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.

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

A Theoretical Approach to Analyze the Parametric Influence on Spatial Patterns of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) Populations.

PubMed

Garcia, A G; Godoy, W A C

2017-06-01

Studies of the influence of biological parameters on the spatial distribution of lepidopteran insects can provide useful information for managing agricultural pests, since the larvae of many species cause serious impacts on crops. Computational models to simulate the spatial dynamics of insect populations are increasingly used, because of their efficiency in representing insect movement. In this study, we used a cellular automata model to explore different patterns of population distribution of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), when the values of two biological parameters that are able to influence the spatial pattern (larval viability and adult longevity) are varied. We mapped the spatial patterns observed as the parameters varied. Additionally, by using population data for S. frugiperda obtained in different hosts under laboratory conditions, we were able to describe the expected spatial patterns occurring in corn, cotton, millet, and soybean crops based on the parameters varied. The results are discussed from the perspective of insect ecology and pest management. We concluded that computational approaches can be important tools to study the relationship between the biological parameters and spatial distributions of lepidopteran insect pests.

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.

A hybrid model of cell cycle in mammals.

PubMed

Behaegel, Jonathan; Comet, Jean-Paul; Bernot, Gilles; Cornillon, Emilien; Delaunay, Franck

2016-02-01

Time plays an essential role in many biological systems, especially in cell cycle. Many models of biological systems rely on differential equations, but parameter identification is an obstacle to use differential frameworks. In this paper, we present a new hybrid modeling framework that extends René Thomas' discrete modeling. The core idea is to associate with each qualitative state "celerities" allowing us to compute the time spent in each state. This hybrid framework is illustrated by building a 5-variable model of the mammalian cell cycle. Its parameters are determined by applying formal methods on the underlying discrete model and by constraining parameters using timing observations on the cell cycle. This first hybrid model presents the most important known behaviors of the cell cycle, including quiescent phase and endoreplication.

Bayesian Parameter Inference and Model Selection by Population Annealing in Systems Biology

PubMed Central

Murakami, Yohei

2014-01-01

Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection. Especially, the framework named approximate Bayesian computation is often used for parameter inference and model selection in systems biology. However, Monte Carlo methods needs to be used to compute Bayesian posterior distributions. In addition, the posterior distributions of parameters are sometimes almost uniform or very similar to their prior distributions. In such cases, it is difficult to choose one specific value of parameter with high credibility as the representative value of the distribution. To overcome the problems, we introduced one of the population Monte Carlo algorithms, population annealing. Although population annealing is usually used in statistical mechanics, we showed that population annealing can be used to compute Bayesian posterior distributions in the approximate Bayesian computation framework. To deal with un-identifiability of the representative values of parameters, we proposed to run the simulations with the parameter ensemble sampled from the posterior distribution, named “posterior parameter ensemble”. We showed that population annealing is an efficient and convenient algorithm to generate posterior parameter ensemble. We also showed that the simulations with the posterior parameter ensemble can, not only reproduce the data used for parameter inference, but also capture and predict the data which was not used for parameter inference. Lastly, we introduced the marginal likelihood in the approximate Bayesian computation framework for Bayesian model selection. We showed that population annealing enables us to compute the marginal likelihood in the approximate Bayesian computation framework and conduct model selection depending on the Bayes factor. PMID:25089832

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental disturbances, is also proposed, together with a simulation example. PMID:23515190

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology.

PubMed

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental disturbances, is also proposed, together with a simulation example.

The effects of morphological irregularity on the mechanical behavior of interdigitated biological sutures under tension.

PubMed

Liu, Lei; Jiang, Yunyao; Boyce, Mary; Ortiz, Christine; Baur, Jeffery; Song, Juha; Li, Yaning

2017-06-14

Irregular interdigitated morphology is prevalent in biological sutures in nature. Suture complexity index has long been recognized as the most important morphological parameter to govern the mechanical properties of biological sutures. However, the suture complexity index alone does not reflect all aspects of suture morphology. The goal of this investigation was to determine that besides suture complexity index, whether the degree of morphological irregularity of biological sutures has influences on the mechanical properties, and if there is any, how to quantify these influences. To explore these issues, theoretical and finite element (FE) suture models with the same suture complexity index but different levels of morphological irregularity were developed. The quasi-static stiffness, strength for damage initiation and post-failure process of irregular sutures were studied. It was shown that for the same suture complexity index, when the level of morphological irregularity increases, the overall strain to failure will increase while tensile stiffness is retained; also, the total energy to fracture increases with a sacrifice in strength to damage initiation. These results reveal that morphological irregularity is another important independent parameter to govern and balance the mechanical properties of biological sutures. Therefore, from the mechanics point of view, the prevalence of irregular suture morphology in nature is a merit, not a defect. Copyright © 2017 Elsevier Ltd. All rights reserved.

Biological and analytical variations of 16 parameters related to coagulation screening tests and the activity of coagulation factors.

PubMed

Chen, Qian; Shou, Weiling; Wu, Wei; Guo, Ye; Zhang, Yujuan; Huang, Chunmei; Cui, Wei

2015-04-01

To accurately estimate longitudinal changes in individuals, it is important to take into consideration the biological variability of the measurement. The few studies available on the biological variations of coagulation parameters are mostly outdated. We confirmed the published results using modern, fully automated methods. Furthermore, we added data for additional coagulation parameters. At 8:00 am, 12:00 pm, and 4:00 pm on days 1, 3, and 5, venous blood was collected from 31 healthy volunteers. A total of 16 parameters related to coagulation screening tests as well as the activity of coagulation factors were analyzed; these included prothrombin time, fibrinogen (Fbg), activated partial thromboplastin time, thrombin time, international normalized ratio, prothrombin time activity, activated partial thromboplastin time ratio, fibrin(-ogen) degradation products, as well as the activity of factor II, factor V, factor VII, factor VIII, factor IX, and factor X. All intraindividual coefficients of variation (CVI) values for the parameters of the screening tests (except Fbg) were less than 5%. Conversely, the CVI values for the activity of coagulation factors were all greater than 5%. In addition, we calculated the reference change value to determine whether a significant difference exists between two test results from the same individual. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Engineering Parameters in Bioreactor's Design: A Critical Aspect in Tissue Engineering

PubMed Central

Amoabediny, Ghassem; Pouran, Behdad; Tabesh, Hadi; Shokrgozar, Mohammad Ali; Haghighipour, Nooshin; Khatibi, Nahid; Mottaghy, Khosrow; Zandieh-Doulabi, Behrouz

2013-01-01

Bioreactors are important inevitable part of any tissue engineering (TE) strategy as they aid the construction of three-dimensional functional tissues. Since the ultimate aim of a bioreactor is to create a biological product, the engineering parameters, for example, internal and external mass transfer, fluid velocity, shear stress, electrical current distribution, and so forth, are worth to be thoroughly investigated. The effects of such engineering parameters on biological cultures have been addressed in only a few preceding studies. Furthermore, it would be highly inefficient to determine the optimal engineering parameters by trial and error method. A solution is provided by emerging modeling and computational tools and by analyzing oxygen, carbon dioxide, and nutrient and metabolism waste material transports, which can simulate and predict the experimental results. Discovering the optimal engineering parameters is crucial not only to reduce the cost and time of experiments, but also to enhance efficacy and functionality of the tissue construct. This review intends to provide an inclusive package of the engineering parameters together with their calculation procedure in addition to the modeling techniques in TE bioreactors. PMID:24000327

Engineering parameters in bioreactor's design: a critical aspect in tissue engineering.

PubMed

Salehi-Nik, Nasim; Amoabediny, Ghassem; Pouran, Behdad; Tabesh, Hadi; Shokrgozar, Mohammad Ali; Haghighipour, Nooshin; Khatibi, Nahid; Anisi, Fatemeh; Mottaghy, Khosrow; Zandieh-Doulabi, Behrouz

2013-01-01

Bioreactors are important inevitable part of any tissue engineering (TE) strategy as they aid the construction of three-dimensional functional tissues. Since the ultimate aim of a bioreactor is to create a biological product, the engineering parameters, for example, internal and external mass transfer, fluid velocity, shear stress, electrical current distribution, and so forth, are worth to be thoroughly investigated. The effects of such engineering parameters on biological cultures have been addressed in only a few preceding studies. Furthermore, it would be highly inefficient to determine the optimal engineering parameters by trial and error method. A solution is provided by emerging modeling and computational tools and by analyzing oxygen, carbon dioxide, and nutrient and metabolism waste material transports, which can simulate and predict the experimental results. Discovering the optimal engineering parameters is crucial not only to reduce the cost and time of experiments, but also to enhance efficacy and functionality of the tissue construct. This review intends to provide an inclusive package of the engineering parameters together with their calculation procedure in addition to the modeling techniques in TE bioreactors.

A theoretical framework for biological control of soil-borne plant pathogens: Identifying effective strategies.

PubMed

Cunniffe, Nik J; Gilligan, Christopher A

2011-06-07

We develop and analyse a flexible compartmental model of the interaction between a plant host, a soil-borne pathogen and a microbial antagonist, for use in optimising biological control. By extracting invasion and persistence thresholds of host, pathogen and biological control agent, performing an equilibrium analysis, and numerical investigation of sensitivity to parameters and initial conditions, we determine criteria for successful biological control. We identify conditions for biological control (i) to prevent a pathogen entering a system, (ii) to eradicate a pathogen that is already present and, if that is not possible, (iii) to reduce the density of the pathogen. Control depends upon the epidemiology of the pathogen and how efficiently the antagonist can colonise particular habitats (i.e. healthy tissue, infected tissue and/or soil-borne inoculum). A sharp transition between totally effective control (i.e. eradication of the pathogen) and totally ineffective control can follow slight changes in biologically interpretable parameters or to the initial amounts of pathogen and biological control agent present. Effective biological control requires careful matching of antagonists to pathosystems. For preventative/eradicative control, antagonists must colonise susceptible hosts. However, for reduction in disease prevalence, the range of habitat is less important than the antagonist's bulking-up efficiency. Copyright © 2011 Elsevier Ltd. All rights reserved.

Comparative bionomics of four populations of Meccus longipennis (Hemiptera: Reduviidae: Triatominae) under laboratory conditions.

PubMed

Martínez-Ibarra, José Alejandro; Nogueda-Torres, Benjamín; Licón-Trillo, Ángel; Villagrán-Herrera, María Elena; de Diego-Cabrera, José Antonio; Montañez-Valdez, Oziel Dante; Rocha-Chávez, Gonzalo

2013-04-01

The values of biological parameters related to the life cycles of four populations of Meccus longipennis (Reduviidae: Triatominae) were evaluated. Cohorts of each of the four studied populations from different geographical areas of Mexico were maintained under similar laboratory conditions and then compared. The population from El Saucito de Araujo was different from the other three studied populations, which could help explain the secondary importance of M. longipennis in the state of Chihuahua. This paper also supports the proposition that biological traits are important criteria for determining relationships between populations.

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.

Probabilistic parameter estimation of activated sludge processes using Markov Chain Monte Carlo.

PubMed

Sharifi, Soroosh; Murthy, Sudhir; Takács, Imre; Massoudieh, Arash

2014-03-01

One of the most important challenges in making activated sludge models (ASMs) applicable to design problems is identifying the values of its many stoichiometric and kinetic parameters. When wastewater characteristics data from full-scale biological treatment systems are used for parameter estimation, several sources of uncertainty, including uncertainty in measured data, external forcing (e.g. influent characteristics), and model structural errors influence the value of the estimated parameters. This paper presents a Bayesian hierarchical modeling framework for the probabilistic estimation of activated sludge process parameters. The method provides the joint probability density functions (JPDFs) of stoichiometric and kinetic parameters by updating prior information regarding the parameters obtained from expert knowledge and literature. The method also provides the posterior correlations between the parameters, as well as a measure of sensitivity of the different constituents with respect to the parameters. This information can be used to design experiments to provide higher information content regarding certain parameters. The method is illustrated using the ASM1 model to describe synthetically generated data from a hypothetical biological treatment system. The results indicate that data from full-scale systems can narrow down the ranges of some parameters substantially whereas the amount of information they provide regarding other parameters is small, due to either large correlations between some of the parameters or a lack of sensitivity with respect to the parameters. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

Farashi, Sajjad

2017-01-01

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

[Biological markers of alcoholism].

PubMed

Marcos Martín, M; Pastor Encinas, I; Laso Guzmán, F J

2005-09-01

Diagnosis of alcoholism is very important, given its high prevalence and possibility of influencing the disease course. For this reason, the so-called biological markers of alcoholism are useful. These are analytic parameters that alter in the presence of excessive alcohol consumption. The two most relevant markers are the gamma-glutamyltranspeptidase and carbohydrate deficient transferrin. With this clinical comment, we aim to contribute to the knowledge of these tests and promote its use in the clinical practice.

Biomedical implications of information processing in chemical systems: non-classical approach to photochemistry of coordination compounds.

PubMed

Szaciłowski, Konrad

2007-01-01

Analogies between photoactive nitric oxide generators and various electronic devices: logic gates and operational amplifiers are presented. These analogies have important biological consequences: application of control parameters allows for better targeting and control of nitric oxide drugs. The same methodology may be applied in the future for other therapeutic strategies and at the same time helps to understand natural regulatory and signaling processes in biological systems.

Development of a calibration protocol and identification of the most sensitive parameters for the particulate biofilm models used in biological wastewater treatment.

PubMed

Eldyasti, Ahmed; Nakhla, George; Zhu, Jesse

2012-05-01

Biofilm models are valuable tools for process engineers to simulate biological wastewater treatment. In order to enhance the use of biofilm models implemented in contemporary simulation software, model calibration is both necessary and helpful. The aim of this work was to develop a calibration protocol of the particulate biofilm model with a help of the sensitivity analysis of the most important parameters in the biofilm model implemented in BioWin® and verify the predictability of the calibration protocol. A case study of a circulating fluidized bed bioreactor (CFBBR) system used for biological nutrient removal (BNR) with a fluidized bed respirometric study of the biofilm stoichiometry and kinetics was used to verify and validate the proposed calibration protocol. Applying the five stages of the biofilm calibration procedures enhanced the applicability of BioWin®, which was capable of predicting most of the performance parameters with an average percentage error (APE) of 0-20%. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

POTENTIAL OF BIOLOGICAL MONITORING SYSTEMS TO DETECT TOXICITY IN A FINISHED MATRIX

EPA Science Inventory

Distribution systems of the U.S. are vulnerable to natural and anthropogenic factors affecting quality for use as drinking water. Important factors include physical parameters such as increased turbidity, ecological cycles such as algal blooms, and episodic contamination events ...

On Finding and Using Identifiable Parameter Combinations in Nonlinear Dynamic Systems Biology Models and COMBOS: A Novel Web Implementation

PubMed Central

DiStefano, Joseph

2014-01-01

Parameter identifiability problems can plague biomodelers when they reach the quantification stage of development, even for relatively simple models. Structural identifiability (SI) is the primary question, usually understood as knowing which of P unknown biomodel parameters p 1,…, pi,…, pP are-and which are not-quantifiable in principle from particular input-output (I-O) biodata. It is not widely appreciated that the same database also can provide quantitative information about the structurally unidentifiable (not quantifiable) subset, in the form of explicit algebraic relationships among unidentifiable pi. Importantly, this is a first step toward finding what else is needed to quantify particular unidentifiable parameters of interest from new I–O experiments. We further develop, implement and exemplify novel algorithms that address and solve the SI problem for a practical class of ordinary differential equation (ODE) systems biology models, as a user-friendly and universally-accessible web application (app)–COMBOS. Users provide the structural ODE and output measurement models in one of two standard forms to a remote server via their web browser. COMBOS provides a list of uniquely and non-uniquely SI model parameters, and–importantly-the combinations of parameters not individually SI. If non-uniquely SI, it also provides the maximum number of different solutions, with important practical implications. The behind-the-scenes symbolic differential algebra algorithms are based on computing Gröbner bases of model attributes established after some algebraic transformations, using the computer-algebra system Maxima. COMBOS was developed for facile instructional and research use as well as modeling. We use it in the classroom to illustrate SI analysis; and have simplified complex models of tumor suppressor p53 and hormone regulation, based on explicit computation of parameter combinations. It’s illustrated and validated here for models of moderate complexity, with and without initial conditions. Built-in examples include unidentifiable 2 to 4-compartment and HIV dynamics models. PMID:25350289

Tracing molecular dephasing in biological tissue

NASA Astrophysics Data System (ADS)

Mokim, M.; Carruba, C.; Ganikhanov, F.

2017-10-01

We demonstrate the quantitative spectroscopic characterization and imaging of biological tissue using coherent time-domain microscopy with a femtosecond resolution. We identify tissue constituents and perform dephasing time (T2) measurements of characteristic Raman active vibrations. This was shown in subcutaneous mouse fat embedded within collagen rich areas of the dermis and the muscle connective tissue. The demonstrated equivalent spectral resolution (<0.3 cm-1) is an order of magnitude better compared to commonly used frequency-domain methods for characterization of biological media. This provides with the important dimensions and parameters in biological media characterization and can become an effective tool in detecting minute changes in the bio-molecular composition and environment that is critical for molecular level diagnosis.

Parameter estimation and sensitivity analysis for a mathematical model with time delays of leukemia

NASA Astrophysics Data System (ADS)

Cândea, Doina; Halanay, Andrei; Rǎdulescu, Rodica; Tǎlmaci, Rodica

2017-01-01

We consider a system of nonlinear delay differential equations that describes the interaction between three competing cell populations: healthy, leukemic and anti-leukemia T cells involved in Chronic Myeloid Leukemia (CML) under treatment with Imatinib. The aim of this work is to establish which model parameters are the most important in the success or failure of leukemia remission under treatment using a sensitivity analysis of the model parameters. For the most significant parameters of the model which affect the evolution of CML disease during Imatinib treatment we try to estimate the realistic values using some experimental data. For these parameters, steady states are calculated and their stability is analyzed and biologically interpreted.

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems

PubMed Central

Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

2006-01-01

Background We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. Results We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Conclusion Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems. PMID:17081289

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems.

PubMed

Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

2006-11-02

We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems.

Structural identifiability of cyclic graphical models of biological networks with latent variables.

PubMed

Wang, Yulin; Lu, Na; Miao, Hongyu

2016-06-13

Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and is thus of higher resolution in comparison with many existing approaches. Overall, this study provides a basis for systematic examination and refinement of graphical models of biological networks from the identifiability point of view, and it has a significant potential to be extended to more complex network structures or high-dimensional systems.

Relative toxicity testing of spacecraft materials. 2: Aircraft materials

NASA Technical Reports Server (NTRS)

Lawrence, W. H.

1980-01-01

The relative toxicity of thermodegradation (pyrolysis/combustion) products of aircraft materials was studied. Two approaches were taken to assess the biological activity of the pyrolysis/combustion products of these materials: (1) determine the acute lethality to rats from inhalation of these pyrolysates and (2) examine the tendency for sublethal exposure to the pyrolysates to disrupt behavioral (shock avoidance) performance of exposed rats. The ralative importance of lethality vs. behavioral effects in selection of a material may be dictated by whether or not individuals potentially exposed to such products, would have an opportunity to escape if they were behaviorally capable of doing so. If so, the second parameter would assume greater importance, but if not the first parameter may be of much greater importance in selecting materials.

The Importance of Conducting Life Sciences Experiments on the Deep Space Gateway Platform

NASA Technical Reports Server (NTRS)

Bhattacharya, S.

2018-01-01

Over the last several decades important information has been gathered by conducting life science experiments on the Space Shuttle and on the International Space Station. It is now time to leverage that scientific knowledge, as well as aspects of the hardware that have been developed to support the biological model systems, to NASA's next frontier - the Deep Space Gateway. In order to facilitate long duration deep space exploration for humans, it is critical for NASA to understand the effects of long duration, low dose, deep space radiation on biological systems. While carefully controlled ground experiments on Earth-based radiation facilities have provided valuable preliminary information, we still have a significant knowledge gap on the biological responses of organisms to chronic low doses of the highly ionizing particles encountered beyond low Earth orbit. Furthermore, the combined effects of altered gravity and radiation have the potential to cause greater biological changes than either of these parameters alone. Therefore a thorough investigation of the biological effects of a cis-lunar environment will facilitate long term human exploration of deep space.

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.

Determination of selenium in biological samples with an energy-dispersive X-ray fluorescence spectrometer.

PubMed

Li, Xiaoli; Yu, Zhaoshui

2016-05-01

Selenium is both a nutrient and a toxin. Selenium-especially organic selenium-is a core component of human nutrition. Thus, it is very important to measure selenium in biological samples. The limited sensitivity of conventional XRF hampers its widespread use in biological samples. Here, we describe the use of high-energy (100kV, 600W) linearly polarized beam energy-dispersive X-Ray fluorescence spectroscopy (EDXRF) in tandem with a three-dimensional optics design to determine 0.1-5.1μgg(-1) levels of selenium in biological samples. The effects of various experimental parameters such as applied voltage, acquisition time, secondary target and various filters were thoroughly investigated. The detection limit of selenium in biological samples via high-energy (100kV, 600W) linearly polarized beam energy-dispersive X-ray fluorescence spectroscopy was decreased by one order of magnitude versus conventional XRF (Paltridge et al., 2012) and found to be 0.1μg/g. To the best of our knowledge, this is the first report to describe EDXRF measurements of Se in biological samples with important implications for the nutrition and analytical chemistry communities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Importance of dosimetry protocol for cell irradiation on a low X-rays facility and consequences for the biological response.

PubMed

Dos Santos, Morgane; Paget, Vincent; Ben Kacem, Mariam; Trompier, François; Benadjaoud, Mohamed Amine; François, Agnès; Guipaud, Olivier; Benderitter, Marc; Milliat, Fabien

2018-06-01

The main objective of radiobiology is to establish links between doses and radiation-induced biological effects. In this context, well-defined dosimetry protocols are crucial to the determination of experimental protocols. This work proposes a new dosimetry protocol for cell irradiation in a SARRP and shows the importance of the modification of some parameters defined in dosimetry protocol for physical dose and biological outcomes. Once all parameters of the configuration were defined, dosimetry measurements with ionization chambers and EBT3 films were performed to evaluate the dose rate and the attenuation due to the cell culture medium. To evaluate the influence of changes in cell culture volume and/or additional filtration, 6-well plates containing EBT3 films with water were used to determine the impact on the physical dose at 80 kV. Then, experiments with the same irradiation conditions were performed by replacing EBT3 films by HUVECs. The biological response was assessed using clonogenic assay. Using a 0.15 mm copper filter lead to a variation of +1% using medium thickness of 0.104 cm to -8% using a medium thickness of 0.936 cm on the physical dose compare to the reference condition (0.313 cm). For the 1 mm aluminum filter, a variation of +8 to -40% for the same medium thickness conditions has been observed. Cells irradiated in the same conditions showed significant differences in survival fraction, corroborating the effects of dosimetric changes on physical dose. This work shows the importance of dosimetry in radiobiology studies and the need of an accurate description of the dosimetry protocol used for irradiation.

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.

PubMed

Ligon, Thomas S; Fröhlich, Fabian; Chis, Oana T; Banga, Julio R; Balsa-Canto, Eva; Hasenauer, Jan

2018-04-15

Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models. GenSSI 2.0 is an open-source MATLAB toolbox and available at https://github.com/genssi-developer/GenSSI. thomas.ligon@physik.uni-muenchen.de or jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

Bioinspiration: applying mechanical design to experimental biology.

PubMed

Flammang, Brooke E; Porter, Marianne E

2011-07-01

The production of bioinspired and biomimetic constructs has fostered much collaboration between biologists and engineers, although the extent of biological accuracy employed in the designs produced has not always been a priority. Even the exact definitions of "bioinspired" and "biomimetic" differ among biologists, engineers, and industrial designers, leading to confusion regarding the level of integration and replication of biological principles and physiology. By any name, biologically-inspired mechanical constructs have become an increasingly important research tool in experimental biology, offering the opportunity to focus research by creating model organisms that can be easily manipulated to fill a desired parameter space of structural and functional repertoires. Innovative researchers with both biological and engineering backgrounds have found ways to use bioinspired models to explore the biomechanics of organisms from all kingdoms to answer a variety of different questions. Bringing together these biologists and engineers will hopefully result in an open discourse of techniques and fruitful collaborations for experimental and industrial endeavors.

Parameter Balancing in Kinetic Models of Cell Metabolism†

PubMed Central

2010-01-01

Kinetic modeling of metabolic pathways has become a major field of systems biology. It combines structural information about metabolic pathways with quantitative enzymatic rate laws. Some of the kinetic constants needed for a model could be collected from ever-growing literature and public web resources, but they are often incomplete, incompatible, or simply not available. We address this lack of information by parameter balancing, a method to complete given sets of kinetic constants. Based on Bayesian parameter estimation, it exploits the thermodynamic dependencies among different biochemical quantities to guess realistic model parameters from available kinetic data. Our algorithm accounts for varying measurement conditions in the input data (pH value and temperature). It can process kinetic constants and state-dependent quantities such as metabolite concentrations or chemical potentials, and uses prior distributions and data augmentation to keep the estimated quantities within plausible ranges. An online service and free software for parameter balancing with models provided in SBML format (Systems Biology Markup Language) is accessible at www.semanticsbml.org. We demonstrate its practical use with a small model of the phosphofructokinase reaction and discuss its possible applications and limitations. In the future, parameter balancing could become an important routine step in the kinetic modeling of large metabolic networks. PMID:21038890

Kinetics and mechanisms of thiol-disulfide exchange covering direct substitution and thiol oxidation-mediated pathways.

PubMed

Nagy, Péter

2013-05-01

Disulfides are important building blocks in the secondary and tertiary structures of proteins, serving as inter- and intra-subunit cross links. Disulfides are also the major products of thiol oxidation, a process that has primary roles in defense mechanisms against oxidative stress and in redox regulation of cell signaling. Although disulfides are relatively stable, their reduction, isomerisation, and interconversion as well as their production reactions are catalyzed by delicate enzyme machineries, providing a dynamic system in biology. Redox homeostasis, a thermodynamic parameter that determines which reactions can occur in cellular compartments, is also balanced by the thiol-disulfide pool. However, it is the kinetic properties of the reactions that best represent cell dynamics, because the partitioning of the possible reactions depends on kinetic parameters. This review is focused on the kinetics and mechanisms of thiol-disulfide substitution and redox reactions. It summarizes the challenges and advances that are associated with kinetic investigations in small molecular and enzymatic systems from a rigorous chemical perspective using biological examples. The most important parameters that influence reaction rates are discussed in detail. Kinetic studies of proteins are more challenging than small molecules, and quite often investigators are forced to sacrifice the rigor of the experimental approach to obtain the important kinetic and mechanistic information. However, recent technological advances allow a more comprehensive analysis of enzymatic systems via using the systematic kinetics apparatus that was developed for small molecule reactions, which is expected to provide further insight into the cell's machinery.

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.

Cation Selectivity in Biological Cation Channels Using Experimental Structural Information and Statistical Mechanical Simulation.

PubMed

Finnerty, Justin John; Peyser, Alexander; Carloni, Paolo

2015-01-01

Cation selective channels constitute the gate for ion currents through the cell membrane. Here we present an improved statistical mechanical model based on atomistic structural information, cation hydration state and without tuned parameters that reproduces the selectivity of biological Na+ and Ca2+ ion channels. The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores.

Human hair follicle organ culture: theory, application and perspectives.

PubMed

Langan, Ewan A; Philpott, Michael P; Kloepper, Jennifer E; Paus, Ralf

2015-12-01

For almost a quarter of a century, ex vivo studies of human scalp hair follicles (HFs) have permitted major advances in hair research, spanning diverse fields such as chronobiology, endocrinology, immunology, metabolism, mitochondrial biology, neurobiology, pharmacology, pigmentation and stem cell biology. Despite this, a comprehensive methodological guide to serum-free human HF organ culture (HFOC) that facilitates the selection and analysis of standard HF biological parameters and points out both research opportunities and pitfalls to newcomers to the field is still lacking. The current methods review aims to close an important gap in the literature and attempts to promote standardisation of human HFOC. We provide basic information outlining the establishment of HFOC through to detailed descriptions of the analysis of standard read-out parameters alongside practical examples. The guide closes by pointing out how serum-free HFOC can be utilised optimally to obtain previously inaccessible insights into human HF biology and pathology that are of interest to experimental dermatologists, geneticists, developmental biologists and (neuro-) endocrinologists alike and by highlighting novel applications of the model, including gene silencing and gene expression profiling of defined, laser capture-microdissected HF compartments. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Gravity-Driven Thin Film Flow of an Ellis Fluid.

PubMed

Kheyfets, Vitaly O; Kieweg, Sarah L

2013-12-01

The thin film lubrication approximation has been studied extensively for moving contact lines of Newtonian fluids. However, many industrial and biological applications of the thin film equation involve shear-thinning fluids, which often also exhibit a Newtonian plateau at low shear. This study presents new numerical simulations of the three-dimensional (i.e. two-dimensional spreading), constant-volume, gravity-driven, free surface flow of an Ellis fluid. The numerical solution was validated with a new similarity solution, compared to previous experiments, and then used in a parametric study. The parametric study centered around rheological data for an example biological application of thin film flow: topical drug delivery of anti-HIV microbicide formulations, e.g. hydroxyethylcellulose (HEC) polymer solutions. The parametric study evaluated how spreading length and front velocity saturation depend on Ellis parameters. A lower concentration polymer solution with smaller zero shear viscosity ( η 0 ), τ 1/2 , and λ values spread further. However, when comparing any two fluids with any possible combinations of Ellis parameters, the impact of changing one parameter on spreading length depends on the direction and magnitude of changes in the other two parameters. In addition, the isolated effect of the shear-thinning parameter, λ , on the front velocity saturation depended on τ 1/2 . This study highlighted the relative effects of the individual Ellis parameters, and showed that the shear rates in this flow were in both the shear-thinning and plateau regions of rheological behavior, emphasizing the importance of characterizing the full range of shear-rates in rheological measurements. The validated numerical model and parametric study provides a useful tool for future steps to optimize flow of a fluid with rheological behavior well-described by the Ellis constitutive model, in a range of industrial and biological applications.

A simple method for identifying parameter correlations in partially observed linear dynamic models.

PubMed

Li, Pu; Vu, Quoc Dong

2015-12-14

Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a software packet.

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

NASA Astrophysics Data System (ADS)

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

1999-01-01

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

Flow cytogenetics and chromosome sorting.

PubMed

Cram, L S

1990-06-01

This review of flow cytogenetics and chromosome sorting provides an overview of general information in the field and describes recent developments in more detail. From the early developments of chromosome analysis involving single parameter or one color analysis to the latest developments in slit scanning of single chromosomes in a flow stream, the field has progressed rapidly and most importantly has served as an important enabling technology for the human genome project. Technological innovations that advanced flow cytogenetics are described and referenced. Applications in basic cell biology, molecular biology, and clinical investigations are presented. The necessary characteristics for large number chromosome sorting are highlighted. References to recent review articles are provided as a starting point for locating individual references that provide more detail. Specific references are provided for recent developments.

Enzyme activities by indicator of quality in organic soil

NASA Astrophysics Data System (ADS)

Raigon Jiménez, Mo; Fita, Ana Delores; Rodriguez Burruezo, Adrián

2016-04-01

The analytical determination of biochemical parameters, as soil enzyme activities and those related to the microbial biomass is growing importance by biological indicator in soil science studies. The metabolic activity in soil is responsible of important processes such as mineralization and humification of organic matter. These biological reactions will affect other key processes involved with elements like carbon, nitrogen and phosphorus , and all transformations related in soil microbial biomass. The determination of biochemical parameters is useful in studies carried out on organic soil where microbial processes that are key to their conservation can be analyzed through parameters of the metabolic activity of these soils. The main objective of this work is to apply analytical methodologies of enzyme activities in soil collections of different physicochemical characteristics. There have been selective sampling of natural soils, organic farming soils, conventional farming soils and urban soils. The soils have been properly identified conserved at 4 ° C until analysis. The enzyme activities determinations have been: catalase, urease, cellulase, dehydrogenase and alkaline phosphatase, which bring together a representative group of biological transformations that occur in the soil environment. The results indicate that for natural and agronomic soil collections, the values of the enzymatic activities are within the ranges established for forestry and agricultural soils. Organic soils are generally higher level of enzymatic, regardless activity of the enzyme involved. Soil near an urban area, levels of activities have been significantly reduced. The vegetation cover applied to organic soils, results in greater enzymatic activity. So the quality of these soils, defined as the ability to maintain their biological productivity is increased with the use of cover crops, whether or spontaneous species. The practice of cover based on legumes could be used as an ideal choice for the recovery of degraded soils, because these soils have the highest levels of enzymatic activities.

The impact of different dose response parameters on biologically optimized IMRT in breast cancer

NASA Astrophysics Data System (ADS)

Costa Ferreira, Brigida; Mavroidis, Panayiotis; Adamus-Górka, Magdalena; Svensson, Roger; Lind, Bengt K.

2008-05-01

The full potential of biologically optimized radiation therapy can only be maximized with the prediction of individual patient radiosensitivity prior to treatment. Unfortunately, the available biological parameters, derived from clinical trials, reflect an average radiosensitivity of the examined populations. In the present study, a breast cancer patient of stage I II with positive lymph nodes was chosen in order to analyse the effect of the variation of individual radiosensitivity on the optimal dose distribution. Thus, deviations from the average biological parameters, describing tumour, heart and lung response, were introduced covering the range of patient radiosensitivity reported in the literature. Two treatment configurations of three and seven biologically optimized intensity-modulated beams were employed. The different dose distributions were analysed using biological and physical parameters such as the complication-free tumour control probability (P+), the biologically effective uniform dose (\\bar{\\bar{D}} ), dose volume histograms, mean doses, standard deviations, maximum and minimum doses. In the three-beam plan, the difference in P+ between the optimal dose distribution (when the individual patient radiosensitivity is known) and the reference dose distribution, which is optimal for the average patient biology, ranges up to 13.9% when varying the radiosensitivity of the target volume, up to 0.9% when varying the radiosensitivity of the heart and up to 1.3% when varying the radiosensitivity of the lung. Similarly, in the seven-beam plan, the differences in P+ are up to 13.1% for the target, up to 1.6% for the heart and up to 0.9% for the left lung. When the radiosensitivity of the most important tissues in breast cancer radiation therapy was simultaneously changed, the maximum gain in outcome was as high as 7.7%. The impact of the dose response uncertainties on the treatment outcome was clinically insignificant for the majority of the simulated patients. However, the jump from generalized to individualized radiation therapy may significantly increase the therapeutic window for patients with extreme radio sensitivity or radioresistance, provided that these are identified. Even for radiosensitive patients a simple treatment technique is sufficient to maximize the outcome, since no significant benefits were obtained with a more complex technique using seven intensity-modulated beams portals.

Contact nanomechanical measurements with the AFM

NASA Astrophysics Data System (ADS)

Geisse, Nicholas

2013-03-01

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

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.

The impact of temporal sampling resolution on parameter inference for biological transport models.

PubMed

Harrison, Jonathan U; Baker, Ruth E

2018-06-25

Imaging data has become an essential tool to explore key biological questions at various scales, for example the motile behaviour of bacteria or the transport of mRNA, and it has the potential to transform our understanding of important transport mechanisms. Often these imaging studies require us to compare biological species or mutants, and to do this we need to quantitatively characterise their behaviour. Mathematical models offer a quantitative description of a system that enables us to perform this comparison, but to relate mechanistic mathematical models to imaging data, we need to estimate their parameters. In this work we study how collecting data at different temporal resolutions impacts our ability to infer parameters of biological transport models; performing exact inference for simple velocity jump process models in a Bayesian framework. The question of how best to choose the frequency with which data is collected is prominent in a host of studies because the majority of imaging technologies place constraints on the frequency with which images can be taken, and the discrete nature of observations can introduce errors into parameter estimates. In this work, we mitigate such errors by formulating the velocity jump process model within a hidden states framework. This allows us to obtain estimates of the reorientation rate and noise amplitude for noisy observations of a simple velocity jump process. We demonstrate the sensitivity of these estimates to temporal variations in the sampling resolution and extent of measurement noise. We use our methodology to provide experimental guidelines for researchers aiming to characterise motile behaviour that can be described by a velocity jump process. In particular, we consider how experimental constraints resulting in a trade-off between temporal sampling resolution and observation noise may affect parameter estimates. Finally, we demonstrate the robustness of our methodology to model misspecification, and then apply our inference framework to a dataset that was generated with the aim of understanding the localization of RNA-protein complexes.

A confidence building exercise in data and identifiability: Modeling cancer chemotherapy as a case study.

PubMed

Eisenberg, Marisa C; Jain, Harsh V

2017-10-27

Mathematical modeling has a long history in the field of cancer therapeutics, and there is increasing recognition that it can help uncover the mechanisms that underlie tumor response to treatment. However, making quantitative predictions with such models often requires parameter estimation from data, raising questions of parameter identifiability and estimability. Even in the case of structural (theoretical) identifiability, imperfect data and the resulting practical unidentifiability of model parameters can make it difficult to infer the desired information, and in some cases, to yield biologically correct inferences and predictions. Here, we examine parameter identifiability and estimability using a case study of two compartmental, ordinary differential equation models of cancer treatment with drugs that are cell cycle-specific (taxol) as well as non-specific (oxaliplatin). We proceed through model building, structural identifiability analysis, parameter estimation, practical identifiability analysis and its biological implications, as well as alternative data collection protocols and experimental designs that render the model identifiable. We use the differential algebra/input-output relationship approach for structural identifiability, and primarily the profile likelihood approach for practical identifiability. Despite the models being structurally identifiable, we show that without consideration of practical identifiability, incorrect cell cycle distributions can be inferred, that would result in suboptimal therapeutic choices. We illustrate the usefulness of estimating practically identifiable combinations (in addition to the more typically considered structurally identifiable combinations) in generating biologically meaningful insights. We also use simulated data to evaluate how the practical identifiability of the model would change under alternative experimental designs. These results highlight the importance of understanding the underlying mechanisms rather than purely using parsimony or information criteria/goodness-of-fit to decide model selection questions. The overall roadmap for identifiability testing laid out here can be used to help provide mechanistic insight into complex biological phenomena, reduce experimental costs, and optimize model-driven experimentation. Copyright © 2017. Published by Elsevier Ltd.

CT dose reduction in children.

PubMed

Vock, Peter

2005-11-01

World wide, the number of CT studies in children and the radiation exposure by CT increases. The same energy dose has a greater biological impact in children than in adults, and scan parameters have to be adapted to the smaller diameter of the juvenile body. Based on seven rules, a practical approach to paediatric CT is shown: Justification and patient preparation are important steps before scanning, and they differ from the preparation of adult patients. The subsequent choice of scan parameters aims at obtaining the minimal signal-to-noise ratio and volume coverage needed in a specific medical situation; exposure can be divided in two aspects: the CT dose index determining energy deposition per rotation and the dose-length product (DLP) determining the volume dose. DLP closely parallels the effective dose, the best parameter of the biological impact. Modern scanners offer dose modulation to locally minimise exposure while maintaining image quality. Beyond the selection of the physical parameters, the dose can be kept low by scanning the minimal length of the body and by avoiding any non-qualified repeated scanning of parts of the body. Following these rules, paediatric CT examinations of good quality can be obtained at a reasonable cost of radiation exposure.

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

Gap assessment in current soil monitoring networks across Europe for measuring soil functions

NASA Astrophysics Data System (ADS)

van Leeuwen, J. P.; Saby, N. P. A.; Jones, A.; Louwagie, G.; Micheli, E.; Rutgers, M.; Schulte, R. P. O.; Spiegel, H.; Toth, G.; Creamer, R. E.

2017-12-01

Soil is the most important natural resource for life on Earth after water. Given its fundamental role in sustaining the human population, both the availability and quality of soil must be managed sustainably and protected. To ensure sustainable management we need to understand the intrinsic functional capacity of different soils across Europe and how it changes over time. Soil monitoring is needed to support evidence-based policies to incentivise sustainable soil management. To this aim, we assessed which soil attributes can be used as potential indicators of five soil functions; (1) primary production, (2) water purification and regulation, (3) carbon sequestration and climate regulation, (4) soil biodiversity and habitat provisioning and (5) recycling of nutrients. We compared this list of attributes to existing national (regional) and EU-wide soil monitoring networks. The overall picture highlighted a clearly unbalanced dataset, in which predominantly chemical soil parameters were included, and soil biological and physical attributes were severely under represented. Methods applied across countries for indicators also varied. At a European scale, the LUCAS-soil survey was evaluated and again confirmed a lack of important soil biological parameters, such as C mineralisation rate, microbial biomass and earthworm community, and soil physical measures such as bulk density. In summary, no current national or European monitoring system exists which has the capacity to quantify the five soil functions and therefore evaluate multi-functional capacity of a soil and in many countries no data exists at all. This paper calls for the addition of soil biological and some physical parameters within the LUCAS-soil survey at European scale and for further development of national soil monitoring schemes.

Towards Engineering Biological Systems in a Broader Context.

PubMed

Venturelli, Ophelia S; Egbert, Robert G; Arkin, Adam P

2016-02-27

Significant advances have been made in synthetic biology to program information processing capabilities in cells. While these designs can function predictably in controlled laboratory environments, the reliability of these devices in complex, temporally changing environments has not yet been characterized. As human society faces global challenges in agriculture, human health and energy, synthetic biology should develop predictive design principles for biological systems operating in complex environments. Natural biological systems have evolved mechanisms to overcome innumerable and diverse environmental challenges. Evolutionary design rules should be extracted and adapted to engineer stable and predictable ecological function. We highlight examples of natural biological responses spanning the cellular, population and microbial community levels that show promise in synthetic biology contexts. We argue that synthetic circuits embedded in host organisms or designed ecologies informed by suitable measurement of biotic and abiotic environmental parameters could be used as engineering substrates to achieve target functions in complex environments. Successful implementation of these methods will broaden the context in which synthetic biological systems can be applied to solve important problems. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluating effective swath width and droplet distribution of aerial spraying systems on M-18B and Thrush 510G airplanes

USDA-ARS?s Scientific Manuscript database

Aerial spraying plays an important role in promoting agricultural production and protecting the biological environment due to its flexibility, high effectiveness, and large operational area per unit of time. In order to evaluate the performance parameters of the spraying systems on two fixed wing ai...

Opinion Building on a Socio-Scientific Issue: The Case of Genetically Modified Plants

ERIC Educational Resources Information Center

Ekborg, Margareta

2008-01-01

This paper presents results from a study with the following research questions: (a) are pupils' opinions on genetically modified organisms (GMOs) influenced by biology teaching; and (b) what is important for the opinion pupils hold and how does knowledge work together with other parameters such as values? 64 pupils in an upper secondary school…

An improved hybrid of particle swarm optimization and the gravitational search algorithm to produce a kinetic parameter estimation of aspartate biochemical pathways.

PubMed

Ismail, Ahmad Muhaimin; Mohamad, Mohd Saberi; Abdul Majid, Hairudin; Abas, Khairul Hamimah; Deris, Safaai; Zaki, Nazar; Mohd Hashim, Siti Zaiton; Ibrahim, Zuwairie; Remli, Muhammad Akmal

2017-12-01

Mathematical modelling is fundamental to understand the dynamic behavior and regulation of the biochemical metabolisms and pathways that are found in biological systems. Pathways are used to describe complex processes that involve many parameters. It is important to have an accurate and complete set of parameters that describe the characteristics of a given model. However, measuring these parameters is typically difficult and even impossible in some cases. Furthermore, the experimental data are often incomplete and also suffer from experimental noise. These shortcomings make it challenging to identify the best-fit parameters that can represent the actual biological processes involved in biological systems. Computational approaches are required to estimate these parameters. The estimation is converted into multimodal optimization problems that require a global optimization algorithm that can avoid local solutions. These local solutions can lead to a bad fit when calibrating with a model. Although the model itself can potentially match a set of experimental data, a high-performance estimation algorithm is required to improve the quality of the solutions. This paper describes an improved hybrid of particle swarm optimization and the gravitational search algorithm (IPSOGSA) to improve the efficiency of a global optimum (the best set of kinetic parameter values) search. The findings suggest that the proposed algorithm is capable of narrowing down the search space by exploiting the feasible solution areas. Hence, the proposed algorithm is able to achieve a near-optimal set of parameters at a fast convergence speed. The proposed algorithm was tested and evaluated based on two aspartate pathways that were obtained from the BioModels Database. The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. Nevertheless, the proposed algorithm is only expected to work well in small scale systems. In addition, the results of this study can be used to estimate kinetic parameter values in the stage of model selection for different experimental conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of terahertz dielectric properties of pork tissue

NASA Astrophysics Data System (ADS)

Huang, Yuqing; Xie, Qiaoling; Sun, Ping

2017-10-01

Seeing that about 70% component of fresh biological tissues is water, many scientists try to use water models to describe the dielectric properties of biological tissues. The classical water dielectric models are Debye model, Double Debye model and Cole-Cole model. This work aims to determine a suitable model by comparing three models above with experimental data. These models are applied to fresh pork tissue. By means of least square method, the parameters of different models are fitted with the experimental data. Comparing different models on both dielectric function, the Cole-Cole model is verified the best to describe the experiments of pork tissue. The correction factor α of the Cole-Cole model is an important modification for biological tissues. So Cole-Cole model is supposed to be a priority selection to describe the dielectric properties for biological tissues in the terahertz range.

Investigating biological activity spectrum for novel quinoline analogues.

PubMed

Musiol, Robert; Jampilek, Josef; Kralova, Katarina; Richardson, Des R; Kalinowski, Danuta; Podeszwa, Barbara; Finster, Jacek; Niedbala, Halina; Palka, Anna; Polanski, Jaroslaw

2007-02-01

The lack of the wide spectrum of biological data is an important obstacle preventing the efficient molecular design. Quinoline derivatives are known to exhibit a variety of biological effects. In the current publication, we tested a series of novel quinoline analogues for their photosynthesis-inhibiting activity (the inhibition of photosynthetic electron transport in spinach chloroplasts (Spinacia oleracea L.) and the reduction of chlorophyll content in Chlorella vulgaris Beij.). Moreover, antiproliferative activity was measured using SK-N-MC neuroepithelioma cell line. We described the structure-activity relationships (SAR) between the chemical structure and biological effects of the synthesized compounds. We also measured the lipophilicity of the novel compounds by means of the RP-HPLC and illustrate the relationships between the RP-HPLC retention parameter logK (the logarithm of capacity factor K) and logP data calculated by available programs.

Testing the coherence between occupational exposure limits for inhalation and their biological limit values with a generalized PBPK-model: the case of 2-propanol and acetone.

PubMed

Huizer, Daan; Huijbregts, Mark A J; van Rooij, Joost G M; Ragas, Ad M J

2014-08-01

The coherence between occupational exposure limits (OELs) and their corresponding biological limit values (BLVs) was evaluated for 2-propanol and acetone. A generic human PBPK model was used to predict internal concentrations after inhalation exposure at the level of the OEL. The fraction of workers with predicted internal concentrations lower than the BLV, i.e. the 'false negatives', was taken as a measure for incoherence. The impact of variability and uncertainty in input parameters was separated by means of nested Monte Carlo simulation. Depending on the exposure scenario considered, the median fraction of the population for which the limit values were incoherent ranged from 2% to 45%. Parameter importance analysis showed that body weight was the main factor contributing to interindividual variability in blood and urine concentrations and that the metabolic parameters Vmax and Km were the most important sources of uncertainty. This study demonstrates that the OELs and BLVs for 2-propanol and acetone are not fully coherent, i.e. enforcement of BLVs may result in OELs being violated. In order to assess the acceptability of this "incoherence", a maximum population fraction at risk of exceeding the OEL should be specified as well as a minimum level of certainty in predicting this fraction. Copyright © 2014 Elsevier Inc. All rights reserved.

Ride comfort analysis with physiological parameters for an e-health train.

PubMed

Lee, Youngbum; Shin, Kwangsoo; Lee, Sangjoon; Song, Yongsoo; Han, Sungho; Lee, Myoungho

2009-12-01

Transportation by train has numerous advantages over road transportation, especially with regard to energy efficiency, ecological features, safety, and punctuality. However, the contrast in ride comfort between standard road transportation and train travel has become a competitive issue. The ride comfort enhancement technology of tilting trains (TTX) is a particularly important issue in the development of the Korean high-speed railroad business. Ride comfort is now defined in international standards such as UIC13 and ISO2631. The Korean standards such as KSR9216 mainly address physical parameters such as vibration and noise. In the area of ride comfort, living quality parameter techniques have recently been considered in Korea, Japan, and Europe. This study introduces biological parameters, particularly variations in heart rate, as a more direct measure of comfort. Biological parameters are based on physiological responses rather than on purely external mechanical parameters. Variability of heart rate and other physiological parameters of passengers are measured in a simulation involving changes in the tilting angle of the TTX. This research is a preliminary study for the implementation of an e-health train, which would provide passengers with optimized ride comfort. The e-health train would also provide feedback on altered ride comfort situations that can improve a passenger's experience and provide a healthcare service on the train. The aim of this research was to develop a ride comfort evaluation system for the railway industry, the automobile industry, and the air industry. The degree of tilt correlated with heart rate, fatigue, and unrelieved alertness.

Kinetics and Mechanisms of Thiol–Disulfide Exchange Covering Direct Substitution and Thiol Oxidation-Mediated Pathways

PubMed Central

2013-01-01

Abstract Significance: Disulfides are important building blocks in the secondary and tertiary structures of proteins, serving as inter- and intra-subunit cross links. Disulfides are also the major products of thiol oxidation, a process that has primary roles in defense mechanisms against oxidative stress and in redox regulation of cell signaling. Although disulfides are relatively stable, their reduction, isomerisation, and interconversion as well as their production reactions are catalyzed by delicate enzyme machineries, providing a dynamic system in biology. Redox homeostasis, a thermodynamic parameter that determines which reactions can occur in cellular compartments, is also balanced by the thiol–disulfide pool. However, it is the kinetic properties of the reactions that best represent cell dynamics, because the partitioning of the possible reactions depends on kinetic parameters. Critical Issues: This review is focused on the kinetics and mechanisms of thiol–disulfide substitution and redox reactions. It summarizes the challenges and advances that are associated with kinetic investigations in small molecular and enzymatic systems from a rigorous chemical perspective using biological examples. The most important parameters that influence reaction rates are discussed in detail. Recent Advances and Future Directions: Kinetic studies of proteins are more challenging than small molecules, and quite often investigators are forced to sacrifice the rigor of the experimental approach to obtain the important kinetic and mechanistic information. However, recent technological advances allow a more comprehensive analysis of enzymatic systems via using the systematic kinetics apparatus that was developed for small molecule reactions, which is expected to provide further insight into the cell's machinery. Antioxid. Redox Signal. 18, 1623–1641. PMID:23075118

Systematic characterization and fluorescence threshold strategies for the wideband integrated bioaerosol sensor (WIBS) using size-resolved biological and interfering particles

NASA Astrophysics Data System (ADS)

Savage, Nicole J.; Krentz, Christine E.; Könemann, Tobias; Han, Taewon T.; Mainelis, Gediminas; Pöhlker, Christopher; Huffman, J. Alex

2017-11-01

Atmospheric particles of biological origin, also referred to as bioaerosols or primary biological aerosol particles (PBAP), are important to various human health and environmental systems. There has been a recent steep increase in the frequency of published studies utilizing commercial instrumentation based on ultraviolet laser/light-induced fluorescence (UV-LIF), such as the WIBS (wideband integrated bioaerosol sensor) or UV-APS (ultraviolet aerodynamic particle sizer), for bioaerosol detection both outdoors and in the built environment. Significant work over several decades supported the development of the general technologies, but efforts to systematically characterize the operation of new commercial sensors have remained lacking. Specifically, there have been gaps in the understanding of how different classes of biological and non-biological particles can influence the detection ability of LIF instrumentation. Here we present a systematic characterization of the WIBS-4A instrument using 69 types of aerosol materials, including a representative list of pollen, fungal spores, and bacteria as well as the most important groups of non-biological materials reported to exhibit interfering fluorescent properties. Broad separation can be seen between the biological and non-biological particles directly using the five WIBS output parameters and by taking advantage of the particle classification analysis introduced by Perring et al. (2015). We highlight the importance that particle size plays on observed fluorescence properties and thus in the Perring-style particle classification. We also discuss several particle analysis strategies, including the commonly used fluorescence threshold defined as the mean instrument background (forced trigger; FT) plus 3 standard deviations (σ) of the measurement. Changing the particle fluorescence threshold was shown to have a significant impact on fluorescence fraction and particle type classification. We conclude that raising the fluorescence threshold from FT + 3σ to FT + 9σ does little to reduce the relative fraction of biological material considered fluorescent but can significantly reduce the interference from mineral dust and other non-biological aerosols. We discuss examples of highly fluorescent interfering particles, such as brown carbon, diesel soot, and cotton fibers, and how these may impact WIBS analysis and data interpretation in various indoor and outdoor environments. The performance of the particle asymmetry factor (AF) reported by the instrument was assessed across particle types as a function of particle size, and comments on the reliability of this parameter are given. A comprehensive online supplement is provided, which includes size distributions broken down by fluorescent particle type for all 69 aerosol materials and comparing threshold strategies. Lastly, the study was designed to propose analysis strategies that may be useful to the broader community of UV-LIF instrumentation users in order to promote deeper discussions about how best to continue improving UV-LIF instrumentation and results.

A biological perspective on differences and similarities between burnout and depression.

PubMed

Orosz, Ariane; Federspiel, Andrea; Haisch, Sarie; Seeher, Christian; Dierks, Thomas; Cattapan, Katja

2017-02-01

To compare and contrast burnout and depression is not only a conceptual issue, but may deliver important directions for treatment approaches and stabilize the awareness of disease which is essential for affected individuals. Because of the symptomatic overlap, it is a subject of multidimensional research and discussion to find specific signatures to differentiate between the two phenomena or to present evidence that they are different aspects of the same disorder. Both pathologies are regarded as stress-related disorders. Therefore, in this review burnout and depression are discussed on the basis of biological parameters, mainly heart rate variability (HRV) and brain-derived neurotrophic factor (BDNF), which are crucial to the stress response system. It emerges that instead of finding one specific discriminating marker, future research should rather concentrate on elaborating indices for burnout and depression which integrate combinations of parameters found in genetics, neurobiology, physiology and environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cation Selectivity in Biological Cation Channels Using Experimental Structural Information and Statistical Mechanical Simulation

PubMed Central

Finnerty, Justin John

2015-01-01

Cation selective channels constitute the gate for ion currents through the cell membrane. Here we present an improved statistical mechanical model based on atomistic structural information, cation hydration state and without tuned parameters that reproduces the selectivity of biological Na+ and Ca2+ ion channels. The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores. PMID:26460827

[Development and Application of Metabonomics in Forensic Toxicology].

PubMed

Yan, Hui; Shen, Min

2015-06-01

Metabonomics is an important branch of system biology following the development of genomics, transcriptomics and proteomics. It can perform high-throughput detection and data processing with multiple parameters, potentially enabling the identification and quantification of all small metabolites in a biological system. It can be used to provide comprehensive information on the toxicity effects, toxicological mechanisms and biomarkers, sensitively finding the unusual metabolic changes caused by poison. This article mainly reviews application of metabonomics in toxicological studies of abused drugs, pesticides, poisonous plants and poisonous animals, and also illustrates the new direction of forensic toxicology research.

Influential Parameters for the Analysis of Intracellular Parasite Metabolomics.

PubMed

Carey, Maureen A; Covelli, Vincent; Brown, Audrey; Medlock, Gregory L; Haaren, Mareike; Cooper, Jessica G; Papin, Jason A; Guler, Jennifer L

2018-04-25

Metabolomics is increasingly popular for the study of pathogens. For the malaria parasite Plasmodium falciparum , both targeted and untargeted metabolomics have improved our understanding of pathogenesis, host-parasite interactions, and antimalarial drug treatment and resistance. However, purification and analysis procedures for performing metabolomics on intracellular pathogens have not been explored. Here, we purified in vitro -grown ring-stage intraerythrocytic P. falciparum parasites for untargeted metabolomics studies; the small size of this developmental stage amplifies the challenges associated with metabolomics studies as the ratio between host and parasite biomass is maximized. Following metabolite identification and data preprocessing, we explored multiple confounding factors that influence data interpretation, including host contamination and normalization approaches (including double-stranded DNA, total protein, and parasite numbers). We conclude that normalization parameters have large effects on differential abundance analysis and recommend the thoughtful selection of these parameters. However, normalization does not remove the contribution from the parasite's extracellular environment (culture media and host erythrocyte). In fact, we found that extraparasite material is as influential on the metabolome as treatment with a potent antimalarial drug with known metabolic effects (artemisinin). Because of this influence, we could not detect significant changes associated with drug treatment. Instead, we identified metabolites predictive of host and medium contamination that could be used to assess sample purification. Our analysis provides the first quantitative exploration of the effects of these factors on metabolomics data analysis; these findings provide a basis for development of improved experimental and analytical methods for future metabolomics studies of intracellular organisms. IMPORTANCE Molecular characterization of pathogens such as the malaria parasite can lead to improved biological understanding and novel treatment strategies. However, the distinctive biology of the Plasmodium parasite, including its repetitive genome and the requirement for growth within a host cell, hinders progress toward these goals. Untargeted metabolomics is a promising approach to learn about pathogen biology. By measuring many small molecules in the parasite at once, we gain a better understanding of important pathways that contribute to the parasite's response to perturbations such as drug treatment. Although increasingly popular, approaches for intracellular parasite metabolomics and subsequent analysis are not well explored. The findings presented in this report emphasize the critical need for improvements in these areas to limit misinterpretation due to host metabolites and to standardize biological interpretation. Such improvements will aid both basic biological investigations and clinical efforts to understand important pathogens. Copyright © 2018 Carey et al.

Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds.

PubMed

Feng, Yan; Mitchison, Timothy J; Bender, Andreas; Young, Daniel W; Tallarico, John A

2009-07-01

Multi-parameter phenotypic profiling of small molecules provides important insights into their mechanisms of action, as well as a systems level understanding of biological pathways and their responses to small molecule treatments. It therefore deserves more attention at an early step in the drug discovery pipeline. Here, we summarize the technologies that are currently in use for phenotypic profiling--including mRNA-, protein- and imaging-based multi-parameter profiling--in the drug discovery context. We think that an earlier integration of phenotypic profiling technologies, combined with effective experimental and in silico target identification approaches, can improve success rates of lead selection and optimization in the drug discovery process.

Parameter estimation and sensitivity analysis in an agent-based model of Leishmania major infection

PubMed Central

Jones, Douglas E.; Dorman, Karin S.

2009-01-01

Computer models of disease take a systems biology approach toward understanding host-pathogen interactions. In particular, data driven computer model calibration is the basis for inference of immunological and pathogen parameters, assessment of model validity, and comparison between alternative models of immune or pathogen behavior. In this paper we describe the calibration and analysis of an agent-based model of Leishmania major infection. A model of macrophage loss following uptake of necrotic tissue is proposed to explain macrophage depletion following peak infection. Using Gaussian processes to approximate the computer code, we perform a sensitivity analysis to identify important parameters and to characterize their influence on the simulated infection. The analysis indicates that increasing growth rate can favor or suppress pathogen loads, depending on the infection stage and the pathogen’s ability to avoid detection. Subsequent calibration of the model against previously published biological observations suggests that L. major has a relatively slow growth rate and can replicate for an extended period of time before damaging the host cell. PMID:19837088

Effects of trawl selectivity and genetic parameters on fish body length under long-term trawling

NASA Astrophysics Data System (ADS)

Yu, Yang; Sun, Peng; Cui, He; Sheng, Huaxiang; Zhao, Fenfang; Tang, Yanli; Chen, Zelin

2015-10-01

Long-term fishing pressure affects the biological characteristics of exploited fish stocks. The biological characteristics of hairtail ( Trichiurus lepturus) in the East China Sea are unable to recover because of long-term trawling. Fishing induces evolutionary effects on the fish's biological characteristics. Evidence of these changes includes small size at age, a shift to earlier age structure, and early maturation. Natural and artificial selection usually affect the fish's life history. Selection can induce different chances of reproduction, and individual fish can give a different genetic contribution to the next generation. In this study, analysis of time-dependent probability of significance and test of sensitivity were used to explore the effects of fish exploitation rate, mesh size, and heritability with long-term trawling. Results showed that fishing parameters were important drivers to exploited fish population. However, genetic traits altered by fishing were slow, and the changes in biological characteristics were weaker than those caused by fishing selection. Exploitation rate and mesh size exhibited similar evolutionary trend tendency under long-term fishing. The time-dependent probability of significance trend showed a gradual growth and tended to be stable. Therefore, the direction of fishing-induced evolution and successful management of fish species require considerable attention to contribute to sustainable fisheries in China.

Relativistic parameters of senescence.

PubMed

Stathatos, Marios A

2005-01-01

The laws of biochemistry and biology are governed by parameters whose description in mathematical formulas is based on the three-dimensional space. It is a fact, however, that the life span of a cell and its specific functions, though limited, can be extended or diminished depending on the genetic code but also, on the natural pressure of the environment. The plasticity exhibited by a cellular system has been attributed to the change of the three-dimensional structure of the cell, with time being a simple measure of this change. The model of biological relativity proposed here, considers time as a flexible fourth dimension that corresponds directly to the inertial status of the cells. Two types of clocks are defined: the relativistic biological clock (RBC) and the mechanical clock (MC). In contrast to the MCs that show the astrological reference time, the time shown by the RBCs delay because it depends on cellular activity. The maximum and the expected life span of the cells and/or the organisms can be therefore relied on time transformation. One of the most important factors that can affect time flow is the energy that is produced during metabolic work. Based on this observation, RBCs can be constructed following series of theoretical experiments in order to assess biological time and life span changes.

Predicting CYP2C19 Catalytic Parameters for Enantioselective Oxidations Using Artificial Neural Networks and a Chirality Code

PubMed Central

Hartman, Jessica H.; Cothren, Steven D.; Park, Sun-Ha; Yun, Chul-Ho; Darsey, Jerry A.; Miller, Grover P.

2013-01-01

Cytochromes P450 (CYP for isoforms) play a central role in biological processes especially metabolism of chiral molecules; thus, development of computational methods to predict parameters for chiral reactions is important for advancing this field. In this study, we identified the most optimal artificial neural networks using conformation-independent chirality codes to predict CYP2C19 catalytic parameters for enantioselective reactions. Optimization of the neural networks required identifying the most suitable representation of structure among a diverse array of training substrates, normalizing distribution of the corresponding catalytic parameters (kcat, Km, and kcat/Km), and determining the best topology for networks to make predictions. Among different structural descriptors, the use of partial atomic charges according to the CHelpG scheme and inclusion of hydrogens yielded the most optimal artificial neural networks. Their training also required resolution of poorly distributed output catalytic parameters using a Box-Cox transformation. End point leave-one-out cross correlations of the best neural networks revealed that predictions for individual catalytic parameters (kcat and Km) were more consistent with experimental values than those for catalytic efficiency (kcat/Km). Lastly, neural networks predicted correctly enantioselectivity and comparable catalytic parameters measured in this study for previously uncharacterized CYP2C19 substrates, R- and S-propranolol. Taken together, these seminal computational studies for CYP2C19 are the first to predict all catalytic parameters for enantioselective reactions using artificial neural networks and thus provide a foundation for expanding the prediction of cytochrome P450 reactions to chiral drugs, pollutants, and other biologically active compounds. PMID:23673224

Non-target toxicity of synthetic insecticides on the biological performance and population growth of Bracon hebetor Say.

PubMed

Muslim, Mohammad; Ansari, M Shafiq; Hasan, Fazil

2018-05-24

Bracon hebetor Say (Hymenoptera: Braconidae) is an important biological control agent of various species of order Lepidoptera and extensively used in biological control program worldwide. Present study evaluated the lethal and sublethal effects of insecticides on B. hebetor using demographic and population growth parameters. Doses of all the tested insecticides were within a maximum range of their recommended field dosages and adults were treated using residual glass vials method. For control experiments adults were treated with distilled water. Among the tested insecticides, the survivorship of various stages of B. hebetor was considerably prolonged on cyantraniliprole followed by chlorantraniliprole and shortest on chlorpyrifos and profenofos treated group. Total immature development time was prolonged in chlorpyrifos and profenofos treated group. Population growth parameters like intrinsic rate of natural increase (r m ), net reproductive rate (R 0 ), finite rate of increase (λ) and mean generation time (T c ) were considerably reduced in B. hebetor groups treated with chlorpyrifos and profenofos. However, B. hebetor groups treated with chlorantraniliprole and cyantraniliprole showed a little or no much difference in population growth parameters when compared with untreated group. It was also observed that chlorpyrifos and profenofos modified the sex ratio, thereby female emergence get reduced. On the basis of present findings it can be concluded that all tested insecticides caused considerable ecotoxic effects on B. hebetor compared to control. However, comparisons among the tested insecticides on the basis of IOBC criteria showed that chlorantraniliprol and cyntraniliprol was less toxic as compared to other insecticides tested on this biological control agent.

Research of human kidney thermal properties for the purpose of cryosurgery

NASA Astrophysics Data System (ADS)

Ponomarev, D. E.; Pushkarev, A. V.

2017-11-01

Calculation of the heat transfer is required to correctly predict the results of cryosurgery, cryopreservation, etc. One of the important initial parameters are the thermophysical properties of biological tissues. In the present study, the values of the heat capacity, cryoscopic temperature and enthalpy of the phase transition of the kidney samples in vitro were obtained by differential scanning calorimetry.

Extension of TOPAS for the simulation of proton radiation effects considering molecular and cellular endpoints

NASA Astrophysics Data System (ADS)

Polster, Lisa; Schuemann, Jan; Rinaldi, Ilaria; Burigo, Lucas; McNamara, Aimee L.; Stewart, Robert D.; Attili, Andrea; Carlson, David J.; Sato, Tatsuhiko; Ramos Méndez, José; Faddegon, Bruce; Perl, Joseph; Paganetti, Harald

2015-07-01

The aim of this work is to extend a widely used proton Monte Carlo tool, TOPAS, towards the modeling of relative biological effect (RBE) distributions in experimental arrangements as well as patients. TOPAS provides a software core which users configure by writing parameter files to, for instance, define application specific geometries and scoring conditions. Expert users may further extend TOPAS scoring capabilities by plugging in their own additional C++ code. This structure was utilized for the implementation of eight biophysical models suited to calculate proton RBE. As far as physics parameters are concerned, four of these models are based on the proton linear energy transfer, while the others are based on DNA double strand break induction and the frequency-mean specific energy, lineal energy, or delta electron generated track structure. The biological input parameters for all models are typically inferred from fits of the models to radiobiological experiments. The model structures have been implemented in a coherent way within the TOPAS architecture. Their performance was validated against measured experimental data on proton RBE in a spread-out Bragg peak using V79 Chinese Hamster cells. This work is an important step in bringing biologically optimized treatment planning for proton therapy closer to the clinical practice as it will allow researchers to refine and compare pre-defined as well as user-defined models.

Extension of TOPAS for the simulation of proton radiation effects considering molecular and cellular endpoints

PubMed Central

Polster, Lisa; Schuemann, Jan; Rinaldi, Ilaria; Burigo, Lucas; McNamara, Aimee L.; Stewart, Robert D.; Attili, Andrea; Carlson, David J.; Sato, Tatsuhiko; Méndez, José Ramos; Faddegon, Bruce; Perl, Joseph; Paganetti, Harald

2015-01-01

The aim of this work is to extend a widely used proton Monte Carlo tool, TOPAS, towards the modeling of relative biological effect (RBE) distributions in experimental arrangements as well as patients. TOPAS provides a software core which users configure by writing parameter files to, for instance, define application specific geometries and scoring conditions. Expert users may further extend TOPAS scoring capabilities by plugging in their own additional C++ code. This structure was utilized for the implementation of eight biophysical models suited to calculate proton RBE. As far as physics parameters are concerned, four of these models are based on the proton linear energy transfer (LET), while the others are based on DNA Double Strand Break (DSB) induction and the frequency-mean specific energy, lineal energy, or delta electron generated track structure. The biological input parameters for all models are typically inferred from fits of the models to radiobiological experiments. The model structures have been implemented in a coherent way within the TOPAS architecture. Their performance was validated against measured experimental data on proton RBE in a spread-out Bragg peak using V79 Chinese Hamster cells. This work is an important step in bringing biologically optimized treatment planning for proton therapy closer to the clinical practice as it will allow researchers to refine and compare pre-defined as well as user-defined models. PMID:26061666

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

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.

Cell phone radiation exposure on brain and associated biological systems.

PubMed

Kesari, Kavindra Kumar; Siddiqui, Mohd Haris; Meena, Ramovatar; Verma, H N; Kumar, Shivendra

2013-03-01

Wireless technologies are ubiquitous today and the mobile phones are one of the prodigious output of this technology. Although the familiarization and dependency of mobile phones is growing at an alarming pace, the biological effects due to the exposure of radiations have become a subject of intense debate. The present evidence on mobile phone radiation exposure is based on scientific research and public policy initiative to give an overview of what is known of biological effects that occur at radiofrequency (RF)/ electromagnetic fields (EMFs) exposure. The conflict in conclusions is mainly because of difficulty in controlling the affecting parameters. Biological effects are dependent not only on the distance and size of the object (with respect to the object) but also on the environmental parameters. Health endpoints reported to be associated with RF include childhood leukemia, brain tumors, genotoxic effects, neurological effects and neurodegenerative diseases, immune system deregulation, allergic and inflammatory responses, infertility and some cardiovascular effects. Most of the reports conclude a reasonable suspicion of mobile phone risk that exists based on clear evidence of bio-effects which with prolonged exposures may reasonably be presumed to result in health impacts. The present study summarizes the public issue based on mobile phone radiation exposure and their biological effects. This review concludes that the regular and long term use of microwave devices (mobile phone, microwave oven) at domestic level can have negative impact upon biological system especially on brain. It also suggests that increased reactive oxygen species (ROS) play an important role by enhancing the effect of microwave radiations which may cause neurodegenerative diseases.

A case study of tuning MapReduce for efficient Bioinformatics in the cloud

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

Shi, Lizhen; Wang, Zhong; Yu, Weikuan

The combination of the Hadoop MapReduce programming model and cloud computing allows biological scientists to analyze next-generation sequencing (NGS) data in a timely and cost-effective manner. Cloud computing platforms remove the burden of IT facility procurement and management from end users and provide ease of access to Hadoop clusters. However, biological scientists are still expected to choose appropriate Hadoop parameters for running their jobs. More importantly, the available Hadoop tuning guidelines are either obsolete or too general to capture the particular characteristics of bioinformatics applications. In this paper, we aim to minimize the cloud computing cost spent on bioinformatics datamore » analysis by optimizing the extracted significant Hadoop parameters. When using MapReduce-based bioinformatics tools in the cloud, the default settings often lead to resource underutilization and wasteful expenses. We choose k-mer counting, a representative application used in a large number of NGS data analysis tools, as our study case. Experimental results show that, with the fine-tuned parameters, we achieve a total of 4× speedup compared with the original performance (using the default settings). Finally, this paper presents an exemplary case for tuning MapReduce-based bioinformatics applications in the cloud, and documents the key parameters that could lead to significant performance benefits.« less

A combined approach of physicochemical and biological methods for the characterization of petroleum hydrocarbon-contaminated soil.

PubMed

Masakorala, Kanaji; Yao, Jun; Chandankere, Radhika; Liu, Haijun; Liu, Wenjuan; Cai, Minmin; Choi, Martin M F

2014-01-01

Main physicochemical and microbiological parameters of collected petroleum-contaminated soils with different degrees of contamination from DaGang oil field (southeast of Tianjin, northeast China) were comparatively analyzed in order to assess the influence of petroleum contaminants on the physicochemical and microbiological properties of soil. An integration of microcalorimetric technique with urease enzyme analysis was used with the aim to assess a general status of soil metabolism and the potential availability of nitrogen nutrient in soils stressed by petroleum-derived contaminants. The total petroleum hydrocarbon (TPH) content of contaminated soils varied from 752.3 to 29,114 mg kg(−1). Although the studied physicochemical and biological parameters showed variations dependent on TPH content, the correlation matrix showed also highly significant correlation coefficients among parameters, suggesting their utility in describing a complex matrix such as soil even in the presence of a high level of contaminants. The microcalorimetric measures gave evidence of microbial adaptation under highest TPH concentration; this would help in assessing the potential of a polluted soil to promote self-degradation of oil-derived hydrocarbon under natural or assisted remediation. The results highlighted the importance of the application of combined approach in the study of those parameters driving the soil amelioration and bioremediation.

Ionic scattering factors of atoms that compose biological molecules

PubMed Central

Matsuoka, Rei; Yamashita, Yoshiki; Yamane, Tsutomu; Kidera, Akinori; Maki-Yonekura, Saori

2018-01-01

Ionic scattering factors of atoms that compose biological molecules have been computed by the multi-configuration Dirac–Fock method. These ions are chemically unstable and their scattering factors had not been reported except for O−. Yet these factors are required for the estimation of partial charges in protein molecules and nucleic acids. The electron scattering factors of these ions are particularly important as the electron scattering curves vary considerably between neutral and charged atoms in the spatial-resolution range explored in structural biology. The calculated X-ray and electron scattering factors have then been parameterized for the major scattering curve models used in X-ray and electron protein crystallography and single-particle cryo-EM. The X-ray and electron scattering factors and the fitting parameters are presented for future reference. PMID:29755750

Size, weight and position: ion mobility spectrometry and imaging MS combined.

PubMed

Kiss, András; Heeren, Ron M A

2011-03-01

Size, weight and position are three of the most important parameters that describe a molecule in a biological system. Ion mobility spectrometry is capable of separating molecules on the basis of their size or shape, whereas imaging mass spectrometry is an effective tool to measure the molecular weight and spatial distribution of molecules. Recent developments in both fields enabled the combination of the two technologies. As a result, ion-mobility-based imaging mass spectrometry is gaining more and more popularity as a (bio-)analytical tool enabling the determination of the size, weight and position of several molecules simultaneously on biological surfaces. This paper reviews the evolution of ion-mobility-based imaging mass spectrometry and provides examples of its application in analytical studies of biological surfaces.

The pediatric sepsis biomarker risk model: potential implications for sepsis therapy and biology.

PubMed

Alder, Matthew N; Lindsell, Christopher J; Wong, Hector R

2014-07-01

Sepsis remains a major cause of morbidity and mortality in adult and pediatric intensive care units. Heterogeneity of demographics, comorbidities, biological mechanisms, and severity of illness leads to difficulty in determining which patients are at highest risk of mortality. Determining mortality risk is important for weighing the potential benefits of more aggressive interventions and for deciding whom to enroll in clinical trials. Biomarkers can be used to parse patients into different risk categories and can outperform current methods of patient risk stratification based on physiologic parameters. Here we review the Pediatric Sepsis Biomarker Risk Model that has also been modified and applied to estimate mortality risk in adult patients. We compare the two models and speculate on the biological implications of the biomarkers in patients with sepsis.

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/.

Estimation of key parameters in adaptive neuron model according to firing patterns based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yuan, Chunhua; Wang, Jiang; Yi, Guosheng

2017-03-01

Estimation of ion channel parameters is crucial to spike initiation of neurons. The biophysical neuron models have numerous ion channel parameters, but only a few of them play key roles in the firing patterns of the models. So we choose three parameters featuring the adaptation in the Ermentrout neuron model to be estimated. However, the traditional particle swarm optimization (PSO) algorithm is still easy to fall into local optimum and has the premature convergence phenomenon in the study of some problems. In this paper, we propose an improved method that uses a concave function and dynamic logistic chaotic mapping mixed to adjust the inertia weights of the fitness value, effectively improve the global convergence ability of the algorithm. The perfect predicting firing trajectories of the rebuilt model using the estimated parameters prove that only estimating a few important ion channel parameters can establish the model well and the proposed algorithm is effective. Estimations using two classic PSO algorithms are also compared to the improved PSO to verify that the algorithm proposed in this paper can avoid local optimum and quickly converge to the optimal value. The results provide important theoretical foundations for building biologically realistic neuron models.

The fundamentals of biotribology and its application to spine arthroplasty

PubMed Central

Harper, Megan L.; Dooris, Andrew; Paré, Philippe E.

2009-01-01

The biological effect of wear of articulating surfaces is a continued concern with large joint replacements and, likewise, of interest for total disc replacements. There are a number of important biotribological testing parameters that can greatly affect the outcome of a wear study in addition to the implant design and material selection. The current ASTM and ISO wear testing standards/guides for spine arthroplasty leave many choices as testing parameters. These factors include but are not limited to the sequence of kinematics and load, phasing, type of lubricant, and specimen preparation (sterilization and artificial aging). The spinal community should critically assess wear studies and be cognizant of the influence of the selected parameters on the test results. PMID:25802638

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

NASA Astrophysics Data System (ADS)

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

PubMed

Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

2017-01-04

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

PubMed Central

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O’Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike. PMID:28051123

Hidden Markov models of biological primary sequence information.

PubMed Central

Baldi, P; Chauvin, Y; Hunkapiller, T; McClure, M A

1994-01-01

Hidden Markov model (HMM) techniques are used to model families of biological sequences. A smooth and convergent algorithm is introduced to iteratively adapt the transition and emission parameters of the models from the examples in a given family. The HMM approach is applied to three protein families: globins, immunoglobulins, and kinases. In all cases, the models derived capture the important statistical characteristics of the family and can be used for a number of tasks, including multiple alignments, motif detection, and classification. For K sequences of average length N, this approach yields an effective multiple-alignment algorithm which requires O(KN2) operations, linear in the number of sequences. PMID:8302831

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.

The fractured landscape of RNA-seq alignment: the default in our STARs.

PubMed

Ballouz, Sara; Dobin, Alexander; Gingeras, Thomas R; Gillis, Jesse

2018-06-01

Many tools are available for RNA-seq alignment and expression quantification, with comparative value being hard to establish. Benchmarking assessments often highlight methods' good performance, but are focused on either model data or fail to explain variation in performance. This leaves us to ask, what is the most meaningful way to assess different alignment choices? And importantly, where is there room for progress? In this work, we explore the answers to these two questions by performing an exhaustive assessment of the STAR aligner. We assess STAR's performance across a range of alignment parameters using common metrics, and then on biologically focused tasks. We find technical metrics such as fraction mapping or expression profile correlation to be uninformative, capturing properties unlikely to have any role in biological discovery. Surprisingly, we find that changes in alignment parameters within a wide range have little impact on both technical and biological performance. Yet, when performance finally does break, it happens in difficult regions, such as X-Y paralogs and MHC genes. We believe improved reporting by developers will help establish where results are likely to be robust or fragile, providing a better baseline to establish where methodological progress can still occur.

A monoclonal antibody based elisa for quantitation of human leukaemia inhibitory factor.

PubMed

Taupin, J L; Gualde, N; Moreau, J F

1997-02-01

The authors report on the development of a new sandwich enzyme-linked immunoabsorbent assay (ELISA) for the quantitation of the human cytokine leukaemia inhibitory factor/human interleukin for DA cells (LIF/HILDA) with high accuracy and sensitivity (23 pg/ml), in less than 5 h and in various biological fluids. The antibodies used in this assay were raised against recombinant glycosylated LIF expressed in vivo following inoculation of recombinant vaccinia viruses, and screened with the biologically active cytokine in a flow cytometry assay using cells expressing a membrane-bound form of LIF. Furthermore, this home-made assay was compared with two commercially available ELISA kits. The results led to the conclusion that these three assays are far from being equivalent between each other, in terms of sensitivity towards non-glycosylated vs glycosylated LIF. Two major parameters must be incriminated: the glycosylation status of the LIF molecule used as the calibrator, and the binding characteristics of the monoclonal antibodies used to set up these assays toward LIF derived from Escherichia coli or from eukaryotic cells. This points out the importance of these parameters for the design of ELISAs meant for the quantitation of glycosylated cytokines in biological fluids.

Neural network models for biological waste-gas treatment systems.

PubMed

Rene, Eldon R; Estefanía López, M; Veiga, María C; Kennes, Christian

2011-12-15

This paper outlines the procedure for developing artificial neural network (ANN) based models for three bioreactor configurations used for waste-gas treatment. The three bioreactor configurations chosen for this modelling work were: biofilter (BF), continuous stirred tank bioreactor (CSTB) and monolith bioreactor (MB). Using styrene as the model pollutant, this paper also serves as a general database of information pertaining to the bioreactor operation and important factors affecting gas-phase styrene removal in these biological systems. Biological waste-gas treatment systems are considered to be both advantageous and economically effective in treating a stream of polluted air containing low to moderate concentrations of the target contaminant, over a rather wide range of gas-flow rates. The bioreactors were inoculated with the fungus Sporothrix variecibatus, and their performances were evaluated at different empty bed residence times (EBRT), and at different inlet styrene concentrations (C(i)). The experimental data from these bioreactors were modelled to predict the bioreactors performance in terms of their removal efficiency (RE, %), by adequate training and testing of a three-layered back propagation neural network (input layer-hidden layer-output layer). Two models (BIOF1 and BIOF2) were developed for the BF with different combinations of easily measurable BF parameters as the inputs, that is concentration (gm(-3)), unit flow (h(-1)) and pressure drop (cm of H(2)O). The model developed for the CSTB used two inputs (concentration and unit flow), while the model for the MB had three inputs (concentration, G/L (gas/liquid) ratio, and pressure drop). Sensitivity analysis in the form of absolute average sensitivity (AAS) was performed for all the developed ANN models to ascertain the importance of the different input parameters, and to assess their direct effect on the bioreactors performance. The performance of the models was estimated by the regression coefficient values (R(2)) for the test data set. The results obtained from this modelling work can be useful for obtaining important relationships between different bioreactor parameters and for estimating their safe operating regimes. Copyright © 2011. Published by Elsevier B.V.

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.

Shielding in biology and biophysics: Methodology, dosimetry, interpretation

NASA Astrophysics Data System (ADS)

Vladimirsky, B. M.; Temuryants, N. A.

2016-12-01

An interdisciplinary review of the publications on the shielding of organisms by different materials is presented. The authors show that some discrepancies between the results of different researchers might be attributed to methodological reasons, including purely biological (neglect of rhythms) and technical (specific features of the design or material of the screen) ones. In some cases, an important factor is the instability of control indices due to the variations in space weather. According to the modern concept of biological exposure to microdoses, any isolation of a biological object by any material necessarily leads to several simultaneous changes in environmental parameters, and this undermines the principle of "all other conditions being equal" in the classical differential scheme of an experiment. The shielding effects of water solution are universally recognized and their influence is to be observed for all organisms. Data on the exposure of living organisms to weak combined magnetic fields and on the influence of space weather enabled the development of theoretical models generally explaining the effect of shielding for bioorganisms. Ferromagnetic shielding results in changes of both the static magnetic field and the field of radio waves within the area protected by the screen. When screens are nonmagnetic, changes are due to the isolation from the radio waves. In both cases, some contribution to the fluctuations of measured parameters can be made by variations in the level of ionizing radiation.

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

Recommendations for the validation of cell-based assays used for the detection of neutralizing antibody immune responses elicited against biological therapeutics.

PubMed

Gupta, Shalini; Devanarayan, Viswanath; Finco, Deborah; Gunn, George R; Kirshner, Susan; Richards, Susan; Rup, Bonita; Song, An; Subramanyam, Meena

2011-07-15

The administration of biological therapeutics may result in the development of anti-drug antibodies (ADAs) in treated subjects. In some cases, ADA responses may result in the loss of therapeutic efficacy due to the formation of neutralizing ADAs (NAbs). An important characteristic of anti-drug NAbs is their direct inhibitory effect on the pharmacological activity of the therapeutic. Neutralizing antibody responses are of particular concern for biologic products with an endogenous homolog whose activity can be potentially dampened or completely inhibited by the NAbs leading to an autoimmune-type deficiency syndrome. Therefore, it is important that ADAs are detected and characterized appropriately using sensitive and reliable methods. The design, development and optimization of cell-based assays used for detection of NAbs have been published previously by Gupta et al. 2007 [1]. This paper provides recommendations on best practices for the validation of cell-based NAb assay and suggested validation parameters based on the experience of the authors. Copyright © 2011 Elsevier B.V. All rights reserved.

Current advancement in radiation therapy for uterine cervical cancer.

PubMed

Nakano, Takashi; Ohno, Tatsuya; Ishikawa, Hitoshi; Suzuki, Yoshiyuki; Takahashi, Takeo

2010-01-01

Radiation therapy is one of the effective curative treatments for uterine cervical cancer. However poor clinical results for the advanced stages require further improvement of the treatment. Intensive studies on basic and clinical research have been made to improve local control, primarily important for long term survival in radiation therapy. Regarding current advancement in radiation therapy for uterine cervical cancer, the following three major subjects are pointed out; technological development to improve dose distribution by image guided radiation therapy technology, the concomitant anticancer chemotherapy with combination of radiation therapy, and radiation biological assessment of the radiation resistance of tumors. The biological factors overviewed in this article include hypoxia relating factors of HIF-1alpha, SOD, cell cycle parameters of pMI, proliferation factors of Ki67, EGFR, cerbB2, COX-2, cycle regulation proteins p53, p21, apoptosis regulation proteins Bcl2 and Bax and so on. Especially, the variety of these radiation biological factors is important for the selection of an effective treatment method for each patient to maximize the treatment benefit.

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

Distinguishing Functional DNA Words; A Method for Measuring Clustering Levels

NASA Astrophysics Data System (ADS)

Moghaddasi, Hanieh; Khalifeh, Khosrow; Darooneh, Amir Hossein

2017-01-01

Functional DNA sub-sequences and genome elements are spatially clustered through the genome just as keywords in literary texts. Therefore, some of the methods for ranking words in texts can also be used to compare different DNA sub-sequences. In analogy with the literary texts, here we claim that the distribution of distances between the successive sub-sequences (words) is q-exponential which is the distribution function in non-extensive statistical mechanics. Thus the q-parameter can be used as a measure of words clustering levels. Here, we analyzed the distribution of distances between consecutive occurrences of 16 possible dinucleotides in human chromosomes to obtain their corresponding q-parameters. We found that CG as a biologically important two-letter word concerning its methylation, has the highest clustering level. This finding shows the predicting ability of the method in biology. We also proposed that chromosome 18 with the largest value of q-parameter for promoters of genes is more sensitive to dietary and lifestyle. We extended our study to compare the genome of some selected organisms and concluded that the clustering level of CGs increases in higher evolutionary organisms compared to lower ones.

Complexity of generic biochemical circuits: topology versus strength of interactions.

PubMed

Tikhonov, Mikhail; Bialek, William

2016-12-06

The historical focus on network topology as a determinant of biological function is still largely maintained today, illustrated by the rise of structure-only approaches to network analysis. However, biochemical circuits and genetic regulatory networks are defined both by their topology and by a multitude of continuously adjustable parameters, such as the strength of interactions between nodes, also recognized as important. Here we present a class of simple perceptron-based Boolean models within which comparing the relative importance of topology versus interaction strengths becomes a quantitatively well-posed problem. We quantify the intuition that for generic networks, optimization of interaction strengths is a crucial ingredient of achieving high complexity, defined here as the number of fixed points the network can accommodate. We propose a new methodology for characterizing the relative role of parameter optimization for topologies of a given class.

Mathematical models of radiation action on living cells: From the target theory to the modern approaches. A historical and critical review.

PubMed

Bodgi, Larry; Canet, Aurélien; Pujo-Menjouet, Laurent; Lesne, Annick; Victor, Jean-Marc; Foray, Nicolas

2016-04-07

Cell survival is conventionally defined as the capability of irradiated cells to produce colonies. It is quantified by the clonogenic assays that consist in determining the number of colonies resulting from a known number of irradiated cells. Several mathematical models were proposed to describe the survival curves, notably from the target theory. The Linear-Quadratic (LQ) model, which is to date the most frequently used model in radiobiology and radiotherapy, dominates all the other models by its robustness and simplicity. Its usefulness is particularly important because the ratio of the values of the adjustable parameters, α and β, on which it is based, predicts the occurrence of post-irradiation tissue reactions. However, the biological interpretation of these parameters is still unknown. Throughout this review, we revisit and discuss historically, mathematically and biologically, the different models of the radiation action by providing clues for resolving the enigma of the LQ model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Noise-aided computation within a synthetic gene network through morphable and robust logic gates

NASA Astrophysics Data System (ADS)

Dari, Anna; Kia, Behnam; Wang, Xiao; Bulsara, Adi R.; Ditto, William

2011-04-01

An important goal for synthetic biology is to build robust and tunable genetic regulatory networks that are capable of performing assigned operations, usually in the presence of noise. In this work, a synthetic gene network derived from the bacteriophage λ underpins a reconfigurable logic gate wherein we exploit noise and nonlinearity through the application of the logical stochastic resonance paradigm. This biological logic gate can emulate or “morph” the AND and OR operations through varying internal system parameters in a noisy background. Such genetic circuits can afford intriguing possibilities in the realization of engineered genetic networks in which the actual function of the gate can be changed after the network has been built, via an external control parameter. In this article, the full system characterization is reported, with the logic gate performance studied in the presence of external and internal noise. The robustness of the gate, to noise, is studied and illustrated through numerical simulations.

Role of access to parks and markets with anthropometric measurements, biological markers, and a healthy lifestyle.

PubMed

Mena, Carlos; Fuentes, Eduardo; Ormazábal, Yony; Palomo-Vélez, Gonzalo; Palomo, Iván

2015-01-01

This study examined the association between access to urban green spaces and markets with anthropometric measurements, biological markers, sociodemographic, and healthy lifestyle. Geographic information systems were used to establish a correlation between environmental features and cardiovascular risk parameters. A total number of 832 (age range 18-74 years) individuals were selected for this study. Body mass index was significantly and positively related to the distance to parks (ρ = 0.079, p < 0.05), but negatively related to the distance to markets (ρ = -0.125, p < 0.05). In addition, waist circumference was similar and positively related to distance to parks (ρ = 0.097, p < 0.05) and negatively related to distance to markets (ρ = -0.092, p < 0.05). With respect to biochemical parameters, when there was an increase in the distance to markets, high-density lipoprotein cholesterol increased and glycemia decreased. The results of this study suggest the importance of the role of environmental factors such as parks and markets in the development of cardiovascular risk.

Effects of wastewater constituents and operational conditions on the composition and dynamics of anodic microbial communities in bioelectrochemical systems.

PubMed

Kokko, Marika; Epple, Stefanie; Gescher, Johannes; Kerzenmacher, Sven

2018-06-01

Over the last decade, there has been an ever-growing interest in bioelectrochemical systems (BES) as a sustainable technology enabling simultaneous wastewater treatment and biological production of, e.g. electricity, hydrogen, and further commodities. A key component of any BES degrading organic matter is the anode where electric current is biologically generated from the oxidation of organic compounds. The performance of BES depends on the interactions of the anodic microbial communities. To optimize the operational parameters and process design of BES a better comprehension of the microbial community dynamics and interactions at the anode is required. This paper reviews the abundance of different microorganisms in anodic biofilms and discusses their roles and possible side reactions with respect to their implications on the performance of BES utilizing wastewaters. The most important operational parameters affecting anodic microbial communities grown with wastewaters are highlighted and guidelines for controlling the composition of microbial communities are given. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Biomolecular Crystallization Database Version 4: expanded content and new features.

PubMed

Tung, Michael; Gallagher, D Travis

2009-01-01

The Biological Macromolecular Crystallization Database (BMCD) has been a publicly available resource since 1988, providing a curated archive of information on crystal growth for proteins and other biological macromolecules. The BMCD content has recently been expanded to include 14 372 crystal entries. The resource continues to be freely available at http://xpdb.nist.gov:8060/BMCD4. In addition, the software has been adapted to support the Java-based Lucene query language, enabling detailed searching over specific parameters, and explicit search of parameter ranges is offered for five numeric variables. Extensive tools have been developed for import and handling of data from the RCSB Protein Data Bank. The updated BMCD is called version 4.02 or BMCD4. BMCD4 entries have been expanded to include macromolecule sequence, enabling more elaborate analysis of relations among protein properties, crystal-growth conditions and the geometric and diffraction properties of the crystals. The BMCD version 4.02 contains greatly expanded content and enhanced search capabilities to facilitate scientific analysis and design of crystal-growth strategies.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty.

PubMed

Mdluli, Thembi; Buzzard, Gregery T; Rundell, Ann E

2015-09-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm's scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty

PubMed Central

Mdluli, Thembi; Buzzard, Gregery T.; Rundell, Ann E.

2015-01-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm’s scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements. PMID:26379275

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

Radiotherapy Dose Fractionation under Parameter Uncertainty

NASA Astrophysics Data System (ADS)

Davison, Matt; Kim, Daero; Keller, Harald

2011-11-01

In radiotherapy, radiation is directed to damage a tumor while avoiding surrounding healthy tissue. Tradeoffs ensue because dose cannot be exactly shaped to the tumor. It is particularly important to ensure that sensitive biological structures near the tumor are not damaged more than a certain amount. Biological tissue is known to have a nonlinear response to incident radiation. The linear quadratic dose response model, which requires the specification of two clinically and experimentally observed response coefficients, is commonly used to model this effect. This model yields an optimization problem giving two different types of optimal dose sequences (fractionation schedules). Which fractionation schedule is preferred depends on the response coefficients. These coefficients are uncertainly known and may differ from patient to patient. Because of this not only the expected outcomes but also the uncertainty around these outcomes are important, and it might not be prudent to select the strategy with the best expected outcome.

Particle bombardment - mediated gene transfer and GFP transient expression in Seteria viridis.

PubMed

Mookkan, Muruganantham

2018-04-03

Setaria viridis is one of the most important model grasses in studying monocot plant biology. Transient gene expression study is a very important tool in plant biotechnology, functional genomics, and CRISPR-Cas9 genome editing technology via particle bombardment. In this study, a particle bombardment-mediated protocol was developed to introduce DNA into Setaria viridis in vitro leaf explants. In addition, physical and biological parameters, such as helium pressure, distance from stopping screen to the target tissues, DNA concentration, and number of bombardments, were tested and optimized. Optimum concentration of transient GFP expression was achieved using 1.5 ug plasmid DNA with 0.6 mm gold particles and 6 cm bombardment distance, using 1,100 psi. Doubling the bombardment instances provides the maximum number of foci of transient GFP expression. This simple protocol will be helpful for genomics studies in the S. viridis monocot model.

Prediction of interface residue based on the features of residue interaction network.

PubMed

Jiao, Xiong; Ranganathan, Shoba

2017-11-07

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Saliva and dental erosion

PubMed Central

BUZALAF, Marília Afonso Rabelo; HANNAS, Angélicas Reis; KATO, Melissa Thiemi

2012-01-01

Dental erosion is a multifactorial condition. The consideration of chemical, biological and behavioral factors is fundamental for its prevention and therapy. Among the biological factors, saliva is one of the most important parameters in the protection against erosive wear. Objective This review discusses the role of salivary factors on the development of dental erosion. Material and Methods A search was undertaken on MEDLINE website for papers from 1969 to 2010. The keywords used in the research were "saliva", "acquired pellicle", "salivary flow", "salivary buffering capacity" and "dental erosion". Inclusion of studies, data extraction and quality assessment were undertaken independently and in duplicate by two members of the review team. Disagreements were solved by discussion and consensus or by a third party. Results Several characteristics and properties of saliva play an important role in dental erosion. Salivary clearance gradually eliminates the acids through swallowing and saliva presents buffering capacity causing neutralization and buffering of dietary acids. Salivary flow allows dilution of the acids. In addition, saliva is supersaturated with respect to tooth mineral, providing calcium, phosphate and fluoride necessary for remineralization after an erosive challenge. Furthermore, many proteins present in saliva and acquired pellicle play an important role in dental erosion. Conclusions Saliva is the most important biological factor affecting the progression of dental erosion. Knowledge of its components and properties involved in this protective role can drive the development of preventive measures targeting to enhance its known beneficial effects. PMID:23138733

Saliva and dental erosion.

PubMed

Buzalaf, Marília Afonso Rabelo; Hannas, Angélicas Reis; Kato, Melissa Thiemi

2012-01-01

Dental erosion is a multifactorial condition. The consideration of chemical, biological and behavioral factors is fundamental for its prevention and therapy. Among the biological factors, saliva is one of the most important parameters in the protection against erosive wear. This review discusses the role of salivary factors on the development of dental erosion. A search was undertaken on MeDLINe website for papers from 1969 to 2010. The keywords used in the research were "saliva", "acquired pellicle", "salivary flow", "salivary buffering capacity" and "dental erosion". Inclusion of studies, data extraction and quality assessment were undertaken independently and in duplicate by two members of the review team. Disagreements were solved by discussion and consensus or by a third party. Several characteristics and properties of saliva play an important role in dental erosion. Salivary clearance gradually eliminates the acids through swallowing and saliva presents buffering capacity causing neutralization and buffering of dietary acids. Salivary flow allows dilution of the acids. In addition, saliva is supersaturated with respect to tooth mineral, providing calcium, phosphate and fluoride necessary for remineralization after an erosive challenge. Furthermore, many proteins present in saliva and acquired pellicle play an important role in dental erosion. Saliva is the most important biological factor affecting the progression of dental erosion. Knowledge of its components and properties involved in this protective role can drive the development of preventive measures targeting to enhance its known beneficial effects.

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.

Influence of cadmium on life-history characteristics of Folsomia candida (Willem) in an artificial soil substrate

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

Crommentuijn, T.; Brils, J.; Van Straalen, N.M.

1993-10-01

To understand the consequences of soil pollution on higher levels of biological organization, the chain of effects of cadmium on several interrelated responses was studied in a chronic toxicity experiment using the collembolan species Folsomia candida (Willem) in an artificial soil. The individual parameters survival, growth, and number of offspring were determined after different time intervals up to 9 weeks. The accumulation of cadmium in springtails and the population increase during the experimental period were also determined. By combining all the mentioned parameters and their development in time, a detailed picture of the action of cadmium on F. candida wasmore » obtained. In order of decreasing sensitivity the EC50 values for Von Bertalanffy growth, number of offspring, population increase, and survival were 256, > 326, 475, and 850 micrograms Cd/g dry soil, respectively. The ultimate LC50 value and also the equilibrium body burden were reached after about 20 days. Reproduction started later because of retarded growth, but was not affected directly and eventually reached the control level. The results are discussed in light of the seemingly contradictory ideas of Halbach (1984, Hydrobiologia 109, 79-96) and Meyer et al. (1987, Environ. Toxicol. Chem. 6, 115-126) about the sensitivity of individual and population parameters. It appears to be very important to know how individual parameters develop in time so that the most sensitive parameter and the consequences for higher levels of biological organization can be determined.« less

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

Chapter A6. Section 6.1. Temperature

USGS Publications Warehouse

Revised by Wilde, Franceska D.

2006-01-01

Accurate temperature measurements are required for accurate determinations of important environmental parameters such as pH, specific electrical conductance, and dissolved oxygen, and to the determination of chemical reaction rates and equilibria, biological activity, and physical fluid properties. This section of the National Field Manual (NFM) describes U.S. Geological Survey (USGS) guidance and protocols for measurement of temperature in air, ground water, and surface water and calibration of the equipment used.

Growth-rate-dependent dynamics of a bacterial genetic oscillator

NASA Astrophysics Data System (ADS)

Osella, Matteo; Lagomarsino, Marco Cosentino

2013-01-01

Gene networks exhibiting oscillatory dynamics are widespread in biology. The minimal regulatory designs giving rise to oscillations have been implemented synthetically and studied by mathematical modeling. However, most of the available analyses generally neglect the coupling of regulatory circuits with the cellular “chassis” in which the circuits are embedded. For example, the intracellular macromolecular composition of fast-growing bacteria changes with growth rate. As a consequence, important parameters of gene expression, such as ribosome concentration or cell volume, are growth-rate dependent, ultimately coupling the dynamics of genetic circuits with cell physiology. This work addresses the effects of growth rate on the dynamics of a paradigmatic example of genetic oscillator, the repressilator. Making use of empirical growth-rate dependencies of parameters in bacteria, we show that the repressilator dynamics can switch between oscillations and convergence to a fixed point depending on the cellular state of growth, and thus on the nutrients it is fed. The physical support of the circuit (type of plasmid or gene positions on the chromosome) also plays an important role in determining the oscillation stability and the growth-rate dependence of period and amplitude. This analysis has potential application in the field of synthetic biology, and suggests that the coupling between endogenous genetic oscillators and cell physiology can have substantial consequences for their functionality.

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

Hematology and biochemistry reference intervals for Ontario commercial nursing pigs close to the time of weaning

PubMed Central

Perri, Amanda M.; O’Sullivan, Terri L.; Harding, John C.S.; Wood, R. Darren; Friendship, Robert M.

2017-01-01

The evaluation of pig hematology and biochemistry parameters is rarely done largely due to the costs associated with laboratory testing and labor, and the limited availability of reference intervals needed for interpretation. Within-herd and between-herd biological variation of these values also make it difficult to establish reference intervals. Regardless, baseline reference intervals are important to aid veterinarians in the interpretation of blood parameters for the diagnosis and treatment of diseased swine. The objective of this research was to provide reference intervals for hematology and biochemistry parameters of 3-week-old commercial nursing piglets in Ontario. A total of 1032 pigs lacking clinical signs of disease from 20 swine farms were sampled for hematology and iron panel evaluation, with biochemistry analysis performed on a subset of 189 randomly selected pigs. The 95% reference interval, mean, median, range, and 90% confidence intervals were calculated for each parameter. PMID:28373729

Determinants Affecting Physical Activity Levels In Animal Models

NASA Technical Reports Server (NTRS)

Tou, Janet C. L.; Wade, Charles E.; Dalton, Bonnie P. (Technical Monitor)

2001-01-01

Weight control is dependent on energy balance. Reduced energy expenditure (EE) associated with decreased physical activity is suggested to be a major underlying cause in the increasing prevalence of weight gain and obesity. Therefore, a better understanding of the biological determinants involved in the regulation of physical activity is essential. To facilitate interpretation in humans, it is helpful to consider the evidence from animal studies. This review focuses on animal studies examining the biological determinants influencing activity and potential implications to human. It appears that physical activity is influenced by a number of parameters. However, regardless of the parameter involved, body weight appears to play all underlying role in the regulation of activity. Furthermore, the regulation of activity associated with body weight appears to occur only after the animal achieves a critical weight. This suggests that activity levels are a consequence rather than a contributor to weight control. However, the existence of an inverse weight-activity relationship remains inconclusive. Confounding the results are the multi-factorial nature of physical activity and the lack of appropriate measuring devices. Furthermore, many determinants of body weight are closely interlocked making it difficult to determine whether a single, combination or interaction of factors is important for the regulation of activity. For example, diet-induced obesity, aging, lesions to tile ventral medial hypothalamus and genetics all produce hypoactivity. Providing a better understanding of the biological determinants involved in the regulation of activity has important implications for the development of strategies for the prevention of weight gain leading to obesity and subsequent morbidity and mortality in the human population.

Determinants affecting physical activity levels in animal models

NASA Technical Reports Server (NTRS)

Tou, Janet C L.; Wade, Charles E.

2002-01-01

Weight control is dependent on energy balance. Reduced energy expenditure (EE) associated with decreased physical activity is suggested to be a major underlying cause in the increasing prevalence of weight gain and obesity. Therefore, a better understanding of the biological determinants involved in the regulation of physical activity is essential. To facilitate interpretation in humans, it is helpful to consider the evidence from animal studies. This review focuses on animal studies examining the biological determinants influencing activity and potential implications to human. It appears that physical activity is influenced by a number of parameters. However, regardless of the parameter involved, body weight appears to play an underlying role in the regulation of activity. Furthermore, the regulation of activity associated with body weight appears to occur only after the animal achieves a critical weight. This suggests that activity levels are a consequence rather than a contributor to weight control. However, the existence of an inverse weight-activity relationship remains inconclusive. Confounding the results are the multifactorial nature of physical activity and the lack of appropriate measuring devices. Furthermore, many determinants of body weight are closely interlocked, making it difficult to determine whether a single, combination, or interaction of factors is important for the regulation of activity. For example, diet-induced obesity, aging, lesions to the ventral medial hypothalamus, and genetics all produce hypoactivity. Providing a better understanding of the biological determinants involved in the regulation of activity has important implications for the development of strategies for the prevention of weight gain leading to obesity and subsequent morbidity and mortality in the human population.

Fundamentals of cutting.

PubMed

Williams, J G; Patel, Y

2016-06-06

The process of cutting is analysed in fracture mechanics terms with a view to quantifying the various parameters involved. The model used is that of orthogonal cutting with a wedge removing a layer of material or chip. The behaviour of the chip is governed by its thickness and for large radii of curvature the chip is elastic and smooth cutting occurs. For smaller thicknesses, there is a transition, first to plastic bending and then to plastic shear for small thicknesses and smooth chips are formed. The governing parameters are tool geometry, which is principally the wedge angle, and the material properties of elastic modulus, yield stress and fracture toughness. Friction can also be important. It is demonstrated that the cutting process may be quantified via these parameters, which could be useful in the study of cutting in biology.

Near Infrared Dyes as Lifetime Solvatochromic Probes for Micropolarity Measurements of Biological Systems

PubMed Central

Berezin, Mikhail Y.; Lee, Hyeran; Akers, Walter; Achilefu, Samuel

2007-01-01

The polarity of biological mediums controls a host of physiological processes such as digestion, signaling, transportation, metabolism, and excretion. With the recent widespread use of near-infrared (NIR) fluorescent dyes for biological imaging of cells and living organisms, reporting medium polarity with these dyes would provide invaluable functional information in addition to conventional optical imaging parameters. Here, we report a new approach to determine polarities of macro- and microsystems for in vitro and potential in vivo applications using NIR polymethine molecular probes. Unlike the poor solvatochromic response of NIR dyes in solvents with diverse polarity, their fluorescence lifetimes are highly sensitive, increasing by a factor of up to 8 on moving from polar to nonpolar mediums. We also established a correlation between fluorescence lifetime and solvent orientation polarizability and developed a lifetime polarity index for determining the polarity of complex systems, including micelles and albumin binding sites. Because of the importance of medium polarity in molecular, cellular, and biochemical processes and the significance of reduced autofluorescence and deep tissue penetration of light in the NIR region, the findings reported herein represent an important advance toward using NIR molecular probes to measure the polarity of complex biological systems in vitro and in vivo. PMID:17573433

Identification of the most sensitive parameters in the activated sludge model implemented in BioWin software.

PubMed

Liwarska-Bizukojc, Ewa; Biernacki, Rafal

2010-10-01

In order to simulate biological wastewater treatment processes, data concerning wastewater and sludge composition, process kinetics and stoichiometry are required. Selection of the most sensitive parameters is an important step of model calibration. The aim of this work is to verify the predictability of the activated sludge model, which is implemented in BioWin software, and select its most influential kinetic and stoichiometric parameters with the help of sensitivity analysis approach. Two different measures of sensitivity are applied: the normalised sensitivity coefficient (S(i,j)) and the mean square sensitivity measure (delta(j)(msqr)). It occurs that 17 kinetic and stoichiometric parameters of the BioWin activated sludge (AS) model can be regarded as influential on the basis of S(i,j) calculations. Half of the influential parameters are associated with growth and decay of phosphorus accumulating organisms (PAOs). The identification of the set of the most sensitive parameters should support the users of this model and initiate the elaboration of determination procedures for the parameters, for which it has not been done yet. Copyright 2010 Elsevier Ltd. All rights reserved.

Differences on biological attributes of three populations of Meccus pallidipennis Stål (Hemiptera: Reduviidae).

PubMed

Martínez-Ibarra, José A; Nogueda-Torres, Benjamin; Salazar-Schettino, Paz M; Vences-Blanco, Mauro O; de la Torre-Álvarez, Felipe J; Montañez-Valdez, Oziel D

2014-03-01

Meccus pallidipennis is one of the most epidemiologically important vectors of Trypanosoma cruzi to reservoir hosts in nine states of Mexico. Triatomines occurring in distinct locations normally adapt to local conditions. The aim of this study was to examine the biological attributes of three populations of M. pallidipennis from areas with different environmental characteristics as a factor influencing the triatomine capacity for T. cruzi transmission. The values of biological parameters related to the life cycle, the number of blood meals to molt to next instar, fecundity and percentage of females after a biological cycle of three populations of M. pallidipennis were evaluated. A cohort of each of the three studied populations from different geographical areas of Mexico was maintained under similar laboratory conditions and then compared with each other. The life cycle was less than six months in all the studied cohorts, with differences among them. The number of blood meals to molt was lower for the cohort from Izϊcar de Matamoros. Laid eggs per day per female was lower for the cohort from Luvianos. In contrast, no important differences were recorded on the percentage of mortality, egg eclosion rate or percentages of obtained females. It was found that an important level of heterogeneity exist between the three studied populations of M. pallidipennis, apparently influenced by the remarkable differences on environmental conditions on the localities where the founders were initially collected, that emphasizes the necessity of studies on local populations of triatomines.

The relative importance of physical and biological energy in landscape evolution

NASA Astrophysics Data System (ADS)

Turowski, J. M.; Schwanghart, W.

2017-12-01

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

Using global sensitivity analysis of demographic models for ecological impact assessment.

PubMed

Aiello-Lammens, Matthew E; Akçakaya, H Resit

2017-02-01

Population viability analysis (PVA) is widely used to assess population-level impacts of environmental changes on species. When combined with sensitivity analysis, PVA yields insights into the effects of parameter and model structure uncertainty. This helps researchers prioritize efforts for further data collection so that model improvements are efficient and helps managers prioritize conservation and management actions. Usually, sensitivity is analyzed by varying one input parameter at a time and observing the influence that variation has over model outcomes. This approach does not account for interactions among parameters. Global sensitivity analysis (GSA) overcomes this limitation by varying several model inputs simultaneously. Then, regression techniques allow measuring the importance of input-parameter uncertainties. In many conservation applications, the goal of demographic modeling is to assess how different scenarios of impact or management cause changes in a population. This is challenging because the uncertainty of input-parameter values can be confounded with the effect of impacts and management actions. We developed a GSA method that separates model outcome uncertainty resulting from parameter uncertainty from that resulting from projected ecological impacts or simulated management actions, effectively separating the 2 main questions that sensitivity analysis asks. We applied this method to assess the effects of predicted sea-level rise on Snowy Plover (Charadrius nivosus). A relatively small number of replicate models (approximately 100) resulted in consistent measures of variable importance when not trying to separate the effects of ecological impacts from parameter uncertainty. However, many more replicate models (approximately 500) were required to separate these effects. These differences are important to consider when using demographic models to estimate ecological impacts of management actions. © 2016 Society for Conservation Biology.

Detecting and evaluating communities in complex human and biological networks

NASA Astrophysics Data System (ADS)

Morrison, Greg; Mahadevan, L.

2012-02-01

We develop a simple method for detecting the community structure in a network can by utilizing a measure of closeness between nodes. This approach readily leads to a method of coarse graining the network, which allows the detection of the natural hierarchy (or hierarchies) of community structure without appealing to an unknown resolution parameter. The closeness measure can also be used to evaluate the robustness of an individual node's assignment to its community (rather than evaluating only the quality of the global structure). Each of these methods in community detection and evaluation are illustrated using a variety of real world networks of either biological or sociological importance and illustrate the power and flexibility of the approach.

Differential Multiphoton Laser Scanning Microscopy

PubMed Central

Field, Jeffrey J.; Sheetz, Kraig E.; Chandler, Eric V.; Hoover, Erich E.; Young, Michael D.; Ding, Shi-you; Sylvester, Anne W.; Kleinfeld, David; Squier, Jeff A.

2016-01-01

Multifocal multiphoton microscopy (MMM) in the biological and medical sciences has become an important tool for obtaining high resolution images at video rates. While current implementations of MMM achieve very high frame rates, they are limited in their applicability to essentially those biological samples that exhibit little or no scattering. In this paper, we report on a method for MMM in which imaging detection is not necessary (single element point detection is implemented), and is therefore fully compatible for use in imaging through scattering media. Further, we demonstrate that this method leads to a new type of MMM wherein it is possible to simultaneously obtain multiple images and view differences in excitation parameters in a single shot. PMID:27390511

Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer.

PubMed

Schob, Stefan; Meyer, Hans Jonas; Dieckow, Julia; Pervinder, Bhogal; Pazaitis, Nikolaos; Höhn, Anne Kathrin; Garnov, Nikita; Horvath-Rizea, Diana; Hoffmann, Karl-Titus; Surov, Alexey

2017-04-12

Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm². Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted.

Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer

PubMed Central

Schob, Stefan; Meyer, Hans Jonas; Dieckow, Julia; Pervinder, Bhogal; Pazaitis, Nikolaos; Höhn, Anne Kathrin; Garnov, Nikita; Horvath-Rizea, Diana; Hoffmann, Karl-Titus; Surov, Alexey

2017-01-01

Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm2. Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. Conclusions: histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted. PMID:28417929

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.

Clustering change patterns using Fourier transformation with time-course gene expression data.

PubMed

Kim, Jaehee

2011-01-01

To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a period of time because biologically related gene groups can share the same change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. This work is aimed at discovering gene groups with similar change patterns which share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. We applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns.

The role of wind-tunnel studies in integrative research on migration biology.

PubMed

Engel, Sophia; Bowlin, Melissa S; Hedenström, Anders

2010-09-01

Wind tunnels allow researchers to investigate animals' flight under controlled conditions, and provide easy access to the animals during flight. These increasingly popular devices can benefit integrative migration biology by allowing us to explore the links between aerodynamic theory and migration as well as the links between flight behavior and physiology. Currently, wind tunnels are being used to investigate many different migratory phenomena, including the relationship between metabolic power and flight speed and carry-over effects between different seasons. Although biotelemetry is also becoming increasingly common, it is unlikely that it will be able to completely supplant wind tunnels because of the difficulty of measuring or varying parameters such as flight speed or temperature in the wild. Wind tunnels and swim tunnels will therefore continue to be important tools we can use for studying integrative migration biology. © The Author 2010. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved.

Systems modelling methodology for the analysis of apoptosis signal transduction and cell death decisions.

PubMed

Rehm, Markus; Prehn, Jochen H M

2013-06-01

Systems biology and systems medicine, i.e. the application of systems biology in a clinical context, is becoming of increasing importance in biology, drug discovery and health care. Systems biology incorporates knowledge and methods that are applied in mathematics, physics and engineering, but may not be part of classical training in biology. We here provide an introduction to basic concepts and methods relevant to the construction and application of systems models for apoptosis research. We present the key methods relevant to the representation of biochemical processes in signal transduction models, with a particular reference to apoptotic processes. We demonstrate how such models enable a quantitative and temporal analysis of changes in molecular entities in response to an apoptosis-inducing stimulus, and provide information on cell survival and cell death decisions. We introduce methods for analyzing the spatial propagation of cell death signals, and discuss the concepts of sensitivity analyses that enable a prediction of network responses to disturbances of single or multiple parameters. Copyright © 2013 Elsevier Inc. 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.

A new parametric method to smooth time-series data of metabolites in metabolic networks.

PubMed

Miyawaki, Atsuko; Sriyudthsak, Kansuporn; Hirai, Masami Yokota; Shiraishi, Fumihide

2016-12-01

Mathematical modeling of large-scale metabolic networks usually requires smoothing of metabolite time-series data to account for measurement or biological errors. Accordingly, the accuracy of smoothing curves strongly affects the subsequent estimation of model parameters. Here, an efficient parametric method is proposed for smoothing metabolite time-series data, and its performance is evaluated. To simplify parameter estimation, the method uses S-system-type equations with simple power law-type efflux terms. Iterative calculation using this method was found to readily converge, because parameters are estimated stepwise. Importantly, smoothing curves are determined so that metabolite concentrations satisfy mass balances. Furthermore, the slopes of smoothing curves are useful in estimating parameters, because they are probably close to their true behaviors regardless of errors that may be present in the actual data. Finally, calculations for each differential equation were found to converge in much less than one second if initial parameters are set at appropriate (guessed) values. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Probabilistic modeling of percutaneous absorption for risk-based exposure assessments and transdermal drug delivery.

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

Ho, Clifford Kuofei

Chemical transport through human skin can play a significant role in human exposure to toxic chemicals in the workplace, as well as to chemical/biological warfare agents in the battlefield. The viability of transdermal drug delivery also relies on chemical transport processes through the skin. Models of percutaneous absorption are needed for risk-based exposure assessments and drug-delivery analyses, but previous mechanistic models have been largely deterministic. A probabilistic, transient, three-phase model of percutaneous absorption of chemicals has been developed to assess the relative importance of uncertain parameters and processes that may be important to risk-based assessments. Penetration routes through the skinmore » that were modeled include the following: (1) intercellular diffusion through the multiphase stratum corneum; (2) aqueous-phase diffusion through sweat ducts; and (3) oil-phase diffusion through hair follicles. Uncertainty distributions were developed for the model parameters, and a Monte Carlo analysis was performed to simulate probability distributions of mass fluxes through each of the routes. Sensitivity analyses using stepwise linear regression were also performed to identify model parameters that were most important to the simulated mass fluxes at different times. This probabilistic analysis of percutaneous absorption (PAPA) method has been developed to improve risk-based exposure assessments and transdermal drug-delivery analyses, where parameters and processes can be highly uncertain.« less

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

PubMed

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

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

From Understanding the Development Landscape of the Canonical Fate-Switch Pair to Constructing a Dynamic Landscape for Two-Step Neural Differentiation

PubMed Central

2012-01-01

Abstract Recent progress in stem cell biology, notably cell fate conversion, calls for novel theoretical understanding for cell differentiation. The existing qualitative concept of Waddington’s “epigenetic landscape” has attracted particular attention because it captures subsequent fate decision points, thus manifesting the hierarchical (“tree-like”) nature of cell fate diversification. Here, we generalized a recent work and explored such a developmental landscape for a two-gene fate decision circuit by integrating the underlying probability landscapes with different parameters (corresponding to distinct developmental stages). The change of entropy production rate along the parameter changes indicates which parameter changes can represent a normal developmental process while other parameters’ change can not. The transdifferentiation paths over the landscape under certain conditions reveal the possibility of a direct and reversible phenotypic conversion. As the intensity of noise increases, we found that the landscape becomes flatter and the dominant paths more straight, implying the importance of biological noise processing mechanism in development and reprogramming. We further extended the landscape of the one-step fate decision to that for two-step decisions in central nervous system (CNS) differentiation. A minimal network and dynamic model for CNS differentiation was firstly constructed where two three-gene motifs are coupled. We then implemented the SDEs (Stochastic Differentiation Equations) simulation for the validity of the network and model. By integrating the two landscapes for the two switch gene pairs, we constructed the two-step development landscape for CNS differentiation. Our work provides new insights into cellular differentiation and important clues for better reprogramming strategies. PMID:23300518

Resilience of Key Biological Parameters of the Senegalese Flat Sardinella to Overfishing and Climate Change.

PubMed

Ba, Kamarel; Thiaw, Modou; Lazar, Najih; Sarr, Alassane; Brochier, Timothée; Ndiaye, Ismaïla; Faye, Alioune; Sadio, Oumar; Panfili, Jacques; Thiaw, Omar Thiom; Brehmer, Patrice

2016-01-01

The stock of the Senegalese flat sardinella, Sardinella maderensis, is highly exploited in Senegal, West Africa. Its growth and reproduction parameters are key biological indicators for improving fisheries management. This study reviewed these parameters using landing data from small-scale fisheries in Senegal and literature information dated back more than 25 years. Age was estimated using length-frequency data to calculate growth parameters and assess the growth performance index. With global climate change there has been an increase in the average sea surface temperature along the Senegalese coast but the length-weight parameters, sex ratio, size at first sexual maturity, period of reproduction and condition factor of S. maderensis have not changed significantly. The above parameters of S. maderensis have hardly changed, despite high exploitation and fluctuations in environmental conditions that affect the early development phases of small pelagic fish in West Africa. This lack of plasticity of the species regarding of the biological parameters studied should be considered when planning relevant fishery management plans.

Modularity Induced Gating and Delays in Neuronal Networks

PubMed Central

Shein-Idelson, Mark; Cohen, Gilad; Hanein, Yael

2016-01-01

Neural networks, despite their highly interconnected nature, exhibit distinctly localized and gated activation. Modularity, a distinctive feature of neural networks, has been recently proposed as an important parameter determining the manner by which networks support activity propagation. Here we use an engineered biological model, consisting of engineered rat cortical neurons, to study the role of modular topology in gating the activity between cell populations. We show that pairs of connected modules support conditional propagation (transmitting stronger bursts with higher probability), long delays and propagation asymmetry. Moreover, large modular networks manifest diverse patterns of both local and global activation. Blocking inhibition decreased activity diversity and replaced it with highly consistent transmission patterns. By independently controlling modularity and disinhibition, experimentally and in a model, we pose that modular topology is an important parameter affecting activation localization and is instrumental for population-level gating by disinhibition. PMID:27104350

Atmospheric corrections for satellite water quality studies

NASA Technical Reports Server (NTRS)

Piech, K. R.; Schott, J. R.

1975-01-01

Variations in the relative value of the blue and green reflectances of a lake can be correlated with important optical and biological parameters measured from surface vessels. Measurement of the relative reflectance values from color film imagery requires removal of atmospheric effects. Data processing is particularly crucial because: (1) lakes are the darkest objects in a scene; (2) minor reflectance changes can correspond to important physical changes; (3) lake systems extend over broad areas in which atmospheric conditions may fluctuate; (4) seasonal changes are of importance; and, (5) effects of weather are important, precluding flights under only ideal weather conditions. Data processing can be accomplished through microdensitometry of scene shadow areas. Measurements of reflectance ratios can be made to an accuracy of plus or minus 12%, sufficient to permit monitoring of important eutrophication indices.

Capturing extracellular matrix properties in vitro: Microengineering materials to decipher cell and tissue level processes.

PubMed

Abdeen, Amr A; Lee, Junmin; Kilian, Kristopher A

2016-05-01

Rapid advances in biology have led to the establishment of new fields with tremendous translational potential including regenerative medicine and immunoengineering. One commonality to these fields is the need to extract cells for manipulation in vitro; however, results obtained in laboratory cell culture will often differ widely from observations made in vivo. To more closely emulate native cell biology in the laboratory, designer engineered environments have proved a successful methodology to decipher the properties of the extracellular matrix that govern cellular decision making. Here, we present an overview of matrix properties that affect cell behavior, strategies for recapitulating important parameters in vitro, and examples of how these properties can affect cell and tissue level processes, with emphasis on leveraging these tools for immunoengineering. © 2016 by the Society for Experimental Biology and Medicine.

Cell illustrator 4.0: a computational platform for systems biology.

PubMed

Nagasaki, Masao; Saito, Ayumu; Jeong, Euna; Li, Chen; Kojima, Kaname; Ikeda, Emi; Miyano, Satoru

2011-01-01

Cell Illustrator is a software platform for Systems Biology that uses the concept of Petri net for modeling and simulating biopathways. It is intended for biological scientists working at bench. The latest version of Cell Illustrator 4.0 uses Java Web Start technology and is enhanced with new capabilities, including: automatic graph grid layout algorithms using ontology information; tools using Cell System Markup Language (CSML) 3.0 and Cell System Ontology 3.0; parameter search module; high-performance simulation module; CSML database management system; conversion from CSML model to programming languages (FORTRAN, C, C++, Java, Python and Perl); import from SBML, CellML, and BioPAX; and, export to SVG and HTML. Cell Illustrator employs an extension of hybrid Petri net in an object-oriented style so that biopathway models can include objects such as DNA sequence, molecular density, 3D localization information, transcription with frame-shift, translation with codon table, as well as biochemical reactions.

Leveraging advances in biology to design biomaterials

NASA Astrophysics Data System (ADS)

Darnell, Max; Mooney, David J.

2017-12-01

Biomaterials have dramatically increased in functionality and complexity, allowing unprecedented control over the cells that interact with them. From these engineering advances arises the prospect of improved biomaterial-based therapies, yet practical constraints favour simplicity. Tools from the biology community are enabling high-resolution and high-throughput bioassays that, if incorporated into a biomaterial design framework, could help achieve unprecedented functionality while minimizing the complexity of designs by identifying the most important material parameters and biological outputs. However, to avoid data explosions and to effectively match the information content of an assay with the goal of the experiment, material screens and bioassays must be arranged in specific ways. By borrowing methods to design experiments and workflows from the bioprocess engineering community, we outline a framework for the incorporation of next-generation bioassays into biomaterials design to effectively optimize function while minimizing complexity. This framework can inspire biomaterials designs that maximize functionality and translatability.

Examining Microbial Survival During Infall onto Europa: An Important Limit on the Origin of Potential European Life

NASA Technical Reports Server (NTRS)

Fries, M.; Conrad, P.; Matney, M.; Steele, A.

2015-01-01

Previous work shows that transfer of material from Earth to Europa is statistically possible, opening the question of whether terrestrial biota may have transferred to Europa to populate that world. Transfer of viable organisms is a function of parameters such as ejection shock, radiation exposure, and others, applied across four phases in the transfer process: ejection from the parent body, transport through interplanetary space, infall onto the target world, and biological adaptation. If terrestrial biota could survive transport to Europa, then biology on Europa may be either the product of a separate and unrelated origin or they are the descendants of transferred terrestrial organisms. If, however, transfer of viable organisms is impossible, then any biota present on Europa must be the product of a biological origin independent from terrestrial life. We will investigate the survival likelihood of material falling onto Europa.

Squid as nutrient vectors linking Southwest Atlantic marine ecosystems

NASA Astrophysics Data System (ADS)

Arkhipkin, Alexander I.

2013-10-01

Long-term investigations of three abundant nektonic squid species from the Southwest Atlantic, Illex argentinus, Doryteuthis gahi and Onykia ingens, permitted to estimate important population parameters including individual growth rates, duration of ontogenetic phases and mortalities. Using production model, the productivity of squid populations at different phases of their life cycle was assessed and the amount of biomass they convey between marine ecosystems as a result of their ontogenetic migrations was quantified. It was found that squid are major nutrient vectors and play a key role as transient 'biological pumps' linking spatially distinct marine ecosystems. I. argentinus has the largest impact in all three ecosystems it encounters due to its high abundance and productivity. The variable nature of squid populations increases the vulnerability of these biological conveyers to overfishing and environmental change. Failure of these critical biological pathways may induce irreversible long-term consequences for biodiversity, resource abundance and spatial availability in the world ocean.

Cell Illustrator 4.0: a computational platform for systems biology.

PubMed

Nagasaki, Masao; Saito, Ayumu; Jeong, Euna; Li, Chen; Kojima, Kaname; Ikeda, Emi; Miyano, Satoru

2010-01-01

Cell Illustrator is a software platform for Systems Biology that uses the concept of Petri net for modeling and simulating biopathways. It is intended for biological scientists working at bench. The latest version of Cell Illustrator 4.0 uses Java Web Start technology and is enhanced with new capabilities, including: automatic graph grid layout algorithms using ontology information; tools using Cell System Markup Language (CSML) 3.0 and Cell System Ontology 3.0; parameter search module; high-performance simulation module; CSML database management system; conversion from CSML model to programming languages (FORTRAN, C, C++, Java, Python and Perl); import from SBML, CellML, and BioPAX; and, export to SVG and HTML. Cell Illustrator employs an extension of hybrid Petri net in an object-oriented style so that biopathway models can include objects such as DNA sequence, molecular density, 3D localization information, transcription with frame-shift, translation with codon table, as well as biochemical reactions.

Data bank of optical properties of biological tissue and blood in the visible and near infrared spectral region

NASA Astrophysics Data System (ADS)

Khairullina, Alphiya Y.; Bui, Lilia; Oleinik, Tatiana V.; Artishevsky, Nelli; Prigoun, Natalia; Sevkovsky, Jakov; Mokhort, Tatiana

1996-12-01

The data bank contains optical, ordinary biochemical and biophysical information on 120 venous blood samples of donors, healthy persons, patients with high pathology, 60 tissue samples. The optical parameters include diffuse reflection R((lambda) ) and transmission T((lambda) ) coefficients for optically thick layers, the absorption K((lambda) ) and extinction (epsilon) ((lambda) ) spectra, oxygenation degree CO2, parameter p determined by sizes and shapes of cells and their aggregates, refractive index of a disperse phase relative to surrounding media, and cooperative effects at high relative concentration. The peculiarities in absorption K((lambda) spectra are connected with different pathologies. It is shown from K((lambda) ) that the grade of pathology connected with the concentration of hemoglobin and mithohondrion together with oxygenation degree of blood and tissues, with the pathological hemoglobin's forms and its decomposition products of different levels. Parameter p is an important diagnostic parameter. We consider that it is necessary to include the oxygenation degree and erythrocyte's aggregation parameter to extend the range of common diagnostic parameters of blood by the first rota.

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.

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

Modeling metapopulation dynamics for single species of seabirds

USGS Publications Warehouse

Buckley, P.A.; Downer, R.; McCullough, D.R.; Barrett, R.H.

1992-01-01

Seabirds share many characteristics setting them apart from other birds. Importantly, they breed more or less obligatorily in local clusters of colonies that can move regularly from site to site, and they routinely exchange breeders. The properties of such metapopulations have only recently begun to be examined, often with models that are occupancy-based (using only colony presence or absence data) and deterministic (using single, empirically determined values for each of several population biology parameters). Some recent models are now frequency-based (using actual population sizes at each site), as well as stochastic (randomly varying critical parameters between biologically realistic limits), yielding better estimates of the behavior of future populations. Using two such models designed to quantify relative risks of population changes under different future scenarios (RAMAS/stage and RAMAS/space), we have examined probable future populations dynamics for three hypothetical seabirds -- an albatross, a cormorant, and a tern. With real parameters and ranges of values we alternatively modelled each species with and without density dependence, as well as with their numbers in a single, large colony, or in many smaller ones, distributed evenly or lognormally. We produced a series of species-typical lines for different population risks over the 50 years we simulated. We call these curves Instantaneous Threat Assessments (ITAs), and their shapes mirror the varying life history characteristics of our three species. We also demonstrated (by a process known as sensitivity analysis) that the most important parameters determining future population fates of all three species were correlation of mean growth rate among colonies; dispersal rate of present and future breeders; subadult survivorship; and the number of subpopulations (=colonies) - in roughly that descending order of importance. In addition, density dependence was found to markedly alter ITA line shape and position, dramatically in the tern. Finally, we show that for each of our three seabirds, a substantial reduction in the risk of the entire population's going to extinction was provided by a metapopulation (i.e. colonial) breeding structure -- thus comfortably confirming what avian ecologists have long known but about which population modellers are somtimes still unsure.

A Discontinuous Potential Model for Protein-Protein Interactions.

PubMed

Shao, Qing; Hall, Carol K

2016-01-01

Protein-protein interactions play an important role in many biologic and industrial processes. In this work, we develop a two-bead-per-residue model that enables us to account for protein-protein interactions in a multi-protein system using discontinuous molecular dynamics simulations. This model deploys discontinuous potentials to describe the non-bonded interactions and virtual bonds to keep proteins in their native state. The geometric and energetic parameters are derived from the potentials of mean force between sidechain-sidechain, sidechain-backbone, and backbone-backbone pairs. The energetic parameters are scaled with the aim of matching the second virial coefficient of lysozyme reported in experiment. We also investigate the performance of several bond-building strategies.

On the Optimum Architecture of the Biologically Inspired Hierarchical Temporal Memory Model Applied to the Hand-Written Digit Recognition

NASA Astrophysics Data System (ADS)

Štolc, Svorad; Bajla, Ivan

2010-01-01

In the paper we describe basic functions of the Hierarchical Temporal Memory (HTM) network based on a novel biologically inspired model of the large-scale structure of the mammalian neocortex. The focus of this paper is in a systematic exploration of possibilities how to optimize important controlling parameters of the HTM model applied to the classification of hand-written digits from the USPS database. The statistical properties of this database are analyzed using the permutation test which employs a randomization distribution of the training and testing data. Based on a notion of the homogeneous usage of input image pixels, a methodology of the HTM parameter optimization is proposed. In order to study effects of two substantial parameters of the architecture: the patch size and the overlap in more details, we have restricted ourselves to the single-level HTM networks. A novel method for construction of the training sequences by ordering series of the static images is developed. A novel method for estimation of the parameter maxDist based on the box counting method is proposed. The parameter sigma of the inference Gaussian is optimized on the basis of the maximization of the belief distribution entropy. Both optimization algorithms can be equally applied to the multi-level HTM networks as well. The influences of the parameters transitionMemory and requestedGroupCount on the HTM network performance have been explored. Altogether, we have investigated 2736 different HTM network configurations. The obtained classification accuracy results have been benchmarked with the published results of several conventional classifiers.

Topsoil structure stability in a restored floodplain: Impacts of fluctuating water levels, soil parameters and ecosystem engineers.

PubMed

Schomburg, A; Schilling, O S; Guenat, C; Schirmer, M; Le Bayon, R C; Brunner, P

2018-10-15

Ecosystem services provided by floodplains are strongly controlled by the structural stability of soils. The development of a stable structure in floodplain soils is affected by a complex and poorly understood interplay of hydrological, physico-chemical and biological processes. This paper aims at analysing relations between fluctuating groundwater levels, soil physico-chemical and biological parameters on soil structure stability in a restored floodplain. Water level fluctuations in the soil are modelled using a numerical surface-water-groundwater flow model and correlated to soil physico-chemical parameters and abundances of plants and earthworms. Causal relations and multiple interactions between the investigated parameters are tested through structural equation modelling (SEM). Fluctuating water levels in the soil did not directly affect the topsoil structure stability, but indirectly through affecting plant roots and soil parameters that in turn determine topsoil structure stability. These relations remain significant for mean annual days of complete and partial (>25%) water saturation. Ecosystem functioning of a restored floodplain might already be affected by the fluctuation of groundwater levels alone, and not only through complete flooding by surface water during a flood period. Surprisingly, abundances of earthworms did not show any relation to other variables in the SEM. These findings emphasise that earthworms have efficiently adapted to periodic stress and harsh environmental conditions. Variability of the topsoil structure stability is thus stronger driven by the influence of fluctuating water levels on plants than by the abundance of earthworms. This knowledge about the functional network of soil engineering organisms, soil parameters and fluctuating water levels and how they affect soil structural stability is of fundamental importance to define management strategies of near-natural or restored floodplains in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

Studies on the interaction of a synthetic nitro-flavone derivative with DNA: A multi-spectroscopic and molecular docking approach.

PubMed

Mitra, A; Saikh, F; Das, J; Ghosh, S; Ghosh, R

2018-05-22

Interaction of a ligand with DNA is often the basis of drug action of many molecules. Flavones are important in this regard as their structural features confer them the ability to bind to DNA. 2-(4-Nitrophenyl)-4H-chromen-4-one (4NCO) is an important biologically active synthetic flavone derivative. We are therefore interested in studying its interaction with DNA. Absorption spectroscopy studies included standard and reverse titration, effect of ionic strength on titration, determination of stoichiometry of binding and thermal denaturation. Spectrofluorimetry techniques included fluorimetric titration, quenching studies and fluorescence displacement assay. Assessment of relative viscosity and estimation of thermodynamic parameters from CD spectral studies were also undertaken. Furthermore, molecular docking analyses were also done with different short DNA sequences. The fluorescent flavone 4NCO reversibly interacted with DNA through partial intercalation as well as minor-groove binding. The binding constant and the number of binding sites were of the order 10 4  M -1 and 1 respectively. The binding stoichiometry with DNA was found to be 1:1. The nature of the interaction of 4NCO with DNA was hydrophobic in nature and the process of binding was spontaneous, endothermic and entropy-driven. The flavone also showed a preference for binding to GC rich sequences. The study presents a profile for structural and thermodynamic parameters, for the binding of 4NCO with DNA. DNA is an important target for ligands that are effective against cell proliferative disorders. In this regard, the molecule 4NCO is important since it can exert its biological activity through its DNA binding ability and can be a potential drug candidate. Copyright © 2018 Elsevier B.V. All rights reserved.

The effects of dynamic loading on the intervertebral disc.

PubMed

Chan, Samantha C W; Ferguson, Stephen J; Gantenbein-Ritter, Benjamin

2011-11-01

Loading is important to maintain the balance of matrix turnover in the intervertebral disc (IVD). Daily cyclic diurnal assists in the transport of large soluble factors across the IVD and its surrounding circulation and applies direct and indirect stimulus to disc cells. Acute mechanical injury and accumulated overloading, however, could induce disc degeneration. Recently, there is more information available on how cyclic loading, especially axial compression and hydrostatic pressure, affects IVD cell biology. This review summarises recent studies on the response of the IVD and stem cells to applied cyclic compression and hydrostatic pressure. These studies investigate the possible role of loading in the initiation and progression of disc degeneration as well as quantifying a physiological loading condition for the study of disc degeneration biological therapy. Subsequently, a possible physiological/beneficial loading range is proposed. This physiological/beneficial loading could provide insight into how to design loading regimes in specific system for the testing of various biological therapies such as cell therapy, chemical therapy or tissue engineering constructs to achieve a better final outcome. In addition, the parameter space of 'physiological' loading may also be an important factor for the differentiation of stem cells towards most ideally 'discogenic' cells for tissue engineering purpose.

Comparative physiology of mice and rats: radiometric measurement of vascular parameters in rodent tissues.

PubMed

Boswell, C Andrew; Mundo, Eduardo E; Ulufatu, Sheila; Bumbaca, Daniela; Cahaya, Hendry S; Majidy, Nicholas; Van Hoy, Marjie; Schweiger, Michelle G; Fielder, Paul J; Prabhu, Saileta; Khawli, Leslie A

2014-05-05

A solid understanding of physiology is beneficial in optimizing drug delivery and in the development of clinically predictive models of drug disposition kinetics. Although an abundance of data exists in the literature, it is often confounded by the use of various experimental methods and a lack of consensus in values from different sources. To help address this deficiency, we sought to directly compare three important vascular parameters at the tissue level using the same experimental approach in both mice and rats. Interstitial volume, vascular volume, and blood flow were radiometrically measured in selected harvested tissues of both species by extracellular marker infusion, red blood cell labeling, and rubidium chloride bolus distribution, respectively. The latter two parameters were further compared by whole-body autoradiographic imaging. An overall good interspecies agreement was observed for interstitial volume and blood flow on a weight-normalized basis in most tissues. In contrast, the measured vascular volumes of most rat tissues were higher than for mouse. Mice and rats, the two most commonly utilized rodent species in translational drug development, should not be considered as interchangeable in terms of vascular volume per gram of tissue. This will be particularly critical in biodistribution studies of drugs, as the amount of drug in the residual blood of tissues is often not negligible, especially for biologic drugs (e.g., antibodies) having long circulation half-lives. Physiologically based models of drug pharmacokinetics and/or pharmacodynamics also rely on accurate knowledge of biological parameters in tissues. For tissue parameters with poor interspecies agreement, the significance and possible drivers are discussed.

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.

Rate heterogeneity across Squamata, misleading ancestral state reconstruction and the importance of proper null model specification.

PubMed

Harrington, S; Reeder, T W

2017-02-01

The binary-state speciation and extinction (BiSSE) model has been used in many instances to identify state-dependent diversification and reconstruct ancestral states. However, recent studies have shown that the standard procedure of comparing the fit of the BiSSE model to constant-rate birth-death models often inappropriately favours the BiSSE model when diversification rates vary in a state-independent fashion. The newly developed HiSSE model enables researchers to identify state-dependent diversification rates while accounting for state-independent diversification at the same time. The HiSSE model also allows researchers to test state-dependent models against appropriate state-independent null models that have the same number of parameters as the state-dependent models being tested. We reanalyse two data sets that originally used BiSSE to reconstruct ancestral states within squamate reptiles and reached surprising conclusions regarding the evolution of toepads within Gekkota and viviparity across Squamata. We used this new method to demonstrate that there are many shifts in diversification rates across squamates. We then fit various HiSSE submodels and null models to the state and phylogenetic data and reconstructed states under these models. We found that there is no single, consistent signal for state-dependent diversification associated with toepads in gekkotans or viviparity across all squamates. Our reconstructions show limited support for the recently proposed hypotheses that toepads evolved multiple times independently in Gekkota and that transitions from viviparity to oviparity are common in Squamata. Our results highlight the importance of considering an adequate pool of models and null models when estimating diversification rate parameters and reconstructing ancestral states. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

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.

Diffusion-advection within dynamic biological gaps driven by structural motion

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

Multiple expression patterns of biopathological markers in primary invasive breast carcinoma: a useful tool for elucidating its biological behaviour.

PubMed

Ceccarelli, C; Santini, D; Chieco, P; Taffurelli, M; Marrano, D; Mancini, A M

1995-03-01

Commonly used clinical and morphologic criteria have been reported to be of limited value in predicting the outcome of malignant tumours of the breast. Integrated information from the quantitative analysis in tumour tissue of biological parameters such as oestrogen and progesterone receptors (ER and PGR), proliferative activity, and proto-oncogene p53, c-erB2, and bcl-2 expression, may be useful for defining the biology of growth of breast carcinoma and to plan effective therapeutic strategies. Immunohistochemistry with antibodies recognizing ER, PGR, Ki-67, and the p53, c-erbB2, and bcl-2 encoded proteins was performed on 291 primary breast carcinomas. Results were integrated with clinico-pathological indicators and examined with multivariate statistical procedures and modeling. P53, c-erbB2, and bcl-2 gene products were detected, respectively, in 30.6%, 31.6%, and 85.9% of the examined invasive breast carcinomas, revealing variable associations with cellular differentiation and proliferation as defined by ER/PGR status, Ki-67, tumour mass and histologic and nuclear grading. A multivariate graphical display on a subset of the most informative cases revealed that bcl-2 expression parallels ER/PGR status and is of importance in separating tumour clusters with different degrees of aggressiveness. The results of this study indicate that multivariate explorative analyses conducted on biological and clinico-pathological parameters might constitute an integrated approach to data analysis useful for distinguishing different biological behaviours and therapeutic groups in breast carcinoma. Our findings also suggest that bcl-2 expression may play a pivotal role in tumours lacking ER-mediated growth regulation.

Smooth 2D manifold extraction from 3D image stack

PubMed Central

Shihavuddin, Asm; Basu, Sreetama; Rexhepaj, Elton; Delestro, Felipe; Menezes, Nikita; Sigoillot, Séverine M; Del Nery, Elaine; Selimi, Fekrije; Spassky, Nathalie; Genovesio, Auguste

2017-01-01

Three-dimensional fluorescence microscopy followed by image processing is routinely used to study biological objects at various scales such as cells and tissue. However, maximum intensity projection, the most broadly used rendering tool, extracts a discontinuous layer of voxels, obliviously creating important artifacts and possibly misleading interpretation. Here we propose smooth manifold extraction, an algorithm that produces a continuous focused 2D extraction from a 3D volume, hence preserving local spatial relationships. We demonstrate the usefulness of our approach by applying it to various biological applications using confocal and wide-field microscopy 3D image stacks. We provide a parameter-free ImageJ/Fiji plugin that allows 2D visualization and interpretation of 3D image stacks with maximum accuracy. PMID:28561033

Using LabView for real-time monitoring and tracking of multiple biological objects

NASA Astrophysics Data System (ADS)

Nikolskyy, Aleksandr I.; Krasilenko, Vladimir G.; Bilynsky, Yosyp Y.; Starovier, Anzhelika

2017-04-01

Today real-time studying and tracking of movement dynamics of various biological objects is important and widely researched. Features of objects, conditions of their visualization and model parameters strongly influence the choice of optimal methods and algorithms for a specific task. Therefore, to automate the processes of adaptation of recognition tracking algorithms, several Labview project trackers are considered in the article. Projects allow changing templates for training and retraining the system quickly. They adapt to the speed of objects and statistical characteristics of noise in images. New functions of comparison of images or their features, descriptors and pre-processing methods will be discussed. The experiments carried out to test the trackers on real video files will be presented and analyzed.

Microbial diversity and structure are drivers of the biological barrier effect against Listeria monocytogenes in soil.

PubMed

Vivant, Anne-Laure; Garmyn, Dominique; Maron, Pierre-Alain; Nowak, Virginie; Piveteau, Pascal

2013-01-01

Understanding the ecology of pathogenic organisms is important in order to monitor their transmission in the environment and the related health hazards. We investigated the relationship between soil microbial diversity and the barrier effect against Listeria monocytogenes invasion. By using a dilution-to-extinction approach, we analysed the consequence of eroding microbial diversity on L. monocytogenes population dynamics under standardised conditions of abiotic parameters and microbial abundance in soil microcosms. We demonstrated that highly diverse soil microbial communities act as a biological barrier against L. monocytogenes invasion and that phylogenetic composition of the community also has to be considered. This suggests that erosion of diversity may have damaging effects regarding circulation of pathogenic microorganisms in the environment.

Integration of planetary protection activities

NASA Technical Reports Server (NTRS)

Race, Margaret S.

1995-01-01

For decades, NASA has been concerned about the protection of planets and other solar system bodies from biological contamination. Its policies regarding biological contamination control for outbound and inbound planetary spacecraft have evolved to focus on three important areas: (1) the preservation of celestial objects and the space environment; (2) protection of Earth from extraterrestrial hazards; and (3) ensuring the integrity of its scientific investigations. Over the years as new information has been obtained from planetary exploration and research, planetary protection parameters and policies have been modified accordingly. The overall focus of research under this cooperative agreement has been to provide information about non-scientific and societal factors related to planetary protection and use it in the planning and implementation phases of future Mars sample return missions.

Gastric lymphomas in Turkey. Analysis of prognostic factors with special emphasis on flow cytometric DNA content.

PubMed

Aydin, Z D; Barista, I; Canpinar, H; Sungur, A; Tekuzman, G

2000-07-01

In contrast to DNA ploidy, to the authors' knowledge the prognostic significance of S-phase fraction (SPF) in gastric lymphomas has not been determined. In the current study, the prognostic significance of various parameters including SPF and DNA aneuploidy were analyzed and some distinct epidemiologic and biologic features of gastric lymphomas in Turkey were found. A series of 78 gastric lymphoma patients followed at Hacettepe University is reported. DNA flow cytometry was performed for 34 patients. The influence of various parameters on survival was investigated with the log rank test. The Cox proportional hazards model was fitted to identify independent prognostic factors. The median age of the patients was 50 years. There was no correlation between patient age and tumor grade. DNA content analysis revealed 4 of the 34 cases to be aneuploid with DNA index values < 1.0. The mean SPF was 33.5%. In the univariate analysis, surgical resection of the tumor, modified Ann Arbor stage, performance status, response to first-line chemotherapy, lactate dehydrogenase (LDH) level, and SPF were important prognostic factors for disease free survival (DFS). The same parameters, excluding LDH level, were important for determining overall survival (OS). In the multivariate analysis, surgical resection of the tumor, disease stage, performance status, and age were found to be important prognostic factors for OS. To the authors' knowledge the current study is the first to demonstrate the prognostic significance of SPF in gastric lymphomas. The distinguishing features of Turkish gastric lymphoma patients are 1) DNA indices of aneuploid cases that all are < 1.0, which is a unique feature; 2) a lower percentage of aneuploid cases; 3) a higher SPF; 4) a younger age distribution; and 5) lack of an age-grade correlation. The authors conclude that gastric lymphomas in Turkey have distinct biologic and epidemiologic characteristics. Copyright 2000 American Cancer Society.

Biodiversity patterns of rock encrusting fauna from the shallow sublittoral of the Admiralty Bay.

PubMed

Krzeminska, Malgorzata; Kuklinski, Piotr

2018-08-01

The Antarctic sublittoral is one of the most demanding habitat for polar bottom-dwelling organisms, as the disturbance of this zone is highly intense. Rapid changes in the marine environment, such as increases in atmosphere and surface water temperatures, can cause dramatic changes in biodiversity, especially in glacial fjords affected by heavy melt water inputs from the retreating glaciers. In such areas, rocks are often an important support for local diversity, providing habitats for a number of encrusting organisms. Thus, understanding the patterns of diversity of shallow rock encrusting fauna and factors controlling it are particularly important. The structure and diversity patterns of rock encrusting fauna were examined from four ecologically contrasting sites in the shallow sublittoral (6-20 m) of Admiralty Bay (King George Island). The results revealed a rich and abundant encrusting community with bryozoans and polychaetes outcompeting representatives of other fauna such as foraminifera and porifera. Spatial variability in species composition, as well as biological parameters, revealed the trend of encrusting assemblages declining towards the inner fjord areas - strongly affected by high sediment input (species richness: 13.3 ± 1.2, and abundance: 68,932.99 ± 11,915.98 individuals m -2  ± standard error). In contrast, at sites more open to the central basin, a peak of biological parameters was observed (24.8 ± 1.4 and 297,360.9 ± 30,314.72, respectively). We suggest that increased sedimentation was the major factor structuring the encrusting assemblages in Ezcurra Inlet, masking the influence of other parameters, such as food and light availability, which are important for the distribution of epifauna. Thus, if the increasing intensity of glacial processes will continue in the upcoming years, the diversity of the encrusting fauna in the shallow sublittoral could dramatically decrease. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multi-scale Functional and Molecular Photoacoustic Tomography

PubMed Central

Yao, Junjie; Xia, Jun; Wang, Lihong V.

2015-01-01

Photoacoustic tomography (PAT) combines rich optical absorption contrast with the high spatial resolution of ultrasound at depths in tissue. The high scalability of PAT has enabled anatomical imaging of biological structures ranging from organelles to organs. The inherent functional and molecular imaging capabilities of PAT have further allowed it to measure important physiological parameters and track critical cellular activities. Integration of PAT with other imaging technologies provides complementary capabilities and can potentially accelerate the clinical translation of PAT. PMID:25933617

Quantitative Förster resonance energy transfer analysis for kinetic determinations of SUMO-specific protease.

PubMed

Liu, Yan; Song, Yang; Madahar, Vipul; Liao, Jiayu

2012-03-01

Förster resonance energy transfer (FRET) technology has been widely used in biological and biomedical research, and it is a very powerful tool for elucidating protein interactions in either dynamic or steady state. SUMOylation (the process of SUMO [small ubiquitin-like modifier] conjugation to substrates) is an important posttranslational protein modification with critical roles in multiple biological processes. Conjugating SUMO to substrates requires an enzymatic cascade. Sentrin/SUMO-specific proteases (SENPs) act as an endopeptidase to process the pre-SUMO or as an isopeptidase to deconjugate SUMO from its substrate. To fully understand the roles of SENPs in the SUMOylation cycle, it is critical to understand their kinetics. Here, we report a novel development of a quantitative FRET-based protease assay for SENP1 kinetic parameter determination. The assay is based on the quantitative analysis of the FRET signal from the total fluorescent signal at acceptor emission wavelength, which consists of three components: donor (CyPet-SUMO1) emission, acceptor (YPet) emission, and FRET signal during the digestion process. Subsequently, we developed novel theoretical and experimental procedures to determine the kinetic parameters, k(cat), K(M), and catalytic efficiency (k(cat)/K(M)) of catalytic domain SENP1 toward pre-SUMO1. Importantly, the general principles of this quantitative FRET-based protease kinetic determination can be applied to other proteases. Copyright © 2011 Elsevier Inc. All rights reserved.

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

PubMed Central

2017-01-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability. PMID:29186132

Influence of space flight conditions on phenotypes and functionality of nephritic immune cells of fish (Xiphophorus helleri)

NASA Astrophysics Data System (ADS)

Piepenbreier, K.; Renn, J.; Fischer, R.; Goerlich, R.

Microgravity is considered to directly perturb a number of immunological and haematological parameters in mammalians, and therefore is of fundamental importance in space biology. The viviparous teleost Xiphophorus helleri (swordtail) was used as a "lower vertebrate model" in the shuttle missions STS-89 (Small Payload) and STS-90 (NEUROLAB). When developing a regenerative aquatic system (like the Closed Equilibrated Biological Aquatic System - C.E.B.A.S.) to produce food fish on long-term space missions, we have to make sure that microgravity and other space conditions do not endanger the animals' health. Immunological aspects are very important in this field. The major research targets were immunological research of accessory (monocytes) and immunoreactive cells (lymphocytes) of the kidney from X. helleri, which were exposed to microgravity in comparison to ground control animals. Cell cycle analysis of the main haematopoetic organ (kidney), cell behaviour, cell cytochemistry, phagocytic ability and in vitro stimulation of immunoreactive cells from kidney after return to earth were investigated. The results are also important for basic research in immunotoxicology and developmental biology. As there is an interrelation between immune cells and bone metabolism, the investigations are also interesting for space medicine. Acknowledgement: This work was supported by the German Aerospace Center (DLR) (50 WB 9412, 50 WB 9996) and the National Aeronautics and Space Administration (NASA 98HEDS-02-418)

Biological oxygen apparent transmissibility of hydrogel contact lenses with and without organosilicon moieties.

PubMed

Compañ, V; López-Alemany, A; Riande, E; Refojo, M F

2004-01-01

The instrument oxygen transmissibility (IOT) of organosilicon hydrogels, measured by electrochemical procedures, is 5-10 times larger than that of conventional hydrogels. A method is described that allows the estimation of the oxygen tension at the lens-cornea interface for closed- and open-eyelids situations by combining the IOT of the hydrogels and corneal parameters such as corneal thickness, corneal permeability and oxygen flux across the cornea. From these results the biological oxygen apparent transmissibility (BOAT) is obtained, an important parameter which an multiplication with the pressure of oxygen on the external part of the lens gives the oxygen flux onto the cornea. Contact lenses with oxygen transmissibility higher than 100 Dk/t units [1 Dk/t unit=10(-9) [cm(3) O(2) (STp) cm(-2)s(-1)(mmHg)(-1)] posses a large oxygen tension at the lens-cornea interface that substantially reduces the oxygen flux onto the cornea. Lenses whose oxygen transmissibility is lower than 50 Dk/t units allow a rather small oxygen flux onto the cornea under closed eyelids condition that prevent their use for extended wear.

Characterizing white matter tissue in large strain via asymmetric indentation and inverse finite element modeling.

PubMed

Feng, Yuan; Lee, Chung-Hao; Sun, Lining; Ji, Songbai; Zhao, Xuefeng

2017-01-01

Characterizing the mechanical properties of white matter is important to understand and model brain development and injury. With embedded aligned axonal fibers, white matter is typically modeled as a transversely isotropic material. However, most studies characterize the white matter tissue using models with a single anisotropic invariant or in a small-strain regime. In this study, we combined a single experimental procedure - asymmetric indentation - with inverse finite element (FE) modeling to estimate the nearly incompressible transversely isotropic material parameters of white matter. A minimal form comprising three parameters was employed to simulate indentation responses in the large-strain regime. The parameters were estimated using a global optimization procedure based on a genetic algorithm (GA). Experimental data from two indentation configurations of porcine white matter, parallel and perpendicular to the axonal fiber direction, were utilized to estimate model parameters. Results in this study confirmed a strong mechanical anisotropy of white matter in large strain. Further, our results suggested that both indentation configurations are needed to estimate the parameters with sufficient accuracy, and that the indenter-sample friction is important. Finally, we also showed that the estimated parameters were consistent with those previously obtained via a trial-and-error forward FE method in the small-strain regime. These findings are useful in modeling and parameterization of white matter, especially under large deformation, and demonstrate the potential of the proposed asymmetric indentation technique to characterize other soft biological tissues with transversely isotropic properties. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Soil degradation effect on biological activity in Mediterranean calcareous soils

NASA Astrophysics Data System (ADS)

Roca-Pérez, L.; Alcover-Sáez, S.; Mormeneo, S.; Boluda, R.

2009-04-01

Soil degradation processes include erosion, organic matter decline, compaction, salinization, landslides, contamination, sealing and biodiversity decline. In the Mediterranean region the climatological and lithological conditions, together with relief on the landscape and anthropological activity are responsible for increasing desertification process. It is therefore considered to be extreme importance to be able to measure soil degradation quantitatively. We studied soil characteristics, microbiological and biochemical parameters in different calcareous soil sequences from Valencia Community (Easter Spain), in an attempt to assess the suitability of the parameters measured to reflect the state of soil degradation and the possibility of using the parameters to assess microbiological decline and soil quality. For this purpose, forest, scrubland and agricultural soil in three soil sequences were sampled in different areas. Several sensors of the soil biochemistry and microbiology related with total organic carbon, microbial biomass carbon, soil respiration, microorganism number and enzyme activities were determined. The results show that, except microorganism number, these parameters are good indicators of a soil biological activity and soil quality. The best enzymatic activities to use like indicators were phosphatases, esterases, amino-peptidases. Thus, the enzymes test can be used as indicators of soil degradation when this degradation is related with organic matter losses. There was a statistically significant difference in cumulative O2 uptake and extracellular enzymes among the soils with different degree of degradation. We would like to thank Spanish government-MICINN for funding and support (MICINN, project CGL2006-09776).

Parameter Estimation of a Spiking Silicon Neuron

PubMed Central

Russell, Alexander; Mazurek, Kevin; Mihalaş, Stefan; Niebur, Ernst; Etienne-Cummings, Ralph

2012-01-01

Spiking neuron models are used in a multitude of tasks ranging from understanding neural behavior at its most basic level to neuroprosthetics. Parameter estimation of a single neuron model, such that the model’s output matches that of a biological neuron is an extremely important task. Hand tuning of parameters to obtain such behaviors is a difficult and time consuming process. This is further complicated when the neuron is instantiated in silicon (an attractive medium in which to implement these models) as fabrication imperfections make the task of parameter configuration more complex. In this paper we show two methods to automate the configuration of a silicon (hardware) neuron’s parameters. First, we show how a Maximum Likelihood method can be applied to a leaky integrate and fire silicon neuron with spike induced currents to fit the neuron’s output to desired spike times. We then show how a distance based method which approximates the negative log likelihood of the lognormal distribution can also be used to tune the neuron’s parameters. We conclude that the distance based method is better suited for parameter configuration of silicon neurons due to its superior optimization speed. PMID:23852978

Bioorganometallic chemistry. 8. The molecular recognition of aromatic and aliphatic amino acids and substituted aromatic and aliphatic carboxylic acid guests with supramolecular ({eta}{sup 5}-pentamethylcyclopentadienyl)rhodium - nucleobase, nucleoside, and nucleotide cyclic trimer hosts via non-covalent {pi}-{pi} and hydrophobic interactions in water: Steric, electronic, and conformational parameters

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

Chen, H.; Ogo, Seiji; Fish, R.H.

Molecular recognition, via non-covalent processes such as hydrogen bonding, {pi}-{pi}, and hydrophobic interactions, is an important biological phenomenon for guests, such as drugs, proteins, and other important biological molecules with, for example, host DNA/RNA. We have studied a novel molecular recognition process using guests that encompass aromatic and aliphatic amino acids [L-alanine, L-glutamine (L-Gln), L-histidine, L-isoleucine(L-Ile), L-leucine(L-Leu), L-phenylalanine(L-Phe), L-proline, L-tryptophan(L-Trp), L-valine(L-Val)], substituted aromatic carboxylic acids o-, m-, p-aminobenzoic acids (G1-3), benzoic acid (G4), phenylacetic acid (G5), p-methoxyphenylacetic acid (G6), o-methyoxybenozoic acid (G9), o-nitrobenzoic acid (G10), and aliphatic carboxylic acids [cyclohexylacetic acid (G7), 1-adamantanecarboxylic acid (G8)] with supramolecular, bioorganometallic hosts, ({eta}{supmore » 5}-pentamethylcyclopentadienyl)rhodium (Cp{sup *}Rh)-nucleobase, nucleoside, and nucleotide cyclic trimer complexes in aqueous solution at pH 7, utilizing {sup 1}H NMR, NOE, and molecular modeling techniques, and, as well, determining association constants (K{sub a}) and free energies of complexation ({Delta}{degree}G). The host-guest complexation occurs predominantly via non-covalent {pi}-{pi}, hydrophobic, and possible subtle H-bonding interactions, with steric, electronic, and molecular conformational parameters as important criteria. 8 refs., 6 figs., 3 tabs.« less

[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.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

A Diagnostic Assessment for Introductory Molecular and Cell Biology

PubMed Central

Wood, William B.; Martin, Jennifer M.; Guild, Nancy A.; Vicens, Quentin; Knight, Jennifer K.

2010-01-01

We have developed and validated a tool for assessing understanding of a selection of fundamental concepts and basic knowledge in undergraduate introductory molecular and cell biology, focusing on areas in which students often have misconceptions. This multiple-choice Introductory Molecular and Cell Biology Assessment (IMCA) instrument is designed for use as a pre- and posttest to measure student learning gains. To develop the assessment, we first worked with faculty to create a set of learning goals that targeted important concepts in the field and seemed likely to be emphasized by most instructors teaching these subjects. We interviewed students using open-ended questions to identify commonly held misconceptions, formulated multiple-choice questions that included these ideas as distracters, and reinterviewed students to establish validity of the instrument. The assessment was then evaluated by 25 biology experts and modified based on their suggestions. The complete revised assessment was administered to more than 1300 students at three institutions. Analysis of statistical parameters including item difficulty, item discrimination, and reliability provides evidence that the IMCA is a valid and reliable instrument with several potential uses in gauging student learning of key concepts in molecular and cell biology. PMID:21123692

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.

Towards a minimal stochastic model for a large class of diffusion-reactions on biological membranes.

PubMed

Chevalier, Michael W; El-Samad, Hana

2012-08-28

Diffusion of biological molecules on 2D biological membranes can play an important role in the behavior of stochastic biochemical reaction systems. Yet, we still lack a fundamental understanding of circumstances where explicit accounting of the diffusion and spatial coordinates of molecules is necessary. In this work, we illustrate how time-dependent, non-exponential reaction probabilities naturally arise when explicitly accounting for the diffusion of molecules. We use the analytical expression of these probabilities to derive a novel algorithm which, while ignoring the exact position of the molecules, can still accurately capture diffusion effects. We investigate the regions of validity of the algorithm and show that for most parameter regimes, it constitutes an accurate framework for studying these systems. We also document scenarios where large spatial fluctuation effects mandate explicit consideration of all the molecules and their positions. Taken together, our results derive a fundamental understanding of the role of diffusion and spatial fluctuations in these systems. Simultaneously, they provide a general computational methodology for analyzing a broad class of biological networks whose behavior is influenced by diffusion on membranes.

Continuous flow stable isotope methods for study of δ13C fractionation during halomethane production and degradation

USGS Publications Warehouse

Kalin, Robert M.; Hamilton, John T.G.; Harper, David B.; Miller, Laurence G.; Lamb, Clare; Kennedy, James T.; Downey, Angela; McCauley, Sean; Goldstein, Allen H.

2001-01-01

Gas chromatography/mass spectrometry/isotope ratio mass spectrometry (GC/MS/IRMS) methods for δ13C measurement of the halomethanes CH3Cl, CH3Br, CH3I and methanethiol (CH3SH) during studies of their biological production, biological degradation, and abiotic reactions are presented. Optimisation of gas chromatographic parameters allowed the identification and quantification of CO2, O2, CH3Cl, CH3Br, CH3I and CH3SH from a single sample, and also the concurrent measurement of δ13C for each of the halomethanes and methanethiol. Precision of δ13C measurements for halomethane standards decreased (±0.3, ±0.5 and ±1.3‰) with increasing mass (CH3Cl, CH3Br, CH3I, respectively). Given that carbon isotope effects during biological production, biological degradation and some chemical (abiotic) reactions can be as much as 100‰, stable isotope analysis offers a precise method to study the global sources and sinks of these halogenated compounds that are of considerable importance to our understanding of stratospheric ozone destruction. 

[Dosimetric aspects in studying the biological action of nonionizing electromagnetic radiation].

PubMed

Karpov, V N; Galkin, A A; Davydov, B I

1984-01-01

In order to clarify mechanisms of biological reactions, it is very important to study the absorption and spatial distribution of the absorbed electromagnetic energy. The procedures and methods of calculating the electromagnetic energy absorption of biological specimens exposed to nonionizing electromagnetic irradiation in a wide frequency range (0-300 GHz) are described. Also presented are formulas and plots to be used in calculating the specific absorption of the dose rate by biological specimens, with the inclusion of resonance absorption, polarization of the incident electromagnetic wave, presence of reflecting surfaces and grounding. The extrapolation of the average energy absorption from one animal species to another and to man is discussed, assuming that spatial and energy distributions are equivalent. The notion of the irradiation quality coefficient is introduced. The magnitudes of the coefficients are given as related to the irradiation frequency and polarization type. A mathematical relation is offered to determine the safety of a complex spectrum of electromagnetic irradiation. The relation takes into consideration different dimensionality of the parameters of the electromagnetic field in the low- and high-frequency ranges.

[Biological treatments for contaminated soils: hydrocarbon contamination. Fungal applications in bioremediation treatment].

PubMed

Martín Moreno, Carmen; González Becerra, Aldo; Blanco Santos, María José

2004-09-01

Bioremediation is a spontaneous or controlled process in which biological, mainly microbiological, methods are used to degrade or transform contaminants to non or less toxic products, reducing the environmental pollution. The most important parameters to define a contaminated site are: biodegradability, contaminant distribution, lixiviation grade, chemical reactivity of the contaminants, soil type and properties, oxygen availability and occurrence of inhibitory substances. Biological treatments of organic contaminations are based on the degradative abilities of the microorganisms. Therefore the knowledge on the physiology and ecology of the biological species or consortia involved as well as the characteristics of the polluted sites are decisive factors to select an adequate biorremediation protocol. Basidiomycetes which cause white rot decay of wood are able to degrade lignin and a variety of environmentally persistent pollutants. Thus, white rot fungi and their enzymes are thought to be useful not only in some industrial process like biopulping and biobleaching but also in bioremediation. This paper provides a review of different aspects of bioremediation technologies and recent advances on ligninolytic metabolism research.

The influence of the ocean circulation state on ocean carbon storage and CO2 drawdown potential in an Earth system model

NASA Astrophysics Data System (ADS)

Ödalen, Malin; Nycander, Jonas; Oliver, Kevin I. C.; Brodeau, Laurent; Ridgwell, Andy

2018-03-01

During the four most recent glacial cycles, atmospheric CO2 during glacial maxima has been lowered by about 90-100 ppm with respect to interglacials. There is widespread consensus that most of this carbon was partitioned in the ocean. It is, however, still debated which processes were dominant in achieving this increased carbon storage. In this paper, we use an Earth system model of intermediate complexity to explore the sensitivity of ocean carbon storage to ocean circulation state. We carry out a set of simulations in which we run the model to pre-industrial equilibrium, but in which we achieve different states of ocean circulation by changing forcing parameters such as wind stress, ocean diffusivity and atmospheric heat diffusivity. As a consequence, the ensemble members also have different ocean carbon reservoirs, global ocean average temperatures, biological pump efficiencies and conditions for air-sea CO2 disequilibrium. We analyse changes in total ocean carbon storage and separate it into contributions by the solubility pump, the biological pump and the CO2 disequilibrium component. We also relate these contributions to differences in the strength of the ocean overturning circulation. Depending on which ocean forcing parameter is tuned, the origin of the change in carbon storage is different. When wind stress or ocean diapycnal diffusivity is changed, the response of the biological pump gives the most important effect on ocean carbon storage, whereas when atmospheric heat diffusivity or ocean isopycnal diffusivity is changed, the solubility pump and the disequilibrium component are also important and sometimes dominant. Despite this complexity, we obtain a negative linear relationship between total ocean carbon and the combined strength of the northern and southern overturning cells. This relationship is robust to different reservoirs dominating the response to different forcing mechanisms. Finally, we conduct a drawdown experiment in which we investigate the capacity for increased carbon storage by artificially maximising the efficiency of the biological pump in our ensemble members. We conclude that different initial states for an ocean model result in different capacities for ocean carbon storage due to differences in the ocean circulation state and the origin of the carbon in the initial ocean carbon reservoir. This could explain why it is difficult to achieve comparable responses of the ocean carbon pumps in model inter-comparison studies in which the initial states vary between models. We show that this effect of the initial state is quantifiable. The drawdown experiment highlights the importance of the strength of the biological pump in the control state for model studies of increased biological efficiency.

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

PubMed Central

2012-01-01

Background An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge. PMID:22578440

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.

Entangled Parametric Hierarchies: Problems for an Overspecified Universal Grammar

PubMed Central

Boeckx, Cedric; Leivada, Evelina

2013-01-01

This study addresses the feasibility of the classical notion of parameter in linguistic theory from the perspective of parametric hierarchies. A novel program-based analysis is implemented in order to show certain empirical problems related to these hierarchies. The program was developed on the basis of an enriched data base spanning 23 contemporary and 5 ancient languages. The empirical issues uncovered cast doubt on classical parametric models of language acquisition as well as on the conceptualization of an overspecified Universal Grammar that has parameters among its primitives. Pinpointing these issues leads to the proposal that (i) the (bio)logical problem of language acquisition does not amount to a process of triggering innately pre-wired values of parameters and (ii) it paves the way for viewing language, epigenetic (‘parametric’) variation as an externalization-related epiphenomenon, whose learning component may be more important than what sometimes is assumed. PMID:24019867

Influence of Femtosecond Laser Parameters and Environment on Surface Texture Characteristics of Metals and Non-Metals - State of the Art

NASA Astrophysics Data System (ADS)

Bharatish, A.; Soundarapandian, S.

2018-04-01

Enhancing the surface functionality by ultrashort pulsed laser texturing has received the considerable attention from researchers in the past few decades. Femtosecond lasers are widely adopted since it provides high repeatability and reproducibility by minimizing the heat affected zone (HAZ) and other collateral damages to a great extent. The present paper reports some recent studies being made worldwide on femtosecond laser surface texturing of metals, ceramics, polymers, semiconductors, thinfilms and advanced nanocomposites. It presents the state of the art knowledge in femtosecond laser surface texturing and the potential of this technology to improve properties in terms of biological, tribological and wetting performance. Since the texture quality and functionality are enhanced by the proper selection of appropriate laser parameters and ambient conditions for individual application, reporting the influence of laser parameters on surface texture characteristics assume utmost importance.

Influence of Femtosecond Laser Parameters and Environment on Surface Texture Characteristics of Metals and Non-Metals - State of the Art

NASA Astrophysics Data System (ADS)

Bharatish, A.; Soundarapandian, S.

2018-06-01

Enhancing the surface functionality by ultrashort pulsed laser texturing has received the considerable attention from researchers in the past few decades. Femtosecond lasers are widely adopted since it provides high repeatability and reproducibility by minimizing the heat affected zone (HAZ) and other collateral damages to a great extent. The present paper reports some recent studies being made worldwide on femtosecond laser surface texturing of metals, ceramics, polymers, semiconductors, thinfilms and advanced nanocomposites. It presents the state of the art knowledge in femtosecond laser surface texturing and the potential of this technology to improve properties in terms of biological, tribological and wetting performance. Since the texture quality and functionality are enhanced by the proper selection of appropriate laser parameters and ambient conditions for individual application, reporting the influence of laser parameters on surface texture characteristics assume utmost importance.

Effects of C/N ratio on nitrous oxide production from nitrification in a laboratory-scale biological aerated filter reactor.

PubMed

He, Qiang; Zhu, Yinying; Fan, Leilei; Ai, Hainan; Huangfu, Xiaoliu; Chen, Mei

2017-03-01

Emission of nitrous oxide (N 2 O) during biological wastewater treatment is of growing concern. This paper reports findings of the effects of carbon/nitrogen (C/N) ratio on N 2 O production rates in a laboratory-scale biological aerated filter (BAF) reactor, focusing on the biofilm during nitrification. Polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and microelectrode technology were utilized to evaluate the mechanisms associated with N 2 O production during wastewater treatment using BAF. Results indicated that the ability of N 2 O emission in biofilm at C/N ratio of 2 was much stronger than at C/N ratios of 5 and 8. PCR-DGGE analysis showed that the microbial community structures differed completely after the acclimatization at tested C/N ratios (i.e., 2, 5, and 8). Measurements of critical parameters including dissolved oxygen, oxidation reduction potential, NH 4 + -N, NO 3 - -N, and NO 2 - -N also demonstrated that the internal micro-environment of the biofilm benefit N 2 O production. DNA analysis showed that Proteobacteria comprised the majority of the bacteria, which might mainly result in N 2 O emission. Based on these results, C/N ratio is one of the parameters that play an important role in the N 2 O emission from the BAF reactors during nitrification.

Analysis of cortical bone porosity using synchrotron radiation microtomography to evaluate the effects of chemotherapy

NASA Astrophysics Data System (ADS)

Alessio, R.; Nogueira, L. P.; Salata, C.; Mantuano, A.; Almeida, A. P.; Braz, D.; de Almeida, C. E.; Tromba, G.; Barroso, R. C.

2015-11-01

Microporosities play important biologic and mechanical roles on health. One of the side effects caused by some chemotherapy drugs is the induction of amenorrhea, temporary or not, in premenopausal women, with a consequent decrease in estrogen production, which can lead to cortical bone changes. In the present work, the femur diaphysis of rats treated with chemotherapy drugs were evaluated by 3D morphometric parameters using synchrotron radiation microtomography. Control animals were also evaluated for comparison. The 3D tomographic images were obtained at the SYRMEP (SYnchrotron Radiation for MEdical Physics) beamline at the ELETTRA Synchrotron Laboratory in Trieste, Italy. Results showed significant differences in morphometric parameters measured from the 3D images of femur diaphysis of rats.

Longevity and aging. Mechanisms and perspectives.

PubMed

Labat-Robert, J; Robert, L

2015-12-01

Longevity can mostly be determined with relative accuracy from birth and death registers when available. Aging is a multifactorial process, much more difficult to quantitate. Every measurable physiological function declines with specific speeds over a wide range. The mechanisms involved are also different, genetic factors are of importance for longevity determinations. The best-known genes involved are the Sirtuins, active at the genetic and epigenetic level. Aging is multifactorial, not "coded" in the genome. There are, however, a number of well-studied physical and biological parameters involved in aging, which can be determined and quantitated. We shall try to identify parameters affecting longevity as well as aging and suggest some reasonable predictions for the future. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

An approach to the coastal water circulation in the Piratuba Lake Biological Reservation, Northeast of Amapa State, Brazil

NASA Astrophysics Data System (ADS)

Takiyama, L. R.; Silveira, O. M.

2007-05-01

This study shows the pioneer results of the water quality characterization of a lake region, including the Piratuba lake (within the limits of the Piratuba Lake Biological Reservation) and the Sucuriju river, localized at the northeast portion of the Amapa State, Brazil, and left margin of the Amazon River mouth. Due to the influence of the Amazon river and another important river, the Araguari river, the northeast coast of Amapa State receive little impact of salty water from the Atlantic ocean. The highest salinity values detected on this coastal area is 20 psu. The Piratuba Lake region which can be described as an unique wetland system formed by recent geological processes (Quaternary), it constitutes a very fragile environment and possesses a number of shallow water lakes distributed into a mixed mangrove and "varzea" type of vegetation and it is considered very important looking at the biological point of view. The borderline between this lake system with the coastal waters is a narrow portion of mangrove containing species of Rizhophora and Avicennia parallel to the coast line. A preliminary water circulation could be accessed through the detection of variation in water quality parameters throughout three field studies conducted on March, 2004, June 2005 and November 2005. Surface water sampling points spatially distributed on the study area with distances less than 2 km were set, covering almost 800 square kilometers. Among the parameters studied (pH, electrical conductivity, turbidity, concentration of suspended solids, depth, temperature, chloride, dissolved oxygen, nitrate, nitrite and phosphate) the turbidity, electrical conductivity and pH were the most important for identifying the entering of coastal waters into the lake region. Mainly, three points of direct contact were identified; one of them is a manmade illegal entrance to the Biological Reservation. The seasonal variation was also very important factor and as expected, during the dry season (July to November, represented by the study on November 2006), we could measured the highest values of conductivity, pH and turbidity in many of the lakes sampled. The implications of understanding, even preliminarily the water circulation in the study area is related to the influence onto the freshwater living species, environemtnal conservation management purposes, geomorphology process indicator and the possible biogeochemical exchanges dynamics, once the Amazon waters can be nutrient rich and the lake waters apparently have high dissolved organic carbon content.

Analytical approaches to determination of carnitine in biological materials, foods and dietary supplements.

PubMed

Dąbrowska, Monika; Starek, Małgorzata

2014-01-01

l-Carnitine is a vitamin-like amino acid derivative, which is an essential factor in fatty acid metabolism as acyltransferase cofactor and in energy production processes, such as interconversion in the mechanisms of regulation of cetogenesis and termogenesis, and it is also used in the therapy of primary and secondary deficiency, and in other diseases. The determination of carnitine and acyl-carnitines can provide important information about inherited or acquired metabolic disorders, and for monitoring the biochemical effect of carnitine therapy. The endogenous carnitine pool in humans is maintained by biosynthesis and absorption of carnitine from the diet. Carnitine has one asymmetric carbon giving two stereoisomers d and l, but only the l form has a biological positive effect, thus chiral recognition of l-carnitine enantiomers is extremely important in biological, chemical and pharmaceutical sciences. In order to get more insight into carnitine metabolism and synthesis, a sensitive analysis for the determination of the concentration of free carnitine, carnitine esters and the carnitine precursors is required. Carnitine has been investigated in many biochemical, pharmacokinetic, metabolic and toxicokinetic studies and thus many analytical methods have been developed and published for the determination of carnitine in foods, dietary supplements, pharmaceutical formulations, biological tissues and body fluid. The analytical procedures presented in this review have been validated in terms of basic parameters (linearity, limit of detection, limit of quantitation, sensitivity, accuracy, and precision). This article presented the impact of different analytical techniques, and provides an overview of applications that address a diverse array of pharmaceutical and biological questions and samples. Copyright © 2013 Elsevier Ltd. All rights reserved.

The oxalate-carbonate pathway: at the interface between biology and geology

NASA Astrophysics Data System (ADS)

Junier, P.; Cailleau, G.; Martin, G.; Guggiari, M.; Bravo, D.; Clerc, M.; Aragno, M.; Job, D.; Verrecchia, E.

2012-04-01

The formation of calcite in otherwise carbonate-free acidic soils through the biological degradation of oxalate is a mechanism termed oxalate-carbonate pathway. This pathway lies at the interface between biological and geological systems and constitutes an important, although underestimated, soil mineral carbon sink. In this case, atmospheric CO2 is fixed by the photosynthetic activity of oxalogenic plants, which is partly destined to the production of oxalate used for the chelation of metals, and particularly, calcium. Fungi are also able to produce oxalate to cope with elevated concentrations of metals. In spite of its abundance as a substrate, oxalate is a very stable organic anion that can be metabolized only by a group of bacteria that use it as carbon and energy sources. These bacteria close the biological cycle by degrading calcium oxalate, releasing Ca2+ and inducing a change in local soil pH. If parameters are favourable, the geological part of the pathway begins, because this change in pH will indirectly lead to the precipitation of secondary calcium carbonate (calcite) in unexpected geological conditions. Due to the initial acidic soil conditions, and the absence of geological carbonate in the basement, it is unexpected to find C in the form of calcite. The activity of the oxalate-carbonate pathway has now been demonstrated in several places around the world, suggesting that its importance can be even greater than expected. In addition, new roles for each of the biological players of the pathway have been revealed recently forcing us to reconsider a global biogeochemical model for oxalate cycling.

[Influence of iron nanoparticles on cardiac performance and hemodynamics in rabbits after intravenous administration in acute experiment].

PubMed

Doroshenko, A M

2014-01-01

Iron nanoparticles are possessed by high potential in the creation of effective and safe antianemic drugs due to the enhanced biological activity of metal nanoparticles. As a step of intravenous dosage form development the study of short-term effects of iron nanoparticles on the cardiovascular system is important. Dose-dependent changes of systemic hemodynamics' parameters were established in acute experiment on rabbits after several intravenous injections of zero-valent iron nanoparticles solution.

Synchronisation of chaos and its applications

NASA Astrophysics Data System (ADS)

Eroglu, Deniz; Lamb, Jeroen S. W.; Pereira, Tiago

2017-07-01

Dynamical networks are important models for the behaviour of complex systems, modelling physical, biological and societal systems, including the brain, food webs, epidemic disease in populations, power grids and many other. Such dynamical networks can exhibit behaviour in which deterministic chaos, exhibiting unpredictability and disorder, coexists with synchronisation, a classical paradigm of order. We survey the main theory behind complete, generalised and phase synchronisation phenomena in simple as well as complex networks and discuss applications to secure communications, parameter estimation and the anticipation of chaos.

Laboratory simulations of Martian surface parameters and the biological response of terrestrial model organisms to 'extreme' environments

NASA Astrophysics Data System (ADS)

Rettberg, P.; Moller, R.; Pogoda de La Vega, U.; Rabbow, E.; Panitz, C.; Mohlmann, D.; Reitz, G.

For the development of adequate instruments and methods for in situ life detection analysis and for the avoidance of contaminating of Mars by terrestrial life forms introduced to it's surface unintentionally, it is necessary to understand the potential and limits of life on Earth. Whereas it is possible to test most of the environmental parameters of Mars separately in the laboratory, like diurnal and seasonal temperature cyles, pressure, atmospheric composition, and to investigate their biological effects in detail, it is technically more difficult to simulate two or more parameters at the same time. The realistic simulation of a complete Martian surface environment is a considerable technical challenge. It is especially difficult to reproduce the Martian UV climate realistically. Up to now no total Mars simulation was performed in one single experiment which should include diurnal cycles of temperature, UV radiation and humidity in a simulated Martian atmosphere and at Martian pressure, with Martian soil analogues, dust particles, and ionising radiation. However, it is absolutely essential to investigate the biological effects of combined environmental parameters, because it is already known for some cases that biological effects might not necessarily be additive, but can be synergistic or antagonistic. A prominent example is the synergistic effect of vacuum and UV radiation on the survivability of B. subtilis spores. From several investigations in the last decades the Martian UV climate with it's energy-rich short-wavelength radiation down to 200 nm turned out to be the most important deleterious environmental parameter on Mars. Direct UV exposure caused a rapid and nearly complete inactivation of spores. However, thin layers of Martian soil analogue material, like simulated standard Mars JSC-1 or Fe-montmorillonite, are sufficient to shield spores from the deleterious effects of UV radiation. From these results it can be concluded that in spite of the destructive UV climate at least a part of a microbial population might be able to escape the inactiviation by UV radiation, if covered accidentally by Martian dust and soil particles. Up to now the molecular basis of the strong oxidizing properties of Martian soil found 1 by the Viking landers is not completely understood. This chemical reactivity capable of decomposing organic molecules was attributed to the presence of one or more as- yet-unidentified inorganic superoxides or peroxides in the Martian soil. The biological consequences of these photochemical reactions are not yet investigated in detail, although it is known that B. subtilis spores are able to withstand oxidative conditions to a certain degree. The determination of the survival of microorganisms under the physical and chemical `extremes' of Mars will provide detailed insights into the potential for contamination that will allow the development and improvement of planetary protection measures. 2

Spacecraft cabin environment effects on the growth and behavior of Chlorella vulgaris for life support applications

NASA Astrophysics Data System (ADS)

Niederwieser, Tobias; Kociolek, Patrick; Klaus, David

2018-02-01

An Environmental Control and Life Support System (ECLSS) is necessary for humans to survive in the hostile environment of space. As future missions move beyond Earth orbit for extended durations, reclaiming human metabolic waste streams for recycled use becomes increasingly important. Historically, these functions have been accomplished using a variety of physical and chemical processes with limited recycling capabilities. In contrast, biological systems can also be incorporated into a spacecraft to essentially mimic the balance of photosynthesis and respiration that occurs in Earth's ecosystem, along with increasing the reuse of biomass throughout the food chain. In particular, algal photobioreactors that use Chlorella vulgaris have been identified as potential multifunctional components for use as part of such a bioregenerative life support system (BLSS). However, a connection between the biological research examining C. vulgaris behavior and the engineered spacecraft cabin environmental conditions has not yet been thoroughly established. This review article characterizes the ranges of prior and expected cabin parameters (e.g. temperature, lighting, carbon dioxide, pH, oxygen, pressure, growth media, contamination, gravity, and radiation) and reviews algal metabolic response (e.g. growth rate, composition, carbon dioxide fixation rates, and oxygen evolution rates) to changes in those parameters that have been reported in prior space research and from related Earth-based experimental observations. Based on our findings, it appears that C. vulgaris offers many promising advantages for use in a BLSS. Typical atmospheric conditions found in spacecraft such as elevated carbon dioxide levels are, in fact, beneficial for algal cultivation. Other spacecraft cabin parameters, however, introduce unique environmental factors, such as reduced total pressure with elevated oxygen concentration, increased radiation, and altered gravity, whose effects on the biological responses of C. vulgaris are not yet well understood. A summary of optimum growth parameter ranges for C. vulgaris is presented in this article as a guideline for designing and integrating an algal photobioreactor into a spacecraft life support system. Additional research challenges for evaluating as of yet uncharacterized parameters are also identified in this article that have the potential for improving spaceflight applications as well as terrestrial aquatic algal cultivation systems.

MONALISA for stochastic simulations of Petri net models of biochemical systems.

PubMed

Balazki, Pavel; Lindauer, Klaus; Einloft, Jens; Ackermann, Jörg; Koch, Ina

2015-07-10

The concept of Petri nets (PN) is widely used in systems biology and allows modeling of complex biochemical systems like metabolic systems, signal transduction pathways, and gene expression networks. In particular, PN allows the topological analysis based on structural properties, which is important and useful when quantitative (kinetic) data are incomplete or unknown. Knowing the kinetic parameters, the simulation of time evolution of such models can help to study the dynamic behavior of the underlying system. If the number of involved entities (molecules) is low, a stochastic simulation should be preferred against the classical deterministic approach of solving ordinary differential equations. The Stochastic Simulation Algorithm (SSA) is a common method for such simulations. The combination of the qualitative and semi-quantitative PN modeling and stochastic analysis techniques provides a valuable approach in the field of systems biology. Here, we describe the implementation of stochastic analysis in a PN environment. We extended MONALISA - an open-source software for creation, visualization and analysis of PN - by several stochastic simulation methods. The simulation module offers four simulation modes, among them the stochastic mode with constant firing rates and Gillespie's algorithm as exact and approximate versions. The simulator is operated by a user-friendly graphical interface and accepts input data such as concentrations and reaction rate constants that are common parameters in the biological context. The key features of the simulation module are visualization of simulation, interactive plotting, export of results into a text file, mathematical expressions for describing simulation parameters, and up to 500 parallel simulations of the same parameter sets. To illustrate the method we discuss a model for insulin receptor recycling as case study. We present a software that combines the modeling power of Petri nets with stochastic simulation of dynamic processes in a user-friendly environment supported by an intuitive graphical interface. The program offers a valuable alternative to modeling, using ordinary differential equations, especially when simulating single-cell experiments with low molecule counts. The ability to use mathematical expressions provides an additional flexibility in describing the simulation parameters. The open-source distribution allows further extensions by third-party developers. The software is cross-platform and is licensed under the Artistic License 2.0.

Chasing Perfection: Should We Reduce Model Uncertainty in Carbon Cycle-Climate Feedbacks

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Lombardozzi, D.; Wieder, W. R.; Lindsay, K. T.; Thomas, R. Q.

2015-12-01

Earth system model simulations of the terrestrial carbon (C) cycle show large multi-model spread in the carbon-concentration and carbon-climate feedback parameters. Large differences among models are also seen in their simulation of global vegetation and soil C stocks and other aspects of the C cycle, prompting concern about model uncertainty and our ability to faithfully represent fundamental aspects of the terrestrial C cycle in Earth system models. Benchmarking analyses that compare model simulations with common datasets have been proposed as a means to assess model fidelity with observations, and various model-data fusion techniques have been used to reduce model biases. While such efforts will reduce multi-model spread, they may not help reduce uncertainty (and increase confidence) in projections of the C cycle over the twenty-first century. Many ecological and biogeochemical processes represented in Earth system models are poorly understood at both the site scale and across large regions, where biotic and edaphic heterogeneity are important. Our experience with the Community Land Model (CLM) suggests that large uncertainty in the terrestrial C cycle and its feedback with climate change is an inherent property of biological systems. The challenge of representing life in Earth system models, with the rich diversity of lifeforms and complexity of biological systems, may necessitate a multitude of modeling approaches to capture the range of possible outcomes. Such models should encompass a range of plausible model structures. We distinguish between model parameter uncertainty and model structural uncertainty. Focusing on improved parameter estimates may, in fact, limit progress in assessing model structural uncertainty associated with realistically representing biological processes. Moreover, higher confidence may be achieved through better process representation, but this does not necessarily reduce uncertainty.

Distribution of hydro-biological parameters in coastal waters off Rushikulya Estuary, East Coast of India: a premonsoon case study.

PubMed

Baliarsingh, S K; Srichandan, S; Naik, S; Sahu, K C; Lotliker, Aneesh A; Kumar, T S

2013-08-15

The hydro-biological parameters of coastal waters off Rushikulya estuary was investigated during premonsoon 2011. Important hydro-biological parameters such as water temperature, salinity, pH, DO, NO2, NO3, NH4, PO4, SiO4, TSM, Chl-a, phytoplankton and zooplankton were measured during the present study. Temperature established a strong positive correlation with salinity and pH during the present study. Chl-a found in positive relation with NO3, SiO, and TSM. Analysis of variance revealed significant monthly variation in pH, salinity and TSM. Significant station wise variation was observed in DO and most of the nutrients i.e., NO3, NH4, PO4, SiO4. A total of 119 species of phytoplankton were identified of which 84 species are of diatoms, 22 species of dinoflagellates, 7 species of green algae, 5 species of cyanobacteria (blue green algae) and 1 species of cocolithophore. Phytoplankton abundance varied between 25543 (Nos. L(-1)) and 36309 (Nos. L(-1)). Diatoms dominated the phytoplankton community followed by dinoflagellates in all the months. Diatoms contributed to 82-89% of the total phytoplankton population density whereas dinoflagellates contributed to 6-12%. The regression between Chl-a and phytoplankton abundance resulted with weak relation (R(2) = 0.042). Zooplankton fauna composed of 134 species of holoplankton and 20 types of meroplankton were encountered during the study period. Zooplankton population dominated by copepod during all months and accounted for 74 to 85% to the total zooplankton. The population density ranged from 6959 to 35869 Nos./10 m(3). Analysis of variance explained no significant variation in total zooplankton abundance and also for different groups of zooplankton.

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.

Treatment of ankylosing spondylitis with biologics and targeted physical therapy: positive effect on chest pain, diminished chest mobility, and respiratory function.

PubMed

Gyurcsik, Z; Bodnár, N; Szekanecz, Z; Szántó, S

2013-12-01

Biologics are highly effective in ankylosing spondylitis (AS). In this self-controlled study, we assessed the additive value of complex physiotherapy in decreasing chest pain and tenderness and improving respiratory function in AS patients treated with tumor necrosis factor α (TNF-α) inhibitors. The trial consisted of 2 parts. In study I, clinical data of AS patients with (n=55) or without biological therapy (n=20) were retrospectively analyzed and compared. Anthropometrical data, duration since diagnosis and patient assessment of disease activity, pain intensity, tender points, sacroiliac joint involvement determined by X-ray, functional condition, and physical activity level were recorded. Subjective, functional, and physical tests were performed. In study II, 10 voluntary patients (6 men and 4 women, age 52.4 ± 13.6 years) with definite AS and receiving anti-TNF therapy were recruited. It was a prospective, non-randomized physiotherapeutic trial. BASFI (Bath Ankylosing Spondylitis Functional Index), BASDAI (Bath Ankylosing Spondylitis Disease Activity Index), modified Schober Index, occiput-to-wall distance, and fingertip-to-floor distance were evaluated. Forced vital capacity, forced 1-s expiratory volume, peak expiratory flow, and maximum voluntary ventilation were recorded. Furthermore, typical tender points were recorded. A targeted physiotherapy program was conducted twice a week for 12 weeks and all above parameters were recorded at baseline and after 12 weeks. Differences in patient assessment of disease activity (p=0.019) and pain intensity (p=0.017) were found in study I. Pain and tenderness of the thoracic spine were observed in both groups. Back pain without biologic therapy was slightly higher than other group. In study II, we found that patient assessment of disease activity and pain intensity significantly improved after the physical therapy program (p=0.002 and p<0.001). BASFI and BASDAI increased after treatment (p=0.004 and p<0.001). The finger-to-floor distance, chest expansion, and modified Schober index increased (p=0.008, p<0.001, and p=0.031, respectively). The respiratory functional parameters showed a tendency towards improvement. AS patients already receiving biological therapy may benefit from additional targeted physiotherapy. Physical therapy may be of important additive value in AS patients being treated with biological. The exercise program presented here showed an improvement in functional parameters as well as spine and chest mobility, thereby enhancing the favorable effects of biological therapy.

Parameter Sensitivity and Laboratory Benchmarking of a Biogeochemical Process Model for Enhanced Anaerobic Dechlorination

NASA Astrophysics Data System (ADS)

Kouznetsova, I.; Gerhard, J. I.; Mao, X.; Barry, D. A.; Robinson, C.; Brovelli, A.; Harkness, M.; Fisher, A.; Mack, E. E.; Payne, J. A.; Dworatzek, S.; Roberts, J.

2008-12-01

A detailed model to simulate trichloroethene (TCE) dechlorination in anaerobic groundwater systems has been developed and implemented through PHAST, a robust and flexible geochemical modeling platform. The approach is comprehensive but retains flexibility such that models of varying complexity can be used to simulate TCE biodegradation in the vicinity of nonaqueous phase liquid (NAPL) source zones. The complete model considers a full suite of biological (e.g., dechlorination, fermentation, sulfate and iron reduction, electron donor competition, toxic inhibition, pH inhibition), physical (e.g., flow and mass transfer) and geochemical processes (e.g., pH modulation, gas formation, mineral interactions). Example simulations with the model demonstrated that the feedback between biological, physical, and geochemical processes is critical. Successful simulation of a thirty-two-month column experiment with site soil, complex groundwater chemistry, and exhibiting both anaerobic dechlorination and endogenous respiration, provided confidence in the modeling approach. A comprehensive suite of batch simulations was then conducted to estimate the sensitivity of predicted TCE degradation to the 36 model input parameters. A local sensitivity analysis was first employed to rank the importance of parameters, revealing that 5 parameters consistently dominated model predictions across a range of performance metrics. A global sensitivity analysis was then performed to evaluate the influence of a variety of full parameter data sets available in the literature. The modeling study was performed as part of the SABRE (Source Area BioREmediation) project, a public/private consortium whose charter is to determine if enhanced anaerobic bioremediation can result in effective and quantifiable treatment of chlorinated solvent DNAPL source areas. The modelling conducted has provided valuable insight into the complex interactions between processes in the evolving biogeochemical systems, particularly at the laboratory scale.

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.

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.

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.

Interpreting Microbial Biosynthesis in the Genomic Age: Biological and Practical Considerations

PubMed Central

Miller, Ian J.; Chevrette, Marc G.; Kwan, Jason C.

2017-01-01

Genome mining has become an increasingly powerful, scalable, and economically accessible tool for the study of natural product biosynthesis and drug discovery. However, there remain important biological and practical problems that can complicate or obscure biosynthetic analysis in genomic and metagenomic sequencing projects. Here, we focus on limitations of available technology as well as computational and experimental strategies to overcome them. We review the unique challenges and approaches in the study of symbiotic and uncultured systems, as well as those associated with biosynthetic gene cluster (BGC) assembly and product prediction. Finally, to explore sequencing parameters that affect the recovery and contiguity of large and repetitive BGCs assembled de novo, we simulate Illumina and PacBio sequencing of the Salinispora tropica genome focusing on assembly of the salinilactam (slm) BGC. PMID:28587290

The spectroscopic search for the trace aerosols in the planetary atmospheres - the results of numerical simulations

NASA Astrophysics Data System (ADS)

Blecka, Maria I.

2010-05-01

The passive remote spectrometric methods are important in examinations the atmospheres of planets. The radiance spectra inform us about values of thermodynamical parameters and composition of the atmospheres and surfaces. The spectral technology can be useful in detection of the trace aerosols like biological substances (if present) in the environments of the planets. We discuss here some of the aspects related to the spectroscopic search for the aerosols and dust in planetary atmospheres. Possibility of detection and identifications of biological aerosols with a passive InfraRed spectrometer in an open-air environment is discussed. We present numerically simulated, based on radiative transfer theory, spectroscopic observations of the Earth atmosphere. Laboratory measurements of transmittance of various kinds of aerosols, pollens and bacterias were used in modeling.

Microbial Diversity and Structure Are Drivers of the Biological Barrier Effect against Listeria monocytogenes in Soil

PubMed Central

Vivant, Anne-Laure; Garmyn, Dominique; Maron, Pierre-Alain; Nowak, Virginie; Piveteau, Pascal

2013-01-01

Understanding the ecology of pathogenic organisms is important in order to monitor their transmission in the environment and the related health hazards. We investigated the relationship between soil microbial diversity and the barrier effect against Listeria monocytogenes invasion. By using a dilution-to-extinction approach, we analysed the consequence of eroding microbial diversity on L. monocytogenes population dynamics under standardised conditions of abiotic parameters and microbial abundance in soil microcosms. We demonstrated that highly diverse soil microbial communities act as a biological barrier against L. monocytogenes invasion and that phylogenetic composition of the community also has to be considered. This suggests that erosion of diversity may have damaging effects regarding circulation of pathogenic microorganisms in the environment. PMID:24116193

Species-Specific Thiol-Disulfide Equilibrium Constant: A Tool To Characterize Redox Transitions of Biological Importance.

PubMed

Mirzahosseini, Arash; Somlyay, Máté; Noszál, Béla

2015-08-13

Microscopic redox equilibrium constants, a new species-specific type of physicochemical parameters, were introduced and determined to quantify thiol-disulfide equilibria of biological significance. The thiol-disulfide redox equilibria of glutathione with cysteamine, cysteine, and homocysteine were approached from both sides, and the equilibrium mixtures were analyzed by quantitative NMR methods to characterize the highly composite, co-dependent acid-base and redox equilibria. The directly obtained, pH-dependent, conditional constants were then decomposed by a new evaluation method, resulting in pH-independent, microscopic redox equilibrium constants for the first time. The 80 different, microscopic redox equilibrium constant values show close correlation with the respective thiolate basicities and provide sound means for the development of potent agents against oxidative stress.

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.

Clinico-pathological and biological prognostic variables in squamous cell carcinoma of the vulva.

PubMed

Gadducci, Angiolo; Tana, Roberta; Barsotti, Cecilia; Guerrieri, Maria Elena; Genazzani, Andrea Riccardo

2012-07-01

Several clinical-pathological parameters have been related to survival of patients with invasive squamous cell carcinoma of the vulva, whereas few studies have investigated the ability of biological variables to predict the clinical outcome of these patients. The present paper reviews the literature data on the prognostic relevance of lymph node-related parameters, primary tumor-related parameters, FIGO stage, blood variables, and tissue biological variables. Regarding these latter, the paper takes into account the analysis of DNA content, cell cycle-regulatory proteins, apoptosis-related proteins, epidermal growth factor receptor [EGFR], and proteins that are involved in tumor invasiveness, metastasis and angiogenesis. At present, the lymph node status and FIGO stage according to the new 2009 classification system are the main predictors for vulvar squamous cell carcinoma, whereas biological variables do not have yet a clinical relevance and their role is still investigational. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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.

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

Differentiation of K562 cells under ELF-EMF applied at different time courses.

PubMed

Ayşe, Inhan-Garip; Zafer, Akan; Sule, Oncul; Işil, Işal-Turgut; Kalkan, Tunaya

2010-08-01

The time-course of ELF-EMF application to biological systems is thought to be an important parameter determining the physiological outcome. This study investigated the effect of ELF-EMF on the differentiation of K562 cells at different time courses. ELF-EMF (50 Hz, 5 mT, 1 h) was applied at two different time-courses; first at the onset of hemin induction for 1 h, and second, daily 1 h for four days. While single exposure to ELF-EMF resulted in a decrease in differentiation, ELF-EMF applied everyday for 1 h caused an increase in differentiation. The effect of co-stressors, magnesium, and heat-shock was also determined and similar results were obtained. ELF-EMF increased ROS levels in K562 cells not treated with hemin, however did not change ROS levels of hemin treated cells indicating that ROS was not the cause. Overall, these results imply that the time-course of application is an important parameter determining the physiological response of cells to ELF-EMF.

Simulation study and guidelines to generate Laser-induced Surface Acoustic Waves for human skin feature detection

NASA Astrophysics Data System (ADS)

Li, Tingting; Fu, Xing; Chen, Kun; Dorantes-Gonzalez, Dante J.; Li, Yanning; Wu, Sen; Hu, Xiaotang

2015-12-01

Despite the seriously increasing number of people contracting skin cancer every year, limited attention has been given to the investigation of human skin tissues. To this regard, Laser-induced Surface Acoustic Wave (LSAW) technology, with its accurate, non-invasive and rapid testing characteristics, has recently shown promising results in biological and biomedical tissues. In order to improve the measurement accuracy and efficiency of detecting important features in highly opaque and soft surfaces such as human skin, this paper identifies the most important parameters of a pulse laser source, as well as provides practical guidelines to recommended proper ranges to generate Surface Acoustic Waves (SAWs) for characterization purposes. Considering that melanoma is a serious type of skin cancer, we conducted a finite element simulation-based research on the generation and propagation of surface waves in human skin containing a melanoma-like feature, determine best pulse laser parameter ranges of variation, simulation mesh size and time step, working bandwidth, and minimal size of detectable melanoma.

Auditory P300 event related potentials in acute and transient psychosis-Comparison with schizophrenia.

PubMed

Sahoo, Swapnajeet; Malhotra, Savita; Basu, Debasish; Modi, Manish

2016-10-01

Limited biological research data are available on acute and transient psychotic disorder (ATPD) vis-à-vis schizophrenia. P300 event related potentials (ERP) have been extensively studied as an important neurophysiological parameter in schizophrenia. However, no P300 ERP studies comparing the two disorders are available. We compared auditory P300 ERP in patients remitted from ATPD with schizophrenia in remission and biologically unrelated healthy controls. In this case-control study design, 25 subjects remitted from ATPD were age-/gender-matched with healthy controls and patients with schizophrenia in remission. Clinical assessment and auditory P300 ERP (amplitude and latencies at central and parietal sites, reaction time) were recorded. The ERP parameters were compared across the three groups. All three groups showed significant differences in P300 amplitudes and latencies at central and parietal sites. Schizophrenia group differed significantly (p<0.001) from the ATPD group in all the P300 parameters. The ATPD group was found to have lower Pz latency (p<0.05) and lower mean reaction time (p<0.001) as compared to healthy controls. The results suggest that P300 could easily distinguish between ATPD and schizophrenia in remission, thus neurophysiologically differentiating the two disorders. Lower P300 latency and reaction time, which indicate hyper-arousability, distinguished ATPD from normal controls, with implications for a better understanding of ATPD. Copyright © 2016 Elsevier B.V. All rights reserved.

Functional Imaging Biomarkers: Potential to Guide an Individualised Approach to Radiotherapy.

PubMed

Prestwich, R J D; Vaidyanathan, S; Scarsbrook, A F

2015-10-01

The identification of robust prognostic and predictive biomarkers would transform the ability to implement an individualised approach to radiotherapy. In this regard, there has been a surge of interest in the use of functional imaging to assess key underlying biological processes within tumours and their response to therapy. Importantly, functional imaging biomarkers hold the potential to evaluate tumour heterogeneity/biology both spatially and temporally. An ever-increasing range of functional imaging techniques is now available primarily involving positron emission tomography and magnetic resonance imaging. Small-scale studies across multiple tumour types have consistently been able to correlate changes in functional imaging parameters during radiotherapy with disease outcomes. Considerable challenges remain before the implementation of functional imaging biomarkers into routine clinical practice, including the inherent temporal variability of biological processes within tumours, reproducibility of imaging, determination of optimal imaging technique/combinations, timing during treatment and design of appropriate validation studies. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Self-assembly of polyelectrolyte surfactant complexes using large scale MD simulation

NASA Astrophysics Data System (ADS)

Goswami, Monojoy; Sumpter, Bobby

2014-03-01

Polyelectrolytes (PE) and surfactants are known to form interesting structures with varied properties in aqueous solutions. The morphological details of the PE-surfactant complexes depend on a combination of polymer backbone, electrostatic interactions and hydrophobic interactions. We study the self-assembly of cationic PE and anionic surfactants complexes in dilute condition. The importance of such complexes of PE with oppositely charged surfactants can be found in biological systems, such as immobilization of enzymes in polyelectrolyte complexes or nonspecific association of DNA with protein. Many useful properties of PE surfactant complexes come from the highly ordered structures of surfactant self-assembly inside the PE aggregate which has applications in industry. We do large scale molecular dynamics simulation using LAMMPS to understand the structure and dynamics of PE-surfactant systems. Our investigation shows highly ordered pearl-necklace structures that have been observed experimentally in biological systems. We investigate many different properties of PE-surfactant complexation for different parameter ranges that are useful for pharmaceutical, engineering and biological applications.

The role and control of sludge age in biological nutrient removal activated sludge systems.

PubMed

Ekama, G A

2010-01-01

The sludge age is the most fundamental and important parameter in the design, operation and control of biological nutrient removal (BNR) activated sludge (AS) systems. Generally, the better the effluent and waste sludge quality required from the system, the longer the sludge age, the larger the biological reactor and the more wastewater characteristics need to be known. Controlling the reactor concentration does not control sludge age, only the mass of sludge in the system. When nitrification is a requirement, sludge age control becomes a requirement and the secondary settling tanks can no longer serve the dual purpose of clarifier and waste activated sludge thickeners. The easiest and most practical way to control sludge age is with hydraulic control by wasting a defined proportion of the reactor volume daily. In AS plants with reactor concentration control, nitrification fails first. With hydraulic control of sludge age, nitrification will not fail, rather the plant fails by shedding solids over the secondary settling tank effluent weirs.

A stochastic multicellular model identifies biological watermarks from disorders in self-organized patterns of phyllotaxis

PubMed Central

Refahi, Yassin; Brunoud, Géraldine; Farcot, Etienne; Jean-Marie, Alain; Pulkkinen, Minna; Vernoux, Teva; Godin, Christophe

2016-01-01

Exploration of developmental mechanisms classically relies on analysis of pattern regularities. Whether disorders induced by biological noise may carry information on building principles of developmental systems is an important debated question. Here, we addressed theoretically this question using phyllotaxis, the geometric arrangement of plant aerial organs, as a model system. Phyllotaxis arises from reiterative organogenesis driven by lateral inhibitions at the shoot apex. Motivated by recurrent observations of disorders in phyllotaxis patterns, we revisited in depth the classical deterministic view of phyllotaxis. We developed a stochastic model of primordia initiation at the shoot apex, integrating locality and stochasticity in the patterning system. This stochastic model recapitulates phyllotactic patterns, both regular and irregular, and makes quantitative predictions on the nature of disorders arising from noise. We further show that disorders in phyllotaxis instruct us on the parameters governing phyllotaxis dynamics, thus that disorders can reveal biological watermarks of developmental systems. DOI: http://dx.doi.org/10.7554/eLife.14093.001 PMID:27380805

Implant Surface Design Regulates Mesenchymal Stem Cell Differentiation and Maturation

PubMed Central

Boyan, B.D.; Cheng, A.; Olivares-Navarrete, R.; Schwartz, Z.

2016-01-01

Changes in dental implant materials, structural design, and surface properties can all affect biological response. While bulk properties are important for mechanical stability of the implant, surface design ultimately contributes to osseointegration. This article reviews the surface parameters of dental implant materials that contribute to improved cell response and osseointegration. In particular, we focus on how surface design affects mesenchymal cell response and differentiation into the osteoblast lineage. Surface roughness has been largely studied at the microscale, but recent studies have highlighted the importance of hierarchical micron/submicron/nanosurface roughness, as well as surface roughness in combination with surface wettability. Integrins are transmembrane receptors that recognize changes in the surface and mediate downstream signaling pathways. Specifically, the noncanonical Wnt5a pathway has been implicated in osteoblastic differentiation of cells on titanium implant surfaces. However, much remains to be elucidated. Only recently have studies been conducted on the differences in biological response to implants based on sex, age, and clinical factors; these all point toward differences that advocate for patient-specific implant design. Finally, challenges in implant surface characterization must be addressed to optimize and compare data across studies. An understanding of both the science and the biology of the materials is crucial for developing novel dental implant materials and surface modifications for improved osseointegration. PMID:26927483

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.

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

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.

Toxicity of ionic liquids: eco(cyto)activity as complicated, but unavoidable parameter for task-specific optimization.

PubMed

Egorova, Ksenia S; Ananikov, Valentine P

2014-02-01

Rapid progress in the field of ionic liquids in recent decades led to the development of many outstanding energy-conversion processes, catalytic systems, synthetic procedures, and important practical applications. Task-specific optimization emerged as a sharpening stone for the fine-tuning of structure of ionic liquids, which resulted in unprecedented efficiency at the molecular level. Ionic-liquid systems showed promising opportunities in the development of green and sustainable technologies; however, the chemical nature of ionic liquids is not intrinsically green. Many ionic liquids were found to be toxic or even highly toxic towards cells and living organisms. In this Review, we show that biological activity and cytotoxicity of ionic liquids dramatically depend on the nature of a biological system. An ionic liquid may be not toxic for particular cells or organisms, but may demonstrate high toxicity towards another target present in the environment. Thus, a careful selection of biological activity data is a must for the correct assessment of chemical technologies involving ionic liquids. In addition to the direct biological activity (immediate response), several indirect effects and aftereffects are of primary importance. The following principal factors were revealed to modulate toxicity of ionic liquids: i) length of an alkyl chain in the cation; ii) degree of functionalization in the side chain of the cation; iii) anion nature; iv) cation nature; and v) mutual influence of anion and cation. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The effects of small field dosimetry on the biological models used in evaluating IMRT dose distributions

NASA Astrophysics Data System (ADS)

Cardarelli, Gene A.

The primary goal in radiation oncology is to deliver lethal radiation doses to tumors, while minimizing dose to normal tissue. IMRT has the capability to increase the dose to the targets and decrease the dose to normal tissue, increasing local control, decrease toxicity and allow for effective dose escalation. This advanced technology does present complex dose distributions that are not easily verified. Furthermore, the dose inhomogeneity caused by non-uniform dose distributions seen in IMRT treatments has caused the development of biological models attempting to characterize the dose-volume effect in the response of organized tissues to radiation. Dosimetry of small fields can be quite challenging when measuring dose distributions for high-energy X-ray beams used in IMRT. The proper modeling of these small field distributions is essential in reproducing accurate dose for IMRT. This evaluation was conducted to quantify the effects of small field dosimetry on IMRT plan dose distributions and the effects on four biological model parameters. The four biological models evaluated were: (1) the generalized Equivalent Uniform Dose (gEUD), (2) the Tumor Control Probability (TCP), (3) the Normal Tissue Complication Probability (NTCP) and (4) the Probability of uncomplicated Tumor Control (P+). These models are used to estimate local control, survival, complications and uncomplicated tumor control. This investigation compares three distinct small field dose algorithms. Dose algorithms were created using film, small ion chamber, and a combination of ion chamber measurements and small field fitting parameters. Due to the nature of uncertainties in small field dosimetry and the dependence of biological models on dose volume information, this examination quantifies the effects of small field dosimetry techniques on radiobiological models and recommends pathways to reduce the errors in using these models to evaluate IMRT dose distributions. This study demonstrates the importance of valid physical dose modeling prior to the use of biological modeling. The success of using biological function data, such as hypoxia, in clinical IMRT planning will greatly benefit from the results of this study.

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.

Factors controlling nitrous oxide emissions from a full-scale activated sludge system in the tropics.

PubMed

Brotto, Ariane C; Kligerman, Débora C; Andrade, Samara A; Ribeiro, Renato P; Oliveira, Jaime L M; Chandran, Kartik; de Mello, William Z

2015-08-01

Despite interest in characterizing nitrous oxide (N2O) emissions from wastewater treatment plants (WWTPs) in several parts of the globe, there are few studies in tropical zones. This study focus on the contribution of the scientific knowledge of anthropogenic nitrogen greenhouse gas emissions to climate change in tropical countries, investigating factors controlling N2O emissions in a non-biological nitrogen removal municipal WWTP. In terms of operational parameters, dissolved oxygen (DO) concentrations displayed a biphasic impact on N2O production and emission, with the highest emission at DO of 2.0 mg O2 L(-1). The low solids retention time of 3 days also played a significant role, leading to nitrite accumulation, which is an important trigger for N2O production during nitrification. Furthermore, other factor especially important for tropical countries, namely, temperature, also had a positive correlation with N2O production. Emission factors estimated for this study were 0.12 (0.02-0.31)% of the influent total nitrogen load and 8.1 (3-17) g N2O person(-1) year(-1), 2.5 times higher than currently proposed emission factors. Therefore, the highly variability and dependence on operational parameters reinforce the use of a single emission factor is inadequate, especially for developing countries with limited or variable extent of biological wastewater treatment and in regions of the world with widely varying climate patterns.

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.

Biological characteristics of geographically isolated populations of Meccus mazzottii (Hemiptera: Reduviidae) in southern Mexico.

PubMed

Martínez-Ibarra, J A; Nogueda-Torres, B; Vargas-Llamas, V; García-Benavides, G; Bustos-Saldaña, R; Villagrán, M E; de Diego-Cabrera, J A; Tapia-González, J M

2014-01-01

Chagas disease, caused by Trypanosoma cruzi Chagas, is one of the most epidemiologically important vector-borne zoonoses in Mexico. Among the 32 reported triatomine species from Mexico, Meccus mazzottii (Usinger) (Hemiptera: Reduviidae) is one of the most important vectors of T. cruzi in the southern part of the country. Variability among populations of triatomines has been recorded for several species (Meccus longipennis (Usinger) and Meccus pallidipennis (Stal)) that are closely related to M. mazzottii, showing an apparent influence of local environmental conditions on the biology of each population, which could modify the impact of vector control measurements. Therefore, this study sought to compare the biological features of populations of M. mazzottii from two geographically far apart areas that have similar environmental characteristics and to compare populations from close geographical areas that have different environmental characteristics. The mean longevity, percentages of mortality of nymphs, the total mean number of bloodmeals to molt (considered instar by instar), the mean number of eggs laid by females, and the percentage of hatched eggs were similar between the two localities that are geographically far apart but have similar environmental characteristics. On the other hand, important differences were noticed when a comparison was carried out on the two localities with similar environmental conditions with respect to that locality with different conditions, independent of geographic distance. Most of the studied parameters led us to conclude that the three studied populations are very highly influenced by local environmental conditions. The results of this study indicate the importance of studying the biological characteristics of local populations of triatomines to carry out specific control measurements, instead of using standard ones that could fail if they are not adapted to the target population. © The Author 2014. Published by Oxford University Press on behalf of the Entomological Society of America.

Integrating Information in Biological Ontologies and Molecular Networks to Infer Novel Terms.

PubMed

Li, Le; Yip, Kevin Y

2016-12-15

Currently most terms and term-term relationships in Gene Ontology (GO) are defined manually, which creates cost, consistency and completeness issues. Recent studies have demonstrated the feasibility of inferring GO automatically from biological networks, which represents an important complementary approach to GO construction. These methods (NeXO and CliXO) are unsupervised, which means 1) they cannot use the information contained in existing GO, 2) the way they integrate biological networks may not optimize the accuracy, and 3) they are not customized to infer the three different sub-ontologies of GO. Here we present a semi-supervised method called Unicorn that extends these previous methods to tackle the three problems. Unicorn uses a sub-tree of an existing GO sub-ontology as training part to learn parameters in integrating multiple networks. Cross-validation results show that Unicorn reliably inferred the left-out parts of each specific GO sub-ontology. In addition, by training Unicorn with an old version of GO together with biological networks, it successfully re-discovered some terms and term-term relationships present only in a new version of GO. Unicorn also successfully inferred some novel terms that were not contained in GO but have biological meanings well-supported by the literature. Source code of Unicorn is available at http://yiplab.cse.cuhk.edu.hk/unicorn/.

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI)

PubMed Central

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non–expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI’s robustness and sensitivity in capturing useful data relating to the students’ conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. PMID:26903497

A comparative pharmacological investigation of three samples of 'Guduchi ghrita' for adaptogenic activity against forced swimming induced gastric ulceration and hematological changes in albino rats

PubMed Central

Savrikar, Shriram S.; Dole, Vilas; Ravishankar, B.; Shukla, Vinay J.

2010-01-01

This study was undertaken to investigate the impact of formulation factors and adjuvants on the expression of biological activity of Tinospora cordifolia (Willd.) Miers. The adaptogenic effect of three samples of Guduchi ghrita, prepared using plain ghee (clarified butter) obtained from three different sources was studied in albino rats and compared with expressed juice of stem of Guduchi. The test preparations were evaluated against forced–swimming induced hypothermia, gastric ulceration and changes in the hematological parameters. The test drug given in the form of 'ghrita' produced better effect in comparison to the expressed juice. Among the three 'ghrita' preparations evaluated, only the 'Solapur Guduchi ghrita' (SGG) was found to produce significant inhibition of stress hypothermia and gastric ulceration. The other two preparations 'Nanded Guduchi ghrita' (NGG), and 'Wardha Guduchi ghrita' (WGG) could produce only a marginal effect. In hematological parameters 'Guduchi' juice produced better reversal of the stress-induced changes in comparison to the test 'ghrita' preparations. The present study provides evidence highlighting the importance of formulation factors for the expression of biological activity. PMID:20814518

Comparing transformation methods for DNA microarray data

PubMed Central

Thygesen, Helene H; Zwinderman, Aeilko H

2004-01-01

Background When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. Results We used the ratio between biological variance and measurement variance (which is an F-like statistic) as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. Conclusions The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method. PMID:15202953

Comparing transformation methods for DNA microarray data.

PubMed

Thygesen, Helene H; Zwinderman, Aeilko H

2004-06-17

When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. We used the ratio between biological variance and measurement variance (which is an F-like statistic) as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method.

Comparing a discrete and continuum model of the intestinal crypt

PubMed Central

Murray, Philip J.; Walter, Alex; Fletcher, Alex G.; Edwards, Carina M.; Tindall, Marcus J.; Maini, Philip K.

2011-01-01

The integration of processes at different scales is a key problem in the modelling of cell populations. Owing to increased computational resources and the accumulation of data at the cellular and subcellular scales, the use of discrete, cell-level models, which are typically solved using numerical simulations, has become prominent. One of the merits of this approach is that important biological factors, such as cell heterogeneity and noise, can be easily incorporated. However, it can be difficult to efficiently draw generalisations from the simulation results, as, often, many simulation runs are required to investigate model behaviour in typically large parameter spaces. In some cases, discrete cell-level models can be coarse-grained, yielding continuum models whose analysis can lead to the development of insight into the underlying simulations. In this paper we apply such an approach to the case of a discrete model of cell dynamics in the intestinal crypt. An analysis of the resulting continuum model demonstrates that there is a limited region of parameter space within which steady-state (and hence biologically realistic) solutions exist. Continuum model predictions show good agreement with corresponding results from the underlying simulations and experimental data taken from murine intestinal crypts. PMID:21411869

Computational dynamic approaches for temporal omics data with applications to systems medicine.

PubMed

Liang, Yulan; Kelemen, Arpad

2017-01-01

Modeling and predicting biological dynamic systems and simultaneously estimating the kinetic structural and functional parameters are extremely important in systems and computational biology. This is key for understanding the complexity of the human health, drug response, disease susceptibility and pathogenesis for systems medicine. Temporal omics data used to measure the dynamic biological systems are essentials to discover complex biological interactions and clinical mechanism and causations. However, the delineation of the possible associations and causalities of genes, proteins, metabolites, cells and other biological entities from high throughput time course omics data is challenging for which conventional experimental techniques are not suited in the big omics era. In this paper, we present various recently developed dynamic trajectory and causal network approaches for temporal omics data, which are extremely useful for those researchers who want to start working in this challenging research area. Moreover, applications to various biological systems, health conditions and disease status, and examples that summarize the state-of-the art performances depending on different specific mining tasks are presented. We critically discuss the merits, drawbacks and limitations of the approaches, and the associated main challenges for the years ahead. The most recent computing tools and software to analyze specific problem type, associated platform resources, and other potentials for the dynamic trajectory and interaction methods are also presented and discussed in detail.

Cold denaturation as a tool to measure protein stability

PubMed Central

Sanfelice, Domenico; Temussi, Piero Andrea

2016-01-01

Protein stability is an important issue for the interpretation of a wide variety of biological problems but its assessment is at times difficult. The most common parameter employed to describe protein stability is the temperature of melting, at which the populations of folded and unfolded species are identical. This parameter may yield ambiguous results. It would always be preferable to measure the whole stability curve. The calculation of this curve is greatly facilitated whenever it is possible to observe cold denaturation. Using Yfh1, one of the few proteins whose cold denaturation occurs at neutral pH and low ionic strength, we could measure the variation of its full stability curve under several environmental conditions. Here we show the advantages of gauging stability as a function of external variables using stability curves. PMID:26026885

ShinyKGode: an interactive application for ODE parameter inference using gradient matching.

PubMed

Wandy, Joe; Niu, Mu; Giurghita, Diana; Daly, Rónán; Rogers, Simon; Husmeier, Dirk

2018-07-01

Mathematical modelling based on ordinary differential equations (ODEs) is widely used to describe the dynamics of biological systems, particularly in systems and pathway biology. Often the kinetic parameters of these ODE systems are unknown and have to be inferred from the data. Approximate parameter inference methods based on gradient matching (which do not require performing computationally expensive numerical integration of the ODEs) have been getting popular in recent years, but many implementations are difficult to run without expert knowledge. Here, we introduce ShinyKGode, an interactive web application to perform fast parameter inference on ODEs using gradient matching. ShinyKGode can be used to infer ODE parameters on simulated and observed data using gradient matching. Users can easily load their own models in Systems Biology Markup Language format, and a set of pre-defined ODE benchmark models are provided in the application. Inferred parameters are visualized alongside diagnostic plots to assess convergence. The R package for ShinyKGode can be installed through the Comprehensive R Archive Network (CRAN). Installation instructions, as well as tutorial videos and source code are available at https://joewandy.github.io/shinyKGode. Supplementary data are available at Bioinformatics online.

Designing synthetic networks in silico: a generalised evolutionary algorithm approach.

PubMed

Smith, Robert W; van Sluijs, Bob; Fleck, Christian

2017-12-02

Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses.

Quantifying pCO2 in biological ocean acidification experiments: A comparison of four methods.

PubMed

Watson, Sue-Ann; Fabricius, Katharina E; Munday, Philip L

2017-01-01

Quantifying the amount of carbon dioxide (CO2) in seawater is an essential component of ocean acidification research; however, equipment for measuring CO2 directly can be costly and involve complex, bulky apparatus. Consequently, other parameters of the carbonate system, such as pH and total alkalinity (AT), are often measured and used to calculate the partial pressure of CO2 (pCO2) in seawater, especially in biological CO2-manipulation studies, including large ecological experiments and those conducted at field sites. Here we compare four methods of pCO2 determination that have been used in biological ocean acidification experiments: 1) Versatile INstrument for the Determination of Total inorganic carbon and titration Alkalinity (VINDTA) measurement of dissolved inorganic carbon (CT) and AT, 2) spectrophotometric measurement of pHT and AT, 3) electrode measurement of pHNBS and AT, and 4) the direct measurement of CO2 using a portable CO2 equilibrator with a non-dispersive infrared (NDIR) gas analyser. In this study, we found these four methods can produce very similar pCO2 estimates, and the three methods often suited to field-based application (spectrophotometric pHT, electrode pHNBS and CO2 equilibrator) produced estimated measurement uncertainties of 3.5-4.6% for pCO2. Importantly, we are not advocating the replacement of established methods to measure seawater carbonate chemistry, particularly for high-accuracy quantification of carbonate parameters in seawater such as open ocean chemistry, for real-time measures of ocean change, nor for the measurement of small changes in seawater pCO2. However, for biological CO2-manipulation experiments measuring differences of over 100 μatm pCO2 among treatments, we find the four methods described here can produce similar results with careful use.

Quantifying pCO2 in biological ocean acidification experiments: A comparison of four methods

PubMed Central

Fabricius, Katharina E.; Munday, Philip L.

2017-01-01

Quantifying the amount of carbon dioxide (CO2) in seawater is an essential component of ocean acidification research; however, equipment for measuring CO2 directly can be costly and involve complex, bulky apparatus. Consequently, other parameters of the carbonate system, such as pH and total alkalinity (AT), are often measured and used to calculate the partial pressure of CO2 (pCO2) in seawater, especially in biological CO2-manipulation studies, including large ecological experiments and those conducted at field sites. Here we compare four methods of pCO2 determination that have been used in biological ocean acidification experiments: 1) Versatile INstrument for the Determination of Total inorganic carbon and titration Alkalinity (VINDTA) measurement of dissolved inorganic carbon (CT) and AT, 2) spectrophotometric measurement of pHT and AT, 3) electrode measurement of pHNBS and AT, and 4) the direct measurement of CO2 using a portable CO2 equilibrator with a non-dispersive infrared (NDIR) gas analyser. In this study, we found these four methods can produce very similar pCO2 estimates, and the three methods often suited to field-based application (spectrophotometric pHT, electrode pHNBS and CO2 equilibrator) produced estimated measurement uncertainties of 3.5–4.6% for pCO2. Importantly, we are not advocating the replacement of established methods to measure seawater carbonate chemistry, particularly for high-accuracy quantification of carbonate parameters in seawater such as open ocean chemistry, for real-time measures of ocean change, nor for the measurement of small changes in seawater pCO2. However, for biological CO2-manipulation experiments measuring differences of over 100 μatm pCO2 among treatments, we find the four methods described here can produce similar results with careful use. PMID:28957378

Evolutionary Tradeoffs between Economy and Effectiveness in Biological Homeostasis Systems

PubMed Central

Szekely, Pablo; Sheftel, Hila; Mayo, Avi; Alon, Uri

2013-01-01

Biological regulatory systems face a fundamental tradeoff: they must be effective but at the same time also economical. For example, regulatory systems that are designed to repair damage must be effective in reducing damage, but economical in not making too many repair proteins because making excessive proteins carries a fitness cost to the cell, called protein burden. In order to see how biological systems compromise between the two tasks of effectiveness and economy, we applied an approach from economics and engineering called Pareto optimality. This approach allows calculating the best-compromise systems that optimally combine the two tasks. We used a simple and general model for regulation, known as integral feedback, and showed that best-compromise systems have particular combinations of biochemical parameters that control the response rate and basal level. We find that the optimal systems fall on a curve in parameter space. Due to this feature, even if one is able to measure only a small fraction of the system's parameters, one can infer the rest. We applied this approach to estimate parameters in three biological systems: response to heat shock and response to DNA damage in bacteria, and calcium homeostasis in mammals. PMID:23950698

Evolutionary tradeoffs between economy and effectiveness in biological homeostasis systems.

PubMed

Szekely, Pablo; Sheftel, Hila; Mayo, Avi; Alon, Uri

2013-01-01

Biological regulatory systems face a fundamental tradeoff: they must be effective but at the same time also economical. For example, regulatory systems that are designed to repair damage must be effective in reducing damage, but economical in not making too many repair proteins because making excessive proteins carries a fitness cost to the cell, called protein burden. In order to see how biological systems compromise between the two tasks of effectiveness and economy, we applied an approach from economics and engineering called Pareto optimality. This approach allows calculating the best-compromise systems that optimally combine the two tasks. We used a simple and general model for regulation, known as integral feedback, and showed that best-compromise systems have particular combinations of biochemical parameters that control the response rate and basal level. We find that the optimal systems fall on a curve in parameter space. Due to this feature, even if one is able to measure only a small fraction of the system's parameters, one can infer the rest. We applied this approach to estimate parameters in three biological systems: response to heat shock and response to DNA damage in bacteria, and calcium homeostasis in mammals.

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

PubMed

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

2011-11-01

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

General ecological models for human subsistence, health and poverty.

PubMed

Ngonghala, Calistus N; De Leo, Giulio A; Pascual, Mercedes M; Keenan, Donald C; Dobson, Andrew P; Bonds, Matthew H

2017-08-01

The world's rural poor rely heavily on their immediate natural environment for subsistence and suffer high rates of morbidity and mortality from infectious diseases. We present a general framework for modelling subsistence and health of the rural poor by coupling simple dynamic models of population ecology with those for economic growth. The models show that feedbacks between the biological and economic systems can lead to a state of persistent poverty. Analyses of a wide range of specific systems under alternative assumptions show the existence of three possible regimes corresponding to a globally stable development equilibrium, a globally stable poverty equilibrium and bistability. Bistability consistently emerges as a property of generalized disease-economic systems for about a fifth of the feasible parameter space. The overall proportion of parameters leading to poverty is larger than that resulting in healthy/wealthy development. All the systems are found to be most sensitive to human disease parameters. The framework highlights feedbacks, processes and parameters that are important to measure in studies of rural poverty to identify effective pathways towards sustainable development.

Microdosimetric Modeling of Biological Effectiveness for Boron Neutron Capture Therapy Considering Intra- and Intercellular Heterogeneity in 10B Distribution.

PubMed

Sato, Tatsuhiko; Masunaga, Shin-Ichiro; Kumada, Hiroaki; Hamada, Nobuyuki

2018-01-17

We here propose a new model for estimating the biological effectiveness for boron neutron capture therapy (BNCT) considering intra- and intercellular heterogeneity in 10 B distribution. The new model was developed from our previously established stochastic microdosimetric kinetic model that determines the surviving fraction of cells irradiated with any radiations. In the model, the probability density of the absorbed doses in microscopic scales is the fundamental physical index for characterizing the radiation fields. A new computational method was established to determine the probability density for application to BNCT using the Particle and Heavy Ion Transport code System PHITS. The parameters used in the model were determined from the measured surviving fraction of tumor cells administrated with two kinds of 10 B compounds. The model quantitatively highlighted the indispensable need to consider the synergetic effect and the dose dependence of the biological effectiveness in the estimate of the therapeutic effect of BNCT. The model can predict the biological effectiveness of newly developed 10 B compounds based on their intra- and intercellular distributions, and thus, it can play important roles not only in treatment planning but also in drug discovery research for future BNCT.

Hierarchical statistical modeling of xylem vulnerability to cavitation.

PubMed

Ogle, Kiona; Barber, Jarrett J; Willson, Cynthia; Thompson, Brenda

2009-01-01

Cavitation of xylem elements diminishes the water transport capacity of plants, and quantifying xylem vulnerability to cavitation is important to understanding plant function. Current approaches to analyzing hydraulic conductivity (K) data to infer vulnerability to cavitation suffer from problems such as the use of potentially unrealistic vulnerability curves, difficulty interpreting parameters in these curves, a statistical framework that ignores sampling design, and an overly simplistic view of uncertainty. This study illustrates how two common curves (exponential-sigmoid and Weibull) can be reparameterized in terms of meaningful parameters: maximum conductivity (k(sat)), water potential (-P) at which percentage loss of conductivity (PLC) =X% (P(X)), and the slope of the PLC curve at P(X) (S(X)), a 'sensitivity' index. We provide a hierarchical Bayesian method for fitting the reparameterized curves to K(H) data. We illustrate the method using data for roots and stems of two populations of Juniperus scopulorum and test for differences in k(sat), P(X), and S(X) between different groups. Two important results emerge from this study. First, the Weibull model is preferred because it produces biologically realistic estimates of PLC near P = 0 MPa. Second, stochastic embolisms contribute an important source of uncertainty that should be included in such analyses.

Biological systems for human life support: Review of the research in the USSR

NASA Technical Reports Server (NTRS)

Shepelev, Y. Y.

1979-01-01

Various models of biological human life support systems are surveyed. Biological structures, dimensions, and functional parameters of man-chlorella-microorganism models are described. Significant observations and the results obtained from these models are reported.

Quantifying Selection with Pool-Seq Time Series Data.

PubMed

Taus, Thomas; Futschik, Andreas; Schlötterer, Christian

2017-11-01

Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (Ne) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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

Evaluation of landfill gas production and emissions in a MSW large-scale Experimental Cell in Brazil.

PubMed

Maciel, Felipe Jucá; Jucá, José Fernando Thomé

2011-05-01

Landfill gas (LFG) emissions from municipal solid waste (MSW) landfills are an important environmental concern in Brazil due to the existence of several uncontrolled disposal sites. A program of laboratory and field tests was conducted to investigate gas generation in and emission from an Experimental Cell with a 36,659-ton capacity in Recife/PE - Brazil. This investigation involved waste characterisation, gas production and emission monitoring, and geotechnical and biological evaluations and was performed using three types of final cover layers. The results obtained in this study showed that waste decomposes 4-5 times faster in a tropical wet climate than predicted by traditional first-order models using default parameters. This fact must be included when considering the techniques and economics of projects developed in tropical climate countries. The design of the final cover layer and its geotechnical and biological behaviour proved to have an important role in minimising gas emissions to the atmosphere. Capillary and methanotrophic final cover layers presented lower CH(4) flux rates than the conventional layer. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

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

2004-01-01

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

A new method for parameter estimation in nonlinear dynamical equations

NASA Astrophysics Data System (ADS)

Wang, Liu; He, Wen-Ping; Liao, Le-Jian; Wan, Shi-Quan; He, Tao

2015-01-01

Parameter estimation is an important scientific problem in various fields such as chaos control, chaos synchronization and other mathematical models. In this paper, a new method for parameter estimation in nonlinear dynamical equations is proposed based on evolutionary modelling (EM). This will be achieved by utilizing the following characteristics of EM which includes self-organizing, adaptive and self-learning features which are inspired by biological natural selection, and mutation and genetic inheritance. The performance of the new method is demonstrated by using various numerical tests on the classic chaos model—Lorenz equation (Lorenz 1963). The results indicate that the new method can be used for fast and effective parameter estimation irrespective of whether partial parameters or all parameters are unknown in the Lorenz equation. Moreover, the new method has a good convergence rate. Noises are inevitable in observational data. The influence of observational noises on the performance of the presented method has been investigated. The results indicate that the strong noises, such as signal noise ratio (SNR) of 10 dB, have a larger influence on parameter estimation than the relatively weak noises. However, it is found that the precision of the parameter estimation remains acceptable for the relatively weak noises, e.g. SNR is 20 or 30 dB. It indicates that the presented method also has some anti-noise performance.

Methods and pitfalls of measuring thermal preference and tolerance in lizards.

PubMed

Camacho, Agustín; Rusch, Travis W

2017-08-01

Understanding methodological and biological sources of bias during the measurement of thermal parameters is essential for the advancement of thermal biology. For more than a century, studies on lizards have deepened our understanding of thermal ecophysiology, employing multiple methods to measure thermal preferences and tolerances. We reviewed 129 articles concerned with measuring preferred body temperature (PBT), voluntary thermal tolerance, and critical temperatures of lizards to offer: a) an overview of the methods used to measure and report these parameters, b) a summary of the methodological and biological factors affecting thermal preference and tolerance, c) recommendations to avoid identified pitfalls, and d) directions for continued progress in our application and understanding of these thermal parameters. We emphasize the need for more methodological and comparative studies. Lastly, we urge researchers to provide more detailed methodological descriptions and suggest ways to make their raw data more informative to increase the utility of thermal biology studies. Copyright © 2017 Elsevier Ltd. All rights reserved.

A method for operative quantitative interpretation of multispectral images of biological tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2013-10-01

A method for operative retrieval of spatial distributions of biophysical parameters of a biological tissue by using a multispectral image of it has been developed. The method is based on multiple regressions between linearly independent components of the diffuse reflection spectrum of the tissue and unknown parameters. Possibilities of the method are illustrated by an example of determining biophysical parameters of the skin (concentrations of melanin, hemoglobin and bilirubin, blood oxygenation, and scattering coefficient of the tissue). Examples of quantitative interpretation of the experimental data are presented.

[Antisocial personality disorder].

PubMed

Repo-Tiihonen, Eila; Hallikainen, Tero

2016-01-01

Antisocial personality disorder (ASP), especially psychopathy as its extreme form, has provoked fear and excitement over thousands of years. Ruthless violence involved in the disorder has inspired scientists, too.The abundance of research results concerning epidemiology, physiology, neuroanatomy, heritability, and treatment interventions has made ASP one of the best documented disorders in psychiatry. Numerous interventions have been tested, but there is no current treatment algorithm. Biological and sociological parameters indicate the importance of early targeted interventions among the high risk children. Otherwise, as adults they cause the greatest harm. The use of medications or psychotherapy for adults needs careful consideration.

Efficient Ensemble State-Parameters Estimation Techniques in Ocean Ecosystem Models: Application to the North Atlantic

NASA Astrophysics Data System (ADS)

El Gharamti, M.; Bethke, I.; Tjiputra, J.; Bertino, L.

2016-02-01

Given the recent strong international focus on developing new data assimilation systems for biological models, we present in this comparative study the application of newly developed state-parameters estimation tools to an ocean ecosystem model. It is quite known that the available physical models are still too simple compared to the complexity of the ocean biology. Furthermore, various biological parameters remain poorly unknown and hence wrong specifications of such parameters can lead to large model errors. Standard joint state-parameters augmentation technique using the ensemble Kalman filter (Stochastic EnKF) has been extensively tested in many geophysical applications. Some of these assimilation studies reported that jointly updating the state and the parameters might introduce significant inconsistency especially for strongly nonlinear models. This is usually the case for ecosystem models particularly during the period of the spring bloom. A better handling of the estimation problem is often carried out by separating the update of the state and the parameters using the so-called Dual EnKF. The dual filter is computationally more expensive than the Joint EnKF but is expected to perform more accurately. Using a similar separation strategy, we propose a new EnKF estimation algorithm in which we apply a one-step-ahead smoothing to the state. The new state-parameters estimation scheme is derived in a consistent Bayesian filtering framework and results in separate update steps for the state and the parameters. Unlike the classical filtering path, the new scheme starts with an update step and later a model propagation step is performed. We test the performance of the new smoothing-based schemes against the standard EnKF in a one-dimensional configuration of the Norwegian Earth System Model (NorESM) in the North Atlantic. We use nutrients profile (up to 2000 m deep) data and surface partial CO2 measurements from Mike weather station (66o N, 2o E) to estimate different biological parameters of phytoplanktons and zooplanktons. We analyze the performance of the filters in terms of complexity and accuracy of the state and parameters estimates.

A hybrid artificial neural network as a software sensor for optimal control of a wastewater treatment process.

PubMed

Choi, D J; Park, H

2001-11-01

For control and automation of biological treatment processes, lack of reliable on-line sensors to measure water quality parameters is one of the most important problems to overcome. Many parameters cannot be measured directly with on-line sensors. The accuracy of existing hardware sensors is also not sufficient and maintenance problems such as electrode fouling often cause trouble. This paper deals with the development of software sensor techniques that estimate the target water quality parameter from other parameters using the correlation between water quality parameters. We focus our attention on the preprocessing of noisy data and the selection of the best model feasible to the situation. Problems of existing approaches are also discussed. We propose a hybrid neural network as a software sensor inferring wastewater quality parameter. Multivariate regression, artificial neural networks (ANN), and a hybrid technique that combines principal component analysis as a preprocessing stage are applied to data from industrial wastewater processes. The hybrid ANN technique shows an enhancement of prediction capability and reduces the overfitting problem of neural networks. The result shows that the hybrid ANN technique can be used to extract information from noisy data and to describe the nonlinearity of complex wastewater treatment processes.

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal-scale biological variability.

PubMed

Litzow, Michael A; Mueter, Franz J; Hobday, Alistair J

2014-01-01

In areas of the North Pacific that are largely free of overfishing, climate regime shifts - abrupt changes in modes of low-frequency climate variability - are seen as the dominant drivers of decadal-scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific-North American Pattern (PNA), North Pacific Index (NPI), El Niño-Southern Oscillation (ENSO)] to explain decadal-scale (1965-2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1-2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1-2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1-2 satisfied assumptions of independent residuals and out-performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1-2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations. © 2013 John Wiley & Sons Ltd.

A Liver Index and its Relationship to Indices of HCC Aggressiveness

PubMed Central

Carr, Brian I; Guerra, Vito; Giannini, Edoardo G; Farinati, Fabio; Ciccarese, Francesca; Rapaccini, Gian Ludovico; Di Marco, Maria; Benvegnù, Luisa; Zoli, Marco; Borzio, Franco; Caturelli, Eugenio; Masotto, Alberto; Trevisani, Franco

2017-01-01

A Hepatocellular (HCC) Aggressiveness Index was recently constructed, consisting of the sum of the scores for the 4 clinical parameters of maximum tumor size, multifocality, presence of portal vein thrombus and blood alphafetoprotein levels. It was observed that there was an association with several liver function tests. We have now formed a Liver Index from the 4 liver parameters with the highest hazard ratios with respect to HCC aggressiveness, namely: blood total bilirubin, gamma glutamyl transpeptidase (GGTP), albumin and platelet levels (cirrhosis surrogate). We found that the scores for the Liver Index related significantly to survival, but also to the Aggressiveness Index and to its individual HCC components as well as showing significant trends with the components. These results support the hypothesis that liver function is not only an important prognostic factor in HCC patients, but may also be involved in HCC biology and aggressiveness. Blood albumin, GGTP, albumin and platelet levels were used to create a Liver Index that related significantly to parameters of HCC aggressiveness. PMID:28580457

Optimal structure and parameter learning of Ising models

DOE PAGES

Lokhov, Andrey; Vuffray, Marc Denis; Misra, Sidhant; ...

2018-03-16

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, whichmore » is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.« less

Technical Note: Artificial coral reef mesocosms for ocean acidification investigations

NASA Astrophysics Data System (ADS)

Leblud, J.; Moulin, L.; Batigny, A.; Dubois, P.; Grosjean, P.

2014-11-01

The design and evaluation of replicated artificial mesocosms are presented in the context of a thirteen month experiment on the effects of ocean acidification on tropical coral reefs. They are defined here as (semi)-closed (i.e. with or without water change from the reef) mesocosms in the laboratory with a more realistic physico-chemical environment than microcosms. Important physico-chemical parameters (i.e. pH, pO2, pCO2, total alkalinity, temperature, salinity, total alkaline earth metals and nutrients availability) were successfully monitored and controlled. Daily variations of irradiance and pH were applied to approach field conditions. Results highlighted that it was possible to maintain realistic physico-chemical parameters, including daily changes, into artificial mesocosms. On the other hand, the two identical artificial mesocosms evolved differently in terms of global community oxygen budgets although the initial biological communities and physico-chemical parameters were comparable. Artificial reef mesocosms seem to leave enough degrees of freedom to the enclosed community of living organisms to organize and change along possibly diverging pathways.

Optimal structure and parameter learning of Ising models

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

Lokhov, Andrey; Vuffray, Marc Denis; Misra, Sidhant

Reconstruction of the structure and parameters of an Ising model from binary samples is a problem of practical importance in a variety of disciplines, ranging from statistical physics and computational biology to image processing and machine learning. The focus of the research community shifted toward developing universal reconstruction algorithms that are both computationally efficient and require the minimal amount of expensive data. Here, we introduce a new method, interaction screening, which accurately estimates model parameters using local optimization problems. The algorithm provably achieves perfect graph structure recovery with an information-theoretically optimal number of samples, notably in the low-temperature regime, whichmore » is known to be the hardest for learning. Here, the efficacy of interaction screening is assessed through extensive numerical tests on synthetic Ising models of various topologies with different types of interactions, as well as on real data produced by a D-Wave quantum computer. Finally, this study shows that the interaction screening method is an exact, tractable, and optimal technique that universally solves the inverse Ising problem.« less

Panaceas, uncertainty, and the robust control framework in sustainability science

PubMed Central

Anderies, John M.; Rodriguez, Armando A.; Janssen, Marco A.; Cifdaloz, Oguzhan

2007-01-01

A critical challenge faced by sustainability science is to develop strategies to cope with highly uncertain social and ecological dynamics. This article explores the use of the robust control framework toward this end. After briefly outlining the robust control framework, we apply it to the traditional Gordon–Schaefer fishery model to explore fundamental performance–robustness and robustness–vulnerability trade-offs in natural resource management. We find that the classic optimal control policy can be very sensitive to parametric uncertainty. By exploring a large class of alternative strategies, we show that there are no panaceas: even mild robustness properties are difficult to achieve, and increasing robustness to some parameters (e.g., biological parameters) results in decreased robustness with respect to others (e.g., economic parameters). On the basis of this example, we extract some broader themes for better management of resources under uncertainty and for sustainability science in general. Specifically, we focus attention on the importance of a continual learning process and the use of robust control to inform this process. PMID:17881574

Bayesian parameter estimation for stochastic models of biological cell migration

NASA Astrophysics Data System (ADS)

Dieterich, Peter; Preuss, Roland

2013-08-01

Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths.

Similar and functionally typical kinematic reaching parameters in 7- and 15-month-old in utero cocaine-exposed and unexposed infants.

PubMed

Tronick, E Z; Fetters, Linda; Olson, Karen L; Chen, Yuping

2004-04-01

This study examined the effects of intrauterine cocaine exposure on the reaches of 19 exposed and 15 unexposed infants at 7 and 15 months using kinematic measures. Infants sat at a table and reached for a rattle, a toy doll, and a chair. Videotaped reaches were digitized using the Peak Performance system. Kinematic movement variables were extracted (e.g., reach duration, peak velocity, movement units, path length) and ratios computed (e.g., path length divided by number of movement units). Regardless of exposure status, reaches of older infants were faster, more direct, had fewer movement units, and covered more distance with the first movement unit. Exposed infants covered more distance per movement unit than unexposed infants, but there were no other significant differences. Reaches of exposed and unexposed infants were essentially similar. Importantly, reach parameters for these high-risk infants were similar to reach parameters for infants at lower social and biological risk. Copyright 2004 Wiley Periodicals, Inc.

Defining the Role of Solid Stress and Matrix Stiffness in Cancer Cell Proliferation and Metastasis

PubMed Central

Kalli, Maria; Stylianopoulos, Triantafyllos

2018-01-01

Solid tumors are characterized by an abnormal stroma that contributes to the development of biomechanical abnormalities in the tumor microenvironment. In particular, these abnormalities include an increase in matrix stiffness and an accumulation of solid stress in the tumor interior. So far, it is not clearly defined whether matrix stiffness and solid stress are strongly related to each other or they have distinct roles in tumor progression. Moreover, while the effects of stiffness on tumor progression are extensively studied compared to the contribution of solid stress, it is important to ascertain the biological outcomes of both abnormalities in tumorigenesis and metastasis. In this review, we discuss how each of these parameters is evolved during tumor growth and how these parameters are influenced by each other. We further review the effects of matrix stiffness and solid stress on the proliferative and metastatic potential of cancer and stromal cells and summarize the in vitro experimental setups that have been designed to study the individual contribution of these parameters. PMID:29594037

A new approach to estimate parameters of speciation models with application to apes.

PubMed

Becquet, Celine; Przeworski, Molly

2007-10-01

How populations diverge and give rise to distinct species remains a fundamental question in evolutionary biology, with important implications for a wide range of fields, from conservation genetics to human evolution. A promising approach is to estimate parameters of simple speciation models using polymorphism data from multiple loci. Existing methods, however, make a number of assumptions that severely limit their applicability, notably, no gene flow after the populations split and no intralocus recombination. To overcome these limitations, we developed a new Markov chain Monte Carlo method to estimate parameters of an isolation-migration model. The approach uses summaries of polymorphism data at multiple loci surveyed in a pair of diverging populations or closely related species and, importantly, allows for intralocus recombination. To illustrate its potential, we applied it to extensive polymorphism data from populations and species of apes, whose demographic histories are largely unknown. The isolation-migration model appears to provide a reasonable fit to the data. It suggests that the two chimpanzee species became reproductively isolated in allopatry approximately 850 Kya, while Western and Central chimpanzee populations split approximately 440 Kya but continued to exchange migrants. Similarly, Eastern and Western gorillas and Sumatran and Bornean orangutans appear to have experienced gene flow since their splits approximately 90 and over 250 Kya, respectively.

Age and growth of the sword razor clam Ensis arcuatus in the Ría de Pontevedra (NW Spain): Influence of environmental parameters

NASA Astrophysics Data System (ADS)

Hernández-Otero, A.; Gaspar, M. B.; Macho, G.; Vázquez, E.

2014-01-01

The sword razor clam Ensis arcuatus is the most important commercial species of razor clam in Spain, and its fishery in the Ría de Pontevedra (Galicia, NW Spain) is the most productive. Despite the economic importance of this species, information on its biology is scarce. This study reports shell morphometric relationships, age, and growth rates of E. arcuatus in three fishing beds in the Ría de Pontevedra (Brensa, Bueu and Ons, located in respectively the inner, middle and outer zones of the ria), providing the first estimates of growth parameters for the species in the Iberian Peninsula. Growth was estimated by examination of surface growth rings and internal shell microgrowth patterns (acetate peel technique) that proved to be the most suitable method for growth estimate. Growth of E. arcuatus was slower in Bueu (L∞ = 140.4, k = 0.40) followed by Brensa (L∞ = 151.91, k = 0.40) and Ons (L∞ = 172.7, k = 0.33), and the clams reached commercial size in 1.7, 2.3 and 2.8 years in Ons, Brensa and Bueu, respectively. The differences in growth between sites in relation to environmental parameters are evaluated and the implications for the razor clam fishery are discussed.

Statistical analysis of polarization interference images of biological fluids polycrystalline films in the tasks of optical anisotropy weak changes differentiation

NASA Astrophysics Data System (ADS)

Ushenko, Yu. O.; Dubolazov, O. V.; Ushenko, V. O.; Zhytaryuk, V. G.; Prydiy, O. G.; Pavlyukovich, N.; Pavlyukovich, O.

2018-01-01

In this paper, we present the results of a statistical analysis of polarization-interference images of optically thin histological sections of biological tissues and polycrystalline films of biological fluids of human organs. A new analytical parameter is introduced-the local contrast of the interference pattern in the plane of a polarizationinhomogeneous microscopic image of a biological preparation. The coordinate distributions of the given parameter and the sets of statistical moments of the first-fourth order that characterize these distributions are determined. On this basis, the differentiation of degenerative-dystrophic changes in the myocardium and the polycrystalline structure of the synovial fluid of the human knee with different pathologies is realized.

A high-throughput screening approach to discovering good forms of biologically inspired visual representation.

PubMed

Pinto, Nicolas; Doukhan, David; DiCarlo, James J; Cox, David D

2009-11-01

While many models of biological object recognition share a common set of "broad-stroke" properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model--e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct "parts" have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision.

A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation

PubMed Central

Pinto, Nicolas; Doukhan, David; DiCarlo, James J.; Cox, David D.

2009-01-01

While many models of biological object recognition share a common set of “broad-stroke” properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model—e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct “parts” have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision. PMID:19956750

Impact of country of birth on progression of steady and pulsatile hemodynamic parameters in normotensive and hypertensive subjects.

PubMed

Thomas, Frédérique; Pannier, Bruno; Safar, Michel E

2013-01-01

The impact of country of birth (Africa, Asia, or France) on variations of hemodynamic, clinical, and biological parameters of a French general population was evaluated. The study included 2743 subjects (1641 men, 1102 women; mean age 45.4 ± 13.5 years) with at least two health checkups at the Centre d'Investigations Préventives et Cliniques, Paris, between 2008 and 2011. The interval between the two visits (V1, V2) was 1.74 ± 0.66 years. Changes of hemodynamic, biological and clinical markers were calculated using the V2-V1 absolute difference or percent variation. African- and Asian-born were compared separately to French-born subjects using variance analysis and χ² tests. In men, country of birth was not associated with any significant mean hemodynamic parameter variation. In women, mean brachial and central pulse pressures, heart rate (HR), and central augmentation index (CAI) varied significantly more among African- than Asian-born women, when compared with French-born women. For each hemodynamic parameter, V1 values were the first predictive of this change. Country of birth was a significant predictor of HR and CAI changes. Evaluation of interactions showed that a gender × birth country interaction was significant with CAI variation and, to a lesser extent, HR. Finally, country of birth impacted changes in CAI differently in men and women, suggesting that wave reflections play an important role in cardiovascular risk mainly in women. Their effects act predominantly on pulse pressure level and its amplification, indicating an increasing contribution of CAI with age. Copyright © 2013 American Society of Hypertension. Published by Elsevier Inc. All rights reserved.

Wall shear stress fixed points in blood flow

NASA Astrophysics Data System (ADS)

Arzani, Amirhossein; Shadden, Shawn

2017-11-01

Patient-specific computational fluid dynamics produces large datasets, and wall shear stress (WSS) is one of the most important parameters due to its close connection with the biological processes at the wall. While some studies have investigated WSS vectorial features, the WSS fixed points have not received much attention. In this talk, we will discuss the importance of WSS fixed points from three viewpoints. First, we will review how WSS fixed points relate to the flow physics away from the wall. Second, we will discuss how certain types of WSS fixed points lead to high biochemical surface concentration in cardiovascular mass transport problems. Finally, we will introduce a new measure to track the exposure of endothelial cells to WSS fixed points.

Mapping Nearshore Seagrass and Colonized Hard Bottom Spatial Distribution and Percent Biological Cover in Florida, USA Using Object Based Image Analysis of WorldView-2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Baumstark, R. D.; Duffey, R.; Pu, R.

2016-12-01

The offshore extent of seagrass habitat along the West Florida (USA) coast represents an important corridor for inshore-offshore migration of economically important fish and shellfish. Surviving at the fringe of light requirements, offshore seagrass beds are sensitive to changes in water clarity. Beyond and intermingled with the offshore seagrass areas are large swaths of colonized hard bottom. These offshore habitats of the West Florida coast have lacked mapping efforts needed for status and trends monitoring. The objective of this study was to propose an object-based classification method for mapping offshore habitats and to compare results to traditional photo-interpreted maps. Benthic maps depicting the spatial distribution and percent biological cover were created from WorldView-2 satellite imagery using Object Based Image Analysis (OBIA) method and a visual photo-interpretation method. A logistic regression analysis identified depth and distance from shore as significant parameters for discriminating spectrally similar seagrass and colonized hard bottom features. Seagrass, colonized hard bottom and unconsolidated sediment (sand) were mapped with 78% overall accuracy using the OBIA method compared to 71% overall accuracy using the photo-interpretation method. This study presents an alternative for mapping deeper, offshore habitats capable of producing higher thematic (percent biological cover) and spatial resolution maps compared to those created with the traditional photo-interpretation method.

Changes in the Bacterial Community of Soil from a Neutral Mine Drainage Channel

PubMed Central

Pereira, Letícia Bianca; Vicentini, Renato; Ottoboni, Laura M. M.

2014-01-01

Mine drainage is an important environmental disturbance that affects the chemical and biological components in natural resources. However, little is known about the effects of neutral mine drainage on the soil bacteria community. Here, a high-throughput 16S rDNA pyrosequencing approach was used to evaluate differences in composition, structure, and diversity of bacteria communities in samples from a neutral drainage channel, and soil next to the channel, at the Sossego copper mine in Brazil. Advanced statistical analyses were used to explore the relationships between the biological and chemical data. The results showed that the neutral mine drainage caused changes in the composition and structure of the microbial community, but not in its diversity. The Deinococcus/Thermus phylum, especially the Meiothermus genus, was in large part responsible for the differences between the communities, and was positively associated with the presence of copper and other heavy metals in the environmental samples. Other important parameters that influenced the bacterial diversity and composition were the elements potassium, sodium, nickel, and zinc, as well as pH. The findings contribute to the understanding of bacterial diversity in soils impacted by neutral mine drainage, and demonstrate that heavy metals play an important role in shaping the microbial population in mine environments. PMID:24796430

Biological characterization of Aedes albopictus (Diptera: Culicidae) in Argentina: implications for arbovirus transmission.

PubMed

Chuchuy, Ailen; Rodriguero, Marcela S; Ferrari, Walter; Ciota, Alexander T; Kramer, Laura D; Micieli, María V

2018-03-22

Aedes albopictus (Diptera: Culicidae) is an invasive mosquito, native to Asia, that has expanded its range worldwide. It is considered to be a public health threat as it is a competent vector of viruses of medical importance, including dengue, chikungunya, and Zika. Despite its medical importance there is almost no information on biologically important traits of Ae. albopictus in Argentina. We studied life cycle traits, demographic parameters and analyzed the competence of this mosquito as a virus vector. In addition, we determined the prevalence of Wolbachia strains in Ae. albopictus as a first approach to investigate the potential role of this bacteria in modulating vector competence for arboviruses. We observed low hatch rates of eggs, which led to a negative growth rate. We found that Ae. albopictus individuals were infected with Wolbachia in the F1 but while standard superinfection with wAlbA and wAlbB types was found in 66.7% of the females, 16.7% of the females and 62.5% of the males were single-infected with the wAlbB strain. Finally, despite high levels of infection and dissemination, particularly for chikungunya virus, Ae. albopictus from subtropical Argentina were found to be relatively inefficient vectors for transmission of both chikungunya and dengue viruses.

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks.

PubMed

Rumschinski, Philipp; Borchers, Steffen; Bosio, Sandro; Weismantel, Robert; Findeisen, Rolf

2010-05-25

Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates.

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks

PubMed Central

2010-01-01

Background Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. Results In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. Conclusions The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates. PMID:20500862

A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking.

PubMed

Ballester, Pedro J; Mitchell, John B O

2010-05-01

Accurately predicting the binding affinities of large sets of diverse protein-ligand complexes is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for analysing the outputs of molecular docking, which in turn is an important technique for drug discovery, chemical biology and structural biology. Each scoring function assumes a predetermined theory-inspired functional form for the relationship between the variables that characterize the complex, which also include parameters fitted to experimental or simulation data and its predicted binding affinity. The inherent problem of this rigid approach is that it leads to poor predictivity for those complexes that do not conform to the modelling assumptions. Moreover, resampling strategies, such as cross-validation or bootstrapping, are still not systematically used to guard against the overfitting of calibration data in parameter estimation for scoring functions. We propose a novel scoring function (RF-Score) that circumvents the need for problematic modelling assumptions via non-parametric machine learning. In particular, Random Forest was used to implicitly capture binding effects that are hard to model explicitly. RF-Score is compared with the state of the art on the demanding PDBbind benchmark. Results show that RF-Score is a very competitive scoring function. Importantly, RF-Score's performance was shown to improve dramatically with training set size and hence the future availability of more high-quality structural and interaction data is expected to lead to improved versions of RF-Score. pedro.ballester@ebi.ac.uk; jbom@st-andrews.ac.uk Supplementary data are available at Bioinformatics online.

Case studies on ESA-doping as revealed by the Biological Passport.

PubMed

Zorzoli, Mario; Rossi, Francesca

2012-11-01

Blood doping, through the increase of red cells, induces changes of hematological parameters. The aim of the Biological Passport is first to analyse individual longitudinal profiles in order to identify, through variations of the specific parameters, doping manipulations. Additionally, on the basis of abnormal values or profiles, athletes can be targeted for traditional anti-doping tests in order to detect forbidden substances or methods. We report the experience of the International Cycling Union in applying the Biological Passport to target athletes for the presence of erythropoiesis stimulating agents. All positive results which have been reported between 2008 and 2010 concerning athletes enrolled in the Biological Passport program are presented. Four cases are discussed more in details. To conclude, we propose possible ways of using the Biological Passport in order to better understand athletes' doping modalities, so that testing programs efficiency can be improved. Copyright © 2012 John Wiley & Sons, Ltd.

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.

Determination of optical absorption coefficient with focusing photoacoustic imaging.

PubMed

Li, Zhifang; Li, Hui; Zeng, Zhiping; Xie, Wenming; Chen, Wei R

2012-06-01

Absorption coefficient of biological tissue is an important factor for photothermal therapy and photoacoustic imaging. However, its determination remains a challenge. In this paper, we propose a method using focusing photoacoustic imaging technique to quantify the target optical absorption coefficient. It utilizes the ratio of the amplitude of the peak signal from the top boundary of the target to that from the bottom boundary based on wavelet transform. This method is self-calibrating. Factors, such as absolute optical fluence, ultrasound parameters, and Grüneisen parameter, can be canceled by dividing the amplitudes of the two peaks. To demonstrate this method, we quantified the optical absorption coefficient of a target with various concentrations of an absorbing dye. This method is particularly useful to provide accurate absorption coefficient for predicting the outcomes of photothermal interaction for cancer treatment with absorption enhancement.

Update of KDBI: Kinetic Data of Bio-molecular Interaction database

PubMed Central

Kumar, Pankaj; Han, B. C.; Shi, Z.; Jia, J.; Wang, Y. P.; Zhang, Y. T.; Liang, L.; Liu, Q. F.; Ji, Z. L.; Chen, Y. Z.

2009-01-01

Knowledge of the kinetics of biomolecular interactions is important for facilitating the study of cellular processes and underlying molecular events, and is essential for quantitative study and simulation of biological systems. Kinetic Data of Bio-molecular Interaction database (KDBI) has been developed to provide information about experimentally determined kinetic data of protein–protein, protein–nucleic acid, protein–ligand, nucleic acid–ligand binding or reaction events described in the literature. To accommodate increasing demand for studying and simulating biological systems, numerous improvements and updates have been made to KDBI, including new ways to access data by pathway and molecule names, data file in System Biology Markup Language format, more efficient search engine, access to published parameter sets of simulation models of 63 pathways, and 2.3-fold increase of data (19 263 entries of 10 532 distinctive biomolecular binding and 11 954 interaction events, involving 2635 proteins/protein complexes, 847 nucleic acids, 1603 small molecules and 45 multi-step processes). KDBI is publically available at http://bidd.nus.edu.sg/group/kdbi/kdbi.asp. PMID:18971255

[Chemical and biological evaluation of ripe banana peel].

PubMed

Ranzani, M R; Sturion, G L; Bicudo, M H

1996-12-01

Chemical and biological evaluation of ripe banana peel was conducted, aiming its potential use as a source of dietary fiber in human nutrition. Two types of flour were prepared from banana peel: a) untreated (UT), using washed and dried peel; b) treated (SMB), using peel treated with sodium metabisulfite and citric acid, in attempt to minimize the darkening of the flour. As expected, banana peel flour revealed to be an important source of fiber (NDF), corresponding about 32% of its dried weight. The addition of this flour to a basal casein diet lowered its protein digestibility and increased the fecal bulk of the rats, which are the known effects of dietary fiber. However, it did not alter the protein quality, since there was no difference in the PER values of the diets studied; in addition, the growth of the rats fed diets containing banana peel did not differ from those fed control diet. These results suggest the feasibility of technological studies aiming the development of food products with banana peel. Besides, biological assays should be realized in the elucidation of its effects in food intake and biochemical parameters.

Flexible Transient Optical Waveguides and Surface-Wave Biosensors Constructed from Monocrystalline Silicon.

PubMed

Bai, Wubin; Yang, Hongjun; Ma, Yinji; Chen, Hao; Shin, Jiho; Liu, Yonghao; Yang, Quansan; Kandela, Irawati; Liu, Zhonghe; Kang, Seung-Kyun; Wei, Chen; Haney, Chad R; Brikha, Anlil; Ge, Xiaochen; Feng, Xue; Braun, Paul V; Huang, Yonggang; Zhou, Weidong; Rogers, John A

2018-06-26

Optical technologies offer important capabilities in both biological research and clinical care. Recent interest is in implantable devices that provide intimate optical coupling to biological tissues for a finite time period and then undergo full bioresorption into benign products, thereby serving as temporary implants for diagnosis and/or therapy. The results presented here establish a silicon-based, bioresorbable photonic platform that relies on thin filaments of monocrystalline silicon encapsulated by polymers as flexible, transient optical waveguides for accurate light delivery and sensing at targeted sites in biological systems. Comprehensive studies of the mechanical and optical properties associated with bending and unfurling the waveguides from wafer-scale sources of materials establish general guidelines in fabrication and design. Monitoring biochemical species such as glucose and tracking physiological parameters such as oxygen saturation using near-infrared spectroscopic methods demonstrate modes of utility in biomedicine. These concepts provide versatile capabilities in biomedical diagnosis, therapy, deep-tissue imaging, and surgery, and suggest a broad range of opportunities for silicon photonics in bioresorbable technologies. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Stomatal characteristics and infection biology of Pyrenopeziza betulicola in Betula pendula trees grown under elevated CO2 and O3.

PubMed

Riikonen, Johanna; Syrjälä, Leena; Tulva, Ingmar; Mänd, Pille; Oksanen, Elina; Poteri, Marja; Vapaavuori, Elina

2008-11-01

Two silver birch clones were exposed to ambient and elevated concentrations of CO(2) and O(3), and their combination for 3 years, using open-top chambers. We evaluated the effects of elevated CO(2) and O(3) on stomatal conductance (g(s)), density (SD) and index (SI), length of the guard cells, and epidermal cell size and number, with respect to crown position and leaf type. The relationship between the infection biology of the fungus (Pyrenopeziza betulicola) causing leaf spot disease and stomatal characteristics was also studied. Leaf type was an important determinant of O(3) response in silver birch, while crown position and clone played only a minor role. Elevated CO(2) reduced the g(s), but had otherwise no significant effect on the parameters studied. No significant interactions between elevated CO(2) and O(3) were found. The infection biology of P. betulicola was not correlated with SD or g(s), but it did occasionally correlate positively with the length of the guard cells.

Density dependence in demography and dispersal generates fluctuating invasion speeds

PubMed Central

Li, Bingtuan; Miller, Tom E. X.

2017-01-01

Density dependence plays an important role in population regulation and is known to generate temporal fluctuations in population density. However, the ways in which density dependence affects spatial population processes, such as species invasions, are less understood. Although classical ecological theory suggests that invasions should advance at a constant speed, empirical work is illuminating the highly variable nature of biological invasions, which often exhibit nonconstant spreading speeds, even in simple, controlled settings. Here, we explore endogenous density dependence as a mechanism for inducing variability in biological invasions with a set of population models that incorporate density dependence in demographic and dispersal parameters. We show that density dependence in demography at low population densities—i.e., an Allee effect—combined with spatiotemporal variability in population density behind the invasion front can produce fluctuations in spreading speed. The density fluctuations behind the front can arise from either overcompensatory population growth or density-dependent dispersal, both of which are common in nature. Our results show that simple rules can generate complex spread dynamics and highlight a source of variability in biological invasions that may aid in ecological forecasting. PMID:28442569

Hybrid modelling based on support vector regression with genetic algorithms in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain).

PubMed

García Nieto, P J; Alonso Fernández, J R; de Cos Juez, F J; Sánchez Lasheras, F; Díaz Muñiz, C

2013-04-01

Cyanotoxins, a kind of poisonous substances produced by cyanobacteria, are responsible for health risks in drinking and recreational waters. As a result, anticipate its presence is a matter of importance to prevent risks. The aim of this study is to use a hybrid approach based on support vector regression (SVR) in combination with genetic algorithms (GAs), known as a genetic algorithm support vector regression (GA-SVR) model, in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain). The GA-SVR approach is aimed at highly nonlinear biological problems with sharp peaks and the tests carried out proved its high performance. Some physical-chemical parameters have been considered along with the biological ones. The results obtained are two-fold. In the first place, the significance of each biological and physical-chemical variable on the cyanotoxins presence in the reservoir is determined with success. Finally, a predictive model able to forecast the possible presence of cyanotoxins in a short term was obtained. Copyright © 2013 Elsevier Inc. All rights reserved.

Microbial fuel cell (MFC) power performance improvement through enhanced microbial electrogenicity.

PubMed

Li, Ming; Zhou, Minghua; Tian, Xiaoyu; Tan, Chaolin; McDaniel, Cameron T; Hassett, Daniel J; Gu, Tingyue

Within the past 5 years, tremendous advances have been made to maximize the performance of microbial fuel cells (MFCs) for both "clean" bioenergy production and bioremediation. Most research efforts have focused on parameters including (i) optimizing reactor configuration, (ii) electrode construction, (iii) addition of redox-active, electron donating mediators, (iv) biofilm acclimation and feed nutrient adjustment, as well as (v) other parameters that contribute to enhanced MFC performance. To date, tremendous advances have been made, but further improvements are needed for MFCs to be economically practical. In this review, the diversity of electrogenic microorganisms and microbial community changes in mixed cultures are discussed. More importantly, different approaches including chemical/genetic modifications and gene regulation of exoelectrogens, synthetic biology approaches and bacterial community cooperation are reviewed. Advances in recent years in metagenomics and microbiomes have allowed researchers to improve bacterial electrogenicity of robust biofilms in MFCs using novel, unconventional approaches. Taken together, this review provides some important and timely information to researchers who are examining additional means to enhance power production of MFCs. Copyright © 2018 Elsevier Inc. All rights reserved.

Modern Perspectives on Numerical Modeling of Cardiac Pacemaker Cell

PubMed Central

Maltsev, Victor A.; Yaniv, Yael; Maltsev, Anna V.; Stern, Michael D.; Lakatta, Edward G.

2015-01-01

Cardiac pacemaking is a complex phenomenon that is still not completely understood. Together with experimental studies, numerical modeling has been traditionally used to acquire mechanistic insights in this research area. This review summarizes the present state of numerical modeling of the cardiac pacemaker, including approaches to resolve present paradoxes and controversies. Specifically we discuss the requirement for realistic modeling to consider symmetrical importance of both intracellular and cell membrane processes (within a recent “coupled-clock” theory). Promising future developments of the complex pacemaker system models include the introduction of local calcium control, mitochondria function, and biochemical regulation of protein phosphorylation and cAMP production. Modern numerical and theoretical methods such as multi-parameter sensitivity analyses within extended populations of models and bifurcation analyses are also important for the definition of the most realistic parameters that describe a robust, yet simultaneously flexible operation of the coupled-clock pacemaker cell system. The systems approach to exploring cardiac pacemaker function will guide development of new therapies, such as biological pacemakers for treating insufficient cardiac pacemaker function that becomes especially prevalent with advancing age. PMID:24748434

A global sensitivity analysis for African sleeping sickness.

PubMed

Davis, Stephen; Aksoy, Serap; Galvani, Alison

2011-04-01

African sleeping sickness is a parasitic disease transmitted through the bites of tsetse flies of the genus Glossina. We constructed mechanistic models for the basic reproduction number, R0, of Trypanosoma brucei gambiense and Trypanosoma brucei rhodesiense, respectively the causative agents of West and East African human sleeping sickness. We present global sensitivity analyses of these models that rank the importance of the biological parameters that may explain variation in R0, using parameter ranges based on literature, field data and expertize out of Uganda. For West African sleeping sickness, our results indicate that the proportion of bloodmeals taken from humans by Glossina fuscipes fuscipes is the most important factor, suggesting that differences in the exposure of humans to tsetse are fundamental to the distribution of T. b. gambiense. The second ranked parameter for T. b. gambiense and the highest ranked for T. b. rhodesiense was the proportion of Glossina refractory to infection. This finding underlines the possible implications of recent work showing that nutritionally stressed tsetse are more susceptible to trypanosome infection, and provides broad support for control strategies in development that are aimed at increasing refractoriness in tsetse flies. We note though that for T. b. rhodesiense the population parameters for tsetse - species composition, survival and abundance - were ranked almost as highly as the proportion refractory, and that the model assumed regular treatment of livestock with trypanocides as an established practice in the areas of Uganda experiencing East African sleeping sickness.

Integrating Information in Biological Ontologies and Molecular Networks to Infer Novel Terms

PubMed Central

Li, Le; Yip, Kevin Y.

2016-01-01

Currently most terms and term-term relationships in Gene Ontology (GO) are defined manually, which creates cost, consistency and completeness issues. Recent studies have demonstrated the feasibility of inferring GO automatically from biological networks, which represents an important complementary approach to GO construction. These methods (NeXO and CliXO) are unsupervised, which means 1) they cannot use the information contained in existing GO, 2) the way they integrate biological networks may not optimize the accuracy, and 3) they are not customized to infer the three different sub-ontologies of GO. Here we present a semi-supervised method called Unicorn that extends these previous methods to tackle the three problems. Unicorn uses a sub-tree of an existing GO sub-ontology as training part to learn parameters in integrating multiple networks. Cross-validation results show that Unicorn reliably inferred the left-out parts of each specific GO sub-ontology. In addition, by training Unicorn with an old version of GO together with biological networks, it successfully re-discovered some terms and term-term relationships present only in a new version of GO. Unicorn also successfully inferred some novel terms that were not contained in GO but have biological meanings well-supported by the literature.Availability: Source code of Unicorn is available at http://yiplab.cse.cuhk.edu.hk/unicorn/. PMID:27976738

Bayesian Nonparametric Ordination for the Analysis of Microbial Communities.

PubMed

Ren, Boyu; Bacallado, Sergio; Favaro, Stefano; Holmes, Susan; Trippa, Lorenzo

2017-01-01

Human microbiome studies use sequencing technologies to measure the abundance of bacterial species or Operational Taxonomic Units (OTUs) in samples of biological material. Typically the data are organized in contingency tables with OTU counts across heterogeneous biological samples. In the microbial ecology community, ordination methods are frequently used to investigate latent factors or clusters that capture and describe variations of OTU counts across biological samples. It remains important to evaluate how uncertainty in estimates of each biological sample's microbial distribution propagates to ordination analyses, including visualization of clusters and projections of biological samples on low dimensional spaces. We propose a Bayesian analysis for dependent distributions to endow frequently used ordinations with estimates of uncertainty. A Bayesian nonparametric prior for dependent normalized random measures is constructed, which is marginally equivalent to the normalized generalized Gamma process, a well-known prior for nonparametric analyses. In our prior, the dependence and similarity between microbial distributions is represented by latent factors that concentrate in a low dimensional space. We use a shrinkage prior to tune the dimensionality of the latent factors. The resulting posterior samples of model parameters can be used to evaluate uncertainty in analyses routinely applied in microbiome studies. Specifically, by combining them with multivariate data analysis techniques we can visualize credible regions in ecological ordination plots. The characteristics of the proposed model are illustrated through a simulation study and applications in two microbiome datasets.

Cloning cattle: the methods in the madness.

PubMed

Oback, Björn; Wells, David N

2007-01-01

Somatic cell nuclear transfer (SCNT) is much more widely and efficiently practiced in cattle than in any other species, making this arguably the most important mammal cloned to date. While the initial objective behind cattle cloning was commercially driven--in particular to multiply genetically superior animals with desired phenotypic traits and to produce genetically modified animals-researchers have now started to use bovine SCNT as a tool to address diverse questions in developmental and cell biology. In this paper, we review current cattle cloning methodologies and their potential technical or biological pitfalls at any step of the procedure. In doing so, we focus on one methodological parameter, namely donor cell selection. We emphasize the impact of epigenetic and genetic differences between embryonic, germ, and somatic donor cell types on cloning efficiency. Lastly, we discuss adult phenotypes and fitness of cloned cattle and their offspring and illustrate some of the more imminent commercial cattle cloning applications.

Live-cell imaging of invasion and intravasation in an artificial microvessel platform.

PubMed

Wong, Andrew D; Searson, Peter C

2014-09-01

Methods to visualize metastasis exist, but additional tools to better define the biologic and physical processes underlying invasion and intravasation are still needed. One difficulty in studying metastasis stems from the complexity of the interface between the tumor microenvironment and the vascular system. Here, we report the development of an investigational platform that positions tumor cells next to an artificial vessel embedded in an extracellular matrix. On this platform, we used live-cell fluorescence microscopy to analyze the complex interplay between metastatic cancer cells and a functional artificial microvessel that was lined with endothelial cells. The platform recapitulated known interactions, and its use demonstrated the capabilities for a systematic study of novel physical and biologic parameters involved in invasion and intravasation. In summary, our work offers an important new tool to advance knowledge about metastasis and candidate antimetastatic therapies. ©2014 American Association for Cancer Research.

Influence of operating pressure on the biological hydrogen methanation in trickle-bed reactors.

PubMed

Ullrich, Timo; Lindner, Jonas; Bär, Katharina; Mörs, Friedemann; Graf, Frank; Lemmer, Andreas

2018-01-01

In order to investigate the influence of pressures up to 9bar absolute on the productivity of trickle-bed reactors for biological methanation of hydrogen and carbon dioxide, experiments were carried out in a continuously operated experimental plant with three identical reactors. The pressure increase promises a longer residence time and improved mass transfer of H 2 due to higher gas partial pressures. The study covers effects of different pressures on important parameters like gas hourly space velocity, methane formation rate, conversion rates and product gas quality. The methane content of 64.13±3.81vol-% at 1.5bar could be increased up to 86.51±0.49vol-% by raising the pressure to 9bar. Methane formation rates of up to 4.28±0.26m 3 m -3 d -1 were achieved. Thus, pressure increase could significantly improve reactor performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Breeding biology of Mottled Ducks on agricultural lands in southwestern Louisiana

USGS Publications Warehouse

Durham, R.S.; Afton, A.D.

2006-01-01

Breeding biology of Anas fulvigula maculosa (Mottled Ducks) has been described in coastal marsh and associated habitats, but little information is available for agricultural habitats in Louisiana. We located nests to determine nest-initiation dates and clutch sizes during the primary breeding season (February-May) in 1999 (n = 29) and 2000 (n = 37) on agricultural lands in southwestern Louisiana. In 1999, 60% of located nests were initiated between 22 March and 10 April, whereas in 2000, only 22% of nests were initiated during the same time period. Average clutch size was 0.9 eggs smaller in 2000 than in 1999. Annual differences in reproductive parameters corresponded with extremely dry conditions caused by low rainfall before the laying period in 2000. Flooded rice fields appear to be important loafing and feeding habitat of Mottled Ducks nesting in agricultural lands, especially during drought periods when other wetland types are not available or where natural wetlands have been eliminated.

New tools for redox biology: From imaging to manipulation.

PubMed

Bilan, Dmitry S; Belousov, Vsevolod V

2017-08-01

Redox reactions play a key role in maintaining essential biological processes. Deviations in redox pathways result in the development of various pathologies at cellular and organismal levels. Until recently, studies on transformations in the intracellular redox state have been significantly hampered in living systems. The genetically encoded indicators, based on fluorescent proteins, have provided new opportunities in biomedical research. The existing indicators already enable monitoring of cellular redox parameters in different processes including embryogenesis, aging, inflammation, tissue regeneration, and pathogenesis of various diseases. In this review, we summarize information about all genetically encoded redox indicators developed to date. We provide the description of each indicator and discuss its advantages and limitations, as well as points that need to be considered when choosing an indicator for a particular experiment. One chapter is devoted to the important discoveries that have been made by using genetically encoded redox indicators. Copyright © 2016 Elsevier Inc. All rights reserved.

G =  MAT: linking transcription factor expression and DNA binding data.

PubMed

Tretyakov, Konstantin; Laur, Sven; Vilo, Jaak

2011-01-31

Transcription factors are proteins that bind to motifs on the DNA and thus affect gene expression regulation. The qualitative description of the corresponding processes is therefore important for a better understanding of essential biological mechanisms. However, wet lab experiments targeted at the discovery of the regulatory interplay between transcription factors and binding sites are expensive. We propose a new, purely computational method for finding putative associations between transcription factors and motifs. This method is based on a linear model that combines sequence information with expression data. We present various methods for model parameter estimation and show, via experiments on simulated data, that these methods are reliable. Finally, we examine the performance of this model on biological data and conclude that it can indeed be used to discover meaningful associations. The developed software is available as a web tool and Scilab source code at http://biit.cs.ut.ee/gmat/.

G = MAT: Linking Transcription Factor Expression and DNA Binding Data

PubMed Central

Tretyakov, Konstantin; Laur, Sven; Vilo, Jaak

2011-01-01

Transcription factors are proteins that bind to motifs on the DNA and thus affect gene expression regulation. The qualitative description of the corresponding processes is therefore important for a better understanding of essential biological mechanisms. However, wet lab experiments targeted at the discovery of the regulatory interplay between transcription factors and binding sites are expensive. We propose a new, purely computational method for finding putative associations between transcription factors and motifs. This method is based on a linear model that combines sequence information with expression data. We present various methods for model parameter estimation and show, via experiments on simulated data, that these methods are reliable. Finally, we examine the performance of this model on biological data and conclude that it can indeed be used to discover meaningful associations. The developed software is available as a web tool and Scilab source code at http://biit.cs.ut.ee/gmat/. PMID:21297945

Relation between the electromagnetic processes in the near-Earth space and dynamics of the biological resources in Russian Arctic

NASA Astrophysics Data System (ADS)

Makarova, L. N.; Shirochkov, A. V.; Tumanov, I. L.

The start of the satellite era in the Space explorations led to new and more profound knowledge of the solar physics and the sources of its activity. From these points of view, it is worthy to examine again the relations between biological processes and the solar activity. We explore the relation between dynamics of the solar activity (including the solar wind) and changes in population of some species of Arctic fauna (lemmings, polar foxes, caribous, wolves, elks, etc.). The data include statistical rows of various lengths (30 80 years). The best correlation between two data sets is found when the solar wind dynamic pressure as well as variations of the total solar irradiance (i.e., level of the solar UV radiation) is taken as the space parameters. Probably the electromagnetic fields of space origin are an important factor determining dynamics of population of the Arctic fauna species.

Multi-scale modularity and motif distributional effect in metabolic networks.

PubMed

Gao, Shang; Chen, Alan; Rahmani, Ali; Zeng, Jia; Tan, Mehmet; Alhajj, Reda; Rokne, Jon; Demetrick, Douglas; Wei, Xiaohui

2016-01-01

Metabolism is a set of fundamental processes that play important roles in a plethora of biological and medical contexts. It is understood that the topological information of reconstructed metabolic networks, such as modular organization, has crucial implications on biological functions. Recent interpretations of modularity in network settings provide a view of multiple network partitions induced by different resolution parameters. Here we ask the question: How do multiple network partitions affect the organization of metabolic networks? Since network motifs are often interpreted as the super families of evolved units, we further investigate their impact under multiple network partitions and investigate how the distribution of network motifs influences the organization of metabolic networks. We studied Homo sapiens, Saccharomyces cerevisiae and Escherichia coli metabolic networks; we analyzed the relationship between different community structures and motif distribution patterns. Further, we quantified the degree to which motifs participate in the modular organization of metabolic networks.

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

PubMed

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

2010-01-01

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

Ixtoc oil spill assessment

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

Boehm, P.

The blowout of the Ixtoc I oil well in the Bay of Campeche resulted in the largest documented spill in history. Approximately half a million metric tons of oil were released from June 3, 1979 to March 23, 1980. Of that amount, an estimated 11 thousand metric tons impacted south Texas beaches. As a result of the movement of oil from the Ixtoc I well blowout into the South Texas Outer Continental Shelf (STOCS) environment, a study was undertaken to establish the magnitude and areal extent of perturbation of the benthic community caused by chemical residues of Ixtoc oil. Themore » study focused on the inner shelf region to the 60-metre isobath and examined both the biology and hydrocarbon geochemistry of 12 sites coincident with those of four previously studied (1975-1977) baseline transects. Additionally, 26 sites within the region sampled during 1979 (mid-spill) for chemical parameters and again in 1980 (post-spill) for chemical and biological parameters, and 39 other sites sampled in 1979 for chemical parameters, were studied. The Burmah Agate oil tanker collided with the freighter Mimosa in November, 1979 5 miles off of Galveston, Texas and spilled part of its cargo of light crude oil. Approximately 21 thousand metric tons of the spilled oil burned in an ensuing fire. As the potentially complicating impact of the Burmah Agate tanker collision was of importance in the region, a set of six sites in the Galveston region were sampled to gain knowledge of the presence and nature of introduced chemical residues from this event. This study established a chemical and biological framework for carrying out spill assessment studies of this nature. It utilized a significant environmental data base for post-impact studies for the first time, and identified several sampling methodology deficiencies which, if corrected, may help to fine-tune such assessments.« less

A consistent S-Adenosylmethionine force field improved by dynamic Hirshfeld-I atomic charges for biomolecular simulation

NASA Astrophysics Data System (ADS)

Saez, David Adrian; Vöhringer-Martinez, Esteban

2015-10-01

S-Adenosylmethionine (AdoMet) is involved in many biological processes as cofactor in enzymes transferring its sulfonium methyl group to various substrates. Additionally, it is used as drug and nutritional supplement to reduce the pain in osteoarthritis and against depression. Due to the biological relevance of AdoMet it has been part of various computational simulation studies and will also be in the future. However, to our knowledge no rigorous force field parameter development for its simulation in biological systems has been reported. Here, we use electronic structure calculations combined with molecular dynamics simulations in explicit solvent to develop force field parameters compatible with the AMBER99 force field. Additionally, we propose new dynamic Hirshfeld-I atomic charges which are derived from the polarized electron density of AdoMet in aqueous solution to describe its electrostatic interactions in biological systems. The validation of the force field parameters and the atomic charges is performed against experimental interproton NOE distances of AdoMet in aqueous solution and crystal structures of AdoMet in the cavity of three representative proteins.

Biological monitoring results for cadmium exposed workers.

PubMed

McDiarmid, M A; Freeman, C S; Grossman, E A; Martonik, J

1996-11-01

As part of a settlement agreement with the Occupational Safety and Health Administration (OSHA) involving exposure to cadmium (Cd), a battery production facility provided medical surveillance data to OSHA for review. Measurements of cadmium in blood, cadmium in urine, and beta 2-microglobulin in urine were obtained for more than 100 workers over an 18-month period. Some airborne Cd exposure data were also made available. Two subpopulations of this cohort were of primary interest in evaluating compliance with the medical surveillance provisions of the Cadmium Standard. These were a group of 16 workers medically removed from cadmium exposure due to elevations in some biological parameter, and a group of platemakers. Platemaking had presented a particularly high exposure opportunity and had recently undergone engineering interventions to minimize exposure. The effect on three biological monitoring parameters of medical removal protection in the first group and engineering controls in platemakers is reported. Results reveal that both medical removal from cadmium exposures and exposure abatement through the use of engineering and work practice controls generally result in declines in biological monitoring parameters of exposed workers. Implications for the success of interventions are discussed.

Robust Design of Biological Circuits: Evolutionary Systems Biology Approach

PubMed Central

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

2011-01-01

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

Robust design of biological circuits: evolutionary systems biology approach.

PubMed

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

2011-01-01

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

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

NASA Technical Reports Server (NTRS)

Johnson, R. W.

1974-01-01

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

Direct medical costs and their predictors in the EMAR-II cohort: "Variability in the management of rheumatoid arthritis and spondyloarthritis in Spain".

PubMed

Leon, Leticia; Abasolo, Lydia; Fernandez-Gutierrez, Benjamin; Jover, Juan Angel; Hernandez-Garcia, Cesar

To analyze the resource utilization in rheumatoid arthritis (RA) patients and predictive factors in and patients treated with biological drugs and biologic-naïve. A cross-sectional study was performed in a sample including all regions and hospitals throughout the country. Sociodemographic data, disease activity parameters and treatment data were obtained. Resource utilization for two years of study was recorded and we made costs imputation. Correlation analyzes were performed on all RA patients and those treated with biological and biological naïve, to estimate the differences in resource utilization. Factors associated with increased resources utilization (costs) attending to treatment was analyzed by linear regression models. We included 1,095 RA patients, 26% male, mean age of 62±14 years. Mean of direct medical costs per patient was €24,291±€45,382. Excluding biological drugs, the average cost per patient was €3,742±€3,711. After adjustment, factors associated with direct medical costs for all RA patients were biologic drugs (P=.02) and disease activity (P=.004). In the biologic-naïve group, the predictor of direct medical costs was comorbidity (P<.001). In the biologic treatment group predictors were follow-up length of the disease (P=.04), age (P=.02) and disease activity (P=.007). Our data show a remarkable economic impact of RA. It is important to identify and estimate the economic impact of the disease, compare data from other geographic samples and to develop improvement strategies to reduce these costs and increase the quality of care. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Reumatología y Colegio Mexicano de Reumatología. All rights reserved.

Phytoplankton production in the Sargasso Sea as determined using optical mooring data

NASA Technical Reports Server (NTRS)

Waters, K. J.; Smith, R. C.; Marra, J.

1994-01-01

Optical measurements from an untended mooring provide high-frequency observations of in-water optical properties and permit the estimation of important biological parameters continuously as a function of time. A 9-month time series, composed of three separate deployments, of optical data from the BIOWATT 1987 deep-sea mooring located in the oligotrophic waters of the Sargasso Sea at 34 deg N, 70 deg W are presented. These data have been tested using several bio-optical models for the purpose of providing a continuous estimate of phytoplankton productivity. The data are discussed in the context of contemporaneous shipboard observations and for future ocean color satellite observations. We present a continuous estimation of phytoplankton productivity for the 9-month time series. Results from the first 70-day deployment are emphasized to demonstrate the utility of optical observations as proxy measures of biological parameters, to present preliminary analysis, and to compare our bio-optical observations with concurrent physical observations. The bio-optical features show variation in response to physical forcings including diel variations of incident solar irradiance, episodic changes corresponding to wind forcing, variability caused by advective mesoscale eddy events in the vicinity of the mooring, and seasonal variability corresponding to changes in solar radiation, shoaling of the mixed layer depth, and succession of phytoplankton populations.

Extracellular mass transport considerations for space flight research concerning suspended and adherent in vitro cell cultures

NASA Technical Reports Server (NTRS)

Klaus, David M.; Benoit, Michael R.; Nelson, Emily S.; Hammond, Timmothy G.

2004-01-01

Conducting biological research in space requires consideration be given to isolating appropriate control parameters. For in vitro cell cultures, numerous environmental factors can adversely affect data interpretation. A biological response attributed to microgravity can, in theory, be explicitly correlated to a specific lack of weight or gravity-driven motion occurring to, within or around a cell. Weight can be broken down to include the formation of hydrostatic gradients, structural load (stress) or physical deformation (strain). Gravitationally induced motion within or near individual cells in a fluid includes sedimentation (or buoyancy) of the cell and associated shear forces, displacement of cytoskeleton or organelles, and factors associated with intra- or extracellular mass transport. Finally, and of particular importance for cell culture experiments, the collective effects of gravity must be considered for the overall system consisting of the cells, their environment and the device in which they are contained. This does not, however, rule out other confounding variables such as launch acceleration, on orbit vibration, transient acceleration impulses or radiation, which can be isolated using onboard centrifuges or vibration isolation techniques. A framework is offered for characterizing specific cause-and-effect relationships for gravity-dependent responses as a function of the above parameters.

Measuring systems of hard to get objects: problems with analysis of measurement results

NASA Astrophysics Data System (ADS)

Gilewska, Grazyna

2005-02-01

The problem accessibility of metrological parameters features of objects appeared in many measurements. Especially if it is biological object which parameters very often determined on the basis of indirect research. Accidental component predominate in forming of measurement results with very limited access to measurement objects. Every measuring process has a lot of conditions limiting its abilities to any way processing (e.g. increase number of measurement repetition to decrease random limiting error). It may be temporal, financial limitations, or in case of biological object, small volume of sample, influence measuring tool and observers on object, or whether fatigue effects e.g. at patient. It's taken listing difficulties into consideration author worked out and checked practical application of methods outlying observation reduction and next innovative methods of elimination measured data with excess variance to decrease of mean standard deviation of measured data, with limited aomunt of data and accepted level of confidence. Elaborated methods wee verified on the basis of measurement results of knee-joint width space got from radiographs. Measurements were carried out by indirectly method on the digital images of radiographs. Results of examination confirmed legitimacy to using of elaborated methodology and measurement procedures. Such methodology has special importance when standard scientific ways didn't bring expectations effects.

Multistationarity in mass action networks with applications to ERK activation.

PubMed

Conradi, Carsten; Flockerzi, Dietrich

2012-07-01

Ordinary Differential Equations (ODEs) are an important tool in many areas of Quantitative Biology. For many ODE systems multistationarity (i.e. the existence of at least two positive steady states) is a desired feature. In general establishing multistationarity is a difficult task as realistic biological models are large in terms of states and (unknown) parameters and in most cases poorly parameterized (because of noisy measurement data of few components, a very small number of data points and only a limited number of repetitions). For mass action networks establishing multistationarity hence is equivalent to establishing the existence of at least two positive solutions of a large polynomial system with unknown coefficients. For mass action networks with certain structural properties, expressed in terms of the stoichiometric matrix and the reaction rate-exponent matrix, we present necessary and sufficient conditions for multistationarity that take the form of linear inequality systems. Solutions of these inequality systems define pairs of steady states and parameter values. We also present a sufficient condition to identify networks where the aforementioned conditions hold. To show the applicability of our results we analyse an ODE system that is defined by the mass action network describing the extracellular signal-regulated kinase (ERK) cascade (i.e. ERK-activation).

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.

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

Espinoza, I; Peschke, P; Karger, C

Purpose: In radiotherapy, it is important to predict the response of tumour to irradiation prior to the treatment. Mathematical modelling of tumour control probability (TCP) based on the dose distribution, medical imaging and other biological information may help to improve this prediction and to optimize the treatment plan. The aim of this work is to develop an image based 3D multiscale radiobiological model, which describes the growth and the response to radiotherapy of hypoxic tumors. Methods: The computer model is based on voxels, containing tumour, normal (including capillary) and dead cells. Killing of tumour cells due to irradiation is calculatedmore » by the Linear Quadratic Model (extended for hypoxia), and the proliferation and resorption of cells are modelled by exponential laws. The initial shape of the tumours is taken from CT images and the initial vascular and cell density information from PET and/or MR images. Including the fractionation regime and the physical dose distribution of the radiation treatment, the model simulates the spatial-temporal evolution of the tumor. Additionally, the dose distribution may be biologically optimized. Results: The model describes the appearance of hypoxia during tumour growth and the reoxygenation processes during radiotherapy. Among other parameters, the TCP is calculated for different dose distributions. The results are in accordance with published results. Conclusion: The simulation model may contribute to the understanding of the influence of biological parameters on tumor response during treatment, and specifically on TCP. It may be used to implement dose-painting approaches. Experimental and clinical validation is needed. This study is supported by a grant from the Ministry of Education of Chile, Programa Mece Educacion Superior (2)« less

Biophysical and biological contributions of polyamine-coated carbon nanotubes and bidimensional buckypapers in the delivery of miRNAs to human cells.

PubMed

Celluzzi, Antonella; Paolini, Alessandro; D'Oria, Valentina; Risoluti, Roberta; Materazzi, Stefano; Pezzullo, Marco; Casciardi, Stefano; Sennato, Simona; Bordi, Federico; Masotti, Andrea

2018-01-01

Recent findings in nanomedicine have revealed that carbon nanotubes (CNTs) can be used as potential drug carriers, therapeutic agents and diagnostics tools. Moreover, due to their ability to cross cellular membranes, their nanosize dimension, high surface area and relatively good biocompatibility, CNTs have also been employed as a novel gene delivery vector system. In our previous work, we functionalized CNTs with two polyamine polymers, polyethyleneimine (PEI) and polyamidoamine dendrimer (PAMAM). These compounds have low cytotoxicity, ability to conjugate microRNAs (such as miR-503) and, at the same time, transfect efficiently endothelial cells. The parameters contributing to the good efficiency of transfection that we observed were not investigated in detail. In fact, the diameter and length of CNTs are important parameters to be taken into account when evaluating the effects on drug delivery efficiency. In order to investigate the biophysical and biological contributions of polymer-coated CNTs in delivery of miRNAs to human cells, we decided to investigate three different preparations, characterized by different dimensions and aspect ratios. In particular, we took into account very small CNTs, a suspension of CNTs starting from the commercial product and a 2D material based on CNTs (ie, buckypapers [BPs]) to examine the transfection efficiency of a rigid scaffold. In conclusion, we extensively investigated the biophysical and biological contributions of polyamine-coated CNTs and bidimensional BPs in the delivery of miRNAs to human cells, in order to optimize the transfection efficiency of these compounds to be employed as efficient drug delivery vectors in biomedical applications.

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.

Bayesian model comparison and parameter inference in systems biology using nested sampling.

PubMed

Pullen, Nick; Morris, Richard J

2014-01-01

Inferring parameters for models of biological processes is a current challenge in systems biology, as is the related problem of comparing competing models that explain the data. In this work we apply Skilling's nested sampling to address both of these problems. Nested sampling is a Bayesian method for exploring parameter space that transforms a multi-dimensional integral to a 1D integration over likelihood space. This approach focuses on the computation of the marginal likelihood or evidence. The ratio of evidences of different models leads to the Bayes factor, which can be used for model comparison. We demonstrate how nested sampling can be used to reverse-engineer a system's behaviour whilst accounting for the uncertainty in the results. The effect of missing initial conditions of the variables as well as unknown parameters is investigated. We show how the evidence and the model ranking can change as a function of the available data. Furthermore, the addition of data from extra variables of the system can deliver more information for model comparison than increasing the data from one variable, thus providing a basis for experimental design.

Spectral fingerprint of electrostatic forces between biological cells

NASA Astrophysics Data System (ADS)

Murovec, T.; Brosseau, C.

2015-10-01

The prediction of electrostatic forces (EFs) between biological cells still poses challenges of great scientific importance, e.g., cell recognition, electroporation (EP), and mechanosensing. Frequency-domain finite element simulations explore a variety of cell configurations in the range of parameters typical for eukaryotic cells. Here, by applying an electric field to a pair of layered concentric shells, a prototypical model of a biological cell, we provide numerical evidence that the instantaneous EF changes from repulsion to attraction as the drive frequency of the electric field is varied. We identify crossover frequencies and discuss their dependence as a function of field frequency, conductivity of the extracellular medium, and symmetry of the configuration of cells. We present findings which suggest that the spectrum of EFs depends sensitively on the configuration of cells. We discuss the signatures of the collective behavior of systems with many cells in the spectrum of the EF and highlight a few of the observational consequences that this behavior implies. By looking at different cell configurations, we are able to show that the repulsion-to-attraction transition phenomenon is largely associated with an asymmetric electrostatic screening at very small separation between cells. These findings pave the way for the experimental observation of the electromagnetic properties of efficient and simple models of biological tissues.

An overview of surface radiance and biology studies in FIFE

NASA Astrophysics Data System (ADS)

Blad, B. L.; Schimel, D. S.

1992-11-01

The use of satellite data to study and to understand energy and mass exchanges between the land surface and the atmosphere requires information about various biological processes and how various reflected or emitted spectral radiances are influenced by or manifested in these processes. To obtain such information, studies were conducted by the First ISLSCP Field Experiment (FIFE) surface radiances and biology (SRB) group using surface, near-surface, helicopter, and aircraft measurements. The two primary objectives of this group were to relate radiative fluxes to biophysical parameters and physiological processes and to assess how various management treatments affect important biological processes. This overview paper summarizes the results obtained by various SRB teams working in nine different areas: (1) measurement of bidirectional reflectance and estimation of hemispherical albedo; (2) evaluation of spatial and seasonal variability of spectral reflectance and vegetation indices; (3) determination of surface and radiational factors and their effects on vegetation indices and PAR relationships; (4) use of surface temperatures to estimate sensible heat flux; (5) controls over photosynthesis and respiration at small scales; (6) soil surface CO2 fluxes and grassland carbon budget; (7) landscape variations in controls over gas exchange and energy partitioning; (8) radiometric response of prairie to management and topography; and (9) determination of nitrogen gas exchanges in a tallgrass prairie.

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.

Spectral fingerprint of electrostatic forces between biological cells.

PubMed

Murovec, T; Brosseau, C

2015-10-01

The prediction of electrostatic forces (EFs) between biological cells still poses challenges of great scientific importance, e.g., cell recognition, electroporation (EP), and mechanosensing. Frequency-domain finite element simulations explore a variety of cell configurations in the range of parameters typical for eukaryotic cells. Here, by applying an electric field to a pair of layered concentric shells, a prototypical model of a biological cell, we provide numerical evidence that the instantaneous EF changes from repulsion to attraction as the drive frequency of the electric field is varied. We identify crossover frequencies and discuss their dependence as a function of field frequency, conductivity of the extracellular medium, and symmetry of the configuration of cells. We present findings which suggest that the spectrum of EFs depends sensitively on the configuration of cells. We discuss the signatures of the collective behavior of systems with many cells in the spectrum of the EF and highlight a few of the observational consequences that this behavior implies. By looking at different cell configurations, we are able to show that the repulsion-to-attraction transition phenomenon is largely associated with an asymmetric electrostatic screening at very small separation between cells. These findings pave the way for the experimental observation of the electromagnetic properties of efficient and simple models of biological tissues.

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.

Ruthenium(III) catalyzed oxidation of sugar alcohols by dichloroisocyanuric acid—A kinetic study

NASA Astrophysics Data System (ADS)

Lakshman Kumar, Y.; Venkata Nadh, R.; Radhakrishnamurti, P. S.

2016-02-01

Kinetics of ruthenium(III) catalyzed oxidation of biologically important sugar alcohols (myo-inositol, D-sorbitol, and D-mannitol) by dichloroisocyanuric acid was carried out in aqueous acetic acid—perchloric medium. The reactions were found to be first order in case of oxidant and ruthenium(III). Zero order was observed with the concentrations of sorbitol and mannitol whereas, a positive fractional order was found in the case of inositol concentration. An inverse fractional order was observed with perchloric acid in oxidation of three substrates. Arrhenius parameters were calculated and a plausible mechanism was proposed.

Thermomicrocapillaries as temperature biosensors in single cells

NASA Astrophysics Data System (ADS)

Herth, Simone; Giesguth, Miriam; Wedel, Waldemar; Reiss, Günther; Dietz, Karl-Josef

2013-03-01

Temperature is an important physical parameter in biology and its deviation from optimum can cause damage in biosystems. Thermocouples based on the Seebeck effect can be structured on glass microcapillaries to obtain thermomicrocapillaries (TMCs) usable in a micromanipulation setup. The suitability of the setup was proven by monitoring the temperature increase upon illumination of leaves and single cells following insertion of the TMC. The increase was 1.5 K in green tissue and 0.75 K in white leaf sections due to lower absorption. In single cells of trichomes, the increase was 0.5 K due to heat dissipation to the surrounding air.

Factors controlling threshold friction velocity in semiarid and arid areas of the United States

USGS Publications Warehouse

Marticorena, Beatrice; Bergametti, G.; Belnap, Jayne

1997-01-01

A physical model was developed to explain threshold friction velocities u*t for particles of the size 60a??120 I?m lying on a rough surface in loose soils for semiarid and arid parts of the United States. The model corrected for the effect of momentum absorption by the nonerodible roughness. For loose or disturbed soils the most important parameter that controls u*t is the aerodynamic roughness height z 0. For physical crusts damaged by wind the size of erodible crust pieces is important along with the roughness. The presence of cyanobacteriallichen soil crusts roughens the surface, and the biological fibrous growth aggregates soil particles. Only undisturbed sandy soils and disturbed soils of all types would be expected to be erodible in normal wind storms. Therefore disturbance of soils by both cattle and humans is very important in predicting wind erosion as confirmed by our measurements.

Emergence and Utility of Nonspherical Particles in Biomedicine

PubMed Central

Fish, Margaret B.; Thompson, Alex J.; Fromen, Catherine A.; Eniola-Adefeso, Omolola

2016-01-01

The importance of the size of targeted, spherical drug carriers has been previously explored and reviewed. Particle shape has emerged as an equally important parameter in determining the in vivo journey and efficiency of drug carrier systems. Researchers have invented techniques to better control the geometry of particles of many different materials, which have allowed for exploration of the role of particle geometry in the phases of drug delivery. The important biological processes include clearance by the immune system, trafficking to the target tissue, margination to the endothelial surface, interaction with the target cell, and controlled release of a payload. The review of current literature herein supports that particle shape can be altered to improve a system’s targeting efficiency. Non-spherical particles can harness the potential of targeted drug carriers by enhancing targeted site accumulation while simultaneously decreasing side effects and mitigating some limitations faced by spherical carriers. PMID:27182109

The beginning of Space Life Science in China exploration rockets for biological experiment during 1960's

NASA Astrophysics Data System (ADS)

Jiang, Peidong; Zhang, Jingxue

The first step of space biological experiment in China was a set of five exploration rockets launched during 1964 to 1966, by Shanghai Institute of Machine and Electricity, and Institute of Biophysics of The Chinese Academy of Sciences. Three T-7AS1rockets for rats, mice and other samples in a biological cabin were launched and recovered safely in July of 1964 and June of 1965. Two T-7AS2rockets for dog, rats, mice and other samples in a biological cabin were launched and recovered safely in July of 1966. Institute of Biophysics in charged of the general design of biological experiments, telemetry of physiological parameters, and selection and training of experiment animals. The samples on-board were: rats, mice, dogs, and test tubes with fruit fly, enzyme, bacteria, E. Coli., lysozyme, bacteriaphage, RNAase, DNAase, crystals of enzyme, etc. Physiological, biochemical, bacte-riological, immunological, genetic, histochemical studies had been conducted, in cellular and sub cellular level. The postures of rat and dog were monitored during flight and under weight-lessness. Physiological parameters of ECG, blood pressure, respiration rate, body temperature were recorded. A dog named"Xiao Bao"was flight in 1966 with video monitor, life support system and conditioned reflex equipment. It flighted for more than 20 minutes and about 70km high. After 40 years, the experimental data recorded of its four physiological parameters during the flight process was reviewed. The change of 4 parameters during various phase of total flight process were compared, analyzed and discussed.

Optimal properties for coated titanium implants with the hydroxyapatite layer formed by the pulsed laser deposition technique

NASA Astrophysics Data System (ADS)

Himmlova, Lucia; Dostalova, Tatjana; Jelinek, Miroslav; Bartova, Jirina; Pesakova, V.; Adam, M.

1999-02-01

Pulsed laser deposition technique allow to 'tailor' bioceramic coat for metal implants by the change of deposition conditions. Each attribute is influenced by the several deposition parameters and each parameter change several various properties. Problem caused that many parameters has an opposite function and improvement of one property is followed by deterioration of other attribute. This study monitor influence of each single deposition parameter and evaluate its importance form the point of view of coat properties. For deposition KrF excimer laser in stainless-steel deposition chamber was used. Deposition conditions (ambient composition and pressures, metallic substrate temperature, energy density and target-substrate distance) were changed according to the film properties. A non-coated titanium implant was used as a control. Films with promising mechanical quality underwent an in vitro biological tests -- measurement of proliferation activity, observing cell interactions with macrophages, fibroblasts, testing toxicity of percolates, observing a solubility of hydroxyapatite (HA) coat. Deposition conditions corresponding with the optimal mechanical and biochemical properties are: metal temperature 490 degrees Celsius, ambient-mixture of argon and water vapor, energy density 3 Jcm-2, target-substrate distance 7.5 cm.

Abiotic and biotic dynamics during the initial stages of high solids switchgrass degradation.

PubMed

Fontenelle, L T; Corgie, S C; Walker, L P

2011-07-01

An understanding of the underlying dynamics of how biotic variables drive changes in abiotic parameters in the early stages of biomass biodegradation is essential for better control of the process. Probe hybridization was used to quantitatively study the growth of bacteria, yeast and fungi for three levels of initial moisture content (60, 65 and 75% MC) over a period of 64 h. Changes in abiotic parameters were also documented. By 64 h, samples were significantly differentiated both in temporal and spatial dimension, proving that considerable changes had occurred in these initial stages. Maximum carbon (C) conversion occurred in the 75% MC reactor at a peak value of 49%, with 40% and 37% in the 65 and 60% MC reactors, respectively. Higher temperature, higher pH, higher rates of O2 consumption and CO2 evolution were also observed in the highest moisture reactor; suggesting that of the three MCs studied, 75% MC was the optimal one for the process. MC during the process also proved to be important because it greatly influenced variation in the spatial dimension, further underscoring the importance of characterizing changes with bed height. Most importantly, we were able to positively correlate the rate of substrate degradation with bacterial biomass levels and highlight the critical role of bacteria in biological decomposition.

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view. PMID:23515240

A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology.

PubMed

Chen, Bor-Sen; Lin, Ying-Po

2013-01-01

Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view.

Performance evaluation of a hybrid-passive landfill leachate treatment system using multivariate statistical techniques

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

Wallace, Jack, E-mail: jack.wallace@ce.queensu.ca; Champagne, Pascale, E-mail: champagne@civil.queensu.ca; Monnier, Anne-Charlotte, E-mail: anne-charlotte.monnier@insa-lyon.fr

Highlights: • Performance of a hybrid passive landfill leachate treatment system was evaluated. • 33 Water chemistry parameters were sampled for 21 months and statistically analyzed. • Parameters were strongly linked and explained most (>40%) of the variation in data. • Alkalinity, ammonia, COD, heavy metals, and iron were criteria for performance. • Eight other parameters were key in modeling system dynamics and criteria. - Abstract: A pilot-scale hybrid-passive treatment system operated at the Merrick Landfill in North Bay, Ontario, Canada, treats municipal landfill leachate and provides for subsequent natural attenuation. Collected leachate is directed to a hybrid-passive treatment system,more » followed by controlled release to a natural attenuation zone before entering the nearby Little Sturgeon River. The study presents a comprehensive evaluation of the performance of the system using multivariate statistical techniques to determine the interactions between parameters, major pollutants in the leachate, and the biological and chemical processes occurring in the system. Five parameters (ammonia, alkalinity, chemical oxygen demand (COD), “heavy” metals of interest, with atomic weights above calcium, and iron) were set as criteria for the evaluation of system performance based on their toxicity to aquatic ecosystems and importance in treatment with respect to discharge regulations. System data for a full range of water quality parameters over a 21-month period were analyzed using principal components analysis (PCA), as well as principal components (PC) and partial least squares (PLS) regressions. PCA indicated a high degree of association for most parameters with the first PC, which explained a high percentage (>40%) of the variation in the data, suggesting strong statistical relationships among most of the parameters in the system. Regression analyses identified 8 parameters (set as independent variables) that were most frequently retained for modeling the five criteria parameters (set as dependent variables), on a statistically significant level: conductivity, dissolved oxygen (DO), nitrite (NO{sub 2}{sup −}), organic nitrogen (N), oxidation reduction potential (ORP), pH, sulfate and total volatile solids (TVS). The criteria parameters and the significant explanatory parameters were most important in modeling the dynamics of the passive treatment system during the study period. Such techniques and procedures were found to be highly valuable and could be applied to other sites to determine parameters of interest in similar naturalized engineered systems.« less

Experimental Design for Parameter Estimation of Gene Regulatory Networks

PubMed Central

Timmer, Jens

2012-01-01

Systems biology aims for building quantitative models to address unresolved issues in molecular biology. In order to describe the behavior of biological cells adequately, gene regulatory networks (GRNs) are intensively investigated. As the validity of models built for GRNs depends crucially on the kinetic rates, various methods have been developed to estimate these parameters from experimental data. For this purpose, it is favorable to choose the experimental conditions yielding maximal information. However, existing experimental design principles often rely on unfulfilled mathematical assumptions or become computationally demanding with growing model complexity. To solve this problem, we combined advanced methods for parameter and uncertainty estimation with experimental design considerations. As a showcase, we optimized three simulated GRNs in one of the challenges from the Dialogue for Reverse Engineering Assessment and Methods (DREAM). This article presents our approach, which was awarded the best performing procedure at the DREAM6 Estimation of Model Parameters challenge. For fast and reliable parameter estimation, local deterministic optimization of the likelihood was applied. We analyzed identifiability and precision of the estimates by calculating the profile likelihood. Furthermore, the profiles provided a way to uncover a selection of most informative experiments, from which the optimal one was chosen using additional criteria at every step of the design process. In conclusion, we provide a strategy for optimal experimental design and show its successful application on three highly nonlinear dynamic models. Although presented in the context of the GRNs to be inferred for the DREAM6 challenge, the approach is generic and applicable to most types of quantitative models in systems biology and other disciplines. PMID:22815723

Computational structure analysis of biomacromolecule complexes by interface geometry.

PubMed

Mahdavi, Sedigheh; Salehzadeh-Yazdi, Ali; Mohades, Ali; Masoudi-Nejad, Ali

2013-12-01

The ability to analyze and compare protein-nucleic acid and protein-protein interaction interface has critical importance in understanding the biological function and essential processes occurring in the cells. Since high-resolution three-dimensional (3D) structures of biomacromolecule complexes are available, computational characterizing of the interface geometry become an important research topic in the field of molecular biology. In this study, the interfaces of a set of 180 protein-nucleic acid and protein-protein complexes are computed to understand the principles of their interactions. The weighted Voronoi diagram of the atoms and the Alpha complex has provided an accurate description of the interface atoms. Our method is implemented in the presence and absence of water molecules. A comparison among the three types of interaction interfaces show that RNA-protein complexes have the largest size of an interface. The results show a high correlation coefficient between our method and the PISA server in the presence and absence of water molecules in the Voronoi model and the traditional model based on solvent accessibility and the high validation parameters in comparison to the classical model. Copyright © 2013 Elsevier Ltd. All rights reserved.

Non-spherical micro- and nanoparticles: fabrication, characterization and drug delivery applications.

PubMed

Mathaes, Roman; Winter, Gerhard; Besheer, Ahmed; Engert, Julia

2015-03-01

Micro- and nanoparticles in drug and vaccine delivery have opened up new possibilities in pharmaceutics. In the past, researchers focused mainly on particle size, surface chemistry and the use of various materials to control particle characteristics and functions. Lately, shape has been acknowledged as an important design parameter having an impact on the interaction with biological systems. In this review, we report on the latest developments in fabrication methods to tailor particle geometry, summarize analytical techniques for non-spherical particles and highlight the most important findings regarding their interaction with biological systems and their potential applications in drug delivery. The impact of shape on particle internalization into different cell types and particle biodistribution has been extensively studied in the past. Current research focuses on shape-dependent uptake mechanisms and applications for tumour therapy and vaccination. Different fabrication methods can be used to produce a variety of different particle types and shapes. Key challenges will be the transfer of new non-spherical particle fabrication methods from lab-scale to industrial large-scale production. Not all techniques may be scalable for the production of high quantities of particles. It will also be challenging to transfer the promising in vitro findings to suitable in vivo models.

Physicochemical characterization of modified clay based composites obtained by a novel method

NASA Astrophysics Data System (ADS)

Kalra, Swati; Dudi, D.; Singh, G. P.; Verma, S. K.; Bhojak, N.

2018-05-01

Material science is one of the important fields where, absorption spectra of lanthanide ions have been a subject of several investigations because of their possible use as laser materials, diagnostic tools and sensors. Study of absorption spectra in visible and near infrared regions yields useful information regarding energy and intensity parameters, and nature and probabilities of transitions. Chemical physics provides fundamental tool to develop lanthanide chemistry, which has been increasingly significant in the last few years due to the wide variety of potential applications of their complexes in many important areas of biology and medicines. The present work describes the development of a novel method of composite preparation based on clay and its physiochemical characterization. Simultaneous measurement of some thermal properties has made study more useful. Results match with accepted models.

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.

Methods and means of 3D diffuse Mueller-matrix tomography of depolarizing optically anisotropic biological layers

NASA Astrophysics Data System (ADS)

Dubolazov, O. V.; Ushenko, V. O.; Trifoniuk, L.; Ushenko, Yu. O.; Zhytaryuk, V. G.; Prydiy, O. G.; Grytsyuk, M.; Kushnerik, L.; Meglinskiy, I.

2017-09-01

A new technique of Mueller-matrix mapping of polycrystalline structure of histological sections of biological tissues is suggested. The algorithms of reconstruction of distribution of parameters of linear and circular birefringence of prostate histological sections are found. The interconnections between such distributions and parameters of linear and circular birefringence of prostate tissue histological sections are defined. The comparative investigations of coordinate distributions of phase anisotropy parameters formed by fibrillar networks of prostate tissues of different pathological states (adenoma and carcinoma) are performed. The values and ranges of change of the statistical (moments of the 1st - 4th order) parameters of coordinate distributions of the value of linear and circular birefringence are defined. The objective criteria of cause of Benign and malignant conditions differentiation are determined.

A General Approach for Specifying Informative Prior Distributions for PBPK Model Parameters

EPA Science Inventory

Characterization of uncertainty in model predictions is receiving more interest as more models are being used in applications that are critical to human health. For models in which parameters reflect biological characteristics, it is often possible to provide estimates of paramet...

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.

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.

3D surface reconstruction and visualization of the Drosophila wing imaginal disc at cellular resolution

NASA Astrophysics Data System (ADS)

Bai, Linge; Widmann, Thomas; Jülicher, Frank; Dahmann, Christian; Breen, David

2013-01-01

Quantifying and visualizing the shape of developing biological tissues provide information about the morphogenetic processes in multicellular organisms. The size and shape of biological tissues depend on the number, size, shape, and arrangement of the constituting cells. To better understand the mechanisms that guide tissues into their final shape, it is important to investigate the cellular arrangement within tissues. Here we present a data processing pipeline to generate 3D volumetric surface models of epithelial tissues, as well as geometric descriptions of the tissues' apical cell cross-sections. The data processing pipeline includes image acquisition, editing, processing and analysis, 2D cell mesh generation, 3D contourbased surface reconstruction, cell mesh projection, followed by geometric calculations and color-based visualization of morphological parameters. In their first utilization we have applied these procedures to construct a 3D volumetric surface model at cellular resolution of the wing imaginal disc of Drosophila melanogaster. The ultimate goal of the reported effort is to produce tools for the creation of detailed 3D geometric models of the individual cells in epithelial tissues. To date, 3D volumetric surface models of the whole wing imaginal disc have been created, and the apicolateral cell boundaries have been identified, allowing for the calculation and visualization of cell parameters, e.g. apical cross-sectional area of cells. The calculation and visualization of morphological parameters show position-dependent patterns of cell shape in the wing imaginal disc. Our procedures should offer a general data processing pipeline for the construction of 3D volumetric surface models of a wide variety of epithelial tissues.

Effects of cover crops on soil quality: Selected chemical and biological parameters

USDA-ARS?s Scientific Manuscript database

Cover crops may improve soil physical, chemical, and biological properties and thus help improve land productivity. The objective of this study was to evaluate short-term changes (6, 9, and 12 weeks) in soil chemical and biological properties as influenced by cover crops for two different soils and...

Plasma medicine—current state of research and medical application

NASA Astrophysics Data System (ADS)

Weltmann, K.-D.; von Woedtke, Th

2017-01-01

Plasma medicine means the direct application of cold atmospheric plasma (CAP) on or in the human body for therapeutic purposes. Further, the field interacts strongly with results gained for biological decontamination. Experimental research as well as first practical application is realized using two basic principles of CAP sources: dielectric barrier discharges (DBD) and atmospheric pressure plasma jets (APPJ). Originating from the fundamental insights that the biological effects of CAP are most probably caused by changes of the liquid environment of cells, and are dominated by reactive oxygen and nitrogen species (ROS, RNS), basic mechanisms of biological plasma activity are identified. It was demonstrated that there is no increased risk of cold plasma application and, above all, there are no indications for genotoxic effects. The most important biological effects of cold atmospheric pressure plasma were identified: (1) inactivation of a broad spectrum of microorganisms including multidrug resistant ones; (2) stimulation of cell proliferation and tissue regeneration with lower plasma treatment intensity (treatment time); (3) inactivation of cells by initialization of programmed cell death (apoptosis) with higher plasma treatment intensity (treatment time). In recent years, the main focus of clinical applications was in the field of wound healing and treatment of infective skin diseases. First CAP sources are CE-certified as medical devices now which is the main precondition to start the introduction of plasma medicine into clinical reality. Plasma application in dentistry and, above all, CAP use for cancer treatment are becoming more and more important research fields in plasma medicine. A further in-depth knowledge of control and adaptation of plasma parameters and plasma geometries is needed to obtain suitable and reliable plasma sources for the different therapeutic indications and to open up new fields of medical application.

Evidence of opposing fitness effects of parental heterozygosity and relatedness in a critically endangered marine turtle?

PubMed

Phillips, K P; Jorgensen, T H; Jolliffe, K G; Richardson, D S

2017-11-01

How individual genetic variability relates to fitness is important in understanding evolution and the processes affecting populations of conservation concern. Heterozygosity-fitness correlations (HFCs) have been widely used to study this link in wild populations, where key parameters that affect both variability and fitness, such as inbreeding, can be difficult to measure. We used estimates of parental heterozygosity and genetic similarity ('relatedness') derived from 32 microsatellite markers to explore the relationship between genetic variability and fitness in a population of the critically endangered hawksbill turtle, Eretmochelys imbricata. We found no effect of maternal MLH (multilocus heterozygosity) on clutch size or egg success rate, and no single-locus effects. However, we found effects of paternal MLH and parental relatedness on egg success rate that interacted in a way that may result in both positive and negative effects of genetic variability. Multicollinearity in these tests was within safe limits, and null simulations suggested that the effect was not an artefact of using paternal genotypes reconstructed from large samples of offspring. Our results could imply a tension between inbreeding and outbreeding depression in this system, which is biologically feasible in turtles: female-biased natal philopatry may elevate inbreeding risk and local adaptation, and both processes may be disrupted by male-biased dispersal. Although this conclusion should be treated with caution due to a lack of significant identity disequilibrium, our study shows the importance of considering both positive and negative effects when assessing how variation in genetic variability affects fitness in wild systems. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Impacts of Bottom Fishing on Sediment Biogeochemical and Biological Parameters in Cohesive and Non-cohesive Sediments

NASA Astrophysics Data System (ADS)

Sciberras, M.; Hiddink, J. G.; Powell, C.; Parker, R.; Krӧger, S.; Bolam, S. G.; Robertson, C.

2016-02-01

Sediment resuspension and bed reworking by tides, waves and biological activity are frequent in the energetic coastal environments. Sediment mixing by tides and waves are generally more important in regulating sediment processes in advection-dominated system such as sandy sediments, whereas sediment reworking by bioturbation is more important in diffusion-dominated systems such as muddy sediments. Bottom fishing constitutes an additional significant impact on benthic communities and sediment biogeochemical processes in coastal areas through physical changes in sediment resuspension and mixing and changes to bioturbating fauna. This study examined the biological (macro-infaunal) and biogeochemical responses to fishing at a muddy and sandy site in the Irish Sea that were predominantly impacted by otter trawls and scallop dredges, respectively. The sandy habitat (>90% sand) was typical of a hydrodynamic environment characterized by a diverse array of small infaunal species, low organic carbon levels and fast remineralisation of organic matter in the sediment. The muddier habitat (>65% fines) was dominated by fewer but larger bioturbating species compared to sand, and illustrated highly diffusional solute transport, higher organic carbon content and a shallower oxygen penetration depth. Generally there appeared to be no clear statistically significant changes in the biogeochemistry of the sandy or muddy habitat that could be attributed to different intensities of fishing. However, pore-water nutrient profiles of ammonium, phosphate and silicate provided clear evidence of organic matter burial and/or mixing as a result of trawling at the muddy site. The biogeochemistry at the sandy site appeared to remain dominated by the natural physical environment, so impact of fishing disturbance was less evident. These results suggest that fishing does not have comparable effects on the biology and biogeochemical processes in all benthic habitats.

Genuine binding energy of the hydrated electron

PubMed Central

Luckhaus, David; Yamamoto, Yo-ichi; Suzuki, Toshinori; Signorell, Ruth

2017-01-01

The unknown influence of inelastic and elastic scattering of slow electrons in water has made it difficult to clarify the role of the solvated electron in radiation chemistry and biology. We combine accurate scattering simulations with experimental photoemission spectroscopy of the hydrated electron in a liquid water microjet, with the aim of resolving ambiguities regarding the influence of electron scattering on binding energy spectra, photoelectron angular distributions, and probing depths. The scattering parameters used in the simulations are retrieved from independent photoemission experiments of water droplets. For the ground-state hydrated electron, we report genuine values devoid of scattering contributions for the vertical binding energy and the anisotropy parameter of 3.7 ± 0.1 eV and 0.6 ± 0.2, respectively. Our probing depths suggest that even vacuum ultraviolet probing is not particularly surface-selective. Our work demonstrates the importance of quantitative scattering simulations for a detailed analysis of key properties of the hydrated electron. PMID:28508051

Evaluation of the biological effects of police radar RAMER 7F

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

Rotkovska, D.; Kautska, J.; Bartonickova, A.

1993-06-01

This paper presents results of experiments on the effects of electromagnetic radiation in the millimeter range (frequency 34.0 [+-] 0.1 GHz, power density 20 [mu]W/cm[sup 2]) emitted by a police radar device. Considering the physical properties of the radiation in millimeter range (skin effects), the experiments were carried out on hairless mice. The main physiological parameters tested were body mass, body temperature, peripheral blood, and mass and cellularity of several important organs. Critical organs, the skin, and cornea were examined by electron microscopy. Differentiation ability of hematopoietic cells, progenitors of granulocytes and macrophages, and DNA synthesis in the cornea weremore » compared in irradiated and nonirradiated animals. None of the parameters tested was affected to an extent that would indicate the start of a pathological process or the risk of damage to genetic material.« less

Use of Artificial Neural Networks to Examine Parameters Affecting the Immobilization of Streptokinase in Chitosan

PubMed Central

Modaresi, Seyed Mohamad Sadegh; Faramarzi, Mohammad Ali; Soltani, Arash; Baharifar, Hadi; Amani, Amir

2014-01-01

Streptokinase is a potent fibrinolytic agent which is widely used in treatment of deep vein thrombosis (DVT), pulmonary embolism (PE) and acute myocardial infarction (MI). Major limitation of this enzyme is its short biological half-life in the blood stream. Our previous report showed that complexing streptokinase with chitosan could be a solution to overcome this limitation. The aim of this research was to establish an artificial neural networks (ANNs) model for identifying main factors influencing the loading efficiency of streptokinase, as an essential parameter determining efficacy of the enzyme. Three variables, namely, chitosan concentration, buffer pH and enzyme concentration were considered as input values and the loading efficiency was used as output. Subsequently, the experimental data were modeled and the model was validated against a set of unseen data. The developed model indicated chitosan concentration as probably the most important factor, having reverse effect on the loading efficiency. PMID:25587327

A Maximum Likelihood Approach to Functional Mapping of Longitudinal Binary Traits

PubMed Central

Wang, Chenguang; Li, Hongying; Wang, Zhong; Wang, Yaqun; Wang, Ningtao; Wang, Zuoheng; Wu, Rongling

2013-01-01

Despite their importance in biology and biomedicine, genetic mapping of binary traits that change over time has not been well explored. In this article, we develop a statistical model for mapping quantitative trait loci (QTLs) that govern longitudinal responses of binary traits. The model is constructed within the maximum likelihood framework by which the association between binary responses is modeled in terms of conditional log odds-ratios. With this parameterization, the maximum likelihood estimates (MLEs) of marginal mean parameters are robust to the misspecification of time dependence. We implement an iterative procedures to obtain the MLEs of QTL genotype-specific parameters that define longitudinal binary responses. The usefulness of the model was validated by analyzing a real example in rice. Simulation studies were performed to investigate the statistical properties of the model, showing that the model has power to identify and map specific QTLs responsible for the temporal pattern of binary traits. PMID:23183762

Analysis of the fluctuations of the tumour/host interface

NASA Astrophysics Data System (ADS)

Milotti, Edoardo; Vyshemirsky, Vladislav; Stella, Sabrina; Dogo, Federico; Chignola, Roberto

2017-11-01

In a recent analysis of metabolic scaling in solid tumours we found a scaling law that interpolates between the power laws μ ∝ V and μ ∝V 2 / 3, where μ is the metabolic rate expressed as the glucose absorption rate and V is the tumour volume. The scaling law fits quite well both in vitro and in vivo data, however we also observed marked fluctuations that are associated with the specific biological properties of individual tumours. Here we analyse these fluctuations, in an attempt to find the population-wide distribution of an important parameter (A) which expresses the total extent of the interface between the solid tumour and the non-cancerous environment. Heuristic considerations suggest that the values of the A parameter follow a lognormal distribution, and, allowing for the large uncertainties of the experimental data, our statistical analysis confirms this.

Improvement of Biogas Production by Bioaugmentation

PubMed Central

Kovács, K. L.; Ács, N.; Kovács, E.; Wirth, R.; Rákhely, G.; Strang, Orsolya; Herbel, Zsófia; Bagi, Z.

2013-01-01

Biogas production technologies commonly involve the use of natural anaerobic consortia of microbes. The objective of this study was to elucidate the importance of hydrogen in this complex microbial food chain. Novel laboratory biogas reactor prototypes were designed and constructed. The fates of pure hydrogen-producing cultures of Caldicellulosiruptor saccharolyticus and Enterobacter cloacae were followed in time in thermophilic and mesophilic natural biogas-producing communities, respectively. Molecular biological techniques were applied to study the altered ecosystems. A systematic study in 5-litre CSTR digesters revealed that a key fermentation parameter in the maintenance of an altered population balance is the loading rate of total organic solids. Intensification of the biogas production was observed and the results corroborate that the enhanced biogas productivity is associated with the increased abundance of the hydrogen producers. Fermentation parameters did not indicate signs of failure in the biogas production process. Rational construction of more efficient and sustainable biogas-producing microbial consortia is proposed. PMID:23484123

On the strength of random fiber networks

NASA Astrophysics Data System (ADS)

Deogekar, S.; Picu, R. C.

2018-07-01

Damage accumulation and failure in random fiber networks is of importance in a variety of applications, from design of synthetic materials, such as paper and non-wovens, to accidental tearing of biological tissues. In this work we study these processes using three-dimensional models of athermal fiber networks, focusing attention on the modes of failure and on the relationship between network strength and network structural parameters. We consider network failure at small and large strains associated with the rupture of inter-fiber bonds. It is observed that the strength increases linearly with the network volume fraction and with the bond strength, while the stretch at peak stress is inversely related to these two parameters. A small fraction of the bonds rupture before peak stress and this fraction increases with increasing failure stretch. Rendering the bond strength stochastic causes a reduction of the network strength. However, heterogeneity retards damage localization and increases the stretch at peak stress, therefore promoting ductility.

Extraction of Blebs in Human Embryonic Stem Cell Videos.

PubMed

Guan, Benjamin X; Bhanu, Bir; Talbot, Prue; Weng, Nikki Jo-Hao

2016-01-01

Blebbing is an important biological indicator in determining the health of human embryonic stem cells (hESC). Especially, areas of a bleb sequence in a video are often used to distinguish two cell blebbing behaviors in hESC: dynamic and apoptotic blebbings. This paper analyzes various segmentation methods for bleb extraction in hESC videos and introduces a bio-inspired score function to improve the performance in bleb extraction. Full bleb formation consists of bleb expansion and retraction. Blebs change their size and image properties dynamically in both processes and between frames. Therefore, adaptive parameters are needed for each segmentation method. A score function derived from the change of bleb area and orientation between consecutive frames is proposed which provides adaptive parameters for bleb extraction in videos. In comparison to manual analysis, the proposed method provides an automated fast and accurate approach for bleb sequence extraction.

9 CFR 112.9 - Biological products imported for research and evaluation.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Biological products imported for research and evaluation. 112.9 Section 112.9 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... PACKAGING AND LABELING § 112.9 Biological products imported for research and evaluation. A biological...

9 CFR 112.9 - Biological products imported for research and evaluation.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Biological products imported for research and evaluation. 112.9 Section 112.9 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... PACKAGING AND LABELING § 112.9 Biological products imported for research and evaluation. A biological...

9 CFR 112.9 - Biological products imported for research and evaluation.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Biological products imported for research and evaluation. 112.9 Section 112.9 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... PACKAGING AND LABELING § 112.9 Biological products imported for research and evaluation. A biological...

9 CFR 112.9 - Biological products imported for research and evaluation.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 9 Animals and Animal Products 1 2014-01-01 2014-01-01 false Biological products imported for research and evaluation. 112.9 Section 112.9 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... PACKAGING AND LABELING § 112.9 Biological products imported for research and evaluation. A biological...

9 CFR 112.9 - Biological products imported for research and evaluation.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Biological products imported for research and evaluation. 112.9 Section 112.9 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION... PACKAGING AND LABELING § 112.9 Biological products imported for research and evaluation. A biological...

Minimum Winfree loop determines self-sustained oscillations in excitable Erdös-Rényi random networks.

PubMed

Qian, Yu; Cui, Xiaohua; Zheng, Zhigang

2017-07-18

The investigation of self-sustained oscillations in excitable complex networks is very important in understanding various activities in brain systems, among which the exploration of the key determinants of oscillations is a challenging task. In this paper, by investigating the influence of system parameters on self-sustained oscillations in excitable Erdös-Rényi random networks (EERRNs), the minimum Winfree loop (MWL) is revealed to be the key factor in determining the emergence of collective oscillations. Specifically, the one-to-one correspondence between the optimal connection probability (OCP) and the MWL length is exposed. Moreover, many important quantities such as the lower critical connection probability (LCCP), the OCP, and the upper critical connection probability (UCCP) are determined by the MWL. Most importantly, they can be approximately predicted by the network structure analysis, which have been verified in numerical simulations. Our results will be of great importance to help us in understanding the key factors in determining persistent activities in biological systems.

An appraisal of biological responses and network of environmental interactions in non-mining and mining impacted coastal waters.

PubMed

Fernandes, Christabelle E G; Malik, Ashish; Jineesh, V K; Fernandes, Sheryl O; Das, Anindita; Pandey, Sunita S; Kanolkar, Geeta; Sujith, P P; Velip, Dhillan M; Shaikh, Shagufta; Helekar, Samita; Gonsalves, Maria Judith; Nair, Shanta; LokaBharathi, P A

2015-08-01

The coastal waters of Goa and Ratnagiri lying on the West coast of India are influenced by terrestrial influx. However, Goa is influenced anthropogenically by iron-ore mining, while Ratnagiri is influenced by deposition of heavy minerals containing iron brought from the hinterlands. We hypothesize that there could be a shift in biological response along with changes in network of interactions between environmental and biological variables in these mining and non-mining impacted regions, lying 160 nmi apart. Biological and environmental parameters were analyzed during pre-monsoon season. Except silicates, the measured parameters were higher at Goa and related significantly, suggesting bacteria centric, detritus-driven region. At Ratnagiri, phytoplankton biomass related positively with silicate suggesting a region dominated by primary producers. This dominance perhaps got reflected as a higher tertiary yield. Thus, even though the regions are geographically proximate, the different biological response could be attributed to the differences in the web of interactions between the measured variables.

Degradation of PPCPs in activated sludge from different WWTPs in Denmark.

PubMed

Chen, Xijuan; Vollertsen, Jes; Nielsen, Jeppe Lund; Dall, Agnieszka Gieraltowska; Bester, Kai

2015-12-01

Pharmaceuticals and Personal care products (PPCPs) are often found in effluents from wastewater treatment plants (WWTPs) due to insufficient removal during wastewater treatment processes. To understand the factors affecting the removal of PPCPs in classical activated sludge WWTPs, the present study was performed to assess the removal of frequently occurring pharmaceuticals (Naproxen, Fenoprofen, Ketoprofen, Dichlofenac, Carbamazepine) and the biocide Triclosan in activated sludge from four different Danish WWTPs. The respective degradation constants were compared to operational parameters previous shown to be of importance for degradation of micropollutants such as biomass concentration, and sludge retention time (SRT). The most rapid degradation, was observed for NSAID pharmaceuticals (55-90% for Fenoprofen, 77-94% for Ketoprofen and 46-90% for Naproxen), followed by Triclosan (61-91%), while Dichlofenac and Carbamazepine were found to be persistent in the systems. Degradation rate constants were calculated as 0.0026-0.0407 for NSAID pharmaceuticals and 0.0022-0.0065 for triclosan. No relationships were observed between degradation rates and biomass concentrations in the diverse sludges. However, for the investigated PPCPs, the optimal SRT was within 14-20 days (for these values degradation of these PPCPs was the most efficient). Though all of these parameters influence the degradation rate, none of them seems to be overall decisive. These observations indicate that the biological composition of the sludge is more important than the design parameters of the respective treatment plant.

Assessing Interval Estimation Methods for Hill Model Parameters in a High-Throughput Screening Context (SOT)

EPA Science Inventory

The Hill model of concentration-response is ubiquitous in toxicology, perhaps because its parameters directly relate to biologically significant metrics of toxicity such as efficacy and potency. Point estimates of these parameters obtained through least squares regression or maxi...

Assessing Interval Estimation Methods for Hill Model Parameters in a High-Throughput Screening Context (IVIVE meeting)

EPA Science Inventory

The Hill model of concentration-response is ubiquitous in toxicology, perhaps because its parameters directly relate to biologically significant metrics of toxicity such as efficacy and potency. Point estimates of these parameters obtained through least squares regression or maxi...

Identification of Boolean Network Models From Time Series Data Incorporating Prior Knowledge.

PubMed

Leifeld, Thomas; Zhang, Zhihua; Zhang, Ping

2018-01-01

Motivation: Mathematical models take an important place in science and engineering. A model can help scientists to explain dynamic behavior of a system and to understand the functionality of system components. Since length of a time series and number of replicates is limited by the cost of experiments, Boolean networks as a structurally simple and parameter-free logical model for gene regulatory networks have attracted interests of many scientists. In order to fit into the biological contexts and to lower the data requirements, biological prior knowledge is taken into consideration during the inference procedure. In the literature, the existing identification approaches can only deal with a subset of possible types of prior knowledge. Results: We propose a new approach to identify Boolean networks from time series data incorporating prior knowledge, such as partial network structure, canalizing property, positive and negative unateness. Using vector form of Boolean variables and applying a generalized matrix multiplication called the semi-tensor product (STP), each Boolean function can be equivalently converted into a matrix expression. Based on this, the identification problem is reformulated as an integer linear programming problem to reveal the system matrix of Boolean model in a computationally efficient way, whose dynamics are consistent with the important dynamics captured in the data. By using prior knowledge the number of candidate functions can be reduced during the inference. Hence, identification incorporating prior knowledge is especially suitable for the case of small size time series data and data without sufficient stimuli. The proposed approach is illustrated with the help of a biological model of the network of oxidative stress response. Conclusions: The combination of efficient reformulation of the identification problem with the possibility to incorporate various types of prior knowledge enables the application of computational model inference to systems with limited amount of time series data. The general applicability of this methodological approach makes it suitable for a variety of biological systems and of general interest for biological and medical research.

Applications of Fluorescence Spectroscopy for dissolved organic matter characterization in wastewater treatment plants

NASA Astrophysics Data System (ADS)

Goffin, Angélique; Guérin, Sabrina; Rocher, Vincent; Varrault, Gilles

2016-04-01

Dissolved organic matter (DOM) influences wastewater treatment plants efficiency (WTTP): variations in its quality and quantity can induce a foaming phenomenon and a fouling event inside biofiltration processes. Moreover, in order to manage denitrification step (control and optimization of the nitrate recirculation), it is important to be able to estimate biodegradable organic matter quantity before biological treatment. But the current methods used to characterize organic matter quality, like biological oxygen demand are laborious, time consuming and sometimes not applicable to directly monitor organic matter in situ. In the context of MOCOPEE research program (www.mocopee.com), this study aims to assess the use of optical techniques, such as UV-Visible absorbance and more specifically fluorescence spectroscopy in order to monitor and to optimize process efficiency in WWTP. Fluorescence excitation-emission matrix (EEM) spectroscopy was employed to prospect the possibility of using this technology online and in real time to characterize dissolved organic matter in different effluents of the WWTP Seine Centre (240,000 m3/day) in Paris, France. 35 sewage water influent samples were collected on 10 days at different hours. Data treatment were performed by two methods: peak picking and parallel factor analysis (PARAFAC). An evolution of DOM quality (position of excitation - emission peaks) and quantity (intensity of fluorescence) was observed between the different treatment steps (influent, primary treatment, biological treatment, effluent). Correlations were found between fluorescence indicators and different water quality key parameters in the sewage influents. We developed different multivariate linear regression models in order to predict a variety of water quality parameters by fluorescence intensity at specific excitation-emission wavelengths. For example dissolved biological oxygen demand (r2=0,900; p<0,0001) and ammonium concentration (r2=0,898; p<0,0001) present good correlation with specific fluorescence peaks and indicators. These indicators derived from 3D spectrofluorescence could be used in order to characterize DOM online and thus to optimize process efficiency in WWTP.

Collective behaviour in vertebrates: a sensory perspective

PubMed Central

Collignon, Bertrand; Fernández-Juricic, Esteban

2016-01-01

Collective behaviour models can predict behaviours of schools, flocks, and herds. However, in many cases, these models make biologically unrealistic assumptions in terms of the sensory capabilities of the organism, which are applied across different species. We explored how sensitive collective behaviour models are to these sensory assumptions. Specifically, we used parameters reflecting the visual coverage and visual acuity that determine the spatial range over which an individual can detect and interact with conspecifics. Using metric and topological collective behaviour models, we compared the classic sensory parameters, typically used to model birds and fish, with a set of realistic sensory parameters obtained through physiological measurements. Compared with the classic sensory assumptions, the realistic assumptions increased perceptual ranges, which led to fewer groups and larger group sizes in all species, and higher polarity values and slightly shorter neighbour distances in the fish species. Overall, classic visual sensory assumptions are not representative of many species showing collective behaviour and constrain unrealistically their perceptual ranges. More importantly, caution must be exercised when empirically testing the predictions of these models in terms of choosing the model species, making realistic predictions, and interpreting the results. PMID:28018616

Aerobic stabilization of biological sludge characterized by an extremely low decay rate: modeling, identifiability analysis and parameter estimation.

PubMed

Martínez-García, C G; Olguín, M T; Fall, C

2014-08-01

Aerobic digestion batch tests were run on a sludge model that contained only two fractions, the heterotrophic biomass (XH) and its endogenous residue (XP). The objective was to describe the stabilization of the sludge and estimate the endogenous decay parameters. Modeling was performed with Aquasim, based on long-term data of volatile suspended solids and chemical oxygen demand (VSS, COD). Sensitivity analyses were carried out to determine the conditions for unique identifiability of the parameters. Importantly, it was found that the COD/VSS ratio of the endogenous residues (1.06) was significantly lower than for the active biomass fraction (1.48). The decay rate constant of the studied sludge (low bH, 0.025 d(-1)) was one-tenth that usually observed (0.2d(-1)), which has two main practical significances. Digestion time required is much more long; also the oxygen uptake rate might be <1.5 mg O₂/gTSSh (biosolids standards), without there being significant decline in the biomass. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identification and evaluation of air-pollution-tolerant plants around lignite-based thermal power station for greenbelt development.

PubMed

Govindaraju, M; Ganeshkumar, R S; Muthukumaran, V R; Visvanathan, P

2012-05-01

Thermal power plants emit various gaseous and particulate pollutants into the atmosphere. It is well known that trees help to reduce air pollution. Development of a greenbelt with suitable plant species around the source of emission will mitigate the air pollution. Selection of suitable plant species for a greenbelt is very important. Present study evaluates different plant species around Neyveli thermal power plant by calculating the Air Pollution Tolerance Index (APTI) which is based on their significant biochemical parameters. Also Anticipated Performance Index (API) was calculated for these plant species by combining APTI values with other socio-economic and biological parameters. Based on these indices, the most appropriate plant species were identified for the development of a greenbelt around the thermal power plant to mitigate air pollution. Among the 30 different plant species evaluated, Mangifere indica L. was identified as keystone species which is coming under the excellent category. Ambient air quality parameters were correlated with the biochemical characteristics of plant leaves and significant changes were observed in the plants biochemical characteristics due to the air pollution stress.

Multiphysics and Thermal Response Models to Improve Accuracy of Local Temperature Estimation in Rat Cortex under Microwave Exposure

PubMed Central

Kodera, Sachiko; Gomez-Tames, Jose; Hirata, Akimasa; Masuda, Hiroshi; Arima, Takuji; Watanabe, Soichi

2017-01-01

The rapid development of wireless technology has led to widespread concerns regarding adverse human health effects caused by exposure to electromagnetic fields. Temperature elevation in biological bodies is an important factor that can adversely affect health. A thermophysiological model is desired to quantify microwave (MW) induced temperature elevations. In this study, parameters related to thermophysiological responses for MW exposures were estimated using an electromagnetic-thermodynamics simulation technique. To the authors’ knowledge, this is the first study in which parameters related to regional cerebral blood flow in a rat model were extracted at a high degree of accuracy through experimental measurements for localized MW exposure at frequencies exceeding 6 GHz. The findings indicate that the improved modeling parameters yield computed results that match well with the measured quantities during and after exposure in rats. It is expected that the computational model will be helpful in estimating the temperature elevation in the rat brain at multiple observation points (that are difficult to measure simultaneously) and in explaining the physiological changes in the local cortex region. PMID:28358345

A simple model of hysteresis behavior using spreadsheet analysis

NASA Astrophysics Data System (ADS)

Ehrmann, A.; Blachowicz, T.

2015-01-01

Hysteresis loops occur in many scientific and technical problems, especially as field dependent magnetization of ferromagnetic materials, but also as stress-strain-curves of materials measured by tensile tests including thermal effects, liquid-solid phase transitions, in cell biology or economics. While several mathematical models exist which aim to calculate hysteresis energies and other parameters, here we offer a simple model for a general hysteretic system, showing different hysteresis loops depending on the defined parameters. The calculation which is based on basic spreadsheet analysis plus an easy macro code can be used by students to understand how these systems work and how the parameters influence the reactions of the system on an external field. Importantly, in the step-by-step mode, each change of the system state, compared to the last step, becomes visible. The simple program can be developed further by several changes and additions, enabling the building of a tool which is capable of answering real physical questions in the broad field of magnetism as well as in other scientific areas, in which similar hysteresis loops occur.

Critical modeling parameters identified for 3D CFD modeling of rectangular final settling tanks for New York City wastewater treatment plants.

PubMed

Ramalingam, K; Xanthos, S; Gong, M; Fillos, J; Beckmann, K; Deur, A; McCorquodale, J A

2012-01-01

New York City Environmental Protection is in the process of incorporating biological nitrogen removal (BNR) in its wastewater treatment plants (WWTPs) which entails operating the aeration tanks with higher levels of mixed liquor suspended solids (MLSS) than a conventional activated sludge process. The objective of this paper is to discuss two of the important parameters introduced in the 3D CFD model that has been developed by the City College of New York (CCNY) group: (a) the development of the 'discrete particle' measurement technique to carry out the fractionation of the solids in the final settling tank (FST) which has critical implications in the prediction of the effluent quality; and (b) the modification of the floc aggregation (K(A)) and floc break-up (K(B)) coefficients that are found in Parker's flocculation equation (Parker et al. 1970, 1971) used in the CFD model. The dependence of these parameters on the predictions of the CFD model will be illustrated with simulation results on one of the FSTs at the 26th Ward WWTP in Brooklyn, NY.

Thermotaxis is a Robust Mechanism for Thermoregulation in C. elegans Nematodes

PubMed Central

Ramot, Daniel; MacInnis, Bronwyn L.; Lee, Hau-Chen; Goodman, Miriam B.

2013-01-01

Many biochemical networks are robust to variations in network or stimulus parameters. Although robustness is considered an important design principle of such networks, it is not known whether this principle also applies to higher-level biological processes such as animal behavior. In thermal gradients, C. elegans uses thermotaxis to bias its movement along the direction of the gradient. Here we develop a detailed, quantitative map of C. elegans thermotaxis and use these data to derive a computational model of thermotaxis in the soil, a natural environment of C. elegans. This computational analysis indicates that thermotaxis enables animals to avoid temperatures at which they cannot reproduce, to limit excursions from their adapted temperature, and to remain relatively close to the surface of the soil, where oxygen is abundant. Furthermore, our analysis reveals that this mechanism is robust to large variations in the parameters governing both worm locomotion and temperature fluctuations in the soil. We suggest that, similar to biochemical networks, animals evolve behavioral strategies that are robust, rather than strategies that rely on fine-tuning of specific behavioral parameters. PMID:19020047

Parameter Calculation Technique for the Waste Treatment Facilities Using Naturally-Aerated Blocks in the Bog Ecosystems

NASA Astrophysics Data System (ADS)

Akhmed-Ogly, K. V.; Savichev, O. G.; Tokarenko, O. G.; Pasechnik, E. Yu; Reshetko, M. V.; Nalivajko, N. G.; Vlasova, M. V.

2014-08-01

Technique for the domestic wastewater treatment in the small residential areas and oil and gas facilities of the natural and man-made systems including a settling tank for mechanical treatment and a biological pond with peat substrate and bog vegetation for biological treatment has been substantiated. Technique for parameters calculation of the similar natural and man-made systems has been developed. It was proven that effective treatment of wastewater can be performed in Siberia all year round.

Additive genetic variance and developmental plasticity in growth trajectories in a wild cooperative mammal.

PubMed

Huchard, E; Charmantier, A; English, S; Bateman, A; Nielsen, J F; Clutton-Brock, T

2014-09-01

Individual variation in growth is high in cooperative breeders and may reflect plastic divergence in developmental trajectories leading to breeding vs. helping phenotypes. However, the relative importance of additive genetic variance and developmental plasticity in shaping growth trajectories is largely unknown in cooperative vertebrates. This study exploits weekly sequences of body mass from birth to adulthood to investigate sources of variance in, and covariance between, early and later growth in wild meerkats (Suricata suricatta), a cooperative mongoose. Our results indicate that (i) the correlation between early growth (prior to nutritional independence) and adult mass is positive but weak, and there are frequent changes (compensatory growth) in post-independence growth trajectories; (ii) among parameters describing growth trajectories, those describing growth rate (prior to and at nutritional independence) show undetectable heritability while associated size parameters (mass at nutritional independence and asymptotic mass) are moderately heritable (0.09 ≤ h(2) < 0.3); and (iii) additive genetic effects, rather than early environmental effects, mediate the covariance between early growth and adult mass. These results reveal that meerkat growth trajectories remain plastic throughout development, rather than showing early and irreversible divergence, and that the weak effects of early growth on adult mass, an important determinant of breeding success, are partly genetic. In contrast to most cooperative invertebrates, the acquisition of breeding status is often determined after sexual maturity and strongly impacted by chance in many cooperative vertebrates, who may therefore retain the ability to adjust their morphology to environmental changes and social opportunities arising throughout their development, rather than specializing early. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

The influence of environmental parameters in the biocolonization of the Mithraeum in the roman masonry of casa di Diana (Ostia Antica, Italy).

PubMed

Scatigno, C; Moricca, C; Tortolini, C; Favero, G

2016-07-01

The microclimatic parameters (Ta, RH, E, and CO2) reflect the indoor quality of the environment. Their relationship, connected with the design of the building, can facilitate the growth of photo/heterotrophic organisms and therefore facilitate the increase of the relative CO2 production. Taking this into account, the impact of biological proliferation in a historical building is discussed for the Mithraeum of "Casa di Diana" in the archaeological site of Ostia Antica, which is subjected to guided tours. In this work, for the first time, we propose a study on biological monitoring to evaluate the contribution of bioactivity to air quality, with the objective to increase the comfort of visitors and to open the site for more than one day per week, suggesting possible tools providing a good compromise between building conservation and human comfort. In the sense, it has been possible to distinguish the contribution of the plants from the one deriving from humans: high values of carbon dioxide have been recorded during the night and its scarce removal during the day (air flow). The window present is not sufficient to eliminate the CO2, involving concentrations of CO2 relatively high in comparison to the proposed limits and guidelines defined by law. The obtained results strongly encouraged the elimination of flora in order to increase the comfort of visitors and to open the house for more than one day per week. Although, this process involves an important economic effort, the present study allows making an objective decision which has an important value in a cultural heritage management. Graphical Abstract CO2 contribute by bioactivity as damage to human health.

Major factors influencing bacterial leaching of heavy metals (Cu and Zn) from anaerobic sludge.

PubMed

Couillard, D; Chartier, M; Mercier, G

1994-01-01

Anaerobically digested sewage sludges were treated for heavy metal removal through a biological solubilization process called bacterial leaching (bioleaching). The solubilization of copper and zinc from these sludges is described in this study: using continuously stirred tank reactors with and without sludge recycling at different mean hydraulic residence times (1, 2, 3 and 4 days). Significant linear equations were established for the solubilization of zinc and copper according to relevant parameters: oxygen reduction potential (ORP), pH and residence time (t). Zinc solubilization was related to the residence time with a r2 (explained variance) of 0.82. Considering only t=2 and 3 days explained variance of 0.31 and 0.24 were found between zinc solubilization as a function of ORP and pH indicating a minor importance of those two factors for this metal in the range of pH and ORP experimented. Cu solubilization was weakly correlated to mean hydraulic residence time (r2=0.48), while it was highly correlated to ORP (r2=0.80) and pH (r2=0.62) considering only t of 2 and 3 days in the case of pH and ORP. The ORP dependence of Cu solubilization has been clearly demonstrated in this study. In addition to this, the importance of the substrate concentration for Cu solubilization has been confirmed. The hypothesis of a biological solubilization of Cu by the indirect mechanism has been supported. The results permit, under optimum conditions, the drawing of linear equations which will allow prediction of metal solubilization efficiencies from the parameters pH (Cu), ORP (Cu) and residence time (Cu and Zn), during the treatment. The linear regressions will be a useful tool for routine operation of the process.

Antidrug Antibody Formation in Oncology: Clinical Relevance and Challenges.

PubMed

van Brummelen, Emilie M J; Ros, Willeke; Wolbink, Gertjan; Beijnen, Jos H; Schellens, Jan H M

2016-10-01

: In oncology, an increasing number of targeted anticancer agents and immunotherapies are of biological origin. These biological drugs may trigger immune responses that lead to the formation of antidrug antibodies (ADAs). ADAs are directed against immunogenic parts of the drug and may affect efficacy and safety. In other medical fields, such as rheumatology and hematology, the relevance of ADA formation is well established. However, the relevance of ADAs in oncology is just starting to be recognized, and literature on this topic is scarce. In an attempt to fill this gap in the literature, we provide an up-to-date status of ADA formation in oncology. In this focused review, data on ADAs was extracted from 81 clinical trials with biological anticancer agents. We found that most biological anticancer drugs in these trials are immunogenic and induce ADAs (63%). However, it is difficult to establish the clinical relevance of these ADAs. In order to determine this relevance, the possible effects of ADAs on pharmacokinetics, efficacy, and safety parameters need to be investigated. Our data show that this was done in fewer than 50% of the trials. In addition, we describe the incidence and consequences of ADAs for registered agents. We highlight the challenges in ADA detection and argue for the importance of validating, standardizing, and describing well the used assays. Finally, we discuss prevention strategies such as immunosuppression and regimen adaptations. We encourage the launch of clinical trials that explore these strategies in oncology. Because of the increasing use of biologicals in oncology, many patients are at risk of developing antidrug antibodies (ADAs) during therapy. Although clinical consequences are uncertain, ADAs may affect pharmacokinetics, patient safety, and treatment efficacy. ADA detection and reporting is currently highly inconsistent, which makes it difficult to evaluate the clinical consequences. Standardized reporting of ADA investigations in the context of the aforementioned parameters is critical to understanding the relevance of ADA formation for each drug. Furthermore, the development of trials that specifically aim to investigate clinical prevention strategies in oncology is needed. ©AlphaMed Press.

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI).

PubMed

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non-expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI's robustness and sensitivity in capturing useful data relating to the students' conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. © 2016 T. Deane et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Student Interpretations of Phylogenetic Trees in an Introductory Biology Course

ERIC Educational Resources Information Center

Dees, Jonathan; Momsen, Jennifer L.; Niemi, Jarad; Montplaisir, Lisa

2014-01-01

Phylogenetic trees are widely used visual representations in the biological sciences and the most important visual representations in evolutionary biology. Therefore, phylogenetic trees have also become an important component of biology education. We sought to characterize reasoning used by introductory biology students in interpreting taxa…

Helminth communities of four commercially important fish species from Chetumal Bay, Mexico.

PubMed

Aguirre-Macedo, M L; Vidal-Martínez, V M; González-Solís, D; Caballero, P I

2007-03-01

The relative importance of ecology and evolution as factors determining species richness and composition of the helminth communities of fish is a matter of current debate. Theoretical studies use host-parasite lists, but these do not include studies on a temporal or spatial scale. Local environmental conditions and host biological characteristics are shown to influence helminth species richness and composition in four fish species (Eugerres plumieri, Hexanematichthys assimilis, Oligoplites saurus, and Scomberomorus maculatus) in Chetumal Bay, Mexico. With the exception of H. assimilis, the helminth communities had not been previously studied and possible associations between environmental and host biological characteristics as factors determining helminth species richness and composition using redundancy analysis (RDA) are described. Thirty-four helminth species are identified, with the highest number of species (19 total (mean = 6.3 +/- 2.1)) and the lowest (9 (4.0 +/- 1.0)) occurring in H. assimilis and S. maculatus, respectively. The larval nematodes Contracaecum sp. and Pseudoterranova sp. were not only the helminth species shared by all four host species but also were the most prevalent and abundant. Statistical associations between helminth community parameters and local ecological variables such as host habitat use, feeding habits, mobility, and time of residence in coastal lagoons are identified. Phylogeny is important because it clearly separates all four host species by their specialist parasites, although specific habitat and feeding habits also significantly influence the differentiation between the four fish species.

Mucor indicus: biology and industrial application perspectives: a review.

PubMed

Karimi, Keikhosro; Zamani, Akram

2013-01-01

Mucor indicus, one of the most important strains of zygomycetes fungi, has been the subject of several studies since a couple of hundred years ago. This fungus, regarded as a non-pathogenic dimorphic microorganism, is used for production of several beers and foods. Morphology of the fungus can be manipulated and well controlled by changing a number of parameters. Furthermore, M. indicus can grow on a variety of substrates including lignocellulosic hydrolysates which are mixtures of hexoses, pentoses, and different severe fermentation inhibitors. Indeed, high yield ethanol production is among the most important features of this strain. Presence of considerable amounts of chitosan in the cell wall is another important aspect of the fungus. Besides production of ethanol and chitosan, the biomass of this fungus has shown a great potential to be used as a rich nutritional source, e.g. fish feed. The fungus is also among the oleaginous fungi and produces high amounts of polyunsaturated fatty acids particularly γ-linolenic acid. Furthermore, the biomass autolysate has a high potential for yeast extract replacement in fermentation by the fungus. Additionally, the strain has shown promising results in heavy metal removal from wastewaters. This review discusses different aspects of biology and industrial application perspectives of M. indicus. Furthermore, open areas for the future basic and applied levels of research are also presented. Copyright © 2013 Elsevier Inc. All rights reserved.

Education, income and ethnic differences in cumulative biological risk profiles in a national sample of US adults: NHANES III (1988-1994).

PubMed

Seeman, Teresa; Merkin, Sharon S; Crimmins, Eileen; Koretz, Brandon; Charette, Susan; Karlamangla, Arun

2008-01-01

Data from the nationally representative US National Health and Nutrition Examination Survey (NHANES) III cohort were used to examine the hypothesis that socio-economic status is consistently and negatively associated with levels of biological risk, as measured by nine biological parameters known to predict health risks (diastolic and systolic blood pressure, pulse, HDL and total cholesterol, glycosylated hemoglobin, c-reactive protein, albumin and waist-hip ratio), resulting in greater cumulative burdens of biological risk among those of lower education and/or income. As hypothesized, consistent education and income gradients were seen for biological parameters reflecting cardiovascular, metabolic and inflammatory risk: those with lower education and income exhibiting greater prevalence of high-risk values for each of nine individual biological risk factors. Significant education and income gradients were also seen for summary indices reflecting cumulative burdens of cardiovascular, metabolic and inflammatory risks as well as overall total biological risks. Multivariable cumulative logistic regression models revealed that the education and income effects were each independently and negatively associated with cumulative biological risks, and that these effects remained significant independent of age, gender, ethnicity and lifestyle factors such as smoking and physical activity. There were no significant ethnic differences in the patterns of association between socio-economic status and biological risks, but older age was associated with significantly weaker education and income gradients.

Genomic data assimilation for estimating hybrid functional Petri net from time-course gene expression data.

PubMed

Nagasaki, Masao; Yamaguchi, Rui; Yoshida, Ryo; Imoto, Seiya; Doi, Atsushi; Tamada, Yoshinori; Matsuno, Hiroshi; Miyano, Satoru; Higuchi, Tomoyuki

2006-01-01

We propose an automatic construction method of the hybrid functional Petri net as a simulation model of biological pathways. The problems we consider are how we choose the values of parameters and how we set the network structure. Usually, we tune these unknown factors empirically so that the simulation results are consistent with biological knowledge. Obviously, this approach has the limitation in the size of network of interest. To extend the capability of the simulation model, we propose the use of data assimilation approach that was originally established in the field of geophysical simulation science. We provide genomic data assimilation framework that establishes a link between our simulation model and observed data like microarray gene expression data by using a nonlinear state space model. A key idea of our genomic data assimilation is that the unknown parameters in simulation model are converted as the parameter of the state space model and the estimates are obtained as the maximum a posteriori estimators. In the parameter estimation process, the simulation model is used to generate the system model in the state space model. Such a formulation enables us to handle both the model construction and the parameter tuning within a framework of the Bayesian statistical inferences. In particular, the Bayesian approach provides us a way of controlling overfitting during the parameter estimations that is essential for constructing a reliable biological pathway. We demonstrate the effectiveness of our approach using synthetic data. As a result, parameter estimation using genomic data assimilation works very well and the network structure is suitably selected.

Macro-/micro-environment-sensitive chemosensing and biological imaging.

PubMed

Yang, Zhigang; Cao, Jianfang; He, Yanxia; Yang, Jung Ho; Kim, Taeyoung; Peng, Xiaojun; Kim, Jong Seung

2014-07-07

Environment-related parameters, including viscosity, polarity, temperature, hypoxia, and pH, play pivotal roles in controlling the physical or chemical behaviors of local molecules. In particular, in a biological environment, such factors predominantly determine the biological properties of the local environment or reflect corresponding status alterations. Abnormal changes in these factors would cause cellular malfunction or become a hallmark of the occurrence of severe diseases. Therefore, in recent years, they have increasingly attracted research interest from the fields of chemistry and biological chemistry. With the emergence of fluorescence sensing and imaging technology, several fluorescent chemosensors have been designed to respond to such parameters and to further map their distributions and variations in vitro/in vivo. In this work, we have reviewed a number of various environment-responsive chemosensors related to fluorescent recognition of viscosity, polarity, temperature, hypoxia, and pH that have been reported thus far.

Identifying data gaps and prioritizing restoration strategies for Fremont cottonwood using linked geomorphic and population models

NASA Astrophysics Data System (ADS)

Harper, E. B.; Stella, J. C.; Fremier, A. K.

2009-12-01

Fremont cottonwood (Populus fremontii) is an important component of semi-arid riparian ecosystems throughout western North America, but its populations are in decline due to flow regulation. Achieving a balance between human resource needs and riparian ecosystem function requires a mechanistic understanding of the multiple geomorphic and biological factors affecting tree recruitment and survival, including the timing and magnitude of river flows, and the concomitant influence on suitable habitat creation and mortality from scour and sedimentation burial. Despite a great deal of empirical research on some components of the system, such as factors affecting cottonwood recruitment, other key components are less studied. Yet understanding the relative influence of the full suite of physical and life-history drivers is critical to modeling whole-population dynamics under changing environmental conditions. We addressed these issues for the Fremont cottonwood population along the Sacramento River, CA using a sensitivity analysis approach to quantify uncertainty in parameters on the outcomes of a patch-based, dynamic population model. Using a broad range of plausible values for 15 model parameters that represent key physical, biological and climatic components of the ecosystem, we ran 1,000 population simulations that consisted of a subset of 14.3 million possible combinations of parameter estimates to predict the frequency of patch colonization and total forest habitat predicted to occur under current hydrologic conditions after 175 years. Results indicate that Fremont cottonwood populations are highly sensitive to the interactions among flow regime, sedimentation rate and the depth of the capillary fringe (Fig. 1). Estimates of long-term floodplain sedimentation rate would substantially improve model accuracy. Spatial variation in sediment texture was also important to the extent that it determines the depth of the capillary fringe, which regulates the availability of water for germination and adult tree growth. Our sensitivity analyses suggest that models of future scenarios should incorporate regional climate change projections because changes in temperature and the timing and volume of precipitation affects sensitive aspects of the system, including the timing of seed release and spring snowmelt runoff. Figure 1. The relative effects on model predictions of uncertainty around each parameter included in the patch-based population model for Fremont cottonwood.

Process-based modeling of silicate mineral weathering responses to increasing atmospheric CO2 and climate change

NASA Astrophysics Data System (ADS)

Banwart, Steven A.; Berg, Astrid; Beerling, David J.

2009-12-01

A mathematical model describes silicate mineral weathering processes in modern soils located in the boreal coniferous region of northern Europe. The process model results demonstrate a stabilizing biological feedback mechanism between atmospheric CO2 levels and silicate weathering rates as is generally postulated for atmospheric evolution. The process model feedback response agrees within a factor of 2 of that calculated by a weathering feedback function of the type generally employed in global geochemical carbon cycle models of the Earth's Phanerozoic CO2 history. Sensitivity analysis of parameter values in the process model provides insight into the key mechanisms that influence the strength of the biological feedback to weathering. First, the process model accounts for the alkalinity released by weathering, whereby its acceleration stabilizes pH at values that are higher than expected. Although the process model yields faster weathering with increasing temperature, because of activation energy effects on mineral dissolution kinetics at warmer temperature, the mineral dissolution rate laws utilized in the process model also result in lower dissolution rates at higher pH values. Hence, as dissolution rates increase under warmer conditions, more alkalinity is released by the weathering reaction, helping maintain higher pH values thus stabilizing the weathering rate. Second, the process model yields a relatively low sensitivity of soil pH to increasing plant productivity. This is due to more rapid decomposition of dissolved organic carbon (DOC) under warmer conditions. Because DOC fluxes strongly influence the soil water proton balance and pH, this increased decomposition rate dampens the feedback between productivity and weathering. The process model is most sensitive to parameters reflecting soil structure; depth, porosity, and water content. This suggests that the role of biota to influence these characteristics of the weathering profile is as important, if not more important, than the role of biota to influence mineral dissolution rates through changes in soil water chemistry. This process-modeling approach to quantify the biological weathering feedback to atmospheric CO2 demonstrates the potential for a far more mechanistic description of weathering feedback in simulations of the global geochemical carbon cycle.

Wear Debris Characterization and Corresponding Biological Response: Artificial Hip and Knee Joints

PubMed Central

Nine, Md J.; Choudhury, Dipankar; Hee, Ay Ching; Mootanah, Rajshree; Osman, Noor Azuan Abu

2014-01-01

Wear debris, of deferent sizes, shapes and quantities, generated in artificial hip and knees is largely confined to the bone and joint interface. This debris interacts with periprosthetic tissue and may cause aseptic loosening. The purpose of this review is to summarize and collate findings of the recent demonstrations on debris characterization and their biological response that influences the occurrence in implant migration. A systematic review of peer-reviewed literature is performed, based on inclusion and exclusion criteria addressing mainly debris isolation, characterization, and biologic responses. Results show that debris characterization largely depends on their appropriate and accurate isolation protocol. The particles are found to be non-uniform in size and non-homogeneously distributed into the periprosthetic tissues. In addition, the sizes, shapes, and volumes of the particles are influenced by the types of joints, bearing geometry, material combination, and lubricant. Phagocytosis of wear debris is size dependent; high doses of submicron-sized particles induce significant level of secretion of bone resorbing factors. However, articles on wear debris from engineered surfaces (patterned and coated) are lacking. The findings suggest considering debris morphology as an important parameter to evaluate joint simulator and newly developed implant materials. PMID:28788496

Confronting uncertainty in wildlife management: performance of grizzly bear management.

PubMed

Artelle, Kyle A; Anderson, Sean C; Cooper, Andrew B; Paquet, Paul C; Reynolds, John D; Darimont, Chris T

2013-01-01

Scientific management of wildlife requires confronting the complexities of natural and social systems. Uncertainty poses a central problem. Whereas the importance of considering uncertainty has been widely discussed, studies of the effects of unaddressed uncertainty on real management systems have been rare. We examined the effects of outcome uncertainty and components of biological uncertainty on hunt management performance, illustrated with grizzly bears (Ursus arctos horribilis) in British Columbia, Canada. We found that both forms of uncertainty can have serious impacts on management performance. Outcome uncertainty alone--discrepancy between expected and realized mortality levels--led to excess mortality in 19% of cases (population-years) examined. Accounting for uncertainty around estimated biological parameters (i.e., biological uncertainty) revealed that excess mortality might have occurred in up to 70% of cases. We offer a general method for identifying targets for exploited species that incorporates uncertainty and maintains the probability of exceeding mortality limits below specified thresholds. Setting targets in our focal system using this method at thresholds of 25% and 5% probability of overmortality would require average target mortality reductions of 47% and 81%, respectively. Application of our transparent and generalizable framework to this or other systems could improve management performance in the presence of uncertainty.

Cell refractive index for cell biology and disease diagnosis: past, present and future.

PubMed

Liu, P Y; Chin, L K; Ser, W; Chen, H F; Hsieh, C-M; Lee, C-H; Sung, K-B; Ayi, T C; Yap, P H; Liedberg, B; Wang, K; Bourouina, T; Leprince-Wang, Y

2016-02-21

Cell refractive index is a key biophysical parameter, which has been extensively studied. It is correlated with other cell biophysical properties including mechanical, electrical and optical properties, and not only represents the intracellular mass and concentration of a cell, but also provides important insight for various biological models. Measurement techniques developed earlier only measure the effective refractive index of a cell or a cell suspension, providing only limited information on cell refractive index and hence hindering its in-depth analysis and correlation. Recently, the emergence of microfluidic, photonic and imaging technologies has enabled the manipulation of a single cell and the 3D refractive index of a single cell down to sub-micron resolution, providing powerful tools to study cells based on refractive index. In this review, we provide an overview of cell refractive index models and measurement techniques including microfluidic chip-based techniques for the last 50 years, present the applications and significance of cell refractive index in cell biology, hematology, and pathology, and discuss future research trends in the field, including 3D imaging methods, integration with microfluidics and potential applications in new and breakthrough research areas.

Structure investigation of three hydrazones Schiff's bases by spectroscopic, thermal and molecular orbital calculations and their biological activities

NASA Astrophysics Data System (ADS)

Belal, Arafa A. M.; Zayed, M. A.; El-Desawy, M.; Rakha, Sh. M. A. H.

2015-03-01

Three Schiff's bases AI (2(1-hydrazonoethyl)phenol), AII (2, 4-dibromo 6-(hydrazonomethyl)phenol) and AIII (2(hydrazonomethyl)phenol) were prepared as new hydrazone compounds via condensation reactions with molar ratio (1:1) of reactants. Firstly by reaction of 2-hydroxy acetophenone solution and hydrazine hydrate; it gives AI. Secondly condensation between 3,5-dibromo-salicylaldehyde and hydrazine hydrate gives AII. Thirdly condensation between salicylaldehyde and hydrazine hydrate gives AIII. The structures of AI-AIII were characterized by elemental analysis (EA), mass (MS), FT-IR and 1H NMR spectra, and thermal analyses (TG, DTG, and DTA). The activation thermodynamic parameters, such as, ΔE∗, ΔH∗, ΔS∗ and ΔG∗ were calculated from the TG curves using Coats-Redfern method. It is important to investigate their molecular structures to know the active groups and weak bond responsible for their biological activities. Consequently in the present work, the obtained thermal (TA) and mass (MS) practical results are confirmed by semi-empirical MO-calculations (MOCS) using PM3 procedure. Their biological activities have been tested in vitro against Escherichia coli, Proteus vulgaris, Bacillissubtilies and Staphylococcus aurous bacteria in order to assess their anti-microbial potential.

Choosing an Appropriate Modelling Framework for Analysing Multispecies Co-culture Cell Biology Experiments.

PubMed

Markham, Deborah C; Simpson, Matthew J; Baker, Ruth E

2015-04-01

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insufficient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

Reticulocytes in sports medicine.

PubMed

Banfi, Giuseppe

2008-01-01

Reticulocytes are the transitional cells from erythroblasts to mature erythrocytes. Reticulocytes are present in blood for a period of 1-4 days and can be recognized by staining with supravital dyes, such as new methylene blue, or fluorescent markers, which couple residual nucleic acid molecules, a hallmark of the immature forms of erythrocytes. Although reticulocytes could be counted through a microscope (there is a standard of International Committee for Standardisation in Haematology for manual counting), this method is reported to be time consuming, inaccurate and imprecise. The integration of the reticulocyte count in automated haematology systems allowed the widespread use of these parameters, although the lack of calibration material and different markers, technologies and software used in automated systems could engender discrepancies among data obtained from different analytical systems.The importance of reticulocytes in sports medicine derives from their sensitivity, the highest among haematology parameters, in identifying the bone marrow stimulation, especially when recombinant human erythropoietin is fraudulently used. Automated systems are also able to supply information on volume, density and the haemoglobin content of reticulocytes. Some of the related parameters are also used in algorithms for identifying abnormal stimulation of bone marrow as reticulocytes haematocrit. The pre-analytical variability of reticulocytes (transportation, storage, biological variability) should be taken into account in sports medicine also. Reticulocytes remain stable for almost 24 hours at 4 degrees C from blood drawing, they are affected by transportation, and biological variability is not high in general. It could be remarked, however, that the intra-individual variability is high when compared with other haematological parameters such as haemoglobin and haematocrit. The intervals of data reported in athletes are very similar to reference intervals characterizing the general population.The reticulocyte count shows some modifications after training and during the competition season. The variability induced by exercise cannot be overlooked since the so-called haematological passport, a personal athlete's document in which haemoglobin and other parameters are registered, may be introduced by sports federations. Exposure to naturally high altitude and 'living high-training low' programmes determined contentious results on reticulocytes. Simulated high altitude induced by intermittent hypobaric hypoxia does not modify reticulocytes, despite an increase in erythropoietin serum concentration. The variability among athletes competing in different sport disciplines is apparently limited. The knowledge of the behaviour of reticulocytes in training and competitions is crucial for defining their role in an antidoping control context. It is important for sport physicians and clinical pathologists to know the reticulocyte variability in the general population and in athletes, the pre-analytical warnings, the different methodologies for counting reticulocytes and the derived parameters automatically available, and, finally, the possible influence of training, competitions, type of sport and altitude.

Spreading speeds for plant populations in landscapes with low environmental variation.

PubMed

Gilbert, Mark A; Gaffney, Eamonn A; Bullock, James M; White, Steven M

2014-12-21

Characterising the spread of biological populations is crucial in responding to both biological invasions and the shifting of habitat under climate change. Spreading speeds can be studied through mathematical models such as the discrete-time integro-difference equation (IDE) framework. The usual approach in implementing IDE models has been to ignore spatial variation in the demographic and dispersal parameters and to assume that these are spatially homogeneous. On the other hand, real landscapes are rarely spatially uniform with environmental variation being very important in determining biological spread. This raises the question of under what circumstances spatial structure need not be modelled explicitly. Recent work has shown that spatial variation can be ignored for the specific case where the scale of landscape variation is much smaller than the spreading population׳s dispersal scale. We consider more general types of landscape, where the spatial scales of environmental variation are arbitrarily large, but the maximum change in environmental parameters is relatively small. We find that the difference between the wave-speeds of populations spreading in a spatially structured periodic landscape and its homogenisation is, in general, proportional to ϵ(2), where ϵ governs the degree of environmental variation. For stochastically generated landscapes we numerically demonstrate that the error decays faster than ϵ. In both cases, this means that for sufficiently small ϵ, the homogeneous approximation is better than might be expected. Hence, in many situations, the precise details of the landscape can be ignored in favour of spatially homogeneous parameters. This means that field ecologists can use the homogeneous IDE as a relatively simple modelling tool--in terms of both measuring parameter values and doing the modelling itself. However, as ϵ increases, this homogeneous approximation loses its accuracy. The change in wave-speed due to the extrinsic (landscape) variation can be positive or negative, which is in contrast to the reduction in wave-speed caused by intrinsic stochasticity. To deal with the loss of accuracy as ϵ increases, we formulate a second-order approximation to the wave-speed for periodic landscapes and compare both approximations against the results of numerical simulation and show that they are both accurate for the range of landscapes considered. Copyright © 2014 Elsevier Ltd. All rights reserved.

Larval food quantity affects development time, survival and adult biological traits that influence the vectorial capacity of Anopheles darlingi under laboratory conditions.

PubMed

Araújo, Maisa da-Silva; Gil, Luiz Herman S; e-Silva, Alexandre de-Almeida

2012-08-02

The incidence of malaria in the Amazon is seasonal and mosquito vectorial capacity parameters, including abundance and longevity, depend on quantitative and qualitative aspects of the larval diet. Anopheles darlingi is a major malaria vector in the Amazon, representing >95% of total Anopheles population present in the Porto Velho region. Despite its importance in the transmission of the Plasmodium parasite, knowledge of the larval biology and ecology is limited. Studies regarding aspects of adult population ecology are more common than studies on larval ecology. However, in order develop effective control strategies and laboratory breeding conditions for this species, more data on the factors affecting vector biology is needed. The aim of the present study is to assess the effects of larval food quantity on the vectorial capacity of An. darling under laboratory conditions. Anopheles darlingi was maintained at 28°C, 80% humidity and exposed to a daily photoperiod of 12 h. Larvae were divided into three experimental groups that were fed either a low, medium, or high food supply (based on the food amounts consumed by other species of culicids). Each experiment was replicated for six times. A cohort of adults were also exposed to each type of diet and assessed for several biological characteristics (e.g. longevity, bite frequency and survivorship), which were used to estimate the vectorial capacity of each experimental group. The group supplied with higher food amounts observed a reduction in development time while larval survival increased. In addition to enhanced longevity, increasing larval food quantity was positively correlated with increasing frequency of bites, longer blood meal duration and wing length, resulting in greater vectorial capacity. However, females had greater longevity than males despite having smaller wings. Overall, several larval and adult biological traits were significantly affected by larval food availability. Greater larval food supply led to enhance larval and production and larger mosquitoes with longer longevity and higher biting frequency. Thus, larval food availability can alter important biological traits that influence the vectorial capacity of An. darlingi.

Real versus Simulated Mobile Phone Exposures in Experimental Studies

PubMed Central

Panagopoulos, Dimitris J.; Johansson, Olle; Carlo, George L.

2015-01-01

We examined whether exposures to mobile phone radiation in biological/clinical experiments should be performed with real-life Electromagnetic Fields (EMFs) emitted by commercially available mobile phone handsets, instead of simulated EMFs emitted by generators or test phones. Real mobile phone emissions are constantly and unpredictably varying and thus are very different from simulated emissions which employ fixed parameters and no variability. This variability is an important parameter that makes real emissions more bioactive. Living organisms seem to have decreased defense against environmental stressors of high variability. While experimental studies employing simulated EMF-emissions present a strong inconsistency among their results with less than 50% of them reporting effects, studies employing real mobile phone exposures demonstrate an almost 100% consistency in showing adverse effects. This consistency is in agreement with studies showing association with brain tumors, symptoms of unwellness, and declines in animal populations. Average dosimetry in studies with real emissions can be reliable with increased number of field measurements, and variation in experimental outcomes due to exposure variability becomes less significant with increased number of experimental replications. We conclude that, in order for experimental findings to reflect reality, it is crucially important that exposures be performed by commercially available mobile phone handsets. PMID:26346766

Structural Connectivity Networks of Transgender People

PubMed Central

Hahn, Andreas; Kranz, Georg S.; Küblböck, Martin; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F.; Lanzenberger, Rupert

2015-01-01

Although previous investigations of transsexual people have focused on regional brain alterations, evaluations on a network level, especially those structural in nature, are largely missing. Therefore, we investigated the structural connectome of 23 female-to-male (FtM) and 21 male-to-female (MtF) transgender patients before hormone therapy as compared with 25 female and 25 male healthy controls. Graph theoretical analysis of whole-brain probabilistic tractography networks (adjusted for differences in intracranial volume) showed decreased hemispheric connectivity ratios of subcortical/limbic areas for both transgender groups. Subsequent analysis revealed that this finding was driven by increased interhemispheric lobar connectivity weights (LCWs) in MtF transsexuals and decreased intrahemispheric LCWs in FtM patients. This was further reflected on a regional level, where the MtF group showed mostly increased local efficiencies and FtM patients decreased values. Importantly, these parameters separated each patient group from the remaining subjects for the majority of significant findings. This work complements previously established regional alterations with important findings of structural connectivity. Specifically, our data suggest that network parameters may reflect unique characteristics of transgender patients, whereas local physiological aspects have been shown to represent the transition from the biological sex to the actual gender identity. PMID:25217469

[Effect of magnesium deficiency on photosynthetic physiology and triacylglyceride (TAG) accumulation of Chlorella vulgaris].

PubMed

Wang, Shan; Zhao, Shu-Xin; Wei, Chang-Long; Yu, Shui-Yan; Shi, Ji-Ping; Zhang, Bao-Guo

2014-04-01

As an excellent biological resource, Chlorella has wide applications for production of biofuel, bioactive substances and water environment restoration. Therefore, it is very important to understand the photosynthetic physiology characteristics of Chlorella. Magnesium ions play an important role in the growth of microalgae, not only the central atom of chlorophyll, but also the cofactor of some key enzyme in the metabolic pathway. A laboratory study was conducted to evaluate the effects of magnesium deficiency on several photosynthetic and physiological parameters and the triacylglyceride (TAG) accumulation of the green alga, Chlorella vulgaris, in the photoautotrophic culture process. Chlorella vulgaris biomass, protein, chlorophyll a and chlorophyll b contents decreased by 20%, 43.96%, 27.52% and 28.07% in response to magnesium deficiency, while the total oil content increased by 19.60%. Moreover, magnesium deficiency decreased the maximal photochemical efficiency F(v)/F(m) by 22.54%, but increased the non-photochemical quenching parameters qN. Our results indicated the decline of chlorophyll caused by magnesium, which affected the photosynthesis efficiency, lead to the growth inhibition of Chlorella vulgaris and affected the protein synthesis and increased the triacylglyceride (TAG) accumulation.

Physical development and swimming performance during biological maturation in young female swimmers.

PubMed

Lätt, Evelin; Jürimäe, Jaak; Haljaste, Kaja; Cicchella, Antonio; Purge, Priit; Jürimäe, Toivo

2009-03-01

The present study analyzed the development of physiological, biomechanical and anthropometrical parameters in young female swimmers and assessed the effect of these parameters on swimming performance during biological maturation. In total, 26 female swimmers participated in the study in which data were annually collected for two consecutive years. Body composition, basic anthropometrical parameters and biological age were measured. During the 400-m front-crawl swimming, the energy cost of swimming and stroking parameters were assessed. Peak oxygen consumption (VO2(peak)) was assessed by means of the backward-extrapolation technique recording VO2 during the first 20 sec of the recovery period after a maximal trial of 400-m distance. During the 2-year follow-up study period, age, height, body mass, body fat %, fat free mass, bone mineral mass, total bone mineral density, arm span and biological maturation values significantly increased during each year (p < 0.05). The tracking of the physical characteristics measured over the 2-year study period was relatively high (r > 0.694), except for the body fat% (r > 0.554). The tracking of the Tanner stages was also high (r = 0.759-0.780). Stepwise regression analyses showed that biomechanical factors (R2 > 0.322; p < 0.05) best characterized the 400-metre swimming performance in young female swimmers, followed by bioenergetical (R2 > 0.311; p < 0.05) and physical (R2 > 0.203; p < 0.05) factors during all three measurement times.

Population and biological parameters of selected fish species from the middle Xingu River, Amazon Basin.

PubMed

Camargo, M; Giarrizzo, T; Isaac, V J

2015-08-01

This study estimates the main biological parameters, including growth rates, asymptotic length, mortality, consumption by biomass, biological yield, and biomass, for the most abundant fish species found on the middle Xingu River, prior to the construction of the Belo Monte Dam. The specimens collected in experimental catches were analysed with empirical equations and length-based FISAT methods. For the 63 fish species studied, high growth rates (K) and high natural mortality (M) were related to early sexual maturation and low longevity. The predominance of species with short life cycles and a reduced number of age classes, determines high rates of stock turnover, which indicates high productivity for fisheries, and a low risk of overfishing.

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

PubMed

Lakatos, Eszter; Stumpf, Michael P H

2017-08-01

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

Control mechanisms for stochastic biochemical systems via computation of reachable sets

PubMed Central

Lakatos, Eszter

2017-01-01

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

Results of heavy ion radiotherapy

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

Castro, J.R.

1994-04-01

The potential of heavy ion therapy for clinical use in cancer therapy stems from the biological parameters of heavy charged particles, and their precise dose localization. Biologically, carbon, neon and other heavy ion beams (up to about silicon) are clinically useful in overcoming the radioresistance of hypoxic tumors, thus increasing biological effectiveness relative to low-LET x-ray or electron beams. Cells irradiated by heavy ions show less variation in cell-cycle related radiosensitivity and decreased repair of radiation injury. The physical parameters of these heavy charged particles allow precise delivery of high radiation doses to tumors while minimizing irradiation of normal tissues.more » Clinical use requires close interaction between radiation oncologists, medical physicists, accelerator physicists, engineers, computer scientists and radiation biologists.« less

Quantification of tissue texture with photoacoustic spectrum analysis

NASA Astrophysics Data System (ADS)

Wang, Xueding; Xu, Guan; Meng, Zhuo-Xian; Lin, Jiandie; Carson, Paul

2014-05-01

Photoacoustic (PA) imaging is an emerging technology that could map the functional contrasts in deep biological tissues in high resolution by "listening" to the laser induced thermoelastic waves. Almost all of the current studies in PA imaging are focused on the intensity of the PA signals as an indication of the optical absorbance of the biological tissues. Our group has for the first time demonstrated that the frequency domain power distribution of the broadband PA signals encode the texture information within the regions-of-interest (ROI). Following the similar method of ultrasound spectral analysis (USSA), photoacoustic spectrum analysis (PASA) could evaluate the relative concentrations and, more importantly, the dimensions of microstructures of the optically absorbing materials in biological tissues, including lipid, collagen, water and hemoglobin. By providing valuable insights into tissue pathology, PASA should benefit basic research and clinical management of many diseases, and may help achieve eventual "noninvasive biopsy". In this work, taking advantage of the optical absorption contrasts contributed by lipid and hemoglobin at 1200-nm and 532-nm wavelengths respectively, we investigated the capability of PASA in identifying histological changes corresponding to fat accumulation livers through the study on ex vivo and in situ mouse models. The PA signals from the mouse livers were acquired using our PA and US dual-modality imaging system, and analyzed in the frequency domain. After quantifying the power spectrum by fitting it to a first order model, three spectral parameters, including the intercept, the midband fit and the slope, were extracted and used to differentiate fatty livers from normal livers. The comparison between the PASA parameters from the normal and the fatty livers supports our hypotheses that PASA can quantitatively identify the microstructure changes in liver tissues for differentiating normal and fatty livers.

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

An easy-to-build and re-usable microfluidic system for live-cell imaging.

PubMed

Babic, Julien; Griscom, Laurent; Cramer, Jeremy; Coudreuse, Damien

2018-06-20

Real-time monitoring of cellular responses to dynamic changes in their environment or to specific treatments has become central to cell biology. However, when coupled to live-cell imaging, such strategies are difficult to implement with precision and high time resolution, and the simultaneous alteration of multiple parameters is a major challenge. Recently, microfluidics has provided powerful solutions for such analyses, bringing an unprecedented level of control over the conditions and the medium in which cells under microscopic observation are grown. However, such technologies have remained under-exploited, largely as a result of the complexity associated with microfabrication procedures. In this study, we have developed simple but powerful microfluidic devices dedicated to live-cell imaging. These microsystems take advantage of a robust elastomer that is readily available to researchers and that presents excellent bonding properties, in particular to microscopy-grade glass coverslips. Importantly, the chips are easy-to-build without sophisticated equipment, and they are compatible with the integration of complex, customized fluidic networks as well as with the multiplexing of independent assays on a single device. We show that the chips are re-usable, a significant advantage for the popularization of microfluidics in cell biology. Moreover, we demonstrate that they allow for the dynamic, accurate and simultaneous control of multiple parameters of the cellular environment. While they do not possess all the features of the microdevices that are built using complex and costly procedures, the simplicity and versatility of the chips that we have developed make them an attractive alternative for a range of applications. The emergence of such devices, which can be fabricated and used by any laboratory, will provide the possibility for a larger number of research teams to take full advantage of these new methods for investigating cell biology.

Tamoxifen affects glucose and lipid metabolism parameters, causes browning of subcutaneous adipose tissue and transient body composition changes in C57BL/6NTac mice

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

Hesselbarth, Nico; Pettinelli, Chiara; Gericke, Martin

Tamoxifen is a selective estrogen receptor (ER) modulator which is widely used to generate inducible conditional transgenic mouse models. Activation of ER signaling plays an important role in the regulation of adipose tissue (AT) metabolism. We therefore tested the hypothesis that tamoxifen administration causes changes in AT biology in vivo. 12 weeks old male C57BL/6NTac mice were treated with either tamoxifen (n = 18) or vehicle (n = 18) for 5 consecutive days. Tamoxifen treatment effects on body composition, energy homeostasis, parameters of AT biology, glucose and lipid metabolism were investigated up to an age of 18 weeks. We found that tamoxifen treatment causes: I)more » significantly increased HbA{sub 1c}, triglyceride and free fatty acid serum concentrations (p < 0.01), II) browning of subcutaneous AT and increased UCP-1 expression, III) increased AT proliferation marker Ki67 mRNA expression, IV) changes in adipocyte size distribution, and V) transient body composition changes. Tamoxifen may induce changes in body composition, whole body glucose and lipid metabolism and has significant effects on AT biology, which need to be considered when using Tamoxifen as a tool to induce conditional transgenic mouse models. Our data further suggest that tamoxifen-treated wildtype mice should be characterized in parallel to experimental transgenic models to control for tamoxifen administration effects. - Highlights: • Tamoxifen treatment causes significantly increased HbA{sub 1c}, triglyceride and free fatty acid serum concentrations. • Tamoxifen induces browning of subcutaneous AT and increased UCP-1 expression. • Tamoxifen changes adipocyte size distribution, and transient body composition.« less

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.

Validation of a motor activity system by a robotically controlled vehicle and using standard reference compounds.

PubMed

Patterson, John P; Markgraf, Carrie G; Cirino, Maria; Bass, Alan S

2005-01-01

A series of experiments were undertaken to evaluate the accuracy, precision, specificity, and sensitivity of an automated, infrared photo beam-based open field motor activity system, the MotorMonitor v. 4.01, Hamilton-Kinder, LLC, for use in a good laboratory practices (GLP) Safety Pharmacology laboratory. This evaluation consisted of two phases: (1) system validation, employing known inputs using the EM-100 Controller Photo Beam Validation System, a robotically controlled vehicle representing a rodent and (2) biologic validation, employing groups of rats treated with the standard pharmacologic agents diazepam or D-amphetamine. The MotorMonitor's parameters that described the open-field activity of a subject were: basic movements, total distance, fine movements, x/y horizontal ambulations, rearing, and total rest time. These measurements were evaluated over a number of zones within each enclosure. System validation with the EM-100 Controller Photo Beam Validation System showed that all the parameters accurately and precisely measured what they were intended to measure, with the exception of fine movements and x/y ambulations. Biologic validation using the central nervous system depressant diazepam at 1, 2, or 5 mg/kg, i.p. produced the expected dose-dependent reduction in rat motor activity. In contrast, the central nervous system stimulant D-amphetamine produced the expected increases in rat motor activity at 0.1 and 1 mg/kg, i.p, demonstrating the specificity and sensitivity of the system. Taken together, these studies of the accuracy, precision, specificity, and sensitivity show the importance of both system and biologic validation in the evaluation of an automated open field motor activity system for use in a GLP compliant laboratory.

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.

Entropy Generation Analysis in Convective Ferromagnetic Nano Blood Flow Through a Composite Stenosed Arteries with Permeable Wall

NASA Astrophysics Data System (ADS)

Sher Akbar, Noreen; Wahid Butt, Adil

2017-05-01

The study of heat transfer is of significant importance in many biological and biomedical industry problems. This investigation comprises of the study of entropy generation analysis of the blood flow in the arteries with permeable walls. The convection through the flow is studied with compliments to the entropy generation. Governing problem is formulized and solved for low Reynold’s number and long wavelength approximations. Exact analytical solutions have been obtained and are analyzed graphically. It is seen that temperature for pure water is lower as compared to the copper water. It gains magnitude with an increase in the slip parameter.

Lipophilicity, antifungal and antioxidant properties of persilben.

PubMed

Smolarz, Helena D; Kosikowska, Urszula; Baraniak, Barbara; Malm, Anna; Persona, Andrzej

2005-01-01

The lipophilicity of persilben, an important parameter influencing the penetration of the compound through biological membranes, was determined experimentally by dynamic method and was theoretically calculated according to the fragmentation methods introduced by Crippen, Broto and Viswanadhan. The higher value of partition coefficient (log P = 3.89) obtained for persilben than that for resveratrol points to potentially higher ease of penetration of persilben into cells of living organism. Antimicrobial and antioxidant activities of persilben were tested. The obtained data suggest that this compound possesses some antioxidant activity. Persilben appears to have also some inhibitory effect against some species of dermatophytes from Tnichophyton genus but only at high concentrations.

An enantioselective approach toward 3,4-dihydroisocoumarin through the bromocyclization of styrene-type carboxylic acids.

PubMed

Chen, Jie; Zhou, Ling; Tan, Chong Kiat; Yeung, Ying-Yeung

2012-01-20

A facile and enantioselective approach toward 3,4-dihydroisocoumarin was developed. The method involved an amino-thiocarbamate catalyzed enantioselective bromocyclization of styrene-type carboxylic acids, yielding 3-bromo-3,4-dihydroisocoumarins with good yields and ee's. 3-Bromo-3,4-dihydroisocoumarins are versatile building blocks for various dihydroisocoumarin derivatives in which the Br group can readily be modified to achieve biologically important 4-O-type and 4-N-type 3,4-dihydroisocoumarin systems. In addition, studies indicated that, by refining some parameters, the synthetically useful 5-exo phthalide products could be achieved with good yields and ee's.

Online quantitative analysis of multispectral images of human body tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.

2013-08-01

A method is developed for online monitoring of structural and morphological parameters of biological tissues (haemoglobin concentration, degree of blood oxygenation, average diameter of capillaries and the parameter characterising the average size of tissue scatterers), which involves multispectral tissue imaging, image normalisation to one of its spectral layers and determination of unknown parameters based on their stable regression relation with the spectral characteristics of the normalised image. Regression is obtained by simulating numerically the diffuse reflectance spectrum of the tissue by the Monte Carlo method at a wide variation of model parameters. The correctness of the model calculations is confirmed by the good agreement with the experimental data. The error of the method is estimated under conditions of general variability of structural and morphological parameters of the tissue. The method developed is compared with the traditional methods of interpretation of multispectral images of biological tissues, based on the solution of the inverse problem for each pixel of the image in the approximation of different analytical models.

Biosensing Using Magnetic Particle Detection Techniques

PubMed Central

Chen, Yi-Ting; Kolhatkar, Arati G.; Zenasni, Oussama; Xu, Shoujun

2017-01-01

Magnetic particles are widely used as signal labels in a variety of biological sensing applications, such as molecular detection and related strategies that rely on ligand-receptor binding. In this review, we explore the fundamental concepts involved in designing magnetic particles for biosensing applications and the techniques used to detect them. First, we briefly describe the magnetic properties that are important for bio-sensing applications and highlight the associated key parameters (such as the starting materials, size, functionalization methods, and bio-conjugation strategies). Subsequently, we focus on magnetic sensing applications that utilize several types of magnetic detection techniques: spintronic sensors, nuclear magnetic resonance (NMR) sensors, superconducting quantum interference devices (SQUIDs), sensors based on the atomic magnetometer (AM), and others. From the studies reported, we note that the size of the MPs is one of the most important factors in choosing a sensing technique. PMID:28994727

Sensitivity of midge larvae of Chironomus tentans Fabricius (Diptera Chironomidae) to heavy metals

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

Khangarot, B.S.; Ray, P.K.

1989-03-01

The discharge of heavy metals into the natural waters has numerous obvious impacts on physical, chemical and biological parameters of aquatic ecosystem. Bioassay tests are important steps in establishing appropriate water quality criteria and standards for diverse use of ponds, lakes, streams and river waters. Therefore, the acute toxicities of various heavy metals to water flea Daphnia magna, and snail Lymnaea acuminata, and toad tadpoles Bufo mentanostictus have been reported from the authors' laboratory. Chironomid larvae might be particularly useful as indicators of water quality because they are widely distributed in freshwater systems and often from diverse communities within particularmore » habitat. The aim of this study was to determine the acute toxicity of ten heavy metals to the midge larvae Chironomus tentans Fabricius, which forms an important link in aquatic food chain(s).« less

Propesticides and their use as agrochemicals.

PubMed

Jeschke, Peter

2016-02-01

The synthesis of propesticides is an important concept in design of modern agrochemicals with optimal efficacy, environmental safety, user friendliness and economic variability. Based on increasing knowledge of the biochemistry and genetics of major pest insects, weeds and agricultural pathogens, the search for selectivity has become an ever more important part of pesticide development and can be achieved by appropriate structural modifications of the active ingredient. Propesticides affect the absorption, distribution, metabolism and excretion parameters, which can lead to biological superiority of these modified active ingredients over their non-derivatised analogues. Various selected commercial propesticides testify to the successful utilisation of this concept in the design of agrochemicals. This review describes comprehensively the successful utilisation of propesticides and their role in syntheses of modern agrochemicals, exemplified by selected commercial products coming from different agrochemical areas. © 2015 Society of Chemical Industry.

Adhesion and volume constraints via nonlocal interactions determine cell organisation and migration profiles.

PubMed

Carrillo, José Antonio; Colombi, Annachiara; Scianna, Marco

2018-05-14

The description of the cell spatial pattern and characteristic distances is fundamental in a wide range of physio-pathological biological phenomena, from morphogenesis to cancer growth. Discrete particle models are widely used in this field, since they are focused on the cell-level of abstraction and are able to preserve the identity of single individuals reproducing their behavior. In particular, a fundamental role in determining the usefulness and the realism of a particle mathematical approach is played by the choice of the intercellular pairwise interaction kernel and by the estimate of its parameters. The aim of the paper is to demonstrate how the concept of H-stability, deriving from statistical mechanics, can have important implications in this respect. For any given interaction kernel, it in fact allows to a priori predict the regions of the free parameter space that result in stable configurations of the system characterized by a finite and strictly positive minimal interparticle distance, which is fundamental when dealing with biological phenomena. The proposed analytical arguments are indeed able to restrict the range of possible variations of selected model coefficients, whose exact estimate however requires further investigations (e.g., fitting with empirical data), as illustrated in this paper by series of representative simulations dealing with cell colony reorganization, sorting phenomena and zebrafish embryonic development. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Mathematical Model for Dengue Epidemics with Differential Susceptibility and Asymptomatic Patients Using Computer Algebra

NASA Astrophysics Data System (ADS)

Saldarriaga Vargas, Clarita

When there are diseases affecting large populations where the social, economic and cultural diversity is significant within the same region, the biological parameters that determine the behavior of the dispersion disease analysis are affected by the selection of different individuals. Therefore and because of the variety and magnitude of the communities at risk of contracting dengue disease around all over the world, suggest defining differentiated populations with individual contributions in the results of the dispersion dengue disease analysis. In this paper those conditions were taken in account when several epidemiologic models were analyzed. Initially a stability analysis was done for a SEIR mathematical model of Dengue disease without differential susceptibility. Both free disease and endemic equilibrium states were found in terms of the basic reproduction number and were defined in the Theorem (3.1). Then a DSEIR model was solved when a new susceptible group was introduced to consider the effects of important biological parameters of non-homogeneous populations in the spreading analysis. The results were compiled in the Theorem (3.2). Finally Theorems (3.3) and (3.4) resumed the basic reproduction numbers for three and n different susceptible groups respectively, giving an idea of how differential susceptibility affects the equilibrium states. The computations were done using an algorithmic method implemented in Maple 11, a general-purpose computer algebra system.

Synthesis, characterization and biological evaluation of strontium/magnesium-co-substituted hydroxyapatite.

PubMed

Geng, Zhen; Wang, Renfeng; Li, Zhaoyang; Cui, Zhenduo; Zhu, Shengli; Liang, Yanqin; Liu, Yunde; Huijing, Bao; Li, Xue; Huo, Qianyu; Liu, Zhili; Yang, Xianjin

2016-07-01

The present study aims to investigate the contribution of two biologically important cations, Mg(2+) and Sr(2+), when co-substituted into the structure of hydroxyapatite (Ca10(PO4)6(OH)2, HA). The substituted samples were synthesized by a hydrothermal method that involved the addition of Mg(2+) and Sr(2+) containing precursors to partially replace Ca(2+) in the apatite structure. Four co-substituted HA samples with different concentrations of Mg(2+) and Sr(2+) ((Mg + Sr)/(Mg + Sr + Ca) = 30%) were investigated, and they were compared with pure HA. Experimental results showed that only a limited amount of Mg (Mg/(Mg + Ca + Sr) < 14%) could successfully substitute for Ca in HA. In addition, Mg substitution resulted in reduced crystallinity, thermal stability and lattice parameters of HA. In contrast, Sr could fully substitute for Ca. Furthermore, the addition of Sr increased the lattice parameters of HA. Here, we obtained the cation leach liquor by immersing the prepared samples in a culture medium for cell experiments. The in vitro study showed that 10Mg20Sr promoted better MG63 cell attachment, proliferation and differentiation than HA. Thus, the presence of an appropriate proportion of Mg and Sr could play a significant role in the increased biocompatibility of HA. © The Author(s) 2016.

Energy deposition processes in biological tissue: nonthermal biohazards seem unlikely in the ultra-high frequency range.

PubMed

Pickard, W F; Moros, E G

2001-02-01

The prospects of ultra high frequency (UHF, 300--3000 MHz) irradiation producing a nonthermal bioeffect are considered theoretically and found to be small. First, a general formula is derived within the framework of macroscopic electrodynamics for the specific absorption rate of microwaves in a biological tissue; this involves the complex Poynting vector, the mass density of the medium, the angular frequency of the electromagnetic field, and the three complex electromagnetic constitutive parameters of the medium. In the frequency ranges used for cellular telephony and personal communication systems, this model predicts that the chief physical loss mechanism will be ionic conduction, with increasingly important contributions from dielectric relaxation as the frequency rises. However, even in a magnetite unit cell within a magnetosome the deposition rate should not exceed 1/10 k(B)T per second. This supports previous arguments for the improbability of biological effects at UHF frequencies unless a mechanism can be found for accumulating energy over time and space and focussing it. Second, three possible nonthermal accumulation mechanisms are then considered and shown to be unlikely: (i) multiphoton absorption processes; (ii) direct electric field effects on ions; (iii) cooperative effects and/or coherent excitations. Finally, it is concluded that the rate of energy deposition from a typical field and within a typical tissue is so small as to make unlikely any significant nonthermal biological effect. Copyright 2001 Wiley-Liss, Inc.

A theoretical framework for jamming in confluent biological tissues

NASA Astrophysics Data System (ADS)

Manning, M. Lisa

2015-03-01

For important biological functions such as wound healing, embryonic development, and cancer tumorogenesis, cells must initially rearrange and move over relatively large distances, like a liquid. Subsequently, these same tissues must undergo buckling and support shear stresses, like a solid. Our work suggests that biological tissues can accommodate these disparate requirements because the tissues are close to glass or jamming transition. While recent self propelled particle models generically predict a glass/jamming transition that is driven by packing density φ and happens at some critical φc less than unity, many biological tissues that are confluent with no gaps between cells appear to undergo a jamming transition at a constant density (φ = 1). I will discuss a new theoretical framework for predicting energy barriers and rates of cell migration in 2D tissue monolayers, and show that this model predicts a novel type of rigidity transition, which takes place at constant φ = 1 and depends only on single cell properties such as cell-cell adhesion, cortical tension and cell elasticity. This model additionally predicts that an experimentally observable parameter, the ratio between a cell's perimeter and the square root of its cross-sectional area, attains a specific, critical value at the jamming transition. We show that this prediction is precisely realized in primary epithelial cultures from human patients, with implications for asthma pathology.

Changes in hormone and stress-inducing activities of municipal wastewater in a conventional activated sludge wastewater treatment plant.

PubMed

Wojnarowicz, Pola; Yang, Wenbo; Zhou, Hongde; Parker, Wayne J; Helbing, Caren C

2014-12-01

Conventional municipal wastewater treatment plants do not efficiently remove contaminants of emerging concern, and so are primary sources for contaminant release into the aquatic environment. Although these contaminants are present in effluents at ng-μg/L concentrations (i.e. microcontaminants), many compounds can act as endocrine disrupting compounds or stress-inducing agents at these levels. Chemical fate analyses indicate that additional levels of wastewater treatment reduce but do not always completely remove all microcontaminants. The removal of microcontaminants from wastewater does not necessarily correspond to a reduction in biological activity, as contaminant metabolites or byproducts may still be biologically active. To evaluate the efficacy of conventional municipal wastewater treatment plants to remove biological activity, we examined the performance of a full scale conventional activated sludge municipal wastewater treatment plant located in Guelph, Ontario, Canada. We assessed reductions in levels of conventional wastewater parameters and thyroid hormone disrupting and stress-inducing activities in wastewater at three phases along the treatment train using a C-fin assay. Wastewater treatment was effective at reducing total suspended solids, chemical and biochemical oxygen demand, and stress-inducing bioactivity. However, only minimal reduction was observed in thyroid hormone disrupting activities. The present study underscores the importance of examining multiple chemical and biological endpoints in evaluating and monitoring the effectiveness of wastewater treatment for removal of microcontaminants. Copyright © 2014 Elsevier Ltd. All rights reserved.

NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities.

PubMed

da Rocha, Edroaldo Lummertz; Ung, Choong Yong; McGehee, Cordelia D; Correia, Cristina; Li, Hu

2016-06-02

The sequential chain of interactions altering the binary state of a biomolecule represents the 'information flow' within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein-protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes-network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code (http://www.NetDecoder.org) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Parameter estimation methods for gene circuit modeling from time-series mRNA data: a comparative study.

PubMed

Fan, Ming; Kuwahara, Hiroyuki; Wang, Xiaolei; Wang, Suojin; Gao, Xin

2015-11-01

Parameter estimation is a challenging computational problem in the reverse engineering of biological systems. Because advances in biotechnology have facilitated wide availability of time-series gene expression data, systematic parameter estimation of gene circuit models from such time-series mRNA data has become an important method for quantitatively dissecting the regulation of gene expression. By focusing on the modeling of gene circuits, we examine here the performance of three types of state-of-the-art parameter estimation methods: population-based methods, online methods and model-decomposition-based methods. Our results show that certain population-based methods are able to generate high-quality parameter solutions. The performance of these methods, however, is heavily dependent on the size of the parameter search space, and their computational requirements substantially increase as the size of the search space increases. In comparison, online methods and model decomposition-based methods are computationally faster alternatives and are less dependent on the size of the search space. Among other things, our results show that a hybrid approach that augments computationally fast methods with local search as a subsequent refinement procedure can substantially increase the quality of their parameter estimates to the level on par with the best solution obtained from the population-based methods while maintaining high computational speed. These suggest that such hybrid methods can be a promising alternative to the more commonly used population-based methods for parameter estimation of gene circuit models when limited prior knowledge about the underlying regulatory mechanisms makes the size of the parameter search space vastly large. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

An application of the Krylov-FSP-SSA method to parameter fitting with maximum likelihood

NASA Astrophysics Data System (ADS)

Dinh, Khanh N.; Sidje, Roger B.

2017-12-01

Monte Carlo methods such as the stochastic simulation algorithm (SSA) have traditionally been employed in gene regulation problems. However, there has been increasing interest to directly obtain the probability distribution of the molecules involved by solving the chemical master equation (CME). This requires addressing the curse of dimensionality that is inherent in most gene regulation problems. The finite state projection (FSP) seeks to address the challenge and there have been variants that further reduce the size of the projection or that accelerate the resulting matrix exponential. The Krylov-FSP-SSA variant has proved numerically efficient by combining, on one hand, the SSA to adaptively drive the FSP, and on the other hand, adaptive Krylov techniques to evaluate the matrix exponential. Here we apply this Krylov-FSP-SSA to a mutual inhibitory gene network synthetically engineered in Saccharomyces cerevisiae, in which bimodality arises. We show numerically that the approach can efficiently approximate the transient probability distribution, and this has important implications for parameter fitting, where the CME has to be solved for many different parameter sets. The fitting scheme amounts to an optimization problem of finding the parameter set so that the transient probability distributions fit the observations with maximum likelihood. We compare five optimization schemes for this difficult problem, thereby providing further insights into this approach of parameter estimation that is often applied to models in systems biology where there is a need to calibrate free parameters. Work supported by NSF grant DMS-1320849.

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network

PubMed Central

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins. PMID:27418910

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

PubMed

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins.

Biological mechanisms of normal tissue damage: importance for the design of NTCP models.

PubMed

Trott, Klaus-Rüdiger; Doerr, Wolfgang; Facoetti, Angelica; Hopewell, John; Langendijk, Johannes; van Luijk, Peter; Ottolenghi, Andrea; Smyth, Vere

2012-10-01

The normal tissue complication probability (NTCP) models that are currently being proposed for estimation of risk of harm following radiotherapy are mainly based on simplified empirical models, consisting of dose distribution parameters, possibly combined with clinical or other treatment-related factors. These are fitted to data from retrospective or prospective clinical studies. Although these models sometimes provide useful guidance for clinical practice, their predictive power on individuals seems to be limited. This paper examines the radiobiological mechanisms underlying the most important complications induced by radiotherapy, with the aim of identifying the essential parameters and functional relationships needed for effective predictive NTCP models. The clinical features of the complications are identified and reduced as much as possible into component parts. In a second step, experimental and clinical data are considered in order to identify the gross anatomical structures involved, and which dose distributions lead to these complications. Finally, the pathogenic pathways and cellular and more specific anatomical parameters that have to be considered in this pathway are determined. This analysis is carried out for some of the most critical organs and sites in radiotherapy, i.e. spinal cord, lung, rectum, oropharynx and heart. Signs and symptoms of severe late normal tissue complications present a very variable picture in the different organs at risk. Only in rare instances is the entire organ the critical target which elicits the particular complication. Moreover, the biological mechanisms that are involved in the pathogenesis differ between the different complications, even in the same organ. Different mechanisms are likely to be related to different shapes of dose effect relationships and different relationships between dose per fraction, dose rate, and overall treatment time and effects. There is good reason to conclude that each type of late complication after radiotherapy depends on its own specific mechanism which is triggered by the radiation exposure of particular structures or sub-volumes of (or related to) the respective organ at risk. Hence each complication will need the development of an NTCP model designed to accommodate this structure. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Flow cytometry in the post fluorescence era.

PubMed

Nolan, Garry P

2011-12-01

While flow cytometry once enabled researchers to examine 10--15 cell surface parameters, new mass flow cytometry technology enables interrogation of up to 45 parameters on a single cell. This new technology has increased understanding of cell expression and how cells differentiate during hematopoiesis. Using this information, knowledge of leukemia cell biology has also increased. Other new technologies, such as SPADE analysis and single cell network profiling (SCNP), are enabling researchers to put different cancers into more biologically similar categories and have the potential to enable more personalized medicine. Copyright © 2011. Published by Elsevier Ltd.

Biological optimization systems for enhancing photosynthetic efficiency and methods of use

DOEpatents

Hunt, Ryan W.; Chinnasamy, Senthil; Das, Keshav C.; de Mattos, Erico Rolim

2012-11-06

Biological optimization systems for enhancing photosynthetic efficiency and methods of use. Specifically, methods for enhancing photosynthetic efficiency including applying pulsed light to a photosynthetic organism, using a chlorophyll fluorescence feedback control system to determine one or more photosynthetic efficiency parameters, and adjusting one or more of the photosynthetic efficiency parameters to drive the photosynthesis by the delivery of an amount of light to optimize light absorption of the photosynthetic organism while providing enough dark time between light pulses to prevent oversaturation of the chlorophyll reaction centers are disclosed.

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

Scanning number and brightness yields absolute protein concentrations in live cells: a crucial parameter controlling functional bio-molecular interaction networks.

PubMed

Papini, Christina; Royer, Catherine A

2018-02-01

Biological function results from properly timed bio-molecular interactions that transduce external or internal signals, resulting in any number of cellular fates, including triggering of cell-state transitions (division, differentiation, transformation, apoptosis), metabolic homeostasis and adjustment to changing physical or nutritional environments, amongst many more. These bio-molecular interactions can be modulated by chemical modifications of proteins, nucleic acids, lipids and other small molecules. They can result in bio-molecular transport from one cellular compartment to the other and often trigger specific enzyme activities involved in bio-molecular synthesis, modification or degradation. Clearly, a mechanistic understanding of any given high level biological function requires a quantitative characterization of the principal bio-molecular interactions involved and how these may change dynamically. Such information can be obtained using fluctation analysis, in particular scanning number and brightness, and used to build and test mechanistic models of the functional network to define which characteristics are the most important for its regulation.

High in Vivo Stability of 64Cu-Labeled Cross-Bridged Chelators Is a Crucial Factor in Improved Tumor Imaging of RGD Peptide Conjugates.

PubMed

Sarkar, Swarbhanu; Bhatt, Nikunj; Ha, Yeong Su; Huynh, Phuong Tu; Soni, Nisarg; Lee, Woonghee; Lee, Yong Jin; Kim, Jung Young; Pandya, Darpan N; An, Gwang Il; Lee, Kyo Chul; Chang, Yongmin; Yoo, Jeongsoo

2018-01-11

Although the importance of bifunctional chelators (BFCs) is well recognized, the chemophysical parameters of chelators that govern the biological behavior of the corresponding bioconjugates have not been clearly elucidated. Here, five BFCs closely related in structure were conjugated with a cyclic RGD peptide and radiolabeled with Cu-64 ions. Various biophysical and chemical properties of the Cu(II) complexes were analyzed with the aim of identifying correlations between individual factors and the biological behavior of the conjugates. Tumor uptake and body clearance of the 64 Cu-labeled bioconjugates were directly compared by animal PET imaging in animal models, which was further supported by biodistribution studies. Conjugates containing propylene cross-bridged chelators showed higher tumor uptake, while a closely related ethylene cross-bridged analogue exhibited rapid body clearance. High in vivo stability of the copper-chelator complex was strongly correlated with high tumor uptake, while the overall lipophilicity of the bioconjugate affected both tumor uptake and body clearance.

Incorporation of nanoparticles into polymersomes: size and concentration effects.

PubMed

Jaskiewicz, Karmena; Larsen, Antje; Schaeffel, David; Koynov, Kaloian; Lieberwirth, Ingo; Fytas, George; Landfester, Katharina; Kroeger, Anja

2012-08-28

Because of the rapidly growing field of nanoparticles in therapeutic applications, understanding and controlling the interaction between nanoparticles and membranes is of great importance. While a membrane is exposed to nanoparticles its behavior is mediated by both their biological and physical properties. Constant interplay of these biological and physicochemical factors makes selective studies of nanoparticles uptake demanding. Artificial model membranes can serve as a platform to investigate physical parameters of the process in the absence of any biofunctional molecules and/or supplementary energy. Here we report on photon- and fluorescence-correlation spectroscopic studies of the uptake of nanosized SiO(2) nanoparticles by poly(dimethylsiloxane)-block-poly(2-methyloxazoline) vesicles allowing species selectivity. Analogous to the cell membrane, polymeric membrane incorporates particles using membrane fission and particles wrapping as suggested by cryo-TEM imaging. It is revealed that the incorporation process can be controlled to a significant extent by changing nanoparticles size and concentration. Conditions for nanoparticle uptake and controlled filling of polymersomes are presented.

Metamaterial Absorber Based Multifunctional Sensor Application

NASA Astrophysics Data System (ADS)

Ozer, Z.; Mamedov, A. M.; Ozbay, E.

2017-02-01

In this study metamaterial based (MA) absorber sensor, integrated with an X-band waveguide, is numerically and experimentally suggested for important application including pressure, density sensing and marble type detecting applications based on rectangular split ring resonator, sensor layer and absorber layer that measures of changing in the dielectric constant and/or the thickness of a sensor layer. Changing of physical, chemical or biological parameters in the sensor layer can be detected by measuring the resonant frequency shifting of metamaterial absorber based sensor. Suggested MA based absorber sensor can be used for medical, biological, agricultural and chemical detecting applications in microwave frequency band. We compare the simulation and experimentally obtained results from the fabricated sample which are good agreement. Simulation results show that the proposed structure can detect the changing of the refractive indexes of different materials via special resonance frequencies, thus it could be said that the MA-based sensors have high sensitivity. Additionally due to the simple and tiny structures it could be adapted to other electronic devices in different sizes.

Design and synthesis of some new 2,3'-bipyridine-5-carbonitriles as potential anti-inflammatory/antimicrobial agents.

PubMed

Elzahhar, Perihan A; Elkazaz, Salwa; Soliman, Raafat; El-Tombary, Alaa A; Shaltout, Hossam A; El-Ashmawy, Ibrahim M; Abdel Wahab, Abeer E; El-Hawash, Soad A

2017-08-01

Inflammation may cause accumulation of fluid in the injured area, which may promote bacterial growth. Other reports disclosed that non-steroidal anti-inflammatory drugs may enhance progression of bacterial infection. This work describes synthesis of new series of 2,3'-bipyridine-5-carbonitriles as structural analogs of etoricoxib, linked at position-6 to variously substituted thio or oxo moieties. Biological screening results revealed that compounds 2b, 4b, 7e and 8 showed significant acute and chronic AI activities and broad spectrum of antimicrobial activity. In addition, similarity ensemble approach was applied to predict potential biological targets of the tested compounds. Then, pharmacophore modeling study was employed to determine the most important structural parameters controlling bioactivity. Moreover, title compounds showed physicochemical properties within those considered adequate for drug candidates. This study explored the potential of such series of compounds as structural leads for further modification to develop a new class of dual AI-antimicrobial agents.

On the Reproduction Number of a Gut Microbiota Model.

PubMed

Barril, Carles; Calsina, Àngel; Ripoll, Jordi

2017-11-01

A spatially structured linear model of the growth of intestinal bacteria is analysed from two generational viewpoints. Firstly, the basic reproduction number associated with the bacterial population, i.e. the expected number of daughter cells per bacterium, is given explicitly in terms of biological parameters. Secondly, an alternative quantity is introduced based on the number of bacteria produced within the intestine by one bacterium originally in the external media. The latter depends on the parameters in a simpler way and provides more biological insight than the standard reproduction number, allowing the design of experimental procedures. Both quantities coincide and are equal to one at the extinction threshold, below which the bacterial population becomes extinct. Optimal values of both reproduction numbers are derived assuming parameter trade-offs.

Azimuthally invariant Mueller-matrix mapping of biological optically anisotropic network

NASA Astrophysics Data System (ADS)

Ushenko, Yu. O.; Vanchuliak, O.; Bodnar, G. B.; Ushenko, V. O.; Grytsyuk, M.; Pavlyukovich, N.; Pavlyukovich, O. V.; Antonyuk, O.

2017-09-01

A new technique of Mueller-matrix mapping of polycrystalline structure of histological sections of biological tissues is suggested. The algorithms of reconstruction of distribution of parameters of linear and circular dichroism of histological sections liver tissue of mice with different degrees of severity of diabetes are found. The interconnections between such distributions and parameters of linear and circular dichroism of liver of mice tissue histological sections are defined. The comparative investigations of coordinate distributions of parameters of amplitude anisotropy formed by Liver tissue with varying severity of diabetes (10 days and 24 days) are performed. The values and ranges of change of the statistical (moments of the 1st - 4th order) parameters of coordinate distributions of the value of linear and circular dichroism are defined. The objective criteria of cause of the degree of severity of the diabetes differentiation are determined.

A method of online quantitative interpretation of diffuse reflection profiles of biological tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2013-02-01

We have developed a method of combined interpretation of spectral and spatial characteristics of diffuse reflection of biological tissues, which makes it possible to determine biophysical parameters of the tissue with a high accuracy in real time under conditions of their general variability. Using the Monte Carlo method, we have modeled a statistical ensemble of profiles of diffuse reflection coefficients of skin, which corresponds to a wave variation of its biophysical parameters. On its basis, we have estimated the retrieval accuracy of biophysical parameters using the developed method and investigated the stability of the method to errors of optical measurements. We have showed that it is possible to determine online the concentrations of melanin, hemoglobin, bilirubin, oxygen saturation of blood, and structural parameters of skin from measurements of its diffuse reflection in the spectral range 450-800 nm at three distances between the radiation source and detector.

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

PubMed Central

Golightly, Andrew; Wilkinson, Darren J.

2011-01-01

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

Estimating cellular parameters through optimization procedures: elementary principles and applications.

PubMed

Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki

2015-01-01

Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.

Convergence in parameters and predictions using computational experimental design.

PubMed

Hagen, David R; White, Jacob K; Tidor, Bruce

2013-08-06

Typically, biological models fitted to experimental data suffer from significant parameter uncertainty, which can lead to inaccurate or uncertain predictions. One school of thought holds that accurate estimation of the true parameters of a biological system is inherently problematic. Recent work, however, suggests that optimal experimental design techniques can select sets of experiments whose members probe complementary aspects of a biochemical network that together can account for its full behaviour. Here, we implemented an experimental design approach for selecting sets of experiments that constrain parameter uncertainty. We demonstrated with a model of the epidermal growth factor-nerve growth factor pathway that, after synthetically performing a handful of optimal experiments, the uncertainty in all 48 parameters converged below 10 per cent. Furthermore, the fitted parameters converged to their true values with a small error consistent with the residual uncertainty. When untested experimental conditions were simulated with the fitted models, the predicted species concentrations converged to their true values with errors that were consistent with the residual uncertainty. This paper suggests that accurate parameter estimation is achievable with complementary experiments specifically designed for the task, and that the resulting parametrized models are capable of accurate predictions.

Parameter estimation for the exponential-normal convolution model for background correction of affymetrix GeneChip data.

PubMed

McGee, Monnie; Chen, Zhongxue

2006-01-01

There are many methods of correcting microarray data for non-biological sources of error. Authors routinely supply software or code so that interested analysts can implement their methods. Even with a thorough reading of associated references, it is not always clear how requisite parts of the method are calculated in the software packages. However, it is important to have an understanding of such details, as this understanding is necessary for proper use of the output, or for implementing extensions to the model. In this paper, the calculation of parameter estimates used in Robust Multichip Average (RMA), a popular preprocessing algorithm for Affymetrix GeneChip brand microarrays, is elucidated. The background correction method for RMA assumes that the perfect match (PM) intensities observed result from a convolution of the true signal, assumed to be exponentially distributed, and a background noise component, assumed to have a normal distribution. A conditional expectation is calculated to estimate signal. Estimates of the mean and variance of the normal distribution and the rate parameter of the exponential distribution are needed to calculate this expectation. Simulation studies show that the current estimates are flawed; therefore, new ones are suggested. We examine the performance of preprocessing under the exponential-normal convolution model using several different methods to estimate the parameters.

Identification of predictor parameters to determine agro-industrial compost suppressiveness against Fusarium oxysporum and Phytophthora capsici diseases in muskmelon and pepper seedlings.

PubMed

Blaya, Josefa; Lloret, Eva; Ros, Margarita; Pascual, Jose Antonio

2015-05-01

The lack of reliable prediction tools for evaluation of the level and specificity of compost suppressiveness limits its application. In our study, different chemical, biological and microbiological parameters were used to evaluate their potential use as a predictor parameter for the suppressive effect of composts against Fusarium oxysporum f. sp. melonis (FOM) and Phytophthora capsici (P. capsici) in muskmelon and pepper seedlings respectively. Composts were obtained from artichoke sludge, chopped vineyard pruning waste and various agro-industrial wastes (C1: blanched artichokes; C2: garlic waste; C3: dry olive cake). Compost C3 proved to offer the highest level of resistance against FOM, and compost C2 the highest level of resistance against P. capsici. Analysis of phospholipid fatty acids isolated from compost revealed that the three composts showed different microbial community structures. Protease, NAGase and chitinase activities were significantly higher in compost C3, as was dehydrogenase activity in compost C2. The use of specific parameters such as general (dehydrogenase activity) and specific enzymatic activities (protease, NAGase and chitinase activities) may be useful to predict compost suppressiveness against both pathogens. The selection of raw materials for agro-industrial composts is important in controlling Fusarium wilt and Phytophthora root rot. © 2014 Society of Chemical Industry.

Homogenization Theory for the Prediction of Obstructed Solute Diffusivity in Macromolecular Solutions.

PubMed

Donovan, Preston; Chehreghanianzabi, Yasaman; Rathinam, Muruhan; Zustiak, Silviya Petrova

2016-01-01

The study of diffusion in macromolecular solutions is important in many biomedical applications such as separations, drug delivery, and cell encapsulation, and key for many biological processes such as protein assembly and interstitial transport. Not surprisingly, multiple models for the a-priori prediction of diffusion in macromolecular environments have been proposed. However, most models include parameters that are not readily measurable, are specific to the polymer-solute-solvent system, or are fitted and do not have a physical meaning. Here, for the first time, we develop a homogenization theory framework for the prediction of effective solute diffusivity in macromolecular environments based on physical parameters that are easily measurable and not specific to the macromolecule-solute-solvent system. Homogenization theory is useful for situations where knowledge of fine-scale parameters is used to predict bulk system behavior. As a first approximation, we focus on a model where the solute is subjected to obstructed diffusion via stationary spherical obstacles. We find that the homogenization theory results agree well with computationally more expensive Monte Carlo simulations. Moreover, the homogenization theory agrees with effective diffusivities of a solute in dilute and semi-dilute polymer solutions measured using fluorescence correlation spectroscopy. Lastly, we provide a mathematical formula for the effective diffusivity in terms of a non-dimensional and easily measurable geometric system parameter.

Rapid and precise determination of zero-field splittings by terahertz time-domain electron paramagnetic resonance spectroscopy.

PubMed

Lu, Jian; Ozel, I Ozge; Belvin, Carina A; Li, Xian; Skorupskii, Grigorii; Sun, Lei; Ofori-Okai, Benjamin K; Dincă, Mircea; Gedik, Nuh; Nelson, Keith A

2017-11-01

Zero-field splitting (ZFS) parameters are fundamentally tied to the geometries of metal ion complexes. Despite their critical importance for understanding the magnetism and spectroscopy of metal complexes, they are not routinely available through general laboratory-based techniques, and are often inferred from magnetism data. Here we demonstrate a simple tabletop experimental approach that enables direct and reliable determination of ZFS parameters in the terahertz (THz) regime. We report time-domain measurements of electron paramagnetic resonance (EPR) signals associated with THz-frequency ZFSs in molecular complexes containing high-spin transition-metal ions. We measure the temporal profiles of the free-induction decays of spin resonances in the complexes at zero and nonzero external magnetic fields, and we derive the EPR spectra via numerical Fourier transformation of the time-domain signals. In most cases, absolute values of the ZFS parameters are extracted from the measured zero-field EPR frequencies, and the signs can be determined by zero-field measurements at two different temperatures. Field-dependent EPR measurements further allow refined determination of the ZFS parameters and access to the g -factor. The results show good agreement with those obtained by other methods. The simplicity of the method portends wide applicability in chemistry, biology and material science.

Ribosome biogenesis in replicating cells: Integration of experiment and theory.

PubMed

Earnest, Tyler M; Cole, John A; Peterson, Joseph R; Hallock, Michael J; Kuhlman, Thomas E; Luthey-Schulten, Zaida

2016-10-01

Ribosomes-the primary macromolecular machines responsible for translating the genetic code into proteins-are complexes of precisely folded RNA and proteins. The ways in which their production and assembly are managed by the living cell is of deep biological importance. Here we extend a recent spatially resolved whole-cell model of ribosome biogenesis in a fixed volume [Earnest et al., Biophys J 2015, 109, 1117-1135] to include the effects of growth, DNA replication, and cell division. All biological processes are described in terms of reaction-diffusion master equations and solved stochastically using the Lattice Microbes simulation software. In order to determine the replication parameters, we construct and analyze a series of Escherichia coli strains with fluorescently labeled genes distributed evenly throughout their chromosomes. By measuring these cells' lengths and number of gene copies at the single-cell level, we could fit a statistical model of the initiation and duration of chromosome replication. We found that for our slow-growing (120 min doubling time) E. coli cells, replication was initiated 42 min into the cell cycle and completed after an additional 42 min. While simulations of the biogenesis model produce the correct ribosome and mRNA counts over the cell cycle, the kinetic parameters for transcription and degradation are lower than anticipated from a recent analytical time dependent model of in vivo mRNA production. Describing expression in terms of a simple chemical master equation, we show that the discrepancies are due to the lack of nonribosomal genes in the extended biogenesis model which effects the competition of mRNA for ribosome binding, and suggest corrections to parameters to be used in the whole-cell model when modeling expression of the entire transcriptome. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 735-751, 2016. © 2016 Wiley Periodicals, Inc.

Intra-operative feedback and dynamic compensation for image-guided robotic focal ultrasound surgery.

PubMed

Chauhan, S; Amir, H; Chen, G; Hacker, A; Michel, M S; Koehrmann, K U

2008-11-01

This paper describes a non-invasive remote temperature measurement technique integrated with a biomechatronic surgery system devised in our laboratory and named FUSBOT (Focal Ultrasound Surgery RoBOT). FUSBOTs use High-Intensity Focused Ultrasound (HIFU) for ablation of cancers/tumors and targets accessible through various soft-tissue acoustic windows in the human body. The focused ultrasound beam parameters are chosen so that biologically significant temperature rises are achieved only within the focal volume. In this paper, FUSBOT(BS), a customized system for breast surgery, is taken as a representative example to demonstrate the implementation and the results of non-invasive feedback during ablation. An 8-axis PC-based controller controls various sub-sections of the system within a safe constrained work envelope. Temperature is a prime target parameter in ablative procedures, and it is of paramount importance that means should be devised for its measurement and control in order to design optimal dose protocols and judge the efficacy of FUS systems. A customized sensory interface is devised and integrated with FUSBOT(BS), and dedicated software algorithms are embedded for surgical planning based on real-time guidance and feedback. Variations in the physical parameters of the tissue interacting with the incident modality are used as surgical feedback. The use of real-time ultrasound imaging and data processed from various sensors to deduce lesion position and thermal feedback during surgery, as integrated with the robotic system for online surgical planning, is described. Dynamic registration algorithms are developed for compensation and re-registration of the robotic end-effector with respect to the target, and representative empirical outcomes for lesion tracking and online temperature estimation in various biological tissues are presented.

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.

DAISY: a new software tool to test global identifiability of biological and physiological systems.

PubMed

Bellu, Giuseppina; Saccomani, Maria Pia; Audoly, Stefania; D'Angiò, Leontina

2007-10-01

A priori global identifiability is a structural property of biological and physiological models. It is considered a prerequisite for well-posed estimation, since it concerns the possibility of recovering uniquely the unknown model parameters from measured input-output data, under ideal conditions (noise-free observations and error-free model structure). Of course, determining if the parameters can be uniquely recovered from observed data is essential before investing resources, time and effort in performing actual biomedical experiments. Many interesting biological models are nonlinear but identifiability analysis for nonlinear system turns out to be a difficult mathematical problem. Different methods have been proposed in the literature to test identifiability of nonlinear models but, to the best of our knowledge, so far no software tools have been proposed for automatically checking identifiability of nonlinear models. In this paper, we describe a software tool implementing a differential algebra algorithm to perform parameter identifiability analysis for (linear and) nonlinear dynamic models described by polynomial or rational equations. Our goal is to provide the biological investigator a completely automatized software, requiring minimum prior knowledge of mathematical modelling and no in-depth understanding of the mathematical tools. The DAISY (Differential Algebra for Identifiability of SYstems) software will potentially be useful in biological modelling studies, especially in physiology and clinical medicine, where research experiments are particularly expensive and/or difficult to perform. Practical examples of use of the software tool DAISY are presented. DAISY is available at the web site http://www.dei.unipd.it/~pia/.

Clinical and Biological Predictors of Plasma Levels of Soluble RAGE in Critically Ill Patients: Secondary Analysis of a Prospective Multicenter Observational Study.

PubMed

Pranal, Thibaut; Pereira, Bruno; Berthelin, Pauline; Roszyk, Laurence; Godet, Thomas; Chabanne, Russell; Eisenmann, Nathanael; Lautrette, Alexandre; Belville, Corinne; Blondonnet, Raiko; Cayot, Sophie; Gillart, Thierry; Skrzypczak, Yvan; Souweine, Bertrand; Bouvier, Damien; Blanchon, Loic; Sapin, Vincent; Constantin, Jean-Michel; Jabaudon, Matthieu

2018-01-01

Although soluble forms of the receptor for advanced glycation end products (RAGE) have been recently proposed as biomarkers in multiple acute or chronic diseases, few studies evaluated the influence of usual clinical and biological parameters, or of patient characteristics and comorbidities, on circulating levels of soluble RAGE in the intensive care unit (ICU) setting. To determine, among clinical and biological parameters that are usually recorded upon ICU admission, which variables, if any, could be associated with plasma levels of soluble RAGE. Data for this ancillary study were prospectively obtained from adult patients with at least one ARDS risk factor upon ICU admission enrolled in a large multicenter observational study. At ICU admission, plasma levels of total soluble RAGE (sRAGE) and endogenous secretory (es)RAGE were measured by duplicate ELISA and baseline patient characteristics, comorbidities, and usual clinical and biological indices were recorded. After univariate analyses, significant variables were used in multivariate, multidimensional analyses. 294 patients were included in this ancillary study, among whom 62% were admitted for medical reasons, including septic shock (11%), coma (11%), and pneumonia (6%). Although some variables were associated with plasma levels of RAGE soluble forms in univariate analysis, multidimensional analyses showed no significant association between admission parameters and baseline plasma sRAGE or esRAGE. We found no obvious association between circulating levels of soluble RAGE and clinical and biological indices that are usually recorded upon ICU admission. This trial is registered with NCT02070536.

Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development

PubMed Central

2014-01-01

Background Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. Results The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input–output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on average 15% of the mean values over the succeeding parameter sets. Conclusions Our results indicate that the presented approach is effective for comparing model alternatives and reducing models to the minimum complexity replicating measured data. We therefore believe that this approach has significant potential for reparameterising existing frameworks, for identification of redundant model components of large biophysical models and to increase their predictive capacity. PMID:24886522

BIOPACK: the ground controlled late access biological research facility.

PubMed

van Loon, Jack J W A

2004-03-01

Future Space Shuttle flights shall be characterized by activities necessary to further build the International Space Station, ISS. During these missions limited resources are available to conduct biological experiments in space. The Shuttles' Middeck is a very suitable place to conduct science during the ISS assembly missions or dedicated science missions. The BIOPACK, which flew its first mission during the STS-107, provides a versatile Middeck Locker based research tool for gravitational biology studies. The core facility occupies the space of only two Middeck Lockers. Experiment temperatures are controlled for bacteria, plant, invertebrate and mammalian cultures. Gravity levels and profiles can be set ranging from 0 to 2.0 x g on three independent centrifuges. This provides the experimenter with a 1.0 x g on-board reference and intermediate hypogravity and hypergravity data points to investigate e.g. threshold levels in biological responses. Temperature sensitive items can be stored in the facilities' -10 degrees C and +4 degrees C stowage areas. During STS-107 the facility also included a small glovebox (GBX) and passive temperature controlled units (PTCU). The GBX provides the experimenter with two extra levels of containment for safe sample handling. This biological research facility is a late access (L-10 hrs) laboratory, which, when reaching orbit, could automatically be starting up reducing important experiment lag-time and valuable crew time. The system is completely telecommanded when needed. During flight system parameters like temperatures, centrifuge speeds, experiment commanding or sensor readouts can be monitored and changed when needed. Although ISS provides a wide range of research facilities there is still need for an STS-based late access facility such as the BIOPACK providing experimenters with a very versatile research cabinet for biological experiments under microgravity and in-flight control conditions.

Molecular interactions between single layered MoS2 and biological molecules† †Electronic supplementary information (ESI) available: SFG data analysis methods, spectral fitting parameters, additional spectra, CD spectrum, and details about MD simulation methods. See DOI: 10.1039/c7sc04884j

PubMed Central

Xiao, Minyu; Wei, Shuai; Li, Yaoxin; Jasensky, Joshua; Chen, Junjie; Brooks, Charles L.

2017-01-01

Two-dimensional (2D) materials such as graphene, molybdenum disulfide (MoS2), tungsten diselenide (WSe2), and black phosphorous are being developed for sensing applications with excellent selectivity and high sensitivity. In such applications, 2D materials extensively interact with various analytes including biological molecules. Understanding the interfacial molecular interactions of 2D materials with various targets becomes increasingly important for the progression of better-performing 2D-material based sensors. In this research, molecular interactions between several de novo designed alpha-helical peptides and monolayer MoS2 have been studied. Molecular dynamics simulations were used to validate experimental data. The results suggest that, in contrast to peptide–graphene interactions, peptide aromatic residues do not interact strongly with the MoS2 surface. It is also found that charged amino acids are important for ensuring a standing-up pose for peptides interacting with MoS2. By performing site-specific mutations on the peptide, we could mediate the peptide–MoS2 interactions to control the peptide orientation on MoS2. PMID:29675220