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The effect of cigarette smoking on endothelial damage and atherosclerosis development – modeled and analyzed using Petri nets

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Atherosclerosis as one of the crucial causes of cardiovascular diseases (CVD) is the leading reason of death worldwide. One of the contributing factors to this phenomenon is endothelial dysfunction, which is associated with the impact of various agents and their interactions. Tobacco smoke is one of the well known factors here. For better understanding of its significance a model of its impact on atherosclerotic plaque formation has been proposed. The model contains selected aspects of the influence of tobacco smoke, dual function of nitric oxide (NO) (influence of various mechanisms on NO bioavailability), oxidative stress which promotes low density lipoproteins oxidation, macrophages significance and other mechanisms leading to an aggravation of the endothelial disturbances. The model has been built using Petri nets theory and the analysis has been based on t-invariants. This approach allowed to confirm the important role of inflammation and oxidative stress in atherosclerosis development and moreover it has shown the considerable influence of the cigarette smoke.
Rocznik
Strony
211--228
Opis fizyczny
Bibliogr. 30 poz., rys., schem., tab.
Twórcy
  • Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
  • Department of Clinical Biochemistry and Laboratory Medicine, Poznan University of Medical Sciences, Grunwaldzka 6, 60-780 Poznan, Poland
  • Institute of Computing Science, Poznan University of Technology, Piotrowo str. 2, 60-965 Poznan and Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego str. 12/14, 61-704 Poznan, Poland
Bibliografia
  • [1] P. Baldan, N. Cocco, A. Marin and M. Simeoni: Petri nets for modelling metabolic pathways: a survey. Natural Compututing, 9(4), (2010), 955-989.
  • [2] E. Birben, U.M. Sahiner, C. Sackesen, S. Erzurum and O. Kalayci: Oxidative stress and antioxidant defense. World Allergy Organ J., 5(1), (2012), 9-19.
  • [3] K. Chmielewska, D. Formanowicz and P. Formanowicz: Modelowanie i analiza uszkodzeń środbłonka za pomoca sieci Petriego. In: A. Świerniak, J. Krystek (Eds.): Automatyzacja Procesów Dyskretnych. Teoria i Zastosowania, Vol. II, Wydawnictwo Pracowni Komputerowej Jacka Skalmierskiego, (2016), 41-56, (in Polish).
  • [4] T. Calinski and J. Harabasz: A dendrite method for cluster analysis. Communications in Statistics, 3(1), (1974), 1-27.
  • [5] R. David and H. Alla: Discrete, Continuous, and Hybrid Petri Nets. Springer Science & Business Media, 2005.
  • [6] J. Einloft, J. Ackermann, J. Nöthen and I. Koch: MonaLisa–visualization and analysis of functional modules in biochemical networks. Bioinformatics, 29(11), (2013), 1469-70.
  • [7] D. Formanowicz, A. Kozak, T. Głowacki, M. Radom and P. Formanowicz: Hemojuvelin - hepcidin axis modeled and analyzed using Petri nets. J. of Biomedical Informatics, 46(6), (2013), 1030-1043.
  • [8] D. Formanowicz, M. Radom, P. Zawierucha and P. Formanowicz: Petri net-based approach to modeling and analysis of selected aspects of the molecular regulation of angiogenesis. PLoS ONE, 12(3), (2017), e0173020.
  • [9] P. Formanowicz: On the border between biology, mathematics and computer science. BioTechnologia, 92(3), (2011), 217-220.
  • [10] J. Frostegård: Immunity, atherosclerosis and cardiovascular disease. BMC Medicine, 11(1), (2013), 117.
  • [11] D. Grassi, G. Desideri, L. Ferri, A. Aggio, S. Tiberti and C. Ferri: Oxidative stress and endothelial dysfunction: say NO to cigarette smoking. Current Pharmaceutical Design, 16(23), (2010), 2539-2550.
  • [12] E. Grafahrend-Belau, F. Schreiber, M. Heiner, A. Sackmann, B.H. Junker, S. Grunwald, A. Speer, K. Winder and I. Koch: Modularization of biochemical networks based on classification of Petri net t-invariants. BMC Bioinformatics, 9(90), (2008).
  • [13] M. Heiner, M. Herajy, F. Liu, C. Rohr and M. Schwarick: Snoopy - a unifying Petri net tool. Lecture Notes in Computer Science, 7347, (2012), 398-407.
  • [14] M. Heiner, M. Schwarick and J. Wegener: Charlie – an extensible Petri net analysis tool. In Proc. PETRI NETS 2015, Brussels, Springer, LNCS. 9115, (2015), 200-211.
  • [15] M. Kitami and M. K. Ali: Tobacco, metabolic and inflammatory pathways, and CVD risk. Global Heart, 7(2), (2012), 121-128.
  • [16] E. Klipp, W. Liebermeister, C. Wierling, A. Kowald, H. Lehrach and R. Herwig: Systems biology. A textbook. Wiley-VCH, Weinheim, 2009.
  • [17] L. Kaufman and P. J. Rousseeuw: Finding Groups in Data: An Introduction to Cluster Analysis. New York: John Wiley and Sons, 1990.
  • [18] I. Koch, W. Reisig and F. Schreiber: (Ed.) Modeling in systems biology. The Petri net approach. Springer, London, 2011.
  • [19] B. Messner and D. Bernhard: Smoking and cardiovascular disease: mechanisms of endothelial dysfunction and early atherogenesis. Arteriosclerosis, Thrombosis, and Vascular Biology, 34(3), (2014), 509-515.
  • [20] T. Murata: Petri nets: Properties, analysis and applications. Proc. of the IEEE, 77(4), (1989), 541-580.
  • [21] K. M. Naseem: The role of nitric oxide in cardiovascular diseases. Molecular Aspects of Medicine, 26(1-2), (2005), 33-65.
  • [22] C. A. Petri: Communication with Automata (in German). Schriften des Instituts fur Instrumentelle Mathematik, Bonn, 1962.
  • [23] S. Parthasarathy, A. Raghavamenon, M. O. Garelnab and N. Santanam: Oxidized low-density lipoprotein. Methods in Molecular Biology, 610 (2010), 403-417.
  • [24] W. Reising: Understanding Petri Nets. Modeling Techniques, Analysis Methods, Case Studies. Springer-Verlag, Berlin, Heidelberg, 2013.
  • [25] M. Rosselli, P. J. Keller and R. K. Dubey: Role of nitric oxide in the biology, physiology and pathophysiology of reproduction. Human Reproduction Update, 4(1), (1998), 3-24.
  • [26] P. J. Rousseeuw: Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. of Computational and Applied Mathematics, 20 (1987), 53-65.
  • [27] B. Sun, B. B. Boyanovsky, M. A. Connelly, P. Shridas, D. R. van der Westhuyzen and N. R. Webb: Distinct mechanisms for OxLDL uptake and cellular trafficking by class B scavenger receptors CD36 and SR-BI. J. of Lipid Research, 48(12), (2007), 2560-2570.
  • [28] A. Sackmann, M. Heiner and I. Koch: Application of Petri net based analysis techniques to signal transduction pathways. BMC Bioinformatics, 7(482), (2006).
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  • [30] V. M. Victor, M. Rocha, E. Solá, C. Bañuls, K. Garcia-Malpartida and A. Hernández-Mijares: Oxidative stress, endothelial dysfunction and atherosclerosis. Current Pharmaceutical Design, 15(26), (2009), 2988-3002.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-344657dd-91d2-4591-aaa1-da9cb735aa72
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