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

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

Lewis, Daniel D.; Department of Biomedical Engineering, University of California Davis, Davis, CA; Villarreal, Fernando D.

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

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

PubMed Central

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

2014-01-01

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems. PMID:25538941

Synthetic biology outside the cell: linking computational tools to cell-free systems.

PubMed

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

2014-01-01

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

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

ERIC Educational Resources Information Center

AHI, Berat

2017-01-01

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

Bipartite graphs in systems biology and medicine: a survey of methods and applications.

PubMed

Pavlopoulos, Georgios A; Kontou, Panagiota I; Pavlopoulou, Athanasia; Bouyioukos, Costas; Markou, Evripides; Bagos, Pantelis G

2018-04-01

The latest advances in high-throughput techniques during the past decade allowed the systems biology field to expand significantly. Today, the focus of biologists has shifted from the study of individual biological components to the study of complex biological systems and their dynamics at a larger scale. Through the discovery of novel bioentity relationships, researchers reveal new information about biological functions and processes. Graphs are widely used to represent bioentities such as proteins, genes, small molecules, ligands, and others such as nodes and their connections as edges within a network. In this review, special focus is given to the usability of bipartite graphs and their impact on the field of network biology and medicine. Furthermore, their topological properties and how these can be applied to certain biological case studies are discussed. Finally, available methodologies and software are presented, and useful insights on how bipartite graphs can shape the path toward the solution of challenging biological problems are provided.

Algorithms in nature: the convergence of systems biology and computational thinking

PubMed Central

Navlakha, Saket; Bar-Joseph, Ziv

2011-01-01

Computer science and biology have enjoyed a long and fruitful relationship for decades. Biologists rely on computational methods to analyze and integrate large data sets, while several computational methods were inspired by the high-level design principles of biological systems. Recently, these two directions have been converging. In this review, we argue that thinking computationally about biological processes may lead to more accurate models, which in turn can be used to improve the design of algorithms. We discuss the similar mechanisms and requirements shared by computational and biological processes and then present several recent studies that apply this joint analysis strategy to problems related to coordination, network analysis, and tracking and vision. We also discuss additional biological processes that can be studied in a similar manner and link them to potential computational problems. With the rapid accumulation of data detailing the inner workings of biological systems, we expect this direction of coupling biological and computational studies to greatly expand in the future. PMID:22068329

‘Integrative Physiology 2.0’: integration of systems biology into physiology and its application to cardiovascular homeostasis

PubMed Central

Kuster, Diederik W D; Merkus, Daphne; van der Velden, Jolanda; Verhoeven, Adrie J M; Duncker, Dirk J

2011-01-01

Since the completion of the Human Genome Project and the advent of the large scaled unbiased ‘-omics’ techniques, the field of systems biology has emerged. Systems biology aims to move away from the traditional reductionist molecular approach, which focused on understanding the role of single genes or proteins, towards a more holistic approach by studying networks and interactions between individual components of networks. From a conceptual standpoint, systems biology elicits a ‘back to the future’ experience for any integrative physiologist. However, many of the new techniques and modalities employed by systems biologists yield tremendous potential for integrative physiologists to expand their tool arsenal to (quantitatively) study complex biological processes, such as cardiac remodelling and heart failure, in a truly holistic fashion. We therefore advocate that systems biology should not become/stay a separate discipline with ‘-omics’ as its playing field, but should be integrated into physiology to create ‘Integrative Physiology 2.0’. PMID:21224228

Systems biology of cellular membranes: a convergence with biophysics.

PubMed

Chabanon, Morgan; Stachowiak, Jeanne C; Rangamani, Padmini

2017-09-01

Systems biology and systems medicine have played an important role in the last two decades in shaping our understanding of biological processes. While systems biology is synonymous with network maps and '-omics' approaches, it is not often associated with mechanical processes. Here, we make the case for considering the mechanical and geometrical aspects of biological membranes as a key step in pushing the frontiers of systems biology of cellular membranes forward. We begin by introducing the basic components of cellular membranes, and highlight their dynamical aspects. We then survey the functions of the plasma membrane and the endomembrane system in signaling, and discuss the role and origin of membrane curvature in these diverse cellular processes. We further give an overview of the experimental and modeling approaches to study membrane phenomena. We close with a perspective on the converging futures of systems biology and membrane biophysics, invoking the need to include physical variables such as location and geometry in the study of cellular membranes. WIREs Syst Biol Med 2017, 9:e1386. doi: 10.1002/wsbm.1386 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

How do biological systems discriminate among physically similar ions?

PubMed

Diamond, J M

1975-10-01

This paper reviews the history of understanding how biological systems can discriminate so strikingly among physically similar ions, especially alkali cations. Appreciation of qualitative regularities ("permitted sequences") and quantitative regularities ("selectivity isotherms") in ion selectivity grew first from studies of ion exchangers and glass electrodes, then of biological systems such as enzymes and cell membranes, and most recently of lipid bilayers doped with model pores and carriers. Discrimination of ions depends on both electrostatic and steric forces. "Black-box" studies on intact biological membranes have in some cases yielded molecular clues to the structure of the actual biological pores and carriers. Major current problems involve the extraction of these molecules; how to do it, what to do when it is achieved, and how (and if) it is relevant to the central problems of membrane function. Further advances are expected soon from studies of rate barriers within membranes, of voltage-dependent ("excitable") conducting channels, and of increasingly complex model systems and biological membranes.

CHEMICAL EFFECTS IN BIOLOGICAL SYSTEMS – DATA DICTIONARY (CEBS-DD): A COMPENDIUM OF TERMS FOR THE CAPTURE AND INTEGRATION OF BIOLOGICAL STUDY DESIGN DESCRIPTION, CONVENTIONAL PHENOTYPES AND ‘OMICS’ DATA

EPA Science Inventory

A critical component in the design of the Chemical Effects in Biological Systems (CEBS) Knowledgebase is a strategy to capture toxicogenomics study protocols and the toxicity endpoint data (clinical pathology and histopathology). A Study is generally an experiment carried out du...

Systems biology of human atherosclerosis.

PubMed

Shalhoub, Joseph; Sikkel, Markus B; Davies, Kerry J; Vorkas, Panagiotis A; Want, Elizabeth J; Davies, Alun H

2014-01-01

Systems biology describes a holistic and integrative approach to understand physiology and pathology. The "omic" disciplines include genomics, transcriptomics, proteomics, and metabolic profiling (metabonomics and metabolomics). By adopting a stance, which is opposing (yet complimentary) to conventional research techniques, systems biology offers an overview by assessing the "net" biological effect imposed by a disease or nondisease state. There are a number of different organizational levels to be understood, from DNA to protein, metabolites, cells, organs and organisms, even beyond this to an organism's context. Systems biology relies on the existence of "nodes" and "edges." Nodes are the constituent part of the system being studied (eg, proteins in the proteome), while the edges are the way these constituents interact. In future, it will be increasingly important to collaborate, collating data from multiple studies to improve data sets, making them freely available and undertaking integrative analyses.

Studying Plant-Rhizobium Mutualism in the Biology Classroom: Connecting the Big Ideas in Biology through Inquiry

ERIC Educational Resources Information Center

Suwa, Tomomi; Williamson, Brad

2014-01-01

We present a guided-inquiry biology lesson, using the plant-rhizobium symbiosis as a model system. This system provides a rich environment for developing connections between the big ideas in biology as outlined in the College Board's new AP Biology Curriculum. Students gain experience with the practice of scientific investigation, from…

Network science of biological systems at different scales: A review

NASA Astrophysics Data System (ADS)

Gosak, Marko; Markovič, Rene; Dolenšek, Jurij; Slak Rupnik, Marjan; Marhl, Marko; Stožer, Andraž; Perc, Matjaž

2018-03-01

Network science is today established as a backbone for description of structure and function of various physical, chemical, biological, technological, and social systems. Here we review recent advances in the study of complex biological systems that were inspired and enabled by methods of network science. First, we present

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.

Characterising the Development of the Understanding of Human Body Systems in High-School Biology Students--A Longitudinal Study

ERIC Educational Resources Information Center

Snapir, Zohar; Eberbach, Catherine; Ben-Zvi-Assaraf, Orit; Hmelo-Silver, Cindy; Tripto, Jaklin

2017-01-01

Science education today has become increasingly focused on research into complex natural, social and technological systems. In this study, we examined the development of high-school biology students' systems understanding of the human body, in a three-year longitudinal study. The development of the students' system understanding was evaluated…

Systems Biology Approach in Hypertension Research.

PubMed

Delles, Christian; Husi, Holger

2017-01-01

Systems biology is an approach to study all genes, gene transcripts, proteins, metabolites, and their interactions in specific cells, tissues, organs, or the whole organism. It is based on data derived from high-throughput analytical technologies and bioinformatics tools to analyze these data, and aims to understand the whole system rather than individual aspects of it. Systems biology can be applied to virtually all conditions and diseases and therefore also to hypertension and its underlying vascular disorders. Unlike other methods in this book there is no clear-cut protocol to explain a systems biology approach. We will instead outline some of the most important and common steps in the generation and analysis of systems biology data.

Use of EPR to Solve Biochemical Problems

PubMed Central

Sahu, Indra D.; McCarrick, Robert M.; Lorigan, Gary A.

2013-01-01

EPR spectroscopy is a very powerful biophysical tool that can provide valuable structural and dynamic information on a wide variety of biological systems. The intent of this review is to provide a general overview for biochemists and biological researchers on the most commonly used EPR methods and how these techniques can be used to answer important biological questions. The topics discussed could easily fill one or more textbooks; thus, we present a brief background on several important biological EPR techniques and an overview of several interesting studies that have successfully used EPR to solve pertinent biological problems. The review consists of the following sections: an introduction to EPR techniques, spin labeling methods, and studies of naturally occurring organic radicals and EPR active transition metal systems which are presented as a series of case studies in which EPR spectroscopy has been used to greatly further our understanding of several important biological systems. PMID:23961941

Synthetic biology: programming cells for biomedical applications.

PubMed

Hörner, Maximilian; Reischmann, Nadine; Weber, Wilfried

2012-01-01

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

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

Approaches to Quality Risk Management When Using Single-Use Systems in the Manufacture of Biologics.

PubMed

Ishii-Watabe, Akiko; Hirose, Akihiko; Katori, Noriko; Hashii, Norikata; Arai, Susumu; Awatsu, Hirotoshi; Eiza, Akira; Hara, Yoshiaki; Hattori, Hideshi; Inoue, Tomomi; Isono, Tetsuya; Iwakura, Masahiro; Kajihara, Daisuke; Kasahara, Nobuo; Matsuda, Hiroyuki; Murakami, Sei; Nakagawa, Taishiro; Okumura, Takehiro; Omasa, Takeshi; Takuma, Shinya; Terashima, Iyo; Tsukahara, Masayoshi; Tsutsui, Maiko; Yano, Takahiro; Kawasaki, Nana

2015-10-01

Biologics manufacturing technology has made great progress in the last decade. One of the most promising new technologies is the single-use system, which has improved the efficiency of biologics manufacturing processes. To ensure safety of biologics when employing such single-use systems in the manufacturing process, various issues need to be considered including possible extractables/leachables and particles arising from the components used in single-use systems. Japanese pharmaceutical manufacturers, together with single-use suppliers, members of the academia and regulatory authorities have discussed the risks of using single-use systems and established control strategies for the quality assurance of biologics. In this study, we describe approaches for quality risk management when employing single-use systems in the manufacturing of biologics. We consider the potential impact of impurities related to single-use components on drug safety and the potential impact of the single-use system on other critical quality attributes as well as the stable supply of biologics. We also suggest a risk-mitigating strategy combining multiple control methods which includes the selection of appropriate single-use components, their inspections upon receipt and before releasing for use and qualification of single-use systems. Communication between suppliers of single-use systems and the users, as well as change controls in the facilities both of suppliers and users, are also important in risk-mitigating strategies. Implementing these control strategies can mitigate the risks attributed to the use of single-use systems. This study will be useful in promoting the development of biologics as well as in ensuring their safety, quality and stable supply.

Engineering scalable biological systems

PubMed Central

2010-01-01

Synthetic biology is focused on engineering biological organisms to study natural systems and to provide new solutions for pressing medical, industrial and environmental problems. At the core of engineered organisms are synthetic biological circuits that execute the tasks of sensing inputs, processing logic and performing output functions. In the last decade, significant progress has been made in developing basic designs for a wide range of biological circuits in bacteria, yeast and mammalian systems. However, significant challenges in the construction, probing, modulation and debugging of synthetic biological systems must be addressed in order to achieve scalable higher-complexity biological circuits. Furthermore, concomitant efforts to evaluate the safety and biocontainment of engineered organisms and address public and regulatory concerns will be necessary to ensure that technological advances are translated into real-world solutions. PMID:21468204

Genomes, Proteomes and the Central Dogma

PubMed Central

Franklin, Sarah; Vondriska, Thomas M.

2011-01-01

Systems biology, with its associated technologies of proteomics, genomics and metabolomics, is driving the evolution of our understanding of cardiovascular physiology. Rather than studying individual molecules or even single reactions, a systems approach allows integration of orthogonal datasets from distinct tiers of biological data, including gene, RNA, protein, metabolite and other component networks. Together these networks give rise to emergent properties of cellular function and it is their reprogramming that causes disease. We present five observations regarding how systems biology is guiding a revisiting of the central dogma: (i) de-emphasizing the unidirectional flow of information from genes to proteins; (ii) revealing the role of modules of molecules as opposed to individual proteins acting in isolation; (iii) enabling discovery of novel emergent properties; (iv) demonstrating the importance of networks in biology; and (v) adding new dimensionality to the study of biological systems. PMID:22010165

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

Review of the fundamental theories behind small angle X-ray scattering, molecular dynamics simulations, and relevant integrated application.

PubMed

Boldon, Lauren; Laliberte, Fallon; Liu, Li

2015-01-01

In this paper, the fundamental concepts and equations necessary for performing small angle X-ray scattering (SAXS) experiments, molecular dynamics (MD) simulations, and MD-SAXS analyses were reviewed. Furthermore, several key biological and non-biological applications for SAXS, MD, and MD-SAXS are presented in this review; however, this article does not cover all possible applications. SAXS is an experimental technique used for the analysis of a wide variety of biological and non-biological structures. SAXS utilizes spherical averaging to produce one- or two-dimensional intensity profiles, from which structural data may be extracted. MD simulation is a computer simulation technique that is used to model complex biological and non-biological systems at the atomic level. MD simulations apply classical Newtonian mechanics' equations of motion to perform force calculations and to predict the theoretical physical properties of the system. This review presents several applications that highlight the ability of both SAXS and MD to study protein folding and function in addition to non-biological applications, such as the study of mechanical, electrical, and structural properties of non-biological nanoparticles. Lastly, the potential benefits of combining SAXS and MD simulations for the study of both biological and non-biological systems are demonstrated through the presentation of several examples that combine the two techniques.

Sender–receiver systems and applying information theory for quantitative synthetic biology

PubMed Central

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

2015-01-01

Sender–receiver (S–R) systems abound in biology, with communication systems sending information in various forms. Information theory provides a quantitative basis for analysing these processes and is being applied to study natural genetic, enzymatic and neural networks. Recent advances in synthetic biology are providing us with a wealth of artificial S–R systems, giving us quantitative control over networks with a finite number of well-characterised components. Combining the two approaches can help to predict how to maximise signalling robustness, and will allow us to make increasingly complex biological computers. Ultimately, pushing the boundaries of synthetic biology will require moving beyond engineering the flow of information and towards building more sophisticated circuits that interpret biological meaning. PMID:25282688

Biology of Elderly Suicide.

ERIC Educational Resources Information Center

Rifai, A. Hind; And Others

1992-01-01

Describes age-related changes in central nervous system pertinent to biology of suicide. Reviews postmortem biological studies of brains of suicides and suicide attempters. As suicide attempts in elderly are characterized by violence, discusses biological studies of impulsive violence. Describes data on effect of degenerative diseases on serotonin…

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.

Controllability and observability of Boolean networks arising from biology

NASA Astrophysics Data System (ADS)

Li, Rui; Yang, Meng; Chu, Tianguang

2015-02-01

Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.

Comprehensive Evaluation of Biological Growth Control by Chlorine-Based Biocides in Power Plant Cooling Systems Using Tertiary Effluent

PubMed Central

Chien, Shih-Hsiang; Dzombak, David A.; Vidic, Radisav D.

2013-01-01

Abstract Recent studies have shown that treated municipal wastewater can be a reliable cooling water alternative to fresh water. However, elevated nutrient concentration and microbial population in wastewater lead to aggressive biological proliferation in the cooling system. Three chlorine-based biocides were evaluated for the control of biological growth in cooling systems using tertiary treated wastewater as makeup, based on their biocidal efficiency and cost-effectiveness. Optimal chemical regimens for achieving successful biological growth control were elucidated based on batch-, bench-, and pilot-scale experiments. Biocide usage and biological activity in planktonic and sessile phases were carefully monitored to understand biological growth potential and biocidal efficiency of the three disinfectants in this particular environment. Water parameters, such as temperature, cycles of concentration, and ammonia concentration in recirculating water, critically affected the biocide performance in recirculating cooling systems. Bench-scale recirculating tests were shown to adequately predict the biocide residual required for a pilot-scale cooling system. Optimal residuals needed for proper biological growth control were 1, 2–3, and 0.5–1 mg/L as Cl2 for NaOCl, preformed NH2Cl, and ClO2, respectively. Pilot-scale tests also revealed that Legionella pneumophila was absent from these cooling systems when using the disinfectants evaluated in this study. Cost analysis showed that NaOCl is the most cost-effective for controlling biological growth in power plant recirculating cooling systems using tertiary-treated wastewater as makeup. PMID:23781129

Comprehensive Evaluation of Biological Growth Control by Chlorine-Based Biocides in Power Plant Cooling Systems Using Tertiary Effluent.

PubMed

Chien, Shih-Hsiang; Dzombak, David A; Vidic, Radisav D

2013-06-01

Recent studies have shown that treated municipal wastewater can be a reliable cooling water alternative to fresh water. However, elevated nutrient concentration and microbial population in wastewater lead to aggressive biological proliferation in the cooling system. Three chlorine-based biocides were evaluated for the control of biological growth in cooling systems using tertiary treated wastewater as makeup, based on their biocidal efficiency and cost-effectiveness. Optimal chemical regimens for achieving successful biological growth control were elucidated based on batch-, bench-, and pilot-scale experiments. Biocide usage and biological activity in planktonic and sessile phases were carefully monitored to understand biological growth potential and biocidal efficiency of the three disinfectants in this particular environment. Water parameters, such as temperature, cycles of concentration, and ammonia concentration in recirculating water, critically affected the biocide performance in recirculating cooling systems. Bench-scale recirculating tests were shown to adequately predict the biocide residual required for a pilot-scale cooling system. Optimal residuals needed for proper biological growth control were 1, 2-3, and 0.5-1 mg/L as Cl 2 for NaOCl, preformed NH 2 Cl, and ClO 2 , respectively. Pilot-scale tests also revealed that Legionella pneumophila was absent from these cooling systems when using the disinfectants evaluated in this study. Cost analysis showed that NaOCl is the most cost-effective for controlling biological growth in power plant recirculating cooling systems using tertiary-treated wastewater as makeup.

Molecular dynamics simulations and applications in computational toxicology and nanotoxicology.

PubMed

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

2018-02-01

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

Systems Approaches to Cancer Biology.

PubMed

Archer, Tenley C; Fertig, Elana J; Gosline, Sara J C; Hafner, Marc; Hughes, Shannon K; Joughin, Brian A; Meyer, Aaron S; Piccolo, Stephen R; Shajahan-Haq, Ayesha N

2016-12-01

Cancer systems biology aims to understand cancer as an integrated system of genes, proteins, networks, and interactions rather than an entity of isolated molecular and cellular components. The inaugural Systems Approaches to Cancer Biology Conference, cosponsored by the Association of Early Career Cancer Systems Biologists and the National Cancer Institute of the NIH, focused on the interdisciplinary field of cancer systems biology and the challenging cancer questions that are best addressed through the combination of experimental and computational analyses. Attendees found that elucidating the many molecular features of cancer inevitably reveals new forms of complexity and concluded that ensuring the reproducibility and impact of cancer systems biology studies will require widespread method and data sharing and, ultimately, the translation of important findings to the clinic. Cancer Res; 76(23); 6774-7. ©2016 AACR. ©2016 American Association for Cancer Research.

How Is the Body's Systemic Nature Manifested amongst High School Biology Students?

ERIC Educational Resources Information Center

Tripto, Jaklin; Assaraf, Orit Ben; Snapir, Zohar; Amit, Miriam

2017-01-01

This study follows two groups of students (67 in all) through the 3 years of their high school biology education and examines the development of their systems thinking--specifically their models of the human body as a system. Both groups were composed of biology majors, but the students in one group also participated in a PBLbased extension…

Applications of systems approaches in the study of rheumatic diseases.

PubMed

Kim, Ki-Jo; Lee, Saseong; Kim, Wan-Uk

2015-03-01

The complex interaction of molecules within a biological system constitutes a functional module. These modules are then acted upon by both internal and external factors, such as genetic and environmental stresses, which under certain conditions can manifest as complex disease phenotypes. Recent advances in high-throughput biological analyses, in combination with improved computational methods for data enrichment, functional annotation, and network visualization, have enabled a much deeper understanding of the mechanisms underlying important biological processes by identifying functional modules that are temporally and spatially perturbed in the context of disease development. Systems biology approaches such as these have produced compelling observations that would be impossible to replicate using classical methodologies, with greater insights expected as both the technology and methods improve in the coming years. Here, we examine the use of systems biology and network analysis in the study of a wide range of rheumatic diseases to better understand the underlying molecular and clinical features.

On the search for design principles in biological systems.

PubMed

Poyatos, Juan F

2012-01-01

The search for basic concepts and underlying principles was at the core of the systems approach to science and technology. This approach was somehow abandoned in mainstream biology after its initial proposal, due to the rise and success of molecular biology. This situation has changed. The accumulated knowledge of decades of molecular studies in combination with new technological advances, while further highlighting the intricacies of natural systems, is also bringing back the quest-for-principles research program. Here, I present two lessons that I derived from my own quest: the importance of studying biological information processing to identify common principles in seemingly unrelated contexts and the adequacy of using known design principles at one level of biological organization as a valuable tool to help recognizing principles at an alternative one. These and additional lessons should contribute to the ultimate goal of establishing principles able to integrate the many scales of biological complexity.

Information Complexity and Biology

NASA Astrophysics Data System (ADS)

Bagnoli, Franco; Bignone, Franco A.; Cecconi, Fabio; Politi, Antonio

Kolmogorov contributed directly to Biology in essentially three problems: the analysis of population dynamics (Lotka-Volterra equations), the reaction-diffusion formulation of gene spreading (FKPP equation), and some discussions about Mendel's laws. However, the widely recognized importance of his contribution arises from his work on algorithmic complexity. In fact, the limited direct intervention in Biology reflects the generally slow growth of interest of mathematicians towards biological issues. From the early work of Vito Volterra on species competition, to the slow growth of dynamical systems theory, contributions to the study of matter and the physiology of the nervous system, the first 50-60 years have witnessed important contributions, but as scattered pieces apparently uncorrelated, and in branches often far away from Biology. Up to the 40' it is hard to see the initial loose build up of a convergence, for those theories that will become mainstream research by the end of the century, and connected by the study of biological systems per-se.

Multi-level and hybrid modelling approaches for systems biology.

PubMed

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

2017-01-01

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

Fabrication, Characterization, and Biological Activity of Avermectin Nano-delivery Systems with Different Particle Sizes

NASA Astrophysics Data System (ADS)

Wang, Anqi; Wang, Yan; Sun, Changjiao; Wang, Chunxin; Cui, Bo; Zhao, Xiang; Zeng, Zhanghua; Yao, Junwei; Yang, Dongsheng; Liu, Guoqiang; Cui, Haixin

2018-01-01

Nano-delivery systems for the active ingredients of pesticides can improve the utilization rates of pesticides and prolong their control effects. This is due to the nanocarrier envelope and controlled release function. However, particles containing active ingredients in controlled release pesticide formulations are generally large and have wide size distributions. There have been limited studies about the effect of particle size on the controlled release properties and biological activities of pesticide delivery systems. In the current study, avermectin (Av) nano-delivery systems were constructed with different particle sizes and their performances were evaluated. The Av release rate in the nano-delivery system could be effectively controlled by changing the particle size. The biological activity increased with decreasing particle size. These results suggest that Av nano-delivery systems can significantly improve the controllable release, photostability, and biological activity, which will improve efficiency and reduce pesticide residues.

Review of the fundamental theories behind small angle X-ray scattering, molecular dynamics simulations, and relevant integrated application

PubMed Central

Boldon, Lauren; Laliberte, Fallon; Liu, Li

2015-01-01

In this paper, the fundamental concepts and equations necessary for performing small angle X-ray scattering (SAXS) experiments, molecular dynamics (MD) simulations, and MD-SAXS analyses were reviewed. Furthermore, several key biological and non-biological applications for SAXS, MD, and MD-SAXS are presented in this review; however, this article does not cover all possible applications. SAXS is an experimental technique used for the analysis of a wide variety of biological and non-biological structures. SAXS utilizes spherical averaging to produce one- or two-dimensional intensity profiles, from which structural data may be extracted. MD simulation is a computer simulation technique that is used to model complex biological and non-biological systems at the atomic level. MD simulations apply classical Newtonian mechanics’ equations of motion to perform force calculations and to predict the theoretical physical properties of the system. This review presents several applications that highlight the ability of both SAXS and MD to study protein folding and function in addition to non-biological applications, such as the study of mechanical, electrical, and structural properties of non-biological nanoparticles. Lastly, the potential benefits of combining SAXS and MD simulations for the study of both biological and non-biological systems are demonstrated through the presentation of several examples that combine the two techniques. PMID:25721341

Pairwise Maximum Entropy Models for Studying Large Biological Systems: When They Can Work and When They Can't

PubMed Central

Roudi, Yasser; Nirenberg, Sheila; Latham, Peter E.

2009-01-01

One of the most critical problems we face in the study of biological systems is building accurate statistical descriptions of them. This problem has been particularly challenging because biological systems typically contain large numbers of interacting elements, which precludes the use of standard brute force approaches. Recently, though, several groups have reported that there may be an alternate strategy. The reports show that reliable statistical models can be built without knowledge of all the interactions in a system; instead, pairwise interactions can suffice. These findings, however, are based on the analysis of small subsystems. Here, we ask whether the observations will generalize to systems of realistic size, that is, whether pairwise models will provide reliable descriptions of true biological systems. Our results show that, in most cases, they will not. The reason is that there is a crossover in the predictive power of pairwise models: If the size of the subsystem is below the crossover point, then the results have no predictive power for large systems. If the size is above the crossover point, then the results may have predictive power. This work thus provides a general framework for determining the extent to which pairwise models can be used to predict the behavior of large biological systems. Applied to neural data, the size of most systems studied so far is below the crossover point. PMID:19424487

Plant defense compounds: systems approaches to metabolic analysis.

PubMed

Kliebenstein, Daniel J

2012-01-01

Systems biology attempts to answer biological questions by integrating across diverse genomic data sets. With the increasing ability to conduct genomics experiments, this integrative approach is being rapidly applied across numerous biological research communities. One of these research communities investigates how plants utilize secondary metabolites or defense metabolites to defend against attack by pathogens and other biotic organisms. This use of systems biology to integrate across transcriptomics, metabolomics, and genomics is significantly enhancing the rate of discovery of genes, metabolites, and bioactivities for plant defense compounds as well as extending our knowledge of how these compounds are regulated. Plant defense compounds are also providing a unique proving platform to develop new approaches that enhance the ability to conduct systems biology with existing and previously unforseen genomics data sets. This review attempts to illustrate both how systems biology is helping the study of plant defense compounds and vice versa.

Metabolomics: Definitions and Significance in Systems Biology.

PubMed

Klassen, Aline; Faccio, Andréa Tedesco; Canuto, Gisele André Baptista; da Cruz, Pedro Luis Rocha; Ribeiro, Henrique Caracho; Tavares, Marina Franco Maggi; Sussulini, Alessandra

2017-01-01

Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

Digital biology and chemistry.

PubMed

Witters, Daan; Sun, Bing; Begolo, Stefano; Rodriguez-Manzano, Jesus; Robles, Whitney; Ismagilov, Rustem F

2014-09-07

This account examines developments in "digital" biology and chemistry within the context of microfluidics, from a personal perspective. Using microfluidics as a frame of reference, we identify two areas of research within digital biology and chemistry that are of special interest: (i) the study of systems that switch between discrete states in response to changes in chemical concentration of signals, and (ii) the study of single biological entities such as molecules or cells. In particular, microfluidics accelerates analysis of switching systems (i.e., those that exhibit a sharp change in output over a narrow range of input) by enabling monitoring of multiple reactions in parallel over a range of concentrations of signals. Conversely, such switching systems can be used to create new kinds of microfluidic detection systems that provide "analog-to-digital" signal conversion and logic. Microfluidic compartmentalization technologies for studying and isolating single entities can be used to reconstruct and understand cellular processes, study interactions between single biological entities, and examine the intrinsic heterogeneity of populations of molecules, cells, or organisms. Furthermore, compartmentalization of single cells or molecules in "digital" microfluidic experiments can induce switching in a range of reaction systems to enable sensitive detection of cells or biomolecules, such as with digital ELISA or digital PCR. This "digitizing" offers advantages in terms of robustness, assay design, and simplicity because quantitative information can be obtained with qualitative measurements. While digital formats have been shown to improve the robustness of existing chemistries, we anticipate that in the future they will enable new chemistries to be used for quantitative measurements, and that digital biology and chemistry will continue to provide further opportunities for measuring biomolecules, understanding natural systems more deeply, and advancing molecular and cellular analysis. Microfluidics will impact digital biology and chemistry and will also benefit from them if it becomes massively distributed.

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

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?

Systems Biology-Based Investigation of Host-Plasmodium Interactions.

PubMed

Smith, Maren L; Styczynski, Mark P

2018-05-18

Malaria is a serious, complex disease caused by parasites of the genus Plasmodium. Plasmodium parasites affect multiple tissues as they evade immune responses, replicate, sexually reproduce, and transmit between vertebrate and invertebrate hosts. The explosion of omics technologies has enabled large-scale collection of Plasmodium infection data, revealing systems-scale patterns, mechanisms of pathogenesis, and the ways that host and pathogen affect each other. Here, we provide an overview of recent efforts using systems biology approaches to study host-Plasmodium interactions and the biological themes that have emerged from these efforts. We discuss some of the challenges in using systems biology for this goal, key research efforts needed to address those issues, and promising future malaria applications of systems biology. Copyright © 2018 Elsevier Ltd. All rights reserved.

Biostack: A study of the biological effects on HZE galactic cosmic radiation

NASA Technical Reports Server (NTRS)

Buecker, H.

1975-01-01

The Biostack experiment designed to study the effect of individual heavy nucleii of the cosmic radiation environment upon biological systems during actual space flight is described. In each Biostack, several thousand biological objects were hit by an HZE particle. The response of the biological objects was studied. Results are discussed in terms of sensitivity to the hit.

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

PubMed

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

2008-10-01

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

Synthetic Biology: Engineering Living Systems from Biophysical Principles.

PubMed

Bartley, Bryan A; Kim, Kyung; Medley, J Kyle; Sauro, Herbert M

2017-03-28

Synthetic biology was founded as a biophysical discipline that sought explanations for the origins of life from chemical and physical first principles. Modern synthetic biology has been reinvented as an engineering discipline to design new organisms as well as to better understand fundamental biological mechanisms. However, success is still largely limited to the laboratory and transformative applications of synthetic biology are still in their infancy. Here, we review six principles of living systems and how they compare and contrast with engineered systems. We cite specific examples from the synthetic biology literature that illustrate these principles and speculate on their implications for further study. To fully realize the promise of synthetic biology, we must be aware of life's unique properties. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Fock space, symbolic algebra, and analytical solutions for small stochastic systems.

PubMed

Santos, Fernando A N; Gadêlha, Hermes; Gaffney, Eamonn A

2015-12-01

Randomness is ubiquitous in nature. From single-molecule biochemical reactions to macroscale biological systems, stochasticity permeates individual interactions and often regulates emergent properties of the system. While such systems are regularly studied from a modeling viewpoint using stochastic simulation algorithms, numerous potential analytical tools can be inherited from statistical and quantum physics, replacing randomness due to quantum fluctuations with low-copy-number stochasticity. Nevertheless, classical studies remained limited to the abstract level, demonstrating a more general applicability and equivalence between systems in physics and biology rather than exploiting the physics tools to study biological systems. Here the Fock space representation, used in quantum mechanics, is combined with the symbolic algebra of creation and annihilation operators to consider explicit solutions for the chemical master equations describing small, well-mixed, biochemical, or biological systems. This is illustrated with an exact solution for a Michaelis-Menten single enzyme interacting with limited substrate, including a consideration of very short time scales, which emphasizes when stiffness is present even for small copy numbers. Furthermore, we present a general matrix representation for Michaelis-Menten kinetics with an arbitrary number of enzymes and substrates that, following diagonalization, leads to the solution of this ubiquitous, nonlinear enzyme kinetics problem. For this, a flexible symbolic maple code is provided, demonstrating the prospective advantages of this framework compared to stochastic simulation algorithms. This further highlights the possibilities for analytically based studies of stochastic systems in biology and chemistry using tools from theoretical quantum physics.

Growing trend of CE at the omics level: the frontier of systems biology.

PubMed

Oh, Eulsik; Hasan, Md Nabiul; Jamshed, Muhammad; Park, Soo Hyun; Hong, Hye-Min; Song, Eun Joo; Yoo, Young Sook

2010-01-01

In a novel attempt to comprehend the complexity of life, systems biology has recently emerged as a state-of-the-art approach for biological research in contrast to the reductionist approaches that have been used in molecular cell biology since the 1950s. Because a massive amount of information is required in many systems biology studies of life processes, we have increasingly come to depend on techniques that provide high-throughput omics data. CE and CE coupled to MS have served as powerful analytical tools for providing qualitative and quantitative omics data. Recent systems biology studies have focused strongly on the diagnosis and treatment of diseases. The increasing number of clinical research papers on drug discovery and disease therapies reflects this growing interest among scientists. Since such clinical research reflects one of the ultimate purposes of bioscience, these trends will be sustained for a long time. Thus, this review mainly focuses on the application of CE and CE-MS in diagnosis as well as on the latest CE methods developed. Furthermore, we outline the new challenges that arose in 2008 and later in elucidating the system-level functions of the bioconstituents of living organisms.

When preparation meets opportunity: a case study exploring the feasibility of pursuing a career in biology for two Latina high school girls

NASA Astrophysics Data System (ADS)

García, Yeni Violeta

2013-12-01

The future of this country depends on utilizing human intellectual resources from varying viewpoints to make informed decisions on issues from conservation biology to biotechnology, or even bioengineering. An increase in Latina/o students in the biological sciences would bring a variety of viewpoints, as well as personal and cultural experiences that would advance the field. To insure that we have enough experts in biology that represent changes in demographic trends, we must look into utilizing the expertise of students in our current educational system to continue and complete careers in biology. In this study, a career in biology referred to careers that require an expertise in biology that is gained by completing a bachelor's degree in biology or an affiliated field. Using case study methodology, I explored the experiences of two Latina students, one who is undocumented, and focused on the nature of the experiences and how they related to the young women's decision to pursue a career in biology. This study is grounded on a theoretical framework of critical systems theory and the notion that there are systems and components within those systems that either facilitate or hinder students' ability to pursue various pathways. Data were generated from semi-structured interviews, artifacts, life narratives, and cultural descriptors to gain an understanding of the girls' past, present, and future decisions regarding the feasibility of pursuing a degree in biology. Four common themes emerged: (1) experiences that made a lasting positive or negative impact early in life; (2) an intrinsic desire to serve their community or people in need; (3) sociocultural support networks; and (4) opportunities or circumstances within the cultural commons associated with their legal status in the United States, which caused the girls to continue or to deviate from their path towards pursuing a career in biology.

The Effects of Restructuring Biology Teaching by a Constructivist Teaching Approach: An Action Research.

ERIC Educational Resources Information Center

Lin, Wan-Ju

This study reports on the improvement of a teacher researcher's teaching practice by adopting a constructivist teaching approach. Four biology units on the nervous system, human circulatory system, evolution, and vertebrate classification were selected to illustrate a model of biology teaching. Data were drawn from student responses to…

Holistic systems biology approaches to molecular mechanisms of human helper T cell differentiation to functionally distinct subsets.

PubMed

Chen, Z; Lönnberg, T; Lahesmaa, R

2013-08-01

Current knowledge of helper T cell differentiation largely relies on data generated from mouse studies. To develop therapeutical strategies combating human diseases, understanding the molecular mechanisms how human naïve T cells differentiate to functionally distinct T helper (Th) subsets as well as studies on human differentiated Th cell subsets is particularly valuable. Systems biology approaches provide a holistic view of the processes of T helper differentiation, enable discovery of new factors and pathways involved and generation of new hypotheses to be tested to improve our understanding of human Th cell differentiation and immune-mediated diseases. Here, we summarize studies where high-throughput systems biology approaches have been exploited to human primary T cells. These studies reveal new factors and signalling pathways influencing T cell differentiation towards distinct subsets, important for immune regulation. Such information provides new insights into T cell biology and into targeting immune system for therapeutic interventions. © 2013 John Wiley & Sons Ltd.

The species translation challenge—A systems biology perspective on human and rat bronchial epithelial cells

PubMed Central

Poussin, Carine; Mathis, Carole; Alexopoulos, Leonidas G; Messinis, Dimitris E; Dulize, Rémi H J; Belcastro, Vincenzo; Melas, Ioannis N; Sakellaropoulos, Theodore; Rhrissorrakrai, Kahn; Bilal, Erhan; Meyer, Pablo; Talikka, Marja; Boué, Stéphanie; Norel, Raquel; Rice, John J; Stolovitzky, Gustavo; Ivanov, Nikolai V; Peitsch, Manuel C; Hoeng, Julia

2014-01-01

The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to ‘translate’ the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies. PMID:25977767

The species translation challenge-a systems biology perspective on human and rat bronchial epithelial cells.

PubMed

Poussin, Carine; Mathis, Carole; Alexopoulos, Leonidas G; Messinis, Dimitris E; Dulize, Rémi H J; Belcastro, Vincenzo; Melas, Ioannis N; Sakellaropoulos, Theodore; Rhrissorrakrai, Kahn; Bilal, Erhan; Meyer, Pablo; Talikka, Marja; Boué, Stéphanie; Norel, Raquel; Rice, John J; Stolovitzky, Gustavo; Ivanov, Nikolai V; Peitsch, Manuel C; Hoeng, Julia

2014-01-01

The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to 'translate' the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies.

Designing and testing a classroom curriculum to teach preschoolers about the biology of physical activity: The respiration system as an underlying biological causal mechanism

NASA Astrophysics Data System (ADS)

Ewing, Tracy S.

The present study examined young children's understanding of respiration and oxygen as a source of vital energy underlying physical activity. Specifically, the purpose of the study was to explore whether a coherent biological theory, characterized by an understanding that bodily parts (heart and lungs) and processes (oxygen in respiration) as part of a biological system, can be taught as a foundational concept to reason about physical activity. The effects of a biology-based intervention curriculum designed to teach preschool children about bodily functions as a part of the respiratory system, the role of oxygen as a vital substance and how physical activity acts an energy source were examined. Participants were recruited from three private preschool classrooms (two treatment; 1 control) in Southern California and included a total of 48 four-year-old children (30 treatment; 18 control). Findings from this study suggested that young children could be taught relevant biological concepts about the role of oxygen in respiratory processes. Children who received biology-based intervention curriculum made significant gains in their understanding of the biology of respiration, identification of physical and sedentary activities. In addition these children demonstrated that coherence of conceptual knowledge was correlated with improved accuracy at activity identification and reasoning about the inner workings of the body contributing to endurance. Findings from this study provided evidence to support the benefits of providing age appropriate but complex coherent biological instruction to children in early childhood settings.

The road not taken: Applications of fluorescence spectroscopy and electronic structure theory to systems of materials and biological relevance

NASA Astrophysics Data System (ADS)

Carlson, Philip Joseph

Applications of Fluorescence Spectroscopy and Electronic Structure Theory to Systems of Materials and Biological Relevance. The photophysics of curcumin was studied in micelles and the solvation dynamics were probed. The high-energy ionic liquid HEATN was also studied using the fragment molecular orbital method. The solvation dynamics of the HEATN system were determined. This marks the first study of the solvation dynamics in a triazolium ionic liquid system.

The Future of Cell Biology: Emerging Model Organisms.

PubMed

Goldstein, Bob; King, Nicole

2016-11-01

Most current research in cell biology uses just a handful of model systems including yeast, Arabidopsis, Drosophila, Caenorhabditis elegans, zebrafish, mouse, and cultured mammalian cells. And for good reason - for many biological questions, the best system for the question is likely to be found among these models. However, in some cases, and particularly as the questions that engage scientists broaden, the best system for a question may be a little-studied organism. Modern research tools are facilitating a renaissance for unusual and interesting organisms as emerging model systems. As a result, we predict that an ever-expanding breadth of model systems may be a hallmark of future cell biology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Vision-guided micromanipulation system for biomedical application

NASA Astrophysics Data System (ADS)

Shim, Jae-Hong; Cho, Sung-Yong; Cha, Dong-Hyuk

2004-10-01

In these days, various researches for biomedical application of robots have been carried out. Particularly, robotic manipulation of the biological cells has been studied by many researchers. Usually, most of the biological cell's shape is sphere. Commercial biological manipulation systems have been utilized the 2-Dimensional images through the optical microscopes only. Moreover, manipulation of the biological cells mainly depends on the subjective viewpoint of an operator. Due to these reasons, there exist lots of problems such as slippery and destruction of the cell membrane and damage of the pipette tip etc. In order to overcome the problems, we have proposed a vision-guided biological cell manipulation system. The newly proposed manipulation system makes use of vision and graphic techniques. Through the proposed procedures, an operator can inject the biological cell scientifically and objectively. Also, the proposed manipulation system can measure the contact force occurred at injection of a biological cell. It can be transmitted a measured force to the operator by the proposed haptic device. Consequently, the proposed manipulation system could safely handle the biological cells without any damage. This paper presents the introduction of our vision-guided manipulation techniques and the concept of the contact force sensing. Through a series of experiments the proposed vision-guided manipulation system shows the possibility of application for precision manipulation of the biological cell such as DNA.

Systems Biology Analysis of Heterocellular Signaling.

PubMed

Tape, Christopher J

2016-08-01

Tissues comprise multiple heterotypic cell types (e.g., epithelial, mesenchymal, and immune cells). Communication between heterotypic cell types is essential for biological cohesion and is frequently dysregulated in disease. Despite the importance of heterocellular communication, most systems biology techniques do not report cell-specific signaling data from mixtures of cells. As a result, our existing perspective of cellular behavior under-represents the influence of heterocellular signaling. Recent technical advances now permit the resolution of systems-level cell-specific signaling data. This review discusses how new physical, spatial, and isotopic resolving methods are facilitating unique systems biology studies of heterocellular communication. Copyright © 2016 Elsevier Ltd. All rights reserved.

Metabolic engineering with systems biology tools to optimize production of prokaryotic secondary metabolites.

PubMed

Kim, Hyun Uk; Charusanti, Pep; Lee, Sang Yup; Weber, Tilmann

2016-08-27

Covering: 2012 to 2016Metabolic engineering using systems biology tools is increasingly applied to overproduce secondary metabolites for their potential industrial production. In this Highlight, recent relevant metabolic engineering studies are analyzed with emphasis on host selection and engineering approaches for the optimal production of various prokaryotic secondary metabolites: native versus heterologous hosts (e.g., Escherichia coli) and rational versus random approaches. This comparative analysis is followed by discussions on systems biology tools deployed in optimizing the production of secondary metabolites. The potential contributions of additional systems biology tools are also discussed in the context of current challenges encountered during optimization of secondary metabolite production.

Quantitative biology of single neurons

PubMed Central

Eberwine, James; Lovatt, Ditte; Buckley, Peter; Dueck, Hannah; Francis, Chantal; Kim, Tae Kyung; Lee, Jaehee; Lee, Miler; Miyashiro, Kevin; Morris, Jacqueline; Peritz, Tiina; Schochet, Terri; Spaethling, Jennifer; Sul, Jai-Yoon; Kim, Junhyong

2012-01-01

The building blocks of complex biological systems are single cells. Fundamental insights gained from single-cell analysis promise to provide the framework for understanding normal biological systems development as well as the limits on systems/cellular ability to respond to disease. The interplay of cells to create functional systems is not well understood. Until recently, the study of single cells has concentrated primarily on morphological and physiological characterization. With the application of new highly sensitive molecular and genomic technologies, the quantitative biochemistry of single cells is now accessible. PMID:22915636

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.

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

Information theory in systems biology. Part I: Gene regulatory and metabolic networks.

PubMed

Mousavian, Zaynab; Kavousi, Kaveh; Masoudi-Nejad, Ali

2016-03-01

"A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory. Copyright © 2015 Elsevier Ltd. All rights reserved.

An outlook review: mechanochromic materials and their potential for biological and healthcare applications.

PubMed

Jiang, Ying

2014-12-01

Macroscopic mechanical perturbations have been observed to result in optical changes for certain compounds and composite materials. This phenomenon could originate from chemical and physical changes across various length scales, from the rearrangement of chemical bonds to alteration of molecular domains on the order of several hundred nanometers. This review classifies the mechanisms and surveys of how each class of mechanochromic materials has been, and can potentially be applied in biological and healthcare innovations. The study of cellular and molecular responses to mechanical forces in biological systems is an emerging field; there is potential in applying mechanochromic principles and material systems for probing biological systems. On the other hand, application of mechanochromic materials for medical and healthcare consumer products has been described in a wide variety of concepts and inventions. It is hopeful that further understanding of mechanochromism and material innovations would initiate concrete, impactful studies in biological systems soon. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative systems biology between human and animal models based on next-generation sequencing methods.

PubMed

Zhao, Yu-Qi; Li, Gong-Hua; Huang, Jing-Fei

2013-04-01

Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.

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.

Macro- and microscale fluid flow systems for endothelial cell biology.

PubMed

Young, Edmond W K; Simmons, Craig A

2010-01-21

Recent advances in microfluidics have brought forth new tools for studying flow-induced effects on mammalian cells, with important applications in cardiovascular, bone and cancer biology. The plethora of microscale systems developed to date demonstrate the flexibility of microfluidic designs, and showcase advantages of the microscale that are simply not available at the macroscale. However, the majority of these systems will likely not achieve widespread use in the biological laboratory due to their complexity and lack of user-friendliness. To gain widespread acceptance in the biological research community, microfluidics engineers must understand the needs of cell biologists, while biologists must be made aware of available technology. This review provides a critical evaluation of cell culture flow (CCF) systems used to study the effects of mechanical forces on endothelial cells (ECs) in vitro. To help understand the need for various designs of CCF systems, we first briefly summarize main properties of ECs and their native environments. Basic principles of various macro- and microscale systems are described and evaluated. New opportunities are uncovered for developing technologies that have potential to both improve efficiency of experimentation as well as answer important biological questions that otherwise cannot be tackled with existing systems. Finally, we discuss some of the unresolved issues related to microfluidic cell culture, suggest possible avenues of investigation that could resolve these issues, and provide an outlook for the future of microfluidics in biological research.

Stochastic and deterministic multiscale models for systems biology: an auxin-transport case study.

PubMed

Twycross, Jamie; Band, Leah R; Bennett, Malcolm J; King, John R; Krasnogor, Natalio

2010-03-26

Stochastic and asymptotic methods are powerful tools in developing multiscale systems biology models; however, little has been done in this context to compare the efficacy of these methods. The majority of current systems biology modelling research, including that of auxin transport, uses numerical simulations to study the behaviour of large systems of deterministic ordinary differential equations, with little consideration of alternative modelling frameworks. In this case study, we solve an auxin-transport model using analytical methods, deterministic numerical simulations and stochastic numerical simulations. Although the three approaches in general predict the same behaviour, the approaches provide different information that we use to gain distinct insights into the modelled biological system. We show in particular that the analytical approach readily provides straightforward mathematical expressions for the concentrations and transport speeds, while the stochastic simulations naturally provide information on the variability of the system. Our study provides a constructive comparison which highlights the advantages and disadvantages of each of the considered modelling approaches. This will prove helpful to researchers when weighing up which modelling approach to select. In addition, the paper goes some way to bridging the gap between these approaches, which in the future we hope will lead to integrative hybrid models.

Co-culture systems and technologies: taking synthetic biology to the next level

PubMed Central

Goers, Lisa; Freemont, Paul; Polizzi, Karen M.

2014-01-01

Co-culture techniques find myriad applications in biology for studying natural or synthetic interactions between cell populations. Such techniques are of great importance in synthetic biology, as multi-species cell consortia and other natural or synthetic ecology systems are widely seen to hold enormous potential for foundational research as well as novel industrial, medical and environmental applications with many proof-of-principle studies in recent years. What is needed for co-cultures to fulfil their potential? Cell–cell interactions in co-cultures are strongly influenced by the extracellular environment, which is determined by the experimental set-up, which therefore needs to be given careful consideration. An overview of existing experimental and theoretical co-culture set-ups in synthetic biology and adjacent fields is given here, and challenges and opportunities involved in such experiments are discussed. Greater focus on foundational technology developments for co-cultures is needed for many synthetic biology systems to realize their potential in both applications and answering biological questions. PMID:24829281

Will Systems Biology Deliver Its Promise and Contribute to the Development of New or Improved Vaccines? What Really Constitutes the Study of "Systems Biology" and How Might Such an Approach Facilitate Vaccine Design.

PubMed

Germain, Ronald N

2017-10-16

A dichotomy exists in the field of vaccinology about the promise versus the hype associated with application of "systems biology" approaches to rational vaccine design. Some feel it is the only way to efficiently uncover currently unknown parameters controlling desired immune responses or discover what elements actually mediate these responses. Others feel that traditional experimental, often reductionist, methods for incrementally unraveling complex biology provide a more solid way forward, and that "systems" approaches are costly ways to collect data without gaining true insight. Here I argue that both views are inaccurate. This is largely because of confusion about what can be gained from classical experimentation versus statistical analysis of large data sets (bioinformatics) versus methods that quantitatively explain emergent properties of complex assemblies of biological components, with the latter reflecting what was previously called "physiology." Reductionist studies will remain essential for generating detailed insight into the functional attributes of specific elements of biological systems, but such analyses lack the power to provide a quantitative and predictive understanding of global system behavior. But by employing (1) large-scale screening methods for discovery of unknown components and connections in the immune system ( omics ), (2) statistical analysis of large data sets ( bioinformatics ), and (3) the capacity of quantitative computational methods to translate these individual components and connections into models of emergent behavior ( systems biology ), we will be able to better understand how the overall immune system functions and to determine with greater precision how to manipulate it to produce desired protective responses. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

Studies on Semantic Systems Chemical Biology

ERIC Educational Resources Information Center

Chen, Bin

2012-01-01

Current "one disease, one target and one drug" drug development paradigm is under question as relatively few drugs have reached the market in the last two decades. Increasingly research focus is being placed on the study of drug action against biological systems as a whole rather than against a single component (called "Systems…

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

PubMed Central

Chen, Bor-Sen; Wu, Chia-Chou

2013-01-01

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

Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

PubMed

Chen, Bor-Sen; Wu, Chia-Chou

2013-10-11

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

Mathematical modeling of physiological systems: an essential tool for discovery.

PubMed

Glynn, Patric; Unudurthi, Sathya D; Hund, Thomas J

2014-08-28

Mathematical models are invaluable tools for understanding the relationships between components of a complex system. In the biological context, mathematical models help us understand the complex web of interrelations between various components (DNA, proteins, enzymes, signaling molecules etc.) in a biological system, gain better understanding of the system as a whole, and in turn predict its behavior in an altered state (e.g. disease). Mathematical modeling has enhanced our understanding of multiple complex biological processes like enzyme kinetics, metabolic networks, signal transduction pathways, gene regulatory networks, and electrophysiology. With recent advances in high throughput data generation methods, computational techniques and mathematical modeling have become even more central to the study of biological systems. In this review, we provide a brief history and highlight some of the important applications of modeling in biological systems with an emphasis on the study of excitable cells. We conclude with a discussion about opportunities and challenges for mathematical modeling going forward. In a larger sense, the review is designed to help answer a simple but important question that theoreticians frequently face from interested but skeptical colleagues on the experimental side: "What is the value of a model?" Copyright © 2014 Elsevier Inc. All rights reserved.

Robust Design of Biological Circuits: Evolutionary Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia

2011-01-01

Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise. PMID:22187523

Robust design of biological circuits: evolutionary systems biology approach.

PubMed

Chen, Bor-Sen; Hsu, Chih-Yuan; Liou, Jing-Jia

2011-01-01

Artificial gene circuits have been proposed to be embedded into microbial cells that function as switches, timers, oscillators, and the Boolean logic gates. Building more complex systems from these basic gene circuit components is one key advance for biologic circuit design and synthetic biology. However, the behavior of bioengineered gene circuits remains unstable and uncertain. In this study, a nonlinear stochastic system is proposed to model the biological systems with intrinsic parameter fluctuations and environmental molecular noise from the cellular context in the host cell. Based on evolutionary systems biology algorithm, the design parameters of target gene circuits can evolve to specific values in order to robustly track a desired biologic function in spite of intrinsic and environmental noise. The fitness function is selected to be inversely proportional to the tracking error so that the evolutionary biological circuit can achieve the optimal tracking mimicking the evolutionary process of a gene circuit. Finally, several design examples are given in silico with the Monte Carlo simulation to illustrate the design procedure and to confirm the robust performance of the proposed design method. The result shows that the designed gene circuits can robustly track desired behaviors with minimal errors even with nontrivial intrinsic and external noise.

Simultaneous biological nutrient removal: evaluation of autotrophic denitrification, heterotrophic nitrification, and biological phosphorus removal in full-scale systems.

PubMed

Littleton, Helen X; Daigger, Glen T; Strom, Peter F; Cowan, Robert A

2003-01-01

Simultaneous biological nutrient removal (SBNR) is the biological removal of nitrogen and phosphorus in excess of that required for biomass synthesis in a biological wastewater treatment system without defined anaerobic or anoxic zones. Evidence is growing that significant SBNR can occur in many systems, including the aerobic zone of systems already configured for biological nutrient removal. Although SBNR systems offer several potential advantages, they cannot be fully realized until the mechanisms responsible for SBNR are better understood. Consequently, a research program was initiated with the basic hypothesis that three mechanisms might be responsible for SBNR: the reactor macroenvironment, the floc microenvironment, and novel microorganisms. Previously, the nutrient removal capabilities of seven full-scale, staged, closed-loop bioreactors known as Orbal oxidation ditches were evaluated. Chemical analysis and microbiological observations suggested that SBNR occurred in these systems. Three of these plants were further examined in this research to evaluate the importance of novel microorganisms, especially for nitrogen removal. A screening tool was developed to determine the relative significance of the activities of microorganisms capable of autotrophic denitrification and heterotrophic nitrification-aerobic denitrification in biological nutrient removal systems. The results indicated that novel microorganisms were not substantial contributors to SBNR in the plants studied. Phosphorus metabolism (anaerobic release, aerobic uptake) was also tested in one of the plants. Activity within the mixed liquor that was consistent with current theories for phosphorus-accumulating organisms (PAOs) was observed. Along with other observations, this suggests the presence of PAOs in the facilities studied.

Omics/systems biology and cancer cachexia.

PubMed

Gallagher, Iain J; Jacobi, Carsten; Tardif, Nicolas; Rooyackers, Olav; Fearon, Kenneth

2016-06-01

Cancer cachexia is a complex syndrome generated by interaction between the host and tumour cells with a background of treatment effects and toxicity. The complexity of the physiological pathways likely involved in cancer cachexia necessitates a holistic view of the relevant biology. Emergent properties are characteristic of complex systems with the result that the end result is more than the sum of its parts. Recognition of the importance of emergent properties in biology led to the concept of systems biology wherein a holistic approach is taken to the biology at hand. Systems biology approaches will therefore play an important role in work to uncover key mechanisms with therapeutic potential in cancer cachexia. The 'omics' technologies provide a global view of biological systems. Genomics, transcriptomics, proteomics, lipidomics and metabolomics approaches all have application in the study of cancer cachexia to generate systems level models of the behaviour of this syndrome. The current work reviews recent applications of these technologies to muscle atrophy in general and cancer cachexia in particular with a view to progress towards integration of these approaches to better understand the pathology and potential treatment pathways in cancer cachexia. Copyright © 2016. Published by Elsevier Ltd.

Dietary antioxidant synergy in chemical and biological systems.

PubMed

Wang, Sunan; Zhu, Fan

2017-07-24

Antioxidant (AOX) synergies have been much reported in chemical ("test-tube" based assays focusing on pure chemicals), biological (tissue culture, animal and clinical models), and food systems during the past decade. Tentative synergies differ from each other due to the composition of AOX and the quantification methods. Regeneration mechanism responsible for synergy in chemical systems has been discussed. Solvent effects could contribute to the artifacts of synergy observed in the chemical models. Synergy in chemical models may hardly be relevant to biological systems that have been much less studied. Apparent discrepancies exist in understanding the molecular mechanisms in both chemical and biological systems. This review discusses diverse variables associated with AOX synergy and molecular scenarios for explanation. Future research to better utilize the synergy is suggested.

Bayesian comparative effectiveness study of four consensus treatment plans for initial management of systemic juvenile idiopathic arthritis: FiRst-Line Options for Systemic juvenile idiopathic arthritis Treatment (FROST).

PubMed

Nigrovic, Peter A; Beukelman, Timothy; Tomlinson, George; Feldman, Brian M; Schanberg, Laura E; Kimura, Yukiko

2018-06-01

Systemic juvenile idiopathic arthritis is a rare febrile arthritis of childhood characterized by a potentially severe course, including prolonged glucocorticoid exposure, growth failure, destructive arthritis, and life-threatening macrophage activation syndrome. Early cytokine-blocking biologic therapy may improve long-term outcomes, although some systemic juvenile idiopathic arthritis patients respond well to non-biologic treatment, leaving optimal management undefined. Consequently, treatment of new-onset systemic juvenile idiopathic arthritis by expert clinicians varies widely. To describe a pragmatic, observational comparative effectiveness study that takes advantage of diversity in the management of a rare disease: FiRst-Line Options for Systemic juvenile idiopathic arthritis Treatment (FROST), comparing non-biologic and biologic consensus treatment plans for new-onset systemic juvenile idiopathic arthritis within the 60-center Childhood Arthritis and Rheumatology Research Alliance Registry (CARRA). FiRst-Line Options for Systemic juvenile idiopathic arthritis Treatment (FROST) is a multicenter, prospective, non-randomized study that compares four Childhood Arthritis and Rheumatology Research Alliance (CARRA) consensus treatment plans for new-onset systemic juvenile idiopathic arthritis: (1) glucocorticoids alone, (2) methotrexate, (3) interleukin-1 blockade, and (4) interleukin-6 blockade. Patients consenting to participation in the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry are started on one of four Consensus Treatment Plans at the discretion of the treating physician. The outcome of primary interest is clinically inactive disease off glucocorticoids at 9 months, comparing non-biologic (Consensus Treatment Plans 1 + 2) versus biologic (Consensus Treatment Plans 3 + 4) strategies. Bayesian analytic methods will be employed to evaluate response rates, using propensity scoring to balance treatment groups for potential confounding. With 200 patients in a 2:1 ratio of biologic to non-biologic, there is a >90% probability of finding biologic consensus treatment plans more effective if the rate of clinically inactive disease is 30% higher than for non-biologic therapy. Additional outcomes include Patient-Reported Outcomes Measurement Information System measures and other parent-/patient-reported outcomes reported in real time using smartphone technology. Routine operation of the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry will allow assessment of outcomes over at least 10 years. FiRst-Line Options for Systemic juvenile idiopathic arthritis Treatment (FROST) began enrollment in November 2016. The observational design may not provide balance in measured and unmeasured confounders. Use of consensus treatment plan (CTP) strategies at frequencies more unbalanced than predicted could reduce the chance of finding differences in efficacy. FiRst-Line Options for Systemic juvenile idiopathic arthritis Treatment (FROST) will provide the first prospective comparison of Childhood Arthritis and Rheumatology Research Alliance's (CARRA's) consensus-derived non-biologic versus biologic management strategies in systemic juvenile idiopathic arthritis, performed in a real-world setting wherein each patient receives standard-of-care treatment selected by the treating physician. Outcomes include clinician- and patient-/family-reported outcomes, empowering both physician and patient decision making in new-onset systemic juvenile idiopathic arthritis.

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology. PMID:23578051

Metabolic systems biology: a brief primer.

PubMed

Edwards, Lindsay M

2017-05-01

In the early to mid-20th century, reductionism as a concept in biology was challenged by key thinkers, including Ludwig von Bertalanffy. He proposed that living organisms were specific examples of complex systems and, as such, they should display characteristics including hierarchical organisation and emergent behaviour. Yet the true study of complete biological systems (for example, metabolism) was not possible until technological advances that occurred 60 years later. Technology now exists that permits the measurement of complete levels of the biological hierarchy, for example the genome and transcriptome. The complexity and scale of these data require computational models for their interpretation. The combination of these - systems thinking, high-dimensional data and computation - defines systems biology, typically accompanied by some notion of iterative model refinement. Only sequencing-based technologies, however, offer full coverage. Other 'omics' platforms trade coverage for sensitivity, although the densely connected nature of biological networks suggests that full coverage may not be necessary. Systems biology models are often characterised as either 'bottom-up' (mechanistic) or 'top-down' (statistical). This distinction can mislead, as all models rely on data and all are, to some degree, 'middle-out'. Systems biology has matured as a discipline, and its methods are commonplace in many laboratories. However, many challenges remain, especially those related to large-scale data integration. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

"Toward High School Biology": Helping Middle School Students Understand Chemical Reactions and Conservation of Mass in Nonliving and Living Systems

ERIC Educational Resources Information Center

Herrmann-Abell, Cari F.; Koppal, Mary; Roseman, Jo Ellen

2016-01-01

Modern biology has become increasingly molecular in nature, requiring students to understand basic chemical concepts. Studies show, however, that many students fail to grasp ideas about atom rearrangement and conservation during chemical reactions or the application of these ideas to biological systems. To help provide students with a better…

Systems Biology Approaches for Host–Fungal Interactions: An Expanding Multi-Omics Frontier

PubMed Central

Culibrk, Luka; Croft, Carys A.

2016-01-01

Abstract Opportunistic fungal infections are an increasing threat for global health, and for immunocompromised patients in particular. These infections are characterized by interaction between fungal pathogen and host cells. The exact mechanisms and the attendant variability in host and fungal pathogen interaction remain to be fully elucidated. The field of systems biology aims to characterize a biological system, and utilize this knowledge to predict the system's response to stimuli such as fungal exposures. A multi-omics approach, for example, combining data from genomics, proteomics, metabolomics, would allow a more comprehensive and pan-optic “two systems” biology of both the host and the fungal pathogen. In this review and literature analysis, we present highly specialized and nascent methods for analysis of multiple -omes of biological systems, in addition to emerging single-molecule visualization techniques that may assist in determining biological relevance of multi-omics data. We provide an overview of computational methods for modeling of gene regulatory networks, including some that have been applied towards the study of an interacting host and pathogen. In sum, comprehensive characterizations of host–fungal pathogen systems are now possible, and utilization of these cutting-edge multi-omics strategies may yield advances in better understanding of both host biology and fungal pathogens at a systems scale. PMID:26885725

Modelling of pathologies of the nervous system by the example of computational and electronic models of elementary nervous systems

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

Shumilov, V. N., E-mail: vnshumilov@rambler.ru; Syryamkin, V. I., E-mail: maximus70sir@gmail.com; Syryamkin, M. V., E-mail: maximus70sir@gmail.com

The paper puts forward principles of action of devices operating similarly to the nervous system and the brain of biological systems. We propose an alternative method of studying diseases of the nervous system, which may significantly influence prevention, medical treatment, or at least retardation of development of these diseases. This alternative is to use computational and electronic models of the nervous system. Within this approach, we represent the brain in the form of a huge electrical circuit composed of active units, namely, neuron-like units and connections between them. As a result, we created computational and electronic models of elementary nervousmore » systems, which are based on the principles of functioning of biological nervous systems that we have put forward. Our models demonstrate reactions to external stimuli and their change similarly to the behavior of simplest biological organisms. The models possess the ability of self-training and retraining in real time without human intervention and switching operation/training modes. In our models, training and memorization take place constantly under the influence of stimuli on the organism. Training is without any interruption and switching operation modes. Training and formation of new reflexes occur by means of formation of new connections between excited neurons, between which formation of connections is physically possible. Connections are formed without external influence. They are formed under the influence of local causes. Connections are formed between outputs and inputs of two neurons, when the difference between output and input potentials of excited neurons exceeds a value sufficient to form a new connection. On these grounds, we suggest that the proposed principles truly reflect mechanisms of functioning of biological nervous systems and the brain. In order to confirm the correspondence of the proposed principles to biological nature, we carry out experiments for the study of processes of formation of connections between neurons in simplest biological objects. Based on the correspondence of function of the created models to function of biological nervous systems we suggest the use of computational and electronic models of the brain for the study of its function under normal and pathological conditions, because operating principles of the models are built on principles imitating the function of biological nervous systems and the brain.« less

Modelling of pathologies of the nervous system by the example of computational and electronic models of elementary nervous systems

NASA Astrophysics Data System (ADS)

Shumilov, V. N.; Syryamkin, V. I.; Syryamkin, M. V.

2015-11-01

The paper puts forward principles of action of devices operating similarly to the nervous system and the brain of biological systems. We propose an alternative method of studying diseases of the nervous system, which may significantly influence prevention, medical treatment, or at least retardation of development of these diseases. This alternative is to use computational and electronic models of the nervous system. Within this approach, we represent the brain in the form of a huge electrical circuit composed of active units, namely, neuron-like units and connections between them. As a result, we created computational and electronic models of elementary nervous systems, which are based on the principles of functioning of biological nervous systems that we have put forward. Our models demonstrate reactions to external stimuli and their change similarly to the behavior of simplest biological organisms. The models possess the ability of self-training and retraining in real time without human intervention and switching operation/training modes. In our models, training and memorization take place constantly under the influence of stimuli on the organism. Training is without any interruption and switching operation modes. Training and formation of new reflexes occur by means of formation of new connections between excited neurons, between which formation of connections is physically possible. Connections are formed without external influence. They are formed under the influence of local causes. Connections are formed between outputs and inputs of two neurons, when the difference between output and input potentials of excited neurons exceeds a value sufficient to form a new connection. On these grounds, we suggest that the proposed principles truly reflect mechanisms of functioning of biological nervous systems and the brain. In order to confirm the correspondence of the proposed principles to biological nature, we carry out experiments for the study of processes of formation of connections between neurons in simplest biological objects. Based on the correspondence of function of the created models to function of biological nervous systems we suggest the use of computational and electronic models of the brain for the study of its function under normal and pathological conditions, because operating principles of the models are built on principles imitating the function of biological nervous systems and the brain.

The use of continuous culture in systems biology investigations.

PubMed

Winder, Catherine L; Lanthaler, Karin

2011-01-01

When acquiring data for systems biology studies, it is essential to perform the experiments in controlled and reproducible conditions. Advances in the fields of proteomics and metabolomics allow the quantitative analysis of the components of the biological cell. It is essential to include a method in the experimental pipeline to culture the biological system in controlled and reproducible conditions to facilitate the acquisition of high-quality data. The employment of continuous culture methods for the growth of microorganisms is an ideal tool to achieve these objectives. This chapter will review the continuous culture approaches which may be applied in such studies, outline the experimental options which should be considered, and describe the approach applied in the production of steady-state cultures of Saccharomyces cerevisiae. Copyright © 2011 Elsevier Inc. All rights reserved.

[Biotechnological functional systems].

PubMed

Bokser, O Ia

1999-01-01

Based on the theory of functional systems and a concept of the quantum system of behavior, studies of the quantumsystems were conducted. Their structure, the interaction of biological and technical sections were analyzed. Mathematical, biophysical, and experimental models were designed. The paper shows that biotechnical quantumsystems are involved in the formation of biological feedback. A system with imperative feedback from the programmed and introduced current results of efforts has been developed and put into practice for the self-regulation of muscle tension. Training by using this biological feedback system causes a stable increase in the perception rate of proprioceptive stimulus in examinees (operates, sportsmen, neurological patients).

A dedicated database system for handling multi-level data in systems biology.

PubMed

Pornputtapong, Natapol; Wanichthanarak, Kwanjeera; Nilsson, Avlant; Nookaew, Intawat; Nielsen, Jens

2014-01-01

Advances in high-throughput technologies have enabled extensive generation of multi-level omics data. These data are crucial for systems biology research, though they are complex, heterogeneous, highly dynamic, incomplete and distributed among public databases. This leads to difficulties in data accessibility and often results in errors when data are merged and integrated from varied resources. Therefore, integration and management of systems biological data remain very challenging. To overcome this, we designed and developed a dedicated database system that can serve and solve the vital issues in data management and hereby facilitate data integration, modeling and analysis in systems biology within a sole database. In addition, a yeast data repository was implemented as an integrated database environment which is operated by the database system. Two applications were implemented to demonstrate extensibility and utilization of the system. Both illustrate how the user can access the database via the web query function and implemented scripts. These scripts are specific for two sample cases: 1) Detecting the pheromone pathway in protein interaction networks; and 2) Finding metabolic reactions regulated by Snf1 kinase. In this study we present the design of database system which offers an extensible environment to efficiently capture the majority of biological entities and relations encountered in systems biology. Critical functions and control processes were designed and implemented to ensure consistent, efficient, secure and reliable transactions. The two sample cases on the yeast integrated data clearly demonstrate the value of a sole database environment for systems biology research.

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

PubMed

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

2016-09-01

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

Emerging systems biology approaches in nanotoxicology: Towards a mechanism-based understanding of nanomaterial hazard and risk

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

Costa, Pedro M.; Fadeel, Bengt, E-mail: Bengt.Fade

Engineered nanomaterials are being developed for a variety of technological applications. However, the increasing use of nanomaterials in society has led to concerns about their potential adverse effects on human health and the environment. During the first decade of nanotoxicological research, the realization has emerged that effective risk assessment of the multitudes of new nanomaterials would benefit from a comprehensive understanding of their toxicological mechanisms, which is difficult to achieve with traditional, low-throughput, single end-point oriented approaches. Therefore, systems biology approaches are being progressively applied within the nano(eco)toxicological sciences. This novel paradigm implies that the study of biological systems shouldmore » be integrative resulting in quantitative and predictive models of nanomaterial behaviour in a biological system. To this end, global ‘omics’ approaches with which to assess changes in genes, proteins, metabolites, etc. are deployed allowing for computational modelling of the biological effects of nanomaterials. Here, we highlight omics and systems biology studies in nanotoxicology, aiming towards the implementation of a systems nanotoxicology and mechanism-based risk assessment of nanomaterials. - Highlights: • Systems nanotoxicology is a multi-disciplinary approach to quantitative modelling. • Transcriptomics, proteomics and metabolomics remain the most common methods. • Global “omics” techniques should be coupled to computational modelling approaches. • The discovery of nano-specific toxicity pathways and biomarkers is a prioritized goal. • Overall, experimental nanosafety research must endeavour reproducibility and relevance.« less

Impacts of Insufficient Instructional Materials on Teaching Biology: Higher Education Systems in Focus

ERIC Educational Resources Information Center

Edessa, Sutuma

2017-01-01

The purpose of this study was to assess and determine impacts of insufficient instructional materials and ineffective lesson delivery methods on teaching in biology higher education. The participants of this study were 60 trainees who graduated in Bachelor of Sciences from eight public universities in majoring biology. Data for the study was…

The Second Annual Symposium of the NASA Specialized Center of Research and Training (NSCORT) in Gravitational Biology.

PubMed

Spooner, B S

1993-04-01

The second annual meeting of the NSCORT in Gravitational Biology was held at Kansas State University on September 29-October 1, 1992. Symposium presentations at the meeting included ones on basic gravitational cellular and developmental biology, spaceflight hardware for biological studies, studies on Space Shuttle, and special talks on Space Station Freedom and on life support systems.

The Second Annual Symposium of the NASA Specialized Center of Research and Training (NSCORT) in Gravitational Biology

NASA Technical Reports Server (NTRS)

Spooner, B. S.

1993-01-01

The second annual meeting of the NSCORT in Gravitational Biology was held at Kansas State University on September 29-October 1, 1992. Symposium presentations at the meeting included ones on basic gravitational cellular and developmental biology, spaceflight hardware for biological studies, studies on Space Shuttle, and special talks on Space Station Freedom and on life support systems.

Systems biology of eukaryotic superorganisms and the holobiont concept.

PubMed

Kutschera, Ulrich

2018-06-14

The founders of modern biology (Jean Lamarck, Charles Darwin, August Weismann etc.) were organismic life scientists who attempted to understand the morphology and evolution of living beings as a whole (i.e., the phenotype). However, with the emergence of the study of animal and plant physiology in the nineteenth century, this "holistic view" of the living world changed and was ultimately replaced by a reductionistic perspective. Here, I summarize the history of systems biology, i.e., the modern approach to understand living beings as integrative organisms, from genotype to phenotype. It is documented that the physiologists Claude Bernard and Julius Sachs, who studied humans and plants, respectively, were early pioneers of this discipline, which was formally founded 50 years ago. In 1968, two influential monographs, authored by Ludwig von Bertalanffy and Mihajlo D. Mesarović, were published, wherein a "systems theory of biology" was outlined. Definitions of systems biology are presented with reference to metabolic or cell signaling networks, analyzed via genomics, proteomics, and other methods, combined with computer simulations/mathematical modeling. Then, key insights of this discipline with respect to epiphytic microbes (Methylobacterium sp.) and simple bacteria (Mycoplasma sp.) are described. The principles of homeostasis, molecular systems energetics, gnotobiology, and holobionts (i.e., complexities of host-microbiota interactions) are outlined, and the significance of systems biology for evolutionary theories is addressed. Based on the microbe-Homo sapiens-symbiosis, it is concluded that human biology and health should be interpreted in light of a view of the biomedical sciences that is based on the holobiont concept.

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

PubMed

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

2006-11-01

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

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

PubMed

Jia, Chen; Qian, Minping; Jiang, Daquan

2014-08-01

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

Information processing in bacteria: memory, computation, and statistical physics: a key issues review

NASA Astrophysics Data System (ADS)

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network—the main players (nodes) and their interactions (links)—in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

Information processing in bacteria: memory, computation, and statistical physics: a key issues review.

PubMed

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network-the main players (nodes) and their interactions (links)-in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

Dormancy and Recovery Testing for Biological Wastewater Processors

NASA Technical Reports Server (NTRS)

Hummerick, Mary F.; Coutts, Janelle L.; Lunn, Griffin M.; Spencer, LaShelle; Khodadad, Christina L.; Birmele, Michele N.; Frances, Someliz; Wheeler, Raymond

2015-01-01

Resource recovery and recycling waste streams to usable water via biological water processors is a plausible component of an integrated water purification system. Biological processing as a pretreatment can reduce the load of organic carbon and nitrogen compounds entering physiochemical systems downstream. Aerated hollow fiber membrane bioreactors, have been proposed and studied for a number of years as an approach for treating wastewater streams for space exploration.

A Case Study of Web-Based Instruction (WBI): The Effectiveness of Using Frontpage Feedback System (FFS) as Metacognition Strategy for Freshmen Biology Teaching

ERIC Educational Resources Information Center

Wang, Tzu-Hua; Wang, Wei-Lung; Wang, Kuo-Hua; Huang, Hsih-Chieh

2004-01-01

This research aims to develop a Metacognition strategy for Web-Based Instruction (WBI) to stimulate reflective questions in biology learning to run Frontpage Feedback System (FFS) embedded in web pages, and thus to evaluate the influence of this internet-teaching style on biology learning among freshmen. According to the questionnaire survey, we…

Co-culture systems and technologies: taking synthetic biology to the next level.

PubMed

Goers, Lisa; Freemont, Paul; Polizzi, Karen M

2014-07-06

Co-culture techniques find myriad applications in biology for studying natural or synthetic interactions between cell populations. Such techniques are of great importance in synthetic biology, as multi-species cell consortia and other natural or synthetic ecology systems are widely seen to hold enormous potential for foundational research as well as novel industrial, medical and environmental applications with many proof-of-principle studies in recent years. What is needed for co-cultures to fulfil their potential? Cell-cell interactions in co-cultures are strongly influenced by the extracellular environment, which is determined by the experimental set-up, which therefore needs to be given careful consideration. An overview of existing experimental and theoretical co-culture set-ups in synthetic biology and adjacent fields is given here, and challenges and opportunities involved in such experiments are discussed. Greater focus on foundational technology developments for co-cultures is needed for many synthetic biology systems to realize their potential in both applications and answering biological questions. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Bio-Physics Manifesto -- for the Future of Physics and Biology

NASA Astrophysics Data System (ADS)

Oono, Y.

2008-04-01

The Newtonian revolution taught us how to dissect phenomena into contingencies (e.g., initial conditions) and fundamental laws (e.g., equations of motion). Since then, `fundamental physics' has been pursuing purer and leaner fundamental laws. Consequently, to explain real phenomena a lot of auxiliary conditions become required. Isn't it now the time to start studying `auxiliary conditions' seriously? The study of biological systems has a possibility of shedding light on this neglected side of phenomena in physics, because we organisms were constructed by our parents who supplied indispensable auxiliary conditions; we never self-organize. Thus, studying the systems lacking self-organizing capability (such as complex systems) may indicate new directions to physics and biology (biophysics). There have been attempts to construct a `general theoretical framework' of biology, but most of them never seriously looked at the actual biological world. Every serious natural science must start with establishing a phenomenological framework. Therefore, this must be the main part of bio-physics. However, this article is addressed mainly to theoretical physicists and discusses only certain theoretical aspects (with real illustrative examples).

Molecular phenology in plants: in natura systems biology for the comprehensive understanding of seasonal responses under natural environments.

PubMed

Kudoh, Hiroshi

2016-04-01

Phenology refers to the study of seasonal schedules of organisms. Molecular phenology is defined here as the study of the seasonal patterns of organisms captured by molecular biology techniques. The history of molecular phenology is reviewed briefly in relation to advances in the quantification technology of gene expression. High-resolution molecular phenology (HMP) data have enabled us to study phenology with an approach of in natura systems biology. I review recent analyses of FLOWERING LOCUS C (FLC), a temperature-responsive repressor of flowering, along the six steps in the typical flow of in natura systems biology. The extensive studies of the regulation of FLC have made this example a successful case in which a comprehensive understanding of gene functions has been progressing. The FLC-mediated long-term memory of past temperatures creates time lags with other seasonal signals, such as photoperiod and short-term temperature. Major signals that control flowering time have a phase lag between them under natural conditions, and hypothetical phase lag calendars are proposed as mechanisms of season detection in plants. Transcriptomic HMP brings a novel strategy to the study of molecular phenology, because it provides a comprehensive representation of plant functions. I discuss future perspectives of molecular phenology from the standpoints of molecular biology, evolutionary biology and ecology. © 2015 The Author. New Phytologist © 2015 New Phytologist Trust.

NMR spectroscopy of Group 13 metal ions: biologically relevant aspects.

PubMed

André, J P; Mäcke, H R

2003-12-01

In spite of the fact that Group 13 metal ions (Al(3+), Ga(3+), In(3+) and Tl(+/3+)) show no main biological role, they are NMR-active nuclides which can be used in magnetic resonance spectroscopy of biologically relevant systems. The fact that these metal ions are quadrupolar (with the exception of thallium) means that they are particularly sensitive to ligand type and coordination geometry. The line width of the NMR signals of their complexes shows a strong dependence on the symmetry of coordination, which constitutes an effective tool in the elucidation of structures. Here we report published NMR studies of this family of elements, applied to systems of biological importance. Special emphasis is given to binding studies of these cations to biological molecules, such as proteins, and to chelating agents of radiopharmaceutical interest. The possibility of in vivo NMR studies is also stressed, with extension to (27)Al-based MRI (magnetic resonance imaging) experiments.

Pacific Northwest Laboratory annual report for 1993 to the DOE Office of Energy Research. Part 1: Biomedical Sciences

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

Lumetta, C.C.; Park, J.F.

1994-03-01

This report summarizes FY 1993 progress in biological and general life sciences research programs conducted for the Department of Energy`s Office of Health and Environmental REsearch (OHER) at Pacific Northwest Laboratory (PNL). This research provides knowledge of fundamental principles necessary to identify, understand, and anticipate the long-term health consequences of exposure to energy-related radiation and chemicals. The Biological Research section contains reports of studies using laboratory animals, in vitro cell systems, and molecular biological systems. This research includes studies of the impact of radiation, radionuclides, and chemicals on biological responses at all levels of biological organization. The General Life Sciencesmore » Research section reports research conducted for the OHER human genome program.« less

Physical methods for investigating structural colours in biological systems

PubMed Central

Vukusic, P.; Stavenga, D.G.

2009-01-01

Many biological systems are known to use structural colour effects to generate aspects of their appearance and visibility. The study of these phenomena has informed an eclectic group of fields ranging, for example, from evolutionary processes in behavioural biology to micro-optical devices in technologically engineered systems. However, biological photonic systems are invariably structurally and often compositionally more elaborate than most synthetically fabricated photonic systems. For this reason, an appropriate gamut of physical methods and investigative techniques must be applied correctly so that the systems' photonic behaviour may be appropriately understood. Here, we survey a broad range of the most commonly implemented, successfully used and recently innovated physical methods. We discuss the costs and benefits of various spectrometric methods and instruments, namely scatterometers, microspectrophotometers, fibre-optic-connected photodiode array spectrometers and integrating spheres. We then discuss the role of the materials' refractive index and several of the more commonly used theoretical approaches. Finally, we describe the recent developments in the research field of photonic crystals and the implications for the further study of structural coloration in animals. PMID:19158009

Scaffolded biology.

PubMed

Minelli, Alessandro

2016-09-01

Descriptions and interpretations of the natural world are dominated by dichotomies such as organism vs. environment, nature vs. nurture, genetic vs. epigenetic, but in the last couple of decades strong dissatisfaction with those partitions has been repeatedly voiced and a number of alternative perspectives have been suggested, from perspectives such as Dawkins' extended phenotype, Turner's extended organism, Oyama's Developmental Systems Theory and Odling-Smee's niche construction theory. Last in time is the description of biological phenomena in terms of hybrids between an organism (scaffolded system) and a living or non-living scaffold, forming unit systems to study processes such as reproduction and development. As scaffold, eventually, we can define any resource used by the biological system, especially in development and reproduction, without incorporating it as happens in the case of resources fueling metabolism. Addressing biological systems as functionally scaffolded systems may help pointing to functional relationships that can impart temporal marking to the developmental process and thus explain its irreversibility; revisiting the boundary between development and metabolism and also regeneration phenomena, by suggesting a conceptual framework within which to investigate phenomena of regular hypermorphic regeneration such as characteristic of deer antlers; fixing a periodization of development in terms of the times at which a scaffolding relationship begins or is terminated; and promoting plant galls to legitimate study objects of developmental biology.

Biological attachment devices: exploring nature's diversity for biomimetics.

PubMed

Gorb, Stanislav N

2008-05-13

Many species of animals and plants are supplied with diverse attachment devices, in which morphology depends on the species biology and the particular function in which the attachment device is involved. Many functional solutions have evolved independently in different lineages of animals and plants. Since the diversity of such biological structures is huge, there is a need for their classification. This paper, based on the original and literature data, proposes ordering of biological attachment systems according to several principles: (i) fundamental physical mechanism, according to which the system operates, (ii) biological function of the attachment device, and (iii) duration of the contact. Finally, we show a biomimetic potential of studies on biological attachment devices.

6th Institute for Systems Biology International Symposium: Systems Biology and the Environment

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

Galitski, Timothy P.

2007-04-23

Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology is an annual two-day event gathering the most influential researchers transforming biology into an integrative discipline investigating complex systems. In recognition of the fundamental similarity between the scientific problems addressed in environmental science and systems biology studies at the molecular, cellular, and organismal levels, the 2007 Symposium featured global leaders in “Systems Biology and the Environment.” The objective of the 2007 “Systems Biology and the Environment” International Symposium was to stimulate interdisciplinary thinking and research that spans systems biology andmore » environmental science. This Symposium was well aligned with the DOE’s Genomics: GTL program efforts to achieve scientific objectives for each of the three DOE missions: Develop biofuels as a major secure energy source for this century; Develop biological solutions for intractable environmental problems; Understand biosystems’ climate impacts and assess sequestration strategies. Our scientific program highlighted world-class research exemplifying these priorities. The Symposium featured 45 minute lectures from 12 researchers including: Penny/Sallie Chisholm of MIT gave the keynote address “Tiny Cells, Global Impact: What Prochlorococcus Can Teach Us About Systems Biology”, plus Jim Fredrickson of PNNL, Nitin Baliga of ISB, Steve Briggs of UCSD, David Cox of Perlegen Sciences, Antoine Danchin of Institut Pasteur, John Delaney of the U of Washington, John Groopman of Johns Hopkins, Ben Kerr of the U of Washington, Steve Koonin of BP, Elliott Meyerowitz of Caltech, and Ed Rubin of LBNL. The 2007 Symposium promoted DOE’s three mission areas among scientists from multiple disciplines representing academia, non-profit research institutions, and the private sector. As in all previous Symposia, we had excellent attendance of participants representing 20-30 academic or research-oriented facilities along with 25-30 private corporations from 5-10 countries. To broaden the audience for the Symposium and ensure the continued accessibility of the presentations, we made the presentation videos available afterward on the ISB’s website.« less

Biological Basis For Computer Vision: Some Perspectives

NASA Astrophysics Data System (ADS)

Gupta, Madan M.

1990-03-01

Using biology as a basis for the development of sensors, devices and computer vision systems is a challenge to systems and vision scientists. It is also a field of promising research for engineering applications. Biological sensory systems, such as vision, touch and hearing, sense different physical phenomena from our environment, yet they possess some common mathematical functions. These mathematical functions are cast into the neural layers which are distributed throughout our sensory regions, sensory information transmission channels and in the cortex, the centre of perception. In this paper, we are concerned with the study of the biological vision system and the emulation of some of its mathematical functions, both retinal and visual cortex, for the development of a robust computer vision system. This field of research is not only intriguing, but offers a great challenge to systems scientists in the development of functional algorithms. These functional algorithms can be generalized for further studies in such fields as signal processing, control systems and image processing. Our studies are heavily dependent on the the use of fuzzy - neural layers and generalized receptive fields. Building blocks of such neural layers and receptive fields may lead to the design of better sensors and better computer vision systems. It is hoped that these studies will lead to the development of better artificial vision systems with various applications to vision prosthesis for the blind, robotic vision, medical imaging, medical sensors, industrial automation, remote sensing, space stations and ocean exploration.

Programmable chemical reaction networks: emulating regulatory functions in living cells using a bottom-up approach.

PubMed

van Roekel, Hendrik W H; Rosier, Bas J H M; Meijer, Lenny H H; Hilbers, Peter A J; Markvoort, Albert J; Huck, Wilhelm T S; de Greef, Tom F A

2015-11-07

Living cells are able to produce a wide variety of biological responses when subjected to biochemical stimuli. It has become apparent that these biological responses are regulated by complex chemical reaction networks (CRNs). Unravelling the function of these circuits is a key topic of both systems biology and synthetic biology. Recent progress at the interface of chemistry and biology together with the realisation that current experimental tools are insufficient to quantitatively understand the molecular logic of pathways inside living cells has triggered renewed interest in the bottom-up development of CRNs. This builds upon earlier work of physical chemists who extensively studied inorganic CRNs and showed how a system of chemical reactions can give rise to complex spatiotemporal responses such as oscillations and pattern formation. Using purified biochemical components, in vitro synthetic biologists have started to engineer simplified model systems with the goal of mimicking biological responses of intracellular circuits. Emulation and reconstruction of system-level properties of intracellular networks using simplified circuits are able to reveal key design principles and molecular programs that underlie the biological function of interest. In this Tutorial Review, we present an accessible overview of this emerging field starting with key studies on inorganic CRNs followed by a discussion of recent work involving purified biochemical components. Finally, we review recent work showing the versatility of programmable biochemical reaction networks (BRNs) in analytical and diagnostic applications.

7th Annual Systems Biology Symposium: Systems Biology and Engineering

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

Galitski, Timothy P.

2008-04-01

Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology has been hosted by the Institute for Systems Biology in Seattle, Washington, since 2002. The annual two-day event gathers the most influential researchers transforming biology into an integrative discipline investingating complex systems. Engineering and application of new technology is a central element of systems biology. Genome-scale, or very small-scale, biological questions drive the enigneering of new technologies, which enable new modes of experimentation and computational analysis, leading to new biological insights and questions. Concepts and analytical methods in engineering aremore » now finding direct applications in biology. Therefore, the 2008 Symposium, funded in partnership with the Department of Energy, featured global leaders in "Systems Biology and Engineering."« less

Development and biological applications of optical tweezers and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Xie, Chang'an

Optical tweezers is a three-dimensional manipulation tool that employs a gradient force that originates from the single highly focused laser beam. Raman spectroscopy is a molecular analytical tool that can give a highly unique "fingerprint" for each substance by measuring the unique vibrations of its molecules. The combination of these two optical techniques offers a new tool for the manipulation and identification of single biological cells and microscopic particles. In this thesis, we designed and implemented a Laser-Tweezers-Raman-Spectroscopy (LTRS) system, also called the Raman-tweezers, for the simultaneous capture and analysis of both biological particles and non-biological particles. We show that microparticles can be conveniently captured at the focus of a laser beam and the Raman spectra of trapped particles can be acquired with high quality. The LTRS system overcomes the intrinsic Brownian motion and cell motility of microparticles in solution and provides a promising tool for in situ identifying suspicious agents. In order to increase the signal to noise ratio, several schemes were employed in LTRS system to reduce the blank noise and the fluorescence signal coming from analytes and the surrounding background. These techniques include near-infrared excitation, optical levitation, confocal microscopy, and frequency-shifted Raman difference. The LTRS system has been applied for the study in cell biology at the single cell level. With the built Raman-tweezers system, we studied the dynamic physiological processes of single living cells, including cell cycle, the transcription and translation of recombinant protein in transgenic yeast cells and the T cell activation. We also studied cell damage and associated biochemical processes in optical traps, UV radiations, and evaluated heating by near-infrared Raman spectroscopy. These studies show that the Raman-tweezers system is feasible to provide rapid and reliable diagnosis of cellular disorders and can be used as a valuable tool to study cellular processes within single living cells or intracellular organelles and may aid research in molecular and cellular biology.

Thermal Quantum Correlations in Photosynthetic Light-Harvesting Complexes

NASA Astrophysics Data System (ADS)

Mahdian, M.; Kouhestani, H.

2015-08-01

Photosynthesis is one of the ancient biological processes, playing crucial role converting solar energy to cellular usable currency. Environmental factors and external perturbations has forced nature to choose systems with the highest efficiency and performance. Recent theoretical and experimental studies have proved the presence of quantum properties in biological systems. Energy transfer systems like Fenna-Matthews-Olson (FMO) complex shows quantum entanglement between sites of Bacteriophylla molecules in protein environment and presence of decoherence. Complex biological systems implement more truthful mechanisms beside chemical-quantum correlations to assure system's efficiency. In this study we investigate thermal quantum correlations in FMO protein of the photosynthetic apparatus of green sulfur bacteria by quantum discord measure. The results confirmed existence of remarkable quantum correlations of of BChla pigments in room temperature. This results approve involvement of quantum correlation mechanisms for information storage and retention in living organisms that could be useful for further evolutionary studies. Inspired idea of this study is potentially interesting to practice by the same procedure in genetic data transfer mechanisms.

Investigating cholesterol metabolism and ageing using a systems biology approach.

PubMed

Morgan, A E; Mooney, K M; Wilkinson, S J; Pickles, N A; Mc Auley, M T

2017-08-01

CVD accounted for 27 % of all deaths in the UK in 2014, and was responsible for 1·7 million hospital admissions in 2013/2014. This condition becomes increasingly prevalent with age, affecting 34·1 and 29·8 % of males and females over 75 years of age respectively in 2011. The dysregulation of cholesterol metabolism with age, often observed as a rise in LDL-cholesterol, has been associated with the pathogenesis of CVD. To compound this problem, it is estimated by 2050, 22 % of the world's population will be over 60 years of age, in culmination with a growing resistance and intolerance to pre-existing cholesterol regulating drugs such as statins. Therefore, it is apparent research into additional therapies for hypercholesterolaemia and CVD prevention is a growing necessity. However, it is also imperative to recognise this complex biological system cannot be studied using a reductionist approach; rather its biological uniqueness necessitates a more integrated methodology, such as that offered by systems biology. In this review, we firstly discuss cholesterol metabolism and how it is affected by diet and the ageing process. Next, we describe therapeutic strategies for hypercholesterolaemia, and finally how the systems biology paradigm can be utilised to investigate how ageing interacts with complex systems such as cholesterol metabolism. We conclude by emphasising the need for nutritionists to work in parallel with the systems biology community, to develop novel approaches to studying cholesterol metabolism and its interaction with ageing.

Nanoscale hybrid systems based on carbon nanotubes for biological sensing and control

PubMed Central

Cho, Youngtak; Shin, Narae; Kim, Daesan; Park, Jae Yeol

2017-01-01

This paper provides a concise review on the recent development of nanoscale hybrid systems based on carbon nanotubes (CNTs) for biological sensing and control. CNT-based hybrid systems have been intensively studied for versatile applications of biological interfaces such as sensing, cell therapy and tissue regeneration. Recent advances in nanobiotechnology not only enable the fabrication of highly sensitive biosensors at nanoscale but also allow the applications in the controls of cell growth and differentiation. This review describes the fabrication methods of such CNT-based hybrid systems and their applications in biosensing and cell controls. PMID:28188158

The developmental genetics of biological robustness

PubMed Central

Mestek Boukhibar, Lamia; Barkoulas, Michalis

2016-01-01

Background Living organisms are continuously confronted with perturbations, such as environmental changes that include fluctuations in temperature and nutrient availability, or genetic changes such as mutations. While some developmental systems are affected by such challenges and display variation in phenotypic traits, others continue consistently to produce invariable phenotypes despite perturbation. This ability of a living system to maintain an invariable phenotype in the face of perturbations is termed developmental robustness. Biological robustness is a phenomenon observed across phyla, and studying its mechanisms is central to deciphering the genotype–phenotype relationship. Recent work in yeast, animals and plants has shown that robustness is genetically controlled and has started to reveal the underlying mechinisms behind it. Scope and Conclusions Studying biological robustness involves focusing on an important property of developmental traits, which is the phenotypic distribution within a population. This is often neglected because the vast majority of developmental biology studies instead focus on population aggregates, such as trait averages. By drawing on findings in animals and yeast, this Viewpoint considers how studies on plant developmental robustness may benefit from strict definitions of what is the developmental system of choice and what is the relevant perturbation, and also from clear distinctions between gene effects on the trait mean and the trait variance. Recent advances in quantitative developmental biology and high-throughput phenotyping now allow the design of targeted genetic screens to identify genes that amplify or restrict developmental trait variance and to study how variation propagates across different phenotypic levels in biological systems. The molecular characterization of more quantitative trait loci affecting trait variance will provide further insights into the evolution of genes modulating developmental robustness. The study of robustness mechanisms in closely related species will address whether mechanisms of robustness are evolutionarily conserved. PMID:26292993

A Biochemistry and Molecular Biology Experiment and Evaluation System for Biotechnology Specialty Students: An Effective Evaluation System to Improve the Biochemistry and Molecular Biology Experiment Teaching

ERIC Educational Resources Information Center

Li, Suxia; Wu, Haizhen; Zhao, Jian; Ou, Ling; Zhang, Yuanxing

2010-01-01

In an effort to achieve high success in knowledge and technique acquisition as a whole, a biochemistry and molecular biology experiment was established for high-grade biotechnology specialty students after they had studied essential theory and received proper technique training. The experiment was based on cloning and expression of alkaline…

The Effect of Knowledge Linking Levels in Biology Lessons upon Students' Knowledge Structure

ERIC Educational Resources Information Center

Wadouh, Julia; Liu, Ning; Sandmann, Angela; Neuhaus, Birgit J.

2014-01-01

Knowledge structure is an important aspect for defining students' competency in biology learning, but how knowledge structure is influenced by the teaching process in naturalistic biology classroom settings has scarcely been empirically investigated. In this study, 49 biology lessons in the teaching unit "blood and circulatory system" in…

Invited review: gravitational biology of the neuromotor systems: a perspective to the next era

NASA Technical Reports Server (NTRS)

Edgerton, V. R.; Roy, R. R.

2000-01-01

Earth's gravity has had a significant impact on the designs of the neuromotor systems that have evolved. Early indications are that gravity also plays a key role in the ontogenesis of some of these design features. The purpose of the present review is not to assess and interpret a body of knowledge in the usual sense of a review but to look ahead, given some of the general concepts that have evolved and observations made to date, which can guide our future approach to gravitational biology. We are now approaching an era in gravitational biology during which well-controlled experiments can be conducted for sustained periods in a microgravity environment. Thus it is now possible to study in greater detail the role of gravity in phylogenesis and ontogenesis. Experiments can range from those conducted on the simplest levels of organization of the components that comprise the neuromotor system to those conducted on the whole organism. Generally, the impact of Earth's gravitational environment on living systems becomes more complex as the level of integration of the biological phenomenon of interest increases. Studies of the effects of gravitational vectors on neuromotor systems have and should continue to provide unique insight into these mechanisms that control and maintain neural control systems designed to function in Earth's gravitational environment. A number of examples are given of how a gravitational biology perspective can lead to a clearer understanding of neuromotor disorders. Furthermore, the technologies developed for spaceflight studies have contributed and should continue to contribute to studies of motor dysfunctions, such as spinal cord injury and stroke. Disorders associated with energy support and delivery systems and how these functions are altered by sedentary life styles at 1 G and by space travel in a microgravity environment are also discussed.

Biological stress systems, adverse life events and the onset of chronic multisite musculoskeletal pain: a 6-year cohort study.

PubMed

Generaal, Ellen; Vogelzangs, Nicole; Macfarlane, Gary J; Geenen, Rinie; Smit, Johannes H; de Geus, Eco J C N; Penninx, Brenda W J H; Dekker, Joost

2016-05-01

Dysregulated biological stress systems and adverse life events, independently and in interaction, have been hypothesised to initiate chronic pain. We examine whether (1) function of biological stress systems, (2) adverse life events, and (3) their combination predict the onset of chronic multisite musculoskeletal pain. Subjects (n=2039) of the Netherlands Study of Depression and Anxiety, free from chronic multisite musculoskeletal pain at baseline, were identified using the Chronic Pain Grade Questionnaire and followed up for the onset of chronic multisite musculoskeletal pain over 6 years. Baseline assessment of biological stress systems comprised function of the hypothalamic-pituitary-adrenal axis (1-h cortisol awakening response, evening levels, postdexamethasone levels), the immune system (basal and lipopolysaccharide-stimulated inflammation) and the autonomic nervous system (heart rate, pre-ejection period, SD of the normal-to-normal interval, respiratory sinus arrhythmia). The number of recent adverse life events was assessed at baseline using the List of Threatening Events Questionnaire. Hypothalamic-pituitary-adrenal axis, immune system and autonomic nervous system functioning was not associated with onset of chronic multisite musculoskeletal pain, either by itself or in interaction with adverse life events. Adverse life events did predict onset of chronic multisite musculoskeletal pain (HR per event=1.14, 95% CI 1.04 to 1.24, p=0.005). This longitudinal study could not confirm that dysregulated biological stress systems increase the risk of developing chronic multisite musculoskeletal pain. Adverse life events were a risk factor for the onset of chronic multisite musculoskeletal pain, suggesting that psychosocial factors play a role in triggering the development of this condition. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Calculating life? Duelling discourses in interdisciplinary systems biology.

PubMed

Calvert, Jane; Fujimura, Joan H

2011-06-01

A high profile context in which physics and biology meet today is in the new field of systems biology. Systems biology is a fascinating subject for sociological investigation because the demands of interdisciplinary collaboration have brought epistemological issues and debates front and centre in discussions amongst systems biologists in conference settings, in publications, and in laboratory coffee rooms. One could argue that systems biologists are conducting their own philosophy of science. This paper explores the epistemic aspirations of the field by drawing on interviews with scientists working in systems biology, attendance at systems biology conferences and workshops, and visits to systems biology laboratories. It examines the discourses of systems biologists, looking at how they position their work in relation to previous types of biological inquiry, particularly molecular biology. For example, they raise the issue of reductionism to distinguish systems biology from molecular biology. This comparison with molecular biology leads to discussions about the goals and aspirations of systems biology, including epistemic commitments to quantification, rigor and predictability. Some systems biologists aspire to make biology more similar to physics and engineering by making living systems calculable, modelable and ultimately predictable-a research programme that is perhaps taken to its most extreme form in systems biology's sister discipline: synthetic biology. Other systems biologists, however, do not think that the standards of the physical sciences are the standards by which we should measure the achievements of systems biology, and doubt whether such standards will ever be applicable to 'dirty, unruly living systems'. This paper explores these epistemic tensions and reflects on their sociological dimensions and their consequences for future work in the life sciences. Copyright © 2010 Elsevier Ltd. All rights reserved.

Back to the biology in systems biology: what can we learn from biomolecular networks?

PubMed

Huang, Sui

2004-02-01

Genome-scale molecular networks, including protein interaction and gene regulatory networks, have taken centre stage in the investigation of the burgeoning disciplines of systems biology and biocomplexity. What do networks tell us? Some see in networks simply the comprehensive, detailed description of all cellular pathways, others seek in networks simple, higher-order qualities that emerge from the collective action of the individual pathways. This paper discusses networks from an encompassing category of thinking that will hopefully help readers to bridge the gap between these polarised viewpoints. Systems biology so far has emphasised the characterisation of large pathway maps. Now one has to ask: where is the actual biology in 'systems biology'? As structures midway between genome and phenome, and by serving as an 'extended genotype' or an 'elementary phenotype', molecular networks open a new window to the study of evolution and gene function in complex living systems. For the study of evolution, features in network topology offer a novel starting point for addressing the old debate on the relative contributions of natural selection versus intrinsic constraints to a particular trait. To study the function of genes, it is necessary not only to see them in the context of gene networks, but also to reach beyond describing network topology and to embrace the global dynamics of networks that will reveal higher-order, collective behaviour of the interacting genes. This will pave the way to understanding how the complexity of genome-wide molecular networks collapses to produce a robust whole-cell behaviour that manifests as tightly-regulated switching between distinct cell fates - the basis for multicellular life.

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

PubMed Central

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

2012-01-01

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

What have humans done for evolutionary biology? Contributions from genes to populations.

PubMed

Briga, Michael; Griffin, Robert M; Berger, Vérane; Pettay, Jenni E; Lummaa, Virpi

2017-11-15

Many fundamental concepts in evolutionary biology were discovered using non-human study systems. Humans are poorly suited to key study designs used to advance this field, and are subject to cultural, technological, and medical influences often considered to restrict the pertinence of human studies to other species and general contexts. Whether studies using current and recent human populations provide insights that have broader biological relevance in evolutionary biology is, therefore, frequently questioned. We first surveyed researchers in evolutionary biology and related fields on their opinions regarding whether studies on contemporary humans can advance evolutionary biology. Almost all 442 participants agreed that humans still evolve, but fewer agreed that this occurs through natural selection. Most agreed that human studies made valuable contributions to evolutionary biology, although those less exposed to human studies expressed more negative views. With a series of examples, we discuss strengths and limitations of evolutionary studies on contemporary humans. These show that human studies provide fundamental insights into evolutionary processes, improve understanding of the biology of many other species, and will make valuable contributions to evolutionary biology in the future. © 2017 The Author(s).

What have humans done for evolutionary biology? Contributions from genes to populations

PubMed Central

Briga, Michael; Griffin, Robert M.; Berger, Vérane; Pettay, Jenni E.

2017-01-01

Many fundamental concepts in evolutionary biology were discovered using non-human study systems. Humans are poorly suited to key study designs used to advance this field, and are subject to cultural, technological, and medical influences often considered to restrict the pertinence of human studies to other species and general contexts. Whether studies using current and recent human populations provide insights that have broader biological relevance in evolutionary biology is, therefore, frequently questioned. We first surveyed researchers in evolutionary biology and related fields on their opinions regarding whether studies on contemporary humans can advance evolutionary biology. Almost all 442 participants agreed that humans still evolve, but fewer agreed that this occurs through natural selection. Most agreed that human studies made valuable contributions to evolutionary biology, although those less exposed to human studies expressed more negative views. With a series of examples, we discuss strengths and limitations of evolutionary studies on contemporary humans. These show that human studies provide fundamental insights into evolutionary processes, improve understanding of the biology of many other species, and will make valuable contributions to evolutionary biology in the future. PMID:29118130

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

ERIC Educational Resources Information Center

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

2012-01-01

The dominance behavioral system (DBS) can be conceptualized as a biologically based system that guides dominance motivation, dominant and subordinate behavior, and responsivity to perceptions of power and subordination. A growing body of research suggests that problems with the DBS are evident across a broad range of psychopathologies. We begin by…

CONCEPTUAL FRAMEWORK FOR THE CHEMICAL EFFECTS IN BIOLOGICAL SYSTEMS (CEBS) TOXICOGENOMICS KNOWLEDGE BASE

EPA Science Inventory

Conceptual Framework for the Chemical Effects in Biological Systems (CEBS) T oxicogenomics Knowledge Base

Abstract
Toxicogenomics studies how the genome is involved in responses to environmental stressors or toxicants. It combines genetics, genome-scale mRNA expressio...

Biocellion: accelerating computer simulation of multicellular biological system models

PubMed Central

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-01-01

Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572

Circadian systems biology in Metazoa.

PubMed

Lin, Li-Ling; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2015-11-01

Systems biology, which can be defined as integrative biology, comprises multistage processes that can be used to understand components of complex biological systems of living organisms and provides hierarchical information to decoding life. Using systems biology approaches such as genomics, transcriptomics and proteomics, it is now possible to delineate more complicated interactions between circadian control systems and diseases. The circadian rhythm is a multiscale phenomenon existing within the body that influences numerous physiological activities such as changes in gene expression, protein turnover, metabolism and human behavior. In this review, we describe the relationships between the circadian control system and its related genes or proteins, and circadian rhythm disorders in systems biology studies. To maintain and modulate circadian oscillation, cells possess elaborative feedback loops composed of circadian core proteins that regulate the expression of other genes through their transcriptional activities. The disruption of these rhythms has been reported to be associated with diseases such as arrhythmia, obesity, insulin resistance, carcinogenesis and disruptions in natural oscillations in the control of cell growth. This review demonstrates that lifestyle is considered as a fundamental factor that modifies circadian rhythm, and the development of dysfunctions and diseases could be regulated by an underlying expression network with multiple circadian-associated signals. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Biology Curriculum Reform in Venezuela.

ERIC Educational Resources Information Center

Rondon, Leonor Mariasole

2001-01-01

Describes science in the Venezuelan school system which reflects on the process of development followed to design and validate the Biology Study Programs (BSP) with the emphasis on the relevance of curricular changes proposed in biological science for secondary education. (Contains 19 references.) (ASK)

Big data mining powers fungal research: recent advances in fission yeast systems biology approaches.

PubMed

Wang, Zhe

2017-06-01

Biology research has entered into big data era. Systems biology approaches therefore become the powerful tools to obtain the whole landscape of how cell separate, grow, and resist the stresses. Fission yeast Schizosaccharomyces pombe is wonderful unicellular eukaryote model, especially studying its division and metabolism can facilitate to understanding the molecular mechanism of cancer and discovering anticancer agents. In this perspective, we discuss the recent advanced fission yeast systems biology tools, mainly focus on metabolomics profiling and metabolic modeling, protein-protein interactome and genetic interaction network, DNA sequencing and applications, and high-throughput phenotypic screening. We therefore hope this review can be useful for interested fungal researchers as well as bioformaticians.

Systems biology for understanding and engineering of heterotrophic oleaginous microorganisms.

PubMed

Park, Beom Gi; Kim, Minsuk; Kim, Joonwon; Yoo, Heewang; Kim, Byung-Gee

2017-01-01

Heterotrophic oleaginous microorganisms continue to draw interest as they can accumulate a large amount of lipids which is a promising feedstock for the production of biofuels and oleochemicals. Nutrient limitation, especially nitrogen limitation, is known to effectively trigger the lipid production in these microorganisms. For the aim of developing improved strains, the mechanisms behind the lipid production have been studied for a long time. Nowadays, system-level understanding of their metabolism and associated metabolic switches is attainable with modern systems biology tools. This work reviews the systems biology studies, based on (i) top-down, large-scale 'omics' tools, and (ii) bottom-up, mathematical modeling methods, on the heterotrophic oleaginous microorganisms with an emphasis on further application to metabolic engineering. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Membrane-bound cytokine and feedforward regulation].

PubMed

Wu, Ke-Fu; Zheng, Guo-Guang; Ma, Xiao-Tong; Song, Yu-Hua

2013-10-01

Feedback and feedforward widely exist in life system, both of them are the basic processes of control system. While the concept of feedback has been widely used in life science, feedforward regulation was systematically studied in neurophysiology, awaiting further evidence and mechanism in molecular biology and cell biology. The authors put forward a hypothesis about the feedforward regulation of membrane bound macrophage colony stimulation factor (mM-CSF) on the basis of their previous work. This hypothesis might provide a new direction for the study on the biological effects of mM-CSF on leukemia and solid tumors, and contribute to the study on other membrane bound cytokines.

Nestedness across biological scales

PubMed Central

Marquitti, Flavia M. D.; Raimundo, Rafael L. G.; Sebastián-González, Esther; Coltri, Patricia P.; Perez, S. Ivan; Brandt, Débora Y. C.; Nunes, Kelly; Daura-Jorge, Fábio G.; Floeter, Sergio R.; Guimarães, Paulo R.

2017-01-01

Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general compromise between two features: specificity (the number of interactions the elements of the system can have) and affinity (how these elements can be connected to each other). Our findings suggesting occurrence of nestedness throughout biological scales can stimulate the debate on how pervasive nestedness may be in nature, while the theoretical emergent principles can aid further research on commonalities of biological networks. PMID:28166284

Modeling for Visual Feature Extraction Using Spiking Neural Networks

NASA Astrophysics Data System (ADS)

Kimura, Ichiro; Kuroe, Yasuaki; Kotera, Hiromichi; Murata, Tomoya

This paper develops models for “visual feature extraction” in biological systems by using “spiking neural network (SNN)”. The SNN is promising for developing the models because the information is encoded and processed by spike trains similar to biological neural networks. Two architectures of SNN are proposed for modeling the directionally selective and the motion parallax cell in neuro-sensory systems and they are trained so as to possess actual biological responses of each cell. To validate the developed models, their representation ability is investigated and their visual feature extraction mechanisms are discussed from the neurophysiological viewpoint. It is expected that this study can be the first step to developing a sensor system similar to the biological systems and also a complementary approach to investigating the function of the brain.

Genome Scale Modeling in Systems Biology: Algorithms and Resources

PubMed Central

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

2014-01-01

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

Systems Biology-an interdisciplinary approach.

PubMed

Friboulet, Alain; Thomas, Daniel

2005-06-15

System-level approaches in biology are not new but foundations of "Systems Biology" are achieved only now at the beginning of the 21st century [Kitano, H., 2001. Foundations of Systems Biology. MIT Press, Cambridge, MA]. The renewed interest for a system-level approach is linked to the progress in collecting experimental data and to the limits of the "reductionist" approach. System-level understanding of native biological and pathological systems is needed to provide potential therapeutic targets. Examples of interdisciplinary approach in Systems Biology are described in U.S., Japan and Europe. Robustness in biology, metabolic engineering and idiotypic networks are discussed in the framework of Systems Biology.

High performance computing in biology: multimillion atom simulations of nanoscale systems

PubMed Central

Sanbonmatsu, K. Y.; Tung, C.-S.

2007-01-01

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nanoscale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail. PMID:17187988

Biomarkers for Uranium Risk Assessment for the Development of the CURE (Concerted Uranium Research in Europe) Molecular Epidemiological Protocol.

PubMed

Guéguen, Yann; Roy, Laurence; Hornhardt, Sabine; Badie, Christophe; Hall, Janet; Baatout, Sarah; Pernot, Eileen; Tomasek, Ladislav; Laurent, Olivier; Ebrahimian, Teni; Ibanez, Chrystelle; Grison, Stephane; Kabacik, Sylwia; Laurier, Dominique; Gomolka, Maria

2017-01-01

Despite substantial experimental and epidemiological research, there is limited knowledge of the uranium-induce health effects after chronic low-dose exposures in humans. Biological markers can objectively characterize pathological processes or environmental responses to uranium and confounding agents. The integration of such biological markers into a molecular epidemiological study would be a useful approach to improve and refine estimations of uranium-induced health risks. To initiate such a study, Concerted Uranium Research in Europe (CURE) was established, and involves biologists, epidemiologists and dosimetrists. The aims of the biological work package of CURE were: 1. To identify biomarkers and biological specimens relevant to uranium exposure; 2. To define standard operating procedures (SOPs); and 3. To set up a common protocol (logistic, questionnaire, ethical aspects) to perform a large-scale molecular epidemiologic study in uranium-exposed cohorts. An intensive literature review was performed and led to the identification of biomarkers related to: 1. retention organs (lungs, kidneys and bone); 2. other systems/organs with suspected effects (cardiovascular system, central nervous system and lympho-hematopoietic system); 3. target molecules (DNA damage, genomic instability); and 4. high-throughput methods for the identification of new biomarkers. To obtain high-quality biological materials, SOPs were established for the sampling and storage of different biospecimens. A questionnaire was developed to assess potential confounding factors. The proposed strategy can be adapted to other internal exposures and should improve the characterization of the biological and health effects that are relevant for risk assessment.

Utilizing population variation, vaccination, and systems biology to study human immunology

PubMed Central

Tsang, John S.

2016-01-01

The move toward precision medicine has highlighted the importance of understanding biological variability within and across individuals in the human population. In particular, given the prevalent involvement of the immune system in diverse pathologies, an important question is how much and what information about the state of the immune system is required to enable accurate prediction of future health and response to medical interventions. Towards addressing this question, recent studies using vaccination as a model perturbation and systems-biology approaches are beginning to provide a glimpse of how natural population variation together with multiplexed, high-throughput measurement and computational analysis can be used to uncover predictors of immune response quality in humans. Here I discuss recent developments in this emerging field, with emphasis on baseline correlates of vaccination responses, sources of immune-state variability, as well as relevant features of study design, data generation, and computational analysis. PMID:26187853

Hemojuvelin-hepcidin axis modeled and analyzed using Petri nets.

PubMed

Formanowicz, Dorota; Kozak, Adam; Głowacki, Tomasz; Radom, Marcin; Formanowicz, Piotr

2013-12-01

Systems biology approach to investigate biological phenomena seems to be very promising because it is capable to capture one of the fundamental properties of living organisms, i.e. their inherent complexity. It allows for analysis biological entities as complex systems of interacting objects. The first and necessary step of such an analysis is building a precise model of the studied biological system. This model is expressed in the language of some branch of mathematics, as for example, differential equations. During the last two decades the theory of Petri nets has appeared to be very well suited for building models of biological systems. The structure of these nets reflects the structure of interacting biological molecules and processes. Moreover, on one hand, Petri nets have intuitive graphical representation being very helpful in understanding the structure of the system and on the other hand, there is a lot of mathematical methods and software tools supporting an analysis of the properties of the nets. In this paper a Petri net based model of the hemojuvelin-hepcidin axis involved in the maintenance of the human body iron homeostasis is presented. The analysis based mainly on T-invariants of the model properties has been made and some biological conclusions have been drawn. Copyright © 2013 Elsevier Inc. All rights reserved.

Modelling biological behaviours with the unified modelling language: an immunological case study and critique.

PubMed

Read, Mark; Andrews, Paul S; Timmis, Jon; Kumar, Vipin

2014-10-06

We present a framework to assist the diagrammatic modelling of complex biological systems using the unified modelling language (UML). The framework comprises three levels of modelling, ranging in scope from the dynamics of individual model entities to system-level emergent properties. By way of an immunological case study of the mouse disease experimental autoimmune encephalomyelitis, we show how the framework can be used to produce models that capture and communicate the biological system, detailing how biological entities, interactions and behaviours lead to higher-level emergent properties observed in the real world. We demonstrate how the UML can be successfully applied within our framework, and provide a critique of UML's ability to capture concepts fundamental to immunology and biology more generally. We show how specialized, well-explained diagrams with less formal semantics can be used where no suitable UML formalism exists. We highlight UML's lack of expressive ability concerning cyclic feedbacks in cellular networks, and the compounding concurrency arising from huge numbers of stochastic, interacting agents. To compensate for this, we propose several additional relationships for expressing these concepts in UML's activity diagram. We also demonstrate the ambiguous nature of class diagrams when applied to complex biology, and question their utility in modelling such dynamic systems. Models created through our framework are non-executable, and expressly free of simulation implementation concerns. They are a valuable complement and precursor to simulation specifications and implementations, focusing purely on thoroughly exploring the biology, recording hypotheses and assumptions, and serve as a communication medium detailing exactly how a simulation relates to the real biology.

Modelling biological behaviours with the unified modelling language: an immunological case study and critique

PubMed Central

Read, Mark; Andrews, Paul S.; Timmis, Jon; Kumar, Vipin

2014-01-01

We present a framework to assist the diagrammatic modelling of complex biological systems using the unified modelling language (UML). The framework comprises three levels of modelling, ranging in scope from the dynamics of individual model entities to system-level emergent properties. By way of an immunological case study of the mouse disease experimental autoimmune encephalomyelitis, we show how the framework can be used to produce models that capture and communicate the biological system, detailing how biological entities, interactions and behaviours lead to higher-level emergent properties observed in the real world. We demonstrate how the UML can be successfully applied within our framework, and provide a critique of UML's ability to capture concepts fundamental to immunology and biology more generally. We show how specialized, well-explained diagrams with less formal semantics can be used where no suitable UML formalism exists. We highlight UML's lack of expressive ability concerning cyclic feedbacks in cellular networks, and the compounding concurrency arising from huge numbers of stochastic, interacting agents. To compensate for this, we propose several additional relationships for expressing these concepts in UML's activity diagram. We also demonstrate the ambiguous nature of class diagrams when applied to complex biology, and question their utility in modelling such dynamic systems. Models created through our framework are non-executable, and expressly free of simulation implementation concerns. They are a valuable complement and precursor to simulation specifications and implementations, focusing purely on thoroughly exploring the biology, recording hypotheses and assumptions, and serve as a communication medium detailing exactly how a simulation relates to the real biology. PMID:25142524

Systems biology approaches to understand the effects of nutrition and promote health.

PubMed

Badimon, Lina; Vilahur, Gemma; Padro, Teresa

2017-01-01

Within the last years the implementation of systems biology in nutritional research has emerged as a powerful tool to understand the mechanisms by which dietary components promote health and prevent disease as well as to identify the biologically active molecules involved in such effects. Systems biology, by combining several '-omics' disciplines (mainly genomics/transcriptomics, proteomics and metabolomics), creates large data sets that upon computational integration provide in silico predictive networks that allow a more extensive analysis of the individual response to a nutritional intervention and provide a more global comprehensive understanding of how diet may influence health and disease. Numerous studies have demonstrated that diet and particularly bioactive food components play a pivotal role in helping to counteract environmental-related oxidative damage. Oxidative stress is considered to be strongly implicated in ageing and the pathophysiology of numerous diseases including neurodegenerative disease, cancers, metabolic disorders and cardiovascular diseases. In the following review we will provide insights into the role of systems biology in nutritional research and focus on transcriptomic, proteomic and metabolomics studies that have demonstrated the ability of functional foods and their bioactive components to fight against oxidative damage and contribute to health benefits. © 2016 The British Pharmacological Society.

Translational Systems Biology and Voice Pathophysiology

PubMed Central

Li, Nicole Y. K.; Abbott, Katherine Verdolini; Rosen, Clark; An, Gary; Hebda, Patricia A.; Vodovotz, Yoram

2011-01-01

Objectives/Hypothesis Personalized medicine has been called upon to tailor healthcare to an individual's needs. Evidence-based medicine (EBM) has advocated using randomized clinical trials with large populations to evaluate treatment effects. However, due to large variations across patients, the results are likely not to apply to an individual patient. We suggest that a complementary, systems biology approach using computational modeling may help tackle biological complexity in order to improve ultimate patient care. The purpose of the article is: 1) to review the pros and cons of EBM, and 2) to discuss the alternative systems biology method and present its utility in clinical voice research. Study Design Tutorial Methods Literature review and discussion. Results We propose that translational systems biology can address many of the limitations of EBM pertinent to voice and other health care domains, and thus complement current health research models. In particular, recent work using mathematical modeling suggests that systems biology has the ability to quantify the highly complex biologic processes underlying voice pathophysiology. Recent data support the premise that this approach can be applied specifically in the case of phonotrauma and surgically induced vocal fold trauma, and may have particular power to address personalized medicine. Conclusions We propose that evidence around vocal health and disease be expanded beyond a population-based method to consider more fully issues of complexity and systems interactions, especially in implementing personalized medicine in voice care and beyond. PMID:20025041

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

PubMed

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

2014-01-15

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

The evolution of early cellular systems viewed through the lens of biological interactions.

PubMed

Poole, Anthony M; Lundin, Daniel; Rytkönen, Kalle T

2015-01-01

The minimal cell concept represents a pragmatic approach to the question of how few genes are required to run a cell. This is a helpful way to build a parts-list, and has been more successful than attempts to deduce a minimal gene set for life by inferring the gene repertoire of the last universal common ancestor, as few genes trace back to this hypothetical ancestral state. However, the study of minimal cellular systems is the study of biological outliers where, by practical necessity, coevolutionary interactions are minimized or ignored. In this paper, we consider the biological context from which minimal genomes have been removed. For instance, some of the most reduced genomes are from endosymbionts and are the result of coevolutionary interactions with a host; few such organisms are "free-living." As few, if any, biological systems exist in complete isolation, we expect that, as with modern life, early biological systems were part of an ecosystem, replete with organismal interactions. We favor refocusing discussions of the evolution of cellular systems on processes rather than gene counts. We therefore draw a distinction between a pragmatic minimal cell (an interesting engineering problem), a distributed genome (a system resulting from an evolutionary transition involving more than one cell) and the looser coevolutionary interactions that are ubiquitous in ecosystems. Finally, we consider the distributed genome and coevolutionary interactions between genomic entities in the context of early evolution.

Thiol/disulfide redox states in signaling and sensing

PubMed Central

Go, Young-Mi; Jones, Dean P.

2015-01-01

Rapid advances in redox systems biology are creating new opportunities to understand complexities of human disease and contributions of environmental exposures. New understanding of thiol-disulfide systems have occurred during the past decade as a consequence of the discoveries that thiol and disulfide systems are maintained in kinetically controlled steady-states displaced from thermodynamic equilibrium, that a widely distributed family of NADPH oxidases produces oxidants that function in cell signaling, and that a family of peroxiredoxins utilize thioredoxin as a reductant to complement the well-studied glutathione antioxidant system for peroxide elimination and redox regulation. This review focuses on thiol/disulfide redox state in biologic systems and the knowledge base available to support development of integrated redox systems biology models to better understand the function and dysfunction of thiol-disulfide redox systems. In particular, central principles have emerged concerning redox compartmentalization and utility of thiol/disulfide redox measures as indicators of physiologic function. Advances in redox proteomics show that, in addition to functioning in protein active sites and cell signaling, cysteine residues also serve as redox sensors to integrate biologic functions. These advances provide a framework for translation of redox systems biology concepts to practical use in understanding and treating human disease. Biological responses to cadmium, a widespread environmental agent, are used to illustrate the utility of these advances to the understanding of complex pleiotropic toxicities. PMID:23356510

Behavior of nanoceria in biologically-relevant environments

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

Kumar, Amit; Das, Soumen; Munusamy, Prabhakaran

2014-09-08

Cerium oxide nanoparticles (CNPs) have gained a considerable attention in biological research due to their anti-oxidant like behaviour and regenerative nature. The current literature on CNPs reports many successful attempts on harnessing the beneficial therapeutic properties in biology. However studies have also shown toxicity effect with some types of CNPs. This review discusses issues associated with the behaviours of CNPs in biological systems and identifies key knowledge gaps. We explore how salient physicochemical properties (size, surface chemistry, surface stabilizers) contribute to the potential positive and negative aspects of nanoceria in biological systems. Based on variations of results reported in themore » literature, important issues need to be addressed. Are we really studying the same particles with slight variations in size and physicochemical properties or do the particles being examined have fundamentally different behaviours? Are the variations observed in the result of differences in the initial properties of the particles or the results of downstream effects that emerge as the particles are prepared for specific studies and they interact with biological or other environmental moieties? How should particles be appropriately prepared for relevant environmental/toxicology/safety studies? It is useful to recognize that nanoparticles encompass some of the same complexities and variability associated with biological components« less

Quality of life, treatment satisfaction and efficacy of non-biological systemic therapies in patients with plaque psoriasis: study protocol for a prospective observational study.

PubMed

Fink, Christine; Schank, Timo E; Trenkler, Nina; Uhlmann, Lorenz; Schäkel, Knut

2017-06-30

Psoriasis vulgaris often leads to a significant impaired quality of life and dissatisfaction with the existing therapeutic approaches. However, patients' quality of life and treatment satisfaction are of utmost importance, since it is positively related to therapy adherence and encourages patient's compliance. The study described herein evaluates the quality of life, treatment satisfaction and efficacy during the initial 6 months of treatment with a non-biological systemic agent in a real-life clinical setting. This observational study compares quality of life, treatment satisfaction and the efficacy of non-biological systemic therapy between 60 patients suffering from plaque psoriasis receiving the non-biological systemic therapies with apremilast, methotrexate and fumaric acid esters. Ethics approval was provided by the ethics committee of the medical faculty of the University of Heidelberg. Ethics approval number is S-298/2015. The design and the final results of the study will be published and made available to the public. German Clinical Trial Register (DRKS): DRKS00008721 (https://www.germanctr.de/). © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Global analysis of an impulsive delayed Lotka-Volterra competition system

NASA Astrophysics Data System (ADS)

Xia, Yonghui

2011-03-01

In this paper, a retarded impulsive n-species Lotka-Volterra competition system with feedback controls is studied. Some sufficient conditions are obtained to guarantee the global exponential stability and global asymptotic stability of a unique equilibrium for such a high-dimensional biological system. The problem considered in this paper is in many aspects more general and incorporates as special cases various problems which have been extensively studied in the literature. Moreover, applying the obtained results to some special cases, I derive some new criteria which generalize and greatly improve some well known results. A method is proposed to investigate biological systems subjected to the effect of both impulses and delays. The method is based on Banach fixed point theory and matrix's spectral theory as well as Lyapunov function. Moreover, some novel analytic techniques are employed to study GAS and GES. It is believed that the method can be extended to other high-dimensional biological systems and complex neural networks. Finally, two examples show the feasibility of the results.

Control of biological growth in recirculating cooling systems using treated secondary effluent as makeup water with monochloramine.

PubMed

Chien, Shih-Hsiang; Chowdhury, Indranil; Hsieh, Ming-Kai; Li, Heng; Dzombak, David A; Vidic, Radisav D

2012-12-01

Secondary-treated municipal wastewater, an abundant and widely distributed impaired water source, is a promising alternative water source for thermoelectric power plant cooling. However, excessive biological growth is a major challenge associated with wastewater reuse in cooling systems as it can interfere with normal system operation as well as enhance corrosion and scaling problems. Furthermore, possible emission of biological aerosols (e.g., Legionella pneumophila) with the cooling tower drift can lead to public health concerns within the zone of aerosol deposition. In this study, the effectiveness of pre-formed and in-situ-formed monochloramine was evaluated for its ability to control biological growth in recirculating cooling systems using secondary-treated municipal wastewater as the only makeup water source. Bench-scale studies were compared with pilot-scale studies for their ability to predict system behavior under realistic process conditions. Effectiveness of the continuous addition of pre-formed monochloramine and monochloramine formed in-situ through the reaction of free chlorine with ammonia in the incoming water was evaluated in terms of biocide residual and its ability to control both planktonic and sessile microbial populations. Results revealed that monochloramine can effectively control biofouling in cooling systems employing secondary-treated municipal wastewater and has advantages relative to use of free chlorine, but that bench-scale studies seriously underestimate biocide dose and residual requirements for proper control of biological growth in full-scale systems. Pre-formed monochloramine offered longer residence time and more reliable performance than in-situ-formed monochloramine due to highly variable ammonia concentration in the recirculating water caused by ammonia stripping in the cooling tower. Pilot-scale tests revealed that much lower dosing rate was required to maintain similar total chlorine residual when pre-formed monochloramine was used as compared to in-situ-formed monochloramine. Adjustment of biocide dose to maintain monochloramine residual above 3mg/L is needed to achieve successful biological growth control in recirculating cooling systems using secondary-treated municipal effluent as the only source of makeup water. Copyright © 2012 Elsevier Ltd. All rights reserved.

Characterising the development of the understanding of human body systems in high-school biology students - a longitudinal study

NASA Astrophysics Data System (ADS)

Snapir, Zohar; Eberbach, Catherine; Ben-Zvi-Assaraf, Orit; Hmelo-Silver, Cindy; Tripto, Jaklin

2017-10-01

Science education today has become increasingly focused on research into complex natural, social and technological systems. In this study, we examined the development of high-school biology students' systems understanding of the human body, in a three-year longitudinal study. The development of the students' system understanding was evaluated using the Components Mechanisms Phenomena (CMP) framework for conceptual representation. We coded and analysed the repertory grid personal constructs of 67 high-school biology students at 4 points throughout the study. Our data analysis builds on the assumption that systems understanding entails a perception of all the system categories, including structures within the system (its Components), specific processes and interactions at the macro and micro levels (Mechanisms), and the Phenomena that present the macro scale of processes and patterns within a system. Our findings suggest that as the learning process progressed, the systems understanding of our students became more advanced, moving forward within each of the major CMP categories. Moreover, there was an increase in the mechanism complexity presented by the students, manifested by more students describing mechanisms at the molecular level. Thus, the 'mechanism' category and the micro level are critical components that enable students to understand system-level phenomena such as homeostasis.

Systems biology of meridians, acupoints, and chinese herbs in disease.

PubMed

Lin, Li-Ling; Wang, Ya-Hui; Lai, Chi-Yu; Chau, Chan-Lao; Su, Guan-Chin; Yang, Chun-Yi; Lou, Shu-Ying; Chen, Szu-Kai; Hsu, Kuan-Hao; Lai, Yen-Ling; Wu, Wei-Ming; Huang, Jian-Long; Liao, Chih-Hsin; Juan, Hsueh-Fen

2012-01-01

Meridians, acupoints, and Chinese herbs are important components of traditional Chinese medicine (TCM). They have been used for disease treatment and prevention and as alternative and complementary therapies. Systems biology integrates omics data, such as transcriptional, proteomic, and metabolomics data, in order to obtain a more global and complete picture of biological activity. To further understand the existence and functions of the three components above, we reviewed relevant research in the systems biology literature and found many recent studies that indicate the value of acupuncture and Chinese herbs. Acupuncture is useful in pain moderation and relieves various symptoms arising from acute spinal cord injury and acute ischemic stroke. Moreover, Chinese herbal extracts have been linked to wound repair, the alleviation of postmenopausal osteoporosis severity, and anti-tumor effects, among others. Different acupoints, variations in treatment duration, and herbal extracts can be used to alleviate various symptoms and conditions and to regulate biological pathways by altering gene and protein expression. Our paper demonstrates how systems biology has helped to establish a platform for investigating the efficacy of TCM in treating different diseases and improving treatment strategies.

Functional Genomics Assistant (FUGA): a toolbox for the analysis of complex biological networks

PubMed Central

2011-01-01

Background Cellular constituents such as proteins, DNA, and RNA form a complex web of interactions that regulate biochemical homeostasis and determine the dynamic cellular response to external stimuli. It follows that detailed understanding of these patterns is critical for the assessment of fundamental processes in cell biology and pathology. Representation and analysis of cellular constituents through network principles is a promising and popular analytical avenue towards a deeper understanding of molecular mechanisms in a system-wide context. Findings We present Functional Genomics Assistant (FUGA) - an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology. Conclusion FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at http://code.google.com/p/fuga. PMID:22035155

Graphics processing units in bioinformatics, computational biology and systems biology.

PubMed

Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

2017-09-01

Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

Simulation of physiological systems in order to evaluate and predict the human condition in a space flight

NASA Technical Reports Server (NTRS)

Verigo, V. V.

1979-01-01

Simulation models were used to study theoretical problems of space biology and medicine. The reaction and adaptation of the main physiological systems to the complex effects of space flight were investigated. Mathematical models were discussed in terms of their significance in the selection of the structure and design of biological life support systems.

A Systems Biology Approach to Iron Metabolism

PubMed Central

Chifman, J.; Laubenbacher, R.; Torti, S.V.

2015-01-01

Iron is critical to the survival of almost all living organisms. However, inappropriately low or high levels of iron are detrimental and contribute to a wide range of diseases. Recent advances in the study of iron metabolism have revealed multiple intricate pathways that are essential to the maintenance of iron homeostasis. Further, iron regulation involves processes at several scales, ranging from the subcellular to the organismal. This complexity makes a systems biology approach crucial, with its enabling technology of computational models based on a mathematical description of regulatory systems. Systems biology may represent a new strategy for understanding imbalances in iron metabolism and their underlying causes. PMID:25480643

Vibrational resonances in biological systems at microwave frequencies.

PubMed

Adair, Robert K

2002-03-01

Many biological systems can be expected to exhibit resonance behavior involving the mechanical vibration of system elements. The natural frequencies of such resonances will, generally, be in the microwave frequency range. Some of these systems will be coupled to the electromagnetic field by the charge distributions they carry, thus admitting the possibility that microwave exposures may generate physiological effects in man and other species. However, such microwave excitable resonances are expected to be strongly damped by interaction with their aqueous biological environment. Although those dissipation mechanisms have been studied, the limitations on energy transfers that follow from the limited coupling of these resonances to the electromagnetic field have not generally been considered. We show that this coupling must generally be very small and thus the absorbed energy is so strongly limited that such resonances cannot affect biology significantly even if the systems are much less strongly damped than expected from basic dissipation models.

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

PubMed

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

2013-12-01

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

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

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.

On the mechanism of adhesion in biological systems

NASA Astrophysics Data System (ADS)

Persson, B. N. J.

2003-04-01

I study adhesion relevant to biological systems, e.g., flies, crickets and lizards, where the adhesive microstructures consist of arrays of thin fibers. The effective elastic modulus of the fiber arrays can be very small which is of fundamental importance for adhesion on smooth and rough substrates. I study how the adhesion depend on the substrate roughness amplitude and apply the theoretical results to lizards.

Interaction between pancreatic β cell and electromagnetic fields: A systematic study toward finding the natural frequency spectrum of β cell system.

PubMed

Farashi, Sajjad

2017-01-01

Interaction between biological systems and environmental electric or magnetic fields has gained attention during the past few decades. Although there are a lot of studies that have been conducted for investigating such interaction, the reported results are considerably inconsistent. Besides the complexity of biological systems, the important reason for such inconsistent results may arise due to different excitation protocols that have been applied in different experiments. In order to investigate carefully the way that external electric or magnetic fields interact with a biological system, the parameters of excitation, such as intensity or frequency, should be selected purposefully due to the influence of these parameters on the system response. In this study, pancreatic β cell, the main player of blood glucose regulating system, is considered and the study is focused on finding the natural frequency spectrum of the system using modeling approach. Natural frequencies of a system are important characteristics of the system when external excitation is applied. The result of this study can help researchers to select proper frequency parameter for electrical excitation of β cell system. The results show that there are two distinct frequency ranges for natural frequency of β cell system, which consist of extremely low (or near zero) and 100-750 kHz frequency ranges. There are experimental works on β cell exposure to electromagnetic fields that support such finding.

Integrating Computer Interfaced Videodisc Systems in Introductory College Biology.

ERIC Educational Resources Information Center

Ebert-Zawasky, Kathleen; Abegg, Gerald L.

This study was designed as a systematic investigation of the feasibility and effectiveness of student authored videodisc presentations in a non-major introductory level college biology course. Students (n=66) used a quick-learn authoring system, the Macintosh computer, and videodisc player with color monitor. Results included: (1) students managed…

Promoting Systems Thinking through Biology Lessons

ERIC Educational Resources Information Center

Riess, Werner; Mischo, Christoph

2010-01-01

This study's goal was to analyze various teaching approaches within the context of natural science lessons, especially in biology. The main focus of the paper lies on the effectiveness of different teaching methods in promoting systems thinking in the field of Education for Sustainable Development. The following methods were incorporated into the…

NITRIFICATION AND ARSENIC REMOVAL IN BIOLOGICALLY ACTIVE FILTERS: A CASE STUDY

EPA Science Inventory

Ammonia in source waters can cause water treatment and distribution system problems, many of which are associated with biological nitrification. Therefore, in some cases, the removal of ammonia from water is desirable. Biological oxidation of ammonia to nitrate and nitrate (nitr...

Biological-based and physical-based optimization for biological evaluation of prostate patient's plans

NASA Astrophysics Data System (ADS)

Sukhikh, E.; Sheino, I.; Vertinsky, A.

2017-09-01

Modern modalities of radiation treatment therapy allow irradiation of the tumor to high dose values and irradiation of organs at risk (OARs) to low dose values at the same time. In this paper we study optimal radiation treatment plans made in Monaco system. The first aim of this study was to evaluate dosimetric features of Monaco treatment planning system using biological versus dose-based cost functions for the OARs and irradiation targets (namely tumors) when the full potential of built-in biological cost functions is utilized. The second aim was to develop criteria for the evaluation of radiation dosimetry plans for patients based on the macroscopic radiobiological criteria - TCP/NTCP. In the framework of the study four dosimetric plans were created utilizing the full extent of biological and physical cost functions using dose calculation-based treatment planning for IMRT Step-and-Shoot delivery of stereotactic body radiation therapy (SBRT) in prostate case (5 fractions per 7 Gy).

Designing mental health interventions informed by child development and human biology theory: A social ecology intervention for child soldiers in Nepal

PubMed Central

Kohrt, Brandon A.; Jordans, Mark J.D.; Koirala, Suraj; Worthman, Carol M.

2017-01-01

The anthropological study of human biology, health, and child development provides a model with potential to address the gap in population-wide mental health interventions. Four key concepts from human biology can inform public mental health interventions: life history theory and tradeoffs, redundancy and plurality of pathways, cascades and multiplier effects in biological systems, and proximate feedback systems. A public mental health intervention for former child soldiers in Nepal is used to illustrate the role of these concepts in intervention design and evaluation. Future directions and recommendations for applying human biology theory in pursuit of public mental health interventions are discussed. PMID:25380194

Designing mental health interventions informed by child development and human biology theory: a social ecology intervention for child soldiers in Nepal.

PubMed

Kohrt, Brandon A; Jordans, Mark J D; Koirala, Suraj; Worthman, Carol M

2015-01-01

The anthropological study of human biology, health, and child development provides a model with potential to address the gap in population-wide mental health interventions. Four key concepts from human biology can inform public mental health interventions: life history theory and tradeoffs, redundancy and plurality of pathways, cascades and multiplier effects in biological systems, and proximate feedback systems. A public mental health intervention for former child soldiers in Nepal is used to illustrate the role of these concepts in intervention design and evaluation. Future directions and recommendations for applying human biology theory in pursuit of public mental health interventions are discussed. © 2014 Wiley Periodicals, Inc.

Conceptual Foundations of Systems Biology Explaining Complex Cardiac Diseases.

PubMed

Louridas, George E; Lourida, Katerina G

2017-02-21

Systems biology is an important concept that connects molecular biology and genomics with computing science, mathematics and engineering. An endeavor is made in this paper to associate basic conceptual ideas of systems biology with clinical medicine. Complex cardiac diseases are clinical phenotypes generated by integration of genetic, molecular and environmental factors. Basic concepts of systems biology like network construction, modular thinking, biological constraints (downward biological direction) and emergence (upward biological direction) could be applied to clinical medicine. Especially, in the field of cardiology, these concepts can be used to explain complex clinical cardiac phenotypes like chronic heart failure and coronary artery disease. Cardiac diseases are biological complex entities which like other biological phenomena can be explained by a systems biology approach. The above powerful biological tools of systems biology can explain robustness growth and stability during disease process from modulation to phenotype. The purpose of the present review paper is to implement systems biology strategy and incorporate some conceptual issues raised by this approach into the clinical field of complex cardiac diseases. Cardiac disease process and progression can be addressed by the holistic realistic approach of systems biology in order to define in better terms earlier diagnosis and more effective therapy.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Genomewide effects of peroxisome proliferator-activated receptor gamma in macrophages and dendritic cells--revealing complexity through systems biology.

PubMed

Cuaranta-Monroy, Ixchelt; Kiss, Mate; Simandi, Zoltan; Nagy, Laszlo

2015-09-01

Systems biology approaches have become indispensable tools in biomedical and basic research. These data integrating bioinformatic methods gained prominence after high-throughput technologies became available to investigate complex cellular processes, such as transcriptional regulation and protein-protein interactions, on a scale that had not been studied before. Immunology is one of the medical fields that systems biology impacted profoundly due to the plasticity of cell types involved and the accessibility of a wide range of experimental models. In this review, we summarize the most important recent genomewide studies exploring the function of peroxisome proliferator-activated receptor γ in macrophages and dendritic cells. PPARγ ChIP-seq experiments were performed in adipocytes derived from embryonic stem cells to complement the existing data sets and to provide comparators to macrophage data. Finally, lists of regulated genes generated from such experiments were analysed with bioinformatics and system biology approaches. We show that genomewide studies utilizing high-throughput data acquisition methods made it possible to gain deeper insights into the role of PPARγ in these immune cell types. We also demonstrate that analysis and visualization of data using network-based approaches can be used to identify novel genes and functions regulated by the receptor. The example of PPARγ in macrophages and dendritic cells highlights the crucial importance of systems biology approaches in establishing novel cellular functions for long-known signaling pathways. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

The painted turtle, Chrysemys picta: a model system for vertebrate evolution, ecology, and human health.

PubMed

Valenzuela, Nicole

2009-07-01

Painted turtles (Chrysemys picta) are representatives of a vertebrate clade whose biology and phylogenetic position hold a key to our understanding of fundamental aspects of vertebrate evolution. These features make them an ideal emerging model system. Extensive ecological and physiological research provide the context in which to place new research advances in evolutionary genetics, genomics, evolutionary developmental biology, and ecological developmental biology which are enabled by current resources, such as a bacterial artificial chromosome (BAC) library of C. picta, and the imminent development of additional ones such as genome sequences and cDNA and expressed sequence tag (EST) libraries. This integrative approach will allow the research community to continue making advances to provide functional and evolutionary explanations for the lability of biological traits found not only among reptiles but vertebrates in general. Moreover, because humans and reptiles share a common ancestor, and given the ease of using nonplacental vertebrates in experimental biology compared with mammalian embryos, painted turtles are also an emerging model system for biomedical research. For example, painted turtles have been studied to understand many biological responses to overwintering and anoxia, as potential sentinels for environmental xenobiotics, and as a model to decipher the ecology and evolution of sexual development and reproduction. Thus, painted turtles are an excellent reptilian model system for studies with human health, environmental, ecological, and evolutionary significance.

Biological Stress Systems, Adverse Life Events, and the Improvement of Chronic Multisite Musculoskeletal Pain Across a 6-Year Follow-Up.

PubMed

Generaal, Ellen; Vogelzangs, Nicole; Macfarlane, Gary J; Geenen, Rinie; Smit, Johannes H; de Geus, Eco J C N; Dekker, Joost; Penninx, Brenda W J H

2017-02-01

Dysfunction of biological stress systems and adverse life events, independently and in interaction, have been hypothesized to predict chronic pain persistence. Conversely, these factors may hamper the improvement of chronic pain. Longitudinal evidence is currently lacking. We examined whether: 1) function of biological stress systems, 2) adverse life events, and 3) their combination predict the improvement of chronic multisite musculoskeletal pain. Subjects of the Netherlands Study of Depression and Anxiety (NESDA) with chronic multisite musculoskeletal pain at baseline (N = 665) were followed-up 2, 4, and 6 years later. The Chronic Pain Grade Questionnaire was used to determine improvement (not meeting the criteria) of chronic multisite musculoskeletal pain at follow-up. Baseline assessment of biological stress systems included function of hypothalamic-pituitary-adrenal axis (1-hour cortisol awakening response, evening level, and post dexamethasone level), the immune system (basal and lipopolysaccharide-stimulated inflammatory markers), the autonomic nervous system (heart rate, pre-ejection period, SD of the normal-to-normal interval, and respiratory sinus arrhythmia). The number of adverse life events were assessed at baseline and 2-year follow-up using the List of Threatening Events Questionnaire. We showed that hypothalamic-pituitary-adrenal axis, immune system, and autonomic nervous system functioning and adverse life events were not associated with the improvement of chronic multisite musculoskeletal pain, either as a main effect or in interaction. This longitudinal study could not confirm that biological stress system dysfunction and adverse life events affect the course of chronic multisite musculoskeletal pain. Biological stress systems and adverse life events are not associated with the improvement of chronic multisite musculoskeletal pain over 6 years of follow-up. Other determinants should thus be considered in future research to identify in which persons pain symptoms will improve. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Biocellion: accelerating computer simulation of multicellular biological system models.

PubMed

Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

2014-11-01

Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Observability of Boolean multiplex control networks

NASA Astrophysics Data System (ADS)

Wu, Yuhu; Xu, Jingxue; Sun, Xi-Ming; Wang, Wei

2017-04-01

Boolean multiplex (multilevel) networks (BMNs) are currently receiving considerable attention as theoretical arguments for modeling of biological systems and system level analysis. Studying control-related problems in BMNs may not only provide new views into the intrinsic control in complex biological systems, but also enable us to develop a method for manipulating biological systems using exogenous inputs. In this article, the observability of the Boolean multiplex control networks (BMCNs) are studied. First, the dynamical model and structure of BMCNs with control inputs and outputs are constructed. By using of Semi-Tensor Product (STP) approach, the logical dynamics of BMCNs is converted into an equivalent algebraic representation. Then, the observability of the BMCNs with two different kinds of control inputs is investigated by giving necessary and sufficient conditions. Finally, examples are given to illustrate the efficiency of the obtained theoretical results.

Analysis of undergraduate students' conceptual models of a complex biological system across a diverse body of learners

NASA Astrophysics Data System (ADS)

Dirnbeck, Matthew R.

Biological systems pose a challenge both for learners and teachers because they are complex systems mediated by feedback loops; networks of cause-effect relationships; and non-linear, hierarchical, and emergent properties. Teachers and scientists routinely use models to communicate ideas about complex systems. Model-based pedagogies engage students in model construction as a means of practicing higher-order reasoning skills. One such modeling paradigm describes systems in terms of their structures, behaviors, and functions (SBF). The SBF framework is a simple modeling language that has been used to teach about complex biological systems. Here, we used student-generated SBF models to assess students' causal reasoning in the context of a novel biological problem on an exam. We compared students' performance on the modeling problem, their performance on a set of knowledge/comprehension questions, and their performance on a set of scientific reasoning questions. We found that students who performed well on knowledge and understanding questions also constructed more networked, higher quality models. Previous studies have shown that learners' mental maps increase in complexity with increased expertise. We wanted to investigate if biology students with varying levels of training in biology showed a similar pattern when constructing system models. In a pilot study, we administered the same modeling problem to two additional groups of students: 1) an animal physiology course for students pursuing a major in biology (n=37) and 2) an exercise physiology course for non-majors (n=27). We found that there was no significant difference in model organization across the three student populations, but there was a significant difference in the ability to represent function between the three populations. Between the three groups the non-majors had the lowest function scores, the introductory majors had the middle function scores, and the upper division majors had the highest function scores.

Biological satellite scientific devices

NASA Astrophysics Data System (ADS)

Perepech, B. L.; Rumiantsev, V. P.; Galkin, V. M.; Shakhvorostov, S. V.; Rvachev, S. S.

1991-02-01

The paper describes the NA SBS 9 systems developed for the ninth Cosmos-2044 biological test mission. The NA SBS 9 life support systems designed for monkeys and rats follow standard design of BIOS-Vivarium and BIOS-Primate units. The main features of NA SBS 9 include the use of a recently developed HF physiological data recorder Skat-3; the incorporation into BIOS-Primate of two units intended for biorhythmic studies (the BBI-Zh system for studying beetles and the VITALOG developed by NASA for studies on monkeys); and a new version of BIOS-Primate system incorporating a capacitance-link and an inductance-link temperature transmitters and a brain tissue oxygen tension control channel.

Systems interface biology

PubMed Central

Doyle, Francis J; Stelling, Jörg

2006-01-01

The field of systems biology has attracted the attention of biologists, engineers, mathematicians, physicists, chemists and others in an endeavour to create systems-level understanding of complex biological networks. In particular, systems engineering methods are finding unique opportunities in characterizing the rich behaviour exhibited by biological systems. In the same manner, these new classes of biological problems are motivating novel developments in theoretical systems approaches. Hence, the interface between systems and biology is of mutual benefit to both disciplines. PMID:16971329

Experimental concept for examination of biological effects of magnetic field concealed by gravity.

PubMed

Yamashita, M; Tomita-Yokotani, K; Hashimoto, H; Takai, M; Tsushima, M; Nakamura, T

2004-01-01

Space is not only a place to study biological effects of gravity, but also provides unique opportunities to examine other environmental factors, where the biological actions are masked by gravity on the ground. Even the earth's magnetic field is steadily acting on living systems, and is known to influence many biological processes. A systematic survey and assessment of its action are difficult to conduct in the presence of dominant factors, such as gravity. Investigation of responses of biological systems against the combined environment of zero-gravity and zero-magnetic field might establish the baseline for the analysis of biological effects of magnetic factors. We propose, in this paper, an experimental concept in this context, together with a practical approach of the experiments, both in orbit and on the ground, with a thin magnetic shielding film. Plant epicotyl growth was taken as an exemplar index to evaluate technical and scientific feasibility of the proposed system concept. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

NITRIFICATION AND IRON AND ARSENIC REMOVAL IN BIOLOGICALLY ACTIVE FILTERS: A CASE STUDY

EPA Science Inventory

Ammonia in source waters can cause water treatment and distribution system problems, many of which are associated with biological nitrification. Therefore, in some cases, the removal of ammonia from water is desirable. Biological oxidation of ammonia to nitrate and nitrate (nitr...

Peptide π-Electron Conjugates: Organic Electronics for Biology?

PubMed

Ardoña, Herdeline Ann M; Tovar, John D

2015-12-16

Highly ordered arrays of π-conjugated molecules are often viewed as a prerequisite for effective charge-transporting materials. Studies involving these materials have traditionally focused on organic electronic devices, with more recent emphasis on biological systems. In order to facilitate the transition to biological environments, biomolecules that can promote hierarchical ordering and water solubility are often covalently appended to the π-electron unit. This review highlights recent work on π-conjugated systems bound to peptide moieties that exhibit self-assembly and aims to provide an overview on the development and emerging applications of peptide-based supramolecular π-electron systems.

Comparative evaluation of Populus variants total sugar release and structural features following pretreatment and digestion by two distinct biological systems

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

Thomas, Vanessa A.; Kothari, Ninad; Bhagia, Samarthya

Populus natural variants have been shown to realize a broad range of sugar yields during saccharification, however, the structural features responsible for higher sugar release from natural variants are not clear. In addition, the sugar release patterns resulting from digestion with two distinct biological systems, fungal enzymes and Clostridium thermocellum, have yet to be evaluated and compared. This study evaluates the effect of structural features of three natural variant Populus lines, which includes the line BESC standard, with respect to the overall process of sugar release for two different biological systems.

Comparative evaluation of Populus variants total sugar release and structural features following pretreatment and digestion by two distinct biological systems

DOE PAGES

Thomas, Vanessa A.; Kothari, Ninad; Bhagia, Samarthya; ...

2017-11-30

Populus natural variants have been shown to realize a broad range of sugar yields during saccharification, however, the structural features responsible for higher sugar release from natural variants are not clear. In addition, the sugar release patterns resulting from digestion with two distinct biological systems, fungal enzymes and Clostridium thermocellum, have yet to be evaluated and compared. This study evaluates the effect of structural features of three natural variant Populus lines, which includes the line BESC standard, with respect to the overall process of sugar release for two different biological systems.

Search for organising principles: understanding in systems biology.

PubMed

Mesarovic, M D; Sreenath, S N; Keene, J D

2004-06-01

Due in large measure to the explosive progress in molecular biology, biology has become arguably the most exciting scientific field. The first half of the 21st century is sometimes referred to as the 'era of biology', analogous to the first half of the 20th century, which was considered to be the 'era of physics'. Yet, biology is facing a crisis--or is it an opportunity--reminiscent of the state of biology in pre-double-helix time. The principal challenge facing systems biology is complexity. According to Hood, 'Systems biology defines and analyses the interrelationships of all of the elements in a functioning system in order to understand how the system works.' With 30000+ genes in the human genome the study of all relationships simultaneously becomes a formidably complex problem. Hanahan and Weinberg raised the question as to whether progress will consist of 'adding further layers of complexity to a scientific literature that is already complex almost beyond measure' or whether the progress will lead to a 'science with a conceptual structure and logical coherence that rivals that of chemistry or physics.' At the core of the challenge is the need for a new approach, a shift from reductionism to a holistic perspective. However, more than just a pronouncement of a new approach is needed. We suggest that what is needed is to provide a conceptual framework for systems biology research. We propose that the concept of a complex system, i.e. a system of systems as defined in mathematical general systems theory (MGST), is central to provide such a framework. We further argue that for a deeper understanding in systems biology investigations should go beyond building numerical mathematical or computer models--important as they are. Biological phenomena cannot be predicted with the level of numerical precision as in classical physics. Explanations in terms of how the categories of systems are organised to function in ever changing conditions are more revealing. Non-numerical mathematical tools are appropriate for the task. Such a categorical perspective led us to propose that the core of understanding in systems biology depends on the search for organising principles rather than solely on construction of predictive descriptions (i.e. models) that exactly outline the evolution of systems in space and time. The search for organising principles requires an identification/discovery of new concepts and hypotheses. Some of them, such as coordination motifs for transcriptional regulatory networks and bounded autonomy of levccels in a hierarchy, are outlined in this article. Experimental designs are outlined to help verify the applicability of the interaction balance principle of coordination to transcriptional and posttranscriptional networks.

Experimental design and reporting standards for metabolomics studies of mammalian cell lines.

PubMed

Hayton, Sarah; Maker, Garth L; Mullaney, Ian; Trengove, Robert D

2017-12-01

Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

SYSTEMS BIOLOGY MODEL DEVELOPMENT AND APPLICATION

EPA Science Inventory

System biology models holistically describe, in a quantitative fashion, the relationships between different levels of a biologic system. Relationships between individual components of a system are delineated. System biology models describe how the components of the system inter...

[The characteristics of the geroprotective action of magnetotherapy in elderly patients with combined cardiovascular pathology].

PubMed

Abramovich, S G; Fedotchenko, A A; Koriakina, A V; Pogodin, K V; Smirnov, S N

1999-01-01

Central hemodynamics, diastolic and pumping functions of the heart, myocardial reactivity, microcirculation and biological age of cardiovascular system were studied in 66 elderly patients suffering from hypertension and ischemic heart disease. The patients received systemic magnetotherapy which produced a geroprotective effect as shown by improved microcirculation, myocardial reactivity, central hemodynamics reducing biological age of cardiovascular system and inhibiting its ageing.

Thermostability of biological systems: fundamentals, challenges, and quantification.

PubMed

He, Xiaoming

2011-01-01

This review examines the fundamentals and challenges in engineering/understanding the thermostability of biological systems over a wide temperature range (from the cryogenic to hyperthermic regimen). Applications of the bio-thermostability engineering to either destroy unwanted or stabilize useful biologicals for the treatment of diseases in modern medicine are first introduced. Studies on the biological responses to cryogenic and hyperthermic temperatures for the various applications are reviewed to understand the mechanism of thermal (both cryo and hyperthermic) injury and its quantification at the molecular, cellular and tissue/organ levels. Methods for quantifying the thermophysical processes of the various applications are then summarized accounting for the effect of blood perfusion, metabolism, water transport across cell plasma membrane, and phase transition (both equilibrium and non-equilibrium such as ice formation and glass transition) of water. The review concludes with a summary of the status quo and future perspectives in engineering the thermostability of biological systems.

Thermostability of Biological Systems: Fundamentals, Challenges, and Quantification

PubMed Central

He, Xiaoming

2011-01-01

This review examines the fundamentals and challenges in engineering/understanding the thermostability of biological systems over a wide temperature range (from the cryogenic to hyperthermic regimen). Applications of the bio-thermostability engineering to either destroy unwanted or stabilize useful biologicals for the treatment of diseases in modern medicine are first introduced. Studies on the biological responses to cryogenic and hyperthermic temperatures for the various applications are reviewed to understand the mechanism of thermal (both cryo and hyperthermic) injury and its quantification at the molecular, cellular and tissue/organ levels. Methods for quantifying the thermophysical processes of the various applications are then summarized accounting for the effect of blood perfusion, metabolism, water transport across cell plasma membrane, and phase transition (both equilibrium and non-equilibrium such as ice formation and glass transition) of water. The review concludes with a summary of the status quo and future perspectives in engineering the thermostability of biological systems. PMID:21769301

Using Petri Net Tools to Study Properties and Dynamics of Biological Systems

PubMed Central

Peleg, Mor; Rubin, Daniel; Altman, Russ B.

2005-01-01

Petri Nets (PNs) and their extensions are promising methods for modeling and simulating biological systems. We surveyed PN formalisms and tools and compared them based on their mathematical capabilities as well as by their appropriateness to represent typical biological processes. We measured the ability of these tools to model specific features of biological systems and answer a set of biological questions that we defined. We found that different tools are required to provide all capabilities that we assessed. We created software to translate a generic PN model into most of the formalisms and tools discussed. We have also made available three models and suggest that a library of such models would catalyze progress in qualitative modeling via PNs. Development and wide adoption of common formats would enable researchers to share models and use different tools to analyze them without the need to convert to proprietary formats. PMID:15561791

From biological and social network metaphors to coupled bio-social wireless networks

PubMed Central

Barrett, Christopher L.; Eubank, Stephen; Anil Kumar, V.S.; Marathe, Madhav V.

2010-01-01

Biological and social analogies have been long applied to complex systems. Inspiration has been drawn from biological solutions to solve problems in engineering products and systems, ranging from Velcro to camouflage to robotics to adaptive and learning computing methods. In this paper, we present an overview of recent advances in understanding biological systems as networks and use this understanding to design and analyse wireless communication networks. We expand on two applications, namely cognitive sensing and control and wireless epidemiology. We discuss how our work in these two applications is motivated by biological metaphors. We believe that recent advances in computing and communications coupled with advances in health and social sciences raise the possibility of studying coupled bio-social communication networks. We argue that we can better utilise the advances in our understanding of one class of networks to better our understanding of the other. PMID:21643462

Controlled ecological life support system higher plant flight experiments

NASA Technical Reports Server (NTRS)

Tibbitts, T. W.; Wheeler, R. M.

1984-01-01

Requirements for spaceflight experments which involve higher plants were determined. The plants are studied for use in controlled ecological life support systems (CELSS). Two categories of research requirements are discussed: (1) the physical needs which include nutrient, water and gas exchange requirements; (2) the biological and physiological functions which affect plants in zero gravity environments. Physical problems studies are given the priority since they affect all biological experiments.

Increasing URM Undergraduate Student Success through Assessment-Driven Interventions: A Multiyear Study Using Freshman-Level General Biology as a Model System

ERIC Educational Resources Information Center

Carmichael, Mary C.; St. Clair, Candace; Edwards, Andrea M.; Barrett, Peter; McFerrin, Harris; Davenport, Ian; Awad, Mohamed; Kundu, Anup; Ireland, Shubha Kale

2016-01-01

Xavier University of Louisiana leads the nation in awarding BS degrees in the biological sciences to African-American students. In this multiyear study with ~5500 participants, data-driven interventions were adopted to improve student academic performance in a freshman-level general biology course. The three hour-long exams were common and…

Prospects for Applying Synthetic Biology to Toxicology: Future Opportunities and Current Limitations for the Repurposing of Cytochrome P450 Systems.

PubMed

Behrendorff, James B Y H; Gillam, Elizabeth M J

2017-01-17

The 30 years since the inception of Chemical Research in Toxicology, game-changing advances in chemical and molecular biology, the fundamental disciplines underpinning molecular toxicology, have been made. While these have led to important advances in the study of mechanisms by which chemicals damage cells and systems, there has been less focus on applying these advances to prediction, detection, and mitigation of toxicity. Over the last ∼15 years, synthetic biology, the repurposing of biological "parts" in systems engineered for useful ends, has been explored in other areas of the biomedical and life sciences, for such applications as detecting metabolites, drug discovery and delivery, investigating disease mechanisms, improving medical treatment, and producing useful chemicals. These examples provide models for the application of synthetic biology to toxicology, which, for the most part, has not yet benefited from such approaches. In this perspective, we review the synthetic biology approaches that have been applied to date and speculate on possible short to medium term and "blue sky" aspirations for synthetic biology, particularly in clinical and environmental toxicology. Finally, we point out key hurdles that must be overcome for the full potential of synthetic biology to be realized.

Databases, Repositories and Other Data Resources in Structural Biology

PubMed Central

Zheng, Heping; Porebski, Przemyslaw J.; Grabowski, Marek; Cooper, David R.; Minor, Wladek

2017-01-01

Structural biology, like many other areas of modern science, produces an enormous amount of primary, derived, and “meta” data with a high demand on data storage and manipulations. Primary data comes from various steps of sample preparation, diffraction experiments, and functional studies. These data are not only used to obtain tangible results, like macromolecular structural models, but also to enrich and guide our analysis and interpretation of existing biomedical studies. Herein we define several categories of data resources, (a) Archives, (b) Repositories, (c) “Databases” and (d) Advanced Information Systems, that can accommodate primary, derived, or reference data. Data resources may be used either as web portals or internally by structural biology software. To be useful, each resource must be maintained, curated, and be integrated with other resources. Ideally, the system of interconnected resources should evolve toward comprehensive “hubs” or Advanced Information Systems. Such systems, encompassing the PDB and UniProt, are indispensable not only for structural biology, but for many related fields of science. The categories of data resources described herein are applicable well beyond our usual scientific endeavors. PMID:28573593

Future Science Teachers' Understandings of Diffusion and Osmosis Concepts

ERIC Educational Resources Information Center

Tomazic, Iztok; Vidic, Tatjana

2012-01-01

The concepts of diffusion and osmosis cross the disciplinary boundaries of physics, chemistry and biology. They are important for understanding how biological systems function. Since future (pre-service) science teachers in Slovenia encounter both concepts at physics, chemistry and biology courses during their studies, we assessed the first-,…

The Effects of Explicit Visual Cues in Reading Biological Diagrams

ERIC Educational Resources Information Center

Ge, Yun-Ping; Unsworth, Len; Wang, Kuo-Hua

2017-01-01

Drawing on cognitive theories, this study intends to investigate the effects of explicit visual cues which have been proposed as a critical factor in facilitating understanding of biological images. Three diagrams from Taiwanese textbooks with implicit visual cues, involving the concepts of biological classification systems, fish taxonomy, and…

Biological Motion Cues Trigger Reflexive Attentional Orienting

ERIC Educational Resources Information Center

Shi, Jinfu; Weng, Xuchu; He, Sheng; Jiang, Yi

2010-01-01

The human visual system is extremely sensitive to biological signals around us. In the current study, we demonstrate that biological motion walking direction can induce robust reflexive attentional orienting. Following a brief presentation of a central point-light walker walking towards either the left or right direction, observers' performance…

Industrial methodology for process verification in research (IMPROVER): toward systems biology verification

PubMed Central

Meyer, Pablo; Hoeng, Julia; Rice, J. Jeremy; Norel, Raquel; Sprengel, Jörg; Stolle, Katrin; Bonk, Thomas; Corthesy, Stephanie; Royyuru, Ajay; Peitsch, Manuel C.; Stolovitzky, Gustavo

2012-01-01

Motivation: Analyses and algorithmic predictions based on high-throughput data are essential for the success of systems biology in academic and industrial settings. Organizations, such as companies and academic consortia, conduct large multi-year scientific studies that entail the collection and analysis of thousands of individual experiments, often over many physical sites and with internal and outsourced components. To extract maximum value, the interested parties need to verify the accuracy and reproducibility of data and methods before the initiation of such large multi-year studies. However, systematic and well-established verification procedures do not exist for automated collection and analysis workflows in systems biology which could lead to inaccurate conclusions. Results: We present here, a review of the current state of systems biology verification and a detailed methodology to address its shortcomings. This methodology named ‘Industrial Methodology for Process Verification in Research’ or IMPROVER, consists on evaluating a research program by dividing a workflow into smaller building blocks that are individually verified. The verification of each building block can be done internally by members of the research program or externally by ‘crowd-sourcing’ to an interested community. www.sbvimprover.com Implementation: This methodology could become the preferred choice to verify systems biology research workflows that are becoming increasingly complex and sophisticated in industrial and academic settings. Contact: gustavo@us.ibm.com PMID:22423044

On a biologically inspired topology optimization method

NASA Astrophysics Data System (ADS)

Kobayashi, Marcelo H.

2010-03-01

This work concerns the development of a biologically inspired methodology for the study of topology optimization in engineering and natural systems. The methodology is based on L systems and its turtle interpretation for the genotype-phenotype modeling of the topology development. The topology is analyzed using the finite element method, and optimized using an evolutionary algorithm with the genetic encoding of the L system and its turtle interpretation, as well as, body shape and physical characteristics. The test cases considered in this work clearly show the suitability of the proposed method for the study of engineering and natural complex systems.

Magnetoencephalography Study of Right Parietal Lobe Dysfunction of the Evoked Mirror Neuron System in Antipsychotic-Free Schizophrenia

PubMed Central

Kato, Yutaka; Muramatsu, Taro; Kato, Motoichiro; Shibukawa, Yoshiyuki; Shintani, Masuro; Mimura, Masaru

2011-01-01

Introduction Patients with schizophrenia commonly exhibit deficits of non-verbal communication in social contexts, which may be related to cognitive dysfunction that impairs recognition of biological motion. Although perception of biological motion is known to be mediated by the mirror neuron system, there have been few empirical studies of this system in patients with schizophrenia. Methods Using magnetoencephalography, we examined whether antipsychotic-free schizophrenia patients displayed mirror neuron system dysfunction during observation of biological motion (jaw movement of another individual). Results Compared with normal controls, the patients with schizophrenia had fewer components of both the waveform and equivalent current dipole, suggesting aberrant brain activity resulting from dysfunction of the right inferior parietal cortex. They also lacked the changes of alpha band and gamma band oscillation seen in normal controls, and had weaker phase-locking factors and gamma-synchronization predominantly in right parietal cortex. Conclusions Our findings demonstrate that untreated patients with schizophrenia exhibit aberrant mirror neuron system function based on the right inferior parietal cortex, which is characterized by dysfunction of gamma-synchronization in the right parietal lobe during observation of biological motion. PMID:22132217

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

PubMed Central

Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary

2018-01-01

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574

Social relationships and their biological correlates: Coronary Artery Risk Development in Young Adults (CARDIA) study.

PubMed

Seeman, Teresa E; Gruenewald, Tara L; Cohen, Sheldon; Williams, David R; Matthews, Karen A

2014-05-01

Analyses test the hypothesis that aspects of social relationships (quantity of ties, social support and social strain) are associated with differences in levels of biological risk across multiple major physiological regulatory systems and consequently overall multi-systems risk (i.e., allostatic load [AL]). Data are from the Coronary Artery Risk Development in Young Adults (CARDIA) study--a bi-ethnic, prospective, multi-center epidemiological study, initiated in 1985-1986 to track the development of cardiovascular risk in young adulthood (N=5115). At the year 15 follow-up when participants were between 32 and 45 years of age, additional social and biological data were collected; biological data used to assess AL were collected at the Oakland, CA and Chicago, IL sites (N=844). Social strains were most strongly and positively related to overall AL (Cohen's d=.79 for highest vs. lowest quartile), and to each of its component biological subsystems, independent of social ties and support as well as sociodemographics and health behaviors. Social ties and emotional support were also negatively related to AL (Cohen's d=.33 and d=.44 for lowest vs. highest quartiles of ties and support, respectively) though controls for social strains reduced these associations to non-significance. Social support and social strain were more strongly related to overall AL than to any of its component subscales while social ties were less strongly related to AL and to its component subscales. There was no evidence that effects differed by sex, age or ethnicity. Findings focus attention on the particularly strong relationship between social strains and profiles of biological risk and support the cumulative impact of social factors on biological risks, showing larger effects for cumulative AL than for any of the individual biological systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling multisystem biological risk in young adults: The Coronary Artery Risk Development in Young Adults Study.

PubMed

Seeman, Teresa; Gruenewald, Tara; Karlamangla, Arun; Sidney, Steve; Liu, Kiang; McEwen, Bruce; Schwartz, Joseph

2010-01-01

Although much prior research has focused on identifying the roles of major regulatory systems in health risks, the concept of allostatic load (AL) focuses on the importance of a more multisystems view of health risks. How best to operationalize allostatic load, however, remains the subject of some debate. We sought to test a hypothesized metafactor model of allostatic load composed of a number of biological system factors, and to investigate model invariance across sex and ethnicity. Biological data from 782 men and women, aged 32-47, from the Oakland, CA and Chicago, IL sites of the Coronary Artery Risk Development in Young Adults Study (CARDIA) were collected as part of the Year 15exam in 2000. These include measures of blood pressure, metabolic parameters (glucose, insulin, lipid profiles, and waist circumference), markers of inflammation (interleukin-6, C-reactive protein, and fibrinogen), heart rate variability, sympathetic nervous system activity (12-hr urinary norepinephrine and epinephrine) and hypothalamic-pituitary-adrenal axis activity (diurnal salivary free cortisol). A "metafactor" model of AL as an aggregate measure of six underlying latent biological subfactors was found to fit the data, with the metafactor structure capturing 84% of variance of all pairwise associations among biological subsystems. There was little evidence of model variance across sex and/or ethnicity. These analyses extend work operationalizing AL as a multisystems index of biological dysregulation, providing initial support for a model of AL as a metaconstruct of inter-relationships among multiple biological regulatory systems, that varies little across sex or ethnicity.

Research on Life Science and Life Support Engineering Problems of Manned Deep Space Exploration Mission

NASA Astrophysics Data System (ADS)

Qi, Bin; Guo, Linli; Zhang, Zhixian

2016-07-01

Space life science and life support engineering are prominent problems in manned deep space exploration mission. Some typical problems are discussed in this paper, including long-term life support problem, physiological effect and defense of varying extraterrestrial environment. The causes of these problems are developed for these problems. To solve these problems, research on space life science and space medical-engineering should be conducted. In the aspect of space life science, the study of space gravity biology should focus on character of physiological effect in long term zero gravity, co-regulation of physiological systems, impact on stem cells in space, etc. The study of space radiation biology should focus on target effect and non-target effect of radiation, carcinogenicity of radiation, spread of radiation damage in life system, etc. The study of basic biology of space life support system should focus on theoretical basis and simulating mode of constructing the life support system, filtration and combination of species, regulation and optimization method of life support system, etc. In the aspect of space medical-engineering, the study of bio-regenerative life support technology should focus on plants cultivation technology, animal-protein production technology, waste treatment technology, etc. The study of varying gravity defense technology should focus on biological and medical measures to defend varying gravity effect, generation and evaluation of artificial gravity, etc. The study of extraterrestrial environment defense technology should focus on risk evaluation of radiation, monitoring and defending of radiation, compound prevention and removal technology of dust, etc. At last, a case of manned lunar base is analyzed, in which the effective schemes of life support system, defense of varying gravity, defense of extraterrestrial environment are advanced respectively. The points in this paper can be used as references for intensive study on key technologies.

Students' Learning Activities While Studying Biological Process Diagrams

ERIC Educational Resources Information Center

Kragten, Marco; Admiraal, Wilfried; Rijlaarsdam, Gert

2015-01-01

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

Mechanisms for Robust Cognition.

PubMed

Walsh, Matthew M; Gluck, Kevin A

2015-08-01

To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within variable environments. This raises the question, how do cognitive systems achieve similarly high degrees of robustness? The aim of this study was to identify a set of mechanisms that enhance robustness in cognitive systems. We identify three mechanisms that enhance robustness in biological and engineered systems: system control, redundancy, and adaptability. After surveying the psychological literature for evidence of these mechanisms, we provide simulations illustrating how each contributes to robust cognition in a different psychological domain: psychomotor vigilance, semantic memory, and strategy selection. These simulations highlight features of a mathematical approach for quantifying robustness, and they provide concrete examples of mechanisms for robust cognition. © 2014 Cognitive Science Society, Inc.

Genetic and Genomic Toolbox of Zea mays

PubMed Central

Nannas, Natalie J.; Dawe, R. Kelly

2015-01-01

Maize has a long history of genetic and genomic tool development and is considered one of the most accessible higher plant systems. With a fully sequenced genome, a suite of cytogenetic tools, methods for both forward and reverse genetics, and characterized phenotype markers, maize is amenable to studying questions beyond plant biology. Major discoveries in the areas of transposons, imprinting, and chromosome biology came from work in maize. Moving forward in the post-genomic era, this classic model system will continue to be at the forefront of basic biological study. In this review, we outline the basics of working with maize and describe its rich genetic toolbox. PMID:25740912

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.

Multidisciplinary approaches to solar hydrogen

PubMed Central

Bren, Kara L.

2015-01-01

This review summarizes three different approaches to engineering systems for the solar-driven evolution of hydrogen fuel from water: molecular, nanomaterials and biomolecular. Molecular systems have the advantage of being highly amenable to modification and detailed study and have provided great insight into photophysics, electron transfer and catalytic mechanism. However, they tend to display poor stability. Systems based on nanomaterials are more robust but also are more difficult to synthesize in a controlled manner and to modify and study in detail. Biomolecular systems share many properties with molecular systems and have the advantage of displaying inherently high efficiencies for light absorption, electron–hole separation and catalysis. However, biological systems must be engineered to couple modules that capture and convert solar photons to modules that produce hydrogen fuel. Furthermore, biological systems are prone to degradation when employed in vitro. Advances that use combinations of these three tactics also are described. Multidisciplinary approaches to this problem allow scientists to take advantage of the best features of biological, molecular and nanomaterials systems provided that the components can be coupled for efficient function. PMID:26052425

Advances of Molecular Imaging for Monitoring the Anatomical and Functional Architecture of the Olfactory System.

PubMed

Zhang, Xintong; Bi, Anyao; Gao, Quansheng; Zhang, Shuai; Huang, Kunzhu; Liu, Zhiguo; Gao, Tang; Zeng, Wenbin

2016-01-20

The olfactory system of organisms serves as a genetically and anatomically model for studying how sensory input can be translated into behavior output. Some neurologic diseases are considered to be related to olfactory disturbance, especially Alzheimer's disease, Parkinson's disease, multiple sclerosis, and so forth. However, it is still unclear how the olfactory system affects disease generation processes and olfaction delivery processes. Molecular imaging, a modern multidisciplinary technology, can provide valid tools for the early detection and characterization of diseases, evaluation of treatment, and study of biological processes in living subjects, since molecular imaging applies specific molecular probes as a novel approach to produce special data to study biological processes in cellular and subcellular levels. Recently, molecular imaging plays a key role in studying the activation of olfactory system, thus it could help to prevent or delay some diseases. Herein, we present a comprehensive review on the research progress of the imaging probes for visualizing olfactory system, which is classified on different imaging modalities, including PET, MRI, and optical imaging. Additionally, the probes' design, sensing mechanism, and biological application are discussed. Finally, we provide an outlook for future studies in this field.

Invited Review Article: Current State of Research on Biological Effects of Terahertz Radiation

NASA Astrophysics Data System (ADS)

Wilmink, Gerald J.; Grundt, Jessica E.

2011-10-01

Terahertz (THz) imaging and sensing technologies are increasingly being used in a host of medical, military, and security applications. For example, THz systems are now being tested at international airports for security screening purposes, at major medical centers for cancer and burn diagnosis, and at border patrol checkpoints for identification of concealed explosives, drugs, and weapons. Recent advances in THz applications have stimulated renewed interest regarding the biological effects associated with this frequency range. Biological effects studies are a valuable type of basic science research because they serve to enhance our fundamental understanding of the mechanisms that govern THz interactions with biological systems. Such studies are also important because they often times lay the foundation for the development of future applications. In addition, from a practical standpoint, THz biological effects research is also necessary for accurate health hazard evaluation, the development of empirically-based safety standards, and for the safe use of THz systems. Given the importance and timeliness of THz bioeffects data, the purpose of this review is twofold. First, to provide readers with a common reference, which contains the necessary background concepts in biophysics and THz technology, that are required to both conduct and evaluate THz biological research. Second, to provide a critical review of the scientific literature.

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'.

Comparative study of binding interactions between porphyrin systems and aromatic compounds of biological importance by multiple spectroscopic techniques: A review

NASA Astrophysics Data System (ADS)

Makarska-Bialokoz, Magdalena

2018-07-01

The specific spectroscopic and redox properties of porphyrins predestine them to fulfill the role of sensors during interacting with different biologically active substances. Monitoring of binding interactions in the systems porphyrin-biologically active compound is a key question not only in the field of physiological functions of living organisms, but also in environmental protection, notably in the light of the rapidly growing drug consumption and concurrently the production of drug effluents. Not always beneficial action of drugs on natural porphyrin systems induces to further studies, with commercially available porphyrins as the model systems. Therefore the binding process between several water-soluble porphyrins and a series of biologically active compounds (e.g. caffeine, guanine, theophylline, theobromine, xanthine, uric acid) has been studied in different aqueous solutions analyzing their absorption and steady-state fluorescence spectra, the porphyrin fluorescence lifetimes and their quantum yields. The magnitude of the binding and fluorescence quenching constants values for particular quenchers decreases in a series: uric acid > guanine > caffeine > theophylline > theobromine > xanthine. In all the systems studied there are characters of static quenching, as a consequence of the π-π-stacked non-covalent and non-fluorescent complexes formation between porphyrins and interacting compounds, accompanied simultaneously by the additional specific binding interactions. The porphyrin fluorescence quenching can be explain by the photoinduced intermolecular electron transfer from aromatic compound to the center of the porphyrin molecule, playing the role of the binding site. Presented results can be valuable for designing of new fluorescent porphyrin chemosensors or monitoring of drug traces in aqueous solutions. The obtained outcomes have also the toxicological and medical importance, providing insight into the interactions of the water-soluble porphyrins with biologically active substances.

Growing Spaceships?

NASA Technical Reports Server (NTRS)

Robertson, Glen A.

2013-01-01

NASA currently has a program called the Space Synthetic Biology Project. Synthetic Biology or SynBio is the design and construction of new biological functions and systems not found in nature. Four NASA field centers, along with experts from industry and academia, have been partnering on the Space Synthetic Biology Project and are working on new breakthroughs in this increasingly useful pursuit, which is part a science discipline and part engineering. Led by researchers at NASA s Ames Research Center, the team is studying how this powerful new tool can help NASA now and in the future. The project was created to harness biology in reliable, robust, engineered systems to support the agency s exploration and science missions, to improve life on Earth and to help shape NASA's future. The program also is intended to contribute foundational tools to the synthetic biology research community.

Studying cell biology in the skin.

PubMed

Morrow, Angel; Lechler, Terry

2015-11-15

Advances in cell biology have often been driven by studies in diverse organisms and cell types. Although there are technical reasons for why different cell types are used, there are also important physiological reasons. For example, ultrastructural studies of vesicle transport were aided by the use of professional secretory cell types. The use of tissues/primary cells has the advantage not only of using cells that are adapted to the use of certain cell biological machinery, but also of highlighting the physiological roles of this machinery. Here we discuss advantages of the skin as a model system. We discuss both advances in cell biology that used the skin as a driving force and future prospects for use of the skin to understand basic cell biology. A unique combination of characteristics and tools makes the skin a useful in vivo model system for many cell biologists. © 2015 Morrow and Lechler. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Utilizing population variation, vaccination, and systems biology to study human immunology.

PubMed

Tsang, John S

2015-08-01

The move toward precision medicine has highlighted the importance of understanding biological variability within and across individuals in the human population. In particular, given the prevalent involvement of the immune system in diverse pathologies, an important question is how much and what information about the state of the immune system is required to enable accurate prediction of future health and response to medical interventions. Towards addressing this question, recent studies using vaccination as a model perturbation and systems-biology approaches are beginning to provide a glimpse of how natural population variation together with multiplexed, high-throughput measurement and computational analysis can be used to uncover predictors of immune response quality in humans. Here I discuss recent developments in this emerging field, with emphasis on baseline correlates of vaccination responses, sources of immune-state variability, as well as relevant features of study design, data generation, and computational analysis. Copyright © 2015 The Author. Published by Elsevier Ltd.. All rights reserved.

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

PubMed Central

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

2016-01-01

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways. PMID:27075000

Penetration and propagation into biological matter and biological effects of high-power ultra-wideband pulses: a review.

PubMed

Schunck, Thérèse; Bieth, François; Pinguet, Sylvain; Delmote, Philippe

2016-01-01

Systems emitting ultra-wideband high power microwave (HP/UWB) pulses are developed for military and civilian applications. HP/UWB pulses typically have durations on the order of nanoseconds, rise times of picoseconds and amplitudes around 100 kV m(-1). This article reviews current research on biological effects from HP/UWB exposure. The different references were classified according to endpoints (cardiovascular system, central nervous system, behavior, genotoxicity, teratology …). The article also reviews the aspects of mechanisms of interactions and tissue damage as well as the numerical work that has been done for studying HP/UWB pulse propagation and pulse energy deposition inside biological tissues. The mechanisms proposed are the molecular conformation change, the modification of chemical reaction rates, membrane excitation and breakdown and direct electrical forces on cells or cell constituents, and the energy deposition. As regards the penetration of biological matter and the deposited energy, mainly computations were published. They have shown that the EM field inside the biological matter is strongly modified compared to the incident EM field and that the energy absorption for HP/UWB pulses occurs in the same way as for continuous waves. However, the energy carried by a HP/UWB pulse is very low and the deposited energy is low. The number of published studies dealing with the biological effects is small and only a few pointed out slight effects. It should be further noted that the animal populations used in the studies were not always large, the statistical analyses not always relevant and the teams involved in this research rather limited in number.

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.

What Is Sleep Apnea?

MedlinePlus

... NHLBI Division of Intramural Research and its Systems Biology Center are studying how genes and the environment ... which supports research on sleep and the circadian biology of sleep disorders, including how the body regulates ...

Information theory in systems biology. Part II: protein-protein interaction and signaling networks.

PubMed

Mousavian, Zaynab; Díaz, José; Masoudi-Nejad, Ali

2016-03-01

By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation of the Biolog MicroStation system for yeast identification

NASA Technical Reports Server (NTRS)

McGinnis, M. R.; Molina, T. C.; Pierson, D. L.; Mishra, S. K.

1996-01-01

One hundred and fifty-nine isolates representing 16 genera and 53 species of yeasts were processed with the Biolog MicroStation System for yeast identification. Thirteen genera and 38 species were included in the Biolog database. For these 129 isolates, correct identifications to the species level were 13.2, 39.5 and 48.8% after 24, 48 and 72 hours incubation at 30 degrees C, respectively. Three genera and 15 species which were not included in the Biolog database were also tested. Of the 30 isolates studied, 16.7, 53.3 and 56.7% of the isolates were given incorrect names from the system's database after 24,48 and 72 h incubation at 30 degrees C, respectively. The remaining isolates of this group were not identified.

Rapid Start-up and Loading of an Attached Growth, Simultaneous Nitrification/Denitrification Membrane Aerated Bioreactor

NASA Technical Reports Server (NTRS)

Meyer, Caitlin E.; Pensinger, Stuart; Pickering, Karen D.; Barta, Daniel; Shull, Sarah A.; Vega, Letticia M.; Christenson, Dylan; Jackson, W. Andrew

2015-01-01

Membrane aerated bioreactors (MABR) are attached-growth biological systems used for simultaneous nitrification and denitrification to reclaim water from waste. This design is an innovative approach to common terrestrial wastewater treatments for nitrogen and carbon removal and implementing a biologically-based water treatment system for long-duration human exploration is an attractive, low energy alternative to physiochemical processes. Two obstacles to implementing such a system are (1) the "start-up" duration from inoculation to steady-state operations and (2) the amount of surface area needed for the biological activity to occur. The Advanced Water Recovery Systems (AWRS) team at JSC explored these two issues through two tests; a rapid inoculation study and a wastewater loading study. Results from these tests demonstrate that the duration from inoculation to steady state can be reduced to under two weeks, and that despite low ammonium removal rates, the MABRs are oversized.

Morphomics: An integral part of systems biology of the human placenta.

PubMed

Mayhew, T M

2015-04-01

The placenta is a transient organ the functioning of which has health consequences far beyond the embryo/fetus. Understanding the biology of any system (organ, organism, single cell, etc) requires a comprehensive and inclusive approach which embraces all the biomedical disciplines and 'omic' technologies and then integrates information obtained from all of them. Among the latest 'omics' is morphomics. The terms morphome and morphomics have been applied incoherently in biology and biomedicine but, recently, they have been given clear and widescale definitions. Morphomics is placed in the context of other 'omics' and its pertinent technologies and tools for sampling and quantitation are reviewed. Emphasis is accorded to the importance of random sampling principles in systems biology and the value of combining 3D quantification with alternative imaging techniques to advance knowledge and understanding of the human placental morphome. By analogy to other 'omes', the morphome is the totality of morphological features within a system and morphomics is the systematic study of those structures. Information about structure is required at multiple levels of resolution in order to understand better the processes by which a given system alters with time, experimental treatment or environmental insult. Therefore, morphomics research includes all imaging techniques at all levels of achievable resolution from gross anatomy and medical imaging, via optical and electron microscopy, to molecular characterisation. Quantification is an important element of all 'omics' studies and, because biological systems exist and operate in 3-dimensional (3D) space, precise descriptions of form, content and spatial relationships require the quantification of structure in 3D. These considerations are relevant to future study contributions to the Human Placenta Project. Copyright © 2015 Elsevier Ltd. All rights reserved.

First-principles modeling of biological systems and structure-based drug-design.

PubMed

Sgrignani, Jacopo; Magistrato, Alessandra

2013-03-01

Molecular modeling techniques play a relevant role in drug design providing detailed information at atomistic level on the structural, dynamical, mechanistic and electronic properties of biological systems involved in diseases' onset, integrating and supporting commonly used experimental approaches. These information are often not accessible to the experimental techniques taken singularly, but are of crucial importance for drug design. Due to the enormous increase of the computer power in the last decades, quantum mechanical (QM) or first-principles-based methods have become often used to address biological issues of pharmaceutical relevance, providing relevant information for drug design. Due to their complexity and their size, biological systems are often investigated by means of a mixed quantum-classical (QM/MM) approach, which treats at an accurate QM level a limited chemically relevant portion of the system and at the molecular mechanics (MM) level the remaining of the biomolecule and its environment. This method provides a good compromise between computational cost and accuracy, allowing to characterize the properties of the biological system and the (free) energy landscape of the process in study with the accuracy of a QM description. In this review, after a brief introduction of QM and QM/MM methods, we will discuss few representative examples, taken from our work, of the application of these methods in the study of metallo-enzymes of pharmaceutical interest, of metal-containing anticancer drugs targeting the DNA as well as of neurodegenerative diseases. The information obtained from these studies may provide the basis for a rationale structure-based drug design of new and more efficient inhibitors or drugs.

Systems biology for molecular life sciences and its impact in biomedicine.

PubMed

Medina, Miguel Ángel

2013-03-01

Modern systems biology is already contributing to a radical transformation of molecular life sciences and biomedicine, and it is expected to have a real impact in the clinical setting in the next years. In this review, the emergence of systems biology is contextualized with a historic overview, and its present state is depicted. The present and expected future contribution of systems biology to the development of molecular medicine is underscored. Concerning the present situation, this review includes a reflection on the "inflation" of biological data and the urgent need for tools and procedures to make hidden information emerge. Descriptions of the impact of networks and models and the available resources and tools for applying them in systems biology approaches to molecular medicine are provided as well. The actual current impact of systems biology in molecular medicine is illustrated, reviewing two cases, namely, those of systems pharmacology and cancer systems biology. Finally, some of the expected contributions of systems biology to the immediate future of molecular medicine are commented.

The Physics of Open Ended Evolution

NASA Astrophysics Data System (ADS)

Adams, Alyssa M.

What makes living systems different than non-living ones? Unfortunately this question is impossible to answer, at least currently. Instead, we must face computationally tangible questions based on our current understanding of physics, computation, information, and biology. Yet we have few insights into how living systems might quantifiably differ from their non-living counterparts, as in a mathematical foundation to explain away our observations of biological evolution, emergence, innovation, and organization. The development of a theory of living systems, if at all possible, demands a mathematical understanding of how data generated by complex biological systems changes over time. In addition, this theory ought to be broad enough as to not be constrained to an Earth-based biochemistry. In this dissertation, the philosophy of studying living systems from the perspective of traditional physics is first explored as a motivating discussion for subsequent research. Traditionally, we have often thought of the physical world from a bottom-up approach: things happening on a smaller scale aggregate into things happening on a larger scale. In addition, the laws of physics are generally considered static over time. Research suggests that biological evolution may follow dynamic laws that (at least in part) change as a function of the state of the system. Of the three featured research projects, cellular automata (CA) are used as a model to study certain aspects of living systems in two of them. These aspects include self-reference, open-ended evolution, local physical universality, subjectivity, and information processing. Open-ended evolution and local physical universality are attributed to the vast amount of innovation observed throughout biological evolution. Biological systems may distinguish themselves in terms of information processing and storage, not outside the theory of computation. The final research project concretely explores real-world phenomenon by means of mapping dominance hierarchies in the evolution of video game strategies. Though the main question of how life differs from non-life remains unanswered, the mechanisms behind open-ended evolution and physical universality are revealed.

Advances on plant-pathogen interactions from molecular toward systems biology perspectives.

PubMed

Peyraud, Rémi; Dubiella, Ullrich; Barbacci, Adelin; Genin, Stéphane; Raffaele, Sylvain; Roby, Dominique

2017-05-01

In the past 2 decades, progress in molecular analyses of the plant immune system has revealed key elements of a complex response network. Current paradigms depict the interaction of pathogen-secreted molecules with host target molecules leading to the activation of multiple plant response pathways. Further research will be required to fully understand how these responses are integrated in space and time, and exploit this knowledge in agriculture. In this review, we highlight systems biology as a promising approach to reveal properties of molecular plant-pathogen interactions and predict the outcome of such interactions. We first illustrate a few key concepts in plant immunity with a network and systems biology perspective. Next, we present some basic principles of systems biology and show how they allow integrating multiomics data and predict cell phenotypes. We identify challenges for systems biology of plant-pathogen interactions, including the reconstruction of multiscale mechanistic models and the connection of host and pathogen models. Finally, we outline studies on resistance durability through the robustness of immune system networks, the identification of trade-offs between immunity and growth and in silico plant-pathogen co-evolution as exciting perspectives in the field. We conclude that the development of sophisticated models of plant diseases incorporating plant, pathogen and climate properties represent a major challenge for agriculture in the future. © 2016 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

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

PubMed

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

2018-02-01

In an effort to address a major challenge in chemical safety assessment, alternative approaches for characterizing systemic effect levels, a predictive model was developed. Systemic effect levels were curated from ToxRefDB, HESS-DB and COSMOS-DB from numerous study types totaling 4379 in vivo studies for 1247 chemicals. Observed systemic effects in mammalian models are a complex function of chemical dynamics, kinetics, and inter- and intra-individual variability. To address this complex problem, systemic effect levels were modeled at the study-level by leveraging study covariates (e.g., study type, strain, administration route) in addition to multiple descriptor sets, including chemical (ToxPrint, PaDEL, and Physchem), biological (ToxCast), and kinetic descriptors. Using random forest modeling with cross-validation and external validation procedures, study-level covariates alone accounted for approximately 15% of the variance reducing the root mean squared error (RMSE) from 0.96 log 10 to 0.85 log 10  mg/kg/day, providing a baseline performance metric (lower expectation of model performance). A consensus model developed using a combination of study-level covariates, chemical, biological, and kinetic descriptors explained a total of 43% of the variance with an RMSE of 0.69 log 10  mg/kg/day. A benchmark model (upper expectation of model performance) was also developed with an RMSE of 0.5 log 10  mg/kg/day by incorporating study-level covariates and the mean effect level per chemical. To achieve a representative chemical-level prediction, the minimum study-level predicted and observed effect level per chemical were compared reducing the RMSE from 1.0 to 0.73 log 10  mg/kg/day, equivalent to 87% of predictions falling within an order-of-magnitude of the observed value. Although biological descriptors did not improve model performance, the final model was enriched for biological descriptors that indicated xenobiotic metabolism gene expression, oxidative stress, and cytotoxicity, demonstrating the importance of accounting for kinetics and non-specific bioactivity in predicting systemic effect levels. Herein, we generated an externally predictive model of systemic effect levels for use as a safety assessment tool and have generated forward predictions for over 30,000 chemicals.

Biological life-support systems

NASA Technical Reports Server (NTRS)

Shepelev, Y. Y.

1975-01-01

The establishment of human living environments by biologic methods, utilizing the appropriate functions of autotrophic and heterotrophic organisms is examined. Natural biologic systems discussed in terms of modeling biologic life support systems (BLSS), the structure of biologic life support systems, and the development of individual functional links in biologic life support systems are among the factors considered. Experimental modeling of BLSS in order to determine functional characteristics, mechanisms by which stability is maintained, and principles underlying control and regulation is also discussed.

Development of biological control of Tetranychus urticae (Acari:Tetranychidae) and Phorodon humuli (Hemiptera: Aphididae) in Oregon Hop yards

USDA-ARS?s Scientific Manuscript database

The temporal development of biological control of arthropod pests in perennial cropping systems is largely unreported. In this study, the development of biological control of twospotted spider mite, Tetranychus urticae Koch and hop aphid, Phorodon humuli (Schrank) in a new planting of hop in Oregon...

The Biology and Evolution of Music: A Comparative Perspective

ERIC Educational Resources Information Center

Fitch, W. Tecumseh

2006-01-01

Studies of the biology of music (as of language) are highly interdisciplinary and demand the integration of diverse strands of evidence. In this paper, I present a comparative perspective on the biology and evolution of music, stressing the value of comparisons both with human language, and with those animal communication systems traditionally…

A Best-Practice Model for Academic Advising of University Biology Majors

ERIC Educational Resources Information Center

Heekin, Jonathan Ralph Calvin

2013-01-01

Biology faculty at an East Coast university believed their undergraduate students were not being well served by the existing academic advising program. The purpose of this mixed methods project study was to evaluate the effectiveness of the academic advising model in a biology department. Guided by system-based organizational theory, a learning…

The biological microprocessor, or how to build a computer with biological parts

PubMed Central

Moe-Behrens, Gerd HG

2013-01-01

Systemics, a revolutionary paradigm shift in scientific thinking, with applications in systems biology, and synthetic biology, have led to the idea of using silicon computers and their engineering principles as a blueprint for the engineering of a similar machine made from biological parts. Here we describe these building blocks and how they can be assembled to a general purpose computer system, a biological microprocessor. Such a system consists of biological parts building an input / output device, an arithmetic logic unit, a control unit, memory, and wires (busses) to interconnect these components. A biocomputer can be used to monitor and control a biological system. PMID:24688733

Method for photo-altering a biological system to improve biological effect

DOEpatents

Hill, Richard A.; Doiron, Daniel R.; Crean, David H.

2000-08-01

Photodynamic therapy is a new adjunctive therapy for filtration surgery that does not use chemotherapy agents or radiation, but uses pharmacologically-active sensitizing compounds to produce a titratable, localized, transient, post operative avascular conjunctiva. A photosensitizing agent in a biological system is selectively activated by delivering the photosensitive agent to the biological system and laser activating only a spatially selected portion of the delivered photosensitive agent. The activated portion of the photosensitive agent reacts with the biological system to obtain a predetermined biological effect. As a result, an improved spatial disposition and effectuation of the biological effect by the photosensitive agent in the biological system is achieved.

A system for success: BMC Systems Biology, a new open access journal.

PubMed

Hodgkinson, Matt J; Webb, Penelope A

2007-09-04

BMC Systems Biology is the first open access journal spanning the growing field of systems biology from molecules up to ecosystems. The journal has launched as more and more institutes are founded that are similarly dedicated to this new approach. BMC Systems Biology builds on the ongoing success of the BMC series, providing a venue for all sound research in the systems-level analysis of biology.

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

Informing Biological Design by Integration of Systems and Synthetic Biology

PubMed Central

Smolke, Christina D.; Silver, Pamela A.

2011-01-01

Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields. PMID:21414477

Structural and practical identifiability analysis of S-system.

PubMed

Zhan, Choujun; Li, Benjamin Yee Shing; Yeung, Lam Fat

2015-12-01

In the field of systems biology, biological reaction networks are usually modelled by ordinary differential equations. A sub-class, the S-systems representation, is a widely used form of modelling. Existing S-systems identification techniques assume that the system itself is always structurally identifiable. However, due to practical limitations, biological reaction networks are often only partially measured. In addition, the captured data only covers a limited trajectory, therefore data can only be considered as a local snapshot of the system responses with respect to the complete set of state trajectories over the entire state space. Hence the estimated model can only reflect partial system dynamics and may not be unique. To improve the identification quality, the structural and practical identifiablility of S-system are studied. The S-system is shown to be identifiable under a set of assumptions. Then, an application on yeast fermentation pathway was conducted. Two case studies were chosen; where the first case is based on a larger state trajectories and the second case is based on a smaller one. By expanding the dataset which span a relatively larger state space, the uncertainty of the estimated system can be reduced. The results indicated that initial concentration is related to the practical identifiablity.

Cross-hierarchy systems principles.

PubMed

Goentoro, Lea

2017-02-01

One driving motivation of systems biology is the search for general principles that govern the design of biological systems. But questions often arise as to what kind of general principles biology could have. Concepts from engineering such as robustness and modularity are indeed becoming a regular way of describing biological systems. Another source of potential general principles is the emerging similarities found in processes across biological hierarchies. In this piece, I describe several emerging cross-hierarchy similarities. Identification of more cross-hierarchy principles, and understanding the implications these convergence have on the construction of biological systems, I believe, present exciting challenges for systems biology in the decades to come.

EPR spectroscopy of complex biological iron-sulfur systems.

PubMed

Hagen, Wilfred R

2018-02-21

From the very first discovery of biological iron-sulfur clusters with EPR, the spectroscopy has been used to study not only purified proteins but also complex systems such as respiratory complexes, membrane particles and, later, whole cells. In recent times, the emphasis of iron-sulfur biochemistry has moved from characterization of individual proteins to the systems biology of iron-sulfur biosynthesis, regulation, degradation, and implications for human health. Although this move would suggest a blossoming of System-EPR as a specific, non-invasive monitor of Fe/S (dys)homeostasis in whole cells, a review of the literature reveals limited success possibly due to technical difficulties in adherence to EPR spectroscopic and biochemical standards. In an attempt to boost application of System-EPR the required boundary conditions and their practical applications are explicitly and comprehensively formulated.

Rapid Startup and Loading of an Attached Growth, Simultaneous Nitrification/Denitrification Membrane Aerated Bioreactor

NASA Technical Reports Server (NTRS)

Meyer, Caitlin; Vega, Leticia

2014-01-01

The Membrane Aerated Bioreactor (MABR) is an attached-growth biological system for simultaneous nitrification and denitrification. This design is an innovative approach to common terrestrial wastewater treatments for nitrogen and carbon removal. Implementing a biologically-based water treatment system for long-duration human exploration is an attractive, low energy alternative to physiochemical processes. Two obstacles to implementing such a system are (1) the "start-up" duration from inoculation to steady-state operations and (2) the amount of surface area needed for the biological activity to occur. The Advanced Water Recovery Systems (AWRS) team at JSC explored these two issues through two tests; a rapid inoculation study and a wastewater loading study. Results from these tests demonstrate that the duration from inoculation to steady state can be reduced to two weeks and that the surface area to volume ratio baseline used in the Alternative Water Processor (AWP) test was higher than what was needed to remove the organic carbon and ammonium from the system.

Agent-Based Modeling in Molecular Systems Biology.

PubMed

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-07-01

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

[Chronobiology of immune system].

PubMed

Trufakin, V A; Shurlygina, A V; Dergacheva, T I; Litvinenko, G I; Verbitskaia, L V

1999-01-01

The biological rhythmological programme of the immune system is a constituent of the body's common biological rhythmological programme. Its pattern seems to be genetically determined and reflects the functional status of the system. The chronobiological mechanisms responsible for the regulation of immune functions lie in the presence of certain phasic interrelations between the biological rhythms of the synthesis and production of regulatory agents on the one hand, and those of the receptor system and metabolic potential of immunocompetent cells on the other. The facts given in the paper may be a basis for a chronobiological approach to better understanding the mechanisms of the physiology and pathology of the immune system. The medical significance of study of the structural and temporal pattern of the immune system consists in the development of new techniques for diagnosis, prognosis, therapy, and assessment of risk factors in immunopathological conditions.

State-of-the-art exposure chamber for highly controlled and reproducible THz biological effects studies

NASA Astrophysics Data System (ADS)

Cerna, Cesario Z.; Elam, David P.; Echchgadda, Ibtissam; Sloan, Mark A.; Wilmink, Gerald J.

2014-03-01

Terahertz (THz) imaging and sensing technologies are increasingly being used at international airports for security screening purposes and at major medical centers for cancer and burn diagnosis. The emergence of new THz applications has directly resulted in an increased interest regarding the biological effects associated with this frequency range. Knowledge of THz biological effects is also desired for the safe use of THz systems, identification of health hazards, and development of empirically-based safety standards. In this study, we developed a state-of-the-art exposure chamber that allowed for highly controlled and reproducible studies of THz biological effects. This innovative system incorporated an industry grade cell incubator system that permitted a highly controlled exposure environment, where temperatures could be maintained at 37 °C +/- 0.1 °C, carbon dioxide (CO2) levels at 5% +/- 0.1%, and relative humidity (RH) levels at 95% +/- 1%. To maximize the THz power transmitted to the cell culture region inside the humid incubator, a secondary custom micro-chamber was fabricated and incorporated into the system. This micro-chamber shields the THz beam from the incubator environment and could be nitrogen-purged to eliminate water absorption effects. Additionally, a microscope that allowed for real-time visualization of the live cells before, during, and after THz exposure was integrated into the exposure system.

Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability

PubMed Central

Pathak, Rajesh Kumar; Gupta, Sanjay Mohan; Gaur, Vikram Singh; Pandey, Dinesh

2015-01-01

Abstract In recent years, rapid developments in several omics platforms and next generation sequencing technology have generated a huge amount of biological data about plants. Systems biology aims to develop and use well-organized and efficient algorithms, data structure, visualization, and communication tools for the integration of these biological data with the goal of computational modeling and simulation. It studies crop plant systems by systematically perturbing them, checking the gene, protein, and informational pathway responses; integrating these data; and finally, formulating mathematical models that describe the structure of system and its response to individual perturbations. Consequently, systems biology approaches, such as integrative and predictive ones, hold immense potential in understanding of molecular mechanism of agriculturally important complex traits linked to agricultural productivity. This has led to identification of some key genes and proteins involved in networks of pathways involved in input use efficiency, biotic and abiotic stress resistance, photosynthesis efficiency, root, stem and leaf architecture, and nutrient mobilization. The developments in the above fields have made it possible to design smart crops with superior agronomic traits through genetic manipulation of key candidate genes. PMID:26484978

Toxicity of silver nanoparticles in biological systems: Does the complexity of biological systems matter?

PubMed

Vazquez-Muñoz, Roberto; Borrego, Belen; Juárez-Moreno, Karla; García-García, Maritza; Mota Morales, Josué D; Bogdanchikova, Nina; Huerta-Saquero, Alejandro

2017-07-05

Currently, nanomaterials are more frequently in our daily life, specifically in biomedicine, electronics, food, textiles and catalysis just to name a few. Although nanomaterials provide many benefits, recently their toxicity profiles have begun to be explored. In this work, the toxic effects of silver nanoparticles (35nm-average diameter and Polyvinyl-Pyrrolidone-coated) on biological systems of different levels of complexity was assessed in a comprehensive and comparatively way, through a variety of viability and toxicological assays. The studied organisms included viruses, bacteria, microalgae, fungi, animal and human cells (including cancer cell lines). It was found that biological systems of different taxonomical groups are inhibited at concentrations of silver nanoparticles within the same order of magnitude. Thus, the toxicity of nanomaterials on biological/living systems, constrained by their complexity, e.g. taxonomic groups, resulted contrary to the expected. The fact that cells and virus are inhibited with a concentration of silver nanoparticles within the same order of magnitude could be explained considering that silver nanoparticles affects very primitive cellular mechanisms by interacting with fundamental structures for cells and virus alike. Copyright © 2017 Elsevier B.V. All rights reserved.

Generative mechanistic explanation building in undergraduate molecular and cellular biology

NASA Astrophysics Data System (ADS)

Southard, Katelyn M.; Espindola, Melissa R.; Zaepfel, Samantha D.; Bolger, Molly S.

2017-09-01

When conducting scientific research, experts in molecular and cellular biology (MCB) use specific reasoning strategies to construct mechanistic explanations for the underlying causal features of molecular phenomena. We explored how undergraduate students applied this scientific practice in MCB. Drawing from studies of explanation building among scientists, we created and applied a theoretical framework to explore the strategies students use to construct explanations for 'novel' biological phenomena. Specifically, we explored how students navigated the multi-level nature of complex biological systems using generative mechanistic reasoning. Interviews were conducted with introductory and upper-division biology students at a large public university in the United States. Results of qualitative coding revealed key features of students' explanation building. Students used modular thinking to consider the functional subdivisions of the system, which they 'filled in' to varying degrees with mechanistic elements. They also hypothesised the involvement of mechanistic entities and instantiated abstract schema to adapt their explanations to unfamiliar biological contexts. Finally, we explored the flexible thinking that students used to hypothesise the impact of mutations on multi-leveled biological systems. Results revealed a number of ways that students drew mechanistic connections between molecules, functional modules (sets of molecules with an emergent function), cells, tissues, organisms and populations.

Cardiovascular safety of biologic therapies for the treatment of RA.

PubMed

Greenberg, Jeffrey D; Furer, Victoria; Farkouh, Michael E

2011-11-15

Cardiovascular disease represents a major source of extra-articular comorbidity in patients with rheumatoid arthritis (RA). A combination of traditional cardiovascular risk factors and RA-related factors accounts for the excess risk in RA. Among RA-related factors, chronic systemic inflammation has been implicated in the pathogenesis and progression of atherosclerosis. A growing body of evidence--mainly derived from observational databases and registries--suggests that specific RA therapies, including methotrexate and anti-TNF biologic agents, can reduce the risk of future cardiovascular events in patients with RA. The cardiovascular profile of other biologic therapies for the treatment of RA has not been adequately studied, including of investigational drugs that improve systemic inflammation but alter traditional cardiovascular risk factors. In the absence of large clinical trials adequately powered to detect differences in cardiovascular events between biologic drugs in RA, deriving firm conclusions on cardiovascular safety is challenging. Nevertheless, observational research using large registries has emerged as a promising approach to study the cardiovascular risk of emerging RA biologic therapies.

Bone effects of biologic drugs in rheumatoid arthritis.

PubMed

Corrado, Addolorata; Neve, Anna; Maruotti, Nicola; Cantatore, Francesco Paolo

2013-01-01

Biologic agents used in the treatment of rheumatoid arthritis (RA) are able to reduce both disease activity and radiographic progression of joint disease. These drugs are directed against several proinflammatory cytokines (TNF α , IL-6, and IL-1) which are involved both in the pathogenesis of chronic inflammation and progression of joint structural damage and in systemic and local bone loss typically observed in RA. However, the role of biologic drugs in preventing bone loss in clinical practice has not yet clearly assessed. Many clinical studies showed a trend to a positive effect of biologic agents in preventing systemic bone loss observed in RA. Although the suppression of inflammation is the main goal in the treatment of RA and the anti-inflammatory effects of biologic drugs exert a positive effect on bone metabolism, the exact relationship between the prevention of bone loss and control of inflammation has not been clearly established, and if the available biologic drugs against TNF α , IL-1, and IL-6 can exert their effect on systemic and local bone loss also through a direct mechanism on bone cell metabolism is still to be clearly defined.

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.

Molecular Force Spectroscopy on Cells

NASA Astrophysics Data System (ADS)

Liu, Baoyu; Chen, Wei; Zhu, Cheng

2015-04-01

Molecular force spectroscopy has become a powerful tool to study how mechanics regulates biology, especially the mechanical regulation of molecular interactions and its impact on cellular functions. This force-driven methodology has uncovered a wealth of new information of the physical chemistry of molecular bonds for various biological systems. The new concepts, qualitative and quantitative measures describing bond behavior under force, and structural bases underlying these phenomena have substantially advanced our fundamental understanding of the inner workings of biological systems from the nanoscale (molecule) to the microscale (cell), elucidated basic molecular mechanisms of a wide range of important biological processes, and provided opportunities for engineering applications. Here, we review major force spectroscopic assays, conceptual developments of mechanically regulated kinetics of molecular interactions, and their biological relevance. We also present current challenges and highlight future directions.

Mathematics for understanding disease.

PubMed

Bies, R R; Gastonguay, M R; Schwartz, S L

2008-06-01

The application of mathematical models to reflect the organization and activity of biological systems can be viewed as a continuum of purpose. The far left of the continuum is solely the prediction of biological parameter values, wherein an understanding of the underlying biological processes is irrelevant to the purpose. At the far right of the continuum are mathematical models, the purposes of which are a precise understanding of those biological processes. No models in present use fall at either end of the continuum. Without question, however, the emphasis in regards to purpose has been on prediction, e.g., clinical trial simulation and empirical disease progression modeling. Clearly the model that ultimately incorporates a universal understanding of biological organization will also precisely predict biological events, giving the continuum the logical form of a tautology. Currently that goal lies at an immeasurable distance. Nonetheless, the motive here is to urge movement in the direction of that goal. The distance traveled toward understanding naturally depends upon the nature of the scientific question posed with respect to comprehending and/or predicting a particular disease process. A move toward mathematical models implies a move away from static empirical modeling and toward models that focus on systems biology, wherein modeling entails the systematic study of the complex pattern of organization inherent in biological systems.

Systems Proteomics for Translational Network Medicine

PubMed Central

Arrell, D. Kent; Terzic, Andre

2012-01-01

Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis. PMID:22896016

The "What Is a System" Reflection Interview as a Knowledge Integration Activity for High School Students' Understanding of Complex Systems in Human Biology

ERIC Educational Resources Information Center

Tripto, Jaklin; Ben-Zvi Assaraf, Orit; Snapir, Zohar; Amit, Miriam

2016-01-01

This study examined the reflection interview as a tool for assessing and facilitating the use of "systems language" amongst 11th grade students who have recently completed their first year of high school biology. Eighty-three students composed two concept maps in the 10th grade--one at the beginning of the school year and one at its end.…

Carbon dioxide evolution rate as a method to monitor and control an aerobic biological waste treatment system

NASA Technical Reports Server (NTRS)

Lee, S. S.; Shuler, M. L.

1986-01-01

An experimental system was developed to study the microbial growth kinetic of an undefined mixed culture in an erobic biological waste treatment process. The experimental results were used to develop a mathematical model that can predict the performance of a bioreactor. The bioreactor will be used to regeneratively treat waste material which is expected to be generated during a long term manned space mission. Since the presence of insoluble particles in the chemically undefined complex media made estimating biomass very difficult in the real system, a clean system was devised to study the microbial growth from the soluble substrate.

Synthetic Nanoelectronic Probes for Biological Cells and Tissue

PubMed Central

2013-01-01

Research at the interface between nanoscience and biology has the potential to produce breakthroughs in fundamental science and lead to revolutionary technologies. In this review, we focus on nanoelectronic/biological interfaces. First, we discuss nanoscale field effect transistors (nanoFETs) as probes to study cellular systems, including the realization of nanoFET comparable in size to biological nanostructures involved in communication using synthesized nanowires. Second, we overview current progress in multiplexed extracellular sensing using planar nanoFET arrays. Third, we describe the design and implementation of three distinct nanoFETs used to realize the first intracellular electrical recording from single cells. Fourth, we present recent progress in merging electronic and biological systems at the 3D tissue level by using macroporous nanoelectronic scaffolds. Finally, we discuss future development in this research area, the unique challenges and opportunities, and the tremendous impact these nanoFET based technologies might have in advancing biology and medical sciences. PMID:23451719

A Converter from the Systems Biology Markup Language to the Synthetic Biology Open Language.

PubMed

Nguyen, Tramy; Roehner, Nicholas; Zundel, Zach; Myers, Chris J

2016-06-17

Standards are important to synthetic biology because they enable exchange and reproducibility of genetic designs. This paper describes a procedure for converting between two standards: the Systems Biology Markup Language (SBML) and the Synthetic Biology Open Language (SBOL). SBML is a standard for behavioral models of biological systems at the molecular level. SBOL describes structural and basic qualitative behavioral aspects of a biological design. Converting SBML to SBOL enables a consistent connection between behavioral and structural information for a biological design. The conversion process described in this paper leverages Systems Biology Ontology (SBO) annotations to enable inference of a designs qualitative function.

I-DIRT, a general method for distinguishing between specific and nonspecific protein interactions.

PubMed

Tackett, Alan J; DeGrasse, Jeffrey A; Sekedat, Matthew D; Oeffinger, Marlene; Rout, Michael P; Chait, Brian T

2005-01-01

Isolation of protein complexes via affinity-tagged proteins provides a powerful tool for studying biological systems, but the technique is often compromised by co-enrichment of nonspecifically interacting proteins. We describe a new technique (I-DIRT) that distinguishes contaminants from bona fide interactors in immunopurifications, overcoming this most challenging problem in defining protein complexes. I-DIRT will be of broad value for studying protein complexes in biological systems that can be metabolically labeled.

Single molecule tools for enzymology, structural biology, systems biology and nanotechnology: an update

PubMed Central

Widom, Julia R.; Dhakal, Soma; Heinicke, Laurie A.; Walter, Nils G.

2015-01-01

Toxicology is the highly interdisciplinary field studying the adverse effects of chemicals on living organisms. It requires sensitive tools to detect such effects. After their initial implementation during the 1990s, single-molecule fluorescence detection tools were quickly recognized for their potential to contribute greatly to many different areas of scientific inquiry. In the intervening time, technical advances in the field have generated ever-improving spatial and temporal resolution, and have enabled the application of single-molecule fluorescence to increasingly complex systems, such as live cells. In this review, we give an overview of the optical components necessary to implement the most common versions of single-molecule fluorescence detection. We then discuss current applications to enzymology and structural studies, systems biology, and nanotechnology, presenting the technical considerations that are unique to each area of study, along with noteworthy recent results. We also highlight future directions that have the potential to revolutionize these areas of study by further exploiting the capabilities of single-molecule fluorescence microscopy. PMID:25212907

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Computational systems chemical biology.

PubMed

Oprea, Tudor I; May, Elebeoba E; Leitão, Andrei; Tropsha, Alexander

2011-01-01

There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology (SCB) (Nat Chem Biol 3: 447-450, 2007).The overarching goal of computational SCB is to develop tools for integrated chemical-biological data acquisition, filtering and processing, by taking into account relevant information related to interactions between proteins and small molecules, possible metabolic transformations of small molecules, as well as associated information related to genes, networks, small molecules, and, where applicable, mutants and variants of those proteins. There is yet an unmet need to develop an integrated in silico pharmacology/systems biology continuum that embeds drug-target-clinical outcome (DTCO) triplets, a capability that is vital to the future of chemical biology, pharmacology, and systems biology. Through the development of the SCB approach, scientists will be able to start addressing, in an integrated simulation environment, questions that make the best use of our ever-growing chemical and biological data repositories at the system-wide level. This chapter reviews some of the major research concepts and describes key components that constitute the emerging area of computational systems chemical biology.

Computational Systems Chemical Biology

PubMed Central

Oprea, Tudor I.; May, Elebeoba E.; Leitão, Andrei; Tropsha, Alexander

2013-01-01

There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically-based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology, SCB (Oprea et al., 2007). The overarching goal of computational SCB is to develop tools for integrated chemical-biological data acquisition, filtering and processing, by taking into account relevant information related to interactions between proteins and small molecules, possible metabolic transformations of small molecules, as well as associated information related to genes, networks, small molecules and, where applicable, mutants and variants of those proteins. There is yet an unmet need to develop an integrated in silico pharmacology / systems biology continuum that embeds drug-target-clinical outcome (DTCO) triplets, a capability that is vital to the future of chemical biology, pharmacology and systems biology. Through the development of the SCB approach, scientists will be able to start addressing, in an integrated simulation environment, questions that make the best use of our ever-growing chemical and biological data repositories at the system-wide level. This chapter reviews some of the major research concepts and describes key components that constitute the emerging area of computational systems chemical biology. PMID:20838980

NEURODEVELOPMENTAL BIOLOGY ASSOCIATED WITH CHILDHOOD SEXUAL ABUSE

PubMed Central

De Bellis, Michael D.; Spratt, Eve G.; Hooper, Stephen R.

2013-01-01

Child maltreatment appears to be the single most preventable cause of mental illness and behavioral dysfunction in the US. There are few published studies examining the developmental and the psychobiological consequences of sexual abuse. There are multiple mechanisms through which sexual abuse can cause PTSD, activate biological stress response systems, and contribute to adverse brain development. This article will critically review the psychiatric problems associated with maltreatment and the emerging biologic stress system research with a special emphasis on what is known about victimization by sexual abuse. PMID:21970646

The pedestrian watchmaker: Genetic clocks from engineered oscillators

PubMed Central

Cookson, Natalie A.; Tsimring, Lev S.; Hasty, Jeff

2010-01-01

The crucial role of time-keeping has required organisms to develop sophisticated regulatory networks to ensure the reliable propagation of periodic behavior. These biological clocks have long been a focus of research; however, a clear understanding of how they maintain oscillations in the face of unpredictable environments and the inherent noise of biological systems remains elusive. Here, we review the current understanding of circadian oscillations using Drosophila melanogaster as a typical example and discuss the utility of an alternative synthetic biology approach to studying these highly intricate systems. PMID:19903483

Evolutionary biology through the lens of budding yeast comparative genomics.

PubMed

Marsit, Souhir; Leducq, Jean-Baptiste; Durand, Éléonore; Marchant, Axelle; Filteau, Marie; Landry, Christian R

2017-10-01

The budding yeast Saccharomyces cerevisiae is a highly advanced model system for studying genetics, cell biology and systems biology. Over the past decade, the application of high-throughput sequencing technologies to this species has contributed to this yeast also becoming an important model for evolutionary genomics. Indeed, comparative genomic analyses of laboratory, wild and domesticated yeast populations are providing unprecedented detail about many of the processes that govern evolution, including long-term processes, such as reproductive isolation and speciation, and short-term processes, such as adaptation to natural and domestication-related environments.

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

Wireless Biological Electronic Sensors.

PubMed

Cui, Yue

2017-10-09

The development of wireless biological electronic sensors could open up significant advances for both fundamental studies and practical applications in a variety of areas, including medical diagnosis, environmental monitoring, and defense applications. One of the major challenges in the development of wireless bioelectronic sensors is the successful integration of biosensing units and wireless signal transducers. In recent years, there are a few types of wireless communication systems that have been integrated with biosensing systems to construct wireless bioelectronic sensors. To successfully construct wireless biological electronic sensors, there are several interesting questions: What types of biosensing transducers can be used in wireless bioelectronic sensors? What types of wireless systems can be integrated with biosensing transducers to construct wireless bioelectronic sensors? How are the electrical sensing signals generated and transmitted? This review will highlight the early attempts to address these questions in the development of wireless biological electronic sensors.

Soil Biological Activity Contributing to Phosphorus Availability in Vertisols under Long-Term Organic and Conventional Agricultural Management

PubMed Central

Bhat, Nisar A.; Riar, Amritbir; Ramesh, Aketi; Iqbal, Sanjeeda; Sharma, Mahaveer P.; Sharma, Sanjay K.; Bhullar, Gurbir S.

2017-01-01

Mobilization of unavailable phosphorus (P) to plant available P is a prerequisite to sustain crop productivity. Although most of the agricultural soils have sufficient amounts of phosphorus, low availability of native soil P remains a key limiting factor to increasing crop productivity. Solubilization and mineralization of applied and native P to plant available form is mediated through a number of biological and biochemical processes that are strongly influenced by soil carbon/organic matter, besides other biotic and abiotic factors. Soils rich in organic matter are expected to have higher P availability potentially due to higher biological activity. In conventional agricultural systems mineral fertilizers are used to supply P for plant growth, whereas organic systems largely rely on inputs of organic origin. The soils under organic management are supposed to be biologically more active and thus possess a higher capability to mobilize native or applied P. In this study we compared biological activity in soil of a long-term farming systems comparison field trial in vertisols under a subtropical (semi-arid) environment. Soil samples were collected from plots under 7 years of organic and conventional management at five different time points in soybean (Glycine max) -wheat (Triticum aestivum) crop sequence including the crop growth stages of reproductive significance. Upon analysis of various soil biological properties such as dehydrogenase, β-glucosidase, acid and alkaline phosphatase activities, microbial respiration, substrate induced respiration, soil microbial biomass carbon, organically managed soils were found to be biologically more active particularly at R2 stage in soybean and panicle initiation stage in wheat. We also determined the synergies between these biological parameters by using the methodology of principle component analysis. At all sampling points, P availability in organic and conventional systems was comparable. Our findings clearly indicate that owing to higher biological activity, organic systems possess equal capabilities of supplying P for crop growth as are conventional systems with inputs of mineral P fertilizers. PMID:28928758

Diagnostic of students' misconceptions using the Biological Concepts Instrument (BCI): A method for conducting an educational needs assessment

PubMed Central

Champagne Queloz, Annie; Klymkowsky, Michael W.; Stern, Elsbeth; Hafen, Ernst; Köhler, Katja

2017-01-01

Concept inventories, constructed based on an analysis of students’ thinking and their explanations of scientific situations, serve as diagnostics for identifying misconceptions and logical inconsistencies and provide data that can help direct curricular reforms. In the current project, we distributed the Biological Concepts Instrument (BCI) to 17-18-year-old students attending the highest track of the Swiss school system (Gymnasium). Students’ performances on many questions related to evolution, genetics, molecular properties and functions were diverse. Important common misunderstandings were identified in the areas of evolutionary processes, molecular properties and an appreciation of stochastic processes in biological systems. Our observations provide further evidence that the BCI is efficient in identifying specific areas where targeted instruction is required. Based on these observations we have initiated changes at several levels to reconsider how biological systems are presented to university biology studies with the goal of improving student’s foundational understanding. PMID:28493960

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.

Hybrid semi-parametric mathematical systems: bridging the gap between systems biology and process engineering.

PubMed

Teixeira, Ana P; Carinhas, Nuno; Dias, João M L; Cruz, Pedro; Alves, Paula M; Carrondo, Manuel J T; Oliveira, Rui

2007-12-01

Systems biology is an integrative science that aims at the global characterization of biological systems. Huge amounts of data regarding gene expression, proteins activity and metabolite concentrations are collected by designing systematic genetic or environmental perturbations. Then the challenge is to integrate such data in a global model in order to provide a global picture of the cell. The analysis of these data is largely dominated by nonparametric modelling tools. In contrast, classical bioprocess engineering has been primarily founded on first principles models, but it has systematically overlooked the details of the embedded biological system. The full complexity of biological systems is currently assumed by systems biology and this knowledge can now be taken by engineers to decide how to optimally design and operate their processes. This paper discusses possible methodologies for the integration of systems biology and bioprocess engineering with emphasis on applications involving animal cell cultures. At the mathematical systems level, the discussion is focused on hybrid semi-parametric systems as a way to bridge systems biology and bioprocess engineering.

A subcontinental view of forest plant invasions

Treesearch

Christopher M. Oswalt; Songlin Fei; Qinfeng Guo; Basil V. Iannone III; Sonja N. Oswalt; Bryan C. Pijanowski; Kevin M. Potter

2015-01-01

Over the last few decades, considerable attention has focused on small-scale studies of invasive plants and invaded systems. Unfortunately, small scale studies rarely provide comprehensive insight into the complexities of biological invasions at macroscales. Systematic and repeated monitoring of biological invasions at broad scales are rare. In this report, we...

Environmental and Ecology Branch Progress Report, 1974 through 1976 Volume 2

DTIC Science & Technology

1978-06-01

nitrogen wastes generated by manufacture of Army explosives have been studied with reqard to aeration rates, residence times, nutrient requirements...STATES ...... ....... .......................... .. 18 vii BIOLOGICAL TREATMENT OF EXPLOSIVE WASTES ..... ............. ... 19 BIOLOGICAL AEROSOLS...1976, and the information was forwarded to Chemical Systems Laboratory for inclusion in the final report to ERDA. 13 BIOLOGICAL TREATMENT OF EXPLOSIVE

Summary Report: Pilot Study of an Innovative Biological Treatment Process for the Removal of Ammonia from a Small Drinking Water System

EPA Science Inventory

The use of biologically active filtration to oxidize ammonia as a full-scale drinking water treatment process has not been thoroughly considered in the United States. A number of concerns with biological water treatment exist including the potential release of excessive numbers o...

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

ERIC Educational Resources Information Center

Bardi, Lara; Regolin, Lucia; Simion, Francesca

2011-01-01

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

Exploring the MACH Model's Potential as a Metacognitive Tool to Help Undergraduate Students Monitor Their Explanations of Biological Mechanisms

ERIC Educational Resources Information Center

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

When undergraduate biology students learn to explain biological mechanisms, they face many challenges and may overestimate their understanding of living systems. Previously, we developed the MACH model of four components used by expert biologists to explain mechanisms: Methods, Analogies, Context, and How. This study explores the implementation of…

A Systems Approach to Exposure Modeling (ExpoCast)(FutureTox3)

EPA Science Inventory

Systems Biology might be described as the understanding of how interactions on multiple scales integrate into a homeostatic system. Systems Toxicology could then be the study of the impact of chemical perturbations of homeostasis. Systems exposure might then be the study of the i...

Informing biological design by integration of systems and synthetic biology.

PubMed

Smolke, Christina D; Silver, Pamela A

2011-03-18

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

Systems biology approaches to evaluate arsenic toxicity and carcinogenicity: an overview.

PubMed

Bhattacharjee, Pritha; Chatterjee, Debmita; Singh, Keshav K; Giri, Ashok K

2013-08-01

Long term exposure to arsenic, either through groundwater, food stuff or occupational sources, results in a plethora of dermatological and non-dermatological health effects including multi-organ cancer and early mortality. Several epidemiological studies, across the globe have reported arsenic-induced health effects and cancerous outcomes; but the prevalence of such diseases varies depending on environmental factors (geographical location, exposure level), and genetic makeup (and variants thereof); which is further modulated by several other factors like ethnicity, age-sex, smoking status, diet, etc. It is also interesting to note that, chronic arsenic exposure to a similar extent, even among the same family members, result in wide inter-individual variations. To understand the adverse effect of this toxic metabolite on biological system (cellular targets), and to unravel the underlying molecular basis (at the level of transcript, proteome, or metabolite), a holistic, systems biology approach was taken. Due to the paradoxical nature and unavailability of any suitable animal model system; the literature review is primarily based on cell line and population based studies. Thus, here we present a comprehensive review on the systems biology approaches to explore the underlying mechanism of arsenic-induced carcinogenicity, along with our own observations and an overview of mitigation strategies and their effectiveness till date. Copyright © 2013 Elsevier GmbH. All rights reserved.

Maze learning by a hybrid brain-computer system

NASA Astrophysics Data System (ADS)

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system.

PubMed

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-13

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system

PubMed Central

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-01-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation. PMID:27619326

Distribution and Biological Effects of Nanoparticles in the Reproductive System.

PubMed

Liu, Ying; Li, Hongxia; Xiao, Kai

2016-01-01

Nanoparticles have shown great potential in biomedical applications such as imaging probes and drug delivery. However, the increasing use of nanoparticles has raised concerns about their adverse effects on human health and environment. Reproductive tissues and gametes represent highly delicate biological systems with the essential function of transmitting genetic information to the offspring, which is highly sensitive to environmental toxicants. This review aims to summarzie the penetration of physiological barriers (blood-testis barrier and placental barrier), distribution and biological effects of nanoparticles in the reproductive system, which is essential to control the beneficial effects of nanoparticles applications and to avoid their adverse effects on the reproductive system. We referred to a large number of relevant peer-reviewed research articles about the reproductive toxicity of nanoparticles. The comprehensive information was summarized into two parts: physiological barrier penetration and biological effects of nanoparticles in male or female reproductive system; distribution and metabolism of nanoparticles in the reproductive system. The representative examples were also presented in four tables. The in vitro and in vivo studies imply that some nanoparticles are able to cross the blood-testis barrier or placental barrier, and their penetration depends on the physicochemical characteristics of nanoparticles (e.g., composition, shape, particle size and surface coating). The toxicity assays indicate that nanoparticles might induce adverse physiological effects and impede fertility or embryogenesis. The barrier penetration, adverse physiological effects, distribution and metabolism are closely related to physicochemical characteristics of nanoparticles. Further systematic and mechanistic studies using well-characterized nanoparticles, relevant administration routes, and doses relevant to the expected exposure level are required to improve our understanding of biological effects of nanoparticles on the reproductive system.

Description of Patients Treated with Biologic Drugs as First-Line Systemic Therapy in the BIOBADADERM Registry Between 2008 and 2016.

PubMed

Carretero Hernández, G; Ferrándiz, C; Rivera Díaz, R; Daudén Tello, E; de la Cueva-Dobao, P; Gómez-García, F J; Herrera-Ceballos, E; Belinchón Romero, I; López-Estebaranz, J L; Alsina Gibert, M; Sánchez-Carazo, J L; Ferrán Farrés, M; González Quesada, A; Carrascosa Carrillo, J M; Llamas-Velasco, M; Mendiola Fernández, M V; Ruiz Genao, D; Muñoz Santos, C; García-Doval, I; Descalzo, M A

2018-06-07

Biologic drugs are usually prescribed as second-line treatment for psoriasis, that is, after the patient has first been treated with a conventional psoriasis drug. There are, however, cases where, depending on the characteristics of the patient or the judgement of the physician, biologics may be chosen as first-line therapy. No studies to date have analyzed the demographics or clinical characteristics of patients in this setting or the safety profile of the agents used. The main aim of this study was to characterize these aspects of first-line biologic therapy and compare them to those observed for patients receiving biologics as second-line therapy. We conducted an observational study of 181 patients treated in various centers with a systemic biologic drug as first-line treatment for moderate to severe psoriasis between January 2008 and November 2016. All the patients were registered in the Spanish Registry of Adverse Events Associated with Biologic Drugs in Dermatology. The characteristics of the first- and second-line groups were very similar, although the patients receiving a biologic as first-line treatment for their psoriasis were older. No differences were observed for disease severity (assessed using the PASI) or time to diagnosis. Hypertension, diabetes, and liver disease were all more common in the first-line group. There were no differences between the groups in terms of reasons for drug withdrawal or occurrence of adverse effects. No major differences were found between patients with psoriasis receiving biologic drugs as first- or second-line therapy, a finding that provides further evidence of the safety of biologic therapy in patients with psoriasis. Publicado por Elsevier España, S.L.U.

Multidimensional approaches for studying plant defence against insects: from ecology to omics and synthetic biology.

PubMed

Barah, Pankaj; Bones, Atle M

2015-02-01

The biggest challenge for modern biology is to integrate multidisciplinary approaches towards understanding the organizational and functional complexity of biological systems at different hierarchies, starting from the subcellular molecular mechanisms (microscopic) to the functional interactions of ecological communities (macroscopic). The plant-insect interaction is a good model for this purpose with the availability of an enormous amount of information at the molecular and the ecosystem levels. Changing global climatic conditions are abruptly resetting plant-insect interactions. Integration of discretely located heterogeneous information from the ecosystem to genes and pathways will be an advantage to understand the complexity of plant-insect interactions. This review will present the recent developments in omics-based high-throughput experimental approaches, with particular emphasis on studying plant defence responses against insect attack. The review highlights the importance of using integrative systems approaches to study plant-insect interactions from the macroscopic to the microscopic level. We analyse the current efforts in generating, integrating and modelling multiomics data to understand plant-insect interaction at a systems level. As a future prospect, we highlight the growing interest in utilizing the synthetic biology platform for engineering insect-resistant plants. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Toxicology of organic-inorganic hybrid molecules: bio-organometallics and its toxicology.

PubMed

Fujie, Tomoya; Hara, Takato; Kaji, Toshiyuki

2016-01-01

Bio-organometallics is a research strategy of biology that uses organic-inorganic hybrid molecules. The molecules are expected to exhibit useful bioactivities based on the unique structure formed by interaction between the organic structure and intramolecular metal(s). However, studies on both biology and toxicology of organic-inorganic hybrid molecules have been incompletely performed. There can be two types of toxicological studies of bio-organometallics; one is evaluation of organic-inorganic hybrid molecules and the other is analysis of biological systems from the viewpoint of toxicology using organic-inorganic hybrid molecules. Our recent studies indicate that cytotoxicity of hybrid molecules containing a metal that is nontoxic in inorganic forms can be more toxic than that of hybrid molecules containing a metal that is toxic in inorganic forms when the structure of the ligand is the same. Additionally, it was revealed that organic-inorganic hybrid molecules are useful for analysis of biological systems important for understanding the toxicity of chemical compounds including heavy metals.

Frequency modulation atomic force microscopy: a dynamic measurement technique for biological systems

NASA Astrophysics Data System (ADS)

Higgins, Michael J.; Riener, Christian K.; Uchihashi, Takayuki; Sader, John E.; McKendry, Rachel; Jarvis, Suzanne P.

2005-03-01

Frequency modulation atomic force microscopy (FM-AFM) has been modified to operate in a liquid environment within an atomic force microscope specifically designed for investigating biological samples. We demonstrate the applicability of FM-AFM to biological samples using the spectroscopy mode to measure the unbinding forces of a single receptor-ligand (biotin-avidin) interaction. We show that quantitative adhesion force measurements can only be obtained provided certain modifications are made to the existing theory, which is used to convert the detected frequency shifts to an interaction force. Quantitative force measurements revealed that the unbinding forces for the biotin-avidin interaction were greater than those reported in previous studies. This finding was due to the use of high average tip velocities, which were calculated to be two orders of magnitude greater than those typically used in unbinding receptor-ligand experiments. This study therefore highlights the potential use of FM-AFM to study a range of biological systems, including living cells and/or single biomolecule interactions.

Genome Editing to Study Ca2+ Homeostasis in Zebrafish Cone Photoreceptors.

PubMed

Brockerhoff, Susan E

2017-01-01

Photoreceptors are specialized sensory neurons with unique biological features. Phototransduction is well understood due in part to the exclusive expression and function of the molecular components of this cascade. Many other processes are less well understood, but also extremely important for understanding photoreceptor function and for treating disease. One example is the role of Ca 2+ in the cell body and overall compartmentalization and regulation of Ca 2+ within the cell. The recent development of CRISPR/Cas9 genome editing techniques has made it possible to rapidly and cheaply alter specific genes. This will help to define the biological function of elusive processes that have been more challenging to study. CRISPR/Cas9 has been optimized in many systems including zebrafish, which already has some distinct advantages for studying photoreceptor biology and function. These new genome editing technologies and the continued use of the zebrafish model system will help advance our understanding of important understudied aspects of photoreceptor biology.

Analytic considerations and axiomatic approaches to the concept cell death and cell survival functions in biology and cancer treatment.

PubMed

Gkigkitzis, Ioannis; Haranas, Ioannis; Austerlitz, Carlos

2015-01-01

This study contains a discussion on the connection between current mathematical and biological modeling systems in response to the main research need for the development of a new mathematical theory for study of cell survival after medical treatment and cell biological behavior in general. This is a discussion of suggested future research directions and relations with interdisciplinary science. In an effort to establish the foundations for a possible framework that may be adopted to study and analyze the process of cell survival during treatment, we investigate the organic connection among an axiomatic system foundation, a predator-prey rate equation, and information theoretic signal processing. A new set theoretic approach is also introduced through the definition of cell survival units or cell survival units indicating the use of "proper classes" according to the Zermelo-Fraenkel set theory and the axiom of choice, as the mathematics appropriate for the development of biological theory of cell survival.

“Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases

PubMed Central

Gutierrez Najera, Nora A.; Resendis-Antonio, Osbaldo; Nicolini, Humberto

2017-01-01

The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder) will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome). In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention) that in turn are programmed by genes and influenced by environmental processes (epigenetic). Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity) or more than one disease (multimorbidity) adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics). The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed. PMID:28536537

Near-infrared Raman spectroscopy of single optically trapped biological cells

NASA Astrophysics Data System (ADS)

Xie, Changan; Dinno, Mumtaz A.; Li, Yong-Qing

2002-02-01

We report on the development and testing of a compact laser tweezers Raman spectroscopy (LTRS) system. The system combines optical trapping and near-infrared Raman spectroscopy for manipulation and identification of single biological cells in solution. A low-power diode laser at 785 nm was used for both trapping and excitation for Raman spectroscopy of the suspended microscopic particles. The design of the LTRS system provides high sensitivity and permits real-time spectroscopic measurements of the biological sample. The system was calibrated by use of polystyrene microbeads and tested on living blood cells and on both living and dead yeast cells. As expected, different images and Raman spectra were observed for the different cells. The LTRS system may provide a valuable tool for the study of fundamental cellular processes and the diagnosis of cellular disorders.

Two classes of bipartite networks: nested biological and social systems.

PubMed

Burgos, Enrique; Ceva, Horacio; Hernández, Laura; Perazzo, R P J; Devoto, Mariano; Medan, Diego

2008-10-01

Bipartite graphs have received some attention in the study of social networks and of biological mutualistic systems. A generalization of a previous model is presented, that evolves the topology of the graph in order to optimally account for a given contact preference rule between the two guilds of the network. As a result, social and biological graphs are classified as belonging to two clearly different classes. Projected graphs, linking the agents of only one guild, are obtained from the original bipartite graph. The corresponding evolution of its statistical properties is also studied. An example of a biological mutualistic network is analyzed in detail, and it is found that the model provides a very good fitting of all the main statistical features. The model also provides a proper qualitative description of the same features observed in social webs, suggesting the possible reasons underlying the difference in the organization of these two kinds of bipartite networks.

Systems biology approach to bioremediation

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

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

2012-06-01

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

Hierarchical structure of biological systems

PubMed Central

Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

2014-01-01

A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961

Hierarchical structure of biological systems: a bioengineering approach.

PubMed

Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

2014-01-01

A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems.

Mass fractionation processes of transition metal isotopes

NASA Astrophysics Data System (ADS)

Zhu, X. K.; Guo, Y.; Williams, R. J. P.; O'Nions, R. K.; Matthews, A.; Belshaw, N. S.; Canters, G. W.; de Waal, E. C.; Weser, U.; Burgess, B. K.; Salvato, B.

2002-06-01

Recent advances in mass spectrometry make it possible to utilise isotope variations of transition metals to address some important issues in solar system and biological sciences. Realisation of the potential offered by these new isotope systems however requires an adequate understanding of the factors controlling their isotope fractionation. Here we show the results of a broadly based study on copper and iron isotope fractionation during various inorganic and biological processes. These results demonstrate that: (1) naturally occurring inorganic processes can fractionate Fe isotope to a detectable level even at temperature ˜1000°C, which challenges the previous view that Fe isotope variations in natural system are unique biosignatures; (2) multiple-step equilibrium processes at low temperatures may cause large mass fractionation of transition metal isotopes even when the fractionation per single step is small; (3) oxidation-reduction is an importation controlling factor of isotope fractionation of transition metal elements with multiple valences, which opens a wide range of applications of these new isotope systems, ranging from metal-silicate fractionation in the solar system to uptake pathways of these elements in biological systems; (4) organisms incorporate lighter isotopes of transition metals preferentially, and transition metal isotope fractionation occurs stepwise along their pathways within biological systems during their uptake.

Population dynamics in controlled unsteady-state systems: An application to the degradation of glyphosate in a sequencing batch reactor

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

Devarakonda, M.S.

1988-01-01

Control over population dynamics and organism selection in a biological waste treatment system provides an effective means of engineering process efficiency. Examples of applications of organism selection include control of filamentous organisms, biological nutrient removal, industrial waste treatment requiring the removal of specific substrates, and hazardous waste treatment. Inherently, full scale biological waste treatment systems are unsteady state systems due to the variations in the waste streams and mass flow rates of the substrates. Some systems, however, have the capacity to impose controlled selective pressures on the biological population by means of their operation. An example of such a systemmore » is the Sequencing Batch Reactor (SBR) which was the experimental system utilized in this research work. The concepts of organism selection were studied in detail for the biodegradation of a herbicide waste stream, with glyphosate as the target compound. The SBR provided a reactor configuration capable of exerting the necessary selective pressures to select and enrich for a glyphosate degrading population. Based on results for bench scale SBRs, a hypothesis was developed to explain population dynamics in glyphosate degrading systems.« less

Degradation characteristics of 2,4-dichlorophenoxyacetic acid in electro-biological system.

PubMed

Zhang, Jingli; Cao, Zhanping; Zhang, Hongwei; Zhao, Lianmei; Sun, Xudong; Mei, Feng

2013-11-15

The reductive degradation of 2,4-dichlorophenoxyacetic acid (2,4-D) was studied in an electro-biological system, a biological system and an electric catalytic system, respectively. Electrochemical characteristics were monitored by cyclic voltammetry and the intermediate products of 2,4-D degradation were determined by high speed liquid chromatography (HPLC). The results showed that all 2,4-D degradations in the three systems conformed to the kinetics characteristics of one-order reaction, and the degradation kinetics constants were 28.74 × 10(-2) h(-1), 19.73 × 10(-2) h(-1) and 3.54 × 10(-2) h(-1), respectively. The kinetics constant in the electro-biological system was higher than the sum in the other two systems by 19%. The electrochemical assistance provided the electrons and accelerated the electron transfer rate in the microbial degradation of 2,4-D. The degradation resulted from the microbial reduction strengthened by the electrochemical assistance. The electron transfer existed between the electrode, cytochrome, NAD and the pollutants. A long-range electron transfer process could be achieved on the multi-phase interfaces between the electrode, bacteria and the pollutants. Copyright © 2013 Elsevier B.V. All rights reserved.

Biological Effects of Ionizing Radiation

DOE R&D Accomplishments Database

Ingram, M.; Mason, W. B.; Whipple, G. H.; Howland, J. W.

1952-04-07

This report presents a review of present knowledge and concepts of the biological effects of ionizing radiations. Among the topics discussed are the physical and chemical effects of ionizing radiation on biological systems, morphological and physiological changes observed in biological systems subjected to ionizing radiations, physiological changes in the intact animal, latent changes following exposure of biological systems to ionizing radiations, factors influencing the biological response to ionizing radiation, relative effects of various ionizing radiations, and biological dosimetry.

Hazard identification and risk assessment for biologics targeting the immune system.

PubMed

Weir, Andrea B

2008-01-01

Biologic pharmaceuticals include a variety of products, such as monoclonal antibodies, fusion proteins and cytokines. Products in those classes include immunomodulatory biologics, which are intended to enhance or diminish the activity of the immune system. Immunomodulatory biologics have been approved by the U.S. FDA for a variety of indications, including cancer and inflammatory conditions. Prior to gaining approval for marketing, sponsoring companies for all types of products must demonstrate a product's safety in toxicology studies conducted in animals and show safety and efficacy in clinical trials conducted in patients. The overall goal of toxicology studies, which applies to immunomodulatory and other product types, is to identify the hazards that products pose to humans. Because biologics are generally highly selective for specific targets (receptors/epitopes), conducting toxicology studies in animal models with the target is essential. Such animals are referred to as pharmacologically relevant. Endpoints routinely included in toxicology studies, such as hematology, organ weight and histopathology, can be used to assess the effect of a product on the structure of the immune system. Additionally, specialized endpoints, such as immunophenotyping and immune function tests, can be used to define effects of immunomodulatory products on the immune system. Following hazard identification, risks posed to patients are assessed and managed. Risks can be managed through clinical trial design and risk communication, a practice that applies to immunomodulatory and other product types. Examples of risk management in clinical trial design include establishing a safe starting dose, defining the appropriate patient population and establishing appropriate patient monitoring. Risk communication starts during clinical trials and continues after product approval. A combination of hazard identification, risk assessment and risk management allows for drug development to proceed with minimum risks to patients.

The Biology of the Glutamatergic System and Potential Role in Migraine

PubMed Central

Gasparini, C. F.; Griffiths, L. R.

2013-01-01

Migraine is a common genetically linked neurovascular disorder. Approximately ∼12% of the Caucasian population are affected including 18% of adult women and 6% of adult men (1, 2). A notable female bias is observed in migraine prevalence studies with females affected ∼3 times more than males and is credited to differences in hormone levels arising from reproductive achievements. Migraine is extremely debilitating with wide-ranging socioeconomic impact significantly affecting people’s health and quality of life. A number of neurotransmitter systems have been implicated in migraine, the most studied include the serotonergic and dopaminergic systems. Extensive genetic research has been carried out to identify genetic variants that may alter the activity of a number of genes involved in synthesis and transport of neurotransmitters of these systems. The biology of the Glutamatergic system in migraine is the least studied however there is mounting evidence that its constituents could contribute to migraine. The discovery of antagonists that selectively block glutamate receptors has enabled studies on the physiologic role of glutamate, on one hand, and opened new perspectives pertaining to the potential therapeutic applications of glutamate receptor antagonists in diverse neurologic diseases. In this brief review, we discuss the biology of the Glutamatergic system in migraine outlining recent findings that support a role for altered Glutamatergic neurotransmission from biochemical and genetic studies in the manifestation of migraine and the implications of this on migraine treatment. PMID:23675283

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

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

PubMed

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

2016-04-01

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

Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI)

PubMed Central

George, Ansel; Dorval, Alan D.; Christini, David J.

2017-01-01

The ability to experimentally perturb biological systems has traditionally been limited to static pre-programmed or operator-controlled protocols. In contrast, real-time control allows dynamic probing of biological systems with perturbations that are computed on-the-fly during experimentation. Real-time control applications for biological research are available; however, these systems are costly and often restrict the flexibility and customization of experimental protocols. The Real-Time eXperiment Interface (RTXI) is an open source software platform for achieving hard real-time data acquisition and closed-loop control in biological experiments while retaining the flexibility needed for experimental settings. RTXI has enabled users to implement complex custom closed-loop protocols in single cell, cell network, animal, and human electrophysiology studies. RTXI is also used as a free and open source, customizable electrophysiology platform in open-loop studies requiring online data acquisition, processing, and visualization. RTXI is easy to install, can be used with an extensive range of external experimentation and data acquisition hardware, and includes standard modules for implementing common electrophysiology protocols. PMID:28557998

Transient Resetting: A Novel Mechanism for Synchrony and Its Biological Examples

PubMed Central

Li, Chunguang; Chen, Luonan; Aihara, Kazuyuki

2006-01-01

The study of synchronization in biological systems is essential for the understanding of the rhythmic phenomena of living organisms at both molecular and cellular levels. In this paper, by using simple dynamical systems theory, we present a novel mechanism, named transient resetting, for the synchronization of uncoupled biological oscillators with stimuli. This mechanism not only can unify and extend many existing results on (deterministic and stochastic) stimulus-induced synchrony, but also may actually play an important role in biological rhythms. We argue that transient resetting is a possible mechanism for the synchronization in many biological organisms, which might also be further used in the medical therapy of rhythmic disorders. Examples of the synchronization of neural and circadian oscillators as well as a chaotic neuron model are presented to verify our hypothesis. PMID:16933980

Institute for Genomics and Systems Biology

Science.gov Websites

Institute for Genomics and Systems Biology Discover. Predict. Improve. Advancing Human and , 2015 See all Research Papers Featured Video Introduction to Systems Biology Video: Introduction to Systems Biology News Jack Gilbert Heading UChicago Startup that Aims to Predict Behavior of Trillions of

Apparatus and Methods for Manipulation and Optimization of Biological Systems

NASA Technical Reports Server (NTRS)

Sun, Ren (Inventor); Ho, Chih-Ming (Inventor); Wong, Pak Kin (Inventor); Yu, Fuqu (Inventor)

2014-01-01

The invention provides systems and methods for manipulating biological systems, for example to elicit a more desired biological response from a biological sample, such as a tissue, organ, and/or a cell. In one aspect, the invention operates by efficiently searching through a large parametric space of stimuli and system parameters to manipulate, control, and optimize the response of biological samples sustained in the system. In one aspect, the systems and methods of the invention use at least one optimization algorithm to modify the actuator's control inputs for stimulation, responsive to the sensor's output of response signals. The invention can be used, e.g., to optimize any biological system, e.g., bioreactors for proteins, and the like, small molecules, polysaccharides, lipids, and the like. Another use of the apparatus and methods includes is for the discovery of key parameters in complex biological systems.

The next step in biology: a periodic table?

PubMed

Dhar, Pawan K

2007-08-01

Systems biology is an approach to explain the behaviour of a system in relation to its individual components. Synthetic biology uses key hierarchical and modular concepts of systems biology to engineer novel biological systems. In my opinion the next step in biology is to use molecule-to-phenotype data using these approaches and integrate them in the form a periodic table. A periodic table in biology would provide chassis to classify, systematize and compare diversity of component properties vis-a-vis system behaviour. Using periodic table it could be possible to compute higher- level interactions from component properties. This paper examines the concept of building a bio-periodic table using protein fold as the fundamental unit.

Genetic and biochemical changes of the serotonergic system in migraine pathobiology.

PubMed

Gasparini, Claudia Francesca; Smith, Robert Anthony; Griffiths, Lyn Robyn

2017-12-01

Migraine is a brain disorder characterized by a piercing headache which affects one side of the head, located mainly at the temples and in the area around the eye. Migraine imparts substantial suffering to the family in addition to the sufferer, particularly as it affects three times more women than men and is most prevalent between the ages of 25 and 45, the years of child rearing. Migraine typically occurs in individuals with a genetic predisposition and is aggravated by specific environmental triggers. Attempts to study the biochemistry of migraine began as early as the 1960s and were primarily directed at serotonin metabolism after an increase of 5-hydroxyindoleacetic acid (5-HIAA), the main metabolite of serotonin was observed in urine of migraineurs. Genetic and biochemical studies have primarily focused on the neurotransmitter serotonin, considering receptor binding, transport and synthesis of serotonin and have investigated serotonergic mediators including enzymes, receptors as well as intermediary metabolites. These studies have been mainly assayed in blood, CSF and urine as the most accessible fluids. More recently PET imaging technology integrated with a metabolomics and a systems biology platform are being applied to study serotonergic biology. The general trend observed is that migraine patients have alterations of neurotransmitter metabolism detected in biological fluids with different biochemistry from controls, however the interpretation of the biological significance of these peripheral changes is unresolved. In this review we present the biology of the serotonergic system and metabolic routes for serotonin and discuss results of biochemical studies with regard to alterations in serotonin in brain, cerebrospinal fluid, saliva, platelets, plasma and urine of migraine patients.

The system-resonance approach in modeling genetic structures.

PubMed

Petoukhov, Sergey V

2016-01-01

The founder of the theory of resonance in structural chemistry Linus Pauling established the importance of resonance patterns in organization of living systems. Any living organism is a great chorus of coordinated oscillatory processes. From the formal point of view, biological organism is an oscillatory system with a great number of degrees of freedom. Such systems are studied in the theory of oscillations using matrix mathematics of their resonance characteristics. This study is devoted to a new approach for modeling genetically inherited structures and processes in living organisms using mathematical tools of the theory of resonances. This approach reveals hidden relationships in a number of genetic phenomena and gives rise to a new class of bio-mathematical models, which contribute to a convergence of biology with physics and informatics. In addition some relationships of molecular-genetic ensembles with mathematics of noise-immunity coding of information in modern communications technology are shown. Perspectives of applications of the phenomena of vibrational mechanics for modeling in biology are discussed. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

From globally coupled maps to complex-systems biology

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

Kaneko, Kunihiko, E-mail: kaneko@complex.c.u-tokyo.ac.jp

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

Toward a Biosignature for Suicide

PubMed Central

Oquendo, Maria A.; Sullivan, Gregory M.; Sudol, Katherin; Baca-Garcia, Enrique; Stanley, Barbara H.; Sublette, M. Elizabeth; Mann, J. John

2015-01-01

Objective Suicide, a major cause of death worldwide, has distinct biological underpinnings. The authors review and synthesize the research literature on biomarkers of suicide, with the aim of using the findings of these studies to develop a coherent model for the biological diathesis for suicide. Method The authors examined studies covering a large range of neurobiological systems implicated in suicide. They provide succinct descriptions of each system to provide a context for interpreting the meaning of findings in suicide. Results Several lines of evidence implicate dysregulation in stress response systems, especially the hypothalamic-pituitary-adrenal axis, as a diathesis for suicide. Additional findings related to neuroinflammatory indices, glutamatergic function, and neuronal plasticity at the cellular and circuitry level may reflect downstream effects of such dysregulation. Whether serotonergic abnormalities observed in individuals who have died by suicide are independent of stress response abnormalities is an unresolved question. Conclusions The most compelling biomarkers for suicide are linked to altered stress responses and their downstream effects, and to abnormalities in the serotonergic system. Studying these systems in parallel and in the same populations may elucidate the role of each and their interplay, possibly leading to identification of new treatment targets and biological predictors. PMID:25263730

Logic Gate Operation by DNA Translocation through Biological Nanopores.

PubMed

Yasuga, Hiroki; Kawano, Ryuji; Takinoue, Masahiro; Tsuji, Yutaro; Osaki, Toshihisa; Kamiya, Koki; Miki, Norihisa; Takeuchi, Shoji

2016-01-01

Logical operations using biological molecules, such as DNA computing or programmable diagnosis using DNA, have recently received attention. Challenges remain with respect to the development of such systems, including label-free output detection and the rapidity of operation. Here, we propose integration of biological nanopores with DNA molecules for development of a logical operating system. We configured outputs "1" and "0" as single-stranded DNA (ssDNA) that is or is not translocated through a nanopore; unlabeled DNA was detected electrically. A negative-AND (NAND) operation was successfully conducted within approximately 10 min, which is rapid compared with previous studies using unlabeled DNA. In addition, this operation was executed in a four-droplet network. DNA molecules and associated information were transferred among droplets via biological nanopores. This system would facilitate linking of molecules and electronic interfaces. Thus, it could be applied to molecular robotics, genetic engineering, and even medical diagnosis and treatment.

BIOCHEMISTRY OF MOBILE ZINC AND NITRIC OXIDE REVEALED BY FLUORESCENT SENSORS

PubMed Central

Pluth, Michael D.; Tomat, Elisa; Lippard, Stephen J.

2010-01-01

Biologically mobile zinc and nitric oxide (NO) are two prominent examples of inorganic compounds involved in numerous signaling pathways in living systems. In the past decade, a synergy of regulation, signaling, and translocation of these two species has emerged in several areas of human physiology, providing additional incentive for developing adequate detection systems for Zn(II) ions and NO in biological specimens. Fluorescent probes for both of these bioinorganic analytes provide excellent tools for their detection, with high spatial and temporal resolution. We review the most widely used fluorescent sensors for biological zinc and nitric oxide, together with promising new developments and unmet needs of contemporary Zn(II) and NO biological imaging. The interplay between zinc and nitric oxide in the nervous, cardiovascular, and immune systems is highlighted to illustrate the contributions of selective fluorescent probes to the study of these two important bioinorganic analytes. PMID:21675918

[Construction of automatic elucidation platform for mechanism of traditional Chinese medicine].

PubMed

Zhang, Bai-xia; Luo, Si-jun; Yan, Jing; Gu, Hao; Luo, Ji; Zhang, Yan-ling; Tao, Ou; Wang, Yun

2015-10-01

Aim at the two problems in the field of traditional Chinese medicine (TCM) mechanism elucidation, one is the lack of detailed biological processes information, next is the low efficient in constructing network models, we constructed an auxiliary elucidation system for the TCM mechanism and realize the automatic establishment of biological network model. This study used the Entity Grammar Systems (EGS) as the theoretical framework, integrated the data of formulae, herbs, chemical components, targets of component, biological reactions, signaling pathways and disease related proteins, established the formal models, wrote the reasoning engine, constructed the auxiliary elucidation system for the TCM mechanism elucidation. The platform provides an automatic modeling method for biological network model of TCM mechanism. It would be benefit to perform the in-depth research on TCM theory of natures and combination and provides the scientific references for R&D of TCM.

Logic Gate Operation by DNA Translocation through Biological Nanopores

PubMed Central

Takinoue, Masahiro; Tsuji, Yutaro; Osaki, Toshihisa; Kamiya, Koki; Miki, Norihisa; Takeuchi, Shoji

2016-01-01

Logical operations using biological molecules, such as DNA computing or programmable diagnosis using DNA, have recently received attention. Challenges remain with respect to the development of such systems, including label-free output detection and the rapidity of operation. Here, we propose integration of biological nanopores with DNA molecules for development of a logical operating system. We configured outputs “1” and “0” as single-stranded DNA (ssDNA) that is or is not translocated through a nanopore; unlabeled DNA was detected electrically. A negative-AND (NAND) operation was successfully conducted within approximately 10 min, which is rapid compared with previous studies using unlabeled DNA. In addition, this operation was executed in a four-droplet network. DNA molecules and associated information were transferred among droplets via biological nanopores. This system would facilitate linking of molecules and electronic interfaces. Thus, it could be applied to molecular robotics, genetic engineering, and even medical diagnosis and treatment. PMID:26890568

Wireless Biological Electronic Sensors

PubMed Central

Cui, Yue

2017-01-01

The development of wireless biological electronic sensors could open up significant advances for both fundamental studies and practical applications in a variety of areas, including medical diagnosis, environmental monitoring, and defense applications. One of the major challenges in the development of wireless bioelectronic sensors is the successful integration of biosensing units and wireless signal transducers. In recent years, there are a few types of wireless communication systems that have been integrated with biosensing systems to construct wireless bioelectronic sensors. To successfully construct wireless biological electronic sensors, there are several interesting questions: What types of biosensing transducers can be used in wireless bioelectronic sensors? What types of wireless systems can be integrated with biosensing transducers to construct wireless bioelectronic sensors? How are the electrical sensing signals generated and transmitted? This review will highlight the early attempts to address these questions in the development of wireless biological electronic sensors. PMID:28991220

Humidity-controlled preparation of frozen-hydrated biological samples for cryogenic coherent x-ray diffraction microscopy

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

Takayama, Yuki; Nakasako, Masayoshi; RIKEN Harima Institute/SPring-8, 1-1-1 Kouto, Mikaduki, Sayo, Hyogo 679-5148

2012-05-15

Coherent x-ray diffraction microscopy (CXDM) has the potential to visualize the structures of micro- to sub-micrometer-sized biological particles, such as cells and organelles, at high resolution. Toward advancing structural studies on the functional states of such particles, here, we developed a system for the preparation of frozen-hydrated biological samples for cryogenic CXDM experiments. The system, which comprised a moist air generator, microscope, micro-injector mounted on a micromanipulator, custom-made sample preparation chamber, and flash-cooling device, allowed for the manipulation of sample particles in the relative humidity range of 20%-94%rh at 293 K to maintain their hydrated and functional states. Here, wemore » report the details of the system and the operation procedure, including its application to the preparation of a frozen-hydrated chloroplast sample. Sample quality was evaluated through a cryogenic CXDM experiment conducted at BL29XUL of SPring-8. Taking the performance of the system and the quality of the sample, the system was suitable to prepare frozen-hydrated biological samples for cryogenic CXDM experiments.« less

First Steps in Computational Systems Biology: A Practical Session in Metabolic Modeling and Simulation

ERIC Educational Resources Information Center

Reyes-Palomares, Armando; Sanchez-Jimenez, Francisca; Medina, Miguel Angel

2009-01-01

A comprehensive understanding of biological functions requires new systemic perspectives, such as those provided by systems biology. Systems biology approaches are hypothesis-driven and involve iterative rounds of model building, prediction, experimentation, model refinement, and development. Developments in computer science are allowing for ever…

Construction of new synthetic biology tools for the control of gene expression in the cyanobacterium Synechococcus sp. strain PCC 7002.

PubMed

Zess, Erin K; Begemann, Matthew B; Pfleger, Brian F

2016-02-01

Predictive control of gene expression is an essential tool for developing synthetic biological systems. The current toolbox for controlling gene expression in cyanobacteria is a barrier to more in-depth genetic analysis and manipulation. Towards relieving this bottleneck, this work describes the use of synthetic biology to construct an anhydrotetracycline-based induction system and adapt a trans-acting small RNA (sRNA) system for use in the cyanobacterium Synechococcus sp. strain PCC 7002. An anhydrotetracycline-inducible promoter was developed to maximize intrinsic strength and dynamic range. The resulting construct, PEZtet , exhibited tight repression and a maximum 32-fold induction upon addition of anhydrotetracycline. Additionally, a sRNA system based on the Escherichia coli IS10 RNA-IN/OUT regulator was adapted for use in Synechococcus sp. strain PCC 7002. This system exhibited 70% attenuation of target gene expression, providing a demonstration of the use of sRNAs for differential gene expression in cyanobacteria. These systems were combined to produce an inducible sRNA system, which demonstrated 59% attenuation of target gene expression. Lastly, the role of Hfq, a critical component of sRNA systems in E. coli, was investigated. Genetic studies showed that the Hfq homolog in Synechococcus sp. strain PCC 7002 did not impact repression by the engineered sRNA system. In summary, this work describes new synthetic biology tools that can be applied to physiological studies, metabolic engineering, or sRNA platforms in Synechococcus sp. strain PCC 7002. © 2015 Wiley Periodicals, Inc.

NMR-based Metabolomics Applications in Biological and Environmental Science

EPA Science Inventory

As a complimentary tool to other omics platforms, metabolomics is increasingly being used bybiologists to study the dynamic response of biological systems (cells, tissues, or wholeorganisms) under diverse physiological or pathological conditions. Metabolomics deals with the quali...

Pilot study comparing the Childhood Arthritis & Rheumatology Research Alliance (CARRA) systemic Juvenile Idiopathic Arthritis Consensus Treatment Plans.

PubMed

Kimura, Yukiko; Grevich, Sriharsha; Beukelman, Timothy; Morgan, Esi; Nigrovic, Peter A; Mieszkalski, Kelly; Graham, T Brent; Ibarra, Maria; Ilowite, Norman; Klein-Gitelman, Marisa; Onel, Karen; Prahalad, Sampath; Punaro, Marilynn; Ringold, Sarah; Toib, Dana; Van Mater, Heather; Weiss, Jennifer E; Weiss, Pamela F; Schanberg, Laura E

2017-04-11

To assess the feasibility of studying the comparative effectiveness of the Childhood Arthritis and Rheumatology Research Alliance (CARRA) consensus treatment plans (CTPs) for systemic Juvenile Idiopathic Arthritis (JIA) using an observational registry. Untreated systemic JIA patients enrolled in the CARRA Registry were begun on one of 4 CTPs chosen by the treating physician and patient/family (glucocorticoid [GC] alone; methotrexate [MTX] ± GC; IL1 inhibitor [IL1i] ± GC; IL6 inhibitor [IL6i] ± GC). The primary outcome of clinical inactive disease (CID) without current GC use was assessed at 9 months. clinicaltrials.gov NCT01697254; first registered 9/28/12 (retrospectively enrolled). Thirty patients were enrolled at 13 sites; eight patients were started on a non-biologic CTP (2 GC, 6 MTX) and 22 patients on a biologic CTP (12 IL1i, 10 IL6i) at disease onset. Demographic and disease features were similar between CTP groups. CTP choice appeared to segregate by site preference. CID off GC was achieved by 37% (11 of 30) including 11/22 (50%) starting a biologic CTP compared to 0/8 starting a non-biologic CTP (p = 0.014). There were four serious adverse events: two infections, one appendicitis and one macrophage activation syndrome. The CARRA systemic JIA CTP pilot study demonstrated successful implementation of CTPs using the CARRA registry infrastructure. Having demonstrated feasibility, a larger study using CTP response to better determine the relative effectiveness of treatments for new-onset systemic JIA is now underway.

The development of synthetic biology: a patent analysis.

PubMed

van Doren, Davy; Koenigstein, Stefan; Reiss, Thomas

2013-12-01

In the past decades, synthetic biology has gained interest regarding research and development efforts within the biotechnology domain. However, it is unclear to what extent synthetic biology has matured already into being commercially exploitable. By means of a patent analysis, this study shows that there is an increasing trend regarding synthetic biology related patent applications. The majority of retrieved patents relates to innovations facilitating the realisation of synthetic biology through improved understanding of biological systems. In addition, there is increased activity concerning the development of synthetic biology based applications. When looking at potential application areas, the majority of synthetic biology patents seems most relevant for the medical, energy and industrial sector. Furthermore, the analysis shows that most activity has been carried out by the USA, with Japan and a number of European countries considerably trailing behind. In addition, both universities and companies are major patent applicant actor types. The results presented here form a starting point for follow-up studies concerning the identification of drivers explaining the observed patent application trends in synthetic biology.

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

Enhanced sampling techniques in molecular dynamics simulations of biological systems.

PubMed

Bernardi, Rafael C; Melo, Marcelo C R; Schulten, Klaus

2015-05-01

Molecular dynamics has emerged as an important research methodology covering systems to the level of millions of atoms. However, insufficient sampling often limits its application. The limitation is due to rough energy landscapes, with many local minima separated by high-energy barriers, which govern the biomolecular motion. In the past few decades methods have been developed that address the sampling problem, such as replica-exchange molecular dynamics, metadynamics and simulated annealing. Here we present an overview over theses sampling methods in an attempt to shed light on which should be selected depending on the type of system property studied. Enhanced sampling methods have been employed for a broad range of biological systems and the choice of a suitable method is connected to biological and physical characteristics of the system, in particular system size. While metadynamics and replica-exchange molecular dynamics are the most adopted sampling methods to study biomolecular dynamics, simulated annealing is well suited to characterize very flexible systems. The use of annealing methods for a long time was restricted to simulation of small proteins; however, a variant of the method, generalized simulated annealing, can be employed at a relatively low computational cost to large macromolecular complexes. Molecular dynamics trajectories frequently do not reach all relevant conformational substates, for example those connected with biological function, a problem that can be addressed by employing enhanced sampling algorithms. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.

Research Plan for Study of Biological and Ecological Effects of the Solar Power Satellite Transmission System

NASA Technical Reports Server (NTRS)

Newsom, B. D.

1978-01-01

A programmatic research plan for a three year study is presented to generate knowledge on effects of the continuous wave 2.45 GHz microwave power transmission that the Solar Power Satellite might have on biological and ecological elements, within and around the rectenna receiving site.

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

Hypothermic temperature effects on organ survival and restoration

PubMed Central

Ishikawa, Jun; Oshima, Masamitsu; Iwasaki, Fumitaka; Suzuki, Ryoji; Park, Joonhong; Nakao, Kazuhisa; Matsuzawa-Adachi, Yuki; Mizutsuki, Taro; Kobayashi, Ayaka; Abe, Yuta; Kobayashi, Eiji; Tezuka, Katsunari; Tsuji, Takashi

2015-01-01

A three-dimensional multicellular organism maintains the biological functions of life support by using the blood circulation to transport oxygen and nutrients and to regulate body temperature for intracellular enzymatic reactions. Donor organ transplantation using low-temperature storage is used as the fundamental treatment for dysfunctional organs. However, this approach has a serious problem in that donor organs maintain healthy conditions only during short-term storage. In this study, we developed a novel liver perfusion culture system based on biological metabolism that can maintain physiological functions, including albumin synthesis, bile secretion and urea production. This system also allows for the resurrection of a severely ischaemic liver. This study represents a significant advance for the development of an ex vivo organ perfusion system based on biological metabolism. It can be used not only to address donor organ shortages but also as the basis of future regenerative organ replacement therapy. PMID:25900715

Engineering artificial cells by combining HeLa-based cell-free expression and ultra-thin double emulsion template

PubMed Central

Ho, Kwun Yin; Murray, Victoria L.; Liu, Allen P.

2015-01-01

Generation of artificial cells provides the bridge needed to cover the gap between studying the complexity of biological processes in whole cells and studying these same processes in an in vitro reconstituted system. Artificial cells are defined as the encapsulation of biologically active material in a biological or synthetic membrane. Here, we describe a robust and general method to produce artificial cells for the purpose of mimicking one or more behaviors of a cell. A microfluidic double emulsion system is used to encapsulate a mammalian cell free expression system that is able to express membrane proteins into the bilayer or soluble proteins inside the vesicles. The development of a robust platform that allows the assembly of artificial cells is valuable in understanding subcellular functions and emergent behaviors in a more cell-like environment as well as for creating novel signaling pathways to achieve specific cellular behaviors. PMID:25997354

A Dielectric Rod Antenna for Picosecond Pulse Stimulation of Neurological Tissue

PubMed Central

Petrella, Ross A.; Schoenbach, Karl H.; Xiao, Shu

2016-01-01

A dielectrically loaded wideband rod antenna has been studied as a pulse delivery system to subcutaneous tissues. Simulation results applying 100 ps electrical pulse show that it allows us to generate critical electric field for biological effects, such as brain stimulation, in the range of several centimeters. In order to reach the critical electric field for biological effects, which is approximately 20 kV/cm, at a depth of 2 cm, the input voltage needs to be 175 kV. The electric field spot size in the brain at this position is approximately 1 cm2. Experimental studies in free space with a conical antenna (part of the antenna system) with aluminum nitride as the dielectric have confirmed the accuracy of the simulation. These results set the foundation for high voltage in situ experiments on the complete antenna system and the delivery of pulses to biological tissue. PMID:27563160

Metagenomic systems biology and metabolic modeling of the human microbiome: from species composition to community assembly rules.

PubMed

Levy, Roie; Borenstein, Elhanan

2014-01-01

The human microbiome is a key contributor to health and development. Yet little is known about the ecological forces that are at play in defining the composition of such host-associated communities. Metagenomics-based studies have uncovered clear patterns of community structure but are often incapable of distinguishing alternative structuring paradigms. In a recent study, we integrated metagenomic analysis with a systems biology approach, using a reverse ecology framework to model numerous human microbiota species and to infer metabolic interactions between species. Comparing predicted interactions with species composition data revealed that the assembly of the human microbiome is dominated at the community level by habitat filtering. Furthermore, we demonstrated that this habitat filtering cannot be accounted for by known host phenotypes or by the metabolic versatility of the various species. Here we provide a summary of our findings and offer a brief perspective on related studies and on future approaches utilizing this metagenomic systems biology framework.

A Unique Large-Scale Undergraduate Research Experience in Molecular Systems Biology for Non-Mathematics Majors

ERIC Educational Resources Information Center

Kappler, Ulrike; Rowland, Susan L.; Pedwell, Rhianna K.

2017-01-01

Systems biology is frequently taught with an emphasis on mathematical modeling approaches. This focus effectively excludes most biology, biochemistry, and molecular biology students, who are not mathematics majors. The mathematical focus can also present a misleading picture of systems biology, which is a multi-disciplinary pursuit requiring…

Biological Concepts. Student Manual. Biological Treatment Process Control.

ERIC Educational Resources Information Center

Carnegie, John W.

This manual contains the textual material for a three-lesson unit which introduces students to the basic concepts applicable to all biological treatment systems. The general topic areas addressed in the lessons are: (1) the microorganisms found in biological systems; (2) the factors that affect the growth and health of biological systems; and (3)…

Integrating Omics Technologies to Study Pulmonary Physiology and Pathology at the Systems Level

PubMed Central

Pathak, Ravi Ramesh; Davé, Vrushank

2014-01-01

Assimilation and integration of “omics” technologies, including genomics, epigenomics, proteomics, and metabolomics has readily altered the landscape of medical research in the last decade. The vast and complex nature of omics data can only be interpreted by linking molecular information at the organismic level, forming the foundation of systems biology. Research in pulmonary biology/medicine has necessitated integration of omics, network, systems and computational biology data to differentially diagnose, interpret, and prognosticate pulmonary diseases, facilitating improvement in therapy and treatment modalities. This review describes how to leverage this emerging technology in understanding pulmonary diseases at the systems level –called a “systomic” approach. Considering the operational wholeness of cellular and organ systems, diseased genome, proteome, and the metabolome needs to be conceptualized at the systems level to understand disease pathogenesis and progression. Currently available omics technology and resources require a certain degree of training and proficiency in addition to dedicated hardware and applications, making them relatively less user friendly for the pulmonary biologist and clinicians. Herein, we discuss the various strategies, computational tools and approaches required to study pulmonary diseases at the systems level for biomedical scientists and clinical researchers. PMID:24802001

Formal reasoning about systems biology using theorem proving

PubMed Central

Hasan, Osman; Siddique, Umair; Tahar, Sofiène

2017-01-01

System biology provides the basis to understand the behavioral properties of complex biological organisms at different levels of abstraction. Traditionally, analysing systems biology based models of various diseases have been carried out by paper-and-pencil based proofs and simulations. However, these methods cannot provide an accurate analysis, which is a serious drawback for the safety-critical domain of human medicine. In order to overcome these limitations, we propose a framework to formally analyze biological networks and pathways. In particular, we formalize the notion of reaction kinetics in higher-order logic and formally verify some of the commonly used reaction based models of biological networks using the HOL Light theorem prover. Furthermore, we have ported our earlier formalization of Zsyntax, i.e., a deductive language for reasoning about biological networks and pathways, from HOL4 to the HOL Light theorem prover to make it compatible with the above-mentioned formalization of reaction kinetics. To illustrate the usefulness of the proposed framework, we present the formal analysis of three case studies, i.e., the pathway leading to TP53 Phosphorylation, the pathway leading to the death of cancer stem cells and the tumor growth based on cancer stem cells, which is used for the prognosis and future drug designs to treat cancer patients. PMID:28671950

An integrative approach to inferring biologically meaningful gene modules.

PubMed

Cho, Ji-Hoon; Wang, Kai; Galas, David J

2011-07-26

The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.

Will Quantitative Proteomics Redefine Some of the Key Concepts in Skeletal Muscle Physiology?

PubMed

Gizak, Agnieszka; Rakus, Dariusz

2016-01-11

Molecular and cellular biology methodology is traditionally based on the reasoning called "the mechanistic explanation". In practice, this means identifying and selecting correlations between biological processes which result from our manipulation of a biological system. In theory, a successful application of this approach requires precise knowledge about all parameters of a studied system. However, in practice, due to the systems' complexity, this requirement is rarely, if ever, accomplished. Typically, it is limited to a quantitative or semi-quantitative measurements of selected parameters (e.g., concentrations of some metabolites), and a qualitative or semi-quantitative description of expression/post-translational modifications changes within selected proteins. A quantitative proteomics approach gives a possibility of quantitative characterization of the entire proteome of a biological system, in the context of the titer of proteins as well as their post-translational modifications. This enables not only more accurate testing of novel hypotheses but also provides tools that can be used to verify some of the most fundamental dogmas of modern biology. In this short review, we discuss some of the consequences of using quantitative proteomics to verify several key concepts in skeletal muscle physiology.

Cancer Systems Biology: a peak into the future of patient care?

PubMed Central

Werner, Henrica M. J.; Mills, Gordon B.; Ram, Prahlad T.

2015-01-01

Traditionally, scientific research has focused on studying individual events, such as single mutations, gene function or the effect of the manipulation of one protein on a biological phenotype. A range of technologies, combined with the ability to develop robust and predictive mathematical models, is beginning to provide information that will enable a holistic view of how the genomic and epigenetic aberrations in cancer cells can alter the homeostasis of signalling networks within these cells, between cancer cells and the local microenvironment, at the organ and organism level. This systems biology process needs to be integrated with an iterative approach wherein hypotheses and predictions that arise from modelling are refined and constrained by experimental evaluation. Systems biology approaches will be vital for developing and implementing effective strategies to deliver personalized cancer therapy. Specifically, these approaches will be important to select those patients most likely to benefit from targeted therapies as well as for the development and implementation of rational combinatorial therapies. Systems biology can help to increase therapy efficacy or bypass the emergence of resistance, thus converting the current (often short term) effects of targeted therapies into durable responses, ultimately to improve quality of life and provide a cure. PMID:24492837

Set membership experimental design for biological systems.

PubMed

Marvel, Skylar W; Williams, Cranos M

2012-03-21

Experimental design approaches for biological systems are needed to help conserve the limited resources that are allocated for performing experiments. The assumptions used when assigning probability density functions to characterize uncertainty in biological systems are unwarranted when only a small number of measurements can be obtained. In these situations, the uncertainty in biological systems is more appropriately characterized in a bounded-error context. Additionally, effort must be made to improve the connection between modelers and experimentalists by relating design metrics to biologically relevant information. Bounded-error experimental design approaches that can assess the impact of additional measurements on model uncertainty are needed to identify the most appropriate balance between the collection of data and the availability of resources. In this work we develop a bounded-error experimental design framework for nonlinear continuous-time systems when few data measurements are available. This approach leverages many of the recent advances in bounded-error parameter and state estimation methods that use interval analysis to generate parameter sets and state bounds consistent with uncertain data measurements. We devise a novel approach using set-based uncertainty propagation to estimate measurement ranges at candidate time points. We then use these estimated measurements at the candidate time points to evaluate which candidate measurements furthest reduce model uncertainty. A method for quickly combining multiple candidate time points is presented and allows for determining the effect of adding multiple measurements. Biologically relevant metrics are developed and used to predict when new data measurements should be acquired, which system components should be measured and how many additional measurements should be obtained. The practicability of our approach is illustrated with a case study. This study shows that our approach is able to 1) identify candidate measurement time points that maximize information corresponding to biologically relevant metrics and 2) determine the number at which additional measurements begin to provide insignificant information. This framework can be used to balance the availability of resources with the addition of one or more measurement time points to improve the predictability of resulting models.

Set membership experimental design for biological systems

PubMed Central

2012-01-01

Background Experimental design approaches for biological systems are needed to help conserve the limited resources that are allocated for performing experiments. The assumptions used when assigning probability density functions to characterize uncertainty in biological systems are unwarranted when only a small number of measurements can be obtained. In these situations, the uncertainty in biological systems is more appropriately characterized in a bounded-error context. Additionally, effort must be made to improve the connection between modelers and experimentalists by relating design metrics to biologically relevant information. Bounded-error experimental design approaches that can assess the impact of additional measurements on model uncertainty are needed to identify the most appropriate balance between the collection of data and the availability of resources. Results In this work we develop a bounded-error experimental design framework for nonlinear continuous-time systems when few data measurements are available. This approach leverages many of the recent advances in bounded-error parameter and state estimation methods that use interval analysis to generate parameter sets and state bounds consistent with uncertain data measurements. We devise a novel approach using set-based uncertainty propagation to estimate measurement ranges at candidate time points. We then use these estimated measurements at the candidate time points to evaluate which candidate measurements furthest reduce model uncertainty. A method for quickly combining multiple candidate time points is presented and allows for determining the effect of adding multiple measurements. Biologically relevant metrics are developed and used to predict when new data measurements should be acquired, which system components should be measured and how many additional measurements should be obtained. Conclusions The practicability of our approach is illustrated with a case study. This study shows that our approach is able to 1) identify candidate measurement time points that maximize information corresponding to biologically relevant metrics and 2) determine the number at which additional measurements begin to provide insignificant information. This framework can be used to balance the availability of resources with the addition of one or more measurement time points to improve the predictability of resulting models. PMID:22436240

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.

PubMed

Dona, Anthony C; Kyriakides, Michael; Scott, Flora; Shephard, Elizabeth A; Varshavi, Dorsa; Veselkov, Kirill; Everett, Jeremy R

2016-01-01

Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

Biomedical experiments. Part A: Biostack experiment

NASA Technical Reports Server (NTRS)

Buecker, H.; Horneck, G.; Reinholz, E.; Scheuermann, W.; Ruether, W.; Graul, E. H.; Planel, H.; Soleilhavoup, J. P.; Cuer, P.; Kaiser, R.

1972-01-01

The biostack experiment is described which was designed to study the biologic effects of individual heavy nuclei of galactic cosmic radiation during space flight outside the magnetosphere of the earth. Specifically, the biostack experiment was designed to promote research on the effects of high energy/high Z particles of galactic cosmic radiation on a broad spectrum of biologic systems, from the molecular to the highly organized and developed forms of life. The experiment was considered unique and scientifically meritorious because of its potential yield of information - currently unavailable on earth - on the interaction of biologic systems with the heavy particles of galactic cosmic radiation.

The National Biological Information Infrastructure: Coming of age

USGS Publications Warehouse

Cotter, G.; Frame, M.; Sepic, R.; Zolly, L.

2000-01-01

Coordinated by the US Geological Survey, the National Biological Information Infrastructure (NBII) is a Web-based system that provides increased access to data and information on the nation's biological resources. The NBII can be viewed from a variety of perspectives. This article - an individual case study and not a broad survey with extensive references to the literature - addresses the structure of the NBII related to thematic sections, infrastructure sections and place-based sections, and other topics such as the Integrated Taxonomic Information System (one of our more innovative tools) and the development of our controlled vocabulary.

System Theory and Physiological Processes.

PubMed

Jones, R W

1963-05-03

Engineers and physiologists working together in experimental and theoretical studies predict that the application of system analysis to biological processes will increase understanding of these processes and broaden the base of system theory. Richard W. Jones, professor of electrical engineering at Northwestern University, Evanston, Illinois, and John S. Gray, professor of physiology at Northwestern's Medical School, discuss these developments. Their articles are adapted from addresses delivered in Chicago in November 1962 at the 15th Annual Conference on Engineering in Medicine and Biology.

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

A Systems Biology Approach Reveals Converging Molecular Mechanisms that Link Different POPs to Common Metabolic Diseases.

PubMed

Ruiz, Patricia; Perlina, Ally; Mumtaz, Moiz; Fowler, Bruce A

2016-07-01

A number of epidemiological studies have identified statistical associations between persistent organic pollutants (POPs) and metabolic diseases, but testable hypotheses regarding underlying molecular mechanisms to explain these linkages have not been published. We assessed the underlying mechanisms of POPs that have been associated with metabolic diseases; three well-known POPs [2,3,7,8-tetrachlorodibenzodioxin (TCDD), 2,2´,4,4´,5,5´-hexachlorobiphenyl (PCB 153), and 4,4´-dichlorodiphenyldichloroethylene (p,p´-DDE)] were studied. We used advanced database search tools to delineate testable hypotheses and to guide laboratory-based research studies into underlying mechanisms by which this POP mixture could produce or exacerbate metabolic diseases. For our searches, we used proprietary systems biology software (MetaCore™/MetaDrug™) to conduct advanced search queries for the underlying interactions database, followed by directional network construction to identify common mechanisms for these POPs within two or fewer interaction steps downstream of their primary targets. These common downstream pathways belong to various cytokine and chemokine families with experimentally well-documented causal associations with type 2 diabetes. Our systems biology approach allowed identification of converging pathways leading to activation of common downstream targets. To our knowledge, this is the first study to propose an integrated global set of step-by-step molecular mechanisms for a combination of three common POPs using a systems biology approach, which may link POP exposure to diseases. Experimental evaluation of the proposed pathways may lead to development of predictive biomarkers of the effects of POPs, which could translate into disease prevention and effective clinical treatment strategies. Ruiz P, Perlina A, Mumtaz M, Fowler BA. 2016. A systems biology approach reveals converging molecular mechanisms that link different POPs to common metabolic diseases. Environ Health Perspect 124:1034-1041; http://dx.doi.org/10.1289/ehp.1510308.

Comparative study of binding interactions between porphyrin systems and aromatic compounds of biological importance by multiple spectroscopic techniques: A review.

PubMed

Makarska-Bialokoz, Magdalena

2018-07-05

The specific spectroscopic and redox properties of porphyrins predestine them to fulfill the role of sensors during interacting with different biologically active substances. Monitoring of binding interactions in the systems porphyrin-biologically active compound is a key question not only in the field of physiological functions of living organisms, but also in environmental protection, notably in the light of the rapidly growing drug consumption and concurrently the production of drug effluents. Not always beneficial action of drugs on natural porphyrin systems induces to further studies, with commercially available porphyrins as the model systems. Therefore the binding process between several water-soluble porphyrins and a series of biologically active compounds (e.g. caffeine, guanine, theophylline, theobromine, xanthine, uric acid) has been studied in different aqueous solutions analyzing their absorption and steady-state fluorescence spectra, the porphyrin fluorescence lifetimes and their quantum yields. The magnitude of the binding and fluorescence quenching constants values for particular quenchers decreases in a series: uric acid > guanine > caffeine > theophylline > theobromine > xanthine. In all the systems studied there are characters of static quenching, as a consequence of the π-π-stacked non-covalent and non-fluorescent complexes formation between porphyrins and interacting compounds, accompanied simultaneously by the additional specific binding interactions. The porphyrin fluorescence quenching can be explain by the photoinduced intermolecular electron transfer from aromatic compound to the center of the porphyrin molecule, playing the role of the binding site. Presented results can be valuable for designing of new fluorescent porphyrin chemosensors or monitoring of drug traces in aqueous solutions. The obtained outcomes have also the toxicological and medical importance, providing insight into the interactions of the water-soluble porphyrins with biologically active substances. Copyright © 2018 Elsevier B.V. All rights reserved.

The genome of herpesvirus papio 2 is closely related to the genomes of human herpes simplex viruses.

PubMed

Bigger, John E; Martin, David W

2003-06-01

Infection of baboons (Papio species) with herpesvirus papio 2 (HVP-2) produces a disease that is clinically similar to herpes simplex virus (HSV-1 and HSV-2) infection of humans. The development of a primate model of simplexvirus infection based on HVP-2 would provide a powerful resource to study virus biology and test vaccine strategies. In order to characterize the molecular biology of HVP-2 and justify further development of this model system we have constructed a physical map of the HVP-2 genome. The results of these studies have identified the presence of 26 reading frames that closely resemble HSV homologues. Furthermore, the HVP-2 genome shares a collinear arrangement with the genome of HSV. These studies further validate the development of the HVP-2 model as a surrogate system to study the biology of HSV infections.

Cellular signaling identifiability analysis: a case study.

PubMed

Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo

2010-05-21

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

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

From systems biology to systems biomedicine.

PubMed

Antony, Paul M A; Balling, Rudi; Vlassis, Nikos

2012-08-01

Systems Biology is about combining theory, technology, and targeted experiments in a way that drives not only data accumulation but knowledge as well. The challenge in Systems Biomedicine is to furthermore translate mechanistic insights in biological systems to clinical application, with the central aim of improving patients' quality of life. The challenge is to find theoretically well-chosen models for the contextually correct and intelligible representation of multi-scale biological systems. In this review, we discuss the current state of Systems Biology, highlight the emergence of Systems Biomedicine, and highlight some of the topics and views that we think are important for the efficient application of Systems Theory in Biomedicine. Copyright © 2011 Elsevier Ltd. All rights reserved.

Computational Study of the Genomic and Epigenomic Phenomena

NASA Astrophysics Data System (ADS)

Yang, Wenjing

Biological systems are perhaps the ultimate complex systems, uniquely capable of processing and communicating information, reproducing in their lifetimes, and adapting in evolutionary time scales. My dissertation research focuses on using computational approaches to understand the biocomplexity manifested in the multitude of length scales and time scales. At the molecular and cellular level, central to the complex behavior of a biological system is the regulatory network. My research study focused on epigenetics, which is essential for multicellular organisms to establish cellular identity during development or in response to intracellular and environmental stimuli. My computational study of epigenomics is greatly facilitated by recent advances in high-throughput sequencing technology, which enables high-resolution snapshots of epigenomes and transcriptomes. Using human CD4+ T cell as a model system, the dynamical changes in epigenome and transcriptome pertinent to T cell activation were investigated at the genome scale. Going beyond traditional focus on transcriptional regulation, I provided evidences that post-transcriptional regulation may serve as a major component of the regulatory network. In addition, I explored alternative polyadenylation, another novel aspect of gene regulation, and how it cross-talks with the local chromatin structure. As the renowned theoretical biologist Theodosius Dobzhansky said eloquently, "Nothing in biology makes sense except in the light of evolution''. To better understand this ubiquitous driving force in the biological world, I went beyond molecular events in a single organism, and investigated the dynamical changes of population structure along the evolutionary time scale. To this end, we used HIV virus population dynamics in the host immune system as a model system. The evolution of HIV viral population plays a key role in AIDS immunopathogenesis with its exceptionally high mutation rate. However, the theoretical studies of the effect of recombination have been rather limited. Given the phylogenetic and experimental evidences for the high recombination rate and its important role in HIV evolution and epidemics, I established a mathematical model to study the effect of recombination, and explored the complex behavior of this dynamics system.

Improving Satellite Compatible Microdevices to Study Biology in Space

NASA Technical Reports Server (NTRS)

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

2017-01-01

The technology for biology in space lags far behind the gold standard for biological experiments on Earth. To remedy this disparity, the Rothschild lab works on proof of concept, prototyping, and developing of new sensors and devices to further the capabilities of biology research on satellites. One such device is the PowerCell Payload System. One goal for synthetic biology in aiding space travel and colonization is to genetically engineer living cells to produce biochemicals in space. However, such farming in space presupposes bacteria retain their functionality post-launch, bombarded by radiation, and without the 1G of Earth. Our questions is, does a co-culture of cyanobacteria and protein-synthesizing bacteria produce Earth-like yields of target proteins? Is the yield sensitive to variable gravitational forces? To answer these questions, a PowerCell Payload System will spend 1 year aboard the German Aerospace Center's Euglena and Combined Regenerative Organic-food Production In Space (Eu:CROPIS) mission satellite. The PowerCell system is a pair of two 48-well microfluidic cards, each well seeded with bacteria. The system integrates fluidic, thermal, optical, electronic, and control systems to germinate bacteria spores, then measure the protein synthesized for comparison to parallel experiments conducted on the Earth. In developing the PowerCell Payload, we gained insight into the shortcomings of biology experiments on satellites. To address these issues, we have started three new prototyping projects: 1) The development of an extremely stable and radiation resistant cell-free system, allowing for the construction of proteins utilizing only cell components instead of living cells. This can be lyophilized on a substrate, like paper. (2) Using paper as a microfluidic platform that is flexible, stable, cheap, and wicking. The capillary action eliminates the need for pumps, reducing volume, mass, and potential failing points. Electrodes can be printed on the paper to sense for biochemicals. (3) Developing a modular, semi-autonomous microfluidic device that can be easily adapted for a variety of common biological experiments. This versatility will allow for quicker and cheaper experimentation. These improvements to satellite experiment platforms have the potential to radically increase the return from NASA's biological and field studies with reduced development time, mass, and cost with increased robustness data and interpretation.

Describing the complexity of systems: multivariable "set complexity" and the information basis of systems biology.

PubMed

Galas, David J; Sakhanenko, Nikita A; Skupin, Alexander; Ignac, Tomasz

2014-02-01

Context dependence is central to the description of complexity. Keying on the pairwise definition of "set complexity," we use an information theory approach to formulate general measures of systems complexity. We examine the properties of multivariable dependency starting with the concept of interaction information. We then present a new measure for unbiased detection of multivariable dependency, "differential interaction information." This quantity for two variables reduces to the pairwise "set complexity" previously proposed as a context-dependent measure of information in biological systems. We generalize it here to an arbitrary number of variables. Critical limiting properties of the "differential interaction information" are key to the generalization. This measure extends previous ideas about biological information and provides a more sophisticated basis for the study of complexity. The properties of "differential interaction information" also suggest new approaches to data analysis. Given a data set of system measurements, differential interaction information can provide a measure of collective dependence, which can be represented in hypergraphs describing complex system interaction patterns. We investigate this kind of analysis using simulated data sets. The conjoining of a generalized set complexity measure, multivariable dependency analysis, and hypergraphs is our central result. While our focus is on complex biological systems, our results are applicable to any complex system.

Human-aided admixture may fuel ecosystem transformation during biological invasions: theoretical and experimental evidence.

PubMed

Molofsky, Jane; Keller, Stephen R; Lavergne, Sébastien; Kaproth, Matthew A; Eppinga, Maarten B

2014-04-01

Biological invasions can transform our understanding of how the interplay of historical isolation and contemporary (human-aided) dispersal affects the structure of intraspecific diversity in functional traits, and in turn, how changes in functional traits affect other scales of biological organization such as communities and ecosystems. Because biological invasions frequently involve the admixture of previously isolated lineages as a result of human-aided dispersal, studies of invasive populations can reveal how admixture results in novel genotypes and shifts in functional trait variation within populations. Further, because invasive species can be ecosystem engineers within invaded ecosystems, admixture-induced shifts in the functional traits of invaders can affect the composition of native biodiversity and alter the flow of resources through the system. Thus, invasions represent promising yet under-investigated examples of how the effects of short-term evolutionary changes can cascade across biological scales of diversity. Here, we propose a conceptual framework that admixture between divergent source populations during biological invasions can reorganize the genetic variation underlying key functional traits, leading to shifts in the mean and variance of functional traits within invasive populations. Changes in the mean or variance of key traits can initiate new ecological feedback mechanisms that result in a critical transition from a native ecosystem to a novel invasive ecosystem. We illustrate the application of this framework with reference to a well-studied plant model system in invasion biology and show how a combination of quantitative genetic experiments, functional trait studies, whole ecosystem field studies and modeling can be used to explore the dynamics predicted to trigger these critical transitions.

Networks’ Characteristics Matter for Systems Biology

PubMed Central

Rider, Andrew K.; Milenković, Tijana; Siwo, Geoffrey H.; Pinapati, Richard S.; Emrich, Scott J.; Ferdig, Michael T.; Chawla, Nitesh V.

2015-01-01

A fundamental goal of systems biology is to create models that describe relationships between biological components. Networks are an increasingly popular approach to this problem. However, a scientist interested in modeling biological (e.g., gene expression) data as a network is quickly confounded by the fundamental problem: how to construct the network? It is fairly easy to construct a network, but is it the network for the problem being considered? This is an important problem with three fundamental issues: How to weight edges in the network in order to capture actual biological interactions? What is the effect of the type of biological experiment used to collect the data from which the network is constructed? How to prune the weighted edges (or what cut-off to apply)? Differences in the construction of networks could lead to different biological interpretations. Indeed, we find that there are statistically significant dissimilarities in the functional content and topology between gene co-expression networks constructed using different edge weighting methods, data types, and edge cut-offs. We show that different types of known interactions, such as those found through Affinity Capture-Luminescence or Synthetic Lethality experiments, appear in significantly varying amounts in networks constructed in different ways. Hence, we demonstrate that different biological questions may be answered by the different networks. Consequently, we posit that the approach taken to build a network can be matched to biological questions to get targeted answers. More study is required to understand the implications of different network inference approaches and to draw reliable conclusions from networks used in the field of systems biology. PMID:26500772

[Metabolomics research of medicinal plants].

PubMed

Duan, Li-Xin; Dai, Yun-Tao; Sun, Chao; Chen, Shi-Lin

2016-11-01

Metabolomics is the comprehensively study of chemical processes involving small molecule metabolites. It is an important part of systems biology, and is widely applied in complex traditional Chinese medicine（TCM）system. Metabolites biosynthesized by medicinal plants are the effective basis for TCM. Metabolomics studies of medicinal plants will usher in a new period of vigorous development with the implementation of Herb Genome Program and the development of TCM synthetic biology. This manuscript introduces the recent research progresses of metabolomics technology and the main research contents of metabolomics studies for medicinal plants, including identification and quality evaluation for medicinal plants, cultivars breeding, stress resistance, metabolic pathways, metabolic network, metabolic engineering and synthetic biology researches. The integration of genomics, transcriptomics and metabolomics approaches will finally lay foundation for breeding of medicinal plants, R&D, quality and safety evaluation of innovative drug. Copyright© by the Chinese Pharmaceutical Association.

Tramesan, a novel polysaccharide from Trametes versicolor. Structural characterization and biological effects

PubMed Central

Sveronis, Aris; Cescutti, Paola; Rizzo, Roberto

2017-01-01

Mushrooms represent a formidable source of bioactive compounds. Some of these may be considered as biological response modifiers; these include compounds with a specific biological function: antibiotics (e.g. plectasin), immune system stimulator (e,g, lentinan), antitumor agents (e.g. krestin, PSK) and hypolipidemic agents (e.g. lovastatin) inter alia. In this study, we focused on the Chinese medicinal mushroom “yun zhi”, Trametes versicolor, traditionally used for (cit.) “replenish essence and qi (vital energy)”. Previous studies indicated the potential activity of extracts from culture filtrate of asexual mycelia of T. versicolor in controlling the growth and secondary metabolism (e.g. mycotoxins) of plant pathogenic fungi. The quest of active principles produced by T. versicolor, allowed us characterising an exo-polysaccharide released in its culture filtrate and naming it Tramesan. Herein we evaluate the biological activity of Tramesan in different organisms: plants, mammals and plant pathogenic fungi. We suggest that the bioactivity of Tramesan relies mostly on its ability to act as pro antioxidant molecule regardless the biological system on which it was applied. PMID:28829786

Tramesan, a novel polysaccharide from Trametes versicolor. Structural characterization and biological effects.

PubMed

Scarpari, Marzia; Reverberi, Massimo; Parroni, Alessia; Scala, Valeria; Fanelli, Corrado; Pietricola, Chiara; Zjalic, Slaven; Maresca, Vittoria; Tafuri, Agostino; Ricciardi, Maria R; Licchetta, Roberto; Mirabilii, Simone; Sveronis, Aris; Cescutti, Paola; Rizzo, Roberto

2017-01-01

Mushrooms represent a formidable source of bioactive compounds. Some of these may be considered as biological response modifiers; these include compounds with a specific biological function: antibiotics (e.g. plectasin), immune system stimulator (e,g, lentinan), antitumor agents (e.g. krestin, PSK) and hypolipidemic agents (e.g. lovastatin) inter alia. In this study, we focused on the Chinese medicinal mushroom "yun zhi", Trametes versicolor, traditionally used for (cit.) "replenish essence and qi (vital energy)". Previous studies indicated the potential activity of extracts from culture filtrate of asexual mycelia of T. versicolor in controlling the growth and secondary metabolism (e.g. mycotoxins) of plant pathogenic fungi. The quest of active principles produced by T. versicolor, allowed us characterising an exo-polysaccharide released in its culture filtrate and naming it Tramesan. Herein we evaluate the biological activity of Tramesan in different organisms: plants, mammals and plant pathogenic fungi. We suggest that the bioactivity of Tramesan relies mostly on its ability to act as pro antioxidant molecule regardless the biological system on which it was applied.

Membrane materials for storing biological samples intended for comparative nanotoxicological testing

NASA Astrophysics Data System (ADS)

Metelkin, A.; Kuznetsov, D.; Kolesnikov, E.; Chuprunov, K.; Kondakov, S.; Osipov, A.; Samsonova, J.

2015-11-01

The study is aimed at identifying the samples of most promising membrane materials for storing dry specimens of biological fluids (Dried Blood Spots, DBS technology). Existing sampling systems using cellulose fiber filter paper have a number of drawbacks such as uneven distribution of the sample spot, dependence of the spot spreading area on the individual biosample properties, incomplete washing-off of the sample due to partially inconvertible sorption of blood components on cellulose fibers, etc. Samples of membrane materials based on cellulose, polymers and glass fiber with applied biosamples were studied using methods of scanning electron microscopy, FT-IR spectroscopy and surface-wetting measurement. It was discovered that cellulose-based membrane materials sorb components of biological fluids inside their structure, while membranes based on glass fiber display almost no interaction with the samples and biological fluid components dry to films in the membrane pores between the structural fibers. This characteristic, together with the fact that membrane materials based on glass fiber possess sufficient strength, high wetting properties and good storage capacity, attests them as promising material for dry samples of biological fluids storage systems.

Development of sensory systems in zebrafish (Danio rerio)

NASA Technical Reports Server (NTRS)

Moorman, S. J.

2001-01-01

Zebrafish possess all of the classic sensory modalities: taste, tactile, smell, balance, vision, and hearing. For each sensory system, this article provides a brief overview of the system in the adult zebrafish followed by a more detailed overview of the development of the system. By far the majority of studies performed in each of the sensory systems of the zebrafish have involved some aspect of molecular biology or genetics. Although molecular biology and genetics are not major foci of the paper, brief discussions of some of the mutant strains of zebrafish that have developmental defects in each specific sensory system are included. The development of the sensory systems is only a small sampling of the work being done using zebrafish and provides a mere glimpse of the potential of this model for the study of vertebrate development, physiology, and human disease.

Applications of NMR-based metabolomics in biological and environmental research

EPA Science Inventory

As a complimentary tool to other omics platforms, metabolomics is increasingly being used by biologists to study the dynamic response of biological systems (cells, tissues, or whole organisms) under diverse physiological or pathological conditions. Metabolomics deals with the qu...

Extended Kalman Filter for Estimation of Parameters in Nonlinear State-Space Models of Biochemical Networks

PubMed Central

Sun, Xiaodian; Jin, Li; Xiong, Momiao

2008-01-01

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks. PMID:19018286

Synthetic and systems biology for microbial production of commodity chemicals.

PubMed

Chubukov, Victor; Mukhopadhyay, Aindrila; Petzold, Christopher J; Keasling, Jay D; Martín, Héctor García

2016-01-01

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

Synthetic and systems biology for microbial production of commodity chemicals

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

Chubukov, Victor; Mukhopadhyay, Aindrila; Petzold, Christopher J.

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges startmore » at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.« less

Synthetic and systems biology for microbial production of commodity chemicals

DOE PAGES

Chubukov, Victor; Mukhopadhyay, Aindrila; Petzold, Christopher J.; ...

2016-04-07

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges startmore » at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.« less

Next-Generation Machine Learning for Biological Networks.

PubMed

Camacho, Diogo M; Collins, Katherine M; Powers, Rani K; Costello, James C; Collins, James J

2018-06-14

Machine learning, a collection of data-analytical techniques aimed at building predictive models from multi-dimensional datasets, is becoming integral to modern biological research. By enabling one to generate models that learn from large datasets and make predictions on likely outcomes, machine learning can be used to study complex cellular systems such as biological networks. Here, we provide a primer on machine learning for life scientists, including an introduction to deep learning. We discuss opportunities and challenges at the intersection of machine learning and network biology, which could impact disease biology, drug discovery, microbiome research, and synthetic biology. Copyright © 2018 Elsevier Inc. All rights reserved.

Synthetic biology through biomolecular design and engineering.

PubMed

Channon, Kevin; Bromley, Elizabeth H C; Woolfson, Derek N

2008-08-01

Synthetic biology is a rapidly growing field that has emerged in a global, multidisciplinary effort among biologists, chemists, engineers, physicists, and mathematicians. Broadly, the field has two complementary goals: To improve understanding of biological systems through mimicry and to produce bio-orthogonal systems with new functions. Here we review the area specifically with reference to the concept of synthetic biology space, that is, a hierarchy of components for, and approaches to generating new synthetic and functional systems to test, advance, and apply our understanding of biological systems. In keeping with this issue of Current Opinion in Structural Biology, we focus largely on the design and engineering of biomolecule-based components and systems.

Thermodynamics of Biological Processes

PubMed Central

Garcia, Hernan G.; Kondev, Jane; Orme, Nigel; Theriot, Julie A.; Phillips, Rob

2012-01-01

There is a long and rich tradition of using ideas from both equilibrium thermodynamics and its microscopic partner theory of equilibrium statistical mechanics. In this chapter, we provide some background on the origins of the seemingly unreasonable effectiveness of ideas from both thermodynamics and statistical mechanics in biology. After making a description of these foundational issues, we turn to a series of case studies primarily focused on binding that are intended to illustrate the broad biological reach of equilibrium thinking in biology. These case studies include ligand-gated ion channels, thermodynamic models of transcription, and recent applications to the problem of bacterial chemotaxis. As part of the description of these case studies, we explore a number of different uses of the famed Monod–Wyman–Changeux (MWC) model as a generic tool for providing a mathematical characterization of two-state systems. These case studies should provide a template for tailoring equilibrium ideas to other problems of biological interest. PMID:21333788

Bioinspired Infrared Sensing Materials and Systems.

PubMed

Shen, Qingchen; Luo, Zhen; Ma, Shuai; Tao, Peng; Song, Chengyi; Wu, Jianbo; Shang, Wen; Deng, Tao

2018-05-11

Bioinspired engineering offers a promising alternative approach in accelerating the development of many man-made systems. Next-generation infrared (IR) sensing systems can also benefit from such nature-inspired approach. The inherent compact and uncooled operation of biological IR sensing systems provides ample inspiration for the engineering of portable and high-performance artificial IR sensing systems. This review overviews the current understanding of the biological IR sensing systems, most of which are thermal-based IR sensors that rely on either bolometer-like or photomechanic sensing mechanism. The existing efforts inspired by the biological IR sensing systems and possible future bioinspired approaches in the development of new IR sensing systems are also discussed in the review. Besides these biological IR sensing systems, other biological systems that do not have IR sensing capabilities but can help advance the development of engineered IR sensing systems are also discussed, and the related engineering efforts are overviewed as well. Further efforts in understanding the biological IR sensing systems, the learning from the integration of multifunction in biological systems, and the reduction of barriers to maximize the multidiscipline collaborations are needed to move this research field forward. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Petunia, Your Next Supermodel?

PubMed Central

Vandenbussche, Michiel; Chambrier, Pierre; Rodrigues Bento, Suzanne; Morel, Patrice

2016-01-01

Plant biology in general, and plant evo–devo in particular would strongly benefit from a broader range of available model systems. In recent years, technological advances have facilitated the analysis and comparison of individual gene functions in multiple species, representing now a fairly wide taxonomic range of the plant kingdom. Because genes are embedded in gene networks, studying evolution of gene function ultimately should be put in the context of studying the evolution of entire gene networks, since changes in the function of a single gene will normally go together with further changes in its network environment. For this reason, plant comparative biology/evo–devo will require the availability of a defined set of ‘super’ models occupying key taxonomic positions, in which performing gene functional analysis and testing genetic interactions ideally is as straightforward as, e.g., in Arabidopsis. Here we review why petunia has the potential to become one of these future supermodels, as a representative of the Asterid clade. We will first detail its intrinsic qualities as a model system. Next, we highlight how the revolution in sequencing technologies will now finally allows exploitation of the petunia system to its full potential, despite that petunia has already a long history as a model in plant molecular biology and genetics. We conclude with a series of arguments in favor of a more diversified multi-model approach in plant biology, and we point out where the petunia model system may further play a role, based on its biological features and molecular toolkit. PMID:26870078

The centrifuge facility - A life sciences research laboratory for Space Station Freedom

NASA Technical Reports Server (NTRS)

Fuller, Charles A.; Johnson, Catherine C.; Hargens, Alan R.

1991-01-01

The paper describes the centrifugal facility that is presently being developed by NASA for studies aboard the Space Station Freedom on the role of gravity, or its absence, at varying intensities for varying periods of time and with multiple model systems. Special attention is given to the design of the centrifuge system, the habitats designed to hold plants and animals, the glovebox system designed for experimental manipulations of the specimens, and the service unit. Studies planned for the facility will include experiments in the following disciplines: cell and developmental biology, plant biology, regulatory physiology, musculoskeletal physiology, behavior and performance, neurosciences, cardiopulmonary physiology, and environmental health and radiation.

Biomolecular computing systems: principles, progress and potential.

PubMed

Benenson, Yaakov

2012-06-12

The task of information processing, or computation, can be performed by natural and man-made 'devices'. Man-made computers are made from silicon chips, whereas natural 'computers', such as the brain, use cells and molecules. Computation also occurs on a much smaller scale in regulatory and signalling pathways in individual cells and even within single biomolecules. Indeed, much of what we recognize as life results from the remarkable capacity of biological building blocks to compute in highly sophisticated ways. Rational design and engineering of biological computing systems can greatly enhance our ability to study and to control biological systems. Potential applications include tissue engineering and regeneration and medical treatments. This Review introduces key concepts and discusses recent progress that has been made in biomolecular computing.

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

Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2018-03-01

I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

PubMed

Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

2006-07-01

Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

Bacteriophage-based synthetic biology for the study of infectious diseases

PubMed Central

Lu, Timothy K.

2014-01-01

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

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

Magnetic nanoparticles in different biological environments analyzed by magnetic particle spectroscopy

NASA Astrophysics Data System (ADS)

Löwa, Norbert; Seidel, Maria; Radon, Patricia; Wiekhorst, Frank

2017-04-01

Quantification of magnetic iron oxide nanoparticles (MNP) in biological systems like cells, tissue, or organs is of vital importance for development of novel biomedical applications, e.g. magnetofection, drug targeting or hyperthermia. Among others, the recently developed magnetic measurement technique magnetic particle spectroscopy (MPS) provides signals that are specific for MNP. MPS is based on the non-linear magnetic response of MNP exposed to a strong sinusoidal excitation field of up to 25 mT amplitude and 25 kHz frequency. So far, it has been proven a powerful tool for quantification of MNP in biological systems. In this study we investigated in detail the influence of typical biological media on the magnetic behavior of different MNP systems by MPS. The results reveal that amplitude and shape (ratio of harmonics) of the MPS spectra allow for perceptively monitoring changes in MNP magnetism caused by different physiological media. Additionally, the observed linear correlation between MPS amplitude and shape alterations can be used to reduce the quantification uncertainty for MNP suspended in a biological environment.

Rewiring cells: synthetic biology as a tool to interrogate the organizational principles of living systems.

PubMed

Bashor, Caleb J; Horwitz, Andrew A; Peisajovich, Sergio G; Lim, Wendell A

2010-01-01

The living cell is an incredibly complex entity, and the goal of predictively and quantitatively understanding its function is one of the next great challenges in biology. Much of what we know about the cell concerns its constituent parts, but to a great extent we have yet to decode how these parts are organized to yield complex physiological function. Classically, we have learned about the organization of cellular networks by disrupting them through genetic or chemical means. The emerging discipline of synthetic biology offers an additional, powerful approach to study systems. By rearranging the parts that comprise existing networks, we can gain valuable insight into the hierarchical logic of the networks and identify the modular building blocks that evolution uses to generate innovative function. In addition, by building minimal toy networks, one can systematically explore the relationship between network structure and function. Here, we outline recent work that uses synthetic biology approaches to investigate the organization and function of cellular networks, and describe a vision for a synthetic biology toolkit that could be used to interrogate the design principles of diverse systems.

A cell-based systems biology assessment of human blood to monitor immune responses after influenza vaccination.

PubMed

Hoek, Kristen L; Samir, Parimal; Howard, Leigh M; Niu, Xinnan; Prasad, Nripesh; Galassie, Allison; Liu, Qi; Allos, Tara M; Floyd, Kyle A; Guo, Yan; Shyr, Yu; Levy, Shawn E; Joyce, Sebastian; Edwards, Kathryn M; Link, Andrew J

2015-01-01

Systems biology is an approach to comprehensively study complex interactions within a biological system. Most published systems vaccinology studies have utilized whole blood or peripheral blood mononuclear cells (PBMC) to monitor the immune response after vaccination. Because human blood is comprised of multiple hematopoietic cell types, the potential for masking responses of under-represented cell populations is increased when analyzing whole blood or PBMC. To investigate the contribution of individual cell types to the immune response after vaccination, we established a rapid and efficient method to purify human T and B cells, natural killer (NK) cells, myeloid dendritic cells (mDC), monocytes, and neutrophils from fresh venous blood. Purified cells were fractionated and processed in a single day. RNA-Seq and quantitative shotgun proteomics were performed to determine expression profiles for each cell type prior to and after inactivated seasonal influenza vaccination. Our results show that transcriptomic and proteomic profiles generated from purified immune cells differ significantly from PBMC. Differential expression analysis for each immune cell type also shows unique transcriptomic and proteomic expression profiles as well as changing biological networks at early time points after vaccination. This cell type-specific information provides a more comprehensive approach to monitor vaccine responses.

Supporting cognition in systems biology analysis: findings on users' processes and design implications.

PubMed

Mirel, Barbara

2009-02-13

Current usability studies of bioinformatics tools suggest that tools for exploratory analysis support some tasks related to finding relationships of interest but not the deep causal insights necessary for formulating plausible and credible hypotheses. To better understand design requirements for gaining these causal insights in systems biology analyses a longitudinal field study of 15 biomedical researchers was conducted. Researchers interacted with the same protein-protein interaction tools to discover possible disease mechanisms for further experimentation. Findings reveal patterns in scientists' exploratory and explanatory analysis and reveal that tools positively supported a number of well-structured query and analysis tasks. But for several of scientists' more complex, higher order ways of knowing and reasoning the tools did not offer adequate support. Results show that for a better fit with scientists' cognition for exploratory analysis systems biology tools need to better match scientists' processes for validating, for making a transition from classification to model-based reasoning, and for engaging in causal mental modelling. As the next great frontier in bioinformatics usability, tool designs for exploratory systems biology analysis need to move beyond the successes already achieved in supporting formulaic query and analysis tasks and now reduce current mismatches with several of scientists' higher order analytical practices. The implications of results for tool designs are discussed.

Ferromagnetic nanoparticles containing biologically active alkanolamines: preparation and properties

NASA Astrophysics Data System (ADS)

Segal, I.; Zablotskaya, A.; Lukevics, E.; Maiorov, M.; Zablotsky, D.

2005-12-01

The objective of the present study is to investigate the possibility of sorption on ultrafine magnetic particles of some model biologically active organosilicon alkanolamines, structural analogs of natural biologically active substances, choline and colamine, with increased lipophilicity. Double-coated ferromagnetic samples containing oleic acid, as a first layer, and organosilicon alcanolamines, as a second layer, were obtained and characterized by their physical/chemical (sorption and magnetisation) and biological (toxicity and cytotoxicity) properties. The present results clearly reveal the sorption of the biologically active alkanolamines on the surface of magnetic particles and a principal possibility to coat magnetite directly with biologically active alkanolamines, creating a mono-layer cover. The data presented in the study of cytotoxic properties of the newly obtained ferromagnetic nanoparticles show that it is reasonable to investigate such systems as potential cytotoxic agents. Tables 3, Figs 3, Refs 16.

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.

From immunology to MRI data anlysis: Problems in mathematical biology

NASA Astrophysics Data System (ADS)

Waters, Ryan Samuel

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

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

PubMed Central

Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems. PMID:27187178

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

PubMed

Pârvu, Ovidiu; Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems.

Introducing Evolution to Non-Biology Majors via the Fossil Record: A Case Study from the Israeli High School System.

ERIC Educational Resources Information Center

Dodick, Jeff; Orion, Nir

2003-01-01

Discusses challenges faced in the teaching and learning of evolution. Presents a curricular program and a case study on evolutionary biology. Investigates students' conceptual knowledge after exposure to the program "From Dinosaurs to Darwin," which focuses on fossil records as evidence of evolution. (Contains 32 references.) (YDS)

A Model System for the Study of Gene Expression in the Undergraduate Laboratory

ERIC Educational Resources Information Center

Hargadon, Kristian M.

2016-01-01

The flow of genetic information from DNA to RNA to protein, otherwise known as the "central dogma" of biology, is one of the most basic and overarching concepts in the biological sciences. Nevertheless, numerous studies have reported student misconceptions at the undergraduate level of this fundamental process of gene expression. This…

Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit.

PubMed

Qin, Nan; Shen, Chenyang; Tsai, Min-Yu; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B; Parodi, Katia; Jia, Xun

2018-01-01

One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC. The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases. Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation. We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame. Copyright © 2017 Elsevier Inc. All rights reserved.

Computational modeling of ion transport through nanopores.

PubMed

Modi, Niraj; Winterhalter, Mathias; Kleinekathöfer, Ulrich

2012-10-21

Nanoscale pores are ubiquitous in biological systems while artificial nanopores are being fabricated for an increasing number of applications. Biological pores are responsible for the transport of various ions and substrates between the different compartments of biological systems separated by membranes while artificial pores are aimed at emulating such transport properties. As an experimental method, electrophysiology has proven to be an important nano-analytical tool for the study of substrate transport through nanopores utilizing ion current measurements as a probe for the detection. Independent of the pore type, i.e., biological or synthetic, and objective of the study, i.e., to model cellular processes of ion transport or electrophysiological experiments, it has become increasingly important to understand the dynamics of ions in nanoscale confinements. To this end, numerical simulations have established themselves as an indispensable tool to decipher ion transport processes through biological as well as artificial nanopores. This article provides an overview of different theoretical and computational methods to study ion transport in general and to calculate ion conductance in particular. Potential new improvements in the existing methods and their applications are highlighted wherever applicable. Moreover, representative examples are given describing the ion transport through biological and synthetic nanopores as well as the high selectivity of ion channels. Special emphasis is placed on the usage of molecular dynamics simulations which already have demonstrated their potential to unravel ion transport properties at an atomic level.

Developmental Gene Regulation and Mechanisms of Evolution

NASA Technical Reports Server (NTRS)

1998-01-01

The Marine Biological Laboratory and the National Aeronautics and Space Administration have established a cooperative agreement with the formation of a Center for Advanced Studies 'in the Space Life Sciences (CASSLS) at the MBL. This Center serves as an interface between NASA and the basic science community, addressing issues of mutual interest. The Center for Advanced Studies 'in the Space Life Sciences provides a forum for scientists to think and discuss, often for the first time, the role that gravity and aspects of spaceflight may play 'in fundamental cellular and physiologic processes. In addition the Center will sponsor discussions on evolutionary biology. These interactions will inform the community of research opportunities that are of interest to NASA. This workshop is one of a series of symposia, workshops and seminars that will be held at the MBL to advise NASA on a wide variety of topics in the life sciences, including cell biology, developmental biology, mg evolutionary biology, molecular biology, neurobiology, plant biology and systems biology.

Singlet oxygen detection in biological systems: Uses and limitations.

PubMed

Koh, Eugene; Fluhr, Robert

2016-07-02

The study of singlet oxygen in biological systems is challenging in many ways. Singlet oxygen is a relatively unstable ephemeral molecule, and its properties make it highly reactive with many biomolecules, making it difficult to quantify accurately. Several methods have been developed to study this elusive molecule, but most studies thus far have focused on those conditions that produce relatively large amounts of singlet oxygen. However, the need for more sensitive methods is required as one begins to explore the levels of singlet oxygen required in signaling and regulatory processes. Here we discuss the various methods used in the study of singlet oxygen, and outline their uses and limitations.

78 FR 22527 - Army Science Board Request for Information on Technology and Core Competencies

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-16

...); Edgewood Chemical Biological Command (ECBC); Natick Soldier Research, Development & Engineering Center...; C4ISR; Night Vision; Chemical/Biological Warfare; and Soldier Systems. The study will focus on...); Armament Research, Development & Engineering Center (ARDEC); Aviation & Missile Research, Development...

POLISHING EFFLUENT FROM A PERCHLORATE-REDUCING ANAEROBIC BIOLOGICAL CONTACTOR

EPA Science Inventory

The U.S. Environmental Protection Agency undertook at 3 ½ year pilot-scale biological perchlorate treatment study that included two long (311 and 340 days) examinations of anaerobic effluent polishing. The polishing system consisted of hydrogen peroxide addition and aeration, fo...

Human Nature, Crime and Society.

ERIC Educational Resources Information Center

Mednick, Sarnoff A.

The paper discusses literature which reports biological factors of criminal behavior and suggests how such biological characteristics might interact with the learning of moral behavior. The first three studies of predelinquent and prerecidivistic criminals measured autonomic nervous system responses to stress. Those who later became delinquent…

CURRENT PRACTICES IN QSAR DEVELOPMENT AND APPLICATIONS

EPA Science Inventory

Current Practices in QSAR Development and Applications

Although it is commonly assumed that the structure and properties of a single chemical determines its activity in a particular biological system, it is only through study of how biological activity varies with changes...

Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology.

PubMed

Aretz, Ina; Meierhofer, David

2016-04-27

Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.

Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology

PubMed Central

Aretz, Ina; Meierhofer, David

2016-01-01

Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology. PMID:27128910

Invited review article: Advanced light microscopy for biological space research.

PubMed

De Vos, Winnok H; Beghuin, Didier; Schwarz, Christian J; Jones, David B; van Loon, Jack J W A; Bereiter-Hahn, Juergen; Stelzer, Ernst H K

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Invited Review Article: Advanced light microscopy for biological space research

NASA Astrophysics Data System (ADS)

De Vos, Winnok H.; Beghuin, Didier; Schwarz, Christian J.; Jones, David B.; van Loon, Jack J. W. A.; Bereiter-Hahn, Juergen; Stelzer, Ernst H. K.

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Landfill leachate treatment using a rotating biological contactor and an upward-flow anaerobic sludge bed reactor

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

Castillo, E.; Vergara, M.; Moreno, Y.

2007-07-01

This paper describes the feasibility of an aerobic system (rotating biological contactor, RBC) and a biological anaerobic system (upward-flow anaerobic sludge bed reactor) at small scale for the treatment of a landfill leachate. In the first phase of the aerobic system study, a cyclic-batch RBC system was used to select perforated acetate discs among three different acetate disc configurations. These discs were chosen on the basis of high COD removal (65%) and biological stability. In the second phase, the RBC system (using four stages) was operated continuously at different hydraulic retention times (HRT), at different rotational speeds, and with varyingmore » organic concentrations of the influent leachate (2500-9000 mg L{sup -1}). Forty percent of the total surface area of each perforated disc was submerged in the leachate. A COD removal of about 52% was obtained at an HRT of 24 h and a rotational speed of 6 rpm. For the anaerobic system, the reactor was evaluated with a volumetric organic load of 3273 g-COD m{sup -3} day{sup -1} at an HRT of 54, 44, 39, 24 and 17 h. At these conditions, the system reached COD removal efficiencies of 62%, 61%, 59%, 44% and 24%, respectively.« less

Assessment of the effects of student response systems on student learning and attitudes over a broad range of biology courses.

PubMed

Preszler, Ralph W; Dawe, Angus; Shuster, Charles B; Shuster, Michèle

2007-01-01

With the advent of wireless technology, new tools are available that are intended to enhance students' learning and attitudes. To assess the effectiveness of wireless student response systems in the biology curriculum at New Mexico State University, a combined study of student attitudes and performance was undertaken. A survey of students in six biology courses showed that strong majorities of students had favorable overall impressions of the use of student response systems and also thought that the technology improved their interest in the course, attendance, and understanding of course content. Students in lower-division courses had more strongly positive overall impressions than did students in upper-division courses. To assess the effects of the response systems on student learning, the number of in-class questions was varied within each course throughout the semester. Students' performance was compared on exam questions derived from lectures with low, medium, or high numbers of in-class questions. Increased use of the response systems in lecture had a positive influence on students' performance on exam questions across all six biology courses. Students not only have favorable opinions about the use of student response systems, increased use of these systems increases student learning.

Bayesian parameter estimation for nonlinear modelling of biological pathways.

PubMed

Ghasemi, Omid; Lindsey, Merry L; Yang, Tianyi; Nguyen, Nguyen; Huang, Yufei; Jin, Yu-Fang

2011-01-01

The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC) method. We applied this approach to the biological pathways involved in the left ventricle (LV) response to myocardial infarction (MI) and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly parameterized dynamic systems. Our proposed Bayesian algorithm successfully estimated parameters in nonlinear mathematical models for biological pathways. This method can be further extended to high order systems and thus provides a useful tool to analyze biological dynamics and extract information using temporal data.

TRIENNIAL LACTATION SYMPOSIUM: Nutrigenomics in livestock: Systems biology meets nutrition.

PubMed

Loor, J J; Vailati-Riboni, M; McCann, J C; Zhou, Z; Bionaz, M

2015-12-01

The advent of high-throughput technologies to study an animal's genome, proteome, and metabolome (i.e., "omics" tools) constituted a setback to the use of reductionism in livestock research. More recent development of "next-generation sequencing" tools was instrumental in allowing in-depth studies of the microbiome in the rumen and other sections of the gastrointestinal tract. Omics, along with bioinformatics, constitutes the foundation of modern systems biology, a field of study widely used in model organisms (e.g., rodents, yeast, humans) to enhance understanding of the complex biological interactions occurring within cells and tissues at the gene, protein, and metabolite level. Application of systems biology concepts is ideal for the study of interactions between nutrition and physiological state with tissue and cell metabolism and function during key life stages of livestock species, including the transition from pregnancy to lactation, in utero development, or postnatal growth. Modern bioinformatic tools capable of discerning functional outcomes and biologically meaningful networks complement the ever-increasing ability to generate large molecular, microbial, and metabolite data sets. Simultaneous visualization of the complex intertissue adaptations to physiological state and nutrition can now be discerned. Studies to understand the linkages between the microbiome and the absorptive epithelium using the integrative approach are emerging. We present examples of new knowledge generated through the application of functional analyses of transcriptomic, proteomic, and metabolomic data sets encompassing nutritional management of dairy cows, pigs, and poultry. Published work to date underscores that the integrative approach across and within tissues may prove useful for fine-tuning nutritional management of livestock. An important goal during this process is to uncover key molecular players involved in the organismal adaptations to nutrition.

Micro-separation toward systems biology.

PubMed

Liu, Bi-Feng; Xu, Bo; Zhang, Guisen; Du, Wei; Luo, Qingming

2006-02-17

Current biology is experiencing transformation in logic or philosophy that forces us to reevaluate the concept of cell, tissue or entire organism as a collection of individual components. Systems biology that aims at understanding biological system at the systems level is an emerging research area, which involves interdisciplinary collaborations of life sciences, computational and mathematical sciences, systems engineering, and analytical technology, etc. For analytical chemistry, developing innovative methods to meet the requirement of systems biology represents new challenges as also opportunities and responsibility. In this review, systems biology-oriented micro-separation technologies are introduced for comprehensive profiling of genome, proteome and metabolome, characterization of biomolecules interaction and single cell analysis such as capillary electrophoresis, ultra-thin layer gel electrophoresis, micro-column liquid chromatography, and their multidimensional combinations, parallel integrations, microfabricated formats, and nano technology involvement. Future challenges and directions are also suggested.

Estimating the dilemma strength for game systems. Comment on "Universal scaling for the dilemma strength in evolutionary games", by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Chen, Xiaojie

2015-09-01

The puzzle of cooperation exists widely in the realistic world, including biological, social, and engineering systems. How to solve the cooperation puzzle has received considerable attention in recent years [1]. Evolutionary game theory provides a common mathematical framework to study the problem of cooperation. In principle, these practical biological, social, or engineering systems can be described by complex game models composed of multiple autonomous individuals with mutual interactions. And generally there exists a dilemma for the evolution of cooperation in the game systems.

Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

PubMed Central

Gu, Shuo

2017-01-01

With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed. PMID:28690664

Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective.

PubMed

Gu, Shuo; Pei, Jianfeng

2017-01-01

With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regulatory function of herbal medicine in the treatment of inflammation at network level. Finally, a computational workflow for the network-based TCM study, derived from our previous successful applications, was proposed.

CINRG: Systems Biology of Glucocorticoids in Muscle Disease

DTIC Science & Technology

2012-10-01

Duchenne Muscular dystrophy , Glucocorticoids, Systems biology, Drug mechanism CINRG: Systems Biology of Glucocorticoids in Muscle Disease Zuyi Wang, Ph.D...2011-2012) for Contract W81XWH-09-1-0726 SYSTEMS BIOLOGY OF GLUCOCORTICOIDS IN MUSCLE DISEASE Introduction Duchenne muscular dystrophy ...DMD) is the most common and incurable muscular dystrophy of childhood. Muscle regeneration fails with advancing age, leading to considerable fibrosis

Tracing organizing principles: learning from the history of systems biology.

PubMed

Green, Sara; Wolkenhauer, Olaf

2013-01-01

With the emergence of systems biology, the identification of organizing principles is being highlighted as a key research aim. Researchers attempt to "reverse engineer" the functional organization of biological systems using methodologies from mathematics, engineering and computer science while taking advantage of data produced by new experimental techniques. While systems biology is a relatively new approach, the quest for general principles of biological organization dates back to systems theoretic approaches in early and mid-twentieth century. The aim of this paper is to draw on this historical background in order to increase the understanding of the motivation behind the search for general principles and to clarify different epistemic aims within systems biology. We pinpoint key aspects of earlier approaches that also underlie the current practice. These are i) the focus on relational and system-level properties, ii) the inherent critique of reductionism and fragmentation of knowledge resulting from overspecialization, and iii) the insight that the ideal of formulating abstract organizing principles is complementary to, rather than conflicting with, the aim of formulating detailed explanations of biological mechanisms. We argue that looking back not only helps us understand the current practice but also points to possible future directions for systems biology.

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

USGS Publications Warehouse

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

2005-01-01

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

Cosmic heavy ion tracks in mesoscopic biological test objects

NASA Technical Reports Server (NTRS)

Facius, R.

1994-01-01

Since more than 20 years ago, when the National Academy of Sciences and the National Research Council of the U.S.A. released their report on 'HZE particle effects in manned spaced flight', it has been emphasized how difficult - if not even impossible - it is to assess their radiobiological impact on man from conventional studies where biological test organisms are stochastically exposed to 'large' fluences of heavy ions. An alternative, competing approach had been realized in the BIOSTACK experiments, where the effects of single cosmic as well as accelerator - heavy ions on individual biological test organisms could be investigated. Although presented from the beginning as the preferable approach for terrestrial investigations with accelerator heavy ions too ('The BIOSTACK as an approach to high LET radiation research'), only recently this insight is gaining more widespread recognition. In space flight experiments, additional constraints imposed by the infrastructure of the vehicle or satellite further impede such investigations. Restrictions concern the physical detector systems needed for the registration of the cosmic heavy ions' trajectories as well as the biological systems eligible as test organisms. Such optimized procedures and techniques were developed for the investigations on chromosome aberrations induced by cosmic heavy ions in cells of the stem meristem of lettuce seeds (Lactuca sativa) and for the investigation of the radiobiological response of Wolffia arriza, which is the smallest flowering (water) plant. The biological effects were studied by the coworkers of the Russian Institute of Biomedical Problems (IBMP) which in cooperation with the European Space Agency ESA organized the exposure in the Biosatellites of the Cosmos series. Since biological investigations and physical measurements of particle tracks had to be performed in laboratories widely separated, the preferred fixed contact between biological test objects and the particle detectors until the geometrical correlation between tracks and organisms has been established could not be maintained. This gave rise to half a dozen of coordinate systems for different measurements which finally had to be related to a single stack reference system.

Understanding the biology and control of the poultry red mite Dermanyssus gallinae: a review.

PubMed

Pritchard, James; Kuster, Tatiana; Sparagano, Olivier; Tomley, Fiona

2015-01-01

Dermanyssus gallinae, the poultry red mite (PRM), is a blood-feeding ectoparasite capable of causing pathology in birds, amongst other animals. It is an increasingly important pathogen in egg layers and is responsible for substantial economic losses to the poultry industry worldwide. Even though PRM poses a serious problem, very little is known about the basic biology of the mite. Here we review the current body of literature describing red mite biology and discuss how this has been, or could be, used to develop methods to control PRM infestations. We focus primarily on the PRM digestive system, salivary glands, nervous system and exoskeleton and also explore areas of PRM biology which have to date received little or no study but have the potential to offer new control targets.

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

USGS Publications Warehouse

D'Erchia, Frank; Getter, James; D'Erchia, Terry D.; Root, Ralph; Stitt, Susan; White, Barbara

1998-01-01

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Systems medicine: a new approach to clinical practice.

PubMed

Cardinal-Fernández, Pablo; Nin, Nicolás; Ruíz-Cabello, Jesús; Lorente, José A

2014-10-01

Most respiratory diseases are considered complex diseases as their susceptibility and outcomes are determined by the interaction between host-dependent factors (genetic factors, comorbidities, etc.) and environmental factors (exposure to microorganisms or allergens, treatments received, etc.) The reductionist approach in the study of diseases has been of fundamental importance for the understanding of the different components of a system. Systems biology or systems medicine is a complementary approach aimed at analyzing the interactions between the different components within one organizational level (genome, transcriptome, proteome), and then between the different levels. Systems medicine is currently used for the interpretation and understanding of the pathogenesis and pathophysiology of different diseases, biomarker discovery, design of innovative therapeutic targets, and the drawing up of computational models for different biological processes. In this review we discuss the most relevant concepts of the theory underlying systems medicine, as well as its applications in the various biological processes in humans. Copyright © 2013 SEPAR. Published by Elsevier Espana. All rights reserved.

Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research.

PubMed

Jinawath, Natini; Bunbanjerdsuk, Sacarin; Chayanupatkul, Maneerat; Ngamphaiboon, Nuttapong; Asavapanumas, Nithi; Svasti, Jisnuson; Charoensawan, Varodom

2016-11-22

With the wealth of data accumulated from completely sequenced genomes and other high-throughput experiments, global studies of biological systems, by simultaneously investigating multiple biological entities (e.g. genes, transcripts, proteins), has become a routine. Network representation is frequently used to capture the presence of these molecules as well as their relationship. Network biology has been widely used in molecular biology and genetics, where several network properties have been shown to be functionally important. Here, we discuss how such methodology can be useful to translational biomedical research, where scientists traditionally focus on one or a small set of genes, diseases, and drug candidates at any one time. We first give an overview of network representation frequently used in biology: what nodes and edges represent, and review its application in preclinical research to date. Using cancer as an example, we review how network biology can facilitate system-wide approaches to identify targeted small molecule inhibitors. These types of inhibitors have the potential to be more specific, resulting in high efficacy treatments with less side effects, compared to the conventional treatments such as chemotherapy. Global analysis may provide better insight into the overall picture of human diseases, as well as identify previously overlooked problems, leading to rapid advances in medicine. From the clinicians' point of view, it is necessary to bridge the gap between theoretical network biology and practical biomedical research, in order to improve the diagnosis, prevention, and treatment of the world's major diseases.

An integrative approach to inferring biologically meaningful gene modules

PubMed Central

2011-01-01

Background The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. Results We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. Conclusions The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level. PMID:21791051

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.

Yeast: An Experimental Organism for Modern Biology.

ERIC Educational Resources Information Center

Botstein, David; Fink, Gerald R.

1988-01-01

Discusses the applicability and advantages of using yeasts as popular and ideal model systems for studying and understanding eukaryotic biology at the cellular and molecular levels. Cites experimental tractability and the cooperative tradition of the research community of yeast biologists as reasons for this success. (RT)

Developments in the Tools and Methodologies of Synthetic Biology

PubMed Central

Kelwick, Richard; MacDonald, James T.; Webb, Alexander J.; Freemont, Paul

2014-01-01

Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. However, biological systems are generally complex and unpredictable, and are therefore, intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a “body of knowledge” from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled, and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled, and its functionality tested. At each stage of the design cycle, an expanding repertoire of tools is being developed. In this review, we highlight several of these tools in terms of their applications and benefits to the synthetic biology community. PMID:25505788

On extracting design principles from biology: I. Method-General answers to high-level design questions for bioinspired robots.

PubMed

Haberland, M; Kim, S

2015-02-02

When millions of years of evolution suggest a particular design solution, we may be tempted to abandon traditional design methods and copy the biological example. However, biological solutions do not often translate directly into the engineering domain, and even when they do, copying eliminates the opportunity to improve. A better approach is to extract design principles relevant to the task of interest, incorporate them in engineering designs, and vet these candidates against others. This paper presents the first general framework for determining whether biologically inspired relationships between design input variables and output objectives and constraints are applicable to a variety of engineering systems. Using optimization and statistics to generalize the results beyond a particular system, the framework overcomes shortcomings observed of ad hoc methods, particularly those used in the challenging study of legged locomotion. The utility of the framework is demonstrated in a case study of the relative running efficiency of rotary-kneed and telescoping-legged robots.

Membrane Lipid Oscillation: An Emerging System of Molecular Dynamics in the Plant Membrane.

PubMed

Nakamura, Yuki

2018-03-01

Biological rhythm represents a major biological process of living organisms. However, rhythmic oscillation of membrane lipid content is poorly described in plants. The development of lipidomic technology has led to the illustration of precise molecular profiles of membrane lipids under various growth conditions. Compared with conventional lipid signaling, which produces unpredictable lipid changes in response to ever-changing environmental conditions, lipid oscillation generates a fairly predictable lipid profile, adding a new layer of biological function to the membrane system and possible cross-talk with the other chronobiological processes. This mini review covers recent studies elucidating membrane lipid oscillation in plants.

Suppression of single-wall carbon nanotube redox reaction by adsorbed proteins

NASA Astrophysics Data System (ADS)

Nakayama, Tomohito; Tanaka, Takeshi; Shiraki, Kentaro; Hase, Muneaki; Hirano, Atsushi

2018-07-01

Single-wall carbon nanotubes (SWCNTs) are widely used in biological applications. In biological systems, proteins readily adsorb to SWCNTs. However, little is known about the effects of proteins on the physicochemical properties of SWCNTs, such as their redox reaction. In this study, we measured the absorption and Raman spectra of SWCNTs dispersed in the presence of proteins such as bovine serum albumin to observe the redox reaction of the protein-adsorbed SWCNTs. The adsorbed proteins suppressed the redox reaction by forming thick and dense layers around the SWCNTs. Our findings are useful for understanding the behaviors of SWCNTs in biological systems.

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 366)

NASA Technical Reports Server (NTRS)

1992-01-01

This bibliography lists 248 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System during Aug. 1992. Subject coverage concentrates on the biological, physiological, psychological, and environmental effects to which humans are subjected during and following simulated or actual flight in the Earth's atmosphere or in interplanetary space. References describing similar effects on biological organisms of lower order are also included. Such related topics as sanitary problems, pharmacology, toxicology, safety and survival, life support systems, exobiology, and personnel factors receive appropriate attention. Applied research receives the most emphasis, but references to fundamental studies and theoretical principles related to experimental development also qualify for inclusion.

Nanoelectronics Meets Biology: From Novel Nanoscale Devices for Live Cell Recording to 3D Innervated Tissues†

PubMed Central

Duan, Xiaojie; Lieber, Charles M.

2013-01-01

High spatio-temporal resolution interfacing between electrical sensors and biological systems, from single live cells to tissues, is crucial for many areas, including fundamental biophysical studies as well as medical monitoring and intervention. This focused review summarizes recent progresses in the development and application of novel nanoscale devices for intracellular electrical recordings of action potentials, and the effort of merging electronic and biological systems seamlessly in three dimension using macroporous nanoelectronic scaffolds. The uniqueness of these nanoscale devices for minimally invasive, large scale, high spatial resolution, and three dimensional neural activity mapping will be highlighted. PMID:23946279

Databases, Repositories, and Other Data Resources in Structural Biology.

PubMed

Zheng, Heping; Porebski, Przemyslaw J; Grabowski, Marek; Cooper, David R; Minor, Wladek

2017-01-01

Structural biology, like many other areas of modern science, produces an enormous amount of primary, derived, and "meta" data with a high demand on data storage and manipulations. Primary data come from various steps of sample preparation, diffraction experiments, and functional studies. These data are not only used to obtain tangible results, like macromolecular structural models, but also to enrich and guide our analysis and interpretation of various biomedical problems. Herein we define several categories of data resources, (a) Archives, (b) Repositories, (c) Databases, and (d) Advanced Information Systems, that can accommodate primary, derived, or reference data. Data resources may be used either as web portals or internally by structural biology software. To be useful, each resource must be maintained, curated, as well as integrated with other resources. Ideally, the system of interconnected resources should evolve toward comprehensive "hubs", or Advanced Information Systems. Such systems, encompassing the PDB and UniProt, are indispensable not only for structural biology, but for many related fields of science. The categories of data resources described herein are applicable well beyond our usual scientific endeavors.

New tools for the analysis of glial cell biology in Drosophila.

PubMed

Awasaki, Takeshi; Lee, Tzumin

2011-09-01

Because of its genetic, molecular, and behavioral tractability, Drosophila has emerged as a powerful model system for studying molecular and cellular mechanisms underlying the development and function of nervous systems. The Drosophila nervous system has fewer neurons and exhibits a lower glia:neuron ratio than is seen in vertebrate nervous systems. Despite the simplicity of the Drosophila nervous system, glial organization in flies is as sophisticated as it is in vertebrates. Furthermore, fly glial cells play vital roles in neural development and behavior. In addition, powerful genetic tools are continuously being created to explore cell function in vivo. In taking advantage of these features, the fly nervous system serves as an excellent model system to study general aspects of glial cell development and function in vivo. In this article, we review and discuss advanced genetic tools that are potentially useful for understanding glial cell biology in Drosophila. Copyright © 2011 Wiley-Liss, Inc.

Using nuclear microscopy to characterize the interaction of textile-used silver nanoparticles with a biological wastewater treatment system

NASA Astrophysics Data System (ADS)

Bento, J. B.; Franca, R. D. G.; Pinheiro, T.; Alves, L. C.; Pinheiro, H. M.; Lourenço, N. D.

2017-08-01

The use of engineered nanoparticles in the textile industry has been rapidly increasing but their fate during biological wastewater treatment is largely unknown. The goal of the current study was to characterize the interaction of silver nanoparticles (AgNPs), used in the textile industry, with a biological wastewater treatment system based on aerobic granular sludge (AGS). The exposure tests were performed using a laboratory-scale sequencing batch reactor (SBR) system with AGS. The behavior and fate of textile AgNPs in the AGS system was studied with nuclear microscopy techniques. Elemental maps of AGS samples collected from the SBR showed that AgNPs typically clustered in agglomerates of small dimensions (<10 μm), which were preferentially associated with extracellular polymeric substances (EPS). This preliminary study highlights the potential application of nuclear microscopy for the characterization of the behavior and fate of AgNPs in AGS. The detailed compartmentalization of AgNPs in AGS components obtained with nuclear microscopy provides new and relevant information concerning AgNPs retention. This will be important in biotechnological terms to delineate strategies for AgNPs removal from textile wastewater.

Separating intrinsic from extrinsic fluctuations in dynamic biological systems

PubMed Central

Paulsson, Johan

2011-01-01

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems. PMID:21730172

Separating intrinsic from extrinsic fluctuations in dynamic biological systems.

PubMed

Hilfinger, Andreas; Paulsson, Johan

2011-07-19

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

Agribusiness: Industry Study Final Report, AY 2003-2004, Seminar 1

DTIC Science & Technology

2004-01-01

vulnerability of our nation’s food supply to a potential biological attack, primarily due to inadequate governmental oversight. He states, "The Food and Drug...national laboratory system to assist with chemical, biological , and radiological agent identification and analysis. Following the passage of the...Genetically Modified Foods,” June 2003. Chalk, Peter, “Hitting America’s Soft Underbelly: The Potential Threat of Deliberate Biological Attacks

Chemogenomics: a discipline at the crossroad of high throughput technologies, biomarker research, combinatorial chemistry, genomics, cheminformatics, bioinformatics and artificial intelligence.

PubMed

Maréchal, Eric

2008-09-01

Chemogenomics is the study of the interaction of functional biological systems with exogenous small molecules, or in broader sense the study of the intersection of biological and chemical spaces. Chemogenomics requires expertises in biology, chemistry and computational sciences (bioinformatics, cheminformatics, large scale statistics and machine learning methods) but it is more than the simple apposition of each of these disciplines. Biological entities interacting with small molecules can be isolated proteins or more elaborate systems, from single cells to complete organisms. The biological space is therefore analyzed at various postgenomic levels (genomic, transcriptomic, proteomic or any phenotypic level). The space of small molecules is partially real, corresponding to commercial and academic collections of compounds, and partially virtual, corresponding to the chemical space possibly synthesizable. Synthetic chemistry has developed novel strategies allowing a physical exploration of this universe of possibilities. A major challenge of cheminformatics is to charter the virtual space of small molecules using realistic biological constraints (bioavailability, druggability, structural biological information). Chemogenomics is a descendent of conventional pharmaceutical approaches, since it involves the screening of chemolibraries for their effect on biological targets, and benefits from the advances in the corresponding enabling technologies and the introduction of new biological markers. Screening was originally motivated by the rigorous discovery of new drugs, neglecting and throwing away any molecule that would fail to meet the standards required for a therapeutic treatment. It is now the basis for the discovery of small molecules that might or might not be directly used as drugs, but which have an immense potential for basic research, as probes to explore an increasing number of biological phenomena. Concerns about the environmental impact of chemical industry open new fields of research for chemogenomics.

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

Shimizu, Y; Yoon, Y; Iwase, K

Purpose: We are trying to develop an image-searching technique to identify misfiled images in a picture archiving and communication system (PACS) server by using five biological fingerprints: the whole lung field, cardiac shadow, superior mediastinum, lung apex, and right lower lung. Each biological fingerprint in a chest radiograph includes distinctive anatomical structures to identify misfiled images. The whole lung field was less effective for evaluating the similarity between two images than the other biological fingerprints. This was mainly due to the variation in the positioning for chest radiographs. The purpose of this study is to develop new biological fingerprints thatmore » could reduce influence of differences in the positioning for chest radiography. Methods: Two hundred patients were selected randomly from our database (36,212 patients). These patients had two images each (current and previous images). Current images were used as the misfiled images in this study. A circumscribed rectangular area of the lung and the upper half of the rectangle were selected automatically as new biological fingerprints. These biological fingerprints were matched to all previous images in the database. The degrees of similarity between the two images were calculated for the same and different patients. The usefulness of new the biological fingerprints for automated patient recognition was examined in terms of receiver operating characteristic (ROC) analysis. Results: Area under the ROC curves (AUCs) for the circumscribed rectangle of the lung, upper half of the rectangle, and whole lung field were 0.980, 0.994, and 0.950, respectively. The new biological fingerprints showed better performance in identifying the patients correctly than the whole lung field. Conclusion: We have developed new biological fingerprints: circumscribed rectangle of the lung and upper half of the rectangle. These new biological fingerprints would be useful for automated patient identification system because they are less affected by positioning differences during imaging.« less

Developing and establishing bee species as crop pollinators: the example of Osmia spp. (Hymenoptera: Megachilidae) and fruit trees.

PubMed

Bosch, J; Bosch, J; Kemp, W P

2002-02-01

The development of a bee species as a new crop pollinator starts with the identification of a pollination-limited crop production deficit and the selection of one or more candidate pollinator species. The process continues with a series of studies on the developmental biology, pollinating efficacy, nesting behaviour, preference for different nesting substrates, and population dynamics of the candidate pollinator. Parallel studies investigate the biology of parasites, predators and pathogens. The information gained in these studies is combined with information on the reproductive biology of the crop to design a management system. Complete management systems should provide guidelines on rearing and releasing methods, bee densities required for adequate pollination, nesting materials, and control against parasites, predators and pathogens. Management systems should also provide methods to ensure a reliable pollinator supply. Pilot tests on a commercial scale are then conducted to test and eventually refine the management system. The process culminates with the delivery of a viable system to manage and sustain the new pollinator on a commercial scale. The process is illustrated by the development of three mason bees, Osmia cornifrons (Radoszkowski), O. lignaria Say and O. cornuta (Latreille) as orchard pollinators in Japan, the USA and Europe, respectively.

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view. PMID:23515240

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology.

PubMed

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view.

Hormones and the autonomic nervous system are involved in suprachiasmatic nucleus modulation of glucose homeostasis.

PubMed

Ruiter, Marieke; Buijs, Ruud M; Kalsbeek, Andries

2006-05-01

Glucose is one of the most important energy sources for the body in general, and the brain in particular. It is essential for survival to keep glucose levels within strict boundaries. Acute disturbances of glucose homeostasis are rapidly corrected by hormonal and neuronal mechanisms. Furthermore, changes in energy expenditure associated with the light-dark cycle induce variations in the plasma glucose concentration that are more gradual. Organisms take advantage of adapting their internal physiology to the predictable daily changes in energy expenditure, because it enables them to anticipate these changes and to prevent unnecessary disturbance of homeostasis. The hypothalamic biological clock, located in the suprachiasmatic nucleus (SCN), receives light information from the eyes and transmits this information to the rest of the body to synchronize physiology to the environment. Here we review several studies providing evidence for biological clock control of the daily variation in several aspects of glucose metabolism. Although both hormones and the autonomic nervous system can stimulate glucose uptake or production by organs in the periphery, we have shown that the biological clock control of glucose metabolism mostly occurs through the autonomic nervous system. The critical involvement of the biological clock is also indicated by several studies, indicating that disturbance of the biological clock is often associated with metabolic diseases, such as obesity, diabetes mellitus and hypertension.

Review of Canadian Light Source facilities for biological applications

NASA Astrophysics Data System (ADS)

Grochulski, Pawel; Fodje, Michel; Labiuk, Shaun; Wysokinski, Tomasz W.; Belev, George; Korbas, Malgorzata; Rosendahl, Scott M.

2017-11-01

The newly-created Biological and Life Sciences Department at the Canadian Light Source (CLS) encompasses four sets of beamlines devoted to biological studies ranging in scope from the atomic scale to cells, tissues and whole organisms. The Canadian Macromolecular Crystallography Facility (CMCF) consists of two beamlines devoted primarily to crystallographic studies of proteins and other macromolecules. The Mid-Infrared Spectromicroscopy (Mid-IR) beamline focusses on using infrared energy to obtain biochemical, structural and dynamical information about biological systems. The Bio-Medical Imaging and Therapy (BMIT) facility consists of two beamlines devoted to advanced imaging and X-ray therapy techniques. The Biological X-ray Absorption Spectroscopy (BioXAS) facility is being commissioned and houses three beamlines devoted to X-ray absorption spectroscopy and multi-mode X-ray fluorescence imaging. Together, these beamlines provide CLS Users with a powerful array of techniques to study today's most pressing biological questions. We describe these beamlines along with their current powerful features and envisioned future capabilities.

Biocharts: a visual formalism for complex biological systems

PubMed Central

Kugler, Hillel; Larjo, Antti; Harel, David

2010-01-01

We address one of the central issues in devising languages, methods and tools for the modelling and analysis of complex biological systems, that of linking high-level (e.g. intercellular) information with lower-level (e.g. intracellular) information. Adequate ways of dealing with this issue are crucial for understanding biological networks and pathways, which typically contain huge amounts of data that continue to grow as our knowledge and understanding of a system increases. Trying to comprehend such data using the standard methods currently in use is often virtually impossible. We propose a two-tier compound visual language, which we call Biocharts, that is geared towards building fully executable models of biological systems. One of the main goals of our approach is to enable biologists to actively participate in the computational modelling effort, in a natural way. The high-level part of our language is a version of statecharts, which have been shown to be extremely successful in software and systems engineering. The statecharts can be combined with any appropriately well-defined language (preferably a diagrammatic one) for specifying the low-level dynamics of the pathways and networks. We illustrate the language and our general modelling approach using the well-studied process of bacterial chemotaxis. PMID:20022895

Next-generation mammalian genetics toward organism-level systems biology.

PubMed

Susaki, Etsuo A; Ukai, Hideki; Ueda, Hiroki R

2017-01-01

Organism-level systems biology in mammals aims to identify, analyze, control, and design molecular and cellular networks executing various biological functions in mammals. In particular, system-level identification and analysis of molecular and cellular networks can be accelerated by next-generation mammalian genetics. Mammalian genetics without crossing, where all production and phenotyping studies of genome-edited animals are completed within a single generation drastically reduce the time, space, and effort of conducting the systems research. Next-generation mammalian genetics is based on recent technological advancements in genome editing and developmental engineering. The process begins with introduction of double-strand breaks into genomic DNA by using site-specific endonucleases, which results in highly efficient genome editing in mammalian zygotes or embryonic stem cells. By using nuclease-mediated genome editing in zygotes, or ~100% embryonic stem cell-derived mouse technology, whole-body knock-out and knock-in mice can be produced within a single generation. These emerging technologies allow us to produce multiple knock-out or knock-in strains in high-throughput manner. In this review, we discuss the basic concepts and related technologies as well as current challenges and future opportunities for next-generation mammalian genetics in organism-level systems biology.

Using the Unified Modelling Language (UML) to guide the systemic description of biological processes and systems.

PubMed

Roux-Rouquié, Magali; Caritey, Nicolas; Gaubert, Laurent; Rosenthal-Sabroux, Camille

2004-07-01

One of the main issues in Systems Biology is to deal with semantic data integration. Previously, we examined the requirements for a reference conceptual model to guide semantic integration based on the systemic principles. In the present paper, we examine the usefulness of the Unified Modelling Language (UML) to describe and specify biological systems and processes. This makes unambiguous representations of biological systems, which would be suitable for translation into mathematical and computational formalisms, enabling analysis, simulation and prediction of these systems behaviours.

Traceability of Biologics in The Netherlands: An Analysis of Information-Recording Systems in Clinical Practice and Spontaneous ADR Reports.

PubMed

Klein, Kevin; Scholl, Joep H G; Vermeer, Niels S; Broekmans, André W; Van Puijenbroek, Eugène P; De Bruin, Marie L; Stolk, Pieter

2016-02-01

Pharmacovigilance requirements for biologics mandate that EU Member States shall ensure that any biologic that is the subject of a suspected adverse drug reaction (ADR) is identifiable by brand name and batch number. Recent studies showed that brand name identification is well established, whereas batch numbers are (still) poorly reported. We evaluated information-recording systems and practices in the Dutch hospital setting to identify determinants for brand name and batch number recording as well as success factors and bottlenecks for traceability. We surveyed Dutch hospital pharmacists with an online questionnaire on systems and practices in hospitals for recording brand names and batch numbers. Additionally, we performed an analysis of the traceability of recombinant biologics in spontaneous ADR reports (received between 2009 and 2014) from the Netherlands Pharmacovigilance Centre Lareb. The survey showed that brand names are not routinely recorded in the clinical practice of Dutch hospitals, whereas batch numbers are poorly recorded. Seventy-six percent of the 1523 ADR reports for recombinant biologics had a traceable brand name whereas 5% of these reports contained a batch number. The results suggest a possible relationship between the availability of brand and batch number information in clinical practice and the inclusion of this information in ADR reports for biologics. The limited traceability of brand names and batch numbers in ADR reports may be primarily caused by the shortcomings in the recording of information in clinical practice. We recommend efforts to improve information-recording systems as a first step to improve the traceability of biologics in ADR reporting.

Integration of functional myotubes with a Bio-MEMS device for non-invasive interrogation.

PubMed

Wilson, Kerry; Molnar, Peter; Hickman, James

2007-07-01

We have developed a biological micro-electromechanical system (Bio-MEMS) device consisting of surface-modified microfabricated silicon cantilevers and an AFM detection apparatus for the study of cultured myotubes. With this system we are able to selectively stimulate the myotubes as well as report on a variety of physiological properties of the myotubes in real time and in a high-throughput manner. This system will serve as the foundation for future work integrating multiple tissue types for the creation of Bio-MEMS analogues of complex tissues and biological circuits.

Illuminating Cell Biology

NASA Technical Reports Server (NTRS)

2002-01-01

NASA's Ames Research Center awarded Ciencia, Inc., a Small Business Innovation Research contract to develop the Cell Fluorescence Analysis System (CFAS) to address the size, mass, and power constraints of using fluorescence spectroscopy in the International Space Station's Life Science Research Facility. The system will play an important role in studying biological specimen's long-term adaptation to microgravity. Commercial applications for the technology include diverse markets such as food safety, in situ environmental monitoring, online process analysis, genomics and DNA chips, and non-invasive diagnostics. Ciencia has already sold the system to the private sector for biosensor applications.

How simple autonomous decisions evolve into robust behaviours? A review from neurorobotics, cognitive, self-organized and artificial immune systems fields.

PubMed

Fernandez-Leon, Jose A; Acosta, Gerardo G; Rozenfeld, Alejandro

2014-10-01

Researchers in diverse fields, such as in neuroscience, systems biology and autonomous robotics, have been intrigued by the origin and mechanisms for biological robustness. Darwinian evolution, in general, has suggested that adaptive mechanisms as a way of reaching robustness, could evolve by natural selection acting successively on numerous heritable variations. However, is this understanding enough for realizing how biological systems remain robust during their interactions with the surroundings? Here, we describe selected studies of bio-inspired systems that show behavioral robustness. From neurorobotics, cognitive, self-organizing and artificial immune system perspectives, our discussions focus mainly on how robust behaviors evolve or emerge in these systems, having the capacity of interacting with their surroundings. These descriptions are twofold. Initially, we introduce examples from autonomous robotics to illustrate how the process of designing robust control can be idealized in complex environments for autonomous navigation in terrain and underwater vehicles. We also include descriptions of bio-inspired self-organizing systems. Then, we introduce other studies that contextualize experimental evolution with simulated organisms and physical robots to exemplify how the process of natural selection can lead to the evolution of robustness by means of adaptive behaviors. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Anion binding in biological systems

NASA Astrophysics Data System (ADS)

Feiters, Martin C.; Meyer-Klaucke, Wolfram; Kostenko, Alexander V.; Soldatov, Alexander V.; Leblanc, Catherine; Michel, Gurvan; Potin, Philippe; Küpper, Frithjof C.; Hollenstein, Kaspar; Locher, Kaspar P.; Bevers, Loes E.; Hagedoorn, Peter-Leon; Hagen, Wilfred R.

2009-11-01

We compare aspects of biological X-ray absorption spectroscopy (XAS) studies of cations and anions, and report on some examples of anion binding in biological systems. Brown algae such as Laminaria digitata (oarweed) are effective accumulators of I from seawater, with tissue concentrations exceeding 50 mM, and the vanadate-containing enzyme haloperoxidase is implicated in halide accumulation. We have studied the chemical state of iodine and its biological role in Laminaria at the I K edge, and bromoperoxidase from Ascophyllum nodosum (knotted wrack) at the Br K edge. Mo is essential for many forms of life; W only for certain archaea, such as Archaeoglobus fulgidus and the hyperthermophilic archaeon Pyrococcus furiosus, and some bacteria. The metals are bound and transported as their oxo-anions, molybdate and tungstate, which are similar in size. The transport protein WtpA from P. furiosus binds tungstate more strongly than molybdate, and is related in sequence to Archaeoglobus fulgidus ModA, of which a crystal structure is known. We have measured A. fulgidus ModA with tungstate at the W L3 (2p3/2) edge, and compared the results with the refined crystal structure. XAS studies of anion binding are feasible even if only weak interactions are present, are biologically relevant, and give new insights in the spectroscopy.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

PubMed

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets.

PubMed

McKinney, Bill; Meyer, Peter A; Crosas, Mercè; Sliz, Piotr

2017-01-01

Access to experimental X-ray diffraction image data is important for validation and reproduction of macromolecular models and indispensable for the development of structural biology processing methods. In response to the evolving needs of the structural biology community, we recently established a diffraction data publication system, the Structural Biology Data Grid (SBDG, data.sbgrid.org), to preserve primary experimental datasets supporting scientific publications. All datasets published through the SBDG are freely available to the research community under a public domain dedication license, with metadata compliant with the DataCite Schema (schema.datacite.org). A proof-of-concept study demonstrated community interest and utility. Publication of large datasets is a challenge shared by several fields, and the SBDG has begun collaborating with the Institute for Quantitative Social Science at Harvard University to extend the Dataverse (dataverse.org) open-source data repository system to structural biology datasets. Several extensions are necessary to support the size and metadata requirements for structural biology datasets. In this paper, we describe one such extension-functionality supporting preservation of file system structure within Dataverse-which is essential for both in-place computation and supporting non-HTTP data transfers. © 2016 New York Academy of Sciences.

Dupuytren's: a systems biology disease

PubMed Central

2011-01-01

Dupuytren's disease (DD) is an ill-defined fibroproliferative disorder of the palm of the hands leading to digital contracture. DD commonly occurs in individuals of northern European extraction. Cellular components and processes associated with DD pathogenesis include altered gene and protein expression of cytokines, growth factors, adhesion molecules, and extracellular matrix components. Histology has shown increased but varying levels of particular types of collagen, myofibroblasts and myoglobin proteins in DD tissue. Free radicals and localised ischaemia have been suggested to trigger the proliferation of DD tissue. Although the existing available biological information on DD may contain potentially valuable (though largely uninterpreted) information, the precise aetiology of DD remains unknown. Systems biology combines mechanistic modelling with quantitative experimentation in studies of networks and better understanding of the interaction of multiple components in disease processes. Adopting systems biology may be the ideal approach for future research in order to improve understanding of complex diseases of multifactorial origin. In this review, we propose that DD is a disease of several networks rather than of a single gene, and show that this accounts for the experimental observations obtained to date from a variety of sources. We outline how DD may be investigated more effectively by employing a systems biology approach that considers the disease network as a whole rather than focusing on any specific single molecule. PMID:21943049

Demonstration Bulletin: Aqueous Biological Treatment System (Fixed-Film Biodegradation), Biotrol, Inc

EPA Science Inventory

This patented biological treatment system, called the BioTrol Aqueous Treatment System (BATS)., uses an amended microbial population to achieve biological degradation. The system is considered amended when a specific microorganism is added to the indigenous microbial population ...

New Tools and New Biology: Recent Miniaturized Systems for Molecular and Cellular Biology

PubMed Central

Hamon, Morgan; Hong, Jong Wook

2013-01-01

Recent advances in applied physics and chemistry have led to the development of novel microfluidic systems. Microfluidic systems allow minute amounts of reagents to be processed using μm-scale channels and offer several advantages over conventional analytical devices for use in biological sciences: faster, more accurate and more reproducible analytical performance, reduced cell and reagent consumption, portability, and integration of functional components in a single chip. In this review, we introduce how microfluidics has been applied to biological sciences. We first present an overview of the fabrication of microfluidic systems and describe the distinct technologies available for biological research. We then present examples of microsystems used in biological sciences, focusing on applications in molecular and cellular biology. PMID:24305843

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.

Electromagnetic fields as structure-function zeitgebers in biological systems: environmental orchestrations of morphogenesis and consciousness.

PubMed

Rouleau, Nicolas; Dotta, Blake T

2014-01-01

Within a cell system structure dictates function. Any interaction between cells, or a cell and its environment, has the potential to have long term implications on the function of a given cell and emerging cell aggregates. The structure and function of cells are continuously subjected to modification by electrical and chemical stimuli. However, biological systems are also subjected to an ever-present influence: the electromagnetic (EM) environment. Biological systems have the potential to be influenced by subtle energies which are exchanged at atomic and subatomic scales as EM phenomena. These energy exchanges have the potential to manifest at higher orders of discourse and affect the output (behavior) of a biological system. Here we describe theoretical and experimental evidence of EM influence on cells and the integration of whole systems. Even weak interactions between EM energies and biological systems display the potential to affect a developing system. We suggest the growing literature of EM effects on biological systems has significant implications to the cell and its functional aggregates.

Integrative Systems Biology for Data Driven Knowledge Discovery

PubMed Central

Greene, Casey S.; Troyanskaya, Olga G.

2015-01-01

Integrative systems biology is an approach that brings together diverse high throughput experiments and databases to gain new insights into biological processes or systems at molecular through physiological levels. These approaches rely on diverse high-throughput experimental techniques that generate heterogeneous data by assaying varying aspects of complex biological processes. Computational approaches are necessary to provide an integrative view of these experimental results and enable data-driven knowledge discovery. Hypotheses generated from these approaches can direct definitive molecular experiments in a cost effective manner. Using integrative systems biology approaches, we can leverage existing biological knowledge and large-scale data to improve our understanding of yet unknown components of a system of interest and how its malfunction leads to disease. PMID:21044756

Frontiers, Opportunities, and Challenges in Biochemical and Chemical Catalysis of CO2

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

Appel, Aaron M.; Bercaw, John E.; Bocarsly, Andrew B.

2013-08-14

Our central premise is that catalytic scientists can learn by studying how these important metabolic processes occur in nature. Complementarily, biochemists can learn by studying how catalytic scientists view these same chemical transformations promoted by synthetic catalysts. From these studies, hypotheses can be developed and tested through manipulation of enzyme structure and by synthesizing simple molecular catalysts to incorporate different structural features of the enzymes. It is hoped that these studies will lead to new and useful concepts in catalyst design for fuel production and utilization. This paper describes the results of a workshop held to explore these concepts inmore » regard to the development of new and more efficient catalytic processes for the conversion of CO2 to a variety of carbon-based fuels. The organization of this overview/review is as follows: 1) The first section briefly explores how interactions between the catalysis and biological communities have been fruitful in developing new catalysts for the reduction of protons to hydrogen, the simplest fuel generation reaction. 2) The second section assesses the state of the art in both biological and chemical reduction of CO2 by two electrons to form either carbon monoxide (CO) or formate (HCOO-). It also attempts to identify common principles between biological and synthetic catalysts and productive areas for future research. 3) The third section explores both biological and chemical processes that result in the reduction of CO2 beyond the level of CO and formate, again seeking to identify common principles and productive areas of future research. 4) The fourth section explores the formation of carbon-carbon bonds in biological and chemical systems in the same vein as the other sections. 5) A fifth section addresses the role of non-redox reactions of CO2 in biological systems and their role in carbon metabolism, with a parallel discussion of chemical systems. 6) In section 6, the topics of electrode modification, photochemical systems, and tandem catalysis are briefly discussed. These areas may be important for developing practical systems for CO2 reduction, and they share the common theme of coupling chemical reactions. 7) Section 7 describes some of the crosscutting activities that are critical for advancing the science underpinning catalyst development. 8) The last section attempts to summarize common issues in biological and chemical catalysis and to identify challenges that must be addressed to achieve practical catalysts that are suitable for the reduction of CO2 to fuels.« less

Rapid Analyses of Polyetheretherketone Wear Characteristics by Accelerated Wear Testing with Microfabricated Surfaces for Artificial Joint Systems

PubMed Central

Kuo, Chien-Wei

2017-01-01

Wear particle-induced biological responses are the major factors resulting in the loosening and then failure of total joint arthroplasties. It is feasible to improve the lubrication and reduce the wear of artificial joint system. Polyetheretherketone (PEEK) is considered as a potential bearing material due to its mechanical characteristics of resistance to fatigue strain. The PEEK wear particles have been indicated to be involved in biological responses in vitro, and further studies regarding the wear phenomena and wear particle generation are needed. In this study, we have established an accelerated wear testing system with microfabricated surfaces. Various contact pressures and lubricants have been utilized in the accelerated wear tests. Our results showed that increasing contact pressure resulted in an increase of wear particle sizes and wear rate, and the size of PEEK wear particles can be controlled by the feature size of microfabricated surfaces. These results provided the information rapidly about factors that affect the morphology and amount of PEEK wear particles and can be applied in the future for application of PEEK on the biological articulation system. PMID:29230411

A systems biology approach to defining regulatory mechanisms for cartilage and tendon cell phenotypes.

PubMed

Mueller, A J; Tew, S R; Vasieva, O; Clegg, P D; Canty-Laird, E G

2016-09-27

Phenotypic plasticity of adult somatic cells has provided emerging avenues for the development of regenerative therapeutics. In musculoskeletal biology the mechanistic regulatory networks of genes governing the phenotypic plasticity of cartilage and tendon cells has not been considered systematically. Additionally, a lack of strategies to effectively reproduce in vitro functional models of cartilage and tendon is retarding progress in this field. De- and redifferentiation represent phenotypic transitions that may contribute to loss of function in ageing musculoskeletal tissues. Applying a systems biology network analysis approach to global gene expression profiles derived from common in vitro culture systems (monolayer and three-dimensional cultures) this study demonstrates common regulatory mechanisms governing de- and redifferentiation transitions in cartilage and tendon cells. Furthermore, evidence of convergence of gene expression profiles during monolayer expansion of cartilage and tendon cells, and the expression of key developmental markers, challenges the physiological relevance of this culture system. The study also suggests that oxidative stress and PI3K signalling pathways are key modulators of in vitro phenotypes for cells of musculoskeletal origin.

Rapid Analyses of Polyetheretherketone Wear Characteristics by Accelerated Wear Testing with Microfabricated Surfaces for Artificial Joint Systems.

PubMed

Su, Chen-Ying; Kuo, Chien-Wei; Fang, Hsu-Wei

2017-01-01

Wear particle-induced biological responses are the major factors resulting in the loosening and then failure of total joint arthroplasties. It is feasible to improve the lubrication and reduce the wear of artificial joint system. Polyetheretherketone (PEEK) is considered as a potential bearing material due to its mechanical characteristics of resistance to fatigue strain. The PEEK wear particles have been indicated to be involved in biological responses in vitro, and further studies regarding the wear phenomena and wear particle generation are needed. In this study, we have established an accelerated wear testing system with microfabricated surfaces. Various contact pressures and lubricants have been utilized in the accelerated wear tests. Our results showed that increasing contact pressure resulted in an increase of wear particle sizes and wear rate, and the size of PEEK wear particles can be controlled by the feature size of microfabricated surfaces. These results provided the information rapidly about factors that affect the morphology and amount of PEEK wear particles and can be applied in the future for application of PEEK on the biological articulation system.

Phenomenological and molecular-level Petri net modeling and simulation of long-term potentiation.

PubMed

Hardy, S; Robillard, P N

2005-10-01

Petri net-based modeling methods have been used in many research projects to represent biological systems. Among these, the hybrid functional Petri net (HFPN) was developed especially for biological modeling in order to provide biologists with a more intuitive Petri net-based method. In the literature, HFPNs are used to represent kinetic models at the molecular level. We present two models of long-term potentiation previously represented by differential equations which we have transformed into HFPN models: a phenomenological synapse model and a molecular-level model of the CaMKII regulation pathway. Through simulation, we obtained results similar to those of previous studies using these models. Our results open the way to a new type of modeling for systems biology where HFPNs are used to combine different levels of abstraction within one model. This approach can be useful in fully modeling a system at the molecular level when kinetic data is missing or when a full study of a system at the molecular level it is not within the scope of the research.

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

De Vos, Winnok H., E-mail: winnok.devos@uantwerpen.be; Cell Systems and Imaging Research Group, Department of Molecular Biotechnology, Ghent University, Ghent; Beghuin, Didier

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALMmore » ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.« less

Nonlinear characterization of elasticity using quantitative optical coherence elastography.

PubMed

Qiu, Yi; Zaki, Farzana R; Chandra, Namas; Chester, Shawn A; Liu, Xuan

2016-11-01

Optical coherence elastography (OCE) has been used to perform mechanical characterization on biological tissue at the microscopic scale. In this work, we used quantitative optical coherence elastography (qOCE), a novel technology we recently developed, to study the nonlinear elastic behavior of biological tissue. The qOCE system had a fiber-optic probe to exert a compressive force to deform tissue under the tip of the probe. Using the space-division multiplexed optical coherence tomography (OCT) signal detected by a spectral domain OCT engine, we were able to simultaneously quantify the probe deformation that was proportional to the force applied, and to quantify the tissue deformation. In other words, our qOCE system allowed us to establish the relationship between mechanical stimulus and tissue response to characterize the stiffness of biological tissue. Most biological tissues have nonlinear elastic behavior, and the apparent stress-strain relationship characterized by our qOCE system was nonlinear an extended range of strain, for a tissue-mimicking phantom as well as biological tissues. Our experimental results suggested that the quantification of force in OCE was critical for accurate characterization of tissue mechanical properties and the qOCE technique was capable of differentiating biological tissues based on the elasticity of tissue that is generally nonlinear.

Generation of infectious recombinant Adeno-associated virus in Saccharomyces cerevisiae.

PubMed

Barajas, Daniel; Aponte-Ubillus, Juan Jose; Akeefe, Hassibullah; Cinek, Tomas; Peltier, Joseph; Gold, Daniel

2017-01-01

The yeast Saccharomyces cerevisiae has been successfully employed to establish model systems for a number of viruses. Such model systems are powerful tools to study the virus biology and in particular for the identification and characterization of host factors playing a role in the viral infection cycle. Adeno-associated viruses (AAV) are heavily studied due to their use as gene delivery vectors. AAV relies on other helper viruses for successful replication and on host factors for several aspects of the viral life cycle. However the role of host and helper viral factors is only partially known. Production of recombinant AAV (rAAV) vectors for gene delivery applications depends on knowledge of AAV biology and the limited understanding of host and helper viral factors may be precluding efficient production, particularly in heterologous systems. Model systems in simpler eukaryotes like the yeast S. cerevisiae would be useful tools to identify and study the role of host factors in AAV biology. Here we show that expression of AAV2 viral proteins VP1, VP2, VP3, AAP, Rep78, Rep52 and an ITR-flanked DNA in yeast leads to capsid formation, DNA replication and encapsidation, resulting in formation of infectious particles. Many of the AAV characteristics observed in yeast resemble those in other systems, making it a suitable model system. Future findings in the yeast system could be translatable to other AAV host systems and aid in more efficient production of rAAV vectors.

Fabrication, Physicochemical Characterization, and Performance Evaluation of Biodegradable Polymeric Microneedle Patch System for Enhanced Transcutaneous Flux of High Molecular Weight Therapeutics.

PubMed

Shah, Viral; Choudhury, Bijaya Krushna

2017-11-01

A revolutionary paradigm shift is being observed currently, towards the use of therapeutic biologics for disease management. The present research was focused on designing an efficient dosage form for transdermal delivery of α-choriogonadotropin (high molecular weight biologic), through biodegradable polymeric microneedles. Polyvinylpyrrolidone-based biodegradable microneedle arrays loaded with high molecular weight polypeptide, α-choriogonadotropin, were fabricated for its systemic delivery via transdermal route. Varied process and formulation parameters were optimized for fabricating microneedle array, which in turn was expected to temporally rupture the stratum corneum layer of the skin, acting as a major barrier to drug delivery through transdermal route. The developed polymeric microneedles were optimized on the basis of quality attributes like mechanical strength, axial strength, insertion ratio, and insertion force analysis. The optimized polymeric microneedle arrays were characterized for in vitro drug release studies, ex vivo drug permeation studies, skin resealing studies, and in vivo pharmacokinetic studies. Results depicted that fabricated polymeric microneedle arrays with mechanical strength of above 5 N and good insertion ratio exhibited similar systemic bioavailability of α-choriogonadotropin in comparison to marketed subcutaneous injection formulation of α-choriogonadotropin. Thus, it was ultimately concluded that the designed drug delivery system can serve as an efficient tool for systemic delivery of therapeutic biologics, with an added benefit of overcoming the limitations of parenteral delivery, achieving better patient acceptability and compliance.

An energy-efficient communication method based on the relationships between biological signals for ubiquitous health monitoring.

PubMed

Kwon, Hyok Chon; Na, Doosu; Ko, Byung Geun; Lee, Songjun

2008-01-01

Wireless sensor networks have been studied in the area of intelligent transportation systems, disaster perception, environment monitoring, ubiquitous healthcare, home network, and so on. For the ubiquitous healthcare, the previous systems collect the sensed health related data at portable devices without regard to correlations of various biological signals to determine the health conditions. It is not the energy-efficient method to gather a lot of information into a specific node to decide the health condition. Since the biological signals are related with each other to estimate certain body condition, it is necessary to be collected selectively by their relationship for energy efficiency of the networked nodes. One of researches about low power consumption is the reduction of the amount of packet transmission. In this paper, a health monitoring system, which allows the transmission of the reduced number of packets by means of setting the routing path considered the relations of biological signals, is proposed.

Biological treatment of winery wastewater: an overview.

PubMed

Andreottola, G; Foladori, P; Ziglio, G

2009-01-01

The treatment of winery wastewater can realised using several biological processes based both on aerobic or anaerobic systems using suspended biomass or biofilms. Several systems are currently offered by technology providers and current research envisages the availability of new promising technologies for winery wastewater treatment. The present paper intends to present a brief state of the art of the existing status and advances in biological treatment of winery wastewater in the last decade, considering both lab, pilot and full-scale studies. Advantages, drawbacks, applied organic loads, removal efficiency and emerging aspects of the main biological treatments were considered and compared. Nevertheless in most treatments the COD removal efficiency was around 90-95% (remaining COD is due to the un-biodegradable soluble fraction), the applied organic loads are very different depending on the applied technology, varying for an order of magnitude. Applied organic loads are higher in biofilm systems than in suspended biomass while anaerobic biofilm processes have the smaller footprint but in general a higher level of complexity.