Identification of Molecular Mechanisms Involved in Viral Infection Progression Based on Text Mining: Case Study for HIV Infection

Viruses cause various infections that may affect human lifestyle for durations ranging from several days to for many years. Although preventative and therapeutic remedies are available for many viruses, they may still have a profound impact on human life. The human immunodeficiency virus type 1 is the most common cause of HIV infection, which represents one of the most dangerous and complex diseases since it affects the immune system and causes its disruption, leading to secondary complications and negatively influencing health-related quality of life. While highly active antiretroviral therapy may decrease the viral load and the velocity of HIV infection progression, some individual peculiarities may affect viral load control or the progression of T-cell malfunction induced by HIV. Our study is aimed at the text-based identification of molecular mechanisms that may be involved in viral infection progression, using HIV as a case study. Specifically, we identified human proteins and genes which commonly occurred, overexpressed or underexpressed, in the collections of publications relevant to (i) HIV infection progression and (ii) acute and chronic stages of HIV infection. Then, we considered biological processes that are controlled by the identified protein and genes. We verified the impact of the identified molecules in the associated clinical study. © 2023 by the authors.

Авторы
Tarasova O. , Biziukova N. , Shemshura A. , Filimonov D. , Kireev D. , Pokrovskaya A. , Poroikov V.V.
Издательство
MDPI AG
Номер выпуска
2
Язык
Английский
Статус
Опубликовано
Номер
1465
Том
24
Год
2023
Организации
  • 1 Institute of Biomedical Chemistry, 10 Bldg. 8, Pogodinskaya Str., Moscow, 119121, Russian Federation
  • 2 Federal Budget Public Health Institution “Clinical Center of HIV/AIDS Treatment and Prevention” of the Ministry of Health of Krasnodar Region, 204/2, im. Mitrofana Sedina Str., Krasnodar, 350000, Russian Federation
  • 3 Federal Budget Institution of Science «Central Research Institute for Epidemiology» of the Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing, Novogireevskaya Str., 3A, Moscow, 111123, Russian Federation
  • 4 Department of Infectious Diseases with Courses of Epidemiology and Phthisiology, Medical Institute, Peoples’ Friendship University of Russia, 6 Miklukho-Maklaya Str., Moscow, 117198, Russian Federation
Ключевые слова
acute HIV infection; chronic HIV infection; HIV/AIDS; machine learning; text mining; viral infection; viral infection progression
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