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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">rosped</journal-id><journal-title-group><journal-title xml:lang="ru">Российский педиатрический журнал имени М.Я. Студеникина</journal-title><trans-title-group xml:lang="en"><trans-title>M.Ya. Studenikin Russian Pediatric Journal</trans-title></trans-title-group></journal-title-group><publisher><publisher-name>ФГАУ «НМИЦ здоровья детей» Минздрава России</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.46563/1560-9561-2022-25-1-28-31</article-id><article-id custom-type="edn" pub-id-type="custom">fyihcf</article-id><article-id custom-type="elpub" pub-id-type="custom">rosped-347</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>ОРИГИНАЛЬНЫЕ ИССЛЕДОВАНИЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ORIGINAL INVESTIGATIONS</subject></subj-group></article-categories><title-group><article-title>Математическое моделирование в изучении патогенеза вирусного гепатита у детей</article-title><trans-title-group xml:lang="en"><trans-title>Mathematical modelling in the study of the pathogenesis of viral hepatitis in children</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0818-5316</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Мартусевич</surname><given-names>Андрей Кимович</given-names></name><name name-style="western" xml:lang="en"><surname>Martusevich</surname><given-names>Andrey K.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Доктор биол. наук, вед. науч. сотр., руководитель лаб., медицинской биофизики Университетской клиники ФГБОУ ВО ПИМУ Минздрава России.</p><p>e-mail: cryst-mart@yandex.ru</p></bio><email xlink:type="simple">cryst-mart@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-9574-2933</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Галова</surname><given-names>Елена Анатольевна</given-names></name><name name-style="western" xml:lang="en"><surname>Galova</surname><given-names>Elena A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Канд. мед. наук, зам. директора Университетской клиники по науке, ФГБОУ ВО ПИМУ Минздрава России.</p><p>e-mail: galova75@mail.ru</p></bio><email xlink:type="simple">galova75@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-3717-2186</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Поповичева</surname><given-names>Александра Николаевна</given-names></name><name name-style="western" xml:lang="en"><surname>Popovicheva</surname><given-names>Aleksandra N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Мл. науч. сотр. лаб. медицинской биофизики Университетской клиники ФГБОУ ВО ПИМУ Минздрава России.</p><p>e-mail: alexandra.popovichus@yandex.ru</p></bio><bio xml:lang="en"><p>Junior researcher, Laboratory of medical biophysics of the University Clinic, Privolzhsky Research Medical University, Nizhny Novgorod, 603950, Russian Federation.</p><p>e-mail: alexandra.popovichus@yandex.ru</p></bio><email xlink:type="simple">alexandra.popovichus@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">ФГБОУ ВО «Приволжский исследовательский медицинский университет» Минздрава России<country>Россия</country></aff><aff xml:lang="en">Privolzhsky Research Medical University<country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2022</year></pub-date><pub-date pub-type="epub"><day>11</day><month>10</month><year>2023</year></pub-date><volume>25</volume><issue>1</issue><fpage>28</fpage><lpage>31</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Мартусевич А.К., Галова Е.А., Поповичева А.Н., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Мартусевич А.К., Галова Е.А., Поповичева А.Н.</copyright-holder><copyright-holder xml:lang="en">Martusevich A.K., Galova E.A., Popovicheva A.N.</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://www.rosped.ru/jour/article/view/347">https://www.rosped.ru/jour/article/view/347</self-uri><abstract><p>Цель работы — сформировать математическую модель вирусных гепатитов на основании структурного моделирования, дискриминантного и факторного анализов лабораторных параметров пациентов.</p><sec><title>Материалы и методы</title><p>Материалы и методы. В массив данных были включены данные комплексного лабораторного обследования 109 детей с вирусными гепатитами В и С (33 параметра).</p></sec><sec><title>Результаты</title><p>Результаты. Выявлены 7 основных факторов патогенеза вирусного гепатита у детей, преимущественно отражающих выраженность эндогенной интоксикации и нарушений белкового обмена, а также определена модификация режима функционирования ферментов и надмолекулярных мультиэнзимных комплексов в условиях прогрессирования первых двух компонентов.</p></sec><sec><title>Заключение</title><p>Заключение. Выделенные факторы патогенеза вирусного гепатита у детей способны отражать развивающуюся в процессе формирования патологии эндогенную интоксикацию, состояние ферментных систем детоксикации и формирующиеся в дальнейшем фибротические изменения в печени.</p></sec><sec><title>Участие авторов</title><p>Участие авторов:Мартусевич А.К., Галова Е.А., Поповичева А.Н. — концепция и дизайн исследования, сбор и обработка материала, написание текста.Все соавторы — утверждение окончательного варианта статьи, ответственность за целостность всех её частей.</p></sec><sec><title>Финансирование</title><p>Финансирование: авторы статьи подтверждают отсутствие финансовой поддержки.</p></sec><sec><title>Конфликт интересов</title><p>Конфликт интересов: авторы заявили об отсутствии конфликта интересов.</p></sec><sec><title>Поступила 14</title><p>Поступила 14.01.2022Принята к печати 17.02.2022Опубликована 15.03.2022</p></sec></abstract><trans-abstract xml:lang="en"><p>The aim of the work is to form a mathematical model of viral hepatitis based on structural modelling, discriminant and factorial analysis of laboratory parameters of patients.</p><sec><title>Materials and methods</title><p>Materials and methods. The data array included the results of a comprehensive laboratory testing of 109 children with viral hepatitis B and C (33 parameters).</p></sec><sec><title>Results</title><p>Results. Seven main factors in the pathogenesis of viral hepatitis in children reflect the severity of endogenous intoxication and disorders of protein metabolism, modification of the mode of functioning of enzymes, and supramolecular multi-enzyme complexes in conditions of progression of the first two components.</p></sec><sec><title>Conclusion</title><p>Conclusion. The identified factors of the pathogenesis of viral hepatitis may reflect the endogenous intoxication during disease progression, the state of detoxification enzyme systems, and the further fibrotic changes in the liver.</p></sec><sec><title>Contribution</title><p>Contribution:Martusevich A.K. — the concept and design of the study, the collection and processing of material, writing the text;Galova E.A. — providing material for research;Korkotashvili L.V. — carrying out mathematical modeling;Popovicheva A.N. — editing the text of the article.Аll co-authors — аpproval of the final version of the article, responsibility for the integrity of all parts of the article.</p></sec><sec><title>Informed consent</title><p>Informed consent: informed consent was received from the patients parents for the publication of a description of the clinical case.</p></sec><sec><title>Acknowledgment</title><p>Acknowledgment. The study had no sponsorship.</p></sec><sec><title>Conflict of interest</title><p>Conflict of interest. The authors declare no conflict of interest.</p></sec><sec><title>Received</title><p>Received: January 14, 2022Accepted: February 17, 2022Published: March 15, 2022</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>вирусные гепатиты</kwd><kwd>математическое моделирование</kwd><kwd>фиброз</kwd><kwd>эндогенная интоксикация</kwd></kwd-group><kwd-group xml:lang="en"><kwd>viral hepatitis</kwd><kwd>mathematical modeling</kwd><kwd>fibrosis</kwd><kwd>endogenous intoxication</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Aston P.J. A new model for the dynamics of hepatitis C infection: derivation, analysis and implications. Viruses. 2018; 10(4): 195. https://doi.org/10.3390/v10040195</mixed-citation><mixed-citation xml:lang="en">Aston P.J. A new model for the dynamics of hepatitis C infection: derivation, analysis and implications. Viruses. 2018; 10(4): 195. https://doi.org/10.3390/v10040195</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Scheel T.K.H., Rice C.M. Understanding the hepatitis C virus life cycle paves the way for highly effective therapies. Nat Med. 2013; 19: 837-49. https://doi.org/10.1038/nm.3248</mixed-citation><mixed-citation xml:lang="en">Scheel T.K.H., Rice C.M. Understanding the hepatitis C virus life cycle paves the way for highly effective therapies. Nat Med. 2013; 19: 837–49. https://doi.org/10.1038/nm.3248</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Shin E.C., Han J.W., Kang W., Kato T., Kim S.J., Zhong J., et al. The beginning of ending hepatitis C virus: A summary of the 26th international symposium on hepatitis C virus and related viruses. Viruses. 2020; 12(3): 302. https://doi.org/10.3390/v12030302</mixed-citation><mixed-citation xml:lang="en">Shin E.C., Han J.W., Kang W., Kato T., Kim S.J., Zhong J., et al. The beginning of ending hepatitis C virus: A summary of the 26th international symposium on hepatitis C virus and related viruses. Viruses. 2020; 12(3): 302. https://doi.org/10.3390/v12030302</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Stanaway J.D., Flaxman A.D., Naghavi M., Fitzmaurice C., Vos T., Abubakar I., et al. The global burden of viral hepatitis from 1990 to 2013: findings from the Global Burden of Disease Study 2013. Lancet. 2016; 388: 1081-8. https://doi.org/10.1016/S0140-6736(16)30579-7</mixed-citation><mixed-citation xml:lang="en">Stanaway J.D., Flaxman A.D., Naghavi M., Fitzmaurice C., Vos T., Abubakar I., et al. The global burden of viral hepatitis from 1990 to 2013: findings from the Global Burden of Disease Study 2013. Lancet. 2016; 388: 1081–8. https://doi.org/10.1016/S0140-6736(16)30579-7</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Klasse P.J. Molecular determinants of the ratio of inert to infectious virus particles. Prog Mol Biol Transl Sci. 2015; 129: 285-326. https://doi.org/10.1016/bs.pmbts.2014.10.012</mixed-citation><mixed-citation xml:lang="en">Klasse P.J. Molecular determinants of the ratio of inert to infectious virus particles. Prog Mol Biol Transl Sci. 2015; 129: 285–326. https://doi.org/10.1016/bs.pmbts.2014.10.012</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Pradeep K.S., Medhi S., Asim M., Das B.C., Gondal R., Kar P. Evaluation of adefovir &amp; lamivudine in chronic hepatitis B: correlation with HBV viral kinetic, hepatic-necro inflammation &amp; fibrosis. Indian J Med Res. 2011; 133(1): 50-6.</mixed-citation><mixed-citation xml:lang="en">Pradeep K.S., Medhi S., Asim M., Das B.C., Gondal R., Kar P. Evaluation of adefovir &amp; lamivudine in chronic hepatitis B: correlation with HBV viral kinetic, hepatic-necro inflammation &amp; fibrosis. Indian J Med Res. 2011; 133(1): 50–6.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Hao W., Komar H.M., Hart P.A., Conwell D.L., Lesinski G.B., Friedman A. Mathematical model of chronic pancreatitis. PNAS. 2017; 114(19): 5011-6. https://doi.org/10.1073/pnas.1620264114</mixed-citation><mixed-citation xml:lang="en">Hao W., Komar H.M., Hart P.A., Conwell D.L., Lesinski G.B., Friedman A. Mathematical model of chronic pancreatitis. PNAS. 2017; 114(19): 5011–6. https://doi.org/10.1073/pnas.1620264114</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Kim Y., Lawler S., Nowicki M.O., Chiocca E.A., Friedman A. A mathematical model for pattern formation of glioma cells outside the tumor spheroid core. J Theor Biol. 2009; 260(3): 359-71. https://doi.org/10.1016/j.jtbi.2009.06.025</mixed-citation><mixed-citation xml:lang="en">Kim Y., Lawler S., Nowicki M.O., Chiocca E.A., Friedman A. A mathematical model for pattern formation of glioma cells outside the tumor spheroid core. J Theor Biol. 2009; 260(3): 359–71. https://doi.org/10.1016/j.jtbi.2009.06.025</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Siewe N., Yakubu A.A., Satoskar A.R., Friedman A. Immune response to infection by leishmania: A mathematical model. Mathematical Biosciences. 2016; 276: 28-43. https://doi.org/10.1016/j.mbs.2016.02</mixed-citation><mixed-citation xml:lang="en">Siewe N., Yakubu A.A., Satoskar A.R., Friedman A. Immune response to infection by leishmania: A mathematical model. Mathematical Biosciences. 2016; 276: 28–43. https://doi.org/10.1016/j.mbs.2016.02</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Siewe N., Yakubu A.A., Satoskar A.R., Friedman A. Granuloma formation in leishmaniasis: A Mathematical model. J Theor Biol. 2017; 412: 48-60. https://doi.org/10.1016/j.jtbi.2016.10.004</mixed-citation><mixed-citation xml:lang="en">Siewe N., Yakubu A.A., Satoskar A.R., Friedman A. Granuloma formation in leishmaniasis: A Mathematical model. J Theor Biol. 2017; 412: 48–60. https://doi.org/10.1016/j.jtbi.2016.10.004</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Friedman A., Hao W. Mathematical Modeling of Liver Fibrosis. Mat Biosc Eng. 2017; 14(1): 143-64. https://doi.org/10.3934/mbe.2017010</mixed-citation><mixed-citation xml:lang="en">Friedman A., Hao W. Mathematical Modeling of Liver Fibrosis. Mat Biosc Eng. 2017; 14(1): 143–64. https://doi.org/10.3934/mbe.2017010</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Friedman A., Siewe N. Chronic hepatitis B virus and liver fibrosis: A mathematical model. PLoS One. 2018; 13(4): e0195037. https://doi.org/10.1371/journal.pone.0195037</mixed-citation><mixed-citation xml:lang="en">Friedman A., Siewe N. Chronic hepatitis B virus and liver fibrosis: A mathematical model. PLoS One. 2018; 13(4): e0195037. https://doi.org/10.1371/journal.pone.0195037</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Graw F., Perelson A.S. Modeling Viral Spread. Annu Rev Virol. 2016; 3: 555-72. https://doi.org/10.1146/annurev-virology-110615-042249</mixed-citation><mixed-citation xml:lang="en">Graw F., Perelson A.S. Modeling Viral Spread. Annu Rev Virol. 2016; 3: 555–72. https://doi.org/10.1146/annurev-virology-110615-042249</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Hao W., Rovin B.H., Friedman A. Mathematical model of renal interstitial fibrosis. Proc Natl Acad Sci. 2014; 111(39): 14193-8. https://doi.org/10.1073/pnas.1413970111</mixed-citation><mixed-citation xml:lang="en">Hao W., Rovin B.H., Friedman A. Mathematical model of renal interstitial fibrosis. Proc Natl Acad Sci. 2014; 111(39): 14193–8. https://doi.org/10.1073/pnas.1413970111</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Zhao S., Su Z., Lu Y. A mathematical model of hepatitis B virus transmission and its application for vaccination strategy in China. Int J Epidemiol. 2000; 29(4): 744-52. https://doi.org/10.1093/ije/29.4.744</mixed-citation><mixed-citation xml:lang="en">Zhao S., Su Z., Lu Y. A mathematical model of hepatitis B virus transmission and its application for vaccination strategy in China. Int J Epidemiol. 2000; 29(4): 744–52. https://doi.org/10.1093/ije/29.4.744</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Kalemera M., Mincheva D., Grove J., Illingworth C.J.R. Building a mechanistic mathematical model of hepatitis C virus entry. PLoS Comput Biol. 2019; 15(3): e1006905. https://doi.org/10.1371/journal.pcbi.1006905</mixed-citation><mixed-citation xml:lang="en">Kalemera M., Mincheva D., Grove J., Illingworth C.J.R. Building a mechanistic mathematical model of hepatitis C virus entry. PLoS Comput Biol. 2019; 15(3): e1006905. https://doi.org/10.1371/journal.pcbi.1006905</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Kamyad A.V., Akbari R., Heydari A.A., Heydari A. Mathematical modeling of transmission dynamics and optimal control of vaccination and treatment for hepatitis B virus. Comp Math Methods Med. 2014. 475451; 2014: 1-15. https://doi.org/10.1155/2014/475451</mixed-citation><mixed-citation xml:lang="en">Kamyad A.V., Akbari R., Heydari A.A., Heydari A. Mathematical modeling of transmission dynamics and optimal control of vaccination and treatment for hepatitis B virus. Comp Math Methods Med. 2014. 475451; 2014: 1–15. https://doi.org/10.1155/2014/475451</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Ciupe S.M., Ribiero R.M., Nelson P.W., Perelson A.S. Modeling the mechanisms of acute hepatitis B virus infection. J Theor Biol. 2007; 247: 23-35. https://doi.org/10.1016/j.jtbi.2007.02.017</mixed-citation><mixed-citation xml:lang="en">Ciupe S.M., Ribiero R.M., Nelson P.W., Perelson A.S. Modeling the mechanisms of acute hepatitis B virus infection. J Theor Biol. 2007; 247: 23–35. https://doi.org/10.1016/j.jtbi.2007.02.017</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Padmanabhan P., Dixit N.M. Mathematical model of viral kinetics in vitro estimates the number of E2-CD81 complexes necessary for hepatitis C virus entry. PLoS Comput Biol. 2011; 7: e1002307. https://doi.org/10.1371/journal.pcbi.1002307</mixed-citation><mixed-citation xml:lang="en">Padmanabhan P., Dixit N.M. Mathematical model of viral kinetics in vitro estimates the number of E2-CD81 complexes necessary for hepatitis C virus entry. PLoS Comput Biol. 2011; 7: e1002307. https://doi.org/10.1371/journal.pcbi.1002307</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Aunins T.R., Marsh K.A., Subramanya G., Uprichard S.L., Perelson A.S., Chatterjee A. Intracellular hepatitis C virus modeling predicts infection dynamics and viral protein mechanisms. J Virol. 2018; 92(11): e02098-17. https://doi.org/10.1128/JVI.02098-17</mixed-citation><mixed-citation xml:lang="en">Aunins T.R., Marsh K.A., Subramanya G., Uprichard S.L., Perelson A.S., Chatterjee A. Intracellular hepatitis C virus modeling predicts infection dynamics and viral protein mechanisms. J Virol. 2018; 92(11): e02098–17. https://doi.org/10.1128/JVI.02098-17</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Dixit N.M., Layden-Almer J.E., Layden T.J., Perelson A.S. Modelling how ribavirin improves interferon response rates in hepatitis C virus infection. Nature. 2004; 432: 922-4. https://doi.org/10.1038/nature03153</mixed-citation><mixed-citation xml:lang="en">Dixit N.M., Layden-Almer J.E., Layden T.J., Perelson A.S. Modelling how ribavirin improves interferon response rates in hepatitis C virus infection. Nature. 2004; 432: 922–4. https://doi.org/10.1038/nature03153</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
