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@article{MBB_2018_13_2_a19, author = {I. E. Mysin and I. Yu. Popova and A. A. Osipov}, title = {The mathematical model of disturbance of energy metabolism in brain during development of neurodegenerative diseases: a proposed mechanism of cell death}, journal = {Matemati\v{c}eska\^a biologi\^a i bioinformatika}, pages = {591--608}, publisher = {mathdoc}, volume = {13}, number = {2}, year = {2018}, language = {ru}, url = {http://geodesic.mathdoc.fr/item/MBB_2018_13_2_a19/} }
TY - JOUR AU - I. E. Mysin AU - I. Yu. Popova AU - A. A. Osipov TI - The mathematical model of disturbance of energy metabolism in brain during development of neurodegenerative diseases: a proposed mechanism of cell death JO - Matematičeskaâ biologiâ i bioinformatika PY - 2018 SP - 591 EP - 608 VL - 13 IS - 2 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/MBB_2018_13_2_a19/ LA - ru ID - MBB_2018_13_2_a19 ER -
%0 Journal Article %A I. E. Mysin %A I. Yu. Popova %A A. A. Osipov %T The mathematical model of disturbance of energy metabolism in brain during development of neurodegenerative diseases: a proposed mechanism of cell death %J Matematičeskaâ biologiâ i bioinformatika %D 2018 %P 591-608 %V 13 %N 2 %I mathdoc %U http://geodesic.mathdoc.fr/item/MBB_2018_13_2_a19/ %G ru %F MBB_2018_13_2_a19
I. E. Mysin; I. Yu. Popova; A. A. Osipov. The mathematical model of disturbance of energy metabolism in brain during development of neurodegenerative diseases: a proposed mechanism of cell death. Matematičeskaâ biologiâ i bioinformatika, Tome 13 (2018) no. 2, pp. 591-608. http://geodesic.mathdoc.fr/item/MBB_2018_13_2_a19/
[1] A. P. Kudin, G. Zsurka, C. E. Elger, W. S. Kunz, “Mitochondrial involvement in temporal lobe epilepsy”, Exp. Neurol., 218:2 (2009), 326–332 | DOI
[2] S. Y. Jeon, D. Yi, M. S. Byun, H. J. Choi, H. J. Kim, J. H. Lee, H. Baek, Y. M. Choe, Y. Lee, J. I. Woo, D. Y. Lee, “Differential patterns of regional cerebral hypometabolism according to the level of cerebral amyloid deposition in patients with amnestic mild cognitive impairment”, Neurosci. Lett., 632 (2016), 104–108 | DOI
[3] J. W. Williamson, A. Pan, I. Cavus, H. P. Hetherington, H. Zaveri, O. A. Petroff, D. D. Spencer, “Neurometabolism in human epilepsy”, Epilepsia, 49:3 (2008), 31–41 | DOI
[4] Y. Zilberter, M. Zilberter, “The vicious circle of hypometabolism in neurodegenerative diseases: Ways and mechanisms of metabolic correction”, J. Neurosci. Res., 95:11 (2017), 2217–2235 | DOI
[5] H. Onodera, K. Iijima, K. Kogure, “Mononucleotide metabolism in the rat brain after transient ischemia”, J. Neurochem., 46:6 (1986), 1704–1710 | DOI
[6] M. Erecinska, I. A. Silver, “Ions and energy in mammalian brain”, Prog. Neurobiol., 43:1 (1994), 37–71 | DOI
[7] N. J. Gerkau, C. Rakers, G. C. Petzold, C. R. Rose, “Differential effects of energy deprivation on intracellular sodium homeostasis in neurons and astrocytes”, J. Neurosci. Res., 95:11 (2017), 2275–2285 | DOI
[8] L. B. Tovar-y-Romo, A. Penagos-Puig, J. O. Ramirez-Jarquin, “Endogenous recovery after brain damage: molecular mechanisms that balance neuronal life/death fate”, J. Neurochem., 136:1 (2016), 13–27 | DOI
[9] N. M. C. Connolly, B. D'Orsi, N. Monsefi, H. J. Huber, J. H. Prehn, “Computational analysis of AMPK-mediated neuroprotection suggests acute excitotoxic bioenergetics and glucose dynamics are regulated by a minimal set of critical reactions”, PLoS ONE, 11:2 (2016), e0148326 | DOI
[10] N. M. C. Connolly, J. H. M. Prehn, “The metabolic response to excitotoxicity — lessons from single-cell imaging”, J. Bioenerg. Biomembr., 47:1–2 (2015), 75–88 | DOI
[11] R. Jolivet, J. S. Coggan, I. Allaman, P. J. Magistretti, “Multi-timescale modeling of activity-dependent metabolic coupling in the neuron-glia-vasculature ensemble”, PLoS Comput. Biol., 11:2 (2015), e1004036 | DOI
[12] A. Aubert, R. Costalat, “Interaction between astrocytes and neurons studied using a mathematical model of compartmentalized energy metabolism”, J. Cereb. Blood Flow Metab., 25:11 (2005), 1476–1490 | DOI
[13] B. S. Chander, V. S. Chakravarthy, “A computational model of neuro-glio-vascular loop interactions”, PLoS ONE, 7:11 (2012), e48802 | DOI
[14] R. Heinrich, S. Schuster, The regulation of cellular systems, Springer US, Boston, MA, 1996, 291 pp.
[15] A. Aubert, R. Costalat, R. Valabregue, “Modelling of the coupling between brain electrical activity and metabolism”, Acta Biotheor., 49:4 (2001), 301–326 | DOI
[16] A. Aubert, R. Costalat, “A model of the coupling between brain electrical activity, metabolism, and hemodynamics: application to the interpretation of functional neuroimaging”, Neuroimage, 17:3 (2002), 1162–1181 | DOI | MR
[17] L. Petzold, “Automatic selection of methods for solving stiff and nonstiff systems of ordinary differential equations”, SIAM J. Sci. and Stat. Comput., 4:1 (1983), 136–148 | DOI | MR | Zbl
[18] A. C. Hindmarsh, “ODEPACK, A Systematized Collection of ODE Solvers”, IMACS Transactions on Scientific Computation, 1 (1983), 55–64 | MR
[19] N. M. C. Connolly, H. Dussmann, U. Anilkumar, H. J. Huber, J. H. Prehn, “Single-cell imaging of bioenergetic responses to neuronal excitotoxicity and oxygen and glucose deprivation”, J. Neurosci., 34:31 (2014), 10192–10205 | DOI
[20] K. A. Kasischke, H. D. Vishwasrao, P. J. Fisher, W. R. Zipfel, W. W. Webb, “Neural activity triggers neuronal oxidative metabolism followed by astrocytic glycolysis”, Science, 305:5680 (2004), 99–103 | DOI
[21] E. Samokhina, I. Popova, A. Malkov, A. I. Ivanov, D. Papadia, A. Osypov, M. Molchanov, S. Paskevich, A. Fisahn, M. Zilberter, Y. Zilberter, “Chronic inhibition of brain glycolysis initiates epileptogenesis”, J. Neurosci. Res., 95:11 (2017), 2195–2206 | DOI
[22] T. G. Bidder, “Hexose translocation across the blood-brain interface: configurational aspects”, J. Neurochem., 15:8 (1968), 867–874 | DOI
[23] H. S. Bachelard, A. G. Clark, M. F. Thompson, “Cerebral-cortex hexokinase”, Elucidation of reaction mechanisms by substrate and dead-end inhibitor kinetic analysis. Biochem. J., 123:5 (1971), 707–715
[24] W. H. Oldendorf, “Brain uptake of radiolabeled amino acids, amines, and hexoses after arterial injection”, Am. J. Physiol., 221:6 (1971), 1629–1639 | DOI
[25] R. K. Crane, A. Sols, “The non-competitive inhibition of brain hexokinase by glucose-6-phosphate and related compounds”, J. Biol. Chem., 210:2 (1954), 597–606
[26] A. N. Wick, D. R. Drury, T. N. Morita, “2-Deoxyglucose; a metabolic block for glucose”, Proc. Soc. Exp. Biol. Med., 89:4 (1955), 579–582 | DOI
[27] J. Brown, “Effects of 2-deoxyglucose on carbohydrate metablism: review of the literature and studies in the rat”, Metab. Clin. Exp., 11 (1962), 1098–1112
[28] C. E. Stafstrom, A. Roopra, T. P. Sutula, “Seizure suppression via glycolysis inhibition with 2-deoxy-D-glucose (2DG)”, Epilepsia, 49:8, Suppl. (2008), 97–100 | DOI
[29] E. Samokhina, A. Malkov, A. Samokhin, I. Popova, Selective hippocampal cell damage and mossy fiber sprouting induced by chronic impairment of cerebral glucose metabolism, in press
[30] A. Malkov, A. I. Ivanov, S. Buldakova, T. Waseem, I. Popova, M. Zilberter, Y. Zilberter, “Seizure-induced reduction in glucose utilization promotes brain hypometabolism during epileptogenesis”, Neurobiol. Dis., 116 (2018), 28–38 | DOI
[31] G. Oz, M. DiNuzzo, A. Kumar, A. Moheet, E. R. Seaquist, “Revisiting glycogen content in the human brain”, Neurochem. Res., 40:12 (2015), 2473–2481 | DOI
[32] J. Langer, N. J. Gerkau, A. Derouiche, C. Kleinhans, B. Moshrefi-Ravasdjani, M. Fredrich, K. W. Kafitz, G. Seifert, C. Steinhauser, C. R. Rose, “Rapid sodium signaling couples glutamate uptake to breakdown of ATP in perivascular astrocyte endfeet”, Glia, 65:2 (2017), 293–308 | DOI
[33] T. Shinotsuka, M. Yasui, M. Nuriya, “Astrocytic gap junctional networks suppress cellular damage in an in vitro model of ischemia”, Biochem. Biophys. Res. Commun., 444:2 (2014), 171–176 | DOI
[34] J. Fan, T. M. Dawson, V. L. Dawson, “Cell death mechanisms of neurodegeneration”, Adv. Neurobiol., 15 (2017), 403–425 | DOI