Modelling baculovirus infection of insect cells in culture

Conclusions Infection of insect cells with baculovirus is a potentially attractive means for producing both viral insecticides and recombinant proteins. The continuation of mathematical modelling studies such as those reviewed in this paper are essential in order to realise the full potential of the system. Through mathematical models it is possible to predict complex behaviours such as those observed when infecting cells at low MOI or when propagating virus in a continuous culture system. A purely empirical analysis of the same phenomena is very difficult if not impossible.The present three models are — despite their complexity and the effort that has gone into developing them — all first generation models. They summarise, to a large extent, our present quantitative understanding of the interaction between baculovirus and insect cells, when looked upon as a black box system. The binding and initial infection processes are still quantitatively poorly understood and further work in this area is much needed. On the longer term, a second generation of models is likely to consider interior processes such as viral DNA and RNA accumulation in much more detail using a structured model of the infection cycle.     

A Monte Carlo method for the simulation of kinetie models

The purpose of this note is to illustrate the feasibility of simulating kinetic systems, such as commonly encountered in photosynthesis research, using the Monte Carlo (MC) method. In this approach, chemical events are considered at the molecular level where they occur randomly and the macroscopic kinetic evolution results from averaging a large number of such events. Their repeated simulation is easily accomplished using digital computing. It is shown that the MC approach is well suited to the capabilities and resources of modern microcomputers. A software package is briefly described and discussed, allowing a simple programming of any kinetic model system and its resolution. The execution is reasonably fast and accurate; it is not subject to such instabilities as found with the conventional analytical approach.Abbreviations MC Monte Carlo - RN random number - PSU photosynthetic unit Dedicated to Prof. L.N.M. Duysens on the occasion of his retirement.     

A mathematical model of baculovirus infection on insect cells at low multiplicity of infection

The expression efficiency of the insect cells-baculovirus system used for insecticidal virus production and the expression of medically useful foreign genes is closely related with the dynamics of infection. The present studies develop a model of the dynamic process of insect cell infection with baculovirus at low multiplicity of     

A tubular segmented-flow bioreactor for the infection of insect cells with recombinant baculovirus

A continuous process of insect cell (S f9) growth and baculovirus infection is tested with the sequential combination of a CSTR and a tubular reactor. A tubular infection reactor enables continuous introduction of baculovirus and therefore avoids the ‘passage effect’ observed in two-stage CSTR systems. Moreover, a tubular reactor can be used to test cell infection kinetics and the subsequent metabolism of infected insect cells. Unlike batch and CSTR culture, cells in a horizontally positioned tubular reactor settle due to poor mixing. We have overcome this problem by alternately introducing air bubbles and media and by maintaining a linear velocity sufficient to keep cells suspended. This article addresses the development of the tubular reactor and demonstrates its use as an infection system that complements the two-stage CSTR. This revised version was published online in July 2006 with corrections to the Cover Date.     

Kinetic Monte Carlo simulation for the striation distribution of void defects in Czochralski silicon growth

Unique crystal-originated pit (COP) distribution, similar to a striation pattern, is well matched with the oxygen profile in experimental analysis. It shows the strong relationship between oxygen concentration and COP distribution. In this paper, we study the generation of void defects and the relationship between interstitial oxygen and vacancy using the kinetic lattice Monte Carlo (KLMC) method. The KLMC method has been applied extensively in various forms to the study of micro-defects in silicon wafers. It explained well the formation of void defects such as vacancy–oxygen complex and vacancy–vacancy complex. The formation of clusters is strongly affected by oxygen concentration, which showed the relationship between COP distribution and oxygen concentration. The unique COP distribution could be correctly explained with KLMC results, and this kind of meso-scale results has not yet been reported.     

A Monte Carlo model for the internal dosimetry of choroid plexuses in nuclear medicine procedures

Choroid plexuses are vascular structures located in the brain ventricles, showing specific uptake of some diagnostic and therapeutic radiopharmaceuticals currently under clinical investigation, such as integrin-binding arginine-glycine-aspartic acid (RGD) peptides. No specific geometry for choroid plexuses has been implemented in commercially available software for internal dosimetry.The aims of the present study were to assess the dependence of absorbed dose to the choroid plexuses on the organ geometry implemented in Monte Carlo simulations, and to propose an analytical model for the internal dosimetry of these structures for ¹⁸F, ⁶⁴Cu, ⁶⁷Cu, ⁶⁸Ga, ⁹⁰Y, ¹³¹I and ¹⁷⁷Lu nuclides. A GAMOS Monte Carlo simulation based on direct organ segmentation was taken as the gold standard to validate a second simulation based on a simplified geometrical model of the choroid plexuses. Both simulations were compared with the OLINDA/EXM sphere model.The gold standard and the simplified geometrical model gave similar dosimetry results (dose difference < 3.5%), indicating that the latter can be considered as a satisfactory approximation of the real geometry. In contrast, the sphere model systematically overestimated the absorbed dose compared to both Monte Carlo models (range: 4–50% dose difference), depending on the isotope energy and organ mass. Therefore, the simplified geometric model was adopted to introduce an analytical approach for choroid plexuses dosimetry in the mass range 2–16 g. The proposed model enables the estimation of the choroid plexuses dose by a simple bi-parametric function, once the organ mass and the residence time of the radiopharmaceutical under investigation are provided.     

A Monte Carlo software bench for simulation of spectral k-edge CT imaging: Initial results

PurposeSpectral Computed Tomography (SCT) systems equipped with photon counting detectors (PCD) are clinically desired, since such systems provide not only additional diagnostic information but also radiation dose reductions by a factor of two or more. The current unavailability of clinical PCDs makes a simulation of such systems necessary.MethodsIn this paper, we present a Monte Carlo-based simulation of a SCT equipped with a PCD. The aim of this development is to facilitate research on potential clinical applications. Our MC simulator takes into account scattering interactions within the scanned object and has the ability to simulate scans with and without scatter and a wide variety of imaging parameters. To demonstrate the usefulness of such a MC simulator for development of SCT applications, a phantom with contrast targets covering a wide range of clinically significant iodine concentrations is simulated. With those simulations the impact of scatter and exposure on image quality and material decomposition results is investigated.ResultsOur results illustrate that scatter radiation plays a significant role in visual as well as quantitative results. Scatter radiation can reduce the accuracy of contrast agent concentration by up to 15%.ConclusionsWe present a reliable and robust software bench for simulation of SCTs equipped with PCDs.     

Reverse Monte Carlo Simulation: A New Technique for the Determination of Disordered Structures

Abstract

We have developed a new technique, based on the standard Monte Carlo simulation method with Markov chain sampling, in which a set of three dimensional particle configurations are generated that are consistent with the experimentally measured structure factor. A(Q), and radial distribution function, g(r), of a liquid or other disordered system. Consistency is determined by a standard χ² test using the experimental errors. No input potential is required, we present initial results for liquid argon. Since the technique can work directly from the structure factor it promises to be useful for modelling the structures of glasses or amorphous materials. It also has other advantages in multicomponent systems and as a tool for experimental data analysis.     

Study of thermodynamic properties of symmetric and asymmetric electrolyte systems in mixture with neutral components: Monte Carlo simulation results and integral equation predictions

Monte Carlo simulation is conducted to obtain the structure, excess internal energy and Helmholtz energy for systems containing charged and neutral hard spheres of comparable concentrations. The results are compared with the thermodynamic properties predicted by solving Ornstein–Zernike equation with hypernetted chain (HNC) and mean spherical approximation (MSA) closures. The HNC approximation is found to well represent the simulation results for both structure and excess energy, while the excess energy of MSA deviates from the simulation results in the intermediate- and high-density range. A simple modification of MSA, referred to as KMSA, is proposed to accurately predict the excess internal and Helmholtz energy in the studied density range. KMSA is proved to capture the effects of neutral component, size and charge asymmetry, system temperature and dielectric constant of the background solvent, on the excess energy of electrolyte systems.     

Configuration and validation of an analytical model predicting secondary neutron radiation in proton therapy using Monte Carlo simulations and experimental measurements

PurposeThis study focuses on the configuration and validation of an analytical model predicting leakage neutron doses in proton therapy.MethodsUsing Monte Carlo (MC) calculations, a facility-specific analytical model was built to reproduce out-of-field neutron doses while separately accounting for the contribution of intra-nuclear cascade, evaporation, epithermal and thermal neutrons. This model was first trained to reproduce in-water neutron absorbed doses and in-air neutron ambient dose equivalents, H*(10), calculated using MCNPX. Its capacity in predicting out-of-field doses at any position not involved in the training phase was also checked. The model was next expanded to enable a full 3D mapping of H*(10) inside the treatment room, tested in a clinically relevant configuration and finally consolidated with experimental measurements.ResultsFollowing the literature approach, the work first proved that it is possible to build a facility-specific analytical model that efficiently reproduces in-water neutron doses and in-air H*(10) values with a maximum difference less than 25%. In addition, the analytical model succeeded in predicting out-of-field neutron doses in the lateral and vertical direction. Testing the analytical model in clinical configurations proved the need to separate the contribution of internal and external neutrons. The impact of modulation width on stray neutrons was found to be easily adjustable while beam collimation remains a challenging issue. Finally, the model performance agreed with experimental measurements with satisfactory results considering measurement and simulation uncertainties.ConclusionAnalytical models represent a promising solution that substitutes for time-consuming MC calculations when assessing doses to healthy organs.     

Monte Carlo simulation for Neptun 10 PC medical linear accelerator and calculations of output factor for electron beam

AimExact knowledge of dosimetric parameters is an essential pre-requisite of an effective treatment in radiotherapy. In order to fulfill this consideration, different techniques have been used, one of which is Monte Carlo simulation.Materials and methodsThis study used the MCNP-4C^b to simulate electron beams from Neptun 10 PC medical linear accelerator. Output factors for 6, 8 and 10 MeV electrons applied to eleven different conventional fields were both measured and calculated.ResultsThe measurements were carried out by a Wellhofler-Scanditronix dose scanning system. Our findings revealed that output factors acquired by MCNP-4C simulation and the corresponding values obtained by direct measurements are in a very good agreement.ConclusionIn general, very good consistency of simulated and measured results is a good proof that the goal of this work has been accomplished.     

A Monte Carlo simulation model for studying evolution in age-structured populations

This model provides for any number of genotypes defined by age-specific survival and fecundity rates in a population with completely overlapping generations and growing under the control of density-governing functions affecting survival or fecundity. It is tested in situations involving two alleles at one locus. Nonselection populations at Hardy–Weinberg equilibrium obey the ecogenetic law; i.e., each genotype follows Lotka's law regarding rate of increase and stable age distribution as if it were an independent true-breeding population. Populations experiencing age- and density-independent selection approximate this situation, and the changes in gene frequency are predicted by relative fitnesses bases on λ, the finite rate of increase of the genotypes. Polymorphic gene equilibria occurring at steady-state population sizes are determined by fitnesses based on R, the net reproductive rate. In examples involving differences in generation time produced by age-dependent differences in fecundity, the allele associated with longer generation time may be favored or opposed by selection, depending on whether the density-governing factor controlling population size affects survival or fecundity. If such genotypes have similar R's, a genetic equilibrium may be established if the population is governed by a density function acting upon fecundity. Received: August 23, 1999 / Accepted: July 13, 2000     

Lipid droplets fusion in adipocyte differentiated 3T3-L1 cells: A Monte Carlo simulation

Several human worldwide diseases like obesity, type 2 diabetes, hepatic steatosis, atherosclerosis and other metabolic pathologies are related to the excessive accumulation of lipids in cells. Lipids accumulate in spherical cellular inclusions called lipid droplets (LDs) whose sizes range from fraction to one hundred of micrometers in adipocytes. It has been suggested that LDs can grow in size due to a fusion process by which a larger LD is obtained with spherical shape and volume equal to the sum of the progenitors’ ones. In this study, the size distribution of two populations of LDs was analyzed in immature and mature (5-days differentiated) 3T3-L1 adipocytes (first and second populations, respectively) after Oil Red O staining. A Monte Carlo simulation of interaction between LDs has been developed in order to quantify the size distribution and the number of fusion events needed to obtain the distribution of the second population size starting from the first one. Four models are presented here based on different kinds of interaction: a surface weighted interaction (R2 Model), a volume weighted interaction (R3 Model), a random interaction (Random model) and an interaction related to the place where the LDs are born (Nearest Model). The last two models mimic quite well the behavior found in the experimental data. This work represents a first step in developing numerical simulations of the LDs growth process. Due to the complex phenomena involving LDs (absorption, growth through additional neutral lipid deposition in existing droplets, de novo formation and catabolism) the study focuses on the fusion process. The results suggest that, to obtain the observed size distribution, a number of fusion events comparable with the number of LDs themselves is needed. Moreover the MC approach results a powerful tool for investigating the LDs growth process.     

Implementation and application of a Monte Carlo model for an in vivo micro computed tomography system

Micro computed tomography (µCT) scanners are used to create high-resolution images and to quantify properties of the scanned objects. While modern µCT scanners benefit from the cone beam geometry, they are compromised by scatter radiation. This work aims to develop a Monte Carlo (MC) model of a µCT scanner in order to characterize the scatter radiation in the detector plane.The EGS++ framework with the MC code EGSnrc was used to simulate the particle transport through the main components of the XtremeCT (SCANCO Medical AG, Switzerland). The developed MC model was based on specific information of the manufacturer and was validated against measurements. The primary and the scatter radiation were analyzed and by implementing a dedicated tracing method, the scatter radiation was subdivided into different scatter components.The comparisons of measured and simulated transmission values for different absorber and filter combinations result in a mean difference of 0.2% ± 1.4%, with a maximal local difference of 3.4%. The reconstructed image of the phantom based on measurements agrees well with the image reconstructed using the MC model. The local contribution of scattered radiation is up to 10% of the total radiation in the detector plane and most of the scattered particles result from interactions in the scanned object. The MC simulations show that scatter radiation contains information about the structure of the object.In conclusion, a MC model for a µCT scanner was successfully validated and applied to analyze the characteristics of the scatter radiation for a µCT scanner.     

Construction of an intermediate-resolution lattice model and re-examination of the helix-coil transition: a dynamic Monte Carlo simulation

In protein modeling, spatial resolution and computational efficiency are always incompatible. As a compromise, an intermediate-resolution lattice model has been constructed in the present work. Each residue is decomposed into four basic units, i.e. the α-carbon group, the carboxyl group, the imino group, and the side-chain group, and each basic coarse-grained unit is represented by a minimum cubic box with eight lattice sites. The spacing of the lattice is about 0.56?Å, holding the highest spatial resolution for the present lattice protein models. As the first report of this new model, the helix-coil transition of a polyalanine chain was examined via dynamic Monte Carlo simulation. The period of formed α-helix was about 3.68 residues, close to that of a natural α-helix. The resultant backbone motion was found to be in the realistic regions of the conformational space in the Ramachandran plot. Helix propagation constant and nucleation constant were further determined through the dynamic hydrogen bonding process and torsional angle variation, and the results were used to make comparison between classical Zimm-Bragg theory and Lifson-Roig theory based on the Qian-Schellman relationship. The simulation results confirmed that our lattice model can reproduce the helix-coil transition of polypeptide and construct a moderately fine α-helix conformation without significantly weakening the priority in efficiency for a lattice model.     

A grand canonical Monte Carlo simulation study of argon and krypton confined inside weakly attractive slit pores

Grand canonical Monte Carlo simulations are performed to investigate the adsorption of argon and krypton inside weakly attractive slit pores. We examine the effects of confinement on these monoatomic fluids (modelled using the triangle-well potential) in a hard wall slit pore as also when the pore-fluid interactions are uniformly and weakly attractive. The effects of temperature and pressure on the adsorption isotherms of these confined fluids are found to be the same as those reported in literature. The equilibrium density profiles for argon and krypton exhibit both uniform distribution and layering under different conditions. In addition, for krypton, under specific conditions inside the narrow pores, we note the development of frustrated layering.     

Assessment of skin dose in breast cancer radiotherapy: on-phantom measurement and Monte Carlo simulation

AimThe main purpose of the present study is assessment of skin dose in breast cancer radiotherapy.BackgroundAccurate assessment of skin dose in radiotherapy can provide useful information for clinical considerations.Materials and methodsA RANDO phantom was irradiated using a 6 MV Siemens Primus linac with medial and tangential radiotherapy fields for simulating breast cancer treatment. Dosimetry was also performed on various positions across the fields using an EBT3 radiochromic film. Similar conditions of measurement on the RANDO phantom including field size, irradiation angle, number of fields, etc. were subsequently simulated via the Monte Carlo N-Particle Transport code (MCNP). Ultimately, dose values for corresponding points from both methods were compared.ResultsConsidering dosimetry using radiochromic films on the RANDO phantom, there were points having underdose and overdose based on the prescribed dose and skin tolerance levels. In this respect, 81.25% and 18.75% of the points had underdose and overdose, respectively. In some cases, several differences were observed between the measurement and the MCNP simulation results associated with skin dose.ConclusionBased on the results of the points which had underdose, it was suggested that a bolus should be used for the given points. With regard to overdose points, it was advocated to consider skin tolerance dose in treatment planning. Differences between the measurement and the MCNP simulation results might be due to voxel size of tally cells in simulations, effect of beam’s angle of incidence, validation time of linac’s head, lack of electronic equilibrium in the build-up region, as well as MCNP tally type.     

A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. II. A simulation study

A Bayesian approach to the statistical mapping of Quantitative Trait Loci (QTLs) using single markers was implemented via Markov Chain Monte Carlo (MCMC) algorithms for parameter estimation and hypothesis testing. Parameters were estimated by marginal posterior means computed with a Gibbs sampler with data augmentation. Variables sampled included the augmented data (marker-QTL genotypes, polygenic effects), the event of linkage or nonlinkage, and the parameters (allele frequencies, QTL substitution effect, recombination rate, polygenic and residual variances). The analysis was evaluated empirically via application to simulated granddaughter designs consisting of 2000 sons, 20 related sires and their ancestors. Results obtained in this study and preliminary work on multiple linked markers and multiple QTLs support the usefulness of the Bayesian method for the statistical mapping of QTLs.     

Modeling the population dynamics of baculovirus-infected insect cells: Optimizing infection strategies for enhanced recombinant protein yields

The insect cell-baculovirus model presented here is capable of simulating cell population dynamics, extracellular virion densities, and heterologous product titers in reasonable agreement with experimental data for a wide rang of multiplicities of infection (MOI) and times of infection. The model accounts for the infection of a single cell by multiple virions and the consequences on the time course of infection. The probability of infection by more than one virion was approximated using the Poisson distribution, which proved to be a refinement over second-order kinetics. The model tracks initiation and duration of important events in the progression of infected cell development (virus replication, recombinant protein synthesis, and cell lysis) for subpopulations delineated by the time and extent of their initial infection. The model suggests infection strategies, weighing the importance of MOI and infection time. Maximum product titers result from infection in the early exponential growth phase with low MOI.