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Detailed Models (detailed + models)
Selected AbstractsORIGINAL ARTICLE: Probability of emergence of antimalarial resistance in different stages of the parasite life cycleEVOLUTIONARY APPLICATIONS (ELECTRONIC), Issue 1 2009Wirichada Pongtavornpinyo Abstract Understanding the evolution of drug resistance in malaria is a central area of study at the intersection of evolution and medicine. Antimalarial drug resistance is a major threat to malaria control and directly related to trends in malaria attributable mortality. Artemisinin combination therapies (ACT) are now recommended worldwide as first line treatment for uncomplicated malaria, and losing them to resistance would be a disaster for malaria control. Understanding the emergence and spread of antimalarial drug resistance in the context of different scenarios of antimalarial drug use is essential for the development of strategies protecting ACTs. In this study, we review the basic mechanisms of resistance emergence and describe several simple equations that can be used to estimate the probabilities of de novo resistance mutations at three stages of the parasite life cycle: sporozoite, hepatic merozoite and asexual blood stages; we discuss the factors that affect parasite survival in a single host in the context of different levels of antimalarial drug use, immunity and parasitaemia. We show that in the absence of drug effects, and despite very different parasite numbers, the probability of resistance emerging at each stage is very low and similar in all stages (for example per-infection probability of 10,10,10,9 if the per-parasite chance of mutation is 10,10 per asexual division). However, under the selective pressure provided by antimalarial treatment and particularly in the presence of hyperparasitaemia, the probability of resistance emerging in the blood stage of the parasite can be approximately five orders of magnitude higher than in the absence of drugs. Detailed models built upon these basic methods should allow us to assess the relative probabilities of resistance emergence in the different phases of the parasite life cycle. [source] A photometric,spectroscopic analysis and the evolutionary status of the Algol-type binary U Coronae BorealisMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 4 2003S. K. Yerli ABSTRACT The prime purposes of this study are to obtain reliable orbital parameters for the Algol-type binary U Coronae Borealis (U CrB) and to explain the evolutionary status of this system. All observations of the primary star's radial velocity are consistent with the value K1= 58.6 ± 2.0 km s,1. Measurements of the radial velocity of the secondary component give K2 = 185.2 ± 5.0 km s,1. Using the photometrically determined inclination of 78.7 ± 0.3, the masses of the two stars are therefore deduced to be 4.74 ± 0.28 and 1.46 ± 0.06 M, for the primary and secondary components, respectively. Using all available observations, we discuss the origin and evolution of the close binary system U CrB. We derive the restrictions concerning masses and period from a general network of calculations of medium mass close binary evolution. Detailed models are calculated within the derived ranges, giving the most likely initial system parameters as and Pi= 1.4 d. It turns out that the interactive evolution up to the present stage has been non-conservative. During its evolution, U CrB has lost about 14 per cent of its initial total mass (,M, 1 M,) and around 18 per cent of its initial total angular momentum. We also examine the possibility of probing dynamo action in the mass-losing component of U CrB. We point out that, in order to maintain the evolution of U CrB in its later stages, which is presumably driven by stellar ,magnetic braking', an efficient mechanism for producing large-scale surface magnetic fields in the donor star is required. We suggest that observed X-ray activity in U CrB may be a good indicator of its evolutionary status and the internal structure of the mass-losing component. [source] Millisecond catalytic wall reactors: I. Radiant burnerAICHE JOURNAL, Issue 5 2001J. M. Redenius Short-contact-time reactors have potential for high throughput in reactors much smaller than their traditional counterparts. While they operate adiabatically, heat can be exchanged at short contact time by integrating heat exchange into the reactor. Hot effluent of exothermic reaction systems can be redirected over feed gases to recuperate a portion of the sensible heat. Placing catalyst directly on reactor walls eliminates the resistance to heat transfer in the thermal boundary layer so that heat released by combustion can be effectively coupled to an emitter, such as in a radiant burner. A radiant heater was constructed, operated, and simulated incorporating short contact time, energy recuperation, and a catalytic wall. This burner operated stably for many hours at a firing rate from ,50 to > 160 kW/m2 at a radiant temperature of 950 to 1,150 K at a radiant efficiency of ,60% with a residence time in the reacting zone of ,10 ms. This reactor was modeled using 2-D Navier-Stokes equations including detailed models for chemistry and heat transport. Temperature and compositions predicted agreed well with experimental measurements. [source] Model Development in Thermal Styrene PolymerizationMACROMOLECULAR SYMPOSIA, Issue 1 2007Bryan Matthews Abstract Summary: The thermal polymerization of styrene is usually modeled by relying on a reaction scheme and a set of equations that were developed more than three decades ago by Hui and Hamielec. Many detailed models of styrene polymerization are available in the open literature and they are mostly based on the work of Hui and Hamielec, which nearly makes this the standard to follow in explaining the behavior of polystyrene reactors. The model of Hui and Hamielec does a very nice job of describing monomer conversion data but discrepancies are seen between observed and predicted values of number and weight average molecular weights, Mn and Mw. Discrepancies in number average molecular weight seem to be the result of random noise. Discrepancies in weight average molecular weight grow as the polymerization temperature decreases and some of the trends observed in the residuals over the entire temperature range cannot be attributed to random noise. Hui and Hamielec attributed the observed deficiencies to a standard deviation of ±10% in their GPC measurements. A new data set with an experimental error of 2% for average molecular weights is presented. The set contains measured values of Mn, Mw and Mz, so the polymerization scheme has been extended to include third order moments. The data set also includes the effect of ethylbenzene as a chain transfer agent. We present the results of comparing model predictions to our measurements and the adjustments made in the original set of kinetic parameters published by Hui and Hamielec. [source] Calcium sensing and cell signaling processes in the local regulation of osteoclastic bone resorptionBIOLOGICAL REVIEWS, Issue 1 2004Mone Zaidi ABSTRACT The skeletal matrix in terrestrial vertebrates undergoes continual cycles of removal and replacement in the processes of bone growth, repair and remodeling. The osteoclast is uniquely important in bone resorption and thus is implicated in the pathogenesis of clinically important bone and joint diseases. Activated osteoclasts form a resorptive hemivacuole with the bone surface into which they release both acid and osteoclastic lysosomal hydrolases. This article reviews cell physiological studies of the local mechanisms that regulate the resorptive process. These used in vitro methods for the isolation, culture and direct study of the properties of neonatal rat osteoclasts. They demonstrated that both local microvascular agents and products of the bone resorptive process such as ambient Ca2+ could complement longer-range systemic regulatory mechanisms such as those that might be exerted through calcitonin (CT). Thus elevated extracellular [Ca2+], or applications of surrogate divalent cation agonists for Ca2+, inhibited bone resorptive activity and produced parallel increases in cytosolic [Ca2+], cell retraction and longer-term inhibition of enzyme release in isolated rat osteoclasts. These changes showed specificity, inactivation, and voltage-dependent properties that implicated a cell surface Ca2+ receptor (CaR) sensitive to millimolar extracellular [Ca2+]. Pharmacological, biophysical and immunochemical evidence implicated a ryanodine-receptor (RyR) type II isoform in this process and localized it to a unique, surface membrane site, with an outward-facing channel-forming domain. Such a surface RyR might function either directly or indirectly in the process of extracellular [Ca2+] sensing and in turn be modulated by cyclic adenosine diphosphate ribose (cADPr) produced by the ADP-ribosyl cyclase, CD38. The review finishes by speculating about possible detailed models for these transduction events and their possible interactions with other systemic mechanisms involved in Ca2+ homeostasis as well as the possible role of the RyR-based signaling mechanisms in longer-term cell regulatory processes. [source] Prediction of metabolic function from limited data: Lumped hybrid cybernetic modeling (L-HCM)BIOTECHNOLOGY & BIOENGINEERING, Issue 2 2010Hyun-Seob Song Abstract Motivated by the need for a quick quantitative assessment of metabolic function without extensive data, we present an adaptation of the cybernetic framework, denoted as the lumped hybrid cybernetic model (L-HCM), which combines the attributes of the classical lumped cybernetic model (LCM) and the recently developed HCM. The basic tenet of L-HCM and HCM is the same, that is, they both view the uptake flux as being split among diverse pathways in an optimal way as a result of cellular regulation such that some chosen metabolic objective is realized. The L-HCM, however, portrays this flux distribution to occur in a hierarchical way, that is, first among lumped pathways, and next among individual elementary modes (EM) in each lumped pathway. Both splits are described by the cybernetic control laws using operational and structural return-on-investments, respectively. That is, the distribution of uptake flux at the first split is dynamically regulated according to environmental conditions, while the subsequent split is based purely on the stoichiometry of EMs. The resulting model is conveniently represented in terms of lumped pathways which are fully identified with respect to yield coefficients of all products unlike classical LCMs based on instinctive lumping. These characteristics enable the model to account for the complete set of EMs for arbitrarily large metabolic networks despite containing only a small number of parameters which can be identified using minimal data. However, the inherent conflict of questing for quantification of larger networks with smaller number of parameters cannot be resolved without a mechanism for parameter tuning of an empirical nature. In this work, this is accomplished by manipulating the relative importance of EMs by tuning the cybernetic control of mode-averaged enzyme activity with an empirical parameter. In a case study involving aerobic batch growth of Saccharomyces cerevisiae, L-HCM is compared with LCM. The former provides a much more satisfactory prediction than the latter when parameters are identified from a few primary metabolites. On the other hand, the classical model is more accurate than L-HCM when sufficient datasets are involved in parameter identification. In applying the two models to a chemostat scenario, L-HCM shows a reasonable prediction on metabolic shift from respiration to fermentation due to the Crabtree effect, which LCM predicts unsatisfactorily. While L-HCM appears amenable to expeditious estimates of metabolic function with minimal data, the more detailed dynamic models [such as HCM or those of Young et al. (Young et al., Biotechnol Bioeng, 2008; 100: 542,559)] are best suited for accurate treatment of metabolism when the potential of modern omic technology is fully realized. However, in view of the monumental effort surrounding the development of detailed models from extensive omic measurements, the preliminary insight into the behavior of a genotype and metabolic engineering directives that can come from L-HCM is indeed valuable. Biotechnol. Bioeng. 2010;106: 271,284. © 2010 Wiley Periodicals, Inc. [source] A hybrid model of anaerobic E. coli GJT001: Combination of elementary flux modes and cybernetic variablesBIOTECHNOLOGY PROGRESS, Issue 5 2008Jin Il Kim Flux balance analysis (FBA) in combination with the decomposition of metabolic networks into elementary modes has provided a route to modeling cellular metabolism. It is dependent, however, on the availability of external fluxes such as substrate uptake or growth rate before estimates can become available of intracellular fluxes. The framework classically does not allow modeling of metabolic regulation or the formulation of dynamic models except through dynamic measurement of external fluxes. The cybernetic modeling approach of Ramkrishna and coworkers provides a dynamic framework for modeling metabolic systems because of its focus on describing regulatory processes based on cybernetic arguments and hence has the capacity to describe both external and internal fluxes. In this article, we explore the alternative of developing hybrid models combining cybernetic models for the external fluxes with the flux balance approach for estimation of the internal fluxes. The approach has the merit of the simplicity of the early cybernetic models and hence computationally facile while also providing detailed information on intracellular fluxes. The hybrid model of this article is based on elementary mode decomposition of the metabolic network. The uptake rates for the various elementary modes are combined using global cybernetic variables based on maximizing substrate uptake rates. Estimation of intracellular metabolism is based on its stoichiometric coupling with the external fluxes under the assumption of (pseudo-) steady state conditions. The set of parameters of the hybrid model was estimated with the aid of nonlinear optimization routine, by fitting simulations with dynamic experimental data on concentrations of biomass, substrate, and fermentation products. The hybrid model estimations were tested with FBA (based on measured substrate uptake rate) for two different metabolic networks (one is a reduced network which fixes ATP contribution to the biomass and maintenance requirement of ATP, and the other network is a more complex network which has a separate reaction for maintenance.) for the same experiment involving anaerobic growth of E. coli GJT001. The hybrid model estimated glucose consumption and all fermentation byproducts to better than 10%. The FBA makes similar estimations of fermentation products, however, with the exception of succinate. The simulation results show that the global cybernetic variables alone can regulate the metabolic reactions obtaining a very satisfactory fit to the measured fermentation byproducts. In view of the hybrid model's ability to predict biomass growth and fermentation byproducts of anaerobic E. coli GJT001, this reduced order model offers a computationally efficient alternative to more detailed models of metabolism and hence useful for the simulation of bioreactors. [source] | ||||||||||