S
Sergey P Zavadskiy
Researcher at I.M. Sechenov First Moscow State Medical University
Publications - 10
Citations - 52
Sergey P Zavadskiy is an academic researcher from I.M. Sechenov First Moscow State Medical University. The author has contributed to research in topics: Medicine & Gene. The author has an hindex of 2, co-authored 7 publications receiving 14 citations.
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Journal ArticleDOI
Dual Character of Reactive Oxygen, Nitrogen, and Halogen Species: Endogenous Sources, Interconversions and Neutralization.
N. T. Moldogazieva,Innokenty M. Mokhosoev,Tatiana I Melnikova,Sergey P Zavadskiy,A. N. Kuzmenko,Alexander A Terentiev +5 more
TL;DR: Analysis of interactions between RONS and relationships between different endogenous sources of these compounds will contribute to better understanding of their role in the maintenance of cell redox homeostasis as well as initiation and progression of diseases.
Journal ArticleDOI
Predictive biomarkers for systemic therapy of hepatocellular carcinoma.
N. T. Moldogazieva,Sergey P Zavadskiy,Susanna S Sologova,Innokenty M. Mokhosoev,Alexander A Terentiev +4 more
TL;DR: In this paper, a review of recent advancements in the identification of proteomic/genomic/epigenomic/transcriptomic biomarkers for predicting HCC treatment efficacy with the use of multi-kinase inhibitors (MKIs), CDK4/6 inhibitors, and immune checkpoint inhibitors (ICIs).
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Genomic Landscape of Liquid Biopsy for Hepatocellular Carcinoma Personalized Medicine.
TL;DR: In this paper, the authors highlight and critically discuss the latest progress in characterizing the genomic landscape of liquid biopsy, which can advance HCC personalized medicine by identifying individual variabilities in genomic signatures.
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Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine
TL;DR: In this article, the authors focus on the recent progress in integrative proteomic profiling strategies and their usage in combination with machine learning and deep learning technologies for the discovery of novel biomarker candidates for HCC early diagnosis and prognosis.
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Short Linear Motifs Orchestrate Functioning of Human Proteins during Embryonic Development, Redox Regulation, and Cancer
TL;DR: The hypothesis that conserved SLiMs are incorporated into non-homologous proteins to serve as functional blocks for their orchestrated functioning is supported.