The Southern Ocean biogeochemical divide.

PubMed

Marinov, I; Gnanadesikan, A; Toggweiler, J R; Sarmiento, J L

2006-06-22

Modelling studies have demonstrated that the nutrient and carbon cycles in the Southern Ocean play a central role in setting the air-sea balance of CO(2) and global biological production. Box model studies first pointed out that an increase in nutrient utilization in the high latitudes results in a strong decrease in the atmospheric carbon dioxide partial pressure (pCO2). This early research led to two important ideas: high latitude regions are more important in determining atmospheric pCO2 than low latitudes, despite their much smaller area, and nutrient utilization and atmospheric pCO2 are tightly linked. Subsequent general circulation model simulations show that the Southern Ocean is the most important high latitude region in controlling pre-industrial atmospheric CO(2) because it serves as a lid to a larger volume of the deep ocean. Other studies point out the crucial role of the Southern Ocean in the uptake and storage of anthropogenic carbon dioxide and in controlling global biological production. Here we probe the system to determine whether certain regions of the Southern Ocean are more critical than others for air-sea CO(2) balance and the biological export production, by increasing surface nutrient drawdown in an ocean general circulation model. We demonstrate that atmospheric CO(2) and global biological export production are controlled by different regions of the Southern Ocean. The air-sea balance of carbon dioxide is controlled mainly by the biological pump and circulation in the Antarctic deep-water formation region, whereas global export production is controlled mainly by the biological pump and circulation in the Subantarctic intermediate and mode water formation region. The existence of this biogeochemical divide separating the Antarctic from the Subantarctic suggests that it may be possible for climate change or human intervention to modify one of these without greatly altering the other.

Producing a Mouse Model to Explore the Linkages Between Tocopherol Biology and Prostate Cancer

DTIC Science & Technology

2005-07-01

Edwards, Prostate cancer and supplementation with alpha-tocopherol and beta -carotene: incidence and mortality in a controlled trial. J Natl Cancer ...1-0153 TITLE: Producing a Mouse Model to Explore the Linkages Between Tocopherol Biology and Prostate Cancer ...TITLE AND SUBTITLE Producing a Mouse Model to Explore the Linkages Between Tocopherol 5a. CONTRACT NUMBER Biology and Prostate Cancer 5b. GRANT

Modelling malaria control by introduction of larvivorous fish.

PubMed

Lou, Yijun; Zhao, Xiao-Qiang

2011-10-01

Malaria creates serious health and economic problems which call for integrated management strategies to disrupt interactions among mosquitoes, the parasite and humans. In order to reduce the intensity of malaria transmission, malaria vector control may be implemented to protect individuals against infective mosquito bites. As a sustainable larval control method, the use of larvivorous fish is promoted in some circumstances. To evaluate the potential impacts of this biological control measure on malaria transmission, we propose and investigate a mathematical model describing the linked dynamics between the host-vector interaction and the predator-prey interaction. The model, which consists of five ordinary differential equations, is rigorously analysed via theories and methods of dynamical systems. We derive four biologically plausible and insightful quantities (reproduction numbers) that completely determine the community composition. Our results suggest that the introduction of larvivorous fish can, in principle, have important consequences for malaria dynamics, but also indicate that this would require strong predators on larval mosquitoes. Integrated strategies of malaria control are analysed to demonstrate the biological application of our developed theory.

Model Organisms Fact Sheet: Using Model Organisms to Study Health and Disease

MedlinePlus

... NIGMS use research organisms to explore the basic biology and chemistry of life. Scientists decide which organism ... controls allow for more precise understanding of the biological factors being studied and provide greater certainty about ...

Research on Objectives for High-School Biology

ERIC Educational Resources Information Center

Korgan, John J., Jr.; Wilson, John T.

1973-01-01

Describes procedures to develop instructional objectives for high school biology. Two kinds of objectives are identified as pre-objectives and performance objectives. Models to classify these in branches of biology and to ensure quality control are provided. (PS)

Integrative structure modeling with the Integrative Modeling Platform.

PubMed

Webb, Benjamin; Viswanath, Shruthi; Bonomi, Massimiliano; Pellarin, Riccardo; Greenberg, Charles H; Saltzberg, Daniel; Sali, Andrej

2018-01-01

Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (https://integrativemodeling.org), and demonstrate its use. © 2017 The Protein Society.

Biological indicators for monitoring water quality of MTF canals system

NASA Technical Reports Server (NTRS)

Sethi, S. L.

1975-01-01

Biological models, diversity indexes, were developed to predict environmental effects of NASA's Mississippi test facility (MTF) chemical operations on canal systems in the area. To predict the effects on local streams, a physical model of unpolluted streams was established. The model is fed by artesian well water free of background levels of pollutants. The species diversity and biota composition of unpolluted MTF stream was determined; resulting information will be used to form baseline data for future comparisons. Biological modeling was accomplished by adding controlled quantities or kinds of chemical pollutants and evaluating the effects of these chemicals on the biological life of the stream.

Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions.

PubMed

Nehaniv, Chrystopher L; Rhodes, John; Egri-Nagy, Attila; Dini, Paolo; Morris, Eric Rothstein; Horváth, Gábor; Karimi, Fariba; Schreckling, Daniel; Schilstra, Maria J

2015-07-28

Interaction computing is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are to (i) identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this and (ii) use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in systems biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, the Krebs cycle and p53-mdm2 genetic regulation constructed from systems biology models have canonically associated algebraic structures (their transformation semigroups). These contain permutation groups (local substructures exhibiting symmetry) that correspond to 'pools of reversibility'. These natural subsystems are related to one another in a hierarchical manner by the notion of 'weak control'. We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-Abelian groups are found in biological examples and can be harnessed to realize finitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.

Retrospective Analysis of a Classical Biological Control Programme

USDA-ARS?s Scientific Manuscript database

1. Classical biological control has been a key technology in the management of invasive arthropod pests globally for over 120 years, yet rigorous quantitative evaluations of programme success or failure are rare. Here, I used life table and matrix model analyses, and life table response experiments ...

Adaptive walking of a quadrupedal robot based on layered biological reflexes

NASA Astrophysics Data System (ADS)

Zhang, Xiuli; Mingcheng, E.; Zeng, Xiangyu; Zheng, Haojun

2012-07-01

A multiple-legged robot is traditionally controlled by using its dynamic model. But the dynamic-model-based approach fails to acquire satisfactory performances when the robot faces rough terrains and unknown environments. Referring animals' neural control mechanisms, a control model is built for a quadruped robot walking adaptively. The basic rhythmic motion of the robot is controlled by a well-designed rhythmic motion controller(RMC) comprising a central pattern generator(CPG) for hip joints and a rhythmic coupler (RC) for knee joints. CPG and RC have relationships of motion-mapping and rhythmic couple. Multiple sensory-motor models, abstracted from the neural reflexes of a cat, are employed. These reflex models are organized and thus interact with the CPG in three layers, to meet different requirements of complexity and response time to the tasks. On the basis of the RMC and layered biological reflexes, a quadruped robot is constructed, which can clear obstacles and walk uphill and downhill autonomously, and make a turn voluntarily in uncertain environments, interacting with the environment in a way similar to that of an animal. The paper provides a biologically inspired architecture, with which a robot can walk adaptively in uncertain environments in a simple and effective way, and achieve better performances.

Biologically inspired adaptive walking of a quadruped robot.

PubMed

Kimura, Hiroshi; Fukuoka, Yasuhiro; Cohen, Avis H

2007-01-15

We describe here the efforts to induce a quadruped robot to walk with medium-walking speed on irregular terrain based on biological concepts. We propose the necessary conditions for stable dynamic walking on irregular terrain in general, and we design the mechanical and the neural systems by comparing biological concepts with those necessary conditions described in physical terms. PD-controller at joints constructs the virtual spring-damper system as the viscoelasticity model of a muscle. The neural system model consists of a central pattern generator (CPG), reflexes and responses. We validate the effectiveness of the proposed neural system model control using the quadruped robots called 'Tekken1&2'. MPEG footage of experiments can be seen at http://www.kimura.is.uec.ac.jp.

Finalizing host range determination of a weed biological control pathogen with BLUPs and damage assessment

USDA-ARS?s Scientific Manuscript database

Colletotrichum gloeosporioides f. sp. salsolae (Penz.) Penz. & Sacc. in Penz. (CGS) is a facultative parasitic fungus being evaluated as a classical biological control agent of Russian thistle or tumbleweed (Salsola tragus L.). In initial host range determination tests, Henderson’s mixed model equat...

Promoting Learning through the Use of Analogies in High School Biology Textbooks.

ERIC Educational Resources Information Center

Radford, David L.

A model for developing instructional analogies was used to produce experimental treatments that included text from a high school biology textbook to which was added extended verbal analogies written by the researcher linking each of two biology concepts to analogous familiar concepts. The control treatment was text from the biology textbook…

Quantifying uncertainty in partially specified biological models: how can optimal control theory help us?

PubMed

Adamson, M W; Morozov, A Y; Kuzenkov, O A

2016-09-01

Mathematical models in biology are highly simplified representations of a complex underlying reality and there is always a high degree of uncertainty with regards to model function specification. This uncertainty becomes critical for models in which the use of different functions fitting the same dataset can yield substantially different predictions-a property known as structural sensitivity. Thus, even if the model is purely deterministic, then the uncertainty in the model functions carries through into uncertainty in model predictions, and new frameworks are required to tackle this fundamental problem. Here, we consider a framework that uses partially specified models in which some functions are not represented by a specific form. The main idea is to project infinite dimensional function space into a low-dimensional space taking into account biological constraints. The key question of how to carry out this projection has so far remained a serious mathematical challenge and hindered the use of partially specified models. Here, we propose and demonstrate a potentially powerful technique to perform such a projection by using optimal control theory to construct functions with the specified global properties. This approach opens up the prospect of a flexible and easy to use method to fulfil uncertainty analysis of biological models.

A Biological Condition Gradient Model for Historical Assessment of Estuarine Habitat Structure

EPA Science Inventory

Coastal ecosystems are affected by ever increasing natural and human pressures. Because the physical, chemical, and biological characteristics unique to each ecosystem control the ways that biological resources respond to ecosystem stressors, we recommend a flexible and adaptable...

A biologically inspired approach to modeling unmanned vehicle teams

NASA Astrophysics Data System (ADS)

Cortesi, Roger S.; Galloway, Kevin S.; Justh, Eric W.

2008-04-01

Cooperative motion control of teams of agile unmanned vehicles presents modeling challenges at several levels. The "microscopic equations" describing individual vehicle dynamics and their interaction with the environment may be known fairly precisely, but are generally too complicated to yield qualitative insights at the level of multi-vehicle trajectory coordination. Interacting particle models are suitable for coordinating trajectories, but require care to ensure that individual vehicles are not driven in a "costly" manner. From the point of view of the cooperative motion controller, the individual vehicle autopilots serve to "shape" the microscopic equations, and we have been exploring the interplay between autopilots and cooperative motion controllers using a multivehicle hardware-in-the-loop simulator. Specifically, we seek refinements to interacting particle models in order to better describe observed behavior, without sacrificing qualitative understanding. A recent analogous example from biology involves introducing a fixed delay into a curvature-control-based feedback law for prey capture by an echolocating bat. This delay captures both neural processing time and the flight-dynamic response of the bat as it uses sensor-driven feedback. We propose a comparable approach for unmanned vehicle modeling; however, in contrast to the bat, with unmanned vehicles we have an additional freedom to modify the autopilot. Simulation results demonstrate the effectiveness of this biologically guided modeling approach.

A TCP model for external beam treatment of intermediate-risk prostate cancer

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

Walsh, Sean; Putten, Wil van der

2013-03-15

Purpose: Biological models offer the ability to predict clinical outcomes. The authors describe a model to predict the clinical response of intermediate-risk prostate cancer to external beam radiotherapy for a variety of fractionation regimes. Methods: A fully heterogeneous population averaged tumor control probability model was fit to clinical outcome data for hyper, standard, and hypofractionated treatments. The tumor control probability model was then employed to predict the clinical outcome of extreme hypofractionation regimes, as utilized in stereotactic body radiotherapy. Results: The tumor control probability model achieves an excellent level of fit, R{sup 2} value of 0.93 and a root meanmore » squared error of 1.31%, to the clinical outcome data for hyper, standard, and hypofractionated treatments using realistic values for biological input parameters. Residuals Less-Than-Or-Slanted-Equal-To 1.0% are produced by the tumor control probability model when compared to clinical outcome data for stereotactic body radiotherapy. Conclusions: The authors conclude that this tumor control probability model, used with the optimized radiosensitivity values obtained from the fit, is an appropriate mechanistic model for the analysis and evaluation of external beam RT plans with regard to tumor control for these clinical conditions.« less

An Evaluation of Teachers' Attitudes and Beliefs Levels on Classroom Control in Terms of Teachers' Sense of Efficacy (The Sample of Biology Teachers in Turkey)

ERIC Educational Resources Information Center

Kurt, Hakan

2014-01-01

The aim of this study is to evaluate biology teachers' attitudes and belief levels on classroom control in terms of teachers' sense of efficacy. The screening model was used in the study. The study group was comprised of 135 biology teachers. In this study, Teachers' Sense of Efficacy Scale (TSES) and The Attitudes and Beliefs on Classroom Control…

Cerebellar-inspired algorithm for adaptive control of nonlinear dielectric elastomer-based artificial muscle

PubMed Central

Assaf, Tareq; Rossiter, Jonathan M.; Porrill, John

2016-01-01

Electroactive polymer actuators are important for soft robotics, but can be difficult to control because of compliance, creep and nonlinearities. Because biological control mechanisms have evolved to deal with such problems, we investigated whether a control scheme based on the cerebellum would be useful for controlling a nonlinear dielectric elastomer actuator, a class of artificial muscle. The cerebellum was represented by the adaptive filter model, and acted in parallel with a brainstem, an approximate inverse plant model. The recurrent connections between the two allowed for direct use of sensory error to adjust motor commands. Accurate tracking of a displacement command in the actuator's nonlinear range was achieved by either semi-linear basis functions in the cerebellar model or semi-linear functions in the brainstem corresponding to recruitment in biological muscle. In addition, allowing transfer of training between cerebellum and brainstem as has been observed in the vestibulo-ocular reflex prevented the steady increase in cerebellar output otherwise required to deal with creep. The extensibility and relative simplicity of the cerebellar-based adaptive-inverse control scheme suggests that it is a plausible candidate for controlling this type of actuator. Moreover, its performance highlights important features of biological control, particularly nonlinear basis functions, recruitment and transfer of training. PMID:27655667

Economic Analysis of Biological Invasions in Forests

Treesearch

Tomas P. Holmes; Julian Aukema; Jeffrey Englin; Robert G. Haight; Kent Kovacs; Brian Leung

2014-01-01

Biological invasions of native forests by nonnative pests result from complex stochastic processes that are difficult to predict. Although economic optimization models describe efficient controls across the stages of an invasion, the ability to calibrate such models is constrained by lack of information on pest population dynamics and consequent economic damages. Here...

Using insects to drive mobile robots - hybrid robots bridge the gap between biological and artificial systems.

PubMed

Ando, Noriyasu; Kanzaki, Ryohei

2017-09-01

The use of mobile robots is an effective method of validating sensory-motor models of animals in a real environment. The well-identified insect sensory-motor systems have been the major targets for modeling. Furthermore, mobile robots implemented with such insect models attract engineers who aim to avail advantages from organisms. However, directly comparing the robots with real insects is still difficult, even if we successfully model the biological systems, because of the physical differences between them. We developed a hybrid robot to bridge the gap. This hybrid robot is an insect-controlled robot, in which a tethered male silkmoth (Bombyx mori) drives the robot in order to localize an odor source. This robot has the following three advantages: 1) from a biomimetic perspective, the robot enables us to evaluate the potential performance of future insect-mimetic robots; 2) from a biological perspective, the robot enables us to manipulate the closed-loop of an onboard insect for further understanding of its sensory-motor system; and 3) the robot enables comparison with insect models as a reference biological system. In this paper, we review the recent works regarding insect-controlled robots and discuss the significance for both engineering and biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adhesion control by inflation: implications from biology to artificial attachment device

NASA Astrophysics Data System (ADS)

Dening, Kirstin; Heepe, Lars; Afferrante, Luciano; Carbone, Giuseppe; Gorb, Stanislav N.

2014-08-01

There is an increasing demand for materials that incorporate advanced adhesion properties, such as an ability to adhere in a reversible and controllable manner. In biological systems, these features are known from adhesive pads of the tree frog, Litoria caerulea, and the bush-cricket, Tettigonia viridissima. These species have convergently developed soft, hemispherically shaped pads that might be able to control their adhesion through active changing the curvature of the pad. Inspired by these biological systems, an artificial model system is developed here. It consists of an inflatable membrane clamped to the metallic cylinder and filled with air. Pull-off force measurements of the membrane surface were conducted in contact with the membrane at five different radii of curvature r c with (1) a smooth polyvinylsiloxane membrane and (2) mushroom-shaped adhesive microstructured membrane made of the same polymer. The hypothesis that an increased internal pressure, acting on the membrane, reduces the radius of the membrane curvature, resulting in turn in a lower pull-off force, is verified. Such an active control of adhesion, inspired by biological models, will lead to the development of industrial pick-and-drop devices with controllable adhesive properties.

Model of two infectious diseases in nettle caterpillar population

NASA Astrophysics Data System (ADS)

Firdausi, F. Z.; Nuraini, N.

2016-04-01

Palm oil is a vital commodity to the economy of Indonesia. The area of oil palm plantations in Indonesia has increased from year to year. However, the effectiveness of palm oil production is reduced by pest infestation. One of the pest which often infests oil palm plantations is nettle caterpillar. The pest control used in this study is biological control, viz. biological agents given to oil palm trees. This paper describes a mathematical model of two infectious diseases in nettle caterpillar population. The two infectious diseases arise due to two biological agents, namely Bacillus thuringiensis bacterium and parasite which usually attack nettle caterpillars. The derivation of the model constructed in this paper is obtained from ordinary differential equations without time delay. The equilibrium points are analyzed. Two of three equilibrium points are stable if the Routh-Hurwitz criteria are fulfilled. In addition, this paper also presents the numerical simulation of the model which has been constructed.

Neural systems for preparatory control of imitation.

PubMed

Cross, Katy A; Iacoboni, Marco

2014-01-01

Humans have an automatic tendency to imitate others. Previous studies on how we control these tendencies have focused on reactive mechanisms, where inhibition of imitation is implemented after seeing an action. This work suggests that reactive control of imitation draws on at least partially specialized mechanisms. Here, we examine preparatory imitation control, where advance information allows control processes to be employed before an action is observed. Drawing on dual route models from the spatial compatibility literature, we compare control processes using biological and non-biological stimuli to determine whether preparatory imitation control recruits specialized neural systems that are similar to those observed in reactive imitation control. Results indicate that preparatory control involves anterior prefrontal, dorsolateral prefrontal, posterior parietal and early visual cortices regardless of whether automatic responses are evoked by biological (imitative) or non-biological stimuli. These results indicate both that preparatory control of imitation uses general mechanisms, and that preparatory control of imitation draws on different neural systems from reactive imitation control. Based on the regions involved, we hypothesize that preparatory control is implemented through top-down attentional biasing of visual processing.

Quantifying control effort of biological and technical movements: an information-entropy-based approach.

PubMed

Haeufle, D F B; Günther, M; Wunner, G; Schmitt, S

2014-01-01

In biomechanics and biorobotics, muscles are often associated with reduced movement control effort and simplified control compared to technical actuators. This is based on evidence that the nonlinear muscle properties positively influence movement control. It is, however, open how to quantify the simplicity aspect of control effort and compare it between systems. Physical measures, such as energy consumption, stability, or jerk, have already been applied to compare biological and technical systems. Here a physical measure of control effort based on information entropy is presented. The idea is that control is simpler if a specific movement is generated with less processed sensor information, depending on the control scheme and the physical properties of the systems being compared. By calculating the Shannon information entropy of all sensor signals required for control, an information cost function can be formulated allowing the comparison of models of biological and technical control systems. Exemplarily applied to (bio-)mechanical models of hopping, the method reveals that the required information for generating hopping with a muscle driven by a simple reflex control scheme is only I=32 bits versus I=660 bits with a DC motor and a proportional differential controller. This approach to quantifying control effort captures the simplicity of a control scheme and can be used to compare completely different actuators and control approaches.

Atypical biological motion kinematics are represented by complementary lower-level and top-down processes during imitation learning.

PubMed

Hayes, Spencer J; Dutoy, Chris A; Elliott, Digby; Gowen, Emma; Bennett, Simon J

2016-01-01

Learning a novel movement requires a new set of kinematics to be represented by the sensorimotor system. This is often accomplished through imitation learning where lower-level sensorimotor processes are suggested to represent the biological motion kinematics associated with an observed movement. Top-down factors have the potential to influence this process based on the social context, attention and salience, and the goal of the movement. In order to further examine the potential interaction between lower-level and top-down processes in imitation learning, the aim of this study was to systematically control the mediating effects during an imitation of biological motion protocol. In this protocol, we used non-human agent models that displayed different novel atypical biological motion kinematics, as well as a control model that displayed constant velocity. Importantly the three models had the same movement amplitude and movement time. Also, the motion kinematics were displayed in the presence, or absence, of end-state-targets. Kinematic analyses showed atypical biological motion kinematics were imitated, and that this performance was different from the constant velocity control condition. Although the imitation of atypical biological motion kinematics was not modulated by the end-state-targets, movement time was more accurate in the absence, compared to the presence, of an end-state-target. The fact that end-state targets modulated movement time accuracy, but not biological motion kinematics, indicates imitation learning involves top-down attentional, and lower-level sensorimotor systems, which operate as complementary processes mediated by the environmental context. Copyright © 2015 Elsevier B.V. All rights reserved.

Sensitivity analysis of dynamic biological systems with time-delays.

PubMed

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2010-10-15

Mathematical modeling has been applied to the study and analysis of complex biological systems for a long time. Some processes in biological systems, such as the gene expression and feedback control in signal transduction networks, involve a time delay. These systems are represented as delay differential equation (DDE) models. Numerical sensitivity analysis of a DDE model by the direct method requires the solutions of model and sensitivity equations with time-delays. The major effort is the computation of Jacobian matrix when computing the solution of sensitivity equations. The computation of partial derivatives of complex equations either by the analytic method or by symbolic manipulation is time consuming, inconvenient, and prone to introduce human errors. To address this problem, an automatic approach to obtain the derivatives of complex functions efficiently and accurately is necessary. We have proposed an efficient algorithm with an adaptive step size control to compute the solution and dynamic sensitivities of biological systems described by ordinal differential equations (ODEs). The adaptive direct-decoupled algorithm is extended to solve the solution and dynamic sensitivities of time-delay systems describing by DDEs. To save the human effort and avoid the human errors in the computation of partial derivatives, an automatic differentiation technique is embedded in the extended algorithm to evaluate the Jacobian matrix. The extended algorithm is implemented and applied to two realistic models with time-delays: the cardiovascular control system and the TNF-α signal transduction network. The results show that the extended algorithm is a good tool for dynamic sensitivity analysis on DDE models with less user intervention. By comparing with direct-coupled methods in theory, the extended algorithm is efficient, accurate, and easy to use for end users without programming background to do dynamic sensitivity analysis on complex biological systems with time-delays.

Pig Brain Mitochondria as a Biological Model for Study of Mitochondrial Respiration.

PubMed

Fišar, Z; Hroudová, J

2016-01-01

Oxidative phosphorylation is a key process of intracellular energy transfer by which mitochondria produce ATP. Isolated mitochondria serve as a biological model for understanding the mitochondrial respiration control, effects of various biologically active substances, and pathophysiology of mitochondrial diseases. The aim of our study was to evaluate pig brain mitochondria as a proper biological model for investigation of activity of the mitochondrial electron transport chain. Oxygen consumption rates of isolated pig brain mitochondria were measured using high-resolution respirometry. Mitochondrial respiration of crude mitochondrial fraction, mitochondria purified in sucrose gradient, and mitochondria purified in Percoll gradient were assayed as a function of storage time. Oxygen flux and various mitochondrial respiratory control ratios were not changed within two days of mitochondria storage on ice. Leak respiration was found higher and Complex I-linked respiration lower in purified mitochondria compared to the crude mitochondrial fraction. Damage to both outer and inner mitochondrial membrane caused by the isolation procedure was the greatest after purification in a sucrose gradient. We confirmed that pig brain mitochondria can serve as a biological model for investigation of mitochondrial respiration. The advantage of this biological model is the stability of respiratory parameters for more than 48 h and the possibility to isolate large amounts of mitochondria from specific brain areas without the need to kill laboratory animals. We suggest the use of high-resolution respirometry of pig brain mitochondria for research of the neuroprotective effects and/or mitochondrial toxicity of new medical drugs.

A Simulation Model for Studying Effects of Pollution and Freshwater Inflow on Secondary Productivity in an Ecosystem. Ph.D. Thesis - North Carolina State Univ.

NASA Technical Reports Server (NTRS)

Johnson, R. W.

1974-01-01

A mathematical model of an ecosystem is developed. Secondary productivity is evaluated in terms of man related and controllable factors. Information from an existing physical parameters model is used as well as pertinent biological measurements. Predictive information of value to estuarine management is presented. Biological, chemical, and physical parameters measured in order to develop models of ecosystems are identified.

Applications of biological control in resistant host-pathogen systems.

PubMed

White, Steven M; White, K A Jane

2005-09-01

Insect pest species can have devastating effects on crops. Control of these insect pests is usually achieved by using chemical insecticides. However, there has been much cause for concern with their overuse. Consequently, research has been carried out into alternative forms of control, in particular biological control methods. Recent laboratory studies have indicated that these natural forms of control can induce resistant strains of insect pest. In this paper we present a discrete-time host-pathogen model to describe the interaction between a host (insect species) that can develop a resistant strain and a pathogen (biological control) that can be externally applied to the system. For this model we use a single-state variable for the host population. We show that the proportion of resistance in the population impacts on the viability of the host population. Moreover, when the host population does persist, we explore the interaction between host susceptibility and host population levels. The different scenarios which arise are explained ecologically in terms of trade-offs in intrinsic growth rates, disease susceptibility and intraspecific host competition for the resistant subclass.

Control of Plasmodium knowlesi malaria

NASA Astrophysics Data System (ADS)

Abdullahi, Mohammed Baba; Hasan, Yahya Abu; Abdullah, Farah Aini

2015-10-01

The most significant and efficient measures against Plasmodium knowlesi outbreaks are efficient anti malaria drug, biological control in form of predatory mosquitoes and culling control strategies. In this paper optimal control theory is applied to a system of ordinary differential equation. It describes the disease transmission and Pontryagin's Maximum Principle is applied for analysis of the control. To this end, three control strategies representing biological control, culling and treatment were incorporated into the disease transmission model. The simulation results show that the implementation of the combination strategy during the epidemic is the most cost-effective strategy for disease transmission.

Payao: a community platform for SBML pathway model curation

PubMed Central

Matsuoka, Yukiko; Ghosh, Samik; Kikuchi, Norihiro; Kitano, Hiroaki

2010-01-01

Summary: Payao is a community-based, collaborative web service platform for gene-regulatory and biochemical pathway model curation. The system combines Web 2.0 technologies and online model visualization functions to enable a collaborative community to annotate and curate biological models. Payao reads the models in Systems Biology Markup Language format, displays them with CellDesigner, a process diagram editor, which complies with the Systems Biology Graphical Notation, and provides an interface for model enrichment (adding tags and comments to the models) for the access-controlled community members. Availability and implementation: Freely available for model curation service at http://www.payaologue.org. Web site implemented in Seaser Framework 2.0 with S2Flex2, MySQL 5.0 and Tomcat 5.5, with all major browsers supported. Contact: kitano@sbi.jp PMID:20371497

Constructing biological pathway models with hybrid functional Petri nets.

PubMed

Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru

2004-01-01

In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.

Constructing biological pathway models with hybrid functional petri nets.

PubMed

Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru

2011-01-01

In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.

Controlling automatic imitative tendencies: interactions between mirror neuron and cognitive control systems.

PubMed

Cross, Katy A; Torrisi, Salvatore; Reynolds Losin, Elizabeth A; Iacoboni, Marco

2013-12-01

Humans have an automatic tendency to imitate others. Although several regions commonly observed in social tasks have been shown to be involved in imitation control, there is little work exploring how these regions interact with one another. We used fMRI and dynamic causal modeling to identify imitation-specific control mechanisms and examine functional interactions between regions. Participants performed a pre-specified action (lifting their index or middle finger) in response to videos depicting the same two actions (biological cues) or dots moving with similar trajectories (non-biological cues). On congruent trials, the stimulus and response were similar (e.g. index finger response to index finger or left side dot stimulus), while on incongruent trials the stimulus and response were dissimilar (e.g. index finger response to middle finger or right side dot stimulus). Reaction times were slower on incongruent compared to congruent trials for both biological and non-biological stimuli, replicating previous findings that suggest the automatic imitative or spatially compatible (congruent) response must be controlled on incongruent trials. Neural correlates of the congruency effects were different depending on the cue type. The medial prefrontal cortex, anterior cingulate, inferior frontal gyrus pars opercularis (IFGpo) and the left anterior insula were involved specifically in controlling imitation. In addition, the IFGpo was also more active for biological compared to non-biological stimuli, suggesting that the region represents the frontal node of the human mirror neuron system (MNS). Effective connectivity analysis exploring the interactions between these regions, suggests a role for the mPFC and ACC in imitative conflict detection and the anterior insula in conflict resolution processes, which may occur through interactions with the frontal node of the MNS. We suggest an extension of the previous models of imitation control involving interactions between imitation-specific and general cognitive control mechanisms. © 2013.

Classical Biological Control of Invasive Legacy Crop Pests: New Technologies Offer Opportunities to Revisit Old Pest Problems in Perennial Tree Crops

PubMed Central

Hoddle, Mark S.; Warner, Keith; Steggall, John; Jetter, Karen M.

2014-01-01

Advances in scientific disciplines that support classical biological control have provided “new tools” that could have important applications for biocontrol programs for some long-established invasive arthropod pests. We suggest that these previously unavailable tools should be used in biological control programs targeting “legacy pests”, even if they have been targets of previously unsuccessful biocontrol projects. Examples of “new tools” include molecular analyses to verify species identities and likely geographic area of origin, climate matching and ecological niche modeling, preservation of natural enemy genetic diversity in quarantine, the use of theory from invasion biology to maximize establishment likelihoods for natural enemies, and improved understanding of the interactions between natural enemy and target pest microbiomes. This review suggests that opportunities exist for revisiting old pest problems and funding research programs using “new tools” for developing biological control programs for “legacy pests” could provide permanent suppression of some seemingly intractable pest problems. As a case study, we use citricola scale, Coccus pseudomagnoliarum, an invasive legacy pest of California citrus, to demonstrate the potential of new tools to support a new classical biological control program targeting this insect. PMID:26463063

Study report on guidelines and test procedures for investigating stability of nonlinear cardiovascular control system models

NASA Technical Reports Server (NTRS)

Fitzjerrell, D. G.

1974-01-01

A general study of the stability of nonlinear as compared to linear control systems is presented. The analysis is general and, therefore, applies to other types of nonlinear biological control systems as well as the cardiovascular control system models. Both inherent and numerical stability are discussed for corresponding analytical and graphic methods and numerical methods.

Microbiological control of soil-borne phytopathogenic fungi with special emphasis on wilt-inducing Fusarium oxysporum.

PubMed

Alabouvette, Claude; Olivain, Chantal; Migheli, Quirico; Steinberg, Christian

2009-11-01

Plant diseases induced by soil-borne plant pathogens are among the most difficult to control. In the absence of effective chemical control methods, there is renewed interest in biological control based on application of populations of antagonistic micro-organisms. In addition to Pseudomonas spp. and Trichoderma spp., which are the two most widely studied groups of biological control agents, the protective strains of Fusarium oxysporum represent an original model. These protective strains of F. oxysporum can be used to control wilt induced by pathogenic strains of the same species. Exploring the mechanisms involved in the protective capability of these strains is not only necessary for their development as commercial biocontrol agents but raises many basic questions related to the determinism of pathogenicity versus biocontrol capacity in the F. oxysporum species complex. In this paper, current knowledge regarding the interaction between the plant and the protective strains is reviewed in comparison with interactions between the plant and pathogenic strains. The success of biological control depends not only on plant-microbial interactions but also on the ecological fitness of the biological control agents.

Effect of a care plan based on Roy adaptation model biological dimension on stroke patients' physiologic adaptation level.

PubMed

Alimohammadi, Nasrollah; Maleki, Bibi; Shahriari, Mohsen; Chitsaz, Ahmad

2015-01-01

Stroke is a stressful event with several functional, physical, psychological, social, and economic problems that affect individuals' different living balances. With coping strategies, patients try to control these problems and return to their natural life. The aim of this study is to investigate the effect of a care plan based on Roy adaptation model biological dimension on stroke patients' physiologic adaptation level. This study is a clinical trial in which 50 patients, affected by brain stroke and being admitted in the neurology ward of Kashani and Alzahra hospitals, were randomly assigned to control and study groups in Isfahan in 2013. Roy adaptation model care plan was administered in biological dimension in the form of four sessions and phone call follow-ups for 1 month. The forms related to Roy adaptation model were completed before and after intervention in the two groups. Chi-square test and t-test were used to analyze the data through SPSS 18. There was a significant difference in mean score of adaptation in physiological dimension in the study group after intervention (P < 0.001) compared to before intervention. Comparison of the mean scores of changes of adaptation in the patients affected by brain stroke in the study and control groups showed a significant increase in physiological dimension in the study group by 47.30 after intervention (P < 0.001). The results of study showed that Roy adaptation model biological dimension care plan can result in an increase in adaptation in patients with stroke in physiological dimension. Nurses can use this model for increasing patients' adaptation.

A survey of fuzzy logic monitoring and control utilisation in medicine.

PubMed

Mahfouf, M; Abbod, M F; Linkens, D A

2001-01-01

Intelligent systems have appeared in many technical areas, such as consumer electronics, robotics and industrial control systems. Many of these intelligent systems are based on fuzzy control strategies which describe complex systems mathematical models in terms of linguistic rules. Since the 1980s new techniques have appeared from which fuzzy logic has been applied extensively in medical systems. The justification for such intelligent systems driven solutions is that biological systems are so complex that the development of computerised systems within such environments is not always a straightforward exercise. In practice, a precise model may not exist for biological systems or it may be too difficult to model. In most cases fuzzy logic is considered to be an ideal tool as human minds work from approximate data, extract meaningful information and produce crisp solutions. This paper surveys the utilisation of fuzzy logic control and monitoring in medical sciences with an analysis of its possible future penetration.

Allee effects in tritrophic food chains: some insights in pest biological control.

PubMed

Costa, Michel Iskin da S; Dos Anjos, Lucas

2016-12-01

Release of natural enemies to control pest populations is a common strategy in biological control. However, its effectiveness is supposed to be impaired, among other factors, by Allee effects in the biological control agent and by the fact that introduced pest natural enemies interact with some native species of the ecosystem. In this work, we devise a tritrophic food chain model where the assumptions previously raised are proved correct when a hyperpredator attacks the introduced pest natural enemy by a functional response type 2 or 3. Moreover, success of pest control is shown to be related to the release of large amounts (i.e., inundative releases) of natural enemies. © The authors 2015. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Biology-Inspired Autonomous Control

DTIC Science & Technology

2011-08-31

from load sensing in a turbulent flow field with high levels of plant uncertainty and optical feedback latency. The results of this paper suggest... Mimicry of biological systems, in the form of precise mathematical or physical dynamical modeling, is yielding impressive insight into the underlying...processing and plants , the aerospace industry has been slow to accept adaptive control. In the past decade however, newer methods for design of adaptive

Engineering challenges of BioNEMS: the integration of microfluidics, micro- and nanodevices, models and external control for systems biology.

PubMed

Wikswo, J P; Prokop, A; Baudenbacher, F; Cliffel, D; Csukas, B; Velkovsky, M

2006-08-01

Systems biology, i.e. quantitative, postgenomic, postproteomic, dynamic, multiscale physiology, addresses in an integrative, quantitative manner the shockwave of genetic and proteomic information using computer models that may eventually have 10(6) dynamic variables with non-linear interactions. Historically, single biological measurements are made over minutes, suggesting the challenge of specifying 10(6) model parameters. Except for fluorescence and micro-electrode recordings, most cellular measurements have inadequate bandwidth to discern the time course of critical intracellular biochemical events. Micro-array expression profiles of thousands of genes cannot determine quantitative dynamic cellular signalling and metabolic variables. Major gaps must be bridged between the computational vision and experimental reality. The analysis of cellular signalling dynamics and control requires, first, micro- and nano-instruments that measure simultaneously multiple extracellular and intracellular variables with sufficient bandwidth; secondly, the ability to open existing internal control and signalling loops; thirdly, external BioMEMS micro-actuators that provide high bandwidth feedback and externally addressable intracellular nano-actuators; and, fourthly, real-time, closed-loop, single-cell control algorithms. The unravelling of the nested and coupled nature of cellular control loops requires simultaneous recording of multiple single-cell signatures. Externally controlled nano-actuators, needed to effect changes in the biochemical, mechanical and electrical environment both outside and inside the cell, will provide a major impetus for nanoscience.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology.

PubMed

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

2012-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

PubMed Central

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

2013-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals. PMID:24688682

Biological control via "ecological" damping: An approach that attenuates non-target effects.

PubMed

Parshad, Rana D; Quansah, Emmanuel; Black, Kelly; Beauregard, Matthew

2016-03-01

In this work we develop and analyze a mathematical model of biological control to prevent or attenuate the explosive increase of an invasive species population, that functions as a top predator, in a three-species food chain. We allow for finite time blow-up in the model as a mathematical construct to mimic the explosive increase in population, enabling the species to reach "disastrous", and uncontrollable population levels, in a finite time. We next improve the mathematical model and incorporate controls that are shown to drive down the invasive population growth and, in certain cases, eliminate blow-up. Hence, the population does not reach an uncontrollable level. The controls avoid chemical treatments and/or natural enemy introduction, thus eliminating various non-target effects associated with such classical methods. We refer to these new controls as "ecological damping", as their inclusion dampens the invasive species population growth. Further, we improve prior results on the regularity and Turing instability of the three-species model that were derived in Parshad et al. (2014). Lastly, we confirm the existence of spatiotemporal chaos. Copyright © 2016 Elsevier Inc. All rights reserved.

Ion-driven photoluminescence modulation of quasi-two-dimensional MoS2 nanoflakes for applications in biological systems.

PubMed

Ou, Jian Zhen; Chrimes, Adam F; Wang, Yichao; Tang, Shi-yang; Strano, Michael S; Kalantar-zadeh, Kourosh

2014-02-12

Quasi-two-dimensional (quasi-2D) molybdenum disulfide (MoS2) is a photoluminescence (PL) material with unique properties. The recent demonstration of its PL, controlled by the intercalation of positive ions, can lead to many opportunities for employing this quasi-2D material in ion-related biological applications. Here, we present two representative models of biological systems that incorporate the ion-controlled PL of quasi-2D MoS2 nanoflakes. The ion exchange behaviors of these two models are investigated to reveal enzymatic activities and cell viabilities. While the ion intercalation of MoS2 in enzymatic activities is enabled via an external applied voltage, the intercalation of ions in cell viability investigations occurs in the presence of the intrinsic cell membrane potential.

Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

USDA-ARS?s Scientific Manuscript database

Ecosystem-service models are increasingly implemented in diverse decision-making contexts, from land-use planning to corporate risk management. Though widely valued, biological control of crop pests is rarely considered in such decisions in part because suitable pest-control models do not exist. Her...

Modeling and Advanced Control for Sustainable Process Systems

EPA Science Inventory

This book chapter introduces a novel process systems engineering framework that integrates process control with sustainability assessment tools for the simultaneous evaluation and optimization of process operations. The implemented control strategy consists of a biologically-insp...

Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery.

PubMed

Bosl, William J

2007-02-15

Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer.

BinQuasi: a peak detection method for ChIP-sequencing data with biological replicates.

PubMed

Goren, Emily; Liu, Peng; Wang, Chao; Wang, Chong

2018-04-19

ChIP-seq experiments that are aimed at detecting DNA-protein interactions require biological replication to draw inferential conclusions, however there is no current consensus on how to analyze ChIP-seq data with biological replicates. Very few methodologies exist for the joint analysis of replicated ChIP-seq data, with approaches ranging from combining the results of analyzing replicates individually to joint modeling of all replicates. Combining the results of individual replicates analyzed separately can lead to reduced peak classification performance compared to joint modeling. Currently available methods for joint analysis may fail to control the false discovery rate at the nominal level. We propose BinQuasi, a peak caller for replicated ChIP-seq data, that jointly models biological replicates using a generalized linear model framework and employs a one-sided quasi-likelihood ratio test to detect peaks. When applied to simulated data and real datasets, BinQuasi performs favorably compared to existing methods, including better control of false discovery rate than existing joint modeling approaches. BinQuasi offers a flexible approach to joint modeling of replicated ChIP-seq data which is preferable to combining the results of replicates analyzed individually. Source code is freely available for download at https://cran.r-project.org/package=BinQuasi, implemented in R. pliu@iastate.edu or egoren@iastate.edu. Supplementary material is available at Bioinformatics online.

Controlling complexity: the clinical relevance of mouse complex genetics

PubMed Central

Schughart, Klaus; Libert, Claude; Kas, Martien J

2013-01-01

Experimental animal models are essential to obtain basic knowledge of the underlying biological mechanisms in human diseases. Here, we review major contributions to biomedical research and discoveries that were obtained in the mouse model by using forward genetics approaches and that provided key insights into the biology of human diseases and paved the way for the development of novel therapeutic approaches. PMID:23632795

Dynamics and Control of a Biomimetic Vehicle Using Biased Wingbeat Forcing Functions: Part 1 - Aerodynamic Model (Postprint)

DTIC Science & Technology

2010-01-01

Experimental Biology, Vol. 46, 1967, pp. 431–443. 5Sane, S. P. and Dickenson , M. H., “The Control of Flight Force by a Flapping Wing: Lift and Drag Force...Production,” The Journal of Experimental Biology, Vol. 204, 2001, pp. 2607–2626. 6Sane, S. P. and Dickenson , M. H., “The aerodynamic effects of wing

Biohybrid Control of General Linear Systems Using the Adaptive Filter Model of Cerebellum.

PubMed

Wilson, Emma D; Assaf, Tareq; Pearson, Martin J; Rossiter, Jonathan M; Dean, Paul; Anderson, Sean R; Porrill, John

2015-01-01

The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems, such as the vestibulo-ocular reflex (VOR), and to sensory processing problems, such as the adaptive cancelation of reafferent noise. It has also been successfully applied to problems in robotics, such as adaptive camera stabilization and sensor noise cancelation. In previous applications to inverse control problems, the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity) control of this plant results in unstable learning and control. To be more generally useful in engineering problems, it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC) scheme, which stabilizes the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar-inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.

Virtual Transgenics: Using a Molecular Biology Simulation to Impact Student Academic Achievement and Attitudes

NASA Astrophysics Data System (ADS)

Shegog, Ross; Lazarus, Melanie M.; Murray, Nancy G.; Diamond, Pamela M.; Sessions, Nathalie; Zsigmond, Eva

2012-10-01

The transgenic mouse model is useful for studying the causes and potential cures for human genetic diseases. Exposing high school biology students to laboratory experience in developing transgenic animal models is logistically prohibitive. Computer-based simulation, however, offers this potential in addition to advantages of fidelity and reach. This study describes and evaluates a computer-based simulation to train advanced placement high school science students in laboratory protocols, a transgenic mouse model was produced. A simulation module on preparing a gene construct in the molecular biology lab was evaluated using a randomized clinical control design with advanced placement high school biology students in Mercedes, Texas ( n = 44). Pre-post tests assessed procedural and declarative knowledge, time on task, attitudes toward computers for learning and towards science careers. Students who used the simulation increased their procedural and declarative knowledge regarding molecular biology compared to those in the control condition (both p < 0.005). Significant increases continued to occur with additional use of the simulation ( p < 0.001). Students in the treatment group became more positive toward using computers for learning ( p < 0.001). The simulation did not significantly affect attitudes toward science in general. Computer simulation of complex transgenic protocols have potential to provide a "virtual" laboratory experience as an adjunct to conventional educational approaches.

Agent-based modelling in synthetic biology.

PubMed

Gorochowski, Thomas E

2016-11-30

Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. © 2016 The Author(s).

Control of Stochastic Master Equation Models of Genetic Regulatory Networks by Approximating Their Average Behavior

NASA Astrophysics Data System (ADS)

Umut Caglar, Mehmet; Pal, Ranadip

2010-10-01

The central dogma of molecular biology states that ``information cannot be transferred back from protein to either protein or nucleic acid.'' However, this assumption is not exactly correct in most of the cases. There are a lot of feedback loops and interactions between different levels of systems. These types of interactions are hard to analyze due to the lack of data in the cellular level and probabilistic nature of interactions. Probabilistic models like Stochastic Master Equation (SME) or deterministic models like differential equations (DE) can be used to analyze these types of interactions. SME models based on chemical master equation (CME) can provide detailed representation of genetic regulatory system, but their use is restricted by the large data requirements and computational costs of calculations. The differential equations models on the other hand, have low calculation costs and much more adequate to generate control procedures on the system; but they are not adequate to investigate the probabilistic nature of interactions. In this work the success of the mapping between SME and DE is analyzed, and the success of a control policy generated by DE model with respect to SME model is examined. Index Terms--- Stochastic Master Equation models, Differential Equation Models, Control Policy Design, Systems biology

Identifying biological concepts from a protein-related corpus with a probabilistic topic model

PubMed Central

Zheng, Bin; McLean, David C; Lu, Xinghua

2006-01-01

Background Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE© titles and abstracts by applying a probabilistic topic model. Results The latent Dirichlet allocation (LDA) model was applied to the corpus. Based on the Bayesian model selection, 300 major topics were extracted from the corpus. The majority of identified topics/concepts was found to be semantically coherent and most represented biological objects or concepts. The identified topics/concepts were further mapped to the controlled vocabulary of the Gene Ontology (GO) terms based on mutual information. Conclusion The major and recurring biological concepts within a collection of MEDLINE documents can be extracted by the LDA model. The identified topics/concepts provide parsimonious and semantically-enriched representation of the texts in a semantic space with reduced dimensionality and can be used to index text. PMID:16466569

Anomalous glassy dynamics in simple models of dense biological tissue

NASA Astrophysics Data System (ADS)

Sussman, Daniel M.; Paoluzzi, M.; Marchetti, M. Cristina; Manning, M. Lisa

2018-02-01

In order to understand the mechanisms for glassy dynamics in biological tissues and shed light on those in non-biological materials, we study the low-temperature disordered phase of 2D vertex-like models. Recently it has been noted that vertex models have quite unusual behavior in the zero-temperature limit, with rigidity transitions that are controlled by residual stresses and therefore exhibit very different scaling and phenomenology compared to particulate systems. Here we investigate the finite-temperature phase of two-dimensional Voronoi and Vertex models, and show that they have highly unusual, sub-Arrhenius scaling of dynamics with temperature. We connect the anomalous glassy dynamics to features of the potential energy landscape associated with zero-temperature inherent states.

Fifty years of the integrated control concept: moving the model and implementation forward in Arizona††

PubMed Central

Naranjo, Steven E; Ellsworth, Peter C

2009-01-01

Fifty years ago, Stern, Smith, van den Bosch and Hagen outlined a simple but sophisticated idea of pest control predicated on the complementary action of chemical and biological control. This integrated control concept has since been a driving force and conceptual foundation for all integrated pest management (IPM) programs. The four basic elements include thresholds for determining the need for control, sampling to determine critical densities, understanding and conserving the biological control capacity in the system and the use of selective insecticides or selective application methods, when needed, to augment biological control. Here we detail the development, evolution, validation and implementation of an integrated control (IC) program for whitefly, Bemisia tabaci (Genn.), in the Arizona cotton system that provides a rare example of the vision of Stern and his colleagues. Economic thresholds derived from research-based economic injury levels were developed and integrated with rapid and accurate sampling plans into validated decision tools widely adopted by consultants and growers. Extensive research that measured the interplay among pest population dynamics, biological control by indigenous natural enemies and selective insecticides using community ordination methods, predator:prey ratios, predator exclusion and demography validated the critical complementary roles played by chemical and biological control. The term ‘bioresidual’ was coined to describe the extended environmental resistance from biological control and other forces possible when selective insecticides are deployed. The tangible benefits have been a 70% reduction in foliar insecticides, a >$200 million saving in control costs and yield, along with enhanced utilization of ecosystem services over the last 14 years. Published in 2009 by John Wiley & Sons, Ltd. PMID:19834884

Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale

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

Zabaras, Nicolas J.

2016-11-08

Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.

Models for integrated pest control and their biological implications.

PubMed

Tang, Sanyi; Cheke, Robert A

2008-09-01

Successful integrated pest management (IPM) control programmes depend on many factors which include host-parasitoid ratios, starting densities, timings of parasitoid releases, dosages and timings of insecticide applications and levels of host-feeding and parasitism. Mathematical models can help us to clarify and predict the effects of such factors on the stability of host-parasitoid systems, which we illustrate here by extending the classical continuous and discrete host-parasitoid models to include an IPM control programme. The results indicate that one of three control methods can maintain the host level below the economic threshold (ET) in relation to different ET levels, initial densities of host and parasitoid populations and host-parasitoid ratios. The effects of host intrinsic growth rate and parasitoid searching efficiency on host mean outbreak period can be calculated numerically from the models presented. The instantaneous pest killing rate of an insecticide application is also estimated from the models. The results imply that the modelling methods described can help in the design of appropriate control strategies and assist management decision-making. The results also indicate that a high initial density of parasitoids (such as in inundative releases) and high parasitoid inter-generational survival rates will lead to more frequent host outbreaks and, therefore, greater economic damage. The biological implications of this counter intuitive result are discussed.

Enhanced treatment of secondary municipal wastewater effluent: comparing (biological) filtration and ozonation in view of micropollutant removal, unselective effluent toxicity, and the potential for real-time control.

PubMed

Chys, Michael; Demeestere, Kristof; Ingabire, Ange Sabine; Dries, Jan; Van Langenhove, Herman; Van Hulle, Stijn W H

2017-07-01

Ozonation and three (biological) filtration techniques (trickling filtration (TF), slow sand filtration (SSF) and biological activated carbon (BAC) filtration) have been evaluated in different combinations as tertiary treatment for municipal wastewater effluent. The removal of 18 multi-class pharmaceuticals, as model trace organic contaminants (TrOCs), has been studied. (Biological) activated carbon filtration could reduce the amount of TrOCs significantly (>99%) but is cost-intensive for full-scale applications. Filtration techniques mainly depending on biodegradation mechanisms (TF and SSF) are found to be inefficient for TrOCs removal as a stand alone technique. Ozonation resulted in 90% removal of the total amount of quantified TrOCs, but a post-ozonation step is needed to cope with an increased unselective toxicity. SSF following ozonation showed to be the only technique able to reduce the unselective toxicity to the same level as before ozonation. In view of process control, innovative correlation models developed for the monitoring and control of TrOC removal during ozonation, are verified for their applicability during ozonation in combination with TF, SSF or BAC. Particularly for the poorly ozone reactive TrOCs, statistically significant models were obtained that correlate TrOC removal and reduction in UVA 254 as an online measured surrogate parameter.

Speed adaptation in a powered transtibial prosthesis controlled with a neuromuscular model.

PubMed

Markowitz, Jared; Krishnaswamy, Pavitra; Eilenberg, Michael F; Endo, Ken; Barnhart, Chris; Herr, Hugh

2011-05-27

Control schemes for powered ankle-foot prostheses would benefit greatly from a means to make them inherently adaptive to different walking speeds. Towards this goal, one may attempt to emulate the intact human ankle, as it is capable of seamless adaptation. Human locomotion is governed by the interplay among legged dynamics, morphology and neural control including spinal reflexes. It has been suggested that reflexes contribute to the changes in ankle joint dynamics that correspond to walking at different speeds. Here, we use a data-driven muscle-tendon model that produces estimates of the activation, force, length and velocity of the major muscles spanning the ankle to derive local feedback loops that may be critical in the control of those muscles during walking. This purely reflexive approach ignores sources of non-reflexive neural drive and does not necessarily reflect the biological control scheme, yet can still closely reproduce the muscle dynamics estimated from biological data. The resulting neuromuscular model was applied to control a powered ankle-foot prosthesis and tested by an amputee walking at three speeds. The controller produced speed-adaptive behaviour; net ankle work increased with walking speed, highlighting the benefits of applying neuromuscular principles in the control of adaptive prosthetic limbs.

Evidence-based economic analysis demonstrates that ecosystem service benefits of water hyacinth management greatly exceed research and control costs

PubMed Central

Harms, Nathan E.; Magen, Cedric; Liang, Dong; Nesslage, Genevieve M.; McMurray, Anna M.; Cofrancesco, Al F.

2018-01-01

Invasive species management can be a victim of its own success when decades of effective control cause memories of past harm to fade and raise questions of whether programs should continue. Economic analysis can be used to assess the efficiency of investing in invasive species control by comparing ecosystem service benefits to program costs, but only if appropriate data exist. We used a case study of water hyacinth (Eichhornia crassipes (Mart.) Solms), a nuisance floating aquatic plant, in Louisiana to demonstrate how comprehensive record-keeping supports economic analysis. Using long-term data sets, we developed empirical and spatio-temporal simulation models of intermediate complexity to project invasive species growth for control and no-control scenarios. For Louisiana, we estimated that peak plant cover would be 76% higher without the substantial growth rate suppression (84% reduction) that appeared due primarily to biological control agents. Our economic analysis revealed that combined biological and herbicide control programs, monitored over an unusually long time period (1975–2013), generated a benefit-cost ratio of about 34:1 derived from the relatively modest costs of $124 million ($2013) compared to the $4.2 billion ($2013) in benefits to anglers, waterfowl hunters, boating-dependent businesses, and water treatment facilities over the 38-year analysis period. This work adds to the literature by: (1) providing evidence of the effectiveness of water hyacinth biological control; (2) demonstrating use of parsimonious spatio-temporal models to estimate benefits of invasive species control; and (3) incorporating activity substitution into economic benefit transfer to avoid overstating benefits. Our study suggests that robust and cost-effective economic analysis is enabled by good record keeping and generalizable models that can demonstrate management effectiveness and promote social efficiency of invasive species control. PMID:29844976

Evidence-based economic analysis demonstrates that ecosystem service benefits of water hyacinth management greatly exceed research and control costs.

PubMed

Wainger, Lisa A; Harms, Nathan E; Magen, Cedric; Liang, Dong; Nesslage, Genevieve M; McMurray, Anna M; Cofrancesco, Al F

2018-01-01

Invasive species management can be a victim of its own success when decades of effective control cause memories of past harm to fade and raise questions of whether programs should continue. Economic analysis can be used to assess the efficiency of investing in invasive species control by comparing ecosystem service benefits to program costs, but only if appropriate data exist. We used a case study of water hyacinth ( Eichhornia crassipes (Mart.) Solms), a nuisance floating aquatic plant, in Louisiana to demonstrate how comprehensive record-keeping supports economic analysis. Using long-term data sets, we developed empirical and spatio-temporal simulation models of intermediate complexity to project invasive species growth for control and no-control scenarios. For Louisiana, we estimated that peak plant cover would be 76% higher without the substantial growth rate suppression (84% reduction) that appeared due primarily to biological control agents. Our economic analysis revealed that combined biological and herbicide control programs, monitored over an unusually long time period (1975-2013), generated a benefit-cost ratio of about 34:1 derived from the relatively modest costs of $124 million ($2013) compared to the $4.2 billion ($2013) in benefits to anglers, waterfowl hunters, boating-dependent businesses, and water treatment facilities over the 38-year analysis period. This work adds to the literature by: (1) providing evidence of the effectiveness of water hyacinth biological control; (2) demonstrating use of parsimonious spatio-temporal models to estimate benefits of invasive species control; and (3) incorporating activity substitution into economic benefit transfer to avoid overstating benefits. Our study suggests that robust and cost-effective economic analysis is enabled by good record keeping and generalizable models that can demonstrate management effectiveness and promote social efficiency of invasive species control.

Parameterization and Sensitivity Analysis of a Complex Simulation Model for Mosquito Population Dynamics, Dengue Transmission, and Their Control

PubMed Central

Ellis, Alicia M.; Garcia, Andres J.; Focks, Dana A.; Morrison, Amy C.; Scott, Thomas W.

2011-01-01

Models can be useful tools for understanding the dynamics and control of mosquito-borne disease. More detailed models may be more realistic and better suited for understanding local disease dynamics; however, evaluating model suitability, accuracy, and performance becomes increasingly difficult with greater model complexity. Sensitivity analysis is a technique that permits exploration of complex models by evaluating the sensitivity of the model to changes in parameters. Here, we present results of sensitivity analyses of two interrelated complex simulation models of mosquito population dynamics and dengue transmission. We found that dengue transmission may be influenced most by survival in each life stage of the mosquito, mosquito biting behavior, and duration of the infectious period in humans. The importance of these biological processes for vector-borne disease models and the overwhelming lack of knowledge about them make acquisition of relevant field data on these biological processes a top research priority. PMID:21813844

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

Demirag, N

Purpose: To verify the benefits of the biological cost functions. Methods: TG166 patients were used for the test case scenarios. Patients were planned using Monaco V5.0 (CMS/Elekta, St.Louis, MO) Monaco has 3 biological and 8 physical CFs. In this study the plans were optimized using 3 different scenarios. 1- Biological CFs only 2-Physical CFs only 3- Combination of Physical and Biological CFsMonaco has 3 biological CFs. Target EUD used for the targets, derived from the poisson cell kill model, has an α value that controls the cold spots inside the target. α values used in the optimization were 0.5 andmore » 0.8. if cold spots needs to be penalized α value increased. Serial CF: it's called serial to mimic the behaviour of the serial organs, if a high k value like 12 or 14 is used it controls the maximum dose. Serial CF has a k parameter that is used to shape the whole dvh curve. K value ranges between 1–20. k:1 is used to control the mean dose, lower k value controls the mean dose, higher k value controls the higher dose, using 2 serial CFs with different k values controls the whole DVH. Paralel CF controls the percentage of the volume that tolerates higher doses than the reference dose to mimic the behaviour of the paralel organs. Results: It was possible to achive clinically accepted plans in all 3 scenarios. The benefit of the biological cost functions were to control the mean dose for target and OAR, to shape the DVH curve using one EUD value and one k value simplifies the optimization process. Using the biological CFs alone, it was hard to control the dose at a point. Conclusion: Biological CFs in Monaco doesn't require the ntcp/tcp values from the labs and useful to shape the whole dvh curve. I work as an applications support specialist for Elekta and I am a Ph.D. Student in Istanbul University for radiation therapy physics.« less

Cerebellarlike corrective model inference engine for manipulation tasks.

PubMed

Luque, Niceto Rafael; Garrido, Jesús Alberto; Carrillo, Richard Rafael; Coenen, Olivier J-M D; Ros, Eduardo

2011-10-01

This paper presents how a simple cerebellumlike architecture can infer corrective models in the framework of a control task when manipulating objects that significantly affect the dynamics model of the system. The main motivation of this paper is to evaluate a simplified bio-mimetic approach in the framework of a manipulation task. More concretely, the paper focuses on how the model inference process takes place within a feedforward control loop based on the cerebellar structure and on how these internal models are built up by means of biologically plausible synaptic adaptation mechanisms. This kind of investigation may provide clues on how biology achieves accurate control of non-stiff-joint robot with low-power actuators which involve controlling systems with high inertial components. This paper studies how a basic temporal-correlation kernel including long-term depression (LTD) and a constant long-term potentiation (LTP) at parallel fiber-Purkinje cell synapses can effectively infer corrective models. We evaluate how this spike-timing-dependent plasticity correlates sensorimotor activity arriving through the parallel fibers with teaching signals (dependent on error estimates) arriving through the climbing fibers from the inferior olive. This paper addresses the study of how these LTD and LTP components need to be well balanced with each other to achieve accurate learning. This is of interest to evaluate the relevant role of homeostatic mechanisms in biological systems where adaptation occurs in a distributed manner. Furthermore, we illustrate how the temporal-correlation kernel can also work in the presence of transmission delays in sensorimotor pathways. We use a cerebellumlike spiking neural network which stores the corrective models as well-structured weight patterns distributed among the parallel fibers to Purkinje cell connections.

Robotics-inspired biology.

PubMed

Gravish, Nick; Lauder, George V

2018-03-29

For centuries, designers and engineers have looked to biology for inspiration. Biologically inspired robots are just one example of the application of knowledge of the natural world to engineering problems. However, recent work by biologists and interdisciplinary teams have flipped this approach, using robots and physical models to set the course for experiments on biological systems and to generate new hypotheses for biological research. We call this approach robotics-inspired biology; it involves performing experiments on robotic systems aimed at the discovery of new biological phenomena or generation of new hypotheses about how organisms function that can then be tested on living organisms. This new and exciting direction has emerged from the extensive use of physical models by biologists and is already making significant advances in the areas of biomechanics, locomotion, neuromechanics and sensorimotor control. Here, we provide an introduction and overview of robotics-inspired biology, describe two case studies and suggest several directions for the future of this exciting new research area. © 2018. Published by The Company of Biologists Ltd.

Impaired associative learning in schizophrenia: behavioral and computational studies

PubMed Central

Diwadkar, Vaibhav A.; Flaugher, Brad; Jones, Trevor; Zalányi, László; Ujfalussy, Balázs; Keshavan, Matcheri S.

2008-01-01

Associative learning is a central building block of human cognition and in large part depends on mechanisms of synaptic plasticity, memory capacity and fronto–hippocampal interactions. A disorder like schizophrenia is thought to be characterized by altered plasticity, and impaired frontal and hippocampal function. Understanding the expression of this dysfunction through appropriate experimental studies, and understanding the processes that may give rise to impaired behavior through biologically plausible computational models will help clarify the nature of these deficits. We present a preliminary computational model designed to capture learning dynamics in healthy control and schizophrenia subjects. Experimental data was collected on a spatial-object paired-associate learning task. The task evinces classic patterns of negatively accelerated learning in both healthy control subjects and patients, with patients demonstrating lower rates of learning than controls. Our rudimentary computational model of the task was based on biologically plausible assumptions, including the separation of dorsal/spatial and ventral/object visual streams, implementation of rules of learning, the explicit parameterization of learning rates (a plausible surrogate for synaptic plasticity), and learning capacity (a plausible surrogate for memory capacity). Reductions in learning dynamics in schizophrenia were well-modeled by reductions in learning rate and learning capacity. The synergy between experimental research and a detailed computational model of performance provides a framework within which to infer plausible biological bases of impaired learning dynamics in schizophrenia. PMID:19003486

Statistical Selection of Biological Models for Genome-Wide Association Analyses.

PubMed

Bi, Wenjian; Kang, Guolian; Pounds, Stanley B

2018-05-24

Genome-wide association studies have discovered many biologically important associations of genes with phenotypes. Typically, genome-wide association analyses formally test the association of each genetic feature (SNP, CNV, etc) with the phenotype of interest and summarize the results with multiplicity-adjusted p-values. However, very small p-values only provide evidence against the null hypothesis of no association without indicating which biological model best explains the observed data. Correctly identifying a specific biological model may improve the scientific interpretation and can be used to more effectively select and design a follow-up validation study. Thus, statistical methodology to identify the correct biological model for a particular genotype-phenotype association can be very useful to investigators. Here, we propose a general statistical method to summarize how accurately each of five biological models (null, additive, dominant, recessive, co-dominant) represents the data observed for each variant in a GWAS study. We show that the new method stringently controls the false discovery rate and asymptotically selects the correct biological model. Simulations of two-stage discovery-validation studies show that the new method has these properties and that its validation power is similar to or exceeds that of simple methods that use the same statistical model for all SNPs. Example analyses of three data sets also highlight these advantages of the new method. An R package is freely available at www.stjuderesearch.org/site/depts/biostats/maew. Copyright © 2018. Published by Elsevier Inc.

Autodyne effect in a single-mode Er fibre laser and the possibility of its usage for recognising the evaporated biotissue type

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

Dmitriev, A K; Konovalov, A N; Ul'yanov, V A

2015-12-31

The autodyne signal arising in an Er fibre laser in the course of evaporating biological models of different types is studied and the possibility of recognising the biotissue type using the method of autodyne detection of the backscattered Doppler signal is assessed. In the experiments we modelled the process of surgical intervention using the contact (hole perforation with the Er laser fibre) and noncontact (surface evaporation with the focused radiation) regimes of impact on different biological models. The amplitude – frequency characteristic of the autodyne detection for the Er fibre laser is measured and the initial spectra of the backscatteredmore » Doppler signal arising under the action of laser radiation on the samples of biological models are obtained. The experiments have shown that the spectra of the backscattered Doppler signal, arising in the course of the contact and noncontact action of the Er fibre laser on different biological models, demonstrate clear-cut distinctions. (control of laser radiation parameters)« less

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

PubMed

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.

Control mechanisms for stochastic biochemical systems via computation of reachable sets.

PubMed

Lakatos, Eszter; Stumpf, Michael P H

2017-08-01

Controlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently nonlinear. We present an approach to studying the impact of control measures on motifs of molecular interactions that addresses the problems faced in many biological systems: stochasticity, parameter uncertainty and nonlinearity. We show that our reachability analysis formalism can describe the potential behaviour of biological (naturally evolved as well as engineered) systems, and provides a set of bounds on their dynamics at the level of population statistics: for example, we can obtain the possible ranges of means and variances of mRNA and protein expression levels, even in the presence of uncertainty about model parameters.

Control mechanisms for stochastic biochemical systems via computation of reachable sets

PubMed Central

Lakatos, Eszter

2017-01-01

Controlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently nonlinear. We present an approach to studying the impact of control measures on motifs of molecular interactions that addresses the problems faced in many biological systems: stochasticity, parameter uncertainty and nonlinearity. We show that our reachability analysis formalism can describe the potential behaviour of biological (naturally evolved as well as engineered) systems, and provides a set of bounds on their dynamics at the level of population statistics: for example, we can obtain the possible ranges of means and variances of mRNA and protein expression levels, even in the presence of uncertainty about model parameters. PMID:28878957

Biologically-inspired hexapod robot design and simulation

NASA Technical Reports Server (NTRS)

Espenschied, Kenneth S.; Quinn, Roger D.

1994-01-01

The design and construction of a biologically-inspired hexapod robot is presented. A previously developed simulation is modified to include models of the DC drive motors, the motor driver circuits and their transmissions. The application of this simulation to the design and development of the robot is discussed. The mechanisms thought to be responsible for the leg coordination of the walking stick insect were previously applied to control the straight-line locomotion of a robot. We generalized these rules for a robot walking on a plane. This biologically-inspired control strategy is used to control the robot in simulation. Numerical results show that the general body motion and performance of the simulated robot is similar to that of the robot based on our preliminary experimental results.

Mathematical Modeling of RNA-Based Architectures for Closed Loop Control of Gene Expression.

PubMed

Agrawal, Deepak K; Tang, Xun; Westbrook, Alexandra; Marshall, Ryan; Maxwell, Colin S; Lucks, Julius; Noireaux, Vincent; Beisel, Chase L; Dunlop, Mary J; Franco, Elisa

2018-05-08

Feedback allows biological systems to control gene expression precisely and reliably, even in the presence of uncertainty, by sensing and processing environmental changes. Taking inspiration from natural architectures, synthetic biologists have engineered feedback loops to tune the dynamics and improve the robustness and predictability of gene expression. However, experimental implementations of biomolecular control systems are still far from satisfying performance specifications typically achieved by electrical or mechanical control systems. To address this gap, we present mathematical models of biomolecular controllers that enable reference tracking, disturbance rejection, and tuning of the temporal response of gene expression. These controllers employ RNA transcriptional regulators to achieve closed loop control where feedback is introduced via molecular sequestration. Sensitivity analysis of the models allows us to identify which parameters influence the transient and steady state response of a target gene expression process, as well as which biologically plausible parameter values enable perfect reference tracking. We quantify performance using typical control theory metrics to characterize response properties and provide clear selection guidelines for practical applications. Our results indicate that RNA regulators are well-suited for building robust and precise feedback controllers for gene expression. Additionally, our approach illustrates several quantitative methods useful for assessing the performance of biomolecular feedback control systems.

A biologically based model for the integration of sensory-motor contingencies in rules and plans: a prefrontal cortex based extension of the Distributed Adaptive Control architecture.

PubMed

Duff, Armin; Fibla, Marti Sanchez; Verschure, Paul F M J

2011-06-30

Intelligence depends on the ability of the brain to acquire and apply rules and representations. At the neuronal level these properties have been shown to critically depend on the prefrontal cortex. Here we present, in the context of the Distributed Adaptive Control architecture (DAC), a biologically based model for flexible control and planning based on key physiological properties of the prefrontal cortex, i.e. reward modulated sustained activity and plasticity of lateral connectivity. We test the model in a series of pertinent tasks, including multiple T-mazes and the Tower of London that are standard experimental tasks to assess flexible control and planning. We show that the model is both able to acquire and express rules that capture the properties of the task and to quickly adapt to changes. Further, we demonstrate that this biomimetic self-contained cognitive architecture generalizes to planning. In addition, we analyze the extended DAC architecture, called DAC 6, as a model that can be applied for the creation of intelligent and psychologically believable synthetic agents. Copyright © 2010 Elsevier Inc. All rights reserved.

Effects of crop species richness on pest-natural enemy systems based on an experimental model system using a microlandscape.

PubMed

Zhao, ZiHua; Shi, PeiJian; Men, XingYuan; Ouyang, Fang; Ge, Feng

2013-08-01

The relationship between crop richness and predator-prey interactions as they relate to pest-natural enemy systems is a very important topic in ecology and greatly affects biological control services. The effects of crop arrangement on predator-prey interactions have received much attention as the basis for pest population management. To explore the internal mechanisms and factors driving the relationship between crop richness and pest population management, we designed an experimental model system of a microlandscape that included 50 plots and five treatments. Each treatment had 10 repetitions in each year from 2007 to 2010. The results showed that the biomass of pests and their natural enemies increased with increasing crop biomass and decreased with decreasing crop biomass; however, the effects of plant biomass on the pest and natural enemy biomass were not significant. The relationship between adjacent trophic levels was significant (such as pests and their natural enemies or crops and pests), whereas non-adjacent trophic levels (crops and natural enemies) did not significantly interact with each other. The ratio of natural enemy/pest biomass was the highest in the areas of four crop species that had the best biological control service. Having either low or high crop species richness did not enhance the pest population management service and lead to loss of biological control. Although the resource concentration hypothesis was not well supported by our results, high crop species richness could suppress the pest population, indicating that crop species richness could enhance biological control services. These results could be applied in habitat management aimed at biological control, provide the theoretical basis for agricultural landscape design, and also suggest new methods for integrated pest management.

[Mathematic modeling and experimental validation of macrostate quality expression for multicomponent in Chinese materia medica].

PubMed

He, Fuyuan; Deng, Kaiwen; Shi, Jilian; Liu, Wenlong; Pi, Fengjuan

2011-11-01

To establish the unitive multicomponent quality system bridged macrostate mathematic model parameters of material quality and microstate component concentration for Chinese materia medica (CMM). According to law of biologic laws of thermodynamics, the state functions of macrostate qulity of the CMM were established. The validation test was carried out as modeling drug as alcohol extract of Radix Rhozome (AERR), their enthalpy of combustion was determined, and entropy and the capability of information by chromatographic fingerprint were assayed, and then the biologic apparent macrostate parameters were calculated. The biologic macrostate mathematic models, for the CMM quality controll, were established as parameters as the apparent equilibrium constant, biologic enthalpy, Gibbs free energy and biologic entropy etc. The total molarity for the 10 batchs of AERR were 0.153 4 mmol x g(-1) with 28.26% of RSD, with the average of apparent equilibrium constants, biologic enthalpy, Gibbs free energy and biologic entropy were 0.039 65, 8 005 J x mol(-1), -2.408 x 10(7) J x mol(-1) and - 8.078 x 10(4) J x K(-1) with RSD as 6.020%, 1.860%, 42.32% and 42.31%, respectively. The macrostate quality models for CMM can represent their intrinsic quality for multicomponent dynamic system such as the CMM, to manifest out as if the forest away from or tree near from to see it.

Stochastic cycle selection in active flow networks

NASA Astrophysics Data System (ADS)

Woodhouse, Francis; Forrow, Aden; Fawcett, Joanna; Dunkel, Jorn

2016-11-01

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such non-equilibrium networks. By connecting concepts from lattice field theory, graph theory and transition rate theory, we show how topology controls dynamics in a generic model for actively driven flow on a network. Through theoretical and numerical analysis we identify symmetry-based rules to classify and predict the selection statistics of complex flow cycles from the network topology. Our conceptual framework is applicable to a broad class of biological and non-biological far-from-equilibrium networks, including actively controlled information flows, and establishes a new correspondence between active flow networks and generalized ice-type models.

Echinococcus as a model system: biology and epidemiology.

PubMed

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.

SEEK: a systems biology data and model management platform.

PubMed

Wolstencroft, Katherine; Owen, Stuart; Krebs, Olga; Nguyen, Quyen; Stanford, Natalie J; Golebiewski, Martin; Weidemann, Andreas; Bittkowski, Meik; An, Lihua; Shockley, David; Snoep, Jacky L; Mueller, Wolfgang; Goble, Carole

2015-07-11

Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them. The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data. The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and features of the SEEK software, and describes the use of the SEEK in the SysMO consortium (Systems biology for Micro-organisms), and the VLN (virtual Liver Network), two large systems biology initiatives with different research aims and different scientific communities.

The Spring of Systems Biology-Driven Breeding.

PubMed

Lavarenne, Jérémy; Guyomarc'h, Soazig; Sallaud, Christophe; Gantet, Pascal; Lucas, Mikaël

2018-05-12

Genetics and molecular biology have contributed to the development of rationalized plant breeding programs. Recent developments in both high-throughput experimental analyses of biological systems and in silico data processing offer the possibility to address the whole gene regulatory network (GRN) controlling a given trait. GRN models can be applied to identify topological features helping to shortlist potential candidate genes for breeding purposes. Time-series data sets can be used to support dynamic modelling of the network. This will enable a deeper comprehension of network behaviour and the identification of the few elements to be genetically rewired to push the system towards a modified phenotype of interest. This paves the way to design more efficient, systems biology-based breeding strategies. Copyright © 2018 Elsevier Ltd. All rights reserved.

3D topography of biologic tissue by multiview imaging and structured light illumination

NASA Astrophysics Data System (ADS)

Liu, Peng; Zhang, Shiwu; Xu, Ronald

2014-02-01

Obtaining three-dimensional (3D) information of biologic tissue is important in many medical applications. This paper presents two methods for reconstructing 3D topography of biologic tissue: multiview imaging and structured light illumination. For each method, the working principle is introduced, followed by experimental validation on a diabetic foot model. To compare the performance characteristics of these two imaging methods, a coordinate measuring machine (CMM) is used as a standard control. The wound surface topography of the diabetic foot model is measured by multiview imaging and structured light illumination methods respectively and compared with the CMM measurements. The comparison results show that the structured light illumination method is a promising technique for 3D topographic imaging of biologic tissue.

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework

PubMed Central

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation. PMID:28225811

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

PubMed

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.

A two-agent model applied to the biological control of the sugarcane borer (Diatraea saccharalis) by the egg parasitoid Trichogramma galloi and the larvae parasitoid Cotesia flavipes.

PubMed

Molnár, Sándor; López, Inmaculada; Gámez, Manuel; Garay, József

2016-03-01

The paper is aimed at a methodological development in biological pest control. The considered one pest two-agent system is modelled as a verticum-type system. Originally, linear verticum-type systems were introduced by one of the authors for modelling certain industrial systems. These systems are hierarchically composed of linear subsystems such that a part of the state variables of each subsystem affect the dynamics of the next subsystem. Recently, verticum-type system models have been applied to population ecology as well, which required the extension of the concept a verticum-type system to the nonlinear case. In the present paper the general concepts and technics of nonlinear verticum-type control systems are used to obtain biological control strategies in a two-agent system. For the illustration of this verticum-type control, these tools of mathematical systems theory are applied to a dynamic model of interactions between the egg and larvae populations of the sugarcane borer (Diatraea saccharalis) and its parasitoids: the egg parasitoid Trichogramma galloi and the larvae parasitoid Cotesia flavipes. In this application a key role is played by the concept of controllability, which means that it is possible to steer the system to an equilibrium in given time. In addition to a usual linearization, the basic idea is a decomposition of the control of the whole system into the control of the subsystems, making use of the verticum structure of the population system. The main aim of this study is to show several advantages of the verticum (or decomposition) approach over the classical control theoretical model (without decomposition). For example, in the case of verticum control the pest larval density decreases below the critical threshold value much quicker than without decomposition. Furthermore, it is also shown that the verticum approach may be better even in terms of cost effectiveness. The presented optimal control methodology also turned out to be an efficient tool for the "in silico" analysis of the cost-effectiveness of different biocontrol strategies, e.g. by answering the question how far it is cost-effective to speed up the reduction of the pest larvae density, or along which trajectory this reduction should be carried out. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

In silico evolution of the hunchback gene indicates redundancy in cis-regulatory organization and spatial gene expression

PubMed Central

Zagrijchuk, Elizaveta A.; Sabirov, Marat A.; Holloway, David M.; Spirov, Alexander V.

2014-01-01

Biological development depends on the coordinated expression of genes in time and space. Developmental genes have extensive cis-regulatory regions which control their expression. These regions are organized in a modular manner, with different modules controlling expression at different times and locations. Both how modularity evolved and what function it serves are open questions. We present a computational model for the cis-regulation of the hunchback (hb) gene in the fruit fly (Drosophila). We simulate evolution (using an evolutionary computation approach from computer science) to find the optimal cis-regulatory arrangements for fitting experimental hb expression patterns. We find that the cis-regulatory region tends to readily evolve modularity. These cis-regulatory modules (CRMs) do not tend to control single spatial domains, but show a multi-CRM/multi-domain correspondence. We find that the CRM-domain correspondence seen in Drosophila evolves with a high probability in our model, supporting the biological relevance of the approach. The partial redundancy resulting from multi-CRM control may confer some biological robustness against corruption of regulatory sequences. The technique developed on hb could readily be applied to other multi-CRM developmental genes. PMID:24712536

A reaction-diffusion-based coding rate control mechanism for camera sensor networks.

PubMed

Yamamoto, Hiroshi; Hyodo, Katsuya; Wakamiya, Naoki; Murata, Masayuki

2010-01-01

A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal.

Biochemical Frequency Control by Synchronisation of Coupled Repressilators: An In Silico Study of Modules for Circadian Clock Systems

PubMed Central

Hinze, Thomas; Schumann, Mathias; Bodenstein, Christian; Heiland, Ines; Schuster, Stefan

2011-01-01

Exploration of chronobiological systems emerges as a growing research field within bioinformatics focusing on various applications in medicine, agriculture, and material sciences. From a systems biological perspective, the question arises whether biological control systems for regulation of oscillatory signals and their technical counterparts utilise similar mechanisms. If so, modelling approaches and parameterisation adopted from building blocks can help to identify general components for frequency control in circadian clocks along with gaining insight into mechanisms of clock synchronisation to external stimuli like the daily rhythm of sunlight and darkness. Phase-locked loops could be an interesting candidate in this context. Both, biology and engineering, can benefit from a unified view resulting from systems modularisation. In a first experimental study, we analyse a model of coupled repressilators. We demonstrate its ability to synchronise clock signals in a monofrequential manner. Several oscillators initially deviate in phase difference and frequency with respect to explicit reaction and diffusion rates. Accordingly, the duration of the synchronisation process depends on dedicated reaction and diffusion parameters whose settings still lack to be sufficiently captured analytically. PMID:22046179

The markup is the model: reasoning about systems biology models in the Semantic Web era.

PubMed

Kell, Douglas B; Mendes, Pedro

2008-06-07

Metabolic control analysis, co-invented by Reinhart Heinrich, is a formalism for the analysis of biochemical networks, and is a highly important intellectual forerunner of modern systems biology. Exchanging ideas and exchanging models are part of the international activities of science and scientists, and the Systems Biology Markup Language (SBML) allows one to perform the latter with great facility. Encoding such models in SBML allows their distributed analysis using loosely coupled workflows, and with the advent of the Internet the various software modules that one might use to analyze biochemical models can reside on entirely different computers and even on different continents. Optimization is at the core of many scientific and biotechnological activities, and Reinhart made many major contributions in this area, stimulating our own activities in the use of the methods of evolutionary computing for optimization.

Refined stratified-worm-burden models that incorporate specific biological features of human and snail hosts provide better estimates of Schistosoma diagnosis, transmission, and control.

PubMed

Gurarie, David; King, Charles H; Yoon, Nara; Li, Emily

2016-08-04

Schistosoma parasites sustain a complex transmission process that cycles between a definitive human host, two free-swimming larval stages, and an intermediate snail host. Multiple factors modify their transmission and affect their control, including heterogeneity in host populations and environment, the aggregated distribution of human worm burdens, and features of parasite reproduction and host snail biology. Because these factors serve to enhance local transmission, their inclusion is important in attempting accurate quantitative prediction of the outcomes of schistosomiasis control programs. However, their inclusion raises many mathematical and computational challenges. To address these, we have recently developed a tractable stratified worm burden (SWB) model that occupies an intermediate place between simpler deterministic mean worm burden models and the very computationally-intensive, autonomous agent models. To refine the accuracy of model predictions, we modified an earlier version of the SWB by incorporating factors representing essential in-host biology (parasite mating, aggregation, density-dependent fecundity, and random egg-release) into demographically structured host communities. We also revised the snail component of the transmission model to reflect a saturable form of human-to-snail transmission. The new model allowed us to realistically simulate overdispersed egg-test results observed in individual-level field data. We further developed a Bayesian-type calibration methodology that accounted for model and data uncertainties. The new model methodology was applied to multi-year, individual-level field data on S. haematobium infections in coastal Kenya. We successfully derived age-specific estimates of worm burden distributions and worm fecundity and crowding functions for children and adults. Estimates from the new SWB model were compared with those from the older, simpler SWB with some substantial differences noted. We validated our new SWB estimates in prediction of drug treatment-based control outcomes for a typical Kenyan community. The new version of the SWB model provides a better tool to predict the outcomes of ongoing schistosomiasis control programs. It reflects parasite features that augment and perpetuate transmission, while it also readily incorporates differences in diagnostic testing and human sub-population differences in treatment coverage. Once extended to other Schistosoma species and transmission environments, it will provide a useful and efficient tool for planning control and elimination strategies.

Algorithm for cellular reprogramming.

PubMed

Ronquist, Scott; Patterson, Geoff; Muir, Lindsey A; Lindsly, Stephen; Chen, Haiming; Brown, Markus; Wicha, Max S; Bloch, Anthony; Brockett, Roger; Rajapakse, Indika

2017-11-07

The day we understand the time evolution of subcellular events at a level of detail comparable to physical systems governed by Newton's laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology. With data-guided frameworks we can develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. Here we describe an approach for optimizing the use of transcription factors (TFs) in cellular reprogramming, based on a device commonly used in optimal control. We construct an approximate model for the natural evolution of a cell-cycle-synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points during the cell cycle. To arrive at a model of moderate complexity, we cluster gene expression based on division of the genome into topologically associating domains (TADs) and then model the dynamics of TAD expression levels. Based on this dynamical model and additional data, such as known TF binding sites and activity, we develop a methodology for identifying the top TF candidates for a specific cellular reprogramming task. Our data-guided methodology identifies a number of TFs previously validated for reprogramming and/or natural differentiation and predicts some potentially useful combinations of TFs. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes. Copyright © 2017 the Author(s). Published by PNAS.

Population control methods in stochastic extinction and outbreak scenarios.

PubMed

Segura, Juan; Hilker, Frank M; Franco, Daniel

2017-01-01

Adaptive limiter control (ALC) and adaptive threshold harvesting (ATH) are two related control methods that have been shown to stabilize fluctuating populations. Large variations in population abundance can threaten the constancy and the persistence stability of ecological populations, which may impede the success and efficiency of managing natural resources. Here, we consider population models that include biological mechanisms characteristic for causing extinctions on the one hand and pest outbreaks on the other hand. These models include Allee effects and the impact of natural enemies (as is typical of forest defoliating insects). We study the impacts of noise and different levels of biological parameters in three extinction and two outbreak scenarios. Our results show that ALC and ATH have an effect on extinction and outbreak risks only for sufficiently large control intensities. Moreover, there is a clear disparity between the two control methods: in the extinction scenarios, ALC can be effective and ATH can be counterproductive, whereas in the outbreak scenarios the situation is reversed, with ATH being effective and ALC being potentially counterproductive.

The effect of cooperative learning on the attitudes toward science and the achievement of students in a non-science majors' general biology laboratory course at an urban community college

NASA Astrophysics Data System (ADS)

Chung-Schickler, Genevieve C.

The purpose of this study was to evaluate the effect of cooperative learning strategies on students' attitudes toward science and achievement in BSC 1005L, a non-science majors' general biology laboratory course at an urban community college. Data were gathered on the participants' attitudes toward science and cognitive biology level pre and post treatment in BSC 1005L. Elements of the Learning Together model developed by Johnson and Johnson and the Student Team-Achievement Divisions model created by Slavin were incorporated into the experimental sections of BSC 1005L. Four sections of BSC 1005L participated in this study. Participants were enrolled in the 1998 spring (January) term. Students met weekly in a two hour laboratory session. The treatment was administered to the experimental group over a ten week period. A quasi-experimental pretest-posttest control group design was used. Students in the cooperative learning group (nsb1 = 27) were administered the Test of Science-Related Attitudes (TOSRA) and the cognitive biology test at the same time as the control group (nsb2 = 19) (at the beginning and end of the term). Statistical analyses confirmed that both groups were equivalent regarding ethnicity, gender, college grade point average and number of absences. Independent sample t-tests performed on pretest mean scores indicated no significant differences in the TOSRA scale two or biology knowledge between the cooperative learning group and the control group. The scores of TOSRA scales: one, three, four, five, six, and seven were significantly lower in the cooperative learning group. Independent sample t-tests of the mean score differences did not show any significant differences in posttest attitudes toward science or biology knowledge between the two groups. Paired t-tests did not indicate any significant differences on the TOSRA or biology knowledge within the cooperative learning group. Paired t-tests did show significant differences within the control group on TOSRA scale two and biology knowledge. ANCOVAs did not indicate any significant differences on the post mean scores of the TOSRA or biology knowledge adjusted by differences in the pretest mean scores. Analysis of the research data did not show any significant correlation between attitudes toward science and biology knowledge.

Population-expression models of immune response

NASA Astrophysics Data System (ADS)

Stromberg, Sean P.; Antia, Rustom; Nemenman, Ilya

2013-06-01

The immune response to a pathogen has two basic features. The first is the expansion of a few pathogen-specific cells to form a population large enough to control the pathogen. The second is the process of differentiation of cells from an initial naive phenotype to an effector phenotype which controls the pathogen, and subsequently to a memory phenotype that is maintained and responsible for long-term protection. The expansion and the differentiation have been considered largely independently. Changes in cell populations are typically described using ecologically based ordinary differential equation models. In contrast, differentiation of single cells is studied within systems biology and is frequently modeled by considering changes in gene and protein expression in individual cells. Recent advances in experimental systems biology make available for the first time data to allow the coupling of population and high dimensional expression data of immune cells during infections. Here we describe and develop population-expression models which integrate these two processes into systems biology on the multicellular level. When translated into mathematical equations, these models result in non-conservative, non-local advection-diffusion equations. We describe situations where the population-expression approach can make correct inference from data while previous modeling approaches based on common simplifying assumptions would fail. We also explore how model reduction techniques can be used to build population-expression models, minimizing the complexity of the model while keeping the essential features of the system. While we consider problems in immunology in this paper, we expect population-expression models to be more broadly applicable.

Adaptive Control Model Reveals Systematic Feedback and Key Molecules in Metabolic Pathway Regulation

PubMed Central

Moffitt, Richard A.; Merrill, Alfred H.; Wang, May D.

2011-01-01

Abstract Robust behavior in metabolic pathways resembles stabilized performance in systems under autonomous control. This suggests we can apply control theory to study existing regulation in these cellular networks. Here, we use model-reference adaptive control (MRAC) to investigate the dynamics of de novo sphingolipid synthesis regulation in a combined theoretical and experimental case study. The effects of serine palmitoyltransferase over-expression on this pathway are studied in vitro using human embryonic kidney cells. We report two key results from comparing numerical simulations with observed data. First, MRAC simulations of pathway dynamics are comparable to simulations from a standard model using mass action kinetics. The root-sum-square (RSS) between data and simulations in both cases differ by less than 5%. Second, MRAC simulations suggest systematic pathway regulation in terms of adaptive feedback from individual molecules. In response to increased metabolite levels available for de novo sphingolipid synthesis, feedback from molecules along the main artery of the pathway is regulated more frequently and with greater amplitude than from other molecules along the branches. These biological insights are consistent with current knowledge while being new that they may guide future research in sphingolipid biology. In summary, we report a novel approach to study regulation in cellular networks by applying control theory in the context of robust metabolic pathways. We do this to uncover potential insight into the dynamics of regulation and the reverse engineering of cellular networks for systems biology. This new modeling approach and the implementation routines designed for this case study may be extended to other systems. Supplementary Material is available at www.liebertonline.com/cmb. PMID:21314456

Radiobiological concepts for treatment planning of schemes that combines external beam radiotherapy and systemic targeted radiotherapy

NASA Astrophysics Data System (ADS)

Fabián Calderón Marín, Carlos; González González, Joaquín Jorge; Laguardia, Rodolfo Alfonso

2017-09-01

The combination of radiotherapy modalities with external bundles and systemic radiotherapy (CIERT) could be a reliable alternative for patients with multiple lesions or those where treatment planning maybe difficult because organ(s)-at-risk (OARs) constraints. Radiobiological models should have the capacity for predicting the biological irradiation response considering the differences in the temporal pattern of dose delivering in both modalities. Two CIERT scenarios were studied: sequential combination in which one modality is executed following the other one and concurrent combination when both modalities are running simultaneously. Expressions are provided for calculation of the dose-response magnitudes Tumor Control Probability (TCP) and Normal Tissue Complication Probability (NTCP). General results on radiobiological modeling using the linear-quadratic (LQ) model are also discussed. Inter-subject variation of radiosensitivity and volume irradiation effect in CIERT are studied. OARs should be under control during the planning in concurrent CIERT treatment as the administered activity is increased. The formulation presented here may be used for biological evaluation of prescriptions and biological treatment planning of CIERT schemes in clinical situation.

Backward bifurcation and optimal control of Plasmodium Knowlesi malaria

NASA Astrophysics Data System (ADS)

Abdullahi, Mohammed Baba; Hasan, Yahya Abu; Abdullah, Farah Aini

2014-07-01

A deterministic model for the transmission dynamics of Plasmodium Knowlesi malaria with direct transmission is developed. The model is analyzed using dynamical system techniques and it shows that the backward bifurcation occurs for some range of parameters. The model is extended to assess the impact of time dependent preventive (biological and chemical control) against the mosquitoes and vaccination for susceptible humans, while treatment for infected humans. The existence of optimal control is established analytically by the use of optimal control theory. Numerical simulations of the problem, suggest that applying the four control measure can effectively reduce if not eliminate the spread of Plasmodium Knowlesi in a community.

Teaching Culture within the Nursing Curriculum Using the Giger-Davidhizar Model of Transcultural Nursing Assessment.

ERIC Educational Resources Information Center

Davidhizar, Ruth; Giger, Joyce Newman

2001-01-01

Presents a method for integrating cultural competence throughout the nursing curriculum. The model contains six cultural phenomena: communication, space, social organization, time, environmental control, and biological variation. Contains 17 references. (SK)

Mathematical models of the AIDS epidemic: An historical perspective

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

Stanley, E.A.

1988-01-01

Researchers developing mathematical models of the spreading of HIV, the Human Immunodeficiency Virus that causes AIDS, hope to achieve a number of goals. These goals may be classified rather broadly into three categories: understanding, prediction, and control. Understanding which are the key biological and sociological processes spreading this epidemic and leading to the deaths of those infected will allow AIDS researchers to collect better data and to identify ways of slowing the epidemic. Predicting the groups at risk and future numbers of ill people will allow an appropriate allocation of health-care resources. Analysis and comparison of proposed control methods willmore » point out unexpected consequences and allow a better design of these programs. The processes which lead to the spread of HIV are biologically and sociologically complex. Mathematical models allow us to organize our knowledge into a coherent picture and examine the logical consequences, therefore they have the potential to be extremely useful in the search to control this disease. 24 refs., 3 figs.« less

Calibration and simulation of two large wastewater treatment plants operated for nutrient removal.

PubMed

Ferrer, J; Morenilla, J J; Bouzas, A; García-Usach, F

2004-01-01

Control and optimisation of plant processes has become a priority for WWTP managers. The calibration and verification of a mathematical model provides an important tool for the investigation of advanced control strategies that may assist in the design or optimization of WWTPs. This paper describes the calibration of the ASM2d model for two full scale biological nitrogen and phosphorus removal plants in order to characterize the biological process and to upgrade the plants' performance. Results from simulation showed a good correspondence with experimental data demonstrating that the model and the calibrated parameters were able to predict the behaviour of both WWTPs. Once the calibration and simulation process was finished, a study for each WWTP was done with the aim of improving its performance. Modifications focused on reactor configuration and operation strategies were proposed.

Development of a Systems Computational Model to Investigate Early Biological Events in Hepatic Activation of Constitutive Androstane Receptor (CAR) by Phenobarbital

EPA Science Inventory

Activation of the nuclear receptor CAR (constitutive active/androstane receptor) is implicated in the control several key biological events such as metabolic pathways. Here, we combined data from literature with information obtained from in vitro assays in the US EPA ToxCast dat...

A Framework for Engineering Stress Resilient Plants Using Genetic Feedback Control and Regulatory Network Rewiring.

PubMed

Foo, Mathias; Gherman, Iulia; Zhang, Peijun; Bates, Declan G; Denby, Katherine J

2018-05-23

Crop disease leads to significant waste worldwide, both pre- and postharvest, with subsequent economic and sustainability consequences. Disease outcome is determined both by the plants' response to the pathogen and by the ability of the pathogen to suppress defense responses and manipulate the plant to enhance colonization. The defense response of a plant is characterized by significant transcriptional reprogramming mediated by underlying gene regulatory networks, and components of these networks are often targeted by attacking pathogens. Here, using gene expression data from Botrytis cinerea-infected Arabidopsis plants, we develop a systematic approach for mitigating the effects of pathogen-induced network perturbations, using the tools of synthetic biology. We employ network inference and system identification techniques to build an accurate model of an Arabidopsis defense subnetwork that contains key genes determining susceptibility of the plant to the pathogen attack. Once validated against time-series data, we use this model to design and test perturbation mitigation strategies based on the use of genetic feedback control. We show how a synthetic feedback controller can be designed to attenuate the effect of external perturbations on the transcription factor CHE in our subnetwork. We investigate and compare two approaches for implementing such a controller biologically-direct implementation of the genetic feedback controller, and rewiring the regulatory regions of multiple genes-to achieve the network motif required to implement the controller. Our results highlight the potential of combining feedback control theory with synthetic biology for engineering plants with enhanced resilience to environmental stress.

Planning for smallpox outbreaks

NASA Astrophysics Data System (ADS)

Ferguson, Neil M.; Keeling, Matt J.; John Edmunds, W.; Gani, Raymond; Grenfell, Bryan T.; Anderson, Roy M.; Leach, Steve

2003-10-01

Mathematical models of viral transmission and control are important tools for assessing the threat posed by deliberate release of the smallpox virus and the best means of containing an outbreak. Models must balance biological realism against limitations of knowledge, and uncertainties need to be accurately communicated to policy-makers. Smallpox poses the particular challenge that key biological, social and spatial factors affecting disease spread in contemporary populations must be elucidated largely from historical studies undertaken before disease eradication in 1979. We review the use of models in smallpox planning within the broader epidemiological context set by recent outbreaks of both novel and re-emerging pathogens.

Simplification and its consequences in biological modelling: conclusions from a study of calcium oscillations in hepatocytes.

PubMed

Hetherington, James P J; Warner, Anne; Seymour, Robert M

2006-04-22

Systems Biology requires that biological modelling is scaled up from small components to system level. This can produce exceedingly complex models, which obscure understanding rather than facilitate it. The successful use of highly simplified models would resolve many of the current problems faced in Systems Biology. This paper questions whether the conclusions of simple mathematical models of biological systems are trustworthy. The simplification of a specific model of calcium oscillations in hepatocytes is examined in detail, and the conclusions drawn from this scrutiny generalized. We formalize our choice of simplification approach through the use of functional 'building blocks'. A collection of models is constructed, each a progressively more simplified version of a well-understood model. The limiting model is a piecewise linear model that can be solved analytically. We find that, as expected, in many cases the simpler models produce incorrect results. However, when we make a sensitivity analysis, examining which aspects of the behaviour of the system are controlled by which parameters, the conclusions of the simple model often agree with those of the richer model. The hypothesis that the simplified model retains no information about the real sensitivities of the unsimplified model can be very strongly ruled out by treating the simplification process as a pseudo-random perturbation on the true sensitivity data. We conclude that sensitivity analysis is, therefore, of great importance to the analysis of simple mathematical models in biology. Our comparisons reveal which results of the sensitivity analysis regarding calcium oscillations in hepatocytes are robust to the simplifications necessarily involved in mathematical modelling. For example, we find that if a treatment is observed to strongly decrease the period of the oscillations while increasing the proportion of the cycle during which cellular calcium concentrations are rising, without affecting the inter-spike or maximum calcium concentrations, then it is likely that the treatment is acting on the plasma membrane calcium pump.

APG: an Active Protein-Gene network model to quantify regulatory signals in complex biological systems.

PubMed

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information.

APG: an Active Protein-Gene Network Model to Quantify Regulatory Signals in Complex Biological Systems

PubMed Central

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information. PMID:23346354

Coupling of Coastal Zone Color Scanner data to a physical-biological model of the southeastern U.S. continental shelf ecosystem. I - CZCS data description and Lagrangian particle tracing experiments. II - An Eulerian model. III - Nutrient and phytoplankton fluxes and CZCS data assimilation

NASA Technical Reports Server (NTRS)

Ishizaka, Joji

1990-01-01

Surface phytoplankton biomass of the southeastern U.S. continental shelf area is discussed based on coastal zone color scanner (CZCS) images obtained in April 1980. Data of chlorophyll distributions are analyzed in conjunction with concurrent flow and temperature fields. Lagrangian particle tracing experiments show that the particles move consistently with the evolution of the chlorophyll patterns. A four-component physical-biological model for a horizontal plane at a nominal depth of 17 m is presented. Model simulations using various physical-biological dynamics and boundary conditions show that the variability of chlorophyll distributions is controlled by horizontal advection. Phytoplankton and nutrient fluxes, calculated using the model, show considerable variability with time. The chlorophyll distributions obtained from the CZCS images are assimilated into the model to improve the phytoplankton flux estimates.

Variation across mitochondrial gene trees provides evidence for systematic error: How much gene tree variation is biological?

PubMed

Richards, Emilie J; Brown, Jeremy M; Barley, Anthony J; Chong, Rebecca A; Thomson, Robert C

2018-02-19

The use of large genomic datasets in phylogenetics has highlighted extensive topological variation across genes. Much of this discordance is assumed to result from biological processes. However, variation among gene trees can also be a consequence of systematic error driven by poor model fit, and the relative importance of biological versus methodological factors in explaining gene tree variation is a major unresolved question. Using mitochondrial genomes to control for biological causes of gene tree variation, we estimate the extent of gene tree discordance driven by systematic error and employ posterior prediction to highlight the role of model fit in producing this discordance. We find that the amount of discordance among mitochondrial gene trees is similar to the amount of discordance found in other studies that assume only biological causes of variation. This similarity suggests that the role of systematic error in generating gene tree variation is underappreciated and critical evaluation of fit between assumed models and the data used for inference is important for the resolution of unresolved phylogenetic questions.

BioModels.net Web Services, a free and integrated toolkit for computational modelling software.

PubMed

Li, Chen; Courtot, Mélanie; Le Novère, Nicolas; Laibe, Camille

2010-05-01

Exchanging and sharing scientific results are essential for researchers in the field of computational modelling. BioModels.net defines agreed-upon standards for model curation. A fundamental one, MIRIAM (Minimum Information Requested in the Annotation of Models), standardises the annotation and curation process of quantitative models in biology. To support this standard, MIRIAM Resources maintains a set of standard data types for annotating models, and provides services for manipulating these annotations. Furthermore, BioModels.net creates controlled vocabularies, such as SBO (Systems Biology Ontology) which strictly indexes, defines and links terms used in Systems Biology. Finally, BioModels Database provides a free, centralised, publicly accessible database for storing, searching and retrieving curated and annotated computational models. Each resource provides a web interface to submit, search, retrieve and display its data. In addition, the BioModels.net team provides a set of Web Services which allows the community to programmatically access the resources. A user is then able to perform remote queries, such as retrieving a model and resolving all its MIRIAM Annotations, as well as getting the details about the associated SBO terms. These web services use established standards. Communications rely on SOAP (Simple Object Access Protocol) messages and the available queries are described in a WSDL (Web Services Description Language) file. Several libraries are provided in order to simplify the development of client software. BioModels.net Web Services make one step further for the researchers to simulate and understand the entirety of a biological system, by allowing them to retrieve biological models in their own tool, combine queries in workflows and efficiently analyse models.

Modeling the compensatory response of an invasive tree to specialist insect herbivory

USGS Publications Warehouse

Zhang, Bo; Liu, Xin; DeAngelis, Donald L.; Zhai, Lu; Rayamajhi, Min B.; Ju, Shu

2018-01-01

The severity of the effects of herbivory on plant fitness can be moderated by the ability of plants to compensate for biomass loss. Compensation is an important component of the ecological fitness in many plants, and has been shown to reduce the effects of pests on agricultural plant yields. It can also reduce the effectiveness of biocontrol through introduced herbivores in controlling weedy invasive plants. This study used a modeling approach to predict the effect of different levels of foliage herbivory by biological control agents introduced to control the invasive tree Melaleuca quinquennervia (melaleuca) in Florida. It is assumed in the model that melaleuca can optimally change its carbon and nitrogen allocation strategies in order to compensate for the effects of herbivory. The model includes reallocation of more resources to production and maintenance of photosynthetic tissues at the expense of roots. This compensation is shown to buffer the severity of the defoliation effect, but the model predicts a limit on the maximum herbivory that melaleuca can tolerate and survive. The model also shows that the level of available limiting nutrient (e.g., soil nitrogen) may play an important role in a melaleuca’s ability to compensate for herbivory. This study has management implications for the best ways to maximize the level of damage using biological control or other means of defoliation.

A detailed observation of the ejection and retraction of defense tissue acontia in sea anemone (Exaiptasia pallida).

PubMed

Lam, Julie; Cheng, Ya-Wen; Chen, Wan-Nan U; Li, Hsing-Hui; Chen, Chii-Shiarng; Peng, Shao-En

2017-01-01

Acontia, located in the gastrovascular cavity of anemone, are thread-like tissue containing numerous stinging cells which serve as a unique defense tissue against predators of the immobile acontiarian sea anemone. Although its morphology and biological functions, such as defense and digestion, have been studied, the defense behavior and the specific events of acontia ejection and retraction are unclear. The aim of this study is to observe and record the detailed process of acontia control in anemones. Observations reveal that the anemone, Exaiptasia pallida , possibly controls a network of body muscles and manipulates water pressure in the gastrovascular cavity to eject and retract acontia. Instead of resynthesizing acontia after each ejection, the retraction and reuse of acontia enables the anemone to respond quickly at any given time, thus increasing its overall survivability. Since the Exaiptasia anemone is an emerging model for coral biology, this study provides a foundation to further investigate the biophysics, neuroscience, and defense biology of this marine model organism.

A detailed observation of the ejection and retraction of defense tissue acontia in sea anemone (Exaiptasia pallida)

PubMed Central

Lam, Julie; Cheng, Ya-Wen; Chen, Wan-Nan U.; Li, Hsing-Hui; Chen, Chii-Shiarng

2017-01-01

Acontia, located in the gastrovascular cavity of anemone, are thread-like tissue containing numerous stinging cells which serve as a unique defense tissue against predators of the immobile acontiarian sea anemone. Although its morphology and biological functions, such as defense and digestion, have been studied, the defense behavior and the specific events of acontia ejection and retraction are unclear. The aim of this study is to observe and record the detailed process of acontia control in anemones. Observations reveal that the anemone, Exaiptasia pallida, possibly controls a network of body muscles and manipulates water pressure in the gastrovascular cavity to eject and retract acontia. Instead of resynthesizing acontia after each ejection, the retraction and reuse of acontia enables the anemone to respond quickly at any given time, thus increasing its overall survivability. Since the Exaiptasia anemone is an emerging model for coral biology, this study provides a foundation to further investigate the biophysics, neuroscience, and defense biology of this marine model organism. PMID:28243530

Augmenting the efficacy of fungal and mycotoxin control via chemosensitization

USDA-ARS?s Scientific Manuscript database

Antimycotic chemosensitization could serve as an effective method for control of fungal pathogens. In a chemo-biological platform to enhance antimycotic susceptibility of fungi or to overcome fungal tolerance to conventional antimycotic agents, the model yeast S. cerevisiae could be a functional too...

Quantification of 2D elemental distribution maps of intermediate-thick biological sections by low energy synchrotron μ-X-ray fluorescence spectrometry

NASA Astrophysics Data System (ADS)

Kump, P.; Vogel-Mikuš, K.

2018-05-01

Two fundamental-parameter (FP) based models for quantification of 2D elemental distribution maps of intermediate-thick biological samples by synchrotron low energy μ-X-ray fluorescence spectrometry (SR-μ-XRF) are presented and applied to the elemental analysis in experiments with monochromatic focused photon beam excitation at two low energy X-ray fluorescence beamlines—TwinMic, Elettra Sincrotrone Trieste, Italy, and ID21, ESRF, Grenoble, France. The models assume intermediate-thick biological samples composed of measured elements, the sources of the measurable spectral lines, and by the residual matrix, which affects the measured intensities through absorption. In the first model a fixed residual matrix of the sample is assumed, while in the second model the residual matrix is obtained by the iteration refinement of elemental concentrations and an adjusted residual matrix. The absorption of the incident focused beam in the biological sample at each scanned pixel position, determined from the output of a photodiode or a CCD camera, is applied as a control in the iteration procedure of quantification.

Computational Modeling in Concert with Laboratory Studies: Application to B Cell Differentiation

EPA Science Inventory

Remediation is expensive, so accurate prediction of dose-response is important to help control costs. Dose response is a function of biological mechanisms. Computational models of these mechanisms improve the efficiency of research and provide the capability for prediction.

Is there evidence for a set point that regulates human body weight?

PubMed

Müller, Manfred J; Bosy-Westphal, Anja; Heymsfield, Steven B

2010-08-09

There is evidence for the idea that there is biological (active) control of body weight at a given set point. Body weight is the product of genetic effects (DNA), epigenetic effects (heritable traits that do not involve changes in DNA), and the environment. Regulation of body weight is asymmetric, being more effective in response to weight loss than to weight gain. However, regulation may be lost or camouflaged by Western diets, suggesting that the failure of biological control is due mainly to external factors. In this situation, the body's 'set point' (i.e., a constant 'body-inherent' weight regulated by a proportional feedback control system) is replaced by various 'settling points' that are influenced by energy and macronutrient intake in order for the body to achieve a zero energy balance. In a world of abundance, a prudent lifestyle and thus cognitive control are preconditions of effective biological control and a stable body weight. This idea also impacts future genetic research on body weight regulation. Searching for the genetic background of excess weight gain in a world of abundance is misleading since the possible biological control is widely overshadowed by the effect of the environment. In regard to clinical practice, dietary approaches to both weight loss and weight gain have to be reconsidered. In underweight patients (e.g., patients with anorexia nervosa), weight gain is supported by biological mechanisms that may or may not be suppressed by hyperalimentation. To overcome weight loss-induced counter-regulation in the overweight, biological signals have to be taken into account. Computational modeling of weight changes based on metabolic flux and its regulation will provide future strategies for clinical nutrition.

Pattern dynamics of the reaction-diffusion immune system.

PubMed

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.

Biologically Inspired Micro-Flight Research

NASA Technical Reports Server (NTRS)

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.

WE-B-304-03: Biological Treatment Planning

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

Orton, C.

The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning bymore » the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations.« less

WE-B-304-02: Treatment Planning Evaluation and Optimization Should Be Biologically and Not Dose/volume Based

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

Deasy, J.

The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning bymore » the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations.« less

WE-B-304-01: Treatment Planning Evaluation and Optimization Should Be Dose/volume and Not Biologically Based

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

Mayo, C.

The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning bymore » the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations.« less

Stiffness control of a nylon twisted coiled actuator for use in mechatronic rehabilitation devices.

PubMed

Edmonds, Brandon P R; Trejos, Ana Luisa

2017-07-01

Mechatronic rehabilitation devices, especially wearables, have been researched extensively and proven to be promising additions to physical therapy, but most designs utilize traditional actuators providing unnatural, robot-like movements. Therefore, many researchers have focused on the development of actuators that mimic biological properties to provide patients with improved results, safety, and comfort. Recently, a twisted-coiled actuator (TCA) made from nylon thread has been found to possess many of these important properties when heated, such as variable stiffness, flexibility, and high power density. So far, TCAs have been characterized in controlled environments to define their fundamental properties under simple loading configurations. However, for an actuator like this to be implemented in a biomimetic design such as an exoskeleton, it needs to be characterized and controlled as a biological muscle. One major control law that natural muscles exhibit is stiffness control, allowing humans to passively avoid injury from external forces, or move the limbs in a controlled or high impact motion. This type of control is created by the antagonistic muscle arrangement. In this paper, an antagonistic apparatus was developed to model the TCAs from a biological standpoint, the stiffness was characterized with respect to the TCA temperature, and a fully functional stiffness and position controller was implemented with an incorporated TCA thermal model. The stiffness was found to have a linear relationship to the TCA temperatures (R 2 =0.95). The controller performed with a stiffness accuracy of 98.95% and a position accuracy of 92.7%. A final trial with varying continuous position input and varying stepped stiffness input exhibited position control with R 2 =0.9638.

Empirical modeling for intelligent, real-time manufacture control

NASA Technical Reports Server (NTRS)

Xu, Xiaoshu

1994-01-01

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.

High school and college biology: A multi-level model of the effects of high school biology courses on student academic performance in introductory college biology courses

NASA Astrophysics Data System (ADS)

Loehr, John Francis

The issue of student preparation for college study in science has been an ongoing concern for both college-bound students and educators of various levels. This study uses a national sample of college students enrolled in introductory biology courses to address the relationship between high school biology preparation and subsequent introductory college biology performance. Multi-Level Modeling was used to investigate the relationship between students' high school science and mathematics experiences and college biology performance. This analysis controls for student demographic and educational background factors along with factors associated with the college or university attended. The results indicated that high school course-taking and science instructional experiences have the largest impact on student achievement in the first introductory college biology course. In particular, enrollment in courses, such as high school Calculus and Advanced Placement (AP) Biology, along with biology course content that focuses on developing a deep understanding of the topics is found to be positively associated with student achievement in introductory college biology. On the other hand, experiencing high numbers of laboratory activities, demonstrations, and independent projects along with higher levels of laboratory freedom are associated with negative achievement. These findings are relevant to high school biology teachers, college students, their parents, and educators looking beyond the goal of high school graduation.

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

PubMed

Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

PubMed Central

Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

Invasive Species Distribution Modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?

Treesearch

Tomáš Václavík; Ross K. Meentemeyer

2009-01-01

Species distribution models (SDMs) based on statistical relationships between occurrence data and underlying environmental conditions are increasingly used to predict spatial patterns of biological invasions and prioritize locations for early detection and control of invasion outbreaks. However, invasive species distribution models (iSDMs) face special challenges...

Physico-chemical and biological characterization of anopheline mosquito larval habitats (Diptera: Culicidae): implications for malaria control.

PubMed

Mereta, Seid Tiku; Yewhalaw, Delenasaw; Boets, Pieter; Ahmed, Abdulhakim; Duchateau, Luc; Speybroeck, Niko; Vanwambeke, Sophie O; Legesse, Worku; De Meester, Luc; Goethals, Peter L M

2013-11-04

A fundamental understanding of the spatial distribution and ecology of mosquito larvae is essential for effective vector control intervention strategies. In this study, data-driven decision tree models, generalized linear models and ordination analysis were used to identify the most important biotic and abiotic factors that affect the occurrence and abundance of mosquito larvae in Southwest Ethiopia. In total, 220 samples were taken at 180 sampling locations during the years 2010 and 2012. Sampling sites were characterized based on physical, chemical and biological attributes. The predictive performance of decision tree models was evaluated based on correctly classified instances (CCI), Cohen's kappa statistic (κ) and the determination coefficient (R2). A conditional analysis was performed on the regression tree models to test the relation between key environmental and biological parameters and the abundance of mosquito larvae. The decision tree model developed for anopheline larvae showed a good model performance (CCI = 84 ± 2%, and κ = 0.66 ± 0.04), indicating that the genus has clear habitat requirements. Anopheline mosquito larvae showed a widespread distribution and especially occurred in small human-made aquatic habitats. Water temperature, canopy cover, emergent vegetation cover, and presence of predators and competitors were found to be the main variables determining the abundance and distribution of anopheline larvae. In contrast, anopheline mosquito larvae were found to be less prominently present in permanent larval habitats. This could be attributed to the high abundance and diversity of natural predators and competitors suppressing the mosquito population densities. The findings of this study suggest that targeting smaller human-made aquatic habitats could result in effective larval control of anopheline mosquitoes in the study area. Controlling the occurrence of mosquito larvae via drainage of permanent wetlands may not be a good management strategy as it negatively affects the occurrence and abundance of mosquito predators and competitors and promotes an increase in anopheline population densities.

Physico-chemical and biological characterization of anopheline mosquito larval habitats (Diptera: Culicidae): implications for malaria control

PubMed Central

2013-01-01

Background A fundamental understanding of the spatial distribution and ecology of mosquito larvae is essential for effective vector control intervention strategies. In this study, data-driven decision tree models, generalized linear models and ordination analysis were used to identify the most important biotic and abiotic factors that affect the occurrence and abundance of mosquito larvae in Southwest Ethiopia. Methods In total, 220 samples were taken at 180 sampling locations during the years 2010 and 2012. Sampling sites were characterized based on physical, chemical and biological attributes. The predictive performance of decision tree models was evaluated based on correctly classified instances (CCI), Cohen’s kappa statistic (κ) and the determination coefficient (R2). A conditional analysis was performed on the regression tree models to test the relation between key environmental and biological parameters and the abundance of mosquito larvae. Results The decision tree model developed for anopheline larvae showed a good model performance (CCI = 84 ± 2%, and κ = 0.66 ± 0.04), indicating that the genus has clear habitat requirements. Anopheline mosquito larvae showed a widespread distribution and especially occurred in small human-made aquatic habitats. Water temperature, canopy cover, emergent vegetation cover, and presence of predators and competitors were found to be the main variables determining the abundance and distribution of anopheline larvae. In contrast, anopheline mosquito larvae were found to be less prominently present in permanent larval habitats. This could be attributed to the high abundance and diversity of natural predators and competitors suppressing the mosquito population densities. Conclusions The findings of this study suggest that targeting smaller human-made aquatic habitats could result in effective larval control of anopheline mosquitoes in the study area. Controlling the occurrence of mosquito larvae via drainage of permanent wetlands may not be a good management strategy as it negatively affects the occurrence and abundance of mosquito predators and competitors and promotes an increase in anopheline population densities. PMID:24499518

Geometric effects in microfluidics on heterogeneous cell stress using an Eulerian-Lagrangian approach.

PubMed

Warren, K M; Mpagazehe, J N; LeDuc, P R; Higgs, C F

2016-02-07

The response of individual cells at the micro-scale in cell mechanics is important in understanding how they are affected by changing environments. To control cell stresses, microfluidics can be implemented since there is tremendous control over the geometry of the devices. Designing microfluidic devices to induce and manipulate stress levels on biological cells can be aided by computational modeling approaches. Such approaches serve as an efficient precursor to fabricating various microfluidic geometries that induce predictable levels of stress on biological cells, based on their mechanical properties. Here, a three-dimensional, multiphase computational fluid dynamics (CFD) modeling approach was implemented for soft biological materials. The computational model incorporates the physics of the particle dynamics, fluid dynamics and solid mechanics, which allows us to study how stresses affect the cells. By using an Eulerian-Lagrangian approach to treat the fluid domain as a continuum in the microfluidics, we are conducting studies of the cells' movement and the stresses applied to the cell. As a result of our studies, we were able to determine that a channel with periodically alternating columns of obstacles was capable of stressing cells at the highest rate, and that microfluidic systems can be engineered to impose heterogenous cell stresses through geometric configuring. We found that when using controlled geometries of the microfluidics channels with staggered obstructions, we could increase the maximum cell stress by nearly 200 times over cells flowing through microfluidic channels with no obstructions. Incorporating computational modeling in the design of microfluidic configurations for controllable cell stressing could help in the design of microfludic devices for stressing cells such as cell homogenizers.

Integrated Micro/nanoengineered Functional Biomaterials for Cell Mechanics and Mechanobiology: A Materials Perspective

PubMed Central

Shao, Yue

2014-01-01

The rapid development of micro/nanoengineered functional biomaterials in the last two decades has empowered materials scientists and bioengineers to precisely control different aspects of the in vitro cell microenvironment. Following a philosophy of reductionism, many studies using synthetic functional biomaterials have revealed instructive roles of individual extracellular biophysical and biochemical cues in regulating cellular behaviors. Development of integrated micro/nanoengineered functional biomaterials to study complex and emergent biological phenomena has also thrived rapidly in recent years, revealing adaptive and integrated cellular behaviors closely relevant to human physiological and pathological conditions. Working at the interface between materials science and engineering, biology, and medicine, we are now at the beginning of a great exploration using micro/nanoengineered functional biomaterials for both fundamental biology study and clinical and biomedical applications such as regenerative medicine and drug screening. In this review, we present an overview of state of the art micro/nanoengineered functional biomaterials that can control precisely individual aspects of cell-microenvironment interactions and highlight them as well-controlled platforms for mechanistic studies of mechano-sensitive and -responsive cellular behaviors and integrative biology research. We also discuss the recent exciting trend where micro/nanoengineered biomaterials are integrated into miniaturized biological and biomimetic systems for dynamic multiparametric microenvironmental control of emergent and integrated cellular behaviors. The impact of integrated micro/nanoengineered functional biomaterials for future in vitro studies of regenerative medicine, cell biology, as well as human development and disease models are discussed. PMID:24339188

Wave cybernetics: A simple model of wave-controlled nonlinear and nonlocal cooperative phenomena

NASA Astrophysics Data System (ADS)

Yasue, Kunio

1988-09-01

A simple theoretical description of nonlinear and nonlocal cooperative phenomena is presented in which the global control mechanism of the whole system is given by the tuned-wave propagation. It provides us with an interesting universal scheme of systematization in physical and biological systems called wave cybernetics, and may be understood as a model realizing Bohm's idea of implicate order in natural philosophy.

An Efficient Computational Model to Predict Protonation at the Amide Nitrogen and Reactivity along the C–N Rotational Pathway

PubMed Central

Szostak, Roman; Aubé, Jeffrey

2015-01-01

N-protonation of amides is critical in numerous biological processes, including amide bonds proteolysis and protein folding, as well as in organic synthesis as a method to activate amide bonds towards unconventional reactivity. A computational model enabling prediction of protonation at the amide bond nitrogen atom along the C–N rotational pathway is reported. Notably, this study provides a blueprint for the rational design and application of amides with a controlled degree of rotation in synthetic chemistry and biology. PMID:25766378

Anaerobic phosphate release from activated sludge with enhanced biological phosphorus removal. A possible mechanism of intracellular pH control

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

Bond, P.L.; Keller, J.; Blackall, L.L.

The biochemical mechanisms of the wastewater treatment process known as enhanced biological phosphorus removal (EBPR) are presently described in a metabolic model. The authors investigated details of the EBPR model to determine the nature of the anaerobic phosphate release and how this may be metabolically associated with polyhydroxyalkanoate (PHA) formation. Iodoacetate, an inhibitor of glycolysis, was found to inhibit the anaerobic formation of PHA and phosphate release, supporting the pathways proposed in the EBPR metabolic model. In the metabolic model, it is proposed that polyphosphate degradation provides energy for the microorganisms in anaerobic regions of these treatment systems. Other investigationsmore » have shown that anaerobic phosphate release depends on the extracellular pH. The authors observed that when the intracellular pH of EBPR sludge was raised, substantial anaerobic phosphate release was caused without volatile fatty acid (VFA) uptake. Acidification of the sludge inhibited anaerobic phosphate release even in the presence of VFA. from these observations, the authors postulate that an additional possible role of anaerobic polyphosphate degradation in EBPR is for intracellular pH control. Intracellular pH control may be a metabolic feature of EBPR, not previously considered, that could have some use in the control and optimization of EBPR.« less

A geometrically controlled rigidity transition in a model for confluent 3D tissues

NASA Astrophysics Data System (ADS)

Merkel, Matthias; Manning, M. Lisa

2018-02-01

The origin of rigidity in disordered materials is an outstanding open problem in statistical physics. Previously, a class of 2D cellular models has been shown to undergo a rigidity transition controlled by a mechanical parameter that specifies cell shapes. Here, we generalize this model to 3D and find a rigidity transition that is similarly controlled by the preferred surface area S 0: the model is solid-like below a dimensionless surface area of {s}0\\equiv {S}0/{\\bar{V}}2/3≈ 5.413 with \\bar{V} being the average cell volume, and fluid-like above this value. We demonstrate that, unlike jamming in soft spheres, residual stresses are necessary to create rigidity. These stresses occur precisely when cells are unable to obtain their desired geometry, and we conjecture that there is a well-defined minimal surface area possible for disordered cellular structures. We show that the behavior of this minimal surface induces a linear scaling of the shear modulus with the control parameter at the transition point, which is different from the scaling observed in particulate matter. The existence of such a minimal surface may be relevant for biological tissues and foams, and helps explain why cell shapes are a good structural order parameter for rigidity transitions in biological tissues.

A Neuro-Musculo-Skeletal Model for Insects With Data-driven Optimization.

PubMed

Guo, Shihui; Lin, Juncong; Wöhrl, Toni; Liao, Minghong

2018-02-01

Simulating the locomotion of insects is beneficial to many areas such as experimental biology, computer animation and robotics. This work proposes a neuro-musculo-skeletal model, which integrates the biological inspirations from real insects and reproduces the gait pattern on virtual insects. The neural system is a network of spiking neurons, whose spiking patterns are controlled by the input currents. The spiking pattern provides a uniform representation of sensory information, high-level commands and control strategy. The muscle models are designed following the characteristic Hill-type muscle with customized force-length and force-velocity relationships. The model parameters, including both the neural and muscular components, are optimized via an approach of evolutionary optimization, with the data captured from real insects. The results show that the simulated gait pattern, including joint trajectories, matches the experimental data collected from real ants walking in the free mode. The simulated character is capable of moving at different directions and traversing uneven terrains.

Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis.

PubMed

Kurhekar, Manish; Deshpande, Umesh

2016-01-01

Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.

Near-optimal experimental design for model selection in systems biology.

PubMed

Busetto, Alberto Giovanni; Hauser, Alain; Krummenacher, Gabriel; Sunnåker, Mikael; Dimopoulos, Sotiris; Ong, Cheng Soon; Stelling, Jörg; Buhmann, Joachim M

2013-10-15

Biological systems are understood through iterations of modeling and experimentation. Not all experiments, however, are equally valuable for predictive modeling. This study introduces an efficient method for experimental design aimed at selecting dynamical models from data. Motivated by biological applications, the method enables the design of crucial experiments: it determines a highly informative selection of measurement readouts and time points. We demonstrate formal guarantees of design efficiency on the basis of previous results. By reducing our task to the setting of graphical models, we prove that the method finds a near-optimal design selection with a polynomial number of evaluations. Moreover, the method exhibits the best polynomial-complexity constant approximation factor, unless P = NP. We measure the performance of the method in comparison with established alternatives, such as ensemble non-centrality, on example models of different complexity. Efficient design accelerates the loop between modeling and experimentation: it enables the inference of complex mechanisms, such as those controlling central metabolic operation. Toolbox 'NearOED' available with source code under GPL on the Machine Learning Open Source Software Web site (mloss.org).

Set points, settling points and some alternative models: theoretical options to understand how genes and environments combine to regulate body adiposity

PubMed Central

Speakman, John R.; Levitsky, David A.; Allison, David B.; Bray, Molly S.; de Castro, John M.; Clegg, Deborah J.; Clapham, John C.; Dulloo, Abdul G.; Gruer, Laurence; Haw, Sally; Hebebrand, Johannes; Hetherington, Marion M.; Higgs, Susanne; Jebb, Susan A.; Loos, Ruth J. F.; Luckman, Simon; Luke, Amy; Mohammed-Ali, Vidya; O’Rahilly, Stephen; Pereira, Mark; Perusse, Louis; Robinson, Tom N.; Rolls, Barbara; Symonds, Michael E.; Westerterp-Plantenga, Margriet S.

2011-01-01

The close correspondence between energy intake and expenditure over prolonged time periods, coupled with an apparent protection of the level of body adiposity in the face of perturbations of energy balance, has led to the idea that body fatness is regulated via mechanisms that control intake and energy expenditure. Two models have dominated the discussion of how this regulation might take place. The set point model is rooted in physiology, genetics and molecular biology, and suggests that there is an active feedback mechanism linking adipose tissue (stored energy) to intake and expenditure via a set point, presumably encoded in the brain. This model is consistent with many of the biological aspects of energy balance, but struggles to explain the many significant environmental and social influences on obesity, food intake and physical activity. More importantly, the set point model does not effectively explain the ‘obesity epidemic’ – the large increase in body weight and adiposity of a large proportion of individuals in many countries since the 1980s. An alternative model, called the settling point model, is based on the idea that there is passive feedback between the size of the body stores and aspects of expenditure. This model accommodates many of the social and environmental characteristics of energy balance, but struggles to explain some of the biological and genetic aspects. The shortcomings of these two models reflect their failure to address the gene-by-environment interactions that dominate the regulation of body weight. We discuss two additional models – the general intake model and the dual intervention point model – that address this issue and might offer better ways to understand how body fatness is controlled. PMID:22065844

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

NASA Astrophysics Data System (ADS)

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.

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

NONE

The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning bymore » the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations.« less

Biology and air-sea gas exchange controls on the distribution of carbon isotope ratios (δ13C) in the ocean

NASA Astrophysics Data System (ADS)

Schmittner, A.; Gruber, N.; Mix, A. C.; Key, R. M.; Tagliabue, A.; Westberry, T. K.

2013-05-01

Analysis of observations and sensitivity experiments with a new three-dimensional global model of stable carbon isotope cycling elucidate the processes that control the distribution of δ13C in the contemporary and preindustrial ocean. Biological fractionation dominates the distribution of δ13CDIC of dissolved inorganic carbon (DIC) due to the sinking of isotopically light δ13C organic matter from the surface into the interior ocean. This process leads to low δ13CDIC values at dephs and in high latitude surface waters and high values in the upper ocean at low latitudes with maxima in the subtropics. Air-sea gas exchange provides an important secondary influence due to two effects. First, it acts to reduce the spatial gradients created by biology. Second, the associated temperature dependent fractionation tends to increase (decrease) δ13CDIC values of colder (warmer) water, which generates gradients that oppose those arising from biology. Our model results suggest that both effects are similarly important in influencing surface and interior δ13CDIC distributions. However, air-sea gas exchange is slow, so biological effect dominate spatial δ13CDIC gradients both in the interior and at the surface, in constrast to conclusions from some previous studies. Analysis of a new synthesis of δ13CDIC measurements from years 1990 to 2005 is used to quantify preformed (δ13Cpre) and remineralized (δ13Crem) contributions as well as the effects of biology (Δδ13Cbio) and air-sea gas exchange (δ13C*). The model reproduces major features of the observed large-scale distribution of δ13CDIC, δ13Cpre, δ13Crem, δ13C*, and Δδ13Cbio. Residual misfits are documented and analyzed. Simulated surface and subsurface δ13CDIC are influenced by details of the ecosystem model formulation. For example, inclusion of a simple parameterization of iron limitation of phytoplankton growth rates and temperature-dependent zooplankton grazing rates improves the agreement with δ13CDIC observations and satellite estimates of phytoplankton growth rates and biomass, suggesting that δ13C can also be a useful test of ecosystem models.

Physical models have gender-specific effects on student understanding of protein structure-function relationships.

PubMed

Forbes-Lorman, Robin M; Harris, Michelle A; Chang, Wesley S; Dent, Erik W; Nordheim, Erik V; Franzen, Margaret A

2016-07-08

Understanding how basic structural units influence function is identified as a foundational/core concept for undergraduate biological and biochemical literacy. It is essential for students to understand this concept at all size scales, but it is often more difficult for students to understand structure-function relationships at the molecular level, which they cannot as effectively visualize. Students need to develop accurate, 3-dimensional mental models of biomolecules to understand how biomolecular structure affects cellular functions at the molecular level, yet most traditional curricular tools such as textbooks include only 2-dimensional representations. We used a controlled, backward design approach to investigate how hand-held physical molecular model use affected students' ability to logically predict structure-function relationships. Brief (one class period) physical model use increased quiz score for females, whereas there was no significant increase in score for males using physical models. Females also self-reported higher learning gains in their understanding of context-specific protein function. Gender differences in spatial visualization may explain the gender-specific benefits of physical model use observed. © 2016 The Authors Biochemistry and Molecular Biology Education published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology, 44(4):326-335, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

Low Fidelity Imitation of Atypical Biological Kinematics in Autism Spectrum Disorders Is Modulated by Self-Generated Selective Attention

ERIC Educational Resources Information Center

Hayes, Spencer J.; Andrew, Matthew; Elliott, Digby; Gowen, Emma; Bennett, Simon J.

2016-01-01

We examined whether adults with autism had difficulty imitating atypical biological kinematics. To reduce the impact that higher-order processes have on imitation we used a non-human agent model to control social attention, and removed end-state target goals in half of the trials to minimise goal-directed attention. Findings showed that only…

The Effects of the SUN Project on Teacher Knowledge and Self-Efficacy regarding Biological Energy Transfer Are Significant and Long-Lasting: Results of a Randomized Controlled Trial

ERIC Educational Resources Information Center

Batiza, Ann Finney; Gruhl, Mary; Zhang, Bo; Harrington, Tom; Roberts, Marisa; LaFlamme, Donna; Haasch, Mary Anne; Knopp, Jonathan; Vogt, Gina; Goodsell, David; Hagedorn, Eric; Marcey, David; Hoelzer, Mark; Nelson, Dave

2013-01-01

Biological energy flow has been notoriously difficult to teach. Our approach to this topic relies on abiotic and biotic examples of the energy released by moving electrons in thermodynamically spontaneous reactions. A series of analogical model-building experiences was supported with common language and representations including manipulatives.…

A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics.

PubMed

Somvanshi, Pramod Rajaram; Venkatesh, K V

2014-03-01

Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.

Biological role of bacterial inclusion bodies: a model for amyloid aggregation.

PubMed

García-Fruitós, Elena; Sabate, Raimon; de Groot, Natalia S; Villaverde, Antonio; Ventura, Salvador

2011-07-01

Inclusion bodies are insoluble protein aggregates usually found in recombinant bacteria when they are forced to produce heterologous protein species. These particles are formed by polypeptides that cross-interact through sterospecific contacts and that are steadily deposited in either the cell's cytoplasm or the periplasm. An important fraction of eukaryotic proteins form inclusion bodies in bacteria, which has posed major problems in the development of the biotechnology industry. Over the last decade, the fine dissection of the quality control system in bacteria and the recognition of the amyloid-like architecture of inclusion bodies have provided dramatic insights on the dynamic biology of these aggregates. We discuss here the relevant aspects, in the interface between cell physiology and structural biology, which make inclusion bodies unique models for the study of protein aggregation, amyloid formation and prion biology in a physiologically relevant background. © 2011 The Authors Journal compilation © 2011 FEBS.

"SABER": A new software tool for radiotherapy treatment plan evaluation.

PubMed

Zhao, Bo; Joiner, Michael C; Orton, Colin G; Burmeister, Jay

2010-11-01

Both spatial and biological information are necessary in order to perform true optimization of a treatment plan and for predicting clinical outcome. The goal of this work is to develop an enhanced treatment plan evaluation tool which incorporates biological parameters and retains spatial dose information. A software system is developed which provides biological plan evaluation with a novel combination of features. It incorporates hyper-radiosensitivity using the induced-repair model and applies the new concept of dose convolution filter (DCF) to simulate dose wash-out effects due to cell migration, bystander effect, and/or tissue motion during treatment. Further, the concept of spatial DVH (sDVH) is introduced to evaluate and potentially optimize the spatial dose distribution in the target volume. Finally, generalized equivalent uniform dose is derived from both the physical dose distribution (gEUD) and the distribution of equivalent dose in 2 Gy fractions (gEUD2) and the software provides three separate models for calculation of tumor control probability (TCP), normal tissue complication probability (NTCP), and probability of uncomplicated tumor control (P+). TCP, NTCP, and P+ are provided as a function of prescribed dose and multivariable TCP, NTCP, and P+ plots are provided to illustrate the dependence on individual parameters used to calculate these quantities. Ten plans from two clinical treatment sites are selected to test the three calculation models provided by this software. By retaining both spatial and biological information about the dose distribution, the software is able to distinguish features of radiotherapy treatment plans not discernible using commercial systems. Plans that have similar DVHs may have different spatial and biological characteristics and the application of novel tools such as sDVH and DCF within the software may substantially change the apparent plan quality or predicted plan metrics such as TCP and NTCP. For the cases examined, both the calculation method and the application of DCF can change the ranking order of competing plans. The voxel-by-voxel TCP model makes it feasible to incorporate spatial variations of clonogen densities (n), radiosensitivities (SF2), and fractionation sensitivities (alpha/beta) as those data become available. The new software incorporates both spatial and biological information into the treatment planning process. The application of multiple methods for the incorporation of biological and spatial information has demonstrated that the order of application of biological models can change the order of plan ranking. Thus, the results of plan evaluation and optimization are dependent not only on the models used but also on the order in which they are applied. This software can help the planner choose more biologically optimal treatment plans and potentially predict treatment outcome more accurately.

Structuring and extracting knowledge for the support of hypothesis generation in molecular biology

PubMed Central

Roos, Marco; Marshall, M Scott; Gibson, Andrew P; Schuemie, Martijn; Meij, Edgar; Katrenko, Sophia; van Hage, Willem Robert; Krommydas, Konstantinos; Adriaans, Pieter W

2009-01-01

Background Hypothesis generation in molecular and cellular biology is an empirical process in which knowledge derived from prior experiments is distilled into a comprehensible model. The requirement of automated support is exemplified by the difficulty of considering all relevant facts that are contained in the millions of documents available from PubMed. Semantic Web provides tools for sharing prior knowledge, while information retrieval and information extraction techniques enable its extraction from literature. Their combination makes prior knowledge available for computational analysis and inference. While some tools provide complete solutions that limit the control over the modeling and extraction processes, we seek a methodology that supports control by the experimenter over these critical processes. Results We describe progress towards automated support for the generation of biomolecular hypotheses. Semantic Web technologies are used to structure and store knowledge, while a workflow extracts knowledge from text. We designed minimal proto-ontologies in OWL for capturing different aspects of a text mining experiment: the biological hypothesis, text and documents, text mining, and workflow provenance. The models fit a methodology that allows focus on the requirements of a single experiment while supporting reuse and posterior analysis of extracted knowledge from multiple experiments. Our workflow is composed of services from the 'Adaptive Information Disclosure Application' (AIDA) toolkit as well as a few others. The output is a semantic model with putative biological relations, with each relation linked to the corresponding evidence. Conclusion We demonstrated a 'do-it-yourself' approach for structuring and extracting knowledge in the context of experimental research on biomolecular mechanisms. The methodology can be used to bootstrap the construction of semantically rich biological models using the results of knowledge extraction processes. Models specific to particular experiments can be constructed that, in turn, link with other semantic models, creating a web of knowledge that spans experiments. Mapping mechanisms can link to other knowledge resources such as OBO ontologies or SKOS vocabularies. AIDA Web Services can be used to design personalized knowledge extraction procedures. In our example experiment, we found three proteins (NF-Kappa B, p21, and Bax) potentially playing a role in the interplay between nutrients and epigenetic gene regulation. PMID:19796406

Revised radiobiological modelling of the contribution of synchronous chemotherapy to the rate of grades 3-4 mucositis in head and neck cancer.

PubMed

Meade, Sara; McConkey, Chris; Sanghera, Paul; Mehanna, Hisham; Hartley, Andrew

2013-12-01

Biological effective dose (BED) calculations modelled on reduced accelerated repopulation when synchronous chemotherapy is delivered significantly correlate with observed differences in local control in randomised trials of platinum-based chemoradiation. The purpose of this study was to examine whether a similar relationship existed in the context of grades 3-4 mucositis. Biological effective dose from radiotherapy and synchronous chemotherapy was calculated using three different models: AB using the additional BED attributable to chemotherapy and standard repopulation parameters; zero repopulation (ZRP) using zero correction for repopulation; and variable t(p) (Vt(p)) using a variable doubling time for mucosal stem cell repopulation. The correlation between the percentage change in biological effective dose between trial arms, and the observed percentage change in the rate of grades 3-4 mucositis was examined by using the Pearson product-moment correlation. With the AB model, there were no significant correlations with observed differences in rates of grades 3-4 mucositis. With either the ZRP or Vt(p) models, significant correlations were observed. A value of 5 days for the doubling time during repopulation (T(p)) was associated with the most significant correlation (P = 0.002). Models where the dose lost due to accelerated repopulation is reduced imply a therapeutic loss from the use of synchronous chemotherapy when only local control and the rate of acute grades 3-4 mucositis are considered. © 2013 The Royal Australian and New Zealand College of Radiologists.

Untangling the biological contributions to soil stability in semiarid shrublands

USGS Publications Warehouse

Chaudhary, V. Bala; Bowker, Matthew A.; O'Dell, Thomas E.; Grace, James B.; Redman, Andrea E.; Rillig, Matthias C.; Johnson, Nancy C.

2009-01-01

Communities of plants, biological soil crusts (BSCs), and arbuscular mycorrhizal (AM) fungi are known to influence soil stability individually, but their relative contributions, interactions, and combined effects are not well understood, particularly in arid and semiarid ecosystems. In a landscape-scale field study we quantified plant, BSC, and AM fungal communities at 216 locations along a gradient of soil stability levels in southern Utah, USA. We used multivariate modeling to examine the relative influences of plants, BSCs, and AM fungi on surface and subsurface stability in a semiarid shrubland landscape. Models were found to be congruent with the data and explained 35% of the variation in surface stability and 54% of the variation in subsurface stability. The results support several tentative conclusions. While BSCs, plants, and AM fungi all contribute to surface stability, only plants and AM fungi contribute to subsurface stability. In both surface and subsurface models, the strongest contributions to soil stability are made by biological components of the system. Biological soil crust cover was found to have the strongest direct effect on surface soil stability (0.60; controlling for other factors). Surprisingly, AM fungi appeared to influence surface soil stability (0.37), even though they are not generally considered to exist in the top few millimeters of the soil. In the subsurface model, plant cover appeared to have the strongest direct influence on soil stability (0.42); in both models, results indicate that plant cover influences soil stability both directly (controlling for other factors) and indirectly through influences on other organisms. Soil organic matter was not found to have a direct contribution to surface or subsurface stability in this system. The relative influence of AM fungi on soil stability in these semiarid shrublands was similar to that reported for a mesic tallgrass prairie. Estimates of effects that BSCs, plants, and AM fungi have on soil stability in these models are used to suggest the relative amounts of resources that erosion control practitioners should devote to promoting these communities. This study highlights the need for system approaches in combating erosion, soil degradation, and arid-land desertification.

Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models.

PubMed

Erguler, Kamil; Stumpf, Michael P H

2011-05-01

The size and complexity of cellular systems make building predictive models an extremely difficult task. In principle dynamical time-course data can be used to elucidate the structure of the underlying molecular mechanisms, but a central and recurring problem is that many and very different models can be fitted to experimental data, especially when the latter are limited and subject to noise. Even given a model, estimating its parameters remains challenging in real-world systems. Here we present a comprehensive analysis of 180 systems biology models, which allows us to classify the parameters with respect to their contribution to the overall dynamical behaviour of the different systems. Our results reveal candidate elements of control in biochemical pathways that differentially contribute to dynamics. We introduce sensitivity profiles that concisely characterize parameter sensitivity and demonstrate how this can be connected to variability in data. Systematically linking data and model sloppiness allows us to extract features of dynamical systems that determine how well parameters can be estimated from time-course measurements, and associates the extent of data required for parameter inference with the model structure, and also with the global dynamical state of the system. The comprehensive analysis of so many systems biology models reaffirms the inability to estimate precisely most model or kinetic parameters as a generic feature of dynamical systems, and provides safe guidelines for performing better inferences and model predictions in the context of reverse engineering of mathematical models for biological systems.

Applying differential dynamic logic to reconfigurable biological networks.

PubMed

Figueiredo, Daniel; Martins, Manuel A; Chaves, Madalena

2017-09-01

Qualitative and quantitative modeling frameworks are widely used for analysis of biological regulatory networks, the former giving a preliminary overview of the system's global dynamics and the latter providing more detailed solutions. Another approach is to model biological regulatory networks as hybrid systems, i.e., systems which can display both continuous and discrete dynamic behaviors. Actually, the development of synthetic biology has shown that this is a suitable way to think about biological systems, which can often be constructed as networks with discrete controllers, and present hybrid behaviors. In this paper we discuss this approach as a special case of the reconfigurability paradigm, well studied in Computer Science (CS). In CS there are well developed computational tools to reason about hybrid systems. We argue that it is worth applying such tools in a biological context. One interesting tool is differential dynamic logic (dL), which has recently been developed by Platzer and applied to many case-studies. In this paper we discuss some simple examples of biological regulatory networks to illustrate how dL can be used as an alternative, or also as a complement to methods already used. Copyright © 2017 Elsevier Inc. All rights reserved.

Simulations in Medicine and Biology: Insights and perspectives

NASA Astrophysics Data System (ADS)

Spyrou, George M.

2015-01-01

Modern medicine and biology have been transformed into quantitative sciences of high complexity, with challenging objectives. The aims of medicine are related to early diagnosis, effective therapy, accurate intervention, real time monitoring, procedures/systems/instruments optimization, error reduction, and knowledge extraction. Concurrently, following the explosive production of biological data concerning DNA, RNA, and protein biomolecules, a plethora of questions has been raised in relation to their structure and function, the interactions between them, their relationships and dependencies, their regulation and expression, their location, and their thermodynamic characteristics. Furthermore, the interplay between medicine and biology gives rise to fields like molecular medicine and systems biology which are further interconnected with physics, mathematics, informatics, and engineering. Modelling and simulation is a powerful tool in the fields of Medicine and Biology. Simulating the phenomena hidden inside a diagnostic or therapeutic medical procedure, we are able to obtain control on the whole system and perform multilevel optimization. Furthermore, modelling and simulation gives insights in the various scales of biological representation, facilitating the understanding of the huge amounts of derived data and the related mechanisms behind them. Several examples, as well as the insights and the perspectives of simulations in biomedicine will be presented.

Cancer Control Research Training for Native Researchers: A Model for Development of Additional Native Researcher Training Programs

ERIC Educational Resources Information Center

Becker, Thomas M.; Dunn, Esther; Tom-Orme, Lillian; Joe, Jennie

2005-01-01

Several social and biological scientists who have Native status are engaged in productive research careers, but the encouragement that has been offered to Native students to formulate career goals devoted to cancer etiology or cancer control in Native peoples has had limited success. Hence, the Native Researchers' Cancer Control Training Program…

Numerical Estimation of the Curvature of Biological Surfaces

NASA Technical Reports Server (NTRS)

Todd, P. H.

1985-01-01

Many biological systems may profitably be studied as surface phenomena. A model consisting of isotropic growth of a curved surface from a flat sheet is assumed. With such a model, the Gaussian curvature of the final surface determines whether growth rate of the surface is subharmonic or superharmonic. These properties correspond to notions of convexity and concavity, and thus to local excess growth and local deficiency of growth. In biological models where the major factors controlling surface growth are intrinsic to the surface, researchers thus gained from geometrical study information on the differential growth undergone by the surface. These ideas were applied to an analysis of the folding of the cerebral cortex, a geometrically rather complex surface growth. A numerical surface curvature technique based on an approximation to the Dupin indicatrix of the surface was developed. A metric for comparing curvature estimates is introduced, and considerable numerical testing indicated the reliability of this technique.

The Effects of the SUN Project on Teacher Knowledge and Self-Efficacy Regarding Biological Energy Transfer Are Significant and Long-Lasting: Results of a Randomized Controlled Trial

PubMed Central

Batiza, Ann Finney; Gruhl, Mary; Zhang, Bo; Harrington, Tom; Roberts, Marisa; LaFlamme, Donna; Haasch, Mary Anne; Knopp, Jonathan; Vogt, Gina; Goodsell, David; Hagedorn, Eric; Marcey, David; Hoelzer, Mark; Nelson, Dave

2013-01-01

Biological energy flow has been notoriously difficult to teach. Our approach to this topic relies on abiotic and biotic examples of the energy released by moving electrons in thermodynamically spontaneous reactions. A series of analogical model-building experiences was supported with common language and representations including manipulatives. These materials were designed to help learners understand why electrons move in a hydrogen explosion and hydrogen fuel cell, so they could ultimately understand the rationale for energy transfer in the mitochondrion and the chloroplast. High school biology teachers attended a 2-wk Students Understanding eNergy (SUN) workshop during a randomized controlled trial. These treatment group teachers then took hydrogen fuel cells, manipulatives, and other materials into their regular biology classrooms. In this paper, we report significant gains in teacher knowledge and self-efficacy regarding biological energy transfer in the treatment group versus randomized controls. Significant effects on treatment group teacher knowledge and self-efficacy were found not only post–SUN workshop but even 1 yr later. Teacher knowledge was measured with both a multiple-choice exam and a drawing with a written explanation. Teacher confidence in their ability to teach biological energy transfer was measured by a modified form of the Science Teaching Efficacy Belief Instrument, In-Service A. Professional development implications regarding this topic are discussed. PMID:23737635

The effects of the SUN project on teacher knowledge and self-efficacy regarding biological energy transfer are significant and long-lasting: results of a randomized controlled trial.

PubMed

Batiza, Ann Finney; Gruhl, Mary; Zhang, Bo; Harrington, Tom; Roberts, Marisa; LaFlamme, Donna; Haasch, Mary Anne; Knopp, Jonathan; Vogt, Gina; Goodsell, David; Hagedorn, Eric; Marcey, David; Hoelzer, Mark; Nelson, Dave

2013-06-01

Biological energy flow has been notoriously difficult to teach. Our approach to this topic relies on abiotic and biotic examples of the energy released by moving electrons in thermodynamically spontaneous reactions. A series of analogical model-building experiences was supported with common language and representations including manipulatives. These materials were designed to help learners understand why electrons move in a hydrogen explosion and hydrogen fuel cell, so they could ultimately understand the rationale for energy transfer in the mitochondrion and the chloroplast. High school biology teachers attended a 2-wk Students Understanding eNergy (SUN) workshop during a randomized controlled trial. These treatment group teachers then took hydrogen fuel cells, manipulatives, and other materials into their regular biology classrooms. In this paper, we report significant gains in teacher knowledge and self-efficacy regarding biological energy transfer in the treatment group versus randomized controls. Significant effects on treatment group teacher knowledge and self-efficacy were found not only post-SUN workshop but even 1 yr later. Teacher knowledge was measured with both a multiple-choice exam and a drawing with a written explanation. Teacher confidence in their ability to teach biological energy transfer was measured by a modified form of the Science Teaching Efficacy Belief Instrument, In-Service A. Professional development implications regarding this topic are discussed.

Biologically inspired design of feedback control systems implemented using DNA strand displacement reactions.

PubMed

Foo, Mathias; Sawlekar, Rucha; Kulkarni, Vishwesh V; Bates, Declan G

2016-08-01

The use of abstract chemical reaction networks (CRNs) as a modelling and design framework for the implementation of computing and control circuits using enzyme-free, entropy driven DNA strand displacement (DSD) reactions is starting to garner widespread attention in the area of synthetic biology. Previous work in this area has demonstrated the theoretical plausibility of using this approach to design biomolecular feedback control systems based on classical proportional-integral (PI) controllers, which may be constructed from CRNs implementing gain, summation and integrator operators. Here, we propose an alternative design approach that utilises the abstract chemical reactions involved in cellular signalling cycles to implement a biomolecular controller - termed a signalling-cycle (SC) controller. We compare the performance of the PI and SC controllers in closed-loop with a nonlinear second-order chemical process. Our results show that the SC controller outperforms the PI controller in terms of both performance and robustness, and also requires fewer abstract chemical reactions to implement, highlighting its potential usefulness in the construction of biomolecular control circuits.

Conservation law for self-paced movements.

PubMed

Huh, Dongsung; Sejnowski, Terrence J

2016-08-02

Optimal control models of biological movements introduce external task factors to specify the pace of movements. Here, we present the dual to the principle of optimality based on a conserved quantity, called "drive," that represents the influence of internal motivation level on movement pace. Optimal control and drive conservation provide equivalent descriptions for the regularities observed within individual movements. For regularities across movements, drive conservation predicts a previously unidentified scaling law between the overall size and speed of various self-paced hand movements in the absence of any external tasks, which we confirmed with psychophysical experiments. Drive can be interpreted as a high-level control variable that sets the overall pace of movements and may be represented in the brain as the tonic levels of neuromodulators that control the level of internal motivation, thus providing insights into how internal states affect biological motor control.

The biological carbon pump in the ocean: Reviewing model representations and its feedbacks on climate perturbations.

NASA Astrophysics Data System (ADS)

Hülse, Dominik; Arndt, Sandra; Ridgwell, Andy; Wilson, Jamie

2016-04-01

The ocean-sediment system, as the biggest carbon reservoir in the Earth's carbon cycle, plays a crucial role in regulating atmospheric carbon dioxide concentrations and climate. Therefore, it is essential to constrain the importance of marine carbon cycle feedbacks on global warming and ocean acidification. Arguably, the most important single component of the ocean's carbon cycle is the so-called "biological carbon pump". It transports carbon that is fixed in the light-flooded surface layer of the ocean to the deep ocean and the surface sediment, where it is degraded/dissolved or finally buried in the deep sediments. Over the past decade, progress has been made in understanding different factors that control the efficiency of the biological carbon pump and their feedbacks on the global carbon cycle and climate (i.e. ballasting = ocean acidification feedback; temperature dependant organic matter degradation = global warming feedback; organic matter sulphurisation = anoxia/euxinia feedback). Nevertheless, many uncertainties concerning the interplay of these processes and/or their relative significance remain. In addition, current Earth System Models tend to employ empirical and static parameterisations of the biological pump. As these parametric representations are derived from a limited set of present-day observations, their ability to represent carbon cycle feedbacks under changing climate conditions is limited. The aim of my research is to combine past carbon cycling information with a spatially resolved global biogeochemical model to constrain the functioning of the biological pump and to base its mathematical representation on a more mechanistic approach. Here, I will discuss important aspects that control the efficiency of the ocean's biological carbon pump, review how these processes of first order importance are mathematically represented in existing Earth system Models of Intermediate Complexity (EMIC) and distinguish different approaches to approximate biogeochemical processes in the sediments. The performance of the respective mathematical representations in constraining the importance of carbon pump feedbacks on marine biogeochemical dynamics is then compared and evaluated under different extreme climate scenarios (e.g. OAE2, Eocene) using the Earth system model 'GENIE' and proxy records. The compiled mathematical descriptions and the model results underline the lack of a complete and mechanistic framework to represent the short-term carbon cycle in most EMICs which seriously limits the ability of these models to constrain the response of the ocean's carbon cycle to past and in particular future climate change. In conclusion, this presentation will critically evaluate the approaches currently used in marine biogeochemical modelling and outline key research directions concerning model development in the future.

Force modeling for incision surgery into tissue with haptic application

NASA Astrophysics Data System (ADS)

Kim, Pyunghwa; Kim, Soomin; Choi, Seung-Hyun; Oh, Jong-Seok; Choi, Seung-Bok

2015-04-01

This paper presents a novel force modeling for an incision surgery into tissue and its haptic application for a surgeon. During the robot-assisted incision surgery, it is highly urgent to develop the haptic system for realizing sense of touch in the surgical area because surgeons cannot sense sensations. To achieve this goal, the force modeling related to reaction force of biological tissue is proposed in the perspective on energy. The force model describes reaction force focused on the elastic feature of tissue during the incision surgery. Furthermore, the force is realized using calculated information from the model by haptic device using magnetorheological fluid (MRF). The performance of realized force that is controlled by PID controller with open loop control is evaluated.

On the analysis of competitive displacement in dengue disease transmission

NASA Astrophysics Data System (ADS)

Wijaya, Karunia P.; Nuraini, Nuning; Soewono, Edy; Handayani, Dewi

2014-03-01

We study a host-vector model involving the interplay of competitive displacement mechanism in a specific DENV serotype, both in human blood and mosquito blood. Using phylogenetic analysis, world virologists investigate the severe manifestations of dengue fever caused by the displacements within weakly virulent pathogens (native strains) by more virulent pathogens (invasive strains) in one serotype. We construct SIR model for human and SI model for mosquito to explore the key determinants of those displacements. Analysis of nonnegativity and boundedness of the solution as well as the basic reproduction number (R0) are taken into account for verifying the model into biological meaningfulness. To generate predictions of the outcomes of control strategies, we derive an optimal control model which involves two control apparatus: fluid infusion (for human) and fumigation (for vector). Numerical results show the dynamics of host-vector in an observation period, both under control and without control.

Cost modeling of biocontrol strains Pseudomonas chlororaphis and P. flurorescens for competitive exclusion of Salmonella enterica on tomatoes

USDA-ARS?s Scientific Manuscript database

Biological control of foodborne pathogens may complement postharvest intervention measures to enhance food safety of minimally processed produce. The purpose of this research was to develop cost model estimates for application of competitive exclusion process (CEM) using Pseudomonas chlororaphis and...

On The Development of Biophysical Models for Space Radiation Risk Assessment

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Dicello, J. F.

1999-01-01

Experimental techniques in molecular biology are being applied to study biological risks from space radiation. The use of molecular assays presents a challenge to biophysical models which in the past have relied on descriptions of energy deposition and phenomenological treatments of repair. We describe a biochemical kinetics model of cell cycle control and DNA damage response proteins in order to model cellular responses to radiation exposures. Using models of cyclin-cdk, pRB, E2F's, p53, and GI inhibitors we show that simulations of cell cycle populations and GI arrest can be described by our biochemical approach. We consider radiation damaged DNA as a substrate for signal transduction processes and consider a dose and dose-rate reduction effectiveness factor (DDREF) for protein expression.

A Research Agenda for Helminth Diseases of Humans: Modelling for Control and Elimination

PubMed Central

Basáñez, María-Gloria; McCarthy, James S.; French, Michael D.; Yang, Guo-Jing; Walker, Martin; Gambhir, Manoj; Prichard, Roger K.; Churcher, Thomas S.

2012-01-01

Mathematical modelling of helminth infections has the potential to inform policy and guide research for the control and elimination of human helminthiases. However, this potential, unlike in other parasitic and infectious diseases, has yet to be realised. To place contemporary efforts in a historical context, a summary of the development of mathematical models for helminthiases is presented. These efforts are discussed according to the role that models can play in furthering our understanding of parasite population biology and transmission dynamics, and the effect on such dynamics of control interventions, as well as in enabling estimation of directly unobservable parameters, exploration of transmission breakpoints, and investigation of evolutionary outcomes of control. The Disease Reference Group on Helminth Infections (DRG4), established in 2009 by the Special Programme for Research and Training in Tropical Diseases (TDR), was given the mandate to review helminthiases research and identify research priorities and gaps. A research and development agenda for helminthiasis modelling is proposed based on identified gaps that need to be addressed for models to become useful decision tools that can support research and control operations effectively. This agenda includes the use of models to estimate the impact of large-scale interventions on infection incidence; the design of sampling protocols for the monitoring and evaluation of integrated control programmes; the modelling of co-infections; the investigation of the dynamical relationship between infection and morbidity indicators; the improvement of analytical methods for the quantification of anthelmintic efficacy and resistance; the determination of programme endpoints; the linking of dynamical helminth models with helminth geostatistical mapping; and the investigation of the impact of climate change on human helminthiases. It is concluded that modelling should be embedded in helminth research, and in the planning, evaluation, and surveillance of interventions from the outset. Modellers should be essential members of interdisciplinary teams, propitiating a continuous dialogue with end users and stakeholders to reflect public health needs in the terrain, discuss the scope and limitations of models, and update biological assumptions and model outputs regularly. It is highlighted that to reach these goals, a collaborative framework must be developed for the collation, annotation, and sharing of databases from large-scale anthelmintic control programmes, and that helminth modellers should join efforts to tackle key questions in helminth epidemiology and control through the sharing of such databases, and by using diverse, yet complementary, modelling approaches. PMID:22545162

Engineering and control of biological systems: A new way to tackle complex diseases.

PubMed

Menolascina, Filippo; Siciliano, Velia; di Bernardo, Diego

2012-07-16

The ongoing merge between engineering and biology has contributed to the emerging field of synthetic biology. The defining features of this new discipline are abstraction and standardisation of biological parts, decoupling between parts to prevent undesired cross-talking, and the application of quantitative modelling of synthetic genetic circuits in order to guide their design. Most of the efforts in the field of synthetic biology in the last decade have been devoted to the design and development of functional gene circuits in prokaryotes and unicellular eukaryotes. Researchers have used synthetic biology not only to engineer new functions in the cell, but also to build simpler models of endogenous gene regulatory networks to gain knowledge of the "rules" governing their wiring diagram. However, the need for innovative approaches to study and modify complex signalling and regulatory networks in mammalian cells and multicellular organisms has prompted advances of synthetic biology also in these species, thus contributing to develop innovative ways to tackle human diseases. In this work, we will review the latest progress in synthetic biology and the most significant developments achieved so far, both in unicellular and multicellular organisms, with emphasis on human health. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Model-Data Fusion to Test Hypothesized Drivers of Lake Carbon Cycling Reveals Importance of Physical Controls

NASA Astrophysics Data System (ADS)

Hararuk, Oleksandra; Zwart, Jacob A.; Jones, Stuart E.; Prairie, Yves; Solomon, Christopher T.

2018-03-01

Formal integration of models and data to test hypotheses about the processes controlling carbon dynamics in lakes is rare, despite the importance of lakes in the carbon cycle. We built a suite of models (n = 102) representing different hypotheses about lake carbon processing, fit these models to data from a north-temperate lake using data assimilation, and identified which processes were essential for adequately describing the observations. The hypotheses that we tested concerned organic matter lability and its variability through time, temperature dependence of biological decay, photooxidation, microbial dynamics, and vertical transport of water via hypolimnetic entrainment and inflowing density currents. The data included epilimnetic and hypolimnetic CO2 and dissolved organic carbon, hydrologic fluxes, carbon loads, gross primary production, temperature, and light conditions at high frequency for one calibration and one validation year. The best models explained 76-81% and 64-67% of the variability in observed epilimnetic CO2 and dissolved organic carbon content in the validation data. Accurately describing C dynamics required accounting for hypolimnetic entrainment and inflowing density currents, in addition to accounting for biological transformations. In contrast, neither photooxidation nor variable organic matter lability improved model performance. The temperature dependence of biological decay (Q10) was estimated at 1.45, significantly lower than the commonly assumed Q10 of 2. By confronting multiple models of lake C dynamics with observations, we identified processes essential for describing C dynamics in a temperate lake at daily to annual scales, while also providing a methodological roadmap for using data assimilation to further improve understanding of lake C cycling.

Integrated micro/nanoengineered functional biomaterials for cell mechanics and mechanobiology: a materials perspective.

PubMed

Shao, Yue; Fu, Jianping

2014-03-12

The rapid development of micro/nanoengineered functional biomaterials in the last two decades has empowered materials scientists and bioengineers to precisely control different aspects of the in vitro cell microenvironment. Following a philosophy of reductionism, many studies using synthetic functional biomaterials have revealed instructive roles of individual extracellular biophysical and biochemical cues in regulating cellular behaviors. Development of integrated micro/nanoengineered functional biomaterials to study complex and emergent biological phenomena has also thrived rapidly in recent years, revealing adaptive and integrated cellular behaviors closely relevant to human physiological and pathological conditions. Working at the interface between materials science and engineering, biology, and medicine, we are now at the beginning of a great exploration using micro/nanoengineered functional biomaterials for both fundamental biology study and clinical and biomedical applications such as regenerative medicine and drug screening. In this review, an overview of state of the art micro/nanoengineered functional biomaterials that can control precisely individual aspects of cell-microenvironment interactions is presented and they are highlighted them as well-controlled platforms for mechanistic studies of mechano-sensitive and -responsive cellular behaviors and integrative biology research. The recent exciting trend where micro/nanoengineered biomaterials are integrated into miniaturized biological and biomimetic systems for dynamic multiparametric microenvironmental control of emergent and integrated cellular behaviors is also discussed. The impact of integrated micro/nanoengineered functional biomaterials for future in vitro studies of regenerative medicine, cell biology, as well as human development and disease models are discussed. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entropic-elasticity-controlled dissociation and energetic-elasticity-controlled rupture induce catch-to-slip bonds in cell-adhesion molecules.

PubMed

Wei, YuJie

2008-03-01

We develop a physical model to describe the kinetic behavior in cell-adhesion molecules. Unbinding of noncovalent biological bonds is assumed to occur by both bond dissociation and bond rupture. Such a decomposition of debonding processes is a space decomposition of the debonding events. Dissociation under thermal fluctuation is nondirectional in a three-dimensional space, and its energy barrier to escape is not influenced by a tensile force, but the microstates that could lead to dissociation are changed by the tensile force; rupture happens along the tensile force direction. An applied force effectively lowers the energy barrier to escape along the loading direction. The lifetime of the biological bond, due to the two concurrent off rates, may grow with increasing tensile force to a moderate amount and then decrease with further increasing load. We hypothesize that a catch-to-slip bond transition is a generic feature in biological bonds. The model also predicts that catch bonds in a more flexible molecular structure have longer lifetimes and need less force to be fully activated.

Biological pacemaker created by minimally invasive somatic reprogramming in pigs with complete heart block

PubMed Central

Hu, Yu-Feng; Dawkins, James Frederick; Cho, Hee Cheol; Marbán, Eduardo; Cingolani, Eugenio

2016-01-01

Somatic reprogramming by reexpression of the embryonic transcription factor T-box 18 (TBX18) converts cardiomyocytes into pacemaker cells. We hypothesized that this could be a viable therapeutic avenue for pacemaker-dependent patients afflicted with device-related complications, and therefore tested whether adenoviral TBX18 gene transfer could create biological pacemaker activity in vivo in a large-animal model of complete heart block. Biological pacemaker activity, originating from the intramyocardial injection site, was evident in TBX18-transduced animals starting at day 2 and persisted for the duration of the study (14 days) with minimal backup electronic pacemaker use. Relative to controls transduced with a reporter gene, TBX18-transduced animals exhibited enhanced autonomic responses and physiologically superior chronotropic support of physical activity. Induced sinoatrial node cells could be identified by their distinctive morphology at the site of injection in TBX18-transduced animals, but not in controls. No local or systemic safety concerns arose. Thus, minimally invasive TBX18 gene transfer creates physiologically relevant pacemaker activity in complete heart block, providing evidence for therapeutic somatic reprogramming in a clinically relevant disease model. PMID:25031269

The Effect of the Use of Smart Board in the Biology Class on the Academic Achievement of Student

ERIC Educational Resources Information Center

Onder, Recep; Aydin, Halil

2016-01-01

The objective of this study is to reveal the effect of the use of smart board in the biology class at the tenth grade of the secondary education on the academic achievements of students. The study used the quasi-experimental model with pre-test and post-test control groups and semi-structured interviews were made with the students. The study group…

Chemical combination effects predict connectivity in biological systems

PubMed Central

Lehár, Joseph; Zimmermann, Grant R; Krueger, Andrew S; Molnar, Raymond A; Ledell, Jebediah T; Heilbut, Adrian M; Short, Glenn F; Giusti, Leanne C; Nolan, Garry P; Magid, Omar A; Lee, Margaret S; Borisy, Alexis A; Stockwell, Brent R; Keith, Curtis T

2007-01-01

Efforts to construct therapeutically useful models of biological systems require large and diverse sets of data on functional connections between their components. Here we show that cellular responses to combinations of chemicals reveal how their biological targets are connected. Simulations of pathways with pairs of inhibitors at varying doses predict distinct response surface shapes that are reproduced in a yeast experiment, with further support from a larger screen using human tumour cells. The response morphology yields detailed connectivity constraints between nearby targets, and synergy profiles across many combinations show relatedness between targets in the whole network. Constraints from chemical combinations complement genetic studies, because they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. After extending this initial study to cover a wider range of combination effects and pathway topologies, chemical combinations may be used to refine network models or to identify novel targets. This response surface methodology may even apply to non-biological systems where responses to targeted perturbations can be measured. PMID:17332758

Biology and air-sea gas exchange controls on the distribution of carbon isotope ratios (δ13C) in the ocean

NASA Astrophysics Data System (ADS)

Schmittner, A.; Gruber, N.; Mix, A. C.; Key, R. M.; Tagliabue, A.; Westberry, T. K.

2013-09-01

Analysis of observations and sensitivity experiments with a new three-dimensional global model of stable carbon isotope cycling elucidate processes that control the distribution of δ13C of dissolved inorganic carbon (DIC) in the contemporary and preindustrial ocean. Biological fractionation and the sinking of isotopically light δ13C organic matter from the surface into the interior ocean leads to low δ13CDIC values at depths and in high latitude surface waters and high values in the upper ocean at low latitudes with maxima in the subtropics. Air-sea gas exchange has two effects. First, it acts to reduce the spatial gradients created by biology. Second, the associated temperature-dependent fractionation tends to increase (decrease) δ13CDIC values of colder (warmer) water, which generates gradients that oppose those arising from biology. Our model results suggest that both effects are similarly important in influencing surface and interior δ13CDIC distributions. However, since air-sea gas exchange is slow in the modern ocean, the biological effect dominates spatial δ13CDIC gradients both in the interior and at the surface, in contrast to conclusions from some previous studies. Calcium carbonate cycling, pH dependency of fractionation during air-sea gas exchange, and kinetic fractionation have minor effects on δ13CDIC. Accumulation of isotopically light carbon from anthropogenic fossil fuel burning has decreased the spatial variability of surface and deep δ13CDIC since the industrial revolution in our model simulations. Analysis of a new synthesis of δ13CDIC measurements from years 1990 to 2005 is used to quantify preformed and remineralized contributions as well as the effects of biology and air-sea gas exchange. The model reproduces major features of the observed large-scale distribution of δ13CDIC as well as the individual contributions and effects. Residual misfits are documented and analyzed. Simulated surface and subsurface δ13CDIC are influenced by details of the ecosystem model formulation. For example, inclusion of a simple parameterization of iron limitation of phytoplankton growth rates and temperature-dependent zooplankton grazing rates improves the agreement with δ13CDIC observations and satellite estimates of phytoplankton growth rates and biomass, suggesting that δ13C can also be a useful test of ecosystem models.

Mirror me: Imitative responses in adults with autism.

PubMed

Schunke, Odette; Schöttle, Daniel; Vettorazzi, Eik; Brandt, Valerie; Kahl, Ursula; Bäumer, Tobias; Ganos, Christos; David, Nicole; Peiker, Ina; Engel, Andreas K; Brass, Marcel; Münchau, Alexander

2016-02-01

Dysfunctions of the human mirror neuron system have been postulated to underlie some deficits in autism spectrum disorders including poor imitative performance and impaired social skills. Using three reaction time experiments addressing mirror neuron system functions under simple and complex conditions, we examined 20 adult autism spectrum disorder participants and 20 healthy controls matched for age, gender and education. Participants performed simple finger-lifting movements in response to (1) biological finger and non-biological dot movement stimuli, (2) acoustic stimuli and (3) combined visual-acoustic stimuli with different contextual (compatible/incompatible) and temporal (simultaneous/asynchronous) relation. Mixed model analyses revealed slower reaction times in autism spectrum disorder. Both groups responded faster to biological compared to non-biological stimuli (Experiment 1) implying intact processing advantage for biological stimuli in autism spectrum disorder. In Experiment 3, both groups had similar 'interference effects' when stimuli were presented simultaneously. However, autism spectrum disorder participants had abnormally slow responses particularly when incompatible stimuli were presented consecutively. Our results suggest imitative control deficits rather than global imitative system impairments. © The Author(s) 2015.

Agent-Based Models and Optimal Control in Biology: A Discrete Approach

DTIC Science & Technology

2012-01-01

different parts of the human body to cure diseases such as hypertension, cancer, or heart disease. And we need to control microbes for the efficient...antelope herd interacts with an aggregated prey agent such as cheetahs or lions, the size of each may expand or contract accordingly). Of course, such

Proceedings 3rd NASA/IEEE Workshop on Formal Approaches to Agent-Based Systems (FAABS-III)

NASA Technical Reports Server (NTRS)

Hinchey, Michael (Editor); Rash, James (Editor); Truszkowski, Walt (Editor); Rouff, Christopher (Editor)

2004-01-01

These preceedings contain 18 papers and 4 poster presentation, covering topics such as: multi-agent systems, agent-based control, formalism, norms, as well as physical and biological models of agent-based systems. Some applications presented in the proceedings include systems analysis, software engineering, computer networks and robot control.

Shallow water processes govern system-wide phytoplankton bloom dynamics: A modeling study

USGS Publications Warehouse

Lucas, L.V.; Koseff, Jeffrey R.; Monismith, Stephen G.; Thompson, J.K.

2009-01-01

A pseudo-two-dimensional numerical model of estuarine phytoplankton growth and consumption, vertical turbulent mixing, and idealized cross-estuary transport was developed and applied to South San Francisco Bay. This estuary has two bathymetrically distinct habitat types (deep channel, shallow shoal) and associated differences in local net rates of phytoplankton growth and consumption, as well as differences in the water column's tendency to stratify. Because many physical and biological time scales relevant to algal population dynamics decrease with decreasing depth, process rates can be especially fast in the shallow water. We used the model to explore the potential significance of hydrodynamic connectivity between a channel and shoal and whether lateral transport can allow physical or biological processes (e.g. stratification, benthic grazing, light attenuation) in one sub-region to control phytoplankton biomass and bloom development in the adjacent sub-region. Model results for South San Francisco Bay suggest that lateral transport from a productive shoal can result in phytoplankton biomass accumulation in an adjacent deep, unproductive channel. The model further suggests that turbidity and benthic grazing in the shoal can control the occurrence of a bloom system-wide; whereas, turbidity, benthic grazing, and vertical density stratification in the channel are likely to only control local bloom occurrence or modify system-wide bloom magnitude. Measurements from a related field program are generally consistent with model-derived conclusions. ?? 2008 Elsevier B.V.

Add Control: plant virtualization for control solutions in WWTP.

PubMed

Maiza, M; Bengoechea, A; Grau, P; De Keyser, W; Nopens, I; Brockmann, D; Steyer, J P; Claeys, F; Urchegui, G; Fernández, O; Ayesa, E

2013-01-01

This paper summarizes part of the research work carried out in the Add Control project, which proposes an extension of the wastewater treatment plant (WWTP) models and modelling architectures used in traditional WWTP simulation tools, addressing, in addition to the classical mass transformations (transport, physico-chemical phenomena, biological reactions), all the instrumentation, actuation and automation & control components (sensors, actuators, controllers), considering their real behaviour (signal delays, noise, failures and power consumption of actuators). Its ultimate objective is to allow a rapid transition from the simulation of the control strategy to its implementation at full-scale plants. Thus, this paper presents the application of the Add Control simulation platform for the design and implementation of new control strategies at the WWTP of Mekolalde.

Multichannel microformulators for massively parallel machine learning and automated design of biological experiments

NASA Astrophysics Data System (ADS)

Wikswo, John; Kolli, Aditya; Shankaran, Harish; Wagoner, Matthew; Mettetal, Jerome; Reiserer, Ronald; Gerken, Gregory; Britt, Clayton; Schaffer, David

Genetic, proteomic, and metabolic networks describing biological signaling can have 102 to 103 nodes. Transcriptomics and mass spectrometry can quantify 104 different dynamical experimental variables recorded from in vitro experiments with a time resolution approaching 1 s. It is difficult to infer metabolic and signaling models from such massive data sets, and it is unlikely that causality can be determined simply from observed temporal correlations. There is a need to design and apply specific system perturbations, which will be difficult to perform manually with 10 to 102 externally controlled variables. Machine learning and optimal experimental design can select an experiment that best discriminates between multiple conflicting models, but a remaining problem is to control in real time multiple variables in the form of concentrations of growth factors, toxins, nutrients and other signaling molecules. With time-division multiplexing, a microfluidic MicroFormulator (μF) can create in real time complex mixtures of reagents in volumes suitable for biological experiments. Initial 96-channel μF implementations control the exposure profile of cells in a 96-well plate to different temporal profiles of drugs; future experiments will include challenge compounds. Funded in part by AstraZeneca, NIH/NCATS HHSN271201600009C and UH3TR000491, and VIIBRE.

An autonomous molecular computer for logical control of gene expression.

PubMed

Benenson, Yaakov; Gil, Binyamin; Ben-Dor, Uri; Adar, Rivka; Shapiro, Ehud

2004-05-27

Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems. Recently, simple molecular-scale autonomous programmable computers were demonstrated allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for 'logical' control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug.

The export and fate of organic matter in the ocean: New constraints from combining satellite and oceanographic tracer observations

NASA Astrophysics Data System (ADS)

DeVries, Tim; Weber, Thomas

2017-03-01

The ocean's biological pump transfers carbon from the surface euphotic zone into the deep ocean, reducing the atmospheric CO2 concentration. Despite its climatic importance, there are large uncertainties in basic metrics of the biological pump. Previous estimates of the strength of the biological pump, as measured by the amount of organic carbon exported from the euphotic zone, range from about 4 to 12 Pg C yr-1. The fate of exported carbon, in terms of how efficiently it is transferred into the deep ocean, is even more uncertain. Here we present a new model of the biological pump that assimilates satellite and oceanographic tracer observations to constrain rates and patterns of organic matter production, export, and remineralization in the ocean. The data-assimilated model predicts a global particulate organic carbon (POC) flux out of the euphotic zone of ˜9 Pg C yr-1. The particle export ratio (the ratio of POC export to net primary production) is highest at high latitudes and lowest at low latitudes, but low-latitude export is greater than predicted by previous models, in better agreement with observed patterns of long-term carbon export. Particle transfer efficiency (Teff) through the mesopelagic zone is controlled by temperature and oxygen, with highest Teff for high-latitude regions and oxygen minimum zones. In contrast, Teff in the deep ocean (below 1000 m) is controlled by particle sinking speed, with highest deep ocean Teff below the subtropical gyres. These results emphasize the utility of both remote sensing and oceanographic tracer observations for constraining the operation of the biological pump.

Microengineering in cardiovascular research: new developments and translational applications.

PubMed

Chan, Juliana M; Wong, Keith H K; Richards, Arthur Mark; Drum, Chester L

2015-04-01

Microfluidic, cellular co-cultures that approximate macro-scale biology are important tools for refining the in vitro study of organ-level function and disease. In recent years, advances in technical fabrication and biological integration have provided new insights into biological phenomena, improved diagnostic measurements, and made major steps towards de novo tissue creation. Here we review applications of these technologies specific to the cardiovascular field, emphasizing three general categories of use: reductionist vascular models, tissue-engineered vascular models, and point-of-care diagnostics. With continued progress in the ability to purposefully control microscale environments, the detailed study of both primary and cultured cells may find new relevance in the general cardiovascular research community. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Cardiology.

Experimental design and modeling of a microscale differential thermal calorimeter for the purposes of cryopreservation

NASA Astrophysics Data System (ADS)

Armes, James L.

In order to develop successful cryopreservation protocols for various biological materials, it is necessary to determine the thermodynamic properties of nanoliter- scale biological samples: ranging from heat capacity to heat of fusion. Differential thermal analysis is a calorimetric technique which is efficacious at determining these thermodynamic properties and will help lend insight into the formation of intracellular ice which depends heavily on the rate at which the sample is cooled. If too much intracellular ice is formed during the cooling process, the biological material can be destroyed. To investigate the effects of a range of cooling and warming rates on a cell, a control system and data acquisition software has been developed for use with a custom microfabricated differential thermal analyzer (muDTA). Utilizing either an a-priori prediction of the muDTA's thermal response or an integrated software-based PID control system, the program developed allows for precise control over the cooling and warming rate of the muDTA. In order to enhance the accuracy of the a-priori predicted current profile, a 2D numeric model was developed of the muDTA. This model also has allowed for geometric optimization to be performed on the next generation prototype of the muDTA. The muDTA has been shown to accurately measure the freezing point and heat of fusion of deionized water samples, with sample volumes on the order of nanoliters. The heat capacity of dimethyl sulfoxide (DMSO) has also been experimentally determined.

Bio-soliton model that predicts non-thermal electromagnetic frequency bands, that either stabilize or destabilize living cells.

PubMed

Geesink, J H; Meijer, D K F

2017-01-01

Solitons, as self-reinforcing solitary waves, interact with complex biological phenomena such as cellular self-organization. A soliton model is able to describe a spectrum of electromagnetism modalities that can be applied to understand the physical principles of biological effects in living cells, as caused by endogenous and exogenous electromagnetic fields and is compatible with quantum coherence. A bio-soliton model is proposed, that enables to predict which eigen-frequencies of non-thermal electromagnetic waves are life-sustaining and which are, in contrast, detrimental for living cells. The particular effects are exerted by a range of electromagnetic wave eigen-frequencies of one-tenth of a Hertz till Peta Hertz that show a pattern of 12 bands, and can be positioned on an acoustic reference frequency scale. The model was substantiated by a meta-analysis of 240 published articles of biological electromagnetic experiments, in which a spectrum of non-thermal electromagnetic waves were exposed to living cells and intact organisms. These data support the concept of coherent quantized electromagnetic states in living organisms and the theories of Fröhlich, Davydov and Pang. It is envisioned that a rational control of shape by soliton-waves and related to a morphogenetic field and parametric resonance provides positional information and cues to regulate organism-wide systems properties like anatomy, control of reproduction and repair.

Mammalian synthetic biology for studying the cell

PubMed Central

Mathur, Melina; Xiang, Joy S.

2017-01-01

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. PMID:27932576

Biomimetic approaches to control soluble concentration gradients in biomaterials.

PubMed

Nguyen, Eric H; Schwartz, Michael P; Murphy, William L

2011-04-08

Soluble concentration gradients play a critical role in controlling tissue formation during embryonic development. The importance of soluble signaling in biology has motivated engineers to design systems that allow precise and quantitative manipulation of gradient formation in vitro. Engineering techniques have increasingly moved to the third dimension in order to provide more physiologically relevant models to study the biological role of gradient formation and to guide strategies for controlling new tissue formation for therapeutic applications. This review provides an overview of efforts to design biomimetic strategies for soluble gradient formation, with a focus on microfluidic techniques and biomaterials approaches for moving gradient generation to the third dimension. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Nanomaterial interactions with biomembranes: Bridging the gap between soft matter models and biological context.

PubMed

Werner, Marco; Auth, Thorsten; Beales, Paul A; Fleury, Jean Baptiste; Höök, Fredrik; Kress, Holger; Van Lehn, Reid C; Müller, Marcus; Petrov, Eugene P; Sarkisov, Lev; Sommer, Jens-Uwe; Baulin, Vladimir A

2018-04-03

Synthetic polymers, nanoparticles, and carbon-based materials have great potential in applications including drug delivery, gene transfection, in vitro and in vivo imaging, and the alteration of biological function. Nature and humans use different design strategies to create nanomaterials: biological objects have emerged from billions of years of evolution and from adaptation to their environment resulting in high levels of structural complexity; in contrast, synthetic nanomaterials result from minimalistic but controlled design options limited by the authors' current understanding of the biological world. This conceptual mismatch makes it challenging to create synthetic nanomaterials that possess desired functions in biological media. In many biologically relevant applications, nanomaterials must enter the cell interior to perform their functions. An essential transport barrier is the cell-protecting plasma membrane and hence the understanding of its interaction with nanomaterials is a fundamental task in biotechnology. The authors present open questions in the field of nanomaterial interactions with biological membranes, including: how physical mechanisms and molecular forces acting at the nanoscale restrict or inspire design options; which levels of complexity to include next in computational and experimental models to describe how nanomaterials cross barriers via passive or active processes; and how the biological media and protein corona interfere with nanomaterial functionality. In this Perspective, the authors address these questions with the aim of offering guidelines for the development of next-generation nanomaterials that function in biological media.

Improving Conceptual Understanding and Representation Skills Through Excel-Based Modeling

NASA Astrophysics Data System (ADS)

Malone, Kathy L.; Schunn, Christian D.; Schuchardt, Anita M.

2018-02-01

The National Research Council framework for science education and the Next Generation Science Standards have developed a need for additional research and development of curricula that is both technologically model-based and includes engineering practices. This is especially the case for biology education. This paper describes a quasi-experimental design study to test the effectiveness of a model-based curriculum focused on the concepts of natural selection and population ecology that makes use of Excel modeling tools (Modeling Instruction in Biology with Excel, MBI-E). The curriculum revolves around the bio-engineering practice of controlling an invasive species. The study takes place in the Midwest within ten high schools teaching a regular-level introductory biology class. A post-test was designed that targeted a number of common misconceptions in both concept areas as well as representational usage. The results of a post-test demonstrate that the MBI-E students significantly outperformed the traditional classes in both natural selection and population ecology concepts, thus overcoming a number of misconceptions. In addition, implementing students made use of more multiple representations as well as demonstrating greater fascination for science.

Multiscale systems biology of trauma-induced coagulopathy.

PubMed

Tsiklidis, Evan; Sims, Carrie; Sinno, Talid; Diamond, Scott L

2018-07-01

Trauma with hypovolemic shock is an extreme pathological state that challenges the body to maintain blood pressure and oxygenation in the face of hemorrhagic blood loss. In conjunction with surgical actions and transfusion therapy, survival requires the patient's blood to maintain hemostasis to stop bleeding. The physics of the problem are multiscale: (a) the systemic circulation sets the global blood pressure in response to blood loss and resuscitation therapy, (b) local tissue perfusion is altered by localized vasoregulatory mechanisms and bleeding, and (c) altered blood and vessel biology resulting from the trauma as well as local hemodynamics control the assembly of clotting components at the site of injury. Building upon ongoing modeling efforts to simulate arterial or venous thrombosis in a diseased vasculature, computer simulation of trauma-induced coagulopathy is an emerging approach to understand patient risk and predict response. Despite uncertainties in quantifying the patient's dynamic injury burden, multiscale systems biology may help link blood biochemistry at the molecular level to multiorgan responses in the bleeding patient. As an important goal of systems modeling, establishing early metrics of a patient's high-dimensional trajectory may help guide transfusion therapy or warn of subsequent later stage bleeding or thrombotic risks. This article is categorized under: Analytical and Computational Methods > Computational Methods Biological Mechanisms > Regulatory Biology Models of Systems Properties and Processes > Mechanistic Models. © 2018 Wiley Periodicals, Inc.

Green Jobs: Definition and Method of Appraisal of Chemical and Biological Risks

PubMed Central

Cheneval, Erwan; Busque, Marc-Antoine; Ostiguy, Claude; Lavoie, Jacques; Bourbonnais, Robert; Labrèche, France; Bakhiyi, Bouchra; Zayed, Joseph

2016-01-01

In the wake of sustainable development, green jobs are developing rapidly, changing the work environment. However a green job is not automatically a safe job. The aim of the study was to define green jobs, and to establish a preliminary risk assessment of chemical substances and biological agents for workers in Quebec. An operational definition was developed, along with criteria and sustainable development principles to discriminate green jobs from regular jobs. The potential toxicity or hazard associated with their chemical and biological exposures was assessed, and the workers’ exposure appraised using an expert assessment method. A control banding approach was then used to assess risks for workers in selected green jobs. A double entry model allowed us to set priorities in terms of chemical or biological risk. Among jobs that present the highest risk potential, several are related to waste management. The developed method is flexible and could be adapted to better appraise the risks that workers are facing or to propose control measures. PMID:26718400

Engineering modular and orthogonal genetic logic gates for robust digital-like synthetic biology.

PubMed

Wang, Baojun; Kitney, Richard I; Joly, Nicolas; Buck, Martin

2011-10-18

Modular and orthogonal genetic logic gates are essential for building robust biologically based digital devices to customize cell signalling in synthetic biology. Here we constructed an orthogonal AND gate in Escherichia coli using a novel hetero-regulation module from Pseudomonas syringae. The device comprises two co-activating genes hrpR and hrpS controlled by separate promoter inputs, and a σ(54)-dependent hrpL promoter driving the output. The hrpL promoter is activated only when both genes are expressed, generating digital-like AND integration behaviour. The AND gate is demonstrated to be modular by applying new regulated promoters to the inputs, and connecting the output to a NOT gate module to produce a combinatorial NAND gate. The circuits were assembled using a parts-based engineering approach of quantitative characterization, modelling, followed by construction and testing. The results show that new genetic logic devices can be engineered predictably from novel native orthogonal biological control elements using quantitatively in-context characterized parts. © 2011 Macmillan Publishers Limited. All rights reserved.

Structure and Nanomechanics of Model Membranes by Atomic Force Microscopy and Spectroscopy: Insights into the Role of Cholesterol and Sphingolipids.

PubMed

Gumí-Audenis, Berta; Costa, Luca; Carlá, Francesco; Comin, Fabio; Sanz, Fausto; Giannotti, Marina I

2016-12-19

Biological membranes mediate several biological processes that are directly associated with their physical properties but sometimes difficult to evaluate. Supported lipid bilayers (SLBs) are model systems widely used to characterize the structure of biological membranes. Cholesterol (Chol) plays an essential role in the modulation of membrane physical properties. It directly influences the order and mechanical stability of the lipid bilayers, and it is known to laterally segregate in rafts in the outer leaflet of the membrane together with sphingolipids (SLs). Atomic force microscope (AFM) is a powerful tool as it is capable to sense and apply forces with high accuracy, with distance and force resolution at the nanoscale, and in a controlled environment. AFM-based force spectroscopy (AFM-FS) has become a crucial technique to study the nanomechanical stability of SLBs by controlling the liquid media and the temperature variations. In this contribution, we review recent AFM and AFM-FS studies on the effect of Chol on the morphology and mechanical properties of model SLBs, including complex bilayers containing SLs. We also introduce a promising combination of AFM and X-ray (XR) techniques that allows for in situ characterization of dynamic processes, providing structural, morphological, and nanomechanical information.

Structure and Nanomechanics of Model Membranes by Atomic Force Microscopy and Spectroscopy: Insights into the Role of Cholesterol and Sphingolipids

PubMed Central

Gumí-Audenis, Berta; Costa, Luca; Carlá, Francesco; Comin, Fabio; Sanz, Fausto; Giannotti, Marina I.

2016-01-01

Biological membranes mediate several biological processes that are directly associated with their physical properties but sometimes difficult to evaluate. Supported lipid bilayers (SLBs) are model systems widely used to characterize the structure of biological membranes. Cholesterol (Chol) plays an essential role in the modulation of membrane physical properties. It directly influences the order and mechanical stability of the lipid bilayers, and it is known to laterally segregate in rafts in the outer leaflet of the membrane together with sphingolipids (SLs). Atomic force microscope (AFM) is a powerful tool as it is capable to sense and apply forces with high accuracy, with distance and force resolution at the nanoscale, and in a controlled environment. AFM-based force spectroscopy (AFM-FS) has become a crucial technique to study the nanomechanical stability of SLBs by controlling the liquid media and the temperature variations. In this contribution, we review recent AFM and AFM-FS studies on the effect of Chol on the morphology and mechanical properties of model SLBs, including complex bilayers containing SLs. We also introduce a promising combination of AFM and X-ray (XR) techniques that allows for in situ characterization of dynamic processes, providing structural, morphological, and nanomechanical information. PMID:27999368

Modeling and simulation of an aquatic habitat for bioregenerative life support research

NASA Astrophysics Data System (ADS)

Drayer, Gregorio E.; Howard, Ayanna M.

2014-01-01

Long duration human spaceflight poses challenges for spacecraft autonomy and the regeneration of life support consumables, such as oxygen and water. Bioregenerative life support systems (BLSS), which make use of biological processes to transform biological byproducts back into consumables, have the ability to recycle organic byproducts and are the preferred option for food production. A limitation in BLSS research is in the non-availability of small-scale experimental capacities that may help to better understand the challenges in system closure, integration, and control. Ground-based aquatic habitats are an option for small-scale research relevant to bioregenerative life support systems (BLSS), given that they can operate as self-contained systems enclosing a habitat composed of various species in a single volume of water. The purpose of this paper is to present the modeling and simulation of a reconfigurable aquatic habitat for experiments in regenerative life support automation; it supports the use of aquatic habitats as a small-scale approach to experiments relevant to larger-scale regenerative life support systems. It presents ground-based aquatic habitats as an option for small-scale BLSS research focusing on the process of respiration, and elaborates on the description of biological processes by introducing models of ecophysiological phenomena for consumers and producers: higher plants of the species Bacopa monnieri produce O2 for snails of the genus Pomacea; the snails consume O2 and generate CO2, which is used by the plants in combination with radiant energy to generate O2 through the process of photosynthesis. Feedback controllers are designed to regulate the concentration of dissolved oxygen in the water. This paper expands the description of biological processes by introducing models of ecophysiological phenomena of the organisms involved. The model of the plants includes a description of the rate of CO2 assimilation as a function of irradiance. Simulations and validation runs with hardware show how these phenomena may act as disturbances to the control mechanisms that maintain safe concentration levels of dissolved oxygen in the habitat.

Environmental fate and biodegradability of benzene derivatives as studied in a model aquatic ecosystem.

PubMed Central

Lu, P Y; Metcalf, R L

1975-01-01

A model aquatic ecosystem is devised for studying relatively volatile organic compounds and simulating direct discharge of chemical wastes into aquatic ecosystems. Six simple benzene derivatives (aniline, anisole, benzoic acid, chlorobenzene, nitrobenzene, and phthalic anhydride) and other important specialty chemicals: hexachlorobenzene, pentachlorophenol, 2,6-diethylaniline, and 3,5,6-trichloro-2-pyridinol were also chosen for study of environmental behavior and fate in the model aquatic ecosystem. Quantitative relationships of the intrinsic molecular properties of the environmental micropollutants with biological responses are established, e.g., water solubility, partition coefficient, pi constant, sigma constant, ecological magnification, biodegradability index, and comparative detoxication mechanisms, respectively. Water solubility, pi constant, and sigma constant are the most significant factors and control the biological responses of the food chain members. Water solubility and pi constant control the degree of bioaccumulation, and sigma constant limits the metabolism of the xenobiotics via microsomal detoxication enzymes. These highly significant correlations should be useful for predicting environmental fate of organic chemicals. PMID:1157796

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering.

PubMed

Menolascina, Filippo; Bellomo, Domenico; Maiwald, Thomas; Bevilacqua, Vitoantonio; Ciminelli, Caterina; Paradiso, Angelo; Tommasi, Stefania

2009-10-15

Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments. We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification. We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the 'data rich--data poor' paradox in Systems Biology.

Structure-based control of complex networks with nonlinear dynamics.

PubMed

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

Preface.

PubMed

Friedman, Avner; Lachowicz, Mirosław; Ledzewicz, Urszula; Piotrowska, Monika Joanna; Szymanska, Zuzanna

2017-02-01

This volume was inspired by the topics presented at the international conference "Micro and Macro Systems in Life Sciences" which was held on Jun 8-12, 2015 in Będlewo, Poland. System biology is an approach which tries to understand how micro systems, at the molecular and cellular levels, affect macro systems such as organs, tissue and populations. Thus it is not surprising that a major theme of this volume evolves around cancer and its treatment. Articles on this topic include models for tumor induced angiogenesis, without and with delays, metastatic niche of the bone marrow, drug resistance and metronomic chemotherapy, and virotherapy of glioma. Methods range from dynamical systems to optimal control. Another well represented topic of this volume is mathematical modeling in epidemiology. Mathematical approaches to modeling and control of more specific diseases like malaria, Ebola or human papillomavirus are discussed as well as a more general approaches to the SEIR, and even more general class of models in epidemiology, by using the tools of optimal control and optimization. The volume also brings up challenges in mathematical modeling of other diseases such as tuberculosis. Partial differential equations combined with numerical approaches are becoming important tools in modeling not only tumor growth and treatment, but also other diseases, such as fibrosis of the liver, and atherosclerosis and its associated blood flow dynamics, and our volume presents a state of the art approach on these topics. Understanding mathematics behind the cell motion, appearance of the special patterns in various cell populations, and age structured mutations are among topics addressed inour volume. A spatio-temporal models of synthetic genetic oscillators brings the analysis to the gene level which is the focus of much of current biological research. Mathematics can help biologists to explain the collective behavior of bacterial, a topic that is also presented here. Finally some more across the discipline topics are being addresses, which can appear as a challenge in studying problems in systems biology on all, macro, meso and micro levels. They include numerical approaches to stochastic wave equation arising in modeling Brownian motion, discrete velocity models, many particle approximations as well as very important aspect on the connection between discrete measurement and the construction of the models for various phenomena, particularly the one involving delays. With the variety of biological topics and their mathematical approaches we very much hope that the reader of the Mathematical Biosciences and Engineering will find this volume interesting and inspirational for their own research.

Uniqueness of polymorphism for a discrete, selection-migration model with genetic dominance

Treesearch

James F. Selgrade; James H. Roberds

2009-01-01

The migration into a natural population of a controlled population, e.g., a transgenic population, is studied using a one island selection-migration model. A 2-dimensional system of nonlinear difference equations describes changes in allele frequency and population size between generations. Biologically reasonable conditions are obtained which guarantee the existence...

Visible and near-infrared laser radiation in a biological tissue. A forward model for medical imaging by optical tomography.

PubMed

Trabelsi, H; Gantri, M; Sediki, E

2010-01-01

We present a numerical model for the study of a general, two-dimensional, time-dependent, laser radiation transfer problem in a biological tissue. The model is suitable for many situations, especially when the external laser source is pulsed or continuous. We used a control volume discrete-ordinate method associated with an implicit, three-level, second-order, time-differencing scheme. In medical imaging by laser techniques, this could be an optical tomography forward model. We considered a very thin rectangular biological tissue-like medium submitted to a visible or a near-infrared laser source. Different cases were treated numerically. The source was assumed to be monochromatic and collimated. We used either a continuous source or a short-pulsed source. The transmitted radiance was computed in detector points on the boundaries. Also, the distribution of the internal radiation intensity for different instants is presented. According to the source type, we examined either the steady-state response or the transient response of the medium. First, our model was validated by experimental results from the literature for a homogeneous biological tissue. The space and angular grid independency of our results is shown. Next, the proposed model was used to study changes in transmitted radiation for a homogeneous background medium in which were imbedded two heterogeneous objects. As a last investigation, we studied a multilayered biological tissue. We simulated near-infrared radiation in human skin, fat and muscle. Some results concerning the effects of fat thickness and positions of the detector source on the reflected radiation are presented.

Reverse engineering and identification in systems biology: strategies, perspectives and challenges.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2014-02-06

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology?

Indirect nontarget effects of host-specific biological control agents: Implications for biological control

Treesearch

Dean E. Pearson; Ragan M. Callaway

2005-01-01

Classical biological control of weeds currently operates under the assumption that biological control agents are safe (i.e., low risk) if they do not directly attack nontarget species. However, recent studies indicate that even highly host-specific biological control agents can impact nontarget species through indirect effects. This finding has profound...

Cooperativity to increase Turing pattern space for synthetic biology.

PubMed

Diambra, Luis; Senthivel, Vivek Raj; Menendez, Diego Barcena; Isalan, Mark

2015-02-20

It is hard to bridge the gap between mathematical formulations and biological implementations of Turing patterns, yet this is necessary for both understanding and engineering these networks with synthetic biology approaches. Here, we model a reaction-diffusion system with two morphogens in a monostable regime, inspired by components that we recently described in a synthetic biology study in mammalian cells.1 The model employs a single promoter to express both the activator and inhibitor genes and produces Turing patterns over large regions of parameter space, using biologically interpretable Hill function reactions. We applied a stability analysis and identified rules for choosing biologically tunable parameter relationships to increase the likelihood of successful patterning. We show how to control Turing pattern sizes and time evolution by manipulating the values for production and degradation relationships. More importantly, our analysis predicts that steep dose-response functions arising from cooperativity are mandatory for Turing patterns. Greater steepness increases parameter space and even reduces the requirement for differential diffusion between activator and inhibitor. These results demonstrate some of the limitations of linear scenarios for reaction-diffusion systems and will help to guide projects to engineer synthetic Turing patterns.

Separating physical and biological controls on ten-year evapotranspiration fluctuations in an irrigated cropland in the North China Plain

NASA Astrophysics Data System (ADS)

Lei, Huimin

2016-04-01

The North China Plain, the largest agricultural production area in China, is a water-limited region where more than 50% of the nation's wheat and 33% of its maize production is grown. Evapotranspiration (ET) is a major component of the water balance in this agricultural ecosystem. Thus, hydrological cycle is very sensitive to the seasonal and interannual variability in ET. Understanding the variability in ET at different temporal scales and identifying out the dominant factor among the climatic factors (i.e., physical factors), crop factors (i.e., biological factors), and anthropogenic factors (i.e., irrigation) regulating ET is vital for promoting the development of agro-hydrological modeling. However, little is known about how ecosystem-level ET of irrigated cropland responds to these physical and biological factors over the long term, e.g., greater than 10 years. We have operated an eddy-covariance tower in a winter wheat-summer maize cropland for a 10-year period from 2005 through 2015, providing continuous measurements of ET and its relevant variables. The 10-year measurement period covers episodes of extremely high to low annual precipitation and higher air temperatures. The 10-year dataset provides opportunity to investigate the response of site-specific ecosystem ET to the variability of environmental factors. In this study, we reconcile an agro-hydrological model and the observations, to separate the physical and biological controls on ET fluctuations at different temporal scales. First, the model is calibrated carefully based on the observations. Second, a number of model runs are designed to disentangle the influence of climate, irrigation and biological drivers through constrained simulations. The climate drivers include precipitation, air temperature, air humidity, wind speed, and solar radiation, and the biological drivers include leaf area index and leaf-level stomatal conductance. In addition, the impacts of the variability in irrigation on ET will be studied. Last, based on the numerical runs, the dominant factor at each temporal scale (i.e., from weekly to annual) is identified.

Growth control of the eukaryote cell: a systems biology study in yeast.

PubMed

Castrillo, Juan I; Zeef, Leo A; Hoyle, David C; Zhang, Nianshu; Hayes, Andrew; Gardner, David Cj; Cornell, Michael J; Petty, June; Hakes, Luke; Wardleworth, Leanne; Rash, Bharat; Brown, Marie; Dunn, Warwick B; Broadhurst, David; O'Donoghue, Kerry; Hester, Svenja S; Dunkley, Tom Pj; Hart, Sarah R; Swainston, Neil; Li, Peter; Gaskell, Simon J; Paton, Norman W; Lilley, Kathryn S; Kell, Douglas B; Oliver, Stephen G

2007-01-01

Cell growth underlies many key cellular and developmental processes, yet a limited number of studies have been carried out on cell-growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are currently lacking. Metabolic control analysis is being exploited in a systems biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endometabolome and exometabolome of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rate-associated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly upregulated with increasing growth rate are frequently essential and encode evolutionarily conserved proteins of known function that participate in many protein-protein interactions. In contrast, more unknown, and fewer essential, genes are downregulated with increasing growth rate; their protein products rarely interact with one another. A large proportion of yeast genes under positive growth-rate control share orthologs with other eukaryotes, including humans. Significantly, transcription of genes encoding components of the TOR complex (a major controller of eukaryotic cell growth) is not subject to growth-rate regulation. Moreover, integrative studies reveal the extent and importance of post-transcriptional control, patterns of control of metabolic fluxes at the level of enzyme synthesis, and the relevance of specific enzymatic reactions in the control of metabolic fluxes during cell growth. This work constitutes a first comprehensive systems biology study on growth-rate control in the eukaryotic cell. The results have direct implications for advanced studies on cell growth, in vivo regulation of metabolic fluxes for comprehensive metabolic engineering, and for the design of genome-scale systems biology models of the eukaryotic cell.

Growth control of the eukaryote cell: a systems biology study in yeast

PubMed Central

Castrillo, Juan I; Zeef, Leo A; Hoyle, David C; Zhang, Nianshu; Hayes, Andrew; Gardner, David CJ; Cornell, Michael J; Petty, June; Hakes, Luke; Wardleworth, Leanne; Rash, Bharat; Brown, Marie; Dunn, Warwick B; Broadhurst, David; O'Donoghue, Kerry; Hester, Svenja S; Dunkley, Tom PJ; Hart, Sarah R; Swainston, Neil; Li, Peter; Gaskell, Simon J; Paton, Norman W; Lilley, Kathryn S; Kell, Douglas B; Oliver, Stephen G

2007-01-01

Background Cell growth underlies many key cellular and developmental processes, yet a limited number of studies have been carried out on cell-growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are currently lacking. Results Metabolic control analysis is being exploited in a systems biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endometabolome and exometabolome of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rate-associated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly upregulated with increasing growth rate are frequently essential and encode evolutionarily conserved proteins of known function that participate in many protein-protein interactions. In contrast, more unknown, and fewer essential, genes are downregulated with increasing growth rate; their protein products rarely interact with one another. A large proportion of yeast genes under positive growth-rate control share orthologs with other eukaryotes, including humans. Significantly, transcription of genes encoding components of the TOR complex (a major controller of eukaryotic cell growth) is not subject to growth-rate regulation. Moreover, integrative studies reveal the extent and importance of post-transcriptional control, patterns of control of metabolic fluxes at the level of enzyme synthesis, and the relevance of specific enzymatic reactions in the control of metabolic fluxes during cell growth. Conclusion This work constitutes a first comprehensive systems biology study on growth-rate control in the eukaryotic cell. The results have direct implications for advanced studies on cell growth, in vivo regulation of metabolic fluxes for comprehensive metabolic engineering, and for the design of genome-scale systems biology models of the eukaryotic cell. PMID:17439666

Linear control theory for gene network modeling.

PubMed

Shin, Yong-Jun; Bleris, Leonidas

2010-09-16

Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

Surface electromyogram for the control of anthropomorphic teleoperator fingers.

PubMed

Gupta, V; Reddy, N P

1996-01-01

Growing importance of telesurgery has led to the need for the development of synergistic control of anthropomorphic teleoperators. Synergistic systems can be developed using direct biological control. The purpose of this study was to develop techniques for direct biocontrol of anthropomorphic teleoperators using surface electromyogram (EMG). A computer model of a two finger teleoperator was developed and controlled using surface EMG from the flexor digitorum superficialis during flexion-extension of the index finger. The results of the study revealed a linear relationship between the RMS EMG and the flexion-extension of the finger model. Therefore, surface EMG can be used as a direct biocontrol for teleoperators and in VR applications.

Using CONFIG for Simulation of Operation of Water Recovery Subsystems for Advanced Control Software Evaluation

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Flores, Luis; Fleming, Land; Throop, Daiv

2002-01-01

A hybrid discrete/continuous simulation tool, CONFIG, has been developed to support evaluation of the operability life support systems. CON FIG simulates operations scenarios in which flows and pressures change continuously while system reconfigurations occur as discrete events. In simulations, intelligent control software can interact dynamically with hardware system models. CONFIG simulations have been used to evaluate control software and intelligent agents for automating life support systems operations. A CON FIG model of an advanced biological water recovery system has been developed to interact with intelligent control software that is being used in a water system test at NASA Johnson Space Center

Enhancing dendritic cell immunotherapy for melanoma using a simple mathematical model.

PubMed

Castillo-Montiel, E; Chimal-Eguía, J C; Tello, J Ignacio; Piñon-Zaráte, G; Herrera-Enríquez, M; Castell-Rodríguez, A E

2015-06-09

The immunotherapy using dendritic cells (DCs) against different varieties of cancer is an approach that has been previously explored which induces a specific immune response. This work presents a mathematical model of DCs immunotherapy for melanoma in mice based on work by Experimental Immunotherapy Laboratory of the Medicine Faculty in the Universidad Autonoma de Mexico (UNAM). The model is a five delay differential equation (DDEs) which represents a simplified view of the immunotherapy mechanisms. The mathematical model takes into account the interactions between tumor cells, dendritic cells, naive cytotoxic T lymphocytes cells (inactivated cytotoxic cells), effector cells (cytotoxic T activated cytotoxic cells) and transforming growth factor β cytokine (T G F-β). The model is validated comparing the computer simulation results with biological trial results of the immunotherapy developed by the research group of UNAM. The results of the growth of tumor cells obtained by the control immunotherapy simulation show a similar amount of tumor cell population than the biological data of the control immunotherapy. Moreover, comparing the increase of tumor cells obtained from the immunotherapy simulation and the biological data of the immunotherapy applied by the UNAM researchers obtained errors of approximately 10 %. This allowed us to use the model as a framework to test hypothetical treatments. The numerical simulations suggest that by using more doses of DCs and changing the infusion time, the tumor growth decays compared with the current immunotherapy. In addition, a local sensitivity analysis is performed; the results show that the delay in time " τ", the maximal growth rate of tumor "r" and the maximal efficiency of tumor cytotoxic cells rate "aT" are the most sensitive model parameters. By using this mathematical model it is possible to simulate the growth of the tumor cells with or without immunotherapy using the infusion protocol of the UNAM researchers, to obtain a good approximation of the biological trials data. It is worth mentioning that by manipulating the different parameters of the model the effectiveness of the immunotherapy may increase. This last suggests that different protocols could be implemented by the Immunotherapy Laboratory of UNAM in order to improve their results.

Constituent bioconcentration in rainbow trout exposed to a complex chemical mixture

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

Linder, G.; Bergman, H.L.; Meyer, J.S.

1984-09-01

Classically, aquatic contaminant fate models predicting a chemical's bioconcentration factor (BCF) are based upon single-compound derived models, yet such BCF predictions may deviate from observed BCFs when physicochemical interactions or biological responses to complex chemical mixture exposures are not adequately considered in the predictive model. Rainbow trout were exposed to oil-shale retort waters. Such a study was designed to model the potential biological effects precluded by exposure to complex chemical mixtures such as solid waste leachates, agricultural runoff, and industrial process waste waters. Chromatographic analysis of aqueous and nonaqueous liquid-liquid reservoir components yielded differences in mixed extraction solvent HPLC profilesmore » of whole fish exposed for 1 and 3 weeks to the highest dilution of the complex chemical mixture when compared to their corresponding control, yet subsequent whole fish extractions at 6, 9, 12, and 15 weeks into exposure demonstrated no qualitative differences between control and exposed fish. Liver extractions and deproteinized bile samples from exposed fish were qualitatively different than their corresponding controls. These findings support the projected NOEC of 0.0045% dilution, even though the differences in bioconcentration profiles suggest hazard assessment strategies may be useful in evaluating environmental fate processes associated with complex chemical mixtures. 12 references, 4 figures, 2 tables.« less

An age-structured model to evaluate the potential of novel malaria-control interventions: a case study of fungal biopesticide sprays

PubMed Central

Hancock, P.A; Thomas, M.B; Godfray, H.C.J

2008-01-01

It has recently been proposed that mosquito vectors of human diseases, particularly malaria, may be controlled by spraying with fungal biopesticides that increase the rate of adult mortality. Though fungal pathogens do not cause instantaneous mortality, they can kill mosquitoes before they are old enough to transmit disease. A model is developed (i) to explore the potential for fungal entomopathogens to reduce significantly infectious mosquito populations, (ii) to assess the relative value of the many different fungal strains that might be used, and (iii) to help guide the tactical design of vector-control programmes. The model follows the dynamics of different classes of adult mosquitoes with the risk of mortality due to the fungus being assumed to be a function of time since infection (modelled using the Weibull distribution). It is shown that substantial reductions in mosquito numbers are feasible for realistic assumptions about mosquito, fungus and malaria biology and moderate to low daily fungal infection probability. The choice of optimal fungal strain and spraying regime is shown to depend on local mosquito and malaria biology. Fungal pathogens may also influence the ability of mosquitoes to transmit malaria and such effects are shown to further reduce vectorial capacity. PMID:18765347

Fuzzy logic for plant-wide control of biological wastewater treatment process including greenhouse gas emissions.

PubMed

Santín, I; Barbu, M; Pedret, C; Vilanova, R

2018-06-01

The application of control strategies is increasingly used in wastewater treatment plants with the aim of improving effluent quality and reducing operating costs. Due to concerns about the progressive growth of greenhouse gas emissions (GHG), these are also currently being evaluated in wastewater treatment plants. The present article proposes a fuzzy controller for plant-wide control of the biological wastewater treatment process. Its design is based on 14 inputs and 6 outputs in order to reduce GHG emissions, nutrient concentration in the effluent and operational costs. The article explains and shows the effect of each one of the inputs and outputs of the fuzzy controller, as well as the relationship between them. Benchmark Simulation Model no 2 Gas is used for testing the proposed control strategy. The results of simulation results show that the fuzzy controller is able to reduce GHG emissions while improving, at the same time, the common criteria of effluent quality and operational costs. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Nature as an engineer: one simple concept of a bio-inspired functional artificial muscle.

PubMed

Schmitt, S; Haeufle, D F B; Blickhan, R; Günther, M

2012-09-01

The biological muscle is a powerful, flexible and versatile actuator. Its intrinsic characteristics determine the way how movements are generated and controlled. Robotic and prosthetic applications expect to profit from relying on bio-inspired actuators which exhibit natural (muscle-like) characteristics. As of today, when constructing a technical actuator, it is not possible to copy the exact molecular structure of a biological muscle. Alternatively, the question may be put how its characteristics can be realized with known mechanical components. Recently, a mechanical construct for an artificial muscle was proposed, which exhibits hyperbolic force-velocity characteristics. In this paper, we promote the constructing concept which is made by substantiating the mechanical design of biological muscle by a simple model, proving the feasibility of its real-world implementation, and checking their output both for mutual consistency and agreement with biological measurements. In particular, the relations of force, enthalpy rate and mechanical efficiency versus contraction velocity of both the construct's technical implementation and its numerical model were determined in quick-release experiments. All model predictions for these relations and the hardware results are now in good agreement with the biological literature. We conclude that the construct represents a mechanical concept of natural actuation, which is suitable for laying down some useful suggestions when designing bio-inspired actuators.

Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.

PubMed

Li, Xiangfang L; Oduola, Wasiu O; Qian, Lijun; Dougherty, Edward R

2015-01-01

In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system's pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas systems pharmacology has a strong focus on studying drugs with regard to the pharmacokinetic (PK) and pharmacodynamic (PD) relations accompanying drug interactions with multiscale physiology as well as the prediction of dosage-exposure responses and economic potentials of drugs. Thus, it requires multiscale methods to address the need for integrating models from the molecular levels to the cellular, tissue, and organism levels. It is a common belief that tumorigenesis and tumor growth can be best understood and tackled by employing and integrating a multifaceted approach that includes in vivo and in vitro experiments, in silico models, multiscale tumor modeling, continuous/discrete modeling, agent-based modeling, and multiscale modeling with PK/PD drug effect inputs. We provide an example application of multiscale modeling employing stochastic hybrid system for a colon cancer cell line HCT-116 with the application of Lapatinib drug. It is observed that the simulation results are similar to those observed from the setup of the wet-lab experiments at the Translational Genomics Research Institute.

Average of delta: a new quality control tool for clinical laboratories.

PubMed

Jones, Graham R D

2016-01-01

Average of normals is a tool used to control assay performance using the average of a series of results from patients' samples. Delta checking is a process of identifying errors in individual patient results by reviewing the difference from previous results of the same patient. This paper introduces a novel alternate approach, average of delta, which combines these concepts to use the average of a number of sequential delta values to identify changes in assay performance. Models for average of delta and average of normals were developed in a spreadsheet application. The model assessed the expected scatter of average of delta and average of normals functions and the effect of assay bias for different values of analytical imprecision and within- and between-subject biological variation and the number of samples included in the calculations. The final assessment was the number of patients' samples required to identify an added bias with 90% certainty. The model demonstrated that with larger numbers of delta values, the average of delta function was tighter (lower coefficient of variation). The optimal number of samples for bias detection with average of delta was likely to be between 5 and 20 for most settings and that average of delta outperformed average of normals when the within-subject biological variation was small relative to the between-subject variation. Average of delta provides a possible additional assay quality control tool which theoretical modelling predicts may be more valuable than average of normals for analytes where the group biological variation is wide compared with within-subject variation and where there is a high rate of repeat testing in the laboratory patient population. © The Author(s) 2015.

Tissue vascularization through 3D printing: Will technology bring us flow?

PubMed

Paulsen, S J; Miller, J S

2015-05-01

Though in vivo models provide the most physiologically relevant environment for studying tissue function, in vitro studies provide researchers with explicit control over experimental conditions and the potential to develop high throughput testing methods. In recent years, advancements in developmental biology research and imaging techniques have significantly improved our understanding of the processes involved in vascular development. However, the task of recreating the complex, multi-scale vasculature seen in in vivo systems remains elusive. 3D bioprinting offers a potential method to generate controlled vascular networks with hierarchical structure approaching that of in vivo networks. Bioprinting is an interdisciplinary field that relies on advances in 3D printing technology along with advances in imaging and computational modeling, which allow researchers to monitor cellular function and to better understand cellular environment within the printed tissue. As bioprinting technologies improve with regards to resolution, printing speed, available materials, and automation, 3D printing could be used to generate highly controlled vascularized tissues in a high throughput manner for use in regenerative medicine and the development of in vitro tissue models for research in developmental biology and vascular diseases. © 2015 Wiley Periodicals, Inc.

A Model of Controlled Growth

NASA Astrophysics Data System (ADS)

Bressan, Alberto; Lewicka, Marta

2018-03-01

We consider a free boundary problem for a system of PDEs, modeling the growth of a biological tissue. A morphogen, controlling volume growth, is produced by specific cells and then diffused and absorbed throughout the domain. The geometric shape of the growing tissue is determined by the instantaneous minimization of an elastic deformation energy, subject to a constraint on the volumetric growth. For an initial domain with C}^{2,α boundary, our main result establishes the local existence and uniqueness of a classical solution, up to a rigid motion.

Young-Age Gender Differences in Mathematics Mediated by Independent Control or Uncontrollability

ERIC Educational Resources Information Center

Zirk-Sadowski, Jan; Lamptey, Charlotte; Devine, Amy; Haggard, Mark; Szucs, Dénes

2014-01-01

We studied whether the origins of math anxiety can be related to a biologically supported framework of stress induction: (un)controllability perception, here indicated by self-reported independent efforts in mathematics. Math anxiety was tested in 182 children (8- to 11-year-olds). "Latent factor modeling" was used to test hypotheses on…

Benchmarking Measures of Network Controllability on Canonical Graph Models

NASA Astrophysics Data System (ADS)

Wu-Yan, Elena; Betzel, Richard F.; Tang, Evelyn; Gu, Shi; Pasqualetti, Fabio; Bassett, Danielle S.

2018-03-01

The control of networked dynamical systems opens the possibility for new discoveries and therapies in systems biology and neuroscience. Recent theoretical advances provide candidate mechanisms by which a system can be driven from one pre-specified state to another, and computational approaches provide tools to test those mechanisms in real-world systems. Despite already having been applied to study network systems in biology and neuroscience, the practical performance of these tools and associated measures on simple networks with pre-specified structure has yet to be assessed. Here, we study the behavior of four control metrics (global, average, modal, and boundary controllability) on eight canonical graphs (including Erdős-Rényi, regular, small-world, random geometric, Barábasi-Albert preferential attachment, and several modular networks) with different edge weighting schemes (Gaussian, power-law, and two nonparametric distributions from brain networks, as examples of real-world systems). We observe that differences in global controllability across graph models are more salient when edge weight distributions are heavy-tailed as opposed to normal. In contrast, differences in average, modal, and boundary controllability across graph models (as well as across nodes in the graph) are more salient when edge weight distributions are less heavy-tailed. Across graph models and edge weighting schemes, average and modal controllability are negatively correlated with one another across nodes; yet, across graph instances, the relation between average and modal controllability can be positive, negative, or nonsignificant. Collectively, these findings demonstrate that controllability statistics (and their relations) differ across graphs with different topologies and that these differences can be muted or accentuated by differences in the edge weight distributions. More generally, our numerical studies motivate future analytical efforts to better understand the mathematical underpinnings of the relationship between graph topology and control, as well as efforts to design networks with specific control profiles.

Suppressive composts from organic wastes as agents of biological control of fusariosis in Tatartan Republic (Russia)

NASA Astrophysics Data System (ADS)

Gumerova, Raushaniya; Galitskaya, Polina; Beru, Franchesca; Selivanovskaya, Svetlana

2015-04-01

Plant diseases are one of the seriously limiting factors of agriculture efficiency around the world. Diseases caused by fungi are the major threat to plants. Crop protection in modern agriculture heavily depends on chemical fungicides. Disadvantages of chemical pesticides soon became apparent as damage to the environment and a hazard to human health. In this regard use of biopesticides becomes an attractive alternative method of plant protection. For biological control of fungal plant diseases, separate bacterial or fungal strains as well as their communities can be used. Biopreparations must consist of microbes that are typical for local climate and soil conditions and therefore are able to survive in environments for a long time. Another option of plant pests' biological control is implementation of suppressive composts made of agricultural or other organic wastes. These composts can not only prevent the development of plant diseases, but also improve the soil fertility. The objective of this work was estimation of potential of composts and strains isolated from these composts as means for biological control of fusariosis that is one of the most widespread plant soil born disease. The composts were made up of the commonly produced agricultural wastes produced in Tatarstan Republic (Russia). Fusarium oxysporum f. sp. radicis-lycopersici was used as a model phytopathogen. Ten types of organic waste (Goat manure (GM), Chicken dung (CD), Chicken dung with straw addition (CS), Rabbit dung (RD), Cow manure (CM), Rerotting pork manure (RPM), Fresh pork manure (FPM), Pork manure with sawdust and straw (PMS), the remains of plants and leaves (PL), the vegetable waste (VW) were sampled in the big farms situated in Tatarstan Republic which is one of the main agricultural regions of Russia. The initial wastes were composted for 150 days. Further, the following characteristics of the composts were assessed: pH, electro conductivity, TOC, DOC, Ntot. On petri dishes with meat pepton agar, the composts and their water extracts were checked towards their ability to inhibit growth of F. oxysporum. It was shown that three composts - CD, FPM and RD - possessed suppressiveness towards the model phytopathogen. From these three wastes, 28 bacterial and fungal strains were isolated and, in their turn, checked towards their ability to inhibit F. oxysporum. It was demonstrated that five of the isolated strains are highly suppressive to model test-object (the growth area of F. oxysporum did not exceed 30%), six of the stains were moderate suppressive (the growth area of F. oxysporum ranged from 35% to 60%), and other strains did not cause negative effects for the model phytopathogen. Further, we will check the composts and the isolated strains using the model system "soil - tomato plant - phytopathogen". As a result, effective composts and strains will be recommended as agents for biological control of fungal diseases in the region. Besides, the structure of bacterial and fungal community of the composts with suppressive properties will be assessed using 454-pyrosequencing.

Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

Recent development and biomedical applications of probabilistic Boolean networks

PubMed Central

2013-01-01

Probabilistic Boolean network (PBN) modelling is a semi-quantitative approach widely used for the study of the topology and dynamic aspects of biological systems. The combined use of rule-based representation and probability makes PBN appealing for large-scale modelling of biological networks where degrees of uncertainty need to be considered. A considerable expansion of our knowledge in the field of theoretical research on PBN can be observed over the past few years, with a focus on network inference, network intervention and control. With respect to areas of applications, PBN is mainly used for the study of gene regulatory networks though with an increasing emergence in signal transduction, metabolic, and also physiological networks. At the same time, a number of computational tools, facilitating the modelling and analysis of PBNs, are continuously developed. A concise yet comprehensive review of the state-of-the-art on PBN modelling is offered in this article, including a comparative discussion on PBN versus similar models with respect to concepts and biomedical applications. Due to their many advantages, we consider PBN to stand as a suitable modelling framework for the description and analysis of complex biological systems, ranging from molecular to physiological levels. PMID:23815817

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks

PubMed Central

Walpole, J.; Chappell, J.C.; Cluceru, J.G.; Mac Gabhann, F.; Bautch, V.L.; Peirce, S. M.

2015-01-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods. PMID:26158406

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

PubMed

Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

2015-09-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

Topological Principles of Control in Dynamical Networks

NASA Astrophysics Data System (ADS)

Kim, Jason; Pasqualetti, Fabio; Bassett, Danielle

Networked biological systems, such as the brain, feature complex patterns of interactions. To predict and correct the dynamic behavior of such systems, it is imperative to understand how the underlying topological structure affects and limits the function of the system. Here, we use network control theory to extract topological features that favor or prevent network controllability, and to understand the network-wide effect of external stimuli on large-scale brain systems. Specifically, we treat each brain region as a dynamic entity with real-valued state, and model the time evolution of all interconnected regions using linear, time-invariant dynamics. We propose a simplified feed-forward scheme where the effect of upstream regions (drivers) on the connected downstream regions (non-drivers) is characterized in closed-form. Leveraging this characterization of the simplified model, we derive topological features that predict the controllability properties of non-simplified networks. We show analytically and numerically that these predictors are accurate across a large range of parameters. Among other contributions, our analysis shows that heterogeneity in the network weights facilitate controllability, and allows us to implement targeted interventions that profoundly improve controllability. By assuming an underlying dynamical mechanism, we are able to understand the complex topology of networked biological systems in a functionally meaningful way.

Understanding ethnopharmacolgy: implications for cultural relativism.

PubMed

Davidhizar, Ruth; Giger, Joyce Newman

2008-07-01

It is commonly accepted that people differ culturally. In the Giger and Davidhizar Transcultural Assessment Model, cultural differences are evident in communication, spatial relationships and needs, social organizations (church, family, kinships, and clubs), time orientation, the ability or desire to control the environment, and biological variations (Giger & Davidhizar, 2008). While many individuals appreciate that there are differences between cultures, what is less well recognized is that people also vary according to biological variations depending on their racial and ethnic group. In the last 15 years, information about biological variations has rapidly expanded and that knowledge is essential in order to understand and provide care to individuals from another culture or another racial and ethnic group. Attention to biological variations related to race and ethnicity, the last component of the Giger and Davidhizar Transcultural Nursing Assessment Model, is a critical phenomenon that needs to be assessed in order to develop and implement a culturally sensitive plan of care in an effort to understand ethnopharmacolgy.

Temperature prediction of space flight experiments by computer thermal analysis

NASA Technical Reports Server (NTRS)

Birdsong, M. B.; Luttges, M. W.

1994-01-01

Life sciences experiments are especially sensitive to temperature. A small temperature difference between otherwise identical samples can cause various differences in biological reaction rates. Knowledge of experimental temperatures and temperature histories help to distinguish the effects of microgravity and temperature on spaceflight experiments compared to ground based studies, and allow appropriate controls and sensitivity tests. Up to the present time, the Orbiter (Space Shuttle) has not generally provided temperature measurement instrumentation inside ambient lockers located in the Mid-deck of the Orbiter, or inside similar facilities such as Spacehab and Spacelab, but many pieces of hardware do have temperature recording capability. Most of these temperatures, however, have only been roughly measured or estimated. Such reported experimental temperatures, while accurate within a range of several degrees Celsius, are of limited utility to biological researchers. The temperature controlled lockers used in spaceflight, such as Commerical-Refrigeration Incubation Modules (C-R/IMs), severely reduce the mass and volume available for test samples and do not necessarily provide uniform thermal environments. While these test carriers avoid some of the experimental temperature variations of the ambient lockers, the number of samples which can be accommodated in these temperature controlled units is limited. In the present work, improved models of thermal prediction and control were sought. Temperatures are predicted by thermal analysis software using empirical temperatures recorded during STS-57. These temperatures are compared to data recorded throughout the mission using Ambient Temperature Recorders (ATRs) located within several payload lockers. Additional test cases are undertaken using controlled ground experiments to more precisely determine the reliability of the thermal model. The approach presented should increase the utility of various spaceflight carriers in the support of biological and material science research and ground control studies done in preparation for flight.

Temperature prediction of space flight experiments by computer thermal analysis.

PubMed

Birdsong, M B; Luttges, M W

1995-02-01

Life sciences experiments are especially sensitive to temperature. A small temperature difference between otherwise identical samples can cause various differences in biological reaction rates. Knowledge of experimental temperatures and temperature histories help to distinguish the effects of microgravity and temperature on spaceflight experiments compared to ground based studies, and allow appropriate controls and sensitivity tests. Up to the present time, the Orbiter (Space Shuttle) has not generally provided temperature measurement instrumentation inside ambient lockers located in the Mid-deck of the Orbiter, or inside similar facilities such as Spacehab and Spacelab, but many pieces of hardware do have temperature recording capability. Most of these temperatures, however, have only been roughly measured or estimated. Such reported experimental temperatures, while accurate within a range of several degrees Celsius, are of limited utility to biological researchers. The temperature controlled lockers used in spaceflight, such as Commercial-Refrigeration Incubation Modules (C-R/IMs), severely reduce the mass and volume available for test samples and do not necessarily provide uniform thermal environments. While these test carriers avoid some of the experimental temperature variations of the ambient lockers, the number of samples which can be accommodated in these temperature controlled units is limited. In the present work, improved models of thermal prediction and control were sought. Temperatures are predicted by thermal analysis software using empirical temperatures recorded during STS-57. These temperatures are compared to data recorded throughout the mission using Ambient Temperature Recorders (ATRs) located within several payload lockers. Additional test cases are undertaken using controlled ground experiments to more precisely determine the reliability of the thermal model. The approach presented should increase the utility of various spaceflight carriers in the support of biological and material science research and ground control studies done in preparation for flight.

Development and Clinical Assessment of a Comprehensive Product for Pigmentation Control in Multiple Ethnic Populations.

PubMed

Makino, Elizabeth T; Kadoya, Kuniko; Sigler, Monya L; Hino, Peter D; Mehta, Rahul C

2016-12-01

Pigmentary changes in people of different ethnic origins are controlled by slight variations in key biological pathways leading to different outcomes from the same treatment. It is important to develop and test products for desired outcomes in varying ethnic populations. To develop a comprehensive product (LYT2) that affects all major biological pathways controlling pigmentation and test for clinical efficacy and safety in different ethnic populations. A thorough analysis of biological pathways was used to identify ingredient combinations for LYT2 that provided optimal melanin reduction in a 3-D skin model. Expression of four key genes for melanogenesis, TYR, TYRP-1, DCT, and MITF was analyzed by qPCR. Clinical study was conducted to compare the efficacy and tolerability of LYT2 against 4% hydroquinone (HQ). Average melanin suppression by LYT2 in 7 independent experiments was 45%. All four key genes show significant down- regulation of expression. LYT2 provided statistically significant reductions in mean overall hyperpigmentation grades as early as week 2 compared to baseline, with continued significant improvements through week 12 in all ethnic groups tested. We have successfully combined management of 6 categories of pathways related to melanogenesis: melanocyte activation, melanosome development, melanin production, melanin distribution, keratinocyte turnover, and barrier function to create a comprehensive HQ-free product. The outcome clearly shows greater pigmentation control with LYT2 compared to other HQ-free products in skin tissue models and earlier control in clinical studies compared to 4% HQ. Clinical study shows pigmentation control benefits of LYT2 in people of Caucasian, Hispanic, and African ethnic origins. J Drugs Dermatol. 2016;15(12):1562-1570.

Equilibrium control of nonlinear verticum-type systems, applied to integrated pest control.

PubMed

Molnár, S; Gámez, M; López, I; Cabello, T

2013-08-01

Linear verticum-type control and observation systems have been introduced for modelling certain industrial systems, consisting of subsystems, vertically connected by certain state variables. Recently the concept of verticum-type observation systems and the corresponding observability condition have been extended by the authors to the nonlinear case. In the present paper the general concept of a nonlinear verticum-type control system is introduced, and a sufficient condition for local controllability to equilibrium is obtained. In addition to a usual linearization, the basic idea is a decomposition of the control of the whole system into the control of the subsystems. Starting from the integrated pest control model of Rafikov and Limeira (2012) and Rafikov et al. (2012), a nonlinear verticum-type model has been set up an equilibrium control is obtained. Furthermore, a corresponding bioeconomical problem is solved minimizing the total cost of integrated pest control (combining chemical control with a biological one). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A bio-inspired glucose controller based on pancreatic β-cell physiology.

PubMed

Herrero, Pau; Georgiou, Pantelis; Oliver, Nick; Johnston, Desmond G; Toumazou, Christofer

2012-05-01

Control algorithms for closed-loop insulin delivery in type 1 diabetes have been mainly based on control engineering or artificial intelligence techniques. These, however, are not based on the physiology of the pancreas but seek to implement engineering solutions to biology. Developments in mathematical models of the β-cell physiology of the pancreas have described the glucose-induced insulin release from pancreatic β cells at a molecular level. This has facilitated development of a new class of bio-inspired glucose control algorithms that replicate the functionality of the biological pancreas. However, technologies for sensing glucose levels and delivering insulin use the subcutaneous route, which is nonphysiological and introduces some challenges. In this article, a novel glucose controller is presented as part of a bio-inspired artificial pancreas. A mathematical model of β-cell physiology was used as the core of the proposed controller. In order to deal with delays and lack of accuracy introduced by the subcutaneous route, insulin feedback and a gain scheduling strategy were employed. A United States Food and Drug Administration-accepted type 1 diabetes mellitus virtual population was used to validate the presented controller. Premeal and postmeal mean ± standard deviation blood glucose levels for the adult and adolescent populations were well within the target range set for the controller [(70, 180) mg/dl], with a percent time in range of 92.8 ± 7.3% for the adults and 83.5 ± 14% for the adolescents. This article shows for the first time very good glucose control in a virtual population with type 1 diabetes mellitus using a controller based on a subcellular β-cell model. © 2012 Diabetes Technology Society.

A Bio-Inspired Glucose Controller Based on Pancreatic β-Cell Physiology

PubMed Central

Herrero, Pau; Georgiou, Pantelis; Oliver, Nick; Johnston, Desmond G; Toumazou, Christofer

2012-01-01

Introduction Control algorithms for closed-loop insulin delivery in type 1 diabetes have been mainly based on control engineering or artificial intelligence techniques. These, however, are not based on the physiology of the pancreas but seek to implement engineering solutions to biology. Developments in mathematical models of the β-cell physiology of the pancreas have described the glucose-induced insulin release from pancreatic β cells at a molecular level. This has facilitated development of a new class of bio-inspired glucose control algorithms that replicate the functionality of the biological pancreas. However, technologies for sensing glucose levels and delivering insulin use the subcutaneous route, which is nonphysiological and introduces some challenges. In this article, a novel glucose controller is presented as part of a bio-inspired artificial pancreas. Methods A mathematical model of β-cell physiology was used as the core of the proposed controller. In order to deal with delays and lack of accuracy introduced by the subcutaneous route, insulin feedback and a gain scheduling strategy were employed. A United States Food and Drug Administration-accepted type 1 diabetes mellitus virtual population was used to validate the presented controller. Results Premeal and postmeal mean ± standard deviation blood glucose levels for the adult and adolescent populations were well within the target range set for the controller [(70, 180) mg/dl], with a percent time in range of 92.8 ± 7.3% for the adults and 83.5 ± 14% for the adolescents. Conclusions This article shows for the first time very good glucose control in a virtual population with type 1 diabetes mellitus using a controller based on a subcellular β-cell model. PMID:22768892

Economic value of biological control in integrated pest management of managed plant systems.

PubMed

Naranjo, Steven E; Ellsworth, Peter C; Frisvold, George B

2015-01-07

Biological control is an underlying pillar of integrated pest management, yet little focus has been placed on assigning economic value to this key ecosystem service. Setting biological control on a firm economic foundation would help to broaden its utility and adoption for sustainable crop protection. Here we discuss approaches and methods available for valuation of biological control of arthropod pests by arthropod natural enemies and summarize economic evaluations in classical, augmentative, and conservation biological control. Emphasis is placed on valuation of conservation biological control, which has received little attention. We identify some of the challenges of and opportunities for applying economics to biological control to advance integrated pest management. Interaction among diverse scientists and stakeholders will be required to measure the direct and indirect costs and benefits of biological control that will allow farmers and others to internalize the benefits that incentivize and accelerate adoption for private and public good.

Mammalian synthetic biology for studying the cell.

PubMed

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.

A Dynamical Analysis of a Piecewise Smooth Pest Control SI Model

NASA Astrophysics Data System (ADS)

Liu, Bing; Liu, Wanbo; Tao, Fennmei; Kang, Baolin; Cong, Jiguang

In this paper, we propose a piecewise smooth SI pest control system to model the process of spraying pesticides and releasing infectious pests. We assume that the pest population consists of susceptible pests and infectious pests, and that the disease spreads horizontally between pests. We take the susceptible pest as the control index on whether to implement chemical control and biological control strategies. Based on the theory of Filippov system, the sliding-mode domain and conditions for the existence of real equilibria, virtual equilibria, pseudo-equilibrium and boundary equilibria are given. Further, we show the global stability of real equilibria (or boundary equilibria) and pseudo-equilibrium. Our results can provide theoretical guidance for the problem of pest control.

Modeling the Spread and Control of the Asian Tiger Mosquito in Los Angeles

NASA Astrophysics Data System (ADS)

Barker, C.; Montecino, D.; Marcantonio, M.

2015-12-01

The Asian tiger mosquito, Aedes albopictus, is among the world's most invasive species. Its spread has been facilitated by rapid global transport of cargo and potentially by the warming of climate, and it is now established on every continent except Antarctica. This species represents a "triple threat" to human health, being a day-biting pest, a competent vector of globally important dengue and chikungunya viruses, and a potential bridge vector of several zoonotic arboviruses. As a result of its importance, the biology of Ae. albopictus is also well-studied, but the fine-scale processes by which it becomes established in a given location are poorly understood. This is because even intensive surveillance systems yield limited information during the early phase of invasions when densities are low, and detection often occurs after populations are relatively widespread. Fine-scale spatial models for mosquito dynamics and movement offer a way forward, marrying our understanding of Ae. albopictus biology with surveillance paradigms and detailed data on the real landscapes where invasions occur. This presentation will consider the impacts of climate on the biology of Ae. albopictus and explore their implications for the ongoing invasion and establishment of Ae. albopictus in Los Angeles since 2011. We have used hierarchical modeling to account for heterogeneities in household-level suitability, then we modeled the stochastic dynamics of Ae. albopictus on this landscape using the suitability surface and a temperature-dependent, dynamical model for reproduction and spread. I will discuss the modeling approach and use the model results to answer policy-relevant questions related to our ability to detect and control these highly invasive mosquitoes.

Stochastic cycle selection in active flow networks.

PubMed

Woodhouse, Francis G; Forrow, Aden; Fawcett, Joanna B; Dunkel, Jörn

2016-07-19

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models.

A systematic analysis of the Braitenberg vehicle 2b for point-like stimulus sources.

PubMed

Rañó, Iñaki

2012-09-01

Braitenberg vehicles have been used experimentally for decades in robotics with limited empirical understanding. This paper presents the first mathematical model of the vehicle 2b, displaying so-called aggression behaviour, and analyses the possible trajectories for point-like smooth stimulus sources. This sensory-motor steering control mechanism is used to implement biologically grounded target approach, target-seeking or obstacle-avoidance behaviour. However, the analysis of the resulting model reveals that complex and unexpected trajectories can result even for point-like stimuli. We also prove how the implementation of the controller and the vehicle morphology interact to affect the behaviour of the vehicle. This work provides a better understanding of Braitenberg vehicle 2b, explains experimental results and paves the way for a formally grounded application on robotics as well as for a new way of understanding target seeking in biology.

Stochastic cycle selection in active flow networks

PubMed Central

Woodhouse, Francis G.; Forrow, Aden; Fawcett, Joanna B.; Dunkel, Jörn

2016-01-01

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models. PMID:27382186

INSTAR: simulating the biological cycle of a forest pest in Mediterranean pine stands

NASA Astrophysics Data System (ADS)

Suárez-Muñoz, María; Bonet García, Francisco J.; Hódar, José A.

2017-04-01

The pine processionary moth (Thaumetopoea pityocampa) is a typically Mediterranean forest pest feeding on pine needles during its larval stages. The outbreaks of this pest cause important landscape impacts and public health problems (i.e. larvae are very urticant). Larvae feed during winter months and cold temperature is the main limiting factor in their development. Therefore, rising temperatures are thought to benefit this species. Indeed, observations suggest that outbreaks are becoming more frequent and populations are shifting uphill. The objective of this work is to simulate the biological cycle of T. pityocampa to make predictions about where and when outbreaks will occur. Thus, we have created a model called INSTAR that will help to identify hotspots and foresee massive defoliation episodes. This will enhance the information available for the control of this pest. INSTAR is an Agent-Based Model, which allows the inclusion of important characteristics of the system: emergence, feedback (i.e. interaction between agents and their environment), adaptation (i.e. decision based on the mentioned interactions) and path dependence (i.e. possibilities at one time point are determined by past conditions). These characteristics arise from a set of functions simulating pine growth, processionary development, mortality and movement. These functions are easily extrapolable to other similar biological processes and therefore INSTAR aims at serving of example for other forest pest models. INSTAR is the first comprehensive approach to simulate the biological cycle of T pityocampa. It simulates the pest development in a given area, from which elevation and pine trees are considered. Moreover, it is also a good example of integrating environmental information into a population dynamic model: meteorological variables and soil moisture are obtained from a hydrological model (WiMMed, Herrero et al. 2009) executed for the area of interest. These variables are the inputs of the model, which feed the functions that simulate the processionary life cycle. Model's executions in two different areas and for relatively long time frames (1993-2014 and 2000-2014) yield relevant information about the biological cycle of the forest pest: the simulated peaks of larvae are followed by minimal values of pine biomass and pine infections are more abundant at the edge of the stands. Moreover, emerging patterns such as denso-dependency can be observed. To sum up, INSTAR is a promising tool for modeling T. pityocampa population dynamics. The obtained model will help to improve the decision making process regarding the control of the forest pest. Moreover, its simple structure of functions will facilitate the design of new models simulating other forest pests.

Computational Models of Cognitive Control

PubMed Central

O’Reilly, Randall C.; Herd, Seth A.; Pauli, Wolfgang M.

2010-01-01

Cognitive control refers to the ability to perform task-relevant processing in the face of other distractions or other forms of interference, in the absence of strong environmental support. It depends on the integrity of the prefrontal cortex and associated biological structures (e.g., the basal ganglia). Computational models have played an influential role in developing our understanding of this system, and we review current developments in three major areas: dynamic gating of prefrontal representations, hierarchies in the prefrontal cortex, and reward, motivation, and goal-related processing in prefrontal cortex. Models in these and other areas are advancing the field further forward. PMID:20185294

Genomic imprinting—an epigenetic gene-regulatory model

PubMed Central

Koerner, Martha V; Barlow, Denise P

2010-01-01

Epigenetic mechanisms (Box 1) are considered to play major gene-regulatory roles in development, differentiation and disease. However, the relative importance of epigenetics in defining the mammalian transcriptome in normal and disease states is unknown. The mammalian genome contains only a few model systems where epigenetic gene regulation has been shown to play a major role in transcriptional control. These model systems are important not only to investigate the biological function of known epigenetic modifications but also to identify new and unexpected epigenetic mechanisms in the mammalian genome. Here we review recent progress in understanding how epigenetic mechanisms control imprinted gene expression. PMID:20153958

Mapping annotations with textual evidence using an scLDA model.

PubMed

Jin, Bo; Chen, Vicky; Chen, Lujia; Lu, Xinghua

2011-01-01

Most of the knowledge regarding genes and proteins is stored in biomedical literature as free text. Extracting information from complex biomedical texts demands techniques capable of inferring biological concepts from local text regions and mapping them to controlled vocabularies. To this end, we present a sentence-based correspondence latent Dirichlet allocation (scLDA) model which, when trained with a corpus of PubMed documents with known GO annotations, performs the following tasks: 1) learning major biological concepts from the corpus, 2) inferring the biological concepts existing within text regions (sentences), and 3) identifying the text regions in a document that provides evidence for the observed annotations. When applied to new gene-related documents, a trained scLDA model is capable of predicting GO annotations and identifying text regions as textual evidence supporting the predicted annotations. This study uses GO annotation data as a testbed; the approach can be generalized to other annotated data, such as MeSH and MEDLINE documents.

Population-level effects of abamectin, azadirachtin and fenpyroximate on the predatory mite Neoseiulus baraki.

PubMed

Lima, Debora B; Melo, José W S; Gondim, Manoel G C; Guedes, Raul N C; Oliveira, José E M

2016-10-01

The coconut production system, in which the coconut mite Aceria guerreronis is considered a key pest, provides an interesting model for integration of biological and chemical control. In Brazil, the most promising biological control agent for the coconut mite is the phytoseiid predator Neoseiulus baraki. However, acaricides are widely used to control the coconut mite, although they frequently produce unsatisfactory results. In this study, we evaluated the simultaneous direct effect of dry residue contact and contaminated prey ingestion of the main acaricides used on coconut palms (i.e., abamectin, azadirachtin and fenpyroximate) on life-history traits of N. baraki and their offspring. These acaricides are registered, recommended and widely used against A. guerreronis in Brazil, and they were tested at their label rates. The offspring of the exposed predators was also evaluated by estimating the instantaneous rate of population increase (r i ). Abamectin compromised female performance, whereas fenpyroximate did not affect the exposed females (F0). Nonetheless, fenpyroximate strongly compromised the offspring (F1) net reproductive rate (R0), intrinsic rate of population growth (r i ), and doubling time (DT). In contrast, fenpyroximate did not have such effects on the 2nd generation (F2) of predators with acaricide-exposed grandparents. Azadirachtin did not affect the predators, suggesting that this acaricide can be used in association with biological control by this predatory species. In contrast, the use of abamectin and fenpyroximate is likely to lead to adverse consequences in the biological control of A. guerreronis using N. baraki.

Is Ground Cover Vegetation an Effective Biological Control Enhancement Strategy against Olive Pests?

PubMed Central

Paredes, Daniel; Cayuela, Luis; Gurr, Geoff M.; Campos, Mercedes

2015-01-01

Ground cover vegetation is often added or allowed to generate to promote conservation biological control, especially in perennial crops. Nevertheless, there is inconsistent evidence of its effectiveness, with studies reporting positive, nil or negative effects on pest control. This might arise from differences between studies at the local scale (e.g. orchard management and land use history), the landscape context (e.g. presence of patches of natural or semi-natural vegetation near the focal orchard), or regional factors, particularly climate in the year of the study. Here we present the findings from a long-term regional monitoring program conducted on four pest species (Bactrocera oleae, Prays oleae, Euphyllura olivina, Saissetia oleae) in 2,528 olive groves in Andalusia (Spain) from 2006 to 2012. Generalized linear mixed effect models were used to analyze the effect of ground cover on different response variables related to pest abundance, while accounting for variability at the local, landscape and regional scales. There were small and inconsistent effects of ground cover on the abundance of pests whilst local, landscape and regional variability explained a large proportion of the variability in pest response variables. This highlights the importance of local and landscape-related variables in biological control and the potential effects that might emerge from their interaction with practices, such as groundcover vegetation, implemented to promote natural enemy activity. The study points to perennial vegetation close to the focal crop as a promising alternative strategy for conservation biological control that should receive more attention. PMID:25646778

Chromatin Computation

PubMed Central

Bryant, Barbara

2012-01-01

In living cells, DNA is packaged along with protein and RNA into chromatin. Chemical modifications to nucleotides and histone proteins are added, removed and recognized by multi-functional molecular complexes. Here I define a new computational model, in which chromatin modifications are information units that can be written onto a one-dimensional string of nucleosomes, analogous to the symbols written onto cells of a Turing machine tape, and chromatin-modifying complexes are modeled as read-write rules that operate on a finite set of adjacent nucleosomes. I illustrate the use of this “chromatin computer” to solve an instance of the Hamiltonian path problem. I prove that chromatin computers are computationally universal – and therefore more powerful than the logic circuits often used to model transcription factor control of gene expression. Features of biological chromatin provide a rich instruction set for efficient computation of nontrivial algorithms in biological time scales. Modeling chromatin as a computer shifts how we think about chromatin function, suggests new approaches to medical intervention, and lays the groundwork for the engineering of a new class of biological computing machines. PMID:22567109

Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks.

PubMed

Tan, Jie; Doing, Georgia; Lewis, Kimberley A; Price, Courtney E; Chen, Kathleen M; Cady, Kyle C; Perchuk, Barret; Laub, Michael T; Hogan, Deborah A; Greene, Casey S

2017-07-26

Cross-experiment comparisons in public data compendia are challenged by unmatched conditions and technical noise. The ADAGE method, which performs unsupervised integration with denoising autoencoder neural networks, can identify biological patterns, but because ADAGE models, like many neural networks, are over-parameterized, different ADAGE models perform equally well. To enhance model robustness and better build signatures consistent with biological pathways, we developed an ensemble ADAGE (eADAGE) that integrated stable signatures across models. We applied eADAGE to a compendium of Pseudomonas aeruginosa gene expression profiling experiments performed in 78 media. eADAGE revealed a phosphate starvation response controlled by PhoB in media with moderate phosphate and predicted that a second stimulus provided by the sensor kinase, KinB, is required for this PhoB activation. We validated this relationship using both targeted and unbiased genetic approaches. eADAGE, which captures stable biological patterns, enables cross-experiment comparisons that can highlight measured but undiscovered relationships. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Metabolic Free Energy and Biological Codes: A 'Data Rate Theorem' Aging Model.

PubMed

Wallace, Rodrick

2015-06-01

A famous argument by Maturana and Varela (Autopoiesis and cognition. Reidel, Dordrecht, 1980) holds that the living state is cognitive at every scale and level of organization. Since it is possible to associate many cognitive processes with 'dual' information sources, pathologies can sometimes be addressed using statistical models based on the Shannon Coding, the Shannon-McMillan Source Coding, the Rate Distortion, and the Data Rate Theorems, which impose necessary conditions on information transmission and system control. Deterministic-but-for-error biological codes do not directly invoke cognition, but may be essential subcomponents within larger cognitive processes. A formal argument, however, places such codes within a similar framework, with metabolic free energy serving as a 'control signal' stabilizing biochemical code-and-translator dynamics in the presence of noise. Demand beyond available energy supply triggers punctuated destabilization of the coding channel, affecting essential biological functions. Aging, normal or prematurely driven by psychosocial or environmental stressors, must interfere with the routine operation of such mechanisms, initiating the chronic diseases associated with senescence. Amyloid fibril formation, intrinsically disordered protein logic gates, and cell surface glycan/lectin 'kelp bed' logic gates are reviewed from this perspective. The results generalize beyond coding machineries having easily recognizable symmetry modes, and strip a layer of mathematical complication from the study of phase transitions in nonequilibrium biological systems.

Contact nanomechanical measurements with the AFM

NASA Astrophysics Data System (ADS)

Geisse, Nicholas

2013-03-01

The atomic force microscope (AFM) has found broad use in the biological sciences largely due to its ability to make measurements on unfixed and unstained samples under liquid. In addition to imaging at multiple spatial scales ranging from micro- to nanometer, AFMs are commonly used as nanomechanical probes. This is pertinent for cell biology, as it has been demonstrated that the geometrical and mechanical properties of the extracellular microenvironment are important in such processes as cancer, cardiovascular disease, muscular dystrophy, and even the control of cell life and death. Indeed, the ability to control and quantify these external geometrical and mechanical parameters arises as a key issue in the field. Because AFM can quantitatively measure the mechanical properties of various biological samples, novel insights to cell function and to cell-substrate interactions are now possible. As the application of AFM to these types of problems is widened, it is important to understand the performance envelope of the technique and its associated data analyses. This talk will discuss the important issues that must be considered when mechanical models are applied to real-world data. Examples of the effect of different model assumptions on our understanding of the measured material properties will be shown. Furthermore, specific examples of the importance of mechanical stimuli and the micromechanical environment to the structure and function of biological materials will be presented.

Kirigami artificial muscles with complex biologically inspired morphologies

NASA Astrophysics Data System (ADS)

Sareh, Sina; Rossiter, Jonathan

2013-01-01

In this paper we present bio-inspired smart structures which exploit the actuation of flexible ionic polymer composites and the kirigami design principle. Kirigami design is used to convert planar actuators into active 3D structures capable of large out-of-plane displacement and that replicate biological mechanisms. Here we present the burstbot, a fluid control and propulsion mechanism based on the atrioventricular cuspid valve, and the vortibot, a spiral actuator based on Vorticella campanula, a ciliate protozoa. Models derived from biological counterparts are used as a platform for design optimization and actuator performance measurement. The symmetric and asymmetric fluid interactions of the burstbot are investigated and the effectiveness in fluid transport applications is demonstrated. The vortibot actuator is geometrically optimized as a camera positioner capable of 360° scanning. Experimental results for a one-turn spiral actuator show complex actuation derived from a single degree of freedom control signal.

Identifying Stride-To-Stride Control Strategies in Human Treadmill Walking

PubMed Central

Dingwell, Jonathan B.; Cusumano, Joseph P.

2015-01-01

Variability is ubiquitous in human movement, arising from internal and external noise, inherent biological redundancy, and from the neurophysiological control actions that help regulate movement fluctuations. Increased walking variability can lead to increased energetic cost and/or increased fall risk. Conversely, biological noise may be beneficial, even necessary, to enhance motor performance. Indeed, encouraging more variability actually facilitates greater improvements in some forms of locomotor rehabilitation. Thus, it is critical to identify the fundamental principles humans use to regulate stride-to-stride fluctuations in walking. This study sought to determine how humans regulate stride-to-stride fluctuations in stepping movements during treadmill walking. We developed computational models based on pre-defined goal functions to compare if subjects, from each stride to the next, tried to maintain the same speed as the treadmill, or instead stay in the same position on the treadmill. Both strategies predicted average behaviors empirically indistinguishable from each other and from that of humans. These strategies, however, predicted very different stride-to-stride fluctuation dynamics. Comparisons to experimental data showed that human stepping movements were generally well-predicted by the speed-control model, but not by the position-control model. Human subjects also exhibited no indications they corrected deviations in absolute position only intermittently: i.e., closer to the boundaries of the treadmill. Thus, humans clearly do not adopt a control strategy whose primary goal is to maintain some constant absolute position on the treadmill. Instead, humans appear to regulate their stepping movements in a way most consistent with a strategy whose primary goal is to try to maintain the same speed as the treadmill at each consecutive stride. These findings have important implications both for understanding how biological systems regulate walking in general and for being able to harness these mechanisms to develop more effective rehabilitation interventions to improve locomotor performance. PMID:25910253

Integrative Radiation Biology

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

Barcellos-Hoff, Mary Helen

We plan to study tissue-level mechanisms important to human breast radiation carcinogenesis. We propose that the cell biology of irradiated tissues reveals a coordinated multicellular damage response program in which individual cell contributions are primarily directed towards suppression of carcinogenesis and reestablishment of homeostasis. We identified transforming growth factor β1 (TGFβ) as a pivotal signal. Notably, we have discovered that TGFβ suppresses genomic instability by controlling the intrinsic DNA damage response and centrosome integrity. However, TGFβ also mediates disruption of microenvironment interactions, which drive epithelial to mesenchymal transition in irradiated human mammary epithelial cells. This apparent paradox of positive andmore » negative controls by TGFβ is the topic of the present proposal. First, we postulate that these phenotypes manifest differentially following fractionated or chronic exposures; second, that the interactions of multiple cell types in tissues modify the responses evident in this single cell type culture models. The goals are to: 1) study the effect of low dose rate and fractionated radiation exposure in combination with TGFβ on the irradiated phenotype and genomic instability of non-malignant human epithelial cells; and 2) determine whether stromal-epithelial interactions suppress the irradiated phenotype in cell culture and the humanized mammary mouse model. These data will be used to 3) develop a systems biology model that integrates radiation effects across multiple levels of tissue organization and time. Modeling multicellular radiation responses coordinated via extracellular signaling could have a significant impact on the extrapolation of human health risks from high dose to low dose/rate radiation exposure.« less

Reverse engineering and identification in systems biology: strategies, perspectives and challenges

PubMed Central

Villaverde, Alejandro F.; Banga, Julio R.

2014-01-01

The interplay of mathematical modelling with experiments is one of the central elements in systems biology. The aim of reverse engineering is to infer, analyse and understand, through this interplay, the functional and regulatory mechanisms of biological systems. Reverse engineering is not exclusive of systems biology and has been studied in different areas, such as inverse problem theory, machine learning, nonlinear physics, (bio)chemical kinetics, control theory and optimization, among others. However, it seems that many of these areas have been relatively closed to outsiders. In this contribution, we aim to compare and highlight the different perspectives and contributions from these fields, with emphasis on two key questions: (i) why are reverse engineering problems so hard to solve, and (ii) what methods are available for the particular problems arising from systems biology? PMID:24307566

Rapid biological speciation driven by tectonic evolution in New Zealand

NASA Astrophysics Data System (ADS)

Craw, Dave; Upton, Phaedra; Burridge, Christopher P.; Wallis, Graham P.; Waters, Jonathan M.

2016-02-01

Collisions between tectonic plates lead to the rise of new mountain ranges that can separate biological populations and ultimately result in new species. However, the identification of links between tectonic mountain-building and biological speciation is confounded by environmental and ecological factors. Thus, there are surprisingly few well-documented examples of direct tectonic controls on terrestrial biological speciation. Here we present examples from New Zealand, where the rapid evolution of 18 species of freshwater fishes has resulted from parallel tectonic landscape evolution. We use numerical models to reconstruct changes in the deep crustal structure and surface drainage catchments of the southern island of New Zealand over the past 25 million years. We show that the island and mountain topography evolved in six principal tectonic zones, which have distinct drainage catchments that separated fish populations. We use new and existing phylogenetic analyses of freshwater fish populations, based on over 1,000 specimens from more than 400 localities, to show that fish genomes can retain evidence of this tectonic landscape development, with a clear correlation between geologic age and extent of DNA sequence divergence. We conclude that landscape evolution has controlled on-going biological diversification over the past 25 million years.

A Virtual Look at Epstein–Barr Virus Infection: Biological Interpretations

PubMed Central

Delgado-Eckert, Edgar; Hadinoto, Vey; Jarrah, Abdul S; Laubenbacher, Reinhard; Lee, Kichol; Luzuriaga, Katherine; Polys, Nicholas F; Thorley-Lawson, David A

2007-01-01

The possibility of using computer simulation and mathematical modeling to gain insight into biological and other complex systems is receiving increased attention. However, it is as yet unclear to what extent these techniques will provide useful biological insights or even what the best approach is. Epstein–Barr virus (EBV) provides a good candidate to address these issues. It persistently infects most humans and is associated with several important diseases. In addition, a detailed biological model has been developed that provides an intricate understanding of EBV infection in the naturally infected human host and accounts for most of the virus' diverse and peculiar properties. We have developed an agent-based computer model/simulation (PathSim, Pathogen Simulation) of this biological model. The simulation is performed on a virtual grid that represents the anatomy of the tonsils of the nasopharyngeal cavity (Waldeyer ring) and the peripheral circulation—the sites of EBV infection and persistence. The simulation is presented via a user friendly visual interface and reproduces quantitative and qualitative aspects of acute and persistent EBV infection. The simulation also had predictive power in validation experiments involving certain aspects of viral infection dynamics. Moreover, it allows us to identify switch points in the infection process that direct the disease course towards the end points of persistence, clearance, or death. Lastly, we were able to identify parameter sets that reproduced aspects of EBV-associated diseases. These investigations indicate that such simulations, combined with laboratory and clinical studies and animal models, will provide a powerful approach to investigating and controlling EBV infection, including the design of targeted anti-viral therapies. PMID:17953479

Impact of Release Rates on the Effectiveness of Augmentative Biological Control Agents

PubMed Central

Crowder, David W.

2007-01-01

To access the effect of augmentative biological control agents, 31 articles were reviewed that investigated the impact of release rates of 35 augmentative biological control agents on the control of 42 arthropod pests. In 64% of the cases, the release rate of the biological control agent did not significantly affect the density or mortality of the pest insect. Results where similar when parasitoidsor predators were utilized as the natural enemy. Within any order of natural enemy, there were more cases where release rates did not affect augmentative biological control than cases where release rates were significant. There were more cases in which release rates did not affect augmentative biological control when pests were from the orders Hemiptera, Acari, or Diptera, but not with pests from the order Lepidoptera. In most cases, there was an optimal release rate that produced effective control of a pest species. This was especially true when predators were used as a biological control agent. Increasing the release rate above the optimal rate did not improve control of the pest and thus would be economically detrimental. Lower release rates were of ten optimal when biological control was used in conjunction with insecticides. In many cases, the timing and method of biological control applications were more significant factors impacting the effectiveness of biological control than the release rate. Additional factors that may limit the relative impact of release rates include natural enemy fecundity, establishment rates, prey availability, dispersal, and cannibalism. PMID:20307240

An autonomous molecular computer for logical control of gene expression

PubMed Central

Benenson, Yaakov; Gil, Binyamin; Ben-Dor, Uri; Adar, Rivka; Shapiro, Ehud

2013-01-01

Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems1–7. Recently, simple molecular-scale autonomous programmable computers were demonstrated8–15 allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for ‘logical’ control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton12–17; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes18–22 associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug. PMID:15116117

Systems biology and mechanics of growth.

PubMed

Eskandari, Mona; Kuhl, Ellen

2015-01-01

In contrast to inert systems, living biological systems have the advantage to adapt to their environment through growth and evolution. This transfiguration is evident during embryonic development, when the predisposed need to grow allows form to follow function. Alterations in the equilibrium state of biological systems breed disease and mutation in response to environmental triggers. The need to characterize the growth of biological systems to better understand these phenomena has motivated the continuum theory of growth and stimulated the development of computational tools in systems biology. Biological growth in development and disease is increasingly studied using the framework of morphoelasticity. Here, we demonstrate the potential for morphoelastic simulations through examples of volume, area, and length growth, inspired by tumor expansion, chronic bronchitis, brain development, intestine formation, plant shape, and myopia. We review the systems biology of living systems in light of biochemical and optical stimuli and classify different types of growth to facilitate the design of growth models for various biological systems within this generic framework. Exploring the systems biology of growth introduces a new venue to control and manipulate embryonic development, disease progression, and clinical intervention. © 2015 Wiley Periodicals, Inc.

Effects of species biological traits and environmental heterogeneity on simulated tree species distribution shifts under climate change.

PubMed

Wang, Wen J; He, Hong S; Thompson, Frank R; Spetich, Martin A; Fraser, Jacob S

2018-09-01

Demographic processes (fecundity, dispersal, colonization, growth, and mortality) and their interactions with environmental changes are not well represented in current climate-distribution models (e.g., niche and biophysical process models) and constitute a large uncertainty in projections of future tree species distribution shifts. We investigate how species biological traits and environmental heterogeneity affect species distribution shifts. We used a species-specific, spatially explicit forest dynamic model LANDIS PRO, which incorporates site-scale tree species demography and competition, landscape-scale dispersal and disturbances, and regional-scale abiotic controls, to simulate the distribution shifts of four representative tree species with distinct biological traits in the central hardwood forest region of United States. Our results suggested that biological traits (e.g., dispersal capacity, maturation age) were important for determining tree species distribution shifts. Environmental heterogeneity, on average, reduced shift rates by 8% compared to perfect environmental conditions. The average distribution shift rates ranged from 24 to 200myear -1 under climate change scenarios, implying that many tree species may not able to keep up with climate change because of limited dispersal capacity, long generation time, and environmental heterogeneity. We suggest that climate-distribution models should include species demographic processes (e.g., fecundity, dispersal, colonization), biological traits (e.g., dispersal capacity, maturation age), and environmental heterogeneity (e.g., habitat fragmentation) to improve future predictions of species distribution shifts in response to changing climates. Copyright © 2018 Elsevier B.V. All rights reserved.

Real-time product attribute control to manufacture antibodies with defined N-linked glycan levels.

PubMed

Zupke, Craig; Brady, Lowell J; Slade, Peter G; Clark, Philip; Caspary, R Guy; Livingston, Brittney; Taylor, Lisa; Bigham, Kyle; Morris, Arvia E; Bailey, Robert W

2015-01-01

Pressures for cost-effective new therapies and an increased emphasis on emerging markets require technological advancements and a flexible future manufacturing network for the production of biologic medicines. The safety and efficacy of a product is crucial, and consistent product quality is an essential feature of any therapeutic manufacturing process. The active control of product quality in a typical biologic process is challenging because of measurement lags and nonlinearities present in the system. The current study uses nonlinear model predictive control to maintain a critical product quality attribute at a predetermined value during pilot scale manufacturing operations. This approach to product quality control ensures a more consistent product for patients, enables greater manufacturing efficiency, and eliminates the need for extensive process characterization by providing direct measures of critical product quality attributes for real time release of drug product. © 2015 American Institute of Chemical Engineers.

Modeling of Receptor Tyrosine Kinase Signaling: Computational and Experimental Protocols.

PubMed

Fey, Dirk; Aksamitiene, Edita; Kiyatkin, Anatoly; Kholodenko, Boris N

2017-01-01

The advent of systems biology has convincingly demonstrated that the integration of experiments and dynamic modelling is a powerful approach to understand the cellular network biology. Here we present experimental and computational protocols that are necessary for applying this integrative approach to the quantitative studies of receptor tyrosine kinase (RTK) signaling networks. Signaling by RTKs controls multiple cellular processes, including the regulation of cell survival, motility, proliferation, differentiation, glucose metabolism, and apoptosis. We describe methods of model building and training on experimentally obtained quantitative datasets, as well as experimental methods of obtaining quantitative dose-response and temporal dependencies of protein phosphorylation and activities. The presented methods make possible (1) both the fine-grained modeling of complex signaling dynamics and identification of salient, course-grained network structures (such as feedback loops) that bring about intricate dynamics, and (2) experimental validation of dynamic models.

BioModels Database: a repository of mathematical models of biological processes.

PubMed

Chelliah, Vijayalakshmi; Laibe, Camille; Le Novère, Nicolas

2013-01-01

BioModels Database is a public online resource that allows storing and sharing of published, peer-reviewed quantitative, dynamic models of biological processes. The model components and behaviour are thoroughly checked to correspond the original publication and manually curated to ensure reliability. Furthermore, the model elements are annotated with terms from controlled vocabularies as well as linked to relevant external data resources. This greatly helps in model interpretation and reuse. Models are stored in SBML format, accepted in SBML and CellML formats, and are available for download in various other common formats such as BioPAX, Octave, SciLab, VCML, XPP and PDF, in addition to SBML. The reaction network diagram of the models is also available in several formats. BioModels Database features a search engine, which provides simple and more advanced searches. Features such as online simulation and creation of smaller models (submodels) from the selected model elements of a larger one are provided. BioModels Database can be accessed both via a web interface and programmatically via web services. New models are available in BioModels Database at regular releases, about every 4 months.

A biologically inspired meta-control navigation system for the Psikharpax rat robot.

PubMed

Caluwaerts, K; Staffa, M; N'Guyen, S; Grand, C; Dollé, L; Favre-Félix, A; Girard, B; Khamassi, M

2012-06-01

A biologically inspired navigation system for the mobile rat-like robot named Psikharpax is presented, allowing for self-localization and autonomous navigation in an initially unknown environment. The ability of parts of the model (e.g. the strategy selection mechanism) to reproduce rat behavioral data in various maze tasks has been validated before in simulations. But the capacity of the model to work on a real robot platform had not been tested. This paper presents our work on the implementation on the Psikharpax robot of two independent navigation strategies (a place-based planning strategy and a cue-guided taxon strategy) and a strategy selection meta-controller. We show how our robot can memorize which was the optimal strategy in each situation, by means of a reinforcement learning algorithm. Moreover, a context detector enables the controller to quickly adapt to changes in the environment-recognized as new contexts-and to restore previously acquired strategy preferences when a previously experienced context is recognized. This produces adaptivity closer to rat behavioral performance and constitutes a computational proposition of the role of the rat prefrontal cortex in strategy shifting. Moreover, such a brain-inspired meta-controller may provide an advancement for learning architectures in robotics.

Single neuron modeling and data assimilation in BNST neurons

NASA Astrophysics Data System (ADS)

Farsian, Reza

Neurons, although tiny in size, are vastly complicated systems, which are responsible for the most basic yet essential functions of any nervous system. Even the most simple models of single neurons are usually high dimensional, nonlinear, and contain many parameters and states which are unobservable in a typical neurophysiological experiment. One of the most fundamental problems in experimental neurophysiology is the estimation of these parameters and states, since knowing their values is essential in identification, model construction, and forward prediction of biological neurons. Common methods of parameter and state estimation do not perform well for neural models due to their high dimensionality and nonlinearity. In this dissertation, two alternative approaches for parameters and state estimation of biological neurons have been demonstrated: dynamical parameter estimation (DPE) and a Markov Chain Monte Carlo (MCMC) method. The first method uses elements of chaos control and synchronization theory for parameter and state estimation. MCMC is a statistical approach which uses a path integral formulation to evaluate a mean and an error bound for these unobserved parameters and states. These methods have been applied to biological system of neurons in Bed Nucleus of Stria Termialis neurons (BNST) of rats. State and parameters of neurons in both systems were estimated, and their value were used for recreating a realistic model and predicting the behavior of the neurons successfully. The knowledge of biological parameters can ultimately provide a better understanding of the internal dynamics of a neuron in order to build robust models of neuron networks.

Molecular mechanisms of system responses to novel stimuli are predictable from public data

PubMed Central

Danziger, Samuel A.; Ratushny, Alexander V.; Smith, Jennifer J.; Saleem, Ramsey A.; Wan, Yakun; Arens, Christina E.; Armstrong, Abraham M.; Sitko, Katherine; Chen, Wei-Ming; Chiang, Jung-Hsien; Reiss, David J.; Baliga, Nitin S.; Aitchison, John D.

2014-01-01

Systems scale models provide the foundation for an effective iterative cycle between hypothesis generation, experiment and model refinement. Such models also enable predictions facilitating the understanding of biological complexity and the control of biological systems. Here, we demonstrate the reconstruction of a globally predictive gene regulatory model from public data: a model that can drive rational experiment design and reveal new regulatory mechanisms underlying responses to novel environments. Specifically, using ∼1500 publically available genome-wide transcriptome data sets from Saccharomyces cerevisiae, we have reconstructed an environment and gene regulatory influence network that accurately predicts regulatory mechanisms and gene expression changes on exposure of cells to completely novel environments. Focusing on transcriptional networks that induce peroxisomes biogenesis, the model-guided experiments allow us to expand a core regulatory network to include novel transcriptional influences and linkage across signaling and transcription. Thus, the approach and model provides a multi-scalar picture of gene dynamics and are powerful resources for exploiting extant data to rationally guide experimentation. The techniques outlined here are generally applicable to any biological system, which is especially important when experimental systems are challenging and samples are difficult and expensive to obtain—a common problem in laboratory animal and human studies. PMID:24185701

Mathematical Models for Predicting Development of Orius majusculus (Heteroptera: Anthocoridae) and Its Applicability to Biological Control.

PubMed

Martínez-García, Héctor; Aragón-Sánchez, Miguel; Sáenz-Romo, María G; Román-Fernández, Luis R; Veas-Bernal, Ariadna; Marco-Mancebón, Vicente S; Pérez-Moreno, Ignacio

2018-05-19

Complete development of Orius majusculus Reuter (Heteroptera: Anthocoridae) at nine constant temperatures, between 12 and 34°C, was evaluated under laboratory conditions. The maximum developmental period of 90.75 d occurred at 12°C, whereas the minimum of 11.34 d occurred at 30°C. From 30 to 34°C, the developmental period increased to 13.50 d. Between 21 and 33°C the survival rate was more than 80%. The optimal temperature when considering developmental rate and survival was between 24 and 30°C. At constant temperatures, four models were developed, one of which was linear and three nonlinear (Logan type III, Lactin, and Brière). All models were validated under field conditions and diel temperature variations. The values of the adjusted determination coefficients of the linear (>0.77) and nonlinear models (>0.93) were high. The thermal requirement for complete development, from egg to adult, was 284.5 degree-days (DD). In all nonlinear models, elevated levels of accuracy (≥90.31%) in field validation were also obtained, especially in the Brière model. With the results obtained herein, the optimization of O. majusculus mass rearing, its ideal use, and field management in biological control strategies can be improved.

Biological agents for controlling excessive scarring.

PubMed

Berman, Brian

2010-01-01

The potential of various biological agents to reduce or prevent excessive scar formation has now been evaluated in numerous in-vitro studies, experimental animal models and preliminary clinical trials, in some cases with particularly promising results. Perhaps prominent among this group of biological agents, and, to some degree, possibly representing marketed compounds already being used 'off label' to manage excessive scarring, are the tumor necrosis factor alpha antagonist etanercept, and immune-response modifiers such as IFNalpha2b and imiquimod. Additional assessment of these novel agents is now justified with a view to reducing or preventing hypertrophic scars, keloid scars and the recurrence of post-excision keloid lesions.

Biological Bases of Space Radiation Risk

NASA Technical Reports Server (NTRS)

1997-01-01

In this session, Session JP4, the discussion focuses on the following topics: Hematopoiesis Dynamics in Irradiated Mammals, Mathematical Modeling; Estimating Health Risks in Space from Galactic Cosmic Rays; Failure of Heavy Ions to Affect Physiological Integrity of the Corneal Endothelial Monolayer; Application of an Unbiased Two-Gel CDNA Library Screening Method to Expression Monitoring of Genes in Irradiated Versus Control Cells; Detection of Radiation-Induced DNA Strand Breaks in Mammalian Cells By Enzymatic Post-Labeling; Evaluation of Bleomycin-Induced Chromosome Aberrations Under Microgravity Conditions in Human Lymphocytes, Using "Fish" Techniques; Technical Description of the Space Exposure Biology Assembly Seba on ISS; and Cytogenetic Research in Biological Dosimetry.

Using biological control research in the classroom to promote scientific inquiry and literacy

USDA-ARS?s Scientific Manuscript database

Many scientists who research biological control also teach at universities or more informally through cooperative outreach. The purpose of this paper is to review biological control activities for the classroom in four refereed journals, The American Biology Teacher, Journal of Biological Education...

The sensitivity of Turing self-organization to biological feedback delays: 2D models of fish pigmentation.

PubMed

Gaffney, E A; Lee, S Seirin

2015-03-01

Turing morphogen models have been extensively explored in the context of large-scale self-organization in multicellular biological systems. However, reconciling the detailed biology of morphogen dynamics, while accounting for time delays associated with gene expression, reveals aberrant behaviours that are not consistent with early developmental self-organization, especially the requirement for exquisite temporal control. Attempts to reconcile the interpretation of Turing's ideas with an increasing understanding of the mechanisms driving zebrafish pigmentation suggests that one should reconsider Turing's model in terms of pigment cells rather than morphogens (Nakamasu et al., 2009, PNAS, 106: , 8429-8434; Yamaguchi et al., 2007, PNAS, 104: , 4790-4793). Here the dynamics of pigment cells is subject to response delays implicit in the cell cycle and apoptosis. Hence we explore simulations of fish skin patterning, focussing on the dynamical influence of gene expression delays in morphogen-based Turing models and response delays for cell-based Turing models. We find that reconciling the mechanisms driving the behaviour of Turing systems with observations of fish skin patterning remains a fundamental challenge. © The Authors 2013. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Modeling of short-term mechanism of arterial pressure control in the cardiovascular system: object-oriented and acausal approach.

PubMed

Kulhánek, Tomáš; Kofránek, Jiří; Mateják, Marek

2014-11-01

This letter introduces an alternative approach to modeling the cardiovascular system with a short-term control mechanism published in Computers in Biology and Medicine, Vol. 47 (2014), pp. 104-112. We recommend using abstract components on a distinct physical level, separating the model into hydraulic components, subsystems of the cardiovascular system and individual subsystems of the control mechanism and scenario. We recommend utilizing an acausal modeling feature of Modelica language, which allows model variables to be expressed declaratively. Furthermore, the Modelica tool identifies which are the dependent and independent variables upon compilation. An example of our approach is introduced on several elementary components representing the hydraulic resistance to fluid flow and the elastic response of the vessel, among others. The introduced model implementation can be more reusable and understandable for the general scientific community. Copyright © 2014 Elsevier Ltd. All rights reserved.

A habitat overlap analysis derived from maxent for tamarisk and the south-western willow flycatcher

NASA Astrophysics Data System (ADS)

York, Patricia; Evangelista, Paul; Kumar, Sunil; Graham, James; Flather, Curtis; Stohlgren, Thomas

2011-06-01

Biologic control of the introduced and invasive, woody plant tamarisk ( Tamarix spp, saltcedar) in south-western states is controversial because it affects habitat of the federally endangered South-western Willow Flycatcher ( Empidonax traillii extimus). These songbirds sometimes nest in tamarisk where floodplain-level invasion replaces native habitats. Biologic control, with the saltcedar leaf beetle ( Diorhabda elongate), began along the Virgin River, Utah, in 2006, enhancing the need for comprehensive understanding of the tamarisk-flycatcher relationship. We used maximum entropy (Maxent) modeling to separately quantify the current extent of dense tamarisk habitat (>50% cover) and the potential extent of habitat available for E. traillii extimus within the studied watersheds. We used transformations of 2008 Landsat Thematic Mapper images and a digital elevation model as environmental input variables. Maxent models performed well for the flycatcher and tamarisk with Area Under the ROC Curve (AUC) values of 0.960 and 0.982, respectively. Classification of thresholds and comparison of the two Maxent outputs indicated moderate spatial overlap between predicted suitable habitat for E. traillii extimus and predicted locations with dense tamarisk stands, where flycatcher habitat will potentially change flycatcher habitats. Dense tamarisk habitat comprised 500 km2 within the study area, of which 11.4% was also modeled as potential habitat for E. traillii extimus. Potential habitat modeled for the flycatcher constituted 190 km2, of which 30.7% also contained dense tamarisk habitat. Results showed that both native vegetation and dense tamarisk habitats exist in the study area and that most tamarisk infestations do not contain characteristics that satisfy the habitat requirements of E. traillii extimus. Based on this study, effective biologic control of Tamarix spp. may, in the short term, reduce suitable habitat available to E. traillii extimus, but also has the potential in the long term to increase suitable habitat if appropriate mixes of native woody vegetation replace tamarisk in biocontrol areas.

A Computational Model of the Rainbow Trout Hypothalamus-Pituitary-Ovary-Liver Axis

PubMed Central

Gillies, Kendall; Krone, Stephen M.; Nagler, James J.; Schultz, Irvin R.

2016-01-01

Reproduction in fishes and other vertebrates represents the timely coordination of many endocrine factors that culminate in the production of mature, viable gametes. In recent years there has been rapid growth in understanding fish reproductive biology, which has been motivated in part by recognition of the potential effects that climate change, habitat destruction and contaminant exposure can have on natural and cultured fish populations. New approaches to understanding the impacts of these stressors are being developed that require a systems biology approach with more biologically accurate and detailed mathematical models. We have developed a multi-scale mathematical model of the female rainbow trout hypothalamus-pituitary-ovary-liver axis to use as a tool to help understand the functioning of the system and for extrapolation of laboratory findings of stressor impacts on specific components of the axis. The model describes the essential endocrine components of the female rainbow trout reproductive axis. The model also describes the stage specific growth of maturing oocytes within the ovary and permits the presence of sub-populations of oocytes at different stages of development. Model formulation and parametrization was largely based on previously published in vivo and in vitro data in rainbow trout and new data on the synthesis of gonadotropins in the pituitary. Model predictions were validated against several previously published data sets for annual changes in gonadotropins and estradiol in rainbow trout. Estimates of select model parameters can be obtained from in vitro assays using either quantitative (direct estimation of rate constants) or qualitative (relative change from control values) approaches. This is an important aspect of mathematical models as in vitro, cell-based assays are expected to provide the bulk of experimental data for future risk assessments and will require quantitative physiological models to extrapolate across biological scales. PMID:27096735

A Computational Model of the Rainbow Trout Hypothalamus-Pituitary-Ovary-Liver Axis.

PubMed

Gillies, Kendall; Krone, Stephen M; Nagler, James J; Schultz, Irvin R

2016-04-01

Reproduction in fishes and other vertebrates represents the timely coordination of many endocrine factors that culminate in the production of mature, viable gametes. In recent years there has been rapid growth in understanding fish reproductive biology, which has been motivated in part by recognition of the potential effects that climate change, habitat destruction and contaminant exposure can have on natural and cultured fish populations. New approaches to understanding the impacts of these stressors are being developed that require a systems biology approach with more biologically accurate and detailed mathematical models. We have developed a multi-scale mathematical model of the female rainbow trout hypothalamus-pituitary-ovary-liver axis to use as a tool to help understand the functioning of the system and for extrapolation of laboratory findings of stressor impacts on specific components of the axis. The model describes the essential endocrine components of the female rainbow trout reproductive axis. The model also describes the stage specific growth of maturing oocytes within the ovary and permits the presence of sub-populations of oocytes at different stages of development. Model formulation and parametrization was largely based on previously published in vivo and in vitro data in rainbow trout and new data on the synthesis of gonadotropins in the pituitary. Model predictions were validated against several previously published data sets for annual changes in gonadotropins and estradiol in rainbow trout. Estimates of select model parameters can be obtained from in vitro assays using either quantitative (direct estimation of rate constants) or qualitative (relative change from control values) approaches. This is an important aspect of mathematical models as in vitro, cell-based assays are expected to provide the bulk of experimental data for future risk assessments and will require quantitative physiological models to extrapolate across biological scales.

Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization

PubMed Central

Hiraishi, Kunihiko

2014-01-01

One of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GRNs to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of GRNs, and gene expression is expressed by a binary value (ON or OFF). In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. For CS-PBNs, the verification problem and the optimal control problem are considered. For the verification problem, a solution method using the probabilistic model checker PRISM is proposed. For the optimal control problem, a solution method using polynomial optimization is proposed. Finally, a numerical example on the WNT5A network, which is related to melanoma, is presented. The proposed methods provide us useful tools in control theory of GRNs. PMID:24587766

Access and benefit sharing (ABS) under the convention on biological diversity (CBD): implications for microbial biological control

USDA-ARS?s Scientific Manuscript database

Researchers and implementers of biological control are confronted with a variety of scientific, regulatory and administrative challenges to their biological control programs. One developing challenge will arise from the implementation of provisions of the Convention on Biological Diversity (CBD) co...

Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling

PubMed Central

Dick, Thomas E.; Molkov, Yaroslav I.; Nieman, Gary; Hsieh, Yee-Hsee; Jacono, Frank J.; Doyle, John; Scheff, Jeremy D.; Calvano, Steve E.; Androulakis, Ioannis P.; An, Gary; Vodovotz, Yoram

2012-01-01

Acute inflammation leads to organ failure by engaging catastrophic feedback loops in which stressed tissue evokes an inflammatory response and, in turn, inflammation damages tissue. Manifestations of this maladaptive inflammatory response include cardio-respiratory dysfunction that may be reflected in reduced heart rate and ventilatory pattern variabilities. We have developed signal-processing algorithms that quantify non-linear deterministic characteristics of variability in biologic signals. Now, coalescing under the aegis of the NIH Computational Biology Program and the Society for Complexity in Acute Illness, two research teams performed iterative experiments and computational modeling on inflammation and cardio-pulmonary dysfunction in sepsis as well as on neural control of respiration and ventilatory pattern variability. These teams, with additional collaborators, have recently formed a multi-institutional, interdisciplinary consortium, whose goal is to delineate the fundamental interrelationship between the inflammatory response and physiologic variability. Multi-scale mathematical modeling and complementary physiological experiments will provide insight into autonomic neural mechanisms that may modulate the inflammatory response to sepsis and simultaneously reduce heart rate and ventilatory pattern variabilities associated with sepsis. This approach integrates computational models of neural control of breathing and cardio-respiratory coupling with models that combine inflammation, cardiovascular function, and heart rate variability. The resulting integrated model will provide mechanistic explanations for the phenomena of respiratory sinus-arrhythmia and cardio-ventilatory coupling observed under normal conditions, and the loss of these properties during sepsis. This approach holds the potential of modeling cross-scale physiological interactions to improve both basic knowledge and clinical management of acute inflammatory diseases such as sepsis and trauma. PMID:22783197

Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling.

PubMed

Dick, Thomas E; Molkov, Yaroslav I; Nieman, Gary; Hsieh, Yee-Hsee; Jacono, Frank J; Doyle, John; Scheff, Jeremy D; Calvano, Steve E; Androulakis, Ioannis P; An, Gary; Vodovotz, Yoram

2012-01-01

Acute inflammation leads to organ failure by engaging catastrophic feedback loops in which stressed tissue evokes an inflammatory response and, in turn, inflammation damages tissue. Manifestations of this maladaptive inflammatory response include cardio-respiratory dysfunction that may be reflected in reduced heart rate and ventilatory pattern variabilities. We have developed signal-processing algorithms that quantify non-linear deterministic characteristics of variability in biologic signals. Now, coalescing under the aegis of the NIH Computational Biology Program and the Society for Complexity in Acute Illness, two research teams performed iterative experiments and computational modeling on inflammation and cardio-pulmonary dysfunction in sepsis as well as on neural control of respiration and ventilatory pattern variability. These teams, with additional collaborators, have recently formed a multi-institutional, interdisciplinary consortium, whose goal is to delineate the fundamental interrelationship between the inflammatory response and physiologic variability. Multi-scale mathematical modeling and complementary physiological experiments will provide insight into autonomic neural mechanisms that may modulate the inflammatory response to sepsis and simultaneously reduce heart rate and ventilatory pattern variabilities associated with sepsis. This approach integrates computational models of neural control of breathing and cardio-respiratory coupling with models that combine inflammation, cardiovascular function, and heart rate variability. The resulting integrated model will provide mechanistic explanations for the phenomena of respiratory sinus-arrhythmia and cardio-ventilatory coupling observed under normal conditions, and the loss of these properties during sepsis. This approach holds the potential of modeling cross-scale physiological interactions to improve both basic knowledge and clinical management of acute inflammatory diseases such as sepsis and trauma.

An approach to the mathematical modelling of a controlled ecological life support system

NASA Technical Reports Server (NTRS)

Averner, M. M.

1981-01-01

An approach to the design of a computer based model of a closed ecological life-support system suitable for use in extraterrestrial habitats is presented. The model is based on elemental mass balance and contains representations of the metabolic activities of biological components. The model can be used as a tool in evaluating preliminary designs for closed regenerative life support systems and as a method for predicting the behavior of such systems.

Green Jobs: Definition and Method of Appraisal of Chemical and Biological Risks.

PubMed

Cheneval, Erwan; Busque, Marc-Antoine; Ostiguy, Claude; Lavoie, Jacques; Bourbonnais, Robert; Labrèche, France; Bakhiyi, Bouchra; Zayed, Joseph

2016-04-01

In the wake of sustainable development, green jobs are developing rapidly, changing the work environment. However a green job is not automatically a safe job. The aim of the study was to define green jobs, and to establish a preliminary risk assessment of chemical substances and biological agents for workers in Quebec. An operational definition was developed, along with criteria and sustainable development principles to discriminate green jobs from regular jobs. The potential toxicity or hazard associated with their chemical and biological exposures was assessed, and the workers' exposure appraised using an expert assessment method. A control banding approach was then used to assess risks for workers in selected green jobs. A double entry model allowed us to set priorities in terms of chemical or biological risk. Among jobs that present the highest risk potential, several are related to waste management. The developed method is flexible and could be adapted to better appraise the risks that workers are facing or to propose control measures. © The Author 2015. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Inverse biomimetics: how robots can help to verify concepts concerning sensorimotor control of human arm and leg movements.

PubMed

Kalveram, Karl Theodor; Seyfarth, André

2009-01-01

Simulation test, hardware test and behavioral comparison test are proposed to experimentally verify whether a technical control concept for limb movements is logically precise, physically sound, and biologically relevant. Thereby, robot test-beds may play an integral part by mimicking functional limb movements. The procedure is exemplarily demonstrated for human aiming movements with the forearm: when comparing competitive control concepts, these movements are described best by a spring-like operating muscular-skeletal device which is assisted by feedforward control through an inverse internal model of the limb--without regress to a forward model of the limb. In a perspective on hopping, the concept of exploitive control is addressed, and its comparison to concepts derived from classical control theory advised.

Adaptive Proactive Inhibitory Control for Embedded Real-Time Applications

PubMed Central

Yang, Shufan; McGinnity, T. Martin; Wong-Lin, KongFatt

2012-01-01

Psychologists have studied the inhibitory control of voluntary movement for many years. In particular, the countermanding of an impending action has been extensively studied. In this work, we propose a neural mechanism for adaptive inhibitory control in a firing-rate type model based on current findings in animal electrophysiological and human psychophysical experiments. We then implement this model on a field-programmable gate array (FPGA) prototyping system, using dedicated real-time hardware circuitry. Our results show that the FPGA-based implementation can run in real-time while achieving behavioral performance qualitatively suggestive of the animal experiments. Implementing such biological inhibitory control in an embedded device can lead to the development of control systems that may be used in more realistic cognitive robotics or in neural prosthetic systems aiding human movement control. PMID:22701420

Applying ecological and evolutionary theory to cancer: a long and winding road.

PubMed

Thomas, Frédéric; Fisher, Daniel; Fort, Philippe; Marie, Jean-Pierre; Daoust, Simon; Roche, Benjamin; Grunau, Christoph; Cosseau, Céline; Mitta, Guillaume; Baghdiguian, Stephen; Rousset, François; Lassus, Patrice; Assenat, Eric; Grégoire, Damien; Missé, Dorothée; Lorz, Alexander; Billy, Frédérique; Vainchenker, William; Delhommeau, François; Koscielny, Serge; Itzykson, Raphael; Tang, Ruoping; Fava, Fanny; Ballesta, Annabelle; Lepoutre, Thomas; Krasinska, Liliana; Dulic, Vjekoslav; Raynaud, Peggy; Blache, Philippe; Quittau-Prevostel, Corinne; Vignal, Emmanuel; Trauchessec, Hélène; Perthame, Benoit; Clairambault, Jean; Volpert, Vitali; Solary, Eric; Hibner, Urszula; Hochberg, Michael E

2013-01-01

Since the mid 1970s, cancer has been described as a process of Darwinian evolution, with somatic cellular selection and evolution being the fundamental processes leading to malignancy and its many manifestations (neoangiogenesis, evasion of the immune system, metastasis, and resistance to therapies). Historically, little attention has been placed on applications of evolutionary biology to understanding and controlling neoplastic progression and to prevent therapeutic failures. This is now beginning to change, and there is a growing international interest in the interface between cancer and evolutionary biology. The objective of this introduction is first to describe the basic ideas and concepts linking evolutionary biology to cancer. We then present four major fronts where the evolutionary perspective is most developed, namely laboratory and clinical models, mathematical models, databases, and techniques and assays. Finally, we discuss several of the most promising challenges and future prospects in this interdisciplinary research direction in the war against cancer.

Artificial Immune System Approaches for Aerospace Applications

NASA Technical Reports Server (NTRS)

KrishnaKumar, Kalmanje; Koga, Dennis (Technical Monitor)

2002-01-01

Artificial Immune Systems (AIS) combine a priori knowledge with the adapting capabilities of biological immune system to provide a powerful alternative to currently available techniques for pattern recognition, modeling, design, and control. Immunology is the science of built-in defense mechanisms that are present in all living beings to protect against external attacks. A biological immune system can be thought of as a robust, adaptive system that is capable of dealing with an enormous variety of disturbances and uncertainties. Biological immune systems use a finite number of discrete "building blocks" to achieve this adaptiveness. These building blocks can be thought of as pieces of a puzzle which must be put together in a specific way-to neutralize, remove, or destroy each unique disturbance the system encounters. In this paper, we outline AIS models that are immediately applicable to aerospace problems and identify application areas that need further investigation.

Assessing Probabilistic Risk Assessment Approaches for Insect Biological Control Introductions.

PubMed

Kaufman, Leyla V; Wright, Mark G

2017-07-07

The introduction of biological control agents to new environments requires host specificity tests to estimate potential non-target impacts of a prospective agent. Currently, the approach is conservative, and is based on physiological host ranges determined under captive rearing conditions, without consideration for ecological factors that may influence realized host range. We use historical data and current field data from introduced parasitoids that attack an endemic Lepidoptera species in Hawaii to validate a probabilistic risk assessment (PRA) procedure for non-target impacts. We use data on known host range and habitat use in the place of origin of the parasitoids to determine whether contemporary levels of non-target parasitism could have been predicted using PRA. Our results show that reasonable predictions of potential non-target impacts may be made if comprehensive data are available from places of origin of biological control agents, but scant data produce poor predictions. Using apparent mortality data rather than marginal attack rate estimates in PRA resulted in over-estimates of predicted non-target impact. Incorporating ecological data into PRA models improved the predictive power of the risk assessments.

Assessing Probabilistic Risk Assessment Approaches for Insect Biological Control Introductions

PubMed Central

Kaufman, Leyla V.; Wright, Mark G.

2017-01-01

The introduction of biological control agents to new environments requires host specificity tests to estimate potential non-target impacts of a prospective agent. Currently, the approach is conservative, and is based on physiological host ranges determined under captive rearing conditions, without consideration for ecological factors that may influence realized host range. We use historical data and current field data from introduced parasitoids that attack an endemic Lepidoptera species in Hawaii to validate a probabilistic risk assessment (PRA) procedure for non-target impacts. We use data on known host range and habitat use in the place of origin of the parasitoids to determine whether contemporary levels of non-target parasitism could have been predicted using PRA. Our results show that reasonable predictions of potential non-target impacts may be made if comprehensive data are available from places of origin of biological control agents, but scant data produce poor predictions. Using apparent mortality data rather than marginal attack rate estimates in PRA resulted in over-estimates of predicted non-target impact. Incorporating ecological data into PRA models improved the predictive power of the risk assessments. PMID:28686180

Dissecting innate immune responses with the tools of systems biology.

PubMed

Smith, Kelly D; Bolouri, Hamid

2005-02-01

Systems biology strives to derive accurate predictive descriptions of complex systems such as innate immunity. The innate immune system is essential for host defense, yet the resulting inflammatory response must be tightly regulated. Current understanding indicates that this system is controlled by complex regulatory networks, which maintain homoeostasis while accurately distinguishing pathogenic infections from harmless exposures. Recent studies have used high throughput technologies and computational techniques that presage predictive models and will be the foundation of a systems level understanding of innate immunity.

Cyber integrated MEMS microhand for biological applications

NASA Astrophysics Data System (ADS)

Weissman, Adam; Frazier, Athena; Pepen, Michael; Lu, Yen-Wen; Yang, Shanchieh Jay

2009-05-01

Anthropomorphous robotic hands at microscales have been developed to receive information and perform tasks for biological applications. To emulate a human hand's dexterity, the microhand requires a master-slave interface with a wearable controller, force sensors, and perception displays for tele-manipulation. Recognizing the constraints and complexity imposed in developing feedback interface during miniaturization, this project address the need by creating an integrated cyber environment incorporating sensors with a microhand, haptic/visual display, and object model, to emulates human hands' psychophysical perception at microscale.

Hearing Tests on Mobile Devices: Evaluation of the Reference Sound Level by Means of Biological Calibration.

PubMed

Masalski, Marcin; Kipiński, Lech; Grysiński, Tomasz; Kręcicki, Tomasz

2016-05-30

Hearing tests carried out in home setting by means of mobile devices require previous calibration of the reference sound level. Mobile devices with bundled headphones create a possibility of applying the predefined level for a particular model as an alternative to calibrating each device separately. The objective of this study was to determine the reference sound level for sets composed of a mobile device and bundled headphones. Reference sound levels for Android-based mobile devices were determined using an open access mobile phone app by means of biological calibration, that is, in relation to the normal-hearing threshold. The examinations were conducted in 2 groups: an uncontrolled and a controlled one. In the uncontrolled group, the fully automated self-measurements were carried out in home conditions by 18- to 35-year-old subjects, without prior hearing problems, recruited online. Calibration was conducted as a preliminary step in preparation for further examination. In the controlled group, audiologist-assisted examinations were performed in a sound booth, on normal-hearing subjects verified through pure-tone audiometry, recruited offline from among the workers and patients of the clinic. In both the groups, the reference sound levels were determined on a subject's mobile device using the Bekesy audiometry. The reference sound levels were compared between the groups. Intramodel and intermodel analyses were carried out as well. In the uncontrolled group, 8988 calibrations were conducted on 8620 different devices representing 2040 models. In the controlled group, 158 calibrations (test and retest) were conducted on 79 devices representing 50 models. Result analysis was performed for 10 most frequently used models in both the groups. The difference in reference sound levels between uncontrolled and controlled groups was 1.50 dB (SD 4.42). The mean SD of the reference sound level determined for devices within the same model was 4.03 dB (95% CI 3.93-4.11). Statistically significant differences were found across models. Reference sound levels determined in the uncontrolled group are comparable to the values obtained in the controlled group. This validates the use of biological calibration in the uncontrolled group for determining the predefined reference sound level for new devices. Moreover, due to a relatively small deviation of the reference sound level for devices of the same model, it is feasible to conduct hearing screening on devices calibrated with the predefined reference sound level.

Cell size control and homeostasis in bacteria

NASA Astrophysics Data System (ADS)

Bradde, Serena; Taheri, Sattar; Sauls, John; Hill, Nobert; Levine, Petra; Paulsson, Johan; Vergassola, Massimo; Jun, Suckjoon

2015-03-01

How cells control their size is a fundamental question in biology. The mechanisms for sensing size, time, or a combination of the two are not supported by experimental evidence. By analysing distributions of size at division at birth and generation time of hundreds of thousands of Gram-negative E. coli and Gram-positive B. subtilis cells under a wide range of tightly controlled steady-state growth conditions, we are now in the position to validate different theoretical models. In this talk I will present all possible models in details and present a general mechanism that quantitatively explains all measurable aspects of growth and cell division at both population and single-cell levels.

Multiscale mechanobiology: computational models for integrating molecules to multicellular systems

PubMed Central

Mak, Michael; Kim, Taeyoon

2015-01-01

Mechanical signals exist throughout the biological landscape. Across all scales, these signals, in the form of force, stiffness, and deformations, are generated and processed, resulting in an active mechanobiological circuit that controls many fundamental aspects of life, from protein unfolding and cytoskeletal remodeling to collective cell motions. The multiple scales and complex feedback involved present a challenge for fully understanding the nature of this circuit, particularly in development and disease in which it has been implicated. Computational models that accurately predict and are based on experimental data enable a means to integrate basic principles and explore fine details of mechanosensing and mechanotransduction in and across all levels of biological systems. Here we review recent advances in these models along with supporting and emerging experimental findings. PMID:26019013

Non-target effects of an introduced biological control agent on deer mouse ecology

Treesearch

Dean E. Pearson; Kevin S. McKelvey; Leonard F. Ruggiero

2000-01-01

Release of exotic insects as biological control agents is a common approach to controlling exotic plants. Though controversy has ensued regarding the deleterious direct effects of biological control agents to non-target species, few have examined the indirect effects of a "well-behaved" biological control agent on native fauna. We studied a grassland in west-...

Bionic models for identification of biological systems

NASA Astrophysics Data System (ADS)

Gerget, O. M.

2017-01-01

This article proposes a clinical decision support system that processes biomedical data. For this purpose a bionic model has been designed based on neural networks, genetic algorithms and immune systems. The developed system has been tested on data from pregnant women. The paper focuses on the approach to enable selection of control actions that can minimize the risk of adverse outcome. The control actions (hyperparameters of a new type) are further used as an additional input signal. Its values are defined by a hyperparameter optimization method. A software developed with Python is briefly described.

Simulations of molecular self-assembled monolayers on surfaces: packing structures, formation processes and functions tuned by intermolecular and interfacial interactions.

PubMed

Wen, Jin; Li, Wei; Chen, Shuang; Ma, Jing

2016-08-17

Surfaces modified with a functional molecular monolayer are essential for the fabrication of nano-scale electronics or machines with novel physical, chemical, and/or biological properties. Theoretical simulation based on advanced quantum chemical and classical models is at present a necessary tool in the development, design, and understanding of the interfacial nanostructure. The nanoscale surface morphology, growth processes, and functions are controlled by not only the electronic structures (molecular energy levels, dipole moments, polarizabilities, and optical properties) of building units but also the subtle balance between intermolecular and interfacial interactions. The switchable surfaces are also constructed by introducing stimuli-responsive units like azobenzene derivatives. To bridge the gap between experiments and theoretical models, opportunities and challenges for future development of modelling of ferroelectricity, entropy, and chemical reactions of surface-supported monolayers are also addressed. Theoretical simulations will allow us to obtain important and detailed information about the structure and dynamics of monolayer modified interfaces, which will guide the rational design and optimization of dynamic interfaces to meet challenges of controlling optical, electrical, and biological functions.

Peripersonal Space and Margin of Safety around the Body: Learning Visuo-Tactile Associations in a Humanoid Robot with Artificial Skin.

PubMed

Roncone, Alessandro; Hoffmann, Matej; Pattacini, Ugo; Fadiga, Luciano; Metta, Giorgio

2016-01-01

This paper investigates a biologically motivated model of peripersonal space through its implementation on a humanoid robot. Guided by the present understanding of the neurophysiology of the fronto-parietal system, we developed a computational model inspired by the receptive fields of polymodal neurons identified, for example, in brain areas F4 and VIP. The experiments on the iCub humanoid robot show that the peripersonal space representation i) can be learned efficiently and in real-time via a simple interaction with the robot, ii) can lead to the generation of behaviors like avoidance and reaching, and iii) can contribute to the understanding the biological principle of motor equivalence. More specifically, with respect to i) the present model contributes to hypothesizing a learning mechanisms for peripersonal space. In relation to point ii) we show how a relatively simple controller can exploit the learned receptive fields to generate either avoidance or reaching of an incoming stimulus and for iii) we show how the robot can select arbitrary body parts as the controlled end-point of an avoidance or reaching movement.

Casablanca International Workshop in Mathematical Biology: Control and Analysis

DTIC Science & Technology

2012-10-05

Africa such Cholera, Malaria, HIV and within-­host diseases such as cancers . The economic, demographical and environmental changes in Africa require that...mathematical modeling of emerging diseases in Africa, cancer modeling, calcium oscillation, population dynamics, signaling networks, and optimal...INVESTIGATOR(S): Phone Number: 4807275005 Principal: Y Name: Abdessamad Tridane Email: atridan@asu.edu diseases such as cancer , vector-­borne diseases

Entropy-based separation of yeast cells using a microfluidic system of conjoined spheres

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

Huang, Kai-Jian; Qin, S.-J., E-mail: shuijie.qin@gmail.com; Bai, Zhong-Chen

2013-11-21

A physical model is derived to create a biological cell separator that is based on controlling the entropy in a microfluidic system having conjoined spherical structures. A one-dimensional simplified model of this three-dimensional problem in terms of the corresponding effects of entropy on the Brownian motion of particles is presented. This dynamic mechanism is based on the Langevin equation from statistical thermodynamics and takes advantage of the characteristics of the Fokker-Planck equation. This mechanism can be applied to manipulate biological particles inside a microfluidic system with identical, conjoined, spherical compartments. This theoretical analysis is verified by performing a rapid andmore » a simple technique for separating yeast cells in these conjoined, spherical microfluidic structures. The experimental results basically match with our theoretical model and we further analyze the parameters which can be used to control this separation mechanism. Both numerical simulations and experimental results show that the motion of the particles depends on the geometrical boundary conditions of the microfluidic system and the initial concentration of the diffusing material. This theoretical model can be implemented in future biophysics devices for the optimized design of passive cell sorters.« less

Climate matching: implications for the biological control of hemlock woolly adelgid

Treesearch

R. Talbot III Trotter

2008-01-01

Classical biological control programs are faced with a daunting challenge: inserting a new species into an existing ecological system. In order for the newly introduced biological control species to survive and reproduce, the recipient ecosystem must provide the required biotic and abiotic requirements. The Adelgid Biological Control simulator (ABCs), a simulation...

40 CFR 152.20 - Exemptions for pesticides adequately regulated by another Federal agency.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Federal agency. (a) Certain biological control agents. (1) Except as provided by paragraphs (a)(3) and (a)(4) of this section, all biological control agents are exempt from FIFRA requirements. (2) If the Agency determines that an individual biological control agent or class of biological control agents is no...

40 CFR 152.20 - Exemptions for pesticides adequately regulated by another Federal agency.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Federal agency. (a) Certain biological control agents. (1) Except as provided by paragraphs (a)(3) and (a)(4) of this section, all biological control agents are exempt from FIFRA requirements. (2) If the Agency determines that an individual biological control agent or class of biological control agents is no...

Biological control agents elevate hantavirus by subsidizing deer mouse populations

Treesearch

Dean E. Pearson; Ragan M. Callaway

2006-01-01

Biological control of exotic invasive plants using exotic insects is practiced under the assumption that biological control agents are safe if they do not directly attack non-target species. We tested this assumption by evaluating the potential for two host-specific biological control agents (Urophora spp.), widely established in North America for spotted...

Entrainment in the master equation.

PubMed

Margaliot, Michael; Grüne, Lars; Kriecherbauer, Thomas

2018-04-01

The master equation plays an important role in many scientific fields including physics, chemistry, systems biology, physical finance and sociodynamics. We consider the master equation with periodic transition rates. This may represent an external periodic excitation like the 24 h solar day in biological systems or periodic traffic lights in a model of vehicular traffic. Using tools from systems and control theory, we prove that under mild technical conditions every solution of the master equation converges to a periodic solution with the same period as the rates. In other words, the master equation entrains (or phase locks) to periodic excitations. We describe two applications of our theoretical results to important models from statistical mechanics and epidemiology.

From systems biology to dynamical neuropharmacology: proposal for a new methodology.

PubMed

Erdi, P; Kiss, T; Tóth, J; Ujfalussy, B; Zalányi, L

2006-07-01

The concepts and methods of systems biology are extended to neuropharmacology in order to test and design drugs for the treatment of neurological and psychiatric disorders. Computational modelling by integrating compartmental neural modelling techniques and detailed kinetic descriptions of pharmacological modulation of transmitter-receptor interaction is offered as a method to test the electrophysiological and behavioural effects of putative drugs. Even more, an inverse method is suggested as a method for controlling a neural system to realise a prescribed temporal pattern. In particular, as an application of the proposed new methodology, a computational platform is offered to analyse the generation and pharmacological modulation of theta rhythm related to anxiety.

Entrainment in the master equation

PubMed Central

Grüne, Lars; Kriecherbauer, Thomas

2018-01-01

The master equation plays an important role in many scientific fields including physics, chemistry, systems biology, physical finance and sociodynamics. We consider the master equation with periodic transition rates. This may represent an external periodic excitation like the 24 h solar day in biological systems or periodic traffic lights in a model of vehicular traffic. Using tools from systems and control theory, we prove that under mild technical conditions every solution of the master equation converges to a periodic solution with the same period as the rates. In other words, the master equation entrains (or phase locks) to periodic excitations. We describe two applications of our theoretical results to important models from statistical mechanics and epidemiology. PMID:29765669

Development and Effectiveness of an Educational Card Game as Supplementary Material in Understanding Selected Topics in Biology

PubMed Central

Gutierrez, Arnel F.

2014-01-01

The complex concepts and vocabulary of biology classes discourage many students. In this study, a pretest–posttest model was used to test the effectiveness of an educational card game in reinforcing biological concepts in comparison with traditional teaching methods. The subjects of this study were two biology classes at Bulacan State University–Sarmiento Campus. Both classes received conventional instruction; however, the experimental group's instruction was supplemented with the card game, while the control group's instruction was reinforced with traditional exercises and assignments. The score increases from pretest to posttest showed that both methods effectively reinforced biological concepts, but a t test showed that the card game is more effective than traditional teaching methods. Additionally, students from the experimental group evaluated the card game using five criteria: goals, design, organization, playability, and usefulness. The students rated the material very satisfactory. PMID:24591506

Development and effectiveness of an educational card game as supplementary material in understanding selected topics in biology.

PubMed

Gutierrez, Arnel F

2014-01-01

The complex concepts and vocabulary of biology classes discourage many students. In this study, a pretest-posttest model was used to test the effectiveness of an educational card game in reinforcing biological concepts in comparison with traditional teaching methods. The subjects of this study were two biology classes at Bulacan State University-Sarmiento Campus. Both classes received conventional instruction; however, the experimental group's instruction was supplemented with the card game, while the control group's instruction was reinforced with traditional exercises and assignments. The score increases from pretest to posttest showed that both methods effectively reinforced biological concepts, but a t test showed that the card game is more effective than traditional teaching methods. Additionally, students from the experimental group evaluated the card game using five criteria: goals, design, organization, playability, and usefulness. The students rated the material very satisfactory.

Synergizing Engineering and Biology to Treat and Model Skeletal Muscle Injury and Disease

PubMed Central

Bursac, Nenad; Juhas, Mark; Rando, Thomas A.

2016-01-01

Although skeletal muscle is one of the most regenerative organs in our body, various genetic defects, alterations in extrinsic signaling, or substantial tissue damage can impair muscle function and the capacity for self-repair. The diversity and complexity of muscle disorders have attracted much interest from both cell biologists and, more recently, bioengineers, leading to concentrated efforts to better understand muscle pathology and develop more efficient therapies. This review describes the biological underpinnings of muscle development, repair, and disease, and discusses recent bioengineering efforts to design and control myomimetic environments, both to study muscle biology and function and to aid in the development of new drug, cell, and gene therapies for muscle disorders. The synergy between engineering-aided biological discovery and biology-inspired engineering solutions will be the path forward for translating laboratory results into clinical practice. PMID:26643021

Oxygen regulates molecular mechanisms of cancer progression and metastasis.

PubMed

Gupta, Kartik; Madan, Esha; Sayyid, Muzzammil; Arias-Pulido, Hugo; Moreno, Eduardo; Kuppusamy, Periannan; Gogna, Rajan

2014-03-01

Oxygen is the basic molecule which supports life and it truly is "god's gift to life." Despite its immense importance, research on "oxygen biology" has never received the light of the day and has been limited to physiological and biochemical studies. It seems that in modern day biology, oxygen research is summarized in one word "hypoxia." Scientists have focused on hypoxia-induced transcriptomics and molecular-cellular alterations exclusively in disease models. Interestingly, the potential of oxygen to control the basic principles of biology like homeostatic maintenance, transcription, replication, and protein folding among many others, at the molecular level, has been completely ignored. Here, we present a perspective on the crucial role played by oxygen in regulation of basic biological phenomena. Our conclusion highlights the importance of establishing novel research areas like oxygen biology, as there is great potential in this field for basic science discoveries and clinical benefits to the society.

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

JOHNSON, A.R.

Biological control is any activity taken to prevent, limit, clean up, or remediate potential environmental, health and safety, or workplace quality impacts from plants, animals, or microorganisms. At Hanford the principal emphasis of biological control is to prevent the transport of radioactive contamination by biological vectors (plants, animals, or microorganisms), and where necessary, control and clean up resulting contamination. Other aspects of biological control at Hanford include industrial weed control (e.g.; tumbleweeds), noxious weed control (invasive, non-native plant species), and pest control (undesirable animals such as rodents and stinging insects; and microorganisms such as molds that adversely affect the qualitymore » of the workplace environment). Biological control activities may be either preventive (apriori) or in response to existing contamination spread (aposteriori). Surveillance activities, including ground, vegetation, flying insect, and other surveys, and apriori control actions, such as herbicide spraying and placing biological barriers, are important in preventing radioactive contamination spread. If surveillance discovers that biological vectors have spread radioactive contamination, aposteriori control measures, such as fixing contamination, followed by cleanup and removal of the contamination to an approved disposal location are typical response functions. In some cases remediation following the contamination cleanup and removal is necessary. Biological control activities for industrial weeds, noxious weeds and pests have similar modes of prevention and response.« less

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

JOHNSON, A.R.

Biological control is any activity taken to prevent, limit, clean up, or remediate potential environmental, health and safety, or workplace quality impacts from plants, animals, or microorganisms. At Hanford the principal emphasis of biological control is to prevent the transport of radioactive contamination by biological vectors (plants, animals, or microorganisms), and where necessary, control and clean up resulting contamination. Other aspects of biological control at Hanford include industrial weed control (e.g.; tumbleweeds), noxious weed control (invasive, non-native plant species), and pest control (undesirable animals such as rodents and stinging insects, and microorganisms such as molds that adversely affect the qualitymore » of the workplace environment). Biological control activities may be either preventive (a priori) or in response to existing contamination spread (a posteriori). Surveillance activities, including ground, vegetation, flying insect, and other surveys, and a priori control actions, such as herbicide spraying and placing biological barriers, are important in preventing radioactive contamination spread. If surveillance discovers that biological vectors have spread radioactive contamination, a posteriori control measures, such as fixing contamination, followed by cleanup and removal of the contamination to an approved disposal location are typical response functions. In some cases remediation following the contamination cleanup and removal is necessary. Biological control activities for industrial weeds, noxious weeds and pests have similar modes of prevention and response.« less

The evolution and devolution of cognitive control: The costs of deliberation in a competitive world

PubMed Central

Tomlin, Damon; Rand, David G.; Ludvig, Elliot A.; Cohen, Jonathan D.

2015-01-01

Dual-system theories of human cognition, under which fast automatic processes can complement or compete with slower deliberative processes, have not typically been incorporated into larger scale population models used in evolutionary biology, macroeconomics, or sociology. However, doing so may reveal important phenomena at the population level. Here, we introduce a novel model of the evolution of dual-system agents using a resource-consumption paradigm. By simulating agents with the capacity for both automatic and controlled processing, we illustrate how controlled processing may not always be selected over rigid, but rapid, automatic processing. Furthermore, even when controlled processing is advantageous, frequency-dependent effects may exist whereby the spread of control within the population undermines this advantage. As a result, the level of controlled processing in the population can oscillate persistently, or even go extinct in the long run. Our model illustrates how dual-system psychology can be incorporated into population-level evolutionary models, and how such a framework can be used to examine the dynamics of interaction between automatic and controlled processing that transpire over an evolutionary time scale. PMID:26078086

The evolution and devolution of cognitive control: The costs of deliberation in a competitive world.

PubMed

Tomlin, Damon; Rand, David G; Ludvig, Elliot A; Cohen, Jonathan D

2015-06-16

Dual-system theories of human cognition, under which fast automatic processes can complement or compete with slower deliberative processes, have not typically been incorporated into larger scale population models used in evolutionary biology, macroeconomics, or sociology. However, doing so may reveal important phenomena at the population level. Here, we introduce a novel model of the evolution of dual-system agents using a resource-consumption paradigm. By simulating agents with the capacity for both automatic and controlled processing, we illustrate how controlled processing may not always be selected over rigid, but rapid, automatic processing. Furthermore, even when controlled processing is advantageous, frequency-dependent effects may exist whereby the spread of control within the population undermines this advantage. As a result, the level of controlled processing in the population can oscillate persistently, or even go extinct in the long run. Our model illustrates how dual-system psychology can be incorporated into population-level evolutionary models, and how such a framework can be used to examine the dynamics of interaction between automatic and controlled processing that transpire over an evolutionary time scale.

A Combination of Hand-Held Models and Computer Imaging Programs Helps Students Answer Oral Questions about Molecular Structure and Function: A Controlled Investigation of Student Learning

ERIC Educational Resources Information Center

Harris, Michelle A.; Peck, Ronald F.; Colton, Shannon; Morris, Jennifer; Neto, Elias Chaibub; Kallio, Julie

2009-01-01

We conducted a controlled investigation to examine whether a combination of computer imagery and tactile tools helps introductory cell biology laboratory undergraduate students better learn about protein structure/function relationships as compared with computer imagery alone. In all five laboratory sections, students used the molecular imaging…

Development of a Biological Control Program for Eurasian Watermilfoil (Myriophyllum spicatum)

DTIC Science & Technology

2008-08-01

spicatum). Rawalpindi: Pakistan Station Commonwealth Institute of Biological Control. Gleason, H. A ., and A . Cronquist . 1991. Manual of vascular plants...ER D C/ EL T R- 08 -2 2 Aquatic Plant Control Research Program Development of a Biological Control Program for Eurasian Watermilfoil... a Biological Control Program for Eurasian Watermilfoil (Myriophyllum spicatum) Matthew J. W. Cock, Hariet L. Hinz, Gitta Grosskopf, and Patrick

A BIOLOGICALLY BASED MODEL FOR THE HORMONAL CONTROL OF THE MENSTRUAL CYCLE

EPA Science Inventory

Recent studies suggest that environmental substances that mimic endogenous estrogens (eg. estradiol) may disrupt the endocrine system. While high-level exposures to estrogenic substances are believed to contribute to such adverse effects as cancer, developmental disorders, and fe...

Mathematical modeling relevant to closed artificial ecosystems

USGS Publications Warehouse

DeAngelis, D.L.

2003-01-01

The mathematical modeling of ecosystems has contributed much to the understanding of the dynamics of such systems. Ecosystems can include not only the natural variety, but also artificial systems designed and controlled by humans. These can range from agricultural systems and activated sludge plants, down to mesocosms, microcosms, and aquaria, which may have practical or research applications. Some purposes may require the design of systems that are completely closed, as far as material cycling is concerned. In all cases, mathematical modeling can help not only to understand the dynamics of the system, but also to design methods of control to keep the system operating in desired ranges. This paper reviews mathematical modeling relevant to the simulation and control of closed or semi-closed artificial ecosystems designed for biological production and recycling in applications in space. Published by Elsevier Science Ltd on behalf of COSPAR.

Electromagnetic Model Reliably Predicts Radar Scattering Characteristics of Airborne Organisms

NASA Astrophysics Data System (ADS)

Mirkovic, Djordje; Stepanian, Phillip M.; Kelly, Jeffrey F.; Chilson, Phillip B.

2016-10-01

The radar scattering characteristics of aerial animals are typically obtained from controlled laboratory measurements of a freshly harvested specimen. These measurements are tedious to perform, difficult to replicate, and typically yield only a small subset of the full azimuthal, elevational, and polarimetric radio scattering data. As an alternative, biological applications of radar often assume that the radar cross sections of flying animals are isotropic, since sophisticated computer models are required to estimate the 3D scattering properties of objects having complex shapes. Using the method of moments implemented in the WIPL-D software package, we show for the first time that such electromagnetic modeling techniques (typically applied to man-made objects) can accurately predict organismal radio scattering characteristics from an anatomical model: here the Brazilian free-tailed bat (Tadarida brasiliensis). The simulated scattering properties of the bat agree with controlled measurements and radar observations made during a field study of bats in flight. This numerical technique can produce the full angular set of quantitative polarimetric scattering characteristics, while eliminating many practical difficulties associated with physical measurements. Such a modeling framework can be applied for bird, bat, and insect species, and will help drive a shift in radar biology from a largely qualitative and phenomenological science toward quantitative estimation of animal densities and taxonomic identification.

Electromagnetic Model Reliably Predicts Radar Scattering Characteristics of Airborne Organisms

PubMed Central

Mirkovic, Djordje; Stepanian, Phillip M.; Kelly, Jeffrey F.; Chilson, Phillip B.

2016-01-01

The radar scattering characteristics of aerial animals are typically obtained from controlled laboratory measurements of a freshly harvested specimen. These measurements are tedious to perform, difficult to replicate, and typically yield only a small subset of the full azimuthal, elevational, and polarimetric radio scattering data. As an alternative, biological applications of radar often assume that the radar cross sections of flying animals are isotropic, since sophisticated computer models are required to estimate the 3D scattering properties of objects having complex shapes. Using the method of moments implemented in the WIPL-D software package, we show for the first time that such electromagnetic modeling techniques (typically applied to man-made objects) can accurately predict organismal radio scattering characteristics from an anatomical model: here the Brazilian free-tailed bat (Tadarida brasiliensis). The simulated scattering properties of the bat agree with controlled measurements and radar observations made during a field study of bats in flight. This numerical technique can produce the full angular set of quantitative polarimetric scattering characteristics, while eliminating many practical difficulties associated with physical measurements. Such a modeling framework can be applied for bird, bat, and insect species, and will help drive a shift in radar biology from a largely qualitative and phenomenological science toward quantitative estimation of animal densities and taxonomic identification. PMID:27762292

A biological approach to characterizing exposure to metalworking fluids and risk of prostate cancer (United States).

PubMed

Agalliu, Ilir; Eisen, Ellen A; Kriebel, David; Quinn, Margaret M; Wegman, David H

2005-05-01

Prostate cancer is hormone-related and chemicals that interfere with hormones may contribute to carcinogenesis. In a cohort of autoworkers we characterized exposure to metalworking fluids (MWF) into age windows with homogenous biological risk for prostate cancer, and examined exposure-response relationships using semi-parametric modeling. Incident cases (n=872) were identified via Michigan cancer registry from 1985 through 2000. Controls were selected using incidence-density sampling, 5:1 ratio. Using a hormonal-based model, exposure was accumulated in three windows: (1) late puberty, (2) adulthood, and (3) middle age. We used penalized splines to model risk as a smooth function of exposure, and controlled for race and calendar year of diagnosis in a Cox model. Risk of prostate cancer linearly increased with exposure to straight MWF in the first window, with a relative risk of 2.4 per 10 mg/m(3)-years. Autoworkers exposed to MWF at a young age also had an increased risk associated with MWF exposure incurred later in life. For soluble MWF there was a slightly increased risk in the third window. Exposure characterization based on a hormonal model identified heightened risk with early age of exposure to straight MWF. Results also support a long latency period for exposure related prostate cancer.

Electromagnetic Model Reliably Predicts Radar Scattering Characteristics of Airborne Organisms.

PubMed

Mirkovic, Djordje; Stepanian, Phillip M; Kelly, Jeffrey F; Chilson, Phillip B

2016-10-20

The radar scattering characteristics of aerial animals are typically obtained from controlled laboratory measurements of a freshly harvested specimen. These measurements are tedious to perform, difficult to replicate, and typically yield only a small subset of the full azimuthal, elevational, and polarimetric radio scattering data. As an alternative, biological applications of radar often assume that the radar cross sections of flying animals are isotropic, since sophisticated computer models are required to estimate the 3D scattering properties of objects having complex shapes. Using the method of moments implemented in the WIPL-D software package, we show for the first time that such electromagnetic modeling techniques (typically applied to man-made objects) can accurately predict organismal radio scattering characteristics from an anatomical model: here the Brazilian free-tailed bat (Tadarida brasiliensis). The simulated scattering properties of the bat agree with controlled measurements and radar observations made during a field study of bats in flight. This numerical technique can produce the full angular set of quantitative polarimetric scattering characteristics, while eliminating many practical difficulties associated with physical measurements. Such a modeling framework can be applied for bird, bat, and insect species, and will help drive a shift in radar biology from a largely qualitative and phenomenological science toward quantitative estimation of animal densities and taxonomic identification.

Inferring the Impact of Regulatory Mechanisms that Underpin CD8+ T Cell Control of B16 Tumor Growth In vivo Using Mechanistic Models and Simulation.

PubMed

Klinke, David J; Wang, Qing

2016-01-01

A major barrier for broadening the efficacy of immunotherapies for cancer is identifying key mechanisms that limit the efficacy of tumor infiltrating lymphocytes. Yet, identifying these mechanisms using human samples and mouse models for cancer remains a challenge. While interactions between cancer and the immune system are dynamic and non-linear, identifying the relative roles that biological components play in regulating anti-tumor immunity commonly relies on human intuition alone, which can be limited by cognitive biases. To assist natural intuition, modeling and simulation play an emerging role in identifying therapeutic mechanisms. To illustrate the approach, we developed a multi-scale mechanistic model to describe the control of tumor growth by a primary response of CD8+ T cells against defined tumor antigens using the B16 C57Bl/6 mouse model for malignant melanoma. The mechanistic model was calibrated to data obtained following adenovirus-based immunization and validated to data obtained following adoptive transfer of transgenic CD8+ T cells. More importantly, we use simulation to test whether the postulated network topology, that is the modeled biological components and their associated interactions, is sufficient to capture the observed anti-tumor immune response. Given the available data, the simulation results also provided a statistical basis for quantifying the relative importance of different mechanisms that underpin CD8+ T cell control of B16F10 growth. By identifying conditions where the postulated network topology is incomplete, we illustrate how this approach can be used as part of an iterative design-build-test cycle to expand the predictive power of the model.

Robust control for fractional variable-order chaotic systems with non-singular kernel

NASA Astrophysics Data System (ADS)

Zuñiga-Aguilar, C. J.; Gómez-Aguilar, J. F.; Escobar-Jiménez, R. F.; Romero-Ugalde, H. M.

2018-01-01

This paper investigates the chaos control for a class of variable-order fractional chaotic systems using robust control strategy. The variable-order fractional models of the non-autonomous biological system, the King Cobra chaotic system, the Halvorsen's attractor and the Burke-Shaw system, have been derived using the fractional-order derivative with Mittag-Leffler in the Liouville-Caputo sense. The fractional differential equations and the control law were solved using the Adams-Bashforth-Moulton algorithm. To test the control stability efficiency, different statistical indicators were introduced. Finally, simulation results demonstrate the effectiveness of the proposed robust control.

Spatial Patterns in the Efficiency of the Biological Pump: What Controls Export Ratios at the Global Scale?

NASA Astrophysics Data System (ADS)

Moore, J. K.

2016-02-01

The efficiency of the biological pump is influenced by complex interactions between chemical, biological, and physical processes. The efficiency of export out of surface waters and down through the water column to the deep ocean has been linked to a number of factors including biota community composition, production of mineral ballast components, physical aggregation and disaggregation processes, and ocean oxygen concentrations. I will examine spatial patterns in the export ratio and the efficiency of the biological pump at the global scale using the Community Earth System Model (CESM). There are strong spatial variations in the export efficiency as simulated by the CESM, which are strongly correlated with new nutrient inputs to the euphotic zone and their impacts on phytoplankton community structure. I will compare CESM simulations that include dynamic, variable export ratios driven by the phytoplankton community structure, with simulations that impose a near-constant export ratio to examine the effects of export efficiency on nutrient and surface chlorophyll distributions. The model predicted export ratios will also be compared with recent satellite-based estimates.

77 FR 46373 - Field Release of Aphelinus glycinis for the Biological Control of the Soybean Aphid in the...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-03

... Inspection Service [Docket No APHIS-2012-0061] Field Release of Aphelinus glycinis for the Biological Control... for the biological control of the soybean aphid, Aphis glycines, in the continental United States. We... glycinis for the Biological Control of the Soybean Aphid in the Continental United States'' (March 2012...

Punctuated equilibrium and power law in economic dynamics

NASA Astrophysics Data System (ADS)

Gupta, Abhijit Kar

2012-02-01

This work is primarily based on a recently proposed toy model by Thurner et al. (2010) [3] on Schumpeterian economic dynamics (inspired by the idea of economist Joseph Schumpeter [9]). Interestingly, punctuated equilibrium has been shown to emerge from the dynamics. The punctuated equilibrium and Power law are known to be associated with similar kinds of biologically relevant evolutionary models proposed in the past. The occurrence of the Power law is a signature of Self-Organised Criticality (SOC). In our view, power laws can be obtained by controlling the dynamics through incorporating the idea of feedback into the algorithm in some way. The so-called 'feedback' was achieved by introducing the idea of fitness and selection processes in the biological evolutionary models. Therefore, we examine the possible emergence of a power law by invoking the concepts of 'fitness' and 'selection' in the present model of economic evolution.

Environmental parameters of the Tennessee River in Alabama. 2: Physical, chemical, and biological parameters. [biological and chemical effects of thermal pollution from nuclear power plants on water quality

NASA Technical Reports Server (NTRS)

Rosing, L. M.

1976-01-01

Physical, chemical and biological water quality data from five sites in the Tennessee River, two in Guntersville Reservoir and three in Wheeler Reservoir were correlated with climatological data for three annual cycles. Two of the annual cycles are for the years prior to the Browns Ferry Nuclear Power Plant operations and one is for the first 14 months of Plant operations. A comparison of the results of the annual cycles indicates that two distinct physical conditions in the reservoirs occur, one during the warm months when the reservoirs are at capacity and one during the colder winter months when the reservoirs have been drawn-down for water storage during the rainy months and for weed control. The wide variations of physical and chemical parameters to which the biological organisms are subjected on an annual basis control the biological organisms and their population levels. A comparison of the parameters of the site below the Power plant indicates that the heated effluent from the plant operating with two of the three reactors has not had any effect on the organisms at this site. Recommendations given include the development of prediction mathematical models (statistical analysis) for the physical and chemical parameters under specific climatological conditions which affect biological organisms. Tabulated data of chemical analysis of water and organism populations studied is given.

Dynamic sensitivity analysis of biological systems

PubMed Central

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2008-01-01

Background A mathematical model to understand, predict, control, or even design a real biological system is a central theme in systems biology. A dynamic biological system is always modeled as a nonlinear ordinary differential equation (ODE) system. How to simulate the dynamic behavior and dynamic parameter sensitivities of systems described by ODEs efficiently and accurately is a critical job. In many practical applications, e.g., the fed-batch fermentation systems, the system admissible input (corresponding to independent variables of the system) can be time-dependent. The main difficulty for investigating the dynamic log gains of these systems is the infinite dimension due to the time-dependent input. The classical dynamic sensitivity analysis does not take into account this case for the dynamic log gains. Results We present an algorithm with an adaptive step size control that can be used for computing the solution and dynamic sensitivities of an autonomous ODE system simultaneously. Although our algorithm is one of the decouple direct methods in computing dynamic sensitivities of an ODE system, the step size determined by model equations can be used on the computations of the time profile and dynamic sensitivities with moderate accuracy even when sensitivity equations are more stiff than model equations. To show this algorithm can perform the dynamic sensitivity analysis on very stiff ODE systems with moderate accuracy, it is implemented and applied to two sets of chemical reactions: pyrolysis of ethane and oxidation of formaldehyde. The accuracy of this algorithm is demonstrated by comparing the dynamic parameter sensitivities obtained from this new algorithm and from the direct method with Rosenbrock stiff integrator based on the indirect method. The same dynamic sensitivity analysis was performed on an ethanol fed-batch fermentation system with a time-varying feed rate to evaluate the applicability of the algorithm to realistic models with time-dependent admissible input. Conclusion By combining the accuracy we show with the efficiency of being a decouple direct method, our algorithm is an excellent method for computing dynamic parameter sensitivities in stiff problems. We extend the scope of classical dynamic sensitivity analysis to the investigation of dynamic log gains of models with time-dependent admissible input. PMID:19091016

Models of Small-Scale Patchiness

NASA Technical Reports Server (NTRS)

McGillicuddy, D. J.

2001-01-01

Patchiness is perhaps the most salient characteristic of plankton populations in the ocean. The scale of this heterogeneity spans many orders of magnitude in its spatial extent, ranging from planetary down to microscale. It has been argued that patchiness plays a fundamental role in the functioning of marine ecosystems, insofar as the mean conditions may not reflect the environment to which organisms are adapted. Understanding the nature of this patchiness is thus one of the major challenges of oceanographic ecology. The patchiness problem is fundamentally one of physical-biological-chemical interactions. This interconnection arises from three basic sources: (1) ocean currents continually redistribute dissolved and suspended constituents by advection; (2) space-time fluctuations in the flows themselves impact biological and chemical processes, and (3) organisms are capable of directed motion through the water. This tripartite linkage poses a difficult challenge to understanding oceanic ecosystems: differentiation between the three sources of variability requires accurate assessment of property distributions in space and time, in addition to detailed knowledge of organismal repertoires and the processes by which ambient conditions control the rates of biological and chemical reactions. Various methods of observing the ocean tend to lie parallel to the axes of the space/time domain in which these physical-biological-chemical interactions take place. Given that a purely observational approach to the patchiness problem is not tractable with finite resources, the coupling of models with observations offers an alternative which provides a context for synthesis of sparse data with articulations of fundamental principles assumed to govern functionality of the system. In a sense, models can be used to fill the gaps in the space/time domain, yielding a framework for exploring the controls on spatially and temporally intermittent processes. The following discussion highlights only a few of the multitude of models which have yielded insight into the dynamics of plankton patchiness. In addition, this particular collection of examples is intended to furnish some exposure to the diversity of modeling approaches which can be brought to bear on the problem. These approaches range from abstract theoretical models intended to elucidate specific processes, to complex numerical formulations which can be used to actually simulate observed distributions in detail.

Biological effect on restenosis and vascular healing of encapsulated paclitaxel nanocrystals delivered via coated balloon technology in the familial hypercholesterolaemic swine model of in-stent restenosis.

PubMed

Cheng, Yanping; Shibuya, Masahiko; McGregor, Jenn; Conditt, Gerard B; Yi, Geng-Hua; Kaluza, Greg L; Gray, William; Doshi, Manish; Sojitra, Prakash; Granada, Juan F

2016-10-20

The aim of this study was to evaluate the biological efficacy of a novel lower-dose (2.5 µg/mm2) encapsulated paclitaxel nanocrystal-coated balloon (Nano-PCB) in the familial hypercholesterolaemic swine (FHS) model of iliofemoral in-stent restenosis. Nano-PCB pharmacokinetics were assessed in 20 femoral arteries (domestic swine). Biological efficacy was evaluated in ten FHS: 14 days following bare metal stent implantation each stent segment was randomised to a clinically available PCB (IN.PACT, n=14), the Nano-PCB (n=14) or an uncoated balloon (n=12). Angiographic, optical coherence tomography and histological evaluation was performed at 28 days after treatment. Arterial paclitaxel concentration was 120.7 ng/mg at one hour and 7.65 ng/mg of tissue at 28 days with the Nano-PCB. Compared to the control uncoated group, both PCBs significantly reduced percent area stenosis (Nano-PCB: 36.0±14.2%, IN.PACT: 29.3±9.2% vs control: 67.9±15.1%, p<0.001). Neointimal distribution in the entire stent length was more homogenous in the Nano-PCB. Histological evaluation showed comparable degrees of neointimal proliferation in both PCBs; however, the Nano-PCB showed slightly higher levels of neointimal maturity and endothelialisation. Lower-dose encapsulated paclitaxel nanocrystals delivered via a coated balloon displayed comparable biological efficacy with superior healing features compared to a clinically validated PCB technology.

Biomedical and Catalytic Opportunities of Virus-Like Particles in Nanotechnology

PubMed Central

Schwarz, B.; Uchida, M.; Douglas, T.

2016-01-01

Within biology, molecules are arranged in hierarchical structures that coordinate and control the many processes that allow for complex organisms to exist. Proteins and other functional macromolecules are often studied outside their natural nanostructural context because it remains difficult to create controlled arrangements of proteins at this size scale. Viruses are elegantly simple nanosystems that exist at the interface of living organisms and nonliving biological machines. Studied and viewed primarily as pathogens to be combatted, viruses have emerged as models of structural efficiency at the nanoscale and have spurred the development of biomimetic nanoparticle systems. Virus-like particles (VLPs) are noninfectious protein cages derived from viruses or other cage-forming systems. VLPs provide incredibly regular scaffolds for building at the nanoscale. Composed of self-assembling protein subunits, VLPs provide both a model for studying materials’ assembly at the nanoscale and useful building blocks for materials design. The robustness and degree of understanding of many VLP structures allow for the ready use of these systems as versatile nanoparticle platforms for the conjugation of active molecules or as scaffolds for the structural organization of chemical processes. Lastly the prevalence of viruses in all domains of life has led to unique activities of VLPs in biological systems most notably the immune system. Here we discuss recent efforts to apply VLPs in a wide variety of applications with the aim of highlighting how the common structural elements of VLPs have led to their emergence as paradigms for the understanding and design of biological nanomaterials. PMID:28057256

Nature of motor control: perspectives and issues.

PubMed

Turvey, Michael T; Fonseca, Sergio

2009-01-01

Four perspectives on motor control provide the framework for developing a comprehensive theory of motor control in biological systems. The four perspectives, of decreasing orthodoxy, are distinguished by their sources of inspiration: neuroanatomy, robotics, self-organization, and ecological realities. Twelve major issues that commonly constrain (either explicitly or implicitly) the understanding of the control and coordination of movement are identified and evaluated within the framework of the four perspectives. The issues are as follows: (1) Is control strictly neural? (2) Is there a divide between planning and execution? (3) Does control entail a frequently involved knowledgeable executive? (4) Do analytical internal models mediate control? (5) Is anticipation necessarily model dependent? (6) Are movements preassembled? (7) Are the participating components context independent? (8) Is force transmission strictly myotendinous? (9) Is afference a matter of local linear signaling? (10) Is neural noise an impediment? (11) Do standard variables (of mechanics and physiology) suffice? (12) Is the organization of control hierarchical?

Nature of Motor Control: Perspectives and Issues

PubMed Central

Turvey, M. T.; Fonseca, Sergio

2013-01-01

Four perspectives on motor control provide the framework for developing a comprehensive theory of motor control in biological systems. The four perspectives, of decreasing orthodoxy, are distinguished by their sources of inspiration: neuroanatomy, robotics, self-organization, and ecological realities. Twelve major issues that commonly constrain (either explicitly or implicitly) the understanding of the control and coordination of movement are identified and evaluated within the framework of the four perspectives. The issues are as follows: (1) Is control strictly neural? (2) Is there a divide between planning and execution? (3) Does control entail a frequently involved knowledgeable executive? (4) Do analytical internal models mediate control? (5) Is anticipation necessarily model dependent? (6) Are movements preassembled? (7) Are the participating components context independent? (8) Is force transmission strictly myotendinous? (9) Is afference a matter of local linear signaling? (10) Is neural noise an impediment? (11) Do standard variables (of mechanics and physiology) suffice? (12) Is the organization of control hierarchical? PMID:19227497

Microbial load monitor

NASA Technical Reports Server (NTRS)

Caplin, R. S.; Royer, E. R.

1978-01-01

Attempts are made to provide a total design of a Microbial Load Monitor (MLM) system flight engineering model. Activities include assembly and testing of Sample Receiving and Card Loading Devices (SRCLDs), operator related software, and testing of biological samples in the MLM. Progress was made in assembling SRCLDs with minimal leaks and which operate reliably in the Sample Loading System. Seven operator commands are used to control various aspects of the MLM such as calibrating and reading the incubating reading head, setting the clock and reading time, and status of Card. Testing of the instrument, both in hardware and biologically, was performed. Hardware testing concentrated on SRCLDs. Biological testing covered 66 clinical and seeded samples. Tentative thresholds were set and media performance listed.

Nanogel Carrier Design for Targeted Drug Delivery

PubMed Central

Eckmann, D. M.; Composto, R. J.; Tsourkas, A.; Muzykantov, V. R.

2014-01-01

Polymer-based nanogel formulations offer features attractive for drug delivery, including ease of synthesis, controllable swelling and viscoelasticity as well as drug loading and release characteristics, passive and active targeting, and the ability to formulate nanogel carriers that can respond to biological stimuli. These unique features and low toxicity make the nanogels a favorable option for vascular drug targeting. In this review, we address key chemical and biological aspects of nanogel drug carrier design. In particular, we highlight published studies of nanogel design, descriptions of nanogel functional characteristics and their behavior in biological models. These studies form a compendium of information that supports the scientific and clinical rationale for development of this carrier for targeted therapeutic interventions. PMID:25485112

Modern methods and systems for precise control of the quality of agricultural and food production

NASA Astrophysics Data System (ADS)

Bednarjevsky, Sergey S.; Veryasov, Yuri V.; Akinina, Evgeniya V.; Smirnov, Gennady I.

1999-01-01

The results on the modeling of non-linear dynamics of strong continuous and impulse radiation in the laser nephelometry of polydisperse biological systems, important from the viewpoint of applications in biotechnologies, are presented. The processes of nonlinear self-action of the laser radiation by the multiple scattering in the disperse biological agro-media are considered. The simplified algorithms of the calculation of the parameters of the biological media under investigation are indicated and the estimates of the errors of the laser-nephelometric measurements are given. The universal high-informative optical analyzers and the standard etalon specimens of agro- objects make the technological foundation of the considered methods and systems.

Synchrony and entrainment properties of robust circadian oscillators

PubMed Central

Bagheri, Neda; Taylor, Stephanie R.; Meeker, Kirsten; Petzold, Linda R.; Doyle, Francis J.

2008-01-01

Systems theoretic tools (i.e. mathematical modelling, control, and feedback design) advance the understanding of robust performance in complex biological networks. We highlight phase entrainment as a key performance measure used to investigate dynamics of a single deterministic circadian oscillator for the purpose of generating insight into the behaviour of a population of (synchronized) oscillators. More specifically, the analysis of phase characteristics may facilitate the identification of appropriate coupling mechanisms for the ensemble of noisy (stochastic) circadian clocks. Phase also serves as a critical control objective to correct mismatch between the biological clock and its environment. Thus, we introduce methods of investigating synchrony and entrainment in both stochastic and deterministic frameworks, and as a property of a single oscillator or population of coupled oscillators. PMID:18426774

Feasibility of using mixtures of silicone elastomers and silicone oils to model the mechanical behaviour of biological tissues

PubMed Central

Ahmadzadeh, S Mohammad Hassan

2014-01-01

Mixtures of silicone elastomer and silicone oil were prepared and the values of their Young’s moduli, E, determined in compression. The mixtures had volume fractions, ϕ, of silicone oil in the range of 0–0.73. Measurements were made, under displacement control, for strain rates, ε·, in the range of 0.04–3.85 s−1. The behaviour of E as a function of ϕ and ε· was investigated using a response surface model. The effects of the two variables were independent for the silicones used in this investigation. As a result, the dependence of E values (measured in MPa) on ϕ and ε· (s−1) could be represented by E=0.57−0.75ϕ+0.01loge(ε·). This means that these silicones can be mixed to give materials with E values in the range of about 0.02–0.57 MPa, which includes E values for many biological tissues. Thus, the mixtures can be used for making models for training health-care professionals and may be useful in some research applications as model tissues that do not exhibit biological variability. PMID:24951628

Assessing the dynamics of the upper soil layer relative to soil management practices

NASA Astrophysics Data System (ADS)

Hatfield, J.; Wacha, K.; Dold, C.

2017-12-01

The upper layer of the soil is the critical interface between the soil and the atmosphere and is the most dynamic in response to management practices. One of the soil properties most reflective to changes in management is the stability of the aggregates because this property controls infiltration of water and exchange of gases. An aggregation model has been developed based on the factors that control how aggregates form and the forces which degrade aggregates. One of the major factors for this model is the storage of carbon into the soil and the interaction with the soil biological component. To increase soil biology requires a stable microclimate that provides food, water, shelter, and oxygen which in turn facilitates the incorporation of organic material into forms that can be combined with soil particles to create stable aggregates. The processes that increase aggregate size and stability are directly linked the continual functioning of the biological component which in turn changes the physical and chemical properties of the soil. Soil aggregates begin to degrade as soon as there is no longer a supply of organic material into the soil. These processes can range from removal of organic material and excessive tillage. To increase aggregation of the upper soil layer requires a continual supply of organic material and the biological activity that incorporates organic material into substances that create a stable aggregate. Soils that exhibit stable soil aggregates at the surface have a prolonged infiltration rate with less runoff and a gas exchange that ensures adequate oxygen for maximum biological activity. Quantifying the dynamics of the soil surface layer provides a quantitative understanding of how management practices affect aggregate stability.

Model-based redesign of global transcription regulation

PubMed Central

Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso

2009-01-01

Synthetic biology aims to the design or redesign of biological systems. In particular, one possible goal could be the rewiring of the transcription regulation network by exchanging the endogenous promoters. To achieve this objective, we have adapted current methods to the inference of a model based on ordinary differential equations that is able to predict the network response after a major change in its topology. Our procedure utilizes microarray data for training. We have experimentally validated our inferred global regulatory model in Escherichia coli by predicting transcriptomic profiles under new perturbations. We have also tested our methodology in silico by providing accurate predictions of the underlying networks from expression data generated with artificial genomes. In addition, we have shown the predictive power of our methodology by obtaining the gene profile in experimental redesigns of the E. coli genome, where rewiring the transcriptional network by means of knockouts of master regulators or by upregulating transcription factors controlled by different promoters. Our approach is compatible with most network inference methods, allowing to explore computationally future genome-wide redesign experiments in synthetic biology. PMID:19188257

Mitochondrial pathways governing stress resistance, life, and death in the fungal aging model Podospora anserina.

PubMed

Osiewacz, Heinz D; Brust, Diana; Hamann, Andrea; Kunstmann, Birgit; Luce, Karin; Müller-Ohldach, Mathis; Scheckhuber, Christian Q; Servos, Jörg; Strobel, Ingmar

2010-06-01

Work from more than 50 years of research has unraveled a number of molecular pathways that are involved in controlling aging of the fungal model system Podospora anserina. Early research revealed that wild-type strain aging is linked to gross reorganization of the mitochondrial DNA. Later it was shown that aging of P. anserina does also take place, although at a slower pace, when the wild-type specific mitochondrial DNA rearrangements do not occur. Now it is clear that a network of different pathways is involved in the control of aging. Branches of these pathways appear to be connected and constitute a hierarchical system of responses. Although cross talk between the individual pathways seems to be fundamental in the coordination of the overall system, the precise underlying interactions remain to be unraveled. Such a systematic approach aims at a holistic understanding of the process of biological aging, the ultimate goal of modern systems biology.

Physical constraints on biological integral control design for homeostasis and sensory adaptation.

PubMed

Ang, Jordan; McMillen, David R

2013-01-22

Synthetic biology includes an effort to use design-based approaches to create novel controllers, biological systems aimed at regulating the output of other biological processes. The design of such controllers can be guided by results from control theory, including the strategy of integral feedback control, which is central to regulation, sensory adaptation, and long-term robustness. Realization of integral control in a synthetic network is an attractive prospect, but the nature of biochemical networks can make the implementation of even basic control structures challenging. Here we present a study of the general challenges and important constraints that will arise in efforts to engineer biological integral feedback controllers or to analyze existing natural systems. Constraints arise from the need to identify target output values that the combined process-plus-controller system can reach, and to ensure that the controller implements a good approximation of integral feedback control. These constraints depend on mild assumptions about the shape of input-output relationships in the biological components, and thus will apply to a variety of biochemical systems. We summarize our results as a set of variable constraints intended to provide guidance for the design or analysis of a working biological integral feedback controller. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

The evolution of respect for property.

PubMed

Sherratt, T N; Mesterton-Gibbons, M

2015-06-01

Although possession is 'nine-tenths of the law', respect for ownership is widespread in the animal kingdom even without third-party enforcement. Thus, the first individuals to find objects are frequently left unchallenged by potential competitors and tend to win contests when disputes arise. Game theory has shown that respect for ownership ('Bourgeois' behaviour) can arise as an arbitrary convention to avoid costly disputes. However, the same theory predicts that a paradoxical respect for lack of ownership ('anti-Bourgeois' behaviour) can evolve under the same conditions and in some cases is the only stable outcome. Despite these predictions, anti-Bourgeois behaviour is rare in nature, whereas respect for ownership is frequently not absolute. Here, we review extensions of the classic models involving repeated interactions, confusion over roles, strategic coordination of behaviour ('secret handshakes'), owner-intruder asymmetries and continuous control of fighting investment. Confusion over roles and owner-intruder asymmetries in fighting ability may explain why respect for ownership is often partial. Moreover, although most model extensions facilitate the evolution of Bourgeois-like behaviour, secret handshakes and continuous control of fighting investment render the alternative anti-Bourgeois convention unstable. We develop these insights to highlight several key areas for future investigation. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Revision history aware repositories of computational models of biological systems.

PubMed

Miller, Andrew K; Yu, Tommy; Britten, Randall; Cooling, Mike T; Lawson, James; Cowan, Dougal; Garny, Alan; Halstead, Matt D B; Hunter, Peter J; Nickerson, David P; Nunns, Geo; Wimalaratne, Sarala M; Nielsen, Poul M F

2011-01-14

Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs) for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. We have extended the Physiome Model Repository software to be fully revision history aware, by building it on top of Mercurial, an existing DVCS. We have demonstrated the utility of this approach, when used in conjunction with the model composition facilities in CellML, to build and understand more complex models. We have also demonstrated the ability of the repository software to present version history to casual users over the web, and to highlight specific versions which are likely to be useful to users. Providing facilities for maintaining and using revision history information is an important part of building a useful repository of computational models, as this information is useful both for understanding the source of and justification for parts of a model, and to facilitate automated processes such as merges. The availability of fully revision history aware repositories, and associated tools, will therefore be of significant benefit to the community.

Using Biological-Control Research in the Classroom to Promote Scientific Inquiry & Literacy

ERIC Educational Resources Information Center

Richardson, Matthew L.; Richardson, Scott L.; Hall, David G.

2012-01-01

Scientists researching biological control should engage in education because translating research programs into classroom activities is a pathway to increase scientific literacy among students. Classroom activities focused on biological control target all levels of biological organization and can be cross-disciplinary by drawing from subject areas…

Dual Neural Network Model for the Evolution of Speech and Language.

PubMed

Hage, Steffen R; Nieder, Andreas

2016-12-01

Explaining the evolution of speech and language poses one of the biggest challenges in biology. We propose a dual network model that posits a volitional articulatory motor network (VAMN) originating in the prefrontal cortex (PFC; including Broca's area) that cognitively controls vocal output of a phylogenetically conserved primary vocal motor network (PVMN) situated in subcortical structures. By comparing the connections between these two systems in human and nonhuman primate brains, we identify crucial biological preadaptations in monkeys for the emergence of a language system in humans. This model of language evolution explains the exclusiveness of non-verbal communication sounds (e.g., cries) in infants with an immature PFC, as well as the observed emergence of non-linguistic vocalizations in adults after frontal lobe pathologies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Overview of saltcedar biological control

Treesearch

C. Jack DeLoach; Lindsey R. Milbrath; Ray Carruthers; Allen E. Knutson; Fred Nibling; Debra Eberts; David C. Thompson; David J. Kazmer; Tom L. Dudley; Dan W. Bean; Jeff B. Knight

2006-01-01

Biological control has successfully controlled 10 exotic, invasive weeds of rangelands and natural ecosystems in the United States since 1945, and control of others is in progress. We initiated biological control of saltcedar (Tamarix spp.) in 1987, using host-specific insect herbivores that regulate saltcedar populations in the Old World. We did a...

Gene × environment interaction studies have not properly controlled for potential confounders: the problem and the (simple) solution.

PubMed

Keller, Matthew C

2014-01-01

Candidate gene × environment (G × E) interaction research tests the hypothesis that the effects of some environmental variable (e.g., childhood maltreatment) on some outcome measure (e.g., depression) depend on a particular genetic polymorphism. Because this research is inherently nonexperimental, investigators have been rightly concerned that detected interactions could be driven by confounders (e.g., ethnicity, gender, age, socioeconomic status) rather than by the specified genetic or environmental variables per se. In an attempt to eliminate such alternative explanations for detected G × E interactions, investigators routinely enter the potential confounders as covariates in general linear models. However, this practice does not control for the effects these variables might have on the G × E interaction. Rather, to properly control for confounders, researchers need to enter the covariate × environment and the covariate × gene interaction terms in the same model that tests the G × E term. In this manuscript, I demonstrate this point analytically and show that the practice of improperly controlling for covariates is the norm in the G × E interaction literature to date. Thus, many alternative explanations for G × E findings that investigators had thought were eliminated have not been. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.

A novel approach to simulate gene-environment interactions in complex diseases.

PubMed

Amato, Roberto; Pinelli, Michele; D'Andrea, Daniel; Miele, Gennaro; Nicodemi, Mario; Raiconi, Giancarlo; Cocozza, Sergio

2010-01-05

Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study.

The perceptual shaping of anticipatory actions.

PubMed

Maffei, Giovanni; Herreros, Ivan; Sanchez-Fibla, Marti; Friston, Karl J; Verschure, Paul F M J

2017-12-20

Humans display anticipatory motor responses to minimize the adverse effects of predictable perturbations. A widely accepted explanation for this behaviour relies on the notion of an inverse model that, learning from motor errors, anticipates corrective responses. Here, we propose and validate the alternative hypothesis that anticipatory control can be realized through a cascade of purely sensory predictions that drive the motor system, reflecting the causal sequence of the perceptual events preceding the error. We compare both hypotheses in a simulated anticipatory postural adjustment task. We observe that adaptation in the sensory domain, but not in the motor one, supports the robust and generalizable anticipatory control characteristic of biological systems. Our proposal unites the neurobiology of the cerebellum with the theory of active inference and provides a concrete implementation of its core tenets with great relevance both to our understanding of biological control systems and, possibly, to their emulation in complex artefacts. © 2017 The Author(s).

Cell mechanics: a dialogue.

PubMed

Tao, Jiaxiang; Li, Yizeng; Vig, Dhruv K; Sun, Sean X

2017-03-01

Under the microscope, eukaryotic animal cells can adopt a variety of different shapes and sizes. These cells also move and deform, and the physical mechanisms driving these movements and shape changes are important in fundamental cell biology, tissue mechanics, as well as disease biology. This article reviews some of the basic mechanical concepts in cells, emphasizing continuum mechanics description of cytoskeletal networks and hydrodynamic flows across the cell membrane. We discuss how cells can generate movement and shape changes by controlling mass fluxes at the cell boundary. These mass fluxes can come from polymerization/depolymerization of actin cytoskeleton, as well as osmotic and hydraulic pressure-driven flow of water across the cell membrane. By combining hydraulic pressure control with force balance conditions at the cell surface, we discuss a quantitative mechanism of cell shape and volume control. The broad consequences of this model on cell mechanosensation and tissue mechanics are outlined.

Cell mechanics: a dialogue

PubMed Central

Tao, Jiaxiang; Li, Yizeng; Vig, Dhruv K; Sun, Sean X

2017-01-01

Under the microscope, eukaryotic animal cells can adopt a variety of different shapes and sizes. These cells also move and deform, and the physical mechanisms driving these movements and shape changes are important in fundamental cell biology, tissue mechanics, as well as disease biology. This article reviews some of the basic mechanical concepts in cells, emphasizing continuum mechanics description of cytoskeletal networks and hydrodynamic flows across the cell membrane. We discuss how cells can generate movement and shape changes by controlling mass fluxes at the cell boundary. These mass fluxes can come from polymerization/depolymerization of actin cytoskeleton, as well as osmotic and hydraulic pressure-driven flow of water across the cell membrane. By combining hydraulic pressure control with force balance conditions at the cell surface, we discuss a quantitative mechanism of cell shape and volume control. The broad consequences of this model on cell mechanosensation and tissue mechanics are outlined. PMID:28129208

Cell mechanics: a dialogue

NASA Astrophysics Data System (ADS)

Tao, Jiaxiang; Li, Yizeng; Vig, Dhruv K.; Sun, Sean X.

2017-03-01

Under the microscope, eukaryotic animal cells can adopt a variety of different shapes and sizes. These cells also move and deform, and the physical mechanisms driving these movements and shape changes are important in fundamental cell biology, tissue mechanics, as well as disease biology. This article reviews some of the basic mechanical concepts in cells, emphasizing continuum mechanics description of cytoskeletal networks and hydrodynamic flows across the cell membrane. We discuss how cells can generate movement and shape changes by controlling mass fluxes at the cell boundary. These mass fluxes can come from polymerization/depolymerization of actin cytoskeleton, as well as osmotic and hydraulic pressure-driven flow of water across the cell membrane. By combining hydraulic pressure control with force balance conditions at the cell surface, we discuss a quantitative mechanism of cell shape and volume control. The broad consequences of this model on cell mechanosensation and tissue mechanics are outlined.

Electronic control of H+ current in a bioprotonic device with Gramicidin A and Alamethicin

NASA Astrophysics Data System (ADS)

Hemmatian, Zahra; Keene, Scott; Josberger, Erik; Miyake, Takeo; Arboleda, Carina; Soto-Rodríguez, Jessica; Baneyx, François; Rolandi, Marco

2016-10-01

In biological systems, intercellular communication is mediated by membrane proteins and ion channels that regulate traffic of ions and small molecules across cell membranes. A bioelectronic device with ion channels that control ionic flow across a supported lipid bilayer (SLB) should therefore be ideal for interfacing with biological systems. Here, we demonstrate a biotic-abiotic bioprotonic device with Pd contacts that regulates proton (H+) flow across an SLB incorporating the ion channels Gramicidin A (gA) and Alamethicin (ALM). We model the device characteristics using the Goldman-Hodgkin-Katz (GHK) solution to the Nernst-Planck equation for transport across the membrane. We derive the permeability for an SLB integrating gA and ALM and demonstrate pH control as a function of applied voltage and membrane permeability. This work opens the door to integrating more complex H+ channels at the Pd contact interface to produce responsive biotic-abiotic devices with increased functionality.

Biological control agents elevate hantavirus by subsidizing deer mouse populations.

PubMed

Pearson, Dean E; Callaway, Ragan M

2006-04-01

Biological control of exotic invasive plants using exotic insects is practiced under the assumption that biological control agents are safe if they do not directly attack non-target species. We tested this assumption by evaluating the potential for two host-specific biological control agents (Urophora spp.), widely established in North America for spotted knapweed (Centaurea maculosa) control, to indirectly elevate Sin Nombre hantavirus by providing food subsidies to populations of deer mice (Peromyscus maniculatus), the primary reservoir for the virus. We show that seropositive deer mice (mice testing positive for hantavirus) were over three times more abundant in the presence of the biocontrol food subsidy. Elevating densities of seropositive mice may increase risk of hantavirus infection in humans and significantly alter hantavirus ecology. Host specificity alone does not ensure safe biological control. To minimize indirect risks to non-target species, biological control agents must suppress pest populations enough to reduce their own numbers.

Optimal control applied to a model for species augmentation.

PubMed

Bodine, Erin N; Gross, Louis J; Lenhart, Suzanne

2008-10-01

Species augmentation is a method of reducing species loss via augmenting declining or threatened populations with individuals from captive-bred or stable, wild populations. In this paper, we develop a differential equations model and optimal control formulation for a continuous time augmentation of a general declining population. We find a characterization for the optimal control and show numerical results for scenarios of different illustrative parameter sets. The numerical results provide considerably more detail about the exact dynamics of optimal augmentation than can be readily intuited. The work and results presented in this paper are a first step toward building a general theory of population augmentation, which accounts for the complexities inherent in many conservation biology applications.

Low Fidelity Imitation of Atypical Biological Kinematics in Autism Spectrum Disorders Is Modulated by Self-Generated Selective Attention.

PubMed

Hayes, Spencer J; Andrew, Matthew; Elliott, Digby; Gowen, Emma; Bennett, Simon J

2016-02-01

We examined whether adults with autism had difficulty imitating atypical biological kinematics. To reduce the impact that higher-order processes have on imitation we used a non-human agent model to control social attention, and removed end-state target goals in half of the trials to minimise goal-directed attention. Findings showed that only neurotypical adults imitated atypical biological kinematics. Adults with autism did, however, become significantly more accurate at imitating movement time. This confirmed they engaged in the task, and that sensorimotor adaptation was self-regulated. The attentional bias to movement time suggests the attenuation in imitating kinematics might be a compensatory strategy due to deficits in lower-level visuomotor processes associated with self-other mapping, or selective attention modulated the processes that represent biological kinematics.

Dynamics of Active Layer Depth across Alaskan Tundra Ecosystems

NASA Astrophysics Data System (ADS)

Ma, C.; Zhang, X.; Song, X.; Xu, X.

2016-12-01

The thickness of the active layer, near-surface layer of Earth material above permafrost undergoing seasonal freezing and thawing, is of considerable importance in high-latitude environments because most physical, chemical, and biological processes in the permafrost region take place within it. The dynamics of active layer thickness (ALT) result from a combination of various factors including heat transfer, soil water content, soil texture, root density, stem density, moss layer thickness, organic layer thickness, etc. However, the magnitude and controls of ALT in the permafrost region remain uncertain. The purpose of this study is to improve our understanding of the dynamics of ALT across Alaskan tundra ecosystems and their controls at multiple scales, ranging from plots to entire Alaska. This study compiled a comprehensive dataset of ALT at site and regional scales across the Alaskan tundra ecosystems, and further analyzed ALT dynamics and their hierarchical controls. We found that air temperature played a predominant role on the seasonality of ALT, regulated by other physical and chemical factors including soil texture, moisture, and root density. The structural equation modeling (SEM) analysis confirmed the predominant role of physical controls (dominated by heat and soil properties), followed by chemical and biological factors. Then a simple empirical model was developed to reconstruct the ALT across the Alaska. The comparisons against field observational data show that the method used in this study is robust; the reconstructed time-series ALT across Alaska provides a valuable dataset source for understanding ALT and validating large-scale ecosystem models.

Assessing anthropogenic impact on boreal lakes with historical fish species distribution data and hydrogeochemical modeling.

PubMed

Valinia, Salar; Englund, Göran; Moldan, Filip; Futter, Martyn N; Köhler, Stephan J; Bishop, Kevin; Fölster, Jens

2014-09-01

Quantifying the effects of human activity on the natural environment is dependent on credible estimates of reference conditions to define the state of the environment before the onset of adverse human impacts. In Europe, emission controls that aimed at restoring ecological status were based on hindcasts from process-based models or paleolimnological reconstructions. For instance, 1860 is used in Europe as the target for restoration from acidification concerning biological and chemical parameters. A more practical problem is that the historical states of ecosystems and their function cannot be observed directly. Therefore, we (i) compare estimates of acidification based on long-term observations of roach (Rutilus rutilus) populations with hindcast pH from the hydrogeochemical model MAGIC; (ii) discuss policy implications and possible scope for use of long-term archival data for assessing human impacts on the natural environment and (iii) present a novel conceptual model for interpreting the importance of physico-chemical and ecological deviations from reference conditions. Of the 85 lakes studied, 78 were coherently classified by both methods. In 1980, 28 lakes were classified as acidified with the MAGIC model, however, roach was present in 14 of these. In 2010, MAGIC predicted chemical recovery in 50% of the lakes, however roach only recolonized in five lakes after 1990, showing a lag between chemical and biological recovery. Our study is the first study of its kind to use long-term archival biological data in concert with hydrogeochemical modeling for regional assessments of anthropogenic acidification. Based on our results, we show how the conceptual model can be used to understand and prioritize management of physico-chemical and ecological effects of anthropogenic stressors on surface water quality. © 2014 The Authors Global Change Biology Published by John Wiley & Sons Ltd.

Building adaptive connectionist-based controllers: review of experiments in human-robot interaction, collective robotics, and computational neuroscience

NASA Astrophysics Data System (ADS)

Billard, Aude

2000-10-01

This paper summarizes a number of experiments in biologically inspired robotics. The common feature to all experiments is the use of artificial neural networks as the building blocks for the controllers. The experiments speak in favor of using a connectionist approach for designing adaptive and flexible robot controllers, and for modeling neurological processes. I present 1) DRAMA, a novel connectionist architecture, which has general property for learning time series and extracting spatio-temporal regularities in multi-modal and highly noisy data; 2) Robota, a doll-shaped robot, which imitates and learns a proto-language; 3) an experiment in collective robotics, where a group of 4 to 15 Khepera robots learn dynamically the topography of an environment whose features change frequently; 4) an abstract, computational model of primate ability to learn by imitation; 5) a model for the control of locomotor gaits in a quadruped legged robot.

Is the efficacy of biological control against plant diseases likely to be more durable than that of chemical pesticides?

PubMed Central

Bardin, Marc; Ajouz, Sakhr; Comby, Morgane; Lopez-Ferber, Miguel; Graillot, Benoît; Siegwart, Myriam; Nicot, Philippe C.

2015-01-01

The durability of a control method for plant protection is defined as the persistence of its efficacy in space and time. It depends on (i) the selection pressure exerted by it on populations of plant pathogens and (ii) on the capacity of these pathogens to adapt to the control method. Erosion of effectiveness of conventional plant protection methods has been widely studied in the past. For example, apparition of resistance to chemical pesticides in plant pathogens or pests has been extensively documented. The durability of biological control has often been assumed to be higher than that of chemical control. Results concerning pest management in agricultural systems have shown that this assumption may not always be justified. Resistance of various pests to one or several toxins of Bacillus thuringiensis and apparition of resistance of the codling moth Cydia pomonella to the C. pomonella granulovirus have, for example, been described. In contrast with the situation for pests, the durability of biological control of plant diseases has hardly been studied and no scientific reports proving the loss of efficiency of biological control agents against plant pathogens in practice has been published so far. Knowledge concerning the possible erosion of effectiveness of biological control is essential to ensure a durable efficacy of biological control agents on target plant pathogens. This knowledge will result in identifying risk factors that can foster the selection of strains of plant pathogens resistant to biological control agents. It will also result in identifying types of biological control agents with lower risk of efficacy loss, i.e., modes of action of biological control agents that does not favor the selection of resistant isolates in natural populations of plant pathogens. An analysis of the scientific literature was then conducted to assess the potential for plant pathogens to become resistant to biological control agents. PMID:26284088

Eradication and control of livestock ticks: biological, economic and social perspectives.

PubMed

Walker, Alan R

2011-07-01

Comparisons of successful and failed attempts to eradicate livestock ticks reveal that the social context of farming and management of the campaigns have greater influence than techniques of treatment. The biology of ticks is considered principally where it has contributed to control of ticks as practiced on farms. The timing of treatments by life cycle and season can be exploited to reduce numbers of treatments per year. Pastures can be managed to starve and desiccate vulnerable larvae questing on vegetation. Immunity to ticks acquired by hosts can be enhanced by livestock breeding. The aggregated distribution of ticks on hosts with poor immunity can be used to select animals for removal from the herd. Models of tick population dynamics required for predicting outcomes of control methods need better understanding of drivers of distribution, aggregation, stability, and density-dependent mortality. Changing social circumstances, especially of land-use, has an influence on exposure to tick-borne pathogens that can be exploited for disease control.

The Ecological Areawide Management (TEAM) of leafy spurge program of the United States Department of Agriculture-Agricultural Research Service.

PubMed

Anderson, Gerald L; Prosser, Chad W; Wendel, Lloyd E; Delfosse, Ernest S; Faust, Robert M

2003-01-01

The Ecological Areawide Management (TEAM) of Leafy Spurge program was developed to focus research and control efforts on a single weed, leafy spurge, and demonstrate the effectiveness of a coordinated, biologically based, integrated pest management program (IPM). This was accomplished through partnerships and teamwork that clearly demonstrated the advantages of the biologically based IPM approach. However, the success of regional weed control programs horizontally across several states and provinces also requires a vertical integration of several sectors of society. Awareness and education are the essential elements of vertical integration. Therefore, a substantial effort was made to produce a wide variety of information products specifically designed to educate different segments of society. During its tenure, land managers and agency decision makers have seen the potential of using the TEAM approach to accelerate the regional control of leafy spurge. The example set by the TEAM organization and participants is viewed as a model for future weed-control efforts.

Shared control of gene expression in bacteria by transcription factors and global physiology of the cell

PubMed Central

Berthoumieux, Sara; de Jong, Hidde; Baptist, Guillaume; Pinel, Corinne; Ranquet, Caroline; Ropers, Delphine; Geiselmann, Johannes

2013-01-01

Gene expression is controlled by the joint effect of (i) the global physiological state of the cell, in particular the activity of the gene expression machinery, and (ii) DNA-binding transcription factors and other specific regulators. We present a model-based approach to distinguish between these two effects using time-resolved measurements of promoter activities. We demonstrate the strength of the approach by analyzing a circuit involved in the regulation of carbon metabolism in E. coli. Our results show that the transcriptional response of the network is controlled by the physiological state of the cell and the signaling metabolite cyclic AMP (cAMP). The absence of a strong regulatory effect of transcription factors suggests that they are not the main coordinators of gene expression changes during growth transitions, but rather that they complement the effect of global physiological control mechanisms. This change of perspective has important consequences for the interpretation of transcriptome data and the design of biological networks in biotechnology and synthetic biology. PMID:23340840

Illuminating the landscape of host–pathogen interactions with the bacterium Listeria monocytogenes

PubMed Central

Cossart, Pascale

2011-01-01

Listeria monocytogenes has, in 25 y, become a model in infection biology. Through the analysis of both its saprophytic life and infectious process, new concepts in microbiology, cell biology, and pathogenesis have been discovered. This review will update our knowledge on this intracellular pathogen and highlight the most recent breakthroughs. Promising areas of investigation such as the increasingly recognized relevance for the infectious process, of RNA-mediated regulations in the bacterium, and the role of bacterially controlled posttranslational and epigenetic modifications in the host will also be discussed. PMID:22114192

Modulation of TLR2 protein expression by a miR-105 in human oral keratinocytes

EPA Science Inventory

Mammalian biological processes such as inflammation, involve regulation of hundreds of genes controlling onset and termination. MicroRNAs (miRNAs) can translationally repress target mRNAs and can regulate innate immune responses. Our model system comprised primary human keratinoc...

Apple miRNAs and tasiRNAs with novel regulatory networks

USDA-ARS?s Scientific Manuscript database

MiRNAs, negatively affecting gene expression at the post-transcriptional levels, have been shown to control numerous genes involved in various biological and metabolic processes. To date, the identification of miRNAs in plants focused on certain model plants, such as Arabidopsis and rice. Investig...

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

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

NONE

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Behavioural system identification of visual flight speed control in Drosophila melanogaster

PubMed Central

Rohrseitz, Nicola; Fry, Steven N.

2011-01-01

Behavioural control in many animals involves complex mechanisms with intricate sensory-motor feedback loops. Modelling allows functional aspects to be captured without relying on a description of the underlying complex, and often unknown, mechanisms. A wide range of engineering techniques are available for modelling, but their ability to describe time-continuous processes is rarely exploited to describe sensory-motor control mechanisms in biological systems. We performed a system identification of visual flight speed control in the fruitfly Drosophila, based on an extensive dataset of open-loop responses previously measured under free flight conditions. We identified a second-order under-damped control model with just six free parameters that well describes both the transient and steady-state characteristics of the open-loop data. We then used the identified control model to predict flight speed responses after a visual perturbation under closed-loop conditions and validated the model with behavioural measurements performed in free-flying flies under the same closed-loop conditions. Our system identification of the fruitfly's flight speed response uncovers the high-level control strategy of a fundamental flight control reflex without depending on assumptions about the underlying physiological mechanisms. The results are relevant for future investigations of the underlying neuromotor processing mechanisms, as well as for the design of biomimetic robots, such as micro-air vehicles. PMID:20525744

Behavioural system identification of visual flight speed control in Drosophila melanogaster.

PubMed

Rohrseitz, Nicola; Fry, Steven N

2011-02-06

Behavioural control in many animals involves complex mechanisms with intricate sensory-motor feedback loops. Modelling allows functional aspects to be captured without relying on a description of the underlying complex, and often unknown, mechanisms. A wide range of engineering techniques are available for modelling, but their ability to describe time-continuous processes is rarely exploited to describe sensory-motor control mechanisms in biological systems. We performed a system identification of visual flight speed control in the fruitfly Drosophila, based on an extensive dataset of open-loop responses previously measured under free flight conditions. We identified a second-order under-damped control model with just six free parameters that well describes both the transient and steady-state characteristics of the open-loop data. We then used the identified control model to predict flight speed responses after a visual perturbation under closed-loop conditions and validated the model with behavioural measurements performed in free-flying flies under the same closed-loop conditions. Our system identification of the fruitfly's flight speed response uncovers the high-level control strategy of a fundamental flight control reflex without depending on assumptions about the underlying physiological mechanisms. The results are relevant for future investigations of the underlying neuromotor processing mechanisms, as well as for the design of biomimetic robots, such as micro-air vehicles.

Modeling and control of a dielectric elastomer actuator

NASA Astrophysics Data System (ADS)

Gupta, Ujjaval; Gu, Guo-Ying; Zhu, Jian

2016-04-01

The emerging field of soft robotics offers the prospect of applying soft actuators as artificial muscles in the robots, replacing traditional actuators based on hard materials, such as electric motors, piezoceramic actuators, etc. Dielectric elastomers are one class of soft actuators, which can deform in response to voltage and can resemble biological muscles in the aspects of large deformation, high energy density and fast response. Recent research into dielectric elastomers has mainly focused on issues regarding mechanics, physics, material designs and mechanical designs, whereas less importance is given to the control of these soft actuators. Strong nonlinearities due to large deformation and electromechanical coupling make control of the dielectric elastomer actuators challenging. This paper investigates feed-forward control of a dielectric elastomer actuator by using a nonlinear dynamic model. The material and physical parameters in the model are identified by quasi-static and dynamic experiments. A feed-forward controller is developed based on this nonlinear dynamic model. Experimental evidence shows that this controller can control the soft actuator to track the desired trajectories effectively. The present study confirms that dielectric elastomer actuators are capable of being precisely controlled with the nonlinear dynamic model despite the presence of material nonlinearity and electromechanical coupling. It is expected that the reported results can promote the applications of dielectric elastomer actuators to soft robots or biomimetic robots.

From the track to the ocean: Using flow control to improve marine bio-logging tags for cetaceans

PubMed Central

Fiore, Giovani; Anderson, Erik; Garborg, C. Spencer; Murray, Mark; Johnson, Mark; Moore, Michael J.; Howle, Laurens

2017-01-01

Bio-logging tags are an important tool for the study of cetaceans, but superficial tags inevitably increase hydrodynamic loading. Substantial forces can be generated by tags on fast-swimming animals, potentially affecting behavior and energetics or promoting early tag removal. Streamlined forms have been used to reduce loading, but these designs can accelerate flow over the top of the tag. This non-axisymmetric flow results in large lift forces (normal to the animal) that become the dominant force component at high speeds. In order to reduce lift and minimize total hydrodynamic loading this work presents a new tag design (Model A) that incorporates a hydrodynamic body, a channel to reduce fluid speed differences above and below the housing and wing to redirect flow to counter lift. Additionally, three derivatives of the Model A design were used to examine the contribution of individual flow control features to overall performance. Hydrodynamic loadings of four models were compared using computational fluid dynamics (CFD). The Model A design eliminated all lift force and generated up to ~30 N of downward force in simulated 6 m/s aligned flow. The simulations were validated using particle image velocimetry (PIV) to experimentally characterize the flow around the tag design. The results of these experiments confirm the trends predicted by the simulations and demonstrate the potential benefit of flow control elements for the reduction of tag induced forces on the animal. PMID:28196148

Reading Quizzes Improve Exam Scores for Community College Students.

PubMed

Pape-Lindstrom, Pamela; Eddy, Sarah; Freeman, Scott

2018-06-01

To test the hypothesis that adding course structure may encourage self-regulated learning skills resulting in an increase in student exam performance in the community college setting, we added daily preclass online, open-book reading quizzes to an introductory biology course. We compared three control terms without reading quizzes and three experimental terms with online, open-book reading quizzes; the instructor of record, class size, and instructional time did not vary. Analyzing the Bloom's taxonomy level of a random sample of exam questions indicated a similar cognitive level of high-stakes assessments across all six terms in the study. To control for possible changes in student preparation or ability over time, we calculated each student's grade point average in courses other than biology during the term under study and included it as a predictor variable in our regression models. Our final model showed that students in the experimental terms had significantly higher exam scores than students in the control terms. This result shows that online reading quizzes can boost achievement in community college students. We also comment on the importance of discipline-based education research in community college settings and the structure of our community college/4-year institution collaboration.

Biological control: Insect pathogens, parasitoids, and predators

USDA-ARS?s Scientific Manuscript database

This book chapter provides an overview of biological control of insect pests of stored grain and stored products. The advantages and disadvantages of biological control for stored-product insect control are discussed. There are several species of protozoa, viruses, and bacteria that could be used to...

Switching Adaptability in Human-Inspired Sidesteps: A Minimal Model.

PubMed

Fujii, Keisuke; Yoshihara, Yuki; Tanabe, Hiroko; Yamamoto, Yuji

2017-01-01

Humans can adapt to abruptly changing situations by coordinating redundant components, even in bipedality. Conventional adaptability has been reproduced by various computational approaches, such as optimal control, neural oscillator, and reinforcement learning; however, the adaptability in bipedal locomotion necessary for biological and social activities, such as unpredicted direction change in chase-and-escape, is unknown due to the dynamically unstable multi-link closed-loop system. Here we propose a switching adaptation model for performing bipedal locomotion by improving autonomous distributed control, where autonomous actuators interact without central control and switch the roles for propulsion, balancing, and leg swing. Our switching mobility model achieved direction change at any time using only three actuators, although it showed higher motor costs than comparable models without direction change. Our method of evaluating such adaptation at any time should be utilized as a prerequisite for understanding universal motor control. The proposed algorithm may simply explain and predict the adaptation mechanism in human bipedality to coordinate the actuator functions within and between limbs.

Why we cannot conclude that sexual orientation is primarily a biological phenomenon.

PubMed

Byne, W

1997-01-01

While all mental phenomena must have an ultimate biological substrate, the precise contribution of biological factors to the development of sexual orientation remains to be elucidated. Does biology merely provide the slate of neural circuitry upon which sexual orientation is inscribed by experience? Do biological factors directly wire the brain so that it will support a particular orientation? Or do biological factors influence sexual orientation only indirectly, perhaps by influencing personality variables that in turn influence how one interacts with and shapes the environment as it contributes to the social relationships and experiences that shape sexual orientation as it emerges developmentally? Recent neurostructural and genetic linkage evidence pertaining to sexual orientation must be viewed tentatively until it has been adequately corroborated and integrated with psychological and cultural models. Moreover, even a reliable and robust correlation between a biological marker and sexual orientation would be equally compatible with the second and third possibilities delineated above. Yet if the third possibility more closely approximates reality, the search for predisposing biological factors will result in incomplete and misleading findings until their interactions with environmental factors are taken into account and controlled for in adequate longitudinal studies.

The Grand Challenges of Command and Control Policy

DTIC Science & Technology

2006-06-01

Memetic Warfare Memes are ideas that can be modeled and simulated. In a modern journalistic environment, dynamic information feedback from the theater...output type such that both adversarial meme processes and our counter anti- memetic activity could be modeled, simulated, and assessed. I am now...opposing force of the consequence of using biological or chemical weapons on the invading American forces. Do we have the proper memetic dynamics

Neuromechanical tuning of nonlinear postural control dynamics

NASA Astrophysics Data System (ADS)

Ting, Lena H.; van Antwerp, Keith W.; Scrivens, Jevin E.; McKay, J. Lucas; Welch, Torrence D. J.; Bingham, Jeffrey T.; DeWeerth, Stephen P.

2009-06-01

Postural control may be an ideal physiological motor task for elucidating general questions about the organization, diversity, flexibility, and variability of biological motor behaviors using nonlinear dynamical analysis techniques. Rather than presenting "problems" to the nervous system, the redundancy of biological systems and variability in their behaviors may actually be exploited to allow for the flexible achievement of multiple and concurrent task-level goals associated with movement. Such variability may reflect the constant "tuning" of neuromechanical elements and their interactions for movement control. The problem faced by researchers is that there is no one-to-one mapping between the task goal and the coordination of the underlying elements. We review recent and ongoing research in postural control with the goal of identifying common mechanisms underlying variability in postural control, coordination of multiple postural strategies, and transitions between them. We present a delayed-feedback model used to characterize the variability observed in muscle coordination patterns during postural responses to perturbation. We emphasize the significance of delays in physiological postural systems, requiring the modulation and coordination of both the instantaneous, "passive" response to perturbations as well as the delayed, "active" responses to perturbations. The challenge for future research lies in understanding the mechanisms and principles underlying neuromechanical tuning of and transitions between the diversity of postural behaviors. Here we describe some of our recent and ongoing studies aimed at understanding variability in postural control using physical robotic systems, human experiments, dimensional analysis, and computational models that could be enhanced from a nonlinear dynamics approach.

Agonist-antagonist active knee prosthesis: a preliminary study in level-ground walking.

PubMed

Martinez-Villalpando, Ernesto C; Herr, Hugh

2009-01-01

We present a powered knee prosthesis with two series-elastic actuators positioned in parallel in an agonist-antagonist arrangement. To motivate the knee's design, we developed a prosthetic knee model that comprises a variable damper and two series-elastic clutch units that span the knee joint. Using human gait data to constrain the model's joint to move biologically, we varied model parameters using an optimization scheme that minimized the sum over time of the squared difference between the model's joint torque and biological knee values. We then used these optimized values to specify the mechanical and control design of the prosthesis for level-ground walking. We hypothesized that a variable-impedance control design could produce humanlike knee mechanics during steady-state level-ground walking. As a preliminary evaluation of this hypothesis, we compared the prosthetic knee mechanics of an amputee walking at a self-selected gait speed with those of a weight- and height-matched nonamputee. We found qualitative agreement between prosthetic and human knee mechanics. Because the knee's motors never perform positive work on the knee joint throughout the level-ground gait cycle, the knee's electrical power requirement is modest in walking (8 W), decreasing the size of the onboard battery required to power the prosthesis.

A Compact Synchronous Cellular Model of Nonlinear Calcium Dynamics: Simulation and FPGA Synthesis Results.

PubMed

Soleimani, Hamid; Drakakis, Emmanuel M

2017-06-01

Recent studies have demonstrated that calcium is a widespread intracellular ion that controls a wide range of temporal dynamics in the mammalian body. The simulation and validation of such studies using experimental data would benefit from a fast large scale simulation and modelling tool. This paper presents a compact and fully reconfigurable cellular calcium model capable of mimicking Hopf bifurcation phenomenon and various nonlinear responses of the biological calcium dynamics. The proposed cellular model is synthesized on a digital platform for a single unit and a network model. Hardware synthesis, physical implementation on FPGA, and theoretical analysis confirm that the proposed cellular model can mimic the biological calcium behaviors with considerably low hardware overhead. The approach has the potential to speed up large-scale simulations of slow intracellular dynamics by sharing more cellular units in real-time. To this end, various networks constructed by pipelining 10 k to 40 k cellular calcium units are compared with an equivalent simulation run on a standard PC workstation. Results show that the cellular hardware model is, on average, 83 times faster than the CPU version.

Operation and model description of a sequencing batch reactor treating reject water for biological nitrogen removal via nitrite.

PubMed

Dosta, J; Galí, A; Benabdallah El-Hadj, T; Macé, S; Mata-Alvarez, J

2007-08-01

The aim of this study was the operation and model description of a sequencing batch reactor (SBR) for biological nitrogen removal (BNR) from a reject water (800-900 mg NH(4)(+)-NL(-1)) from a municipal wastewater treatment plant (WWTP). The SBR was operated with three cycles per day, temperature 30 degrees C, SRT 11 days and HRT 1 day. During the operational cycle, three alternating oxic/anoxic periods were performed to avoid alkalinity restrictions. Oxygen supply and working pH range were controlled to achieve the BNR via nitrite, which makes the process more economical. Under steady state conditions, a total nitrogen removal of 0.87 kg N (m(3)day)(-1) was reached. A four-step nitrogen removal model was developed to describe the process. This model enlarges the IWA activated sludge models for a more detailed description of the nitrogen elimination processes and their inhibitions. A closed intermittent-flow respirometer was set up for the estimation of the most relevant model parameters. Once calibrated, model predictions reproduced experimental data accurately.

The (Mathematical) Modeling Process in Biosciences.

PubMed

Torres, Nestor V; Santos, Guido

2015-01-01

In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology.

Encyrtid parasitoids of soft scale insects: biology, behavior, and their use in biological control.

PubMed

Kapranas, Apostolos; Tena, Alejandro

2015-01-07

Parasitoids of the hymenopterous family Encyrtidae are one of the most important groups of natural enemies of soft scale insects and have been used extensively in biological control. We summarize existing knowledge of the biology, ecology, and behavior of these parasitoids and how it relates to biological control. Soft scale stage/size and phenology are important determinants of host range and host utilization, which are key aspects in understanding how control by these parasitoids is exerted. Furthermore, the nutritional ecology of encyrtids and their physiological interactions with their hosts affect soft scale insect population dynamics. Lastly, the interactions among encyrtids, heteronomous parasitoids, and ants shape parasitoid species complexes and consequently have a direct impact on the biological control of soft scale insects.

Developing PFC representations using reinforcement learning.

PubMed

Reynolds, Jeremy R; O'Reilly, Randall C

2009-12-01

From both functional and biological considerations, it is widely believed that action production, planning, and goal-oriented behaviors supported by the frontal cortex are organized hierarchically [Fuster (1991); Koechlin, E., Ody, C., & Kouneiher, F. (2003). Neuroscience: The architecture of cognitive control in the human prefrontal cortex. Science, 424, 1181-1184; Miller, G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the structure of behavior. New York: Holt]. However, the nature of the different levels of the hierarchy remains unclear, and little attention has been paid to the origins of such a hierarchy. We address these issues through biologically-inspired computational models that develop representations through reinforcement learning. We explore several different factors in these models that might plausibly give rise to a hierarchical organization of representations within the PFC, including an initial connectivity hierarchy within PFC, a hierarchical set of connections between PFC and subcortical structures controlling it, and differential synaptic plasticity schedules. Simulation results indicate that architectural constraints contribute to the segregation of different types of representations, and that this segregation facilitates learning. These findings are consistent with the idea that there is a functional hierarchy in PFC, as captured in our earlier computational models of PFC function and a growing body of empirical data.

Peripersonal Space and Margin of Safety around the Body: Learning Visuo-Tactile Associations in a Humanoid Robot with Artificial Skin

PubMed Central

Roncone, Alessandro; Fadiga, Luciano; Metta, Giorgio

2016-01-01

This paper investigates a biologically motivated model of peripersonal space through its implementation on a humanoid robot. Guided by the present understanding of the neurophysiology of the fronto-parietal system, we developed a computational model inspired by the receptive fields of polymodal neurons identified, for example, in brain areas F4 and VIP. The experiments on the iCub humanoid robot show that the peripersonal space representation i) can be learned efficiently and in real-time via a simple interaction with the robot, ii) can lead to the generation of behaviors like avoidance and reaching, and iii) can contribute to the understanding the biological principle of motor equivalence. More specifically, with respect to i) the present model contributes to hypothesizing a learning mechanisms for peripersonal space. In relation to point ii) we show how a relatively simple controller can exploit the learned receptive fields to generate either avoidance or reaching of an incoming stimulus and for iii) we show how the robot can select arbitrary body parts as the controlled end-point of an avoidance or reaching movement. PMID:27711136

Biological Control Strategies for Mosquito Vectors of Arboviruses.

PubMed

Huang, Yan-Jang S; Higgs, Stephen; Vanlandingham, Dana L

2017-02-10

Historically, biological control utilizes predatory species and pathogenic microorganisms to reduce the population of mosquitoes as disease vectors. This is particularly important for the control of mosquito-borne arboviruses, which normally do not have specific antiviral therapies available. Although development of resistance is likely, the advantages of biological control are that the resources used are typically biodegradable and ecologically friendly. Over the past decade, the advancement of molecular biology has enabled optimization by the manipulation of genetic materials associated with biological control agents. Two significant advancements are the discovery of cytoplasmic incompatibility induced by Wolbachia bacteria, which has enhanced replacement programs, and the introduction of dominant lethal genes into local mosquito populations through the release of genetically modified mosquitoes. As various arboviruses continue to be significant public health threats, biological control strategies have evolved to be more diverse and become critical tools to reduce the disease burden of arboviruses.

Biological Control Strategies for Mosquito Vectors of Arboviruses

PubMed Central

Huang, Yan-Jang S.; Higgs, Stephen; Vanlandingham, Dana L.

2017-01-01

Historically, biological control utilizes predatory species and pathogenic microorganisms to reduce the population of mosquitoes as disease vectors. This is particularly important for the control of mosquito-borne arboviruses, which normally do not have specific antiviral therapies available. Although development of resistance is likely, the advantages of biological control are that the resources used are typically biodegradable and ecologically friendly. Over the past decade, the advancement of molecular biology has enabled optimization by the manipulation of genetic materials associated with biological control agents. Two significant advancements are the discovery of cytoplasmic incompatibility induced by Wolbachia bacteria, which has enhanced replacement programs, and the introduction of dominant lethal genes into local mosquito populations through the release of genetically modified mosquitoes. As various arboviruses continue to be significant public health threats, biological control strategies have evolved to be more diverse and become critical tools to reduce the disease burden of arboviruses. PMID:28208639

The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes

USGS Publications Warehouse

Pangle, Luke A.; DeLong, Stephen B.; Abramson, Nate; Adams, John; Barron-Gafford, Greg A.; Breshears, David D.; Brooks, Paul D.; Chorover, Jon; Dietrich, William E.; Dontsova, Katerina; Durcik, Matej; Espeleta, Javier; Ferré, T.P.A.; Ferriere, Regis; Henderson, Whitney; Hunt, Edward A.; Huxman, Travis E.; Millar, David; Murphy, Brendan; Niu, Guo-Yue; Pavao-Zuckerman, Mitch; Pelletier, Jon D.; Rasmussen, Craig; Ruiz, Joaquin; Saleska, Scott; Schaap, Marcel; Sibayan, Michael; Troch, Peter A.; Tuller, Markus; van Haren, Joost; Zeng, Xubin

2015-01-01

Zero-order drainage basins, and their constituent hillslopes, are the fundamental geomorphic unit comprising much of Earth's uplands. The convergent topography of these landscapes generates spatially variable substrate and moisture content, facilitating biological diversity and influencing how the landscape filters precipitation and sequesters atmospheric carbon dioxide. In light of these significant ecosystem services, refining our understanding of how these functions are affected by landscape evolution, weather variability, and long-term climate change is imperative. In this paper we introduce the Landscape Evolution Observatory (LEO): a large-scale controllable infrastructure consisting of three replicated artificial landscapes (each 330 m2 surface area) within the climate-controlled Biosphere 2 facility in Arizona, USA. At LEO, experimental manipulation of rainfall, air temperature, relative humidity, and wind speed are possible at unprecedented scale. The Landscape Evolution Observatory was designed as a community resource to advance understanding of how topography, physical and chemical properties of soil, and biological communities coevolve, and how this coevolution affects water, carbon, and energy cycles at multiple spatial scales. With well-defined boundary conditions and an extensive network of sensors and samplers, LEO enables an iterative scientific approach that includes numerical model development and virtual experimentation, physical experimentation, data analysis, and model refinement. We plan to engage the broader scientific community through public dissemination of data from LEO, collaborative experimental design, and community-based model development.

Control of Mycobacterial Infections in Mice Expressing Human Tumor Necrosis Factor (TNF) but Not Mouse TNF.

PubMed

Olleros, Maria L; Chavez-Galan, Leslie; Segueni, Noria; Bourigault, Marie L; Vesin, Dominique; Kruglov, Andrey A; Drutskaya, Marina S; Bisig, Ruth; Ehlers, Stefan; Aly, Sahar; Walter, Kerstin; Kuprash, Dmitry V; Chouchkova, Miliana; Kozlov, Sergei V; Erard, François; Ryffel, Bernard; Quesniaux, Valérie F J; Nedospasov, Sergei A; Garcia, Irene

2015-09-01

Tumor necrosis factor (TNF) is an important cytokine for host defense against pathogens but is also associated with the development of human immunopathologies. TNF blockade effectively ameliorates many chronic inflammatory conditions but compromises host immunity to tuberculosis. The search for novel, more specific human TNF blockers requires the development of a reliable animal model. We used a novel mouse model with complete replacement of the mouse TNF gene by its human ortholog (human TNF [huTNF] knock-in [KI] mice) to determine resistance to Mycobacterium bovis BCG and M. tuberculosis infections and to investigate whether TNF inhibitors in clinical use reduce host immunity. Our results show that macrophages from huTNF KI mice responded to BCG and lipopolysaccharide similarly to wild-type macrophages by NF-κB activation and cytokine production. While TNF-deficient mice rapidly succumbed to mycobacterial infection, huTNF KI mice survived, controlling the bacterial burden and activating bactericidal mechanisms. Administration of TNF-neutralizing biologics disrupted the control of mycobacterial infection in huTNF KI mice, leading to an increased bacterial burden and hyperinflammation. Thus, our findings demonstrate that human TNF can functionally replace murine TNF in vivo, providing mycobacterial resistance that could be compromised by TNF neutralization. This new animal model will be helpful for the testing of specific biologics neutralizing human TNF. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-01-01

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

Some Applications of Piece-Wise Smooth Dynamical Systems

NASA Astrophysics Data System (ADS)

Janovská, Drahoslava; Hanus, Tomáš; Biák, Martin

2010-09-01

The Filippov systems theory is applied to selected problems from biology and chemical engineering, namely we explore and simulate Bazykin's ecological model, an ideal closed gas-liquid system including its dimensionless formulation. The last investigated system is a CSTR with an outfall and the CSTR with a reactor volume control.

Hemispheric Dissociation and Dyslexia in a Computational Model of Reading

ERIC Educational Resources Information Center

Monaghan, Padraic; Shillcock, Richard

2008-01-01

There are several causal explanations for dyslexia, drawing on distinctions between dyslexics and control groups at genetic, biological, or cognitive levels of description. However, few theories explicitly bridge these different levels of description. In this paper, we review a long-standing theory that some dyslexics' reading impairments are due…

Identifying critical life stage transitions for biological control of long-lived perennial Vincetoxicum species

USDA-ARS?s Scientific Manuscript database

Demographic matrix modeling of invasive plant populations can be a powerful tool to identify key life stage transitions for targeted disruption in order to cause population decline. This approach can provide quantitative estimates of reductions in select vital rates needed to reduce population growt...

Modeling pesticide diuron loading from the San Joaquin watershed into the Sacramento-San Joaquin Delta using SWAT

USDA-ARS?s Scientific Manuscript database

Quantitative information on pesticide loading into the Sacramento-San Joaquin Delta waterways of northern California is critical for water resource management in the region, and potentially useful for biological weed control planning. The San Joaquin watershed, an agriculturally intensive area, is a...

Network Analyses in Plant Pathogens.

PubMed

Botero, David; Alvarado, Camilo; Bernal, Adriana; Danies, Giovanna; Restrepo, Silvia

2018-01-01

Even in the age of big data in Biology, studying the connections between the biological processes and the molecular mechanisms behind them is a challenging task. Systems biology arose as a transversal discipline between biology, chemistry, computer science, mathematics, and physics to facilitate the elucidation of such connections. A scenario, where the application of systems biology constitutes a very powerful tool, is the study of interactions between hosts and pathogens using network approaches. Interactions between pathogenic bacteria and their hosts, both in agricultural and human health contexts are of great interest to researchers worldwide. Large amounts of data have been generated in the last few years within this area of research. However, studies have been relatively limited to simple interactions. This has left great amounts of data that remain to be utilized. Here, we review the main techniques in network analysis and their complementary experimental assays used to investigate bacterial-plant interactions. Other host-pathogen interactions are presented in those cases where few or no examples of plant pathogens exist. Furthermore, we present key results that have been obtained with these techniques and how these can help in the design of new strategies to control bacterial pathogens. The review comprises metabolic simulation, protein-protein interactions, regulatory control of gene expression, host-pathogen modeling, and genome evolution in bacteria. The aim of this review is to offer scientists working on plant-pathogen interactions basic concepts around network biology, as well as an array of techniques that will be useful for a better and more complete interpretation of their data.

Status of biological control in vegetation management in forestry

Treesearch

George P. Markin; Donald E. Gardner

1993-01-01

Biological control traditionally depends upon importing the natural enemies of introduced weeds. Since vegetation management in forestry has primarily been aimed at protecting economic species of trees from competition from other native plants, biological control has been of little use in forestry. An alternative approach to controlling unwanted native plants,...

Pythium species and isolate diversity influence inhibition by the biological control agent Streptomyces lydicus

USDA-ARS?s Scientific Manuscript database

Disease control of soilborne pathogens by biological control agents has often been inconsistent under field conditions. One factor that may contribute to this inconsistency is the variability in response among pathogen populations and/or communities to the selected biological control agent. One hund...

Improved understanding of weed biological control safety and impact with chemical ecology: a review

USDA-ARS?s Scientific Manuscript database

We review chemical ecology literature as it relates to weed biological control and discuss how this means of controlling invasive plants could be enhanced by the consideration of several well established research developments. The interface between chemical ecology and weed biological control presen...

Analysis of the Sheltered Instruction Observation Protocol Model on Academic Performance of English Language Learners

NASA Astrophysics Data System (ADS)

Ingram, Sandra W.

This quantitative comparative descriptive study involved analyzing archival data from end-of-course (EOC) test scores in biology of English language learners (ELLs) taught or not taught using the sheltered instruction observation protocol (SIOP) model. The study includes descriptions and explanations of the benefits of the SIOP model to ELLs, especially in content area subjects such as biology. Researchers have shown that ELLs in high school lag behind their peers in academic achievement in content area subjects. Much of the research on the SIOP model took place in elementary and middle school, and more research was necessary at the high school level. This study involved analyzing student records from archival data to describe and explain if the SIOP model had an effect on the EOC test scores of ELLs taught or not taught using it. The sample consisted of 527 Hispanic students (283 females and 244 males) from Grades 9-12. An independent sample t-test determined if a significant difference existed in the mean EOC test scores of ELLs taught using the SIOP model as opposed to ELLs not taught using the SIOP model. The results indicated that a significant difference existed between EOC test scores of ELLs taught using the SIOP model and ELLs not taught using the SIOP model (p = .02). A regression analysis indicated a significant difference existed in the academic performance of ELLs taught using the SIOP model in high school science, controlling for free and reduced-price lunch (p = .001) in predicting passing scores on the EOC test in biology at the school level. The data analyzed for free and reduced-price lunch together with SIOP data indicated that both together were not significant (p = .175) for predicting passing scores on the EOC test in high school biology. Future researchers should repeat the study with student-level data as opposed to school-level data, and data should span at least three years.

Structure-based control of complex networks with nonlinear dynamics

NASA Astrophysics Data System (ADS)

Zanudo, Jorge G. T.; Yang, Gang; Albert, Reka

What can we learn about controlling a system solely from its underlying network structure? Here we use a framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system towards any of its natural long term dynamic behaviors, regardless of the dynamic details and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of classical structural control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case, but not in specific model instances. This work was supported by NSF Grants PHY 1205840 and IIS 1160995. JGTZ is a recipient of a Stand Up To Cancer - The V Foundation Convergence Scholar Award.

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

PubMed

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 generic distributed biological systems.

Integrating systems biology models and biomedical ontologies

PubMed Central

2011-01-01

Background 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. Results 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. Conclusions 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. PMID:21835028

Design methodology and results evaluation of a heating functionality in modular lab-on-chip systems

NASA Astrophysics Data System (ADS)

Streit, Petra; Nestler, Joerg; Shaporin, Alexey; Graunitz, Jenny; Otto, Thomas

2018-06-01

Lab-on-a-chip (LoC) systems offer the opportunity of fast and customized biological analyses executed at the ‘point-of-need’ without expensive lab equipment. Some biological processes need a temperature treatment. Therefore, it is important to ensure a defined and stable temperature distribution in the biosensor area. An integrated heating functionality is realized with discrete resistive heating elements including temperature measurement. The focus of this contribution is a design methodology and evaluation technique of the temperature distribution in the biosensor area with regard to the thermal-electrical behaviour of the heat sources. Furthermore, a sophisticated control of the biosensor temperature is proposed. A finite element (FE) model with one and more integrated heat sources in a polymer-based LoC system is used to investigate the impact of the number and arrangement of heating elements on the temperature distribution around the heating elements and in the biosensor area. Based on this model, various LOC systems are designed and fabricated. Electrical characterization of the heat sources and independent temperature measurements with infrared technique are performed to verify the model parameters and prove the simulation approach. The FE model and the proposed methodology is the foundation for optimization and evaluation of new designs with regard to temperature requirements of the biosensor. Furthermore, a linear dependency of the heater temperature on the electric current is demonstrated in the targeted temperature range of 20 °C to 70 °C enabling the usage of the heating functionality for biological reactions requiring a steady-state temperature up to 70 °C. The correlation between heater and biosensor area temperature is derived for a direct control through the heating current.

Reconstructing the regulatory circuit of cell fate determination in yeast mating response.

PubMed

Shao, Bin; Yuan, Haiyu; Zhang, Rongfei; Wang, Xuan; Zhang, Shuwen; Ouyang, Qi; Hao, Nan; Luo, Chunxiong

2017-07-01

Massive technological advances enabled high-throughput measurements of proteomic changes in biological processes. However, retrieving biological insights from large-scale protein dynamics data remains a challenging task. Here we used the mating differentiation in yeast Saccharomyces cerevisiae as a model and developed integrated experimental and computational approaches to analyze the proteomic dynamics during the process of cell fate determination. When exposed to a high dose of mating pheromone, the yeast cell undergoes growth arrest and forms a shmoo-like morphology; however, at intermediate doses, chemotropic elongated growth is initialized. To understand the gene regulatory networks that control this differentiation switch, we employed a high-throughput microfluidic imaging system that allows real-time and simultaneous measurements of cell growth and protein expression. Using kinetic modeling of protein dynamics, we classified the stimulus-dependent changes in protein abundance into two sources: global changes due to physiological alterations and gene-specific changes. A quantitative framework was proposed to decouple gene-specific regulatory modes from the growth-dependent global modulation of protein abundance. Based on the temporal patterns of gene-specific regulation, we established the network architectures underlying distinct cell fates using a reverse engineering method and uncovered the dose-dependent rewiring of gene regulatory network during mating differentiation. Furthermore, our results suggested a potential crosstalk between the pheromone response pathway and the target of rapamycin (TOR)-regulated ribosomal biogenesis pathway, which might underlie a cell differentiation switch in yeast mating response. In summary, our modeling approach addresses the distinct impacts of the global and gene-specific regulation on the control of protein dynamics and provides new insights into the mechanisms of cell fate determination. We anticipate that our integrated experimental and modeling strategies could be widely applicable to other biological systems.

Hemoglobin mass and biological passport for the detection of autologous blood doping.

PubMed

Pottgiesser, Torben; Echteler, Tobias; Sottas, Pierre-Edouard; Umhau, Markus; Schumacher, Yorck Olaf

2012-05-01

The most promising attempt to reveal otherwise undetectable autologous blood doping is the Athlete Biological Passport enabling a longitudinal monitoring of hematological measures. Recently, the determination of hemoglobin mass (tHb) was suggested to be incorporated in the adaptive model of the Athlete Biological Passport. The purpose therefore was to evaluate the performance of tHb as part of the adaptive model for the detection of autologous blood transfusions in a longitudinal blinded study. Twenty-one subjects were divided into a doped group (n = 11) and a control group (n = 10). During the time course of a simulated cycling season (42 wk) including three major competitions (Classics, Grand Tour, World Championships), multiple autologous transfusions of erythrocyte concentrates were assigned in the doped group. A blinded investigator ordered up to 10 tHb measurements (carbon monoxide rebreathing) per subject, mimicking an intelligent doping testing approach in obtaining hematological data (tHb, OFFmass (novel marker including reticulocytes), and respective sequences) for the adaptive model. The final analysis included 199 of 206 overall tHb measurements. The use of tHb, OFFmass, and their sequences as markers of the adaptive model at the 99% specificity level allowed identification of 10 of 11 doped subjects (91% sensitivity) including one false positive in the control group. At the 99.9% specificity level, 8 of 11 subjects were identified without false positives (73% sensitivity). It seems that the problems of tHb determination by carbon monoxide rebreathing limit the application of this method in antidoping. Because of its potential to detect individual abnormalities associated with autologous blood transfusions shown in this study, a method for tHb determination that is compatible with today's standards of testing should be the focus of future research.

Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation.

PubMed

Chisholm, Rebecca H; Lorenzi, Tommaso; Clairambault, Jean

2016-11-01

Drug-induced drug resistance in cancer has been attributed to diverse biological mechanisms at the individual cell or cell population scale, relying on stochastically or epigenetically varying expression of phenotypes at the single cell level, and on the adaptability of tumours at the cell population level. We focus on intra-tumour heterogeneity, namely between-cell variability within cancer cell populations, to account for drug resistance. To shed light on such heterogeneity, we review evolutionary mechanisms that encompass the great evolution that has designed multicellular organisms, as well as smaller windows of evolution on the time scale of human disease. We also present mathematical models used to predict drug resistance in cancer and optimal control methods that can circumvent it in combined therapeutic strategies. Plasticity in cancer cells, i.e., partial reversal to a stem-like status in individual cells and resulting adaptability of cancer cell populations, may be viewed as backward evolution making cancer cell populations resistant to drug insult. This reversible plasticity is captured by mathematical models that incorporate between-cell heterogeneity through continuous phenotypic variables. Such models have the benefit of being compatible with optimal control methods for the design of optimised therapeutic protocols involving combinations of cytotoxic and cytostatic treatments with epigenetic drugs and immunotherapies. Gathering knowledge from cancer and evolutionary biology with physiologically based mathematical models of cell population dynamics should provide oncologists with a rationale to design optimised therapeutic strategies to circumvent drug resistance, that still remains a major pitfall of cancer therapeutics. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016 Elsevier B.V. All rights reserved.

How do precision medicine and system biology response to human body's complex adaptability?

PubMed

Yuan, Bing

2016-12-01

In the field of life sciences, although system biology and "precision medicine" introduce some complex scientifific methods and techniques, it is still based on the "analysis-reconstruction" of reductionist theory as a whole. Adaptability of complex system increase system behaviour uncertainty as well as the difficulties of precise identifification and control. It also put systems biology research into trouble. To grasp the behaviour and characteristics of organism fundamentally, systems biology has to abandon the "analysis-reconstruction" concept. In accordance with the guidelines of complexity science, systems biology should build organism model from holistic level, just like the Chinese medicine did in dealing with human body and disease. When we study the living body from the holistic level, we will fifind the adaptability of complex system is not the obstacle that increases the diffificulty of problem solving. It is the "exceptional", "right-hand man" that helping us to deal with the complexity of life more effectively.

21 CFR 510.4 - Biologics; products subject to license control.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 6 2013-04-01 2013-04-01 false Biologics; products subject to license control... Biologics; products subject to license control. An animal drug produced and distributed in full conformance..., Drug, and Cosmetic Act. ...

21 CFR 510.4 - Biologics; products subject to license control.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 6 2011-04-01 2011-04-01 false Biologics; products subject to license control... Biologics; products subject to license control. An animal drug produced and distributed in full conformance..., Drug, and Cosmetic Act. ...

21 CFR 510.4 - Biologics; products subject to license control.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 6 2014-04-01 2014-04-01 false Biologics; products subject to license control... Biologics; products subject to license control. An animal drug produced and distributed in full conformance..., Drug, and Cosmetic Act. ...

Biomedical and Catalytic Opportunities of Virus-Like Particles in Nanotechnology.

PubMed

Schwarz, B; Uchida, M; Douglas, T

2017-01-01

Within biology, molecules are arranged in hierarchical structures that coordinate and control the many processes that allow for complex organisms to exist. Proteins and other functional macromolecules are often studied outside their natural nanostructural context because it remains difficult to create controlled arrangements of proteins at this size scale. Viruses are elegantly simple nanosystems that exist at the interface of living organisms and nonliving biological machines. Studied and viewed primarily as pathogens to be combatted, viruses have emerged as models of structural efficiency at the nanoscale and have spurred the development of biomimetic nanoparticle systems. Virus-like particles (VLPs) are noninfectious protein cages derived from viruses or other cage-forming systems. VLPs provide incredibly regular scaffolds for building at the nanoscale. Composed of self-assembling protein subunits, VLPs provide both a model for studying materials' assembly at the nanoscale and useful building blocks for materials design. The robustness and degree of understanding of many VLP structures allow for the ready use of these systems as versatile nanoparticle platforms for the conjugation of active molecules or as scaffolds for the structural organization of chemical processes. Lastly the prevalence of viruses in all domains of life has led to unique activities of VLPs in biological systems most notably the immune system. Here we discuss recent efforts to apply VLPs in a wide variety of applications with the aim of highlighting how the common structural elements of VLPs have led to their emergence as paradigms for the understanding and design of biological nanomaterials. © 2017 Elsevier Inc. All rights reserved.

Modeling the Temperature- and Age-Dependent Survival, Development, and Oviposition Rates of Stable Flies (Stomoxys calcitrans) (Diptera: Muscidae).

PubMed

Skovgård, Henrik; Nachman, Gösta

2017-10-01

Stable flies (Stomoxys calcitrans (L.)) can be a serious pest associated with cattle facilities. In Denmark, they occur most abundantly at organic farms, where they cannot be controlled by means of insecticides. On traditional farms, where chemical control is widely used, development of resistance is of increasing concern. Therefore, interest in biological control or other alternative methods has been growing during the recent years. In order to understand the complex relationships between a pest and its natural enemies in a variable environment, it is necessary to know how temperature affects the dynamics of the involved species. In this paper, we apply data derived from several existing sources to investigate the influence of temperature on development and survival of eggs, larvae, pupae, and adult stable flies, as well as on the fecundity of adult females. We demonstrate that the same modeling framework (called SANDY), previously applied to lifetable data of the pteromalid pupal parasitoid (Spalangia cameroni Perkins), a biological control agent used against stable flies, can also be used to model S. calcitrans. However, the predicted temperature responses depend on the data sources used to parameterize the model, which is reflected by differences in estimated population growth rates obtained from American and non-American studies. Elasticity analysis shows that growth rates are more sensitive to changes in viability, in particular of adult flies, than in fecundity, which may have implications for the management of stable fly populations. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

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

Stewart, R.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

TH-A-BRD-01: Radiation Biology for Radiation Therapy Physicists

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

Orton, C; Borras, C; Carlson, D

Mechanisms by which radiation kills cells and ways cell damage can be repaired will be reviewed. The radiobiological parameters of dose, fractionation, delivery time, dose rate, and LET will be discussed. The linear-quadratic model for cell survival for high and low dose rate treatments and the effect of repopulation will be presented and discussed. The rationale for various radiotherapy techniques such as conventional fractionation, hyperfractionation, hypofractionation, and low and high dose rate brachytherapy, including permanent implants, will be presented. The radiobiological principles underlying radiation protection guidelines and the different radiation dosimetry terms used in radiation biology and in radiation protectionmore » will be reviewed. Human data on radiation induced cancer, including increases in the risk of second cancers following radiation therapy, as well as data on radiation induced tissue reactions, such as cardiovascular effects, for follow up times up to 20–40 years, published by ICRP, NCRP and BEIR Committees, will be examined. The latest risk estimates per unit dose will be presented. Their adoption in recent radiation protection standards and guidelines and their impact on patient and workers safety in radiotherapy will be discussed. Biologically-guided radiotherapy (BGRT) provides a systematic method to derive prescription doses that integrate patient-specific information about tumor and normal tissue biology. Treatment individualization based on patient-specific biology requires the identification of biological objective functions to facilitate the design and comparison of competing treatment modalities. Biological objectives provide a more direct approach to plan optimization instead of relying solely on dose-based surrogates and can incorporate factors that alter radiation response, such as DNA repair, tumor hypoxia, and relative biological effectiveness. We review concepts motivating biological objectives and provide examples of how they might be used to address clinically relevant problems. Underlying assumptions and limitations of existing models and their proper application will be discussed. This multidisciplinary educational session combines the fundamentals of radiobiology for radiation therapy and radiation protection with the practical application of biophysical models for treatment planning and evaluation. Learning Objectives: To understand fractionation in teletherapy and dose rate techniques in brachytherapy. To understand how the linear-quadratic models the effect of radiobiological parameters for radiotherapy. To understand the radiobiological basis of radiation protection standards applied to radiotherapy. To distinguish between stochastic effects and tissue reactions. To learn how to apply concepts of biological effective dose and RBE-weighted dose and to incorporate biological factors that alter radiation response. To discuss clinical strategies to increase therapeutic ratio, i.e., maximize local control while minimizing the risk of acute and late normal tissue effects.« less

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

McMahon, S.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

WE-DE-202-01: Connecting Nanoscale Physics to Initial DNA Damage Through Track Structure Simulations

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

Schuemann, J.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Effects of help-seeking in a blended high school Biology class

NASA Astrophysics Data System (ADS)

Deguzman, Paolo

Distance learning provides an opportunity for students to learn valuable information through technology and interactive media. Distance learning additionally offers educational institutions the flexibility of synchronous and asynchronous instruction while increasing enrollment and lowering cost. However, distance education has not been well documented within the context of urban high schools. Distance learning may allow high school students to understand material at an individualized pace for either enrichment or remediation. A successful high school student who participates in distance learning should exhibit high self regulatory skills. However, most urban high school students have not been exposed to distance learning and should be introduced to proper self regulatory strategies that should increase the likelihood of understanding the material. To help facilitate a move into distance learning, a blended distance learning model, the combination of distance learning and traditional learning, will be used. According to O'Neil's (in preparation) revised problem solving model, self regulation is a component of problem solving. Within the Blended Biology course, urban high school students will be trained in help-seeking strategies to further their understanding of genetics and Punnett Square problem solving. This study investigated the effects of help-seeking in a blended high school Biology course. The main study consisted of a help-seeking group (n=55) and a control group (n=53). Both the help-seeking group and the control group were taught by one teacher for two weeks. The help-seeking group had access to Blended Biology with Help-Seeking while the control group only had access to Blended Biology. The main study used a pretest and posttest to measure Genetics Content Understanding, Punnett Square Problem Solving, Adaptive Help-Seeking, Maladaptive Help-Seeking, and Self Regulation. The analysis showed no significant difference in any of the measures in terms of help seeking. However, blended distance learning appeared to work as posttest means increased significantly from the pretest means. Future studies should consider the method of communication for help-seeking and help-giving within a high school distance learning context. Further studies should consider developing instruments to measure the difference in knowing when help is needed versus active choice.

Active machine learning-driven experimentation to determine compound effects on protein patterns.

PubMed

Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F

2016-02-03

High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance.

Germline Modification and Engineering in Avian Species

PubMed Central

Lee, Hong Jo; Lee, Hyung Chul; Han, Jae Yong

2015-01-01

Production of genome-edited animals using germline-competent cells and genetic modification tools has provided opportunities for investigation of biological mechanisms in various organisms. The recently reported programmed genome editing technology that can induce gene modification at a target locus in an efficient and precise manner facilitates establishment of animal models. In this regard, the demand for genome-edited avian species, which are some of the most suitable model animals due to their unique embryonic development, has also increased. Furthermore, germline chimera production through long-term culture of chicken primordial germ cells (PGCs) has facilitated research on production of genome-edited chickens. Thus, use of avian germline modification is promising for development of novel avian models for research of disease control and various biological mechanisms. Here, we discuss recent progress in genome modification technology in avian species and its applications and future strategies. PMID:26333275

Genomic data assimilation for estimating hybrid functional Petri net from time-course gene expression data.

PubMed

Nagasaki, Masao; Yamaguchi, Rui; Yoshida, Ryo; Imoto, Seiya; Doi, Atsushi; Tamada, Yoshinori; Matsuno, Hiroshi; Miyano, Satoru; Higuchi, Tomoyuki

2006-01-01

We propose an automatic construction method of the hybrid functional Petri net as a simulation model of biological pathways. The problems we consider are how we choose the values of parameters and how we set the network structure. Usually, we tune these unknown factors empirically so that the simulation results are consistent with biological knowledge. Obviously, this approach has the limitation in the size of network of interest. To extend the capability of the simulation model, we propose the use of data assimilation approach that was originally established in the field of geophysical simulation science. We provide genomic data assimilation framework that establishes a link between our simulation model and observed data like microarray gene expression data by using a nonlinear state space model. A key idea of our genomic data assimilation is that the unknown parameters in simulation model are converted as the parameter of the state space model and the estimates are obtained as the maximum a posteriori estimators. In the parameter estimation process, the simulation model is used to generate the system model in the state space model. Such a formulation enables us to handle both the model construction and the parameter tuning within a framework of the Bayesian statistical inferences. In particular, the Bayesian approach provides us a way of controlling overfitting during the parameter estimations that is essential for constructing a reliable biological pathway. We demonstrate the effectiveness of our approach using synthetic data. As a result, parameter estimation using genomic data assimilation works very well and the network structure is suitably selected.

A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy.

PubMed

Haworth, Annette; Mears, Christopher; Betts, John M; Reynolds, Hayley M; Tack, Guido; Leo, Kevin; Williams, Scott; Ebert, Martin A

2016-01-07

Treatment plans for ten patients, initially treated with a conventional approach to low dose-rate brachytherapy (LDR, 145 Gy to entire prostate), were compared with plans for the same patients created with an inverse-optimisation planning process utilising a biologically-based objective. The 'biological optimisation' considered a non-uniform distribution of tumour cell density through the prostate based on known and expected locations of the tumour. Using dose planning-objectives derived from our previous biological-model validation study, the volume of the urethra receiving 125% of the conventional prescription (145 Gy) was reduced from a median value of 64% to less than 8% whilst maintaining high values of TCP. On average, the number of planned seeds was reduced from 85 to less than 75. The robustness of plans to random seed displacements needs to be carefully considered when using contemporary seed placement techniques. We conclude that an inverse planning approach to LDR treatments, based on a biological objective, has the potential to maintain high rates of tumour control whilst minimising dose to healthy tissue. In future, the radiobiological model will be informed using multi-parametric MRI to provide a personalised medicine approach.

A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy

NASA Astrophysics Data System (ADS)

Haworth, Annette; Mears, Christopher; Betts, John M.; Reynolds, Hayley M.; Tack, Guido; Leo, Kevin; Williams, Scott; Ebert, Martin A.

2016-01-01

Treatment plans for ten patients, initially treated with a conventional approach to low dose-rate brachytherapy (LDR, 145 Gy to entire prostate), were compared with plans for the same patients created with an inverse-optimisation planning process utilising a biologically-based objective. The ‘biological optimisation’ considered a non-uniform distribution of tumour cell density through the prostate based on known and expected locations of the tumour. Using dose planning-objectives derived from our previous biological-model validation study, the volume of the urethra receiving 125% of the conventional prescription (145 Gy) was reduced from a median value of 64% to less than 8% whilst maintaining high values of TCP. On average, the number of planned seeds was reduced from 85 to less than 75. The robustness of plans to random seed displacements needs to be carefully considered when using contemporary seed placement techniques. We conclude that an inverse planning approach to LDR treatments, based on a biological objective, has the potential to maintain high rates of tumour control whilst minimising dose to healthy tissue. In future, the radiobiological model will be informed using multi-parametric MRI to provide a personalised medicine approach.

The biology of small, introduced populations, with special reference to biological control

PubMed Central

Fauvergue, Xavier; Vercken, Elodie; Malausa, Thibaut; Hufbauer, Ruth A

2012-01-01

Populations are introduced into novel environments in different contexts, one being the biological control of pests. Despite intense efforts, less than half introduced biological control agents establish. Among the possible approaches to improve biological control, one is to better understand the processes that underpin introductions and contribute to ecological and evolutionary success. In this perspective, we first review the demographic and genetic processes at play in small populations, be they stochastic or deterministic. We discuss the theoretical outcomes of these different processes with respect to individual fitness, population growth rate, and establishment probability. Predicted outcomes differ subtly in some cases, but enough so that the evaluating results of introductions have the potential to reveal which processes play important roles in introduced populations. Second, we attempt to link the theory we have discussed with empirical data from biological control introductions. A main result is that there are few available data, but we nonetheless report on an increasing number of well-designed, theory-driven, experimental approaches. Combining demography and genetics from both theoretical and empirical perspectives highlights novel and exciting avenues for research on the biology of small, introduced populations, and great potential for improving both our understanding and practice of biological control. PMID:22949919

Glycoengineering in CHO Cells: Advances in Systems Biology.

PubMed

Tejwani, Vijay; Andersen, Mikael R; Nam, Jong Hyun; Sharfstein, Susan T

2018-03-01

For several decades, glycoprotein biologics have been successfully produced from Chinese hamster ovary (CHO) cells. The therapeutic efficacy and potency of glycoprotein biologics are often dictated by their post-translational modifications, particularly glycosylation, which unlike protein synthesis, is a non-templated process. Consequently, both native and recombinant glycoprotein production generate heterogeneous mixtures containing variable amounts of different glycoforms. Stability, potency, plasma half-life, and immunogenicity of the glycoprotein biologic are directly influenced by the glycoforms. Recently, CHO cells have also been explored for production of therapeutic glycosaminoglycans (e.g., heparin), which presents similar challenges as producing glycoproteins biologics. Approaches to controlling heterogeneity in CHO cells and directing the biosynthetic process toward desired glycoforms are not well understood. A systems biology approach combining different technologies is needed for complete understanding of the molecular processes accounting for this variability and to open up new venues in cell line development. In this review, we describe several advances in genetic manipulation, modeling, and glycan and glycoprotein analysis that together will provide new strategies for glycoengineering of CHO cells with desired or enhanced glycosylation capabilities. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biphasic dose responses in biology, toxicology and medicine: accounting for their generalizability and quantitative features.

PubMed

Calabrese, Edward J

2013-11-01

The most common quantitative feature of the hormetic-biphasic dose response is its modest stimulatory response which at maximum is only 30-60% greater than control values, an observation that is consistently independent of biological model, level of organization (i.e., cell, organ or individual), endpoint measured, chemical/physical agent studied, or mechanism. This quantitative feature suggests an underlying "upstream" mechanism common across biological systems, therefore basic and general. Hormetic dose response relationships represent an estimate of the peak performance of integrative biological processes that are allometrically based. Hormetic responses reflect both direct stimulatory or overcompensation responses to damage induced by relatively low doses of chemical or physical agents. The integration of the hormetic dose response within an allometric framework provides, for the first time, an explanation for both the generality and the quantitative features of the hormetic dose response. Copyright © 2013 Elsevier Ltd. All rights reserved.

Plant synthetic biology for molecular engineering of signalling and development.

PubMed

Nemhauser, Jennifer L; Torii, Keiko U

2016-03-02

Molecular genetic studies of model plants in the past few decades have identified many key genes and pathways controlling development, metabolism and environmental responses. Recent technological and informatics advances have led to unprecedented volumes of data that may uncover underlying principles of plants as biological systems. The newly emerged discipline of synthetic biology and related molecular engineering approaches is built on this strong foundation. Today, plant regulatory pathways can be reconstituted in heterologous organisms to identify and manipulate parameters influencing signalling outputs. Moreover, regulatory circuits that include receptors, ligands, signal transduction components, epigenetic machinery and molecular motors can be engineered and introduced into plants to create novel traits in a predictive manner. Here, we provide a brief history of plant synthetic biology and significant recent examples of this approach, focusing on how knowledge generated by the reference plant Arabidopsis thaliana has contributed to the rapid rise of this new discipline, and discuss potential future directions.

Permeating disciplines: Overcoming barriers between molecular simulations and classical structure-function approaches in biological ion transport.

PubMed

Howard, Rebecca J; Carnevale, Vincenzo; Delemotte, Lucie; Hellmich, Ute A; Rothberg, Brad S

2018-04-01

Ion translocation across biological barriers is a fundamental requirement for life. In many cases, controlling this process-for example with neuroactive drugs-demands an understanding of rapid and reversible structural changes in membrane-embedded proteins, including ion channels and transporters. Classical approaches to electrophysiology and structural biology have provided valuable insights into several such proteins over macroscopic, often discontinuous scales of space and time. Integrating these observations into meaningful mechanistic models now relies increasingly on computational methods, particularly molecular dynamics simulations, while surfacing important challenges in data management and conceptual alignment. Here, we seek to provide contemporary context, concrete examples, and a look to the future for bridging disciplinary gaps in biological ion transport. This article is part of a Special Issue entitled: Beyond the Structure-Function Horizon of Membrane Proteins edited by Ute Hellmich, Rupak Doshi and Benjamin McIlwain. Copyright © 2017 Elsevier B.V. All rights reserved.

Improving the cost-effectiveness, trade and safety of biological control for agricultural insect pests using nuclear techniques

USDA-ARS?s Scientific Manuscript database

If appropriately applied, biological control offers one of the most promising, environmentally sound, and sustainable control tactics for arthropod pests and weeds for application as part of an integrated pest management (IPM) approach. Public support for biological control as one of the preferred m...

Understanding the side effects of classical biological control

Treesearch

Dean Pearson

2008-01-01

Classical biological control involves the use of imported natural enemies to suppress or control populations of the target pest species below an economically or ecologically relevant threshold. Biological control is a useful tool for mitigating the impacts of exotic invasive plants; however, its application is not without risk (see Carruthers and D’Antonio...

The (Mathematical) Modeling Process in Biosciences

PubMed Central

Torres, Nestor V.; Santos, Guido

2015-01-01

In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology. PMID:26734063

How causal analysis can reveal autonomy in models of biological systems

NASA Astrophysics Data System (ADS)

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'.

Multilevel systems biology modeling characterized the atheroprotective efficiencies of modified dairy fats in a hamster model.

PubMed

Martin, Jean-Charles; Berton, Amélie; Ginies, Christian; Bott, Romain; Scheercousse, Pierre; Saddi, Alessandra; Gripois, Daniel; Landrier, Jean-François; Dalemans, Daniel; Alessi, Marie-Christine; Delplanque, Bernadette

2015-09-01

We assessed the atheroprotective efficiency of modified dairy fats in hyperlipidemic hamsters. A systems biology approach was implemented to reveal and quantify the dietary fat-related components of the disease. Three modified dairy fats (40% energy) were prepared from regular butter by mixing with a plant oil mixture, by removing cholesterol alone, or by removing cholesterol in combination with reducing saturated fatty acids. A plant oil mixture and a regular butter were used as control diets. The atherosclerosis severity (aortic cholesteryl-ester level) was higher in the regular butter-fed hamsters than in the other four groups (P < 0.05). Eighty-seven of the 1,666 variables measured from multiplatform analysis were found to be strongly associated with the disease. When aggregated into 10 biological clusters combined into a multivariate predictive equation, these 87 variables explained 81% of the disease variability. The biological cluster "regulation of lipid transport and metabolism" appeared central to atherogenic development relative to diets. The "vitamin E metabolism" cluster was the main driver of atheroprotection with the best performing transformed dairy fat. Under conditions that promote atherosclerosis, the impact of dairy fats on atherogenesis could be greatly ameliorated by technological modifications. Our modeling approach allowed for identifying and quantifying the contribution of complex factors to atherogenic development in each dietary setup. Copyright © 2015 the American Physiological Society.

TRIENNIAL LACTATION SYMPOSIUM: Systems biology of regulatory mechanisms of nutrient metabolism in lactation.

PubMed

McNamara, J P

2015-12-01

A major role of the dairy cow is to convert low-quality plant materials into high-quality protein and other nutrients for humans. We must select and manage cows with the goal of having animals of the greatest efficiency matched to their environment. We have increased efficiency tremendously over the years, yet the variation in productive and reproductive efficiency among animals is still large. In part, this is because of a lack of full integration of genetic, nutritional, and reproductive biology into management decisions. However, integration across these disciplines is increasing as the biological research findings show specific control points at which genetics, nutrition, and reproduction interact. An ordered systems biology approach that focuses on why and how cells regulate energy and N use and on how and why organs interact through endocrine and neurocrine mechanisms will speed improvements in efficiency. More sophisticated dairy managers will demand better information to improve the efficiency of their animals. Using genetic improvement and animal management to improve milk productive and reproductive efficiency requires a deeper understanding of metabolic processes throughout the life cycle. Using existing metabolic models, we can design experiments specifically to integrate data from global transcriptional profiling into models that describe nutrient use in farm animals. A systems modeling approach can help focus our research to make faster and larger advances in efficiency and determine how this knowledge can be applied on the farms.

Modelling and analysis of gene regulatory network using feedback control theory

NASA Astrophysics Data System (ADS)

El-Samad, H.; Khammash, M.

2010-01-01

Molecular pathways are a part of a remarkable hierarchy of regulatory networks that operate at all levels of organisation. These regulatory networks are responsible for much of the biological complexity within the cell. The dynamic character of these pathways and the prevalence of feedback regulation strategies in their operation make them amenable to systematic mathematical analysis using the same tools that have been used with success in analysing and designing engineering control systems. In this article, we aim at establishing this strong connection through various examples where the behaviour exhibited by gene networks is explained in terms of their underlying control strategies. We complement our analysis by a survey of mathematical techniques commonly used to model gene regulatory networks and analyse their dynamic behaviour.

Role of physicochemical properties in the activation of peroxisome proliferator-activated receptor δ.

PubMed

Maltarollo, Vinícius G; Homem-de-Mello, Paula; Honorio, Káthia M

2011-10-01

Current researches on treatments for metabolic diseases involve a class of biological receptors called peroxisome proliferator-activated receptors (PPARs), which control the metabolism of carbohydrates and lipids. A subclass of these receptors, PPARδ, regulates several metabolic processes, and the substances that activate them are being studied as new drug candidates for the treatment of diabetes mellitus and metabolic syndrome. In this study, several PPARδ agonists with experimental biological activity were selected for a structural and chemical study. Electronic, stereochemical, lipophilic and topological descriptors were calculated for the selected compounds using various theoretical methods, such as density functional theory (DFT). Fisher's weight and principal components analysis (PCA) methods were employed to select the most relevant variables for this study. The partial least squares (PLS) method was used to construct the multivariate statistical model, and the best model obtained had 4 PCs, q ( 2 ) = 0.80 and r ( 2 ) = 0.90, indicating a good internal consistency. The prediction residues calculated for the compounds in the test set had low values, indicating the good predictive capability of our PLS model. The model obtained in this study is reliable and can be used to predict the biological activity of new untested compounds. Docking studies have also confirmed the importance of the molecular descriptors selected for this system.

Neural control of muscle

NASA Technical Reports Server (NTRS)

Max, S. R.; Markelonis, G. J.

1983-01-01

Cholinergic innervation regulates the physiological and biochemical properties of skeletal muscle. The mechanisms that appear to be involved in this regulation include soluble, neurally-derived polypeptides, transmitter-evoked muscle activity and the neurotransmitter, acetylcholine, itself. Despite extensive research, the interacting neural mechanisms that control such macromolecules as acetylcholinesterase, the acetylcholine receptor and glucose 6-phosphate dehydrogenase remain unclear. It may be that more simplified in vitro model systems coupled with recent dramatic advances in the molecular biology of neurally-regulated proteins will begin to allow researchers to unravel the mechanisms controlling the expression and maintenance of these macromolecules.

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

PubMed

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

The 'Biologically-Inspired Computing' Column

NASA Technical Reports Server (NTRS)

Hinchey, Mike

2006-01-01

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.

Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks.

PubMed

Flassig, R J; Sundmacher, K

2012-12-01

Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. flassig@mpi-magdeburg.mpg.de Supplementary data are are available at Bioinformatics online.

Moving towards ecosystem-based fisheries management: Options for parameterizing multi-species biological reference points

NASA Astrophysics Data System (ADS)

Moffitt, Elizabeth A.; Punt, André E.; Holsman, Kirstin; Aydin, Kerim Y.; Ianelli, James N.; Ortiz, Ivonne

2016-12-01

Multi-species models can improve our understanding of the effects of fishing so that it is possible to make informed and transparent decisions regarding fishery impacts. Broad application of multi-species assessment models to support ecosystem-based fisheries management (EBFM) requires the development and testing of multi-species biological reference points (MBRPs) for use in harvest-control rules. We outline and contrast several possible MBRPs that range from those that can be readily used in current frameworks to those belonging to a broader EBFM context. We demonstrate each of the possible MBRPs using a simple two species model, motivated by walleye pollock (Gadus chalcogrammus) and Pacific cod (Gadus macrocephalus) in the eastern Bering Sea, to illustrate differences among methods. The MBRPs we outline each differ in how they approach the multiple, potentially conflicting management objectives and trade-offs of EBFM. These options for MBRPs allow multi-species models to be readily adapted for EBFM across a diversity of management mandates and approaches.

Modelling cell wall growth using a fibre-reinforced hyperelastic-viscoplastic constitutive law

NASA Astrophysics Data System (ADS)

Huang, R.; Becker, A. A.; Jones, I. A.

2012-04-01

A fibre-reinforced hyperelastic-viscoplastic model using a finite strain Finite Element (FE) analysis is presented to study the expansive growth of cell walls. Based on the connections between biological concepts and plasticity theory, e.g. wall-loosening and plastic yield, wall-stiffening and plastic hardening, the modelling of cell wall growth is established within a framework of anisotropic viscoplasticity aiming to represent the corresponding biology-controlled behaviour of a cell wall. In order to model in vivo growth, special attention is paid to the differences between a living cell and an isolated wall. The proposed hyperelastic-viscoplastic theory provides a unique framework to clarify the interplay between cellulose microfibrils and cell wall matrix and how this interplay regulates sustainable growth in a particular direction while maintaining the mechanical strength of the cell walls by new material deposition. Moreover, the effect of temperature is taken into account. A numerical scheme is suggested and FE case studies are presented and compared with experimental data.

Neuroproteomics and Systems Biology Approach to Identify Temporal Biomarker Changes Post Experimental Traumatic Brain Injury in Rats.

PubMed

Kobeissy, Firas H; Guingab-Cagmat, Joy D; Zhang, Zhiqun; Moghieb, Ahmed; Glushakova, Olena Y; Mondello, Stefania; Boutté, Angela M; Anagli, John; Rubenstein, Richard; Bahmad, Hisham; Wagner, Amy K; Hayes, Ronald L; Wang, Kevin K W

2016-01-01

Traumatic brain injury (TBI) represents a critical health problem of which diagnosis, management, and treatment remain challenging. TBI is a contributing factor in approximately one-third of all injury-related deaths in the United States. The Centers for Disease Control and Prevention estimate that 1.7 million people suffer a TBI in the United States annually. Efforts continue to focus on elucidating the complex molecular mechanisms underlying TBI pathophysiology and defining sensitive and specific biomarkers that can aid in improving patient management and care. Recently, the area of neuroproteomics-systems biology is proving to be a prominent tool in biomarker discovery for central nervous system injury and other neurological diseases. In this work, we employed the controlled cortical impact (CCI) model of experimental TBI in rat model to assess the temporal-global proteome changes after acute (1 day) and for the first time, subacute (7 days), post-injury time frame using the established cation-anion exchange chromatography-1D SDS gel electrophoresis LC-MS/MS platform for protein separation combined with discrete systems biology analyses to identify temporal biomarker changes related to this rat TBI model. Rather than focusing on any one individual molecular entity, we used in silico systems biology approach to understand the global dynamics that govern proteins that are differentially altered post-injury. In addition, gene ontology analysis of the proteomic data was conducted in order to categorize the proteins by molecular function, biological process, and cellular localization. Results show alterations in several proteins related to inflammatory responses and oxidative stress in both acute (1 day) and subacute (7 days) periods post-TBI. Moreover, results suggest a differential upregulation of neuroprotective proteins at 7 days post-CCI involved in cellular functions such as neurite growth, regeneration, and axonal guidance. Our study is among the first to assess temporal neuroproteome changes in the CCI model. Data presented here unveil potential neural biomarkers and therapeutic targets that could be used for diagnosis, for treatment and, most importantly, for temporal prognostic assessment following brain injury. Of interest, this work relies on in silico bioinformatics approach to draw its conclusion; further work is conducted for functional studies to validate and confirm the omics data obtained.

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

PubMed

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 biology has advanced rapidly with increasing availability of new data and powerful simulation techniques, a quantitative orientation is still lacking in life sciences education to make efficient use of these new tools to implement the new toxicity testing paradigm. A revamped undergraduate curriculum in the biological sciences including compulsory courses in mathematics and analysis of dynamical systems is required to address this gap. In parallel, dissemination of computational systems biology techniques and other analytical tools among practicing toxicologists and risk assessment professionals will help accelerate implementation of the new toxicity testing vision.

Effects of aerobic and anaerobic biological processes on leaching of heavy metals from soil amended with sewage sludge compost.

PubMed

Fang, Wen; Wei, Yonghong; Liu, Jianguo; Kosson, David S; van der Sloot, Hans A; Zhang, Peng

2016-12-01

The risk from leaching of heavy metals is a major factor hindering land application of sewage sludge compost (SSC). Understanding the change in heavy metal leaching resulting from soil biological processes provides important information for assessing long-term behavior of heavy metals in the compost amended soil. In this paper, 180days aerobic incubation and 240days anaerobic incubation were conducted to investigate the effects of the aerobic and anaerobic biological processes on heavy metal leaching from soil amended with SSC, combined with chemical speciation modeling. Results showed that leaching concentrations of heavy metals at natural pH were similar before and after biological process. However, the major processes controlling heavy metals were influenced by the decrease of DOC with organic matter mineralization during biological processes. Mineralization of organic matter lowered the contribution of DOC-complexation to Ni and Zn leaching. Besides, the reducing condition produced by biological processes, particularly by the anaerobic biological process, resulted in the loss of sorption sites for As on Fe hydroxide, which increased the potential risk of As release at alkaline pH. Copyright © 2016 Elsevier Ltd. All rights reserved.

Concerted control of Escherichia coli cell division

PubMed Central

Osella, Matteo; Nugent, Eileen; Cosentino Lagomarsino, Marco

2014-01-01

The coordination of cell growth and division is a long-standing problem in biology. Focusing on Escherichia coli in steady growth, we quantify cell division control using a stochastic model, by inferring the division rate as a function of the observable parameters from large empirical datasets of dividing cells. We find that (i) cells have mechanisms to control their size, (ii) size control is effected by changes in the doubling time, rather than in the single-cell elongation rate, (iii) the division rate increases steeply with cell size for small cells, and saturates for larger cells. Importantly, (iv) the current size is not the only variable controlling cell division, but the time spent in the cell cycle appears to play a role, and (v) common tests of cell size control may fail when such concerted control is in place. Our analysis illustrates the mechanisms of cell division control in E. coli. The phenomenological framework presented is sufficiently general to be widely applicable and opens the way for rigorous tests of molecular cell-cycle models. PMID:24550446

Mathematical Simulation of the Process of Aerobic Treatment of Wastewater under Conditions of Diffusion and Mass Transfer Perturbations

NASA Astrophysics Data System (ADS)

Bomba, A. Ya.; Safonik, A. P.

2018-05-01

A mathematical model of the process of aerobic treatment of wastewater has been refined. It takes into account the interaction of bacteria, as well as of organic and biologically nonoxidizing substances under conditions of diffusion and mass transfer perturbations. An algorithm of the solution of the corresponding nonlinear perturbed problem of convection-diffusion-mass transfer type has been constructed, with a computer experiment carried out based on it. The influence of the concentration of oxygen and of activated sludge on the quality of treatment is shown. Within the framework of the model suggested, a possibility of automated control of the process of deposition of impurities in a biological filter depending on the initial parameters of the water medium is suggested.

Mathematical Simulation of the Process of Aerobic Treatment of Wastewater under Conditions of Diffusion and Mass Transfer Perturbations

NASA Astrophysics Data System (ADS)

Bomba, A. Ya.; Safonik, A. P.

2018-03-01

A mathematical model of the process of aerobic treatment of wastewater has been refined. It takes into account the interaction of bacteria, as well as of organic and biologically nonoxidizing substances under conditions of diffusion and mass transfer perturbations. An algorithm of the solution of the corresponding nonlinear perturbed problem of convection-diffusion-mass transfer type has been constructed, with a computer experiment carried out based on it. The influence of the concentration of oxygen and of activated sludge on the quality of treatment is shown. Within the framework of the model suggested, a possibility of automated control of the process of deposition of impurities in a biological filter depending on the initial parameters of the water medium is suggested.

Iron control on global productivity: an efficient inverse model of the ocean's coupled phosphate and iron cycles.

NASA Astrophysics Data System (ADS)

Pasquier, B.; Holzer, M.; Frants, M.

2016-02-01

We construct a data-constrained mechanistic inverse model of the ocean's coupled phosphorus and iron cycles. The nutrient cycling is embedded in a data-assimilated steady global circulation. Biological nutrient uptake is parameterized in terms of nutrient, light, and temperature limitations on growth for two classes of phytoplankton that are not transported explicitly. A matrix formulation of the discretized nutrient tracer equations allows for efficient numerical solutions, which facilitates the objective optimization of the key biogeochemical parameters. The optimization minimizes the misfit between the modelled and observed nutrient fields of the current climate. We systematically assess the nonlinear response of the biological pump to changes in the aeolian iron supply for a variety of scenarios. Specifically, Green-function techniques are employed to quantify in detail the pathways and timescales with which those perturbations are propagated throughout the world oceans, determining the global teleconnections that mediate the response of the global ocean ecosystem. We confirm previous findings from idealized studies that increased iron fertilization decreases biological production in the subtropical gyres and we quantify the counterintuitive and asymmetric response of global productivity to increases and decreases in the aeolian iron supply.

Tensegrity I. Cell structure and hierarchical systems biology

NASA Technical Reports Server (NTRS)

Ingber, Donald E.

2003-01-01

In 1993, a Commentary in this journal described how a simple mechanical model of cell structure based on tensegrity architecture can help to explain how cell shape, movement and cytoskeletal mechanics are controlled, as well as how cells sense and respond to mechanical forces (J. Cell Sci. 104, 613-627). The cellular tensegrity model can now be revisited and placed in context of new advances in our understanding of cell structure, biological networks and mechanoregulation that have been made over the past decade. Recent work provides strong evidence to support the use of tensegrity by cells, and mathematical formulations of the model predict many aspects of cell behavior. In addition, development of the tensegrity theory and its translation into mathematical terms are beginning to allow us to define the relationship between mechanics and biochemistry at the molecular level and to attack the larger problem of biological complexity. Part I of this two-part article covers the evidence for cellular tensegrity at the molecular level and describes how this building system may provide a structural basis for the hierarchical organization of living systems--from molecule to organism. Part II, which focuses on how these structural networks influence information processing networks, appears in the next issue.

SBMLeditor: effective creation of models in the Systems Biology Markup Language (SBML)

PubMed Central

Rodriguez, Nicolas; Donizelli, Marco; Le Novère, Nicolas

2007-01-01

Background The need to build a tool to facilitate the quick creation and editing of models encoded in the Systems Biology Markup language (SBML) has been growing with the number of users and the increased complexity of the language. SBMLeditor tries to answer this need by providing a very simple, low level editor of SBML files. Users can create and remove all the necessary bits and pieces of SBML in a controlled way, that maintains the validity of the final SBML file. Results SBMLeditor is written in JAVA using JCompneur, a library providing interfaces to easily display an XML document as a tree. This decreases dramatically the development time for a new XML editor. The possibility to include custom dialogs for different tags allows a lot of freedom for the editing and validation of the document. In addition to Xerces, SBMLeditor uses libSBML to check the validity and consistency of SBML files. A graphical equation editor allows an easy manipulation of MathML. SBMLeditor can be used as a module of the Systems Biology Workbench. Conclusion SBMLeditor contains many improvements compared to a generic XML editor, and allow users to create an SBML model quickly and without syntactic errors. PMID:17341299

SBMLeditor: effective creation of models in the Systems Biology Markup language (SBML).

PubMed

Rodriguez, Nicolas; Donizelli, Marco; Le Novère, Nicolas

2007-03-06

The need to build a tool to facilitate the quick creation and editing of models encoded in the Systems Biology Markup language (SBML) has been growing with the number of users and the increased complexity of the language. SBMLeditor tries to answer this need by providing a very simple, low level editor of SBML files. Users can create and remove all the necessary bits and pieces of SBML in a controlled way, that maintains the validity of the final SBML file. SBMLeditor is written in JAVA using JCompneur, a library providing interfaces to easily display an XML document as a tree. This decreases dramatically the development time for a new XML editor. The possibility to include custom dialogs for different tags allows a lot of freedom for the editing and validation of the document. In addition to Xerces, SBMLeditor uses libSBML to check the validity and consistency of SBML files. A graphical equation editor allows an easy manipulation of MathML. SBMLeditor can be used as a module of the Systems Biology Workbench. SBMLeditor contains many improvements compared to a generic XML editor, and allow users to create an SBML model quickly and without syntactic errors.

The Role of Laboratory-Based Studies of the Physical and Biological Properties of Sea Ice in Supporting the Observation and Modeling of Ice Covered Seas

NASA Astrophysics Data System (ADS)

Light, B.; Krembs, C.

2003-12-01

Laboratory-based studies of the physical and biological properties of sea ice are an essential link between high latitude field observations and existing numerical models. Such studies promote improved understanding of climatic variability and its impact on sea ice and the structure of ice-dependent marine ecosystems. Controlled laboratory experiments can help identify feedback mechanisms between physical and biological processes and their response to climate fluctuations. Climatically sensitive processes occurring between sea ice and the atmosphere and sea ice and the ocean determine surface radiative energy fluxes and the transfer of nutrients and mass across these boundaries. High temporally and spatially resolved analyses of sea ice under controlled environmental conditions lend insight to the physics that drive these transfer processes. Techniques such as optical probing, thin section photography, and microscopy can be used to conduct experiments on natural sea ice core samples and laboratory-grown ice. Such experiments yield insight on small scale processes from the microscopic to the meter scale and can be powerful interdisciplinary tools for education and model parameterization development. Examples of laboratory investigations by the authors include observation of the response of sea ice microstructure to changes in temperature, assessment of the relationships between ice structure and the partitioning of solar radiation by first-year sea ice covers, observation of pore evolution and interfacial structure, and quantification of the production and impact of microbial metabolic products on the mechanical, optical, and textural characteristics of sea ice.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Stochastic modelling of direct costs of pancreas disease (PD) in Norwegian farmed Atlantic salmon (Salmo salar L.).

PubMed

Aunsmo, Arnfinn; Valle, Paul Steinar; Sandberg, Marianne; Midtlyng, Paul Johan; Bruheim, Torkjel

2010-02-01

An economic model for estimating the direct costs of disease in industrial aquaculture was developed to include the following areas: biological losses, extraordinary costs, costs of treatment, costs of prevention and insurance pay-out. Direct costs of a pancreas disease (PD) outbreak in Norwegian farmed Atlantic salmon were estimated in the model, using probability distributions for the biological losses and expenditures associated with the disease. The biological effects of PD on mortality, growth, feed conversion and carcass quality and their correlations, together with costs of prevention were established using elicited data from an expert panel, and combined with basal losses in a control model. Extraordinary costs and costs associated with treatment were collected through a questionnaire sent to staff managing disease outbreaks. Norwegian national statistics for 2007 were used for prices and production costs in the model. Direct costs associated with a PD-outbreak in a site stocked with 500,000 smolts (vs. a similar site without the disease) were estimated to NOK (Norwegian kroner) 14.4 million (5% and 95% percentile: 10.5 and 17.8) (NOK=euro0.12 or $0.17 for 2007). Production was reduced to 70% (5% and 95% percentile: 57% and 81%) saleable biomass, and at an increased production cost of NOK 6.0 per kg (5% and 95% percentile: 3.5 and 8.7). Copyright 2009 Elsevier B.V. All rights reserved.

Development of a Biological Control Program for Eurasian Watermilfoil (Myriophyllum Spicatum)

DTIC Science & Technology

2006-12-22

spicatum). Pakistan Station Commonwealth Institute of Biological Control, Rawalpindi. 16 Gleason, H.A., Cronquist , A . 1991. Manual of Vascular Plants of...Development of a biological control program for Eurasian watermilfoil (Myriophyllum spicatum...control agents have not considered potential impact on non target indigenous species. A phased programme to address these gaps is put forward. List of

76 FR 3076 - Availability of an Environmental Assessment for a Biological Control Agent for Air Potato

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-19

...] Availability of an Environmental Assessment for a Biological Control Agent for Air Potato AGENCY: Animal and... environmental assessment (EA) relative to the control of air potato (Dioscorea bulbifera). The EA considers the... States for use as a biological control agent to reduce the severity of air potato infestations. We are...

A Review of the Integration of Classical Biological Control with other Management Techniques to Manage Invasive Weeds in Natural Areas and Rangelands

USDA-ARS?s Scientific Manuscript database

Integrating classical biological control with other management techniques such as herbicide, fire, mechanical control, grazing, or plant competition, can be the most effective way to manage invasive weeds in natural areas and rangelands. Biological control agents can be protected from potential nega...

Simulations of population dynamics of hemlock woolly adelgid and potential impact of biological control agents

Treesearch

Joseph S. Elkinton; Robert T. Trotter; Ann F. Paradis

2011-01-01

The hemlock woolly adelgid (Adelges tsugae) is a small invasive Hemipteran herbivore that threatens the continued presence and abundance of hemlock in eastern North America. Efforts to control the adelgid have focused on the introduction of classical biological control agents. These biological controls include six different species of predatory...

Neuroinspired control strategies with applications to flapping flight

NASA Astrophysics Data System (ADS)

Dorothy, Michael Ray

This dissertation is centered on a theoretical, simulation, and experimental study of control strategies which are inspired by biological systems. Biological systems, along with sufficiently complicated engineered systems, often have many interacting degrees of freedom and need to excite large-displacement oscillations in order to locomote. Combining these factors can make high-level control design difficult. This thesis revolves around three different levels of abstraction, providing tools for analysis and design. First, we consider central pattern generators (CPGs) to control flapping-flight dynamics. The key idea here is dimensional reduction - we want to convert complicated interactions of many degrees of freedom into a handful of parameters which have intuitive connections to the overall system behavior, leaving the control designer unconcerned with the details of particular motions. A rigorous mathematical and control theoretic framework to design complex three-dimensional wing motions is presented based on phase synchronization of nonlinear oscillators. In particular, we show that flapping-flying dynamics without a tail or traditional aerodynamic control surfaces can be effectively controlled by a reduced set of central pattern generator parameters that generate phase-synchronized or symmetry-breaking oscillatory motions of two main wings. Furthermore, by using a Hopf bifurcation, we show that tailless aircraft (inspired by bats) alternating between flapping and gliding can be effectively stabilized by smooth wing motions driven by the central pattern generator network. Results of numerical simulation with a full six-degree-of-freedom flight dynamic model validate the effectiveness of the proposed neurobiologically inspired control approach. Further, we present experimental micro aerial vehicle (MAV) research with low-frequency flapping and articulated wing gliding. The importance of phase difference control via an abstract mathematical model of central pattern generators is confirmed with a robotic bat on a 3-DOF pendulum platform. An aerodynamic model for the robotic bat based on the complex wing kinematics is presented. Closed loop experiments show that control dimension reduction is achievable - unstable longitudinal modes are stabilized and controlled using only two control parameters. A transition of flight modes, from flapping to gliding and vice-versa, is demonstrated within the CPG control scheme. The second major thrust is inspired by this idea that mode switching is useful. Many bats and birds adopt a mixed strategy of flapping and gliding to provide agility when necessary and to increase overall efficiency. This work explores dwell time constraints on switched systems with multiple, possibly disparate invariant limit sets. We show that, under suitable conditions, trajectories globally converge to a superset of the limit sets and then remain in a second, larger superset. We show the effectiveness of the dwell-time conditions by using examples of nonlinear switching limit cycles from our work on flapping flight. This level of abstraction has been found to be useful in many ways, but it also produces its own challenges. For example, we discuss death of oscillation which can occur for many limit-cycle controllers and the difficulty in incorporating fast, high-displacement reflex feedback. This leads us to our third major thrust - considering biologically realistic neuron circuits instead of a limit cycle abstraction. Biological neuron circuits are incredibly diverse in practice, giving us a convincing rationale that they can aid us in our quest for flexibility. Nevertheless, that flexibility provides its own challenges. It is not currently known how most biological neuron circuits work, and little work exists that connects the principles of a neuron circuit to the principles of control theory. We begin the process of trying to bridge this gap by considering the simplest of classical controllers, PD control. We propose a simple two-neuron, two-synapse circuit based on the concept that synapses provide attenuation and a delay. We present a simulation-based method of analysis, including a smoothing algorithm, a steady-state response curve, and a system identification procedure for capturing differentiation. There will never be One True Control Method that will solve all problems. Nature's solution to a diversity of systems and situations is equally diverse. This will inspire many strategies and require a multitude of analysis tools. This thesis is my contribution of a few.

Suppression of Phytophthora capsici on bell pepper with isolates of Trichoderma

USDA-ARS?s Scientific Manuscript database

Biologically based disease management strategies, including biological control, are being developed for Phytophthora capsici on bell pepper. Biological control agents that are effective in controlling this disease under a number of soil environmental conditions when applied alone or with cover crop...

7 CFR 301.1 - Purpose and scope.

Code of Federal Regulations, 2011 CFR

2011-01-01

... articles, means of conveyance, plants, plant products, biological control organisms, plant pests, or... biological control organism, plant pest, or noxious weed within the United States. The only exceptions to..., plant products, biological control organisms, plant pests, or noxious weeds that are in addition to the...

An Exercise in Biological Control.

ERIC Educational Resources Information Center

Lennox, John; Duke, Michael

1997-01-01

Discusses the history of the use of pesticides and biological control. Introduces the concept of biological control as illustrated in the use of the entomopathogenic bacterium Bacillus thuringiensis and highlights laboratory demonstrations of Koch's postulates. Includes an exercise that offers the student and teacher several integrated learning…

7 CFR 301.1 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-01-01

... articles, means of conveyance, plants, plant products, biological control organisms, plant pests, or... biological control organism, plant pest, or noxious weed within the United States. The only exceptions to..., plant products, biological control organisms, plant pests, or noxious weeds that are in addition to the...

Chemical-Reaction-Controlled Phase Separated Drops: Formation, Size Selection, and Coarsening

NASA Astrophysics Data System (ADS)

Wurtz, Jean David; Lee, Chiu Fan

2018-02-01

Phase separation under nonequilibrium conditions is exploited by biological cells to organize their cytoplasm but remains poorly understood as a physical phenomenon. Here, we study a ternary fluid model in which phase-separating molecules can be converted into soluble molecules, and vice versa, via chemical reactions. We elucidate using analytical and simulation methods how drop size, formation, and coarsening can be controlled by the chemical reaction rates, and categorize the qualitative behavior of the system into distinct regimes. Ostwald ripening arrest occurs above critical reaction rates, demonstrating that this transition belongs entirely to the nonequilibrium regime. Our model is a minimal representation of the cell cytoplasm.

Special Issue on Optochemical and Optogenetic Control of Cellular Processes.

PubMed

Deiters, Alexander

2018-06-06

Diverse optochemical and optobiological approaches are being developed and applied to the light-regulation of cellular processes with exquisite spatial and temporal resolution in cells and multicellular model organisms. In this special issue, experts report some of the latest progress in the expanding field of the optical control of biological systems and present an overview of the state of the art of select approaches. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Young-age gender differences in mathematics mediated by independent control or uncontrollability.

PubMed

Zirk-Sadowski, Jan; Lamptey, Charlotte; Devine, Amy; Haggard, Mark; Szűcs, Dénes

2014-05-01

We studied whether the origins of math anxiety can be related to a biologically supported framework of stress induction: (un)controllability perception, here indicated by self-reported independent efforts in mathematics. Math anxiety was tested in 182 children (8- to 11-year-olds). Latent factor modeling was used to test hypotheses on plausible causal processes and mediations within competing models in quasi-experimental contrasts. Uncontrollability perception in mathematics, or (in)dependence of efforts, best fit the data as an antecedent of math anxiety. In addition, the relationship of math anxiety with gender was fully mediated by adaptive perception of control (i.e. controllability). That is, young boys differ from girls in terms of their experience of control in mathematics learning. These differences influence math anxiety. Our findings are consistent with recent suggestions in clinical literature according to which uncontrollability makes women more susceptible to fear and anxiety disorders. © 2014 John Wiley & Sons Ltd.

Uncertainty, learning, and the optimal management of wildlife

USGS Publications Warehouse

Williams, B.K.

2001-01-01

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.

Insecticide Resistance and Malaria Vector Control: The Importance of Fitness Cost Mechanisms in Determining Economically Optimal Control Trajectories

PubMed Central

Brown, Zachary S.; Dickinson, Katherine L.; Kramer, Randall A.

2014-01-01

The evolutionary dynamics of insecticide resistance in harmful arthropods has economic implications, not only for the control of agricultural pests (as has been well studied), but also for the control of disease vectors, such as malaria-transmitting Anopheles mosquitoes. Previous economic work on insecticide resistance illustrates the policy relevance of knowing whether insecticide resistance mutations involve fitness costs. Using a theoretical model, this article investigates economically optimal strategies for controlling malaria-transmitting mosquitoes when there is the potential for mosquitoes to evolve resistance to insecticides. Consistent with previous literature, we find that fitness costs are a key element in the computation of economically optimal resistance management strategies. Additionally, our models indicate that different biological mechanisms underlying these fitness costs (e.g., increased adult mortality and/or decreased fecundity) can significantly alter economically optimal resistance management strategies. PMID:23448053

Utilizing Biological Models to Determine the Recruitment of the IRA by Modeling the Voting Behavior of Sinn Fein

DTIC Science & Technology

2006-03-01

models, the thesis applies a biological model, the Lotka - Volterra predator- prey model, to a highly suggestive case study, that of the Irish Republican...Model, Irish Republican Army, Sinn Féin, Lotka - Volterra Predator Prey Model, Recruitment, British Army 16. PRICE CODE 17. SECURITY CLASSIFICATION OF...weaknesses of sociological and biological models, the thesis applies a biological model, the Lotka - Volterra predator-prey model, to a highly suggestive

Regulatory RNA in Mycobacterium tuberculosis, back to basics.

PubMed

Schwenk, Stefan; Arnvig, Kristine B

2018-06-01

Since the turn of the millenium, RNA-based control of gene expression has added an extra dimension to the central dogma of molecular biology. Still, the roles of Mycobacterium tuberculosis regulatory RNAs and the proteins that facilitate their functions remain elusive, although there can be no doubt that RNA biology plays a central role in the baterium's adaptation to its many host environments. In this review, we have presented examples from model organisms and from M. tuberculosis to showcase the abundance and versatility of regulatory RNA, in order to emphasise the importance of these 'fine-tuners' of gene expression.

BIOCOMPUTATION: some history and prospects.

PubMed

Cull, Paul

2013-06-01

At first glance, biology and computer science are diametrically opposed sciences. Biology deals with carbon based life forms shaped by evolution and natural selection. Computer Science deals with electronic machines designed by engineers and guided by mathematical algorithms. In this brief paper, we review biologically inspired computing. We discuss several models of computation which have arisen from various biological studies. We show what these have in common, and conjecture how biology can still suggest answers and models for the next generation of computing problems. We discuss computation and argue that these biologically inspired models do not extend the theoretical limits on computation. We suggest that, in practice, biological models may give more succinct representations of various problems, and we mention a few cases in which biological models have proved useful. We also discuss the reciprocal impact of computer science on biology and cite a few significant contributions to biological science. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Conserving and enhancing biological control of nematodes.

PubMed

Timper, Patricia

2014-06-01

Conservation biological control is the modification of the environment or existing practices to protect and enhance antagonistic organisms to reduce damage from pests. This approach to biological control has received insufficient attention compared with inundative applications of microbial antagonists to control nematodes. This review provides examples of how production practices can enhance or diminish biological control of plant-parasitic nematodes and other soilborne pests. Antagonists of nematodes can be enhanced by providing supplementary food sources such as occurs when organic amendments are applied to soil. However, some organic amendments (e.g., manures and plants containing allelopathic compounds) can also be detrimental to nematode antagonists. Plant species and genotype can strongly influence the outcome of biological control. For instance, the susceptibility of the plant to the nematode can determine the effectiveness of control; good hosts will require greater levels of suppression than poor hosts. Plant genotype can also influence the degree of rhizosphere colonization and antibiotic production by antagonists, as well the expression of induced resistance by plants. Production practices such as crop rotation, fallow periods, tillage, and pesticide applications can directly disrupt populations of antagonistic organisms. These practices can also indirectly affect antagonists by reducing their primary nematode host. One of the challenges of conservation biological control is that practices intended to protect or enhance suppression of nematodes may not be effective in all field sites because they are dependent on indigenous antagonists. Ultimately, indicators will need to be identified, such as the presence of particular antagonists, which can guide decisions on where it is practical to use conservation biological control. Antagonists can also be applied to field sites in conjunction with conservation practices to improve the consistency, efficacy, and duration of biological control. In future research, greater use should be made of bioassays that measure nematode suppression because changes in abundance of particular antagonists may not affect biological control of plant parasites.

Conserving and Enhancing Biological Control of Nematodes

PubMed Central

Timper, Patricia

2014-01-01

Conservation biological control is the modification of the environment or existing practices to protect and enhance antagonistic organisms to reduce damage from pests. This approach to biological control has received insufficient attention compared with inundative applications of microbial antagonists to control nematodes. This review provides examples of how production practices can enhance or diminish biological control of plant-parasitic nematodes and other soilborne pests. Antagonists of nematodes can be enhanced by providing supplementary food sources such as occurs when organic amendments are applied to soil. However, some organic amendments (e.g., manures and plants containing allelopathic compounds) can also be detrimental to nematode antagonists. Plant species and genotype can strongly influence the outcome of biological control. For instance, the susceptibility of the plant to the nematode can determine the effectiveness of control; good hosts will require greater levels of suppression than poor hosts. Plant genotype can also influence the degree of rhizosphere colonization and antibiotic production by antagonists, as well the expression of induced resistance by plants. Production practices such as crop rotation, fallow periods, tillage, and pesticide applications can directly disrupt populations of antagonistic organisms. These practices can also indirectly affect antagonists by reducing their primary nematode host. One of the challenges of conservation biological control is that practices intended to protect or enhance suppression of nematodes may not be effective in all field sites because they are dependent on indigenous antagonists. Ultimately, indicators will need to be identified, such as the presence of particular antagonists, which can guide decisions on where it is practical to use conservation biological control. Antagonists can also be applied to field sites in conjunction with conservation practices to improve the consistency, efficacy, and duration of biological control. In future research, greater use should be made of bioassays that measure nematode suppression because changes in abundance of particular antagonists may not affect biological control of plant parasites. PMID:24987159

USE OF MOLECULAR BIOLOGICAL TECHNIQUES TO EVALUATE EFFECT OF ENDOGENOUS HORMONES AND A XENOBIOTIC PESTICIDE ON GROWTH OF SHEEPSHEAD MINNOW

EPA Science Inventory

We have developed a teleost model to screen physiological effects of endocrine disrupting chemicals (EDCs) on somatic growth. Growth is largely controlled by the endocrine system via the growth-hormone releasing hormone (GRF) - growth hormone (GH) - insulin-like growth factor (IG...