Optimal Electroporation Condition for Small Interfering RNA Transfection into MDA-MB-468 Cell Line
Rita Arabsolghar
2012-09-01
Full Text Available Background: Electroporation is a valuable tool for small interfering RNA (siRNA delivery into cells because it efficiently transforms a wide variety of cell types. Since electroporation condition for each cell type must be determined experimentally, this study presents an optimal electroporation strategy to reproducibly and efficiently transfect MDA-MB 468 human breast cancer cell with siRNA. Methods: To identify the best condition, the cells were firstly electroporated without siRNA and cell viability was determined by trypan blue and MTT assays. Then siRNA transfection in the best condition was performed. Western blot analysis was used for monitoring successful siRNA transfection. Results: The best condition for electroporation of this cell line was 220 volt and 975 µF in exponential decay using the Gene Pulser X cell electroporation system. Our data demonstrated that by using proper electroporation condition, DNA methyl transferase mRNA was silenced by 10 nmol DNMT1 siRNA in MDA-MB 468 cells when compared with negative control siRNA electroporation. Analysis of cell viability demonstrated that optimal electroporation condition resulted in 74% and 78% cell viability by trypan blue staining and MTT assay, respectively. Conclusion: Transfection of the MDA-MB-468 breast cancer cell line with siRNA in the obtained electroporation condition was successful and resulted in effective gene silencing and high cellular viability.
CYP1-mediated antiproliferative activity of dietary flavonoids in MDA-MB-468 breast cancer cells
Among the different mechanisms proposed to explain the cancer-protecting effect of dietary flavonoids, substrate-like interactions with cytochrome P450 CYP1 enzymes have recently been explored. In the present study, the metabolism of the flavonoids chrysin, baicalein, scutellarein, sinensetin and genkwanin by recombinant CYP1A1, CYP1B1 and CYP1A2 enzymes, as well as their antiproliferative activity in MDA-MB-468 human breast adenocarcinoma and MCF-10A normal breast cell lines, were investigated. Baicalein and 6-hydroxyluteolin were the only conversion products of chrysin and scutellarein metabolism by CYP1 family enzymes, respectively, while baicalein itself was not metabolized further. Sinensetin and genkwanin produced a greater number of metabolites and were shown to inhibit strongly in vitro proliferation of MDA-MB-468 cells at submicromolar and micromolar concentrations, respectively, without essentially affecting the viability of MCF-10A cells. Cotreatment of the CYP1 family inhibitor acacetin reversed the antiproliferative activity noticed for the two flavones in MDA-MB-468 cells to 13 and 14 μM respectively. In contrast chrysin, baicalein and scutellarein inhibited proliferation of MDA-MB-468 cells to a lesser extent than sinensetin and genkwanin. The metabolism of genkwanin to apigenin and of chrysin to baicalein was favored by CYP1B1 and CYP1A1, respectively. Taken together the data suggests that CYP1 family enzymes enhance the antiproliferative activity of dietary flavonoids in breast cancer cells, through bioconversion to more active products.
Fructose as a carbon source induces an aggressive phenotype in MDA-MB-468 breast tumor cells
MONZAVI-KARBASSI, BEHJATOLAH; HINE, R. JEAN; STANLEY, JOSEPH S.; RAMANI, VISHNU PRAKASH; CARCEL-TRULLOLS, JAIME; WHITEHEAD, TRACY L.; KELLY, THOMAS; SIEGEL, ERIC R.; ARTAUD, CECILE; SHAAF, SAEID; SAHA, RINKU; JOUSHEGHANY, FARIBA; HENRY-TILLMAN, RONDA; KIEBER-EMMONS, THOMAS
2012-01-01
Aberrant glycosylation is a universal feature of cancer cells, and certain glycan structures are well-known markers for tumor progression. Availability and composition of sugars in the microenvironment may affect cell glycosylation. Recent studies of human breast tumor cell lines indicate their ability to take up and utilize fructose. Here we tested the hypothesis that adding fructose to culture as a carbon source induces phenotypic changes in cultured human breast tumor cells that are associated with metastatic disease. MDA-MB-468 cells were adapted to culture media in which fructose was substituted for glucose. Changes in cell surface glycan structures, expression of genes related to glycan assembly, cytoskeleton F-actin, migration, adhesion and invasion were determined. Cells cultured in fructose expressed distinct cell-surface glycans. The addition of fructose affected sialylation and fucosylation patterns. Fructose feeding also increased binding of leukoagglutinating Phaseolus vulgaris isolectin, suggesting a possible rise in expression of branching β-1, 6 GlcNAc structures. Rhodamine-phalloidin staining revealed an altered F-actin cytoskeletal system. Fructose accelerated cellular migration and increased invasion. These data suggest that changing the carbon source of the less aggressive MDA-MB-468 cell line induced characteristics associated with more aggressive phenotypes. These data could be of fundamental importance due to the markedly increased consumption of sweeteners containing free fructose in recent years, as they suggest that the presence of fructose in nutritional micro-environment of tumor cells may negatively affect the outcome for some breast cancer patients. PMID:20664930
Jin, Un-Ho; Lee, Syng-Ook; Safe, Stephen
2012-01-01
Leflunomide, flutamide, nimodipine, mexiletine, sulindac, tranilast, 4-hydroxytamoxifen, and omeprazole are pharmaceuticals previously characterized as aryl hydrocarbon receptor (AHR) agonists in various cell lines and animal models. In this study, the eight AHR-active pharmaceuticals were investigated in highly aggressive aryl hydrocarbon (Ah)-responsive BT474 and MDA-MB-468 breast cancer cell lines, and their effects on AHR protein, CYP1A1 (protein and mRNA), CYP1B1 (mRNA), and cell migrati...
[Different coexisting genotypes in the breast cancer cell line MDA-MB-468].
Agelopoulos, K; Schmidt, H; Korsching, E; Buerger, H; Brandt, B
2008-11-01
Intratumor genetic heterogeneity, a well-known characteristic of numerous cancers, often confounds a precise diagnosis and leads to therapy resistance. This study deals with such chromosomal variability, which may be due to an inherent genetic instability affecting heterogeneity and clonal effects. Subpopulations of the breast cancer cell line MDA-MB-468 were isolated according to epidermal growth factor receptor (EGFR) expression by FACS. Whole genome profiling (CGH; mapping arrays) and determination of egfr gene amplification (fluorescence in situ hybridisation, FISH; qPCR) were done directly after sorting or after several passages of cell culture. Subpopulations differed in the amplification of the egfr-locus 7p11-14 showing egfr gene amplification rates of up to 60-fold in high-level expressing populations and less than 2-fold in low-level expressing populations. However, after several passages the original low-level cells showed a new amplification of the egfr gene, which was as heterogeneous as the original amplification detected in MDA-MB-468. Additional, spontaneously expressed fragile sites could be shown in FISH analyses which may affect cell culture heterogeneity. Understanding the precise chromosomal process would clarify mechanisms in vivo and improve both diagnosis and therapy of corresponding cancers. PMID:18751981
Stewart, Teneale A; Azimi, Iman; Brooks, Andrew J; Thompson, Erik W; Roberts-Thomson, Sarah J; Monteith, Gregory R
2016-07-01
Epithelial-mesenchymal transition (EMT) is an important process associated with the metastasis of breast cancer cells. Members of the Janus kinases (JAKs) and Src family kinases (SFKs) are implicated in the regulation of an invasive phenotype in various cancer cell types. Using the pharmacological inhibitors JAK Inhibitor I (a pan-JAK inhibitor) and PP2 we investigated the role of the JAKs and SFKs, respectively, in the regulation of EMT markers in the MDA-MB-468 breast cancer cell line model of epidermal growth factor (EGF)-induced EMT. We identified selective inhibition of EGF induction of the mesenchymal marker vimentin by PP2 and JAK Inhibitor I. The effect of JAK Inhibitor I on vimentin protein induction occurred at a concentration lower than that required to significantly inhibit EGF-mediated signal transducer and activator of transcription 3 (STAT3)-phosphorylation, suggesting involvement of a STAT3-independent mechanism of EGF-induced vimentin regulation by JAKs. Despite our identification of a role for the JAK family in EGF-induced vimentin protein expression, siRNA-mediated silencing of each member of the JAK family was unable to phenocopy pharmacological inhibition, indicating potential redundancy among the JAK family members in this pathway. While SFKs and JAKs do not represent global regulators of the EMT phenotype, our findings have identified a role for members of these signaling pathways in the regulation of EGF-induced vimentin expression in the MDA-MB-468 breast cancer cell line. PMID:27163529
Jahidin, Aisyah H; Stewart, Teneale A; Thompson, Erik W; Roberts-Thomson, Sarah J; Monteith, Gregory R
2016-09-01
Two-pore channel proteins, TPC1 and TPC2, are calcium permeable ion channels found localized to the membranes of endolysosomal calcium stores. There is increasing interest in the role of TPC-mediated intracellular signaling in various pathologies; however their role in breast cancer has not been extensively evaluated. TPC1 and TPC2 mRNA was present in all non-tumorigenic and tumorigenic breast cell lines assessed. Silencing of TPC2 but not TPC1 attenuated epidermal growth factor-induced vimentin expression in MDA-MB-468 breast cancer cells. This effect was not due to a general inhibition of epithelial to mesenchymal transition (EMT) as TPC2 silencing had no effect on epidermal growth factor (EGF)-induced changes on E-cadherin expression. TPC1 and TPC2 were also shown to differentially regulate cyclopiazonic acid (CPA)-mediated changes in cytosolic free Ca(2+). These findings indicate potential differential regulation of signaling processes by TPC1 and TPC2 in breast cancer cells. PMID:27353380
Huan-Chen Cheng
2012-05-01
Full Text Available 3-(5'-hydroxymethyl-2'-furyl-1-benzyl indazole (YC-1, the hypoxia-inducible factor-1 alpha (HIF-1α inhibitor, suppresses tumor proliferation and metastasis by down-regulating HIF-1α expression under hypoxic conditions. Our previous studies demonstrated that YC-1 inhibited breast cancer cell proliferation under normoxic conditions. In the current study, we investigated the targets of YC-1 and mechanism of its action in MDA-MB-468 breast cancer cells. In the in vitro experiments, we found that YC-1 significantly inhibited MDA-MB-468 cell proliferation in normoxia and hypoxia. Under normoxic conditions, YC-1 induced apoptosis of MDA-MB-468 cells and blocked cell cycle in the G1 phase, and these effects were possibly related to caspase 8, p21, and p27 expression. RT-PCR and Western blotting results showed that YC-1 primarily inhibited HIF-1α at the mRNA and protein levels under hypoxic conditions, but suppressed the expression of epidermal growth factor receptor(EGFR at the mRNA and protein levels under normoxic conditions. In vivo, YC-1 prolonged survival, increased survival rate, decreased tumor size and metastasis rate, and inhibited tissue EGFR and HIF-1α expression. However, YC-1 exerted no obvious effect on body weight. These results indicate that YC-1 inhibits the proliferation of MDA-MB-468 cells by acting on multiple targets with minimal side effects. Thus, YC-1 is a promising target drug for breast cancer.
Mohammadi, A; Mansoori, B; Goldar, S; Shanehbandi, D; Khaze, V; Mohammadnejad, L; Baghbani, E; Baradaran, B
2016-01-01
Breast cancer is the most common cancer among women in worldwide, especially in developing countries. Therefore, a large number of anticancer agents with herbal origins have been reported against this deadly disease. This study is the first to examine the cytotoxic and apoptotic effects of Urtica dioica in MDA-MB-468, human breast adenocarcinoma cells. The 3-(4,5-dimethylethiazol-2 yl)-2,5- diphenyltetrazolium (MTT) reduction and trypan-blue exclusion assay were performed in MDA-MB-468 cells as well as control cell line L929 to analyze the cytotoxic activity of the dichloromethane extract. In addition, Apoptosis induction of Urtica dioica on the MDA-MB-468 cells was assessed using TUNEL (terminal deoxy transferase (TdT)-mediated dUTP nick- end labeling) assay and DNA fragmentation analysis and real-time polymerase chain reaction (PCR). The results showed that the extract significantly inhibited cell growth and viability without inducing damage to normal control cells. Nuclei Staining in TUNEL and DNA fragments in DNA fragmentation assay and increase in the mRNA expression levels of caspase-3, caspase-9, decrease in the bcl2 and no significant change in the caspase-8 mRNA expression level, showed that the induction of apoptosis was the main mechanism of cell death that induce by Urtica dioica extract. Our results suggest that urtica dioica dichloromethane extract may contain potential bioactive compound(s) for the treatment of breast adenocarcinoma. PMID:26950453
Mousumi Majumder
Full Text Available INTRODUCTION AND OBJECTIVES: Lymphatic metastasis is a common occurrence in human breast cancer, mechanisms remaining poorly understood. MDA-MB-468LN (468LN, a variant of the MDA-MB-468GFP (468GFP human breast cancer cell line, produces extensive lymphatic metastasis in nude mice. 468LN cells differentially express α9β1 integrin, a receptor for lymphangiogenic factors VEGF-C/-D. We explored whether (1 differential production of VEGF-C/-D by 468LN cells provides an autocrine stimulus for cellular motility by interacting with α9β1 and a paracrine stimulus for lymphangiogenesis in vitro as measured with capillary-like tube formation by human lymphatic endothelial cells (HMVEC-dLy; (2 differential expression of α9 also promotes cellular motility/invasiveness by interacting with macrophage derived factors; (3 stable knock-down of VEGF-D or α9 in 468LN cells abrogates lymphangiogenesis and lymphatic metastasis in vivo in nude mice. RESULTS: A comparison of expression of cyclo-oxygenase (COX-2 (a VEGF-C/-D inducer, VEGF-C/-D and their receptors revealed little COX-2 expression by either cells. However, 468LN cells showed differential VEGF-D and α9β1 expression, VEGF-D secretion, proliferative, migratory/invasive capacities, latter functions being stimulated further with VEGF-D. The requirement of α9β1 for native and VEGF-D-stimulated proliferation, migration and Erk activation was demonstrated by treating with α9β1 blocking antibody or knock-down of α9. An autocrine role of VEGF-D in migration was shown by its impairment by silencing VEGF-D and restoration with VEGF-D. 468LN cells and their soluble products stimulated tube formation, migration/invasiveness of HMVEC-dLy cell in a VEGF-D dependent manner as indicated by the loss of stimulation by silencing VEGF-D in 468LN cells. Furthermore, 468LN cells showed α9-dependent stimulation of migration/invasiveness by macrophage products. Finally, capacity for intra-tumoral lymphangiogenesis and
Parson, Carl; SMITH, VALERIE; Krauss, Christopher; Banerjee, Hirendra N.; Reilly, Christopher; Krause, Jeanette A.; Wachira, James M.; Giri, Dipak; Winstead, Angela; Mandal, Santosh K.
2015-01-01
Aim To study the efficacy of novel rhenium compounds to treat triple node negative breast cancer. Place and Duration Six (6) novel rhenium pentycarbanato compounds (PC1-6) were synthesized and triple node negative breast cancer cell lines HTB-132 and Balb/c mouse kidney cell lines were treated with each of them for 48 hours. The results were analyzed by a common trypan blue cell death assay system and statistically analyzed. Place and Duration The compounds were synthesized, analyzed and eval...
Testing the applicability of mathematical models with carefully designed experiments is a powerful tool in the investigations of the effects of ionizing radiation on cells. The modeling and cellular studies complement each other, for modeling provides guidance for designing critical experiments which must provide definitive results, while the experiments themselves provide new input to the model. Based on previous experimental results the model for the accumulation of damage in Chlamydomonas reinhardi has been extended to include various multiple two-event combinations. Split dose survival experiments have shown that models tested to date predict most but not all the observed behavior. Stationary-phase mammalian cells, required for tests of other aspects of the model, have been shown to be at different points in the cell cycle depending on how they were forced to stop proliferating. These cultures also demonstrate different capacities for repair of sublethal radiation damage
Endy, Drew; Brent, Roger
2001-01-01
Representations of cellular processes that can be used to compute their future behaviour would be of general scientific and practical value. But past attempts to construct such representations have been disappointing. This is now changing. Increases in biological understanding combined with advances in computational methods and in computer power make it possible to foresee construction of useful and predictive simulations of cellular processes.
Predictive Modelling of Cellular Load
Carolan, Emmett; McLoone, Seamus; Farrell, Ronan
2015-01-01
This work examines the temporal dynamics of cellular load in four Irish regions. Large scale underutilisation of network resources is identified both at the regional level and at the level of individual cells. Cellular load is modeled and prediction intervals are generated. These prediction intervals are used to put an upper bound on usage in a particular cell at a particular time. Opportunities for improvements in network utilization by incorporating these upper bounds on usage are identifie...
Activity of the kinesin spindle protein inhibitor ispinesib (SB-715992) in models of breast cancer
Purcell, James W; Davis, Jefferson; Reddy, Mamatha; Martin, Shamra; Samayoa, Kimberly; Vo, Hung; Thomsen, Karen; Bean, Peter; Kuo, Wen Lin; Ziyad, Safiyyah; Billig, Jessica; Feiler, Heidi S; Gray, Joe W; Wood, Kenneth W; Cases, Sylvaine
2009-06-10
Ispinesib (SB-715992) is a potent inhibitor of kinesin spindle protein (KSP), a kinesin motor protein essential for the formation of a bipolar mitotic spindle and cell cycle progression through mitosis. Clinical studies of ispinesib have demonstrated a 9% response rate in patients with locally advanced or metastatic breast cancer, and a favorable safety profile without significant neurotoxicities, gastrointestinal toxicities or hair loss. To better understand the potential of ispinesib in the treatment of breast cancer we explored the activity of ispinesib alone and in combination several therapies approved for the treatment of breast cancer. We measured the ispinesib sensitivity and pharmacodynamic response of breast cancer cell lines representative of various subtypes in vitro and as xenografts in vivo, and tested the ability of ispinesib to enhance the anti-tumor activity of approved therapies. In vitro, ispinesib displayed broad anti-proliferative activity against a panel of 53 breast cell-lines. In vivo, ispinesib produced regressions in each of five breast cancer models, and tumor free survivors in three of these models. The effects of ispinesib treatment on pharmacodynamic markers of mitosis and apoptosis were examined in vitro and in vivo, revealing a greater increase in both mitotic and apoptotic markers in the MDA-MB-468 model than in the less sensitive BT-474 model. In vivo, ispinesib enhanced the anti-tumor activity of trastuzumab, lapatinib, doxorubicin, and capecitabine, and exhibited activity comparable to paclitaxel and ixabepilone. These findings support further clinical exploration of KSP inhibitors for the treatment of breast cancer.
Over-expression of epidermal growth factor receptor (EGFR) or insulin-like growth factor-1 receptor (IGF-1R) have been shown to closely correlate with radioresistance of breast cancer cells. This study aimed to investigate the impact of co-inhibition of EGFR and IGF-1R on the radiosensitivity of two breast cancer cells with different profiles of EGFR and IGF-1R expression. The MCF-7 (EGFR +/−, IGF-1R +++) and MDA-MB-468 (EGFR +++, IGF-1R +++) breast cancer cell lines were used. Radiosensitizing effects were determined by colony formation assay. Apoptosis and cell cycle distribution were measured by flow cytometry. Phospho-Akt and phospho-Erk1/2 were quantified by western blot. In vivo studies were conducted using MDA-MB-468 cells xenografted in nu/nu mice. In MDA-MB-468 cells, the inhibition of IGF-1R upregulated the p-EGFR expression. Either EGFR (AG1478) or IGF-1R inhibitor (AG1024) radiosensitized MDA-MB-468 cells. In MCF-7 cells, radiosensitivity was enhanced by AG1024, but not by AG1478. Synergistical radiosensitizing effect was observed by co-inhibition of EGFR and IGF-1R only in MDA-MB-468 cells with a DMF10% of 1.90. The co-inhibition plus irradiation significantly induced more apoptosis and arrested the cells at G0/G1 phase in MDA-MB-468 cells. Only co-inhibition of EGFR and IGF-1R synergistically diminished the expression of p-Akt and p-Erk1/2 in MDA-MB-468 cells. In vivo studies further verified the radiosensitizing effects by co-inhibition of both pathways in a MDA-MB-468 xenograft model. Our data suggested that co-inhibition of EGFR and IGF-1R synergistically radiosensitized breast cancer cells with both EGFR and IGF-1R high expression. The approach may have an important therapeutic implication in the treatment of breast cancer patients with high expression of EGFR and IGF-1R
Cellular automata a parallel model
Mazoyer, J
1999-01-01
Cellular automata can be viewed both as computational models and modelling systems of real processes. This volume emphasises the first aspect. In articles written by leading researchers, sophisticated massive parallel algorithms (firing squad, life, Fischer's primes recognition) are treated. Their computational power and the specific complexity classes they determine are surveyed, while some recent results in relation to chaos from a new dynamic systems point of view are also presented. Audience: This book will be of interest to specialists of theoretical computer science and the parallelism challenge.
Chinchar, Edmund; Makey, Kristina L; Gibson, John; Chen, Fang; Cole, Shelby A; Megason, Gail C; Vijayakumar, Srinivassan; Miele, Lucio; Gu, Jian-Wei
2014-01-01
The majority of triple-negative breast cancers (TNBCs) are basal-like breast cancers. However there is no reported study on anti-tumor effects of sunitinib in xenografts of basal-like TNBC (MDA-MB-468) cells. In the present study, MDA-MB-231, MDA-MB-468, MCF-7 cells were cultured using RPMI 1640 media with 10% FBS. Vascular endothelia growth factor (VEGF) protein levels were detected using ELISA (R & D Systams). MDA-MB-468 cells were exposed to sunitinib for 18 hours for measuring proliferation (3H-thymidine incorporation), migration (BD Invasion Chamber), and apoptosis (ApopTag and ApoScreen Anuexin V Kit). The effect of sunitinib on Notch-1 expression was determined by Western blot in cultured MDA-MB-468 cells. 10(6) MDA-MB-468 cells were inoculated into the left fourth mammary gland fat pad in athymic nude-foxn1 mice. When the tumor volume reached 100 mm(3), sunitinib was given by gavage at 80 mg/kg/2 days for 4 weeks. Tumor angiogenesis was determined by CD31 immunohistochemistry. Breast cancer stem cells (CSCs) isolated from the tumors were determined by flow cytometry analysis using CD44(+)/CD24(-) or low. ELISA indicated that VEGF was much more highly expressed in MDA-MB-468 cells than MDA-MB-231 and MCF-7 cells. Sunitinib significantly inhibited the proliferation, invasion, and apoptosis resistance in cultured basal like breast cancer cells. Sunitinib significantly increased the expression of Notch-1 protein in cultured MDA-MB-468 or MDA-MB-231 cells. The xenograft models showed that oral sunitinib significantly reduced the tumor volume of TNBCs in association with the inhibition of tumor angiogeneisis, but increased breast CSCs. These findings support the hypothesis that the possibility should be considered of sunitinib increasing breast CSCs though it inhibits TNBC tumor angiogenesis and growth/progression, and that effects of sunitinib on Notch expression and hypoxia may increase breast cancer stem cells. This work provides the groundwork for an
Understanding cisplatin resistance using cellular models.
STORDAL, BRITTA KRISTINA
2007-01-01
PUBLISHED Many mechanisms of cisplatin resistance have been proposed from studies of cellular models of resistance including changes in cellular drug accumulation, detoxification of the drug, inhibition of apoptosis and repair of the DNA adducts. A series of resistant models were developed from CCRF-CEM leukaemia cells with increasing doses of cisplatin from 100 ng/ml. This produced increasing resistance up to 7-fold with a treatment dose of 1.6 ?g/ml. Cisplatin resistance i...
Understanding cisplatin resistance using cellular models
Stordal, Britta; Davey, Mary
2007-01-01
Many mechanisms of cisplatin resistance have been proposed from studies of cellular models of resistance including changes in cellular drug accumulation, detoxification of the drug, inhibition of apoptosis and repair of the DNA adducts. A series of resistant models were developed from CCRF-CEM leukaemia cells with increasing doses of cisplatin from 100 ng/ml. This produced increasing resistance up to 7-fold with a treatment dose of 1.6 microg/ml. Cisplatin resistance in these cells correlated...
Animal and cellular models of human disease
Arends, Mark; White, Eric; Whitelaw, Christopher
2016-01-01
In this eighteenth (2016) Annual Review Issue of The Journal of Pathology, we present a collection of 19 invited review articles that cover different aspects of cellular and animal models of disease. These include genetically-engineered models, chemically-induced models, naturally-occurring models, and combinations thereof, with the focus on recent methodological and conceptual developments across a wide range of human diseases.
A Modified Sensitive Driving Cellular Automaton Model
GE Hong-Xia; DAI Shi-Qiang; DONG Li-Yun; LEI Li
2005-01-01
A modified cellular automaton model for traffic flow on highway is proposed with a novel concept about the variable security gap. The concept is first introduced into the original Nagel-Schreckenberg model, which is called the non-sensitive driving cellular automaton model. And then it is incorporated with a sensitive driving NaSch model,in which the randomization brake is arranged before the deterministic deceleration. A parameter related to the variable security gap is determined through simulation. Comparison of the simulation results indicates that the variable security gap has different influence on the two models. The fundamental diagram obtained by simulation with the modified sensitive driving NaSch model shows that the maximumflow are in good agreement with the observed data, indicating that the presented model is more reasonable and realistic.
Paydar, Mohammadjavad; Kamalidehghan, Behnam; Wong, Yi Li; Wong, Won Fen; Looi, Chung Yeng; Mustafa, Mohd Rais
2014-01-01
To date, plants have been the major source of anticancer drugs. Boldine is a natural alkaloid commonly found in the leaves and bark of Peumus boldus. In this study, we found that boldine potently inhibited the viability of the human invasive breast cancer cell lines, MDA-MB-231 (48-hour IC₅₀ 46.5±3.1 μg/mL) and MDA-MB-468 (48-hour IC₅₀ 50.8±2.7 μg/mL). Boldine had a cytotoxic effect and induced apoptosis in breast cancer cells as indicated by a higher amount of lactate dehydrogenase released, membrane permeability, and DNA fragmentation. In addition, we demonstrated that boldine induced cell cycle arrest at G2/M phase. The anticancer mechanism is associated with disruption of the mitochondrial membrane potential and release of cytochrome c in MDA-MB-231. Boldine selectively induced activation of caspase-9 and caspase-3/7, but not caspase-8. We also found that boldine could inhibit nuclear factor kappa B activation, a key molecule in tumor progression and metastasis. In addition, protein array and Western blotting analysis showed that treatment with boldine resulted in downregulation of Bcl-2 and heat shock protein 70 and upregulation of Bax in the MDA-MB-231 cell line. An acute toxicity study in rats revealed that boldine at a dose of 100 mg/kg body weight was well tolerated. Moreover, intraperitoneal injection of boldine (50 or 100 mg/kg) significantly reduced tumor size in an animal model of breast cancer. Our results suggest that boldine is a potentially useful agent for the treatment of breast cancer. PMID:24944509
Li, Fiona; Cho, Sung Ju; Yu, Lihai; Hudson, Robert H. E.; Luyt, Leonard G.; Pin, Christopher L.; Kovacs, Michael S.; Koropatnick, James; Lee, Ting-Yim
2016-03-01
Alteration in genetic expression is as important as gene mutation in cancer development and proliferation. Epigenetic changes affect gene expression without altering the DNA sequence. Histone deacetylase (HDAC), an enzyme facilitating histone remodelling, can lead to silencing of tumor suppressor genes making HDAC inhibitors viable anticancer drugs against tumors with increased activity of the enzyme. In this study we evaluated 18F-fluroacetamido-1-hexanoicanilide (18F-FAHA), an artificial HDAC substrate, as imaging probe of HDAC activity of human tumor xenografts in immunocompromised host mice. Human breast and melanoma cell lines, MDA-MB-468 and MDA-MB-435 respectively, known to overexpress HDAC activity were xenografted into immunocompromised mice and HDAC activity was imaged using 18F-FAHA. The melanoma group was treated with saline, SAHA (suberoylanilide hydroxamic acid, an approved anticancer HDAC inhibitor) in DMSO, or DMSO as positive control. Tracer kinetic modelling and SUV were used to estimate HDAC activity from dynamic PET data. Both breast tumor and melanoma group showed great variability in binding rate constant (BRC) of 18F-FAHA suggesting highly variable inter- and intra-tumoral HDAC activity. For the SAHA treated melanoma group, HDAC activity, as monitored by BRC of 18F-FAHA, decreased more than the two (positive and negative) control groups but not tumor growth. Our preliminary study showed that noninvasive PET imaging with 18F-FAHA has the potential to identify patients for whom treatment with HDAC inhibitors are appropriate, to assess the effectiveness of that treatment as an early marker of target reduction, and also eliminate the need for invasive tissue biopsy to individualize treatment.
Heravi, Mitra [Department of Human Genetics, McGill University, Montreal (Canada); Department of Radiation Oncology, McGill University, Montreal (Canada); Segal Cancer Center, Jewish General Hospital, Montreal (Canada); Kumala, Slawomir [Department of Radiation Oncology, McGill University, Montreal (Canada); Segal Cancer Center, Jewish General Hospital, Montreal (Canada); Rachid, Zakaria; Jean-Claude, Bertrand J. [Cancer Drug Research Laboratory, McGill University Health Center, Montreal (Canada); Radzioch, Danuta [Department of Human Genetics, McGill University, Montreal (Canada); Muanza, Thierry M., E-mail: tmuanza@yahoo.com [Department of Radiation Oncology, McGill University, Montreal (Canada); Segal Cancer Center, Jewish General Hospital, Montreal (Canada)
2015-06-01
Purpose: ZRBA1 is a combi-molecule designed to induce DNA alkylating lesions and to block epidermal growth factor receptor (EGFR) TK domain. Inasmuch as ZRBA1 downregulates the EGFR TK-mediated antisurvival signaling and induces DNA damage, we postulated that it might be a radiosensitizer. The aim of this study was to further investigate the potentiating effect of ZRBA1 in combination with radiation and to elucidate the possible mechanisms of interaction between these 2 treatment modalities. Methods and Materials: The triple negative human breast MDA-MB-468 cancer cell line and mouse mammary cancer 4T1 cell line were used in this study. Clonogenic assay, Western blot analysis, and DNA damage analysis were performed at multiple time points after treatment. To confirm our in vitro findings, in vivo tumor growth delay assay was performed. Results: Our results show that a combination of ZRBA1 and radiation increases the radiation sensitivity of both cell lines significantly with a dose enhancement factor of 1.56, induces significant numbers of DNA strand breaks, prolongs higher DNA damage up to 24 hours after treatment, and significantly increases tumor growth delay in a syngeneic mouse model. Conclusions: Our data suggest that the higher efficacy of this combination could be partially due to increased DNA damage and delayed DNA repair process and to the inhibition of EGFR. The encouraging results of this combination demonstrated a significant improvement in treatment efficiency and therefore could be applicable in early clinical trial settings.
Purpose: ZRBA1 is a combi-molecule designed to induce DNA alkylating lesions and to block epidermal growth factor receptor (EGFR) TK domain. Inasmuch as ZRBA1 downregulates the EGFR TK-mediated antisurvival signaling and induces DNA damage, we postulated that it might be a radiosensitizer. The aim of this study was to further investigate the potentiating effect of ZRBA1 in combination with radiation and to elucidate the possible mechanisms of interaction between these 2 treatment modalities. Methods and Materials: The triple negative human breast MDA-MB-468 cancer cell line and mouse mammary cancer 4T1 cell line were used in this study. Clonogenic assay, Western blot analysis, and DNA damage analysis were performed at multiple time points after treatment. To confirm our in vitro findings, in vivo tumor growth delay assay was performed. Results: Our results show that a combination of ZRBA1 and radiation increases the radiation sensitivity of both cell lines significantly with a dose enhancement factor of 1.56, induces significant numbers of DNA strand breaks, prolongs higher DNA damage up to 24 hours after treatment, and significantly increases tumor growth delay in a syngeneic mouse model. Conclusions: Our data suggest that the higher efficacy of this combination could be partially due to increased DNA damage and delayed DNA repair process and to the inhibition of EGFR. The encouraging results of this combination demonstrated a significant improvement in treatment efficiency and therefore could be applicable in early clinical trial settings
A Mathematical Model for Cisplatin Cellular Pharmacodynamics
Ardith W. El-Kareh
2003-03-01
Full Text Available A simple theoretical model for the cellular pharmacodynamics of cisplatin is presented. The model, which takes into account the kinetics of cisplatin uptake by cells and the intracellular binding of the drug, can be used to predict the dependence of survival (relative to controls on the time course of extracellular exposure. Cellular pharmacokinetic parameters are derived from uptake data for human ovarian and head and neck cancer cell lines. Survival relative to controls is assumed to depend on the peak concentration of DNA-bound intracellular platinum. Model predictions agree well with published data on cisplatin cytotoxicity for three different cancer cell lines, over a wide range of exposure times. In comparison with previously published mathematical models for anticancer drug pharmacodynamics, the present model provides a better fit to experimental data sets including long exposure times (∼100 hours. The model provides a possible explanation for the fact that cell kill correlates well with area under the extracellular concentration-time curve in some data sets, but not in others. The model may be useful for optimizing delivery schedules and for the dosing of cisplatin for cancer therapy.
Cellular automata modelling of hantarvirus infection
Hantaviruses are a group of viruses which have been identified as being responsible for the outbreak of diseases such as the hantavirus pulmonary syndrome. In an effort to understand the characteristics and dynamics of hantavirus infection, mathematical models based on differential equations have been developed and widely studied. However, such models neglect the local characteristics of the spreading process and do not include variable susceptibility of individuals. In this paper, we develop an alternative approach based on cellular automata to analyze and study the spatiotemporal patterns of hantavirus infection.
Cellular automata modelling of hantarvirus infection
Abdul Karim, Mohamad Faisal [School of Distance Education, Universiti Sains Malaysia, Minden 11800, Penang (Malaysia)], E-mail: faisal@usm.my; Md Ismail, Ahmad Izani [School of Mathematical Sciences, Universiti Sains Malaysia, Minden 11800, Penang (Malaysia)], E-mail: izani@cs.usm.my; Ching, Hoe Bee [School of Mathematical Sciences, Universiti Sains Malaysia, Minden 11800, Penang (Malaysia)], E-mail: Bee_Ching_Janice_Hoe@dell.com
2009-09-15
Hantaviruses are a group of viruses which have been identified as being responsible for the outbreak of diseases such as the hantavirus pulmonary syndrome. In an effort to understand the characteristics and dynamics of hantavirus infection, mathematical models based on differential equations have been developed and widely studied. However, such models neglect the local characteristics of the spreading process and do not include variable susceptibility of individuals. In this paper, we develop an alternative approach based on cellular automata to analyze and study the spatiotemporal patterns of hantavirus infection.
Spatial game in cellular automaton evacuation model
von Schantz, Anton; Ehtamo, Harri
2015-11-01
For numerical simulations of crowd dynamics in an evacuation we need a computationally light environment, such as the cellular automaton model (CA). By choosing the right model parameters, different types of crowd behavior and collective effects can be produced. But the CA does not answer why, when, and how these different behaviors and collective effects occur. In this article, we present a model, where we couple a spatial evacuation game to the CA. In the game, an agent chooses its strategy by observing its neighbors' strategies. The game matrix changes with the distance to the exit as the evacuation conditions develop. In the resulting model, an agent's strategy choice alters the parameters that govern its behavior in the CA. Thus, with our model, we are able to simulate how evacuation conditions affect the behavior of the crowd. Also, we show that some of the collective effects observed in evacuations are a result of the simple game the agents play.
A cellular automata model for ant trails
Sibel Gokce; Ozhan Kayacan
2013-05-01
In this study, the unidirectional ant traffic flow with U-turn in an ant trail was investigated using one-dimensional cellular automata model. It is known that ants communicate with each other by dropping a chemical, called pheromone, on the substrate. Apart from the studies in the literature, it was considered in the model that (i) ant colony consists of two kinds of ants, goodand poor-smelling ants, (ii) ants might make U-turn for some special reasons. For some values of densities of good- and poor-smelling ants, the flux and mean velocity of the colony were studied as a function of density and evaporation rate of pheromone.
Modeling the topological organization of cellular processes.
Giavitto, Jean-Louis; Michel, Olivier
2003-07-01
The cell as a dynamical system presents the characteristics of having a dynamical structure. That is, the exact phase space of the system cannot be fixed before the evolution and integrative cell models must state the evolution of the structure jointly with the evolution of the cell state. This kind of dynamical systems is very challenging to model and simulate. New programming concepts must be developed to ease their modeling and simulation. In this context, the goal of the MGS project is to develop an experimental programming language dedicated to the simulation of this kind of systems. MGS proposes a unified view on several computational mechanisms (CHAM, Lindenmayer systems, Paun systems, cellular automata) enabling the specification of spatially localized computations on heterogeneous entities. The evolution of a dynamical structure is handled through the concept of transformation which relies on the topological organization of the system components. An example based on the modeling of spatially distributed biochemical networks is used to illustrate how these notions can be used to model the spatial and temporal organization of intracellular processes. PMID:12915272
Cellular automata modelling of biomolecular networks dynamics.
Bonchev, D; Thomas, S; Apte, A; Kier, L B
2010-01-01
The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215
Cellular automata modeling of cooperative eutectic growth
E. Olejnik
2010-01-01
Full Text Available The model and results of the 2D simulation of the cooperative growth of two phases in the lamellar eutectic are presented. The pro-posed model takes into account heat transfer, components diffusion and nonstationary concentration distribution in the liquid and solid phases, non-equlibrium nature of the phase transformation and kinetics of the growth, influence of the surface energy and interface curva-ture on the conditions of the thermodynamic equilibrium. For the determination of the phase interface shape the Cellular Automata tech-nique (CA was used. For the calculation of temperature and concentration distribution the numerical solution of the Fourier equation was used. The partial differential equations were solved by Finite Differences Method (FDM. The spatial position and cell sizes of CA lattice and FDM mesh are equal.Proposed model can predict the steady state growth with a constant interlamellar spacing in the regular plate eutectic, as well as some transient processes that bring to the changes of that parameters. Obtained simulation data show the solid-liquid interface changes result in the termination of lamella and enlargement of interlamellar spacing. Another simulation results illustrate a pocket formation in the center of one phase that forestalls nucleation (or intergrowth of the new lamellae of another phase. The data of the solidification study of the transparent material (CBr4 – 8,4% C2Cl6 obtained in the thin layer demonstrate the qualita-tive agreement of the simulation.
Modeling cellular effects of coal pollutants
The goal of this project is to develop and test models for the dose and dose-rate dependence of biological effects of coal pollutants on mammalian cells in tissue culture. Particular attention is given to the interaction of pollutants with the genetic material (deoxyribonucleic acid, or NDA) in the cell. Unlike radiation, which can interact directly with chromatin, chemical pollutants undergo numerous changes before the ultimate carcinogen becomes covalently bound to the DNA. Synthetic vesicles formed from a phospholipid bilayer are being used to investigate chemical transformations that may occur during the transport of pollutants across cellular membranes. The initial damage to DNA is rapidly modified by enzymatic repair systems in most living organisms. A model has been developed for predicting the effects of excision repair on the survival of human cells exposed to chemical carcinogens. In addition to the excision system, normal human cells also have tolerance mechanisms that permit continued growth and division of cells without removal of the damage. We are investigating the biological effect of damage passed to daughter cells by these tolerance mechanisms
Analytical Modeling of Uplink Cellular Networks
Novlan, Thomas D; Andrews, Jeffrey G
2012-01-01
Cellular uplink analysis has typically been undertaken by either a simple approach that lumps all interference into a single deterministic or random parameter in a Wyner-type model, or via complex system level simulations that often do not provide insight into why various trends are observed. This paper proposes a novel middle way that is both accurate and also results in easy-to-evaluate integral expressions based on the Laplace transform of the interference. We assume mobiles and base stations are randomly placed in the network with each mobile pairing up to its closest base station. The model requires two important changes compared to related recent work on the downlink. First, dependence is introduced between the user and base station point processes to make sure each base station serves a single mobile in the given resource block. Second, per-mobile power control is included, which further couples the locations of the mobiles and their receiving base stations. Nevertheless, we succeed in deriving the cov...
Typhoid fever as cellular microbiological model
Andrade Dahir Ramos de; Andrade Júnior Dahir Ramos de
2003-01-01
The knowledge about typhoid fever pathogenesis is growing in the last years, mainly about the cellular and molecular phenomena that are responsible by clinical manifestations of this disease. In this article are discussed several recent discoveries, as follows: a) Bacterial type III protein secretion system; b) The five virulence genes of Salmonella spp. that encoding Sips (Salmonella invasion protein) A, B, C, D and E, which are capable of induce apoptosis in macrophages; c) The function of ...
Our objective was to study the cellular and nuclear uptake of 123I-mouse IgG (123I-mIgG) linked to peptides [GRKKRRQRRRPPQGYGC] harbouring the membrane-translocating and nuclear import sequences of HIV-1 tat protein. Carbohydrates on mIgG were oxidized by NaIO4, then reacted with a 40-fold excess of peptides. Displacement of binding of anti-mouse IgG (Fab specific; α-mFab) to 123I-mIgG by tat-mIgG or mIgG was compared. Internalization and nuclear translocation of 123I-tat-mIgG in MDA-MB-468, MDA-MB-231 or MCF-7 breast cancer cells were measured. The immunoreactivity of imported tat-mIgG was evaluated by measuring binding of 123I-α-mFab to cell lysate and by displacement of binding of 123I-mIgG to α-mFab by cell lysate. Biodistribution and nuclear uptake of 123I-tat-mIgG, 123I-mIgG and 123I-tat were compared in mice bearing s.c. MDA-MB-468 tumours. There was a 15-fold decrease in affinity of α-mFab for tat-mIgG compared with mIgG. Internalized radioactivity imported into the nucleus for 123I-tat-mIgG in MDA-MB-468, MDA-MB-231 and MCF-7 cells was 61.5±0.6%, 60.3±3.6% and 64.7±1.0%, respectively. The binding of 123I-α-mFab to lysate from MDA-MB-468 cells importing tat-mIgG was 17-fold higher than that for cells not exposed to tat-mIgG. Imported tat-mIgG competed with tat-mIgG for displacement of binding of 123I-mIgG to α-mFab. Conjugation of mIgG to tat peptides did not change tissue distribution. Nuclear localization for 123I-tat-mIgG in MDA-MB-468 tumours was 28.1±5.6%, and for liver, spleen and kidneys it was 41.7±2.7%, 13.8±0.8% and 36.9±3.3%, respectively. (orig.)
Typhoid fever as cellular microbiological model
Andrade Dahir Ramos de
2003-01-01
Full Text Available The knowledge about typhoid fever pathogenesis is growing in the last years, mainly about the cellular and molecular phenomena that are responsible by clinical manifestations of this disease. In this article are discussed several recent discoveries, as follows: a Bacterial type III protein secretion system; b The five virulence genes of Salmonella spp. that encoding Sips (Salmonella invasion protein A, B, C, D and E, which are capable of induce apoptosis in macrophages; c The function of Toll R2 and Toll R4 receptors present in the macrophage surface (discovered in the Drosophila. The Toll family receptors are critical in the signalizing mediated by LPS in macrophages in association with LBP and CD14; d The lines of immune defense between intestinal lumen and internal organs; e The fundamental role of the endothelial cells in the inflammatory deviation from bloodstream into infected tissues by bacteria. In addition to above subjects, the authors comment the correlation between the clinical features of typhoid fever and the cellular and molecular phenomena of this disease, as well as the therapeutic consequences of this knowledge.
Typhoid fever as cellular microbiological model.
de Andrade, Dahir Ramos; de Andrade Júnior, Dahir Ramos
2003-01-01
The knowledge about typhoid fever pathogenesis is growing in the last years, mainly about the cellular and molecular phenomena that are responsible by clinical manifestations of this disease. In this article are discussed several recent discoveries, as follows: a) Bacterial type III protein secretion system; b) The five virulence genes of Salmonella spp. that encoding Sips (Salmonella invasion protein) A, B, C, D and E, which are capable of induce apoptosis in macrophages; c) The function of Toll R2 and Toll R4 receptors present in the macrophage surface (discovered in the Drosophila). The Toll family receptors are critical in the signalizing mediated by LPS in macrophages in association with LBP and CD14; d) The lines of immune defense between intestinal lumen and internal organs; e) The fundamental role of the endothelial cells in the inflammatory deviation from bloodstream into infected tissues by bacteria. In addition to above subjects, the authors comment the correlation between the clinical features of typhoid fever and the cellular and molecular phenomena of this disease, as well as the therapeutic consequences of this knowledge. PMID:14502344
Inhibitors of cyclo-oxygenase (COX)-2 are being extensively studied as anticancer agents. In the present study we evaluated the mechanisms by which a highly selective COX-2 inhibitor, celecoxib, affects tumor growth of two differentially invasive human breast cancer cell lines. MDA-MB-231 (highly invasive) and MDA-MB-468 (moderately invasive) cell lines were treated with varying concentrations of celecoxib in vitro, and the effects of this agent on cell growth and angiogenesis were monitored by evaluating cell proliferation, apoptosis, cell cycle arrest, and vasculogenic mimicry. The in vitro results of MDA-MB-231 cell line were further confirmed in vivo in a mouse xenograft model. The highly invasive MDA-MB-231 cells express higher levels of COX-2 than do the less invasive MDA-MB-468 cells. Celecoxib treatment inhibited COX-2 activity, indicated by prostaglandin E2 secretion, and caused significant growth arrest in both breast cancer cell lines. In the highly invasive MDA-MB-231 cells, the mechanism of celecoxib-induced growth arrest was by induction of apoptosis, associated with reduced activation of protein kinase B/Akt, and subsequent activation of caspases 3 and 7. In the less invasive MDA-MB-468 cells, growth arrest was a consequence of cell cycle arrest at the G0/G1 checkpoint. Celecoxib-induced growth inhibition was reversed by addition of exogenous prostaglandin E2 in MDA-MB-468 cells but not in MDA-MB-231 cells. Furthermore, MDA-MB-468 cells formed significantly fewer extracellular matrix associated microvascular channels in vitro than did the high COX-2 expressing MDA-MB-231 cells. Celecoxib treatment not only inhibited cell growth and vascular channel formation but also reduced vascular endothelial growth factor levels. The in vitro findings corroborated in vivo data from a mouse xenograft model in which daily administration of celecoxib significantly reduced tumor growth of MDA-MB-231 cells, which was associated with reduced vascularization and
Modeling In Vitro Cellular Responses to Silver Nanoparticles
Dwaipayan Mukherjee
2014-01-01
Full Text Available Engineered nanoparticles (NPs have been widely demonstrated to induce toxic effects to various cell types. In vitro cell exposure systems have high potential for reliable, high throughput screening of nanoparticle toxicity, allowing focusing on particular pathways while excluding unwanted effects due to other cells or tissue dosimetry. The work presented here involves a detailed biologically based computational model of cellular interactions with NPs; it utilizes measurements performed in human cell culture systems in vitro, to develop a mechanistic mathematical model that can support analysis and prediction of in vivo effects of NPs. The model considers basic cellular mechanisms including proliferation, apoptosis, and production of cytokines in response to NPs. This new model is implemented for macrophages and parameterized using in vitro measurements of changes in cellular viability and mRNA levels of cytokines: TNF, IL-1b, IL-6, IL-8, and IL-10. The model includes in vitro cellular dosimetry due to nanoparticle transport and transformation. Furthermore, the model developed here optimizes the essential cellular parameters based on in vitro measurements, and provides a “stepping stone” for the development of more advanced in vivo models that will incorporate additional cellular and NP interactions.
TRAFFIC FLOW MODEL BASED ON CELLULAR AUTOMATION WITH ADAPTIVE DECELERATION
Shinkarev, A. A.
2016-01-01
This paper describes continuation of the authors’ work in the field of traffic flow mathematical models based on the cellular automata theory. The refactored representation of the multifactorial traffic flow model based on the cellular automata theory is used for a representation of an adaptive deceleration step implementation. The adaptive deceleration step in the case of a leader deceleration allows slowing down smoothly but not instantly. Concepts of the number of time steps without confli...
Oh, Eung Seok; Heo, Chaejeong; Kim, Ji Seon; Lee, Young Hee; Kim, Jong Min
2013-05-01
Parkinson's disease (PD) is characterized by progressive dopaminergic cell loss in the substantianigra (SN) and elevated iron levels demonstrated by autopsy and with 7-Tesla magnetic resonance imaging. Direct visualization of iron with live imaging techniques has not yet been successful. The aim of this study is to visualize and quantify the distribution of cellular iron using an intrinsic iron hyperspectral fluorescence signal. The 1-methyl-4-phenylpyridinium (MPP+)-induced cellular model of PD was established in SHSY5Y cells. The cells were exposed to iron by treatment with ferric ammonium citrate (FAC, 100 μM) for up to 6 hours. The hyperspectral fluorescence imaging signal of iron was examined usinga high- resolution dark-field optical microscope system with signal absorption for the visible/ near infrared (VNIR) spectral range. The 6-hour group showed heavy cellular iron deposition compared with the small amount of iron accumulation in the 1-hour group. The cellular iron was dispersed in a small, particulate form, whereas extracellular iron was detected in an aggregated form. In addition, iron particles were found to be concentrated on the cell membrane/edge of shrunken cells. The cellular iron accumulation readily occurred in MPP+-induced cells, which is consistent with previous studies demonstrating elevated iron levels in the SN in PD. This direct iron imaging methodology could be applied to analyze the physiological role of iron in PD, and its application might be expanded to various neurological disorders involving other metals, such as copper, manganese or zinc.
Cellular automaton for realistic modelling of landslides
E. Segre
1995-01-01
Full Text Available A numerical model is developed for the simulation of debris flow in landslides over a complex three dimensional topography. The model is then validated by comparing a simulation with reported field data. Our model is in fact a realistic elaboration of simpler "sandpile automata", which have in recent years been studied as supposedly paradigmatic of "self-organized criticality". Statistics and scaling properties of the simulation are examined, and show that the model has an intermittent behaviour.
Body composition analysis: Cellular level modeling of body component ratios
Z. Wang; Heymsfield, S. B.; PI-SUNYER, F.X.; Gallagher, D.; PIERSON, R.N.
2008-01-01
During the past two decades, a major outgrowth of efforts by our research group at St. Luke’s-Roosevelt Hospital is the development of body composition models that include cellular level models, models based on body component ratios, total body potassium models, multi-component models, and resting energy expenditure-body composition models. This review summarizes these models with emphasis on component ratios that we believe are fundamental to understanding human body composition during growt...
QSAR modeling, synthesis and bioassay of diverse leukemia RPMI-8226 cell line active agents.
Katritzky, Alan R; Girgis, Adel S; Slavov, Svetoslav; Tala, Srinivasa R; Stoyanova-Slavova, Iva
2010-11-01
A rigorous QSAR modeling procedure employing CODESSA PRO descriptors has been utilized for the prediction of more efficient anti-leukemia agents. Experimental data concerning the effect on leukemia RPMI-8226 cell line tumor growth of 34 compounds (treated at a dose of 10 μM) was related to their chemical structures by a 4-descriptor QSAR model. Four bis(oxy)bis-urea and bis(sulfanediyl)bis-urea derivatives (4a, 4b, 8, 11a) predicted as active by this model, together with 11b predicted to be of low activity, were synthesized and screened for anti-tumor activity utilizing 55 different tumor cell lines. Compounds 8 and 11a showed anti-tumor properties against most of the adopted cell lines with growth inhibition exceeding 50%. The highly promising preliminary anti-tumor properties of compounds 8 and 11a, were screened at serial dilutions (10(-4)-10(-8) μM) for determination of their GI(50) and TGI against the screened human tumor cell lines. Compound 11a (GI(50) = 1.55, TGI = 8.68 μM) is more effective than compound 8 (GI(50)=58.30, TGI = > 100 μM) against the target leukemia RPMI-8226 cell line. Compound 11a also exhibits highly pronounced anti-tumor properties against NCI-H226, NCI-H23 (non-small cell lung cancer), COLO 205 (colon cancer), SNB-75 (CNS cancer), OVCAR-3, SK-OV-3 (ovarian cancer), A498 (renal cancer) MDA-MB-231/ATCC and MDA-MB-468 (breast cancer) cell lines (GI(50) = 1.95, 1.61, 1.38, 1.56, 1.30, 1.98, 1.18, 1.85, 1.08, TGI = 8.35, 6.01, 2.67, 8.59, 4.01, 7.01, 5.62, 6.38, 5.63 μM, respectively). Thus 11a could be a suitable lead towards the design of broad spectrum anti-tumor active agents targeting various human tumor cell lines. PMID:20843586
Modeling cellular deformations using the level set formalism
Yang Liu
2008-07-01
Full Text Available Abstract Background Many cellular processes involve substantial shape changes. Traditional simulations of these cell shape changes require that grids and boundaries be moved as the cell's shape evolves. Here we demonstrate that accurate cell shape changes can be recreated using level set methods (LSM, in which the cellular shape is defined implicitly, thereby eschewing the need for updating boundaries. Results We obtain a viscoelastic model of Dictyostelium cells using micropipette aspiration and show how this viscoelastic model can be incorporated into LSM simulations to recreate the observed protrusion of cells into the micropipette faithfully. We also demonstrate the use of our techniques by simulating the cell shape changes elicited by the chemotactic response to an external chemoattractant gradient. Conclusion Our results provide a simple but effective means of incorporating cellular deformations into mathematical simulations of cell signaling. Such methods will be useful for simulating important cellular events such as chemotaxis and cytokinesis.
Computational model of cellular metabolic dynamics
Li, Yanjun; Solomon, Thomas; Haus, Jacob M;
2010-01-01
Identifying the mechanisms by which insulin regulates glucose metabolism in skeletal muscle is critical to understanding the etiology of insulin resistance and type 2 diabetes. Our knowledge of these mechanisms is limited by the difficulty of obtaining in vivo intracellular data. To quantitatively...... cytosol and mitochondria. The model simulated skeletal muscle metabolic responses to insulin corresponding to human hyperinsulinemic-euglycemic clamp studies. Insulin-mediated rate of glucose disposal was the primary model input. For model validation, simulations were compared with experimental data...... type 2 diabetes....
Modeling cellular deformations using the level set formalism
Yang Liu; Effler Janet C; Kutscher Brett L; Sullivan Sarah E; Robinson Douglas N; Iglesias Pablo A
2008-01-01
Abstract Background Many cellular processes involve substantial shape changes. Traditional simulations of these cell shape changes require that grids and boundaries be moved as the cell's shape evolves. Here we demonstrate that accurate cell shape changes can be recreated using level set methods (LSM), in which the cellular shape is defined implicitly, thereby eschewing the need for updating boundaries. Results We obtain a viscoelastic model of Dictyostelium cells using micropipette aspiratio...
Cellular automata modeling of cooperative eutectic growth
E. Olejnik; E. Fraś; D. Gurgul; A. Burbelko
2010-01-01
The model and results of the 2D simulation of the cooperative growth of two phases in the lamellar eutectic are presented. The pro-posed model takes into account heat transfer, components diffusion and nonstationary concentration distribution in the liquid and solid phases, non-equlibrium nature of the phase transformation and kinetics of the growth, influence of the surface energy and interface curva-ture on the conditions of the thermodynamic equilibrium. For the determination of the phase ...
Development and validation of computational models of cellular interaction
Smallwood, R H; Holcombe, W.M.L.; Walker, D C
2004-01-01
In this paper we take the view that computational models of biological systems should satisfy two conditions – they should be able to predict function at a systems biology level, and robust techniques of validation against biological models must be available. A modelling paradigm for developing a predictive computational model of cellular interaction is described, and methods of providing robust validation against biological models are explored, followed by a consideration of soft...
Cellular Automaton Model for Immunology of Tumor Growth
Voitikova, M
1998-01-01
The stochastic discrete space-time model of an immune response on tumor spreading in a two-dimensional square lattice has been developed. The immunity-tumor interactions are described at the cellular level and then transferred into the setting of cellular automata (CA). The multistate CA model for system, in which all statesoflattice sites, composing of both immune and tumor cells populations, are the functions of the states of the 12 nearest neighbors. The CA model incorporates the essential featuresof the immunity-tumor system. Three regimes of neoplastic evolution including metastatic tumor growth and screen effect by inactive immune cells surrounding a tumor have been predicted.
A cellular automata evacuation model considering friction and repulsion
SONG Weiguo; YU Yanfei; FAN Weicheng; Zhang Heping
2005-01-01
There exist interactions among pedestrians and between pedestrian and environment in evacuation. These interactions include attraction, repulsion and friction that play key roles in human evacuation behaviors, speed and efficiency. Most former evacuation models focus on the attraction force, while repulsion and friction are not well modeled. As a kind of multi-particle self-driven model, the social force model introduced in recent years can represent those three forces but with low simulation efficiency because it is a continuous model with complex rules. Discrete models such as the cellular automata model and the lattice gas model have simple rules and high simulation efficiency, but are not quite suitable for interactions' simulation. In this paper, a new cellular automata model based on traditional models is introduced in which repulsion and friction are modeled quantitatively. It is indicated that the model can simulate some basic behaviors, e.g.arching and the "faster-is-slower" phenomenon, in evacuation as multi-particle self-driven models, but with high efficiency as the normal cellular automata model and the lattice gas model.
Modeling diffusion of innovations with probabilistic cellular automata
Boccara, Nino; Fuks, Henryk
1997-01-01
We present a family of one-dimensional cellular automata modeling the diffusion of an innovation in a population. Starting from simple deterministic rules, we construct models parameterized by the interaction range and exhibiting a second-order phase transition. We show that the number of individuals who eventually keep adopting the innovation strongly depends on connectivity between individuals.
Modeling integrated cellular machinery using hybrid Petri-Boolean networks.
Natalie Berestovsky
Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them
Paydar M
2014-06-01
Full Text Available Mohammadjavad Paydar,1 Behnam Kamalidehghan,2 Yi Li Wong,1 Won Fen Wong,3 Chung Yeng Looi,1 Mohd Rais Mustafa11Department of Pharmacology, 2Department of Pharmacy, 3Department of Medical Microbiology, Faculty of Medicine, University of Malaya, Kuala Lumpur, MalaysiaAbstract: To date, plants have been the major source of anticancer drugs. Boldine is a natural alkaloid commonly found in the leaves and bark of Peumus boldus. In this study, we found that boldine potently inhibited the viability of the human invasive breast cancer cell lines, MDA-MB-231 (48-hour IC50 46.5±3.1 µg/mL and MDA-MB-468 (48-hour IC50 50.8±2.7 µg/mL. Boldine had a cytotoxic effect and induced apoptosis in breast cancer cells as indicated by a higher amount of lactate dehydrogenase released, membrane permeability, and DNA fragmentation. In addition, we demonstrated that boldine induced cell cycle arrest at G2/M phase. The anticancer mechanism is associated with disruption of the mitochondrial membrane potential and release of cytochrome c in MDA-MB-231. Boldine selectively induced activation of caspase-9 and caspase-3/7, but not caspase-8. We also found that boldine could inhibit nuclear factor kappa B activation, a key molecule in tumor progression and metastasis. In addition, protein array and Western blotting analysis showed that treatment with boldine resulted in downregulation of Bcl-2 and heat shock protein 70 and upregulation of Bax in the MDA-MB-231 cell line. An acute toxicity study in rats revealed that boldine at a dose of 100 mg/kg body weight was well tolerated. Moreover, intraperitoneal injection of boldine (50 or 100 mg/kg significantly reduced tumor size in an animal model of breast cancer. Our results suggest that boldine is a potentially useful agent for the treatment of breast cancer.Keywords: boldine, breast cancer, caspase cascade, Bcl-2/Bax, heat shock protein 70, nuclear factor kappa B
WWW Business Applications Based on the Cellular Model
Toshio Kodama; Tosiyasu L. Kunii; Yoichi Seki
2008-01-01
A cellular model based on the Incrementally Modular Abstraction Hierarchy (IMAH) is a novel model that can represent the architecture of and changes in cyberworlds, preserving invariants from a general level to a specific one. We have developed a data processing system called the Cellular Data System (CDS). In the development of business applications, you can prevent combinatorial explosion in the process of business design and testing by using CDS. In this paper, we have first designed and implemented wide-use algebra on the presentation level. Next, we have developed and verified the effectiveness of two general business applications using CDS: 1) a customer information management system, and 2) an estimate system.
Lattice gas cellular automata and lattice Boltzmann models an introduction
Wolf-Gladrow, Dieter A
2000-01-01
Lattice-gas cellular automata (LGCA) and lattice Boltzmann models (LBM) are relatively new and promising methods for the numerical solution of nonlinear partial differential equations. The book provides an introduction for graduate students and researchers. Working knowledge of calculus is required and experience in PDEs and fluid dynamics is recommended. Some peculiarities of cellular automata are outlined in Chapter 2. The properties of various LGCA and special coding techniques are discussed in Chapter 3. Concepts from statistical mechanics (Chapter 4) provide the necessary theoretical background for LGCA and LBM. The properties of lattice Boltzmann models and a method for their construction are presented in Chapter 5.
Modeling evolution and immune system by cellular automata
Bezzi, M. [Scuola Internazionale Superiore di Studi Avanzati, Trieste (Italy); Istituto Nazionale di Fisica della Materia, Florence (Italy)
2001-07-01
In this review the behavior of two different biological systems is investigated using cellular automata. Starting from this spatially extended approach it is also tried, in some cases, to reduce the complexity of the system introducing mean-field approximation, and solving (or trying to solve) these simplified systems. It is discussed the biological meaning of the results, the comparison with experimental data (if available) and the different features between spatially extended and mean-field versions. The biological systems considered in this review are the following: Darwinian evolution in simple ecosystems and immune system response. In the first section the main features of molecular evolution are introduced, giving a short survey of genetics for physicists and discussing some models for prebiotic systems and simple ecosystems. It is also introduced a cellular automaton model for studying a set of evolving individuals in a general fitness landscape, considering also the effects of co-evolution. In particular the process of species formation (speciation) is described in sect. 5. The second part deals with immune system modeling. The biological features of immune response are discussed, as well as it is introduced the concept of shape space and of idiotypic network. More detailed reviews which deal with immune system models (mainly focused on idiotypic network models) can be found. Other themes here discussed: the applications of CA to immune system modeling, two complex cellular automata for humoral and cellular immune response. Finally, it is discussed the biological data and the general conclusions are drawn in the last section.
Modeling evolution and immune system by cellular automata
In this review the behavior of two different biological systems is investigated using cellular automata. Starting from this spatially extended approach it is also tried, in some cases, to reduce the complexity of the system introducing mean-field approximation, and solving (or trying to solve) these simplified systems. It is discussed the biological meaning of the results, the comparison with experimental data (if available) and the different features between spatially extended and mean-field versions. The biological systems considered in this review are the following: Darwinian evolution in simple ecosystems and immune system response. In the first section the main features of molecular evolution are introduced, giving a short survey of genetics for physicists and discussing some models for prebiotic systems and simple ecosystems. It is also introduced a cellular automaton model for studying a set of evolving individuals in a general fitness landscape, considering also the effects of co-evolution. In particular the process of species formation (speciation) is described in sect. 5. The second part deals with immune system modeling. The biological features of immune response are discussed, as well as it is introduced the concept of shape space and of idiotypic network. More detailed reviews which deal with immune system models (mainly focused on idiotypic network models) can be found. Other themes here discussed: the applications of CA to immune system modeling, two complex cellular automata for humoral and cellular immune response. Finally, it is discussed the biological data and the general conclusions are drawn in the last section
A sub-cellular viscoelastic model for cell population mechanics.
Yousef Jamali
Full Text Available Understanding the biomechanical properties and the effect of biomechanical force on epithelial cells is key to understanding how epithelial cells form uniquely shaped structures in two or three-dimensional space. Nevertheless, with the limitations and challenges posed by biological experiments at this scale, it becomes advantageous to use mathematical and 'in silico' (computational models as an alternate solution. This paper introduces a single-cell-based model representing the cross section of a typical tissue. Each cell in this model is an individual unit containing several sub-cellular elements, such as the elastic plasma membrane, enclosed viscoelastic elements that play the role of cytoskeleton, and the viscoelastic elements of the cell nucleus. The cell membrane is divided into segments where each segment (or point incorporates the cell's interaction and communication with other cells and its environment. The model is capable of simulating how cells cooperate and contribute to the overall structure and function of a particular tissue; it mimics many aspects of cellular behavior such as cell growth, division, apoptosis and polarization. The model allows for investigation of the biomechanical properties of cells, cell-cell interactions, effect of environment on cellular clusters, and how individual cells work together and contribute to the structure and function of a particular tissue. To evaluate the current approach in modeling different topologies of growing tissues in distinct biochemical conditions of the surrounding media, we model several key cellular phenomena, namely monolayer cell culture, effects of adhesion intensity, growth of epithelial cell through interaction with extra-cellular matrix (ECM, effects of a gap in the ECM, tensegrity and tissue morphogenesis and formation of hollow epithelial acini. The proposed computational model enables one to isolate the effects of biomechanical properties of individual cells and the
Station Model for Rail Transit System Using Cellular Automata
XUN Jing; NING Bin; LI Ke-Ping
2009-01-01
In this paper, we propose a new cellular automata model to simulate the railway traffic at station.Based on NaSch model, the proposed station model is composed of the main track and the siding track.Two different schemes for trains passing through station are considered.One is the scheme of "pass by the main track, start and stop by the siding track".The other is the scheme of "two tracks play the same role".We simulate the train movement using the proposed model and analyze the traffic flow at station.The simulation results demonstrate that the proposed cellular automata model can be successfully used for the simulations of railway traffic.Some characteristic behaviors of railway traffic flow can be reproduced.Moreover, the simulation values of the minimum headway are close to the theoretical values.This result demonstrates the dependability and availability of the proposed model.
Cellular worlds: a framework for modeling micro - macro dynamics
H Couclelis
1985-01-01
Cellular spaces have recently received a lot of attention in computer science and elsewhere as models capable of bridging the gap between disaggregate and aggregate description. Despite their obvious spatial interpretation, standard cell-space models are too constrained by their background conventions to be useful in realistic geographic applications. In this paper, a generalization of the cell-space principle is presented, based on discrete model theory, and then applied to a hypothetical bu...
A Modified Cellular Automaton Model for Traffic Flow
葛红霞; 董力耘; 雷丽; 戴世强
2004-01-01
A modified cellular automaton model for traffic flow was proposed. A novel concept about the changeable security gap was introduced and a parameter related to the variable security gap was determined. The fundamental diagram obtained by simulation shows that the maximum flow more approaches to the observed data than that of the NaSch model, indicating that the presented model is more reasonable and realistic.
The brittleness model of complex system based on cellular automata
LIN De-ming; JIN Hong-zhang; LI Qi; WU Hong-mei
2004-01-01
Now the research on the complex system is a hot spot. Brittleness is one of the basic characteristics of a complex system. In a complex system, after one of subsystems is struck to be collapsed, the whole system will collapse. Meanwhile, cellular automata is a discrete dynamic system. When the rule is given, the cellular automata could be defined. Then it can imitate the complex action. Cellular automata is used to simulate the brittleness action in this study. Entropy was used to analyze the action and get the rule. Then,three normal brittleness models were given. The result shows that the brittleness of complex system is existent and in addition some important behavior mode of complex system brittleness has been achieved.
Fire Spread Model for Old Towns Based on Cellular Automaton
GAO Nan; WENG Wenguo; MA Wei; NI Shunjiang; HUANG Quanyi; YUAN Hongyong
2008-01-01
Old towns like Lijiang have enormous historic,artistic,and architectural value.The buildings in such old towns are usually made of highly combustible materials,such as wood and grass.If a fire breaks out,it will spread to multiple buildings,so fire spreading and controlling in old towns need to be studied.This paper presents a fire spread model for old towns based on cellular automaton.The cellular automaton rules were set according to historical fire data in empirical formulas.The model also considered the effects of climate.The simulation results were visualized in a geography information system.An example of a fire spread in Lijiang was investigated with the results showing that this model provides a realistic tool for predicting fire spread in old towns.Fire brigades can use this tool to predict when and how a fire spreads to minimize the losses.
An intelligent floor field cellular automata model for pedestrian dynamics
Kirik, Ekaterina; Krouglov, Dmitriy
2009-01-01
A stochastic cellular automata (CA) model for pedestrian dynamics is presented. Our goal is to simulate different types of pedestrian movement, from regular to panic. But here we emphasize regular situations which imply that pedestrians analyze environment and choose their route more carefully. And transition probabilities have to depict such effect. The potentials of floor fields and environment analysis are combined in the model obtained. People patience is included in the model. This makes simulation of pedestrians movement more realistic. Some simulation results are presented and comparison with basic FF-model is made.
A cellular automata model of Ebola virus dynamics
Burkhead, Emily; Hawkins, Jane
2015-11-01
We construct a stochastic cellular automaton (SCA) model for the spread of the Ebola virus (EBOV). We make substantial modifications to an existing SCA model used for HIV, introduced by others and studied by the authors. We give a rigorous analysis of the similarities between models due to the spread of virus and the typical immune response to it, and the differences which reflect the drastically different timing of the course of EBOV. We demonstrate output from the model and compare it with clinical data.
Car Deceleration Considering Its Own Velocity in Cellular Automata Model
LI Ke-Ping
2006-01-01
In this paper, we propose a new cellular automaton model, which is based on NaSch traffic model. In our method, when a car has a larger velocity, if the gap between the car and its leading car is not enough large, it will decrease. The aim is that the following car has a buffer space to decrease its velocity at the next time, and then avoid to decelerate too high. The simulation results show that using our model, the car deceleration is realistic, and is closer to thefield measure than that of NaSch model.
Simulations of Living Cell Origins Using a Cellular Automata Model
Ishida, Takeshi
2014-04-01
Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.
Mathematical model for flood routing based on cellular automaton
Xin CAI
2014-04-01
Full Text Available Increasing frequency and severity of flooding have caused tremendous damage in China, requiring more essential countermeasures to alleviate the damage. In this study, the dynamic simulation property of a cellular automaton was used to make further progress in flood routing. In consideration of terrain’s influence on flood routing, we regarded the terrain elevation as an auxiliary attribute of a two-dimensional cellular automaton in path selection for flood routing and developed a mathematical model based on a cellular automaton. A numerical case of propagation of an outburst flood in an area of the lower Yangtze River was analyzed with both the fixed-step and variable-step models. The results show that the flood does not spread simultaneously in all directions, but flows into the lower place first, and that the submerged area grows quickly at the beginning, but slowly later on. The final submerged areas obtained from the two different models are consistent, and the flood volume balance test shows that the flood volume meets the requirement of the total volume balance. The analysis of the case shows that the proposed model can be a valuable tool for flood routing.
Modeling self-organizing traffic lights with elementary cellular automata
Gershenson, Carlos
2009-01-01
There have been several highway traffic models proposed based on cellular automata. The simplest one is elementary cellular automaton rule 184. We extend this model to city traffic with cellular automata coupled at intersections using only rules 184, 252, and 136. The simplicity of the model offers a clear understanding of the main properties of city traffic and its phase transitions. We use the proposed model to compare two methods for coordinating traffic lights: a green-wave method that tries to optimize phases according to expected flows and a self-organizing method that adapts to the current traffic conditions. The self-organizing method delivers considerable improvements over the green-wave method. For low densities, the self-organizing method promotes the formation and coordination of platoons that flow freely in four directions, i.e. with a maximum velocity and no stops. For medium densities, the method allows a constant usage of the intersections, exploiting their maximum flux capacity. For high dens...
A Cellular Model for Screening Neuronal Nitric Oxide Synthase Inhibitors
Fang, Jianguo; Silverman, Richard B.
2009-01-01
Nitric oxide synthase (NOS) inhibitors are potential drug candidates because it has been well demonstrated that excessive production of NO critically contributes to a range of diseases. Most inhibitors have been screened in vitro using recombinant enzymes, leading to the discovery of a variety of potent compounds. To make inhibition studies more physiologically relevant and bridge the gap between the in vitro assay and in vivo studies, we report here a cellular model for screening NOS inhibit...
Cellular-Based Statistical Model for Mobile Dispersion
Abdulla, Mouhamed; Shayan, Yousef R.
2013-01-01
While analyzing mobile systems we often approximate the actual coverage surface and assume an ideal cell shape. In a multi-cellular network, because of its tessellating nature, a hexagon is more preferred than a circular geometry. Despite this reality, perhaps due to the inherent simplicity, only a model for circular based random spreading is available. However, if used, this results an unfair terminal distribution for non-circular contours. Therefore, in this paper we specifically derived an...
Modelling of detonation cellular structure in aluminium suspensions
Briand, A.; Veyssiere, B.; Khasainov, B. A.
2010-12-01
Heterogeneous detonations involving aluminium suspensions have been studied for many years for industrial safety policies, and for military and propulsion applications. Owing to their weak detonability and to the lack of available experimental results on the detonation cellular structure, numerical simulations provide a convenient way to improve the knowledge of such detonations. One major difficulty arising in numerical study of heterogeneous detonations involving suspensions of aluminium particles in oxidizing atmospheres is the modelling of aluminium combustion. Our previous two-step model provided results on the effect on the detonation cellular structure of particle diameter and characteristic chemical lengths. In this study, a hybrid model is incorporated in the numerical code EFAE, combining both kinetic and diffusion regimes in parallel. This more realistic model provides good agreement with the previous two-step model and confirms the correlations found between the detonation cell width, and particle diameter and characteristic lengths. Moreover, the linear dependence found between the detonation cell width and the induction length remains valid with the hybrid model.
A cellular automaton model for tumor growth in heterogeneous environment
Jiao, Yang; Torquato, Sal
2011-03-01
Cancer is not a single disease: it exhibits heterogeneity on different spatial and temporal scales and strongly interacts with its host environment. Most mathematical modeling of malignant tumor growth has assumed a homogeneous host environment. We have developed a cellular automaton model for tumor growth that explicitly incorporates the structural heterogeneity of the host environment such as tumor stroma. We show that these structural heterogeneities have non-trivial effects on the tumor growth dynamics and prognosis. Y. J. is supported by PSOC, NCI.
Cellular automata model of magnetospheric-ionospheric coupling
Kozelov, B. V.; Kozelova, T. V.
2003-01-01
We propose a cellular automata model (CAM) to describe the substorm activity of the magnetospheric-ionospheric system. The state of each cell in the model is described by two numbers that correspond to the energy content in a region of the current sheet in the magnetospheric tail and to the conductivity of the ionospheric domain that is magnetically connected with this region. The driving force of the system is supposed to be provided by the solar wind that is convected along the two b...
A Realistic Cellular Automaton Model for Synchronized Traffic Flow
ZHAO Bo-Han; HU Mao-Bin; JIANG Rui; WU Qing-Song
2009-01-01
A cellular automaton model is proposed to consider the anticipation effect in drivers' behavior. It is shown that the anticipation effect can be one of the origins of synchronized traffic flow. With anticipation effect, the congested traffic flow simulated by the model exhibits the features of synchronized flow. The spatiotemporal patterns induced by an on-ramp are also consistent with the three-phaee traffic theory. Since the origin of synchronized flow is still controversial, our work can shed some light on the mechanism of synchronized flow.
Cellular automata modelling of phase-change memories
Wanhua Yu; David Wright
2008-01-01
A novel approach to modelling phase-transition processes in phase change materials used for optical and electrical data storage applications is presented. The model is based on a cellular automaton (CA) approach to predict crystallization behaviour that is linked to thermal and electrical simulations to enable the study of the data writing and erasing processes. The CA approach is shown to be able to predict the evolution of the microstructure during the rapid heating and cooling cycles pertinent to data storage technology, and maps crystallization behaviour on the nanoscale. A simple example based on possible future nonvolatile phase-change random access solid-state memory is presented.
Modeling and simulation for train control system using cellular automata
LI; KePing; GAO; ZiYou; YANG; LiXing
2007-01-01
Train control system plays a key role in railway traffic. Its function is to manage and control the train movement on railway networks. In our previous works, based on the cellular automata (CA) model, we proposed several models and algorithms for simulating the train movement under different control system conditions. However, these models are only suitable for some simple traffic conditions. Some basic factors, which are important for train movement, are not considered. In this paper, we extend these models and algorithms and give a unified formula. Using the proposed method, we analyze and discuss the space-time diagram of railway traffic flow and the trajectories of the train movement. The numerical simulation and analytical results demonstrate that the unified CA model is an effective tool for simulating the train control system.
Cellular automaton model considering headway-distance effect
Hu, Shou-Xin; Gao, Kun; Wang, Bing-Hong; Lu, Yu-Feng
2008-05-01
This paper presents a cellular automaton model for single-lane traffic flow. On the basis of the Nagel-Schreckenberg (NS) model, it further considers the effect of headway-distance between two successive cars on the randomization of the latter one. In numerical simulations, this model shows the following characteristics. (1) With a simple structure, this model succeeds in reproducing the hysteresis effect, which is absent in the NS model. (2) Compared with the slow-to-start models, this model exhibits a local fundamental diagram which is more consistent to empirical observations. (3) This model has much higher efficiency in dissolving congestions compared with the so-called NS model with velocity-dependent randomization (VDR model). (4) This model is more robust when facing traffic obstructions. It can resist much longer shock times and has much shorter relaxation times on the other hand. To summarize, compared with the existing models, this model is quite simple in structure, but has good characteristics.
Structural modeling of sandwich structures with lightweight cellular cores
T. Liu; Z. C. Deng; T. J. Lu
2007-01-01
An effective single layered finite element (FE) computational model is proposed to predict the structural behavior of lightweight sandwich panels having two dimensional (2D) prismatic or three dimensional (3D) truss cores.Three different types of cellular core topology are considered: pyramidal truss core (3D), Kagome truss core (3D) and corrugated core (2D), representing three kinds of material anisotropy: orthotropic, monoclinic and general anisotropic. A homogenization technique is developed to obtain the homogenized macroscopic stiffness properties of the cellular core. In comparison with the results obtained by using detailed FE model, the single layered computational model cangive acceptable predictions for both the static and dynamic behaviors of orthotropic truss core sandwich panels. However, for non-orthotropic 3D truss cores, the predictions are not so well. For both static and dynamic behaviors of a 2D corrugated core sandwich panel, the predictions derived by the single layered computational model is generally acceptable when the size of the unit cell varies within a certain range, with the predictions for moderately strong or strong corrugated cores more accurate than those for weak cores.
A Fluid Model for Performance Analysis in Cellular Networks
Coupechoux Marceau
2010-01-01
Full Text Available We propose a new framework to study the performance of cellular networks using a fluid model and we derive from this model analytical formulas for interference, outage probability, and spatial outage probability. The key idea of the fluid model is to consider the discrete base station (BS entities as a continuum of transmitters that are spatially distributed in the network. This model allows us to obtain simple analytical expressions to reveal main characteristics of the network. In this paper, we focus on the downlink other-cell interference factor (OCIF, which is defined for a given user as the ratio of its outer cell received power to its inner cell received power. A closed-form formula of the OCIF is provided in this paper. From this formula, we are able to obtain the global outage probability as well as the spatial outage probability, which depends on the location of a mobile station (MS initiating a new call. Our analytical results are compared to Monte Carlo simulations performed in a traditional hexagonal network. Furthermore, we demonstrate an application of the outage probability related to cell breathing and densification of cellular networks.
Integrating cellular metabolism into a multiscale whole-body model.
Markus Krauss
Full Text Available Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development.
Robustness of a Cellular Automata Model for the HIV Infection
Figueirêdo, P H; Santos, R M Zorzenon dos
2008-01-01
An investigation was conducted to study the robustness of the results obtained from the cellular automata model which describes the spread of the HIV infection within lymphoid tissues [R. M. Zorzenon dos Santos and S. Coutinho, Phys. Rev. Lett. 87, 168102 (2001)]. The analysis focussed on the dynamic behavior of the model when defined in lattices with different symmetries and dimensionalities. The results illustrated that the three-phase dynamics of the planar models suffered minor changes in relation to lattice symmetry variations and, while differences were observed regarding dimensionality changes, qualitative behavior was preserved. A further investigation was conducted into primary infection and sensitiveness of the latency period to variations of the model's stochastic parameters over wide ranging values. The variables characterizing primary infection and the latency period exhibited power-law behavior when the stochastic parameters varied over a few orders of magnitude. The power-law exponents were app...
Fluctuation in option pricing using cellular automata based market models
Gao, Yuying; Beni, Gerardo
2005-05-01
A new agent-based Cellular Automaton (CA) computational algorithm for option pricing is proposed. CAs have been extensively used in modeling complex dynamical systems but not in modeling option prices. Compared with traditional tools, which rely on guessing volatilities to calculate option prices, the CA model is directly addressing market mechanisms and simulates price fluctuation from aggregation of actions made by interacting individual market makers in a large population. This paper explores whether CA models can provide reasonable good answers to pricing European options. The Black-Scholes model and the Binomial Tree model are used for comparison. Comparison reveals that CA models perform reasonably well in pricing options, reproducing overall characteristics of random walk based model, while at the same time providing plausible results for the 'fat-tail' phenomenon observed in many markets. We also show that the binomial tree model can be obtained from a CA rule. Thus, CA models are suitable tools to generalize the standard theories of option pricing.
Simulation of root forms using cellular automata model
This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled “A New Kind of Science” discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram’s investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations
A hybrid parallel framework for the cellular Potts model simulations
Jiang, Yi [Los Alamos National Laboratory; He, Kejing [SOUTH CHINA UNIV; Dong, Shoubin [SOUTH CHINA UNIV
2009-01-01
The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approach achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).
Simulation of root forms using cellular automata model
Winarno, Nanang; Prima, Eka Cahya; Afifah, Ratih Mega Ayu
2016-02-01
This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled "A New Kind of Science" discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram's investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.
Simulation of root forms using cellular automata model
Winarno, Nanang, E-mail: nanang-winarno@upi.edu; Prima, Eka Cahya [International Program on Science Education, Universitas Pendidikan Indonesia, Jl. Dr. Setiabudi no 229, Bandung40154 (Indonesia); Afifah, Ratih Mega Ayu [Department of Physics Education, Post Graduate School, Universitas Pendidikan Indonesia, Jl. Dr. Setiabudi no 229, Bandung40154 (Indonesia)
2016-02-08
This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled “A New Kind of Science” discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram’s investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.
Tandon Apurva
2011-08-01
Full Text Available Abstract Background In normal cells proliferation and apoptosis are tightly regulated, whereas in tumor cells the balance is shifted in favor of increased proliferation and reduced apoptosis. Anticancer agents mediate tumor cell death via targeting multiple pathways of programmed cell death. We have reported that the non-pathogenic, tumor suppressive Adeno-Associated Virus Type 2 (AAV2 induces apoptosis in Human Papillomavirus (HPV positive cervical cancer cells, but not in normal keratinocytes. In the current study, we examined the potential of AAV2 to inhibit proliferation of MCF-7 and MDA-MB-468 (both weakly invasive, as well as MDA-MB-231 (highly invasive human breast cancer derived cell lines. As controls, we used normal human mammary epithelial cells (nHMECs isolated from tissue biopsies of patients undergoing breast reduction surgery. Results AAV2 infected MCF-7 line underwent caspase-independent, and MDA-MB-468 and MDA-MB-231 cell lines underwent caspase-dependent apoptosis. Death of MDA-MB-468 cells was marked by caspase-9 activation, whereas death of MDA-MB-231 cells was marked by activation of both caspase-8 and caspase-9, and resembled a mixture of apoptotic and necrotic cell death. Cellular demise was correlated with the ability of AAV2 to productively infect and differentially express AAV2 non-structural proteins: Rep78, Rep68 and Rep40, dependent on the cell line. Cell death in the MCF-7 and MDA-MB-231 lines coincided with increased S phase entry, whereas the MDA-MB-468 cells increasingly entered into G2. AAV2 infection led to decreased cell viability which correlated with increased expression of proliferation markers c-Myc and Ki-67. In contrast, nHMECs that were infected with AAV2 failed to establish productive infection or undergo apoptosis. Conclusion AAV2 regulated enrichment of cell cycle check-point functions in G1/S, S and G2 phases could create a favorable environment for Rep protein expression. Inherent Rep associated
National Oceanic and Atmospheric Administration, Department of Commerce — The purpose of this project is to adapt cellular in vitro assay systems of the rainbow trout pituitary, liver and ovary for high-throughput screening (HTS) of...
Cellular automaton model of cell response to targeted radiation
It has been shown that the response of cells to low doses of radiation is not linear and cannot be accurately extrapolated from the high dose response. To investigate possible mechanisms involved in the behaviour of cells under very low doses of radiation, a cellular automaton (CA) model was created. The diffusion and consumption of glucose in the culture dish were computed in parallel to the growth of cells. A new model for calculating survival probability was introduced; the communication between targeted and non-targeted cells was also included. Early results on the response of non-confluent cells to targeted irradiation showed the capability of the model to take account for the non-linear response in the low-dose domain
Cellular automaton model of coupled mass transport and chemical reactions
Mass transport, coupled with chemical reactions, is modelled as a cellular automaton in which solute molecules perform a random walk on a lattice and react according to a local probabilistic rule. Assuming molecular chaos and a smooth density function, we obtain the standard reaction-transport equations in the continuum limit. The model is applied to the reactions a + b ↔c and a + b →c, where we observe interesting macroscopic effects resulting from microscopic fluctuations and spatial correlations between molecules. We also simulate autocatalytic reaction schemes displaying spontaneous formation of spatial concentration patterns. Finally, we propose and discuss the limitations of a simple model for mineral-solute interaction. (author) 5 figs., 20 refs
Global Network Model based on Earth Grid and Cellular
Dongqi Lu
2014-06-01
Full Text Available We aim to understand the current health state of the Earth and find how human activities influence it. Based on the theory of Earth’s Grid and Cellular Automata, we define and test a global network model, analyze the mutual interactions and feedbacks of ecosystem, hydrologic circle and atmosphere. In addition, we consult a lot of data to find a benchmark for the “Earth Health Map”, with the ecosystem distribution on it, which can be helpful for making a strategic decision for policy makers and prediction. Our model can be extended to other similar fields. In the end, we discuss the sensitivity of parameters selection, and the superiorities and weaknesses of our model.
A cellular automata-based mathematical model for thymocyte development.
Hallan Souza-e-Silva
Full Text Available Intrathymic T cell development is an important process necessary for the normal formation of cell-mediated immune responses. Importantly, such a process depends on interactions of developing thymocytes with cellular and extracellular elements of the thymic microenvironment. Additionally, it includes a series of oriented and tunely regulated migration events, ultimately allowing mature cells to cross endothelial barriers and leave the organ. Herein we built a cellular automata-based mathematical model for thymocyte migration and development. The rules comprised in this model take into account the main stages of thymocyte development, two-dimensional sections of the normal thymic microenvironmental network, as well as the chemokines involved in intrathymic cell migration. Parameters of our computer simulations with further adjusted to results derived from previous experimental data using sub-lethally irradiated mice, in which thymus recovery can be evaluated. The model fitted with the increasing numbers of each CD4/CD8-defined thymocyte subset. It was further validated since it fitted with the times of permanence experimentally ascertained in each CD4/CD8-defined differentiation stage. Importantly, correlations using the whole mean volume of young normal adult mice revealed that the numbers of cells generated in silico with the mathematical model fall within the range of total thymocyte numbers seen in these animals. Furthermore, simulations made with a human thymic epithelial network using the same mathematical model generated similar profiles for temporal evolution of thymocyte developmental stages. Lastly, we provided in silico evidence that the thymus architecture is important in the thymocyte development, since changes in the epithelial network result in different theoretical profiles for T cell development/migration. This model likely can be used to predict thymocyte evolution following therapeutic strategies designed for recovery of the
Motor Schema-Based Cellular Automaton Model for Pedestrian Dynamics
Weng, Wenguo; Hasemi, Yuji; Fan, Weicheng
A new cellular automaton model for pedestrian dynamics based on motor schema is presented. Each pedestrian is treated as an intelligent mobile robot, and motor schemas including move-to-goal, avoid-away and avoid-around drive pedestrians to interact with their environment. We investigate the phenomenon of many pedestrians with different move velocities escaping from a room. The results show that the pedestrian with high velocity have predominance in competitive evacuation, if we only consider repulsion from or avoiding around other pedestrians, and interaction with each other leads to disordered evacuation, i.e., decreased evacuation efficiency. Extensions of the model using learning algorithms for controlling pedestrians, i.e., reinforcement learning, neural network and genetic algorithms, etc. are noted.
Critical Behavior in a Cellular Automata Animal Disease Transmission Model
Morley, P D; Chang, Julius
2003-01-01
Using a cellular automata model, we simulate the British Government Policy (BGP) in the 2001 foot and mouth epidemic in Great Britain. When clinical symptoms of the disease appeared on a farm, there is mandatory slaughter (culling) of all livestock on an infected premise (IP). Those farms that neighbor an IP (contiguous premise, CP), are also culled, aka nearest neighbor interaction. Farms where the disease may be prevalent from animal, human, vehicle or airborne transmission (dangerous contact, DC), are additionally culled, aka next-to-nearest neighbor iteractions and lightning factor. The resulting mathematical model possesses a phase transition, whereupon if the physical disease transmission kernel exceeds a critical value, catastrophic loss of animals ensues. The non-local disease transport probability can be as low as .01% per day and the disease can still be in the high mortality phase. We show that the fundamental equation for sustainable disease transport is the criticality equation for neutron fissio...
Multiscale Model of Colorectal Cancer Using the Cellular Potts Framework
Osborne, James M
2015-01-01
Colorectal cancer (CRC) is one of the major causes of death in the developed world and forms a canonical example of tumorigenesis. CRC arises from a string of mutations of individual cells in the colorectal crypt, making it particularly suited for multiscale multicellular modeling, where mutations of individual cells can be clearly represented and their effects readily tracked. In this paper, we present a multicellular model of the onset of colorectal cancer, utilizing the cellular Potts model (CPM). We use the model to investigate how, through the modification of their mechanical properties, mutant cells colonize the crypt. Moreover, we study the influence of mutations on the shape of cells in the crypt, suggesting possible cell- and tissue-level indicators for identifying early-stage cancerous crypts. Crucially, we discuss the effect that the motility parameters of the model (key factors in the behavior of the CPM) have on the distribution of cells within a homeostatic crypt, resulting in an optimal parameter regime that accurately reflects biological assumptions. In summary, the key results of this paper are 1) how to couple the CPM with processes occurring on other spatial scales, using the example of the crypt to motivate suitable motility parameters; 2) modeling mutant cells with the CPM; 3) and investigating how mutations influence the shape of cells in the crypt. PMID:26461973
Computer Modeling of the Earliest Cellular Structures and Functions
Pohorille, Andrew
2000-03-01
In the absence of extinct or extant record of protocells (the earliest ancestors of contemporary cells), the most direct way to test ourunderstanding of the origin of cellular life is to construct laboratory models of protocells. Such efforts are currently underway in the NASA Astrobiology Program. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs for molecules that perform protocellular functions. Many of these functions, such as import of nutrients, capture and storage of energy, and response to changes in the environment are carried out by proteins bound to membranes. We will discuss a series of large-scale, molecular-level computer simulations which demonstrate (a) how small proteins (peptides)organize themselves into ordered structures at water-membrane interfaces and insert into membranes, (b) how these peptides aggregate to form membrane-spanning structures (e.g. channels), and (c) by what mechanisms such aggregates perform essential protocellular functions, such as proton transport of protons across cell walls, a key step in cellular bioenergetics. The simulations were performed using the molecular dynamics method, in which Newton's equations of motion for each atom in the system are solved iteratively. The problems of interest required simulations on multi-nanosecond time scales, which corresponded to 10^6-10^8 time steps.
Load-Aware Modeling and Analysis of Heterogeneous Cellular Networks
Dhillon, Harpreet S; Andrews, Jeffrey G
2012-01-01
Random spatial models are attractive for modeling heterogeneous cellular networks (HCNs) due to their realism, tractability, and scalability. A major limitation of such models to date in the context of HCNs is the neglect of network traffic and load: all base stations (BSs) have typically been assumed to always be transmitting. Small cells in particular will have a lighter load than macrocells, and so their contribution to the network interference may be significantly overstated in a fully loaded model. This paper incorporates a flexible notion of BS load by introducing a new idea of conditionally thinning the interference field. For a $K$-tier HCN where BSs across tiers differ in terms of transmit power, supported data rate, deployment density, and now load, we derive the coverage probability for a typical mobile, which connects to the strongest BS signal. Conditioned on this connection, the interfering BSs of the $i^{th}$ tier are assumed to transmit independently with probability $p_i$, which models the lo...
A Computational Model of Cellular Response to Modulated Radiation Fields
Purpose: To develop a model to describe the response of cell populations to spatially modulated radiation exposures of relevance to advanced radiotherapies. Materials and Methods: A Monte Carlo model of cellular radiation response was developed. This model incorporated damage from both direct radiation and intercellular communication including bystander signaling. The predictions of this model were compared to previously measured survival curves for a normal human fibroblast line (AGO1522) and prostate tumor cells (DU145) exposed to spatially modulated fields. Results: The model was found to be able to accurately reproduce cell survival both in populations which were directly exposed to radiation and those which were outside the primary treatment field. The model predicts that the bystander effect makes a significant contribution to cell killing even in uniformly irradiated cells. The bystander effect contribution varies strongly with dose, falling from a high of 80% at low doses to 25% and 50% at 4 Gy for AGO1522 and DU145 cells, respectively. This was verified using the inducible nitric oxide synthase inhibitor aminoguanidine to inhibit the bystander effect in cells exposed to different doses, which showed significantly larger reductions in cell killing at lower doses. Conclusions: The model presented in this work accurately reproduces cell survival following modulated radiation exposures, both in and out of the primary treatment field, by incorporating a bystander component. In addition, the model suggests that the bystander effect is responsible for a significant portion of cell killing in uniformly irradiated cells, 50% and 70% at doses of 2 Gy in AGO1522 and DU145 cells, respectively. This description is a significant departure from accepted radiobiological models and may have a significant impact on optimization of treatment planning approaches if proven to be applicable in vivo.
A cellular automaton model for neurogenesis in Drosophila
Luthi, Pascal O.; Chopard, Bastien; Preiss, Anette; Ramsden, Jeremy J.
1998-07-01
A cellular automaton (CA) is constructed for the formation of the central nervous system of the Drosophila embryo. This is an experimentally well-studied system in which complex interactions between neighbouring cells appear to drive their differentiation into different types. It appears that all the cells initially have the potential to become neuroblasts, and all strive to this end, but those which differentiate first block their as yet undifferentiated neighbours from doing so. The CA makes use of observational evidence for a lateral inhibition mechanism involving signalling products S of the ‘proneural’ or neuralizing genes. The key concept of the model is that cells are continuously producing S, but the production rate is lowered by inhibitory signals received from neighbouring cells which have advanced further along the developmental pathway. Comparison with experimental data shows that it well accounts for the observed proportion of neuroectodermal cells delaminating as neuroblasts.
Cellular automaton model of mass transport with chemical reactions
The transport and chemical reactions of solutes are modelled as a cellular automaton in which molecules of different species perform a random walk on a regular lattice and react according to a local probabilistic rule. The model describes advection and diffusion in a simple way, and as no restriction is placed on the number of particles at a lattice site, it is also able to describe a wide variety of chemical reactions. Assuming molecular chaos and a smooth density function, we obtain the standard reaction-transport equations in the continuum limit. Simulations on one-and two-dimensional lattices show that the discrete model can be used to approximate the solutions of the continuum equations. We discuss discrepancies which arise from correlations between molecules and how these discrepancies disappear as the continuum limit is approached. Of particular interest are simulations displaying long-time behaviour which depends on long-wavelength statistical fluctuations not accounted for by the standard equations. The model is applied to the reactions a + b ↔ c and a + b → c with homogeneous and inhomogeneous initial conditions as well as to systems subject to autocatalytic reactions and displaying spontaneous formation of spatial concentration patterns. (author) 9 figs., 34 refs
COMPARATIVE ANALYSIS OF CONGESTION CONTROL MODELS FOR CELLULAR WIRELESS NETWORK
Falade A. J
2015-08-01
Full Text Available Cellular wireless systems like GSM suffer from congestion resulting in overall system degradation and poor service delivery. When the traffic demand in a geographical area is high, the input traffic rate will exceed thecapacity of the output lines. This work focused on homogenous wireless network (the network traffic and resource dimensioning that are statistically identical such that the network performance evaluation can be reduced to a system with single cell and a single traffic type. Such system can employa queuing model to evaluate the performance metric of a cell in terms of blocking probability. Five congestion control models were compared in the work to ascertain their peculiarities, they are Erlang B, Erlang C, Engset (cleared, Engset (buffered, and Bernoulli. To analyze the system, an aggregate onedimensional Markov chain wasderived, such that it describes a call arrival process under the assumption that it is Poisson distributed. The models were simulated and their results show varying performances, however the Bernoulli model (Pb5 tends to show a situation that allows more users access to the system and the congestion level remain unaffected despite increase in the number of users and the offered traffic into the system.
Cellular automaton model of crowd evacuation inspired by slime mould
Kalogeiton, V. S.; Papadopoulos, D. P.; Georgilas, I. P.; Sirakoulis, G. Ch.; Adamatzky, A. I.
2015-04-01
In all the living organisms, the self-preservation behaviour is almost universal. Even the most simple of living organisms, like slime mould, is typically under intense selective pressure to evolve a response to ensure their evolution and safety in the best possible way. On the other hand, evacuation of a place can be easily characterized as one of the most stressful situations for the individuals taking part on it. Taking inspiration from the slime mould behaviour, we are introducing a computational bio-inspired model crowd evacuation model. Cellular Automata (CA) were selected as a fully parallel advanced computation tool able to mimic the Physarum's behaviour. In particular, the proposed CA model takes into account while mimicking the Physarum foraging process, the food diffusion, the organism's growth, the creation of tubes for each organism, the selection of optimum tube for each human in correspondence to the crowd evacuation under study and finally, the movement of all humans at each time step towards near exit. To test the model's efficiency and robustness, several simulation scenarios were proposed both in virtual and real-life indoor environments (namely, the first floor of office building B of the Department of Electrical and Computer Engineering of Democritus University of Thrace). The proposed model is further evaluated in a purely quantitative way by comparing the simulation results with the corresponding ones from the bibliography taken by real data. The examined fundamental diagrams of velocity-density and flow-density are found in full agreement with many of the already published corresponding results proving the adequacy, the fitness and the resulting dynamics of the model. Finally, several real Physarum experiments were conducted in an archetype of the aforementioned real-life environment proving at last that the proposed model succeeded in reproducing sufficiently the Physarum's recorded behaviour derived from observation of the aforementioned
Some properties of the floor field cellular automata evacuation model
Gwizdałła, Tomasz M.
2015-02-01
We study the process of evacuation of pedestrians from the room with the given arrangement of doors and obstacles by using the cellular automata technique. The technique which became quite popular is characterized by the discretization of time as well as space. For such a discretized space we use so-called floor field model which generally corresponds to the description of every cell by some monotonic function of distance between this cell and the closest exit. We study several types of effects. We start from some general features of model like the kind of a neighborhood or the factors disrupting the motion. Then we analyze the influence of asymmetry and size on the evacuation time. Finally we show characteristics concerning different arrangements of exits and include a particular approach to the proxemics effects. The scaling analyses help us to distinguish these cases which just reflect the geometry of the system and those which depend also on the simulation properties. All calculations are performed for a wide range of initial densities corresponding to different occupation rates as described by the typical crowd counting techniques.
From equilibrium spin models to probabilistic cellular automata
The general equivalence between D-dimensional probabilistic cellular automata (PCA) and (D + 1)-dimensional equilibrium spin models satisfying a disorder condition is first described in a pedagogical way and then used to analyze the phase diagrams, the critical behavior, and the universality classes of some automato. Diagrammatic representations of time-dependent correlation functions PCA are introduced. Two important classes of PCA are singled out for which these correlation functions simplify: (1) Quasi-Hamiltonian automata, which have a current-carrying steady state, and for which some correlation functions are those of a D-dimensional static model PCA satisfying the detailed balance condition appear as a particular case of these rules for which the current vanishes. (2) Linear (and more generally affine) PCA for which the diagrammatics reduces to a random walk problem closely related to (D + 1)-dimensional directed SAWs: both problems display a critical behavior with mean-field exponents in any dimension. The correlation length and effective velocity of propagation of excitations can be calculated for affine PCA, as is shown on an explicit D = 1 example. The authors conclude with some remarks on nonlinear PCA, for which the diagrammatics is related to reaction-diffusion processes, and which belong in some cases to the universality class of Reggeon field theory
Modeling chemical systems using cellular automata a textbook and laboratory manual
Kier, Lemont B; Cheng, Chao-Kun
2006-01-01
Provides a practical introduction to an exciting modeling paradigm for complex systems. This book discusses the nature of scientific inquiry using models and simulations, and describes the nature of cellular automata models. It gives descriptions of how cellular automata models can be used in the study of a variety of phenomena.
Relationship between cellular response models and biochemical mechanisms
In most cellular response experiments, survival reflects the kinetics of a variety of damage and repair processes. Unfortunately, biochemical studies of molecular repair deal with mechanisms which cannot be readily correlated with these kinetic observations. The difference in these approaches sometimes leads to confusion over terms such as potentially-lethal and sublethal damage. These terms were introduced with operation definitions, derived from kinetic studies of cell survival, but some researchers have since attempted to associate them with specific biochemical mechanisms. Consequently, the terms are often used in totally different ways be different investigators. The use of carefully constructed models originating either out of assumptions based on mechanisms, or on kinetics, can be used to design experiments to eliminate some alternative kinetic schemes. In turn, some mechanisms may also be eliminated, resulting in a reduction in the number of mechanisms which must be investigated biochemically. One must take advantage of a wide range of specialized radiation procedures in order to accomplish this. Examples of the use of such specialized experimental designs, which have led to a more detailed understanding of the kinetics of both algal and mammalian cell responses, are discussed
Modeling and Performance Analyses of Hybrid Cellular and Broadcasting Networks
Peter Unger
2009-01-01
Full Text Available Mobile communication services are getting more and more important and, in particular, multimedia services have attracted the interest of the users. Mobile TV is one of the most demanded candidates. Powerful and efficient communication systems are needed, which provide high capacities, especially at the downlink. Furthermore, interactivity is essential for supporting the user needs and to extend the service offering. As one possible solution to meet the mentioned requirements, we consider the combination of the cellular network UMTS and the mobile broadcast network DVB-H, which form a hybrid network. We investigate the performance of hybrid networks and develop a system model, which describes the hybrid network and the load switching between both networks. One of the contributions is the definition of the switching bound concept, which represents an efficient tool to assess the necessity and the feasibility of hybrid networks and the amount of load switching. The performance indicators cell load and grade of service are analyzed by using theoretical and realistic scenarios.
Chang-Hua Zou
2009-01-01
Full Text Available Problem statement: Cardiovascular Diseases (CVD continued to be the leading cause of death. Failure or abnormal cardiac cellular or sub-cellular vibrations (oscillations could lead failure or abnormal heart beats that could cause CVD. Understanding the mechanisms of the vibrations (oscillations could help to prevent or to treat the diseases. Scientists have studied the mechanisms for more than 100 years. To our knowledge, the mechanisms are still unclear today. In this investigation, based on published data or results, conservation laws of the momentum as well as the energy, in views of biology, biochemistry, informatics and physics (BioChemInfoPhysics, we proposed our models of cardiac cellular and sub-cellular vibrations (oscillations of biological components, such as free ions in Biological Fluids (BF, Biological Membranes (BM, Ca++H+ (Ca++ and Na+K+ ATPases, Na+Ca++ exchangers (NCX, Ca++ carriers and myosin heads. Approach: Our models were described with 4-D (x, y, z, t or r, ?, z, t momentum transfer equations in mathematical physics. Results: The momentum transfer equations were solved with free and forced, damped, un-damped and over-damped, vibrations (oscillations. The biological components could be modeled as resonators or vibrators (oscillators, such as liquid plasmas, membranes, active springs, passive springs and active swings. Conclusion: We systematically provided new insights of automation (ignition and maintain, transportation, propagation and orientation of the cardiac cellular and sub-cellular vibrations (oscillations and resonances, with our BioChemInfoPhysics models of 4-D momentum transfer equations. Our modeling results implied: Auto-rhythmic cells (Sinoatrial Node Cells (SANC, Atrioventricular Node Cells (AVNC, Purkinje fibers, non-Auto-rhythmic ventricular myocytes and their Sarcoplasmic Reticulums (SR work as Biological Liquid Plasma Resonators (BLPR. The resonators were
Cellular automata model of magnetospheric-ionospheric coupling
B. V. Kozelov
Full Text Available We propose a cellular automata model (CAM to describe the substorm activity of the magnetospheric-ionospheric system. The state of each cell in the model is described by two numbers that correspond to the energy content in a region of the current sheet in the magnetospheric tail and to the conductivity of the ionospheric domain that is magnetically connected with this region. The driving force of the system is supposed to be provided by the solar wind that is convected along the two boundaries of the system. The energy flux inside is ensured by the penetration of the energy from the solar wind into the array of cells (magnetospheric tail with a finite velocity. The third boundary (near to the Earth is closed and the fourth boundary is opened, thereby modeling the flux far away from the tail. The energy dissipation in the system is quite similar to other CAM models, when the energy in a particular cell exceeds some pre-defined threshold, and the part of the energy excess is redistributed between the neighbouring cells. The second number attributed to each cell mimics ionospheric conductivity that can allow for a part of the energy to be shed on field-aligned currents. The feedback between "ionosphere" and "magnetospheric tail" is provided by the change in a part of the energy, which is redistributed in the tail when the threshold is surpassed. The control parameter of the model is the z-component of the interplanetary magnetic field (Bz IMF, "frozen" into the solar wind. To study the internal dynamics of the system at the beginning, this control parameter is taken to be constant. The dynamics of the system undergoes several bifurcations, when the constant varies from - 0.6 to - 6.0. The Bz IMF input results in the periodic transients (activation regions and the inter-transient period decreases with the decrease of Bz. At the same time the onset of activations in the array shifts towards the "Earth". When the modulus of the Bz IMF exceeds some
Millimeter Wave Channel Modeling and Cellular Capacity Evaluation
Akdeniz, Mustafa Riza; Liu, Yuanpeng; Samimi, Mathew K.; Sun, Shu; Rangan, Sundeep; Rappaport, Theodore S.; Erkip, Elza
2013-01-01
With the severe spectrum shortage in conventional cellular bands, millimeter wave (mmW) frequencies between 30 and 300 GHz have been attracting growing attention as a possible candidate for next-generation micro- and picocellular wireless networks. The mmW bands offer orders of magnitude greater spectrum than current cellular allocations and enable very high-dimensional antenna arrays for further gains via beamforming and spatial multiplexing. This paper uses recent real-world measurements at...
A Cellular Automata Model for the Study of Landslides
Liucci, Luisa; Suteanu, Cristian; Melelli, Laura
2016-04-01
Power-law scaling has been observed in the frequency distribution of landslide sizes in many regions of the world, for landslides triggered by different factors, and in both multi-temporal and post-event datasets, thus indicating the universal character of this property of landslides and suggesting that the same mechanisms drive the dynamics of mass wasting processes. The reasons for the scaling behavior of landslide sizes are widely debated, since their understanding would improve our knowledge of the spatial and temporal evolution of this phenomenon. Self-Organized Critical (SOC) dynamics and the key role of topography have been suggested as possible explanations. The scaling exponent of the landslide size-frequency distribution defines the probability of landslide magnitudes and it thus represents an important parameter for hazard assessment. Therefore, another - still unanswered - important question concerns the factors on which its value depends. This paper investigates these issues using a Cellular Automata (CA) model. The CA uses a real topographic surface acquired from a Digital Elevation Model to represent the initial state of the system, where the states of cells are defined in terms of altitude. The stability criterion is based on the slope gradient. The system is driven to instability through a temporal decrease of the stability condition of cells, which may be thought of as representing the temporal weakening of soil caused by factors like rainfall. A transition rule defines the way in which instabilities lead to discharge from unstable cells to the neighboring cells, deciding upon the landslide direction and the quantity of mass involved. Both the direction and the transferred mass depend on the local topographic features. The scaling properties of the area-frequency distributions of the resulting landslide series are investigated for several rates of weakening and for different time windows, in order to explore the response of the system to model
Cellular Automata Models Applied to the Study of Landslide Dynamics
Liucci, Luisa; Melelli, Laura; Suteanu, Cristian
2015-04-01
Landslides are caused by complex processes controlled by the interaction of numerous factors. Increasing efforts are being made to understand the spatial and temporal evolution of this phenomenon, and the use of remote sensing data is making significant contributions in improving forecast. This paper studies landslides seen as complex dynamic systems, in order to investigate their potential Self Organized Critical (SOC) behavior, and in particular, scale-invariant aspects of processes governing the spatial development of landslides and their temporal evolution, as well as the mechanisms involved in driving the system and keeping it in a critical state. For this purpose, we build Cellular Automata Models, which have been shown to be capable of reproducing the complexity of real world features using a small number of variables and simple rules, thus allowing for the reduction of the number of input parameters commonly used in the study of processes governing landslide evolution, such as those linked to the geomechanical properties of soils. This type of models has already been successfully applied in studying the dynamics of other natural hazards, such as earthquakes and forest fires. The basic structure of the model is composed of three modules: (i) An initialization module, which defines the topographic surface at time zero as a grid of square cells, each described by an altitude value; the surface is acquired from real Digital Elevation Models (DEMs). (ii) A transition function, which defines the rules used by the model to update the state of the system at each iteration. The rules use a stability criterion based on the slope angle and introduce a variable describing the weakening of the material over time, caused for example by rainfall. The weakening brings some sites of the system out of equilibrium thus causing the triggering of landslides, which propagate within the system through local interactions between neighboring cells. By using different rates of
Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity
Louis, S.J.; Raines, G.L.
2003-01-01
We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.
The similia principle: results obtained in a cellular model system.
Wiegant, Fred; Van Wijk, Roeland
2010-01-01
This paper describes the results of a research program focused on the beneficial effect of low dose stress conditions that were applied according to the similia principle to cells previously disturbed by more severe stress conditions. In first instance, we discuss criteria for research on the similia principle at the cellular level. Then, the homologous ('isopathic') approach is reviewed, in which the initial (high dose) stress used to disturb cellular physiology and the subsequent (low dose) stress are identical. Beneficial effects of low dose stress are described in terms of increased cellular survival capacity and at the molecular level as an increase in the synthesis of heat shock proteins (hsps). Both phenomena reflect a stimulation of the endogenous cellular self-recovery capacity. Low dose stress conditions applied in a homologous approach stimulate the synthesis of hsps and enhance survival in comparison with stressed cells that were incubated in the absence of low dose stress conditions. Thirdly, the specificity of the low dose stress condition is described where the initial (high dose) stress is different in nature from the subsequently applied (low dose) stress; the heterologous or 'heteropathic' approach. The results support the similia principle at the cellular level and add to understanding of how low dose stress conditions influence the regulatory processes underlying self-recovery. In addition, the phenomenon of 'symptom aggravation' which is also observed at the cellular level, is discussed in the context of self-recovery. Finally, the difference in efficiency between the homologous and the heterologous approach is discussed; a perspective is indicated for further research; and the relationship between studies on the similia principle and the recently introduced concept of 'postconditioning hormesis' is emphasized. PMID:20129172
Cellular-automata model of the dwarf shrubs populations and communities dynamics
A. S. Komarov; E. V. Zubkova; P. V. Frolov
2015-01-01
The probabilistic cellular-automata model of development and long-time dynamics of dwarf shrub populations and communities is developed. It is based on the concept of discrete description of the plant ontogenesis and joint model approaches in terms of probabilistic cellular automata and L-systems by Lindenmayer. Short representation of the basic model allows evaluation of the approach and software implementation. The main variables of the model are a number of partial bushes in clones or area...
Stochastic Models of Vesicular Sorting in Cellular Organelles
Vagne, Quentin
2016-01-01
The proper sorting of membrane components by regulated exchange between cellular organelles is crucial to intra-cellular organization. This process relies on the budding and fusion of transport vesicles, and should be strongly influenced by stochastic fluctuations considering the relatively small size of many organelles. We identify the perfect sorting of two membrane components initially mixed in a single compartment as a first passage process, and we show that the mean sorting time exhibits two distinct regimes as a function of the ratio of vesicle fusion to budding rates. Low ratio values leads to fast sorting, but results in a broad size distribution of sorted compartments dominated by small entities. High ratio values result in two well defined sorted compartments but is exponentially slow. Our results suggests an optimal balance between vesicle budding and fusion for the rapid and efficient sorting of membrane components, and highlight the importance of stochastic effects for the steady-state organizati...
Mathematical models and multiscale simulations of cellular secretion processes
González-Vélez, Virginia
2011-01-01
Exocytosis is the cellular process whereby a product such as a hormone or a neurotransmitter is released as a response to stimulation. There are a lot of exocytotic cells in mammals, and each cell type has their specific subcellular mechanisms, needed to achieve the final substance release. Therefore, unveiling the role of subcellular mechanisms in secretion processes is highly relevant to understand disease evolution and possible therapies. The efficiency of the coupling between stimulus...
A Large Deformation Model for the Elastic Moduli of Two-dimensional Cellular Materials
HU Guoming; WAN Hui; ZHANG Youlin; BAO Wujun
2006-01-01
We developed a large deformation model for predicting the elastic moduli of two-dimensional cellular materials. This large deformation model was based on the large deflection of the inclined members of the cells of cellular materials. The deflection of the inclined member, the strain of the representative structure and the elastic moduli of two-dimensional cellular materials were expressed using incomplete elliptic integrals. The experimental results show that these elastic moduli are no longer constant at large deformation, but vary significantly with the strain. A comparison was made between this large deformation model and the small deformation model proposed by Gibson and Ashby.
A mathematical model of amphibian skin epithelium with two types of transporting cellular units
Larsen, Erik Hviid; Rasmussen, B E
1985-01-01
A computer model of ion transport across amphibian skin epithelium containing two types of cellular units, their relative number and sizes, and a paracellular pathway has been developed. The two cellular units are, a large Na+ transporting compartment representing the major epithelium from stratum...
Predictive model to describe water migration in cellular solid foods during storage
Voogt, J.A.; Hirte, A.; Meinders, M.B.J.
2011-01-01
BACKGROUND: Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. RESULTS: Water migration in cellular solid foods invo
Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model
Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran
2014-09-01
Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.
Dynamic modeling of cellular response to DNA damage based on p53 stress response networks
Jinpeng Qi; Yongsheng Ding; Shihuang Shao
2009-01-01
Under acute perturbations from the outside, cells can trigger self-defensive mechanisms to fight against genome stress. To investigate the cellular response to continuous ion radiation (IR), a dynamic model for p53 stress response networks at the cellular level is proposed. The model can successfully be used to simulate the dynamic processes of double-strand breaks (DSBs) generation and their repair, switch-like ataxia telangiectasia mutated (ATM) activation, oscillations occurring in the p53-MDM2 feedback loop, as well as toxins elimination triggered by p53 stress response networks. Especially, the model can predict the plausible outcomes of cellular response under different IR dose regimes.
Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial
ElSawy, Hesham
2016-03-22
This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a basic cellular network model. Then, it characterizes signal-tointerference- plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the baseline unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. Finally, we point out future research directions.
Cellular Automation Model of Traffic Flow Based on the Car-Following Model
LI Ke-Ping; GAO Zi-You
2004-01-01
@@ We propose a new cellular automation (CA) traffic model that is based on the car-following model. A class of driving strategies is used in the car-following model instead of the acceleration in the NaSch traffic model. In our model, some realistic driver behaviour and detailed vehicle characteristics have been taken into account, such as distance-headway and safe distance, etc. The simulation results show that our model can exhibit some traffic flow states that have been observed in the real traffic, and both of the maximum flux and the critical density are very close to the real measurement. Moreover, it is easy to extend our method to multi-lane traffic.
Kapitanov, Georgi I.; Wang, Xiayi; Ayati, Bruce P; Brouillette, Marc J.; Martin, James A.
2016-01-01
A severe application of stress on articular cartilage can initiate a cascade of biochemical reactions that can lead to the development of osteoarthritis. We constructed a multiscale mathematical model of the process with three components: cellular, chemical, and mechanical. The cellular component describes the different chondrocyte states according to the chemicals these cells release. The chemical component models the change in concentrations of those chemicals. The mechanical component cont...
Simulation Modeling by Classification of Problems: A Case of Cellular Manufacturing
Afiqah, K. N.; Mahayuddin, Z. R.
2016-02-01
Cellular manufacturing provides good solution approach to manufacturing area by applying Group Technology concept. The evolution of cellular manufacturing can enhance performance of the cell and to increase the quality of the product manufactured but it triggers other problem. Generally, this paper highlights factors and problems which emerge commonly in cellular manufacturing. The aim of the research is to develop a thorough understanding of common problems in cellular manufacturing. A part from that, in order to find a solution to the problems exist using simulation technique, this classification framework is very useful to be adapted during model building. Biology evolution tool was used in the research in order to classify the problems emerge. The result reveals 22 problems and 25 factors using cladistic technique. In this research, the expected result is the cladogram established based on the problems in cellular manufacturing gathered.
Cellular cardiac electrophysiology modeling with Chaste and CellML
Cooper, Jonathan; Spiteri, Raymond J.; Mirams, Gary R
2014-01-01
Chaste is an open-source C++ library for computational biology that has well-developed cardiac electrophysiology tissue simulation support. In this paper, we introduce the features available for performing cardiac electrophysiology action potential simulations using a wide range of models from the Physiome repository. The mathematics of the models are described in CellML, with units for all quantities. The primary idea is that the model is defined in one place (the CellML file), and all model...
Modelling lava flows by Cellular Nonlinear Networks (CNN: preliminary results
C. Del Negro
2005-01-01
Full Text Available The forecasting of lava flow paths is a complex problem in which temperature, rheology and flux-rate all vary with space and time. The problem is more difficult to solve when lava runs down a real topography, considering that the relations between characteristic parameters of flow are typically nonlinear. An alternative approach to this problem that does not use standard differential equation methods is Cellular Nonlinear Networks (CNNs. The CNN paradigm is a natural and flexible framework for describing locally interconnected, simple, dynamic systems that have a lattice-like structure. They consist of arrays of essentially simple, nonlinearly coupled dynamic circuits containing linear and non-linear elements able to process large amounts of information in real time. Two different approaches have been implemented in simulating some lava flows. Firstly, a typical technique of the CNNs to analyze spatio-temporal phenomena (as Autowaves in 2-D and in 3-D has been utilized. Secondly, the CNNs have been used as solvers of partial differential equations of the Navier-Stokes treatment of Newtonian flow.
Study of phase separation using liquid-gas model of lattice-gas cellular automata
This report describes the study of phase separation by the liquid gas model of lattice gas cellular automata. The lattice gas cellular automaton is one model for simulating fluid phenomena which was proposed by Frisch, Hasslacher and Pomeau in 1986. In 1990, Appert and Zaleski added a new long-range interaction to lattice gas cellular automata to construct a model, the liquid-gas model, which could simulate phase separation using lattice-gas cellular automata. Gerits et al formulated the liquid-gas model mathematically using the theory of statistical dynamics in 1993 and explained the mechanism of phase separation in the liquid-gas model using the equation of state. At first this report explains the FHP model of lattice gas cellular automata and derives fluid dynamics equations such as the equation of continuity and the Navier-Stokes equation. Then the equation of state for the liquid-gas model which was derived by Gerits et al is modified by adding the interactions which were proposed by Appert but not considered by Gerits et al. The modified equation of state is verified by the computer simulation using the liquid gas model. The relation between phase separation and the equation of state is discussed. (author)
ZHU Ming-fang; CAO Wei-sheng; CHEN Shuang-lin; XIE Fan-you; HONG Chunpyo; CHANG Y. Austin
2006-01-01
A modified cellular automaton (MCA) model has been extended to the ternary alloy system by coupling thermodynamic and phase equilibrium calculation engine PanEngine. In the present model the dendrite growth is driven by the difference between the local equilibrium liquidus temperature and local actual temperature, incorporating the effect of curvature. The local equilibrium liquidus temperature is calculated with PanEngine according to the local liquid concentrations of two solutes, which are determined by numerically solving the species transport equation in the domain. Model validation was carried out through the comparison of the simulated values to the prediction of the Scheil model for solute profiles in the primary dendrites. The simulated data with zero solid diffusivity and limited liquid diffusivity were increasingly close to the Scheil profiles as the solidification rate decreased. The simulated microstructure and microsegregation in an Al-Cu-Mg ternary alloy were compared with those obtained experimentally.
Jeans type instability for a chemotactic model of cellular aggregation
Chavanis, Pierre-Henri
2008-01-01
We consider an inertial model of chemotactic aggregation generalizing the Keller-Segel model and we study the linear dynamical stability of an infinite and homogeneous distribution of cells (bacteria, amoebae, endothelial cells,...) when inertial effects are accounted for. These inertial terms model cells directional persistance. We determine the condition of instability and the growth rate of the perturbation as a function of the cell density and the wavelength of the perturbation. We discuss the differences between overdamped (Keller-Segel) and inertial models. Finally, we show the analogy between the instability criterion for biological populations and the Jeans instability criterion in astrophysics.
From cellular to tissue scales by asymptotic limits of thermostatted kinetic models
Bianca, Carlo; Dogbe, Christian; Lemarchand, Annie
2016-02-01
Tumor growth strictly depends on the interactions occurring at the cellular scale. In order to obtain the linking between the dynamics described at tissue and cellular scales, asymptotic methods have been employed, consisting in deriving tissue equations by suitable limits of mesoscopic models. In this paper, the evolution at the cellular scale is described by thermostatted kinetic theory that include conservative, nonconservative (proliferation, destruction and mutations), stochastic terms, and the role of external agents. The dynamics at the tissue scale (cell-density evolution) is obtained by performing a low-field scaling and considering the related convergence of the rescaled framework when the scaling parameter goes to zero.
Cellular cardiac electrophysiology modeling with Chaste and CellML.
Cooper, Jonathan; Spiteri, Raymond J; Mirams, Gary R
2014-01-01
Chaste is an open-source C++ library for computational biology that has well-developed cardiac electrophysiology tissue simulation support. In this paper, we introduce the features available for performing cardiac electrophysiology action potential simulations using a wide range of models from the Physiome repository. The mathematics of the models are described in CellML, with units for all quantities. The primary idea is that the model is defined in one place (the CellML file), and all model code is auto-generated at compile or run time; it never has to be manually edited. We use ontological annotation to identify model variables describing certain biological quantities (membrane voltage, capacitance, etc.) to allow us to import any relevant CellML models into the Chaste framework in consistent units and to interact with them via consistent interfaces. This approach provides a great deal of flexibility for analysing different models of the same system. Chaste provides a wide choice of numerical methods for solving the ordinary differential equations that describe the models. Fixed-timestep explicit and implicit solvers are provided, as discussed in previous work. Here we introduce the Rush-Larsen and Generalized Rush-Larsen integration techniques, made available via symbolic manipulation of the model equations, which are automatically rearranged into the forms required by these approaches. We have also integrated the CVODE solvers, a 'gold standard' for stiff systems, and we have developed support for symbolic computation of the Jacobian matrix, yielding further increases in the performance and accuracy of CVODE. We discuss some of the technical details of this work and compare the performance of the available numerical methods. Finally, we discuss how this is generalized in our functional curation framework, which uses a domain-specific language for defining complex experiments as a basis for comparison of model behavior. PMID:25610400
A study of a main-road cellular automata traffic flow model
黄乒花; 孔令江; 刘慕仁
2002-01-01
A main-road cellular automata traffic flow model on two dimensions is presented based on the Biham-Middleton-Levine traffic model. Its evolution equations are given and the self-organization and organization cooperation phenomenain this model are also studied by using computer simulation.
Propagation Path Loss Models for 5G Urban Micro- and Macro-Cellular Scenarios
Sun, Shu; Rappaport, Theodore S.; Rangan, Sundeep;
2016-01-01
This paper presents and compares two candidate large-scale propagation path loss models, the alpha-beta-gamma (ABG) model and the close-in (CI) free space reference distance model, for the design of fifth generation (5G) wireless communication systems in urban micro- and macro-cellular scenarios...
Jokar Arsanjani, J.; Helbich, M.; Kainz, W.; Boloorani, A.
2013-01-01
This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-eco
On Modeling Coverage and Rate of Random Cellular Networks under Generic Channel Fading
Al-Hourani, Akram; Kandeepan, Sithamparanathan
2016-01-01
In this paper we provide an analytic framework for computing the expected downlink coverage probability, and the associated data rate of cellular networks, where base stations are distributed in a random manner. The provided expressions are in computable integral forms that accommodate generic channel fading conditions. We develop these expressions by modelling the cellular interference using stochastic geometry analysis, then we employ them for comparing the coverage resulting from various c...
A cellular network model with Ginibre configured base stations
Miyoshi, Naoto; Shirai, Tomoyuki
2014-01-01
Stochastic geometry models for wireless communication networks have recently attracted much attention. This is because the performance of such networks critically depends on the spatial configuration of wireless nodes and the irregularity of the node configuration in a real network can be captured by a spatial point process. However, most analysis of such stochastic geometry models for wireless networks assumes, owing to its tractability, that the wireless nodes are deployed...
A cellular automata model for simulating fed-batch penicillin fermentation process
Yu Naigong; Ruan Xiaogang
2006-01-01
A cellular automata model to simulate penicillin fed-batch fermentation process(CAPFM)was established in this study,based on a morphologically structured dynamic penicillin production model,that is in turn based on the growth mechanism of penicillin producing microorganisms and the characteristics of penicillin fed-batch fermentation.CAPFM uses the three-dimensional cellular automata as a growth space,and a Moore-type neighborhood as the cellular neighborhood.The transition roles of CAPFM are designed based on mechanical and structural kinetic models of penicillin batch-fed fermentation processes.Every cell of CAPFM represents a single or specific number of penicillin producing microorganisms,and has various state.The simulation experimental results show that CAPFM replicates the evolutionary behavior of penicillin batch-fed fermentation processes described by the structured penicillin production kinetic model accordingly.
Mathematical Modeling Predicts How Proteins Affect Cellular Communication
Lee Ethan; Salic Adrian; Krüger Roland; Heinrich Reinhart; Kirschner Marc W
2003-01-01
Wnt signaling plays an important role in both oncogenesis and development. Activation of the Wnt pathway results in stabilization of the transcriptional coactivator beta-catenin. Recent studies have demonstrated that axin, which coordinates beta-catenin degradation, is itself degraded. Although the key molecules required for transducing a Wnt signal have been identified, a quantitative understanding of this pathway has been lacking. We have developed a mathematical model for the canonical Wnt...
Cellular automata cell structure for modeling heterogeneous traffic
Pal, Dibyendu; C.Mallikarjuna
2010-01-01
Gap maintaining behavior significantly affects the traffic flow modeling under heterogeneous traffic conditions. The clearance between two adjacent moving vehicles varies depending on several traffic conditions. From the data collected on the gap maintaining behavior it has been observed that vehicles maintain different gaps when travelling under different traffic conditions and this is also influenced by lateral position of the vehicle. Mallikarjuna (2007) has found that this variable gap ma...
Cellular models and therapies for age-related macular degeneration
David L. Forest
2015-05-01
Full Text Available Age-related macular degeneration (AMD is a complex neurodegenerative visual disorder that causes profound physical and psychosocial effects. Visual impairment in AMD is caused by the loss of retinal pigmented epithelium (RPE cells and the light-sensitive photoreceptor cells that they support. There is currently no effective treatment for the most common form of this disease (dry AMD. A new approach to treating AMD involves the transplantation of RPE cells derived from either human embryonic or induced pluripotent stem cells. Multiple clinical trials are being initiated using a variety of cell therapies. Although many animal models are available for AMD research, most do not recapitulate all aspects of the disease, hampering progress. However, the use of cultured RPE cells in AMD research is well established and, indeed, some of the more recently described RPE-based models show promise for investigating the molecular mechanisms of AMD and for screening drug candidates. Here, we discuss innovative cell-culture models of AMD and emerging stem-cell-based therapies for the treatment of this vision-robbing disease.
Equal Distribution Model of Epidemic Drugs Based on a Cellular Automata Model
Huang Xinyi
2015-01-01
Full Text Available The epidemic spreading of infectious disease is a process of evolution over time. Based on the cellular automata model[1], this paper analyzes the epidemic spreading rules, and establishes an efficient equal distribution model of drugs in a broad sense. For multiple regions, in case of demand of drugs exceeding supply, the drugs shall be distributed according to the proportion of a total number of people in each region, the number of patients, the number of the isolated, and the number of deaths. It is necessary to simulate based on these four schemes to obtain simulation results. The results show that, when the drugs are distributed by the proportion of the number of deaths, it is optimal for controlling over epidemic situations.
Stochastic Model of Maturation and Vesicular Exchange in Cellular Organelles
Vagne, Quentin
2016-01-01
The dynamical organization of membrane-bound organelles along intracellular transport pathways relies on vesicular exchange between organelles and on biochemical maturation of the organelle content by specific enzymes. The relative importance of each mechanism in controlling organelle dynamics remains controversial, in particular for transport through the Golgi apparatus. Using a stochastic model, we show that full maturation of membrane-bound compartments can be seen as the stochastic escape from a steady-state in which export is dominated by vesicular exchange. We show that full maturation can contribute a significant fraction of the total out-flux for small organelles such as endosomes and Golgi cisternae.
Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model
Jantz, C.A.; Goetz, S.J.; Donato, D.; Claggett, P.
2010-01-01
This paper presents a fine-scale (30 meter resolution) regional land cover modeling system, based on the SLEUTH cellular automata model, that was developed for a 257000 km2 area comprising the Chesapeake Bay drainage basin in the eastern United States. As part of this effort, we developed a new version of the SLEUTH model (SLEUTH-3r), which introduces new functionality and fit metrics that substantially increase the performance and applicability of the model. In addition, we developed methods that expand the capability of SLEUTH to incorporate economic, cultural and policy information, opening up new avenues for the integration of SLEUTH with other land-change models. SLEUTH-3r is also more computationally efficient (by a factor of 5) and uses less memory (reduced 65%) than the original software. With the new version of SLEUTH, we were able to achieve high accuracies at both the aggregate level of 15 sub-regional modeling units and at finer scales. We present forecasts to 2030 of urban development under a current trends scenario across the entire Chesapeake Bay drainage basin, and three alternative scenarios for a sub-region within the Chesapeake Bay watershed to illustrate the new ability of SLEUTH-3r to generate forecasts across a broad range of conditions. ?? 2009 Elsevier Ltd.
Modelling Cellular Processes using Membrane Systems with Peripheral and Integral Proteins
Cavaliere, Matteo; Sedwards, Sean
2006-01-01
Membrane systems were introduced as models of computation inspired by the structure and functioning of biological cells. Recently, membrane systems have also been shown to be suitable to model cellular processes. We introduce a new model called Membrane Systems with Peripheral and Integral Proteins. The model has compartments enclosed by membranes, floating objects, objects associated to the internal and external surfaces of the membranes and also objects integral to the membranes. The floati...
Evaluation of BACE1 Silencing in Cellular Models
Barbara Nawrot
2009-01-01
Full Text Available Beta-secretase (BACE1 is the major enzyme participating in generation of toxic amyloid-beta (Aβ peptides, identified in amyloid plaques of Alzheimer's disease (AD brains. Its downregulation results in decreasing secretion of Aβ. Thus, BACE1 silencing by RNAi represents possible strategy for antiamyloid therapy in the treatment of AD. In this study, a series of newly designed sequences of synthetic and vector-encoded siRNAs (pSilencer, pcPURhU6, and lentivirus were tested against overexpressed and endogenous BACE1 in several cell lines and in adult neural progenitor cells, derived from rat hippocampus. SiRNAs active in human, mouse, and rat cell models were shown to diminish the level of BACE1. In HCN A94 cells, two BACE1-specific siRNAs did not alter the expression of genes of BACE2 and several selected genes involved in neurogenesis (Synapsin I, βIII-Tubulin, Calbidin, NeuroD1, GluR2, CREB, MeCP2, PKR, however, remarkable lowering of SCG10 mRNA, coding protein of stathmin family, important in the development of nervous system, was observed.
Tools and Models for Integrating Multiple Cellular Networks
Gerstein, Mark [Yale Univ., New Haven, CT (United States). Gerstein Lab.
2015-11-06
CRIT for correlation analysis in systems biology [5]. For Aim 3, we have further investigated the scaling relationship that the number of Transcription Factors (TFs) in a genome is proportional to the square of the total number of genes. We have extended the analysis from transcription factors to various classes of functional categories, and from individual categories to joint distribution [6]. By introducing a new analytical framework, we have generalized the original toolbox model to take into account of metabolic network with arbitrary network topology [7].
Mondry Adrian
2004-08-01
Full Text Available Abstract Background Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. Methods We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. Results We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. Conclusions Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods
Wimol San-Um
2015-12-01
Full Text Available This paper presents a robust cellular associative memory for pattern recognitions using composite trigonometric chaotic neuron models. Robust chaotic neurons are designed through a scan of positive Lyapunov Exponent (LE bifurcation structures, which indicate the quantitative measure of chaoticity for one-dimensional discrete-time dynamical systems. The proposed chaotic neuron model is a composite of sine and cosine chaotic maps, which are independent from the output activation function. Dynamics behaviors are demonstrated through bifurcation diagrams and LE-based bifurcation structures. An application to associative memories of binary patterns in Cellular Neural Networks (CNN topology is demonstrated using a signum output activation function. Examples of English alphabets are stored using symmetric auto-associative matrix of n-binary patterns. Simulation results have demonstrated that the cellular neural network can quickly and effectively restore the distorted pattern to expected information.
Platinum nanozymes recover cellular ROS homeostasis in an oxidative stress-mediated disease model
Moglianetti, Mauro; de Luca, Elisa; Pedone, Deborah; Marotta, Roberto; Catelani, Tiziano; Sartori, Barbara; Amenitsch, Heinz; Retta, Saverio Francesco; Pompa, Pier Paolo
2016-02-01
In recent years, the use of nanomaterials as biomimetic enzymes has attracted great interest. In this work, we show the potential of biocompatible platinum nanoparticles (Pt NPs) as antioxidant nanozymes, which combine abundant cellular internalization and efficient scavenging activity of cellular reactive oxygen species (ROS), thus simultaneously integrating the functions of nanocarriers and antioxidant drugs. Careful toxicity assessment and intracellular tracking of Pt NPs proved their cytocompatibility and high cellular uptake, with compartmentalization within the endo/lysosomal vesicles. We have demonstrated that Pt NPs possess strong and broad antioxidant properties, acting as superoxide dismutase, catalase, and peroxidase enzymes, with similar or even superior performance than natural enzymes, along with higher adaptability to the changes in environmental conditions. We then exploited their potent activity as radical scavenging materials in a cellular model of an oxidative stress-related disorder, namely human Cerebral Cavernous Malformation (CCM) disease, which is associated with a significant increase in intracellular ROS levels. Noteworthily, we found that Pt nanozymes can efficiently reduce ROS levels, completely restoring the cellular physiological homeostasis.In recent years, the use of nanomaterials as biomimetic enzymes has attracted great interest. In this work, we show the potential of biocompatible platinum nanoparticles (Pt NPs) as antioxidant nanozymes, which combine abundant cellular internalization and efficient scavenging activity of cellular reactive oxygen species (ROS), thus simultaneously integrating the functions of nanocarriers and antioxidant drugs. Careful toxicity assessment and intracellular tracking of Pt NPs proved their cytocompatibility and high cellular uptake, with compartmentalization within the endo/lysosomal vesicles. We have demonstrated that Pt NPs possess strong and broad antioxidant properties, acting as superoxide
Kirchner, Ansgar; Schadschneider, Andreas
2002-01-01
We present simulations of evacuation processes using a recently introduced cellular automaton model for pedestrian dynamics. This model applies a bionics approach to describe the interaction between the pedestrians using ideas from chemotaxis. Here we study a rather simple situation, namely the evacuation from a large room with one or two doors. It is shown that the variation of the model parameters allows to describe different types of behaviour, from regular to panic. We find a non-monotoni...
Color Graphs: An Efficient Model For Two-Dimensional Cellular Automata Linear Rules
Nayak, Birendra Kumar; Rout, Sushant Kumar
2008-01-01
Two-dimensional nine neighbor hood rectangular Cellular Automata rules can be modeled using many different techniques like Rule matrices, State Transition Diagrams, Boolean functions, Algebraic Normal Form etc. In this paper, a new model is introduced using color graphs to model all the 512 linear rules. The graph theoretic properties therefore studied in this paper simplifies the analysis of all linear rules in comparison with other ways of its study.
A Modified Cellular Automaton Approach for Mixed Bicycle Traffic Flow Modeling
Xiaonian Shan; Zhibin Li; Xiaohong Chen; Jianhong Ye
2015-01-01
Several previous studies have used the Cellular Automaton (CA) for the modeling of bicycle traffic flow. However, previous CA models have several limitations, resulting in differences between the simulated and the observed traffic flow features. The primary objective of this study is to propose a modified CA model for simulating the characteristics of mixed bicycle traffic flow. Field data were collected on physically separated bicycle path in Shanghai, China, and were used to calibrate the C...
Lattice gas cellular automata model for rippling and aggregation in myxobacteria
Alber, Mark S.; Jiang, Yi; Kiskowski, Maria A.
2004-01-01
A lattice-gas cellular automaton (LGCA) model is used to simulate rippling and aggregation in myxobacteria. An efficient way of representing cells of different cell size, shape and orientation is presented that may be easily extended to model later stages of fruiting body formation. This LGCA model is designed to investigate whether a refractory period, a minimum response time, a maximum oscillation period and non-linear dependence of reversals of cells on C-factor are necessary assumptions f...
Özen, Şükrü; Köylü, Halis
2010-01-01
ABSTRACTThere is a necessity of tissue equivalent (phantom) models in research of electromagnetic (EM) effects in biologic tissues. Recently, many kinds of tissue models depend on the different aim were proposed. So many studies were carried on the interaction of human-head and cellular phone. The most of them are related to numerical models. Owing to difficulty of study on human body, simulation of human tissues is required. In this study two different, for 900MHz and for 1800MHz, brain equi...
Embryonic stem cells as an ectodermal cellular model of human p63-related dysplasia syndromes.
Rostagno, P.; Wolchinsky, Z.; Vigano, A.M.; Shivtiel, S.; Zhou, H.; Bokhoven, J.H.L.M. van; Ferone, G.; Missero, C.; Mantovani, R.; Aberdam, D.; Virolle, T.
2010-01-01
Heterozygous mutations in the TP63 transcription factor underlie the molecular basis of several similar autosomal dominant ectodermal dysplasia (ED) syndromes. Here we provide a novel cellular model derived from embryonic stem (ES) cells that recapitulates in vitro the main steps of embryonic skin d
An agent-based model of cellular dynamics and circadian variability in human endotoxemia.
Tung T Nguyen
Full Text Available As cellular variability and circadian rhythmicity play critical roles in immune and inflammatory responses, we present in this study an agent-based model of human endotoxemia to examine the interplay between circadian controls, cellular variability and stochastic dynamics of inflammatory cytokines. The model is qualitatively validated by its ability to reproduce circadian dynamics of inflammatory mediators and critical inflammatory responses after endotoxin administration in vivo. Novel computational concepts are proposed to characterize the cellular variability and synchronization of inflammatory cytokines in a population of heterogeneous leukocytes. Our results suggest that there is a decrease in cell-to-cell variability of inflammatory cytokines while their synchronization is increased after endotoxin challenge. Model parameters that are responsible for IκB production stimulated by NFκB activation and for the production of anti-inflammatory cytokines have large impacts on system behaviors. Additionally, examining time-dependent systemic responses revealed that the system is least vulnerable to endotoxin in the early morning and most vulnerable around midnight. Although much remains to be explored, proposed computational concepts and the model we have pioneered will provide important insights for future investigations and extensions, especially for single-cell studies to discover how cellular variability contributes to clinical implications.
Guedes, J.M.; Rodrigues, H.C.; Bendsøe, Martin P.
2003-01-01
This paper describes a computational model, based on inverse homogenization and topology design, for approximating energy bounds for two-phase composites under multiple load cases. The approach allows for the identification of possible single-scale cellular materials that give rise to the optimal...
Model Perubahan Penggunaan Lahan Menggunakan Cellular Automata-Markov Chain di Kawasan Mamminasata
Vera Damayanti Peruge, Tiur
2012-01-01
Telah dilakukan penelitian tentang perubahan penggunaan lahan di kawasan Mamminasata menggunakan model Cellular Automata-Markov Chain. Tujuan dari penelitian ini adalah menganalisis perubahan penggunaan lahan melalui peta penggunaan lahan kawasan Mamminasata tahun 2004 dan 2009 untuk memperoleh penggunaan lahan tahun 2012 berbasis Markov Chain dengan analisis probabilitas transisi Markov. Hasil analisis yang diperoleh dilakukan validasi dengan validasi Kappa m...
Hannan, Shabab B; Dräger, Nina M; Rasse, Tobias M; Voigt, Aaron; Jahn, Thomas R
2016-04-01
Abnormal tau accumulations were observed and documented in post-mortem brains of patients affected by Alzheimer's disease (AD) long before the identification of mutations in the Microtubule-associated protein tau (MAPT) gene, encoding the tau protein, in a different neurodegenerative disease called Frontotemporal dementia and Parkinsonism linked to chromosome 17 (FTDP-17). The discovery of mutations in the MAPT gene associated with FTDP-17 highlighted that dysfunctions in tau alone are sufficient to cause neurodegeneration. Invertebrate models have been diligently utilized in investigating tauopathies, contributing to the understanding of cellular and molecular pathways involved in disease etiology. An important discovery came with the demonstration that over-expression of human tau in Drosophila leads to premature mortality and neuronal dysfunction including neurodegeneration, recapitulating some key neuropathological features of the human disease. The simplicity of handling invertebrate models combined with the availability of a diverse range of experimental resources make these models, in particular Drosophila a powerful invertebrate screening tool. Consequently, several large-scale screens have been performed using Drosophila, to identify modifiers of tau toxicity. The screens have revealed not only common cellular and molecular pathways, but in some instances the same modifier has been independently identified in two or more screens suggesting a possible role for these modifiers in regulating tau toxicity. The purpose of this review is to discuss the genetic modifier screens on tauopathies performed in Drosophila and C. elegans models, and to highlight the common cellular and molecular pathways that have emerged from these studies. Here, we summarize results of tau toxicity screens providing mechanistic insights into pathological alterations in tauopathies. Key pathways or modifiers that have been identified are associated with a broad range of processes
J. P. M. Whitty
2014-01-01
Full Text Available A novel computational technique is presented for embedding mass-loss due to burning into the ANSYS finite element modelling code. The approaches employ a range of computational modelling methods in order to provide more complete theoretical treatment of thermoelasticity absent from the literature for over six decades. Techniques are employed to evaluate structural integrity (namely, elastic moduli, Poisson’s ratios, and compressive brittle strength of honeycomb systems known to approximate three-dimensional cellular chars. That is, reducing the mass of diagonal ribs and both diagonal-plus-vertical ribs simultaneously show rapid decreases in the structural integrity of both conventional and reentrant (auxetic, i.e., possessing a negative Poisson’s ratio honeycombs. On the other hand, reducing only the vertical ribs shows initially modest reductions in such properties, followed by catastrophic failure of the material system. Calculations of thermal stress distributions indicate that in all cases the total stress is reduced in reentrant (auxetic cellular solids. This indicates that conventional cellular solids are expected to fail before their auxetic counterparts. Furthermore, both analytical and FE modelling predictions of the brittle crush strength of both auxteic and conventional cellular solids show a relationship with structural stiffness.
Modeling of solidification grain structure for Ti-45%Al alloy ingot by cellular automaton
WU Shi-ping; LIU Dong-rong; GUO Jing-jie; FU Heng-zhi
2005-01-01
A cellular automaton model for simulating grain structure formation during solidification processes of Ti45%Al(mole fraction) alloy ingot was developed, based on finite differential method for macroscopic modeling of heat transfer and a cellular automaton technique for microscopic modeling of nucleation, growth, solute redistribution and solute diffusion. The relation between the growth velocity of a dendrite tip and the local undercooling,which consists of constitutional, thermal, curvature and attachment kinetics undercooling is calculated according to the Kurz-Giovanola-Trivedi model. The effect of solidification contraction is taken into consideration. The influence of process variables upon the resultant grain structures was investigated. Special moving allocation technique was designed to minimize the computation time and memory size associated with a large number of cells. The predicted grain structures are in good agreement with the experimental results.
Parallel Genetic Algorithms for calibrating Cellular Automata models: Application to lava flows
Cellular Automata are highly nonlinear dynamical systems which are suitable far simulating natural phenomena whose behaviour may be specified in terms of local interactions. The Cellular Automata model SCIARA, developed far the simulation of lava flows, demonstrated to be able to reproduce the behaviour of Etnean events. However, in order to apply the model far the prediction of future scenarios, a thorough calibrating phase is required. This work presents the application of Genetic Algorithms, general-purpose search algorithms inspired to natural selection and genetics, far the parameters optimisation of the model SCIARA. Difficulties due to the elevated computational time suggested the adoption a Master-Slave Parallel Genetic Algorithm far the calibration of the model with respect to the 2001 Mt. Etna eruption. Results demonstrated the usefulness of the approach, both in terms of computing time and quality of performed simulations
Tamaddon AM.; Hosseini-Shirazi F.; Moghimi HR
2007-01-01
Cationic liposomes are used for cellular delivery of antisense oligodeoxynucleotide (AsODN), where release of encapsulated AsODN is mainly controlled by endocytosis and fusion mechanisms. In this investigation, it was tried to model such a release process that is difficult to evaluate in cell culture. For this purpose, an AsODN model (against protein kinase C-α) was encapsulated in a DODAP-containing cationic liposome and evaluated for size, zeta-potential, encapsulation and ODN stab...
Modeling of aluminum-silicon irregular eutectic growth by cellular automaton model
Rui Chen
2016-03-01
Full Text Available Due to the extensive application of Al-Si alloys in the automotive and aerospace industries as structural components, an understanding of their microstructural formation, such as dendrite and (Al+Si eutectic, is of great importance to control the desirable microstructure, so as to modify the performance of castings. Since previous major themes of microstructural simulation are dendrite and regular eutectic growth, few efforts have been paid to simulate the irregular eutectic growth. Therefore, a multiphase cellular automaton (CA model is developed and applied to simulate the time-dependent Al-Si irregular eutectic growth. Prior to model establishment, related experiments were carried out to investigate the influence of cooling rate and Sr modification on the growth of eutectic Si. This CA model incorporates several aspects, including growth algorithms and nucleation criterion, to achieve the competitive and cooperative growth mechanism for nonfaceted-faceted Al-Si irregular eutectic. The growth kinetics considers thermal undercooling, constitutional undercooling, and curvature undercooling, as well as the anisotropic characteristic of eutectic Si growth. The capturing rule takes into account the effects of modification on the silicon growth behaviors. The simulated results indicate that for unmodified alloy, the higher eutectic undercooling results in the higher eutectic growth velocity, and a more refined eutectic microstructure as well as narrower eutectic lamellar spacing. For modified alloy, the eutectic silicon tends to be obvious fibrous morphology and the morphology of eutectic Si is determined by both chemical modifier and cooling rate. The predicted microstructure of Al-7Si alloy under different solidification conditions shows that this proposed model can successfully reproduce both dendrite and eutectic microstructures.
Schmidt, Brian; Ebrahim, Ali; Metz, Thomas O.; Adkins, Joshua N.; Palsson, Bernard O.; Hyduke, Daniel R.
2013-11-15
Motivation: Genome-scale metabolic models have been used extensively to investigate alterations in cellular metabolism. The accuracy of these models to represent cellular metabolism in specific conditions has been improved by constraining the model with omics data sources. However, few practical methods for integrating metabolomics data with other omics data sources into genome-scale models of metabolism have been reported. Results: GIMMME (Gene Inactivation Moderated by Metabolism, Metabolomics, and Expression) is an algorithm that enables the development of condition-specific models based on an objective function, transcriptomics, and intracellular metabolomics data. GIMMME establishes metabolite utilization requirements with metabolomics data, uses model-paired transcriptomics data to find experimentally supported solutions, and also provides calculations of the turnover (production / consumption) flux of metabolites. GIMMME was employed to investigate the effects of integrating additional omics datasets to create increasingly constrained solution spaces of Salmonella Typhimurium metabolism during growth in both rich and virulence media. This integration proved to be informative and resulted in a requirement of additional active reactions (12 in each case) or metabolites (26 or 29, respectively). The addition of constraints from transcriptomics also impacted the allowed solution space, and the cellular metabolites with turnover fluxes that were necessarily altered by the change in conditions increased from 118 to 271 of 1397. Availability: GIMMME has been implemented in Python and requires a COBRApy 0.2.x. The algorithm and sample data described here are freely available at: http://opencobra.sourceforge.net/
Magneto-optical cellular chip model for intracellular orientational-dynamic-activity detection
Miyashita, Y.; Iwasaka, M.; Kurita, S.; Owada, N.
2012-04-01
In the present study, a magneto-optical cellular chip model (MoCCM) was developed to detect intracellular dynamics in macromolecules by using magneto-optical effects. For the purpose of cell-measurement under strong static magnetic fields of up to 10 T, we constructed a cellular chip model, which was a thin glass plate with a well for a cell culture. A cell line of osteoblast MC3T3-E1 was incubated in the glass well, and the well, 0.3 mm in depth, was sealed by a cover glass when the MoCCM was set in a fiber optic system. An initial intensity change of the polarized light transmission, which dispersed perpendicular to the cell's attaching surface, was collected for 10 to 60 min, and then magnetic fields were applied parallel and perpendicular to the surface and light direction, respectively. The magnetic birefringence signals that originated from the magnetic orientation of intracellular molecules such as cytoskeletons apparently appeared when the magnetic fields were constant at 10 T. A statistical analysis with 15 experiments confirmed that the cellular components under 10 T magnetic fields caused a stronger alignment, which was transferred into polarizing light intensity that increased more than the case before exposure. Cellular conditions such as generation and cell density affected the magnetic birefringence signals.
Modeling of time-dose-LET effects in the cellular response to radiation
This work is dedicated to the elucidation of time-dose- and if applicable linear energy transfer (LET) effects in the cellular response to ion or photon radiation. In particular, the common concept of the Local Effect Model (LEM) and the Giant Loop Binary Lesion (GLOBLE) model, which explains cell survival probabilities on the hand of clustering of double-strand breaks (DSB) in micrometer-sized sub-structural units of the DNA, was investigated with regard to temporal aspects. In previous studies with the LEM and GLOBLE model, it has been demonstrated that the definition of two lesion classes, characterized by single or multiple DSB in a DNA giant loop, with two repair fidelities is adequate to comprehensively describe the dose dependence of the cellular response to instantaneous photon irradiation or ion irradiation with varying LET. Furthermore, with the GLOBLE model for photon radiation, it has been shown that the assignment of two repair time scales to the two lesion classes allows to adequately reproduce time-dose effects after photon irradiation with an arbitrary constant dose-rate. In this work, the results of four projects that strengthen the mechanistic consistency and the practical applicability of the LEM and GLOBLE model will be presented. First, it was found that the GLOBLE model is applicable to describe time-dose effects in the cellular response to two split photon doses and in the occurrence of deterministic radiation effects. Second, in a comparison of ten models for the temporal course of DSB rejoining, it was revealed that a bi-exponential approach, as suggested by the LEM and GLOBLE model, finds a relatively large support by 61 experimental data sets. Third, in a comparison of four kinetic photon cell survival models that was based on fits to 13 dose-rate experiments, it was shown that the GLOBLE model performs well with respect to e.g. accuracy, parsimony, reliability and other factors that characterize a good approach. Last but not least, the
Modeling of time-dose-LET effects in the cellular response to radiation
Herr, Lisa Antje
2015-07-20
This work is dedicated to the elucidation of time-dose- and if applicable linear energy transfer (LET) effects in the cellular response to ion or photon radiation. In particular, the common concept of the Local Effect Model (LEM) and the Giant Loop Binary Lesion (GLOBLE) model, which explains cell survival probabilities on the hand of clustering of double-strand breaks (DSB) in micrometer-sized sub-structural units of the DNA, was investigated with regard to temporal aspects. In previous studies with the LEM and GLOBLE model, it has been demonstrated that the definition of two lesion classes, characterized by single or multiple DSB in a DNA giant loop, with two repair fidelities is adequate to comprehensively describe the dose dependence of the cellular response to instantaneous photon irradiation or ion irradiation with varying LET. Furthermore, with the GLOBLE model for photon radiation, it has been shown that the assignment of two repair time scales to the two lesion classes allows to adequately reproduce time-dose effects after photon irradiation with an arbitrary constant dose-rate. In this work, the results of four projects that strengthen the mechanistic consistency and the practical applicability of the LEM and GLOBLE model will be presented. First, it was found that the GLOBLE model is applicable to describe time-dose effects in the cellular response to two split photon doses and in the occurrence of deterministic radiation effects. Second, in a comparison of ten models for the temporal course of DSB rejoining, it was revealed that a bi-exponential approach, as suggested by the LEM and GLOBLE model, finds a relatively large support by 61 experimental data sets. Third, in a comparison of four kinetic photon cell survival models that was based on fits to 13 dose-rate experiments, it was shown that the GLOBLE model performs well with respect to e.g. accuracy, parsimony, reliability and other factors that characterize a good approach. Last but not least, the
A Cellular Automaton Model for Tumor Dormancy: Emergence of a Proliferative Switch
Chen, Duyu; Torquato, Salvatore
2014-01-01
Malignant cancers that lead to fatal outcomes for patients may remain dormant for very long periods of time. Although individual mechanisms such as cellular dormancy, angiogenic dormancy and immunosurveillance have been proposed, a comprehensive understanding of cancer dormancy and the "switch" from a dormant to a proliferative state still needs to be strengthened from both a basic and clinical point of view. Computational modeling enables one to explore a variety of scenarios for possible but realistic microscopic dormancy mechanisms and their predicted outcomes. The aim of this paper is to devise such a predictive computational model of dormancy with an emergent "switch" behavior. Specifically, we generalize a previous cellular automaton (CA) model for proliferative growth of solid tumor that now incorporates a variety of cell-level tumor-host interactions and different mechanisms for tumor dormancy, for example the effects of the immune system. Our new CA rules induce a natural "competition" between the tu...
Li, Qi-Lang; Wong, S. C.; Min, Jie; Tian, Shuo; Wang, Bing-Hong
2016-08-01
This study examines the cellular automata traffic flow model, which considers the heterogeneity of vehicle acceleration and the delay probability of vehicles. Computer simulations are used to identify three typical phases in the model: free-flow, synchronized flow, and wide moving traffic jam. In the synchronized flow region of the fundamental diagram, the low and high velocity vehicles compete with each other and play an important role in the evolution of the system. The analysis shows that there are two types of bistable phases. However, in the original Nagel and Schreckenberg cellular automata traffic model, there are only two kinds of traffic conditions, namely, free-flow and traffic jams. The synchronized flow phase and bistable phase have not been found.
An Extended Cellular Automaton Model for Train Traffic Flow on the Dedicated Passenger Lines
Wenbo Zhao
2014-01-01
Full Text Available As one of the key components for the railway transportation system, the Train Operation Diagram can be greatly influenced by many extrinsic and intrinsic factors. Therefore, the railway train flow has shown the strong nonlinear characteristics, which makes it quite difficult to take further relative studies. Fortunately, the cellular automaton model has its own advantages in solving nonlinear problems and traffic flow simulation. Considering the mixed features of multispeed running trains on the passenger dedicated lines, this paper presents a new train model under the moving block system with different types of trains running with the cellular automaton idea. By analyzing such key factors as the maintenance skylight, the proportion of the multispeed running trains, and the distance between adjacent stations and departure intervals, the corresponding running rules for the cellular automaton model are reestablished herewith. By means of this CA model, the program of train running system is designed to analyze the potential impact on railway carrying capacity by various factors; the model can also be implemented to simulate the actual train running process and to draw the train operation diagram by computers. Basically the theory can be applied to organize the train operation on the dedicated passenger lines.
A generalized cellular automata approach to modeling first order enzyme kinetics
Abhishek Dutta; Saurajyoti Kar; Advait Apte; Ingmar Nopens; Denis Constales
2015-04-01
Biochemical processes occur through intermediate steps which are associated with the formation of reaction complexes. These enzyme-catalyzed biochemical reactions are inhibited in a number of ways such as inhibitors competing for the binding site directly, inhibitors deforming the allosteric site or inhibitors changing the structure of active substrate. Using an in silico approach, the concentration of various reaction agents can be monitored at every single time step, which are otherwise difficult to analyze experimentally. Cell-based models with discrete state variables, such as Cellular Automata (CA) provide an understanding of the organizational principles of interacting cellular systems to link the individual cell (microscopic) dynamics wit a particular collective (macroscopic) phenomenon. In this study, a CA model representing a first order enzyme kinetics with inhibitor activity is formulated. The framework of enzyme reaction rules described in this study is probabilistic. An extended von Neumann neighborhood with periodic boundary condition is implemented on a two-dimensional (2D) lattice framework. The effect of lattice-size variation is studied followed by a sensitivity analysis of the model output to the probabilistic parameters which represent various kinetic reaction constants in the enzyme kinetic model. This provides a deeper insight into the sensitivity of the CA model to these parameters. It is observed that cellular automata can capture the essential features of a discrete real system, consisting of space, time and state, structured with simple local rules without making complex implementations but resulting in complex but explainable patterns.
In Silico Modeling of the Immune System: Cellular and Molecular Scale Approaches
Mariagrazia Belfiore
2014-01-01
Full Text Available The revolutions in biotechnology and information technology have produced clinical data, which complement biological data. These data enable detailed descriptions of various healthy and diseased states and responses to therapies. For the investigation of the physiology and pathology of the immune responses, computer and mathematical models have been used in the last decades, enabling the representation of biological processes. In this modeling effort, a major issue is represented by the communication between models that work at cellular and molecular level, that is, multiscale representation. Here we sketch some attempts to model immune system dynamics at both levels.
A Stochastic Cellular Automaton Model of Non-linear Diffusion and Diffusion with Reaction
Brieger, Leesa M.; Bonomi, Ernesto
1991-06-01
This article presents a stochastic cellular automaton model of diffusion and diffusion with reaction. The master equations for the model are examined, and we assess the difference between the implementation in which a single particle at a time moves (asynchronous dynamics) and one implementation in which all particles move simultaneously (synchronous dynamics). Biasing locally each particle's random walk, we alter the diffusion coefficients of the system. By appropriately choosing the biasing function, we can impose a desired non-linear diffusive behaviour in the model. We present an application of this model, adapted to include two diffusing species, two static species, and a chemical reaction in a prototypical simulation of carbonation in concrete.
Efficient Analysis of Systems Biology Markup Language Models of Cellular Populations Using Arrays.
Watanabe, Leandro; Myers, Chris J
2016-08-19
The Systems Biology Markup Language (SBML) has been widely used for modeling biological systems. Although SBML has been successful in representing a wide variety of biochemical models, the core standard lacks the structure for representing large complex regular systems in a standard way, such as whole-cell and cellular population models. These models require a large number of variables to represent certain aspects of these types of models, such as the chromosome in the whole-cell model and the many identical cell models in a cellular population. While SBML core is not designed to handle these types of models efficiently, the proposed SBML arrays package can represent such regular structures more easily. However, in order to take full advantage of the package, analysis needs to be aware of the arrays structure. When expanding the array constructs within a model, some of the advantages of using arrays are lost. This paper describes a more efficient way to simulate arrayed models. To illustrate the proposed method, this paper uses a population of repressilator and genetic toggle switch circuits as examples. Results show that there are memory benefits using this approach with a modest cost in runtime. PMID:26912276
Konstantinos B. Baltzis
2008-10-01
Full Text Available A common assumption in cellular communications is the circular-cell approximation. In this paper, an alternative analysis based on the hexagonal shape of the cells is presented. A geometrical-based stochastic model is proposed to describe the angle of arrival of the interfering signals in the reverse link of a cellular system. Explicit closed form expressions are derived, and simulations performed exhibit the characteristics and validate the accuracy of the proposed model. Applications in the capacity estimation of WCDMA cellular networks are presented. Dependence of system capacity of the sectorization of the cells and the base station antenna radiation pattern is explored. Comparisons with data in literature validate the accuracy of the proposed model. The degree of error of the hexagonal and the circular-cell approaches has been investigated indicating the validity of the proposed model. Results have also shown that, in many cases, the two approaches give similar results when the radius of the circle equals to the hexagon inradius. A brief discussion on how the proposed technique may be applied to broadband access networks is finally made.
Hui Guo
2016-07-01
Full Text Available Evodiamine (EVO and rutaecarpine (RUT are promising anti-tumor drug candidates. The evaluation of the anti-proliferative activity and cellular uptake of EVO and RUT in 3D multicellular spheroids of cancer cells would better recapitulate the native situation and thus better reflect an in vivo response to the treatment. Herein, we employed the 3D culture of MCF-7 and SMMC-7721 cells based on hanging drop method and evaluated the anti-proliferative activity and cellular uptake of EVO and RUT in 3D multicellular spheroids, and compared the results with those obtained from 2D monolayers. The drugs’ IC50 values were significantly increased from the range of 6.4–44.1 μM in 2D monolayers to 21.8–138.0 μM in 3D multicellular spheroids, which may be due to enhanced mass barrier and reduced drug penetration in 3D models. The fluorescence of EVO and RUT was measured via fluorescence spectroscopy and the cellular uptake of both drugs was characterized in 2D tumor models. The results showed that the cellular uptake concentrations of RUT increased with increasing drug concentrations. However, the EVO concentrations uptaken by the cells showed only a small change with increasing drug concentrations, which may be due to the different solubility of EVO and Rut in solvents. Overall, this study provided a new vision of the anti-tumor activity of EVO and RUT via 3D multicellular spheroids and cellular uptake through the fluorescence of compounds.
Analysis on Traffic Conflicts of Two-lane Highway Based on Improved Cellular Automation Model
Xiru Tang
2013-06-01
Full Text Available Based on microscopic traffic characteristics of two-lane highway and different driving characteristics for drivers, the characteristics of drivers and vehicle structure are introduced into Cellular Automation model for establishing new Cellular Automation model of two-lane highway. Through computer simulation, the paper analyzes the effect of the promotion of different vehicles, drivers and arrival rates on traffic conflicts of two-lane highway, which gets the relationship between the parameters such as road traffic and velocity variance and collision. The results indicate that the frequency of traffic conflicts has close relationship with the product of traffic flow and velocity variation. When the traffic flow and velocity variation are great, the frequency of the conflict is the greatest, and when the traffic flow and velocity variation are little, the frequency of the conflict is the least.
Bit-Vectorized GPU Implementation of a Stochastic Cellular Automaton Model for Surface Growth
Kelling, Jeffrey; Gemming, Sibylle
2016-01-01
Stochastic surface growth models aid in studying properties of universality classes like the Kardar--Paris--Zhang class. High precision results obtained from large scale computational studies can be transferred to many physical systems. Many properties, such as roughening and some two-time functions can be studied using stochastic cellular automaton (SCA) variants of stochastic models. Here we present a highly efficient SCA implementation of a surface growth model capable of simulating billions of lattice sites on a single GPU. We also provide insight into cases requiring arbitrary random probabilities which are not accessible through bit-vectorization.
Transfer-matrix DMRG for stochastic models: The Domany-Kinzel cellular automaton
Kemper, A.; Schadschneider, A.; Zittartz, J.
2001-01-01
We apply the transfer-matrix DMRG (TMRG) to a stochastic model, the Domany-Kinzel cellular automaton, which exhibits a non-equilibrium phase transition in the directed percolation universality class. Estimates for the stochastic time evolution, phase boundaries and critical exponents can be obtained with high precision. This is possible using only modest numerical effort since the thermodynamic limit can be taken analytically in our approach. We also point out further advantages of the TMRG o...
An Exact Path-Loss Density Model for Mobiles in a Cellular System
Abdulla, Mouhamed; Shayan, Yousef R.
2013-01-01
In trying to emulate the spatial position of wireless nodes for purpose of analysis, we rely on stochastic simulation. And, it is customary, for mobile systems, to consider a base-station radiation coverage by an ideal cell shape. For cellular analysis, a hexagon contour is always preferred mainly because of its tessellating nature. Despite this fact, largely due to its intrinsic simplicity, in literature only random dispersion model for a circular shape is known. However, if considered, this...
Tóth, Attila; Brózik, Anna; Szakács, Gergely; Sarkadi, Balázs; Hegedüs, Tamás
2015-01-01
Cells cope with the threat of xenobiotic stress by activating a complex molecular network that recognizes and eliminates chemically diverse toxic compounds. This “chemoimmune system” consists of cellular Phase I and Phase II metabolic enzymes, Phase 0 and Phase III ATP Binding Cassette (ABC) membrane transporters, and nuclear receptors regulating these components. In order to provide a systems biology characterization of the chemoimmune network, we designed a reaction kinetic model based on d...
Van De Wiel, Marco J.; Coulthard, Tom J.; Macklin, Mark G.; Lewin, John
2007-10-01
We introduce a new computational model designed to simulate and investigate reach-scale alluvial dynamics within a landscape evolution model. The model is based on the cellular automaton concept, whereby the continued iteration of a series of local process 'rules' governs the behaviour of the entire system. The model is a modified version of the CAESAR landscape evolution model, which applies a suite of physically based rules to simulate the entrainment, transport and deposition of sediments. The CAESAR model has been altered to improve the representation of hydraulic and geomorphic processes in an alluvial environment. In-channel and overbank flow, sediment entrainment and deposition, suspended load and bed load transport, lateral erosion and bank failure have all been represented as local cellular automaton rules. Although these rules are relatively simple and straightforward, their combined and repeatedly iterated effect is such that complex, non-linear geomorphological response can be simulated within the model. Examples of such larger-scale, emergent responses include channel incision and aggradation, terrace formation, channel migration and river meandering, formation of meander cutoffs, and transitions between braided and single-thread channel patterns. In the current study, the model is illustrated on a reach of the River Teifi, near Lampeter, Wales, UK.
HE; Chunyang; SHI; Peijun; CHEN; Jin; Li; Xiaobing; PAN; Ya
2005-01-01
Modeling land use scenario changes and its potential impacts on the structure and function of the ecosystem in the typical regions are helpful to understanding the interactive mechanism between land use system and ecological system. A Land Use Scenario Dynamics (LUSD) model by the integration of System Dynamics (SD) model and Cellular Automata (CA) model is developed with land use scenario changes in northern China in the next 20 years simulated in this paper. The basic idea of LUSD model is to simulate the land use scenario demands by using SD model at first, then allocate the land use scenario patterns at the local scale with the considerations of land use suitability, inheritance ability and neighborhood effect by using CA model to satisfy the balance between land use scenario demands and supply. The application of LUSD model in northern China suggests that the model has the ability to reflect the complex behavior of land use system at different scales to some extent and is a useful tool for assessing the potential impacts of land use system on ecological system. In addition, the simulated results also indicate that obvious land use changes will take place in the farming-pastoral zone of northern China in the next 20 years with cultivated land and urban land being the most active land use types.
Ozcan, H. Kurtulus; Bilgili, Erdem; Sahin, Ulku; Ucan, O. Nuri; Bayat, Cuma
2007-09-01
Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.
H. Kurtulus OZCAN; Erdem BILGILI; Ulku SAHIN; O. Nuri UCAN; Cuma BAYAT
2007-01-01
Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.
Al-toub, Mashael; Vishnubalaji, Radhakrishnan; Hamam, Rimi;
2015-01-01
: (MCF7, BT-20, BT-474, MDA-MB-468, T-47D, SK-BR-3, MDA-MB-231, PC-3, HT-29, MDA-MB-435s, and FaDu) and changes in their morphology were assessed using fluorescent microscopy. For cellular tracking, cells were labeled with Vybrant DiO, DiL, and DiD lipophilic dyes. Time-lapse microscopy was conducted...... signaling pathways related to bone formation, FAK and MAPKK signaling. Co-culturing hMSCs with MCF7 cells increased their growth evidenced by increase in Ki67 and PCNA staining in tumor cells in direct contact with hMSCs niche. On the other hand, co-culturing hMSCs with FaDu, HT-29 or MDA-MB-231 cells led...
An improved multi-value cellular automata model for heterogeneous bicycle traffic flow
This letter develops an improved multi-value cellular automata model for heterogeneous bicycle traffic flow taking the higher maximum speed of electric bicycles into consideration. The update rules of both regular and electric bicycles are improved, with maximum speeds of two and three cells per second respectively. Numerical simulation results for deterministic and stochastic cases are obtained. The fundamental diagrams and multiple states effects under different model parameters are analyzed and discussed. Field observations were made to calibrate the slowdown probabilities. The results imply that the improved extended Burgers cellular automata (IEBCA) model is more consistent with the field observations than previous models and greatly enhances the realism of the bicycle traffic model. - Highlights: • We proposed an improved multi-value CA model with higher maximum speed. • Update rules are introduced for heterogeneous bicycle traffic with maximum speed 2 and 3 cells/s. • Simulation results of the proposed model are consistent with field bicycle data. • Slowdown probabilities of both regular and electric bicycles are calibrated
An improved multi-value cellular automata model for heterogeneous bicycle traffic flow
Jin, Sheng [College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, 310058 China (China); Qu, Xiaobo [Griffith School of Engineering, Griffith University, Gold Coast, 4222 Australia (Australia); Xu, Cheng [Department of Transportation Management Engineering, Zhejiang Police College, Hangzhou, 310053 China (China); College of Transportation, Jilin University, Changchun, 130022 China (China); Ma, Dongfang, E-mail: mdf2004@zju.edu.cn [Ocean College, Zhejiang University, Hangzhou, 310058 China (China); Wang, Dianhai [College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, 310058 China (China)
2015-10-16
This letter develops an improved multi-value cellular automata model for heterogeneous bicycle traffic flow taking the higher maximum speed of electric bicycles into consideration. The update rules of both regular and electric bicycles are improved, with maximum speeds of two and three cells per second respectively. Numerical simulation results for deterministic and stochastic cases are obtained. The fundamental diagrams and multiple states effects under different model parameters are analyzed and discussed. Field observations were made to calibrate the slowdown probabilities. The results imply that the improved extended Burgers cellular automata (IEBCA) model is more consistent with the field observations than previous models and greatly enhances the realism of the bicycle traffic model. - Highlights: • We proposed an improved multi-value CA model with higher maximum speed. • Update rules are introduced for heterogeneous bicycle traffic with maximum speed 2 and 3 cells/s. • Simulation results of the proposed model are consistent with field bicycle data. • Slowdown probabilities of both regular and electric bicycles are calibrated.
Modelling land-use effects of future urbanization using cellular automata
Fuglsang, Morten; Münier, B.; Hansen, H.S.
2013-01-01
The modelling of land use change is a way to analyse future scenarios by modelling different pathways. Application of spatial data of different scales coupled with socio-economic data makes it possible to explore and test the understanding of land use change relations. In the EU-FP7 research...... project PASHMINA (Paradigm Shift modelling and innovative approaches), three storylines of future transportation paradigm shifts towards 2040 are created. These storylines are translated into spatial planning strategies and modelled using the cellular automata model LUCIA. For the modelling, an Eastern...... Danish case area was selected, comprising of the Copenhagen metropolitan area and its hinterland. The different scenarios are described using a range of different descriptive GIS datasets. These include mapping of accessibility based on public and private transportation, urban density and structure, and...
Guided Inquiry and Consensus-Building Used to Construct Cellular Models
Joel I. Cohen
2015-02-01
Full Text Available Using models helps students learn from a “whole systems” perspective when studying the cell. This paper describes a model that employs guided inquiry and requires consensus building among students for its completion. The model is interactive, meaning that it expands upon a static model which, once completed, cannot be altered and additionally relates various levels of biological organization (molecular, organelle, and cellular to define cell and organelle function and interaction. Learning goals are assessed using data summed from final grades and from images of the student’s final cell model (plant, bacteria, and yeast taken from diverse seventh grade classes. Instructional figures showing consensus-building pathways and seating arrangements are discussed. Results suggest that the model leads to a high rate of participation, facilitates guided inquiry, and fosters group and individual exploration by challenging student understanding of the living cell.
W.H. Yu; E.J. Palmiere; S.P. Banks; J.T. Han
2005-01-01
A novel 2D cellular automata (CA) model has been developed for description of normal grain coarsening and abnormal grain coarsening process. The program reflects the grain coarsening quite well even through the average grain size becomes very large. Follow results have been obtained: (a) The model reflect the normal grain growth kinetics gradually increase with probability and grain growth speed can be controlled. Based on this result, temperature can be coupled in the model. (b) Abnormal grain growth is modelled successfully. (c) Methodology has been put forward to find the relationship between the experiment results and modelling results. The experimental work on the grain coarsening has been carried out. Graphical output matched the realistic microstructure in every detail. Because many physical parameters can be taken into account in the CA programme, this CA model could not only qualitatively demonstrate the grain growth process, but also quantitatively predict and analyse the grain coarsening process.
Random walk theory of jamming in a cellular automaton model for traffic flow
Barlovic, Robert; Schadschneider, Andreas; Schreckenberg, Michael
2001-05-01
The jamming behavior of a single lane traffic model based on a cellular automaton approach is studied. Our investigations concentrate on the so-called VDR model which is a simple generalization of the well-known Nagel-Schreckenberg model. In the VDR model one finds a separation between a free flow phase and jammed vehicles. This phase separation allows to use random walk like arguments to predict the resolving probabilities and lifetimes of jam clusters or disturbances. These predictions are in good agreement with the results of computer simulations and even become exact for a special case of the model. Our findings allow a deeper insight into the dynamics of wide jams occuring in the model.
McCune, Matthew; Shafiee, Ashkan; Forgacs, Gabor; Kosztin, Ioan
2014-03-01
Cellular Particle Dynamics (CPD) is an effective computational method for describing and predicting the time evolution of biomechanical relaxation processes of multicellular systems. A typical example is the fusion of spheroidal bioink particles during post bioprinting structure formation. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short-range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. CPD was successfully applied to describe and predict the fusion of 3D tissue construct involving identical spherical aggregates. Here, we demonstrate that CPD can also predict tissue formation involving uneven spherical aggregates whose volumes decrease during the fusion process. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.
Keith L. Black
2012-09-01
Full Text Available Doxorubicin (DOX is currently used in cancer chemotherapy to treat many tumors and shows improved delivery, reduced toxicity and higher treatment efficacy when being part of nanoscale delivery systems. However, a major drawback remains its toxicity to healthy tissue and the development of multi-drug resistance during prolonged treatment. This is why in our work we aimed to improve DOX delivery and reduce the toxicity by chemical conjugation with a new nanoplatform based on polymalic acid. For delivery into recipient cancer cells, DOX was conjugated via pH-sensitive hydrazone linkage along with polyethylene glycol (PEG to a biodegradable, non-toxic and non-immunogenic nanoconjugate platform: poly(β-L-malic acid (PMLA. DOX-nanoconjugates were found stable under physiological conditions and shown to successfully inhibit in vitro cancer cell growth of several invasive breast carcinoma cell lines such as MDA-MB-231 and MDA-MB- 468 and of primary glioma cell lines such as U87MG and U251.
A Cellular Automaton Model for Heterogeneous and Incosistent Driver Behavior in Urban Traffic
Liu, Ming-Zhe; Zhao, Shi-Bo; Wang, Rui-Li
2012-11-01
In this paper a cellular automaton model is proposed to describe driver behavior at a single-lane urban roundabout. Driver behavior has been considered as heterogeneous and inconsistent. Most traffic papers in the literature just discussed heterogeneous driver behavior, to our best knowledge. Two truncated Gaussian distributions are used to model heterogeneous and inconsistent driver behavior, respectively. The physical meanings of two truncated distributions are indicated. This method may help enhance a better understanding of driver behavior at roundabout traffic, and even possibly provide references for roundabout design and management.
ZHANG Lin; ZHANG Cai-bei
2006-01-01
Two-dimensional cellular automaton(CA) simulations of phase transformations of binary alloys during solidification were reported. The modelling incorporates local concentration and heat changes into a nucleation or growth function, which is utilized by the automaton in a probabilistic fashion. These simulations may provide an efficient method of discovering how the physical processes involved in solidification processes dynamically progress and how they interact with each other during solidification. The simulated results show that the final morphology during solidification is related with the cooling conditions. The established model can be used to evaluate the phase transformation of binary alloys during solidification.
A Cellular Automaton Model for Heterogeneous and Incosistent Driver Behavior in Urban Traffic
LIUMing-Zhe; ZHAO Shi-Bo; WANG Rui-Li
2012-01-01
In this paper a cellular automaton model is proposed to describe driver behavior at a single-lane urban roundabout. Driver behavior has been considered as heterogeneous and inconsistent. Most traffic papers in the literature just discussed heterogeneous driver behavior, to our best knowledge. Two truncated Caussian distributions are used to model heterogeneous and inconsistent driver behavior, respectively. The physical meanings of two truncated distributions are indicated. This method may help enhance a better understanding of driver behavior at roundabout traffic, and even possibly provide references for roundabout design and management.
Modeling Mixed Bicycle Traffic Flow: A Comparative Study on the Cellular Automata Approach
Dan Zhou
2015-01-01
Full Text Available Simulation, as a powerful tool for evaluating transportation systems, has been widely used in transportation planning, management, and operations. Most of the simulation models are focused on motorized vehicles, and the modeling of nonmotorized vehicles is ignored. The cellular automata (CA model is a very important simulation approach and is widely used for motorized vehicle traffic. The Nagel-Schreckenberg (NS CA model and the multivalue CA (M-CA model are two categories of CA model that have been used in previous studies on bicycle traffic flow. This paper improves on these two CA models and also compares their characteristics. It introduces a two-lane NS CA model and M-CA model for both regular bicycles (RBs and electric bicycles (EBs. In the research for this paper, many cases, featuring different values for the slowing down probability, lane-changing probability, and proportion of EBs, were simulated, while the fundamental diagrams and capacities of the proposed models were analyzed and compared between the two models. Field data were collected for the evaluation of the two models. The results show that the M-CA model exhibits more stable performance than the two-lane NS model and provides results that are closer to real bicycle traffic.
2D cellular automaton model for the evolution of active region coronal plasmas
Fuentes, Marcelo López
2016-01-01
We study a 2D cellular automaton (CA) model for the evolution of coronal loop plasmas. The model is based on the idea that coronal loops are made of elementary magnetic strands that are tangled and stressed by the displacement of their footpoints by photospheric motions. The magnetic stress accumulated between neighbor strands is released in sudden reconnection events or nanoflares that heat the plasma. We combine the CA model with the Enthalpy Based Thermal Evolution of Loops (EBTEL) model to compute the response of the plasma to the heating events. Using the known response of the XRT telescope on board Hinode we also obtain synthetic data. The model obeys easy to understand scaling laws relating the output (nanoflare energy, temperature, density, intensity) to the input parameters (field strength, strand length, critical misalignment angle). The nanoflares have a power-law distribution with a universal slope of -2.5, independent of the input parameters. The repetition frequency of nanoflares, expressed in t...
Numerical study on photoresist etching processes based on a cellular automata model
2007-01-01
For the three-dimensional (3-D) numerical study of photoresist etching processes, the 2-D dynamic cellular automata (CA) model has been successfully extended to a 3-D dynamic CA model. Only the boundary cells will be processed in the 3-D dy-namic CA model and the structure of “if-else” description in the simulation pro-gram is avoided to speed up the simulation. The 3-D dynamic CA model has found to be stable, fast and accurate for the numerical study of photoresist etching processes. The exposure simulation, post-exposure bake (PEB) simulation and etching simulation are integrated together to further investigate the performances of the CA model. Simulation results have been compared with the available ex-perimental results and the simulations show good agreement with the available experiments.
Numerical study on photoresist etching processes based on a cellular automata model
ZHOU ZaiFa; HUANG QingAn; LI WeiHua; LU Wei
2007-01-01
For the three-dimensional (3-D) numerical study of photoresist etching processes, the 2-D dynamic cellular automata (CA) model has been successfully extended to a 3-D dynamic CA model. Only the boundary cells will be processed in the 3-D dynamic CA model and the structure of "if-else" description in the simulation program is avoided to speed up the simulation. The 3-D dynamic CA model has found to be stable, fast and accurate for the numerical study of photoresist etching processes. The exposure simulation, post-exposure bake (PEB) simulation and etching simulation are integrated together to further investigate the performances of the CA model. Simulation results have been compared with the available experimental results and the simulations show good agreement with the available experiments.
A traffic flow cellular automaton model to considering drivers' learning and forgetting behaviour
Ding Jian-Xun; Huang Hai-Jun; Tian Qiong
2011-01-01
It is known that the commonly used NaSch cellular automaton (CA) model and its modifications can help explain the internal causes of the macro phenomena of traffic flow. However, the randomization probability of vehicle velocity used in these models is assumed to be an exogenous constant or a conditional constant, which cannot reflect the learning and forgetting behaviour of drivers with historical experiences. This paper further modifies the NaSch model by enabling the randomization probability to be adjusted on the bases of drivers' memory. The Markov properties of this modified model are discussed. Analytical and simulation results show that the traffic fundamental diagrams can be indeed improved when considering drivers' intelligent behaviour. Some new features of traffic are revealed by differently combining the model parameters representing learning and forgetting behaviour.
Attila Tóth
Full Text Available Cells cope with the threat of xenobiotic stress by activating a complex molecular network that recognizes and eliminates chemically diverse toxic compounds. This "chemoimmune system" consists of cellular Phase I and Phase II metabolic enzymes, Phase 0 and Phase III ATP Binding Cassette (ABC membrane transporters, and nuclear receptors regulating these components. In order to provide a systems biology characterization of the chemoimmune network, we designed a reaction kinetic model based on differential equations describing Phase 0-III participants and regulatory elements, and characterized cellular fitness to evaluate toxicity. In spite of the simplifications, the model recapitulates changes associated with acquired drug resistance and allows toxicity predictions under variable protein expression and xenobiotic exposure conditions. Our simulations suggest that multidrug ABC transporters at Phase 0 significantly facilitate the defense function of successive network members by lowering intracellular drug concentrations. The model was extended with a novel toxicity framework which opened the possibility of performing in silico cytotoxicity assays. The alterations of the in silico cytotoxicity curves show good agreement with in vitro cell killing experiments. The behavior of the simplified kinetic model suggests that it can serve as a basis for more complex models to efficiently predict xenobiotic and drug metabolism for human medical applications.
Calibrating Cellular Automata of Land Use/cover Change Models Using a Genetic Algorithm
Mas, J. F.; Soares-Filho, B.; Rodrigues, H.
2015-08-01
Spatially explicit land use / land cover (LUCC) models aim at simulating the patterns of change on the landscape. In order to simulate landscape structure, the simulation procedures of most computational LUCC models use a cellular automata to replicate the land use / cover patches. Generally, model evaluation is based on assessing the location of the simulated changes in comparison to the true locations but landscapes metrics can also be used to assess landscape structure. As model complexity increases, the need to improve calibration and assessment techniques also increases. In this study, we applied a genetic algorithm tool to optimize cellular automata's parameters to simulate deforestation in a region of the Brazilian Amazon. We found that the genetic algorithm was able to calibrate the model to simulate more realistic landscape in term of connectivity. Results show also that more realistic simulated landscapes are often obtained at the expense of the location coincidence. However, when considering processes such as the fragmentation impacts on biodiversity, the simulation of more realistic landscape structure should be preferred to spatial coincidence performance.
Solari, Cristian A; Kessler, John O; Goldstein, Raymond E
2013-03-01
The transition from unicellular, to colonial, to larger multicellular organisms has benefits, costs, and requirements. Here we present a model inspired by the volvocine green algae that explains the dynamics involved in the unicellular-multicellular transition using life-history theory and allometry. We model the two fitness components (fecundity and viability) and compare the fitness of hypothetical colonies of different sizes with varying degrees of cellular differentiation to understand the general principles that underlie the evolution of multicellularity. We argue that germ-soma separation may have evolved to counteract the increasing costs and requirements of larger multicellular colonies. The model shows that the cost of investing in soma decreases with size. For lineages such as the Volvocales, as reproduction costs increase with size for undifferentiated colonies, soma specialization benefits the colony indirectly by decreasing such costs and directly by helping reproductive cells acquire resources for their metabolic needs. Germ specialization is favored once soma evolves and takes care of vegetative functions. To illustrate the model, we use some allometric relationships measured in Volvocales. Our analysis shows that the cost of reproducing an increasingly larger group has likely played an important role in the transition to multicellularity and cellular differentiation. PMID:23448886
Simulation of emotional contagion using modified SIR model: A cellular automaton approach
Fu, Libi; Song, Weiguo; Lv, Wei; Lo, Siuming
2014-07-01
Emotion plays an important role in the decision-making of individuals in some emergency situations. The contagion of emotion may induce either normal or abnormal consolidated crowd behavior. This paper aims to simulate the dynamics of emotional contagion among crowds by modifying the epidemiological SIR model to a cellular automaton approach. This new cellular automaton model, entitled the “CA-SIRS model”, captures the dynamic process ‘susceptible-infected-recovered-susceptible', which is based on SIRS contagion in epidemiological theory. Moreover, in this new model, the process is integrated with individual movement. The simulation results of this model show that multiple waves and dynamical stability around a mean value will appear during emotion spreading. It was found that the proportion of initial infected individuals had little influence on the final stable proportion of infected population in a given system, and that infection frequency increased with an increase in the average crowd density. Our results further suggest that individual movement accelerates the spread speed of emotion and increases the stable proportion of infected population. Furthermore, decreasing the duration of an infection and the probability of reinfection can markedly reduce the number of infected individuals. It is hoped that this study will be helpful in crowd management and evacuation organization.
Non-linearity and spatial resolution in a cellular automaton model of a small upland basin
T. J. Coulthard
1998-01-01
Full Text Available The continuing development of computational fluid dynamics is allowing the high resolution study of hydraulic and sediment transport processes but, due to computational complexities, these are rarely applied to areas larger than a reach. Existing approaches, based upon linked cross sections, can give a quasi two-dimensional view, effectively simulating sediment transport for a single river reach. However, a basin represents a whole discrete dynamic system within which channel, floodplain and slope processes operate over a wide range of space and time scales. Here, a cellular automaton (CA approach has been used to overcome some of these difficulties, in which the landscape is represented as a series of fixed size cells. For every model iteration, each cell acts only in relation to the influence of its immediate neighbours in accordance with appropriate rules. The model presented here takes approximations of existing flow and sediment transport equations, and integrates them, together with slope and floodplain approximations, within a cellular automaton framework. This method has been applied to the basin of Cam Gill Beck (4.2 km2 above Starbotton, upper Wharfedale, a tributary of the River Wharfe, North Yorkshire, UK. This approach provides, for the first time, a workable model of the whole basin at a 1 m resolution. Preliminary results show the evolution of bars, braids, terraces and alluvial fans which are similar to those observed in the field, and examples of large and small scale non-linear behaviour which may have considerable implications for future models.
Advanced spatial metrics analysis in cellular automata land use and cover change modeling
This paper proposes an approach for a more effective definition of cellular automata transition rules for landscape change modeling using an advanced spatial metrics analysis. This approach considers a four-stage methodology based on: (i) the search for the appropriate spatial metrics with minimal correlations; (ii) the selection of the appropriate neighborhood size; (iii) the selection of the appropriate technique for spatial metrics application; and (iv) the analysis of the contribution level of each spatial metric for joint use. The case study uses an initial set of 7 spatial metrics of which 4 are selected for modeling. Results show a better model performance when compared to modeling without any spatial metrics or with the initial set of 7 metrics.
Empirical results for pedestrian dynamics and their implications for cellular automata models
Schadschneider, Andreas
2010-01-01
A large number of models for pedestrian dynamics have been developed over the years. However, so far not much attention has been paid to their quantitative validation. Usually the focus is on the reproduction of empirically observed collective phenomena, as lane formation in counterflow. This can give an indication for the realism of the model, but practical applications, e.g. in safety analysis, require quantitative predictions. We discuss the current experimental situation, especially for the fundamental diagram which is the most important quantity needed for calibration. In addition we consider the implications for the modelling based on cellular automata. As specific example the floor field model is introduced. Apart from the properties of its fundamental diagram we discuss the implications of an egress experiment for the relevance of conflicts and friction effects.
A new three-step cellular automaton model considering a realistic driving decision
Most cellular automaton (CA) traffic flow models include four steps and take the velocity as the driver’s main concern. To better understand traffic behaviors, a new three-step CA model is studied, in which a realistic driving decision is divided into three stages: decision-making, action and result. The new model is novel in using the acceleration as a decision variable. It considers the deceleration limitation and proposes the maximum deceleration to be 2 cells per time step, based on real experimental data. Simulation results show that the model can reproduce the synchronized flow effectively and describe the phase transition well. Moreover, it can exhibit metastability and hysteresis if the slow-to-start effect is involved. Finally, a realistic application to systematic flow optimization is analyzed and an interesting result is obtained that a restriction of the inflow can lead to an improvement of the total flow through a bottleneck. (paper)
M. Górny
2012-12-01
Full Text Available The mathematical model of the globular eutectic solidification in 2D was designed. Proposed model is based on the Cellular AutomatonFinite Differences (CA-FD calculation method. Model has been used for studies of the primary austenite and of globular eutectic grainsgrowth during the ductile iron solidification in the thin wall casting. Model takes into account, among other things, non-uniformtemperature distribution in the casting wall cross-section, kinetics of the austenite and graphite grains nucleation, and non-equilibriumnature of the interphase boundary migration. Calculation of eutectic saturation influence (Sc = 0.9 - 1.1 on microstructure (austenite and graphite fraction, density of austenite and graphite grains and temperature curves in 2 mm wall ductile iron casting has been done.
Cellular-automata model of the dwarf shrubs populations and communities dynamics
A. S. Komarov
2015-06-01
Full Text Available The probabilistic cellular-automata model of development and long-time dynamics of dwarf shrub populations and communities is developed. It is based on the concept of discrete description of the plant ontogenesis and joint model approaches in terms of probabilistic cellular automata and L-systems by Lindenmayer. Short representation of the basic model allows evaluation of the approach and software implementation. The main variables of the model are a number of partial bushes in clones or area projective cover. The model allows us to investigate the conditions of self-maintenance and sustainability population under different environmental conditions (inaccessibility of the territory for settlement, mosaic moisture conditions of soil and wealth. The model provides a forecast of the total biomass dynamics shrubs and their fractions (stems, leaves, roots, fine roots, fruits on the basis of the data obtained in the discrete description of ontogenesis and further information on the productivity of the plant fractions. The inclusion of the joint dynamics of biomass of shrubs and soil in EFIMOD models cycle of carbon and nitrogen to evaluate the role of shrubs in these circulations, especially at high impact, such as forest fires and clear cutting, allow forecasting of the dynamics of populations and ecosystem functions of shrubs (regulation of biogeochemical cycles maintaining biodiversity, participation in the creation of non-wood products with changing climatic conditions and strong damaging effects (logging, fires; and application of the models developed to investigate the stability and productivity of shrubs and their participation in the cycle of carbon and nitrogen in different climatic and edaphic conditions.
Cellular automata model based on GIS and urban sprawl dynamics simulation
Mu, Fengyun; Zhang, Zengxiang
2005-10-01
The simulation of land use change process needs the support of Geographical Information System (GIS) and other relative technologies. While the present commercial GIS lack capabilities of distribution, prediction, and simulation of spatial-temporal data. Cellular automata (CA) provide dynamically modeling "from bottom-to-top" framework and posses the capability of modeling spatial-temporal evolvement process of a complicated geographical system, which is composed of a fourfold: cells, states, neighbors and rules. The simplicity and flexibility make CA have the ability to simulate a variety of behaviors of complex systems. One of the most potentially useful applications of cellular automata from the point of view of spatial planning is their use in simulations of urban sprawl at local and regional level. The paper firstly introduces the principles and characters of the cellular automata, and then discusses three methods of the integration of CA and GIS. The paper analyses from a practical point of view the factors that effect urban activities in the science of spatial decision-making. The status of using CA to dynamic simulates of urban expansion at home and abroad is analyzed. Finally, the problems and tendencies that exist in the application of CA model are detailed discussed, such as the quality of the data that the CA needs, the self-organization of the CA roots in the mutual function among the elements of the system, the partition of the space scale, the time calibration of the CA and the integration of the CA with other modular such as artificial nerve net modular and population modular etc.
Khan, Muhammad Sadiq Ali; Yousuf, Sidrah
2016-03-01
Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle. PMID:27087101
In situ sensing and modeling of molecular events at the cellular level
Yang, Ruiguo
We developed the Atomic Force Microscopy (AFM) based nanorobot in combination with other nanomechanical sensors for the investigation of cell signaling pathways. The AFM nanorobotics hinge on the superior spatial resolution of AFM in imaging and extends it into the measurement of biological processes and manipulation of biological matters. A multiple input single output control system was designed and implemented to solve the issues of nanomanipulation of biological materials, feedback, response frequency and nonlinearity. The AFM nanorobotic system therefore provide the human-directed position, velocity and force control with high frequency feedback, and more importantly it can feed the operator with the real-time imaging of manipulation result from the fast-imaging based local scanning. The use of the system has taken the study of cellular process at the molecular scale into a new level. The cellular response to the physiological conditions can be significantly manifested in cellular mechanics. Dynamic mechanical property has been regarded as biomarkers, sometimes even regulators of the signaling and physiological processes, thus the name mechanobiology. We sought to characterize the relationship between the structural dynamics and the molecular dynamics and the role of them in the regulation of cell behavior. We used the AFM nanorobotics to investigate the mechanical properties in real-time of cells that are stimulated by different chemical species. These reagents could result in similar ion channel responses but distinctive mechanical behaviors. We applied these measurement results to establish a model that describes the cellular stimulation and the mechanical property change, a "two-hit" model that comprises the loss of cell adhesion and the initiation of cell apoptosis. The first hit was verified by functional experiments: depletion of Calcium and nanosurgery to disrupt the cellular adhesion. The second hit was tested by a labeling of apoptotic markers that
Bagnoli, Franco
1998-01-01
An introduction to cellular automata (both deterministic and probabilistic) with examples. Definition of deterministic automata, dynamical properties, damage spreading and Lyapunov exponents; probabilistic automata and Markov processes, nonequilibrium phase transitions, directed percolation, diffusion; simulation techniques, mean field. Investigation themes: life, epidemics, forest fires, percolation, modeling of ecosystems and speciation. They represent my notes for the school "Dynamical Mod...
A novel model for studies of blood-mediated long-term responses to cellular transplants
Hårdstedt, Maria; Lindblom, Susanne; Hong, Jaan; Nilsson, Bo; Korsgren, Olle; Ronquist, Gunnar
2015-01-01
Aims Interaction between blood and bio-surfaces is important in many medical fields. With the aim of studying blood-mediated reactions to cellular transplants, we developed a whole-blood model for incubation of small volumes for up to 48 h. Methods Heparinized polyvinyl chloride tubing was cut in suitable lengths and sealed to create small bags. Multiple bags, with fresh venous blood, were incubated attached to a rotating wheel at 37°C. Physiological variables in blood were monitored: glucose...
Case Study of Phase Transition in Cellular Models of Pedestrian Flow
Bukáček, M.; Hrabák, Pavel
Cham : Springer, 2014 - (Was, J.; Sirakoulis, G.; Bandini, S.), s. 508-517 ISBN 978-3-319-11519-1. ISSN 0302-9743. - (Lecture Notes in Computer Science. 8751). [ACRI 2014. International Conference on Cellular Automata for Research and Industry /11./. Krakov (PL), 22.09.2014-25.09.2014] R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Floor field model * phase transition * travel time * bounds principle * asynchronous update Subject RIV: IN - Informatics, Computer Science http://library.utia.cas.cz/separaty/2014/AS/hrabak-0432244.pdf
Metabolically active portion of fat-free mass: a cellular body composition level modeling analysis
Wang, ZiMian; Heshka, Stanley; Wang, Jack; Gallagher, Dympna; Deurenberg, Paul; Chen, Zhao; Heymsfield, Steven B
2006-01-01
The proportion of fat-free mass (FFM) as body cell mass (BCM) is highly related to whole body resting energy expenditure. However, the magnitude of BCM/FFM may have been underestimated in previous studies. This is because Moore’s equation [BCM (kg) =0.00833 × total body potassium (in mmol)], which was used to predict BCM, underestimates BCM by ~ %. The aims of the present study were to develop a theoretical BCM/FFM model at the cellular level and to explore the influences of sex, age, and adi...
Driver’s Awareness and Lane Changing Maneuver in Traffic Flow based on Cellular Automaton Model
Kohei Arai; Steven Ray Sentinuwo
2015-01-01
Effect of driver’s awareness (e.g., to estimate the speed and arrival time of another vehicle) on the lane changing maneuver is discussed. “Scope awareness” is defined as the visibility which is required for the driver to make a visual perception about road condition and the speed of vehicle that appears in the target lane for lane changing in the road. Cellular automaton based simulation model is created and applied to simulation studies for driver awareness behavior. This study clarifies re...
Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi
2015-08-01
Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.
Transition between immune and disease states in a cellular automaton model of clonal immune response
Bezzi, M; Ruffo, S; Seiden, P E; Bezzi, Michele; Celada, Franco; Ruffo, Stefano; Seiden, Philip E.
1997-01-01
In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infectious virus and cytotoxic T lymphocytes (cellular response). The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host's ability to eliminate the virus. We find two basins of attraction in the dynamics of this system, one is identified with disease and the other with the immune state. There is also an oscillating state that exists on the border of these two stable states. Fluctuations in the population of virus or antibody can end the oscillation and drive the system into one of the stable states. The introduction of mechanisms of cross-regulation between the two responses can bias the system towards one of them. We also study a mean field model, based on coupled maps, to investigate virus-like infections. This simple model reproduces the attractors for average populations observed in the cellular automaton. All the dynamical behavior connect...
An implementation of cellular automaton model for single-line train working diagram
Hua Wei; Liu Jun
2006-01-01
According to the railway transportation system's characteristics,a new cellular automaton model for the singleline railway system is presented in this paper.Based on this model,several simulations were done to imitate the train operation under three working diagrams.From a different angle the results show how the organization of train operation impacts on the railway carrying capacity.By using the non-parallel train working diagram the influence of fast-train on slow-train is found to be the strongest.Many slow-trains have to wait in-between neighbouring stations to let the fast-train(s) pass through first.So the slow-train will advance like a wave propagating from the departure station to the arrival station.This also resembles the situation of a highway jammed traffic flow.Furthermore,the nonuniformity of travel times between the sections also greatly limits the railway carrying capacity.After converting the nonuniform sections into the sections with uniform travel times while the total travel time is kept unchanged,all three carrying capacities are improved greatly as shown by simulation.It also shows that the cellular automaton model is an effective and feasible way to investigate the railway transDortation system.
Modeling of the competition life cycle using the software complex of cellular automata PyCAlab
Berg, D. B.; Beklemishev, K. A.; Medvedev, A. N.; Medvedeva, M. A.
2015-11-01
The aim of the work is to develop a numerical model of the life cycle of competition on the basis of software complex cellular automata PyCAlab. The model is based on the general patterns of growth of various systems in resource-limited settings. At examples it is shown that the period of transition from an unlimited growth of the market agents to the stage of competitive growth takes quite a long time and may be characterized as monotonic. During this period two main strategies of competitive selection coexist: 1) capture of maximum market space with any reasonable costs; 2) saving by reducing costs. The obtained results allow concluding that the competitive strategies of companies must combine two mentioned types of behavior, and this issue needs to be given adequate attention in the academic literature on management. The created numerical model may be used for market research when developing of the strategies for promotion of new goods and services.
A Two-Lane Cellular Automata Model with Influence of Next-Nearest Neighbor Vehicle
In this paper, we propose a new two-lane cellular automata model in which the influence of the next-nearest neighbor vehicle is considered. The attributes of the traffic system composed of fast-lane and slow-lane are investigated by the new traffic model. The simulation results show that the proposed two-lane traffic model can reproduce some traffic phenomena observed in real traffic, and that maximum flux and critical density are close to the field measurements. Moreover, the initial density distribution of the fast-lane and slow-lane has much influence on the traffic flow states. With the ratio between the densities of slow lane and fast lane increasing the lane changing frequency increases, but maximum flux decreases. Finally, the influence of the sensitivity coefficients is discussed.
Aalaei, Amin; Davoudpour, Hamid
2012-11-01
This article presents designing a new mathematical model for integrating dynamic cellular manufacturing into supply chain system with an extensive coverage of important manufacturing features consideration of multiple plants location, multi-markets allocation, multi-period planning horizons with demand and part mix variation, machine capacity, and the main constraints are demand of markets satisfaction in each period, machine availability, machine time-capacity, worker assignment, available time of worker, production volume for each plant and the amounts allocated to each market. The aim of the proposed model is to minimize holding and outsourcing costs, inter-cell material handling cost, external transportation cost, procurement & maintenance and overhead cost of machines, setup cost, reconfiguration cost of machines installation and removal, hiring, firing and salary worker costs. Aimed to prove the potential benefits of such a design, presented an example is shown using a proposed model.
Ren, Gang; Jiang, Hang; Chen, Jingxu; Huang, Zhengfeng; Lu, Lili
2016-06-01
This paper presents a cellular automata (CA) model to elucidate the straight-through movements of the heterogeneous bicycle traffic at signalized intersection. The CA model, via simulation, particularly exposits the dispersion phenomenon existing in the straight-through bicycle traffic. The nonlane-based cycling behavior and diverse bicycle properties are also incorporated in the CA model. A series of simulations are conducted to reveal the travel process, bicycles interaction and influence of the dispersion phenomenon. The simulation results show that the dispersion phenomenon significantly results in more bicycles interactions in terms of spilling maneuvers and overtaking maneuvers during the straight-through movements. Meanwhile, the dispersion phenomenon could contribute to the efficiency of the bicycle traffic, and straight-through bicycles need less time to depart the intersection under the circumstance of dispersion phenomenon. The simulation results are able to provide specific guideline for reasonably utilizing the dispersion phenomenon to improve the operational efficiency of straight-through bicycle traffic.
Kamran Forghani
2012-10-01
Full Text Available In this paper, a new mathematical model in cellular manufacturing systems (CMSs has been presented. In order to increase the performance of manufacturing system, the production quantity of parts has been considered as a decision variable, i.e. each part can be produced and outsourced, simultaneously. This extension would be minimized the unused capacity of machines. The exceptional elements (EEs are taken into account and would be totally outsourced to the external supplier in order to remove intercellular material handling cost. The problem has been formulated as a mixed-integer programming to minimize the sum of manufacturing variable costs under budget, machines capacity and demand constraints. Also, to evaluate advantages of the model, several illustrative numerical examples have been provided to compare the performance of the proposed model with the available classical approaches in the literature.
Steady state speed distribution analysis for a combined cellular automaton traffic model
Wang Jun-Feng; Chen Gui-Sheng; Liu Jin
2008-01-01
Cellular Automaton (CA) baaed traffic flow models have been extensively studied due to their effectiveness and simplicity in recent years. This paper develops a discrete time Markov chain (DTMC) analytical framework for a Nagel-Schreckenberg and Fukui-Ishibashi combined CA model (W2H traffic flow model) from microscopic point of view to capture the macroscopic steady state speed distributions. The inter-vehicle spacing Markov chain and the steady state speed Markov chain are proved to be irreducible and ergodie. The theoretical speed probability distributions depending on the traffic density and stochastic delay probability are in good accordance with numerical simulations. The derived fundamental diagram of the average speed from theoretical speed distributions is equivalent to the results in the previous work.
The problem of quantitative mathematical models in cellular radiation biology is discussed in a general way. It is emphasized that there are a number of stages, starting from the spatial pattern of energy deposition and ending with repair/misrepair processes which all need to be incorporated. Since different types of radiation commonly yield very similar dose-response curves a model which is only valid for one special case cannot claim general applicability. Interaction experiments with ultraviolet and ionizing radiation are discussed in this context. Also the role of different experimental systems (microorganisms versus mammalian cells) has to be taken into account. A number of current model approaches are discussed within this context, and it is shown that most of them do not satisfy the criterion of universal applicability and can therefore not claim to give a 'true' picture of biological reality. Shouldered survival curves are taken as an example to illustrate these points in a more specific way
A computable cellular stress network model for non-diseased pulmonary and cardiovascular tissue
Drubin David
2011-10-01
Full Text Available Abstract Background Humans and other organisms are equipped with a set of responses that can prevent damage from exposure to a multitude of endogenous and environmental stressors. If these stress responses are overwhelmed, this can result in pathogenesis of diseases, which is reflected by an increased development of, e.g., pulmonary and cardiac diseases in humans exposed to chronic levels of environmental stress, including inhaled cigarette smoke (CS. Systems biology data sets (e.g., transcriptomics, phosphoproteomics, metabolomics could enable comprehensive investigation of the biological impact of these stressors. However, detailed mechanistic networks are needed to determine which specific pathways are activated in response to different stressors and to drive the qualitative and eventually quantitative assessment of these data. A current limiting step in this process is the availability of detailed mechanistic networks that can be used as an analytical substrate. Results We have built a detailed network model that captures the biology underlying the physiological cellular response to endogenous and exogenous stressors in non-diseased mammalian pulmonary and cardiovascular cells. The contents of the network model reflect several diverse areas of signaling, including oxidative stress, hypoxia, shear stress, endoplasmic reticulum stress, and xenobiotic stress, that are elicited in response to common pulmonary and cardiovascular stressors. We then tested the ability of the network model to identify the mechanisms that are activated in response to CS, a broad inducer of cellular stress. Using transcriptomic data from the lungs of mice exposed to CS, the network model identified a robust increase in the oxidative stress response, largely mediated by the anti-oxidant NRF2 pathways, consistent with previous reports on the impact of CS exposure in the mammalian lung. Conclusions The results presented here describe the construction of a cellular stress
Zhao, Yuchao; Conolly, Rory B; Andersen, Melvin E.
2006-11-21
This report describes the development of a computational systems biology approach to evaluate the hypotheses of molecular and cellular mechanisms of adaptive response to low dose ionizing radiation. Our concept is that computational models of signaling pathways can be developed and linked to biologically based dose response models to evaluate the underlying molecular mechanisms which lead to adaptive response. For development of quantitatively accurate, predictive models, it will be necessary to describe tissues consisting of multiple cell types where the different types each contribute in their own way to the overall function of the tissue. Such a model will probably need to incorporate not only cell type-specific data but also spatial information on the architecture of the tissue and on intercellular signaling. The scope of the current model was more limited. Data obtained in a number of different biological systems were synthesized to describe a chimeric, “average” population cell. Biochemical signaling pathways involved in sensing of DNA damage and in the activation of cell cycle checkpoint controls and the apoptotic path were also included. As with any computational modeling effort, it was necessary to develop these simplified initial descriptions (models) that can be iteratively refined. This preliminary model is a starting point which, with time, can evolve to a level of refinement where large amounts of detailed biological information are synthesized and a capability for robust predictions of dose- and time-response behaviors is obtained.
A Vector-based Cellular Automata Model for Simulating Urban Land Use Change
LU Yi; CAO Min; ZHANG Lei
2015-01-01
Cellular Automata (CA) is widely used for the simulation of land use changes.This study applied a vector-based CA model to simulate land use change in order to minimize or eliminate the scale sensitivity in traditional raster-based CA model.The cells of vector-based CA model are presented according to the shapes and attributes of geographic entities,and the transition rules of vector-based CA model are improved by taking spatial variables of the study area into consideration.The vector-based CA model is applied to simulate land use changes in downtown of Qidong City,Jiangsu Province,China and its validation is confirmed by the methods of visual assessment and spatial accuracy.The simulation result of vector-based CA model reveals that nearly 75％ of newly increased urban cells are located in the northwest and southwest parts of the study area from 2002 to 2007,which is in consistent with real land use map.In addition,the simulation results of the vector-based and raster-based CA models are compared to real land use data and their spatial accuracies are found to be 84.0％ and 81.9％,respectively.In conclusion,results from this study indicate that the vector-based CA model is a practical and applicable method for the simulation of urbanization processes.
Geographic Spatiotemporal Dynamic Model using Cellular Automata and Data Mining Techniques
Ahmad Zuhdi
2011-05-01
Full Text Available Geospatial data and information availability has been increasing rapidly and has provided users with knowledge on entities change and movement in a system. Cellular Geography model applies Cellular Automata on Geographic data by defining transition rules to the data grid. This paper presents the techniques for extracting transition rule(s from time series data grids, using multiple linear regression analysis. Clustering technique is applied to minimize the number of transition rules, which can be offered and chosen to change a new unknown grid. Each centroid of a cluster is associated with a transition rule and a grid of data. The chosen transition rule is associated with grid that has a minimum distance to the new data grid to be simulated. Validation of the model can be provided either quantitatively through an error measurement or qualitatively by visualizing the result of the simulation process. The visualization can also be more informative by adding the error information. Increasing number of cluster may give possibility to improve the simulation accuracy.
The mechanics of cellular compartmentalization as a model for tumor spreading
Fritsch, Anatol; Pawlizak, Steve; Zink, Mareike; Kaes, Josef A.
2012-02-01
Based on a recently developed surgical method of Michael H"ockel, which makes use of cellular confinement to compartments in the human body, we study the mechanics of the process of cell segregation. Compartmentalization is a fundamental process of cellular organization and occurs during embryonic development. A simple model system can demonstrate the process of compartmentalization: When two populations of suspended cells are mixed, this mixture will eventually segregate into two phases, whereas mixtures of the same cell type will not. In the 1960s, Malcolm S. Steinberg formulated the so-called differential adhesion hypothesis which explains the segregation in the model system and the process of compartmentalization by differences in surface tension and adhesiveness of the interacting cells. We are interested in to which extend the same physical principles affect tumor growth and spreading between compartments. For our studies, we use healthy and cancerous breast cell lines of different malignancy as well as primary cells from human cervix carcinoma. We apply a set of techniques to study their mechanical properties and interactions. The Optical Stretcher is used for whole cell rheology, while Cell-cell-adhesion forces are directly measured with a modified AFM. In combination with 3D segregation experiments in droplet cultures we try to clarify the role of surface tension in tumor spreading.
Achour, Imène; Arel-Dubeau, Anne-Marie; Renaud, Justine; Legrand, Manon; Attard, Everaldo; Germain, Marc; Martinoli, Maria-Grazia
2016-01-01
Parkinson's disease (PD) is a progressive neurodegenerative disorder, primarily affecting dopaminergic neurons in the substantia nigra. There is currently no cure for PD and present medications aim to alleviate clinical symptoms, thus prevention remains the ideal strategy to reduce the prevalence of this disease. The goal of this study was to investigate whether oleuropein (OLE), the major phenolic compound in olive derivatives, may prevent neuronal degeneration in a cellular dopaminergic model of PD, differentiated PC12 cells exposed to the potent parkinsonian toxin 6-hydroxydopamine (6-OHDA). We also investigated OLE's ability to mitigate mitochondrial oxidative stress and modulate the autophagic flux. Our results obtained by measuring cytotoxicity and apoptotic events demonstrate that OLE significantly decreases neuronal death. OLE could also reduce mitochondrial production of reactive oxygen species resulting from blocking superoxide dismutase activity. Moreover, quantification of autophagic and acidic vesicles in the cytoplasm alongside expression of specific autophagic markers uncovered a regulatory role for OLE against autophagic flux impairment induced by bafilomycin A1. Altogether, our results define OLE as a neuroprotective, anti-oxidative and autophagy-regulating molecule, in a neuronal dopaminergic cellular model. PMID:27517912
Imène Achour
2016-08-01
Full Text Available Parkinson’s disease (PD is a progressive neurodegenerative disorder, primarily affecting dopaminergic neurons in the substantia nigra. There is currently no cure for PD and present medications aim to alleviate clinical symptoms, thus prevention remains the ideal strategy to reduce the prevalence of this disease. The goal of this study was to investigate whether oleuropein (OLE, the major phenolic compound in olive derivatives, may prevent neuronal degeneration in a cellular dopaminergic model of PD, differentiated PC12 cells exposed to the potent parkinsonian toxin 6-hydroxydopamine (6-OHDA. We also investigated OLE’s ability to mitigate mitochondrial oxidative stress and modulate the autophagic flux. Our results obtained by measuring cytotoxicity and apoptotic events demonstrate that OLE significantly decreases neuronal death. OLE could also reduce mitochondrial production of reactive oxygen species resulting from blocking superoxide dismutase activity. Moreover, quantification of autophagic and acidic vesicles in the cytoplasm alongside expression of specific autophagic markers uncovered a regulatory role for OLE against autophagic flux impairment induced by bafilomycin A1. Altogether, our results define OLE as a neuroprotective, anti-oxidative and autophagy-regulating molecule, in a neuronal dopaminergic cellular model.
Topol, Igor A.; Nemukhin, Alexander V.; Burt, Stanley K.
Interactions of 1,2-dithiolane species with zinc-containing sites, which mimic the zinc finger domains of retroviral and the cellular zinc finger proteins, have been investigated by quantum chemistry tools. According to the calculations, the immediate domains of zinc binding sites in the cellular and retroviral zinc fingers interact differently with such agents of the disulphide family. Thus, when approaching the model cellular-type domains, the molecules of 1,2-dithiolanes experience considerable potential barriers along the reaction path. However, these species react practically barrier-less with the model retroviral-type domains at the correlated DFT level. The results of the quantum chemical modelling provide firm support to the selectivity of 1,2-dithiolanes towards retroviral and cellular zinc fingers. This can be of great practical importance for the design of therapeutics that accomplish functional inactivation of the zinc fingers of the human immunodeficiency virus (HIV-1) retroviral type nucleocapsid protein NCp7.
Megan Olsen
Full Text Available Computational models in the field of cancer research have focused primarily on estimates of biological events based on laboratory generated data. We introduce a novel in-silico technology that takes us to the next level of prediction models and facilitates innovative solutions through the mathematical system. The model's building blocks are cells defined phenotypically as normal or tumor, with biological processes translated into equations describing the life protocols of the cells in a quantitative and stochastic manner. The essentials of communication in a society composed of normal and tumor cells are explored to reveal "protocols" for selective tumor eradication. Results consistently identify "citizenship properties" among cells that are essential for the induction of healing processes in a healthy system invaded by cancer. These properties act via inter-cellular communication protocols that can be optimized to induce tumor eradication along with system recovery. Within the computational systems, the protocols universally succeed in removing a wide variety of tumors defined by proliferation rates, initial volumes, and apoptosis resistant phenotypes; they show high adaptability for biological details and allow incorporation of population heterogeneity. These protocols work as long as at least 32% of cells obey extra-cellular commands and at least 28% of cancer cells report their deaths. This low percentage implies that the protocols are resilient to the suboptimal situations often seen in biological systems. We conclude that our in-silico model is a powerful tool to investigate, to propose, and to exercise logical anti-cancer solutions. Functional results should be confirmed in a biological system and molecular findings should be loaded into the computational model for the next level of directed experiments.
A Modified Cellular Automaton Approach for Mixed Bicycle Traffic Flow Modeling
Xiaonian Shan
2015-01-01
Full Text Available Several previous studies have used the Cellular Automaton (CA for the modeling of bicycle traffic flow. However, previous CA models have several limitations, resulting in differences between the simulated and the observed traffic flow features. The primary objective of this study is to propose a modified CA model for simulating the characteristics of mixed bicycle traffic flow. Field data were collected on physically separated bicycle path in Shanghai, China, and were used to calibrate the CA model using the genetic algorithm. Traffic flow features between simulations of several CA models and field observations were compared. The results showed that our modified CA model produced more accurate simulation for the fundamental diagram and the passing events in mixed bicycle traffic flow. Based on our model, the bicycle traffic flow features, including the fundamental diagram, the number of passing events, and the number of lane changes, were analyzed. We also analyzed the traffic flow features with different traffic densities, traffic components on different travel lanes. Results of the study can provide important information for understanding and simulating the operations of mixed bicycle traffic flow.
Idealized Mesoscale Model Simulations of Open Cellular Convection Over the Sea
Vincent, Claire Louise; Hahmann, Andrea N.; Kelly, Mark C.
2012-01-01
important terms in the budgets were buoyancy, pressure balance and inter-scale transfer to subgrid scales. Cells were also composited to calculate the average cell-scale flow and each of the budget terms on two-dimensional cross-sections through the cells, parallel and perpendicular to the mean wind......The atmospheric conditions during an observed case of open cellular convection over the North Sea were simulated using the Weather Research and Forecasting (WRF) numerical model. Wind, temperature and water vapour mixing ratio profiles from the WRF simulation were used to initialize an idealized...... version of the model, which excluded the effects of topography, surface inhomogeneities and large-scale weather forcing. Cells with an average diameter of 17.4 km developed. Simulations both with and without a capping inversion were made, and the cell-scale kinetic energy budget was calculated for each...
Modeling and Simulation for Urban Rail Traffic Problem Based on Cellular Automata
许琰; 曹成铉; 李明华; 罗金龙
2012-01-01
Based on the Nagel-Schreckenberg model, we propose a new cellular automata model to simulate the urban rail traffic flow under moving block system and present a new minimum instantaneous distance formula under pure moving block. We also analyze the characteristics of the urban rail traffic flow under the influence of train density, station dwell times, the length of train, and the train velocity. Train delays can be decreased effectively through flexible departure intervals according to the preceding train type before its departure. The results demonstrate that a suitable adjustment of the current train velocity based on the following train velocity can greatly shorten the minimum departure intervals and then increase the capacity of rail transit.