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In silico characterization and expression profiling of the diacylglycerol acyltransferase gene family (DGAT1, DGAT2, DGAT3 and WS/DGAT) from oil palm, Elaeis guineensis

Rosli R, Chan PL, Chan KL, Amiruddin N, Low EL, Singh R, et al.

Plant Sci, 2018 Oct;275:84-96.
PMID: 30107884 DOI: 10.1016/j.plantsci.2018.07.011

The diacylglycerol acyltransferases (DGAT) (diacylglycerol:acyl-CoA acyltransferase, EC 2.3.1.20) are a key group of enzymes that catalyse the final and usually the most important rate-limiting step of triacylglycerol biosynthesis in plants and other organisms. Genes encoding four distinct functional families of DGAT enzymes have been characterised in the genome of the African oil palm, Elaeis guineensis. The contrasting features of the various isoforms within the four families of DGAT genes, namely DGAT1, DGAT2, DGAT3 and WS/DGAT are presented both in the oil palm itself and, for comparative purposes, in 12 other oil crop or model/related plants, namely Arabidopsis thaliana, Brachypodium distachyon, Brassica napus, Elaeis oleifera, Glycine max, Gossypium hirsutum, Helianthus annuus, Musa acuminata, Oryza sativa, Phoenix dactylifera, Sorghum bicolor, and Zea mays. The oil palm genome contains respectively three, two, two and two distinctly expressed functional copies of the DGAT1, DGAT2, DGAT3 and WS/DGAT genes. Phylogenetic analyses of the four DGAT families showed that the E. guineensis genes tend to cluster with sequences from P. dactylifera and M. acuminata rather than with other members of the Commelinid monocots group, such as the Poales which include the major cereal crops such as rice and maize. Comparison of the predicted DGAT protein sequences with other animal and plant DGATs was consistent with the E. guineensis DGAT1 being ER located with its active site facing the lumen while DGAT2, although also ER located, had a predicted cytosol-facing active site. In contrast, DGAT3 and some (but not all) WS/DGAT in E. guineensis are predicted to be soluble, cytosolic enzymes. Evaluation of E. guineensis DGAT gene expression in different tissues and developmental stages suggests that the four DGAT groups have distinctive physiological roles and are particularly prominent in developmental processes relating to reproduction, such as flowering, and in fruit/seed formation especially in the mesocarp and endosperm tissues.

Matched MeSH terms: Computer Simulation
Fulltext Epidemic dynamics, interactions and predictability of enteroviruses associated with hand, foot and mouth disease in Japan

Takahashi S, Metcalf CJE, Arima Y, Fujimoto T, Shimizu H, Rogier van Doorn H, et al.

J R Soc Interface, 2018 09 12;15(146).
PMID: 30209044 DOI: 10.1098/rsif.2018.0507

Outbreaks of hand, foot and mouth disease have been documented in Japan since 1963. This disease is primarily caused by the two closely related serotypes of Enterovirus A71 (EV-A71) and Coxsackievirus A16 (CV-A16). Here, we analyse Japanese virologic and syndromic surveillance time-series data from 1982 to 2015. As in some other countries in the Asia Pacific region, EV-A71 in Japan has a 3 year cyclical component, whereas CV-A16 is predominantly annual. We observe empirical signatures of an inhibitory interaction between the serotypes; virologic lines of evidence suggest they may indeed interact immunologically. We fit the time series to mechanistic epidemiological models: as a first-order effect, we find the data consistent with single-serotype susceptible-infected-recovered dynamics. We then extend the modelling to incorporate an inhibitory interaction between serotypes. Our results suggest the existence of a transient cross-protection and possible asymmetry in its strength such that CV-A16 serves as a stronger forcing on EV-A71. Allowing for asymmetry yields accurate out-of-sample predictions and the directionality of this effect is consistent with the virologic literature. Confirmation of these hypothesized interactions would have important implications for understanding enterovirus epidemiology and informing vaccine development. Our results highlight the general implication that even subtle interactions could have qualitative impacts on epidemic dynamics and predictability.

Matched MeSH terms: Computer Simulation
Patient asynchrony modelling during controlled mechanical ventilation therapy

Arunachalam GR, Chiew YS, Tan CP, Ralib AM, Nor MBM

Comput Methods Programs Biomed, 2020 Jan;183:105103.
PMID: 31606559 DOI: 10.1016/j.cmpb.2019.105103

BACKGROUND AND OBJECTIVE: Mechanical ventilation therapy of respiratory failure patients can be guided by monitoring patient-specific respiratory mechanics. However, the patient's spontaneous breathing effort during controlled ventilation changes airway pressure waveform and thus affects the model-based identification of patient-specific respiratory mechanics parameters. This study develops a model to estimate respiratory mechanics in the presence of patient effort.
METHODS: Gaussian effort model (GEM) is a derivative of the single-compartment model with basis function. GEM model uses a linear combination of basis functions to model the nonlinear pressure waveform of spontaneous breathing patients. The GEM model estimates respiratory mechanics such as Elastance and Resistance along with the magnitudes of basis functions, which accounts for patient inspiratory effort.
RESULTS AND DISCUSSION: The GEM model was tested using both simulated data and a retrospective observational clinical trial patient data. GEM model fitting to the original airway pressure waveform is better than any existing models when reverse triggering asynchrony is present. The fitting error of GEM model was less than 10% for both simulated data and clinical trial patient data.
CONCLUSION: GEM can capture the respiratory mechanics in the presence of patient effect in volume control ventilation mode and also can be used to assess patient-ventilator interaction. This model determines basis functions magnitudes, which can be used to simulate any waveform of patient effort pressure for future studies. The estimation of parameter identification GEM model can further be improved by constraining the parameters within a physiologically plausible range during least-square nonlinear regression.

Matched MeSH terms: Computer Simulation
Fulltext An analytical model to minimize the latency in healthcare internet-of-things in fog computing environment

Shukla S, Hassan MF, Khan MK, Jung LT, Awang A

PLoS One, 2019;14(11):e0224934.
PMID: 31721807 DOI: 10.1371/journal.pone.0224934

Fog computing (FC) is an evolving computing technology that operates in a distributed environment. FC aims to bring cloud computing features close to edge devices. The approach is expected to fulfill the minimum latency requirement for healthcare Internet-of-Things (IoT) devices. Healthcare IoT devices generate various volumes of healthcare data. This large volume of data results in high data traffic that causes network congestion and high latency. An increase in round-trip time delay owing to large data transmission and large hop counts between IoTs and cloud servers render healthcare data meaningless and inadequate for end-users. Time-sensitive healthcare applications require real-time data. Traditional cloud servers cannot fulfill the minimum latency demands of healthcare IoT devices and end-users. Therefore, communication latency, computation latency, and network latency must be reduced for IoT data transmission. FC affords the storage, processing, and analysis of data from cloud computing to a network edge to reduce high latency. A novel solution for the abovementioned problem is proposed herein. It includes an analytical model and a hybrid fuzzy-based reinforcement learning algorithm in an FC environment. The aim is to reduce high latency among healthcare IoTs, end-users, and cloud servers. The proposed intelligent FC analytical model and algorithm use a fuzzy inference system combined with reinforcement learning and neural network evolution strategies for data packet allocation and selection in an IoT-FC environment. The approach is tested on simulators iFogSim (Net-Beans) and Spyder (Python). The obtained results indicated the better performance of the proposed approach compared with existing methods.

Matched MeSH terms: Computer Simulation
A level-set method for the evolution of cells and tissue during curvature-controlled growth

Alias MA, Buenzli PR

Int J Numer Method Biomed Eng, 2020 01;36(1):e3279.
PMID: 31724309 DOI: 10.1002/cnm.3279

Most biological tissues grow by the synthesis of new material close to the tissue's interface, where spatial interactions can exert strong geometric influences on the local rate of growth. These geometric influences may be mechanistic or cell behavioural in nature. The control of geometry on tissue growth has been evidenced in many in vivo and in vitro experiments, including bone remodelling, wound healing, and tissue engineering scaffolds. In this paper, we propose a generalisation of a mathematical model that captures the mechanistic influence of curvature on the joint evolution of cell density and tissue shape during tissue growth. This generalisation allows us to simulate abrupt topological changes such as tissue fragmentation and tissue fusion, as well as three dimensional cases, through a level-set-based method. The level-set method developed introduces another Eulerian field than the level-set function. This additional field represents the surface density of tissue-synthesising cells, anticipated at future locations of the interface. Numerical tests performed with this level-set-based method show that numerical conservation of cells is a good indicator of simulation accuracy, particularly when cusps develop in the tissue's interface. We apply this new model to several situations of curvature-controlled tissue evolutions that include fragmentation and fusion.

Matched MeSH terms: Computer Simulation
Fulltext Genome-Wide Computational Identification of Biologically Significant Cis-Regulatory Elements and Associated Transcription Factors from Rice

Ho CL, Geisler M

Plants (Basel), 2019 Oct 23;8(11).
PMID: 31652796 DOI: 10.3390/plants8110441

The interactions between transcription factors (TFs) and cis-acting regulatory elements (CREs) provide crucial information on the regulation of gene expression. The determination of TF-binding sites and CREs experimentally is costly and time intensive. An in silico identification and annotation of TFs, and the prediction of CREs from rice are made possible by the availability of whole genome sequence and transcriptome data. In this study, we tested the applicability of two algorithms developed for other model systems for the identification of biologically significant CREs of co-expressed genes from rice. CREs were identified from the DNA sequences located upstream from the transcription start sites, untranslated regions (UTRs), and introns, and downstream from the translational stop codons of co-expressed genes. The biologically significance of each CRE was determined by correlating their absence and presence in each gene with that gene's expression profile using a meta-database constructed from 50 rice microarray data sets. The reliability of these methods in the predictions of CREs and their corresponding TFs was supported by previous wet lab experimental data and a literature review. New CREs corresponding to abiotic stresses, biotic stresses, specific tissues, and developmental stages were identified from rice, revealing new pieces of information for future experimental testing. The effectiveness of some-but not all-CREs was found to be affected by copy number, position, and orientation. The corresponding TFs that were most likely correlated with each CRE were also identified. These findings not only contribute to the prioritization of candidates for further analysis, the information also contributes to the understanding of the gene regulatory network.

Matched MeSH terms: Computer Simulation
CHARACTERISATION AND EVALUATION OF AL2O3:C-BASED OPTICALLY STIMULATED LUMINESCENT DOSEMETER SYSTEM FOR DIAGNOSTIC X-RAYS: PERSONAL AND IN VIVO DOSIMETRY

Wong JHD, Bakhsh M, Cheah YY, Jong WL, Khor JS, Ng KH

Radiat Prot Dosimetry, 2019 Dec 31;187(4):451-460.
PMID: 31650160 DOI: 10.1093/rpd/ncz186

This study characterises and evaluates an Al2O3:C-based optically stimulated luminescent dosemeter (OSLD) system, commercially known as the nanoDot™ dosemeter and the InLight® microStar reader, for personal and in vivo dose measurements in diagnostic radiology. The system characteristics, such as dose linearity, reader accuracy, reproducibility, batch homogeneity, energy dependence and signal stability, were explored. The suitability of the nanoDot™ dosemeters was evaluated by measuring the depth dose curve, in vivo dose measurement and image perturbation. The nanoDot™ dosemeters were observed to produce a linear dose with ±2.8% coefficient variation. Significant batch inhomogeneity (8.3%) was observed. A slight energy dependence (±6.1%) was observed between 60 and 140 kVp. The InLight® microStar reader demonstrated good accuracy and a reproducibility of ±2%. The depth dose curve measured using nanoDot™ dosemeters showed slightly lower responses than Monte Carlo simulation results. The total uncertainty for a single dose measurement using this system was 11%, but it could be reduced to 9.2% when energy dependence correction was applied.

Matched MeSH terms: Computer Simulation
The role of end-diastolic myocardial fibre stretch on infarct extension

Leong CN, Dokos S, Andriyana A, Liew YM, Chan BT, Abdul Aziz YF, et al.

Int J Numer Method Biomed Eng, 2020 01;36(1):e3291.
PMID: 31799767 DOI: 10.1002/cnm.3291

Myocardial infarct extension, a process involving the enlargement of infarct and border zone, leads to progressive degeneration of left ventricular (LV) function and eventually gives rise to heart failure. Despite carrying a high risk, the causation of infarct extension is still a subject of much speculation. In this study, patient-specific LV models were developed to investigate the correlation between infarct extension and impaired regional mechanics. Subsequently, sensitivity analysis was performed to examine the causal factors responsible for the impaired regional mechanics observed in regions surrounding the infarct and border zone. From our simulations, fibre strain, fibre stress and fibre stress-strain loop (FSSL) were the key biomechanical variables affected in these regions. Among these variables, only FSSL was correlated with infarct extension, as reflected in its work density dissipation (WDD) index value, with high WDD indices recorded at regions with infarct extension. Impaired FSSL is caused by inadequate contraction force generation during the isovolumic contraction and ejection phases. Our further analysis revealed that the inadequacy in contraction force generation is not necessarily due to impaired myocardial intrinsic contractility, but at least in part, due to inadequate muscle fibre stretch at end-diastole, which depresses the ability of myocardium to generate adequate contraction force in the subsequent systole (according to the Frank-Starling law). Moreover, an excessively stiff infarct may cause its neighbouring myocardium to be understretched at end-diastole, subsequently depressing the systolic contractile force of the neighbouring myocardium, which was found to be correlated with infarct extension.

Matched MeSH terms: Computer Simulation
Monte Carlo simulations and analysis of transmitted gamma ray spectra through various tissue phantoms

Moradi F, Khandaker MU, Alrefae T, Ramazanian H, Bradley DA

Appl Radiat Isot, 2019 Apr;146:120-126.
PMID: 30769172 DOI: 10.1016/j.apradiso.2019.01.031

Studies of radiation interactions with tissue equivalent material find importance in efforts that seek to avoid unjustifiable dose to patients, also in ensuring quality control of for instance nuclear medicine imaging equipment. Use of the Monte Carlo (MC) simulation tool in such characterization processes allows for the avoidance of costly experiments involving transmitted X- and γ-ray spectrometry. Present work investigates MC simulations of γ-ray transmission through tissue equivalent solid phantoms. Use has been made of a range of radionuclide gamma ray sources, 99mTc, 131I, 137Cs, 60Co (offering photons in the energy range from a few keV up to low MeV), popularly applied in medicine and in some cases for gauging in industry, obtaining the transmission spectra following their interaction with various phantom materials and thicknesses. In validation of the model, the simulated values of mass attenuation coefficients (μ/ρ) for different phantom materials and thicknesses were found to be in good agreement with reference values (NIST, 2004) to within 1.1% for all material compositions. For all of the primary photon energies and medium thicknesses of interest herein, results show that multiple scattering peaks are generally located at energies lower than 100 keV, although for the larger phantom thicknesses it is more difficult to distinguish single, double and multiple scattering in the gamma spectra. Transmitted photon spectra investigated for water, soft tissue, breast, brain and lung tissue slab phantoms are demonstrated to be practically independent of the phantom material, while a significant difference is observed for the spectra transmitted through bone that was proved to be due to the density effect and not material composition.

Matched MeSH terms: Computer Simulation
Fulltext DAD-match; Security technique to prevent denial of service attack on duplicate address detection process in IPv6 link-local network

Al-Ani AK, Anbar M, Manickam S, Al-Ani A

PLoS One, 2019;14(4):e0214518.
PMID: 30939154 DOI: 10.1371/journal.pone.0214518

An efficiently unlimited address space is provided by Internet Protocol version 6 (IPv6). It aims to accommodate thousands of hundreds of unique devices on a similar link. This can be achieved through the Duplicate Address Detection (DAD) process. It is considered one of the core IPv6 network's functions. It is implemented to make sure that IP addresses do not conflict with each other on the same link. However, IPv6 design's functions are exposed to security threats like the DAD process, which is vulnerable to Denial of Service (DoS) attack. Such a threat prevents the host from configuring its IP address by responding to each Neighbor Solicitation (NS) through fake Neighbor Advertisement (NA). Various mechanisms have been proposed to secure the IPv6 DAD procedure. The proposed mechanisms, however, suffer from complexity, high processing time, and the consumption of more resources. The experiments-based findings revealed that all the existing mechanisms had failed to secure the IPv6 DAD process. Therefore, DAD-match security technique is proposed in this study to efficiently secure the DAD process consuming less processing time. DAD-match is built based on SHA-3 to hide the exchange tentative IP among hosts throughout the process of DAD in an IPv6 link-local network. The obtained experimental results demonstrated that the DAD-match security technique achieved less processing time compared with the existing mechanisms as it can resist a range of different threats like collision and brute-force attacks. The findings concluded that the DAD-match technique effectively prevents the DoS attack during the DAD process. The DAD-match technique is implemented on a small area IPv6 network; hence, the author future work is to implement and test the DAD-match technique on a large area IPv6 network.

Matched MeSH terms: Computer Simulation
Insights into DEPTOR regulation from in silico analysis of DEPTOR complexes

Teh AH, Yeap KH, Hisano T

J Struct Biol, 2020 11 01;212(2):107602.
PMID: 32798656 DOI: 10.1016/j.jsb.2020.107602

DEPTOR is an inhibitor of the mTOR kinase which controls cell growth. DEPTOR consists of two DEP domains and a PDZ domain connected by an unstructured linker, and its stability is tightly regulated through post-translational modifications of its linker region that contains the 286SSGYFS291 degron. Based on the mTORC1 complex, our modelling suggests a possible spatial arrangement of DEPTOR which is characterised to form a dimer. Our model shows that the two PDZ domains of a DEPTOR dimer bind separately to the dimeric mTOR's FAT domains ~130 Å apart, while each of the two extended linkers is sufficiently long to span from the FAT domain to the kinase domain of mTOR and beyond to join a shared dimer of the DEP domains. This places the linker's S299 closest to the kinase's catalytic site, indicating that phosphorylation would start with it and successively upstream towards DEPTOR's degron. The CK1α kinase is reportedly responsible for the phosphorylation of the degron, and our docking analysis further reveals that CK1α contains sites to bind DEPTOR's pS286, pS287 and pT295, which may act as priming phosphates for the phosphorylation of the degron's S291. DEPTOR's linker can also be ubiquitylated by the UbcH5A-SCFβ-TrCP complex without its PDZ dissociating from mTOR according to the modelling. As the catalytic cleft of mTOR's kinase is restricted, interactions between the kinase's unstructured segment surrounding the cleft and DEPTOR's linker, which may involve S293 and S299, may be critical to controlling DEPTOR's access to the catalytic cleft and hence its phosphorylation by mTOR in a manner dependent on mTOR's activation.

Matched MeSH terms: Computer Simulation
Developmental Approach for Behavior Learning Using Primitive Motion Skills

Dawood F, Loo CK

Int J Neural Syst, 2018 May;28(4):1750038.
PMID: 29022403 DOI: 10.1142/S0129065717500381

Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet the discussion on the origin of primitive imitative abilities is often neglected, referring instead to the possibility of its innateness. This paper presents a developmental model of imitation learning based on the hypothesis that humanoid robot acquires imitative abilities as induced by sensorimotor associative learning through self-exploration. In designing such learning system, several key issues will be addressed: automatic segmentation of the observed actions into motion primitives using raw images acquired from the camera without requiring any kinematic model; incremental learning of spatio-temporal motion sequences to dynamically generates a topological structure in a self-stabilizing manner; organization of the learned data for easy and efficient retrieval using a dynamic associative memory; and utilizing segmented motion primitives to generate complex behavior by the combining these motion primitives. In our experiment, the self-posture is acquired through observing the image of its own body posture while performing the action in front of a mirror through body babbling. The complete architecture was evaluated by simulation and real robot experiments performed on DARwIn-OP humanoid robot.

Matched MeSH terms: Computer Simulation
In silico identification of genes involved in chronic metabolic acidosis

Sheikh IA, Malik A, AlBasri SFM, Beg MA

Life Sci, 2018 Jan 01;192:246-252.
PMID: 29138116 DOI: 10.1016/j.lfs.2017.11.014

AIMS: Chronic metabolic acidosis (CMA) refers to increased plasma acidity due to disturbed acid-base equilibrium in human body. CMA leads to many dysfunctions including disorders of intestinal metabolism and barrier functions. The human body responds to these intestinal dysfunctions by creating a compensatory mechanism at genomic level in intestinal epithelial cells. This study was to identify the molecular pathways involved in metabolic dysfunction and compensatory adaptations in intestinal epithelium during CMA.
MAIN METHODS: In silico approaches were utilized to characterize a set of 88 differentially expressed genes (DEGs) from intestinal cells of rat CMA model. Interaction networks were constructed for DEGs by GeneMANIA and hub genes as well as enriched clusters in the network were screened using GLay. Gene Ontology (GO) was used for enriching functions in each cluster.
KEY FINDINGS: Four gene hubs, i.e., trefoil factor 1, 5-hydroxytryptamine (serotonin) receptor 5a, solute carrier family 6 (neurotransmitter transporter), member 11, and glutamate receptor, ionotropic, n-methyl d-aspartate 2b, exhibiting the highest node degree were predicted. Six biologically related gene clusters were also predicted. Functional enrichment of GO terms predicted neurological processes such as neurological system process regulation and nerve impulse transmission which are related to negative and positive regulation of digestive system processes., intestinal motility and absorption and maintenance of gastrointestinal epithelium.
SIGNIFICANCE: The study predicted several important genomic pathways that potentially play significant roles in metabolic disruptions or compensatory adaptations of intestinal epithelium induced by CMA. The results provide a further insight into underlying molecular mechanisms associated with CMA.

Matched MeSH terms: Computer Simulation
MicroRNA profiling in MDA-MB-231 human breast cancer cell exposed to the Phaleria macrocarpa (Boerl.) fruit ethyl acetate fraction (PMEAF) through IIlumina Hi-Seq technologies and various in silico bioinformatics tools

Kavitha N, Vijayarathna S, Shanmugapriya, Oon CE, Chen Y, Kanwar JR, et al.

J Ethnopharmacol, 2018 Mar 01;213:118-131.
PMID: 29154802 DOI: 10.1016/j.jep.2017.11.009

ETHNOPHARMACOLOGICAL RELEVANCE: Phaleria macrocarpa (Scheff) Boerl, is a famous traditional medicinal plant which exhibited cytotoxicity against various cancerous cells. Traditionally, P. macrocarpa has been used to control cancer, impotency, hemorrhoids, diabetes mellitus, allergies, liver and heart disease, kidney disorders, blood diseases, acne, stroke, migraine, and various skin diseases.
AIM OF THE STUDY: Recent studies have demonstrated a potent anticancer potential of P. macrocarpa, especially against HeLa cell. The objective of this study was to investigate the regulation of miRNAs on MDA-MB-231 treated with P. macrocarpa ethyl acetate fraction (PMEAF).
MATERIALS AND METHODS: The regulation of miRNAs on MDA-MB-231 cells treated with PMEAF was studied through IIlumina, Hi-Seq. 2000 platform of Next Generation Sequencing (NGS) and various in silico bioinformatics tools.
RESULTS: The PMEAF treatment against MDA-MB-231 cells identified 10 upregulated and 10 downregulated miRNAs. A set of 606 target genes of 10 upregulated miRNAs and 517 target genes of 10 downregulated miRNAs were predicted based on computational and validated databases by using miRGate DB Query. Meanwhile, results from DAVID Bioinformatics Resources 6.8 specified the functional annotation of the upregulated miRNAs involvement in cancer pathway by suppressing the oncogenes and downregulating miRNAs by expressing the tumour suppressor genes in the regulation of apoptosis pathway.
CONCLUSION: In conclusion, the results of this study proved that PMEAF is a promising anticancer agent with high cytotoxicity against MDA-MB-231 breast cancer cells and it induced apoptotic cell death mechanism through the regulation of miRNAs. PMEAF might be the best candidate for developing more potent anticancer drugs or chemo preventive supplements.

Matched MeSH terms: Computer Simulation
Fulltext In vitro and in silico Approaches to Study Cytochrome P450-Mediated Interactions

Tan BH, Pan Y, Dong AN, Ong CE

J Pharm Pharm Sci, 2017;20(1):319-328.
PMID: 29145931 DOI: 10.18433/J3434R

In vitro and in silico models of drug metabolism are utilized regularly in the drug research and development as tools for assessing pharmacokinetic variability and drug-drug interaction risk. The use of in vitro and in silico predictive approaches offers advantages including guiding rational design of clinical drug-drug interaction studies, minimization of human risk in the clinical trials, as well as cost and time savings due to lesser attrition during compound development process. This article gives a review of some of the current in vitro and in silico methods used to characterize cytochrome P450(CYP)-mediated drug metabolism for estimating pharmacokinetic variability and the magnitude of drug-drug interactions. Examples demonstrating the predictive applicability of specific in vitro and in silico approaches are described. Commonly encountered confounding factors and sources of bias and error in these approaches are presented. With the advent of technological advancement in high throughput screening and computer power, the in vitro and in silico methods are becoming more efficient and reliable and will continue to contribute to the process of drug discovery, development and ultimately safer and more effective pharmacotherapy. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

Matched MeSH terms: Computer Simulation
Measuring Anger Types among Malaysian Adolescents using the Rasch Model

Khairani AZ, Ahmad NS, Khairani MZ

J Appl Meas, 2017;18(4):449-458.
PMID: 29252212

Adolescences is an important transitional phase in human development where they experience physiological as well as psychological changes. Nevertheless, these changes are often understood by teachers, parents, and even the adolescents themselves. Thus, conflicts exist and adolescents are affected from the conflict physically and emotionally. An important state of emotions that result from this conflict is anger. This article describes the development and validation of the 34-item Adolescent Anger Inventory (AAI) to measure types of anger among Malaysian adolescents. A sample of 2,834 adolescents in secondary school who provide responses that were analyzed using Rasch model measurement framework. The 4 response category worked satisfactorily for the scale developed. A total of 11 items did not fit to the model's expectations, and thus dropped from the final scale. The scale also demonstrated satisfactory reliability and separation evidence. Also, items in the AAI depicted no evidence of DIF between 14- and 16-year-old adolescents. Nevertheless, the AAI did not have sufficient items to target adolescents with a high level of physical aggressive anger.

Matched MeSH terms: Computer Simulation
An Îto stochastic differential equations model for the dynamics of the MCF-7 breast cancer cell line treated by radiotherapy

Oroji A, Omar M, Yarahmadian S

J Theor Biol, 2016 10 21;407:128-137.
PMID: 27457094 DOI: 10.1016/j.jtbi.2016.07.035

In this paper, a new mathematical model is proposed for studying the population dynamics of breast cancer cells treated by radiotherapy by using a system of stochastic differential equations. The novelty of the model is essentially in capturing the concept of the cell cycle in the modeling to be able to evaluate the tumor lifespan. According to the cell cycle, each cell belongs to one of three subpopulations G, S, or M, representing gap, synthesis and mitosis subpopulations. Cells in the M subpopulation are highly radio-sensitive, whereas cells in the S subpopulation are highly radio-resistant. Therefore, in the process of radiotherapy, cell death rates of different subpopulations are not equal. In addition, since flow cytometry is unable to detect apoptotic cells accurately, the small changes in cell death rate in each subpopulation during treatment are considered. Subsequently, the proposed model is calibrated using experimental data from previous experiments involving the MCF-7 breast cancer cell line. Consequently, the proposed model is able to predict tumor lifespan based on the number of initial carcinoma cells. The results show the effectiveness of the radiation under the condition of stability, which describes the decreasing trend of the tumor cells population.

Matched MeSH terms: Computer Simulation
Modification of Aortic Cannula With an Inlet Chamber to Induce Spiral Flow and Improve Outlet Flow

Darlis N, Osman K, Padzillah MH, Dillon J, Md Khudzari AZ

Artif Organs, 2018 May;42(5):493-499.
PMID: 29280161 DOI: 10.1111/aor.13021

Physiologically, blood ejected from the left ventricle in systole exhibited spiral flow characteristics. This spiral flow has been proven to have several advantages such as lateral reduction of directed forces and thrombus formation, while it also appears to be clinically beneficial in suppressing neurological complications. In order to deliver spiral flow characteristics during cardiopulmonary bypass operation, several modifications have been made on an aortic cannula either at the internal or at the outflow tip; these modifications have proven to yield better hemodynamic performances compared to standard cannula. However, there is no modification done at the inlet part of the aortic cannula for inducing spiral flow so far. This study was carried out by attaching a spiral inducer at the inlet of an aortic cannula. Then, the hemodynamic performances of the new cannula were compared with the standard straight tip end-hole cannula. This is achieved by modeling the cannula and attaching the cannula at a patient-specific aorta model. Numerical approach was utilized to evaluate the hemodynamic performance, and a water jet impact experiment was used to demonstrate the jet force generated by the cannula. The new spiral flow aortic cannula has shown some improvements by reducing approximately 21% of impinging velocity near to the aortic wall, and more than 58% reduction on total force generated as compared to standard cannula.

Matched MeSH terms: Computer Simulation
Effects of vibration on occupant driving performance under simulated driving conditions

Azizan A, Fard M, Azari MF, Jazar R

Appl Ergon, 2017 Apr;60:348-355.
PMID: 28166895 DOI: 10.1016/j.apergo.2016.12.020

Although much research has been devoted to the characterization of the effects of whole-body vibration on seated occupants' comfort, drowsiness induced by vibration has received less attention to date. There are also little validated measurement methods available to quantify whole body vibration-induced drowsiness. Here, the effects of vibration on drowsiness were investigated. Twenty male volunteers were recruited for this experiment. Drowsiness was measured in a driving simulator, before and after 30-min exposure to vibration. Gaussian random vibration, with 1-15 Hz frequency bandwidth was used for excitation. During the driving session, volunteers were required to obey the speed limit of 100 kph and maintain a steady position on the left-hand lane. A deviation in lane position, steering angle variability, and speed deviation were recorded and analysed. Alternatively, volunteers rated their subjective drowsiness by Karolinska Sleepiness Scale (KSS) scores every 5-min. Following 30-min of exposure to vibration, a significant increase of lane deviation, steering angle variability, and KSS scores were observed in all volunteers suggesting the adverse effects of vibration on human alertness level.

Matched MeSH terms: Computer Simulation
Fulltext Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy-TOPSIS methods

Albahri AS, Hamid RA, Albahri OS, Zaidan AA

Artif Intell Med, 2021 Jan;111:101983.
PMID: 33461683 DOI: 10.1016/j.artmed.2020.101983

CONTEXT AND BACKGROUND: Corona virus (COVID) has rapidly gained a foothold and caused a global pandemic. Particularists try their best to tackle this global crisis. New challenges outlined from various medical perspectives may require a novel design solution. Asymptomatic COVID-19 carriers show different health conditions and no symptoms; hence, a differentiation process is required to avert the risk of chronic virus carriers.
OBJECTIVES: Laboratory criteria and patient dataset are compulsory in constructing a new framework. Prioritisation is a popular topic and a complex issue for patients with COVID-19, especially for asymptomatic carriers due to multi-laboratory criteria, criterion importance and trade-off amongst these criteria. This study presents new integrated decision-making framework that handles the prioritisation of patients with COVID-19 and can detect the health conditions of asymptomatic carriers.
METHODS: The methodology includes four phases. Firstly, eight important laboratory criteria are chosen using two feature selection approaches. Real and simulation datasets from various medical perspectives are integrated to produce a new dataset involving 56 patients with different health conditions and can be used to check asymptomatic cases that can be detected within the prioritisation configuration. The first phase aims to develop a new decision matrix depending on the intersection between 'multi-laboratory criteria' and 'COVID-19 patient list'. In the second phase, entropy is utilised to set the objective weight, and TOPSIS is adapted to prioritise patients in the third phase. Finally, objective validation is performed.
RESULTS: The patients are prioritised based on the selected criteria in descending order of health situation starting from the worst to the best. The proposed framework can discriminate among mild, serious and critical conditions and put patients in a queue while considering asymptomatic carriers. Validation findings revealed that the patients are classified into four equal groups and showed significant differences in their scores, indicating the validity of ranking.
CONCLUSIONS: This study implies and discusses the numerous benefits of the suggested framework in detecting/recognising the health condition of patients prior to discharge, supporting the hospitalisation characteristics, managing patient care and optimising clinical prediction rule.

Matched MeSH terms: Computer Simulation

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