MyMedR

Displaying publications 21 - 40 of 405 in total

Abstract:

Sort:

Fulltext Exoskeleton robot control for synchronous walking assistance in repetitive manual handling works based on dual unscented Kalman filter

Sado F, Yap HJ, Ghazilla RAR, Ahmad N

PLoS One, 2018;13(7):e0200193.
PMID: 30001415 DOI: 10.1371/journal.pone.0200193

Prolong walking is a notable risk factor for work-related lower-limb disorders (WRLLD) in industries such as agriculture, construction, service profession, healthcare and retail works. It is one of the common causes of lower limb fatigue or muscular exhaustion leading to poor balance and fall. Exoskeleton technology is seen as a modern strategy to assist worker's in these professions to minimize or eliminate the risk of WRLLDs. Exoskeleton has potentials to benefit workers in prolong walking (amongst others) by augmenting their strength, increasing their endurance, and minimizing high muscular activation, resulting in overall work efficiency and productivity. Controlling exoskeleton to achieve this purpose for able-bodied personnel without impeding their natural movement is, however, challenging. In this study, we propose a control strategy that integrates a Dual Unscented Kalman Filter (DUKF) for trajectory generation/prediction of the spatio-temporal features of human walking (i.e. joint position, and velocity, and acceleration) and an impedance cum supervisory controller to enable the exoskeleton to follow this trajectory to synchronize with the human walking. Experiment is conducted with four subjects carrying a load and walking at their normal speed- a typical scenario in industries. EMG signals taken at two muscles: Right Vastus Intermedius (on the thigh) and Right Gastrocnemius (on the calf) indicated reduction in muscular activation during the experiment. The results also show the ability of the control system to predict spatio-temporal features of the pilots' walking and to enable the exoskeleton to move in concert with the pilot.

Matched MeSH terms: Models, Biological
Fulltext Biosurfactant Production and Growth Kinetics Studies of the Waste Canola Oil-Degrading Bacterium Rhodococcuserythropolis AQ5-07 from Antarctica

Ibrahim S, Abdul Khalil K, Zahri KNM, Gomez-Fuentes C, Convey P, Zulkharnain A, et al.

Molecules, 2020 Aug 26;25(17).
PMID: 32858796 DOI: 10.3390/molecules25173878

With the progressive increase in human activities in the Antarctic region, the possibility of domestic oil spillage also increases. Developing means for the removal of oils, such as canola oil, from the environment and waste "grey" water using biological approaches is therefore desirable, since the thermal process of oil degradation is expensive and ineffective. Thus, in this study an indigenous cold-adapted Antarctic soil bacterium, Rhodococcus erythropolis strain AQ5-07, was screened for biosurfactant production ability using the multiple approaches of blood haemolysis, surface tension, emulsification index, oil spreading, drop collapse and "MATH" assay for cellular hydrophobicity. The growth kinetics of the bacterium containing different canola oil concentration was studied. The strain showed β-haemolysis on blood agar with a high emulsification index and low surface tension value of 91.5% and 25.14 mN/m, respectively. Of the models tested, the Haldane model provided the best description of the growth kinetics, although several models were similar in performance. Parameters obtained from the modelling were the maximum specific growth rate (qmax), concentration of substrate at the half maximum specific growth rate, Ks% (v/v) and the inhibition constant Ki% (v/v), with values of 0.142 h-1, 7.743% (v/v) and 0.399% (v/v), respectively. These biological coefficients are useful in predicting growth conditions for batch studies, and also relevant to "in field" bioremediation strategies where the concentration of oil might need to be diluted to non-toxic levels prior to remediation. Biosurfactants can also have application in enhanced oil recovery (EOR) under different environmental conditions.

Matched MeSH terms: Models, Biological*
Preconditioning as a potential strategy for the prevention of Parkinson's disease

Golpich M, Rahmani B, Mohamed Ibrahim N, Dargahi L, Mohamed Z, Raymond AA, et al.

Mol Neurobiol, 2015 Feb;51(1):313-30.
PMID: 24696268 DOI: 10.1007/s12035-014-8689-6

Parkinson's disease (PD) is a chronic neurodegenerative movement disorder characterized by the progressive and massive loss of dopaminergic neurons by neuronal apoptosis in the substantia nigra pars compacta and depletion of dopamine in the striatum, which lead to pathological and clinical abnormalities. A numerous of cellular processes including oxidative stress, mitochondrial dysfunction, and accumulation of α-synuclein aggregates are considered to contribute to the pathogenesis of Parkinson's disease. A further understanding of the cellular and molecular mechanisms involved in the pathophysiology of PD is crucial for developing effective diagnostic, preventative, and therapeutic strategies to cure this devastating disorder. Preconditioning (PC) is assumed as a natural adaptive process whereby a subthreshold stimulus can promote protection against a subsequent lethal stimulus in the brain as well as in other tissues that affords robust brain tolerance facing neurodegenerative insults. Multiple lines of evidence have demonstrated that preconditioning as a possible neuroprotective technique may reduce the neural deficits associated with neurodegenerative diseases such as PD. Throughout the last few decades, a lot of efforts have been made to discover the molecular determinants involved in preconditioning-induced protective responses; although, the accurate mechanisms underlying this "tolerance" phenomenon are not fully understood in PD. In this review, we will summarize pathophysiology and current therapeutic approaches in PD and discuss about preconditioning in PD as a potential neuroprotective strategy. Also the role of gene reprogramming and mitochondrial biogenesis involved in the preconditioning-mediated neuroprotective events will be highlighted. Preconditioning may represent a promising therapeutic weapon to combat neurodegeneration.

Matched MeSH terms: Models, Biological
Fulltext Hybrid flower pollination algorithm strategies for t-way test suite generation

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*
Modeling of passengers' safety perception for buses on mountainous roads

Khoo HL, Ahmed M

Accid Anal Prev, 2018 Apr;113:106-116.
PMID: 29407657 DOI: 10.1016/j.aap.2018.01.025

This study had developed a passenger safety perception model specifically for buses taking into consideration the various factors, namely driver characteristics, environmental conditions, and bus characteristics using Bayesian Network. The behaviour of bus driver is observed through the bus motion profile, measured in longitudinal, lateral, and vertical accelerations. The road geometry is recorded using GPS and is computed with the aid of the Google map while the perceived bus safety is rated by the passengers in the bus in real time. A total of 13 variables were derived and used in the model development. The developed Bayesian Network model shows that the type of bus and the experience of the driver on the investigated route could have an influence on passenger's perception of their safety on buses. Road geometry is an indirect influencing factor through the driver's behavior. The findings of this model are useful for the authorities to structure an effective strategy to improve the level of perceived bus safety. A high level of bus safety will definitely boost passenger usage confidence which will subsequently increase ridership.

Matched MeSH terms: Models, Biological
Comparing biomechanical strength of unicortical locking plate versus bicortical compression plate for transverse midshaft metacarpal fracture

Shanmugam R, Jian CYCCS, Haseeb A, Aik S

J Orthop Surg (Hong Kong), 2018 10 3;26(3):2309499018802511.
PMID: 30270746 DOI: 10.1177/2309499018802511

PURPOSE: Metacarpal bone fractures constitute 10% of all fractures. Unstable metacarpal fractures require surgical intervention, which poses danger to flexor tendon either due to bicortical drilling or construct of the implant. Unicortical locking plate fixation may be the solution to preventing flexor tendon injury. Studies have compared locking and compression plates. However, in these studies, the biomechanical properties were tested using the static loading method. This study looks into cyclical loading that is more representative of in vivo conditions, particularly for early rehabilitation. We compared the biomechanical strength of the unicortical locking plate and bicortical compression plate system in a transverse metacarpal fracture, tested with cyclical loading and torsion.
METHOD: Twenty pieces of fourth-generation, biomechanical testing grade, left third metacarpal composite bones were used. Resin was used to create the holding block at both ends of the bone. An oscillating saw with 0.8 mm thick saw blade was used to osteotomize the metacarpal sawbones to create a midshaft transverse metacarpal fracture model. Ten pieces were fixed with a 2.0 mm titanium locking plate via unicortical screw purchase and 10 were fixed with a 2.0 mm, four holes, titanium dynamic compression plate, bicortical purchase of screws. They were subjected to cyclic load to failure testing three-point bending and torsion.
RESULTS: There were no significant difference in stiffness and cyclic three-point bending to failure between the unicortical locking plate group and the bicortical compression plate group. The bicortical compression plate group is stiffer and has a higher cyclic bending load to failure as compared to the unicortical locking plate group.
CONCLUSION: Unicortical locking plate fixation of metacarpal fracture can be reliably applied clinically to produce a strong and stable construct that allows early mobilization of the joints. This will not only reduce the complication rate of metacarpal plating, but also improve the functional outcome of the hand.

Matched MeSH terms: Models, Biological
Fulltext Concentric ballooned catheterization to the fractional non-newtonian hybrid nano blood flow through a stenosed aneurysmal artery with heat transfer

Mehmood OU, Bibi S, Jamil DF, Uddin S, Roslan R, Akhir MKM

Sci Rep, 2021 10 14;11(1):20379.
PMID: 34650140 DOI: 10.1038/s41598-021-99499-z

The current work analyzes the effects of concentric ballooned catheterization and heat transfer on the hybrid nano blood flow through diseased arterial segment having both stenosis and aneurysm along its boundary. A fractional second-grade fluid model is considered which describes the non-Newtonian characteristics of the blood. Governing equations are linearized under mild stenosis and mild aneurysm assumptions. Precise articulations for various important flow characteristics such as heat transfer, hemodynamic velocity, wall shear stress, and resistance impedance are attained. Graphical portrayals for the impact of the significant parameters on the flow attributes have been devised. The streamlines of blood flow have been examined as well. The present finding is useful for drug conveyance system and biomedicines.

Matched MeSH terms: Models, Biological
Fulltext Hypoxic culture conditions as a solution for mesenchymal stem cell based regenerative therapy

Haque N, Rahman MT, Abu Kasim NH, Alabsi AM

ScientificWorldJournal, 2013;2013:632972.
PMID: 24068884 DOI: 10.1155/2013/632972

Cell-based regenerative therapies, based on in vitro propagation of stem cells, offer tremendous hope to many individuals suffering from degenerative diseases that were previously deemed untreatable. Due to the self-renewal capacity, multilineage potential, and immunosuppressive property, mesenchymal stem cells (MSCs) are considered as an attractive source of stem cells for regenerative therapies. However, poor growth kinetics, early senescence, and genetic instability during in vitro expansion and poor engraftment after transplantation are considered to be among the major disadvantages of MSC-based regenerative therapies. A number of complex inter- and intracellular interactive signaling systems control growth, multiplication, and differentiation of MSCs in their niche. Common laboratory conditions for stem cell culture involve ambient O₂ concentration (20%) in contrast to their niche where they usually reside in 2-9% O₂. Notably, O₂ plays an important role in maintaining stem cell fate in terms of proliferation and differentiation, by regulating hypoxia-inducible factor-1 (HIF-1) mediated expression of different genes. This paper aims to describe and compare the role of normoxia (20% O₂) and hypoxia (2-9% O₂) on the biology of MSCs. Finally it is concluded that a hypoxic environment can greatly improve growth kinetics, genetic stability, and expression of chemokine receptors during in vitro expansion and eventually can increase efficiency of MSC-based regenerative therapies.

Matched MeSH terms: Models, Biological
Utilization of sludge palm oil as a novel substrate for biosurfactant production

Wan Nawawi WM, Jamal P, Alam MZ

Bioresour Technol, 2010 Dec;101(23):9241-7.
PMID: 20674345 DOI: 10.1016/j.biortech.2010.07.024

This paper introduces sludge palm oil (SPO) as a novel substrate for biosurfactant production by liquid state fermentation. Potential strains of microorganism were isolated from various hydrocarbon-based sources at palm oil mill and screened for biosurfactant production with the help of drop collapse method and surface tension activity. Out of 22 isolates of microorganism, the strain S02 showed the highest bacterial growth with a surface tension of 36.2 mN/m and was therefore, selected as a potential biosurfactant producing microorganism. Plackett-Burman experimental design was employed to determine the important nutritional requirement for biosurfactant production by the selected strain under controlled conditions. Six out of 11 factors of the production medium were found to significantly affect the biosurfactant production. K(2)HPO(4) had a direct proportional correlation with the biosurfactant production while sucrose, glucose, FeSO(4), MgSO(4), and NaNO(3) showed inversely proportional relationship with biosurfactant production in the selected experimental range.

Matched MeSH terms: Models, Biological
Fulltext The possible potential therapeutic targets for drug induced gingival overgrowth

Subramani T, Rathnavelu V, Alitheen NB

Mediators Inflamm, 2013;2013:639468.
PMID: 23690667 DOI: 10.1155/2013/639468

Gingival overgrowth is a side effect of certain medications. The most fibrotic drug-induced lesions develop in response to therapy with phenytoin, the least fibrotic lesions are caused by cyclosporin A, and the intermediate fibrosis occurs in nifedipine-induced gingival overgrowth. Fibrosis is one of the largest groups of diseases for which there is no therapy but is believed to occur because of a persistent tissue repair program. During connective tissue repair, activated gingival fibroblasts synthesize and remodel newly created extracellular matrix. Proteins such as transforming growth factor (TGF), endothelin-1 (ET-1), angiotensin II (Ang II), connective tissue growth factor (CCN2/CTGF), insulin-like growth factor (IGF), and platelet-derived growth factor (PDGF) appear to act in a network that contributes to the development of gingival fibrosis. Since inflammation is the prerequisite for gingival overgrowth, mast cells and its protease enzymes also play a vital role in the pathogenesis of gingival fibrosis. Drugs targeting these proteins are currently under consideration as antifibrotic treatments. This review summarizes recent observations concerning the contribution of TGF-β, CTGF, IGF, PDGF, ET-1, Ang II, and mast cell chymase and tryptase enzymes to fibroblast activation in gingival fibrosis and the potential utility of agents blocking these proteins in affecting the outcome of drug-induced gingival overgrowth.

Matched MeSH terms: Models, Biological
A new twist on a very old binary similarity coefficient

Alroy J

Ecology, 2015 Feb;96(2):575-86.
PMID: 26240877

Pairwise similarity coefficients are downward biased when samples only record presences and sampling is partial. A simple but forgotten index proposed by Stephen Forbes in 1907 can help solve this problem. His original equation requires knowing the number of species absent in both samples that could have been present. It is proposed that this count should simply be ignored and that the coefficient should be adjusted using a simple heuristic correction. Four analyses show that the corrected equation outperforms the Dice and Simpson indices, which are highly correlated with many others. In two-sample simulations, similarity is almost always closer to the assumed value when the species pool size and sampling intensity are varied, regardless of whether the underlying abundance distribution is uniform, log-normal, or geometric. The index is also much more robust when sampling is unequal. An analysis of bat samples from peninsular Malaysia buttresses these conclusions. The corrected coefficient also indicates that local assemblages of North American mammals are random subsamples of larger species pools by returning similarity of values of around 1, and it suggests a more consistent relationship between biome-scale comparisons and local-scale comparisons. Finally, it yields a better-dispersed pattern when the biome-scale inventories are ordinated. If these results are generalizable, then the new and old equation should see wide application, potentially taking the place of the two most commonly used alternatives (the interrelated Dice and Jaccard indices) whenever sampling is incomplete.

Matched MeSH terms: Models, Biological
Optimization of thermo-alkaline disintegration of sewage sludge for enhanced biogas yield

Shehu MS, Abdul Manan Z, Alwi SR

Bioresour Technol, 2012 Jun;114:69-74.
PMID: 22444634 DOI: 10.1016/j.biortech.2012.02.135

Optimization of thermo-alkaline disintegration of sewage sludge for enhanced biogas yield was carried out using response surface methodology (RSM) and Box-Behnken design of experiment. The individual linear and quadratic effects as well as the interactive effects of temperature, NaOH concentration and time on the degree of disintegration were investigated. The optimum degree of disintegration achieved was 61.45% at 88.50 °C, 2.29 M NaOH (24.23%w/w total solids) and 21 min retention time. Linear and quadratic effects of temperature are most significant in affecting the degree of disintegration. The coefficient of determination (R(2)) of 99.5% confirms that the model used in predicting the degree of disintegration process has a very good fitness with the experimental variables. The disintegrated sludge increased the biogas yield by 36%v/v compared to non-disintegrated sludge. The RSM with Box-Behnken design is an effective tool in predicting the optimum degree of disintegration of sewage sludge for increased biogas yield.

Matched MeSH terms: Models, Biological*
Fulltext Mouth-clicks used by blind expert human echolocators - signal description and model based signal synthesis

Thaler L, Reich GM, Zhang X, Wang D, Smith GE, Tao Z, et al.

PLoS Comput Biol, 2017 Aug;13(8):e1005670.
PMID: 28859082 DOI: 10.1371/journal.pcbi.1005670

Echolocation is the ability to use sound-echoes to infer spatial information about the environment. Some blind people have developed extraordinary proficiency in echolocation using mouth-clicks. The first step of human biosonar is the transmission (mouth click) and subsequent reception of the resultant sound through the ear. Existing head-related transfer function (HRTF) data bases provide descriptions of reception of the resultant sound. For the current report, we collected a large database of click emissions with three blind people expertly trained in echolocation, which allowed us to perform unprecedented analyses. Specifically, the current report provides the first ever description of the spatial distribution (i.e. beam pattern) of human expert echolocation transmissions, as well as spectro-temporal descriptions at a level of detail not available before. Our data show that transmission levels are fairly constant within a 60° cone emanating from the mouth, but levels drop gradually at further angles, more than for speech. In terms of spectro-temporal features, our data show that emissions are consistently very brief (~3ms duration) with peak frequencies 2-4kHz, but with energy also at 10kHz. This differs from previous reports of durations 3-15ms and peak frequencies 2-8kHz, which were based on less detailed measurements. Based on our measurements we propose to model transmissions as sum of monotones modulated by a decaying exponential, with angular attenuation by a modified cardioid. We provide model parameters for each echolocator. These results are a step towards developing computational models of human biosonar. For example, in bats, spatial and spectro-temporal features of emissions have been used to derive and test model based hypotheses about behaviour. The data we present here suggest similar research opportunities within the context of human echolocation. Relatedly, the data are a basis to develop synthetic models of human echolocation that could be virtual (i.e. simulated) or real (i.e. loudspeaker, microphones), and which will help understanding the link between physical principles and human behaviour.

Matched MeSH terms: Models, Biological*
Fulltext An improved swarm optimization for parameter estimation and biological model selection

Abdullah A, Deris S, Mohamad MS, Anwar S

PLoS One, 2013;8(4):e61258.
PMID: 23593445 DOI: 10.1371/journal.pone.0061258

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

Matched MeSH terms: Models, Biological*
Fulltext Comparative analyses of response surface methodology and artificial neural network on medium optimization for Tetraselmis sp. FTC209 grown under mixotrophic condition

Mohamed MS, Tan JS, Mohamad R, Mokhtar MN, Ariff AB

ScientificWorldJournal, 2013;2013:948940.
PMID: 24109209 DOI: 10.1155/2013/948940

Mixotrophic metabolism was evaluated as an option to augment the growth and lipid production of marine microalga Tetraselmis sp. FTC 209. In this study, a five-level three-factor central composite design (CCD) was implemented in order to enrich the W-30 algal growth medium. Response surface methodology (RSM) was employed to model the effect of three medium variables, that is, glucose (organic C source), NaNO3 (primary N source), and yeast extract (supplementary N, amino acids, and vitamins) on biomass concentration, X(max), and lipid yield, P(max)/X(max). RSM capability was also weighed against an artificial neural network (ANN) approach for predicting a composition that would result in maximum lipid productivity, Pr(lipid). A quadratic regression from RSM and a Levenberg-Marquardt trained ANN network composed of 10 hidden neurons eventually produced comparable results, albeit ANN formulation was observed to yield higher values of response outputs. Finalized glucose (24.05 g/L), NaNO3 (4.70 g/L), and yeast extract (0.93 g/L) concentration, affected an increase of X(max) to 12.38 g/L and lipid a accumulation of 195.77 mg/g dcw. This contributed to a lipid productivity of 173.11 mg/L per day in the course of two-week cultivation.

Matched MeSH terms: Models, Biological
Improved production of live cells of Lactobacillus rhamnosus by continuous cultivation using glucose-yeast extract medium

Ling LS, Mohamad R, Rahim RA, Wan HY, Ariff AB

J Microbiol, 2006 Aug;44(4):439-46.
PMID: 16953180

In this study, the growth kinetics of Lactobacillus rhamnosus and lactic acid production in continuous culture were assessed at a range of dilution rates (0.05 h(-1) to 0.40 h(-1)) using a 2 L stirred tank fermenter with a working volume of 600 ml. Unstructured models, predicated on the Monod and Luedeking-Piret equations, were employed to simulate the growth of the bacterium, glucose consumption, and lactic acid production at different dilution rates in continuous cultures. The maximum specific growth rate of L. rhamnosus, mu-max, was estimated at 0.40 h(-1), and the Monod cell growth saturation constant, Ks, at approximately 0.25 g/L. Maximum cell viability (1.3 x 10(10) CFU/ml) was achieved in the dilution rate range of D = 0.28 h(-1) to 0.35 h(-1). Both maximum viable cell yield and productivity were achieved at D = 0.35 h(-1). The continuous cultivation of L. rhamnosus at D = 0.35 h(-1) resulted in substantial improvements in cell productivity, of 267% (viable cell count) that achieved via batch cultivation.

Matched MeSH terms: Models, Biological
Community fluctuations and local extinction in a planktonic food web

Segura AM, Calliari D, Lan BL, Fort H, Widdicombe CE, Harmer R, et al.

Ecol Lett, 2017 04;20(4):471-476.
PMID: 28239940 DOI: 10.1111/ele.12749

Determining statistical patterns irrespective of interacting agents (i.e. macroecology) is useful to explore the mechanisms driving population fluctuations and extinctions in natural food webs. Here, we tested four predictions of a neutral model on the distribution of community fluctuations (CF) and the distributions of persistence times (APT). Novel predictions for the food web were generated by combining (1) body size-density scaling, (2) Taylor's law and (3) low efficiency of trophic transference. Predictions were evaluated on an exceptional data set of plankton with 15 years of weekly samples encompassing c. 250 planktonic species from three trophic levels, sampled in the western English Channel. Highly symmetric non-Gaussian distributions of CF support zero-sum dynamics. Variability in CF decreased while a change from an exponential to a power law distribution of APT from basal to upper trophic positions was detected. Results suggest a predictable but profound effect of trophic position on fluctuations and extinction in natural communities.

Matched MeSH terms: Models, Biological
Fulltext An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters

Abdullah A, Deris S, Anwar S, Arjunan SN

PLoS One, 2013;8(3):e56310.
PMID: 23469172 DOI: 10.1371/journal.pone.0056310

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

Matched MeSH terms: Models, Biological*
Surface reaction-diffusion kinetics on lattice at the microscopic scale

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*
A kinetic study of autohydrogenotrophic denitrification at the optimum pH and sodium bicarbonate dose

Ghafari S, Hasan M, Aroua MK

Bioresour Technol, 2010 Apr;101(7):2236-42.
PMID: 20015639 DOI: 10.1016/j.biortech.2009.11.068

In this study the kinetics of autohydrogenotrophic denitrification was studied under optimum solution pH and bicarbonate concentration. The optimal pH and bicarbonate concentration were firstly obtained using a design of experiment (DOE) methodology. For this purpose a total of 11 experiments were carried out. Sodium bicarbonate concentrations ranging of 20-2000 mg/L and pH values from 6.5 to 8.5 were used in the optimization runs. It was found that the pH has a more pronounced effect on the denitrification process as compared to the bicarbonate dose. The developed quadratic model predicted the optimum conditions at pH 8 and 1100 mg NaHCO(3)/L. Using these optimal conditions, the kinetics of denitrification for nitrate and nitrite degradation were investigated in separate experiments. Both processes were found to follow a zero order kinetic model. The ultimate specific degradation rates for nitrate and nitrite remediation were 29.60 mg NO(3)(-)-N/g MLVSS/L and 34.85 mg NO(3)(-)-N/g MLVSS/L respectively, when hydrogen was supplied every 0.5h.

Matched MeSH terms: Models, Biological

Filters

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links