Set membership experimental design for biological systems.

PubMed

Marvel, Skylar W; Williams, Cranos M

2012-03-21

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

Set membership experimental design for biological systems

PubMed Central

2012-01-01

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

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.

Retrieving relevant time-course experiments: a study on Arabidopsis microarrays.

PubMed

Şener, Duygu Dede; Oğul, Hasan

2016-06-01

Understanding time-course regulation of genes in response to a stimulus is a major concern in current systems biology. The problem is usually approached by computational methods to model the gene behaviour or its networked interactions with the others by a set of latent parameters. The model parameters can be estimated through a meta-analysis of available data obtained from other relevant experiments. The key question here is how to find the relevant experiments which are potentially useful in analysing current data. In this study, the authors address this problem in the context of time-course gene expression experiments from an information retrieval perspective. To this end, they introduce a computational framework that takes a time-course experiment as a query and reports a list of relevant experiments retrieved from a given repository. These retrieved experiments can then be used to associate the environmental factors of query experiment with the findings previously reported. The model is tested using a set of time-course Arabidopsis microarrays. The experimental results show that relevant experiments can be successfully retrieved based on content similarity.

The use and QA of biologically related models for treatment planning: short report of the TG-166 of the therapy physics committee of the AAPM.

PubMed

Allen Li, X; Alber, Markus; Deasy, Joseph O; Jackson, Andrew; Ken Jee, Kyung-Wook; Marks, Lawrence B; Martel, Mary K; Mayo, Charles; Moiseenko, Vitali; Nahum, Alan E; Niemierko, Andrzej; Semenenko, Vladimir A; Yorke, Ellen D

2012-03-01

Treatment planning tools that use biologically related models for plan optimization and/or evaluation are being introduced for clinical use. A variety of dose-response models and quantities along with a series of organ-specific model parameters are included in these tools. However, due to various limitations, such as the limitations of models and available model parameters, the incomplete understanding of dose responses, and the inadequate clinical data, the use of biologically based treatment planning system (BBTPS) represents a paradigm shift and can be potentially dangerous. There will be a steep learning curve for most planners. The purpose of this task group is to address some of these relevant issues before the use of BBTPS becomes widely spread. In this report, the authors (1) discuss strategies, limitations, conditions, and cautions for using biologically based models and parameters in clinical treatment planning; (2) demonstrate the practical use of the three most commonly used commercially available BBTPS and potential dosimetric differences between biologically model based and dose-volume based treatment plan optimization and evaluation; (3) identify the desirable features and future directions in developing BBTPS; and (4) provide general guidelines and methodology for the acceptance testing, commissioning, and routine quality assurance (QA) of BBTPS.

Using machine learning tools to model complex toxic interactions with limited sampling regimes.

PubMed

Bertin, Matthew J; Moeller, Peter; Guillette, Louis J; Chapman, Robert W

2013-03-19

A major impediment to understanding the impact of environmental stress, including toxins and other pollutants, on organisms, is that organisms are rarely challenged by one or a few stressors in natural systems. Thus, linking laboratory experiments that are limited by practical considerations to a few stressors and a few levels of these stressors to real world conditions is constrained. In addition, while the existence of complex interactions among stressors can be identified by current statistical methods, these methods do not provide a means to construct mathematical models of these interactions. In this paper, we offer a two-step process by which complex interactions of stressors on biological systems can be modeled in an experimental design that is within the limits of practicality. We begin with the notion that environment conditions circumscribe an n-dimensional hyperspace within which biological processes or end points are embedded. We then randomly sample this hyperspace to establish experimental conditions that span the range of the relevant parameters and conduct the experiment(s) based upon these selected conditions. Models of the complex interactions of the parameters are then extracted using machine learning tools, specifically artificial neural networks. This approach can rapidly generate highly accurate models of biological responses to complex interactions among environmentally relevant toxins, identify critical subspaces where nonlinear responses exist, and provide an expedient means of designing traditional experiments to test the impact of complex mixtures on biological responses. Further, this can be accomplished with an astonishingly small sample size.

Electronic structure, dielectric response, and surface charge distribution of RGD (1FUV) peptide.

PubMed

Adhikari, Puja; Wen, Amy M; French, Roger H; Parsegian, V Adrian; Steinmetz, Nicole F; Podgornik, Rudolf; Ching, Wai-Yim

2014-07-08

Long and short range molecular interactions govern molecular recognition and self-assembly of biological macromolecules. Microscopic parameters in the theories of these molecular interactions are either phenomenological or need to be calculated within a microscopic theory. We report a unified methodology for the ab initio quantum mechanical (QM) calculation that yields all the microscopic parameters, namely the partial charges as well as the frequency-dependent dielectric response function, that can then be taken as input for macroscopic theories of electrostatic, polar, and van der Waals-London dispersion intermolecular forces. We apply this methodology to obtain the electronic structure of the cyclic tripeptide RGD-4C (1FUV). This ab initio unified methodology yields the relevant parameters entering the long range interactions of biological macromolecules, providing accurate data for the partial charge distribution and the frequency-dependent dielectric response function of this peptide. These microscopic parameters determine the range and strength of the intricate intermolecular interactions between potential docking sites of the RGD-4C ligand and its integrin receptor.

Modeling the Normal and Neoplastic Cell Cycle with 'Realistic Boolean Genetic Networks': Their Application for Understanding Carcinogenesis and Assessing Therapeutic Strategies

NASA Technical Reports Server (NTRS)

Szallasi, Zoltan; Liang, Shoudan

2000-01-01

In this paper we show how Boolean genetic networks could be used to address complex problems in cancer biology. First, we describe a general strategy to generate Boolean genetic networks that incorporate all relevant biochemical and physiological parameters and cover all of their regulatory interactions in a deterministic manner. Second, we introduce 'realistic Boolean genetic networks' that produce time series measurements very similar to those detected in actual biological systems. Third, we outline a series of essential questions related to cancer biology and cancer therapy that could be addressed by the use of 'realistic Boolean genetic network' modeling.

Analysis of Nonstationary Time Series for Biological Rhythms Research.

PubMed

Leise, Tanya L

2017-06-01

This article is part of a Journal of Biological Rhythms series exploring analysis and statistics topics relevant to researchers in biological rhythms and sleep research. The goal is to provide an overview of the most common issues that arise in the analysis and interpretation of data in these fields. In this article on time series analysis for biological rhythms, we describe some methods for assessing the rhythmic properties of time series, including tests of whether a time series is indeed rhythmic. Because biological rhythms can exhibit significant fluctuations in their period, phase, and amplitude, their analysis may require methods appropriate for nonstationary time series, such as wavelet transforms, which can measure how these rhythmic parameters change over time. We illustrate these methods using simulated and real time series.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Biology, Bionomics and Molecular Biology of Anopheles sinensis Wiedemann 1828 (Diptera: Culicidae), Main Malaria Vector in China

PubMed Central

Feng, Xinyu; Zhang, Shaosen; Huang, Fang; Zhang, Li; Feng, Jun; Xia, Zhigui; Zhou, Hejun; Hu, Wei; Zhou, Shuisen

2017-01-01

China has set a goal to eliminate all malaria in the country by 2020, but it is unclear if current understanding of malaria vectors and transmission is sufficient to achieve this objective. Anopheles sinensis is the most widespread malaria vector specie in China, which is also responsible for vivax malaria outbreak in central China. We reviewed literature from 1954 to 2016 on An. sinensis with emphasis on biology, bionomics, and molecular biology. A total of 538 references were relevant and included. An. sienesis occurs in 29 Chinese provinces. Temperature can affect most life-history parameters. Most An. sinensis are zoophilic, but sometimes they are facultatively anthropophilic. Sporozoite analysis demonstrated An. sinensis efficacy on Plasmodium vivax transmission. An. sinensis was not stringently refractory to P. falciparum under experimental conditions, however, sporozoite was not found in salivary glands of field collected An. sinensis. The literature on An. sienesis biology and bionomics was abundant, but molecular studies, such as gene functions and mechanisms, were limited. Only 12 molecules (genes, proteins or enzymes) have been studied. In addition, there were considerable untapped omics resources for potential vector control tools. Existing information on An. sienesis could serve as a baseline for advanced research on biology, bionomics and genetics relevant to vector control strategies. PMID:28848504

Biology, Bionomics and Molecular Biology of Anopheles sinensis Wiedemann 1828 (Diptera: Culicidae), Main Malaria Vector in China.

PubMed

Feng, Xinyu; Zhang, Shaosen; Huang, Fang; Zhang, Li; Feng, Jun; Xia, Zhigui; Zhou, Hejun; Hu, Wei; Zhou, Shuisen

2017-01-01

China has set a goal to eliminate all malaria in the country by 2020, but it is unclear if current understanding of malaria vectors and transmission is sufficient to achieve this objective. Anopheles sinensis is the most widespread malaria vector specie in China, which is also responsible for vivax malaria outbreak in central China. We reviewed literature from 1954 to 2016 on An. sinensis with emphasis on biology, bionomics, and molecular biology. A total of 538 references were relevant and included. An. sienesis occurs in 29 Chinese provinces. Temperature can affect most life-history parameters. Most An. sinensis are zoophilic, but sometimes they are facultatively anthropophilic. Sporozoite analysis demonstrated An. sinensis efficacy on Plasmodium vivax transmission. An. sinensis was not stringently refractory to P. falciparum under experimental conditions, however, sporozoite was not found in salivary glands of field collected An. sinensis . The literature on An. sienesis biology and bionomics was abundant, but molecular studies, such as gene functions and mechanisms, were limited. Only 12 molecules (genes, proteins or enzymes) have been studied. In addition, there were considerable untapped omics resources for potential vector control tools. Existing information on An. sienesis could serve as a baseline for advanced research on biology, bionomics and genetics relevant to vector control strategies.

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.

Comparative evaluation of topographical data of dental implant surfaces applying optical interferometry and scanning electron microscopy.

PubMed

Kournetas, N; Spintzyk, S; Schweizer, E; Sawada, T; Said, F; Schmid, P; Geis-Gerstorfer, J; Eliades, G; Rupp, F

2017-08-01

Comparability of topographical data of implant surfaces in literature is low and their clinical relevance often equivocal. The aim of this study was to investigate the ability of scanning electron microscopy and optical interferometry to assess statistically similar 3-dimensional roughness parameter results and to evaluate these data based on predefined criteria regarded relevant for a favorable biological response. Four different commercial dental screw-type implants (NanoTite Certain Prevail, TiUnite Brånemark Mk III, XiVE S Plus and SLA Standard Plus) were analyzed by stereo scanning electron microscopy and white light interferometry. Surface height, spatial and hybrid roughness parameters (Sa, Sz, Ssk, Sku, Sal, Str, Sdr) were assessed from raw and filtered data (Gaussian 50μm and 5μm cut-off-filters), respectively. Data were statistically compared by one-way ANOVA and Tukey-Kramer post-hoc test. For a clinically relevant interpretation, a categorizing evaluation approach was used based on predefined threshold criteria for each roughness parameter. The two methods exhibited predominantly statistical differences. Dependent on roughness parameters and filter settings, both methods showed variations in rankings of the implant surfaces and differed in their ability to discriminate the different topographies. Overall, the analyses revealed scale-dependent roughness data. Compared to the pure statistical approach, the categorizing evaluation resulted in much more similarities between the two methods. This study suggests to reconsider current approaches for the topographical evaluation of implant surfaces and to further seek after proper experimental settings. Furthermore, the specific role of different roughness parameters for the bioresponse has to be studied in detail in order to better define clinically relevant, scale-dependent and parameter-specific thresholds and ranges. Copyright © 2017 The Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

SBRML: a markup language for associating systems biology data with models.

PubMed

Dada, Joseph O; Spasić, Irena; Paton, Norman W; Mendes, Pedro

2010-04-01

Research in systems biology is carried out through a combination of experiments and models. Several data standards have been adopted for representing models (Systems Biology Markup Language) and various types of relevant experimental data (such as FuGE and those of the Proteomics Standards Initiative). However, until now, there has been no standard way to associate a model and its entities to the corresponding datasets, or vice versa. Such a standard would provide a means to represent computational simulation results as well as to frame experimental data in the context of a particular model. Target applications include model-driven data analysis, parameter estimation, and sharing and archiving model simulations. We propose the Systems Biology Results Markup Language (SBRML), an XML-based language that associates a model with several datasets. Each dataset is represented as a series of values associated with model variables, and their corresponding parameter values. SBRML provides a flexible way of indexing the results to model parameter values, which supports both spreadsheet-like data and multidimensional data cubes. We present and discuss several examples of SBRML usage in applications such as enzyme kinetics, microarray gene expression and various types of simulation results. The XML Schema file for SBRML is available at http://www.comp-sys-bio.org/SBRML under the Academic Free License (AFL) v3.0.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks.

PubMed

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-08-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks

PubMed Central

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-01-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is “non-intrusive” and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design. PMID:26317784

Computing the structural influence matrix for biological systems.

PubMed

Giordano, Giulia; Cuba Samaniego, Christian; Franco, Elisa; Blanchini, Franco

2016-06-01

We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics.

WE-D-BRE-07: Variance-Based Sensitivity Analysis to Quantify the Impact of Biological Uncertainties in Particle Therapy

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

Kamp, F.; Brueningk, S.C.; Wilkens, J.J.

Purpose: In particle therapy, treatment planning and evaluation are frequently based on biological models to estimate the relative biological effectiveness (RBE) or the equivalent dose in 2 Gy fractions (EQD2). In the context of the linear-quadratic model, these quantities depend on biological parameters (α, β) for ions as well as for the reference radiation and on the dose per fraction. The needed biological parameters as well as their dependency on ion species and ion energy typically are subject to large (relative) uncertainties of up to 20–40% or even more. Therefore it is necessary to estimate the resulting uncertainties in e.g.more » RBE or EQD2 caused by the uncertainties of the relevant input parameters. Methods: We use a variance-based sensitivity analysis (SA) approach, in which uncertainties in input parameters are modeled by random number distributions. The evaluated function is executed 10{sup 4} to 10{sup 6} times, each run with a different set of input parameters, randomly varied according to their assigned distribution. The sensitivity S is a variance-based ranking (from S = 0, no impact, to S = 1, only influential part) of the impact of input uncertainties. The SA approach is implemented for carbon ion treatment plans on 3D patient data, providing information about variations (and their origin) in RBE and EQD2. Results: The quantification enables 3D sensitivity maps, showing dependencies of RBE and EQD2 on different input uncertainties. The high number of runs allows displaying the interplay between different input uncertainties. The SA identifies input parameter combinations which result in extreme deviations of the result and the input parameter for which an uncertainty reduction is the most rewarding. Conclusion: The presented variance-based SA provides advantageous properties in terms of visualization and quantification of (biological) uncertainties and their impact. The method is very flexible, model independent, and enables a broad assessment of uncertainties. Supported by DFG grant WI 3745/1-1 and DFG cluster of excellence: Munich-Centre for Advanced Photonics.« less

Exact solutions of a two parameter flux model and cryobiological applications.

PubMed

Benson, James D; Chicone, Carmen C; Critser, John K

2005-06-01

Solute-solvent transmembrane flux models are used throughout biological sciences with applications in plant biology, cryobiology (transplantation and transfusion medicine), as well as circulatory and kidney physiology. Using a standard two parameter differential equation model of solute and solvent transmembrane flux described by Jacobs [The simultaneous measurement of cell permeability to water and to dissolved substances, J. Cell. Comp. Physiol. 2 (1932) 427-444], we determine the functions that describe the intracellular water volume and moles of intracellular solute for every time t and every set of initial conditions. Here, we provide several novel biophysical applications of this theory to important biological problems. These include using this result to calculate the value of cell volume excursion maxima and minima along with the time at which they occur, a novel result that is of significant relevance to the addition and removal of permeating solutes during cryopreservation. We also present a methodology that produces extremely accurate sum of squares estimates when fitting data for cellular permeability parameter values. Finally, we show that this theory allows a significant increase in both accuracy and speed of finite element methods for multicellular volume simulations, which has critical clinical biophysical applications in cryosurgical approaches to cancer treatment.

Electronic Structure, Dielectric Response, and Surface Charge Distribution of RGD (1FUV) Peptide

PubMed Central

Adhikari, Puja; Wen, Amy M.; French, Roger H.; Parsegian, V. Adrian; Steinmetz, Nicole F.; Podgornik, Rudolf; Ching, Wai-Yim

2014-01-01

Long and short range molecular interactions govern molecular recognition and self-assembly of biological macromolecules. Microscopic parameters in the theories of these molecular interactions are either phenomenological or need to be calculated within a microscopic theory. We report a unified methodology for the ab initio quantum mechanical (QM) calculation that yields all the microscopic parameters, namely the partial charges as well as the frequency-dependent dielectric response function, that can then be taken as input for macroscopic theories of electrostatic, polar, and van der Waals-London dispersion intermolecular forces. We apply this methodology to obtain the electronic structure of the cyclic tripeptide RGD-4C (1FUV). This ab initio unified methodology yields the relevant parameters entering the long range interactions of biological macromolecules, providing accurate data for the partial charge distribution and the frequency-dependent dielectric response function of this peptide. These microscopic parameters determine the range and strength of the intricate intermolecular interactions between potential docking sites of the RGD-4C ligand and its integrin receptor. PMID:25001596

Estimation of biological parameters of marine organisms using linear and nonlinear acoustic scattering model-based inversion methods.

PubMed

Chu, Dezhang; Lawson, Gareth L; Wiebe, Peter H

2016-05-01

The linear inversion commonly used in fisheries and zooplankton acoustics assumes a constant inversion kernel and ignores the uncertainties associated with the shape and behavior of the scattering targets, as well as other relevant animal parameters. Here, errors of the linear inversion due to uncertainty associated with the inversion kernel are quantified. A scattering model-based nonlinear inversion method is presented that takes into account the nonlinearity of the inverse problem and is able to estimate simultaneously animal abundance and the parameters associated with the scattering model inherent to the kernel. It uses sophisticated scattering models to estimate first, the abundance, and second, the relevant shape and behavioral parameters of the target organisms. Numerical simulations demonstrate that the abundance, size, and behavior (tilt angle) parameters of marine animals (fish or zooplankton) can be accurately inferred from the inversion by using multi-frequency acoustic data. The influence of the singularity and uncertainty in the inversion kernel on the inversion results can be mitigated by examining the singular values for linear inverse problems and employing a non-linear inversion involving a scattering model-based kernel.

Medulloblastoma: Tumor Biology and Relevance to Treatment and Prognosis Paradigm.

PubMed

Coluccia, Daniel; Figuereido, Carlyn; Isik, Semra; Smith, Christian; Rutka, James T

2016-05-01

Medulloblastoma is a malignant embryonic brain tumor arising in the posterior fossa and typically occurring in pediatric patients. Current multimodal treatment regimes have significantly improved the survival rates; however, a marked heterogeneity in therapy response is observed, and one third of all patients die within 5 years after diagnosis. Large-scale genetic and transcriptome analysis revealed four medulloblastoma subgroups (WNT, SHH, Group 3, and Group 4) associated with different demographic parameters, tumor manifestation, and clinical behavior. Future treatment protocols will integrate molecular classification schemes to evaluate subgroup-specific intensification or de-escalation of adjuvant therapies aimed to increase tumor control and reduce iatrogenic induced morbidity. Furthermore, the identification of genetic drivers allows assessing target therapies in order to increase the chemotherapeutic armamentarium. This review highlights the biology behind the current classification system and elucidates relevant aspects of the disease influencing forthcoming clinical trials.

Medicinal Chemical Properties of Successful Central Nervous System Drugs

PubMed Central

Pajouhesh, Hassan; Lenz, George R.

2005-01-01

Summary: Fundamental physiochemical features of CNS drugs are related to their ability to penetrate the blood-brain barrier affinity and exhibit CNS activity. Factors relevant to the success of CNS drugs are reviewed. CNS drugs show values of molecular weight, lipophilicity, and hydrogen bond donor and acceptor that in general have a smaller range than general therapeutics. Pharmacokinetic properties can be manipulated by the medicinal chemist to a significant extent. The solubility, permeability, metabolic stability, protein binding, and human ether-ago-go-related gene inhibition of CNS compounds need to be optimized simultaneously with potency, selectivity, and other biological parameters. The balance between optimizing the physiochemical and pharmacokinetic properties to make the best compromises in properties is critical for designing new drugs likely to penetrate the blood brain barrier and affect relevant biological systems. This review is intended as a guide to designing CNS therapeutic agents with better drug-like properties. PMID:16489364

Exploring JWST's Capability to Constrain Habitability on Simulated Terrestrial TESS Planets

NASA Astrophysics Data System (ADS)

Tremblay, Luke; Britt, Amber; Batalha, Natasha; Schwieterman, Edward; Arney, Giada; Domagal-Goldman, Shawn; Mandell, Avi; Planetary Systems Laboratory; Virtual Planetary Laboratory

2017-01-01

In the following, we have worked to develop a flexible "observability" scale of biologically relevant molecules in the atmospheres of newly discovered exoplanets for the instruments aboard NASA's next flagship mission, the James Webb Space Telescope (JWST). We sought to create such a scale in order to provide the community with a tool with which to optimize target selection for JWST observations based on detections of the upcoming Transiting Exoplanet Satellite Survey (TESS). Current literature has laid the groundwork for defining both biologically relevant molecules as well as what characteristics would make a new world "habitable", but it has so far lacked a cohesive analysis of JWST's capabilities to observe these molecules in exoplanet atmospheres and thereby constrain habitability. In developing our Observability Scale, we utilized a range of hypothetical planets (over planetary radii and stellar insolation) and generated three self-consistent atmospheric models (of dierent molecular compositions) for each of our simulated planets. With these planets and their corresponding atmospheres, we utilized the most accurate JWST instrument simulator, created specically to process transiting exoplanet spectra. Through careful analysis of these simulated outputs, we were able to determine the relevant parameters that effected JWST's ability to constrain each individual molecular bands with statistical accuracy and therefore generate a scale based on those key parameters. As a preliminary test of our Observability Scale, we have also applied it to the list of TESS candidate stars in order to determine JWST's observational capabilities for any soon-to-be-detected planet in those solar systems.

A Study of the Interaction of Millimeter Wave Fields with Biological Systems.

DTIC Science & Technology

1984-07-01

structurally complex proteins . The third issue is the relevance of the parameters used in previous modeling efforts. The strength of the exciton-phonon...modes of proteins in the millimeter and submillimeter regions of the electromagnetic spectrum. Specifically: o " Four separate groups of frequencies...Rhodopseudomonas Sphaeroides (4). In industrial or military environments a significant number of personnel are exposed to electromagnetic fields

The biological activity of chernozems in the Central Caucasus Mountains (Terskii variant of altitudinal zonality), Kabardino-Balkaria

NASA Astrophysics Data System (ADS)

Gedgafova, F. V.; Uligova, T. S.; Gorobtsova, O. N.; Tembotov, R. Kh.

2015-12-01

Some parameters of the biological activity (humus content; activity of hydrolytic enzymes invertase, phosphatase, urease; and the intensity of carbon dioxide emission) were studied in the chernozems of agrocenoses and native biogeocenoses in the foothills of the Caucasus Mountains representing the Terskii variant of the altitudinal zonality. The statistically significant differences were revealed between the relevant characteristics of the soils of the agrocenoses and of the native biogeocenoses. The integral index of the ecological-biological state of the soils was used to estimate changes in the biological activity of the arable chernozems. The 40-60% decrease of this index in the cultivated chernozems testified to their degradation with a decrease in fertility and the disturbance of ecological functions as compared to these characteristics in the virgin chernozems.

Accelerated telomere attrition is associated with relative household income, diet and inflammation in the pSoBid cohort.

PubMed

Shiels, Paul G; McGlynn, Liane M; MacIntyre, Alan; Johnson, Paul C D; Batty, G David; Burns, Harry; Cavanagh, Jonathan; Deans, Kevin A; Ford, Ian; McConnachie, Alex; McGinty, Agnes; McLean, Jennifer S; Millar, Keith; Sattar, Naveed; Tannahill, Carol; Velupillai, Yoga N; Packard, Chris J

2011-01-01

It has previously been hypothesized that lower socio-economic status can accelerate biological ageing, and predispose to early onset of disease. This study investigated the association of socio-economic and lifestyle factors, as well as traditional and novel risk factors, with biological-ageing, as measured by telomere length, in a Glasgow based cohort that included individuals with extreme socio-economic differences. A total of 382 blood samples from the pSoBid study were available for telomere analysis. For each participant, data was available for socio-economic status factors, biochemical parameters and dietary intake. Statistical analyses were undertaken to investigate the association between telomere lengths and these aforementioned parameters. The rate of age-related telomere attrition was significantly associated with low relative income, housing tenure and poor diet. Notably, telomere length was positively associated with LDL and total cholesterol levels, but inversely correlated to circulating IL-6. These data suggest lower socio-economic status and poor diet are relevant to accelerated biological ageing. They also suggest potential associations between elevated circulating IL-6, a measure known to predict cardiovascular disease and diabetes with biological ageing. These observations require further study to tease out potential mechanistic links.

Caenorhabditis elegans - A model system for space biology studies

NASA Technical Reports Server (NTRS)

Johnson, Thomas E.; Nelson, Gregory A.

1991-01-01

The utility of the nematode Caenorhabditis elegans in studies spanning aspects of development, aging, and radiobiology is reviewed. These topics are interrelated via cellular and DNA repair processes especially in the context of oxidative stress and free-radical metabolism. The relevance of these research topics to problems in space biology is discussed and properties of the space environment are outlined. Exposure to the space-flight environment can induce rapid changes in living systems that are similar to changes occurring during aging; manipulation of these environmental parameters may represent an experimental strategy for studies of development and senescence. The current and future opportunities for such space-flight experimentation are presented.

Smart Contrast Agents for Magnetic Resonance Imaging.

PubMed

Bonnet, Célia S; Tóth, Éva

2016-01-01

By visualizing bioactive molecules or biological parameters in vivo, molecular imaging is searching for information at the molecular level in living organisms. In addition to contributing to earlier and more personalized diagnosis in medicine, it also helps understand and rationalize the molecular factors underlying physiological and pathological processes. In magnetic resonance imaging (MRI), complexes of paramagnetic metal ions, mostly lanthanides, are commonly used to enhance the intrinsic image contrast. They rely either on the relaxation effect of these metal chelates (T(1) agents), or on the phenomenon of paramagnetic chemical exchange saturation transfer (PARACEST agents). In both cases, responsive molecular magnetic resonance imaging probes can be designed to report on various biomarkers of biological interest. In this context, we review recent work in the literature and from our group on responsive T(1) and PARACEST MRI agents for the detection of biogenic metal ions (such as calcium or zinc), enzymatic activities, or neurotransmitter release. These examples illustrate the general strategies that can be applied to create molecular imaging agents with an MRI detectable response to biologically relevant parameters.

Review on innovative techniques in oil sludge bioremediation

NASA Astrophysics Data System (ADS)

Mahdi, Abdullah M. El; Aziz, Hamidi Abdul; Eqab, Eqab Sanoosi

2017-10-01

Petroleum hydrocarbon waste is produced in worldwide refineries in significant amount. In Libya, approximately 10,000 tons of oil sludge is generated in oil refineries (hydrocarbon waste mixtures) annually. Insufficient treatment of those wastes can threaten the human health and safety as well as our environment. One of the major challenges faced by petroleum refineries is the safe disposal of oil sludge generated during the cleaning and refining process stages of crude storage facilities. This paper reviews the hydrocarbon sludge characteristics and conventional methods for remediation of oil hydrocarbon from sludge. This study intensively focuses on earlier literature to describe the recently selected innovation technology in oily hydrocarbon sludge bioremediation process. Conventional characterization parameters or measurable factors can be gathered in chemical, physical, and biological parameters: (1) Chemical parameters are consequently necessary in the case of utilization of topsoil environment when they become relevant to the presence of nutrients and toxic compounds; (2) Physical parameters provide general data on sludge process and hand ability; (3) Biological parameters provide data on microbial activity and organic matter presence, which will be used to evaluate the safety of the facilities. The objective of this research is to promote the bioremediating oil sludge feasibility from Marsa El Hariga Terminal and Refinery (Tobruk).

Atomic force microscopy of red-light photoreceptors using peakforce quantitative nanomechanical property mapping.

PubMed

Kroeger, Marie E; Sorenson, Blaire A; Thomas, J Santoro; Stojković, Emina A; Tsonchev, Stefan; Nicholson, Kenneth T

2014-10-24

Atomic force microscopy (AFM) uses a pyramidal tip attached to a cantilever to probe the force response of a surface. The deflections of the tip can be measured to ~10 pN by a laser and sectored detector, which can be converted to image topography. Amplitude modulation or "tapping mode" AFM involves the probe making intermittent contact with the surface while oscillating at its resonant frequency to produce an image. Used in conjunction with a fluid cell, tapping-mode AFM enables the imaging of biological macromolecules such as proteins in physiologically relevant conditions. Tapping-mode AFM requires manual tuning of the probe and frequent adjustments of a multitude of scanning parameters which can be challenging for inexperienced users. To obtain high-quality images, these adjustments are the most time consuming. PeakForce Quantitative Nanomechanical Property Mapping (PF-QNM) produces an image by measuring a force response curve for every point of contact with the sample. With ScanAsyst software, PF-QNM can be automated. This software adjusts the set-point, drive frequency, scan rate, gains, and other important scanning parameters automatically for a given sample. Not only does this process protect both fragile probes and samples, it significantly reduces the time required to obtain high resolution images. PF-QNM is compatible for AFM imaging in fluid; therefore, it has extensive application for imaging biologically relevant materials. The method presented in this paper describes the application of PF-QNM to obtain images of a bacterial red-light photoreceptor, RpBphP3 (P3), from photosynthetic R. palustris in its light-adapted state. Using this method, individual protein dimers of P3 and aggregates of dimers have been observed on a mica surface in the presence of an imaging buffer. With appropriate adjustments to surface and/or solution concentration, this method may be generally applied to other biologically relevant macromolecules and soft materials.

Endogenous Crisis Waves: Stochastic Model with Synchronized Collective Behavior

NASA Astrophysics Data System (ADS)

Gualdi, Stanislao; Bouchaud, Jean-Philippe; Cencetti, Giulia; Tarzia, Marco; Zamponi, Francesco

2015-02-01

We propose a simple framework to understand commonly observed crisis waves in macroeconomic agent-based models, which is also relevant to a variety of other physical or biological situations where synchronization occurs. We compute exactly the phase diagram of the model and the location of the synchronization transition in parameter space. Many modifications and extensions can be studied, confirming that the synchronization transition is extremely robust against various sources of noise or imperfections.

Investigations of biological processes in Austrian MBT plants.

PubMed

Tintner, J; Smidt, E; Böhm, K; Binner, E

2010-10-01

Mechanical biological treatment (MBT) of municipal solid waste (MSW) has become an important technology in waste management during the last decade. The paper compiles investigations of mechanical biological processes in Austrian MBT plants. Samples from all plants representing different stages of degradation were included in this study. The range of the relevant parameters characterizing the materials and their behavior, e.g. total organic carbon, total nitrogen, respiration activity and gas generation sum, was determined. The evolution of total carbon and nitrogen containing compounds was compared and related to process operation. The respiration activity decreases in most of the plants by about 90% of the initial values whereas the ammonium release is still ongoing at the end of the biological treatment. If the biogenic waste fraction is not separated, it favors humification in MBT materials that is not observed to such extent in MSW. The amount of organic carbon is about 15% dry matter at the end of the biological treatment. (c) 2010 Elsevier Ltd. All rights reserved.

Scaling Laws of Microactuators and Potential Applications of Electroactive Polymers in MEMS

NASA Technical Reports Server (NTRS)

Liu, Chang; Bar-Cohen, Y.

1999-01-01

Besides the scale factor that distinguishes the various species, fundamentally biological muscles changes little between species, indicating a highly optimized system. Electroactive polymer actuators offer the closest resemblance to biological muscles, however besides the large actuation displacement these materials are falling short with regards to the actuation force. As improved materials are emerging it is becoming necessary to address key issues such as the need for effective electromechanical modeling and guiding parameters in scaling the actuators. In this paper, we will review the scaling laws for three major actuation mechanisms that are of relevance to micro electromechanical systems: electrostatic actuation, magnetic actuation, thermal bimetallic actuation, and piezoelectric actuation.

Balancing novelty with confined chemical space in modern drug discovery.

PubMed

Medina-Franco, José L; Martinez-Mayorga, Karina; Meurice, Nathalie

2014-02-01

The concept of chemical space has broad applications in drug discovery. In response to the needs of drug discovery campaigns, different approaches are followed to efficiently populate, mine and select relevant chemical spaces that overlap with biologically relevant chemical spaces. This paper reviews major trends in current drug discovery and their impact on the mining and population of chemical space. We also survey different approaches to develop screening libraries with confined chemical spaces balancing physicochemical properties. In this context, the confinement is guided by criteria that can be divided in two broad categories: i) library design focused on a relevant therapeutic target or disease and ii) library design focused on the chemistry or a desired molecular function. The design and development of chemical libraries should be associated with the specific purpose of the library and the project goals. The high complexity of drug discovery and the inherent imperfection of individual experimental and computational technologies prompt the integration of complementary library design and screening approaches to expedite the identification of new and better drugs. Library design approaches including diversity-oriented synthesis, biological-oriented synthesis or combinatorial library design, to name a few, and the design of focused libraries driven by target/disease, chemical structure or molecular function are more efficient if they are guided by multi-parameter optimization. In this context, consideration of pharmaceutically relevant properties is essential for balancing novelty with chemical space in drug discovery.

Comparison of the perceived relevance of oral biology reported by students and interns of a Pakistani dental college.

PubMed

Farooq, I; Ali, S

2014-11-01

The purpose of this study was to analyse and compare the perceived relevance of oral biology with dentistry as reported by dental students and interns and to investigate the most popular teaching approach and learning resource. A questionnaire aiming to ask about the relevance of oral biology to dentistry, most popular teaching method and learning resource was utilised in this study. Study groups encompassed second-year dental students who had completed their course and dental interns. The data were obtained and analysed statistically. The overall response rate for both groups was 60%. Both groups reported high relevance of oral biology to dentistry. Perception of dental interns regarding the relevance of oral biology to dentistry was higher than that of students. Both groups identified student presentations as the most important teaching method. Amongst the most important learning resources, textbooks were considered most imperative by interns, whereas lecture handouts received the highest importance score by students. Dental students and interns considered oral biology to be relevant to dentistry, although greater relevance was reported by interns. Year-wise advancement in dental education and training improves the perception of the students about the relevance of oral biology to dentistry. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Student perception of relevance of biology content to everyday life: A study in higher education biology courses

NASA Astrophysics Data System (ADS)

Himschoot, Agnes Rose

The purpose of this mixed method case study was to examine the effects of methods of instruction on students' perception of relevance in higher education non-biology majors' courses. Nearly ninety percent of all students in a liberal arts college are required to take a general biology course. It is proposed that for many of those students, this is the last science course they will take for life. General biology courses are suspected of discouraging student interest in biology with large enrollment, didactic instruction, covering a huge amount of content in one semester, and are charged with promoting student disengagement with biology by the end of the course. Previous research has been aimed at increasing student motivation and interest in biology as measured by surveys and test results. Various methods of instruction have been tested and show evidence of improved learning gains. This study focused on students' perception of relevance of biology content to everyday life and the methods of instruction that increase it. A quantitative survey was administered to assess perception of relevance pre and post instruction over three topics typically taught in a general biology course. A second quantitative survey of student experiences during instruction was administered to identify methods of instruction used in the course lecture and lab. While perception of relevance dropped in the study, qualitative focus groups provided insight into the surprising results by identifying topics that are more relevant than the ones chosen for the study, conveying the affects of the instructor's personal and instructional skills on student engagement, explanation of how active engagement during instruction promotes understanding of relevance, the roll of laboratory in promoting students' understanding of relevance as well as identifying external factors that affect student engagement. The study also investigated the extent to which gender affected changes in students' perception of relevance. The results of this study will inform instructors' pedagogical and logistical choices in the design and implementation of higher education biology courses for non-biology majors. Recommendations for future research will include refining the study to train instructors in methods of instruction that promote student engagement as well as to identify biology topics that are more relevant to students enrolled in non-major biology courses.

Methods for Improving the Curvature of Steerable Needles in Biological Tissue

PubMed Central

Adebar, Troy K.; Greer, Joseph D.; Laeseke, Paul F.; Hwang, Gloria L.; Okamura, Allison M.

2016-01-01

Robotic needle steering systems have the potential to improve percutaneous interventions such as radiofrequency ablation of liver tumors, but steering techniques described to date have not achieved sufficiently small radius of curvature in biological tissue to be relevant to this application. In this work, the impact of tip geometry on steerable needle curvature is examined. Finite-element simulations and experiments with bent-tip needles in ex vivo liver tissue demonstrate that selection of tip length and angle can greatly improve curvature, with radius of curvature below 5 cm in liver tissue possible through judicious selection of these parameters. Motivated by the results of this analysis, a new articulated-tip steerable needle is described, in which a distal section is actively switched by a robotic system between a straight tip (resulting in a straight path) and a bent tip (resulting in a curved path). This approach allows the tip length and angle to be increased, while the straight configuration allows the needle tip to still pass through an introducer sheath and rotate inside the body. Validation testing in liver tissue shows that the new articulated-tip steerable needle achieves smaller radius of curvature compared to bent-tip needles described in previous work. Steerable needles with optimized tip parameters, which can generate tight curves in liver tissue, increase the clinical relevance of needle steering to percutaneous interventions. PMID:26441438

Prediction of EST functional relationships via literature mining with user-specified parameters.

PubMed

Wang, Hei-Chia; Huang, Tian-Hsiang

2009-04-01

The massive amount of expressed sequence tags (ESTs) gathered over recent years has triggered great interest in efficient applications for genomic research. In particular, EST functional relationships can be used to determine a possible gene network for biological processes of interest. In recent years, many researchers have tried to determine EST functional relationships by analyzing the biological literature. However, it has been challenging to find efficient prediction methods. Moreover, an annotated EST is usually associated with many functions, so successful methods must be able to distinguish between relevant and irrelevant functions based on user specifications. This paper proposes a method to discover functional relationships between ESTs of interest by analyzing literature from the Medical Literature Analysis and Retrieval System Online, with user-specified parameters for selecting keywords. This method performs better than the multiple kernel documents method in setting up a specific threshold for gathering materials. The method is also able to uncover known functional relationships, as shown by a comparison with the Kyoto Encyclopedia of Genes and Genomes database. The reliable EST relationships predicted by the proposed method can help to construct gene networks for specific biological functions of interest.

Psychosocial influences on HIV-1 disease progression: neural, endocrine, and virologic mechanisms.

PubMed

Cole, Steve W

2008-06-01

This review surveys empirical research pertinent to the hypothesis that activity of the hypothalamus-pituitary-adrenal (HPA) axis and/or the sympathetic nervous system (SNS) might mediate biobehavioral influences on HIV-1 pathogenesis and disease progression. Data are considered based on causal effects of neuroeffector molecules on HIV-1 replication, prospective relationships between neural/endocrine parameters and HIV-relevant biological or clinical markers, and correlational data consistent with in vivo neural/endocrine mediation in human or animal studies. Results show that HPA and SNS effector molecules can enhance HIV-1 replication in cellular models via effects on viral infectivity, viral gene expression, and the innate immune response to infection. Animal models and human clinical studies both provide evidence consistent with SNS regulation of viral replication, but data on HPA mediation are less clear. Regulation of leukocyte biology by neuroeffector molecules provides a plausible biological mechanism by which psychosocial factors might influence HIV-1 pathogenesis, even in the era of effective antiretroviral therapy. As such, neural and endocrine parameters might provide useful biomarkers for gauging the promise of behavioral interventions and suggest novel adjunctive strategies for controlling HIV-1 disease progression.

Is the evaluation of "traditional" physicochemical parameters sufficient to explain the potential toxicity of the treated wastewater at sewage treatment plants?

PubMed

Vasquez, M I; Fatta-Kassinos, D

2013-06-01

Water scarcity is one of the most important environmental and public health problems of our century. Treated wastewater reuse seems to be the most attractive option for the enhancement of water resources. However, the lack of uniform guidelines at European and/or Mediterranean level leaves room for application of varying guidelines and regulations, usually not based on risk assessment towards humans and the environment. The benefits of complementing the physicochemical evaluation of wastewater with a biological one are demonstrated in the present study using Cyprus, a country with extended water reuse applications, as an example. Four organisms from different trophic levels were used for the biological assessment of the wastewater, namely, Pseudokirchneriella subcapitata, Daphnia magna, Artemia salina and Vibrio fischeri. The physicochemical assessment of wastewater based on "traditional" chemical parameters indicated that the quality of the wastewater complies with the limits set by the relevant national guidelines for disposal. The ecotoxicological assessment, however, indicated the presence of toxicity throughout the sampling periods and most importantly an increase of the toxicity of the treated wastewater during summer compared to winter. The resulting poor correlation between the physicochemical and biological assessments demonstrates that the two assessments are necessary and should be performed in parallel in order to be able to obtain concrete results on the overall quality of the treated effluent. Moreover, a hazard classification scheme for wastewater is proposed, which can enable the comparison of the data sets of the various parameters deriving from the biological assessment in a comprehensive way.

Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites

PubMed Central

Meinicke, Peter; Tech, Maike; Morgenstern, Burkhard; Merkl, Rainer

2004-01-01

Background Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying biological signals. Results We propose a kernel-based approach to datamining on biological sequences. With our method it is possible to model and analyze positional variability of oligomers of any length in a natural way. On one hand this is achieved by mapping the sequences to an intuitive but high-dimensional feature space, well-suited for interpretation of the learnt models. On the other hand, by means of the kernel trick we can provide a general learning algorithm for that high-dimensional representation because all required statistics can be computed without performing an explicit feature space mapping of the sequences. By introducing a kernel parameter that controls the degree of position-dependency, our feature space representation can be tailored to the characteristics of the biological problem at hand. A regularized learning scheme enables application even to biological problems for which only small sets of example sequences are available. Our approach includes a visualization method for transparent representation of characteristic sequence features. Thereby importance of features can be measured in terms of discriminative strength with respect to classification of the underlying sequences. To demonstrate and validate our concept on a biochemically well-defined case, we analyze E. coli translation initiation sites in order to show that we can find biologically relevant signals. For that case, our results clearly show that the Shine-Dalgarno sequence is the most important signal upstream a start codon. The variability in position and composition we found for that signal is in accordance with previous biological knowledge. We also find evidence for signals downstream of the start codon, previously introduced as transcriptional enhancers. These signals are mainly characterized by occurrences of adenine in a region of about 4 nucleotides next to the start codon. Conclusions We showed that the oligo kernel can provide a valuable tool for the analysis of relevant signals in biological sequences. In the case of translation initiation sites we could clearly deduce the most discriminative motifs and their positional variation from example sequences. Attractive features of our approach are its flexibility with respect to oligomer length and position conservation. By means of these two parameters oligo kernels can easily be adapted to different biological problems. PMID:15511290

Tunable Collagen I Hydrogels for Engineered Physiological Tissue Micro-Environments

PubMed Central

Antoine, Elizabeth E.; Vlachos, Pavlos P.; Rylander, Marissa N.

2015-01-01

Collagen I hydrogels are commonly used to mimic the extracellular matrix (ECM) for tissue engineering applications. However, the ability to design collagen I hydrogels similar to the properties of physiological tissues has been elusive. This is primarily due to the lack of quantitative correlations between multiple fabrication parameters and resulting material properties. This study aims to enable informed design and fabrication of collagen hydrogels in order to reliably and reproducibly mimic a variety of soft tissues. We developed empirical predictive models relating fabrication parameters with material and transport properties. These models were obtained through extensive experimental characterization of these properties, which include compression modulus, pore and fiber diameter, and diffusivity. Fabrication parameters were varied within biologically relevant ranges and included collagen concentration, polymerization pH, and polymerization temperature. The data obtained from this study elucidates previously unknown fabrication-property relationships, while the resulting equations facilitate informed a priori design of collagen hydrogels with prescribed properties. By enabling hydrogel fabrication by design, this study has the potential to greatly enhance the utility and relevance of collagen hydrogels in order to develop physiological tissue microenvironments for a wide range of tissue engineering applications. PMID:25822731

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

Silk-polypyrrole biocompatible actuator performance under biologically relevant conditions

NASA Astrophysics Data System (ADS)

Hagler, Jo'elen; Peterson, Ben; Murphy, Amanda; Leger, Janelle

Biocompatible actuators that are capable of controlled movement and can function under biologically relevant conditions are of significant interest in biomedical fields. Previously, we have demonstrated that a composite material of silk biopolymer and the conducting polymer polypyrrole (PPy) can be formed into a bilayer device that can bend under applied voltage. Further, these silk-PPy composites can generate forces comparable to human muscle (>0.1 MPa) making them ideal candidates for interfacing with biological tissues. Here silk-PPy composite films are tested for performance under biologically relevant conditions including exposure to a complex protein serum and biologically relevant temperatures. Free-end bending actuation performance, current response, force generation and, mass degradation were investigated . Preliminary results show that when exposed to proteins and biologically relevant temperatures, these silk-PPy composites show minimal degradation and are able to generate forces and conduct currents comparable to devices tested under standard conditions. NSF.

On the relationship between indentation hardness and modulus, and the damage resistance of biological materials.

PubMed

Labonte, David; Lenz, Anne-Kristin; Oyen, Michelle L

2017-07-15

The remarkable mechanical performance of biological materials is based on intricate structure-function relationships. Nanoindentation has become the primary tool for characterising biological materials, as it allows to relate structural changes to variations in mechanical properties on small scales. However, the respective theoretical background and associated interpretation of the parameters measured via indentation derives largely from research on 'traditional' engineering materials such as metals or ceramics. Here, we discuss the functional relevance of indentation hardness in biological materials by presenting a meta-analysis of its relationship with indentation modulus. Across seven orders of magnitude, indentation hardness was directly proportional to indentation modulus. Using a lumped parameter model to deconvolute indentation hardness into components arising from reversible and irreversible deformation, we establish criteria which allow to interpret differences in indentation hardness across or within biological materials. The ratio between hardness and modulus arises as a key parameter, which is related to the ratio between irreversible and reversible deformation during indentation, the material's yield strength, and the resistance to irreversible deformation, a material property which represents the energy required to create a unit volume of purely irreversible deformation. Indentation hardness generally increases upon material dehydration, however to a larger extent than expected from accompanying changes in indentation modulus, indicating that water acts as a 'plasticiser'. A detailed discussion of the role of indentation hardness, modulus and toughness in damage control during sharp or blunt indentation yields comprehensive guidelines for a performance-based ranking of biological materials, and suggests that quasi-plastic deformation is a frequent yet poorly understood damage mode, highlighting an important area of future research. Instrumented indentation is a widespread tool for characterising the mechanical properties of biological materials. Here, we show that the ratio between indentation hardness and modulus is approximately constant in biological materials. A simple elastic-plastic series deformation model is employed to rationalise part of this correlation, and criteria for a meaningful comparison of indentation hardness across biological materials are proposed. The ratio between indentation hardness and modulus emerges as the key parameter characterising the relative amount of irreversible deformation during indentation. Despite their comparatively high hardness to modulus ratio, biological materials are susceptible to quasiplastic deformation, due to their high toughness: quasi-plastic deformation is hence hypothesised to be a frequent yet poorly understood phenomenon, highlighting an important area of future research. Copyright © 2017 Acta Materialia Inc. All rights reserved.

Ultrasensitive investigations of biological systems by fluorescence correlation spectroscopy.

PubMed

Haustein, Elke; Schwille, Petra

2003-02-01

Fluorescence correlation spectroscopy (FCS) extracts information about molecular dynamics from the tiny fluctuations that can be observed in the emission of small ensembles of fluorescent molecules in thermodynamic equilibrium. Employing a confocal setup in conjunction with highly dilute samples, the average number of fluorescent particles simultaneously within the measurement volume (approximately 1 fl) is minimized. Among the multitude of chemical and physical parameters accessible by FCS are local concentrations, mobility coefficients, rate constants for association and dissociation processes, and even enzyme kinetics. As any reaction causing an alteration of the primary measurement parameters such as fluorescence brightness or mobility can be monitored, the application of this noninvasive method to unravel processes in living cells is straightforward. Due to the high spatial resolution of less than 0.5 microm, selective measurements in cellular compartments, e.g., to probe receptor-ligand interactions on cell membranes, are feasible. Moreover, the observation of local molecular dynamics provides access to environmental parameters such as local oxygen concentrations, pH, or viscosity. Thus, this versatile technique is of particular attractiveness for researchers striving for quantitative assessment of interactions and dynamics of small molecular quantities in biologically relevant systems.

Assimilable organic carbon (AOC) variation in reclaimed water: Insight on biological stability evaluation and control for sustainable water reuse.

PubMed

Chen, Zhuo; Yu, Tong; Ngo, Huu Hao; Lu, Yun; Li, Guoqiang; Wu, Qianyuan; Li, Kuixiao; Bai, Yu; Liu, Shuming; Hu, Hong-Ying

2018-04-01

This review highlights the importance of conducting biological stability evaluation due to water reuse progression. Specifically, assimilable organic carbon (AOC) has been identified as a practical indicator for microbial occurrence and regrowth which ultimately influence biological stability. Newly modified AOC bioassays aimed for reclaimed water are introduced. Since elevated AOC levels are often detected after tertiary treatment, the review emphasizes that actions can be taken to either limit AOC levels prior to disinfection or conduct post-treatment (e.g. biological filtration) as a supplement to chemical oxidation based approaches (e.g. ozonation and chlorine disinfection). During subsequent distribution and storage, microbial community and possible microbial regrowth caused by complex interactions are discussed. It is suggested that microbial surveillance, AOC threshold values, real-time field applications and surrogate parameters could provide additional information. This review can be used to formulate regulatory plans and strategies, and to aid in deriving relevant control, management and operational guidance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Conditional robustness analysis for fragility discovery and target identification in biochemical networks and in cancer systems biology.

PubMed

Bianconi, Fortunato; Baldelli, Elisa; Ludovini, Vienna; Luovini, Vienna; Petricoin, Emanuel F; Crinò, Lucio; Valigi, Paolo

2015-10-19

The study of cancer therapy is a key issue in the field of oncology research and the development of target therapies is one of the main problems currently under investigation. This is particularly relevant in different types of tumor where traditional chemotherapy approaches often fail, such as lung cancer. We started from the general definition of robustness introduced by Kitano and applied it to the analysis of dynamical biochemical networks, proposing a new algorithm based on moment independent analysis of input/output uncertainty. The framework utilizes novel computational methods which enable evaluating the model fragility with respect to quantitative performance measures and parameters such as reaction rate constants and initial conditions. The algorithm generates a small subset of parameters that can be used to act on complex networks and to obtain the desired behaviors. We have applied the proposed framework to the EGFR-IGF1R signal transduction network, a crucial pathway in lung cancer, as an example of Cancer Systems Biology application in drug discovery. Furthermore, we have tested our framework on a pulse generator network as an example of Synthetic Biology application, thus proving the suitability of our methodology to the characterization of the input/output synthetic circuits. The achieved results are of immediate practical application in computational biology, and while we demonstrate their use in two specific examples, they can in fact be used to study a wider class of biological systems.

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.

Population Genomics and the Statistical Values of Race: An Interdisciplinary Perspective on the Biological Classification of Human Populations and Implications for Clinical Genetic Epidemiological Research

PubMed Central

Maglo, Koffi N.; Mersha, Tesfaye B.; Martin, Lisa J.

2016-01-01

The biological status and biomedical significance of the concept of race as applied to humans continue to be contentious issues despite the use of advanced statistical and clustering methods to determine continental ancestry. It is thus imperative for researchers to understand the limitations as well as potential uses of the concept of race in biology and biomedicine. This paper deals with the theoretical assumptions behind cluster analysis in human population genomics. Adopting an interdisciplinary approach, it demonstrates that the hypothesis that attributes the clustering of human populations to “frictional” effects of landform barriers at continental boundaries is empirically incoherent. It then contrasts the scientific status of the “cluster” and “cline” constructs in human population genomics, and shows how cluster may be instrumentally produced. It also shows how statistical values of race vindicate Darwin's argument that race is evolutionarily meaningless. Finally, the paper explains why, due to spatiotemporal parameters, evolutionary forces, and socio-cultural factors influencing population structure, continental ancestry may be pragmatically relevant to global and public health genomics. Overall, this work demonstrates that, from a biological systematic and evolutionary taxonomical perspective, human races/continental groups or clusters have no natural meaning or objective biological reality. In fact, the utility of racial categorizations in research and in clinics can be explained by spatiotemporal parameters, socio-cultural factors, and evolutionary forces affecting disease causation and treatment response. PMID:26925096

Stimulus Sensitivity of a Spiking Neural Network Model

NASA Astrophysics Data System (ADS)

Chevallier, Julien

2018-02-01

Some recent papers relate the criticality of complex systems to their maximal capacity of information processing. In the present paper, we consider high dimensional point processes, known as age-dependent Hawkes processes, which have been used to model spiking neural networks. Using mean-field approximation, the response of the network to a stimulus is computed and we provide a notion of stimulus sensitivity. It appears that the maximal sensitivity is achieved in the sub-critical regime, yet almost critical for a range of biologically relevant parameters.

Social and environmental factors modulate leucocyte profiles in free-living Greylag geese (Anser anser)

PubMed Central

Ludwig, Sonja C.; Hemetsberger, Josef; Kotrschal, Kurt; Wascher, Claudia A.F.

2017-01-01

Background Blood parameters such as haematocrit or leucocyte counts are indicators of immune status and health, which can be affected, in a complex way, by exogenous as well as endogenous factors. Additionally, social context is known to be among the most potent stressors in group living individuals, therefore potentially influencing haematological parameters. However, with few exceptions, this potential causal relationship received only moderate scientific attention. Methods In a free-living and individually marked population of the highly social and long-lived Greylag goose, Anser anser, we relate variation in haematocrit (HCT), heterophils to lymphocytes ratio (H/L) and blood leucocyte counts to the following factors: intrinsic (sex, age, raising condition, i.e. goose- or hand-raised), social (pair-bond status, pair-bond duration and parental experience) and environmental (biologically relevant periods, ambient temperature) factors. Blood samples were collected repeatedly from a total of 105 focal birds during three biologically relevant seasons (winter flock, mating season, summer). Results We found significant relationships between haematological parameters and social as well as environmental factors. During the mating season, unpaired individuals had higher HCT compared to paired and family individuals and this pattern reversed in fall. Similarly, H/L ratio was positively related to pair-bond status in a seasonally dependent way, with highest values during mating and successful pairs had higher H/L ratio than unsuccessful ones. Also, absolute number of leucocytes tended to vary depending on raising condition in a seasonally dependent way. Discussion Haematology bears a great potential in ecological and behavioural studies on wild vertebrates. In sum, we found that HTC, H/L ratio and absolute number of leucocytes are modulated by social factors and conclude that they may be considered valid indicators of individual stress load. PMID:28070455

Application of Biologically-Based Lumping To Investigate the ...

EPA Pesticide Factsheets

People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. However, investigators have often considered complex mixtures as one lumped entity. Valuable information can be obtained from these experiments, though this simplification provides little insight into the impact of a mixture's chemical composition on toxicologically-relevant metabolic interactions that may occur among its constituents. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically-based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate performance of our PBPK model. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course kinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for the 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 non-target chemicals. Application of this biologic

Monitoring biological heterogeneity in a northern mixed prairie using hierarchical remote sensing methods

NASA Astrophysics Data System (ADS)

Zhang, Chunhua

Heterogeneity, the degree of dissimilarity, is one of the most important and widely applicable concepts in ecology. It is highly related to ecosystem conditions and features wildlife habitat. Grasslands have been described as inherently heterogeneous because their composition and productivity are highly variable across multiple scales. Therefore, biological heterogeneity can be an indicator of ecosystem health. The mixed prairie in Canada, characterized by its semiarid environment, sparse canopy, and plant litter, offers a challenging region for environmental research using remote sensing techniques. This thesis dwells with the plant canopy heterogeneity of the mixed prairie ecosystem in the Grasslands National Park (GNP) and surrounding pastures by combining field biological parameters (e.g., grass cover, leaf area index, and biomass), field collected hyperspectral data, and hierarchical resolution satellite imagery. The thesis scrutinized four aspects of heterogeneity study: the importance of scale in grassland research, relationships between biological parameters and remotely collected data, methodology of measuring biological heterogeneity, and the influence of climatic variation on grasslands biological heterogeneity. First, the importance of scale is examined by applying the semivariogram analysis on field collected hyperspectral and biophysical data. Results indicate that 15 - 20 m should be the appropriate resolution when variations of biological parameters and canopy reflectance are sampled. Therefore, it is reasonable to use RADARSAT 1, Landsat TM, and SPOT images, whose resolutions are around 20 m, to assess the variation of biological heterogeneity. Second, the efficiency of vegetation indices derived from SPOT 4 and Landsat 5 TM images in monitoring the northern mixed prairie health was examined using Pearson's correlation and stepwise regression analyses. Results show that the spectral curve of the grass canopy is similar to that of the bare soil with lower reflectance at each band. Therefore, vegetation indices are not necessarily better than reflectance at green and red wavelength regions in extracting biological information. Two new indices, combining reflectance from red and mid infrared wavelength regions, are proposed to measure biological parameters in the northern mixed prairie. Third, texture analysis was applied to quantify the biological variation in the grasslands. The textural parameters of RADARSAT imagery correlated highly with standard deviation of the field collected canopy parameters. Therefore, textural parameters can be applied to study the variations within the mixed prairie. Finally, the impacts of climatic variation on grassland heterogeneity at a long time scale were evaluated using Advanced Very High Resolution Radiometer (AVHRR), Normalized Difference Vegetation Index (NDVI), Maximum Value Composite (MVC), and SPOT Vegetation NDVI MVC imagery from 1993 to 2004. A drought index based on precipitation data was used to represent soil moisture for the study area. It was found that changes of temperature and precipitation explain about 50% of the variation in AVHRR NDVI (i.e., temporal heterogeneity) of the northern mixed prairie. Trend line analysis indicates that the removal of grazing cattle carry multiple influences such as decreasing NDVI in some parts of the upland and valley grassland and increasing NDVI in the valley grassland. Results from this thesis are relevant for park management by adjusting grassland management strategies and monitoring the changes in community sizes. The other output of the thesis is furthering the remote sensing investigation of the mixed prairie based on information of the most appropriate resolution imagery.

Correlation between structure, retention, property, and activity of biologically relevant 1,7-bis(aminoalkyl)diazachrysene derivatives.

PubMed

Šegan, Sandra; Trifković, Jelena; Verbić, Tatjana; Opsenica, Dejan; Zlatović, Mario; Burnett, James; Šolaja, Bogdan; Milojković-Opsenica, Dušanka

2013-01-01

The physicochemical properties, retention parameters (R(M)(0)), partition coefficients (logP(OW)), and pK(a) values for a series of thirteen 1,7-bis(aminoalkyl) diazachrysene (1,7-DAAC) derivatives were determined in order to reveal the characteristics responsible for their biological behavior. The investigated compounds inhibit three unrelated pathogens (the Botulinum neurotoxin serotype A light chain (BoNT/A LC), Plasmodium falciparum malaria, and Ebola filovirus) via three different mechanisms of action. To determine the most influential factors governing the retention and activities of the investigated diazachrysenes, R(M)(0), logP(OW), and biological activity values were correlated with 2D and 3D molecular descriptors, using a partial least squares regression. The resulting quantitative structure-retention (property) relationships indicate the importance of descriptors related to the hydrophobicity of the molecules (e.g., predicted partition coefficients and hydrophobic surface area). Quantitative structure-activity relationship models for describing biological activity against the BoNT/A LC and malarial strains also include overall compound polarity, electron density distribution, and proton donor/acceptor potential. Furthermore, models for Ebola filovirus inhibition are presented qualitatively to provide insights into parameters that may contribute to the compounds' antiviral activities. Overall, the models form the basis for selecting structural features that significantly affect the compound's absorption, distribution, metabolism, excretion, and toxicity profiles. Copyright © 2012 Elsevier B.V. All rights reserved.

The use of 'Omics technology to rationally improve industrial mammalian cell line performance.

PubMed

Lewis, Amanda M; Abu-Absi, Nicholas R; Borys, Michael C; Li, Zheng Jian

2016-01-01

Biologics represent an increasingly important class of therapeutics, with 7 of the 10 top selling drugs from 2013 being in this class. Furthermore, health authority approval of biologics in the immuno-oncology space is expected to transform treatment of patients with debilitating and deadly diseases. The growing importance of biologics in the healthcare field has also resulted in the recent approvals of several biosimilars. These recent developments, combined with pressure to provide treatments at lower costs to payers, are resulting in increasing need for the industry to quickly and efficiently develop high yielding, robust processes for the manufacture of biologics with the ability to control quality attributes within narrow distributions. Achieving this level of manufacturing efficiency and the ability to design processes capable of regulating growth, death and other cellular pathways through manipulation of media, feeding strategies, and other process parameters will undoubtedly be facilitated through systems biology tools generated in academic and public research communities. Here we discuss the intersection of systems biology, 'Omics technologies, and mammalian bioprocess sciences. Specifically, we address how these methods in conjunction with traditional monitoring techniques represent a unique opportunity to better characterize and understand host cell culture state, shift from an empirical to rational approach to process development and optimization of bioreactor cultivation processes. We summarize the following six key areas: (i) research applied to parental, non-recombinant cell lines; (ii) systems level datasets generated with recombinant cell lines; (iii) datasets linking phenotypic traits to relevant biomarkers; (iv) data depositories and bioinformatics tools; (v) in silico model development, and (vi) examples where these approaches have been used to rationally improve cellular processes. We critically assess relevant and state of the art research being conducted in academic, government and industrial laboratories. Furthermore, we apply our expertise in bioprocess to define a potential model for integration of these systems biology approaches into biologics development. © 2015 Wiley Periodicals, Inc.

Spectral embedding finds meaningful (relevant) structure in image and microarray data

PubMed Central

Higgs, Brandon W; Weller, Jennifer; Solka, Jeffrey L

2006-01-01

Background Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing measurements across thousands of variables. Principal components analysis (PCA) is a linear dimensionality reduction (DR) method that is unsupervised in that it relies only on the data; projections are calculated in Euclidean or a similar linear space and do not use tuning parameters for optimizing the fit to the data. However, relationships within sets of nonlinear data types, such as biological networks or images, are frequently mis-rendered into a low dimensional space by linear methods. Nonlinear methods, in contrast, attempt to model important aspects of the underlying data structure, often requiring parameter(s) fitting to the data type of interest. In many cases, the optimal parameter values vary when different classification algorithms are applied on the same rendered subspace, making the results of such methods highly dependent upon the type of classifier implemented. Results We present the results of applying the spectral method of Lafon, a nonlinear DR method based on the weighted graph Laplacian, that minimizes the requirements for such parameter optimization for two biological data types. We demonstrate that it is successful in determining implicit ordering of brain slice image data and in classifying separate species in microarray data, as compared to two conventional linear methods and three nonlinear methods (one of which is an alternative spectral method). This spectral implementation is shown to provide more meaningful information, by preserving important relationships, than the methods of DR presented for comparison. Tuning parameter fitting is simple and is a general, rather than data type or experiment specific approach, for the two datasets analyzed here. Tuning parameter optimization is minimized in the DR step to each subsequent classification method, enabling the possibility of valid cross-experiment comparisons. Conclusion Results from the spectral method presented here exhibit the desirable properties of preserving meaningful nonlinear relationships in lower dimensional space and requiring minimal parameter fitting, providing a useful algorithm for purposes of visualization and classification across diverse datasets, a common challenge in systems biology. PMID:16483359

Oscillations and Multiple Equilibria in Microvascular Blood Flow.

PubMed

Karst, Nathaniel J; Storey, Brian D; Geddes, John B

2015-07-01

We investigate the existence of oscillatory dynamics and multiple steady-state flow rates in a network with a simple topology and in vivo microvascular blood flow constitutive laws. Unlike many previous analytic studies, we employ the most biologically relevant models of the physical properties of whole blood. Through a combination of analytic and numeric techniques, we predict in a series of two-parameter bifurcation diagrams a range of dynamical behaviors, including multiple equilibria flow configurations, simple oscillations in volumetric flow rate, and multiple coexistent limit cycles at physically realizable parameters. We show that complexity in network topology is not necessary for complex behaviors to arise and that nonlinear rheology, in particular the plasma skimming effect, is sufficient to support oscillatory dynamics similar to those observed in vivo.

BIOREL: the benchmark resource to estimate the relevance of the gene networks.

PubMed

Antonov, Alexey V; Mewes, Hans W

2006-02-06

The progress of high-throughput methodologies in functional genomics has lead to the development of statistical procedures to infer gene networks from various types of high-throughput data. However, due to the lack of common standards, the biological significance of the results of the different studies is hard to compare. To overcome this problem we propose a benchmark procedure and have developed a web resource (BIOREL), which is useful for estimating the biological relevance of any genetic network by integrating different sources of biological information. The associations of each gene from the network are classified as biologically relevant or not. The proportion of genes in the network classified as "relevant" is used as the overall network relevance score. Employing synthetic data we demonstrated that such a score ranks the networks fairly in respect to the relevance level. Using BIOREL as the benchmark resource we compared the quality of experimental and theoretically predicted protein interaction data.

A systematic approach to infer biological relevance and biases of gene network structures.

PubMed

Antonov, Alexey V; Tetko, Igor V; Mewes, Hans W

2006-01-10

The development of high-throughput technologies has generated the need for bioinformatics approaches to assess the biological relevance of gene networks. Although several tools have been proposed for analysing the enrichment of functional categories in a set of genes, none of them is suitable for evaluating the biological relevance of the gene network. We propose a procedure and develop a web-based resource (BIOREL) to estimate the functional bias (biological relevance) of any given genetic network by integrating different sources of biological information. The weights of the edges in the network may be either binary or continuous. These essential features make our web tool unique among many similar services. BIOREL provides standardized estimations of the network biases extracted from independent data. By the analyses of real data we demonstrate that the potential application of BIOREL ranges from various benchmarking purposes to systematic analysis of the network biology.

Edge instability in incompressible planar active fluids

NASA Astrophysics Data System (ADS)

Nesbitt, David; Pruessner, Gunnar; Lee, Chiu Fan

2017-12-01

Interfacial instability is highly relevant to many important biological processes. A key example arises in wound healing experiments, which observe that an epithelial layer with an initially straight edge does not heal uniformly. We consider the phenomenon in the context of active fluids. Improving upon the approximation used by Zimmermann, Basan, and Levine [Eur. Phys. J.: Spec. Top. 223, 1259 (2014), 10.1140/epjst/e2014-02189-7], we perform a linear stability analysis on a two-dimensional incompressible hydrodynamic model of an active fluid with an open interface. We categorize the stability of the model and find that for experimentally relevant parameters, fingering instability is always absent in this minimal model. Our results point to the crucial role of density variation in the fingering instability in tissue regeneration.

Identification and MS-assisted interpretation of genetically influenced NMR signals in human plasma

PubMed Central

2013-01-01

Nuclear magnetic resonance spectroscopy (NMR) provides robust readouts of many metabolic parameters in one experiment. However, identification of clinically relevant markers in 1H NMR spectra is a major challenge. Association of NMR-derived quantities with genetic variants can uncover biologically relevant metabolic traits. Using NMR data of plasma samples from 1,757 individuals from the KORA study together with 655,658 genetic variants, we show that ratios between NMR intensities at two chemical shift positions can provide informative and robust biomarkers. We report seven loci of genetic association with NMR-derived traits (APOA1, CETP, CPS1, GCKR, FADS1, LIPC, PYROXD2) and characterize these traits biochemically using mass spectrometry. These ratios may now be used in clinical studies. PMID:23414815

Statistics of optimal information flow in ensembles of regulatory motifs

NASA Astrophysics Data System (ADS)

Crisanti, Andrea; De Martino, Andrea; Fiorentino, Jonathan

2018-02-01

Genetic regulatory circuits universally cope with different sources of noise that limit their ability to coordinate input and output signals. In many cases, optimal regulatory performance can be thought to correspond to configurations of variables and parameters that maximize the mutual information between inputs and outputs. Since the mid-2000s, such optima have been well characterized in several biologically relevant cases. Here we use methods of statistical field theory to calculate the statistics of the maximal mutual information (the "capacity") achievable by tuning the input variable only in an ensemble of regulatory motifs, such that a single controller regulates N targets. Assuming (i) sufficiently large N , (ii) quenched random kinetic parameters, and (iii) small noise affecting the input-output channels, we can accurately reproduce numerical simulations both for the mean capacity and for the whole distribution. Our results provide insight into the inherent variability in effectiveness occurring in regulatory systems with heterogeneous kinetic parameters.

Automatic detection of slight parameter changes associated to complex biomedical signals using multiresolution q-entropy1.

PubMed

Torres, M E; Añino, M M; Schlotthauer, G

2003-12-01

It is well known that, from a dynamical point of view, sudden variations in physiological parameters which govern certain diseases can cause qualitative changes in the dynamics of the corresponding physiological process. The purpose of this paper is to introduce a technique that allows the automated temporal localization of slight changes in a parameter of the law that governs the nonlinear dynamics of a given signal. This tool takes, from the multiresolution entropies, the ability to show these changes as statistical variations at each scale. These variations are held in the corresponding principal component. Appropriately combining these techniques with a statistical changes detector, a complexity change detection algorithm is obtained. The relevance of the approach, together with its robustness in the presence of moderate noise, is discussed in numerical simulations and the automatic detector is applied to real and simulated biological signals.

Expression of Truncated Neurokinin-1 Receptor in Childhood Neuroblastoma is Independent of Tumor Biology and Stage.

PubMed

Pohl, Alexandra; Kappler, Roland; Mühling, Jakob; VON Schweinitz, Dietrich; Berger, Michael

2017-11-01

Neuroblastoma is an embryonal malignancy arising from the aberrant growth of neural crest progenitor cells of the sympathetic nervous system. The tachykinin receptor 1 (TACR1) - substance P complex is associated with tumoral angiogenesis and cell proliferation in a variety of cancer types. Inhibition of TACR1 was recently described to impede growth of NB cell lines. However, the relevance of TACR1 in clinical settings is unknown. We investigated gene expression levels of full-length and truncated TACR1 in 59 neuroblastomas and correlated these data with the patients' clinical parameters such as outcome, metastasis, International Neuroblastoma Staging System (INSS) status, MYCN proto-oncogene, bHLH transcription factor (MYCN) status, gender and age. Our results indicated that TACR1 is ubiquitously expressed in neuroblastoma but expression levels are independent of clinical parameters. Our data suggest that TACR1 might serve as a potent anticancer target in a large variety of patients with neuroblastoma, independent of tumor biology and clinical stage. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

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

NASA Astrophysics Data System (ADS)

Merkel, Matthias; Manning, M. Lisa

2018-02-01

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

Regulation of Spatiotemporal Patterns by Biological Variability: General Principles and Applications to Dictyostelium discoideum

PubMed Central

Grace, Miriam; Hütt, Marc-Thorsten

2015-01-01

Spatiotemporal patterns often emerge from local interactions in a self-organizing fashion. In biology, the resulting patterns are also subject to the influence of the systematic differences between the system’s constituents (biological variability). This regulation of spatiotemporal patterns by biological variability is the topic of our review. We discuss several examples of correlations between cell properties and the self-organized spatiotemporal patterns, together with their relevance for biology. Our guiding, illustrative example will be spiral waves of cAMP in a colony of Dictyostelium discoideum cells. Analogous processes take place in diverse situations (such as cardiac tissue, where spiral waves occur in potentially fatal ventricular fibrillation) so a deeper understanding of this additional layer of self-organized pattern formation would be beneficial to a wide range of applications. One of the most striking differences between pattern-forming systems in physics or chemistry and those in biology is the potential importance of variability. In the former, system components are essentially identical with random fluctuations determining the details of the self-organization process and the resulting patterns. In biology, due to variability, the properties of potentially very few cells can have a driving influence on the resulting asymptotic collective state of the colony. Variability is one means of implementing a few-element control on the collective mode. Regulatory architectures, parameters of signaling cascades, and properties of structure formation processes can be "reverse-engineered" from observed spatiotemporal patterns, as different types of regulation and forms of interactions between the constituents can lead to markedly different correlations. The power of this biology-inspired view of pattern formation lies in building a bridge between two scales: the patterns as a collective state of a very large number of cells on the one hand, and the internal parameters of the single cells on the other. PMID:26562406

Catalytic Properties and Biomedical Applications of Cerium Oxide Nanoparticles

PubMed Central

Walkey, Carl; Das, Soumen; Seal, Sudipta; Erlichman, Joseph; Heckman, Karin; Ghibelli, Lina; Traversa, Enrico; McGinnis, James F.; Self, William T.

2014-01-01

Cerium oxide nanoparticles (Nanoceria) have shown promise as catalytic antioxidants in the test tube, cell culture models and animal models of disease. However given the reactivity that is well established at the surface of these nanoparticles, the biological utilization of Nanoceria as a therapeutic still poses many challenges. Moreover the form that these particles take in a biological environment, such as the changes that can occur due to a protein corona, are not well established. This review aims to summarize the existing literature on biological use of Nanoceria, and to raise questions about what further study is needed to apply this interesting catalytic material to biomedical applications. These questions include: 1) How does preparation, exposure dose, route and experimental model influence the reported effects of Nanoceria in animal studies? 2) What are the considerations to develop Nanoceria as a therapeutic agent in regards to these parameters? 3) What biological targets of reactive oxygen species (ROS) and reactive nitrogen species (RNS) are relevant to this targeting, and how do these properties also influence the safety of these nanomaterials? PMID:26207185

Nanoshells for photothermal therapy: a Monte-Carlo based numerical study of their design tolerance

PubMed Central

Grosges, Thomas; Barchiesi, Dominique; Kessentini, Sameh; Gréhan, Gérard; de la Chapelle, Marc Lamy

2011-01-01

The optimization of the coated metallic nanoparticles and nanoshells is a current challenge for biological applications, especially for cancer photothermal therapy, considering both the continuous improvement of their fabrication and the increasing requirement of efficiency. The efficiency of the coupling between illumination with such nanostructures for burning purposes depends unevenly on their geometrical parameters (radius, thickness of the shell) and material parameters (permittivities which depend on the illumination wavelength). Through a Monte-Carlo method, we propose a numerical study of such nanodevice, to evaluate tolerances (or uncertainty) on these parameters, given a threshold of efficiency, to facilitate the design of nanoparticles. The results could help to focus on the relevant parameters of the engineering process for which the absorbed energy is the most dependant. The Monte-Carlo method confirms that the best burning efficiency are obtained for hollow nanospheres and exhibit the sensitivity of the absorbed electromagnetic energy as a function of each parameter. The proposed method is general and could be applied in design and development of new embedded coated nanomaterials used in biomedicine applications. PMID:21698021

Comparing human peritoneal fluid and phosphate-buffered saline for drug delivery: do we need bio-relevant media?

PubMed

Bhusal, Prabhat; Rahiri, Jamie Lee; Sua, Bruce; McDonald, Jessica E; Bansal, Mahima; Hanning, Sara; Sharma, Manisha; Chandramouli, Kaushik; Harrison, Jeff; Procter, Georgina; Andrews, Gavin; Jones, David S; Hill, Andrew G; Svirskis, Darren

2018-06-01

An understanding of biological fluids at the site of administration is important to predict the fate of drug delivery systems in vivo. Little is known about peritoneal fluid; therefore, we have investigated this biological fluid and compared it to phosphate-buffered saline, a synthetic media commonly used for in vitro evaluation of intraperitoneal drug delivery systems. Human peritoneal fluid samples were analysed for electrolyte, protein and lipid levels. In addition, physicochemical properties were measured alongside rheological parameters. Significant inter-patient variations were observed with regard to pH (p < 0.001), buffer capacity (p < 0.05), osmolality (p < 0.001) and surface tension (p < 0.05). All the investigated physicochemical properties of peritoneal fluid differed from phosphate-buffered saline (p < 0.001). Rheological examination of peritoneal fluid demonstrated non-Newtonian shear thinning behaviour and predominantly exhibited the characteristics of an entangled network. Inter-patient and inter-day variability in the viscosity of peritoneal fluid was observed. The solubility of the local anaesthetic lidocaine in peritoneal fluid was significantly higher (p < 0.05) when compared to phosphate-buffered saline. Interestingly, the dissolution rate of lidocaine was not significantly different between the synthetic and biological media. Importantly, and with relevance to intraperitoneal drug delivery systems, the sustained release of lidocaine from a thermosensitive gel formulation occurred at a significantly faster rate into peritoneal fluid. Collectively, these data demonstrate the variation between commonly used synthetic media and human peritoneal fluid. The differences in drug release rates observed illustrate the need for bio-relevant media, which ultimately would improve in vitro-in vivo correlation.

Advances and applications of occupancy models

USGS Publications Warehouse

Bailey, Larissa; MacKenzie, Darry I.; Nichols, James D.

2013-01-01

Summary: The past decade has seen an explosion in the development and application of models aimed at estimating species occurrence and occupancy dynamics while accounting for possible non-detection or species misidentification. We discuss some recent occupancy estimation methods and the biological systems that motivated their development. Collectively, these models offer tremendous flexibility, but simultaneously place added demands on the investigator. Unlike many mark–recapture scenarios, investigators utilizing occupancy models have the ability, and responsibility, to define their sample units (i.e. sites), replicate sampling occasions, time period over which species occurrence is assumed to be static and even the criteria that constitute ‘detection’ of a target species. Subsequent biological inference and interpretation of model parameters depend on these definitions and the ability to meet model assumptions. We demonstrate the relevance of these definitions by highlighting applications from a single biological system (an amphibian–pathogen system) and discuss situations where the use of occupancy models has been criticized. Finally, we use these applications to suggest future research and model development.

Clinical, functional, behavioural and epigenomic biomarkers of obesity.

PubMed

Lafortuna, Claudio L; Tovar, Armando R; Rastelli, Fabio; Tabozzi, Sarah A; Caramenti, Martina; Orozco-Ruiz, Ximena; Aguilar-Lopez, Miriam; Guevara-Cruz, Martha; Avila-Nava, Azalia; Torres, Nimbe; Bertoli, Gloria

2017-06-01

Overweight and obesity are highly prevalent conditions worldwide, linked to an increased risk for death, disability and disease due to metabolic and biochemical abnormalities affecting the biological human system throughout different domains. Biomarkers, defined as indicators of biological processes in health and disease, relevant for body mass excess management have been identified according to different criteria, including anthropometric and molecular indexes, as well as physiological and behavioural aspects. Analysing these different biomarkers, we identified their potential role in diagnosis, prognosis and treatment. Epigenetic biomarkers, cellular mediators of inflammation and factors related to microbiota-host interactions may be considered to have a theranostic value. Though, the molecular processes responsible for the biological phenomenology detected by the other analysed markers, is not clear yet. Nevertheless, these biomarkers possess valuable diagnostic and prognostic power. A new frontier for theranostic biomarkers can be foreseen in the exploitation of parameters defining behaviours and lifestyles linked to the risk of obesity, capable to describe the effects of interventions for obesity prevention and treatment which include also behaviour change strategies.

Frequency domain phosphorescence lifetime Imaging measurements and applications by ISS FastFLIM and multi pulse excitation

NASA Astrophysics Data System (ADS)

Coskun, Ulas C.; Lam, Sandra; Sun, Yuansheng; Liao, Shih-Chu Jeff; George, Steven C.; Barbieri, Beniamino

2017-02-01

Phosphorescence probes can have significantly long lifetimes, on the order of micro- to milli-seconds or longer. In addition, environmental changes can affect the lifetimes of these phosphorescence probes. Thus, Phosphorescence Lifetime Imaging Microscopy (PLIM) is a very useful tool to localize the phosphorescence probes based on their lifetimes to study the variance in the lifetimes due to the micro environmental changes. Since the probes respond to the biologically relevant parameters like oxygen concentration, they can be used to study various biologically relevant processes like cellular metabolism, protein interaction etc. In this case, we study the effects of oxygen on Oxyphor G4 with PLIM. Since The Oxyphor G4 can be quenched by O2, it is a good example of such a probe and has a lifetime around 250us. Here we present the digital frequency domain PLIM technique and study the lifetime of the Oxyphor G4 as a function of the O2 concentration. The lifetime data are successfully presented in a phasor plot for various O2 concentrations and are consistent with the time domain data. Overall, we can analyze the oxygen consumption of varying cells using this technique.

Biological permeable reactive barriers coupled with electrokinetic soil flushing for the treatment of diesel-polluted clay soil.

PubMed

Mena, Esperanza; Ruiz, Clara; Villaseñor, José; Rodrigo, Manuel A; Cañizares, Pablo

2015-01-01

Removal of diesel from spiked kaolin has been studied in the laboratory using coupled electrokinetic soil flushing (EKSF) and bioremediation through an innovative biological permeable reactive barriers (Bio-PRBs) positioned between electrode wells. The results show that this technology is efficient in the removal of pollutants and allows the soil to maintain the appropriate conditions for microorganism growth in terms of pH, temperature, and nutrients. At the same time, EKSF was demonstrated to be a very interesting technology for transporting pollutants, microorganisms and nutrients, although results indicate that careful management is necessary to avoid the depletion of nutrients, which are effectively transported by electro-migration. After two weeks of operation, 30% of pollutants are removed and energy consumption is under 70 kWh m(-3). Main fluxes (electroosmosis and evaporation) and changes in the most relevant parameters (nutrients, diesel, microorganisms, surfactants, moisture conductivity and pH) during treatment and in a complete post-study analysis are studied to give a comprehensive description of the most relevant processes occurring in the soil (pollutant transport and biodegradation). Copyright © 2014 Elsevier B.V. All rights reserved.

Making Plant Biology Curricula Relevant.

ERIC Educational Resources Information Center

Hershey, David R.

1992-01-01

Reviews rationale, purposes, challenges, and relevance of hands-on, plant biology curricula that have been developed in response to the limited use of plants in biology education. Discusses methods to maintain both instructional rigor and student interest in the following topics: cut flowers, container-growing media, fertilizers, hydroponics,…

Parameter space exploration within dynamic simulations of signaling networks.

PubMed

De Ambrosi, Cristina; Barla, Annalisa; Tortolina, Lorenzo; Castagnino, Nicoletta; Pesenti, Raffaele; Verri, Alessandro; Ballestrero, Alberto; Patrone, Franco; Parodi, Silvio

2013-02-01

We started offering an introduction to very basic aspects of molecular biology, for the reader coming from computer sciences, information technology, mathematics. Similarly we offered a minimum of information about pathways and networks in graph theory, for a reader coming from the bio-medical sector. At the crossover about the two different types of expertise, we offered some definition about Systems Biology. The core of the article deals with a Molecular Interaction Map (MIM), a network of biochemical interactions involved in a small signaling-network sub-region relevant in breast cancer. We explored robustness/sensitivity to random perturbations. It turns out that our MIM is a non-isomorphic directed graph. For non physiological directions of propagation of the signal the network is quite resistant to perturbations. The opposite happens for biologically significant directions of signal propagation. In these cases we can have no signal attenuation, and even signal amplification. Signal propagation along a given pathway is highly unidirectional, with the exception of signal-feedbacks, that again have a specific biological role and significance. In conclusion, even a relatively small network like our present MIM reveals the preponderance of specific biological functions over unspecific isomorphic behaviors. This is perhaps the consequence of hundreds of millions of years of biological evolution.

Auditory-visual object recognition time suggests specific processing for animal sounds.

PubMed

Suied, Clara; Viaud-Delmon, Isabelle

2009-01-01

Recognizing an object requires binding together several cues, which may be distributed across different sensory modalities, and ignoring competing information originating from other objects. In addition, knowledge of the semantic category of an object is fundamental to determine how we should react to it. Here we investigate the role of semantic categories in the processing of auditory-visual objects. We used an auditory-visual object-recognition task (go/no-go paradigm). We compared recognition times for two categories: a biologically relevant one (animals) and a non-biologically relevant one (means of transport). Participants were asked to react as fast as possible to target objects, presented in the visual and/or the auditory modality, and to withhold their response for distractor objects. A first main finding was that, when participants were presented with unimodal or bimodal congruent stimuli (an image and a sound from the same object), similar reaction times were observed for all object categories. Thus, there was no advantage in the speed of recognition for biologically relevant compared to non-biologically relevant objects. A second finding was that, in the presence of a biologically relevant auditory distractor, the processing of a target object was slowed down, whether or not it was itself biologically relevant. It seems impossible to effectively ignore an animal sound, even when it is irrelevant to the task. These results suggest a specific and mandatory processing of animal sounds, possibly due to phylogenetic memory and consistent with the idea that hearing is particularly efficient as an alerting sense. They also highlight the importance of taking into account the auditory modality when investigating the way object concepts of biologically relevant categories are stored and retrieved.

Rational design of gold nanoparticle toxicology assays: a question of exposure scenario, dose and experimental setup.

PubMed

Taylor, Ulrike; Rehbock, Christoph; Streich, Carmen; Rath, Detlef; Barcikowski, Stephan

2014-09-01

Many studies have evaluated the toxicity of gold nanoparticles, although reliable predictions based on these results are rare. In order to overcome this problem, this article highlights strategies to improve comparability and standardization of nanotoxicological studies. To this end, it is proposed that we should adapt the nanomaterial to the addressed exposure scenario, using ligand-free nanoparticle references in order to differentiate ligand effects from size effects. Furthermore, surface-weighted particle dosing referenced to the biologically relevant parameter (e.g., cell number or organ mass) is proposed as the gold standard. In addition, it is recommended that we should shift the focus of toxicological experiments from 'live-dead' assays to the assessment of cell function, as this strategy allows observation of bioresponses at lower doses that are more relevant for in vivo scenarios.

A "weight of evidence" approach for the integration of environmental "triad" data to assess ecological risk and biological vulnerability.

PubMed

Dagnino, Alessandro; Sforzini, Susanna; Dondero, Francesco; Fenoglio, Stefano; Bona, Elisa; Jensen, John; Viarengo, Aldo

2008-07-01

A new Expert Decision Support System (EDSS) that can integrate Triad data for assessing environmental risk and biological vulnerability at contaminated sites has been developed. Starting with ecosystem relevance, the EDSS assigns different weights to the results obtained from Triad disciplines. The following parameters have been employed: 1) chemical soil analyses (revealing the presence of potentially dangerous substances), 2) ecotoxicological bioassays (utilizing classical endpoints such as survival and reproduction rates), 3) biomarkers (showing sublethal pollutant effects), and 4) ecological parameters (assessing changes in community structure and functions). For each Triad discipline, the EDSS compares the data obtained at the studied field sites with reference values and calculates different 0-1 indexes (e.g., Chemical Risk Index, Ecotoxicological Risk Index, and Ecological Risk Index). The EDSS output consists of 3 indexes: 1) Environmental Risk index (EnvRI), quantifying the levels of biological damage at population-community level, 2) Biological Vulnerability Index (BVI), assessing the potential threats to biological equilibriums, and 3) Genotoxicity Index (GTI), screening genotoxicity effects. The EDSS has been applied in the integration of a battery of Triad data obtained during the European Union-funded Life Intervention in the Fraschetta Area (LINFA) project, which has been carried out in order to estimate the potential risk from soils of a highly anthropized area (Alessandria, Italy) mainly impacted by deposition of atmospheric pollutants. Results obtained during 4 seasonal sampling campaigns (2004-2005) show maximum values of EnvRI in sites A and B (characterized by industrial releases) and lower levels in site D (affected by vehicular traffic emissions). All 3 potentially polluted sites have shown high levels of BVI and GTI, suggesting a general change from reference conditions (site C).

Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sample sizes.

PubMed

Frömke, Cornelia; Hothorn, Ludwig A; Kropf, Siegfried

2008-01-27

In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a significant difference in location parameters from zero or one for ratios thereof for each variable. However, in some studies a significant deviation of the difference in locations from zero (or 1 in terms of the ratio) is biologically meaningless. A relevant difference or ratio is sought in such cases. This article addresses the use of relevance-shifted tests on ratios for a multivariate parallel two-sample group design. Two empirical procedures are proposed which embed the relevance-shifted test on ratios. As both procedures test a hypothesis for each variable, the resulting multiple testing problem has to be considered. Hence, the procedures include a multiplicity correction. Both procedures are extensions of available procedures for point null hypotheses achieving exact control of the familywise error rate. Whereas the shift of the null hypothesis alone would give straight-forward solutions, the problems that are the reason for the empirical considerations discussed here arise by the fact that the shift is considered in both directions and the whole parameter space in between these two limits has to be accepted as null hypothesis. The first algorithm to be discussed uses a permutation algorithm, and is appropriate for designs with a moderately large number of observations. However, many experiments have limited sample sizes. Then the second procedure might be more appropriate, where multiplicity is corrected according to a concept of data-driven order of hypotheses.

Learning Quantitative Sequence-Function Relationships from Massively Parallel Experiments

NASA Astrophysics Data System (ADS)

Atwal, Gurinder S.; Kinney, Justin B.

2016-03-01

A fundamental aspect of biological information processing is the ubiquity of sequence-function relationships—functions that map the sequence of DNA, RNA, or protein to a biochemically relevant activity. Most sequence-function relationships in biology are quantitative, but only recently have experimental techniques for effectively measuring these relationships been developed. The advent of such "massively parallel" experiments presents an exciting opportunity for the concepts and methods of statistical physics to inform the study of biological systems. After reviewing these recent experimental advances, we focus on the problem of how to infer parametric models of sequence-function relationships from the data produced by these experiments. Specifically, we retrace and extend recent theoretical work showing that inference based on mutual information, not the standard likelihood-based approach, is often necessary for accurately learning the parameters of these models. Closely connected with this result is the emergence of "diffeomorphic modes"—directions in parameter space that are far less constrained by data than likelihood-based inference would suggest. Analogous to Goldstone modes in physics, diffeomorphic modes arise from an arbitrarily broken symmetry of the inference problem. An analytically tractable model of a massively parallel experiment is then described, providing an explicit demonstration of these fundamental aspects of statistical inference. This paper concludes with an outlook on the theoretical and computational challenges currently facing studies of quantitative sequence-function relationships.

A Statistical Physicist's Approach to Biological Motion: From the the Kinesin Walk to Muscle Contraction

NASA Astrophysics Data System (ADS)

Vicsek, Tamas

1997-03-01

It is demonstrated that a wide range of experimental results on biological motion can be successfully interpreted in terms of statistical physics motivated models taking into account the relevant microscopic details of motor proteins and allowing analytic solutions. Two important examples are considered, i) the motion of a single kinesin molecule along microtubules inside individual cells and ii) muscle contraction which is a macroscopic phenomenon due to the collective action of a large number of myosin heads along actin filaments. i) Recently individual two-headed kinesin molecules have been studied in in vitro motility assays revealing a number of their peculiar transport properties. Here we propose a simple and robust model for the kinesin stepping process with elastically coupled Brownian heads showing all of these properties. The analytic treatment of our model results in a very good fit to the experimental data and practically has no free parameters. ii) Myosin is an ATPase enzyme that converts the chemical energy stored in ATP molecules into mechanical work. During muscle contraction, the myosin cross-bridges attach to the actin filaments and exert force on them yielding a relative sliding of the actin and myosin filaments. In this paper we present a simple mechanochemical model for the cross-bridge interaction involving the relevant kinetic data and providing simple analytic solutions for the mechanical properties of muscle contraction, such as the force-velocity relationship or the relative number of the attached cross-bridges. So far the only analytic formula which could be fitted to the measured force-velocity curves has been the well known Hill equation containing parameters lacking clear microscopic origin. The main advantages of our new approach are that it explicitly connects the mechanical data with the kinetic data and the concentration of the ATP and ATPase products and as such it leads to new analytic solutions which agree extremely well with a wide range of experimental curves, while the parameters of the corresponding expressions have well defined microscopic meaning.

Fast Biological Modeling for Voxel-based Heavy Ion Treatment Planning Using the Mechanistic Repair-Misrepair-Fixation Model and Nuclear Fragment Spectra

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

Kamp, Florian; Department of Radiation Oncology, Technische Universität München, Klinikum Rechts der Isar, München; Physik-Department, Technische Universität München, Garching

2015-11-01

Purpose: The physical and biological differences between heavy ions and photons have not been fully exploited and could improve treatment outcomes. In carbon ion therapy, treatment planning must account for physical properties, such as the absorbed dose and nuclear fragmentation, and for differences in the relative biological effectiveness (RBE) of ions compared with photons. We combined the mechanistic repair-misrepair-fixation (RMF) model with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. Methods and Materials: Relative changes in double-strand break yields and radiosensitivity parameters with particle type and energy were determined using the independently benchmarked Monte Carlo damagemore » simulation and the RMF model to estimate the RBE values for primary carbon ions and secondary fragments. Depth-dependent energy spectra were generated with the Monte Carlo code FLUKA for clinically relevant initial carbon ion energies. The predicted trends in RBE were compared with the published experimental data. Biological optimization for carbon ions was implemented in a 3-dimensional research treatment planning tool. Results: We compared the RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The inclusion of fragments in the simulations led to smaller RBE predictions. A validation of RMF against measured cell survival data reported in published studies showed reasonable agreement. We calculated and optimized the RWD distributions on patient data and compared the RMF predictions with those from other biological models. The RBE values in an astrocytoma tumor ranged from 2.2 to 4.9 (mean 2.8) for a RWD of 3 Gy(RBE) assuming (α/β){sub X} = 2 Gy. Conclusions: These studies provide new information to quantify and assess uncertainties in the clinically relevant RBE values for carbon ion therapy based on biophysical mechanisms. We present results from the first biological optimization of carbon ion radiation therapy beams on patient data using a combined RMF and Monte Carlo damage simulation modeling approach. The presented method is advantageous for fast biological optimization.« less

Fast Biological Modeling for Voxel-based Heavy Ion Treatment Planning Using the Mechanistic Repair-Misrepair-Fixation Model and Nuclear Fragment Spectra.

PubMed

Kamp, Florian; Cabal, Gonzalo; Mairani, Andrea; Parodi, Katia; Wilkens, Jan J; Carlson, David J

2015-11-01

The physical and biological differences between heavy ions and photons have not been fully exploited and could improve treatment outcomes. In carbon ion therapy, treatment planning must account for physical properties, such as the absorbed dose and nuclear fragmentation, and for differences in the relative biological effectiveness (RBE) of ions compared with photons. We combined the mechanistic repair-misrepair-fixation (RMF) model with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. Relative changes in double-strand break yields and radiosensitivity parameters with particle type and energy were determined using the independently benchmarked Monte Carlo damage simulation and the RMF model to estimate the RBE values for primary carbon ions and secondary fragments. Depth-dependent energy spectra were generated with the Monte Carlo code FLUKA for clinically relevant initial carbon ion energies. The predicted trends in RBE were compared with the published experimental data. Biological optimization for carbon ions was implemented in a 3-dimensional research treatment planning tool. We compared the RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The inclusion of fragments in the simulations led to smaller RBE predictions. A validation of RMF against measured cell survival data reported in published studies showed reasonable agreement. We calculated and optimized the RWD distributions on patient data and compared the RMF predictions with those from other biological models. The RBE values in an astrocytoma tumor ranged from 2.2 to 4.9 (mean 2.8) for a RWD of 3 Gy(RBE) assuming (α/β)X = 2 Gy. These studies provide new information to quantify and assess uncertainties in the clinically relevant RBE values for carbon ion therapy based on biophysical mechanisms. We present results from the first biological optimization of carbon ion radiation therapy beams on patient data using a combined RMF and Monte Carlo damage simulation modeling approach. The presented method is advantageous for fast biological optimization. Copyright © 2015 Elsevier Inc. All rights reserved.

ITALICS: an algorithm for normalization and DNA copy number calling for Affymetrix SNP arrays.

PubMed

Rigaill, Guillem; Hupé, Philippe; Almeida, Anna; La Rosa, Philippe; Meyniel, Jean-Philippe; Decraene, Charles; Barillot, Emmanuel

2008-03-15

Affymetrix SNP arrays can be used to determine the DNA copy number measurement of 11 000-500 000 SNPs along the genome. Their high density facilitates the precise localization of genomic alterations and makes them a powerful tool for studies of cancers and copy number polymorphism. Like other microarray technologies it is influenced by non-relevant sources of variation, requiring correction. Moreover, the amplitude of variation induced by non-relevant effects is similar or greater than the biologically relevant effect (i.e. true copy number), making it difficult to estimate non-relevant effects accurately without including the biologically relevant effect. We addressed this problem by developing ITALICS, a normalization method that estimates both biological and non-relevant effects in an alternate, iterative manner, accurately eliminating irrelevant effects. We compared our normalization method with other existing and available methods, and found that ITALICS outperformed these methods for several in-house datasets and one public dataset. These results were validated biologically by quantitative PCR. The R package ITALICS (ITerative and Alternative normaLIzation and Copy number calling for affymetrix Snp arrays) has been submitted to Bioconductor.

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies

PubMed Central

Zhang, Shujun

2018-01-01

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study. PMID:29377896

Spatial capture-recapture

USGS Publications Warehouse

Royle, J. Andrew; Chandler, Richard B.; Sollmann, Rahel; Gardner, Beth

2013-01-01

Spatial Capture-Recapture provides a revolutionary extension of traditional capture-recapture methods for studying animal populations using data from live trapping, camera trapping, DNA sampling, acoustic sampling, and related field methods. This book is a conceptual and methodological synthesis of spatial capture-recapture modeling. As a comprehensive how-to manual, this reference contains detailed examples of a wide range of relevant spatial capture-recapture models for inference about population size and spatial and temporal variation in demographic parameters. Practicing field biologists studying animal populations will find this book to be a useful resource, as will graduate students and professionals in ecology, conservation biology, and fisheries and wildlife management.

Zinc(II) complexation by some biologically relevant pH buffers.

PubMed

Wyrzykowski, D; Tesmar, A; Jacewicz, D; Pranczk, J; Chmurzyński, L

2014-12-01

The isothermal titration calorimetry (ITC) technique supported by potentiometric titration data was used to study the interaction of zinc ions with pH buffer substances, namely 2-(N-morpholino)ethanesulfonic acid (Mes), piperazine-N,N'-bis(2-ethanesulfonic acid) (Pipes), and dimethylarsenic acid (Caco). The displacement ITC titration method with nitrilotriacetic acid as a strong, competitive ligand was applied to determine conditional-independent thermodynamic parameters for the binding of Zn(II) to Mes, Pipes, and Caco. Furthermore, the relationship between the proposed coordination mode of the buffers and the binding enthalpy has been discussed. Copyright © 2014 John Wiley & Sons, Ltd.

Heritability in the genomics era--concepts and misconceptions.

PubMed

Visscher, Peter M; Hill, William G; Wray, Naomi R

2008-04-01

Heritability allows a comparison of the relative importance of genes and environment to the variation of traits within and across populations. The concept of heritability and its definition as an estimable, dimensionless population parameter was introduced by Sewall Wright and Ronald Fisher nearly a century ago. Despite continuous misunderstandings and controversies over its use and application, heritability remains key to the response to selection in evolutionary biology and agriculture, and to the prediction of disease risk in medicine. Recent reports of substantial heritability for gene expression and new estimation methods using marker data highlight the relevance of heritability in the genomics era.

Knowledge Driven Variable Selection (KDVS) – a new approach to enrichment analysis of gene signatures obtained from high–throughput data

PubMed Central

2013-01-01

Background High–throughput (HT) technologies provide huge amount of gene expression data that can be used to identify biomarkers useful in the clinical practice. The most frequently used approaches first select a set of genes (i.e. gene signature) able to characterize differences between two or more phenotypical conditions, and then provide a functional assessment of the selected genes with an a posteriori enrichment analysis, based on biological knowledge. However, this approach comes with some drawbacks. First, gene selection procedure often requires tunable parameters that affect the outcome, typically producing many false hits. Second, a posteriori enrichment analysis is based on mapping between biological concepts and gene expression measurements, which is hard to compute because of constant changes in biological knowledge and genome analysis. Third, such mapping is typically used in the assessment of the coverage of gene signature by biological concepts, that is either score–based or requires tunable parameters as well, limiting its power. Results We present Knowledge Driven Variable Selection (KDVS), a framework that uses a priori biological knowledge in HT data analysis. The expression data matrix is transformed, according to prior knowledge, into smaller matrices, easier to analyze and to interpret from both computational and biological viewpoints. Therefore KDVS, unlike most approaches, does not exclude a priori any function or process potentially relevant for the biological question under investigation. Differently from the standard approach where gene selection and functional assessment are applied independently, KDVS embeds these two steps into a unified statistical framework, decreasing the variability derived from the threshold–dependent selection, the mapping to the biological concepts, and the signature coverage. We present three case studies to assess the usefulness of the method. Conclusions We showed that KDVS not only enables the selection of known biological functionalities with accuracy, but also identification of new ones. An efficient implementation of KDVS was devised to obtain results in a fast and robust way. Computing time is drastically reduced by the effective use of distributed resources. Finally, integrated visualization techniques immediately increase the interpretability of results. Overall, KDVS approach can be considered as a viable alternative to enrichment–based approaches. PMID:23302187

Synthesis and Demonstration of the Biological Relevance of sp3 -rich Scaffolds Distantly Related to Natural Product Frameworks.

PubMed

Foley, Daniel J; Craven, Philip G E; Collins, Patrick M; Doveston, Richard G; Aimon, Anthony; Talon, Romain; Churcher, Ian; von Delft, Frank; Marsden, Stephen P; Nelson, Adam

2017-10-26

The productive exploration of chemical space is an enduring challenge in chemical biology and medicinal chemistry. Natural products are biologically relevant, and their frameworks have facilitated chemical tool and drug discovery. A "top-down" synthetic approach is described that enabled a range of complex bridged intermediates to be converted with high step efficiency into 26 diverse sp 3 -rich scaffolds. The scaffolds have local natural product-like features, but are only distantly related to specific natural product frameworks. To assess biological relevance, a set of 52 fragments was prepared, and screened by high-throughput crystallography against three targets from two protein families (ATAD2, BRD1 and JMJD2D). In each case, 3D fragment hits were identified that would serve as distinctive starting points for ligand discovery. This demonstrates that frameworks that are distantly related to natural products can facilitate discovery of new biologically relevant regions within chemical space. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Synthesis and Demonstration of the Biological Relevance of sp3‐rich Scaffolds Distantly Related to Natural Product Frameworks

PubMed Central

Foley, Daniel J.; Craven, Philip G. E.; Collins, Patrick M.; Doveston, Richard G.; Aimon, Anthony; Talon, Romain; Churcher, Ian; von Delft, Frank

2017-01-01

Abstract The productive exploration of chemical space is an enduring challenge in chemical biology and medicinal chemistry. Natural products are biologically relevant, and their frameworks have facilitated chemical tool and drug discovery. A “top‐down” synthetic approach is described that enabled a range of complex bridged intermediates to be converted with high step efficiency into 26 diverse sp3‐rich scaffolds. The scaffolds have local natural product‐like features, but are only distantly related to specific natural product frameworks. To assess biological relevance, a set of 52 fragments was prepared, and screened by high‐throughput crystallography against three targets from two protein families (ATAD2, BRD1 and JMJD2D). In each case, 3D fragment hits were identified that would serve as distinctive starting points for ligand discovery. This demonstrates that frameworks that are distantly related to natural products can facilitate discovery of new biologically relevant regions within chemical space. PMID:28983993

AMOEBA Polarizable Force Field Parameters of the Heme Cofactor in Its Ferrous and Ferric Forms.

PubMed

Wu, Xiaojing; Clavaguera, Carine; Lagardère, Louis; Piquemal, Jean-Philip; de la Lande, Aurélien

2018-05-08

We report the first parameters of the heme redox cofactors for the polarizable AMOEBA force field in both the ferric and ferrous forms. We consider two types of complexes, one with two histidine side chains as axial ligands and one with a histidine and a methionine side chain as ligands. We have derived permanent multipoles from second-order Møller-Plesset perturbation theory (MP2). The sets of parameters have been validated in a first step by comparison of AMOEBA interaction energies of heme and a collection of biologically relevant molecules with MP2 and Density Functional Theory (DFT) calculations. In a second validation step, we consider interaction energies with large aggregates comprising around 80 H 2 O molecules. These calculations are repeated for 30 structures extracted from semiempirical PM7 DM simulations. Very encouraging agreement is found between DFT and the AMOEBA force field, which results from an accurate treatment of electrostatic interactions. We finally report long (10 ns) MD simulations of cytochromes in two redox states with AMOEBA testing both the 2003 and 2014 AMOEBA water models. These simulations have been carried out with the TINKER-HP (High Performance) program. In conclusion, owing to their ubiquity in biology, we think the present work opens a wide array of applications of the polarizable AMOEBA force field on hemeproteins.

3D-modelling of radon-induced cellular radiobiological effects in bronchial airway bifurcations: direct versus bystander effects.

PubMed

Szőke, István; Farkas, Arpád; Balásházy, Imre; Hofmann, Werner; Madas, Balázs G; Szőke, Réka

2012-06-01

The primary objective of this paper was to investigate the distribution of radiation doses and the related biological responses in cells of a central airway bifurcation of the human lung of a hypothetical worker of the New Mexico uranium mines during approximately 12 hours of exposure to short-lived radon progenies. State-of-the-art computational modelling techniques were applied to simulate the relevant biophysical and biological processes in a central human airway bifurcation. The non-uniform deposition pattern of inhaled radon daughters caused a non-uniform distribution of energy deposition among cells, and of related cell inactivation and cell transformation probabilities. When damage propagation via bystander signalling was assessed, it produced more cell killing and cell transformation events than did direct effects. If bystander signalling was considered, variations of the average probabilities of cell killing and cell transformation were supra-linear over time. Our results are very sensitive to the radiobiological parameters, derived from in vitro experiments (e.g., range of bystander signalling), applied in this work and suggest that these parameters may not be directly applicable to realistic three-dimensional (3D) epithelium models.

Characterization of a dielectric barrier discharge in controlled atmosphere

NASA Astrophysics Data System (ADS)

Kogelheide, Friederike; Offerhaus, Björn; Bibinov, Nikita; Bracht, Vera; Smith, Ryan; Lackmann, Jan-Wilm; Awakowicz, Peter; Stapelmann, Katharina; Bimap Team; Aept Team

2016-09-01

Non-thermal atmospheric-pressure plasmas are advantageous for various biomedical applications as they make a contact- and painless therapy possible. Due to the potential medical relevance of such plasma sources further understanding of the chemical and physical impact on biological tissue regarding the efficacy and health-promoting effect is necessary. The knowledge of properties and effects offers the possibility to configure plasmas free of risk for humans. Therefore, tailoring the discharge chemistry in regard to resulting oxidative and nitrosative effects on biological tissue by adjusting different parameters is of growing interest. In order to ensure stable conditions for the characterization of the discharge, the used dielectric barrier discharge was mounted in a vessel. Absolutely calibrated optical emission spectroscopy was carried out to analyze the electron density and the reduced electric field. The rather oxygen-based discharge was tuned towards a more nitrogen-based discharge by adjusting several parameters as reactive nitrogen species are known to promote wound healing. Furthermore, the impact of an ozone-free discharge has to be studied. This work was funded by the German Research Foundation (DFG) with the packet grant PAK 816 `Plasma Cell Interaction in Dermatology'.

Using novel descriptor accounting for ligand-receptor interactions to define and visually explore biologically relevant chemical space.

PubMed

Rabal, Obdulia; Oyarzabal, Julen

2012-05-25

The definition and pragmatic implementation of biologically relevant chemical space is critical in addressing navigation strategies in the overlapping regions where chemistry and therapeutically relevant targets reside and, therefore, also key to performing an efficient drug discovery project. Here, we describe the development and implementation of a simple and robust method for representing biologically relevant chemical space as a general reference according to current knowledge, independently of any reference space, and analyzing chemical structures accordingly. Underlying our method is the generation of a novel descriptor (LiRIf) that converts structural information into a one-dimensional string accounting for the plausible ligand-receptor interactions as well as for topological information. Capitalizing on ligand-receptor interactions as a descriptor enables the clustering, profiling, and comparison of libraries of compounds from a chemical biology and medicinal chemistry perspective. In addition, as a case study, R-groups analysis is performed to identify the most populated ligand-receptor interactions according to different target families (GPCR, kinases, etc.), as well as to evaluate the coverage of biologically relevant chemical space by structures annotated in different databases (ChEMBL, Glida, etc.).

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

SacconePhD, Scott F; Chesler, Elissa J; Bierut, Laura J

Commercial SNP microarrays now provide comprehensive and affordable coverage of the human genome. However, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is thought to be influenced by complex interactions among many relevant genes and pathways. We have assembled a list of 486 biologically relevant genes nominated by a panel of experts on addiction. We then added 424 genes that showed evidence of association with addiction phenotypes through mouse QTL mappings and gene co-expression analysis. We demonstrate that there are a substantial number of SNPs in these genes that are not well representedmore » by commercial SNP platforms. We address this problem by introducing a publicly available SNP database for addiction. The database is annotated using numeric prioritization scores indicating the extent of biological relevance. The scores incorporate a number of factors such as SNP/gene functional properties (including synonymy and promoter regions), data from mouse systems genetics and measures of human/mouse evolutionary conservation. We then used HapMap genotyping data to determine if a SNP is tagged by a commercial microarray through linkage disequilibrium. This combination of biological prioritization scores and LD tagging annotation will enable addiction researchers to supplement commercial SNP microarrays to ensure comprehensive coverage of biologically relevant regions.« less

Reconstructing the hidden states in time course data of stochastic models.

PubMed

Zimmer, Christoph

2015-11-01

Parameter estimation is central for analyzing models in Systems Biology. The relevance of stochastic modeling in the field is increasing. Therefore, the need for tailored parameter estimation techniques is increasing as well. Challenges for parameter estimation are partial observability, measurement noise, and the computational complexity arising from the dimension of the parameter space. This article extends the multiple shooting for stochastic systems' method, developed for inference in intrinsic stochastic systems. The treatment of extrinsic noise and the estimation of the unobserved states is improved, by taking into account the correlation between unobserved and observed species. This article demonstrates the power of the method on different scenarios of a Lotka-Volterra model, including cases in which the prey population dies out or explodes, and a Calcium oscillation system. Besides showing how the new extension improves the accuracy of the parameter estimates, this article analyzes the accuracy of the state estimates. In contrast to previous approaches, the new approach is well able to estimate states and parameters for all the scenarios. As it does not need stochastic simulations, it is of the same order of speed as conventional least squares parameter estimation methods with respect to computational time. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A Systematic Review of the Cost-Effectiveness of Biologics for Ulcerative Colitis.

PubMed

Stawowczyk, Ewa; Kawalec, Paweł

2018-04-01

Ulcerative colitis (UC) is a chronic autoimmune inflammation of the colon. The condition significantly decreases quality of life and generates a substantial economic burden for healthcare payers, patients and the society in which they live. Some patients require chronic pharmacotherapy, and access to novel biologic drugs might be crucial for long-term remission. The analyses of cost-effectiveness for biologic drugs are necessary to assess their efficiency and provide the best available drugs to patients. Our aim was to collect and assess the quality of economic analyses carried out for biologic agents used in the treatment of UC, as well as to summarize evidence on the drivers of cost-effectiveness and evaluate the transferability and generalizability of conclusions. A systematic database review was conducted using MEDLINE (via PubMed), EMBASE, Cost-Effectiveness Analysis Registry and CRD0. Both authors independently reviewed the identified articles to determine their eligibility for final review. Hand searching of references in collected papers was also performed to find any relevant articles. The reporting quality of economic analyses included was evaluated by two reviewers using the International Society of Pharmacoeconomics and Outcomes Research (ISPOR) Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement checklist. We reviewed the sensitivity analyses in cost-effectiveness analyses to identify the variables that may have changed the conclusions of the study. Key drivers of cost-effectiveness were selected by identifying uncertain parameters that caused the highest change of the results of the analyses compared with base-case results. Of the 576 identified records, 87 were excluded as duplicates and 16 studies were included in the final review; evaluations for Canada, the UK and Poland were mostly performed. The majority of the evaluations revealed were performed for infliximab (approximately 75% of total volume); however, some assessments were also performed for adalimumab (50%) and golimumab (31%). Only three analyses were conducted for vedolizumab, whereas no relevant studies were found for etrolizumab and tofacitinib. The reporting quality of the included economic analyses was assessed as high, with an average score of 21 points per 24 maximum possible (range 14-23 points according to the ISPOR CHEERS statement checklist). In the case of most analyses, quality-adjusted life-years were used as a clinical outcome, and endpoints such as remission, response and mucosal healing were less common. The higher clinical effectiveness (based on response rates) of biological treatment over non-biological treatments was presented in revealed analyses. The incremental cost-utility ratios for biologics, compared with standard care, varied significantly between the studies and ranged from US$36,309 to US$456,979. The lowest value was obtained for infliximab and the highest for the treatment scheme including infliximab 5 mg/kg and infliximab 10 mg/kg + adalimumab. The change of utility weights and clinical parameters had the most significant influence on the results of the analysis; the variable related to surgery was the least sensitive. Limited data on the cost-effectiveness of UC therapy were identified. In the majority of studies, the lack of cost-effectiveness was revealed for biologics, which was associated with their high costs. Clinical outcomes are transferable to other countries and could be generalized; however, cost inputs are country-specific and therefore limit the transferability and generalizability of conclusions. The key drivers and variables that showed the greatest effect on the analysis results were utility weights and clinical parameters.

Interplay of stereoelectronic and enviromental effects in tuning the structural and magnetic properties of a prototypical spin probe: further insights from a first principle dynamical approach.

PubMed

Pavone, Michele; Cimino, Paola; De Angelis, Filippo; Barone, Vincenzo

2006-04-05

The nitrogen isotropic hyperfine coupling constant (hcc) and the g tensor of a prototypical spin probe (di-tert-butyl nitroxide, DTBN) in aqueous solution have been investigated by means of an integrated computational approach including Car-Parrinello molecular dynamics and quantum mechanical calculations involving a discrete-continuum embedding. The quantitative agreement between computed and experimental parameters fully validates our integrated approach. Decoupling of the structural, dynamical, and environmental contributions acting onto the spectral observables allows an unbiased judgment of the role played by different effects in determining the overall experimental observables and highlights the importance of finite-temperature vibrational averaging. Together with their intrinsic interest, our results pave the route toward more reliable interpretations of EPR parameters of complex systems of biological and technological relevance.

Stress-driven buckling patterns in spheroidal core/shell structures.

PubMed

Yin, Jie; Cao, Zexian; Li, Chaorong; Sheinman, Izhak; Chen, Xi

2008-12-09

Many natural fruits and vegetables adopt an approximately spheroidal shape and are characterized by their distinct undulating topologies. We demonstrate that various global pattern features can be reproduced by anisotropic stress-driven buckles on spheroidal core/shell systems, which implies that the relevant mechanical forces might provide a template underpinning the topological conformation in some fruits and plants. Three dimensionless parameters, the ratio of effective size/thickness, the ratio of equatorial/polar radii, and the ratio of core/shell moduli, primarily govern the initiation and formation of the patterns. A distinct morphological feature occurs only when these parameters fall within certain ranges: In a prolate spheroid, reticular buckles take over longitudinal ridged patterns when one or more parameters become large. Our results demonstrate that some universal features of fruit/vegetable patterns (e.g., those observed in Korean melons, silk gourds, ribbed pumpkins, striped cavern tomatoes, and cantaloupes, etc.) may be related to the spontaneous buckling from mechanical perspectives, although the more complex biological or biochemical processes are involved at deep levels.

Natural abundance (25)Mg solid-state NMR of mg oxyanion systems: a combined experimental and computational study.

PubMed

Cahill, Lindsay S; Hanna, John V; Wong, Alan; Freitas, Jair C C; Yates, Jonathan R; Harris, Robin K; Smith, Mark E

2009-09-28

Solid-state (25)Mg magic angle spinning nuclear magnetic resonance (MAS NMR) data are reported from a range of organic and inorganic magnesium-oxyanion compounds at natural abundance. To constrain the determination of the NMR interaction parameters (delta(iso), chi(Q), eta(Q)) data have been collected at three external magnetic fields (11.7, 14.1 and 18.8 T). Corresponding NMR parameters have also been calculated by using density functional theory (DFT) methods using the GIPAW approach, with good correlations being established between experimental and calculated values of both chi(Q) and delta(iso). These correlations demonstrate that the (25)Mg NMR parameters are very sensitive to the structure, with small changes in the local Mg(2+) environment and the overall hydration state profoundly affecting the observed spectra. The observations suggest that (25)Mg NMR spectroscopy is a potentially potent probe for addressing some key problems in inorganic materials and of metal centres in biologically relevant molecules.

Parametric studies on droplet generation reproducibility for applications with biological relevant fluids

PubMed Central

Eichler, Marko; Römer, Robert; Grodrian, Andreas; Lemke, Karen; Nagel, Krees; Klages, Claus‐Peter; Gastrock, Gunter

2017-01-01

Abstract Although the great potential of droplet based microfluidic technologies for routine applications in industry and academia has been successfully demonstrated over the past years, its inherent potential is not fully exploited till now. Especially regarding to the droplet generation reproducibility and stability, two pivotally important parameters for successful applications, there is still a need for improvement. This is even more considerable when droplets are created to investigate tissue fragments or cell cultures (e.g. suspended cells or 3D cell cultures) over days or even weeks. In this study we present microfluidic chips composed of a plasma coated polymer, which allow surfactants‐free, highly reproducible and stable droplet generation from fluids like cell culture media. We demonstrate how different microfluidic designs and different flow rates (and flow rate ratios) affect the reproducibility of the droplet generation process and display the applicability for a wide variety of bio(techno)logically relevant media. PMID:29399017

Ocean acidification in the coastal zone from an organism's perspective: multiple system parameters, frequency domains, and habitats.

PubMed

Waldbusser, George G; Salisbury, Joseph E

2014-01-01

Multiple natural and anthropogenic processes alter the carbonate chemistry of the coastal zone in ways that either exacerbate or mitigate ocean acidification effects. Freshwater inputs and multiple acid-base reactions change carbonate chemistry conditions, sometimes synergistically. The shallow nature of these systems results in strong benthic-pelagic coupling, and marine invertebrates at different life history stages rely on both benthic and pelagic habitats. Carbonate chemistry in coastal systems can be highly variable, responding to processes with temporal modes ranging from seconds to centuries. Identifying scales of variability relevant to levels of biological organization requires a fuller characterization of both the frequency and magnitude domains of processes contributing to or reducing acidification in pelagic and benthic habitats. We review the processes that contribute to coastal acidification with attention to timescales of variability and habitats relevant to marine bivalves.

Topological dimension tunes activity patterns in hierarchical modular networks

NASA Astrophysics Data System (ADS)

Safari, Ali; Moretti, Paolo; Muñoz, Miguel A.

2017-11-01

Connectivity patterns of relevance in neuroscience and systems biology can be encoded in hierarchical modular networks (HMNs). Recent studies highlight the role of hierarchical modular organization in shaping brain activity patterns, providing an excellent substrate to promote both segregation and integration of neural information. Here, we propose an extensive analysis of the critical spreading rate (or ‘epidemic’ threshold)—separating a phase with endemic persistent activity from one in which activity ceases—on diverse HMNs. By employing analytical and computational techniques we determine the nature of such a threshold and scrutinize how it depends on general structural features of the underlying HMN. We critically discuss the extent to which current graph-spectral methods can be applied to predict the onset of spreading in HMNs and, most importantly, we elucidate the role played by the network topological dimension as a relevant and unifying structural parameter, controlling the epidemic threshold.

Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder

USGS Publications Warehouse

Menke, S.B.; Holway, D.A.; Fisher, R.N.; Jetz, W.

2009-01-01

Aim: Species distribution models (SDMs) or, more specifically, ecological niche models (ENMs) are a useful and rapidly proliferating tool in ecology and global change biology. ENMs attempt to capture associations between a species and its environment and are often used to draw biological inferences, to predict potential occurrences in unoccupied regions and to forecast future distributions under environmental change. The accuracy of ENMs, however, hinges critically on the quality of occurrence data. ENMs often use haphazardly collected data rather than data collected across the full spectrum of existing environmental conditions. Moreover, it remains unclear how processes affecting ENM predictions operate at different spatial scales. The scale (i.e. grain size) of analysis may be dictated more by the sampling regime than by biologically meaningful processes. The aim of our study is to jointly quantify how issues relating to region and scale affect ENM predictions using an economically important and ecologically damaging invasive species, the Argentine ant (Linepithema humile). Location: California, USA. Methods: We analysed the relationship between sampling sufficiency, regional differences in environmental parameter space and cell size of analysis and resampling environmental layers using two independently collected sets of presence/absence data. Differences in variable importance were determined using model averaging and logistic regression. Model accuracy was measured with area under the curve (AUC) and Cohen's kappa. Results: We first demonstrate that insufficient sampling of environmental parameter space can cause large errors in predicted distributions and biological interpretation. Models performed best when they were parametrized with data that sufficiently sampled environmental parameter space. Second, we show that altering the spatial grain of analysis changes the relative importance of different environmental variables. These changes apparently result from how environmental constraints and the sampling distributions of environmental variables change with spatial grain. Conclusions: These findings have clear relevance for biological inference. Taken together, our results illustrate potentially general limitations for ENMs, especially when such models are used to predict species occurrences in novel environments. We offer basic methodological and conceptual guidelines for appropriate sampling and scale matching. ?? 2009 The Authors Journal compilation ?? 2009 Blackwell Publishing.

Prediction of bioavailability of selected bisphosphonates using in silico methods towards categorization into a biopharmaceutical classification system.

PubMed

Biernacka, Joanna; Betlejewska-Kielak, Katarzyna; Kłosińska-Szmurło, Ewa; Pluciński, Franciszek A; Mazurek, Aleksander P

2013-01-01

The physicochemical properties relevant to biological activity of selected bisphosphonates such as clodronate disodium salt, etidronate disodium salt, pamidronate disodium salt, alendronate sodium salt, ibandronate sodium salt, risedronate sodium salt and zoledronate disodium salt were determined using in silico methods. The main aim of our research was to investigate and propose molecular determinants thataffect bioavailability of above mentioned compounds. These determinants are: stabilization energy (deltaE), free energy of solvation (deltaG(solv)), electrostatic potential, dipole moment, as well as partition and distribution coefficients estimated by the log P and log D values. Presented values indicate that selected bisphosphonates a recharacterized by high solubility and low permeability. The calculated parameters describing both solubility and permeability through biological membranes seem to be a good bioavailability indicators of bisphosphonates examined and can be a useful tool to include into Biopharmaceutical Classification System (BCS) development.

Bio-activity of aminosulfonyl ureas in the light of nucleic acid bases and DNA base pair interaction.

PubMed

Mondal Roy, Sutapa

2018-08-01

The quantum chemical descriptors based on density functional theory (DFT) are applied to predict the biological activity (log IC 50 ) of one class of acyl-CoA: cholesterol O-acyltransferase (ACAT) inhibitors, viz. aminosulfonyl ureas. ACAT are very effective agents for reduction of triglyceride and cholesterol levels in human body. Successful two parameter quantitative structure-activity relationship (QSAR) models are developed with a combination of relevant global and local DFT based descriptors for prediction of biological activity of aminosulfonyl ureas. The global descriptors, electron affinity of the ACAT inhibitors (EA) and/or charge transfer (ΔN) between inhibitors and model biosystems (NA bases and DNA base pairs) along with the local group atomic charge on sulfonyl moiety (∑Q Sul ) of the inhibitors reveals more than 90% efficacy of the selected descriptors for predicting the experimental log (IC 50 ) values. Copyright © 2018 Elsevier Ltd. All rights reserved.

Industrial activated sludge exhibit unique bacterial community composition at high taxonomic ranks.

PubMed

Ibarbalz, Federico M; Figuerola, Eva L M; Erijman, Leonardo

2013-07-01

Biological degradation of domestic and industrial wastewater by activated sludge depends on a common process of separation of the diverse self-assembled and self-sustained microbial flocs from the treated wastewater. Previous surveys of bacterial communities indicated the presence of a common core of bacterial phyla in municipal activated sludge, an observation consistent with the concept of ecological coherence of high taxonomic ranks. The aim of this work was to test whether this critical feature brings about a common pattern of abundance distribution of high bacterial taxa in industrial and domestic activated sludge, and to relate the bacterial community structure of industrial activated sludge with relevant operational parameters. We have applied 454 pyrosequencing of 16S rRNA genes to evaluate bacterial communities in full-scale biological wastewater treatment plants sampled at different times, including seven systems treating wastewater from different industries and one plant that treats domestic wastewater, and compared our datasets with the data from municipal wastewater treatment plants obtained by three different laboratories. We observed that each industrial activated sludge system exhibited a unique bacterial community composition, which is clearly distinct from the common profile of bacterial phyla or classes observed in municipal plants. The influence of process parameters on the bacterial community structure was evaluated using constrained analysis of principal coordinates (CAP). Part of the differences in the bacterial community structure between industrial wastewater treatment systems were explained by dissolved oxygen and pH. Despite the ecological relevance of floc formation for the assembly of bacterial communities in activated sludge, the wastewater characteristics are likely to be the major determinant that drives bacterial composition at high taxonomic ranks. Copyright © 2013 Elsevier Ltd. All rights reserved.

Spatial distribution of osteopontin, CD44v6 and podoplanin in the lining epithelium of odontogenic keratocyst, and their biological relevance.

PubMed

Kechik, Khamisah Awang; Siar, Chong Huat

2018-02-01

The odontogenic keratocyst (OKC) remains the most challenging jaw cyst to treat because of its locally-aggressive behaviour and high recurrence potential. Emerging evidence suggests that osteopontin, its receptors CD44v6 and integrin α v , and podoplanin, have a role in the local invasiveness of this cyst. However the spatial distribution characteristics of these pro-invasive markers in the lining epithelium of OKC, and their association with the clinicopathologic parameters of OKC are largely unexplored. This study sought to address these issues in comparison with dentigerous cysts (DCs) and radicular cysts (RCs) and to evaluate their biological relevance. A sample consisting of 20 OKC cases, 10 DCs and 10 RCs was subjected to immunohistochemical staining for osteopontin, CD44v6 and integrin α v , and podoplanin, and semiquantitative analysis was performed. All factors (except integrin α v ) were detected heterogeneously in the constitutive layers of the lining epithelium in all three cyst types. Key observations were significant upregulation of CD44v6 and podoplanin in OKC compared to DCs and RCs, suggesting that these protein molecules may play crucial roles in promoting local invasiveness in OKC (P<0.05). Osteopontin underexpression and distribution patterns were indistinctive among all three cysts indicating its limited role as pro-invasive factor. Clinical parameters showed no significant correlations with all protein factors investigated. Present findings suggest that an osteopontin low CD44v6 high and podoplanin high immunoprofile most probably represent epithelial signatures of OKC and are markers of local invasiveness in this cyst. Copyright © 2017 Elsevier Inc. All rights reserved.

Biological relevance of streamflow metrics: Regional and national perspectives

USGS Publications Warehouse

Carlisle, Daren M.; Grantham, Theodore E.; Eng, Kenny; Wolock, David M.

2017-01-01

Protecting the health of streams and rivers requires identifying ecologically significant attributes of the natural flow regime. Streamflow regimes are routinely quantified using a plethora of hydrologic metrics (HMs), most of which have unknown relevance to biological communities. At regional and national scales, we evaluated which of 509 commonly used HMs were associated with biological indicators of fish and invertebrate community integrity. We quantified alteration of each HM by using statistical models to predict site-specific natural baseline values for each of 728 sites across the USA where streamflow monitoring data were available concurrent with assessments of invertebrate or fish community integrity. We then ranked HMs according to their individual association with biological integrity based on random forest models that included HMs and other relevant covariates, such as land cover and stream chemistry. HMs were generally the most important predictors of biological integrity relative to the covariates. At a national scale, the most influential HMs were measures of depleted high flows, homogenization of flows, and erratic flows. Unique combinations of biologically relevant HMs were apparent among regions. We discuss the implications of our findings to the challenge of selecting HMs for streamflow research and management.

Statistical approach for selection of biologically informative genes.

PubMed

Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

2018-05-20

Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes from high dimensional expression data for breeding and system biology studies. Published by Elsevier B.V.

Privileged structures: efficient chemical "navigators" toward unexplored biologically relevant chemical spaces.

PubMed

Kim, Jonghoon; Kim, Heejun; Park, Seung Bum

2014-10-22

In the search for new therapeutic agents for currently incurable diseases, attention has turned to traditionally "undruggable" targets, and collections of drug-like small molecules with high diversity and quality have become a prerequisite for new breakthroughs. To generate such collections, the diversity-oriented synthesis (DOS) strategy was developed, which aims to populate new chemical space with drug-like compounds containing a high degree of molecular diversity. The resulting DOS-derived libraries have been of great value for the discovery of various bioactive small molecules and therapeutic agents, and thus DOS has emerged as an essential tool in chemical biology and drug discovery. However, the key challenge has become how to design and synthesize drug-like small-molecule libraries with improved biological relevancy as well as maximum molecular diversity. This Perspective presents the development of privileged substructure-based DOS (pDOS), an efficient strategy for the construction of polyheterocyclic compound libraries with high biological relevancy. We envisioned the specific interaction of drug-like small molecules with certain biopolymers via the incorporation of privileged substructures into polyheterocyclic core skeletons. The importance of privileged substructures such as benzopyran, pyrimidine, and oxopiperazine in rigid skeletons was clearly demonstrated through the discovery of bioactive small molecules and the subsequent identification of appropriate target biomolecule using a method called "fluorescence difference in two-dimensional gel electrophoresis". Focusing on examples of pDOS-derived bioactive compounds with exceptional specificity, we discuss the capability of privileged structures to serve as chemical "navigators" toward biologically relevant chemical spaces. We also provide an outlook on chemical biology research and drug discovery using biologically relevant compound libraries constructed by pDOS, biology-oriented synthesis, or natural product-inspired DOS.

Modelling Wolbachia infection in a sex-structured mosquito population carrying West Nile virus.

PubMed

Farkas, József Z; Gourley, Stephen A; Liu, Rongsong; Yakubu, Abdul-Aziz

2017-09-01

Wolbachia is possibly the most studied reproductive parasite of arthropod species. It appears to be a promising candidate for biocontrol of some mosquito borne diseases. We begin by developing a sex-structured model for a Wolbachia infected mosquito population. Our model incorporates the key effects of Wolbachia infection including cytoplasmic incompatibility and male killing. We also allow the possibility of reduced reproductive output, incomplete maternal transmission, and different mortality rates for uninfected/infected male/female individuals. We study the existence and local stability of equilibria, including the biologically relevant and interesting boundary equilibria. For some biologically relevant parameter regimes there may be multiple coexistence steady states including, very importantly, a coexistence steady state in which Wolbachia infected individuals dominate. We also extend the model to incorporate West Nile virus (WNv) dynamics, using an SEI modelling approach. Recent evidence suggests that a particular strain of Wolbachia infection significantly reduces WNv replication in Aedes aegypti. We model this via increased time spent in the WNv-exposed compartment for Wolbachia infected female mosquitoes. A basic reproduction number [Formula: see text] is computed for the WNv infection. Our results suggest that, if the mosquito population consists mainly of Wolbachia infected individuals, WNv eradication is likely if WNv replication in Wolbachia infected individuals is sufficiently reduced.

An analytical poroelastic model for ultrasound elastography imaging of tumors

NASA Astrophysics Data System (ADS)

Tauhidul Islam, Md; Chaudhry, Anuj; Unnikrishnan, Ginu; Reddy, J. N.; Righetti, Raffaella

2018-01-01

The mechanical behavior of biological tissues has been studied using a number of mechanical models. Due to the relatively high fluid content and mobility, many biological tissues have been modeled as poroelastic materials. Diseases such as cancers are known to alter the poroelastic response of a tissue. Tissue poroelastic properties such as compressibility, interstitial permeability and fluid pressure also play a key role for the assessment of cancer treatments and for improved therapies. At the present time, however, a limited number of poroelastic models for soft tissues are retrievable in the literature, and the ones available are not directly applicable to tumors as they typically refer to uniform tissues. In this paper, we report the analytical poroelastic model for a non-uniform tissue under stress relaxation. Displacement, strain and fluid pressure fields in a cylindrical poroelastic sample containing a cylindrical inclusion during stress relaxation are computed. Finite element simulations are then used to validate the proposed theoretical model. Statistical analysis demonstrates that the proposed analytical model matches the finite element results with less than 0.5% error. The availability of the analytical model and solutions presented in this paper may be useful to estimate diagnostically relevant poroelastic parameters such as interstitial permeability and fluid pressure, and, in general, for a better interpretation of clinically-relevant ultrasound elastography results.

Text Mining Effectively Scores and Ranks the Literature for Improving Chemical-Gene-Disease Curation at the Comparative Toxicogenomics Database

PubMed Central

Johnson, Robin J.; Lay, Jean M.; Lennon-Hopkins, Kelley; Saraceni-Richards, Cynthia; Sciaky, Daniela; Murphy, Cynthia Grondin; Mattingly, Carolyn J.

2013-01-01

The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) is a public resource that curates interactions between environmental chemicals and gene products, and their relationships to diseases, as a means of understanding the effects of environmental chemicals on human health. CTD provides a triad of core information in the form of chemical-gene, chemical-disease, and gene-disease interactions that are manually curated from scientific articles. To increase the efficiency, productivity, and data coverage of manual curation, we have leveraged text mining to help rank and prioritize the triaged literature. Here, we describe our text-mining process that computes and assigns each article a document relevancy score (DRS), wherein a high DRS suggests that an article is more likely to be relevant for curation at CTD. We evaluated our process by first text mining a corpus of 14,904 articles triaged for seven heavy metals (cadmium, cobalt, copper, lead, manganese, mercury, and nickel). Based upon initial analysis, a representative subset corpus of 3,583 articles was then selected from the 14,094 articles and sent to five CTD biocurators for review. The resulting curation of these 3,583 articles was analyzed for a variety of parameters, including article relevancy, novel data content, interaction yield rate, mean average precision, and biological and toxicological interpretability. We show that for all measured parameters, the DRS is an effective indicator for scoring and improving the ranking of literature for the curation of chemical-gene-disease information at CTD. Here, we demonstrate how fully incorporating text mining-based DRS scoring into our curation pipeline enhances manual curation by prioritizing more relevant articles, thereby increasing data content, productivity, and efficiency. PMID:23613709

Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

PubMed Central

Xu, Jianfeng; Lan, Yueheng

2015-01-01

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

A quantitative approach to neuropsychiatry: The why and the how.

PubMed

Kas, Martien J; Penninx, Brenda; Sommer, Bernd; Serretti, Alessandro; Arango, Celso; Marston, Hugh

2017-12-12

The current nosology of neuropsychiatric disorders allows for a pragmatic approach to treatment choice, regulation and clinical research. However, without a biological rationale for these disorders, drug development has stagnated. The recently EU-funded PRISM project aims to develop a quantitative biological approach to the understanding and classification of neuropsychiatric diseases to accelerate the discovery and development of better treatments. By combining clinical data sets from major worldwide disease cohorts and by applying innovative technologies to deeply phenotype stratified patient groups, we will define a set of quantifiable biological parameters for social withdrawal and cognitive deficits common to Schizophrenia (SZ), Major Depression (MD), and Alzheimer's Disease (AD). These studies aim to provide new classification and assessment tools for social and cognitive performance across neuropsychiatric disorders, clinically relevant substrates for treatment development, and predictive, preclinical animal systems. With patients and regulatory agencies, we seek to provide clear routes for the future translation and regulatory approval for new treatments and provide solutions to the growing public health challenges of psychiatry and neurology. Copyright © 2017. Published by Elsevier Ltd.

HUMAN BIOMONITORING TO LINK ENVIRONMENTAL EXPOSURE TO BIOLOGICALLY RELEVANT DOSE

EPA Science Inventory

The abstract and presentation on Human Biomonitoring to Link Environmental Exposure to Biologically Relevant Dose describes the use of biomarkers of exposure, biomarkers of current health state, and biomarker measurements. The abstract and presentation focuses on how biomarkers ...

Fundamentals of microfluidic cell culture in controlled microenvironments†

PubMed Central

Young, Edmond W. K.; Beebe, David J.

2010-01-01

Microfluidics has the potential to revolutionize the way we approach cell biology research. The dimensions of microfluidic channels are well suited to the physical scale of biological cells, and the many advantages of microfluidics make it an attractive platform for new techniques in biology. One of the key benefits of microfluidics for basic biology is the ability to control parameters of the cell microenvironment at relevant length and time scales. Considerable progress has been made in the design and use of novel microfluidic devices for culturing cells and for subsequent treatment and analysis. With the recent pace of scientific discovery, it is becoming increasingly important to evaluate existing tools and techniques, and to synthesize fundamental concepts that would further improve the efficiency of biological research at the microscale. This tutorial review integrates fundamental principles from cell biology and local microenvironments with cell culture techniques and concepts in microfluidics. Culturing cells in microscale environments requires knowledge of multiple disciplines including physics, biochemistry, and engineering. We discuss basic concepts related to the physical and biochemical microenvironments of the cell, physicochemical properties of that microenvironment, cell culture techniques, and practical knowledge of microfluidic device design and operation. We also discuss the most recent advances in microfluidic cell culture and their implications on the future of the field. The goal is to guide new and interested researchers to the important areas and challenges facing the scientific community as we strive toward full integration of microfluidics with biology. PMID:20179823

Biologics in pediatric psoriasis - efficacy and safety.

PubMed

Dogra, Sunil; Mahajan, Rahul

2018-01-01

Childhood psoriasis is a special situation that is a management challenge for the treating dermatologist. As is the situation with traditional systemic agents, which are commonly used in managing severe psoriasis in children, the biologics are being increasingly used in the recalcitrant disease despite limited data on long term safety. Areas covered: We performed an extensive literature search to collect evidence-based data on the use of biologics in pediatric psoriasis. The relevant literature published from 2000 to September 2017 was obtained from PubMed, using the MeSH words 'biologics', 'biologic response modifiers' and 'treatment of pediatric/childhood psoriasis'. All clinical trials, randomized double-blind or single-blind controlled trials, open-label studies, retrospective studies, reviews, case reports and letters concerning the use of biologics in pediatric psoriasis were screened. Articles covering the use of biologics in pediatric psoriasis were screened and reference lists in the selected articles were scrutinized to identify other relevant articles that had not been found in the initial search. Articles without relevant information about biologics in general (e.g. its mechanism of action, pharmacokinetics and adverse effects) and its use in psoriasis in particular were excluded. We screened 427 articles and finally selected 41 relevant articles. Expert opinion: The available literature on the use of biologics such as anti-tumor necrosis factor (TNF)-α agents, and anti-IL-12/23 agents like ustekinumab suggests that these are effective and safe in managing severe pediatric psoriasis although there is an urgent need to generate more safety data. Dermatologists must be careful about the potential adverse effects of the biologics before administering them to children with psoriasis. It is likely that with rapidly evolving scenario of biologics in psoriasis, these will prove to be very useful molecules particularly in managing severe and recalcitrant psoriasis in pediatric age group.

Decoherence and spin echo in biological systems.

PubMed

Nesterov, Alexander I; Berman, Gennady P

2015-05-01

The spin-echo approach is extended to include biocomplexes for which the interaction with dynamical noise, produced by the protein environment, is strong. Significant restoration of the free induction decay signal due to homogeneous (decoherence) and inhomogeneous (dephasing) broadening is demonstrated analytically and numerically for both an individual dimer of interacting chlorophylls and for an ensemble of dimers. Our approach does not require the use of small interaction constants between the electron states and the protein fluctuations. It is based on an exact and closed system of ordinary differential equations that can be easily solved for a wide range of parameters that are relevant for bioapplications.

Decoherence and spin echo in biological systems

NASA Astrophysics Data System (ADS)

Nesterov, Alexander I.; Berman, Gennady P.

2015-05-01

The spin-echo approach is extended to include biocomplexes for which the interaction with dynamical noise, produced by the protein environment, is strong. Significant restoration of the free induction decay signal due to homogeneous (decoherence) and inhomogeneous (dephasing) broadening is demonstrated analytically and numerically for both an individual dimer of interacting chlorophylls and for an ensemble of dimers. Our approach does not require the use of small interaction constants between the electron states and the protein fluctuations. It is based on an exact and closed system of ordinary differential equations that can be easily solved for a wide range of parameters that are relevant for bioapplications.

Moderator's view: High-volume plasma exchange: pro, con and consensus.

PubMed

Kaplan, Andre A

2017-09-01

I have been asked to comment on the pro and con opinions regarding high-volume plasma exchange. The authors of both positions have provided cogent arguments and a reasonable approach to choosing the exchange volume for any given therapeutic plasma exchange. The major issue of relevance in this discussion is the nature of the toxins targeted for removal. These parameters include molecular weight, the apparent volume of distribution, the degree of protein binding, the biologic and chemical half-life, and the severity and rapidity of its toxicity. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Determination of the Biologically Relevant Sampling Depth for Terrestrial and Aquatic Ecological Risk Assessments (Final Report)

EPA Science Inventory

The Ecological Risk Assessment Support Center (ERASC) announced the release of the final report, Determination of the Biologically Relevant Sampling Depth for Terrestrial and Aquatic Ecological Risk Assessments. This technical paper provides defensible approximations fo...

Bayesian parameter estimation for nonlinear modelling of biological pathways.

PubMed

Ghasemi, Omid; Lindsey, Merry L; Yang, Tianyi; Nguyen, Nguyen; Huang, Yufei; Jin, Yu-Fang

2011-01-01

The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC) method. We applied this approach to the biological pathways involved in the left ventricle (LV) response to myocardial infarction (MI) and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly parameterized dynamic systems. Our proposed Bayesian algorithm successfully estimated parameters in nonlinear mathematical models for biological pathways. This method can be further extended to high order systems and thus provides a useful tool to analyze biological dynamics and extract information using temporal data.

Balancing the Interactions of Ions, Water, and DNA in the Drude Polarizable Force Field

PubMed Central

2015-01-01

Recently we presented a first-generation all-atom Drude polarizable force field for DNA based on the classical Drude oscillator model, focusing on optimization of key dihedral angles followed by extensive validation of the force field parameters. Presently, we describe the procedure for balancing the electrostatic interactions between ions, water, and DNA as required for development of the Drude force field for DNA. The proper balance of these interactions is shown to impact DNA stability and subtler conformational properties, including the conformational equilibrium between the BI and BII states, and the A and B forms of DNA. The parametrization efforts were simultaneously guided by gas-phase quantum mechanics (QM) data on small model compounds and condensed-phase experimental data on the hydration and osmotic properties of biologically relevant ions and their solutions, as well as theoretical predictions for ionic distribution around DNA oligomer. In addition, fine-tuning of the internal base parameters was performed to obtain the final DNA model. Notably, the Drude model is shown to more accurately reproduce counterion condensation theory predictions of DNA charge neutralization by the condensed ions as compared to the CHARMM36 additive DNA force field, indicating an improved physical description of the forces dictating the ionic solvation of DNA due to the explicit treatment of electronic polarizability. In combination with the polarizable DNA force field, the availability of Drude polarizable parameters for proteins, lipids, and carbohydrates will allow for simulation studies of heterogeneous biological systems. PMID:24874104

Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

NASA Astrophysics Data System (ADS)

Bereau, Tristan; DiStasio, Robert A.; Tkatchenko, Alexandre; von Lilienfeld, O. Anatole

2018-06-01

Classical intermolecular potentials typically require an extensive parametrization procedure for any new compound considered. To do away with prior parametrization, we propose a combination of physics-based potentials with machine learning (ML), coined IPML, which is transferable across small neutral organic and biologically relevant molecules. ML models provide on-the-fly predictions for environment-dependent local atomic properties: electrostatic multipole coefficients (significant error reduction compared to previously reported), the population and decay rate of valence atomic densities, and polarizabilities across conformations and chemical compositions of H, C, N, and O atoms. These parameters enable accurate calculations of intermolecular contributions—electrostatics, charge penetration, repulsion, induction/polarization, and many-body dispersion. Unlike other potentials, this model is transferable in its ability to handle new molecules and conformations without explicit prior parametrization: All local atomic properties are predicted from ML, leaving only eight global parameters—optimized once and for all across compounds. We validate IPML on various gas-phase dimers at and away from equilibrium separation, where we obtain mean absolute errors between 0.4 and 0.7 kcal/mol for several chemically and conformationally diverse datasets representative of non-covalent interactions in biologically relevant molecules. We further focus on hydrogen-bonded complexes—essential but challenging due to their directional nature—where datasets of DNA base pairs and amino acids yield an extremely encouraging 1.4 kcal/mol error. Finally, and as a first look, we consider IPML for denser systems: water clusters, supramolecular host-guest complexes, and the benzene crystal.

Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

NASA Technical Reports Server (NTRS)

Gentry, Diana

2017-01-01

The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may soon enable unique insight into which measured phenomena correlate to biological mechanisms that are truly affected by spaceflight conditions; which are most likely to be confounded by other variables; and which are insufficiently characterized, significantly increasing existing and future science return from ISS and spaceflight missions.

Parameterization of DFTB3/3OB for Sulfur and Phosphorus for Chemical and Biological Applications

PubMed Central

2015-01-01

We report the parametrization of the approximate density functional tight binding method, DFTB3, for sulfur and phosphorus. The parametrization is done in a framework consistent with our previous 3OB set established for O, N, C, and H, thus the resulting parameters can be used to describe a broad set of organic and biologically relevant molecules. The 3d orbitals are included in the parametrization, and the electronic parameters are chosen to minimize errors in the atomization energies. The parameters are tested using a fairly diverse set of molecules of biological relevance, focusing on the geometries, reaction energies, proton affinities, and hydrogen bonding interactions of these molecules; vibrational frequencies are also examined, although less systematically. The results of DFTB3/3OB are compared to those from DFT (B3LYP and PBE), ab initio (MP2, G3B3), and several popular semiempirical methods (PM6 and PDDG), as well as predictions of DFTB3 with the older parametrization (the MIO set). In general, DFTB3/3OB is a major improvement over the previous parametrization (DFTB3/MIO), and for the majority cases tested here, it also outperforms PM6 and PDDG, especially for structural properties, vibrational frequencies, hydrogen bonding interactions, and proton affinities. For reaction energies, DFTB3/3OB exhibits major improvement over DFTB3/MIO, due mainly to significant reduction of errors in atomization energies; compared to PM6 and PDDG, DFTB3/3OB also generally performs better, although the magnitude of improvement is more modest. Compared to high-level calculations, DFTB3/3OB is most successful at predicting geometries; larger errors are found in the energies, although the results can be greatly improved by computing single point energies at a high level with DFTB3 geometries. There are several remaining issues with the DFTB3/3OB approach, most notably its difficulty in describing phosphate hydrolysis reactions involving a change in the coordination number of the phosphorus, for which a specific parametrization (3OB/OPhyd) is developed as a temporary solution; this suggests that the current DFTB3 methodology has limited transferability for complex phosphorus chemistry at the level of accuracy required for detailed mechanistic investigations. Therefore, fundamental improvements in the DFTB3 methodology are needed for a reliable method that describes phosphorus chemistry without ad hoc parameters. Nevertheless, DFTB3/3OB is expected to be a competitive QM method in QM/MM calculations for studying phosphorus/sulfur chemistry in condensed phase systems, especially as a low-level method that drives the sampling in a dual-level QM/MM framework. PMID:24803865

Bayesian LASSO, scale space and decision making in association genetics.

PubMed

Pasanen, Leena; Holmström, Lasse; Sillanpää, Mikko J

2015-01-01

LASSO is a penalized regression method that facilitates model fitting in situations where there are as many, or even more explanatory variables than observations, and only a few variables are relevant in explaining the data. We focus on the Bayesian version of LASSO and consider four problems that need special attention: (i) controlling false positives, (ii) multiple comparisons, (iii) collinearity among explanatory variables, and (iv) the choice of the tuning parameter that controls the amount of shrinkage and the sparsity of the estimates. The particular application considered is association genetics, where LASSO regression can be used to find links between chromosome locations and phenotypic traits in a biological organism. However, the proposed techniques are relevant also in other contexts where LASSO is used for variable selection. We separate the true associations from false positives using the posterior distribution of the effects (regression coefficients) provided by Bayesian LASSO. We propose to solve the multiple comparisons problem by using simultaneous inference based on the joint posterior distribution of the effects. Bayesian LASSO also tends to distribute an effect among collinear variables, making detection of an association difficult. We propose to solve this problem by considering not only individual effects but also their functionals (i.e. sums and differences). Finally, whereas in Bayesian LASSO the tuning parameter is often regarded as a random variable, we adopt a scale space view and consider a whole range of fixed tuning parameters, instead. The effect estimates and the associated inference are considered for all tuning parameters in the selected range and the results are visualized with color maps that provide useful insights into data and the association problem considered. The methods are illustrated using two sets of artificial data and one real data set, all representing typical settings in association genetics.

Behavioral and Biological Effects of Housing Conditions and Stress in Male Rats - Relevance to Heart Disease

DTIC Science & Technology

2006-08-01

animals had higher corticosterone than Combined Enrichment/Not Stressed (CNS) animals (F [1, 22 ] = 6.78, p < 0.01). The greatest effects were in...biological effects of stress. In particular, plasma corticosterone levels have been reported to increase in response to stressors in different... effects of restraint stress on the biological and behavioral factors relevant to cardiovascular disease (e.g., plasma corticosterone levels

Genetic differences in human circadian clock genes among worldwide populations.

PubMed

Ciarleglio, Christopher M; Ryckman, Kelli K; Servick, Stein V; Hida, Akiko; Robbins, Sam; Wells, Nancy; Hicks, Jennifer; Larson, Sydney A; Wiedermann, Joshua P; Carver, Krista; Hamilton, Nalo; Kidd, Kenneth K; Kidd, Judith R; Smith, Jeffrey R; Friedlaender, Jonathan; McMahon, Douglas G; Williams, Scott M; Summar, Marshall L; Johnson, Carl Hirschie

2008-08-01

The daily biological clock regulates the timing of sleep and physiological processes that are of fundamental importance to human health, performance, and well-being. Environmental parameters of relevance to biological clocks include (1) daily fluctuations in light intensity and temperature, and (2) seasonal changes in photoperiod (day length) and temperature; these parameters vary dramatically as a function of latitude and locale. In wide-ranging species other than humans, natural selection has genetically optimized adaptiveness along latitudinal clines. Is there evidence for selection of clock gene alleles along latitudinal/photoperiod clines in humans? A number of polymorphisms in the human clock genes Per2, Per3, Clock, and AANAT have been reported as alleles that could be subject to selection. In addition, this investigation discovered several novel polymorphisms in the human Arntl and Arntl2 genes that may have functional impact upon the expression of these clock transcriptional factors. The frequency distribution of these clock gene polymorphisms is reported for diverse populations of African Americans, European Americans, Ghanaians, Han Chinese, and Papua New Guineans (including 5 subpopulations within Papua New Guinea). There are significant differences in the frequency distribution of clock gene alleles among these populations. Population genetic analyses indicate that these differences are likely to arise from genetic drift rather than from natural selection.

Transdisciplinary Application of Cross-Scale Resilience ...

EPA Pesticide Factsheets

The cross-scale resilience model was developed in ecology to explain the emergence of resilience from the distribution of ecological functions within and across scales, and as a tool to assess resilience. We propose that the model and the underlyingdiscontinuity hypothesis are relevant to other complex adaptive systems, and can be used to identify and track changes in system parameters related to resilience. We explain the theory behind the cross-scale resilience model, review the cases where it has been applied to non-ecological systems, and discuss some examples of social-ecological, archaeological/anthropological, and economic systems where a cross-scale resilience analysis could add a quantitative dimension to our current understanding of system dynamics and resilience. We argue that the scaling and diversity parameters suitable for a resilience analysis of ecological systems are appropriate for a broad suite of systems where non-normative quantitative assessments of resilience are desired. Our planet is currently characterized by fast environmental and social change, and the cross-scale resilience model has the potential to quantify resilience across many types of complex adaptive systems. Comparative analyses of complex systems have, in fact, demonstrated commonalities among distinctly different types of systems (Schneider & Kay 1994; Holling 2001; Lansing 2003; Foster 2005; Bullmore et al. 2009). Both biological and non-biological complex systems appear t

Bioavailability of antioxidants in extruded products prepared from purple potato and dry pea flours

USDA-ARS?s Scientific Manuscript database

Measuring antioxidant activity using biological relevant assay is unique to understand the role of phytochemicals in vivo than common chemical assays. Cellular antioxidant activity assay could provide more biological relevant information on bioactive compounds in the raw as well as processed food pr...

Brachypodium as a model for the grasses: today and the future

USDA-ARS?s Scientific Manuscript database

Over the past several years, Brachypodium distachyon (Brachypodium) has emerged as a tractable model system to study biological questions relevant to the grasses. To place its relevance in the larger context of plant biology, we outline here the expanding adoption of Brachypodium as a model grass an...

IDENTIFICATION OF BIOLOGICALLY RELEVANT GENES USING A DATABASE OF RAT LIVER AND KIDNEY BASELINE GENE EXPRESSION

EPA Science Inventory

Microarray data from independent labs and studies can be compared to potentially identify toxicologically and biologically relevant genes. The Baseline Animal Database working group of HESI was formed to assess baseline gene expression from microarray data derived from control or...

Integration of robotics and neuroscience beyond the hand: What kind of synergies?. Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by Marco Santello et al.

NASA Astrophysics Data System (ADS)

d'Avella, Andrea

2016-07-01

Santello et al. [1] review an impressive amount of work on the control of biological and artificial hands that demonstrates how the concept of synergies can lead to a successful integration of robotics and neuroscience. Is it possible to generalize the same approach to the control of biological and artificial limbs and bodies beyond the hand? The human hand synergies that appear most relevant for robotic hands are those defined at the kinematic level, i.e. postural synergies [2]. Postural synergies capture the geometric relations among the many joints of the hand and allow for a low dimensional characterization and synthesis of the static hand postures involved in grasping and manipulating a large set of objects. However, many other complex motor skills such as walking, reaching, throwing, and catching require controlling multi-articular time-varying trajectories rather than static postures. Dynamic control of biological and artificial limbs and bodies, especially when geometric and inertial parameters are uncertain and the joints are compliant, poses great challenges. What kind of synergies might simplify the dynamic control of motor skills involving upper and lower limbs as well as the whole body?

Culture and symptom reporting at menopause.

PubMed

Melby, Melissa K; Lock, Margaret; Kaufert, Patricia

2005-01-01

The purpose of the present paper is to review recent research on the relationship of culture and menopausal symptoms and propose a biocultural framework that makes use of both biological and cultural parameters in future research. Medline was searched for English-language articles published from 2000 to 2004 using the keyword 'menopause' in the journals--Menopause, Maturitas, Climacteric, Social Science and Medicine, Medical Anthropology Quarterly, Journal of Women's Health, Journal of the American Medical Association, American Journal of Epidemiology, Lancet and British Medical Journal, excluding articles concerning small clinical samples, surgical menopause or HRT. Additionally, references of retrieved articles and reviews were hand-searched. Although a large number of studies and publications exist, methodological differences limit attempts at comparison or systematic review. We outline a theoretical framework in which relevant biological and cultural variables can be operationalized and measured, making it possible for rigorous comparisons in the future. Several studies carried out in Japan, North America and Australia, using similar methodology but different culture/ethnic groups, indicate that differences in symptom reporting are real and highlight the importance of biocultural research. We suggest that both biological variation and cultural differences contribute to the menopausal transition, and that more rigorous data collection is required to elucidate how biology and culture interact in female ageing.

Medical smart textiles based on fiber optic technology: an overview.

PubMed

Massaroni, Carlo; Saccomandi, Paola; Schena, Emiliano

2015-04-13

The growing interest in the development of smart textiles for medical applications is driven by the aim to increase the mobility of patients who need a continuous monitoring of such physiological parameters. At the same time, the use of fiber optic sensors (FOSs) is gaining large acceptance as an alternative to traditional electrical and mechanical sensors for the monitoring of thermal and mechanical parameters. The potential impact of FOSs is related to their good metrological properties, their small size and their flexibility, as well as to their immunity from electromagnetic field. Their main advantage is the possibility to use textile based on fiber optic in a magnetic resonance imaging environment, where standard electronic sensors cannot be employed. This last feature makes FOSs suitable for monitoring biological parameters (e.g., respiratory and heartbeat monitoring) during magnetic resonance procedures. Research interest in combining FOSs and textiles into a single structure to develop wearable sensors is rapidly growing. In this review we provide an overview of the state-of-the-art of textiles, which use FOSs for monitoring of mechanical parameters of physiological interest. In particular we briefly describe the working principle of FOSs employed in this field and their relevant advantages and disadvantages. Also reviewed are their applications for the monitoring of mechanical parameters of physiological interest.

Medical Smart Textiles Based on Fiber Optic Technology: An Overview

PubMed Central

Massaroni, Carlo; Saccomandi, Paola; Schena, Emiliano

2015-01-01

The growing interest in the development of smart textiles for medical applications is driven by the aim to increase the mobility of patients who need a continuous monitoring of such physiological parameters. At the same time, the use of fiber optic sensors (FOSs) is gaining large acceptance as an alternative to traditional electrical and mechanical sensors for the monitoring of thermal and mechanical parameters. The potential impact of FOSs is related to their good metrological properties, their small size and their flexibility, as well as to their immunity from electromagnetic field. Their main advantage is the possibility to use textile based on fiber optic in a magnetic resonance imaging environment, where standard electronic sensors cannot be employed. This last feature makes FOSs suitable for monitoring biological parameters (e.g., respiratory and heartbeat monitoring) during magnetic resonance procedures. Research interest in combining FOSs and textiles into a single structure to develop wearable sensors is rapidly growing. In this review we provide an overview of the state-of-the-art of textiles, which use FOSs for monitoring of mechanical parameters of physiological interest. In particular we briefly describe the working principle of FOSs employed in this field and their relevant advantages and disadvantages. Also reviewed are their applications for the monitoring of mechanical parameters of physiological interest. PMID:25871010

Biological parameters used in setting captive-breeding quotas for Indonesia's breeding facilities.

PubMed

Janssen, Jordi; Chng, Serene C L

2018-02-01

The commercial captive breeding of wildlife is often seen as a potential conservation tool to relieve pressure on wild populations, but laundering of wild-sourced specimens as captive bred can seriously undermine conservation efforts and provide a false sense of sustainability. Indonesia is at the center of such controversy; therefore, we examined Indonesia's captive-breeding production plan (CBPP) for 2016. We compared the biological parameters used in the CBPP with parameters in the literature and with parameters suggested by experts on each species and identified shortcomings of the CBPP. Production quotas for 99 out of 129 species were based on inaccurate or unrealistic biological parameters and production quotas deviated more than 10% from what parameters in the literature allow for. For 38 species, the quota exceeded the number of animals that can be bred based on the biological parameters (range 100-540%) calculated with equations in the CBPP. We calculated a lower reproductive output for 88 species based on published biological parameters compared with the parameters used in the CBPP. The equations used in the production plan did not appear to account for other factors (e.g., different survival rate for juveniles compared to adult animals) involved in breeding the proposed large numbers of specimens. We recommend the CBPP be adjusted so that realistic published biological parameters are applied and captive-breeding quotas are not allocated to species if their captive breeding is unlikely to be successful or no breeding stock is available. The shortcomings in the current CBPP create loopholes that mean mammals, reptiles, and amphibians from Indonesia declared captive bred may have been sourced from the wild. © 2017 Society for Conservation Biology.

Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.

PubMed

Dresch, Jacqueline M; Liu, Xiaozhou; Arnosti, David N; Ay, Ahmet

2010-10-24

Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. We apply local and global sensitivity analyses to two recent transcriptional models to determine the sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive, while values for protein cooperativities are not, and provide insights on why these differential sensitivities stem from both biological effects and the structure of the applied models. In a second case, we demonstrate that parameters that were thought to prove the system's dependence on activator-activator cooperativity are relatively insensitive. We show that there are numerous parameter sets that do not satisfy the relationships proferred as the optimal solutions, indicating that structural differences between the two types of transcriptional enhancers analyzed may not be as simple as altered activator cooperativity. Our results emphasize the need for sensitivity analysis to examine model construction and forms of biological data used for modeling transcriptional processes, in order to determine the significance of estimated parameter values for thermodynamic models. Knowledge of parameter sensitivities can provide the necessary context to determine how modeling results should be interpreted in biological systems.

Beyond arousal and valence: the importance of the biological versus social relevance of emotional stimuli.

PubMed

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-03-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention, memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that (1) biologically emotional images hold attention more strongly than do socially emotional images, (2) memory for biologically emotional images was enhanced even with limited cognitive resources, but (3) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images' subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in the visual cortex and greater functional connectivity between the amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in the medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between the amygdala and MPFC than did biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity.

Beyond arousal and valence: The importance of the biological versus social relevance of emotional stimuli

PubMed Central

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-01-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention; memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that: a) biologically emotional images hold attention more strongly than socially emotional images, b) memory for biologically emotional images was enhanced even with limited cognitive resources, but c) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images’ subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in visual cortex and greater functional connectivity between amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between amygdala and MPFC than biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity. PMID:21964552

Surgeon Reported Outcome Measure for Spine Trauma: An International Expert Survey Identifying Parameters Relevant for the Outcome of Subaxial Cervical Spine Injuries.

PubMed

Sadiqi, Said; Verlaan, Jorrit-Jan; Lehr, A Mechteld; Dvorak, Marcel F; Kandziora, Frank; Rajasekaran, S; Schnake, Klaus J; Vaccaro, Alexander R; Oner, F Cumhur

2016-12-15

International web-based survey. To identify clinical and radiological parameters that spine surgeons consider most relevant when evaluating clinical and functional outcomes of subaxial cervical spine trauma patients. Although an outcome instrument that reflects the patients' perspective is imperative, there is also a need for a surgeon reported outcome measure to reflect the clinicians' perspective adequately. A cross-sectional online survey was conducted among a selected number of spine surgeons from all five AOSpine International world regions. They were asked to indicate the relevance of a compilation of 21 parameters, both for the short term (3 mo-2 yr) and long term (≥2 yr), on a five-point scale. The responses were analyzed using descriptive statistics, frequency analysis, and Kruskal-Wallis test. Of the 279 AOSpine International and International Spinal Cord Society members who received the survey, 108 (38.7%) participated in the study. Ten parameters were identified as relevant both for short term and long term by at least 70% of the participants. Neurological status, implant failure within 3 months, and patient satisfaction were most relevant. Bony fusion was the only parameter for the long term, whereas five parameters were identified for the short term. The remaining six parameters were not deemed relevant. Minor differences were observed when analyzing the responses according to each world region, or spine surgeons' degree of experience. The perspective of an international sample of highly experienced spine surgeons was explored on the most relevant parameters to evaluate and predict outcomes of subaxial cervical spine trauma patients. These results form the basis for the development of a disease-specific surgeon reported outcome measure, which will be a helpful tool in research and clinical practice. 4.

Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters

PubMed Central

Liu, Fei; Heiner, Monika; Yang, Ming

2016-01-01

Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information. PMID:26910830

Evolutionary perspectives on learning: conceptual and methodological issues in the study of adaptive specializations.

PubMed

Krause, Mark A

2015-07-01

Inquiry into evolutionary adaptations has flourished since the modern synthesis of evolutionary biology. Comparative methods, genetic techniques, and various experimental and modeling approaches are used to test adaptive hypotheses. In psychology, the concept of adaptation is broadly applied and is central to comparative psychology and cognition. The concept of an adaptive specialization of learning is a proposed account for exceptions to general learning processes, as seen in studies of Pavlovian conditioning of taste aversions, sexual responses, and fear. The evidence generally consists of selective associations forming between biologically relevant conditioned and unconditioned stimuli, with conditioned responses differing in magnitude, persistence, or other measures relative to non-biologically relevant stimuli. Selective associations for biologically relevant stimuli may suggest adaptive specializations of learning, but do not necessarily confirm adaptive hypotheses as conceived of in evolutionary biology. Exceptions to general learning processes do not necessarily default to an adaptive specialization explanation, even if experimental results "make biological sense". This paper examines the degree to which hypotheses of adaptive specializations of learning in sexual and fear response systems have been tested using methodologies developed in evolutionary biology (e.g., comparative methods, quantitative and molecular genetics, survival experiments). A broader aim is to offer perspectives from evolutionary biology for testing adaptive hypotheses in psychological science.

TH-A-BRD-01: Radiation Biology for Radiation Therapy Physicists

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

Orton, C; Borras, C; Carlson, D

Mechanisms by which radiation kills cells and ways cell damage can be repaired will be reviewed. The radiobiological parameters of dose, fractionation, delivery time, dose rate, and LET will be discussed. The linear-quadratic model for cell survival for high and low dose rate treatments and the effect of repopulation will be presented and discussed. The rationale for various radiotherapy techniques such as conventional fractionation, hyperfractionation, hypofractionation, and low and high dose rate brachytherapy, including permanent implants, will be presented. The radiobiological principles underlying radiation protection guidelines and the different radiation dosimetry terms used in radiation biology and in radiation protectionmore » will be reviewed. Human data on radiation induced cancer, including increases in the risk of second cancers following radiation therapy, as well as data on radiation induced tissue reactions, such as cardiovascular effects, for follow up times up to 20–40 years, published by ICRP, NCRP and BEIR Committees, will be examined. The latest risk estimates per unit dose will be presented. Their adoption in recent radiation protection standards and guidelines and their impact on patient and workers safety in radiotherapy will be discussed. Biologically-guided radiotherapy (BGRT) provides a systematic method to derive prescription doses that integrate patient-specific information about tumor and normal tissue biology. Treatment individualization based on patient-specific biology requires the identification of biological objective functions to facilitate the design and comparison of competing treatment modalities. Biological objectives provide a more direct approach to plan optimization instead of relying solely on dose-based surrogates and can incorporate factors that alter radiation response, such as DNA repair, tumor hypoxia, and relative biological effectiveness. We review concepts motivating biological objectives and provide examples of how they might be used to address clinically relevant problems. Underlying assumptions and limitations of existing models and their proper application will be discussed. This multidisciplinary educational session combines the fundamentals of radiobiology for radiation therapy and radiation protection with the practical application of biophysical models for treatment planning and evaluation. Learning Objectives: To understand fractionation in teletherapy and dose rate techniques in brachytherapy. To understand how the linear-quadratic models the effect of radiobiological parameters for radiotherapy. To understand the radiobiological basis of radiation protection standards applied to radiotherapy. To distinguish between stochastic effects and tissue reactions. To learn how to apply concepts of biological effective dose and RBE-weighted dose and to incorporate biological factors that alter radiation response. To discuss clinical strategies to increase therapeutic ratio, i.e., maximize local control while minimizing the risk of acute and late normal tissue effects.« less

Hierarchical cluster-based partial least squares regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models.

PubMed

Tøndel, Kristin; Indahl, Ulf G; Gjuvsland, Arne B; Vik, Jon Olav; Hunter, Peter; Omholt, Stig W; Martens, Harald

2011-06-01

Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. HC-PLSR is a promising approach for metamodelling in systems biology, especially for highly nonlinear or non-monotone parameter to phenotype maps. The algorithm can be flexibly adjusted to suit the complexity of the dynamic model behaviour, inviting automation in the metamodelling of complex systems.

Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models

PubMed Central

2011-01-01

Background Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Results Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. Conclusions HC-PLSR is a promising approach for metamodelling in systems biology, especially for highly nonlinear or non-monotone parameter to phenotype maps. The algorithm can be flexibly adjusted to suit the complexity of the dynamic model behaviour, inviting automation in the metamodelling of complex systems. PMID:21627852

Dose addition models based on biologically-relevant reductions in fetal testosterone accurately predict postnatal reproductive tract alterations by a phthalate mixture in rats

EPA Science Inventory

Challenges in cumulative risk assessment of anti-androgenic phthalate mixtures include a lack of data on all the individual phthalates and difficulty determining the biological relevance of reduction in fetal testosterone (T) on postnatal development. The objectives of the curren...

[Mechanisms and applications of transcutaneous electrical nerve stimulation in analgesia].

PubMed

Tang, Zheng-Yu; Wang, Hui-Quan; Xia, Xiao-Lei; Tang, Yi; Peng, Wei-Wei; Hu, Li

2017-06-25

Transcutaneous electrical nerve stimulation (TENS), as a non-pharmacological and non-invasive analgesic therapy with low-cost, has been widely used to relieve pain in various clinical applications, by delivering current pulses to the skin area to activate the peripheral nerve fibers. Nevertheless, analgesia induced by TENS varied in the clinical practice, which could be caused by the fact that TENS with different stimulus parameters has different biological mechanisms in relieving pain. Therefore, to advance our understanding of TENS in various basic and clinical studies, we discussed (1) neurophysiological and biochemical mechanisms of TENS-induced analgesia; (2) relevant factors that may influence analgesic effects of TENS from the perspectives of stimulus parameters, including stimulated position, pulse parameters (current intensity, frequency, and pulse width), stimulus duration and used times in each day; and (3) applications of TENS in relieving clinical pain, including post-operative pain, chronic low back pain and labor pain. Finally, we propose that TENS may involve multiple and complex psychological neurophysiological mechanisms, and suggest that different analgesic effects of TENS with different stimulus parameters should be taken into consideration in clinical applications. In addition, to optimize analgesic effect, we recommend that individual-based TENS stimulation parameters should be designed by considering individual differences among patients, e.g., adaptively adjusting the stimulation parameters based on the dynamic ratings of patients' pain.

Approximate, computationally efficient online learning in Bayesian spiking neurons.

PubMed

Kuhlmann, Levin; Hauser-Raspe, Michael; Manton, Jonathan H; Grayden, David B; Tapson, Jonathan; van Schaik, André

2014-03-01

Bayesian spiking neurons (BSNs) provide a probabilistic interpretation of how neurons perform inference and learning. Online learning in BSNs typically involves parameter estimation based on maximum-likelihood expectation-maximization (ML-EM) which is computationally slow and limits the potential of studying networks of BSNs. An online learning algorithm, fast learning (FL), is presented that is more computationally efficient than the benchmark ML-EM for a fixed number of time steps as the number of inputs to a BSN increases (e.g., 16.5 times faster run times for 20 inputs). Although ML-EM appears to converge 2.0 to 3.6 times faster than FL, the computational cost of ML-EM means that ML-EM takes longer to simulate to convergence than FL. FL also provides reasonable convergence performance that is robust to initialization of parameter estimates that are far from the true parameter values. However, parameter estimation depends on the range of true parameter values. Nevertheless, for a physiologically meaningful range of parameter values, FL gives very good average estimation accuracy, despite its approximate nature. The FL algorithm therefore provides an efficient tool, complementary to ML-EM, for exploring BSN networks in more detail in order to better understand their biological relevance. Moreover, the simplicity of the FL algorithm means it can be easily implemented in neuromorphic VLSI such that one can take advantage of the energy-efficient spike coding of BSNs.

Demographic inference under the coalescent in a spatial continuum.

PubMed

Guindon, Stéphane; Guo, Hongbin; Welch, David

2016-10-01

Understanding population dynamics from the analysis of molecular and spatial data requires sound statistical modeling. Current approaches assume that populations are naturally partitioned into discrete demes, thereby failing to be relevant in cases where individuals are scattered on a spatial continuum. Other models predict the formation of increasingly tight clusters of individuals in space, which, again, conflicts with biological evidence. Building on recent theoretical work, we introduce a new genealogy-based inference framework that alleviates these issues. This approach effectively implements a stochastic model in which the distribution of individuals is homogeneous and stationary, thereby providing a relevant null model for the fluctuation of genetic diversity in time and space. Importantly, the spatial density of individuals in a population and their range of dispersal during the course of evolution are two parameters that can be inferred separately with this method. The validity of the new inference framework is confirmed with extensive simulations and the analysis of influenza sequences collected over five seasons in the USA. Copyright © 2016 Elsevier Inc. All rights reserved.

Wireless Integrated Biosensors for Point-of-Care Diagnostic Applications

PubMed Central

Ghafar-Zadeh, Ebrahim

2015-01-01

Recent advances in integrated biosensors, wireless communication and power harvesting techniques are enticing researchers into spawning a new breed of point-of-care (POC) diagnostic devices that have attracted significant interest from industry. Among these, it is the ones equipped with wireless capabilities that drew our attention in this review paper. Indeed, wireless POC devices offer a great advantage, that of the possibility of exerting continuous monitoring of biologically relevant parameters, metabolites and other bio-molecules, relevant to the management of various morbid diseases such as diabetes, brain cancer, ischemia, and Alzheimer’s. In this review paper, we examine three major categories of miniaturized integrated devices, namely; the implantable Wireless Bio-Sensors (WBSs), the wearable WBSs and the handheld WBSs. In practice, despite the aforesaid progress made in developing wireless platforms, early detection of health imbalances remains a grand challenge from both the technological and the medical points of view. This paper addresses such challenges and reports the state-of-the-art in this interdisciplinary field. PMID:25648709

Semantic technologies improving the recall and precision of the Mercury metadata search engine

NASA Astrophysics Data System (ADS)

Pouchard, L. C.; Cook, R. B.; Green, J.; Palanisamy, G.; Noy, N.

2011-12-01

The Mercury federated metadata system [1] was developed at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), a NASA-sponsored effort holding datasets about biogeochemical dynamics, ecological data, and environmental processes. Mercury currently indexes over 100,000 records from several data providers conforming to community standards, e.g. EML, FGDC, FGDC Biological Profile, ISO 19115 and DIF. With the breadth of sciences represented in Mercury, the potential exists to address some key interdisciplinary scientific challenges related to climate change, its environmental and ecological impacts, and mitigation of these impacts. However, this wealth of metadata also hinders pinpointing datasets relevant to a particular inquiry. We implemented a semantic solution after concluding that traditional search approaches cannot improve the accuracy of the search results in this domain because: a) unlike everyday queries, scientific queries seek to return specific datasets with numerous parameters that may or may not be exposed to search (Deep Web queries); b) the relevance of a dataset cannot be judged by its popularity, as each scientific inquiry tends to be unique; and c)each domain science has its own terminology, more or less curated, consensual, and standardized depending on the domain. The same terms may refer to different concepts across domains (homonyms), but different terms mean the same thing (synonyms). Interdisciplinary research is arduous because an expert in a domain must become fluent in the language of another, just to find relevant datasets. Thus, we decided to use scientific ontologies because they can provide a context for a free-text search, in a way that string-based keywords never will. With added context, relevant datasets are more easily discoverable. To enable search and programmatic access to ontology entities in Mercury, we are using an instance of the BioPortal ontology repository. Mercury accesses ontology entities using the BioPortal REST API by passing a search parameter to BioPortal that may return domain context, parameter attribute, or entity annotations depending on the entity's associated ontological relationships. As Mercury's facetted search is popular with users, the results are displayed as facets. Unlike a facetted search however, the ontology-based solution implements both restrictions (improving precision) and expansions (improving recall) on the results of the initial search. For instance, "carbon" acquires a scientific context and additional key terms or phrases for discovering domain-specific datasets. A limitation of our solution is that the user must perform an additional step. Another limitation is that the quality of the newly discovered metadata is contingent upon the quality of the ontologies we use. Our solution leverages Mercury's federated capabilities to collect records from heterogeneous domains, and BioPortal's storage, curation and access capabilities for ontology entities. With minimal additional development, our approach builds on two mature systems for finding relevant datasets for interdisciplinary inquiries. We thus indicate a path forward for linking environmental, ecological and biological sciences. References: [1] Devarakonda, R., Palanisamy, G., Wilson, B. E., & Green, J. M. (2010). Mercury: reusable metadata management, data discovery and access system. Earth Science Informatics, 3(1-2), 87-94.

Psycho-biological correlates of free-floating anxiety symptoms in male patients with sexual dysfunctions.

PubMed

Corona, Giovanni; Mannucci, Edoardo; Petrone, Luisa; Ricca, Valdo; Balercia, Giancarlo; Giommi, Roberta; Forti, Gianni; Maggi, Mario

2006-01-01

Anxiety has a relevant impact on everyday life, including sexual life, and therefore is considered the final common pathway by which social, psychological, and biological stressors negatively affect sexual functioning. The aim of this study is to define the psycho-biological correlates of free-floating anxiety in a large sample of patients complaining of erectile dysfunction (ED)-based sexual problems. We studied a consecutive series of 882 ED patients using SIEDY, a 13-item structured interview, composed of 3 scales that identify and quantify organic, relational, and intrapsychic domains. MHQ-A scoring from Middlesex Hospital Questionnaire (MHQ) was used as a putative marker of free-floating anxiety symptoms (AS). Metabolic and hormonal parameters, nocturnal penile tumescence (NPT) test, and penile Doppler ultrasound (PDU) examination were also performed. MHQ-A score was significantly higher in patients complaining of difficulties in maintaining erection and in those reporting premature ejaculation (6.5 +/- 3.3 vs 5.8 +/- 3.3 and 6.6 +/- 3.3 vs 6.1 +/- 3.3, respectively; both P < .05). Moreover, ASs were significantly correlated to life stressors quantified by SIEDY scale 2 (relational component) and scale 3 (intrapsychic component) scores, as dissatisfaction at work or within the family or couple relationships. Among physical, biochemical, or instrumental parameters tested, only end-diastolic velocity at PDU was significantly (P < .05) related to ASs. In conclusion, in patients with ED-based sexual problems, ASs are correlated to many relational and life stressors. Conversely, organic problems are not necessarily associated with MHQ-A score.

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.

Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

2015-07-01

The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

Submicron scale tissue multifractal anisotropy in polarized laser light scattering

NASA Astrophysics Data System (ADS)

Das, Nandan Kumar; Dey, Rajib; Chakraborty, Semanti; Panigrahi, Prasanta K.; Meglinski, Igor; Ghosh, Nirmalya

2018-03-01

The spatial fluctuations of the refractive index within biological tissues exhibit multifractal anisotropy, leaving its signature as a spectral linear diattenuation of scattered polarized light. The multifractal anisotropy has been quantitatively assessed by the processing of relevant Mueller matrix elements in the Fourier domain, utilizing the Born approximation and subsequent multifractal analysis. The differential scaling exponent and width of the singularity spectrum appear to be highly sensitive to the structural multifractal anisotropy at the micron/sub-micron length scales. An immediate practical use of these multifractal anisotropy parameters was explored for non-invasive screening of cervical precancerous alterations ex vivo, with the indication of a strong potential for clinical diagnostic purposes.

The evolution of phase holographic imaging from a research idea to publicly traded company

NASA Astrophysics Data System (ADS)

Egelberg, Peter

2018-02-01

Recognizing the value and unmet need for label-free kinetic cell analysis, Phase Holograhic Imaging defines its market segment as automated, easy to use and affordable time-lapse cytometry. The process of developing new technology, meeting customer expectations, sources of corporate funding and R&D adjustments prompted by field experience will be reviewed. Additionally, it is discussed how relevant biological information can be extracted from a sequence of quantitative phase images, with negligible user assistance and parameter tweaking, to simultaneously provide cell culture characteristics such as cell growth rate, viability, division rate, mitosis duration, phagocytosis rate, migration, motility and cell-cell adherence without requiring any artificial cell manipulation.

Estimating the physicochemical properties of polyhalogenated aromatic and aliphatic compounds using UPPER: part 2. Aqueous solubility, octanol solubility and octanol-water partition coefficient.

PubMed

Admire, Brittany; Lian, Bo; Yalkowsky, Samuel H

2015-01-01

The UPPER (Unified Physicochemical Property Estimation Relationships) model uses additive and non-additive parameters to estimate 20 biologically relevant properties of organic compounds. The model has been validated by Lian and Yalkowsky (2014) on a data set of 700 hydrocarbons. Recently, Admire et al. (2014) expanded the model to predict the boiling and melting points of 1288 polyhalogenated benzenes, biphenyls, dibenzo-p-dioxins, diphenyl ethers, anisoles and alkanes. In this work, 19 new group descriptors are determined and used to predict the aqueous solubilities, octanol solubilities and the octanol-water coefficients. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2011-01-01

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

Non-equilibrium fluctuations of a semi-flexible filament driven by active cross-linkers

NASA Astrophysics Data System (ADS)

Weber, I.; Appert-Rolland, C.; Schehr, G.; Santen, L.

2017-11-01

The cytoskeleton is an inhomogeneous network of semi-flexible filaments, which are involved in a wide variety of active biological processes. Although the cytoskeletal filaments can be very stiff and embedded in a dense and cross-linked network, it has been shown that, in cells, they typically exhibit significant bending on all length scales. In this work we propose a model of a semi-flexible filament deformed by different types of cross-linkers for which one can compute and investigate the bending spectrum. Our model allows to couple the evolution of the deformation of the semi-flexible polymer with the stochastic dynamics of linkers which exert transversal forces onto the filament. We observe a q-2 dependence of the bending spectrum for some biologically relevant parameters and in a certain range of wave numbers q, as observed in some experiments. However, generically, the spatially localized forcing and the non-thermal dynamics both introduce deviations from the thermal-like q-2 spectrum.

The potential for biologically catalyzed anaerobic methane oxidation on ancient Mars.

PubMed

Marlow, Jeffrey J; Larowe, Douglas E; Ehlmann, Bethany L; Amend, Jan P; Orphan, Victoria J

2014-04-01

This study examines the potential for the biologically mediated anaerobic oxidation of methane (AOM) coupled to sulfate reduction on ancient Mars. Seven distinct fluids representative of putative martian groundwater were used to calculate Gibbs energy values in the presence of dissolved methane under a range of atmospheric CO2 partial pressures. In all scenarios, AOM is exergonic, ranging from -31 to -135 kJ/mol CH4. A reaction transport model was constructed to examine how environmentally relevant parameters such as advection velocity, reactant concentrations, and biomass production rate affect the spatial and temporal dependences of AOM reaction rates. Two geologically supported models for ancient martian AOM are presented: a sulfate-rich groundwater with methane produced from serpentinization by-products, and acid-sulfate fluids with methane from basalt alteration. The simulations presented in this study indicate that AOM could have been a feasible metabolism on ancient Mars, and fossil or isotopic evidence of this metabolic pathway may persist beneath the surface and in surface exposures of eroded ancient terrains.

Effect of fortification with parsley (Petroselinum crispum Mill.) leaves on the nutraceutical and nutritional quality of wheat pasta.

PubMed

Sęczyk, Łukasz; Świeca, Michał; Gawlik-Dziki, Urszula; Luty, Marcin; Czyż, Jarosław

2016-01-01

This study examines the nutraceutical (phenolics content, antioxidant activity, biological activity) and nutritional potential (starch and protein digestibility) of wheat pasta supplemented with 1-4% of powdered parsley leaves. Compared to the control, the potentially bioaccessible fraction of pasta fortified with 4% parsley leaves was characterized by 67% increased phenolics content, a 146% higher antiradical ability and 220% additional reducing power. Elevation of these parameters in fortified pasta was accompanied by an augmentation of its antiproliferative effect on carcinoma cells, which confirms their biological relevance. Supplementation of pasta had no significant effect on starch digestibility, while negatively affecting protein digestibility (a reduction by about 20% for pasta with a 4% supplement). Electrophoretic and chromatographic analyses indicated the presence of phenolic interactions with proteins and/or digestive enzymes. Fortification improved the nutraceutical and nutritional potential of the studied pasta; however, the final effect is made by many factors, including phenolics-food matrix interactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions.

PubMed

Tran, Tran T; Kulis, Christina; Long, Steven M; Bryant, Darryn; Adams, Peter; Smythe, Mark L

2010-11-01

Medicinal chemists synthesize arrays of molecules by attaching functional groups to scaffolds. There is evidence suggesting that some scaffolds yield biologically active molecules more than others, these are termed privileged substructures. One role of the scaffold is to present its side-chains for molecular recognition, and biologically relevant scaffolds may present side-chains in biologically relevant geometries or shapes. Since drug discovery is primarily focused on the discovery of compounds that bind to proteinaceous targets, we have been deciphering the scaffold shapes that are used for binding proteins as they reflect biologically relevant shapes. To decipher the scaffold architecture that is important for binding protein surfaces, we have analyzed the scaffold architecture of protein loops, which are defined in this context as continuous four residue segments of a protein chain that are not part of an α-helix or β-strand secondary structure. Loops are an important molecular recognition motif of proteins. We have found that 39 clusters reflect the scaffold architecture of 89% of the 23,331 loops in the dataset, with average intra-cluster and inter-cluster RMSD of 0.47 and 1.91, respectively. These protein loop scaffolds all have distinct shapes. We have used these 39 clusters that reflect the scaffold architecture of protein loops as biological descriptors. This involved generation of a small dataset of scaffold-based peptidomimetics. We found that peptidomimetic scaffolds with reported biological activities matched loop scaffold geometries and those peptidomimetic scaffolds with no reported biologically activities did not. This preliminary evidence suggests that organic scaffolds with tight matches to the preferred loop scaffolds of proteins, implies the likelihood of the scaffold to be biologically relevant.

Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions

NASA Astrophysics Data System (ADS)

Tran, Tran T.; Kulis, Christina; Long, Steven M.; Bryant, Darryn; Adams, Peter; Smythe, Mark L.

2010-11-01

Medicinal chemists synthesize arrays of molecules by attaching functional groups to scaffolds. There is evidence suggesting that some scaffolds yield biologically active molecules more than others, these are termed privileged substructures. One role of the scaffold is to present its side-chains for molecular recognition, and biologically relevant scaffolds may present side-chains in biologically relevant geometries or shapes. Since drug discovery is primarily focused on the discovery of compounds that bind to proteinaceous targets, we have been deciphering the scaffold shapes that are used for binding proteins as they reflect biologically relevant shapes. To decipher the scaffold architecture that is important for binding protein surfaces, we have analyzed the scaffold architecture of protein loops, which are defined in this context as continuous four residue segments of a protein chain that are not part of an α-helix or β-strand secondary structure. Loops are an important molecular recognition motif of proteins. We have found that 39 clusters reflect the scaffold architecture of 89% of the 23,331 loops in the dataset, with average intra-cluster and inter-cluster RMSD of 0.47 and 1.91, respectively. These protein loop scaffolds all have distinct shapes. We have used these 39 clusters that reflect the scaffold architecture of protein loops as biological descriptors. This involved generation of a small dataset of scaffold-based peptidomimetics. We found that peptidomimetic scaffolds with reported biological activities matched loop scaffold geometries and those peptidomimetic scaffolds with no reported biologically activities did not. This preliminary evidence suggests that organic scaffolds with tight matches to the preferred loop scaffolds of proteins, implies the likelihood of the scaffold to be biologically relevant.

[The enigma of the biological interpretation of the linear-quadratic model finally resolved? A summary for non-mathematicians].

PubMed

Bodgi, L; Canet, A; Granzotto, A; Britel, M; Puisieux, A; Bourguignon, M; Foray, N

2016-06-01

The linear-quadratic (LQ) model is the only mathematical formula linking cellular survival and radiation dose that is sufficiently consensual to help radiation oncologists and radiobiologists in describing the radiation-induced events. However, this formula proposed in the 1970s and α and β parameters on which it is based remained without relevant biological meaning. From a collection of cutaneous fibroblasts with different radiosensitivity, built over 12 years by more than 50 French radiation oncologists, we recently pointed out that the ATM protein, major actor of the radiation response, diffuses from the cytoplasm to the nucleus after irradiation. The evidence of this nuclear shuttling of ATM allowed us to provide a biological interpretation of the LQ model in its mathematical features, validated by a hundred of radiosensitive cases. A mechanistic explanation of the radiosensitivity of syndromes caused by the mutation of cytoplasmic proteins and of the hypersensitivity to low-dose phenomenon has been proposed, as well. In this review, we present our resolution of the LQ model in the most didactic way. Copyright © 2016 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Application of Biologically Based Lumping To Investigate the Toxicokinetic Interactions of a Complex Gasoline Mixture.

PubMed

Jasper, Micah N; Martin, Sheppard A; Oshiro, Wendy M; Ford, Jermaine; Bushnell, Philip J; El-Masri, Hisham

2016-03-15

People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate the performance of our PBPK model and chemical lumping method. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course toxicokinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 nontarget chemicals. The same biologically based lumping approach can be used to simplify any complex mixture with tens, hundreds, or thousands of constituents.

Fitness costs associated with field-evolved resistance to Bt maize in Spodoptera frugiperda (Lepidoptera: Noctuidae).

PubMed

Jakka, S R K; Knight, V R; Jurat-Fuentes, J L

2014-02-01

Increasing adoption of transgenic crops expressing cry toxin genes from Bacillus thuringiensis (Bt crops) represents an augmented risk for development of insect resistance. While fitness costs can greatly influence the rate of resistance evolution, most available data related to Bt resistance have been obtained from laboratory-selected insect strains. In this article, we test the existence of fitness costs associated with high levels of field-evolved resistance to Bt maize event TC1507 in a strain of Spodoptera frugiperda (JE Smith) originated from maize fields in Puerto Rico. Fitness costs in resistant S. frugiperda were evaluated by comparing biological performance to susceptible insects when reared on meridic diet, maize or soybean leaf tissue, or cotton reproductive tissues. Parameters monitored included larval survival, larval and pupal weights, developmental time (larval and pupal), adult longevity, reproductive traits (fecundity and fertility), and sex ratio. We found that all monitored parameters were influenced to a similar extent by the host, independently of susceptibility to Bt maize. The only parameter that significantly differed between strains for all hosts was a longer larval developmental period in resistant S. frugiperda, which resulted in emergence asynchrony between susceptible and resistant adults. To test the relevance of fitness costs in resistant S. frugiperda, we performed a selection experiment to monitor the stability of resistance in a heterogeneous strain through 12 generations of rearing on meridic diet. Our data demonstrate lack of fitness costs relevant to stability of field-evolved resistance to Bt maize and help explain reported stability of field-evolved resistance in Puerto Rican populations of S. frugiperda.

Structure and Dynamics of Type III Secretion Effector Protein ExoU As determined by SDSL-EPR Spectroscopy in Conjunction with De Novo Protein Folding

PubMed Central

2017-01-01

ExoU is a 74 kDa cytotoxin that undergoes substantial conformational changes as part of its function, that is, it has multiple thermodynamically stable conformations that interchange depending on its environment. Such flexible proteins pose unique challenges to structural biology: (1) not only is it often difficult to determine structures by X-ray crystallography for all biologically relevant conformations because of the flat energy landscape (2) but also experimental conditions can easily perturb the biologically relevant conformation. The first challenge can be overcome by applying orthogonal structural biology techniques that are capable of observing alternative, biologically relevant conformations. The second challenge can be addressed by determining the structure in the same biological state with two independent techniques under different experimental conditions. If both techniques converge to the same structural model, the confidence that an unperturbed biologically relevant conformation is observed increases. To this end, we determine the structure of the C-terminal domain of the effector protein, ExoU, from data obtained by electron paramagnetic resonance spectroscopy in conjunction with site-directed spin labeling and in silico de novo structure determination. Our protocol encompasses a multimodule approach, consisting of low-resolution topology sampling, clustering, and high-resolution refinement. The resulting model was compared with an ExoU model in complex with its chaperone SpcU obtained previously by X-ray crystallography. The two models converged to a minimal RMSD100 of 3.2 Å, providing evidence that the unbound structure of ExoU matches the fold observed in complex with SpcU. PMID:28691114

Rapid Parallel Screening for Strain Optimization

DTIC Science & Technology

2013-08-16

fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can...reporter, and, 2) a yeast TAR cloning shuttle vector for transferring catabolic clusters to E. coli. 15. SUBJECT TERMS NA 16. SECURITY CLASSIFICATION OF... fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can utilize

Rapid Parallel Screening for Strain Optimization

DTIC Science & Technology

2013-05-16

fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can...reporter, and, 2) a yeast TAR cloning shuttle vector for transferring catabolic clusters to E. coli. 15. SUBJECT TERMS NA 16. SECURITY CLASSIFICATION OF... fermentation yields of industrially relevant biological compounds. Screening of the desired chemicals was completed previously. Microbes that can utilize

Comparative Evaluation of Two Serial Gene Expression Experiments | Division of Cancer Prevention

Cancer.gov

Stuart G. Baker, 2014 Introduction This program fits biologically relevant response curves in comparative analysis of the two gene expression experiments involving same genes but under different scenarios and at least 12 responses. The program outputs gene pairs with biologically relevant response curve shapes including flat, linear, sigmoid, hockey stick, impulse and step

Optimal experimental design for parameter estimation of a cell signaling model.

PubMed

Bandara, Samuel; Schlöder, Johannes P; Eils, Roland; Bock, Hans Georg; Meyer, Tobias

2009-11-01

Differential equation models that describe the dynamic changes of biochemical signaling states are important tools to understand cellular behavior. An essential task in building such representations is to infer the affinities, rate constants, and other parameters of a model from actual measurement data. However, intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values. Here we utilized a numerical method to iteratively design optimal live-cell fluorescence microscopy experiments in order to reveal pharmacological and kinetic parameters of a phosphatidylinositol 3,4,5-trisphosphate (PIP(3)) second messenger signaling process that is deregulated in many tumors. The experimental approach included the activation of endogenous phosphoinositide 3-kinase (PI3K) by chemically induced recruitment of a regulatory peptide, reversible inhibition of PI3K using a kinase inhibitor, and monitoring of the PI3K-mediated production of PIP(3) lipids using the pleckstrin homology (PH) domain of Akt. We found that an intuitively planned and established experimental protocol did not yield data from which relevant parameters could be inferred. Starting from a set of poorly defined model parameters derived from the intuitively planned experiment, we calculated concentration-time profiles for both the inducing and the inhibitory compound that would minimize the predicted uncertainty of parameter estimates. Two cycles of optimization and experimentation were sufficient to narrowly confine the model parameters, with the mean variance of estimates dropping more than sixty-fold. Thus, optimal experimental design proved to be a powerful strategy to minimize the number of experiments needed to infer biological parameters from a cell signaling assay.

SBML-PET: a Systems Biology Markup Language-based parameter estimation tool.

PubMed

Zi, Zhike; Klipp, Edda

2006-11-01

The estimation of model parameters from experimental data remains a bottleneck for a major breakthrough in systems biology. We present a Systems Biology Markup Language (SBML) based Parameter Estimation Tool (SBML-PET). The tool is designed to enable parameter estimation for biological models including signaling pathways, gene regulation networks and metabolic pathways. SBML-PET supports import and export of the models in the SBML format. It can estimate the parameters by fitting a variety of experimental data from different experimental conditions. SBML-PET has a unique feature of supporting event definition in the SMBL model. SBML models can also be simulated in SBML-PET. Stochastic Ranking Evolution Strategy (SRES) is incorporated in SBML-PET for parameter estimation jobs. A classic ODE Solver called ODEPACK is used to solve the Ordinary Differential Equation (ODE) system. http://sysbio.molgen.mpg.de/SBML-PET/. The website also contains detailed documentation for SBML-PET.

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

Carlson, D.

The physical pattern of energy deposition and the enhanced relative biological effectiveness (RBE) of protons and carbon ions compared to photons offer unique and not fully understood or exploited opportunities to improve the efficacy of radiation therapy. Variations in RBE within a pristine or spread out Bragg peak and between particle types may be exploited to enhance cell killing in target regions without a corresponding increase in damage to normal tissue structures. In addition, the decreased sensitivity of hypoxic tumors to photon-based therapies may be partially overcome through the use of more densely ionizing radiations. These and other differences betweenmore » particle and photon beams may be used to generate biologically optimized treatments that reduce normal tissue complications. In this symposium, speakers will examine the impact of the RBE of charged particles on measurable biological endpoints, treatment plan optimization, and the prediction or retrospective assessment of treatment outcomes. In particular, an AAPM task group was formed to critically examine the evidence for a spatially-variant RBE in proton therapy. Current knowledge of proton RBE variation with respect to dose, biological endpoint, and physics parameters will be reviewed. Further, the clinical relevance of these variations will be discussed. Recent work focused on improving simulations of radiation physics and biological response in proton and carbon ion therapy will also be presented. Finally, relevant biology research and areas of research needs will be highlighted, including the dependence of RBE on genetic factors including status of DNA repair pathways, the sensitivity of cancer stem-like cells to charged particles, the role of charged particles in hypoxic tumors, and the importance of fractionation effects. In addition to the physical advantages of protons and more massive ions over photons, the future application of biologically optimized treatment plans and their potential to provide higher levels of local tumor control and improved normal tissue sparing will be discussed. Learning Objectives: To assess whether the current practice of a constant RBE of 1.1 should be revised or maintained in proton therapy and to evaluate the potential clinical consequences of delivering RBE-weighted dose distributions based on variable RBE To review current research on biological models used to predict the increased biological effectiveness of proton and carbon ions to help move towards a practical understanding and implementation of biological optimization in particle therapy To discuss potential differences in biological mechanisms between photons and charged particles (light and heavy ions) that could impact clinical cancer therapy H. Paganetti, NCI U19 CA21239D. Grosshans, Our research is supported by the NCIK. Held, Funding Support: National Cancer Institute of the National Institutes of Health, USA, under Award Number R21CA182259 and Federal Share of Program Income Earned by Massachusetts General Hospital on C06CA059267, Proton Therapy Research and Treatment Center.« less

A sensitivity analysis of process design parameters, commodity prices and robustness on the economics of odour abatement technologies.

PubMed

Estrada, José M; Kraakman, N J R Bart; Lebrero, Raquel; Muñoz, Raúl

2012-01-01

The sensitivity of the economics of the five most commonly applied odour abatement technologies (biofiltration, biotrickling filtration, activated carbon adsorption, chemical scrubbing and a hybrid technology consisting of a biotrickling filter coupled with carbon adsorption) towards design parameters and commodity prices was evaluated. Besides, the influence of the geographical location on the Net Present Value calculated for a 20 years lifespan (NPV20) of each technology and its robustness towards typical process fluctuations and operational upsets were also assessed. This comparative analysis showed that biological techniques present lower operating costs (up to 6 times) and lower sensitivity than their physical/chemical counterparts, with the packing material being the key parameter affecting their operating costs (40-50% of the total operating costs). The use of recycled or partially treated water (e.g. secondary effluent in wastewater treatment plants) offers an opportunity to significantly reduce costs in biological techniques. Physical/chemical technologies present a high sensitivity towards H2S concentration, which is an important drawback due to the fluctuating nature of malodorous emissions. The geographical analysis evidenced high NPV20 variations around the world for all the technologies evaluated, but despite the differences in wage and price levels, biofiltration and biotrickling filtration are always the most cost-efficient alternatives (NPV20). When, in an economical evaluation, the robustness is as relevant as the overall costs (NPV20), the hybrid technology would move up next to BTF as the most preferred technologies. Copyright © 2012 Elsevier Inc. All rights reserved.

CellBase, a comprehensive collection of RESTful web services for retrieving relevant biological information from heterogeneous sources.

PubMed

Bleda, Marta; Tarraga, Joaquin; de Maria, Alejandro; Salavert, Francisco; Garcia-Alonso, Luz; Celma, Matilde; Martin, Ainoha; Dopazo, Joaquin; Medina, Ignacio

2012-07-01

During the past years, the advances in high-throughput technologies have produced an unprecedented growth in the number and size of repositories and databases storing relevant biological data. Today, there is more biological information than ever but, unfortunately, the current status of many of these repositories is far from being optimal. Some of the most common problems are that the information is spread out in many small databases; frequently there are different standards among repositories and some databases are no longer supported or they contain too specific and unconnected information. In addition, data size is increasingly becoming an obstacle when accessing or storing biological data. All these issues make very difficult to extract and integrate information from different sources, to analyze experiments or to access and query this information in a programmatic way. CellBase provides a solution to the growing necessity of integration by easing the access to biological data. CellBase implements a set of RESTful web services that query a centralized database containing the most relevant biological data sources. The database is hosted in our servers and is regularly updated. CellBase documentation can be found at http://docs.bioinfo.cipf.es/projects/cellbase.

Sociability modifies dogs' sensitivity to biological motion of different social relevance.

PubMed

Ishikawa, Yuko; Mills, Daniel; Willmott, Alexander; Mullineaux, David; Guo, Kun

2018-03-01

Preferential attention to living creatures is believed to be an intrinsic capacity of the visual system of several species, with perception of biological motion often studied and, in humans, it correlates with social cognitive performance. Although domestic dogs are exceptionally attentive to human social cues, it is unknown whether their sociability is associated with sensitivity to conspecific and heterospecific biological motion cues of different social relevance. We recorded video clips of point-light displays depicting a human or dog walking in either frontal or lateral view. In a preferential looking paradigm, dogs spontaneously viewed 16 paired point-light displays showing combinations of normal/inverted (control condition), human/dog and frontal/lateral views. Overall, dogs looked significantly longer at frontal human point-light display versus the inverted control, probably due to its clearer social/biological relevance. Dogs' sociability, assessed through owner-completed questionnaires, further revealed that low-sociability dogs preferred the lateral point-light display view, whereas high-sociability dogs preferred the frontal view. Clearly, dogs can recognize biological motion, but their preference is influenced by their sociability and the stimulus salience, implying biological motion perception may reflect aspects of dogs' social cognition.

Modelling the host-pathogen interactions of macrophages and Candida albicans using Game Theory and dynamic optimization.

PubMed

Dühring, Sybille; Ewald, Jan; Germerodt, Sebastian; Kaleta, Christoph; Dandekar, Thomas; Schuster, Stefan

2017-07-01

The release of fungal cells following macrophage phagocytosis, called non-lytic expulsion, is reported for several fungal pathogens. On one hand, non-lytic expulsion may benefit the fungus in escaping the microbicidal environment of the phagosome. On the other hand, the macrophage could profit in terms of avoiding its own lysis and being able to undergo proliferation. To analyse the causes of non-lytic expulsion and the relevance of macrophage proliferation in the macrophage- Candida albicans interaction, we employ Evolutionary Game Theory and dynamic optimization in a sequential manner. We establish a game-theoretical model describing the different strategies of the two players after phagocytosis. Depending on the parameter values, we find four different Nash equilibria and determine the influence of the systems state of the host upon the game. As our Nash equilibria are a direct consequence of the model parameterization, we can depict several biological scenarios. A parameter region, where the host response is robust against the fungal infection, is determined. We further apply dynamic optimization to analyse whether macrophage mitosis is relevant in the host-pathogen interaction of macrophages and C. albicans For this, we study the population dynamics of the macrophage- C. albicans interactions and the corresponding optimal controls for the macrophages, indicating the best macrophage strategy of switching from proliferation to attacking fungal cells. © 2017 The Author(s).

An analysis of neural receptive field plasticity by point process adaptive filtering

PubMed Central

Brown, Emery N.; Nguyen, David P.; Frank, Loren M.; Wilson, Matthew A.; Solo, Victor

2001-01-01

Neural receptive fields are plastic: with experience, neurons in many brain regions change their spiking responses to relevant stimuli. Analysis of receptive field plasticity from experimental measurements is crucial for understanding how neural systems adapt their representations of relevant biological information. Current analysis methods using histogram estimates of spike rate functions in nonoverlapping temporal windows do not track the evolution of receptive field plasticity on a fine time scale. Adaptive signal processing is an established engineering paradigm for estimating time-varying system parameters from experimental measurements. We present an adaptive filter algorithm for tracking neural receptive field plasticity based on point process models of spike train activity. We derive an instantaneous steepest descent algorithm by using as the criterion function the instantaneous log likelihood of a point process spike train model. We apply the point process adaptive filter algorithm in a study of spatial (place) receptive field properties of simulated and actual spike train data from rat CA1 hippocampal neurons. A stability analysis of the algorithm is sketched in the Appendix. The adaptive algorithm can update the place field parameter estimates on a millisecond time scale. It reliably tracked the migration, changes in scale, and changes in maximum firing rate characteristic of hippocampal place fields in a rat running on a linear track. Point process adaptive filtering offers an analytic method for studying the dynamics of neural receptive fields. PMID:11593043

Methodological problems and amendments to demonstrate effects of temperature on the epidemiology of malaria. A new perspective on the highland epidemics in Madagascar, 1972-89.

PubMed

Bouma, Menno Jan

2003-01-01

There is a growing consensus that changes in climate will have major consequences for human health through a reduction in the availability of food and an increasing frequency of natural disasters. However, the contribution of higher temperatures to vector-borne diseases, particularly malaria, remains controversial despite the known biological dependence of both vector and pathogen on climate. Misconceptions and inappropriate use of variables and methods have contributed to the controversy. At present there appears to be more support for non-climatic explanations to account for the resurgence of malaria in the African highlands, e.g. the deterioration of malaria control and the development of drug resistance. An attempt is made here to show that dismissing temperature as a driving force in the case of malaria is premature. Using a de-trended time-series of malaria incidence in Madagascar between 1972 and 1989 indicated that a minimum temperature during 2 months at the start of the transmission season can account for most of the variability between years (r2 = 0.66). These months correspond with the months when the human-vector (Anopheles gambiae sensu lato) contact is greatest. The relationship between El Niño Southern Oscillation (ENSO) and temperature (r = 0.79), and ENSO and malaria (r = 0.64), suggests that there might be an increased epidemic risk during post-Niño years in the Madagascar highlands and therefore warrants increased vigilance and extended control efforts in the first half of 2003. This review suggests that the rejection of climate-disease associations in studies so far published may not have used biologically relevant climate parameters. It highlights the importance of identifying more relevant parameters during critical periods of the transmission season in order to aid epidemic forecasting and to assess the potential impact of global warming.

The Microbe-Free Plant: Fact or Artifact?

PubMed Central

Partida-Martínez, Laila P.; Heil, Martin

2011-01-01

Plant–microbe interactions are ubiquitous. Plants are threatened by pathogens, but they are even more commonly engaged in neutral or mutualistic interactions with microbes: belowground microbial plant associates are mycorrhizal fungi, Rhizobia, and plant-growth promoting rhizosphere bacteria, aboveground plant parts are colonized by internally living bacteria and fungi (endophytes) and by microbes in the phyllosphere (epiphytes). We emphasize here that a completely microbe-free plant is an exotic exception rather than the biologically relevant rule. The complex interplay of such microbial communities with the host–plant affects multiple vital parameters such as plant nutrition, growth rate, resistance to biotic and abiotic stressors, and plant survival and distribution. The mechanisms involved reach from direct ones such as nutrient acquisition, the production of plant hormones, or direct antibiosis, to indirect ones that are mediated by effects on host resistance genes or via interactions at higher trophic levels. Plant-associated microbes are heterotrophic and cause costs to their host plant, whereas the benefits depend on the current environment. Thus, the outcome of the interaction for the plant host is highly context dependent. We argue that considering the microbe-free plant as the “normal” or control stage significantly impairs research into important phenomena such as (1) phenotypic and epigenetic plasticity, (2) the “normal” ecological outcome of a given interaction, and (3) the evolution of plants. For the future, we suggest cultivation-independent screening methods using direct PCR from plant tissue of more than one fungal and bacterial gene to collect data on the true microbial diversity in wild plants. The patterns found could be correlated to host species and environmental conditions, in order to formulate testable hypotheses on the biological roles of plant endophytes in nature. Experimental approaches should compare different host–endophyte combinations under various relevant environmental conditions and study at the genetic, epigenetic, transcriptional, and physiological level the parameters that cause the interaction to shift along the mutualism–parasitism continuum. PMID:22639622

Biological Relevance of Key Events (KE) in utero in The Androgen Adverse Outcome Pathway Network (AOPn) to Adverse Effects in F1 Male Rats

EPA Science Inventory

We are conducting studies to evaluate the biological relevance of changes in KEs and molecular initiating events (MIE) in AOPs to determine if these can accurately predict of the dose levels of chemicals that disrupt the androgen signaling pathway in utero. Herein, we focus on ch...

Interactive Effects of Working Memory Self-Regulatory Ability and Relevance Instructions on Text Processing

ERIC Educational Resources Information Center

Hamilton, Nancy Jo

2012-01-01

Reading is a process that requires the enactment of many cognitive processes. Each of these processes uses a certain amount of working memory resources, which are severely constrained by biology. More efficiency in the function of working memory may mediate the biological limits of same. Reading relevancy instructions may be one such method to…

Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, Wiesław; Wrzesien, Mariusz; Niemiec, Rafał; Rudnicki, Witold R.

2016-03-01

Climate models are extremely complex pieces of software. They reflect the best knowledge on the physical components of the climate; nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a simulation crashing. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to the simulation crashing and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the data set used in this research using different methodology. We confirm the main conclusion of the original study concerning the suitability of machine learning for the prediction of crashes. We show that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three others are relevant but redundant and two are not relevant at all. We also show that the variance due to the split of data between training and validation sets has a large influence both on the accuracy of predictions and on the relative importance of variables; hence only a cross-validated approach can deliver a robust prediction of performance and relevance of variables.

II. Species sensitivity distributions based on biomarkers and whole organism responses for integrated impact and risk assessment criteria.

PubMed

Sanni, Steinar; Lyng, Emily; Pampanin, Daniela M; Smit, Mathijs G D

2017-06-01

The aim of this paper is to bridge gaps between biomarker and whole organism responses related to oil based offshore discharges. These biomarker bridges will facilitate acceptance criteria for biomarker data linked to environmental risk assessment and translate biomarker results to higher order effects. Biomarker based species sensitivity distributions (SSD biomarkers ) have been constructed for relevant groups of biomarkers based on laboratory data from oil exposures. SSD curves express the fraction of species responding to different types of biomarkers. They have been connected to SSDs for whole organism responses (WORs) constructed in order to relate the SSD biomarkers to animal fitness parameters that are commonly used in environmental risk assessment. The resulting SSD curves show that biomarkers and WORs can be linked through their potentially affected fraction of species (PAF) distributions, enhancing the capability to monitor field parameters with better correlation to impact and risk assessment criteria and providing improved chemical/biological integration. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improved Atomistic Monte Carlo Simulations Demonstrate that Poly-L-Proline Adopts Heterogeneous Ensembles of Conformations of Semi-Rigid Segments Interrupted by Kinks

PubMed Central

Radhakrishnan, Aditya; Vitalis, Andreas; Mao, Albert H.; Steffen, Adam T.; Pappu, Rohit V.

2012-01-01

Poly-L-proline (PLP) polymers are useful mimics of biologically relevant proline-rich sequences. Biophysical and computational studies of PLP polymers in aqueous solutions are challenging because of the diversity of length scales and the slow time scales for conformational conversions. We describe an atomistic simulation approach that combines an improved ABSINTH implicit solvation model, with conformational sampling based on standard and novel Metropolis Monte Carlo moves. Refinements to forcefield parameters were guided by published experimental data for proline-rich systems. We assessed the validity of our simulation results through quantitative comparisons to experimental data that were not used in refining the forcefield parameters. Our analysis shows that PLP polymers form heterogeneous ensembles of conformations characterized by semi-rigid, rod-like segments interrupted by kinks, which result from a combination of internal cis peptide bonds, flexible backbone ψ-angles, and the coupling between ring puckering and backbone degrees of freedom. PMID:22329658

Altitude training causes haematological fluctuations with relevance for the Athlete Biological Passport.

PubMed

Bonne, Thomas Christian; Lundby, Carsten; Lundby, Anne Kristine; Sander, Mikael; Bejder, Jacob; Nordsborg, Nikolai Baastrup

2015-08-01

The impact of altitude training on haematological parameters and the Athlete Biological Passport (ABP) was evaluated in international-level elite athletes. One group of swimmers lived high and trained high (LHTH, n = 10) for three to four weeks at 2130 m or higher whereas a control group (n = 10) completed a three-week training camp at sea-level. Haematological parameters were determined weekly three times before and four times after the training camps. ABP thresholds for haemoglobin concentration ([Hb]), reticulocyte percentage (RET%), OFF score and the abnormal blood profile score (ABPS) were calculated using the Bayesian model. After altitude training, six swimmers exceeded the 99% ABP thresholds: two swimmers exceeded the OFF score thresholds at day +7; one swimmer exceeded the OFF score threshold at day +28; one swimmer exceeded the threshold for RET% at day +14; and one swimmer surpassed the ABPS threshold at day +14. In the control group, no values exceeded the individual ABP reference range. In conclusion, LHTH induces haematological changes in Olympic-level elite athletes which can exceed the individually generated references in the ABP. Training at altitude should be considered a confounding factor for ABP interpretation for up to four weeks after altitude exposure but does not consistently cause abnormal values in the ABP. Copyright © 2014 John Wiley & Sons, Ltd.

A survey of the year 2007 literature on applications of isothermal titration calorimetry.

PubMed

Bjelić, Sasa; Jelesarov, Ilian

2008-01-01

Elucidation of the energetic principles of binding affinity and specificity is a central task in many branches of current sciences: biology, medicine, pharmacology, chemistry, material sciences, etc. In biomedical research, integral approaches combining structural information with in-solution biophysical data have proved to be a powerful way toward understanding the physical basis of vital cellular phenomena. Isothermal titration calorimetry (ITC) is a valuable experimental tool facilitating quantification of the thermodynamic parameters that characterize recognition processes involving biomacromolecules. The method provides access to all relevant thermodynamic information by performing a few experiments. In particular, ITC experiments allow to by-pass tedious and (rarely precise) procedures aimed at determining the changes in enthalpy and entropy upon binding by van't Hoff analysis. Notwithstanding limitations, ITC has now the reputation of being the "gold standard" and ITC data are widely used to validate theoretical predictions of thermodynamic parameters, as well as to benchmark the results of novel binding assays. In this paper, we discuss several publications from 2007 reporting ITC results. The focus is on applications in biologically oriented fields. We do not intend a comprehensive coverage of all newly accumulated information. Rather, we emphasize work which has captured our attention with originality and far-reaching analysis, or else has provided ideas for expanding the potential of the method. Copyright (c) 2008 John Wiley & Sons, Ltd.

Physically based model for extracting dual permeability parameters using non-Newtonian fluids

NASA Astrophysics Data System (ADS)

Abou Najm, M. R.; Basset, C.; Stewart, R. D.; Hauswirth, S.

2017-12-01

Dual permeability models are effective for the assessment of flow and transport in structured soils with two dominant structures. The major challenge to those models remains in the ability to determine appropriate and unique parameters through affordable, simple, and non-destructive methods. This study investigates the use of water and a non-Newtonian fluid in saturated flow experiments to derive physically-based parameters required for improved flow predictions using dual permeability models. We assess the ability of these two fluids to accurately estimate the representative pore sizes in dual-domain soils, by determining the effective pore sizes of macropores and micropores. We developed two sub-models that solve for the effective macropore size assuming either cylindrical (e.g., biological pores) or planar (e.g., shrinkage cracks and fissures) pore geometries, with the micropores assumed to be represented by a single effective radius. Furthermore, the model solves for the percent contribution to flow (wi) corresponding to the representative macro and micro pores. A user-friendly solver was developed to numerically solve the system of equations, given that relevant non-Newtonian viscosity models lack forms conducive to analytical integration. The proposed dual-permeability model is a unique attempt to derive physically based parameters capable of measuring dual hydraulic conductivities, and therefore may be useful in reducing parameter uncertainty and improving hydrologic model predictions.

Stability of haematological parameters and its relevance on the athlete's biological passport model.

PubMed

Lombardi, Giovanni; Lanteri, Patrizia; Colombini, Alessandra; Lippi, Giuseppe; Banfi, Giuseppe

2011-12-01

The stability of haematological parameters is crucial to guarantee accurate and reliable data for implementing and interpreting the athlete's biological passport (ABP). In this model, the values of haemoglobin, reticulocytes and out-of-doping period (OFF)-score (Hb-60√Ret) are used to monitor the possible variations of those parameters, and also to compare the thresholds developed by the statistical model for the single athlete on the basis of its personal values and the variance of parameters in the modal group. Nevertheless, a critical review of the current scientific literature dealing with the stability of the haematological parameters included in the ABP programme, and which are used for evaluating the probability of anomalies in the athlete's profile, is currently lacking. In addition, we collected information from published studies, in order to supply a useful, practical and updated review to sports physicians and haematologists. There are some parameters that are highly stable, such as haemoglobin and erythrocytes (red blood cells [RBCs]), whereas others, (e.g. reticulocytes, mean RBC volume and haematocrit) appear less stable. Regardless of the methodology, the stability of haematological parameters is improved by sample refrigeration. The stability of all parameters is highly affected from high storage temperatures, whereas the stability of RBCs and haematocrit is affected by initial freezing followed by refrigeration. Transport and rotation of tubes do not substantially influence any haematological parameter except for reticulocytes. In all the studies we reviewed that used Sysmex instrumentation, which is recommended for ABP measurements, stability was shown for 72 hours at 4 ° C for haemoglobin, RBCs and mean curpuscular haemoglobin concentration (MCHC); up to 48 hours for reticulocytes; and up to 24 hours for haematocrit. In one study, Sysmex instrumentation shows stability extended up to 72 hours at 4 ° C for all the parameters. There are significant differences among methods and instruments: Siemens Advia shows lower stability than Sysmex as regards to reticulocytes. However, the limit of 36 hours from blood collection to analysis as recommended by ABP scientists is reasonable to guarantee analytical quality, when samples are transported at 4 ° C and are accompanied by a certified steadiness of this temperature. There are some parameters that are highly stable, such as haemoglobin and RBCs; whereas others, such as reticulocytes, mean cell volume and haematocrit are more unstable. The stability of haematological parameters might be improved independently from the analytical methodology, by refrigeration of the specimens.

Design and validation of an ontology-driven animal-free testing strategy for developmental neurotoxicity testing.

PubMed

Hessel, Ellen V S; Staal, Yvonne C M; Piersma, Aldert H

2018-03-13

Developmental neurotoxicity entails one of the most complex areas in toxicology. Animal studies provide only limited information as to human relevance. A multitude of alternative models have been developed over the years, providing insights into mechanisms of action. We give an overview of fundamental processes in neural tube formation, brain development and neural specification, aiming at illustrating complexity rather than comprehensiveness. We also give a flavor of the wealth of alternative methods in this area. Given the impressive progress in mechanistic knowledge of human biology and toxicology, the time is right for a conceptual approach for designing testing strategies that cover the integral mechanistic landscape of developmental neurotoxicity. The ontology approach provides a framework for defining this landscape, upon which an integral in silico model for predicting toxicity can be built. It subsequently directs the selection of in vitro assays for rate-limiting events in the biological network, to feed parameter tuning in the model, leading to prediction of the toxicological outcome. Validation of such models requires primary attention to coverage of the biological domain, rather than classical predictive value of individual tests. Proofs of concept for such an approach are already available. The challenge is in mining modern biology, toxicology and chemical information to feed intelligent designs, which will define testing strategies for neurodevelopmental toxicity testing. Copyright © 2018 Elsevier Inc. All rights reserved.

The Biology of Cancer Health Disparities

Cancer.gov

These examples show how biology contributes to health disparities (differences in disease incidence and outcomes among distinct racial and ethnic groups, ), and how biological factors interact with other relevant factors, such as diet and the environment.

Electroencephalographic neurofeedback: Level of evidence in mental and brain disorders and suggestions for good clinical practice.

PubMed

Micoulaud-Franchi, J-A; McGonigal, A; Lopez, R; Daudet, C; Kotwas, I; Bartolomei, F

2015-12-01

The technique of electroencephalographic neurofeedback (EEG NF) emerged in the 1970s and is a technique that measures a subject's EEG signal, processes it in real time, extracts a parameter of interest and presents this information in visual or auditory form. The goal is to effectuate a behavioural modification by modulating brain activity. The EEG NF opens new therapeutic possibilities in the fields of psychiatry and neurology. However, the development of EEG NF in clinical practice requires (i) a good level of evidence of therapeutic efficacy of this technique, (ii) a good practice guide for this technique. Firstly, this article investigates selected trials with the following criteria: study design with controlled, randomized, and open or blind protocol, primary endpoint related to the mental and brain disorders treated and assessed with standardized measurement tools, identifiable EEG neurophysiological targets, underpinned by pathophysiological relevance. Trials were found for: epilepsies, migraine, stroke, chronic insomnia, attentional-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, major depressive disorder, anxiety disorders, addictive disorders, psychotic disorders. Secondly, this article investigates the principles of neurofeedback therapy in line with learning theory. Different underlying therapeutic models are presented didactically between two continua: a continuum between implicit and explicit learning and a continuum between the biomedical model (centred on "the disease") and integrative biopsychosocial model of health (centred on "the illness"). The main relevant learning model is to link neurofeedback therapy with the field of cognitive remediation techniques. The methodological specificity of neurofeedback is to be guided by biologically relevant neurophysiological parameters. Guidelines for good clinical practice of EEG NF concerning technical issues of electrophysiology and of learning are suggested. These require validation by institutional structures for the clinical practice of EEG NF. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Selection, calibration, and validation of models of tumor growth.

PubMed

Lima, E A B F; Oden, J T; Hormuth, D A; Yankeelov, T E; Almeida, R C

2016-11-01

This paper presents general approaches for addressing some of the most important issues in predictive computational oncology concerned with developing classes of predictive models of tumor growth. First, the process of developing mathematical models of vascular tumors evolving in the complex, heterogeneous, macroenvironment of living tissue; second, the selection of the most plausible models among these classes, given relevant observational data; third, the statistical calibration and validation of models in these classes, and finally, the prediction of key Quantities of Interest (QOIs) relevant to patient survival and the effect of various therapies. The most challenging aspects of this endeavor is that all of these issues often involve confounding uncertainties: in observational data, in model parameters, in model selection, and in the features targeted in the prediction. Our approach can be referred to as "model agnostic" in that no single model is advocated; rather, a general approach that explores powerful mixture-theory representations of tissue behavior while accounting for a range of relevant biological factors is presented, which leads to many potentially predictive models. Then representative classes are identified which provide a starting point for the implementation of OPAL, the Occam Plausibility Algorithm (OPAL) which enables the modeler to select the most plausible models (for given data) and to determine if the model is a valid tool for predicting tumor growth and morphology ( in vivo ). All of these approaches account for uncertainties in the model, the observational data, the model parameters, and the target QOI. We demonstrate these processes by comparing a list of models for tumor growth, including reaction-diffusion models, phase-fields models, and models with and without mechanical deformation effects, for glioma growth measured in murine experiments. Examples are provided that exhibit quite acceptable predictions of tumor growth in laboratory animals while demonstrating successful implementations of OPAL.

SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models.

PubMed

Zi, Zhike

2011-04-01

Parameter estimation is crucial for the modeling and dynamic analysis of biological systems. However, implementing parameter estimation is time consuming and computationally demanding. Here, we introduced a parallel parameter estimation tool for Systems Biology Markup Language (SBML)-based models (SBML-PET-MPI). SBML-PET-MPI allows the user to perform parameter estimation and parameter uncertainty analysis by collectively fitting multiple experimental datasets. The tool is developed and parallelized using the message passing interface (MPI) protocol, which provides good scalability with the number of processors. SBML-PET-MPI is freely available for non-commercial use at http://www.bioss.uni-freiburg.de/cms/sbml-pet-mpi.html or http://sites.google.com/site/sbmlpetmpi/.

Parameter estimation using meta-heuristics in systems biology: a comprehensive review.

PubMed

Sun, Jianyong; Garibaldi, Jonathan M; Hodgman, Charlie

2012-01-01

This paper gives a comprehensive review of the application of meta-heuristics to optimization problems in systems biology, mainly focussing on the parameter estimation problem (also called the inverse problem or model calibration). It is intended for either the system biologist who wishes to learn more about the various optimization techniques available and/or the meta-heuristic optimizer who is interested in applying such techniques to problems in systems biology. First, the parameter estimation problems emerging from different areas of systems biology are described from the point of view of machine learning. Brief descriptions of various meta-heuristics developed for these problems follow, along with outlines of their advantages and disadvantages. Several important issues in applying meta-heuristics to the systems biology modelling problem are addressed, including the reliability and identifiability of model parameters, optimal design of experiments, and so on. Finally, we highlight some possible future research directions in this field.

Chromosome Gene Orientation Inversion Networks (GOINs) of Plasmodium Proteome.

PubMed

Quevedo-Tumailli, Viviana F; Ortega-Tenezaca, Bernabé; González-Díaz, Humbert

2018-03-02

The spatial distribution of genes in chromosomes seems not to be random. For instance, only 10% of genes are transcribed from bidirectional promoters in humans, and many more are organized into larger clusters. This raises intriguing questions previously asked by different authors. We would like to add a few more questions in this context, related to gene orientation inversions. Does gene orientation (inversion) follow a random pattern? Is it relevant to biological activity somehow? We define a new kind of network coined as the gene orientation inversion network (GOIN). GOIN's complex network encodes short- and long-range patterns of inversion of the orientation of pairs of gene in the chromosome. We selected Plasmodium falciparum as a case of study due to the high relevance of this parasite to public health (causal agent of malaria). We constructed here for the first time all of the GOINs for the genome of this parasite. These networks have an average of 383 nodes (genes in one chromosome) and 1314 links (pairs of gene with inverse orientation). We calculated node centralities and other parameters of these networks. These numerical parameters were used to study different properties of gene inversion patterns, for example, distribution, local communities, similarity to Erdös-Rényi random networks, randomness, and so on. We find clues that seem to indicate that gene orientation inversion does not follow a random pattern. We noted that some gene communities in the GOINs tend to group genes encoding for RIFIN-related proteins in the proteome of the parasite. RIFIN-like proteins are a second family of clonally variant proteins expressed on the surface of red cells infected with Plasmodium falciparum. Consequently, we used these centralities as input of machine learning (ML) models to predict the RIFIN-like activity of 5365 proteins in the proteome of Plasmodium sp. The best linear ML model found discriminates RIFIN-like from other proteins with sensitivity and specificity 70-80% in training and external validation series. All of these results may point to a possible biological relevance of gene orientation inversion not directly dependent on genetic sequence information. This work opens the gate to the use of GOINs as a tool for the study of the structure of chromosomes and the study of protein function in proteome research.

Biological Evidence Management for DNA Analysis in Cases of Sexual Assault

PubMed Central

Magalhães, Teresa; Dinis-Oliveira, Ricardo Jorge; Silva, Benedita; Corte-Real, Francisco; Nuno Vieira, Duarte

2015-01-01

Biological evidence with forensic interest may be found in several cases of assault, being particularly relevant if sexually related. Sexual assault cases are characterized by low rates of disclosure, reporting, prosecution, and conviction. Biological evidence is sometimes the only way to prove the occurrence of sexual contact and to identify the perpetrator. The major focus of this review is to propose practical approaches and guidelines to help health, forensic, and law enforcement professionals to deal with biological evidence for DNA analysis. Attention should be devoted to avoiding contamination, degradation, and loss of biological evidence, as well as respecting specific measures to properly handle evidence (i.e., selection, collection, packing, sealing, labeling, storage, preservation, transport, and guarantee of the chain custody). Biological evidence must be carefully managed since the relevance of any finding in Forensic Genetics is determined, in the first instance, by the integrity and quantity of the samples submitted for analysis. PMID:26587562

Retrieving the optical parameters of biological tissues using diffuse reflectance spectroscopy and Fourier series expansions. I. theory and application.

PubMed

Muñoz Morales, Aarón A; Vázquez Y Montiel, Sergio

2012-10-01

The determination of optical parameters of biological tissues is essential for the application of optical techniques in the diagnosis and treatment of diseases. Diffuse Reflection Spectroscopy is a widely used technique to analyze the optical characteristics of biological tissues. In this paper we show that by using diffuse reflectance spectra and a new mathematical model we can retrieve the optical parameters by applying an adjustment of the data with nonlinear least squares. In our model we represent the spectra using a Fourier series expansion finding mathematical relations between the polynomial coefficients and the optical parameters. In this first paper we use spectra generated by the Monte Carlo Multilayered Technique to simulate the propagation of photons in turbid media. Using these spectra we determine the behavior of Fourier series coefficients when varying the optical parameters of the medium under study. With this procedure we find mathematical relations between Fourier series coefficients and optical parameters. Finally, the results show that our method can retrieve the optical parameters of biological tissues with accuracy that is adequate for medical applications.

Laser tailored nanoparticle arrays to detect molecules at dilute concentration

NASA Astrophysics Data System (ADS)

Zanchi, Chiara; Lucotti, Andrea; Tommasini, Matteo; Trusso, Sebastiano; de Grazia, Ugo; Ciusani, Emilio; Ossi, Paolo M.

2017-02-01

By nanosecond pulsed laser ablation in an ambient gas gold nanoparticles (NPs) were produced that self-assemble on a substrate resulting in increasingly elaborated architectures of growing thickness, from isolated NP arrays up to percolated films. NPs nucleate and grow in the plasma plume propagating through the gas. Process parameters including laser wavelength, laser energy density, target to substrate distance, nature and pressure of the gas affect plasma expansion, thus asymptotic NP size and kinetic energy. NP size, energy and mobility at landing determine film growth and morphology that affect the physico-chemical properties of the film. Keeping fixed the other process parameters, we discuss the sensitive dependence of film surface nanostructure on Ar pressure and on laser pulse number. The initial plume velocity and average ablated mass per pulse allow predicting the asymptotic NP size. The control of growth parameters favors fine-tuning of NP aggregation, relevant to plasmonics to get optimized substrates for surface enhanced Raman spectroscopy (SERS). Their behavior is discussed for testing conditions of interest for clinical application. Both in aqueous and in biological solutions we obtained good sensitivity and reproducibility of the SERS signals for the anti-Parkinson drug apomorphine, and for the anti-epilepsy drug carbamazepine.

Biomachining: metal etching via microorganisms.

PubMed

Díaz-Tena, Estíbaliz; Barona, Astrid; Gallastegui, Gorka; Rodríguez, Adrián; López de Lacalle, L Norberto; Elías, Ana

2017-05-01

The use of microorganisms to remove metal from a workpiece is known as biological machining or biomachining, and it has gained in both importance and scientific relevance over the past decade. Conversely to mechanical methods, the use of readily available microorganisms is low-energy consuming, and no thermal damage is caused during biomachining. The performance of this sustainable process is assessed by the material removal rate, and certain parameters have to be controlled for manufacturing the machined part with the desired surface finish. Although the variety of microorganisms is scarce, cell concentration or density plays an important role in the process. There is a need to control the temperature to maintain microorganism activity at its optimum, and a suitable shaking rate provides an efficient contact between the workpiece and the biological medium. The system's tolerance to the sharp changes in pH is quite limited, and in many cases, an acid medium has to be maintained for effective performance. This process is highly dependent on the type of metal being removed. Consequently, the operating parameters need to be determined on a case-by-case basis. The biomachining time is another variable with a direct impact on the removal rate. This biological technique can be used for machining simple and complex shapes, such as series of linear, circular, and square micropatterns on different metal surfaces. The optimal biomachining process should be fast enough to ensure high production, a smooth and homogenous surface finish and, in sum, a high-quality piece. As a result of the high global demand for micro-components, biomachining provides an effective and sustainable alternative. However, its industrial-scale implementation is still pending.

Biosimilarity and Interchangeability: Principles and Evidence: A Systematic Review.

PubMed

McKinnon, Ross A; Cook, Matthew; Liauw, Winston; Marabani, Mona; Marschner, Ian C; Packer, Nicolle H; Prins, Johannes B

2018-02-01

The efficacy, safety and immunogenicity risk of switching between an originator biologic and a biosimilar or from one biosimilar to another are of potential concern. The aim was to conduct a systematic literature review of the outcomes of switching between biologics and their biosimilars and identify any evidence gaps. A systematic literature search was conducted in PubMed, EMBASE and Cochrane Library from inception to June 2017. Relevant societal meetings were also checked. Peer-reviewed studies reporting efficacy and/or safety data on switching between originator and biosimilar products or from one biosimilar to another were selected. Studies with fewer than 20 switched patients were excluded. Data were extracted on interventions, study population, reason for treatment switching, efficacy outcomes, safety and anti-drug antibodies. The systematic literature search identified 63 primary publications covering 57 switching studies. The reason for switching was reported as non-medical in 50 studies (23 clinical, 27 observational). Seven studies (all observational) did not report whether the reasons for switching were medical or non-medical. In 38 of the 57 studies, fewer than 100 patients were switched. Follow-up after switching went beyond 1 year in eight of the 57 studies. Of the 57 studies, 33 included statistical analysis of disease activity or patient outcomes; the majority of these studies found no statistically significant differences between groups for main efficacy parameters (based on P < 0.05 or predefined acceptance ranges), although some studies observed changes for some parameters. Most studies reported similar safety profiles between groups. There are important evidence gaps around the safety of switching between biologics and their biosimilars. Sufficiently powered and appropriately statistically analysed clinical trials and pharmacovigilance studies, with long-term follow-ups and multiple switches, are needed to support decision-making around biosimilar switching.

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…

A Comparison of Biological and Adoptive Mothers and Fathers: The Relevance of Biological Kinship and Gendered Constructs of Parenthood.

ERIC Educational Resources Information Center

Miall, Charlene E.; March, Karen

2003-01-01

Used qualitative interviews to examine beliefs and values about biological and adoptive parents. Considered how biological kinship, gender, and actual parenting behavior affect the assessments respondents made of the emotional bonding between parents and children. Found that biological and adoptive parents viewed motherhood as instinctive and…

Estimating the physicochemical properties of polyhalogenated aromatic and aliphatic compounds using UPPER: part 1. Boiling point and melting point.

PubMed

Admire, Brittany; Lian, Bo; Yalkowsky, Samuel H

2015-01-01

The UPPER (Unified Physicochemical Property Estimation Relationships) model uses enthalpic and entropic parameters to estimate 20 biologically relevant properties of organic compounds. The model has been validated by Lian and Yalkowsky on a data set of 700 hydrocarbons. The aim of this work is to expand the UPPER model to estimate the boiling and melting points of polyhalogenated compounds. In this work, 19 new group descriptors are defined and used to predict the transition temperatures of an additional 1288 compounds. The boiling points of 808 and the melting points of 742 polyhalogenated compounds are predicted with average absolute errors of 13.56 K and 25.85 K, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Anthropocene concept in ecology and conservation.

PubMed

Corlett, Richard T

2015-01-01

The term 'Anthropocene' was first used in the year 2000 to refer to the current time period in which human impacts are at least as important as natural processes. It is currently being considered as a potential geological epoch, following on from the Holocene. While most environmental scientists accept that many key environmental parameters are now outside their Holocene ranges, there is no agreement on when the Anthropocene started, with plausible dates ranging from the Late Pleistocene megafaunal extinctions to the recent globalization of industrial impacts. In ecology, the Anthropocene concept has focused attention on human-dominated habitats and novel ecosystems, while in conservation biology it has sparked a divisive debate on the continued relevance of the traditional biocentric aims. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using the NASA Giovanni DICCE Portal to Investigate Land-Ocean Linkages with Satellite and Model Data

NASA Technical Reports Server (NTRS)

Acker, James G.; Zalles, Daniel; Krumhansl, Ruth

2012-01-01

Data-enhanced Investigations for Climate Change Education (DICCE), a NASA climate change education project, employs the NASA Giovanni data system to enable teachers to create climate-related classroom projects using selected satellite and assimilated model data. The easy-to-use DICCE Giovanni portal (DICCE-G) provides data parameters relevant to oceanic, terrestrial, and atmospheric processes. Participants will explore land-ocean linkages using the available data in the DICCE-G portal, in particular focusing on temperature, ocean biology, and precipitation variability related to El Ni?o and La Ni?a events. The demonstration includes the enhanced information for educators developed for the DICCE-G portal. The prototype DICCE Learning Environment (DICCE-LE) for classroom project development will also be demonstrated.

Microbial Development and Metabolic Engineering | Bioenergy | NREL

Science.gov Websites

beaker filled with a green liquid cyanobacteria culture that is bubbling. Synthetic Biology We have utilized the power of synthetic biology to uncover relevant genetic factors to predictably regulate gene operating a gas chromatograph mass spectrometer. Systems Biology Our comprehensive systems biology

PathText: a text mining integrator for biological pathway visualizations

PubMed Central

Kemper, Brian; Matsuzaki, Takuya; Matsuoka, Yukiko; Tsuruoka, Yoshimasa; Kitano, Hiroaki; Ananiadou, Sophia; Tsujii, Jun'ichi

2010-01-01

Motivation: Metabolic and signaling pathways are an increasingly important part of organizing knowledge in systems biology. They serve to integrate collective interpretations of facts scattered throughout literature. Biologists construct a pathway by reading a large number of articles and interpreting them as a consistent network, but most of the models constructed currently lack direct links to those articles. Biologists who want to check the original articles have to spend substantial amounts of time to collect relevant articles and identify the sections relevant to the pathway. Furthermore, with the scientific literature expanding by several thousand papers per week, keeping a model relevant requires a continuous curation effort. In this article, we present a system designed to integrate a pathway visualizer, text mining systems and annotation tools into a seamless environment. This will enable biologists to freely move between parts of a pathway and relevant sections of articles, as well as identify relevant papers from large text bases. The system, PathText, is developed by Systems Biology Institute, Okinawa Institute of Science and Technology, National Centre for Text Mining (University of Manchester) and the University of Tokyo, and is being used by groups of biologists from these locations. Contact: brian@monrovian.com. PMID:20529930

A likelihood-based biostatistical model for analyzing consumer movement in simultaneous choice experiments.

PubMed

Zeilinger, Adam R; Olson, Dawn M; Andow, David A

2014-08-01

Consumer feeding preference among resource choices has critical implications for basic ecological and evolutionary processes, and can be highly relevant to applied problems such as ecological risk assessment and invasion biology. Within consumer choice experiments, also known as feeding preference or cafeteria experiments, measures of relative consumption and measures of consumer movement can provide distinct and complementary insights into the strength, causes, and consequences of preference. Despite the distinct value of inferring preference from measures of consumer movement, rigorous and biologically relevant analytical methods are lacking. We describe a simple, likelihood-based, biostatistical model for analyzing the transient dynamics of consumer movement in a paired-choice experiment. With experimental data consisting of repeated discrete measures of consumer location, the model can be used to estimate constant consumer attraction and leaving rates for two food choices, and differences in choice-specific attraction and leaving rates can be tested using model selection. The model enables calculation of transient and equilibrial probabilities of consumer-resource association, which could be incorporated into larger scale movement models. We explore the effect of experimental design on parameter estimation through stochastic simulation and describe methods to check that data meet model assumptions. Using a dataset of modest sample size, we illustrate the use of the model to draw inferences on consumer preference as well as underlying behavioral mechanisms. Finally, we include a user's guide and computer code scripts in R to facilitate use of the model by other researchers.

Assessment of health status of oysters (Crassostreagigas) exposed to environmentally relevant concentrations of Ag and Cu in brackish waters

NASA Astrophysics Data System (ADS)

Rementeria, Ane; Mikolaczyk, Mathilde; Peña, Ainhize; Lanceleur, Laurent; Blanc, Gérard; Soto, Manu; Schäfer, Jörg; Zaldibar, Beñat

2017-12-01

Human activities have altered estuarine environments leading to increased presence of different pollutants including metals. Although the implementation of new environmental policies has caused a considerable decrease in trace metal concentrations in estuaries around the Bay of Biscay, some elements such as copper (Cu) and silver (Ag) are still present in relatively high concentrations. Oysters have been widely used in environmental biomonitoring programs as sentinel organisms. Oysters Crassostrea gigas from an uncontaminated estuary were exposed to sublethal, environmentally relevant concentrations of Cu (2000 ng Cu/L) and Ag (500 ng Ag/L) during 14 days in brackish water (S = 18). A battery of cell and tissue level (exposure) biomarkers at different levels of biological complexity was applied and integrated into the Integrative Biological Response (IBR) index including: metallothionein contents, intralysosomal metal accumulation, digestive gland atrophy and digestive gland tissue integrity. Condition Index (CI) was incorporated into the IBR index as a complementary parameter that reflects the general physiological condition of oysters (organism level). Results indicated an increase in intralysosomal metal accumulation after 7 and 14 days of exposure to Ag together with an increase in the digestive epithelium atrophy and lipofuscin content after 7 days of exposure to Ag. The responses detected with the aid of biomarkers integrated in the IBR index showed higher toxicity in oysters exposed to Ag, inducing the clear onset of detoxification processes which also occurred, to a lower extent, in Cu-exposed oysters.

Information Theory in Biology after 18 Years

ERIC Educational Resources Information Center

Johnson, Horton A.

1970-01-01

Reviews applications of information theory to biology, concluding that they have not proved very useful. Suggests modifications and extensions to increase the biological relevance of the theory, and speculates about applications in quantifying cell proliferation, chemical homeostasis and aging. (EB)

Human Metabolites of Cannabidiol: A Review on Their Formation, Biological Activity, and Relevance in Therapy

PubMed Central

Ujváry, István; Hanuš, Lumír

2016-01-01

Abstract Cannabidiol (CBD), the main nonpsychoactive constituent of Cannabis sativa, has shown a wide range of therapeutically promising pharmacological effects either as a sole drug or in combination with other drugs in adjunctive therapy. However, the targets involved in the therapeutic effects of CBD appear to be elusive. Furthermore, scarce information is available on the biological activity of its human metabolites which, when formed in pharmacologically relevant concentration, might contribute to or even account for the observed therapeutic effects. The present overview summarizes our current knowledge on the pharmacokinetics and metabolic fate of CBD in humans, reviews studies on the biological activity of CBD metabolites either in vitro or in vivo, and discusses relevant drug–drug interactions. To facilitate further research in the area, the reported syntheses of CBD metabolites are also catalogued. PMID:28861484

Human Metabolites of Cannabidiol: A Review on Their Formation, Biological Activity, and Relevance in Therapy.

PubMed

Ujváry, István; Hanuš, Lumír

2016-01-01

Cannabidiol (CBD), the main nonpsychoactive constituent of Cannabis sativa , has shown a wide range of therapeutically promising pharmacological effects either as a sole drug or in combination with other drugs in adjunctive therapy. However, the targets involved in the therapeutic effects of CBD appear to be elusive. Furthermore, scarce information is available on the biological activity of its human metabolites which, when formed in pharmacologically relevant concentration, might contribute to or even account for the observed therapeutic effects. The present overview summarizes our current knowledge on the pharmacokinetics and metabolic fate of CBD in humans, reviews studies on the biological activity of CBD metabolites either in vitro or in vivo , and discusses relevant drug-drug interactions. To facilitate further research in the area, the reported syntheses of CBD metabolites are also catalogued.

Biology of acute lymphoblastic leukemia (ALL): clinical and therapeutic relevance.

PubMed

Graux, Carlos

2011-04-01

Acute lymphoblastic leukemia is a heterogeneous disease comprising several clinico-biological entities. Karyotyping of leukemic cells identifies recurrent chromosome rearrangements. These are usually translocations that activate genes encoding transcription factor regulating B- or T-cell differentiation. Gene expression-array confirms the prognostic relevance of ALL subgroups identified by specific chromosomal rearrangements and isolates new subgroups. Analysis of genomic copy number changes and high throughput sequencing reveal new cryptic deletions. The challenge is now to understand how these cooperative genetic lesions interact in order to have the molecular rationales needed to select new therapeutic targets and to develop and combine inhibitors with high levels of anti-leukemic specificity. The aim of this paper is to provide some data on the biology of acute lymphoblastic leukemia which are relevant in clinical practice. Copyright © 2011 Elsevier Ltd. All rights reserved.

Vision and change in introductory physics for the life sciences

NASA Astrophysics Data System (ADS)

Mochrie, S. G. J.

2016-07-01

Since 2010, our physics department has offered a re-imagined calculus-based introductory physics sequence for the life sciences. These courses include a selection of biologically and medically relevant topics that we believe are more meaningful to undergraduate premedical and biological science students than those found in a traditional course. In this paper, we highlight new aspects of the first-semester course, and present a comparison of student evaluations of this course versus a more traditional one. We also present the effect on student perception of the relevance of physics to biology and medicine after having taken this course.

An inventory and evaluation of biological investigations that relate to stream-water quality in the upper Illinois River basin of Illinois, Indiana, and Wisconsin

USGS Publications Warehouse

Steffeck, D.W.; Striegl, Robert G.

1989-01-01

Results of studies of the aquatic biology of the upper Illinois River basin provide a historical data source from which inferences can be made about changes in the quality of water in the main stem river and its tributaries. The results of biological investigations that have been conducted throughout the basin since 1900 are summarized and their relevance to stream-water-quality assessment is described, particularly their relevance to the upper Illinois River basin pilot project for the National Water Quality Assessment program. Four general categories of biological investigations were identified: Populations and community structure, chemical concentrations in tissue, organism health, and toxicity measurements. Biological investigations were identified by their location in the basin and by their relevance to each general investigation category. The most abundant literature was in the populations and community structure category. Tissue data were limited to polychlorinated biphenyls, organochlorine pesticides, dioxin, and several metals. The most cited measure of organism health was a condition factor for fish that associates body length with weight or body depth. Toxicity measurements included bioassays and the Ames Tests. The bioassays included several testing methods and test organism. (USGS)

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.

Calculating background levels for ecological risk parameters in toxic harbor sediment

USGS Publications Warehouse

Leadon, C.J.; McDonnell, T.R.; Lear, J.; Barclift, D.

2007-01-01

Establishing background levels for biological parameters is necessary in assessing the ecological risks from harbor sediment contaminated with toxic chemicals. For chemicals in sediment, the term contaminated is defined as having concentrations above background and significant human health or ecological risk levels. For biological parameters, a site could be considered contaminated if levels of the parameter are either more or less than the background level, depending on the specific parameter. Biological parameters can include tissue chemical concentrations in ecological receptors, bioassay responses, bioaccumulation levels, and benthic community metrics. Chemical parameters can include sediment concentrations of a variety of potentially toxic chemicals. Indirectly, contaminated harbor sediment can impact shellfish, fish, birds, and marine mammals, and human populations. This paper summarizes the methods used to define background levels for chemical and biological parameters from a survey of ecological risk investigations of marine harbor sediment at California Navy bases. Background levels for regional biological indices used to quantify ecological risks for benthic communities are also described. Generally, background stations are positioned in relatively clean areas exhibiting the same physical and general chemical characteristics as nearby areas with contaminated harbor sediment. The number of background stations and the number of sample replicates per background station depend on the statistical design of the sediment ecological risk investigation, developed through the data quality objective (DQO) process. Biological data from the background stations can be compared to data from a contaminated site by using minimum or maximum background levels or comparative statistics. In Navy ecological risk assessments (ERA's), calculated background levels and appropriate ecological risk screening criteria are used to identify sampling stations and sites with contaminated sediments.

Parameter Estimation and Model Selection in Computational Biology

PubMed Central

Lillacci, Gabriele; Khammash, Mustafa

2010-01-01

A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants) are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection. PMID:20221262

biologically relevant effects of dipentyl phthalate

EPA Pesticide Factsheets

metadata sheet, data sheet for each table and figure in the published manuscriptThis dataset is associated with the following publication:Gray , E., J. Furr , K. Tatum-Gibbs, C. Lambright , H. Sampson, B. Hannas, V. Wilson , A. Hotchkiss , and P. Foster. Establishing the Biological Relevance of Dipentyl Phthalate Reductions in Fetal Rat Testosterone Production and Plasma and Testis Testosterone Levels. TOXICOLOGICAL SCIENCES. Society of Toxicology, 149(1): 178-91, (2016).

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

PubMed

Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith

2018-01-02

Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour and identifies the sets of rate parameters of interest.

An analysis of the positional distribution of DNA motifs in promoter regions and its biological relevance.

PubMed

Casimiro, Ana C; Vinga, Susana; Freitas, Ana T; Oliveira, Arlindo L

2008-02-07

Motif finding algorithms have developed in their ability to use computationally efficient methods to detect patterns in biological sequences. However the posterior classification of the output still suffers from some limitations, which makes it difficult to assess the biological significance of the motifs found. Previous work has highlighted the existence of positional bias of motifs in the DNA sequences, which might indicate not only that the pattern is important, but also provide hints of the positions where these patterns occur preferentially. We propose to integrate position uniformity tests and over-representation tests to improve the accuracy of the classification of motifs. Using artificial data, we have compared three different statistical tests (Chi-Square, Kolmogorov-Smirnov and a Chi-Square bootstrap) to assess whether a given motif occurs uniformly in the promoter region of a gene. Using the test that performed better in this dataset, we proceeded to study the positional distribution of several well known cis-regulatory elements, in the promoter sequences of different organisms (S. cerevisiae, H. sapiens, D. melanogaster, E. coli and several Dicotyledons plants). The results show that position conservation is relevant for the transcriptional machinery. We conclude that many biologically relevant motifs appear heterogeneously distributed in the promoter region of genes, and therefore, that non-uniformity is a good indicator of biological relevance and can be used to complement over-representation tests commonly used. In this article we present the results obtained for the S. cerevisiae data sets.

NanoTopoChip: High-throughput nanotopographical cell instruction.

PubMed

Hulshof, Frits F B; Zhao, Yiping; Vasilevich, Aliaksei; Beijer, Nick R M; de Boer, Meint; Papenburg, Bernke J; van Blitterswijk, Clemens; Stamatialis, Dimitrios; de Boer, Jan

2017-10-15

Surface topography is able to influence cell phenotype in numerous ways and offers opportunities to manipulate cells and tissues. In this work, we develop the Nano-TopoChip and study the cell instructive effects of nanoscale topographies. A combination of deep UV projection lithography and conventional lithography was used to fabricate a library of more than 1200 different defined nanotopographies. To illustrate the cell instructive effects of nanotopography, actin-RFP labeled U2OS osteosarcoma cells were cultured and imaged on the Nano-TopoChip. Automated image analysis shows that of many cell morphological parameters, cell spreading, cell orientation and actin morphology are mostly affected by the nanotopographies. Additionally, by using modeling, the changes of cell morphological parameters could by predicted by several feature shape parameters such as lateral size and spacing. This work overcomes the technological challenges of fabricating high quality defined nanoscale features on unprecedented large surface areas of a material relevant for tissue culture such as PS and the screening system is able to infer nanotopography - cell morphological parameter relationships. Our screening platform provides opportunities to identify and study the effect of nanotopography with beneficial properties for the culture of various cell types. The nanotopography of biomaterial surfaces can be modified to influence adhering cells with the aim to improve the performance of medical implants and tissue culture substrates. However, the necessary knowledge of the underlying mechanisms remains incomplete. One reason for this is the limited availability of high-resolution nanotopographies on relevant biomaterials, suitable to conduct systematic biological studies. The present study shows the fabrication of a library of nano-sized surface topographies with high fidelity. The potential of this library, called the 'NanoTopoChip' is shown in a proof of principle HTS study which demonstrates how cells are affected by nanotopographies. The large dataset, acquired by quantitative high-content imaging, allowed us to use predictive modeling to describe how feature dimensions affect cell morphology. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Biology Curriculum Reform in Venezuela.

ERIC Educational Resources Information Center

Rondon, Leonor Mariasole

2001-01-01

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

A flexible, interactive software tool for fitting the parameters of neuronal models.

PubMed

Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs

2014-01-01

The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool.

A flexible, interactive software tool for fitting the parameters of neuronal models

PubMed Central

Friedrich, Péter; Vella, Michael; Gulyás, Attila I.; Freund, Tamás F.; Káli, Szabolcs

2014-01-01

The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool. PMID:25071540

A novel database of bio-effects from non-ionizing radiation.

PubMed

Leach, Victor; Weller, Steven; Redmayne, Mary

2018-06-06

A significant amount of electromagnetic field/electromagnetic radiation (EMF/EMR) research is available that examines biological and disease associated endpoints. The quantity, variety and changing parameters in the available research can be challenging when undertaking a literature review, meta-analysis, preparing a study design, building reference lists or comparing findings between relevant scientific papers. The Oceania Radiofrequency Scientific Advisory Association (ORSAA) has created a comprehensive, non-biased, multi-categorized, searchable database of papers on non-ionizing EMF/EMR to help address these challenges. It is regularly added to, freely accessible online and designed to allow data to be easily retrieved, sorted and analyzed. This paper demonstrates the content and search flexibility of the ORSAA database. Demonstration searches are presented by Effect/No Effect; frequency-band/s; in vitro; in vivo; biological effects; study type; and funding source. As of the 15th September 2017, the clear majority of 2653 papers captured in the database examine outcomes in the 300 MHz-3 GHz range. There are 3 times more biological "Effect" than "No Effect" papers; nearly a third of papers provide no funding statement; industry-funded studies more often than not find "No Effect", while institutional funding commonly reveal "Effects". Country of origin where the study is conducted/funded also appears to have a dramatic influence on the likely result outcome.

Physicochemical water quality of the Mfoundi River watershed at Yaoundé, Cameroon, and its relevance to the distribution of bacterial indicators of faecal contamination.

PubMed

Djuikom, E; Jugnia, L B; Nola, M; Foto, S; Sikati, V

2009-01-01

Water quality of the Mfoundi River and four of its tributaries was studied by assessing some physicochemical variables (temperature, pH, conductivity, chlorides, phosphates and nitrogen ammonia, dissolved oxygen and carbon dioxide, organic matter content and Biological Oxygen Demand) and their influence on the distribution of bacterial indicators of faecal contamination (total coliform, faecal coliform and faecal streptococci). For this, standard methods for the examination of physicochemical parameters in water were followed, and statistical analysis (Pearson correlations) used to establish any relationships between physicochemical and biological variables. Our results revealed that almost all of the examined physicochemical variables exceeded World Health Organization (WHO) guidelines for recreational water. This was in agreement with a previous microbiological study indicating that these waters were not safe for human use or primary contact according to water quality standards established by the WHO. Results of our correlation analysis suggested that physicochemical and biological variables interact in complicated ways reflecting the complex processes occurring in the natural environment. It was also concluded that pollution in the Mfoundi River watershed poses an increased risk of infection for users and there exists an urgent need to control dumping of wastewater into this watershed.

Study of the degradation in aqueous solution of a refractory organic compound: avermectin type used as pesticide in agriculture.

PubMed

Boukhrissa, Athir; Ferrag-Siagh, Fatiha; Rouidi, Lina-Mounia; Chemat, Smaïn; Aït-Amar, Hamid

2017-10-01

We examined the removal of abamectin by the electro-Fenton (EF) process and the feasibility of biological treatment after degradation. The effect of the operating parameters showed that abamectin (Aba) degradation was enhanced with increasing temperature. Response surface analysis of the central composite design led to the following optimal conditions for the abatement of chemical oxygen demand: 45.5 °C, 5 mg L -1 , 150 mA, and 0.15 mmol L -1 for the temperature, initial Aba concentration, current intensity, and catalyst concentration, respectively. Under these conditions, 68.01% of the organic matter was removed and 94% of Aba was degraded after 5 h and 20 min of electrolysis, respectively. A biodegradability test, which was performed on a solution electrolyzed at 47 °C, 9 mg L -1 , 150 mA, and 0.15 mmol L -1 , confirms that the ratio of biological oxygen demand/chemical oxygen demand increased appreciably from 0.0584 to 0.64 after 5 h of electrolysis. This increased ratio is slightly above the limit of biodegradability (0.4). These results show the relevance of the EF process and its effectiveness for abamectin degradation. We conclude that biological treatment can be combined with the EF process for total mineralization.

Bayesian Covariate Selection in Mixed-Effects Models For Longitudinal Shape Analysis

PubMed Central

Muralidharan, Prasanna; Fishbaugh, James; Kim, Eun Young; Johnson, Hans J.; Paulsen, Jane S.; Gerig, Guido; Fletcher, P. Thomas

2016-01-01

The goal of longitudinal shape analysis is to understand how anatomical shape changes over time, in response to biological processes, including growth, aging, or disease. In many imaging studies, it is also critical to understand how these shape changes are affected by other factors, such as sex, disease diagnosis, IQ, etc. Current approaches to longitudinal shape analysis have focused on modeling age-related shape changes, but have not included the ability to handle covariates. In this paper, we present a novel Bayesian mixed-effects shape model that incorporates simultaneous relationships between longitudinal shape data and multiple predictors or covariates to the model. Moreover, we place an Automatic Relevance Determination (ARD) prior on the parameters, that lets us automatically select which covariates are most relevant to the model based on observed data. We evaluate our proposed model and inference procedure on a longitudinal study of Huntington's disease from PREDICT-HD. We first show the utility of the ARD prior for model selection in a univariate modeling of striatal volume, and next we apply the full high-dimensional longitudinal shape model to putamen shapes. PMID:28090246

Physical modelling of the nuclear pore complex

PubMed Central

Fassati, Ariberto; Ford, Ian J.; Hoogenboom, Bart W.

2013-01-01

Physically interesting behaviour can arise when soft matter is confined to nanoscale dimensions. A highly relevant biological example of such a phenomenon is the Nuclear Pore Complex (NPC) found perforating the nuclear envelope of eukaryotic cells. In the central conduit of the NPC, of ∼30–60 nm diameter, a disordered network of proteins regulates all macromolecular transport between the nucleus and the cytoplasm. In spite of a wealth of experimental data, the selectivity barrier of the NPC has yet to be explained fully. Experimental and theoretical approaches are complicated by the disordered and heterogeneous nature of the NPC conduit. Modelling approaches have focused on the behaviour of the partially unfolded protein domains in the confined geometry of the NPC conduit, and have demonstrated that within the range of parameters thought relevant for the NPC, widely varying behaviour can be observed. In this review, we summarise recent efforts to physically model the NPC barrier and function. We illustrate how attempts to understand NPC barrier function have employed many different modelling techniques, each of which have contributed to our understanding of the NPC.

Kinetic modelling of passive transport and active efflux of a fluoroquinolone across Caco-2 cells using a compartmental approach in NONMEM.

PubMed

González-Alvarez, I; Fernández-Teruel, C; Garrigues, T M; Casabo, V G; Ruiz-García, A; Bermejo, M

2005-12-01

The purpose was to develop a general mathematical model for estimating passive permeability and efflux transport parameters from in vitro cell culture experiments. The procedure is applicable for linear and non-linear transport of drug with time, <10 or >10% of drug transport, negligible or relevant back flow, and would allow the adequate correction in the case of relevant mass balance problems. A compartmental kinetic approach was used and the transport barriers were described quantitatively in terms of apical and basolateral clearances. The method can be applied when sink conditions are not achieved and it allows the evaluation of the location of the transporter and its binding site. In this work it was possible to demonstrate, from a functional point of view, the higher efflux capacity of the TC7 clone and to identify the apical membrane as the main resistance for the xenobiotic transport. This methodology can be extremely useful as a complementary tool for molecular biology approaches in order to establish meaningful hypotheses about transport mechanisms.

Transbulbar B-Mode Sonography in Multiple Sclerosis: Clinical and Biological Relevance.

PubMed

De Masi, Roberto; Orlando, Stefania; Conte, Aldo; Pasca, Sergio; Scarpello, Rocco; Spagnolo, Pantaleo; Muscella, Antonella; De Donno, Antonella

2016-12-01

Optic nerve sheath diameter quantification by transbulbar B-mode sonography is a recently validated technique, but its clinical relevance in relapse-free multiple sclerosis patients remains unexplored. In an open-label, comparative, cross-sectional study, we aimed to assess possible differences between patients and healthy controls in terms of optic nerve sheath diameter and its correlation with clinical/paraclinical parameters in this disease. Sixty unselected relapse-free patients and 35 matched healthy controls underwent transbulbar B-mode sonography. Patients underwent routine neurologic examination, brain magnetic resonance imaging and visual evoked potential tests. The mean optic nerve sheath diameter 3 and 5 mm from the eyeball was 22-25% lower in patients than controls and correlated with the Expanded Disability Status Scale (r = -0.34, p = 0.048, and r = -0.32, p = 0.042, respectively). We suggest that optic nerve sheath diameter quantified by transbulbar B-mode sonography should be included in routine assessment of the disease as an extension of the neurologic examination. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

IQ Predicts Biological Motion Perception in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Rutherford, M. D.; Troje, Nikolaus F.

2012-01-01

Biological motion is easily perceived by neurotypical observers when encoded in point-light displays. Some but not all relevant research shows significant deficits in biological motion perception among those with ASD, especially with respect to emotional displays. We tested adults with and without ASD on the perception of masked biological motion…

Teaching Biology through Statistics: Application of Statistical Methods in Genetics and Zoology Courses

ERIC Educational Resources Information Center

Colon-Berlingeri, Migdalisel; Burrowes, Patricia A.

2011-01-01

Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the…

WE-FG-BRB-00: The Challenges of Predicting RBE Effects in Particle Therapy and Opportunities for Improving Cancer Therapy

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

NONE

The physical pattern of energy deposition and the enhanced relative biological effectiveness (RBE) of protons and carbon ions compared to photons offer unique and not fully understood or exploited opportunities to improve the efficacy of radiation therapy. Variations in RBE within a pristine or spread out Bragg peak and between particle types may be exploited to enhance cell killing in target regions without a corresponding increase in damage to normal tissue structures. In addition, the decreased sensitivity of hypoxic tumors to photon-based therapies may be partially overcome through the use of more densely ionizing radiations. These and other differences betweenmore » particle and photon beams may be used to generate biologically optimized treatments that reduce normal tissue complications. In this symposium, speakers will examine the impact of the RBE of charged particles on measurable biological endpoints, treatment plan optimization, and the prediction or retrospective assessment of treatment outcomes. In particular, an AAPM task group was formed to critically examine the evidence for a spatially-variant RBE in proton therapy. Current knowledge of proton RBE variation with respect to dose, biological endpoint, and physics parameters will be reviewed. Further, the clinical relevance of these variations will be discussed. Recent work focused on improving simulations of radiation physics and biological response in proton and carbon ion therapy will also be presented. Finally, relevant biology research and areas of research needs will be highlighted, including the dependence of RBE on genetic factors including status of DNA repair pathways, the sensitivity of cancer stem-like cells to charged particles, the role of charged particles in hypoxic tumors, and the importance of fractionation effects. In addition to the physical advantages of protons and more massive ions over photons, the future application of biologically optimized treatment plans and their potential to provide higher levels of local tumor control and improved normal tissue sparing will be discussed. Learning Objectives: To assess whether the current practice of a constant RBE of 1.1 should be revised or maintained in proton therapy and to evaluate the potential clinical consequences of delivering RBE-weighted dose distributions based on variable RBE To review current research on biological models used to predict the increased biological effectiveness of proton and carbon ions to help move towards a practical understanding and implementation of biological optimization in particle therapy To discuss potential differences in biological mechanisms between photons and charged particles (light and heavy ions) that could impact clinical cancer therapy H. Paganetti, NCI U19 CA21239D. Grosshans, Our research is supported by the NCIK. Held, Funding Support: National Cancer Institute of the National Institutes of Health, USA, under Award Number R21CA182259 and Federal Share of Program Income Earned by Massachusetts General Hospital on C06CA059267, Proton Therapy Research and Treatment Center.« less

WE-FG-BRB-04: RBEs for Human Lung Cancer Cells Exposed to Protons and Heavier Ions: Implications for Clinical Use of Charged Particles in Cancer Therapy

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

Held, K.

The physical pattern of energy deposition and the enhanced relative biological effectiveness (RBE) of protons and carbon ions compared to photons offer unique and not fully understood or exploited opportunities to improve the efficacy of radiation therapy. Variations in RBE within a pristine or spread out Bragg peak and between particle types may be exploited to enhance cell killing in target regions without a corresponding increase in damage to normal tissue structures. In addition, the decreased sensitivity of hypoxic tumors to photon-based therapies may be partially overcome through the use of more densely ionizing radiations. These and other differences betweenmore » particle and photon beams may be used to generate biologically optimized treatments that reduce normal tissue complications. In this symposium, speakers will examine the impact of the RBE of charged particles on measurable biological endpoints, treatment plan optimization, and the prediction or retrospective assessment of treatment outcomes. In particular, an AAPM task group was formed to critically examine the evidence for a spatially-variant RBE in proton therapy. Current knowledge of proton RBE variation with respect to dose, biological endpoint, and physics parameters will be reviewed. Further, the clinical relevance of these variations will be discussed. Recent work focused on improving simulations of radiation physics and biological response in proton and carbon ion therapy will also be presented. Finally, relevant biology research and areas of research needs will be highlighted, including the dependence of RBE on genetic factors including status of DNA repair pathways, the sensitivity of cancer stem-like cells to charged particles, the role of charged particles in hypoxic tumors, and the importance of fractionation effects. In addition to the physical advantages of protons and more massive ions over photons, the future application of biologically optimized treatment plans and their potential to provide higher levels of local tumor control and improved normal tissue sparing will be discussed. Learning Objectives: To assess whether the current practice of a constant RBE of 1.1 should be revised or maintained in proton therapy and to evaluate the potential clinical consequences of delivering RBE-weighted dose distributions based on variable RBE To review current research on biological models used to predict the increased biological effectiveness of proton and carbon ions to help move towards a practical understanding and implementation of biological optimization in particle therapy To discuss potential differences in biological mechanisms between photons and charged particles (light and heavy ions) that could impact clinical cancer therapy H. Paganetti, NCI U19 CA21239D. Grosshans, Our research is supported by the NCIK. Held, Funding Support: National Cancer Institute of the National Institutes of Health, USA, under Award Number R21CA182259 and Federal Share of Program Income Earned by Massachusetts General Hospital on C06CA059267, Proton Therapy Research and Treatment Center.« less

WE-FG-BRB-02: Spatial Mapping of the RBE of Scanned Particle Beams

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

Grosshans, D.

2016-06-15

The physical pattern of energy deposition and the enhanced relative biological effectiveness (RBE) of protons and carbon ions compared to photons offer unique and not fully understood or exploited opportunities to improve the efficacy of radiation therapy. Variations in RBE within a pristine or spread out Bragg peak and between particle types may be exploited to enhance cell killing in target regions without a corresponding increase in damage to normal tissue structures. In addition, the decreased sensitivity of hypoxic tumors to photon-based therapies may be partially overcome through the use of more densely ionizing radiations. These and other differences betweenmore » particle and photon beams may be used to generate biologically optimized treatments that reduce normal tissue complications. In this symposium, speakers will examine the impact of the RBE of charged particles on measurable biological endpoints, treatment plan optimization, and the prediction or retrospective assessment of treatment outcomes. In particular, an AAPM task group was formed to critically examine the evidence for a spatially-variant RBE in proton therapy. Current knowledge of proton RBE variation with respect to dose, biological endpoint, and physics parameters will be reviewed. Further, the clinical relevance of these variations will be discussed. Recent work focused on improving simulations of radiation physics and biological response in proton and carbon ion therapy will also be presented. Finally, relevant biology research and areas of research needs will be highlighted, including the dependence of RBE on genetic factors including status of DNA repair pathways, the sensitivity of cancer stem-like cells to charged particles, the role of charged particles in hypoxic tumors, and the importance of fractionation effects. In addition to the physical advantages of protons and more massive ions over photons, the future application of biologically optimized treatment plans and their potential to provide higher levels of local tumor control and improved normal tissue sparing will be discussed. Learning Objectives: To assess whether the current practice of a constant RBE of 1.1 should be revised or maintained in proton therapy and to evaluate the potential clinical consequences of delivering RBE-weighted dose distributions based on variable RBE To review current research on biological models used to predict the increased biological effectiveness of proton and carbon ions to help move towards a practical understanding and implementation of biological optimization in particle therapy To discuss potential differences in biological mechanisms between photons and charged particles (light and heavy ions) that could impact clinical cancer therapy H. Paganetti, NCI U19 CA21239D. Grosshans, Our research is supported by the NCIK. Held, Funding Support: National Cancer Institute of the National Institutes of Health, USA, under Award Number R21CA182259 and Federal Share of Program Income Earned by Massachusetts General Hospital on C06CA059267, Proton Therapy Research and Treatment Center.« less

WE-FG-BRB-01: Clinical Significance of RBE Variations in Proton Therapy

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

Paganetti, H.

2016-06-15

The physical pattern of energy deposition and the enhanced relative biological effectiveness (RBE) of protons and carbon ions compared to photons offer unique and not fully understood or exploited opportunities to improve the efficacy of radiation therapy. Variations in RBE within a pristine or spread out Bragg peak and between particle types may be exploited to enhance cell killing in target regions without a corresponding increase in damage to normal tissue structures. In addition, the decreased sensitivity of hypoxic tumors to photon-based therapies may be partially overcome through the use of more densely ionizing radiations. These and other differences betweenmore » particle and photon beams may be used to generate biologically optimized treatments that reduce normal tissue complications. In this symposium, speakers will examine the impact of the RBE of charged particles on measurable biological endpoints, treatment plan optimization, and the prediction or retrospective assessment of treatment outcomes. In particular, an AAPM task group was formed to critically examine the evidence for a spatially-variant RBE in proton therapy. Current knowledge of proton RBE variation with respect to dose, biological endpoint, and physics parameters will be reviewed. Further, the clinical relevance of these variations will be discussed. Recent work focused on improving simulations of radiation physics and biological response in proton and carbon ion therapy will also be presented. Finally, relevant biology research and areas of research needs will be highlighted, including the dependence of RBE on genetic factors including status of DNA repair pathways, the sensitivity of cancer stem-like cells to charged particles, the role of charged particles in hypoxic tumors, and the importance of fractionation effects. In addition to the physical advantages of protons and more massive ions over photons, the future application of biologically optimized treatment plans and their potential to provide higher levels of local tumor control and improved normal tissue sparing will be discussed. Learning Objectives: To assess whether the current practice of a constant RBE of 1.1 should be revised or maintained in proton therapy and to evaluate the potential clinical consequences of delivering RBE-weighted dose distributions based on variable RBE To review current research on biological models used to predict the increased biological effectiveness of proton and carbon ions to help move towards a practical understanding and implementation of biological optimization in particle therapy To discuss potential differences in biological mechanisms between photons and charged particles (light and heavy ions) that could impact clinical cancer therapy H. Paganetti, NCI U19 CA21239D. Grosshans, Our research is supported by the NCIK. Held, Funding Support: National Cancer Institute of the National Institutes of Health, USA, under Award Number R21CA182259 and Federal Share of Program Income Earned by Massachusetts General Hospital on C06CA059267, Proton Therapy Research and Treatment Center.« less

Focus issue: series on computational and systems biology.

PubMed

Gough, Nancy R

2011-09-06

The application of computational biology and systems biology is yielding quantitative insight into cellular regulatory phenomena. For the month of September, Science Signaling highlights research featuring computational approaches to understanding cell signaling and investigation of signaling networks, a series of Teaching Resources from a course in systems biology, and various other articles and resources relevant to the application of computational biology and systems biology to the study of signal transduction.

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

PubMed

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

2014-01-15

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

Severe impingement of lumbar disc replacements increases the functional biological activity of polyethylene wear debris.

PubMed

Baxter, Ryan M; Macdonald, Daniel W; Kurtz, Steven M; Steinbeck, Marla J

2013-06-05

Wear, oxidation, and particularly rim impingement damage of ultra-high molecular weight polyethylene total disc replacement components have been observed following surgical revision. However, neither in vitro testing nor retrieval-based evidence has shown the effect(s) of impingement on the characteristics of polyethylene wear debris. Thus, we sought to determine (1) differences in polyethylene particle size, shape, number, or biological activity that correspond to mild or severe rim impingement and (2) in an analysis of all total disc replacements, regardless of impingement classification, whether there are correlations between the extent of regional damage and the characteristics of polyethylene wear debris. The extent of dome and rim damage was characterized for eleven retrieved polyethylene cores obtained at revision surgery after an average duration of implantation of 9.7 years (range, 4.6 to 16.1 years). Polyethylene wear debris was isolated from periprosthetic tissues with use of nitric acid and was imaged with use of environmental scanning electron microscopy. Subsequently, particle size, shape, number, biological activity, and chronic inflammation scores were determined. Grouping of particles by size ranges that represented high biological relevance (<0.1 to 1-μm particles), intermediate biological relevance (1 to 10-μm particles), and low biological relevance (>10-μm particles) revealed an increased volume fraction of particles in the <0.1 to 1-μm and 1 to 10-μm size ranges in the mild-impingement cohort as compared with the severe-impingement cohort. The increased volume fractions resulted in a higher specific biological activity per unit particle volume in the mild-impingement cohort than in the severe-impingement cohort. However, functional biological activity, which is normalized by particle volume (mm3/g of tissue), was significantly higher in the severe-impingement cohort. This increase was due to a larger volume of particles in all three size ranges. In both cohorts, the functional biological activity correlated with the chronic inflammatory response, and the extent of rim penetration positively correlated with increasing particle size, number, and functional biological activity. The results of this study suggest that severe rim impingement increases the production of biologically relevant particles from motion-preserving lumbar total disc replacement components. Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Severe Impingement of Lumbar Disc Replacements Increases the Functional Biological Activity of Polyethylene Wear Debris

PubMed Central

Baxter, Ryan M.; MacDonald, Daniel W.; Kurtz, Steven M.; Steinbeck, Marla J.

2013-01-01

Background: Wear, oxidation, and particularly rim impingement damage of ultra-high molecular weight polyethylene total disc replacement components have been observed following surgical revision. However, neither in vitro testing nor retrieval-based evidence has shown the effect(s) of impingement on the characteristics of polyethylene wear debris. Thus, we sought to determine (1) differences in polyethylene particle size, shape, number, or biological activity that correspond to mild or severe rim impingement and (2) in an analysis of all total disc replacements, regardless of impingement classification, whether there are correlations between the extent of regional damage and the characteristics of polyethylene wear debris. Methods: The extent of dome and rim damage was characterized for eleven retrieved polyethylene cores obtained at revision surgery after an average duration of implantation of 9.7 years (range, 4.6 to 16.1 years). Polyethylene wear debris was isolated from periprosthetic tissues with use of nitric acid and was imaged with use of environmental scanning electron microscopy. Subsequently, particle size, shape, number, biological activity, and chronic inflammation scores were determined. Results: Grouping of particles by size ranges that represented high biological relevance (<0.1 to 1-μm particles), intermediate biological relevance (1 to 10-μm particles), and low biological relevance (>10-μm particles) revealed an increased volume fraction of particles in the <0.1 to 1-μm and 1 to 10-μm size ranges in the mild-impingement cohort as compared with the severe-impingement cohort. The increased volume fractions resulted in a higher specific biological activity per unit particle volume in the mild-impingement cohort than in the severe-impingement cohort. However, functional biological activity, which is normalized by particle volume (mm3/g of tissue), was significantly higher in the severe-impingement cohort. This increase was due to a larger volume of particles in all three size ranges. In both cohorts, the functional biological activity correlated with the chronic inflammatory response, and the extent of rim penetration positively correlated with increasing particle size, number, and functional biological activity. Conclusions: The results of this study suggest that severe rim impingement increases the production of biologically relevant particles from motion-preserving lumbar total disc replacement components. Level of Evidence: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence. PMID:23780545

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

PubMed

Sumner, T; Shephard, E; Bogle, I D L

2012-09-07

One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.

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

PubMed Central

Sun, Xiaodian; Jin, Li; Xiong, Momiao

2008-01-01

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

Oxidative DNA damage background estimated by a system model of base excision repair

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

Sokhansanj, B A; Wilson, III, D M

Human DNA can be damaged by natural metabolism through free radical production. It has been suggested that the equilibrium between innate damage and cellular DNA repair results in an oxidative DNA damage background that potentially contributes to disease and aging. Efforts to quantitatively characterize the human oxidative DNA damage background level based on measuring 8-oxoguanine lesions as a biomarker have led to estimates varying over 3-4 orders of magnitude, depending on the method of measurement. We applied a previously developed and validated quantitative pathway model of human DNA base excision repair, integrating experimentally determined endogenous damage rates and model parametersmore » from multiple sources. Our estimates of at most 100 8-oxoguanine lesions per cell are consistent with the low end of data from biochemical and cell biology experiments, a result robust to model limitations and parameter variation. Our results show the power of quantitative system modeling to interpret composite experimental data and make biologically and physiologically relevant predictions for complex human DNA repair pathway mechanisms and capacity.« less

Synthetic control of a fitness tradeoff in yeast nitrogen metabolism

PubMed Central

Bayer, Travis S; Hoff, Kevin G; Beisel, Chase L; Lee, Jack J; Smolke, Christina D

2009-01-01

Background Microbial communities are involved in many processes relevant to industrial and medical biotechnology, such as the formation of biofilms, lignocellulosic degradation, and hydrogen production. The manipulation of synthetic and natural microbial communities and their underlying ecological parameters, such as fitness, evolvability, and variation, is an increasingly important area of research for synthetic biology. Results Here, we explored how synthetic control of an endogenous circuit can be used to regulate a tradeoff between fitness in resource abundant and resource limited environments in a population of Saccharomyces cerevisiae. We found that noise in the expression of a key enzyme in ammonia assimilation, Gdh1p, mediated a tradeoff between growth in low nitrogen environments and stress resistance in high ammonia environments. We implemented synthetic control of an endogenous Gdh1p regulatory network to construct an engineered strain in which the fitness of the population was tunable in response to an exogenously-added small molecule across a range of ammonia environments. Conclusion The ability to tune fitness and biological tradeoffs will be important components of future efforts to engineer microbial communities. PMID:19118500

Slide Set: Reproducible image analysis and batch processing with ImageJ.

PubMed

Nanes, Benjamin A

2015-11-01

Most imaging studies in the biological sciences rely on analyses that are relatively simple. However, manual repetition of analysis tasks across multiple regions in many images can complicate even the simplest analysis, making record keeping difficult, increasing the potential for error, and limiting reproducibility. While fully automated solutions are necessary for very large data sets, they are sometimes impractical for the small- and medium-sized data sets common in biology. Here we present the Slide Set plugin for ImageJ, which provides a framework for reproducible image analysis and batch processing. Slide Set organizes data into tables, associating image files with regions of interest and other relevant information. Analysis commands are automatically repeated over each image in the data set, and multiple commands can be chained together for more complex analysis tasks. All analysis parameters are saved, ensuring transparency and reproducibility. Slide Set includes a variety of built-in analysis commands and can be easily extended to automate other ImageJ plugins, reducing the manual repetition of image analysis without the set-up effort or programming expertise required for a fully automated solution.

Operation and model description of a sequencing batch reactor treating reject water for biological nitrogen removal via nitrite.

PubMed

Dosta, J; Galí, A; Benabdallah El-Hadj, T; Macé, S; Mata-Alvarez, J

2007-08-01

The aim of this study was the operation and model description of a sequencing batch reactor (SBR) for biological nitrogen removal (BNR) from a reject water (800-900 mg NH(4)(+)-NL(-1)) from a municipal wastewater treatment plant (WWTP). The SBR was operated with three cycles per day, temperature 30 degrees C, SRT 11 days and HRT 1 day. During the operational cycle, three alternating oxic/anoxic periods were performed to avoid alkalinity restrictions. Oxygen supply and working pH range were controlled to achieve the BNR via nitrite, which makes the process more economical. Under steady state conditions, a total nitrogen removal of 0.87 kg N (m(3)day)(-1) was reached. A four-step nitrogen removal model was developed to describe the process. This model enlarges the IWA activated sludge models for a more detailed description of the nitrogen elimination processes and their inhibitions. A closed intermittent-flow respirometer was set up for the estimation of the most relevant model parameters. Once calibrated, model predictions reproduced experimental data accurately.

Development of water quality thresholds during dredging for the protection of benthic primary producer habitats.

PubMed

Sofonia, Jeremy J; Unsworth, Richard K F

2010-01-01

Given the potential for adverse effects of ocean dredging on marine organisms, particularly benthic primary producer communities, the management and monitoring of those activities which cause elevated turbidity and sediment loading is critical. In practice, however, this has proven challenging as the development of water quality threshold values, upon which management responses are based, are subject to a large number of physical and biological parameters that are spatially and temporally specific. As a consequence, monitoring programs to date have taken a wide range of different approaches, most focusing on measures of turbidity reported as nephelometric turbidity units (NTU). This paper presents a potential approach in the determination of water quality thresholds which utilises data gathered through the long-term deployment of in situ water instruments, but suggests a focus on photosynthetic active radiation (PAR) rather than NTU as it is more relevant biologically and inclusive of other site conditions. A simple mathematical approach to data interpretation is also presented which facilitates threshold value development, not individual values of concentrations over specific intervals, but as an equation which may be utilized in numerical modelling.

Design, Development, and Psychometric Analysis of a General, Organic, and Biological Chemistry Topic Inventory Based on the Identified Main Chemistry Topics Relevant to Nursing Clinical Practice

ERIC Educational Resources Information Center

Brown, Corina E.

2013-01-01

This two-stage study focused on the undergraduate nursing course that covers topics in general, organic, and biological (GOB) chemistry. In the first stage, the central objective was to identify the main concepts of GOB chemistry relevant to the clinical practice of nursing. The collection of data was based on open-ended interviews of both nursing…

Lateral Hypothalamus GABAergic Neurons Modulate Consummatory Behaviors Regardless of the Caloric Content or Biological Relevance of the Consumed Stimuli.

PubMed

Navarro, Montserrat; Olney, Jeffrey J; Burnham, Nathan W; Mazzone, Christopher M; Lowery-Gionta, Emily G; Pleil, Kristen E; Kash, Thomas L; Thiele, Todd E

2016-05-01

It was recently reported that activation of a subset of lateral hypothalamus (LH) GABAergic neurons induced both appetitive (food-seeking) and consummatory (eating) behaviors in vGat-ires-cre mice, while inhibition or deletion of GABAergic neurons blunted these behaviors. As food and caloric-dense liquid solutions were used, the data reported suggest that these LH GABAergic neurons may modulate behaviors that function to maintain homeostatic caloric balance. Here we report that chemogenetic activation of this GABAergic population in vGat-ires-cre mice increased consummatory behavior directed at any available stimulus, including those entailing calories (food, sucrose, and ethanol), those that do not (saccharin and water), and those lacking biological relevance (wood). Chemogenetic inhibition of these neurons attenuated consummatory behaviors. These data indicate that LH GABAergic neurons modulate consummatory behaviors regardless of the caloric content or biological relevance of the consumed stimuli.

Relevance in the science classroom: A multidimensional analysis

NASA Astrophysics Data System (ADS)

Hartwell, Matthew F.

While perceived relevance is considered a fundamental component of adaptive learning, the experience of relevance and its conceptual definition have not been well described. The mixed-methods research presented in this dissertation aimed to clarify the conceptual meaning of relevance by focusing on its phenomenological experience from the students' perspective. Following a critical literature review, I propose an identity-based model of perceived relevance that includes three components: a contextual target, an identity target, and a connection type, or lens. An empirical investigation of this model that consisted of two general phases was implemented in four 9th grade-biology classrooms. Participants in Phase 1 (N = 118) completed a series of four open-ended writing activities focused on eliciting perceived personal connections to academic content. Exploratory qualitative content analysis of a 25% random sample of the student responses was used to identify the main meaning-units of the proposed model as well as different dimensions of student relevance perceptions. These meaning-units and dimensions provided the basis for the construction of a conceptual mapping sentence capturing students' perceived relevance, which was then applied in a confirmatory analysis to all other student responses. Participants in Phase 2 (N = 139) completed a closed survey designed based on the mapping sentence to assess their perceived relevance of a biology unit. The survey also included scales assessing other domain-level motivational processes. Exploratory factor analysis and non-metric multidimensional scaling indicated a coherent conceptual structure, which included a primary interpretive relevance dimension. Comparison of the conceptual structure across various groups (randomly-split sample, gender, academic level, domain-general motivational profiles) provided support for its ubiquity and insight into variation in the experience of perceived relevance among students of different groups. The findings combine to support a multidimensional perspective of relevance in the 9th grade biology classroom; offering researchers a useful model for future investigation and educators with insights into the students' classroom experience.

Recent developments on ultrasound-assisted one-pot multicomponent synthesis of biologically relevant heterocycles.

PubMed

Banerjee, Bubun

2017-03-01

Heterocycles are the backbone of organic compounds. Specially, N- &O-containing heterocycles represent privileged structural subunits well distributed in naturally occurring compounds with immense biological activities. Multicomponent reactions (MCRs) are becoming valuable tool for synthesizing structurally diverse molecular entities. On the other hand, the last decade has seen a tremendous outburst in modifying chemical processes to make them sustainable for the betterment of our environment. The application of ultrasound in organic synthesis is fulfilling some of the goals of 'green and sustainable chemistry' as it has some advantages over the traditional thermal methods in terms of reaction rates, yields, purity of the products, product selectivity, etc. Therefore the synthesis of biologically relevant heterocycles using one-pot multi-component technique coupled with the application of ultrasound is one of the thrusting areas in the 21st Century among the organic chemists. The present review deals with the "up to date" developments on ultrasound assisted one-pot multi-component synthesis of biologically relevant heterocycles reported so far. Copyright © 2016 Elsevier B.V. All rights reserved.

Visualising associations between paired ‘omics’ data sets

PubMed Central

2012-01-01

Background Each omics platform is now able to generate a large amount of data. Genomics, proteomics, metabolomics, interactomics are compiled at an ever increasing pace and now form a core part of the fundamental systems biology framework. Recently, several integrative approaches have been proposed to extract meaningful information. However, these approaches lack of visualisation outputs to fully unravel the complex associations between different biological entities. Results The multivariate statistical approaches ‘regularized Canonical Correlation Analysis’ and ‘sparse Partial Least Squares regression’ were recently developed to integrate two types of highly dimensional ‘omics’ data and to select relevant information. Using the results of these methods, we propose to revisit few graphical outputs to better understand the relationships between two ‘omics’ data and to better visualise the correlation structure between the different biological entities. These graphical outputs include Correlation Circle plots, Relevance Networks and Clustered Image Maps. We demonstrate the usefulness of such graphical outputs on several biological data sets and further assess their biological relevance using gene ontology analysis. Conclusions Such graphical outputs are undoubtedly useful to aid the interpretation of these promising integrative analysis tools and will certainly help in addressing fundamental biological questions and understanding systems as a whole. Availability The graphical tools described in this paper are implemented in the freely available R package mixOmics and in its associated web application. PMID:23148523

Biomonitoring and risk assessment on earth and during exploratory missions using AquaHab ®

NASA Astrophysics Data System (ADS)

Slenzka, K.; Dünne, M.; Jastorff, B.

2008-12-01

Bioregenerative closed ecological life support systems (CELSS) will be necessary in the exploration context revitalizing atmosphere, waste water and producing food for the human CELSS mates. During these long-term space travels and stays far away from Earth in an hostile environment as well as far for example from any hospital and surgery potential, it will be necessary to know much more about chemical and drug contamination in the special sense and by human's themselves in detail. Additionally, there is a strong need on Earth for more relevant standardized test systems including aquatic ones for the prospective risk assessment of chemicals and drugs in general on a laboratory scale. Current standardized test systems are mono species tests, and thus do not represent system aspects and have reduced environmental relevance. The experience gained during the last years in our research group lead to the development of a self-sustaining closed aquatic habitat/facility, called AquaHab ® which can serve regarding space exploration and Earth application. The AquaHab ® module can be the home of several fish species, snails, plants, amphipods and bacteria. The possibility to use different effect endpoints with certain beneficial characteristics is the basis for the application of AquaHab ® in different fields. Influence of drugs and chemicals can be tested on several trophic levels and ecosystem levels; guaranteeing a high relevance for aquatic systems in the real environment. Analyses of effect parameters of different complexity (e.g. general biological and water chemical parameters, activity of biotransforming enzymes) result in broad spectra of sensitivity. Combined with residual analyses (including all metabolites), this leads to an extended prospective risk assessment of a chemical on Earth and in a closed Life Support System. The possibility to measure also sensitive "online" parameters (e.g. behavior, respiration/photosynthetic activity) enables a quick and sensitive effect analysis of water contaminants in respective environments. AquaHab ® is currently under development to an early warning biomonitoring system using genetically modified fish and green algae. The implementation of biosensors/biochip in addition is also discussed.

Conservation biology in Asia: the major policy challenges.

PubMed

McNeely, Jeffrey A; Kapoor-Vijay, Promila; Zhi, Lu; Olsvig-Whittaker, Linda; Sheikh, Kashif M; Smith, Andrew T

2009-08-01

With about half the world's human population and booming economies, Asia faces numerous challenges to its biodiversity. The Asia Section of the Society for Conservation Biology has identified some key policy issues in which significant progress can be made. These include developing new sources of funding for forest conservation; identifying potential impacts of energy alternatives on the conservation of biodiversity; curbing the trade in endangered species of plants and animals; a special focus on the conservation of mountain biodiversity; enhancing relevant research; ensuring that conservation biology contributes to major international conventions and funding mechanisms; using conservation biology to build a better understanding of zoonotic diseases; more effectively addressing human-animal conflicts; enhancing community-based conservation; and using conservation biology to help address the pervasive water-deficit problems in much of Asia. These challenges can be met through improved regional cooperation among the relevant stakeholders.

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

PubMed

André, J P; Mäcke, H R

2003-12-01

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

Urokinase-receptor (u-PAR): an essential player in multiple games of cancer: a review on its role in tumor progression, invasion, metastasis, proliferation/dormancy, clinical outcome and minimal residual disease.

PubMed

Laufs, Stephanie; Schumacher, Jens; Allgayer, Heike

2006-08-01

The relevance of the u-PA system in mediating tumor-associated proteolysis, invasion and metastasis, amongst other phenomena associated with tumor progression, has been clearly demonstrated in diverse cancer entities. This review will update on the biological and clinical relevance of the urokinase-receptor (u-PAR). Specifically, the article focuses on the potential importance of u-PAR for the development of minimal residual disease in solid cancer, and in this context reviews the biological relevance of the u-PAR for tumor cell dormancy. Furthermore, transcriptional mechanisms regulating u-PAR in vitro and in vivo, and their potential clinical and therapeutic relevance in gastrointestinal cancers, are elucidated.

Bioinformatics and School Biology

ERIC Educational Resources Information Center

Dalpech, Roger

2006-01-01

The rapidly changing field of bioinformatics is fuelling the need for suitably trained personnel with skills in relevant biological "sub-disciplines" such as proteomics, transcriptomics and metabolomics, etc. But because of the complexity--and sheer weight of data--associated with these new areas of biology, many school teachers feel…

Exemplary Programs in Secondary School Biology.

ERIC Educational Resources Information Center

McComas, William F.; Penick, John E.

1989-01-01

Summarizes 10 exemplary programs which address topics on individualized biology, a modified team approach, limnology, physical anthropology, the relevance of biology to society, ecology, and health. Provides names and addresses of contact persons for further information. Units cover a broad range of abilities and activities. (RT)

Identifying relevant data for a biological database: handcrafted rules versus machine learning.

PubMed

Sehgal, Aditya Kumar; Das, Sanmay; Noto, Keith; Saier, Milton H; Elkan, Charles

2011-01-01

With well over 1,000 specialized biological databases in use today, the task of automatically identifying novel, relevant data for such databases is increasingly important. In this paper, we describe practical machine learning approaches for identifying MEDLINE documents and Swiss-Prot/TrEMBL protein records, for incorporation into a specialized biological database of transport proteins named TCDB. We show that both learning approaches outperform rules created by hand by a human expert. As one of the first case studies involving two different approaches to updating a deployed database, both the methods compared and the results will be of interest to curators of many specialized databases.

A Road Less Traveled By: Exploring a Decade of Ellman Chemistry

PubMed Central

Shelat, Anang A.; Guy, R. Kiplin

2009-01-01

The Ellman group has been one of the most influential in the development and widespread adoption of combinatorial chemistry techniques for biomedical research. Their work has included substantial methodological development for library synthesis with a particular focus on new scaffolds rationally targeted to biomolecules of interest and biologically relevant natural products. Herein we analyze a representative set of libraries from this group with respect to their biological and biomedical relevance in comparison to existing drugs and probe compounds. This analysis reveals that the Ellman group has not only provided new methodologies to the community but also provided libraries with unique potential for further biological study. PMID:18343129

Bridging Physics and Biology Using Resistance and Axons

ERIC Educational Resources Information Center

Dyer, Joshua M.

2014-01-01

When teaching physics, it is often difficult to get biology-oriented students to see the relevance of physics. A complaint often heard is that biology students are required to take physics for the Medical College Admission Test (MCAT) as part of a "weeding out" process, but that they don't feel like they need physics for biology. Despite…

Making Research Fly in Schools: "Drosophila" as a Powerful Modern Tool for Teaching Biology

ERIC Educational Resources Information Center

Harbottle, Jennifer; Strangward, Patrick; Alnuamaani, Catherine; Lawes, Surita; Patel, Sanjai; Prokop, Andreas

2016-01-01

The "droso4schools" project aims to introduce the fruit fly "Drosophila" as a powerful modern teaching tool to convey curriculum-relevant specifications in biology lessons. Flies are easy and cheap to breed and have been at the forefront of biology research for a century, providing unique conceptual understanding of biology and…

A versatile mathematical work-flow to explore how Cancer Stem Cell fate influences tumor progression.

PubMed

Fornari, Chiara; Balbo, Gianfranco; Halawani, Sami M; Ba-Rukab, Omar; Ahmad, Ab Rahman; Calogero, Raffaele A; Cordero, Francesca; Beccuti, Marco

2015-01-01

Nowadays multidisciplinary approaches combining mathematical models with experimental assays are becoming relevant for the study of biological systems. Indeed, in cancer research multidisciplinary approaches are successfully used to understand the crucial aspects implicated in tumor growth. In particular, the Cancer Stem Cell (CSC) biology represents an area particularly suited to be studied through multidisciplinary approaches, and modeling has significantly contributed to pinpoint the crucial aspects implicated in this theory. More generally, to acquire new insights on a biological system it is necessary to have an accurate description of the phenomenon, such that making accurate predictions on its future behaviors becomes more likely. In this context, the identification of the parameters influencing model dynamics can be advantageous to increase model accuracy and to provide hints in designing wet experiments. Different techniques, ranging from statistical methods to analytical studies, have been developed. Their applications depend on case-specific aspects, such as the availability and quality of experimental data, and the dimension of the parameter space. The study of a new model on the CSC-based tumor progression has been the motivation to design a new work-flow that helps to characterize possible system dynamics and to identify those parameters influencing such behaviors. In detail, we extended our recent model on CSC-dynamics creating a new system capable of describing tumor growth during the different stages of cancer progression. Indeed, tumor cells appear to progress through lineage stages like those of normal tissues, being their division auto-regulated by internal feedback mechanisms. These new features have introduced some non-linearities in the model, making it more difficult to be studied by solely analytical techniques. Our new work-flow, based on statistical methods, was used to identify the parameters which influence the tumor growth. The effectiveness of the presented work-flow was firstly verified on two well known models and then applied to investigate our extended CSC model. We propose a new work-flow to study in a practical and informative way complex systems, allowing an easy identification, interpretation, and visualization of the key model parameters. Our methodology is useful to investigate possible model behaviors and to establish factors driving model dynamics. Analyzing our new CSC model guided by the proposed work-flow, we found that the deregulation of CSC asymmetric proliferation contributes to cancer initiation, in accordance with several experimental evidences. Specifically, model results indicated that the probability of CSC symmetric proliferation is responsible of a switching-like behavior which discriminates between tumorigenesis and unsustainable tumor growth.

Parameter estimation of qubit states with unknown phase parameter

NASA Astrophysics Data System (ADS)

Suzuki, Jun

2015-02-01

We discuss a problem of parameter estimation for quantum two-level system, qubit system, in presence of unknown phase parameter. We analyze trade-off relations for mean square errors (MSEs) when estimating relevant parameters with separable measurements based on known precision bounds; the symmetric logarithmic derivative (SLD) Cramér-Rao (CR) bound and Hayashi-Gill-Massar (HGM) bound. We investigate the optimal measurement which attains the HGM bound and discuss its properties. We show that the HGM bound for relevant parameters can be attained asymptotically by using some fraction of given n quantum states to estimate the phase parameter. We also discuss the Holevo bound which can be attained asymptotically by a collective measurement.

Membrane tension: A challenging but universal physical parameter in cell biology.

PubMed

Pontes, Bruno; Monzo, Pascale; Gauthier, Nils C

2017-11-01

The plasma membrane separates the interior of cells from the outside environment. The membrane tension, defined as the force per unit length acting on a cross-section of membrane, regulates many vital biological processes. In this review, we summarize the first historical findings and the latest advances, showing membrane tension as an important physical parameter in cell biology. We also discuss how this parameter must be better integrated and we propose experimental approaches for key unanswered questions. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Dispersion Behaviour of Silica Nanoparticles in Biological Media and Its Influence on Cellular Uptake.

PubMed

Halamoda-Kenzaoui, Blanka; Ceridono, Mara; Colpo, Pascal; Valsesia, Andrea; Urbán, Patricia; Ojea-Jiménez, Isaac; Gioria, Sabrina; Gilliland, Douglas; Rossi, François; Kinsner-Ovaskainen, Agnieszka

2015-01-01

Given the increasing variety of manufactured nanomaterials, suitable, robust, standardized in vitro screening methods are needed to study the mechanisms by which they can interact with biological systems. The in vitro evaluation of interactions of nanoparticles (NPs) with living cells is challenging due to the complex behaviour of NPs, which may involve dissolution, aggregation, sedimentation and formation of a protein corona. These variable parameters have an influence on the surface properties and the stability of NPs in the biological environment and therefore also on the interaction of NPs with cells. We present here a study using 30 nm and 80 nm fluorescently-labelled silicon dioxide NPs (Rubipy-SiO2 NPs) to evaluate the NPs dispersion behaviour up to 48 hours in two different cellular media either supplemented with 10% of serum or in serum-free conditions. Size-dependent differences in dispersion behaviour were observed and the influence of the living cells on NPs stability and deposition was determined. Using flow cytometry and fluorescence microscopy techniques we studied the kinetics of the cellular uptake of Rubipy-SiO2 NPs by A549 and CaCo-2 cells and we found a correlation between the NPs characteristics in cell media and the amount of cellular uptake. Our results emphasize how relevant and important it is to evaluate and to monitor the size and agglomeration state of nanoparticles in the biological medium, in order to interpret correctly the results of the in vitro toxicological assays.

Dispersion Behaviour of Silica Nanoparticles in Biological Media and Its Influence on Cellular Uptake

PubMed Central

Halamoda-Kenzaoui, Blanka; Ceridono, Mara; Colpo, Pascal; Valsesia, Andrea; Urbán, Patricia; Ojea-Jiménez, Isaac; Gioria, Sabrina; Gilliland, Douglas; Rossi, François; Kinsner-Ovaskainen, Agnieszka

2015-01-01

Given the increasing variety of manufactured nanomaterials, suitable, robust, standardized in vitro screening methods are needed to study the mechanisms by which they can interact with biological systems. The in vitro evaluation of interactions of nanoparticles (NPs) with living cells is challenging due to the complex behaviour of NPs, which may involve dissolution, aggregation, sedimentation and formation of a protein corona. These variable parameters have an influence on the surface properties and the stability of NPs in the biological environment and therefore also on the interaction of NPs with cells. We present here a study using 30 nm and 80 nm fluorescently-labelled silicon dioxide NPs (Rubipy-SiO2 NPs) to evaluate the NPs dispersion behaviour up to 48 hours in two different cellular media either supplemented with 10% of serum or in serum-free conditions. Size-dependent differences in dispersion behaviour were observed and the influence of the living cells on NPs stability and deposition was determined. Using flow cytometry and fluorescence microscopy techniques we studied the kinetics of the cellular uptake of Rubipy-SiO2 NPs by A549 and CaCo-2 cells and we found a correlation between the NPs characteristics in cell media and the amount of cellular uptake. Our results emphasize how relevant and important it is to evaluate and to monitor the size and agglomeration state of nanoparticles in the biological medium, in order to interpret correctly the results of the in vitro toxicological assays. PMID:26517371

Impact of processing parameters on the haemocompatibility of Bombyx mori silk films.

PubMed

Seib, F Philipp; Maitz, Manfred F; Hu, Xiao; Werner, Carsten; Kaplan, David L

2012-02-01

Silk has traditionally been used for surgical sutures due to its lasting strength and durability; however, the use of purified silk proteins as a scaffold material for vascular tissue engineering goes beyond traditional use and requires application-orientated biocompatibility testing. For this study, a library of Bombyx mori silk films was generated and exposed to various solvents and treatment conditions to reflect current silk processing techniques. The films, along with clinically relevant reference materials, were exposed to human whole blood to determine silk blood compatibility. All substrates showed an initial inflammatory response comparable to polylactide-co-glycolide (PLGA), and a low to moderate haemostasis response similar to polytetrafluoroethylene (PTFE) substrates. In particular, samples that were water annealed at 25 °C for 6 h demonstrated the best blood compatibility based on haemostasis parameters (e.g. platelet decay, thrombin-antithrombin complex, platelet factor 4, granulocytes-platelet conjugates) and inflammatory parameters (e.g. C3b, C5a, CD11b, surface-associated leukocytes). Multiple factors such as treatment temperature and solvent influenced the biological response, though no single physical parameter such as β-sheet content, isoelectric point or contact angle accurately predicted blood compatibility. These findings, when combined with prior in vivo data on silk, support a viable future for silk-based vascular grafts. Copyright © 2011 Elsevier Ltd. All rights reserved.

General two-species interacting Lotka-Volterra system: Population dynamics and wave propagation

NASA Astrophysics Data System (ADS)

Zhu, Haoqi; Wang, Mao-Xiang; Lai, Pik-Yin

2018-05-01

The population dynamics of two interacting species modeled by the Lotka-Volterra (LV) model with general parameters that can promote or suppress the other species is studied. It is found that the properties of the two species' isoclines determine the interaction of species, leading to six regimes in the phase diagram of interspecies interaction; i.e., there are six different interspecific relationships described by the LV model. Four regimes allow for nontrivial species coexistence, among which it is found that three of them are stable, namely, weak competition, mutualism, and predator-prey scenarios can lead to win-win coexistence situations. The Lyapunov function for general nontrivial two-species coexistence is also constructed. Furthermore, in the presence of spatial diffusion of the species, the dynamics can lead to steady wavefront propagation and can alter the population map. Propagating wavefront solutions in one dimension are investigated analytically and by numerical solutions. The steady wavefront speeds are obtained analytically via nonlinear dynamics analysis and verified by numerical solutions. In addition to the inter- and intraspecific interaction parameters, the intrinsic speed parameters of each species play a decisive role in species populations and wave properties. In some regimes, both species can copropagate with the same wave speeds in a finite range of parameters. Our results are further discussed in the light of possible biological relevance and ecological implications.

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.

Physico-chemical and biological characterization of urban municipal landfill leachate.

PubMed

Naveen, B P; Mahapatra, Durga Madhab; Sitharam, T G; Sivapullaiah, P V; Ramachandra, T V

2017-01-01

Unscientific management and ad-hoc approaches in municipal solid waste management have led to a generation of voluminous leachate in urban conglomerates. Quantification, quality assessment, following treatment and management of leachate has become a serious problem worldwide. In this context, the present study investigates the physico-chemical and biological characterization of landfill leachate and nearby water sources and attempts to identify relationships between the key parameters together with understanding the various processes for chemical transformations. The analysis shows an intermediate leachate age (5-10 years) with higher nutrient levels of 10,000-12,000 mg/l and ∼2000-3000 mg/l of carbon (COD) and nitrogen (TKN) respectively. Elemental analysis and underlying mechanisms reveal chemical precipitation and co-precipitation as the vital processes in leachate pond systems resulting in accumulation of trace metals. Based on the above criteria the samples were clustered into major groups that showed a clear distinction between leachate and water bodies. The microbial analysis showed bacterial communities correlating with specific factors relevant to redox environments indicating a gradient in nature and abundance of biotic diversity with a change in leachate environment. Finally, the quality and the contamination potential of the samples were evaluated with the help of leachate pollution index (LPI) and water quality index (WQI) analysis. The study helps in understanding the contamination potential of landfill leachate and establishes linkages between microbial communities and physico-chemical parameters for effective management of landfill leachate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integrating sphere-based photoacoustic setup for simultaneous absorption coefficient and Grüneisen parameter measurements of biomedical liquids

NASA Astrophysics Data System (ADS)

Villanueva, Yolanda; Hondebrink, Erwin; Petersen, Wilma; Steenbergen, Wiendelt

2015-03-01

A method for simultaneously measuring the absorption coefficient μa and Grüneisen parameter Γ of biological absorbers in photoacoustics is designed and implemented using a coupled-integrating sphere system. A soft transparent tube with inner diameter of 0.58mm is used to mount the liquid absorbing sample horizontally through the cavity of two similar and adjacent integrating spheres. One sphere is used for measuring the sample's μa using a continuous halogen light source and a spectrometer fiber coupled to the input and output ports, respectively. The other sphere is used for simultaneous photoacoustic measurement of the sample's Γ using an incident pulsed light with wavelength of 750nm and a flat transducer with central frequency of 5MHz. Absolute optical energy and pressure measurements are not necessary. However, the derived equations for determining the sample's μa and Γ require calibration of the setup using aqueous ink dilutions. Initial measurements are done with biological samples relevant to biomedical imaging such as human whole blood, joint and cyst fluids. Absorption of joint and cyst fluids is enhanced using a contrast agent like aqueous indocyanine green dye solution. For blood sample, measured values of μa = 0.580 +/- 0.016 mm-1 and Γ = 0.166 +/- 0.006 are within the range of values reported in literature. Measurements with the absorbing joint and cyst fluid samples give Γ values close to 0.12, which is similar to that of water and plasma.

A rigidity transition and glassy dynamics in a model for confluent 3D tissues

NASA Astrophysics Data System (ADS)

Merkel, Matthias; Manning, M. Lisa

The origin of rigidity in disordered materials is an outstanding open problem in statistical physics. Recently, a new type of rigidity transition was discovered in a family of models for 2D biological tissues, but the mechanisms responsible for rigidity remain unclear. This is not just a statistical physics problem, but also relevant for embryonic development, cancer growth, and wound healing. To gain insight into this rigidity transition and make new predictions about biological bulk tissues, we have developed a fully 3D self-propelled Voronoi (SPV) model. The model takes into account shape, elasticity, and self-propelled motion of the individual cells. We find that in the absence of self-propulsion, this model exhibits a rigidity transition that is controlled by a dimensionless model parameter describing the preferred cell shape, with an accompanying structural order parameter. In the presence of self-propulsion, the rigidity transition appears as a glass-like transition featuring caging and aging effects. Given the similarities between this transition and jamming in particulate solids, it is natural to ask if the two transitions are related. By comparing statistics of Voronoi geometries, we show the transitions are surprisingly close but demonstrably distinct. Furthermore, an index theorem used to identify topologically protected mechanical modes in jammed systems can be extended to these vertex-type models. In our model, residual stresses govern the transition and enter the index theorem in a different way compared to jammed particles, suggesting the origin of rigidity may be different between the two.

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

NASA Technical Reports Server (NTRS)

Rosing, L. M.

1976-01-01

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

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

PubMed

Sgrignani, Jacopo; Magistrato, Alessandra

2013-03-01

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

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.

Self-Relevance Constructions of Biology Concepts: Meaning-Making and Identity-Formation

ERIC Educational Resources Information Center

Davidson, Yonaton Sahar

2018-01-01

Recent research supports the benefit of students' construction of relevance through writing about the connection of content to their life. However, most such research defines relevance narrowly as utility value--perceived instrumentality of the content to the student's career goals. Furthermore, the scope of phenomenological and conceptual…

[The common bed bug (Cimex lectularius) - biology, medical relevance, possibilities for the detection and control].

PubMed

Rupeš, V; Vlčková, J; Holý, O; Horáková, D; Azeem, K; Kollárová, H

2017-01-01

Bed bugs have become a major concern worldwide in the 21st century and are therefore intensively investigated. The new findings not only extend the knowledge of their biology, medical relevance, and causes of the resurgence, but also can be used in bed bug management. A brief overview is provided of some of the most important research results and opinions, published in the last few years in prestigious international journals.

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

NASA Astrophysics Data System (ADS)

Carlson, Philip Joseph

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

Developmental Testing of Liquid and Gaseous/Vaporous Decontamination on Bacterial Spores and Other Biological Warfare Agents on Military Relevant Surfaces

DTIC Science & Technology

2016-02-11

process ( gas /vapor or liquid ), sampling will be conducted as soon as possible. Samples will be incubated for 12 to 48 hours (depending on the...Final 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE Test Operations Procedure (TOP) 08-2-065 Developmental Testing of Liquid and Gaseous...biological decontamination protocol to analyze the efficacy of liquid and gaseous/vaporous decontaminants on military-relevant surfaces. The

Enhancing light-harvesting power with coherent vibrational interactions: A quantum heat engine picture

NASA Astrophysics Data System (ADS)

Killoran, N.; Huelga, S. F.; Plenio, M. B.

2015-10-01

Recent evidence suggests that quantum effects may have functional importance in biological light-harvesting systems. Along with delocalized electronic excitations, it is now suspected that quantum coherent interactions with certain near-resonant vibrations may contribute to light-harvesting performance. However, the actual quantum advantage offered by such coherent vibrational interactions has not yet been established. We investigate a quantum design principle, whereby coherent exchange of single energy quanta between electronic and vibrational degrees of freedom can enhance a light-harvesting system's power above what is possible by thermal mechanisms alone. We present a prototype quantum heat engine which cleanly illustrates this quantum design principle and quantifies its quantum advantage using thermodynamic measures of performance. We also demonstrate the principle's relevance in parameter regimes connected to natural light-harvesting structures.

Single-molecule spectroscopic methods.

PubMed

Haustein, Elke; Schwille, Petra

2004-10-01

Being praised for the mere fact of enabling the detection of individual fluorophores a dozen years ago, single-molecule techniques nowadays represent standard methods for the elucidation of the structural rearrangements of biologically relevant macromolecules. Single-molecule-sensitive techniques, such as fluorescence correlation spectroscopy, allow real-time access to a multitude of molecular parameters (e.g. diffusion coefficients, concentration and molecular interactions). As a result of various recent advances, this technique shows promise even for intracellular applications. Fluorescence imaging can reveal the spatial localization of fluorophores on nanometer length scales, whereas fluorescence resonance energy transfer supports a wide range of different applications, including real-time monitoring of conformational rearrangements (as in protein folding). Still in their infancy, single-molecule spectroscopic methods thus provide unprecedented insights into basic molecular mechanisms. Copyright 2004 Elsevier Ltd.

Effective ergodicity breaking in an exclusion process with varying system length

NASA Astrophysics Data System (ADS)

Schultens, Christoph; Schadschneider, Andreas; Arita, Chikashi

2015-09-01

Stochastic processes of interacting particles in systems with varying length are relevant e.g. for several biological applications. We try to explore what kind of new physical effects one can expect in such systems. As an example, we extend the exclusive queueing process that can be viewed as a one-dimensional exclusion process with varying length, by introducing Langmuir kinetics. This process can be interpreted as an effective model for a queue that interacts with other queues by allowing incoming and leaving of customers in the bulk. We find surprising indications for breaking of ergodicity in a certain parameter regime, where the asymptotic growth behavior depends on the initial length. We show that a random walk with site-dependent hopping probabilities exhibits qualitatively the same behavior.

Biological competition: Decision rules, pattern formation, and oscillations

PubMed Central

Grossberg, Stephen

1980-01-01

Competition solves a universal problem about pattern processing by cellular systems. Competition allows cells to automatically retune their sensitivity to avoid noise and saturation effects. All competitive systems induce decision schemes that permit them to be classified. Systems are identified that achieve global pattern formation, or decision-making, no matter how their parameters are chosen. Oscillations can occur due to contradictions in a system's decision scheme. The pattern formation and oscillation results are extreme examples of a complementarity principle that seems to hold for competitive systems. Nonlinear competitive systems can sometimes appear, to a macroscopic observer, to have linear and cooperative properties, although the two types of systems are not equivalent. This observation is relevant to theories about the evolutionary transition from competitive to cooperative behavior. PMID:16592807

Biomimetic strategies for engineering composite tissues.

PubMed

Lee, Nancy; Robinson, Jennifer; Lu, Helen

2016-08-01

The formation of multiple tissue types and their integration into composite tissue units presents a frontier challenge in regenerative engineering. Tissue-tissue synchrony is crucial in providing structural support for internal organs and enabling daily activities. This review highlights the state-of-the-art in composite tissue scaffold design, and explores how biomimicry can be strategically applied to avoid over-engineering the scaffold. Given the complexity of biological tissues, determining the most relevant parameters for recapitulating native structure-function relationships through strategic biomimicry will reduce the burden for clinical translation. It is anticipated that these exciting efforts in composite tissue engineering will enable integrative and functional repair of common soft tissue injuries and lay the foundation for total joint or limb regeneration. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identifying marker genes in transcription profiling data using a mixture of feature relevance experts.

PubMed

Chow, M L; Moler, E J; Mian, I S

2001-03-08

Transcription profiling experiments permit the expression levels of many genes to be measured simultaneously. Given profiling data from two types of samples, genes that most distinguish the samples (marker genes) are good candidates for subsequent in-depth experimental studies and developing decision support systems for diagnosis, prognosis, and monitoring. This work proposes a mixture of feature relevance experts as a method for identifying marker genes and illustrates the idea using published data from samples labeled as acute lymphoblastic and myeloid leukemia (ALL, AML). A feature relevance expert implements an algorithm that calculates how well a gene distinguishes samples, reorders genes according to this relevance measure, and uses a supervised learning method [here, support vector machines (SVMs)] to determine the generalization performances of different nested gene subsets. The mixture of three feature relevance experts examined implement two existing and one novel feature relevance measures. For each expert, a gene subset consisting of the top 50 genes distinguished ALL from AML samples as completely as all 7,070 genes. The 125 genes at the union of the top 50s are plausible markers for a prototype decision support system. Chromosomal aberration and other data support the prediction that the three genes at the intersection of the top 50s, cystatin C, azurocidin, and adipsin, are good targets for investigating the basic biology of ALL/AML. The same data were employed to identify markers that distinguish samples based on their labels of T cell/B cell, peripheral blood/bone marrow, and male/female. Selenoprotein W may discriminate T cells from B cells. Results from analysis of transcription profiling data from tumor/nontumor colon adenocarcinoma samples support the general utility of the aforementioned approach. Theoretical issues such as choosing SVM kernels and their parameters, training and evaluating feature relevance experts, and the impact of potentially mislabeled samples on marker identification (feature selection) are discussed.

Relevance Rank Platform (RRP) for Functional Filtering of High Content Protein-Protein Interaction Data.

PubMed

Pokharel, Yuba Raj; Saarela, Jani; Szwajda, Agnieszka; Rupp, Christian; Rokka, Anne; Lal Kumar Karna, Shibendra; Teittinen, Kaisa; Corthals, Garry; Kallioniemi, Olli; Wennerberg, Krister; Aittokallio, Tero; Westermarck, Jukka

2015-12-01

High content protein interaction screens have revolutionized our understanding of protein complex assembly. However, one of the major challenges in translation of high content protein interaction data is identification of those interactions that are functionally relevant for a particular biological question. To address this challenge, we developed a relevance ranking platform (RRP), which consist of modular functional and bioinformatic filters to provide relevance rank among the interactome proteins. We demonstrate the versatility of RRP to enable a systematic prioritization of the most relevant interaction partners from high content data, highlighted by the analysis of cancer relevant protein interactions for oncoproteins Pin1 and PME-1. We validated the importance of selected interactions by demonstration of PTOV1 and CSKN2B as novel regulators of Pin1 target c-Jun phosphorylation and reveal previously unknown interacting proteins that may mediate PME-1 effects via PP2A-inhibition. The RRP framework is modular and can be modified to answer versatile research problems depending on the nature of the biological question under study. Based on comparison of RRP to other existing filtering tools, the presented data indicate that RRP offers added value especially for the analysis of interacting proteins for which there is no sufficient prior knowledge available. Finally, we encourage the use of RRP in combination with either SAINT or CRAPome computational tools for selecting the candidate interactors that fulfill the both important requirements, functional relevance, and high confidence interaction detection. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Estimating the Relevance of World Disturbances to Explain Savings, Interference and Long-Term Motor Adaptation Effects

PubMed Central

Berniker, Max; Kording, Konrad P.

2011-01-01

Recent studies suggest that motor adaptation is the result of multiple, perhaps linear processes each with distinct time scales. While these models are consistent with some motor phenomena, they can neither explain the relatively fast re-adaptation after a long washout period, nor savings on a subsequent day. Here we examined if these effects can be explained if we assume that the CNS stores and retrieves movement parameters based on their possible relevance. We formalize this idea with a model that infers not only the sources of potential motor errors, but also their relevance to the current motor circumstances. In our model adaptation is the process of re-estimating parameters that represent the body and the world. The likelihood of a world parameter being relevant is then based on the mismatch between an observed movement and that predicted when not compensating for the estimated world disturbance. As such, adapting to large motor errors in a laboratory setting should alert subjects that disturbances are being imposed on them, even after motor performance has returned to baseline. Estimates of this external disturbance should be relevant both now and in future laboratory settings. Estimated properties of our bodies on the other hand should always be relevant. Our model demonstrates savings, interference, spontaneous rebound and differences between adaptation to sudden and gradual disturbances. We suggest that many issues concerning savings and interference can be understood when adaptation is conditioned on the relevance of parameters. PMID:21998574

Environmental chemicals and breast cancer: An updated review of epidemiological literature informed by biological mechanisms.

PubMed

Rodgers, Kathryn M; Udesky, Julia O; Rudel, Ruthann A; Brody, Julia Green

2018-01-01

Many common environmental chemicals are mammary gland carcinogens in animal studies, activate relevant hormonal pathways, or enhance mammary gland susceptibility to carcinogenesis. Breast cancer's long latency and multifactorial etiology make evaluation of these chemicals in humans challenging. For chemicals previously identified as mammary gland toxicants, we evaluated epidemiologic studies published since our 2007 review. We assessed whether study designs captured relevant exposures and disease features suggested by toxicological and biological evidence of genotoxicity, endocrine disruption, tumor promotion, or disruption of mammary gland development. We systematically searched the PubMed database for articles with breast cancer outcomes published in 2006-2016 using terms for 134 environmental chemicals, sources, or biomarkers of exposure. We critically reviewed the articles. We identified 158 articles. Consistent with experimental evidence, a few key studies suggested higher risk for exposures during breast development to dichlorodiphenyltrichloroethane (DDT), dioxins, perfluorooctane-sulfonamide (PFOSA), and air pollution (risk estimates ranged from 2.14 to 5.0), and for occupational exposure to solvents and other mammary carcinogens, such as gasoline components (risk estimates ranged from 1.42 to 3.31). Notably, one 50-year cohort study captured exposure to DDT during several critical windows for breast development (in utero, adolescence, pregnancy) and when this chemical was still in use. Most other studies did not assess exposure during a biologically relevant window or specify the timing of exposure. Few studies considered genetic variation, but the Long Island Breast Cancer Study Project reported higher breast cancer risk for polycyclic aromatic hydrocarbons (PAHs) in women with certain genetic variations, especially in DNA repair genes. New studies that targeted toxicologically relevant chemicals and captured biological hypotheses about genetic variants or windows of breast susceptibility added to evidence of links between environmental chemicals and breast cancer. However, many biologically relevant chemicals, including current-use consumer product chemicals, have not been adequately studied in humans. Studies are challenged to reconstruct exposures that occurred decades before diagnosis or access biological samples stored that long. Other problems include measuring rapidly metabolized chemicals and evaluating exposure to mixtures. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Making Biology Learning Relevant to Students: Integrating People, History, and Context into College Biology Teaching

ERIC Educational Resources Information Center

Chamany, Katayoun; Allen, Deborah; Tanner, Kimberly

2008-01-01

Teaching students to make connections between what they learn in the classroom and what they see in everyday life is imperative. As biology instructors, they may choose to teach biology devoid of social context, believing that students can make these connections on their own. However, students model their instructors' behaviors, and follow their…

Can a Diversified Instructional Approach Featuring Active Learning Improve Biology Students' Attitudes toward General Education?

ERIC Educational Resources Information Center

Rutledge, Michael L.; Lampley, Sandra A.

2017-01-01

In an effort to make our classes more engaging, we recently reorganized sections of our nonmajors biology course, using current issues in biology and society as a premise to promote coherence among course content and emphasize the relevance of biological concepts to everyday life. A key aspect of the reorganization included the development and…

Physicians' perspective on the clinical meaningfulness of inflammatory bowel disease trial results: an International Organization for the Study of Inflammatory Bowel Disease (IOIBD) survey.

PubMed

Olivera, P; Sandborn, W J; Panés, J; Baumann, C; D'Haens, G; Vermeire, S; Danese, S; Peyrin-Biroulet, L

2018-03-01

Several novel compounds are being developed for inflammatory bowel diseases (IBD). In addition, biosimilar drugs are being approved. An increasing number of head-to-head, superiority and non-inferiority trials in patients with IBD are expected in the future. The clinical relevance of the magnitude of the effect size is often debated. To better understand physicians' perspectives on the clinical meaningfulness of IBD trial results. We conducted an online survey among all IOIBD (International Organization for the Study of Inflammatory Bowel Diseases) members, asking their opinion on the clinical relevance of the results of IBD trials. Forty-six IOIBD members responded to the survey (52.3%). In biologic-naïve ulcerative colitis (UC) and Crohn's disease (CD) patients, most of the participants considered a 15% difference with placebo for clinical remission and endoscopic remission to be clinically relevant. In head-to-head trials, most of participants considerer a 10% difference between groups for clinical remission and endoscopic remission to be clinically relevant. Half of respondents considered 10% to be an adequate margin in non-inferiority trials. In bioequivalence studies, most of the participants considered adequate a ± 5% difference between a biosimilar and the originator for pharmacokinetic parameters, efficacy, safety and immunogenicity. Regarding safety, the difference between two drugs considered clinically relevant varied from 1% to 5%, depending on the type of adverse event. This is the first survey exploring how physicians perceive IBD trial results, providing an estimation of the magnitude of the difference between treatment arms that may directly influence clinical practice. © 2018 John Wiley & Sons Ltd.

Crossing Boundaries in Undergraduate Biology Education

ERIC Educational Resources Information Center

Vanderklein, Dirk; Munakata, Mika; McManus, Jason

2016-01-01

In an effort to make mathematics relevant to biology students, the authors developed two modules that sought to integrate mathematics and ecology instruction to differing degrees. The modules were developed by a team of biology and mathematics educators and were implemented in an ecology course using three different instructional methods for three…

Linking School Biology and Community in Developing Countries.

ERIC Educational Resources Information Center

Knamiller, Gary W.

1984-01-01

Explores the role of biological education in placing the school in its own local community and the real social-economic environment that surrounds it. Particular reference is made to issue-based biological education in schools as an attempt to bridge the gap between purely academic schooling and education for relevance. (Author)

Multimodal transport and dispersion of organelles in narrow tubular cells

NASA Astrophysics Data System (ADS)

Mogre, Saurabh S.; Koslover, Elena F.

2018-04-01

Intracellular components explore the cytoplasm via active motor-driven transport in conjunction with passive diffusion. We model the motion of organelles in narrow tubular cells using analytical techniques and numerical simulations to study the efficiency of different transport modes in achieving various cellular objectives. Our model describes length and time scales over which each transport mode dominates organelle motion, along with various metrics to quantify exploration of intracellular space. For organelles that search for a specific target, we obtain the average capture time for given transport parameters and show that diffusion and active motion contribute to target capture in the biologically relevant regime. Because many organelles have been found to tether to microtubules when not engaged in active motion, we study the interplay between immobilization due to tethering and increased probability of active transport. We derive parameter-dependent conditions under which tethering enhances long-range transport and improves the target capture time. These results shed light on the optimization of intracellular transport machinery and provide experimentally testable predictions for the effects of transport regulation mechanisms such as tethering.

Machine-assisted discovery of relationships in astronomy

NASA Astrophysics Data System (ADS)

Graham, Matthew J.; Djorgovski, S. G.; Mahabal, Ashish A.; Donalek, Ciro; Drake, Andrew J.

2013-05-01

High-volume feature-rich data sets are becoming the bread-and-butter of 21st century astronomy but present significant challenges to scientific discovery. In particular, identifying scientifically significant relationships between sets of parameters is non-trivial. Similar problems in biological and geosciences have led to the development of systems which can explore large parameter spaces and identify potentially interesting sets of associations. In this paper, we describe the application of automated discovery systems of relationships to astronomical data sets, focusing on an evolutionary programming technique and an information-theory technique. We demonstrate their use with classical astronomical relationships - the Hertzsprung-Russell diagram and the Fundamental Plane of elliptical galaxies. We also show how they work with the issue of binary classification which is relevant to the next generation of large synoptic sky surveys, such as the Large Synoptic Survey Telescope (LSST). We find that comparable results to more familiar techniques, such as decision trees, are achievable. Finally, we consider the reality of the relationships discovered and how this can be used for feature selection and extraction.

Single neuron modeling and data assimilation in BNST neurons

NASA Astrophysics Data System (ADS)

Farsian, Reza

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

Mapping networks of light-dark transition in LOV photoreceptors.

PubMed

Kaur Grewal, Rajdeep; Mitra, Devrani; Roy, Soumen

2015-11-15

In optogenetics, designing modules of long or short signaling state lifetime is necessary for control over precise cellular events. A critical parameter for designing artificial or synthetic photoreceptors is the signaling state lifetime of photosensor modules. Design and engineering of biologically relevant artificial photoreceptors is based on signaling mechanisms characteristic of naturally occurring photoreceptors. Therefore identifying residues important for light-dark transition is a definite first step towards rational design of synthetic photoreceptors. A thorough grasp of detailed mechanisms of photo induced signaling process would be immensely helpful in understanding the behaviour of organisms. Herein, we introduce the technique of differential networks. We identify key biological interactions, using light-oxygen-voltage domains of all organisms whose dark and light state crystal structures are simultaneously available. Even though structural differences between dark and light states are subtle (other than the covalent bond formation between flavin chromophore and active site Cysteine), our results successfully capture functionally relevant residues and are in complete agreement with experimental findings from literature. Additionally, using sequence-structure alignments, we predict functional significance of interactions found to be important from network perspective yet awaiting experimental validation. Our approach would not only help in minimizing extensive photo-cycle kinetics procedure but is also helpful in providing first-hand information on the fundamentals of photo-adaptation and rational design of synthetic photoreceptors in optogenetics. devrani.dbs@presiuniv.ac.in or soumen@jcbose.ac.in Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

OCT-based approach to local relaxations discrimination from translational relaxation motions

NASA Astrophysics Data System (ADS)

Matveev, Lev A.; Matveyev, Alexandr L.; Gubarkova, Ekaterina V.; Gelikonov, Grigory V.; Sirotkina, Marina A.; Kiseleva, Elena B.; Gelikonov, Valentin M.; Gladkova, Natalia D.; Vitkin, Alex; Zaitsev, Vladimir Y.

2016-04-01

Multimodal optical coherence tomography (OCT) is an emerging tool for tissue state characterization. Optical coherence elastography (OCE) is an approach to mapping mechanical properties of tissue based on OCT. One of challenging problems in OCE is elimination of the influence of residual local tissue relaxation that complicates obtaining information on elastic properties of the tissue. Alternatively, parameters of local relaxation itself can be used as an additional informative characteristic for distinguishing the tissue in normal and pathological states over the OCT image area. Here we briefly present an OCT-based approach to evaluation of local relaxation processes in the tissue bulk after sudden unloading of its initial pre-compression. For extracting the local relaxation rate we evaluate temporal dependence of local strains that are mapped using our recently developed hybrid phase resolved/displacement-tracking (HPRDT) approach. This approach allows one to subtract the contribution of global displacements of scatterers in OCT scans and separate the temporal evolution of local strains. Using a sample excised from of a coronary arteria, we demonstrate that the observed relaxation of local strains can be reasonably fitted by an exponential law, which opens the possibility to characterize the tissue by a single relaxation time. The estimated local relaxation times are assumed to be related to local biologically-relevant processes inside the tissue, such as diffusion, leaking/draining of the fluids, local folding/unfolding of the fibers, etc. In general, studies of evolution of such features can provide new metrics for biologically-relevant changes in tissue, e.g., in the problems of treatment monitoring.

Combining fungal biopesticides and insecticide-treated bednets to enhance malaria control.

PubMed

Hancock, Penelope A

2009-10-01

In developing strategies to control malaria vectors, there is increased interest in biological methods that do not cause instant vector mortality, but have sublethal and lethal effects at different ages and stages in the mosquito life cycle. These techniques, particularly if integrated with other vector control interventions, may produce substantial reductions in malaria transmission due to the total effect of alterations to multiple life history parameters at relevant points in the life-cycle and transmission-cycle of the vector. To quantify this effect, an analytically tractable gonotrophic cycle model of mosquito-malaria interactions is developed that unites existing continuous and discrete feeding cycle approaches. As a case study, the combined use of fungal biopesticides and insecticide treated bednets (ITNs) is considered. Low values of the equilibrium EIR and human prevalence were obtained when fungal biopesticides and ITNs were combined, even for scenarios where each intervention acting alone had relatively little impact. The effect of the combined interventions on the equilibrium EIR was at least as strong as the multiplicative effect of both interventions. For scenarios representing difficult conditions for malaria control, due to high transmission intensity and widespread insecticide resistance, the effect of the combined interventions on the equilibrium EIR was greater than the multiplicative effect, as a result of synergistic interactions between the interventions. Fungal biopesticide application was found to be most effective when ITN coverage was high, producing significant reductions in equilibrium prevalence for low levels of biopesticide coverage. By incorporating biological mechanisms relevant to vectorial capacity, continuous-time vector population models can increase their applicability to integrated vector management.

An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N V

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

An Evolutionary Firefly Algorithm for the Estimation of Nonlinear Biological Model Parameters

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Anwar, Sohail; Arjunan, Satya N. V.

2013-01-01

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test. PMID:23469172

Enhanced Bone Formation in Segmental Defects with BMP2 in a Biologically Relevant Molecular Context

DTIC Science & Technology

2016-10-16

gun shots . These do not heal on their own once a ‘critical size’ segment of bone is missing. One strategy to induce healing is to use bone-inducing...accelerate BMP2-induced bone formation by presenting the growth factor in a more biologically relevant context. This is based on our observation...that manganese increases the binding of BMP2 to COMP. The next steps are to validate these observations using BMP2:COMP on HA/PLG scaffolds in-vitro

Uptake and localization mechanisms of fluorescent and colored lipid probes. Part 2. QSAR models that predict localization of fluorescent probes used to identify ("specifically stain") various biomembranes and membranous organelles.

PubMed

Horobin, R W; Stockert, J C; Rashid-Doubell, F

2015-05-01

We discuss a variety of biological targets including generic biomembranes and the membranes of the endoplasmic reticulum, endosomes/lysosomes, Golgi body, mitochondria (outer and inner membranes) and the plasma membrane of usual fluidity. For each target, we discuss the access of probes to the target membrane, probe uptake into the membrane and the mechanism of selectivity of the probe uptake. A statement of the QSAR decision rule that describes the required physicochemical features of probes that enable selective staining also is provided, followed by comments on exceptions and limits. Examples of probes typically used to demonstrate each target structure are noted and decision rule tabulations are provided for probes that localize in particular targets; these tabulations show distribution of probes in the conceptual space defined by the relevant structure parameters ("parameter space"). Some general implications and limitations of the QSAR models for probe targeting are discussed including the roles of certain cell and protocol factors that play significant roles in lipid staining. A case example illustrates the predictive ability of QSAR models. Key limiting values of the head group hydrophilicity parameter associated with membrane-probe interactions are discussed in an appendix.

Mathematics as a Conduit for Translational Research in Post-Traumatic Osteoarthritis

PubMed Central

Ayati, Bruce P.; Kapitanov, Georgi I.; Coleman, Mitchell C.; Anderson, Donald D.; Martin, James A.

2016-01-01

Biomathematical models offer a powerful method of clarifying complex temporal interactions and the relationships among multiple variables in a system. We present a coupled in silico biomathematical model of articular cartilage degeneration in response to impact and/or aberrant loading such as would be associated with injury to an articular joint. The model incorporates fundamental biological and mechanical information obtained from explant and small animal studies to predict post-traumatic osteoarthritis (PTOA) progression, with an eye toward eventual application in human patients. In this sense, we refer to the mathematics as a “conduit of translation”. The new in silico framework presented in this paper involves a biomathematical model for the cellular and biochemical response to strains computed using finite element analysis. The model predicts qualitative responses presently, utilizing system parameter values largely taken from the literature. To contribute to accurate predictions, models need to be accurately parameterized with values that are based on solid science. We discuss a parameter identification protocol that will enable us to make increasingly accurate predictions of PTOA progression using additional data from smaller scale explant and small animal assays as they become available. By distilling the data from the explant and animal assays into parameters for biomathematical models, mathematics can translate experimental data to clinically relevant knowledge. PMID:27653021

Ultra-weak photon emission in healthy subjects and patients with type 2 diabetes: evidence for a non-invasive diagnostic tool.

PubMed

Yang, Meina; Ding, Wenyu; Liu, Yanli; Fan, Hua; Bajpai, Rajendra P; Fu, Jialei; Pang, Jingxiang; Zhao, Xiaolei; Han, Jinxiang

2017-05-17

Spontaneous ultra-weak photon emission (UPE) is a common phenomenon in biological systems and has been linked to pathological states. Researchers have always considered ultra-weak photon emission a potential non-invasive diagnostic tool, but its application in the medical field is stagnant due to the lack of relevant data for pathological states. Ultra-weak photon signals from five body sites (forehead, neck, heart, stomach, and navel) in fifty patients with type 2 diabetes and sixty age-matched healthy subjects were measured using a moveable whole-body biophoton detection system. Photon signal is measured for 10 min and detected in bins of 50 ms by a photomultiplier with a range of 290-630 nm. Each signal is a time series of 12 000 elements. Various parameters including photon intensity, Q value, squeezed state parameters (|α|, θ, ø, r) and SSI were analyzed. we found significant differences in the abovementioned parameters between groups, and all subjects could be clustered into two groups according to the results obtained by principal component analysis. Methods and results from this study could be useful for constructing a UPE database for a range of diseases, which would promote the application of UPE in clinical diagnosis in the future.

Linking field-based metabolomics and chemical analyses to prioritize contaminants of emerging concern in the Great Lakes basin

USGS Publications Warehouse

Davis, John M.; Ekman, Drew R.; Teng, Quincy; Ankley, Gerald T.; Berninger, Jason P.; Cavallin, Jenna E.; Jensen, Kathleen M.; Kahl, Michael D.; Schroeder, Anthony L.; Villeneuve, Daniel L.; Jorgenson, Zachary G.; Lee, Kathy E.; Collette, Timothy W.

2016-01-01

The ability to focus on the most biologically relevant contaminants affecting aquatic ecosystems can be challenging because toxicity-assessment programs have not kept pace with the growing number of contaminants requiring testing. Because it has proven effective at assessing the biological impacts of potentially toxic contaminants, profiling of endogenous metabolites (metabolomics) may help screen out contaminants with a lower likelihood of eliciting biological impacts, thereby prioritizing the most biologically important contaminants. The authors present results from a study that utilized cage-deployed fathead minnows (Pimephales promelas) at 18 sites across the Great Lakes basin. They measured water temperature and contaminant concentrations in water samples (132 contaminants targeted, 86 detected) and used 1H-nuclear magnetic resonance spectroscopy to measure endogenous metabolites in polar extracts of livers. They used partial least-squares regression to compare relative abundances of endogenous metabolites with contaminant concentrations and temperature. The results indicated that profiles of endogenous polar metabolites covaried with at most 49 contaminants. The authors identified up to 52% of detected contaminants as not significantly covarying with changes in endogenous metabolites, suggesting they likely were not eliciting measurable impacts at these sites. This represents a first step in screening for the biological relevance of detected contaminants by shortening lists of contaminants potentially affecting these sites. Such information may allow risk assessors to prioritize contaminants and focus toxicity testing on the most biologically relevant contaminants. Environ Toxicol Chem 2016;35:2493–2502.

Extracellular matrix stiffness causes systematic variations in proliferation and chemosensitivity in myeloid leukemias.

PubMed

Shin, Jae-Won; Mooney, David J

2016-10-25

Extracellular matrix stiffness influences biological functions of some tumors. However, it remains unclear how cancer subtypes with different oncogenic mutations respond to matrix stiffness. In addition, the relevance of matrix stiffness to in vivo tumor growth kinetics and drug efficacy remains elusive. Here, we designed 3D hydrogels with physical parameters relevant to hematopoietic tissues and adapted them to a quantitative high-throughput screening format to facilitate mechanistic investigations into the role of matrix stiffness on myeloid leukemias. Matrix stiffness regulates proliferation of some acute myeloid leukemia types, including MLL-AF9 + MOLM-14 cells, in a biphasic manner by autocrine regulation, whereas it decreases that of chronic myeloid leukemia BCR-ABL + K-562 cells. Although Arg-Gly-Asp (RGD) integrin ligand and matrix softening confer resistance to a number of drugs, cells become sensitive to drugs against protein kinase B (PKB or AKT) and rapidly accelerated fibrosarcoma (RAF) proteins regardless of matrix stiffness when MLL-AF9 and BCR-ABL are overexpressed in K-562 and MOLM-14 cells, respectively. By adapting the same hydrogels to a xenograft model of extramedullary leukemias, we confirm the pathological relevance of matrix stiffness in growth kinetics and drug sensitivity against standard chemotherapy in vivo. The results thus demonstrate the importance of incorporating 3D mechanical cues into screening for anticancer drugs.

A Unifying Review of Bioassay-Guided Fractionation, Effect-Directed Analysis and Related Techniques

PubMed Central

Weller, Michael G.

2012-01-01

The success of modern methods in analytical chemistry sometimes obscures the problem that the ever increasing amount of analytical data does not necessarily give more insight of practical relevance. As alternative approaches, toxicity- and bioactivity-based assays can deliver valuable information about biological effects of complex materials in humans, other species or even ecosystems. However, the observed effects often cannot be clearly assigned to specific chemical compounds. In these cases, the establishment of an unambiguous cause-effect relationship is not possible. Effect-directed analysis tries to interconnect instrumental analytical techniques with a biological/biochemical entity, which identifies or isolates substances of biological relevance. Successful application has been demonstrated in many fields, either as proof-of-principle studies or even for complex samples. This review discusses the different approaches, advantages and limitations and finally shows some practical examples. The broad emergence of effect-directed analytical concepts might lead to a true paradigm shift in analytical chemistry, away from ever growing lists of chemical compounds. The connection of biological effects with the identification and quantification of molecular entities leads to relevant answers to many real life questions. PMID:23012539

A direct method for computing extreme value (Gumbel) parameters for gapped biological sequence alignments.

PubMed

Quinn, Terrance; Sinkala, Zachariah

2014-01-01

We develop a general method for computing extreme value distribution (Gumbel, 1958) parameters for gapped alignments. Our approach uses mixture distribution theory to obtain associated BLOSUM matrices for gapped alignments, which in turn are used for determining significance of gapped alignment scores for pairs of biological sequences. We compare our results with parameters already obtained in the literature.

Computation of the effective mechanical response of biological networks accounting for large configuration changes.

PubMed

El Nady, K; Ganghoffer, J F

2016-05-01

The asymptotic homogenization technique is involved to derive the effective elastic response of biological membranes viewed as repetitive beam networks. Thereby, a systematic methodology is established, allowing the prediction of the overall mechanical properties of biological membranes in the nonlinear regime, reflecting the influence of the geometrical and mechanical micro-parameters of the network structure on the overall response of the equivalent continuum. Biomembranes networks are classified based on nodal connectivity, so that we analyze in this work 3, 4 and 6-connectivity networks, which are representative of most biological networks. The individual filaments of the network are described as undulated beams prone to entropic elasticity, with tensile moduli determined from their persistence length. The effective micropolar continuum evaluated as a continuum substitute of the biological network has a kinematics reflecting the discrete network deformation modes, involving a nodal displacement and a microrotation. The statics involves the classical Cauchy stress and internal moments encapsulated into couple stresses, which develop internal work in duality to microcurvatures reflecting local network undulations. The relative ratio of the characteristic bending length of the effective micropolar continuum to the unit cell size determines the relevant choice of the equivalent medium. In most cases, the Cauchy continuum is sufficient to model biomembranes. The peptidoglycan network may exhibit a re-entrant hexagonal configuration due to thermal or pressure fluctuations, for which micropolar effects become important. The homogenized responses are in good agreement with FE simulations performed over the whole network. The predictive nature of the employed homogenization technique allows the identification of a strain energy density of a hyperelastic model, for the purpose of performing structural calculations of the shape evolutions of biomembranes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Acoustic fine structure may encode biologically relevant information for zebra finches.

PubMed

Prior, Nora H; Smith, Edward; Lawson, Shelby; Ball, Gregory F; Dooling, Robert J

2018-04-18

The ability to discriminate changes in the fine structure of complex sounds is well developed in birds. However, the precise limit of this discrimination ability and how it is used in the context of natural communication remains unclear. Here we describe natural variability in acoustic fine structure of male and female zebra finch calls. Results from psychoacoustic experiments demonstrate that zebra finches are able to discriminate extremely small differences in fine structure, which are on the order of the variation in acoustic fine structure that is present in their vocal signals. Results from signal analysis methods also suggest that acoustic fine structure may carry information that distinguishes between biologically relevant categories including sex, call type and individual identity. Combined, our results are consistent with the hypothesis that zebra finches can encode biologically relevant information within the fine structure of their calls. This study provides a foundation for our understanding of how acoustic fine structure may be involved in animal communication.

Sex and gonadal hormones in mouse models of Alzheimer’s disease: what is relevant to the human condition?

PubMed Central

2012-01-01

Biologic sex and gonadal hormones matter in human aging and diseases of aging such as Alzheimer’s – and the importance of studying their influences relates directly to human health. The goal of this article is to review the literature to date on sex and hormones in mouse models of Alzheimer’s disease (AD) with an exclusive focus on interpreting the relevance of findings to the human condition. To this end, we highlight advances in AD and in sex and hormone biology, discuss what these advances mean for merging the two fields, review the current mouse model literature, raise major unresolved questions, and offer a research framework that incorporates human reproductive aging for future studies aimed at translational discoveries in this important area. Unraveling human relevant pathways in sex and hormone-based biology may ultimately pave the way to novel and urgently needed treatments for AD and other neurodegenerative diseases. PMID:23126652

Perspectives on the Use of Algae as Biological Indicators for Monitoring and Protecting Aquatic Environments, with Special Reference to Malaysian Freshwater Ecosystems

PubMed Central

Omar, Wan Maznah Wan

2010-01-01

Algal communities possess many attributes as biological indicators of spatial and temporal environmental changes. Algal parameters, especially the community structural and functional variables that have been used in biological monitoring programs, are highlighted in this document. Biological indicators like algae have only recently been included in water quality assessments in some areas of Malaysia. The use of algal parameters in identifying various types of water degradation is essential and complementary to other environmental indicators. PMID:24575199

Australian Biology Test Item Bank, Years 11 and 12. Volume II: Year 12.

ERIC Educational Resources Information Center

Brown, David W., Ed.; Sewell, Jeffrey J., Ed.

This document consists of test items which are applicable to biology courses throughout Australia (irrespective of course materials used); assess key concepts within course statement (for both core and optional studies); assess a wide range of cognitive processes; and are relevant to current biological concepts. These items are arranged under…

Context, Cortex, and Dopamine: A Connectionist Approach to Behavior and Biology in Schizophrenia.

ERIC Educational Resources Information Center

Cohen, Jonathan D.; Servan-Schreiber, David

1992-01-01

Using a connectionist framework, it is possible to develop models exploring effects of biologically relevant variables on behavior. The ability of such models to explain schizophrenic behavior in terms of biological disturbances is considered, and computer models are presented that simulate normal and schizophrenic behavior in an attentional task.…

Understanding the side effects of classical biological control

Treesearch

Dean Pearson

2008-01-01

Classical biological control involves the use of imported natural enemies to suppress or control populations of the target pest species below an economically or ecologically relevant threshold. Biological control is a useful tool for mitigating the impacts of exotic invasive plants; however, its application is not without risk (see Carruthers and D’Antonio...

"Evo in the News:" Understanding Evolution and Students' Attitudes toward the Relevance of Evolutionary Biology

ERIC Educational Resources Information Center

Infanti, Lynn M.; Wiles, Jason R.

2014-01-01

This investigation evaluated the effects of exposure to the "Evo in the News" section of the "Understanding Evolution" website on students' attitudes toward biological evolution in undergraduates in a mixed-majors introductory biology course at Syracuse University. Students' attitudes toward evolution and changes therein were…

Australian Biology Test Item Bank, Years 11 and 12. Volume I: Year 11.

ERIC Educational Resources Information Center

Brown, David W., Ed.; Sewell, Jeffrey J., Ed.

This document consists of test items which are applicable to biology courses throughout Australia (irrespective of course materials used); assess key concepts within course statement (for both core and optional studies); assess a wide range of cognitive processes; and are relevant to current biological concepts. These items are arranged under…

WHO Expert Committee on Biological Standardization.

PubMed

2002-01-01

This report presents the recommendations of a WHO Expert Committee commissioned to coordinate activities leading to the adoption of international recommendations for the production and quality control of vaccines and other biologicals and the establishment of international biological reference materials. The report starts with a discussion of general issues brought to the attention of the Committee and provides information on issues relevant to international guidelines, recommendations and other matters related to the manufacture and quality control of biologicals. This is followed by information on the status and development of reference materials for bovine spongiform encephalopathy, various antigens, blood products, cytokines, growth factors and endocrinological substances. The second part of the report, of particular interest to manufacturers and national control authorities, contains sets of recommendations for the production and control of poliomyelitis vaccine (oral) and poliomyelitis vaccine (inactivated) and guidelines for the production and control of live attenuated Japanese encephalitis vaccine. Also included are lists of recommendations and guidelines for biological substances used in medicine, and other relevant documents.

Control-Relevant Modeling, Analysis, and Design for Scramjet-Powered Hypersonic Vehicles

NASA Technical Reports Server (NTRS)

Rodriguez, Armando A.; Dickeson, Jeffrey J.; Sridharan, Srikanth; Benavides, Jose; Soloway, Don; Kelkar, Atul; Vogel, Jerald M.

2009-01-01

Within this paper, control-relevant vehicle design concepts are examined using a widely used 3 DOF (plus flexibility) nonlinear model for the longitudinal dynamics of a generic carrot-shaped scramjet powered hypersonic vehicle. Trade studies associated with vehicle/engine parameters are examined. The impact of parameters on control-relevant static properties (e.g. level-flight trimmable region, trim controls, AOA, thrust margin) and dynamic properties (e.g. instability and right half plane zero associated with flight path angle) are examined. Specific parameters considered include: inlet height, diffuser area ratio, lower forebody compression ramp inclination angle, engine location, center of gravity, and mass. Vehicle optimizations is also examined. Both static and dynamic considerations are addressed. The gap-metric optimized vehicle is obtained to illustrate how this control-centric concept can be used to "reduce" scheduling requirements for the final control system. A classic inner-outer loop control architecture and methodology is used to shed light on how specific vehicle/engine design parameter selections impact control system design. In short, the work represents an important first step toward revealing fundamental tradeoffs and systematically treating control-relevant vehicle design.

The association of posttraumatic stress disorder and metabolic syndrome: a study of increased health risk in veterans.

PubMed

Heppner, Pia S; Crawford, Eric F; Haji, Uzair A; Afari, Niloofar; Hauger, Richard L; Dashevsky, Boris A; Horn, Paul S; Nunnink, Sarah E; Baker, Dewleen G

2009-01-09

There is accumulating evidence for a link between trauma exposure, posttraumatic stress disorder (PTSD) and diminished health status. To assess PTSD-related biological burden, we measured biological factors that comprise metabolic syndrome, an important established predictor of morbidity and mortality, as a correlate of long-term health risk in PTSD. We analyzed clinical data from 253 male and female veterans, corresponding to five factors linked to metabolic syndrome (systolic and diastolic blood pressure, waist-to-hip ratio and fasting measures of high-density lipoprotein (HDL) cholesterol, serum triglycerides and plasma glucose concentration). Clinical cut-offs were defined for each biological parameter based on recommendations from the World Health Organization and the National Cholesterol Education Program. Controlling for relevant variables including sociodemographic variables, alcohol/substance/nicotine use and depression, we examined the impact of PTSD on metabolic syndrome using a logistic regression model. Two-fifths (40%) of the sample met criteria for metabolic syndrome. Of those with PTSD (n = 139), 43% met criteria for metabolic syndrome. The model predicted metabolic syndrome well (-2 log likelihood = 316.650, chi-squared = 23.731, p = 0.005). Veterans with higher severity of PTSD were more likely to meet diagnostic criteria for metabolic syndrome (Wald = 4.76, p = 0.03). These findings provide preliminary evidence linking higher severity of PTSD with risk factors for diminished health and increased morbidity, as represented by metabolic syndrome.

The World Health Organization Global Programme on AIDS proposal for standardization of HIV sequence nomenclature. WHO Network for HIV Isolation and Characterization.

PubMed

Korber, B T; Osmanov, S; Esparza, J; Myers, G

1994-11-01

The World Health Organization Global Programme on AIDS (WHO/GPA) is conducting a large-scale collaborative study of human immunodeficiency virus type 1 (HIV-1) variation, based in four potential vaccine-trial site countries: Brazil, Rwanda, Thailand, and Uganda. Through the course of this study, it was crucial to keep track of certain attributes of the samples from which the viral nucleotide sequences were derived (e.g., country of origin and viral culture characterization), so that meaningful sequence comparisons could be made. Here we describe a system developed in the context of the WHO/GPA study that summarizes such critical attributes by representing them as standardized characters directly incorporated into sequence names. This nomenclature allows linkage of clinical, phenotypic, and geographic information with molecular data. We propose that other investigators involved in human immunodeficiency virus (HIV) nucleotide sequencing efforts adopt a similar standardized sequence nomenclature to facilitate cross-study sequence comparison. HIV sequence data are being generated at an ever-increasing rate; directly coupled to this increase is our deepening understanding of biological parameters that influence or result from sequence variability. A standardized sequence nomenclature that includes relevant biological information would enable researchers to better utilize the growing body of sequence data, and enhance their ability to interpret the biological implications of their own data through facilitating comparisons with previously published work.

Scoring clustering solutions by their biological relevance.

PubMed

Gat-Viks, I; Sharan, R; Shamir, R

2003-12-12

A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering gene expression data into homogeneous groups was shown to be instrumental in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on clustering algorithms for gene expression analysis, very few works addressed the systematic comparison and evaluation of clustering results. Typically, different clustering algorithms yield different clustering solutions on the same data, and there is no agreed upon guideline for choosing among them. We developed a novel statistically based method for assessing a clustering solution according to prior biological knowledge. Our method can be used to compare different clustering solutions or to optimize the parameters of a clustering algorithm. The method is based on projecting vectors of biological attributes of the clustered elements onto the real line, such that the ratio of between-groups and within-group variance estimators is maximized. The projected data are then scored using a non-parametric analysis of variance test, and the score's confidence is evaluated. We validate our approach using simulated data and show that our scoring method outperforms several extant methods, including the separation to homogeneity ratio and the silhouette measure. We apply our method to evaluate results of several clustering methods on yeast cell-cycle gene expression data. The software is available from the authors upon request.

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

Students' Personal Connection with Science: Investigating the Multidimensional Phenomenological Structure of Self-Relevance

ERIC Educational Resources Information Center

Hartwell, Matthew; Kaplan, Avi

2018-01-01

This paper presents findings from a two-phase mixed methods study investigating the phenomenological structure of self-relevance among ninth-grade junior high school biology students (Phase 1: N = 118; Phase 2: N = 139). We begin with a phenomenological multidimensional definition of self-relevance as comprising three dimensions: the academic…

Universally Sloppy Parameter Sensitivities in Systems Biology Models

PubMed Central

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-01-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a “sloppy” spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters. PMID:17922568

Universally sloppy parameter sensitivities in systems biology models.

PubMed

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Invited review article: Advanced light microscopy for biological space research.

PubMed

De Vos, Winnok H; Beghuin, Didier; Schwarz, Christian J; Jones, David B; van Loon, Jack J W A; Bereiter-Hahn, Juergen; Stelzer, Ernst H K

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Invited Review Article: Advanced light microscopy for biological space research

NASA Astrophysics Data System (ADS)

De Vos, Winnok H.; Beghuin, Didier; Schwarz, Christian J.; Jones, David B.; van Loon, Jack J. W. A.; Bereiter-Hahn, Juergen; Stelzer, Ernst H. K.

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

[Effects of biologically active pectin-containing dietary supplement on gastroduodenal motility in patients with a functional dyspepsia].

PubMed

Loranskaia, T I; Kabanova, I N; Klykova, E V

2002-01-01

For 21 patients with a functional dyspepsia the influencing biologically active additives to nutrition "Pekcecom" on dynamics of clinical symptoms and parameters gastroduodenal motility under the data gastroduodenoscintigraphy was studied. The usage of biologically active additives during 4 weeks was accompanied by deboosting of accelerated gastric emptying for want of statistically significant influencing on a normal and delayed gastric emptying and parameters of duodenal transit.

Multisensor Instrument for Real-Time Biological Monitoring

NASA Technical Reports Server (NTRS)

Zhang, Sean (Zhanxiang); Xu, Guoda; Qiu, Wei; Lin, Freddie

2004-01-01

The figure schematically depicts an instrumentation system, called a fiber optic-based integration system (FOBIS), that is undergoing development to enable real-time monitoring of fluid cell cultures, bioprocess flows, and the like. The FOBIS design combines a micro flow cytometer (MFC), a microphotometer (MP), and a fluorescence-spectrum- or binding-force-measuring micro-sensor (MS) in a single instrument that is capable of measuring multiple biological parameters simultaneously or sequentially. The fiber-optic-based integration system is so named because the MFC, the MP, and the MS are integrated into a single optical system that is coupled to light sources and photometric equipment via optical fibers. The optical coupling components also include a wavelength-division multiplexer and diffractive optical elements. The FOBIS includes a laserdiode- and fiber-optic-based optical trapping subsystem (optical tweezers ) with microphotometric and micro-sensing capabilities for noninvasive confinement and optical measurement of relevant parameters of a single cell or other particle. Some of the measurement techniques implemented together by the FOBIS have long been used separately to obtain basic understanding of the optical properties of individual cells and other organisms, the optical properties of populations of organisms, and the interrelationships among these properties, physiology of the organisms, and physical processes that govern the media that surround the organisms. For example, flow cytometry yields information on numerical concentrations, cross-sectional areas, and types of cells or other particles. Micro-sensing can be used to measure pH and concentrations of oxygen, carbon dioxide, glucose, metabolites, calcium, and antigens in a cell-culture fluid, thereby providing feedback that can be helpful in improving control over a bioprocess. Microphotometry (including measurements of scattering and fluorescence) can yield further information about optically trapped individual particles. In addition to the multifunctionality not previously available in a single biological monitoring system, the FOBIS offers advantages of low mass, sensitivity, accuracy, portability, low cost, compactness (the overall dimensions of the fully developed FOBIS sensor head are expected to be less than 1 by 1 by 2 cm), and immunity to electromagnetic interference at suboptical frequencies. FOBIS could be useful in a variety of laboratory and field settings in such diverse endeavors as medical, veterinary, and general biological research; medical and veterinary diagnosis monitoring of industrial bioprocesses; and analysis of biological contaminants in air, water, and food.

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

PubMed

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

2011-07-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

Finding Relevant Parameters for the Thin-film Photovoltaic Cells Production Process with the Application of Data Mining Methods.

PubMed

Ulaczyk, Jan; Morawiec, Krzysztof; Zabierowski, Paweł; Drobiazg, Tomasz; Barreau, Nicolas

2017-09-01

A data mining approach is proposed as a useful tool for the control parameters analysis of the 3-stage CIGSe photovoltaic cell production process, in order to find variables that are the most relevant for cell electric parameters and efficiency. The analysed data set consists of stage duration times, heater power values as well as temperatures for the element sources and the substrate - there are 14 variables per sample in total. The most relevant variables of the process have been found based on the so-called random forest analysis with the application of the Boruta algorithm. 118 CIGSe samples, prepared at Institut des Matériaux Jean Rouxel, were analysed. The results are close to experimental knowledge on the CIGSe cells production process. They bring new evidence to production parameters of new cells and further research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analyzing the texture changes in the quantitative phase maps of adipocytes

NASA Astrophysics Data System (ADS)

Roitshtain, Darina; Sharabani-Yosef, Orna; Gefen, Amit; Shaked, Natan T.

2016-03-01

We present a new analysis tool for studying texture changes in the quantitative phase maps of live cells acquired by wide-field interferometry. The sensitivity of wide-field interferometry systems to small changes in refractive index enables visualizing cells and inner cell organelles without the using fluorescent dyes or other cell-invasive approaches, which may affect the measurement and require external labeling. Our label-free texture-analysis tool is based directly on the optical path delay profile of the sample and does not necessitate decoupling refractive index and thickness in the cell quantitative phase profile; thus, relevant parameters can be calculated using a single-frame acquisition. Our experimental system includes low-coherence wide-field interferometer, combined with simultaneous florescence microscopy system for validation. We used this system and analysis tool for studying lipid droplets formation in adipocytes. The latter demonstration is relevant for various cellular functions such as lipid metabolism, protein storage and degradation to viral replication. These processes are functionally linked to several physiological and pathological conditions, including obesity and metabolic diseases. Quantification of these biological phenomena based on the texture changes in the cell phase map has a potential as a new cellular diagnosis tool.

Fundamentals and applications of SERS-based bioanalytical sensing

NASA Astrophysics Data System (ADS)

Kahraman, Mehmet; Mullen, Emma R.; Korkmaz, Aysun; Wachsmann-Hogiu, Sebastian

2017-03-01

Plasmonics is an emerging field that examines the interaction between light and metallic nanostructures at the metal-dielectric interface. Surface-enhanced Raman scattering (SERS) is a powerful analytical technique that uses plasmonics to obtain detailed chemical information of molecules or molecular assemblies adsorbed or attached to nanostructured metallic surfaces. For bioanalytical applications, these surfaces are engineered to optimize for high enhancement factors and molecular specificity. In this review we focus on the fabrication of SERS substrates and their use for bioanalytical applications. We review the fundamental mechanisms of SERS and parameters governing SERS enhancement. We also discuss developments in the field of novel SERS substrates. This includes the use of different materials, sizes, shapes, and architectures to achieve high sensitivity and specificity as well as tunability or flexibility. Different fundamental approaches are discussed, such as label-free and functional assays. In addition, we highlight recent relevant advances for bioanalytical SERS applied to small molecules, proteins, DNA, and biologically relevant nanoparticles. Subsequently, we discuss the importance of data analysis and signal detection schemes to achieve smaller instruments with low cost for SERS-based point-of-care technology developments. Finally, we review the main advantages and challenges of SERS-based biosensing and provide a brief outlook.

Development of Clinically Relevant Implantable Pressure Sensors: Perspectives and Challenges

PubMed Central

Clausen, Ingelin; Glott, Thomas

2014-01-01

This review describes different aspects to consider when developing implantable pressure sensor systems. Measurement of pressure is in general highly important in clinical practice and medical research. Due to the small size, light weight and low energy consumption Micro Electro Mechanical Systems (MEMS) technology represents new possibilities for monitoring of physiological parameters inside the human body. Development of clinical relevant sensors requires close collaboration between technological experts and medical clinicians. Site of operation, size restrictions, patient safety, and required measurement range and resolution, are only some conditions that must be taken into account. An implantable device has to operate under very hostile conditions. Long-term in vivo pressure measurements are particularly demanding because the pressure sensitive part of the sensor must be in direct or indirect physical contact with the medium for which we want to detect the pressure. New sensor packaging concepts are demanded and must be developed through combined effort between scientists in MEMS technology, material science, and biology. Before launching a new medical device on the market, clinical studies must be performed. Regulatory documents and international standards set the premises for how such studies shall be conducted and reported. PMID:25248071

The C-terminal Helix of Pseudomonas aeruginosa Elongation Factor Ts Tunes EF-Tu Dynamics to Modulate Nucleotide Exchange.

PubMed

De Laurentiis, Evelina Ines; Mercier, Evan; Wieden, Hans-Joachim

2016-10-28

Little is known about the conservation of critical kinetic parameters and the mechanistic strategies of elongation factor (EF) Ts-catalyzed nucleotide exchange in EF-Tu in bacteria and particularly in clinically relevant pathogens. EF-Tu from the clinically relevant pathogen Pseudomonas aeruginosa shares over 84% sequence identity with the corresponding elongation factor from Escherichia coli Interestingly, the functionally closely linked EF-Ts only shares 55% sequence identity. To identify any differences in the nucleotide binding properties, as well as in the EF-Ts-mediated nucleotide exchange reaction, we performed a comparative rapid kinetics and mutagenesis analysis of the nucleotide exchange mechanism for both the E. coli and P. aeruginosa systems, identifying helix 13 of EF-Ts as a previously unnoticed regulatory element in the nucleotide exchange mechanism with species-specific elements. Our findings support the base side-first entry of the nucleotide into the binding pocket of the EF-Tu·EF-Ts binary complex, followed by displacement of helix 13 and rapid binding of the phosphate side of the nucleotide, ultimately leading to the release of EF-Ts. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

In silico analysis of antibiotic-induced Clostridium difficile infection: Remediation techniques and biological adaptations

PubMed Central

Carlson, Jean M.

2018-01-01

In this paper we study antibiotic-induced C. difficile infection (CDI), caused by the toxin-producing C. difficile (CD), and implement clinically-inspired simulated treatments in a computational framework that synthesizes a generalized Lotka-Volterra (gLV) model with SIR modeling techniques. The gLV model uses parameters derived from an experimental mouse model, in which the mice are administered antibiotics and subsequently dosed with CD. We numerically identify which of the experimentally measured initial conditions are vulnerable to CD colonization, then formalize the notion of CD susceptibility analytically. We simulate fecal transplantation, a clinically successful treatment for CDI, and discover that both the transplant timing and transplant donor are relevant to the the efficacy of the treatment, a result which has clinical implications. We incorporate two nongeneric yet dangerous attributes of CD into the gLV model, sporulation and antibiotic-resistant mutation, and for each identify relevant SIR techniques that describe the desired attribute. Finally, we rely on the results of our framework to analyze an experimental study of fecal transplants in mice, and are able to explain observed experimental results, validate our simulated results, and suggest model-motivated experiments. PMID:29451873

Solitonic dynamics and excitations of the nonlinear Schrödinger equation with third-order dispersion in non-Hermitian PT-symmetric potentials.

PubMed

Chen, Yong; Yan, Zhenya

2016-03-22

Solitons are of the important significant in many fields of nonlinear science such as nonlinear optics, Bose-Einstein condensates, plamas physics, biology, fluid mechanics, and etc. The stable solitons have been captured not only theoretically and experimentally in both linear and nonlinear Schrödinger (NLS) equations in the presence of non-Hermitian potentials since the concept of the parity-time -symmetry was introduced in 1998. In this paper, we present novel bright solitons of the NLS equation with third-order dispersion in some complex -symmetric potentials (e.g., physically relevant -symmetric Scarff-II-like and harmonic-Gaussian potentials). We find stable nonlinear modes even if the respective linear -symmetric phases are broken. Moreover, we also use the adiabatic changes of the control parameters to excite the initial modes related to exact solitons to reach stable nonlinear modes. The elastic interactions of two solitons are exhibited in the third-order NLS equation with -symmetric potentials. Our results predict the dynamical phenomena of soliton equations in the presence of third-order dispersion and -symmetric potentials arising in nonlinear fiber optics and other physically relevant fields.

Solitonic dynamics and excitations of the nonlinear Schrödinger equation with third-order dispersion in non-Hermitian PT-symmetric potentials

PubMed Central

Chen, Yong; Yan, Zhenya

2016-01-01

Solitons are of the important significant in many fields of nonlinear science such as nonlinear optics, Bose-Einstein condensates, plamas physics, biology, fluid mechanics, and etc. The stable solitons have been captured not only theoretically and experimentally in both linear and nonlinear Schrödinger (NLS) equations in the presence of non-Hermitian potentials since the concept of the parity-time -symmetry was introduced in 1998. In this paper, we present novel bright solitons of the NLS equation with third-order dispersion in some complex -symmetric potentials (e.g., physically relevant -symmetric Scarff-II-like and harmonic-Gaussian potentials). We find stable nonlinear modes even if the respective linear -symmetric phases are broken. Moreover, we also use the adiabatic changes of the control parameters to excite the initial modes related to exact solitons to reach stable nonlinear modes. The elastic interactions of two solitons are exhibited in the third-order NLS equation with -symmetric potentials. Our results predict the dynamical phenomena of soliton equations in the presence of third-order dispersion and -symmetric potentials arising in nonlinear fiber optics and other physically relevant fields. PMID:27002543

Development of clinically relevant implantable pressure sensors: perspectives and challenges.

PubMed

Clausen, Ingelin; Glott, Thomas

2014-09-22

This review describes different aspects to consider when developing implantable pressure sensor systems. Measurement of pressure is in general highly important in clinical practice and medical research. Due to the small size, light weight and low energy consumption Micro Electro Mechanical Systems (MEMS) technology represents new possibilities for monitoring of physiological parameters inside the human body. Development of clinical relevant sensors requires close collaboration between technological experts and medical clinicians.  Site of operation, size restrictions, patient safety, and required measurement range and resolution, are only some conditions that must be taken into account. An implantable device has to operate under very hostile conditions. Long-term in vivo pressure measurements are particularly demanding because the pressure sensitive part of the sensor must be in direct or indirect physical contact with the medium for which we want to detect the pressure. New sensor packaging concepts are demanded and must be developed through combined effort between scientists in MEMS technology, material science, and biology. Before launching a new medical device on the market, clinical studies must be performed. Regulatory documents and international standards set the premises for how such studies shall be conducted and reported.

Topological robustness analysis of protein interaction networks reveals key targets for overcoming chemotherapy resistance in glioma

NASA Astrophysics Data System (ADS)

Azevedo, Hátylas; Moreira-Filho, Carlos Alberto

2015-11-01

Biological networks display high robustness against random failures but are vulnerable to targeted attacks on central nodes. Thus, network topology analysis represents a powerful tool for investigating network susceptibility against targeted node removal. Here, we built protein interaction networks associated with chemoresistance to temozolomide, an alkylating agent used in glioma therapy, and analyzed their modular structure and robustness against intentional attack. These networks showed functional modules related to DNA repair, immunity, apoptosis, cell stress, proliferation and migration. Subsequently, network vulnerability was assessed by means of centrality-based attacks based on the removal of node fractions in descending orders of degree, betweenness, or the product of degree and betweenness. This analysis revealed that removing nodes with high degree and high betweenness was more effective in altering networks’ robustness parameters, suggesting that their corresponding proteins may be particularly relevant to target temozolomide resistance. In silico data was used for validation and confirmed that central nodes are more relevant for altering proliferation rates in temozolomide-resistant glioma cell lines and for predicting survival in glioma patients. Altogether, these results demonstrate how the analysis of network vulnerability to topological attack facilitates target prioritization for overcoming cancer chemoresistance.

In silico analysis of antibiotic-induced Clostridium difficile infection: Remediation techniques and biological adaptations.

PubMed

Jones, Eric W; Carlson, Jean M

2018-02-01

In this paper we study antibiotic-induced C. difficile infection (CDI), caused by the toxin-producing C. difficile (CD), and implement clinically-inspired simulated treatments in a computational framework that synthesizes a generalized Lotka-Volterra (gLV) model with SIR modeling techniques. The gLV model uses parameters derived from an experimental mouse model, in which the mice are administered antibiotics and subsequently dosed with CD. We numerically identify which of the experimentally measured initial conditions are vulnerable to CD colonization, then formalize the notion of CD susceptibility analytically. We simulate fecal transplantation, a clinically successful treatment for CDI, and discover that both the transplant timing and transplant donor are relevant to the the efficacy of the treatment, a result which has clinical implications. We incorporate two nongeneric yet dangerous attributes of CD into the gLV model, sporulation and antibiotic-resistant mutation, and for each identify relevant SIR techniques that describe the desired attribute. Finally, we rely on the results of our framework to analyze an experimental study of fecal transplants in mice, and are able to explain observed experimental results, validate our simulated results, and suggest model-motivated experiments.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters

USGS Publications Warehouse

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters.

PubMed

Grisham, Blake A; Boal, Clint W; Haukos, David A; Davis, Dawn M; Boydston, Kathy K; Dixon, Charles; Heck, Willard R

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

PURY: a database of geometric restraints of hetero compounds for refinement in complexes with macromolecular structures.

PubMed

Andrejasic, Miha; Praaenikar, Jure; Turk, Dusan

2008-11-01

The number and variety of macromolecular structures in complex with ;hetero' ligands is growing. The need for rapid delivery of correct geometric parameters for their refinement, which is often crucial for understanding the biological relevance of the structure, is growing correspondingly. The current standard for describing protein structures is the Engh-Huber parameter set. It is an expert data set resulting from selection and analysis of the crystal structures gathered in the Cambridge Structural Database (CSD). Clearly, such a manual approach cannot be applied to the vast and ever-growing number of chemical compounds. Therefore, a database, named PURY, of geometric parameters of chemical compounds has been developed, together with a server that accesses it. PURY is a compilation of the whole CSD. It contains lists of atom classes and bonds connecting them, as well as angle, chirality, planarity and conformation parameters. The current compilation is based on CSD 5.28 and contains 1978 atom classes and 32,702 bonding, 237,068 angle, 201,860 dihedral and 64,193 improper geometric restraints. Analysis has confirmed that the restraints from the PURY database are suitable for use in macromolecular crystal structure refinement and should be of value to the crystallographic community. The database can be accessed through the web server http://pury.ijs.si/, which creates topology and parameter files from deposited coordinates in suitable forms for the refinement programs MAIN, CNS and REFMAC. In the near future, the server will move to the CSD website http://pury.ccdc.cam.ac.uk/.

Online model checking approach based parameter estimation to a neuronal fate decision simulation model in Caenorhabditis elegans with hybrid functional Petri net with extension.

PubMed

Li, Chen; Nagasaki, Masao; Koh, Chuan Hock; Miyano, Satoru

2011-05-01

Mathematical modeling and simulation studies are playing an increasingly important role in helping researchers elucidate how living organisms function in cells. In systems biology, researchers typically tune many parameters manually to achieve simulation results that are consistent with biological knowledge. This severely limits the size and complexity of simulation models built. In order to break this limitation, we propose a computational framework to automatically estimate kinetic parameters for a given network structure. We utilized an online (on-the-fly) model checking technique (which saves resources compared to the offline approach), with a quantitative modeling and simulation architecture named hybrid functional Petri net with extension (HFPNe). We demonstrate the applicability of this framework by the analysis of the underlying model for the neuronal cell fate decision model (ASE fate model) in Caenorhabditis elegans. First, we built a quantitative ASE fate model containing 3327 components emulating nine genetic conditions. Then, using our developed efficient online model checker, MIRACH 1.0, together with parameter estimation, we ran 20-million simulation runs, and were able to locate 57 parameter sets for 23 parameters in the model that are consistent with 45 biological rules extracted from published biological articles without much manual intervention. To evaluate the robustness of these 57 parameter sets, we run another 20 million simulation runs using different magnitudes of noise. Our simulation results concluded that among these models, one model is the most reasonable and robust simulation model owing to the high stability against these stochastic noises. Our simulation results provide interesting biological findings which could be used for future wet-lab experiments.

miRNA profiling in gastrointestinal stromal tumors: implication as diagnostic and prognostic markers.

PubMed

Nannini, Margherita; Ravegnini, Gloria; Angelini, Sabrina; Astolfi, Annalisa; Biasco, Guido; Pantaleo, Maria A

2015-01-01

MicroRNAs are a class of short noncoding RNAs, that play a relevant role in multiple biological processes, such as differentiation, proliferation and apoptosis. Gastrointestinal stromal tumors (GIST) are considered as a paradigm of molecular biology in solid tumors worldwide, and after the discovery of specific alterations in the KIT and PDGFRA genes, they have emerged from anonymity to become a model for targeted therapy. Epigenetics have an emerging and relevant role in different steps of GIST biology such as tumorigenesis, disease progression, prognosis and drug resistance. The aim of the present review was to summarize the current evidence about the role of microRNAs in GIST, including their potential application as well as their limits.

Review: bioprinting: a beginning.

PubMed

Mironov, Vladimir; Reis, Nuno; Derby, Brian

2006-04-01

An increasing demand for directed assembly of biologically relevant materials, with prescribed three-dimensional hierarchical organizations, is stimulating technology developments with the ultimate goal of re-creating multicellular tissues and organs de novo. Existing techniques, mostly adapted from other applications or fields of research, are capable of independently meeting partial requirements for engineering biological or biomimetic structures, but their integration toward organ engineering is proving difficult. Inspired by recent developments in material transfer processes operating at all relevant length scales--from nano to macro--which are amenable to biological elements, a new research field of bioprinting and biopatterning has emerged. Here we present a short review regarding the framework, state of the art, and perspectives of this new field, based on the findings presented at a recent international workshop.

Origin of the spike-timing-dependent plasticity rule

NASA Astrophysics Data System (ADS)

Cho, Myoung Won; Choi, M. Y.

2016-08-01

A biological synapse changes its efficacy depending on the difference between pre- and post-synaptic spike timings. Formulating spike-timing-dependent interactions in terms of the path integral, we establish a neural-network model, which makes it possible to predict relevant quantities rigorously by means of standard methods in statistical mechanics and field theory. In particular, the biological synaptic plasticity rule is shown to emerge as the optimal form for minimizing the free energy. It is further revealed that maximization of the entropy of neural activities gives rise to the competitive behavior of biological learning. This demonstrates that statistical mechanics helps to understand rigorously key characteristic behaviors of a neural network, thus providing the possibility of physics serving as a useful and relevant framework for probing life.

Sting_RDB: a relational database of structural parameters for protein analysis with support for data warehousing and data mining.

PubMed

Oliveira, S R M; Almeida, G V; Souza, K R R; Rodrigues, D N; Kuser-Falcão, P R; Yamagishi, M E B; Santos, E H; Vieira, F D; Jardine, J G; Neshich, G

2007-10-05

An effective strategy for managing protein databases is to provide mechanisms to transform raw data into consistent, accurate and reliable information. Such mechanisms will greatly reduce operational inefficiencies and improve one's ability to better handle scientific objectives and interpret the research results. To achieve this challenging goal for the STING project, we introduce Sting_RDB, a relational database of structural parameters for protein analysis with support for data warehousing and data mining. In this article, we highlight the main features of Sting_RDB and show how a user can explore it for efficient and biologically relevant queries. Considering its importance for molecular biologists, effort has been made to advance Sting_RDB toward data quality assessment. To the best of our knowledge, Sting_RDB is one of the most comprehensive data repositories for protein analysis, now also capable of providing its users with a data quality indicator. This paper differs from our previous study in many aspects. First, we introduce Sting_RDB, a relational database with mechanisms for efficient and relevant queries using SQL. Sting_rdb evolved from the earlier, text (flat file)-based database, in which data consistency and integrity was not guaranteed. Second, we provide support for data warehousing and mining. Third, the data quality indicator was introduced. Finally and probably most importantly, complex queries that could not be posed on a text-based database, are now easily implemented. Further details are accessible at the Sting_RDB demo web page: http://www.cbi.cnptia.embrapa.br/StingRDB.

Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific

NASA Astrophysics Data System (ADS)

Hoshiba, Yasuhiro; Hirata, Takafumi; Shigemitsu, Masahito; Nakano, Hideyuki; Hashioka, Taketo; Masuda, Yoshio; Yamanaka, Yasuhiro

2018-06-01

Ecosystem models are used to understand ecosystem dynamics and ocean biogeochemical cycles and require optimum physiological parameters to best represent biological behaviours. These physiological parameters are often tuned up empirically, while ecosystem models have evolved to increase the number of physiological parameters. We developed a three-dimensional (3-D) lower-trophic-level marine ecosystem model known as the Nitrogen, Silicon and Iron regulated Marine Ecosystem Model (NSI-MEM) and employed biological data assimilation using a micro-genetic algorithm to estimate 23 physiological parameters for two phytoplankton functional types in the western North Pacific. The estimation of the parameters was based on a one-dimensional simulation that referenced satellite data for constraining the physiological parameters. The 3-D NSI-MEM optimized by the data assimilation improved the timing of a modelled plankton bloom in the subarctic and subtropical regions compared to the model without data assimilation. Furthermore, the model was able to improve not only surface concentrations of phytoplankton but also their subsurface maximum concentrations. Our results showed that surface data assimilation of physiological parameters from two contrasting observatory stations benefits the representation of vertical plankton distribution in the western North Pacific.

Modulating biological events by biophysics: an innovative molecular methodology using ion cyclotron resonance--a pilot study.

PubMed

Corbellini, Ezio; Corbellini, Monica; Licciardello, Orazio; Marotta, Francesco

2014-04-01

The QUEC PHISIS(™) technology, based on the theory of coherence domains of water, is the most advanced application of quantum electrodynamics coherence suitable for transferring highly targeted and personalized electromagnetic signals to the living cells. Several experimental studies in aged rats confirm its beneficial action on vital cellular parameters while also optimizing the bioavailability and absorption of fundamental elements in cellular metabolism. Clinical observations have followed and have strengthened its applicability in healthy volunteers and in patients with complex diseases such as cardiovascular, neuromuscular, and metabolic disorders. Our pilot study on severely compromised, frail subjects corroborates its relevance. The delivery of correct frequencies has the potential to become a safe, very affordable, and effective therapeutic modality that is amenable to being integrated with pharmacological drugs, thus representing a substantial innovation in medical practice.

Kinetics and thermodynamics of oxidation mediated reaction in L-cysteine and its methyl and ethyl esters in dimethyl sulfoxide-d6 by NMR spectroscopy

NASA Astrophysics Data System (ADS)

Dougherty, Ryan J.; Singh, Jaideep; Krishnan, V. V.

2017-03-01

L-Cysteine (L-Cys), L-Cysteine methyl ester (L-CysME) or L-Cysteine ethyl ester (L-CysEE), when dissolved in dimethyl sulfoxide, undergoes an oxidation process. This process is slow enough and leads to nuclear magnetic resonance (NMR) spectral changes that could be monitored in real time. The oxidation mediated transition is modeled as a pseudo-first order kinetics and the thermodynamic parameters are estimated using the Eyring's formulation. L-Cysteine and their esters are often used as biological models due to the remarkable thiol group that can be found in different oxidation states. This oxidation mediated transition is due to the combination of thiol oxidation to a disulfide followed by solvent-induced effects may be relevant in designing cysteine-based molecular models.

Metastable Prepores in Tension-Free Lipid Bilayers

NASA Astrophysics Data System (ADS)

Ting, Christina L.; Awasthi, Neha; Müller, Marcus; Hub, Jochen S.

2018-03-01

The formation and closure of aqueous pores in lipid bilayers is a key step in various biophysical processes. Large pores are well described by classical nucleation theory, but the free-energy landscape of small, biologically relevant pores has remained largely unexplored. The existence of small and metastable "prepores" was hypothesized decades ago from electroporation experiments, but resolving metastable prepores from theoretical models remained challenging. Using two complementary methods—atomistic simulations and self-consistent field theory of a minimal lipid model—we determine the parameters for which metastable prepores occur in lipid membranes. Both methods consistently suggest that pore metastability depends on the relative volume ratio between the lipid head group and lipid tails: lipids with a larger head-group volume fraction (or shorter saturated tails) form metastable prepores, whereas lipids with a smaller head-group volume fraction (or longer unsaturated tails) form unstable prepores.

Surface growth kinematics via local curve evolution.

PubMed

Moulton, Derek E; Goriely, Alain

2014-01-01

A mathematical framework is developed to model the kinematics of surface growth for objects that can be generated by evolving a curve in space, such as seashells and horns. Growth is dictated by a growth velocity vector field defined at every point on a generating curve. A local orthonormal basis is attached to each point of the generating curve and the velocity field is given in terms of the local coordinate directions, leading to a fully local and elegant mathematical structure. Several examples of increasing complexity are provided, and we demonstrate how biologically relevant structures such as logarithmic shells and horns emerge as analytical solutions of the kinematics equations with a small number of parameters that can be linked to the underlying growth process. Direct access to cell tracks and local orientation enables for connections to be made to the underlying growth process.

The European nanometrology landscape.

PubMed

Leach, Richard K; Boyd, Robert; Burke, Theresa; Danzebrink, Hans-Ulrich; Dirscherl, Kai; Dziomba, Thorsten; Gee, Mark; Koenders, Ludger; Morazzani, Valérie; Pidduck, Allan; Roy, Debdulal; Unger, Wolfgang E S; Yacoot, Andrew

2011-02-11

This review paper summarizes the European nanometrology landscape from a technical perspective. Dimensional and chemical nanometrology are discussed first as they underpin many of the developments in other areas of nanometrology. Applications for the measurement of thin film parameters are followed by two of the most widely relevant families of functional properties: measurement of mechanical and electrical properties at the nanoscale. Nanostructured materials and surfaces, which are seen as key materials areas having specific metrology challenges, are covered next. The final section describes biological nanometrology, which is perhaps the most interdisciplinary applications area, and presents unique challenges. Within each area, a review is provided of current status, the capabilities and limitations of current techniques and instruments, and future directions being driven by emerging industrial measurement requirements. Issues of traceability, standardization, national and international programmes, regulation and skills development will be discussed in a future paper.

The European nanometrology landscape

NASA Astrophysics Data System (ADS)

Leach, Richard K.; Boyd, Robert; Burke, Theresa; Danzebrink, Hans-Ulrich; Dirscherl, Kai; Dziomba, Thorsten; Gee, Mark; Koenders, Ludger; Morazzani, Valérie; Pidduck, Allan; Roy, Debdulal; Unger, Wolfgang E. S.; Yacoot, Andrew

2011-02-01

This review paper summarizes the European nanometrology landscape from a technical perspective. Dimensional and chemical nanometrology are discussed first as they underpin many of the developments in other areas of nanometrology. Applications for the measurement of thin film parameters are followed by two of the most widely relevant families of functional properties: measurement of mechanical and electrical properties at the nanoscale. Nanostructured materials and surfaces, which are seen as key materials areas having specific metrology challenges, are covered next. The final section describes biological nanometrology, which is perhaps the most interdisciplinary applications area, and presents unique challenges. Within each area, a review is provided of current status, the capabilities and limitations of current techniques and instruments, and future directions being driven by emerging industrial measurement requirements. Issues of traceability, standardization, national and international programmes, regulation and skills development will be discussed in a future paper.

Enhancing light-harvesting power with coherent vibrational interactions: A quantum heat engine picture

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

Killoran, N.; Huelga, S. F.; Plenio, M. B.

Recent evidence suggests that quantum effects may have functional importance in biological light-harvesting systems. Along with delocalized electronic excitations, it is now suspected that quantum coherent interactions with certain near-resonant vibrations may contribute to light-harvesting performance. However, the actual quantum advantage offered by such coherent vibrational interactions has not yet been established. We investigate a quantum design principle, whereby coherent exchange of single energy quanta between electronic and vibrational degrees of freedom can enhance a light-harvesting system’s power above what is possible by thermal mechanisms alone. We present a prototype quantum heat engine which cleanly illustrates this quantum design principlemore » and quantifies its quantum advantage using thermodynamic measures of performance. We also demonstrate the principle’s relevance in parameter regimes connected to natural light-harvesting structures.« less

Sleep mechanisms: Sleep deprivation and detection of changing levels of consciousness

NASA Technical Reports Server (NTRS)

Dement, W. C.; Barchas, J. D.

1972-01-01

An attempt was made to obtain information relevant to assessing the need to sleep and make up for lost sleep. Physiological and behavioral parameters were used as measuring parameters. Sleep deprivation in a restricted environment, derivation of data relevant to determining sleepiness from EEG, and the development of the Sanford Sleepiness Scale were discussed.

Public Understanding of Plant Biology: Voices from the Bottom of the Garden

ERIC Educational Resources Information Center

Watts, Mike

2015-01-01

Many household gardeners accumulate considerable knowledge of plant biology through a range of informal learning sources. This knowledge seldom relates to school biology and is driven by interest, keen motivation and what is termed here "vital relevance." A small opportunity sample of 12 gardeners (6 M, 6 F) is interviewed in terms of…

Piquing Student Interest with Pharmacology: An Interdisciplinary Program Helps High School Students Learn Biology and Chemistry Principles

ERIC Educational Resources Information Center

Halpin, Myra J.; Hoeffler, Leanne; Schwartz-Bloom, Rochelle D.

2005-01-01

To help students learn science concepts, Pharmacology Education Partnership (PEP)--a science education program that incorporates relevant topics related to drugs and drug abuse into standard biology and chemistry curricula was developed. The interdisciplinary PEP curriculum provides six modules to teach biology and chemistry principles within the…

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

De Vos, Winnok H., E-mail: winnok.devos@uantwerpen.be; Cell Systems and Imaging Research Group, Department of Molecular Biotechnology, Ghent University, Ghent; Beghuin, Didier

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALMmore » ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.« less

Biological Relevance of Free Radicals and Nitroxides.

PubMed

Prescott, Christopher; Bottle, Steven E

2017-06-01

Nitroxides are stable, kinetically-persistent free radicals which have been successfully used in the study and intervention of oxidative stress, a critical issue pertaining to cellular health which results from an imbalance in the levels of damaging free radicals and redox-active species in the cellular environment. This review gives an overview of some of the biological processes that produce radicals and other reactive oxygen species with relevance to oxidative stress, and then discusses interactions of nitroxides with these species in terms of the use of nitroxides as redox-sensitive probes and redox-active therapeutic agents.

Monitoring Membrane Hydration with 2-(Dimethylamino)-6-Acylnaphtalenes Fluorescent Probes.

PubMed

Bagatolli, Luis A

2015-01-01

A family of polarity sensitive fluorescent probes (2-(dimethylamino)-6-acylnaphtalenes, i.e. LAURDAN, PRODAN, ACDAN) was introduced by Gregorio Weber in 1979, with the aim to monitor solvent relaxation phenomena on protein matrices. In the following years, however, PRODAN and particularly LAURDAN, were used to study membrane lateral structure and associated dynamics. Once incorporated into membranes, the (nanosecond) fluorescent decay of these probes is strongly affected by changes in the local polarity and relaxation dynamics of restricted water molecules existing at the membrane/water interface. For instance, when glycerophospholipid containing membranes undertake a solid ordered (gel) to liquid disordered phase transition the fluorescence emission maximum of these probes shift ~ 50 nm with a significant change in their fluorescence lifetime. Furthermore, the fluorescence parameters of LAURDAN and PRODAN are exquisitely sensitive to cholesterol effects, allowing interpretations that correlate changes in membrane packing with membrane hydration. Different membrane model systems as well as innate biological membranes have been studied with this family of probes allowing interesting comparative studies. This chapter presents a short historical overview about these fluorescent reporters, discusses on different models proposed to explain their sensitivity to membrane hydration, and includes relevant examples from experiments performed in artificial and biological membranes.

Characterizing Flexible and Instrinsically Unstructured Biological Macromolecules by SAS using the Porod-Debye Law

PubMed Central

Rambo, Robert P.; Tainer, John A.

2011-01-01

Unstructured proteins, RNA or DNA components provide functionally important flexibility that is key to many macromolecular assemblies throughout cell biology. As objective, quantitative experimental measures of flexibility and disorder in solution are limited, small angle scattering (SAS), and in particular small angle X-ray scattering (SAXS), provides a critical technology to assess macromolecular flexibility as well as shape and assembly. Here, we consider the Porod-Debye law as a powerful tool for detecting biopolymer flexibility in SAS experiments. We show that the Porod-Debye region fundamentally describes the nature of the scattering intensity decay, which captures information needed for distinguishing between folded and flexible particles. Particularly for comparative SAS experiments, application of the law, as described here, can distinguish between discrete conformational changes and localized flexibility relevant to molecular recognition and interaction networks. This approach aids insightful analyses of fully and partly flexible macromolecules that is more robust and conclusive than traditional Kratky analyses. Furthermore, we demonstrate for prototypic SAXS data that the ability to calculate particle density by the Porod-Debye criteria, as shown here, provides an objective quality assurance parameter that may prove of general use for SAXS modeling and validation. PMID:21509745

Partition coefficients of organic compounds between water and imidazolium-, pyridinium-, and phosphonium-based ionic liquids.

PubMed

Padró, Juan M; Pellegrino Vidal, Rocío B; Reta, Mario

2014-12-01

The partition coefficients, P IL/w, of several compounds, some of them of biological and pharmacological interest, between water and room-temperature ionic liquids based on the imidazolium, pyridinium, and phosphonium cations, namely 1-octyl-3-methylimidazolium hexafluorophosphate, N-octylpyridinium tetrafluorophosphate, trihexyl(tetradecyl)phosphonium chloride, trihexyl(tetradecyl)phosphonium bromide, trihexyl(tetradecyl)phosphonium bis(trifluoromethylsulfonyl)imide, and trihexyl(tetradecyl)phosphonium dicyanamide, were accurately measured. In this way, we extended our database of partition coefficients in room-temperature ionic liquids previously reported. We employed the solvation parameter model with different probe molecules (the training set) to elucidate the chemical interactions involved in the partition process and discussed the most relevant differences among the three types of ionic liquids. The multiparametric equations obtained with the aforementioned model were used to predict the partition coefficients for compounds (the test set) not present in the training set, most being of biological and pharmacological interest. An excellent agreement between calculated and experimental log P IL/w values was obtained. Thus, the obtained equations can be used to predict, a priori, the extraction efficiency for any compound using these ionic liquids as extraction solvents in liquid-liquid extractions.

Fighting Cancer with Mathematics and Viruses.

PubMed

Santiago, Daniel N; Heidbuechel, Johannes P W; Kandell, Wendy M; Walker, Rachel; Djeu, Julie; Engeland, Christine E; Abate-Daga, Daniel; Enderling, Heiko

2017-08-23

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex antitumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these research fields to increase the value of the preclinical development and the therapeutic efficacy of the resulting treatments.

A new standard model for milk yield in dairy cows based on udder physiology at the milking-session level.

PubMed

Gasqui, Patrick; Trommenschlager, Jean-Marie

2017-08-21

Milk production in dairy cow udders is a complex and dynamic physiological process that has resisted explanatory modelling thus far. The current standard model, Wood's model, is empirical in nature, represents yield in daily terms, and was published in 1967. Here, we have developed a dynamic and integrated explanatory model that describes milk yield at the scale of the milking session. Our approach allowed us to formally represent and mathematically relate biological features of known relevance while accounting for stochasticity and conditional elements in the form of explicit hypotheses, which could then be tested and validated using real-life data. Using an explanatory mathematical and biological model to explore a physiological process and pinpoint potential problems (i.e., "problem finding"), it is possible to filter out unimportant variables that can be ignored, retaining only those essential to generating the most realistic model possible. Such modelling efforts are multidisciplinary by necessity. It is also helpful downstream because model results can be compared with observed data, via parameter estimation using maximum likelihood and statistical testing using model residuals. The process in its entirety yields a coherent, robust, and thus repeatable, model.

Femtosecond Optoinjection of Intact Tobacco BY-2 Cells Using a Reconfigurable Photoporation Platform

PubMed Central

Mitchell, Claire A.; Kalies, Stefan; Cizmár, Tomás; Heisterkamp, Alexander; Torrance, Lesley; Roberts, Alison G.; Gunn-Moore, Frank J.; Dholakia, Kishan

2013-01-01

A tightly-focused ultrashort pulsed laser beam incident upon a cell membrane has previously been shown to transiently increase cell membrane permeability while maintaining the viability of the cell, a technique known as photoporation. This permeability can be used to aid the passage of membrane-impermeable biologically-relevant substances such as dyes, proteins and nucleic acids into the cell. Ultrashort-pulsed lasers have proven to be indispensable for photoporating mammalian cells but they have rarely been applied to plant cells due to their larger sizes and rigid and thick cell walls, which significantly hinders the intracellular delivery of exogenous substances. Here we demonstrate and quantify femtosecond optical injection of membrane impermeable dyes into intact BY-2 tobacco plant cells growing in culture, investigating both optical and biological parameters. Specifically, we show that the long axial extent of a propagation invariant (“diffraction-free”) Bessel beam, which relaxes the requirements for tight focusing on the cell membrane, outperforms a standard Gaussian photoporation beam, achieving up to 70% optoinjection efficiency. Studies on the osmotic effects of culture media show that a hypertonic extracellular medium was found to be necessary to reduce turgor pressure and facilitate molecular entry into the cells. PMID:24244456

Femtosecond optoinjection of intact tobacco BY-2 cells using a reconfigurable photoporation platform.

PubMed

Mitchell, Claire A; Kalies, Stefan; Cizmár, Tomás; Heisterkamp, Alexander; Torrance, Lesley; Roberts, Alison G; Gunn-Moore, Frank J; Dholakia, Kishan

2013-01-01

A tightly-focused ultrashort pulsed laser beam incident upon a cell membrane has previously been shown to transiently increase cell membrane permeability while maintaining the viability of the cell, a technique known as photoporation. This permeability can be used to aid the passage of membrane-impermeable biologically-relevant substances such as dyes, proteins and nucleic acids into the cell. Ultrashort-pulsed lasers have proven to be indispensable for photoporating mammalian cells but they have rarely been applied to plant cells due to their larger sizes and rigid and thick cell walls, which significantly hinders the intracellular delivery of exogenous substances. Here we demonstrate and quantify femtosecond optical injection of membrane impermeable dyes into intact BY-2 tobacco plant cells growing in culture, investigating both optical and biological parameters. Specifically, we show that the long axial extent of a propagation invariant ("diffraction-free") Bessel beam, which relaxes the requirements for tight focusing on the cell membrane, outperforms a standard Gaussian photoporation beam, achieving up to 70% optoinjection efficiency. Studies on the osmotic effects of culture media show that a hypertonic extracellular medium was found to be necessary to reduce turgor pressure and facilitate molecular entry into the cells.

Fighting Cancer with Mathematics and Viruses

PubMed Central

Santiago, Daniel N.; Heidbuechel, Johannes P. W.; Kandell, Wendy M.; Walker, Rachel; Djeu, Julie; Abate-Daga, Daniel; Enderling, Heiko

2017-01-01

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex antitumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these research fields to increase the value of the preclinical development and the therapeutic efficacy of the resulting treatments. PMID:28832539

Particle deposition onto people in a transit venue

DOE PAGES

Liljegren, James C.; Brown, David F.; Lunden, Melissa M.; ...

2016-07-11

Following the release of an aerosolized biological agent in a transit venue, material deposited on waiting passengers and subsequently shed from their clothing may significantly magnify the scope and consequences of such an attack. Published estimates of the relevant particle deposition and resuspension parameters for complex, real-world environments such as a transit facility are non-existent. In this study, measurements of particle deposition velocity onto cotton fabric samples affixed to stationary and walking persons in a large multimodal transit facility were obtained for tracer particle releases carried out as part of a larger study of subway airflows and particulate transport. Depositionmore » velocities onto cotton and wool were also obtained using a novel automated sampling mechanism deployed at locations in the transit facility and throughout the subway. The data revealed higher deposition velocities than have been previously reported for people exposed in test chambers or office environments. Furthermore, the relatively high rates of deposition onto people in a transit venue obtained in this study suggest it is possible that fomite transport by subway and commuter/regional rail passengers could present a significant mechanism for rapidly dispersing a biological agent throughout a metropolitan area and beyond.« less

Design and implementation of an automated compound management system in support of lead optimization.

PubMed

Quintero, Catherine; Kariv, Ilona

2009-06-01

To meet the needs of the increasingly rapid and parallelized lead optimization process, a fully integrated local compound storage and liquid handling system was designed and implemented to automate the generation of assay-ready plates directly from newly submitted and cherry-picked compounds. A key feature of the system is the ability to create project- or assay-specific compound-handling methods, which provide flexibility for any combination of plate types, layouts, and plate bar-codes. Project-specific workflows can be created by linking methods for processing new and cherry-picked compounds and control additions to produce a complete compound set for both biological testing and local storage in one uninterrupted workflow. A flexible cherry-pick approach allows for multiple, user-defined strategies to select the most appropriate replicate of a compound for retesting. Examples of custom selection parameters include available volume, compound batch, and number of freeze/thaw cycles. This adaptable and integrated combination of software and hardware provides a basis for reducing cycle time, fully automating compound processing, and ultimately increasing the rate at which accurate, biologically relevant results can be produced for compounds of interest in the lead optimization process.

Particle deposition onto people in a transit venue

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

Liljegren, James C.; Brown, David F.; Lunden, Melissa M.

Following the release of an aerosolized biological agent in a transit venue, material deposited on waiting passengers and subsequently shed from their clothing may significantly magnify the scope and consequences of such an attack. Published estimates of the relevant particle deposition and resuspension parameters for complex, real-world environments such as a transit facility are non-existent. In this study, measurements of particle deposition velocity onto cotton fabric samples affixed to stationary and walking persons in a large multimodal transit facility were obtained for tracer particle releases carried out as part of a larger study of subway airflows and particulate transport. Depositionmore » velocities onto cotton and wool were also obtained using a novel automated sampling mechanism deployed at locations in the transit facility and throughout the subway. The data revealed higher deposition velocities than have been previously reported for people exposed in test chambers or office environments. Furthermore, the relatively high rates of deposition onto people in a transit venue obtained in this study suggest it is possible that fomite transport by subway and commuter/regional rail passengers could present a significant mechanism for rapidly dispersing a biological agent throughout a metropolitan area and beyond.« less

Using Bioinformatics Approach to Explore the Pharmacological Mechanisms of Multiple Ingredients in Shuang-Huang-Lian

PubMed Central

Zhang, Bai-xia; Li, Jian; Gu, Hao; Li, Qiang; Zhang, Qi; Zhang, Tian-jiao; Wang, Yun; Cai, Cheng-ke

2015-01-01

Due to the proved clinical efficacy, Shuang-Huang-Lian (SHL) has developed a variety of dosage forms. However, the in-depth research on targets and pharmacological mechanisms of SHL preparations was scarce. In the presented study, the bioinformatics approaches were adopted to integrate relevant data and biological information. As a result, a PPI network was built and the common topological parameters were characterized. The results suggested that the PPI network of SHL exhibited a scale-free property and modular architecture. The drug target network of SHL was structured with 21 functional modules. According to certain modules and pharmacological effects distribution, an antitumor effect and potential drug targets were predicted. A biological network which contained 26 subnetworks was constructed to elucidate the antipneumonia mechanism of SHL. We also extracted the subnetwork to explicitly display the pathway where one effective component acts on the pneumonia related targets. In conclusions, a bioinformatics approach was established for exploring the drug targets, pharmacological activity distribution, effective components of SHL, and its mechanism of antipneumonia. Above all, we identified the effective components and disclosed the mechanism of SHL from the view of system. PMID:26495421

Bone marrow fibrosis in myelodysplastic syndromes: a prospective evaluation including mutational analysis

PubMed Central

Ramos, Fernando; Robledo, Cristina; Izquierdo-García, Francisco Miguel; Suárez-Vilela, Dimas; Benito, Rocío; Fuertes, Marta; Insunza, Andrés; Barragán, Eva; del Rey, Mónica; de Morales, José María García-Ruiz; Tormo, Mar; Salido, Eduardo; Zamora, Lurdes; Pedro, Carmen; Sánchez-del-Real, Javier; Díez-Campelo, María; del Cañizo, Consuelo; Sanz, Guillermo F.; Hernández-Rivas, Jesús María

2016-01-01

The biological and molecular events that underlie bone marrow fibrosis in patients with myelodysplastic syndromes are poorly understood, and its prognostic role in the era of the Revised International Prognostic Scoring System (IPSS-R) is not yet fully determined. We have evaluated the clinical and biological events that underlie bone marrow fibrotic changes, as well as its prognostic role, in a well-characterized prospective patient cohort (n=77) of primary MDS patients. The degree of marrow fibrosis was linked to parameters of erythropoietic failure, marrow cellularity, p53 protein accumulation, WT1 gene expression, and serum levels of CXCL9 and CXCL10, but not to other covariates including the IPSS-R score. The presence of bone marrow fibrosis grade 2 or higher was associated with the presence of mutations in cohesin complex genes (31.5% vs. 5.4%, p=0.006). By contrast, mutations in CALR, JAK2, PDGFRA, PDGFRB, and TP53 were very rare. Survival analysis showed that marrow fibrosis grade 2 or higher was a relevant significant predictor for of overall survival, and independent of age, performance status, and IPSS-R score in multivariate analysis. PMID:27127180

Genetics of regular exercise and sedentary behaviors.

PubMed

de Geus, Eco J C; Bartels, Meike; Kaprio, Jaakko; Lightfoot, J Timothy; Thomis, Martine

2014-08-01

Studies on the determinants of physical activity have traditionally focused on social factors and environmental barriers, but recent research has shown the additional importance of biological factors, including genetic variation. Here we review the major tenets of this research to arrive at three major conclusions: First, individual differences in physical activity traits are significantly influenced by genetic factors, but genetic contribution varies strongly over age, with heritability of leisure time exercise behavior ranging from 27% to 84% and heritability of sedentary behaviors ranging from 9% to 48%. Second, candidate gene approaches based on animal or human QTLs or on biological relevance (e.g., dopaminergic or cannabinoid activity in the brain, or exercise performance influencing muscle physiology) have not yet yielded the necessary evidence to specify the genetic mechanisms underlying the heritability of physical activity traits. Third, there is significant genetic modulation of the beneficial effects of daily physical activity patterns on strength and endurance improvements and on health-related parameters like body mass index. Further increases in our understanding of the genetic determinants of sedentary and exercise behaviors as well as the genetic modulation of their effects on fitness and health will be key to meaningful future intervention on these behaviors.

Comparative Study of the Minichromosome Maintenance Proteins Complex (MCM 4/5/6) in Ameloblastoma and Unicystic Ameloblastoma.

PubMed

Apellániz, Delmira; Pereira-Prado, Vanesa; Sicco, Estefania; Vigil-Bastitta, Gabriela; González-González, Rogelio; Mosqueda-Taylor, Adalberto; Molina-Frechero, Nelly; Hernandez, Marcela; Sánchez-Romero, Celeste; Bologna-Molina, Ronell

2018-05-01

Solid/conventional ameloblastoma (AM) and unicystic ameloblastoma (UAM) are the most frequent benign epithelial odontogenic tumors located in the maxillary region, and their treatment usually consists of extensive surgical resection. Therefore, it is relevant to study molecular markers to better understand the biological behavior of these tumors. The aim of this study was to describe and compare the expression of proteins related to cellular proliferation: Ki-67 and MCM4-6 complex. An immunohistochemistry technique was performed, with antibodies against Ki-67, MCM4, MCM5, and MCM6, in 10 AM and 10 UAM tumors. The results were quantified using label index and analyzed statistically. AM and UAM had greater expression of MCM6, followed by MCM5, MCM4, and Ki-67 ( P < .05). Immunoexpression of Ki-67 and MCM5 was exclusively nuclear, whereas the expression of MCM4 and MCM6 was nuclear and cytoplasmic. The results suggest that MCM5 is a trustable cell proliferation marker with higher sensitivity compared with Ki-67 and may be useful to predict the biological behavior of AM and UAM. Despite this, further studies are necessary, including a correlation with clinical parameters to confirm these findings.

Seamount ecology and dynamics: A multidisciplinary data set from repeated surveys at different seamounts in the Northeast Atlantic and Mediterranean (2003 - 2013).

NASA Astrophysics Data System (ADS)

Mohn, C.; Christiansen, B.; Denda, A.; George, K. H.; Kaufmann, M.; Maranhão, M.; Martin, B.; Metzger, T.; Peine, F.; Schuster, A.; Springer, B.; Stefanowitsch, B.; Turnewitsch, R.; Wehrmann, H.

2016-02-01

Seamounts are amongst the most common physiographic open ocean systems, but remoteness and geographic complexity have limited the number of integrated and multidisciplinary seamount surveys in the past. As a consequence, important aspects of seamount ecology and dynamics remain poorly studied. Here we present a multi-parameter data set from individual and repeated seamount surveys conducted at different sites in the Northeast Atlantic and Eastern Mediterranean between 2003 and 2013. The main objective of these surveys was to establish a collection of ecosystem relevant descriptors and to develop a better understanding of seamount ecosystem composition and variability in different dynamical and bio-geographic environments. Measurements were conducted at four seamounts in the Northeast Atlantic (Ampère, Sedlo, Seine, Senghor) and two seamounts in the Eastern Mediterranean (Anaximenes, Eratosthenes). The data set comprises records from a total number of 11 cruises including physical oceanography (temperature, salinity, pressure, currents), biology (phytoplankton, zooplankton, fish, benthos) and biogeochemistry (sedimentary particle dynamics, carbon flux). The resulting multi-disciplinary data collection provides a unique opportunity for comparative studies of seamount ecosystem structure and dynamics between different physical, biological and biogeochemical regimes

A Comparison of Multiple Methods for Estimating Parasitemia of Hemogregarine Hemoparasites (Apicomplexa: Adeleorina) and Its Application for Studying Infection in Natural Populations

PubMed Central

Maia, João P.; Harris, D. James; Carranza, Salvador; Gómez-Díaz, Elena

2014-01-01

Identifying factors influencing infection patterns among hosts is critical for our understanding of the evolution and impact of parasitism in natural populations. However, the correct estimation of infection parameters depends on the performance of detection and quantification methods. In this study, we designed a quantitative PCR (qPCR) assay targeting the 18 S rRNA gene to estimate prevalence and intensity of Hepatozoon infection and compared its performance with microscopy and PCR. Using qPCR, we also compared various protocols that differ in the biological source and the extraction methods. Our results show that the qPCR approach on DNA extracted from blood samples, regardless of the extraction protocol, provided the most sensitive estimates of Hepatozoon infection parameters; while allowed us to differentiate between mixed infections of Adeleorinid (Hepatozoon) and Eimeriorinid (Schellackia and Lankesterella), based on the analysis of melting curves. We also show that tissue and saline methods can be used as low-cost alternatives in parasitological studies. The next step was to test our qPCR assay in a biological context, and for this purpose we investigated infection patterns between two sympatric lacertid species, which are naturally infected with apicomplexan hemoparasites, such as the genera Schellackia (Eimeriorina) and Hepatozoon (Adeleorina). From a biological standpoint, we found a positive correlation between Hepatozoon intensity of infection and host body size within each host species, being significantly higher in males, and higher in the smaller sized host species. These variations can be associated with a number of host intrinsic factors, like hormonal and immunological traits, that require further investigation. Our findings are relevant as they pinpoint the importance of accounting for methodological issues to better estimate infection in parasitological studies, and illustrate how between-host factors can influence parasite distributions in sympatric natural populations. PMID:24743340

Finite Element Model of Oxygen Transport for the Design of Geometrically Complex Microfluidic Devices Used in Biological Studies

PubMed Central

Fraser, Graham M.; Goldman, Daniel; Ellis, Christopher G.

2016-01-01

Red blood cells play a crucial role in the local regulation of oxygen supply in the microcirculation through the oxygen dependent release of ATP. Since red blood cells serve as an oxygen sensor for the circulatory system, the dynamics of ATP release determine the effectiveness of red blood cells to relate the oxygen levels to the vessels. Previous work has focused on the feasibility of developing a microfluidic system to measure the dynamics of ATP release. The objective was to determine if a steep oxygen gradient could be developed in the channel to cause a rapid decrease in hemoglobin oxygen saturation in order to measure the corresponding levels of ATP released from the red blood cells. In the present study, oxygen transport simulations were used to optimize the geometric design parameters for a similar system which is easier to fabricate. The system is composed of a microfluidic device stacked on top of a large, gas impermeable flow channel with a hole to allow gas exchange. The microfluidic device is fabricated using soft lithography in polydimethyl-siloxane, an oxygen permeable material. Our objective is twofold: (1) optimize the parameters of our system and (2) develop a method to assess the oxygen distribution in complex 3D microfluidic device geometries. 3D simulations of oxygen transport were performed to simulate oxygen distribution throughout the device. The simulations demonstrate that microfluidic device geometry plays a critical role in molecule exchange, for instance, changing the orientation of the short wide microfluidic channel results in a 97.17% increase in oxygen exchange. Since microfluidic devices have become a more prominent tool in biological studies, understanding the transport of oxygen and other biological molecules in microfluidic devices is critical for maintaining a physiologically relevant environment. We have also demonstrated a method to assess oxygen levels in geometrically complex microfluidic devices. PMID:27829071

Finite Element Model of Oxygen Transport for the Design of Geometrically Complex Microfluidic Devices Used in Biological Studies.

PubMed

Sové, Richard J; Fraser, Graham M; Goldman, Daniel; Ellis, Christopher G

2016-01-01

Red blood cells play a crucial role in the local regulation of oxygen supply in the microcirculation through the oxygen dependent release of ATP. Since red blood cells serve as an oxygen sensor for the circulatory system, the dynamics of ATP release determine the effectiveness of red blood cells to relate the oxygen levels to the vessels. Previous work has focused on the feasibility of developing a microfluidic system to measure the dynamics of ATP release. The objective was to determine if a steep oxygen gradient could be developed in the channel to cause a rapid decrease in hemoglobin oxygen saturation in order to measure the corresponding levels of ATP released from the red blood cells. In the present study, oxygen transport simulations were used to optimize the geometric design parameters for a similar system which is easier to fabricate. The system is composed of a microfluidic device stacked on top of a large, gas impermeable flow channel with a hole to allow gas exchange. The microfluidic device is fabricated using soft lithography in polydimethyl-siloxane, an oxygen permeable material. Our objective is twofold: (1) optimize the parameters of our system and (2) develop a method to assess the oxygen distribution in complex 3D microfluidic device geometries. 3D simulations of oxygen transport were performed to simulate oxygen distribution throughout the device. The simulations demonstrate that microfluidic device geometry plays a critical role in molecule exchange, for instance, changing the orientation of the short wide microfluidic channel results in a 97.17% increase in oxygen exchange. Since microfluidic devices have become a more prominent tool in biological studies, understanding the transport of oxygen and other biological molecules in microfluidic devices is critical for maintaining a physiologically relevant environment. We have also demonstrated a method to assess oxygen levels in geometrically complex microfluidic devices.

A comparison of multiple methods for estimating parasitemia of hemogregarine hemoparasites (apicomplexa: adeleorina) and its application for studying infection in natural populations.

PubMed

Maia, João P; Harris, D James; Carranza, Salvador; Gómez-Díaz, Elena

2014-01-01

Identifying factors influencing infection patterns among hosts is critical for our understanding of the evolution and impact of parasitism in natural populations. However, the correct estimation of infection parameters depends on the performance of detection and quantification methods. In this study, we designed a quantitative PCR (qPCR) assay targeting the 18 S rRNA gene to estimate prevalence and intensity of Hepatozoon infection and compared its performance with microscopy and PCR. Using qPCR, we also compared various protocols that differ in the biological source and the extraction methods. Our results show that the qPCR approach on DNA extracted from blood samples, regardless of the extraction protocol, provided the most sensitive estimates of Hepatozoon infection parameters; while allowed us to differentiate between mixed infections of Adeleorinid (Hepatozoon) and Eimeriorinid (Schellackia and Lankesterella), based on the analysis of melting curves. We also show that tissue and saline methods can be used as low-cost alternatives in parasitological studies. The next step was to test our qPCR assay in a biological context, and for this purpose we investigated infection patterns between two sympatric lacertid species, which are naturally infected with apicomplexan hemoparasites, such as the genera Schellackia (Eimeriorina) and Hepatozoon (Adeleorina). From a biological standpoint, we found a positive correlation between Hepatozoon intensity of infection and host body size within each host species, being significantly higher in males, and higher in the smaller sized host species. These variations can be associated with a number of host intrinsic factors, like hormonal and immunological traits, that require further investigation. Our findings are relevant as they pinpoint the importance of accounting for methodological issues to better estimate infection in parasitological studies, and illustrate how between-host factors can influence parasite distributions in sympatric natural populations.

Biophysical and medical safety basis of laser emission

NASA Astrophysics Data System (ADS)

Paltsev, Yu.; Levina, A.

1996-01-01

Laser equipment may inflict serious losses to human health if safety norms established by relevant standards and other documentation are not properly observed. It is explained by physical properties of laser emission (LE) which differs from general light sources by quantitative behavior of such parameters as the degrees of coherence, monochromaticity, brightness, polarization. Thus, biological effects due to laser emission, as a rule, are more expressed comparing with other types of emission from other spontaneous light sources. LE effects biological tissues through the density of energy flow and impulse duration. It is common knowledge nowadays that LE biological action is assessed by two criteria: physical parameters and absorptive properties of tissues exposed to rays. LE causes the greatest danger to the eyes due to their specific structure. The next target organ vulnerable to LE is skin. Pathological changes of skin depend on the LE power, time of exposure, wave length, and the extent of skin pigmentation. Along with different kinds of damage directly in the tissues exposed to rays, LE may cause changes in organs and body systems subject to indirect exposure. It is important that these changes may develop due to low intensity levels of LE that do not cause local damage. National and international standards on LE safety are based on maximum allowable levels (MAL) of exposure. It has been generally accepted that the main MAL criterion is LE threshold minimal exposure which causes damage to retina, eyes, and skin. As distinct from foreign safety standards, hygienic norms and regulations are in force in the Russian Federation where additional co-efficients along with standard generally accepted MAL values have been introduced for the persons who are subject to occupational regular exposure to lasers. This approach has been chosen after the results of follow-up and health studies of these occupational contingents have been analyzed, and experiments on laboratory animals assessed.

Automatic classification of fluorescence and optical diffusion spectroscopy data in neuro-oncology

NASA Astrophysics Data System (ADS)

Savelieva, T. A.; Loshchenov, V. B.; Goryajnov, S. A.; Potapov, A. A.

2018-04-01

The complexity of the biological tissue spectroscopic analysis due to the overlap of biological molecules' absorption spectra, multiple scattering effect, as well as measurement geometry in vivo has caused the relevance of this work. In the neurooncology the problem of tumor boundaries delineation is especially acute and requires the development of new methods of intraoperative diagnosis. Methods of optical spectroscopy allow detecting various diagnostically significant parameters non-invasively. 5-ALA induced protoporphyrin IX is frequently used as fluorescent tumor marker in neurooncology. At the same time analysis of the concentration and the oxygenation level of haemoglobin and significant changes of light scattering in tumor tissues have a high diagnostic value. This paper presents an original method for the simultaneous registration of backward diffuse reflectance and fluorescence spectra, which allows defining all the parameters listed above simultaneously. The clinical studies involving 47 patients with intracranial glial tumors of II-IV Grades were carried out in N.N. Burdenko National Medical Research Center of Neurosurgery. To register the spectral dependences the spectroscopic system LESA- 01-BIOSPEC was used with specially developed w-shaped diagnostic fiber optic probe. The original algorithm of combined spectroscopic signal processing was developed. We have created a software and hardware, which allowed (as compared with the methods currently used in neurosurgical practice) to increase the sensitivity of intraoperative demarcation of intracranial tumors from 78% to 96%, specificity of 60% to 82%. The result of analysis of different techniques of automatic classification shows that in our case the most appropriate is the k Nearest Neighbors algorithm with cubic metrics.

Linear modeling of human hand-arm dynamics relevant to right-angle torque tool interaction.

PubMed

Ay, Haluk; Sommerich, Carolyn M; Luscher, Anthony F

2013-10-01

A new protocol was evaluated for identification of stiffness, mass, and damping parameters employing a linear model for human hand-arm dynamics relevant to right-angle torque tool use. Powered torque tools are widely used to tighten fasteners in manufacturing industries. While these tools increase accuracy and efficiency of tightening processes, operators are repetitively exposed to impulsive forces, posing risk of upper extremity musculoskeletal injury. A novel testing apparatus was developed that closely mimics biomechanical exposure in torque tool operation. Forty experienced torque tool operators were tested with the apparatus to determine model parameters and validate the protocol for physical capacity assessment. A second-order hand-arm model with parameters extracted in the time domain met model accuracy criterion of 5% for time-to-peak displacement error in 93% of trials (vs. 75% for frequency domain). Average time-to-peak handle displacement and relative peak handle force errors were 0.69 ms and 0.21%, respectively. Model parameters were significantly affected by gender and working posture. Protocol and numerical calculation procedures provide an alternative method for assessing mechanical parameters relevant to right-angle torque tool use. The protocol more closely resembles tool use, and calculation procedures demonstrate better performance of parameter extraction using time domain system identification methods versus frequency domain. Potential future applications include parameter identification for in situ torque tool operation and equipment development for human hand-arm dynamics simulation under impulsive forces that could be used for assessing torque tools based on factors relevant to operator health (handle dynamics and hand-arm reaction force).

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

PubMed

Erguler, Kamil; Stumpf, Michael P H

2011-05-01

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

Autofluorescence of atmospheric bioaerosols - fluorescent biomolecules and potential interferences

NASA Astrophysics Data System (ADS)

Pöhlker, C.; Huffman, J. A.; Pöschl, U.

2012-01-01

Primary biological aerosol particles (PBAP) are an important subset of air particulate matter with a substantial contribution to the organic aerosol fraction and potentially strong effects on public health and climate. Recent progress has been made in PBAP quantification by utilizing real-time bioaerosol detectors based on the principle that specific organic molecules of biological origin such as proteins, coenzymes, cell wall compounds and pigments exhibit intrinsic fluorescence. The properties of many fluorophores have been well documented, but it is unclear which are most relevant for detection of atmospheric PBAP. The present study provides a systematic synthesis of literature data on potentially relevant biological fluorophores. We analyze and discuss their relative importance for the detection of fluorescent biological aerosol particles (FBAP) by online instrumentation for atmospheric measurements such as the ultraviolet aerodynamic particle sizer (UV-APS) or the wide issue bioaerosol sensor (WIBS). In addition, we provide new laboratory measurement data for selected compounds using bench-top fluorescence spectroscopy. Relevant biological materials were chosen for comparison with existing literature data and to fill in gaps of understanding. The excitation-emission matrices (EEM) exhibit pronounced peaks at excitation wavelengths of ~280 nm and ~360 nm, confirming the suitability of light sources used for online detection of FBAP. They also show, however, that valuable information is missed by instruments that do not record full emission spectra at multiple wavelengths of excitation, and co-occurrence of multiple fluorophores within a detected sample will likely confound detailed molecular analysis. Selected non-biological materials were also analyzed to assess their possible influence on FBAP detection and generally exhibit only low levels of background-corrected fluorescent emission. This study strengthens the hypothesis that ambient supermicron particle fluorescence in wavelength ranges used for most FBAP instruments is likely to be dominated by biological material and that such instrumentation is able to discriminate between FBAP and non-biological material in many situations. More detailed follow-up studies on single particle fluorescence are still required to reduce these uncertainties further, however.

Autofluorescence of atmospheric bioaerosols - fluorescent biomolecules and potential interferences

NASA Astrophysics Data System (ADS)

Pöhlker, C.; Huffman, J. A.; Pöschl, U.

2011-09-01

Primary biological aerosol particles (PBAP) are an important subset of air particulate matter with a substantial contribution to the organic aerosol fraction and potentially strong effects on public health and climate. Recent progress has been made in PBAP quantification by utilizing real-time bioaerosol detectors based on the principle that specific organic molecules of biological origin such as proteins, coenzymes, cell wall compounds and pigments exhibit intrinsic fluorescence. The properties of many fluorophores have been well documented, but it is unclear which are most relevant for detection of atmospheric PBAP. The present study provides a systematic synthesis of literature data on potentially relevant biological fluorophores. We analyze and discuss their relative importance for the detection of fluorescent biological aerosol particles (FBAP) by online instrumentation for atmospheric measurements such as the ultraviolet aerodynamic particle sizer (UV-APS) or the wide issue bioaerosol sensor (WIBS). In addition, we provide new laboratory measurement data for selected compounds using bench-top fluorescence spectroscopy. Relevant biological materials were chosen for comparison with existing literature data and to fill in gaps of understanding. The excitation-emission matrices (EEM) exhibit pronounced peaks at excitation wavelengths of ~280 nm and ~360 nm, confirming the suitability of light sources used for online detection of FBAP. They also show, however, that valuable information is missed by instruments that do not record full emission spectra at multiple wavelengths of excitation, and co-occurrence of multiple fluorophores within a detected sample will likely confound detailed molecular analysis. Selected non-biological materials were also analyzed to assess their possible influence on FBAP detection and generally exhibit only low levels of background-corrected fluorescent emission. This study strengthens the hypothesis that ambient supermicron particle fluorescence in wavelength ranges used for most FBAP instruments is likely to be dominated by biological material and that such instrumentation is able to discriminate between FBAP and non-biological material in many situations. More detailed follow-up studies on single particle fluorescence are still required to reduce these uncertainties further, however.

Geostatistical characterisation of geothermal parameters for a thermal aquifer storage site in Germany

NASA Astrophysics Data System (ADS)

Rodrigo-Ilarri, J.; Li, T.; Grathwohl, P.; Blum, P.; Bayer, P.

2009-04-01

The design of geothermal systems such as aquifer thermal energy storage systems (ATES) must account for a comprehensive characterisation of all relevant parameters considered for the numerical design model. Hydraulic and thermal conductivities are the most relevant parameters and its distribution determines not only the technical design but also the economic viability of such systems. Hence, the knowledge of the spatial distribution of these parameters is essential for a successful design and operation of such systems. This work shows the first results obtained when applying geostatistical techniques to the characterisation of the Esseling Site in Germany. In this site a long-term thermal tracer test (> 1 year) was performed. On this open system the spatial temperature distribution inside the aquifer was observed over time in order to obtain as much information as possible that yield to a detailed characterisation both of the hydraulic and thermal relevant parameters. This poster shows the preliminary results obtained for the Esseling Site. It has been observed that the common homogeneous approach is not sufficient to explain the observations obtained from the TRT and that parameter heterogeneity must be taken into account.

Mini-review of the geotechnical parameters of municipal solid waste: Mechanical and biological pre-treated versus raw untreated waste.

PubMed

Petrovic, Igor

2016-09-01

The most viable option for biostabilisation of old sanitary landfills, filled with raw municipal solid waste, is the so-called bioreactor landfill. Even today, bioreactor landfills are viable options in many economically developing countries. However, in order to reduce the biodegradable component of landfilled waste, mechanical and biological treatment has become a widely accepted waste treatment technology, especially in more prosperous countries. Given that mechanical and biological treatment alters the geotechnical properties of raw waste material, the design of sanitary landfills which accepts mechanically and biologically treated waste, should be carried out with a distinct set of geotechnical parameters. However, under the assumption that 'waste is waste', some design engineers might be tempted to use geotechnical parameters of untreated raw municipal solid waste and mechanical and biological pre-treated municipal solid waste interchangeably. Therefore, to provide guidelines for use and to provide an aggregated source of this information, this mini-review provides comparisons of geotechnical parameters of mechanical and biological pre-treated waste and raw untreated waste at various decomposition stages. This comparison reveals reasonable correlations between the hydraulic conductivity values of untreated and mechanical and biological pre-treated municipal solid waste. It is recognised that particle size might have a significant influence on the hydraulic conductivity of both municipal solid waste types. However, the compression ratios and shear strengths of untreated and pre-treated municipal solid waste do not show such strong correlations. Furthermore, another emerging topic that requires appropriate attention is the recovery of resources that are embedded in old landfills. Therefore, the presented results provide a valuable tool for engineers designing landfills for mechanical and biological pre-treated waste or bioreactor landfills for untreated raw waste as well as planning landfill mining projects. © The Author(s) 2016.

Pushing the size limit of de novo structure ensemble prediction guided by sparse SDSL-EPR restraints to 200 residues: The monomeric and homodimeric forms of BAX

PubMed Central

Fischer, Axel W.; Bordignon, Enrica; Bleicken, Stephanie; García-Sáez, Ana J.; Jeschke, Gunnar; Meiler, Jens

2016-01-01

Structure determination remains a challenge for many biologically important proteins. In particular, proteins that adopt multiple conformations often evade crystallization in all biologically relevant states. Although computational de novo protein folding approaches often sample biologically relevant conformations, the selection of the most accurate model for different functional states remains a formidable challenge, in particular, for proteins with more than about 150 residues. Electron paramagnetic resonance (EPR) spectroscopy can obtain limited structural information for proteins in well-defined biological states and thereby assist in selecting biologically relevant conformations. The present study demonstrates that de novo folding methods are able to accurately sample the folds of 192-residue long soluble monomeric Bcl-2-associated X protein (BAX). The tertiary structures of the monomeric and homodimeric forms of BAX were predicted using the primary structure as well as 25 and 11 EPR distance restraints, respectively. The predicted models were subsequently compared to respective NMR/X-ray structures of BAX. EPR restraints improve the protein-size normalized root-mean-square-deviation (RMSD100) of the most accurate models with respect to the NMR/crystal structure from 5.9 Å to 3.9 Å and from 5.7 Å to 3.3 Å, respectively. Additionally, the model discrimination is improved, which is demonstrated by an improvement of the enrichment from 5% to 15% and from 13% to 21%, respectively. PMID:27129417

Single cell biology beyond the era of antibodies: relevance, challenges, and promises in biomedical research.

PubMed

Abraham, Parvin; Maliekal, Tessy Thomas

2017-04-01

Research of the past two decades has proved the relevance of single cell biology in basic research and translational medicine. Successful detection and isolation of specific subsets is the key to understand their functional heterogeneity. Antibodies are conventionally used for this purpose, but their relevance in certain contexts is limited. In this review, we discuss some of these contexts, posing bottle neck for different fields of biology including biomedical research. With the advancement of chemistry, several methods have been introduced to overcome these problems. Even though microfluidics and microraft array are newer techniques exploited for single cell biology, fluorescence-activated cell sorting (FACS) remains the gold standard technique for isolation of cells for many biomedical applications, like stem cell therapy. Here, we present a comprehensive and comparative account of some of the probes that are useful in FACS. Further, we illustrate how these techniques could be applied in biomedical research. It is postulated that intracellular molecular markers like nucleostemin (GNL3), alkaline phosphatase (ALPL) and HIRA can be used for improving the outcome of cardiac as well as bone regeneration. Another field that could utilize intracellular markers is diagnostics, and we propose the use of specific peptide nucleic acid probes (PNPs) against certain miRNAs for cancer surgical margin prediction. The newer techniques for single cell biology, based on intracellular molecules, will immensely enhance the repertoire of possible markers for the isolation of cell types useful in biomedical research.

Comprehensive inventory of protein complexes in the Protein Data Bank from consistent classification of interfaces.

PubMed

Bordner, Andrew J; Gorin, Andrey A

2008-05-12

Protein-protein interactions are ubiquitous and essential for all cellular processes. High-resolution X-ray crystallographic structures of protein complexes can reveal the details of their function and provide a basis for many computational and experimental approaches. Differentiation between biological and non-biological contacts and reconstruction of the intact complex is a challenging computational problem. A successful solution can provide additional insights into the fundamental principles of biological recognition and reduce errors in many algorithms and databases utilizing interaction information extracted from the Protein Data Bank (PDB). We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1) comprehensively collecting all protein-protein interfaces; (2) clustering similar protein-protein interfaces together; (3) estimating the probability that each cluster is relevant based on a diverse set of properties; and (4) combining these scores for each PDB entry in order to predict the complex structure. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions. These interfaces, as well as the predicted protein complexes, are available from the Protein Interface Server (PInS) website (see Availability and requirements section). Our method demonstrates an almost two-fold reduction of the annotation error rate as evaluated on a large benchmark set of complexes validated from the literature. We also estimate relative contributions of each interface property to the accurate discrimination of biologically relevant interfaces and discuss possible directions for further improving the prediction method.

Study of Carrying Capacity Assesment for Natural Fisheries in Jatibarang Reservoir In Semarang City

NASA Astrophysics Data System (ADS)

Sujono, Bambang; Anggoro, Sutrisno

2018-02-01

Jatibarang reservoir serves as water supply in dry season and controlling flood in Semarang City. This reservoir is stem Kreo River which cathment areas of 54 km2, pool of area 110 ha and volume is 20 billion m3. This reservoir is potential to develop as natural fisheries area. The goals of this research were to explore existing condition of physical, biological as well as chemical parameter; carrying capacity assessment for natural fisheries; determining appropriate fish species to be developed in Jatibarang reservoir. This research was done in descriptive explorative scheme. Field survey and laboratory analyses were conducted to identify physical, chemical and biological parameters of the water. Physical parameters measured were temperature and water brightness. Chemical parameters measured were pH, DO, phosphate, Ammonia, nitrites and nitrate, while biological parameter measured were chlorophyll-a concentration. Carrying capacity analyses was done referred to the Government Regulation Number 82, 2001 that regulate the management of water quality and water pollution control. Based on the research, it showed that the existing condition of physical, chemical and biological parameters were still good to be used for natural fisheries. Based on TSI index, it classified as eutrofic water. Furthermore, tilapia fish (Oreochromis mossambicus), nile tilapia (Oreochromis niloticus) tawes (Barbonymus gonionotus) and carper fish (Cyprinus carpio) were considered as best species for natural fisheries in Jatibarang Reservoir.

Biological Weapons -- Still a Relevant Threat

DTIC Science & Technology

2012-03-22

destruction in general, and biological weapons in particular. The IHS Janes: Defence and Security Intelligence & Analysis website notes that a number of...responder capabilities, and intelligence agency inputs. There needs, as well, to be continued research and development of sensor technologies, which...Mass Destruction – Radiological, Chemical and Biological,‖ 109 10 Mark, J. Carson; Taylor, Theodore; Eyster, Eugene; Maraman, William; Wechsler

PyDREAM: high-dimensional parameter inference for biological models in python.

PubMed

Shockley, Erin M; Vrugt, Jasper A; Lopez, Carlos F; Valencia, Alfonso

2018-02-15

Biological models contain many parameters whose values are difficult to measure directly via experimentation and therefore require calibration against experimental data. Markov chain Monte Carlo (MCMC) methods are suitable to estimate multivariate posterior model parameter distributions, but these methods may exhibit slow or premature convergence in high-dimensional search spaces. Here, we present PyDREAM, a Python implementation of the (Multiple-Try) Differential Evolution Adaptive Metropolis [DREAM(ZS)] algorithm developed by Vrugt and ter Braak (2008) and Laloy and Vrugt (2012). PyDREAM achieves excellent performance for complex, parameter-rich models and takes full advantage of distributed computing resources, facilitating parameter inference and uncertainty estimation of CPU-intensive biological models. PyDREAM is freely available under the GNU GPLv3 license from the Lopez lab GitHub repository at http://github.com/LoLab-VU/PyDREAM. c.lopez@vanderbilt.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Apparatus and Methods for Manipulation and Optimization of Biological Systems

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

21 CFR 601.32 - General factors relevant to safety and effectiveness.

Code of Federal Regulations, 2010 CFR

2010-04-01

... SERVICES (CONTINUED) BIOLOGICS LICENSING Diagnostic Radiopharmaceuticals § 601.32 General factors relevant to safety and effectiveness. FDA's determination of the safety and effectiveness of a diagnostic radiopharmaceutical includes consideration of the following: (a) The proposed use of the diagnostic...

The Anatomical Biological Value on Pretreatment (18)F-fluorodeoxyglucose Positron Emission Tomography Computed Tomography Predicts Response and Survival in Locally Advanced Head and Neck Cancer.

PubMed

Ashamalla, Hani; Mattes, Malcolm; Guirguis, Adel; Zaidi, Arifa; Mokhtar, Bahaa; Tejwani, Ajay

2014-05-01

(18)F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) has become increasingly relevant in the staging of head and neck cancers, but its prognostic value is controversial. The objective of this study was to evaluate different PET/CT parameters for their ability to predict response to therapy and survival in patients treated for head and neck cancer. A total of 28 consecutive patients with a variety of newly diagnosed head and neck cancers underwent PET/CT scanning at our institution before initiating definitive radiation therapy. All underwent a posttreatment PET/CT to gauge tumor response. Pretreatment PET/CT parameters calculated include the standardized uptake value (SUV) and the anatomical biological value (ABV), which is the product of SUV and greatest tumor diameter. Maximum and mean values were studied for both SUV and ABV, and correlated with response rate and survival. The mean pretreatment tumor ABVmax decreased from 35.5 to 7.9 (P = 0.0001). Of the parameters tested, only pretreatment ABVmax was significantly different among those patients with a complete response (CR) and incomplete response (22.8 vs. 65, respectively, P = 0.021). This difference was maximized at a cut-off ABVmax of 30 and those patients with ABVmax < 30 were significantly more likely to have a CR compared to those with ABVmax of ≥ 30 (93.8% vs. 50%, respectively, P = 0.023). The 5-year overall survival was 80% compared to 36%, respectively, (P = 0.028). Multivariate analysis confirmed that ABVmax was an independent prognostic factor. Our data supports the use of PET/CT, and specifically ABVmax, as a prognostic factor in head and neck cancer. Patients who have an ABVmax ≥ 30 were more likely to have a poor outcome with chemoradiation alone, and a more aggressive trimodality approach may be indicated in these patients.

Effect of a vegan diet on biomarkers of chemoprevention in females.

PubMed

Verhagen, H; Rauma, A L; Törrönen, R; de Vogel, N; Bruijntjes-Rozier, G C; Drevo, M A; Bogaards, J J; Mykkänen, H

1996-10-01

1. In order to study the potential beneficial effects of a vegan diet, a cross-sectional study was performed and several biomarkers of chemoprevention were measured in a population of female 'living food' eaters ('vegans'; n = 20) vs matched omnivorous controls (n = 20). 2. White blood cells obtained from fresh blood samples were subjected to the single-cell gel-electrophoresis assay. There was no statistically significant difference between the vegans and controls in the parameters 'tail length' and 'tail moment'. However, the 'tail moment' was significantly lower in a subset of the vegans (i.e.in those who did not use any vitamin and/or mineral supplements). 3. Fresh blood samples were exposed in vitro to the mutagen mitomycin C just prior to culturing. After culturing the number of binucleated lymphocytes with micronuclei was scored. There was no difference between the controls and vegans in the incidence of baseline micronuclei, nor in the number of mitomycin C-induced micronuclei. However, a significant correlation (r = -0.64, P < 0.01) between the number of mitomycin C-induced micronuclei and the activity of erythrocyte superoxide dismutase was found in the vegans. The number of baseline micronuclei increased with age in both groups. These findings may be of biological relevance. 4. The content of glutathione-S-transferase-alpha in plasma was not different between the vegans (n = 12) and controls (n = 12). 5. The present data indicate a few differences in biomarkers of chemopreventive potential in strict vegans vs matched omnivorous controls. The significance of these changes as biologically relevant indicators of beneficial effects of vegan diets in humans needs to be determined in studies with a larger number of subjects.

Differentiating Pathway-Specific From Nonspecific Effects in High-Throughput Toxicity Data: A Foundation for Prioritizing Adverse Outcome Pathway Development.

PubMed

Fay, Kellie A; Villeneuve, Daniel L; Swintek, Joe; Edwards, Stephen W; Nelms, Mark D; Blackwell, Brett R; Ankley, Gerald T

2018-06-01

The U.S. Environmental Protection Agency's ToxCast program has screened thousands of chemicals for biological activity, primarily using high-throughput in vitro bioassays. Adverse outcome pathways (AOPs) offer a means to link pathway-specific biological activities with potential apical effects relevant to risk assessors. Thus, efforts are underway to develop AOPs relevant to pathway-specific perturbations detected in ToxCast assays. Previous work identified a "cytotoxic burst" (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared with the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). The prioritization approaches did not appear to be influenced by inter-assay differences in chemical bioavailability. Furthermore, the outcomes were robust based on a variety of different parameters used to define the CTB.

Clofibrate-induced gene expression changes in rat liver: a cross-laboratory analysis using membrane cDNA arrays.

PubMed Central

Baker, Valerie A; Harries, Helen M; Waring, Jeff F; Duggan, Colette M; Ni, Hong A; Jolly, Robert A; Yoon, Lawrence W; De Souza, Angus T; Schmid, Judith E; Brown, Roger H; Ulrich, Roger G; Rockett, John C

2004-01-01

Microarrays have the potential to significantly impact our ability to identify toxic hazards by the identification of mechanistically relevant markers of toxicity. To be useful for risk assessment, however, microarray data must be challenged to determine reliability and interlaboratory reproducibility. As part of a series of studies conducted by the International Life Sciences Institute Health and Environmental Science Institute Technical Committee on the Application of Genomics to Mechanism-Based Risk Assessment, the biological response in rats to the hepatotoxin clofibrate was investigated. Animals were treated with high (250 mg/kg/day) or low (25 mg/kg/day) doses for 1, 3, or 7 days in two laboratories. Clinical chemistry parameters were measured, livers removed for histopathological assessment, and gene expression analysis was conducted using cDNA arrays. Expression changes in genes involved in fatty acid metabolism (e.g., acyl-CoA oxidase), cell proliferation (e.g., topoisomerase II-Alpha), and fatty acid oxidation (e.g., cytochrome P450 4A1), consistent with the mechanism of clofibrate hepatotoxicity, were detected. Observed differences in gene expression levels correlated with the level of biological response induced in the two in vivo studies. Generally, there was a high level of concordance between the gene expression profiles generated from pooled and individual RNA samples. Quantitative real-time polymerase chain reaction was used to confirm modulations for a number of peroxisome proliferator marker genes. Though the results indicate some variability in the quantitative nature of the microarray data, this appears due largely to differences in experimental and data analysis procedures used within each laboratory. In summary, this study demonstrates the potential for gene expression profiling to identify toxic hazards by the identification of mechanistically relevant markers of toxicity. PMID:15033592

An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.

PubMed

Nandi, Sutanu; Subramanian, Abhishek; Sarkar, Ram Rup

2017-07-25

Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems, like imbalanced provision of training datasets, biased choice of the best model for a given balanced dataset, choice of a complex machine learning algorithm, and data-based automated selection of biologically relevant features for classification. Here, we propose a simple support vector machine-based learning strategy for the prediction of essential genes in Escherichia coli K-12 MG1655 metabolism that integrates a non-conventional combination of an appropriate sample balanced training set, a unique organism-specific genotype, phenotype attributes that characterize essential genes, and optimal parameters of the learning algorithm to generate the best machine learning model (the model with the highest accuracy among all the models trained for different sample training sets). For the first time, we also introduce flux-coupled metabolic subnetwork-based features for enhancing the classification performance. Our strategy proves to be superior as compared to previous SVM-based strategies in obtaining a biologically relevant classification of genes with high sensitivity and specificity. This methodology was also trained with datasets of other recent supervised classification techniques for essential gene classification and tested using reported test datasets. The testing accuracy was always high as compared to the known techniques, proving that our method outperforms known methods. Observations from our study indicate that essential genes are conserved among homologous bacterial species, demonstrate high codon usage bias, GC content and gene expression, and predominantly possess a tendency to form physiological flux modules in metabolism.

Behavior of nanoceria in biologically-relevant environments

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

Kumar, Amit; Das, Soumen; Munusamy, Prabhakaran

2014-09-08

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

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

PubMed

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

Determination of the dynamical behaviour of biological materials during impact using a pendulum device

NASA Astrophysics Data System (ADS)

Van Zeebroeck, M.; Tijskens, E.; Van Liedekerke, P.; Deli, V.; De Baerdemaeker, J.; Ramon, H.

2003-09-01

A pendulum device has been developed to measure contact force, displacement and displacement rate of an impactor during its impact on the sample. Displacement, classically measured by double integration of an accelerometer, was determined in an alternative way using a more accurate incremental optical encoder. The parameters of the Kuwabara-Kono contact force model for impact of spheres have been estimated using an optimization method, taking the experimentally measured displacement, displacement rate and contact force into account. The accuracy of the method was verified using a rubber ball. Contact force parameters for the Kuwabara-Kono model have been estimated with success for three biological materials, i.e., apples, tomatoes and potatoes. The variability in the parameter estimations for the biological materials was quite high and can be explained by geometric differences (radius of curvature) and by biological variation of mechanical tissue properties.

Bio-logging of physiological parameters in higher marine vertebrates

NASA Astrophysics Data System (ADS)

Ponganis, Paul J.

2007-02-01

Bio-logging of physiological parameters in higher marine vertebrates had its origins in the field of bio-telemetry in the 1960s and 1970s. The development of microprocessor technology allowed its first application to bio-logging investigations of Weddell seal diving physiology in the early 1980s. Since that time, with the use of increased memory capacity, new sensor technology, and novel data processing techniques, investigators have examined heart rate, temperature, swim speed, stroke frequency, stomach function (gastric pH and motility), heat flux, muscle oxygenation, respiratory rate, diving air volume, and oxygen partial pressure (P) during diving. Swim speed, heart rate, and body temperature have been the most commonly studied parameters. Bio-logging investigation of pressure effects has only been conducted with the use of blood samplers and nitrogen analyses on animals diving at isolated dive holes. The advantages/disadvantages and limitations of recording techniques, probe placement, calibration techniques, and study conditions are reviewed.

Finding Our Way through Phenotypes

PubMed Central

Deans, Andrew R.; Lewis, Suzanna E.; Huala, Eva; Anzaldo, Salvatore S.; Ashburner, Michael; Balhoff, James P.; Blackburn, David C.; Blake, Judith A.; Burleigh, J. Gordon; Chanet, Bruno; Cooper, Laurel D.; Courtot, Mélanie; Csösz, Sándor; Cui, Hong; Dahdul, Wasila; Das, Sandip; Dececchi, T. Alexander; Dettai, Agnes; Diogo, Rui; Druzinsky, Robert E.; Dumontier, Michel; Franz, Nico M.; Friedrich, Frank; Gkoutos, George V.; Haendel, Melissa; Harmon, Luke J.; Hayamizu, Terry F.; He, Yongqun; Hines, Heather M.; Ibrahim, Nizar; Jackson, Laura M.; Jaiswal, Pankaj; James-Zorn, Christina; Köhler, Sebastian; Lecointre, Guillaume; Lapp, Hilmar; Lawrence, Carolyn J.; Le Novère, Nicolas; Lundberg, John G.; Macklin, James; Mast, Austin R.; Midford, Peter E.; Mikó, István; Mungall, Christopher J.; Oellrich, Anika; Osumi-Sutherland, David; Parkinson, Helen; Ramírez, Martín J.; Richter, Stefan; Robinson, Peter N.; Ruttenberg, Alan; Schulz, Katja S.; Segerdell, Erik; Seltmann, Katja C.; Sharkey, Michael J.; Smith, Aaron D.; Smith, Barry; Specht, Chelsea D.; Squires, R. Burke; Thacker, Robert W.; Thessen, Anne; Fernandez-Triana, Jose; Vihinen, Mauno; Vize, Peter D.; Vogt, Lars; Wall, Christine E.; Walls, Ramona L.; Westerfeld, Monte; Wharton, Robert A.; Wirkner, Christian S.; Woolley, James B.; Yoder, Matthew J.; Zorn, Aaron M.; Mabee, Paula

2015-01-01

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility. PMID:25562316

Finding our way through phenotypes.

PubMed

Deans, Andrew R; Lewis, Suzanna E; Huala, Eva; Anzaldo, Salvatore S; Ashburner, Michael; Balhoff, James P; Blackburn, David C; Blake, Judith A; Burleigh, J Gordon; Chanet, Bruno; Cooper, Laurel D; Courtot, Mélanie; Csösz, Sándor; Cui, Hong; Dahdul, Wasila; Das, Sandip; Dececchi, T Alexander; Dettai, Agnes; Diogo, Rui; Druzinsky, Robert E; Dumontier, Michel; Franz, Nico M; Friedrich, Frank; Gkoutos, George V; Haendel, Melissa; Harmon, Luke J; Hayamizu, Terry F; He, Yongqun; Hines, Heather M; Ibrahim, Nizar; Jackson, Laura M; Jaiswal, Pankaj; James-Zorn, Christina; Köhler, Sebastian; Lecointre, Guillaume; Lapp, Hilmar; Lawrence, Carolyn J; Le Novère, Nicolas; Lundberg, John G; Macklin, James; Mast, Austin R; Midford, Peter E; Mikó, István; Mungall, Christopher J; Oellrich, Anika; Osumi-Sutherland, David; Parkinson, Helen; Ramírez, Martín J; Richter, Stefan; Robinson, Peter N; Ruttenberg, Alan; Schulz, Katja S; Segerdell, Erik; Seltmann, Katja C; Sharkey, Michael J; Smith, Aaron D; Smith, Barry; Specht, Chelsea D; Squires, R Burke; Thacker, Robert W; Thessen, Anne; Fernandez-Triana, Jose; Vihinen, Mauno; Vize, Peter D; Vogt, Lars; Wall, Christine E; Walls, Ramona L; Westerfeld, Monte; Wharton, Robert A; Wirkner, Christian S; Woolley, James B; Yoder, Matthew J; Zorn, Aaron M; Mabee, Paula

2015-01-01

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.

Quantifying the Relationship between Curvature and Electric Potential in Lipid Bilayers.

PubMed

Bruhn, Dennis S; Lomholt, Michael A; Khandelia, Himanshu

2016-06-02

Cellular membranes mediate vital cellular processes by being subject to curvature and transmembrane electrical potentials. Here we build upon the existing theory for flexoelectricity in liquid crystals to quantify the coupling between lipid bilayer curvature and membrane potentials. Using molecular dynamics simulations, we show that headgroup dipole moments, the lateral pressure profile across the bilayer, and spontaneous curvature all systematically change with increasing membrane potentials. In particular, there is a linear dependence between the bending moment (the product of bending rigidity and spontaneous curvature) and the applied membrane potentials. We show that biologically relevant membrane potentials can induce biologically relevant curvatures corresponding to radii of around 500 nm. The implications of flexoelectricity in lipid bilayers are thus likely to be of considerable consequence both in biology and in model lipid bilayer systems.

Philosophy of race meets population genetics.

PubMed

Spencer, Quayshawn

2015-08-01

In this paper, I respond to four common semantic and metaphysical objections that philosophers of race have launched at scholars who interpret recent human genetic clustering results in population genetics as evidence for biological racial realism. I call these objections 'the discreteness objection', 'the visibility objection', 'the very important objection', and 'the objectively real objection.' After motivating each objection, I show that each one stems from implausible philosophical assumptions about the relevant meaning of 'race' or the nature of biological racial realism. In order to be constructive, I end by offering some advice for how we can productively critique attempts to defend biological racial realism based on recent human genetic clustering results. I also offer a clarification of the relevant human-population genetic research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mammalian lipoxygenases and their biological relevance.

PubMed

Kuhn, Hartmut; Banthiya, Swathi; van Leyen, Klaus

2015-04-01

Lipoxygenases (LOXs) form a heterogeneous class of lipid peroxidizing enzymes, which have been implicated not only in cell proliferation and differentiation but also in the pathogenesis of various diseases with major public health relevance. As other fatty acid dioxygenases LOXs oxidize polyunsaturated fatty acids to their corresponding hydroperoxy derivatives, which are further transformed to bioactive lipid mediators (eicosanoids and related substances). On the other hand, lipoxygenases are key players in the regulation of the cellular redox homeostasis, which is an important element in gene expression regulation. Although the first mammalian lipoxygenases were discovered 40 years ago and although the enzymes have been well characterized with respect to their structural and functional properties the biological roles of the different lipoxygenase isoforms are not completely understood. This review is aimed at summarizing the current knowledge on the physiological roles of different mammalian LOX-isoforms and their patho-physiological function in inflammatory, metabolic, hyperproliferative, neurodegenerative and infectious disorders. This article is part of a Special Issue entitled "Oxygenated metabolism of PUFA: analysis and biological relevance". Copyright © 2014 Elsevier B.V. All rights reserved.

Electrochemical detection of a single cytomegalovirus at an ultramicroelectrode and its antibody anchoring

PubMed Central

Dick, Jeffrey E.; Hilterbrand, Adam T.; Boika, Aliaksei; Upton, Jason W.; Bard, Allen J.

2015-01-01

We report observations of stochastic collisions of murine cytomegalovirus (MCMV) on ultramicroelectrodes (UMEs), extending the observation of discrete collision events on UMEs to biologically relevant analytes. Adsorption of an antibody specific for a virion surface glycoprotein allowed differentiation of MCMV from MCMV bound by antibody from the collision frequency decrease and current magnitudes in the electrochemical collision experiments, which shows the efficacy of the method to size viral samples. To add selectivity to the technique, interactions between MCMV, a glycoprotein-specific primary antibody to MCMV, and polystyrene bead “anchors,” which were functionalized with a secondary antibody specific to the Fc region of the primary antibody, were used to affect virus mobility. Bead aggregation was observed, and the extent of aggregation was measured using the electrochemical collision technique. Scanning electron microscopy and optical microscopy further supported aggregate shape and extent of aggregation with and without MCMV. This work extends the field of collisions to biologically relevant antigens and provides a novel foundation upon which qualitative sensor technology might be built for selective detection of viruses and other biologically relevant analytes. PMID:25870261

GPER (GPR30): A Nongenomic Receptor (GPCR) for Steroid Hormones with Implications for Cardiovascular Disease and Cancer.

PubMed

Feldman, Ross D; Limbird, Lee E

2017-01-06

Although the rapid effects of steroids, such as estrogen and aldosterone, were postulated originally to be nongenomic, it is now appreciated that activation of such signaling pathways via a steroid-acting G protein-coupled receptor, the G protein estrogen receptor (GPER), has important transcription-dependent outcomes in the regulation of cell growth and programmed cell death secondary to GPER-regulated second-messenger pathways. GPER is expressed ubiquitously and has diverse biological effects, including regulation of endocrine, immune, neuronal, and cardiovascular functions. Perhaps the most biologically important consequences of GPER activation are the regulation of cell growth, migration, and apoptotic cell death. These cell growth regulatory effects, important in cancer biology, are also relevant in the regulation of cardiac and vascular hypertrophy and in the response to ischemia. This review provides a summary of relevant findings of the impact of GPER regulation by either estradiol or aldosterone in in vitro model systems and extends those findings to in vivo studies of direct clinical relevance for development of GPER-directed agents for treatment of cancer and cardiovascular diseases associated with cellular proliferation.

Ocular side effects of biological agents in oncology: what should the clinician be aware of?

PubMed Central

Hager, Tobias; Seitz, B

2014-01-01

During the last 20 years, biologicals have become increasingly relevant in oncologic therapy. Depending on the medication used, there are different profiles of ocular side effects. Although these can be present in up to 70% of patients, they are generally underreported in the literature. Therefore, the pathophysiological details of their development are often poorly understood. Herein we attempt to identify groups of biologicals to which a specific side effect profile can be assigned. We also tried to capture all relevant side effects and therefore conducted several database investigation including Medline, Cochrane library, and the drugs section of the US Food and Drug Administration (FDA), using the following search strings: “name of biological agent (both generic and commercial names)” AND “eye” OR “ocular”. If we found a side effect that has been associated with a drug, we researched Medline using the following search string: “name of biological agent” (both generic and commercial names) AND “term for the specific side effect”. Due to the wealth of material we report only the drugs that are approved by the FDA. PMID:24391443

Determination of morphological parameters of biological cells by analysis of scattered-light distributions

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

Burger, D.E.

1979-11-01

The extraction of morphological parameters from biological cells by analysis of light-scatter patterns is described. A light-scattering measurement system has been designed and constructed that allows one to visually examine and photographically record biological cells or cell models and measure the light-scatter pattern of an individual cell or cell model. Using a laser or conventional illumination, the imaging system consists of a modified microscope with a 35 mm camera attached to record the cell image or light-scatter pattern. Models of biological cells were fabricated. The dynamic range and angular distributions of light scattered from these models was compared to calculatedmore » distributions. Spectrum analysis techniques applied on the light-scatter data give the sought after morphological cell parameters. These results compared favorably to shape parameters of the fabricated cell models confirming the mathematical model procedure. For nucleated biological material, correct nuclear and cell eccentricity as well as the nuclear and cytoplasmic diameters were determined. A method for comparing the flow equivalent of nuclear and cytoplasmic size to the actual dimensions is shown. This light-scattering experiment provides baseline information for automated cytology. In its present application, it involves correlating average size as measured in flow cytology to the actual dimensions determined from this technique. (ERB)« less

Biomarkers and Environmental Stress: Relevance of Cellular Responses in Determining Adverse Outcomes

EPA Science Inventory

Biomarkers are measurable changes in a biological system indicative of an interaction with a chemical, physical, or biological agent. Such changes can be molecular, biochemical, physiological, or histological and can be reflective of either xenobiotic exposures or effects. Molecu...

How is physiology relevant to behavior analysis?

PubMed Central

Reese, Hayne W.

1996-01-01

Physiology is an important biological science; but behavior analysis is not a biological science, and behavior analysts can safely ignore biological processes. However, ignoring products of biological processes might be a serious mistake. The important products include behavior, instinctive drift, behavior potentials, hunger, and many developmental milestones and events. Physiology deals with the sources of such products; behavior analysis can deal with how the products affect behavior, which can be understood without understanding their sources. PMID:22478240

Biological Correlates of Intimate Partner Violence Perpetration

PubMed Central

Pinto, Lavinia A.; Sullivan, Eric L.; Rosenbaum, Alan; Wyngarden, Nicole; Umhau, John C.; Miller, Mark W.; Taft, Casey T.

2013-01-01

An extensive literature documents biological correlates of general aggression, but there has been less focus on biological correlates of intimate partner violence (IPV). The purpose of this review is to summarize the research literature to date that has reported on biological factors in IPV perpetration. We review the existing literature on four domains of biological processes that have been examined with respect to IPV perpetration, including: head injury and neuropsychology; psychophysiology; neurochemistry, metabolism and endocrinology; and genetics. We critique the literature, discuss the clinical relevance of research findings, and provide some recommendations for future biologically-oriented IPV research. PMID:23393423

A conceptual and practical guide to the behavioural evaluation of animal models of the symptomatology and therapy of schizophrenia

PubMed Central

Yee, Benjamin K.; Singer, Philipp

2013-01-01

Schizophrenia is a chronic debilitating brain disorder characterized by a complex set of perceptual and behavioural symptoms that severely disrupt and undermine the patient’s psychological well-being and quality of life. Since the exact disease mechanisms remain essentially unknown, holistic animal models are indispensable tools for any serious investigation into the neurobiology of schizophrenia, including the search of remedies, prevention, and possible biological markers. This review provides some practical advice to those confronted with the task of evaluating their animal models for relevance to schizophrenia that inevitably involves behavioural tests with animals. To a novice, this challenge is not only a technical one, as it also entails attention to interpretative issues concerning validity and translational power. Here, we attempt to offer some guidance to help overcome these obstacles by drawing on our experience on diverse animal models of schizophrenia based on genetics, strain difference, brain lesions, pharmacological induction, and early life developmental manipulations. The review pays equal emphasis on the general (theoretical) considerations in experimental design and the illustration of the problematics related to test parameters and data analysis of selected exemplar behavioural tests. Finally, the individual difference of behavioural expression in relevant tests observed in wild type animals may offer an alternative approach to explore the mechanism of schizophrenia-related behavioural dysfunction at the molecular, cellular and structural levels that are of more immediate relevance to cell and tissue research. PMID:23579553

A computational kinetic model of diffusion for molecular systems.

PubMed

Teo, Ivan; Schulten, Klaus

2013-09-28

Regulation of biomolecular transport in cells involves intra-protein steps like gating and passage through channels, but these steps are preceded by extra-protein steps, namely, diffusive approach and admittance of solutes. The extra-protein steps develop over a 10-100 nm length scale typically in a highly particular environment, characterized through the protein's geometry, surrounding electrostatic field, and location. In order to account for solute energetics and mobility of solutes in this environment at a relevant resolution, we propose a particle-based kinetic model of diffusion based on a Markov State Model framework. Prerequisite input data consist of diffusion coefficient and potential of mean force maps generated from extensive molecular dynamics simulations of proteins and their environment that sample multi-nanosecond durations. The suggested diffusion model can describe transport processes beyond microsecond duration, relevant for biological function and beyond the realm of molecular dynamics simulation. For this purpose the systems are represented by a discrete set of states specified by the positions, volumes, and surface elements of Voronoi grid cells distributed according to a density function resolving the often intricate relevant diffusion space. Validation tests carried out for generic diffusion spaces show that the model and the associated Brownian motion algorithm are viable over a large range of parameter values such as time step, diffusion coefficient, and grid density. A concrete application of the method is demonstrated for ion diffusion around and through the Eschericia coli mechanosensitive channel of small conductance ecMscS.

Cooperativity to increase Turing pattern space for synthetic biology.

PubMed

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

2015-02-20

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

Reproducible, high-throughput synthesis of colloidal nanocrystals for optimization in multidimensional parameter space.

PubMed

Chan, Emory M; Xu, Chenxu; Mao, Alvin W; Han, Gang; Owen, Jonathan S; Cohen, Bruce E; Milliron, Delia J

2010-05-12

While colloidal nanocrystals hold tremendous potential for both enhancing fundamental understanding of materials scaling and enabling advanced technologies, progress in both realms can be inhibited by the limited reproducibility of traditional synthetic methods and by the difficulty of optimizing syntheses over a large number of synthetic parameters. Here, we describe an automated platform for the reproducible synthesis of colloidal nanocrystals and for the high-throughput optimization of physical properties relevant to emerging applications of nanomaterials. This robotic platform enables precise control over reaction conditions while performing workflows analogous to those of traditional flask syntheses. We demonstrate control over the size, size distribution, kinetics, and concentration of reactions by synthesizing CdSe nanocrystals with 0.2% coefficient of variation in the mean diameters across an array of batch reactors and over multiple runs. Leveraging this precise control along with high-throughput optical and diffraction characterization, we effectively map multidimensional parameter space to tune the size and polydispersity of CdSe nanocrystals, to maximize the photoluminescence efficiency of CdTe nanocrystals, and to control the crystal phase and maximize the upconverted luminescence of lanthanide-doped NaYF(4) nanocrystals. On the basis of these demonstrative examples, we conclude that this automated synthesis approach will be of great utility for the development of diverse colloidal nanomaterials for electronic assemblies, luminescent biological labels, electroluminescent devices, and other emerging applications.

A preliminary and qualitative study of resource ratio theory to nitrifying lab-scale bioreactors

PubMed Central

Bellucci, Micol; Ofiţeru, Irina D; Beneduce, Luciano; Graham, David W; Head, Ian M; Curtis, Thomas P

2015-01-01

The incorporation of microbial diversity in design would ideally require predictive theory that would relate operational parameters to the numbers and distribution of taxa. Resource ratio-theory (RRT) might be one such theory. Based on Monod kinetics, it explains diversity in function of resource-ratio and richness. However, to be usable in biological engineered system, the growth parameters of all the bacteria under consideration and the resource supply and diffusion parameters for all the relevant nutrients should be determined. This is challenging, but plausible, at least for low diversity groups with simple resource requirements like the ammonia oxidizing bacteria (AOB). One of the major successes of RRT was its ability to explain the ‘paradox of enrichment’ which states that diversity first increases and then decreases with resource richness. Here, we demonstrate that this pattern can be seen in lab-scale-activated sludge reactors and parallel simulations that incorporate the principles of RRT in a floc-based system. High and low ammonia and oxygen were supplied to continuous flow bioreactors with resource conditions correlating with the composition and diversity of resident AOB communities based on AOB 16S rDNA clone libraries. Neither the experimental work nor the simulations are definitive proof for the application of RRT in this context. However, it is sufficient evidence that such approach might work and justify a more rigorous investigation. PMID:25874592

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

PubMed

Tsai, Kuan-Yao; Wang, Feng-Sheng

2005-04-01

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

Assessing the effect of selection with deltamethrin on biological parameters and detoxifying enzymes in Aedes aegypti (L.).

PubMed

Alvarez-Gonzalez, Leslie C; Briceño, Arelis; Ponce-Garcia, Gustavo; Villanueva-Segura, O Karina; Davila-Barboza, Jesus A; Lopez-Monroy, Beatriz; Gutierrez-Rodriguez, Selene M; Contreras-Perera, Yamili; Rodriguez-Sanchez, Iram P; Flores, Adriana E

2017-11-01

Resistance to insecticides through one or several mechanisms has a cost for an insect in various parameters of its biological cycle. The present study evaluated the effect of deltamethrin on detoxifying enzymes and biological parameters in a population of Aedes aegypti selected for 15 generations. The enzyme activities of alpha- and beta-esterases, mixed-function oxidases and glutathione-S-transferases were determined during selection, along with biological parameters. Overexpression of mixed-function oxidases as a mechanism of metabolic resistance to deltamethrin was found. There were decreases in percentages of eggs hatching, pupation and age-specific survival and in total survival at the end of the selection (F 16 ). Although age-specific fecundity was not affected by selection with deltamethrin, total fertility, together with lower survival, significantly affected gross reproduction rate, gradually decreasing due to deltamethrin selection. Similarly, net reproductive rate and intrinsic growth rate were affected by selection. Alterations in life parameters could be due to the accumulation of noxious effects or deleterious genes related to detoxifying enzymes, specifically those coding for mixed-function oxidases, along with the presence of recessive alleles of the V1016I and F1534C mutations, associating deltamethrin resistance with fitness cost in Ae. aegypti. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Monochloramine Cometabolism by Nitrifying Biofilm Relevant ...

EPA Pesticide Factsheets

Recently, biological monochloramine removal (i.e., cometabolism) by a pure culture ammonia–oxidizing bacteria, Nitrosomonas europaea, and a nitrifying mixed–culture have been shown to increase monochloramine demand. Although important, these previous suspended culture batch kinetic experiments were not representative of drinking water distribution systems where bacteria grow predominantly as biofilm attached to pipe walls or sediments and physiological differences may exist between suspension and biofilm growth. Therefore, the current research was an important next step in extending the previous results to investigate monochloramine cometabolism by biofilm grown in annular reactors under drinking water relevant conditions. Estimated monochloramine cometabolism kinetics were similar to those of ammonia metabolism, and monochloramine cometabolism was a significant loss mechanism (25–40% of the observed monochloramine loss). These results demonstrated that monochloramine cometabolism occurred in drinking water relevant nitrifying biofilm; thus, cometabolism may be a significant contribution to monochloramine loss during nitrification episodes in distribution systems. Investigate whether or not nitrifying biofilm can biologically transform monochloramine under drinking water relevant conditions.

Transforming Big Data into cancer-relevant insight: An initial, multi-tier approach to assess reproducibility and relevance

PubMed Central

2016-01-01

The Cancer Target Discovery and Development (CTD2) Network was established to accelerate the transformation of “Big Data” into novel pharmacological targets, lead compounds, and biomarkers for rapid translation into improved patient outcomes. It rapidly became clear in this collaborative network that a key central issue was to define what constitutes sufficient computational or experimental evidence to support a biologically or clinically relevant finding. This manuscript represents a first attempt to delineate the challenges of supporting and confirming discoveries arising from the systematic analysis of large-scale data resources in a collaborative work environment and to provide a framework that would begin a community discussion to resolve these challenges. The Network implemented a multi-Tier framework designed to substantiate the biological and biomedical relevance as well as the reproducibility of data and insights resulting from its collaborative activities. The same approach can be used by the broad scientific community to drive development of novel therapeutic and biomarker strategies for cancer. PMID:27401613

SU-E-T-248: An Extended Generalized Equivalent Uniform Dose Accounting for Dose-Range Dependency of Radio-Biological Parameters.

PubMed

Troeller, A; Soehn, M; Yan, D

2012-06-01

Introducing an extended, phenomenological, generalized equivalent uniform dose (eEUD) that incorporates multiple volume-effect parameters for different dose-ranges. The generalized EUD (gEUD) was introduced as an estimate of the EUD that incorporates a single, tissue-specific parameter - the volume-effect-parameter (VEP) 'a'. As a purely phenomenological concept, its radio-biological equivalency to a given inhomogeneous dose distribution is not a priori clear and mechanistic models based on radio-biological parameters are assumed to better resemble the underlying biology. However, for normal organs mechanistic models are hard to derive, since the structural organization of the tissue plays a significant role. Consequently, phenomenological approaches might be especially useful in order to describe dose-response for normal tissues. However, the single parameter used to estimate the gEUD may not suffice in accurately representing more complex biological effects that have been discussed in the literature. For instance, radio-biological parameters and hence the effects of fractionation are known to be dose-range dependent. Therefore, we propose an extended phenomenological eEUD formula that incorporates multiple VEPs accounting for dose-range dependency. The eEUD introduced is a piecewise polynomial expansion of the gEUD formula. In general, it allows for an arbitrary number of VEPs, each valid for a certain dose-range. We proved that the formula fulfills required mathematical and physical criteria such as invertibility of the underlying dose-effect and continuity in dose. Furthermore, it contains the gEUD as a special case, if all VEPs are equal to 'a' from the gEUD model. The eEUD is a concept that expands the gEUD such that it can theoretically represent dose-range dependent effects. Its practicality, however, remains to be shown. As a next step, this will be done by estimating the eEUD from patient data using maximum-likelihood based NTCP modelling in the same way it is commonly done for the gEUD. © 2012 American Association of Physicists in Medicine.

Mode of action in relevance of rodent liver tumors to human cancer risk.

PubMed

Holsapple, Michael P; Pitot, Henri C; Cohen, Samuel M; Cohen, Samuel H; Boobis, Alan R; Klaunig, James E; Pastoor, Timothy; Dellarco, Vicki L; Dragan, Yvonne P

2006-01-01

Hazard identification and risk assessment paradigms depend on the presumption of the similarity of rodents to humans, yet species specific responses, and the extrapolation of high-dose effects to low-dose exposures can affect the estimation of human risk from rodent data. As a consequence, a human relevance framework concept was developed by the International Programme on Chemical Safety (IPCS) and International Life Sciences Institute (ILSI) Risk Science Institute (RSI) with the central tenet being the identification of a mode of action (MOA). To perform a MOA analysis, the key biochemical, cellular, and molecular events need to first be established, and the temporal and dose-dependent concordance of each of the key events in the MOA can then be determined. The key events can be used to bridge species and dose for a given MOA. The next step in the MOA analysis is the assessment of biological plausibility for determining the relevance of the specified MOA in an animal model for human cancer risk based on kinetic and dynamic parameters. Using the framework approach, a MOA in animals could not be defined for metal overload. The MOA for phenobarbital (PB)-like P450 inducers was determined to be unlikely in humans after kinetic and dynamic factors were considered. In contrast, after these factors were considered with reference to estrogen, the conclusion was drawn that estrogen-induced tumors were plausible in humans. Finally, it was concluded that the induction of rodent liver tumors by porphyrogenic compounds followed a cytotoxic MOA, and that liver tumors formed as a result of sustained cytotoxicity and regenerative proliferation are considered relevant for evaluating human cancer risk if appropriate metabolism occurs in the animal models and in humans.

Characterizing Isozymes of Chlorite Dismutase for Water Treatment

PubMed Central

Mobilia, Kellen C.; Hutchison, Justin M.; Zilles, Julie L.

2017-01-01

This work investigated the potential for biocatalytic degradation of micropollutants, focusing on chlorine oxyanions as model contaminants, by mining biology to identify promising biocatalysts. Existing isozymes of chlorite dismutase (Cld) were characterized with respect to parameters relevant to this high volume, low-value product application: kinetic parameters, resistance to catalytic inactivation, and stability. Maximum reaction velocities (Vmax) were typically on the order of 104 μmol min-1 (μmol heme)-1. Substrate affinity (Km) values were on the order of 100 μM, except for the Cld from Candidatus Nitrospira defluvii (NdCld), which showed a significantly lower affinity for chlorite. NdCld also had the highest susceptibility to catalytic inactivation. In contrast, the Cld from Ideonella dechloratans was least susceptible to catalytic inactivation, with a maximum turnover number of approximately 150,000, more than sevenfold higher than other tested isozymes. Under non-reactive conditions, Cld was quite stable, retaining over 50% of activity after 30 days, and most samples retained activity even after 90–100 days. Overall, Cld from I. dechloratans was the most promising candidate for environmental applications, having high affinity and activity, a relatively low propensity for catalytic inactivation, and excellent stability. PMID:29312158

Noisy coupled logistic maps in the vicinity of chaos threshold.

PubMed

Tirnakli, Ugur; Tsallis, Constantino

2016-04-01

We focus on a linear chain of N first-neighbor-coupled logistic maps in the vicinity of their edge of chaos in the presence of a common noise. This model, characterised by the coupling strength ϵ and the noise width σmax, was recently introduced by Pluchino et al. [Phys. Rev. E 87, 022910 (2013)]. They detected, for the time averaged returns with characteristic return time τ, possible connections with q-Gaussians, the distributions which optimise, under appropriate constraints, the nonadditive entropy, Sq, basis of nonextensive statistics mechanics. Here, we take a closer look on this model, and numerically obtain probability distributions which exhibit a slight asymmetry for some parameter values, in variance with simple q-Gaussians. Nevertheless, along many decades, the fitting with q-Gaussians turns out to be numerically very satisfactory for wide regions of the parameter values, and we illustrate how the index q evolves with (N,τ,ϵ,σmax). It is nevertheless instructive on how careful one must be in such numerical analysis. The overall work shows that physical and/or biological systems that are correctly mimicked by this model are thermostatistically related to nonextensive statistical mechanics when time-averaged relevant quantities are studied.

Body mass index is not associated with sperm-zona pellucida binding ability in subfertile males.

PubMed

Sermondade, Nathalie; Dupont, Charlotte; Faure, Céline; Boubaya, Marouane; Cédrin-Durnerin, Isabelle; Chavatte-Palmer, Pascale; Sifer, Christophe; Lévy, Rachel

2013-09-01

Lifestyle factors, such as weight and nutritional status may affect male fertility, including sperm fertilization ability. The objective of this retrospective study was to evaluate the association between body mass index (BMI) and sperm-zona pellucida binding ability assessed according to the zona binding (ZB) test, which has been described to be a relevant diagnostic tool for the prediction of in vitro fertilization (IVF) ability. Three hundred and six male patients from couples diagnosed with primary idiopathic or mild male factor infertility were included. Correlations between BMI and semen parameters according to ZB test indices were assessed, together with frequencies of positive and negative tests across the BMI categories. In this selected population, BMI was not related to conventional semen parameters or sperm quality assessed according to the ability of spermatozoa to bind to the zona pellucida. The previously described poor outcomes of IVF procedures in cases of male obesity could be due to other sperm defects, such as alterations of sperm capacitation or acrosome reaction. The link between male BMI and biological outcomes during IVF procedures, such as fertilization rates, should be further evaluated.

Tea and coffee time with bacteria - Investigation of uptake of key coffee and tea phenolics by wild type E. coli.

PubMed

Hakeem Said, Inamullah; Gencer, Selin; Ullrich, Matthias S; Kuhnert, Nikolai

2018-06-01

Dietary phenolic compounds are often transformed by gut microbiota prior to absorption. This transformation may modulate their biological activities. Many fundamental questions still need to be addressed to understand how the gut microbiota-diet interactions affect human health. Herein, a UHPLC-QTOF mass spectrometry-based method for the quantification of uptake and determination of intracellular bacterial concentrations of dietary phenolics from coffee and tea was developed. Quantitative uptake data for selected single purified phenolics were determined. The specific uptake from mixtures containing up to four dietary relevant compounds was investigated to assess changes of uptake parameters in a mixture model system. Indeed, perturbation of bacteria by several compounds alters uptake parameter in particular t max . Finally, model bacteria were dosed with complex dietary mixtures such as diluted tea or coffee extracts. The uptake kinetics of the twenty most abundant phenolics was quantified and the findings are discussed. For the first time, quantitative data on in-vitro uptake of dietary phenolics from food matrices were obtained indicating a time-dependent differential uptake of nutritional compounds. Copyright © 2018. Published by Elsevier Ltd.

Manufacturing of Wearable Sensors for Human Health and Performance Monitoring

NASA Astrophysics Data System (ADS)

Alizadeh, Azar

2015-03-01

Continuous monitoring of physiological and biological parameters is expected to improve performance and medical outcomes by assessing overall health status and alerting for life-saving interventions. Continuous monitoring of these parameters requires wearable devices with an appropriate form factor (lightweight, comfortable, low energy consuming and even single-use) to avoid disrupting daily activities thus ensuring operation relevance and user acceptance. Many previous efforts to implement remote and wearable sensors have suffered from high cost and poor performance, as well as low clinical and end-use acceptance. New manufacturing and system level design approaches are needed to make the performance and clinical benefits of these sensors possible while satisfying challenging economic, regulatory, clinical, and user-acceptance criteria. In this talk we will review several recent design and manufacturing efforts aimed at designing and building prototype wearable sensors. We will discuss unique opportunities and challenges provided by additive manufacturing, including 3D printing, to drive innovation through new designs, faster prototyping and manufacturing, distributed networks, and new ecosystems. We will also show alternative hybrid self-assembly based integration techniques for low cost large scale manufacturing of single use wearable devices. Coauthors: Prabhjot Singh and Jeffrey Ashe.

Noisy coupled logistic maps in the vicinity of chaos threshold

NASA Astrophysics Data System (ADS)

Tirnakli, Ugur; Tsallis, Constantino

2016-04-01

We focus on a linear chain of N first-neighbor-coupled logistic maps in the vicinity of their edge of chaos in the presence of a common noise. This model, characterised by the coupling strength ɛ and the noise width σmax, was recently introduced by Pluchino et al. [Phys. Rev. E 87, 022910 (2013)]. They detected, for the time averaged returns with characteristic return time τ, possible connections with q-Gaussians, the distributions which optimise, under appropriate constraints, the nonadditive entropy, Sq, basis of nonextensive statistics mechanics. Here, we take a closer look on this model, and numerically obtain probability distributions which exhibit a slight asymmetry for some parameter values, in variance with simple q-Gaussians. Nevertheless, along many decades, the fitting with q-Gaussians turns out to be numerically very satisfactory for wide regions of the parameter values, and we illustrate how the index q evolves with ( N , τ , ɛ , σ m a x ) . It is nevertheless instructive on how careful one must be in such numerical analysis. The overall work shows that physical and/or biological systems that are correctly mimicked by this model are thermostatistically related to nonextensive statistical mechanics when time-averaged relevant quantities are studied.

Discretization analysis of bifurcation based nonlinear amplifiers

NASA Astrophysics Data System (ADS)

Feldkord, Sven; Reit, Marco; Mathis, Wolfgang

2017-09-01

Recently, for modeling biological amplification processes, nonlinear amplifiers based on the supercritical Andronov-Hopf bifurcation have been widely analyzed analytically. For technical realizations, digital systems have become the most relevant systems in signal processing applications. The underlying continuous-time systems are transferred to the discrete-time domain using numerical integration methods. Within this contribution, effects on the qualitative behavior of the Andronov-Hopf bifurcation based systems concerning numerical integration methods are analyzed. It is shown exemplarily that explicit Runge-Kutta methods transform the truncated normalform equation of the Andronov-Hopf bifurcation into the normalform equation of the Neimark-Sacker bifurcation. Dependent on the order of the integration method, higher order terms are added during this transformation.A rescaled normalform equation of the Neimark-Sacker bifurcation is introduced that allows a parametric design of a discrete-time system which corresponds to the rescaled Andronov-Hopf system. This system approximates the characteristics of the rescaled Hopf-type amplifier for a large range of parameters. The natural frequency and the peak amplitude are preserved for every set of parameters. The Neimark-Sacker bifurcation based systems avoid large computational effort that would be caused by applying higher order integration methods to the continuous-time normalform equations.

Modeling of Soft Poroelastic Tissue in Time-Harmonic MR Elastography

PubMed Central

Perriñez, Phillip R.; Kennedy, Francis E.; Van Houten, Elijah E. W.; Weaver, John B.; Paulsen, Keith D.

2010-01-01

Elastography is an emerging imaging technique that focuses on assessing the resistance to deformation of soft biological tissues in vivo. Magnetic resonance elastography (MRE) uses measured displacement fields resulting from low-amplitude, low-frequency (10 Hz–1 kHz) time-harmonic vibration to recover images of the elastic property distribution of tissues including breast, liver, muscle, prostate, and brain. While many soft tissues display complex time-dependent behavior not described by linear elasticity, the models most commonly employed in MRE parameter reconstructions are based on elastic assumptions. Further, elasticity models fail to include the interstitial fluid phase present in vivo. Alternative continuum models, such as consolidation theory, are able to represent tissue and other materials comprising two distinct phases, generally consisting of a porous elastic solid and penetrating fluid. MRE reconstructions of simulated elastic and poroelastic phantoms were performed to investigate the limitations of current-elasticity-based methods in producing accurate elastic parameter estimates in poroelastic media. The results indicate that linearly elastic reconstructions of fluid-saturated porous media at amplitudes and frequencies relevant to steady-state MRE can yield misleading effective property distributions resulting from the complex interaction between their solid and fluid phases. PMID:19272864

Clinical relevance and biology of circulating tumor cells

PubMed Central

2011-01-01

Most breast cancer patients die due to metastases, and the early onset of this multistep process is usually missed by current tumor staging modalities. Therefore, ultrasensitive techniques have been developed to enable the enrichment, detection, isolation and characterization of disseminated tumor cells in bone marrow and circulating tumor cells in the peripheral blood of cancer patients. There is increasing evidence that the presence of these cells is associated with an unfavorable prognosis related to metastatic progression in the bone and other organs. This review focuses on investigations regarding the biology and clinical relevance of circulating tumor cells in breast cancer. PMID:22114869

Parameterized Algorithmics for Finding Exact Solutions of NP-Hard Biological Problems.

PubMed

Hüffner, Falk; Komusiewicz, Christian; Niedermeier, Rolf; Wernicke, Sebastian

2017-01-01

Fixed-parameter algorithms are designed to efficiently find optimal solutions to some computationally hard (NP-hard) problems by identifying and exploiting "small" problem-specific parameters. We survey practical techniques to develop such algorithms. Each technique is introduced and supported by case studies of applications to biological problems, with additional pointers to experimental results.

Ordinary differential equations with applications in molecular biology.

PubMed

Ilea, M; Turnea, M; Rotariu, M

2012-01-01

Differential equations are of basic importance in molecular biology mathematics because many biological laws and relations appear mathematically in the form of a differential equation. In this article we presented some applications of mathematical models represented by ordinary differential equations in molecular biology. The vast majority of quantitative models in cell and molecular biology are formulated in terms of ordinary differential equations for the time evolution of concentrations of molecular species. Assuming that the diffusion in the cell is high enough to make the spatial distribution of molecules homogenous, these equations describe systems with many participating molecules of each kind. We propose an original mathematical model with small parameter for biological phospholipid pathway. All the equations system includes small parameter epsilon. The smallness of epsilon is relative to the size of the solution domain. If we reduce the size of the solution region the same small epsilon will result in a different condition number. It is clear that the solution for a smaller region is less difficult. We introduce the mathematical technique known as boundary function method for singular perturbation system. In this system, the small parameter is an asymptotic variable, different from the independent variable. In general, the solutions of such equations exhibit multiscale phenomena. Singularly perturbed problems form a special class of problems containing a small parameter which may tend to zero. Many molecular biology processes can be quantitatively characterized by ordinary differential equations. Mathematical cell biology is a very active and fast growing interdisciplinary area in which mathematical concepts, techniques, and models are applied to a variety of problems in developmental medicine and bioengineering. Among the different modeling approaches, ordinary differential equations (ODE) are particularly important and have led to significant advances. Ordinary differential equations are used to model biological processes on various levels ranging from DNA molecules or biosynthesis phospholipids on the cellular level.

Characterizing gene sets using discriminative random walks with restart on heterogeneous biological networks.

PubMed

Blatti, Charles; Sinha, Saurabh

2016-07-15

Analysis of co-expressed gene sets typically involves testing for enrichment of different annotations or 'properties' such as biological processes, pathways, transcription factor binding sites, etc., one property at a time. This common approach ignores any known relationships among the properties or the genes themselves. It is believed that known biological relationships among genes and their many properties may be exploited to more accurately reveal commonalities of a gene set. Previous work has sought to achieve this by building biological networks that combine multiple types of gene-gene or gene-property relationships, and performing network analysis to identify other genes and properties most relevant to a given gene set. Most existing network-based approaches for recognizing genes or annotations relevant to a given gene set collapse information about different properties to simplify (homogenize) the networks. We present a network-based method for ranking genes or properties related to a given gene set. Such related genes or properties are identified from among the nodes of a large, heterogeneous network of biological information. Our method involves a random walk with restarts, performed on an initial network with multiple node and edge types that preserve more of the original, specific property information than current methods that operate on homogeneous networks. In this first stage of our algorithm, we find the properties that are the most relevant to the given gene set and extract a subnetwork of the original network, comprising only these relevant properties. We then re-rank genes by their similarity to the given gene set, based on a second random walk with restarts, performed on the above subnetwork. We demonstrate the effectiveness of this algorithm for ranking genes related to Drosophila embryonic development and aggressive responses in the brains of social animals. DRaWR was implemented as an R package available at veda.cs.illinois.edu/DRaWR. blatti@illinois.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Balancing Scientific Publication and National Security Concerns: Issues for Congress

DTIC Science & Technology

2003-01-10

because of its potential relevance to biological weapons of mass destruction. Whether the current method of only using classification to limit the...terrorist groups in developing weapons of mass destruction. In 2000, researchers at the Co-operative Research Centre for the Biological Control of Pest...development of chemical, biological , or nuclear weapons is not made accessible to terrorists or countries of proliferation concern. The resolution

"Evo in the News": A Pedagogical Tool to Enhance Students' Perceptions of the Relevance of Evolutionary Biology

ERIC Educational Resources Information Center

Infanti, Lynn M.

2012-01-01

This investigation evaluated the effects of the use of the pedagogical tool "Evo in the News" on the attitudes toward and knowledge of biological evolution in a sample of undergraduate non-major biology students at a large, private research university. In addition, this study looked at the initial attitudes of the students and their…

Biological Aspects of Anorexia Nervosa and Bulimia Nervosa.

ERIC Educational Resources Information Center

Kaplan, Allan S.; Woodside, D. Blake

1987-01-01

Reviews biological factors relevant to the understanding of anorexia nervosa and bulimia nervosa. Considers the physical presentation of these disorders; the medical complications of starvation, binging, and purging; and the cognitive and behavioral effects of starvation. Reviews neurophysiological and neurochemical aspects of these illnesses and…

Epigenetic profiling of growth plate chondrocytes sheds insight into regulatory genetic variation influencing height.

PubMed

Guo, Michael; Liu, Zun; Willen, Jessie; Shaw, Cameron P; Richard, Daniel; Jagoda, Evelyn; Doxey, Andrew C; Hirschhorn, Joel; Capellini, Terence D

2017-12-05

GWAS have identified hundreds of height-associated loci. However, determining causal mechanisms is challenging, especially since height-relevant tissues (e.g. growth plates) are difficult to study. To uncover mechanisms by which height GWAS variants function, we performed epigenetic profiling of murine femoral growth plates. The profiled open chromatin regions recapitulate known chondrocyte and skeletal biology, are enriched at height GWAS loci, particularly near differentially expressed growth plate genes, and enriched for binding motifs of transcription factors with roles in chondrocyte biology. At specific loci, our analyses identified compelling mechanisms for GWAS variants. For example, at CHSY1 , we identified a candidate causal variant (rs9920291) overlapping an open chromatin region. Reporter assays demonstrated that rs9920291 shows allelic regulatory activity, and CRISPR/Cas9 targeting of human chondrocytes demonstrates that the region regulates CHSY1 expression. Thus, integrating biologically relevant epigenetic information (here, from growth plates) with genetic association results can identify biological mechanisms important for human growth.

Biological aspects of chondrosarcoma: Leaps and hurdles.

PubMed

Mery, Benoîte; Espenel, Sophie; Guy, Jean-Baptiste; Rancoule, Chloé; Vallard, Alexis; Aloy, Marie-Thérèse; Rodriguez-Lafrasse, Claire; Magné, Nicolas

2018-06-01

Chondrosarcomas are characterized by their chemo- and radioresistance leading to a therapeutic surgical approach which remains the only available treatment with a 10-year survival between 30% and 80% depending on the grade. Non-surgical treatments are under investigation and rely on an accurate biological understanding of drug resistance mechanisms. Novel targeted therapy which represents a new relevant therapeutic approach will open new treatment options by targeting several pathways responsible for processes of proliferation and invasion. Survival pathways such as PI3K, AKT, mTOR and VEGF have been shown to be involved in proliferation of chondrosarcoma cells and antiapoptotic proteins may also play a relevant role. Other proteins such as p53 or COX2 have been identified as potential new targets. This review provides an insight into the biological substantial treatment challenges of CHS and focuses on improving our understanding of CH biology through an overview of major signaling pathways that could represent targets for new therapeutic approaches. Copyright © 2018 Elsevier B.V. All rights reserved.

Simulating the bio nanoelectronic interface

NASA Astrophysics Data System (ADS)

Millar, Campbell; Roy, Scott; Brown, Andrew R.; Asenov, Asen

2007-05-01

As the size of conventional nano-CMOS devices continues to shrink, they are beginning to approach the size of biologically relevant macromolecules such as ion channels. This, in concert with the increasing understanding of the behaviour of proteins in vivo, creates the potential for a revolution in the sensing, measurement and interaction with biological systems. In this paper we will demonstrate the theoretical possibility of directly coupling a nanoscale MOSFET with a model ion channel protein. This will potentially allow a much better understanding of the behaviour of biologically relevant molecules, since the measurement of the motion of charged particles can reveal a substantial amount of information about protein structure-function relationships. We can use the MOSFET's innate sensitivity to stray charge to detect the positions of single ions and, thus, better explore the dynamics of ion conduction in channel proteins. In addition, we also demonstrate that the MOSFET can be 'tuned' to sense current flow through channel proteins, thus providing, for the first time, a direct solid state/biological interface at the atomic level.

PDB-wide identification of biological assemblies from conserved quaternary structure geometry.

PubMed

Dey, Sucharita; Ritchie, David W; Levy, Emmanuel D

2018-01-01

Protein structures are key to understanding biomolecular mechanisms and diseases, yet their interpretation is hampered by limited knowledge of their biologically relevant quaternary structure (QS). A critical challenge in inferring QS information from crystallographic data is distinguishing biological interfaces from fortuitous crystal-packing contacts. Here, we tackled this problem by developing strategies for aligning and comparing QS states across both homologs and data repositories. QS conservation across homologs proved remarkably strong at predicting biological relevance and is implemented in two methods, QSalign and anti-QSalign, for annotating homo-oligomers and monomers, respectively. QS conservation across repositories is implemented in QSbio (http://www.QSbio.org), which approaches the accuracy of manual curation and allowed us to predict >100,000 QS states across the Protein Data Bank. Based on this high-quality data set, we analyzed pairs of structurally conserved interfaces, and this analysis revealed a striking plasticity whereby evolutionary distant interfaces maintain similar interaction geometries through widely divergent chemical properties.

On determining firing delay time of transitions for Petri net based signaling pathways by introducing stochastic decision rules.

PubMed

Miwa, Yoshimasa; Li, Chen; Ge, Qi-Wei; Matsuno, Hiroshi; Miyano, Satoru

2010-01-01

Parameter determination is important in modeling and simulating biological pathways including signaling pathways. Parameters are determined according to biological facts obtained from biological experiments and scientific publications. However, such reliable data describing detailed reactions are not reported in most cases. This prompted us to develop a general methodology of determining the parameters of a model in the case of that no information of the underlying biological facts is provided. In this study, we use the Petri net approach for modeling signaling pathways, and propose a method to determine firing delay times of transitions for Petri net models of signaling pathways by introducing stochastic decision rules. Petri net technology provides a powerful approach to modeling and simulating various concurrent systems, and recently have been widely accepted as a description method for biological pathways. Our method enables to determine the range of firing delay time which realizes smooth token flows in the Petri net model of a signaling pathway. The availability of this method has been confirmed by the results of an application to the interleukin-1 induced signaling pathway.

On determining firing delay time of transitions for petri net based signaling pathways by introducing stochastic decision rules.

PubMed

Miwa, Yoshimasa; Li, Chen; Ge, Qi-Wei; Matsuno, Hiroshi; Miyano, Satoru

2011-01-01

Parameter determination is important in modeling and simulating biological pathways including signaling pathways. Parameters are determined according to biological facts obtained from biological experiments and scientific publications. However, such reliable data describing detailed reactions are not reported in most cases. This prompted us to develop a general methodology of determining the parameters of a model in the case of that no information of the underlying biological facts is provided. In this study, we use the Petri net approach for modeling signaling pathways, and propose a method to determine firing delay times of transitions for Petri net models of signaling pathways by introducing stochastic decision rules. Petri net technology provides a powerful approach to modeling and simulating various concurrent systems, and recently have been widely accepted as a description method for biological pathways. Our method enables to determine the range of firing delay time which realizes smooth token flows in the Petri net model of a signaling pathway. The availability of this method has been confirmed by the results of an application to the interleukin-1 induced signaling pathway.

Variation in skin biology to climate in Shanghai, China.

PubMed

Liu, Xiaoping; Gao, Yanrui; Zhang, Yiyi; Wang, Xuemin

2017-09-01

To explore the relationship between climate and skin condition, and to investigate the variation of skin biology to climatic change. In total, 2005 healthy Chinese volunteers living in Shanghai (aged 13-69 years) were recruited. Transepidermal water loss (TEWL) and SCH were tested on six sites (forehead, cheek, nasolabial, inner forearm, dorsal hand, and palm) by noninvasive devices between January 2005 and December 2012. The corresponding climate data were recorded by local Weather Bureau. TEWL was increased with atmospheric pressure and decreased with temperature, steam pressure, and relative humidity (p < 0.05). SCH was increased with steam pressure and decreased with atmospheric pressure (p < 0.05); there was no obvious trend between SCH and temperature and SCH and relative humidity. To investigate the climate parameters together, we introduced these correlated factors into the multivariate linear regression model which demonstrated that temperature and steam pressure were main factors related to skin biological parameters. At different sites, the effect of climatic factors on skin biology was diverse. Skin biological parameters are associated with climatic factors. Different sites have different sensitivity to climate factors.

Reaction dynamics analysis of a reconstituted Escherichia coli protein translation system by computational modeling

PubMed Central

Matsuura, Tomoaki; Tanimura, Naoki; Hosoda, Kazufumi; Yomo, Tetsuya; Shimizu, Yoshihiro

2017-01-01

To elucidate the dynamic features of a biologically relevant large-scale reaction network, we constructed a computational model of minimal protein synthesis consisting of 241 components and 968 reactions that synthesize the Met-Gly-Gly (MGG) peptide based on an Escherichia coli-based reconstituted in vitro protein synthesis system. We performed a simulation using parameters collected primarily from the literature and found that the rate of MGG peptide synthesis becomes nearly constant in minutes, thus achieving a steady state similar to experimental observations. In addition, concentration changes to 70% of the components, including intermediates, reached a plateau in a few minutes. However, the concentration change of each component exhibits several temporal plateaus, or a quasi-stationary state (QSS), before reaching the final plateau. To understand these complex dynamics, we focused on whether the components reached a QSS, mapped the arrangement of components in a QSS in the entire reaction network structure, and investigated time-dependent changes. We found that components in a QSS form clusters that grow over time but not in a linear fashion, and that this process involves the collapse and regrowth of clusters before the formation of a final large single cluster. These observations might commonly occur in other large-scale biological reaction networks. This developed analysis might be useful for understanding large-scale biological reactions by visualizing complex dynamics, thereby extracting the characteristics of the reaction network, including phase transitions. PMID:28167777

The association of posttraumatic stress disorder and metabolic syndrome: a study of increased health risk in veterans

PubMed Central

Heppner, Pia S; Crawford, Eric F; Haji, Uzair A; Afari, Niloofar; Hauger, Richard L; Dashevsky, Boris A; Horn, Paul S; Nunnink, Sarah E; Baker, Dewleen G

2009-01-01

Background There is accumulating evidence for a link between trauma exposure, posttraumatic stress disorder (PTSD) and diminished health status. To assess PTSD-related biological burden, we measured biological factors that comprise metabolic syndrome, an important established predictor of morbidity and mortality, as a correlate of long-term health risk in PTSD. Methods We analyzed clinical data from 253 male and female veterans, corresponding to five factors linked to metabolic syndrome (systolic and diastolic blood pressure, waist-to-hip ratio and fasting measures of high-density lipoprotein (HDL) cholesterol, serum triglycerides and plasma glucose concentration). Clinical cut-offs were defined for each biological parameter based on recommendations from the World Health Organization and the National Cholesterol Education Program. Controlling for relevant variables including sociodemographic variables, alcohol/substance/nicotine use and depression, we examined the impact of PTSD on metabolic syndrome using a logistic regression model. Results Two-fifths (40%) of the sample met criteria for metabolic syndrome. Of those with PTSD (n = 139), 43% met criteria for metabolic syndrome. The model predicted metabolic syndrome well (-2 log likelihood = 316.650, chi-squared = 23.731, p = 0.005). Veterans with higher severity of PTSD were more likely to meet diagnostic criteria for metabolic syndrome (Wald = 4.76, p = 0.03). Conclusion These findings provide preliminary evidence linking higher severity of PTSD with risk factors for diminished health and increased morbidity, as represented by metabolic syndrome. PMID:19134183

What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology

PubMed Central

McDonnell, Mark D.; Abbott, Derek

2009-01-01

Stochastic resonance is said to be observed when increases in levels of unpredictable fluctuations—e.g., random noise—cause an increase in a metric of the quality of signal transmission or detection performance, rather than a decrease. This counterintuitive effect relies on system nonlinearities and on some parameter ranges being “suboptimal”. Stochastic resonance has been observed, quantified, and described in a plethora of physical and biological systems, including neurons. Being a topic of widespread multidisciplinary interest, the definition of stochastic resonance has evolved significantly over the last decade or so, leading to a number of debates, misunderstandings, and controversies. Perhaps the most important debate is whether the brain has evolved to utilize random noise in vivo, as part of the “neural code”. Surprisingly, this debate has been for the most part ignored by neuroscientists, despite much indirect evidence of a positive role for noise in the brain. We explore some of the reasons for this and argue why it would be more surprising if the brain did not exploit randomness provided by noise—via stochastic resonance or otherwise—than if it did. We also challenge neuroscientists and biologists, both computational and experimental, to embrace a very broad definition of stochastic resonance in terms of signal-processing “noise benefits”, and to devise experiments aimed at verifying that random variability can play a functional role in the brain, nervous system, or other areas of biology. PMID:19562010

Comparing functional responses in predator-infected eco-epidemics models.

PubMed

Haque, Mainul; Rahman, Md Sabiar; Venturino, Ezio

2013-11-01

The current paper deals with the mathematical models of predator-prey system where a transmissible disease spreads among the predator species only. Four mathematical models are proposed and analysed with several popular predator functional responses in order to show the influence of functional response on eco-epidemic models. The existence, boundedness, uniqueness of solutions of all the models are established. Mathematical analysis including stability and bifurcation are observed. Comparison among the results of these models allows the general conclusion that relevant behaviour of the eco-epidemic predator-prey system, including switching of stability, extinction, persistence and oscillations for any species depends on four important parameters viz. the rate of infection, predator interspecies competition and the attack rate on susceptible predator. The paper ends with a discussion of the biological implications of the analytical and numerical results. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Genotoxicity of topoisomerase II inhibitors: an anti-infective perspective.

PubMed

Smart, Daniel J

2008-12-30

At present, an inevitable consequence of a chemical's inhibitory activity on key regulators of DNA topology in bacteria, the type II topoisomerases, is a less pronounced effect on their eukaryotic counterparts. In the context of anti-infectives drug development, this may pose a risk to patient safety as inhibition of eukaryotic type II topoisomerases (TOPO II) can result in the generation of DNA double-strand breaks (DSBs), which have the potential to manifest as mutations, chromosome breakage or cell death. The biological effects of several TOPO II inhibitors in mammalian cells are described herein; their modulation of DSB damage response parameters is examined and evidence for the existence of a threshold concept for genotoxicity and its relevance in safety assessment is discussed. The potential utility of gammaH2AX, a promising and highly sensitive molecular marker for DSBs, in a novel genotoxicity 'pre-screen' to conventional assays is also highlighted.

Generalized Scaling and the Master Variable for Brownian Magnetic Nanoparticle Dynamics

PubMed Central

Reeves, Daniel B.; Shi, Yipeng; Weaver, John B.

2016-01-01

Understanding the dynamics of magnetic particles can help to advance several biomedical nanotechnologies. Previously, scaling relationships have been used in magnetic spectroscopy of nanoparticle Brownian motion (MSB) to measure biologically relevant properties (e.g., temperature, viscosity, bound state) surrounding nanoparticles in vivo. Those scaling relationships can be generalized with the introduction of a master variable found from non-dimensionalizing the dynamical Langevin equation. The variable encapsulates the dynamical variables of the surroundings and additionally includes the particles’ size distribution and moment and the applied field’s amplitude and frequency. From an applied perspective, the master variable allows tuning to an optimal MSB biosensing sensitivity range by manipulating both frequency and field amplitude. Calculation of magnetization harmonics in an oscillating applied field is also possible with an approximate closed-form solution in terms of the master variable and a single free parameter. PMID:26959493

Value of Telemonitoring and Telemedicine in Heart Failure Management

PubMed Central

Alderighi, Camilla; Rasoini, Raffaele; Mazzanti, Marco; Casolo, Giancarlo

2017-01-01

The use of telemonitoring and telemedicine is a relatively new but quickly developing area in medicine. As new digital tools and applications are being created and used to manage medical conditions such as heart failure, many implications require close consideration and further study, including the effectiveness and safety of these telemonitoring tools in diagnosing, treating and managing heart failure compared to traditional face-to-face doctor–patient interaction. When compared to multidisciplinary intervention programs which are frequently hindered by economic, geographic and bureaucratic barriers, non-invasive remote monitoring could be a solution to support and promote the care of patients over time. Therefore it is crucial to identify the most relevant biological parameters to monitor, which heart failure sub-populations may gain real benefits from telehealth interventions and in which specific healthcare subsets these interventions should be implemented in order to maximise value. PMID:29387464

Robust stochastic Turing patterns in the development of a one-dimensional cyanobacterial organism.

PubMed

Di Patti, Francesca; Lavacchi, Laura; Arbel-Goren, Rinat; Schein-Lubomirsky, Leora; Fanelli, Duccio; Stavans, Joel

2018-05-01

Under nitrogen deprivation, the one-dimensional cyanobacterial organism Anabaena sp. PCC 7120 develops patterns of single, nitrogen-fixing cells separated by nearly regular intervals of photosynthetic vegetative cells. We study a minimal, stochastic model of developmental patterns in Anabaena that includes a nondiffusing activator, two diffusing inhibitor morphogens, demographic fluctuations in the number of morphogen molecules, and filament growth. By tracking developing filaments, we provide experimental evidence for different spatiotemporal roles of the two inhibitors during pattern maintenance and for small molecular copy numbers, justifying a stochastic approach. In the deterministic limit, the model yields Turing patterns within a region of parameter space that shrinks markedly as the inhibitor diffusivities become equal. Transient, noise-driven, stochastic Turing patterns are produced outside this region, which can then be fixed by downstream genetic commitment pathways, dramatically enhancing the robustness of pattern formation, also in the biologically relevant situation in which the inhibitors' diffusivities may be comparable.

Metastable Prepores in Tension-Free Lipid Bilayers

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

Ting, Christina L.; Awasthi, Neha; Muller, Marcus

The formation and closure of aqueous pores in lipid bilayers is a key step in various biophysical processes. Large pores are well described by classical nucleation theory, but the free-energy landscape of small, biologically relevant pores has remained largely unexplored. The existence of small and metastable “prepores” was hypothesized decades ago from electroporation experiments, but resolving metastable prepores from theoretical models remained challenging. Using two complementary methods—atomistic simulations and self-consistent field theory of a minimal lipid model—we determine the parameters for which metastable prepores occur in lipid membranes. Here, both methods consistently suggest that pore metastability depends on the relativemore » volume ratio between the lipid head group and lipid tails: lipids with a larger head-group volume fraction (or shorter saturated tails) form metastable prepores, whereas lipids with a smaller head-group volume fraction (or longer unsaturated tails) form unstable prepores.« less

Value of Telemonitoring and Telemedicine in Heart Failure Management.

PubMed

Gensini, Gian Franco; Alderighi, Camilla; Rasoini, Raffaele; Mazzanti, Marco; Casolo, Giancarlo

2017-11-01

The use of telemonitoring and telemedicine is a relatively new but quickly developing area in medicine. As new digital tools and applications are being created and used to manage medical conditions such as heart failure, many implications require close consideration and further study, including the effectiveness and safety of these telemonitoring tools in diagnosing, treating and managing heart failure compared to traditional face-to-face doctor-patient interaction. When compared to multidisciplinary intervention programs which are frequently hindered by economic, geographic and bureaucratic barriers, non-invasive remote monitoring could be a solution to support and promote the care of patients over time. Therefore it is crucial to identify the most relevant biological parameters to monitor, which heart failure sub-populations may gain real benefits from telehealth interventions and in which specific healthcare subsets these interventions should be implemented in order to maximise value.