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Volume 17   Issue 2   Year 2022
References

  1. Macheras P., Iliadis A. In: Modeling in Biopharmaceutics, Pharmacokinetics and Pharmacodynamics: Homogeneous and Heterogeneous Approaches. Springer International Publishing, 2016. doi: 10.1007/978-3-319-27598-7
  2. Boas D.A., Jones S.R., Devor A., Huppert T.J., Dale A.M. A vascular anatomical network model of the spatio-temporal response to brain activation. NeuroImage. 2008;40(3):1116-1129. doi: 10.1016/j.neuroimage.2007.12.061
  3. Chung E.M., Hague J.P., Evans D.H. Revealing the mechanisms underlying embolic stroke using computational modelling. Phys. Med. Biol. 2007;52(23):7153-7166. doi: 10.1088/0031-9155/52/23/025
  4. Safaeian N., David T. A computational model of oxygen transport in the cerebrocapillary levels for normal and pathologic brain function. J. Cereb. Blood Flow Metab. 2013;33(10):1633-1641. doi: 10.1038/jcbfm.2013.119
  5. Secomb T.W., Bullock K.V., Boas D.A., Sakadzic S. The mass transfer coefficient for oxygen transport from blood to tissue in cerebral cortex. J. Cereb. Blood Flow Metab. 2020;40(8):1634-1646. doi: 10.1177/0271678X19870068
  6. Nartsissov Y.R. Application of a multicomponent model of convectional reaction-diffusion to description of glucose gradients in a neurovascular unit. Frontiers in Physiology. 2022;13:843473. doi: 10.3389/fphys.2022.843473
  7. Sharan M., Popel A.S. A compartmental model for oxygen transport in brain microcirculation in the presence of blood substitutes. J. Theor. Biol. 2002;216(4):479-500. doi: 10.1006/jtbi.2002.3001
  8. Fang Q., Sakadzic S., Ruvinskaya L., Devor A., Dale A.M., Boas D.A. Oxygen advection and diffusion in a three-dimensional vascular anatomical network. Opt. Express. 2008;16(22):17530-17541. doi: 10.1364/OE.16.017530
  9. Espinoza I., Peschke P., Karger C.P. A model to simulate the oxygen distribution in hypoxic tumors for different vascular architectures. Med. Phys. 2013;40(8):081703. doi: 10.1118/1.4812431
  10. Vendel E., Rottschafer V., de Lange E.C.M. The need for mathematical modelling of spatial drug distribution within the brain. Fluids Barriers CNS. 2019;16(1):12. doi: 10.1186/s12987-019-0133-x
  11. Sutalo I.D., Bui A.V., Liffman K., Manasseh R. Transport by pulsatile flow in a branching network of cerebral vasculature. WIT Transactions on Biomedicine and Health. 2013;17:13-24. doi: 10.2495/BIO130021
  12. Lehmpfuhl M.C., Hess A., Gaudnek M.A., Sibila M. Fluid dynamic simulation of rat brain vessels, geometrically reconstructed from MR-angiography and validated using phase contrast angiography. Phys. Med. 2011;27(3):169-176. doi: 10.1016/j.ejmp.2010.07.002
  13. Aoi M., Gremaud P., Tran H.T., Novak V., Olufsen M.S. Modeling cerebral blood flow and regulation. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2009;2009:5470-5473. doi: 10.1109/IEMBS.2009.5334057
  14. Cai Y., Zhang J., Wu J., Li Z.Y. Oxygen transport in a three-dimensional microvascular network incorporated with early tumour growth and preexisting vessel cooption: numerical simulation study. BioMed Res. Int. 2015;2015:476964. doi: 10.1155/2015/476964
  15. Beard D.A., Bassingthwaighte J.B. Advection and diffusion of substances in biological tissues with complex vascular networks. Ann. Biomed. Eng. 2000;28(3):253-268. doi: 10.1114/1.273
  16. Dokoumetzidis A., Macheras P. A model for transport and dispersion in the circulatory system based on the vascular fractal tree. Ann. Biomed. Eng. 2003;31(3):284-293. doi: 10.1114/1.1555627
  17. Coutey C., Berg M., Ho H., Hunter P. Computational simulation of blood flow and drug transportation in a large vasculature. In: Computational Biomechanics for Medicine. Springer, 2016. doi: 10.1007/978-3-319-28329-6_12
  18. Nartsissov Y.R. The Effect of Flux Dysconnectivity Functions on Concentration Gradients Changes in a Multicomponent Model of Convectional Reaction-Diffusion by the Example of a Neurovascular Unit. Defect and Diffusion Forum 413. 2021:19-28. doi: 10.4028/www.scientific.net/DDF.413.19
  19. Kopylova V.S., Boronovskii S.E., Nartsissov Ia.R. Molekulyarnaya Meditsina (Molecular medicine). 2019;17(5):47-52 (in Russ.). doi: 10.29296/24999490-2019-05-07
  20. Kopylova V.S., Boronovskiy S.E., Nartsissov Y.R. Application of fractal analysis to evaluate the rat brain arterial system. Biophysics. 2020;65(3):495-504. doi: 10.1134/S0006350920030100
  21. Kopylova V.S., Boronovskiy S.E., Nartsissov Y.R. Tree topology analysis of the arterial system model. Journal of Physics: Conference Series. 2018;1141:012027. doi: 10.1088/1742-6596/1141/1/012027
  22. Kopylova V.S., Boronovskiy S.E., Nartsissov Y.R. Fundamental constraints of vessels network architecture properties revealed by reconstruction of a rat brain vasculature. Math. Biosci. 2019;315:108237. doi: 10.1016/j.mbs.2019.108237
  23. Kopylova V.S., Boronovskiy S.E., Nartsissov Y.R. Multiparametric topological analysis of reconstructed rat brain arterial system. Phys. Biol. 2019;16(5):056002. doi: 10.1088/1478-3975/ab2704
  24. Nartsissov Ia. R., Tiukina E.S., Boronovskii S.E., Sheshegova E.V. Computer modeling of spatial-time distribution of metabolite concentrations in phantoms of biological objects by example of rat brain pial. Biophysics (Russian Federation). 2013;58:703-711. doi: 10.1134/S0006350913050102
  25. Nartsissov Ia.R., Boronovskii S.E., Kopylova V.S., Mashkovtseva E.V. Molekulyarnaya Meditsina (Molecular medicine). 2016;14(1):22-25 (in Russ.).
  26. Nartsissov Ia.R., Kopylova V.S., Mashkovtseva E.V., Boronovskii S.E. Molekulyarnaya Meditsina (Molecular medicine). 2018;16(3):37-41 (in Russ.). doi: 10.29296/24999490-2018-03-07
  27. Barber C.B., Dobkin D.P., Huhdanpaa H. The quickhull algorithm for convex hulls. ACM Trans. Math. Softw. 1996;22(4):469–483. doi: 10.1145/235815.235821
  28. Dienel G.A. Fueling and imaging brain activation. ASN Neuro. 2012;4(5):267-321. doi: 10.1042/AN20120021
  29. Soty M., Gautier-Stein A., Rajas F., Mithieux G. Gut-Brain Glucose Signaling in Energy Homeostasis. Cell Metab. 2017;25(6):1231-1242. doi: 10.1016/j.cmet.2017.04.032
  30. Heiss W.D., Rosner G. Functional recovery of cortical neurons as related to degree and duration of ischemia. Ann. Neurol. 1983;14(3):294-301. doi: 10.1002/ana.410140307
  31. Lee E.S., Bauer G.E., Caldwell M.P., Santilli S.M. Association of artery wall hypoxia and cellular proliferation at a vascular anastomosis. J. Surg. Res. 2000;91(1):32-37. doi: 10.1006/jsre.2000.5891
  32. Keeley T.P., Mann G.E. Defining Physiological Normoxia for Improved Translation of Cell Physiology to Animal Models and Humans. Physiol. Rev. 2019;99(1):161-234. doi: 10.1152/physrev.00041.2017
  33. Myung D., Derr K., Huie P., Noolandi J., Ta K.P., Ta C.N. Glucose permeability of human, bovine, and porcine corneas in vitro. Ophthalmic Res. 2006;38(3):158-163. doi: 10.1159/000090726
  34. Eggleton C.D., Vadapalli A., Roy T.K., Popel A.S. Calculations of intracapillary oxygen tension distributions in muscle. Mathematical Biosciences. 2000;167(2):123-143. doi: 10.1016/S0025-5564(00)00038-9
  35. Lucker A., Secomb T.W., Weber B., Jenny P. The relative influence of hematocrit and red blood cell velocity on oxygen transport from capillaries to tissue. Microcirculation. 2017;24(3). doi: 10.1111/micc.12337
  36. Hall C.N, Attwell D. Assessing the physiological concentration and targets of nitric oxide in brain tissue. J. Physiol. 2008;586(15):3597-615. doi: 10.1113/jphysiol.2008.154724
  37. De Feo P., Gallai V., Mazzotta G., Crispino G., Torlone E., Perriello G., Ventura M.M., Santeusanio F., Brunetti P., Bolli G.B. Modest decrements in plasma glucose concentration cause early impairment in cognitive function and later activation of glucose counterregulation in the absence of hypoglycemic symptoms in normal man. Journal of Clinical Investigation. 1988;82(2):436-444. doi: 10.1172/JCI113616
  38. Nartsissov Y.R. Validation of a spatial-time concentration gradients estimation by the superposition of sphere sources diffusion fields using the finite element method. Journal of Physics: Conference Series. 2021;2090(1):012007. doi: 10.1088/1742-6596/2090/1/01200
  39. Brown G.C. Regulation of mitochondrial respiration by nitric oxide inhibition of cytochrome c oxidase. Biochim. Biophys. Acta. 2001;1504(1):46-57. doi: 10.1016/S0005-2728(00)00238-3
  40. Secomb T.W., Hsu R., Beamer N.B., Coull B.M. Theoretical simulation of oxygen transport to brain by networks of microvessels: effects of oxygen supply and demand on tissue hypoxia. Microcirculation. 2000;7(4):237-247. doi: 10.1111/j.1549-8719.2000.tb00124.x
  41. Feng Z.C., Roberts E.L., Jr., Sick T.J., Rosenthal M. Depth profile of local oxygen tension and blood flow in rat cerebral cortex, white matter and hippocampus. Brain Res. 1988;445(2):280-288. doi: 10.1016/0006-8993(88)91190-0
  42. Gyngell M.L., Michaelis T., Horstermann D., Bruhn H., Hanicke W., Merboldt K.D., Frahm J. Cerebral glucose is detectable by localized proton NMR spectroscopy in normal rat brain in Vivo. Magn. Reson. Med. 1991;19(2):489-495. doi: 10.1002/mrm.1910190243
  43. Grinberg L., Anor T., Cheever E., Madsen J.R., Karniadakis G.E. Simulation of the human intracranial arterial tree. Philos. Trans. A Math. Phys. Eng. Sci. 2009;367(1896):2371-2386. doi: 10.1098/rsta.2008.0307
  44. Ndubuizu O., LaManna J.C. Brain tissue oxygen concentration measurements. Antioxid. Redox Signal. 2007;9(8):1207-1219. doi: 10.1089/ars.2007.1634
  45. Lyons D.G., Parpaleix A., Roche M., Charpak S. Mapping oxygen concentration in the awake mouse brain. Elife. 2016;5:12024 doi: 10.7554/eLife.12024
  46. Sick T.J., Lutz P.L., LaManna J.C., Rosenthal M. Comparative brain oxygenation and mitochondrial redox activity in turtles and rats. J. Appl. Physiol. Respir. Environ. Exerc. Physiol. 1982;53(6):1354-1359. doi: 10.1152/jappl.1982.53.6.1354
  47. Seyde W.C., Longnecker D.E. Cerebral oxygen tension in rats during deliberate hypotension with sodium nitroprusside, 2-chloroadenosine, or deep isoflurane anesthesia. Anesthesiology. 1986;64(4):480-485. doi: 10.1097/00000542-198604000-00011
  48. Secomb T.W. Krogh-cylinder and infinite-domain models for washout of an inert diffusible solute from tissue. Microcirculation. 2015;22(1):91-98. doi: 10.1111/micc.12180
  49. Boehm-Sturm P., Farr T.D., Adamczak J., Jikeli J.F., Mengler L., Wiedermann D., Kallur T., Kiselev V., Hoehn M. Vascular changes after stroke in the rat: a longitudinal study using optimized magnetic resonance imaging. Contrast Media Mol. Imaging. 2013;8(5):383-392. doi: 10.1002/cmmi.1534
  50. Kang M., Jin S., Lee D., Cho H. MRI Visualization of Whole Brain Macro- and Microvascular Remodeling in a Rat Model of Ischemic Stroke: A Pilot Study. Sci. Rep. 2020;10(1):4989. doi: 10.1038/s41598-020-61656-1
Table of Contents
Original Article
Kopylova V.S., Boronovskiy S.E., Nartsissov Ya.R. Estimation of Oxygen and Glucose Concentration Distribution in the Rat Brain Arterial System. Ìàthematical biology and bioinformatics. 2022;17(2):386-400. doi: 10.17537/2022.17.386
(published in Russian)

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