics and biology.

Science.gov (United States)

Lesne, Annick

2008-11-01

The term robustness is encountered in very different scientific fields, from engineering and control theory to dynamical systems to biology. The main question addressed herein is whether the notion of robustness and its correlates (stability, resilience, self-organisation) developed in physics are relevant to biology, or whether specific extensions and novel frameworks are required to account for the robustness properties of living systems. To clarify this issue, the different meanings covered by this unique term are discussed; it is argued that they crucially depend on the kind of perturbations that a robust system should by definition withstand. Possible mechanisms underlying robust behaviours are examined, either encountered in all natural systems (symmetries, conservation laws, dynamic stability) or specific to biological systems (feedbacks and regulatory networks). Special attention is devoted to the (sometimes counterintuitive) interrelations between robustness and noise. A distinction between dynamic selection and natural selection in the establishment of a robust behaviour is underlined. It is finally argued that nested notions of robustness, relevant to different time scales and different levels of organisation, allow one to reconcile the seemingly contradictory requirements for robustness and adaptability in living systems.

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

Directory of Open Access Journals (Sweden)

Daniel eLewis

2014-12-01

Full Text Available As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo systems, with only a few examples of prominent work done on predicting the dynamics of cell-free systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Study of biological effect of radiation

International Nuclear Information System (INIS)

Li Guisheng

1992-01-01

The some progress on the study of biological effect for protract exposure to low dose rate radiation is reported, and it is indicated that the potential risk of this exposure for the human health and the importance of the routine monitoring of radiation dose for various nuclear installations. The potential exposure to the low dose rate radiation would attract people's extra attention

Biomolecular Modeling in a Process Dynamics and Control Course

Science.gov (United States)

Gray, Jeffrey J.

2006-01-01

I present modifications to the traditional course entitled, "Process dynamics and control," which I renamed "Modeling, dynamics, and control of chemical and biological processes." Additions include the central dogma of biology, pharmacokinetic systems, population balances, control of gene transcription, and large­-scale…

Echinococcus as a model system: biology and epidemiology.

Science.gov (United States)

Thompson, R C A; Jenkins, D J

2014-10-15

The introduction of Echinococcus to Australia over 200 years ago and its establishment in sheep rearing areas of the country inflicted a serious medical and economic burden on the country. This resulted in an investment in both basic and applied research aimed at learning more about the biology and life cycle of Echinococcus. This research served to illustrate the uniqueness of the parasite in terms of developmental biology and ecology, and the value of Echinococcus as a model system in a broad range of research, from fundamental biology to theoretical control systems. These studies formed the foundation for an international, diverse and ongoing research effort on the hydatid organisms encompassing stem cell biology, gene regulation, strain variation, wildlife diseases and models of transmission dynamics. We describe the development, nature and diversity of this research, and how it was initiated in Australia but subsequently has stimulated much international and collaborative research on Echinococcus. Copyright © 2014 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

A timeless biology.

Science.gov (United States)

Tozzi, Arturo; Peters, James F; Chafin, Clifford; De Falco, Domenico; Torday, John S

2018-05-01

Contrary to claims that physics is timeless while biology is time-dependent, we take the opposite standpoint: physical systems' dynamics are constrained by the arrow of time, while living assemblies are time-independent. Indeed, the concepts of "constraints" and "displacements" shed new light on the role of continuous time flow in life evolution, allowing us to sketch a physical gauge theory for biological systems in long timescales. In the very short timescales of biological systems' individual lives, time looks like "frozen" and "fixed", so that the second law of thermodynamics is momentarily wrecked. The global symmetries (standing for biological constrained trajectories, i.e. the energetic gradient flows dictated by the second law of thermodynamics in long timescales) are broken by local "displacements" where time is held constant, i.e., modifications occurring in living systems. Such displacements stand for brief local forces, able to temporarily "break" the cosmic increase in entropy. The force able to restore the symmetries (called "gauge field") stands for the very long timescales of biological evolution. Therefore, at the very low speeds of life evolution, time is no longer one of the four phase space coordinates of a spacetime Universe: it becomes just a gauge field superimposed to three-dimensional biological systems. We discuss the implications in biology: when assessing living beings, the underrated role of isolated "spatial" modifications needs to be emphasized, living apart the evolutionary role of time. Copyright © 2017 Elsevier Ltd. All rights reserved.

Extremal dynamics in random replicator ecosystems

Energy Technology Data Exchange (ETDEWEB)

Kärenlampi, Petri P., E-mail: petri.karenlampi@uef.fi

2015-10-02

The seminal numerical experiment by Bak and Sneppen (BS) is repeated, along with computations with replicator models, including a greater amount of features. Both types of models do self-organize, and do obey power-law scaling for the size distribution of activity cycles. However species extinction within the replicator models interferes with the BS self-organized critical (SOC) activity. Speciation–extinction dynamics ruins any stationary state which might contain a steady size distribution of activity cycles. The BS-type activity appears as a dissimilar phenomenon in comparison to speciation–extinction dynamics in the replicator system. No criticality is found from the speciation–extinction dynamics. Neither are speciations and extinctions in real biological macroevolution known to contain any diverging distributions, or self-organization towards any critical state. Consequently, biological macroevolution probably is not a self-organized critical phenomenon. - Highlights: • Extremal Dynamics organizes random replicator ecosystems to two phases in fitness space. • Replicator systems show power-law scaling of activity. • Species extinction interferes with Bak–Sneppen type mutation activity. • Speciation–extinction dynamics does not show any critical phase transition. • Biological macroevolution probably is not a self-organized critical phenomenon.

ADAM: analysis of discrete models of biological systems using computer algebra.

Science.gov (United States)

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web

Mapping biological systems to network systems

CERN Document Server

Rathore, Heena

2016-01-01

The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully ...

100 years after Smoluchowski: stochastic processes in cell biology

International Nuclear Information System (INIS)

Holcman, D; Schuss, Z

2017-01-01

100 years after Smoluchowski introduced his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from a large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here Smoluchowski’s approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation. (topical review)

Students’ learning activities while studying biological process diagrams

NARCIS (Netherlands)

Kragten, M.; Admiraal, W.; Rijlaarsdam, G.

2015-01-01

Process diagrams describe how a system functions (e.g. photosynthesis) and are an important type of representation in Biology education. In the present study, we examined students’ learning activities while studying process diagrams, related to their resulting comprehension of these diagrams. Each

The scope of detector Medipix2 in micro-radiography of biological samples

Energy Technology Data Exchange (ETDEWEB)

Dammer, J., E-mail: jiri.dammer@utef.cvut.cz [Institute of Experimental and Applied Physics, Czech Technical University in Prague, Horska 3a/22, CZ-12800 Prague 2 (Czech Republic); Weyda, F. [Biology Centre of the Academy of Sciences of the Czech Republic, Institute of Entomology, Branisovska 31, CZ-37005 Ceske Budejovice (Czech Republic); Faculty of Science, University of South Bohemia, Branisovska 31, CZ-37005 Ceske Budejovice (Czech Republic); Jakubek, J. [Institute of Experimental and Applied Physics, Czech Technical University in Prague, Horska 3a/22, CZ-12800 Prague 2 (Czech Republic); Skrabal, P. [Faculty of Biomedical Engineering, Czech Technical University in Prague, Nam. Sitna 3105, CZ-272 01 Kladno (Czech Republic); Sopko, V.; Vavrik, D. [Institute of Experimental and Applied Physics, Czech Technical University in Prague, Horska 3a/22, CZ-12800 Prague 2 (Czech Republic)

2011-05-15

We present our experimental setup devoted to high resolution X-ray micro-radiography that is suitable for imaging of small biological samples. The photon source is a FeinFocus micro-focus X-ray tube. The single photon counting pixel device Medipix2 serves as imaging area. Recently used imaging detectors as radiography films or scintillator detectors, cannot visualize required information about inner structure of scanned sample. Detectors Medipix2 do not suffer from so-called dark current noise and work in unlimited dynamic range. These features of detectors confer high quality and high contrast of final images. The radiographic imaging with detectors Medipix2 represents non-invasive and non-destructive method of investigation. Hereby, we demonstrate results of micro-radiographic study of internal structures of tiny biological samples. In addition to morphological and anatomical studies, we would like to present preliminary study of dynamic processes inside of organisms using micro-radiographic video-capturing.

The scope of detector Medipix2 in micro-radiography of biological samples

International Nuclear Information System (INIS)

Dammer, J.; Weyda, F.; Jakubek, J.; Skrabal, P.; Sopko, V.; Vavrik, D.

2011-01-01

We present our experimental setup devoted to high resolution X-ray micro-radiography that is suitable for imaging of small biological samples. The photon source is a FeinFocus micro-focus X-ray tube. The single photon counting pixel device Medipix2 serves as imaging area. Recently used imaging detectors as radiography films or scintillator detectors, cannot visualize required information about inner structure of scanned sample. Detectors Medipix2 do not suffer from so-called dark current noise and work in unlimited dynamic range. These features of detectors confer high quality and high contrast of final images. The radiographic imaging with detectors Medipix2 represents non-invasive and non-destructive method of investigation. Hereby, we demonstrate results of micro-radiographic study of internal structures of tiny biological samples. In addition to morphological and anatomical studies, we would like to present preliminary study of dynamic processes inside of organisms using micro-radiographic video-capturing.

Spectroscopic, thermal and biological studies of coordination

Indian Academy of Sciences (India)

Spectroscopic, thermal and biological studies of coordination compounds of sulfasalazine drug: Mn(II), Hg(II), Cr(III), ZrO(II), VO(II) and Y(III) transition metal ... The thermal decomposition of the complexes as well as thermodynamic parameters ( *}, *, * and *) were estimated using Coats–Redfern and ...

Seasonal dynamics of plankton communities coupled with ...

African Journals Online (AJOL)

In this study, we studied the influence of the physical-chemical and biological factors (bacterioplankton and phytoplankton abundances) for zooplankton dynamics in a Sidi Saâd reservoir in Centre of Tunisia. The samplings were carried out in spring, summer, autumn and winter (2005 to 2006) in the deepest station (surface ...

A soft body as a reservoir: case studies in a dynamic model of octopus-inspired soft robotic arm

Science.gov (United States)

Nakajima, Kohei; Hauser, Helmut; Kang, Rongjie; Guglielmino, Emanuele; Caldwell, Darwin G.; Pfeifer, Rolf

2013-01-01

The behaviors of the animals or embodied agents are characterized by the dynamic coupling between the brain, the body, and the environment. This implies that control, which is conventionally thought to be handled by the brain or a controller, can partially be outsourced to the physical body and the interaction with the environment. This idea has been demonstrated in a number of recently constructed robots, in particular from the field of “soft robotics”. Soft robots are made of a soft material introducing high-dimensionality, non-linearity, and elasticity, which often makes the robots difficult to control. Biological systems such as the octopus are mastering their complex bodies in highly sophisticated manners by capitalizing on their body dynamics. We will demonstrate that the structure of the octopus arm cannot only be exploited for generating behavior but also, in a sense, as a computational resource. By using a soft robotic arm inspired by the octopus we show in a number of experiments how control is partially incorporated into the physical arm's dynamics and how the arm's dynamics can be exploited to approximate non-linear dynamical systems and embed non-linear limit cycles. Future application scenarios as well as the implications of the results for the octopus biology are also discussed. PMID:23847526

A Soft Body as a Reservoir: Case Studies in a Dynamic Model of Octopus-Inspired Soft Robotic Arm

Directory of Open Access Journals (Sweden)

Kohei eNakajima

2013-07-01

Full Text Available The behaviors of the animals or embodied agents are characterized by the dynamic coupling between the brain, the body, and the environment. This implies that control, which is conventionally thought to be handled by the brain or a controller, can partially be outsourced to the physical body and the interaction with the environment. This idea has been demonstrated in a number of recently constructed robots, in particular from the field of soft robotics. Soft robots are made of a soft material introducing high-dimensionality, nonlinearity, and elasticity, which often makes the robots difficult to control. Biological systems such as the octopus are mastering their complex bodies in highly sophisticated manners by capitalizing on their body dynamics. We will demonstrate that the structure of the octopus arm cannot only be exploited for generating behavior but also, in a sense, as a computational resource. By using a soft robotic arm inspired by the octopus we show in a number of experiments how control is partially incorporated into the physical arm’s dynamics and how the arm’s dynamics can be exploited to approximate nonlinear dynamical systems and embed nonlinear limit cycles. Future application scenarios as well as the implications of the results for the octopus biology are also discussed.

Dynamics of proteins and of their hydration layer studied by neutron scattering and additional biophysical methods

International Nuclear Information System (INIS)

Gallat, Francois-Xavier

2011-01-01

This thesis work focused on the dynamics of proteins, surrounded by their hydration layer, a water shell around the protein vital for its biological function. Each of these components is accompanied by a specific dynamics which union reforms the complex energy landscape of the system. The joint implementation of selective deuteration, incoherent neutron scattering and tera-hertz spectroscopy allowed to explore the dynamics of proteins and that of the hydration shell. The influence of the folding state of protein on its dynamics has been studied by elastic neutron scattering. Globular proteins were less dynamic than its intrinsically disordered analogues. Themselves appear to be stiffer than non-physiological unfolded proteins. The oligomerization state and the consequences on the dynamics were investigated. Aggregates of a globular protein proved to be more flexible than the soluble form. In contrast, aggregates of a disordered protein showed lower average dynamics compared to the soluble form. These observations demonstrate the wide range of dynamics among the proteome. Incoherent neutron scattering experiences on the hydration layer of globular and disordered proteins have yielded information on the nature of water motion around these proteins. The measurements revealed the presence of translational motions concomitant with the onset of the transition dynamics of hydration layers, at 220 K. Measurements have also shown a stronger coupling between a disordered protein and its hydration water, compared to a globular protein and its hydration shell. The nature of the hydration layer and its influence on its dynamics has been explored with the use of polymers that mimic the water behavior and that act as a source of flexibility for the protein. Eventually, the dynamics of methyl groups involved in the dynamical changes observed at 150 and 220 K, was investigated. (author) [fr

NATO Advanced Study Institute on Chaotic Dynamics : Theory and Practice

CERN Document Server

1992-01-01

Many conferences, meetings, workshops, summer schools and symposia on nonlinear dynamical systems are being organized these days, dealing with a great variety of topics and themes -classical and quantum, theoretical and experimental. Some focus on integrability, or discuss the mathematical foundations of chaos. Others explore the beauty of fractals, or examine endless possibilities of applications to problems of physics, chemistry, biology and other sciences. A new scientific discipline has thus emerged, with its own distinct philosophical viewpoint and an impressive arsenal of new methods and techniques, which may be called Chaotic Dynamics. Perhaps its most outstanding achievement so far has been to shed new light on many long­ standing issues involving complicated, irregular or "chaotic" nonlinear phenomena. The concepts of randomness, complexity and unpredictability have been critically re-examined and the fundamental importance of scaling, self-similarity and sensitive dependence on parameters a...

Influence of attapulgite addition on the biological performance and microbial communities of submerged dynamic membrane bioreactor

Directory of Open Access Journals (Sweden)

Wensong Duan

2017-12-01

Full Text Available A submerged dynamic membrane bioreactor (sDMBR was developed to test the influence of attapulgite (AT addition on the treatment performances and the microbial community structure and function. The batch experimental results displayed the highest UV254 and dissolved organic carbon (DOC removal efficiencies with 5% AT/mixed liquid suspended solids addition dosage. The continuous sDMBR results showed that the removal efficiencies of chemical oxygen demand, NH4+-N, total nitrogen and total phosphorus significantly increased in the AT added sDMBR. Excitation emission matrix analysis demonstrated that the protein-like peaks and fulvic acid-like peaks were significantly decreased in both in the mixed liquid and the effluent of the AT added reactor. The obligate anaerobes were observed in the sDMBR with AT addition, such as Bacteroidetes and Gamma proteobacterium in the dynamic membrane, which played an important role in the process of sludge granulation. Bacterial community richness significantly increased after AT addition with predominated phyla of Proteobacteria and Bacteroidetes. Similarly, species abundance significantly increased in the AT added sDMBR. Further investigations with cluster proved that AT was a favorite biological carrier for the microbial ecology, which enriched microbial abundance and community diversity of the sDMBR.

Predicting in vivo effect levels for repeat-dose systemic toxicity using chemical, biological, kinetic and study covariates.

Science.gov (United States)

Truong, Lisa; Ouedraogo, Gladys; Pham, LyLy; Clouzeau, Jacques; Loisel-Joubert, Sophie; Blanchet, Delphine; Noçairi, Hicham; Setzer, Woodrow; Judson, Richard; Grulke, Chris; Mansouri, Kamel; Martin, Matthew

2018-02-01

In an effort to address a major challenge in chemical safety assessment, alternative approaches for characterizing systemic effect levels, a predictive model was developed. Systemic effect levels were curated from ToxRefDB, HESS-DB and COSMOS-DB from numerous study types totaling 4379 in vivo studies for 1247 chemicals. Observed systemic effects in mammalian models are a complex function of chemical dynamics, kinetics, and inter- and intra-individual variability. To address this complex problem, systemic effect levels were modeled at the study-level by leveraging study covariates (e.g., study type, strain, administration route) in addition to multiple descriptor sets, including chemical (ToxPrint, PaDEL, and Physchem), biological (ToxCast), and kinetic descriptors. Using random forest modeling with cross-validation and external validation procedures, study-level covariates alone accounted for approximately 15% of the variance reducing the root mean squared error (RMSE) from 0.96 log 10 to 0.85 log 10  mg/kg/day, providing a baseline performance metric (lower expectation of model performance). A consensus model developed using a combination of study-level covariates, chemical, biological, and kinetic descriptors explained a total of 43% of the variance with an RMSE of 0.69 log 10  mg/kg/day. A benchmark model (upper expectation of model performance) was also developed with an RMSE of 0.5 log 10  mg/kg/day by incorporating study-level covariates and the mean effect level per chemical. To achieve a representative chemical-level prediction, the minimum study-level predicted and observed effect level per chemical were compared reducing the RMSE from 1.0 to 0.73 log 10  mg/kg/day, equivalent to 87% of predictions falling within an order-of-magnitude of the observed value. Although biological descriptors did not improve model performance, the final model was enriched for biological descriptors that indicated xenobiotic metabolism gene expression, oxidative stress, and

Effects of dynamic operating conditions on nitrification in biological rapid sand filters for drinking water treatment

DEFF Research Database (Denmark)

Lee, Carson Odell; Boe-Hansen, Rasmus; Musovic, Sanin

2014-01-01

Biological rapid sand filters are often used to remove ammonium from groundwater for drinking water supply. They often operate under dynamic substrate and hydraulic loading conditions, which can lead to increased levels of ammonium and nitrite in the effluent. To determine the maximum nitrification...... operating conditions. The ammonium removal rate of the filter was determined by the ammonium loading rate, but was independent of both the flow and influent ammonium concentration individually. Ammonia-oxidizing bacteria and archaea were almost equally abundant in the filter. Both ammonium removal...... rates and safe operating windows of rapid sand filters, a pilot scale rapid sand filter was used to test short-term increased ammonium loads, set by varying either influent ammonium concentrations or hydraulic loading rates. Ammonium and iron (flock) removal were consistent between the pilot...

Dynamical systems an introduction with applications in economics and biology

CERN Document Server

Tu, Pierre N V

1994-01-01

The favourable reception of the first edition and the encouragement received from many readers have prompted the author to bring out this new edition. This provides the opportunity for correcting a number of errors, typographical and others, contained in the first edition and making further improvements. This second edition has a new chapter on simplifying Dynamical Systems covering Poincare map, Floquet theory, Centre Manifold Theorems, normal forms of dynamical systems, elimination of passive coordinates and Liapunov-Schmidt reduction theory. It would provide a gradual transition to the study of Bifurcation, Chaos and Catastrophe in Chapter 10. Apart from this, most others - in fact all except the first three and last chapters - have been revised and enlarged to bring in some new materials, elaborate some others, especially those sections which many readers felt were rather too concise in the first edition, by providing more explana­ tion, examples and applications. Chapter 11 provides some good examples o...

Ethnographic Observational Study of the Biologic Initiation Conversation Between Rheumatologists and Biologic-Naive Rheumatoid Arthritis Patients.

Science.gov (United States)

Kottak, Nicholas; Tesser, John; Leibowitz, Evan; Rosenberg, Melissa; Parenti, Dennis; DeHoratius, Raphael

2018-01-30

This ethnographic market research study investigated the biologic initiation conversation between rheumatologists and biologic-naive patients with rheumatoid arthritis to assess how therapy options, particularly mode of administration, were discussed. Consenting rheumatologists (n = 16) and patients (n = 48) were videotaped during medical visits and interviewed by a trained ethnographer. The content, structure, and timing of conversations regarding biologic initiation were analyzed. The mean duration of physician-patient visits was approximately 15 minutes; biologic therapies were discussed for a mean of 5.6 minutes. Subcutaneous (SC) and intravenous (IV) therapy options were mentioned in 45 and 35 visits, respectively, out of a total of 48 visits. All patients had some familiarity with SC administration, but nearly half of patients (22 of 48) were unfamiliar with IV therapy going into the visit. IV administration was not defined or described by rheumatologists in 77% of visits (27 of 35) mentioning IV therapy. Thus, 19 of 22 patients who were initially unfamiliar with IV therapy remained unfamiliar after the visit. Disparities in physician-patient perceptions were revealed, as all rheumatologists (16 of 16) believed IV therapy would be less convenient than SC therapy for patients, while 46% of patients (22 of 48) felt this way. In post-visit interviews, some patients seemed confused and overwhelmed, particularly when presented with many treatment choices in a visit. Some patients stated they would benefit from visual aids or summary sheets of key points. This study revealed significant educational opportunities to improve the biologic initiation conversation and indicated a disparity between patients' and rheumatologists' perception of IV therapy. © 2018 The Authors. Arthritis Care & Research published by Wiley Periodicals, Inc. on behalf of American College of Rheumatology.

The relativity of biological function.

Science.gov (United States)

Laubichler, Manfred D; Stadler, Peter F; Prohaska, Sonja J; Nowick, Katja

2015-12-01

Function is a central concept in biological theories and explanations. Yet discussions about function are often based on a narrow understanding of biological systems and processes, such as idealized molecular systems or simple evolutionary, i.e., selective, dynamics. Conflicting conceptions of function continue to be used in the scientific literature to support certain claims, for instance about the fraction of "functional DNA" in the human genome. Here we argue that all biologically meaningful interpretations of function are necessarily context dependent. This implies that they derive their meaning as well as their range of applicability only within a specific theoretical and measurement context. We use this framework to shed light on the current debate about functional DNA and argue that without considering explicitly the theoretical and measurement contexts all attempts to integrate biological theories are prone to fail.

A Trade Study of Two Membrane-Aerated Biological Water Processors

Science.gov (United States)

Allada, Ram; Lange, Kevin; Vega. Leticia; Roberts, Michael S.; Jackson, Andrew; Anderson, Molly; Pickering, Karen

2011-01-01

Biologically based systems are under evaluation as primary water processors for next generation life support systems due to their low power requirements and their inherent regenerative nature. This paper will summarize the results of two recent studies involving membrane aerated biological water processors and present results of a trade study comparing the two systems with regards to waste stream composition, nutrient loading and system design. Results of optimal configurations will be presented.

Synthetic biology and metabolic engineering.

Science.gov (United States)

Stephanopoulos, Gregory

2012-11-16

Metabolic engineering emerged 20 years ago as the discipline occupied with the directed modification of metabolic pathways for the microbial synthesis of various products. As such, it deals with the engineering (design, construction, and optimization) of native as well as non-natural routes of product synthesis, aided in this task by the availability of synthetic DNA, the core enabling technology of synthetic biology. The two fields, however, only partially overlap in their interest in pathway engineering. While fabrication of biobricks, synthetic cells, genetic circuits, and nonlinear cell dynamics, along with pathway engineering, have occupied researchers in the field of synthetic biology, the sum total of these areas does not constitute a coherent definition of synthetic biology with a distinct intellectual foundation and well-defined areas of application. This paper reviews the origins of the two fields and advances two distinct paradigms for each of them: that of unit operations for metabolic engineering and electronic circuits for synthetic biology. In this context, metabolic engineering is about engineering cell factories for the biological manufacturing of chemical and pharmaceutical products, whereas the main focus of synthetic biology is fundamental biological research facilitated by the use of synthetic DNA and genetic circuits.

Piecewise deterministic processes in biological models

CERN Document Server

Rudnicki, Ryszard

2017-01-01

This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their applications to biological models. Further, it presents examples of biological phenomena, such as gene activity and population growth, where different types of PDMPs appear: continuous time Markov chains, deterministic processes with jumps, processes with switching dynamics, and point processes. Subsequent chapters present the necessary tools from the theory of stochastic processes and semigroups of linear operators, as well as theoretical results concerning the long-time behaviour of stochastic semigroups induced by PDMPs and their applications to biological models. As such, the book offers a valuable resource for mathematicians and biologists alike. The first group will find new biological models that lead to interesting and often new mathematical questions, while the second can observe how to include seemingly disparate biological processes into a unified mathematical theory, and...

Study Finds Association between Biological Marker and Susceptibility to the Common Cold

Science.gov (United States)

... W X Y Z Study Finds Association Between Biological Marker and Susceptibility to the Common Cold Share: © ... a cold caused by a particular rhinovirus. The biological marker identified in the study was the length ...

Structure and dynamics of interfacial water. Role of hydratation water in the globular proteins dynamics

International Nuclear Information System (INIS)

Zanotti, J.M.

1997-01-01

This memoir includes five chapters. In the first chapter, are given the elements of the neutrons scattering theory that is used in this study. the second chapter is devoted to a general presentation of the interaction between biological macro molecule and water. The third part is dedicated to the study of the structure and the dynamics of interfacial water in the neighbouring of model systems, the vycor and the amorphous carbon. The results presented in this part are compared with these one relative to water dynamics at the C-phycocyanin surface. This study makes the object of the fourth chapter. Then, in the fifth and last chapter are discussed the results relative to the role of hydratation on the parv-albumin dynamics for which have been combined the neutron quasi elastic incoherent scattering and the nuclear magnetic resonance of the carbon 13 solid in natural abundance

On the relationship between the dynamic behavior and nanoscale staggered structure of the bone

Science.gov (United States)

Qwamizadeh, Mahan; Zhang, Zuoqi; Zhou, Kun; Zhang, Yong Wei

2015-05-01

Bone, a typical load-bearing biological material, composed of ordinary base materials such as organic protein and inorganic mineral arranged in a hierarchical architecture, exhibits extraordinary mechanical properties. Up to now, most of previous studies focused on its mechanical properties under static loading. However, failure of the bone occurs often under dynamic loading. An interesting question is: Are the structural sizes and layouts of the bone related or even adapted to the functionalities demanded by its dynamic performance? In the present work, systematic finite element analysis was performed on the dynamic response of nanoscale bone structures under dynamic loading. It was found that for a fixed mineral volume fraction and unit cell area, there exists a nanoscale staggered structure at some specific feature size and layout which exhibits the fastest attenuation of stress waves. Remarkably, these specific feature sizes and layouts are in excellent agreement with those experimentally observed in the bone at the same scale, indicating that the structural size and layout of the bone at the nanoscale are evolutionarily adapted to its dynamic behavior. The present work points out the importance of dynamic effect on the biological evolution of load-bearing biological materials.

Gas-Phase Molecular Dynamics: Theoretical Studies in Spectroscopy and Chemical Dynamics

Energy Technology Data Exchange (ETDEWEB)

Yu, H.G.; Muckerman, J.T.

2010-06-01

The goal of this program is the development and application of computational methods for studying chemical reaction dynamics and molecular spectroscopy in the gas phase. We are interested in developing rigorous quantum dynamics algorithms for small polyatomic systems and in implementing approximate approaches for complex ones. Particular focus is on the dynamics and kinetics of chemical reactions and on the rovibrational spectra of species involved in combustion processes. This research also explores the potential energy surfaces of these systems of interest using state-of-the-art quantum chemistry methods.

Decay correction methods in dynamic PET studies

International Nuclear Information System (INIS)

Chen, K.; Reiman, E.; Lawson, M.

1995-01-01

In order to reconstruct positron emission tomography (PET) images in quantitative dynamic studies, the data must be corrected for radioactive decay. One of the two commonly used methods ignores physiological processes including blood flow that occur at the same time as radioactive decay; the other makes incorrect use of time-accumulated PET counts. In simulated dynamic PET studies using 11 C-acetate and 18 F-fluorodeoxyglucose (FDG), these methods are shown to result in biased estimates of the time-activity curve (TAC) and model parameters. New methods described in this article provide significantly improved parameter estimates in dynamic PET studies

Transient resetting: a novel mechanism for synchrony and its biological examples.

Directory of Open Access Journals (Sweden)

Chunguang Li

2006-08-01

Full Text Available The study of synchronization in biological systems is essential for the understanding of the rhythmic phenomena of living organisms at both molecular and cellular levels. In this paper, by using simple dynamical systems theory, we present a novel mechanism, named transient resetting, for the synchronization of uncoupled biological oscillators with stimuli. This mechanism not only can unify and extend many existing results on (deterministic and stochastic stimulus-induced synchrony, but also may actually play an important role in biological rhythms. We argue that transient resetting is a possible mechanism for the synchronization in many biological organisms, which might also be further used in the medical therapy of rhythmic disorders. Examples of the synchronization of neural and circadian oscillators as well as a chaotic neuron model are presented to verify our hypothesis.

Correlative study of dynamic MRI and tumor angiogenesis in gastric carcinoma

International Nuclear Information System (INIS)

Tang Qunfeng; Shen Junkang; Feng Yizhong; Qian Minghui; Chai Yuhai

2004-01-01

Objective: To investigate the correlation between the dynamic MRI enhancement characteristics and tumor angiogenesis in gastric carcinoma. Methods: Histopathological slides of 30 patients underwent CD34 and vascular endothelial growth factor (VEGF) immunohistochemical staining. Microvessel density (MVD) and VEGF protein expression were analyzed with their relationship to pathological features. The dynamic MRI characteristics, including the maximum contrast enhancement ratio (CERmax), were correlatively studied with MVD and VEGF expression. Results: In 30 cases, MVD was 13.00 to 68.25 per vision field with an average of 42.95 ±14.79. The low expression rate of VEGF was 30% (9/30), while the high expression rate of VEGF was 70% (21/30). MVD and VEGF expression correlated with lymph node metastasis (P>0.05), but their relationships to the degree of differentiation and depth of invasion were not significant (P>0.05). MVD was related to TNM-staging of gastric carcinoma (P>0.05). The expression of VEGF between the stage I and IV had significant differences (P>0.05). MVD was higher in VEGF-high expression than in VEGF-low expression [(47.30 ± 14.16) per vision versus (32.81 ± 11.25) per vision]. CERmax was significantly correlated with MVD (r=0.556, P=0.0014). The distribution features and shape of microvessels within gastric carcinoma were related to the enhancement characteristics such as irregular enhancement and delaminated enhancement. The correlation between CERmax and expression of VEGF was not significant (t=-0.847, P=0.404). Conclusion: The manifestations on dynamic MR images can reflect the distribution features and shape of microvessels within gastric carcinoma. Dynamic MR imaging may prove to be a valuable means in estimating the MVD of gastric carcinoma noninvasively, and further predicting the biological behavior of gastric carcinoma and judging the prognosis. (authors)

Implications of the use of experimental activities in biology education in public schools

Directory of Open Access Journals (Sweden)

Vânia Cardoso da Silva Morais

2016-04-01

Full Text Available This study aimed to verify the influence of a didactic sequence with experimental activities on student motivation in relation to the subject matter Biology and check the possibility of applying such a result having as input the cultural-historical perspective and the dynamic of the three pedagogical moments. The work is part of a Master Degree research developed with 70 students from a high school in Patos de Minas city. The analysis of the data collected through observation, questionnaires, reports, testimonies of students, filming and photography of biology classes, points out that the use of experimental activities in Biology classes contributed to the increase of student motivation relating to Biology classes favoring the teaching-learning process and also to promote a converge between the scientific knowledge and reality of the students besides encourage their self-esteem and investigative sense. The results also indicate that it is possible to develop at school a didactic sequence based on the complementarity of two different theoretical lines like the dynamics of the three moments and in the historical and cultural perspective. Based on above considerations, we believe that the use of experimental activities following didactics positively influences student motivation in relation to Biology, favoring the teaching and learning of Biology. However, it is the whole of this, as the theory and the posture of motivating teachers, allowed approximation between scientific knowledge and reality of the students, enabling greater learning of biological concepts.

An Axiomatic, Unified Representation of Biosystems and Quantum Dynamics

CERN Document Server

Baianu, I

2004-01-01

An axiomatic representation of system dynamics is introduced in terms of categories, functors, organismal supercategories, limits and colimits of diagrams. Specific examples are considered in Complex Systems Biology, such as ribosome biogenesis and Hormonal Control in human subjects. "Fuzzy" Relational Structures are also proposed for flexible representations of biological system dynamics and organization.

Systems Biology of the Fluxome

Directory of Open Access Journals (Sweden)

Miguel A. Aon

2015-07-01

Full Text Available The advent of high throughput -omics has made the accumulation of comprehensive data sets possible, consisting of changes in genes, transcripts, proteins and metabolites. Systems biology-inspired computational methods for translating metabolomics data into fluxomics provide a direct functional, dynamic readout of metabolic networks. When combined with appropriate experimental design, these methods deliver insightful knowledge about cellular function under diverse conditions. The use of computational models accounting for detailed kinetics and regulatory mechanisms allow us to unravel the control and regulatory properties of the fluxome under steady and time-dependent behaviors. This approach extends the analysis of complex systems from description to prediction, including control of complex dynamic behavior ranging from biological rhythms to catastrophic lethal arrhythmias. The powerful quantitative metabolomics-fluxomics approach will help our ability to engineer unicellular and multicellular organisms evolve from trial-and-error to a more predictable process, and from cells to organ and organisms.

Computational Fluid Dynamics Methods and Their Applications in Medical Science

Directory of Open Access Journals (Sweden)

Kowalewski Wojciech

2016-12-01

Full Text Available As defined by the National Institutes of Health: “Biomedical engineering integrates physical, chemical, mathematical, and computational sciences and engineering principles to study biology, medicine, behavior, and health”. Many issues in this area are closely related to fluid dynamics. This paper provides an overview of the basic concepts concerning Computational Fluid Dynamics and its applications in medicine.

Quasielastic neutron scattering in biology: Theory and applications.

Science.gov (United States)

Vural, Derya; Hu, Xiaohu; Lindner, Benjamin; Jain, Nitin; Miao, Yinglong; Cheng, Xiaolin; Liu, Zhuo; Hong, Liang; Smith, Jeremy C

2017-01-01

Neutrons scatter quasielastically from stochastic, diffusive processes, such as overdamped vibrations, localized diffusion and transitions between energy minima. In biological systems, such as proteins and membranes, these relaxation processes are of considerable physical interest. We review here recent methodological advances and applications of quasielastic neutron scattering (QENS) in biology, concentrating on the role of molecular dynamics simulation in generating data with which neutron profiles can be unambiguously interpreted. We examine the use of massively-parallel computers in calculating scattering functions, and the application of Markov state modeling. The decomposition of MD-derived neutron dynamic susceptibilities is described, and the use of this in combination with NMR spectroscopy. We discuss dynamics at very long times, including approximations to the infinite time mean-square displacement and nonequilibrium aspects of single-protein dynamics. Finally, we examine how neutron scattering and MD can be combined to provide information on lipid nanodomains. This article is part of a Special Issue entitled "Science for Life" Guest Editor: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo. Copyright © 2016 Elsevier B.V. All rights reserved.

How do biological systems escape 'chaotic' state?

Indian Academy of Sciences (India)

B J Rao

2018-02-13

Feb 13, 2018 ... Lorencova 2016), sociology, physics, computer science, economics and even biology ... dynamic complexity associated with them at multiple levels? .... Social anthropology and the science of chaos (Oxford: Berghahn Books).

From immunology to MRI data anlysis: Problems in mathematical biology

Science.gov (United States)

Waters, Ryan Samuel

This thesis represents a collection of four distinct biological projects rising from immunology and metabolomics that required unique and creative mathematical approaches. One project focuses on understanding the role IL-2 plays in immune response regulation and exploring how these effects can be altered. We developed several dynamic models of the receptor signaling network which we analyze analytically and numerically. In a second project focused also on MS, we sought to create a system for grading magnetic resonance images (MRI) with good correlation with disability. The goal is for these MRI scores to provide a better standard for large-scale clinical drug trials, which limits the bias associated with differences in available MRI technology and general grader/participant variability. The third project involves the study of the CRISPR adaptive immune system in bacteria. Bacterial cells recognize and acquire snippets of exogenous genetic material, which they incorporate into their DNA. In this project we explore the optimal design for the CRISPR system given a viral distribution to maximize its probability of survival. The final project involves the study of the benefits for colocalization of coupled enzymes in metabolic pathways. The hypothesized kinetic advantage, known as `channeling', of putting coupled enzymes closer together has been used as justification for the colocalization of coupled enzymes in biological systems. We developed and analyzed a simple partial differential equation of the diffusion of the intermediate substrate between coupled enzymes to explore the phenomena of channeling. The four projects of my thesis represent very distinct biological problems that required a variety of techniques from diverse areas of mathematics ranging from dynamical modeling to statistics, Fourier series and calculus of variations. In each case, quantitative techniques were used to address biological questions from a mathematical perspective ultimately providing

Bacteriophage-based synthetic biology for the study of infectious diseases

Science.gov (United States)

Lu, Timothy K.

2014-01-01

Since their discovery, bacteriophages have contributed enormously to our understanding of molecular biology as model systems. Furthermore, bacteriophages have provided many tools that have advanced the fields of genetic engineering and synthetic biology. Here, we discuss bacteriophage-based technologies and their application to the study of infectious diseases. New strategies for engineering genomes have the potential to accelerate the design of novel phages as therapies, diagnostics, and tools. Though almost a century has elapsed since their discovery, bacteriophages continue to have a major impact on modern biological sciences, especially with the growth of multidrug-resistant bacteria and interest in the microbiome. PMID:24997401

External irradiation facilities open for biological studies - progress in july 2005

International Nuclear Information System (INIS)

Gaillard-Lecanu, E.; Authier, N.; Verrey, B.; Bailly, I.; Bordy, J.M.; Coffigny, H.; Cortela, L.; Duval, D.; Leplat, J.J.; Poncy, J.L.; Testard, I.; Thuret, J.Y.

2005-01-01

The Life Science Division of the Atomic Energy Commission is making an inventory of the various radiation sources accessible for investigation on the biological effects of ionizing radiation. In this field, a wide range of studies is being carried out at the Life Science Division, attempting to characterize the kind of lesions with their early biological consequences (on the various cell compartments) and their late biological consequences (deterministic or stochastic effects), in relation to the radiation type and dose, especially at low doses. Several experimental models are available: plants, bacteria, eukaryotic cells from yeast up to mammalian cells and in vivo studies, mostly on rodents, in order to characterize the somatic late effects and the hereditary effects. Due to the significant cost of these facilities, also to their specific properties (nature of the radiation, dose and dose rate, possible accuracy of the irradiation at the molecular level), the closeness is no longer the only criteria for biologists to make a choice. The current evolution is to set up irradiation infrastructures combining ionizing radiation sources themselves and specific tools dedicated to biological studies: cell or molecular biology laboratories, animal facilities. The purpose, in this new frame, is to provide biologists with the most suitable facilities, and, if possible, to change these facilities according to requirements in radiobiology. In this report, the basics of interactions of ionizing radiation with biological tissues are briefly introduced, followed by a presentation of some of the facilities available for radiobiological studies especially at CEA. This panorama is not a comprehensive one, new data will be included as they advance, whether reporting existing facilities or if a new one is developed. (authors)

Biological Studies with Laser-Polarized ^129Xe

Science.gov (United States)

Tseng, C. H.; Oteiza, E. R.; Wong, G. A.; Walsworth, R. L.; Albert, M. S.; Nascimben, L.; Peled, S.; Sakai, K.; Jolesz, F. A.

1996-05-01

We have studied several biological systems using laser-polarized ^129Xe. In certain tissues magnetic resonance imaging (MRI) using inhaled laser-polarized noble gases may provide images superior to those from conventional proton MRI. High resolution laser-polarized ^3He images of air spaces in the human lung were recently obtained by the Princeton/Duke group. However, ^3He is not very soluble in tissue. Therefore, we are using laser polarized ^129Xe (tissue-soluble), with the long term goal of biomedical functional imaging. We have investigated multi-echo and multi-excitation magnetic resonance detection schemes to exploit the highly non-thermal ^129Xe magnetization produced by the laser polarization technique. We have inhalated live rats with laser-polarized ^129Xe gas and measured three distinct ^129Xe tissue resonances that last 20 to 40 sec. As a demonstration, we obtained a laser polarized ^129Xe image of the human oral cavity. Currently we are measuring the polarization lifetime of ^129Xe dissolved in human blood, the biological transporting medium. These studies and other recent developments will be reported.

Polynomial algebra of discrete models in systems biology.

Science.gov (United States)

Veliz-Cuba, Alan; Jarrah, Abdul Salam; Laubenbacher, Reinhard

2010-07-01

An increasing number of discrete mathematical models are being published in Systems Biology, ranging from Boolean network models to logical models and Petri nets. They are used to model a variety of biochemical networks, such as metabolic networks, gene regulatory networks and signal transduction networks. There is increasing evidence that such models can capture key dynamic features of biological networks and can be used successfully for hypothesis generation. This article provides a unified framework that can aid the mathematical analysis of Boolean network models, logical models and Petri nets. They can be represented as polynomial dynamical systems, which allows the use of a variety of mathematical tools from computer algebra for their analysis. Algorithms are presented for the translation into polynomial dynamical systems. Examples are given of how polynomial algebra can be used for the model analysis. alanavc@vt.edu Supplementary data are available at Bioinformatics online.

On the origin of biological construction, with a focus on multicellularity.

Science.gov (United States)

van Gestel, Jordi; Tarnita, Corina E

2017-10-17

Biology is marked by a hierarchical organization: all life consists of cells; in some cases, these cells assemble into groups, such as endosymbionts or multicellular organisms; in turn, multicellular organisms sometimes assemble into yet other groups, such as primate societies or ant colonies. The construction of new organizational layers results from hierarchical evolutionary transitions, in which biological units (e.g., cells) form groups that evolve into new units of biological organization (e.g., multicellular organisms). Despite considerable advances, there is no bottom-up, dynamical account of how, starting from the solitary ancestor, the first groups originate and subsequently evolve the organizing principles that qualify them as new units. Guided by six central questions, we propose an integrative bottom-up approach for studying the dynamics underlying hierarchical evolutionary transitions, which builds on and synthesizes existing knowledge. This approach highlights the crucial role of the ecology and development of the solitary ancestor in the emergence and subsequent evolution of groups, and it stresses the paramount importance of the life cycle: only by evaluating groups in the context of their life cycle can we unravel the evolutionary trajectory of hierarchical transitions. These insights also provide a starting point for understanding the types of subsequent organizational complexity. The central research questions outlined here naturally link existing research programs on biological construction (e.g., on cooperation, multilevel selection, self-organization, and development) and thereby help integrate knowledge stemming from diverse fields of biology.

Fluid models and simulations of biological cell phenomena

Science.gov (United States)

Greenspan, H. P.

1982-01-01

The dynamics of coated droplets are examined within the context of biofluids. Of specific interest is the manner in which the shape of a droplet, the motion within it as well as that of aggregates of droplets can be controlled by the modulation of surface properties and the extent to which such fluid phenomena are an intrinsic part of cellular processes. From the standpoint of biology, an objective is to elucidate some of the general dynamical features that affect the disposition of an entire cell, cell colonies and tissues. Conventionally averaged field variables of continuum mechanics are used to describe the overall global effects which result from the myriad of small scale molecular interactions. An attempt is made to establish cause and effect relationships from correct dynamical laws of motion rather than by what may have been unnecessary invocation of metabolic or life processes. Several topics are discussed where there are strong analogies droplets and cells including: encapsulated droplets/cell membranes; droplet shape/cell shape; adhesion and spread of a droplet/cell motility and adhesion; and oams and multiphase flows/cell aggregates and tissues. Evidence is presented to show that certain concepts of continuum theory such as suface tension, surface free energy, contact angle, bending moments, etc. are relevant and applicable to the study of cell biology.

Frontiers of NMR in Molecular Biology

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-08-25

NMR spectroscopy is expanding the horizons of structural biology by determining the structures and describing the dynamics of blobular proteins in aqueous solution, as well as other classes of proteins including membrane proteins and the polypeptides that form the aggregates diagnostic of prion and amyloid diseases. Significant results are also emerging on DNA and RNA oligomers and their complexes with proteins. This meeting focused attention on key structural questions emanating from molecular biology and how NMR spectroscopy can be used to answer them.

Dynamics of Intracellular Polymers in Enhanced Biological Phosphorus Removal Processes under Different Organic Carbon Concentrations

Directory of Open Access Journals (Sweden)

Lizhen Xing

2013-01-01

Full Text Available Enhanced biological phosphorus removal (EBPR may deteriorate or fail during low organic carbon loading periods. Polyphosphate accumulating organisms (PAOs in EBPR were acclimated under both high and low organic carbon conditions, and then dynamics of polymers in typical cycles, anaerobic conditions with excess organic carbons, and endogenous respiration conditions were examined. After long-term acclimation, it was found that organic loading rates did not affect the yield of PAOs and the applied low organic carbon concentrations were advantageous for the enrichment of PAOs. A low influent organic carbon concentration induced a high production of extracellular carbohydrate. During both anaerobic and aerobic endogenous respirations, when glycogen decreased to around 80 ± 10 mg C per gram of volatile suspended solids, PAOs began to utilize polyphosphate significantly. Regressed by the first-order reaction model, glycogen possessed the highest degradation rate and then was followed by polyphosphate, while biomass decay had the lowest degradation rate.

Carbon nanomaterials in biological systems

Energy Technology Data Exchange (ETDEWEB)

Pu Chun Ke [Laboratory of Single-Molecule Biophysics and Polymer Physics, Department of Physics and Astronomy, Clemson University, Clemson, SC 29634 (United States); Qiao Rui [Department of Mechanical Engineering, Clemson University, Clemson, SC 29634 (United States)

2007-09-19

This paper intends to reflect, from the biophysical viewpoint, our current understanding on interfacing nanomaterials, such as carbon nanotubes and fullerenes, with biological systems. Strategies for improving the solubility, and therefore, the bioavailability of nanomaterials in aqueous solutions are summarized. In particular, the underlining mechanisms of attaching biomacromolecules (DNA, RNA, proteins) and lysophospholipids onto carbon nanotubes and gallic acids onto fullerenes are analyzed. The diffusion and the cellular delivery of RNA-coated carbon nanotubes are characterized using fluorescence microscopy. The translocation of fullerenes across cell membranes is simulated using molecular dynamics to offer new insight into the complex issue of nanotoxicity. To assess the fate of nanomaterials in the environment, the biomodification of lipid-coated carbon nanotubes by the aquatic organism Daphnia magna is discussed. The aim of this paper is to illuminate the need for adopting multidisciplinary approaches in the field study of nanomaterials in biological systems and in the environment. (topical review)

Carbon nanomaterials in biological systems

International Nuclear Information System (INIS)

Pu Chun Ke; Qiao Rui

2007-01-01

This paper intends to reflect, from the biophysical viewpoint, our current understanding on interfacing nanomaterials, such as carbon nanotubes and fullerenes, with biological systems. Strategies for improving the solubility, and therefore, the bioavailability of nanomaterials in aqueous solutions are summarized. In particular, the underlining mechanisms of attaching biomacromolecules (DNA, RNA, proteins) and lysophospholipids onto carbon nanotubes and gallic acids onto fullerenes are analyzed. The diffusion and the cellular delivery of RNA-coated carbon nanotubes are characterized using fluorescence microscopy. The translocation of fullerenes across cell membranes is simulated using molecular dynamics to offer new insight into the complex issue of nanotoxicity. To assess the fate of nanomaterials in the environment, the biomodification of lipid-coated carbon nanotubes by the aquatic organism Daphnia magna is discussed. The aim of this paper is to illuminate the need for adopting multidisciplinary approaches in the field study of nanomaterials in biological systems and in the environment. (topical review)

Integrating interactive computational modeling in biology curricula.

Directory of Open Access Journals (Sweden)

Tomáš Helikar

2015-03-01

Full Text Available While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

Integrating interactive computational modeling in biology curricula.

Science.gov (United States)

Helikar, Tomáš; Cutucache, Christine E; Dahlquist, Lauren M; Herek, Tyler A; Larson, Joshua J; Rogers, Jim A

2015-03-01

While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

Biological effective dose studies in carcinoma of uterine cervix

International Nuclear Information System (INIS)

Yadav, Poonam; Ramasubramanian, V.

2008-01-01

Cancer of cervix is the second most common cancer worldwide among women. Several treatments related protocols of radiotherapy have been followed over few decades in its treatment for evaluating the response. These physical doses varying on the basics of fractionation size, dose rate and total dose needed to be indicated as biological effective dose (BED) to rationalize these treatments. The curative potential of radiation therapy in the management of carcinoma of the cervix is greatly enhanced by the use of intracavitary brachytherapy. Successful brachytherapy requires the high radiation dose to be delivered to the tumor where as minimum radiation dose reach to surrounding normal tissue. Present study is aimed to evaluate biologically effective dose in patients receiving high dose-rate brachytherapy plus external beam radiotherapy based on tumor cell proliferation values in cancer of the cervix patients. The study includes 30 patients' data as a retrospective analysis. In addition determine extent of a dose-response relationship existing between the biological effective dose at Point A and the bladder and rectum and the clinical outcomes

Approximation of quantum observables by molecular dynamics simulations

KAUST Repository

Sandberg, Mattias

2016-01-01

In this talk I will discuss how to estimate the uncertainty in molecular dynamics simulations. Molecular dynamics is a computational method to study molecular systems in materials science, chemistry, and molecular biology. The wide popularity of molecular dynamics simulations relies on the fact that in many cases it agrees very well with experiments. If we however want the simulation to predict something that has no comparing experiment, we need a mathematical estimate of the accuracy of the computation. In the case of molecular systems with few particles, such studies are made by directly solving the Schrodinger equation. In this talk I will discuss theoretical results on the accuracy between quantum mechanics and molecular dynamics, to be used for systems that are too large to be handled computationally by the Schrodinger equation.

Approximation of quantum observables by molecular dynamics simulations

KAUST Repository

Sandberg, Mattias

2016-01-06

In this talk I will discuss how to estimate the uncertainty in molecular dynamics simulations. Molecular dynamics is a computational method to study molecular systems in materials science, chemistry, and molecular biology. The wide popularity of molecular dynamics simulations relies on the fact that in many cases it agrees very well with experiments. If we however want the simulation to predict something that has no comparing experiment, we need a mathematical estimate of the accuracy of the computation. In the case of molecular systems with few particles, such studies are made by directly solving the Schrodinger equation. In this talk I will discuss theoretical results on the accuracy between quantum mechanics and molecular dynamics, to be used for systems that are too large to be handled computationally by the Schrodinger equation.

XXIII International Conference on Nonlinear Dynamics of Electronic Systems

CERN Document Server

Stoop, Ruedi; Stramaglia, Sebastiano

2017-01-01

This book collects contributions to the XXIII international conference “Nonlinear dynamics of electronic systems”. Topics range from non-linearity in electronic circuits to synchronisation effects in complex networks to biological systems, neural dynamics and the complex organisation of the brain. Resting on a solid mathematical basis, these investigations address highly interdisciplinary problems in physics, engineering, biology and biochemistry.

Computer processing of dynamic scintigraphic studies

International Nuclear Information System (INIS)

Ullmann, V.

1985-01-01

The methods are discussed of the computer processing of dynamic scintigraphic studies which were developed, studied or implemented by the authors within research task no. 30-02-03 in nuclear medicine within the five year plan 1981 to 85. This was mainly the method of computer processing radionuclide angiography, phase radioventriculography, regional lung ventilation, dynamic sequential scintigraphy of kidneys and radionuclide uroflowmetry. The problems are discussed of the automatic definition of fields of interest, the methodology of absolute volumes of the heart chamber in radionuclide cardiology, the design and uses are described of the multipurpose dynamic phantom of heart activity for radionuclide angiocardiography and ventriculography developed within the said research task. All methods are documented with many figures showing typical clinical (normal and pathological) and phantom measurements. (V.U.)

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

Directory of Open Access Journals (Sweden)

Oyang Yen-Jen

2010-10-01

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

Partial differential equations for self-organization in cellular and developmental biology

International Nuclear Information System (INIS)

Baker, R E; Gaffney, E A; Maini, P K

2008-01-01

Understanding the mechanisms governing and regulating the emergence of structure and heterogeneity within cellular systems, such as the developing embryo, represents a multiscale challenge typifying current integrative biology research, namely, explaining the macroscale behaviour of a system from microscale dynamics. This review will focus upon modelling how cell-based dynamics orchestrate the emergence of higher level structure. After surveying representative biological examples and the models used to describe them, we will assess how developments at the scale of molecular biology have impacted on current theoretical frameworks, and the new modelling opportunities that are emerging as a result. We shall restrict our survey of mathematical approaches to partial differential equations and the tools required for their analysis. We will discuss the gap between the modelling abstraction and biological reality, the challenges this presents and highlight some open problems in the field. (invited article)

Studies in Chemical Dynamics

International Nuclear Information System (INIS)

Rabitz, Herschel; Ho, Tak-San

2003-01-01

This final report draws together the research carried from February, 1986 through January, 2003 concerning a series of topics in chemical dynamics. The specific areas of study include molecular collisions, chemical kinetics, data inversion to extract potential energy surfaces, and model reduction of complex kinetic systems

Molecular dynamics simulations and applications in computational toxicology and nanotoxicology.

Science.gov (United States)

Selvaraj, Chandrabose; Sakkiah, Sugunadevi; Tong, Weida; Hong, Huixiao

2018-02-01

Nanotoxicology studies toxicity of nanomaterials and has been widely applied in biomedical researches to explore toxicity of various biological systems. Investigating biological systems through in vivo and in vitro methods is expensive and time taking. Therefore, computational toxicology, a multi-discipline field that utilizes computational power and algorithms to examine toxicology of biological systems, has gained attractions to scientists. Molecular dynamics (MD) simulations of biomolecules such as proteins and DNA are popular for understanding of interactions between biological systems and chemicals in computational toxicology. In this paper, we review MD simulation methods, protocol for running MD simulations and their applications in studies of toxicity and nanotechnology. We also briefly summarize some popular software tools for execution of MD simulations. Published by Elsevier Ltd.

The emerging molecular biology toolbox for the study of long noncoding RNA biology.

Science.gov (United States)

Fok, Ezio T; Scholefield, Janine; Fanucchi, Stephanie; Mhlanga, Musa M

2017-10-01

Long noncoding RNAs (lncRNAs) have been implicated in many biological processes. However, due to the unique nature of lncRNAs and the consequential difficulties associated with their characterization, there is a growing disparity between the rate at which lncRNAs are being discovered and the assignment of biological function to these transcripts. Here we present a molecular biology toolbox equipped to help dissect aspects of lncRNA biology and reveal functionality. We outline an approach that begins with a broad survey of genome-wide, high-throughput datasets to identify potential lncRNA candidates and then narrow the focus on specific methods that are well suited to interrogate the transcripts of interest more closely. This involves the use of imaging-based strategies to validate these candidates and observe the behaviors of these transcripts at single molecule resolution in individual cells. We also describe the use of gene editing tools and interactome capture techniques to interrogate functionality and infer mechanism, respectively. With the emergence of lncRNAs as important molecules in healthy and diseased cellular function, it remains crucial to deepen our understanding of their biology.

Exploring biological network structure with clustered random networks

Directory of Open Access Journals (Sweden)

Bansal Shweta

2009-12-01

Full Text Available Abstract Background Complex biological systems are often modeled as networks of interacting units. Networks of biochemical interactions among proteins, epidemiological contacts among hosts, and trophic interactions in ecosystems, to name a few, have provided useful insights into the dynamical processes that shape and traverse these systems. The degrees of nodes (numbers of interactions and the extent of clustering (the tendency for a set of three nodes to be interconnected are two of many well-studied network properties that can fundamentally shape a system. Disentangling the interdependent effects of the various network properties, however, can be difficult. Simple network models can help us quantify the structure of empirical networked systems and understand the impact of various topological properties on dynamics. Results Here we develop and implement a new Markov chain simulation algorithm to generate simple, connected random graphs that have a specified degree sequence and level of clustering, but are random in all other respects. The implementation of the algorithm (ClustRNet: Clustered Random Networks provides the generation of random graphs optimized according to a local or global, and relative or absolute measure of clustering. We compare our algorithm to other similar methods and show that ours more successfully produces desired network characteristics. Finding appropriate null models is crucial in bioinformatics research, and is often difficult, particularly for biological networks. As we demonstrate, the networks generated by ClustRNet can serve as random controls when investigating the impacts of complex network features beyond the byproduct of degree and clustering in empirical networks. Conclusion ClustRNet generates ensembles of graphs of specified edge structure and clustering. These graphs allow for systematic study of the impacts of connectivity and redundancies on network function and dynamics. This process is a key step in

Cellular automaton modeling of biological pattern formation characterization, examples, and analysis

CERN Document Server

Deutsch, Andreas

2017-01-01

This text explores the use of cellular automata in modeling pattern formation in biological systems. It describes several mathematical modeling approaches utilizing cellular automata that can be used to study the dynamics of interacting cell systems both in simulation and in practice. New in this edition are chapters covering cell migration, tissue development, and cancer dynamics, as well as updated references and new research topic suggestions that reflect the rapid development of the field. The book begins with an introduction to pattern-forming principles in biology and the various mathematical modeling techniques that can be used to analyze them. Cellular automaton models are then discussed in detail for different types of cellular processes and interactions, including random movement, cell migration, adhesive cell interaction, alignment and cellular swarming, growth processes, pigment cell pattern formation, tissue development, tumor growth and invasion, and Turing-type patterns and excitable media. In ...

Biological physics and synchrotron radiation

International Nuclear Information System (INIS)

Filhol, J.M.; Chavanne, J.; Weckert, E.

2001-01-01

This conference deals with the applications of synchrotron radiation to current problems in biology and medicine. Seven sessions take stock on the subject: sources and detectors; inelastic scattering and dynamics; muscle diffraction; reaction mechanisms; macromolecular assemblies; medical applications; imaging and spectroscopy. The document presents the papers abstracts. (A.L.B.)

Biological physics and synchrotron radiation

Energy Technology Data Exchange (ETDEWEB)

Filhol, J M; Chavanne, J [European Synchrotron Radiation Facility, 38 - Grenoble (France); Weckert, E [Hasylab at Desy, Hamburg (Germany); and others

2001-07-01

This conference deals with the applications of synchrotron radiation to current problems in biology and medicine. Seven sessions take stock on the subject: sources and detectors; inelastic scattering and dynamics; muscle diffraction; reaction mechanisms; macromolecular assemblies; medical applications; imaging and spectroscopy. The document presents the papers abstracts. (A.L.B.)

Adapting to Biology: Maintaining Container-Closure System Compatibility with the Therapeutic Biologic Revolution.

Science.gov (United States)

Degrazio, Dominick

Many pharmaceutical companies are transitioning their research and development drug product pipeline from traditional small-molecule injectables to the dimension of evolving therapeutic biologics. Important concerns associated with this changeover are becoming forefront, as challenges develop of varying complexity uncommon with the synthesis and production of traditional drugs. Therefore, alternative measures must be established that aim to preserve the efficacy and functionality of a biologic that might not be implemented for small molecules. Conserving protein stability is relative to perpetuating a net equilibrium of both intrinsic and extrinsic factors. Key to sustaining this balance is the ability of container-closure systems to maintain their compatibility with the ever-changing dynamics of therapeutic biologics. Failure to recognize and adjust the material properties of packaging components to support compatibility with therapeutic biologics can compromise patient safety, drug productivity, and biological stability. This review will examine the differences between small-molecule drugs and therapeutic biologics, lay a basic foundation for understanding the stability of therapeutic biologics, and demonstrate potential sources of container-closure systems' incompatibilities with therapeutic biologics at a mechanistic level. Many pharmaceutical companies are transitioning their research and development drug product pipeline from traditional small-molecule injectables to recombinantly derived therapeutic biologics. Concerns associated with this transformation are becoming prominent, as therapeutic biologics are uncharacteristic to small-molecule drugs. Maintaining the stability of a therapeutic biologic is a combination of balancing intrinsic factors and external elements within the biologic's microenvironment. An important aspect of this balance is relegated to the overall compatibility of primary, parenteral container-closure systems with therapeutic biologics

Floral biology and the effects of plant-pollinator interaction on ...

African Journals Online (AJOL)

Reproductive biology and patterns of plant-pollinator interaction are fundamental to gene flow, diversity and evolutionary success of plants. Consequently, we examined the magnitude of insect-plant interaction based on the dynamics of breeding systems and floral biology and their effects on pollination intensity, fruit and ...

Dynamic MR imaging of pituitary adenoma

International Nuclear Information System (INIS)

Miki, Yukio; Nishizawa, Sadahiko; Kuroda, Yasumasa; Keyaki, Atsushi; Nabeshima, Sachio; Kawamura, Junichiro; Matsuo, Michimasa

1990-01-01

The authors performed serial dynamic MR imaging in patients with 10 normal pituitary and 21 pituitary adenoma utilizing spin-echo sequence with a very short repetition time (SE 100/15) every minute immediately after a bolus injection of Gd-DTPA. Usual T 1 -weighted images (SE 600/15) were also obtained before and after the dynamic study. Pituitary adenomas included 10 adenomas confirmed by surgery, 4 adenomas confirmed by biologic data, and 7 postoperative adenomas. Out of 10 patients who underwent surgery after dynamic MRI, 9 patients underwent postoperative dynamic MRI. In normal patients, the pituitary gland was markedly enhanced on the early-phase images of the dynamic study, followed by gradual decrease of intensity throughout the dynamic study. In cases of microadenomas, the contrast between the normal pituitary gland and adenoma is better than that on the usual T 1 -weighted images by marked enhancement of the normal pituitary gland. Dynamic images clearly showed the residual normal pituitary glands in all cases of macroadenoma larger than 15 mm in diameter, whereas usual contrast-enhanced images showed the normal pituitary gland only in one case. In all patients who underwent both preoperative and postoperative dynamic MRI, postoperative dynamic MRI showed the normal pituitary glands which are markedly enhanced on the early-phase images in the sites which correspond to the preoperative dynamic study. The normal residual anterior gland was also visualized in four out of 7 patients who received only postoperative dynamic MRI. Dynamic MRI is a strong diagnostic modality for visualizing microadenoma and for visualizing the normal pituitary gland in cases of preoperative and postoperative macroadenoma. (author)

Creative design inspired by biological knowledge: Technologies and methods

Science.gov (United States)

Tan, Runhua; Liu, Wei; Cao, Guozhong; Shi, Yuan

2018-05-01

Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.

Dynamic simulation and modeling of the motion modes produced during the 3D controlled manipulation of biological micro/nanoparticles based on the AFM.

Science.gov (United States)

Saraee, Mahdieh B; Korayem, Moharam H

2015-08-07

Determining the motion modes and the exact position of a particle displaced during the manipulation process is of special importance. This issue becomes even more important when the studied particles are biological micro/nanoparticles and the goals of manipulation are the transfer of these particles within body cells, repair of cancerous cells and the delivery of medication to damaged cells. However, due to the delicate nature of biological nanoparticles and their higher vulnerability, by obtaining the necessary force of manipulation for the considered motion mode, we can prevent the sample from interlocking with or sticking to the substrate because of applying a weak force or avoid damaging the sample due to the exertion of excessive force. In this paper, the dynamic behaviors and the motion modes of biological micro/nanoparticles such as DNA, yeast, platelet and bacteria due to the 3D manipulation effect have been investigated. Since the above nanoparticles generally have a cylindrical shape, the cylindrical contact models have been employed in an attempt to more precisely model the forces exerted on the nanoparticle during the manipulation process. Also, this investigation has performed a comprehensive modeling and simulation of all the possible motion modes in 3D manipulation by taking into account the eccentricity of the applied load on the biological nanoparticle. The obtained results indicate that unlike the macroscopic scale, the sliding of nanoparticle on substrate in nano-scale takes place sooner than the other motion modes and that the spinning about the vertical and transverse axes and the rolling of nanoparticle occur later than the other motion modes. The simulation results also indicate that the applied force necessary for the onset of nanoparticle movement and the resulting motion mode depend on the size and aspect ratio of the nanoparticle. Copyright © 2015 Elsevier Ltd. All rights reserved.

Autonomy and Fear of Synthetic Biology: How Can Patients' Autonomy Be Enhanced in the Field of Synthetic Biology? A Qualitative Study with Stable Patients.

Science.gov (United States)

Rakic, Milenko; Wienand, Isabelle; Shaw, David; Nast, Rebecca; Elger, Bernice S

2017-04-01

We analyzed stable patients' views regarding synthetic biology in general, the medical application of synthetic biology, and their potential participation in trials of synthetic biology in particular. The aim of the study was to find out whether patients' views and preferences change after receiving more detailed information about synthetic biology and its clinical applications. The qualitative study was carried out with a purposive sample of 36 stable patients, who suffered from diabetes or gout. Interviews were transcribed verbatim, translated and fully anonymized. Thematic analysis was applied in order to examine stable patients' attitudes towards synthetic biology, its medical application, and their participation in trials. When patients were asked about synthetic biology in general, most of them were anxious that something uncontrollable could be created. After a concrete example of possible future treatment options, patients started to see synthetic biology in a more positive way. Our study constitutes an important first empirical insight into stable patients' views on synthetic biology and into the kind of fears triggered by the term "synthetic biology." Our results show that clear and concrete information can change patients' initial negative feelings towards synthetic biology. Information should thus be transmitted with great accuracy and transparency in order to reduce irrational fears of patients and to minimize the risk that researchers present facts too positively for the purposes of persuading patients to participate in clinical trials. Potential participants need to be adequately informed in order to be able to autonomously decide whether to participate in human subject research involving synthetic biology.

Introduction to stochastic models in biology

DEFF Research Database (Denmark)

Ditlevsen, Susanne; Samson, Adeline

2013-01-01

This chapter is concerned with continuous time processes, which are often modeled as a system of ordinary differential equations (ODEs). These models assume that the observed dynamics are driven exclusively by internal, deterministic mechanisms. However, real biological systems will always be exp...

Researchers study decontamination of chemical, biological warfare agents

OpenAIRE

Trulove, Susan

2007-01-01

The U.S. Army Research Office has awarded Virginia Tech a $680,000 grant over two years to build an instrument that can be used to study the chemistry of gases that will decompose both chemical and biological warfare agents on surfaces.

Complex and unexpected dynamics in simple genetic regulatory networks

Science.gov (United States)

Borg, Yanika; Ullner, Ekkehard; Alagha, Afnan; Alsaedi, Ahmed; Nesbeth, Darren; Zaikin, Alexey

2014-03-01

One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.

Study of β-NMR for Liquid Biological Samples

CERN Document Server

Beattie, Caitlin

2017-01-01

β-NMR is an exotic form of NMR spectroscopy that allows for the characterization of matter based on the anisotropic β-decay of radioactive probe nuclei. This has been shown to be an effective spectroscopic technique for many different compounds, but its use for liquid biological samples is relatively unexplored. The work at the VITO line of ISOLDE seeks to employ this technique to study such samples. Currently, preparations are being made for an experiment to characterize DNA G-quadruplexes and their interactions with stabilizing cations. More specifically, the work in which I engaged as a summer student focused on the experiment’s liquid handling system and the stability of the relevant biological samples under vacuum.

Contributions to the Study of Dynamic Absorbers, a Case Study

Directory of Open Access Journals (Sweden)

Monica Balcau

2012-01-01

Full Text Available Dynamic absorbers are used to reduce torsional vibrations. This paper studies the effect of a dynamic absorber attached to a mechanical system formed of three reduced masses which are acted on by one, two or three order x harmonics of a disruptive force.

Topology in Molecular Biology

CERN Document Server

Monastyrsky, Michail Ilych

2007-01-01

The book presents a class of new results in molecular biology for which topological methods and ideas are important. These include: the large-scale conformation properties of DNA; computational methods (Monte Carlo) allowing the simulation of large-scale properties of DNA; the tangle model of DNA recombination and other applications of Knot theory; dynamics of supercoiled DNA and biocatalitic properties of DNA; the structure of proteins; and other very recent problems in molecular biology. The text also provides a short course of modern topology intended for the broad audience of biologists and physicists. The authors are renowned specialists in their fields and some of the new results presented here are documented for the first time in monographic form.

Theoretical studies of combustion dynamics

Energy Technology Data Exchange (ETDEWEB)

Bowman, J.M. [Emory Univ., Atlanta, GA (United States)

1993-12-01

The basic objectives of this research program are to develop and apply theoretical techniques to fundamental dynamical processes of importance in gas-phase combustion. There are two major areas currently supported by this grant. One is reactive scattering of diatom-diatom systems, and the other is the dynamics of complex formation and decay based on L{sup 2} methods. In all of these studies, the authors focus on systems that are of interest experimentally, and for which potential energy surfaces based, at least in part, on ab initio calculations are available.

Characteristic responses of biological and nanoscale systems in the terahertz frequency range

Energy Technology Data Exchange (ETDEWEB)

Angeluts, A A; Balakin, A V; Evdokimov, M G; Ozheredov, I A; Sapozhnikov, D A; Solyankin, P M; Shkurinov, A P [International Laser Center, M. V. Lomonosov Moscow State University, Moscow (Russian Federation); Esaulkov, M N; Nazarov, M M [Institute on Laser and Information Technologies, Russian Academy of Sciences, Shatura, Moscow Region (Russian Federation); Cherkasova, O P [Institute of Laser Physics, Siberian Branch, Russian Academy of Sciences, Novosibirsk (Russian Federation)

2014-07-31

This paper briefly examines methods for the generation of pulsed terahertz radiation and principles of pulsed terahertz spectroscopy, an advanced informative method for studies of complex biological and nanostructured systems. Some of its practical applications are described. Using a number of steroid hormones as examples, we demonstrate that terahertz spectroscopy in combination with molecular dynamics methods and computer simulation allows one to gain information about the structure of molecules in crystals. A 'terahertz colour vision' method is proposed for analysis of pulsed terahertz signals reflected from biological tissues and it is shown that this method can be effectively used to analyse the properties of biological tissues and for early skin cancer diagnosis. (laser biophotonics)

Temperature dependent dynamics of DegP-trimer: A molecular dynamics study

Directory of Open Access Journals (Sweden)

Nivedita Rai

2015-01-01

Full Text Available DegP is a heat shock protein from high temperature requirement protease A family, which reacts to the environmental stress conditions in an ATP independent way. The objective of the present analysis emerged from the temperature dependent functional diversity of DegP between chaperonic and protease activities at temperatures below and above 28 °C, respectively. DegP is a multimeric protein and the minimal functional unit, DegP-trimer, is of great importance in understanding the DegP pathway. The structural aspects of DegP-trimer with respect to temperature variation have been studied using molecular dynamics simulations (for 100 ns and principal component analysis to highlight the temperature dependent dynamics facilitating its functional diversity. The DegP-trimer revealed a pronounced dynamics at both 280 and 320 K, when compared to the dynamics observed at 300 K. The LA loop is identified as the highly flexible region during dynamics and at extreme temperatures, the residues 46–80 of LA loop express a flip towards right (at 280 and left ( at 320 K with respect to the fixed β-sheet connecting the LA loop of protease for which Phe46 acts as one of the key residues. Such dynamics of LA loop facilitates inter-monomeric interaction with the PDZ1 domain of the neighbouring monomer and explains its active participation when DegP exists as trimer. Hence, the LA loop mediated dynamics of DegP-trimer is expected to provide further insight into the temperature dependent dynamics of DegP towards the understanding of its assembly and functional diversity in the presence of substrate.

Improving the Timed Automata Approach to Biological Pathway Dynamics

NARCIS (Netherlands)

Langerak, R.; Pol, Jaco van de; Post, Janine N.; Schivo, Stefano; Aceto, Luca; Bacci, Giorgio; Bacci, Giovanni; Ingólfsdóttir, Anna; Legay, Axel; Mardare, Radu

2017-01-01

Biological systems such as regulatory or gene networks can be seen as a particular type of distributed systems, and for this reason they can be modeled within the Timed Automata paradigm, which was developed in the computer science context. However, tools designed to model distributed systems often

Application of Confocal Laser Scanning Microscopy in Biology and Medicine

OpenAIRE

I. A. Volkov; N. V. Frigo; L. F. Znamenskaya; O. R. Katunina

2014-01-01

Fluorescence confocal laser scanning microscopy and reflectance confocal laser scanning microscopy are up-to-date highend study methods. Confocal microscopy is used in cell biology and medicine. By using confocal microscopy, it is possible to study bioplasts and localization of protein molecules and other compounds relative to cell or tissue structures, and to monitor dynamic cell processes. Confocal microscopes enable layer-by-layer scanning of test items to create demonstrable 3D models. As...

Gas-Phase Molecular Dynamics: Theoretical Studies In Spectroscopy and Chemical Dynamics

Energy Technology Data Exchange (ETDEWEB)

Yu H. G.; Muckerman, J.T.

2012-05-29

The main goal of this program is the development and application of computational methods for studying chemical reaction dynamics and molecular spectroscopy in the gas phase. We are interested in developing rigorous quantum dynamics algorithms for small polyatomic systems and in implementing approximate approaches for complex ones. Particular focus is on the dynamics and kinetics of chemical reactions and on the rovibrational spectra of species involved in combustion processes. This research also explores the potential energy surfaces of these systems of interest using state-of-the-art quantum chemistry methods, and extends them to understand some important properties of materials in condensed phases and interstellar medium as well as in combustion environments.

Radiochemistry - Applications in the study of radical mechanisms of biological interest

International Nuclear Information System (INIS)

Foos, Jacques

1982-01-01

In biology, oxygen reducing processes give rise to the formation of intermediate radicals. One of the major breakthroughs of radiation chemistry of aqueous solutions is the identification of these compounds. The author describes the techniques used to study the reaction of these radicals (of radiolytic origin) with biological molecules [fr

Economic evaluation of the successful biological control of Azolla filiculoides in South Africa

CSIR Research Space (South Africa)

McConnachie, AJ

2003-09-01

Full Text Available that it was no longer considered a problem in South Africa. The results reflect the dynamics of biological control on site-specific survey information, and place higher benefit–cost ratios achieved in other national level studies in a better context. It also raises...

Learning (from) the errors of a systems biology model.

Science.gov (United States)

Engelhardt, Benjamin; Frőhlich, Holger; Kschischo, Maik

2016-02-11

Mathematical modelling is a labour intensive process involving several iterations of testing on real data and manual model modifications. In biology, the domain knowledge guiding model development is in many cases itself incomplete and uncertain. A major problem in this context is that biological systems are open. Missed or unknown external influences as well as erroneous interactions in the model could thus lead to severely misleading results. Here we introduce the dynamic elastic-net, a data driven mathematical method which automatically detects such model errors in ordinary differential equation (ODE) models. We demonstrate for real and simulated data, how the dynamic elastic-net approach can be used to automatically (i) reconstruct the error signal, (ii) identify the target variables of model error, and (iii) reconstruct the true system state even for incomplete or preliminary models. Our work provides a systematic computational method facilitating modelling of open biological systems under uncertain knowledge.

Short spatio-temporal variations in the population dynamics and biology of the deep-water rose shrimp Parapenaeus longirostris (Decapoda: Crustacea in the western Mediterranean

Directory of Open Access Journals (Sweden)

Beatriz Guijarro

2009-03-01

Full Text Available The deep-water rose shrimp Parapenaeus longirostris is a demersal decapod crustacean that is commercially exploited by trawl fleets. The present work compares its population dynamics, biology and condition in two locations (southern and north-western Mallorca in the Balearic Islands, western Mediterranean, separated by a distance of 120 km with different environmental conditions and explores the relationships between the species and certain environmental factors. Six multidisciplinary bimonthly surveys were carried out during 2003 and 2004 in these two locations (between 150 and 750 m depth in order to collect data on the demersal species with bottom trawl, the hydrography (temperature and salinity with CTD casts, and trophic resources (zooplankton in the water column and suprabenthos with Bongo net and Macer-GIROQ sledge respectively and sediments with a Shipeck dredge. The trawl fleets from both locations were monitored by monthly on board sampling and daily landings obtained from sales bills. Additional data was obtained from other trawl surveys. Temporal differences were detected both annually, with a decreasing trend over the last years in species abundance, and seasonally, in the biological indexes analysed. Bathymetric differences were also found in abundance, mean length, sex-ratio and condition of females. There were clear differences between the two locations studied, with higher abundance, condition and mean length and a lower length at first maturity for females in the north-western location. Trophic conditions could act as a link between geo-physical and biological changes. These short spatio-temporal differences could be due to the higher productivity found at this location, with higher density of preferred prey for the studied species together with adequate seafloor topography, sediment composition and hydrographical characteristics.

Center of cancer systems biology second annual workshop--tumor metronomics: timing and dose level dynamics.

Science.gov (United States)

Hahnfeldt, Philip; Hlatky, Lynn; Klement, Giannoula Lakka

2013-05-15

Metronomic chemotherapy, the delivery of doses in a low, regular manner so as to avoid toxic side effects, was introduced over 12 years ago in the face of substantial clinical and preclinical evidence supporting its tumor-suppressive capability. It constituted a marked departure from the classic maximum-tolerated dose (MTD) strategy, which, given its goal of rapid eradication, uses dosing sufficiently intense to require rest periods between cycles to limit toxicity. Even so, upfront tumor eradication is frequently not achieved with MTD, whereupon a de facto goal of longer-term tumor control is often pursued. As metronomic dosing has shown tumor control capability, even for cancers that have become resistant to the same drug delivered under MTD, the question arises whether it may be a preferable alternative dosing approach from the outset. To date, however, our knowledge of the coupled dynamics underlying metronomic dosing is neither sufficiently well developed nor widely enough disseminated to establish its actual potential. Meeting organizers thus felt the time was right, armed with new quantitative approaches, to call a workshop on "Tumor Metronomics: Timing and Dose Level Dynamics" to explore prospects for gaining a deeper, systems-level appreciation of the metronomics concept. The workshop proved to be a forum in which experts from the clinical, biologic, mathematical, and computational realms could work together to clarify the principles and underpinnings of metronomics. Among other things, the need for significant shifts in thinking regarding endpoints to be used as clinical standards of therapeutic progress was recognized. ©2013 AACR.

Radiolabelled substrates for studying biological effects of trace contaminants

International Nuclear Information System (INIS)

1975-01-01

A programme of coordinated isotopic tracer-aided investigations of the biological side-effects of foreign chemical residues in food and agriculture, initiated in 1973, was reviewed. The current status of representative investigations from the point of view of techniques and priorities was assessed. Such investigations involved radioactive substrates for studying DNA injury and its repair; 14 C-labelled acetylcholine as substrate for measuring enzyme inhibition due to the presence of, or exposure to, anticholinesteratic contaminants; radioactive substrates as indication of side-effects in non-target organisms and of their comparative susceptibilities; radioactive substrates as indicators of persistence or biodegradability of trace contaminants of soil or water; and labelled pools for studying the biological side-effects of trace contaminants. Priorities were identified

Microscopic study on dynamic barrier in fusion reactions

International Nuclear Information System (INIS)

Wu Xizhen; Tian Junlong; Zhao Kai; Li Zhuxia; Wang Ning

2004-01-01

The authors briefly review the fusion process of very heavy nuclear systems and some theoretical models. The authors propose a microscopic transport dynamic model, i.e. the Improved Quantum Molecular Dynamic model, for describing fusion reactions of heavy systems, in which the dynamical behavior of the fusion barrier in heavy fusion systems has been studied firstly. The authors find that with the incident energy decreasing the lowest dynamic barrier is obtained which approaches to the adiabatic static barrier and with increase of the incident energy the dynamic barrier goes up to the diabatic static barrier. The authors also indicate that how the dynamical fusion barrier is correlated with the development of the configuration of fusion partners along the fusion path. Associating the single-particle potentials obtained at different stages of fusion with the Two Center Shell Model, authors can study the time evolution of the single particle states of fusion system in configuration space of single particle orbits along the fusion path. (author)

Multi-level and hybrid modelling approaches for systems biology.

Science.gov (United States)

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

Biologically based neural circuit modelling for the study of fear learning and extinction

Science.gov (United States)

Nair, Satish S.; Paré, Denis; Vicentic, Aleksandra

2016-11-01

The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.

Simulation and Analysis of Complex Biological Processes: an Organisation Modelling Perspective

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.

2005-01-01

This paper explores how the dynamics of complex biological processes can be modelled and simulated as an organisation of multiple agents. This modelling perspective identifies organisational structure occurring in complex decentralised processes and handles complexity of the analysis of the dynamics

International Conference on Recent Advances in Mathematical Biology, Analysis and Applications

CERN Document Server

Saleem, M; Srivastava, H; Khan, Mumtaz; Merajuddin, M

2016-01-01

The book contains recent developments and contemporary research in mathematical analysis and in its application to problems arising from the biological and physical sciences. The book is of interest to readers who wish to learn of new research in such topics as linear and nonlinear analysis, mathematical biology and ecology, dynamical systems, graph theory, variational analysis and inequalities, functional analysis, differential and difference equations, partial differential equations, approximation theory, and chaos. All papers were prepared by participants at the International Conference on Recent Advances in Mathematical Biology, Analysis and Applications (ICMBAA-2015) held during 4–6 June 2015 in Aligarh, India. A focal theme of the conference was the application of mathematics to the biological sciences and on current research in areas of theoretical mathematical analysis that can be used as sophisticated tools for the study of scientific problems. The conference provided researchers, academicians and ...

Biological dosimetry of X-rays by micronuclei study

International Nuclear Information System (INIS)

Gomez, E.; Silva, A.; Navlet, J.

1991-01-01

Biological dosimetry consists of estimating absorbed doses for people exposed to radiation by mean biological methods. Several indicators used are based in hematological, biochemical an cytogenetics data, although nowadays without doubt, the cytogenetic method is considered to be the most reliable, in this case, the study of micronuclei in peripheral blood lymphocytes cytokinetic blocked can be related to absorbed dose through an experimental calibration curve. An experimental dose-response curve, using micronuclei assay for X-rays at 250 kVp, 43,79 rads/min and temperature 37 degree celsius has been produced. Experimental data is fitted to model Y=c+ α D+β D 2 where. Y is the number micronuclei per cell and D the dose. the curve is compared with those produced elsewhere

A multiscale analysis of nutrient transport and biological tissue growth in vitro

KAUST Repository

O'Dea, R. D.

2014-10-15

© The authors 2014. In this paper, we consider the derivation of macroscopic equations appropriate to describe the growth of biological tissue, employing a multiple-scale homogenization method to accommodate explicitly the influence of the underlying microscale structure of the material, and its evolution, on the macroscale dynamics. Such methods have been widely used to study porous and poroelastic materials; however, a distinguishing feature of biological tissue is its ability to remodel continuously in response to local environmental cues. Here, we present the derivation of a model broadly applicable to tissue engineering applications, characterized by cell proliferation and extracellular matrix deposition in porous scaffolds used within tissue culture systems, which we use to study coupling between fluid flow, nutrient transport, and microscale tissue growth. Attention is restricted to surface accretion within a rigid porous medium saturated with a Newtonian fluid; coupling between the various dynamics is achieved by specifying the rate of microscale growth to be dependent upon the uptake of a generic diffusible nutrient. The resulting macroscale model comprises a Darcy-type equation governing fluid flow, with flow characteristics dictated by the assumed periodic microstructure and surface growth rate of the porous medium, coupled to an advection-reaction equation specifying the nutrient concentration. Illustrative numerical simulations are presented to indicate the influence of microscale growth on macroscale dynamics, and to highlight the importance of including experimentally relevant microstructural information to correctly determine flow dynamics and nutrient delivery in tissue engineering applications.

Agent-Based Modeling in Molecular Systems Biology.

Science.gov (United States)

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-06-08

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

Evolutionary formalism from random Leslie matrices in biology

International Nuclear Information System (INIS)

Caceres, M.O.; Caceres-Saez, I.

2008-07-01

We present a perturbative formalism to deal with linear random matrix difference equations. We generalize the concept of the population growth rate when a Leslie matrix has random elements (i.e., characterizing the disorder in the vital parameters). The dominant eigenvalue of which defines the asymptotic dynamics of the mean value population vector state, is presented as the effective growth rate of a random Leslie model. This eigenvalue is calculated from the largest positive root of a secular polynomial. Analytical (exact and perturbative calculations) results are presented for several models of disorder. A 3 x 3 numerical example is applied to study the effective growth rate characterizing the long-time dynamics of a population biological case: the Tursiops sp. (author)

BioNSi: A Discrete Biological Network Simulator Tool.

Science.gov (United States)

Rubinstein, Amir; Bracha, Noga; Rudner, Liat; Zucker, Noga; Sloin, Hadas E; Chor, Benny

2016-08-05

Modeling and simulation of biological networks is an effective and widely used research methodology. The Biological Network Simulator (BioNSi) is a tool for modeling biological networks and simulating their discrete-time dynamics, implemented as a Cytoscape App. BioNSi includes a visual representation of the network that enables researchers to construct, set the parameters, and observe network behavior under various conditions. To construct a network instance in BioNSi, only partial, qualitative biological data suffices. The tool is aimed for use by experimental biologists and requires no prior computational or mathematical expertise. BioNSi is freely available at http://bionsi.wix.com/bionsi , where a complete user guide and a step-by-step manual can also be found.

Fluctuating Nonlinear Spring Model of Mechanical Deformation of Biological Particles.

Directory of Open Access Journals (Sweden)

Olga Kononova

2016-01-01

Full Text Available The mechanical properties of virus capsids correlate with local conformational dynamics in the capsid structure. They also reflect the required stability needed to withstand high internal pressures generated upon genome loading and contribute to the success of important events in viral infectivity, such as capsid maturation, genome uncoating and receptor binding. The mechanical properties of biological nanoparticles are often determined from monitoring their dynamic deformations in Atomic Force Microscopy nanoindentation experiments; but a comprehensive theory describing the full range of observed deformation behaviors has not previously been described. We present a new theory for modeling dynamic deformations of biological nanoparticles, which considers the non-linear Hertzian deformation, resulting from an indenter-particle physical contact, and the bending of curved elements (beams modeling the particle structure. The beams' deformation beyond the critical point triggers a dynamic transition of the particle to the collapsed state. This extreme event is accompanied by a catastrophic force drop as observed in the experimental or simulated force (F-deformation (X spectra. The theory interprets fine features of the spectra, including the nonlinear components of the FX-curves, in terms of the Young's moduli for Hertzian and bending deformations, and the structural damage dependent beams' survival probability, in terms of the maximum strength and the cooperativity parameter. The theory is exemplified by successfully describing the deformation dynamics of natural nanoparticles through comparing theoretical curves with experimental force-deformation spectra for several virus particles. This approach provides a comprehensive description of the dynamic structural transitions in biological and artificial nanoparticles, which is essential for their optimal use in nanotechnology and nanomedicine applications.

Studying chemical reactions in biological systems with MBN Explorer

DEFF Research Database (Denmark)

Sushko, Gennady B.; Solov'yov, Ilia A.; Verkhovtsev, Alexey V.

2016-01-01

The concept of molecular mechanics force field has been widely accepted nowadays for studying various processes in biomolecular systems. In this paper, we suggest a modification for the standard CHARMM force field that permits simulations of systems with dynamically changing molecular topologies....... The implementation of the modified force field was carried out in the popular program MBN Explorer, and, to support the development, we provide several illustrative case studies where dynamical topology is necessary. In particular, it is shown that the modified molecular mechanics force field can be applied...

Automated parameter estimation for biological models using Bayesian statistical model checking.

Science.gov (United States)

Hussain, Faraz; Langmead, Christopher J; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K

2015-01-01

Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.

Quantum Information Biology: From Information Interpretation of Quantum Mechanics to Applications in Molecular Biology and Cognitive Psychology

Science.gov (United States)

Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

2015-10-01

We discuss foundational issues of quantum information biology (QIB)—one of the most successful applications of the quantum formalism outside of physics. QIB provides a multi-scale model of information processing in bio-systems: from proteins and cells to cognitive and social systems. This theory has to be sharply distinguished from "traditional quantum biophysics". The latter is about quantum bio-physical processes, e.g., in cells or brains. QIB models the dynamics of information states of bio-systems. We argue that the information interpretation of quantum mechanics (its various forms were elaborated by Zeilinger and Brukner, Fuchs and Mermin, and D' Ariano) is the most natural interpretation of QIB. Biologically QIB is based on two principles: (a) adaptivity; (b) openness (bio-systems are fundamentally open). These principles are mathematically represented in the framework of a novel formalism— quantum adaptive dynamics which, in particular, contains the standard theory of open quantum systems.

Molecular dynamics studies of superionic conductors

International Nuclear Information System (INIS)

Rahman, A.; Vashishta, P.

1983-01-01

Structural and dynamical properties of superionic conductors AgI and CuI are studied using molecular dynamics (MD) techniques. The model of these superionic conductors is based on the use of effective pair potentials. To determine the constants in these potentials, cohesive energy and bulk modulus are used as input: in addition one uses notions of ionic size based on the known crystal structure. Salient features of the MD technique are outlined. Methods of treating long range Coulomb forces are discussed in detail. This includes the manner of doing Ewald sum for MD cells of arbitrary shape. Features that can be incorporated to expedite the MD calculations are also discussed. A novel MD technique which allows for a dynamically controlled variation of the shape and size of the MD cell is described briefly. The development of this novel technique has made it possible to study structural phase transitions in superionic conductors. 68 references, 17 figures, 2 tables

Comparative study of biological activity of glutathione, sodium ...

African Journals Online (AJOL)

Glutathione (GSH) and sodium tungstate (Na2WO4) are important pharmacological agents. They provide protection to cells against cytotoxic agents and thus reduce their cytotoxicity. It was of interest to study the biological activity of these two pharmacological active agents. Different strains of bacteria were used and the ...

Synthesis, biological evaluation and molecular docking studies of ...

African Journals Online (AJOL)

Synthesis, biological evaluation and molecular docking studies of Mannich bases derived from 1, 3, 4-oxadiazole- 2-thiones as potential urease inhibitors. ... Mannich bases (5-17) were subjected to in silico screening as urease inhibitors, using crystal structure of urease (Protein Data Bank ID: 5FSE) as a model enzyme.

Observation of dehydration dynamics in biological tissues with terahertz digital holography [Invited].

Science.gov (United States)

Guo, Lihan; Wang, Xinke; Han, Peng; Sun, Wenfeng; Feng, Shengfei; Ye, Jiasheng; Zhang, Yan

2017-05-01

A terahertz (THz) digital holographic imaging system is utilized to investigate natural dehydration processes in three types of biological tissues, including cattle, mutton, and pork. An image reconstruction algorithm is applied to remove the diffraction influence of THz waves and further improve clarity of THz images. From THz images of different biological specimens, distinctive water content as well as dehydration features of adipose and muscle tissues are precisely distinguished. By analyzing THz absorption spectra of these samples, temporal evolution characteristics of the absorbances for adipose and muscle tissues are described and compared in detail. Discrepancies between water retention ability of different animal tissues are also discussed. The imaging technique provides a valuable measurement platform for biological sensing.

Boolean modeling in systems biology: an overview of methodology and applications

International Nuclear Information System (INIS)

Wang, Rui-Sheng; Albert, Réka; Saadatpour, Assieh

2012-01-01

Mathematical modeling of biological processes provides deep insights into complex cellular systems. While quantitative and continuous models such as differential equations have been widely used, their use is obstructed in systems wherein the knowledge of mechanistic details and kinetic parameters is scarce. On the other hand, a wealth of molecular level qualitative data on individual components and interactions can be obtained from the experimental literature and high-throughput technologies, making qualitative approaches such as Boolean network modeling extremely useful. In this paper, we build on our research to provide a methodology overview of Boolean modeling in systems biology, including Boolean dynamic modeling of cellular networks, attractor analysis of Boolean dynamic models, as well as inferring biological regulatory mechanisms from high-throughput data using Boolean models. We finally demonstrate how Boolean models can be applied to perform the structural analysis of cellular networks. This overview aims to acquaint life science researchers with the basic steps of Boolean modeling and its applications in several areas of systems biology. (paper)

Dynamic stability of running: The effects of speed and leg amputations on the maximal Lyapunov exponent

International Nuclear Information System (INIS)

Look, Nicole; Arellano, Christopher J.; Grabowski, Alena M.; Kram, Rodger; McDermott, William J.; Bradley, Elizabeth

2013-01-01

In this paper, we study dynamic stability during running, focusing on the effects of speed, and the use of a leg prosthesis. We compute and compare the maximal Lyapunov exponents of kinematic time-series data from subjects with and without unilateral transtibial amputations running at a wide range of speeds. We find that the dynamics of the affected leg with the running-specific prosthesis are less stable than the dynamics of the unaffected leg and also less stable than the biological legs of the non-amputee runners. Surprisingly, we find that the center-of-mass dynamics of runners with two intact biological legs are slightly less stable than those of runners with amputations. Our results suggest that while leg asymmetries may be associated with instability, runners may compensate for this effect by increased control of their center-of-mass dynamics

Analysis of spatiotemporal metabolomic dynamics for sensitively monitoring biological alterations in cisplatin-induced acute kidney injury.

Science.gov (United States)

Irie, Miho; Hayakawa, Eisuke; Fujimura, Yoshinori; Honda, Youhei; Setoyama, Daiki; Wariishi, Hiroyuki; Hyodo, Fuminori; Miura, Daisuke

2018-01-29

Clinical application of the major anticancer drug, cisplatin, is limited by severe side effects, especially acute kidney injury (AKI) caused by nephrotoxicity. The detailed metabolic mechanism is still largely unknown. Here, we used an integrated technique combining mass spectrometry imaging (MSI) and liquid chromatography-mass spectrometry (LC-MS) to visualize the diverse spatiotemporal metabolic dynamics in the mouse kidney after cisplatin dosing. Biological responses to cisplatin was more sensitively detected within 24 h as a metabolic alteration, which is much earlier than possible with the conventional clinical chemistry method of blood urea nitrogen (BUN) measurement. Region-specific changes (e.g., medulla and cortex) in metabolites related to DNA damage and energy generation were observed over the 72-h exposure period. Therefore, this metabolomics approach may become a novel strategy for elucidating early renal responses to cisplatin, prior to the detection of kidney damage evaluated by conventional method. Copyright © 2018. Published by Elsevier Inc.

msiDBN: A Method of Identifying Critical Proteins in Dynamic PPI Networks

Directory of Open Access Journals (Sweden)

Yuan Zhang

2014-01-01

Full Text Available Dynamics of protein-protein interactions (PPIs reveals the recondite principles of biological processes inside a cell. Shown in a wealth of study, just a small group of proteins, rather than the majority, play more essential roles at crucial points of biological processes. This present work focuses on identifying these critical proteins exhibiting dramatic structural changes in dynamic PPI networks. First, a comprehensive way of modeling the dynamic PPIs is presented which simultaneously analyzes the activity of proteins and assembles the dynamic coregulation correlation between proteins at each time point. Second, a novel method is proposed, named msiDBN, which models a common representation of multiple PPI networks using a deep belief network framework and analyzes the reconstruction errors and the variabilities across the time courses in the biological process. Experiments were implemented on data of yeast cell cycles. We evaluated our network construction method by comparing the functional representations of the derived networks with two other traditional construction methods. The ranking results of critical proteins in msiDBN were compared with the results from the baseline methods. The results of comparison showed that msiDBN had better reconstruction rate and identified more proteins of critical value to yeast cell cycle process.

Evolutionary optimization with data collocation for reverse engineering of biological networks.

Science.gov (United States)

Tsai, Kuan-Yao; Wang, Feng-Sheng

2005-04-01

Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very efficient computational method to identify the model structure and parameters. Numerical integration for differential equations and finding global parameter values are still two major challenges in this field of the parameter estimation of nonlinear dynamic biological systems. We compare three techniques of parameter estimation for nonlinear dynamic biological systems. In the proposed scheme, the modified collocation method is applied to convert the differential equations to the system of algebraic equations. The observed time-course data are then substituted into the algebraic system equations to decouple system interactions in order to obtain the approximate model profiles. Hybrid differential evolution (HDE) with population size of five is able to find a global solution. The method is not only suited for parameter estimation but also can be applied for structure identification. The solution obtained by HDE is then used as the starting point for a local search method to yield the refined estimates.

Molecular dynamics studies of the dynamics of supercooled Lennard-Jones liquids

International Nuclear Information System (INIS)

De Leeuw, S.W.; Brakkee, M.J.D.

1990-01-01

Results are presented of molecular dynamics experiments, in which the Lennard-Jones liquid is cooled isobarically into the metastable temperature region below the freezing temperature. The variation of the density-density and transverse current correlation functions with temperature is studied. We observed a power-law behaviour for the temperature dependence of dynamical properties (viscosity and coefficienty of self-diffusion) with an exponent in good agreement with prediction of mode coupling theories and recent experimental results. (author). 23 refs, 5 figs

Study of the effects of radon in three biological systems

International Nuclear Information System (INIS)

Tavera, L.; Balcazar, M.; Lopez, A.; Brena, M.; Rosa, M.E. De la; Villalobos P, R.

2002-01-01

The radon and its decay products are responsible of the 3/4 parts of the exposure of the persons to the environmental radiation. The discovery at the end of XIX Century of the illnesses, mainly of cancer, which appeared in the presence of radon, lead to an accelerated growing of the radon studies: monitoring, dosimetry, effects on the persons, etc. Several epidemiological studies of radon in miners and population in general have been realized; advancing in the knowledge about the concentration-lung cancer risk relationship, but with discrepancies in the results depending on the concentration levels. Therefor, studies which consuming time, efforts and money go on doing. The research of the radon effects in biological systems different to human, allows to realize studies in less time, in controlled conditions and generally at lower cost, generating information about the alpha radiation effects in the cellular field. Therefor it was decided to study the response of three biological systems exposed to radon: an unicellular bacteria Escherichia Coli which was exposed directly to alpha particles from an electrodeposited source for determining the sensitivity limit of the chose technique. A plant, Tradescantia, for studying the cytogenetic effect of the system exposed to controlled concentrations of radon. An insect, Drosophila Melanogaster, for studying the genetic effects and the accumulated effects in several generations exposed to radon. In this work the experimental settlements are presented for the expositions of the systems and the biological results commenting the importance of these. (Author)

Biological Dosimetry of X-rays by micronuclei study

International Nuclear Information System (INIS)

Gomez, E.; Silva, A.; Navlet, J.

1991-01-01

Biological dosimetry consists of estimating absorbed doses for people exposed to radiation by mean biological methods. Several indicators used are based in haematological, biochemical an cytogenetics data, although nowadays without doubt, the cytogenetic method is considered to be the most reliable, in this case, the study of micronuclei in peripheral blood lymphocytes citokinetics blocked can be related to absorbed dose through an experimental calibration curve. An experimental dose-response curve, using micronuclei assay for X-rays at 250 kVp, 43,79 rads/min and temperature 37 degree centigree has been produced. Experimental data is fitted to model Y=C+ αD+BD''2 where Y is the number of micronuclei per cell and D the dose. The curve is compared with those produced elsewhere. (Author) 24 refs

Philosophical Basis and Some Historical Aspects of Systems Biology: From Hegel to Noble - Applications for Bioenergetic Research

Science.gov (United States)

Saks, Valdur; Monge, Claire; Guzun, Rita

2009-01-01

We live in times of paradigmatic changes for the biological sciences. Reductionism, that for the last six decades has been the philosophical basis of biochemistry and molecular biology, is being displaced by Systems Biology, which favors the study of integrated systems. Historically, Systems Biology - defined as the higher level analysis of complex biological systems - was pioneered by Claude Bernard in physiology, Norbert Wiener with the development of cybernetics, and Erwin Schrödinger in his thermodynamic approach to the living. Systems Biology applies methods inspired by cybernetics, network analysis, and non-equilibrium dynamics of open systems. These developments follow very precisely the dialectical principles of development from thesis to antithesis to synthesis discovered by Hegel. Systems Biology opens new perspectives for studies of the integrated processes of energy metabolism in different cells. These integrated systems acquire new, system-level properties due to interaction of cellular components, such as metabolic compartmentation, channeling and functional coupling mechanisms, which are central for regulation of the energy fluxes. State of the art of these studies in the new area of Molecular System Bioenergetics is analyzed. PMID:19399243

A Molecular Dynamics Study of Lunasin | Singh | South African ...

African Journals Online (AJOL)

A Molecular Dynamics Study of Lunasin. ... profile of lunasin,using classical molecular dynamics (MD) simulations at the time scale of 300 ns. ... Keywords: Lunasin, molecular dynamics, amber, CLASICO, α-helix, β-turn, PTRAJ, RGD, RMSD ...

Studying protein assembly with reversible Brownian dynamics of patchy particles

International Nuclear Information System (INIS)

Klein, Heinrich C. R.; Schwarz, Ulrich S.

2014-01-01

Assembly of protein complexes like virus shells, the centriole, the nuclear pore complex, or the actin cytoskeleton is strongly determined by their spatial structure. Moreover, it is becoming increasingly clear that the reversible nature of protein assembly is also an essential element for their biological function. Here we introduce a computational approach for the Brownian dynamics of patchy particles with anisotropic assemblies and fully reversible reactions. Different particles stochastically associate and dissociate with microscopic reaction rates depending on their relative spatial positions. The translational and rotational diffusive properties of all protein complexes are evaluated on-the-fly. Because we focus on reversible assembly, we introduce a scheme which ensures detailed balance for patchy particles. We then show how the macroscopic rates follow from the microscopic ones. As an instructive example, we study the assembly of a pentameric ring structure, for which we find excellent agreement between simulation results and a macroscopic kinetic description without any adjustable parameters. This demonstrates that our approach correctly accounts for both the diffusive and reactive processes involved in protein assembly

Studying protein assembly with reversible Brownian dynamics of patchy particles

Energy Technology Data Exchange (ETDEWEB)

Klein, Heinrich C. R. [Institute for Theoretical Physics, Heidelberg University, 69120 Heidelberg (Germany); Schwarz, Ulrich S., E-mail: ulrich.schwarz@bioquant.uni-heidelberg.de [Institute for Theoretical Physics, Heidelberg University, 69120 Heidelberg (Germany); BioQuant, Heidelberg University, 69120 Heidelberg (Germany)

2014-05-14

Assembly of protein complexes like virus shells, the centriole, the nuclear pore complex, or the actin cytoskeleton is strongly determined by their spatial structure. Moreover, it is becoming increasingly clear that the reversible nature of protein assembly is also an essential element for their biological function. Here we introduce a computational approach for the Brownian dynamics of patchy particles with anisotropic assemblies and fully reversible reactions. Different particles stochastically associate and dissociate with microscopic reaction rates depending on their relative spatial positions. The translational and rotational diffusive properties of all protein complexes are evaluated on-the-fly. Because we focus on reversible assembly, we introduce a scheme which ensures detailed balance for patchy particles. We then show how the macroscopic rates follow from the microscopic ones. As an instructive example, we study the assembly of a pentameric ring structure, for which we find excellent agreement between simulation results and a macroscopic kinetic description without any adjustable parameters. This demonstrates that our approach correctly accounts for both the diffusive and reactive processes involved in protein assembly.

Sex matters: The effects of biological sex on adipose tissue biology and energy metabolism

Directory of Open Access Journals (Sweden)

Teresa G. Valencak

2017-08-01

Full Text Available Adipose tissue is a complex and multi-faceted organ. It responds dynamically to internal and external stimuli, depending on the developmental stage and activity of the organism. The most common functional subunits of adipose tissue, white and brown adipocytes, regulate and respond to endocrine processes, which then determine metabolic rate as well as adipose tissue functions. While the molecular aspects of white and brown adipose biology have become clearer in the recent past, much less is known about sex-specific differences in regulation and deposition of adipose tissue, and the specific role of the so-called pink adipocytes during lactation in females. This review summarises the current understanding of adipose tissue dynamics with a focus on sex-specific differences in adipose tissue energy metabolism and endocrine functions, focussing on mammalian model organisms as well as human-derived data. In females, pink adipocytes trans-differentiate during pregnancy from subcutaneous white adipocytes and are responsible for milk-secretion in mammary glands. Overlooking biological sex variation may ultimately hamper clinical treatments of many aspects of metabolic disorders. Keywords: Body fatness, Adipose tissue, Sex-specific differences, Adipokines, Adipocytes, Obesity, Energy metabolism

Synthetic multicellular oscillatory systems: controlling protein dynamics with genetic circuits

International Nuclear Information System (INIS)

Koseska, Aneta; Volkov, Evgenii; Kurths, Juergen

2011-01-01

Synthetic biology is a relatively new research discipline that combines standard biology approaches with the constructive nature of engineering. Thus, recent efforts in the field of synthetic biology have given a perspective to consider cells as 'programmable matter'. Here, we address the possibility of using synthetic circuits to control protein dynamics. In particular, we show how intercellular communication and stochasticity can be used to manipulate the dynamical behavior of a population of coupled synthetic units and, in this manner, finely tune the expression of specific proteins of interest, e.g. in large bioreactors.

Coming out in Class: Challenges and Benefits of Active Learning in a Biology Classroom for LGBTQIA Students

Science.gov (United States)

Cooper, Katelyn M.; Brownell, Sara E.

2016-01-01

As we transition our undergraduate biology classrooms from traditional lectures to active learning, the dynamics among students become more important. These dynamics can be influenced by student social identities. One social identity that has been unexamined in the context of undergraduate biology is the spectrum of lesbian, gay, bisexual,…

Improving Satellite Compatible Microdevices to Study Biology in Space

Science.gov (United States)

Kalkus, Trevor; Snyder, Jessica; Paulino-Lima, Ivan; Rothschild, Lynn

2017-01-01

sense for biochemicals. (3) Developing a modular, semi-autonomous microfluidic device that can be easily adapted for a variety of common biological experiments. This versatility will allow for quicker and cheaper experimentation. These improvements to satellite experiment platforms have the potential to radically increase the return from NASA's biological and field studies with reduced development time, mass, and cost with increased robustness data and interpretation.

Research on condensed matter and atomic physics using major experimental facilities and devices: Physics, chemistry, biology. Reports on results. Vol. 3. 4. Chemistry. 5. Biology. 6. Development of methods and instruments

International Nuclear Information System (INIS)

1993-01-01

This report in three volumes substantiates the contents of the programme survey published in September 1989. The progress reports cover the following research areas: Vol. I, (1). Atomic and molecular physics - free atoms, molecules, macromolecules, clusters, matrix-isolated atoms and molecules. (2) Physics and chemistry of surfaces and interfaces - epitaxy, surface structure, adsorption, electrical, magnetic, and optical properties, thin films, synthetic layer structure. Vol. II, (3). Solid-state physics, and materials science -structural research, lattice dynamics, magnetic structure and dynamics, electronic states; load; spin and pulse density fluctuations; diffusion and internal motion, defects, unordered systems and liquids. Vol. III, (4). Chemistry - bonding and structure, kinetics and reaction mechanisms, polymer research, analysis and synthesis. (5). Biology, - structure and dynamics of biological macromolecules, membrane and cell biology. (6) Development of methods and instruments - neutron sources, synchrotron sources, special accelerators, research with interlinked systems and devices. (orig.) [de

Academic Preparation in Biology and Advocacy for Teaching Evolution: Biology versus Non-Biology Teachers

Science.gov (United States)

Nehm, Ross H.; Kim, Sun Young; Sheppard, Keith

2009-01-01

Despite considerable focus on evolution knowledge-belief relationships, little research has targeted populations with strong content backgrounds, such as undergraduate degrees in biology. This study (1) measured precertified biology and non-biology teachers' (n = 167) knowledge of evolution and the nature of science; (2) quantified teacher…

Structures in dynamics finite dimensional deterministic studies

CERN Document Server

Broer, HW; van Strien, SJ; Takens, F

1991-01-01

The study of non-linear dynamical systems nowadays is an intricate mixture of analysis, geometry, algebra and measure theory and this book takes all aspects into account. Presenting the contents of its authors' graduate courses in non-linear dynamical systems, this volume aims at researchers who wish to be acquainted with the more theoretical and fundamental subjects in non-linear dynamics and is designed to link the popular literature with research papers and monographs. All of the subjects covered in this book are extensively dealt with and presented in a pedagogic

Dynamic games theory and applications

CERN Document Server

Haurie, Alain

2005-01-01

Dynamic games continue to attract strong interest from researchers interested in modeling competitive and conflict situations to study the behavior of players (decision-makers) and to predict the outcome of such situations in many areas including engineering, economics, management science, military, biology, and political science. This collection of articles by established researchers is an excellent reference covering a wide range of emerging and revisited problems in both cooperative and non-cooperative games.

Self-Supervised Dynamical Systems

Science.gov (United States)

Zak, Michail

2003-01-01

Some progress has been made in a continuing effort to develop mathematical models of the behaviors of multi-agent systems known in biology, economics, and sociology (e.g., systems ranging from single or a few biomolecules to many interacting higher organisms). Living systems can be characterized by nonlinear evolution of probability distributions over different possible choices of the next steps in their motions. One of the main challenges in mathematical modeling of living systems is to distinguish between random walks of purely physical origin (for instance, Brownian motions) and those of biological origin. Following a line of reasoning from prior research, it has been assumed, in the present development, that a biological random walk can be represented by a nonlinear mathematical model that represents coupled mental and motor dynamics incorporating the psychological concept of reflection or self-image. The nonlinear dynamics impart the lifelike ability to behave in ways and to exhibit patterns that depart from thermodynamic equilibrium. Reflection or self-image has traditionally been recognized as a basic element of intelligence. The nonlinear mathematical models of the present development are denoted self-supervised dynamical systems. They include (1) equations of classical dynamics, including random components caused by uncertainties in initial conditions and by Langevin forces, coupled with (2) the corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces, denoted supervising forces, composed of probability densities and functionals thereof. The equations of classical mechanics represent motor dynamics that is, dynamics in the traditional sense, signifying Newton s equations of motion. The evolution of the probability densities represents mental dynamics or self-image. Then the interaction between the physical and

Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

Science.gov (United States)

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

2010-02-01

The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell

A mathematical framework for agent based models of complex biological networks.

Science.gov (United States)

Hinkelmann, Franziska; Murrugarra, David; Jarrah, Abdul Salam; Laubenbacher, Reinhard

2011-07-01

Agent-based modeling and simulation is a useful method to study biological phenomena in a wide range of fields, from molecular biology to ecology. Since there is currently no agreed-upon standard way to specify such models, it is not always easy to use published models. Also, since model descriptions are not usually given in mathematical terms, it is difficult to bring mathematical analysis tools to bear, so that models are typically studied through simulation. In order to address this issue, Grimm et al. proposed a protocol for model specification, the so-called ODD protocol, which provides a standard way to describe models. This paper proposes an addition to the ODD protocol which allows the description of an agent-based model as a dynamical system, which provides access to computational and theoretical tools for its analysis. The mathematical framework is that of algebraic models, that is, time-discrete dynamical systems with algebraic structure. It is shown by way of several examples how this mathematical specification can help with model analysis. This mathematical framework can also accommodate other model types such as Boolean networks and the more general logical models, as well as Petri nets.

High-temperature dynamic behavior in bulk liquid water: A molecular dynamics simulation study using the OPC and TIP4P-Ew potentials

Science.gov (United States)

Gabrieli, Andrea; Sant, Marco; Izadi, Saeed; Shabane, Parviz Seifpanahi; Onufriev, Alexey V.; Suffritti, Giuseppe B.

2018-02-01

Classical molecular dynamics simulations were performed to study the high-temperature (above 300 K) dynamic behavior of bulk water, specifically the behavior of the diffusion coefficient, hydrogen bond, and nearest-neighbor lifetimes. Two water potentials were compared: the recently proposed "globally optimal" point charge (OPC) model and the well-known TIP4P-Ew model. By considering the Arrhenius plots of the computed inverse diffusion coefficient and rotational relaxation constants, a crossover from Vogel-Fulcher-Tammann behavior to a linear trend with increasing temperature was detected at T* ≈ 309 and T* ≈ 285 K for the OPC and TIP4P-Ew models, respectively. Experimentally, the crossover point was previously observed at T* ± 315-5 K. We also verified that for the coefficient of thermal expansion α P ( T, P), the isobaric α P ( T) curves cross at about the same T* as in the experiment. The lifetimes of water hydrogen bonds and of the nearest neighbors were evaluated and were found to cross near T*, where the lifetimes are about 1 ps. For T T*, water behaves more like a simple liquid. The fact that T* falls within the biologically relevant temperature range is a strong motivation for further analysis of the phenomenon and its possible consequences for biomolecular systems.

Phytoplankton biomass dynamics and environmental variables around the Rocas Atoll Biological Reserve, South Atlantic

Directory of Open Access Journals (Sweden)

Marina Cavalcanti Jales

2015-12-01

Full Text Available Abstract The Rocas Atoll Biological Reserve is located in the Atlantic Ocean, at 3º 51' S and 33º 49' W. It lies 143 nautical miles from the City of Natal, Rio Grande do Norte (Brazil. The purpose of this study was to analyze the hydrology, water masses, currents and chlorophyll a content to determine the dynamics of phytoplankton biomass around the Rocas Atoll. Samples were collected in July 2010 in the area around the Atoll, using the Research Vessel Cruzeiro do Sul of the Brazilian Navy. Two transects were established according to the surface currents, one of which at the southeast of the Atoll (SE and the other at norwest (NW. Three collection points were determined on each of these transects. Samples were collected at different depths (surface and DCM - Deep Chlorophyll Maximum and different times (day and night. According to PCA (Principal Component Analysis, the nutrients analyzed, DIN (dissolved inorganic nitrogen, DIP (dissolved inorganic phosphorus and silicate, were inversely correlated with temperature and dissolved oxygen. Most environmental variables showed a significant increase due to the turbulence on the Northwest transect. There was an increase in the concentration of chlorophyll a and nutrients when the temperature and oxygen in the mixed layer was reduced due to the influence of the SACW (South Atlantic Central Water. Despite the increase observed in some variables such as nutrient salts and chlorophyll a, the temperature in the mixed layer attained a mean value of 23.23 ºC due to the predominance of Tropical Water. The increase of the phytoplankton biomass on the NW transect was, therefore, caused by the "island effect" and not by upwelling.

Integrating systems biology models and biomedical ontologies.

Science.gov (United States)

Hoehndorf, Robert; Dumontier, Michel; Gennari, John H; Wimalaratne, Sarala; de Bono, Bernard; Cook, Daniel L; Gkoutos, Georgios V

2011-08-11

Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

Synthetic biology analysed tools for discussion and evaluation

CERN Document Server

2016-01-01

Synthetic biology is a dynamic, young, ambitious, attractive, and heterogeneous scientific discipline. It is constantly developing and changing, which makes societal evaluation of this emerging new science a challenging task, prone to misunderstandings. Synthetic biology is difficult to capture, and confusion arises not only regarding which part of synthetic biology the discussion is about, but also with respect to the underlying concepts in use. This book offers a useful toolbox to approach this complex and fragmented field. It provides a biological access to the discussion using a 'layer' model that describes the connectivity of synthetic or semisynthetic organisms and cells to the realm of natural organisms derived by evolution. Instead of directly reviewing the field as a whole, firstly our book addresses the characteristic features of synthetic biology that are relevant to the societal discussion. Some of these features apply only to parts of synthetic biology, whereas others are relevant to synthetic bi...

How causal analysis can reveal autonomy in models of biological systems

Science.gov (United States)

Marshall, William; Kim, Hyunju; Walker, Sara I.; Tononi, Giulio; Albantakis, Larissa

2017-11-01

Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system-whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause-effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause-effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast (Schizosaccharomyces pombe) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem. This article is part of the themed issue 'Reconceptualizing the origins of life'.

Artificial biomembrane morphology: a dissipative particle dynamics study.

Science.gov (United States)

Becton, Matthew; Averett, Rodney; Wang, Xianqiao

2017-09-18

Artificial membranes mimicking biological structures are rapidly breaking new ground in the areas of medicine and soft-matter physics. In this endeavor, we use dissipative particle dynamics simulation to investigate the morphology and behavior of lipid-based biomembranes under conditions of varied lipid density and self-interaction. Our results show that a less-than-normal initial lipid density does not create the traditional membrane; but instead results in the formation of a 'net', or at very low densities, a series of disparate 'clumps' similar to the micelles formed by lipids in nature. When the initial lipid density is high, a membrane forms, but due to the large number of lipids, the naturally formed membrane would be larger than the simulation box, leading to 'rippling' behavior as the excess repulsive force of the membrane interior overcomes the bending energy of the membrane. Once the density reaches a certain point however, 'bubbles' appear inside the membrane, reducing the rippling behavior and eventually generating a relatively flat, but thick, structure with micelles of water inside the membrane itself. Our simulations also demonstrate that the interaction parameter between individual lipids plays a significant role in the formation and behavior of lipid membrane assemblies, creating similar structures as the initial lipid density distribution. This work provides a comprehensive approach to the intricacies of lipid membranes, and offers a guideline to design biological or polymeric membranes through self-assembly processes as well as develop novel cellular manipulation and destruction techniques.

Moessbauer spectroscopic studies of magnetically ordered biological materials

International Nuclear Information System (INIS)

Dickson, D.P.E.

1987-01-01

This paper discusses recent work showing the application of Moessbauer spectroscopy to the study of the properties of the magnetically ordered materials which occur in a variety of biological systems. These materials display a diversity of behaviour which provides good examples of the various possibilities which can arise with iron-containing particles of different compositions and sizes. (orig.)

An Analytical Study of Prostate-Specific Antigen Dynamics.

Science.gov (United States)

Esteban, Ernesto P; Deliz, Giovanni; Rivera-Rodriguez, Jaileen; Laureano, Stephanie M

2016-01-01

The purpose of this research is to carry out a quantitative study of prostate-specific antigen dynamics for patients with prostatic diseases, such as benign prostatic hyperplasia (BPH) and localized prostate cancer (LPC). The proposed PSA mathematical model was implemented using clinical data of 218 Japanese patients with histological proven BPH and 147 Japanese patients with LPC (stages T2a and T2b). For prostatic diseases (BPH and LPC) a nonlinear equation was obtained and solved in a close form to predict PSA progression with patients' age. The general solution describes PSA dynamics for patients with both diseases LPC and BPH. Particular solutions allow studying PSA dynamics for patients with BPH or LPC. Analytical solutions have been obtained and solved in a close form to develop nomograms for a better understanding of PSA dynamics in patients with BPH and LPC. This study may be useful to improve the diagnostic and prognosis of prostatic diseases.

Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells.

Directory of Open Access Journals (Sweden)

Hongbo Shi

Full Text Available Myocardial infarction (MI is a serious heart disease and a leading cause of mortality and morbidity worldwide. Although some molecules (genes, miRNAs and transcription factors (TFs associated with MI have been studied in a specific pathological context, their dynamic characteristics in gene expressions, biological functions and regulatory interactions in MI progression have not been fully elucidated to date. In the current study, we analyzed time-series RNA expression data from peripheral blood mononuclear cells. We observed that significantly differentially expressed genes were sharply up- or down-regulated in the acute phase of MI, and then changed slowly until the chronic phase. Biological functions involved at each stage of MI were identified. Additionally, dynamic miRNA-TF co-regulatory networks were constructed based on the significantly differentially expressed genes and miRNA-TF co-regulatory motifs, and the dynamic interplay of miRNAs, TFs and target genes were investigated. Finally, a new panel of candidate diagnostic biomarkers (STAT3 and ICAM1 was identified to have discriminatory capability for patients with or without MI, especially the patients with or without recurrent events. The results of the present study not only shed new light on the understanding underlying regulatory mechanisms involved in MI progression, but also contribute to the discovery of true diagnostic biomarkers for MI.

Genome Scale Modeling in Systems Biology: Algorithms and Resources

Science.gov (United States)

Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

2014-01-01

In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

Converting differential-equation models of biological systems to membrane computing.

Science.gov (United States)

Muniyandi, Ravie Chandren; Zin, Abdullah Mohd; Sanders, J W

2013-12-01

This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Artificial cell mimics as simplified models for the study of cell biology.

Science.gov (United States)

Salehi-Reyhani, Ali; Ces, Oscar; Elani, Yuval

2017-07-01

Living cells are hugely complex chemical systems composed of a milieu of distinct chemical species (including DNA, proteins, lipids, and metabolites) interconnected with one another through a vast web of interactions: this complexity renders the study of cell biology in a quantitative and systematic manner a difficult task. There has been an increasing drive towards the utilization of artificial cells as cell mimics to alleviate this, a development that has been aided by recent advances in artificial cell construction. Cell mimics are simplified cell-like structures, composed from the bottom-up with precisely defined and tunable compositions. They allow specific facets of cell biology to be studied in isolation, in a simplified environment where control of variables can be achieved without interference from a living and responsive cell. This mini-review outlines the core principles of this approach and surveys recent key investigations that use cell mimics to address a wide range of biological questions. It will also place the field in the context of emerging trends, discuss the associated limitations, and outline future directions of the field. Impact statement Recent years have seen an increasing drive to construct cell mimics and use them as simplified experimental models to replicate and understand biological phenomena in a well-defined and controlled system. By summarizing the advances in this burgeoning field, and using case studies as a basis for discussion on the limitations and future directions of this approach, it is hoped that this minireview will spur others in the experimental biology community to use artificial cells as simplified models with which to probe biological systems.

Reachability in Biochemical Dynamical Systems by Quantitative Discrete Approximation (extended abstract

Directory of Open Access Journals (Sweden)

L. Brim

2011-09-01

Full Text Available In this paper, a novel computational technique for finite discrete approximation of continuous dynamical systems suitable for a significant class of biochemical dynamical systems is introduced. The method is parameterized in order to affect the imposed level of approximation provided that with increasing parameter value the approximation converges to the original continuous system. By employing this approximation technique, we present algorithms solving the reachability problem for biochemical dynamical systems. The presented method and algorithms are evaluated on several exemplary biological models and on a real case study.

Biological studies of the U.S. subseabed disposal program

International Nuclear Information System (INIS)

Gomez, L.S.; Marietta, M.G.; Hessler, R.R.; Smith, K.L. Jr.; Talbert, D.M.; Yayanos, A.A.; Jackson, D.W.

1980-01-01

The Subseabed Disposal Program (SDP) of the U.S. is assessing the feasibility of emplacing high level radioactive wastes (HLW) within deep-sea sediments and is developing the means for assessing the feasibility of the disposal practices of other nations. This paper discusses the role and status of biological research in the SDP. Studies of the disposal methods and of the conceived barriers (canister, waste form and sediment) suggest that biological knowledge will be principally needed to address the impact of accidental releases of radionuclides. Current experimental work is focusing on the deep-sea ecosystem to determine: (1) the structure of benthic communities, including their microbial component; (2) the faunal composition of deep midwater nekton; (3) the biology of deep-sea amphipods; (4) benthic community metabolism; (5) the rates of bacterial processes; (6) the metabolism of deep-sea animals, and (7) the radiation sensitivity of deep-sea organisms. A multi-compartment model is being developed to assess quantitatively, the impact (on the environment and on man) of releases of radionuclides into the sea

Stable States of Biological Organisms

Science.gov (United States)

Yukalov, V. I.; Sornette, D.; Yukalova, E. P.; Henry, J.-Y.; Cobb, J. P.

2009-04-01

A novel model of biological organisms is advanced, treating an organism as a self-consistent system subject to a pathogen flux. The principal novelty of the model is that it describes not some parts, but a biological organism as a whole. The organism is modeled by a five-dimensional dynamical system. The organism homeostasis is described by the evolution equations for five interacting components: healthy cells, ill cells, innate immune cells, specific immune cells, and pathogens. The stability analysis demonstrates that, in a wide domain of the parameter space, the system exhibits robust structural stability. There always exist four stable stationary solutions characterizing four qualitatively differing states of the organism: alive state, boundary state, critical state, and dead state.

Molecular Dynamics Studies of Nanofluidic Devices

DEFF Research Database (Denmark)

Zambrano Rodriguez, Harvey Alexander

of such devices. Computational nanofluidics complements experimental studies by providing detailed spatial and temporal information of the nanosystem. In this thesis, we conduct molecular dynamics simulations to study basic nanoscale devices. We focus our studies on the understanding of transport mechanism...... to drive fluids and solids at the nanoscale. Specifically, we present the results of three different research projects. Throughout the first part of this thesis, we include a comprenhensive introduction to computational nanofluidics and to molecular simulations, and describe the molecular dynamics...... in opposite direction to the imposed thermal gradient also we measure higher velocities as higher thermal gradients are imposed. Secondly, we present an atomistic analysis of a molecular linear motor fabricated of coaxial carbon nanotubes and powered by thermal gradients. The MD simulation results indicate...

Solitary pulmonary nodules: Comparison of dynamic first-pass contrast-enhanced perfusion area-detector CT, dynamic first-pass contrast-enhanced MR imaging, and FDG PET/CT.

Science.gov (United States)

Ohno, Yoshiharu; Nishio, Mizuho; Koyama, Hisanobu; Seki, Shinichiro; Tsubakimoto, Maho; Fujisawa, Yasuko; Yoshikawa, Takeshi; Matsumoto, Sumiaki; Sugimura, Kazuro

2015-02-01

To prospectively compare the capabilities of dynamic perfusion area-detector computed tomography (CT), dynamic magnetic resonance (MR) imaging, and positron emission tomography (PET) combined with CT (PET/CT) with use of fluorine 18 fluorodeoxyglucose (FDG) for the diagnosis of solitary pulmonary nodules. The institutional review board approved this study, and written informed consent was obtained from each subject. A total of 198 consecutive patients with 218 nodules prospectively underwent dynamic perfusion area-detector CT, dynamic MR imaging, FDG PET/CT, and microbacterial and/or pathologic examinations. Nodules were classified into three groups: malignant nodules (n = 133) and benign nodules with low (n = 53) or high (n = 32) biologic activity. Total perfusion was determined with dual-input maximum slope models at area-detector CT, maximum and slope of enhancement ratio at MR imaging, and maximum standardized uptake value (SUVmax) at PET/CT. Next, all indexes for malignant and benign nodules were compared with the Tukey honest significant difference test. Then, receiver operating characteristic analysis was performed for each index. Finally, sensitivity, specificity, and accuracy were compared with the McNemar test. All indexes showed significant differences between malignant nodules and benign nodules with low biologic activity (P Dynamic perfusion area-detector CT is more specific and accurate than dynamic MR imaging and FDG PET/CT in the diagnosis of solitary pulmonary nodules in routine clinical practice. © RSNA, 2014.

Thinking about Digestive System in Early Childhood: A Comparative Study about Biological Knowledge

Science.gov (United States)

AHI, Berat

2017-01-01

The current study aims to explore how children explain the concepts of biology and how biological knowledge develops across ages by focusing on the structure and functions of the digestive system. The study was conducted with 60 children. The data were collected through the interviews conducted within a think-aloud protocol. The interview data…

Using Network Dynamical Influence to Drive Consensus

Science.gov (United States)

Punzo, Giuliano; Young, George F.; MacDonald, Malcolm; Leonard, Naomi E.

2016-05-01

Consensus and decision-making are often analysed in the context of networks, with many studies focusing attention on ranking the nodes of a network depending on their relative importance to information routing. Dynamical influence ranks the nodes with respect to their ability to influence the evolution of the associated network dynamical system. In this study it is shown that dynamical influence not only ranks the nodes, but also provides a naturally optimised distribution of effort to steer a network from one state to another. An example is provided where the “steering” refers to the physical change in velocity of self-propelled agents interacting through a network. Distinct from other works on this subject, this study looks at directed and hence more general graphs. The findings are presented with a theoretical angle, without targeting particular applications or networked systems; however, the framework and results offer parallels with biological flocks and swarms and opportunities for design of technological networks.

Entropy as a method to investigate complex biological systems. An alternative view on the biological transition from healthy aging to frailty

Directory of Open Access Journals (Sweden)

Roberto Siciliano

2017-07-01

Full Text Available Everyone is subject to a process of progressive deterioration of control mechanisms, which supervise the complex network of human physiological functions, reducing the individual ability to adapt to emerging situations of stress or change. In the light of results obtained during the last years, it appears that some of the tools of nonlinear dynamics, first developed for the physical sciences are well suited for studies of biological systems. We believe that, considering the level of order or complexity of the anatomical apparatus by measuring a physical quantity, which is the entropy, we can evaluate the health status or vice versa fragility of a biological system. In particular, a reduction in the entropy value, indicates modification of the structural order with a progressive reduction of functional reserve of the individual, which is associated with a failure to adapt to stress conditions, difficult to be analyzed and documented with a unique traditional biochemical or biomolecular vision. Therefore, in this paper, we present a method that, conceptually combines complexity, disease and aging, alloys Poisson statistics, predictive of the personal level of health, to the entropy value indicating the status of bio-dynamic and functional body, seen as a complex and open thermodynamic system.

Discrete dynamic modeling of cellular signaling networks.

Science.gov (United States)

Albert, Réka; Wang, Rui-Sheng

2009-01-01

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

Population dynamics of bacteria involved in enhanced biological phosphorus removal in Danish wastewater treatment plants.

Science.gov (United States)

Mielczarek, Artur Tomasz; Nguyen, Hien Thi Thu; Nielsen, Jeppe Lund; Nielsen, Per Halkjær

2013-03-15

The enhanced biological phosphorus removal (EBPR) process is increasingly popular as a sustainable method for removal of phosphorus (P) from wastewater. This study consisted of a comprehensive three-year investigation of the identity and population dynamics of polyphosphate-accumulating organisms (PAOs) and glycogen-accumulating organisms (GAOs) in 28 Danish municipal wastewater treatment plants with nutrient removal. Fluorescence in situ hybridization was applied to quantify ten probe-defined populations of PAO and GAO that in total constituted a large fraction (30% on average) of the entire microbial community targeted by the EUBmix probes. Two PAO genera, Accumulibacter and Tetrasphaera, were very abundant in all EBPR plants (average of 3.7% and 27% of all bacteria, respectively), and their abundance was relatively stable in the Danish full-scale plants without clear temporal variations. GAOs were occasionally present in some plants (Competibacter in 11 plants, Defluviicoccus in 6 plants) and were consistent in only a few plants. This shows that these were not core species in the EBPR communities. The total GAO abundance was always lower than that of Accumulibacter. In plants without EBPR design, the abundance of PAO and GAO was significantly lower. Competibacter correlated in general with high fraction of industrial wastewater. In specific plants Accumulibacter correlated with high C/P ratio of the wastewater and Tetrasphaera with high organic loading. Interestingly, the relative microbial composition of the PAO/GAO species was unique to each plant over time, which gives a characteristic plant-specific "fingerprint". Copyright © 2012 Elsevier Ltd. All rights reserved.

Structure and dynamics of solutions

CERN Document Server

Ohtaki, H

2013-01-01

Recent advances in the study of structural and dynamic properties of solutions have provided a molecular picture of solute-solvent interactions. Although the study of thermodynamic as well as electronic properties of solutions have played a role in the development of research on the rate and mechanism of chemical reactions, such macroscopic and microscopic properties are insufficient for a deeper understanding of fast chemical and biological reactions. In order to fill the gap between the two extremes, it is necessary to know how molecules are arranged in solution and how they change their pos

The dynamics of a usage-based approach

NARCIS (Netherlands)

Verspoor, Marjolijn; Daems, Jocelyn; Zenner, Eline; Heylen, Kris; Speelman, Dirk; Cuyckens, Hubert

2015-01-01

This contribution seeks to connect usage based linguistics with dynamic systems theory, in particular as applied by Edelman (1989) and Thelen and Smith (1994). Edelman’s dynamic biological system starts off with a few simple sub-systems (perception, action, value), all of which interacting with each

Nonlinear dynamics and damage induced properties of soft matter with application in oncology

Science.gov (United States)

Naimark, O.

2017-09-01

Molecular-morphological signs of oncogenesis could be linked to multiscale collective effects in molecular, cell and tissue related to defects (damage) dynamics. It was shown that nonlinear behavior of biological systems can be linked to the existence of characteristic collective open state modes providing the coherent expression dynamics. New type of criticality in nonequilibrium systems with defects—structural-scaling transition allows the definition of the `driving force' for a biological soft matter related to consolidated open states. The set of collective open states (breathers, autosolitons and blow-up modes) in the molecular ensembles provides the collective expression dynamics to attract the entire system (cell, tissue) toward a few preferred global states. The co-existence of three types of collective modes determines the multifractal scenario of biological soft matter dynamics. The appearance of `globally convergent' dynamics corresponding to the coherent behavior of multiscale blow-up open states (blow-up gene expression) leads to anomalous localized softening (blow-up localized damage) and the subjection of the cells (or tissue) to monofractal dynamics. This dynamics can be associated with cancer progression.

Biological response to radiation. Studies of model organism, C. elegans, with micro-ion beam

International Nuclear Information System (INIS)

Higashitani, Atsushi

2006-01-01

Described are mainly author's studies on radiation response and its biological significance in a nematode, C. elegans, particularly focusing its germ cells. The model organism is bisexual and the mature one is suitable to observe the development, differentiation and concomitant chromosome dynamics of male and female germ cells, and accordingly, the responses occurring in those cells at different stages post irradiation of the whole worm. Authors have shown in the organism irradiated by 100 Gy X-ray that pachytene cells in meiosis have high radio-resistance due to their increased expression of enzymes related with homologous recombination. They have also presented the apoptotic cascade in germ cells triggered by radiation by comparison of wild type and ab1-1-gene-deleted worms. Micro-beam of 12 C 5+ ion in Takasaki Ion Accelerators for Advanced Radiation Application (TIARA) has been used to irradiate the body parts of the worm to study the bystander effects, which has revealed that germ cells are shielded from the effect in the worm. It is thought important to use the micro-beam, with which the irradiation area can be precisely controllable, for studying the bystander effect in a body of higher animals like a mouse as well as in worm somatic cells. (T.I.)

NMR studies on the structure and dynamics of lac operator DNA

International Nuclear Information System (INIS)

Lee, S.C.

1985-01-01

Nuclear Magnetic Resonance spectroscopy was used to elucidate the relationships between structure, dynamics and function of the gene regulatory sequence corresponding to the lactose operon operator of Escherichia coli. The length of the DNA fragments examined varied from 13 to 36 base pair, containing all or part of the operator sequence. These DNA fragments are either derived genetically or synthesized chemically. Resonances of the imino protons were assigned by one dimensional inter-base pair nuclear Overhauser enhancement (NOE) measurements. Imino proton exchange rates were measured by saturation recovery methods. Results from the kinetic measurements show an interesting dynamic heterogeneity with a maximum opening rate centered about a GTG/CAC sequence which correlates with the biological function of the operator DNA. This particular three base pair sequence occurs frequently and often symmetrically in prokaryotic nd eukaryotic DNA sites where one anticipates specific protein interaction for gene regulation. The observed sequence dependent imino proton exchange rate may be a reflection of variation of the local structure of regulatory DNA. The results also indicate that the observed imino proton exchange rates are length dependent

Stochastic Dynamics through Hierarchically Embedded Markov Chains.

Science.gov (United States)

Vasconcelos, Vítor V; Santos, Fernando P; Santos, Francisco C; Pacheco, Jorge M

2017-02-03

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects-such as mutations in evolutionary dynamics and a random exploration of choices in social systems-including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.

A big data pipeline: Identifying dynamic gene regulatory networks from time-course Gene Expression Omnibus data with applications to influenza infection.

Science.gov (United States)

Carey, Michelle; Ramírez, Juan Camilo; Wu, Shuang; Wu, Hulin

2018-07-01

A biological host response to an external stimulus or intervention such as a disease or infection is a dynamic process, which is regulated by an intricate network of many genes and their products. Understanding the dynamics of this gene regulatory network allows us to infer the mechanisms involved in a host response to an external stimulus, and hence aids the discovery of biomarkers of phenotype and biological function. In this article, we propose a modeling/analysis pipeline for dynamic gene expression data, called Pipeline4DGEData, which consists of a series of statistical modeling techniques to construct dynamic gene regulatory networks from the large volumes of high-dimensional time-course gene expression data that are freely available in the Gene Expression Omnibus repository. This pipeline has a consistent and scalable structure that allows it to simultaneously analyze a large number of time-course gene expression data sets, and then integrate the results across different studies. We apply the proposed pipeline to influenza infection data from nine studies and demonstrate that interesting biological findings can be discovered with its implementation.

Chaos in integrate-and-fire dynamical systems

International Nuclear Information System (INIS)

Coombes, S.

2000-01-01

Integrate-and-fire (IF) mechanisms are often studied within the context of neural dynamics. From a mathematical perspective they represent a minimal yet biologically realistic model of a spiking neuron. The non-smooth nature of the dynamics leads to extremely rich spike train behavior capable of explaining a variety of biological phenomenon including phase-locked states, mode-locking, bursting and pattern formation. The conditions under which chaotic spike trains may be generated in synaptically interacting networks of neural oscillators is an important open question. Using techniques originally introduced for the study of impact oscillators we develop the notion of a Liapunov exponent for IF systems. In the strong coupling regime a network may undergo a discrete Turing-Hopf bifurcation of the firing times from a synchronous state to a state with periodic or quasiperiodic variations of the interspike intervals on closed orbits. Away from the bifurcation point these invariant circles may break up. We establish numerically that in this case the largest IF Liapunov exponent becomes positive. Hence, one route to chaos in networks of synaptically coupled IF neurons is via the breakup of invariant circles

[Application of network biology on study of traditional Chinese medicine].

Science.gov (United States)

Tian, Sai-Sai; Yang, Jian; Zhao, Jing; Zhang, Wei-Dong

2018-01-01

With the completion of the human genome project, people have gradually recognized that the functions of the biological system are fulfilled through network-type interaction between genes, proteins and small molecules, while complex diseases are caused by the imbalance of biological processes due to a number of gene expression disorders. These have contributed to the rise of the concept of the "multi-target" drug discovery. Treatment and diagnosis of traditional Chinese medicine are based on holism and syndrome differentiation. At the molecular level, traditional Chinese medicine is characterized by multi-component and multi-target prescriptions, which is expected to provide a reference for the development of multi-target drugs. This paper reviews the application of network biology in traditional Chinese medicine in six aspects, in expectation to provide a reference to the modernized study of traditional Chinese medicine. Copyright© by the Chinese Pharmaceutical Association.

A graphical method for reducing and relating models in systems biology.

Science.gov (United States)

Gay, Steven; Soliman, Sylvain; Fages, François

2010-09-15

In Systems Biology, an increasing collection of models of various biological processes is currently developed and made available in publicly accessible repositories, such as biomodels.net for instance, through common exchange formats such as SBML. To date, however, there is no general method to relate different models to each other by abstraction or reduction relationships, and this task is left to the modeler for re-using and coupling models. In mathematical biology, model reduction techniques have been studied for a long time, mainly in the case where a model exhibits different time scales, or different spatial phases, which can be analyzed separately. These techniques are however far too restrictive to be applied on a large scale in systems biology, and do not take into account abstractions other than time or phase decompositions. Our purpose here is to propose a general computational method for relating models together, by considering primarily the structure of the interactions and abstracting from their dynamics in a first step. We present a graph-theoretic formalism with node merge and delete operations, in which model reductions can be studied as graph matching problems. From this setting, we derive an algorithm for deciding whether there exists a reduction from one model to another, and evaluate it on the computation of the reduction relations between all SBML models of the biomodels.net repository. In particular, in the case of the numerous models of MAPK signalling, and of the circadian clock, biologically meaningful mappings between models of each class are automatically inferred from the structure of the interactions. We conclude on the generality of our graphical method, on its limits with respect to the representation of the structure of the interactions in SBML, and on some perspectives for dealing with the dynamics. The algorithms described in this article are implemented in the open-source software modeling platform BIOCHAM available at http

Dynamic photosynthesis in different environmental conditions.

Science.gov (United States)

Kaiser, Elias; Morales, Alejandro; Harbinson, Jeremy; Kromdijk, Johannes; Heuvelink, Ep; Marcelis, Leo F M

2015-05-01

Incident irradiance on plant leaves often fluctuates, causing dynamic photosynthesis. Whereas steady-state photosynthetic responses to environmental factors have been extensively studied, knowledge of dynamic modulation of photosynthesis remains scarce and scattered. This review addresses this discrepancy by summarizing available data and identifying the research questions necessary to advance our understanding of interactions between environmental factors and dynamic behaviour of photosynthesis using a mechanistic framework. Firstly, dynamic photosynthesis is separated into sub-processes related to proton and electron transport, non-photochemical quenching, control of metabolite flux through the Calvin cycle (activation states of Rubisco and RuBP regeneration, and post-illumination metabolite turnover), and control of CO₂ supply to Rubisco (stomatal and mesophyll conductance changes). Secondly, the modulation of dynamic photosynthesis and its sub-processes by environmental factors is described. Increases in ambient CO₂ concentration and temperature (up to ~35°C) enhance rates of photosynthetic induction and decrease its loss, facilitating more efficient dynamic photosynthesis. Depending on the sensitivity of stomatal conductance, dynamic photosynthesis may additionally be modulated by air humidity. Major knowledge gaps exist regarding environmental modulation of loss of photosynthetic induction, dynamic changes in mesophyll conductance, and the extent of limitations imposed by stomatal conductance for different species and environmental conditions. The study of mutants or genetic transformants for specific processes under various environmental conditions could provide significant progress in understanding the control of dynamic photosynthesis. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Biological Small Angle Scattering: Techniques, Strategies and Tips

Energy Technology Data Exchange (ETDEWEB)

Chaudhuri, Barnali [University at Buffalo (SUNY); Muñoz, Inés G. [Centro Nacional de Investigaciones Oncológicas Madrid, Madrid, Spain; Urban, Volker S. [ORNL; Qian, Shuo [ORNL

2017-12-01

This book provides a clear, comprehensible and up-to-date description of how Small Angle Scattering (SAS) can help structural biology researchers. SAS is an efficient technique that offers structural information on how biological macromolecules behave in solution. SAS provides distinct and complementary data for integrative structural biology approaches in combination with other widely used probes, such as X-ray crystallography, Nuclear magnetic resonance, Mass spectrometry and Cryo-electron Microscopy. The development of brilliant synchrotron small-angle X-ray scattering (SAXS) beam lines has increased the number of researchers interested in solution scattering. SAS is especially useful for studying conformational changes in proteins, highly flexible proteins, and intrinsically disordered proteins. Small-angle neutron scattering (SANS) with neutron contrast variation is ideally suited for studying multi-component assemblies as well as membrane proteins that are stabilized in surfactant micelles or vesicles. SAS is also used for studying dynamic processes of protein fibrillation in amyloid diseases, and pharmaceutical drug delivery. The combination with size-exclusion chromatography further increases the range of SAS applications.The book is written by leading experts in solution SAS methodologies. The principles and theoretical background of various SAS techniques are included, along with practical aspects that range from sample preparation to data presentation for publication. Topics covered include techniques for improving data quality and analysis, as well as different scientific applications of SAS. With abundant illustrations and practical tips, we hope the clear explanations of the principles and the reviews on the latest progresses will serve as a guide through all aspects of biological solution SAS.The scope of this book is particularly relevant for structural biology researchers who are new to SAS. Advanced users of the technique will find it helpful for

A CMOS active pixel sensor system for laboratory- based x-ray diffraction studies of biological tissue

International Nuclear Information System (INIS)

Bohndiek, Sarah E; Cook, Emily J; Arvanitis, Costas D; Olivo, Alessandro; Royle, Gary J; Clark, Andy T; Prydderch, Mark L; Turchetta, Renato; Speller, Robert D

2008-01-01

X-ray diffraction studies give material-specific information about biological tissue. Ideally, a large area, low noise, wide dynamic range digital x-ray detector is required for laboratory-based x-ray diffraction studies. The goal of this work is to introduce a novel imaging technology, the CMOS active pixel sensor (APS) that has the potential to fulfil all these requirements, and demonstrate its feasibility for coherent scatter imaging. A prototype CMOS APS has been included in an x-ray diffraction demonstration system. An industrial x-ray source with appropriate beam filtration is used to perform angle dispersive x-ray diffraction (ADXRD). Optimization of the experimental set-up is detailed including collimator options and detector operating parameters. Scatter signatures are measured for 11 different materials, covering three medical applications: breast cancer diagnosis, kidney stone identification and bone mineral density calculations. Scatter signatures are also recorded for three mixed samples of known composition. Results are verified using two independent models for predicting the APS scatter signature: (1) a linear systems model of the APS and (2) a linear superposition integral combining known monochromatic scatter signatures with the input polychromatic spectrum used in this case. Cross validation of experimental, modelled and literature results proves that APS are able to record biologically relevant scatter signatures. Coherent scatter signatures are sensitive to multiple materials present in a sample and provide a means to quantify composition. In the future, production of a bespoke APS imager for x-ray diffraction studies could enable simultaneous collection of the transmitted beam and scattered radiation in a laboratory-based coherent scatter system, making clinical transfer of the technique attainable

Philosophical Basis and Some Historical Aspects of Systems Biology: From Hegel to Noble - Applications for Bioenergetic Research

Directory of Open Access Journals (Sweden)

Valdur Saks

2009-03-01

Full Text Available We live in times of paradigmatic changes for the biological sciences. Reductionism, that for the last six decades has been the philosophical basis of biochemistry and molecular biology, is being displaced by Systems Biology, which favors the study of integrated systems. Historically, Systems Biology - defined as the higher level analysis of complex biological systems - was pioneered by Claude Bernard in physiology, Norbert Wiener with the development of cybernetics, and Erwin Schrödinger in his thermodynamic approach to the living. Systems Biology applies methods inspired by cybernetics, network analysis, and non-equilibrium dynamics of open systems. These developments follow very precisely the dialectical principles of development from thesis to antithesis to synthesis discovered by Hegel. Systems Biology opens new perspectives for studies of the integrated processes of energy metabolism in different cells. These integrated systems acquire new, system-level properties due to interaction of cellular components, such as metabolic compartmentation, channeling and functional coupling mechanisms, which are central for regulation of the energy fluxes. State of the art of these studies in the new area of Molecular System Bioenergetics is analyzed.

Creative-Dynamics Approach To Neural Intelligence

Science.gov (United States)

Zak, Michail A.

1992-01-01

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

Method and apparatus to image biological interactions in plants

Science.gov (United States)

Weisenberger, Andrew; Bonito, Gregory M.; Reid, Chantal D.; Smith, Mark Frederick

2015-12-22

A method to dynamically image the actual translocation of molecular compounds of interest in a plant root, root system, and rhizosphere without disturbing the root or the soil. The technique makes use of radioactive isotopes as tracers to label molecules of interest and to image their distribution in the plant and/or soil. The method allows for the study and imaging of various biological and biochemical interactions in the rhizosphere of a plant, including, but not limited to, mycorrhizal associations in such regions.

Dynamic programming algorithms for biological sequence comparison.

Science.gov (United States)

Pearson, W R; Miller, W

1992-01-01

Efficient dynamic programming algorithms are available for a broad class of protein and DNA sequence comparison problems. These algorithms require computer time proportional to the product of the lengths of the two sequences being compared [O(N2)] but require memory space proportional only to the sum of these lengths [O(N)]. Although the requirement for O(N2) time limits use of the algorithms to the largest computers when searching protein and DNA sequence databases, many other applications of these algorithms, such as calculation of distances for evolutionary trees and comparison of a new sequence to a library of sequence profiles, are well within the capabilities of desktop computers. In particular, the results of library searches with rapid searching programs, such as FASTA or BLAST, should be confirmed by performing a rigorous optimal alignment. Whereas rapid methods do not overlook significant sequence similarities, FASTA limits the number of gaps that can be inserted into an alignment, so that a rigorous alignment may extend the alignment substantially in some cases. BLAST does not allow gaps in the local regions that it reports; a calculation that allows gaps is very likely to extend the alignment substantially. Although a Monte Carlo evaluation of the statistical significance of a similarity score with a rigorous algorithm is much slower than the heuristic approach used by the RDF2 program, the dynamic programming approach should take less than 1 hr on a 386-based PC or desktop Unix workstation. For descriptive purposes, we have limited our discussion to methods for calculating similarity scores and distances that use gap penalties of the form g = rk. Nevertheless, programs for the more general case (g = q+rk) are readily available. Versions of these programs that run either on Unix workstations, IBM-PC class computers, or the Macintosh can be obtained from either of the authors.

Nature and Consequences of Biological Reductionism for the Immunological Study of Infectious Diseases

Directory of Open Access Journals (Sweden)

Ariel L. Rivas

2017-05-01

Full Text Available Evolution has conserved “economic” systems that perform many functions, faster or better, with less. For example, three to five leukocyte types protect from thousands of pathogens. To achieve so much with so little, biological systems combine their limited elements, creating complex structures. Yet, the prevalent research paradigm is reductionist. Focusing on infectious diseases, reductionist and non-reductionist views are here described. The literature indicates that reductionism is associated with information loss and errors, while non-reductionist operations can extract more information from the same data. When designed to capture one-to-many/many-to-one interactions—including the use of arrows that connect pairs of consecutive observations—non-reductionist (spatial–temporal constructs eliminate data variability from all dimensions, except along one line, while arrows describe the directionality of temporal changes that occur along the line. To validate the patterns detected by non-reductionist operations, reductionist procedures are needed. Integrated (non-reductionist and reductionist methods can (i distinguish data subsets that differ immunologically and statistically; (ii differentiate false-negative from -positive errors; (iii discriminate disease stages; (iv capture in vivo, multilevel interactions that consider the patient, the microbe, and antibiotic-mediated responses; and (v assess dynamics. Integrated methods provide repeatable and biologically interpretable information.

Reproductive biology and early establishment of Pinus elliottii var. elliottii in Brazilian sandy coastal plain vegetation: implications for biological invasion

Directory of Open Access Journals (Sweden)

Fernando Campanhã Bechara

2013-04-01

Full Text Available Pinus is the most invasive woody taxon, exceeded only by herbaceous plants. This study reports the reproductive biology and early establishment of Pinus elliottii Engelm. var. elliottii, describing its invasive properties in a protected natural area of the Brazilian coastal sandy plains. We evaluated the seed germination and rain, longevity of seed viability and the initial dynamics of the seedlings of Pinus elliottii var elliottii through field and laboratory experiments. We recorded a continuous seed rain of about 204.0 viable seeds m- 2 per year, with a 90 % germination rate. The seeds exhibited a low longevity of viability in the soil and a dense, permanent seedling bank that may explain the high levels of pine invasion. The environmental impact caused by the pine's biological invasion suggests the recommendation for its immediate eradication, together with a restoration plan to restitute the native biodiversity gradually.

Modelling the crop: from system dynamics to systems biology

NARCIS (Netherlands)

Yin, X.; Struik, P.C.

2010-01-01

There is strong interplant competition in a crop stand for various limiting resources, resulting in complex compensation and regulation mechanisms along the developmental cascade of the whole crop. Despite decades-long use of principles in system dynamics (e.g. feedback control), current crop models

Understanding life together: A brief history of collaboration in biology

Science.gov (United States)

Vermeulen, Niki; Parker, John N.; Penders, Bart

2013-01-01

The history of science shows a shift from single-investigator ‘little science’ to increasingly large, expensive, multinational, interdisciplinary and interdependent ‘big science’. In physics and allied fields this shift has been well documented, but the rise of collaboration in the life sciences and its effect on scientific work and knowledge has received little attention. Research in biology exhibits different historical trajectories and organisation of collaboration in field and laboratory – differences still visible in contemporary collaborations such as the Census of Marine Life and the Human Genome Project. We employ these case studies as strategic exemplars, supplemented with existing research on collaboration in biology, to expose the different motives, organisational forms and social dynamics underpinning contemporary large-scale collaborations in biology and their relations to historical patterns of collaboration in the life sciences. We find the interaction between research subject, research approach as well as research organisation influencing collaboration patterns and the work of scientists. PMID:23578694

Diffusion-advection within dynamic biological gaps driven by structural motion

Science.gov (United States)

Asaro, Robert J.; Zhu, Qiang; Lin, Kuanpo

2018-04-01

To study the significance of advection in the transport of solutes, or particles, within thin biological gaps (channels), we examine theoretically the process driven by stochastic fluid flow caused by random thermal structural motion, and we compare it with transport via diffusion. The model geometry chosen resembles the synaptic cleft; this choice is motivated by the cleft's readily modeled structure, which allows for well-defined mechanical and physical features that control the advection process. Our analysis defines a Péclet-like number, AD, that quantifies the ratio of time scales of advection versus diffusion. Another parameter, AM, is also defined by the analysis that quantifies the full potential extent of advection in the absence of diffusion. These parameters provide a clear and compact description of the interplay among the well-defined structural, geometric, and physical properties vis-a ̀-vis the advection versus diffusion process. For example, it is found that AD˜1 /R2 , where R is the cleft diameter and hence diffusion distance. This curious, and perhaps unexpected, result follows from the dependence of structural motion that drives fluid flow on R . AM, on the other hand, is directly related (essentially proportional to) the energetic input into structural motion, and thereby to fluid flow, as well as to the mechanical stiffness of the cleftlike structure. Our model analysis thus provides unambiguous insight into the prospect of competition of advection versus diffusion within biological gaplike structures. The importance of the random, versus a regular, nature of structural motion and of the resulting transient nature of advection under random motion is made clear in our analysis. Further, by quantifying the effects of geometric and physical properties on the competition between advection and diffusion, our results clearly demonstrate the important role that metabolic energy (ATP) plays in this competitive process.

Efficient digital implementation of a conductance-based globus pallidus neuron and the dynamics analysis

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Yang, Shuangming; Wei, Xile; Deng, Bin; Liu, Chen; Li, Huiyan; Wang, Jiang

2018-03-01

Balance between biological plausibility of dynamical activities and computational efficiency is one of challenging problems in computational neuroscience and neural system engineering. This paper proposes a set of efficient methods for the hardware realization of the conductance-based neuron model with relevant dynamics, targeting reproducing the biological behaviors with low-cost implementation on digital programmable platform, which can be applied in wide range of conductance-based neuron models. Modified GP neuron models for efficient hardware implementation are presented to reproduce reliable pallidal dynamics, which decode the information of basal ganglia and regulate the movement disorder related voluntary activities. Implementation results on a field-programmable gate array (FPGA) demonstrate that the proposed techniques and models can reduce the resource cost significantly and reproduce the biological dynamics accurately. Besides, the biological behaviors with weak network coupling are explored on the proposed platform, and theoretical analysis is also made for the investigation of biological characteristics of the structured pallidal oscillator and network. The implementation techniques provide an essential step towards the large-scale neural network to explore the dynamical mechanisms in real time. Furthermore, the proposed methodology enables the FPGA-based system a powerful platform for the investigation on neurodegenerative diseases and real-time control of bio-inspired neuro-robotics.

S1-3: Perception of Biological Motion in Schizophrenia and Obsessive-Compulsive Disorder

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Jejoong Kim

2012-10-01

Full Text Available Major mental disorders including schizophrenia, autism, and obsessive-compulsive disorder (OCD are characterized by impaired social functioning regardless of wide range of clinical symptoms. Past studies also revealed that people with these mental illness exhibit perceptual problems with altered neural activation. For example, schizophrenia patients are deficient in processing rapid and dynamic visual stimuli. As well documented, people are very sensitive to motion signals generated by others (i.e., biological motion even when those motions are portrayed by point-light display. Therefore, ability to perceive biological motion is important for both visual perception and social functioning. Nevertheless, there have been no systematic attempts to investigate biological motion perception in people with mental illness associated with impaired social functioning until a decade ago. Recently, a series of studies newly revealed abnormal patterns of biological motion perception and associated neural activations in schizophrenia and OCD. These new achievements will be reviewed focusing on perceptual and neural difference between patients with schizophrenia/OCD and healthy individuals. Then implications and possible future research will be discussed in this talk.

The Relationships between Epistemic Beliefs in Biology and Approaches to Learning Biology among Biology-Major University Students in Taiwan

Science.gov (United States)

Lin, Yi-Chun; Liang, Jyh-Chong; Tsai, Chin-Chung

2012-01-01

The aim of this study was to investigate the relationships between students' epistemic beliefs in biology and their approaches to learning biology. To this end, two instruments, the epistemic beliefs in biology and the approaches to learning biology surveys, were developed and administered to 520 university biology students, respectively. By and…

Biologically Inspired Micro-Flight Research

Science.gov (United States)

Raney, David L.; Waszak, Martin R.

2003-01-01

Natural fliers demonstrate a diverse array of flight capabilities, many of which are poorly understood. NASA has established a research project to explore and exploit flight technologies inspired by biological systems. One part of this project focuses on dynamic modeling and control of micro aerial vehicles that incorporate flexible wing structures inspired by natural fliers such as insects, hummingbirds and bats. With a vast number of potential civil and military applications, micro aerial vehicles represent an emerging sector of the aerospace market. This paper describes an ongoing research activity in which mechanization and control concepts for biologically inspired micro aerial vehicles are being explored. Research activities focusing on a flexible fixed- wing micro aerial vehicle design and a flapping-based micro aerial vehicle concept are presented.

A Bayesian framework for parameter estimation in dynamical models.

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Flávio Codeço Coelho

Full Text Available Mathematical models in biology are powerful tools for the study and exploration of complex dynamics. Nevertheless, bringing theoretical results to an agreement with experimental observations involves acknowledging a great deal of uncertainty intrinsic to our theoretical representation of a real system. Proper handling of such uncertainties is key to the successful usage of models to predict experimental or field observations. This problem has been addressed over the years by many tools for model calibration and parameter estimation. In this article we present a general framework for uncertainty analysis and parameter estimation that is designed to handle uncertainties associated with the modeling of dynamic biological systems while remaining agnostic as to the type of model used. We apply the framework to fit an SIR-like influenza transmission model to 7 years of incidence data in three European countries: Belgium, the Netherlands and Portugal.

Dimensionless study on dynamics of pressure controlled mechanical ventilation system

International Nuclear Information System (INIS)

Shi, Yan; Niu, Jinglong; Cai, Maolin; Xu, Weiqing

2015-01-01

Dynamics of mechanical ventilation system can be referred in pulmonary diagnostics and treatments. In this paper, to conveniently grasp the essential characteristics of mechanical ventilation system, a dimensionless model of mechanical ventilation system is presented. For the validation of the mathematical model, a prototype mechanical ventilation system of a lung simulator is proposed. Through the simulation and experimental studies on the dimensionless dynamics of the mechanical ventilation system, firstly, the mathematical model is proved to be authentic and reliable. Secondly, the dimensionless dynamics of the mechanical ventilation system are obtained. Last, the influences of key parameters on the dimensionless dynamics of the mechanical ventilation system are illustrated. The study provides a novel method to study the dynamic of mechanical ventilation system, which can be referred in the respiratory diagnostics and treatment.

Dimensionless study on dynamics of pressure controlled mechanical ventilation system

Energy Technology Data Exchange (ETDEWEB)

Shi, Yan; Niu, Jinglong; Cai, Maolin; Xu, Weiqing [Beihang University, Beijing (Korea, Republic of)

2015-02-15

Dynamics of mechanical ventilation system can be referred in pulmonary diagnostics and treatments. In this paper, to conveniently grasp the essential characteristics of mechanical ventilation system, a dimensionless model of mechanical ventilation system is presented. For the validation of the mathematical model, a prototype mechanical ventilation system of a lung simulator is proposed. Through the simulation and experimental studies on the dimensionless dynamics of the mechanical ventilation system, firstly, the mathematical model is proved to be authentic and reliable. Secondly, the dimensionless dynamics of the mechanical ventilation system are obtained. Last, the influences of key parameters on the dimensionless dynamics of the mechanical ventilation system are illustrated. The study provides a novel method to study the dynamic of mechanical ventilation system, which can be referred in the respiratory diagnostics and treatment.

Modeling of biological intelligence for SCM system optimization.

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Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

Full Text Available This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization