Low-frequency Oscillations of Functional Indicators of the Body

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

A number of our studies have shown that low-frequency (LF) oscillations in the functional parameters of the oxygen transport system are stable and synchronized with one another. The literature presents a large number of examples of LF oscillations in various functional parameters that are directly or indirectly related to energy metabolism. In parallel, artificially induced damped and constant spontaneous oscillations related to energy produced by the mitochondria over a range of LF frequencies have been studied for more than 40 years. A parameter study is therefore needed to find the connection between the oscillation amplitudes and the physical characteristics both of the oxygen transport system and mitochondria that operate on common LF range (0.003–0.03 Hz). We believe the nature of all these oscillation amplitudes to be affected by the periodic dynamics of energy dissipation in mitochondria that form an interconnected network. The process of creating these oscillations occurs in two phases. In the 1st phase, the amount of Са2+ entering the mitochondria exceeds the amount of Са2+ released by mitochondria thereby promoting an increase in oxidative phosphorylation efficiency. In the 2nd phase, Са2+ efflux from mitochondria prevails over Са2+ influx and is accompanied by inhibition of oxidative phosphorylation. The oscillations remain stable and spontaneous and arise from an “autocatalytic” interaction based on feedback mechanisms. The inertia of the processes of a full cycle (1st and 2nd phases) that lasts 1–3 minutes may be due to the capacity of the phosphate buffer of mitochondria. The structural basis for synchronizing oscillations at the tissue level may be mitochondrial networks of excitable tissues. Synchronization at the organism level between mitochondrial oscillations and fluctuations in parameters associated with energy metabolism can be achieved through a system of tunnel nanotubes.

About the authors

O. V Grishin

Novosibirsk State Medical University; Novosibirsk State University

Krasny prosp. 52, Novosibirsk, 630091 Russia; ul. Pirogova 2, Novosibirsk, 630090, Russia

V. G Grishin

Federal Research Center for Information and Computational Technologies

Email: victor.grishin.nsk@gmail.com
prosp. Akademika Lavrentieva 6, Novosibirsk, 630090, Russia

References

  1. Treacher D. F. and Leach R. M., Oxygen transport-1. Basic principles. BMJ, 317 (7168), 1302–1306 (1998). doi: 10.1136/bmj.317.7168.1302
  2. Бреслав И. С. и Ноздрачев А. Д., Регуляция дыхании: висцеральная и поведенческая составляющие. Успехи физиол. наук, 38 (2), 26–45 (2007).
  3. Стандарты ОС и Э. Вариабельность сердечного ритма (1999).
  4. Iotti S., Borsari M., and Bendahan D., Oscillations inenergy metabolism, Biochim. Biophys. Acta, 1797 (8), 1353–1361 (2010). doi: 10.1016/j.bbabio.2010.02.019
  5. Серов Д. А., Танканаг А. В. и Асташев М. Е., Синхронизация низкочастотных колебаний [Ca2+] в культивируемых эндотелиоцитах мыши, в сб. статей Междунар. конф. «Рецепторы и внутриклеточная сигнализация» (2021), сс. 250–258.
  6. Гришин В. Г., Гришин О. В., Гультяева В. В., Зинченко М. И. и Урюмцев Д. Ю., Низкочастотные колебания показателей системы транспорта кислорода у человека в покое. Российский физиол. журн. им. И.М. Сеченова, 105 (9), 1154–1162 (2019).
  7. Гришин О. В., Гришин В. Г. и Коваленко Ю. В.,Вариабельность легочного газообмена и дыхательного ритма. Физиология человека, 38 (2), 87–93 (2012).
  8. Сагулова З. Ш., Тлеулова М. Б. и Ташенов К. Т.,Особенности изменения биоритмов температуры тела крыс в онтогенезе. Сер. биологическая и медицинская, № 2, 109–112 (2014).
  9. Sel’kov E. E., Stabilization of Energy Charge, Generation of Oscillations and Multiple Steady States in Energy Metabolism as a Result of Purely Stoichiometric Regulation. Eur. J. Biochem., 59, 151–157 (1975).
  10. Chance B. and Yoshioka T., Sustained oscillations of ionic constituents of mitochondria. Arch. Biochem. Biophys., 117, 451–465 (1966).
  11. Saks V. A., Kaambre T., Sikk P., Eimre M., Orlova E., Paju K., Piirsoo A., Appaix F., Kay L., Regitz-Zagrosek V., Fleck E., and Seppet E., Intracellular energetic units in red muscle cells. Biochem. J., 356, 643–657 (2001).
  12. Skulachev V. P., Mitochondrial filaments and clusters as intracellular power-transmitting cables. Trends Biochem Sci., 26 (1), 23–29 (2001). doi: 10.1016/s09680004(00)01735-7
  13. Aon M. A, Cortassa S., and O'Rourke B., The fundamental organization of cardiac mitochondria as a network of coupled oscillators. Biophys J., 91 (11), 4317– 4327 (2006). doi: 10.1529/biophysj.106.087817
  14. Scholkmann F., Long range physical cell-to-cell signalling via mitochondria inside membrane nano tubes: a hypothesis. Theor. Biol. Med. Model., 13 (1), 16 (2016). doi: 10.1186/s12976-016-0042-5
  15. Huikuri H. V, Perkiömäki J. S, Maestri R., and Pinna G. D. P., Clinical impact of evaluation of cardiovascular control by novel methods of heart rate dynamics. Philos. Trans. Roy. Soc. A.P. Math., Phys. Eng. Sci., 367, 1223–1238 (2009).
  16. Voss A., Schulz S., Schroeder R., Baumert M., andCaminal P. P., Methods derived from njnlinear dynamics for analysing heart rate variability. Philos. Trans. A. Math. Phys. Eng. Sci., 367, 277–296 (2009).
  17. Aletti F., Bassani T., Lucini D., Pagani M., and Baselli G. P., Multivariate decomposition of arterial blood pressure variability for the assessment of arterial control of circulation. IEEE Trans. Biomed. Eng., 56, 1781–1790 (2009).
  18. Migeotte P. F. and Verbandt Y. P., A novel algorithm forthe heart rate variability analysis of short-term recordings: polar representation of respiratory sinus arrhythmia. Comput. Biomed. Res., 32, 56–66 (1999).
  19. Colombo J., Shoemaker W. C., Belzberg H., Hatzakis G., Fathizadeh P., and Demetriades D. P., Noninvasive monitoring of the autonomic nervous system and hemodynamics of patients with blunt and penetrating trauma. J. Trauma, 65, 1364–1373 (2008).
  20. Nozawa M., Yana K., Kaeriyama K., Mizuta H., and Ono T. P., Spontaneous variability analysis for characterizing cardiovascular responses to water ingestion. Conf. Proc. IEEE Eng. Med. Biol. Soc., 2009, 1816–1819 (2009).
  21. Javed F., Middleton P. M, Malouf P., Chan G. S. H.,Savkin A. V, Lovell N. H, Steel E., and Mackie J. P., Frequency spectrum analysis of finger photoplethysmographic waveform variability during haemodialysis. Physiol. Meas., 31, 1203–1216 (2010).
  22. Jurysta F., Lanquart J.-P., Sputaels V., Dumont M.,Migeotte P.-F., Leistedt S., Linkowski P., and van de Borne P. P., The impact of chronic primary insomnia on the heart rate-EEG variability link. Clin. Neurophysiol., 120, 1054–1060 (2009).
  23. Mendonca G. V., Fernhall B., Heffernan K. S., and Pereira F. D. P., Spectral methods of heart rate variability analysis during dynamic exercise. Clin. Auton Res., 19, 237–245 (2009).
  24. Liu C., Liu C., Li L., Zhang Q., and Li B. P., Systolicand Diastolic Time Interval Variability Analysis and Their Relations with Heart Rate Variability. In: 3rd Int. Conf. on Bioinformatics and Biomedical Engineering (ICBBE, 2009), 1–4.
  25. Valencia J. F., Vallverdú M., Schroeder R., Voss A., Vázquez R., Bayés de Luna A., and Caminal P. P. Complexity of the short-term heart-rate variability. IEEE Eng. Med. Biol. Mag., 28, 72–78 (2009).
  26. Sadiq I. and Khan S. A. P. Fuzzification of the Analysisof Heart Rate Variability Using ECG in Time, Frequency and Statistical Domains. In: Int. Conf. on Computer Engineering and Applications (Los Alamitos, CA, USA. IEEE Computer Society, 2010), V. 1, P. 481–485.
  27. Laguna P., Moody G. B, and Mark R. G. P. Powerspectral density of unevenly sampled data by leastsquare analysis. P. performance and application to heart rate signals. IEEE Trans. Biomed. Eng., 45, 698– 715 (1998).
  28. Muthuraman M., Galka A., Deuschl G., Heute U.,and Raethjen J. P. Dynamical correlation of non-stationary signals in time domain – A comparative study. Biomed. Signal Processing and Control, 5, 205–213 (2010).
  29. Mitra P. P. and Pesaran B. P. Analysis of DynamicBrain Imaging Data. Biophys. J., 76, 691–708 (1999).
  30. Martinmaki K., Rusko H., Saalasti S., and Kettunen J. P.Ability of short-time Fourier transform method to detect transient changes in vagal effects on hearts.P. a pharmacological blocking study. Am. J. Physiol. Heart Circ. Physiol., 290, H2582–2589 (2006).
  31. Shafqat K., Pal S. K., Kumari S., and Kyriacou P. A. P.Time-frequency analysis of HRV data from locally anesthetized patients. Conf. Proc. IEEE Eng. Med. Biol. Soc., 2009, 1824–1827 (2009).
  32. Ivanov P. C., Rosenblum M. G., Peng C. K., Mietus J.,Havlin S., Stanley H. E., and Goldberger A. L. P. Scaling behaviour of heartbeat intervals obtained by wavelet-based time-series analysis. Nature, 383, 323–327 (1996).
  33. Torrence C. and Compo G. P. A practical guide towavelet analysis. Bull. Am. Meteorolog. Soc., 79, 61–78 (1998).
  34. Fernández J. R., Hermida R. C., and Mojón A. P.Chronobiological analysis techniques. Application to blood pressure. Philos. Transact. A. Math. Phys. Eng. Sci., 367, 431–445 (2009).
  35. Goya-Esteban R., Mora-Jiménez I., RojoÁlvarez J. L., Barquero-Pérez O., Pastor-Pérez F., Manzano-Martínez S., Pascual-Figal D., and GarcíaAlberola A. P. Heart Rate Variability on 7-Day Holter Monitoring Using a Bootstrap Rhythmometric Procedure. IEEE Trans. Biomed. Eng., 57, 1366–1376 (2010).
  36. Митиш М. Д., Сюткина Е. В., Яцык Г. В. и Брязгунов И. П. Мониторирование артериального давления у детей с психосоматической патологией (сообщение II. Ритмометрический анализ 48-часовых профилей показателей артериального давления). Вопр. соврем. педиатрии, 3 (5), 36–41 (2004).
  37. Липатов И. С. Оценка церебральной гемодинамики плода при плацентарной недостаточности с учетом его суточного биоритмостаза. Рос. вестн. акушера-гинеколога, 15 (4), 42–48 (2015). doi: 10.17116/rosakush201515442-48
  38. Rangayyan R. M. and Wu Y. P. Analysis of vibroarthrographic signals with features related to signal variability and radialbasis functions. Ann. Biomed. Eng., 37, 156– 163 (2009).
  39. Wu Y. and Krishnan S. Computer-aided analysis of gaitrhythm fluctuations in amyotrophic lateral sclerosis. Med. Biol. Eng. Comput., 47, 1165–1171 (2009).
  40. Agarwal R., Gotman J., Flanagan D., and Rosenblatt B. P. Automatic EEG analysis during longterm monitoring in the ICU. Electroencephalography and Clinical Neurophysiology, 107, 44–58 (1998).
  41. Ruffo M., Cesarelli M., Romano M., Bifulco P., andFratini A. P. An algorithm for FHR estimation from foetal phonocardiographic signals. Biomedical Signal Processing and Control, 5, 131–141 (2010).
  42. Gamero L. G., Vila J., and Palacios F., Wavelet transform analysis of heart rate variability during myocardial ischaemia. Med. Biol. Eng. Comput., 40, 72–78 (2002).
  43. Gang Y. and Malik M. P. Heart Rate Variability. Measurements and Risk Stratification. In: Electrical Diseases of the Heart (2008), pp. 365–378. doi: 10.1007/9781-84628-854-8_25
  44. Patangay A., Zhang Y., and Lewicke A. P. Measures of cardiac contractility variability during ischemia. Conf. Proc. IEEE Eng. Med. Biol. Soc., 2009, 4198–4201 (2009).
  45. Goodman L. Oscillatory Behavior of Ventilation in Resting Man. IEEE Trans. Biomed. Eng. (Volume: BME-11, Issue 3, 1964), pp. 1–12.
  46. Hlastala P., Wranne B., and Lenfant C. J. Cyclical variations in FRC and other respiratory variables in resting man. J. Appl. Physiol., 34 (5), 670–676 (1973).
  47. Modarreszadeh M. Systems analysis of breath-to-breath ventilatory variations in man: role of co2 feedback (diss. DDP, Case Western Reserve University, 1991), p. 194.
  48. Van den Aardweg J. G. and Karemaker J. M. Influence of chemoreflexes on respiratory variability in healthy subjects. Am. J. Respir. Crit. Care Med., 165 (8), 1041–1047 (2002).
  49. Yamashiro S. M., Kato T., and Matsumoto T. Altered chemosensitivity to CO2 during exercise. Physiol. Rep. 9 (11), e14882 (2021). doi: 10.14814/phy2.14882
  50. Гришин В. Г., Гришин О. В., Никульцев В. С.,Гультяева В. В., Зинченко М. И. и Урюмцев Д. Ю. Частотно-временной анализ колебаний показателей внешнего дыхания и сердечного ритма человека при физической нагрузке. Биофизика, 67 (4), 755–762 (2022). doi: 10.31857/S0006302922040147
  51. Ramirez J. M. and Baertsch N. A. The Dynamic Basis of Respiratory Rhythm Generation: One Breath at a Time. Annu. Rev. Neurosci., 41, 475–499 (2018). doi: 10.1146/annurev-neuro-080317-061756
  52. Iberall A. S. Human body as an inconstant heat sourceandits relations to clothes insulation. Part 2 − Experimental Investigation Into Dynamics of the Source. J. Fluids Eng., 82 (1), 96–102 (1960). doi: 10.1115/1.3662562 (P1), doi: 10.1115/1.3662494 (P2)
  53. Сагайдачный А. А. Методы тепловизионного анализа пространственно-временной динамики температуры тела человека и их использование в диагностике. Автореферат дисс. … канд. физ.-мат. наук (Саратовский гос. ун-т им. Н.Г. Чернышевского, Саратов, 2010).
  54. Papaioanno V. E., Chouvarda I. G., Maglaveras N. K.,and Pneumatikos I. A. Temperature variability analysis using wavelets and multiscale entropy in patients with systemic inflammatory response syndrome, sepsis, and septic shock. Crit. Care, 16, R51, (2012). http://ccforum.com/content/16/2/R51
  55. Tikhonova I. V., Tankanag A. V., and Chemeris N. K.Time-amplitude analysis of skin blood flow oscillations during the post-occlusive reactive hyperemia in human. Microvasc. Res., 80 (1), 58–64 (2010). doi: 10.1016/j.mvr.2010.03.010
  56. Kvandal P., Landsverk S. A., Bernjak A., Stefanovska A., Kvernmo H. D., and Kirkebøen K. A. Low-frequency oscillations of the laser Doppler perfusion signal in human skin. Microvasc. Res., 72 (3), 120– 127 (2006). doi: 10.1016/j.mvr.2006.05.006
  57. Kvernmo H. D., Stefanovska A., Kirkeboen K. A., and Kvernebo K. Oscillations in the human cutaneous blood perfusion signal modified by endothelium-dependent and endothelium-independent vasodilators. Microvasc. Res. 57 (3), 298–309 (1999). doi: 10.1006/mvre.1998.2139
  58. Yano T., Lian C. S., Arimitsu T., Yamanaka R.,Afroundeh R., Shirakawa K., and Yunoki T. Oscillation of oxygenation in skeletal muscle at rest and in light exercise. Acta Physiol. Hung., 100 (3), 312–320 (2013). doi: 10.1556/APhysiol.100.2013.007
  59. Yano T., Lian C. S., Afroundeh R., Shirakawa K., and Yunoki T. Comparison of oscillations of skin blood flow and deoxygenation in vastus lateralis in light exercise. Biol. Sport., 31 (1), 15–20 (2014). doi: 10.5604/20831862.1083274
  60. Söderström T, Stefanovska A., Veber M., and Svensson H. Involvement of sympathetic nerve activity in skin blood flow oscillations in humans. Am. J. Physiol. Heart Circ. Physiol., 284 (5), H1638–H1646 (2003). doi: 10.1152/ajpheart.00826.2000
  61. Aon M. A., Cortassa S., and O'Rourke B. Mitochondrial oscillations in physiology and pathophysiology. Adv. Exp. Med. Biol., 641, 98–117 (2008). doi: 10.1007/978-0-387-09794-7_8
  62. Woods N.M., Cuthbertson K.S. R., and Cobbold P. H. Repetitive transient rises in cytoplasmic free calcium in hormone-stimulated hepatocytes. Nature, 319, 600–602 (1986).
  63. Jacob R. Calcium oscillations in endothelial cells. Cell Calcium, 12 (2–3), 127–134 (1991). doi: 10.1016/0143-4160(91)90014-6
  64. Prentki M., Glennon M., Thomas A. P., Morris R. L.,Matschinsky F. M., and Corkey B. E. Cell-specific patterns of oscillating free Ca2+ in carbamylcholine-stimulated insulinoma cells. J. Biol. Chem., 263 (23), 11044–11047 (1988).
  65. Rooney T. A., Sass E. J., and Thomas A. P. Characterization of cytosolic calcium oscillations induced by phenylephrine and vasopressin in single fura-2-loaded hepatocytes. J. Biol. Chem., 264 (29), 17131–17141 (1989).
  66. Cornell-Bell A. H., Finkbeiner S. M., Cooper M. S.,and Smith S. J. Glutamate induces calcium waves in cultured astrocytes: long-range glial signaling. Science, 247 (4941), 470–473 (1990). doi: 10.1126/science.1967852
  67. Berridge M. J. Calcium oscillations. J. Biol. Chem., 265 (17), 9583–9586 (1990). https://www.jbc.org/ article/S0021-9258(19)38704-6/pdf
  68. Jacob R., Merritt J. E., Hallam T. J., and Rink T. J. Repetitive spikes in cytoplasmic calcium evoked by histamine in human endothelial cells. Nature, 335 (6185), 40–45 (1988). doi: 10.1038/335040a0
  69. Romashko D. N., Marban E., and O’Rourke B. Subcellular metabolic transients and mitochondrial redox waves in heart cells. Proc. Natl. Acad. Sci. USA, 95 (4), 1618–1623 (1998). doi: 10.1073/pnas.95.4.1618
  70. Панов А. В. и Жолобак Н. М. Функциональная биоэнергетика и механизмы старения организма человека, под ред. С. И. Колесникова (ГЭОТАР-Медиа, М., 2023). doi: 10.33029/9704-7524-9-BIO-2023-13722020)
  71. Yokota Y., Nakajima H., Wakayama Y., Muto A.,Kawakami K., Fukuhara S., Mochizuki N. Endothelial Ca2+ oscillations reflect VEGFR signaling-regulated angiogenic capacity in vivo. Elife, 4, e08817 (2015). doi: 10.7554/eLife.08817
  72. Серов Д. А. Осцилляции [Ca2+]i и [NO]i в эндотелиоцитах как источник низкочастотных колебаний кожной микроциркуляции. Автореферат дисс. … канд. биол. наук (ИБК РАН, Пущино, 2022).
  73. Feissner R. F., Skalska J., Gaum W. E., and Sheu Sh.Sh., Crosstalk signaling between mitochondrial Ca2+ and ROS. Front. Biosci., 14, 1197–1218 (2009). doi: 10.2741/3303
  74. Glancy B., Willis W. T., Chess D. J., and Balaban R. S.,Effect of Calcium on the Oxidative Phosphorylation Cascade in Skeletal Muscle Mitochondria. Biochemistry, 52, 16, 2793–2809 (2013). doi: 10.1021/bi3015983
  75. Yan Y., Wei C. L., Zhang W. R., Cheng H. P., and Liu J.Cross-talk between calcium and reactive oxygen species signaling. Acta Pharmacol Sin., 27 (7), 821–826 (2006).
  76. Lu X., Ginsburg K. S., Kettlewell S., Bossuyt J.,Smith G. L., and Bers D. M. Measuring local gradients of intramitochondrial [Ca2+] in cardiac myocytes during sarcoplasmic reticulum Ca2+ release. Circ. Res., 112, 424–431 (2013). doi: 10.1161/CIRCRESAHA.111.300501
  77. Mironov S. L. and Richter D. W. Oscillations and hypoxic changes of mitochondrial variables in neurons of the brainstem respiratory centre of mice. J. Physiol., 533 (Pt 1), 227–236 (2001). doi: 10.1111/j.14697793.2001.0227b.x
  78. Зацепин Е. Н. и Дробот С. В. Модель метаболических механизмов аккумуляции кальция в митохондриях живой клетки, Докл. БГУИР, № 7 (117), 148–150 (2018).
  79. Kostic M., Katoshevski T., and Sekler I., Allosteric regulation of NCLX by mitochondrial membrane potential links the metabolic state and Ca2+ signaling in mitochondria, Cell Rep., 25, 3465–3475, (2018). doi: 10.1016/j.celrep.2018.11.084
  80. Pfeiffer D. R., Gunter T. E., Eliseev R., Broekemeier K. M., and Gunter K. K. Release of Ca2+ from mitochondria via the saturable mechanisms and the permeability transition. IUBMB Life, 52 (3–5), 205–212 (2001).
  81. Takeuchi A., Kim B., and Matsuoka S. The mitochondrial Na+-Ca2+ exchanger, NCLX, regulates automaticity of HL-1 cardiomyocytes. Sci. Rep., 3, 2766 (2013). doi: 10.1038/srep02766
  82. Belosludtseva N. V., Pavlik L. L., Belosludtsev K. N.,Saris N. L., Shigaeva M. I., and Mironova G. D. The Short-Term Opening of Cyclosporin A-Independent Palmitate/Sr2+-Induced Pore Can Underlie Ion Efflux in the Oscillatory Mode of Functioning of Rat Liver Mitochondria. Membranes (Basel), 12 (7), 667 (2022). doi: 10.3390/membranes12070667
  83. Zoratti M. and Szabò I. The mitochondrial permeability transition. Biochim. Biophys. Acta, 1241 (2), 139–176 (1995). doi: 10.1016/0304-4157(95)00003-a
  84. Weibel E. R. and Hoppeler H. Exercise-induced maximal metabolic rate scales with muscle aerobic capacity. J. Exp. Biol., 208, 1635–1644 (2005).
  85. Magnus G. and Keizer J. Model of beta-cell mitochondrial calcium handling and electrical activity. II. Mitochondrial variables. Am. J. Physiol., 274 (4), C1174–C1184 (1998). doi: 10.1152/ajpcell.1998.274.4.C1174
  86. Perez-Campo R., Lopez-Torres M., Cadenas S.,Rojas C., and Barja G. The rate of free radical production as a determinant of the rate of aging: evidence from the comparative approach. J. Comp. Physiol. (B), 168 (3), 149–158 (1998).
  87. Gunter T. E., Gunter K. K., Sheu S. S., and Gavin C. E.Mitochondrial calcium transport: physiological and pathological relevance. Am. J. Physiol., 267 (2, Pt 1), C313–C339 (1994). doi: 10.1152/ajpcell.1994.267.2.C313
  88. Evtodienko Y. V., Teplova V., Khawaja J., and Saris N. E.The Ca(2+)-induced permeability transition pore is involved in Ca(2+)-induced mitochondrial oscillations. A study on permeabilised Ehrlich ascites tumour cells. Cell Calcium, 15 (2), 143–152 (1994). doi: 10.1016/0143-4160(94)90053-1
  89. Selivanov V. A., Ichas F., Holmuhamedov E. L., Jouaville L. S., Evtodienko I. V., and Mazat J. P. A model of mitochondrial Ca(2+)-induced Ca2+ release simulating the Ca2+ oscillations and spikes generated by mitochondria. Biophys. Chem., 72 (1–2), 111–121 (1998). doi: 10.1016/s0301-4622(98)00127-6
  90. Cortassa S., Aon M. A., Winslow R. L., andO’Rourke B. A mitochondrial oscillator dependent on reactive oxygen species. Biophys. J., 87 (3), 2060–2073 (2004). doi: 10.1529/biophysj.104.041749 91. Dupont G., Combettes L., Bird G. S., and Putney J. W. Calcium oscillations. Cold Spring Harb. Perspect. Biol., 3 (3), a004226 (2011). doi: 10.1101/cshperspect.a004226
  91. Finch E. A., Turner T. J., and Goldin S. M. Calcium asa coagonist of inositol 1,4,5-trisphosphate-induced calcium release. Science, 252 (5004), 443–446 (1991). doi: 10.1126/science.2017683
  92. Patel A., Simkulet M., Maity S., Venkatesan M., Matzavinos A., Madesh M., and Alevriadou B. R. The mitochondrial Ca2+ uniporter channel synergizes with fluid shear stress to induce mitochondrial Ca2+ oscillations. Sci. Rep., 12 (1), 21161 (2022). doi: 10.1038/s41598-022-25583-7
  93. Katoshevski T., Ben-Kasus Nissim T, and Sekler I. Recent studies on NCLX in health and diseases. Cell Calcium, 94, 102345 (2021). doi: 10.1016/j.ceca.2020.102345
  94. Zamponi N., Zamponi E., Cannas S. A., Billoni O. V.,Helguera P. R., and Chialvo D. R. Mitochondrial network complexity emerges from fission/fusion dynamics. Sci. Rep., 8 (1), 363 (2018). doi: 10.1038/s41598017-18351-5
  95. Kurz F. T., Derungs T., Aon M. A., O’Rourke B., and Armoundas A. A. Mitochondrial networks in cardiac myocytes reveal dynamic coupling behavior. Biophys J. 108 (8),1922–1933 (2015). doi: 10.1016/j.bpj. 2015.01.040
  96. Aon M. A., Cortassa S., Marban E., and O'Rourke B.Synchronized whole cell oscillations in mitochondrial metabolism triggered by a local release of reactive oxygen species in cardiac myocytes. J. Biol. Chem., 278 (45), 44735–44744 (2003).
  97. Заводник И. Б. Митохондрии, кальциевый гомеостаз и кальциевая сигнализация, Биомедицинская химия, 62 (3), 311–317 (2016).
  98. Kurz F. T., Derungs T., Aon M. A., O’Rourke B., andArmoundas A. A. Mitochondrial networks in cardiac myocytes reveal dynamic coupling behavior. Biophys.J., 108 (8), 1922–1933 (2015). DOI: 10.1016/ j.bpj.2015.01.040
  99. Aon M. A., Cortassa S., and O'Rourke B. The fundamental organization of cardiac mitochondria as a network of coupled oscillators. Biophys. J., 91, 4317–4327 (2006).
  100. Glancy B., Hartnell L. M., Malide D., Yu. Z. X.,Combs C. A., and Connelly P. S. Mitochondrial reticulum for cellular energy distribution in muscle. Nature, 523 (7562), 617–620 (2015). doi: 10.1038/nature14614
  101. Rustom A., Saffrich R., Markovic I., Walther P., andGerdes H. H. Nanotubular highways for intercellular organelle transport. Science, 303, 1007–1010 (2004).
  102. Zurzolo C. Tunneling nanotubes: Reshaping connectivity. Curr. Opin. Cell Biol., 71, 139–147 (2021). doi: 10.1016/j.ceb.2021.03.003
  103. Wang X., Veruki M. L., Bukoreshtliev N. V.,Hartveit E., and Gerdes H.-H. Animal cells connected by nanotubes can be electrically coupled through interposed gap-junction channels. Proc. Natl. Acad. Sci. USA, 107 (40), 17194–17199 (2010). DOI: 10.1073/ pnas.1006785107
  104. Önfelt B., Nedvetzki S., Benninger R. K. P., Purbhoo M. A., Sowinski S., Hume A. N., Seabra M. C., Neil M. A. A., French P. M. W., and Davis D. M. Structurally distinct membrane nano· tubes between human macrophages support long-distance vesicular traffic or surfing of bacteria. J. Immunol., 177 (12), 8476–8483 (2006).
  105. Yamashita Y. M., Inaba M., and Buszczak M. Specialized intercellular communications via cytonemes and nanotubes. Annu. Rev. Cell Dev. Biol., 34, 59–84 (2018).
  106. Buckman J. F. and Reynolds I. J. Spontaneous changesin mitochondrial membrane potential in cultured neurons. J. Neurosci., 21 (14), 5054–5065 (2001). doi: 10.1523/JNEUROSCI.21-14-05054.2001
  107. Vergun O., Votyakova T. V., and Reynolds I. J. Spontaneous changes in mitochondrial membrane potential in single isolated brain mitochondria. Biophys. J., 85 (5), 3358–3366 (2003). doi: 10.1016/S00063495(03)74755-9

Copyright (c) 2024 Russian Academy of Sciences

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies