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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">vavilov</journal-id><journal-title-group><journal-title xml:lang="ru">Вавиловский журнал генетики и селекции</journal-title><trans-title-group xml:lang="en"><trans-title>Vavilov Journal of Genetics and Breeding</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2500-3259</issn><publisher><publisher-name>Institute of Cytology and Genetics of Siberian Branch of the RAS</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18699/VJGB-23-88</article-id><article-id custom-type="elpub" pub-id-type="custom">vavilov-3975</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>СИСТЕМНАЯ КОМПЬЮТЕРНАЯ БИОЛОГИЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>SYSTEMS COMPUTATIONAL BIOLOGY</subject></subj-group></article-categories><title-group><article-title>Бифуркационный анализ мультистабильности  и гистерезиса в модели ВИЧ-инфекции</article-title><trans-title-group xml:lang="en"><trans-title>Bifurcation analysis of multistability and hysteresis  in a model of HIV infection</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Миронов</surname><given-names>И. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Mironov</surname><given-names>I. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Христиченко</surname><given-names>М. Ю.</given-names></name><name name-style="western" xml:lang="en"><surname>Khristichenk</surname><given-names>M. Yu.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Нечепуренко</surname><given-names>Ю. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Nechepurenko</surname><given-names>Yu. M.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гребенников</surname><given-names>Д. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Grebennikov</surname><given-names>D. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><xref ref-type="aff" rid="aff-3"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5049-0656</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Бочаров</surname><given-names>Г. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Bocharov</surname><given-names>G. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><email xlink:type="simple">gbocharov@gmail.com</email><xref ref-type="aff" rid="aff-3"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Институт прикладной математики им. М.В. Келдыша Российской академии наук; Первый Московский государственный медицинский университет им. И.М. Сеченова Министерства здравоохранения Российской Федерации<country>Россия</country></aff><aff xml:lang="en">Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences; Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation<country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru">Институт прикладной математики им. М.В. Келдыша Российской академии наук; Институт вычислительной математики им. Г.И. Марчука Российской академии наук<country>Россия</country></aff><aff xml:lang="en">Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences; Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences<country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-3"><aff xml:lang="ru">Первый Московский государственный медицинский университет им. И.М. Сеченова Министерства здравоохранения Российской Федерации; Институт вычислительной математики им. Г.И. Марчука Российской академии наук<country>Россия</country></aff><aff xml:lang="en">Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation; Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences<country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>11</day><month>12</month><year>2023</year></pub-date><volume>27</volume><issue>7</issue><fpage>755</fpage><lpage>767</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Миронов И.В., Христиченко М.Ю., Нечепуренко Ю.М., Гребенников Д.С., Бочаров Г.А., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Миронов И.В., Христиченко М.Ю., Нечепуренко Ю.М., Гребенников Д.С., Бочаров Г.А.</copyright-holder><copyright-holder xml:lang="en">Mironov I.V., Khristichenk M.Y., Nechepurenko Y.M., Grebennikov D.S., Bocharov G.A.</copyright-holder><license license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://vavilov.elpub.ru/jour/article/view/3975">https://vavilov.elpub.ru/jour/article/view/3975</self-uri><abstract><p>Инфекционное заболевание, вызванное вирусами иммунодефицита человека первого типа (ВИЧ-1), остается серьез ной угрозой здоровью людей. Существующий подход к лечению ВИЧ-1 основан на применении высокоактивной антиретровирусной терапии, имеющей побочные эффекты для здоровья и высокую стоимость. Для практической медицины актуальной является задача поиска методов функционального лечения, связанных с интенсификацией иммунного контроля размножения вирусов и заражения клеток-мишеней с последующим снижением уровня вирусной нагрузки и восстановления иммунного статуса. Исследования в области иммунотерапии ВИЧ-1 находятся на стадии концептуальной разработки в силу сложности совокупности процессов, регулирующих динамику инфекции и иммунного ответа. По этой причине чрезвычайно актуальным является использование методов математического моделирования динамики ВИЧ-1 инфекции для теоретического анализа возможностей снижения вирусной нагрузки путем воздействия на иммунную систему без применения антивирусной терапии. Целью исследования было изучение, во-первых, свойств би-, мультистабильности и гистерезиса на примере содержательной модели ВИЧ-1 инфекции, которая описывает важнейшие блоки процессов взаимодействия вирусов и организма человека, а именно: распространение инфекции в продуктивно и латентно зараженных клетках, появление мутантов и развитие Т-клеточного иммунного ответа, и, во-вторых, возможностей перевода клинической картины заболевания из более тяжелого состояния в более легкое. В данной работе проведен численный анализ условий существования стационарных решений математической модели ВИЧ-1 инфекции для наборов параметров, отвечающих фенотипически различным вариантам течения инфекционного заболевания. Для этого использованы разработанные авторами методы бифуркационного анализа моделей, представляющих собой системы обыкновенных дифференциальных уравнений и дифференциальных уравнений с запаздыванием. В качестве бифуркационного параметра рассматривается константа скорости активации макрофагов. Определены области в пространстве параметров модели, в частности, для скорости активации клеток врожденного иммунитета (макрофагов), при которых имеют место свойства би-, мультистабильности и гистерезиса, и исследованы особенности кинетики перехода между устойчивыми положениями равновесия. В целом результаты бифуркационного анализа модели ВИЧ-1 инфекции формируют теоретическую основу для разработки комбинированных иммунотерапевтических воздействий для лечения ВИЧ-1. Результаты проведенного исследования модели ВИЧ-1 инфекции для параметров процессов, отвечающих разным фенотипам динамики заболевания (типичное, длительно не прогрессирующее и быстро прогрессирующее), указывают на то, что для эффективного функционального лечения больных ВИЧ-инфекцией требуется развитие персонализированного подхода, учитывающего как свойства популяции квазивидов ВИЧ-1, так и иммунный статус пациента.</p></abstract><trans-abstract xml:lang="en"><p>The infectious disease caused by human immunodeficiency virus type 1 (HIV-1) remains a serious threat to human health. The current approach to HIV-1 treatment is based on the use of highly active antiretroviral therapy, which has side effects and is costly. For clinical practice, it is highly important to create functional cures that can enhance immune control of viral growth and infection of target cells with a subsequent reduction in viral load and restoration of the immune status. HIV-1 control efforts with reliance on immunotherapy remain at a conceptual stage due to the complexity of a set of processes that regulate the dynamics of infection and immune response. For this reason, it is extremely important to use methods of mathematical modeling of HIV-1 infection dynamics for theoretical analysis of possibilities of reducing the viral load by affecting the immune system without the usage of antiviral therapy. The aim of our study is to examine the existence of bi-, multistability and hysteresis properties with a meaningful mathematical model of HIV-1 infection. The model describes the most important blocks of the processes of interaction between viruses and the human body, namely, the spread of infection in productively and latently infected cells, the appearance of viral mutants and the development of the T cell immune response. Furthermore, our analysis aims to study the possibilities of transferring the clinical pattern of the disease from a more severe state to a milder one. We analyze numerically the conditions for the existence of steady states of the mathematical model of HIV-1 infection for the numerical values of model parameters corresponding to phenotypically different variants of the infectious disease course. To this end, original computational methods of bifurcation analysis of mathematical models formulated with systems of ordinary differential equations and delay differential equations are used. The macrophage activation rate constant is considered as a bifurcation parameter. The regions in the model parameter space, in particular, for the rate of activation of innate immune cells (macrophages), in which the properties of bi-, multistability and hysteresis are expressed, have been identified, and the features cha rac terizing transition kinetics between stable equilibrium states have been explored. Overall, the results of bifurcation analysis of the HIV-1 infection model form a theoretical basis for the development of combination immune-based therapeutic approaches to HIV-1 treatment. In particular, the results of the study of the HIV-1 infection model for parameter sets corresponding to different phenotypes of disease dynamics (typical, long-term non-progressing and rapidly progressing courses) indicate that an effective functional treatment (cure) of HIV-1-infected patients requires the development of a personalized approach that takes into account both the properties of the HIV-1 quasispecies population and the patient’s immune status.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>математическая модель</kwd><kwd>ВИЧ-инфекция</kwd><kwd>обыкновенные дифференциальные уравнения</kwd><kwd>бифуркационный анализ</kwd><kwd>стационарные решения</kwd><kwd>бистабильность</kwd><kwd>мультистабильность</kwd><kwd>гистерезис</kwd><kwd>оптимальное управление</kwd></kwd-group><kwd-group xml:lang="en"><kwd>mathematical model</kwd><kwd>HIV infection</kwd><kwd>ordinary differential equations</kwd><kwd>bifurcation analysis</kwd><kwd>stationary solutions</kwd><kwd>bistability</kwd><kwd>multistability</kwd><kwd>hysteresis</kwd><kwd>optimal control</kwd></kwd-group><funding-group xml:lang="en"><funding-statement>This work was financially supported by the Russian Science Foundation, project No. 22-71-10028.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Akın E., Yeni G., Perelson A.S. 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