Applying the Nernst equation to simulate redox potential variations for biological nitrification and denitrification processes.

PubMed

Chang, Cheng-Nan; Cheng, Hong-Bang; Chao, Allen C

2004-03-15

In this paper, various forms of Nernst equations have been developed based on the real stoichiometric relationship of biological nitrification and denitrification reactions. Instead of using the Nernst equation based on a one-to-one stoichiometric relation for the oxidizing and the reducing species, the basic Nernst equation is modified into slightly different forms. Each is suitable for simulating the redox potential (ORP) variation of a specific biological nitrification or denitrification process. Using the data published in the literature, the validity of these developed Nernst equations has been verified by close fits of the measured ORP data with the calculated ORP curve. The simulation results also indicate that if the biological process is simulated using an incorrect form of Nernst equation, the calculated ORP curve will not fit the measured data. Using these Nernst equations, the ORP value that corresponds to a predetermined degree of completion for the biochemical reaction can be calculated. Thus, these Nernst equations will enable a more efficient on-line control of the biological process.

Cancer systems biology: signal processing for cancer research

PubMed Central

Yli-Harja, Olli; Ylipää, Antti; Nykter, Matti; Zhang, Wei

2011-01-01

In this editorial we introduce the research paradigms of signal processing in the era of systems biology. Signal processing is a field of science traditionally focused on modeling electronic and communications systems, but recently it has turned to biological applications with astounding results. The essence of signal processing is to describe the natural world by mathematical models and then, based on these models, develop efficient computational tools for solving engineering problems. Here, we underline, with examples, the endless possibilities which arise when the battle-hardened tools of engineering are applied to solve the problems that have tormented cancer researchers. Based on this approach, a new field has emerged, called cancer systems biology. Despite its short history, cancer systems biology has already produced several success stories tackling previously impracticable problems. Perhaps most importantly, it has been accepted as an integral part of the major endeavors of cancer research, such as analyzing the genomic and epigenomic data produced by The Cancer Genome Atlas (TCGA) project. Finally, we show that signal processing and cancer research, two fields that are seemingly distant from each other, have merged into a field that is indeed more than the sum of its parts. PMID:21439242

A Case Study Documenting the Process by Which Biology Instructors Transition from Teacher-Centered to Learner-Centered Teaching.

PubMed

Marbach-Ad, Gili; Hunt Rietschel, Carly

2016-01-01

In this study, we used a case study approach to obtain an in-depth understanding of the change process of two university instructors who were involved with redesigning a biology course. Given the hesitancy of many biology instructors to adopt evidence-based, learner-centered teaching methods, there is a critical need to understand how biology instructors transition from teacher-centered (i.e., lecture-based) instruction to teaching that focuses on the students. Using the innovation-decision model for change, we explored the motivation, decision-making, and reflective processes of the two instructors through two consecutive, large-enrollment biology course offerings. Our data reveal that the change process is somewhat unpredictable, requiring patience and persistence during inevitable challenges that arise for instructors and students. For example, the change process requires instructors to adopt a teacher-facilitator role as opposed to an expert role, to cover fewer course topics in greater depth, and to give students a degree of control over their own learning. Students must adjust to taking responsibility for their own learning, working collaboratively, and relinquishing the anonymity afforded by lecture-based teaching. We suggest implications for instructors wishing to change their teaching and administrators wishing to encourage adoption of learner-centered teaching at their institutions. © 2016 G. Marbach-Ad and C. H. Rietschel. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

PubMed Central

2009-01-01

Background The identification of essential genes is important for the understanding of the minimal requirements for cellular life and for practical purposes, such as drug design. However, the experimental techniques for essential genes discovery are labor-intensive and time-consuming. Considering these experimental constraints, a computational approach capable of accurately predicting essential genes would be of great value. We therefore present here a machine learning-based computational approach relying on network topological features, cellular localization and biological process information for prediction of essential genes. Results We constructed a decision tree-based meta-classifier and trained it on datasets with individual and grouped attributes-network topological features, cellular compartments and biological processes-to generate various predictors of essential genes. We showed that the predictors with better performances are those generated by datasets with integrated attributes. Using the predictor with all attributes, i.e., network topological features, cellular compartments and biological processes, we obtained the best predictor of essential genes that was then used to classify yeast genes with unknown essentiality status. Finally, we generated decision trees by training the J48 algorithm on datasets with all network topological features, cellular localization and biological process information to discover cellular rules for essentiality. We found that the number of protein physical interactions, the nuclear localization of proteins and the number of regulating transcription factors are the most important factors determining gene essentiality. Conclusion We were able to demonstrate that network topological features, cellular localization and biological process information are reliable predictors of essential genes. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing essentiality. PMID:19758426

A Case Study Documenting the Process by Which Biology Instructors Transition from Teacher-Centered to Learner-Centered Teaching

ERIC Educational Resources Information Center

Marbach-Ad, Gili; Rietschel, Carly Hunt

2016-01-01

In this study, we used a case study approach to obtain an in-depth understanding of the change process of two university instructors who were involved with redesigning a biology course. Given the hesitancy of many biology instructors to adopt evidence-based, learner-centered teaching methods, there is a critical need to understand how biology…

Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution.

PubMed

Djordjevic, Ivan B

2015-08-24

Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i) Markovian classical model, (ii) Markovian-like quantum model, and (iii) hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage) Markov chain-like models of aging, which are mutually coupled.

Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution

PubMed Central

Djordjevic, Ivan B.

2015-01-01

Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i) Markovian classical model, (ii) Markovian-like quantum model, and (iii) hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage) Markov chain-like models of aging, which are mutually coupled. PMID:26305258

Learning Systems Biology: Conceptual Considerations toward a Web-Based Learning Platform

ERIC Educational Resources Information Center

Emmert-Streib, Frank; Dehmer, Matthias; Lyardet, Fernando

2013-01-01

Within recent years, there is an increasing need to train students, from biology and beyond, in quantitative methods that are relevant to cope with data-driven biology. Systems Biology is such a field that places a particular focus on the functional aspect of biology and molecular interacting processes. This paper deals with the conceptual design…

Understanding Randomness and Its Impact on Student Learning: Lessons Learned from Building the Biology Concept Inventory (BCI)

ERIC Educational Resources Information Center

Garvin-Doxas, Kathy; Klymkowsky, Michael W.

2008-01-01

While researching student assumptions for the development of the Biology Concept Inventory (BCI; http://bioliteracy.net), we found that a wide class of student difficulties in molecular and evolutionary biology appears to be based on deep-seated, and often unaddressed, misconceptions about random processes. Data were based on more than 500…

Dynamics of intracellular processes in live-cell systems unveiled by fluorescence correlation microscopy.

PubMed

González Bardeci, Nicolás; Angiolini, Juan Francisco; De Rossi, María Cecilia; Bruno, Luciana; Levi, Valeria

2017-01-01

Fluorescence fluctuation-based methods are non-invasive microscopy tools especially suited for the study of dynamical aspects of biological processes. These methods examine spontaneous intensity fluctuations produced by fluorescent molecules moving through the small, femtoliter-sized observation volume defined in confocal and multiphoton microscopes. The quantitative analysis of the intensity trace provides information on the processes producing the fluctuations that include diffusion, binding interactions, chemical reactions and photophysical phenomena. In this review, we present the basic principles of the most widespread fluctuation-based methods, discuss their implementation in standard confocal microscopes and briefly revise some examples of their applications to address relevant questions in living cells. The ultimate goal of these methods in the Cell Biology field is to observe biomolecules as they move, interact with targets and perform their biological action in the natural context. © 2016 IUBMB Life, 69(1):8-15, 2017. © 2016 International Union of Biochemistry and Molecular Biology.

Embodiment and Performance

ERIC Educational Resources Information Center

Bessell, Jacquelyn; Riddell, Patricia

2016-01-01

Evidence suggests that some cognitive processes are based on sensorimotor systems in the brain (embodied cognition). The premise of this is that "Biological brains are first and foremost the control systems for biological bodies". It has therefore been suggested that both online cognition (processing as we move through the world) and…

Contributions of experimental protobiogenesis to the theory of evolution

NASA Technical Reports Server (NTRS)

Fox, S. W.

1976-01-01

Inferences from experiments in protobiogenesis are examined as a forward extension of the theory of evolutionary biology. A nondiscontinuous, intraconsistent theory of general evolution embracing both protobiology and biology is outlined. This overview emphasizes Darwinian selection in the later stages of evolution, and stereochemical molecular selection in some of its earlier stages. It incorporates the concept of limitation of the scope of evolution by internal constraints on variation, based on the argument that internally limiting constraints observed in experiments with molecules are operative in organisms, if chemical processes occur within biological processes and biological processes are assumed to be exponentializations of chemical processes. Major evolutionary events might have occurred by rapid self-assembly processes analogous to those observed in the formation of phase-separated microspheres from amorphous powder or supersaturated solutions.

Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language.

PubMed

Roehner, Nicholas; Zhang, Zhen; Nguyen, Tramy; Myers, Chris J

2015-08-21

In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).

Cognitive Developmental Biology: History, Process and Fortune's Wheel

ERIC Educational Resources Information Center

Balaban, Evan

2006-01-01

Biological contributions to cognitive development continue to be conceived predominantly along deterministic lines, with proponents of different positions arguing about the preponderance of gene-based versus experience-based influences that organize brain circuits irreversibly during prenatal or early postnatal life, and evolutionary influences…

Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

PubMed

Drier, Yotam; Domany, Eytan

2011-03-14

The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.

Process-based principles for restoring river ecosystems

Treesearch

Timothy J. Beechie; David A. Sear; Julian D. Olden; George R. Pess; John M. Buffington; Hamish Moir; Philip Roni; Michael M. Pollock

2010-01-01

Process-based restoration aims to reestablish normative rates and magnitudes of physical, chemical, and biological processes that sustain river and floodplain ecosystems. Ecosystem conditions at any site are governed by hierarchical regional, watershed, and reach-scale processes controlling hydrologic and sediment regimes; floodplain and aquatic habitat...

HOW CAN BIOLOGICALLY-BASED MODELING OF ARSENIC KINETICS AND DYNAMICS INFORM THE RISK ASSESSMENT PROCESS?

EPA Science Inventory

Quantitative biologically-based models describing key events in the continuum from arsenic exposure to the development of adverse health effects provide a framework to integrate information obtained across diverse research areas. For example, genetic polymorphisms in arsenic met...

Novel biomaterials: plasma-enabled nanostructures and functions

NASA Astrophysics Data System (ADS)

Levchenko, Igor; Keidar, Michael; Cvelbar, Uroš; Mariotti, Davide; Mai-Prochnow, Anne; Fang, Jinghua; (Ken Ostrikov, Kostya

2016-07-01

Material processing techniques utilizing low-temperature plasmas as the main process tool feature many unique capabilities for the fabrication of various nanostructured materials. As compared with the neutral-gas based techniques and methods, the plasma-based approaches offer higher levels of energy and flux controllability, often leading to higher quality of the fabricated nanomaterials and sometimes to the synthesis of the hierarchical materials with interesting properties. Among others, nanoscale biomaterials attract significant attention due to their special properties towards the biological materials (proteins, enzymes), living cells and tissues. This review briefly examines various approaches based on the use of low-temperature plasma environments to fabricate nanoscale biomaterials exhibiting high biological activity, biological inertness for drug delivery system, and other features of the biomaterials make them highly attractive. In particular, we briefly discuss the plasma-assisted fabrication of gold and silicon nanoparticles for bio-applications; carbon nanoparticles for bioimaging and cancer therapy; carbon nanotube-based platforms for enzyme production and bacteria growth control, and other applications of low-temperature plasmas in the production of biologically-active materials.

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.

Network analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge.

PubMed

Zhang, Yuji

2015-01-01

Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static network maps, integrating them with time course gene expression information can provide clues to the dynamic features of these networks and unravel the mechanistic driver genes characterizing cellular responses. Time course gene expression data allow us to broadly "watch" the dynamics of the system. However, one challenge in the analysis of such data is to establish and characterize the interplay among genes that are altered at different time points in the context of a biological process or functional category. Integrative analysis of these data sources will lead us a more complete understanding of how biological entities (e.g., genes and proteins) coordinately perform their biological functions in biological systems. In this paper, we introduced a novel network-based approach to extract functional knowledge from time-dependent biological processes at a system level using time course mRNA sequencing data in zebrafish embryo development. The proposed method was applied to investigate 1α, 25(OH)2D3-altered mechanisms in zebrafish embryo development. We applied the proposed method to a public zebrafish time course mRNA-Seq dataset, containing two different treatments along four time points. We constructed networks between gene ontology biological process categories, which were enriched in differential expressed genes between consecutive time points and different conditions. The temporal propagation of 1α, 25-Dihydroxyvitamin D3-altered transcriptional changes started from a few genes that were altered initially at earlier stage, to large groups of biological coherent genes at later stages. The most notable biological processes included neuronal and retinal development and generalized stress response. In addition, we also investigated the relationship among biological processes enriched in co-expressed genes under different conditions. The enriched biological processes include translation elongation, nucleosome assembly, and retina development. These network dynamics provide new insights into the impact of 1α, 25-Dihydroxyvitamin D3 treatment in bone and cartilage development. We developed a network-based approach to analyzing the DEGs at different time points by integrating molecular interactions and gene ontology information. These results demonstrate that the proposed approach can provide insight on the molecular mechanisms taking place in vertebrate embryo development upon treatment with 1α, 25(OH)2D3. Our approach enables the monitoring of biological processes that can serve as a basis for generating new testable hypotheses. Such network-based integration approach can be easily extended to any temporal- or condition-dependent genomic data analyses.

Creative design inspired by biological knowledge: Technologies and methods

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Selection platforms for directed evolution in synthetic biology

PubMed Central

Tizei, Pedro A.G.; Csibra, Eszter; Torres, Leticia; Pinheiro, Vitor B.

2016-01-01

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules–gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function–be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code. PMID:27528765

Selection platforms for directed evolution in synthetic biology.

PubMed

Tizei, Pedro A G; Csibra, Eszter; Torres, Leticia; Pinheiro, Vitor B

2016-08-15

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules-gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function-be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code. © 2016 The Author(s).

Advanced treatment of biologically pretreated coal gasification wastewater by a novel integration of heterogeneous catalytic ozonation and biological process.

PubMed

Zhuang, Haifeng; Han, Hongjun; Jia, Shengyong; Hou, Baolin; Zhao, Qian

2014-08-01

Advanced treatment of biologically pretreated coal gasification wastewater (CGW) was investigated employing heterogeneous catalytic ozonation integrated with anoxic moving bed biofilm reactor (ANMBBR) and biological aerated filter (BAF) process. The results indicated that catalytic ozonation with the prepared catalyst (i.e. MnOx/SBAC, sewage sludge was converted into sludge based activated carbon (SBAC) which loaded manganese oxides) significantly enhanced performance of pollutants removal by generated hydroxyl radicals. The effluent of catalytic ozonation process was more biodegradable and less toxic than that in ozonation alone. Meanwhile, ANMBBR-BAF showed efficient capacity of pollutants removal in treatment of the effluent of catalytic ozonation at a shorter reaction time, allowing the discharge limits to be met. Therefore, the integrated process with efficient, economical and sustainable advantages was suitable for advanced treatment of real biologically pretreated CGW. Copyright © 2014 Elsevier Ltd. All rights reserved.

A versatile petri net based architecture for modeling and simulation of complex biological processes.

PubMed

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

2004-01-01

The research on modeling and simulation of complex biological systems is getting more important in Systems Biology. In this respect, we have developed Hybrid Function Petri net (HFPN) that was newly developed from existing Petri net because of their intuitive graphical representation and their capabilities for mathematical analyses. However, in the process of modeling metabolic, gene regulatory or signal transduction pathways with the architecture, we have realized three extensions of HFPN, (i) an entity should be extended to contain more than one value, (ii) an entity should be extended to handle other primitive types, e.g. boolean, string, (iii) an entity should be extended to handle more advanced type called object that consists of variables and methods, are necessary for modeling biological systems with Petri net based architecture. To deal with it, we define a new enhanced Petri net called hybrid functional Petri net with extension (HFPNe). To demonstrate the effectiveness of the enhancements, we model and simulate with HFPNe four biological processes that are diffcult to represent with the previous architecture HFPN.

Green Synthesis of Metallic Nanoparticles via Biological Entities

PubMed Central

Shah, Monaliben; Fawcett, Derek; Sharma, Shashi; Tripathy, Suraj Kumar; Poinern, Gérrard Eddy Jai

2015-01-01

Nanotechnology is the creation, manipulation and use of materials at the nanometre size scale (1 to 100 nm). At this size scale there are significant differences in many material properties that are normally not seen in the same materials at larger scales. Although nanoscale materials can be produced using a variety of traditional physical and chemical processes, it is now possible to biologically synthesize materials via environment-friendly green chemistry based techniques. In recent years, the convergence between nanotechnology and biology has created the new field of nanobiotechnology that incorporates the use of biological entities such as actinomycetes algae, bacteria, fungi, viruses, yeasts, and plants in a number of biochemical and biophysical processes. The biological synthesis via nanobiotechnology processes have a significant potential to boost nanoparticles production without the use of harsh, toxic, and expensive chemicals commonly used in conventional physical and chemical processes. The aim of this review is to provide an overview of recent trends in synthesizing nanoparticles via biological entities and their potential applications. PMID:28793638

How Can Biologically-Based Modeling of Arsenic Kinetics and Dynamics Inform the Risk Assessment Process? -- ETD

EPA Science Inventory

Quantitative biologically-based models describing key events in the continuum from arsenic exposure to the development of adverse health effects provide a framework to integrate information obtained across diverse research areas. For example, genetic polymorphisms in arsenic me...

Biotic and abiotic processes in eastside ecosystems: the effects of management on soil properties, processes, and productivity.

Treesearch

Alan E. Harvey; J. Michael Geist; Gerald L McDonald; Martin F. Jurgensen; Patrick H. Cochran; Darlene Zabowski; Robert T. Meurisse

1994-01-01

Productivity of forest and range land soils is based on a combination of diverse physical, chemical and biological properties. In ecosystems characteristic of eastside regions of Oregon and Washington, the productive zone is usually in the upper 1 or 2 m. Not only are the biological processes that drive both soil productivity and root development concentrated in...

Trait-Dependent Biogeography: (Re)Integrating Biology into Probabilistic Historical Biogeographical Models.

PubMed

Sukumaran, Jeet; Knowles, L Lacey

2018-06-01

The development of process-based probabilistic models for historical biogeography has transformed the field by grounding it in modern statistical hypothesis testing. However, most of these models abstract away biological differences, reducing species to interchangeable lineages. We present here the case for reintegration of biology into probabilistic historical biogeographical models, allowing a broader range of questions about biogeographical processes beyond ancestral range estimation or simple correlation between a trait and a distribution pattern, as well as allowing us to assess how inferences about ancestral ranges themselves might be impacted by differential biological traits. We show how new approaches to inference might cope with the computational challenges resulting from the increased complexity of these trait-based historical biogeographical models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Synthetic biology, inspired by synthetic chemistry.

PubMed

Malinova, V; Nallani, M; Meier, W P; Sinner, E K

2012-07-16

The topic synthetic biology appears still as an 'empty basket to be filled'. However, there is already plenty of claims and visions, as well as convincing research strategies about the theme of synthetic biology. First of all, synthetic biology seems to be about the engineering of biology - about bottom-up and top-down approaches, compromising complexity versus stability of artificial architectures, relevant in biology. Synthetic biology accounts for heterogeneous approaches towards minimal and even artificial life, the engineering of biochemical pathways on the organismic level, the modelling of molecular processes and finally, the combination of synthetic with nature-derived materials and architectural concepts, such as a cellular membrane. Still, synthetic biology is a discipline, which embraces interdisciplinary attempts in order to have a profound, scientific base to enable the re-design of nature and to compose architectures and processes with man-made matter. We like to give an overview about the developments in the field of synthetic biology, regarding polymer-based analogs of cellular membranes and what questions can be answered by applying synthetic polymer science towards the smallest unit in life, namely a cell. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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.

Can a Multimedia Tool Help Students' Learning Performance in Complex Biology Subjects?

ERIC Educational Resources Information Center

Koseoglu, Pinar; Efendioglu, Akin

2015-01-01

The aim of the present study was to determine the effects of multimedia-based biology teaching (Mbio) and teacher-centered biology (TCbio) instruction approaches on learners' biology achievements, as well as their views towards learning approaches. During the research process, an experimental design with two groups, TCbio (n = 22) and Mbio (n =…

The Learning Processes of Two High-School Biology Students when Reading Primary Literature. Research Report

ERIC Educational Resources Information Center

Brill, Gilat; Falk, Hedda; Yarden, Anat

2004-01-01

Biology education, like education in any other discipline, strives to make students familiar with the knowledge, activities, and ways of thinking of the community of biologists. We produced a curriculum in developmental biology based on learning through primary literature, in an attempt to develop biological literacy among highschool students.…

Acyl-homoserine lactone-based quorum sensing and quorum quenching hold promise to determine the performance of biological wastewater treatments: An overview.

PubMed

Huang, Jinhui; Shi, Yahui; Zeng, Guangming; Gu, Yanling; Chen, Guiqiu; Shi, Lixiu; Hu, Yi; Tang, Bi; Zhou, Jianxin

2016-08-01

Quorum sensing (QS) is a communication process between cells, in which bacteria secrete and sense the specific chemicals, and regulate gene expression in response to population density. Quorum quenching (QQ) blocks QS system, and inhibits gene expression mediating bacterial behaviors. Given the extensive research of acyl-homoserine lactone (AHL) signals, existences and effects of AHL-based QS and QQ in biological wastewater treatments are being subject to high concern. This review summarizes AHL structure, synthesis mode, degradation mechanisms, analytical methods, environmental factors, AHL-based QS and QQ mechanisms. The existences and roles of AHL-based QS and QQ in biomembrane processes, activated sludge processes and membrane bioreactors are summarized and discussed, and corresponding exogenous regulation strategy by selective enhancement of AHL-based QS or QQ coexisting in biological wastewater treatments is suggested. Such strategies including the addition of AHL signals, AHL-producing bacteria as well as quorum quenching enzyme or bacteria can effectively improve wastewater treatment performance without killing or limiting bacterial survival and growth. This review will present the theoretical and practical cognition for bacterial AHL-based QS and QQ, suggest the feasibility of exogenous regulation strategies in biological wastewater treatments, and provide useful information to scientists and engineers who work in this field. Copyright © 2016 Elsevier Ltd. All rights reserved.

A machine-learned computational functional genomics-based approach to drug classification.

PubMed

Lötsch, Jörn; Ultsch, Alfred

2016-12-01

The public accessibility of "big data" about the molecular targets of drugs and the biological functions of genes allows novel data science-based approaches to pharmacology that link drugs directly with their effects on pathophysiologic processes. This provides a phenotypic path to drug discovery and repurposing. This paper compares the performance of a functional genomics-based criterion to the traditional drug target-based classification. Knowledge discovery in the DrugBank and Gene Ontology databases allowed the construction of a "drug target versus biological process" matrix as a combination of "drug versus genes" and "genes versus biological processes" matrices. As a canonical example, such matrices were constructed for classical analgesic drugs. These matrices were projected onto a toroid grid of 50 × 82 artificial neurons using a self-organizing map (SOM). The distance, respectively, cluster structure of the high-dimensional feature space of the matrices was visualized on top of this SOM using a U-matrix. The cluster structure emerging on the U-matrix provided a correct classification of the analgesics into two main classes of opioid and non-opioid analgesics. The classification was flawless with both the functional genomics and the traditional target-based criterion. The functional genomics approach inherently included the drugs' modulatory effects on biological processes. The main pharmacological actions known from pharmacological science were captures, e.g., actions on lipid signaling for non-opioid analgesics that comprised many NSAIDs and actions on neuronal signal transmission for opioid analgesics. Using machine-learned techniques for computational drug classification in a comparative assessment, a functional genomics-based criterion was found to be similarly suitable for drug classification as the traditional target-based criterion. This supports a utility of functional genomics-based approaches to computational system pharmacology for drug discovery and repurposing.

Hands-on-Entropy, Energy Balance with Biological Relevance

NASA Astrophysics Data System (ADS)

Reeves, Mark

2015-03-01

Entropy changes underlie the physics that dominates biological interactions. Indeed, introductory biology courses often begin with an exploration of the qualities of water that are important to living systems. However, one idea that is not explicitly addressed in most introductory physics or biology textbooks is important contribution of the entropy in driving fundamental biological processes towards equilibrium. From diffusion to cell-membrane formation, to electrostatic binding in protein folding, to the functioning of nerve cells, entropic effects often act to counterbalance deterministic forces such as electrostatic attraction and in so doing, allow for effective molecular signaling. A small group of biology, biophysics and computer science faculty have worked together for the past five years to develop curricular modules (based on SCALEUP pedagogy). This has enabled students to create models of stochastic and deterministic processes. Our students are first-year engineering and science students in the calculus-based physics course and they are not expected to know biology beyond the high-school level. In our class, they learn to reduce complex biological processes and structures in order model them mathematically to account for both deterministic and probabilistic processes. The students test these models in simulations and in laboratory experiments that are biologically relevant such as diffusion, ionic transport, and ligand-receptor binding. Moreover, the students confront random forces and traditional forces in problems, simulations, and in laboratory exploration throughout the year-long course as they move from traditional kinematics through thermodynamics to electrostatic interactions. This talk will present a number of these exercises, with particular focus on the hands-on experiments done by the students, and will give examples of the tangible material that our students work with throughout the two-semester sequence of their course on introductory physics with a bio focus. Supported by NSF DUE.

Peer Review for EPA’s Biologically Based Dose-Response (BBDR) Model for Perchlorate

EPA Science Inventory

EPA is developing a regulation for perchlorate in drinking water. As part the regulatory process EPA must develop a Maximum Contaminant Level Goal (MCLG). FDA and EPA scientists developed a biologically based dose-response (BBDR) model to assist in deriving the MCLG. This mode...

Hybrid Thermochemical/Biological Processing

NASA Astrophysics Data System (ADS)

Brown, Robert C.

The conventional view of biorefineries is that lignocellulosic plant material will be fractionated into cellulose, hemicellulose, lignin, and terpenes before these components are biochemically converted into market products. Occasionally, these plants include a thermochemical step at the end of the process to convert recalcitrant plant components or mixed waste streams into heat to meet thermal energy demands elsewhere in the facility. However, another possibility for converting high-fiber plant materials is to start by thermochemically processing it into a uniform intermediate product that can be biologically converted into a bio-based product. This alternative route to bio-based products is known as hybrid thermochemical/biological processing. There are two distinct approaches to hybrid processing: (a) gasification followed by fermentation of the resulting gaseous mixture of carbon monoxide (CO), hydrogen (H2), and carbon dioxide (CO2) and (b) fast pyrolysis followed by hydrolysis and/or fermentation of the anhydrosugars found in the resulting bio-oil. This article explores this "cart before the horse" approach to biorefineries.

Technology development for lunar base water recycling

NASA Technical Reports Server (NTRS)

Schultz, John R.; Sauer, Richard L.

1992-01-01

This paper will review previous and ongoing work in aerospace water recycling and identify research activities required to support development of a lunar base. The development of a water recycle system for use in the life support systems envisioned for a lunar base will require considerable research work. A review of previous work on aerospace water recycle systems indicates that more efficient physical and chemical processes are needed to reduce expendable and power requirements. Development work on biological processes that can be applied to microgravity and lunar environments also needs to be initiated. Biological processes are inherently more efficient than physical and chemical processes and may be used to minimize resupply and waste disposal requirements. Processes for recovering and recycling nutrients such as nitrogen, phosphorus, and sulfur also need to be developed to support plant growth units. The development of efficient water quality monitors to be used for process control and environmental monitoring also needs to be initiated.

Microgravity Fluids for Biology, Workshop

NASA Technical Reports Server (NTRS)

Griffin, DeVon; Kohl, Fred; Massa, Gioia D.; Motil, Brian; Parsons-Wingerter, Patricia; Quincy, Charles; Sato, Kevin; Singh, Bhim; Smith, Jeffrey D.; Wheeler, Raymond M.

2013-01-01

Microgravity Fluids for Biology represents an intersection of biology and fluid physics that present exciting research challenges to the Space Life and Physical Sciences Division. Solving and managing the transport processes and fluid mechanics in physiological and biological systems and processes are essential for future space exploration and colonization of space by humans. Adequate understanding of the underlying fluid physics and transport mechanisms will provide new, necessary insights and technologies for analyzing and designing biological systems critical to NASAs mission. To enable this mission, the fluid physics discipline needs to work to enhance the understanding of the influence of gravity on the scales and types of fluids (i.e., non-Newtonian) important to biology and life sciences. In turn, biomimetic, bio-inspired and synthetic biology applications based on physiology and biology can enrich the fluid mechanics and transport phenomena capabilities of the microgravity fluid physics community.

pKa shifting in double-stranded RNA is highly dependent upon nearest neighbors and bulge positioning.

PubMed

Wilcox, Jennifer L; Bevilacqua, Philip C

2013-10-22

Shifting of pKa's in RNA is important for many biological processes; however, the driving forces responsible for shifting are not well understood. Herein, we determine how structural environments surrounding protonated bases affect pKa shifting in double-stranded RNA (dsRNA). Using (31)P NMR, we determined the pKa of the adenine in an A(+)·C base pair in various sequence and structural environments. We found a significant dependence of pKa on the base pairing strength of nearest neighbors and the location of a nearby bulge. Increasing nearest neighbor base pairing strength shifted the pKa of the adenine in an A(+)·C base pair higher by an additional 1.6 pKa units, from 6.5 to 8.1, which is well above neutrality. The addition of a bulge two base pairs away from a protonated A(+)·C base pair shifted the pKa by only ~0.5 units less than a perfectly base paired hairpin; however, positioning the bulge just one base pair away from the A(+)·C base pair prohibited formation of the protonated base pair as well as several flanking base pairs. Comparison of data collected at 25 °C and 100 mM KCl to biological temperature and Mg(2+) concentration revealed only slight pKa changes, suggesting that similar sequence contexts in biological systems have the potential to be protonated at biological pH. We present a general model to aid in the determination of the roles protonated bases may play in various dsRNA-mediated processes including ADAR editing, miRNA processing, programmed ribosomal frameshifting, and general acid-base catalysis in ribozymes.

Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle

PubMed Central

Somekh, Judith; Choder, Mordechai; Dori, Dov

2012-01-01

We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure—the objects that comprise the system, and behavior—how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point—the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model. PMID:23308089

On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology.

PubMed

Rao, Rohit T; Scherholz, Megerle L; Hartmanshenn, Clara; Bae, Seul-A; Androulakis, Ioannis P

2017-12-05

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

Reinvigorating Introductory Biology: A Theme-based, Investigative Approach To Teaching Biology Majors.

ERIC Educational Resources Information Center

Norton, Cynthia G.; Gildensoph, Lynne H.; Phillips, Martha M.; Wygal, Deborah D.; Olson, Kurt H.; Pellegrini, John J.; Tweeten, Kathleen A.

1997-01-01

Describes the reform of an introductory biology curriculum to reverse high attrition rates. Objectives include fostering self-directed learning, emphasizing process over content, and offering laboratory experiences that model the way to acquire scientific knowledge. Teaching methods include discussion, group mentoring, laboratory sections, and…

Advances in molecular imaging for breast cancer detection and characterization

PubMed Central

2012-01-01

Advances in our ability to assay molecular processes, including gene expression, protein expression, and molecular and cellular biochemistry, have fueled advances in our understanding of breast cancer biology and have led to the identification of new treatments for patients with breast cancer. The ability to measure biologic processes without perturbing them in vivo allows the opportunity to better characterize tumor biology and to assess how biologic and cytotoxic therapies alter critical pathways of tumor response and resistance. By accurately characterizing tumor properties and biologic processes, molecular imaging plays an increasing role in breast cancer science, clinical care in diagnosis and staging, assessment of therapeutic targets, and evaluation of responses to therapies. This review describes the current role and potential of molecular imaging modalities for detection and characterization of breast cancer and focuses primarily on radionuclide-based methods. PMID:22423895

Implementation of Multi-Agent Object Attention System Based on Biologically Inspired Attractor Selection

NASA Astrophysics Data System (ADS)

Hashimoto, Ryoji; Matsumura, Tomoya; Nozato, Yoshihiro; Watanabe, Kenji; Onoye, Takao

A multi-agent object attention system is proposed, which is based on biologically inspired attractor selection model. Object attention is facilitated by using a video sequence and a depth map obtained through a compound-eye image sensor TOMBO. Robustness of the multi-agent system over environmental changes is enhanced by utilizing the biological model of adaptive response by attractor selection. To implement the proposed system, an efficient VLSI architecture is employed with reducing enormous computational costs and memory accesses required for depth map processing and multi-agent attractor selection process. According to the FPGA implementation result of the proposed object attention system, which is accomplished by using 7,063 slices, 640×512 pixel input images can be processed in real-time with three agents at a rate of 9fps in 48MHz operation.

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

PubMed

Mishra, Bud; Daruwala, Raoul-Sam; Zhou, Yi; Ugel, Nadia; Policriti, Alberto; Antoniotti, Marco; Paxia, Salvatore; Rejali, Marc; Rudra, Archisman; Cherepinsky, Vera; Silver, Naomi; Casey, William; Piazza, Carla; Simeoni, Marta; Barbano, Paolo; Spivak, Marina; Feng, Jiawu; Gill, Ofer; Venkatesh, Mysore; Cheng, Fang; Sun, Bing; Ioniata, Iuliana; Anantharaman, Thomas; Hubbard, E Jane Albert; Pnueli, Amir; Harel, David; Chandru, Vijay; Hariharan, Ramesh; Wigler, Michael; Park, Frank; Lin, Shih-Chieh; Lazebnik, Yuri; Winkler, Franz; Cantor, Charles R; Carbone, Alessandra; Gromov, Mikhael

2003-01-01

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Model-based design of experiments for cellular processes.

PubMed

Chakrabarty, Ankush; Buzzard, Gregery T; Rundell, Ann E

2013-01-01

Model-based design of experiments (MBDOE) assists in the planning of highly effective and efficient experiments. Although the foundations of this field are well-established, the application of these techniques to understand cellular processes is a fertile and rapidly advancing area as the community seeks to understand ever more complex cellular processes and systems. This review discusses the MBDOE paradigm along with applications and challenges within the context of cellular processes and systems. It also provides a brief tutorial on Fisher information matrix (FIM)-based and Bayesian experiment design methods along with an overview of existing software packages and computational advances that support MBDOE application and adoption within the Systems Biology community. As cell-based products and biologics progress into the commercial sector, it is anticipated that MBDOE will become an essential practice for design, quality control, and production. Copyright © 2013 Wiley Periodicals, Inc.

Students' Usability Evaluation of a Web-Based Tutorial Program for College Biology Problem Solving

ERIC Educational Resources Information Center

Kim, H. S.; Prevost, L.; Lemons, P. P.

2015-01-01

The understanding of core concepts and processes of science in solving problems is important to successful learning in biology. We have designed and developed a Web-based, self-directed tutorial program, "SOLVEIT," that provides various scaffolds (e.g., prompts, expert models, visual guidance) to help college students enhance their…

A Computational Approach to Increase Time Scales in Brownian Dynamics–Based Reaction-Diffusion Modeling

PubMed Central

Frazier, Zachary

2012-01-01

Abstract Particle-based Brownian dynamics simulations offer the opportunity to not only simulate diffusion of particles but also the reactions between them. They therefore provide an opportunity to integrate varied biological data into spatially explicit models of biological processes, such as signal transduction or mitosis. However, particle based reaction-diffusion methods often are hampered by the relatively small time step needed for accurate description of the reaction-diffusion framework. Such small time steps often prevent simulation times that are relevant for biological processes. It is therefore of great importance to develop reaction-diffusion methods that tolerate larger time steps while maintaining relatively high accuracy. Here, we provide an algorithm, which detects potential particle collisions prior to a BD-based particle displacement and at the same time rigorously obeys the detailed balance rule of equilibrium reactions. We can show that for reaction-diffusion processes of particles mimicking proteins, the method can increase the typical BD time step by an order of magnitude while maintaining similar accuracy in the reaction diffusion modelling. PMID:22697237

Computational biology for cardiovascular biomarker discovery.

PubMed

Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

2009-07-01

Computational biology is essential in the process of translating biological knowledge into clinical practice, as well as in the understanding of biological phenomena based on the resources and technologies originating from the clinical environment. One such key contribution of computational biology is the discovery of biomarkers for predicting clinical outcomes using 'omic' information. This process involves the predictive modelling and integration of different types of data and knowledge for screening, diagnostic or prognostic purposes. Moreover, this requires the design and combination of different methodologies based on statistical analysis and machine learning. This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational methods for model evaluation will be described together with recommendations for reporting models and results. We will present recent advances in cardiovascular biomarker discovery based on the combination of gene expression and functional network analyses. The review will conclude with a discussion of key challenges for computational biology, including perspectives from the biosciences and clinical areas.

PerSubs: A Graph-Based Algorithm for the Identification of Perturbed Subpathways Caused by Complex Diseases.

PubMed

Vrahatis, Aristidis G; Rapti, Angeliki; Sioutas, Spyros; Tsakalidis, Athanasios

2017-01-01

In the era of Systems Biology and growing flow of omics experimental data from high throughput techniques, experimentalists are in need of more precise pathway-based tools to unravel the inherent complexity of diseases and biological processes. Subpathway-based approaches are the emerging generation of pathway-based analysis elucidating the biological mechanisms under the perspective of local topologies onto a complex pathway network. Towards this orientation, we developed PerSub, a graph-based algorithm which detects subpathways perturbed by a complex disease. The perturbations are imprinted through differentially expressed and co-expressed subpathways as recorded by RNA-seq experiments. Our novel algorithm is applied on data obtained from a real experimental study and the identified subpathways provide biological evidence for the brain aging.

Associations of genetic risk scores based on adult adiposity pathways with childhood growth and adiposity measures.

PubMed

Monnereau, Claire; Vogelezang, Suzanne; Kruithof, Claudia J; Jaddoe, Vincent W V; Felix, Janine F

2016-08-18

Results from genome-wide association studies (GWAS) identified many loci and biological pathways that influence adult body mass index (BMI). We aimed to identify if biological pathways related to adult BMI also affect infant growth and childhood adiposity measures. We used data from a population-based prospective cohort study among 3,975 children with a mean age of 6 years. Genetic risk scores were constructed based on the 97 SNPs associated with adult BMI previously identified with GWAS and on 28 BMI related biological pathways based on subsets of these 97 SNPs. Outcomes were infant peak weight velocity, BMI at adiposity peak and age at adiposity peak, and childhood BMI, total fat mass percentage, android/gynoid fat ratio, and preperitoneal fat area. Analyses were performed using linear regression models. A higher overall adult BMI risk score was associated with infant BMI at adiposity peak and childhood BMI, total fat mass, android/gynoid fat ratio, and preperitoneal fat area (all p-values < 0.05). Analyses focused on specific biological pathways showed that the membrane proteins genetic risk score was associated with infant peak weight velocity, and the genetic risk scores related to neuronal developmental processes, hypothalamic processes, cyclicAMP, WNT-signaling, membrane proteins, monogenic obesity and/or energy homeostasis, glucose homeostasis, cell cycle, and muscle biology pathways were associated with childhood adiposity measures (all p-values <0.05). None of the pathways were associated with childhood preperitoneal fat area. A genetic risk score based on 97 SNPs related to adult BMI was associated with peak weight velocity during infancy and general and abdominal fat measurements at the age of 6 years. Risk scores based on genetic variants linked to specific biological pathways, including central nervous system and hypothalamic processes, influence body fat development from early life onwards.

Modeling biochemical transformation processes and information processing with Narrator.

PubMed

Mandel, Johannes J; Fuss, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-03-27

Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from http://www.narrator-tool.org.

Modeling biochemical transformation processes and information processing with Narrator

PubMed Central

Mandel, Johannes J; Fuß, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-01-01

Background Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Results Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Conclusion Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from . PMID:17389034

Integrated aerobic biological-chemical treatment of winery wastewater diluted with urban wastewater. LED-based photocatalysis in the presence of monoperoxysulfate.

PubMed

Solís, Rafael R; Rivas, Francisco Javier; Ferreira, Leonor C; Pirra, Antonio; Peres, José A

2018-01-28

The oxidation of Winery Wastewater (WW) by conventional aerobic biological treatment usually leads to inefficient results due to the presence of organic substances, which are recalcitrant or toxic in conventional procedures. This study explores the combination of biological and chemical processes in order to complete the oxidation of biodegradable and non-biodegradable compounds in two sequential steps. Thus, a biological oxidation of a diluted WW is carried out by using the activated sludge process. Activated sludge was gradually acclimated to the Diluted Winery Wastewater (DWW). Some aspects concerning the biological process were evaluated (kinetics of the oxidation and sedimentation of the sludge produced). The biological treatment of the DWW led to a 40-50% of Chemical Oxygen Demand (COD) removal in 8 h, being necessary the application of an additional process. Different chemical processes combining UVA-LEDs radiation, monoperoxysulfate (MPS) and photocatalysts were applied in order to complete the COD depletion and efficient removal of polyphenols content, poorly oxidized in the previous biological step. From the options tested, the combination of UVA, MPS and a novel LaCoO 3 -TiO 2 composite, with double route of MPS decomposition through heterogeneous catalysis and photocatalysis, led to the best results (95% of polyphenol degradation, and additional 60% of COD removal). Initial MPS concentration and pH effect in this process were assessed.

Biological Moleculars: Have Most of Our Problems Already Been Solved?

NASA Technical Reports Server (NTRS)

Downey, James P.; Rose, M. Franklin (Technical Monitor)

2000-01-01

Evolution has resulted in biological machinery that engineers have great reason to envy and at present can only poorly mimic. This is not just a curiosity as biological systems perform many functions that are desired industrial processes. Examples include photosynthesis, chemosynthesis, energy storage, low temperature chemical conversion, reproducible manufacture of chemical compounds, etc. The bases of biological machinery are the proteins and nucleic acids that comprise living organisms. Each molecule functions as a part of a biological machine. In many cases the molecule can be properly regarded as a stand alone machine of its own. Concepts and methods for harnessing the power of biological molecules exist but are often overlooked in the industrial world. Some are old and appear crude but are quite effective, e.g. the fermentation of grains and fruits. Currently, there is a revolution in progress regarding the harnessing biological processes. These include techniques such as genetic manipulation via polymerase chain reaction, forced evolution also known as evolution in a test tube, determination of molecular structure, and combinatorial chemistry. The following is a brief discussion on how these processes are performed and how they may relate to industrial and aerospace processes.

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

Primary Literature as a Basis for a High-School Biology Curriculum.

ERIC Educational Resources Information Center

Yarden, Anat; Brill, Gilat; Falk, Hedda

2001-01-01

Adopts primary literature as a means of developing scientific literacy among high-school biology majors. Reports on the development and implementation of a primary literature-based curriculum in developmental biology. Discusses the process of adapting original research articles to the high-school level, as well as a conversational model developed…

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-09-01

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

Positioning Genomics in Biology Education: Content Mapping of Undergraduate Biology Textbooks†

PubMed Central

Wernick, Naomi L. B.; Ndung’u, Eric; Haughton, Dominique; Ledley, Fred D.

2014-01-01

Biological thought increasingly recognizes the centrality of the genome in constituting and regulating processes ranging from cellular systems to ecology and evolution. In this paper, we ask whether genomics is similarly positioned as a core concept in the instructional sequence for undergraduate biology. Using quantitative methods, we analyzed the order in which core biological concepts were introduced in textbooks for first-year general and human biology. Statistical analysis was performed using self-organizing map algorithms and conventional methods to identify clusters of terms and their relative position in the books. General biology textbooks for both majors and nonmajors introduced genome-related content after text related to cell biology and biological chemistry, but before content describing higher-order biological processes. However, human biology textbooks most often introduced genomic content near the end of the books. These results suggest that genomics is not yet positioned as a core concept in commonly used textbooks for first-year biology and raises questions about whether such textbooks, or courses based on the outline of these textbooks, provide an appropriate foundation for understanding contemporary biological science. PMID:25574293

Positioning genomics in biology education: content mapping of undergraduate biology textbooks.

PubMed

Wernick, Naomi L B; Ndung'u, Eric; Haughton, Dominique; Ledley, Fred D

2014-12-01

Biological thought increasingly recognizes the centrality of the genome in constituting and regulating processes ranging from cellular systems to ecology and evolution. In this paper, we ask whether genomics is similarly positioned as a core concept in the instructional sequence for undergraduate biology. Using quantitative methods, we analyzed the order in which core biological concepts were introduced in textbooks for first-year general and human biology. Statistical analysis was performed using self-organizing map algorithms and conventional methods to identify clusters of terms and their relative position in the books. General biology textbooks for both majors and nonmajors introduced genome-related content after text related to cell biology and biological chemistry, but before content describing higher-order biological processes. However, human biology textbooks most often introduced genomic content near the end of the books. These results suggest that genomics is not yet positioned as a core concept in commonly used textbooks for first-year biology and raises questions about whether such textbooks, or courses based on the outline of these textbooks, provide an appropriate foundation for understanding contemporary biological science.

Interactive learning and action: realizing the promise of synthetic biology for global health.

PubMed

Betten, A Wieke; Roelofsen, Anneloes; Broerse, Jacqueline E W

2013-09-01

The emerging field of synthetic biology has the potential to improve global health. For example, synthetic biology could contribute to efforts at vaccine development in a context in which vaccines and immunization have been identified by the international community as being crucial to international development efforts and, in particular, the millennium development goals. However, past experience with innovations shows that realizing a technology's potential can be difficult and complex. To achieve better societal embedding of synthetic biology and to make sure it reaches its potential, science and technology development should be made more inclusive and interactive. Responsible research and innovation is based on the premise that a broad range of stakeholders with different views, needs and ideas should have a voice in the technological development and deployment process. The interactive learning and action (ILA) approach has been developed as a methodology to bring societal stakeholders into a science and technology development process. This paper proposes an ILA in five phases for an international effort, with national case studies, to develop socially robust applications of synthetic biology for global health, based on the example of vaccine development. The design is based on results of a recently initiated ILA project on synthetic biology; results from other interactive initiatives described in the literature; and examples of possible applications of synthetic biology for global health that are currently being developed.

Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models

Treesearch

Louis R. Iverson; Frank R. Thompson; Stephen Matthews; Matthew Peters; Anantha Prasad; William D. Dijak; Jacob Fraser; Wen J. Wang; Brice Hanberry; Hong He; Maria Janowiak; Patricia Butler; Leslie Brandt; Chris Swanston

2016-01-01

Context. Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process...

Agricultural and Food Processing Applications of Pulsed Power Technology

NASA Astrophysics Data System (ADS)

Takaki, Koichi; Ihara, Satoshi

Recent progress of agricultural and food processing applications of pulsed power is described in this paper. Repetitively operated compact pulsed power generators with a moderate peak power have been developed for the agricultural and the food processing applications. These applications are mainly based on biological effects and can be categorized as decontamination of air and liquid, germination promotion, inhabitation of saprophytes growth, extraction of juice from fruits and vegetables, and fertilization of liquid medium, etc. Types of pulsed power that have biological effects are caused with gas discharges, water discharges, and electromagnetic fields. The discharges yield free radicals, UV radiation, intense electric field, and shock waves. Biologically based applications of pulsed power are performed by selecting the type that gives the target objects the adequate result from among these agents or byproducts. For instance, intense electric fields form pores on the cell membrane, which is called electroporation, or influence the nuclei.

Non-equilibrium assembly of microtubules: from molecules to autonomous chemical robots.

PubMed

Hess, H; Ross, Jennifer L

2017-09-18

Biological systems have evolved to harness non-equilibrium processes from the molecular to the macro scale. It is currently a grand challenge of chemistry, materials science, and engineering to understand and mimic biological systems that have the ability to autonomously sense stimuli, process these inputs, and respond by performing mechanical work. New chemical systems are responding to the challenge and form the basis for future responsive, adaptive, and active materials. In this article, we describe a particular biochemical-biomechanical network based on the microtubule cytoskeletal filament - itself a non-equilibrium chemical system. We trace the non-equilibrium aspects of the system from molecules to networks and describe how the cell uses this system to perform active work in essential processes. Finally, we discuss how microtubule-based engineered systems can serve as testbeds for autonomous chemical robots composed of biological and synthetic components.

Terrestrial Slugs as a Model Organism for Inquiry-Based Experimentation in a Majors General Biology Laboratory

ERIC Educational Resources Information Center

Peters, Brenda J.; Blair, Amy C.

2013-01-01

Many biology educators at the undergraduate level are revamping their laboratory curricula to incorporate inquiry-based research experiences so that students can directly participate in the process of science and improve their scientific reasoning skills. Slugs are an ideal organism for use in such a student-directed, hypothesis-driven experience.…

Information Fluency for Undergraduate Biology Majors: Applications of Inquiry-based Learning in a Developmental Biology Course

ERIC Educational Resources Information Center

Gehring, Kathleen M.; Eastman, Deborah A.

2008-01-01

Many initiatives for the improvement of undergraduate science education call for inquiry-based learning that emphasizes investigative projects and reading of the primary literature. These approaches give students an understanding of science as a process and help them integrate content presented in courses. At the same time, general initiatives to…

Developmental engineering: a new paradigm for the design and manufacturing of cell-based products. Part II: from genes to networks: tissue engineering from the viewpoint of systems biology and network science.

PubMed

Lenas, Petros; Moos, Malcolm; Luyten, Frank P

2009-12-01

The field of tissue engineering is moving toward a new concept of "in vitro biomimetics of in vivo tissue development." In Part I of this series, we proposed a theoretical framework integrating the concepts of developmental biology with those of process design to provide the rules for the design of biomimetic processes. We named this methodology "developmental engineering" to emphasize that it is not the tissue but the process of in vitro tissue development that has to be engineered. To formulate the process design rules in a rigorous way that will allow a computational design, we should refer to mathematical methods to model the biological process taking place in vitro. Tissue functions cannot be attributed to individual molecules but rather to complex interactions between the numerous components of a cell and interactions between cells in a tissue that form a network. For tissue engineering to advance to the level of a technologically driven discipline amenable to well-established principles of process engineering, a scientifically rigorous formulation is needed of the general design rules so that the behavior of networks of genes, proteins, or cells that govern the unfolding of developmental processes could be related to the design parameters. Now that sufficient experimental data exist to construct plausible mathematical models of many biological control circuits, explicit hypotheses can be evaluated using computational approaches to facilitate process design. Recent progress in systems biology has shown that the empirical concepts of developmental biology that we used in Part I to extract the rules of biomimetic process design can be expressed in rigorous mathematical terms. This allows the accurate characterization of manufacturing processes in tissue engineering as well as the properties of the artificial tissues themselves. In addition, network science has recently shown that the behavior of biological networks strongly depends on their topology and has developed the necessary concepts and methods to describe it, allowing therefore a deeper understanding of the behavior of networks during biomimetic processes. These advances thus open the door to a transition for tissue engineering from a substantially empirical endeavor to a technology-based discipline comparable to other branches of engineering.

COBRApy: COnstraints-Based Reconstruction and Analysis for Python.

PubMed

Ebrahim, Ali; Lerman, Joshua A; Palsson, Bernhard O; Hyduke, Daniel R

2013-08-08

COnstraint-Based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. Due to the successes with metabolism, there is an increasing effort to apply COBRA methods to reconstruct and analyze integrated models of cellular processes. The COBRA Toolbox for MATLAB is a leading software package for genome-scale analysis of metabolism; however, it was not designed to elegantly capture the complexity inherent in integrated biological networks and lacks an integration framework for the multiomics data used in systems biology. The openCOBRA Project is a community effort to promote constraints-based research through the distribution of freely available software. Here, we describe COBRA for Python (COBRApy), a Python package that provides support for basic COBRA methods. COBRApy is designed in an object-oriented fashion that facilitates the representation of the complex biological processes of metabolism and gene expression. COBRApy does not require MATLAB to function; however, it includes an interface to the COBRA Toolbox for MATLAB to facilitate use of legacy codes. For improved performance, COBRApy includes parallel processing support for computationally intensive processes. COBRApy is an object-oriented framework designed to meet the computational challenges associated with the next generation of stoichiometric constraint-based models and high-density omics data sets. http://opencobra.sourceforge.net/

Promoting Inquiry-Based Teaching in Laboratory Courses: Are We Meeting the Grade?

PubMed Central

Butler, Amy; Burke da Silva, Karen

2014-01-01

Over the past decade, repeated calls have been made to incorporate more active teaching and learning in undergraduate biology courses. The emphasis on inquiry-based teaching is especially important in laboratory courses, as these are the courses in which students are applying the process of science. To determine the current state of research on inquiry-based teaching in undergraduate biology laboratory courses, we reviewed the recent published literature on inquiry-based exercises. The majority of studies in our data set were in the subdisciplines of biochemistry, cell biology, developmental biology, genetics, and molecular biology. In addition, most exercises were guided inquiry, rather than open ended or research based. Almost 75% of the studies included assessment data, with two-thirds of these studies including multiple types of assessment data. However, few exercises were assessed in multiple courses or at multiple institutions. Furthermore, assessments were rarely based on published instruments. Although the results of the studies in our data set show a positive effect of inquiry-based teaching in biology laboratory courses on student learning gains, research that uses the same instrument across a range of courses and institutions is needed to determine whether these results can be generalized. PMID:25185228

On Crowd-verification of Biological Networks

PubMed Central

Ansari, Sam; Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Hayes, William; Hoeng, Julia; Iskandar, Anita; Kleiman, Robin; Norel, Raquel; O’Neel, Bruce; Peitsch, Manuel C.; Poussin, Carine; Pratt, Dexter; Rhrissorrakrai, Kahn; Schlage, Walter K.; Stolovitzky, Gustavo; Talikka, Marja

2013-01-01

Biological networks with a structured syntax are a powerful way of representing biological information generated from high density data; however, they can become unwieldy to manage as their size and complexity increase. This article presents a crowd-verification approach for the visualization and expansion of biological networks. Web-based graphical interfaces allow visualization of causal and correlative biological relationships represented using Biological Expression Language (BEL). Crowdsourcing principles enable participants to communally annotate these relationships based on literature evidences. Gamification principles are incorporated to further engage domain experts throughout biology to gather robust peer-reviewed information from which relationships can be identified and verified. The resulting network models will represent the current status of biological knowledge within the defined boundaries, here processes related to human lung disease. These models are amenable to computational analysis. For some period following conclusion of the challenge, the published models will remain available for continuous use and expansion by the scientific community. PMID:24151423

Global form and motion processing in healthy ageing.

PubMed

Agnew, Hannah C; Phillips, Louise H; Pilz, Karin S

2016-05-01

The ability to perceive biological motion has been shown to deteriorate with age, and it is assumed that older adults rely more on the global form than local motion information when processing point-light walkers. Further, it has been suggested that biological motion processing in ageing is related to a form-based global processing bias. Here, we investigated the relationship between older adults' preference for form information when processing point-light actions and an age-related form-based global processing bias. In a first task, we asked older (>60years) and younger adults (19-23years) to sequentially match three different point-light actions; normal actions that contained local motion and global form information, scrambled actions that contained primarily local motion information, and random-position actions that contained primarily global form information. Both age groups overall performed above chance in all three conditions, and were more accurate for actions that contained global form information. For random-position actions, older adults were less accurate than younger adults but there was no age-difference for normal or scrambled actions. These results indicate that both age groups rely more on global form than local motion to match point-light actions, but can use local motion on its own to match point-light actions. In a second task, we investigated form-based global processing biases using the Navon task. In general, participants were better at discriminating the local letters but faster at discriminating global letters. Correlations showed that there was no significant linear relationship between performance in the Navon task and biological motion processing, which suggests that processing biases in form- and motion-based tasks are unrelated. Copyright © 2016. Published by Elsevier B.V.

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.

Implementing the Science Assessment Standards: Developing and validating a set of laboratory assessment tasks in high school biology

NASA Astrophysics Data System (ADS)

Saha, Gouranga Chandra

Very often a number of factors, especially time, space and money, deter many science educators from using inquiry-based, hands-on, laboratory practical tasks as alternative assessment instruments in science. A shortage of valid inquiry-based laboratory tasks for high school biology has been cited. Driven by this need, this study addressed the following three research questions: (1) How can laboratory-based performance tasks be designed and developed that are doable by students for whom they are designed/written? (2) Do student responses to the laboratory-based performance tasks validly represent at least some of the intended process skills that new biology learning goals want students to acquire? (3) Are the laboratory-based performance tasks psychometrically consistent as individual tasks and as a set? To answer these questions, three tasks were used from the six biology tasks initially designed and developed by an iterative process of trial testing. Analyses of data from 224 students showed that performance-based laboratory tasks that are doable by all students require careful and iterative process of development. Although the students demonstrated more skill in performing than planning and reasoning, their performances at the item level were very poor for some items. Possible reasons for the poor performances have been discussed and suggestions on how to remediate the deficiencies have been made. Empirical evidences for validity and reliability of the instrument have been presented both from the classical and the modern validity criteria point of view. Limitations of the study have been identified. Finally implications of the study and directions for further research have been discussed.

Agent-based models in translational systems biology

PubMed Central

An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

2013-01-01

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

System and method for deriving a process-based specification

NASA Technical Reports Server (NTRS)

Hinchey, Michael Gerard (Inventor); Rouff, Christopher A. (Inventor); Rash, James Larry (Inventor)

2009-01-01

A system and method for deriving a process-based specification for a system is disclosed. The process-based specification is mathematically inferred from a trace-based specification. The trace-based specification is derived from a non-empty set of traces or natural language scenarios. The process-based specification is mathematically equivalent to the trace-based specification. Code is generated, if applicable, from the process-based specification. A process, or phases of a process, using the features disclosed can be reversed and repeated to allow for an interactive development and modification of legacy systems. The process is applicable to any class of system, including, but not limited to, biological and physical systems, electrical and electro-mechanical systems in addition to software, hardware and hybrid hardware-software systems.

Using a Module-Based Laboratory to Incorporate Inquiry into a Large Cell Biology Course

ERIC Educational Resources Information Center

Howard, David R.; Miskowski, Jennifer A.

2005-01-01

Because cell biology has rapidly increased in breadth and depth, instructors are challenged not only to provide undergraduate science students with a strong, up-to-date foundation of knowledge, but also to engage them in the scientific process. To these ends, revision of the Cell Biology Lab course at the University of Wisconsin-La Crosse was…

First-Year Biology Students' Understandings of Meiosis: An Investigation Using a Structural Theoretical Framework

ERIC Educational Resources Information Center

Quinn, Frances; Pegg, John; Panizzon, Debra

2009-01-01

Meiosis is a biological concept that is both complex and important for students to learn. This study aims to explore first-year biology students' explanations of the process of meiosis, using an explicit theoretical framework provided by the Structure of the Observed Learning Outcome (SOLO) model. The research was based on responses of 334…

Towards a Unified Approach to Information Integration - A review paper on data/information fusion

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

Whitney, Paul D.; Posse, Christian; Lei, Xingye C.

2005-10-14

Information or data fusion of data from different sources are ubiquitous in many applications, from epidemiology, medical, biological, political, and intelligence to military applications. Data fusion involves integration of spectral, imaging, text, and many other sensor data. For example, in epidemiology, information is often obtained based on many studies conducted by different researchers at different regions with different protocols. In the medical field, the diagnosis of a disease is often based on imaging (MRI, X-Ray, CT), clinical examination, and lab results. In the biological field, information is obtained based on studies conducted on many different species. In military field, informationmore » is obtained based on data from radar sensors, text messages, chemical biological sensor, acoustic sensor, optical warning and many other sources. Many methodologies are used in the data integration process, from classical, Bayesian, to evidence based expert systems. The implementation of the data integration ranges from pure software design to a mixture of software and hardware. In this review we summarize the methodologies and implementations of data fusion process, and illustrate in more detail the methodologies involved in three examples. We propose a unified multi-stage and multi-path mapping approach to the data fusion process, and point out future prospects and challenges.« less

Dispensing Processes Impact Apparent Biological Activity as Determined by Computational and Statistical Analyses

PubMed Central

Ekins, Sean; Olechno, Joe; Williams, Antony J.

2013-01-01

Dispensing and dilution processes may profoundly influence estimates of biological activity of compounds. Published data show Ephrin type-B receptor 4 IC50 values obtained via tip-based serial dilution and dispensing versus acoustic dispensing with direct dilution differ by orders of magnitude with no correlation or ranking of datasets. We generated computational 3D pharmacophores based on data derived by both acoustic and tip-based transfer. The computed pharmacophores differ significantly depending upon dispensing and dilution methods. The acoustic dispensing-derived pharmacophore correctly identified active compounds in a subsequent test set where the tip-based method failed. Data from acoustic dispensing generates a pharmacophore containing two hydrophobic features, one hydrogen bond donor and one hydrogen bond acceptor. This is consistent with X-ray crystallography studies of ligand-protein interactions and automatically generated pharmacophores derived from this structural data. In contrast, the tip-based data suggest a pharmacophore with two hydrogen bond acceptors, one hydrogen bond donor and no hydrophobic features. This pharmacophore is inconsistent with the X-ray crystallographic studies and automatically generated pharmacophores. In short, traditional dispensing processes are another important source of error in high-throughput screening that impacts computational and statistical analyses. These findings have far-reaching implications in biological research. PMID:23658723

Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N.; Rosenstein, Barry; Deasy, Joseph O.

2017-02-01

The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.

Student Analysis of Handout Development based on Guided Discovery Method in Process Evaluation and Learning Outcomes of Biology

NASA Astrophysics Data System (ADS)

Nerita, S.; Maizeli, A.; Afza, A.

2017-09-01

Process Evaluation and Learning Outcomes of Biology subjects discusses the evaluation process in learning and application of designed and processed learning outcomes. Some problems found during this subject was the student difficult to understand the subject and the subject unavailability of learning resources that can guide and make students independent study. So, it necessary to develop a learning resource that can make active students to think and to make decisions with the guidance of the lecturer. The purpose of this study is to produce handout based on guided discovery method that match the needs of students. The research was done by using 4-D models and limited to define phase that is student requirement analysis. Data obtained from the questionnaire and analyzed descriptively. The results showed that the average requirement of students was 91,43%. Can be concluded that students need a handout based on guided discovery method in the learning process.

Development and implementation of an expert system to improve the control of nitrification and denitrification in the Vic wastewater treatment plant.

PubMed

Ribas, F; Rodríguez-Roda, I; Serrat, J; Clara, P; Comas, J

2008-05-01

Wastewater treatment plants employ various physical, chemical and biological processes to reduce pollutants from raw wastewater. One of the most important is the biological nitrogen removal process through nitrification and denitrification steps taking place in various sections of the biological reactor. One of the most extensively used configurations to achieve the biological nitrogen removal is an activated sludge system using oxidation ditch or extended aeration. To improve nitrogen removal in the wastewater treatment plant (WWTP) of Vic (Catalonia, NE Spain), the automatic aeration control system was complemented with an Expert System to always provide the most appropriate aeration or anoxia sequence based on the values of ammonium and nitrates given by an automatic analyzer. This article illustrates the development and implementation of this knowledge-based system within the framework of a Decision Support System, which performs SCADA functions. The paper also shows that the application of the decision support system in the Vic WWTP resulted in significant improvements to the biological nitrogen removal.

The NASA Space Radiobiology Risk Assessment Project

NASA Astrophysics Data System (ADS)

Cucinotta, Francis A.; Huff, Janice; Ponomarev, Artem; Patel, Zarana; Kim, Myung-Hee

The current first phase (2006-2011) has the three major goals of: 1) optimizing the conventional cancer risk models currently used based on the double-detriment life-table and radiation quality functions; 2) the integration of biophysical models of acute radiation syndromes; and 3) the development of new systems radiation biology models of cancer processes. The first-phase also includes continued uncertainty assessment of space radiation environmental models and transport codes, and relative biological effectiveness factors (RBE) based on flight data and NSRL results, respectively. The second phase of the (2012-2016) will: 1) develop biophysical models of central nervous system risks (CNS); 2) achieve comphrensive systems biology models of cancer processes using data from proton and heavy ion studies performed at NSRL; and 3) begin to identify computational models of biological countermeasures. Goals for the third phase (2017-2021) include: 1) the development of a systems biology model of cancer risks for operational use at NASA; 2) development of models of degenerative risks, 2) quantitative models of counter-measure impacts on cancer risks; and 3) indiviudal based risk assessments. Finally, we will support a decision point to continue NSRL research in support of NASA's exploration goals beyond 2021, and create an archival of NSRL research results for continued analysis. Details on near term goals, plans for a WEB based data resource of NSRL results, and a space radiation Wikepedia are described.

Enhancement of COPD biological networks using a web-based collaboration interface

PubMed Central

Boue, Stephanie; Fields, Brett; Hoeng, Julia; Park, Jennifer; Peitsch, Manuel C.; Schlage, Walter K.; Talikka, Marja; Binenbaum, Ilona; Bondarenko, Vladimir; Bulgakov, Oleg V.; Cherkasova, Vera; Diaz-Diaz, Norberto; Fedorova, Larisa; Guryanova, Svetlana; Guzova, Julia; Igorevna Koroleva, Galina; Kozhemyakina, Elena; Kumar, Rahul; Lavid, Noa; Lu, Qingxian; Menon, Swapna; Ouliel, Yael; Peterson, Samantha C.; Prokhorov, Alexander; Sanders, Edward; Schrier, Sarah; Schwaitzer Neta, Golan; Shvydchenko, Irina; Tallam, Aravind; Villa-Fombuena, Gema; Wu, John; Yudkevich, Ilya; Zelikman, Mariya

2015-01-01

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks. PMID:25767696

Enhancement of COPD biological networks using a web-based collaboration interface.

PubMed

Boue, Stephanie; Fields, Brett; Hoeng, Julia; Park, Jennifer; Peitsch, Manuel C; Schlage, Walter K; Talikka, Marja; Binenbaum, Ilona; Bondarenko, Vladimir; Bulgakov, Oleg V; Cherkasova, Vera; Diaz-Diaz, Norberto; Fedorova, Larisa; Guryanova, Svetlana; Guzova, Julia; Igorevna Koroleva, Galina; Kozhemyakina, Elena; Kumar, Rahul; Lavid, Noa; Lu, Qingxian; Menon, Swapna; Ouliel, Yael; Peterson, Samantha C; Prokhorov, Alexander; Sanders, Edward; Schrier, Sarah; Schwaitzer Neta, Golan; Shvydchenko, Irina; Tallam, Aravind; Villa-Fombuena, Gema; Wu, John; Yudkevich, Ilya; Zelikman, Mariya

2015-01-01

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks.

Characterizing Cancer Drug Response and Biological Correlates: A Geometric Network Approach.

PubMed

Pouryahya, Maryam; Oh, Jung Hun; Mathews, James C; Deasy, Joseph O; Tannenbaum, Allen R

2018-04-23

In the present work, we apply a geometric network approach to study common biological features of anticancer drug response. We use for this purpose the panel of 60 human cell lines (NCI-60) provided by the National Cancer Institute. Our study suggests that mathematical tools for network-based analysis can provide novel insights into drug response and cancer biology. We adopted a discrete notion of Ricci curvature to measure, via a link between Ricci curvature and network robustness established by the theory of optimal mass transport, the robustness of biological networks constructed with a pre-treatment gene expression dataset and coupled the results with the GI50 response of the cell lines to the drugs. Based on the resulting drug response ranking, we assessed the impact of genes that are likely associated with individual drug response. For genes identified as important, we performed a gene ontology enrichment analysis using a curated bioinformatics database which resulted in biological processes associated with drug response across cell lines and tissue types which are plausible from the point of view of the biological literature. These results demonstrate the potential of using the mathematical network analysis in assessing drug response and in identifying relevant genomic biomarkers and biological processes for precision medicine.

Managing unexpected events in the manufacturing of biologic medicines.

PubMed

Grampp, Gustavo; Ramanan, Sundar

2013-08-01

The manufacturing of biologic medicines (biologics) requires robust process and facility design, rigorous regulatory compliance, and a well-trained workforce. Because of the complex attributes of biologics and their sensitivity to production and handling conditions, manufacturing of these medicines also requires a high-reliability manufacturing organization. As required by regulators, such an organization must monitor the state-of-control for the manufacturing process. A high-reliability organization also invests in an experienced and fully engaged technical support staff and fosters a management culture that rewards in-depth analysis of unexpected results, robust risk assessments, and timely and effective implementation of mitigation measures. Such a combination of infrastructure, technology, human capital, management, and a science-based operations culture does not occur without a strong organizational and financial commitment. These attributes of a high-reliability biologics manufacturer are difficult to achieve and may be differentiating factors as the supply of biologics diversifies in future years.

Invited review liquid crystal models of biological materials and silk spinning.

PubMed

Rey, Alejandro D; Herrera-Valencia, Edtson E

2012-06-01

A review of thermodynamic, materials science, and rheological liquid crystal models is presented and applied to a wide range of biological liquid crystals, including helicoidal plywoods, biopolymer solutions, and in vivo liquid crystals. The distinguishing characteristics of liquid crystals (self-assembly, packing, defects, functionalities, processability) are discussed in relation to biological materials and the strong correspondence between different synthetic and biological materials is established. Biological polymer processing based on liquid crystalline precursors includes viscoelastic flow to form and shape fibers. Viscoelastic models for nematic and chiral nematics are reviewed and discussed in terms of key parameters that facilitate understanding and quantitative information from optical textures and rheometers. It is shown that viscoelastic modeling the silk spinning process using liquid crystal theories sheds light on textural transitions in the duct of spiders and silk worms as well as on tactoidal drops and interfacial structures. The range and consistency of the predictions demonstrates that the use of mesoscopic liquid crystal models is another tool to develop the science and biomimetic applications of mesogenic biological soft matter. Copyright © 2011 Wiley Periodicals, Inc.

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.

Transmission as a basic process in microbial biology. Lwoff Award Prize Lecture.

PubMed

Baquero, Fernando

2017-11-01

Transmission is a basic process in biology and evolution, as it communicates different biological entities within and across hierarchical levels (from genes to holobionts) both in time and space. Vertical descent, replication, is transmission of information across generations (in the time dimension), and horizontal descent is transmission of information across compartments (in the space dimension). Transmission is essentially a communication process that can be studied by analogy of the classic information theory, based on 'emitters', 'messages' and 'receivers'. The analogy can be easily extended to the triad 'emigration', 'migration' and 'immigration'. A number of causes (forces) determine the emission, and another set of causes (energies) assures the reception. The message in fact is essentially constituted by 'meaningful' biological entities. A DNA sequence, a cell and a population have a semiotic dimension, are 'signs' that are eventually recognized (decoded) and integrated by receiver biological entities. In cis-acting or unenclosed transmission, the emitters and receivers correspond to separated entities of the same hierarchical level; in trans-acting or embedded transmission, the information flows between different, but frequently nested, hierarchical levels. The result (as in introgressive events) is constantly producing innovation and feeding natural selection, influencing also the evolution of transmission processes. This review is based on the concepts presented at the André Lwoff Award Lecture in the FEMS Microbiology Congress in Maastricht in 2015. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Improving your four-dimensional image: traveling through a decade of light-sheet-based fluorescence microscopy research.

PubMed

Strobl, Frederic; Schmitz, Alexander; Stelzer, Ernst H K

2017-06-01

Light-sheet-based fluorescence microscopy features optical sectioning in the excitation process. This reduces phototoxicity and photobleaching by up to four orders of magnitude compared with that caused by confocal fluorescence microscopy, simplifies segmentation and quantification for three-dimensional cell biology, and supports the transition from on-demand to systematic data acquisition in developmental biology applications.

[Biology and culture: a dimension of collaboration between anthropology and epidemiology].

PubMed

Song, Leiming; Wang, Ning

2016-01-01

Biology is the important basis of epidemiological study. Based on biology, psychology, social and cultural factors can influence human's health and disease incidence. The medical mode has changed from "biomedical mode" to "bio-psycho-social medical model" , but culture factor was neglected somewhat during this process, so paying attention to culture factor in anthropologic study and using it as biologic basis in epidemiologic study might be a dimension of collaboration between of anthropology and epidemiology.

Gene network biological validity based on gene-gene interaction relevance.

PubMed

Gómez-Vela, Francisco; Díaz-Díaz, Norberto

2014-01-01

In recent years, gene networks have become one of the most useful tools for modeling biological processes. Many inference gene network algorithms have been developed as techniques for extracting knowledge from gene expression data. Ensuring the reliability of the inferred gene relationships is a crucial task in any study in order to prove that the algorithms used are precise. Usually, this validation process can be carried out using prior biological knowledge. The metabolic pathways stored in KEGG are one of the most widely used knowledgeable sources for analyzing relationships between genes. This paper introduces a new methodology, GeneNetVal, to assess the biological validity of gene networks based on the relevance of the gene-gene interactions stored in KEGG metabolic pathways. Hence, a complete KEGG pathway conversion into a gene association network and a new matching distance based on gene-gene interaction relevance are proposed. The performance of GeneNetVal was established with three different experiments. Firstly, our proposal is tested in a comparative ROC analysis. Secondly, a randomness study is presented to show the behavior of GeneNetVal when the noise is increased in the input network. Finally, the ability of GeneNetVal to detect biological functionality of the network is shown.

Activated sludge model (ASM) based modelling of membrane bioreactor (MBR) processes: a critical review with special regard to MBR specificities.

PubMed

Fenu, A; Guglielmi, G; Jimenez, J; Spèrandio, M; Saroj, D; Lesjean, B; Brepols, C; Thoeye, C; Nopens, I

2010-08-01

Membrane bioreactors (MBRs) have been increasingly employed for municipal and industrial wastewater treatment in the last decade. The efforts for modelling of such wastewater treatment systems have always targeted either the biological processes (treatment quality target) as well as the various aspects of engineering (cost effective design and operation). The development of Activated Sludge Models (ASM) was an important evolution in the modelling of Conventional Activated Sludge (CAS) processes and their use is now very well established. However, although they were initially developed to describe CAS processes, they have simply been transferred and applied to MBR processes. Recent studies on MBR biological processes have reported several crucial specificities: medium to very high sludge retention times, high mixed liquor concentration, accumulation of soluble microbial products (SMP) rejected by the membrane filtration step, and high aeration rates for scouring purposes. These aspects raise the question as to what extent the ASM framework is applicable to MBR processes. Several studies highlighting some of the aforementioned issues are scattered through the literature. Hence, through a concise and structured overview of the past developments and current state-of-the-art in biological modelling of MBR, this review explores ASM-based modelling applied to MBR processes. The work aims to synthesize previous studies and differentiates between unmodified and modified applications of ASM to MBR. Particular emphasis is placed on influent fractionation, biokinetics, and soluble microbial products (SMPs)/exo-polymeric substances (EPS) modelling, and suggestions are put forward as to good modelling practice with regard to MBR modelling both for end-users and academia. A last section highlights shortcomings and future needs for improved biological modelling of MBR processes. (c) 2010 Elsevier Ltd. All rights reserved.

BIOLOGICALLY ENHANCED OXYGEN TRANSFER IN THE ACTIVATED SLUDGE PROCESS (JOURNAL)

EPA Science Inventory

Biologically enhanced oxgyen transfer has been a hypothesis to explain observed oxygen transfer rates in activated sludge systems that were well above that predicted from aerator clean-water testing. The enhanced oxygen transfer rates were based on tests using BOD bottle oxygen ...

AOX removal from industrial wastewaters using advanced oxidation processes: assessment of a combined chemical-biological oxidation.

PubMed

Luyten, J; Sniegowski, K; Van Eyck, K; Maertens, D; Timmermans, S; Liers, Sven; Braeken, L

2013-01-01

In this paper, the abatement of adsorbable halogenated organic compounds (AOX) from an industrial wastewater containing relatively high chloride concentrations by a combined chemical and biological oxidation is assessed. For chemical oxidation, the O(3)/UV, H(2)O(2)/UV and photo-Fenton processes are evaluated on pilot scale. Biological oxidation is simulated in a 4 h respirometry experiment with periodic aeration. The results show that a selective degradation of AOX with respect to the matrix compounds (expressed as chemical oxygen demand) could be achieved. For O(3)/UV, lowering the ratio of O(3) dosage to UV intensity leads to a better selectivity for AOX. During O(3)-based experiments, the AOX removal is generally less than during the H(2)O(2)-based experiments. However, after biological oxidation, the AOX levels are comparable. For H(2)O(2)/UV, optimal operating parameters for UV and H(2)O(2) dosage are next determined in a second run with another wastewater sample.

Biological and Psychosocial Predictors of Postpartum Depression: Systematic Review and Call for Integration

PubMed Central

Tanner Stapleton, Lynlee R.; Guardino, Christine M.; Hahn-Holbrook, Jennifer; Schetter, Christine Dunkel

2017-01-01

Postpartum depression (PPD) adversely affects the health and well being of many new mothers, their infants, and their families. A comprehensive understanding of biopsychosocial precursors to PPD is needed to solidify the current evidence base for best practices in translation. We conducted a systematic review of research published from 2000 through 2013 on biological and psychosocial factors associated with PPD and postpartum depressive symptoms. Two hundred fourteen publications based on 199 investigations of 151,651 women in the first postpartum year met inclusion criteria. The biological and psychosocial literatures are largely distinct, and few studies provide integrative analyses. The strongest PPD risk predictors among biological processes are hypothalamic-pituitary-adrenal dysregulation, inflammatory processes, and genetic vulnerabilities. Among psychosocial factors, the strongest predictors are severe life events, some forms of chronic strain, relationship quality, and support from partner and mother. Fully integrated biopsychosocial investigations with large samples are needed to advance our knowledge of PPD etiology. PMID:25822344

Process of Argumentation in High School Biology Class: A Qualitative Analysis

NASA Astrophysics Data System (ADS)

Ramli, M.; Rakhmawati, E.; Hendarto, P.; Winarni

2017-02-01

Argumentation skill can be nurtured by designing a lesson in which students are provided with the opportunity to argue. This research aims to analyse argumentation process in biology class. The participants were students of three biology classes from different high schools in Surakarta Indonesia. One of the classroom was taught by a student teacher, and the rest were instructed by the assigned teachers. Through a classroom observation, oral activities were noted, audio-recorded and video-taped. Coding was done based on the existence of claiming-reasoning-evidence (CRE) process by McNeill and Krajcik. Data was analysed qualitatively focusing on the role of teachers to initiate questioning to support argumentation process. The lesson design of three were also analysed. The result shows that pedagogical skill of teachers to support argumentation process, such as skill to ask, answer, and respond to students’ question and statements need to be trained intensively. Most of the argumentation found were only claiming, without reasoning and evidence. Teachers have to change the routine of mostly posing open-ended questions to students, and giving directly a correct answer to students’ questions. Knowledge and skills to encourage student to follow inquiry-based learning have to be acquired by teachers.

From Random Walks to Brownian Motion, from Diffusion to Entropy: Statistical Principles in Introductory Physics

NASA Astrophysics Data System (ADS)

Reeves, Mark

2014-03-01

Entropy changes underlie the physics that dominates biological interactions. Indeed, introductory biology courses often begin with an exploration of the qualities of water that are important to living systems. However, one idea that is not explicitly addressed in most introductory physics or biology textbooks is dominant contribution of the entropy in driving important biological processes towards equilibrium. From diffusion to cell-membrane formation, to electrostatic binding in protein folding, to the functioning of nerve cells, entropic effects often act to counterbalance deterministic forces such as electrostatic attraction and in so doing, allow for effective molecular signaling. A small group of biology, biophysics and computer science faculty have worked together for the past five years to develop curricular modules (based on SCALEUP pedagogy) that enable students to create models of stochastic and deterministic processes. Our students are first-year engineering and science students in the calculus-based physics course and they are not expected to know biology beyond the high-school level. In our class, they learn to reduce seemingly complex biological processes and structures to be described by tractable models that include deterministic processes and simple probabilistic inference. The students test these models in simulations and in laboratory experiments that are biologically relevant. The students are challenged to bridge the gap between statistical parameterization of their data (mean and standard deviation) and simple model-building by inference. This allows the students to quantitatively describe realistic cellular processes such as diffusion, ionic transport, and ligand-receptor binding. Moreover, the students confront ``random'' forces and traditional forces in problems, simulations, and in laboratory exploration throughout the year-long course as they move from traditional kinematics through thermodynamics to electrostatic interactions. This talk will present a number of these exercises, with particular focus on the hands-on experiments done by the students, and will give examples of the tangible material that our students work with throughout the two-semester sequence of their course on introductory physics with a bio focus. Supported by NSF DUE.

Interaction of Herbal Compounds with Biological Targets: A Case Study with Berberine

PubMed Central

Chen, Xiao-Wu; Di, Yuan Ming; Zhang, Jian; Zhou, Zhi-Wei; Li, Chun Guang; Zhou, Shu-Feng

2012-01-01

Berberine is one of the main alkaloids found in the Chinese herb Huang lian (Rhizoma Coptidis), which has been reported to have multiple pharmacological activities. This study aimed to analyze the molecular targets of berberine based on literature data followed by a pathway analysis using the PANTHER program. PANTHER analysis of berberine targets showed that the most classes of molecular functions include receptor binding, kinase activity, protein binding, transcription activity, DNA binding, and kinase regulator activity. Based on the biological process classification of in vitro berberine targets, those targets related to signal transduction, intracellular signalling cascade, cell surface receptor-linked signal transduction, cell motion, cell cycle control, immunity system process, and protein metabolic process are most frequently involved. In addition, berberine was found to interact with a mixture of biological pathways, such as Alzheimer's disease-presenilin and -secretase pathways, angiogenesis, apoptosis signalling pathway, FAS signalling pathway, Hungtington disease, inflammation mediated by chemokine and cytokine signalling pathways, interleukin signalling pathway, and p53 pathways. We also explored the possible mechanism of action for the anti-diabetic effect of berberine. Further studies are warranted to elucidate the mechanisms of action of berberine using systems biology approach. PMID:23213296

Advanced treatment of biologically pretreated coal gasification wastewater by a novel integration of heterogeneous Fenton oxidation and biological process.

PubMed

Xu, Peng; Han, Hongjun; Zhuang, Haifeng; Hou, Baolin; Jia, Shengyong; Xu, Chunyan; Wang, Dexin

2015-04-01

Laboratorial scale experiments were conducted in order to investigate a novel system integrating heterogeneous Fenton oxidation (HFO) with anoxic moving bed biofilm reactor (ANMBBR) and biological aerated filter (BAF) process on advanced treatment of biologically pretreated coal gasification wastewater (CGW). The results indicated that HFO with the prepared catalyst (FeOx/SBAC, sewage sludge based activated carbon (SBAC) which loaded Fe oxides) played a key role in eliminating COD and COLOR as well as in improving the biodegradability of raw wastewater. The surface reaction and hydroxyl radicals (OH) oxidation were the mechanisms for FeOx/SBAC catalytic reaction. Compared with ANMBBR-BAF process, the integrated system was more effective in abating COD, BOD5, total phenols (TPs), total nitrogen (TN) and COLOR and could shorten the retention time. Therefore, the integrated system was a promising technology for engineering applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Benthic biological C processing patterns in two Scottish estuaries and the significance of bacterial C uptake in sandy sediments

NASA Astrophysics Data System (ADS)

Woulds, Clare; Cowie, Greg; Witte, Ursula; Middelburg, Jack

2013-04-01

The supply of detrital organic matter to marine sediments is important for the nutrition of benthic ecosystems, while its remineralisation and burial supplies nutrients to the water column, and is a significant C sequestration process. Biological processes regulate sedimentary organic matter cycling, however the dominant processes vary between sites, and our knowledge of the factors driving that variation is still limited. Isotope tracing experiments have shown that the pattern and rate of biological processing of organic carbon (C) in marine sediments allows sites to be categorised based on the relative importance of different processes and C pools. Thus, total community respiration is often the dominant process, but its dominance is maximal in deep ocean sediments. In shallower settings, with greater organic matter availability, faunal uptake of organic C becomes more significant, and, where there is particularly high faunal biomass, can become dominant. New isotope tracing experiments have been conducted which compare biological C processing patterns in two contrasting Scottish estuaries. These are Loch Etive, where muddy, comparatively organic C rich sediments become hypoxic within millimetres of the sediment-water interface; and the Ythan estuary, where organic C poor, sandy sediments are kept oxygenated by porewater advection. Taken together with other experiments from the literature, the results now suggest that estuarine and shelf sandy sediments constitute a distinct category of biological C processing, in which bacterial C uptake plays a particularly significant role.

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.

Identification of Biokinetic Models Using the Concept of Extents.

PubMed

Mašić, Alma; Srinivasan, Sriniketh; Billeter, Julien; Bonvin, Dominique; Villez, Kris

2017-07-05

The development of a wide array of process technologies to enable the shift from conventional biological wastewater treatment processes to resource recovery systems is matched by an increasing demand for predictive capabilities. Mathematical models are excellent tools to meet this demand. However, obtaining reliable and fit-for-purpose models remains a cumbersome task due to the inherent complexity of biological wastewater treatment processes. In this work, we present a first study in the context of environmental biotechnology that adopts and explores the use of extents as a way to simplify and streamline the dynamic process modeling task. In addition, the extent-based modeling strategy is enhanced by optimal accounting for nonlinear algebraic equilibria and nonlinear measurement equations. Finally, a thorough discussion of our results explains the benefits of extent-based modeling and its potential to turn environmental process modeling into a highly automated task.

A comparison of aerobic granular sludge with conventional and compact biological treatment technologies.

PubMed

Bengtsson, Simon; de Blois, Mark; Wilén, Britt-Marie; Gustavsson, David

2018-03-20

The aerobic granular sludge (AGS) technology is growing towards becoming a mature option for new municipal wastewater treatment plants and capacity extensions. A process based on AGS was compared to conventional activated sludge processes (with and without enhanced biological phosphorus removal), an integrated fixed-film activated sludge (IFAS) process and a membrane bioreactor (MBR) by estimating the land area demand (footprint), electricity demand and chemicals' consumption. The process alternatives compared included pre-settling, sludge digestion and necessary post-treatment to achieve effluent concentrations of 8 mg/L nitrogen and 0.2 mg/L phosphorus at 7°C. The alternative based on AGS was estimated to have a 40-50% smaller footprint and 23% less electricity requirement than conventional activated sludge. In relation to the other compact treatment options IFAS and MBR, the AGS process had an estimated electricity usage that was 35-70% lower. This suggests a favourable potential for processes based on AGS although more available experience of AGS operation and performance at full scale is desired.

Translational systems biology using an agent-based approach for dynamic knowledge representation: An evolutionary paradigm for biomedical research.

PubMed

An, Gary C

2010-01-01

The greatest challenge facing the biomedical research community is the effective translation of basic mechanistic knowledge into clinically effective therapeutics. This challenge is most evident in attempts to understand and modulate "systems" processes/disorders, such as sepsis, cancer, and wound healing. Formulating an investigatory strategy for these issues requires the recognition that these are dynamic processes. Representation of the dynamic behavior of biological systems can aid in the investigation of complex pathophysiological processes by augmenting existing discovery procedures by integrating disparate information sources and knowledge. This approach is termed Translational Systems Biology. Focusing on the development of computational models capturing the behavior of mechanistic hypotheses provides a tool that bridges gaps in the understanding of a disease process by visualizing "thought experiments" to fill those gaps. Agent-based modeling is a computational method particularly well suited to the translation of mechanistic knowledge into a computational framework. Utilizing agent-based models as a means of dynamic hypothesis representation will be a vital means of describing, communicating, and integrating community-wide knowledge. The transparent representation of hypotheses in this dynamic fashion can form the basis of "knowledge ecologies," where selection between competing hypotheses will apply an evolutionary paradigm to the development of community knowledge.

Biological cycling of atmospheric trace gases

NASA Technical Reports Server (NTRS)

Hitchcock, D. R.; Wechsler, A. E.

1972-01-01

A detailed critical review was conducted of present knowledge of the influence of biological processes on the cycling of selected atmospheric gas constituents--methane, carbon monoxide, and gaseous compounds of nitrogen (nitrous oxide, ammonia, nitric oxide, and nitrogen dioxide) and sulfur (hydrogen sulfide and sulfur dioxide). The identification was included of biological and other sources of each gas, a survey of abundance measurements reported in the literature, and a review of the atmospheric fate of each contituent. Information is provided on which to base conclusions regarding the importance of biological processes on the atmospheric distribution and surface-atmosphere exchange of each constituent, and a basis for estimating the adequacy of present knowledge of these factors. A preliminary analysis was conducted of the feasibility of monitoring the biologically influenced temporal and spatial variations in abundance of these gases in the atmosphere from satellites.

Synthetic Biology Guides Biofuel Production

PubMed Central

Connor, Michael R.; Atsumi, Shota

2010-01-01

The advancement of microbial processes for the production of renewable liquid fuels has increased with concerns about the current fuel economy. The development of advanced biofuels in particular has risen to address some of the shortcomings of ethanol. These advanced fuels have chemical properties similar to petroleum-based liquid fuels, thus removing the need for engine modification or infrastructure redesign. While the productivity and titers of each of these processes remains to be improved, progress in synthetic biology has provided tools to guide the engineering of these processes through present and future challenges. PMID:20827393

Modelling and simulation techniques for membrane biology.

PubMed

Burrage, Kevin; Hancock, John; Leier, André; Nicolau, Dan V

2007-07-01

One of the most important aspects of Computational Cell Biology is the understanding of the complicated dynamical processes that take place on plasma membranes. These processes are often so complicated that purely temporal models cannot always adequately capture the dynamics. On the other hand, spatial models can have large computational overheads. In this article, we review some of these issues with respect to chemistry, membrane microdomains and anomalous diffusion and discuss how to select appropriate modelling and simulation paradigms based on some or all the following aspects: discrete, continuous, stochastic, delayed and complex spatial processes.

Plant MetGenMAP: an integrative analysis system for plant systems biology

USDA-ARS?s Scientific Manuscript database

We have developed a web-based system, Plant MetGenMAP, which can identify significantly altered biochemical pathways and highly affected biological processes, predict functional roles of pathway genes, and potential pathway-related regulatory motifs from transcript and metabolite profile datasets. P...

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.

Vitamin C: electron emission, free radicals and biological versatility.

PubMed

Getoff, Nikola

2013-01-01

The many-sided biological role of vitamin C (ascorbate) is briefly illustrated by specific examples. It is demonstrated that in aqueous solutions, vitamin C emits solvated electrons (e(aq)(-)), when excited in single state. Vitamin C can also react with e(aq)(-) as well as transfer them to other biological systems and thereby acts as efficient electron mediator. Based on its chemical and biological properties, it is clear that vitamin C plays a very important role in various functions in the organism alongside biochemical processes.

Biological determination of mental disorders: a discussion based on recent hypotheses from neuroscience.

PubMed

Freitas-Silva, Luna Rodrigues; Ortega, Francisco

2016-08-29

Understanding the processes involved in the development of mental disorders has proven challenging ever since psychiatry was founded as a field. Neuroscience has provided new expectations that an explanation will be found for the development of mental disorders based on biological functioning alone. However, such a goal has not been that easy to achieve, and new hypotheses have begun to appear in neuroscience research. In this article we identify epigenetics, neurodevelopment, and plasticity as the principal avenues for a new understanding of the biology of mental phenomena. Genetic complexity, the environment's formative role, and variations in vulnerability involve important changes in the principal hypotheses on biological determination of mental disorders, suggesting a reconfiguration of the limits between the "social" and the "biological" in neuroscience research.

The Design of a Molecular Assembly Line Based on Biological Molecules

DTIC Science & Technology

2003-06-01

and will demonstrate how one can construct a purely synthetic analogue of a polyketide synthase . 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF...scaffold in programmed assembly and molecular electronics. It is based on the principles of the biological molecules polyketide synthase and kinesin, and in...stereoselective centers) with any reasonable yield, not including the R&D and process development time. Figure 1.6 shows how a polyketide synthase

Information fluency for undergraduate biology majors: applications of inquiry-based learning in a developmental biology course.

PubMed

Gehring, Kathleen M; Eastman, Deborah A

2008-01-01

Many initiatives for the improvement of undergraduate science education call for inquiry-based learning that emphasizes investigative projects and reading of the primary literature. These approaches give students an understanding of science as a process and help them integrate content presented in courses. At the same time, general initiatives to promote information fluency are being promoted on many college and university campuses. Information fluency refers to discipline-specific processing of information, and it involves integration of gathered information with specific ideas to form logical conclusions. We have implemented the use of inquiry-based learning to enhance and study discipline-specific information fluency skills in an upper-level undergraduate Developmental Biology course. In this study, an information literacy tutorial and a set of linked assignments using primary literature analysis were integrated with two inquiry-based laboratory research projects. Quantitative analysis of student responses suggests that the abilities of students to identify and apply valid sources of information were enhanced. Qualitative assessment revealed a set of patterns by which students gather and apply information. Self-assessment responses indicated that students recognized the impact of the assignments on their abilities to gather and apply information and that they were more confident about these abilities for future biology courses and beyond.

Information Fluency for Undergraduate Biology Majors: Applications of Inquiry-based Learning in a Developmental Biology Course

PubMed Central

Gehring, Kathleen M.

2008-01-01

Many initiatives for the improvement of undergraduate science education call for inquiry-based learning that emphasizes investigative projects and reading of the primary literature. These approaches give students an understanding of science as a process and help them integrate content presented in courses. At the same time, general initiatives to promote information fluency are being promoted on many college and university campuses. Information fluency refers to discipline-specific processing of information, and it involves integration of gathered information with specific ideas to form logical conclusions. We have implemented the use of inquiry-based learning to enhance and study discipline-specific information fluency skills in an upper-level undergraduate Developmental Biology course. In this study, an information literacy tutorial and a set of linked assignments using primary literature analysis were integrated with two inquiry-based laboratory research projects. Quantitaitve analysis of student responses suggests that the abilities of students to identify and apply valid sources of information were enhanced. Qualitative assessment revealed a set of patterns by which students gather and apply information. Self-assessment responses indicated that students recognized the impact of the assignments on their abilities to gather and apply information and that they were more confident about these abilities for future biology courses and beyond. PMID:18316808

Development of a paper-based carbon nanotube sensing microfluidic device for biological detection.

PubMed

Yang, Shih-I; Lei, Kin Fong; Tsai, Shiao-Wen; Hsu, Hsiao-Ting

2013-01-01

Carbon nanotube (CNT) has been utilized for the biological detection due to its extremely sensitive to biological molecules. A paper-based CNT sensing microfluidic device has been developed for the detection of protein, i.e., biotin-avidin, binding. We have developed a fabrication method that allows controlled deposition of bundled CNTs with well-defined dimensions to form sensors on paper. Then, polydimethyl siloxane (PDMS) was used to pattern the hydrophobic boundary on paper to form the reaction sites. The proposed fabrication method is based on vacuum filtration process with a metal mask covering on a filter paper for the definition of the dimension of sensor. The length, width, and thickness of the CNT-based sensors are readily controlled by the metal mask and the weight of the CNT powder used during the filtration process, respectively. Homogeneous deposition of CNTs with well-defined dimensions can be achieved. The CNT-based sensor on paper has been demonstrated on the detection of the protein binding. Biotin was first immobilized on the CNT's sidewall and avidin suspended solution was applied to the site. The result of the biotin-avidin binding was measured by the resistance change of the sensor, which is a label-free detection method. It showed the CNT is sensitive to the biological molecules and the proposed paper-based CNT sensing device is a possible candidate for point-of-care biosensors. Thus, electrical bio-assays on paper-based microfluidics can be realized to develop low cost, sensitive, and specific diagnostic devices.

PomBase: The Scientific Resource for Fission Yeast.

PubMed

Lock, Antonia; Rutherford, Kim; Harris, Midori A; Wood, Valerie

2018-01-01

The fission yeast Schizosaccharomyces pombe has become well established as a model species for studying conserved cell-level biological processes, especially the mechanics and regulation of cell division. PomBase integrates the S. pombe genome sequence with traditional genetic, molecular, and cell biological experimental data as well as the growing body of large datasets generated by emerging high-throughput methods. This chapter provides insight into the curation philosophy and data organization at PomBase, and provides a guide to using PomBase for infrequent visitors and anyone considering exploring S. pombe in their research.

[Construction of individual-based ecological model for Scomber japonicas at its early growth stages in East China Sea].

PubMed

Li, Yue-Song; Chen, Xin-Jun; Yang, Hong

2012-06-01

By adopting FVCOM-simulated 3-D physical field and based on the biological processes of chub mackerel (Scomber japonicas) in its early life history from the individual-based biological model, the individual-based ecological model for S. japonicas at its early growth stages in the East China Sea was constructed through coupling the physical field in March-July with the biological model by the method of Lagrange particle tracking. The model constructed could well simulate the transport process and abundance distribution of S. japonicas eggs and larvae. The Taiwan Warm Current, Kuroshio, and Tsushima Strait Warm Current directly affected the transport process and distribution of the eggs and larvae, and indirectly affected the growth and survive of the eggs and larvae through the transport to the nursery grounds with different water temperature and foods. The spawning grounds in southern East China Sea made more contributions to the recruitment to the fishing grounds in northeast East China Sea, but less to the Yangtze estuary and Zhoushan Island. The northwestern and southwestern parts of spawning grounds had strong connectivity with the nursery grounds of Cheju and Tsushima Straits, whereas the northeastern and southeastern parts of the spawning ground had strong connectivity with the nursery grounds of Kyushu and Pacific Ocean.

Quantum biological channel modeling and capacity calculation.

PubMed

Djordjevic, Ivan B

2012-12-10

Quantum mechanics has an important role in photosynthesis, magnetoreception, and evolution. There were many attempts in an effort to explain the structure of genetic code and transfer of information from DNA to protein by using the concepts of quantum mechanics. The existing biological quantum channel models are not sufficiently general to incorporate all relevant contributions responsible for imperfect protein synthesis. Moreover, the problem of determination of quantum biological channel capacity is still an open problem. To solve these problems, we construct the operator-sum representation of biological channel based on codon basekets (basis vectors), and determine the quantum channel model suitable for study of the quantum biological channel capacity and beyond. The transcription process, DNA point mutations, insertions, deletions, and translation are interpreted as the quantum noise processes. The various types of quantum errors are classified into several broad categories: (i) storage errors that occur in DNA itself as it represents an imperfect storage of genetic information, (ii) replication errors introduced during DNA replication process, (iii) transcription errors introduced during DNA to mRNA transcription, and (iv) translation errors introduced during the translation process. By using this model, we determine the biological quantum channel capacity and compare it against corresponding classical biological channel capacity. We demonstrate that the quantum biological channel capacity is higher than the classical one, for a coherent quantum channel model, suggesting that quantum effects have an important role in biological systems. The proposed model is of crucial importance towards future study of quantum DNA error correction, developing quantum mechanical model of aging, developing the quantum mechanical models for tumors/cancer, and study of intracellular dynamics in general.

Process-based network decomposition reveals backbone motif structure

PubMed Central

Wang, Guanyu; Du, Chenghang; Chen, Hao; Simha, Rahul; Rong, Yongwu; Xiao, Yi; Zeng, Chen

2010-01-01

A central challenge in systems biology today is to understand the network of interactions among biomolecules and, especially, the organizing principles underlying such networks. Recent analysis of known networks has identified small motifs that occur ubiquitously, suggesting that larger networks might be constructed in the manner of electronic circuits by assembling groups of these smaller modules. Using a unique process-based approach to analyzing such networks, we show for two cell-cycle networks that each of these networks contains a giant backbone motif spanning all the network nodes that provides the main functional response. The backbone is in fact the smallest network capable of providing the desired functionality. Furthermore, the remaining edges in the network form smaller motifs whose role is to confer stability properties rather than provide function. The process-based approach used in the above analysis has additional benefits: It is scalable, analytic (resulting in a single analyzable expression that describes the behavior), and computationally efficient (all possible minimal networks for a biological process can be identified and enumerated). PMID:20498084

Multi-Step Usage of in Vivo Models During Rational Drug Design and Discovery

PubMed Central

Williams, Charles H.; Hong, Charles C.

2011-01-01

In this article we propose a systematic development method for rational drug design while reviewing paradigms in industry, emerging techniques and technologies in the field. Although the process of drug development today has been accelerated by emergence of computational methodologies, it is a herculean challenge requiring exorbitant resources; and often fails to yield clinically viable results. The current paradigm of target based drug design is often misguided and tends to yield compounds that have poor absorption, distribution, metabolism, and excretion, toxicology (ADMET) properties. Therefore, an in vivo organism based approach allowing for a multidisciplinary inquiry into potent and selective molecules is an excellent place to begin rational drug design. We will review how organisms like the zebrafish and Caenorhabditis elegans can not only be starting points, but can be used at various steps of the drug development process from target identification to pre-clinical trial models. This systems biology based approach paired with the power of computational biology; genetics and developmental biology provide a methodological framework to avoid the pitfalls of traditional target based drug design. PMID:21731440

XML-based approaches for the integration of heterogeneous bio-molecular data.

PubMed

Mesiti, Marco; Jiménez-Ruiz, Ernesto; Sanz, Ismael; Berlanga-Llavori, Rafael; Perlasca, Paolo; Valentini, Giorgio; Manset, David

2009-10-15

The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing. In this paper we survey the most interesting and novel approaches for the representation, integration and management of different kinds of biological data by exploiting XML and the related recommendations and approaches. Moreover, we present new and interesting cutting edge approaches for the appropriate management of heterogeneous biological data represented through XML. XML has succeeded in the integration of heterogeneous biomolecular information, and has established itself as the syntactic glue for biological data sources. Nevertheless, a large variety of XML-based data formats have been proposed, thus resulting in a difficult effective integration of bioinformatics data schemes. The adoption of a few semantic-rich standard formats is urgent to achieve a seamless integration of the current biological resources.

Biology Curriculum Guide. Bulletin 1646.

ERIC Educational Resources Information Center

Louisiana State Dept. of Education, Baton Rouge. Div. of Academic Programs.

This curriculum guide, developed to establish statewide curriculum standards for the Louisiana Competency-based Education Program, contains the minimum competencies and process skills that should be included in a biology course. It consists of: (1) a rationale for an effective science program; (2) a list and description of four major goals of…

THE U.S. ENVIRONMENTAL PROTECTION AGENCY'S STRESSOR IDENTIFICATION GUIDANCE: A PROCESS FOR DETERMINING THE PROBABLE CAUSES OF BIOLOGICAL IMPAIRMENTS

EPA Science Inventory

The United States Environmental Protection Agency (USEPA) has ongoing programs to encourage the evaluation of stream condition based on biological indicators. Bioassessments reveal impairments but do not identify causes of impairments, a necessary step in the restoration of aqua...

Promoting inquiry-based teaching in laboratory courses: are we meeting the grade?

PubMed

Beck, Christopher; Butler, Amy; da Silva, Karen Burke

2014-01-01

Over the past decade, repeated calls have been made to incorporate more active teaching and learning in undergraduate biology courses. The emphasis on inquiry-based teaching is especially important in laboratory courses, as these are the courses in which students are applying the process of science. To determine the current state of research on inquiry-based teaching in undergraduate biology laboratory courses, we reviewed the recent published literature on inquiry-based exercises. The majority of studies in our data set were in the subdisciplines of biochemistry, cell biology, developmental biology, genetics, and molecular biology. In addition, most exercises were guided inquiry, rather than open ended or research based. Almost 75% of the studies included assessment data, with two-thirds of these studies including multiple types of assessment data. However, few exercises were assessed in multiple courses or at multiple institutions. Furthermore, assessments were rarely based on published instruments. Although the results of the studies in our data set show a positive effect of inquiry-based teaching in biology laboratory courses on student learning gains, research that uses the same instrument across a range of courses and institutions is needed to determine whether these results can be generalized. © 2014 C. Beck et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Systems biology of personalized nutrition

PubMed Central

van Ommen, Ben; van den Broek, Tim; de Hoogh, Iris; van Erk, Marjan; van Someren, Eugene; Rouhani-Rankouhi, Tanja; Anthony, Joshua C; Hogenelst, Koen; Pasman, Wilrike; Boorsma, André; Wopereis, Suzan

2017-01-01

Abstract Personalized nutrition is fast becoming a reality due to a number of technological, scientific, and societal developments that complement and extend current public health nutrition recommendations. Personalized nutrition tailors dietary recommendations to specific biological requirements on the basis of a person’s health status and goals. The biology underpinning these recommendations is complex, and thus any recommendations must account for multiple biological processes and subprocesses occurring in various tissues and must be formed with an appreciation for how these processes interact with dietary nutrients and environmental factors. Therefore, a systems biology–based approach that considers the most relevant interacting biological mechanisms is necessary to formulate the best recommendations to help people meet their wellness goals. Here, the concept of “systems flexibility” is introduced to personalized nutrition biology. Systems flexibility allows the real-time evaluation of metabolism and other processes that maintain homeostasis following an environmental challenge, thereby enabling the formulation of personalized recommendations. Examples in the area of macro- and micronutrients are reviewed. Genetic variations and performance goals are integrated into this systems approach to provide a strategy for a balanced evaluation and an introduction to personalized nutrition. Finally, modeling approaches that combine personalized diagnosis and nutritional intervention into practice are reviewed. PMID:28969366

Transformation of Contaminant Candidate List (CCL3) compounds during ozonation and advanced oxidation processes in drinking water: Assessment of biological effects.

PubMed

Mestankova, Hana; Parker, Austa M; Bramaz, Nadine; Canonica, Silvio; Schirmer, Kristin; von Gunten, Urs; Linden, Karl G

2016-04-15

The removal of emerging contaminants during water treatment is a current issue and various technologies are being explored. These include UV- and ozone-based advanced oxidation processes (AOPs). In this study, AOPs were explored for their degradation capabilities of 25 chemical contaminants on the US Environmental Protection Agency's Contaminant Candidate List 3 (CCL3) in drinking water. Twenty-three of these were found to be amenable to hydroxyl radical-based treatment, with second-order rate constants for their reactions with hydroxyl radicals (OH) in the range of 3-8 × 10(9) M(-1) s(-1). The development of biological activity of the contaminants, focusing on mutagenicity and estrogenicity, was followed in parallel with their degradation using the Ames and YES bioassays to detect potential changes in biological effects during oxidative treatment. The majority of treatment cases resulted in a loss of biological activity upon oxidation of the parent compounds without generation of any form of estrogenicity or mutagenicity. However, an increase in mutagenic activity was detected by oxidative transformation of the following CCL3 parent compounds: nitrobenzene (OH, UV photolysis), quinoline (OH, ozone), methamidophos (OH), N-nitrosopyrolidine (OH), N-nitrosodi-n-propylamine (OH), aniline (UV photolysis), and N-nitrosodiphenylamine (UV photolysis). Only one case of formation of estrogenic activity was observed, namely, for the oxidation of quinoline by OH. Overall, this study provides fundamental and practical information on AOP-based treatment of specific compounds of concern and represents a framework for evaluating the performance of transformation-based treatment processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-01-01

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

LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine

PubMed Central

Clasquin, Michelle F.; Melamud, Eugene; Rabinowitz, Joshua D.

2014-01-01

MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis. PMID:22389014

LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine.

PubMed

Clasquin, Michelle F; Melamud, Eugene; Rabinowitz, Joshua D

2012-03-01

MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis.

Materials Manufactured from 3D Printed Synthetic Biology Arrays

NASA Technical Reports Server (NTRS)

Gentry, Diana; Micks, Ashley

2013-01-01

Many complex, biologically-derived materials have extremely useful properties (think wood or silk), but are unsuitable for space-related applications due to production, manufacturing, or processing limitations. Large-scale ecosystem-based production, such as raising and harvesting trees for wood, is impractical in a self-contained habitat such as a space station or potential Mars colony. Manufacturing requirements, such as the specialized equipment needed to harvest and process cotton, add too much upmass for current launch technology. Cells in nature are already highly specialized for making complex biological materials on a micro scale. We envision combining these strengths with the recently emergent technologies of synthetic biology and 3D printing to create 3D-structured arrays of cells that are bioengineered to secrete different materials in a specified three-dimensional pattern.

Photocontrollable Fluorescent Proteins for Superresolution Imaging

PubMed Central

Shcherbakova, Daria M.; Sengupta, Prabuddha; Lippincott-Schwartz, Jennifer; Verkhusha, Vladislav V.

2014-01-01

Superresolution fluorescence microscopy permits the study of biological processes at scales small enough to visualize fine subcellular structures that are unresolvable by traditional diffraction-limited light microscopy. Many superresolution techniques, including those applicable to live cell imaging, utilize genetically encoded photocontrollable fluorescent proteins. The fluorescence of these proteins can be controlled by light of specific wavelengths. In this review, we discuss the biochemical and photophysical properties of photocontrollable fluorescent proteins that are relevant to their use in superresolution microscopy. We then describe the recently developed photoactivatable, photoswitchable, and reversibly photoswitchable fluorescent proteins, and we detail their particular usefulness in single-molecule localization–based and nonlinear ensemble–based superresolution techniques. Finally, we discuss recent applications of photocontrollable proteins in superresolution imaging, as well as how these applications help to clarify properties of intracellular structures and processes that are relevant to cell and developmental biology, neuroscience, cancer biology and biomedicine. PMID:24895855

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

NASA Astrophysics Data System (ADS)

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

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

A simple method of fabricating mask-free microfluidic devices for biological analysis

PubMed Central

Yi, Xin; Kodzius, Rimantas; Gong, Xiuqing; Xiao, Kang; Wen, Weijia

2010-01-01

We report a simple, low-cost, rapid, and mask-free method to fabricate two-dimensional (2D) and three-dimensional (3D) microfluidic chip for biological analysis researches. In this fabrication process, a laser system is used to cut through paper to form intricate patterns and differently configured channels for specific purposes. Bonded with cyanoacrylate-based resin, the prepared paper sheet is sandwiched between glass slides (hydrophilic) or polymer-based plates (hydrophobic) to obtain a multilayer structure. In order to examine the chip’s biocompatibility and applicability, protein concentration was measured while DNA capillary electrophoresis was carried out, and both of them show positive results. With the utilization of direct laser cutting and one-step gas-sacrificing techniques, the whole fabrication processes for complicated 2D and 3D microfluidic devices are shorten into several minutes which make it a good alternative of poly(dimethylsiloxane) microfluidic chips used in biological analysis researches. PMID:20890452

Controlled membrane translocation provides a mechanism for signal transduction and amplification

NASA Astrophysics Data System (ADS)

Langton, Matthew J.; Keymeulen, Flore; Ciaccia, Maria; Williams, Nicholas H.; Hunter, Christopher A.

2017-05-01

Transmission and amplification of chemical signals across lipid bilayer membranes is of profound significance in many biological processes, from the development of multicellular organisms to information processing in the nervous system. In biology, membrane-spanning proteins are responsible for the transmission of chemical signals across membranes, and signal transduction is often associated with an amplified signalling cascade. The ability to reproduce such processes in artificial systems has potential applications in sensing, controlled drug delivery and communication between compartments in tissue-like constructs of synthetic vesicles. Here we describe a mechanism for transmitting a chemical signal across a membrane based on the controlled translocation of a synthetic molecular transducer from one side of a lipid bilayer membrane to the other. The controlled molecular motion has been coupled to the activation of a catalyst on the inside of a vesicle, which leads to a signal-amplification process analogous to the biological counterpart.

The application of biological motion research: biometrics, sport, and the military.

PubMed

Steel, Kylie; Ellem, Eathan; Baxter, David

2015-02-01

The body of research that examines the perception of biological motion is extensive and explores the factors that are perceived from biological motion and how this information is processed. This research demonstrates that individuals are able to use relative (temporal and spatial) information from a person's movement to recognize factors, including gender, age, deception, emotion, intention, and action. The research also demonstrates that movement presents idiosyncratic properties that allow individual discrimination, thus providing the basis for significant exploration in the domain of biometrics and social signal processing. Medical forensics, safety garments, and victim selection domains also have provided a history of research on the perception of biological motion applications; however, a number of additional domains present opportunities for application that have not been explored in depth. Therefore, the purpose of this paper is to present an overview of the current applications of biological motion-based research and to propose a number of areas where biological motion research, specific to recognition, could be applied in the future.

A rigorous approach to investigating common assumptions about disease transmission: Process algebra as an emerging modelling methodology for epidemiology.

PubMed

McCaig, Chris; Begon, Mike; Norman, Rachel; Shankland, Carron

2011-03-01

Changing scale, for example, the ability to move seamlessly from an individual-based model to a population-based model, is an important problem in many fields. In this paper, we introduce process algebra as a novel solution to this problem in the context of models of infectious disease spread. Process algebra allows us to describe a system in terms of the stochastic behaviour of individuals, and is a technique from computer science. We review the use of process algebra in biological systems, and the variety of quantitative and qualitative analysis techniques available. The analysis illustrated here solves the changing scale problem: from the individual behaviour we can rigorously derive equations to describe the mean behaviour of the system at the level of the population. The biological problem investigated is the transmission of infection, and how this relates to individual interactions.

Towards physical principles of biological evolution

NASA Astrophysics Data System (ADS)

Katsnelson, Mikhail I.; Wolf, Yuri I.; Koonin, Eugene V.

2018-03-01

Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics sufficient to adequately describe, model and explain the evolution of biological complexity? Detailed parallels have been drawn between statistical thermodynamics and the population-genetic theory of biological evolution. Based on these parallels, we outline new perspectives on biological innovation and major transitions in evolution, and introduce a biological equivalent of thermodynamic potential that reflects the innovation propensity of an evolving population. Deep analogies have been suggested to also exist between the properties of biological entities and processes, and those of frustrated states in physics, such as glasses. Such systems are characterized by frustration whereby local state with minimal free energy conflict with the global minimum, resulting in ‘emergent phenomena’. We extend such analogies by examining frustration-type phenomena, such as conflicts between different levels of selection, in biological evolution. These frustration effects appear to drive the evolution of biological complexity. We further address evolution in multidimensional fitness landscapes from the point of view of percolation theory and suggest that percolation at level above the critical threshold dictates the tree-like evolution of complex organisms. Taken together, these multiple connections between fundamental processes in physics and biology imply that construction of a meaningful physical theory of biological evolution might not be a futile effort. However, it is unrealistic to expect that such a theory can be created in one scoop; if it ever comes to being, this can only happen through integration of multiple physical models of evolutionary processes. Furthermore, the existing framework of theoretical physics is unlikely to suffice for adequate modeling of the biological level of complexity, and new developments within physics itself are likely to be required.

Bio-inspired nano-sensor-enhanced CNN visual computer.

PubMed

Porod, Wolfgang; Werblin, Frank; Chua, Leon O; Roska, Tamas; Rodriguez-Vazquez, Angel; Roska, Botond; Fay, Patrick; Bernstein, Gary H; Huang, Yih-Fang; Csurgay, Arpad I

2004-05-01

Nanotechnology opens new ways to utilize recent discoveries in biological image processing by translating the underlying functional concepts into the design of CNN (cellular neural/nonlinear network)-based systems incorporating nanoelectronic devices. There is a natural intersection joining studies of retinal processing, spatio-temporal nonlinear dynamics embodied in CNN, and the possibility of miniaturizing the technology through nanotechnology. This intersection serves as the springboard for our multidisciplinary project. Biological feature and motion detectors map directly into the spatio-temporal dynamics of CNN for target recognition, image stabilization, and tracking. The neural interactions underlying color processing will drive the development of nanoscale multispectral sensor arrays for image fusion. Implementing such nanoscale sensors on a CNN platform will allow the implementation of device feedback control, a hallmark of biological sensory systems. These biologically inspired CNN subroutines are incorporated into the new world of analog-and-logic algorithms and software, containing also many other active-wave computing mechanisms, including nature-inspired (physics and chemistry) as well as PDE-based sophisticated spatio-temporal algorithms. Our goal is to design and develop several miniature prototype devices for target detection, navigation, tracking, and robotics. This paper presents an example illustrating the synergies emerging from the convergence of nanotechnology, biotechnology, and information and cognitive science.

Adverse Outcome Pathways – Organizing Toxicological ...

EPA Pesticide Factsheets

The number of chemicals for which environmental regulatory decisions are required far exceeds the current capacity for toxicity testing. High throughput screening (HTS) commonly used for drug discovery has the potential to increase this capacity. The adverse outcome pathway (AOP) concept has emerged as a natural framework for connecting high throughput toxicity testing (HTT) results to potential impacts on humans and wildlife populations. An AOP consists of two main components that describe the biological mechanisms driving toxicity. Key events represent biological processes essential for causing the adverse outcome that are also measurable experimentally. Key event relationships capture the biological processes connecting the key events. Evidence documented for each KER based on measurements of the KEs can provide the confidence needed for extrapolating HTT from early key events to overt toxicity represented by later key events based on the AOP. The IPCS mode of action (MOA) framework incorporates information required for making a chemical-specific toxicity determination. Given the close relationship between the AOP and MOA frameworks, it is possible to assemble an MOA by incorporating HTT results, chemical properties including absorption, distribution, metabolism, and excretion (ADME), and an AOP describing the biological basis of toxicity thereby streamlining the process. While current applications focus on the assessment of risk for environmental chemicals,

Predicting PDZ domain mediated protein interactions from structure

PubMed Central

2013-01-01

Background PDZ domains are structural protein domains that recognize simple linear amino acid motifs, often at protein C-termini, and mediate protein-protein interactions (PPIs) in important biological processes, such as ion channel regulation, cell polarity and neural development. PDZ domain-peptide interaction predictors have been developed based on domain and peptide sequence information. Since domain structure is known to influence binding specificity, we hypothesized that structural information could be used to predict new interactions compared to sequence-based predictors. Results We developed a novel computational predictor of PDZ domain and C-terminal peptide interactions using a support vector machine trained with PDZ domain structure and peptide sequence information. Performance was estimated using extensive cross validation testing. We used the structure-based predictor to scan the human proteome for ligands of 218 PDZ domains and show that the predictions correspond to known PDZ domain-peptide interactions and PPIs in curated databases. The structure-based predictor is complementary to the sequence-based predictor, finding unique known and novel PPIs, and is less dependent on training–testing domain sequence similarity. We used a functional enrichment analysis of our hits to create a predicted map of PDZ domain biology. This map highlights PDZ domain involvement in diverse biological processes, some only found by the structure-based predictor. Based on this analysis, we predict novel PDZ domain involvement in xenobiotic metabolism and suggest new interactions for other processes including wound healing and Wnt signalling. Conclusions We built a structure-based predictor of PDZ domain-peptide interactions, which can be used to scan C-terminal proteomes for PDZ interactions. We also show that the structure-based predictor finds many known PDZ mediated PPIs in human that were not found by our previous sequence-based predictor and is less dependent on training–testing domain sequence similarity. Using both predictors, we defined a functional map of human PDZ domain biology and predict novel PDZ domain function. Users may access our structure-based and previous sequence-based predictors at http://webservice.baderlab.org/domains/POW. PMID:23336252

Sowing the Seeds of the Sciences: Our Gift to the Future

ERIC Educational Resources Information Center

Sillick, Audrey

2013-01-01

Audrey Sillick's article, first printed in 1988, provides a theory base for Maria Montessori's foundational emphasis on the biological sciences and the sustainability of a living, organic planet Earth as part of the educational process "of becoming more fully human." Ms. Sillick helps link primary-level biology with the special energy…

Electrophoretic separator for purifying biologicals, part 1

NASA Technical Reports Server (NTRS)

Mccreight, L. R.

1978-01-01

A program to develop an engineering model of an electrophoretic separator for purifying biologicals is summarized. An extensive mathematical modeling study and numerous ground based tests were included. Focus was placed on developing an actual electrophoretic separator of the continuous flow type, configured and suitable for flight testing as a space processing applications rocket payload.

Using Active Learning in a Studio Classroom to Teach Molecular Biology

ERIC Educational Resources Information Center

Nogaj, Luiza A.

2013-01-01

This article describes the conversion of a lecture-based molecular biology course into an active learning environment in a studio classroom. Specific assignments and activities are provided as examples. The goal of these activities is to involve students in collaborative learning, teach them how to participate in the learning process, and give…

Developmental Origins of Biological Explanations: The case of infants' internal property bias.

PubMed

Taborda-Osorio, Hernando; Cheries, Erik W

2017-10-01

People's explanations about the biological world are heavily biased toward internal, non-obvious properties. Adults and children as young as 5 years of age find internal properties more causally central than external features for explaining general biological processes and category membership. In this paper, we describe how this 'internal property bias' may be grounded in two different developmental precursors observed in studies with infants: (1) an early understanding of biological agency that is apparent in infants' reasoning about animals, and (2) the acquisition of kind-based representations that distinguish between essential and accidental properties, spanning from animals to artifacts. We argue that these precursors may support the progressive construction of the notion of biological kinds and explanations during childhood. Shortly after their first year of life, infants seem to represent the internal properties of animates as more central and identity-determining that external properties. Over time, this skeletal notion of biological kinds is integrated into diverse explanations about kind membership and biological processes, with an increasingly better understanding of the causal role of internal properties.

Plasmonic-based nanoprobes for dynamic sensing of single tumor cells (Conference Presentation)

NASA Astrophysics Data System (ADS)

Chen, Zixuan

2017-02-01

We described here two plasmonic-based nanoprobes with purpose of imaging dynamic biologic process of single tumor cells. At first, we proposed a multi-modified core-shell gold@silver nanorods for real-time monitoring the entire autophagy process at single-cell level. Autophagy is vital for understanding the mechanisms of human pathologies, developing novel drugs and exploring approaches for autophagy controlling. The plasmon resonance scattering spectra of the nanoprobes was superoxide radicals (O2•-)-dependent, a major indicator of cell autophagy, and suitable for real-time monitoring at single-cell level. More importantly, with the introduction of `relay probe' operation, two types of O2•-regulating autophagy processes were successfully traced from the beginning to the end, and the possible mechanism was also proposed. According to our results, intracellular O2•- level controlled the autophagy process by mediating the autolysosome generation. Different starvation approaches can induce different autophagy processes, such as diverse steady state time-consuming. In addition, a plasmonic-based nanothermometer was prepared via dense thermosensitive polymer (pNIPAAm) capping on gold nanorods, of which the plasmon resonance spectra was linearly dependent on adjacent temperature. In this work, the white light transmitted dark-field illuminator was replaced by a laser total internal reflection dark-field microscope (LTIR-DFM) system in order to overcome the low-throughput and inexorable biological scattering background of DFM, as well as interference from mechanic noise, nanoprobe direction, optical system drift, etc. With this nanothermometer, we have successfully captured temporal biological thermal process (thermogenesis) occurred in single tumor cells, providing a new potential strategy for in-situ cellular analysis.

Electrochemical Biosensors - Sensor Principles and Architectures

PubMed Central

Grieshaber, Dorothee; MacKenzie, Robert; Vörös, Janos; Reimhult, Erik

2008-01-01

Quantification of biological or biochemical processes are of utmost importance for medical, biological and biotechnological applications. However, converting the biological information to an easily processed electronic signal is challenging due to the complexity of connecting an electronic device directly to a biological environment. Electrochemical biosensors provide an attractive means to analyze the content of a biological sample due to the direct conversion of a biological event to an electronic signal. Over the past decades several sensing concepts and related devices have been developed. In this review, the most common traditional techniques, such as cyclic voltammetry, chronoamperometry, chronopotentiometry, impedance spectroscopy, and various field-effect transistor based methods are presented along with selected promising novel approaches, such as nanowire or magnetic nanoparticle-based biosensing. Additional measurement techniques, which have been shown useful in combination with electrochemical detection, are also summarized, such as the electrochemical versions of surface plasmon resonance, optical waveguide lightmode spectroscopy, ellipsometry, quartz crystal microbalance, and scanning probe microscopy. The signal transduction and the general performance of electrochemical sensors are often determined by the surface architectures that connect the sensing element to the biological sample at the nanometer scale. The most common surface modification techniques, the various electrochemical transduction mechanisms, and the choice of the recognition receptor molecules all influence the ultimate sensitivity of the sensor. New nanotechnology-based approaches, such as the use of engineered ion-channels in lipid bilayers, the encapsulation of enzymes into vesicles, polymersomes, or polyelectrolyte capsules provide additional possibilities for signal amplification. In particular, this review highlights the importance of the precise control over the delicate interplay between surface nano-architectures, surface functionalization and the chosen sensor transducer principle, as well as the usefulness of complementary characterization tools to interpret and to optimize the sensor response. PMID:27879772

Designer cell signal processing circuits for biotechnology

PubMed Central

Bradley, Robert W.; Wang, Baojun

2015-01-01

Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field. PMID:25579192

Promoting a structural view of biology for varied audiences: an overview of RCSB PDB resources and experiences.

PubMed

Dutta, Shuchismita; Zardecki, Christine; Goodsell, David S; Berman, Helen M

2010-10-01

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) supports scientific research and education worldwide by providing an essential resource of information on biomolecular structures. In addition to serving as a deposition, data-processing and distribution center for PDB data, the RCSB PDB offers resources and online materials that different audiences can use to customize their structural biology instruction. These include resources for general audiences that present macromolecular structure in the context of a biological theme, method-based materials for researchers who take a more traditional approach to the presentation of structural science, and materials that mix theme-based and method-based approaches for educators and students. Through these efforts the RCSB PDB aims to enable optimal use of structural data by researchers, educators and students designing and understanding experiments in biology, chemistry and medicine, and by general users making informed decisions about their life and health.

Expectancies as core features of mental disorders.

PubMed

Rief, Winfried; Glombiewski, Julia A; Gollwitzer, Mario; Schubö, Anna; Schwarting, Rainer; Thorwart, Anna

2015-09-01

Expectancies are core features of mental disorders, and change in expectations is therefore one of the core mechanisms of treatment in psychiatry. We aim to improve our understanding of expectancies by summarizing factors that contribute to their development, persistence, and modification. We pay particular attention to the issue of persistence of expectancies despite experiences that contradict them. Based on recent research findings, we propose a new model for expectation persistence and expectation change. When expectations are established, effects are evident in neural and other biological systems, for example, via anticipatory reactions, different biological reactions to expected versus unexpected stimuli, etc. Psychological 'immunization' and 'assimilation', implicit self-confirming processes, and stability of biological processes help us to better understand why expectancies persist even in the presence of expectation violations. Learning theory, attentional processes, social influences, and biological determinants contribute to the development, persistence, and modification of expectancies. Psychological interventions should focus on optimizing expectation violation to achieve optimal treatment outcome and to avoid treatment failures.

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2013-01-01

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

Semantics-enabled service discovery framework in the SIMDAT pharma grid.

PubMed

Qu, Cangtao; Zimmermann, Falk; Kumpf, Kai; Kamuzinzi, Richard; Ledent, Valérie; Herzog, Robert

2008-03-01

We present the design and implementation of a semantics-enabled service discovery framework in the data Grids for process and product development using numerical simulation and knowledge discovery (SIMDAT) Pharma Grid, an industry-oriented Grid environment for integrating thousands of Grid-enabled biological data services and analysis services. The framework consists of three major components: the Web ontology language (OWL)-description logic (DL)-based biological domain ontology, OWL Web service ontology (OWL-S)-based service annotation, and semantic matchmaker based on the ontology reasoning. Built upon the framework, workflow technologies are extensively exploited in the SIMDAT to assist biologists in (semi)automatically performing in silico experiments. We present a typical usage scenario through the case study of a biological workflow: IXodus.

Rational design and optimization of downstream processes of virus particles for biopharmaceutical applications: current advances.

PubMed

Vicente, Tiago; Mota, José P B; Peixoto, Cristina; Alves, Paula M; Carrondo, Manuel J T

2011-01-01

The advent of advanced therapies in the pharmaceutical industry has moved the spotlight into virus-like particles and viral vectors produced in cell culture holding great promise in a myriad of clinical targets, including cancer prophylaxis and treatment. Even though a couple of cases have reached the clinic, these products have yet to overcome a number of biological and technological challenges before broad utilization. Concerning the manufacturing processes, there is significant research focusing on the optimization of current cell culture systems and, more recently, on developing scalable downstream processes to generate material for pre-clinical and clinical trials. We review the current options for downstream processing of these complex biopharmaceuticals and underline current advances on knowledge-based toolboxes proposed for rational optimization of their processing. Rational tools developed to increase the yet scarce knowledge on the purification processes of complex biologicals are discussed as alternative to empirical, "black-boxed" based strategies classically used for process development. Innovative methodologies based on surface plasmon resonance, dynamic light scattering, scale-down high-throughput screening and mathematical modeling for supporting ion-exchange chromatography show great potential for a more efficient and cost-effective process design, optimization and equipment prototyping. Copyright © 2011 Elsevier Inc. All rights reserved.

Holographic femtosecond laser processing and its application to biological materials (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hayasaki, Yoshio

2017-02-01

Femtosecond laser processing is a promising tool for fabricating novel and useful structures on the surfaces of and inside materials. An enormous number of pulse irradiation points will be required for fabricating actual structures with millimeter scale, and therefore, the throughput of femtosecond laser processing must be improved for practical adoption of this technique. One promising method to improve throughput is parallel pulse generation based on a computer-generated hologram (CGH) displayed on a spatial light modulator (SLM), a technique called holographic femtosecond laser processing. The holographic method has the advantages such as high throughput, high light use efficiency, and variable, instantaneous, and 3D patterning. Furthermore, the use of an SLM gives an ability to correct unknown imperfections of the optical system and inhomogeneity in a sample using in-system optimization of the CGH. Furthermore, the CGH can adaptively compensate in response to dynamic unpredictable mechanical movements, air and liquid disturbances, a shape variation and deformation of the target sample, as well as adaptive wavefront control for environmental changes. Therefore, it is a powerful tool for the fabrication of biological cells and tissues, because they have free form, variable, and deformable structures. In this paper, we present the principle and the experimental setup of holographic femtosecond laser processing, and the effective way for processing the biological sample. We demonstrate the femtosecond laser processing of biological materials and the processing properties.

Process Pharmacology: A Pharmacological Data Science Approach to Drug Development and Therapy.

PubMed

Lötsch, Jörn; Ultsch, Alfred

2016-04-01

A novel functional-genomics based concept of pharmacology that uses artificial intelligence techniques for mining and knowledge discovery in "big data" providing comprehensive information about the drugs' targets and their functional genomics is proposed. In "process pharmacology", drugs are associated with biological processes. This puts the disease, regarded as alterations in the activity in one or several cellular processes, in the focus of drug therapy. In this setting, the molecular drug targets are merely intermediates. The identification of drugs for therapeutic or repurposing is based on similarities in the high-dimensional space of the biological processes that a drug influences. Applying this principle to data associated with lymphoblastic leukemia identified a short list of candidate drugs, including one that was recently proposed as novel rescue medication for lymphocytic leukemia. The pharmacological data science approach provides successful selections of drug candidates within development and repurposing tasks. © 2016 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model

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

Murphy, Cheryl; Nisbet, Roger; Antczak, Philipp

Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) thatmore » link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstract variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.« less

The Comet Cometh: Evolving Developmental Systems.

PubMed

Jaeger, Johannes; Laubichler, Manfred; Callebaut, Werner

In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology (EvoDevo) may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule's prediction is based on a one-sided understanding of systems biology as a science that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach-which is based on reverse engineering, simulation, and mathematical analysis-the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis.

Structure-Based Virtual Screening of Protein Tyrosine Phosphatase Inhibitors: Significance, Challenges, and Solutions.

PubMed

Reddy, Rallabandi Harikrishna; Kim, Hackyoung; Cha, Seungbin; Lee, Bongsoo; Kim, Young Jun

2017-05-28

Phosphorylation, a critical mechanism in biological systems, is estimated to be indispensable for about 30% of key biological activities, such as cell cycle progression, migration, and division. It is synergistically balanced by kinases and phosphatases, and any deviation from this balance leads to disease conditions. Pathway or biological activity-based abnormalities in phosphorylation and the type of involved phosphatase influence the outcome, and cause diverse diseases ranging from diabetes, rheumatoid arthritis, and numerous cancers. Protein tyrosine phosphatases (PTPs) are of prime importance in the process of dephosphorylation and catalyze several biological functions. Abnormal PTP activities are reported to result in several human diseases. Consequently, there is an increased demand for potential PTP inhibitory small molecules. Several strategies in structure-based drug designing techniques for potential inhibitory small molecules of PTPs have been explored along with traditional drug designing methods in order to overcome the hurdles in PTP inhibitor discovery. In this review, we discuss druggable PTPs and structure-based virtual screening efforts for successful PTP inhibitor design.

Encapsulation of biomaterials in porous glass-like matrices prepared via an aqueous colloidal sol-gel process

DOEpatents

Liu, Dean-Mo; Chen, I-Wei

2001-01-01

The present invention provides a process for the encapsulation of biologically important proteins into transparent, porous silica matrices by an alcohol-free, aqueous, colloidal sol-gel process, and to the biological materials encapsulated thereby. The process is exemplified by studies involving encapsulated cytochrome c, catalase, myoglobin, and hemoglobin, although non-proteinaceous biomaterials, such as active DNA or RNA fragments, cells or even tissues, may also be encapsulated in accordance with the present methods. Conformation, and hence activity of the biomaterial, is successfully retained after encapsulation as demonstrated by optical characterization of the molecules, even after long-term storage. The retained conformation of the biomaterial is strongly correlated to both the rate of gelation and the subsequent drying speed of the encapsulatng matrix. Moreover, in accordance with this process, gelation is accelerated by the use of a higher colloidal solid concentration and a lower synthesis pH than conventional methods, thereby enhancing structural stability and retained conformation of the biomaterials. Thus, the invention also provides a remarkable improvement in retaining the biological activity of the encapsulated biomaterial, as compared with those involved in conventional alkoxide-based processes. It further provides new methods for the quantitative and qualitative detection of test substances that are reactive to, or catalyzed by, the active, encapsulated biological materials.

Antibiotics with anaerobic ammonium oxidation in urban wastewater treatment

NASA Astrophysics Data System (ADS)

Zhou, Ruipeng; Yang, Yuanming

2017-05-01

Biofilter process is based on biological oxidation process on the introduction of fast water filter design ideas generated by an integrated filtration, adsorption and biological role of aerobic wastewater treatment process various purification processes. By engineering example, we show that the process is an ideal sewage and industrial wastewater treatment process of low concentration. Anaerobic ammonia oxidation process because of its advantage of the high efficiency and low consumption, wastewater biological denitrification field has broad application prospects. The process in practical wastewater treatment at home and abroad has become a hot spot. In this paper, anammox bacteria habitats and species diversity, and anaerobic ammonium oxidation process in the form of diversity, and one and split the process operating conditions are compared, focusing on a review of the anammox process technology various types of wastewater laboratory research and engineering applications, including general water quality and pressure filtrate sludge digestion, landfill leachate, aquaculture wastewater, monosodium glutamate wastewater, wastewater, sewage, fecal sewage, waste water salinity wastewater characteristics, research progress and application of the obstacles. Finally, we summarize the anaerobic ammonium oxidation process potential problems during the processing of the actual waste water, and proposed future research focus on in-depth study of water quality anammox obstacle factor and its regulatory policy, and vigorously develop on this basis, and combined process optimization.

Extending the knowledge in histochemistry and cell biology.

PubMed

Heupel, Wolfgang-Moritz; Drenckhahn, Detlev

2010-01-01

Central to modern Histochemistry and Cell Biology stands the need for visualization of cellular and molecular processes. In the past several years, a variety of techniques has been achieved bridging traditional light microscopy, fluorescence microscopy and electron microscopy with powerful software-based post-processing and computer modeling. Researchers now have various tools available to investigate problems of interest from bird's- up to worm's-eye of view, focusing on tissues, cells, proteins or finally single molecules. Applications of new approaches in combination with well-established traditional techniques of mRNA, DNA or protein analysis have led to enlightening and prudent studies which have paved the way toward a better understanding of not only physiological but also pathological processes in the field of cell biology. This review is intended to summarize articles standing for the progress made in "histo-biochemical" techniques and their manifold applications.

The use of writing assignments to help students synthesize content in upper-level undergraduate biology courses.

PubMed

Sparks-Thissen, Rebecca L

2017-02-01

Biology education is undergoing a transformation toward a more student-centered, inquiry-driven classroom. Many educators have designed engaging assignments that are designed to help undergraduate students gain exposure to the scientific process and data analysis. One of these types of assignments is use of a grant proposal assignment. Many instructors have used these assignments in lecture-based courses to help students process information in the literature and apply that information to a novel problem such as design of an antiviral drug or a vaccine. These assignments have been helpful in engaging students in the scientific process in the absence of an inquiry-driven laboratory. This commentary discusses the application of these grant proposal writing assignments to undergraduate biology courses. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Systems metabolic engineering strategies for the production of amino acids.

PubMed

Ma, Qian; Zhang, Quanwei; Xu, Qingyang; Zhang, Chenglin; Li, Yanjun; Fan, Xiaoguang; Xie, Xixian; Chen, Ning

2017-06-01

Systems metabolic engineering is a multidisciplinary area that integrates systems biology, synthetic biology and evolutionary engineering. It is an efficient approach for strain improvement and process optimization, and has been successfully applied in the microbial production of various chemicals including amino acids. In this review, systems metabolic engineering strategies including pathway-focused approaches, systems biology-based approaches, evolutionary approaches and their applications in two major amino acid producing microorganisms: Corynebacterium glutamicum and Escherichia coli, are summarized.

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

Global Biology Research Program: Biogeochemical Processes in Wetlands

NASA Technical Reports Server (NTRS)

Bartlett, D. S. (Editor)

1984-01-01

The results of a workshop examining potential NASA contributions to research on wetland processes as they relate to global biogeochemical cycles are summarized. A wetlands data base utilizing remotely sensed inventories, studies of wetland/atmosphere exchange processes, and the extrapolation of local measurements to global biogeochemical cycling processes were identified as possible areas for NASA support.

Multi-Dimensional Scaling based grouping of known complexes and intelligent protein complex detection.

PubMed

Rehman, Zia Ur; Idris, Adnan; Khan, Asifullah

2018-06-01

Protein-Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluating the feasibility of biological waste processing for long term space missions.

PubMed

Garland, J L; Alazraki, M P; Atkinson, C F; Finger, B W

1998-01-01

Recycling waste products during orbital (e.g., International Space Station) and planetary missions (e.g., lunar base, Mars transit mission, Martian base) will reduce storage and resupply costs. Wastes streams on the space station will include human hygiene water, urine, faeces, and trash. Longer term missions will contain human waste and inedible plant material from plant growth systems used for atmospheric regeneration, food production, and water recycling. The feasibility of biological and physical-chemical waste recycling is being investigated as part of National Aeronautics and Space Administration's (NASA) Advanced Life Support (ALS) Program. In-vessel composting has lower manpower requirements, lower water and volume requirements, and greater potential for sanitization of human waste compared to alternative bioreactor designs such as continuously stirred tank reactors (CSTR). Residual solids from the process (i.e. compost) could be used a biological air filter, a plant nutrient source, and a carbon sink. Potential in-vessel composting designs for both near- and long-term space missions are presented and discussed with respect to the unique aspects of space-based systems.

Evaluating the feasibility of biological waste processing for long term space missions

NASA Technical Reports Server (NTRS)

Garland, J. L.; Alazraki, M. P.; Atkinson, C. F.; Finger, B. W.; Sager, J. C. (Principal Investigator)

1998-01-01

Recycling waste products during orbital (e.g., International Space Station) and planetary missions (e.g., lunar base, Mars transit mission, Martian base) will reduce storage and resupply costs. Wastes streams on the space station will include human hygiene water, urine, faeces, and trash. Longer term missions will contain human waste and inedible plant material from plant growth systems used for atmospheric regeneration, food production, and water recycling. The feasibility of biological and physical-chemical waste recycling is being investigated as part of National Aeronautics and Space Administration's (NASA) Advanced Life Support (ALS) Program. In-vessel composting has lower manpower requirements, lower water and volume requirements, and greater potential for sanitization of human waste compared to alternative bioreactor designs such as continuously stirred tank reactors (CSTR). Residual solids from the process (i.e. compost) could be used a biological air filter, a plant nutrient source, and a carbon sink. Potential in-vessel composting designs for both near- and long-term space missions are presented and discussed with respect to the unique aspects of space-based systems.

Life-Game, with Glass Beads and Molecules, on the Principles of the Origin of Life

ERIC Educational Resources Information Center

Eigen, Manfred; Haglund, Herman

1976-01-01

Discusses a theoretical model that uses a game as a base for studying processes of a stochastic nature, which involve chemical reactions, molecular systems, biological processes, cells, or people in a population. (MLH)

PREDICTIVE MODELING OF LIGHT-INDUCED MORTALITY OF ENTEROCOCCI FAECALIS IN RECREATIONAL WATERS

EPA Science Inventory

One approach to predictive modeling of biological contamination of recreational waters involves the application of process-based approaches that consider microbial sources, hydrodynamic transport, and microbial fate. This presentation focuses on one important fate process, light-...

PREDICTING SUBSURFACE CONTAMINANT TRANSPORT AND TRANSFORMATION: CONSIDERATIONS FOR MODEL SELECTION AND FIELD VALIDATION

EPA Science Inventory

Predicting subsurface contaminant transport and transformation requires mathematical models based on a variety of physical, chemical, and biological processes. The mathematical model is an attempt to quantitatively describe observed processes in order to permit systematic forecas...

Development of a Model for Measuring Scientific Processing Skills Based on Brain-Imaging Technology: Focused on the Experimental Design Process

ERIC Educational Resources Information Center

Lee, Il-Sun; Byeon, Jung-Ho; Kim, Young-shin; Kwon, Yong-Ju

2014-01-01

The purpose of this study was to develop a model for measuring experimental design ability based on functional magnetic resonance imaging (fMRI) during biological inquiry. More specifically, the researchers developed an experimental design task that measures experimental design ability. Using the developed experimental design task, they measured…

Nutrients removal from undiluted cattle farm wastewater by the two-stage process of microalgae-based wastewater treatment.

PubMed

Lv, Junping; Liu, Yang; Feng, Jia; Liu, Qi; Nan, Fangru; Xie, Shulian

2018-05-24

Chlorella vulgaris was selected from five freshwater microalgal strains of Chlorophyta, and showed a good potential in nutrients removal from undiluted cattle farm wastewater. By the end of treatment, 62.30%, 81.16% and 85.29% of chemical oxygen demand (COD), ammonium (NH 4 + -N) and total phosphorus (TP) were removed. Then two two-stage processes were established to enhance nutrients removal efficiency for meeting the discharge standards of China. The process A was the biological treatment via C. vulgaris followed by the biological treatment via C. vulgaris, and the process B was the biological treatment via C. vulgaris followed by the activated carbon adsorption. After 3-5 d of treatment of wastewater via the two processes, the nutrients removal efficiency of COD, NH 4 + -N and TP were 91.24%-92.17%, 83.16%-94.27% and 90.98%-94.41%, respectively. The integrated two-stage process could strengthen nutrients removal efficiency from undiluted cattle farm wastewater with high organic substance and nitrogen concentration. Copyright © 2018 Elsevier Ltd. All rights reserved.

Learning Biology through Research Papers: A Stimulus for Question-Asking by High-School Students

ERIC Educational Resources Information Center

Brill, Gilat; Yarden, Anat

2003-01-01

Question-asking is a basic skill, required for the development of scientific thinking. However, the way in which science lessons are conducted does not usually stimulate question-asking by students. To make students more familiar with the scientific inquiry process, we developed a curriculum in developmental biology based on research papers…

Exploring autonomy through computational biomodelling.

PubMed

Palfreyman, Niall

2009-07-01

The question of whether living organisms possess autonomy of action is tied up with the nature of causal efficacy. Yet the nature of organisms is such that they frequently defy conventional causal language. Did the fig wasp select the fig, or vice versa? Is this an epithelial cell because of its genetic structure, or because it develops within the epithelium? The intimate coupling of biological levels of organisation leads developmental systems theory to deconstruct the biological organism into a life-cycle process which constitutes itself from the resources available within a complete developmental system. This radical proposal necessarily raises questions regarding the ontological status of organisms: Does an organism possess existence distinguishable from its molecular composition and social environment? The ambiguity of biological causality makes such questions difficult to answer or even formulate, and computational biology has an important role to play in operationalising the language in which they are framed. In this article we review the role played by computational biomodels in shedding light on the ontological status of organisms. These models are drawn from backgrounds ranging from molecular kinetics to niche construction, and all attempt to trace biological processes to a causal, and therefore existent, source. We conclude that computational biomodelling plays a fertile role in furnishing a proof of concept for conjectures in the philosophy of biology, and suggests the need for a process-based ontology of biological systems.

The relative importance of physical and biological energy in landscape evolution

NASA Astrophysics Data System (ADS)

Turowski, J. M.; Schwanghart, W.

2017-12-01

Landscapes are formed by the interplay of uplift and geomorphic processes, including interacting and competing physical and biological processes. For example, roots re-inforce soil and thereby stabilize hillslopes and the canopy cover of the forest may mediate the impact of precipitation. Furthermore, plants and animals act as geomorphic agents, directly altering landscape response and dynamics by their actions: tree roots may crack rocks, thus changing subsurface water flows and exposing fresh material for denudation; fungi excrete acids that accelerate rates of chemical weathering, and burrowing animals displace soil and rocks while digging holes for shelter or in search of food. Energetically, landscapes can be viewed as open systems in which topography stores potential energy above a base level. Tectonic processes add energy to the system by uplift and mechanically altering rock properties. Especially in unvegetated regions, erosion and transport by wind can be an important geomorphic process. Advection of atmospheric moisture in high altitudes provides potential energy that is converted by water fluxes through catchments. At the same time, the conversion of solar energy through atmospheric and biological processes drives primary production of living organisms. If we accept that biota influence geomorphic processes, then what is their energetic contribution to landscape evolution relative to physical processes? Using two case studies, we demonstrate that all components of energy input are negligible apart from biological production, quantified by net primary productivity (NPP) and potential energy conversion by water that is placed high up in the landscape as rainfall and leaves it as runoff. Assuming that the former is representative for biological energy and the latter for physical energy, we propose that the ratio of these two values can be used as a proxy for the relative importance of biological and physical processes in landscape evolution. All necessary parameters needed to calculate the ratio (NPP, runoff, elevation) are available globally. We find that biological processes are more important in arid and semiarid regions. The wide-spread lack of water strongly limits the energy available for fluvial erosion, while biota are geomorphic engineers less sensitive to water shortage.

A Biologically-Based Alternative Water Processor for Long Duration Space Missions

NASA Technical Reports Server (NTRS)

Barta, Daniel J.; Pickering, Karen D.; Meyer, Caitlin; Pensinger, Stuart; Vega, Leticia; Flynn, Michael; Jackson, Andrew; Wheeler, Raymond

2015-01-01

A wastewater recovery system has been developed that combines novel biological and physicochemical components for recycling wastewater on long duration space missions. Functionally, this Alternative Water Processor (AWP) would replace the Urine Processing Assembly on the International Space Station and reduce or eliminate the need for the multifiltration beds of the Water Processing Assembly (WPA). At its center are two unique game changing technologies: 1) a biological water processor (BWP) to mineralize organic forms of carbon and nitrogen and 2) an advanced membrane processor (Forward Osmosis Secondary Treatment) for removal of solids and inorganic ions. The AWP is designed for recycling larger quantities of wastewater from multiple sources expected during future exploration missions, including urine, hygiene (hand wash, shower, oral and shave) and laundry. The BWP utilizes a single-stage membrane-aerated biological reactor for simultaneous nitrification and denitrification. The Forward Osmosis Secondary Treatment (FOST) system uses a combination of forward osmosis (FO) and reverse osmosis (RO), is resistant to biofouling and can easily tolerate wastewaters high in non-volatile organics and solids associated with shower and/or hand washing. The BWP was operated continuously for over 300 days. After startup, the mature biological system averaged 85% organic carbon removal and 44% nitrogen removal, close to maximum based on available carbon. The FOST has averaged 93% water recovery, with a maximum of 98%. If the wastewater is slighty acidified, ammonia rejection is optimal. This paper will provide a description of the technology and summarize results from ground-based testing using real wastewater.

The multiscale backbone of the human phenotype network based on biological pathways.

PubMed

Darabos, Christian; White, Marquitta J; Graham, Britney E; Leung, Derek N; Williams, Scott M; Moore, Jason H

2014-01-25

Networks are commonly used to represent and analyze large and complex systems of interacting elements. In systems biology, human disease networks show interactions between disorders sharing common genetic background. We built pathway-based human phenotype network (PHPN) of over 800 physical attributes, diseases, and behavioral traits; based on about 2,300 genes and 1,200 biological pathways. Using GWAS phenotype-to-genes associations, and pathway data from Reactome, we connect human traits based on the common patterns of human biological pathways, detecting more pleiotropic effects, and expanding previous studies from a gene-centric approach to that of shared cell-processes. The resulting network has a heavily right-skewed degree distribution, placing it in the scale-free region of the network topologies spectrum. We extract the multi-scale information backbone of the PHPN based on the local densities of the network and discarding weak connection. Using a standard community detection algorithm, we construct phenotype modules of similar traits without applying expert biological knowledge. These modules can be assimilated to the disease classes. However, we are able to classify phenotypes according to shared biology, and not arbitrary disease classes. We present examples of expected clinical connections identified by PHPN as proof of principle. We unveil a previously uncharacterized connection between phenotype modules and discuss potential mechanistic connections that are obvious only in retrospect. The PHPN shows tremendous potential to become a useful tool both in the unveiling of the diseases' common biology, and in the elaboration of diagnosis and treatments.

A comparison of form processing involved in the perception of biological and nonbiological movements

PubMed Central

Thurman, Steven M.; Lu, Hongjing

2016-01-01

Although there is evidence for specialization in the human brain for processing biological motion per se, few studies have directly examined the specialization of form processing in biological motion perception. The current study was designed to systematically compare form processing in perception of biological (human walkers) to nonbiological (rotating squares) stimuli. Dynamic form-based stimuli were constructed with conflicting form cues (position and orientation), such that the objects were perceived to be moving ambiguously in two directions at once. In Experiment 1, we used the classification image technique to examine how local form cues are integrated across space and time in a bottom-up manner. By comparing with a Bayesian observer model that embodies generic principles of form analysis (e.g., template matching) and integrates form information according to cue reliability, we found that human observers employ domain-general processes to recognize both human actions and nonbiological object movements. Experiments 2 and 3 found differential top-down effects of spatial context on perception of biological and nonbiological forms. When a background does not involve social information, observers are biased to perceive foreground object movements in the direction opposite to surrounding motion. However, when a background involves social cues, such as a crowd of similar objects, perception is biased toward the same direction as the crowd for biological walking stimuli, but not for rotating nonbiological stimuli. The model provided an accurate account of top-down modulations by adjusting the prior probabilities associated with the internal templates, demonstrating the power and flexibility of the Bayesian approach for visual form perception. PMID:26746875

Manipulating and Monitoring On-Surface Biological Reactions by Light-Triggered Local pH Alterations.

PubMed

Peretz-Soroka, Hagit; Pevzner, Alexander; Davidi, Guy; Naddaka, Vladimir; Kwiat, Moria; Huppert, Dan; Patolsky, Fernando

2015-07-08

Significant research efforts have been dedicated to the integration of biological species with electronic elements to yield smart bioelectronic devices. The integration of DNA, proteins, and whole living cells and tissues with electronic devices has been developed into numerous intriguing applications. In particular, the quantitative detection of biological species and monitoring of biological processes are both critical to numerous areas of medical and life sciences. Nevertheless, most current approaches merely focus on the "monitoring" of chemical processes taking place on the sensing surfaces, and little efforts have been invested in the conception of sensitive devices that can simultaneously "control" and "monitor" chemical and biological reactions by the application of on-surface reversible stimuli. Here, we demonstrate the light-controlled fine modulation of surface pH by the use of photoactive molecularly modified nanomaterials. Through the use of nanowire-based FET devices, we showed the capability of modulating the on-surface pH, by intensity-controlled light stimulus. This allowed us simultaneously and locally to control and monitor pH-sensitive biological reactions on the nanodevices surfaces, such as the local activation and inhibition of proteolytic enzymatic processes, as well as dissociation of antigen-antibody binding interactions. The demonstrated capability of locally modulating the on-surface effective pH, by a light stimuli, may be further applied in the local control of on-surface DNA hybridization/dehybridization processes, activation or inhibition of living cells processes, local switching of cellular function, local photoactivation of neuronal networks with single cell resolution and so forth.

Systematic analysis of signaling pathways using an integrative environment.

PubMed

Visvanathan, Mahesh; Breit, Marc; Pfeifer, Bernhard; Baumgartner, Christian; Modre-Osprian, Robert; Tilg, Bernhard

2007-01-01

Understanding the biological processes of signaling pathways as a whole system requires an integrative software environment that has comprehensive capabilities. The environment should include tools for pathway design, visualization, simulation and a knowledge base concerning signaling pathways as one. In this paper we introduce a new integrative environment for the systematic analysis of signaling pathways. This system includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning signaling pathways that provides the basic understanding of the biological system, its structure and functioning. The system is designed with a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer. The TNFa-mediated NF-kB signal trans-duction pathway model was designed and tested using our integrative framework. It was also useful to define the structure of the knowledge base. Sensitivity analysis of this specific pathway was performed providing simulation data. Then the model was extended showing promising initial results. The proposed system offers a holistic view of pathways containing biological and modeling data. It will help us to perform biological interpretation of the simulation results and thus contribute to a better understanding of the biological system for drug identification.

Advances in biologically inspired on/near sensor processing

NASA Astrophysics Data System (ADS)

McCarley, Paul L.

1999-07-01

As electro-optic sensors increase in size and frame rate, the data transfer and digital processing resource requirements also increase. In many missions, the spatial area of interest is but a small fraction of the available field of view. Choosing the right region of interest, however, is a challenge and still requires an enormous amount of downstream digital processing resources. In order to filter this ever-increasing amount of data, we look at how nature solves the problem. The Advanced Guidance Division of the Munitions Directorate, Air Force Research Laboratory at Elgin AFB, Florida, has been pursuing research in the are of advanced sensor and image processing concepts based on biologically inspired sensory information processing. A summary of two 'neuromorphic' processing efforts will be presented along with a seeker system concept utilizing this innovative technology. The Neuroseek program is developing a 256 X 256 2-color dual band IRFPA coupled to an optimized silicon CMOS read-out and processing integrated circuit that provides simultaneous full-frame imaging in MWIR/LWIR wavebands along with built-in biologically inspired sensor image processing functions. Concepts and requirements for future such efforts will also be discussed.

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems

PubMed Central

Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K.; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C.; Hoeng, Julia

2015-01-01

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com PMID:25887162

Mathematical manipulative models: in defense of "beanbag biology".

PubMed

Jungck, John R; Gaff, Holly; Weisstein, Anton E

2010-01-01

Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process-1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets-we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project (http://bioquest.org/esteem) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education.

Introducing capnophilic lactic fermentation in a combined dark-photo fermentation process: a route to unparalleled H2 yields.

PubMed

Dipasquale, L; Adessi, A; d'Ippolito, G; Rossi, F; Fontana, A; De Philippis, R

2015-01-01

Two-stage process based on photofermentation of dark fermentation effluents is widely recognized as the most effective method for biological production of hydrogen from organic substrates. Recently, it was described an alternative mechanism, named capnophilic lactic fermentation, for sugar fermentation by the hyperthermophilic bacterium Thermotoga neapolitana in CO2-rich atmosphere. Here, we report the first application of this novel process to two-stage biological production of hydrogen. The microbial system based on T. neapolitana DSM 4359(T) and Rhodopseudomonas palustris 42OL gave 9.4 mol of hydrogen per mole of glucose consumed during the anaerobic process, which is the best production yield so far reported for conventional two-stage batch cultivations. The improvement of hydrogen yield correlates with the increase in lactic production during capnophilic lactic fermentation and takes also advantage of the introduction of original conditions for culturing both microorganisms in minimal media based on diluted sea water. The use of CO2 during the first step of the combined process establishes a novel strategy for biohydrogen technology. Moreover, this study opens the way to cost reduction and use of salt-rich waste as feedstock.

Pathway-Based Analysis of Genome-Wide siRNA Screens Reveals the Regulatory Landscape of App Processing

PubMed Central

Camargo, Luiz Miguel; Zhang, Xiaohua Douglas; Loerch, Patrick; Caceres, Ramon Miguel; Marine, Shane D.; Uva, Paolo; Ferrer, Marc; de Rinaldis, Emanuele; Stone, David J.; Majercak, John; Ray, William J.; Yi-An, Chen; Shearman, Mark S.; Mizuguchi, Kenji

2015-01-01

The progressive aggregation of Amyloid-β (Aβ) in the brain is a major trait of Alzheimer's Disease (AD). Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP). Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPPα. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A) recently implicated with AD through genome wide association studies (GWAS) and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the “regulatory landscape” of APP. PMID:25723573

How to design cell-based biosensors using the sol-gel process.

PubMed

Depagne, Christophe; Roux, Cécile; Coradin, Thibaud

2011-05-01

Inorganic gels formed using the sol-gel process are promising hosts for the encapsulation of living organisms and the design of cell-based biosensors. However, the possibility to use the biological activity of entrapped cells as a biological signal requires a good understanding and careful control of the chemical and physical conditions in which the organisms are placed before, during, and after gel formation, and their impact on cell viability. Moreover, it is important to examine the possible transduction methods that are compatible with sol-gel encapsulated cells. Through an updated presentation of the current knowledge in this field and based on selected examples, this review shows how it has been possible to convert a chemical technology initially developed for the glass industry into a biotechnological tool, with current limitations and promising specificities.

Development of a GCR Event-based Risk Model

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

2009-01-01

A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how GCR event rates mapped to biological signaling induction and relaxation times. We considered several hypotheses related to signaling and cancer risk, and then performed simulations for conditions where aberrant or adaptive signaling would occur on long-duration space mission. Our results do not support the conventional assumptions of dose, linearity and additivity. A discussion on how event-based systems biology models, which focus on biological signaling as the mechanism to propagate damage or adaptation, can be further developed for cancer and CNS space radiation risk projections is given.

Sunlight-induced Transformations of Graphene-based Nanomaterials in Aquatic Environments

EPA Science Inventory

Graphene-based nanomaterials and other related carbon nanomaterials (CNMs) can be released from products during their life cycles. Upon entry into aquatic environments, they are potentially transformed by photochemical reactions, oxidation reactions and biological processes, all ...

Hierarchical thinking in network biology: the unbiased modularization of biochemical networks.

PubMed

Papin, Jason A; Reed, Jennifer L; Palsson, Bernhard O

2004-12-01

As reconstructed biochemical reaction networks continue to grow in size and scope, there is a growing need to describe the functional modules within them. Such modules facilitate the study of biological processes by deconstructing complex biological networks into conceptually simple entities. The definition of network modules is often based on intuitive reasoning. As an alternative, methods are being developed for defining biochemical network modules in an unbiased fashion. These unbiased network modules are mathematically derived from the structure of the whole network under consideration.

Interdisciplinary research and education at the biology-engineering-computer science interface: a perspective.

PubMed

Tadmor, Brigitta; Tidor, Bruce

2005-09-01

Progress in the life sciences, including genome sequencing and high-throughput experimentation, offers an opportunity for understanding biology and medicine from a systems perspective. This 'new view', which complements the more traditional component-based approach, involves the integration of biological research with approaches from engineering disciplines and computer science. The result is more than a new set of technologies. Rather, it promises a fundamental reconceptualization of the life sciences based on the development of quantitative and predictive models to describe crucial processes. To achieve this change, learning communities are being formed at the interface of the life sciences, engineering and computer science. Through these communities, research and education will be integrated across disciplines and the challenges associated with multidisciplinary team-based science will be addressed.

Biogeosystem technique as the way to certainty of soil, hydrosphere, environment and climate

NASA Astrophysics Data System (ADS)

Kalinitchenko, Valery; Batukaev, Abdulmalik; Zarmaev, Ali; Startsev, Viktor; Chernenko, Vladimir; Dikaev, Zaurbek; Sushkova, Svetlana

2016-04-01

The modern technological platform awkwardly imitates the Nature. Teaching the Geosciences, development of technology, overcoming the problem of uncertainty of geospheres is impossible on the base of outdated knowledge. An emphasis is to be done not on the natural analogues, but on our new technologies - Biogeosystem Technique (BGT*). BGT* is a transcendental (not imitating the natural processes) approach to soil processing, regulation of fluxes of energy, gas, water, matter and biological productivity of biosphere: Intrasoil milling processing in 20-50 cm soil layer provides new soil disperse system, best conditions for stable evolution of techno-soil and plant growth in period up to 40 years after the single processing. Pulse intrasoil discrete irrigation provides an injection of small discrete dose of water which distributes in vertical soil cylinder. Lateral distance between successive injections is 10-15 cm. The water within 5-10 min after injection spreads in cylinder of diameter 2-4 cm at depth from 5 to 50 cm. The soil carcass around the cylinder is dry and mechanically stable. Mean thermodynamic soil water potential after watering is of -0.2 MPa. Stomatal apparatus is in a regulation mode, transpiration rate is reduced, soil solution concentration increased, plant nutrition rate and biological productivity are high. No excessive plant transpiration, evaporation and seepage of water from soil. Intrasoil environmentally safe waste return during intrasoil milling processing and (or) intrasoil pulse discrete plants watering with nutrition. Is provided the medically, veterinary and environmentally safe recycle of municipal, industrial, biological and agricultural wastes into the soil continuum. All applied substances transform to plant nutrients, not degrade to the greenhouse gas, or become the deposit of waste. Capabilities of intrasoil technologies of BGT* to correct and sustain the Nature: Correct soil evolution, long-term biological productivity of intrasoil processed soil of 150% higher compared to initial. Save of fresh water by intrasoil irrigation up to 20 times. Biological return of matter and high biological productivity of soil by environmentally safe intrasoil waste recycling. On the base of BGT* are opened the opportunities for: controlled, stable, safe, biologically effective soil, environment and landscape; improved equilibriums in soil, environment and landscape; reduced water consumption; improved waste management; reduced flux of nutrients to water systems; carbon transformation into the soil to the state of elements of plant nutrition; reducing degradation of biological matter to the state of greenhouse gases; increasing biologi al consumption of carbon dioxide by photosynthesis in terrestrial system; prolongation of the phase of carbon in terrestrial biological system for greenhouse gases sequestration; extension of the active area of biosphere on terrestrial part of the Earth; high rate oxidation of methane and hydrogen sulfide by oxygen, which is ionized in photosynthesis, and thus is biologically active; high biological product output of biosphere. The higher biomass on the Earth, the more ecologically safe food, raw material and biofuel can be produced, better conditions for technologies of Noosphere. Uncertainty of soil, hydrosphere, environment and climate will be reduced by the BGT* methods. Are available BGT* robotic systems of low cost and minimal consumption of energy and material.

Biohydrogen Production: Strategies to Improve Process Efficiency through Microbial Routes

PubMed Central

Chandrasekhar, Kuppam; Lee, Yong-Jik; Lee, Dong-Woo

2015-01-01

The current fossil fuel-based generation of energy has led to large-scale industrial development. However, the reliance on fossil fuels leads to the significant depletion of natural resources of buried combustible geologic deposits and to negative effects on the global climate with emissions of greenhouse gases. Accordingly, enormous efforts are directed to transition from fossil fuels to nonpolluting and renewable energy sources. One potential alternative is biohydrogen (H2), a clean energy carrier with high-energy yields; upon the combustion of H2, H2O is the only major by-product. In recent decades, the attractive and renewable characteristics of H2 led us to develop a variety of biological routes for the production of H2. Based on the mode of H2 generation, the biological routes for H2 production are categorized into four groups: photobiological fermentation, anaerobic fermentation, enzymatic and microbial electrolysis, and a combination of these processes. Thus, this review primarily focuses on the evaluation of the biological routes for the production of H2. In particular, we assess the efficiency and feasibility of these bioprocesses with respect to the factors that affect operations, and we delineate the limitations. Additionally, alternative options such as bioaugmentation, multiple process integration, and microbial electrolysis to improve process efficiency are discussed to address industrial-level applications. PMID:25874756

Biohydrogen production: strategies to improve process efficiency through microbial routes.

PubMed

Chandrasekhar, Kuppam; Lee, Yong-Jik; Lee, Dong-Woo

2015-04-14

The current fossil fuel-based generation of energy has led to large-scale industrial development. However, the reliance on fossil fuels leads to the significant depletion of natural resources of buried combustible geologic deposits and to negative effects on the global climate with emissions of greenhouse gases. Accordingly, enormous efforts are directed to transition from fossil fuels to nonpolluting and renewable energy sources. One potential alternative is biohydrogen (H2), a clean energy carrier with high-energy yields; upon the combustion of H2, H2O is the only major by-product. In recent decades, the attractive and renewable characteristics of H2 led us to develop a variety of biological routes for the production of H2. Based on the mode of H2 generation, the biological routes for H2 production are categorized into four groups: photobiological fermentation, anaerobic fermentation, enzymatic and microbial electrolysis, and a combination of these processes. Thus, this review primarily focuses on the evaluation of the biological routes for the production of H2. In particular, we assess the efficiency and feasibility of these bioprocesses with respect to the factors that affect operations, and we delineate the limitations. Additionally, alternative options such as bioaugmentation, multiple process integration, and microbial electrolysis to improve process efficiency are discussed to address industrial-level applications.

An instructional design process based on expert knowledge for teaching students how mechanisms are explained.

PubMed

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

2016-06-01

In biology and physiology courses, students face many difficulties when learning to explain mechanisms, a topic that is demanding due to the immense complexity and abstract nature of molecular and cellular mechanisms. To overcome these difficulties, we asked the following question: how does an instructor transform their understanding of biological mechanisms and other difficult-to-learn topics so that students can comprehend them? To address this question, we first reviewed a model of the components used by biologists to explain molecular and cellular mechanisms: the MACH model, with the components of methods (M), analogies (A), context (C), and how (H). Next, instructional materials were developed and the teaching activities were piloted with a physical MACH model. Students who used the MACH model to guide their explanations of mechanisms exhibited both improvements and some new difficulties. Third, a series of design-based research cycles was applied to bring the activities with an improved physical MACH model into biology and biochemistry courses. Finally, a useful rubric was developed to address prevalent student difficulties. Here, we present, for physiology and biology instructors, the knowledge and resources for explaining molecular and cellular mechanisms in undergraduate courses with an instructional design process aimed at realizing pedagogical content knowledge for teaching. Our four-stage process could be adapted to advance instruction with a range of models in the life sciences. Copyright © 2016 The American Physiological Society.

Ecotoxicological criteria for final storage quality: Possibilities and limits

NASA Astrophysics Data System (ADS)

Zeyer, Josef; Meyer, Joseph

Landfills are complex chemical and biological reactors whose internal processes are often beyond the immediate control of process engineers. Therefore, the concept of a "Final Storage Landfill" may be deceptive. Furthermore, traditional approaches to establishing discharge criteria and treatment requirements for industrial effluents may not work well for landfill emissions. Factories can often be treated as steady-state processes whose inputs and outputs are predictable; however, landfills are batch reactors whose contents and emissions may be unknown and will vary temporally and spatially. If the contents of a landfill are known, the sequence of chemical reactions can be predicted qualitatively. Even if that sequence is predictable, though, quantitative ecotoxicological criteria will be difficult to establish, and risk assessments based on chemical "laundry lists" will be questionable. The situation is not hopeless, though. New approaches can be developed to monitor and predict landfill emissions. We believe these will include (1) testing (biological and chemical) of internal components of landfills as well as emissions; (2) development of laboratory and/or field methods in which the chemical and biological evolution of landfills can be studied at accelerated rates, thus allowing better prediction of future emissions; and (3) flexible ecotoxicological criteria that are adaptable to the evolving nature of landfill emissions. These criteria should be based on complementary chemical analyses and biological tests that fit into a hierarchical (decision-tree) hazard assessment strategy.

An instructional design process based on expert knowledge for teaching students how mechanisms are explained

PubMed Central

Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

In biology and physiology courses, students face many difficulties when learning to explain mechanisms, a topic that is demanding due to the immense complexity and abstract nature of molecular and cellular mechanisms. To overcome these difficulties, we asked the following question: how does an instructor transform their understanding of biological mechanisms and other difficult-to-learn topics so that students can comprehend them? To address this question, we first reviewed a model of the components used by biologists to explain molecular and cellular mechanisms: the MACH model, with the components of methods (M), analogies (A), context (C), and how (H). Next, instructional materials were developed and the teaching activities were piloted with a physical MACH model. Students who used the MACH model to guide their explanations of mechanisms exhibited both improvements and some new difficulties. Third, a series of design-based research cycles was applied to bring the activities with an improved physical MACH model into biology and biochemistry courses. Finally, a useful rubric was developed to address prevalent student difficulties. Here, we present, for physiology and biology instructors, the knowledge and resources for explaining molecular and cellular mechanisms in undergraduate courses with an instructional design process aimed at realizing pedagogical content knowledge for teaching. Our four-stage process could be adapted to advance instruction with a range of models in the life sciences. PMID:27231262

A mechanistic Individual-based Model of microbial communities.

PubMed

Jayathilake, Pahala Gedara; Gupta, Prashant; Li, Bowen; Madsen, Curtis; Oyebamiji, Oluwole; González-Cabaleiro, Rebeca; Rushton, Steve; Bridgens, Ben; Swailes, David; Allen, Ben; McGough, A Stephen; Zuliani, Paolo; Ofiteru, Irina Dana; Wilkinson, Darren; Chen, Jinju; Curtis, Tom

2017-01-01

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for "bottom up" prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup.

A mechanistic Individual-based Model of microbial communities

PubMed Central

Gupta, Prashant; Li, Bowen; Madsen, Curtis; Oyebamiji, Oluwole; González-Cabaleiro, Rebeca; Rushton, Steve; Bridgens, Ben; Swailes, David; Allen, Ben; McGough, A. Stephen; Zuliani, Paolo; Ofiteru, Irina Dana; Wilkinson, Darren; Chen, Jinju; Curtis, Tom

2017-01-01

Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for “bottom up” prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup. PMID:28771505

Dyslexia

MedlinePlus

... techniques to diagnose and treat dyslexia and other learning disabilities, increasing the understanding of the biological and possible genetic bases of learning disabilities, and exploring the relationship between neurophysiological processes and ...

Unified Deep Learning Architecture for Modeling Biology Sequence.

PubMed

Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang

2017-10-09

Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.

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.

The Ontology of Biological and Clinical Statistics (OBCS) for standardized and reproducible statistical analysis.

PubMed

Zheng, Jie; Harris, Marcelline R; Masci, Anna Maria; Lin, Yu; Hero, Alfred; Smith, Barry; He, Yongqun

2016-09-14

Statistics play a critical role in biological and clinical research. However, most reports of scientific results in the published literature make it difficult for the reader to reproduce the statistical analyses performed in achieving those results because they provide inadequate documentation of the statistical tests and algorithms applied. The Ontology of Biological and Clinical Statistics (OBCS) is put forward here as a step towards solving this problem. The terms in OBCS including 'data collection', 'data transformation in statistics', 'data visualization', 'statistical data analysis', and 'drawing a conclusion based on data', cover the major types of statistical processes used in basic biological research and clinical outcome studies. OBCS is aligned with the Basic Formal Ontology (BFO) and extends the Ontology of Biomedical Investigations (OBI), an OBO (Open Biological and Biomedical Ontologies) Foundry ontology supported by over 20 research communities. Currently, OBCS comprehends 878 terms, representing 20 BFO classes, 403 OBI classes, 229 OBCS specific classes, and 122 classes imported from ten other OBO ontologies. We discuss two examples illustrating how the ontology is being applied. In the first (biological) use case, we describe how OBCS was applied to represent the high throughput microarray data analysis of immunological transcriptional profiles in human subjects vaccinated with an influenza vaccine. In the second (clinical outcomes) use case, we applied OBCS to represent the processing of electronic health care data to determine the associations between hospital staffing levels and patient mortality. Our case studies were designed to show how OBCS can be used for the consistent representation of statistical analysis pipelines under two different research paradigms. Other ongoing projects using OBCS for statistical data processing are also discussed. The OBCS source code and documentation are available at: https://github.com/obcs/obcs . The Ontology of Biological and Clinical Statistics (OBCS) is a community-based open source ontology in the domain of biological and clinical statistics. OBCS is a timely ontology that represents statistics-related terms and their relations in a rigorous fashion, facilitates standard data analysis and integration, and supports reproducible biological and clinical research.

[Numerical simulation and operation optimization of biological filter].

PubMed

Zou, Zong-Sen; Shi, Han-Chang; Chen, Xiang-Qiang; Xie, Xiao-Qing

2014-12-01

BioWin software and two sensitivity analysis methods were used to simulate the Denitrification Biological Filter (DNBF) + Biological Aerated Filter (BAF) process in Yuandang Wastewater Treatment Plant. Based on the BioWin model of DNBF + BAF process, the operation data of September 2013 were used for sensitivity analysis and model calibration, and the operation data of October 2013 were used for model validation. The results indicated that the calibrated model could accurately simulate practical DNBF + BAF processes, and the most sensitive parameters were the parameters related to biofilm, OHOs and aeration. After the validation and calibration of model, it was used for process optimization with simulating operation results under different conditions. The results showed that, the best operation condition for discharge standard B was: reflux ratio = 50%, ceasing methanol addition, influent C/N = 4.43; while the best operation condition for discharge standard A was: reflux ratio = 50%, influent COD = 155 mg x L(-1) after methanol addition, influent C/N = 5.10.

[Problems of world outlook and methodology of science integration in biological studies].

PubMed

Khododova, Iu D

1981-01-01

Problems of worldoutlook and methodology of the natural-science knowledge are considered basing on the analysis of tendencies in the development of the membrane theory of cell processes and the use of principles of biological membrane functioning when solving some scientific and applied problems pertaining to different branches of chemistry and biology. The notion scientific knowledge integration is defined as interpenetration of approaches, methods and ideas of different branches of knowledge and enrichment on this basis of their content resulting in knowledge augmentation in each field taken separately. These processes are accompanied by appearance of new branches of knowledge - sciences "on junction" and their subsequent differentiations. The analysis of some gnoseological situations shows that integration of sciences contributes to coordination and some agreement of thinking styles of different specialists, puts forward keen personality of a scientist demanding, in particular, his high professional mobility. Problems of scientific activity organization are considered, which involve social sciences into the integration processes. The role of philosophy in the integration processes is emphasized.

Completing and Adapting Models of Biological Processes

NASA Technical Reports Server (NTRS)

Margaria, Tiziana; Hinchey, Michael G.; Raffelt, Harald; Rash, James L.; Rouff, Christopher A.; Steffen, Bernhard

2006-01-01

We present a learning-based method for model completion and adaptation, which is based on the combination of two approaches: 1) R2D2C, a technique for mechanically transforming system requirements via provably equivalent models to running code, and 2) automata learning-based model extrapolation. The intended impact of this new combination is to make model completion and adaptation accessible to experts of the field, like biologists or engineers. The principle is briefly illustrated by generating models of biological procedures concerning gene activities in the production of proteins, although the main application is going to concern autonomic systems for space exploration.

Comparative Study on Interaction of Form and Motion Processing Streams by Applying Two Different Classifiers in Mechanism for Recognition of Biological Movement

PubMed Central

2014-01-01

Research on psychophysics, neurophysiology, and functional imaging shows particular representation of biological movements which contains two pathways. The visual perception of biological movements formed through the visual system called dorsal and ventral processing streams. Ventral processing stream is associated with the form information extraction; on the other hand, dorsal processing stream provides motion information. Active basic model (ABM) as hierarchical representation of the human object had revealed novelty in form pathway due to applying Gabor based supervised object recognition method. It creates more biological plausibility along with similarity with original model. Fuzzy inference system is used for motion pattern information in motion pathway creating more robustness in recognition process. Besides, interaction of these paths is intriguing and many studies in various fields considered it. Here, the interaction of the pathways to get more appropriated results has been investigated. Extreme learning machine (ELM) has been implied for classification unit of this model, due to having the main properties of artificial neural networks, but crosses from the difficulty of training time substantially diminished in it. Here, there will be a comparison between two different configurations, interactions using synergetic neural network and ELM, in terms of accuracy and compatibility. PMID:25276860

Marketing the use of the space environment for the processing of biological and pharmaceutical materials

NASA Technical Reports Server (NTRS)

1984-01-01

The perceptions of U.S. biotechnology and pharmaceutical companies concerning the potential use of the space environment for the processing of biological substances was examined. Physical phenomena that may be important in space-base processing of biological materials are identified and discussed in the context of past and current experiment programs. The capabilities of NASA to support future research and development, and to engage in cooperative risk sharing programs with industry are discussed. Meetings were held with several biotechnology and pharmaceutical companies to provide data for an analysis of the attitudes and perceptions of these industries toward the use of the space environment. Recommendations are made for actions that might be taken by NASA to facilitate the marketing of the use of the space environment, and in particular the Space Shuttle, to the biotechnology and pharmaceutical industries.

DNA codes for nanoscience.

PubMed

Samorì, Bruno; Zuccheri, Giampaolo

2005-02-11

The nanometer scale is a special place where all sciences meet and develop a particularly strong interdisciplinarity. While biology is a source of inspiration for nanoscientists, chemistry has a central role in turning inspirations and methods from biological systems to nanotechnological use. DNA is the biological molecule by which nanoscience and nanotechnology is mostly fascinated. Nature uses DNA not only as a repository of the genetic information, but also as a controller of the expression of the genes it contains. Thus, there are codes embedded in the DNA sequence that serve to control recognition processes on the atomic scale, such as the base pairing, and others that control processes taking place on the nanoscale. From the chemical point of view, DNA is the supramolecular building block with the highest informational content. Nanoscience has therefore the opportunity of using DNA molecules to increase the level of complexity and efficiency in self-assembling and self-directing processes.

Functional annotation of chemical libraries across diverse biological processes.

PubMed

Piotrowski, Jeff S; Li, Sheena C; Deshpande, Raamesh; Simpkins, Scott W; Nelson, Justin; Yashiroda, Yoko; Barber, Jacqueline M; Safizadeh, Hamid; Wilson, Erin; Okada, Hiroki; Gebre, Abraham A; Kubo, Karen; Torres, Nikko P; LeBlanc, Marissa A; Andrusiak, Kerry; Okamoto, Reika; Yoshimura, Mami; DeRango-Adem, Eva; van Leeuwen, Jolanda; Shirahige, Katsuhiko; Baryshnikova, Anastasia; Brown, Grant W; Hirano, Hiroyuki; Costanzo, Michael; Andrews, Brenda; Ohya, Yoshikazu; Osada, Hiroyuki; Yoshida, Minoru; Myers, Chad L; Boone, Charles

2017-09-01

Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells in the presence of a compound, revealing chemical-genetic interactions that can elucidate a compound's mode of action. We developed a highly parallel, unbiased yeast chemical-genetic screening system involving three key components. First, in a drug-sensitive genetic background, we constructed an optimized diagnostic mutant collection that is predictive for all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode-sequencing protocol, enabling the assembly of thousands of chemical-genetic profiles. Finally, based on comparison of the chemical-genetic profiles with a compendium of genome-wide genetic interaction profiles, we predicted compound functionality. Applying this high-throughput approach, we screened seven different compound libraries and annotated their functional diversity. We further validated biological process predictions, prioritized a diverse set of compounds, and identified compounds that appear to have dual modes of action.

[The history of development of evolutionary methods in St. Petersburg school of computer simulation in biology].

PubMed

Menshutkin, V V; Kazanskiĭ, A B; Levchenko, V F

2010-01-01

The history of rise and development of evolutionary methods in Saint Petersburg school of biological modelling is traced and analyzed. Some pioneering works in simulation of ecological and evolutionary processes, performed in St.-Petersburg school became an exemplary ones for many followers in Russia and abroad. The individual-based approach became the crucial point in the history of the school as an adequate instrument for construction of models of biological evolution. This approach is natural for simulation of the evolution of life-history parameters and adaptive processes in populations and communities. In some cases simulated evolutionary process was used for solving a reverse problem, i. e., for estimation of uncertain life-history parameters of population. Evolutionary computations is one more aspect of this approach application in great many fields. The problems and vistas of ecological and evolutionary modelling in general are discussed.

Rethinking Physics for Biologists: A design-based research approach

NASA Astrophysics Data System (ADS)

Sawtelle, Vashti

2015-03-01

Biology majors at the University of Maryland are required to take courses in biology, chemistry, and physics - but they often see these courses as disconnected. Over the past three years the NEXUS/Physics course has been working to develop an interdisciplinary learning environment that bridges the disciplinary domains of biology and physics. Across the three years we have gone from teaching in a small class with one instructor to teaching in a large lecture hall with multiple instructors. We have used a design-based research approach to support critical reflection of the course at multiple-time scales. In this presentation I will detail our process of collecting systematic data, listening to and valuing students' reasoning, and bridging diverse perspectives led. I will demonstrate how this process led to improved curricular design, refined assessment objectives, and new design heuristics. This work is supported by NSF-TUES DUE 11-22818, the HHMI NEXUS grant, and a NSF Graduate Research Fellowship (DGE 0750616).

COMPUTER-AIDED DRUG DISCOVERY AND DEVELOPMENT (CADDD): in silico-chemico-biological approach

PubMed Central

Kapetanovic, I.M.

2008-01-01

It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3-D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve. PMID:17229415

Fast gene ontology based clustering for microarray experiments.

PubMed

Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

2008-11-21

Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

The assessment of the coke wastewater treatment efficacy in rotating biological contractor.

PubMed

Cema, G; Żabczyński, S; Ziembińska-Buczyńska, A

2016-01-01

Coke wastewater is known to be relatively difficult for biological treatment. Nonetheless, biofilm-based systems seem to be promising tool for such treatment. That is why a rotating biological contactor (RBC) system focused on the Anammox process was used in this study. The experiment was divided into two parts with synthetic and then real wastewater. It was proven that it is possible to treat coke wastewater with RBC but such a procedure requires a very long start-up period for the nitritation (190 days), as well as for the Anammox process, where stable nitrogen removal over 70% was achieved after 400 days of experiment. Interestingly, it was possible at a relatively low (20.2 ± 2.2 °C) temperature. The polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) based monitoring of the bacterial community showed that its biodiversity decreased when the real wastewater was treated and it was composed mainly of GC-rich genotypes, probably because of the modeling influence of this wastewater and the genotypes specialization.

Use of maize wastewater for the cultivation of the Pleurotus spp. mushroom and optimization of its biological efficiency.

PubMed

Loss, Edenes; Royer, Andrea Rafaela; Barreto-Rodrigues, Marcio; Barana, Ana Claudia

2009-07-30

This study evaluated the Pleurotus spp. mushroom production process using an effluent from the maize agroindustrial process as a carbon and nitrogen source and as a wetting agent. A complete experimental design based on factorial planning was used to optimize the biological efficiency and evaluate the effect of the concentration of effluent, pH and species of Pleurotus. The results indicated that the effluent affects the biological efficiency for the production of both species of mushrooms at all pH values studied. The maximum biological efficiency predicted by the model (81.36%) corresponded to the point defined by the effluent contents (X(1)=1), pH (X(2)=-1) and fungus species (X(3)=1), specifically 50%, 5.0 and P. floridae, respectively. The results demonstrated that the effluent is a good alternative for the production of Pleurotus mushrooms.

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.

An improved swarm optimization for parameter estimation and biological model selection.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo

PubMed Central

Golightly, Andrew; Wilkinson, Darren J.

2011-01-01

Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a Lotka–Volterra system and a prokaryotic auto-regulatory network. PMID:23226583

The fairytale of the GSSG/GSH redox potential.

PubMed

Flohé, Leopold

2013-05-01

The term GSSG/GSH redox potential is frequently used to explain redox regulation and other biological processes. The relevance of the GSSG/GSH redox potential as driving force of biological processes is critically discussed. It is recalled that the concentration ratio of GSSG and GSH reflects little else than a steady state, which overwhelmingly results from fast enzymatic processes utilizing, degrading or regenerating GSH. A biological GSSG/GSH redox potential, as calculated by the Nernst equation, is a deduced electrochemical parameter based on direct measurements of GSH and GSSG that are often complicated by poorly substantiated assumptions. It is considered irrelevant to the steering of any biological process. GSH-utilizing enzymes depend on the concentration of GSH, not on [GSH](2), as is predicted by the Nernst equation, and are typically not affected by GSSG. Regulatory processes involving oxidants and GSH are considered to make use of mechanistic principles known for thiol peroxidases which catalyze the oxidation of hydroperoxides by GSH by means of an enzyme substitution mechanism involving only bimolecular reaction steps. The negligibly small rate constants of related spontaneous reactions as compared with enzyme-catalyzed ones underscore the superiority of kinetic parameters over electrochemical or thermodynamic ones for an in-depth understanding of GSH-dependent biological phenomena. At best, the GSSG/GSH potential might be useful as an analytical tool to disclose disturbances in redox metabolism. This article is part of a Special Issue entitled Cellular Functions of Glutathione. Copyright © 2012 Elsevier B.V. All rights reserved.

Science for Survival: The Modern Synthesis of Evolution and the Biological Sciences Curriculum Study

ERIC Educational Resources Information Center

Green, Lisa Anne

2012-01-01

In this historical dissertation, I examined the process of curriculum development in the Biological Sciences Curriculum Study (BSCS) in the United States during the period 1959-1963. The presentation of evolution in the high school texts was based on a more robust form of Darwinian evolution which developed during the 1930s and 1940s called…

Introducing Experimental Design by Evaluating Efficacy of Herbal Remedies (Do Herbal Remedies Really Work?)

ERIC Educational Resources Information Center

Smith, Robert A.; Pontiggia, Laura; Waterman, Carrie; Lichtenwalner, Meghan

2010-01-01

This paper is based upon experiments developed as part of a Directed Research course designed to provide undergraduate biology students experience in the principles and processes of the scientific method used in biological research. The project involved the evaluation of herbal remedies used in many parts of the world in the treatment of diseases…

A fluorogenic molecular nanoprobe with an engineered internal environment for sensitive and selective detection of biological hydrogen sulfide.

PubMed

Kim, Myung; Seo, Young Hun; Kim, Youngsun; Heo, Jeongyun; Jang, Woo-Dong; Sim, Sang Jun; Kim, Sehoon

2017-02-14

A nanoreactor approach based on the amphiphilic assembly of various molecules offers a chance to finely engineer the internal reaction medium to enable highly selective and sensitive detection of H 2 S in biological media, being useful for microscopic imaging of cellular processes and in vitro diagnostics with blood samples.

Stem cells: The Next Therapeutic Frontier

PubMed Central

Humes, H. David

2005-01-01

Cell therapy is one of the most exciting fields in translational medicine. It stands at the intersection of a variety of rapidly developing scientific disciplines: stem cell biology, immunology, tissue engineering, molecular biology, biomaterials, transplantation biology, regenerative medicine, and clinical research. Cell-based therapy may develop into a new therapeutic platform to treat a vast array of clinical disorders. Blood transfusions and bone marrow transplantation are prime examples of the successful application of cell-based therapeutics; but recent advances in cellular and molecular biology have expanded the potential applications of this approach. Although recombinant genetic engineering to produce a variety of therapeutics such as human erythropoietin and insulin has proven successful, these treatments are unable to completely correct or reverse disease states, because most common disease processes are not due to the deficiency of a single protein but develop due to alterations in the complex interactions of a variety of cell components. In these complex situations, cell-based therapy may be a more successful strategy by providing a dynamic, interactive, and individualized therapeutic approach that responds to the pathophysiological condition of the patient. In this regard, cells may provide innovative methods for drug delivery of biologics, immunotherapy, and tissue regenerative or replacement engineering (1,2). The translation of this discipline to medical practice has tremendous potential, but in many applications technological issues need to be overcome. Since many cell-based indications are already being evaluated in the clinic, the field appears to be on the threshold of a number of successes. This review will focus on our group's use of human stem/progenitor cells in the treatment of acute and chronic renal failure as extensions to the current successful renal substitution processes of hemodialysis and hemofiltration. PMID:16555613

Extracting physics of life at the molecular level: A review of single-molecule data analyses.

PubMed

Colomb, Warren; Sarkar, Susanta K

2015-06-01

Studying individual biomolecules at the single-molecule level has proved very insightful recently. Single-molecule experiments allow us to probe both the equilibrium and nonequilibrium properties as well as make quantitative connections with ensemble experiments and equilibrium thermodynamics. However, it is important to be careful about the analysis of single-molecule data because of the noise present and the lack of theoretical framework for processes far away from equilibrium. Biomolecular motion, whether it is free in solution, on a substrate, or under force, involves thermal fluctuations in varying degrees, which makes the motion noisy. In addition, the noise from the experimental setup makes it even more complex. The details of biologically relevant interactions, conformational dynamics, and activities are hidden in the noisy single-molecule data. As such, extracting biological insights from noisy data is still an active area of research. In this review, we will focus on analyzing both fluorescence-based and force-based single-molecule experiments and gaining biological insights at the single-molecule level. Inherently nonequilibrium nature of biological processes will be highlighted. Simulated trajectories of biomolecular diffusion will be used to compare and validate various analysis techniques. Copyright © 2015 Elsevier B.V. All rights reserved.

Identifying cooperative transcriptional regulations using protein–protein interactions

PubMed Central

Nagamine, Nobuyoshi; Kawada, Yuji; Sakakibara, Yasubumi

2005-01-01

Cooperative transcriptional activations among multiple transcription factors (TFs) are important to understand the mechanisms of complex transcriptional regulations in eukaryotes. Previous studies have attempted to find cooperative TFs based on gene expression data with gene expression profiles as a measure of similarity of gene regulations. In this paper, we use protein–protein interaction data to infer synergistic binding of cooperative TFs. Our fundamental idea is based on the assumption that genes contributing to a similar biological process are regulated under the same control mechanism. First, the protein–protein interaction networks are used to calculate the similarity of biological processes among genes. Second, we integrate this similarity and the chromatin immuno-precipitation data to identify cooperative TFs. Our computational experiments in yeast show that predictions made by our method have successfully identified eight pairs of cooperative TFs that have literature evidences but could not be identified by the previous method. Further, 12 new possible pairs have been inferred and we have examined the biological relevances for them. However, since a typical problem using protein–protein interaction data is that many false-positive data are contained, we propose a method combining various biological data to increase the prediction accuracy. PMID:16126847

Bioremediation of trace organic compounds found in precious metals refineries' wastewaters: a review of potential options.

PubMed

Barbosa, V L; Tandlich, R; Burgess, J E

2007-07-01

Platinum group metal (PGM) refining processes produce large quantities of wastewater, which is contaminated with the compounds that make up the solvents/extractants mixtures used in the process. These compounds often include solvesso, beta-hydroxyxime, amines, amides and methyl isobutyl ketone. A process to clean up PGM refinery wastewaters so that they could be re-used in the refining process would greatly contribute to continual water storage problems and to cost reduction for the industry. Based on the concept that organic compounds that are produced biologically can be destroyed biologically, the use of biological processes for the treatment of organic compounds in other types of waste stream has been favoured in recent years, owing to their low cost and environmental acceptability. This review examines the available biotechnologies and their effectiveness for treating compounds likely to be contained in precious metal extraction process wastewaters. The processes examined include: biofilters, fluidized bed reactors, trickle-bed bioreactors, bioscrubbers, two-phase partitioning bioreactors, membrane bioreactors and activated sludge. Although all processes examined showed adequate to excellent removal of organic compounds from various gaseous and fewer liquid waste streams, there was a variation in their effectiveness. Variations in performance of laboratory-scale biological processes are probably due to the inherent change in the microbial population composition due to selection pressure, environmental conditions and the time allowed for adaptation to the organic compounds. However, if these factors are disregarded, it can be established that activated sludge and membrane bioreactors are the most promising processes for use in the treatment of PGM refinery wastewaters.

Fecal indicator organism modeling and microbial source tracking in environmental waters: Chapter 3.4.6

USGS Publications Warehouse

Nevers, Meredith; Byappanahalli, Muruleedhara; Phanikumar, Mantha S.; Whitman, Richard L.

2016-01-01

Mathematical models have been widely applied to surface waters to estimate rates of settling, resuspension, flow, dispersion, and advection in order to calculate movement of particles that influence water quality. Of particular interest are the movement, survival, and persistence of microbial pathogens or their surrogates, which may contaminate recreational water, drinking water, or shellfish. Most models devoted to microbial water quality have been focused on fecal indicator organisms (FIO), which act as a surrogate for pathogens and viruses. Process-based modeling and statistical modeling have been used to track contamination events to source and to predict future events. The use of these two types of models require different levels of expertise and input; process-based models rely on theoretical physical constructs to explain present conditions and biological distribution while data-based, statistical models use extant paired data to do the same. The selection of the appropriate model and interpretation of results is critical to proper use of these tools in microbial source tracking. Integration of the modeling approaches could provide insight for tracking and predicting contamination events in real time. A review of modeling efforts reveals that process-based modeling has great promise for microbial source tracking efforts; further, combining the understanding of physical processes influencing FIO contamination developed with process-based models and molecular characterization of the population by gene-based (i.e., biological) or chemical markers may be an effective approach for locating sources and remediating contamination in order to protect human health better.

Developmental engineering: a new paradigm for the design and manufacturing of cell-based products. Part I: from three-dimensional cell growth to biomimetics of in vivo development.

PubMed

Lenas, Petros; Moos, Malcolm; Luyten, Frank P

2009-12-01

Recent advances in developmental biology, systems biology, and network science are converging to poise the heretofore largely empirical field of tissue engineering on the brink of a metamorphosis into a rigorous discipline based on universally accepted engineering principles of quality by design. Failure of more simplistic approaches to the manufacture of cell-based therapies has led to increasing appreciation of the need to imitate, at least to some degree, natural mechanisms that control cell fate and differentiation. The identification of many of these mechanisms, which in general are based on cell signaling pathways, is an important step in this direction. Some well-accepted empirical concepts of developmental biology, such as path-dependence, robustness, modularity, and semiautonomy of intermediate tissue forms, that appear sequentially during tissue development are starting to be incorporated in process design.

A monolithic glass chip for active single-cell sorting based on mechanical phenotyping.

PubMed

Faigle, Christoph; Lautenschläger, Franziska; Whyte, Graeme; Homewood, Philip; Martín-Badosa, Estela; Guck, Jochen

2015-03-07

The mechanical properties of biological cells have long been considered as inherent markers of biological function and disease. However, the screening and active sorting of heterogeneous populations based on serial single-cell mechanical measurements has not been demonstrated. Here we present a novel monolithic glass chip for combined fluorescence detection and mechanical phenotyping using an optical stretcher. A new design and manufacturing process, involving the bonding of two asymmetrically etched glass plates, combines exact optical fiber alignment, low laser damage threshold and high imaging quality with the possibility of several microfluidic inlet and outlet channels. We show the utility of such a custom-built optical stretcher glass chip by measuring and sorting single cells in a heterogeneous population based on their different mechanical properties and verify sorting accuracy by simultaneous fluorescence detection. This offers new possibilities of exact characterization and sorting of small populations based on rheological properties for biological and biomedical applications.

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES

PubMed Central

Somogyi, Endre; Glazier, James A.

2017-01-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment. PMID:29303160

Agricultural and Food Processing Applications of Pulsed Power and Plasma Technologies

NASA Astrophysics Data System (ADS)

Takaki, Koichi

Agricultural and food processing applications of pulsed power and plasma technologies are described in this paper. Repetitively operated compact pulsed power generators with a moderate peak power are developed for the agricultural and the food processing applications. These applications are mainly based on biological effects and can be categorized as germination control of plants such as Basidiomycota and arabidopsis inactivation of bacteria in soil and liquid medium of hydroponics; extraction of juice from fruits and vegetables; decontamination of air and liquid, etc. Types of pulsed power that have biological effects are caused with gas discharges, water discharges, and electromagnetic fields. The discharges yield free radicals, UV radiation, intense electric field, and shock waves. Biologically based applications of pulsed power and plasma are performed by selecting the type that gives the target objects the adequate result from among these agents or byproducts. For instance, intense electric fields form pores on the cell membrane, which is called electroporation, or influence the nuclei. This paper mainly describes the application of the pulsed power for the germination control of Basidiomycota i.e. mushroom, inactivation of fungi in the soil and the liquid medium in hydroponics, and extraction of polyphenol from skins of grape.

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES.

PubMed

Somogyi, Endre; Glazier, James A

2017-04-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.

Memory and learning behaviors mimicked in nanogranular SiO2-based proton conductor gated oxide-based synaptic transistors

NASA Astrophysics Data System (ADS)

Wan, Chang Jin; Zhu, Li Qiang; Zhou, Ju Mei; Shi, Yi; Wan, Qing

2013-10-01

In neuroscience, signal processing, memory and learning function are established in the brain by modifying ionic fluxes in neurons and synapses. Emulation of memory and learning behaviors of biological systems by nanoscale ionic/electronic devices is highly desirable for building neuromorphic systems or even artificial neural networks. Here, novel artificial synapses based on junctionless oxide-based protonic/electronic hybrid transistors gated by nanogranular phosphorus-doped SiO2-based proton-conducting films are fabricated on glass substrates by a room-temperature process. Short-term memory (STM) and long-term memory (LTM) are mimicked by tuning the pulse gate voltage amplitude. The LTM process in such an artificial synapse is due to the proton-related interfacial electrochemical reaction. Our results are highly desirable for building future neuromorphic systems or even artificial networks via electronic elements.In neuroscience, signal processing, memory and learning function are established in the brain by modifying ionic fluxes in neurons and synapses. Emulation of memory and learning behaviors of biological systems by nanoscale ionic/electronic devices is highly desirable for building neuromorphic systems or even artificial neural networks. Here, novel artificial synapses based on junctionless oxide-based protonic/electronic hybrid transistors gated by nanogranular phosphorus-doped SiO2-based proton-conducting films are fabricated on glass substrates by a room-temperature process. Short-term memory (STM) and long-term memory (LTM) are mimicked by tuning the pulse gate voltage amplitude. The LTM process in such an artificial synapse is due to the proton-related interfacial electrochemical reaction. Our results are highly desirable for building future neuromorphic systems or even artificial networks via electronic elements. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr02987e

Neural systems for preparatory control of imitation.

PubMed

Cross, Katy A; Iacoboni, Marco

2014-01-01

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

An analysis of the Petri net based model of the human body iron homeostasis process.

PubMed

Sackmann, Andrea; Formanowicz, Dorota; Formanowicz, Piotr; Koch, Ina; Blazewicz, Jacek

2007-02-01

In the paper a Petri net based model of the human body iron homeostasis is presented and analyzed. The body iron homeostasis is an important but not fully understood complex process. The modeling of the process presented in the paper is expressed in the language of Petri net theory. An application of this theory to the description of biological processes allows for very precise analysis of the resulting models. Here, such an analysis of the body iron homeostasis model from a mathematical point of view is given.

[Near infrared spectroscopy based process trajectory technology and its application in monitoring and controlling of traditional Chinese medicine manufacturing process].

PubMed

Li, Wen-Long; Qu, Hai-Bin

2016-10-01

In this paper, the principle of NIRS (near infrared spectroscopy)-based process trajectory technology was introduced.The main steps of the technique include:① in-line collection of the processes spectra of different technics; ② unfolding of the 3-D process spectra;③ determination of the process trajectories and their normal limits;④ monitoring of the new batches with the established MSPC (multivariate statistical process control) models.Applications of the technology in the chemical and biological medicines were reviewed briefly. By a comprehensive introduction of our feasibility research on the monitoring of traditional Chinese medicine technical process using NIRS-based multivariate process trajectories, several important problems of the practical applications which need urgent solutions are proposed, and also the application prospect of the NIRS-based process trajectory technology is fully discussed and put forward in the end. Copyright© by the Chinese Pharmaceutical Association.

Research on moving object detection based on frog's eyes

NASA Astrophysics Data System (ADS)

Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

2008-12-01

On the basis of object's information processing mechanism with frog's eyes, this paper discussed a bionic detection technology which suitable for object's information processing based on frog's vision. First, the bionics detection theory by imitating frog vision is established, it is an parallel processing mechanism which including pick-up and pretreatment of object's information, parallel separating of digital image, parallel processing, and information synthesis. The computer vision detection system is described to detect moving objects which has special color, special shape, the experiment indicates that it can scheme out the detecting result in the certain interfered background can be detected. A moving objects detection electro-model by imitating biologic vision based on frog's eyes is established, the video simulative signal is digital firstly in this system, then the digital signal is parallel separated by FPGA. IN the parallel processing, the video information can be caught, processed and displayed in the same time, the information fusion is taken by DSP HPI ports, in order to transmit the data which processed by DSP. This system can watch the bigger visual field and get higher image resolution than ordinary monitor systems. In summary, simulative experiments for edge detection of moving object with canny algorithm based on this system indicate that this system can detect the edge of moving objects in real time, the feasibility of bionic model was fully demonstrated in the engineering system, and it laid a solid foundation for the future study of detection technology by imitating biologic vision.

Understanding the sorption and biotransformation of organic micropollutants in innovative biological wastewater treatment technologies.

PubMed

Alvarino, T; Suarez, S; Lema, J; Omil, F

2018-02-15

New technologies for wastewater treatment have been developed in the last years based on the combination of biological reactors operating under different redox conditions. Their efficiency in the removal of organic micropollutants (OMPs) has not been clearly assessed yet. This review paper is focussed on understanding the sorption and biotransformation of a selected group of 17 OMPs, including pharmaceuticals, hormones and personal care products, during biological wastewater treatment processes. Apart from considering the role of "classical" operational parameters, new factors such as biomass conformation and particle size, upward velocity applied or the addition of adsorbents have been considered. It has been found that the OMP removal by sorption not only depends on their physico-chemical characteristics and other parameters, such as the biomass conformation and particle size, or some operational conditions also relevant. Membrane biological reactors (MBR), have shown to enhance sorption and biotransformation of some OMPs. The same applies to technologies bases on direct addition of activated carbon in bioreactors. The OMP biotransformation degree and pathway is mainly driven by the redox potential and the primary substrate activity. The combination of different redox potentials in hybrid reactor systems can significantly enhance the overall OMP removal efficiency. Sorption and biotransformation can be synergistically promoted in biological reactors by the addition of activated carbon. The deeper knowledge of the main parameters influencing OMP removal provided by this review will allow optimizing the biological processes in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Synaptic plasticity and memory functions achieved in a WO3-x-based nanoionics device by using the principle of atomic switch operation

NASA Astrophysics Data System (ADS)

Yang, Rui; Terabe, Kazuya; Yao, Yiping; Tsuruoka, Tohru; Hasegawa, Tsuyoshi; Gimzewski, James K.; Aono, Masakazu

2013-09-01

A compact neuromorphic nanodevice with inherent learning and memory properties emulating those of biological synapses is the key to developing artificial neural networks rivaling their biological counterparts. Experimental results showed that memorization with a wide time scale from volatile to permanent can be achieved in a WO3-x-based nanoionics device and can be precisely and cumulatively controlled by adjusting the device’s resistance state and input pulse parameters such as the amplitude, interval, and number. This control is analogous to biological synaptic plasticity including short-term plasticity, long-term potentiation, transition from short-term memory to long-term memory, forgetting processes for short- and long-term memory, learning speed, and learning history. A compact WO3-x-based nanoionics device with a simple stacked layer structure should thus be a promising candidate for use as an inorganic synapse in artificial neural networks due to its striking resemblance to the biological synapse.

Promoting a structural view of biology for varied audiences: an overview of RCSB PDB resources and experiences

PubMed Central

Dutta, Shuchismita; Zardecki, Christine; Goodsell, David S.; Berman, Helen M.

2010-01-01

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) supports scientific research and education worldwide by providing an essential resource of information on biomolecular structures. In addition to serving as a deposition, data-processing and distribution center for PDB data, the RCSB PDB offers resources and online materials that different audiences can use to customize their structural biology instruction. These include resources for general audiences that present macromolecular structure in the context of a biological theme, method-based materials for researchers who take a more traditional approach to the presentation of structural science, and materials that mix theme-based and method-based approaches for educators and students. Through these efforts the RCSB PDB aims to enable optimal use of structural data by researchers, educators and students designing and understanding experiments in biology, chemistry and medicine, and by general users making informed decisions about their life and health. PMID:20877496

College Students' Understanding of the Carbon Cycle: Contrasting Principle-Based and Informal Reasoning

ERIC Educational Resources Information Center

Hartley, Laurel M.; Wilke, Brook J.; Schramm, Jonathon W.; D'Avanzo, Charlene; Anderson, Charles W.

2011-01-01

Processes that transform carbon (e.g., photosynthesis) play a prominent role in college biology courses. Our goals were to learn about student reasoning related to these processes and provide faculty with tools for instruction and assessment. We created a framework illustrating how carbon-transforming processes can be related to one another during…

Agent Based Modeling Applications for Geosciences

NASA Astrophysics Data System (ADS)

Stein, J. S.

2004-12-01

Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in a thermodynamic framework as a set of reactions that roll-up the integrated effect that diverse biological communities exert on a geological system. This approach may work well to predict the effect of certain biological communities in specific environments in which experimental data is available. However, it does not further our knowledge of how the geobiological system actually functions on a micro scale. Agent-based techniques may provide a framework to explore the fundamental interactions required to explain the system-wide behavior. This presentation will present a survey of several promising applications of agent-based modeling approaches to problems in the geosciences and describe specific contributions to some of the inherent challenges facing this approach.

SNAD: Sequence Name Annotation-based Designer.

PubMed

Sidorov, Igor A; Reshetov, Denis A; Gorbalenya, Alexander E

2009-08-14

A growing diversity of biological data is tagged with unique identifiers (UIDs) associated with polynucleotides and proteins to ensure efficient computer-mediated data storage, maintenance, and processing. These identifiers, which are not informative for most people, are often substituted by biologically meaningful names in various presentations to facilitate utilization and dissemination of sequence-based knowledge. This substitution is commonly done manually that may be a tedious exercise prone to mistakes and omissions. Here we introduce SNAD (Sequence Name Annotation-based Designer) that mediates automatic conversion of sequence UIDs (associated with multiple alignment or phylogenetic tree, or supplied as plain text list) into biologically meaningful names and acronyms. This conversion is directed by precompiled or user-defined templates that exploit wealth of annotation available in cognate entries of external databases. Using examples, we demonstrate how this tool can be used to generate names for practical purposes, particularly in virology. A tool for controllable annotation-based conversion of sequence UIDs into biologically meaningful names and acronyms has been developed and placed into service, fostering links between quality of sequence annotation, and efficiency of communication and knowledge dissemination among researchers.

Design of virtual simulation experiment based on key events

NASA Astrophysics Data System (ADS)

Zhong, Zheng; Zhou, Dongbo; Song, Lingxiu

2018-06-01

Considering complex content and lacking of guidance in virtual simulation experiments, the key event technology in VR narrative theory was introduced for virtual simulation experiment to enhance fidelity and vividness process. Based on the VR narrative technology, an event transition structure was designed to meet the need of experimental operation process, and an interactive event processing model was used to generate key events in interactive scene. The experiment of" margin value of bees foraging" based on Biologic morphology was taken as an example, many objects, behaviors and other contents were reorganized. The result shows that this method can enhance the user's experience and ensure experimental process complete and effectively.

Investigation of In-situ Biogeochemical Reduction of Chlorinated Solvents in Groundwater by Reduced Iron Minerals

EPA Science Inventory

Biogeochemical transformation is a process in which chlorinated solvents are degraded abiotically by reactive minerals formed by, at least in part or indirectly from, anaerobic biological processes. Five mulch biowall and/or vegetable oil-based bioremediation applications for tr...

Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

PubMed

Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

2012-08-29

Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2) and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different) biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be translated in a set of ordinary differential equations on probability distributions. We developed a C++ software, MaBoSS, that is able to simulate such a system by applying Kinetic Monte-Carlo (or Gillespie algorithm) on the Boolean state space. This software, parallelized and optimized, computes the temporal evolution of probability distributions and estimates stationary distributions. Applications of the Boolean Kinetic Monte-Carlo are demonstrated for three qualitative models: a toy model, a published model of p53/Mdm2 interaction and a published model of the mammalian cell cycle. Our approach allows to describe kinetic phenomena which were difficult to handle in the original models. In particular, transient effects are represented by time dependent probability distributions, interpretable in terms of cell populations.

Extracting microRNA-gene relations from biomedical literature using distant supervision

PubMed Central

Clarke, Luka A.; Couto, Francisco M.

2017-01-01

Many biomedical relation extraction approaches are based on supervised machine learning, requiring an annotated corpus. Distant supervision aims at training a classifier by combining a knowledge base with a corpus, reducing the amount of manual effort necessary. This is particularly useful for biomedicine because many databases and ontologies have been made available for many biological processes, while the availability of annotated corpora is still limited. We studied the extraction of microRNA-gene relations from text. MicroRNA regulation is an important biological process due to its close association with human diseases. The proposed method, IBRel, is based on distantly supervised multi-instance learning. We evaluated IBRel on three datasets, and the results were compared with a co-occurrence approach as well as a supervised machine learning algorithm. While supervised learning outperformed on two of those datasets, IBRel obtained an F-score 28.3 percentage points higher on the dataset for which there was no training set developed specifically. To demonstrate the applicability of IBRel, we used it to extract 27 miRNA-gene relations from recently published papers about cystic fibrosis. Our results demonstrate that our method can be successfully used to extract relations from literature about a biological process without an annotated corpus. The source code and data used in this study are available at https://github.com/AndreLamurias/IBRel. PMID:28263989

Extracting microRNA-gene relations from biomedical literature using distant supervision.

PubMed

Lamurias, Andre; Clarke, Luka A; Couto, Francisco M

2017-01-01

Many biomedical relation extraction approaches are based on supervised machine learning, requiring an annotated corpus. Distant supervision aims at training a classifier by combining a knowledge base with a corpus, reducing the amount of manual effort necessary. This is particularly useful for biomedicine because many databases and ontologies have been made available for many biological processes, while the availability of annotated corpora is still limited. We studied the extraction of microRNA-gene relations from text. MicroRNA regulation is an important biological process due to its close association with human diseases. The proposed method, IBRel, is based on distantly supervised multi-instance learning. We evaluated IBRel on three datasets, and the results were compared with a co-occurrence approach as well as a supervised machine learning algorithm. While supervised learning outperformed on two of those datasets, IBRel obtained an F-score 28.3 percentage points higher on the dataset for which there was no training set developed specifically. To demonstrate the applicability of IBRel, we used it to extract 27 miRNA-gene relations from recently published papers about cystic fibrosis. Our results demonstrate that our method can be successfully used to extract relations from literature about a biological process without an annotated corpus. The source code and data used in this study are available at https://github.com/AndreLamurias/IBRel.

Colloquium: Modeling the dynamics of multicellular systems: Application to tissue engineering

NASA Astrophysics Data System (ADS)

Kosztin, Ioan; Vunjak-Novakovic, Gordana; Forgacs, Gabor

2012-10-01

Tissue engineering is a rapidly evolving discipline that aims at building functional tissues to improve or replace damaged ones. To be successful in such an endeavor, ideally, the engineering of tissues should be based on the principles of developmental biology. Recent progress in developmental biology suggests that the formation of tissues from the composing cells is often guided by physical laws. Here a comprehensive computational-theoretical formalism is presented that is based on experimental input and incorporates biomechanical principles of developmental biology. The formalism is described and it is shown that it correctly reproduces and predicts the quantitative characteristics of the fundamental early developmental process of tissue fusion. Based on this finding, the formalism is then used toward the optimization of the fabrication of tubular multicellular constructs, such as a vascular graft, by bioprinting, a novel tissue engineering technology.

Future directions in inflammatory bowel disease management.

PubMed

D'Haens, Geert R; Sartor, R Balfour; Silverberg, Mark S; Petersson, Joel; Rutgeerts, Paul

2014-08-01

Clinical management of inflammatory bowel diseases (IBD), new treatment modalities and the potential impact of personalised medicine remain topics of intense interest as our understanding of the pathophysiology of IBD expands. Potential future strategies for IBD management are discussed, based on recent preclinical and clinical research. A top-down approach to medical therapy is increasingly being adopted for patients with risk factors for severe inflammation or an unfavourable disease course in an attempt to halt the inflammatory process as early as possible, prevent complications and induce mucosal healing. In the future, biological therapies for IBD are likely to be used more selectively based on personalised benefit/risk assessment, determined through reliable biomarkers and tissue signatures, and will probably be optimised throughout the course of treatment. Biologics with different mechanisms of action will be available; when one drug fails, patients will be able to switch to another and even combination biologics may become a reality. The role of biotherapeutic products that are similar to currently licensed biologics in terms of quality, safety and efficacy - i.e. biosimilars - is at an early stage and requires further experience. Other therapeutic strategies may involve manipulation of the microbiome using antibiotics, probiotics, prebiotics, diet and combinations of all these approaches. Faecal microbiota transplantation is also a potential option in IBD although controlled data are lacking. The future of classifying, prognosticating and managing IBD involves an outcomes-based approach to identify biomarkers reflecting various biological processes that can be matched with clinically important endpoints. Copyright © 2014 European Crohn's and Colitis Organisation. Published by Elsevier B.V. All rights reserved.

A system to evaluate the scientific quality of biological and restoration objectives using National Wildlife Refuge Comprehensive Conservation Plans as a case study

USGS Publications Warehouse

Schroeder, R.L.

2006-01-01

It is widely accepted that plans for restoration projects should contain specific, measurable, and science-based objectives to guide restoration efforts. The United States Fish and Wildlife Service (USFWS) is in the process of developing Comprehensive Conservation Plans (CCPs) for more than 500 units in the National Wildlife Refuge System (NWRS). These plans contain objectives for biological and ecosystem restoration efforts on the refuges. Based on USFWS policy, a system was developed to evaluate the scientific quality of such objectives based on three critical factors: (1) Is the objective specific, measurable, achievable, results-oriented, and time-fixed? (2) What is the extent of the rationale that explains the assumptions, logic, and reasoning for the objective? (3) How well was available science used in the development of the objective? The evaluation system scores each factor on a scale of 1 (poor) to 4 (excellent) according to detailed criteria. The biological and restoration objectives from CCPs published as of September 2004 (60 total) were evaluated. The overall average score for all biological and restoration objectives was 1.73. Average scores for each factor were: Factor 1-1.97; Factor 2-1.86; Factor 3-1.38. The overall scores increased from 1997 to 2004. Future restoration efforts may benefit by using this evaluation system during the process of plan development, to ensure that biological and restoration objectives are of the highest scientific quality possible prior to the implementation of restoration plans, and to allow for improved monitoring and adaptive management.

A Range Finding Protocol to Support Design for Transcriptomics Experimentation: Examples of In-Vitro and In-Vivo Murine UV Exposure

PubMed Central

van Oostrom, Conny T.; Jonker, Martijs J.; de Jong, Mark; Dekker, Rob J.; Rauwerda, Han; Ensink, Wim A.; de Vries, Annemieke; Breit, Timo M.

2014-01-01

In transcriptomics research, design for experimentation by carefully considering biological, technological, practical and statistical aspects is very important, because the experimental design space is essentially limitless. Usually, the ranges of variable biological parameters of the design space are based on common practices and in turn on phenotypic endpoints. However, specific sub-cellular processes might only be partially reflected by phenotypic endpoints or outside the associated parameter range. Here, we provide a generic protocol for range finding in design for transcriptomics experimentation based on small-scale gene-expression experiments to help in the search for the right location in the design space by analyzing the activity of already known genes of relevant molecular mechanisms. Two examples illustrate the applicability: in-vitro UV-C exposure of mouse embryonic fibroblasts and in-vivo UV-B exposure of mouse skin. Our pragmatic approach is based on: framing a specific biological question and associated gene-set, performing a wide-ranged experiment without replication, eliminating potentially non-relevant genes, and determining the experimental ‘sweet spot’ by gene-set enrichment plus dose-response correlation analysis. Examination of many cellular processes that are related to UV response, such as DNA repair and cell-cycle arrest, revealed that basically each cellular (sub-) process is active at its own specific spot(s) in the experimental design space. Hence, the use of range finding, based on an affordable protocol like this, enables researchers to conveniently identify the ‘sweet spot’ for their cellular process of interest in an experimental design space and might have far-reaching implications for experimental standardization. PMID:24823911

Agent-Based Phytoplankton Models of Cellular and Population Processes: Fostering Individual-Based Learning in Undergraduate Research

NASA Astrophysics Data System (ADS)

Berges, J. A.; Raphael, T.; Rafa Todd, C. S.; Bate, T. C.; Hellweger, F. L.

2016-02-01

Engaging undergraduate students in research projects that require expertise in multiple disciplines (e.g. cell biology, population ecology, and mathematical modeling) can be challenging because they have often not developed the expertise that allows them to participate at a satisfying level. Use of agent-based modeling can allow exploration of concepts at more intuitive levels, and encourage experimentation that emphasizes processes over computational skills. Over the past several years, we have involved undergraduate students in projects examining both ecological and cell biological aspects of aquatic microbial biology, using the freely-downloadable, agent-based modeling environment NetLogo (https://ccl.northwestern.edu/netlogo/). In Netlogo, actions of large numbers of individuals can be simulated, leading to complex systems with emergent behavior. The interface features appealing graphics, monitors, and control structures. In one example, a group of sophomores in a BioMathematics program developed an agent-based model of phytoplankton population dynamics in a pond ecosystem, motivated by observed macroscopic changes in cell numbers (due to growth and death), and driven by responses to irradiance, temperature and a limiting nutrient. In a second example, junior and senior undergraduates conducting Independent Studies created a model of the intracellular processes governing stress and cell death for individual phytoplankton cells (based on parameters derived from experiments using single-cell culturing and flow cytometry), and then this model was embedded in the agents in the pond ecosystem model. In our experience, students with a range of mathematical abilities learned to code quickly and could use the software with varying degrees of sophistication, for example, creation of spatially-explicit two and three-dimensional models. Skills developed quickly and transferred readily to other platforms (e.g. Matlab).

Structure-Based Design of Highly Selective Inhibitors of the CREB Binding Protein Bromodomain.

PubMed

Denny, R Aldrin; Flick, Andrew C; Coe, Jotham; Langille, Jonathan; Basak, Arindrajit; Liu, Shenping; Stock, Ingrid; Sahasrabudhe, Parag; Bonin, Paul; Hay, Duncan A; Brennan, Paul E; Pletcher, Mathew; Jones, Lyn H; Chekler, Eugene L Piatnitski

2017-07-13

Chemical probes are required for preclinical target validation to interrogate novel biological targets and pathways. Selective inhibitors of the CREB binding protein (CREBBP)/EP300 bromodomains are required to facilitate the elucidation of biology associated with these important epigenetic targets. Medicinal chemistry optimization that paid particular attention to physiochemical properties delivered chemical probes with desirable potency, selectivity, and permeability attributes. An important feature of the optimization process was the successful application of rational structure-based drug design to address bromodomain selectivity issues (particularly against the structurally related BRD4 protein).

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

PubMed

Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia

2015-01-01

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.

Tetrahymena in the classroom.

PubMed

Smith, Joshua J; Wiley, Emily A; Cassidy-Hanley, Donna M

2012-01-01

Tetrahymena has been a useful model in basic research in part due to the fact it is easy to grow in culture and exhibits a range of complex processes, all within a single cell. For these same reasons Tetrahymena has shown enormous potential as a teaching tool for fundamental principles of biology at multiple science education levels that can be integrated into K-12 classrooms and undergraduate and graduate college laboratory courses. These Tetrahymena-based teaching modules are inquiry-based experiences that are also effective at teaching scientific concepts, retaining students in science, and exciting students about the scientific process. Two learning communities have been developed that utilize Tetrahymena-based teaching modules. Advancing Secondary Science Education with Tetrahymena (ASSET) and the Ciliate Genomics Consortium (CGC) have developed modules for K-12 students and college-level curriculums, respectively. These modules range from addressing topics in ecology, taxonomy, and environmental toxicity to more advanced concepts in biochemistry, proteomics, bioinformatics, cell biology, and molecular biology. An overview of the current modules and their learning outcomes are discussed, as are assessment, dissemination, and sustainability strategies for K-12 and college-level curriculum. Copyright © 2012 Elsevier Inc. All rights reserved.

Systems-based biological concordance and predictive reproducibility of gene set discovery methods in cardiovascular disease.

PubMed

Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying

2011-08-01

The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.

PubMed

Franceschi, Pietro; Mylonas, Roman; Shahaf, Nir; Scholz, Matthias; Arapitsas, Panagiotis; Masuero, Domenico; Weingart, Georg; Carlin, Silvia; Vrhovsek, Urska; Mattivi, Fulvio; Wehrens, Ron

2014-01-01

Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework.

An Ibm PC/AT-Based Image Acquisition And Processing System For Quantitative Image Analysis

NASA Astrophysics Data System (ADS)

Kim, Yongmin; Alexander, Thomas

1986-06-01

In recent years, a large number of applications have been developed for image processing systems in the area of biological imaging. We have already finished the development of a dedicated microcomputer-based image processing and analysis system for quantitative microscopy. The system's primary function has been to facilitate and ultimately automate quantitative image analysis tasks such as the measurement of cellular DNA contents. We have recognized from this development experience, and interaction with system users, biologists and technicians, that the increasingly widespread use of image processing systems, and the development and application of new techniques for utilizing the capabilities of such systems, would generate a need for some kind of inexpensive general purpose image acquisition and processing system specially tailored for the needs of the medical community. We are currently engaged in the development and testing of hardware and software for a fairly high-performance image processing computer system based on a popular personal computer. In this paper, we describe the design and development of this system. Biological image processing computer systems have now reached a level of hardware and software refinement where they could become convenient image analysis tools for biologists. The development of a general purpose image processing system for quantitative image analysis that is inexpensive, flexible, and easy-to-use represents a significant step towards making the microscopic digital image processing techniques more widely applicable not only in a research environment as a biologist's workstation, but also in clinical environments as a diagnostic tool.

Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

PubMed

Wright, Cameron H G; Barrett, Steven F; Pack, Daniel J

2005-01-01

We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.

The Physical Microbe; An introduction to noise, control, and communication in the prokaryotic cell

NASA Astrophysics Data System (ADS)

Hagen, Stephen J.

2017-10-01

Physical biology is a fusion of biology and physics. This book narrows down the scope of physical biology by focusing on the microbial cell; exploring the physical phenomena of noise, feedback, and variability that arise in the cellular information-processing circuits used by bacteria. It looks at the microbe from a physics perspective, asking how the cell optimizes its function to live within the constraints of physics. It introduces a physical and information-based (as opposed to microbiological) perspective on communication and signalling between microbes.

hydropower biological evaluation tools

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

This software is a set of analytical tools to evaluate the physical and biological performance of existing, refurbished, or newly installed conventional hydro-turbines nationwide where fish passage is a regulatory concern. The current version is based on information collected by the Sensor Fish. Future version will include other technologies. The tool set includes data acquisition, data processing, and biological response tools with applications to various turbine designs and other passage alternatives. The associated database is centralized, and can be accessed remotely. We have demonstrated its use for various applications including both turbines and spillways

Vesicle-based method for collecting, manipulating, and chemically processing trace macromolecular species

DOEpatents

Davalos, Rafael V [Oakland, CA; Ellis, Christopher R. B. [Oakland, CA

2010-08-17

Disclosed is an apparatus and method for inserting one or several chemical or biological species into phospholipid containers that are controlled within a microfluidic network, wherein individual containers are tracked and manipulated by electric fields and wherein the contained species may be chemically processed.

Vesicle-based method and apparatus for collecting, manipulating, and chemically processing trace macromolecular species

DOEpatents

Davalos, Rafael V [Oakland, CA; Ellis, Christopher R. B. [Oakland, CA

2008-03-04

Disclosed is an apparatus and method for inserting one or several chemical or biological species into phospholipid containers that are controlled within a microfluidic network, wherein individual containers are tracked and manipulated by electric fields and wherein the contained species may be chemically processed.

Process Relationships for Evaluating the Role of Light-induced Inactivation of Enterococci at Selected Beaches and Nearby Tributaries of the Great Lakes

EPA Science Inventory

One approach to predictive modeling of biological contamination of recreational waters and drinking water sources involves applying process-based models that consider microbial sources, hydrodynamic transport, and microbial fate. Fecal indicator bacteria such as enterococci have ...

Developing Inquiry-Based Labs Using Micro-Column Chromatography

ERIC Educational Resources Information Center

Barden-Gabbei, Laura M.; Moffitt, Deborah L.

2006-01-01

Chromatography is a process by which mixtures can be separated or substances can be purified. Biological and chemical laboratories use many different types of chromatographic processes. For example, the pharmaceutical industry uses chromatographic techniques to purify drugs, medical labs use them to identify blood components such as cholesterol,…

SPIDER image processing for single-particle reconstruction of biological macromolecules from electron micrographs

PubMed Central

Shaikh, Tanvir R; Gao, Haixiao; Baxter, William T; Asturias, Francisco J; Boisset, Nicolas; Leith, Ardean; Frank, Joachim

2009-01-01

This protocol describes the reconstruction of biological molecules from the electron micrographs of single particles. Computation here is performed using the image-processing software SPIDER and can be managed using a graphical user interface, termed the SPIDER Reconstruction Engine. Two approaches are described to obtain an initial reconstruction: random-conical tilt and common lines. Once an existing model is available, reference-based alignment can be used, a procedure that can be iterated. Also described is supervised classification, a method to look for homogeneous subsets when multiple known conformations of the molecule may coexist. PMID:19180078

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.

PubMed

Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T

2017-10-01

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.

Applications of Raman Spectroscopy in Biopharmaceutical Manufacturing: A Short Review.

PubMed

Buckley, Kevin; Ryder, Alan G

2017-06-01

The production of active pharmaceutical ingredients (APIs) is currently undergoing its biggest transformation in a century. The changes are based on the rapid and dramatic introduction of protein- and macromolecule-based drugs (collectively known as biopharmaceuticals) and can be traced back to the huge investment in biomedical science (in particular in genomics and proteomics) that has been ongoing since the 1970s. Biopharmaceuticals (or biologics) are manufactured using biological-expression systems (such as mammalian, bacterial, insect cells, etc.) and have spawned a large (>€35 billion sales annually in Europe) and growing biopharmaceutical industry (BioPharma). The structural and chemical complexity of biologics, combined with the intricacy of cell-based manufacturing, imposes a huge analytical burden to correctly characterize and quantify both processes (upstream) and products (downstream). In small molecule manufacturing, advances in analytical and computational methods have been extensively exploited to generate process analytical technologies (PAT) that are now used for routine process control, leading to more efficient processes and safer medicines. In the analytical domain, biologic manufacturing is considerably behind and there is both a huge scope and need to produce relevant PAT tools with which to better control processes, and better characterize product macromolecules. Raman spectroscopy, a vibrational spectroscopy with a number of useful properties (nondestructive, non-contact, robustness) has significant potential advantages in BioPharma. Key among them are intrinsically high molecular specificity, the ability to measure in water, the requirement for minimal (or no) sample pre-treatment, the flexibility of sampling configurations, and suitability for automation. Here, we review and discuss a representative selection of the more important Raman applications in BioPharma (with particular emphasis on mammalian cell culture). The review shows that the properties of Raman have been successfully exploited to deliver unique and useful analytical solutions, particularly for online process monitoring. However, it also shows that its inherent susceptibility to fluorescence interference and the weakness of the Raman effect mean that it can never be a panacea. In particular, Raman-based methods are intrinsically limited by the chemical complexity and wide analyte-concentration-profiles of cell culture media/bioprocessing broths which limit their use for quantitative analysis. Nevertheless, with appropriate foreknowledge of these limitations and good experimental design, robust analytical methods can be produced. In addition, new technological developments such as time-resolved detectors, advanced lasers, and plasmonics offer potential of new Raman-based methods to resolve existing limitations and/or provide new analytical insights.

40 CFR 63.138 - Process wastewater provisions-performance standards for treatment processes managing Group 1...

Code of Federal Regulations, 2010 CFR

2010-07-01

.../or Table 9 compounds are similar and often identical. (3) Biological treatment processes. Biological treatment processes in compliance with this section may be either open or closed biological treatment processes as defined in § 63.111. An open biological treatment process in compliance with this section need...

Proteomics for Adverse Outcome Pathway Discovery using Human Kidney Cells?

EPA Science Inventory

An Adverse Outcome Pathway (AOP) is a conceptual framework that applies molecular-based data for use in risk assessment and regulatory decision support. AOP development is based on effects data of chemicals on biological processes (i.e., molecular initiating events, key intermedi...

A Model of Generating Visual Place Cells Based on Environment Perception and Similar Measure.

PubMed

Zhou, Yang; Wu, Dewei

2016-01-01

It is an important content to generate visual place cells (VPCs) in the field of bioinspired navigation. By analyzing the firing characteristic of biological place cells and the existing methods for generating VPCs, a model of generating visual place cells based on environment perception and similar measure is abstracted in this paper. VPCs' generation process is divided into three phases, including environment perception, similar measure, and recruiting of a new place cell. According to this process, a specific method for generating VPCs is presented. External reference landmarks are obtained based on local invariant characteristics of image and a similar measure function is designed based on Euclidean distance and Gaussian function. Simulation validates the proposed method is available. The firing characteristic of the generated VPCs is similar to that of biological place cells, and VPCs' firing fields can be adjusted flexibly by changing the adjustment factor of firing field (AFFF) and firing rate's threshold (FRT).

A Model of Generating Visual Place Cells Based on Environment Perception and Similar Measure

PubMed Central

2016-01-01

It is an important content to generate visual place cells (VPCs) in the field of bioinspired navigation. By analyzing the firing characteristic of biological place cells and the existing methods for generating VPCs, a model of generating visual place cells based on environment perception and similar measure is abstracted in this paper. VPCs' generation process is divided into three phases, including environment perception, similar measure, and recruiting of a new place cell. According to this process, a specific method for generating VPCs is presented. External reference landmarks are obtained based on local invariant characteristics of image and a similar measure function is designed based on Euclidean distance and Gaussian function. Simulation validates the proposed method is available. The firing characteristic of the generated VPCs is similar to that of biological place cells, and VPCs' firing fields can be adjusted flexibly by changing the adjustment factor of firing field (AFFF) and firing rate's threshold (FRT). PMID:27597859

Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes

USGS Publications Warehouse

Gerber, Brian D.; Kendall, William L.

2017-01-01

Monitoring animal populations can be difficult. Limited resources often force monitoring programs to rely on unadjusted or smoothed counts as an index of abundance. Smoothing counts is commonly done using a moving-average estimator to dampen sampling variation. These indices are commonly used to inform management decisions, although their reliability is often unknown. We outline a process to evaluate the biological plausibility of annual changes in population counts and indices from a typical monitoring scenario and compare results with a hierarchical Bayesian time series (HBTS) model. We evaluated spring and fall counts, fall indices, and model-based predictions for the Rocky Mountain population (RMP) of Sandhill Cranes (Antigone canadensis) by integrating juvenile recruitment, harvest, and survival into a stochastic stage-based population model. We used simulation to evaluate population indices from the HBTS model and the commonly used 3-yr moving average estimator. We found counts of the RMP to exhibit biologically unrealistic annual change, while the fall population index was largely biologically realistic. HBTS model predictions suggested that the RMP changed little over 31 yr of monitoring, but the pattern depended on assumptions about the observational process. The HBTS model fall population predictions were biologically plausible if observed crane harvest mortality was compensatory up to natural mortality, as empirical evidence suggests. Simulations indicated that the predicted mean of the HBTS model was generally a more reliable estimate of the true population than population indices derived using a moving 3-yr average estimator. Practitioners could gain considerable advantages from modeling population counts using a hierarchical Bayesian autoregressive approach. Advantages would include: (1) obtaining measures of uncertainty; (2) incorporating direct knowledge of the observational and population processes; (3) accommodating missing years of data; and (4) forecasting population size.

Spectroscopy of Isolated Prebiotic Nucleobases

NASA Technical Reports Server (NTRS)

Svadlenak, Nathan; Callahan, Michael P.; Ligare, Marshall; Gulian, Lisa; Gengeliczki, Zsolt; Nachtigallova, Dana; Hobza, Pavel; deVries, Mattanjah

2011-01-01

We use multiphoton ionization and double resonance spectroscopy to study the excited state dynamics of biologically relevant molecules as well as prebiotic nucleobases, isolated in the gas phase. Molecules that are biologically relevant to life today tend to exhibit short excited state lifetimes compared to similar but non-biologically relevant analogs. The mechanism is internal conversion, which may help protect the biologically active molecules from UV damage. This process is governed by conical intersections that depend very strongly on molecular structure. Therefore we have studied purines and pyrimidines with systematic variations of structure, including substitutions, tautomeric forms, and cluster structures that represent different base pair binding motifs. These structural variations also include possible alternate base pairs that may shed light on prebiotic chemistry. With this in mind we have begun to probe the ultrafast dynamics of molecules that exhibit very short excited states and search for evidence of internal conversions.

Prototype Biology-Based Radiation Risk Module Project

NASA Technical Reports Server (NTRS)

Terrier, Douglas; Clayton, Ronald G.; Patel, Zarana; Hu, Shaowen; Huff, Janice

2015-01-01

Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

Inter-institutional Development of a Poster-Based Cancer Biology Learning Tool

PubMed Central

Andraos-Selim, Cecile; Modzelewski, Ruth A.; Steinman, Richard A.

2010-01-01

There is a paucity of African-American Cancer researchers. To help address this, an educational collaboration was developed between a Comprehensive Cancer Center and a distant undergraduate biology department at a minority institution that sought to teach students introductory cancer biology while modeling research culture. A student-centered active learning curriculum was established that incorporated scientific poster presentations and simulated research exercises to foster learning of cancer biology. Students successfully mined primary literature for supportive data to test cancer-related hypotheses. Student feedback indicated that the poster project substantially enhanced depth of understanding of cancer biology and laid the groundwork for subsequent laboratory work. This inter-institutional collaboration modeled the research process while conveying facts and concepts about cancer. PMID:20237886

Technology base for microgravity horticulture

NASA Technical Reports Server (NTRS)

Sauer, R. L.; Magnuson, J. W.; Scruby, R. R.; Scheld, H. W.

1987-01-01

Advanced microgravity plant biology research and life support system development for the spacecraft environment are critically hampered by the lack of a technology base. This inadequacy stems primarily from the fact that microgravity results in a lack of convective currents and phase separation as compared to the one gravity environment. A program plan is being initiated to develop this technology base. This program will provide an iterative flight development effort that will be closely integrated with both basic science investigations and advanced life support system development efforts incorporating biological processes. The critical considerations include optimum illumination methods, root aeration, root and shoot support, and heat rejection and gas exchange in the plant canopy.

Automated production of plant-based vaccines and pharmaceuticals.

PubMed

Wirz, Holger; Sauer-Budge, Alexis F; Briggs, John; Sharpe, Aaron; Shu, Sudong; Sharon, Andre

2012-12-01

A fully automated "factory" was developed that uses tobacco plants to produce large quantities of vaccines and other therapeutic biologics within weeks. This first-of-a-kind factory takes advantage of a plant viral vector technology to produce specific proteins within the leaves of rapidly growing plant biomass. The factory's custom-designed robotic machines plant seeds, nurture the growing plants, introduce a viral vector that directs the plant to produce a target protein, and harvest the biomass once the target protein has accumulated in the plants-all in compliance with Food and Drug Administration (FDA) guidelines (e.g., current Good Manufacturing Practices). The factory was designed to be time, cost, and space efficient. The plants are grown in custom multiplant trays. Robots ride up and down a track, servicing the plants and delivering the trays from the lighted, irrigated growth modules to each processing station as needed. Using preprogrammed robots and processing equipment eliminates the need for human contact, preventing potential contamination of the process and economizing the operation. To quickly produce large quantities of protein-based medicines, we transformed a laboratory-based biological process and scaled it into an industrial process. This enables quick, safe, and cost-effective vaccine production that would be required in case of a pandemic.

Functional networks inference from rule-based machine learning models.

PubMed

Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume

2016-01-01

Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The implementation of our network inference protocol is available at: http://ico2s.org/software/funel.html.

Learning How Scientists Work: Experiential Research Projects to Promote Cell Biology Learning and Scientific Process Skills

PubMed Central

2002-01-01

Facilitating not only the mastery of sophisticated subject matter, but also the development of process skills is an ongoing challenge in teaching any introductory undergraduate course. To accomplish this goal in a sophomore-level introductory cell biology course, I require students to work in groups and complete several mock experiential research projects that imitate the professional activities of the scientific community. I designed these projects as a way to promote process skill development within content-rich pedagogy and to connect text-based and laboratory-based learning with the world of contemporary research. First, students become familiar with one primary article from a leading peer-reviewed journal, which they discuss by means of PowerPoint-based journal clubs and journalism reports highlighting public relevance. Second, relying mostly on primary articles, they investigate the molecular basis of a disease, compose reviews for an in-house journal, and present seminars in a public symposium. Last, students author primary articles detailing investigative experiments conducted in the lab. This curriculum has been successful in both quarter-based and semester-based institutions. Student attitudes toward their learning were assessed quantitatively with course surveys. Students consistently reported that these projects significantly lowered barriers to primary literature, improved research-associated skills, strengthened traditional pedagogy, and helped accomplish course objectives. Such approaches are widely suited for instructors seeking to integrate process with content in their courses. PMID:12669101

Learning how scientists work: experiential research projects to promote cell biology learning and scientific process skills.

PubMed

DebBurman, Shubhik K

2002-01-01

Facilitating not only the mastery of sophisticated subject matter, but also the development of process skills is an ongoing challenge in teaching any introductory undergraduate course. To accomplish this goal in a sophomore-level introductory cell biology course, I require students to work in groups and complete several mock experiential research projects that imitate the professional activities of the scientific community. I designed these projects as a way to promote process skill development within content-rich pedagogy and to connect text-based and laboratory-based learning with the world of contemporary research. First, students become familiar with one primary article from a leading peer-reviewed journal, which they discuss by means of PowerPoint-based journal clubs and journalism reports highlighting public relevance. Second, relying mostly on primary articles, they investigate the molecular basis of a disease, compose reviews for an in-house journal, and present seminars in a public symposium. Last, students author primary articles detailing investigative experiments conducted in the lab. This curriculum has been successful in both quarter-based and semester-based institutions. Student attitudes toward their learning were assessed quantitatively with course surveys. Students consistently reported that these projects significantly lowered barriers to primary literature, improved research-associated skills, strengthened traditional pedagogy, and helped accomplish course objectives. Such approaches are widely suited for instructors seeking to integrate process with content in their courses.

Planar optical waveguide based sandwich assay sensors and processes for the detection of biological targets including protein markers, pathogens and cellular debris

DOEpatents

Martinez, Jennifer S [Santa Fe, NM; Swanson, Basil I [Los Alamos, NM; Grace, Karen M [Los Alamos, NM; Grace, Wynne K [Los Alamos, NM; Shreve, Andrew P [Santa Fe, NM

2009-06-02

An assay element is described including recognition ligands bound to a film on a single mode planar optical waveguide, the film from the group of a membrane, a polymerized bilayer membrane, and a self-assembled monolayer containing polyethylene glycol or polypropylene glycol groups therein and an assay process for detecting the presence of a biological target is described including injecting a biological target-containing sample into a sensor cell including the assay element, with the recognition ligands adapted for binding to selected biological targets, maintaining the sample within the sensor cell for time sufficient for binding to occur between selected biological targets within the sample and the recognition ligands, injecting a solution including a reporter ligand into the sensor cell; and, interrogating the sample within the sensor cell with excitation light from the waveguide, the excitation light provided by an evanescent field of the single mode penetrating into the biological target-containing sample to a distance of less than about 200 nanometers from the waveguide thereby exciting the fluorescent-label in any bound reporter ligand within a distance of less than about 200 nanometers from the waveguide and resulting in a detectable signal.

Biodegradation of phytosanitary products in biological wastewater treatment.

PubMed

Massot, A; Estève, K; Noilet, P; Méoule, C; Poupot, C; Mietton-Peuchot, M

2012-04-15

Agricultural activity generates two types of waste: firstly, biodegradable organic effluents generally treated by biological processes and, secondly, phytosanitary effluents which contain residues of plant protection products. The latter are collected and treated. Current technological solutions are essentially based on concentration or physical-chemical processes. However, recent improvements in the biodegradability of pesticides open the way to the consideration of alternative, biological, treatment using mixed liquor from wastewater plant activated sludge. The feasibility of the biological treatment of viticultural effluents has been evaluated by the application of pesticides to activated sludge. The necessity for selection of a pesticide-resistant biomass has been highlighted. The elimination of the phytosanitary products shows the potential of a resistant biomass in the treatment of pesticides. The aerated biological storage ponds at three wineries, followed by a sand or reed-bed filter, were used for the treatment of the total annual volume of the viticulture effluents and validate the laboratory experiments. The results show that the biological purification of pesticides by activated sludge is possible by allowing approximately 8 days for biomass adaptation. Stability of purification occurs between 20 and 30 days. Copyright © 2012 Elsevier Ltd. All rights reserved.

The effects of problem-based learning on the self-efficacy and attitudes of beginning biology majors

NASA Astrophysics Data System (ADS)

Rajab, Adel Mohammad

The problem of low persistence of science majors has resulted in calls for changes in undergraduate instruction toward environments that foster positive self-efficacy among beginning science majors. Low science self-efficacy and poor attitudes toward science may contribute to high attrition rates of science majors. Classroom environments that foster positive self-efficacy development include pedagogies that promote authentic learning contexts and involve collaborative learning teams. Problem-based learning (PBL) is an instructional model that attempts to create both conditions and may provide every source of information needed for the development of self-efficacy (i.e., mastery experiences, vicarious experiences, verbal persuasion, and physiological states) as postulated by Albert Bandura. The degree to which these sources of self-efficacy are delivered to individuals within a PBL group may depend on how the group members interact and how students perceive the PBL process itself. This study examined the development of biology self-efficacy and attitudes among biology majors in a PBL setting and in a traditional lecture-based setting. Specifically, this project investigated changes in students' biology self-efficacy beliefs, mediating aspects of PBL in self-efficacy development, the relationship between PBL processes and group collective efficacy, the predictive nature of entering self-efficacy levels on attitudes toward PBL and mid-term grades, and changes in student attitudes toward biology. The study design was quasi-experimental and included quantitative pre- and post-surveys, qualitative interviews, and classroom observations. Findings revealed that students enrolled in a PBL class exhibited greater gains in biology self-efficacy and were likely to report more favorable attitudes toward biology compared to students enrolled in a traditional class. The aspects of PBL that most accounted for these findings were students' ownership of the learning process, their deep understanding of the material, and their perceptions of the utility of PBL for their futures. Other aspects of PBL that may have contributed to the self-efficacy and attitudes of PBL students were the interactions of students in their PBL groups. Furthermore, students had favorable attitudes toward PBL regardless of their pre-treatment self-efficacy and achievement levels. Thus PBL may be useful for both high-achieving and low achieving students.

Towards molecular medicine: a case for a biological periodic table.

PubMed

Gawad, Charles

2005-01-01

The recently amplified pace of development in the technologies to study both normal and aberrant cellular physiology has allowed for a transition from the traditional reductionist approaches to global interrogations of human biology. This transformation has created the anticipation that we will soon more effectively treat or contain most types of diseases through a 'systems-based' approach to understanding and correcting the underlying etiology of these processes. However, to accomplish these goals, we must first have a more comprehensive understanding of all the elements involved in human cellular physiology, as well as why and how they interact. With the vast number of biological components that have and are being discovered, creating methods with modern computational techniques to better organize biological elements is the next requisite step in this process. This article aims to articulate the importance of the organization of chemical elements into a periodic table had on the conversion of chemistry into a quantitative, translatable science, as well as how we can apply the lessons learned in that transition to the current transformation taking place in biology.

STOCHSIMGPU: parallel stochastic simulation for the Systems Biology Toolbox 2 for MATLAB.

PubMed

Klingbeil, Guido; Erban, Radek; Giles, Mike; Maini, Philip K

2011-04-15

The importance of stochasticity in biological systems is becoming increasingly recognized and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU that exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB. The GPU-based parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM) and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user's models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2. The software is open source under the GPL v3 and available at http://www.maths.ox.ac.uk/cmb/STOCHSIMGPU. The web site also contains supplementary information. klingbeil@maths.ox.ac.uk Supplementary data are available at Bioinformatics online.

Tinkering: a conceptual and historical evaluation.

PubMed

Laubichler, Manfred D

2007-01-01

Francois Jacob's article 'Evolution and Tinkering' published in Science in 1977 is still the locus classicus for the concept of tinkering in biology. It first introduced the notion of tinkering to a wide audience of scientists. Jacob drew on a variety of different sources ranging from molecular biology to evolutionary biology and cultural anthropology. The notion of tinkering, or more accurately, the concept of bricolage, are conceptual abstractions that allow for the theoretical analysis of a wide range of phenomena that are united by a shared underlying process--tinkering, or the opportunistic rearrangement and recombination of existing elements. This paper looks at Jacob's analysis as itself an example of conceptual tinkering. It traces the history of some of its elements and sketches how it has become part of an inclusive discourse of theoretical biology and evolutionary developmental biology that emerged over the last 30 years. I will argue that the theoretical power of Jacob's analysis lies in the fact that he captured a widespread phenomenon. His conceptual analysis is thus an example of an interdisciplinary synthesis that is based on a shared process rather than a shared object.

Computer retina that models the primate retina

NASA Astrophysics Data System (ADS)

Shah, Samir; Levine, Martin D.

1994-06-01

At the retinal level, the strategies utilized by biological visual systems allow them to outperform machine vision systems, serving to motivate the design of electronic or `smart' sensors based on similar principles. Design of such sensors in silicon first requires a model of retinal information processing which captures the essential features exhibited by biological retinas. In this paper, a simple retinal model is presented, which qualitatively accounts for the achromatic information processing in the primate cone system. The model exhibits many of the properties found in biological retina such as data reduction through nonuniform sampling, adaptation to a large dynamic range of illumination levels, variation of visual acuity with illumination level, and enhancement of spatio temporal contrast information. The model is validated by replicating experiments commonly performed by electrophysiologists on biological retinas and comparing the response of the computer retina to data from experiments in monkeys. In addition, the response of the model to synthetic images is shown. The experiments demonstrate that the model behaves in a manner qualitatively similar to biological retinas and thus may serve as a basis for the development of an `artificial retina.'

A Learning Framework for Winner-Take-All Networks with Stochastic Synapses.

PubMed

Mostafa, Hesham; Cauwenberghs, Gert

2018-06-01

Many recent generative models make use of neural networks to transform the probability distribution of a simple low-dimensional noise process into the complex distribution of the data. This raises the question of whether biological networks operate along similar principles to implement a probabilistic model of the environment through transformations of intrinsic noise processes. The intrinsic neural and synaptic noise processes in biological networks, however, are quite different from the noise processes used in current abstract generative networks. This, together with the discrete nature of spikes and local circuit interactions among the neurons, raises several difficulties when using recent generative modeling frameworks to train biologically motivated models. In this letter, we show that a biologically motivated model based on multilayer winner-take-all circuits and stochastic synapses admits an approximate analytical description. This allows us to use the proposed networks in a variational learning setting where stochastic backpropagation is used to optimize a lower bound on the data log likelihood, thereby learning a generative model of the data. We illustrate the generality of the proposed networks and learning technique by using them in a structured output prediction task and a semisupervised learning task. Our results extend the domain of application of modern stochastic network architectures to networks where synaptic transmission failure is the principal noise mechanism.

Microbial ecology of denitrification in biological wastewater treatment.

PubMed

Lu, Huijie; Chandran, Kartik; Stensel, David

2014-11-01

Globally, denitrification is commonly employed in biological nitrogen removal processes to enhance water quality. However, substantial knowledge gaps remain concerning the overall community structure, population dynamics and metabolism of different organic carbon sources. This systematic review provides a summary of current findings pertaining to the microbial ecology of denitrification in biological wastewater treatment processes. DNA fingerprinting-based analysis has revealed a high level of microbial diversity in denitrification reactors and highlighted the impacts of carbon sources in determining overall denitrifying community composition. Stable isotope probing, fluorescence in situ hybridization, microarrays and meta-omics further link community structure with function by identifying the functional populations and their gene regulatory patterns at the transcriptional and translational levels. This review stresses the need to integrate microbial ecology information into conventional denitrification design and operation at full-scale. Some emerging questions, from physiological mechanisms to practical solutions, for example, eliminating nitrous oxide emissions and supplementing more sustainable carbon sources than methanol, are also discussed. A combination of high-throughput approaches is next in line for thorough assessment of wastewater denitrifying community structure and function. Though denitrification is used as an example here, this synergy between microbial ecology and process engineering is applicable to other biological wastewater treatment processes. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Pushing the lipid envelope: using bio-inspired nanocomposites to understand and exploit lipid membrane limitations

NASA Astrophysics Data System (ADS)

Montano, Gabriel

Lipids serve as the organizing matrix material for biological membranes, the site of interaction of cells with the external environment. . As such, lipids play a critical role in structure/function relationships of an extraordinary number of critical biological processes. In this talk, we will look at bio-inspired membrane assemblies to better understand the roles of lipids in biological systems as well as attempt to generate materials that can mimic and potentially advance upon biological membrane processes. First, we will investigate the response of lipids to adverse conditions. In particular, I will present data that demonstrates the response of lipids to harsh conditions and how such responses can be exploited to generate nanocomposite rearrangements. I will also show the effect of adding the endotoxin lipopolysaccharide (LPS) to lipid bilayer assemblies and describe implications on our understanding of LPS organization in biological systems as well as describe induced lipid modifications that can be exploited to organize membrane composites with precise, two-dimensional geometric control. Lastly, I will describe the use of amphiphilic block copolymers to create membrane nanocomposites capable of mimicking biological systems. In particular, I will describe the use of our polymer-based membranes in creating artificial photosynthetic assemblies that rival biological systems in function in a more flexible, dynamic matrix.

DeDaL: Cytoscape 3 app for producing and morphing data-driven and structure-driven network layouts.

PubMed

Czerwinska, Urszula; Calzone, Laurence; Barillot, Emmanuel; Zinovyev, Andrei

2015-08-14

Visualization and analysis of molecular profiling data together with biological networks are able to provide new mechanistic insights into biological functions. Currently, it is possible to visualize high-throughput data on top of pre-defined network layouts, but they are not always adapted to a given data analysis task. A network layout based simultaneously on the network structure and the associated multidimensional data might be advantageous for data visualization and analysis in some cases. We developed a Cytoscape app, which allows constructing biological network layouts based on the data from molecular profiles imported as values of node attributes. DeDaL is a Cytoscape 3 app, which uses linear and non-linear algorithms of dimension reduction to produce data-driven network layouts based on multidimensional data (typically gene expression). DeDaL implements several data pre-processing and layout post-processing steps such as continuous morphing between two arbitrary network layouts and aligning one network layout with respect to another one by rotating and mirroring. The combination of all these functionalities facilitates the creation of insightful network layouts representing both structural network features and correlation patterns in multivariate data. We demonstrate the added value of applying DeDaL in several practical applications, including an example of a large protein-protein interaction network. DeDaL is a convenient tool for applying data dimensionality reduction methods and for designing insightful data displays based on data-driven layouts of biological networks, built within Cytoscape environment. DeDaL is freely available for downloading at http://bioinfo-out.curie.fr/projects/dedal/.

Evaluating the effectiveness of a practical inquiry-based learning bioinformatics module on undergraduate student engagement and applied skills.

PubMed

Brown, James A L

2016-05-06

A pedagogic intervention, in the form of an inquiry-based peer-assisted learning project (as a practical student-led bioinformatics module), was assessed for its ability to increase students' engagement, practical bioinformatic skills and process-specific knowledge. Elements assessed were process-specific knowledge following module completion, qualitative student-based module evaluation and the novelty, scientific validity and quality of written student reports. Bioinformatics is often the starting point for laboratory-based research projects, therefore high importance was placed on allowing students to individually develop and apply processes and methods of scientific research. Students led a bioinformatic inquiry-based project (within a framework of inquiry), discovering, justifying and exploring individually discovered research targets. Detailed assessable reports were produced, displaying data generated and the resources used. Mimicking research settings, undergraduates were divided into small collaborative groups, with distinctive central themes. The module was evaluated by assessing the quality and originality of the students' targets through reports, reflecting students' use and understanding of concepts and tools required to generate their data. Furthermore, evaluation of the bioinformatic module was assessed semi-quantitatively using pre- and post-module quizzes (a non-assessable activity, not contributing to their grade), which incorporated process- and content-specific questions (indicative of their use of the online tools). Qualitative assessment of the teaching intervention was performed using post-module surveys, exploring student satisfaction and other module specific elements. Overall, a positive experience was found, as was a post module increase in correct process-specific answers. In conclusion, an inquiry-based peer-assisted learning module increased students' engagement, practical bioinformatic skills and process-specific knowledge. © 2016 by The International Union of Biochemistry and Molecular Biology, 44:304-313 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

The Impact of Inquiry Based Instruction on Science Process Skills and Self-Efficacy Perceptions of Pre-Service Science Teachers at a University Level Biology Laboratory

ERIC Educational Resources Information Center

Sen, Ceylan; Sezen Vekli, Gülsah

2016-01-01

The aim of this study is to determine the influence of inquiry-based teaching approach on pre-service science teachers' laboratory self-efficacy perceptions and scientific process skills. The quasi experimental model with pre-test-post-test control group design was used as an experimental design in this research. The sample of this study included…

Rethinking biology instruction: The application of DNR-based instruction to the learning and teaching of biology

NASA Astrophysics Data System (ADS)

Maskiewicz, April Lee

Educational studies report that secondary and college level students have developed only limited understandings of the most basic biological processes and their interrelationships from typical classroom experiences. Furthermore, students have developed undesirable reasoning schemes and beliefs that directly affect how they make sense of and account for biological phenomena. For these reasons, there exists a need to rethink instructional practices in biology. This dissertation discusses how the principles of Harel's (1998, 2001) DNR-based instruction in mathematics could be applied to the teaching and learning of biology. DNR is an acronym for the three foundational principles of the system: Duality, Necessity, and Repeated-reasoning. This study examines the application of these three principles to ecology instruction. Through clinical and teaching interviews, I developed models of students' existing ways of understanding in ecology and inferred their ways of thinking. From these models a hypothetical learning trajectory was developed for 16 college level freshmen enrolled in a 10-week ecology teaching experiment. Through cyclical, interpretive analysis I documented and analyzed the evolution of the participants' progress. The results provide empirical evidence to support the claim that the DNR principles are applicable to ecology instruction. With respect to the Duality Principle, helping students develop specific ways of understanding led to the development of model-based reasoning---a way of thinking and the cognitive objective guiding instruction. Through carefully structured problem solving tasks, the students developed a biological understanding of the relationship between matter cycling, energy flow, and cellular processes such as photosynthesis and respiration, and used this understanding to account for observable phenomena in nature. In the case of intellectual necessity, the results illuminate how problem situations can be developed for biology learners that create cognitive disequilibrium-equilibrium phases and thus lead to modification or refinement of existing schemes. Elements that contributed to creating intellectual need include (a) problem tasks that built on students' existing knowledge; (b) problem tasks that challenged students; (c) a routine in which students presented their group's solution to the class; and (d) the didactical contract (Brousseau, 1997) established in the classroom.

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

ERIC Educational Resources Information Center

Xiang, Lin

2011-01-01

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

Do Teachers Make All Their Students Play the Same Learning Games? A Comparative Study of Learning Games in Biology and English as a Second Language

ERIC Educational Resources Information Center

Gruson, Brigitte; Marlot, Corinne

2016-01-01

This article, based upon the field of comparative didactics, seeks to contribute to the identification of generic and specific features in the teaching and learning process. More particularly, its aim was to examine, through the study of two different school subjects: biology and English as a second language, how "passive didactic…

Simple Math is Enough: Two Examples of Inferring Functional Associations from Genomic Data

NASA Technical Reports Server (NTRS)

Liang, Shoudan

2003-01-01

Non-random features in the genomic data are usually biologically meaningful. The key is to choose the feature well. Having a p-value based score prioritizes the findings. If two proteins share a unusually large number of common interaction partners, they tend to be involved in the same biological process. We used this finding to predict the functions of 81 un-annotated proteins in yeast.

Roadmap on semiconductor-cell biointerfaces

NASA Astrophysics Data System (ADS)

Tian, Bozhi; Xu, Shuai; Rogers, John A.; Cestellos-Blanco, Stefano; Yang, Peidong; Carvalho-de-Souza, João L.; Bezanilla, Francisco; Liu, Jia; Bao, Zhenan; Hjort, Martin; Cao, Yuhong; Melosh, Nicholas; Lanzani, Guglielmo; Benfenati, Fabio; Galli, Giulia; Gygi, Francois; Kautz, Rylan; Gorodetsky, Alon A.; Kim, Samuel S.; Lu, Timothy K.; Anikeeva, Polina; Cifra, Michal; Krivosudský, Ondrej; Havelka, Daniel; Jiang, Yuanwen

2018-05-01

This roadmap outlines the role semiconductor-based materials play in understanding the complex biophysical dynamics at multiple length scales, as well as the design and implementation of next-generation electronic, optoelectronic, and mechanical devices for biointerfaces. The roadmap emphasizes the advantages of semiconductor building blocks in interfacing, monitoring, and manipulating the activity of biological components, and discusses the possibility of using active semiconductor-cell interfaces for discovering new signaling processes in the biological world.

Novel aspects of endometrial function: a biological sensor of embryo quality and driver of pregnancy success.

PubMed

Sandra, Olivier; Mansouri-Attia, Nadéra; Lea, Richard G

2011-01-01

Successful pregnancy depends on complex biological processes that are regulated temporally and spatially throughout gestation. The molecular basis of these processes have been examined in relation to gamete quality, early blastocyst development and placental function, and data have been generated showing perturbations of these developmental stages by environmental insults or embryo biotechnologies. The developmental period falling between the entry of the blastocyst into the uterine cavity to implantation has also been examined in terms of the biological function of the endometrium. Indeed several mechanisms underlying uterine receptivity, controlled by maternal factors, and the maternal recognition of pregnancy, requiring conceptus-produced signals, have been clarified. Nevertheless, recent data based on experimental perturbations have unveiled unexpected biological properties of the endometrium (sensor/driver) that make this tissue a dynamic and reactive entity. Persistent or transient modifications in organisation and functionality of the endometrium can dramatically affect pre-implantation embryo trajectory through epigenetic alterations with lasting consequences on later stages of pregnancy, including placentation, fetal development, pregnancy outcome and post-natal health. Developing diagnostic and prognostic tools based on endometrial factors may enable the assessment of maternal reproductive capacity and/or the developmental potential of the embryo, particularly when assisted reproductive technologies are applied.

Microfluidic Approaches to Synchrotron Radiation-Based Fourier Transform Infrared (SR-FTIR) Spectral Microscopy of Living Biosystems

PubMed Central

Loutherback, Kevin; Birarda, Giovanni; Chen, Liang; Holman, Hoi-Ying N.

2016-01-01

A long-standing desire in biological and biomedical sciences is to be able to probe cellular chemistry as biological processes are happening inside living cells. Synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy is a label-free and nondestructive analytical technique that can provide spatiotemporal distributions and relative abundances of biomolecules of a specimen by their characteristic vibrational modes. Despite great progress in recent years, SR-FTIR imaging of living biological systems remains challenging because of the demanding requirements on environmental control and strong infrared absorption of water. To meet this challenge, microfluidic devices have emerged as a method to control the water thickness while providing a hospitable environment to measure cellular processes and responses over many hours or days. This paper will provide an overview of microfluidic device development for SR-FTIR imaging of living biological systems, provide contrast between the various techniques including closed and open-channel designs, and discuss future directions of development within this area. Even as the fundamental science and technological demonstrations develop, other ongoing issues must be addressed; for example, choosing applications whose experimental requirements closely match device capabilities, and developing strategies to efficiently complete the cycle of development. These will require imagination, ingenuity and collaboration. PMID:26732243

Microfluidic approaches to synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy of living biosystems

DOE PAGES

Loutherback, Kevin; Birarda, Giovanni; Chen, Liang; ...

2016-02-15

A long-standing desire in biological and biomedical sciences is to be able to probe cellular chemistry as biological processes are happening inside living cells. Synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy is a label-free and nondestructive analytical technique that can provide spatiotemporal distributions and relative abundances of biomolecules of a specimen by their characteristic vibrational modes. Despite great progress in recent years, SR-FTIR imaging of living biological systems remains challenging because of the demanding requirements on environmental control and strong infrared absorption of water. To meet this challenge, microfluidic devices have emerged as a method to control the watermore » thickness while providing a hospitable environment to measure cellular processes and responses over many hours or days. This paper will provide an overview of microfluidic device development for SR-FTIR imaging of living biological systems, provide contrast between the various techniques including closed and open-channel designs, and discuss future directions of development within this area. Even as the fundamental science and technological demonstrations develop, other ongoing issues must be addressed; for example, choosing applications whose experimental requirements closely match device capabilities, and developing strategies to efficiently complete the cycle of development. These will require imagination, ingenuity and collaboration.« less

Microfluidic approaches to synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy of living biosystems

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

Loutherback, Kevin; Birarda, Giovanni; Chen, Liang

A long-standing desire in biological and biomedical sciences is to be able to probe cellular chemistry as biological processes are happening inside living cells. Synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy is a label-free and nondestructive analytical technique that can provide spatiotemporal distributions and relative abundances of biomolecules of a specimen by their characteristic vibrational modes. Despite great progress in recent years, SR-FTIR imaging of living biological systems remains challenging because of the demanding requirements on environmental control and strong infrared absorption of water. To meet this challenge, microfluidic devices have emerged as a method to control the watermore » thickness while providing a hospitable environment to measure cellular processes and responses over many hours or days. This paper will provide an overview of microfluidic device development for SR-FTIR imaging of living biological systems, provide contrast between the various techniques including closed and open-channel designs, and discuss future directions of development within this area. Even as the fundamental science and technological demonstrations develop, other ongoing issues must be addressed; for example, choosing applications whose experimental requirements closely match device capabilities, and developing strategies to efficiently complete the cycle of development. These will require imagination, ingenuity and collaboration.« less

Importance of Data Management in a Long-term Biological Monitoring Program

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

Christensen, Sigurd W; Brandt, Craig C; McCracken, Kitty

2011-01-01

The long-term Biological Monitoring and Abatement Program (BMAP) has always needed to collect and retain high-quality data on which to base its assessments of ecological status of streams and their recovery after remediation. Its formal quality assurance, data processing, and data management components all contribute to this need. The Quality Assurance Program comprehensively addresses requirements from various institutions, funders, and regulators, and includes a data management component. Centralized data management began a few years into the program. An existing relational database was adapted and extended to handle biological data. Data modeling enabled the program's database to process, store, and retrievemore » its data. The data base's main data tables and several key reference tables are described. One of the most important related activities supporting long-term analyses was the establishing of standards for sampling site names, taxonomic identification, flagging, and other components. There are limitations. Some types of program data were not easily accommodated in the central systems, and many possible data-sharing and integration options are not easily accessible to investigators. The implemented relational database supports the transmittal of data to the Oak Ridge Environmental Information System (OREIS) as the permanent repository. From our experience we offer data management advice to other biologically oriented long-term environmental sampling and analysis programs.« less

Interannual variability of primary production and air-sea CO2 flux in the Atlantic and Indian sectors of the Southern Ocean.

NASA Astrophysics Data System (ADS)

Dufour, Carolina; Merlivat, Liliane; Le Sommer, Julien; Boutin, Jacqueline; Antoine, David

2013-04-01

As one of the major oceanic sinks of anthropogenic CO2, the Southern Ocean plays a critical role in the climate system. However, due to the scarcity of observations, little is known about physical and biological processes that control air-sea CO2 fluxes and how these processes might respond to climate change. It is well established that primary production is one of the major drivers of air-sea CO2 fluxes, consuming surface Dissolved Inorganic Carbon (DIC) during Summer. Southern Ocean primary production is though constrained by several limiting factors such as iron and light availability, which are both sensitive to mixed layer depth. Mixed layer depth is known to be affected by current changes in wind stress or freshwater fluxes over the Southern Ocean. But we still don't know how primary production may respond to anomalous mixed layer depth neither how physical processes may balance this response to set the seasonal cycle of air-sea CO2 fluxes. In this study, we investigate the impact of anomalous mixed layer depth on surface DIC in the Atlantic and Indian sectors of the Subantarctic zone of the Southern Ocean (60W-60E, 38S-55S) with a combination of in situ data, satellite data and model experiment. We use both a regional eddy permitting ocean biogeochemical model simulation based on NEMO-PISCES and data-based reconstruction of biogeochemical fields based on CARIOCA buoys and SeaWiFS data. A decomposition of the physical and biological processes driving the seasonal variability of surface DIC is performed with both the model data and observations. A good agreement is found between the model and the data for the amplitude of biological and air-sea flux contributions. The model data are further used to investigate the impact of winter and summer anomalies in mixed layer depth on surface DIC over the period 1990-2004. The relative changes of each physical and biological process contribution are quantified and discussed.

Investigating biomolecular recognition at the cell surface using atomic force microscopy.

PubMed

Wang, Congzhou; Yadavalli, Vamsi K

2014-05-01

Probing the interaction forces that drive biomolecular recognition on cell surfaces is essential for understanding diverse biological processes. Force spectroscopy has been a widely used dynamic analytical technique, allowing measurement of such interactions at the molecular and cellular level. The capabilities of working under near physiological environments, combined with excellent force and lateral resolution make atomic force microscopy (AFM)-based force spectroscopy a powerful approach to measure biomolecular interaction forces not only on non-biological substrates, but also on soft, dynamic cell surfaces. Over the last few years, AFM-based force spectroscopy has provided biophysical insight into how biomolecules on cell surfaces interact with each other and induce relevant biological processes. In this review, we focus on describing the technique of force spectroscopy using the AFM, specifically in the context of probing cell surfaces. We summarize recent progress in understanding the recognition and interactions between macromolecules that may be found at cell surfaces from a force spectroscopy perspective. We further discuss the challenges and future prospects of the application of this versatile technique. Copyright © 2014 Elsevier Ltd. All rights reserved.

Computational Systems Biology in Cancer: Modeling Methods and Applications

PubMed Central

Materi, Wayne; Wishart, David S.

2007-01-01

In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to build computer simulations of intra and intercellular processes. Several useful descriptive and predictive models of the origin, growth and spread of cancers have been developed in an effort to better understand the disease and potential therapeutic approaches. In this review we describe and assess the practical and theoretical underpinnings of commonly-used modeling approaches, including ordinary and partial differential equations, petri nets, cellular automata, agent based models and hybrid systems. A number of computer-based formalisms have been implemented to improve the accessibility of the various approaches to researchers whose primary interest lies outside of model development. We discuss several of these and describe how they have led to novel insights into tumor genesis, growth, apoptosis, vascularization and therapy. PMID:19936081

Multidisciplinary design optimisation of a recurve bow based on applications of the autogenetic design theory and distributed computing

NASA Astrophysics Data System (ADS)

Fritzsche, Matthias; Kittel, Konstantin; Blankenburg, Alexander; Vajna, Sándor

2012-08-01

The focus of this paper is to present a method of multidisciplinary design optimisation based on the autogenetic design theory (ADT) that provides methods, which are partially implemented in the optimisation software described here. The main thesis of the ADT is that biological evolution and the process of developing products are mainly similar, i.e. procedures from biological evolution can be transferred into product development. In order to fulfil requirements and boundary conditions of any kind (that may change at any time), both biological evolution and product development look for appropriate solution possibilities in a certain area, and try to optimise those that are actually promising by varying parameters and combinations of these solutions. As the time necessary for multidisciplinary design optimisations is a critical aspect in product development, ways to distribute the optimisation process with the effective use of unused calculating capacity, can reduce the optimisation time drastically. Finally, a practical example shows how ADT methods and distributed optimising are applied to improve a product.

Big Data in Plant Science: Resources and Data Mining Tools for Plant Genomics and Proteomics.

PubMed

Popescu, George V; Noutsos, Christos; Popescu, Sorina C

2016-01-01

In modern plant biology, progress is increasingly defined by the scientists' ability to gather and analyze data sets of high volume and complexity, otherwise known as "big data". Arguably, the largest increase in the volume of plant data sets over the last decade is a consequence of the application of the next-generation sequencing and mass-spectrometry technologies to the study of experimental model and crop plants. The increase in quantity and complexity of biological data brings challenges, mostly associated with data acquisition, processing, and sharing within the scientific community. Nonetheless, big data in plant science create unique opportunities in advancing our understanding of complex biological processes at a level of accuracy without precedence, and establish a base for the plant systems biology. In this chapter, we summarize the major drivers of big data in plant science and big data initiatives in life sciences with a focus on the scope and impact of iPlant, a representative cyberinfrastructure platform for plant science.

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

A novel cell autolysis system for cost-competitive downstream processing.

PubMed

Hajnal, Ivan; Chen, Xiangbin; Chen, Guo-Qiang

2016-11-01

The industrial production of low value-added biological products poses significant challenges due to cost pressures. In recent years, it has been argued that synthetic biology approaches will lead to breakthroughs that eliminate price bottlenecks for the production of a wide range of biological products including bioplastics and biofuels. One significant bottleneck lies in the necessity to break the tough cell walls of microbes in order to release intracellular products. We here report the implementation of the first synthetic biology standard part based on the lambda phage SRRz genes and a synthetic ribosome binding site (RBS) that works in Escherichia coli and Halomonas campaniensis, which enables the producer strains to induce lysis after the addition of small amounts (1-5 %) of solvents or to spontaneously lyse during the stresses of downstream processing, and thus has the potential to eliminate the mechanical cell disruption step as both an efficiency bottleneck and a significant capex barrier when implementing downstream bioprocesses.

Remotely controlled fusion of selected vesicles and living cells: a key issue review

NASA Astrophysics Data System (ADS)

Bahadori, Azra; Moreno-Pescador, Guillermo; Oddershede, Lene B.; Bendix, Poul M.

2018-03-01

Remote control over fusion of single cells and vesicles has a great potential in biological and chemical research allowing both transfer of genetic material between cells and transfer of molecular content between vesicles. Membrane fusion is a critical process in biology that facilitates molecular transport and mixing of cellular cytoplasms with potential formation of hybrid cells. Cells precisely regulate internal membrane fusions with the aid of specialized fusion complexes that physically provide the energy necessary for mediating fusion. Physical factors like membrane curvature, tension and temperature, affect biological membrane fusion by lowering the associated energy barrier. This has inspired the development of physical approaches to harness the fusion process at a single cell level by using remotely controlled electromagnetic fields to trigger membrane fusion. Here, we critically review various approaches, based on lasers or electric pulses, to control fusion between individual cells or between individual lipid vesicles and discuss their potential and limitations for present and future applications within biochemistry, biology and soft matter.

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.

Using Nonlinear Stochastic Evolutionary Game Strategy to Model an Evolutionary Biological Network of Organ Carcinogenesis Under a Natural Selection Scheme

PubMed Central

Chen, Bor-Sen; Tsai, Kun-Wei; Li, Cheng-Wei

2015-01-01

Molecular biologists have long recognized carcinogenesis as an evolutionary process that involves natural selection. Cancer is driven by the somatic evolution of cell lineages. In this study, the evolution of somatic cancer cell lineages during carcinogenesis was modeled as an equilibrium point (ie, phenotype of attractor) shifting, the process of a nonlinear stochastic evolutionary biological network. This process is subject to intrinsic random fluctuations because of somatic genetic and epigenetic variations, as well as extrinsic disturbances because of carcinogens and stressors. In order to maintain the normal function (ie, phenotype) of an evolutionary biological network subjected to random intrinsic fluctuations and extrinsic disturbances, a network robustness scheme that incorporates natural selection needs to be developed. This can be accomplished by selecting certain genetic and epigenetic variations to modify the network structure to attenuate intrinsic fluctuations efficiently and to resist extrinsic disturbances in order to maintain the phenotype of the evolutionary biological network at an equilibrium point (attractor). However, during carcinogenesis, the remaining (or neutral) genetic and epigenetic variations accumulate, and the extrinsic disturbances become too large to maintain the normal phenotype at the desired equilibrium point for the nonlinear evolutionary biological network. Thus, the network is shifted to a cancer phenotype at a new equilibrium point that begins a new evolutionary process. In this study, the natural selection scheme of an evolutionary biological network of carcinogenesis was derived from a robust negative feedback scheme based on the nonlinear stochastic Nash game strategy. The evolvability and phenotypic robustness criteria of the evolutionary cancer network were also estimated by solving a Hamilton–Jacobi inequality – constrained optimization problem. The simulation revealed that the phenotypic shift of the lung cancer-associated cell network takes 54.5 years from a normal state to stage I cancer, 1.5 years from stage I to stage II cancer, and 2.5 years from stage II to stage III cancer, with a reasonable match for the statistical result of the average age of lung cancer. These results suggest that a robust negative feedback scheme, based on a stochastic evolutionary game strategy, plays a critical role in an evolutionary biological network of carcinogenesis under a natural selection scheme. PMID:26244004

Decoding the Heart through Next Generation Sequencing Approaches.

PubMed

Pawlak, Michal; Niescierowicz, Katarzyna; Winata, Cecilia Lanny

2018-06-07

: Vertebrate organs develop through a complex process which involves interaction between multiple signaling pathways at the molecular, cell, and tissue levels. Heart development is an example of such complex process which, when disrupted, results in congenital heart disease (CHD). This complexity necessitates a holistic approach which allows the visualization of genome-wide interaction networks, as opposed to assessment of limited subsets of factors. Genomics offers a powerful solution to address the problem of biological complexity by enabling the observation of molecular processes at a genome-wide scale. The emergence of next generation sequencing (NGS) technology has facilitated the expansion of genomics, increasing its output capacity and applicability in various biological disciplines. The application of NGS in various aspects of heart biology has resulted in new discoveries, generating novel insights into this field of study. Here we review the contributions of NGS technology into the understanding of heart development and its disruption reflected in CHD and discuss how emerging NGS based methodologies can contribute to the further understanding of heart repair.

Super-resolution and super-localization microscopy: A novel tool for imaging chemical and biological processes

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

Dong, Bin

2015-01-01

Optical microscopy imaging of single molecules and single particles is an essential method for studying fundamental biological and chemical processes at the molecular and nanometer scale. The best spatial resolution (~ λ/2) achievable in traditional optical microscopy is governed by the diffraction of light. However, single molecule-based super-localization and super-resolution microscopy imaging techniques have emerged in the past decade. Individual molecules can be localized with nanometer scale accuracy and precision for studying of biological and chemical processes.This work uncovered the heterogeneous properties of the pore structures. In this dissertation, the coupling of molecular transport and catalytic reaction at the singlemore » molecule and single particle level in multilayer mesoporous nanocatalysts was elucidated. Most previous studies dealt with these two important phenomena separately. A fluorogenic oxidation reaction of non-fluorescent amplex red to highly fluorescent resorufin was tested. The diffusion behavior of single resorufin molecules in aligned nanopores was studied using total internal reflection fluorescence microscopy (TIRFM).« less

[Construction of research system for processing mechanism of traditional Chinese medicine based on chemical composition transformation combined with intestinal absorption barrier].

PubMed

Sun, E; Xu, Feng-Juan; Zhang, Zhen-Hai; Wei, Ying-Jie; Tan, Xiao-Bin; Cheng, Xu-Dong; Jia, Xiao-Bin

2014-02-01

Based on practice of Epimedium processing mechanism for many years and integrated multidisciplinary theory and technology, this paper initially constructs the research system for processing mechanism of traditional Chinese medicine based on chemical composition transformation combined with intestinal absorption barrier, which to form an innovative research mode of the " chemical composition changes-biological transformation-metabolism in vitro and in vivo-intestinal absorption-pharmacokinetic combined pharmacodynamic-pharmacodynamic mechanism". Combined with specific examples of Epimedium and other Chinese herbal medicine processing mechanism, this paper also discusses the academic thoughts, research methods and key technologies of this research system, which will be conducive to systematically reveal the modem scientific connotation of traditional Chinese medicine processing, and enrich the theory of Chinese herbal medicine processing.

Endoscopic ultrasound-guided fine-needle aspiration with liquid-based cytologic preparation in the diagnosis of primary pancreatic lymphoma.

PubMed

Rossi, Esther Diana; Larghi, Alberto; Verna, Elizabeth C; Martini, Maurizio; Galasso, Domenico; Carnuccio, Antonella; Larocca, Luigi Maria; Costamagna, Guido; Fadda, Guido

2010-11-01

The diagnosis subtyping of lymphoma on specimens collected by endoscopic ultrasound fine-needle aspiration (EUS-FNA) can be extremely difficult. When a cytopathologist is available for the on-site evaluation, the diagnosis may be achieved by applying flow cytometric techniques. We describe our experience with immunocytochemistry (ICC) and molecular biology studies applied on EUS-FNA specimens processed with a liquid-based cytologic (LBC) preparation for the diagnosis of primary pancreatic lymphoma (PPL). Three patients with a pancreatic mass underwent EUS-FNA. The collected specimens were processed with the ThinPrep method for the cytologic diagnosis and eventual additional investigations. A morphologic picture consistent with PPL was found on the LBC specimens of the 3 patients. Subsequent ICC and molecular biology studies for immunoglobulin heavy chain gene rearrangement established the diagnosis of pancreatic large B-cell non-Hodgkin lymphoma in 2 patients and a non-Hodgkin lymphoma with plasmoblastic/immunoblastic differentiation in the remaining one. An LBC preparation can be used to diagnose and subtype PPL by applying ICC and molecular biology techniques to specimens collected with EUS-FNA. This method can be an additional processing method for EUS-FNA specimens in centers where on-site cytopathologist expertise is not available.

The southern plains LTAR watershed research program

Treesearch

Patrick Starks; Jean L. Steiner

2016-01-01

Water connects physical, biological, chemical, ecological, and economic forces across the landscape. While hydrologic processes and scientific investigations related to sustainable agricultural systems are based on universal principles, research to understand processes and evaluate management practices is often site-specific in order to achieve a critical mass of...

Assessing Inquiry Process Skills in the Lab Using a Fast, Simple, Inexpensive Fermentation Model System

ERIC Educational Resources Information Center

Knabb, Maureen T.; Misquith, Geraldine

2006-01-01

Incorporating inquiry-based learning in the college-level introductory biology laboratory is challenging because the labs serve the dual purpose of providing a hands-on opportunity to explore content while also emphasizing the development of scientific process skills. Time limitations and variations in student preparedness for college further…

Logging the Heart with Microcomputer-Based Labs

ERIC Educational Resources Information Center

van Eijck, Michiel; Goedhart, Martin; Ellermeijer, Ton

2005-01-01

A single heartbeat is a complicated process. In Dutch upper secondary biology textbooks this process is illustrated by the classical Wiggers diagram, which usually shows different heart-related quantities, like voltage (ECG), blood pressure, and the heart sounds. It may help students to understand the nature of the Wiggers diagram if they perform…

Use of micro computed-tomography and 3D printing for reverse engineering of mouse embryo nasal capsule

NASA Astrophysics Data System (ADS)

Tesařová, M.; Zikmund, T.; Kaucká, M.; Adameyko, I.; Jaroš, J.; Paloušek, D.; Škaroupka, D.; Kaiser, J.

2016-03-01

Imaging of increasingly complex cartilage in vertebrate embryos is one of the key tasks of developmental biology. This is especially important to study shape-organizing processes during initial skeletal formation and growth. Advanced imaging techniques that are reflecting biological needs give a powerful impulse to push the boundaries of biological visualization. Recently, techniques for contrasting tissues and organs have improved considerably, extending traditional 2D imaging approaches to 3D . X-ray micro computed tomography (μCT), which allows 3D imaging of biological objects including their internal structures with a resolution in the micrometer range, in combination with contrasting techniques seems to be the most suitable approach for non-destructive imaging of embryonic developing cartilage. Despite there are many software-based ways for visualization of 3D data sets, having a real solid model of the studied object might give novel opportunities to fully understand the shape-organizing processes in the developing body. In this feasibility study we demonstrated the full procedure of creating a real 3D object of mouse embryo nasal capsule, i.e. the staining, the μCT scanning combined by the advanced data processing and the 3D printing.

The peripheral blood proteome signature of idiopathic pulmonary fibrosis is distinct from normal and is associated with novel immunological processes.

PubMed

O'Dwyer, David N; Norman, Katy C; Xia, Meng; Huang, Yong; Gurczynski, Stephen J; Ashley, Shanna L; White, Eric S; Flaherty, Kevin R; Martinez, Fernando J; Murray, Susan; Noth, Imre; Arnold, Kelly B; Moore, Bethany B

2017-04-25

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial pneumonia. The disease pathophysiology is poorly understood and the etiology remains unclear. Recent advances have generated new therapies and improved knowledge of the natural history of IPF. These gains have been brokered by advances in technology and improved insight into the role of various genes in mediating disease, but gene expression and protein levels do not always correlate. Thus, in this paper we apply a novel large scale high throughput aptamer approach to identify more than 1100 proteins in the peripheral blood of well-characterized IPF patients and normal volunteers. We use systems biology approaches to identify a unique IPF proteome signature and give insight into biological processes driving IPF. We found IPF plasma to be altered and enriched for proteins involved in defense response, wound healing and protein phosphorylation when compared to normal human plasma. Analysis also revealed a minimal protein signature that differentiated IPF patients from normal controls, which may allow for accurate diagnosis of IPF based on easily-accessible peripheral blood. This report introduces large scale unbiased protein discovery analysis to IPF and describes distinct biological processes that further inform disease biology.

Metabolic profiling of body fluids and multivariate data analysis.

PubMed

Trezzi, Jean-Pierre; Jäger, Christian; Galozzi, Sara; Barkovits, Katalin; Marcus, Katrin; Mollenhauer, Brit; Hiller, Karsten

2017-01-01

Metabolome analyses of body fluids are challenging due pre-analytical variations, such as pre-processing delay and temperature, and constant dynamical changes of biochemical processes within the samples. Therefore, proper sample handling starting from the time of collection up to the analysis is crucial to obtain high quality samples and reproducible results. A metabolomics analysis is divided into 4 main steps: 1) Sample collection, 2) Metabolite extraction, 3) Data acquisition and 4) Data analysis. Here, we describe a protocol for gas chromatography coupled to mass spectrometry (GC-MS) based metabolic analysis for biological matrices, especially body fluids. This protocol can be applied on blood serum/plasma, saliva and cerebrospinal fluid (CSF) samples of humans and other vertebrates. It covers sample collection, sample pre-processing, metabolite extraction, GC-MS measurement and guidelines for the subsequent data analysis. Advantages of this protocol include: •Robust and reproducible metabolomics results, taking into account pre-analytical variations that may occur during the sampling process•Small sample volume required•Rapid and cost-effective processing of biological samples•Logistic regression based determination of biomarker signatures for in-depth data analysis.

Simulation of CNT-AFM tip based on finite element analysis for targeted probe of the biological cell

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

Yousefi, Amin Termeh, E-mail: at.tyousefi@gmail.com; Miyake, Mikio, E-mail: miyakejaist@gmail.com; Ikeda, Shoichiro, E-mail: sho16.ikeda@gmail.com

Carbon nanotubes (CNTs) are potentially ideal tips for atomic force microscopy (AFM) due to the robust mechanical properties, nano scale diameter and also their ability to be functionalized by chemical and biological components at the tip ends. This contribution develops the idea of using CNTs as an AFM tip in computational analysis of the biological cell’s. Finite element analysis employed for each section and displacement of the nodes located in the contact area was monitored by using an output database (ODB). This reliable integration of CNT-AFM tip process provides a new class of high performance nanoprobes for single biological cellmore » analysis.« less

Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation and Completion of Episodic Information.

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

Aimone, James Bradley; Bernard, Michael Lewis; Vineyard, Craig Michael

2014-10-01

Adult neurogenesis in the hippocampus region of the brain is a neurobiological process that is believed to contribute to the brain's advanced abilities in complex pattern recognition and cognition. Here, we describe how realistic scale simulations of the neurogenesis process can offer both a unique perspective on the biological relevance of this process and confer computational insights that are suggestive of novel machine learning techniques. First, supercomputer based scaling studies of the neurogenesis process demonstrate how a small fraction of adult-born neurons have a uniquely larger impact in biologically realistic scaled networks. Second, we describe a novel technical approach bymore » which the information content of ensembles of neurons can be estimated. Finally, we illustrate several examples of broader algorithmic impact of neurogenesis, including both extending existing machine learning approaches and novel approaches for intelligent sensing.« less

Cancer Cell Biology: A Student-Centered Instructional Module Exploring the Use of Multimedia to Enrich Interactive, Constructivist Learning of Science

PubMed Central

Bockholt, Susanne M.; West, J. Paige; Bollenbacher, Walter E.

2003-01-01

Multimedia has the potential of providing bioscience education novel learning environments and pedagogy applications to foster student interest, involve students in the research process, advance critical thinking/problem-solving skills, and develop conceptual understanding of biological topics. Cancer Cell Biology, an interactive, multimedia, problem-based module, focuses on how mutations in protooncogenes and tumor suppressor genes can lead to uncontrolled cell proliferation by engaging students as research scientists/physicians with the task of diagnosing the molecular basis of tumor growth for a group of patients. The process of constructing the module, which was guided by scientist and student feedback/responses, is described. The completed module and insights gained from its development are presented as a potential “multimedia pedagogy” for the development of other multimedia science learning environments. PMID:12822037

RuleGO: a logical rules-based tool for description of gene groups by means of Gene Ontology

PubMed Central

Gruca, Aleksandra; Sikora, Marek; Polanski, Andrzej

2011-01-01

Genome-wide expression profiles obtained with the use of DNA microarray technology provide abundance of experimental data on biological and molecular processes. Such amount of data need to be further analyzed and interpreted in order to obtain biological conclusions on the basis of experimental results. The analysis requires a lot of experience and is usually time-consuming process. Thus, frequently various annotation databases are used to improve the whole process of analysis. Here, we present RuleGO—the web-based application that allows the user to describe gene groups on the basis of logical rules that include Gene Ontology (GO) terms in their premises. Presented application allows obtaining rules that reflect coappearance of GO-terms describing genes supported by the rules. The ontology level and number of coappearing GO-terms is adjusted in automatic manner. The user limits the space of possible solutions only. The RuleGO application is freely available at http://rulego.polsl.pl/. PMID:21715384

Design control considerations for biologic-device combination products.

PubMed

Anderson, Dave; Liu, Roger; Anand Subramony, J; Cammack, Jon

2017-03-01

Combination products are therapeutic and diagnostic medical products that combine drugs, devices, and/or biological products with one another. Historically, biologics development involved identifying efficacious doses administered to patients intravenously or perhaps by a syringe. Until fairly recently, there has been limited focus on developing an accompanying medical device, such as a prefilled syringe or auto-injector, to enable easy and more efficient delivery. For the last several years, and looking forward, where there may be little to distinguish biologics medicines with relatively similar efficacy profiles, the biotechnology market is beginning to differentiate products by patient-focused, biologic-device based combination products. As innovative as biologic-device combination products are, they can pose considerable development, regulatory, and commercialization challenges due to unique physicochemical properties and special clinical considerations (e.g., dosing volumes, frequency, co-medications, etc.) of the biologic medicine. A biologic-device combination product is a marriage between two partners with "cultural differences," so to speak. There are clear differences in the development, review, and commercialization processes of the biologic and the device. When these two cultures come together in a combination product, developers and reviewers must find ways to address the design controls and risk management processes of both the biologic and device, and knit them into a single entity with supporting product approval documentation. Moreover, digital medicine and connected health trends are pushing the boundaries of combination product development and regulations even further. Despite an admirable cooperation between industry and FDA in recent years, unique product configurations and design features have resulted in review challenges. These challenges have prompted agency reviewers to modernize consultation processes, while at the same time, promoting development of innovative, safe and effective combination products. It remains the manufacturer's responsibility to comply with the relevant requirements and regulations, and develop good business practices that clearly describe how these practices comply with FDA's final rule (21 CFR Part 4) and aligns with the company's already established quality system. Copyright © 2017 Elsevier B.V. All rights reserved.

A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy.

PubMed

Haworth, Annette; Mears, Christopher; Betts, John M; Reynolds, Hayley M; Tack, Guido; Leo, Kevin; Williams, Scott; Ebert, Martin A

2016-01-07

Treatment plans for ten patients, initially treated with a conventional approach to low dose-rate brachytherapy (LDR, 145 Gy to entire prostate), were compared with plans for the same patients created with an inverse-optimisation planning process utilising a biologically-based objective. The 'biological optimisation' considered a non-uniform distribution of tumour cell density through the prostate based on known and expected locations of the tumour. Using dose planning-objectives derived from our previous biological-model validation study, the volume of the urethra receiving 125% of the conventional prescription (145 Gy) was reduced from a median value of 64% to less than 8% whilst maintaining high values of TCP. On average, the number of planned seeds was reduced from 85 to less than 75. The robustness of plans to random seed displacements needs to be carefully considered when using contemporary seed placement techniques. We conclude that an inverse planning approach to LDR treatments, based on a biological objective, has the potential to maintain high rates of tumour control whilst minimising dose to healthy tissue. In future, the radiobiological model will be informed using multi-parametric MRI to provide a personalised medicine approach.

A radiobiology-based inverse treatment planning method for optimisation of permanent l-125 prostate implants in focal brachytherapy

NASA Astrophysics Data System (ADS)

Haworth, Annette; Mears, Christopher; Betts, John M.; Reynolds, Hayley M.; Tack, Guido; Leo, Kevin; Williams, Scott; Ebert, Martin A.

2016-01-01

Treatment plans for ten patients, initially treated with a conventional approach to low dose-rate brachytherapy (LDR, 145 Gy to entire prostate), were compared with plans for the same patients created with an inverse-optimisation planning process utilising a biologically-based objective. The ‘biological optimisation’ considered a non-uniform distribution of tumour cell density through the prostate based on known and expected locations of the tumour. Using dose planning-objectives derived from our previous biological-model validation study, the volume of the urethra receiving 125% of the conventional prescription (145 Gy) was reduced from a median value of 64% to less than 8% whilst maintaining high values of TCP. On average, the number of planned seeds was reduced from 85 to less than 75. The robustness of plans to random seed displacements needs to be carefully considered when using contemporary seed placement techniques. We conclude that an inverse planning approach to LDR treatments, based on a biological objective, has the potential to maintain high rates of tumour control whilst minimising dose to healthy tissue. In future, the radiobiological model will be informed using multi-parametric MRI to provide a personalised medicine approach.

Drawing-to-Learn: A Framework for Using Drawings to Promote Model-Based Reasoning in Biology

PubMed Central

Quillin, Kim; Thomas, Stephen

2015-01-01

The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report’s Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. PMID:25713094

Systems Biology of Recombinant Protein Production in Bacillus megaterium

NASA Astrophysics Data System (ADS)

Biedendieck, Rebekka; Bunk, Boyke; Fürch, Tobias; Franco-Lara, Ezequiel; Jahn, Martina; Jahn, Dieter

Over the last two decades the Gram-positive bacterium Bacillus megaterium was systematically developed to a useful alternative protein production host. Multiple vector systems for high yield intra- and extracellular protein production were constructed. Strong inducible promoters were combined with DNA sequences for optimised ribosome binding sites, various leader peptides for protein export and N- as well as C-terminal affinity tags for affinity chromatographic purification of the desired protein. High cell density cultivation and recombinant protein production were successfully tested. For further system biology based control and optimisation of the production process the genomes of two B. megaterium strains were completely elucidated, DNA arrays designed, proteome, fluxome and metabolome analyses performed and all data integrated using the bioinformatics platform MEGABAC. Now, solid theoretical and experimental bases for primary modeling attempts of the production process are available.

2-Keto acids based biosynthesis pathways for renewable fuels and chemicals.

PubMed

Tashiro, Yohei; Rodriguez, Gabriel M; Atsumi, Shota

2015-03-01

Global energy and environmental concerns have driven the development of biological chemical production from renewable sources. Biological processes using microorganisms are efficient and have been traditionally utilized to convert biomass (i.e., glucose) to useful chemicals such as amino acids. To produce desired fuels and chemicals with high yield and rate, metabolic pathways have been enhanced and expanded with metabolic engineering and synthetic biology approaches. 2-Keto acids, which are key intermediates in amino acid biosynthesis, can be converted to a wide range of chemicals. 2-Keto acid pathways were engineered in previous research efforts and these studies demonstrated that 2-keto acid pathways have high potential for novel metabolic routes with high productivity. In this review, we discuss recently developed 2-keto acid-based pathways.

Small-scale laser based electron accelerators for biology and medicine: a comparative study of the biological effectiveness

NASA Astrophysics Data System (ADS)

Labate, Luca; Andreassi, Maria Grazia; Baffigi, Federica; Basta, Giuseppina; Bizzarri, Ranieri; Borghini, Andrea; Candiano, Giuliana C.; Casarino, Carlo; Cresci, Monica; Di Martino, Fabio; Fulgentini, Lorenzo; Ghetti, Francesco; Gilardi, Maria Carla; Giulietti, Antonio; Köster, Petra; Lenci, Francesco; Levato, Tadzio; Oishi, Yuji; Russo, Giorgio; Sgarbossa, Antonella; Traino, Claudio; Gizzi, Leonida A.

2013-05-01

Laser-driven electron accelerators based on the Laser Wakefield Acceleration process has entered a mature phase to be considered as alternative devices to conventional radiofrequency linear accelerators used in medical applications. Before entering the medical practice, however, deep studies of the radiobiological effects of such short bunches as the ones produced by laser-driven accelerators have to be performed. Here we report on the setup, characterization and first test of a small-scale laser accelerator for radiobiology experiments. A brief description of the experimental setup will be given at first, followed by an overview of the electron bunch characterization, in particular in terms of dose delivered to the samples. Finally, the first results from the irradiation of biological samples will be briefly discussed.

GEOMetaCuration: a web-based application for accurate manual curation of Gene Expression Omnibus metadata

PubMed Central

Li, Zhao; Li, Jin; Yu, Peng

2018-01-01

Abstract Metadata curation has become increasingly important for biological discovery and biomedical research because a large amount of heterogeneous biological data is currently freely available. To facilitate efficient metadata curation, we developed an easy-to-use web-based curation application, GEOMetaCuration, for curating the metadata of Gene Expression Omnibus datasets. It can eliminate mechanical operations that consume precious curation time and can help coordinate curation efforts among multiple curators. It improves the curation process by introducing various features that are critical to metadata curation, such as a back-end curation management system and a curator-friendly front-end. The application is based on a commonly used web development framework of Python/Django and is open-sourced under the GNU General Public License V3. GEOMetaCuration is expected to benefit the biocuration community and to contribute to computational generation of biological insights using large-scale biological data. An example use case can be found at the demo website: http://geometacuration.yubiolab.org. Database URL: https://bitbucket.com/yubiolab/GEOMetaCuration PMID:29688376

[Valorization of biological resources in tumour libraries].

PubMed

Keelaghan, Thérèse

2006-01-01

The transfer and commercialization of biological materials, whether in the form of tumour samples, tissue samples or chemicals, and of the data base pertaining to such material have become a subject of considerable importance for both the private and public sectors involved in medical research. In order to fully appreciate and apprehend the process for the protection and the valuation of the transferred material, intellectual property law must be taken into account. As a result, a distinction is made between the tangible and intangible elements of the biological material and of the attached data base, thus providing the transferring entity the possibility to claim property rights to future intellectual property arising from the research regarding the transferred material. The transfer of biological material and attached data base without such contractual provisions can lead to the loss of this potential value as well as of physical and legal control over the material transferred by the providing entity. The intentions and the assumptions of the parties must be negotiated and written into terms of contract, at the risk of losing future value due to unexpressed assumptions concerning intangible property rights.

Synthesis, characterization and toxicity studies of pyridinecarboxaldehydes and L-tryptophan derived Schiff bases and corresponding copper (II) complexes.

PubMed

Malakyan, Margarita; Babayan, Nelly; Grigoryan, Ruzanna; Sarkisyan, Natalya; Tonoyan, Vahan; Tadevosyan, Davit; Matosyan, Vladimir; Aroutiounian, Rouben; Arakelyan, Arsen

2016-01-01

Schiff bases and their metal-complexes are versatile compounds exhibiting a broad range of biological activities and thus actively used in the drug development process. The aim of the present study was the synthesis and characterization of new Schiff bases and their copper (II) complexes, derived from L-tryptophan and isomeric (2-; 3-; 4-) pyridinecarboxaldehydes, as well as the assessment of their toxicity in vitro . The optimal conditions of the Schiff base synthesis resulting in up to 75-85% yield of target products were identified. The structure-activity relationship analysis indicated that the location of the carboxaldehyde group at 2-, 3- or 4-position with regard to nitrogen of the pyridine ring in aldehyde component of the L-tryptophan derivative Schiff bases and corresponding copper complexes essentially change the biological activity of the compounds. The carboxaldehyde group at 2- and 4-positions leads to the higher cytotoxic activity, than that of at 3-position, and the presence of the copper in the complexes increases the cytotoxicity. Based on toxicity classification data, the compounds with non-toxic profile were identified, which can be used as new entities in the drug development process using Schiff base scaffold.

Synthesis, characterization and toxicity studies of pyridinecarboxaldehydes and L-tryptophan derived Schiff bases and corresponding copper (II) complexes

PubMed Central

Malakyan, Margarita; Babayan, Nelly; Grigoryan, Ruzanna; Sarkisyan, Natalya; Tonoyan, Vahan; Tadevosyan, Davit; Matosyan, Vladimir; Aroutiounian, Rouben; Arakelyan, Arsen

2016-01-01

Schiff bases and their metal-complexes are versatile compounds exhibiting a broad range of biological activities and thus actively used in the drug development process. The aim of the present study was the synthesis and characterization of new Schiff bases and their copper (II) complexes, derived from L-tryptophan and isomeric (2-; 3-; 4-) pyridinecarboxaldehydes, as well as the assessment of their toxicity in vitro. The optimal conditions of the Schiff base synthesis resulting in up to 75-85% yield of target products were identified. The structure-activity relationship analysis indicated that the location of the carboxaldehyde group at 2-, 3- or 4-position with regard to nitrogen of the pyridine ring in aldehyde component of the L-tryptophan derivative Schiff bases and corresponding copper complexes essentially change the biological activity of the compounds. The carboxaldehyde group at 2- and 4-positions leads to the higher cytotoxic activity, than that of at 3-position, and the presence of the copper in the complexes increases the cytotoxicity. Based on toxicity classification data, the compounds with non-toxic profile were identified, which can be used as new entities in the drug development process using Schiff base scaffold. PMID:28344771

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.

Advancing metabolic engineering through systems biology of industrial microorganisms.

PubMed

Dai, Zongjie; Nielsen, Jens

2015-12-01

Development of sustainable processes to produce bio-based compounds is necessary due to the severe environmental problems caused by the use of fossil resources. Metabolic engineering can facilitate the development of highly efficient cell factories to produce these compounds from renewable resources. The objective of systems biology is to gain a comprehensive and quantitative understanding of living cells and can hereby enhance our ability to characterize and predict cellular behavior. Systems biology of industrial microorganisms is therefore valuable for metabolic engineering. Here we review the application of systems biology tools for the identification of metabolic engineering targets which may lead to reduced development time for efficient cell factories. Finally, we present some perspectives of systems biology for advancing metabolic engineering further. Copyright © 2015 Elsevier Ltd. All rights reserved.

Teaching Electrostatics and Entropy in Introductory Physics

NASA Astrophysics Data System (ADS)

Reeves, Mark

Entropy changes underlie the physics that dominates biological interactions. Indeed, introductory biology courses often begin with an exploration of the qualities of water that are important to living systems. However, one idea that is not explicitly addressed in most introductory physics or biology courses is important contribution of the entropy in driving fundamental biological processes towards equilibrium. I will present material developed to teach electrostatic screening in solutions and the function of nerve cells where entropic effects act to counterbalance electrostatic attraction. These ideas are taught in an introductory, calculus-based physics course to biomedical engineers using SCALEUP pedagogy. Results of student mastering of complex problems that cross disciplinary boundaries between biology and physics, as well as the challenges that they face in learning this material will be presented.

The relativity of biological function.

PubMed

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

2015-12-01

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

Synthetic Biology and Microbial Fuel Cells: Towards Self-Sustaining Life Support Systems

NASA Technical Reports Server (NTRS)

Hogan, John Andrew

2014-01-01

NASA ARC and the J. Craig Venter Institute (JCVI) collaborated to investigate the development of advanced microbial fuels cells (MFCs) for biological wastewater treatment and electricity production (electrogenesis). Synthetic biology techniques and integrated hardware advances were investigated to increase system efficiency and robustness, with the intent of increasing power self-sufficiency and potential product formation from carbon dioxide. MFCs possess numerous advantages for space missions, including rapid processing, reduced biomass and effective removal of organics, nitrogen and phosphorus. Project efforts include developing space-based MFC concepts, integration analyses, increasing energy efficiency, and investigating novel bioelectrochemical system applications

Molecular profiles to biology and pathways: a systems biology approach.

PubMed

Van Laere, Steven; Dirix, Luc; Vermeulen, Peter

2016-06-16

Interpreting molecular profiles in a biological context requires specialized analysis strategies. Initially, lists of relevant genes were screened to identify enriched concepts associated with pathways or specific molecular processes. However, the shortcoming of interpreting gene lists by using predefined sets of genes has resulted in the development of novel methods that heavily rely on network-based concepts. These algorithms have the advantage that they allow a more holistic view of the signaling properties of the condition under study as well as that they are suitable for integrating different data types like gene expression, gene mutation, and even histological parameters.

What's that gene (or protein)? Online resources for exploring functions of genes, transcripts, and proteins

PubMed Central

Hutchins, James R. A.

2014-01-01

The genomic era has enabled research projects that use approaches including genome-scale screens, microarray analysis, next-generation sequencing, and mass spectrometry–based proteomics to discover genes and proteins involved in biological processes. Such methods generate data sets of gene, transcript, or protein hits that researchers wish to explore to understand their properties and functions and thus their possible roles in biological systems of interest. Recent years have seen a profusion of Internet-based resources to aid this process. This review takes the viewpoint of the curious biologist wishing to explore the properties of protein-coding genes and their products, identified using genome-based technologies. Ten key questions are asked about each hit, addressing functions, phenotypes, expression, evolutionary conservation, disease association, protein structure, interactors, posttranslational modifications, and inhibitors. Answers are provided by presenting the latest publicly available resources, together with methods for hit-specific and data set–wide information retrieval, suited to any genome-based analytical technique and experimental species. The utility of these resources is demonstrated for 20 factors regulating cell proliferation. Results obtained using some of these are discussed in more depth using the p53 tumor suppressor as an example. This flexible and universally applicable approach for characterizing experimental hits helps researchers to maximize the potential of their projects for biological discovery. PMID:24723265

Validating Experimental Bedform Dynamics on Cohesive Sand-Mud Beds in the Dee Estuary

NASA Astrophysics Data System (ADS)

Baas, Jaco H.; Baker, Megan; Hope, Julie; Malarkey, Jonathan; Rocha, Renata

2014-05-01

Recent laboratory experiments and field measurements have shown that small quantities of cohesive clay, and in particular 'sticky' biological polymers, within a sandy substrate dramatically reduce the development rate of sedimentary bedforms, with major implications for sediment transport rate calculations and process interpretations from the sedimentary record. FURTHER INFORMATION Flow and sediment transport predictions from sedimentary structures found in modern estuaries and within estuarine geological systems are impeded by an almost complete lack of process-based knowledge of the behaviour of natural sediments that consist of mixtures of cohesionless sand and biologically-active cohesive mud. Indeed, existing predictive models are largely based on non-organic cohesionless sands, despite the fact that mud, in pure form or mixed with sand, is the most common sediment on Earth and also the most biologically active interface across a range of Earth-surface environments, including rivers and shallow seas. The multidisciplinary COHBED project uses state-of-the-art laboratory and field technologies to measure the erosional properties of mixed cohesive sediment beds and the formation and stability of sedimentary bedforms on these beds, integrating the key physical and biological processes that govern bed evolution. The development of current ripples on cohesive mixed sediment beds was investigated as a function of physical control on bed cohesion versus biological control on bed cohesion. These investigations included laboratory flume experiments in the Hydrodynamics Laboratory (Bangor University) and field experiments in the Dee estuary (at West Kirby near Liverpool). The flume experiments showed that winnowing of fine-grained cohesive sediment, including biological stabilisers, is an important process affecting the development rate, size and shape of the cohesive bedforms. The ripples developed progressively slower as the kaolin clay fraction in the sandy substrate bed was increased. The same result was obtained for xanthan gum, which is a proxy for biological polymers produced by microphytobenthos. Yet, the xanthan gum was several orders more effective in slowing down ripple development than kaolin clay, suggesting that the cohesive forces for biological polymers are much higher than for clay minerals, and that sedimentological process models should refocus on biostabilisation processes. The first results of the field experiments show that the winnowing of fines from developing ripples and the slowing down of current ripple development in mixed cohesive sediment is mimicked on intertidal flats in the Dee estuary. In particular, these field data revealed that current ripples in cohesive sediment are smaller with more two-dimensional crestlines than in non-cohesive sand. The wider implications of these findings will be discussed. COHBED Project Team (NERC): Alan Davies (Bangor University); Daniel Parsons, Leiping Ye (University of Hull); Jeffrey Peakall (University of Leeds); Dougal Lichtman, Louise O'Boyle, Peter Thorne (NOC Liverpool); Sarah Bass, Andrew Manning, Robert Schindler (University of Plymouth); Rebecca Aspden, Emma Defew, Julie Hope, David Paterson (University of St Andrews)

Effects of biological sex on the pathophysiology of the heart

PubMed Central

Fazal, Loubina; Azibani, Feriel; Vodovar, Nicolas; Cohen Solal, Alain; Delcayre, Claude; Samuel, Jane-Lise

2014-01-01

Cardiovascular diseases are the leading causes of death in men and women in industrialized countries. While the effects of biological sex on cardiovascular pathophysiology have long been known, the sex-specific mechanisms mediating these processes have been further elucidated over recent years. This review aims at analysing the sex-based differences in cardiac structure and function in adult mammals, and the sex-based differences in the main molecular mechanisms involved in the response of the heart to pathological situations. It emerged from this review that the sex-based difference is a variable that should be dealt with, not only in basic science or clinical research, but also with regards to therapeutic approaches. PMID:23763376

Carbon footprint of aerobic biological treatment of winery wastewater.

PubMed

Rosso, D; Bolzonella, D

2009-01-01

The carbon associated with wastewater and its treatment accounts for approximately 6% of the global carbon balance. Within the wastewater treatment industry, winery wastewater has a minor contribution, although it can have a major impact on wine-producing regions. Typically, winery wastewater is treated by biological processes, such as the activated sludge process. Biomass produced during treatment is usually disposed of directly, i.e. without digestion or other anaerobic processes. We applied our previously published model for carbon-footprint calculation to the areas worldwide producing yearly more than 10(6) m(3) of wine (i.e., France, Italy, Spain, California, Argentina, Australia, China, and South Africa). Datasets on wine production from the Food and Agriculture Organisation were processed and wastewater flow rates calculated with assumptions based on our previous experience. Results show that the wine production, hence the calculated wastewater flow, is reported as fairly constant in the period 2005-2007. Nevertheless, treatment process efficiency and energy-conservation may play a significant role on the overall carbon-footprint. We performed a sensitivity analysis on the efficiency of the aeration process (alphaSOTE per unit depth, or alphaSOTE/Z) in the biological treatment operations and showed significant margin for improvement. Our results show that the carbon-footprint reduction via aeration efficiency improvement is in the range of 8.1 to 12.3%.

Gasification of land-based biomass. Final report July 78-December 82

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

Chynoweth, D.P.; Jerger, D.E.; Conrad, J.R.

1983-06-01

The objective of this research was to develop efficient processes for conversion of land-based biomass to methane and other resources. One task was to determine the relative suitability of selected species or feedstocks for biological and thermal gasification processes. The second task was to narrow options for design and operation of the experimental test unit (ETU) on water hyacinth and sludge at Walt Disney World (WDW) and to provide a scientific base for understanding rate- and yield-limiting reactions for biogasification of these feedstocks, (separately and as blends).

Physics-based signal processing algorithms for micromachined cantilever arrays

DOEpatents

Candy, James V; Clague, David S; Lee, Christopher L; Rudd, Robert E; Burnham, Alan K; Tringe, Joseph W

2013-11-19

A method of using physics-based signal processing algorithms for micromachined cantilever arrays. The methods utilize deflection of a micromachined cantilever that represents the chemical, biological, or physical element being detected. One embodiment of the method comprises the steps of modeling the deflection of the micromachined cantilever producing a deflection model, sensing the deflection of the micromachined cantilever and producing a signal representing the deflection, and comparing the signal representing the deflection with the deflection model.

An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data. PMID:23593445

Integrating interactive computational modeling in biology curricula.

PubMed

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

2015-03-01

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

From bench to FDA to bedside: US regulatory trends for new stem cell therapies.

PubMed

Knoepfler, Paul S

2015-03-01

The phrase "bench-to-bedside" is commonly used to describe the translation of basic discoveries such as those on stem cells to the clinic for therapeutic use in human patients. However, there is a key intermediate step in between the bench and the bedside involving governmental regulatory oversight such as by the Food and Drug Administration (FDA) in the United States (US). Thus, it might be more accurate in most cases to describe the stem cell biological drug development process in this way: from bench to FDA to bedside. The intermediate development and regulatory stage for stem cell-based biological drugs is a multifactorial, continually evolving part of the process of developing a biological drug such as a stem cell-based regenerative medicine product. In some situations, stem cell-related products may not be classified as biological drugs in which case the FDA plays a relatively minor role. However, this middle stage is generally a major element of the process and is often colloquially referred to in an ominous way as "The Valley of Death". This moniker seems appropriate because it is at this point, and in particular in the work that ensues after Phase 1, clinical trials that most drug product development is terminated, often due to lack of funding, diseases being refractory to treatment, or regulatory issues. Not surprisingly, workarounds to deal with or entirely avoid this difficult stage of the process are evolving both inside and outside the domains of official regulatory authorities. In some cases these efforts involve the FDA invoking new mechanisms of accelerating the bench to beside process, but in other cases these new pathways bypass the FDA in part or entirely. Together these rapidly changing stem cell product development and regulatory pathways raise many scientific, ethical, and medical questions. These emerging trends and their potential consequences are reviewed here. Copyright © 2014 Elsevier B.V. All rights reserved.

System-based identification of toxicity pathways associated with multi-walled carbon nanotube-induced pathological responses

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

Snyder-Talkington, Brandi N.; Dymacek, Julian; Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506-9300

2013-10-15

The fibrous shape and biopersistence of multi-walled carbon nanotubes (MWCNT) have raised concern over their potential toxicity after pulmonary exposure. As in vivo exposure to MWCNT produced a transient inflammatory and progressive fibrotic response, this study sought to identify significant biological processes associated with lung inflammation and fibrosis pathology data, based upon whole genome mRNA expression, bronchoaveolar lavage scores, and morphometric analysis from C57BL/6J mice exposed by pharyngeal aspiration to 0, 10, 20, 40, or 80 μg MWCNT at 1, 7, 28, or 56 days post-exposure. Using a novel computational model employing non-negative matrix factorization and Monte Carlo Markov Chainmore » simulation, significant biological processes with expression similar to MWCNT-induced lung inflammation and fibrosis pathology data in mice were identified. A subset of genes in these processes was determined to be functionally related to either fibrosis or inflammation by Ingenuity Pathway Analysis and was used to determine potential significant signaling cascades. Two genes determined to be functionally related to inflammation and fibrosis, vascular endothelial growth factor A (vegfa) and C-C motif chemokine 2 (ccl2), were confirmed by in vitro studies of mRNA and protein expression in small airway epithelial cells exposed to MWCNT as concordant with in vivo expression. This study identified that the novel computational model was sufficient to determine biological processes strongly associated with the pathology of lung inflammation and fibrosis and could identify potential toxicity signaling pathways and mechanisms of MWCNT exposure which could be used for future animal studies to support human risk assessment and intervention efforts. - Highlights: • A novel computational model identified toxicity pathways matching in vivo pathology. • Systematic identification of MWCNT-induced biological processes in mouse lungs • MWCNT-induced functional networks of lung inflammation and fibrosis were revealed. • Two functional, representative genes, ccl2 and vegfa, were validated in vitro.« less

From QSAR to QSIIR: Searching for Enhanced Computational Toxicology Models

PubMed Central

Zhu, Hao

2017-01-01

Quantitative Structure Activity Relationship (QSAR) is the most frequently used modeling approach to explore the dependency of biological, toxicological, or other types of activities/properties of chemicals on their molecular features. In the past two decades, QSAR modeling has been used extensively in drug discovery process. However, the predictive models resulted from QSAR studies have limited use for chemical risk assessment, especially for animal and human toxicity evaluations, due to the low predictivity of new compounds. To develop enhanced toxicity models with independently validated external prediction power, novel modeling protocols were pursued by computational toxicologists based on rapidly increasing toxicity testing data in recent years. This chapter reviews the recent effort in our laboratory to incorporate the biological testing results as descriptors in the toxicity modeling process. This effort extended the concept of QSAR to Quantitative Structure In vitro-In vivo Relationship (QSIIR). The QSIIR study examples provided in this chapter indicate that the QSIIR models that based on the hybrid (biological and chemical) descriptors are indeed superior to the conventional QSAR models that only based on chemical descriptors for several animal toxicity endpoints. We believe that the applications introduced in this review will be of interest and value to researchers working in the field of computational drug discovery and environmental chemical risk assessment. PMID:23086837

Corrections to chance fluctuations: quantum mind in biological evolution?

PubMed

Damiani, Giuseppe

2009-01-01

According to neo-Darwinian theory, biological evolution is produced by natural selection of random hereditary variations. This assumption stems from the idea of a mechanical and deterministic world based on the laws of classic physics. However, the increased knowledge of relationships between metabolism, epigenetic systems, and editing of nucleic acids suggests the existence of self-organized processes of adaptive evolution in response to environmental stresses. Living organisms are open thermodynamic systems which use entropic decay of external source of electromagnetic energy to increase their internal dynamic order and to generate new genetic and epigenetic information with a high degree of coherency and teleonomic creativity. Sensing, information processing, and decision making of biological systems might be mainly quantum phenomena. Amplification of microscopic quantum events using the long-range correlation of fractal structures, at the borderline between deterministic order and unpredictable chaos, may be used to direct a reproducible transition of the biological systems towards a defined macroscopic state. The discoveries of many natural genetic engineering systems, the ability to choose the most effective solutions, and the emergence of complex forms of consciousness at different levels confirm the importance of mind-action directed processes in biological evolution, as suggested by Alfred Russel Wallace. Although the main Darwinian principles will remain a crucial component of our understanding of evolution, a radical rethinking of the conceptual structure of the neo-Darwinian theory is needed.

Biological Effects of Atomic Radiations; ACCIONES BIOLOGICAS DE LAS RADIACIONES ATOMICAS

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

Patetta-Queirolo, M.A.

1959-02-01

A resume is presented of each class in a course on the biological effects of nuclear radiations. The topics discussed include the physical and chemical bases of radiation effects, primary and secondary processes, accumulated effects, biochemical and cellular effects, radiation effects on living organisms and tissues, radioecology, genetic effects, cytogenetic effects, genetics of radiation in mammals, response of mammals to irradiation, dosimetry, and protection against radiations. (J.S.R.)

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

Microarray gene-expression study in fibroblast and lymphoblastoid cell lines from antipsychotic-naïve first-episode schizophrenia patients.

PubMed

Gassó, Patricia; Mas, Sergi; Rodríguez, Natalia; Boloc, Daniel; García-Cerro, Susana; Bernardo, Miquel; Lafuente, Amalia; Parellada, Eduard

2017-12-01

Schizophrenia (SZ) is a chronic psychiatric disorder whose onset of symptoms occurs in late adolescence and early adulthood. The etiology is complex and involves important gene-environment interactions. Microarray gene-expression studies on SZ have identified alterations in several biological processes. The heterogeneity in the results can be attributed to the use of different sample types and other important confounding factors including age, illness chronicity and antipsychotic exposure. The aim of the present microarray study was to analyze, for the first time to our knowledge, differences in gene expression profiles in 18 fibroblast (FCLs) and 14 lymphoblastoid cell lines (LCLs) from antipsychotic-naïve first-episode schizophrenia (FES) patients and healthy controls. We used an analytical approach based on protein-protein interaction network construction and functional annotation analysis to identify the biological processes that are altered in SZ. Significant differences in the expression of 32 genes were found when LCLs were assessed. The network and gene set enrichment approach revealed the involvement of similar biological processes in FCLs and LCLs, including apoptosis and related biological terms such as cell cycle, autophagy, cytoskeleton organization and response to stress and stimulus. Metabolism and other processes, including signal transduction, kinase activity and phosphorylation, were also identified. These results were replicated in two independent cohorts using the same analytical approach. This provides more evidence for altered apoptotic processes in antipsychotic-naïve FES patients and other important biological functions such as cytoskeleton organization and metabolism. The convergent results obtained in both peripheral cell models support their usefulness for transcriptome studies on SZ. Copyright © 2017 Elsevier Ltd. All rights reserved.

Database constraints applied to metabolic pathway reconstruction tools.

PubMed

Vilaplana, Jordi; Solsona, Francesc; Teixido, Ivan; Usié, Anabel; Karathia, Hiren; Alves, Rui; Mateo, Jordi

2014-01-01

Our group developed two biological applications, Biblio-MetReS and Homol-MetReS, accessing the same database of organisms with annotated genes. Biblio-MetReS is a data-mining application that facilitates the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (re)annotation of proteomes, to properly identify both the individual proteins involved in the process(es) of interest and their function. It also enables the sets of proteins involved in the process(es) in different organisms to be compared directly. The efficiency of these biological applications is directly related to the design of the shared database. We classified and analyzed the different kinds of access to the database. Based on this study, we tried to adjust and tune the configurable parameters of the database server to reach the best performance of the communication data link to/from the database system. Different database technologies were analyzed. We started the study with a public relational SQL database, MySQL. Then, the same database was implemented by a MapReduce-based database named HBase. The results indicated that the standard configuration of MySQL gives an acceptable performance for low or medium size databases. Nevertheless, tuning database parameters can greatly improve the performance and lead to very competitive runtimes.

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.

Ways of incorporating photographic images in learning and assessing high school biology: A study of visual perception and visual cognition

NASA Astrophysics Data System (ADS)

Nixon, Brenda Chaumont

This study evaluated the cognitive benefits and costs of incorporating biology-textbook and student-generated photographic images into the learning and assessment processes within a 10th grade biology classroom. The study implemented Wandersee's (2000) 20-Q Model of Image-Based Biology Test-Item Design (20-Q Model) to explore the use of photographic images to assess students' understanding of complex biological processes. A thorough review of the students' textbook using ScaleMaster R with PC Interface was also conducted. The photographs, diagrams, and other representations found in the textbook were measured to determine the percentage of each graphic depicted in the book and comparisons were made to the text. The theoretical framework that guided the research included Human Constructivist tenets espoused by Mintzes, Wandersee and Novak (2000). Physiological and cognitive factors of images and image-based learning as described by Robin (1992), Solso (1997) and Wandersee (2000) were examined. Qualitative case study design presented by Yin (1994), Denzin and Lincoln (1994) was applied and data were collected through interviews, observations, student activities, student and school artifacts and Scale Master IIRTM measurements. The results of the study indicate that although 24% of the high school biology textbook is devoted to photographic images which contribute significantly to textbook cost, the teacher and students paid little attention to photographic images other than as aesthetic elements for creating biological ambiance, wasting valuable opportunities for learning. The analysis of the photographs corroborated findings published by the Association American Association for the Advancement of Science that indicated "While most of the books are lavishly illustrated, these representations are rarely helpful, because they are too abstract, needlessly complicated, or inadequately explained" (Roseman, 2000, p. 2). The findings also indicate that applying the 20-Q Model to photographs in biology textbooks can (a) effectively assess students' understanding of complex biological concepts, (b) offer alternative assessment strategies that complement individual learning styles, (c) identify misconceptions, and (d) encourage students to practice metacognition. In addition, once students have learned how to interpret textbook images, application of that knowledge through self-generated biologically relevant digital or print images provides opportunities for increased conceptual understanding.

A Secure Web Application Providing Public Access to High-Performance Data Intensive Scientific Resources - ScalaBLAST Web Application

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

Curtis, Darren S.; Peterson, Elena S.; Oehmen, Chris S.

2008-05-04

This work presents the ScalaBLAST Web Application (SWA), a web based application implemented using the PHP script language, MySQL DBMS, and Apache web server under a GNU/Linux platform. SWA is an application built as part of the Data Intensive Computer for Complex Biological Systems (DICCBS) project at the Pacific Northwest National Laboratory (PNNL). SWA delivers accelerated throughput of bioinformatics analysis via high-performance computing through a convenient, easy-to-use web interface. This approach greatly enhances emerging fields of study in biology such as ontology-based homology, and multiple whole genome comparisons which, in the absence of a tool like SWA, require a heroicmore » effort to overcome the computational bottleneck associated with genome analysis. The current version of SWA includes a user account management system, a web based user interface, and a backend process that generates the files necessary for the Internet scientific community to submit a ScalaBLAST parallel processing job on a dedicated cluster.« less

Fundamentals and Application of Magnetic Particles in Cell Isolation and Enrichment

PubMed Central

Plouffe, Brian D.; Murthy, Shashi K.; Lewis, Laura H.

2014-01-01

Magnetic sorting using magnetic beads has become a routine methodology for the separation of key cell populations from biological suspensions. Due to the inherent ability of magnets to provide forces at a distance, magnetic cell manipulation is now a standardized process step in numerous processes in tissue engineering, medicine, and in fundamental biological research. Herein we review the current status of magnetic particles to enable isolation and separation of cells, with a strong focus on the fundamental governing physical phenomena, properties and syntheses of magnetic particles and on current applications of magnet-based cell separation in laboratory and clinical settings. We highlight the contribution of cell separation to biomedical research and medicine and detail modern cell separation methods (both magnetic and non-magnetic). In addition to a review of the current state-of-the-art in magnet-based cell sorting, we discuss current challenges and available opportunities for further research, development and commercialization of magnetic particle-based cell separation systems. PMID:25471081

A DNA-based pattern classifier with in vitro learning and associative recall for genomic characterization and biosensing without explicit sequence knowledge.

PubMed

Lee, Ju Seok; Chen, Junghuei; Deaton, Russell; Kim, Jin-Woo

2014-01-01

Genetic material extracted from in situ microbial communities has high promise as an indicator of biological system status. However, the challenge is to access genomic information from all organisms at the population or community scale to monitor the biosystem's state. Hence, there is a need for a better diagnostic tool that provides a holistic view of a biosystem's genomic status. Here, we introduce an in vitro methodology for genomic pattern classification of biological samples that taps large amounts of genetic information from all genes present and uses that information to detect changes in genomic patterns and classify them. We developed a biosensing protocol, termed Biological Memory, that has in vitro computational capabilities to "learn" and "store" genomic sequence information directly from genomic samples without knowledge of their explicit sequences, and that discovers differences in vitro between previously unknown inputs and learned memory molecules. The Memory protocol was designed and optimized based upon (1) common in vitro recombinant DNA operations using 20-base random probes, including polymerization, nuclease digestion, and magnetic bead separation, to capture a snapshot of the genomic state of a biological sample as a DNA memory and (2) the thermal stability of DNA duplexes between new input and the memory to detect similarities and differences. For efficient read out, a microarray was used as an output method. When the microarray-based Memory protocol was implemented to test its capability and sensitivity using genomic DNA from two model bacterial strains, i.e., Escherichia coli K12 and Bacillus subtilis, results indicate that the Memory protocol can "learn" input DNA, "recall" similar DNA, differentiate between dissimilar DNA, and detect relatively small concentration differences in samples. This study demonstrated not only the in vitro information processing capabilities of DNA, but also its promise as a genomic pattern classifier that could access information from all organisms in a biological system without explicit genomic information. The Memory protocol has high potential for many applications, including in situ biomonitoring of ecosystems, screening for diseases, biosensing of pathological features in water and food supplies, and non-biological information processing of memory devices, among many.

Patterns of population differentiation of candidate genes for cardiovascular disease.

PubMed

Kullo, Iftikhar J; Ding, Keyue

2007-07-12

The basis for ethnic differences in cardiovascular disease (CVD) susceptibility is not fully understood. We investigated patterns of population differentiation (FST) of a set of genes in etiologic pathways of CVD among 3 ethnic groups: Yoruba in Nigeria (YRI), Utah residents with European ancestry (CEU), and Han Chinese (CHB) + Japanese (JPT). We identified 37 pathways implicated in CVD based on the PANTHER classification and 416 genes in these pathways were further studied; these genes belonged to 6 biological processes (apoptosis, blood circulation and gas exchange, blood clotting, homeostasis, immune response, and lipoprotein metabolism). Genotype data were obtained from the HapMap database. We calculated FST for 15,559 common SNPs (minor allele frequency > or = 0.10 in at least one population) in genes that co-segregated among the populations, as well as an average-weighted FST for each gene. SNPs were classified as putatively functional (non-synonymous and untranslated regions) or non-functional (intronic and synonymous sites). Mean FST values for common putatively functional variants were significantly higher than FST values for nonfunctional variants. A significant variation in FST was also seen based on biological processes; the processes of 'apoptosis' and 'lipoprotein metabolism' showed an excess of genes with high FST. Thus, putative functional SNPs in genes in etiologic pathways for CVD show greater population differentiation than non-functional SNPs and a significant variance of FST values was noted among pairwise population comparisons for different biological processes. These results suggest a possible basis for varying susceptibility to CVD among ethnic groups.

Detergent-Based Isolation of Yeast Membrane Rafts: An Inquiry-Based Laboratory Series for the Undergraduate Cell Biology or Biochemistry Lab

ERIC Educational Resources Information Center

Willhite, D. Grant; Wright, Stephen E.

2009-01-01

Lipid rafts have been implicated in numerous cellular processes including cell signaling, endocytosis, and even viral infection. Isolation of these lipid rafts often involves detergent treatment of the membrane to dissolve nonraft components followed by separation of raft regions in a density gradient. We present here an inquiry-based lab series…

easyDAS: Automatic creation of DAS servers

PubMed Central

2011-01-01

Background The Distributed Annotation System (DAS) has proven to be a successful way to publish and share biological data. Although there are more than 750 active registered servers from around 50 organizations, setting up a DAS server comprises a fair amount of work, making it difficult for many research groups to share their biological annotations. Given the clear advantage that the generalized sharing of relevant biological data is for the research community it would be desirable to facilitate the sharing process. Results Here we present easyDAS, a web-based system enabling anyone to publish biological annotations with just some clicks. The system, available at http://www.ebi.ac.uk/panda-srv/easydas is capable of reading different standard data file formats, process the data and create a new publicly available DAS source in a completely automated way. The created sources are hosted on the EBI systems and can take advantage of its high storage capacity and network connection, freeing the data provider from any network management work. easyDAS is an open source project under the GNU LGPL license. Conclusions easyDAS is an automated DAS source creation system which can help many researchers in sharing their biological data, potentially increasing the amount of relevant biological data available to the scientific community. PMID:21244646

An improved Pearson's correlation proximity-based hierarchical clustering for mining biological association between genes.

PubMed

Booma, P M; Prabhakaran, S; Dhanalakshmi, R

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality.

An Improved Pearson's Correlation Proximity-Based Hierarchical Clustering for Mining Biological Association between Genes

PubMed Central

Booma, P. M.; Prabhakaran, S.; Dhanalakshmi, R.

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality. PMID:25136661

Design and analysis of large-scale biological rhythm studies: a comparison of algorithms for detecting periodic signals in biological data

PubMed Central

Deckard, Anastasia; Anafi, Ron C.; Hogenesch, John B.; Haase, Steven B.; Harer, John

2013-01-01

Motivation: To discover and study periodic processes in biological systems, we sought to identify periodic patterns in their gene expression data. We surveyed a large number of available methods for identifying periodicity in time series data and chose representatives of different mathematical perspectives that performed well on both synthetic data and biological data. Synthetic data were used to evaluate how each algorithm responds to different curve shapes, periods, phase shifts, noise levels and sampling rates. The biological datasets we tested represent a variety of periodic processes from different organisms, including the cell cycle and metabolic cycle in Saccharomyces cerevisiae, circadian rhythms in Mus musculus and the root clock in Arabidopsis thaliana. Results: From these results, we discovered that each algorithm had different strengths. Based on our findings, we make recommendations for selecting and applying these methods depending on the nature of the data and the periodic patterns of interest. Additionally, these results can also be used to inform the design of large-scale biological rhythm experiments so that the resulting data can be used with these algorithms to detect periodic signals more effectively. Contact: anastasia.deckard@duke.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24058056

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

PubMed

Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M

2013-12-16

Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis) whereby the recovered sub-networks reconfirm established plant gene functions and also identify novel associations. Together, we present valuable insights into grapevine transcriptional regulation by developing network models applicable to researchers in their prioritisation of gene candidates, for on-going study of biological processes related to grapevine development, metabolism and stress responses.

Functional proteomic analysis revealed ground-base ion radiations cannot reflect biological effects of space radiations of rice

NASA Astrophysics Data System (ADS)

Wang, Wei; Sun, Yeqing; Zhao, Qian; Han, Lu

2016-07-01

Highly ionizing radiation (HZE) in space is considered as main factor causing biological effects. Radiobiological studies during space flights are unrepeatable due to the variable space radiation environment, ground-base ion radiations are usually performed to simulate of the space biological effect. Spaceflights present a low-dose rate (0.1˜~0.3mGy/day) radiation environment inside aerocrafts while ground-base ion radiations present a much higher dose rate (100˜~500mGy/min). Whether ground-base ion radiation can reflect effects of space radiation is worth of evaluation. In this research, we compared the functional proteomic profiles of rice plants between on-ground simulated HZE particle radiation and spaceflight treatments. Three independent ground-base seed ionizing radiation experiments with different cumulative doses (dose range: 2˜~20000mGy) and different liner energy transfer (LET) values (13.3˜~500keV/μμm) and two independent seed spaceflight experiments onboard Chinese 20th satellite and SZ-6 spacecraft were carried out. Alterations in the proteome were analyzed by two-dimensional difference gel electrophoresis (2-D DIGE) with MALDI-TOF/TOF mass spectrometry identifications. 45 and 59 proteins showed significant (p<0.05) and reproducible quantitative differences in ground-base ion radiation and spaceflight experiments respectively. The functions of ground-base radiation and spaceflight proteins were both involved in a wide range of biological processes. Gene Ontology enrichment analysis further revealed that ground-base radiation responsive proteins were mainly involved in removal of superoxide radicals, defense response to stimulus and photosynthesis, while spaceflight responsive proteins mainly participate in nucleoside metabolic process, protein folding and phosphorylation. The results implied that ground-base radiations cannot truly reflect effects of spaceflight radiations, ground-base radiation was a kind of indirect effect to rice causing oxidation and metabolism stresses, but space radiation was a kind of direct effect leading to macromolecule (DNA and protein) damage and signal pathway disorders. This functional proteomic analysis work might provide a new evaluation method for further on-ground simulated HZE radiation experiments.

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

Oxygen Uptake. Operational Control Tests for Wastewater Treatment Facilities. Instructor's Manual [and] Student Workbook.

ERIC Educational Resources Information Center

Wooley, John F.

Biological waste treatment in the activated sludge process is based on the ability of microorganisms to use dissolved oxygen in breaking down soluble organic substances. The oxygen uptake test is a means of measuring the respiration rate of microorganisms in this process. Designed for individuals who have completed National Pollutant Discharge…

Understanding a Basic Biological Process: Expert and Novice Models of Meiosis.

ERIC Educational Resources Information Center

Kindfield, Ann C. H.

The results of a study of the meiosis models utilized by individuals at varying levels of expertise while reasoning about the process of meiosis are presented. Based on these results, the issues of sources of misconceptions/difficulties and the construction of a sound understanding of meiosis are discussed. Five individuals from each of three…

75 FR 8968 - Draft Guidance for Industry on Adaptive Design Clinical Trials for Drugs and Biologics; Availability

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-26

... the drug development process, it is particularly important to protect study blinding of an adaptive...) and including a description of the responsibilities of each entity involved in the process. Based on... that each SOP will take approximately 30 minutes to document and maintain. B. Perform Simulations and...

Synthetic biology in space: considering the broad societal and ethical implications

NASA Astrophysics Data System (ADS)

Race, Margaret S.; Moses, Jacob; McKay, Christopher; Venkateswaran, Kasthuri J.

2012-02-01

Although the field of synthetic biology is still in its infancy, there are expectations for great advances in the coming decades, both on Earth and potentially in space. Promising applications for long duration space missions include a variety of biologically engineered products and biologically aided processes and technologies, which will undoubtedly be scrutinized for risks and benefits in the broad context of ethical, legal and social realms. By comparing and contrasting features of Earth-based and space-applied synthetic biology, it is possible to identify the likely similarities and differences, and to identify possible challenges ahead for space applications that will require additional research, both in the short and long terms. Using an analytical framework associated with synthetic biology and new technologies on Earth, this paper analyses the kinds of issues and concerns ahead, and identifies those areas where space applications may require additional examination. In general, while Earth- and space-based synthetic biology share many commonalities, space applications have additional challenges such as those raised by space microbiology and environmental factors, legal complications, planetary protection, lack of decision-making infrastructure(s), long duration human missions, terraforming and the possible discovery of extraterrestrial (ET) life. For synthetic biology, the way forward offers many exciting opportunities, but is not without legitimate concerns - for life, environments and society, both on Earth and beyond.

Developing a Teacher Identity: TAs' Perspectives about Learning to Teach Inquiry-Based Biology Labs

ERIC Educational Resources Information Center

Gormally, Cara

2016-01-01

Becoming a teacher involves a continual process of identity development and negotiation. Expectations and norms for particular pedagogies impact and inform this development. In inquiry based classes, instructors are expected to act as learning facilitators rather than information providers. For novice inquiry instructors, developing a teacher…

Information security management system planning for CBRN facilities

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

Lenaeu, Joseph D.; O'Neil, Lori Ross; Leitch, Rosalyn M.

The focus of this document is to provide guidance for the development of information security management system planning documents at chemical, biological, radiological, or nuclear (CBRN) facilities. It describes a risk-based approach for planning information security programs based on the sensitivity of the data developed, processed, communicated, and stored on facility information systems.

Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

PubMed

Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

2016-08-01

The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

Mathematical Simulation of the Process of Aerobic Treatment of Wastewater under Conditions of Diffusion and Mass Transfer Perturbations

NASA Astrophysics Data System (ADS)

Bomba, A. Ya.; Safonik, A. P.

2018-05-01

A mathematical model of the process of aerobic treatment of wastewater has been refined. It takes into account the interaction of bacteria, as well as of organic and biologically nonoxidizing substances under conditions of diffusion and mass transfer perturbations. An algorithm of the solution of the corresponding nonlinear perturbed problem of convection-diffusion-mass transfer type has been constructed, with a computer experiment carried out based on it. The influence of the concentration of oxygen and of activated sludge on the quality of treatment is shown. Within the framework of the model suggested, a possibility of automated control of the process of deposition of impurities in a biological filter depending on the initial parameters of the water medium is suggested.

Mathematical Simulation of the Process of Aerobic Treatment of Wastewater under Conditions of Diffusion and Mass Transfer Perturbations

NASA Astrophysics Data System (ADS)

Bomba, A. Ya.; Safonik, A. P.

2018-03-01

A mathematical model of the process of aerobic treatment of wastewater has been refined. It takes into account the interaction of bacteria, as well as of organic and biologically nonoxidizing substances under conditions of diffusion and mass transfer perturbations. An algorithm of the solution of the corresponding nonlinear perturbed problem of convection-diffusion-mass transfer type has been constructed, with a computer experiment carried out based on it. The influence of the concentration of oxygen and of activated sludge on the quality of treatment is shown. Within the framework of the model suggested, a possibility of automated control of the process of deposition of impurities in a biological filter depending on the initial parameters of the water medium is suggested.

A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data

NASA Astrophysics Data System (ADS)

Feng, Shou; Fu, Ping; Zheng, Wenbin

2018-03-01

Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method. The nodes interaction method revises the preliminary results and guarantees that the predictions are consistent with the hierarchy constraint. This method exploits the label dependency and considers the hierarchical interaction between nodes when making decisions based on the Bayesian network in its first phase. In the second phase, this method further adjusts the results according to the hierarchy constraint. Implementing the nodes interaction method in the HMC framework also enhances the HMC performance for solving the gene function prediction problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph that is more difficult to tackle. The experimental results validate the promising performance of the proposed method compared to state-of-the-art methods on eight benchmark yeast data sets annotated by the GO.

Kramers problem in evolutionary strategies

NASA Astrophysics Data System (ADS)

Dunkel, J.; Ebeling, W.; Schimansky-Geier, L.; Hänggi, P.

2003-06-01

We calculate the escape rates of different dynamical processes for the case of a one-dimensional symmetric double-well potential. In particular, we compare the escape rates of a Smoluchowski process, i.e., a corresponding overdamped Brownian motion dynamics in a metastable potential landscape, with the escape rates obtained for a biologically motivated model known as the Fisher-Eigen process. The main difference between the two models is that the dynamics of the Smoluchowski process is determined by local quantities, whereas the Fisher-Eigen process is based on a global coupling (nonlocal interaction). If considered in the context of numerical optimization algorithms, both processes can be interpreted as archetypes of physically or biologically inspired evolutionary strategies. In this sense, the results discussed in this work are utile in order to evaluate the efficiency of such strategies with regard to the problem of surmounting various barriers. We find that a combination of both scenarios, starting with the Fisher-Eigen strategy, provides a most effective evolutionary strategy.

Processing and characterization of silk sericin from Bombyx mori and its application in biomaterials and biomedicines.

PubMed

Cao, Ting-Ting; Zhang, Yu-Qing

2016-04-01

Bombyx mori silk is composed of 60-80% fibroin, 15-35% sericin and 1-5% non-sericin component including wax, pigments, sugars and other impurities. For two decades, the protein-based silk fibroin was extensively used in the research and development of medical biomaterials and biomedicines. Sericin is frequently ignored and abandoned as a byproduct or waste in the processing of traditional silk fabrics, silk floss or modern silk biomaterials. However, similar to fibroin, sericin is not only a highly useful biological material, but also a lot of biological activity. Moreover, the non-sericin component present with sericin in the cocoon shell also has a strong biological activity. In this review, the extraction and recovery methods of sericin and the non-sericin component from the cocoon layer are reported, and their composition, properties and biological activity are described to produce a comprehensive report on biomedical materials and biological drugs. In addition, related problems or concerns present in the research and development of sericin are discussed, and a potential application of sericin in sustainable development is also presented. Copyright © 2015 Elsevier B.V. All rights reserved.

Pathways to Aging: The Mitochondrion at the Intersection of Biological and Psychosocial Sciences

PubMed Central

Picard, Martin

2011-01-01

Compelling evidence suggests that both biological and psychosocial factors impact the process of aging. However, our understanding of the dynamic interplay among biological and psychosocial factors across the life course is still fragmentary. For example, it needs to be established how the interaction of individual factors (e.g., genetic and epigenetic endowment and personality), behavioral factors (e.g., physical activity, diet, and stress management), and psychosocial experiences (e.g., social support, well-being, socioeconomic status, and marriage) in perinatal, childhood, and adulthood influence health across the aging continuum. This paper aims to outline potential intersection points serving as an interface between biological and psychosocial factors, with an emphasis on the mitochondrion. Mitochondria are cellular organelles which play a critical role in cellular senescence. Both chronic exposure to psychosocial stress and genetic-based mitochondrial dysfunction have strikingly similar biological consequences; both predispose individuals to adverse age-related health disorders and early mortality. Exploring the interactive nature of the factors resulting in pathways to normal healthy aging, as well as those leading to morbidity and early mortality, will continue to enhance our ability to translate research into effective practices that can be implemented throughout the life course to optimise the aging process. PMID:21961065

Pathways to aging: the mitochondrion at the intersection of biological and psychosocial sciences.

PubMed

Picard, Martin

2011-01-01

Compelling evidence suggests that both biological and psychosocial factors impact the process of aging. However, our understanding of the dynamic interplay among biological and psychosocial factors across the life course is still fragmentary. For example, it needs to be established how the interaction of individual factors (e.g., genetic and epigenetic endowment and personality), behavioral factors (e.g., physical activity, diet, and stress management), and psychosocial experiences (e.g., social support, well-being, socioeconomic status, and marriage) in perinatal, childhood, and adulthood influence health across the aging continuum. This paper aims to outline potential intersection points serving as an interface between biological and psychosocial factors, with an emphasis on the mitochondrion. Mitochondria are cellular organelles which play a critical role in cellular senescence. Both chronic exposure to psychosocial stress and genetic-based mitochondrial dysfunction have strikingly similar biological consequences; both predispose individuals to adverse age-related health disorders and early mortality. Exploring the interactive nature of the factors resulting in pathways to normal healthy aging, as well as those leading to morbidity and early mortality, will continue to enhance our ability to translate research into effective practices that can be implemented throughout the life course to optimise the aging process.

Bioorthogonal chemistry: applications in activity-based protein profiling.

PubMed

Willems, Lianne I; van der Linden, Wouter A; Li, Nan; Li, Kah-Yee; Liu, Nora; Hoogendoorn, Sascha; van der Marel, Gijs A; Florea, Bogdan I; Overkleeft, Herman S

2011-09-20

The close interaction between organic chemistry and biology goes back to the late 18th century, when the modern natural sciences began to take shape. After synthetic organic chemistry arose as a discipline, organic chemists almost immediately began to pursue the synthesis of naturally occurring compounds, thereby contributing to the understanding of their functions in biological processes. Research in those days was often remarkably interdisciplinary; in fact, it constituted chemical biology research before the phrase even existed. For example, histological dyes, both of an organic and inorganic nature, were developed and applied by independent researchers (Gram and Golgi) with the aim of visualizing cellular substructures (the bacterial cell wall and the Golgi apparatus). Over the years, as knowledge within the various fields of the natural sciences deepened, research disciplines drifted apart, becoming rather monodisciplinary. In these years, broadly ranging from the end of World War II to about the 1980s, organic chemistry continued to impact life sciences research, but contributions were of a more indirect nature. As an example, the development of the polymerase chain reaction, from which molecular biology and genetics research have greatly profited, was partly predicated on the availability of synthetic oligonucleotides. These molecules first became available in the late 1960s, the result of organic chemists pursuing the synthesis of DNA oligomers primarily because of the synthetic challenges involved. Today, academic natural sciences research is again becoming more interdisciplinary, and sometimes even multidisciplinary. What was termed "chemical biology" by Stuart Schreiber at the end of the last century can be roughly described as the use of intellectually chemical approaches to shed light on processes that are fundamentally rooted in biology. Chemical tools and techniques that are developed for biological studies in the exciting and rapidly evolving field of chemical biology research include contributions from many areas of the multifaceted discipline of chemistry, and particularly from organic chemistry. Researchers apply knowledge inherent to organic chemistry, such as reactivity and selectivity, to the manipulation of specific biomolecules in biological samples (cell extracts, living cells, and sometimes even animal models) to gain insight into the biological phenomena in which these molecules participate. In this Account, we highlight some of the recent developments in chemical biology research driven by organic chemistry, with a focus on bioorthogonal chemistry in relation to activity-based protein profiling. The rigorous demands of bioorthogonality have not yet been realized in a truly bioorthogonal reagent pair, but remarkable progress has afforded a range of tangible contributions to chemical biology research. Activity-based protein profiling, which aims to obtain information on the workings of a protein (or protein family) within the larger context of the full biological system, has in particular benefited from these advances. Both activity-based protein profiling and bioorthogonal chemistry have been around for approximately 15 years, and about 8 years ago the two fields very profitably intersected. We expect that each discipline, both separately and in concert, will continue to make important contributions to chemical biology research. © 2011 American Chemical Society

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

System Analysis of LWDH Related Genes Based on Text Mining in Biological Networks

PubMed Central

Miao, Yingbo; Zhang, Liangcai; Wang, Yang; Feng, Rennan; Yang, Lei; Zhang, Shihua; Jiang, Yongshuai; Liu, Guiyou

2014-01-01

Liuwei-dihuang (LWDH) is widely used in traditional Chinese medicine (TCM), but its molecular mechanism about gene interactions is unclear. LWDH genes were extracted from the existing literatures based on text mining technology. To simulate the complex molecular interactions that occur in the whole body, protein-protein interaction networks (PPINs) were constructed and the topological properties of LWDH genes were analyzed. LWDH genes have higher centrality properties and may play important roles in the complex biological network environment. It was also found that the distances within LWDH genes are smaller than expected, which means that the communication of LWDH genes during the biological process is rapid and effectual. At last, a comprehensive network of LWDH genes, including the related drugs and regulatory pathways at both the transcriptional and posttranscriptional levels, was constructed and analyzed. The biological network analysis strategy used in this study may be helpful for the understanding of molecular mechanism of TCM. PMID:25243143

Fully Automated Sample Preparation for Ultrafast N-Glycosylation Analysis of Antibody Therapeutics.

PubMed

Szigeti, Marton; Lew, Clarence; Roby, Keith; Guttman, Andras

2016-04-01

There is a growing demand in the biopharmaceutical industry for high-throughput, large-scale N-glycosylation profiling of therapeutic antibodies in all phases of product development, but especially during clone selection when hundreds of samples should be analyzed in a short period of time to assure their glycosylation-based biological activity. Our group has recently developed a magnetic bead-based protocol for N-glycosylation analysis of glycoproteins to alleviate the hard-to-automate centrifugation and vacuum-centrifugation steps of the currently used protocols. Glycan release, fluorophore labeling, and cleanup were all optimized, resulting in a <4 h magnetic bead-based process with excellent yield and good repeatability. This article demonstrates the next level of this work by automating all steps of the optimized magnetic bead-based protocol from endoglycosidase digestion, through fluorophore labeling and cleanup with high-throughput sample processing in 96-well plate format, using an automated laboratory workstation. Capillary electrophoresis analysis of the fluorophore-labeled glycans was also optimized for rapid (<3 min) separation to accommodate the high-throughput processing of the automated sample preparation workflow. Ultrafast N-glycosylation analyses of several commercially relevant antibody therapeutics are also shown and compared to their biosimilar counterparts, addressing the biological significance of the differences. © 2015 Society for Laboratory Automation and Screening.

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

PubMed Central

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh; Webb-Robertson, Bobbie-Jo; Hafen, Ryan; Ramey, John; Rodland, Karin D.

2012-01-01

Introduction The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers. PMID:23335946

An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems

PubMed Central

Osseiran, Adam

2017-01-01

The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over the last decade, research on neuromorphic olfaction has established the capability of these sensors to tackle problems that plague the current e-nose implementations such as drift, response time, portability, power consumption and size. This article brings together the key contributions in neuromorphic olfaction and identifies future research directions to develop near-real-time olfactory sensors that can be implemented for a range of applications such as biosecurity and environmental monitoring. Furthermore, we aim to expose the computational parallels between neuromorphic olfaction and gustation for future research focusing on the correlation of these senses. PMID:29125586

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

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

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh D.

2013-01-01

The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities both for purely statistical and expert knowledge-based approaches and would benefit from improved integration of the two. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges thatmore » have been encountered. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to biomarker discovery and characterization are key to future success in the biomarker field. We will describe our recommendations of possible approaches to this problem including metrics for the evaluation of biomarkers.« less

Time rescaling and pattern formation in biological evolution.

PubMed

Igamberdiev, Abir U

2014-09-01

Biological evolution is analyzed as a process of continuous measurement in which biosystems interpret themselves in the environment resulting in changes of both. This leads to rescaling of internal time (heterochrony) followed by spatial reconstructions of morphology (heterotopy). The logical precondition of evolution is the incompleteness of biosystem's internal description, while the physical precondition is the uncertainty of quantum measurement. The process of evolution is based on perpetual changes in interpretation of information in the changing world. In this interpretation the external biospheric gradients are used for establishment of new features of organization. It is concluded that biological evolution involves the anticipatory epigenetic changes in the interpretation of genetic symbolism which cannot generally be forecasted but can provide canalization of structural transformations defined by the existing organization and leading to predictable patterns of form generation. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

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

Kyle, Jennifer E.; Zhang, Xing; Weitz, Karl K.

Understanding how biological molecules are generated, metabolized and eliminated in living systems is important for interpreting processes such as immune response and disease pathology. While genomic and proteomic studies have provided vast amounts of information over the last several decades, interest in lipidomics has also grown due to improved analytical technologies revealing altered lipid metabolism in type 2 diabetes, cancer, and lipid storage disease. Liquid chromatography and mass spectrometry (LC-MS) measurements are currently the dominant approach for characterizing the lipidome by providing detailed information on the spatial and temporal composition of lipids. However, interpreting lipids’ biological roles is challenging duemore » to the existence of numerous structural and stereoisomers (i.e. distinct acyl chain and double-bond positions), which are unresolvable using present LC-MS approaches. Here we show that combining structurally-based ion mobility spectrometry (IMS) with LC-MS measurements distinguishes lipid isomers and allows insight into biological and disease processes.« less

Transport of Proteins through Nanopores

NASA Astrophysics Data System (ADS)

Luan, Binquan

In biological cells, a malfunctioned protein (such as misfolded or damaged) is degraded by a protease in which an unfoldase actively drags the protein into a nanopore-like structure and then a peptidase cuts the linearized protein into small fragments (i.e. a recycling process). Mimicking this biological process, many experimental studies have focused on the transport of proteins through a biological protein pore or a synthetic solid-state nanopore. Potentially, the nanopore-based sensors can provide a platform for interrogating proteins that might be disease-related or be targeted by a new drug molecule. The single-profile of a protein chain inside an extremely small nanopore might even permit the sequencing of the protein. Here, through all-atom molecular dynamics simulations, I will show various types of protein transport through a nanopore and reveal the nanoscale mechanics/energetics that plays an important role governing the protein transport.

Comparative advantages of mechanical biosensors.

PubMed

Arlett, J L; Myers, E B; Roukes, M L

2011-04-01

Mechanical interactions are fundamental to biology. Mechanical forces of chemical origin determine motility and adhesion on the cellular scale, and govern transport and affinity on the molecular scale. Biological sensing in the mechanical domain provides unique opportunities to measure forces, displacements and mass changes from cellular and subcellular processes. Nanomechanical systems are particularly well matched in size with molecular interactions, and provide a basis for biological probes with single-molecule sensitivity. Here we review micro- and nanoscale biosensors, with a particular focus on fast mechanical biosensing in fluid by mass- and force-based methods, and the challenges presented by non-specific interactions. We explain the general issues that will be critical to the success of any type of next-generation mechanical biosensor, such as the need to improve intrinsic device performance, fabrication reproducibility and system integration. We also discuss the need for a greater understanding of analyte-sensor interactions on the nanoscale and of stochastic processes in the sensing environment.

The Spring of Systems Biology-Driven Breeding.

PubMed

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

2018-05-12

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

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Applying systems biology methods to the study of human physiology in extreme environments

PubMed Central

2013-01-01

Systems biology is defined in this review as ‘an iterative process of computational model building and experimental model revision with the aim of understanding or simulating complex biological systems’. We propose that, in practice, systems biology rests on three pillars: computation, the omics disciplines and repeated experimental perturbation of the system of interest. The number of ethical and physiologically relevant perturbations that can be used in experiments on healthy humans is extremely limited and principally comprises exercise, nutrition, infusions (e.g. Intralipid), some drugs and altered environment. Thus, we argue that systems biology and environmental physiology are natural symbionts for those interested in a system-level understanding of human biology. However, despite excellent progress in high-altitude genetics and several proteomics studies, systems biology research into human adaptation to extreme environments is in its infancy. A brief description and overview of systems biology in its current guise is given, followed by a mini review of computational methods used for modelling biological systems. Special attention is given to high-altitude research, metabolic network reconstruction and constraint-based modelling. PMID:23849719

Normal form from biological motion despite impaired ventral stream function.

PubMed

Gilaie-Dotan, S; Bentin, S; Harel, M; Rees, G; Saygin, A P

2011-04-01

We explored the extent to which biological motion perception depends on ventral stream integration by studying LG, an unusual case of developmental visual agnosia. LG has significant ventral stream processing deficits but no discernable structural cortical abnormality. LG's intermediate visual areas and object-sensitive regions exhibit abnormal activation during visual object perception, in contrast to area V5/MT+ which responds normally to visual motion (Gilaie-Dotan, Perry, Bonneh, Malach, & Bentin, 2009). Here, in three studies we used point light displays, which require visual integration, in adaptive threshold experiments to examine LG's ability to detect form from biological and non-biological motion cues. LG's ability to detect and discriminate form from biological motion was similar to healthy controls. In contrast, he was significantly deficient in processing form from non-biological motion. Thus, LG can rely on biological motion cues to perceive human forms, but is considerably impaired in extracting form from non-biological motion. Finally, we found that while LG viewed biological motion, activity in a network of brain regions associated with processing biological motion was functionally correlated with his V5/MT+ activity, indicating that normal inputs from V5/MT+ might suffice to activate his action perception system. These results indicate that processing of biologically moving form can dissociate from other form processing in the ventral pathway. Furthermore, the present results indicate that integrative ventral stream processing is necessary for uncompromised processing of non-biological form from motion. Copyright © 2011 Elsevier Ltd. All rights reserved.

Chemical and Biological Sensing Using Hybridization Chain Reaction.

PubMed

Augspurger, Erik E; Rana, Muhit; Yigit, Mehmet V

2018-05-25

Since the advent of its theoretical discovery more than 30 years ago, DNA nanotechnology has been used in a plethora of diverse applications in both the fundamental and applied sciences. The recent prominence of DNA-based technologies in the scientific community is largely due to the programmable features stored in its nucleobase composition and sequence, which allow it to assemble into highly advanced structures. DNA nanoassemblies are also highly controllable due to the precision of natural and artificial base-pairing, which can be manipulated by pH, temperature, metal ions, and solvent types. This programmability and molecular-level control have allowed scientists to create and utilize DNA nanostructures in one, two, and three dimensions (1D, 2D, and 3D). Initially, these 2D and 3D DNA lattices and shapes attracted a broad scientific audience because they are fundamentally captivating and structurally elegant; however, transforming these conceptual architectural blueprints into functional materials is essential for further advancements in the DNA nanotechnology field. Herein, the chemical and biological sensing applications of a 1D DNA self-assembly process known as hybridization chain reaction (HCR) are reviewed. HCR is a one-dimensional (1D) double stranded (ds) DNA assembly process initiated only in the presence of a specific short ssDNA (initiator) and two kinetically trapped DNA hairpin structures. HCR is considered an enzyme-free isothermal amplification process, which shows substantial promise and offers a wide range of applications for in situ chemical and biological sensing. Due to its modular nature, HCR can be programmed to activate only in the presence of highly specific biological and/or chemical stimuli. HCR can also be combined with different types of molecular reporters and detection approaches for various analytical readouts. While the long dsDNA HCR product may not be as structurally attractive as the 2D and 3D DNA networks, HCR is highly instrumental for applied biological, chemical, and environmental sciences, and has therefore been studied to foster a variety of objectives. In this review, we have focused on nucleic acid, protein, metabolite, and heavy metal ion detection using this 1D DNA nanotechnology via fluorescence, electrochemical, and nanoparticle-based methodologies.

The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence

NASA Technical Reports Server (NTRS)

Colombano, Silvano

2000-01-01

There is no fundamental reason why A-life couldn't simply be a branch of computer science that deals with algorithms that are inspired by, or emulate biological phenomena. However, if these are the limits we place on this field, we miss the opportunity to help advance Theoretical Biology and to contribute to a deeper understanding of the nature of life. The history of Artificial Intelligence provides a good example, in that early interest in the nature of cognition quickly was lost to the process of building tools, such as "expert systems" that, were certainly useful, but provided little insight in the nature of cognition. Based on this lesson, I will discuss criteria for increasing the biological relevance of A-life and the probability that this field may provide a theoretical foundation for Biology.

QUANTITATIVE PROCEDURES FOR NEUROTOXICOLOGY RISK ASSESSMENT

EPA Science Inventory

In this project, previously published information on biologically based dose-response model for brain development was used to quantitatively evaluate critical neurodevelopmental processes, and to assess potential chemical impacts on early brain development. This model has been ex...

Activity Based Profiling of Deubiquitylating Enzymes and Inhibitors in Animal Tissues.

PubMed

McLellan, Lauren; Forder, Cassie; Cranston, Aaron; Harrigan, Jeanine; Jacq, Xavier

2016-01-01

The attachment of ubiquitin or ubiquitin-like modifiers to proteins is an important signal for the regulation of a variety of biological processes including the targeting of substrates for degradation, receptor internalization, regulation of gene expression, and DNA repair. Posttranslational modification of proteins by ubiquitin controls many cellular processes, and aberrant ubiquitylation can contribute to cancer, immunopathologies, and neurodegeneration. Thus, deubiquitylating enzymes (DUBs) that remove ubiquitin from proteins have become attractive therapeutic targets. Monitoring the activity of DUBs in cells or in tissues is critical for understanding the biological function of DUBs in particular pathways and is essential for determining the physiological specificity and potency of small-molecule DUB inhibitors. Here, we describe a method for the homogenization of animal tissues and incubation of tissue lysates with ubiquitin-based activity probes to monitor DUB activity in mouse tissues and target engagement following treatment of animals with small-molecule DUB inhibitors.

Diffusion Tensor Tractography Reveals Disrupted Structural Connectivity during Brain Aging

NASA Astrophysics Data System (ADS)

Lin, Lan; Tian, Miao; Wang, Qi; Wu, Shuicai

2017-10-01

Brain aging is one of the most crucial biological processes that entail many physical, biological, chemical, and psychological changes, and also a major risk factor for most common neurodegenerative diseases. To improve the quality of life for the elderly, it is important to understand how the brain is changed during the normal aging process. We compared diffusion tensor imaging (DTI)-based brain networks in a cohort of 75 healthy old subjects by using graph theory metrics to describe the anatomical networks and connectivity patterns, and network-based statistic (NBS) analysis was used to identify pairs of regions with altered structural connectivity. The NBS analysis revealed a significant network comprising nine distinct fiber bundles linking 10 different brain regions showed altered white matter structures in young-old group compare with middle-aged group (p < .05, family-wise error-corrected). Our results might guide future studies and help to gain a better understanding of brain aging.

Prediction of interface residue based on the features of residue interaction network.

PubMed

Jiao, Xiong; Ranganathan, Shoba

2017-11-07

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fluorescent coumarin-based probe for cysteine and homocysteine with live cell application

NASA Astrophysics Data System (ADS)

Wei, Ling-Fang; Thirumalaivasan, Natesan; Liao, Yu-Cheng; Wu, Shu-Pao

2017-08-01

Cysteine (Cys) and homocysteine (Hcy) are two of important biological thiols and function as important roles in several biological processes. The development of Cys and Hcy probes will help to explore the functions of biothiols in biological systems. In this work, a new coumarin-based probe AC, containing an acryloyl moiety, was developed for Cys and Hcy detection in cells. Cys and Hcy undergo a nucleophilic addition and subsequent cyclization reaction to remove to the acryloyl group and yield a fluorescent product, 7-hydroxylcomuarin. The probe AC showed good selectivity for cysteine and homocysteine over glutathione and other amino acids and had low detection limits of 65 nM for Cys and 79 nM for Hcy, respectively. Additionally, confocal imaging experiments demonstrated that the probe AC can be applied to visualize Cys and Hcy in living cells.

Fluorescent probes and bioimaging: alkali metals, alkaline earth metals and pH.

PubMed

Yin, Jun; Hu, Ying; Yoon, Juyoung

2015-07-21

All living species and life forms have an absolute requirement for bio-functional metals and acid-base equilibrium chemistry owing to the critical roles they play in biological processes. Hence, a great need exists for efficient methods to detect and monitor biometals and acids. In the last few years, great attention has been paid to the development of organic molecule based fluorescent chemosensors. The availability of new synthetic fluorescent probes has made fluorescence microscopy an indispensable tool for tracing biologically important molecules and in the area of clinical diagnostics. This review highlights the recent advances that have been made in the design and bioimaging applications of fluorescent probes for alkali metals and alkaline earth metal cations, including lithium, sodium and potassium, magnesium and calcium, and for pH determination within biological systems.

Revolution of Alzheimer Precision Neurology Passageway of Systems Biology and Neurophysiology.

PubMed

Hampel, Harald; Toschi, Nicola; Babiloni, Claudio; Baldacci, Filippo; Black, Keith L; Bokde, Arun L W; Bun, René S; Cacciola, Francesco; Cavedo, Enrica; Chiesa, Patrizia A; Colliot, Olivier; Coman, Cristina-Maria; Dubois, Bruno; Duggento, Andrea; Durrleman, Stanley; Ferretti, Maria-Teresa; George, Nathalie; Genthon, Remy; Habert, Marie-Odile; Herholz, Karl; Koronyo, Yosef; Koronyo-Hamaoui, Maya; Lamari, Foudil; Langevin, Todd; Lehéricy, Stéphane; Lorenceau, Jean; Neri, Christian; Nisticò, Robert; Nyasse-Messene, Francis; Ritchie, Craig; Rossi, Simone; Santarnecchi, Emiliano; Sporns, Olaf; Verdooner, Steven R; Vergallo, Andrea; Villain, Nicolas; Younesi, Erfan; Garaci, Francesco; Lista, Simone

2018-03-16

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

Revolution of Alzheimer Precision Neurology: Passageway of Systems Biology and Neurophysiology

PubMed Central

Hampel, Harald; Toschi, Nicola; Babiloni, Claudio; Baldacci, Filippo; Black, Keith L.; Bokde, Arun L.W.; Bun, René S.; Cacciola, Francesco; Cavedo, Enrica; Chiesa, Patrizia A.; Colliot, Olivier; Coman, Cristina-Maria; Dubois, Bruno; Duggento, Andrea; Durrleman, Stanley; Ferretti, Maria-Teresa; George, Nathalie; Genthon, Remy; Habert, Marie-Odile; Herholz, Karl; Koronyo, Yosef; Koronyo-Hamaoui, Maya; Lamari, Foudil; Langevin, Todd; Lehéricy, Stéphane; Lorenceau, Jean; Neri, Christian; Nisticò, Robert; Nyasse-Messene, Francis; Ritchie, Craig; Rossi, Simone; Santarnecchi, Emiliano; Sporns, Olaf; Verdooner, Steven R.; Vergallo, Andrea; Villain, Nicolas; Younesi, Erfan; Garaci, Francesco; Lista, Simone

2018-01-01

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an “omics”-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer’s disease (AD). The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group “Alzheimer Precision Medicine” (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development towards breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND. PMID:29562524

[Application of microelectronics CAD tools to synthetic biology].

PubMed

Madec, Morgan; Haiech, Jacques; Rosati, Élise; Rezgui, Abir; Gendrault, Yves; Lallement, Christophe

2017-02-01

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper. © 2017 médecine/sciences – Inserm.

A new theoretical approach to analyze complex processes in cytoskeleton proteins.

PubMed

Li, Xin; Kolomeisky, Anatoly B

2014-03-20

Cytoskeleton proteins are filament structures that support a large number of important biological processes. These dynamic biopolymers exist in nonequilibrium conditions stimulated by hydrolysis chemical reactions in their monomers. Current theoretical methods provide a comprehensive picture of biochemical and biophysical processes in cytoskeleton proteins. However, the description is only qualitative under biologically relevant conditions because utilized theoretical mean-field models neglect correlations. We develop a new theoretical method to describe dynamic processes in cytoskeleton proteins that takes into account spatial correlations in the chemical composition of these biopolymers. Our approach is based on analysis of probabilities of different clusters of subunits. It allows us to obtain exact analytical expressions for a variety of dynamic properties of cytoskeleton filaments. By comparing theoretical predictions with Monte Carlo computer simulations, it is shown that our method provides a fully quantitative description of complex dynamic phenomena in cytoskeleton proteins under all conditions.

Empirical modeling for intelligent, real-time manufacture control

NASA Technical Reports Server (NTRS)

Xu, Xiaoshu

1994-01-01

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

Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes.

PubMed

Foo, Mathias; Kim, Jongrae; Sawlekar, Rucha; Bates, Declan G

2017-04-06

Feedback control is widely used in chemical engineering to improve the performance and robustness of chemical processes. Feedback controllers require a 'subtractor' that is able to compute the error between the process output and the reference signal. In the case of embedded biomolecular control circuits, subtractors designed using standard chemical reaction network theory can only realise one-sided subtraction, rendering standard controller design approaches inadequate. Here, we show how a biomolecular controller that allows tracking of required changes in the outputs of enzymatic reaction processes can be designed and implemented within the framework of chemical reaction network theory. The controller architecture employs an inversion-based feedforward controller that compensates for the limitations of the one-sided subtractor that generates the error signals for a feedback controller. The proposed approach requires significantly fewer chemical reactions to implement than alternative designs, and should have wide applicability throughout the fields of synthetic biology and biological engineering.

A method to identify differential expression profiles of time-course gene data with Fourier transformation.

PubMed

Kim, Jaehee; Ogden, Robert Todd; Kim, Haseong

2013-10-18

Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization.The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics.

Space processing applications payload equipment study. Volume 2A: Experiment requirements

NASA Technical Reports Server (NTRS)

Smith, A. G.; Anderson, W. T., Jr.

1974-01-01

An analysis of the space processing applications payload equipment was conducted. The primary objective was to perform a review and an update of the space processing activity research equipment requirements and specifications that were derived in the first study. The analysis is based on the six major experimental classes of: (1) biological applications, (2) chemical processes in fluids, (3) crystal growth, (4) glass technology, (5) metallurgical processes, and (6) physical processes in fluids. Tables of data are prepared to show the functional requirements for the areas of investigation.

The pomegranate (Punica granatum L.) genome provides insights into fruit quality and ovule developmental biology.

PubMed

Yuan, Zhaohe; Fang, Yanming; Zhang, Taikui; Fei, Zhangjun; Han, Fengming; Liu, Cuiyu; Liu, Min; Xiao, Wei; Zhang, Wenjing; Wu, Shan; Zhang, Mengwei; Ju, Youhui; Xu, Huili; Dai, He; Liu, Yujun; Chen, Yanhui; Wang, Lili; Zhou, Jianqing; Guan, Dian; Yan, Ming; Xia, Yanhua; Huang, Xianbin; Liu, Dongyuan; Wei, Hongmin; Zheng, Hongkun

2017-12-22

Pomegranate (Punica granatum L.) has an ancient cultivation history and has become an emerging profitable fruit crop due to its attractive features such as the bright red appearance and the high abundance of medicinally valuable ellagitannin-based compounds in its peel and aril. However, the limited genomic resources have restricted further elucidation of genetics and evolution of these interesting traits. Here, we report a 274-Mb high-quality draft pomegranate genome sequence, which covers approximately 81.5% of the estimated 336-Mb genome, consists of 2177 scaffolds with an N50 size of 1.7 Mb and contains 30 903 genes. Phylogenomic analysis supported that pomegranate belongs to the Lythraceae family rather than the monogeneric Punicaceae family, and comparative analyses showed that pomegranate and Eucalyptus grandis share the paleotetraploidy event. Integrated genomic and transcriptomic analyses provided insights into the molecular mechanisms underlying the biosynthesis of ellagitannin-based compounds, the colour formation in both peels and arils during pomegranate fruit development, and the unique ovule development processes that are characteristic of pomegranate. This genome sequence provides an important resource to expand our understanding of some unique biological processes and to facilitate both comparative biology studies and crop breeding. © 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Impact of calcium and TOC on biological acidification assessment in Norwegian rivers.

PubMed

Schneider, Susanne C

2011-02-15

Acidification continues to be a major impact in freshwaters of northern Europe, and the biotic response to chemical recovery from acidification is often not a straightforward process. The focus on biological recovery is relevant within the context of the EU Water Framework Directive, where a biological monitoring system is needed that detects differences in fauna and flora compared to undisturbed reference conditions. In order to verify true reference sites for biological analyses, expected river pH is modeled based on Ca and TOC, and 94% of variability in pH at reference sites is explained by Ca alone, while 98% is explained by a combination of Ca and TOC. Based on 59 samples from 28 reference sites, compared to 547 samples from 285 non-reference sites, the impact of calcium and total organic carbon (TOC) on benthic algae species composition, expressed as acidification index periphyton (AIP), is analyzed. Rivers with a high Ca concentration have a naturally higher AIP, and TOC affects reference AIP only at low Ca concentrations. Four biological river types are needed for assessment of river acidification in Norway based on benthic algae: very calcium-poor, humic rivers (Ca<1 mg/l and TOC>2 mg/l); very calcium-poor, clear rivers (Ca<1 mg/l and TOC<2 mg/l); calcium-poor rivers (Ca between 1 and 4 mg/l); moderately calcium rich rivers (Ca>4 mg/l). A biological assessment system for river acidification in Norway based on benthic algae is presented, following the demands of the Water Framework Directive. Copyright © 2010 Elsevier B.V. All rights reserved.

Drawing-to-learn: a framework for using drawings to promote model-based reasoning in biology.

PubMed

Quillin, Kim; Thomas, Stephen

2015-03-02

The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report's Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. © 2015 K. Quillin and S. Thomas. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Biotechnology by Design: An Introductory Level, Project-Based, Synthetic Biology Laboratory Program for Undergraduate Students.

PubMed

Beach, Dale L; Alvarez, Consuelo J

2015-12-01

Synthetic biology offers an ideal opportunity to promote undergraduate laboratory courses with research-style projects, immersing students in an inquiry-based program that enhances the experience of the scientific process. We designed a semester-long, project-based laboratory curriculum using synthetic biology principles to develop a novel sensory device. Students develop subject matter knowledge of molecular genetics and practical skills relevant to molecular biology, recombinant DNA techniques, and information literacy. During the spring semesters of 2014 and 2015, the Synthetic Biology Laboratory Project was delivered to sophomore genetics courses. Using a cloning strategy based on standardized BioBrick genetic "parts," students construct a "reporter plasmid" expressing a reporter gene (GFP) controlled by a hybrid promoter regulated by the lac-repressor protein (lacI). In combination with a "sensor plasmid," the production of the reporter phenotype is inhibited in the presence of a target environmental agent, arabinose. When arabinose is absent, constitutive GFP expression makes cells glow green. But the presence of arabinose activates a second promoter (pBAD) to produce a lac-repressor protein that will inhibit GFP production. Student learning was assessed relative to five learning objectives, using a student survey administered at the beginning (pre-survey) and end (post-survey) of the course, and an additional 15 open-ended questions from five graded Progress Report assignments collected throughout the course. Students demonstrated significant learning gains (p < 0.05) for all learning outcomes. Ninety percent of students indicated that the Synthetic Biology Laboratory Project enhanced their understanding of molecular genetics. The laboratory project is highly adaptable for both introductory and advanced courses.

Reversible and long-term immobilization in a hydrogel-microbead matrix for high-resolution imaging of Caenorhabditis elegans and other small organisms

PubMed Central

Cornaglia, Matteo; Krishnamani, Gopalan; Zhang, Jingwei; Mouchiroud, Laurent; Lehnert, Thomas; Auwerx, Johan; Gijs, Martin A. M.

2018-01-01

The nematode Caenorhabditis elegans is an important model organism for biomedical research and genetic studies relevant to human biology and disease. Such studies are often based on high-resolution imaging of dynamic biological processes in the worm body tissues, requiring well-immobilized and physiologically active animals in order to avoid movement-related artifacts and to obtain meaningful biological information. However, existing immobilization methods employ the application of either anesthetics or servere physical constraints, by using glue or specific microfluidic on-chip mechanical structures, which in some cases may strongly affect physiological processes of the animals. Here, we immobilize C. elegans nematodes by taking advantage of a biocompatible and temperature-responsive hydrogel-microbead matrix. Our gel-based immobilization technique does not require a specific chip design and enables fast and reversible immobilization, thereby allowing successive imaging of the same single worm or of small worm populations at all development stages for several days. We successfully demonstrated the applicability of this method in challenging worm imaging contexts, in particular by applying it for high-resolution confocal imaging of the mitochondrial morphology in worm body wall muscle cells and for the long-term quantification of number and size of specific protein aggregates in different C. elegans neurodegenerative disease models. Our approach was also suitable for immobilizing other small organisms, such as the larvae of the fruit fly Drosophila melanogaster and the unicellular parasite Trypanosoma brucei. We anticipate that this versatile technique will significantly simplify biological assay-based longitudinal studies and long-term observation of small model organisms. PMID:29509812

Fuel from Tobacco and Arundo Donax: Synthetic Crop for Direct Drop-in Biofuel Production through Re-routing the Photorespiration Intermediates and Engineering Terpenoid Pathways

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

None

PETRO Project: Biofuels offer renewable alternatives to petroleum-based fuels that reduce net greenhouse gas emissions to nearly zero. However, traditional biofuels production is limited not only by the small amount of solar energy that plants convert through photosynthesis into biological materials, but also by inefficient processes for converting these biological materials into fuels. Farm-ready, non-food crops are needed that produce fuels or fuel-like precursors at significantly lower costs with significantly higher productivity. To make biofuels cost-competitive with petroleum-based fuels, biofuels production costs must be cut in half.

Using space-based investigations to inform cancer research on Earth.

PubMed

Becker, Jeanne L; Souza, Glauco R

2013-05-01

Experiments conducted in the microgravity environment of space are not typically at the forefront of the mind of a cancer biologist. However, space provides physical conditions that are not achievable on Earth, as well as conditions that can be exploited to study mechanisms and pathways that control cell growth and function. Over the past four decades, studies have shown how exposure to microgravity alters biological processes that may be relevant to cancer. In this Review, we explore the influence of microgravity on cell biology, focusing on tumour cells grown in space together with work carried out using models in ground-based investigations.

High-resolution multiphoton microscopy with a low-power continuous wave laser pump.

PubMed

Chen, Xiang-Dong; Li, Shen; Du, Bo; Dong, Yang; Wang, Ze-Hao; Guo, Guang-Can; Sun, Fang-Wen

2018-02-15

Multiphoton microscopy (MPM) has been widely used for three-dimensional biological imaging. Here, based on the photon-induced charge state conversion process, we demonstrated a low-power high-resolution MPM with a nitrogen vacancy (NV) center in diamond. Continuous wave green and orange lasers were used to pump and detect the two-photon charge state conversion, respectively. The power of the laser for multiphoton excitation was 40 μW. Both the axial and lateral resolutions were improved approximately 1.5 times compared with confocal microscopy. The results can be used to improve the resolution of the NV center-based quantum sensing and biological imaging.

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

PubMed Central

2010-01-01

Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics. PMID:21143785

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

Research into acetone removal from air by biofiltration using a biofilter with straight structure plates

PubMed Central

Baltrėnas, Pranas; Zagorskis, Alvydas; Misevičius, Antonas

2015-01-01

The biological air treatment method is based on the biological destruction of organic compounds using certain cultures of microorganisms. This method is simple and may be applied in many branches of industry. The main element of biological air treatment devices is a filter charge. Tests were carried out using a new-generation laboratory air purifier with a plate structure. This purifier is called biofilter. The biofilter has a special system for packing material humidification which does not require additional energy inputs. In order to extend the packing material's durability, it was composed of thermally treated birch fibre. Pollutant (acetone) biodegradation occurred on thermally treated wood fibre in this research. According to the performed tests and the received results, the process of biodestruction was highly efficient. When acetone was passed through biofilter's packing material at 0.08 m s−1 rate, the efficiency of the biofiltration process was from 70% up to 90%. The species of bacteria capable of removing acetone vapour from the air, i.e. Bacillus (B. cereus, B. subtilis), Pseudomonas (P. aeruginosa, P. putida), Stapylococcus (S. aureus) and Rhodococcus sp., was identified in this study during the process of biofiltration. Their amount in the biological packing material changed from 1.6 × 107 to 3.7 × 1011 CFU g−1. PMID:26019659

Impact of some herbicides on the biomass activity in biological treatment plants and biodegradability enhancement by a photo-Fenton process.

PubMed

Benzaquén, T B; Benzzo, M T; Isla, M A; Alfano, O M

2013-01-01

In recent years, the use of agrochemicals has increased because they are essential for profitable agricultural production. Herbicides are heavily demanded compounds and among these, the most marketed are 2,4-D, atrazine and acetochlor. They have characteristics that can cause problems to humans and the environment. Therefore, it is necessary to design systems that can reduce these compounds to harmless molecules. This work aims at evaluating the possibility of incorporating these herbicides into degradable effluents in a biological treatment system, without reducing its efficiency. For this purpose, studies of organic matter degradability in the presence of these agrochemicals were performed. A synthetic effluent based on glucose and mineral salts was inoculated with microorganisms. Glucose consumption and biomass concentration were assessed. Subsequently, preliminary studies were performed to test the viability of degradation of the most harmful compound with an advanced oxidation process (AOP). The results showed that the incorporation of these herbicides into degradable effluents in a biological treatment system has a negative impact on microorganisms. Therefore, the application of an AOP, such as the Fenton or photo-Fenton processes, prior to a biological treatment was found to degrade these substances to simpler and less toxic molecules.

Research into acetone removal from air by biofiltration using a biofilter with straight structure plates.

PubMed

Baltrėnas, Pranas; Zagorskis, Alvydas; Misevičius, Antonas

2015-03-04

The biological air treatment method is based on the biological destruction of organic compounds using certain cultures of microorganisms. This method is simple and may be applied in many branches of industry. The main element of biological air treatment devices is a filter charge. Tests were carried out using a new-generation laboratory air purifier with a plate structure. This purifier is called biofilter. The biofilter has a special system for packing material humidification which does not require additional energy inputs. In order to extend the packing material's durability, it was composed of thermally treated birch fibre. Pollutant (acetone) biodegradation occurred on thermally treated wood fibre in this research. According to the performed tests and the received results, the process of biodestruction was highly efficient. When acetone was passed through biofilter's packing material at 0.08 m s -1 rate, the efficiency of the biofiltration process was from 70% up to 90%. The species of bacteria capable of removing acetone vapour from the air, i.e. Bacillus ( B. cereus , B. subtilis ), Pseudomonas ( P. aeruginosa , P. putida ), Stapylococcus ( S. aureus ) and Rhodococcus sp., was identified in this study during the process of biofiltration. Their amount in the biological packing material changed from 1.6 × 10 7 to 3.7 × 10 11 CFU g -1 .

Transcriptomic basis for drought-resistance in Brassica napus L.

NASA Astrophysics Data System (ADS)

Wang, Pei; Yang, Cuiling; Chen, Hao; Song, Chunpeng; Zhang, Xiao; Wang, Daojie

2017-01-01

Based on transcriptomic data from four experimental settings with drought-resistant and drought-sensitive cultivars under drought and well-watered conditions, statistical analysis revealed three categories encompassing 169 highly differentially expressed genes (DEGs) in response to drought in Brassica napus L., including 37 drought-resistant cultivar-related genes, 35 drought-sensitive cultivar-related genes and 97 cultivar non-specific ones. We provide evidence that the identified DEGs were fairly uniformly distributed on different chromosomes and their expression patterns are variety specific. Except commonly enriched in response to various stimuli or stresses, different categories of DEGs show specific enrichment in certain biological processes or pathways, which indicated the possibility of functional differences among the three categories. Network analysis revealed relationships among the 169 DEGs, annotated biological processes and pathways. The 169 DEGs can be classified into different functional categories via preferred pathways or biological processes. Some pathways might simultaneously involve a large number of shared DEGs, and these pathways are likely to cross-talk and have overlapping biological functions. Several members of the identified DEGs fit to drought stress signal transduction pathway in Arabidopsis thaliana. Finally, quantitative real-time PCR validations confirmed the reproducibility of the RNA-seq data. These investigations are profitable for the improvement of crop varieties through transgenic engineering.

An Overview of Biofield Devices

PubMed Central

Muehsam, David; Chevalier, Gaétan; Barsotti, Tiffany

2015-01-01

Advances in biophysics, biology, functional genomics, neuroscience, psychology, psychoneuroimmunology, and other fields suggest the existence of a subtle system of “biofield” interactions that organize biological processes from the subatomic, atomic, molecular, cellular, and organismic to the interpersonal and cosmic levels. Biofield interactions may bring about regulation of biochemical, cellular, and neurological processes through means related to electromagnetism, quantum fields, and perhaps other means of modulating biological activity and information flow. The biofield paradigm, in contrast to a reductionist, chemistry-centered viewpoint, emphasizes the informational content of biological processes; biofield interactions are thought to operate in part via low-energy or “subtle” processes such as weak, nonthermal electromagnetic fields (EMFs) or processes potentially related to consciousness and nonlocality. Biofield interactions may also operate through or be reflected in more well-understood informational processes found in electroencephalographic (EEG) and electrocardiographic (ECG) data. Recent advances have led to the development of a wide variety of therapeutic and diagnostic biofield devices, defined as physical instruments best understood from the viewpoint of a biofield paradigm. Here, we provide a broad overview of biofield devices, with emphasis on those devices for which solid, peer-reviewed evidence exists. A subset of these devices, such as those based upon EEG- and ECG-based heart rate variability, function via mechanisms that are well understood and are widely employed in clinical settings. Other device modalities, such a gas discharge visualization and biophoton emission, appear to operate through incompletely understood mechanisms and have unclear clinical significance. Device modes of operation include EMF-light, EMF-heat, EMF-nonthermal, electrical current, vibration and sound, physical and mechanical, intentionality and nonlocality, gas and plasma, and other (mode of operation not well-understood). Methodological issues in device development and interfaces for future interdisciplinary research are discussed. Devices play prominent cultural and scientific roles in our society, and it is likely that device technologies will be one of the most influential access points for the furthering of biofield research and the dissemination of biofield concepts. This developing field of study presents new areas of research that have many important implications for both basic science and clinical medicine. PMID:26665041

An Overview of Biofield Devices.

PubMed

Muehsam, David; Chevalier, Gaétan; Barsotti, Tiffany; Gurfein, Blake T

2015-11-01

Advances in biophysics, biology, functional genomics, neuroscience, psychology, psychoneuroimmunology, and other fields suggest the existence of a subtle system of "biofield" interactions that organize biological processes from the subatomic, atomic, molecular, cellular, and organismic to the interpersonal and cosmic levels. Biofield interactions may bring about regulation of biochemical, cellular, and neurological processes through means related to electromagnetism, quantum fields, and perhaps other means of modulating biological activity and information flow. The biofield paradigm, in contrast to a reductionist, chemistry-centered viewpoint, emphasizes the informational content of biological processes; biofield interactions are thought to operate in part via low-energy or "subtle" processes such as weak, nonthermal electromagnetic fields (EMFs) or processes potentially related to consciousness and nonlocality. Biofield interactions may also operate through or be reflected in more well-understood informational processes found in electroencephalographic (EEG) and electrocardiographic (ECG) data. Recent advances have led to the development of a wide variety of therapeutic and diagnostic biofield devices, defined as physical instruments best understood from the viewpoint of a biofield paradigm. Here, we provide a broad overview of biofield devices, with emphasis on those devices for which solid, peer-reviewed evidence exists. A subset of these devices, such as those based upon EEG- and ECG-based heart rate variability, function via mechanisms that are well understood and are widely employed in clinical settings. Other device modalities, such a gas discharge visualization and biophoton emission, appear to operate through incompletely understood mechanisms and have unclear clinical significance. Device modes of operation include EMF-light, EMF-heat, EMF-nonthermal, electrical current, vibration and sound, physical and mechanical, intentionality and nonlocality, gas and plasma, and other (mode of operation not well-understood). Methodological issues in device development and interfaces for future interdisciplinary research are discussed. Devices play prominent cultural and scientific roles in our society, and it is likely that device technologies will be one of the most influential access points for the furthering of biofield research and the dissemination of biofield concepts. This developing field of study presents new areas of research that have many important implications for both basic science and clinical medicine.

Effects of biological sex on the pathophysiology of the heart.

PubMed

Fazal, Loubina; Azibani, Feriel; Vodovar, Nicolas; Cohen Solal, Alain; Delcayre, Claude; Samuel, Jane-Lise

2014-02-01

Cardiovascular diseases are the leading causes of death in men and women in industrialized countries. While the effects of biological sex on cardiovascular pathophysiology have long been known, the sex-specific mechanisms mediating these processes have been further elucidated over recent years. This review aims at analysing the sex-based differences in cardiac structure and function in adult mammals, and the sex-based differences in the main molecular mechanisms involved in the response of the heart to pathological situations. It emerged from this review that the sex-based difference is a variable that should be dealt with, not only in basic science or clinical research, but also with regards to therapeutic approaches. © 2013 The British Pharmacological Society.

Autism, Asthma, Inflammation, and the Hygiene Hypothesis

PubMed Central

Becker, Kevin G.

2007-01-01

Inflammation and the genes, molecules, and biological pathways that lead to inflammatory processes influence many important and disparate biological processes and disease states that are quite often not generally considered classical inflammatory or autoimmune disorders. These include development, reproduction, aging, tumor development and tumor rejection, cardiovascular pathologies, metabolic disorders, as well as neurological and psychiatric disorders. This paper compares parallel aspects of autism and inflammatory disorders with an emphasis on asthma. These comparisons include epidemiological, morphometric, molecular, and genetic aspects of both disease types, contributing to a hypothesis of autism in the context of the immune based hygiene hypothesis. This hypothesis is meant to address the apparent rise in the prevalence of autism in the population. PMID:17412520

Autism, asthma, inflammation, and the hygiene hypothesis.

PubMed

Becker, Kevin G

2007-01-01

Inflammation and the genes, molecules, and biological pathways that lead to inflammatory processes influence many important and disparate biological processes and disease states that are quite often not generally considered classical inflammatory or autoimmune disorders. These include development, reproduction, aging, tumor development and tumor rejection, cardiovascular pathologies, metabolic disorders, as well as neurological and psychiatric disorders. This paper compares parallel aspects of autism and inflammatory disorders with an emphasis on asthma. These comparisons include epidemiological, morphometric, molecular, and genetic aspects of both disease types, contributing to a hypothesis of autism in the context of the immune based hygiene hypothesis. This hypothesis is meant to address the apparent rise in the prevalence of autism in the population.

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

[Do-it-yourself biology and medicine: history, practices, issues].

PubMed

Meyer, Morgan

2018-05-01

Do-it-yourself (DIY) biology and medicine are based on various practices and logics: amateur and DIY practices, the ethics of hacking and open source, the drive to domesticate molecular biology and genetics, the ideal of participation and citizen science. The article shows that this democratization is a process that is at once spatial (construction of new spaces), technical (creative workarounds equipment), social (establishment of accessible networks/laboratories) and political. It is therefore through their practices, gestures and questions - tinkering, experimenting, working around, amaterializing, ethicizing, comparing, valuating, etc. - that we need to grasp DIY sciences. © 2018 médecine/sciences – Inserm.

On incomplete sampling under birth-death models and connections to the sampling-based coalescent.

PubMed

Stadler, Tanja

2009-11-07

The constant rate birth-death process is used as a stochastic model for many biological systems, for example phylogenies or disease transmission. As the biological data are usually not fully available, it is crucial to understand the effect of incomplete sampling. In this paper, we analyze the constant rate birth-death process with incomplete sampling. We derive the density of the bifurcation events for trees on n leaves which evolved under this birth-death-sampling process. This density is used for calculating prior distributions in Bayesian inference programs and for efficiently simulating trees. We show that the birth-death-sampling process can be interpreted as a birth-death process with reduced rates and complete sampling. This shows that joint inference of birth rate, death rate and sampling probability is not possible. The birth-death-sampling process is compared to the sampling-based population genetics model, the coalescent. It is shown that despite many similarities between these two models, the distribution of bifurcation times remains different even in the case of very large population sizes. We illustrate these findings on an Hepatitis C virus dataset from Egypt. We show that the transmission times estimates are significantly different-the widely used Gamma statistic even changes its sign from negative to positive when switching from the coalescent to the birth-death process.

Penrose-Hameroff orchestrated objective-reduction proposal for human consciousness is not biologically feasible.

PubMed

McKemmish, Laura K; Reimers, Jeffrey R; McKenzie, Ross H; Mark, Alan E; Hush, Noel S

2009-08-01

Penrose and Hameroff have argued that the conventional models of a brain function based on neural networks alone cannot account for human consciousness, claiming that quantum-computation elements are also required. Specifically, in their Orchestrated Objective Reduction (Orch OR) model [R. Penrose and S. R. Hameroff, J. Conscious. Stud. 2, 99 (1995)], it is postulated that microtubules act as quantum processing units, with individual tubulin dimers forming the computational elements. This model requires that the tubulin is able to switch between alternative conformational states in a coherent manner, and that this process be rapid on the physiological time scale. Here, the biological feasibility of the Orch OR proposal is examined in light of recent experimental studies on microtubule assembly and dynamics. It is shown that the tubulins do not possess essential properties required for the Orch OR proposal, as originally proposed, to hold. Further, we consider also recent progress in the understanding of the long-lived coherent motions in biological systems, a feature critical to Orch OR, and show that no reformation of the proposal based on known physical paradigms could lead to quantum computing within microtubules. Hence, the Orch OR model is not a feasible explanation of the origin of consciousness.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World.

PubMed

Di Silvestre, Dario; Bergamaschi, Andrea; Bellini, Edoardo; Mauri, PierLuigi

2018-06-03

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

Digging into the low molecular weight peptidome with the OligoNet web server.

PubMed

Liu, Youzhong; Forcisi, Sara; Lucio, Marianna; Harir, Mourad; Bahut, Florian; Deleris-Bou, Magali; Krieger-Weber, Sibylle; Gougeon, Régis D; Alexandre, Hervé; Schmitt-Kopplin, Philippe

2017-09-15

Bioactive peptides play critical roles in regulating many biological processes. Recently, natural short peptides biomarkers are drawing significant attention and are considered as "hidden treasure" of drug candidates. High resolution and high mass accuracy provided by mass spectrometry (MS)-based untargeted metabolomics would enable the rapid detection and wide coverage of the low-molecular-weight peptidome. However, translating unknown masses (<1 500 Da) into putative peptides is often limited due to the lack of automatic data processing tools and to the limit of peptide databases. The web server OligoNet responds to this challenge by attempting to decompose each individual mass into a combination of amino acids out of metabolomics datasets. It provides an additional network-based data interpretation named "Peptide degradation network" (PDN), which unravels interesting relations between annotated peptides and generates potential functional patterns. The ab initio PDN built from yeast metabolic profiling data shows a great similarity with well-known metabolic networks, and could aid biological interpretation. OligoNet allows also an easy evaluation and interpretation of annotated peptides in systems biology, and is freely accessible at https://daniellyz200608105.shinyapps.io/OligoNet/ .

[Biological treatments for contaminated soils: hydrocarbon contamination. Fungal applications in bioremediation treatment].

PubMed

Martín Moreno, Carmen; González Becerra, Aldo; Blanco Santos, María José

2004-09-01

Bioremediation is a spontaneous or controlled process in which biological, mainly microbiological, methods are used to degrade or transform contaminants to non or less toxic products, reducing the environmental pollution. The most important parameters to define a contaminated site are: biodegradability, contaminant distribution, lixiviation grade, chemical reactivity of the contaminants, soil type and properties, oxygen availability and occurrence of inhibitory substances. Biological treatments of organic contaminations are based on the degradative abilities of the microorganisms. Therefore the knowledge on the physiology and ecology of the biological species or consortia involved as well as the characteristics of the polluted sites are decisive factors to select an adequate biorremediation protocol. Basidiomycetes which cause white rot decay of wood are able to degrade lignin and a variety of environmentally persistent pollutants. Thus, white rot fungi and their enzymes are thought to be useful not only in some industrial process like biopulping and biobleaching but also in bioremediation. This paper provides a review of different aspects of bioremediation technologies and recent advances on ligninolytic metabolism research.

Removal of iron and manganese using biological roughing up flow filtration technology.

PubMed

Pacini, Virginia Alejandra; María Ingallinella, Ana; Sanguinetti, Graciela

2005-11-01

The removal of iron and manganese from groundwater using biological treatment methods is almost unknown in Latin America. Biological systems used in Europe are based on the process of double rapid biofiltration during which dissolved oxygen and pH need to be strictly controlled in order to limit abiotic iron oxidation. The performance of roughing filter technology in a biological treatment process for the removal of iron and manganese, without the use of chemical agents and under natural pH conditions was studied. Two pilot plants, using two different natural groundwaters, were operated with the following treatment line: aeration, up flow roughing filtration and final filtration (either slow or rapid). Iron and manganese removal efficiencies were found to be between 85% and 95%. The high solid retention capability of the roughing filter means that it is possible to remove iron and manganese simultaneously by biotic and abiotic mechanisms. This system combines simple, low-cost operation and maintenance with high iron and manganese removal efficiencies, thus constituting a technology which is particularly suited to small waterworks.

Principles for integrating reactive species into in vivo biological processes: Examples from exercise physiology.

PubMed

Margaritelis, Nikos V; Cobley, James N; Paschalis, Vassilis; Veskoukis, Aristidis S; Theodorou, Anastasios A; Kyparos, Antonios; Nikolaidis, Michalis G

2016-04-01

The equivocal role of reactive species and redox signaling in exercise responses and adaptations is an example clearly showing the inadequacy of current redox biology research to shed light on fundamental biological processes in vivo. Part of the answer probably relies on the extreme complexity of the in vivo redox biology and the limitations of the currently applied methodological and experimental tools. We propose six fundamental principles that should be considered in future studies to mechanistically link reactive species production to exercise responses or adaptations: 1) identify and quantify the reactive species, 2) determine the potential signaling properties of the reactive species, 3) detect the sources of reactive species, 4) locate the domain modified and verify the (ir)reversibility of post-translational modifications, 5) establish causality between redox and physiological measurements, 6) use selective and targeted antioxidants. Fulfilling these principles requires an idealized human experimental setting, which is certainly a utopia. Thus, researchers should choose to satisfy those principles, which, based on scientific evidence, are most critical for their specific research question. Copyright © 2015 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Moore, J. K.

2016-02-01

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

Thermal injury models for optical treatment of biological tissues: a comparative study.

PubMed

Fanjul-Velez, Felix; Ortega-Quijano, Noe; Salas-Garcia, Irene; Arce-Diego, Jose L

2010-01-01

The interaction of optical radiation with biological tissues causes an increase in the temperature that, depending on its magnitude, can provoke a thermal injury process in the tissue. The establishment of laser irradiation pathological limits constitutes an essential task, as long as it enables to fix and delimit a range of parameters that ensure a safe treatment in laser therapies. These limits can be appropriately described by kinetic models of the damage processes. In this work, we present and compare several models for the study of thermal injury in biological tissues under optical illumination, particularly the Arrhenius thermal damage model and the thermal dosimetry model based on CEM (Cumulative Equivalent Minutes) 43°C. The basic concepts that link the temperature and exposition time with the tissue injury or cellular death are presented, and it will be shown that they enable to establish predictive models for the thermal damage in laser therapies. The results obtained by both models will be compared and discussed, highlighting the main advantages of each one and proposing the most adequate one for optical treatment of biological tissues.

Results of the Alternative Water Processor Test, A Novel Technology for Exploration Wastewater Remediation

NASA Technical Reports Server (NTRS)

Meyer, Caitlin E.; Pensinger, Stuart; Adam, Niklas; Pickering, Karen D.; Barta, Daniel; Shull, Sarah A.; Vega, Leticia M.; Lange, Kevin; Christenson, Dylan; Jackson, W. Andrew

2016-01-01

Biologically-based water recovery systems are a regenerative, low energy alternative to physiochemical processes to reclaim water from wastewater. This report summarizes the results of the Alternative Water Processor (AWP) Integrated Test, conducted from June 2013 until April 2014. The system was comprised of four (4) membrane aerated bioreactors (MABRs) to remove carbon and nitrogen from an exploration mission wastewater and a coupled forward and reverse osmosis system to remove large organic and inorganic salts from the biological system effluent. The system exceeded the overall objectives of the test by recovering 90% of the influent wastewater processed into a near potable state and a 64% reduction of consumables from the current state of the art water recovery system on the International Space Station (ISS). However, the biological system fell short of its test goals, failing to remove 75% and 90% of the influent ammonium and organic carbon, respectively. Despite not meeting its test goals, the BWP demonstrated the feasibility of an attached-growth biological system for simultaneous nitrification and denitrification, an innovative, volume- and consumable-saving design that does not require toxic pretreatment.

Evolution of Aging Theories: Why Modern Programmed Aging Concepts Are Transforming Medical Research.

PubMed

Goldsmith, Theodore C

2016-12-01

Programmed aging refers to the idea that senescence in humans and other organisms is purposely caused by evolved biological mechanisms to obtain an evolutionary advantage. Until recently, programmed aging was considered theoretically impossible because of the mechanics of the evolution process, and medical research was based on the idea that aging was not programmed. Theorists struggled for more than a century in efforts to develop non-programmed theories that fit observations, without obtaining a consensus supporting any non-programmed theory. Empirical evidence of programmed lifespan limitations continued to accumulate. More recently, developments, especially in our understanding of biological inheritance, have exposed major issues and complexities regarding the process of evolution, some of which explicitly enable programmed aging of mammals. Consequently, science-based opposition to programmed aging has dramatically declined. This progression has major implications for medical research, because the theories suggest that very different biological mechanisms are ultimately responsible for highly age-related diseases that now represent most research efforts and health costs. Most particularly, programmed theories suggest that aging per se is a treatable condition and suggest a second path toward treating and preventing age-related diseases that can be exploited in addition to the traditional disease-specific approaches. The theories also make predictions regarding the nature of biological aging mechanisms and therefore suggest research directions. This article discusses developments of evolutionary mechanics, the consequent programmed aging theories, and logical inferences concerning biological aging mechanisms. It concludes that major medical research organizations cannot afford to ignore programmed aging concepts in assigning research resources and directions.

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

PubMed

duVerle, David A; Yotsukura, Sohiya; Nomura, Seitaro; Aburatani, Hiroyuki; Tsuda, Koji

2016-09-13

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths. Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights. With cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/ .

New strategy for protein interactions and application to structure-based drug design

NASA Astrophysics Data System (ADS)

Zou, Xiaoqin

One of the greatest challenges in computational biophysics is to predict interactions between biological molecules, which play critical roles in biological processes and rational design of therapeutic drugs. Biomolecular interactions involve delicate interplay between multiple interactions, including electrostatic interactions, van der Waals interactions, solvent effect, and conformational entropic effect. Accurate determination of these complex and subtle interactions is challenging. Moreover, a biological molecule such as a protein usually consists of thousands of atoms, and thus occupies a huge conformational space. The large degrees of freedom pose further challenges for accurate prediction of biomolecular interactions. Here, I will present our development of physics-based theory and computational modeling on protein interactions with other molecules. The major strategy is to extract microscopic energetics from the information embedded in the experimentally-determined structures of protein complexes. I will also present applications of the methods to structure-based therapeutic design. Supported by NSF CAREER Award DBI-0953839, NIH R01GM109980, and the American Heart Association (Midwest Affiliate) [13GRNT16990076].

Repair and tissue engineering techniques for articular cartilage

PubMed Central

Makris, Eleftherios A.; Gomoll, Andreas H.; Malizos, Konstantinos N.; Hu, Jerry C.; Athanasiou, Kyriacos A.

2015-01-01

Chondral and osteochondral lesions due to injury or other pathology commonly result in the development of osteoarthritis, eventually leading to progressive total joint destruction. Although current progress suggests that biologic agents can delay the advancement of deterioration, such drugs are incapable of promoting tissue restoration. The limited ability of articular cartilage to regenerate renders joint arthroplasty an unavoidable surgical intervention. This Review describes current, widely used clinical repair techniques for resurfacing articular cartilage defects; short-term and long-term clinical outcomes of these techniques are discussed. Also reviewed is a developmental pipeline of regenerative biological products that over the next decade could revolutionize joint care by functionally healing articular cartilage. These products include cell-based and cell-free materials such as autologous and allogeneic cell-based approaches and multipotent and pluripotent stem-cell-based techniques. Central to these efforts is the prominent role that tissue engineering has in translating biological technology into clinical products; therefore, concomitant regulatory processes are also discussed. PMID:25247412

Safety of plant-made pharmaceuticals: product development and regulatory considerations based on case studies of two autologous human cancer vaccines.

PubMed

Tusé, Daniel

2011-03-01

Guidelines issued by regulatory agencies for the development of plant-made pharmaceutical (PMP) products provide criteria for product manufacturing and characterization, safety determination, containment and mitigation of environmental risks. Features of plant-made products do not always enable an easy fit within the criteria subscribed to by regulators. The unconventional nature of plant-based manufacturing processes and peculiarities of plant biology relative to that of traditional biological production systems have led to special considerations in the regulatory scrutiny of PMP. Presented in this review are case studies of two plant-made autologous (patient-specific) cancer vaccines, the nature of which introduced challenges to conventional and standardized development and preclinical evaluation routes. The rationale presented to FDA by the sponsors of each vaccine to build consensus and obtain variances to existing guidelines is discussed. While development of many plant-made biologics can be accomplished within the existing regulatory framework, the development of specialized products can be defended with rational arguments based on strong science.

DL-ReSuMe: A Delay Learning-Based Remote Supervised Method for Spiking Neurons.

PubMed

Taherkhani, Aboozar; Belatreche, Ammar; Li, Yuhua; Maguire, Liam P

2015-12-01

Recent research has shown the potential capability of spiking neural networks (SNNs) to model complex information processing in the brain. There is biological evidence to prove the use of the precise timing of spikes for information coding. However, the exact learning mechanism in which the neuron is trained to fire at precise times remains an open problem. The majority of the existing learning methods for SNNs are based on weight adjustment. However, there is also biological evidence that the synaptic delay is not constant. In this paper, a learning method for spiking neurons, called delay learning remote supervised method (DL-ReSuMe), is proposed to merge the delay shift approach and ReSuMe-based weight adjustment to enhance the learning performance. DL-ReSuMe uses more biologically plausible properties, such as delay learning, and needs less weight adjustment than ReSuMe. Simulation results have shown that the proposed DL-ReSuMe approach achieves learning accuracy and learning speed improvements compared with ReSuMe.

Silicon photonics for neuromorphic information processing

NASA Astrophysics Data System (ADS)

Bienstman, Peter; Dambre, Joni; Katumba, Andrew; Freiberger, Matthias; Laporte, Floris; Lugnan, Alessio

2018-02-01

We present our latest results on silicon photonics neuromorphic information processing based a.o. on techniques like reservoir computing. We will discuss aspects like scalability, novel architectures for enhanced power efficiency, as well as all-optical readout. Additionally, we will touch upon new machine learning techniques to operate these integrated readouts. Finally, we will show how these systems can be used for high-speed low-power information processing for applications like recognition of biological cells.

Self-restoration as fundamental property of CES providing their sustainability

NASA Astrophysics Data System (ADS)

Gitelson, I. I.; Degermendzhy, A. G.; Rodicheva, E. K.

Sustainability is one of the most important criteria in the creation and evaluation of human life support systems intended for use during long space flights. The common feature of biological and physicochemical life support systems is that basically they are both catalytic. But there are two fundamental properties distinguishing biological systems: 1) they are auto-catalytic: their catalysts — enzymes of protein nature — are continuously reproduced when the system functions; 2) the program of every process performed by enzymes and the program of their reproduction are inherent in the biological system itself — in the totality of genomes of the species involved in the functioning of the ecosystem. Actually, one cell with the genome capable of the phenotypic realization is enough for the self-restoration of the function performed by the cells of this species in the ecosystem. The continuous microalgal culture of Chlorella vulgaris was taken to investigate quantitatively the process of self-restoration in unicellular algae population. Based on the data obtained, we proposed a mathematical model of the restoration process in a cell population that has suffered an acute radiation damage.

Wavelet data processing of micro-Raman spectra of biological samples

NASA Astrophysics Data System (ADS)

Camerlingo, C.; Zenone, F.; Gaeta, G. M.; Riccio, R.; Lepore, M.

2006-02-01

A wavelet multi-component decomposition algorithm is proposed for processing data from micro-Raman spectroscopy (μ-RS) of biological tissue. The μ-RS has been recently recognized as a promising tool for the biopsy test and in vivo diagnosis of degenerative human tissue pathologies, due to the high chemical and structural information contents of this spectroscopic technique. However, measurements of biological tissues are usually hampered by typically low-level signals and by the presence of noise and background components caused by light diffusion or fluorescence processes. In order to overcome these problems, a numerical method based on discrete wavelet transform is used for the analysis of data from μ-RS measurements performed in vitro on animal (pig and chicken) tissue samples and, in a preliminary form, on human skin and oral tissue biopsy from normal subjects. Visible light μ-RS was performed using a He-Ne laser and a monochromator with a liquid nitrogen cooled charge coupled device equipped with a grating of 1800 grooves mm-1. The validity of the proposed data procedure has been tested on the well-characterized Raman spectra of reference acetylsalicylic acid samples.

Comparative techno-economic analysis of steam explosion, dilute sulfuric acid, ammonia fiber explosion and biological pretreatments of corn stover.

PubMed

Baral, Nawa Raj; Shah, Ajay

2017-05-01

Pretreatment is required to destroy recalcitrant structure of lignocelluloses and then transform into fermentable sugars. This study assessed techno-economics of steam explosion, dilute sulfuric acid, ammonia fiber explosion and biological pretreatments, and identified bottlenecks and operational targets for process improvement. Techno-economic models of these pretreatment processes for a cellulosic biorefinery of 113.5 million liters butanol per year excluding fermentation and wastewater treatment sections were developed using a modelling software-SuperPro Designer. Experimental data of the selected pretreatment processes based on corn stover were gathered from recent publications, and used for this analysis. Estimated sugar production costs ($/kg) via steam explosion, dilute sulfuric acid, ammonia fiber explosion and biological methods were 0.43, 0.42, 0.65 and 1.41, respectively. The results suggest steam explosion and sulfuric acid pretreatment methods might be good alternatives at present state of technology and other pretreatment methods require research and development efforts to be competitive with these pretreatment methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Biological timing and the clock metaphor: oscillatory and hourglass mechanisms.

PubMed

Rensing, L; Meyer-Grahle, U; Ruoff, P

2001-05-01

Living organisms have developed a multitude of timing mechanisms--"biological clocks." Their mechanisms are based on either oscillations (oscillatory clocks) or unidirectional processes (hourglass clocks). Oscillatory clocks comprise circatidal, circalunidian, circadian, circalunar, and circannual oscillations--which keep time with environmental periodicities--as well as ultradian oscillations, ovarian cycles, and oscillations in development and in the brain, which keep time with biological timescales. These clocks mainly determine time points at specific phases of their oscillations. Hourglass clocks are predominantly found in development and aging and also in the brain. They determine time intervals (duration). More complex timing systems combine oscillatory and hourglass mechanisms, such as the case for cell cycle, sleep initiation, or brain clocks, whereas others combine external and internal periodicities (photoperiodism, seasonal reproduction). A definition of a biological clock may be derived from its control of functions external to its own processes and its use in determining temporal order (sequences of events) or durations. Biological and chemical oscillators are characterized by positive and negative feedback (or feedforward) mechanisms. During evolution, living organisms made use of the many existing oscillations for signal transmission, movement, and pump mechanisms, as well as for clocks. Some clocks, such as the circadian clock, that time with environmental periodicities are usually compensated (stabilized) against temperature, whereas other clocks, such as the cell cycle, that keep time with an organismic timescale are not compensated. This difference may be related to the predominance of negative feedback in the first class of clocks and a predominance of positive feedback (autocatalytic amplification) in the second class. The present knowledge of a compensated clock (the circadian oscillator) and an uncompensated clock (the cell cycle), as well as relevant models, are briefly re viewed. Hourglass clocks are based on linear or exponential unidirectional processes that trigger events mainly in the course of development and aging. An important hourglass mechanism within the aging process is the limitation of cell division capacity by the length of telomeres. The mechanism of this clock is briefly reviewed. In all clock mechanisms, thresholds at which "dependent variables" are triggered play an important role.

Biology-inspired AMO physics

NASA Astrophysics Data System (ADS)

Mathur, Deepak

2015-01-01

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

Visual event-related potentials to biological motion stimuli in autism spectrum disorders

PubMed Central

Bletsch, Anke; Krick, Christoph; Siniatchkin, Michael; Jarczok, Tomasz A.; Freitag, Christine M.; Bender, Stephan

2014-01-01

Atypical visual processing of biological motion contributes to social impairments in autism spectrum disorders (ASD). However, the exact temporal sequence of deficits of cortical biological motion processing in ASD has not been studied to date. We used 64-channel electroencephalography to study event-related potentials associated with human motion perception in 17 children and adolescents with ASD and 21 typical controls. A spatio-temporal source analysis was performed to assess the brain structures involved in these processes. We expected altered activity already during early stimulus processing and reduced activity during subsequent biological motion specific processes in ASD. In response to both, random and biological motion, the P100 amplitude was decreased suggesting unspecific deficits in visual processing, and the occipito-temporal N200 showed atypical lateralization in ASD suggesting altered hemispheric specialization. A slow positive deflection after 400 ms, reflecting top-down processes, and human motion-specific dipole activation differed slightly between groups, with reduced and more diffuse activation in the ASD-group. The latter could be an indicator of a disrupted neuronal network for biological motion processing in ADS. Furthermore, early visual processing (P100) seems to be correlated to biological motion-specific activation. This emphasizes the relevance of early sensory processing for higher order processing deficits in ASD. PMID:23887808

Role of isolated and clustered DNA damage and the post-irradiating repair process in the effects of heavy ion beam irradiation.

PubMed

Tokuyama, Yuka; Furusawa, Yoshiya; Ide, Hiroshi; Yasui, Akira; Terato, Hiroaki

2015-05-01

Clustered DNA damage is a specific type of DNA damage induced by ionizing radiation. Any type of ionizing radiation traverses the target DNA molecule as a beam, inducing damage along its track. Our previous study showed that clustered DNA damage yields decreased with increased linear energy transfer (LET), leading us to investigate the importance of clustered DNA damage in the biological effects of heavy ion beam radiation. In this study, we analyzed the yield of clustered base damage (comprising multiple base lesions) in cultured cells irradiated with various heavy ion beams, and investigated isolated base damage and the repair process in post-irradiation cultured cells. Chinese hamster ovary (CHO) cells were irradiated by carbon, silicon, argon and iron ion beams with LETs of 13, 55, 90 and 200 keV µm(-1), respectively. Agarose gel electrophoresis of the cells with enzymatic treatments indicated that clustered base damage yields decreased as the LET increased. The aldehyde reactive probe procedure showed that isolated base damage yields in the irradiated cells followed the same pattern. To analyze the cellular base damage process, clustered DNA damage repair was investigated using DNA repair mutant cells. DNA double-strand breaks accumulated in CHO mutant cells lacking Xrcc1 after irradiation, and the cell viability decreased. On the other hand, mouse embryonic fibroblast (Mef) cells lacking both Nth1 and Ogg1 became more resistant than the wild type Mef. Thus, clustered base damage seems to be involved in the expression of heavy ion beam biological effects via the repair process. © The Author 2015. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Adverse outcome pathway networks II: Network analytics

EPA Science Inventory

The US EPA is developing more cost effective and efficient ways to evaluate chemical safety using high throughput and computationally based testing strategies. An important component of this approach is the ability to translate chemical effects on fundamental biological processes...

Hormesis and adaptive cellular control systems

EPA Science Inventory

Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...

Biodegradability and toxicity assessment of a real textile wastewater effluent treated by an optimized electrocoagulation process.

PubMed

Manenti, Diego R; Módenes, Aparecido N; Soares, Petrick A; Boaventura, Rui A R; Palácio, Soraya M; Borba, Fernando H; Espinoza-Quiñones, Fernando R; Bergamasco, Rosângela; Vilar, Vítor J P

2015-01-01

In this work, the application of an iron electrode-based electrocoagulation (EC) process on the treatment of a real textile wastewater (RTW) was investigated. In order to perform an efficient integration of the EC process with a biological oxidation one, an enhancement in the biodegradability and low toxicity of final compounds was sought. Optimal values of EC reactor operation parameters (pH, current density and electrolysis time) were achieved by applying a full factorial 3(3) experimental design. Biodegradability and toxicity assays were performed on treated RTW samples obtained at the optimal values of: pH of the solution (7.0), current density (142.9 A m(-2)) and different electrolysis times. As response variables for the biodegradability and toxicity assessment, the Zahn-Wellens test (Dt), the ratio values of dissolved organic carbon (DOC) relative to low-molecular-weight carboxylates anions (LMCA) and lethal concentration 50 (LC50) were used. According to the Dt, the DOC/LMCA ratio and LC50, an electrolysis time of 15 min along with the optimal values of pH and current density were suggested as suitable for a next stage of treatment based on a biological oxidation process.

NMR-Fragment Based Virtual Screening: A Brief Overview.

PubMed

Singh, Meenakshi; Tam, Benjamin; Akabayov, Barak

2018-01-25

Fragment-based drug discovery (FBDD) using NMR has become a central approach over the last twenty years for development of small molecule inhibitors against biological macromolecules, to control a variety of cellular processes. Yet, several considerations should be taken into account for obtaining a therapeutically relevant agent. In this review, we aim to list the considerations that make NMR fragment screening a successful process for yielding potent inhibitors. Factors that may govern the competence of NMR in fragment based drug discovery are discussed, as well as later steps that involve optimization of hits obtained by NMR-FBDD.

Students Mental Representation of Biology Diagrams/Pictures Conventions Based on Formation of Causal Network

NASA Astrophysics Data System (ADS)

Sampurno, A. W.; Rahmat, A.; Diana, S.

2017-09-01

Diagrams/pictures conventions is one form of visual media that often used to assist students in understanding the biological concepts. The effectiveness of use diagrams/pictures in biology learning at school level has also been mostly reported. This study examines the ability of high school students in reading diagrams/pictures biological convention which is described by Mental Representation based on formation of causal networks. The study involved 30 students 11th grade MIA senior high school Banten Indonesia who are studying the excretory system. MR data obtained by Instrument worksheet, developed based on CNET-protocol, in which there are diagrams/drawings of nephron structure and urinary mechanism. Three patterns formed MR, namely Markov chain, feedback control with a single measurement, and repeated feedback control with multiple measurement. The third pattern is the most dominating pattern, differences in the pattern of MR reveal the difference in how and from which point the students begin to uncover important information contained in the diagram to establish a causal networks. Further analysis shows that a difference in the pattern of MR relate to how complex the students process the information contained in the diagrams/pictures.