META-ANALYSIS OF ACID-BASE AND REDOX PROCESSES WITHIN THE MITOCHONDRIAL MATRIX, CYTOPLASM, INTERCELLULAR MEDIUM AND BLOOD BASED ON THE TENSOR APPROACH

Cover Page

Cite item

Full Text

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

Abstract

The most important indicator of homeostasis is the acid-base balance (ABB), which for the last half century in clinical practice has been assessed based on the Boston or Copenhagen schools, or relying on the physicochemical interpretation proposed by P. Stewart, which changed the emphasis from direct pH readings to the generalized state of electrochemical equilibrium of the blood. Today, it is generally recognized that all three approaches to assessing the ABB have weaknesses, and they do not have convincing clinical advantages. Since it has been experimentally established that with metabolic acidosis, 57% of buffering is carried out intracellularly, it is more appropriate to consider the ABB not as a purely isolated blood indicator, but to assess it within the framework of energy metabolism (dissimilation), which is a consequence of oxidation-reduction reactions within the mitochondrial matrix, their intermembrane space and the cell cytoplasm, which can be solved by mathematical modeling. The use of tensor notation for mathematical model equations is not only the adoption of standardization rules, but a far-reaching ideology of the invariance of these equations (preservation during transformations of a certain group). The presented work shows that acid-base and oxidation-reduction homeostasis in mathematical model equations can be interpreted as “play” (variations within established boundaries during transformations of a certain type) for specially formulated tensor invariants.

About the authors

A. S Tatevosyan

Kuban State Medical University, Ministry of Health of the Russian Federation

Email: artur-krasnadar@bk.ru
Krasnodar

A. V Bunyakin

Kuban State University

Krasnodar

S. S Kastsyuchenko

Anesthesiology Institute

Cleveland Clinic

S. N Alekseenko

Kuban State Medical University, Ministry of Health of the Russian Federation

Krasnodar

A. E Muronov

Kuban State Medical University, Ministry of Health of the Russian Federation

Krasnodar

Z. O Katani

Kuban State Medical University, Ministry of Health of the Russian Federation

Krasnodar

References

  1. Ашфак Хасан. Справочник по интерпретации газового состава крови и кислотно-щелочного баланса / Пер. с англ. под ред. А.М. Иванова. М.: ГЭОТАР-Медиа, 2023. 440 с.
  2. Severinghays J.W. // Scand. J. Clin. Lab. Invest. Suppl. 1993. V. 214. P. 99. PMID: 8332859
  3. Энн Ларднер // J. of Leukocyte biology. 2001. Т. 169(4). С. 522. doi: 10.1189/jlb.69.4.522
  4. Адам С., Паолини Л., Гуэген Н. и др. // Nat. Communun. 2021. Т. 12. С. 7115. doi: 10.1038/s41467-021-27426-x
  5. Дойен Д., Поэт М., Жаррету Г. и др. // Front. Mol. Biosci. (Sec. Biophysics). 2022. Т. 9. С. 825028. doi: 10.3389/fmolb.2022.825028
  6. Kurtz I., Kraut J., Ornekian V. & Nguyen M.K. // Am.J. Physiol. 2008. V. 294(5). P. F1009. doi: 10.1152/ajprenal.00475.2007
  7. Сейфтер Дж. Л., Чанг Хи. // Physiology (Bethesda). 2017. Т. 32(5). С. 367. doi: 10.1152/physiol.00007.2017.
  8. Костюченко С.С. Кислотно-основное состояние: физиология, нарушения, коррекция. Руководство для врачей и студентов. Витебск-Москва: Медицинская литература, 2024. 336 с.
  9. Белоусов Б.П. Периодически действующая реакция и ее механизм / Сборник рефератов по радиационной медицине за 1958. М.: Медгиз, 1959. 145 с.
  10. Жаботинский А.М. // Биофизика. 1964. Т. 9. С. 306.
  11. Корзухин М.Д., Жаботинский А.М. Математическое моделирование химических и экологических автоколебательных систем. М.: Наука, 1965.
  12. Glandsdorff P. and Prigogine I. Thermodynamic theory of structure, stability and fluctuations. Wiley. New York, 1971.
  13. Tatevosyan A.S., Bunyakin A.V. // Biophysics. 2019. V. 64(6). P. 942. doi: 10.1134/S0006350919060216.
  14. Татевосян А.С., Алексеенко С.Н., Бунякин А.В. // Кардиологический вестник. 2023. Т. 18(1). С. 5. doi: 10.17116/Cardiobulletin2023180115
  15. Татевосян А.С., Алексеенко С.Н., Бунякин А.В. // Журн. Физ. Химии. 2024. Т. 97(1). С. 159. doi: 10.1134/S0036024424010229
  16. Patil N., Bonneau S., Joubert F. et al. // Phys. Rev. E. 2020. Т. 102(2–1). С. 022401. doi: 10.1103/PhysRevE.102.022401
  17. Helfrich W. // Z. Naturforsch. 1973. Т. 28. С. 693. doi: 10.1515/znc-1973-11-1209
  18. Cheng J., Nanayakkara G., Shao Y. et al. // Adv Exp Med Biol. 2017. Т. 982. С. 359. doi: 10.1007/978-3-319-55330-6
  19. Makarov V.I., Khmelinskii I., Khuchua Z. & Javadov S. // Mitochondrion. 2020. Т. 50. С. 71. doi: 10.1016/j.mito.2019.09.006

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2025 Russian Academy of Sciences

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).