Quantifying the Effect of Polymer Blending through Molecular Modelling of Cyanurate Polymers

Modification of polymer properties by blending is a common practice in the polymer industry. We report here a study of blends of cyanurate polymers by molecular modelling that shows that the final experimentally determined properties can be predicted from first principles modelling to a good degree of accuracy. There is always a compromise between simulation length, accuracy and speed of prediction. A comparison of simulation times shows that 125ps of molecular dynamics simulation at each temperature provides the optimum compromise for models of this size with current technology. This study opens up the possibility of computer aided design of polymer blends with desired physical and mechanical properties.     

Computational wear prediction of artificial knee joints based on a new wear law and formulation

Laboratory joint wear simulator testing has become the standard means for preclinical evaluation of wear resistance of artificial knee joints. Recent simulator designs have been advanced and become successful at reproducing the wear patterns observed in clinical retrievals. However, a single simulator test can be very expensive and take a long time to run. On the other hand computational wear modelling is an alternative attractive solution to these limitations. Computational models have been used extensively for wear prediction and optimisation of artificial knee designs. However, all these models have adopted the classical Archard's wear law, which was developed for metallic materials, and have selected wear factors arbitrarily. It is known that such an approach is not generally true for polymeric bearing materials and is difficult to implement due to the high dependence of the wear factor on the contact pressure. Therefore, these studies are generally not independent and lack general predictability. The objective of the present study was to develop a new computational wear model for the knee implants, based on the contact area and an independent experimentally determined non-dimensional wear coefficient. The effects of cross-shear and creep on wear predictions were also considered. The predicted wear volume was compared with the laboratory simulation measurements. The model was run under two different kinematic inputs and two different insert designs with curved and custom designed flat bearing surfaces. The new wear model was shown to be capable of predicting the difference of the wear volume and wear pattern between the two kinematic inputs and the two tibial insert designs. Conversely, the wear factor based approach did not predict such differences. The good agreement found between the computational and experimental results, on both the wear scar areas and volumetric wear rates, suggests that the computational wear modelling based on the new wear law and the experimentally calculated non-dimensional wear coefficient should be more reliable and therefore provide a more robust virtual modelling platform.     

The SBML discrete stochastic models test suite

MOTIVATION: Stochastic simulation is a very important tool for mathematical modelling. However, it is difficult to check the correctness of a stochastic simulator, since any two realizations from a single model will typically be different. RESULTS: We have developed a test suite of stochastic models that have been solved either analytically or using numerical methods. This allows the accuracy of stochastic simulators to be tested against known results. The test suite is already being used by a number of stochastic simulator developers. AVAILABILITY: The latest version of the test suite can be obtained from http://www.calibayes.ncl.ac.uk/Resources/dsmts/ and is licensed under GNU Lesser General Public License.     

Modelling food web complexity: The consequences of individual-based, spatially explicit behavioural ecology on trophic interactions

We present a prototype simulator that enables one to explore the influence of individual behaviour on the dynamics and structural complexity of food webs. In the simulations, individuals act according to simple, biologically plausible rules in a spatially explicit setting. We present the results of a series of simulation experiments on artificial, tri-trophic level food chains used to calibrate the simulator against real-world systems and to demonstrate the simulators promise for ecological modelling. Our primary objective was to discover the biological features leading to stability of artificial food chains over ecological time and under different conditions of trophic efficiency. This involved a qualitative analysis of food chains comprised of a plant, a herbivore and a carnivore species. We explored the consequences of allowing individual heterotrophs to make active choices about resource selection (perception and intentional behaviour) under high and low degrees of trophic efficiency. We found that individuals had to adopt realistic behavioural ecological strategies, such as active resource selection, for systems to persist, especially under conditions in which trophic efficiencies were of the magnitude observed in real systems (e.g. 10%). Our results reaffirm previous convictions that a better understanding of food web interactions in real-world systems will require approaches that blend animal behavioural ecology with population and community ecology. However, the evidence comes from a new mathematical perspective.     

An efficient approach to collaborative simulation of variable structure systems on multi-core machines

Complex variable-structure systems (CVSSs) are a common type of complex systems that exhibit changes both at structural and behavior levels. Simulations of CVSSs challenge current collaborative execution methods with increasingly big and complex models. The emergence of multi-core paradigm presents an exciting opportunity to address such challenge, so an advanced parallel simulator under multi-core environments is proposed. The simulator: (1) provides thread simulation kernels and five kinds of management services to support dynamic model structure flexibly; (2) can explore both inherent and dynamic parallelism among models based on interaction relations, and employ the multi-thread paradigm to gain good speedup; (3) adopts an efficient dynamic load-balancing method, which can migrate models among cores with very low cost and support dynamic core allocation on demand, to address evident load-imbalance problems brought by variable-structure. The experiments show that structure changes can be supported while up to 23 % performance increase can be gained.     

Analysis of the influence of modelling assumptions on the prediction of the elastic properties of cardiac fibres

Abstract

Although several numerical models of the human heart have been proposed in the literature, there are still several discrepancies among the results predicted by each model. These discrepancies can be attributed to the fact that each model has a number of assumptions and simplifications, which can limit the scope and precision of the numerical predictions obtained. Moreover, none of the works reported in the literature have assessed the influence of modelling assumptions on the predicted cardiac fiber elastic properties. In this paper a new passive mechanical model that combines the left ventricular (LV) pressure–volume in-vivo measurements with an indirect approach based on the finite element method (FEM), is proposed and used to analyze the influence of different modelling assumptions on the estimated elastic properties of the cardiac fiber. This analysis is carried out by varying modelling assumptions that are common to existing passive mechanical models. The results have shown that although the different modelling assumptions have a significant effect on the predicted value of the fiber elastic properties, they tend to lead to the same results. This suggests that simplified passive numerical models in combination with adjustment factors, are valid in comparison with more refined and complex LV passive models.     

Development of computational wear simulation of metal-on-metal hip resurfacing replacements

As one of the alternatives to traditional metal-on-polyethylene total hip replacements, metal-on-metal hip resurfacing prostheses demonstrating lower wear have been introduced for younger and more active patients during the past decade. However, in vitro hip simulator testing for the predicted increased lifetime of these surface replacements is time-consuming and costly. Computational wear modelling based on the Archard wear equation and finite element contact analysis was developed in this study for artificial hip joints and particularly applied to metal-on-metal resurfacing bearings under simulator testing conditions to address this issue. Wear factors associated with the Archard wear equation were experimentally determined and based on the short-term hip simulator wear results. The computational wear simulation was further extended to a long-term evaluation up to 50 million cycles assuming that the wear rate stays constant. The prediction from the computational model shows good agreement with the corresponding simulator study in terms of volumetric wear and the wear geometry. The simulation shows the progression of linear wear penetrations, and the complexity of contact stress distribution on the worn bearing surfaces. After 50 million cycles, the maximum linear wear was predicted to be approximately 6 and 8 microm for the cup and head, respectively, and no edge contact was found.     

Individual-based modelling of bacterial ecologies and evolution

This paper presents two approaches to the individual-based modelling of bacterial ecologies and evolution using computational tools. The first approach is a fine-grained model that is based on networks of interactivity between computational objects representing genes and proteins. The second approach is a coarser-grained, agent-based model, which is designed to explore the evolvability of adaptive behavioural strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of these computational models is discussed, and some results from simulation experiments are presented. Finally, the potential applications of the proposed models to the solution of real-world computational problems, and their use in improving our understanding of the mechanisms of evolution, are briefly outlined.     

Modelling a wireless connected swarm of mobile robots

It is a characteristic of swarm robotics that modelling the overall swarm behaviour in terms of the low-level behaviours of individual robots is very difficult. Yet if swarm robotics is to make the transition from the laboratory to real-world engineering realisation such models would be critical for both overall validation of algorithm correctness and detailed parameter optimisation. We seek models with predictive power: models that allow us to determine the effect of modifying parameters in individual robots on the overall swarm behaviour. This paper presents results from a study to apply the probabilistic modelling approach to a class of wireless connected swarms operating in unbounded environments. The paper proposes a probabilistic finite state machine (PFSM) that describes the network connectivity and overall macroscopic behaviour of the swarm, then develops a novel robot-centric approach to the estimation of the state transition probabilities within the PFSM. Using measured data from simulation the paper then carefully validates the PFSM model step by step, allowing us to assess the accuracy and hence the utility of the model.     

Disulfide trapping of protein complexes on the yeast surface

Protein complexes are common in nature and play important roles in biology, but studying the quaternary structure formation in vitro is challenging since it involves lengthy and expensive biochemical steps. There are frequent technical difficulties as well with the sensitivity and resolution of the assays. In this regard, a technique that can analyze protein–protein interactions in high throughput would be a useful experimental tool. Here, we introduce a combination of yeast display and disulfide trapping that we refer to as stabilization of transient and unstable complexes by engineered disulfide (STUCKED) that can be used to detect the formation of a broad spectrum of protein complexes on the yeast surface using fluorescence labeling. The technique uses an engineered intersubunit disulfide to covalently crosslink the subunits of a complex, so that the disulfide‐trapped complex can be displayed on the yeast surface for detection and analysis. Transient protein complexes are difficult to display on the yeast surface, since they may dissociate before they can be detected due to a long induction period in yeast. To this end, we show that three different quaternary structures with the subunit dissociation constant K_d ～ 0.5–20 µM, the antibody variable domain (Fv), the IL‐8 dimer, and the p53–MDM2 complex, cannot be displayed on the yeast surface as a noncovalent complex. However, when we introduce an interchain disulfide between the subunits, all three systems are efficiently displayed on the yeast surface, showing that disulfide trapping can help display protein complexes that cannot be displayed otherwise. We also demonstrate that a disulfide forms only between the subunits that interact specifically, the displayed complexes exhibit functional characteristics that are expected of wt proteins, the mutations that decrease the affinity of subunit interaction also reduce the display efficiency, and most of the disulfide stabilized complexes are formed within the secretory pathway during export to the surface. Disulfide crosslinking is therefore a convenient way to study weak protein association in the context of yeast display. Biotechnol. Bioeng. 2010; 106: 27–41. © 2009 Wiley Periodicals, Inc.     

Flocculation in brewing yeasts: a computer simulation study

A new simulator, INDISIM-FLOC, based on the individual-based simulator INDISIM, is used to examine the predictions of two different models of yeast flocculation. The first, proposed by Calleja is known as the "addition" model. The second, proposed by Stratford is known as the "cascade" model. The simulations show that the latter exhibits a better qualitative agreement with available experimental data.     

Minireview: Characterization of the Yeast Mitochondria Unselective Channel: A Counterpart to the Mammalian Permeability Transition Pore?

Large and unselective permeabilities through the inner membrane of yeast mitochondria have been observed for more than 20 years, but the characterization of these permeabilities, leading to hypothesize the existence of a large-conductance unselective channel in yeast inner mitochondrial membrane, was done only recently by several groups. This channel has been tentatively identified as a yeast counterpart to the mammalian permeability transition pore, the crucial role of which is now well-documented in physiopathological phenomena, such as Ca²⁺ homeostasis, ischemic damages, or programmed cell death. The aim of this review is to make a point on the known characteristics of this yeast mitochondrial unselective channel (YMUC) and to analyze whether or not it can be considered as a yeast permeability transition pore.     

Reconstitution of fibroblast growth factor receptor interactions in the yeast two hybrid system

Fibroblast growth factors (FGF) activate their receptors through the formation of trimolecular complexes, composed of a ligand, a receptor, and a heparan sulfate oligosaccharide, all of which are members of particularly large families capable of multiple interactions in a combinatorial fashion. Understanding this large network of interactions not only presents a great challenge, but is practically beyond the capacity of most classical techniques routinely used to study ligand receptor interactions. We have used the yeast two hybrid system to study protein-protein interaction in the FGF family. Both ligand and receptor ectodomains are properly folded and functional in the yeast. Basic FGF (bFGF) expressed in the yeast dimerizes spontaneously. This self-assembly occurs at low affinity, which can be greatly enhanced by the introduction of heparin, supporting a defined role for heparin in bFGF dimerization. Screening a rat embryo cDNA library with bFGF in the yeast two hybrid system identified a short variant of FGF receptor 1, found most frequently in embryonal and tumor cells and which possesses affinity toward bFGF that is significantly greater than that of the more abundant, full-length receptor. We find the yeast two hybrid system, a most suitable alternative method for the analysis of growth factor-receptor interactions as well as for screening for novel interacting proteins and modulators of FGF and its receptors.     

A novel approach for pilot error detection using Dynamic Bayesian Networks

In the last decade Dynamic Bayesian Networks (DBNs) have become one type of the most attractive probabilistic modelling framework extensions of Bayesian Networks (BNs) for working under uncertainties from a temporal perspective. Despite this popularity not many researchers have attempted to study the use of these networks in anomaly detection or the implications of data anomalies on the outcome of such models. An abnormal change in the modelled environment’s data at a given time, will cause a trailing chain effect on data of all related environment variables in current and consecutive time slices. Albeit this effect fades with time, it still can have an ill effect on the outcome of such models. In this paper we propose an algorithm for pilot error detection, using DBNs as the modelling framework for learning and detecting anomalous data. We base our experiments on the actions of an aircraft pilot, and a flight simulator is created for running the experiments. The proposed anomaly detection algorithm has achieved good results in detecting pilot errors and effects on the whole system.     

Homology modelling and spectroscopy, a never-ending love story

Homology modelling is normally the technique of choice when experimental structure data are not available but three-dimensional coordinates are needed, for example, to aid with detailed interpretation of results of spectroscopic studies. Herein, the state of the art of homology modelling will be described in the light of a series of recent developments, and an overview will be given of the problems and opportunities encountered in this field. The major topic, the accuracy and precision of homology models, will be discussed extensively due to its influence on the reliability of conclusions drawn from the combination of homology models and spectroscopic data. Three real-world examples will illustrate how both homology modelling and spectroscopy can be beneficial for (bio)medical research.     

Random AT library: autonomously replicating sequence (ARS) activity of chemically synthesized random sequences for transformation of nonconventional yeast species

In a search for sequences that confer on bacterial plasmids the capacity of autonomous replication in yeast cells, we chemically synthesized polynucleotides 80 bp in length from an equimolar mixture of A and T. The random AT-polymer population, W80, was inserted into the plasmid YIp5-Kan1 (which carries the markers URA3 and G418(R), but does not replicate in yeast) and amplified in Escherichia coli. This library, representing 10 000 different AT sequences, was transformed into three species of yeast: Saccharomyces cerevisiae, Kluyveromyces lactis and Torulaspora delbrueckii. The aim was to evaluate the frequency, if any, of autonomously replicating sequences (ARSs) in the random sequences. A large number of transformants were obtained from each species. Many of them showed a stable transformed phenotype. Several W80 sequences were found many times for a given species, suggesting that each species preferred particular sequences for ARS function, although they are diverse in their primary sequence. In view of the high frequency and stability of the replicative plasmids found in the different hosts, this small random AT library may be conveniently used as a source of replicative gene vectors for genetic manipulation of many nonconventional yeast species, in place of searching for species-specific chromosomal ARSs.     

自絮凝颗粒酵母乙醇连续发酵耦合酵母回用工艺的研究

模拟现有酒精发酵行业普遍采用的多级发酵罐串联系统,建立了一套由三级串联操作的搅拌式发酵罐和两个沉降罐组成的反应器系统,以脱胚脱皮玉米粉双酶法制备的糖化液为发酵底物,培养基初始还原糖浓度为220g/L,添加(NH4)2HPO41.5g/L和KH2PO42.5g/L,以0.057h-1的恒定稀释速率流加,将自沉降浓缩后的酵母乳先后经活化和不活化两种方式处理并循环至第一级发酵罐,系统在两种操作条件下分别达到了拟稳态。实验结果表明活化处理对改善发酵工艺技术指标方面发挥了显著的作用,发酵终点乙醇浓度达到101g/L,还原糖和残总糖分别在3.2和7.7g/L左右,发酵系统的设备生产强度指标为5.77g/(L.h),与无酵母回用的搅拌式反应器系统中自絮凝颗粒酵母乙醇发酵工艺相比,提高了70%。