Displaying publications 1 - 20 of 347 in total

  1. Abdul Latif NS, Wake GC, Reglinski T, Elmer PA
    J. Theor. Biol., 2014 Apr 21;347:144-50.
    PMID: 24398025 DOI: 10.1016/j.jtbi.2013.12.023
    Plant disease control has traditionally relied heavily on the use of agrochemicals despite their potentially negative impact on the environment. An alternative strategy is that of induced resistance (IR). However, while IR has proven effective in controlled environments, it has shown variable field efficacy, thus raising questions about its potential for disease management in a given crop. Mathematical modelling of IR assists researchers with understanding the dynamics of the phenomenon in a given plant cohort against a selected disease-causing pathogen. Here, a prototype mathematical model of IR promoted by a chemical elicitor is proposed and analysed. Standard epidemiological models describe that, under appropriate environmental conditions, Susceptible plants (S) may become Diseased (D) upon exposure to a compatible pathogen or are able to Resist the infection (R) via basal host defence mechanisms. The application of an elicitor enhances the basal defence response thereby affecting the relative proportion of plants in each of the S, R and D compartments. IR is a transient response and is modelled using reversible processes to describe the temporal evolution of the compartments. Over time, plants can move between these compartments. For example, a plant in the R-compartment can move into the S-compartment and can then become diseased. Once in the D-compartment, however, it is assumed that there is no recovery. The terms in the equations are identified using established principles governing disease transmission and this introduces parameters which are determined by matching data to the model using computer-based algorithms. These then give the best match of the model with experimental data. The model predicts the relative proportion of plants in each compartment and quantitatively estimates elicitor effectiveness. An illustrative case study will be given; however, the model is generic and will be applicable for a range of plant-pathogen-elicitor scenarios.
    Matched MeSH terms: Models, Biological*
  2. Tee SH
    PMID: 30594412 DOI: 10.1016/j.shpsc.2018.12.001
    It is commonly held that in vivo biological experimental models are concrete and non-fictional. This belief is primarily supported by the fact that in vivo studies involve biological models which are alive, and what is alive cannot be fictional. However, I argue that this is not always the case. The design of an experimental model could still render an in vivo model fictional because fictional elements and processes can be built into these in vivo experimental models. These fictional elements are essential parts of a credentialed fiction because the designs of in vivo experimental models are constrained by imaginability, conceivability, and credit-worthiness. Therefore, despite its fictionality, it is credible for an in vivo experimental model to stand in for the phenomenon of interest.
    Matched MeSH terms: Models, Biological*
  3. Mukhamedov F, Izzat Qaralleh, Wan Nur Fairuz Alwani Wan Rozali
    Sains Malaysiana, 2014;43:1275-1281.
    A quadratic stochastic operator (Qso) is usually used to present the time evolution of differing species in biology. Some quadratic stochastic operators have been studied by Lotka and Volterra. The general problem in the nonlinear operator theory is to study the behavior of operators. This problem was not fully finished even for quadratic stochastic operators which are the simplest nonlinear operators. To study this problem, several classes of QSO were investigated. In this paper, we study the fri)-Qso defined on 2D simplex. We first classify 4-(a)-QS0 into 2 non-conjugate classes. Further, we investigate the dynamics of these classes of such operators.
    Matched MeSH terms: Models, Biological
  4. Chan JY, Ooi EH
    Cryobiology, 2016 12;73(3):304-315.
    PMID: 27789380 DOI: 10.1016/j.cryobiol.2016.10.006
    Advancement in biomedical simulation and imaging modality have catalysed the development of in silico predictive models for cryoablation. However, one of the main challenges in ensuring the accuracy of the model prediction is the use of proper thermal and biophysical properties of the patient. These properties are difficult to measure clinically and thus, represent significant uncertainty that can affect the model prediction. Motivated by this, a sensitivity analysis is carried out to identify the model parameters that have the most significant impact on the lesion size during cryoablation. The study is initially carried out using the Morris method to screen for the most dominant parameters. Once determined, analysis of variance (ANOVA) is performed to quantitatively rank the order of importance of each parameter and their interactions. Results from the sensitivity analysis revealed that blood perfusion, water transport and ice nucleation parameters are critical in predicting the lesion size, suggesting that the acquisition of these parameters should be prioritised to ensure the accuracy of the model prediction.
    Matched MeSH terms: Models, Biological*
  5. Alias MA, Buenzli PR
    Biophys. J., 2017 Jan 10;112(1):193-204.
    PMID: 28076811 DOI: 10.1016/j.bpj.2016.11.3203
    The growth of several biological tissues is known to be controlled in part by local geometrical features, such as the curvature of the tissue interface. This control leads to changes in tissue shape that in turn can affect the tissue's evolution. Understanding the cellular basis of this control is highly significant for bioscaffold tissue engineering, the evolution of bone microarchitecture, wound healing, and tumor growth. Although previous models have proposed geometrical relationships between tissue growth and curvature, the role of cell density and cell vigor remains poorly understood. We propose a cell-based mathematical model of tissue growth to investigate the systematic influence of curvature on the collective crowding or spreading of tissue-synthesizing cells induced by changes in local tissue surface area during the motion of the interface. Depending on the strength of diffusive damping, the model exhibits complex growth patterns such as undulating motion, efficient smoothing of irregularities, and the generation of cusps. We compare this model with in vitro experiments of tissue deposition in bioscaffolds of different geometries. By including the depletion of active cells, the model is able to capture both smoothing of initial substrate geometry and tissue deposition slowdown as observed experimentally.
    Matched MeSH terms: Models, Biological*
  6. Thompson MS, Bajuri MN, Khayyeri H, Isaksson H
    Proc Inst Mech Eng H, 2017 May;231(5):369-377.
    PMID: 28427319 DOI: 10.1177/0954411917692010
    Tendons are adapted to carry large, repeated loads and are clinically important for the maintenance of musculoskeletal health in an increasing, actively ageing population, as well as in elite athletes. Tendons are known to adapt to mechanical loading. Also, their healing and disease processes are highly sensitive to mechanical load. Computational modelling approaches developed to capture this mechanobiological adaptation in tendons and other tissues have successfully addressed many important scientific and clinical issues. The aim of this review is to identify techniques and approaches that could be further developed to address tendon-related problems. Biomechanical models are identified that capture the multi-level aspects of tendon mechanics. Continuum whole tendon models, both phenomenological and microstructurally motivated, are important to estimate forces during locomotion activities. Fibril-level microstructural models are documented that can use these estimated forces to detail local mechanical parameters relevant to cell mechanotransduction. Cell-level models able to predict the response to such parameters are also described. A selection of updatable mechanobiological models is presented. These use mechanical signals, often continuum tissue level, along with rules for tissue change and have been applied successfully in many tissues to predict in vivo and in vitro outcomes. Signals may include scalars derived from the stress or strain tensors, or in poroelasticity also fluid velocity, while adaptation may be represented by changes to elastic modulus, permeability, fibril density or orientation. So far, only simple analytical approaches have been applied to tendon mechanobiology. With the development of sophisticated computational mechanobiological models in parallel with reporting more quantitative data from in vivo or clinical mechanobiological studies, for example, appropriate imaging, biochemical and histological data, this field offers huge potential for future development towards clinical applications.
    Matched MeSH terms: Models, Biological*
  7. Nasser AB, Zamli KZ, Alsewari AA, Ahmed BS
    PLoS ONE, 2018;13(5):e0195187.
    PMID: 29718918 DOI: 10.1371/journal.pone.0195187
    The application of meta-heuristic algorithms for t-way testing has recently become prevalent. Consequently, many useful meta-heuristic algorithms have been developed on the basis of the implementation of t-way strategies (where t indicates the interaction strength). Mixed results have been reported in the literature to highlight the fact that no single strategy appears to be superior compared with other configurations. The hybridization of two or more algorithms can enhance the overall search capabilities, that is, by compensating the limitation of one algorithm with the strength of others. Thus, hybrid variants of the flower pollination algorithm (FPA) are proposed in the current work. Four hybrid variants of FPA are considered by combining FPA with other algorithmic components. The experimental results demonstrate that FPA hybrids overcome the problems of slow convergence in the original FPA and offers statistically superior performance compared with existing t-way strategies in terms of test suite size.
    Matched MeSH terms: Models, Biological*
  8. Chew WX, Kaizu K, Watabe M, Muniandy SV, Takahashi K, Arjunan SNV
    Phys Rev E, 2019 Apr;99(4-1):042411.
    PMID: 31108654 DOI: 10.1103/PhysRevE.99.042411
    Microscopic models of reaction-diffusion processes on the cell membrane can link local spatiotemporal effects to macroscopic self-organized patterns often observed on the membrane. Simulation schemes based on the microscopic lattice method (MLM) can model these processes at the microscopic scale by tracking individual molecules, represented as hard spheres, on fine lattice voxels. Although MLM is simple to implement and is generally less computationally demanding than off-lattice approaches, its accuracy and consistency in modeling surface reactions have not been fully verified. Using the Spatiocyte scheme, we study the accuracy of MLM in diffusion-influenced surface reactions. We derive the lattice-based bimolecular association rates for two-dimensional (2D) surface-surface reaction and one-dimensional (1D) volume-surface adsorption according to the Smoluchowski-Collins-Kimball model and random walk theory. We match the time-dependent rates on lattice with off-lattice counterparts to obtain the correct expressions for MLM parameters in terms of physical constants. The expressions indicate that the voxel size needs to be at least 0.6% larger than the molecule to accurately simulate surface reactions on triangular lattice. On square lattice, the minimum voxel size should be even larger, at 5%. We also demonstrate the ability of MLM-based schemes such as Spatiocyte to simulate a reaction-diffusion model that involves all dimensions: three-dimensional (3D) diffusion in the cytoplasm, 2D diffusion on the cell membrane, and 1D cytoplasm-membrane adsorption. With the model, we examine the contribution of the 2D reaction pathway to the overall reaction rate at different reactant diffusivity, reactivity, and concentrations.
    Matched MeSH terms: Models, Biological*
  9. Jabaraj DJ
    Ann Biomed Eng, 2020 Jan;48(1):393-402.
    PMID: 31531790 DOI: 10.1007/s10439-019-02356-4
    We examine the low-frequency limit of hearing of the mammalian ear through the analytical modelling of the natural frequency of the tympanic membrane. The resulting equation of the natural frequency of the modelled tympanic membrane is numerically verified against previous theoretical studies, and is statistically validated against the experimental data on the low-frequency limit of hearing. By utilizing the Wilcoxon signed-rank test; W-values of 29 (p value = 0.25014) and 23 (p value = 0.11642) are respectively obtained for the 0.2% and 0.3% prestrain (at 5% significance level for sample size of 13). We fail to reject the null hypothesis as the W-values are within the critical values of the test statistics, and therefore conclude that the tympanic membrane acts as a low-frequency limiter of acoustic stimulus. Based on our study, we can predict the low-frequency limit of hearing in mammals (e.g., for the whale as 3.6 Hz and for the zebra as 44.0 Hz).
    Matched MeSH terms: Models, Biological*
  10. Lim WL, Wibowo A, Desa MI, Haron H
    Comput Intell Neurosci, 2016;2016:5803893.
    PMID: 26819585 DOI: 10.1155/2016/5803893
    The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them.
    Matched MeSH terms: Models, Biological*
  11. Saad N, Abdeshahian P, Kalil MS, Yusoff WM, Hamid AA
    ScientificWorldJournal, 2014;2014:280146.
    PMID: 25610901 DOI: 10.1155/2014/280146
    The locally isolated filamentous fungus Cunninghamella bainieri 2A1 was cultivated in a 5 L bioreactor to produce lipid and gamma-linolenic acid (GLA). The optimization was carried out using response surface methodology based on a central composite design. A statistical model, second-order polynomial model, was adjusted to the experimental data to evaluate the effect of key operating variables, including aeration rate and agitation speed on lipid production. Process analysis showed that linear and quadratic effect of agitation intensity significantly influenced lipid production process (P < 0.01). The quadratic model also indicated that the interaction between aeration rate and agitation speed had a highly significant effect on lipid production (P < 0.01). Experimental results showed that a lipid content of 38.71% was produced in optimum conditions using an airflow rate and agitation speed of 0.32 vvm and 599 rpm, respectively. Similar results revealed that 0.058(g/g) gamma-linolenic acid was produced in optimum conditions where 1.0 vvm aeration rate and 441.45 rpm agitation rate were used. The regression model confirmed that aeration and agitation were of prime importance for optimum production of lipid in the bioreactor.
    Matched MeSH terms: Models, Biological*
  12. Fayle TM, Eggleton P, Manica A, Yusah KM, Foster WA
    Ecol. Lett., 2015 Mar;18(3):254-62.
    PMID: 25622647 DOI: 10.1111/ele.12403
    Understanding how species assemble into communities is a key goal in ecology. However, assembly rules are rarely tested experimentally, and their ability to shape real communities is poorly known. We surveyed a diverse community of epiphyte-dwelling ants and found that similar-sized species co-occurred less often than expected. Laboratory experiments demonstrated that invasion was discouraged by the presence of similarly sized resident species. The size difference for which invasion was less likely was the same as that for which wild species exhibited reduced co-occurrence. Finally we explored whether our experimentally derived assembly rules could simulate realistic communities. Communities simulated using size-based species assembly exhibited diversities closer to wild communities than those simulated using size-independent assembly, with results being sensitive to the combination of rules employed. Hence, species segregation in the wild can be driven by competitive species assembly, and this process is sufficient to generate observed species abundance distributions for tropical epiphyte-dwelling ants.
    Matched MeSH terms: Models, Biological*
  13. Ismail MA, Deris S, Mohamad MS, Abdullah A
    PLoS ONE, 2015;10(5):e0126199.
    PMID: 25961295 DOI: 10.1371/journal.pone.0126199
    This paper presents an in silico optimization method of metabolic pathway production. The metabolic pathway can be represented by a mathematical model known as the generalized mass action model, which leads to a complex nonlinear equations system. The optimization process becomes difficult when steady state and the constraints of the components in the metabolic pathway are involved. To deal with this situation, this paper presents an in silico optimization method, namely the Newton Cooperative Genetic Algorithm (NCGA). The NCGA used Newton method in dealing with the metabolic pathway, and then integrated genetic algorithm and cooperative co-evolutionary algorithm. The proposed method was experimentally applied on the benchmark metabolic pathways, and the results showed that the NCGA achieved better results compared to the existing methods.
    Matched MeSH terms: Models, Biological*
  14. Aliaga IJ, Vera V, De Paz JF, García AE, Mohamad MS
    Biomed Res Int, 2015;2015:540306.
    PMID: 25866792 DOI: 10.1155/2015/540306
    The lifespan of dental restorations is limited. Longevity depends on the material used and the different characteristics of the dental piece. However, it is not always the case that the best and longest lasting material is used since patients may prefer different treatments according to how noticeable the material is. Over the last 100 years, the most commonly used material has been silver amalgam, which, while very durable, is somewhat aesthetically displeasing. Our study is based on the collection of data from the charts, notes, and radiographic information of restorative treatments performed by Dr. Vera in 1993, the analysis of the information by computer artificial intelligence to determine the most appropriate restoration, and the monitoring of the evolution of the dental restoration. The data will be treated confidentially according to the Organic Law 15/1999 on 13 December on the Protection of Personal Data. This paper also presents a clustering technique capable of identifying the most significant cases with which to instantiate the case-base. In order to classify the cases, a mixture of experts is used which incorporates a Bayesian network and a multilayer perceptron; the combination of both classifiers is performed with a neural network.
    Matched MeSH terms: Models, Biological*
  15. Waran V, Narayanan V, Karuppiah R, Thambynayagam HC, Muthusamy KA, Rahman ZA, et al.
    Simul Healthc, 2015 Feb;10(1):43-8.
    PMID: 25514588 DOI: 10.1097/SIH.0000000000000060
    Training in intraventricular endoscopy is particularly challenging because the volume of cases is relatively small and the techniques involved are unlike those usually used in conventional neurosurgery. Present training models are inadequate for various reasons. Using 3-dimensional (3D) printing techniques, models with pathology can be created using actual patient's imaging data. This technical article introduces a new training model based on a patient with hydrocephalus secondary to a pineal tumour, enabling the models to be used to simulate third ventriculostomies and pineal biopsies.
    Matched MeSH terms: Models, Biological*
  16. Imai N, White MT, Ghani AC, Drakeley CJ
    PLoS Negl Trop Dis, 2014 Jul;8(7):e2978.
    PMID: 25058400 DOI: 10.1371/journal.pntd.0002978
    INTRODUCTION: Plasmodium knowlesi is now recognised as a leading cause of malaria in Malaysia. As humans come into increasing contact with the reservoir host (long-tailed macaques) as a consequence of deforestation, assessing the potential for a shift from zoonotic to sustained P. knowlesi transmission between humans is critical.

    METHODS: A multi-host, multi-site transmission model was developed, taking into account the three areas (forest, farm, and village) where transmission is thought to occur. Latin hypercube sampling of model parameters was used to identify parameter sets consistent with possible prevalence in macaques and humans inferred from observed data. We then explore the consequences of increasing human-macaque contact in the farm, the likely impact of rapid treatment, and the use of long-lasting insecticide-treated nets (LLINs) in preventing wider spread of this emerging infection.

    RESULTS: Identified model parameters were consistent with transmission being sustained by the macaques with spill over infections into the human population and with high overall basic reproduction numbers (up to 2267). The extent to which macaques forage in the farms had a non-linear relationship with human infection prevalence, the highest prevalence occurring when macaques forage in the farms but return frequently to the forest where they experience higher contact with vectors and hence sustain transmission. Only one of 1,046 parameter sets was consistent with sustained human-to-human transmission in the absence of macaques, although with a low human reproduction number (R(0H) = 1.04). Simulations showed LLINs and rapid treatment provide personal protection to humans with maximal estimated reductions in human prevalence of 42% and 95%, respectively.

    CONCLUSION: This model simulates conditions where P. knowlesi transmission may occur and the potential impact of control measures. Predictions suggest that conventional control measures are sufficient at reducing the risk of infection in humans, but they must be actively implemented if P. knowlesi is to be controlled.

    Matched MeSH terms: Models, Biological*
  17. Saat MN, Annuar MS, Alias Z, Chuan LT, Chisti Y
    Bioprocess Biosyst Eng, 2014 May;37(5):765-75.
    PMID: 24005762 DOI: 10.1007/s00449-013-1046-8
    Production of extracellular laccase by the white-rot fungus Pycnoporus sanguineus was examined in batch submerged cultures in shake flasks, baffled shake flasks and a stirred tank bioreactor. The biomass growth in the various culture systems closely followed a logistic growth model. The production of laccase followed a Luedeking-Piret model. A modified Luedeking-Piret model incorporating logistic growth effectively described the consumption of glucose. Biomass productivity, enzyme productivity and substrate consumption were enhanced in baffled shake flasks relative to the cases for the conventional shake flasks. This was associated with improved oxygen transfer in the presence of the baffles. The best results were obtained in the stirred tank bioreactor. At 28 °C, pH 4.5, an agitation speed of 600 rpm and a dissolved oxygen concentration of ~25 % of air saturation, the laccase productivity in the bioreactor exceeded 19 U L(-1 )days(-1), or 1.5-fold better than the best case for the baffled shake flask. The final concentration of the enzyme was about 325 U L(-1).
    Matched MeSH terms: Models, Biological*
  18. Aftab SMA, Ahmad KA
    PLoS ONE, 2017;12(8):e0183456.
    PMID: 28850622 DOI: 10.1371/journal.pone.0183456
    The Humpback whale tubercles have been studied for more than a decade. Tubercle Leading Edge (TLE) effectively reduces the separation bubble size and helps in delaying stall. They are very effective in case of low Reynolds number flows. The current Computational Fluid Dynamics (CFD) study is on NACA 4415 airfoil, at a Reynolds number 120,000. Two TLE shapes are tested on NACA 4415 airfoil. The tubercle designs implemented on the airfoil are sinusoidal and spherical. A parametric study is also carried out considering three amplitudes (0.025c, 0.05c and 0.075c), the wavelength (0.25c) is fixed. Structured mesh is utilized to generate grid and Transition SST turbulence model is used to capture the flow physics. Results clearly show spherical tubercles outperform sinusoidal tubercles. Furthermore experimental study considering spherical TLE is carried out at Reynolds number 200,000. The experimental results show that spherical TLE improve performance compared to clean airfoil.
    Matched MeSH terms: Models, Biological*
  19. Chong SY, Tiňo P, He J, Yao X
    Evol Comput, 2019;27(2):195-228.
    PMID: 29155606 DOI: 10.1162/evco_a_00218
    Studying coevolutionary systems in the context of simplified models (i.e., games with pairwise interactions between coevolving solutions modeled as self plays) remains an open challenge since the rich underlying structures associated with pairwise-comparison-based fitness measures are often not taken fully into account. Although cyclic dynamics have been demonstrated in several contexts (such as intransitivity in coevolutionary problems), there is no complete characterization of cycle structures and their effects on coevolutionary search. We develop a new framework to address this issue. At the core of our approach is the directed graph (digraph) representation of coevolutionary problems that fully captures structures in the relations between candidate solutions. Coevolutionary processes are modeled as a specific type of Markov chains-random walks on digraphs. Using this framework, we show that coevolutionary problems admit a qualitative characterization: a coevolutionary problem is either solvable (there is a subset of solutions that dominates the remaining candidate solutions) or not. This has an implication on coevolutionary search. We further develop our framework that provides the means to construct quantitative tools for analysis of coevolutionary processes and demonstrate their applications through case studies. We show that coevolution of solvable problems corresponds to an absorbing Markov chain for which we can compute the expected hitting time of the absorbing class. Otherwise, coevolution will cycle indefinitely and the quantity of interest will be the limiting invariant distribution of the Markov chain. We also provide an index for characterizing complexity in coevolutionary problems and show how they can be generated in a controlled manner.
    Matched MeSH terms: Models, Biological*
  20. Okie JG, Brown JH
    Proc. Natl. Acad. Sci. U.S.A., 2009 Nov 17;106 Suppl 2:19679-84.
    PMID: 19805179 DOI: 10.1073/pnas.0901654106
    The rising sea level at the end of the Pleistocene that created the islands of the Sunda Shelf in Indonesia and Malaysia provides a natural experiment in community disassembly and offers insights into the effects of body size and niches on abundance, distribution, and diversity. Since isolation, terrestrial mammal communities of these islands have been reduced by extinction, with virtually no offsetting colonization. We document three empirical patterns of disassembly, all of which are significantly different from null models of random assembly: (i) a diversity-area relationship: the number of taxa is strongly and positively correlated with island area; (ii) nested subset composition: species that occur on small islands tend to be subsets of more diverse communities inhabiting larger islands; and (iii) body size distributions: species of intermediate body sizes occur on the greatest number of islands, and smaller islands have smaller ranges of body sizes, caused by the absence of species of both very large and extremely small size. These patterns reveal the role of body size and other niche characteristics, such as habitat requirements and trophic status, in the differential susceptibility of taxa to extinction.
    Matched MeSH terms: Models, Biological*
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