Displaying publications 81 - 100 of 604 in total

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  1. Cardiac glycoside cerberin exerts anticancer activity through PI3K/AKT/mTOR signal transduction inhibition
    Hossan MS, Chan ZY, Collins HM, Shipton FN, Butler MS, Rahmatullah M, et al.
    Cancer Lett, 2019 07 01;453:57-73.
    PMID: 30930233 DOI: 10.1016/j.canlet.2019.03.034
    Natural products possess a significant role in anticancer therapy and many currently-used anticancer drugs are of natural origin. Cerberin (CR), a cardenolide isolated from the fruit kernel of Cerbera odollam, was found to potently inhibit cancer cell growth (GI50 values 60% bioavailability and rapid absorption; doses of 1-10 mg/kg CR were predicted to maintain efficacious unbound plasma concentrations (>GI50 value). CR's potent and selective anti-tumour activity, and its targeting of key signalling mechanisms pertinent to tumourigenesis support further preclinical evaluation of this cardiac glycoside.
    Matched MeSH terms: Computer Simulation
  2. Kinetics based reaction optimization of enzyme catalyzed reduction of formaldehyde to methanol with synchronous cofactor regeneration
    Marpani F, Sárossy Z, Pinelo M, Meyer AS
    Biotechnol Bioeng, 2017 12;114(12):2762-2770.
    PMID: 28832942 DOI: 10.1002/bit.26405
    Enzymatic reduction of carbon dioxide (CO2 ) to methanol (CH3 OH) can be accomplished using a designed set-up of three oxidoreductases utilizing reduced pyridine nucleotide (NADH) as cofactor for the reducing equivalents electron supply. For this enzyme system to function efficiently a balanced regeneration of the reducing equivalents during reaction is required. Herein, we report the optimization of the enzymatic conversion of formaldehyde (CHOH) to CH3 OH by alcohol dehydrogenase, the final step of the enzymatic redox reaction of CO2 to CH3 OH, with kinetically synchronous enzymatic cofactor regeneration using either glucose dehydrogenase (System I) or xylose dehydrogenase (System II). A mathematical model of the enzyme kinetics was employed to identify the best reaction set-up for attaining optimal cofactor recycling rate and enzyme utilization efficiency. Targeted process optimization experiments were conducted to verify the kinetically modeled results. Repetitive reaction cycles were shown to enhance the yield of CH3 OH, increase the total turnover number (TTN) and the biocatalytic productivity rate (BPR) value for both system I and II whilst minimizing the exposure of the enzymes to high concentrations of CHOH. System II was found to be superior to System I with a yield of 8 mM CH3 OH, a TTN of 160 and BPR of 24 μmol CH3 OH/U · h during 6 hr of reaction. The study demonstrates that an optimal reaction set-up could be designed from rational kinetics modeling to maximize the yield of CH3 OH, whilst simultaneously optimizing cofactor recycling and enzyme utilization efficiency.
    Matched MeSH terms: Computer Simulation
  3. Synthesis and biological activity of oxadiazole and triazolothiadiazole derivatives as tyrosinase inhibitors
    Lam KW, Syahida A, Ul-Haq Z, Abdul Rahman MB, Lajis NH
    Bioorg Med Chem Lett, 2010 Jun 15;20(12):3755-9.
    PMID: 20493688 DOI: 10.1016/j.bmcl.2010.04.067
    A series of 16 oxadiazole and triazolothiadiazole derivatives were designed, synthesized and evaluated as mushroom tyrosinase inhibitors. Five derivatives were found to display high inhibition on the tyrosinase activity ranging from 0.87 to 1.49 microM. Compound 5 exhibited highest tyrosinase inhibitory activity with an IC(50) value of 0.87+/-0.16 microM. The in silico protein-ligand docking using AUTODOCK 4.1 was successfully performed on compound 5 with significant binding energy value of -5.58 kcal/mol. The docking results also showed that the tyrosinase inhibition might be due to the metal chelating effect by the presence of thione functionality in compounds 1-5. Further studies revealed that the presence of hydrophobic group such as cycloamine derivatives played a major role in the inhibition. Piperazine moiety in compound 5 appeared to be involved in an extensive hydrophobic contact and a 2.9A hydrogen bonding with residue Glu 182 in the active site.
    Matched MeSH terms: Computer Simulation
  4. Dye degradation, antibacterial and in-silico analysis of Mg/cellulose-doped ZnO nanoparticles
    Ikram M, Mahmood A, Haider A, Naz S, Ul-Hamid A, Nabgan W, et al.
    Int J Biol Macromol, 2021 Aug 31;185:153-164.
    PMID: 34157328 DOI: 10.1016/j.ijbiomac.2021.06.101
    Various concentrations of Mg into fixed amount of cellulose nanocrystals (CNC)-doped ZnO were synthesized using facile chemical precipitation. The aim of present study is to remove dye degradation of methylene blue (MB) and bactericidal behavior with synthesized product. Phase constitution, functional group analysis, optical behavior, elemental composition, morphology and microstructure were examined using XRD, FTIR, UV-Vis spectrophotometer, EDS and HR-TEM. Highly efficient photocatalytic performance was observed in basic medium (98%) relative to neutral (65%), and acidic (83%) was observed upon Mg and CNC co-doping. Significant bactericidal activity of doped ZnO nanoparticles depicted inhibition zones for G -ve and +ve bacteria ranging (2.20 - 4.25 mm) and (5.80-7.25 mm) for E. coli and (1.05 - 2.75 mm) and (2.80 - 4.75 mm) for S. aureus at low and high doses, respectively. Overall, doped nanostructures showed significant (P 
    Matched MeSH terms: Computer Simulation
  5. Fulltext A novel design, analysis and 3D printing of Ti-6Al-4V alloy bio-inspired porous femoral stem
    Mehboob H, Tarlochan F, Mehboob A, Chang SH, Ramesh S, Harun WSW, et al.
    J Mater Sci Mater Med, 2020 Aug 20;31(9):78.
    PMID: 32816091 DOI: 10.1007/s10856-020-06420-7
    The current study is proposing a design envelope for porous Ti-6Al-4V alloy femoral stems to survive under fatigue loads. Numerical computational analysis of these stems with a body-centered-cube (BCC) structure is conducted in ABAQUS. Femoral stems without shell and with various outer dense shell thicknesses (0.5, 1.0, 1.5, and 2 mm) and inner cores (porosities of 90, 77, 63, 47, 30, and 18%) are analyzed. A design space (envelope) is derived by using stem stiffnesses close to that of the femur bone, maximum fatigue stresses of 0.3σys in the porous part, and endurance limits of the dense part of the stems. The Soderberg approach is successfully employed to compute the factor of safety Nf > 1.1. Fully porous stems without dense shells are concluded to fail under fatigue load. It is thus safe to use the porous stems with a shell thickness of 1.5 and 2 mm for all porosities (18-90%), 1 mm shell with 18 and 30% porosities, and 0.5 mm shell with 18% porosity. The reduction in stress shielding was achieved by 28%. Porous stems incorporated BCC structures with dense shells and beads were successfully printed.
    Matched MeSH terms: Computer Simulation
  6. Fulltext A Brief Overview of Potential Treatments for Viral Diseases Using Natural Plant Compounds: The Case of SARS-Cov
    Abiri R, Abdul-Hamid H, Sytar O, Abiri R, Bezerra de Almeida E, Sharma SK, et al.
    Molecules, 2021 Jun 24;26(13).
    PMID: 34202844 DOI: 10.3390/molecules26133868
    The COVID-19 pandemic, as well as the more general global increase in viral diseases, has led researchers to look to the plant kingdom as a potential source for antiviral compounds. Since ancient times, herbal medicines have been extensively applied in the treatment and prevention of various infectious diseases in different traditional systems. The purpose of this review is to highlight the potential antiviral activity of plant compounds as effective and reliable agents against viral infections, especially by viruses from the coronavirus group. Various antiviral mechanisms shown by crude plant extracts and plant-derived bioactive compounds are discussed. The understanding of the action mechanisms of complex plant extract and isolated plant-derived compounds will help pave the way towards the combat of this life-threatening disease. Further, molecular docking studies, in silico analyses of extracted compounds, and future prospects are included. The in vitro production of antiviral chemical compounds from plants using molecular pharming is also considered. Notably, hairy root cultures represent a promising and sustainable way to obtain a range of biologically active compounds that may be applied in the development of novel antiviral agents.
    Matched MeSH terms: Computer Simulation
  7. Fulltext Characterization of α-Glucosidase Inhibitors from Psychotria malayana Jack Leaves Extract Using LC-MS-Based Multivariate Data Analysis and In-Silico Molecular Docking
    Nipun TS, Khatib A, Ibrahim Z, Ahmed QU, Redzwan IE, Saiman MZ, et al.
    Molecules, 2020 Dec 12;25(24).
    PMID: 33322801 DOI: 10.3390/molecules25245885
    Psychotria malayana Jack has traditionally been used to treat diabetes. Despite its potential, the scientific proof in relation to this plant is still lacking. Thus, the present study aimed to investigate the α-glucosidase inhibitors in P.malayana leaf extracts using a metabolomics approach and to elucidate the ligand-protein interactions through in silico techniques. The plant leaves were extracted with methanol and water at five various ratios (100, 75, 50, 25 and 0% v/v; water-methanol). Each extract was tested for α-glucosidase inhibition, followed by analysis using liquid chromatography tandem to mass spectrometry. The data were further subjected to multivariate data analysis by means of an orthogonal partial least square in order to correlate the chemical profile and the bioactivity. The loading plots revealed that the m/z signals correspond to the activity of α-glucosidase inhibitors, which led to the identification of three putative bioactive compounds, namely 5'-hydroxymethyl-1'-(1, 2, 3, 9-tetrahydro-pyrrolo (2, 1-b) quinazolin-1-yl)-heptan-1'-one (1), α-terpinyl-β-glucoside (2), and machaeridiol-A (3). Molecular docking of the identified inhibitors was performed using Auto Dock Vina software against the crystal structure of Saccharomyces cerevisiae isomaltase (Protein Data Bank code: 3A4A). Four hydrogen bonds were detected in the docked complex, involving several residues, namely ASP352, ARG213, ARG442, GLU277, GLN279, HIE280, and GLU411. Compound 1, 2, and 3 showed binding affinity values of -8.3, -7.6, and -10.0 kcal/mol, respectively, which indicate the good binding ability of the compounds towards the enzyme when compared to that of quercetin, a known α-glucosidase inhibitor. The three identified compounds that showed potential binding affinity towards the enzymatic protein in molecular docking interactions could be the bioactive compounds associated with the traditional use of this plant.
    Matched MeSH terms: Computer Simulation
  8. Fulltext Regulation of Proteolytic Activity to Improve the Recovery of Macrobrachium rosenbergii Nodavirus Capsid Protein
    Selvaraj BA, Mariatulqabtiah AR, Ho KL, Ng CL, Yong CY, Tan WS
    Int J Mol Sci, 2021 Aug 13;22(16).
    PMID: 34445426 DOI: 10.3390/ijms22168725
    The causative agent of white tail disease (WTD) in the giant freshwater prawn is Macrobrachium rosenbergii nodavirus (MrNV). The recombinant capsid protein (CP) of MrNV was previously expressed in Escherichia coli, and it self-assembled into icosahedral virus-like particles (VLPs) with a diameter of approximately 30 nm. Extensive studies on the MrNV CP VLPs have attracted widespread attention in their potential applications as biological nano-containers for targeted drug delivery and antigen display scaffolds for vaccine developments. Despite their advantageous features, the recombinant MrNV CP VLPs produced in E. coli are seriously affected by protease degradations, which significantly affect the yield and stability of the VLPs. Therefore, the aim of this study is to enhance the stability of MrNV CP by modulating the protease degradation activity. Edman degradation amino acid sequencing revealed that the proteolytic cleavage occurred at arginine 26 of the MrNV CP. The potential proteases responsible for the degradation were predicted in silico using the Peptidecutter, Expasy. To circumvent proteolysis, specific protease inhibitors (PMSF, AEBSF and E-64) were tested to reduce the degradation rates. Modulation of proteolytic activity demonstrated that a cysteine protease was responsible for the MrNV CP degradation. The addition of E-64, a cysteine protease inhibitor, remarkably improved the yield of MrNV CP by 2.3-fold compared to the control. This innovative approach generates an economical method to improve the scalability of MrNV CP VLPs using individual protease inhibitors, enabling the protein to retain their structural integrity and stability for prominent downstream applications including drug delivery and vaccine development.
    Matched MeSH terms: Computer Simulation
  9. Automated diagnosis of congestive heart failure using dual tree complex wavelet transform and statistical features extracted from 2s of ECG signals
    Sudarshan VK, Acharya UR, Oh SL, Adam M, Tan JH, Chua CK, et al.
    Comput Biol Med, 2017 04 01;83:48-58.
    PMID: 28231511 DOI: 10.1016/j.compbiomed.2017.01.019
    Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant for the prediction of congestive heart failure (CHF). ECG signal analysis carried out using computer-aided techniques can speed up the diagnosis process and aid in the proper management of CHF patients. Therefore, in this work, dual tree complex wavelets transform (DTCWT)-based methodology is proposed for an automated identification of ECG signals exhibiting CHF from normal. In the experiment, we have performed a DTCWT on ECG segments of 2s duration up to six levels to obtain the coefficients. From these DTCWT coefficients, statistical features are extracted and ranked using Bhattacharyya, entropy, minimum redundancy maximum relevance (mRMR), receiver-operating characteristics (ROC), Wilcoxon, t-test and reliefF methods. Ranked features are subjected to k-nearest neighbor (KNN) and decision tree (DT) classifiers for automated differentiation of CHF and normal ECG signals. We have achieved 99.86% accuracy, 99.78% sensitivity and 99.94% specificity in the identification of CHF affected ECG signals using 45 features. The proposed method is able to detect CHF patients accurately using only 2s of ECG signal length and hence providing sufficient time for the clinicians to further investigate on the severity of CHF and treatments.
    Matched MeSH terms: Computer Simulation
  10. Automated characterization of cardiovascular diseases using relative wavelet nonlinear features extracted from ECG signals
    Adam M, Oh SL, Sudarshan VK, Koh JE, Hagiwara Y, Tan JH, et al.
    Comput Methods Programs Biomed, 2018 Jul;161:133-143.
    PMID: 29852956 DOI: 10.1016/j.cmpb.2018.04.018
    Cardiovascular diseases (CVDs) are the leading cause of deaths worldwide. The rising mortality rate can be reduced by early detection and treatment interventions. Clinically, electrocardiogram (ECG) signal provides useful information about the cardiac abnormalities and hence employed as a diagnostic modality for the detection of various CVDs. However, subtle changes in these time series indicate a particular disease. Therefore, it may be monotonous, time-consuming and stressful to inspect these ECG beats manually. In order to overcome this limitation of manual ECG signal analysis, this paper uses a novel discrete wavelet transform (DWT) method combined with nonlinear features for automated characterization of CVDs. ECG signals of normal, and dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM) and myocardial infarction (MI) are subjected to five levels of DWT. Relative wavelet of four nonlinear features such as fuzzy entropy, sample entropy, fractal dimension and signal energy are extracted from the DWT coefficients. These features are fed to sequential forward selection (SFS) technique and then ranked using ReliefF method. Our proposed methodology achieved maximum classification accuracy (acc) of 99.27%, sensitivity (sen) of 99.74%, and specificity (spec) of 98.08% with K-nearest neighbor (kNN) classifier using 15 features ranked by the ReliefF method. Our proposed methodology can be used by clinical staff to make faster and accurate diagnosis of CVDs. Thus, the chances of survival can be significantly increased by early detection and treatment of CVDs.
    Matched MeSH terms: Computer Simulation
  11. Performance of Stochastic Targeted Blood Glucose Control Protocol by virtual trials in the Malaysian intensive care unit
    Jamaludin UK, M Suhaimi F, Abdul Razak NN, Md Ralib A, Mat Nor MB, Pretty CG, et al.
    Comput Methods Programs Biomed, 2018 Aug;162:149-155.
    PMID: 29903481 DOI: 10.1016/j.cmpb.2018.03.001
    BACKGROUND AND OBJECTIVE: Blood glucose variability is common in healthcare and it is not related or influenced by diabetes mellitus. To minimise the risk of high blood glucose in critically ill patients, Stochastic Targeted Blood Glucose Control Protocol is used in intensive care unit at hospitals worldwide. Thus, this study focuses on the performance of stochastic modelling protocol in comparison to the current blood glucose management protocols in the Malaysian intensive care unit. Also, this study is to assess the effectiveness of Stochastic Targeted Blood Glucose Control Protocol when it is applied to a cohort of diabetic patients.

    METHODS: Retrospective data from 210 patients were obtained from a general hospital in Malaysia from May 2014 until June 2015, where 123 patients were having comorbid diabetes mellitus. The comparison of blood glucose control protocol performance between both protocol simulations was conducted through blood glucose fitted with physiological modelling on top of virtual trial simulations, mean calculation of simulation error and several graphical comparisons using stochastic modelling.

    RESULTS: Stochastic Targeted Blood Glucose Control Protocol reduces hyperglycaemia by 16% in diabetic and 9% in nondiabetic cohorts. The protocol helps to control blood glucose level in the targeted range of 4.0-10.0 mmol/L for 71.8% in diabetic and 82.7% in nondiabetic cohorts, besides minimising the treatment hour up to 71 h for 123 diabetic patients and 39 h for 87 nondiabetic patients.

    CONCLUSION: It is concluded that Stochastic Targeted Blood Glucose Control Protocol is good in reducing hyperglycaemia as compared to the current blood glucose management protocol in the Malaysian intensive care unit. Hence, the current Malaysian intensive care unit protocols need to be modified to enhance their performance, especially in the integration of insulin and nutrition intervention in decreasing the hyperglycaemia incidences. Improvement in Stochastic Targeted Blood Glucose Control Protocol in terms of uen model is also a must to adapt with the diabetic cohort.

    Matched MeSH terms: Computer Simulation
  12. Assessing regional left ventricular thickening dysfunction and dyssynchrony via personalized modeling and 3D wall thickness measurements for acute myocardial infarction
    Khalid A, Lim E, Chan BT, Abdul Aziz YF, Chee KH, Yap HJ, et al.
    J Magn Reson Imaging, 2019 04;49(4):1006-1019.
    PMID: 30211445 DOI: 10.1002/jmri.26302
    BACKGROUND: Existing clinical diagnostic and assessment methods could be improved to facilitate early detection and treatment of cardiac dysfunction associated with acute myocardial infarction (AMI) to reduce morbidity and mortality.

    PURPOSE: To develop 3D personalized left ventricular (LV) models and thickening assessment framework for assessing regional wall thickening dysfunction and dyssynchrony in AMI patients.

    STUDY TYPE: Retrospective study, diagnostic accuracy.

    SUBJECTS: Forty-four subjects consisting of 15 healthy subjects and 29 AMI patients.

    FIELD STRENGTH/SEQUENCE: 1.5T/steady-state free precession cine MRI scans; LGE MRI scans.

    ASSESSMENT: Quantitative thickening measurements across all cardiac phases were correlated and validated against clinical evaluation of infarct transmurality by an experienced cardiac radiologist based on the American Heart Association (AHA) 17-segment model.

    STATISTICAL TEST: Nonparametric 2-k related sample-based Kruskal-Wallis test; Mann-Whitney U-test; Pearson's correlation coefficient.

    RESULTS: Healthy LV wall segments undergo significant wall thickening (P 50% transmurality) underwent remarkable wall thinning during contraction (thickening index [TI] = 1.46 ± 0.26 mm) as opposed to healthy myocardium (TI = 4.01 ± 1.04 mm). For AMI patients, LV that showed signs of thinning were found to be associated with a significantly higher percentage of dyssynchrony as compared with healthy subjects (dyssynchrony index [DI] = 15.0 ± 5.0% vs. 7.5 ± 2.0%, P 

    Matched MeSH terms: Computer Simulation
  13. Medroxyprogesterone derivatives from microbial transformation as anti-proliferative agents and acetylcholineterase inhibitors (combined in vitro and in silico approaches)
    Yusop SNW, Imran S, Adenan MI, Sultan S
    Steroids, 2020 12;164:108735.
    PMID: 32976918 DOI: 10.1016/j.steroids.2020.108735
    The fungal transformations of medroxyrogesterone (1) were investigated for the first time using Cunninghamella elegans, Trichothecium roseum, and Mucor plumbeus. The metabolites obtained are as following: 6β, 20-dihydroxymedroxyprogesterone (2), 12β-hydroxymedroxyprogesterone (3), 6β, 11β-dihydroxymedroxyprogesterone (4), 16β-hydroxymedroxyprogesterone (5), 11α, 17-dihydroxy-6α-methylpregn-4-ene-3, 20-dione (6), 11-oxo-medroxyprogesterone (7), 6α-methyl-17α-hydroxypregn-1,4-diene-3,20-dione (8), and 6β-hydroxymedroxyprogesterone (9), 15β-hydroxymedroxyprogesterone (10), 6α-methyl-17α, 11β-dihydroxy-5α-pregnan-3, 20-dione (11), 11β-hydroxymedroxyprogesterone (12), and 11α, 20-dihydroxymedroxyprogesterone (13). Among all the microbial transformed products, the newly isolated biotransformed product 13 showed the most potent activity against proliferation of SH-SY5Y cells. Compounds 12, 5, 6, 9, 11, and 3 (in descending order of activity) also showed some extent of activity against SH-SY5Y tumour cell line. The never been reported biotransformed product, 2, showed the most potent inhibitory activity against acetylcholinesterase. Molecular modelling studies were carried out to understand the observed experimental activities, and also to obtain more information on the binding mode and the interactions between the biotransformed products, and enzyme.
    Matched MeSH terms: Computer Simulation
  14. Influence of omega fatty acids on skin permeation of a coenzyme Q10 nanoemulsion cream formulation: characterization, in silico and ex vivo determination
    Tou KAS, Rehman K, Ishak WMW, Zulfakar MH
    Drug Dev Ind Pharm, 2019 Sep;45(9):1451-1458.
    PMID: 31216907 DOI: 10.1080/03639045.2019.1628042
    Objective: The aim of this study was to develop a coenzyme Q10 nanoemulsion cream, characterize and to determine the influence of omega fatty acids on the delivery of coenzyme Q10 across model skin membrane via ex vivo and in silico techniques. Methods: Coenzyme Q10 nanoemulsion creams were prepared using natural edible oils such as linseed, evening primrose, and olive oil. Their mechanical features and ability to deliver CoQ10 across rat skin were characterized. Computational docking analysis was performed for in silico evaluation of CoQ10 and omega fatty acid interactions. Results: Linseed, evening primrose, and olive oils each produced nano-sized emulsion creams (343.93-409.86 nm) and exhibited excellent rheological features. The computerized docking studies showed favorable interactions between CoQ10 and omega fatty acids that could improve skin permeation. The three edible-oil nanoemulsion creams displayed higher ex vivo skin permeation and drug flux compared to the liquid-paraffin control cream. The linseed oil formulation displayed the highest skin permeation (3.97 ± 0.91 mg/cm2) and drug flux (0.19 ± 0.05 mg/cm2/h). Conclusion: CoQ10 loaded-linseed oil nanoemulsion cream displayed the highest skin permeation. The highest permeation showed by linseed oil nanoemulsion cream may be due to the presence of omega-3, -6, and -9 fatty acids which might serve as permeation enhancers. This indicated that the edible oil nanoemulsion creams have potential as drug vehicles that enhance CoQ10 delivery across skin.
    Matched MeSH terms: Computer Simulation
  15. Fulltext Optimization: Molecular Communication Networks for Viral Disease Analysis Using Deep Leaning Autoencoder
    Junejo AR, Kaabar MKA, Li X
    Comput Math Methods Med, 2021;2021:9949328.
    PMID: 34938362 DOI: 10.1155/2021/9949328
    Developing new treatments for emerging infectious diseases in infectious and noninfectious diseases has attracted a particular attention. The emergence of viral diseases is expected to accelerate; these data indicate the need for a proactive approach to develop widely active family specific and cross family therapies for future disease outbreaks. Viral disease such as pneumonia, severe acute respiratory syndrome type 2, HIV infection, and Hepatitis-C virus can cause directly and indirectly cardiovascular disease (CVD). Emphasis should be placed not only on the development of broad-spectrum molecules and antibodies but also on host factor therapy, including the reutilization of previously approved or developing drugs. Another new class of therapeutics with great antiviral therapeutic potential is molecular communication networks using deep learning autoencoder (DL-AEs). The use of DL-AEs for diagnosis and prognosis prediction of infectious and noninfectious diseases has attracted a particular attention. MCN is map to molecular signaling and communication that are found inside and outside the human body where the goal is to develop a new black box mechanism that can serve the future robust healthcare industry (HCI). MCN has the ability to characterize the signaling process between cells and infectious disease locations at various levels of the human body called point-to-point MCN through DL-AE and provide targeted drug delivery (TDD) environment. Through MCN, and DL-AE healthcare provider can remotely measure biological signals and control certain processes in the required organism for the maintenance of the patient's health state. We use biomicrodevices to promote the real-time monitoring of human health and storage of the gathered data in the cloud. In this paper, we use the DL-based AE approach to design and implement a new drug source and target for the MCN under white Gaussian noise. Simulation results show that transceiver executions for a given medium model that reduces the bit error rate which can be learned. Then, next development of molecular diagnosis such as heart sounds is classified. Furthermore, biohealth interface for the inside and outside human body mechanism is presented, comparative perspective with up-to-date current situation about MCN.
    Matched MeSH terms: Computer Simulation
  16. Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA
    Javed E, Faye I, Malik AS, Abdullah JM
    J Neurosci Methods, 2017 11 01;291:150-165.
    PMID: 28842191 DOI: 10.1016/j.jneumeth.2017.08.020
    BACKGROUND: Simultaneous electroencephalography (EEG) and functional magnetic resonance image (fMRI) acquisitions provide better insight into brain dynamics. Some artefacts due to simultaneous acquisition pose a threat to the quality of the data. One such problematic artefact is the ballistocardiogram (BCG) artefact.

    METHODS: We developed a hybrid algorithm that combines features of empirical mode decomposition (EMD) with principal component analysis (PCA) to reduce the BCG artefact. The algorithm does not require extra electrocardiogram (ECG) or electrooculogram (EOG) recordings to extract the BCG artefact.

    RESULTS: The method was tested with both simulated and real EEG data of 11 participants. From the simulated data, the similarity index between the extracted BCG and the simulated BCG showed the effectiveness of the proposed method in BCG removal. On the other hand, real data were recorded with two conditions, i.e. resting state (eyes closed dataset) and task influenced (event-related potentials (ERPs) dataset). Using qualitative (visual inspection) and quantitative (similarity index, improved normalized power spectrum (INPS) ratio, power spectrum, sample entropy (SE)) evaluation parameters, the assessment results showed that the proposed method can efficiently reduce the BCG artefact while preserving the neuronal signals.

    COMPARISON WITH EXISTING METHODS: Compared with conventional methods, namely, average artefact subtraction (AAS), optimal basis set (OBS) and combined independent component analysis and principal component analysis (ICA-PCA), the statistical analyses of the results showed that the proposed method has better performance, and the differences were significant for all quantitative parameters except for the power and sample entropy.

    CONCLUSIONS: The proposed method does not require any reference signal, prior information or assumption to extract the BCG artefact. It will be very useful in circumstances where the reference signal is not available.

    Matched MeSH terms: Computer Simulation
  17. Humanization of chimeric anti-CD20 antibody by logical and bioinformatics approach with retention of biological activity
    Khoo YL, Cheah SH, Chong H
    Immunotherapy, 2017 06;9(7):567-577.
    PMID: 28595518 DOI: 10.2217/imt-2017-0016
    AIM: To develop a fully bioactive humanized antibody from the chimeric rituximab for potential clinical applications using a relatively simpler and faster logical and bioinformatics approach.

    METHODS: From bioinformatics data, mismatched mouse amino acids in variable light and heavy chain amphipathic regions were identified and substituted with those common to human antibody framework. Appropriate synthetic DNA sequences inserted into vectors were transfected into HEK293 cells to produce the humanized antibody.

    RESULTS: Humanized antibodies showed specific binding to CD20 and greater cytotoxicity to cancer WIL2-NS cell proliferation than rituximab in vitro.

    CONCLUSION: A humanized version of rituximab with potential to be developed into a biobetter for treatment of B-cell disorders has been successfully generated using a logical and bioinformatics approach.

    Matched MeSH terms: Computer Simulation
  18. Fulltext CORNAS: coverage-dependent RNA-Seq analysis of gene expression data without biological replicates
    Low JZB, Khang TF, Tammi MT
    BMC Bioinformatics, 2017 12 28;18(Suppl 16):575.
    PMID: 29297307 DOI: 10.1186/s12859-017-1974-4
    BACKGROUND: In current statistical methods for calling differentially expressed genes in RNA-Seq experiments, the assumption is that an adjusted observed gene count represents an unknown true gene count. This adjustment usually consists of a normalization step to account for heterogeneous sample library sizes, and then the resulting normalized gene counts are used as input for parametric or non-parametric differential gene expression tests. A distribution of true gene counts, each with a different probability, can result in the same observed gene count. Importantly, sequencing coverage information is currently not explicitly incorporated into any of the statistical models used for RNA-Seq analysis.

    RESULTS: We developed a fast Bayesian method which uses the sequencing coverage information determined from the concentration of an RNA sample to estimate the posterior distribution of a true gene count. Our method has better or comparable performance compared to NOISeq and GFOLD, according to the results from simulations and experiments with real unreplicated data. We incorporated a previously unused sequencing coverage parameter into a procedure for differential gene expression analysis with RNA-Seq data.

    CONCLUSIONS: Our results suggest that our method can be used to overcome analytical bottlenecks in experiments with limited number of replicates and low sequencing coverage. The method is implemented in CORNAS (Coverage-dependent RNA-Seq), and is available at https://github.com/joel-lzb/CORNAS .

    Matched MeSH terms: Computer Simulation
  19. Fulltext The heterospecific calling song can improve conspecific signal detection in a bushcricket species
    Abdelatti ZAS, Hartbauer M
    Hear Res, 2017 11;355:70-80.
    PMID: 28974384 DOI: 10.1016/j.heares.2017.09.011
    In forest clearings of the Malaysian rainforest, chirping and trilling Mecopoda species often live in sympatry. We investigated whether a phenomenon known as stochastic resonance (SR) improved the ability of individuals to detect a low-frequent signal component typical of chirps when members of the heterospecific trilling species were simultaneously active. This phenomenon may explain the fact that the chirping species upholds entrainment to the conspecific song in the presence of the trill. Therefore, we evaluated the response probability of an ascending auditory neuron (TN-1) in individuals of the chirping Mecopoda species to triple-pulsed 2, 8 and 20 kHz signals that were broadcast 1 dB below the hearing threshold while increasing the intensity of either white noise or a typical triller song. Our results demonstrate the existence of SR over a rather broad range of signal-to-noise ratios (SNRs) of input signals when periodic 2 kHz and 20 kHz signals were presented at the same time as white noise. Using the chirp-specific 2 kHz signal as a stimulus, the maximum TN-1 response probability frequently exceeded the 50% threshold if the trill was broadcast simultaneously. Playback of an 8 kHz signal, a common frequency band component of the trill, yielded a similar result. Nevertheless, using the trill as a masker, the signal-related TN-1 spiking probability was rather variable. The variability on an individual level resulted from correlations between the phase relationship of the signal and syllables of the trill. For the first time, these results demonstrate the existence of SR in acoustically-communicating insects and suggest that the calling song of heterospecifics may facilitate the detection of a subthreshold signal component in certain situations. The results of the simulation of sound propagation in a computer model suggest a wide range of sender-receiver distances in which the triller can help to improve the detection of subthreshold signals in the chirping species.
    Matched MeSH terms: Computer Simulation
  20. Stress distributions in maxillary central incisors restored with various types of post materials and designs
    Madfa AA, Kadir MR, Kashani J, Saidin S, Sulaiman E, Marhazlinda J, et al.
    Med Eng Phys, 2014 Jul;36(7):962-7.
    PMID: 24834856 DOI: 10.1016/j.medengphy.2014.03.018
    Different dental post designs and materials affect the stability of restoration of a tooth. This study aimed to analyse and compare the stability of two shapes of dental posts (parallel-sided and tapered) made of five different materials (titanium, zirconia, carbon fibre and glass fibre) by investigating their stress transfer through the finite element (FE) method. Ten three-dimensional (3D) FE models of a maxillary central incisor restored with two different designs and five different materials were constructed. An oblique loading of 100 N was applied to each 3D model. Analyses along the centre of the post, the crown-cement/core and the post-cement/dentine interfaces were computed, and the means were calculated. One-way ANOVAs followed by post hoc tests were used to evaluate the effectiveness of the post materials and designs (p=0.05). For post designs, the tapered posts introduced significantly higher stress compared with the parallel-sided post (p<0.05), especially along the centre of the post. Of the materials, the highest level of stress was found for stainless steel, followed by zirconia, titanium, glass fibre and carbon fibre posts (p<0.05). The carbon and glass fibre posts reduced the stress distribution at the middle and apical part of the posts compared with the stainless steel, zirconia and titanium posts. The opposite results were observed at the crown-cement/core interface.
    Matched MeSH terms: Computer Simulation
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