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Sample records for compartmental metabolic models

  1. Retinol metabolism in rats with low vitamin A status: A compartmental model

    International Nuclear Information System (INIS)

    Lewis, K.C.; Green, M.H.; Green, J.B.; Zech, L.A.

    1990-01-01

    A compartmental model was developed to describe the metabolism of vitamin A in rats with low vitamin A status maintained by a low dietary intake of vitamin A (approximately 2 micrograms retinol equivalents/day). After the IV bolus injection of [3H]retinol in its physiological transport complex, tracer and trace data were obtained from plasma, organs (liver, kidneys, small intestine, eyes, adrenals, testes, lungs, carcass), and tracer data were obtained from urine and feces. The dietary protocol developed for this study resulted in animals having plasma vitamin A levels less than 10 micrograms retinol/dl and total liver vitamin A levels of approximately 1 microgram retinol equivalent. Four compartments were used to model the plasma: one to describe retinol, one to describe the nonphysiological portion of the dose, and two to simulate polar metabolites derived from retinol. The liver required two compartments and a delay, the carcass (small intestine, eyes, adrenals, testes, and lungs, plus remaining carcass) required three compartments, and the kidneys required two. The model predicted a vitamin A utilization rate of 1.65 micrograms retinol equivalents/day with the urine and feces accounting for most of the output. The plasma retinol turnover rate was approximately 20 micrograms retinol equivalents/day; this was 12 times greater than the utilization rate. This indicated that, of the large amount of retinol moving through the plasma each day, less than 10% of this was actually being irreversibly utilized. Similarly, as compared to the whole-body utilization rate, there was a relatively high turnover rate of retinol in the kidneys, carcass, and liver, coupled with a high degree of recycling of vitamin A through these tissues. Of the total vitamin A that entered the liver from all sources including the diet, approximately 86% was mobilized into the plasma

  2. Compartmental Modeling and Dosimetry of in Vivo Metabolic Studies of Leucine and Three Secretory Proteins in Humans Using Radioactive Tracers

    Science.gov (United States)

    Venkatakrishnan, Vaidehi

    1995-01-01

    Physical and mathematical models provide a systematic means of looking at biological systems. Radioactive tracer kinetic studies open a unique window to study complex tracee systems such as protein metabolism in humans. This research deals with compartmental modeling of tracer kinetic data on leucine and apolipoprotein metabolism obtained using an endogenous tritiated leucine tracer administered as a bolus, and application of compartmental modeling techniques for dosimetric evaluation of metabolic studies of radioiodinated apolipoproteins. Dr. Waldo R. Fisher, Department of Medicine, was the coordinating research supervisor and the work was carried out in his laboratory. A compartmental model for leucine kinetics in humans has been developed that emphasizes its recycling pathways which were examined over two weeks. This model builds on a previously published model of Cobelli et al, that analyzed leucine kinetic data up to only eight hours. The proposed model includes different routes for re-entry of leucine from protein breakdown into plasma accounting for proteins which turn over at different rates. This new model successfully incorporates published models of three secretory proteins: albumin, apoA-I, and VLDL apoB, in toto thus increasing its validity and utility. The published model of apoA-I, based on an exogenous radioiodinated tracer, was examined with data obtained using an endogenous leucine tracer using compartmental techniques. The analysis concludes that the major portion of apoA-I enters plasma by a fast pathway but the major fraction of apoA-I in plasma resides with a second slow pathway; further the study is suggestive of a precursor-product relationship between the two plasma apoA-I pools. The possible relevance of the latter suggestion to the aberrant kinetics of apoA-I in Tangier disease is discussed. The analysis of apoA-II data resulted in similar conclusions. A methodology for evaluating the dosimetry of radioiodinated apolipoproteins by

  3. Application of compartmental metabolic models for determination of retention and excretion functions

    International Nuclear Information System (INIS)

    Rodrigues Junior, O.

    1994-01-01

    After an intake of radioactive material, its behaviour in the human body can be described by mathematical models, where organs, tissues or regions of the body are treated as a chain of linked compartments. The mathematical approach for such metabolic models is usually done through a system of differential equations of first order with constant coefficients. The solutions of this system of equations associates the radionuclide intake, with the fraction excreted or retained in the organ of interest. A computer program - called INCORP and for running in PC compatible microcomputers - was developed in order to find the solutions of such system of equations, using an analytical method based on expansion of series of exponential matrices. The metabolic model presented in the ICRP-30 publication was simulated using the INCORP program, in order to find the respective retention and excretion curves for selected radionuclides. (author)

  4. Compartmentation of glycogen metabolism revealed from 13C isotopologue distributions

    Directory of Open Access Journals (Sweden)

    Marin de Mas Igor

    2011-10-01

    Full Text Available Abstract Background Stable isotope tracers are used to assess metabolic flux profiles in living cells. The existing methods of measurement average out the isotopic isomer distribution in metabolites throughout the cell, whereas the knowledge of compartmental organization of analyzed pathways is crucial for the evaluation of true fluxes. That is why we accepted a challenge to create a software tool that allows deciphering the compartmentation of metabolites based on the analysis of average isotopic isomer distribution. Results The software Isodyn, which simulates the dynamics of isotopic isomer distribution in central metabolic pathways, was supplemented by algorithms facilitating the transition between various analyzed metabolic schemes, and by the tools for model discrimination. It simulated 13C isotope distributions in glucose, lactate, glutamate and glycogen, measured by mass spectrometry after incubation of hepatocytes in the presence of only labeled glucose or glucose and lactate together (with label either in glucose or lactate. The simulations assumed either a single intracellular hexose phosphate pool, or also channeling of hexose phosphates resulting in a different isotopic composition of glycogen. Model discrimination test was applied to check the consistency of both models with experimental data. Metabolic flux profiles, evaluated with the accepted model that assumes channeling, revealed the range of changes in metabolic fluxes in liver cells. Conclusions The analysis of compartmentation of metabolic networks based on the measured 13C distribution was included in Isodyn as a routine procedure. The advantage of this implementation is that, being a part of evaluation of metabolic fluxes, it does not require additional experiments to study metabolic compartmentation. The analysis of experimental data revealed that the distribution of measured 13C-labeled glucose metabolites is inconsistent with the idea of perfect mixing of hexose

  5. Kinetic compartmental analysis of carnitine metabolism in the dog

    International Nuclear Information System (INIS)

    Rebouche, C.J.; Engel, A.G.

    1983-01-01

    This study was undertaken to quantitate the dynamic parameters of carnitine metabolism in the dog. Six mongrel dogs were given intravenous injections of L-[methyl-3H]carnitine and the specific radioactivity of carnitine was followed in plasma and urine for 19-28 days. The data were analyzed by kinetic compartmental analysis. A three-compartment, open-system model [(a) extracellular fluid, (b) cardiac and skeletal muscle, (c) other tissues, particularly liver and kidney] was adopted and kinetic parameters (carnitine flux, pool sizes, kinetic constants) were derived. In four of six dogs the size of the muscle carnitine pool obtained by kinetic compartmental analysis agreed (+/- 5%) with estimates based on measurement of carnitine concentrations in different muscles. In three of six dogs carnitine excretion rates derived from kinetic compartmental analysis agreed (+/- 9%) with experimentally measured values, but in three dogs the rates by kinetic compartmental analysis were significantly higher than the corresponding rates measured directly. Appropriate chromatographic analyses revealed no radioactive metabolites in muscle or urine of any of the dogs. Turnover times for carnitine were (mean +/- SEM): 0.44 +/- 0.05 h for extracellular fluid, 232 +/- 22 h for muscle, and 7.9 +/- 1.1 h for other tissues. The estimated flux of carnitine in muscle was 210 pmol/min/g of tissue. Whole-body turnover time for carnitine was 62.9 +/- 5.6 days (mean +/- SEM). Estimated carnitine biosynthesis ranged from 2.9 to 28 mumol/kg body wt/day. Results of this study indicate that kinetic compartmental analysis may be applicable to study of human carnitine metabolism

  6. Compartmental modeling and tracer kinetics

    CERN Document Server

    Anderson, David H

    1983-01-01

    This monograph is concerned with mathematical aspects of compartmental an­ alysis. In particular, linear models are closely analyzed since they are fully justifiable as an investigative tool in tracer experiments. The objective of the monograph is to bring the reader up to date on some of the current mathematical prob­ lems of interest in compartmental analysis. This is accomplished by reviewing mathematical developments in the literature, especially over the last 10-15 years, and by presenting some new thoughts and directions for future mathematical research. These notes started as a series of lectures that I gave while visiting with the Division of Applied ~1athematics, Brown University, 1979, and have developed in­ to this collection of articles aimed at the reader with a beginning graduate level background in mathematics. The text can be used as a self-paced reading course. With this in mind, exercises have been appropriately placed throughout the notes. As an aid in reading the material, the e~d of a ...

  7. Compartmentation of redox metabolism in malaria parasites.

    Directory of Open Access Journals (Sweden)

    Sebastian Kehr

    Full Text Available Malaria, caused by the apicomplexan parasite Plasmodium, still represents a major threat to human health and welfare and leads to about one million human deaths annually. Plasmodium is a rapidly multiplying unicellular organism undergoing a complex developmental cycle in man and mosquito - a life style that requires rapid adaptation to various environments. In order to deal with high fluxes of reactive oxygen species and maintain redox regulatory processes and pathogenicity, Plasmodium depends upon an adequate redox balance. By systematically studying the subcellular localization of the major antioxidant and redox regulatory proteins, we obtained the first complete map of redox compartmentation in Plasmodium falciparum. We demonstrate the targeting of two plasmodial peroxiredoxins and a putative glyoxalase system to the apicoplast, a non-photosynthetic plastid. We furthermore obtained a complete picture of the compartmentation of thioredoxin- and glutaredoxin-like proteins. Notably, for the two major antioxidant redox-enzymes--glutathione reductase and thioredoxin reductase--Plasmodium makes use of alternative-translation-initiation (ATI to achieve differential targeting. Dual localization of proteins effected by ATI is likely to occur also in other Apicomplexa and might open new avenues for therapeutic intervention.

  8. Intracellular compartmentalization of skeletal muscle glycogen metabolism and insulin signalling

    DEFF Research Database (Denmark)

    Prats Gavalda, Clara; Gomez-Cabello, Alba; Vigelsø Hansen, Andreas

    2011-01-01

    The interest in skeletal muscle metabolism and insulin signalling has increased exponentially in recent years as a consequence of their role in the development of type 2 diabetes mellitus. Despite this, the exact mechanisms involved in the regulation of skeletal muscle glycogen metabolism...... and insulin signalling transduction remain elusive. We believe that one of the reasons is that the role of intracellular compartmentalization as a regulator of metabolic pathways and signalling transduction has been rather ignored. This paper briefly reviews the literature to discuss the role of intracellular...... compartmentalization in the regulation of skeletal muscle glycogen metabolism and insulin signalling. As a result, a hypothetical regulatory mechanism is proposed by which cells could direct glycogen resynthesis towards different pools of glycogen particles depending on the metabolic needs. Furthermore, we discuss...

  9. The human NAD metabolome: Functions, metabolism and compartmentalization

    Science.gov (United States)

    Nikiforov, Andrey; Kulikova, Veronika; Ziegler, Mathias

    2015-01-01

    Abstract The metabolism of NAD has emerged as a key regulator of cellular and organismal homeostasis. Being a major component of both bioenergetic and signaling pathways, the molecule is ideally suited to regulate metabolism and major cellular events. In humans, NAD is synthesized from vitamin B3 precursors, most prominently from nicotinamide, which is the degradation product of all NAD-dependent signaling reactions. The scope of NAD-mediated regulatory processes is wide including enzyme regulation, control of gene expression and health span, DNA repair, cell cycle regulation and calcium signaling. In these processes, nicotinamide is cleaved from NAD+ and the remaining ADP-ribosyl moiety used to modify proteins (deacetylation by sirtuins or ADP-ribosylation) or to generate calcium-mobilizing agents such as cyclic ADP-ribose. This review will also emphasize the role of the intermediates in the NAD metabolome, their intra- and extra-cellular conversions and potential contributions to subcellular compartmentalization of NAD pools. PMID:25837229

  10. Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils

    Science.gov (United States)

    Álvarez-Yela, Astrid Catalina; Gómez-Cano, Fabio; Zambrano, María Mercedes; Husserl, Johana; Danies, Giovanna; Restrepo, Silvia; González-Barrios, Andrés Fernando

    2017-01-01

    Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA) were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community. PMID:28767679

  11. Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils.

    Directory of Open Access Journals (Sweden)

    María Camila Alvarez-Silva

    Full Text Available Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community.

  12. Aspects of astrocyte energy metabolism, amino acid neurotransmitter homoeostasis and metabolic compartmentation

    DEFF Research Database (Denmark)

    Kreft, Marko; Bak, Lasse Kristoffer; Waagepetersen, Helle S

    2012-01-01

    Astrocytes are key players in brain function; they are intimately involved in neuronal signalling processes and their metabolism is tightly coupled to that of neurons. In the present review, we will be concerned with a discussion of aspects of astrocyte metabolism, including energy......-generating pathways and amino acid homoeostasis. A discussion of the impact that uptake of neurotransmitter glutamate may have on these pathways is included along with a section on metabolic compartmentation....

  13. Application of compartmental metabolic models for determination of retention and excretion functions; Aplicacao de modelos metabolicos para a determinacao de funcoes de excrecao e retencao

    Energy Technology Data Exchange (ETDEWEB)

    Rodrigues, Junior, O

    1994-07-01

    After an intake of radioactive material, its behaviour in the human body can be described by mathematical models, where organs, tissues or regions of the body are treated as a chain of linked compartments. The mathematical approach for such metabolic models is usually done through a system of differential equations of first order with constant coefficients. The solutions of this system of equations associates the radionuclide intake, with the fraction excreted or retained in the organ of interest. A computer program - called INCORP and for running in PC compatible microcomputers - was developed in order to find the solutions of such system of equations, using an analytical method based on expansion of series of exponential matrices. The metabolic model presented in the ICRP-30 publication was simulated using the INCORP program, in order to find the respective retention and excretion curves for selected radionuclides. (author)

  14. A Calculus for Modelling, Simulating and Analysing Compartmentalized Biological Systems

    DEFF Research Database (Denmark)

    Mardare, Radu Iulian; Ihekwaba, Adoha

    2007-01-01

    A. Ihekwaba, R. Mardare. A Calculus for Modelling, Simulating and Analysing Compartmentalized Biological Systems. Case study: NFkB system. In Proc. of International Conference of Computational Methods in Sciences and Engineering (ICCMSE), American Institute of Physics, AIP Proceedings, N 2...

  15. Compartmentalization analysis using discrete fracture network models

    Energy Technology Data Exchange (ETDEWEB)

    La Pointe, P.R.; Eiben, T.; Dershowitz, W. [Golder Associates, Redmond, VA (United States); Wadleigh, E. [Marathon Oil Co., Midland, TX (United States)

    1997-08-01

    This paper illustrates how Discrete Fracture Network (DFN) technology can serve as a basis for the calculation of reservoir engineering parameters for the development of fractured reservoirs. It describes the development of quantitative techniques for defining the geometry and volume of structurally controlled compartments. These techniques are based on a combination of stochastic geometry, computational geometry, and graph the theory. The parameters addressed are compartment size, matrix block size and tributary drainage volume. The concept of DFN models is explained and methodologies to compute these parameters are demonstrated.

  16. Regulation of NAD+ metabolism, signaling and compartmentalization in the yeast Saccharomyces cerevisiae

    Science.gov (United States)

    Kato, Michiko; Lin, Su-Ju

    2014-01-01

    Pyridine nucleotides are essential coenzymes in many cellular redox reactions in all living systems. In addition to functioning as a redox carrier, NAD+ is also a required co-substrate for the conserved sirtuin deacetylases. Sirtuins regulate transcription, genome maintenance and metabolism and function as molecular links between cells and their environment. Maintaining NAD+ homeostasis is essential for proper cellular function and aberrant NAD+ metabolism has been implicated in a number of metabolic- and age-associated diseases. Recently, NAD+ metabolism has been linked to the phosphate-responsive signaling pathway (PHO pathway) in the budding yeast Saccharomyces cerevisiae. Activation of the PHO pathway is associated with the production and mobilization of the NAD+ metabolite nicotinamide riboside (NR), which is mediated in part by PHO-regulated nucleotidases. Cross-regulation between NAD+ metabolism and the PHO pathway has also been reported; however, detailed mechanisms remain to be elucidated. The PHO pathway also appears to modulate the activities of common downstream effectors of multiple nutrient-sensing pathways (Ras-PKA, TOR, Sch9/AKT). These signaling pathways were suggested to play a role in calorie restriction-mediated beneficial effects, which have also been linked to Sir2 function and NAD+ metabolism. Here, we discuss the interactions of these pathways and their potential roles in regulating NAD+ metabolism. In eukaryotic cells, intracellular compartmentalization facilitates the regulation of enzymatic functions and also concentrates or sequesters specific metabolites. Various NAD+-mediated cellular functions such as mitochondrial oxidative phosphorylation are compartmentalized. Therefore, we also discuss several key players functioning in mitochondrial, cytosolic and vacuolar compartmentalization of NAD+ intermediates, and their potential roles in NAD+ homeostasis. To date, it remains unclear how NAD+ and NAD+ intermediates shuttle between different

  17. Regulation of NAD+ metabolism, signaling and compartmentalization in the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Kato, Michiko; Lin, Su-Ju

    2014-11-01

    Pyridine nucleotides are essential coenzymes in many cellular redox reactions in all living systems. In addition to functioning as a redox carrier, NAD(+) is also a required co-substrate for the conserved sirtuin deacetylases. Sirtuins regulate transcription, genome maintenance and metabolism and function as molecular links between cells and their environment. Maintaining NAD(+) homeostasis is essential for proper cellular function and aberrant NAD(+) metabolism has been implicated in a number of metabolic- and age-associated diseases. Recently, NAD(+) metabolism has been linked to the phosphate-responsive signaling pathway (PHO pathway) in the budding yeast Saccharomyces cerevisiae. Activation of the PHO pathway is associated with the production and mobilization of the NAD(+) metabolite nicotinamide riboside (NR), which is mediated in part by PHO-regulated nucleotidases. Cross-regulation between NAD(+) metabolism and the PHO pathway has also been reported; however, detailed mechanisms remain to be elucidated. The PHO pathway also appears to modulate the activities of common downstream effectors of multiple nutrient-sensing pathways (Ras-PKA, TOR, Sch9/AKT). These signaling pathways were suggested to play a role in calorie restriction-mediated beneficial effects, which have also been linked to Sir2 function and NAD(+) metabolism. Here, we discuss the interactions of these pathways and their potential roles in regulating NAD(+) metabolism. In eukaryotic cells, intracellular compartmentalization facilitates the regulation of enzymatic functions and also concentrates or sequesters specific metabolites. Various NAD(+)-mediated cellular functions such as mitochondrial oxidative phosphorylation are compartmentalized. Therefore, we also discuss several key players functioning in mitochondrial, cytosolic and vacuolar compartmentalization of NAD(+) intermediates, and their potential roles in NAD(+) homeostasis. To date, it remains unclear how NAD(+) and NAD(+) intermediates

  18. Analytical properties of a three-compartmental dynamical demographic model

    Science.gov (United States)

    Postnikov, E. B.

    2015-07-01

    The three-compartmental demographic model by Korotaeyv-Malkov-Khaltourina, connecting population size, economic surplus, and education level, is considered from the point of view of dynamical systems theory. It is shown that there exist two integrals of motion, which enables the system to be reduced to one nonlinear ordinary differential equation. The study of its structure provides analytical criteria for the dominance ranges of the dynamics of Malthus and Kremer. Additionally, the particular ranges of parameters enable the derived general ordinary differential equations to be reduced to the models of Gompertz and Thoularis-Wallace.

  19. Utilization of stable isotopes for the study of in vivo compartmental metabolism of poly-insaturate fatty acids

    International Nuclear Information System (INIS)

    Brossard, N.; Croset, M.; Lecerf, J.; Lagarde, M.; Pachiaudi, C.; Normand, S.; Riou, J.P.; Chirouze, V.; Tayot, J.L.

    1994-01-01

    In order to study the compartmental metabolism of the 22:6n-3 fatty acid, and particularly the role of the transport plasmatic forms for the tissue uptake (especially brain), a technique is developed using carbon 13 stable isotope and an isotopic mass spectrometry coupled to gaseous chromatography technique. This method has been validated in rat with docosahexaenoic acid enriched in 13 C and esterified in triglycerides. The compartmental metabolism is monitored by measuring the variation of 22:6n-3 isotopic enrichment in the various lipoprotein lipidic fractions, in blood globules and in the brain. 1 fig., 1 tab., 12 refs

  20. Compartmental transport model of microbicide delivery by an intravaginal ring

    Science.gov (United States)

    Geonnotti, Anthony R.; Katz, David F.

    2010-01-01

    Topical antimicrobials, or microbicides, are being developed to prevent HIV transmission through local, mucosal delivery of antiviral compounds. While hydrogel vehicles deliver the majority of current microbicide products, intravaginal rings (IVRs) are an alternative microbicide modality in preclinical development. IVRs provide a long-term dosing alternative to hydrogel use, and might provide improved user adherence. IVR efficacy requires sustained delivery of antiviral compounds to the entire vaginal compartment. A two-dimensional, compartmental vaginal drug transport model was created to evaluate the delivery of drugs from an intravaginal ring. The model utilized MRI-derived ring geometry and location, experimentally defined ring fluxes and vaginal fluid velocities, and biophysically relevant transport theory. Model outputs indicated the presence of potentially inhibitory concentrations of antiviral compounds along the entire vaginal canal within 24 hours following IVR insertion. Distributions of inhibitory concentrations of antiviral compounds were substantially influenced by vaginal fluid flow and production, while showing little change due to changes in diffusion coefficients or ring fluxes. Additionally, model results were predictive of in vivo concentrations obtained in clinical trials. Overall, this analysis initiates a mechanistic computational framework, heretofore missing, to understand and evaluate the potential of IVRs for effective delivery of antiviral compounds. PMID:20222027

  1. Efficient Vaccine Distribution Based on a Hybrid Compartmental Model.

    Directory of Open Access Journals (Sweden)

    Zhiwen Yu

    Full Text Available To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible-exposed-infectious šC recovered model, named the hybrid SEIR-V model (HSEIR-V, which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk for controlling the spread of viral infections. Based on data from the 2009-2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics.

  2. Compartmental models for assessing the fishery production in the Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Dalal, S.G.; Parulekar, A.H.

    Compartmental models for assessing the fishery production in the Indian Ocean is discussed. The article examines the theoretical basis on which modern fishery sciences is built. The model shows that, large changes in energy flux from one pathway...

  3. Metabolic Compartmentation – A System Level Property of Muscle Cells

    Directory of Open Access Journals (Sweden)

    Theo Wallimann

    2008-05-01

    Full Text Available Problems of quantitative investigation of intracellular diffusion and compartmentation of metabolites are analyzed. Principal controversies in recently published analyses of these problems for the living cells are discussed. It is shown that the formal theoretical analysis of diffusion of metabolites based on Fick’s equation and using fixed diffusion coefficients for diluted homogenous aqueous solutions, but applied for biological systems in vivo without any comparison with experimental results, may lead to misleading conclusions, which are contradictory to most biological observations. However, if the same theoretical methods are used for analysis of actual experimental data, the apparent diffusion constants obtained are orders of magnitude lower than those in diluted aqueous solutions. Thus, it can be concluded that local restrictions of diffusion of metabolites in a cell are a system-level properties caused by complex structural organization of the cells, macromolecular crowding, cytoskeletal networks and organization of metabolic pathways into multienzyme complexes and metabolons. This results in microcompartmentation of metabolites, their channeling between enzymes and in modular organization of cellular metabolic networks. The perspectives of further studies of these complex intracellular interactions in the framework of Systems Biology are discussed.

  4. Kinetic compartmental analysis of carnitine metabolism in the human carnitine deficiency syndromes. Evidence for alterations in tissue carnitine transport

    International Nuclear Information System (INIS)

    Rebouche, C.J.; Engel, A.G.

    1984-01-01

    The human primary carnitine deficiency syndromes are potentially fatal disorders affecting children and adults. The molecular etiologies of these syndromes have not been determined. In this investigation, we considered the hypothesis that these syndromes result from defective transport of carnitine into tissues, particularly skeletal muscle. The problem was approached by mathematical modeling, by using the technique of kinetic compartmental analysis. A tracer dose of L-[methyl-3H]carnitine was administered intravenously to six normal subjects, one patient with primary muscle carnitine deficiency (MCD), and four patients with primary systemic carnitine deficiency (SCD). Specific radioactivity was followed in plasma for 28 d. A three-compartment model (extracellular fluid, muscle, and ''other tissues'') was adopted. Rate constants, fluxes, pool sizes, and turnover times were calculated. Results of these calculations indicated reduced transport of carnitine into muscle in both forms of primary carnitine deficiency. However, in SCD, the reduced rate of carnitine transport was attributed to reduced plasma carnitine concentration. In MCD, the results are consistent with an intrinsic defect in the transport process. Abnormal fluctuations of the plasma carnitine, but of a different form, occurred in MCD and SCD. The significance of these are unclear, but in SCD they suggest abnormal regulation of the muscle/plasma carnitine concentration gradient. In 8 of 11 subjects, carnitine excretion was less than dietary carnitine intake. Carnitine excretion rates calculated by kinetic compartmental analysis were higher than corresponding rates measured directly, indicating degradation of carnitine. However, we found no radioactive metabolites of L-[methyl-3H]carnitine in urine. These observations suggest that dietary carnitine was metabolized in the gastrointestinal tract

  5. Compartmental distribution of radiotracers

    International Nuclear Information System (INIS)

    Robertson, J.S.; Colombetti, L.G.

    1983-01-01

    This book examines the use of radioisotopes in medical diagnosis. Topics considered include compartmental analysis, data processing in nuclear medicine, historical aspects, basic principles, mathematical methods, the application of computers in obtaining numerical solutions to compartmental models, the SAAM and CONSAM programs, some statistical principles in compartmental analysis, and applications

  6. The subcellular compartmentalization of arginine metabolizing enzymes and their role in endothelial dysfunction

    Directory of Open Access Journals (Sweden)

    Feng eChen

    2013-07-01

    Full Text Available The endothelial production of nitric oxide (NO mediates endothelium-dependent vasorelaxation and restrains vascular inflammation, smooth muscle proliferation and platelet aggregation. Impaired production of NO is a hallmark of endothelial dysfunction and promotes the development of cardiovascular disease. In endothelial cells, NO is generated by endothelial nitric oxide synthase (eNOS through the conversion of its substrate, L-arginine to L-citrulline. Reduced access to L-arginine has been proposed as a major mechanism underlying reduced eNOS activity and NO production in cardiovascular disease. The arginases (Arg1 and Arg2 metabolize L-arginine to generate L-ornithine and urea and increased expression of arginase has been proposed as a mechanism of reduced eNOS activity secondary to the depletion of L-arginine. Indeed, supplemental L-arginine and suppression of arginase activity has been shown to improve endothelium-dependent relaxation and ameliorate cardiovascular disease. However, L-arginine concentrations in endothelial cells remain sufficiently high to support NO synthesis suggesting additional mechanisms. The compartmentalization of intracellular L-arginine into poorly interchangeable pools has been proposed to allow for the local depletion of L-arginine. Indeed the subcellular location of L-arginine metabolizing enzymes plays important functional roles. In endothelial cells, eNOS is found in discrete intracellular locations and the capacity to generate NO is heavily influenced by its localtion. Arg1 and Arg2 also reside in different subcellular environments and are thought to differentially influence endothelial function. The plasma membrane solute transporter, CAT-1 and the arginine recycling enzyme, ASL, co-localize with eNOS and facilitate NO release. This review highlights the importance of the subcellular location of eNOS and arginine transporting and metabolizing enzymes to NO release and cardiovascular disease.

  7. Compartmental distribution of radiotracers

    International Nuclear Information System (INIS)

    Roberton, J.S.

    1983-01-01

    Emphasizes applications of compartmental analysis in physiology, pharmacology, and other areas of biology and medicine. Details of computer methods and applications of statistical principles as they apply to compartmental analysis are presented. Of special interest is a step-by-step discussion of Berman's SAAM program in modeling at several different levels of difficulty. Extensive references and sources of additional information in mathematical methods and in applications to specific problems are provided. Contents: Historical Development. Basic Principles, Mathematical Methods. Application of Computers for Obtaining Numerical Solutions to Compartmental Models. Use of Computers in Compartmental Analysis: SAAM and CONSAAM Programs. Some Statistical Principals in Compartmental Analysis. Applications. Index

  8. Compartmental modeling approach to the radiation dosimetry of radiolabeled antibody

    International Nuclear Information System (INIS)

    Zanzonico, P.B.; Bigler, R.E.; Primus, F.J.; Alger, E.; DeJager, R.; Stowe, S.; Ford, E.; Brennan, K.; Goldenberg, D.M.

    1986-01-01

    Essential for the calculation of absorbed doses from systemically administered radiolabled antibody is the determination of the total number of nuclear transformations in specified source regions. Compartmental analysis (using biodistribution data augmented with a priori physiological information), unlike simply integrating empirical time-activity curves, may enable one to calculate the cumulated activity in unsampled as well as sampled source regions. These may include microscopic source regions (e.g. the intracellular space, cell surface, and extracellular space) important for microdosimetry calculations. Of particular importance is the interaction between the anti-tumor antibody and the tumor antigen. 30 references, 9 figures, 2 tables

  9. Global identifiability of linear compartmental models--a computer algebra algorithm.

    Science.gov (United States)

    Audoly, S; D'Angiò, L; Saccomani, M P; Cobelli, C

    1998-01-01

    A priori global identifiability deals with the uniqueness of the solution for the unknown parameters of a model and is, thus, a prerequisite for parameter estimation of biological dynamic models. Global identifiability is however difficult to test, since it requires solving a system of algebraic nonlinear equations which increases both in nonlinearity degree and number of terms and unknowns with increasing model order. In this paper, a computer algebra tool, GLOBI (GLOBal Identifiability) is presented, which combines the topological transfer function method with the Buchberger algorithm, to test global identifiability of linear compartmental models. GLOBI allows for the automatic testing of a priori global identifiability of general structure compartmental models from general multi input-multi output experiments. Examples of usage of GLOBI to analyze a priori global identifiability of some complex biological compartmental models are provided.

  10. A Common Decision of Compartmental Models on the Base of Laplace Transform and Retain Function Concept

    International Nuclear Information System (INIS)

    Dimitrov, L.; Tzvetkova, A.; Nikolov, A.

    1997-01-01

    The compartmental models have a variety of applications in the analysis of the transport of radioactive and non-radioactive material in complex systems as atmosphere, hydrosphere, food chains, human body. The analysis of the biokinetic behaviour of the radioactive material into a human body gives a possibility for correct assessment of the dose from internal irradiation. Skrable has given a decision of non-cyclic linear compartmental models in case of a single intake of material in the compartments as an initial condition. The main purpose of our article is to write down a procedure for analysis of a general compartmental model in case of continuous intake of material into the compartments. This procedure is related to retain function concept and had developed on the base of Laplace transform. On the base on the proposed procedure a non-cyclic linear compartmental model decisions are given in case of both a single and a continuous intake. The Laplace images of cyclic and circular linear compartmental model decisions and their originals in some cases are given too. (author)

  11. Modeling influenza-like illnesses through composite compartmental models

    Science.gov (United States)

    Levy, Nir; , Michael, Iv; Yom-Tov, Elad

    2018-03-01

    Epidemiological models for the spread of pathogens in a population are usually only able to describe a single pathogen. This makes their application unrealistic in cases where multiple pathogens with similar symptoms are spreading concurrently within the same population. Here we describe a method which makes possible the application of multiple single-strain models under minimal conditions. As such, our method provides a bridge between theoretical models of epidemiology and data-driven approaches for modeling of influenza and other similar viruses. Our model extends the Susceptible-Infected-Recovered model to higher dimensions, allowing the modeling of a population infected by multiple viruses. We further provide a method, based on an overcomplete dictionary of feasible realizations of SIR solutions, to blindly partition the time series representing the number of infected people in a population into individual components, each representing the effect of a single pathogen. We demonstrate the applicability of our proposed method on five years of seasonal influenza-like illness (ILI) rates, estimated from Twitter data. We demonstrate that our method describes, on average, 44% of the variance in the ILI time series. The individual infectious components derived from our model are matched to known viral profiles in the populations, which we demonstrate matches that of independently collected epidemiological data. We further show that the basic reproductive numbers (R 0) of the matched components are in range known for these pathogens. Our results suggest that the proposed method can be applied to other pathogens and geographies, providing a simple method for estimating the parameters of epidemics in a population.

  12. Compartmental Model For Uptake Of 137cs By Pine In Forest Soil ...

    African Journals Online (AJOL)

    A compartmental model of soil to pine tree transfer of 137Cs following the Chernobyl nuclear accident is presented. The model was validated using data collected in 1996 at five sites in Northern Ukraine. The transfer constants of 137Cs between model compartments are estimated using a semi-empirical method.

  13. Analysis of a compartmental model of amyloid beta production, irreversible loss and exchange in humans.

    Science.gov (United States)

    Elbert, Donald L; Patterson, Bruce W; Bateman, Randall J

    2015-03-01

    Amyloid beta (Aβ) peptides, and in particular Aβ42, are found in senile plaques associated with Alzheimer's disease. A compartmental model of Aβ production, exchange and irreversible loss was recently developed to explain the kinetics of isotope-labeling of Aβ peptides collected in cerebrospinal fluid (CSF) following infusion of stable isotope-labeled leucine in humans. The compartmental model allowed calculation of the rates of production, irreversible loss (or turnover) and short-term exchange of Aβ peptides. Exchange of Aβ42 was particularly pronounced in amyloid plaque-bearing participants. In the current work, we describe in much greater detail the characteristics of the compartmental model to two distinct audiences: physician-scientists and biokineticists. For physician-scientists, we describe through examples the types of questions the model can and cannot answer, as well as correct some misunderstandings of previous kinetic analyses applied to this type of isotope labeling data. For biokineticists, we perform a system identifiability analysis and a sensitivity analysis of the kinetic model to explore the global and local properties of the model. Combined, these analyses motivate simplifications from a more comprehensive physiological model to the final model that was previously presented. The analyses clearly demonstrate that the current dataset and compartmental model allow determination with confidence a single 'turnover' parameter, a single 'exchange' parameter and a single 'delay' parameter. When combined with CSF concentration data for the Aβ peptides, production rates may also be obtained. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Statistical properties of compartmental model parameters extracted from dynamic positron emission tomography experiments

    International Nuclear Information System (INIS)

    Mazoyer, B.M.; Huesman, R.H.; Budinger, T.F.; Knittel, B.L.

    1986-01-01

    Over the past years a major focus of research in physiologic studies employing tracers has been the computer implementation of mathematical methods of kinetic modeling for extracting the desired physiological parameters from tomographically derived data. A study is reported of factors that affect the statistical properties of compartmental model parameters extracted from dynamic positron emission tomography (PET) experiments

  15. A new method to estimate parameters of linear compartmental models using artificial neural networks

    International Nuclear Information System (INIS)

    Gambhir, Sanjiv S.; Keppenne, Christian L.; Phelps, Michael E.; Banerjee, Pranab K.

    1998-01-01

    At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models. (author)

  16. Kinetic compartmental analysis of carnitine metabolism in the human carnitine deficiency syndromes. Evidence for alterations in tissue carnitine transport.

    OpenAIRE

    Rebouche, C J; Engel, A G

    1984-01-01

    The human primary carnitine deficiency syndromes are potentially fatal disorders affecting children and adults. The molecular etiologies of these syndromes have not been determined. In this investigation, we considered the hypothesis that these syndromes result from defective transport of carnitine into tissues, particularly skeletal muscle. The problem was approached by mathematical modeling, by using the technique of kinetic compartmental analysis. A tracer dose of L-[methyl-3H]carnitine wa...

  17. Robust global identifiability theory using potentials--Application to compartmental models.

    Science.gov (United States)

    Wongvanich, N; Hann, C E; Sirisena, H R

    2015-04-01

    This paper presents a global practical identifiability theory for analyzing and identifying linear and nonlinear compartmental models. The compartmental system is prolonged onto the potential jet space to formulate a set of input-output equations that are integrals in terms of the measured data, which allows for robust identification of parameters without requiring any simulation of the model differential equations. Two classes of linear and non-linear compartmental models are considered. The theory is first applied to analyze the linear nitrous oxide (N2O) uptake model. The fitting accuracy of the identified models from differential jet space and potential jet space identifiability theories is compared with a realistic noise level of 3% which is derived from sensor noise data in the literature. The potential jet space approach gave a match that was well within the coefficient of variation. The differential jet space formulation was unstable and not suitable for parameter identification. The proposed theory is then applied to a nonlinear immunological model for mastitis in cows. In addition, the model formulation is extended to include an iterative method which allows initial conditions to be accurately identified. With up to 10% noise, the potential jet space theory predicts the normalized population concentration infected with pathogens, to within 9% of the true curve. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. A Residual Approach for Balanced Truncation Model Reduction (BTMR of Compartmental Systems

    Directory of Open Access Journals (Sweden)

    William La Cruz

    2014-05-01

    Full Text Available This paper presents a residual approach of the square root balanced truncation algorithm for model order reduction of continuous, linear and time-invariante compartmental systems. Specifically, the new approach uses a residual method to approximate the controllability and observability gramians, whose resolution is an essential step of the square root balanced truncation algorithm, that requires a great computational cost. Numerical experiences are included to highlight the efficacy of the proposed approach.

  19. A compartmentalized solute transport model for redox zones in contaminated aquifers: 1. Theory and development

    Science.gov (United States)

    Abrams , Robert H.; Loague, Keith

    2000-01-01

    This paper, the first of two parts [see Abrams and Loague, this issue], takes the compartmentalized approach for the geochemical evolution of redox zones presented by Abrams et al. [1998] and embeds it within a solute transport framework. In this paper the compartmentalized approach is generalized to facilitate the description of its incorporation into a solute transport simulator. An equivalent formulation is developed which removes any discontinuities that may occur when switching compartments. Rate‐limited redox reactions are modeled with a modified Monod relationship that allows either the organic substrate or the electron acceptor to be the rate‐limiting reactant. Thermodynamic constraints are used to inhibit lower‐energy redox reactions from occurring under infeasible geochemical conditions without imposing equilibrium on the lower‐energy reactions. The procedure used allows any redox reaction to be simulated as being kinetically limited or thermodynamically limited, depending on local geochemical conditions. Empirical reaction inhibition methods are not needed. The sequential iteration approach (SIA), a technique which allows the number of solute transport equations to be reduced, is adopted to solve the coupled geochemical/solute transport problem. When the compartmentalized approach is embedded within the SIA, with the total analytical concentration of each component as the dependent variable in the transport equation, it is possible to reduce the number of transport equations even further than with the unmodified SIA. A one‐dimensional, coupled geochemical/solute transport simulation is presented in which redox zones evolve dynamically in time and space. The compartmentalized solute transport (COMPTRAN) model described in this paper enables the development of redox zones to be simulated under both kinetic and thermodynamic constraints. The modular design of COMPTRAN facilitates the use of many different, preexisting solute transport and

  20. DISTING: A web application for fast algorithmic computation of alternative indistinguishable linear compartmental models.

    Science.gov (United States)

    Davidson, Natalie R; Godfrey, Keith R; Alquaddoomi, Faisal; Nola, David; DiStefano, Joseph J

    2017-05-01

    We describe and illustrate use of DISTING, a novel web application for computing alternative structurally identifiable linear compartmental models that are input-output indistinguishable from a postulated linear compartmental model. Several computer packages are available for analysing the structural identifiability of such models, but DISTING is the first to be made available for assessing indistinguishability. The computational algorithms embedded in DISTING are based on advanced versions of established geometric and algebraic properties of linear compartmental models, embedded in a user-friendly graphic model user interface. Novel computational tools greatly speed up the overall procedure. These include algorithms for Jacobian matrix reduction, submatrix rank reduction, and parallelization of candidate rank computations in symbolic matrix analysis. The application of DISTING to three postulated models with respectively two, three and four compartments is given. The 2-compartment example is used to illustrate the indistinguishability problem; the original (unidentifiable) model is found to have two structurally identifiable models that are indistinguishable from it. The 3-compartment example has three structurally identifiable indistinguishable models. It is found from DISTING that the four-compartment example has five structurally identifiable models indistinguishable from the original postulated model. This example shows that care is needed when dealing with models that have two or more compartments which are neither perturbed nor observed, because the numbering of these compartments may be arbitrary. DISTING is universally and freely available via the Internet. It is easy to use and circumvents tedious and complicated algebraic analysis previously done by hand. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. A mechanistic compartmental model for total antibody uptake in tumors.

    Science.gov (United States)

    Thurber, Greg M; Dane Wittrup, K

    2012-12-07

    Antibodies are under development to treat a variety of cancers, such as lymphomas, colon, and breast cancer. A major limitation to greater efficacy for this class of drugs is poor distribution in vivo. Localization of antibodies occurs slowly, often in insufficient therapeutic amounts, and distributes heterogeneously throughout the tumor. While the microdistribution around individual vessels is important for many therapies, the total amount of antibody localized in the tumor is paramount for many applications such as imaging, determining the therapeutic index with antibody drug conjugates, and dosing in radioimmunotherapy. With imaging and pretargeted therapeutic strategies, the time course of uptake is critical in determining when to take an image or deliver a secondary reagent. We present here a simple mechanistic model of antibody uptake and retention that captures the major rates that determine the time course of antibody concentration within a tumor including dose, affinity, plasma clearance, target expression, internalization, permeability, and vascularization. Since many of the parameters are known or can be estimated in vitro, this model can approximate the time course of antibody concentration in tumors to aid in experimental design, data interpretation, and strategies to improve localization. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. Compartmental modeling alternatives for kinetic analysis of pet neurotransmitter receptor studies

    International Nuclear Information System (INIS)

    Koeppe, R.A.

    1991-01-01

    With the increased interest in studying neurotransmitter and receptor function in vivo, imaging procedures using positron emission tomography have presented new challenges for kinetic modeling and analysis of data. The in vivo behavior of radiolabeled markers for examining these neurotransmitter systems can be quite complex and, therefore, the implementation of compartmental models for data analysis is similarly complex. Often, the variability in the estimates of model parameters representing neurotransmitter or receptor densities, association and dissociation rates, or rates of incorporation or turnover does not permit reliable interpretation of the data. When less complex analyses are used, these model parameters may be biased and thus also do not yield the information being sought. Examination of trade-offs between uncertainty and bias in the parameters of interest may be used to select a compartmental model configuration with an appropriate level of complexity. Modeling alternatives will be discussed for radioligands with varying kinetic properties, such as those that bind reversibly and rapidly and others that bind nearly irreversibly. Specific problems, such as those occurring when a radioligand is open-quotes flow limitedclose quotes also will be discussed

  3. Development and testing of a compartmentalized reaction network model for redox zones in contaminated aquifers

    Science.gov (United States)

    Abrams , Robert H.; Loague, Keith; Kent, Douglas B.

    1998-01-01

    The work reported here is the first part of a larger effort focused on efficient numerical simulation of redox zone development in contaminated aquifers. The sequential use of various electron acceptors, which is governed by the energy yield of each reaction, gives rise to redox zones. The large difference in energy yields between the various redox reactions leads to systems of equations that are extremely ill-conditioned. These equations are very difficult to solve, especially in the context of coupled fluid flow, solute transport, and geochemical simulations. We have developed a general, rational method to solve such systems where we focus on the dominant reactions, compartmentalizing them in a manner that is analogous to the redox zones that are often observed in the field. The compartmentalized approach allows us to easily solve a complex geochemical system as a function of time and energy yield, laying the foundation for our ongoing work in which we couple the reaction network, for the development of redox zones, to a model of subsurface fluid flow and solute transport. Our method (1) solves the numerical system without evoking a redox parameter, (2) improves the numerical stability of redox systems by choosing which compartment and thus which reaction network to use based upon the concentration ratios of key constituents, (3) simulates the development of redox zones as a function of time without the use of inhibition factors or switching functions, and (4) can reduce the number of transport equations that need to be solved in space and time. We show through the use of various model performance evaluation statistics that the appropriate compartment choice under different geochemical conditions leads to numerical solutions without significant error. The compartmentalized approach described here facilitates the next phase of this effort where we couple the redox zone reaction network to models of fluid flow and solute transport.

  4. A compartmental model of the cAMP/PKA/MAPK pathway in Bio-PEPA

    Directory of Open Access Journals (Sweden)

    Federica Ciocchetta

    2009-11-01

    Full Text Available The vast majority of biochemical systems involve the exchange of information between different compartments, either in the form of transportation or via the intervention of membrane proteins which are able to transmit stimuli between bordering compartments. The correct quantitative handling of compartments is, therefore, extremely important when modelling real biochemical systems. The Bio-PEPA process algebra is equipped with the capability of explicitly defining quantitative information such as compartment volumes and membrane surface areas. Furthermore, the recent development of the Bio-PEPA Eclipse Plug-in allows us to perform a correct stochastic simulation of multi-compartmental models. Here we present a Bio-PEPA compartmental model of the cAMP/PKA/MAPK pathway. We analyse the system using the Bio-PEPA Eclipse Plug-in and we show the correctness of our model by comparison with an existing ODE model. Furthermore, we perform computational experiments in order to investigate certain properties of the pathway. Specifically, we focus on the system response to the inhibition and strengthening of feedback loops and to the variation in the activity of key pathway reactions and we observe how these modifications affect the behaviour of the pathway. These experiments are useful to understand the control and regulatory mechanisms of the system.

  5. A comprehensive compartmental model of blood glucose regulation for healthy and type 2 diabetic subjects

    DEFF Research Database (Denmark)

    Vahidi, O; Kwok, K E; Gopaluni, R B

    2016-01-01

    We have expanded a former compartmental model of blood glucose regulation for healthy and type 2 diabetic subjects. The former model was a detailed physiological model which considered the interactions of three substances, glucose, insulin and glucagon on regulating the blood sugar. The main...... variations of blood glucose concentrations following an oral glucose intake. Another model representing the incretins production in the gastrointestinal tract along with their hormonal effects on boosting pancreatic insulin production is also added to the former model. We have used two sets of clinical data...... obtained during oral glucose tolerance test and isoglycemic intravenous glucose infusion test from both type 2 diabetic and healthy subjects to estimate the model parameters and to validate the model results. The estimation of model parameters is accomplished through solving a nonlinear optimization...

  6. Estimation of Caesium-137 Intake in Dicentrarchus Labrax by Using Compartmental Model and Neural Network

    International Nuclear Information System (INIS)

    Yahaghi, E.; Movafeghi, A.; Askari, M. A.; Karimi Diba, G.; Mohammadzadeh, N.

    2012-01-01

    Cs-137 is one of the fission products that is usually released in environment after nuclear accidents. This contamination remains in environment for a long time due to long half life of Cs-137 (30 years) and can enter easily into the human food chain. A two-compartmental model was implemented to describe caesium intake and its distribution in Dicentrarchus Labrax, using a proposed differential equation model. The model included two compartments, the first compartment was the blood and the second one was the tissue. The activity of Cs-137 was undertaken in each compartment by means of a numerical method and the activity of Cs-137 was considered as an input of compartmental equations. We obtained the transfer coefficients between fish tissues by comparing the radiation curves with the actual data. In the light of the differences with the transfer coefficients, the calculation by the COMKAT software was found to be about 2%. Then, we provided the activity curves of Cs-137 and their characteristics (feature extractions) by changing the transfer coefficients and they were utilized to train the neural network. The network was trained for six data groups, and the results of the network testing had about 99% correct response, therefore it can be employed to estimate the transfer coefficients in fish tissue, the salinity range, and the activity of Cs-137 in water.

  7. Metabolic hormones, apolipoproteins, adipokines, and cytokines in the alveolar lining fluid of healthy adults: compartmentalization and physiological correlates.

    Directory of Open Access Journals (Sweden)

    Carlos O Mendivil

    Full Text Available Our current understanding of hormone regulation in lung parenchyma is quite limited. We aimed to quantify a diverse array of biologically relevant protein mediators in alveolar lining fluid (ALF, compared to serum concentrations, and explore factors associated with protein compartmentalization on either side of the air-blood barrier.Participants were 24 healthy adult non-smoker volunteers without respiratory symptoms or significant medical conditions, with normal lung exams and office spirometry. Cell-free bronchoalveolar lavage fluid and serum were analyzed for 24 proteins (including enteric and metabolic hormones, apolipoproteins, adipokines, and cytokines using a highly sensitive multiplex ELISA. Measurements were normalized to ALF concentrations. The ALF:serum concentration ratios were examined in relation to measures of protein size, hydrophobicity, charge, and to participant clinical and spirometric values.ALF measurements from 24 individuals detected 19 proteins, including adiponectin, adipsin, apoA-I, apoA-II, apoB, apoC-II, apoC-III, apoE, C-reactive protein, ghrelin, glucose-dependent insulinotropic peptide (GIP, glucagon-like peptide-1 (GLP-1, glucagon, insulin, leptin, monocyte chemoattractant protein-1, plasminogen activator inhibitor-1, resistin, and visfatin. C-peptide and serpin E1 were not detected in ALF for any individual, and IL-6, IL-10, and TNF-alpha were not detected in either ALF or serum for any individual. In general, ALF levels were similar or lower in concentration for most proteins compared to serum. However, ghrelin, resistin, insulin, visfatin and GLP-1 had ALF concentrations significantly higher compared to serum. Importantly, elevated ALF:serum ratios of ghrelin, visfatin and resistin correlated with protein net charge and isoelectric point, but not with molecular weight or hydrophobicity.Biologically relevant enteric and metabolic hormones, apolipoproteins, adipokines, and cytokines can be detected in the ALF of

  8. Estimation of guinea pig tracheobronchial transport rates using a compartmental model

    International Nuclear Information System (INIS)

    Velasquez, D.J.; Morrow, P.E.

    1984-01-01

    Mucociliary clearance in the tracheobronchial tree of guinea pigs was examined using monodisperse 7.9 μm MMAD polystyrene particles. Animals were exposed for approximately 1 h by inhalation via an intratracheal tube to aerosols tagged with gold-198 and fluorescent dyes. Following exposure, animals were radioactively monitored and sacrificed at predetermined times. The lungs were removed, freeze-dried, sectioned completely, and examined with a fluorescent microscope. Measurements were made of airway diameters where particles were found. An anatomic model for guinea pig lung morphology was used to assign ranges of airway diameters to five zones, which were incorporated into a compartmental model for lung clearance. Kinetic analysis of particle distributions in the zones led to development of first-order equations describing the compartmental clearance. Rate constants obtained from the kinetic analysis were used to estimate mucociliary transport rates in specific bronchial generations, which ranged from approximately 0.001 mm/min in the distal bronchioles to approximately 8 mm/min in the trachea, and resulted in a calculated 24-h clearance time for tracheobronchial clearance in the guinea pig. No evidence for either bronchial penetration by particles or relatively prolonged bronchial retention of particles was found in this study. 22 references, 3 figures, 3 tables

  9. Fatigue in isometric contraction in a single muscle fibre: a compartmental calcium ion flow model.

    Science.gov (United States)

    Kothiyal, K P; Ibramsha, M

    1986-01-01

    Fatigue in muscle is a complex biological phenomenon which has so far eluded a definite explanation. Many biochemical and physiological models have been suggested in the literature to account for the decrement in the ability of muscle to sustain a given level of force for a long time. Some of these models have been critically analysed in this paper and are shown to be not able to explain all the experimental observations. A new compartmental model based on the intracellular calcium ion movement in muscle is proposed to study the mechanical responses of a muscle fibre. Computer simulation is performed to obtain model responses in isometric contraction to an impulse and a train of stimuli of long duration. The simulated curves have been compared with experimentally observed mechanical responses of the semitendinosus muscle fibre of Rana pipiens. The comparison of computed and observed responses indicates that the proposed calcium ion model indeed accounts very well for the muscle fatigue.

  10. Membrane Compartmentalization Reducing the Mobility of Lipids and Proteins within a Model Plasma Membrane.

    Science.gov (United States)

    Koldsø, Heidi; Reddy, Tyler; Fowler, Philip W; Duncan, Anna L; Sansom, Mark S P

    2016-09-01

    The cytoskeleton underlying cell membranes may influence the dynamic organization of proteins and lipids within the bilayer by immobilizing certain transmembrane (TM) proteins and forming corrals within the membrane. Here, we present coarse-grained resolution simulations of a biologically realistic membrane model of asymmetrically organized lipids and TM proteins. We determine the effects of a model of cytoskeletal immobilization of selected membrane proteins using long time scale coarse-grained molecular dynamics simulations. By introducing compartments with varying degrees of restraints within the membrane models, we are able to reveal how compartmentalization caused by cytoskeletal immobilization leads to reduced and anomalous diffusional mobility of both proteins and lipids. This in turn results in a reduced rate of protein dimerization within the membrane and of hopping of membrane proteins between compartments. These simulations provide a molecular realization of hierarchical models often invoked to explain single-molecule imaging studies of membrane proteins.

  11. Compartmentalization today

    Science.gov (United States)

    Kevin T. Smith

    2006-01-01

    For more than 30 years, the compartmentdization concept has helped tree care practitioners and land managers interpret patterns of decay in living trees. Understanding these patterns can help guide the selection of treatments that meet the needs of people and communities while respecting the underlying tree biology. At its simplest, compartmentalization resists the...

  12. Savannah River Laboratory DOSTOMAN code: a compartmental pathways computer model of contaminant transport

    International Nuclear Information System (INIS)

    King, C.M.; Wilhite, E.L.; Root, R.W. Jr.

    1985-01-01

    The Savannah River Laboratory DOSTOMAN code has been used since 1978 for environmental pathway analysis of potential migration of radionuclides and hazardous chemicals. The DOSTOMAN work is reviewed including a summary of historical use of compartmental models, the mathematical basis for the DOSTOMAN code, examples of exact analytical solutions for simple matrices, methods for numerical solution of complex matrices, and mathematical validation/calibration of the SRL code. The review includes the methodology for application to nuclear and hazardous chemical waste disposal, examples of use of the model in contaminant transport and pathway analysis, a user's guide for computer implementation, peer review of the code, and use of DOSTOMAN at other Department of Energy sites. 22 refs., 3 figs

  13. A dynamic compartmental food chain model of radiocaesium transfer to Apodemus sylvaticus in woodland ecosystems

    International Nuclear Information System (INIS)

    Toal, M.E.; Copplestone, D.; Johnson, M.S.; Jackson, D.; Jones, S.R.

    2001-01-01

    A study was undertaken to quantify the activity concentrations of 137Cs in Apodemus sylvaticus (the woodmouse) in two woodland sites, Lady Wood and Longrigg Wood, adjacent to British Nuclear Fuels Ltd. (BNFL) Sellafield, Cumbria, UK. A deterministic dynamic compartmental food chain model was also constructed to predict 137Cs activity concentration [Bq kg -1 dry weight (dw)] in A. sylvaticus on a seasonal basis given the activity concentrations in its diet. Within the coniferous woodland site (Lady Wood), significant differences were found between seasons (P x / 2.3 Bq kg -1 dw) being attributed to mycophagy. Fungal concentrations ranged from 2-3213 Bq kg -1 dw. The modelled activity concentrations fell between the confidence intervals of the observed data in four of the six seasonal cohorts sampled. Disparities between predicted and observed activity concentrations are attributed to uncertainties surrounding the fundamental feeding ecology of small mammals

  14. Compartmentalized Metabolic Engineering for Artemisinin Biosynthesis and Effective Malaria Treatment by Oral Delivery of Plant Cells.

    Science.gov (United States)

    Malhotra, Karan; Subramaniyan, Mayavan; Rawat, Khushboo; Kalamuddin, Md; Qureshi, M Irfan; Malhotra, Pawan; Mohmmed, Asif; Cornish, Katrina; Daniell, Henry; Kumar, Shashi

    2016-11-07

    Artemisinin is highly effective against drug-resistant malarial parasites, which affects nearly half of the global population and kills >500 000 people each year. The primary cost of artemisinin is the very expensive process used to extract and purify the drug from Artemisia annua. Elimination of this apparently unnecessary step will make this potent antimalarial drug affordable to the global population living in endemic regions. Here we reported the oral delivery of a non-protein drug artemisinin biosynthesized (∼0.8 mg/g dry weight) at clinically meaningful levels in tobacco by engineering two metabolic pathways targeted to three different cellular compartments (chloroplast, nucleus, and mitochondria). The doubly transgenic lines showed a three-fold enhancement of isopentenyl pyrophosphate, and targeting AACPR, DBR2, and CYP71AV1 to chloroplasts resulted in higher expression and an efficient photo-oxidation of dihydroartemisinic acid to artemisinin. Partially purified extracts from the leaves of transgenic tobacco plants inhibited in vitro growth progression of Plasmodium falciparum-infected red blood cells. Oral feeding of whole intact plant cells bioencapsulating the artemisinin reduced the parasitemia levels in challenged mice in comparison with commercial drug. Such novel synergistic approaches should facilitate low-cost production and delivery of artemisinin and other drugs through metabolic engineering of edible plants. Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.

  15. The construction of next-generation matrices for compartmental epidemic models.

    Science.gov (United States)

    Diekmann, O; Heesterbeek, J A P; Roberts, M G

    2010-06-06

    The basic reproduction number (0) is arguably the most important quantity in infectious disease epidemiology. The next-generation matrix (NGM) is the natural basis for the definition and calculation of (0) where finitely many different categories of individuals are recognized. We clear up confusion that has been around in the literature concerning the construction of this matrix, specifically for the most frequently used so-called compartmental models. We present a detailed easy recipe for the construction of the NGM from basic ingredients derived directly from the specifications of the model. We show that two related matrices exist which we define to be the NGM with large domain and the NGM with small domain. The three matrices together reflect the range of possibilities encountered in the literature for the characterization of (0). We show how they are connected and how their construction follows from the basic model ingredients, and establish that they have the same non-zero eigenvalues, the largest of which is the basic reproduction number (0). Although we present formal recipes based on linear algebra, we encourage the construction of the NGM by way of direct epidemiological reasoning, using the clear interpretation of the elements of the NGM and of the model ingredients. We present a selection of examples as a practical guide to our methods. In the appendix we present an elementary but complete proof that (0) defined as the dominant eigenvalue of the NGM for compartmental systems and the Malthusian parameter r, the real-time exponential growth rate in the early phase of an outbreak, are connected by the properties that (0) > 1 if and only if r > 0, and (0) = 1 if and only if r = 0.

  16. Evaluation of a compartmental model for estimating tumor hypoxia via FMISO dynamic PET imaging

    International Nuclear Information System (INIS)

    Wang Wenli; Nehmeh, Sadek A; O'Donoghue, Joseph; Zanzonico, Pat B; Schmidtlein, C Ross; Lee, Nancy Y; Humm, John L; Georgi, Jens-Christoph; Paulus, Timo; Narayanan, Manoj; Bal, Matthieu

    2009-01-01

    This paper systematically evaluates a pharmacokinetic compartmental model for identifying tumor hypoxia using dynamic positron emission tomography (PET) imaging with 18 F-fluoromisonidazole (FMISO). A generic irreversible one-plasma two-tissue compartmental model was used. A dynamic PET image dataset was simulated with three tumor regions-normoxic, hypoxic and necrotic-embedded in a normal-tissue background, and with an image-based arterial input function. Each voxelized tissue's time activity curve (TAC) was simulated with typical values of kinetic parameters, as deduced from FMISO-PET data from nine head-and-neck cancer patients. The dynamic dataset was first produced without any statistical noise to ensure that correct kinetic parameters were reproducible. Next, to investigate the stability of kinetic parameter estimation in the presence of noise, 1000 noisy samples of the dynamic dataset were generated, from which 1000 noisy estimates of kinetic parameters were calculated and used to estimate the sample mean and covariance matrix. It is found that a more peaked input function gave less variation in various kinetic parameters, and the variation of kinetic parameters could also be reduced by two region-of-interest averaging techniques. To further investigate how bias in the arterial input function affected the kinetic parameter estimation, a shift error was introduced in the peak amplitude and peak location of the input TAC, and the bias of various kinetic parameters calculated. In summary, mathematical phantom studies have been used to determine the statistical accuracy and precision of model-based kinetic analysis, which helps to validate this analysis and provides guidance in planning clinical dynamic FMISO-PET studies.

  17. A comprehensive compartmental model of blood glucose regulation for healthy and type 2 diabetic subjects.

    Science.gov (United States)

    Vahidi, O; Kwok, K E; Gopaluni, R B; Knop, F K

    2016-09-01

    We have expanded a former compartmental model of blood glucose regulation for healthy and type 2 diabetic subjects. The former model was a detailed physiological model which considered the interactions of three substances, glucose, insulin and glucagon on regulating the blood sugar. The main drawback of the former model was its restriction on the route of glucose entrance to the body which was limited to the intravenous glucose injection. To handle the oral glucose intake, we have added a model of glucose absorption in the gastrointestinal tract to the former model to address the resultant variations of blood glucose concentrations following an oral glucose intake. Another model representing the incretins production in the gastrointestinal tract along with their hormonal effects on boosting pancreatic insulin production is also added to the former model. We have used two sets of clinical data obtained during oral glucose tolerance test and isoglycemic intravenous glucose infusion test from both type 2 diabetic and healthy subjects to estimate the model parameters and to validate the model results. The estimation of model parameters is accomplished through solving a nonlinear optimization problem. The results show acceptable precision of the estimated model parameters and demonstrate the capability of the model in accurate prediction of the body response during the clinical studies.

  18. Compartmental and noncompartmental modeling of ¹³C-lycopene absorption, isomerization, and distribution kinetics in healthy adults.

    Science.gov (United States)

    Moran, Nancy E; Cichon, Morgan J; Riedl, Kenneth M; Grainger, Elizabeth M; Schwartz, Steven J; Novotny, Janet A; Erdman, John W; Clinton, Steven K

    2015-12-01

    Lycopene, which is a red carotenoid in tomatoes, has been hypothesized to mediate disease-preventive effects associated with tomato consumption. Lycopene is consumed primarily as the all-trans geometric isomer in foods, whereas human plasma and tissues show greater proportions of cis isomers. With the use of compartmental modeling and stable isotope technology, we determined whether endogenous all-trans-to-cis-lycopene isomerization or isomeric-bioavailability differences underlie the greater proportion of lycopene cis isomers in human tissues than in tomato foods. Healthy men (n = 4) and women (n = 4) consumed (13)C-lycopene (10.2 mg; 82% all-trans and 18% cis), and plasma was collected over 28 d. Unlabeled and (13)C-labeled total lycopene and lycopene-isomer plasma concentrations, which were measured with the use of high-performance liquid chromatography-mass spectrometry, were fit to a 7-compartment model. Subjects absorbed a mean ± SEM of 23% ± 6% of the lycopene. The proportion of plasma cis-(13)C-lycopene isomers increased over time, and all-trans had a shorter half-life than that of cis isomers (5.3 ± 0.3 and 8.8 ± 0.6 d, respectively; P lycopene bioavailability and endogenous trans-to-cis-lycopene isomerization was predictive of plasma (13)C and unlabeled cis- and all-trans-lycopene concentrations. Although the bioavailability of cis (24.5% ± 6%) and all-trans (23.2% ± 8%) isomers did not differ, endogenous isomerization (0.97 ± 0.25 μmol/d in the fast-turnover tissue lycopene pool) drove tissue and plasma isomeric profiles. (13)C-Lycopene combined with physiologic compartmental modeling provides a strategy for following complex in vivo metabolic processes in humans and reveals that postabsorptive trans-to-cis-lycopene isomerization, and not the differential bioavailability of isomers, drives tissue and plasma enrichment of cis-lycopene. This trial was registered at clinicaltrials.gov as NCT01692340. © 2015 American Society for Nutrition.

  19. Compartmental and noncompartmental modeling of 13C-lycopene absorption, isomerization, and distribution kinetics in healthy adults123

    Science.gov (United States)

    Moran, Nancy E; Cichon, Morgan J; Riedl, Kenneth M; Grainger, Elizabeth M; Schwartz, Steven J; Novotny, Janet A; Erdman, John W; Clinton, Steven K

    2015-01-01

    Background: Lycopene, which is a red carotenoid in tomatoes, has been hypothesized to mediate disease-preventive effects associated with tomato consumption. Lycopene is consumed primarily as the all-trans geometric isomer in foods, whereas human plasma and tissues show greater proportions of cis isomers. Objective: With the use of compartmental modeling and stable isotope technology, we determined whether endogenous all-trans-to-cis-lycopene isomerization or isomeric-bioavailability differences underlie the greater proportion of lycopene cis isomers in human tissues than in tomato foods. Design: Healthy men (n = 4) and women (n = 4) consumed 13C-lycopene (10.2 mg; 82% all-trans and 18% cis), and plasma was collected over 28 d. Unlabeled and 13C-labeled total lycopene and lycopene-isomer plasma concentrations, which were measured with the use of high-performance liquid chromatography–mass spectrometry, were fit to a 7-compartment model. Results: Subjects absorbed a mean ± SEM of 23% ± 6% of the lycopene. The proportion of plasma cis-13C-lycopene isomers increased over time, and all-trans had a shorter half-life than that of cis isomers (5.3 ± 0.3 and 8.8 ± 0.6 d, respectively; P lycopene bioavailability and endogenous trans-to-cis-lycopene isomerization was predictive of plasma 13C and unlabeled cis- and all-trans-lycopene concentrations. Although the bioavailability of cis (24.5% ± 6%) and all-trans (23.2% ± 8%) isomers did not differ, endogenous isomerization (0.97 ± 0.25 μmol/d in the fast-turnover tissue lycopene pool) drove tissue and plasma isomeric profiles. Conclusion: 13C-Lycopene combined with physiologic compartmental modeling provides a strategy for following complex in vivo metabolic processes in humans and reveals that postabsorptive trans-to-cis-lycopene isomerization, and not the differential bioavailability of isomers, drives tissue and plasma enrichment of cis-lycopene. This trial was registered at clinicaltrials.gov as NCT01692340. PMID

  20. Compartmental modelling of the pharmacokinetics of a breast cancer resistance protein.

    Science.gov (United States)

    Grandjean, Thomas R B; Chappell, Mike J; Yates, James T W; Jones, Kevin; Wood, Gemma; Coleman, Tanya

    2011-11-01

    A mathematical model for the pharmacokinetics of Hoechst 33342 following administration into a culture medium containing a population of transfected cells (HEK293 hBCRP) with a potent breast cancer resistance protein inhibitor, Fumitremorgin C (FTC), present is described. FTC is reported to almost completely annul resistance mediated by BCRP in vitro. This non-linear compartmental model has seven macroscopic sub-units, with 14 rate parameters. It describes the relationship between the concentration of Hoechst 33342 and FTC, initially spiked in the medium, and the observed change in fluorescence due to Hoechst 33342 binding to DNA. Structural identifiability analysis has been performed using two methods, one based on the similarity transformation/exhaustive modelling approach and the other based on the differential algebra approach. The analyses demonstrated that all models derived are uniquely identifiable for the experiments/observations available. A kinetic modelling software package, namely FACSIMILE (MPCA Software, UK), was used for parameter fitting and to obtain numerical solutions for the system equations. Model fits gave very good agreement with in vitro data provided by AstraZeneca across a variety of experimental scenarios. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  1. Dynamic PET scanning and compartmental model analysis to determine cellular level radiotracer distribution in vivo

    International Nuclear Information System (INIS)

    Smith, G.T.; Hubner, K.F.; Goodman, M.M.; Stubbs, J.B.

    1992-01-01

    Positron emission tomography (PET) has been used to measure tissue radiotracer concentration in vivo. Radiochemical distribution can be determined with compartmental model analysis. A two compartment model describes the kinetics of N-13 ammonia ( 13 NH 3 ) in the myocardium. The model consists of a vascular space, Q 1 and a space for 13 NH 3 bound within the tissue, Q 2 . Differential equations for the model can be written: X(t) = AX(t) + BU( t), Y(t)= CX(t)+ DU(t) (1) where X(t) is a column vector [Q 1 (t); Q 2 (t)], U(t) is the arterial input activity measured from the left ventricular blood pool, and Y(t) is the measured tissue activity using PET. Matrices A, B, C, and D are dependent on physiological parameters describing the kinetics of 13 NH 3 in the myocardium. Estimated parameter matrices in Equation 1 have been validated in dog experiments by measuring myocardial perfusion with dynamic PET scanning and intravenous injection of 13 NH 3 . Tracer concentrations for each compartment can be calculated by direct integration of Equation 1. If the cellular level distribution of each compartment is known, the concentration of tracer within the intracellular and extracellular space can be determined. Applications of this type of modeling include parameter estimation for measurement of physiological processes, organ level dosimetry, and determination of cellular radiotracer distribution

  2. Integrated compartmental model for describing the transport of solute in a fractured porous medium. [FRACPORT

    Energy Technology Data Exchange (ETDEWEB)

    DeAngelis, D.L.; Yeh, G.T.; Huff, D.D.

    1984-10-01

    This report documents a model, FRACPORT, that simulates the transport of a solute through a fractured porous matrix. The model should be useful in analyzing the possible transport of radionuclides from shallow-land burial sites in humid environments. The use of the model is restricted to transport through saturated zones. The report first discusses the general modeling approach used, which is based on the Integrated Compartmental Method. The basic equations of solute transport are then presented. The model, which assumes a known water velocity field, solves these equations on two different time scales; one related to rapid transport of solute along fractures and the other related to slower transport through the porous matrix. FRACPORT is validated by application to a simple example of fractured porous medium transport that has previously been analyzed by other methods. Then its utility is demonstrated in analyzing more complex cases of pulses of solute into a fractured matrix. The report serves as a user's guide to FRACPORT. A detailed description of data input, along with a listing of input for a sample problem, is provided. 16 references, 18 figures, 3 tables.

  3. Proposing a Compartmental Model for Leprosy and Parameterizing Using Regional Incidence in Brazil.

    Science.gov (United States)

    Smith, Rebecca Lee

    2016-08-01

    Hansen's disease (HD), or leprosy, is still considered a public health risk in much of Brazil. Understanding the dynamics of the infection at a regional level can aid in identification of targets to improve control. A compartmental continuous-time model for leprosy dynamics was designed based on understanding of the biology of the infection. The transmission coefficients for the model and the rate of detection were fit for each region using Approximate Bayesian Computation applied to paucibacillary and multibacillary incidence data over the period of 2000 to 2010, and model fit was validated on incidence data from 2011 to 2012. Regional variation was noted in detection rate, with cases in the Midwest estimated to be infectious for 10 years prior to detection compared to 5 years for most other regions. Posterior predictions for the model estimated that elimination of leprosy as a public health risk would require, on average, 44-45 years in the three regions with the highest prevalence. The model is easily adaptable to other settings, and can be studied to determine the efficacy of improved case finding on leprosy control.

  4. Linear least squares compartmental-model-independent parameter identification in PET

    International Nuclear Information System (INIS)

    Thie, J.A.; Smith, G.T.; Hubner, K.F.

    1997-01-01

    A simplified approach involving linear-regression straight-line parameter fitting of dynamic scan data is developed for both specific and nonspecific models. Where compartmental-model topologies apply, the measured activity may be expressed in terms of: its integrals, plasma activity and plasma integrals -- all in a linear expression with macroparameters as coefficients. Multiple linear regression, as in spreadsheet software, determines parameters for best data fits. Positron emission tomography (PET)-acquired gray-matter images in a dynamic scan are analyzed: both by this method and by traditional iterative nonlinear least squares. Both patient and simulated data were used. Regression and traditional methods are in expected agreement. Monte-Carlo simulations evaluate parameter standard deviations, due to data noise, and much smaller noise-induced biases. Unique straight-line graphical displays permit visualizing data influences on various macroparameters as changes in slopes. Advantages of regression fitting are: simplicity, speed, ease of implementation in spreadsheet software, avoiding risks of convergence failures or false solutions in iterative least squares, and providing various visualizations of the uptake process by straight line graphical displays. Multiparameter model-independent analyses on lesser understood systems is also made possible

  5. Plant metabolic modeling: achieving new insight into metabolism and metabolic engineering.

    Science.gov (United States)

    Baghalian, Kambiz; Hajirezaei, Mohammad-Reza; Schreiber, Falk

    2014-10-01

    Models are used to represent aspects of the real world for specific purposes, and mathematical models have opened up new approaches in studying the behavior and complexity of biological systems. However, modeling is often time-consuming and requires significant computational resources for data development, data analysis, and simulation. Computational modeling has been successfully applied as an aid for metabolic engineering in microorganisms. But such model-based approaches have only recently been extended to plant metabolic engineering, mainly due to greater pathway complexity in plants and their highly compartmentalized cellular structure. Recent progress in plant systems biology and bioinformatics has begun to disentangle this complexity and facilitate the creation of efficient plant metabolic models. This review highlights several aspects of plant metabolic modeling in the context of understanding, predicting and modifying complex plant metabolism. We discuss opportunities for engineering photosynthetic carbon metabolism, sucrose synthesis, and the tricarboxylic acid cycle in leaves and oil synthesis in seeds and the application of metabolic modeling to the study of plant acclimation to the environment. The aim of the review is to offer a current perspective for plant biologists without requiring specialized knowledge of bioinformatics or systems biology. © 2014 American Society of Plant Biologists. All rights reserved.

  6. Linear regressive model structures for estimation and prediction of compartmental diffusive systems

    NARCIS (Netherlands)

    Vries, D; Keesman, K.J.; Zwart, Heiko J.

    In input-output relations of (compartmental) diffusive systems, physical parameters appear non-linearly, resulting in the use of (constrained) non-linear parameter estimation techniques with its short-comings regarding global optimality and computational effort. Given a LTI system in state space

  7. Linear regressive model structures for estimation and prediction of compartmental diffusive systems

    NARCIS (Netherlands)

    Vries, D.; Keesman, K.J.; Zwart, H.

    2006-01-01

    Abstract In input-output relations of (compartmental) diffusive systems, physical parameters appear non-linearly, resulting in the use of (constrained) non-linear parameter estimation techniques with its short-comings regarding global optimality and computational effort. Given a LTI system in state

  8. Validation of Bayesian analysis of compartmental kinetic models in medical imaging.

    Science.gov (United States)

    Sitek, Arkadiusz; Li, Quanzheng; El Fakhri, Georges; Alpert, Nathaniel M

    2016-10-01

    Kinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated. The closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach. Posteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P>0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P<0.0001). The results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  9. Compartmental study of biological systems

    International Nuclear Information System (INIS)

    Moretti, J.L.

    1975-01-01

    The compartmental analysis of biological system is dealt with on several chapters devoted successively to: terminology; a mathematical and symbolic account of a system at equilibrium; different compartment systems; analysis of the experimental results. For this it is pointed out that the application of compartmental systems to biological phenomena is not always without danger. Sometimes the compartmental system established in a reference subject fails to conform in the patient. The compartments can divide into two or join together, completely changing the aspect of the system so that parameters calculated with the old model become entirely false. The conclusion is that the setting up of a compartmental system to represent a biological phenomenon is a tricky undertaking and the results must be constantly criticized and questioned [fr

  10. Computer Modeling of Sand Transport on Mars Using a Compart-Mentalized Fluids Algorithm (CFA)

    Science.gov (United States)

    Marshall, J.; Stratton, D.

    1999-01-01

    of sand comminution on Mars. A multiple-grain transport model using just the equations of grain motion describing lift and drag is impossible to develop owing to stochastic effects --the very effects we wish to model. Also, unless we were to employ supercomputing techniques and extremely complex computer codes that could deal with millions of grains simultaneously, it would also be difficult to model grain transport if we attempted to consider every grain in motion. No existing computer models were found that satisfactorily used the equations of motion to arrive at transport flux numbers for the different populations of saltation and reptation. Modeling all the grains in a transport system was an intractable problem within our resources, and thus we developed what we believe to be a new modeling approach to simulating grain transport. The CFA deals with grain populations, but considers them to belong to various compartmentalized fluid units in the boundary layer. In this way, the model circumvents the multigrain problem by dealing primarily with the consequences of grain transport --momentum transfer between air and grains, which is the physical essence of a dynamic grain-fluid mixture. We thus chose to model the aeolian transport process as a superposition of fluids. These fluids include the air as well as particle populations of various properties. The prime property distinguishing these fluids is upward and downward grain motion. In a normal saltation trajectory, a grain's downwind velocity increases with time, so a rising grain will have a smaller downwind velocity than a failing grain. Because of this disparity in rising and falling grain proper-ties, it seemed appropriate to track these as two separate grain populations within the same physical space. The air itself can be considered a separate fluid superimposed within and interacting with the various grain-cloud "fluids". Additional informaiton is contained in the original.

  11. Mathematical modelling of metabolism

    DEFF Research Database (Denmark)

    Gombert, Andreas Karoly; Nielsen, Jens

    2000-01-01

    Mathematical models of the cellular metabolism have a special interest within biotechnology. Many different kinds of commercially important products are derived from the cell factory, and metabolic engineering can be applied to improve existing production processes, as well as to make new processes...... availability of genomic information and powerful analytical techniques, mathematical models also serve as a tool for understanding the cellular metabolism and physiology....... available. Both stoichiometric and kinetic models have been used to investigate the metabolism, which has resulted in defining the optimal fermentation conditions, as well as in directing the genetic changes to be introduced in order to obtain a good producer strain or cell line. With the increasing...

  12. Stratigraphic and structural compartmentalization observed within a model turbidite reservoir, Pennsylvanian Upper Jackfork Formation, Hollywood Quarry, Arkansas

    Energy Technology Data Exchange (ETDEWEB)

    Slatt, R. [Colorado School of Mines, Golden, CO (United States); Jordan, D. [Arco International Oil and Gas Co., Plano, TX (United States); Stone, C. [Arkansas Geological Commission, Little Rock, AR (United States)] [and others

    1995-08-01

    Hollywood Quarry is a 600 x 375 x 150 ft. (200 x 125 x 50m) excavation which provides a window into lower Pennsylvanian Jackfork Formation turbidite stratal architecture along the crest of a faulted anticlinal fold. A variety of turbidite facies are present, including: (a) lenticular, channelized sandstones, pebbly sandstones, and conglomerates within shale, (b) laterally continuous, interbedded thin sandstones and shales, and (c) thicker, laterally continuous shales. The sandstone and shale layers we broken by several strike-slip and reverse faults, with vertical displacements of up to several feet. This combination of facies and structural elements has resulted in a highly compartmentalized stratigraphic interval, both horizontally and vertically, along the anticlinal flexure. The quarry can be considered analogous to a scaled-down turbidite reservoir. Outcrop gamma-ray logs, measured sections, a fault map, and cross sections provide a database which is analogous to what would be available for a subsurface reservoir. Thus, the quarry provides an ideal outdoor geologic and engineering {open_quote}workshop{close_quote} venue for visualizing the potential complexities of a combination structural-stratigraphic (turbidite) reservoir. Since all forms of compartmentalization are readily visible in the quarry, problems related to management of compartmentalized reservoirs can be discussed and analyzed first-hand while standing in the quarry, within this {open_quote}model reservoir{close_quotes}. These problems include: (a) the high degree of stratigraphic and structural complexity that may be encountered, even at close well spacings, (b) uncertainty in well log correlations and log-shape interpretations, (c) variations in volumetric calculations as a function of amount of data available, and (d) potential production problems associated with specific {open_quote}field{close_quote} development plans.

  13. Modulation of cytokine release by differentiated CACO-2 cells in a compartmentalized coculture model with mononuclear leucocytes and nonpathogenic bacteria

    DEFF Research Database (Denmark)

    Parlesak, Alexandr; Haller, D.; Brinz, S.

    2004-01-01

    To further investigate the interaction between human mononuclear leucocytes [peripheral blood mononuclear cells (PBMC)] and enterocytes, the effect of a confluent layer of differentiated CACO-2 cells on cytokine kinetics during challenge with bacteria in a compartmentalized coculture model...... cells when leucocytes were stimulated directly with bacteria. This suppression was not paralleled by changes in the production of IL-10, IL-6 and transforming growth factor (TGF)-beta. When the bacteria were applied apically to the CACO-2 cell layer, the production of TNF-alpha, IL-12, IL-1beta, IL-8......, IL-6, IL-10, TGF-beta and interferon-gamma was pronouncedly lower as compared to the bacterial stimulation of leucocytes beneath the CACO-2 cells. In the latter experiments, IL-6, IL-8 and TNF-alpha were the cytokines being mostly induced by apical addition of E. coli. Quantitative mRNA expression...

  14. Biodistribution and biological characteristics of p-[(bis-carboxymethyl) aminomethyl carboxyamino] hippuric acid (Pahida) labelled with technetium-99m. Establishment of pharmacokinetics parameters through compartmental model

    International Nuclear Information System (INIS)

    Araujo, E.B. de.

    1990-01-01

    Biologic distribution of p- [(bis-carboxymethylaminomethyl carboxyamino)] hippuric acid (PAHIDA) labeled with sup(99m)Tc in Wistar rats, showed a selective renal uptake among the other organs and tissues. The compound is predominantly eliminated by urinary tract, with small enterohepatic percent of excretion Chromatographic analysis of urine showed the product and possible metabolites. PAHIDA- sup(99m)Tc blood clearance is relatively rapid and a good percent is transported by plasmatic proteins. The percent binding to the erythrocytes is significant after one hour, this is due probably to hydrolysed technetium. The extrapolation of the plasmatic curve denoted the existence of three exponentials, suggesting a model with three compartments: central or intravascular and two peripherics or extravasculars - rapid and slow exchange (retention). Exponential's half life and the transfer constant (k) among the compartments were determined. The compound retention was reaffirmed by whole body determination. The decomposition of the curve in two exponentials allowed to assess the component's half-life. The compartmental model proposed in agreement with the experimental results, showed the complex retention that may be related the binding with the blood components, the possibility of renal metabolization or a structural impediment in the interaction with the tubular cells receptors. (author)

  15. Lyophilized kits of diamino dithiol compounds for labelling with 99m-technetium. Pharmacokinetics studies and distribution compartmental models of the related complexes

    International Nuclear Information System (INIS)

    Araujo, Elaine Bortoleti de

    1995-01-01

    , permitting the acquisition of scintigraphic cerebral images. The cerebral retention of the complex, and also its relative fast elimination are related to the metabolization of the compound to more polar species, identified in the urine and bile HPLC. The lipophilicity of the complex determine high liver uptake and intestinal elimination of the compound. Biological distribution of the complex 99m Tc-L.L-ECD was adjusted to a compartmental distribution model composed by seven compartments, characterized by a fast blood clearance, an unidirectional renal depuration and intestinal elimination, determined by intense hepato-biliary transit. (author)

  16. Two-compartmental population balance modeling of a pulsed spray fluidized bed granulation based on computational fluid dynamics (CFD) analysis.

    Science.gov (United States)

    Liu, Huolong; Li, Mingzhong

    2014-11-20

    In this work a two-compartmental population balance model (TCPBM) was proposed to model a pulsed top-spray fluidized bed granulation. The proposed TCPBM considered the spatially heterogeneous granulation mechanisms of the granule growth by dividing the granulator into two perfectly mixed zones of the wetting compartment and drying compartment, in which the aggregation mechanism was assumed in the wetting compartment and the breakage mechanism was considered in the drying compartment. The sizes of the wetting and drying compartments were constant in the TCPBM, in which 30% of the bed was the wetting compartment and 70% of the bed was the drying compartment. The exchange rate of particles between the wetting and drying compartments was determined by the details of the flow properties and distribution of particles predicted by the computational fluid dynamics (CFD) simulation. The experimental validation has shown that the proposed TCPBM can predict evolution of the granule size and distribution within the granulator under different binder spray operating conditions accurately. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. The role of extracellular conductivity profiles in compartmental models for neurons: particulars for layer 5 pyramidal cells.

    Science.gov (United States)

    Wang, Kai; Riera, Jorge; Enjieu-Kadji, Herve; Kawashima, Ryuta

    2013-07-01

    With the rapid increase in the number of technologies aimed at observing electric activity inside the brain, scientists have felt the urge to create proper links between intracellular- and extracellular-based experimental approaches. Biophysical models at both physical scales have been formalized under assumptions that impede the creation of such links. In this work, we address this issue by proposing a multicompartment model that allows the introduction of complex extracellular and intracellular resistivity profiles. This model accounts for the geometrical and electrotonic properties of any type of neuron through the combination of four devices: the integrator, the propagator, the 3D connector, and the collector. In particular, we applied this framework to model the tufted pyramidal cells of layer 5 (PCL5) in the neocortex. Our model was able to reproduce the decay and delay curves of backpropagating action potentials (APs) in this type of cell with better agreement with experimental data. We used the voltage drops of the extracellular resistances at each compartment to approximate the local field potentials generated by a PCL5 located in close proximity to linear microelectrode arrays. Based on the voltage drops produced by backpropagating APs, we were able to estimate the current multipolar moments generated by a PCL5. By adding external current sources in parallel to the extracellular resistances, we were able to create a sensitivity profile of PCL5 to electric current injections from nearby microelectrodes. In our model for PCL5, the kinetics and spatial profile of each ionic current were determined based on a literature survey, and the geometrical properties of these cells were evaluated experimentally. We concluded that the inclusion of the extracellular space in the compartmental models of neurons as an extra electrotonic medium is crucial for the accurate simulation of both the propagation of the electric potentials along the neuronal dendrites and the

  18. Comparison of linear and nonlinear implementation of the compartmental tissue uptake model for dynamic contrast-enhanced MRI.

    Science.gov (United States)

    Kallehauge, Jesper F; Sourbron, Steven; Irving, Benjamin; Tanderup, Kari; Schnabel, Julia A; Chappell, Michael A

    2017-06-01

    Fitting tracer kinetic models using linear methods is much faster than using their nonlinear counterparts, although this comes often at the expense of reduced accuracy and precision. The aim of this study was to derive and compare the performance of the linear compartmental tissue uptake (CTU) model with its nonlinear version with respect to their percentage error and precision. The linear and nonlinear CTU models were initially compared using simulations with varying noise and temporal sampling. Subsequently, the clinical applicability of the linear model was demonstrated on 14 patients with locally advanced cervical cancer examined with dynamic contrast-enhanced magnetic resonance imaging. Simulations revealed equal percentage error and precision when noise was within clinical achievable ranges (contrast-to-noise ratio >10). The linear method was significantly faster than the nonlinear method, with a minimum speedup of around 230 across all tested sampling rates. Clinical analysis revealed that parameters estimated using the linear and nonlinear CTU model were highly correlated (ρ ≥ 0.95). The linear CTU model is computationally more efficient and more stable against temporal downsampling, whereas the nonlinear method is more robust to variations in noise. The two methods may be used interchangeably within clinical achievable ranges of temporal sampling and noise. Magn Reson Med 77:2414-2423, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

  19. Generalized framework for context-specific metabolic model extraction methods

    Directory of Open Access Journals (Sweden)

    Semidán eRobaina Estévez

    2014-09-01

    Full Text Available Genome-scale metabolic models are increasingly applied to investigate the physiology not only of simple prokaryotes, but also eukaryotes, such as plants, characterized with compartmentalized cells of multiple types. While genome-scale models aim at including the entirety of known metabolic reactions, mounting evidence has indicated that only a subset of these reactions is active in a given context, including: developmental stage, cell type, or environment. As a result, several methods have been proposed to reconstruct context-specific models from existing genome-scale models by integrating various types of high-throughput data. Here we present a mathematical framework that puts all existing methods under one umbrella and provides the means to better understand their functioning, highlight similarities and differences, and to help users in selecting a most suitable method for an application.

  20. Metabolism of γ-hydroxyl-[1-14C] butyrate by rat brain: relationship to the Krebs cycle and metabolic compartmentation of amino acids

    International Nuclear Information System (INIS)

    Doherty, J.D.; Roth, R.H.

    1978-01-01

    Ninhydrin decarboxylation experiments were carried out on the labelled amino acids produced following intraventricular injection of either γ-hydroxy-[1- 14 C] butyric acid (GHB) or [1- 14 C] succinate. The loss of isotope (as 14 CO 2 ) was similar for both substances. The [1- 14 C] GHB metabolites lost 75% of the label and the [1- 14 C] succinate metabolites lost 68%. This observation gives support to the hypothesis that the rat brain has the enzymatic capacity to metabolize [1- 14 C] GHB to succinate and to amino acids that have the isotope in the carboxylic acid group adjacent to the α-amino group. These results also indicate that the label from [1- 14 C] GHB does not enter the Krebs cycle as acetate. The specific activity ratio of radio-labelled glutamine to glutamic acid was determined in order to evaluate which of the two major metabolic compartments prefentially metabolize GHB. It was found that for [1- 14 C] GHB the ratio was 4.20 +- 0.18 (S.E. for n = 7) and for [1- 14 C] succinate the ratio was 7.71 (average of two trials, 7.74 and 7.69). These results suggest that the compartment thought to be associated with glial cells and synaptosomal structures is largely responsible for the metabolism of GHB. Metabolism as it might relate to the neuropharmacological action of GHB is discussed. (author)

  1. A workflow for mathematical modeling of subcellular metabolic pathways in leaf metabolism of Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Thomas eNägele

    2013-12-01

    Full Text Available During the last decade genome sequencing has experienced a rapid technological development resulting in numerous sequencing projects and applications in life science. In plant molecular biology, the availability of sequence data on whole genomes has enabled the reconstruction of metabolic networks. Enzymatic reactions are predicted by the sequence information. Pathways arise due to the participation of chemical compounds as substrates and products in these reactions. Although several of these comprehensive networks have been reconstructed for the genetic model plant Arabidopsis thaliana, the integration of experimental data is still challenging. Particularly the analysis of subcellular organization of plant cells limits the understanding of regulatory instances in these metabolic networks in vivo. In this study, we develop an approach for the functional integration of experimental high-throughput data into such large-scale networks. We present a subcellular metabolic network model comprising 524 metabolic intermediates and 548 metabolic interactions derived from a total of 2769 reactions. We demonstrate how to link the metabolite covariance matrix of different Arabidopsis thaliana accessions with the subcellular metabolic network model for the inverse calculation of the biochemical Jacobian, finally resulting in the calculation of a matrix which satisfies a Lyaponov equation involving a covariance matrix. In this way, differential strategies of metabolite compartmentation and involved reactions were identified in the accessions when exposed to low temperature.

  2. A framework for 2-stage global sensitivity analysis of GastroPlus™ compartmental models.

    Science.gov (United States)

    Scherholz, Megerle L; Forder, James; Androulakis, Ioannis P

    2018-04-01

    Parameter sensitivity and uncertainty analysis for physiologically based pharmacokinetic (PBPK) models are becoming an important consideration for regulatory submissions, requiring further evaluation to establish the need for global sensitivity analysis. To demonstrate the benefits of an extensive analysis, global sensitivity was implemented for the GastroPlus™ model, a well-known commercially available platform, using four example drugs: acetaminophen, risperidone, atenolol, and furosemide. The capabilities of GastroPlus were expanded by developing an integrated framework to automate the GastroPlus graphical user interface with AutoIt and for execution of the sensitivity analysis in MATLAB ® . Global sensitivity analysis was performed in two stages using the Morris method to screen over 50 parameters for significant factors followed by quantitative assessment of variability using Sobol's sensitivity analysis. The 2-staged approach significantly reduced computational cost for the larger model without sacrificing interpretation of model behavior, showing that the sensitivity results were well aligned with the biopharmaceutical classification system. Both methods detected nonlinearities and parameter interactions that would have otherwise been missed by local approaches. Future work includes further exploration of how the input domain influences the calculated global sensitivity measures as well as extending the framework to consider a whole-body PBPK model.

  3. A compartmentalized mathematical model of the β1-adrenergic signaling system in mouse ventricular myocytes.

    Directory of Open Access Journals (Sweden)

    Vladimir E Bondarenko

    Full Text Available The β1-adrenergic signaling system plays an important role in the functioning of cardiac cells. Experimental data shows that the activation of this system produces inotropy, lusitropy, and chronotropy in the heart, such as increased magnitude and relaxation rates of [Ca(2+]i transients and contraction force, and increased heart rhythm. However, excessive stimulation of β1-adrenergic receptors leads to heart dysfunction and heart failure. In this paper, a comprehensive, experimentally based mathematical model of the β1-adrenergic signaling system for mouse ventricular myocytes is developed, which includes major subcellular functional compartments (caveolae, extracaveolae, and cytosol. The model describes biochemical reactions that occur during stimulation of β1-adrenoceptors, changes in ionic currents, and modifications of Ca(2+ handling system. Simulations describe the dynamics of major signaling molecules, such as cyclic AMP and protein kinase A, in different subcellular compartments; the effects of inhibition of phosphodiesterases on cAMP production; kinetics and magnitudes of phosphorylation of ion channels, transporters, and Ca(2+ handling proteins; modifications of action potential shape and duration; magnitudes and relaxation rates of [Ca(2+]i transients; changes in intracellular and transmembrane Ca(2+ fluxes; and [Na(+]i fluxes and dynamics. The model elucidates complex interactions of ionic currents upon activation of β1-adrenoceptors at different stimulation frequencies, which ultimately lead to a relatively modest increase in action potential duration and significant increase in [Ca(2+]i transients. In particular, the model includes two subpopulations of the L-type Ca(2+ channels, in caveolae and extracaveolae compartments, and their effects on the action potential and [Ca(2+]i transients are investigated. The presented model can be used by researchers for the interpretation of experimental data and for the developments of

  4. Compartmental model for tritium persistence in the soil-plant system

    International Nuclear Information System (INIS)

    Iyengar, T.S.; Sadarangani, S.H.; Vaze, P.K.; Soman, S.D.

    1977-01-01

    A three-component computer model for tritium persistence in the soil-plant system, on the basis of an exponential polynomial is attempted. A series of field experiments with four species of trees, viz. Cardia sebastina, Terminalia catappa, Aracaria bidwilli and Mangifera indica, were carried out to generate data for testing the model. It is observed that there are two short-term components and one long-term component for tritium mean residence time, corresponding to the three phases of tritium in the system, viz. Tissue-Free-Water-Tritium, labile component of Tissue-Bound-Tritium and non-labile component of Tissue-Bound-Tritium. (author)

  5. Simulation of radon short lived decay daughters' inhalation using the lung compartmental model

    International Nuclear Information System (INIS)

    Tomulescu, Vlad C.

    2002-01-01

    Radon and its short-lived decay daughters are the main source of radiation on natural ways for population. The radon gas, released from soil, water or construction materials is producing by radioactive decay the following solid daughters: Po-218, Bi-214, Pb-214, and Po-214, which can attach to aerosols, and consequently penetrate the organism by inhalation. The human respiratory tract can be approximated by aid of a compartment model that takes into account the different anatomical structures exposed to contamination and irradiation, as well as the respective physiological processes. This model is associated to a mathematical equation system that describes the behavior of the radioactive material inside the body. The results represent the dose equivalent on different organs and tissues, as a function of subject and the activity performed in contaminating environment. (author)

  6. Analytical solutions to compartmental indoor air quality models with application to environmental tobacco smoke concentrations measured in a house.

    Science.gov (United States)

    Ott, Wayne R; Klepeis, Neil E; Switzer, Paul

    2003-08-01

    This paper derives the analytical solutions to multi-compartment indoor air quality models for predicting indoor air pollutant concentrations in the home and evaluates the solutions using experimental measurements in the rooms of a single-story residence. The model uses Laplace transform methods to solve the mass balance equations for two interconnected compartments, obtaining analytical solutions that can be applied without a computer. Environmental tobacco smoke (ETS) sources such as the cigarette typically emit pollutants for relatively short times (7-11 min) and are represented mathematically by a "rectangular" source emission time function, or approximated by a short-duration source called an "impulse" time function. Other time-varying indoor sources also can be represented by Laplace transforms. The two-compartment model is more complicated than the single-compartment model and has more parameters, including the cigarette or combustion source emission rate as a function of time, room volumes, compartmental air change rates, and interzonal air flow factors expressed as dimensionless ratios. This paper provides analytical solutions for the impulse, step (Heaviside), and rectangular source emission time functions. It evaluates the indoor model in an unoccupied two-bedroom home using cigars and cigarettes as sources with continuous measurements of carbon monoxide (CO), respirable suspended particles (RSP), and particulate polycyclic aromatic hydrocarbons (PPAH). Fine particle mass concentrations (RSP or PM3.5) are measured using real-time monitors. In our experiments, simultaneous measurements of concentrations at three heights in a bedroom confirm an important assumption of the model-spatial uniformity of mixing. The parameter values of the two-compartment model were obtained using a "grid search" optimization method, and the predicted solutions agreed well with the measured concentration time series in the rooms of the home. The door and window positions in

  7. Reconstructing historical radionuclide concentrations along the east coast of Ireland using a compartmental model

    International Nuclear Information System (INIS)

    Smith, C.N.; Clarke, S.; McDonald, P.; Goshawk, J.A.; Jones, S.R.

    2000-01-01

    A mathematical model is presented that simulates the annually averaged transport of radionuclides, originating from the BNFL reprocessing plant at Sellafield, throughout the Irish Sea. The model, CUMBRIA77, represents the processes of radionuclide transport and dispersion in the marine environment and allows predictions of radionuclide concentration in various environmental media, including biota, to be made throughout the whole of the Irish Sea. In this paper we describe the use of the model to reconstruct the historical activity concentrations of 137Cs and 239+240Pu in a variety of environmental media in the western Irish Sea and along the Irish east coast back to 1950. This reconstruction exercise is of interest because only limited measurements of 137Cs and 239+240Pu activity are available prior to the 1980s. The predictions were compared to the available measured data to validate their accuracy. The results of the reconstruction indicate that activity concentrations of 137Cs in the western Irish Sea follow a similar, though slightly delayed and smoothed, profile to the discharges from the Sellafield site, with concentrations at the time of peak discharge (the mid-1970s) being around an order of magnitude higher than those measured in the 1980s and 1990s. By contrast, the concentrations of 239+240Pu at the time of peak discharges were similar to those presently measured. These differences reflect the distinct marine chemistries of the two nuclides, in particular the higher propensity of plutonium to bind to sediments leading to extended transport times. Despite these differences in behaviour the doses to Irish seafood consumers from 137Cs remain significantly higher than those from 239+240Pu

  8. Reconstruction and modeling protein translocation and compartmentalization in Escherichia coli at the genome-scale

    DEFF Research Database (Denmark)

    Liu, Joanne K.; O’Brien, Edward J.; Lerman, Joshua A.

    2014-01-01

    Background: Membranes play a crucial role in cellular functions. Membranes provide a physical barrier, control the trafficking of substances entering and leaving the cell, and are a major determinant of cellular ultra-structure. In addition, components embedded within the membrane participate...... the computation of cellular phenotypes through an integrated computation of proteome composition, abundance, and activity in four cellular compartments (cytoplasm, periplasm, inner and outer membrane). Reconstruction and validation of the model has demonstrated that the iJL1678-ME is capable of capturing...

  9. Classical algorithms for automated parameter-search methods in compartmental neural models - A critical survey based on simulations using neuron

    International Nuclear Information System (INIS)

    Mutihac, R.; Mutihac, R.C.; Cicuttin, A.

    2001-09-01

    gradient-descent techniques are adequate if the parameter space is low-dimensional, relatively smooth, and has a few local minima (e.g., parameterizing single-neuron compartmental models). Only the fast algorithms and/or a decent (low) number of model parameters are candidates for automated parameter search because of practical reasons. Eventually, the size of the parameter space may be reduced and/or parallel supercomputers may be used. Data overfitting may negatively affect the generalization ability of the model. Bayesian methods include Occam's factor, which set the preference for simpler models. Proliferation of (neural) models raises the question of rigorous criteria for comparing the overall performance of various models designed to match the same type of data. Bayesian methods provide the best framework to assess the neural models quantitatively. Paradoxically, parameter-search methods may sometimes be more useful when they fail by discarding unrealistic mechanisms used in the model design, rather than fitting experimental data to an alleged model

  10. A Network Thermodynamic Approach to Compartmental Analysis

    Science.gov (United States)

    Mikulecky, D. C.; Huf, E. G.; Thomas, S. R.

    1979-01-01

    We introduce a general network thermodynamic method for compartmental analysis which uses a compartmental model of sodium flows through frog skin as an illustrative example (Huf and Howell, 1974a). We use network thermodynamics (Mikulecky et al., 1977b) to formulate the problem, and a circuit simulation program (ASTEC 2, SPICE2, or PCAP) for computation. In this way, the compartment concentrations and net fluxes between compartments are readily obtained for a set of experimental conditions involving a square-wave pulse of labeled sodium at the outer surface of the skin. Qualitative features of the influx at the outer surface correlate very well with those observed for the short circuit current under another similar set of conditions by Morel and LeBlanc (1975). In related work, the compartmental model is used as a basis for simulation of the short circuit current and sodium flows simultaneously using a two-port network (Mikulecky et al., 1977a, and Mikulecky et al., A network thermodynamic model for short circuit current transients in frog skin. Manuscript in preparation; Gary-Bobo et al., 1978). The network approach lends itself to computation of classic compartmental problems in a simple manner using circuit simulation programs (Chua and Lin, 1975), and it further extends the compartmental models to more complicated situations involving coupled flows and non-linearities such as concentration dependencies, chemical reaction kinetics, etc. PMID:262387

  11. Mathematical modeling of cancer metabolism.

    Science.gov (United States)

    Medina, Miguel Ángel

    2018-04-01

    Systemic approaches are needed and useful for the study of the very complex issue of cancer. Modeling has a central position in these systemic approaches. Metabolic reprogramming is nowadays acknowledged as an essential hallmark of cancer. Mathematical modeling could contribute to a better understanding of cancer metabolic reprogramming and to identify new potential ways of therapeutic intervention. Herein, I review several alternative approaches to metabolic modeling and their current and future impact in oncology. Copyright © 2018 Elsevier B.V. All rights reserved.

  12. Gadoxetate-enhanced MR imaging and compartmental modelling to assess hepatocyte bidirectional transport function in rats with advanced liver fibrosis

    Energy Technology Data Exchange (ETDEWEB)

    Giraudeau, Celine; Leporq, Benjamin; Doblas, Sabrina [University Paris Diderot, Sorbonne Paris Cite, Hopital Beaujon, Laboratory of Imaging Biomarkers, UMR1149 Inserm, Clichy (France); Lagadec, Matthieu; Daire, Jean-Luc; Van Beers, Bernard E. [University Paris Diderot, Sorbonne Paris Cite, Hopital Beaujon, Laboratory of Imaging Biomarkers, UMR1149 Inserm, Clichy (France); Beaujon University Hospital Paris Nord, Department of Radiology, Clichy (France); Pastor, Catherine M. [University Paris Diderot, Sorbonne Paris Cite, Hopital Beaujon, Laboratory of Imaging Biomarkers, UMR1149 Inserm, Clichy (France); Hopitaux Universitaires de Geneve, Departement d' Imagerie et des Sciences de l' Information Medicale, Geneva (Switzerland)

    2017-05-15

    Changes in the expression of hepatocyte membrane transporters in advanced fibrosis decrease the hepatic transport function of organic anions. The aim of our study was to assess if these changes can be evaluated with pharmacokinetic analysis of the hepatobiliary transport of the MR contrast agent gadoxetate. Dynamic gadoxetate-enhanced MRI was performed in 17 rats with advanced fibrosis and 8 normal rats. After deconvolution, hepatocyte three-compartmental analysis was performed to calculate the hepatocyte influx, biliary efflux and sinusoidal backflux rates. The expression of Oatp1a1, Mrp2 and Mrp3 organic anion membrane transporters was assessed with reverse transcription polymerase chain reaction. In the rats with advanced fibrosis, the influx and efflux rates of gadoxetate decreased and the backflux rate increased significantly (p = 0.003, 0.041 and 0.010, respectively). Significant correlations were found between influx and Oatp1a1 expression (r = 0.78, p < 0.001), biliary efflux and Mrp2 (r = 0.50, p = 0.016) and sinusoidal backflux and Mrp3 (r = 0.61, p = 0.002). These results show that changes in the bidirectional organic anion hepatocyte transport function in rats with advanced liver fibrosis can be assessed with compartmental analysis of gadoxetate-enhanced MRI. (orig.)

  13. Gadoxetate-enhanced MR imaging and compartmental modelling to assess hepatocyte bidirectional transport function in rats with advanced liver fibrosis

    International Nuclear Information System (INIS)

    Giraudeau, Celine; Leporq, Benjamin; Doblas, Sabrina; Lagadec, Matthieu; Daire, Jean-Luc; Van Beers, Bernard E.; Pastor, Catherine M.

    2017-01-01

    Changes in the expression of hepatocyte membrane transporters in advanced fibrosis decrease the hepatic transport function of organic anions. The aim of our study was to assess if these changes can be evaluated with pharmacokinetic analysis of the hepatobiliary transport of the MR contrast agent gadoxetate. Dynamic gadoxetate-enhanced MRI was performed in 17 rats with advanced fibrosis and 8 normal rats. After deconvolution, hepatocyte three-compartmental analysis was performed to calculate the hepatocyte influx, biliary efflux and sinusoidal backflux rates. The expression of Oatp1a1, Mrp2 and Mrp3 organic anion membrane transporters was assessed with reverse transcription polymerase chain reaction. In the rats with advanced fibrosis, the influx and efflux rates of gadoxetate decreased and the backflux rate increased significantly (p = 0.003, 0.041 and 0.010, respectively). Significant correlations were found between influx and Oatp1a1 expression (r = 0.78, p < 0.001), biliary efflux and Mrp2 (r = 0.50, p = 0.016) and sinusoidal backflux and Mrp3 (r = 0.61, p = 0.002). These results show that changes in the bidirectional organic anion hepatocyte transport function in rats with advanced liver fibrosis can be assessed with compartmental analysis of gadoxetate-enhanced MRI. (orig.)

  14. Resistance to Antiangiogenic Therapies by Metabolic Symbiosis in Renal Cell Carcinoma PDX Models and Patients

    Directory of Open Access Journals (Sweden)

    Gabriela Jiménez-Valerio

    2016-05-01

    Full Text Available Antiangiogenic drugs are used clinically for treatment of renal cell carcinoma (RCC as a standard first-line treatment. Nevertheless, these agents primarily serve to stabilize disease, and resistance eventually develops concomitant with progression. Here, we implicate metabolic symbiosis between tumor cells distal and proximal to remaining vessels as a mechanism of resistance to antiangiogenic therapies in patient-derived RCC orthoxenograft (PDX models and in clinical samples. This metabolic patterning is regulated by the mTOR pathway, and its inhibition effectively blocks metabolic symbiosis in PDX models. Clinically, patients treated with antiangiogenics consistently present with histologic signatures of metabolic symbiosis that are exacerbated in resistant tumors. Furthermore, the mTOR pathway is also associated in clinical samples, and its inhibition eliminates symbiotic patterning in patient samples. Overall, these data support a mechanism of resistance to antiangiogenics involving metabolic compartmentalization of tumor cells that can be inhibited by mTOR-targeted drugs.

  15. PET-based compartmental modeling of {sup 124}I-A33 antibody: quantitative characterization of patient-specific tumor targeting in colorectal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Zanzonico, Pat; O' Donoghue, Joseph A.; Humm, John L. [Memorial Sloan Kettering Cancer Center, Department of Medical Physics, New York, NY (United States); Carrasquillo, Jorge A.; Pandit-Taskar, Neeta; Ruan, Shutian; Larson, Steven M. [Memorial Sloan Kettering Cancer Center, Department of Radiology, New York, NY (United States); Smith-Jones, Peter [Memorial Sloan Kettering Cancer Center, Department of Radiology, New York, NY (United States); Stony Brook School of Medicine, Departments of Psychiatry and Radiology, Stony Brook, NY (United States); Divgi, Chaitanya [Columbia University Medical Center, New York, NY (United States); Scott, Andrew M. [La Trobe University, Olivia Newton-John Cancer Research Institute, Melbourne (Australia); Kemeny, Nancy E.; Wong, Douglas; Scheinberg, David [Memorial Sloan Kettering Cancer Center, Department of Medicine, New York, NY (United States); Fong, Yuman [Memorial Sloan Kettering Cancer Center, Department of Surgery, New York, NY (United States); City of Hope, Department of Surgery, Duarte, CA (United States); Ritter, Gerd; Jungbluth, Achem; Old, Lloyd J. [Memorial Sloan Kettering Cancer Center, Ludwig Institute for Cancer Research, New York, NY (United States)

    2015-10-15

    The molecular specificity of monoclonal antibodies (mAbs) directed against tumor antigens has proven effective for targeted therapy of human cancers, as shown by a growing list of successful antibody-based drug products. We describe a novel, nonlinear compartmental model using PET-derived data to determine the ''best-fit'' parameters and model-derived quantities for optimizing biodistribution of intravenously injected {sup 124}I-labeled antitumor antibodies. As an example of this paradigm, quantitative image and kinetic analyses of anti-A33 humanized mAb (also known as ''A33'') were performed in 11 colorectal cancer patients. Serial whole-body PET scans of {sup 124}I-labeled A33 and blood samples were acquired and the resulting tissue time-activity data for each patient were fit to a nonlinear compartmental model using the SAAM II computer code. Excellent agreement was observed between fitted and measured parameters of tumor uptake, ''off-target'' uptake in bowel mucosa, blood clearance, tumor antigen levels, and percent antigen occupancy. This approach should be generally applicable to antibody-antigen systems in human tumors for which the masses of antigen-expressing tumor and of normal tissues can be estimated and for which antibody kinetics can be measured with PET. Ultimately, based on each patient's resulting ''best-fit'' nonlinear model, a patient-specific optimum mAb dose (in micromoles, for example) may be derived. (orig.)

  16. Radiotracers in the study of marine food chains. The use of compartmental analysis and analog modelling in measuring utilization rates of particulate organic matter by benthic invertebrates

    International Nuclear Information System (INIS)

    Gremare, A.; Amouroux, J.M.; Charles, F.

    1991-01-01

    The present study assesses the problem of recycling when using radiotracers to quantify ingestion and assimilation rates of particulate organic matter by benthic invertebrates. The rapid production of dissolved organic matter and its subsequent utilization by benthic invertebrates constitutes a major bias in this kind of study. However recycling processes may also concern POM through the production and reingestion of faeces. The present paper shows that compartmental analysis of the diffusion kinetics of the radiotracer between the different compartments of the system studied and the analog modelling of the exchanges of radioactivity between compartments may be used in order to determine ingestion and assimilation rates. This method is illustrated by the study of a system composed of the bacteria Lactobacillus sp. and the filter-feeding bivalve Venerupis decussata. The advantages and drawbacks of this approach relative to other existing methods are briefly discussed. (Author)

  17. Genome scale metabolic modeling of cancer

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Nielsen, Jens

    2017-01-01

    of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome......Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...

  18. Understanding the drug release mechanism from a montmorillonite matrix and its binary mixture with a hydrophilic polymer using a compartmental modelling approach

    Science.gov (United States)

    Choiri, S.; Ainurofiq, A.

    2018-03-01

    Drug release from a montmorillonite (MMT) matrix is a complex mechanism controlled by swelling mechanism of MMT and an interaction of drug and MMT. The aim of this research was to explain a suitable model of the drug release mechanism from MMT and its binary mixture with a hydrophilic polymer in the controlled release formulation based on a compartmental modelling approach. Theophylline was used as a drug model and incorporated into MMT and a binary mixture with hydroxyl propyl methyl cellulose (HPMC) as a hydrophilic polymer, by a kneading method. The dissolution test was performed and the modelling of drug release was assisted by a WinSAAM software. A 2 model was purposed based on the swelling capability and basal spacing of MMT compartments. The model evaluation was carried out to goodness of fit and statistical parameters and models were validated by a cross-validation technique. The drug release from MMT matrix regulated by a burst release mechanism of unloaded drug, swelling ability, basal spacing of MMT compartment, and equilibrium between basal spacing and swelling compartments. Furthermore, the addition of HPMC in MMT system altered the presence of swelling compartment and equilibrium between swelling and basal spacing compartment systems. In addition, a hydrophilic polymer reduced the burst release mechanism of unloaded drug.

  19. A Simple Plasma Retinol Isotope Ratio Method for Estimating β-Carotene Relative Bioefficacy in Humans: Validation with the Use of Model-Based Compartmental Analysis.

    Science.gov (United States)

    Ford, Jennifer Lynn; Green, Joanne Balmer; Lietz, Georg; Oxley, Anthony; Green, Michael H

    2017-09-01

    Background: Provitamin A carotenoids are an important source of dietary vitamin A for many populations. Thus, accurate and simple methods for estimating carotenoid bioefficacy are needed to evaluate the vitamin A value of test solutions and plant sources. β-Carotene bioefficacy is often estimated from the ratio of the areas under plasma isotope response curves after subjects ingest labeled β-carotene and a labeled retinyl acetate reference dose [isotope reference method (IRM)], but to our knowledge, the method has not yet been evaluated for accuracy. Objectives: Our objectives were to develop and test a physiologically based compartmental model that includes both absorptive and postabsorptive β-carotene bioconversion and to use the model to evaluate the accuracy of the IRM and a simple plasma retinol isotope ratio [(RIR), labeled β-carotene-derived retinol/labeled reference-dose-derived retinol in one plasma sample] for estimating relative bioefficacy. Methods: We used model-based compartmental analysis (Simulation, Analysis and Modeling software) to develop and apply a model that provided known values for β-carotene bioefficacy. Theoretical data for 10 subjects were generated by the model and used to determine bioefficacy by RIR and IRM; predictions were compared with known values. We also applied RIR and IRM to previously published data. Results: Plasma RIR accurately predicted β-carotene relative bioefficacy at 14 d or later. IRM also accurately predicted bioefficacy by 14 d, except that, when there was substantial postabsorptive bioconversion, IRM underestimated bioefficacy. Based on our model, 1-d predictions of relative bioefficacy include absorptive plus a portion of early postabsorptive conversion. Conclusion: The plasma RIR is a simple tracer method that accurately predicts β-carotene relative bioefficacy based on analysis of one blood sample obtained at ≥14 d after co-ingestion of labeled β-carotene and retinyl acetate. The method also provides

  20. Norepinephrine metabolism in humans. Kinetic analysis and model

    International Nuclear Information System (INIS)

    Linares, O.A.; Jacquez, J.A.; Zech, L.A.; Smith, M.J.; Sanfield, J.A.; Morrow, L.A.; Rosen, S.G.; Halter, J.B.

    1987-01-01

    The present study was undertaken to quantify more precisely and to begin to address the problem of heterogeneity of the kinetics of distribution and metabolism of norepinephrine (NE) in humans, by using compartmental analysis. Steady-state NE specific activity in arterialized plasma during [ 3 H]NE infusion and postinfusion plasma disappearance of [ 3 H]NE were measured in eight healthy subjects in the supine and upright positions. Two exponentials were clearly identified in the plasma [ 3 H]NE disappearance curves of each subject studied in the supine (r = 0.94-1.00, all P less than 0.01) and upright (r = 0.90-0.98, all P less than 0.01) positions. A two-compartment model was the minimal model necessary to simultaneously describe the kinetics of NE in the supine and upright positions. The NE input rate into the extravascular compartment 2, estimated with the minimal model, increased with upright posture (1.87 +/- 0.08 vs. 3.25 +/- 0.2 micrograms/min per m2, P less than 0.001). Upright posture was associated with a fall in the volume of distribution of NE in compartment 1 (7.5 +/- 0.6 vs. 4.7 +/- 0.3 liters, P less than 0.001), and as a result of that, there was a fall in the metabolic clearance rate of NE from compartment 1 (1.80 +/- 0.11 vs. 1.21 +/- 0.08 liters/min per m2, P less than 0.001). We conclude that a two-compartment model is the minimal model that can accurately describe the kinetics of distribution and metabolism of NE in humans

  1. Spectral Clustering Predicts Tumor Tissue Heterogeneity Using Dynamic 18F-FDG PET: A Complement to the Standard Compartmental Modeling Approach.

    Science.gov (United States)

    Katiyar, Prateek; Divine, Mathew R; Kohlhofer, Ursula; Quintanilla-Martinez, Leticia; Schölkopf, Bernhard; Pichler, Bernd J; Disselhorst, Jonathan A

    2017-04-01

    In this study, we described and validated an unsupervised segmentation algorithm for the assessment of tumor heterogeneity using dynamic 18 F-FDG PET. The aim of our study was to objectively evaluate the proposed method and make comparisons with compartmental modeling parametric maps and SUV segmentations using simulations of clinically relevant tumor tissue types. Methods: An irreversible 2-tissue-compartmental model was implemented to simulate clinical and preclinical 18 F-FDG PET time-activity curves using population-based arterial input functions (80 clinical and 12 preclinical) and the kinetic parameter values of 3 tumor tissue types. The simulated time-activity curves were corrupted with different levels of noise and used to calculate the tissue-type misclassification errors of spectral clustering (SC), parametric maps, and SUV segmentation. The utility of the inverse noise variance- and Laplacian score-derived frame weighting schemes before SC was also investigated. Finally, the SC scheme with the best results was tested on a dynamic 18 F-FDG measurement of a mouse bearing subcutaneous colon cancer and validated using histology. Results: In the preclinical setup, the inverse noise variance-weighted SC exhibited the lowest misclassification errors (8.09%-28.53%) at all noise levels in contrast to the Laplacian score-weighted SC (16.12%-31.23%), unweighted SC (25.73%-40.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%) segmentation. The classification efficacy of both weighted SC schemes in the clinical case was comparable to the unweighted SC. When applied to the dynamic 18 F-FDG measurement of colon cancer, the proposed algorithm accurately identified densely vascularized regions from the rest of the tumor. In addition, the segmented regions and clusterwise average time-activity curves showed excellent correlation with the tumor histology. Conclusion: The promising results of SC mark its position as a robust tool for quantification of tumor

  2. Modelling of the metabolism of Zymomonas mobilis

    Energy Technology Data Exchange (ETDEWEB)

    Posten, C; Thoma, M

    1986-01-01

    In order to optimize fermentations with respect to media, reactor configuration, and control a structured model of the metabolism of Zymononas mobilis has been developed. The model is based on structure of metabolism, rate limiting steps, energy balance and metabolic elemental balances. A three-fold effect of ethanol has been observed concerning substrate-turnover, ammonia uptake and energy consumption. In addition to the metabolic view a structured cell-membrane-model should be considered.

  3. Use of a "Super-child" Approach to Assess the Vitamin A Equivalence of Moringa oleifera Leaves, Develop a Compartmental Model for Vitamin A Kinetics, and Estimate Vitamin A Total Body Stores in Young Mexican Children.

    Science.gov (United States)

    Lopez-Teros, Veronica; Ford, Jennifer Lynn; Green, Michael H; Tang, Guangwen; Grusak, Michael A; Quihui-Cota, Luis; Muzhingi, Tawanda; Paz-Cassini, Mariela; Astiazaran-Garcia, Humberto

    2017-12-01

    Background: Worldwide, an estimated 250 million children children. Methods: β-Carotene was intrinsically labeled by growing MO plants in a 2 H 2 O nutrient solution. Fifteen well-nourished children (17-35 mo old) consumed puréed MO leaves (1 mg β-carotene) and a reference dose of [ 13 C 10 ]retinyl acetate (1 mg) in oil. Blood (2 samples/child) was collected 10 times (2 or 3 children each time) over 35 d. The bioefficacy of MO leaves was calculated from areas under the composite "super-child" plasma isotope response curves, and MO VA equivalence was estimated through the use of these values; a compartmental model was developed to predict VA TBS and retinol kinetics through the use of composite plasma [ 13 C 10 ]retinol data. TBS were also estimated with isotope dilution. Results: The relative bioefficacy of β-carotene retinol activity equivalents from MO was 28%; VA equivalence was 3.3:1 by weight (0.56 μmol retinol:1 μmol β-carotene). Kinetics of plasma retinol indicate more rapid plasma appearance and turnover and more extensive recycling in these children than are observed in adults. Model-predicted mean TBS (823 μmol) was similar to values predicted using a retinol isotope dilution equation applied to data from 3 to 6 d after dosing (mean ± SD: 832 ± 176 μmol; n = 7). Conclusions: The super-child approach can be used to estimate population carotenoid bioefficacy and VA equivalence, VA status, and parameters of retinol metabolism from a composite data set. Our results provide initial estimates of retinol kinetics in well-nourished young children with adequate VA stores and demonstrate that MO leaves may be an important source of VA. © 2017 American Society for Nutrition.

  4. In or out? On the tightness of glycosomal compartmentalization of metabolites and enzymes in Trypanosoma brucei

    NARCIS (Netherlands)

    Haanstra, Jurgen R.; Bakker, Barbara M.; Michels, Paul A. M.

    Trypanosomatids sequester large parts of glucose metabolism inside specialised peroxisomes, called glycosomes. Many studies have shown that correct glycosomal compartmentalization of glycolytic enzymes is essential for bloodstream-form Trypanosoma brucel. The recent finding of pore-forming

  5. A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

    NARCIS (Netherlands)

    Yamamoto, Yumi; Valitalo, Pyry A.; van den Berg, Dirk-Jan; Hartman, Robin; van den Brink, Willem; Wong, Yin Cheong; Huntjens, Dymphy R.; Proost, Johannes H.; Vermeulen, An; Krauwinkel, Walter; Bakshi, Suruchi; Aranzana-Climent, Vincent; Marchand, Sandrine; Dahyot-Fizelier, Claire; Couet, William; Danhof, Meindert; van Hasselt, Johan G. C.; de lange, Elizabeth C. M.

    Purpose Predicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human

  6. Compartmental modeling with nitrogen-15 to determine effects of degree of fat saturation on intraruminal N recycling.

    Science.gov (United States)

    Oldick, B S; Firkins, J L; Kohn, R A

    2000-09-01

    Two- and three-compartment models were developed to describe N kinetics within the rumen using three Holstein heifers and one nonlactating Holstein cow fitted with ruminal and duodenal cannulas. A 4 x 4 Latin square design included a control diet containing no supplemental fat and diets containing 4.85% of diet dry matter as partially hydrogenated tallow (iodine value = 13), tallow (iodine value = 51), or animal-vegetable fat (iodine value = 110). Effects of fat on intraruminal N recycling and relationships between intraruminal N recycling and ruminal protozoa concentration or the efficiency of microbial protein synthesis were determined. A pulse dose of 15(NH4)2SO4 was introduced into the ruminal NH3 N pool, and samples were taken over time from the ruminal NH3 N and nonammonia N pools. For the three-compartment model, precipitates of nonammonia N after trichloroacetic acid and ethanol extraction were defined as slowly turning over nonammonia N; rapidly turning over nonammonia N was determined by difference. Curves of 15N enrichment were fit to models with two (NH3 N and nonammonia N) or three (NH3 N, rapidly turning over nonammonia N, and slowly turning over nonammonia N) compartments using the software SAAM II. Because the three-compartment model did not remove a small systematic bias or improve the fit of the data, the two-compartment model was used to provide measurements of intraruminal N recycling. Intraruminal NH3 N recycling (45% for control) decreased linearly as fat unsaturation increased (50.2, 43.0, and 41.7% for partially hydrogenated tallow, tallow, and animal-vegetable fat, respectively). Intraruminal nitrogen recycling was not correlated with efficiency of microbial protein synthesis or ruminal protozoa counts.

  7. Network thermodynamic approach compartmental analysis. Na+ transients in frog skin.

    Science.gov (United States)

    Mikulecky, D C; Huf, E G; Thomas, S R

    1979-01-01

    We introduce a general network thermodynamic method for compartmental analysis which uses a compartmental model of sodium flows through frog skin as an illustrative example (Huf and Howell, 1974a). We use network thermodynamics (Mikulecky et al., 1977b) to formulate the problem, and a circuit simulation program (ASTEC 2, SPICE2, or PCAP) for computation. In this way, the compartment concentrations and net fluxes between compartments are readily obtained for a set of experimental conditions involving a square-wave pulse of labeled sodium at the outer surface of the skin. Qualitative features of the influx at the outer surface correlate very well with those observed for the short circuit current under another similar set of conditions by Morel and LeBlanc (1975). In related work, the compartmental model is used as a basis for simulation of the short circuit current and sodium flows simultaneously using a two-port network (Mikulecky et al., 1977a, and Mikulecky et al., A network thermodynamic model for short circuit current transients in frog skin. Manuscript in preparation; Gary-Bobo et al., 1978). The network approach lends itself to computation of classic compartmental problems in a simple manner using circuit simulation programs (Chua and Lin, 1975), and it further extends the compartmental models to more complicated situations involving coupled flows and non-linearities such as concentration dependencies, chemical reaction kinetics, etc.

  8. Genome-scale modeling for metabolic engineering.

    Science.gov (United States)

    Simeonidis, Evangelos; Price, Nathan D

    2015-03-01

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  9. Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

    Science.gov (United States)

    Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

    2014-01-01

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

  10. An optimization model for metabolic pathways.

    Science.gov (United States)

    Planes, F J; Beasley, J E

    2009-10-15

    Different mathematical methods have emerged in the post-genomic era to determine metabolic pathways. These methods can be divided into stoichiometric methods and path finding methods. In this paper we detail a novel optimization model, based upon integer linear programming, to determine metabolic pathways. Our model links reaction stoichiometry with path finding in a single approach. We test the ability of our model to determine 40 annotated Escherichia coli metabolic pathways. We show that our model is able to determine 36 of these 40 pathways in a computationally effective manner.

  11. Advanced compositional gradient and compartmentalization analysis

    Energy Technology Data Exchange (ETDEWEB)

    Canas, Jesus A.; Petti, Daniela; Mullins, Oliver [Schlumberger Servicos de Petroleo Ltda., Rio de Janeiro, RJ (Brazil)

    2008-07-01

    acting as compartmentalization elements. Using this method we present field DFA and pressure gradient data acquisitions and integrate into numerical simulation modeling to conceptually evaluate the impact of fluid composition / properties gradation and compartmentalization in the productivity of some reservoirs. (author)

  12. Drivers of compartmentalization in a Mediterranean pollination network

    DEFF Research Database (Denmark)

    Gonzalez, Ana M. Martin; Allesina, Stefano; Rodrigo, Anselm

    2012-01-01

    We study compartmentalization in a Mediterranean pollination network using three different analytical approaches: unipartite modularity (UM), bipartite modularity (BM) and the group model (GM). Our objectives are to compare compartments obtained with these three approaches and to explore the role...... of several species attributes related to pollination syndromes, species phenology, abundance and connectivity in structuring compartmentalization. BM could not identify compartments in our network. By contrast, UM revealed four modules composed of plants and pollinators, and GM four groups of plants and five...... of pollinators. Phenology had a major influence on compartmentalization, and compartments (both UM and GM) had distinct phenophases. Compartments were also strongly characterized by species degree (number of connections) and betweenness centrality. These two attributes were highly related to each other...

  13. Cancer Metabolism: A Modeling Perspective

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Nielsen, Jens

    2015-01-01

    suggest that utilization of amino acids and lipids contributes significantly to cancer cell metabolism. Also recent progresses in our understanding of carcinogenesis have revealed that cancer is a complex disease and cannot be understood through simple investigation of genetic mutations of cancerous cells...

  14. Ensemble Kinetic Modeling of Metabolic Networks from Dynamic Metabolic Profiles

    Directory of Open Access Journals (Sweden)

    Gengjie Jia

    2012-11-01

    Full Text Available Kinetic modeling of metabolic pathways has important applications in metabolic engineering, but significant challenges still remain. The difficulties faced vary from finding best-fit parameters in a highly multidimensional search space to incomplete parameter identifiability. To meet some of these challenges, an ensemble modeling method is developed for characterizing a subset of kinetic parameters that give statistically equivalent goodness-of-fit to time series concentration data. The method is based on the incremental identification approach, where the parameter estimation is done in a step-wise manner. Numerical efficacy is achieved by reducing the dimensionality of parameter space and using efficient random parameter exploration algorithms. The shift toward using model ensembles, instead of the traditional “best-fit” models, is necessary to directly account for model uncertainty during the application of such models. The performance of the ensemble modeling approach has been demonstrated in the modeling of a generic branched pathway and the trehalose pathway in Saccharomyces cerevisiae using generalized mass action (GMA kinetics.

  15. A new approach to the compartmental analysis in pharmacokinetics: fractional time evolution of diclofenac.

    Science.gov (United States)

    Popović, Jovan K; Atanacković, Milica T; Pilipović, Ana S; Rapaić, Milan R; Pilipović, Stevan; Atanacković, Teodor M

    2010-04-01

    This study presents a new two compartmental model and its application to the evaluation of diclofenac pharmacokinetics in a small number of healthy adults, during a bioequivalence trial. In the model the integer order derivatives are replaced by derivatives of real order often called fractional order derivatives. Physically that means that a history (memory) of a biological process, realized as a transfer from one compartment to another one with the mass balance conservation, is taken into account. This kind of investigations in pharmacokinetics is founded by Dokoumetzidis and Macheras through the one compartmental models while our contribution is the analysis of multi-dimensional compartmental models with the applications of the two compartmental model in evaluation of diclofenac pharmacokinetics. Two experiments were preformed with 12 healthy volunteers with two slow release 100 mg diclofenac tablet formulations. The agreement of the values predicted by the proposed model with the values obtained through experiments is shown to be good. Thus, pharmacokinetics of slow release diclofenac can be described well by a specific two compartmental model with fractional derivatives of the same order. Parameters in the model are determined by the least-squares method and the Particle Swarm Optimization (PSO) numerical procedure is used. The results show that the fractional order two compartmental model for diclofenac is superior in comparison to the classical two compartmental model. Actually this is true in general case since the classical one is a special case of the fractional one.

  16. Computational model of cellular metabolic dynamics

    DEFF Research Database (Denmark)

    Li, Yanjun; Solomon, Thomas; Haus, Jacob M

    2010-01-01

    of the cytosol and mitochondria. The model simulated skeletal muscle metabolic responses to insulin corresponding to human hyperinsulinemic-euglycemic clamp studies. Insulin-mediated rate of glucose disposal was the primary model input. For model validation, simulations were compared with experimental data......: intracellular metabolite concentrations and patterns of glucose disposal. Model variations were simulated to investigate three alternative mechanisms to explain insulin enhancements: Model 1 (M.1), simple mass action; M.2, insulin-mediated activation of key metabolic enzymes (i.e., hexokinase, glycogen synthase......, by application of mechanism M.3, the model predicts metabolite concentration changes and glucose partitioning patterns consistent with experimental data. The reaction rate fluxes quantified by this detailed model of insulin/glucose metabolism provide information that can be used to evaluate the development...

  17. Probiotic modulation of symbiotic gut microbial-host metabolic interactions in a humanized microbiome mouse model

    NARCIS (Netherlands)

    Martin, F.P.J.; Wang, Y.; Sprenger, N.; Yap, K.S.; Rezzi, S.; Ramadan, Z.; Peré-Trepat, E.; Rochat, F.; Cherbut, C.; Bladeren, van P.J.; Fay, L.B.; Kochhar, S.; LindOn, J.C.; Holmes, E.; Nicholson, J.K.

    2008-01-01

    The transgenomic metabolic effects of exposure to either Lactobacillus paracasei or Lactobacillus rhamnosus probiotics have been measured and mapped in humanized extended genome mice (germ-free mice colonized with human baby flora). Statistical analysis of the compartmental fluctuations in diverse

  18. Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis

    Directory of Open Access Journals (Sweden)

    Balagurunathan Balaji

    2012-02-01

    Full Text Available Abstract Background Fermentation of xylose, the major component in hemicellulose, is essential for economic conversion of lignocellulosic biomass to fuels and chemicals. The yeast Scheffersomyces stipitis (formerly known as Pichia stipitis has the highest known native capacity for xylose fermentation and possesses several genes for lignocellulose bioconversion in its genome. Understanding the metabolism of this yeast at a global scale, by reconstructing the genome scale metabolic model, is essential for manipulating its metabolic capabilities and for successful transfer of its capabilities to other industrial microbes. Results We present a genome-scale metabolic model for Scheffersomyces stipitis, a native xylose utilizing yeast. The model was reconstructed based on genome sequence annotation, detailed experimental investigation and known yeast physiology. Macromolecular composition of Scheffersomyces stipitis biomass was estimated experimentally and its ability to grow on different carbon, nitrogen, sulphur and phosphorus sources was determined by phenotype microarrays. The compartmentalized model, developed based on an iterative procedure, accounted for 814 genes, 1371 reactions, and 971 metabolites. In silico computed growth rates were compared with high-throughput phenotyping data and the model could predict the qualitative outcomes in 74% of substrates investigated. Model simulations were used to identify the biosynthetic requirements for anaerobic growth of Scheffersomyces stipitis on glucose and the results were validated with published literature. The bottlenecks in Scheffersomyces stipitis metabolic network for xylose uptake and nucleotide cofactor recycling were identified by in silico flux variability analysis. The scope of the model in enhancing the mechanistic understanding of microbial metabolism is demonstrated by identifying a mechanism for mitochondrial respiration and oxidative phosphorylation. Conclusion The genome

  19. Computational Modeling of Lipid Metabolism in Yeast

    Directory of Open Access Journals (Sweden)

    Vera Schützhold

    2016-09-01

    Full Text Available Lipid metabolism is essential for all major cell functions and has recently gained increasing attention in research and health studies. However, mathematical modeling by means of classical approaches such as stoichiometric networks and ordinary differential equation systems has not yet provided satisfactory insights, due to the complexity of lipid metabolism characterized by many different species with only slight differences and by promiscuous multifunctional enzymes.Here, we present a object-oriented stochastic model approach as a way to cope with the complex lipid metabolic network. While all lipid species are treated objects in the model, they can be modified by the respective converting reactions based on reaction rules, a hybrid method that integrates benefits of agent-based and classical stochastic simulation. This approach allows to follow the dynamics of all lipid species with different fatty acids, different degrees of saturation and different headgroups over time and to analyze the effect of parameter changes, potential mutations in the catalyzing enzymes or provision of different precursors. Applied to yeast metabolism during one cell cycle period, we could analyze the distribution of all lipids to the various membranes in time-dependent manner.The presented approach allows to efficiently treat the complexity of cellular lipid metabolism and to derive conclusions on the time- and location-dependent distributions of lipid species and their properties such as saturation. It is widely applicable, easily extendable and will provide further insights in healthy and diseased states of cell metabolism.

  20. Rodent Models for Metabolic Syndrome Research

    Directory of Open Access Journals (Sweden)

    Sunil K. Panchal

    2011-01-01

    Full Text Available Rodents are widely used to mimic human diseases to improve understanding of the causes and progression of disease symptoms and to test potential therapeutic interventions. Chronic diseases such as obesity, diabetes and hypertension, together known as the metabolic syndrome, are causing increasing morbidity and mortality. To control these diseases, research in rodent models that closely mimic the changes in humans is essential. This review will examine the adequacy of the many rodent models of metabolic syndrome to mimic the causes and progression of the disease in humans. The primary criterion will be whether a rodent model initiates all of the signs, especially obesity, diabetes, hypertension and dysfunction of the heart, blood vessels, liver and kidney, primarily by diet since these are the diet-induced signs in humans with metabolic syndrome. We conclude that the model that comes closest to fulfilling this criterion is the high carbohydrate, high fat-fed male rodent.

  1. Protocell design through modular compartmentalization.

    Science.gov (United States)

    Miller, David; Booth, Paula J; Seddon, John M; Templer, Richard H; Law, Robert V; Woscholski, Rudiger; Ces, Oscar; Barter, Laura M C

    2013-10-06

    De novo synthetic biological design has the potential to significantly impact upon applications such as energy generation and nanofabrication. Current designs for constructing organisms from component parts are typically limited in scope, as they utilize a cut-and-paste ideology to create simple stepwise engineered protein-signalling pathways. We propose the addition of a new design element that segregates components into lipid-bound 'proto-organelles', which are interfaced with response elements and housed within a synthetic protocell. This design is inspired by living cells, which utilize multiple types of signalling molecules to facilitate communication between isolated compartments. This paper presents our design and validation of the components required for a simple multi-compartment protocell machine, for coupling a light transducer to a gene expression system. This represents a general design concept for the compartmentalization of different types of artificial cellular machinery and the utilization of non-protein signal molecules for signal transduction.

  2. Metabolic engineering tools in model cyanobacteria.

    Science.gov (United States)

    Carroll, Austin L; Case, Anna E; Zhang, Angela; Atsumi, Shota

    2018-03-26

    Developing sustainable routes for producing chemicals and fuels is one of the most important challenges in metabolic engineering. Photoautotrophic hosts are particularly attractive because of their potential to utilize light as an energy source and CO 2 as a carbon substrate through photosynthesis. Cyanobacteria are unicellular organisms capable of photosynthesis and CO 2 fixation. While engineering in heterotrophs, such as Escherichia coli, has result in a plethora of tools for strain development and hosts capable of producing valuable chemicals efficiently, these techniques are not always directly transferable to cyanobacteria. However, recent efforts have led to an increase in the scope and scale of chemicals that cyanobacteria can produce. Adaptations of important metabolic engineering tools have also been optimized to function in photoautotrophic hosts, which include Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9, 13 C Metabolic Flux Analysis (MFA), and Genome-Scale Modeling (GSM). This review explores innovations in cyanobacterial metabolic engineering, and highlights how photoautotrophic metabolism has shaped their development. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  3. Calcium metabolism in the rat: A temporal self-organized model

    International Nuclear Information System (INIS)

    Staub, J.F.; Tracqui, P.; Brezillon, P.; Milhaud, G.; Perault-Staub, A.M.

    1988-01-01

    Based on consideration of rat plasma Ca and 45 Ca concentrations, the authors analyze the circadian behavior of Ca metabolism of the rat as the temporal expression of a self-organized system. They present a self-oscillatory model M for rat Ca metabolism based on a compartmental formalism, which includes a second-order autocatalytic process. M describes the entire mass of Ca as made up of eight compartments and predicts a distinction between (1) the amount of Ca deposited in zones of rapid bone growth and reutilized during bone maturation and (2) the amount of Ca in mature bone subdivided into four compartments. Two of these compartments, largely self-oscillating, may represent Ca-P associations at bone liquid/solid interface and are subject to osteoblast-osteocyte control. The other two compartments can be thought of as made up of a large expanding pool of hydroxyapatite (HA) crystals, which are largely unavailable as such, and a small pool of more available HA crystals. Bone Ca influx and rhythmic efflux play a major role in the regulation of Ca in extracellular fluid but must be dissociated from bone accretion and resorption. Application to Ca deficiency was analyzed. Conceptual consequences of the connection of Ca metabolism to a self-regulated system are discussed

  4. Neuro-fuzzy model of homocysteine metabolism

    Indian Academy of Sciences (India)

    In view of well-documented association of hyperhomocysteinaemia with a wide spectrum of diseases and higher incidence of vitamin deficiencies in Indians, we proposed a mathematical model to forecast the role of demographic and geneticvariables in influencing homocysteine metabolism and investigated the influence ...

  5. A Novel Method for Performance Analysis of Compartmentalized Reservoirs

    Directory of Open Access Journals (Sweden)

    Shahamat Mohammad Sadeq

    2016-05-01

    Full Text Available This paper presents a simple analytical model for performance analysis of compartmentalized reservoirs producing under Constant Terminal Rate (CTR and Constant Terminal Pressure (CTP. The model is based on the well-known material balance and boundary dominated flow equations and is written in terms of capacitance and resistance of a production and a support compartment. These capacitance and resistance terms account for a combination of reservoir parameters which enable the developed model to be used for characterizing such systems. In addition to considering the properties contrast between the two reservoir compartments, the model takes into account existence of transmissibility barriers with the use of resistance terms. The model is used to analyze production performance of unconventional reservoirs, where the multistage fracturing of horizontal wells effectively creates a Stimulated Reservoir Volume (SRV with an enhanced permeability surrounded by a non-stimulated region. It can also be used for analysis of compartmentalized conventional reservoirs. The analytical solutions provide type curves through which the controlling reservoirs parameters of a compartmentalized system can be estimated. The contribution of the supporting compartment is modeled based on a boundary dominated flow assumption. The transient behaviour of the support compartment is captured by application of “distance of investigation” concept. The model shows that depletion of the production and support compartments exhibit two unit slopes on a log-log plot of pressure versus time for CTR. For CTP, however, the depletions display two exponential declines. The depletion signatures are separated by transition periods, which depend on the contribution of the support compartment (i.e. transient or boundary dominated flow. The developed equations can be implemented easily in a spreadsheet application, and are corroborated with the use of a numerical simulation. The study

  6. Modeling of Zymomonas mobilis central metabolism for novel metabolic engineering strategies.

    Science.gov (United States)

    Kalnenieks, Uldis; Pentjuss, Agris; Rutkis, Reinis; Stalidzans, Egils; Fell, David A

    2014-01-01

    Mathematical modeling of metabolism is essential for rational metabolic engineering. The present work focuses on several types of modeling approach to quantitative understanding of central metabolic network and energetics in the bioethanol-producing bacterium Zymomonas mobilis. Combined use of Flux Balance, Elementary Flux Mode, and thermodynamic analysis of its central metabolism, together with dynamic modeling of the core catabolic pathways, can help to design novel substrate and product pathways by systematically analyzing the solution space for metabolic engineering, and yields insights into the function of metabolic network, hardly achievable without applying modeling tools.

  7. Network thermodynamic curation of human and yeast genome-scale metabolic models.

    Science.gov (United States)

    Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

    2014-07-15

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  8. Alkaline earth metabolism: the ICRP model reformulated as a semi-Markov model

    International Nuclear Information System (INIS)

    Marcus, A.H.; Becker, A.

    1980-01-01

    Compartmental models are reformulated so as to allow power function or mixed exponential-power function residence time distributions in bone compartments. Numerical results reported for retention functions of calcium, strontium, barium and radium are in reasonable agreement with the ICRP models except at shorter time scales. The number of visits to bone is also sensitive to short-term elimination parameters, so that recycling corrections may require much more detailed analyses at both long and short time-scales. (author)

  9. Lyophilized kits of diamino dithiol compounds for labelling with {sup 99m}-technetium. Pharmacokinetics studies and distribution compartmental models of the related complexes; Conjuntos de reativos liofilizados de compostos diaminoditiolicos para marcacao com tecnecio-99m. Estudo farmacocinetico e elaboracao de modelos compartimentalizados dos respectivos complexos

    Energy Technology Data Exchange (ETDEWEB)

    Araujo, Elaine Bortoleti de

    1995-07-01

    for enough period, permitting the acquisition of scintigraphic cerebral images. The cerebral retention of the complex, and also its relative fast elimination are related to the metabolization of the compound to more polar species, identified in the urine and bile HPLC. The lipophilicity of the complex determine high liver uptake and intestinal elimination of the compound. Biological distribution of the complex {sup 99m}Tc-L.L-ECD was adjusted to a compartmental distribution model composed by seven compartments, characterized by a fast blood clearance, an unidirectional renal depuration and intestinal elimination, determined by intense hepato-biliary transit. (author)

  10. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    Science.gov (United States)

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. © 2016 American Society of Plant Biologists. All rights reserved.

  11. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

    Science.gov (United States)

    Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

    2016-01-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  12. Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach

    Energy Technology Data Exchange (ETDEWEB)

    Liao, James C. [Univ. of California, Los Angeles, CA (United States)

    2016-10-01

    Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.

  13. Relationship Between Kinetics of Inflow and Outflow as the Basis of a Computer Simulation for Solving Compartmental Models: Example of Electrolyte Transfers in Cardiovascular Tissues

    Energy Technology Data Exchange (ETDEWEB)

    Llaurado, J. G. [Biomedical Engineering Group, Marquette University (United States); Marquette School of Medicine, Milwaukee (United States); Nuclear Medicine Service of Veterans Administration Center, Wood, WI (United States)

    1971-02-15

    A method commonly used for the study of the distribution of a substance among the different spaces ol a biological tissue is the continuous washout (outflow) and isotope counting of fragments of tissue previously incubated with a tracer. A first order kinetics compartmental system can be postulated and characterized by the transport rates (k) at which the substance of interest moves across its different compartments. Direct solution from the outflow data requires knowledge of the initial conditions for, or to have access for measurements in, each compartment. This cannot be fulfilled in most biological problems. In the course of studying {sup 22}Na distribution in segments of arteries a digital computer simulation approach was developed to solve the system. In the belief that the approach transcends this particular application, its mathematical basis is herein presented: the movement of radioactive tracer obeys Divides dq/d Divides = - Divides k Divides Divides q Divides + Divides r Divides (1) where |q| is a vector of response functions for each compartment, |k] is a square matrix of transport rate constants and |r| is a vector of input rates to the system. Solution of Eq. 1 is Divides q Divides = e{sup - Divides k Divides t} {integral}{sub 0}{sup t} e{sup Divides k Divides t} Divides r Divides dt + e{sup - Divides k Divides t} Divides q{sub 0} Divides (2) (i) For an inflow experiment, with 0 initial conditions and a constant unit input rate |r{sub u}| Divides q Divides = ( Divides I Divides - e{sup - Divides k Divides t}) Divides k Divides {sup -1} Divides r{sub u} Divides (3) as t --> {infinity}, Divides q{sub {infinity}} Divides = Divides k Divides {sup -1} Divides r{sub u} Divides , which replaced in Eq. 3, Divides q Divides = Divides q{sub {infinity}} Divides -e{sup - Divides k Divides t} Divides q{sub {infinity}} Divides (4) (ii) For an outflow experiment Divides r Divides = 0 and Eq. 2 becomes Divides q Divides = e{sup - Divides k Divides t} Divides q{sub 0

  14. Compartmentalized storage tank for electrochemical cell system

    Science.gov (United States)

    Piecuch, Benjamin Michael (Inventor); Dalton, Luke Thomas (Inventor)

    2010-01-01

    A compartmentalized storage tank is disclosed. The compartmentalized storage tank includes a housing, a first fluid storage section disposed within the housing, a second fluid storage section disposed within the housing, the first and second fluid storage sections being separated by a movable divider, and a constant force spring. The constant force spring is disposed between the housing and the movable divider to exert a constant force on the movable divider to cause a pressure P1 in the first fluid storage section to be greater than a pressure P2 in the second fluid storage section, thereby defining a pressure differential.

  15. Three-compartmental analysis of effects of D-propranolol on thyroid hormone kinetics

    International Nuclear Information System (INIS)

    Van Der Heijden, J.T.M.; Krenning, E.P.; Van Toor, H.; Hennemann, G.; Docter, R.

    1988-01-01

    Tracer thyroxine (T 4 ), 3,3',5-triiodothyronine (T 3 ), and 3,3',5'-triiodothyronine (rT 3 ) kinetic studies were performed in normal T 4 substituted subjects before and during oral D-propranolol treatment to determine whether changes in thyroid hormone metabolism in a propranolol-induced low-T 3 syndrome result from inhibition of 5'-deiodination or inhibition of transport of iodothyronines into tissues. Data were analyzed according to a three-compartmental model of distribution and metabolism. No changes were observed in size of the three T 4 compartments or in fractional and mass transfer rates of T 4 from plasma to the rapidly (REP) and slowly (SEP) equilibrating pools. Serum T 3 , free T 3 , T 3 plasma pool, T 3 mass transfer rate to REP and SEP, and the T 3 pool masses were all significantly decreased during propranolol to a similar extent as the T 3 plasma production rate (PR). It is concluded that the D-propranolol-induced changes in thyroid hormone metabolism, resulting in a low-T 3 syndrome, are due to inhibition of thyroid hormone deiodination. This is in contrast to the low-T 3 syndrome during caloric deprivation, which results from inhibition of transport of iodothyronines into the liver

  16. Applications of computational modeling in metabolic engineering of yeast

    DEFF Research Database (Denmark)

    Kerkhoven, Eduard J.; Lahtvee, Petri-Jaan; Nielsen, Jens

    2015-01-01

    a preferred flux distribution. These methods point to strategies for altering gene expression; however, fluxes are often controlled by post-transcriptional events. Moreover, GEMs are usually not taking into account metabolic regulation, thermodynamics and enzyme kinetics. To facilitate metabolic engineering......, it is necessary to expand the modeling of metabolism to consider kinetics of individual processes. This review will give an overview about models available for metabolic engineering of yeast and discusses their applications....

  17. Pharmacokinetic models relevant to toxicity and metabolism for uranium in humans and animals

    International Nuclear Information System (INIS)

    Wrenn, M.E.

    1989-01-01

    Models to predict short and long term accumulation of uranium in the human kidney are reviewed and summarised. These are generally first order linear compartmental models or pseudo-pharmacokinetic models such as the retention model of the ICRP. Pharmacokinetic models account not only for transfer from blood to organs, but also recirculation from the organ to blood. The most recent information on mammalian and human metabolism of uranium is used to establish a revised model. The model is applied to the short term accumulation of uranium in the human kidney after a single rapid dosage to the blood, such as that obtained by inhaling UF6 or its hydrolysis products. It is shown that the maximum accumulation in the kidney under these conditions is less than the fraction of the material distributed from the blood to kidney if a true pharmacokinetic model is used. The best coefficients applicable to man in the authors' view are summarised in model V. For a half-time of two days in the mammalian kidney, the maximum concentration in kidney is 75% of that predicted by a retention model such as that used by the ICRP following a single acute intake. We conclude that one must use true pharmacokinetic models, which incorporate recirculation from the organs to the blood, in order to realistically predict time dependent uptake in the kidneys and other organs. Information is presented showing that the half-time for urinary excretion of soluble uranium in man after inhalation of UF6 is about one quarter of a day. (author)

  18. Kinetic modeling of cell metabolism for microbial production.

    Science.gov (United States)

    Costa, Rafael S; Hartmann, Andras; Vinga, Susana

    2016-02-10

    Kinetic models of cellular metabolism are important tools for the rational design of metabolic engineering strategies and to explain properties of complex biological systems. The recent developments in high-throughput experimental data are leading to new computational approaches for building kinetic models of metabolism. Herein, we briefly survey the available databases, standards and software tools that can be applied for kinetic models of metabolism. In addition, we give an overview about recently developed ordinary differential equations (ODE)-based kinetic models of metabolism and some of the main applications of such models are illustrated in guiding metabolic engineering design. Finally, we review the kinetic modeling approaches of large-scale networks that are emerging, discussing their main advantages, challenges and limitations. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling

    International Nuclear Information System (INIS)

    Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong; Nelson, David R.; Jijakli, Kenan; Salehi-Ashtiani, Kourosh

    2014-01-01

    Metabolic modeling provides the means to define metabolic processes at a systems level; however, genome-scale metabolic models often remain incomplete in their description of metabolic networks and may include reactions that are experimentally unverified. This shortcoming is exacerbated in reconstructed models of newly isolated algal species, as there may be little to no biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology (Biolog, Hayward, CA, USA) provides an efficient, high-throughput method to functionally define cellular metabolic activities in response to a large array of entry metabolites. The platform can experimentally verify many of the unverified reactions in a network model as well as identify missing or new reactions in the reconstructed metabolic model. The PM technology has been used for metabolic phenotyping of non-photosynthetic bacteria and fungi, but it has not been reported for the phenotyping of microalgae. Here, we introduce the use of PM assays in a systematic way to the study of microalgae, applying it specifically to the green microalgal model species Chlamydomonas reinhardtii. The results obtained in this study validate a number of existing annotated metabolic reactions and identify a number of novel and unexpected metabolites. The obtained information was used to expand and refine the existing COBRA-based C. reinhardtii metabolic network model iRC1080. Over 254 reactions were added to the network, and the effects of these additions on flux distribution within the network are described. The novel reactions include the support of metabolism by a number of d-amino acids, l-dipeptides, and l-tripeptides as nitrogen sources, as well as support of cellular respiration by cysteamine-S-phosphate as a phosphorus source. The protocol developed here can be used as a foundation to functionally profile other microalgae such as known microalgae mutants and novel isolates.

  20. Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling

    Energy Technology Data Exchange (ETDEWEB)

    Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong; Nelson, David R. [Division of Science and Math, New York University Abu Dhabi, Abu Dhabi (United Arab Emirates); Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi Institute, Abu Dhabi (United Arab Emirates); Jijakli, Kenan [Division of Science and Math, New York University Abu Dhabi, Abu Dhabi (United Arab Emirates); Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi Institute, Abu Dhabi (United Arab Emirates); Engineering Division, Biofinery, Manhattan, KS (United States); Salehi-Ashtiani, Kourosh, E-mail: ksa3@nyu.edu [Division of Science and Math, New York University Abu Dhabi, Abu Dhabi (United Arab Emirates); Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi Institute, Abu Dhabi (United Arab Emirates)

    2014-12-10

    Metabolic modeling provides the means to define metabolic processes at a systems level; however, genome-scale metabolic models often remain incomplete in their description of metabolic networks and may include reactions that are experimentally unverified. This shortcoming is exacerbated in reconstructed models of newly isolated algal species, as there may be little to no biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology (Biolog, Hayward, CA, USA) provides an efficient, high-throughput method to functionally define cellular metabolic activities in response to a large array of entry metabolites. The platform can experimentally verify many of the unverified reactions in a network model as well as identify missing or new reactions in the reconstructed metabolic model. The PM technology has been used for metabolic phenotyping of non-photosynthetic bacteria and fungi, but it has not been reported for the phenotyping of microalgae. Here, we introduce the use of PM assays in a systematic way to the study of microalgae, applying it specifically to the green microalgal model species Chlamydomonas reinhardtii. The results obtained in this study validate a number of existing annotated metabolic reactions and identify a number of novel and unexpected metabolites. The obtained information was used to expand and refine the existing COBRA-based C. reinhardtii metabolic network model iRC1080. Over 254 reactions were added to the network, and the effects of these additions on flux distribution within the network are described. The novel reactions include the support of metabolism by a number of d-amino acids, l-dipeptides, and l-tripeptides as nitrogen sources, as well as support of cellular respiration by cysteamine-S-phosphate as a phosphorus source. The protocol developed here can be used as a foundation to functionally profile other microalgae such as known microalgae mutants and novel isolates.

  1. Kinetic Analysis of 2-[11C]Thymidine PET Imaging Studies of Malignant Brain Tumors: Compartmental Model Investigation and Mathematical Analysis

    Directory of Open Access Journals (Sweden)

    Joanne M. Wells

    2002-07-01

    Full Text Available 2-[11C]Thymidine (TdR, a PET tracer for cellular proliferation, may be advantageous for monitoring brain tumor progression and response to therapy. We previously described and validated a five-compartment model for thymidine incorporation into DNA in somatic tissues, but the effect of the blood–brain barrier on the transport of TdR and its metabolites necessitated further validation before it could be applied to brain tumors. Methods: We investigated the behavior of the model under conditions experienced in the normal brain and brain tumors, performed sensitivity and identifiability analysis to determine the ability of the model to estimate the model parameters, and conducted simulations to determine whether it can distinguish between thymidine transport and retention. Results: Sensitivity and identifiability analysis suggested that the non-CO2 metabolite parameters could be fixed without significantly affecting thymidine parameter estimation. Simulations showed that K1t and KTdR could be estimated accurately (r = .97 and .98 for estimated vs. true parameters with standard errors < 15%. The model was able to separate increased transport from increased retention associated with tumor proliferation. Conclusion: Our model adequately describes normal brain and brain tumor kinetics for thymidine and its metabolites, and it can provide an estimate of the rate of cellular proliferation in brain tumors.

  2. Photoperiodism and enzyme activity: towards a model for the control of circadian metabolic rhythms in the crassulacean Acid metabolism.

    Science.gov (United States)

    Queiroz, O; Morel, C

    1974-04-01

    Metabolic readjustments after a change from long days to short days appear, in Kalanchoe blossfeldiana, to be achieved through the operation of two main mechanisms: variation in enzyme capacity, and circadian rhythmicity. After a lag time, capacity in phosphoenolpyruvate carboxylase and capacity in aspartate aminotransferase increase exponentially and appear to be allometrically linked during 50 to 60 short days; then a sudden fall takes place in the activity of the former. Malic enzyme and alanine aminotransferase behave differently. Thus, the operation of the two sections of the pathway (before and after the malate step) give rise to a continuously changing functional compartmentation in the pathway. Circadian rhythmicity, on the other hand, produces time compartmentation through phase shifts and variation in amplitude, independently for each enzyme. These characteristics suggest that the operation of a so-called biological clock would be involved. We propose the hypothesis that feedback regulation would be more accurate and efficient when applied to an already oscillating, clock-controlled enzyme system.

  3. The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism

    DEFF Research Database (Denmark)

    Birkel, Garrett W.; Ghosh, Amit; Kumar, Vinay S.

    2017-01-01

    analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics, proteomics and metabolomics) are urgently needed.Results: The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes......, it introduces the capability to use C-13 labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale C-13 Metabolic Flux Analysis (2S-C-13 MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable...... insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs.Conclusions: jQMM will facilitate the design...

  4. Metabolic dynamics in skeletal muscle during acute reduction in blood flow and oxygen supply to mitochondria: in-silico studies using a multi-scale, top-down integrated model.

    Science.gov (United States)

    Dash, Ranjan K; Li, Yanjun; Kim, Jaeyeon; Beard, Daniel A; Saidel, Gerald M; Cabrera, Marco E

    2008-09-09

    Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD(+). The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and

  5. Compartmental analysis and dosimetric aspects applied to cholesterol with 3H labeled

    International Nuclear Information System (INIS)

    Oliveira, Adriano dos Santos

    2015-01-01

    Cardiovascular diseases (CVDs) are one of the major reasons of death around the world according to the World Health Organization (WHO). It is well known that changes in levels of plasma lipoproteins, which are responsible for the transport of cholesterol into the bloodstream, are associated with cardiovascular diseases. For this reason to know the biokinetic parameters of plasma lipoproteins and quantifies them is important to correct and deep understanding about the diseases associated with these disorders. The main aim of this study is to provide a biokinetic model and estimate the radiometric doses for 3 H-Cholesterol, a radioactive tracer widely used in physiological and metabolic studies. The model was based on [Schwartz et al. 2004] about the distribution of cholesterol by the lipoprotein and gastrointestinal model [ICRP 30, 1979]. The doses distribution in compartments of the model and other organs and tissues of a standard adult described in [ICRP 106, 2008] was calculated using MIRD method (Medical Internal Radiation Dose) and compartmental analysis using the computer program Matlab®. The dose coefficients were estimated for a standard phantom man (73 kg) described in [ICRP 60, 1991]. The estimated doses for both model and for other organs were low and did not exceed the highest dose obtained that was in the upper large intestine, as 44,8 μGy these parameters will assist in ethics committee's opinions on the use of works that use the 3 H-cholesterol which radioactive tracer. (author)

  6. Integrative Analysis of Metabolic Models – from Structure to Dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de [Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben (Germany); Schreiber, Falk [Monash University, Melbourne, VIC (Australia); Martin-Luther-University Halle-Wittenberg, Halle (Germany)

    2015-01-26

    The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the context of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.

  7. Improving Bioenergy Crops through Dynamic Metabolic Modeling

    Directory of Open Access Journals (Sweden)

    Mojdeh Faraji

    2017-10-01

    Full Text Available Enormous advances in genetics and metabolic engineering have made it possible, in principle, to create new plants and crops with improved yield through targeted molecular alterations. However, while the potential is beyond doubt, the actual implementation of envisioned new strains is often difficult, due to the diverse and complex nature of plants. Indeed, the intrinsic complexity of plants makes intuitive predictions difficult and often unreliable. The hope for overcoming this challenge is that methods of data mining and computational systems biology may become powerful enough that they could serve as beneficial tools for guiding future experimentation. In the first part of this article, we review the complexities of plants, as well as some of the mathematical and computational methods that have been used in the recent past to deepen our understanding of crops and their potential yield improvements. In the second part, we present a specific case study that indicates how robust models may be employed for crop improvements. This case study focuses on the biosynthesis of lignin in switchgrass (Panicum virgatum. Switchgrass is considered one of the most promising candidates for the second generation of bioenergy production, which does not use edible plant parts. Lignin is important in this context, because it impedes the use of cellulose in such inedible plant materials. The dynamic model offers a platform for investigating the pathway behavior in transgenic lines. In particular, it allows predictions of lignin content and composition in numerous genetic perturbation scenarios.

  8. Cerebral Metabolic Changes Related to Oxidative Metabolism in a Model of Bacterial Meningitis Induced by Lipopolysaccharide

    DEFF Research Database (Denmark)

    Munk, Michael; Rom Poulsen, Frantz; Larsen, Lykke

    2018-01-01

    BACKGROUND: Cerebral mitochondrial dysfunction is prominent in the pathophysiology of severe bacterial meningitis. In the present study, we hypothesize that the metabolic changes seen after intracisternal lipopolysaccharide (LPS) injection in a piglet model of meningitis is compatible...... with mitochondrial dysfunction and resembles the metabolic patterns seen in patients with bacterial meningitis. METHODS: Eight pigs received LPS injection in cisterna magna, and four pigs received NaCl in cisterna magna as a control. Biochemical variables related to energy metabolism were monitored by intracerebral...... dysfunction with increasing cerebral LPR due to increased lactate and normal pyruvate, PbtO2, and ICP. The metabolic pattern resembles the one observed in patients with bacterial meningitis. Metabolic monitoring in these patients is feasible to monitor for cerebral metabolic derangements otherwise missed...

  9. Inositol lipid turnover and compartmentation in canine trachealis smooth muscle

    International Nuclear Information System (INIS)

    Baron, C.B.; Pring, M.; Coburn, R.F.

    1989-01-01

    We established conditions for the study of metabolism and compartmentation of inositol phospholipids in canine trachealis muscle. Unstimulated muscle was incubated with myo-[3H]inositol for 30 min at 37 degrees C which resulted in labeling of the tissue free myo-inositol pool, whereas only a small amount of radioactivity was incorporated into inositol phospholipids or inositol phosphates. After addition of 5.5 microM carbachol, phosphatidylinositol (PI), phosphatidylinositol-4-phosphate (PIP), and phosphatidylinositol-4,5-bisphosphate (PIP2), specific radioactivities increased exponentially, reaching apparent constant values in 180-240 min. Initial rates of increases in PI, PIP, and PIP2 specific radioactivities were 39, 32, and 66 times that measured in unstimulated muscle. Metabolic flux rates (nmol.100 nmol total lipid Pi-1.min-1) during development of force averaged 0.42 +/- 0.09 and during force maintenance averaged 0.14 +/- 0.01. Fractions of total PI, PIP, and PIP2 pools that were linked to muscarinic cholinergic activation were estimated to be 0.97, 0.85, and 0.65, respectively. Initial rates of increase in specific radioactivities and specific radioactivities during carbachol activation were similar in PI, PIP, and PIP2 fast active compartments, suggesting metabolic flux from PI to PIP to PIP2 was in near chemical equilibrium. Turnover times for PI, PIP, and PIP2 fast active compartments were estimated to be 21, 1.6, and 4.0 min, respectively

  10. Genome-scale reconstruction of the metabolic network in Yersinia pestis CO92

    Science.gov (United States)

    Navid, Ali; Almaas, Eivind

    2007-03-01

    The gram-negative bacterium Yersinia pestis is the causative agent of bubonic plague. Using publicly available genomic, biochemical and physiological data, we have developed a constraint-based flux balance model of metabolism in the CO92 strain (biovar Orientalis) of this organism. The metabolic reactions were appropriately compartmentalized, and the model accounts for the exchange of metabolites, as well as the import of nutrients and export of waste products. We have characterized the metabolic capabilities and phenotypes of this organism, after comparing the model predictions with available experimental observations to evaluate accuracy and completeness. We have also begun preliminary studies into how cellular metabolism affects virulence.

  11. Next-generation genome-scale models for metabolic engineering

    DEFF Research Database (Denmark)

    King, Zachary A.; Lloyd, Colton J.; Feist, Adam M.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict...... examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering....

  12. Antimalarial drug targets in Plasmodium falciparum predicted by stage-specific metabolic network analysis

    OpenAIRE

    Huthmacher, Carola; Hoppe, Andreas; Bulik, Sascha; Holzh?tter, Hermann-Georg

    2010-01-01

    Abstract Background Despite enormous efforts to combat malaria the disease still afflicts up to half a billion people each year of which more than one million die. Currently no approved vaccine is available and resistances to antimalarials are widely spread. Hence, new antimalarial drugs are urgently needed. Results Here, we present a computational analysis of the metabolism of Plasmodium falciparum, the deadliest malaria pathogen. We assembled a compartmentalized metabolic model and predicte...

  13. Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling.

    Science.gov (United States)

    Cuperlovic-Culf, Miroslava

    2018-01-11

    Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies.

  14. Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling

    Science.gov (United States)

    Cuperlovic-Culf, Miroslava

    2018-01-01

    Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies. PMID:29324649

  15. Repurposing the Saccharomyces cerevisiae peroxisome for compartmentalizing multi-enzyme pathways

    Energy Technology Data Exchange (ETDEWEB)

    DeLoache, William [Univ. of California, Berkeley, CA (United States); Russ, Zachary [Univ. of California, Berkeley, CA (United States); Samson, Jennifer [Univ. of California, Berkeley, CA (United States); Dueber, John [Univ. of California, Berkeley, CA (United States)

    2017-09-25

    The peroxisome of Saccharomyces cerevisiae was targeted for repurposing in order to create a synthetic organelle that provides a generalizable compartment for engineered metabolic pathways. Compartmentalization of enzymes into organelles is a promising strategy for limiting metabolic crosstalk, improving pathway efficiency, and ultimately modifying the chemical environment to be distinct from that of the cytoplasm. We focused on the Saccharomyces cerevisiae peroxisome, as this organelle is not required for viability when grown on conventional media. We identified an enhanced peroxisomal targeting signal type 1 (PTS1) for rapidly importing non-native cargo proteins. Additionally, we performed the first systematic in vivo measurements of nonspecific metabolite permeability across the peroxisomal membrane using a polymer exclusion assay and characterized the size dependency of metabolite trafficking. Finally, we applied these new insights to compartmentalize a two-enzyme pathway in the peroxisome and characterize the expression regimes where compartmentalization leads to improved product titer. This work builds a foundation for using the peroxisome as a synthetic organelle, highlighting both promise and future challenges on the way to realizing this goal.

  16. Neuro-fuzzy model of homocysteine metabolism

    Indian Academy of Sciences (India)

    SHAIK Mohammad Naushad

    2017-12-08

    Dec 8, 2017 ... Homocysteine is a nondietary amino acid, which is the byproduct of ... wide spectrum of diseases such as recurrent pregnancy loss (Govindaiah et al. ... A2756G, MTRR A66G were reported in the folate metabolic pathway ...

  17. Compartmentalized human immunodeficiency virus type 1 originates from long-lived cells in some subjects with HIV-1-associated dementia.

    Science.gov (United States)

    Schnell, Gretja; Spudich, Serena; Harrington, Patrick; Price, Richard W; Swanstrom, Ronald

    2009-04-01

    Human immunodeficiency virus type 1 (HIV-1) invades the central nervous system (CNS) shortly after systemic infection and can result in the subsequent development of HIV-1-associated dementia (HAD) in a subset of infected individuals. Genetically compartmentalized virus in the CNS is associated with HAD, suggesting autonomous viral replication as a factor in the disease process. We examined the source of compartmentalized HIV-1 in the CNS of subjects with HIV-1-associated neurological disease and in asymptomatic subjects who were initiating antiretroviral therapy. The heteroduplex tracking assay (HTA), targeting the variable regions of env, was used to determine which HIV-1 genetic variants in the cerebrospinal fluid (CSF) were compartmentalized and which variants were shared with the blood plasma. We then measured the viral decay kinetics of individual variants after the initiation of antiretroviral therapy. Compartmentalized HIV-1 variants in the CSF of asymptomatic subjects decayed rapidly after the initiation of antiretroviral therapy, with a mean half-life of 1.57 days. Rapid viral decay was also measured for CSF-compartmentalized variants in four HAD subjects (t(1/2) mean = 2.27 days). However, slow viral decay was measured for CSF-compartmentalized variants from an additional four subjects with neurological disease (t(1/2) range = 9.85 days to no initial decay). The slow decay detected for CSF-compartmentalized variants was not associated with poor CNS drug penetration, drug resistant virus in the CSF, or the presence of X4 virus genotypes. We found that the slow decay measured for CSF-compartmentalized variants in subjects with neurological disease was correlated with low peripheral CD4 cell count and reduced CSF pleocytosis. We propose a model in which infiltrating macrophages replace CD4(+) T cells as the primary source of productive viral replication in the CNS to maintain high viral loads in the CSF in a substantial subset of subjects with HAD.

  18. Compartmentalized human immunodeficiency virus type 1 originates from long-lived cells in some subjects with HIV-1-associated dementia.

    Directory of Open Access Journals (Sweden)

    Gretja Schnell

    2009-04-01

    Full Text Available Human immunodeficiency virus type 1 (HIV-1 invades the central nervous system (CNS shortly after systemic infection and can result in the subsequent development of HIV-1-associated dementia (HAD in a subset of infected individuals. Genetically compartmentalized virus in the CNS is associated with HAD, suggesting autonomous viral replication as a factor in the disease process. We examined the source of compartmentalized HIV-1 in the CNS of subjects with HIV-1-associated neurological disease and in asymptomatic subjects who were initiating antiretroviral therapy. The heteroduplex tracking assay (HTA, targeting the variable regions of env, was used to determine which HIV-1 genetic variants in the cerebrospinal fluid (CSF were compartmentalized and which variants were shared with the blood plasma. We then measured the viral decay kinetics of individual variants after the initiation of antiretroviral therapy. Compartmentalized HIV-1 variants in the CSF of asymptomatic subjects decayed rapidly after the initiation of antiretroviral therapy, with a mean half-life of 1.57 days. Rapid viral decay was also measured for CSF-compartmentalized variants in four HAD subjects (t(1/2 mean = 2.27 days. However, slow viral decay was measured for CSF-compartmentalized variants from an additional four subjects with neurological disease (t(1/2 range = 9.85 days to no initial decay. The slow decay detected for CSF-compartmentalized variants was not associated with poor CNS drug penetration, drug resistant virus in the CSF, or the presence of X4 virus genotypes. We found that the slow decay measured for CSF-compartmentalized variants in subjects with neurological disease was correlated with low peripheral CD4 cell count and reduced CSF pleocytosis. We propose a model in which infiltrating macrophages replace CD4(+ T cells as the primary source of productive viral replication in the CNS to maintain high viral loads in the CSF in a substantial subset of subjects with HAD.

  19. Applications of computational modeling in metabolic engineering of yeast.

    Science.gov (United States)

    Kerkhoven, Eduard J; Lahtvee, Petri-Jaan; Nielsen, Jens

    2015-02-01

    Generally, a microorganism's phenotype can be described by its pattern of metabolic fluxes. Although fluxes cannot be measured directly, inference of fluxes is well established. In biotechnology the aim is often to increase the capacity of specific fluxes. For this, metabolic engineering methods have been developed and applied extensively. Many of these rely on balancing of intracellular metabolites, redox, and energy fluxes, using genome-scale models (GEMs) that in combination with appropriate objective functions and constraints can be used to predict potential gene targets for obtaining a preferred flux distribution. These methods point to strategies for altering gene expression; however, fluxes are often controlled by post-transcriptional events. Moreover, GEMs are usually not taking into account metabolic regulation, thermodynamics and enzyme kinetics. To facilitate metabolic engineering, tools from synthetic biology have emerged, enabling integration and assembly of naturally nonexistent, but well-characterized components into a living organism. To describe these systems kinetic models are often used and to integrate these systems with the standard metabolic engineering approach, it is necessary to expand the modeling of metabolism to consider kinetics of individual processes. This review will give an overview about models available for metabolic engineering of yeast and discusses their applications. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

  20. Constraint based modeling of metabolism allows finding metabolic cancer hallmarks and identifying personalized therapeutic windows.

    Science.gov (United States)

    Bordel, Sergio

    2018-04-13

    In order to choose optimal personalized anticancer treatments, transcriptomic data should be analyzed within the frame of biological networks. The best known human biological network (in terms of the interactions between its different components) is metabolism. Cancer cells have been known to have specific metabolic features for a long time and currently there is a growing interest in characterizing new cancer specific metabolic hallmarks. In this article it is presented a method to find personalized therapeutic windows using RNA-seq data and Genome Scale Metabolic Models. This method is implemented in the python library, pyTARG. Our predictions showed that the most anticancer selective (affecting 27 out of 34 considered cancer cell lines and only 1 out of 6 healthy mesenchymal stem cell lines) single metabolic reactions are those involved in cholesterol biosynthesis. Excluding cholesterol biosynthesis, all the considered cell lines can be selectively affected by targeting different combinations (from 1 to 5 reactions) of only 18 metabolic reactions, which suggests that a small subset of drugs or siRNAs combined in patient specific manners could be at the core of metabolism based personalized treatments.

  1. Concepts, challenges, and successes in modeling thermodynamics of metabolism.

    Science.gov (United States)

    Cannon, William R

    2014-01-01

    The modeling of the chemical reactions involved in metabolism is a daunting task. Ideally, the modeling of metabolism would use kinetic simulations, but these simulations require knowledge of the thousands of rate constants involved in the reactions. The measurement of rate constants is very labor intensive, and hence rate constants for most enzymatic reactions are not available. Consequently, constraint-based flux modeling has been the method of choice because it does not require the use of the rate constants of the law of mass action. However, this convenience also limits the predictive power of constraint-based approaches in that the law of mass action is used only as a constraint, making it difficult to predict metabolite levels or energy requirements of pathways. An alternative to both of these approaches is to model metabolism using simulations of states rather than simulations of reactions, in which the state is defined as the set of all metabolite counts or concentrations. While kinetic simulations model reactions based on the likelihood of the reaction derived from the law of mass action, states are modeled based on likelihood ratios of mass action. Both approaches provide information on the energy requirements of metabolic reactions and pathways. However, modeling states rather than reactions has the advantage that the parameters needed to model states (chemical potentials) are much easier to determine than the parameters needed to model reactions (rate constants). Herein, we discuss recent results, assumptions, and issues in using simulations of state to model metabolism.

  2. New paradigms for metabolic modeling of human cells

    DEFF Research Database (Denmark)

    Mardinoglu, Adil; Nielsen, Jens

    2015-01-01

    review recent work on reconstruction of GEMs for human cell/tissue types and cancer, and the use of GEMs for identification of metabolic changes occurring in response to disease development. We further discuss how GEMs can be used for the development of efficient therapeutic strategies. Finally......, challenges in integration of cell/tissue models for simulation of whole body functions as well as integration of GEMs with other biological networks for generating complete cell/tissue models are presented.......Abnormalities in cellular functions are associated with the progression of human diseases, often resulting in metabolic reprogramming. GEnome-scale metabolic Models (GEMs) have enabled studying global metabolic reprogramming in connection with disease development in a systematic manner. Here we...

  3. Passive Noise Filtering by Cellular Compartmentalization.

    Science.gov (United States)

    Stoeger, Thomas; Battich, Nico; Pelkmans, Lucas

    2016-03-10

    Chemical reactions contain an inherent element of randomness, which presents itself as noise that interferes with cellular processes and communication. Here we discuss the ability of the spatial partitioning of molecular systems to filter and, thus, remove noise, while preserving regulated and predictable differences between single living cells. In contrast to active noise filtering by network motifs, cellular compartmentalization is highly effective and easily scales to numerous systems without requiring a substantial usage of cellular energy. We will use passive noise filtering by the eukaryotic cell nucleus as an example of how this increases predictability of transcriptional output, with possible implications for the evolution of complex multicellularity. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Sustainability of a Compartmentalized Host-Parasite Replicator System under Periodic Washout-Mixing Cycles

    Directory of Open Access Journals (Sweden)

    Taro Furubayashi

    2018-01-01

    Full Text Available The emergence and dominance of parasitic replicators are among the major hurdles for the proliferation of primitive replicators. Compartmentalization of replicators is proposed to relieve the parasite dominance; however, it remains unclear under what conditions simple compartmentalization uncoupled with internal reaction secures the long-term survival of a population of primitive replicators against incessant parasite emergence. Here, we investigate the sustainability of a compartmentalized host-parasite replicator (CHPR system undergoing periodic washout-mixing cycles, by constructing a mathematical model and performing extensive simulations. We describe sustainable landscapes of the CHPR system in the parameter space and elucidate the mechanism of phase transitions between sustainable and extinct regions. Our findings revealed that a large population size of compartments, a high mixing intensity, and a modest amount of nutrients are important factors for the robust survival of replicators. We also found two distinctive sustainable phases with different mixing intensities. These results suggest that a population of simple host–parasite replicators assumed before the origin of life can be sustained by a simple compartmentalization with periodic washout-mixing processes.

  5. Compartmental analysis, imaging techniques and population pharmacokinetic. Experiences at CENTIS

    International Nuclear Information System (INIS)

    Hernández, Ignacio; León, Mariela; Leyva, Rene; Castro, Yusniel; Ayra, Fernando E.

    2016-01-01

    Introduction: In pharmacokinetic evaluation small rodents are used in a large extend. Traditional pharmacokinetic evaluations by the two steps approach can be replaced by the sparse data design which may also represent a complicated situation to evaluate satisfactorily from the statistical point of view. In this presentation different situations of sparse data sampling are analyzed based on practical consideration. Non linear mixed effect model was selected in order to estimate pharmacokinetic parameters in simulated data from real experimental results using blood sampling and imaging procedures. Materials and methods: Different scenarios representing several experimental designs of incomplete individual profiles were evaluated. Data sets were simulated based on real data from previous experiments. In all cases three to five blood samples were considered per time point. A combination of compartmental analysis with tumor uptake obtained by gammagraphy of radiolabeled drugs is also evaluated.All pharmacokinetic profiles were analyzed by means of MONOLIX software version 4.2.3. Results: All sampling schedules yield the same results when computed using the MONOLIX software and the SAEM algorithm. Population and individual pharmacokinetic parameters were accurately estimated with three or five determination per sampling point. According with the used methodology and software tool, it can be an expected result, but demonstrating the method performance in such situations, allow us to select a more flexible design using a very small number of animals in preclinical research. The combination with imaging procedures also allows us to construct a completely structured compartmental analysis. Results of real experiments are presented demonstrating the versatility of used methodology in different evaluations. The same sampling approach can be considered in phase I or II clinical trials. (author)

  6. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

    DEFF Research Database (Denmark)

    Förster, Jochen; Famili, I.; Fu, P.

    2003-01-01

    The metabolic network in the yeast Saccharomyces cerevisiae was reconstructed using currently available genomic, biochemical, and physiological information. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, and transport steps between the compartments...

  7. Probiotic modulation of symbiotic gut microbial–host metabolic interactions in a humanized microbiome mouse model

    Science.gov (United States)

    Martin, Francois-Pierre J; Wang, Yulan; Sprenger, Norbert; Yap, Ivan K S; Lundstedt, Torbjörn; Lek, Per; Rezzi, Serge; Ramadan, Ziad; van Bladeren, Peter; Fay, Laurent B; Kochhar, Sunil; Lindon, John C; Holmes, Elaine; Nicholson, Jeremy K

    2008-01-01

    The transgenomic metabolic effects of exposure to either Lactobacillus paracasei or Lactobacillus rhamnosus probiotics have been measured and mapped in humanized extended genome mice (germ-free mice colonized with human baby flora). Statistical analysis of the compartmental fluctuations in diverse metabolic compartments, including biofluids, tissue and cecal short-chain fatty acids (SCFAs) in relation to microbial population modulation generated a novel top-down systems biology view of the host response to probiotic intervention. Probiotic exposure exerted microbiome modification and resulted in altered hepatic lipid metabolism coupled with lowered plasma lipoprotein levels and apparent stimulated glycolysis. Probiotic treatments also altered a diverse range of pathways outcomes, including amino-acid metabolism, methylamines and SCFAs. The novel application of hierarchical-principal component analysis allowed visualization of multicompartmental transgenomic metabolic interactions that could also be resolved at the compartment and pathway level. These integrated system investigations demonstrate the potential of metabolic profiling as a top-down systems biology driver for investigating the mechanistic basis of probiotic action and the therapeutic surveillance of the gut microbial activity related to dietary supplementation of probiotics. PMID:18197175

  8. Compartmentation of sucrose during radial transfer in mature sorghum culm

    Directory of Open Access Journals (Sweden)

    Vietor Donald M

    2007-06-01

    Full Text Available Abstract Background The sucrose that accumulates in the culm of sorghum (Sorghum bicolor (L. Moench and other large tropical andropogonoid grasses can be of commercial value, and can buffer assimilate supply during development. Previous study conducted with intact plants showed that sucrose can be radially transferred to the intracellular compartment of mature ripening sorghum internode without being hydrolysed. In this study, culm-infused radiolabelled sucrose was traced between cellular compartments and among related metabolites to determine if the compartmental path of sucrose during radial transfer in culm tissue was symplasmic or included an apoplasmic step. This transfer path was evaluated for elongating and ripening culm tissue of intact plants of two semidwarf grain sorghums. The metabolic path in elongating internode tissue was also evaluated. Results On the day after culm infusion of the tracer sucrose, the specific radioactivity of sucrose recovered from the intracellular compartment of growing axillary-branch tissue was greater (nearly twice than that in the free space, indicating that sucrose was preferentially transferred through symplasmic routes. In contrast, the sucrose specific radioactivity in the intracellular compartment of the mature (ripening culm tissue was probably less (about 3/4's than that in free space indicating that sucrose was preferentially transferred through routes that included an apoplasmic step. In growing internodes of the axillary branch of sorghum, the tritium label initially provided in the fructose moiety of sucrose molecules was largely (81% recovered in the fructose moiety, indicating that a large portion of sucrose molecules is not hydrolysed and resynthesized during radial transfer. Conclusion During radial transfer of sucrose in ripening internodes of intact sorghum plants, much of the sucrose is transferred intact (without hydrolysis and resynthesis and primarily through a path that includes an

  9. Osteoarthritis and metabolic dysregulation: insights from a preclinical model

    NARCIS (Netherlands)

    Visser, H.M. de

    2018-01-01

    This thesis aims to identify the effect of metabolic factors, inflammatory processes and obesity in the pathophysiology of osteoarthritis (OA), using a high-fat diet and/or traumatic injury in a small animal model. The first part of this thesis describes, the rat Groove model of OA, using a one-time

  10. Modeling metabolic response to changes of enzyme amount in ...

    African Journals Online (AJOL)

    Based on the work of Hynne et al. (2001), in an in silico model of glycolysis, Saccharomyces cerevisiae is established by introducing an enzyme amount multiple factor (.) into the kinetic equations. The model is aimed to predict the metabolic response to the change of enzyme amount. With the help of .α, the amounts of ...

  11. Dynamic optimal metabolic control theory: a cybernetic approach for modelling of the central nitrogen metabolism of S. cerevisiae

    NARCIS (Netherlands)

    Riel, van N.A.W.; Giuseppin, M.L.F.; Verrips, C.T.

    2000-01-01

    The theory of dynamic optimal metabolic control (DOMC), as developed by Giuseppin and Van Riel (Metab. Eng., 2000), is applied to model the central nitrogen metabolism (CNM) in Saccharomyces cerevisiae. The CNM represents a typical system encountered in advanced metabolic engineering. The CNM is the

  12. Metabolism

    Science.gov (United States)

    ... Are More Common in People With Type 1 Diabetes Metabolic Syndrome Your Child's Weight Healthy Eating Endocrine System Blood Test: Basic Metabolic Panel (BMP) Activity: Endocrine System Growth Disorders Diabetes Center Thyroid Disorders Your Endocrine System Movie: Endocrine ...

  13. Field Testing of Compartmentalization Methods for Multifamily Construction

    Energy Technology Data Exchange (ETDEWEB)

    Ueno, K. [Building Science Corporation, Westford, MA (United States); Lstiburek, J. W. [Building Science Corporation, Westford, MA (United States)

    2015-03-01

    The 2012 International Energy Conservation Code (IECC) has an airtightness requirement of 3 air changes per hour at 50 Pascals test pressure (3 ACH50) for single-family and multifamily construction (in climate zones 3–8). The Leadership in Energy & Environmental Design certification program and ASHRAE Standard 189 have comparable compartmentalization requirements. ASHRAE Standard 62.2 will soon be responsible for all multifamily ventilation requirements (low rise and high rise); it has an exceptionally stringent compartmentalization requirement. These code and program requirements are driving the need for easier and more effective methods of compartmentalization in multifamily buildings.

  14. Use of genome-scale microbial models for metabolic engineering

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

    2004-01-01

    Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metaboli...... network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction....

  15. Metabolic alterations in experimental models of depression

    Directory of Open Access Journals (Sweden)

    Maria G. Puiu

    2016-10-01

    Full Text Available Introduction: Major depressive disorder is one of the most prevalent psychiatric disorders and is associated with a severe impact on the personal functioning, thus with incurring significant direct and indirect costs. The presence of depression in patients with medical comorbidities increases the risks of myocardial infarction and decreases diabetes control, and adherence to treatment. The mechanism through which these effects are produced is still uncertain. Objectives of this study were to evaluate the metabolic alterations in female Wistar rats with induced depression, with and without administration of Agomelatine. The methods included two experiments. All data were analyzed by comparison with group I (control, and with each other. In the first experiment we induced depression by: exposure to chronic mild stress-group II; olfactory bulbectomy-group III; and exposure to chronic mild stress and hyperlipidic/ hyper caloric dietgroup IV. The second experiment was similar with the first but the rats received Agomelatine (0.16mg/ animal: group V (depression induced through exposure to chronic mild stress, VI (depression induced through olfactory bulbectomy and VII (depression induced through exposure to chronic mild stressing hyperlipidic/ hypercaloric diet. Weight, cholesterol, triglycerides and glycaemia were measured at day 0 and 28, and leptin value was measured at day 28. The results in the 1st experiment revealed significant differences (p<0.01 for weight and cholesterol in Group IV, for triglycerides in groups III and IV (p<0.001, and for glycaemia in group II. The 2nd experiment revealed significant differences (p<0.001 in group VII for weight and triglycerides, and in groups V and VI for triglycerides (p<0.01. In conclusion, significant correlations were found between high level of triglycerides and depression induced by chronic stress and olfactory bulbectomy. Agomelatine groups had a lower increase of triglycerides levels.

  16. Compartmentalization of Aquaporins in the Human Intestine

    Directory of Open Access Journals (Sweden)

    Rajendram V. Rajnarayanan

    2008-06-01

    Full Text Available Improper localization of water channel proteins called aquaporins (AQP induce mucosal injury which is implicated in Crohn’s disease and ulcerative colitis. The amino acid sequences of AQP3 and AQP10 are 79% similar and belong to the mammalian aquaglyceroporin subfamily. AQP10 is localized on the apical compartment of the intestinal epithelium called the glycocalyx while AQP3 is selectively targeted to the basolateral membrane. Despite the high sequence similarity and evolutionary relatedness, the molecular mechanism involved in the polarity, selective targeting and function of AQP3 and AQP10 in the intestine is largely unknown. Our hypothesis is that the differential polarity and selective targeting of AQP3 and AQP10 in the intestinal epithelial cells is influenced by amino acid signal motifs. We performed sequence and structural alignments to determine differences in signals for localization and posttranslational glycosylation. The basolateral sorting motif “YRLL” is present in AQP3 but absent in AQP10; while Nglycosylation signals are present in AQP10 but absent in AQP3. Furthermore, the C-terminal region of AQP3 is longer compared to AQP10. The sequence and structural differences between AQP3 and AQP10 provide insights into the differential compartmentalization and function of these two aquaporins commonly expressed in human intestines.

  17. Compartmentalization and Transport in Synthetic Vesicles

    Directory of Open Access Journals (Sweden)

    Christine eSchmitt

    2016-02-01

    Full Text Available Nano-scale vesicles have become a popular tool in life sciences. Besides liposomes that are generated from phospholipids of natural origin, polymersomes fabricated of synthetic block copolymers enjoy increasing popularity, as they represent more versatile membrane building blocks that can be selected based on their specific physicochemical properties, like permeability, stability or chemical reactivity.In this review, we focus on the application of simple and nested artificial vesicles in synthetic biology. First, we provide an introduction into the utilization of multi-compartmented vesosomes as compartmentalized nano-scale bioreactors. In the bottom-up development of protocells from vesicular nano-reactors, the specific exchange of pathway intermediates across compartment boundaries represents a bottleneck for future studies. To date, most compartmented bioreactors rely on unspecific exchange of substrates and products. This is either based on changes in permeability of the coblock polymer shell by physicochemical triggers or by the incorporation of unspecific porin proteins into the vesicle membrane. Since the incorporation of membrane transport proteins into simple and nested artificial vesicles offers the potential for specific exchange of substances between subcompartments, it opens new vistas in the design of protocells. Therefore we devote the main part of the review to summarize the technical advances in the use of phospholipids and block copolymers for the reconstitution of membrane proteins.

  18. Cardiovascular Changes in Animal Models of Metabolic Syndrome

    Directory of Open Access Journals (Sweden)

    Alexandre M. Lehnen

    2013-01-01

    Full Text Available Metabolic syndrome has been defined as a group of risk factors that directly contribute to the development of cardiovascular disease and/or type 2 diabetes. Insulin resistance seems to have a fundamental role in the genesis of this syndrome. Over the past years to the present day, basic and translational research has used small animal models to explore the pathophysiology of metabolic syndrome and to develop novel therapies that might slow the progression of this prevalent condition. In this paper we discuss the animal models used for the study of metabolic syndrome, with particular focus on cardiovascular changes, since they are the main cause of death associated with the condition in humans.

  19. Dynamic modeling of lactic acid fermentation metabolism with Lactococcus lactis.

    Science.gov (United States)

    Oh, Euhlim; Lu, Mingshou; Park, Changhun; Park, Changhun; Oh, Han Bin; Lee, Sang Yup; Lee, Jinwon

    2011-02-01

    A dynamic model of lactic acid fermentation using Lactococcus lactis was constructed, and a metabolic flux analysis (MFA) and metabolic control analysis (MCA) were performed to reveal an intensive metabolic understanding of lactic acid bacteria (LAB). The parameter estimation was conducted with COPASI software to construct a more accurate metabolic model. The experimental data used in the parameter estimation were obtained from an LC-MS/ MS analysis and time-course simulation study. The MFA results were a reasonable explanation of the experimental data. Through the parameter estimation, the metabolic system of lactic acid bacteria can be thoroughly understood through comparisons with the original parameters. The coefficients derived from the MCA indicated that the reaction rate of L-lactate dehydrogenase was activated by fructose 1,6-bisphosphate and pyruvate, and pyruvate appeared to be a stronger activator of L-lactate dehydrogenase than fructose 1,6-bisphosphate. Additionally, pyruvate acted as an inhibitor to pyruvate kinase and the phosphotransferase system. Glucose 6-phosphate and phosphoenolpyruvate showed activation effects on pyruvate kinase. Hexose transporter was the strongest effector on the flux through L-lactate dehydrogenase. The concentration control coefficient (CCC) showed similar results to the flux control coefficient (FCC).

  20. LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models

    Science.gov (United States)

    Winslow, Luke; Zwart, Jacob A.; Batt, Ryan D.; Dugan, Hilary; Woolway, R. Iestyn; Corman, Jessica; Hanson, Paul C.; Read, Jordan S.

    2016-01-01

    Metabolism is a fundamental process in ecosystems that crosses multiple scales of organization from individual organisms to whole ecosystems. To improve sharing and reuse of published metabolism models, we developed LakeMetabolizer, an R package for estimating lake metabolism from in situ time series of dissolved oxygen, water temperature, and, optionally, additional environmental variables. LakeMetabolizer implements 5 different metabolism models with diverse statistical underpinnings: bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, and Bayesian. Each of these 5 metabolism models can be combined with 1 of 7 models for computing the coefficient of gas exchange across the air–water interface (k). LakeMetabolizer also features a variety of supporting functions that compute conversions and implement calculations commonly applied to raw data prior to estimating metabolism (e.g., oxygen saturation and optical conversion models). These tools have been organized into an R package that contains example data, example use-cases, and function documentation. The release package version is available on the Comprehensive R Archive Network (CRAN), and the full open-source GPL-licensed code is freely available for examination and extension online. With this unified, open-source, and freely available package, we hope to improve access and facilitate the application of metabolism in studies and management of lentic ecosystems.

  1. Individual optimization of therapeutic applications and dosimetry of radiopharmaceuticals with the help of compartmental analysis

    International Nuclear Information System (INIS)

    Augusto Ciussani

    2007-01-01

    Complete test of publication follows. The successful application of radiopharmaceuticals requires a patient-specific optimization of the activity to be administered, in order to deliver the desired therapeutic dose to the target organ while saving the healthy tissues. For a therapy specifically tailored on the characteristics of the patient, the correct knowledge of the morphology of the regions of interest, of the fractional uptake and of the related kinetics is necessary. Compartmental modelling can represent a powerful and simple tool for deriving the information of interest. In this presentation, the potentiality of compartmental analysis will be illustrated and two applications presented. The first study was conducted in patients with the autonomous functioning thyroid nodule (AFTN) syndrome treated with 131 I at the Ospedale Maggiore Policlinico of Milano (Milano, Italy). In these patients, the great challenge is represented by the healthy lobe surrounding the malignant nodule. A model was developed, where nodule and lobe are considered as separate entities in order to provide distinct dose estimates for the two tissues. The model has been also used for the optimization of the sampling schedule and for interpretation of biokinetic discrepancies observed between the diagnostic tests and the therapeutic application. The second study, carried out at Ospedali Riuniti di Bergamo (Bergamo, Italy), dealt with the application of [ 186 Re]-HEDP (hydroxyethyliden-diphosphonate disodium salt) for palliation of pain due to bone metastases of primary carcinomas. On the basis of the biodistribution studies and of chromatographic measurements, a compartmental model was suggested, taking into account the possible dissociation of the compound after injection into the patient. Also in this case, the compartmental model represents a valuable tool for individual optimization of the therapeutic procedure and for a more precise evaluation of the radiation dose the organs.

  2. Mechanistic modeling of aberrant energy metabolism in human disease

    Directory of Open Access Journals (Sweden)

    Vineet eSangar

    2012-10-01

    Full Text Available Dysfunction in energy metabolism—including in pathways localized to the mitochondria—has been implicated in the pathogenesis of a wide array of disorders, ranging from cancer to neurodegenerative diseases to type II diabetes. The inherent complexities of energy and mitochondrial metabolism present a significant obstacle in the effort to understand the role that these molecular processes play in the development of disease. To help unravel these complexities, systems biology methods have been applied to develop an array of computational metabolic models, ranging from mitochondria-specific processes to genome-scale cellular networks. These constraint-based models can efficiently simulate aspects of normal and aberrant metabolism in various genetic and environmental conditions. Development of these models leverages—and also provides a powerful means to integrate and interpret—information from a wide range of sources including genomics, proteomics, metabolomics, and enzyme kinetics. Here, we review a variety of mechanistic modeling studies that explore metabolic functions, deficiency disorders, and aberrant biochemical pathways in mitochondria and related regions in the cell.

  3. Metabolic Models of Protein Allocation Call for the Kinetome

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Nielsen, Jens; Palsson, Bernhard

    2017-01-01

    The flux of metabolites in the living cell depend on enzyme activities. Recently, many metabolic phenotypes have been explained by computer models that incorporate enzyme activity data. To move further, the scientific community needs to measure the kinetics of all enzymes in a systematic way....

  4. Metabolism related toxicity of diclofenac in yeast as model system

    NARCIS (Netherlands)

    van Leeuwen, J.S.; Vredenburg, G.; Dragovic, S.; Tjong, T.F.; Vos, J.C.; Vermeulen, N.P.E.

    2010-01-01

    Diclofenac is a widely used drug that can cause serious hepatotoxicity, which has been linked to metabolism by cytochrome P450s (P450). To investigate the role of oxidative metabolites in diclofenac toxicity, a model for P450-related toxicity was set up in Saccharomyces cerevisiae. We expressed a

  5. Integrating cellular metabolism into a multiscale whole-body model.

    Directory of Open Access Journals (Sweden)

    Markus Krauss

    Full Text Available Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development.

  6. Integrating Cellular Metabolism into a Multiscale Whole-Body Model

    Science.gov (United States)

    Krauss, Markus; Schaller, Stephan; Borchers, Steffen; Findeisen, Rolf; Lippert, Jörg; Kuepfer, Lars

    2012-01-01

    Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development. PMID:23133351

  7. Compartmentalization of prostaglandins in the canine kidney

    International Nuclear Information System (INIS)

    Morgan-Boyd, R.L.

    1986-01-01

    The kidney has been shown to synthesize all of the naturally occurring major prostaglandins which may be restricted to a discrete part of the kidney where their actions are physiologically important, such as the vascular compartment and the tubular compartment. In order to examine this concept of compartmentalization, the authors conducted a series of experiments to determine whether PGl 2 , measured as 6-keto-pGF/sub 1α/, produced in the kidney is restricted to the renal vascular compartment or whether it also has access to the tubular compartment. Experiments were performed in the pentobarbital-anesthetized dog. Increasing pre-glomerular levels of 6-keto-PFG/sub 1α/ caused marked increases in both the urinary excretion and the renal venous outflow to 6-keto-PGF/sub 1α/. When 3 H-6-keto-PGF/sub 1α/ was co-infused with inulin into the renal artery, 33% of the radioactivity and 23% of the inulin was recovered on first pass. With infusion of 3 H-PGl 2 and inulin, 20% of the radioactivity and 28% of the inulin reached the urine on first pass. Radioactive PGl 2 appeared to be less filterable at the glomeruli than either 3 H-6-keto-PGF/sub 1α/ or inulin. In the final set of experiments, in which dogs were prepared for a ureteral stopped-flow study, the PGE 2 /U/P/sub In/ ratio a peak was observed proximal to the Na + plateau but distal to the Na+ nadir. In light of the results from the stopped-flow study and the intrarenal infusion studies, they conclude that PGE 2 synthesized in the kidney enters both the renal and tubular compartments. In contrast, they find that 6-keto-PGF/sub 1α/ of renal origin enters only the renal origin enters only the renal vascular compartment and not the tubular compartment

  8. Metabolism

    Science.gov (United States)

    ... lin), which signals cells to increase their anabolic activities. Metabolism is a complicated chemical process, so it's not ... how those enzymes or hormones work. When the metabolism of body chemicals is ... Hyperthyroidism (pronounced: hi-per-THIGH-roy-dih-zum). Hyperthyroidism ...

  9. Metabolic modeling of synthesis gas fermentation in bubble column reactors.

    Science.gov (United States)

    Chen, Jin; Gomez, Jose A; Höffner, Kai; Barton, Paul I; Henson, Michael A

    2015-01-01

    A promising route to renewable liquid fuels and chemicals is the fermentation of synthesis gas (syngas) streams to synthesize desired products such as ethanol and 2,3-butanediol. While commercial development of syngas fermentation technology is underway, an unmet need is the development of integrated metabolic and transport models for industrially relevant syngas bubble column reactors. We developed and evaluated a spatiotemporal metabolic model for bubble column reactors with the syngas fermenting bacterium Clostridium ljungdahlii as the microbial catalyst. Our modeling approach involved combining a genome-scale reconstruction of C. ljungdahlii metabolism with multiphase transport equations that govern convective and dispersive processes within the spatially varying column. The reactor model was spatially discretized to yield a large set of ordinary differential equations (ODEs) in time with embedded linear programs (LPs) and solved using the MATLAB based code DFBAlab. Simulations were performed to analyze the effects of important process and cellular parameters on key measures of reactor performance including ethanol titer, ethanol-to-acetate ratio, and CO and H2 conversions. Our computational study demonstrated that mathematical modeling provides a complementary tool to experimentation for understanding, predicting, and optimizing syngas fermentation reactors. These model predictions could guide future cellular and process engineering efforts aimed at alleviating bottlenecks to biochemical production in syngas bubble column reactors.

  10. [Regulation of terpene metabolism

    Energy Technology Data Exchange (ETDEWEB)

    Croteau, R.

    1989-11-09

    Terpenoid oils, resins, and waxes from plants are important renewable resources. The objective of this project is to understand the regulation of terpenoid metabolism using the monoterpenes (C[sub 10]) as a model. The pathways of monoterpene biosynthesis and catabolism have been established, and the relevant enzymes characterized. Developmental studies relating enzyme levels to terpene accumulation within the oil gland sites of synthesis, and work with bioregulators, indicate that monoterpene production is controlled by terpene cyclases, the enzymes catalyzing the first step of the monoterpene pathway. As the leaf oil glands mature, cyclase levels decline and monoterpene biosynthesis ceases. Yield then decreases as the monoterpenes undergo catabolism by a process involving conversion to a glycoside and transport from the leaf glands to the root. At this site, the terpenoid is oxidatively degraded to acetate that is recycled into other lipid metabolites. During the transition from terpene biosynthesis to catabolism, the oil glands undergo dramatic ultrastructural modification. Degradation of the producing cells results in mixing of previously compartmentized monoterpenes with the catabolic enzymes, ultimately leading to yield decline. This regulatory model is being applied to the formation of other terpenoid classes (C[sub 15] C[sub 20], C[sub 30], C[sub 40]) within the oil glands. Preliminary investigations on the formation of sesquiterpenes (C[sub 15]) suggest that the corresponding cyclases may play a lesser role in determining yield of these products, but that compartmentation effects are important. From these studies, a comprehensive scheme for the regulation of terpene metabolism is being constructed. Results from this project wail have important consequences for the yield and composition of terpenoid natural products that can be made available for industrial exploitation.

  11. Constraining Genome-Scale Models to Represent the Bow Tie Structure of Metabolism for 13C Metabolic Flux Analysis

    Directory of Open Access Journals (Sweden)

    Tyler W. H. Backman

    2018-01-01

    Full Text Available Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13 C Metabolic Flux Analysis ( 13 C MFA and Two-Scale 13 C Metabolic Flux Analysis (2S- 13 C MFA are two techniques used to determine such fluxes. Both operate on the simplifying approximation that metabolic flux from peripheral metabolism into central “core” carbon metabolism is minimal, and can be omitted when modeling isotopic labeling in core metabolism. The validity of this “two-scale” or “bow tie” approximation is supported both by the ability to accurately model experimental isotopic labeling data, and by experimentally verified metabolic engineering predictions using these methods. However, the boundaries of core metabolism that satisfy this approximation can vary across species, and across cell culture conditions. Here, we present a set of algorithms that (1 systematically calculate flux bounds for any specified “core” of a genome-scale model so as to satisfy the bow tie approximation and (2 automatically identify an updated set of core reactions that can satisfy this approximation more efficiently. First, we leverage linear programming to simultaneously identify the lowest fluxes from peripheral metabolism into core metabolism compatible with the observed growth rate and extracellular metabolite exchange fluxes. Second, we use Simulated Annealing to identify an updated set of core reactions that allow for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13 C MFA or 2S- 13 C MFA, as well as provide for a substantially lower set of flux bounds for fluxes into the core as compared with previous methods. We provide an open source Python implementation of these algorithms at https://github.com/JBEI/limitfluxtocore.

  12. Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

    Science.gov (United States)

    Volyanskyy, Kostyantyn Y.

    Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance

  13. Energetics of glucose metabolism: a phenomenological approach to metabolic network modeling.

    Science.gov (United States)

    Diederichs, Frank

    2010-08-12

    A new formalism to describe metabolic fluxes as well as membrane transport processes was developed. The new flux equations are comparable to other phenomenological laws. Michaelis-Menten like expressions, as well as flux equations of nonequilibrium thermodynamics, can be regarded as special cases of these new equations. For metabolic network modeling, variable conductances and driving forces are required to enable pathway control and to allow a rapid response to perturbations. When applied to oxidative phosphorylation, results of simulations show that whole oxidative phosphorylation cannot be described as a two-flux-system according to nonequilibrium thermodynamics, although all coupled reactions per se fulfill the equations of this theory. Simulations show that activation of ATP-coupled load reactions plus glucose oxidation is brought about by an increase of only two different conductances: a [Ca(2+)] dependent increase of cytosolic load conductances, and an increase of phosphofructokinase conductance by [AMP], which in turn becomes increased through [ADP] generation by those load reactions. In ventricular myocytes, this feedback mechanism is sufficient to increase cellular power output and O(2) consumption several fold, without any appreciable impairment of energetic parameters. Glucose oxidation proceeds near maximal power output, since transformed input and output conductances are nearly equal, yielding an efficiency of about 0.5. This conductance matching is fulfilled also by glucose oxidation of β-cells. But, as a price for the metabolic mechanism of glucose recognition, β-cells have only a limited capability to increase their power output.

  14. Genetic dissection in a mouse model reveals interactions between carotenoids and lipid metabolism[S

    Science.gov (United States)

    Palczewski, Grzegorz; Widjaja-Adhi, M. Airanthi K.; Amengual, Jaume; Golczak, Marcin; von Lintig, Johannes

    2016-01-01

    Carotenoids affect a rich variety of physiological functions in nature and are beneficial for human health. However, knowledge about their biological action and the consequences of their dietary accumulation in mammals is limited. Progress in this research field is limited by the expeditious metabolism of carotenoids in rodents and the confounding production of apocarotenoid signaling molecules. Herein, we established a mouse model lacking the enzymes responsible for carotenoid catabolism and apocarotenoid production, fed on either a β-carotene- or a zeaxanthin-enriched diet. Applying a genome wide microarray analysis, we assessed the effects of the parent carotenoids on the liver transcriptome. Our analysis documented changes in pathways for liver lipid metabolism and mitochondrial respiration. We biochemically defined these effects, and observed that β-carotene accumulation resulted in an elevation of liver triglycerides and liver cholesterol, while zeaxanthin accumulation increased serum cholesterol levels. We further show that carotenoids were predominantly transported within HDL particles in the serum of mice. Finally, we provide evidence that carotenoid accumulation influenced whole-body respiration and energy expenditure. Thus, we observed that accumulation of parent carotenoids interacts with lipid metabolism and that structurally related carotenoids display distinct biological functions in mammals. PMID:27389691

  15. A biokinetic and dosimetric model for the metabolism of uranium

    International Nuclear Information System (INIS)

    Wrenn, M.E.; Bertelli, L.; Durbin, P.W.; Eckerman, K.F.; Lipsztein, J.L.; Singh, N.P.

    1995-10-01

    Experiments involving injection and inhalation of uranium compounds into several animal species as well as those associated with humans are described and analyzed. A revised biokinetic and dosimetric model for the metabolism of uranium suitable for bioassay procedures is proposed. The model consists of a systematic part coupled to a model of the respiratory tract. The model has been tested against human data which incorporates in vivo measurements over the chest and measurements of urine, feces, and autopsy and biopsy samples.In particular the lung model of the International Commission on Radiological Protection, Publication 30 ( ICRP-30 ), has been modified in order to provide a model which more nearly predicts urinary excretion in accord with the experiences in humans and animals. We have also tested the data against the new ICRP (LUDEP) lung model. (author). 55 refs., 14 tabs., 33 figs

  16. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction.

    Directory of Open Access Journals (Sweden)

    Katsunori Yoshikawa

    Full Text Available Arthrospira (Spirulina platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(PH dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source.

  17. Compartmentalized Human Immunodeficiency Virus Type 1 Originates from Long-Lived Cells in Some Subjects with HIV-1–Associated Dementia

    Science.gov (United States)

    Schnell, Gretja; Spudich, Serena; Harrington, Patrick; Price, Richard W.; Swanstrom, Ronald

    2009-01-01

    Human immunodeficiency virus type 1 (HIV-1) invades the central nervous system (CNS) shortly after systemic infection and can result in the subsequent development of HIV-1–associated dementia (HAD) in a subset of infected individuals. Genetically compartmentalized virus in the CNS is associated with HAD, suggesting autonomous viral replication as a factor in the disease process. We examined the source of compartmentalized HIV-1 in the CNS of subjects with HIV-1–associated neurological disease and in asymptomatic subjects who were initiating antiretroviral therapy. The heteroduplex tracking assay (HTA), targeting the variable regions of env, was used to determine which HIV-1 genetic variants in the cerebrospinal fluid (CSF) were compartmentalized and which variants were shared with the blood plasma. We then measured the viral decay kinetics of individual variants after the initiation of antiretroviral therapy. Compartmentalized HIV-1 variants in the CSF of asymptomatic subjects decayed rapidly after the initiation of antiretroviral therapy, with a mean half-life of 1.57 days. Rapid viral decay was also measured for CSF-compartmentalized variants in four HAD subjects (t1/2 mean = 2.27 days). However, slow viral decay was measured for CSF-compartmentalized variants from an additional four subjects with neurological disease (t1/2 range = 9.85 days to no initial decay). The slow decay detected for CSF-compartmentalized variants was not associated with poor CNS drug penetration, drug resistant virus in the CSF, or the presence of X4 virus genotypes. We found that the slow decay measured for CSF-compartmentalized variants in subjects with neurological disease was correlated with low peripheral CD4 cell count and reduced CSF pleocytosis. We propose a model in which infiltrating macrophages replace CD4+ T cells as the primary source of productive viral replication in the CNS to maintain high viral loads in the CSF in a substantial subset of subjects with HAD

  18. Biokinetic models for the metabolism of uranium: an overview

    International Nuclear Information System (INIS)

    Bertelli, Luiz; Lipsztein, Joyce L.; Melo, Dunstana R.; Puerta, Anselmo; Wrenn, McDonald E.

    1997-01-01

    This work reviews the main experiments involving uranium injection and inhalation into several animal species and those associated with humans as well. The literature was carefully selected to involve the uranium intake, distribution and excretion in humans and mammals. The available biokinetic models for the uranium metabolism, proposed by ICRP in Publications 2, 30 and 69, were shortly described and tested against the data. Human data which incorporates measurements of urine, autopsy and biopsy samples were also used completing the review of models associated with the systemic part. (author). 21 refs., 4 figs

  19. Reconstruction of genome-scale human metabolic models using omics data

    DEFF Research Database (Denmark)

    Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup

    2015-01-01

    used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods......, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic...... refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model....

  20. Compartmental analysis to predict biodistribution in radiopharmaceutical design studies

    Energy Technology Data Exchange (ETDEWEB)

    Lima, Marina F.; Pujatti, Priscilla B.; Araujo, Elaine B.; Mesquita, Carlos H. [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)], e-mail: mflima@ipen.br

    2009-07-01

    The use of compartmental analysis allows the mathematical separation of tissues and organs to determinate the concentration of activity in each fraction of interest. Although the radiochemical purity must observe Pharmacopoeia specification (values upper 95%), very lower contains of free radionuclides could contribute significantly as dose in the neighborhood organs and make tumor up take studies not viable in case of radiopharmaceutical on the basis of labeled peptides. Animal studies with a product of Lutetium-177 labeled Bombesin derivative ({sup 177}Lu-BBNP) developed in IPEN-CNEN/SP and free Lutetium-177 developed in CNEA/EZEIZA was used to show how subtract free {sup 177}Lu contribution over {sup 177}Lu-BBNP to estimate the radiopharmaceutical potential as diagnosis or therapy agent. The first approach of the studies included the knowledge of chemical kinetics and mimetism of the Lutetium and the possible targets of the diagnosis/therapy to choose the possible models to apply over the sampling standard methods used in experimental works. A model with only one physical compartment (whole body) and one chemical compartment ({sup 177}Lu-BBNP) generated with the compartmental analysis protocol ANACOMP showed high differences between experimental and theoretical values over 2.5 hours, in spite of the concentration of activity had been in a good statistics rang of measurement. The values used in this work were residence time from three different kinds of study with free {sup 177}Lu: whole body, average excretion and maximum excretion as a chemical compartment. Activity concentration values as time function in measurements of total whole body and activity measurement in samples of blood with projection to total circulating blood volume with {sup 177}Lu-BBNP. Considering the two sources of data in the same modeling a better consistence was obtained. The next step was the statistic treatment of biodistribution and dosimetry in mice (Balb C) considering three chemical

  1. The kinetics of multi-compartmentalized systems, studied by radioactive tracers

    International Nuclear Information System (INIS)

    Gouveia, A.S. de.

    1978-01-01

    The use of compartmental models to investigate kinetic problems is presented. This use is restricted, however, to linear models. As an application of different methods, the kinetic behaviour of haemaccel labelled with iodine 131 is studied, the interval of the physically viable solutions being established. The existence of a class of solutions is explained as a result of lack of knowledge of a complete data set. The possibility of obtaining a single solution is also discussed. The formalism of the program SAAM (Simulation, Analysis and modelling) now judged very important for the study of multi-compartimental analysis is presented. (I.C.R) [pt

  2. Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

    Science.gov (United States)

    Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.

    2016-01-01

    The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809

  3. An age dependent model for radium metabolism in man.

    Science.gov (United States)

    Johnson, J R

    1983-01-01

    The model developed by a Task Group of Committee 2 of ICRP to describe Alkaline Earth Metabolism in Adult Man (ICRP Publication 20) has been modified so that recycling is handled explicitly, and retention in mineral bone is represented by second compartments rather than by the product of a power function and an exponential. This model has been extended to include all ages from birth to adult man, and has been coupled with modified "ICRP" lung and G.I. tract models so that activity in organs can be calculated as functions of time during or after exposures. These activities, and age dependent "specific effective energy" factors, are then used to calculate age dependent dose rates, and dose commitments. This presentation describes this work, with emphasis on the model parameters and results obtained for radium.

  4. Age-dependent metabolic model of radionuclides in Human body

    International Nuclear Information System (INIS)

    Ye Changqing

    1986-01-01

    Age-dependent metabolic model of radionuclides in human body was introduced briefly. These data are necessary in setting up the secondary dose limit of internal exposure of the general public. For the gastro-intestinal tract model, it was shown that the dose of various sections of GI tract caused by unsoluble radioactive materials were influenced by the mass of section and mean residence time, both of which are age-dependent, but the absorption fraction f 1 through gastro-intestinal tract should be corrected only for the infant less than 1 year of age. For the lung model, it was indicated that the fraction of deposition or clearance of particles in the different compartments of lung were related to age. The doses of tracheobronchial and pulmonary compartment of adult for 222 Rn or 220 Rn with their decay products were one third of that of 6-years old child who received the maximum dose in comparison with other ages. The age-dependent metabolic models in organ and/or body of Tritium, Iodine-131, Caesium-137, radioactive Strontium, Radium and Plutonium were reported. A generalized approach for estimating the effect of age on deposition fractions and retention half-time were presented. Calculated results indicated that younger ages were characterized by increased deposition fraction and decreased half-time for retention. Representative examples were provided for 21 elements of current interest in health physics

  5. DRUM: a new framework for metabolic modeling under non-balanced growth. Application to the carbon metabolism of unicellular microalgae.

    Science.gov (United States)

    Baroukh, Caroline; Muñoz-Tamayo, Rafael; Steyer, Jean-Philippe; Bernard, Olivier

    2014-01-01

    Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates.

  6. DRUM: a new framework for metabolic modeling under non-balanced growth. Application to the carbon metabolism of unicellular microalgae.

    Directory of Open Access Journals (Sweden)

    Caroline Baroukh

    Full Text Available Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates.

  7. Metabolic phenotype in the mouse model of osteogenesis imperfecta.

    Science.gov (United States)

    Boraschi-Diaz, Iris; Tauer, Josephine T; El-Rifai, Omar; Guillemette, Delphine; Lefebvre, Geneviève; Rauch, Frank; Ferron, Mathieu; Komarova, Svetlana V

    2017-09-01

    Osteogenesis imperfecta (OI) is the most common heritable bone fragility disorder, usually caused by dominant mutations in genes coding for collagen type I alpha chains, COL1A1 or COL1A2 Osteocalcin (OCN) is now recognized as a bone-derived regulator of insulin secretion and sensitivity and glucose homeostasis. Since OI is associated with increased rates of bone formation and resorption, we hypothesized that the levels of undercarboxylated OCN are increased in OI. The objective of this study was to determine changes in OCN and to elucidate the metabolic phenotype in the Col1a1 Jrt/+ mouse, a model of dominant OI caused by a Col1a1 mutation. Circulating levels of undercarboxylated OCN were higher in 4-week-old OI mice and normal by 8 weeks of age. Young OI animals exhibited a sex-dependent metabolic phenotype, including increased insulin levels in males, improved glucose tolerance in females, lower levels of random glucose and low adiposity in both sexes. The rates of O 2 consumption and CO 2 production, as well as energy expenditure assessed using indirect calorimetry were significantly increased in OI animals of both sexes, whereas respiratory exchange ratio was significantly higher in OI males only. Although OI mice have significant physical impairment that may contribute to metabolic differences, we specifically accounted for movement and compared OI and WT animals during the periods of similar activity levels. Taken together, our data strongly suggest that OI animals have alterations in whole body energy metabolism that are consistent with the action of undercarboxylated osteocalcin. © 2017 Society for Endocrinology.

  8. Integration through Compartmentalization? Pitfalls of “Poldering” in Bangladesh

    NARCIS (Netherlands)

    Warner, J.F.

    2010-01-01

    The article sketches the history of the Flood Action Plan 20 (FAP-20), an experiment with polder compartmentalization, seeking to integrate flood management, drainage, and irrigation, and make it more democratic in response to the destructive 1987 and 1988 floods in Bangladesh. As a transferred

  9. Macroanatomy of compartmentalization in fire scars of three western conifers

    Science.gov (United States)

    Kevin T. Smith; Elaine Sutherland; Estelle Arbellay; Markus Stoffel; Donald. Falk

    2013-01-01

    Fire scars are visible evidence of compartmentalization and closure processes that contribute to tree survival after fire injury. Preliminary observations of dissected fire scars from trees injured within the last decade showed centripetal development of wound-initiated discoloration (WID) through 2-3 decades of former sapwood in Larix occidentalis and Pseudotsuga...

  10. Integration through compartmentalization? Pitfalls of 'poldering' in Bangladesh

    NARCIS (Netherlands)

    Warner, J.F.

    2010-01-01

    The article sketches the history of the Flood Action Plan 20 (FAP-20), an experiment with polder compartmentalization, seeking to integrate flood management, drainage, and irrigation, and make it more democratic in response to the destructive 1987 and 1988 floods in Bangladesh. As a transferred

  11. Formulation, construction and analysis of kinetic models of metabolism: A review of modelling frameworks

    DEFF Research Database (Denmark)

    Saa, Pedro A.; Nielsen, Lars K.

    2017-01-01

    Kinetic models are critical to predict the dynamic behaviour of metabolic networks. Mechanistic kinetic models for large networks remain uncommon due to the difficulty of fitting their parameters. Recent modelling frameworks promise new ways to overcome this obstacle while retaining predictive ca...

  12. Composite PET and MRI for accurate localization and metabolic modeling

    International Nuclear Information System (INIS)

    Bidaut, L.

    1991-01-01

    This paper reports that in order to help in analyzing PET data and really take advantage of their metabolic content, a system was designed and implemented to align and process data from various medical imaging modalities, particularly (but not only) for brain studies. Although this system is for now mostly used for anatomical localization, multi-modality ROIs and pharmaco-kinetic modeling, more multi-modality protocols will be implemented in the future, not only to help in PET reconstruction data correction and semi-automated ROI definition, but also for helping in improving diagnostic accuracy along with surgery and therapy planning

  13. Quantum Mechanics/Molecular Mechanics Modeling of Drug Metabolism

    DEFF Research Database (Denmark)

    Lonsdale, Richard; Fort, Rachel M; Rydberg, Patrik

    2016-01-01

    )-mexiletine in CYP1A2 with hybrid quantum mechanics/molecular mechanics (QM/MM) methods, providing a more detailed and realistic model. Multiple reaction barriers have been calculated at the QM(B3LYP-D)/MM(CHARMM27) level for the direct N-oxidation and H-abstraction/rebound mechanisms. Our calculated barriers......The mechanism of cytochrome P450(CYP)-catalyzed hydroxylation of primary amines is currently unclear and is relevant to drug metabolism; previous small model calculations have suggested two possible mechanisms: direct N-oxidation and H-abstraction/rebound. We have modeled the N-hydroxylation of (R...... indicate that the direct N-oxidation mechanism is preferred and proceeds via the doublet spin state of Compound I. Molecular dynamics simulations indicate that the presence of an ordered water molecule in the active site assists in the binding of mexiletine in the active site...

  14. Compartmental and dosimetric studies of anti-CD20 labelled with 188Re

    International Nuclear Information System (INIS)

    Kuramoto, Graciela Barrio

    2016-01-01

    The radioimmunotherapy (RIT) uses MAbs conjugated to radionuclides α or β - emitters, both for therapy. Your treatment is based on the irradiation and tumor destruction, preserving the normal organs as the excess radiation. Radionuclides β - emitters as 131 I, 90 Y, 188 Re 177 Lu and are useful for the development of therapeutic radiopharmaceuticals and, when coupled with MAb and Anti-CD20 it is important mainly for the treatment of non-Hodgkin's lymphomas (NHL). 188 Re (E β = 2.12 MeV; E γ = 155 keV; t1/2 = 16.9 h) is an attractive radionuclide for RIT. However, 188 Re can be obtained from a radionuclide generator of 188 W/ 188 Re, commercially available, making it convenient for use in research and for clinical routine. The CR of IPEN has a project aimed at the production of radiopharmaceutical 188 Re-Anti-CD20, where the radionuclide can be obtained from a generator system 188 W/ 188 Re. With this proposed a study to assess the efficiency of this labeling technique for treatment in accordance compartmental and dosimetry. The objective of this study was to compare the marking of anti-CD20 MAb with 188 Re with the marking of the antibody with 90 Y, 131 I, 177 Lu and 99m Tc (for their similar chemical characteristics) and 211 At, 213 Bi, 223 Ra and 225 Ac); through the study of labeling techniques reported in literature, the proposal of a compartmental model to evaluate its pharmacokinetic and dosimetric studies, high interest for therapy. The result of the study shows a favorable kinetics for 188 Re, by their physical and chemical characteristics compared to the other evaluated radionuclides. The compartment proposed study describes the metabolism of 188 Reanti- CD20 through a compartment mammillary model, which by their pharmacokinetic analysis, performed compared to products emitters β -131 I-labeled anti CD20, 177 Luanti- CD20, the γ emitter 99m Tc-Anti-CD20 and α emitter 211 At-Anti-CD20 presented a elimination constant of approximately 0.05 hours

  15. Modelling central metabolic fluxes by constraint-based optimization reveals metabolic reprogramming of developing Solanum lycopersicum (tomato) fruit.

    Science.gov (United States)

    Colombié, Sophie; Nazaret, Christine; Bénard, Camille; Biais, Benoît; Mengin, Virginie; Solé, Marion; Fouillen, Laëtitia; Dieuaide-Noubhani, Martine; Mazat, Jean-Pierre; Beauvoit, Bertrand; Gibon, Yves

    2015-01-01

    Modelling of metabolic networks is a powerful tool to analyse the behaviour of developing plant organs, including fruits. Guided by our current understanding of heterotrophic metabolism of plant cells, a medium-scale stoichiometric model, including the balance of co-factors and energy, was constructed in order to describe metabolic shifts that occur through the nine sequential stages of Solanum lycopersicum (tomato) fruit development. The measured concentrations of the main biomass components and the accumulated metabolites in the pericarp, determined at each stage, were fitted in order to calculate, by derivation, the corresponding external fluxes. They were used as constraints to solve the model by minimizing the internal fluxes. The distribution of the calculated fluxes of central metabolism were then analysed and compared with known metabolic behaviours. For instance, the partition of the main metabolic pathways (glycolysis, pentose phosphate pathway, etc.) was relevant throughout fruit development. We also predicted a valid import of carbon and nitrogen by the fruit, as well as a consistent CO2 release. Interestingly, the energetic balance indicates that excess ATP is dissipated just before the onset of ripening, supporting the concept of the climacteric crisis. Finally, the apparent contradiction between calculated fluxes with low values compared with measured enzyme capacities suggest a complex reprogramming of the metabolic machinery during fruit development. With a powerful set of experimental data and an accurate definition of the metabolic system, this work provides important insight into the metabolic and physiological requirements of the developing tomato fruits. © 2014 The Authors The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

  16. In silico strain optimization by adding reactions to metabolic models.

    Science.gov (United States)

    Correia, Sara; Rocha, Miguel

    2012-07-24

    Nowadays, the concerns about the environment and the needs to increase the productivity at low costs, demand for the search of new ways to produce compounds with industrial interest. Based on the increasing knowledge of biological processes, through genome sequencing projects, and high-throughput experimental techniques as well as the available computational tools, the use of microorganisms has been considered as an approach to produce desirable compounds. However, this usually requires to manipulate these organisms by genetic engineering and/ or changing the enviromental conditions to make the production of these compounds possible. In many cases, it is necessary to enrich the genetic material of those microbes with hereologous pathways from other species and consequently adding the potential to produce novel compounds. This paper introduces a new plug-in for the OptFlux Metabolic Engineering platform, aimed at finding suitable sets of reactions to add to the genomes of selected microbes (wild type strain), as well as finding complementary sets of deletions, so that the mutant becomes able to overproduce compounds with industrial interest, while preserving their viability. The necessity of adding reactions to the metabolic model arises from existing gaps in the original model or motivated by the productions of new compounds by the organism. The optimization methods used are metaheuristics such as Evolutionary Algorithms and Simulated Annealing. The usefulness of this plug-in is demonstrated by a case study, regarding the production of vanillin by the bacterium E. coli.

  17. Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism.

    Science.gov (United States)

    Fleming, R M T; Thiele, I; Provan, G; Nasheuer, H P

    2010-06-07

    The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in Escherichia coli and compare favourably with in silico prediction by flux balance analysis. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  18. Impact of prebiotics on metabolic and behavioral alterations in a mouse model of metabolic syndrome.

    Science.gov (United States)

    de Cossío, Lourdes Fernández; Fourrier, Célia; Sauvant, Julie; Everard, Amandine; Capuron, Lucile; Cani, Patrice D; Layé, Sophie; Castanon, Nathalie

    2017-08-01

    Mounting evidence shows that the gut microbiota, an important player within the gut-brain communication axis, can affect metabolism, inflammation, brain function and behavior. Interestingly, gut microbiota composition is known to be altered in patients with metabolic syndrome (MetS), who also often display neuropsychiatric symptoms. The use of prebiotics, which beneficially alters the microbiota, may therefore be a promising way to potentially improve physical and mental health in MetS patients. This hypothesis was tested in a mouse model of MetS, namely the obese and type-2 diabetic db/db mice, which display emotional and cognitive alterations associated with changes in gut microbiota composition and hippocampal inflammation compared to their lean db/+ littermates. We assessed the impact of chronic administration (8weeks) of prebiotics (oligofructose) on both metabolic (body weight, food intake, glucose homeostasis) and behavioral (increased anxiety-like behavior and impaired spatial memory) alterations characterizing db/db mice, as well as related neurobiological correlates, with particular attention to neuroinflammatory processes. Prebiotic administration improved excessive food intake and glycemic dysregulations (glucose tolerance and insulin resistance) in db/db mice. This was accompanied by an increase of plasma anti-inflammatory cytokine IL-10 levels and hypothalamic mRNA expression of the anorexigenic cytokine IL-1β, whereas unbalanced mRNA expression of hypothalamic orexigenic (NPY) and anorexigenic (CART, POMC) peptides was unchanged. We also detected signs of improved blood-brain-barrier integrity in the hypothalamus of oligofructose-treated db/db mice (normalized expression of tight junction proteins ZO-1 and occludin). On the contrary, prebiotic administration did not improve behavioral alterations and associated reduction of hippocampal neurogenesis displayed by db/db mice, despite normalization of increased hippocampal IL-6 mRNA expression. Of note

  19. Metabolic modelling of polyhydroxyalkanoate copolymers production by mixed microbial cultures

    Directory of Open Access Journals (Sweden)

    Reis Maria AM

    2008-07-01

    Full Text Available Abstract Background This paper presents a metabolic model describing the production of polyhydroxyalkanoate (PHA copolymers in mixed microbial cultures, using mixtures of acetic and propionic acid as carbon source material. Material and energetic balances were established on the basis of previously elucidated metabolic pathways. Equations were derived for the theoretical yields for cell growth and PHA production on mixtures of acetic and propionic acid as functions of the oxidative phosphorylation efficiency, P/O ratio. The oxidative phosphorylation efficiency was estimated from rate measurements, which in turn allowed the estimation of the theoretical yield coefficients. Results The model was validated with experimental data collected in a sequencing batch reactor (SBR operated under varying feeding conditions: feeding of acetic and propionic acid separately (control experiments, and the feeding of acetic and propionic acid simultaneously. Two different feast and famine culture enrichment strategies were studied: (i either with acetate or (ii with propionate as carbon source material. Metabolic flux analysis (MFA was performed for the different feeding conditions and culture enrichment strategies. Flux balance analysis (FBA was used to calculate optimal feeding scenarios for high quality PHA polymers production, where it was found that a suitable polymer would be obtained when acetate is fed in excess and the feeding rate of propionate is limited to ~0.17 C-mol/(C-mol.h. The results were compared with published pure culture metabolic studies. Conclusion Acetate was more conducive toward the enrichment of a microbial culture with higher PHA storage fluxes and yields as compared to propionate. The P/O ratio was not only influenced by the selected microbial culture, but also by the carbon substrate fed to each culture, where higher P/O ratio values were consistently observed for acetate than propionate. MFA studies suggest that when mixtures of

  20. Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico.

    Science.gov (United States)

    McAnulty, Michael J; Yen, Jiun Y; Freedman, Benjamin G; Senger, Ryan S

    2012-05-14

    Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. A new method called "flux balance analysis with flux ratios (FBrAtio)" was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.

  1. Computer modelling of HT gas metabolism in humans

    International Nuclear Information System (INIS)

    Peterman, B.F.

    1982-01-01

    A mathematical model was developed to simulate the metabolism of HT gas in humans. The rate constants of the model were estimated by fitting the calculated curves to the experimental data by Pinson and Langham in 1957. The calculations suggest that the oxidation of HT gas (which probably occurs as a result of the enzymatic action of hydrogenase present in bacteria of human gut) occurs at a relatively low rate with a half-time of 10-12 hours. The inclusion of the dose due to the production of the HT oxidation product (HTO) in the soft tissues lowers the value of derived air concentration by about 50%. Furthermore the relationship between the concentration of HTO in urine and the dose to the lung from HT in the air in lungs is linear after short HT exposures, and hence HTO concentrations in urine can be used to estimate the upper limits on the lung dose from HT exposures. (author)

  2. Review of compartmental analysis in ecosystem science

    International Nuclear Information System (INIS)

    O'Neill, R.V.

    1978-01-01

    The compartment model has a large number of applications in ecosystem science. An attempt is made to outline the problem areas and objectives for which this type of model has particular advantages. The areas identified are an adequate model of tracer movement through an undisturbed but non-equilibrium ecosystem; an adequate model of the movement of material in greater than tracer quantity through an ecosystem near steady state; a minimal model based on limited data; a tool for extrapolating past trends; a framework for the summarization of large data sets; and a theoretical tool for exploring and comparing limited aspects of ecosystem dynamics. The review is set in an historical perspective which helps explain why these models were adopted in ecology. References are also provided to literature which documents available mathematical techniques in an ecological context

  3. Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

    Directory of Open Access Journals (Sweden)

    Sriram Chandrasekaran

    2017-12-01

    Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

  4. Rifte Guaritas basin compartmentation in Camaqua

    International Nuclear Information System (INIS)

    Preissler, A; Rolim, S; Philipp, R.

    2010-01-01

    The study contributes to the knowledge of the tectonic evolution of the Guaritas rift basin in Camaqua. Were used aero magnetic geophysical data for modeling the geometry and the depth of the structures and geological units. The research was supported in processing and interpretation of Aster images (EOS-Terra), which were extracted from geophysical models and digital image

  5. Interreligious dialogue: Moving between compartmentalization and complexity

    Directory of Open Access Journals (Sweden)

    Anne Hege Grung

    2011-05-01

    Full Text Available Interreligious dialogues as organized activities establish religious difference among its participants as a premise. This article discusses how various ways of signifying religious difference in interreligious dialogues can impact culturally by looking at the dynamics between the dialogues’ ‘insides’ and ‘outsides’, especially regarding the ways in which differences are conceptualized. The current criticism of interreligious dialogue and the current perspectives on the dialogues’ alleged effects on conceptualizing differences are examined in the examples presented in this article. Finally, two models of interreligious dialogue are suggested. First, a model where religious differences are apprehended as ‘constitutive’, and second, a model where religious differences are viewed as ‘challenge’. The first relates to a multicultural view of differences, and the second to a perspective of cultural complexity. Lastly, the two models are discussed in relation to the notion of strategic essentialism. Anne Hege Grung is a researcher at the Faculty of Theology, University of Oslo.

  6. Brain glucose metabolism in an animal model of depression.

    Science.gov (United States)

    Detka, J; Kurek, A; Kucharczyk, M; Głombik, K; Basta-Kaim, A; Kubera, M; Lasoń, W; Budziszewska, B

    2015-06-04

    An increasing number of data support the involvement of disturbances in glucose metabolism in the pathogenesis of depression. We previously reported that glucose and glycogen concentrations in brain structures important for depression are higher in a prenatal stress model of depression when compared with control animals. A marked rise in the concentrations of these carbohydrates and glucose transporters were evident in prenatally stressed animals subjected to acute stress and glucose loading in adulthood. To determine whether elevated levels of brain glucose are associated with a change in its metabolism in this model, we assessed key glycolytic enzymes (hexokinase, phosphofructokinase and pyruvate kinase), products of glycolysis, i.e., pyruvate and lactate, and two selected enzymes of the tricarboxylic acid cycle (pyruvate dehydrogenase and α-ketoglutarate dehydrogenase) in the hippocampus and frontal cortex. Additionally, we assessed glucose-6-phosphate dehydrogenase activity, a key enzyme in the pentose phosphate pathway (PPP). Prenatal stress increased the levels of phosphofructokinase, an important glycolytic enzyme, in the hippocampus and frontal cortex. However, prenatal stress had no effect on hexokinase or pyruvate kinase levels. The lactate concentration was elevated in prenatally stressed rats in the frontal cortex, and pyruvate levels remained unchanged. Among the tricarboxylic acid cycle enzymes, prenatal stress decreased the level of pyruvate dehydrogenase in the hippocampus, but it had no effect on α-ketoglutarate dehydrogenase. Like in the case of glucose and its transporters, also in the present study, differences in markers of glucose metabolism between control animals and those subjected to prenatal stress were not observed under basal conditions but in rats subjected to acute stress and glucose load in adulthood. Glucose-6-phosphate dehydrogenase activity was not reduced by prenatal stress but was found to be even higher in animals exposed to

  7. Compartmental analysis and dosimetric aspects applied to cholesterol with {sup 3}H labeled; Analise compartimental e aspectos dosimetricos aplicados ao colesterol marcado com {sup 3}H

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira, Adriano dos Santos

    2015-07-01

    Cardiovascular diseases (CVDs) are one of the major reasons of death around the world according to the World Health Organization (WHO). It is well known that changes in levels of plasma lipoproteins, which are responsible for the transport of cholesterol into the bloodstream, are associated with cardiovascular diseases. For this reason to know the biokinetic parameters of plasma lipoproteins and quantifies them is important to correct and deep understanding about the diseases associated with these disorders. The main aim of this study is to provide a biokinetic model and estimate the radiometric doses for {sup 3}H-Cholesterol, a radioactive tracer widely used in physiological and metabolic studies. The model was based on [Schwartz et al. 2004] about the distribution of cholesterol by the lipoprotein and gastrointestinal model [ICRP 30, 1979]. The doses distribution in compartments of the model and other organs and tissues of a standard adult described in [ICRP 106, 2008] was calculated using MIRD method (Medical Internal Radiation Dose) and compartmental analysis using the computer program Matlab®. The dose coefficients were estimated for a standard phantom man (73 kg) described in [ICRP 60, 1991]. The estimated doses for both model and for other organs were low and did not exceed the highest dose obtained that was in the upper large intestine, as 44,8 μGy these parameters will assist in ethics committee's opinions on the use of works that use the {sup 3}H-cholesterol which radioactive tracer. (author)

  8. Parameterization of a ruminant model of phosphorus digestion and metabolism.

    Science.gov (United States)

    Feng, X; Knowlton, K F; Hanigan, M D

    2015-10-01

    The objective of the current work was to parameterize the digestive elements of the model of Hill et al. (2008) using data collected from animals that were ruminally, duodenally, and ileally cannulated, thereby providing a better understanding of the digestion and metabolism of P fractions in growing and lactating cattle. The model of Hill et al. (2008) was fitted and evaluated for adequacy using the data from 6 animal studies. We hypothesized that sufficient data would be available to estimate P digestion and metabolism parameters and that these parameters would be sufficient to derive P bioavailabilities of a range of feed ingredients. Inputs to the model were dry matter intake; total feed P concentration (fPtFd); phytate (Pp), organic (Po), and inorganic (Pi) P as fractions of total P (fPpPt, fPoPt, fPiPt); microbial growth; amount of Pi and Pp infused into the omasum or ileum; milk yield; and BW. The available data were sufficient to derive all model parameters of interest. The final model predicted that given 75 g/d of total P input, the total-tract digestibility of P was 40.8%, Pp digestibility in the rumen was 92.4%, and in the total-tract was 94.7%. Blood P recycling to the rumen was a major source of Pi flow into the small intestine, and the primary route of excretion. A large proportion of Pi flowing to the small intestine was absorbed; however, additional Pi was absorbed from the large intestine (3.15%). Absorption of Pi from the small intestine was regulated, and given the large flux of salivary P recycling, the effective fractional small intestine absorption of available P derived from the diet was 41.6% at requirements. Milk synthesis used 16% of total absorbed P, and less than 1% was excreted in urine. The resulting model could be used to derive P bioavailabilities of commonly used feedstuffs in cattle production. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  9. A Numerical Simulation for a Deterministic Compartmental ...

    African Journals Online (AJOL)

    In this work, an earlier deterministic mathematical model of HIV/AIDS is revisited and numerical solutions obtained using Eulers numerical method. Using hypothetical values for the parameters, a program was written in VISUAL BASIC programming language to generate series for the system of difference equations from the ...

  10. Field Testing of Compartmentalization Methods for Multifamily Construction

    Energy Technology Data Exchange (ETDEWEB)

    Ueno, K. [Building Science Corporation, Westford, MA (United States); Lstiburek, J. [Building Science Corporation, Westford, MA (United States)

    2015-03-01

    The 2012 IECC has an airtightness requirement of 3 air changes per hour at 50 Pascals test pressure for both single-family and multifamily construction in Climate Zones 3-8. Other programs (LEED, ASHRAE 189, ASHRAE 62.2) have similar or tighter compartmentalization requirements, driving the need for easier and more effective methods of compartmentalization in multifamily buildings. Builders and practitioners have found that fire-resistance rated wall assemblies are a major source of difficulty in air sealing/compartmentalization, particularly in townhouse construction. This problem is exacerbated when garages are “tucked in” to the units and living space is located over the garages. In this project, Building Science Corporation examined the taping of exterior sheathing details to improve air sealing results in townhouse and multifamily construction, when coupled with a better understanding of air leakage pathways. Current approaches are cumbersome, expensive, time consuming, and ineffective; these details were proposed as a more effective and efficient method. The effectiveness of these air sealing methods was tested with blower door testing, including “nulled” or “guarded” testing (adjacent units run at equal test pressure to null out inter-unit air leakage, or “pressure neutralization”). Pressure diagnostics were used to evaluate unit-to-unit connections and series leakage pathways (i.e., air leakage from exterior, into the fire-resistance rated wall assembly, and to the interior).

  11. Prediction of lithium-ion battery capacity with metabolic grey model

    International Nuclear Information System (INIS)

    Chen, Lin; Lin, Weilong; Li, Junzi; Tian, Binbin; Pan, Haihong

    2016-01-01

    Given the popularity of Lithium-ion batteries in EVs (electric vehicles), predicting the capacity quickly and accurately throughout a battery's full life-time is still a challenging issue for ensuring the reliability of EVs. This paper proposes an approach in predicting the varied capacity with discharge cycles based on metabolic grey theory and consider issues from two perspectives: 1) three metabolic grey models will be presented, including MGM (metabolic grey model), MREGM (metabolic Residual-error grey model), and MMREGM (metabolic Markov-residual-error grey model); 2) the universality of these models will be explored under different conditions (such as various discharge rates and temperatures). Furthermore, the research findings in this paper demonstrate the excellent performance of the prediction depending on the three models; however, the precision of the MREGM model is inferior compared to the others. Therefore, we have obtained the conclusion in which the MGM model and the MMREGM model have excellent performances in predicting the capacity under a variety of load conditions, even using few data points for modeling. Also, the universality of the metabolic grey prediction theory is verified by predicting the capacity of batteries under different discharge rates and different temperatures. - Highlights: • The metabolic mechanism is introduced in a grey system for capacity prediction. • Three metabolic grey models are presented and studied. • The universality of these models under different conditions is assessed. • A few data points are required for predicting the capacity with these models.

  12. In vivo kinematics of a robot-assisted uni- and multi-compartmental knee arthroplasty.

    Science.gov (United States)

    Watanabe, Toshifumi; Abbasi, Ali Z; Conditt, Michael A; Christopher, Jennifer; Kreuzer, Stefan; Otto, Jason K; Banks, Scott A

    2014-07-01

    There is great interest in providing reliable and durable treatments for one- and two-compartment arthritic degeneration of the cruciate-ligament intact knee. One approach is to resurface only the diseased compartments with discrete unicompartmental components, retaining the undamaged compartment(s). However, placing multiple small implants into the knee presents a greater surgical challenge than total knee arthroplasty, so it is not certain that the natural knee mechanics can be maintained or restored. The goal of this study was to determine whether near-normal knee kinematics can be obtained with a robot-assisted multi-compartmental knee arthroplasty. Thirteen patients with 15 multi-compartmental knee arthroplasties using haptic robotic-assisted bone preparation were involved in this study. Nine subjects received a medial unicompartmental knee arthroplasty (UKA), three subjects received a medial UKA and patellofemoral (PF) arthroplasty, and three subjects received medial and lateral bi-unicondylar arthroplasty. Knee motions were recorded using video-fluoroscopy an average of 13 months (6-29 months) after surgery during stair and kneeling activities. The three-dimensional position and orientation of the implant components were determined using model-image registration techniques. Knee kinematics during maximum flexion kneeling showed femoral external rotation and posterior lateral condylar translation. All knees showed femoral external rotation and posterior condylar translation with flexion during the step activity. Knees with medial UKA and PF arthroplasty showed the most femoral external rotation and posterior translation, and knees with bicondylar UKA showed the least. Knees with accurately placed uni- or bi-compartmental arthroplasty exhibited stable knee kinematics consistent with intact and functioning cruciate ligaments. The patterns of tibiofemoral motion were more similar to natural knees than commonly has been observed in knees with total knee

  13. Incorporating Protein Biosynthesis into the Saccharomyces cerevisiae Genome-scale Metabolic Model

    DEFF Research Database (Denmark)

    Olivares Hernandez, Roberto

    Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been construc......Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been...

  14. Compartmental architecture and dynamics of hematopoiesis.

    Directory of Open Access Journals (Sweden)

    David Dingli

    Full Text Available BACKGROUND: Blood cell formation is maintained by the replication of hematopoietic stem cells (HSC that continuously feed downstream "compartments" where amplification and differentiation of cells occurs, giving rise to all blood lineages. Whereas HSC replicate slowly, committed cells replicate faster as they become more differentiated. METHODOLOGY/SIGNIFICANT FINDING: We propose a multi-compartment model of hematopoiesis, designed on the principle of cell flow conservation under stationary conditions. Cells lost from one compartment due to differentiation are replaced by cells from the upstream compartment. We assume that there is a constant relationship between cell input and output in each compartment and fix the single parameter of the model using data available for granulocyte maturation. We predict that approximately 31 mitotic events separate the HSC from the mature cells observed in the circulation. Besides estimating the number of compartments, our model allows us to estimate the size of each compartment, the rate of cell replication within each compartment, the mean time a given cell type contributes to hematopoiesis, the amplification rate in each compartment, as well as the mean time separating stem-cell replication and mature blood-cell formation. CONCLUSIONS: Despite its simplicity, the model agrees with the limited in vivo data available and can make testable predictions. In particular, our prediction of the average lifetime of a PIG-A mutated clone agrees closely with the experimental results available for the PIG-A gene mutation in healthy adults. The present elucidation of the compartment structure and dynamics of hematopoiesis may prove insightful in further understanding a variety of hematopoietic disorders.

  15. A new kinetic model for human iodine metabolism

    International Nuclear Information System (INIS)

    Ficken, V.J.; Allen, E.W.; Adams, G.D.

    1985-01-01

    A new kinetic model of iodine metabolism incorporating preferential organification of tyrosil (TYR) residues of thyroglobulin is developed and evaluated for euthyroid (n=5) and hyperthyroid (n=11) subjects. Iodine and peripheral T4 metabolims were measured with oral /sup 131/I-NaI and intravenous /sup 125/I-74 respectively. Data (obtained over 10 days) and kinetic model are analyzed using the SAAM27 program developed by Berman (1978). Compartment rate constants (mean rate per hour +- ISD) are tabulated in this paper. Thyroid and renal iodide clearance compare favorably with values reported in the literature. TYR rate constants were not unique; however, values obtained are within the range of rate constants determined from the invitro data reported by others. Intraluminal iodine as coupled TYR is predicted to be 21% for euthyroid and 59% for hyperthyroid subjects compared to analytical chemical methods of 30% and 51% respectively determined elsewhere. The authors plan to evaluate this model as a method of predicting the thyroid radiation dose from orally administered I/sup 131/

  16. Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

    Science.gov (United States)

    Aurich, Maike K; Thiele, Ines

    2016-01-01

    Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

  17. Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

    Energy Technology Data Exchange (ETDEWEB)

    Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M.; Young, Vincent B.; Jansson, Janet K.; Fredricks, David N.; Borenstein, Elhanan; Sanchez, Laura M.

    2015-12-22

    ABSTRACT

    Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in

  18. The obese Göttingen minipig as a model of the metabolic syndrome

    DEFF Research Database (Denmark)

    Johansen, T.; Malmlöf, K.; Hansen, Harald S.

    2001-01-01

    The objective of the study reported here was to induce obesity in the female Göttingen minipig to establish a model of the human metabolic syndrome. Nine- to ten-month-old female Göttingen minipigs received a high-fat high-energy (HFE) diet or a low-fat, low-energy (LFE) diet. The energy contents...... of the metabolic impairments seen in obese humans, and may thus serve as a model of the metabolic syndrome....

  19. In silico analysis of human metabolism: Reconstruction, contextualization and application of genome-scale models

    DEFF Research Database (Denmark)

    Geng, Jun; Nielsen, Jens

    2017-01-01

    The arising prevalence of metabolic diseases calls for a holistic approach for analysis of the underlying nature of abnormalities in cellular functions. Through mathematic representation and topological analysis of cellular metabolism, GEnome scale metabolic Models (GEMs) provide a promising fram...... that correctly describe interactions between cells or tissues, and we therefore discuss how GEMs can be integrated with blood circulation models. Finally, we end the review with proposing some possible future research directions....

  20. Considerations on pig models for appetite, metabolic syndrome and obese type 2 diabetes: Form food intake to metabolic disease

    NARCIS (Netherlands)

    Koopmans, S.J.; Schuurman, T.

    2015-01-01

    (Mini)pigs have proven to be a valuable animal model in nutritional, metabolic and cardiovascular research and in some other biomedical research areas (toxicology, neurobiology). The large resemblance of (neuro)anatomy, the gastro-intestinal tract, body size, body composition, and the omnivorous

  1. Metabolic Engineering and Modeling of Metabolic Pathways to Improve Hydrogen Production by Photosynthetic Bacteria

    Energy Technology Data Exchange (ETDEWEB)

    Jiao, Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Navid, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-12-19

    traits act as the biocatalysts of the process designed to both enhance the system efficiency of CO2 fixation and the net hydrogen production rate. Additionally we applied metabolic engineering approaches guided by computational modeling for the chosen model microorganisms to enable efficient hydrogen production.

  2. Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel.

    Science.gov (United States)

    Dansirikul, Chantaratsamon; Choi, Malcolm; Duffull, Stephen B

    2005-06-01

    This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel spreadsheet was implemented with the use of Solver and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

  3. Mathematical basis for the measurement of absolute and fractional cardiac output with diffusible tracers by compartmental analysis methods

    International Nuclear Information System (INIS)

    Charkes, N.D.

    1984-01-01

    Using compartmental analysis methods, a mathematical basis is given for the measurement of absolute and fractional cardiac output with diffusible tracers. Cardiac output is shown to be the product of the blood volume and the sum of the rate constants of tracer egress from blood, modified by a factor reflecting transcapillary diffusibility, the transfer fraction. The return of tracer to the blood and distant (intracellular) events are shown to play no role in the solution. Fractional cardiac output is the ratio of the rate constant of tracer egress from blood to an organ, divided by the sum of the egress constants from blood. Predominantly extracellular ions such as sodium or bromide are best suited for this technique, although theoretically any diffusible tracer whose compartmental model can be solved may be used. It is shown that fractional cardiac output is independent of the transfer fraction, and therefore can be measured accurately by tracers which are not freely diffusible

  4. Drosophila as a Model to Study the Link between Metabolism and Cancer

    DEFF Research Database (Denmark)

    Herranz, Hector; Cohen, Stephen M.

    2017-01-01

    new approaches to therapy. Drosophila melanogaster is emerging as a valuable model to study multiple aspects of tumor formation and malignant transformation. In this review, we discuss the use of Drosophila as model to study how changes in cellular metabolism, as well as metabolic disease, contribute...

  5. Construction and analysis of the model of energy metabolism in E. coli.

    Directory of Open Access Journals (Sweden)

    Zixiang Xu

    Full Text Available Genome-scale models of metabolism have only been analyzed with the constraint-based modelling philosophy and there have been several genome-scale gene-protein-reaction models. But research on the modelling for energy metabolism of organisms just began in recent years and research on metabolic weighted complex network are rare in literature. We have made three research based on the complete model of E. coli's energy metabolism. We first constructed a metabolic weighted network using the rates of free energy consumption within metabolic reactions as the weights. We then analyzed some structural characters of the metabolic weighted network that we constructed. We found that the distribution of the weight values was uneven, that most of the weight values were zero while reactions with abstract large weight values were rare and that the relationship between w (weight values and v (flux values was not of linear correlation. At last, we have done some research on the equilibrium of free energy for the energy metabolism system of E. coli. We found that E(out (free energy rate input from the environment can meet the demand of E(ch(in (free energy rate dissipated by chemical process and that chemical process plays a great role in the dissipation of free energy in cells. By these research and to a certain extend, we can understand more about the energy metabolism of E. coli.

  6. The iDuo Bi-compartmental Knee Replacement: Our Early Experience.

    Directory of Open Access Journals (Sweden)

    Peter Jemmett

    2016-12-01

    Our early results suggest that the iDuo knee is a good option for those with isolated bi-compartmental disease and outcome scores are comparable with those reported for the BKA. This bi-compartmental design may bridge the gap between the uni-compartmental and total knee replacement. The choice between monolithic or modular designs remains in debate. We will continue to use this prosthesis for a carefully selected group of patients.

  7. Functional compartmentalization of the human superficial masseter muscle.

    Directory of Open Access Journals (Sweden)

    Rodrigo A Guzmán-Venegas

    Full Text Available Some muscles have demonstrated a differential recruitment of their motor units in relation to their location and the nature of the motor task performed; this involves functional compartmentalization. There is little evidence that demonstrates the presence of a compartmentalization of the superficial masseter muscle during biting. The aim of this study was to describe the topographic distribution of the activity of the superficial masseter (SM muscle's motor units using high-density surface electromyography (EMGs at different bite force levels. Twenty healthy natural dentate participants (men: 4; women: 16; age 20±2 years; mass: 60±12 kg, height: 163±7 cm were selected from 316 volunteers and included in this study. Using a gnathodynamometer, bites from 20 to 100% maximum voluntary bite force (MVBF were randomly requested. Using a two-dimensional grid (four columns, six electrodes located on the dominant SM, EMGs in the anterior, middle-anterior, middle-posterior and posterior portions were simultaneously recorded. In bite ranges from 20 to 60% MVBF, the EMG activity was higher in the anterior than in the posterior portion (p-value = 0.001.The center of mass of the EMG activity was displaced towards the posterior part when bite force increased (p-value = 0.001. The topographic distribution of EMGs was more homogeneous at high levels of MVBF (p-value = 0.001. The results of this study show that the superficial masseter is organized into three functional compartments: an anterior, a middle and a posterior compartment. However, this compartmentalization is only seen at low levels of bite force (20-60% MVBF.

  8. TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Jensen Paul A

    2011-09-01

    Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

  9. MicrobesFlux: a web platform for drafting metabolic models from the KEGG database

    Directory of Open Access Journals (Sweden)

    Feng Xueyang

    2012-08-01

    Full Text Available Abstract Background Concurrent with the efforts currently underway in mapping microbial genomes using high-throughput sequencing methods, systems biologists are building metabolic models to characterize and predict cell metabolisms. One of the key steps in building a metabolic model is using multiple databases to collect and assemble essential information about genome-annotations and the architecture of the metabolic network for a specific organism. To speed up metabolic model development for a large number of microorganisms, we need a user-friendly platform to construct metabolic networks and to perform constraint-based flux balance analysis based on genome databases and experimental results. Results We have developed a semi-automatic, web-based platform (MicrobesFlux for generating and reconstructing metabolic models for annotated microorganisms. MicrobesFlux is able to automatically download the metabolic network (including enzymatic reactions and metabolites of ~1,200 species from the KEGG database (Kyoto Encyclopedia of Genes and Genomes and then convert it to a metabolic model draft. The platform also provides diverse customized tools, such as gene knockouts and the introduction of heterologous pathways, for users to reconstruct the model network. The reconstructed metabolic network can be formulated to a constraint-based flux model to predict and analyze the carbon fluxes in microbial metabolisms. The simulation results can be exported in the SBML format (The Systems Biology Markup Language. Furthermore, we also demonstrated the platform functionalities by developing an FBA model (including 229 reactions for a recent annotated bioethanol producer, Thermoanaerobacter sp. strain X514, to predict its biomass growth and ethanol production. Conclusion MicrobesFlux is an installation-free and open-source platform that enables biologists without prior programming knowledge to develop metabolic models for annotated microorganisms in the KEGG

  10. Advanced Imaging Approaches to Characterize Stromal and Metabolic Changes in In Vivo Mammary Tumor Models

    Science.gov (United States)

    2015-02-01

    Bird , L. Yan, K. M. Vrotsos, K. W. Eliceiri, E. M. Vaughan, P. J. Keely, J. G. White, N. Ramanujam, Metabolic mapping of MCF10A human breast cells...1   Award Number: W81XWH-12-1-0025 TITLE: Advanced Imaging Approaches to Characterize Stromal and Metabolic Changes in In Vivo Mammary... Metabolic Changes in In Vivo Mammary Tumor Models 5b. GRANT NUMBER BC112240 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Betty Diamond 5d. PROJECT NUMBER

  11. GENOME-BASED MODELING AND DESIGN OF METABOLIC INTERACTIONS IN MICROBIAL COMMUNITIES

    Directory of Open Access Journals (Sweden)

    Radhakrishnan Mahadevan

    2012-10-01

    With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

  12. Compartmentation and equilibration of abscisic acid in isolated Xanthium cells

    International Nuclear Information System (INIS)

    Bray, E.A.; Zeevaart, J.A.D.

    1986-01-01

    The compartmentation of endogenous abscisic acid (ABA), applied (+/-)-[ 3 H]ABA, and (+/-)-trans-ABA was measured in isolated mesophyll cells of the Chicago strain of Xanthium strumarium L. The release of ABA to the medium in the presence or absence of DMSO was used to determine the equilibration of ABA in the cells. It was found that a greater percentage of the (+/-)-[ 3 H]ABA and the (+/-)-trans-ABA was released into the medium than of the endogenous ABA, indicating that applied ABA did not equilibrate with the endogenous material. Therefore, in further investigations only the compartmentation of endogenous ABA was studied. Endogenous ABA was released from Xanthium cells according to the pH gradients among the various cellular compartments. Thus, darkness, high external pH, KNO 2 , and drought-stress all increased the efflux of ABA from the cells. Efflux of ABA from the cells in the presence of 0.6 M mannitol occurred within 30 seconds, but only 8% of the endogenous material was released during the 20 minute treatment

  13. The monitoring of relative changes in compartmental compliances of brain

    International Nuclear Information System (INIS)

    Kim, Dong-Joo; Carrera, Emmanuel; Castellani, Gianluca; Zweifel, Christian; Smielewski, Peter; Pickard, John D; Czosnyka, Marek; Kasprowicz, Magdalena; Lavinio, Andrea; Sutcliffe, Michael P F

    2009-01-01

    The study aimed to develop a computational method for assessing relative changes in compartmental compliances within the brain: the arterial bed and the cerebrospinal space. The method utilizes the relationship between pulsatile components in the arterial blood volume, arterial blood pressure (ABP) and intracranial pressure (ICP). It was verified by using clinical recordings of intracranial pressure plateau waves, when massive vasodilatation accompanying plateau waves produces changes in brain compliances of the arterial bed (C a ) and compliance of the cerebrospinal space (C i ). Ten patients admitted after head injury with a median Glasgow Coma Score of 6 were studied retrospectively. ABP was directly monitored from the radial artery. Changes in the cerebral arterial blood volume were assessed using Transcranial Doppler (TCD) ultrasonography by digital integration of inflow blood velocity. During plateau waves, ICP increased (P = 0.001), CPP decreased (P = 0.001), ABP remained constant (P = 0.532), blood flow velocity decreased (P = 0.001). Calculated compliance of the arterial bed C a increased significantly (P = 0.001); compliance of the CSF space C i decreased (P = 0.001). We concluded that the method allows for continuous monitoring of relative changes in brain compartmental compliances. Plateau waves affect the balance between vascular and CSF compartments, which is reflected by the inverse change of compliance of the cerebral arterial bed and global compliance of the CSF space

  14. Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data

    Directory of Open Access Journals (Sweden)

    Kansuporn eSriyudthsak

    2016-05-01

    Full Text Available The high-throughput acquisition of metabolome data is greatly anticipated for the complete understanding of cellular metabolism in living organisms. A variety of analytical technologies have been developed to acquire large-scale metabolic profiles under different biological or environmental conditions. Time series data are useful for predicting the most likely metabolic pathways because they provide important information regarding the accumulation of metabolites, which implies causal relationships in the metabolic reaction network. Considerable effort has been undertaken to utilize these data for constructing a mathematical model merging system properties and quantitatively characterizing a whole metabolic system in toto. However, there are technical difficulties between benchmarking the provision and utilization of data. Although hundreds of metabolites can be measured, which provide information on the metabolic reaction system, simultaneous measurement of thousands of metabolites is still challenging. In addition, it is nontrivial to logically predict the dynamic behaviors of unmeasurable metabolite concentrations without sufficient information on the metabolic reaction network. Yet, consolidating the advantages of advancements in both metabolomics and mathematical modeling remain to be accomplished. This review outlines the conceptual basis of and recent advances in technologies in both the research fields. It also highlights the potential for constructing a large-scale mathematical model by estimating model parameters from time series metabolome data in order to comprehensively understand metabolism at the systems level.

  15. A Physiologically-Based Pharmacokinetic (PBPK) Model With Metabolic Interactions of Chloroform (CHCL3) and Trichloroethylene

    Science.gov (United States)

    Exposure to mixtures is frequent, but biologic pathways such as metabolic inhibition, are poorly understood. CHCl3 and TCE are model volatiles frequently co-occurring; combined exposure results in less than additive hepatotoxicity. Here, we explore the underlying metabolic inte...

  16. Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data.

    Science.gov (United States)

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

    2016-01-01

    The high-throughput acquisition of metabolome data is greatly anticipated for the complete understanding of cellular metabolism in living organisms. A variety of analytical technologies have been developed to acquire large-scale metabolic profiles under different biological or environmental conditions. Time series data are useful for predicting the most likely metabolic pathways because they provide important information regarding the accumulation of metabolites, which implies causal relationships in the metabolic reaction network. Considerable effort has been undertaken to utilize these data for constructing a mathematical model merging system properties and quantitatively characterizing a whole metabolic system in toto. However, there are technical difficulties between benchmarking the provision and utilization of data. Although, hundreds of metabolites can be measured, which provide information on the metabolic reaction system, simultaneous measurement of thousands of metabolites is still challenging. In addition, it is nontrivial to logically predict the dynamic behaviors of unmeasurable metabolite concentrations without sufficient information on the metabolic reaction network. Yet, consolidating the advantages of advancements in both metabolomics and mathematical modeling remain to be accomplished. This review outlines the conceptual basis of and recent advances in technologies in both the research fields. It also highlights the potential for constructing a large-scale mathematical model by estimating model parameters from time series metabolome data in order to comprehensively understand metabolism at the systems level.

  17. Computational Modelling of the Metabolic States Regulated by the Kinase Akt

    Directory of Open Access Journals (Sweden)

    Ettore eMosca

    2012-11-01

    Full Text Available Signal transduction pathways and gene regulation determine a major reorganization of metabolic activities in order to support cell proliferation. Protein Kinase B (PKB, also known as Akt, participates in the PI3K/Akt/mTOR pathway, a master regulator of aerobic glycolysis and cellular biosynthesis, two activities shown by both normal and cancer proliferating cells. Not surprisingly considering its relevance for cellular metabolism, Akt/PKB is often found hyperactive in cancer cells. In the last decade, many efforts have been made to improve the understanding of the control of glucose metabolism and the identification of a therapeutic window between proliferating cancer cells and proliferating normal cells. In this context, we have modelled the link between the PI3K/Akt/mTOR pathway, glycolysis, lactic acid production and nucleotide biosynthesis. We used a computational model in order to compare two metabolic states generated by the specific variation of the metabolic fluxes regulated by the activity of the PI3K/Akt/mTOR pathway. One of the two states represented the metabolism of a growing cancer cell characterised by aerobic glycolysis and cellular biosynthesis, while the other state represented the same metabolic network with a reduced glycolytic rate and a higher mitochondrial pyruvate metabolism, as reported in literature in relation to the activity of the PI3K/Akt/mTOR. Some steps that link glycolysis and pentose phosphate pathway revealed their importance for controlling the dynamics of cancer glucose metabolism.

  18. Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

    2015-01-01

    Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies....

  19. Transcriptome data modeling for targeted plant metabolic engineering.

    Science.gov (United States)

    Yonekura-Sakakibara, Keiko; Fukushima, Atsushi; Saito, Kazuki

    2013-04-01

    The massive data generated by omics technologies require the power of bioinformatics, especially network analysis, for data mining and doing data-driven biology. Gene coexpression analysis, a network approach based on comprehensive gene expression data using microarrays, is becoming a standard tool for predicting gene function and elucidating the relationship between metabolic pathways. Differential and comparative gene coexpression analyses suggest a change in coexpression relationships and regulators controlling common and/or specific biological processes. In conjunction with the newly emerging genome editing technology, network analysis integrated with other omics data should pave the way for robust and practical plant metabolic engineering. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. Modeling of Pharmaceutical Biotransformation by Enriched Nitrifying Culture under Different Metabolic Conditions

    DEFF Research Database (Denmark)

    Xu, Yifeng; Chen, Xueming; Yuan, Zhiguo

    2018-01-01

    Pharmaceutical removal could be significantly enhanced through cometabolism during nitrification processes. To date, pharmaceutical biotransformation models have not considered the formation of transformation products associated with the metabolic type of microorganisms. Here we report a comprehe......Pharmaceutical removal could be significantly enhanced through cometabolism during nitrification processes. To date, pharmaceutical biotransformation models have not considered the formation of transformation products associated with the metabolic type of microorganisms. Here we report...... a comprehensive model to describe and evaluate the biodegradation of pharmaceuticals and the formation of their biotransformation products by enriched nitrifying cultures. The biotransformation of parent compounds was linked to the microbial processes via cometabolism induced by ammonium-oxidizing bacteria (AOB......) growth, metabolism by AOB, cometabolism by heterotrophs (HET) growth, and metabolism by HET in the model framework. The model was calibrated and validated using experimental data from pharmaceutical biodegradation experiments at realistic levels, taking two pharmaceuticals as examples, i.e., atenolol...

  1. Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production.

    Directory of Open Access Journals (Sweden)

    Caroline Colijn

    2009-08-01

    Full Text Available Metabolism is central to cell physiology, and metabolic disturbances play a role in numerous disease states. Despite its importance, the ability to study metabolism at a global scale using genomic technologies is limited. In principle, complete genome sequences describe the range of metabolic reactions that are possible for an organism, but cannot quantitatively describe the behaviour of these reactions. We present a novel method for modeling metabolic states using whole cell measurements of gene expression. Our method, which we call E-Flux (as a combination of flux and expression, extends the technique of Flux Balance Analysis by modeling maximum flux constraints as a function of measured gene expression. In contrast to previous methods for metabolically interpreting gene expression data, E-Flux utilizes a model of the underlying metabolic network to directly predict changes in metabolic flux capacity. We applied E-Flux to Mycobacterium tuberculosis, the bacterium that causes tuberculosis (TB. Key components of mycobacterial cell walls are mycolic acids which are targets for several first-line TB drugs. We used E-Flux to predict the impact of 75 different drugs, drug combinations, and nutrient conditions on mycolic acid biosynthesis capacity in M. tuberculosis, using a public compendium of over 400 expression arrays. We tested our method using a model of mycolic acid biosynthesis as well as on a genome-scale model of M. tuberculosis metabolism. Our method correctly predicts seven of the eight known fatty acid inhibitors in this compendium and makes accurate predictions regarding the specificity of these compounds for fatty acid biosynthesis. Our method also predicts a number of additional potential modulators of TB mycolic acid biosynthesis. E-Flux thus provides a promising new approach for algorithmically predicting metabolic state from gene expression data.

  2. Dynamic metabolic modeling of heterotrophic and mixotrophic microalgal growth on fermentative wastes.

    Directory of Open Access Journals (Sweden)

    Caroline Baroukh

    2017-06-01

    Full Text Available Microalgae are promising microorganisms for the production of numerous molecules of interest, such as pigments, proteins or triglycerides that can be turned into biofuels. Heterotrophic or mixotrophic growth on fermentative wastes represents an interesting approach to achieving higher biomass concentrations, while reducing cost and improving the environmental footprint. Fermentative wastes generally consist of a blend of diverse molecules and it is thus crucial to understand microalgal metabolism in such conditions, where switching between substrates might occur. Metabolic modeling has proven to be an efficient tool for understanding metabolism and guiding the optimization of biomass or target molecule production. Here, we focused on the metabolism of Chlorella sorokiniana growing heterotrophically and mixotrophically on acetate and butyrate. The metabolism was represented by 172 metabolic reactions. The DRUM modeling framework with a mildly relaxed quasi-steady-state assumption was used to account for the switching between substrates and the presence of light. Nine experiments were used to calibrate the model and nine experiments for the validation. The model efficiently predicted the experimental data, including the transient behavior during heterotrophic, autotrophic, mixotrophic and diauxic growth. It shows that an accurate model of metabolism can now be constructed, even in dynamic conditions, with the presence of several carbon substrates. It also opens new perspectives for the heterotrophic and mixotrophic use of microalgae, especially for biofuel production from wastes.

  3. Reproductive and metabolic phenotype of a mouse model of PCOS

    NARCIS (Netherlands)

    E. Leonie (E.); A.F. van Houten (A.); P. Kramer (Piet); A. McLuskey; B. Karels (Bas); A.P.N. Themmen (Axel); J.A. Visser (Jenny)

    2012-01-01

    textabstractPolycystic ovary syndrome (PCOS), the most common endocrine disorder in women in their reproductive age, is characterized by both reproductive and metabolic features. Recent studies in human, nonhuman primates, and sheep suggest that hyperandrogenism plays an important role in the

  4. Glucocorticoids, metabolic adaptations and recovery : studies in specific mouse models

    NARCIS (Netherlands)

    Auvinen, Hanna Elina

    2013-01-01

    Today’s Western society and work promotes a sedentary lifestyle. This, coupled with high caloric food availability has increased obesity followed by an increased prevalence of the metabolic syndrome (MetS), type 2 diabetes (T2D) and cardiovascular diseases (CVD). Epidemiological data show a clear

  5. Energetic Metabolism and Biochemical Adaptation: A Bird Flight Muscle Model

    Science.gov (United States)

    Rioux, Pierre; Blier, Pierre U.

    2006-01-01

    The main objective of this class experiment is to measure the activity of two metabolic enzymes in crude extract from bird pectoral muscle and to relate the differences to their mode of locomotion and ecology. The laboratory is adapted to stimulate the interest of wildlife management students to biochemistry. The enzymatic activities of cytochrome…

  6. Measurement of renal glomerular filtration rate using labelled substances with compartmental analysis

    International Nuclear Information System (INIS)

    Eberstadt, P.L.

    1981-10-01

    Using a model for the two-compartmental open system and experiments on animals (rabbits and dogs) as well as on human healthy volunteers, an attempt was made to study the advantages and limitations of different radionuclide methods for glomerular filtration rate determination. Labelled compounds used in different combinations were: 3 H-inulin, sup(113m)In-EDTA, 131 I-iothalamate, sup(99m)Tc-DTPA and 14 C-creatinine. The results of the study lead to some working hypotheses concerning the value of creatinine and other labelled substances in the measurement of glomerular filtration rate in clinical practice. The advantages and disadvantages of individual methods summarized in the final report are generally in agreement with the present views of many research workers. Also the hypothesis can be justified that the different labelled compounds which have been studied might be handled independently by the membranes involved but at the long run produce similar homeostatic balance

  7. An in vitro model for screening estrogen activity of environmental samples after metabolism

    Energy Technology Data Exchange (ETDEWEB)

    Chahbane, N.; Schramm, K.W. [GSF - Forschungszentrum fuer Umwelt und Gesundheit Neuherberg GmbH, Oberschleissheim (Germany). Inst. fuer Oekologische Chemie; Kettrup, A. [Technische Univ. Muenchen, Freising (Germany). Lehrstuhl fuer Oekologische Chemie

    2004-09-15

    For a few years, yeast estrogen assay (YES) was accepted as a reliable and economic model for screening of environmental estrogens. Though the chemicals directly act with estrogen receptor (ER) can be filtered out by this model, there are still chemicals act with ER only after metabolism and some chemicals eliminate their estrogen activities after metabolism. That is to say, their metabolites exert or have stronger estrogen activities than themselves, which can be called bio-activation. In this case, for the lack of the metabolism enzyme system as human and other animals, only the assay with recombinant yeast cells is insufficient. So, it is necessary to combine the YES with metabolism procedure to evaluate the estrogen activities of these chemicals. The most common method used currently for in vitro metabolic activation in mutagenicity testing and also be applied to the estrogen screening field is S-9 mixture. Also, there is an attempt to develop a chemical model for cytochrome P450 as a bio-mimetic metabolic activation system. All these methods can be used as in vitro models for metabolism. Compare with these models, using whole H4II E cells for metabolism is an alternative and with superiorities. It has the excellence of short experiment period as all other in vitro models, but is much more close to the real surroundings as in vivo. Furthermore, the activity of 7-ethoxyresorufin-O-deethylase (EROD) can be easily measured during the whole incubation period for us to discuss the metabolic activities in a quantitative foundation, not only in qualitative. Methoxychlor is one of the chemicals with bio-activation ability. When directly used in the YES, it shows weak estrogen activity. But a main metabolite of methoxychlor, 2,2-bis (p-hydroxyphenyl) - 1,1,1-trichloroethane (HPTE) is a known estrogen mimic. For the long time using methoxychlor as a pesticide and its clear background, it is an ideal chemical to establish this in vitro system.

  8. In silico method for modelling metabolism and gene product expression at genome scale

    Energy Technology Data Exchange (ETDEWEB)

    Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.

    2012-07-03

    Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

  9. Investigating genotype-phenotype relationships in Saccharomyces cerevisiae metabolic network through stoichiometric modeling

    DEFF Research Database (Denmark)

    Brochado, Ana Rita

    processes. Metabolism is an extensively studied and characterised subcellular system, for which several modeling approaches have been proposed over the last 20 years. Nowadays, stoichiometric modeling of metabolism is done at the genome scale and it has diverse applications, many of them for helping....... This chapter aims at providing the reader with relevant state-of-the-art information concerning Systems Biology, Genome-Scale Metabolic Modeling and Metabolic Engineering. Particular attention is given to the yeast Saccharomyces cerevisiae, the eukaryotic model organism used thought the thesis.......A holistic view of the cell is fundamental for gaining insights into genotype to phenotype relationships. Systems Biology is a discipline within Biology, which uses such holistic approach by focusing on the development and application of tools for studying the structure and dynamics of cellular...

  10. 14C and tritium dynamics in wild mammals: a metabolic model

    International Nuclear Information System (INIS)

    Galeriu, D.; Beresford, N.A.; Melintescu, A.; Crout, N.M.J.; Takeda, H.

    2004-01-01

    The protection of biota from ionising radiations needs reliable predictions of radionuclide dynamics in wild animals. Data specific for many wild animals radionuclide combinations is lacking and a number of approaches including allometry have been proposed to address this. However, for 14 C and tritium, which are integral components of animals tissues and their diets, a different approach is needed in the absence of experimental data. Here we propose a metabolically based model which can be parameterized predominantly on the basis of published metabolic data. We begin with a metabolic definition of the 14 C and OBT loss rate (assumed to be the same) from the whole body and also specific organs, using available information on field metabolic rate and body composition. The mammalian body is conceptually partitioned into compartments (body water, viscera, adipose, muscle, blood and remainder) and a simple model defined using net maintenance and growth needs of mammals. Intake and excretion, and transfer to body water are modelled using basic metabolic knowledge and published relationships. The model is tested with data from studies using rats and sheep. It provides a reliable prediction for whole body and muscle activity concentrations without the requirement for any calibration specific to 3 H and 14 C. Predictions from the model for representative wild mammals (as selected to be reference organisms within international programmes) are presented. Potential developments of a metabolic model for birds and the application of our work to human food chain modelling are also discussed. (author)

  11. Predicting growth of the healthy infant using a genome scale metabolic model.

    Science.gov (United States)

    Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

    2017-01-01

    An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.

  12. Synapse-specific and compartmentalized expression of presynaptic homeostatic potentiation

    Science.gov (United States)

    Li, Xiling; Goel, Pragya; Chen, Catherine; Angajala, Varun; Chen, Xun

    2018-01-01

    Postsynaptic compartments can be specifically modulated during various forms of synaptic plasticity, but it is unclear whether this precision is shared at presynaptic terminals. Presynaptic homeostatic plasticity (PHP) stabilizes neurotransmission at the Drosophila neuromuscular junction, where a retrograde enhancement of presynaptic neurotransmitter release compensates for diminished postsynaptic receptor functionality. To test the specificity of PHP induction and expression, we have developed a genetic manipulation to reduce postsynaptic receptor expression at one of the two muscles innervated by a single motor neuron. We find that PHP can be induced and expressed at a subset of synapses, over both acute and chronic time scales, without influencing transmission at adjacent release sites. Further, homeostatic modulations to CaMKII, vesicle pools, and functional release sites are compartmentalized and do not spread to neighboring pre- or post-synaptic structures. Thus, both PHP induction and expression mechanisms are locally transmitted and restricted to specific synaptic compartments. PMID:29620520

  13. Compartmentalization of NO signaling cascade in skeletal muscles

    International Nuclear Information System (INIS)

    Buchwalow, Igor B.; Minin, Evgeny A.; Samoilova, Vera E.; Boecker, Werner; Wellner, Maren; Schmitz, Wilhelm; Neumann, Joachim; Punkt, Karla

    2005-01-01

    Skeletal muscle functions regulated by NO are now firmly established. However, the literature on the compartmentalization of NO signaling in myocytes is highly controversial. To address this issue, we examined localization of enzymes engaged in L-arginine-NO-cGMP signaling in the rat quadriceps muscle. Employing immunocytochemical labeling complemented with tyramide signal amplification and electron microscopy, we found NO synthase expressed not only in the sarcolemma, but also along contractile fibers, in the sarcoplasmic reticulum and mitochondria. The expression pattern of NO synthase in myocytes showed striking parallels with the enzymes engaged in L-arginine-NO-cGMP signaling (arginase, phosphodiesterase, and soluble guanylyl cyclase). Our findings are indicative of an autocrine fashion of NO signaling in skeletal muscles at both cellular and subcellular levels, and challenge the notion that the NO generation is restricted to the sarcolemma

  14. Imaging and compartmental classification of solid pelvic tumours in children

    International Nuclear Information System (INIS)

    Hugosson, C.; Nyman, R.; Jacobsson, B.; Jorulf, H.; McDonald, P.; Sackey, K.

    1996-01-01

    Thirty-five children aged from 1 day to 16 years (median 5 years) with solid pelvic tumours were investigated with US, CT and MR. All three methods gave similar estimates of tumour size. For defining location of the tumours, the pelvis was divided into three midline compartments (anterior, middle and posterior) and a right and left lateral compartment. CT and MR were accurate and equally reliable in determining the tumour location, US was less accurate. Evaluation of confinement to organ of origin was uncertain, regardless of imaging modality. Tissue characteristics with CT and MR did not contribute to the differentiation of the various tumour types, and contrast medium enhancement did not improve the discrimination. Compartmental localization was equally well assessed by CT and MR and, together with sex, was found to correlate with the tumour type. (orig.). With 7 figs., 5 tabs

  15. Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism

    International Nuclear Information System (INIS)

    Ucciferri, Nadia; Sbrana, Tommaso; Ahluwalia, Arti

    2014-01-01

    Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell–cell or cell–tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.

  16. Allometric scaling and cell ratios in multi-organ in vitro models of human metabolism

    Directory of Open Access Journals (Sweden)

    Nadia eUcciferri

    2014-12-01

    Full Text Available Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step towards building an integrated picture of systemic metabolism and signalling in physiological or pathological conditions. However the rational design of in vitro models of cell-cell or cell-tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here we analyse the physiologic relationship between cells, cell metabolism and exchange in the human body using allometric rules, downscaling them to an organ-on-a plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (Cell Number Scaling Model, CNSM, and Metabolic and Surface Scaling model, MSSM are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions which can be extrapolated to the in vivo

  17. Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism.

    Science.gov (United States)

    Ucciferri, Nadia; Sbrana, Tommaso; Ahluwalia, Arti

    2014-01-01

    Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell-cell or cell-tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.

  18. Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism

    Energy Technology Data Exchange (ETDEWEB)

    Ucciferri, Nadia [CNR Institute of Clinical Physiology, Pisa (Italy); Interdepartmental Research Center “E. Piaggio”, University of Pisa, Pisa (Italy); Sbrana, Tommaso [Interdepartmental Research Center “E. Piaggio”, University of Pisa, Pisa (Italy); Ahluwalia, Arti, E-mail: arti.ahluwalia@unipi.it [CNR Institute of Clinical Physiology, Pisa (Italy); Interdepartmental Research Center “E. Piaggio”, University of Pisa, Pisa (Italy)

    2014-12-17

    Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell–cell or cell–tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.

  19. PKA catalytic subunit compartmentation regulates contractile and hypertrophic responses to β-adrenergic signaling

    Science.gov (United States)

    Yang, Jason H.; Polanowska-Grabowska, Renata K.; Smith, Jeffrey S.; Shields, Charles W.; Saucerman, Jeffrey J.

    2014-01-01

    β-adrenergic signaling is spatiotemporally heterogeneous in the cardiac myocyte, conferring exquisite control to sympathetic stimulation. Such heterogeneity drives the formation of protein kinase A (PKA) signaling microdomains, which regulate Ca2+ handling and contractility. Here, we test the hypothesis that the nucleus independently comprises a PKA signaling microdomain regulating myocyte hypertrophy. Spatially-targeted FRET reporters for PKA activity identified slower PKA activation and lower isoproterenol sensitivity in the nucleus (t50 = 10.60±0.68 min; EC50 = 89.00 nmol/L) than in the cytosol (t50 = 3.71±0.25 min; EC50 = 1.22 nmol/L). These differences were not explained by cAMP or AKAP-based compartmentation. A computational model of cytosolic and nuclear PKA activity was developed and predicted that differences in nuclear PKA dynamics and magnitude are regulated by slow PKA catalytic subunit diffusion, while differences in isoproterenol sensitivity are regulated by nuclear expression of protein kinase inhibitor (PKI). These were validated by FRET and immunofluorescence. The model also predicted differential phosphorylation of PKA substrates regulating cell contractility and hypertrophy. Ca2+ and cell hypertrophy measurements validated these predictions and identified higher isoproterenol sensitivity for contractile enhancements (EC50 = 1.84 nmol/L) over cell hypertrophy (EC50 = 85.88 nmol/L). Over-expression of spatially targeted PKA catalytic subunit to the cytosol or nucleus enhanced contractile and hypertrophic responses, respectively. We conclude that restricted PKA catalytic subunit diffusion is an important PKA compartmentation mechanism and the nucleus comprises a novel PKA signaling microdomain, insulating hypertrophic from contractile β-adrenergic signaling responses. PMID:24225179

  20. Analysis of Piscirickettsia salmonis Metabolism Using Genome-Scale Reconstruction, Modeling, and Testing

    Directory of Open Access Journals (Sweden)

    María P. Cortés

    2017-12-01

    Full Text Available Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen’s biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genome-scale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.

  1. Transgenic Mouse Models for Alcohol Metabolism, Toxicity and Cancer

    OpenAIRE

    Heit, Claire; Dong, Hongbin; Chen, Ying; Shah, Yatrik M.; Thompson, David C.; Vasiliou, Vasilis

    2015-01-01

    Alcohol abuse leads to tissue damage including a variety of cancers; however, the molecular mechanisms by which this damage occurs remains to be fully understood. The primary enzymes involved in ethanol metabolism include alcohol dehydrogenase (ADH), cytochrome P450 isoform 2E1, (CYP2E1), catalase (CAT), and aldehyde dehydrogenases (ALDH). Genetic polymorphisms in human genes encoding these enzymes are associated with increased risks of alcohol-related tissue damage, as well as differences in...

  2. Compartmental analysis of the disposition of benzo[a]pyrene in rats.

    Science.gov (United States)

    Bevan, D R; Weyand, E H

    1988-11-01

    We have previously reported the disposition of benzo[a]pyrene (B[a]P) and its metabolites in male Sprague-Dawley rats following intratracheal instillation of [3H]B[a]P [Weyand, E.H. and Bevan, D.R. (1986) Cancer Res., 46, 5655-5661]. In some experiments, cannulas were implanted in the bile duct of the animals prior to administration of [3H]B[a]P [Weyand, E.H. and Bevan, D.R. (1987) Drug Metab. Disposition, 15, 442-448]. Based on these data, we have developed a compartmental model of the distribution of radioactivity to provide a quantitative description of the fate of B[a]P and its metabolites in rats. Modeling of the distribution of radioactivity was performed using the Simulation, Analysis and Modeling (SAAM) and conversational SAAM (CONSAM) computer programs. Compartments in the model included organs into which the largest amounts of radioactivity were distributed as well as pathways for excretion of radioactivity from the animals. Data from animals with and without cannulas implanted in the bile duct were considered simultaneously during modeling. Radioactivity was so rapidly absorbed from the lungs that an absorption phase into blood was not apparent at the earliest sampling times. Using the model of extrapolate to shorter times, it was predicted that the maximum amount of radioactivity was present in blood within 2 min after administration. In addition, considerable recycling of radioactivity back to lungs from blood was predicted by the model. Transfer of radioactivity from blood to liver and carcass (skin, muscle, bones, fat and associated blood) also was extensive. Carcass was modeled as the sum of two compartments to obtain agreement between the model and experimental data. The model accounted for enterohepatic circulation of B[a]P metabolites; data also required that intestinal secretion be included in the model. Quantitative data obtained from compartmental analysis included rate constants for transfer of radioactivity among compartments as well as

  3. 21 CFR 888.3535 - Knee joint femorotibial (uni-compartmental) metal/polymer porous-coated uncemented prosthesis.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Knee joint femorotibial (uni-compartmental) metal... Devices § 888.3535 Knee joint femorotibial (uni-compartmental) metal/polymer porous-coated uncemented prosthesis. (a) Identification. A knee joint femorotibial (uni-compartmental) metal/polymer porous-coated...

  4. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    Energy Technology Data Exchange (ETDEWEB)

    Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  5. Model-based design of bistable cell factories for metabolic engineering.

    Science.gov (United States)

    Srinivasan, Shyam; Cluett, William R; Mahadevan, Radhakrishnan

    2018-04-15

    Metabolism can exhibit dynamic phenomena like bistability due to the presence of regulatory motifs like the positive feedback loop. As cell factories, microorganisms with bistable metabolism can have a high and a low product flux at the two stable steady states, respectively. The exclusion of metabolic regulation and network dynamics limits the ability of pseudo-steady state stoichiometric models to detect the presence of bistability, and reliably assess the outcomes of design perturbations to metabolic networks. Using kinetic models of metabolism, we assess the change in the bistable characteristics of the network, and suggest designs based on perturbations to the positive feedback loop to enable the network to produce at its theoretical maximum rate. We show that the most optimal production design in parameter space, for a small bistable metabolic network, may exist at the boundary of the bistable region separating it from the monostable region of low product fluxes. The results of our analysis can be broadly applied to other bistable metabolic networks with similar positive feedback network topologies. This can complement existing model-based design strategies by providing a smaller number of feasible designs that need to be tested in vivo. http://lmse.biozone.utoronto.ca/downloads/. krishna.mahadevan@utoronto.ca. Supplementary data are available at Bioinformatics online.

  6. Effects of hypoxia on 13NH4+ fluxes in rice roots: kinetics and compartmental analysis

    International Nuclear Information System (INIS)

    Kronzucker, H.J.; Kirk, G.J.D.; Siddiqi, M.Y.; Glass, A.D.M.

    1998-01-01

    Techniques of compartmental (efflux) and kinetic influx analyses with the radiotracer 13NH4+ were used to examine the adaptation to hypoxia (15, 35, and 50% O2 saturation) of root N uptake and metabolism in 3-week-old hydroponically grown rice (Oryza sativa L., cv IR72) seedlings. A time-dependence study of NH4+ influx into rice roots after onset of hypoxia (15% O2) revealed an initial increase in the first 1 to 2.5 h after treatment imposition, followed by a decline to less than 50% of influx in control plants by 4 d. Efflux analyses conducted 0, 1, 3, and 5 d after the treatment confirmed this adaptation pattern of NH4+ uptake. Half-lives for NH4+ exchange with subcellular compartments, cytoplasmic NH4+ concentrations, and efflux (as percentage of influx) were unaffected by hypoxia. However, significant differences were observed in the relative amounts of N allocated to NH4+ assimilation and the vacuole versus translocation to the shoot. Kinetic experiments conducted at 100, 50, 35, and 15% O2 saturation showed no significant change in the K(m) value for NH4+ uptake with varying O2 supply. However, V(max) was 42% higher than controls at 50% O2 saturation, unchanged at 35%, and 10% lower than controls at 15% O2. The significance of these flux adaptations is discussed

  7. Characterization and subcellular compartmentation of recombinant 4-hydroxyphenylpyruvate dioxygenase from Arabidopsis in transgenic tobacco.

    Science.gov (United States)

    Garcia, I; Rodgers, M; Pepin, R; Hsieh, T F; Matringe, M

    1999-04-01

    4-Hydroxyphenylpyruvate dioxygenase (4HPPD) catalyzes the formation of homogentisate (2,5-dihydroxyphenylacetate) from p-hydroxyphenylpyruvate and molecular oxygen. In plants this enzyme activity is involved in two distinct metabolic processes, the biosynthesis of prenylquinones and the catabolism of tyrosine. We report here the molecular and biochemical characterization of an Arabidopsis 4HPPD and the compartmentation of the recombinant protein in chlorophyllous tissues. We isolated a 1508-bp cDNA with one large open reading frame of 1338 bp. Southern analysis strongly suggested that this Arabidopsis 4HPPD is encoded by a single-copy gene. We investigated the biochemical characteristics of this 4HPPD by overproducing the recombinant protein in Escherichia coli JM105. The subcellular localization of the recombinant 4HPPD in chlorophyllous tissues was examined by overexpressing its complete coding sequence in transgenic tobacco (Nicotiana tabacum), using Agrobacterium tumefaciens transformation. We performed western analyses for the immunodetection of protein extracts from purified chloroplasts and total leaf extracts and for the immunocytochemistry on tissue sections. These analyses clearly revealed that 4HPPD was confined to the cytosol compartment, not targeted to the chloroplast. Western analyses confirmed the presence of a cytosolic form of 4HPPD in cultured green Arabidopsis cells.

  8. The human hepatocyte cell lines IHH and HepaRG : models to study glucose, lipid and lipoprotein metabolism

    NARCIS (Netherlands)

    Samanez, Carolina Huaman; Caron, Sandrine; Briand, Olivier; Dehondt, Helene; Duplan, Isabelle; Kuipers, Folkert; Hennuyer, Nathalie; Clavey, Veronique; Staels, Bart

    Metabolic diseases reach epidemic proportions. A better knowledge of the associated alterations in the metabolic pathways in the liver is necessary. These studies need in vitro human cell models. Several human hepatoma models are used, but the response of many metabolic pathways to physiological

  9. Mitochondrial metabolism in early neural fate and its relevance for neuronal disease modeling.

    Science.gov (United States)

    Lorenz, Carmen; Prigione, Alessandro

    2017-12-01

    Modulation of energy metabolism is emerging as a key aspect associated with cell fate transition. The establishment of a correct metabolic program is particularly relevant for neural cells given their high bioenergetic requirements. Accordingly, diseases of the nervous system commonly involve mitochondrial impairment. Recent studies in animals and in neural derivatives of human pluripotent stem cells (PSCs) highlighted the importance of mitochondrial metabolism for neural fate decisions in health and disease. The mitochondria-based metabolic program of early neurogenesis suggests that PSC-derived neural stem cells (NSCs) may be used for modeling neurological disorders. Understanding how metabolic programming is orchestrated during neural commitment may provide important information for the development of therapies against conditions affecting neural functions, including aging and mitochondrial disorders. Copyright © 2017. Published by Elsevier Ltd.

  10. Cs-137 accumulation and elimination by Gracilaria caudata alga and Abudefduf saxatilis fish. Compartmental analysis

    International Nuclear Information System (INIS)

    Mattiolo-Marchese, Sandra Regina

    1998-01-01

    From the ecological point of view, 137 Cs is a critical radionuclide because its physical half-life is long (30 years), and it has a high fission yield. Besides, it presents similar characteristics to sodium and potassium, fundamental elements for the living organisms, in great concentration in all cells. This work has as aim to study the 137 Cs accumulation and elimination by the alga Gracilaria caudata and by the fish Abudefduf saxatilis as well as to obtain the transfer constants of the 137 Cs from the water into the organisms. The concentration factor found for the fish was 5.6 +- 0.2 and for the alga, 13.0 +- 0,6. With 7 and 22 days, the fish and alga respectively had already eliminated half of the accumulated radionuclide. The 137 Cs ingestion efficiency by the fish was also studied and it was verified that the fish assimilated only 47.6 % of the cesium content in the food; and within of 4 days it had eliminated more than half of ingested cesium. A compartmental model was proposed to explain the distribution of cesium in the compartments (water - alga and water - fish). Data obtained from the experiments of 137 Cs accumulation and elimination were applied in the Ana Comp Program. This program permits the compartmental analysis, and quantifies the cesium distribution from the sea-water to the organisms, and vice versa, through the transfer constants (k). The Ana Comp Program also allowed to calculate the dose that one would receive by the consumption of fish contaminated by cesium. Levels of 137 Cs from the global fallout in environmental samples, from Sao Sebastiao, northern coast of Sao Paulo, (where the 'Centro de Biologia Marinha da Universidade de Sao Paulo - CEBIMar - USP' is located), were verified. (author)

  11. A systems biology framework for modeling metabolic enzyme inhibition of Mycobacterium tuberculosis

    Directory of Open Access Journals (Sweden)

    Reifman Jaques

    2009-09-01

    Full Text Available Abstract Background Because metabolism is fundamental in sustaining microbial life, drugs that target pathogen-specific metabolic enzymes and pathways can be very effective. In particular, the metabolic challenges faced by intracellular pathogens, such as Mycobacterium tuberculosis, residing in the infected host provide novel opportunities for therapeutic intervention. Results We developed a mathematical framework to simulate the effects on the growth of a pathogen when enzymes in its metabolic pathways are inhibited. Combining detailed models of enzyme kinetics, a complete metabolic network description as modeled by flux balance analysis, and a dynamic cell population growth model, we quantitatively modeled and predicted the dose-response of the 3-nitropropionate inhibitor on the growth of M. tuberculosis in a medium whose carbon source was restricted to fatty acids, and that of the 5'-O-(N-salicylsulfamoyl adenosine inhibitor in a medium with low-iron concentration. Conclusion The predicted results quantitatively reproduced the experimentally measured dose-response curves, ranging over three orders of magnitude in inhibitor concentration. Thus, by allowing for detailed specifications of the underlying enzymatic kinetics, metabolic reactions/constraints, and growth media, our model captured the essential chemical and biological factors that determine the effects of drug inhibition on in vitro growth of M. tuberculosis cells.

  12. OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis

    Directory of Open Access Journals (Sweden)

    Nielsen Lars K

    2009-05-01

    Full Text Available Abstract Background The quantitative analysis of metabolic fluxes, i.e., in vivo activities of intracellular enzymes and pathways, provides key information on biological systems in systems biology and metabolic engineering. It is based on a comprehensive approach combining (i tracer cultivation on 13C substrates, (ii 13C labelling analysis by mass spectrometry and (iii mathematical modelling for experimental design, data processing, flux calculation and statistics. Whereas the cultivation and the analytical part is fairly advanced, a lack of appropriate modelling software solutions for all modelling aspects in flux studies is limiting the application of metabolic flux analysis. Results We have developed OpenFLUX as a user friendly, yet flexible software application for small and large scale 13C metabolic flux analysis. The application is based on the new Elementary Metabolite Unit (EMU framework, significantly enhancing computation speed for flux calculation. From simple notation of metabolic reaction networks defined in a spreadsheet, the OpenFLUX parser automatically generates MATLAB-readable metabolite and isotopomer balances, thus strongly facilitating model creation. The model can be used to perform experimental design, parameter estimation and sensitivity analysis either using the built-in gradient-based search or Monte Carlo algorithms or in user-defined algorithms. Exemplified for a microbial flux study with 71 reactions, 8 free flux parameters and mass isotopomer distribution of 10 metabolites, OpenFLUX allowed to automatically compile the EMU-based model from an Excel file containing metabolic reactions and carbon transfer mechanisms, showing it's user-friendliness. It reliably reproduced the published data and optimum flux distributions for the network under study were found quickly ( Conclusion We have developed a fast, accurate application to perform steady-state 13C metabolic flux analysis. OpenFLUX will strongly facilitate and

  13. Metabolic network modeling of microbial interactions in natural and engineered environmental systems

    Directory of Open Access Journals (Sweden)

    Octavio ePerez-Garcia

    2016-05-01

    Full Text Available We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA, experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e. i lumped networks, ii compartment per guild networks, iii bi-level optimization simulations and iv dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial

  14. How Energy Metabolism Supports Cerebral Function: Insights from 13C Magnetic Resonance Studies In vivo

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    Sarah Sonnay

    2017-05-01

    Full Text Available Cerebral function is associated with exceptionally high metabolic activity, and requires continuous supply of oxygen and nutrients from the blood stream. Since the mid-twentieth century the idea that brain energy metabolism is coupled to neuronal activity has emerged, and a number of studies supported this hypothesis. Moreover, brain energy metabolism was demonstrated to be compartmentalized in neurons and astrocytes, and astrocytic glycolysis was proposed to serve the energetic demands of glutamatergic activity. Shedding light on the role of astrocytes in brain metabolism, the earlier picture of astrocytes being restricted to a scaffold-associated function in the brain is now out of date. With the development and optimization of non-invasive techniques, such as nuclear magnetic resonance spectroscopy (MRS, several groups have worked on assessing cerebral metabolism in vivo. In this context, 1H MRS has allowed the measurements of energy metabolism-related compounds, whose concentrations can vary under different brain activation states. 1H-[13C] MRS, i.e., indirect detection of signals from 13C-coupled 1H, together with infusion of 13C-enriched glucose has provided insights into the coupling between neurotransmission and glucose oxidation. Although these techniques tackle the coupling between neuronal activity and metabolism, they lack chemical specificity and fail in providing information on neuronal and glial metabolic pathways underlying those processes. Currently, the improvement of detection modalities (i.e., direct detection of 13C isotopomers, the progress in building adequate mathematical models along with the increase in magnetic field strength now available render possible detailed compartmentalized metabolic flux characterization. In particular, direct 13C MRS offers more detailed dataset acquisitions and provides information on metabolic interactions between neurons and astrocytes, and their role in supporting neurotransmission. Here

  15. Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty

    Science.gov (United States)

    Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Read, Emily K.; Solomon, Christopher T.; Adrian, Rita; Hanson, Paul C.

    2014-01-01

    Diel changes in dissolved oxygen are often used to estimate gross primary production (GPP) and ecosystem respiration (ER) in aquatic ecosystems. Despite the widespread use of this approach to understand ecosystem metabolism, we are only beginning to understand the degree and underlying causes of uncertainty for metabolism model parameter estimates. Here, we present a novel approach to improve the precision and accuracy of ecosystem metabolism estimates by identifying physical metrics that indicate when metabolism estimates are highly uncertain. Using datasets from seventeen instrumented GLEON (Global Lake Ecological Observatory Network) lakes, we discovered that many physical characteristics correlated with uncertainty, including PAR (photosynthetically active radiation, 400-700 nm), daily variance in Schmidt stability, and wind speed. Low PAR was a consistent predictor of high variance in GPP model parameters, but also corresponded with low ER model parameter variance. We identified a threshold (30% of clear sky PAR) below which GPP parameter variance increased rapidly and was significantly greater in nearly all lakes compared with variance on days with PAR levels above this threshold. The relationship between daily variance in Schmidt stability and GPP model parameter variance depended on trophic status, whereas daily variance in Schmidt stability was consistently positively related to ER model parameter variance. Wind speeds in the range of ~0.8-3 m s–1 were consistent predictors of high variance for both GPP and ER model parameters, with greater uncertainty in eutrophic lakes. Our findings can be used to reduce ecosystem metabolism model parameter uncertainty and identify potential sources of that uncertainty.

  16. The establishment of animal model of radiation-skin-burn and its changes of tissue metabolism

    International Nuclear Information System (INIS)

    Lu Xingan; Wu Shiliang; Wang Xiuzhen; Zhou Yinghui; Feng Yizhong; Tian Ye; Peng Miao

    2001-01-01

    The biochemistry metabolic changes of the tissues induced by 60 Co γ radiation or by accelerator β radiation on the animal local tissues were observed. The experiment results were shown as follows: (1) 60 Co γ radiation can induce the metabolic changes of the local tissue and led to ulcer or death. (2) Accelerator β radiation at the same dose of γ radiation can only produce ulcer but no death. (3) The biochemistry metabolic changes of the tissues induced by 60 Co γ radiation are similar to that by β radiation, but as a radiation-burn animal model, the latter is better

  17. A model to study intestinal and hepatic metabolism of propranolol in the dog.

    Science.gov (United States)

    Mills, P C; Siebert, G A; Roberts, M S

    2004-02-01

    A model to investigate hepatic drug uptake and metabolism in the dog was developed for this study. Catheters were placed in the portal and hepatic veins during exploratory laparotomy to collect pre- and posthepatic blood samples at defined intervals. Drug concentrations in the portal vein were taken to reflect intestinal uptake and metabolism of an p.o. administered drug (propranolol), while differences in drug and metabolite concentrations between portal and hepatic veins reflected hepatic uptake and metabolism. A significant difference in propranolol concentration between hepatic and portal veins confirmed a high hepatic extraction of this therapeutic agent in the dog. This technically uncomplicated model may be used experimentally or clinically to determine hepatic function and metabolism of drugs that may be administered during anaesthesia and surgery.

  18. Thermodynamic analysis of regulation in metabolic networks using constraint-based modeling

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    Mahadevan Radhakrishnan

    2010-05-01

    Full Text Available Abstract Background Geobacter sulfurreducens is a member of the Geobacter species, which are capable of oxidation of organic waste coupled to the reduction of heavy metals and electrode with applications in bioremediation and bioenergy generation. While the metabolism of this organism has been studied through the development of a stoichiometry based genome-scale metabolic model, the associated regulatory network has not yet been well studied. In this manuscript, we report on the implementation of a thermodynamics based metabolic flux model for Geobacter sulfurreducens. We use this updated model to identify reactions that are subject to regulatory control in the metabolic network of G. sulfurreducens using thermodynamic variability analysis. Findings As a first step, we have validated the regulatory sites and bottleneck reactions predicted by the thermodynamic flux analysis in E. coli by evaluating the expression ranges of the corresponding genes. We then identified ten reactions in the metabolic network of G. sulfurreducens that are predicted to be candidates for regulation. We then compared the free energy ranges for these reactions with the corresponding gene expression fold changes under conditions of different environmental and genetic perturbations and show that the model predictions of regulation are consistent with data. In addition, we also identify reactions that operate close to equilibrium and show that the experimentally determined exchange coefficient (a measure of reversibility is significant for these reactions. Conclusions Application of the thermodynamic constraints resulted in identification of potential bottleneck reactions not only from the central metabolism but also from the nucleotide and amino acid subsystems, thereby showing the highly coupled nature of the thermodynamic constraints. In addition, thermodynamic variability analysis serves as a valuable tool in estimating the ranges of ΔrG' of every reaction in the model

  19. PET studies of brain energy metabolism in a model of subcortical dementia: progressive supranuclear Palsy

    International Nuclear Information System (INIS)

    Blin, J.; Baron, J.C.; Cambon, H.

    1988-01-01

    In 41 patients with clinically determined Progressive Supranuclear Palsy, a model of degenerative subcortical dementia, alterations in regional brain energy metabolism with respect to control subjects have been investigated using positron computed tomography and correlated to clinical and neuropsychological scores. A generalized significant reduction in brain metabolism was found, which predominated in the prefrontal cortex in accordance with, and statistically correlated to, the frontal neuropsychological score

  20. Generation and Validation of the iKp1289 Metabolic Model for Klebsiella pneumoniae KPPR1

    Energy Technology Data Exchange (ETDEWEB)

    Henry, Christopher S.; Rotman, Ella; Lathem, Wyndham W.; Tyo, Keith E. J.; Hauser, Alan R.; Mandel, Mark J.

    2017-02-15

    Klebsiella pneumoniae has a reputation for causing a wide range of infectious conditions, with numerous highly virulent and antibiotic-resistant strains. Metabolic models have the potential to provide insights into the growth behavior, nutrient requirements, essential genes, and candidate drug targets in these strains. Here we develop a metabolic model for KPPR1, a highly virulent strain of K. pneumoniae. We apply a combination of Biolog phenotype data and fitness data to validate and refine our KPPR1 model. The final model displays a predictive accuracy of 75% in identifying potential carbon and nitrogen sources for K. pneumoniae and of 99% in predicting nonessential genes in rich media. We demonstrate how this model is useful in studying the differences in the metabolic capabilities of the low-virulence MGH 78578 strain and the highly virulent KPPR1 strain. For example, we demonstrate that these strains differ in carbohydrate metabolism, including the ability to metabolize dulcitol as a primary carbon source. Our model makes numerous other predictions for follow-up verification and analysis.

  1. Microbial physiology-based model of ethanol metabolism in subsurface sediments

    Science.gov (United States)

    Jin, Qusheng; Roden, Eric E.

    2011-07-01

    A biogeochemical reaction model was developed based on microbial physiology to simulate ethanol metabolism and its influence on the chemistry of anoxic subsurface environments. The model accounts for potential microbial metabolisms that degrade ethanol, including those that oxidize ethanol directly or syntrophically by reducing different electron acceptors. Out of the potential metabolisms, those that are active in the environment can be inferred by fitting the model to experimental observations. This approach was applied to a batch sediment slurry experiment that examined ethanol metabolism in uranium-contaminated aquifer sediments from Area 2 at the U.S. Department of Energy Field Research Center in Oak Ridge, TN. According to the simulation results, complete ethanol oxidation by denitrification, incomplete ethanol oxidation by ferric iron reduction, ethanol fermentation to acetate and H 2, hydrogenotrophic sulfate reduction, and acetoclastic methanogenesis: all contributed significantly to the degradation of ethanol in the aquifer sediments. The assemblage of the active metabolisms provides a frame work to explore how ethanol amendment impacts the chemistry of the environment, including the occurrence and levels of uranium. The results can also be applied to explore how diverse microbial metabolisms impact the progress and efficacy of bioremediation strategies.

  2. Development of an Experimental Model of Diabetes Co-Existing with Metabolic Syndrome in Rats

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    Rajesh Kumar Suman

    2016-01-01

    Full Text Available Background. The incidence of metabolic syndrome co-existing with diabetes mellitus is on the rise globally. Objective. The present study was designed to develop a unique animal model that will mimic the pathological features seen in individuals with diabetes and metabolic syndrome, suitable for pharmacological screening of drugs. Materials and Methods. A combination of High-Fat Diet (HFD and low dose of streptozotocin (STZ at 30, 35, and 40 mg/kg was used to induce metabolic syndrome in the setting of diabetes mellitus in Wistar rats. Results. The 40 mg/kg STZ produced sustained hyperglycemia and the dose was thus selected for the study to induce diabetes mellitus. Various components of metabolic syndrome such as dyslipidemia (increased triglyceride, total cholesterol, LDL cholesterol, and decreased HDL cholesterol, diabetes mellitus (blood glucose, HbA1c, serum insulin, and C-peptide, and hypertension {systolic blood pressure} were mimicked in the developed model of metabolic syndrome co-existing with diabetes mellitus. In addition to significant cardiac injury, atherogenic index, inflammation (hs-CRP, decline in hepatic and renal function were observed in the HF-DC group when compared to NC group rats. The histopathological assessment confirmed presence of edema, necrosis, and inflammation in heart, pancreas, liver, and kidney of HF-DC group as compared to NC. Conclusion. The present study has developed a unique rodent model of metabolic syndrome, with diabetes as an essential component.

  3. Stress, autonomic imbalance, and the prediction of metabolic risk: A model and a proposal for research.

    Science.gov (United States)

    Wulsin, Lawson; Herman, James; Thayer, Julian F

    2018-03-01

    Devising novel prevention strategies for metabolic disorders will depend in part on the careful elucidation of the common pathways for developing metabolic risks. The neurovisceral integration model has proposed that autonomic imbalance plays an important role in the pathway from acute and chronic stress to cardiovascular disease. Though generally overlooked by clinicians, autonomic imbalance (sympathetic overactivity and/or parasympathetic underactivity) can be measured and modified by methods that are available in primary care. This review applies the neurovisceral integration concept to the clinical setting by proposing that autonomic imbalance plays a primary role in the development of metabolic risks. We present a testable model, a systematic review of the evidence in support of autonomic imbalance as a predictor for metabolic risks, and specific approaches to test this model as a guide to future research on the role of stress in metabolic disorders. We propose that autonomic imbalance deserves consideration by researchers, clinicians, and policymakers as a target for early interventions to prevent metabolic disorders. Published by Elsevier Ltd.

  4. Development of an Experimental Model of Diabetes Co-Existing with Metabolic Syndrome in Rats.

    Science.gov (United States)

    Suman, Rajesh Kumar; Ray Mohanty, Ipseeta; Borde, Manjusha K; Maheshwari, Ujwala; Deshmukh, Y A

    2016-01-01

    Background. The incidence of metabolic syndrome co-existing with diabetes mellitus is on the rise globally. Objective. The present study was designed to develop a unique animal model that will mimic the pathological features seen in individuals with diabetes and metabolic syndrome, suitable for pharmacological screening of drugs. Materials and Methods. A combination of High-Fat Diet (HFD) and low dose of streptozotocin (STZ) at 30, 35, and 40 mg/kg was used to induce metabolic syndrome in the setting of diabetes mellitus in Wistar rats. Results. The 40 mg/kg STZ produced sustained hyperglycemia and the dose was thus selected for the study to induce diabetes mellitus. Various components of metabolic syndrome such as dyslipidemia {(increased triglyceride, total cholesterol, LDL cholesterol, and decreased HDL cholesterol)}, diabetes mellitus (blood glucose, HbA1c, serum insulin, and C-peptide), and hypertension {systolic blood pressure} were mimicked in the developed model of metabolic syndrome co-existing with diabetes mellitus. In addition to significant cardiac injury, atherogenic index, inflammation (hs-CRP), decline in hepatic and renal function were observed in the HF-DC group when compared to NC group rats. The histopathological assessment confirmed presence of edema, necrosis, and inflammation in heart, pancreas, liver, and kidney of HF-DC group as compared to NC. Conclusion. The present study has developed a unique rodent model of metabolic syndrome, with diabetes as an essential component.

  5. A proposed model for the transfer of environmental tritium to man and tritium metabolism in model animals

    International Nuclear Information System (INIS)

    Saito, Masahiro; Ishida, M.R.

    1987-01-01

    To evaluate the accumulated dose in human bodies due to the environmental tritium, it is of required to establish an adequate model for the tritium transfer from the environment to man and to obtain enough information on the metabolic behaviour of tritium in animal bodies using model animal system. In this report, first we describe about a proposed model for the transfer of environmental tritium to man and secondly mention briefly about the recent works on the tritium metabolism in newborn animals which have been treated as a model system of tritium intake through food chain. (author)

  6. Transcriptional regulation and steady-state modeling of metabolic networks

    DEFF Research Database (Denmark)

    Zelezniak, Aleksej

    Biological systems are characterized by a high degree of complexity wherein the individual components (e.g. proteins) are inter-linked in a way that leads to emergent behaviors that are difficult to decipher. Uncovering system complexity requires, at least, answers to the following three questions......: what are the components of the systems, how are the different components interconnected and how do these networks perform the functions that make the resulting system behavior? Modern analytical technologies allow us to unravel the constituents and interactions happening in a given system; however......, the third question is the ultimate challenge for systems biology. The work of this thesis systematically addresses this question in the context of metabolic networks, which are arguably the most well characterized cellular networks in terms of their constituting components and interactions among them...

  7. Context-Specific Metabolic Model Extraction Based on Regularized Least Squares Optimization.

    Directory of Open Access Journals (Sweden)

    Semidán Robaina Estévez

    Full Text Available Genome-scale metabolic models have proven highly valuable in investigating cell physiology. Recent advances include the development of methods to extract context-specific models capable of describing metabolism under more specific scenarios (e.g., cell types. Yet, none of the existing computational approaches allows for a fully automated model extraction and determination of a flux distribution independent of user-defined parameters. Here we present RegrEx, a fully automated approach that relies solely on context-specific data and ℓ1-norm regularization to extract a context-specific model and to provide a flux distribution that maximizes its correlation to data. Moreover, the publically available implementation of RegrEx was used to extract 11 context-specific human models using publicly available RNAseq expression profiles, Recon1 and also Recon2, the most recent human metabolic model. The comparison of the performance of RegrEx and its contending alternatives demonstrates that the proposed method extracts models for which both the structure, i.e., reactions included, and the flux distributions are in concordance with the employed data. These findings are supported by validation and comparison of method performance on additional data not used in context-specific model extraction. Therefore, our study sets the ground for applications of other regularization techniques in large-scale metabolic modeling.

  8. METABOLIC MODELLING IN THE DEVELOPMENT OF CELL FACTORIES BY SYNTHETIC BIOLOGY

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    Paula Jouhten

    2012-10-01

    Full Text Available Cell factories are commonly microbial organisms utilized for bioconversion of renewable resources to bulk or high value chemicals. Introduction of novel production pathways in chassis strains is the core of the development of cell factories by synthetic biology. Synthetic biology aims to create novel biological functions and systems not found in nature by combining biology with engineering. The workflow of the development of novel cell factories with synthetic biology is ideally linear which will be attainable with the quantitative engineering approach, high-quality predictive models, and libraries of well-characterized parts. Different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful in particular phases of the synthetic biology workflow. In this minireview, the role of metabolic modelling in synthetic biology will be discussed with a review of current status of compatible methods and models for the in silico design and quantitative evaluation of a cell factory.

  9. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Zhang, Xi-Cheng; Nilsson, Avlant

    2017-01-01

    , which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance...... and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping...... with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between...

  10. Metingear: a development environment for annotating genome-scale metabolic models.

    Science.gov (United States)

    May, John W; James, A Gordon; Steinbeck, Christoph

    2013-09-01

    Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.

  11. Acute metabolic decompensation due to influenza in a mouse model of ornithine transcarbamylase deficiency

    Directory of Open Access Journals (Sweden)

    Peter J. McGuire

    2014-02-01

    Full Text Available The urea cycle functions to incorporate ammonia, generated by normal metabolism, into urea. Urea cycle disorders (UCDs are caused by loss of function in any of the enzymes responsible for ureagenesis, and are characterized by life-threatening episodes of acute metabolic decompensation with hyperammonemia (HA. A prospective analysis of interim HA events in a cohort of individuals with ornithine transcarbamylase (OTC deficiency, the most common UCD, revealed that intercurrent infection was the most common precipitant of acute HA and was associated with markers of increased morbidity when compared with other precipitants. To further understand these clinical observations, we developed a model system of metabolic decompensation with HA triggered by viral infection (PR8 influenza using spf-ash mice, a model of OTC deficiency. Both wild-type (WT and spf-ash mice displayed similar cytokine profiles and lung viral titers in response to PR8 influenza infection. During infection, spf-ash mice displayed an increase in liver transaminases, suggesting a hepatic sensitivity to the inflammatory response and an altered hepatic immune response. Despite having no visible pathological changes by histology, WT and spf-ash mice had reduced CPS1 and OTC enzyme activities, and, unlike WT, spf-ash mice failed to increase ureagenesis. Depression of urea cycle function was seen in liver amino acid analysis, with reductions seen in aspartate, ornithine and arginine during infection. In conclusion, we developed a model system of acute metabolic decompensation due to infection in a mouse model of a UCD. In addition, we have identified metabolic perturbations during infection in the spf-ash mice, including a reduction of urea cycle intermediates. This model of acute metabolic decompensation with HA due to infection in UCD serves as a platform for exploring biochemical perturbations and the efficacy of treatments, and could be adapted to explore acute decompensation in other

  12. The 4D Nucleome: Genome Compartmentalization in an Evolutionary Context.

    Science.gov (United States)

    Cremer, T; Cremer, M; Cremer, C

    2018-04-01

    4D nucleome research aims to understand the impact of nuclear organization in space and time on nuclear functions, such as gene expression patterns, chromatin replication, and the maintenance of genome integrity. In this review we describe evidence that the origin of 4D genome compartmentalization can be traced back to the prokaryotic world. In cell nuclei of animals and plants chromosomes occupy distinct territories, built up from ~1 Mb chromatin domains, which in turn are composed of smaller chromatin subdomains and also form larger chromatin domain clusters. Microscopic evidence for this higher order chromatin landscape was strengthened by chromosome conformation capture studies, in particular Hi-C. This approach demonstrated ~1 Mb sized, topologically associating domains in mammalian cell nuclei separated by boundaries. Mutations, which destroy boundaries, can result in developmental disorders and cancer. Nucleosomes appeared first as tetramers in the Archaea kingdom and later evolved to octamers built up each from two H2A, two H2B, two H3, and two H4 proteins. Notably, nucleosomes were lost during the evolution of the Dinoflagellata phylum. Dinoflagellate chromosomes remain condensed during the entire cell cycle, but their chromosome architecture differs radically from the architecture of other eukaryotes. In summary, the conservation of fundamental features of higher order chromatin arrangements throughout the evolution of metazoan animals suggests the existence of conserved, but still unknown mechanism(s) controlling this architecture. Notwithstanding this conservation, a comparison of metazoans and protists also demonstrates species-specific structural and functional features of nuclear organization.

  13. Pathways and Subcellular Compartmentation of NAD Biosynthesis in Human Cells

    Science.gov (United States)

    Nikiforov, Andrey; Dölle, Christian; Niere, Marc; Ziegler, Mathias

    2011-01-01

    NAD is a vital redox carrier, and its degradation is a key element of important regulatory pathways. NAD-mediated functions are compartmentalized and have to be fueled by specific biosynthetic routes. However, little is known about the different pathways, their subcellular distribution, and regulation in human cells. In particular, the route(s) to generate mitochondrial NAD, the largest subcellular pool, is still unknown. To visualize organellar NAD changes in cells, we targeted poly(ADP-ribose) polymerase activity into the mitochondrial matrix. This activity synthesized immunodetectable poly(ADP-ribose) depending on mitochondrial NAD availability. Based on this novel detector system, detailed subcellular enzyme localizations, and pharmacological inhibitors, we identified extracellular NAD precursors, their cytosolic conversions, and the pathway of mitochondrial NAD generation. Our results demonstrate that, besides nicotinamide and nicotinic acid, only the corresponding nucleosides readily enter the cells. Nucleotides (e.g. NAD and NMN) undergo extracellular degradation resulting in the formation of permeable precursors. These precursors can all be converted to cytosolic and mitochondrial NAD. For mitochondrial NAD synthesis, precursors are converted to NMN in the cytosol. When taken up into the organelles, NMN (together with ATP) serves as substrate of NMNAT3 to form NAD. NMNAT3 was conclusively localized to the mitochondrial matrix and is the only known enzyme of NAD synthesis residing within these organelles. We thus present a comprehensive dissection of mammalian NAD biosynthesis, the groundwork to understand regulation of NAD-mediated processes, and the organismal homeostasis of this fundamental molecule. PMID:21504897

  14. Nuclear Pore-Like Structures in a Compartmentalized Bacterium.

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    Evgeny Sagulenko

    Full Text Available Planctomycetes are distinguished from other Bacteria by compartmentalization of cells via internal membranes, interpretation of which has been subject to recent debate regarding potential relations to Gram-negative cell structure. In our interpretation of the available data, the planctomycete Gemmata obscuriglobus contains a nuclear body compartment, and thus possesses a type of cell organization with parallels to the eukaryote nucleus. Here we show that pore-like structures occur in internal membranes of G.obscuriglobus and that they have elements structurally similar to eukaryote nuclear pores, including a basket, ring-spoke structure, and eight-fold rotational symmetry. Bioinformatic analysis of proteomic data reveals that some of the G. obscuriglobus proteins associated with pore-containing membranes possess structural domains found in eukaryote nuclear pore complexes. Moreover, immunogold labelling demonstrates localization of one such protein, containing a β-propeller domain, specifically to the G. obscuriglobus pore-like structures. Finding bacterial pores within internal cell membranes and with structural similarities to eukaryote nuclear pore complexes raises the dual possibilities of either hitherto undetected homology or stunning evolutionary convergence.

  15. Development of a tree shrew metabolic syndrome model and use of umbilical cord mesenchymal stem cell transplantation for treatment.

    Science.gov (United States)

    Pan, Xing-Hua; Zhu, Lu; Yao, Xiang; Liu, Ju-Fen; Li, Zi-An; Yang, Jian-Yong; Pang, Rong-Qing; Ruan, Guang-Ping

    2016-12-01

    The aim of this study was to establish a tree shrew metabolic syndrome model and demonstrate the utility of MSCs in treating metabolic syndrome. We used tree shrew umbilical cord mesenchymal stem cell (TS-UC-MSC) transplantation for the treatment of metabolic syndrome to demonstrate the clinical application of these stem cells and to provide a theoretical basis and reference methods for this treatment. Tree shrew metabolic syndrome model showed significant insulin resistance, high blood sugar, lipid metabolism disorders, and hypertension, consistent with the diagnostic criteria. TS-UC-MSC transplantation at 16 weeks significantly reduced blood sugar and lipid levels, improved insulin resistance and the regulation of insulin secretion, and reduced the expression levels of the pro-inflammatory cytokines IL-1 and IL-6 (P metabolic syndrome model and showed that MSC migrate in diseased organs and can attenuate metabolic syndrome severity in a tree shrew model.

  16. Plasma proteome profiles associated with diet-induced metabolic syndrome and the early onset of metabolic syndrome in a pig model.

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    Marinus F W te Pas

    Full Text Available Obesity and related diabetes are important health threatening multifactorial metabolic diseases and it has been suggested that 25% of all diabetic patients are unaware of their patho-physiological condition. Biomarkers for monitoring and control are available, but early stage predictive biomarkers enabling prevention of these diseases are still lacking. We used the pig as a model to study metabolic disease because humans and pigs share a multitude of metabolic similarities. Diabetes was chemically induced and control and diabetic pigs were either fed a high unsaturated fat (Mediterranean diet or a high saturated fat/cholesterol/sugar (cafeteria diet. Physiological parameters related to fat metabolism and diabetes were measured. Diabetic pigs' plasma proteome profiles differed more between the two diets than control pigs plasma proteome profiles. The expression levels of several proteins correlated well with (pathophysiological parameters related to the fat metabolism (cholesterol, VLDL, LDL, NEFA and diabetes (Glucose and to the diet fed to the animals. Studying only the control pigs as a model for metabolic syndrome when fed the two diets showed correlations to the same parameters but now more focused on insulin, glucose and abdominal fat depot parameters. We conclude that proteomic profiles can be used as a biomarker to identify pigs with developing metabolic syndrome (prediabetes and diabetes when fed a cafeteria diet. It could be developed into a potential biomarkers for the early recognition of metabolic diseases.

  17. GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes

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    Nakayama Yoichi

    2006-03-01

    Full Text Available Abstract Background Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. Results We developed the Genome-based Modeling (GEM System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. Conclusion The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

  18. Multi site Kinetic Modeling of 13C Metabolic MR Using [1-13C]Pyruvate

    International Nuclear Information System (INIS)

    Damian, P.A.G.; Sperl, J.I.; Janich, M.A.; Wiesinger, F.; Schulte, R.F.; Menzel, M.I.; Damian, P.A.G.; Damian, P.A.G.; Haase, A.; Janich, M.A.; Schwaiger, M.; Janich, M.A.; Khegai, O.; Glaser, S.J.

    2014-01-01

    Hyperpolarized 13 C imaging allows real-time in vivo measurements of metabolite levels. Quantification of metabolite conversion between [1- 13 C]pyruvate and downstream metabolites [1- 13 C]alanine, [1- 13 C]lactate, and [ 13 C] bicarbonate can be achieved through kinetic modeling. Since pyruvate interacts dynamically and simultaneously with its downstream metabolites, the purpose of this work is the determination of parameter values through a multi site, dynamic model involving possible biochemical pathways present in MR spectroscopy. Kinetic modeling parameters were determined by fitting the multi site model to time-domain dynamic metabolite data. The results for different pyruvate doses were compared with those of different two-site models to evaluate the hypothesis that for identical data the uncertainty of a model and the signal-to-noise ratio determine the sensitivity in detecting small physiological differences in the target metabolism. In comparison to the two-site exchange models, the multi site model yielded metabolic conversion rates with smaller bias and smaller standard deviation, as demonstrated in simulations with different signal-to-noise ratio. Pyruvate dose effects observed previously were confirmed and quantified through metabolic conversion rate values. Parameter interdependency allowed an accurate quantification and can therefore be useful for monitoring metabolic activity in different tissues

  19. Multisite Kinetic Modeling of 13C Metabolic MR Using [1-13C]Pyruvate

    Directory of Open Access Journals (Sweden)

    Pedro A. Gómez Damián

    2014-01-01

    Full Text Available Hyperpolarized 13C imaging allows real-time in vivo measurements of metabolite levels. Quantification of metabolite conversion between [1-13C]pyruvate and downstream metabolites [1-13C]alanine, [1-13C]lactate, and [13C]bicarbonate can be achieved through kinetic modeling. Since pyruvate interacts dynamically and simultaneously with its downstream metabolites, the purpose of this work is the determination of parameter values through a multisite, dynamic model involving possible biochemical pathways present in MR spectroscopy. Kinetic modeling parameters were determined by fitting the multisite model to time-domain dynamic metabolite data. The results for different pyruvate doses were compared with those of different two-site models to evaluate the hypothesis that for identical data the uncertainty of a model and the signal-to-noise ratio determine the sensitivity in detecting small physiological differences in the target metabolism. In comparison to the two-site exchange models, the multisite model yielded metabolic conversion rates with smaller bias and smaller standard deviation, as demonstrated in simulations with different signal-to-noise ratio. Pyruvate dose effects observed previously were confirmed and quantified through metabolic conversion rate values. Parameter interdependency allowed an accurate quantification and can therefore be useful for monitoring metabolic activity in different tissues.

  20. Glutathione metabolism modelling: a mechanism for liver drug-robustness and a new biomarker strategy

    NARCIS (Netherlands)

    Geenen, S.; du Preez, F.B.; Snoep, J.L.; Foster, A.J.; Sarda, S.; Kenna, J.G.; Wilson, I.D.; Westerhoff, H.V.

    2013-01-01

    Background Glutathione metabolism can determine an individual's ability to detoxify drugs. To increase understanding of the dynamics of cellular glutathione homeostasis, we have developed an experiment-based mathematical model of the kinetics of the glutathione network. This model was used to

  1. Multivariate modelling of endophenotypes associated with the metabolic syndrome in Chinese twins

    DEFF Research Database (Denmark)

    Pang, Z; Zhang, D; Li, S

    2010-01-01

    AIMS/HYPOTHESIS: The common genetic and environmental effects on endophenotypes related to the metabolic syndrome have been investigated using bivariate and multivariate twin models. This paper extends the pairwise analysis approach by introducing independent and common pathway models to Chinese...

  2. A remediation performance model for enhanced metabolic reductive dechlorination of chloroethenes in fractured clay till

    DEFF Research Database (Denmark)

    Manoli, Gabriele; Chambon, Julie C.; Bjerg, Poul L.

    2012-01-01

    A numerical model of metabolic reductive dechlorination is used to describe the performance of enhanced bioremediation in fractured clay till. The model is developed to simulate field observations of a full scale bioremediation scheme in a fractured clay till and thereby to assess remediation...

  3. The cellular and compartmental profile of mouse retinal glycolysis, tricarboxylic acid cycle, oxidative phosphorylation, and ~P transferring kinases.

    Science.gov (United States)

    Rueda, Elda M; Johnson, Jerry E; Giddabasappa, Anand; Swaroop, Anand; Brooks, Matthew J; Sigel, Irena; Chaney, Shawnta Y; Fox, Donald A

    2016-01-01

    The homeostatic regulation of cellular ATP is achieved by the coordinated activity of ATP utilization, synthesis, and buffering. Glucose is the major substrate for ATP synthesis through glycolysis and oxidative phosphorylation (OXPHOS), whereas intermediary metabolism through the tricarboxylic acid (TCA) cycle utilizes non-glucose-derived monocarboxylates, amino acids, and alpha ketoacids to support mitochondrial ATP and GTP synthesis. Cellular ATP is buffered by specialized equilibrium-driven high-energy phosphate (~P) transferring kinases. Our goals were twofold: 1) to characterize the gene expression, protein expression, and activity of key synthesizing and regulating enzymes of energy metabolism in the whole mouse retina, retinal compartments, and/or cells and 2) to provide an integrative analysis of the results related to function. mRNA expression data of energy-related genes were extracted from our whole retinal Affymetrix microarray data. Fixed-frozen retinas from adult C57BL/6N mice were used for immunohistochemistry, laser scanning confocal microscopy, and enzymatic histochemistry. The immunoreactivity levels of well-characterized antibodies, for all major retinal cells and their compartments, were obtained using our established semiquantitative confocal and imaging techniques. Quantitative cytochrome oxidase (COX) and lactate dehydrogenase (LDH) activity was determined histochemically. The Affymetrix data revealed varied gene expression patterns of the ATP synthesizing and regulating enzymes found in the muscle, liver, and brain. Confocal studies showed differential cellular and compartmental distribution of isozymes involved in glucose, glutamate, glutamine, lactate, and creatine metabolism. The pattern and intensity of the antibodies and of the COX and LDH activity showed the high capacity of photoreceptors for aerobic glycolysis and OXPHOS. Competition assays with pyruvate revealed that LDH-5 was localized in the photoreceptor inner segments. The

  4. Development of Computational Tools for Metabolic Model Curation, Flux Elucidation and Strain Design

    Energy Technology Data Exchange (ETDEWEB)

    Maranas, Costas D

    2012-05-21

    An overarching goal of the Department of Energy mission is the efficient deployment and engineering of microbial and plant systems to enable biomass conversion in pursuit of high energy density liquid biofuels. This has spurred the pace at which new organisms are sequenced and annotated. This torrent of genomic information has opened the door to understanding metabolism in not just skeletal pathways and a handful of microorganisms but for truly genome-scale reconstructions derived for hundreds of microbes and plants. Understanding and redirecting metabolism is crucial because metabolic fluxes are unique descriptors of cellular physiology that directly assess the current cellular state and quantify the effect of genetic engineering interventions. At the same time, however, trying to keep pace with the rate of genomic data generation has ushered in a number of modeling and computational challenges related to (i) the automated assembly, testing and correction of genome-scale metabolic models, (ii) metabolic flux elucidation using labeled isotopes, and (iii) comprehensive identification of engineering interventions leading to the desired metabolism redirection.

  5. Novel insights into obesity and diabetes through genome-scale metabolic modeling

    Directory of Open Access Journals (Sweden)

    Leif eVäremo

    2013-04-01

    Full Text Available The growing prevalence of metabolic diseases, such as obesity and diabetes, are putting a high strain on global healthcare systems as well as increasing the demand for efficient treatment strategies. More than 360 million people worldwide are suffering from type 2 diabetes and, with the current trends, the projection is that 10% of the global adult population will be affected by 2030. In light of the systemic properties of metabolic diseases as well as the interconnected nature of metabolism, it is necessary to begin taking a holistic approach to study these diseases. Human genome-scale metabolic models (GEMs are topological and mathematical representations of cell metabolism and have proven to be valuable tools in the area of systems biology. Successful applications of GEMs include the process of gaining further biological and mechanistic understanding of diseases, finding potential biomarkers and identifying new drug targets. This review will focus on the modeling of human metabolism in the field of obesity and diabetes, showing its vast range of applications of clinical importance as well as point out future challenges.

  6. Deriving metabolic engineering strategies from genome-scale modeling with flux ratio constraints.

    Science.gov (United States)

    Yen, Jiun Y; Nazem-Bokaee, Hadi; Freedman, Benjamin G; Athamneh, Ahmad I M; Senger, Ryan S

    2013-05-01

    Optimized production of bio-based fuels and chemicals from microbial cell factories is a central goal of systems metabolic engineering. To achieve this goal, a new computational method of using flux balance analysis with flux ratios (FBrAtio) was further developed in this research and applied to five case studies to evaluate and design metabolic engineering strategies. The approach was implemented using publicly available genome-scale metabolic flux models. Synthetic pathways were added to these models along with flux ratio constraints by FBrAtio to achieve increased (i) cellulose production from Arabidopsis thaliana; (ii) isobutanol production from Saccharomyces cerevisiae; (iii) acetone production from Synechocystis sp. PCC6803; (iv) H2 production from Escherichia coli MG1655; and (v) isopropanol, butanol, and ethanol (IBE) production from engineered Clostridium acetobutylicum. The FBrAtio approach was applied to each case to simulate a metabolic engineering strategy already implemented experimentally, and flux ratios were continually adjusted to find (i) the end-limit of increased production using the existing strategy, (ii) new potential strategies to increase production, and (iii) the impact of these metabolic engineering strategies on product yield and culture growth. The FBrAtio approach has the potential to design "fine-tuned" metabolic engineering strategies in silico that can be implemented directly with available genomic tools. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. DMPy: a Python package for automated mathematical model construction of large-scale metabolic systems.

    Science.gov (United States)

    Smith, Robert W; van Rosmalen, Rik P; Martins Dos Santos, Vitor A P; Fleck, Christian

    2018-06-19

    Models of metabolism are often used in biotechnology and pharmaceutical research to identify drug targets or increase the direct production of valuable compounds. Due to the complexity of large metabolic systems, a number of conclusions have been drawn using mathematical methods with simplifying assumptions. For example, constraint-based models describe changes of internal concentrations that occur much quicker than alterations in cell physiology. Thus, metabolite concentrations and reaction fluxes are fixed to constant values. This greatly reduces the mathematical complexity, while providing a reasonably good description of the system in steady state. However, without a large number of constraints, many different flux sets can describe the optimal model and we obtain no information on how metabolite levels dynamically change. Thus, to accurately determine what is taking place within the cell, finer quality data and more detailed models need to be constructed. In this paper we present a computational framework, DMPy, that uses a network scheme as input to automatically search for kinetic rates and produce a mathematical model that describes temporal changes of metabolite fluxes. The parameter search utilises several online databases to find measured reaction parameters. From this, we take advantage of previous modelling efforts, such as Parameter Balancing, to produce an initial mathematical model of a metabolic pathway. We analyse the effect of parameter uncertainty on model dynamics and test how recent flux-based model reduction techniques alter system properties. To our knowledge this is the first time such analysis has been performed on large models of metabolism. Our results highlight that good estimates of at least 80% of the reaction rates are required to accurately model metabolic systems. Furthermore, reducing the size of the model by grouping reactions together based on fluxes alters the resulting system dynamics. The presented pipeline automates the

  8. The Genome-Based Metabolic Systems Engineering to Boost Levan Production in a Halophilic Bacterial Model.

    Science.gov (United States)

    Aydin, Busra; Ozer, Tugba; Oner, Ebru Toksoy; Arga, Kazim Yalcin

    2018-03-01

    Metabolic systems engineering is being used to redirect microbial metabolism for the overproduction of chemicals of interest with the aim of transforming microbial hosts into cellular factories. In this study, a genome-based metabolic systems engineering approach was designed and performed to improve biopolymer biosynthesis capability of a moderately halophilic bacterium Halomonas smyrnensis AAD6 T producing levan, which is a fructose homopolymer with many potential uses in various industries and medicine. For this purpose, the genome-scale metabolic model for AAD6 T was used to characterize the metabolic resource allocation, specifically to design metabolic engineering strategies for engineered bacteria with enhanced levan production capability. Simulations were performed in silico to determine optimal gene knockout strategies to develop new strains with enhanced levan production capability. The majority of the gene knockout strategies emphasized the vital role of the fructose uptake mechanism, and pointed out the fructose-specific phosphotransferase system (PTS fru ) as the most promising target for further metabolic engineering studies. Therefore, the PTS fru of AAD6 T was restructured with insertional mutagenesis and triparental mating techniques to construct a novel, engineered H. smyrnensis strain, BMA14. Fermentation experiments were carried out to demonstrate the high efficiency of the mutant strain BMA14 in terms of final levan concentration, sucrose consumption rate, and sucrose conversion efficiency, when compared to the AAD6 T . The genome-based metabolic systems engineering approach presented in this study might be considered an efficient framework to redirect microbial metabolism for the overproduction of chemicals of interest, and the novel strain BMA14 might be considered a potential microbial cell factory for further studies aimed to design levan production processes with lower production costs.

  9. The human body metabolism process mathematical simulation based on Lotka-Volterra model

    Science.gov (United States)

    Oliynyk, Andriy; Oliynyk, Eugene; Pyptiuk, Olexandr; DzierŻak, RóŻa; Szatkowska, Małgorzata; Uvaysova, Svetlana; Kozbekova, Ainur

    2017-08-01

    The mathematical model of metabolism process in human organism based on Lotka-Volterra model has beeng proposed, considering healing regime, nutrition system, features of insulin and sugar fragmentation process in the organism. The numerical algorithm of the model using IV-order Runge-Kutta method has been realized. After the result of calculations the conclusions have been made, recommendations about using the modeling results have been showed, the vectors of the following researches are defined.

  10. MetRxn: a knowledgebase of metabolites and reactions spanning metabolic models and databases

    Directory of Open Access Journals (Sweden)

    Kumar Akhil

    2012-01-01

    Full Text Available Abstract Background Increasingly, metabolite and reaction information is organized in the form of genome-scale metabolic reconstructions that describe the reaction stoichiometry, directionality, and gene to protein to reaction associations. A key bottleneck in the pace of reconstruction of new, high-quality metabolic models is the inability to directly make use of metabolite/reaction information from biological databases or other models due to incompatibilities in content representation (i.e., metabolites with multiple names across databases and models, stoichiometric errors such as elemental or charge imbalances, and incomplete atomistic detail (e.g., use of generic R-group or non-explicit specification of stereo-specificity. Description MetRxn is a knowledgebase that includes standardized metabolite and reaction descriptions by integrating information from BRENDA, KEGG, MetaCyc, Reactome.org and 44 metabolic models into a single unified data set. All metabolite entries have matched synonyms, resolved protonation states, and are linked to unique structures. All reaction entries are elementally and charge balanced. This is accomplished through the use of a workflow of lexicographic, phonetic, and structural comparison algorithms. MetRxn allows for the download of standardized versions of existing genome-scale metabolic models and the use of metabolic information for the rapid reconstruction of new ones. Conclusions The standardization in description allows for the direct comparison of the metabolite and reaction content between metabolic models and databases and the exhaustive prospecting of pathways for biotechnological production. This ever-growing dataset currently consists of over 76,000 metabolites participating in more than 72,000 reactions (including unresolved entries. MetRxn is hosted on a web-based platform that uses relational database models (MySQL.

  11. Genome-based Modeling and Design of Metabolic Interactions in Microbial Communities.

    Science.gov (United States)

    Mahadevan, Radhakrishnan; Henson, Michael A

    2012-01-01

    Biotechnology research is traditionally focused on individual microbial strains that are perceived to have the necessary metabolic functions, or the capability to have these functions introduced, to achieve a particular task. For many important applications, the development of such omnipotent microbes is an extremely challenging if not impossible task. By contrast, nature employs a radically different strategy based on synergistic combinations of different microbial species that collectively achieve the desired task. These natural communities have evolved to exploit the native metabolic capabilities of each species and are highly adaptive to changes in their environments. However, microbial communities have proven difficult to study due to a lack of suitable experimental and computational tools. With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

  12. A Laminin-2, Dystroglycan, Utrophin Axis is Required for Compartmentalization and Elongation of Myelin Segments

    OpenAIRE

    Court, Felipe A.; Hewitt, Jane E.; Davies, Kay; Patton, Bruce L.; Uncini, Antonino; Wrabetz, Lawrence; Feltri, M. Laura

    2009-01-01

    Animal and plant cells compartmentalize to perform morphogenetic functions. Compartmentalization of myelin-forming Schwann cells may favor elongation of myelin segments to the size required for efficient conduction of nerve impulses. Compartments in myelinated fibers were described by Ramon-y-Cajal and depend on periaxin, mutated in the hereditary neuropathy Charcot-Marie-Tooth 4F. Lack of periaxin in mice causes loss of compartments, formation of short myelin segments (internodes) and reduce...

  13. Oral absorption and oxidative metabolism of atrazine in rats evaluated by physiological modeling approaches

    International Nuclear Information System (INIS)

    McMullin, Tami S.; Hanneman, William H.; Cranmer, Brian K.; Tessari, John D.; Andersen, Melvin E.

    2007-01-01

    Atrazine (ATRA) is metabolized by cytochrome P450s to the chlorinated metabolites, 2-chloro-4-ethylamino-6-amino-1,3,5-triazine (ETHYL), 2-chloro-4-amino-6-isopropylamino-1, 3, 5-triazine (ISO), and diaminochlorotriazine (DACT). Here, we develop a set of physiologically based pharmacokinetic (PBPK) models that describe the influence of oral absorption and oxidative metabolism on the blood time course curves of individual chlorotriazines (Cl-TRIs) in rat after oral dosing of ATRA. These models first incorporated in vitro metabolic parameters to describe time course plasma concentrations of DACT, ETHYL, and ISO after dosing with each compound. Parameters from each individual model were linked together into a final composite model in order to describe the time course of all 4 Cl-TRIs after ATRA dosing. Oral administration of ISO, ETHYL and ATRA produced double peaks of the compounds in plasma time courses that were described by multiple absorption phases from gut. An adequate description of the uptake and bioavailability of absorbed ATRA also required inclusion of additional oxidative metabolic clearance of ATRA to the mono-dealkylated metabolites occurring in GI a tract compartment. These complex processes regulating tissue dosimetry of atrazine and its chlorinated metabolites likely reflect limited compound solubility in the gut from dosing with an emulsion, and sequential absorption and metabolism along the GI tract at these high oral doses

  14. Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model

    Directory of Open Access Journals (Sweden)

    Hui Chen

    2014-01-01

    Full Text Available Metabolic syndrome is worldwide public health problem and is a serious threat to people's health and lives. Understanding the relationship between metabolic syndrome and the physical symptoms is a difficult and challenging task, and few studies have been performed in this field. It is important to classify adults who are at high risk of metabolic syndrome without having to use a biochemical index and, likewise, it is important to develop technology that has a high economic rate of return to simplify the complexity of this detection. In this paper, an artificial intelligence model was developed to identify adults at risk of metabolic syndrome based on physical signs; this artificial intelligence model achieved more powerful capacity for classification compared to the PCLR (principal component logistic regression model. A case study was performed based on the physical signs data, without using a biochemical index, that was collected from the staff of Lanzhou Grid Company in Gansu province of China. The results show that the developed artificial intelligence model is an effective classification system for identifying individuals at high risk of metabolic syndrome.

  15. Systems biology from micro-organisms to human metabolic diseases: the role of detailed kinetic models.

    Science.gov (United States)

    Bakker, Barbara M; van Eunen, Karen; Jeneson, Jeroen A L; van Riel, Natal A W; Bruggeman, Frank J; Teusink, Bas

    2010-10-01

    Human metabolic diseases are typically network diseases. This holds not only for multifactorial diseases, such as metabolic syndrome or Type 2 diabetes, but even when a single gene defect is the primary cause, where the adaptive response of the entire network determines the severity of disease. The latter may differ between individuals carrying the same mutation. Understanding the adaptive responses of human metabolism naturally requires a systems biology approach. Modelling of metabolic pathways in micro-organisms and some mammalian tissues has yielded many insights, qualitative as well as quantitative, into their control and regulation. Yet, even for a well-known pathway such as glycolysis, precise predictions of metabolite dynamics from experimentally determined enzyme kinetics have been only moderately successful. In the present review, we compare kinetic models of glycolysis in three cell types (African trypanosomes, yeast and skeletal muscle), evaluate their predictive power and identify limitations in our understanding. Although each of these models has its own merits and shortcomings, they also share common features. For example, in each case independently measured enzyme kinetic parameters were used as input. Based on these 'lessons from glycolysis', we will discuss how to make best use of kinetic computer models to advance our understanding of human metabolic diseases.

  16. Genome-scale metabolic modeling of Mucor circinelloides and comparative analysis with other oleaginous species.

    Science.gov (United States)

    Vongsangnak, Wanwipa; Klanchui, Amornpan; Tawornsamretkit, Iyarest; Tatiyaborwornchai, Witthawin; Laoteng, Kobkul; Meechai, Asawin

    2016-06-01

    We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Computational modeling to predict nitrogen balance during acute metabolic decompensation in patients with urea cycle disorders.

    Science.gov (United States)

    MacLeod, Erin L; Hall, Kevin D; McGuire, Peter J

    2016-01-01

    Nutritional management of acute metabolic decompensation in amino acid inborn errors of metabolism (AA IEM) aims to restore nitrogen balance. While nutritional recommendations have been published, they have never been rigorously evaluated. Furthermore, despite these recommendations, there is a wide variation in the nutritional strategies employed amongst providers, particularly regarding the inclusion of parenteral lipids for protein-free caloric support. Since randomized clinical trials during acute metabolic decompensation are difficult and potentially dangerous, mathematical modeling of metabolism can serve as a surrogate for the preclinical evaluation of nutritional interventions aimed at restoring nitrogen balance during acute decompensation in AA IEM. A validated computational model of human macronutrient metabolism was adapted to predict nitrogen balance in response to various nutritional interventions in a simulated patient with a urea cycle disorder (UCD) during acute metabolic decompensation due to dietary non-adherence or infection. The nutritional interventions were constructed from published recommendations as well as clinical anecdotes. Overall, dextrose alone (DEX) was predicted to be better at restoring nitrogen balance and limiting nitrogen excretion during dietary non-adherence and infection scenarios, suggesting that the published recommended nutritional strategy involving dextrose and parenteral lipids (ISO) may be suboptimal. The implications for patients with AA IEM are that the medical course during acute metabolic decompensation may be influenced by the choice of protein-free caloric support. These results are also applicable to intensive care patients undergoing catabolism (postoperative phase or sepsis), where parenteral nutritional support aimed at restoring nitrogen balance may be more tailored regarding metabolic fuel selection.

  18. Genome-scale metabolic models as platforms for strain design and biological discovery.

    Science.gov (United States)

    Mienda, Bashir Sajo

    2017-07-01

    Genome-scale metabolic models (GEMs) have been developed and used in guiding systems' metabolic engineering strategies for strain design and development. This strategy has been used in fermentative production of bio-based industrial chemicals and fuels from alternative carbon sources. However, computer-aided hypotheses building using established algorithms and software platforms for biological discovery can be integrated into the pipeline for strain design strategy to create superior strains of microorganisms for targeted biosynthetic goals. Here, I described an integrated workflow strategy using GEMs for strain design and biological discovery. Specific case studies of strain design and biological discovery using Escherichia coli genome-scale model are presented and discussed. The integrated workflow presented herein, when applied carefully would help guide future design strategies for high-performance microbial strains that have existing and forthcoming genome-scale metabolic models.

  19. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

    DEFF Research Database (Denmark)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan

    2016-01-01

    diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...... metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease...

  20. Compositions and methods for modeling Saccharomyces cerevisiae metabolism

    DEFF Research Database (Denmark)

    2012-01-01

    The invention provides an in silica model for determining a S. cerevisiae physiological function. The model includes a data structure relating a plurality of S. cerevisiae reactants to a plurality of S. cerevisiae reactions, a constraint set for the plurality of S. cerevisiae reactions, and comma...

  1. Constraining genome-scale models to represent the bow tie structure of metabolism for 13C metabolic flux analysis

    DEFF Research Database (Denmark)

    Backman, Tyler W.H.; Ando, David; Singh, Jahnavi

    2018-01-01

    for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13C MFA or 2S- 13C MFA, as well as provide for a substantially lower set of flux bounds......Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13C Metabolic Flux Analysis (13C MFA) and Two-Scale 13C Metabolic Flux Analysis (2S-13C MFA) are two techniques used...

  2. Need for collection of quantitative distribution data for dosimetry and metabolic modeling

    International Nuclear Information System (INIS)

    Lathrop, K.A.

    1976-01-01

    Problems in radiation dose distribution studies in humans are discussed. Data show the effective half-times for 7 Be and 75 Se in the mouse, rat, monkey, dog, and human show no correlation with weight, body surface, or other readily apparent factor that could be used to equate nonhuman and human data. Another problem sometimes encountered in attempting to extrapolate animal data to humans involves equivalent doses of the radiopharmaceutical. A usual human dose for a radiopharmaceutical is 1 ml or 0.017 mg/kg. The same solution injected into a mouse in a convenient volume of 0.1 ml results in a dose of 4 ml/kg or 240 times that received by the human. The effect on whole body retention produced by a dose difference of similar magnitude for selenium in the rat shows the retention is at least twice as great with the smaller amount. With the development of methods for the collection of data throughout the body representing the fractional distribution of radioactivity versus time, not only can more realistic dose estimates be made, but also the tools will be provided for the study of physiological and biochemical interrelationships in the intact subject from which compartmental models may be made which have diagnostic significance. The unique requirement for quantitative biologic data needed for calculation of radiation absorbed doses is the same as the unique scientific contribution that nuclear medicine can make, which is the quantitative in vivo study of physiologic and biochemical processes. The technique involved is not the same as quantitation of a radionuclide image, but is a step beyond

  3. Skin sensitization: Modeling based on skin metabolism simulation and formation of protein conjugates

    DEFF Research Database (Denmark)

    Dimitrov, Sabcho; Low, Lawrence; Patlewicz, Grace

    2005-01-01

    alerting groups, three-dimensional (3D)-QSARs were developed to describe the multiplicity of physicochemical, steric, and electronic parameters. These 3D-QSARs, so-called pattern recognition-type models, were applied each time a latent alerting group was identified in a parent chemical or its generated...... in the model building. The TIssue MEtabolism Simulator (TIMES) software was used to integrate a skin metabolism simulator and 3D-QSARs to evaluate the reactivity of chemicals thus predicting their likely skin sensitization potency....

  4. Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

    Science.gov (United States)

    Sadhukhan, Priyanka P; Raghunathan, Anu

    2014-01-01

    Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

  5. Systematic construction of kinetic models from genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Natalie J Stanford

    Full Text Available The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.

  6. Systematic Construction of Kinetic Models from Genome-Scale Metabolic Networks

    Science.gov (United States)

    Smallbone, Kieran; Klipp, Edda; Mendes, Pedro; Liebermeister, Wolfram

    2013-01-01

    The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments. PMID:24324546

  7. High-fat diet induces significant metabolic disorders in a mouse model of polycystic ovary syndrome.

    Science.gov (United States)

    Lai, Hao; Jia, Xiao; Yu, Qiuxiao; Zhang, Chenglu; Qiao, Jie; Guan, Youfei; Kang, Jihong

    2014-11-01

    Polycystic ovary syndrome (PCOS) is the most common female endocrinopathy associated with both reproductive and metabolic disorders. Dehydroepiandrosterone (DHEA) is currently used to induce a PCOS mouse model. High-fat diet (HFD) has been shown to cause obesity and infertility in female mice. The possible effect of an HFD on the phenotype of DHEA-induced PCOS mice is unknown. The aim of the present study was to investigate both reproductive and metabolic features of DHEA-induced PCOS mice fed a normal chow or a 60% HFD. Prepubertal C57BL/6 mice (age 25 days) on the normal chow or an HFD were injected (s.c.) daily with the vehicle sesame oil or DHEA for 20 consecutive days. At the end of the experiment, both reproductive and metabolic characteristics were assessed. Our data show that an HFD did not affect the reproductive phenotype of DHEA-treated mice. The treatment of HFD, however, caused significant metabolic alterations in DHEA-treated mice, including obesity, glucose intolerance, dyslipidemia, and pronounced liver steatosis. These findings suggest that HFD induces distinct metabolic features in DHEA-induced PCOS mice. The combined DHEA and HFD treatment may thus serve as a means of studying the mechanisms involved in metabolic derangements of this syndrome, particularly in the high prevalence of hepatic steatosis in women with PCOS. © 2014 by the Society for the Study of Reproduction, Inc.

  8. Compartmentation and complexation of metals in hyperaccumulator plants

    Directory of Open Access Journals (Sweden)

    Barbara eLeitenmaier

    2013-09-01

    Full Text Available Hyperaccumulators are being intensely investigated. They are not only interesting in scientific context due to their strange behaviour in terms of dealing with high concentrations of metals, but also because of their use in phytoremediation and phytomining, for which understanding the mechanisms of hyperaccumulation is crucial. Hyperaccumulators naturally use metal accumulation as a defence against herbivores and pathogens, and therefore deal with accumulated metals in very specific ways of complexation and compartmentation, different from non-hyperaccumulator plants and also non-hyperaccumulated metals. For example, in contrast to non-hyperaccumulators, in hyperaccumulators even the classical phytochelatin-inducing metal, cadmium, is predominantly not bound by such sulfur ligands, but only by weak oxygen ligands. This applies to all hyperaccumulated metals investigated so far, as well as hyperaccumulation of the metalloid arsenic. Stronger ligands, as they have been shown to complex metals in non-hyperaccumulators, are in hyperaccumulators used for transient binding during transport to the storage sites. This confirmed that enhanced active metal transport, and not metal complexation, is the key mechanism of hyperaccumulation. Hyperaccumulators tolerate the high amount of accumulated heavy metals by sequestering them into vacuoles, usually in large storage cells of the epidermis. This is mediated by strongly elevated expression of specific transport proteins in various tissues from metal uptake in the shoots up to the storage sites in the leaf epidermis. However, this mechanism seems to be very metal specific. Non-hyperaccumulated metals in hyperaccumulators seem to be dealt with like in non-hyperaccumulator plants, i.e. detoxified by binding to strong ligands such as metallothioneins.

  9. Glycogen Storage Disease Type Ia in Canines: A Model for Human Metabolic and Genetic Liver Disease

    OpenAIRE

    Specht, Andrew; Fiske, Laurie; Erger, Kirsten; Cossette, Travis; Verstegen, John; Campbell-Thompson, Martha; Struck, Maggie B.; Lee, Young Mok; Chou, Janice Y.; Byrne, Barry J.; Correia, Catherine E.; Mah, Cathryn S.; Weinstein, David A.; Conlon, Thomas J.

    2011-01-01

    A canine model of Glycogen storage disease type Ia (GSDIa) is described. Affected dogs are homozygous for a previously described M121I mutation resulting in a deficiency of glucose-6-phosphatase-α. Metabolic, clinicopathologic, pathologic, and clinical manifestations of GSDIa observed in this model are described and compared to those observed in humans. The canine model shows more complete recapitulation of the clinical manifestations seen in humans including “lactic acidosis”, larger size,...

  10. Predicting effects of structural stress in a genome-reduced model bacterial metabolism

    Science.gov (United States)

    Güell, Oriol; Sagués, Francesc; Serrano, M. Ángeles

    2012-08-01

    Mycoplasma pneumoniae is a human pathogen recently proposed as a genome-reduced model for bacterial systems biology. Here, we study the response of its metabolic network to different forms of structural stress, including removal of individual and pairs of reactions and knockout of genes and clusters of co-expressed genes. Our results reveal a network architecture as robust as that of other model bacteria regarding multiple failures, although less robust against individual reaction inactivation. Interestingly, metabolite motifs associated to reactions can predict the propagation of inactivation cascades and damage amplification effects arising in double knockouts. We also detect a significant correlation between gene essentiality and damages produced by single gene knockouts, and find that genes controlling high-damage reactions tend to be expressed independently of each other, a functional switch mechanism that, simultaneously, acts as a genetic firewall to protect metabolism. Prediction of failure propagation is crucial for metabolic engineering or disease treatment.

  11. The contribution of atom accessibility to site of metabolism models for cytochromes P450

    DEFF Research Database (Denmark)

    Rydberg, Patrik; Rostkowski, M.; Gloriam, D.E.

    2013-01-01

    Three different types of atom accessibility descriptors are investigated in relation to site of metabolism predictions. To enable the integration of local accessibility we have constructed 2DSASA, a method for the calculation of the atomic solvent accessible surface area that is independent of 3D...... coordinates. The method was implemented in the SMARTCyp site of metabolism prediction models and improved the results by up to 4 percentage points for nine cytochrome P450 isoforms. The final models are made available at http://www.farma.ku.dk/smartcyp.......Three different types of atom accessibility descriptors are investigated in relation to site of metabolism predictions. To enable the integration of local accessibility we have constructed 2DSASA, a method for the calculation of the atomic solvent accessible surface area that is independent of 3D...

  12. Metabolic fate of 14-C-fenitrothion in a rice field model ecosystem

    International Nuclear Information System (INIS)

    Nashriyah binti Mat; Nambu, K.; Miyashita, T.; Sakata, S.; Ohshima, M.

    1991-01-01

    Pesticide fenitrothion (Sumithion sup R)is widely used to control rice stem borer and other pests. Its metabolic fate and degradation was studied using the sup 14 C-ring labelled fenitrothion in a model ecosystem consisting of Takarazuka paddy field soil, rice plant (Oryza sativa var. nihonbare), carp fish (Cyprinus carpio L.) and dechlorinated water. Radioactive fenitrothion was applied at a normal rate as used by Japanese farmers and samples of rice plant, fish soil and water were analysed after ten days of application. Fenitrothion was readily metabolized in rice plant and fish and also readily degraded to a number of metabolites in water and flooded soil. Most of the radioactivity applied was found in the soil component of the ecosystem. A trace amount of fenitrooxon, the activated metabolite of fenitrothion was detected only in soil and water. A possible metabolic pathway of fenitrothion in the rice model ecosystem was proposed

  13. The Xenopus oocyte: a model for studying the metabolic regulation of cancer cell death.

    Science.gov (United States)

    Nutt, Leta K

    2012-06-01

    Abnormal metabolism and the evasion of apoptosis are both considered hallmarks of cancer. A remarkable biochemical model system, the Xenopus laevis oocyte, exhibits altered metabolism coupled to its apoptotic machinery in a similar fashion to cancer cells. This review considers the theory that these two hallmarks of cancer are coupled in tumor cells and provides strong proof that the Xenopus laevis oocyte system is an appropriate model in which to dissect the biochemical events underlying the connection between the two hallmarks. By further elucidating the mechanisms through which metabolism suppresses apoptotic machinery, we may gain a better understanding about how normal cells transform into cancer cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

  14. An accurate description of Aspergillus niger organic acid batch fermentation through dynamic metabolic modelling.

    Science.gov (United States)

    Upton, Daniel J; McQueen-Mason, Simon J; Wood, A Jamie

    2017-01-01

    Aspergillus niger fermentation has provided the chief source of industrial citric acid for over 50 years. Traditional strain development of this organism was achieved through random mutagenesis, but advances in genomics have enabled the development of genome-scale metabolic modelling that can be used to make predictive improvements in fermentation performance. The parent citric acid-producing strain of A. niger , ATCC 1015, has been described previously by a genome-scale metabolic model that encapsulates its response to ambient pH. Here, we report the development of a novel double optimisation modelling approach that generates time-dependent citric acid fermentation using dynamic flux balance analysis. The output from this model shows a good match with empirical fermentation data. Our studies suggest that citric acid production commences upon a switch to phosphate-limited growth and this is validated by fitting to empirical data, which confirms the diauxic growth behaviour and the role of phosphate storage as polyphosphate. The calibrated time-course model reflects observed metabolic events and generates reliable in silico data for industrially relevant fermentative time series, and for the behaviour of engineered strains suggesting that our approach can be used as a powerful tool for predictive metabolic engineering.

  15. Atmospheric reaction systems as null-models to identify structural traces of evolution in metabolism.

    Directory of Open Access Journals (Sweden)

    Petter Holme

    Full Text Available The metabolism is the motor behind the biological complexity of an organism. One problem of characterizing its large-scale structure is that it is hard to know what to compare it to. All chemical reaction systems are shaped by the same physics that gives molecules their stability and affinity to react. These fundamental factors cannot be captured by standard null-models based on randomization. The unique property of organismal metabolism is that it is controlled, to some extent, by an enzymatic machinery that is subject to evolution. In this paper, we explore the possibility that reaction systems of planetary atmospheres can serve as a null-model against which we can define metabolic structure and trace the influence of evolution. We find that the two types of data can be distinguished by their respective degree distributions. This is especially clear when looking at the degree distribution of the reaction network (of reaction connected to each other if they involve the same molecular species. For the Earth's atmospheric network and the human metabolic network, we look into more detail for an underlying explanation of this deviation. However, we cannot pinpoint a single cause of the difference, rather there are several concurrent factors. By examining quantities relating to the modular-functional organization of the metabolism, we confirm that metabolic networks have a more complex modular organization than the atmospheric networks, but not much more. We interpret the more variegated modular arrangement of metabolism as a trace of evolved functionality. On the other hand, it is quite remarkable how similar the structures of these two types of networks are, which emphasizes that the constraints from the chemical properties of the molecules has a larger influence in shaping the reaction system than does natural selection.

  16. A dynamic, mechanistic model of metabolism in adipose tissue of lactating dairy cattle.

    Science.gov (United States)

    McNamara, J P; Huber, K; Kenéz, A

    2016-07-01

    Research in dairy cattle biology has resulted in a large body of knowledge on nutrition and metabolism in support of milk production and efficiency. This quantitative knowledge has been compiled in several model systems to balance and evaluate rations and predict requirements. There are also systems models for metabolism and reproduction in the cow that can be used to support research programs. Adipose tissue plays a significant role in the success and efficiency of lactation, and recent research has resulted in several data sets on genomic differences and changes in gene transcription of adipose tissue in dairy cattle. To fully use this knowledge, we need to build and expand mechanistic, dynamic models that integrate control of metabolism and production. Therefore, we constructed a second-generation dynamic, mechanistic model of adipose tissue metabolism of dairy cattle. The model describes the biochemical interconversions of glucose, acetate, β-hydroxybutyrate (BHB), glycerol, C16 fatty acids, and triacylglycerols. Data gathered from our own research and published references were used to set equation forms and parameter values. Acetate, glucose, BHB, and fatty acids are taken up from blood. The fatty acids are activated to the acyl coenzyme A moieties. Enzymatically catalyzed reactions are explicitly described with parameters including maximal velocity and substrate sensitivity. The control of enzyme activity is partially carried out by insulin and norepinephrine, portraying control in the cow. Model behavior was adequate, with sensitive responses to changing substrates and hormones. Increased nutrient uptake and increased insulin stimulate triacylglycerol synthesis, whereas a reduction in nutrient availability or increase in norepinephrine increases triacylglycerol hydrolysis and free fatty acid release to blood. This model can form a basis for more sophisticated integration of existing knowledge and future studies on metabolic efficiency of dairy cattle

  17. Compartmentalized microbial composition, oxygen gradients and nitrogen fixation in the gut of Odontotaenius disjunctus.

    Science.gov (United States)

    Ceja-Navarro, Javier A; Nguyen, Nhu H; Karaoz, Ulas; Gross, Stephanie R; Herman, Donald J; Andersen, Gary L; Bruns, Thomas D; Pett-Ridge, Jennifer; Blackwell, Meredith; Brodie, Eoin L

    2014-01-01

    Coarse woody debris is an important biomass pool in forest ecosystems that numerous groups of insects have evolved to take advantage of. These insects are ecologically important and represent useful natural analogs for biomass to biofuel conversion. Using a range of molecular approaches combined with microelectrode measurements of oxygen, we have characterized the gut microbiome and physiology of Odontotaenius disjunctus, a wood-feeding beetle native to the eastern United States. We hypothesized that morphological and physiological differences among gut regions would correspond to distinct microbial populations and activities. In fact, significantly different communities were found in the foregut (FG), midgut (MG)/posterior hindgut (PHG) and anterior hindgut (AHG), with Actinobacteria and Rhizobiales being more abundant toward the FG and PHG. Conversely, fermentative bacteria such as Bacteroidetes and Clostridia were more abundant in the AHG, and also the sole region where methanogenic Archaea were detected. Although each gut region possessed an anaerobic core, micron-scale profiling identified radial gradients in oxygen concentration in all regions. Nitrogen fixation was confirmed by (15)N2 incorporation, and nitrogenase gene (nifH) expression was greatest in the AHG. Phylogenetic analysis of nifH identified the most abundant transcript as related to Ni-Fe nitrogenase of a Bacteroidetes species, Paludibacter propionicigenes. Overall, we demonstrate not only a compartmentalized microbiome in this beetle digestive tract but also sharp oxygen gradients that may permit aerobic and anaerobic metabolism to occur within the same regions in close proximity. We provide evidence for the microbial fixation of N2 that is important for this beetle to subsist on woody biomass.

  18. Modeling metabolic response to changes of enzyme amount in ...

    African Journals Online (AJOL)

    Jane

    2010-10-11

    Oct 11, 2010 ... In this work, we first introduced the enzyme parameter (ɑ) into the kinetic equations and consequently established an in silico glycolysis model of Saccharomyces cerevisiae in XML format (Figure 1), based on the work of Hynn et al. (2001). Equation 1 shows how the ɑis introduced into the kinetic equation.

  19. Metabolic modeling of mixed substrate uptake for polyhydroxyalkanoate (PHA) production

    NARCIS (Netherlands)

    Jiang, Y.; Hebly, M.; Kleerebezem, R.; Muyzer, G.; van Loosdrecht, M.C.M.

    2011-01-01

    Polyhydroxyalkanoate (PHA) production by mixed microbial communities can be established in a two-stage process, consisting of a microbial enrichment step and a PHA accumulation step. In this study, a mathematical model was constructed for evaluating the influence of the carbon substrate composition

  20. The Establishment of Metabolic Syndrome Model by Induction of Fructose Drinking Water in Male Wistar Rats

    Directory of Open Access Journals (Sweden)

    Norshalizah Mamikutty

    2014-01-01

    Full Text Available Background. Metabolic syndrome can be caused by modification of diet by means of consumption of high carbohydrate and high fat diet such as fructose. Aims. To develop a metabolic syndrome rat model by induction of fructose drinking water (FDW in male Wistar rats. Methods. Eighteen male Wistar rats were fed with FDW 20% and FDW 25% for a duration of eight weeks. The physiological changes with regard to food and fluid intake, as well as calorie intake, were measured. The metabolic changes such as obesity, dyslipidaemia, hypertension, and hyperglycaemia were determined. Data was presented in mean ± SEM subjected to one-way ANOVA. Results. Male Wistar rats fed with FDW 20% for eight weeks developed significant higher obesity parameters compared to those fed with FDW 25%. There was hypertrophy of adipocytes in F20 and F25. There were also systolic hypertension, hypertriglyceridemia, and hyperglycemia in both groups. Conclusion. We conclude that the metabolic syndrome rat model is best established with the induction of FDW 20% for eight weeks. This was evident in the form of higher obesity parameter which caused the development of the metabolic syndrome.

  1. From reconstruction to C>4 metabolic engineering: A case study for overproduction of polyhydroxybutyrate in bioenergy grasses

    DEFF Research Database (Denmark)

    Gomes de Oliveira Dal'Molin, Cristiana; Quek, Lake-Ee; Saa, Pedro A.

    2018-01-01

    bundle sheath (B) and mesophyll (M) across the day and night cycle. The C4 leaf model was used to explore how amenable polyhydroxybutyrate (PHB) production is with these four compartments working cooperatively. A strategic pattern of metabolite conversion and exchange emerged from a systems-level network......The compartmentalization of C4 plants increases photosynthetic efficiency, while constraining how material and energy must flow in leaf tissues. To capture this metabolic phenomenon, a generic plant metabolic reconstruction was replicated into four connected spatiotemporal compartments, namely...... that has very few constraints imposed; mainly the sequential two-step carbon capture in mesophyll, then bundle sheath and photosynthesis during the day only. The building of starch reserves during the day and their mobilization during the night connects day and night metabolism. Flux simulations revealed...

  2. Development of an Age- and Gender-specific Model for Strontium Metabolism in Humans

    International Nuclear Information System (INIS)

    Shagina, N. B.; Degteva, M. O.; Tolstykh, E. I.

    2004-01-01

    This paper presents a development of a new biokinetic model for strontium, which accounts for age and gender differences of metabolism in humans. This model was developed based on the long-term follow-up of the residents living on the banks of the Techa River (Southern Urals, Russia) contaminated with 89,90Sr in 1950-1956. The new model uses the structure of ICRP model for strontium but model parameters have been estimated to account for age, gender and population differences in strontium retention and elimination. Estimates of age- and gender-specific model parameters were derived from (a) the results of long-term measurements of 90Sr-body burden for the Techa River population; (b) experimental studies of calcium and strontium metabolism in humans and (c) non-radiological data regarding bone metabolism (mineral content of the body, bone turnover, etc). As a result, the new model satisfactorily describes data on long-term retention of 90Sr in residents of the Techa River settlements of all ages and both genders and also data from studies during the period of global fallout in the UK and the USA and experimental data on strontium retention in humans. The new model can be used to calculate dose from 89,90Sr for the Techa River residents and also for other populations with similar parameters of skeletal maturation and also for other populations with similar parameters of skeletal maturation and involution. (Author) 27 refs

  3. Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data.

    Science.gov (United States)

    Gu, Deqing; Jian, Xingxing; Zhang, Cheng; Hua, Qiang

    2017-01-01

    Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named logical transformation of model (LTM) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.

  4. a metabolic wastage model for the rate-yield trade off

    Indian Academy of Sciences (India)

    A METABOLIC WASTAGE MODEL FOR THE RATE-YIELD TRADE OFF. There is a growth limiting step in which an intermediate metabolite (m) has to hit a target molecule (t). ... D= rate of diffusing out. S= the rate of formation of the metabolite. The equilibrium loss decides the yield. The no. of activated targets decide the rate ...

  5. Simulating the physiology of athletes during endurance sports events: modelling human energy conversion and metabolism

    NARCIS (Netherlands)

    van Beek, J.H.G.M.; Supandi, F.B.; Gavai, Anand; de Graaf, A.A.; Binsl, T.W.; Hettling, H.

    2011-01-01

    The human physiological system is stressed to its limits during endurance sports competition events.We describe a whole body computational model for energy conversion during bicycle racing. About 23 per cent of the metabolic energy is used for muscle work, the rest is converted to heat. We

  6. Simulating the physiology of athletes during endurance sports events: Modelling human energy conversion and metabolism

    NARCIS (Netherlands)

    Beek, J.H.G.M. van; Supandi, F.; Gavai, A.K.; Graaf, A.A. de; Binsl, T.W.; Hettling, H.

    2011-01-01

    The human physiological system is stressed to its limits during endurance sports competition events.We describe a whole body computational model for energy conversion during bicycle racing. About 23 per cent of the metabolic energy is used for muscle work, the rest is converted to heat. We

  7. Metabolic cleavage of cell-penetrating peptides in contact with epithelial models

    DEFF Research Database (Denmark)

    Tréhin, Rachel; Nielsen, Hanne Mørck; Jahnke, Heinz-Georg

    2004-01-01

    We assessed the metabolic degradation kinetics and cleavage patterns of some selected CPP (cell-penetrating peptides) after incubation with confluent epithelial models. Synthesis of N-terminal CF [5(6)-carboxyfluorescein]-labelled CPP, namely hCT (human calcitonin)-derived sequences, Tat(47-57) a...

  8. Predicting growth of the healthy infant using a genome scale metabolic model

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

    2017-01-01

    to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body...

  9. Modeling Phenotypic Metabolic Adaptations of Mycobacterium tuberculosis H37Rv under Hypoxia

    Science.gov (United States)

    2012-09-13

    Parish T, Brown AC (2008) Mycobacteria protocols. New York, NY: Humana Press. 19. Voskuil MI, Schnappinger D, Visconti KC, Harrell MI, Dolganov GM...Genomics Hum Genet 2: 343–372. 31. Kell DB (2006) Systems biology, metabolic modelling and metabolomics in drug discovery and development. Drug Discov

  10. Inter-compartmental transport of organophosphate and pyrethroid pesticides in South China: Implications for a regional risk assessment

    International Nuclear Information System (INIS)

    Li, Huizhen; Wei, Yanli; Lydy, Michael J.; You, Jing

    2014-01-01

    The dynamic flux of an organophosphate and four pyrethroid pesticides was determined in an air-(soil)-water-sediment system based on monitoring data from Guangzhou, China. The total air–water flux, including air–water gaseous exchange and atmospheric deposition, showed deposition from air to water for chlorpyrifos, bifenthrin and cypermethrin, but volatilization for lambda-cyhalothrin and permethrin. The transport of the pesticides from overlying water to sediment suggested that sediment acted as a sink for the pesticides. Additionally, distinct annual atmospheric depositional fluxes between legacy and current-use pesticides suggested the role of consumer usage in their transport throughout the system. Finally, pesticide toxicity was estimated from annual air–water-sediment flux within an urban stream in Guangzhou. A dynamic flux-based risk assessment indicated that inter-compartmental transport of chlorpyrifos decreased its atmospheric exposure, but had little influence on its aquatic toxicity. Instead, water-to-sediment transport of pyrethroids increased their sediment toxicity, which was supported by previously reported toxicity data. - Highlights: • Transport fluxes of chlorpyrifos and pyrethroids were assessed in Guangzhou, China. • Sediment acted as a sink for chlorpyrifos and pyrethroids. • Air-to-water transport decreased the exposure risk of atmospheric chlorpyrifos. • Dynamic transport might increase the risk of pyrethroids in air and sediment. • Flux-based pesticide concentrations provide a way to estimate sediment toxicity. - Regional risk assessment could be improved by integrating dynamic flux information derived from inter-compartmental models

  11. Modeling phenotypic metabolic adaptations of Mycobacterium tuberculosis H37Rv under hypoxia.

    Directory of Open Access Journals (Sweden)

    Xin Fang

    Full Text Available The ability to adapt to different conditions is key for Mycobacterium tuberculosis, the causative agent of tuberculosis (TB, to successfully infect human hosts. Adaptations allow the organism to evade the host immune responses during acute infections and persist for an extended period of time during the latent infectious stage. In latently infected individuals, estimated to include one-third of the human population, the organism exists in a variety of metabolic states, which impedes the development of a simple strategy for controlling or eradicating this disease. Direct knowledge of the metabolic states of M. tuberculosis in patients would aid in the management of the disease as well as in forming the basis for developing new drugs and designing more efficacious drug cocktails. Here, we propose an in silico approach to create state-specific models based on readily available gene expression data. The coupling of differential gene expression data with a metabolic network model allowed us to characterize the metabolic adaptations of M. tuberculosis H37Rv to hypoxia. Given the microarray data for the alterations in gene expression, our model predicted reduced oxygen uptake, ATP production changes, and a global change from an oxidative to a reductive tricarboxylic acid (TCA program. Alterations in the biomass composition indicated an increase in the cell wall metabolites required for cell-wall growth, as well as heightened accumulation of triacylglycerol in preparation for a low-nutrient, low metabolic activity life style. In contrast, the gene expression program in the deletion mutant of dosR, which encodes the immediate hypoxic response regulator, failed to adapt to low-oxygen stress. Our predictions were compatible with recent experimental observations of M. tuberculosis activity under hypoxic and anaerobic conditions. Importantly, alterations in the flow and accumulation of a particular metabolite were not necessarily directly linked to

  12. Quantitative aspects and dynamic modelling of glucosinolate metabolism

    DEFF Research Database (Denmark)

    Vik, Daniel

    . This enables comparison of transcript and protein levels across mutants and upon induction. I find that unchallenged plants show good correspondence between protein and transcript, but that treatment with methyljasmonate results in significant differences (chapter 1). Functional genomics are used to study......). The construction a dynamic quantitative model of GLS hydrolysis is described. Simulations reveal potential effects on auxin signalling that could reflect defensive strategies (chapter 4). The results presented grant insights into, not only the dynamics of GLS biosynthesis and hydrolysis, but also the relationship...

  13. Functional Effects of Prebiotic Fructans in Colon Cancer and Calcium Metabolism in Animal Models

    OpenAIRE

    Rivera-Huerta, Marisol; Liz?rraga-Grimes, Vania Lorena; Castro-Torres, Ibrahim Guillermo; Tinoco-M?ndez, Mabel; Mac?as-Rosales, Luc?a; S?nchez-Bart?z, Francisco; Tapia-P?rez, Graciela Guadalupe; Romero-Romero, Laura; Gracia-Mora, Mar?a Isabel

    2017-01-01

    Inulin-type fructans are polymers of fructose molecules and are known for their capacity to enhance absorption of calcium and magnesium, to modulate gut microbiota and energy metabolism, and to improve glycemia. We evaluated and compared the effects of Chicory inulin “Synergy 1®” and inulin from Mexican agave “Metlin®” in two experimental models of colon cancer and bone calcium metabolism in mice and rats. Inulins inhibited the development of dextran sulfate sodium-induced colitis and colon c...

  14. Advanced computational workflow for the multi-scale modeling of the bone metabolic processes.

    Science.gov (United States)

    Dao, Tien Tuan

    2017-06-01

    Multi-scale modeling of the musculoskeletal system plays an essential role in the deep understanding of complex mechanisms underlying the biological phenomena and processes such as bone metabolic processes. Current multi-scale models suffer from the isolation of sub-models at each anatomical scale. The objective of this present work was to develop a new fully integrated computational workflow for simulating bone metabolic processes at multi-scale levels. Organ-level model employs multi-body dynamics to estimate body boundary and loading conditions from body kinematics. Tissue-level model uses finite element method to estimate the tissue deformation and mechanical loading under body loading conditions. Finally, cell-level model includes bone remodeling mechanism through an agent-based simulation under tissue loading. A case study on the bone remodeling process located on the human jaw was performed and presented. The developed multi-scale model of the human jaw was validated using the literature-based data at each anatomical level. Simulation outcomes fall within the literature-based ranges of values for estimated muscle force, tissue loading and cell dynamics during bone remodeling process. This study opens perspectives for accurately simulating bone metabolic processes using a fully integrated computational workflow leading to a better understanding of the musculoskeletal system function from multiple length scales as well as to provide new informative data for clinical decision support and industrial applications.

  15. Topological and kinetic determinants of the modal matrices of dynamic models of metabolism.

    Directory of Open Access Journals (Sweden)

    Bin Du

    Full Text Available Large-scale kinetic models of metabolism are becoming increasingly comprehensive and accurate. A key challenge is to understand the biochemical basis of the dynamic properties of these models. Linear analysis methods are well-established as useful tools for characterizing the dynamic response of metabolic networks. Central to linear analysis methods are two key matrices: the Jacobian matrix (J and the modal matrix (M-1 arising from its eigendecomposition. The modal matrix M-1 contains dynamically independent motions of the kinetic model near a reference state, and it is sparse in practice for metabolic networks. However, connecting the structure of M-1 to the kinetic properties of the underlying reactions is non-trivial. In this study, we analyze the relationship between J, M-1, and the kinetic properties of the underlying network for kinetic models of metabolism. Specifically, we describe the origin of mode sparsity structure based on features of the network stoichiometric matrix S and the reaction kinetic gradient matrix G. First, we show that due to the scaling of kinetic parameters in real networks, diagonal dominance occurs in a substantial fraction of the rows of J, resulting in simple modal structures with clear biological interpretations. Then, we show that more complicated modes originate from topologically-connected reactions that have similar reaction elasticities in G. These elasticities represent dynamic equilibrium balances within reactions and are key determinants of modal structure. The work presented should prove useful towards obtaining an understanding of the dynamics of kinetic models of metabolism, which are rooted in the network structure and the kinetic properties of reactions.

  16. Insulin Signaling, Resistance, and the Metabolic Syndrome: Insights from Mouse Models to Disease Mechanisms

    Science.gov (United States)

    Guo, Shaodong

    2014-01-01

    Insulin resistance is a major underlying mechanism for the “metabolic syndrome”, which is also known as insulin resistance syndrome. Metabolic syndrome is increasing at an alarming rate, becoming a major public and clinical problem worldwide. Metabolic syndrome is represented by a group of interrelated disorders, including obesity, hyperglycemia, hyperlipidemia, and hypertension. It is also a significant risk factor for cardiovascular disease and increased morbidity and mortality. Animal studies demonstrate that insulin and its signaling cascade normally control cell growth, metabolism and survival through activation of mitogen-activated protein kinases (MAPKs) and phosphotidylinositide-3-kinase (PI3K), of which activation of PI-3K-associated with insulin receptor substrate-1 and -2 (IRS1, 2) and subsequent Akt→Foxo1 phosphorylation cascade has a central role in control of nutrient homeostasis and organ survival. Inactivation of Akt and activation of Foxo1, through suppression IRS1 and IRS2 in different organs following hyperinsulinemia, metabolic inflammation, and over nutrition may provide the underlying mechanisms for metabolic syndrome in humans. Targeting the IRS→Akt→Foxo1 signaling cascade will likely provide a strategy for therapeutic intervention in the treatment of type 2 diabetes and its complications. This review discusses the basis of insulin signaling, insulin resistance in different mouse models, and how a deficiency of insulin signaling components in different organs contributes to the feature of the metabolic syndrome. Emphasis will be placed on the role of IRS1, IRS2, and associated signaling pathways that couple to Akt and the forkhead/winged helix transcription factor Foxo1. PMID:24281010

  17. Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim

    2008-01-01

    Background: Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number...... to a genome scale metabolic model of A. oryzae. Results: Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted...... model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion: A much enhanced annotation of the A. oryzae genome was performed and a genomescale metabolic model of A. oryzae was reconstructed. The model accurately predicted...

  18. Simultaneous Parameters Identifiability and Estimation of an E. coli Metabolic Network Model

    Directory of Open Access Journals (Sweden)

    Kese Pontes Freitas Alberton

    2015-01-01

    Full Text Available This work proposes a procedure for simultaneous parameters identifiability and estimation in metabolic networks in order to overcome difficulties associated with lack of experimental data and large number of parameters, a common scenario in the modeling of such systems. As case study, the complex real problem of parameters identifiability of the Escherichia coli K-12 W3110 dynamic model was investigated, composed by 18 differential ordinary equations and 35 kinetic rates, containing 125 parameters. With the procedure, model fit was improved for most of the measured metabolites, achieving 58 parameters estimated, including 5 unknown initial conditions. The results indicate that simultaneous parameters identifiability and estimation approach in metabolic networks is appealing, since model fit to the most of measured metabolites was possible even when important measures of intracellular metabolites and good initial estimates of parameters are not available.

  19. In Vitro Disease Model of Microgravity Conditioning on Human Energy Metabolism

    Science.gov (United States)

    Snyder, Jessica; Culbertson, C.; Zhang, Ye; Emami, K.; Wu, H.; Sun, Wei

    2010-01-01

    NASA and its partners are committed to introducing appropriate new technology to enable learning and living safely beyond the Earth for extended periods of time in a sustainable and possibly indefinite manner. In the responsible acquisition of that goal, life sciences is tasked to tune and advance current medical technology to prepare for human health and wellness in the space environment. The space environment affects the condition and function of biological systems from organ level function to shape of individual organelles. The objective of this paper is to study the effect of microgravity on kinetics of drug metabolism. This fundamental characterization is meaningful to (1) scientific understanding of the response of biology to microgravity and (2) clinical dosing requirements and pharmacological thresholds during long term manned space exploration. Metabolism kinetics of the anti-nausea drug promethazine (PMZ) were determined by an in vitro ground model of 3-dimensional aggregates of human hepatocytes conditioned to weightlessness using a rotating wall bioreactor. The authors observed up-regulated PMZ conversion in model microgravity conditions and attribute this to effect to model microgravity conditioning acting on metabolic mechanisms of the cells. Further work is necessary to determine which particular cellular mechanisms are governing the experimental observations, but the authors conclude kinetics of drug metabolism are responsive to gravitational fields and further study of this sensitivity would improve dosing of pharmaceuticals to persons exposed to a microgravity environment.

  20. Model-driven discovery of underground metabolic functions in Escherichia coli

    DEFF Research Database (Denmark)

    Guzmán, Gabriela I.; Utrilla, José; Nurk, Sergey

    2015-01-01

    -scale models, which have been widely used for predicting growth phenotypes in various environments or following a genetic perturbation; however, these predictions occasionally fail. Failed predictions of gene essentiality offer an opportunity for targeting biological discovery, suggesting the presence......E, and gltA and prpC. This study demonstrates how a targeted model-driven approach to discovery can systematically fill knowledge gaps, characterize underground metabolism, and elucidate regulatory mechanisms of adaptation in response to gene KO perturbations....

  1. A Kinetic Modelling of Enzyme Inhibitions in the Central Metabolism of Yeast Cells

    Science.gov (United States)

    Kasbawati; Kalondeng, A.; Aris, N.; Erawaty, N.; Azis, M. I.

    2018-03-01

    Metabolic regulation plays an important role in the metabolic engineering of a cellular process. It is conducted to improve the productivity of a microbial process by identifying the important regulatory nodes of a metabolic pathway such as fermentation pathway. Regulation of enzymes involved in a particular pathway can be held to improve the productivity of the system. In the central metabolism of yeast cell, some enzymes are known as regulating enzymes that can be inhibited to increase the production of ethanol. In this research we study the kinetic modelling of the enzymes in the central pathway of yeast metabolism by taking into consideration the enzyme inhibition effects to the ethanol production. The existence of positive steady state solution and the stability of the system are also analysed to study the property and dynamical behaviour of the system. One stable steady state of the system is produced if some conditions are fulfilled. The conditions concern to the restriction of the maximum reactions of the enzymes in the pyruvate and acetaldehyde branch points. There exists a certain time of fermentation reaction at which a maximum and a minimum ethanol productions are attained after regulating the system. Optimal ethanol concentration is also produced for a certain initial concentration of inhibitor.

  2. Mathematical solutions to problems in radiological protection involving air sampling and biokinetic modelling

    International Nuclear Information System (INIS)

    Birchall, A.

    1989-04-01

    Intakes of radionuclides are estimated with the personal air sampler (PAS) and by biological monitoring techniques: in the case of plutonium, there are problems with both methods. The statistical variation in activity collected when sampling radioactive aerosols with low number concentrations was investigated. It was shown that the PAS is barely adequate for monitoring plutonium at annual limit of intake (ALI) levels in typical workplace conditions. Two algorithms were developed, enabling non-recycling and recycling compartmental models to be solved. Their accuracy and speed were investigated, and methods of dealing with partitioning, continuous intake, and radioactive progeny were discussed. Analytical, rather than numerical, methods were used. These are faster, and thus ideally suited for implementation on microcomputers. The algorithms enable non-specialists to solve quickly and easily any first order compartmental model, including all the ICRP metabolic models. Non-recycling models with up to 50 compartments can be solved in seconds: recycling models take a little longer. A biokinetic model for plutonium in man following systemic uptake was developed. The proposed ICRP lung model (1989) was represented by a first order compartmental model. These two models were combined, and the recycling algorithm was used to calculate urinary and faecal excretion of plutonium following acute or chronic intake by inhalation. The results indicate much lower urinary excretion than predicted by ICRP Publication 54. (author)

  3. Application of the transtheoretical model: exercise behavior in Korean adults with metabolic syndrome.

    Science.gov (United States)

    Kim, Chun-Ja; Kim, Bom-Taeck; Chae, Sun-Mi

    2010-01-01

    Although regular exercise has been recommended to reduce the risk of cardiovascular disease (CVD) among people with metabolic syndrome, little information is available about psychobehavioral strategies in this population. The purpose of this study was to identify the stages, processes of change, decisional balance, and self-efficacy of exercise behavior and to determine the significant predictors explaining regular exercise behavior in adults with metabolic syndrome. This descriptive, cross-sectional survey design enrolled a convenience sample of 210 people with metabolic syndrome at a university hospital in South Korea. Descriptive statistics were used to analyze demographic characteristics, metabolic syndrome risk factors, and transtheoretical model-related variables. A multivariate logistic regression analysis was used to determine the most important predictors of regular exercise stages. Action and maintenance stages comprised 51.9% of regular exercise stages, whereas 48.1% of non-regular exercise stages were precontemplation, contemplation, and preparation stages. Adults with regular exercise stages displayed increased high-density lipoprotein cholesterol level, were more likely to use consciousness raising, self-reevaluation, and self-liberation strategies, and were less likely to evaluate the merits/disadvantages of exercise, compared with those in non-regular exercise stages. In this study of regular exercise behavior and transtheoretical model-related variables, consciousness raising, self-reevaluation, and self-liberation were associated with a positive effect on regular exercise behavior in adults with metabolic syndrome. Our findings could be used to develop strategies and interventions to maintain regular exercise behavior directed at Korean adults with metabolic syndrome to reduce CVD risk. Further prospective intervention studies are needed to investigate the effect of regular exercise program on the prevention and/or reduction of CVD risk among this

  4. Copper metabolism: a multicompartmental model of copper kinetics in the rat

    International Nuclear Information System (INIS)

    Dunn, M.A.

    1985-01-01

    A qualitative multicompartmental model was developed that describes the whole-body kinetics of copper metabolism in the adult rat. The model was developed from radiocopper percent dose vs. time data measured over a three day period in plasma, liver, skin, skeletal muscle, bile and feces after the intravenous injection of 10 μg copper labeled with 64 Cu. Plasma radiocopper was separated into ceruloplasmin (Cp) and nonceruloplasmin (NCp) fractions. Liver cytosolic radiocopper was fractionated into void volume superoxide dismutase (SOD) containing and metallothionein fractions by gel filtration. Liver particulate fractions were isolated by differential centrifugation. The SAAM and CONSAM modeling programs were used to develop the model. The sizes of compartments, fractional rate constants and mass transfer rates between compartments were evaluated. The intracellular metabolism of copper was similar in hepatic and extrahepatic tissues being comprised of a faster turning over compartment (FTC) exchanging copper with NCp and a slower turning over compartment (STC) with input from Cp. Output from the STC was into the FTC. In the liver the STC was postulated to represent SOD copper which unlike the extrahepatic tissues received much of its input from the FTC. A small amount of biliary copper (9%) was postulated to return to plasma NCp by enterohepatic recycling. The model developed was contrasted and compared with two previous models of copper metabolism

  5. Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins.

    Science.gov (United States)

    Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens

    2016-05-01

    Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes. © 2015 Wiley Periodicals, Inc.

  6. Pharmacokinetic models relevant to toxicity and metabolism for uranium in humans and animals

    International Nuclear Information System (INIS)

    Wrenn, M.E.; Lipsztein, J.; Bertelli, L.

    1988-01-01

    The aim of this paper is to summarize pharmacokinetic models of uranium metabolism. Fortunately, others have recently reviewed metabolic models of all types, not just pharmacokinetic models. Their papers should be consulted for greater biological detail than is possible here. Improvements in the models since these other papers are noted. Models for assessing the biological consequences of exposure should account for the kinetics of intake by ingestion, inhalation, and injection, and the chemical form of uranium; predict the time dependent concentration in red blood cells, plasma, urine, kidney, bone and other organs (or compartments); and be adaptable to calculating these concentrations for varying regimens of intake. The biological parameters in the models come from metabolic data in humans and animals. Some of these parameters are reasonably well defined. For example, the cumulative urinary excretion at 24 hours post injection of soluble uranium in man is about 70%, the absorbed fraction for soluble uranium ingested by man in drinking water during normal dietary conditions is about 1%, and the half time in the mammalian kidney is several days. 17 refs., 8 figs

  7. Modeling with a view to target identification in metabolic engineering: a critical evaluation of the available tools.

    Science.gov (United States)

    Maertens, Jo; Vanrolleghem, Peter A

    2010-01-01

    The state of the art tools for modeling metabolism, typically used in the domain of metabolic engineering, were reviewed. The tools considered are stoichiometric network analysis (elementary modes and extreme pathways), stoichiometric modeling (metabolic flux analysis, flux balance analysis, and carbon modeling), mechanistic and approximative modeling, cybernetic modeling, and multivariate statistics. In the context of metabolic engineering, one should be aware that the usefulness of these tools to optimize microbial metabolism for overproducing a target compound depends predominantly on the characteristic properties of that compound. Because of their shortcomings not all tools are suitable for every kind of optimization; issues like the dependence of the target compound's synthesis on severe (redox) constraints, the characteristics of its formation pathway, and the achievable/desired flux towards the target compound should play a role when choosing the optimization strategy.

  8. Characterization and Modeling Of Microbial Carbon Metabolism In Thawing Permafrost

    Science.gov (United States)

    Graham, D. E.; Phelps, T. J.; Xu, X.; Carroll, S.; Jagadamma, S.; Shakya, M.; Thornton, P. E.; Elias, D. A.

    2012-12-01

    Increased annual temperatures in the Arctic are warming the surface and subsurface, resulting in thawing permafrost. Thawing exposes large pools of buried organic carbon to microbial degradation, increasing greenhouse gas generation and emission. Most global-scale land-surface models lack depth-dependent representations of carbon conversion and GHG transport; therefore they do not adequately describe permafrost thawing or microbial mineralization processes. The current work was performed to determine how permafrost thawing at moderately elevated temperatures and anoxic conditions would affect CO2 and CH4 generation, while parameterizing depth-dependent GHG production processes with respect to temperature and pH in biogeochemical models. These enhancements will improve the accuracy of GHG emission predictions and identify key biochemical and geochemical processes for further refinement. Three core samples were obtained from discontinuous permafrost terrain in Fairbanks, AK with a mean annual temperature of -3.3 °C. Each core was sectioned into surface/near surface (0-0.8 m), active layer (0.8-1.6 m), and permafrost (1.6-2.2 m) horizons, which were homogenized for physico-chemical characterization and microcosm construction. Surface samples had low pH values (6.0), low water content (18% by weight), low organic carbon (0.8%), and high C:N ratio (43). Active layer samples had higher pH values (6.4), higher water content (34%), more organic carbon (1.4%) and a lower C:N ratio (24). Permafrost samples had the highest pH (6.5), highest water content (46%), high organic carbon (2.5%) and the lowest C:N ratio (19). Most organic carbon was quantified as labile or intermediate pool versus stable pool in each sample, and all samples had low amounts of carbonate. Surface layer microcosms, containing 20 g sediment in septum-sealed vials, were incubated under oxic conditions, while similar active and permafrost layer samples were anoxic. These microcosms were incubated at -2

  9. Integration of genome-scale metabolic networks into whole-body PBPK models shows phenotype-specific cases of drug-induced metabolic perturbation.

    Science.gov (United States)

    Cordes, Henrik; Thiel, Christoph; Baier, Vanessa; Blank, Lars M; Kuepfer, Lars

    2018-01-01

    Drug-induced perturbations of the endogenous metabolic network are a potential root cause of cellular toxicity. A mechanistic understanding of such unwanted side effects during drug therapy is therefore vital for patient safety. The comprehensive assessment of such drug-induced injuries requires the simultaneous consideration of both drug exposure at the whole-body and resulting biochemical responses at the cellular level. We here present a computational multi-scale workflow that combines whole-body physiologically based pharmacokinetic (PBPK) models and organ-specific genome-scale metabolic network (GSMN) models through shared reactions of the xenobiotic metabolism. The applicability of the proposed workflow is illustrated for isoniazid, a first-line antibacterial agent against Mycobacterium tuberculosis , which is known to cause idiosyncratic drug-induced liver injuries (DILI). We combined GSMN models of a human liver with N-acetyl transferase 2 (NAT2)-phenotype-specific PBPK models of isoniazid. The combined PBPK-GSMN models quantitatively describe isoniazid pharmacokinetics, as well as intracellular responses, and changes in the exometabolome in a human liver following isoniazid administration. Notably, intracellular and extracellular responses identified with the PBPK-GSMN models are in line with experimental and clinical findings. Moreover, the drug-induced metabolic perturbations are distributed and attenuated in the metabolic network in a phenotype-dependent manner. Our simulation results show that a simultaneous consideration of both drug pharmacokinetics at the whole-body and metabolism at the cellular level is mandatory to explain drug-induced injuries at the patient level. The proposed workflow extends our mechanistic understanding of the biochemistry underlying adverse events and may be used to prevent drug-induced injuries in the future.

  10. Modelling of the metabolism of Zymomonas mobilis growing on a defined medium

    Energy Technology Data Exchange (ETDEWEB)

    Posten, C

    1989-08-07

    A structured model of Zymomonas mobilis is presented using fermentation data of a defined aspartate medium. After some remarks on the structure of the metabolism the model is derived by considering sub-models, e.g. balance equations, and by identifying the unknown parameters separately for each sub-model. Some results are the elemental composition of Zymomonas mobilis, a description of the substrate uptake during substrate limitation and the growth inhibition during substrate saturation. The results are shown as simulation and are discussed in relation to the inhibitory effect of ethanol on the bacterial cell. (orig.).

  11. Preclinical experimental models of drug metabolism and disposition in drug discovery and development

    Directory of Open Access Journals (Sweden)

    Donglu Zhang

    2012-12-01

    Full Text Available Drug discovery and development involve the utilization of in vitro and in vivo experimental models. Different models, ranging from test tube experiments to cell cultures, animals, healthy human subjects, and even small numbers of patients that are involved in clinical trials, are used at different stages of drug discovery and development for determination of efficacy and safety. The proper selection and applications of correct models, as well as appropriate data interpretation, are critically important in decision making and successful advancement of drug candidates. In this review, we discuss strategies in the applications of both in vitro and in vivo experimental models of drug metabolism and disposition.

  12. Data-driven integration of genome-scale regulatory and metabolic network models

    Science.gov (United States)

    Imam, Saheed; Schäuble, Sascha; Brooks, Aaron N.; Baliga, Nitin S.; Price, Nathan D.

    2015-01-01

    Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert—a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system. PMID:25999934

  13. Data-driven integration of genome-scale regulatory and metabolic network models

    Directory of Open Access Journals (Sweden)

    Saheed eImam

    2015-05-01

    Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

  14. A Mathematical Model of Metabolism and Regulation Provides a Systems-Level View of How Escherichia coli Responds to Oxygen

    Directory of Open Access Journals (Sweden)

    Michael eEderer

    2014-03-01

    Full Text Available The efficient redesign of bacteria for biotechnological purposes, such as biofuel production, waste disposal or specific biocatalytic functions, requires a quantitative systems-level understanding of energy supply, carbon and redox metabolism. The measurement of transcript levels, metabolite concentrations and metabolic fluxes per se gives an incomplete picture. An appreciation of the interdependencies between the different measurement values is essential for systems-level understanding. Mathematical modeling has the potential to provide a coherent and quantitative description of the interplay between gene expression, metabolite concentrations and metabolic fluxes. Escherichia coli undergoes major adaptations in central metabolism when the availability of oxygen changes. Thus, an integrated description of the oxygen response provides a benchmark of our understanding of carbon, energy and redox metabolism. We present the first comprehensive model of the central metabolism of E. coli that describes steady-state metabolism at different levels of oxygen availability. Variables of the model are metabolite concentrations, gene expression levels, transcription factor activities, metabolic fluxes and biomass concentration. We analyze the model with respect to the production capabilities of central metabolism of E. coli. In particular, we predict how precursor and biomass concentration are affected by product formation.

  15. Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.

    Directory of Open Access Journals (Sweden)

    Eddy J Bautista

    Full Text Available Primarily used for metabolic engineering and synthetic biology, genome-scale metabolic modeling shows tremendous potential as a tool for fundamental research and curation of metabolism. Through a novel integration of flux balance analysis and genetic algorithms, a strategy to curate metabolic networks and facilitate identification of metabolic pathways that may not be directly inferable solely from genome annotation was developed. Specifically, metabolites involved in unknown reactions can be determined, and potentially erroneous pathways can be identified. The procedure developed allows for new fundamental insight into metabolism, as well as acting as a semi-automated curation methodology for genome-scale metabolic modeling. To validate the methodology, a genome-scale metabolic model for the bacterium Mycoplasma gallisepticum was created. Several reactions not predicted by the genome annotation were postulated and validated via the literature. The model predicted an average growth rate of 0.358±0.12[Formula: see text], closely matching the experimentally determined growth rate of M. gallisepticum of 0.244±0.03[Formula: see text]. This work presents a powerful algorithm for facilitating the identification and curation of previously known and new metabolic pathways, as well as presenting the first genome-scale reconstruction of M. gallisepticum.

  16. Understanding the physiology of the ageing individual: computational modelling of changes in metabolism and endurance

    Science.gov (United States)

    2016-01-01

    Ageing and lifespan are strongly affected by metabolism. The maximal possible uptake of oxygen is not only a good predictor of performance in endurance sports, but also of life expectancy. Figuratively speaking, healthy ageing is a competitive sport. Although the root cause of ageing is damage to macromolecules, it is the balance with repair processes that is decisive. Reduced or intermittent nutrition, hormones and intracellular signalling pathways that regulate metabolism have strong effects on ageing. Homeostatic regulatory processes tend to keep the environment of the cells within relatively narrow bounds. On the other hand, the body is constantly adapting to physical activity and food consumption. Spontaneous fluctuations in heart rate and other processes indicate youth and health. A (homeo)dynamic aspect of homeostasis deteriorates with age. We are now in a position to develop computational models of human metabolism and the dynamics of heart rhythm and oxygen transport that will advance our understanding of ageing. Computational modelling of the connections between dietary restriction, metabolism and protein turnover may increase insight into homeostasis of the proteins in our body. In this way, the computational reconstruction of human physiological processes, the Physiome, can help prevent frailty and age-related disease. PMID:27051508

  17. Genome-scale metabolic models applied to human health and disease.

    Science.gov (United States)

    Cook, Daniel J; Nielsen, Jens

    2017-11-01

    Advances in genome sequencing, high throughput measurement of gene and protein expression levels, data accessibility, and computational power have allowed genome-scale metabolic models (GEMs) to become a useful tool for understanding metabolic alterations associated with many different diseases. Despite the proven utility of GEMs, researchers confront multiple challenges in the use of GEMs, their application to human health and disease, and their construction and simulation in an organ-specific and disease-specific manner. Several approaches that researchers are taking to address these challenges include using proteomic and transcriptomic-informed methods to build GEMs for individual organs, diseases, and patients and using constraints on model behavior during simulation to match observed metabolic fluxes. We review the challenges facing researchers in the use of GEMs, review the approaches used to address these challenges, and describe advances that are on the horizon and could lead to a better understanding of human metabolism. WIREs Syst Biol Med 2017, 9:e1393. doi: 10.1002/wsbm.1393 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

  18. Modeling the autonomic and metabolic effects of obstructive sleep apnea: A simulation study.

    Directory of Open Access Journals (Sweden)

    Limei eCheng

    2012-01-01

    Full Text Available Long term exposure to intermittent hypoxia and sleep fragmentation introduced by recurring obstructive sleep apnea has been linked to subsequent cardiovascular disease and Type 2 diabetes. The underlying mechanisms remain unclear, but impairment of the normal interactions among the systems that regulate autonomic and metabolic function is likely involved. We have extended an existing integrative model of respiratory, cardiovascular and sleep-wake state control, to incorporate a sub-model of glucose-insulin-fatty acid regulation. This computational model is capable of simulating the complex dynamics of cardiorespiratory control, chemoreflex and state-related control of breath-to-breath ventilation, state-related and chemoreflex control of upper airway potency, respiratory and circulatory mechanics, as well as the metabolic control of glucose insulin dynamics and its interactions with the autonomic control. The interactions between autonomic and metabolic control include the circadian regulation of epinephrine secretion, epinephrine regulation on dynamic fluctuations in glucose and free-fatty acid in plasma, metabolic coupling among tissues and organs provided by insulin and epinephrine, as well as the effect of insulin on peripheral vascular sympathetic activity. These model simulations provide insight into the relative importance of the various mechanisms that determine the acute and chronic physiological effects of sleep-disordered breathing. The model can also be used to investigate the effects of a variety of interventions, such as different glucose clamps, the intravenous glucose tolerance test and the application of continuous positive airway pressure on obstructive sleep apnea subjects. As such, this model provides the foundation on which future efforts to simulate disease progression and the long-term effects of pharmacological intervention can be based.

  19. A general model for metabolic scaling in self-similar asymmetric networks.

    Directory of Open Access Journals (Sweden)

    Alexander Byers Brummer

    2017-03-01

    Full Text Available How a particular attribute of an organism changes or scales with its body size is known as an allometry. Biological allometries, such as metabolic scaling, have been hypothesized to result from selection to maximize how vascular networks fill space yet minimize internal transport distances and resistances. The West, Brown, Enquist (WBE model argues that these two principles (space-filling and energy minimization are (i general principles underlying the evolution of the diversity of biological networks across plants and animals and (ii can be used to predict how the resulting geometry of biological networks then governs their allometric scaling. Perhaps the most central biological allometry is how metabolic rate scales with body size. A core assumption of the WBE model is that networks are symmetric with respect to their geometric properties. That is, any two given branches within the same generation in the network are assumed to have identical lengths and radii. However, biological networks are rarely if ever symmetric. An open question is: Does incorporating asymmetric branching change or influence the predictions of the WBE model? We derive a general network model that relaxes the symmetric assumption and define two classes of asymmetrically bifurcating networks. We show that asymmetric branching can be incorporated into the WBE model. This asymmetric version of the WBE model results in several theoretical predictions for the structure, physiology, and metabolism of organisms, specifically in the case for the cardiovascular system. We show how network asymmetry can now be incorporated in the many allometric scaling relationships via total network volume. Most importantly, we show that the 3/4 metabolic scaling exponent from Kleiber's Law can still be attained within many asymmetric networks.

  20. Advantage of Animal Models with Metabolic Flexibility for Space Research Beyond Low Earth Orbit

    Science.gov (United States)

    Griko, Yuri V.; Rask, Jon C.; Raychev, Raycho

    2017-01-01

    As the worlds space agencies and commercial entities continue to expand beyond Low Earth Orbit (LEO), novel approaches to carry out biomedical experiments with animals are required to address the challenge of adaptation to space flight and new planetary environments. The extended time and distance of space travel along with reduced involvement of Earth-based mission support increases the cumulative impact of the risks encountered in space. To respond to these challenges, it becomes increasingly important to develop the capability to manage an organisms self-regulatory control system, which would enable survival in extraterrestrial environments. To significantly reduce the risk to animals on future long duration space missions, we propose the use of metabolically flexible animal models as pathfinders, which are capable of tolerating the environmental extremes exhibited in spaceflight, including altered gravity, exposure to space radiation, chemically reactive planetary environments and temperature extremes.In this report we survey several of the pivotal metabolic flexibility studies and discuss the importance of utilizing animal models with metabolic flexibility with particular attention given to the ability to suppress the organism's metabolism in spaceflight experiments beyond LEO. The presented analysis demonstrates the adjuvant benefits of these factors to minimize damage caused by exposure to spaceflight and extreme planetary environments. Examples of microorganisms and animal models with dormancy capabilities suitable for space research are considered in the context of their survivability under hostile or deadly environments outside of Earth. Potential steps toward implementation of metabolic control technology in spaceflight architecture and its benefits for animal experiments and manned space exploration missions are discussed.

  1. Metabolic flexibility of mitochondrial respiratory chain disorders predicted by computer modelling.

    Science.gov (United States)

    Zieliński, Łukasz P; Smith, Anthony C; Smith, Alexander G; Robinson, Alan J

    2016-11-01

    Mitochondrial respiratory chain dysfunction causes a variety of life-threatening diseases affecting about 1 in 4300 adults. These diseases are genetically heterogeneous, but have the same outcome; reduced activity of mitochondrial respiratory chain complexes causing decreased ATP production and potentially toxic accumulation of metabolites. Severity and tissue specificity of these effects varies between patients by unknown mechanisms and treatment options are limited. So far most research has focused on the complexes themselves, and the impact on overall cellular metabolism is largely unclear. To illustrate how computer modelling can be used to better understand the potential impact of these disorders and inspire new research directions and treatments, we simulated them using a computer model of human cardiomyocyte mitochondrial metabolism containing over 300 characterised reactions and transport steps with experimental parameters taken from the literature. Overall, simulations were consistent with patient symptoms, supporting their biological and medical significance. These simulations predicted: complex I deficiencies could be compensated using multiple pathways; complex II deficiencies had less metabolic flexibility due to impacting both the TCA cycle and the respiratory chain; and complex III and IV deficiencies caused greatest decreases in ATP production with metabolic consequences that parallel hypoxia. Our study demonstrates how results from computer models can be compared to a clinical phenotype and used as a tool for hypothesis generation for subsequent experimental testing. These simulations can enhance understanding of dysfunctional mitochondrial metabolism and suggest new avenues for research into treatment of mitochondrial disease and other areas of mitochondrial dysfunction. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  2. A unique rodent model of cardiometabolic risk associated with the metabolic syndrome and polycystic ovary syndrome.

    Science.gov (United States)

    Shi, Danni; Dyck, Michael K; Uwiera, Richard R E; Russell, Jim C; Proctor, Spencer D; Vine, Donna F

    2009-09-01

    Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenism, oligo-/anovulation, and polycystic ovarian morphology and is a complex endocrine disorder that also presents with features of the metabolic syndrome, including obesity, insulin resistance, and dyslipidemia. These latter symptoms form cardiometabolic risk factors predisposing individuals to the development of type 2 diabetes and cardiovascular disease (CVD). To date, animal models to study PCOS in the context of the metabolic syndrome and CVD risk have been lacking. The aim of this study was to investigate the JCR:LA-cp rodent as an animal model of PCOS associated with the metabolic syndrome. Metabolic indices were measured at 6 and 12 wk, and reproductive parameters including ovarian morphology and estrous cyclicity were assessed at 12 wk or adulthood. At 6 wk of age, the cp/cp genotype of the JCR:LA-cp strain developed visceral obesity, insulin resistance, and dyslipidemia (hypertriglyceridemia and hypercholesterolemia) compared with control animals. Serum testosterone concentrations were not significantly different between groups at 6 wk of age. However, at 12 wk, the cp/cp genotype had higher serum testosterone concentrations, compared with control animals, and presented with oligoovulation, a decreased number of corpora lutea, and an increased number of total follicles, in particular atretic and cystic follicles. The cardiometabolic risk factors in the cp/cp animals were exacerbated at 12 wk including obesity, insulin resistance, and dyslipidemia. The results of this study demonstrate that the JCR:LA-cp rodent may be a useful PCOS-like model to study early mechanisms involved in the etiology of cardiometabolic risk factors in the context of both PCOS and the metabolic syndrome.

  3. Work-related pain in extrinsic finger extensor musculature of instrumentalists is associated with intracellular pH compartmentation during exercise.

    Directory of Open Access Journals (Sweden)

    Angel Moreno-Torres

    Full Text Available BACKGROUND: Although non-specific pain in the upper limb muscles of workers engaged in mild repetitive tasks is a common occupational health problem, much is unknown about the associated structural and biochemical changes. In this study, we compared the muscle energy metabolism of the extrinsic finger extensor musculature in instrumentalists suffering from work-related pain with that of healthy control instrumentalists using non-invasive phosphorus magnetic resonance spectroscopy ((31P-MRS. We hypothesize that the affected muscles will show alterations related with an impaired energy metabolism. METHODOLOGY/PRINCIPAL FINDINGS: We studied 19 volunteer instrumentalists (11 subjects with work-related pain affecting the extrinsic finger extensor musculature and 8 healthy controls. We used (31P-MRS to find deviations from the expected metabolic response to exercise in phosphocreatine (PCr, inorganic phosphate (Pi, Pi/PCr ratio and intracellular pH kinetics. We observed a reduced finger extensor exercise tolerance in instrumentalists with myalgia, an intracellular pH compartmentation in the form of neutral and acid compartments, as detected by Pi peak splitting in (31P-MRS spectra, predominantly in myalgic muscles, and a strong association of this pattern with the condition. CONCLUSIONS/SIGNIFICANCE: Work-related pain in the finger extrinsic extensor muscles is associated with intracellular pH compartmentation during exercise, non-invasively detectable by (31P-MRS and consistent with the simultaneous energy production by oxidative metabolism and glycolysis. We speculate that a deficit in energy production by oxidative pathways may exist in the affected muscles. Two possible explanations for this would be the partial and/or local reduction of blood supply and the reduction of the muscle oxidative capacity itself.

  4. Work-Related Pain in Extrinsic Finger Extensor Musculature of Instrumentalists Is Associated with Intracellular pH Compartmentation during Exercise

    Science.gov (United States)

    Moreno-Torres, Angel; Rosset-Llobet, Jaume; Pujol, Jesus; Fàbregas, Sílvia; Gonzalez-de-Suso, Jose-Manuel

    2010-01-01

    Background Although non-specific pain in the upper limb muscles of workers engaged in mild repetitive tasks is a common occupational health problem, much is unknown about the associated structural and biochemical changes. In this study, we compared the muscle energy metabolism of the extrinsic finger extensor musculature in instrumentalists suffering from work-related pain with that of healthy control instrumentalists using non-invasive phosphorus magnetic resonance spectroscopy (31P-MRS). We hypothesize that the affected muscles will show alterations related with an impaired energy metabolism. Methodology/Principal Findings We studied 19 volunteer instrumentalists (11 subjects with work-related pain affecting the extrinsic finger extensor musculature and 8 healthy controls). We used 31P-MRS to find deviations from the expected metabolic response to exercise in phosphocreatine (PCr), inorganic phosphate (Pi), Pi/PCr ratio and intracellular pH kinetics. We observed a reduced finger extensor exercise tolerance in instrumentalists with myalgia, an intracellular pH compartmentation in the form of neutral and acid compartments, as detected by Pi peak splitting in 31P-MRS spectra, predominantly in myalgic muscles, and a strong association of this pattern with the condition. Conclusions/Significance Work-related pain in the finger extrinsic extensor muscles is associated with intracellular pH compartmentation during exercise, non-invasively detectable by 31P-MRS and consistent with the simultaneous energy production by oxidative metabolism and glycolysis. We speculate that a deficit in energy production by oxidative pathways may exist in the affected muscles. Two possible explanations for this would be the partial and/or local reduction of blood supply and the reduction of the muscle oxidative capacity itself. PMID:20161738

  5. Glycogen storage disease type Ia in canines: a model for human metabolic and genetic liver disease.

    Science.gov (United States)

    Specht, Andrew; Fiske, Laurie; Erger, Kirsten; Cossette, Travis; Verstegen, John; Campbell-Thompson, Martha; Struck, Maggie B; Lee, Young Mok; Chou, Janice Y; Byrne, Barry J; Correia, Catherine E; Mah, Cathryn S; Weinstein, David A; Conlon, Thomas J

    2011-01-01

    A canine model of Glycogen storage disease type Ia (GSDIa) is described. Affected dogs are homozygous for a previously described M121I mutation resulting in a deficiency of glucose-6-phosphatase-α. Metabolic, clinicopathologic, pathologic, and clinical manifestations of GSDIa observed in this model are described and compared to those observed in humans. The canine model shows more complete recapitulation of the clinical manifestations seen in humans including "lactic acidosis", larger size, and longer lifespan compared to other animal models. Use of this model in preclinical trials of gene therapy is described and briefly compared to the murine model. Although the canine model offers a number of advantages for evaluating potential therapies for GSDIa, there are also some significant challenges involved in its use. Despite these challenges, the canine model of GSDIa should continue to provide valuable information about the potential for generating curative therapies for GSDIa as well as other genetic hepatic diseases.

  6. Glycogen Storage Disease Type Ia in Canines: A Model for Human Metabolic and Genetic Liver Disease

    Directory of Open Access Journals (Sweden)

    Andrew Specht

    2011-01-01

    Full Text Available A canine model of Glycogen storage disease type Ia (GSDIa is described. Affected dogs are homozygous for a previously described M121I mutation resulting in a deficiency of glucose-6-phosphatase-α. Metabolic, clinicopathologic, pathologic, and clinical manifestations of GSDIa observed in this model are described and compared to those observed in humans. The canine model shows more complete recapitulation of the clinical manifestations seen in humans including “lactic acidosis”, larger size, and longer lifespan compared to other animal models. Use of this model in preclinical trials of gene therapy is described and briefly compared to the murine model. Although the canine model offers a number of advantages for evaluating potential therapies for GSDIa, there are also some significant challenges involved in its use. Despite these challenges, the canine model of GSDIa should continue to provide valuable information about the potential for generating curative therapies for GSDIa as well as other genetic hepatic diseases.

  7. Induction of autophagy by ARHI (DIRAS3) alters fundamental metabolic pathways in ovarian cancer models

    International Nuclear Information System (INIS)

    Ornelas, Argentina; McCullough, Christopher R.; Lu, Zhen; Zacharias, Niki M.; Kelderhouse, Lindsay E.; Gray, Joshua; Yang, Hailing; Engel, Brian J.; Wang, Yan; Mao, Weiqun; Sutton, Margie N.; Bhattacharya, Pratip K.; Bast, Robert C. Jr.; Millward, Steven W.

    2016-01-01

    Autophagy is a bulk catabolic process that modulates tumorigenesis, therapeutic resistance, and dormancy. The tumor suppressor ARHI (DIRAS3) is a potent inducer of autophagy and its expression results in necroptotic cell death in vitro and tumor dormancy in vivo. ARHI is down-regulated or lost in over 60 % of primary ovarian tumors yet is dramatically up-regulated in metastatic disease. The metabolic changes that occur during ARHI induction and their role in modulating death and dormancy are unknown. We employed Nuclear Magnetic Resonance (NMR)-based metabolomic strategies to characterize changes in key metabolic pathways in both cell culture and xenograft models of ARHI expression and autophagy. These pathways were further interrogated by cell-based immunofluorescence imaging, tracer uptake studies, targeted metabolic inhibition, and in vivo PET/CT imaging. Induction of ARHI in cell culture models resulted in an autophagy-dependent increase in lactate production along with increased glucose uptake and enhanced sensitivity to glycolytic inhibitors. Increased uptake of glutamine was also dependent on autophagy and dramatically sensitized cultured ARHI-expressing ovarian cancer cell lines to glutaminase inhibition. Induction of ARHI resulted in a reduction in mitochondrial respiration, decreased mitochondrial membrane potential, and decreased Tom20 staining suggesting an ARHI-dependent loss of mitochondrial function. ARHI induction in mouse xenograft models resulted in an increase in free amino acids, a transient increase in [ 18 F]-FDG uptake, and significantly altered choline metabolism. ARHI expression has previously been shown to trigger autophagy-associated necroptosis in cell culture. In this study, we have demonstrated that ARHI expression results in decreased cellular ATP/ADP, increased oxidative stress, and decreased mitochondrial function. While this bioenergetic shock is consistent with programmed necrosis, our data indicates that the accompanying up

  8. Instantaneous Metabolic Cost of Walking: Joint-Space Dynamic Model with Subject-Specific Heat Rate.

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    Dustyn Roberts

    Full Text Available A subject-specific model of instantaneous cost of transport (ICOT is introduced from the joint-space formulation of metabolic energy expenditure using the laws of thermodynamics and the principles of multibody system dynamics. Work and heat are formulated in generalized coordinates as functions of joint kinematic and dynamic variables. Generalized heat rates mapped from muscle energetics are estimated from experimental walking metabolic data for the whole body, including upper-body and bilateral data synchronization. Identified subject-specific energetic parameters-mass, height, (estimated maximum oxygen uptake, and (estimated maximum joint torques-are incorporated into the heat rate, as opposed to the traditional in vitro and subject-invariant muscle parameters. The total model metabolic energy expenditure values are within 5.7 ± 4.6% error of the measured values with strong (R2 > 0.90 inter- and intra-subject correlations. The model reliably predicts the characteristic convexity and magnitudes (0.326-0.348 of the experimental total COT (0.311-0.358 across different subjects and speeds. The ICOT as a function of time provides insights into gait energetic causes and effects (e.g., normalized comparison and sensitivity with respect to walking speed and phase-specific COT, which are unavailable from conventional metabolic measurements or muscle models. Using the joint-space variables from commonly measured or simulated data, the models enable real-time and phase-specific evaluations of transient or non-periodic general tasks that use a range of (aerobic energy pathway similar to that of steady-state walking.

  9. Metabolic-dopaminergic mapping of the 6-hydroxydopamine rat model for Parkinson's disease

    International Nuclear Information System (INIS)

    Casteels, Cindy; Lauwers, Erwin; Baekelandt, Veerle; Bormans, Guy; Laere, Koen van

    2008-01-01

    The unilateral 6-hydroxydopamine (6-OHDA) lesion rat model is a well-known acute model for Parkinson's disease (PD). Its validity has been supported by invasive histology, behavioral studies and electrophysiology. Here, we have characterized this model in vivo by multitracer imaging [glucose metabolism and dopamine transporter (DAT)] in relation to behavioral and histological parameters. Eighteen female adult Wistar rats (eight 6-OHDA-lesioned, ten controls) were investigated using multitracer [ 18 F]-fluoro-2-deoxy-D-glucose (FDG) and [ 18 F]-FECT 2'-[ 18 F]-fluoroethyl-(1R-2-exo-3-exe)-8-methyl-3-(4-chlorophenyl)- 8-azabicyclo (3.2.1)-octane-2-carboxylate small animal positron emission tomography (PET). Relative glucose metabolism and parametric DAT binding images were anatomically standardized to Paxinos space and analyzed on a voxel-basis using SPM2, supplemented by a template-based predefined volumes-of-interest approach. Behavior was characterized by the limb-use asymmetry test; dopaminergic innervation was validated by in vitro tyrosine hydroxylase staining. In the 6-OHDA model, significant glucose hypometabolism is present in the ipsilateral sensory-motor cortex (-6.3%; p = 4 x 10 -6 ). DAT binding was severely decreased in the ipsilateral caudate-putamen, nucleus accumbens and substantia nigra (all p -9 ), as confirmed by the behavioral and histological outcomes. Correlation analysis revealed a positive relationship between the degree of DAT impairment and the change in glucose metabolism in the ipsilateral hippocampus (p = 3 x 10 -5 ), while cerebellar glucose metabolism was inversely correlated to the level of DAT impairment (p -4 ). In vivo cerebral mapping of 6-OHDA-lesioned rats using [ 18 F ]-FDG and [ 18 F ]-FECT small animal PET shows molecular-functional correspondence to the cortico-subcortical network impairments observed in PD patients. This provides a further molecular validation supporting the validity of the 6-OHDA lesion model to mimic

  10. A model for allometric scaling of mammalian metabolism with ambient heat loss

    KAUST Repository

    Kwak, Ho Sang

    2016-02-02

    Background Allometric scaling, which represents the dependence of biological trait or process relates on body size, is a long-standing subject in biological science. However, there has been no study to consider heat loss to the ambient and an insulation layer representing mammalian skin and fur for the derivation of the scaling law of metabolism. Methods A simple heat transfer model is proposed to analyze the allometry of mammalian metabolism. The present model extends existing studies by incorporating various external heat transfer parameters and additional insulation layers. The model equations were solved numerically and by an analytic heat balance approach. Results A general observation is that the present heat transfer model predicted the 2/3 surface scaling law, which is primarily attributed to the dependence of the surface area on the body mass. External heat transfer effects introduced deviations in the scaling law, mainly due to natural convection heat transfer which becomes more prominent at smaller mass. These deviations resulted in a slight modification of the scaling exponent to a value smaller than 2/3. Conclusion The finding that additional radiative heat loss and the consideration of an outer insulation fur layer attenuate these deviation effects and render the scaling law closer to 2/3 provides in silico evidence for a functional impact of heat transfer mode on the allometric scaling law in mammalian metabolism.

  11. Metabolic Modeling of Common Escherichia coli Strains in Human Gut Microbiome

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    Yue-Dong Gao

    2014-01-01

    Full Text Available The recent high-throughput sequencing has enabled the composition of Escherichia coli strains in the human microbial community to be profiled en masse. However, there are two challenges to address: (1 exploring the genetic differences between E. coli strains in human gut and (2 dynamic responses of E. coli to diverse stress conditions. As a result, we investigated the E. coli strains in human gut microbiome using deep sequencing data and reconstructed genome-wide metabolic networks for the three most common E. coli strains, including E. coli HS, UTI89, and CFT073. The metabolic models show obvious strain-specific characteristics, both in network contents and in behaviors. We predicted optimal biomass production for three models on four different carbon sources (acetate, ethanol, glucose, and succinate and found that these stress-associated genes were involved in host-microbial interactions and increased in human obesity. Besides, it shows that the growth rates are similar among the models, but the flux distributions are different, even in E. coli core reactions. The correlations between human diabetes-associated metabolic reactions in the E. coli models were also predicted. The study provides a systems perspective on E. coli strains in human gut microbiome and will be helpful in integrating diverse data sources in the following study.

  12. Metabolic network model guided engineering ethylmalonyl-CoA pathway to improve ascomycin production in Streptomyces hygroscopicus var. ascomyceticus.

    Science.gov (United States)

    Wang, Junhua; Wang, Cheng; Song, Kejing; Wen, Jianping

    2017-10-03

    Ascomycin is a 23-membered polyketide macrolide with high immunosuppressant and antifungal activity. As the lower production in bio-fermentation, global metabolic analysis is required to further explore its biosynthetic network and determine the key limiting steps for rationally engineering. To achieve this goal, an engineering approach guided by a metabolic network model was implemented to better understand ascomycin biosynthesis and improve its production. The metabolic conservation of Streptomyces species was first investigated by comparing the metabolic enzymes of Streptomyces coelicolor A3(2) with those of 31 Streptomyces strains, the results showed that more than 72% of the examined proteins had high sequence similarity with counterparts in every surveyed strain. And it was found that metabolic reactions are more highly conserved than the enzymes themselves because of its lower diversity of metabolic functions than that of genes. The main source of the observed metabolic differences was from the diversity of secondary metabolism. According to the high conservation of primary metabolic reactions in Streptomyces species, the metabolic network model of Streptomyces hygroscopicus var. ascomyceticus was constructed based on the latest reported metabolic model of S. coelicolor A3(2) and validated experimentally. By coupling with flux balance analysis and using minimization of metabolic adjustment algorithm, potential targets for ascomycin overproduction were predicted. Since several of the preferred targets were highly associated with ethylmalonyl-CoA biosynthesis, two target genes hcd (encoding 3-hydroxybutyryl-CoA dehydrogenase) and ccr (encoding crotonyl-CoA carboxylase/reductase) were selected for overexpression in S. hygroscopicus var. ascomyceticus FS35. Both the mutants HA-Hcd and HA-Ccr showed higher ascomycin titer, which was consistent with the model predictions. Furthermore, the combined effects of the two genes were evaluated and the strain HA

  13. Analysis of Neural-BOLD Coupling through Four Models of the Neural Metabolic Demand

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    Christopher W Tyler

    2015-12-01

    Full Text Available The coupling of the neuronal energetics to the blood-oxygen-level-dependent (BOLD response is still incompletely understood. To address this issue, we compared the fits of four plausible models of neurometabolic coupling dynamics to available data for simultaneous recordings of the local field potential (LFP and the local BOLD response recorded from monkey primary visual cortex over a wide range of stimulus durations. The four models of the metabolic demand driving the BOLD response were: direct coupling with the overall LFP; rectified coupling to the LFP; coupling with a slow adaptive component of the implied neural population response; and coupling with the non-adaptive intracellular input signal defined by the stimulus time course. Taking all stimulus durations into account, the results imply that the BOLD response is most closely coupled with metabolic demand derived from the intracellular input waveform, without significant influence from the adaptive transients and nonlinearities exhibited by the LFP waveform.

  14. On the use of prior information in modelling metabolic utilization of energy in growing pigs

    DEFF Research Database (Denmark)

    Strathe, Anders Bjerring; Jørgensen, Henry; Fernández, José Adalberto

    2011-01-01

    Construction of models that provide a realistic representation of metabolic utilization of energy in growing animals tend to be over-parameterized because data generated from individual metabolic studies are often sparse. In the Bayesian framework prior information can enter the data analysis......, PD and LD) made on a given pig at a given time followed a multivariate normal distribution. Two different equation systems were adopted from Strathe et al. (2010), generating the expected values in the multivariate normal distribution. Non-informative prior distributions were assigned for all model......, kp and kf, respectively. Utilizing both sets of priors showed that the maintenance component was sensitive to the statement of prior belief and, hence, that the estimate of 0.91 MJkg0.60d1 (95% CI: 0.78; 1.09) should be interpreted with caution. It was shown that boars were superior in depositing...

  15. Metabolic Trade-offs between Biomass Synthesis and Photosynthate Export at Different Light Intensities in a Genome–Scale Metabolic Model of Rice

    Directory of Open Access Journals (Sweden)

    Mark Graham Poolman

    2014-11-01

    Full Text Available Previously we have used a genome scale model of rice metabolism to describe how metabolism reconfigures at different light intensities in an expanding leaf of rice. Although this established that the metabolism of the leaf was adequatelyrepresented, in the model, the scenario was not that of the typical function of the leaf --- to provide material for the rest of the plant. Here we extend our analysis to explore the transition to a source leaf as export of photosynthate increases at the expense of making leaf biomass precursors, again as a function of light intensity. In particular we investigate whether, when the leaf is making a smaller range of compounds for export to the phloem, the same changes occur in the interactions between mitochondrial and chloroplast metabolism as seen in biomass synthesis for growth when light intensity increases. Our results show that the same changes occur qualitatively, though there are slight quantitative differences reflecting differences in the energy and redox requirements for the different metabolic outputs.

  16. Modeling metabolism and stage-specific growth of Plasmodium falciparum HB3 during the intraerythrocytic developmental cycle.

    Science.gov (United States)

    Fang, Xin; Reifman, Jaques; Wallqvist, Anders

    2014-10-01

    The human malaria parasite Plasmodium falciparum goes through a complex life cycle, including a roughly 48-hour-long intraerythrocytic developmental cycle (IDC) in human red blood cells. A better understanding of the metabolic processes required during the asexual blood-stage reproduction will enhance our basic knowledge of P. falciparum and help identify critical metabolic reactions and pathways associated with blood-stage malaria. We developed a metabolic network model that mechanistically links time-dependent gene expression, metabolism, and stage-specific growth, allowing us to predict the metabolic fluxes, the biomass production rates, and the timing of production of the different biomass components during the IDC. We predicted time- and stage-specific production of precursors and macromolecules for P. falciparum (strain HB3), allowing us to link specific metabolites to specific physiological functions. For example, we hypothesized that coenzyme A might be involved in late-IDC DNA replication and cell division. Moreover, the predicted ATP metabolism indicated that energy was mainly produced from glycolysis and utilized for non-metabolic processes. Finally, we used the model to classify the entire tricarboxylic acid cycle into segments, each with a distinct function, such as superoxide detoxification, glutamate/glutamine processing, and metabolism of fumarate as a byproduct of purine biosynthesis. By capturing the normal metabolic and growth progression in P. falciparum during the IDC, our model provides a starting point for further elucidation of strain-specific metabolic activity, host-parasite interactions, stress-induced metabolic responses, and metabolic responses to antimalarial drugs and drug candidates.

  17. Energy metabolism and glutamate-glutamine cycle in the brain: a stoichiometric modeling perspective.

    Science.gov (United States)

    Massucci, Francesco A; DiNuzzo, Mauro; Giove, Federico; Maraviglia, Bruno; Castillo, Isaac Perez; Marinari, Enzo; De Martino, Andrea

    2013-10-10

    The energetics of cerebral activity critically relies on the functional and metabolic interactions between neurons and astrocytes. Important open questions include the relation between neuronal versus astrocytic energy demand, glucose uptake and intercellular lactate transfer, as well as their dependence on the level of activity. We have developed a large-scale, constraint-based network model of the metabolic partnership between astrocytes and glutamatergic neurons that allows for a quantitative appraisal of the extent to which stoichiometry alone drives the energetics of the system. We find that the velocity of the glutamate-glutamine cycle (Vcyc) explains part of the uncoupling between glucose and oxygen utilization at increasing Vcyc levels. Thus, we are able to characterize different activation states in terms of the tissue oxygen-glucose index (OGI). Calculations show that glucose is taken up and metabolized according to cellular energy requirements, and that partitioning of the sugar between different cell types is not significantly affected by Vcyc. Furthermore, both the direction and magnitude of the lactate shuttle between neurons and astrocytes turn out to depend on the relative cell glucose uptake while being roughly independent of Vcyc. These findings suggest that, in absence of ad hoc activity-related constraints on neuronal and astrocytic metabolism, the glutamate-glutamine cycle does not control the relative energy demand of neurons and astrocytes, and hence their glucose uptake and lactate exchange.

  18. Energy metabolism and glutamate-glutamine cycle in the brain: a stoichiometric modeling perspective

    Science.gov (United States)

    2013-01-01

    Background The energetics of cerebral activity critically relies on the functional and metabolic interactions between neurons and astrocytes. Important open questions include the relation between neuronal versus astrocytic energy demand, glucose uptake and intercellular lactate transfer, as well as their dependence on the level of activity. Results We have developed a large-scale, constraint-based network model of the metabolic partnership between astrocytes and glutamatergic neurons that allows for a quantitative appraisal of the extent to which stoichiometry alone drives the energetics of the system. We find that the velocity of the glutamate-glutamine cycle (Vcyc) explains part of the uncoupling between glucose and oxygen utilization at increasing Vcyc levels. Thus, we are able to characterize different activation states in terms of the tissue oxygen-glucose index (OGI). Calculations show that glucose is taken up and metabolized according to cellular energy requirements, and that partitioning of the sugar between different cell types is not significantly affected by Vcyc. Furthermore, both the direction and magnitude of the lactate shuttle between neurons and astrocytes turn out to depend on the relative cell glucose uptake while being roughly independent of Vcyc. Conclusions These findings suggest that, in absence of ad hoc activity-related constraints on neuronal and astrocytic metabolism, the glutamate-glutamine cycle does not control the relative energy demand of neurons and astrocytes, and hence their glucose uptake and lactate exchange. PMID:24112710

  19. Lipid metabolism in myelinating glial cells: lessons from human inherited disorders and mouse models.

    Science.gov (United States)

    Chrast, Roman; Saher, Gesine; Nave, Klaus-Armin; Verheijen, Mark H G

    2011-03-01

    The integrity of central and peripheral nervous system myelin is affected in numerous lipid metabolism disorders. This vulnerability was so far mostly attributed to the extraordinarily high level of lipid synthesis that is required for the formation of myelin, and to the relative autonomy in lipid synthesis of myelinating glial cells because of blood barriers shielding the nervous system from circulating lipids. Recent insights from analysis of inherited lipid disorders, especially those with prevailing lipid depletion and from mouse models with glia-specific disruption of lipid metabolism, shed new light on this issue. The particular lipid composition of myelin, the transport of lipid-associated myelin proteins, and the necessity for timely assembly of the myelin sheath all contribute to the observed vulnerability of myelin to perturbed lipid metabolism. Furthermore, the uptake of external lipids may also play a role in the formation of myelin membranes. In addition to an improved understanding of basic myelin biology, these data provide a foundation for future therapeutic interventions aiming at preserving glial cell integrity in metabolic disorders.

  20. Neuronal and astrocytic metabolism in a transgenic rat model of Alzheimer's disease.

    Science.gov (United States)

    Nilsen, Linn Hege; Witter, Menno P; Sonnewald, Ursula

    2014-05-01

    Regional hypometabolism of glucose in the brain is a hallmark of Alzheimer's disease (AD). However, little is known about the specific alterations of neuronal and astrocytic metabolism involved in homeostasis of glutamate and GABA in AD. Here, we investigated the effects of amyloid β (Aβ) pathology on neuronal and astrocytic metabolism and glial-neuronal interactions in amino acid neurotransmitter homeostasis in the transgenic McGill-R-Thy1-APP rat model of AD compared with healthy controls at age 15 months. Rats were injected with [1-(13)C]glucose and [1,2-(13)C]acetate, and extracts of the hippocampal formation as well as several cortical regions were analyzed using (1)H- and (13)C nuclear magnetic resonance spectroscopy and high-performance liquid chromatography. Reduced tricarboxylic acid cycle turnover was evident for glutamatergic and GABAergic neurons in hippocampal formation and frontal cortex, and for astrocytes in frontal cortex. Pyruvate carboxylation, which is necessary for de novo synthesis of amino acids, was decreased and affected the level of glutamine in hippocampal formation and those of glutamate, glutamine, GABA, and aspartate in the retrosplenial/cingulate cortex. Metabolic alterations were also detected in the entorhinal cortex. Overall, perturbations in energy- and neurotransmitter homeostasis, mitochondrial astrocytic and neuronal metabolism, and aspects of the glutamate-glutamine cycle were found in McGill-R-Thy1-APP rats.

  1. Developmental programming of metabolic diseases – a review of studies on experimental animal models

    Directory of Open Access Journals (Sweden)

    Iwona Piotrowska

    2014-06-01

    Full Text Available Growth and development in utero is a complex and dynamic process that requires interaction between the mother organism and the fetus. The delivery of macro – and micronutrients, oxygen and endocrine signals has crucial importance for providing a high level of proliferation, growth and differentiation of cells, and a disruption in food intake not only has an influence on the growth of the fetus, but also has negative consequences for the offspring’s health in the future. Diseases that traditionally are linked to inappropriate life style of adults, such as type 2 diabetes, obesity, and arterial hypertension, can be “programmed” in the early stage of life and the disturbed growth of the fetus leads to the symptoms of the metabolic syndrome. The structural changes of some organs, such as the brain, pancreas and kidney, modifications of the signaling and metabolic pathways in skeletal muscles and in fatty tissue, epigenetic mechanisms and mitochondrial dysfunction are the basis of the metabolic disruptions. The programming of the metabolic disturbances is connected with the disruption in the intrauterine environment experienced in the early and late gestation period. It causes the changes in deposition of triglycerides, activation of the hormonal “stress axis” and disturbances in the offspring’s glucose tolerance. The present review summarizes experimental results that led to the identification of the above-mentioned links and it underlines the role of animal models in the studies of this important concept.

  2. Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

    Science.gov (United States)

    2016-03-15

    RESEARCH ARTICLE Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism Francisco G...jaques.reifman.civ@mail.mil Abstract A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm -based infections that are difficult to...eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic

  3. Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity.

    Directory of Open Access Journals (Sweden)

    Marc Breit

    2015-08-01

    Full Text Available The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity. Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined, obtained from a cycle ergometry cohort study. In total, 110 metabolites (within the classes of acylcarnitines, amino acids, and sugars were measured through a targeted metabolomics approach, combining tandem mass spectrometry (MS/MS with the concept of stable isotope dilution (SID for metabolite quantitation. Biomarker candidates were selected by combined analysis of maximum fold changes (MFCs in concentrations and P-values resulting from statistical hypothesis testing. Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting. Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis. Kinetic shape templates were characterized, defining different forms of basic kinetic response patterns, such as sustained, early, late, and other forms, that can be used for metabolite classification. Acetylcarnitine (C2, showing a late response pattern and having the highest values in MFC and statistical significance, was classified as late marker and ranked as strong predictor (MFC = 1.97, P < 0.001. In the class of amino acids, highest values were shown for alanine (MFC = 1.42, P < 0.001, classified as late marker and strong predictor. Glucose yields a delayed response pattern, similar to a hockey stick function, being classified as delayed marker and ranked as moderate predictor (MFC = 1.32, P < 0.001. These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology, such as β-oxidation of fatty acids, glycolysis, and glycogenolysis. The presented modeling

  4. The human hepatocyte cell lines IHH and HepaRG: models to study glucose, lipid and lipoprotein metabolism.

    Science.gov (United States)

    Samanez, Carolina Huaman; Caron, Sandrine; Briand, Olivier; Dehondt, Hélène; Duplan, Isabelle; Kuipers, Folkert; Hennuyer, Nathalie; Clavey, Véronique; Staels, Bart

    2012-07-01

    Metabolic diseases reach epidemic proportions. A better knowledge of the associated alterations in the metabolic pathways in the liver is necessary. These studies need in vitro human cell models. Several human hepatoma models are used, but the response of many metabolic pathways to physiological stimuli is often lost. Here, we characterize two human hepatocyte cell lines, IHH and HepaRG, by analysing the expression and regulation of genes involved in glucose and lipid metabolism. Our results show that the glycolysis pathway is activated by glucose and insulin in both lines. Gluconeogenesis gene expression is induced by forskolin in IHH cells and inhibited by insulin in both cell lines. The lipogenic pathway is regulated by insulin in IHH cells. Finally, both cell lines secrete apolipoprotein B-containing lipoproteins, an effect promoted by increasing glucose concentrations. These two human cell lines are thus interesting models to study the regulation of glucose and lipid metabolism.

  5. HEPATOKIN1 is a biochemistry-based model of liver metabolism for applications in medicine and pharmacology.

    Science.gov (United States)

    Berndt, Nikolaus; Bulik, Sascha; Wallach, Iwona; Wünsch, Tilo; König, Matthias; Stockmann, Martin; Meierhofer, David; Holzhütter, Hermann-Georg

    2018-06-19

    The epidemic increase of non-alcoholic fatty liver diseases (NAFLD) requires a deeper understanding of the regulatory circuits controlling the response of liver metabolism to nutritional challenges, medical drugs, and genetic enzyme variants. As in vivo studies of human liver metabolism are encumbered with serious ethical and technical issues, we developed a comprehensive biochemistry-based kinetic model of the central liver metabolism including the regulation of enzyme activities by their reactants, allosteric effectors, and hormone-dependent phosphorylation. The utility of the model for basic research and applications in medicine and pharmacology is illustrated by simulating diurnal variations of the metabolic state of the liver at various perturbations caused by nutritional challenges (alcohol), drugs (valproate), and inherited enzyme disorders (galactosemia). Using proteomics data to scale maximal enzyme activities, the model is used to highlight differences in the metabolic functions of normal hepatocytes and malignant liver cells (adenoma and hepatocellular carcinoma).

  6. Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

    Science.gov (United States)

    Henson, Michael A

    2015-12-01

    Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

  7. A Computational Model of Torque Generation: Neural, Contractile, Metabolic and Musculoskeletal Components

    Science.gov (United States)

    Callahan, Damien M.; Umberger, Brian R.; Kent-Braun, Jane A.

    2013-01-01

    The pathway of voluntary joint torque production includes motor neuron recruitment and rate-coding, sarcolemmal depolarization and calcium release by the sarcoplasmic reticulum, force generation by motor proteins within skeletal muscle, and force transmission by tendon across the joint. The direct source of energetic support for this process is ATP hydrolysis. It is possible to examine portions of this physiologic pathway using various in vivo and in vitro techniques, but an integrated view of the multiple processes that ultimately impact joint torque remains elusive. To address this gap, we present a comprehensive computational model of the combined neuromuscular and musculoskeletal systems that includes novel components related to intracellular bioenergetics function. Components representing excitatory drive, muscle activation, force generation, metabolic perturbations, and torque production during voluntary human ankle dorsiflexion were constructed, using a combination of experimentally-derived data and literature values. Simulation results were validated by comparison with torque and metabolic data obtained in vivo. The model successfully predicted peak and submaximal voluntary and electrically-elicited torque output, and accurately simulated the metabolic perturbations associated with voluntary contractions. This novel, comprehensive model could be used to better understand impact of global effectors such as age and disease on various components of the neuromuscular system, and ultimately, voluntary torque output. PMID:23405245

  8. Mechanistic model of mass-specific basal metabolic rate: evaluation in healthy young adults.

    Science.gov (United States)

    Wang, Z; Bosy-Westphal, A; Schautz, B; Müller, M

    2011-12-01

    Mass-specific basal metabolic rate (mass-specific BMR), defined as the resting energy expenditure per unit body mass per day, is an important parameter in energy metabolism research. However, a mechanistic explanation for magnitude of mass-specific BMR remains lacking. The objective of the present study was to validate the applicability of a proposed mass-specific BMR model in healthy adults. A mechanistic model was developed at the organ-tissue level, mass-specific BMR = Σ( K i × F i ), where Fi is the fraction of body mass as individual organs and tissues, and K i is the specific resting metabolic rate of major organs and tissues. The Fi values were measured by multiple MRI scans and the K i values were suggested by Elia in 1992. A database of healthy non-elderly non-obese adults (age 20 - 49 yrs, BMI BMR of all subjects was 21.6 ± 1.9 (mean ± SD) and 21.7 ± 1.6 kcal/kg per day, respectively. The measured mass-specific BMR was correlated with the predicted mass-specific BMR (r = 0.82, P BMR, versus the average of measured and predicted mass-specific BMR. In conclusion, the proposed mechanistic model was validated in non-elderly non-obese adults and can help to understand the inherent relationship between mass-specific BMR and body composition.

  9. Modelling Blood Flow and Metabolism in the Preclinical Neonatal Brain during and Following Hypoxic-Ischaemia.

    Directory of Open Access Journals (Sweden)

    Matthew Caldwell

    Full Text Available Hypoxia-ischaemia (HI is a major cause of neonatal brain injury, often leading to long-term damage or death. In order to improve understanding and test new treatments, piglets are used as preclinical models for human neonates. We have extended an earlier computational model of piglet cerebral physiology for application to multimodal experimental data recorded during episodes of induced HI. The data include monitoring with near-infrared spectroscopy (NIRS and magnetic resonance spectroscopy (MRS, and the model simulates the circulatory and metabolic processes that give rise to the measured signals. Model extensions include simulation of the carotid arterial occlusion used to induce HI, inclusion of cytoplasmic pH, and loss of metabolic function due to cell death. Model behaviour is compared to data from two piglets, one of which recovered following HI while the other did not. Behaviourally-important model parameters are identified via sensitivity analysis, and these are optimised to simulate the experimental data. For the non-recovering piglet, we investigate several state changes that might explain why some MRS and NIRS signals do not return to their baseline values following the HI insult. We discover that the model can explain this failure better when we include, among other factors such as mitochondrial uncoupling and poor cerebral blood flow restoration, the death of around 40% of the brain tissue.

  10. Influence on dose coefficients for workers of the new metabolic models

    International Nuclear Information System (INIS)

    Gomez Parada, I.M.; Rojo, A.M.

    1998-01-01

    The International Commission on Radiological Protection (ICRP) has recently reviewed the biokinetic models used in the internal contamination dose assessment. ICRP has adopted a new model for the human respiratory tract and has updated, in ICRP Publications 56, 67 and 69, some of the biokinetic models of ICRP Publication 30. In this paper, the dose coefficients for some selected radionuclides issued in ICRP Publication 68 are compared with those obtained using the software LUPED (LUng Dose Evaluation Program). The former were calculated using the new systemic models, while the latter are based on the old metabolic models. The aim is to know to what extent the new models for systematic retention influence the dose coefficients for workers. (author) [es

  11. Effect of alternate energy substrates on mammalian brain metabolism during ischemic events.

    Science.gov (United States)

    Koppaka, S S; Puchowicz; LaManna, J C; Gatica, J E

    2008-01-01

    Regulation of brain metabolism and cerebral blood flow involves complex control systems with several interacting variables at both cellular and organ levels. Quantitative understanding of the spatially and temporally heterogeneous brain control mechanisms during internal and external stimuli requires the development and validation of a computational (mathematical) model of metabolic processes in brain. This paper describes a computational model of cellular metabolism in blood-perfused brain tissue, which considers the astrocyte-neuron lactate-shuttle (ANLS) hypothesis. The model structure consists of neurons, astrocytes, extra-cellular space, and a surrounding capillary network. Each cell is further compartmentalized into cytosol and mitochondria. Inter-compartment interaction is accounted in the form of passive and carrier-mediated transport. Our model was validated against experimental data reported by Crumrine and LaManna, who studied the effect of ischemia and its recovery on various intra-cellular tissue substrates under standard diet conditions. The effect of ketone bodies on brain metabolism was also examined under ischemic conditions following cardiac resuscitation through our model simulations. The influence of ketone bodies on lactate dynamics on mammalian brain following ischemia is studied incorporating experimental data.

  12. Precision-cut intestinal slices: alternative model for drug transport, metabolism, and toxicology research.

    Science.gov (United States)

    Li, Ming; de Graaf, Inge A M; Groothuis, Geny M M

    2016-01-01

    The absorption, distribution, metabolism, excretion and toxicity (ADME-tox) processes of drugs are of importance and require preclinical investigation intestine in addition to the liver. Various models have been developed for prediction of ADME-tox in the intestine. In this review, precision-cut intestinal slices (PCIS) are discussed and highlighted as model for ADME-tox studies. This review provides an overview of the applications and an update of the most recent research on PCIS as an ex vivo model to study the transport, metabolism and toxicology of drugs and other xenobiotics. The unique features of PCIS and the differences with other models as well as the translational aspects are also discussed. PCIS are a simple, fast, and reliable ex vivo model for drug ADME-tox research. Therefore, PCIS are expected to become an indispensable link in the in vitro-ex vivo-in vivo extrapolation, and a bridge in translation of animal data to the human situation. In the future, this model may be helpful to study the effects of interorgan interactions, intestinal bacteria, excipients and drug formulations on the ADME-tox properties of drugs. The optimization of culture medium and the development of a (cryo)preservation technique require more research.

  13. Jacobsen Catalyst as a Cytochrome P450 Biomimetic Model for the Metabolism of Monensin A

    Directory of Open Access Journals (Sweden)

    Bruno Alves Rocha

    2014-01-01

    Full Text Available Monensin A is a commercially important natural product isolated from Streptomyces cinnamonensins that is primarily employed to treat coccidiosis. Monensin A selectively complexes and transports sodium cations across lipid membranes and displays a variety of biological properties. In this study, we evaluated the Jacobsen catalyst as a cytochrome P450 biomimetic model to investigate the oxidation of monensin A. Mass spectrometry analysis of the products from these model systems revealed the formation of two products: 3-O-demethyl monensin A and 12-hydroxy monensin A, which are the same ones found in in vivo models. Monensin A and products obtained in biomimetic model were tested in a mitochondrial toxicity model assessment and an antimicrobial bioassay against Staphylococcus aureus, S. aureus methicillin-resistant, Staphylococcus epidermidis, Pseudomonas aeruginosa, and Escherichia coli. Our results demonstrated the toxicological effects of monensin A in isolated rat liver mitochondria but not its products, showing that the metabolism of monensin A is a detoxification metabolism. In addition, the antimicrobial bioassay showed that monensin A and its products possessed activity against Gram-positive microorganisms but not for Gram-negative microorganisms. The results revealed the potential of application of this biomimetic chemical model in the synthesis of drug metabolites, providing metabolites for biological tests and other purposes.

  14. Determination of Glucose Utilization Rates in Cultured Astrocytes and Neurons with [14C]deoxyglucose: Progress, Pitfalls, and Discovery of Intracellular Glucose Compartmentation.

    Science.gov (United States)

    Dienel, Gerald A; Cruz, Nancy F; Sokoloff, Louis; Driscoll, Bernard F

    2017-01-01

    2-Deoxy-D-[ 14 C]glucose ([ 14 C]DG) is commonly used to determine local glucose utilization rates (CMR glc ) in living brain and to estimate CMR glc in cultured brain cells as rates of [ 14 C]DG phosphorylation. Phosphorylation rates of [ 14 C]DG and its metabolizable fluorescent analog, 2-(N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-2-deoxyglucose (2-NBDG), however, do not take into account differences in the kinetics of transport and metabolism of [ 14 C]DG or 2-NBDG and glucose in neuronal and astrocytic cells in cultures or in single cells in brain tissue, and conclusions drawn from these data may, therefore, not be correct. As a first step toward the goal of quantitative determination of CMR glc in astrocytes and neurons in cultures, the steady-state intracellular-to-extracellular concentration ratios (distribution spaces) for glucose and [ 14 C]DG were determined in cultured striatal neurons and astrocytes as functions of extracellular glucose concentration. Unexpectedly, the glucose distribution spaces rose during extreme hypoglycemia, exceeding 1.0 in astrocytes, whereas the [ 14 C]DG distribution space fell at the lowest glucose levels. Calculated CMR glc was greatly overestimated in hypoglycemic and normoglycemic cells because the intracellular glucose concentrations were too high. Determination of the distribution space for [ 14 C]glucose revealed compartmentation of intracellular glucose in astrocytes, and probably, also in neurons. A smaller metabolic pool is readily accessible to hexokinase and communicates with extracellular glucose, whereas the larger pool is sequestered from hexokinase activity. A new experimental approach using double-labeled assays with DG and glucose is suggested to avoid the limitations imposed by glucose compartmentation on metabolic assays.

  15. Macroanatomy and compartmentalization of recent fire scars in three North American conifers

    Science.gov (United States)

    Kevin T. Smith; Estelle Arbellay; Donald A. Falk; Elaine Kennedy Sutherland

    2016-01-01

    Fire scars are initiated by cambial necrosis caused by localized lethal heating of the tree stem. Scars develop as part of the linked survival processes of compartmentalization and wound closure. The position of scars within dated tree ring series is the basis for dendrochronological reconstruction of fire history. Macroanatomical features were described for western...

  16. Meningoencephalitis and Compartmentalization of the Cerebral Ventricles Caused by Enterobacter sakazakii

    Science.gov (United States)

    Kleiman, Martin B.; Allen, Stephen D.; Neal, Patricia; Reynolds, Janet

    1981-01-01

    A necrotizing meningoencephalitis complicated by ventricular compartmentalization and abscess formation caused by Enterobacter sakazakii in a previously healthy 5-week-old female is described. A detailed description of the isolate is presented. This communication firmly establishes the pathogenicity of E. sakazakii. PMID:7287892

  17. Heterogeneity and compartmentalization of Pneumocystis carinii f. sp. hominis genotypes in autopsy lungs

    DEFF Research Database (Denmark)

    Helweg-Larsen, J; Lundgren, Bettina; Lundgren, Jens Dilling

    2001-01-01

    . Not all genotypes present in the lungs at autopsy were detected in the diagnostic respiratory samples. Compartmentalization of specific ITS and mtLSU rRNA sequence types was observed in different lung segments. In conclusion, the interpretation of genotype data and in particular ITS sequence types...

  18. The Contradictions and Compartmentalizing the Interactions between Integrated Business Structures: Aspect of Branding

    Directory of Open Access Journals (Sweden)

    Nifatova Olena M.

    2017-04-01

    Full Text Available The article is aimed at identifying contradictions and developing a compartmentalizing as to the interaction between integrated business structures, taking into consideration the branding approach to management. The main specific features and contradictions that arise in the process of integration in the domestic market of mergers and acquisitions have been allocated. The contradictions identified were systematized and substantiated at three economic levels: macro-, meso-, and microeconomic. A compartmentalizing of the business units interaction in a merge or an acquisition process has been proposed. This compartmentalizing takes account of the branding aspect through the introduction of «brands interaction» – cluster interaction, circular interaction, holding interaction, linear interaction, which enhances the scientific view of exploring the problem of business units interaction in the process of the formations becoming integrated. The development of a compartmentalizing as to the interaction between integrated business structures, taking into consideration the branding approach to management, would provide a more effective use of the fundamental nature of branding as synergistic force in terms of the system of integration of business structures at the current stage of development of the national economy. Further development of branding issues in this sphere will have a significant impact on the functioning of the integrated business structures with the participation of Ukrainian companies.

  19. A compartmentalized out-of-equilibrium enzymatic reaction network for sustained autonomous movement

    NARCIS (Netherlands)

    Nijemeisland, M.; Abdelmohsen, L.K.E.A.; Huck, W.T.S.; Wilson, D.A.; van Hest, J.C.M.

    2016-01-01

    Every living cell is a compartmentalized out-ofequilibrium system exquisitely able to convert chemical energy into function. In order to maintain homeostasis, the flux of metabolites is tightly controlled by regulatory enzymatic networks. A crucial prerequisite for the development of lifelike

  20. SYNCHROTRON X-RAY ABSORPTION-EDGE COMPUTED MICROTOMOGRAPHY IMAGING OF THALLIUM COMPARTMENTALIZATION IN IBERIS INTERMEDIA

    Science.gov (United States)

    Thallium (TI) is an extremely toxic metal which, due to its similarities to K, is readily taken up by plants. Thallium is efficiently hyperaccumulated in Iberis intermedia as TI(I). Distribution and compartmentalization of TI in I. intermedia is highes...

  1. Compartmentalization: a conceptual framework for understanding how trees grow and defend themselves

    Science.gov (United States)

    Alex L. Shigo

    1984-01-01

    The purpose of this chapter is to describe a conceptual framework for understanding how trees grow and how they and other perennial plants defend themselves. The concept of compartmentalization has developed over many years, a synthesis of ideas from a number of investigators. It is derived from detailed studies of the gross morphology and cellular anatomy of the wood...

  2. Ordinary differential equations and Boolean networks in application to modelling of 6-mercaptopurine metabolism.

    Science.gov (United States)

    Lavrova, Anastasia I; Postnikov, Eugene B; Zyubin, Andrey Yu; Babak, Svetlana V

    2017-04-01

    We consider two approaches to modelling the cell metabolism of 6-mercaptopurine, one of the important chemotherapy drugs used for treating acute lymphocytic leukaemia: kinetic ordinary differential equations, and Boolean networks supplied with one controlling node, which takes continual values. We analyse their interplay with respect to taking into account ATP concentration as a key parameter of switching between different pathways. It is shown that the Boolean networks, which allow avoiding the complexity of general kinetic modelling, preserve the possibility of reproducing the principal switching mechanism.

  3. Recellularization of rat liver: An in vitro model for assessing human drug metabolism and liver biology.

    Directory of Open Access Journals (Sweden)

    Matthew J Robertson

    Full Text Available Liver-like organoids that recapitulate the complex functions of the whole liver by combining cells, scaffolds, and mechanical or chemical cues are becoming important models for studying liver biology and drug metabolism. The advantages of growing cells in three-dimensional constructs include enhanced cell-cell and cell-extracellular matrix interactions and preserved cellular phenotype including, prevention of de-differentiation. In the current study, biomimetic liver constructs were made via perfusion decellularization of rat liver, with the goal of maintaining the native composition and structure of the extracellular matrix. We optimized our decellularization process to produce liver scaffolds in which immunogenic residual DNA was removed but glycosaminoglycans were maintained. When the constructs were recellularized with rat or human liver cells, the cells remained viable, capable of proliferation, and functional for 28 days. Specifically, the cells continued to express cytochrome P450 genes and maintained their ability to metabolize a model drug, midazolam. Microarray analysis showed an upregulation of genes involved in liver regeneration and fibrosis. In conclusion, these liver constructs have the potential to be used as test beds for studying liver biology and drug metabolism.

  4. Modeling Inborn Errors of Hepatic Metabolism Using Induced Pluripotent Stem Cells.

    Science.gov (United States)

    Pournasr, Behshad; Duncan, Stephen A

    2017-11-01

    Inborn errors of hepatic metabolism are because of deficiencies commonly within a single enzyme as a consequence of heritable mutations in the genome. Individually such diseases are rare, but collectively they are common. Advances in genome-wide association studies and DNA sequencing have helped researchers identify the underlying genetic basis of such diseases. Unfortunately, cellular and animal models that accurately recapitulate these inborn errors of hepatic metabolism in the laboratory have been lacking. Recently, investigators have exploited molecular techniques to generate induced pluripotent stem cells from patients' somatic cells. Induced pluripotent stem cells can differentiate into a wide variety of cell types, including hepatocytes, thereby offering an innovative approach to unravel the mechanisms underlying inborn errors of hepatic metabolism. Moreover, such cell models could potentially provide a platform for the discovery of therapeutics. In this mini-review, we present a brief overview of the state-of-the-art in using pluripotent stem cells for such studies. © 2017 American Heart Association, Inc.

  5. ACE Reduces Metabolic Abnormalities in a High-Fat Diet Mouse Model

    Directory of Open Access Journals (Sweden)

    Seong-Jong Lee

    2015-01-01

    Full Text Available The medicinal plants Artemisia iwayomogi (A. iwayomogi and Curcuma longa (C. longa radix have been used to treat metabolic abnormalities in traditional Korean medicine and traditional Chinese medicine (TKM and TCM. In this study we evaluated the effect of the water extract of a mixture of A. iwayomogi and C. longa (ACE on high-fat diet-induced metabolic syndrome in a mouse model. Four groups of C57BL/6N male mice (except for the naive group were fed a high-fat diet freely for 10 weeks. Among these, three groups (except the control group were administered a high-fat diet supplemented with ACE (100 or 200 mg/kg or curcumin (50 mg/kg. Body weight, accumulation of adipose tissues in abdomen and size of adipocytes, serum lipid profiles, hepatic steatosis, and oxidative stress markers were analyzed. ACE significantly reduced the body and peritoneal adipose tissue weights, serum lipid profiles (total cholesterol and triglycerides, glucose levels, hepatic lipid accumulation, and oxidative stress markers. ACE normalized lipid synthesis-associated gene expressions (peroxisome proliferator-activated receptor gamma, PPARγ; fatty acid synthase, FAS; sterol regulatory element-binding transcription factor-1c, SREBP-1c; and peroxisome proliferator-activated receptor alpha, PPARα. The results from this study suggest that ACE has the pharmaceutical potential reducing the metabolic abnormalities in an animal model.

  6. Metabolic Effects of Inflammation on Vitamin A and Carotenoids in Humans and Animal Models123

    Science.gov (United States)

    Rubin, Lewis P; Ross, A Catharine; Stephensen, Charles B; Bohn, Torsten; Tanumihardjo, Sherry A

    2017-01-01

    The association between inflammation and vitamin A (VA) metabolism and status assessment has been documented in multiple studies with animals and humans. The relation between inflammation and carotenoid status is less clear. Nonetheless, it is well known that carotenoids are associated with certain health benefits. Understanding these relations is key to improving health outcomes and mortality risk in infants and young children. Hyporetinolemia, i.e., low serum retinol concentrations, occurs during inflammation, and this can lead to the misdiagnosis of VA deficiency. On the other hand, inflammation causes impaired VA absorption and urinary losses that can precipitate VA deficiency in at-risk groups of children. Many epidemiologic studies have suggested that high dietary carotenoid intake and elevated plasma concentrations are correlated with a decreased risk of several chronic diseases; however, large-scale carotenoid supplementation trials have been unable to confirm the health benefits and in some cases resulted in controversial results. However, it has been documented that dietary carotenoids and retinoids play important roles in innate and acquired immunity and in the body’s response to inflammation. Although animal models have been useful in investigating retinoid effects on developmental immunity, it is more challenging to tease out the effects of carotenoids because of differences in the absorption, kinetics, and metabolism between humans and animal models. The current understanding of the relations between inflammation and retinoid and carotenoid metabolism and status are the topics of this review. PMID:28298266

  7. Metabolic Effects of Inflammation on Vitamin A and Carotenoids in Humans and Animal Models.

    Science.gov (United States)

    Rubin, Lewis P; Ross, A Catharine; Stephensen, Charles B; Bohn, Torsten; Tanumihardjo, Sherry A

    2017-03-01

    The association between inflammation and vitamin A (VA) metabolism and status assessment has been documented in multiple studies with animals and humans. The relation between inflammation and carotenoid status is less clear. Nonetheless, it is well known that carotenoids are associated with certain health benefits. Understanding these relations is key to improving health outcomes and mortality risk in infants and young children. Hyporetinolemia, i.e., low serum retinol concentrations, occurs during inflammation, and this can lead to the misdiagnosis of VA deficiency. On the other hand, inflammation causes impaired VA absorption and urinary losses that can precipitate VA deficiency in at-risk groups of children. Many epidemiologic studies have suggested that high dietary carotenoid intake and elevated plasma concentrations are correlated with a decreased risk of several chronic diseases; however, large-scale carotenoid supplementation trials have been unable to confirm the health benefits and in some cases resulted in controversial results. However, it has been documented that dietary carotenoids and retinoids play important roles in innate and acquired immunity and in the body's response to inflammation. Although animal models have been useful in investigating retinoid effects on developmental immunity, it is more challenging to tease out the effects of carotenoids because of differences in the absorption, kinetics, and metabolism between humans and animal models. The current understanding of the relations between inflammation and retinoid and carotenoid metabolism and status are the topics of this review. © 2017 American Society for Nutrition.

  8. A whole-body mathematical model of cholesterol metabolism and its age-associated dysregulation

    Directory of Open Access Journals (Sweden)

    Mc Auley Mark T

    2012-10-01

    Full Text Available Abstract Background Global demographic changes have stimulated marked interest in the process of aging. There has been, and will continue to be, an unrelenting rise in the number of the oldest old ( >85 years of age. Together with an ageing population there comes an increase in the prevalence of age related disease. Of the diseases of ageing, cardiovascular disease (CVD has by far the highest prevalence. It is regarded that a finely tuned lipid profile may help to prevent CVD as there is a long established relationship between alterations to lipid metabolism and CVD risk. In fact elevated plasma cholesterol, particularly Low Density Lipoprotein Cholesterol (LDL-C has consistently stood out as a risk factor for having a cardiovascular event. Moreover it is widely acknowledged that LDL-C may rise with age in both sexes in a wide variety of groups. The aim of this work was to use a whole-body mathematical model to investigate why LDL-C rises with age, and to test the hypothesis that mechanistic changes to cholesterol absorption and LDL-C removal from the plasma are responsible for the rise. The whole-body mechanistic nature of the model differs from previous models of cholesterol metabolism which have either focused on intracellular cholesterol homeostasis or have concentrated on an isolated area of lipoprotein dynamics. The model integrates both current and previously published data relating to molecular biology, physiology, ageing and nutrition in an integrated fashion. Results The model was used to test the hypothesis that alterations to the rate of cholesterol absorption and changes to the rate of removal of LDL-C from the plasma are integral to understanding why LDL-C rises with age. The model demonstrates that increasing the rate of intestinal cholesterol absorption from 50% to 80% by age 65 years can result in an increase of LDL-C by as much as 34 mg/dL in a hypothetical male subject. The model also shows that decreasing the rate of hepatic

  9. Modeling the role of negative cooperativity in metabolic regulation and homeostasis.

    Directory of Open Access Journals (Sweden)

    Eliot C Bush

    Full Text Available A significant proportion of enzymes display cooperativity in binding ligand molecules, and such effects have an important impact on metabolic regulation. This is easiest to understand in the case of positive cooperativity. Sharp responses to changes in metabolite concentrations can allow organisms to better respond to environmental changes and maintain metabolic homeostasis. However, despite the fact that negative cooperativity is almost as common as positive, it has been harder to imagine what advantages it provides. Here we use computational models to explore the utility of negative cooperativity in one particular context: that of an inhibitor binding to an enzyme. We identify several factors which may contribute, and show that acting together they can make negative cooperativity advantageous.

  10. Vitamin B12 Metabolism during Pregnancy and in Embryonic Mouse Models

    Directory of Open Access Journals (Sweden)

    Maira A. Moreno-Garcia

    2013-09-01

    Full Text Available Vitamin B12 (cobalamin, Cbl is required for cellular metabolism. It is an essential coenzyme in mammals for two reactions: the conversion of homocysteine to methionine by the enzyme methionine synthase and the conversion of methylmalonyl-CoA to succinyl-CoA by the enzyme methylmalonyl-CoA mutase. Symptoms of Cbl deficiency are hematological, neurological and cognitive, including megaloblastic anaemia, tingling and numbness of the extremities, gait abnormalities, visual disturbances, memory loss and dementia. During pregnancy Cbl is essential, presumably because of its role in DNA synthesis and methionine synthesis; however, there are conflicting studies regarding an association between early pregnancy loss and Cbl deficiency. We here review the literature about the requirement for Cbl during pregnancy, and summarized what is known of the expression pattern and function of genes required for Cbl metabolism in embryonic mouse models.

  11. Longitudinal Omics Modelling and Integration in Clinical Metabonomics Research: challenges in childhood metabolic health research

    Directory of Open Access Journals (Sweden)

    Peter eSperisen

    2015-08-01

    Full Text Available Systems biology is an important approach for deciphering the complex processes in health maintenance and the etiology of metabolic diseases. Such integrative methodologies will help better understand the molecular mechanisms involved in growth and development throughout childhood, and consequently will result in new insights about metabolic and nutritional requirements of infants, children and adults. To achieve this, a better understanding of the physiological processes at anthropometric, cellular and molecular level for any given individual is needed. In this respect, novel omics technologies in combination with sophisticated data modelling techniques are key. Due to the highly complex network of influential factors determining individual trajectories, it becomes imperative to develop proper tools and solutions that will comprehensively model biological information related to growth and maturation of our body functions. The aim of this review and perspective is to evaluate, succinctly, promising data analysis approaches to enable data integration for clinical research, with an emphasis on the longitudinal component. Approaches based on empirical and mechanistic modelling of omics data are essential to leverage findings from high dimensional omics datasets and enable biological interpretation and clinical translation. On the one hand, empirical methods, which provide quantitative descriptions of patterns in the data, are mostly used for exploring and mining datasets. On the other hand, mechanistic models are based on an understanding of the behavior of a system’s components and condense information about the known functions, allowing robust and reliable analyses to be performed by bioinformatics pipelines and similar tools. Herein, we will illustrate current examples, challenges and perspectives in the applications of empirical and mechanistic modelling in the context of childhood metabolic health research.

  12. Elucidation of xenobiotic metabolism pathways in human skin and human skin models by proteomic profiling.

    Directory of Open Access Journals (Sweden)

    Sven van Eijl

    Full Text Available BACKGROUND: Human skin has the capacity to metabolise foreign chemicals (xenobiotics, but knowledge of the various enzymes involved is incomplete. A broad-based unbiased proteomics approach was used to describe the profile of xenobiotic metabolising enzymes present in human skin and hence indicate principal routes of metabolism of xenobiotic compounds. Several in vitro models of human skin have been developed for the purpose of safety assessment of chemicals. The suitability of these epidermal models for studies involving biotransformation was assessed by comparing their profiles of xenobiotic metabolising enzymes with those of human skin. METHODOLOGY/PRINCIPAL FINDINGS: Label-free proteomic analysis of whole human skin (10 donors was applied and analysed using custom-built PROTSIFT software. The results showed the presence of enzymes with a capacity for the metabolism of alcohols through dehydrogenation, aldehydes through dehydrogenation and oxidation, amines through oxidation, carbonyls through reduction, epoxides and carboxylesters through hydrolysis and, of many compounds, by conjugation to glutathione. Whereas protein levels of these enzymes in skin were mostly just 4-10 fold lower than those in liver and sufficient to support metabolism, the levels of cytochrome P450 enzymes were at least 300-fold lower indicating they play no significant role. Four epidermal models of human skin had profiles very similar to one another and these overlapped substantially with that of whole skin. CONCLUSIONS/SIGNIFICANCE: The proteomics profiling approach was successful in producing a comprehensive analysis of the biotransformation characteristics of whole human skin and various in vitro skin models. The results show that skin contains a range of defined enzymes capable of metabolising different classes of chemicals. The degree of similarity of the profiles of the in vitro models indicates their suitability for epidermal toxicity testing. Overall, these

  13. Advantages and disadvantages of the animal models v. in vitro studies in iron metabolism: a review.

    Science.gov (United States)

    García, Y; Díaz-Castro, J

    2013-10-01

    Iron deficiency is the most common nutritional deficiency in the world. Special molecules have evolved for iron acquisition, transport and storage in soluble, nontoxic forms. Studies about the effects of iron on health are focused on iron metabolism or nutrition to prevent or treat iron deficiency and anemia. These studies are focused in two main aspects: (1) basic studies to elucidate iron metabolism and (2) nutritional studies to evaluate the efficacy of iron supplementation to prevent or treat iron deficiency and anemia. This paper reviews the advantages and disadvantages of the experimental models commonly used as well as the methods that are more used in studies related to iron. In vitro studies have used different parts of the gut. In vivo studies are done in humans and animals such as mice, rats, pigs and monkeys. Iron metabolism is a complex process that includes interactions at the systemic level. In vitro studies, despite physiological differences to humans, are useful to increase knowledge related to this essential micronutrient. Isotopic techniques are the most recommended in studies related to iron, but their high cost and required logistic, making them difficult to use. The depletion-repletion of hemoglobin is a method commonly used in animal studies. Three depletion-repletion techniques are mostly used: hemoglobin regeneration efficiency, relative biological values (RBV) and metabolic balance, which are official methods of the association of official analytical chemists. These techniques are well-validated to be used as studies related to iron and their results can be extrapolated to humans. Knowledge about the main advantages and disadvantages of the in vitro and animal models, and methods used in these studies, could increase confidence of researchers in the experimental results with less costs.

  14. Characterization of reproductive, metabolic, and endocrine features of polycystic ovary syndrome in female hyperandrogenic mouse models.

    Science.gov (United States)

    Caldwell, A S L; Middleton, L J; Jimenez, M; Desai, R; McMahon, A C; Allan, C M; Handelsman, D J; Walters, K A

    2014-08-01

    Polycystic ovary syndrome (PCOS) affects 5-10% of women of reproductive age, causing a range of reproductive, metabolic and endocrine defects including anovulation, infertility, hyperandrogenism, obesity, hyperinsulinism, and an increased risk of type 2 diabetes and cardiovascular disease. Hyperandrogenism is the most consistent feature of PCOS, but its etiology remains unknown, and ethical and logistic constraints limit definitive experimentation in humans to determine mechanisms involved. In this study, we provide the first comprehensive characterization of reproductive, endocrine, and metabolic PCOS traits in 4 distinct murine models of hyperandrogenism, comprising prenatal dihydrotestosterone (DHT, potent nonaromatizable androgen) treatment during days 16-18 of gestation, or long-term treatment (90 days from 21 days of age) with DHT, dehydroepiandrosterone (DHEA), or letrozole (aromatase inhibitor). Prenatal DHT-treated mature mice exhibited irregular estrous cycles, oligo-ovulation, reduced preantral follicle health, hepatic steatosis, and adipocyte hypertrophy, but lacked overall changes in body-fat composition. Long-term DHT treatment induced polycystic ovaries displaying unhealthy antral follicles (degenerate oocyte and/or > 10% pyknotic granulosa cells), as well as anovulation and acyclicity in mature (16-week-old) females. Long-term DHT also increased body and fat pad weights and induced adipocyte hypertrophy and hypercholesterolemia. Long-term letrozole-treated mice exhibited absent or irregular cycles, oligo-ovulation, polycystic ovaries containing hemorrhagic cysts atypical of PCOS, and displayed no metabolic features of PCOS. Long-term dehydroepiandrosterone treatment produced no PCOS features in mature mice. Our findings reveal that long-term DHT treatment replicated a breadth of ovarian, endocrine, and metabolic features of human PCOS and provides the best mouse model for experimental studies of PCOS pathogenesis.

  15. Computational Modeling of Fluctuations in Energy and Metabolic Pathways of Methanogenic Archaea

    Energy Technology Data Exchange (ETDEWEB)

    Luthey-Schulten, Zaida [Univ. of Illinois, Urbana-Champaign, IL (United States). Dept. of Chemistry; Carl R. Woese Inst. for Genomic Biology

    2017-01-04

    The methanogenic archaea, anaerobic microbes that convert CO2 and H2 and/or other small organic fermentation products into methane, play an unusually large role in the global carbon cycle. As they perform the final step in the anaerobic breakdown of biomass, methanogens are a biogenic source of an estimated one billion tons methane each year. Depending on the location, produced methane can be considered as either a greenhouse gas (agricultural byproduct), sequestered carbon storage (methane hydrate deposits), or a potential energy source (organic wastewater treatment). These microbes therefore represent an important target for biotechnology applications. Computational models of methanogens with predictive power are useful aids in the adaptation of methanogenic systems, but need to connect processes of wide-ranging time and length scales. In this project, we developed several computational methodologies for modeling the dynamic behavior of entire cells that connects stochastic reaction-diffusion dynamics of individual biochemical pathways with genome-scale modeling of metabolic networks. While each of these techniques were in the realm of well-defined computational methods, here we integrated them to develop several entirely new approaches to systems biology. The first scientific aim of the project was to model how noise in a biochemical pathway propagates into cellular phenotypes. Genetic circuits have been optimized by evolution to regulate molecular processes despite stochastic noise, but the effect of such noise on a cellular biochemical networks is currently unknown. An integrated stochastic/systems model of Escherichia coli species was created to analyze how noise in protein expression gives—and therefore noise in metabolic fluxes—gives rise to multiple cellular phenotype in isogenic population. After the initial work developing and validating methods that allow characterization of the heterogeneity in the model organism E. coli, the project shifted toward

  16. Metabolic level recognition of progesterone in dairy Holstein cows using probabilistic models

    Directory of Open Access Journals (Sweden)

    Ludmila N. Turino

    2014-05-01

    Full Text Available Administration of exogenous progesterone is widely used in hormonal protocols for estrous (resynchronization of dairy cattle without regarding pharmacological issues for dose calculation. This happens because it is difficult to estimate the metabolic level of progesterone for each individual cow before administration. In the present contribution, progesterone pharmacokinetics has been determined in lactating Holstein cows with different milk production yields. A Bayesian approach has been implemented to build two probabilistic progesterone pharmacokinetic models for high and low yield dairy cows. Such models are based on a one-compartment Hill structure. Posterior probabilistic models have been structurally set up and parametric probability density functions have been empirically estimated. Moreover, a global sensitivity analysis has been done to know sensitivity profile of each model. Finally, posterior probabilistic models have adequately recognized cow’s progesterone metabolic level in a validation set when Kullback-Leibler based indices were used. These results suggest that milk yield may be a good index for estimating pharmacokinetic level of progesterone.

  17. Relationships between metal compartmentalization and biomarkers in earthworms exposed to field-contaminated soils.

    Science.gov (United States)

    Beaumelle, Léa; Hedde, Mickaël; Vandenbulcke, Franck; Lamy, Isabelle

    2017-05-01

    Partitioning tissue metal concentration into subcellular compartments reflecting toxicologically available pools may provide good descriptors of the toxicological effects of metals on organisms. Here we investigated the relationships between internal compartmentalization of Cd, Pb and Zn and biomarker responses in a model soil organism: the earthworm. The aim of this study was to identify metal fractions reflecting the toxic pressure in an endogeic, naturally occurring earthworm species (Aporrectodea caliginosa) exposed to realistic field-contaminated soils. After a 21 days exposure experiment to 31 field-contaminated soils, Cd, Pb and Zn concentrations in earthworms and in three subcellular fractions (cytosol, debris and granules) were quantified. Different biomarkers were measured: the expression of a metallothionein gene (mt), the activity of catalase (CAT) and of glutathione-s-transferase (GST), and the protein, lipid and glycogen reserves. Biomarkers were further combined into an integrated biomarker index (IBR). The subcellular fractionation provided better predictors of biomarkers than the total internal contents hence supporting its use when assessing toxicological bioavailability of metals to earthworms. The most soluble internal pools of metals were not always the best predictors of biomarker responses. metallothionein expression responded to increasing concentrations of Cd in the insoluble fraction (debris + granules). Protein and glycogen contents were also mainly related to Cd and Pb in the insoluble fraction. On the other hand, GST activity was better explained by Pb in the cytosolic fraction. CAT activity and lipid contents variations were not related to metal subcellular distribution. The IBR was best explained by both soluble and insoluble fractions of Pb and Cd. This study further extends the scope of mt expression as a robust and specific biomarker in an ecologically representative earthworm species exposed to field-contaminated soils. The

  18. Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

    KAUST Repository

    Jolivet, Renaud; Coggan, Jay S.; Allaman, Igor; Magistretti, Pierre J.

    2015-01-01

    time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest

  19. Compartmental and dosimetric studies of anti-CD20 labelled with {sup 188}Re; Estudo compartimental e dosimetrico do Anti-CD20 marcado com {sup 188}Re

    Energy Technology Data Exchange (ETDEWEB)

    Kuramoto, Graciela Barrio

    2016-10-01

    The radioimmunotherapy (RIT) uses MAbs conjugated to radionuclides α or β{sup -} emitters, both for therapy. Your treatment is based on the irradiation and tumor destruction, preserving the normal organs as the excess radiation. Radionuclides β{sup -} emitters as {sup 131}I, {sup 90}Y, {sup 188}Re {sup 177}Lu and are useful for the development of therapeutic radiopharmaceuticals and, when coupled with MAb and Anti-CD20 it is important mainly for the treatment of non-Hodgkin's lymphomas (NHL). {sup 188}Re (E{sub β} = 2.12 MeV; E{sub γ} = 155 keV; t1/2 = 16.9 h) is an attractive radionuclide for RIT. However, {sup 188}Re can be obtained from a radionuclide generator of {sup 188}W/{sup 188}Re, commercially available, making it convenient for use in research and for clinical routine. The CR of IPEN has a project aimed at the production of radiopharmaceutical {sup 188}Re-Anti-CD20, where the radionuclide can be obtained from a generator system {sup 188}W/{sup 188}Re. With this proposed a study to assess the efficiency of this labeling technique for treatment in accordance compartmental and dosimetry. The objective of this study was to compare the marking of anti-CD20 MAb with {sup 188}Re with the marking of the antibody with {sup 90}Y, {sup 131}I, {sup 177}Lu and {sup 99m}Tc (for their similar chemical characteristics) and {sup 211}At, {sup 213}Bi, {sup 223}Ra and {sup 225}Ac); through the study of labeling techniques reported in literature, the proposal of a compartmental model to evaluate its pharmacokinetic and dosimetric studies, high interest for therapy. The result of the study shows a favorable kinetics for {sup 188}Re, by their physical and chemical characteristics compared to the other evaluated radionuclides. The compartment proposed study describes the metabolism of {sup 188}Reanti- CD20 through a compartment mammillary model, which by their pharmacokinetic analysis, performed compared to products emitters β{sup -131}I-labeled anti CD20, {sup 177

  20. Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model

    International Nuclear Information System (INIS)

    Dash, Satyakam; Mueller, Thomas J.; Venkataramanan, Keerthi P.; Papoutsakis, Eleftherios T.; Maranas, Costas D.

    2014-01-01

    Clostridia are anaerobic Gram-positive Firmicutes containing broad and flexible systems for substrate utilization, which have been used successfully to produce a range of industrial compounds. Clostridium acetobutylicum has been used to produce butanol on an industrial scale through acetone-butanol-ethanol (ABE) fermentation. A genome-scale metabolic (GSM) model is a powerful tool for understanding the metabolic capacities of an organism and developing metabolic engineering strategies for strain development. The integration of stress related specific transcriptomics information with the GSM model provides opportunities for elucidating the focal points of regulation

  1. The polygonal model: A simple representation of biomolecules as a tool for teaching metabolism.

    Science.gov (United States)

    Bonafe, Carlos Francisco Sampaio; Bispo, Jose Ailton Conceição; de Jesus, Marcelo Bispo

    2018-01-01

    Metabolism involves numerous reactions and organic compounds that the student must master to understand adequately the processes involved. Part of biochemical learning should include some knowledge of the structure of biomolecules, although the acquisition of such knowledge can be time-consuming and may require significant effort from the student. In this report, we describe the "polygonal model" as a new means of graphically representing biomolecules. This model is based on the use of geometric figures such as open triangles, squares, and circles to represent hydroxyl, carbonyl, and carboxyl groups, respectively. The usefulness of the polygonal model was assessed by undergraduate students in a classroom activity that consisted of "transforming" molecules from Fischer models to polygonal models and vice and versa. The survey was applied to 135 undergraduate Biology and Nursing students. Students found the model easy to use and we noted that it allowed identification of students' misconceptions in basic concepts of organic chemistry, such as in stereochemistry and organic groups that could then be corrected. The students considered the polygonal model easier and faster for representing molecules than Fischer representations, without loss of information. These findings indicate that the polygonal model can facilitate the teaching of metabolism when the structures of biomolecules are discussed. Overall, the polygonal model promoted contact with chemical structures, e.g. through drawing activities, and encouraged student-student dialog, thereby facilitating biochemical learning. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):66-75, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.

  2. Inhibition of mirtazapine metabolism by Ecstasy (MDMA) in isolated perfused rat liver model.

    Science.gov (United States)

    Jamshidfar, Sanaz; Ardakani, Yalda H; Lavasani, Hoda; Rouini, Mohammadreza

    2017-06-28

    Nowadays MDMA (3,4-methylendioxymethamphetamine), known as ecstasy, is widely abused among the youth because of euphoria induction in acute exposure. However, abusers are predisposed to depression in chronic consumption of this illicit compound. Mirtazapine (MRZ), an antidepressant agent, may be prescribed in MDMA-induced depression. MRZ is extensively metabolized in liver by CYP450 isoenzymes. 8-hydroxymirtazapine (8-OH) is mainly produced by CYP2D6. N-desmethylmirtazapine (NDES) is generated by CYP3A4. MDMA is also metabolized by the mentioned isoenzymes and demonstrates mechanism-based inhibition (MBI) in association with CYP2D6. Several studies revealed that MDMA showed inhibitory effects on CYP3A4. In the present study, our aim was to evaluate the impact of MDMA on the metabolism of MRZ in liver. Therefore, isolated perfused rat liver model was applied as our model of choice in this assessment. The subjects of the study were categorized into two experimental groups. Rats in the control group received MRZ-containing Krebs-Henselit buffer (1 μg/ml). Rats in the treatment group received aqueous solution of 1 mg/ml MDMA (3 mg/kg) intraperitoneally 1 hour before receiving MRZ. Perfusate samples were analyzed by HPLC. Analyses of perfusate samples showed 80% increase in the parent drug concentrations and 50% decrease in the concentrations of both metabolites in our treatment group compared to the control group. In the treatment group compared to the control group, AUC (0-120) of the parent drug demonstrated 50% increase and AUC (0-120) of 8-OH and NDES showed 70% and 60% decrease, respectively. Observed decrease in metabolic ratios were 83% and 79% for 8-OH and NDES in treatment group compared to control group, respectively. Hepatic clearance (CL h ) and intrinsic clearance (Cl int ) showed 20% and 60% decrease in treatment group compared to control group. All findings prove the inhibitory effects of ecstasy on both CYP2D6 and CYP3A4 hepatic isoenzymes. In

  3. A computer model simulating human glucose absorption and metabolism in health and metabolic disease states [version 1; referees: 2 approved, 1 approved with reservations

    Directory of Open Access Journals (Sweden)

    Richard J. Naftalin

    2016-04-01

    Full Text Available A computer model designed to simulate integrated glucose-dependent changes in splanchnic blood flow with small intestinal glucose absorption, hormonal and incretin circulation and hepatic and systemic metabolism in health and metabolic diseases e.g. non-alcoholic fatty liver disease, (NAFLD, non-alcoholic steatohepatitis, (NASH and type 2 diabetes mellitus, (T2DM demonstrates how when glucagon-like peptide-1, (GLP-1 is synchronously released into the splanchnic blood during intestinal glucose absorption, it stimulates superior mesenteric arterial (SMA blood flow and by increasing passive intestinal glucose absorption, harmonizes absorption with its distribution and metabolism. GLP-1 also synergises insulin-dependent net hepatic glucose uptake (NHGU. When GLP-1 secretion is deficient post-prandial SMA blood flow is not increased and as NHGU is also reduced, hyperglycaemia follows. Portal venous glucose concentration is also raised, thereby retarding the passive component of intestinal glucose absorption.   Increased pre-hepatic sinusoidal resistance combined with portal hypertension leading to opening of intrahepatic portosystemic collateral vessels are NASH-related mechanical defects that alter the balance between splanchnic and systemic distributions of glucose, hormones and incretins.The model reveals the latent contribution of portosystemic shunting in development of metabolic disease. This diverts splanchnic blood content away from the hepatic sinuses to the systemic circulation, particularly during the glucose absorptive phase of digestion, resulting in inappropriate increases in insulin-dependent systemic glucose metabolism.  This hastens onset of hypoglycaemia and thence hyperglucagonaemia. The model reveals that low rates of GLP-1 secretion, frequently associated with T2DM and NASH, may be also be caused by splanchnic hypoglycaemia, rather than to intrinsic loss of incretin secretory capacity. These findings may have therapeutic

  4. Mice with chimeric livers are an improved model for human lipoprotein metabolism.

    Science.gov (United States)

    Ellis, Ewa C S; Naugler, Willscott Edward; Nauglers, Scott; Parini, Paolo; Mörk, Lisa-Mari; Jorns, Carl; Zemack, Helen; Sandblom, Anita Lövgren; Björkhem, Ingemar; Ericzon, Bo-Göran; Wilson, Elizabeth M; Strom, Stephen C; Grompe, Markus

    2013-01-01

    Rodents are poor model for human hyperlipidemias because total cholesterol and low density lipoprotein levels are very low on a normal diet. Lipoprotein metabolism is primarily regulated by hepatocytes and we therefore assessed whether chimeric mice extensively repopulated with human cells can model human lipid and bile acid metabolism. FRG [ F ah(-/-) R ag2(-/-)Il2r g (-/-)]) mice were repopulated with primary human hepatocytes. Serum lipoprotein lipid composition and distribution (VLDL, LDL, and HDL) was analyzed by size exclusion chromatography. Bile was analyzed by LC-MS or by GC-MS. RNA expression levels were measured by quantitative RT-PCR. Chimeric mice displayed increased LDL and VLDL fractions and a lower HDL fraction compared to wild type, thus significantly shifting the ratio of LDL/HDL towards a human profile. Bile acid analysis revealed a human-like pattern with high amounts of cholic acid and deoxycholic acid (DCA). Control mice had only taurine-conjugated bile acids as expcted, but highly repopulated mice had glycine-conjugated cholic acid as found in human bile. RNA levels of human genes involved in bile acid synthesis including CYP7A1, and CYP27A1 were significantly upregulated as compared to human control liver. However, administration of recombinant hFGF19 restored human CYP7A1 levels to normal. Humanized-liver mice showed a typical human lipoprotein profile with LDL as the predominant lipoprotein fraction even on a normal diet. The bile acid profile confirmed presence of an intact enterohepatic circulation. Although bile acid synthesis was deregulated in this model, this could be fully normalized by FGF19 administration. Taken together these data indicate that chimeric FRG-mice are a useful new model for human lipoprotein and bile-acid metabolism.

  5. Towards systems metabolic engineering in Pichia pastoris.

    Science.gov (United States)

    Schwarzhans, Jan-Philipp; Luttermann, Tobias; Geier, Martina; Kalinowski, Jörn; Friehs, Karl

    2017-11-01

    The methylotrophic yeast Pichia pastoris is firmly established as a host for the production of recombinant proteins, frequently outperforming other heterologous hosts. Already, a sizeable amount of systems biology knowledge has been acquired for this non-conventional yeast. By applying various omics-technologies, productivity features have been thoroughly analyzed and optimized via genetic engineering. However, challenging clonal variability, limited vector repertoire and insufficient genome annotation have hampered further developments. Yet, in the last few years a reinvigorated effort to establish P. pastoris as a host for both protein and metabolite production is visible. A variety of compounds from terpenoids to polyketides have been synthesized, often exceeding the productivity of other microbial systems. The clonal variability was systematically investigated and strategies formulated to circumvent untargeted events, thereby streamlining the screening procedure. Promoters with novel regulatory properties were discovered or engineered from existing ones. The genetic tractability was increased via the transfer of popular manipulation and assembly techniques, as well as the creation of new ones. A second generation of sequencing projects culminated in the creation of the second best functionally annotated yeast genome. In combination with landmark physiological insights and increased output of omics-data, a good basis for the creation of refined genome-scale metabolic models was created. The first application of model-based metabolic engineering in P. pastoris showcased the potential of this approach. Recent efforts to establish yeast peroxisomes for compartmentalized metabolite synthesis appear to fit ideally with the well-studied high capacity peroxisomal machinery of P. pastoris. Here, these recent developments are collected and reviewed with the aim of supporting the establishment of systems metabolic engineering in P. pastoris. Copyright © 2017. Published

  6. Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

    DEFF Research Database (Denmark)

    Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.

    2017-01-01

    orders of magnitude. Data values also have greatly varying magnitudes. Standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME......Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many...... models have 70,000 constraints and variables and will grow larger). We have developed a quadrupleprecision version of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging...

  7. LITTLE FISH, BIG DATA: ZEBRAFISH AS A MODEL FOR CARDIOVASCULAR AND METABOLIC DISEASE.

    Science.gov (United States)

    Gut, Philipp; Reischauer, Sven; Stainier, Didier Y R; Arnaout, Rima

    2017-07-01

    The burden of cardiovascular and metabolic diseases worldwide is staggering. The emergence of systems approaches in biology promises new therapies, faster and cheaper diagnostics, and personalized medicine. However, a profound understanding of pathogenic mechanisms at the cellular and molecular levels remains a fundamental requirement for discovery and therapeutics. Animal models of human disease are cornerstones of drug discovery as they allow identification of novel pharmacological targets by linking gene function with pathogenesis. The zebrafish model has been used for decades to study development and pathophysiology. More than ever, the specific strengths of the zebrafish model make it a prime partner in an age of discovery transformed by big-data approaches to genomics and disease. Zebrafish share a largely conserved physiology and anatomy with mammals. They allow a wide range of genetic manipulations, including the latest genome engineering approaches. They can be bred and studied with remarkable speed, enabling a range of large-scale phenotypic screens. Finally, zebrafish demonstrate an impressive regenerative capacity scientists hope to unlock in humans. Here, we provide a comprehensive guide on applications of zebrafish to investigate cardiovascular and metabolic diseases. We delineate advantages and limitations of zebrafish models of human disease and summarize their most significant contributions to understanding disease progression to date. Copyright © 2017 the American Physiological Society.

  8. Genetic dissection in a mouse model reveals interactions between carotenoids and lipid metabolism.

    Science.gov (United States)

    Palczewski, Grzegorz; Widjaja-Adhi, M Airanthi K; Amengual, Jaume; Golczak, Marcin; von Lintig, Johannes

    2016-09-01

    Carotenoids affect a rich variety of physiological functions in nature and are beneficial for human health. However, knowledge about their biological action and the consequences of their dietary accumulation in mammals is limited. Progress in this research field is limited by the expeditious metabolism of carotenoids in rodents and the confounding production of apocarotenoid signaling molecules. Herein, we established a mouse model lacking the enzymes responsible for carotenoid catabolism and apocarotenoid production, fed on either a β-carotene- or a zeaxanthin-enriched diet. Applying a genome wide microarray analysis, we assessed the effects of the parent carotenoids on the liver transcriptome. Our analysis documented changes in pathways for liver lipid metabolism and mitochondrial respiration. We biochemically defined these effects, and observed that β-carotene accumulation resulted in an elevation of liver triglycerides and liver cholesterol, while zeaxanthin accumulation increased serum cholesterol levels. We further show that carotenoids were predominantly transported within HDL particles in the serum of mice. Finally, we provide evidence that carotenoid accumulation influenced whole-body respiration and energy expenditure. Thus, we observed that accumulation of parent carotenoids interacts with lipid metabolism and that structurally related carotenoids display distinct biological functions in mammals. Copyright © 2016 by the American Society for Biochemistry and Molecular Biology, Inc.

  9. Diet-induced metabolic hamster model of nonalcoholic fatty liver disease

    Directory of Open Access Journals (Sweden)

    Bhathena J

    2011-06-01

    Full Text Available Jasmine Bhathena, Arun Kulamarva, Christopher Martoni, Aleksandra Malgorzata Urbanska, Meenakshi Malhotra, Arghya Paul, Satya PrakashBiomedical Technology and Cell Therapy Research Laboratory, Department of Biomedical Engineering, Artificial Cells and Organs Research Centre, Faculty of Medicine, McGill University, Montreal, Québec, CanadaBackground: Obesity, hypercholesterolemia, elevated triglycerides, and type 2 diabetes are major risk factors for metabolic syndrome. Hamsters, unlike rats or mice, respond well to diet-induced obesity, increase body mass and adiposity on group housing, and increase food intake due to social confrontation-induced stress. They have a cardiovascular and hepatic system similar to that of humans, and can thus be a useful model for human pathophysiology.Methods: Experiments were planned to develop a diet-induced Bio F1B Golden Syrian hamster model of dyslipidemia and associated nonalcoholic fatty liver disease in the metabolic syndrome. Hamsters were fed a normal control diet, a high-fat/high-cholesterol diet, a high-fat/high-cholesterol/methionine-deficient/choline-devoid diet, and a high-fat/high-cholesterol/choline-deficient diet. Serum total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, glucose, atherogenic index, and body weight were quantified biweekly. Fat deposition in the liver was observed and assessed following lipid staining with hematoxylin and eosin and with oil red O.Results: In this study, we established a diet-induced Bio F1B Golden Syrian hamster model for studying dyslipidemia and associated nonalcoholic fatty liver disease in the metabolic syndrome. Hyperlipidemia and elevated serum glucose concentrations were induced using this diet. Atherogenic index was elevated, increasing the risk for a cardiovascular event. Histological analysis of liver specimens at the end of four weeks showed increased fat deposition in the liver of animals fed

  10. Adiponectin protects against development of metabolic disturbances in a PCOS mouse model.