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  1. Fulltext Acacia honey accelerates in vitro corneal ulcer wound healing model
    Abd Ghafar N, Ker-Woon C, Hui CK, Mohd Yusof YA, Wan Ngah WZ
    BMC Complement Altern Med, 2016 Jul 29;16:259.
    PMID: 27473120 DOI: 10.1186/s12906-016-1248-0
    BACKGROUND: The study aimed to evaluate the effects of Acacia honey (AH) on the migration, differentiation and healing properties of the cultured rabbit corneal fibroblasts.

    METHODS: Stromal derived corneal fibroblasts from New Zealand White rabbit (n = 6) were isolated and cultured until passage 1. In vitro corneal ulcer was created using a 4 mm corneal trephine onto confluent cultures and treated with basal medium (FD), medium containing serum (FDS), with and without 0.025 % AH. Wound areas were recorded at day 0, 3 and 6 post wound creation. Genes and proteins associated with wound healing and differentiation such as aldehyde dehydrogenase (ALDH), vimentin, alpha-smooth muscle actin (α-SMA), collagen type I, lumican and matrix metalloproteinase 12 (MMP12) were evaluated using qRT-PCR and immunocytochemistry respectively.

    RESULTS: Cells cultured with AH-enriched FDS media achieved complete wound closure at day 6 post wound creation. The cells cultured in AH-enriched FDS media increased the expression of vimentin, collagen type I and lumican genes and decreased the ALDH, α-SMA and MMP12 gene expressions. Protein expression of ALDH, vimentin and α-SMA were in accordance with the gene expression analyses.

    CONCLUSION: These results demonstrated AH accelerate corneal fibroblasts migration and differentiation of the in vitro corneal ulcer model while increasing the genes and proteins associated with stromal wound healing.

    Matched MeSH terms: Models, Biological
  2. Biomechanical characterisation of ovine spinal facet joint cartilage
    Abd Latif MJ, Jin Z, Wilcox RK
    J Biomech, 2012 May 11;45(8):1346-52.
    PMID: 22483055 DOI: 10.1016/j.jbiomech.2012.03.015
    The spinal facet joints are known to be an important component in the kinematics and the load transmission of the spine. The articular cartilage in the facet joint is prone to degenerative changes which lead to back pain and treatments for the condition have had limited long term success. There is currently a lack of information on the basic biomechanical properties of the facet joint cartilage which is needed to develop tissue substitution or regenerative interventions. In the present study, the thickness and biphasic properties of ovine facet cartilage were determined using a combination of indentation tests and computational modelling. The equilibrium biphasic Young's modulus and permeability were derived to be 0.76±0.35 MPa and 1.61±1.10×10⁻¹⁵ m⁴/(Ns) respectively, which were within the range of cartilage properties characterised from the human synovial joints. The average thickness of the ovine facet cartilage was 0.52±0.10 mm, which was measured using a needle indentation test. These properties could potentially be used for the development of substitution or tissue engineering interventions and for computational modelling of the facet joint. Furthermore, the developed method to characterise the facet cartilage could be used for other animals or human donors.
    Matched MeSH terms: Models, Biological*
  3. Development of improved dosing regimens for mycophenolate mofetil based on population pharmacokinetic analyses in adults with lupus nephritis
    Abd Rahman AN, Tett SE, Abdul Gafor HA, McWhinney BC, Staatz CE
    Eur J Drug Metab Pharmacokinet, 2017 Dec;42(6):993-1004.
    PMID: 28536776 DOI: 10.1007/s13318-017-0420-3
    BACKGROUND AND OBJECTIVE: Mycophenolic acid (MPA) provides effective treatment for lupus nephritis patients. Owing to its large pharmacokinetic variability, it is questionable whether standard fixed dose therapy can achieve optimal MPA exposure. The aim of this study was to develop a population pharmacokinetic model of MPA and its metabolite, 7-O-MPA-β-glucuronide (MPAG), to identify important covariate influences and better predict patient dosing requirements.
    METHODS: MPA and MPAG concentration-time profiles were collected from 25 patients receiving mycophenolate mofetil (MMF) with or without cyclosporine (CsA) co-therapy. Samples were collected pre-dose and at 1, 2, 4, 6 and 8 h post-dose on one or two occasions.
    RESULTS: A total of 225 and 226 concentration-time measurements of MPA and MPAG, respectively, were used to develop the model, utilizing NONMEM® software. A two-compartment model with first-order absorption and elimination for MPA and a one-compartment model with first-order elimination and enterohepatic circulation (EHC) for MPAG best described the data. Apparent clearance of MPAG (CL/F MPAG) significantly decreased with reducing renal function and extent of EHC was reduced with concomitant CsA use. Simulations using the final model showed that a 70-kg subject with a creatinine clearance of 90 mL/min receiving concomitant CsA would require 1.25 g of MMF twice daily while a similar subject who did not receive concomitant CsA would require 0.75 g twice daily to achieve a MPA area under the concentration-time curve from 0 to 12 h (AUC0-12) of 45 mg·h/L.
    CONCLUSION: A 'tiered' dosing approach considering patient renal function and CsA co-therapy, rather than a 'one dose fits all' approach, would help individualize MMF therapy in adult lupus nephritis patients to ensure more patients have optimal MPA exposure.
    Study site: Nephrology and Systemic Lupus Erythematosus (SLE) Clinics, Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM), Kuala Lumpur, Malaysia
    Matched MeSH terms: Models, Biological
  4. Modelling induced resistance to plant diseases
    Abdul Latif NS, Wake GC, Reglinski T, Elmer PA
    J Theor Biol, 2014 Apr 21;347:144-50.
    PMID: 24398025 DOI: 10.1016/j.jtbi.2013.12.023
    Plant disease control has traditionally relied heavily on the use of agrochemicals despite their potentially negative impact on the environment. An alternative strategy is that of induced resistance (IR). However, while IR has proven effective in controlled environments, it has shown variable field efficacy, thus raising questions about its potential for disease management in a given crop. Mathematical modelling of IR assists researchers with understanding the dynamics of the phenomenon in a given plant cohort against a selected disease-causing pathogen. Here, a prototype mathematical model of IR promoted by a chemical elicitor is proposed and analysed. Standard epidemiological models describe that, under appropriate environmental conditions, Susceptible plants (S) may become Diseased (D) upon exposure to a compatible pathogen or are able to Resist the infection (R) via basal host defence mechanisms. The application of an elicitor enhances the basal defence response thereby affecting the relative proportion of plants in each of the S, R and D compartments. IR is a transient response and is modelled using reversible processes to describe the temporal evolution of the compartments. Over time, plants can move between these compartments. For example, a plant in the R-compartment can move into the S-compartment and can then become diseased. Once in the D-compartment, however, it is assumed that there is no recovery. The terms in the equations are identified using established principles governing disease transmission and this introduces parameters which are determined by matching data to the model using computer-based algorithms. These then give the best match of the model with experimental data. The model predicts the relative proportion of plants in each compartment and quantitatively estimates elicitor effectiveness. An illustrative case study will be given; however, the model is generic and will be applicable for a range of plant-pathogen-elicitor scenarios.
    Matched MeSH terms: Models, Biological*
  5. Fulltext A modified active appearance model based on an adaptive artificial bee colony
    Abdulameer MH, Sheikh Abdullah SN, Othman ZA
    ScientificWorldJournal, 2014;2014:879031.
    PMID: 25165748 DOI: 10.1155/2014/879031
    Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.
    Matched MeSH terms: Models, Biological*
  6. 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*
  7. 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*
  8. Predicting points of departure for risk assessment based on in vitro cytotoxicity data and physiologically based kinetic (PBK) modeling: The case of kidney toxicity induced by aristolochic acid I
    Abdullah R, Alhusainy W, Woutersen J, Rietjens IM, Punt A
    Food Chem Toxicol, 2016 Jun;92:104-16.
    PMID: 27016491 DOI: 10.1016/j.fct.2016.03.017
    Aristolochic acids are naturally occurring nephrotoxins. This study aims to investigate whether physiologically based kinetic (PBK) model-based reverse dosimetry could convert in vitro concentration-response curves of aristolochic acid I (AAI) to in vivo dose response-curves for nephrotoxicity in rat, mouse and human. To achieve this extrapolation, PBK models were developed for AAI in these different species. Subsequently, concentration-response curves obtained from in vitro cytotoxicity models were translated to in vivo dose-response curves using PBK model-based reverse dosimetry. From the predicted in vivo dose-response curves, points of departure (PODs) for risk assessment could be derived. The PBK models elucidated species differences in the kinetics of AAI with the overall catalytic efficiency for metabolic conversion of AAI to aristolochic acid Ia (AAIa) being 2-fold higher for rat and 64-fold higher for mouse than human. Results show that the predicted PODs generally fall within the range of PODs derived from the available in vivo studies. This study provides proof of principle for a new method to predict a POD for in vivo nephrotoxicity by integrating in vitro toxicity testing with in silico PBK model-based reverse dosimetry.
    Matched MeSH terms: Models, Biological
  9. Fulltext Defining in vivo dose-response curves for kidney DNA adduct formation of aristolochic acid I in rat, mouse and human by an in vitro and physiologically based kinetic modeling approach
    Abdullah R, Wesseling S, Spenkelink B, Louisse J, Punt A, Rietjens IMCM
    J Appl Toxicol, 2020 12;40(12):1647-1660.
    PMID: 33034907 DOI: 10.1002/jat.4024
    Aristolochic acid I (AAI) is a well-known genotoxic kidney carcinogen. Metabolic conversion of AAI into the DNA-reactive aristolactam-nitrenium ion is involved in the mode of action of tumor formation. This study aims to predict in vivo AAI-DNA adduct formation in the kidney of rat, mouse and human by translating the in vitro concentration-response curves for AAI-DNA adduct formation to the in vivo situation using physiologically based kinetic (PBK) modeling-based reverse dosimetry. DNA adduct formation in kidney proximal tubular LLC-PK1 cells exposed to AAI was quantified by liquid chromatography-electrospray ionization-tandem mass spectrometry. Subsequently, the in vitro concentration-response curves were converted to predicted in vivo dose-response curves in rat, mouse and human kidney using PBK models. Results obtained revealed a dose-dependent increase in AAI-DNA adduct formation in the rat, mouse and human kidney and the predicted DNA adduct levels were generally within an order of magnitude compared with values reported in the literature. It is concluded that the combined in vitro PBK modeling approach provides a novel way to define in vivo dose-response curves for kidney DNA adduct formation in rat, mouse and human and contributes to the reduction, refinement and replacement of animal testing.
    Matched MeSH terms: Models, Biological*
  10. Stochastic models in seed dispersals: random walks and birth-death processes
    Abdullahi A, Shohaimi S, Kilicman A, Ibrahim MH
    J Biol Dyn, 2019 12;13(1):345-361.
    PMID: 31056007 DOI: 10.1080/17513758.2019.1605003
    Seed dispersals deal with complex systems through which the data collected using advanced seed tracking facilities pose challenges to conventional approaches, such as empirical and deterministic models. The use of stochastic models in current seed dispersal studies is encouraged. This review describes three existing stochastic models: the birth-death process (BDP), a 2 dimensional (
    2

    D

    ) symmetric random walks and a
    2

    D

    intermittent walks. The three models possess Markovian property, which make them flexible for studying natural phenomena. Only a few of applications in ecology are found in seed dispersals. The review illustrates how the models are to be used in seed dispersals context. Using the nonlinear BDP, we formulate the individual-based models for two competing plant species while the cover time model is formulated by the symmetric and intermittent random walks. We also show that these three stochastic models can be formulated using the Gillespie algorithm. The full cover time obtained by the symmetric random walks can approximate the Gumbel distribution pattern as the other searching strategies do. We suggest that the applications of these models in seed dispersals may lead to understanding of many complex systems, such as the seed removal experiments and behaviour of foraging agents, among others.
    Matched MeSH terms: Models, Biological*
  11. Optimal control strategies for dengue fever spread in Johor, Malaysia
    Abidemi A, Aziz NAB
    Comput Methods Programs Biomed, 2020 Nov;196:105585.
    PMID: 32554024 DOI: 10.1016/j.cmpb.2020.105585
    Background Dengue is a vector-borne viral disease endemic in Malaysia. The disease is presently a public health issue in the country. Hence, the use of mathematical model to gain insights into the transmission dynamics and derive the optimal control strategies for minimizing the spread of the disease is of great importance. Methods A model involving eight mutually exclusive compartments with the introduction of personal protection, larvicide and adulticide control strategies describing dengue fever transmission dynamics is presented. The control-induced basic reproduction number (R˜0) related to the model is computed using the next generation matrix method. Comparison theorem is used to analyse the global dynamics of the model. The model is fitted to the data related to the 2012 dengue outbreak in Johor, Malaysia, using the least-squares method. In a bid to optimally curtail dengue fever propagation, we apply optimal control theory to investigate the effect of several control strategies of combination of optimal personal protection, larvicide and adulticide controls on dengue fever dynamics. The resulting optimality system is simulated in MATLAB using fourth order Runge-Kutta scheme based on the forward-backward sweep method. In addition, cost-effectiveness analysis is performed to determine the most cost-effective strategy among the various control strategies analysed. Results Analysis of the model with control parameters shows that the model has two disease-free equilibria, namely, trivial equilibrium and biologically realistic disease-free equilibrium, and one endemic equilibrium point. It also reveals that the biologically realistic disease-free equilibrium is both locally and globally asymptotically stable whenever the inequality R˜0<1holds. In the case of model with time-dependent control functions, the optimality levels of the three control functions required to optimally control dengue disease transmission are derived. Conclusion We conclude that dengue fever transmission can be curtailed by adopting any of the several control strategies analysed in this study. Furthermore, a strategy which combines personal protection and adulticide controls is found to be the most cost-effective control strategy.
    Matched MeSH terms: Models, Biological
  12. Fulltext Combating obesity through healthy eating behavior: a call for system dynamics optimization
    Abidin NZ, Mamat M, Dangerfield B, Zulkepli JH, Baten MA, Wibowo A
    PLoS One, 2014;9(12):e114135.
    PMID: 25502170 DOI: 10.1371/journal.pone.0114135
    Poor eating behavior has been identified as one of the core contributory factors of the childhood obesity epidemic. The consequences of obesity on numerous aspects of life are thoroughly explored in the existing literature. For instance, evidence shows that obesity is linked to incidences of diseases such as heart disease, type-2 diabetes, and some cancers, as well as psychosocial problems. To respond to the increasing trends in the UK, in 2008 the government set a target to reverse the prevalence of obesity (POB) back to 2000 levels by 2020. This paper will outline the application of system dynamics (SD) optimization to simulate the effect of changes in the eating behavior of British children (aged 2 to 15 years) on weight and obesity. This study also will identify how long it will take to achieve the government's target. This paper proposed a simulation model called Intervention Childhood Obesity Dynamics (ICOD) by focusing the interrelations between various strands of knowledge in one complex human weight regulation system. The model offers distinct insights into the dynamics by capturing the complex interdependencies from the causal loop and feedback structure, with the intention to better understand how eating behaviors influence children's weight, body mass index (BMI), and POB measurement. This study proposed a set of equations that are revised from the original (baseline) equations. The new functions are constructed using a RAMP function of linear decrement in portion size and number of meal variables from 2013 until 2020 in order to achieve the 2020 desired target. Findings from the optimization analysis revealed that the 2020 target won't be achieved until 2026 at the earliest, six years late. Thus, the model suggested that a longer period may be needed to significantly reduce obesity in this population.
    Matched MeSH terms: Models, Biological
  13. Fulltext Biological age for chronic kidney disease patients using index model
    Abu Bakar SA, Syed Mohamed Shahruddin SNS, Ismail N, Wan Md Adnan WAH
    PeerJ, 2022;10:e13694.
    PMID: 35935256 DOI: 10.7717/peerj.13694
    The estimation of biological age (BA) is an important asymptomatic measure that can be used to understand the physical changes and the aging process of a living being. Factors that contribute towards profiling the human biological age can be diverse. Therefore, this study focuses on developing a BA model for patients with Chronic Kidney Disease (CKD). The procedure commences with the selection of significant biomarkers using a correlation test. Appropriate weighting is then assigned to each selected biomarker using the indexing method to produce a BA index. The BA index is matched to the age variation within the sample to acquire additional terms for the chronological age leading ultimately to the estimated BA. From a sample of 190 patients (133 trained data and 57 testing data) obtained from the University of Malaya Medical Centre (UMMC), Malaysia, the intensity of the BA is found to be between three to nine years from the chronological age. Visual observations further validate the high similarities between the training and testing data sets.
    Matched MeSH terms: Models, Biological
  14. Obesity, metabolic syndrome, adipocytes and vascular function: A holistic viewpoint
    Achike FI, To NH, Wang H, Kwan CY
    Clin Exp Pharmacol Physiol, 2011 Jan;38(1):1-10.
    PMID: 21083697 DOI: 10.1111/j.1440-1681.2010.05460.x
    1. Obesity is a metabolic disease of pandemic proportions largely arising from positive energy balance, a consequence of sedentary lifestyle, conditioned by environmental and genetic factors. Several central and peripheral neurohumoral factors (the major ones being the anorectic adipokines leptin and adiponecin and the orexigenic gut hormone ghrelin) acting on the anorectic (pro-opiomelanocortin and cocaine- and amphetamine-regulated transcript) and orexigenic (neuropeptide Y and agouti gene-related protein) neurons regulate energy balance. These neurons, mainly in the arcuate nucleus of the hypothalamus, project to parts of the brain modulating functions such as wakefulness, autonomic function and learning. A tilt in the anorectic-orexigenic balance, perhaps determined genetically, leads to obesity. 2. Excess fat deposition requires space, created by adipocyte (hypertrophy and hyperplasia) and extracellular matrix (ECM) remodelling. This process is regulated by several factors, including several adipocyte-derived Matrix metalloproteinases and the adipokine cathepsin, which degrades fibronectin, a key ECM protein. Excess fat, also deposited in visceral organs, generates chronic low-grade inflammation that eventually triggers insulin resistance and the associated comorbidities of metabolic syndrome (hypertension, atherosclerosis, dyslipidaemia and diabetes mellitus). 3. The perivascular adipose tissue (PVAT) has conventionally been considered non-physiological structural tissue, but has recently been shown to serve a paracrine function, including the release of adipose-derived relaxant and contractile factors, akin to the role of the vascular endothelium. Thus, PVAT regulates vascular function in vivo and in vitro, contributing to the cardiovascular pathophysiology of the metabolic syndrome. Defining the mechanism of PVAT regulation of vascular reactivity requires more and better controlled investigations than currently seen in the literature.
    Matched MeSH terms: Models, Biological
  15. Fulltext In vitro and in vivo anti-inflammatory activity of 17-O-acetylacuminolide through the inhibition of cytokines, NF-κB translocation and IKKβ activity
    Achoui M, Appleton D, Abdulla MA, Awang K, Mohd MA, Mustafa MR
    PLoS One, 2010;5(12):e15105.
    PMID: 21152019 DOI: 10.1371/journal.pone.0015105
    17-O-acetylacuminolide (AA), a diterpenoid labdane, was isolated for the first time from the plant species Neouvaria foetida. The anti-inflammatory effects of this compound were studied both in vitro and in vivo.
    Matched MeSH terms: Models, Biological
  16. In utero Exposure to Germinated Brown Rice and Its GABA Extract Attenuates High-Fat-Diet-Induced Insulin Resistance in Rat Offspring
    Adamu HA, Imam MU, Der-Jiun O, Ismail M
    J Nutrigenet Nutrigenomics, 2017;10(1-2):19-31.
    PMID: 28399529 DOI: 10.1159/000469663
    BACKGROUND: Numerous studies have reported on the influence of diet on insulin resistance. Our study provides insight into the effect of germinated brown rice (GBR) and γ-aminobutyric acid (GABA) on early environment-driven programming and susceptibility to insulin resistance in rat offspring.

    METHODS: Male rat offspring from female Sprague-Dawley rats fed with a high-fat diet (HFD) alone, HFD + GBR, or HFD + GABA extract throughout pregnancy and lactation were weaned 4 weeks after delivery and followed up for 8 weeks. A biochemical analysis and an assessment of the hepatic expression of insulin signaling genes were performed.

    RESULTS: The results showed that intrauterine exposure to HFD caused metabolic perturbations in rat offspring which gravitated towards insulin resistance even though the rat offspring did not consume an HFD. GBR and GABA attenuated the HFD-induced changes by underlying regulation of the insulin signaling genes.

    CONCLUSIONS: The results suggest that intake of GBR and GABA during pregnancy and lactation can influence the programming of genes in rat offspring, thereby enhancing insulin sensitivity.

    Matched MeSH terms: Models, Biological
  17. Fulltext CFD study on NACA 4415 airfoil implementing spherical and sinusoidal Tubercle Leading Edge
    Aftab SMA, Ahmad KA
    PLoS One, 2017;12(8):e0183456.
    PMID: 28850622 DOI: 10.1371/journal.pone.0183456
    The Humpback whale tubercles have been studied for more than a decade. Tubercle Leading Edge (TLE) effectively reduces the separation bubble size and helps in delaying stall. They are very effective in case of low Reynolds number flows. The current Computational Fluid Dynamics (CFD) study is on NACA 4415 airfoil, at a Reynolds number 120,000. Two TLE shapes are tested on NACA 4415 airfoil. The tubercle designs implemented on the airfoil are sinusoidal and spherical. A parametric study is also carried out considering three amplitudes (0.025c, 0.05c and 0.075c), the wavelength (0.25c) is fixed. Structured mesh is utilized to generate grid and Transition SST turbulence model is used to capture the flow physics. Results clearly show spherical tubercles outperform sinusoidal tubercles. Furthermore experimental study considering spherical TLE is carried out at Reynolds number 200,000. The experimental results show that spherical TLE improve performance compared to clean airfoil.
    Matched MeSH terms: Models, Biological*
  18. Theoretically-derived molecular descriptors important in human intestinal absorption
    Agatonovic-Kustrin S, Beresford R, Yusof AP
    J Pharm Biomed Anal, 2001 May;25(2):227-37.
    PMID: 11275432
    A quantitative structure-human intestinal absorption relationship was developed using artificial neural network (ANN) modeling. A set of 86 drug compounds and their experimentally-derived intestinal absorption values used in this study was gathered from the literature and a total of 57 global molecular descriptors, including constitutional, topological, chemical, geometrical and quantum chemical descriptors, calculated for each compound. A supervised network with radial basis transfer function was used to correlate calculated molecular descriptors with experimentally-derived measures of human intestinal absorption. A genetic algorithm was then used to select important molecular descriptors. Intestinal absorption values (IA%) were used as the ANN's output and calculated molecular descriptors as the inputs. The best genetic neural network (GNN) model with 15 input descriptors was chosen, and the significance of the selected descriptors for intestinal absorption examined. Results obtained with the model that was developed indicate that lipophilicity, conformational stability and inter-molecular interactions (polarity, and hydrogen bonding) have the largest impact on intestinal absorption.
    Matched MeSH terms: Models, Biological
  19. Fulltext Factors determining dengue outbreak in Malaysia
    Ahmad R, Suzilah I, Wan Najdah WMA, Topek O, Mustafakamal I, Lee HL
    PLoS One, 2018;13(2):e0193326.
    PMID: 29474401 DOI: 10.1371/journal.pone.0193326
    A large scale study was conducted to elucidate the true relationship among entomological, epidemiological and environmental factors that contributed to dengue outbreak in Malaysia. Two large areas (Selayang and Bandar Baru Bangi) were selected in this study based on five consecutive years of high dengue cases. Entomological data were collected using ovitraps where the number of larvae was used to reflect Aedes mosquito population size; followed by RT-PCR screening to detect and serotype dengue virus in mosquitoes. Notified cases, date of disease onset, and number and type of the interventions were used as epidemiological endpoint, while rainfall, temperature, relative humidity and air pollution index (API) were indicators for environmental data. The field study was conducted during 81 weeks of data collection. Correlation and Autoregressive Distributed Lag Model were used to determine the relationship. The study showed that, notified cases were indirectly related with the environmental data, but shifted one week, i.e. last 3 weeks positive PCR; last 4 weeks rainfall; last 3 weeks maximum relative humidity; last 3 weeks minimum and maximum temperature; and last 4 weeks air pollution index (API), respectively. Notified cases were also related with next week intervention, while conventional intervention only happened 4 weeks after larvae were found, indicating ample time for dengue transmission. Based on a significant relationship among the three factors (epidemiological, entomological and environmental), estimated Autoregressive Distributed Lag (ADL) model for both locations produced high accuracy 84.9% for Selayang and 84.1% for Bandar Baru Bangi in predicting the actual notified cases. Hence, such model can be used in forestalling dengue outbreak and acts as an early warning system. The existence of relationships among the entomological, epidemiological and environmental factors can be used to build an early warning system for the prediction of dengue outbreak so that preventive interventions can be taken early to avert the outbreaks.
    Matched MeSH terms: Models, Biological*
  20. Fulltext Pore formation in lipid membrane I: Continuous reversible trajectory from intact bilayer through hydrophobic defect to transversal pore
    Akimov SA, Volynsky PE, Galimzyanov TR, Kuzmin PI, Pavlov KV, Batishchev OV
    Sci Rep, 2017 09 22;7(1):12152.
    PMID: 28939906 DOI: 10.1038/s41598-017-12127-7
    Lipid membranes serve as effective barriers allowing cells to maintain internal composition differing from that of extracellular medium. Membrane permeation, both natural and artificial, can take place via appearance of transversal pores. The rearrangements of lipids leading to pore formation in the intact membrane are not yet understood in details. We applied continuum elasticity theory to obtain continuous trajectory of pore formation and closure, and analyzed molecular dynamics trajectories of pre-formed pore reseal. We hypothesized that a transversal pore is preceded by a hydrophobic defect: intermediate structure spanning through the membrane, the side walls of which are partially aligned by lipid tails. This prediction was confirmed by our molecular dynamics simulations. Conversion of the hydrophobic defect into the hydrophilic pore required surmounting some energy barrier. A metastable state was found for the hydrophilic pore at the radius of a few nanometers. The dependence of the energy on radius was approximately quadratic for hydrophobic defect and small hydrophilic pore, while for large radii it depended on the radius linearly. The pore energy related to its perimeter, line tension, thus depends of the pore radius. Calculated values of the line tension for large pores were in quantitative agreement with available experimental data.
    Matched MeSH terms: Models, Biological
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